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nerdvegas/rez
|
d392c65bf63b4bca8106f938cec49144ba54e770
|
src/rez/vendor/memcache/memcache.py
|
python
|
_Host.send_cmds
|
(self, cmds)
|
cmds already has trailing \r\n's applied.
|
cmds already has trailing \r\n's applied.
|
[
"cmds",
"already",
"has",
"trailing",
"\\",
"r",
"\\",
"n",
"s",
"applied",
"."
] |
def send_cmds(self, cmds):
"""cmds already has trailing \r\n's applied."""
if isinstance(cmds, six.text_type):
cmds = cmds.encode('utf8')
self.socket.sendall(cmds)
|
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https://github.com/nerdvegas/rez/blob/d392c65bf63b4bca8106f938cec49144ba54e770/src/rez/vendor/memcache/memcache.py#L1427-L1431
|
||
google/Legilimency
|
02cd38fd82a90bca789b8bf61c88f4bc5dd1eb07
|
MemClient.py
|
python
|
MemClient.read64
|
(self, addr)
|
return tokens[0] if addr % (2 * QWORD_SIZE) == 0 else tokens[1]
|
Reads the 64-bit value at the given address.
|
Reads the 64-bit value at the given address.
|
[
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"value",
"at",
"the",
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"address",
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] |
def read64(self, addr):
"""
Reads the 64-bit value at the given address.
"""
if addr % QWORD_SIZE != 0:
raise Exception("Address must be QWORD-aligned : 0x%016X" % addr)
dqword_aligned_addr = addr - (addr % (2 * QWORD_SIZE))
tokens = self.read128(dqword_aligned_addr)
return tokens[0] if addr % (2 * QWORD_SIZE) == 0 else tokens[1]
|
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https://github.com/google/Legilimency/blob/02cd38fd82a90bca789b8bf61c88f4bc5dd1eb07/MemClient.py#L106-L114
|
|
smart-mobile-software/gitstack
|
d9fee8f414f202143eb6e620529e8e5539a2af56
|
python/Lib/lib-tk/Tkinter.py
|
python
|
Menu.activate
|
(self, index)
|
Activate entry at INDEX.
|
Activate entry at INDEX.
|
[
"Activate",
"entry",
"at",
"INDEX",
"."
] |
def activate(self, index):
"""Activate entry at INDEX."""
self.tk.call(self._w, 'activate', index)
|
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https://github.com/smart-mobile-software/gitstack/blob/d9fee8f414f202143eb6e620529e8e5539a2af56/python/Lib/lib-tk/Tkinter.py#L2606-L2608
|
||
XX-net/XX-Net
|
a9898cfcf0084195fb7e69b6bc834e59aecdf14f
|
code/default/lib/noarch/sortedcontainers/sortedlist.py
|
python
|
SortedList.__contains__
|
(self, val)
|
return _lists[pos][idx] == val
|
Return True if and only if *val* is an element in the list.
|
Return True if and only if *val* is an element in the list.
|
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] |
def __contains__(self, val):
"""Return True if and only if *val* is an element in the list."""
_maxes = self._maxes
if not _maxes:
return False
pos = bisect_left(_maxes, val)
if pos == len(_maxes):
return False
_lists = self._lists
idx = bisect_left(_lists[pos], val)
return _lists[pos][idx] == val
|
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https://github.com/XX-net/XX-Net/blob/a9898cfcf0084195fb7e69b6bc834e59aecdf14f/code/default/lib/noarch/sortedcontainers/sortedlist.py#L153-L167
|
|
isce-framework/isce2
|
0e5114a8bede3caf1d533d98e44dfe4b983e3f48
|
components/isceobj/Scene/Frame.py
|
python
|
Frame.getSensingStop
|
(self)
|
return self._sensingStop
|
The UTC date and time of the last azimuth line
|
The UTC date and time of the last azimuth line
|
[
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"the",
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] |
def getSensingStop(self):
"""The UTC date and time of the last azimuth line"""
return self._sensingStop
|
[
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https://github.com/isce-framework/isce2/blob/0e5114a8bede3caf1d533d98e44dfe4b983e3f48/components/isceobj/Scene/Frame.py#L392-L394
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_hxb2/lib/python3.5/site-packages/pip/_vendor/html5lib/_inputstream.py
|
python
|
HTMLUnicodeInputStream._position
|
(self, offset)
|
return (positionLine, positionColumn)
|
[] |
def _position(self, offset):
chunk = self.chunk
nLines = chunk.count('\n', 0, offset)
positionLine = self.prevNumLines + nLines
lastLinePos = chunk.rfind('\n', 0, offset)
if lastLinePos == -1:
positionColumn = self.prevNumCols + offset
else:
positionColumn = offset - (lastLinePos + 1)
return (positionLine, positionColumn)
|
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https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_hxb2/lib/python3.5/site-packages/pip/_vendor/html5lib/_inputstream.py#L224-L233
|
|||
tobegit3hub/deep_image_model
|
8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e
|
java_predict_client/src/main/proto/tensorflow/contrib/learn/python/learn/preprocessing/text.py
|
python
|
VocabularyProcessor.save
|
(self, filename)
|
Saves vocabulary processor into given file.
Args:
filename: Path to output file.
|
Saves vocabulary processor into given file.
|
[
"Saves",
"vocabulary",
"processor",
"into",
"given",
"file",
"."
] |
def save(self, filename):
"""Saves vocabulary processor into given file.
Args:
filename: Path to output file.
"""
with gfile.Open(filename, 'wb') as f:
f.write(pickle.dumps(self))
|
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")"
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https://github.com/tobegit3hub/deep_image_model/blob/8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e/java_predict_client/src/main/proto/tensorflow/contrib/learn/python/learn/preprocessing/text.py#L206-L213
|
||
facebookresearch/BLINK
|
5fe254dd64d37332347edc73738edcb56096183f
|
blink/candidate_ranking/bert_reranking.py
|
python
|
BertReranker._get_context_token_representation
|
(
context_key,
sample,
tokenizer,
max_sub_seq_length,
start_token,
end_token,
mention_text_key="text",
tagged=True,
)
|
return context_tokens
|
Tags the mention, trims the context and concatenates everything to form the context representation
|
Tags the mention, trims the context and concatenates everything to form the context representation
|
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"Tags",
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"trims",
"the",
"context",
"and",
"concatenates",
"everything",
"to",
"form",
"the",
"context",
"representation"
] |
def _get_context_token_representation(
context_key,
sample,
tokenizer,
max_sub_seq_length,
start_token,
end_token,
mention_text_key="text",
tagged=True,
):
"""Tags the mention, trims the context and concatenates everything to form the context representation"""
mention_tokens = (
[start_token] + tokenizer.tokenize(sample[mention_text_key]) + [end_token]
)
max_sub_seq_length = (max_sub_seq_length - len(mention_tokens)) // 2
context_left, context_right = sample[context_key]
context_left = tokenizer.tokenize(context_left)
context_right = tokenizer.tokenize(context_right)
if len(context_left) > max_sub_seq_length:
context_left = context_left[-max_sub_seq_length:]
if len(context_right) > max_sub_seq_length:
context_right = context_right[:max_sub_seq_length]
context_tokens = context_left + mention_tokens + context_right
return context_tokens
|
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https://github.com/facebookresearch/BLINK/blob/5fe254dd64d37332347edc73738edcb56096183f/blink/candidate_ranking/bert_reranking.py#L363-L390
|
|
numba/numba
|
bf480b9e0da858a65508c2b17759a72ee6a44c51
|
numba/core/pythonapi.py
|
python
|
PythonAPI.recreate_record
|
(self, pdata, size, dtype, env_manager)
|
return self.builder.call(fn, [pdata, size, dtypeaddr])
|
[] |
def recreate_record(self, pdata, size, dtype, env_manager):
fnty = Type.function(self.pyobj, [Type.pointer(Type.int(8)),
Type.int(), self.pyobj])
fn = self._get_function(fnty, name="numba_recreate_record")
dtypeaddr = env_manager.read_const(env_manager.add_const(dtype))
return self.builder.call(fn, [pdata, size, dtypeaddr])
|
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https://github.com/numba/numba/blob/bf480b9e0da858a65508c2b17759a72ee6a44c51/numba/core/pythonapi.py#L1544-L1549
|
|||
collinsctk/PyQYT
|
7af3673955f94ff1b2df2f94220cd2dab2e252af
|
ExtentionPackages/pysmi/parser/smi.py
|
python
|
SmiV2Parser.p_importedKeyword
|
(self, p)
|
importedKeyword : importedSMIKeyword
| BITS
| INTEGER32
| IPADDRESS
| MANDATORY_GROUPS
| MODULE_COMPLIANCE
| MODULE_IDENTITY
| OBJECT_GROUP
| OBJECT_IDENTITY
| OBJECT_TYPE
| OPAQUE
| TEXTUAL_CONVENTION
| TIMETICKS
| UNSIGNED32
|
importedKeyword : importedSMIKeyword
| BITS
| INTEGER32
| IPADDRESS
| MANDATORY_GROUPS
| MODULE_COMPLIANCE
| MODULE_IDENTITY
| OBJECT_GROUP
| OBJECT_IDENTITY
| OBJECT_TYPE
| OPAQUE
| TEXTUAL_CONVENTION
| TIMETICKS
| UNSIGNED32
|
[
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"OPAQUE",
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"TEXTUAL_CONVENTION",
"|",
"TIMETICKS",
"|",
"UNSIGNED32"
] |
def p_importedKeyword(self, p):
"""importedKeyword : importedSMIKeyword
| BITS
| INTEGER32
| IPADDRESS
| MANDATORY_GROUPS
| MODULE_COMPLIANCE
| MODULE_IDENTITY
| OBJECT_GROUP
| OBJECT_IDENTITY
| OBJECT_TYPE
| OPAQUE
| TEXTUAL_CONVENTION
| TIMETICKS
| UNSIGNED32"""
p[0] = p[1]
|
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")",
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"[",
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https://github.com/collinsctk/PyQYT/blob/7af3673955f94ff1b2df2f94220cd2dab2e252af/ExtentionPackages/pysmi/parser/smi.py#L157-L172
|
||
linxid/Machine_Learning_Study_Path
|
558e82d13237114bbb8152483977806fc0c222af
|
Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pip/_vendor/distlib/_backport/sysconfig.py
|
python
|
get_config_var
|
(name)
|
return get_config_vars().get(name)
|
Return the value of a single variable using the dictionary returned by
'get_config_vars()'.
Equivalent to get_config_vars().get(name)
|
Return the value of a single variable using the dictionary returned by
'get_config_vars()'.
|
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"of",
"a",
"single",
"variable",
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"dictionary",
"returned",
"by",
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"()",
"."
] |
def get_config_var(name):
"""Return the value of a single variable using the dictionary returned by
'get_config_vars()'.
Equivalent to get_config_vars().get(name)
"""
return get_config_vars().get(name)
|
[
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")",
":",
"return",
"get_config_vars",
"(",
")",
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"get",
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] |
https://github.com/linxid/Machine_Learning_Study_Path/blob/558e82d13237114bbb8152483977806fc0c222af/Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pip/_vendor/distlib/_backport/sysconfig.py#L594-L600
|
|
lsbardel/python-stdnet
|
78db5320bdedc3f28c5e4f38cda13a4469e35db7
|
stdnet/utils/dates.py
|
python
|
Interval.__reduce__
|
(self)
|
return tuple, (tuple(self),)
|
[] |
def __reduce__(self):
return tuple, (tuple(self),)
|
[
"def",
"__reduce__",
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"self",
")",
":",
"return",
"tuple",
",",
"(",
"tuple",
"(",
"self",
")",
",",
")"
] |
https://github.com/lsbardel/python-stdnet/blob/78db5320bdedc3f28c5e4f38cda13a4469e35db7/stdnet/utils/dates.py#L12-L13
|
|||
gem/oq-engine
|
1bdb88f3914e390abcbd285600bfd39477aae47c
|
openquake/hazardlib/gsim/faccioli_cauzzi_2006.py
|
python
|
FaccioliCauzzi2006.compute
|
(self, ctx: np.recarray, imts, mean, sig, tau, phi)
|
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
|
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
|
[
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"GroundShakingIntensityModel",
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"compute",
">",
"for",
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"of",
"input",
"and",
"result",
"values",
"."
] |
def compute(self, ctx: np.recarray, imts, mean, sig, tau, phi):
"""
See :meth:`superclass method
<.base.GroundShakingIntensityModel.compute>`
for spec of input and result values.
"""
for m, imt in enumerate(imts):
C = self.COEFFS[imt]
d = np.sqrt(ctx.repi**2 + C['h']**2)
term01 = C['c3'] * (np.log(d))
mean[m] = C['c1'] + C['c2'] * ctx.mag + term01
sig[m] = C['sigma']
|
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https://github.com/gem/oq-engine/blob/1bdb88f3914e390abcbd285600bfd39477aae47c/openquake/hazardlib/gsim/faccioli_cauzzi_2006.py#L56-L67
|
||
fluentpython/notebooks
|
0f6e1e8d1686743dacd9281df7c5b5921812010a
|
attic/control/adder/coroadder_deco.py
|
python
|
coroutine
|
(func)
|
return primed_coroutine
|
[] |
def coroutine(func):
def primed_coroutine(*args, **kwargs):
coro = func(*args, **kwargs)
next(coro)
return coro
return primed_coroutine
|
[
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"coro",
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"return",
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"return",
"primed_coroutine"
] |
https://github.com/fluentpython/notebooks/blob/0f6e1e8d1686743dacd9281df7c5b5921812010a/attic/control/adder/coroadder_deco.py#L44-L49
|
|||
cupy/cupy
|
a47ad3105f0fe817a4957de87d98ddccb8c7491f
|
cupy/_indexing/indexing.py
|
python
|
take_along_axis
|
(a, indices, axis)
|
return a[tuple(fancy_index)]
|
Take values from the input array by matching 1d index and data slices.
Args:
a (cupy.ndarray): Array to extract elements.
indices (cupy.ndarray): Indices to take along each 1d slice of ``a``.
axis (int): The axis to take 1d slices along.
Returns:
cupy.ndarray: The indexed result.
.. seealso:: :func:`numpy.take_along_axis`
|
Take values from the input array by matching 1d index and data slices.
|
[
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"input",
"array",
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"matching",
"1d",
"index",
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] |
def take_along_axis(a, indices, axis):
"""Take values from the input array by matching 1d index and data slices.
Args:
a (cupy.ndarray): Array to extract elements.
indices (cupy.ndarray): Indices to take along each 1d slice of ``a``.
axis (int): The axis to take 1d slices along.
Returns:
cupy.ndarray: The indexed result.
.. seealso:: :func:`numpy.take_along_axis`
"""
if indices.dtype.kind not in ('i', 'u'):
raise IndexError('`indices` must be an integer array')
if axis is None:
a = a.ravel()
axis = 0
ndim = a.ndim
axis = internal._normalize_axis_index(axis, ndim)
if ndim != indices.ndim:
raise ValueError(
'`indices` and `a` must have the same number of dimensions')
fancy_index = []
for i, n in enumerate(a.shape):
if i == axis:
fancy_index.append(indices)
else:
ind_shape = (1,) * i + (-1,) + (1,) * (ndim - i - 1)
fancy_index.append(cupy.arange(n).reshape(ind_shape))
return a[tuple(fancy_index)]
|
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https://github.com/cupy/cupy/blob/a47ad3105f0fe817a4957de87d98ddccb8c7491f/cupy/_indexing/indexing.py#L31-L68
|
|
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/api/node_v1_api.py
|
python
|
NodeV1Api.get_api_resources_with_http_info
|
(self, **kwargs)
|
return self.api_client.call_api(
'/apis/node.k8s.io/v1/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='V1APIResourceList', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
|
get_api_resources # noqa: E501
get available resources # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_api_resources_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(V1APIResourceList, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
|
get_api_resources # noqa: E501
|
[
"get_api_resources",
"#",
"noqa",
":",
"E501"
] |
def get_api_resources_with_http_info(self, **kwargs): # noqa: E501
"""get_api_resources # noqa: E501
get available resources # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_api_resources_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(V1APIResourceList, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = [
]
all_params.extend(
[
'async_req',
'_return_http_data_only',
'_preload_content',
'_request_timeout'
]
)
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method get_api_resources" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf']) # noqa: E501
# Authentication setting
auth_settings = ['BearerToken'] # noqa: E501
return self.api_client.call_api(
'/apis/node.k8s.io/v1/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='V1APIResourceList', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
|
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"(",
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")",
",",
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"=",
"collection_formats",
")"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/api/node_v1_api.py#L506-L585
|
|
P1sec/pycrate
|
d12bbccf1df8c9c7891a26967a9d2635610ec5b8
|
pycrate_core/base.py
|
python
|
UintLE._to_pack
|
(self)
|
Produces a tuple ready to be packed with pack_val() according to its
internal value
|
Produces a tuple ready to be packed with pack_val() according to its
internal value
|
[
"Produces",
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"ready",
"to",
"be",
"packed",
"with",
"pack_val",
"()",
"according",
"to",
"its",
"internal",
"value"
] |
def _to_pack(self):
"""Produces a tuple ready to be packed with pack_val() according to its
internal value
"""
if not self.get_trans():
return [(TYPE_UINT_LE, self.get_val(), self.get_bl())]
else:
return []
|
[
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"[",
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https://github.com/P1sec/pycrate/blob/d12bbccf1df8c9c7891a26967a9d2635610ec5b8/pycrate_core/base.py#L762-L769
|
||
intel/fMBT
|
a221c55cd7b6367aa458781b134ae155aa47a71f
|
utils/fmbtgti.py
|
python
|
_Paths.oirArgsList
|
(self, bitmap)
|
Returns list of alternative OIR parameters associated to the bitmap
by appropriate .fmbtoirrc file
|
Returns list of alternative OIR parameters associated to the bitmap
by appropriate .fmbtoirrc file
|
[
"Returns",
"list",
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"alternative",
"OIR",
"parameters",
"associated",
"to",
"the",
"bitmap",
"by",
"appropriate",
".",
"fmbtoirrc",
"file"
] |
def oirArgsList(self, bitmap):
"""Returns list of alternative OIR parameters associated to the bitmap
by appropriate .fmbtoirrc file
"""
if bitmap in self._oirAL:
return self._oirAL[bitmap]
else:
absBitmap = self.abspaths(bitmap)[0]
if absBitmap in self._oirAL:
return self._oirAL[absBitmap]
else:
return None
|
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] |
https://github.com/intel/fMBT/blob/a221c55cd7b6367aa458781b134ae155aa47a71f/utils/fmbtgti.py#L1399-L1410
|
||
tp4a/teleport
|
1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad
|
server/www/packages/packages-linux/x64/qrcode/image/svg.py
|
python
|
SvgPathImage.drawrect
|
(self, row, col)
|
[] |
def drawrect(self, row, col):
# (x, y)
self._points.add((col, row))
|
[
"def",
"drawrect",
"(",
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",",
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"add",
"(",
"(",
"col",
",",
"row",
")",
")"
] |
https://github.com/tp4a/teleport/blob/1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad/server/www/packages/packages-linux/x64/qrcode/image/svg.py#L111-L113
|
||||
ARISE-Initiative/robosuite
|
a5dfaf03cd769170881a1931d8f19c8eb72f531a
|
robosuite/controllers/base_controller.py
|
python
|
Controller.reset_goal
|
(self)
|
Resets the goal -- usually by setting to the goal to all zeros, but in some cases may be different (e.g.: OSC)
|
Resets the goal -- usually by setting to the goal to all zeros, but in some cases may be different (e.g.: OSC)
|
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"(",
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":",
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] |
def reset_goal(self):
"""
Resets the goal -- usually by setting to the goal to all zeros, but in some cases may be different (e.g.: OSC)
"""
raise NotImplementedError
|
[
"def",
"reset_goal",
"(",
"self",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/ARISE-Initiative/robosuite/blob/a5dfaf03cd769170881a1931d8f19c8eb72f531a/robosuite/controllers/base_controller.py#L202-L206
|
||
jazzband/django-authority
|
f58bbef27eca18a818fce6f5c25e651c552386c1
|
authority/templatetags/permissions.py
|
python
|
permission_request_delete_link
|
(context, perm)
|
return {"url": None}
|
Renders a html link to the delete view of the given permission request.
Returns no content if the request-user has no permission to delete foreign
permissions.
|
Renders a html link to the delete view of the given permission request.
Returns no content if the request-user has no permission to delete foreign
permissions.
|
[
"Renders",
"a",
"html",
"link",
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"the",
"request",
"-",
"user",
"has",
"no",
"permission",
"to",
"delete",
"foreign",
"permissions",
"."
] |
def permission_request_delete_link(context, perm):
"""
Renders a html link to the delete view of the given permission request.
Returns no content if the request-user has no permission to delete foreign
permissions.
"""
user = context["request"].user
if user.is_authenticated:
link_kwargs = base_link(context, perm, "authority-delete-permission-request")
if user.has_perm("authority.delete_permission"):
link_kwargs["is_requestor"] = False
return link_kwargs
if not perm.approved and perm.user == user:
link_kwargs["is_requestor"] = True
return link_kwargs
return {"url": None}
|
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"link_kwargs",
"return",
"{",
"\"url\"",
":",
"None",
"}"
] |
https://github.com/jazzband/django-authority/blob/f58bbef27eca18a818fce6f5c25e651c552386c1/authority/templatetags/permissions.py#L435-L450
|
|
django-nonrel/django-nonrel
|
4fbfe7344481a5eab8698f79207f09124310131b
|
django/template/base.py
|
python
|
Variable._resolve_lookup
|
(self, context)
|
return current
|
Performs resolution of a real variable (i.e. not a literal) against the
given context.
As indicated by the method's name, this method is an implementation
detail and shouldn't be called by external code. Use Variable.resolve()
instead.
|
Performs resolution of a real variable (i.e. not a literal) against the
given context.
|
[
"Performs",
"resolution",
"of",
"a",
"real",
"variable",
"(",
"i",
".",
"e",
".",
"not",
"a",
"literal",
")",
"against",
"the",
"given",
"context",
"."
] |
def _resolve_lookup(self, context):
"""
Performs resolution of a real variable (i.e. not a literal) against the
given context.
As indicated by the method's name, this method is an implementation
detail and shouldn't be called by external code. Use Variable.resolve()
instead.
"""
current = context
try: # catch-all for silent variable failures
for bit in self.lookups:
try: # dictionary lookup
current = current[bit]
except (TypeError, AttributeError, KeyError):
try: # attribute lookup
current = getattr(current, bit)
except (TypeError, AttributeError):
try: # list-index lookup
current = current[int(bit)]
except (IndexError, # list index out of range
ValueError, # invalid literal for int()
KeyError, # current is a dict without `int(bit)` key
TypeError, # unsubscriptable object
):
raise VariableDoesNotExist("Failed lookup for key [%s] in %r", (bit, current)) # missing attribute
if callable(current):
if getattr(current, 'alters_data', False):
current = settings.TEMPLATE_STRING_IF_INVALID
else:
try: # method call (assuming no args required)
current = current()
except TypeError: # arguments *were* required
# GOTCHA: This will also catch any TypeError
# raised in the function itself.
current = settings.TEMPLATE_STRING_IF_INVALID # invalid method call
except Exception, e:
if getattr(e, 'silent_variable_failure', False):
current = settings.TEMPLATE_STRING_IF_INVALID
else:
raise
return current
|
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",",
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":",
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"(",
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"raise",
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"current"
] |
https://github.com/django-nonrel/django-nonrel/blob/4fbfe7344481a5eab8698f79207f09124310131b/django/template/base.py#L667-L709
|
|
rootpy/rootpy
|
3926935e1f2100d8ba68070c2ab44055d4800f73
|
rootpy/extern/lockfile/__init__.py
|
python
|
LockBase.is_locked
|
(self)
|
Tell whether or not the file is locked.
|
Tell whether or not the file is locked.
|
[
"Tell",
"whether",
"or",
"not",
"the",
"file",
"is",
"locked",
"."
] |
def is_locked(self):
"""
Tell whether or not the file is locked.
"""
raise NotImplemented("implement in subclass")
|
[
"def",
"is_locked",
"(",
"self",
")",
":",
"raise",
"NotImplemented",
"(",
"\"implement in subclass\"",
")"
] |
https://github.com/rootpy/rootpy/blob/3926935e1f2100d8ba68070c2ab44055d4800f73/rootpy/extern/lockfile/__init__.py#L216-L220
|
||
cloudera/hue
|
23f02102d4547c17c32bd5ea0eb24e9eadd657a4
|
desktop/core/ext-py/eventlet-0.24.1/eventlet/green/zmq.py
|
python
|
Socket.send
|
(self, msg, flags=0, copy=True, track=False)
|
A send method that's safe to use when multiple greenthreads
are calling send, send_multipart, recv and recv_multipart on
the same socket.
|
A send method that's safe to use when multiple greenthreads
are calling send, send_multipart, recv and recv_multipart on
the same socket.
|
[
"A",
"send",
"method",
"that",
"s",
"safe",
"to",
"use",
"when",
"multiple",
"greenthreads",
"are",
"calling",
"send",
"send_multipart",
"recv",
"and",
"recv_multipart",
"on",
"the",
"same",
"socket",
"."
] |
def send(self, msg, flags=0, copy=True, track=False):
"""A send method that's safe to use when multiple greenthreads
are calling send, send_multipart, recv and recv_multipart on
the same socket.
"""
if flags & NOBLOCK:
result = _Socket_send(self, msg, flags, copy, track)
# Instead of calling both wake methods, could call
# self.getsockopt(EVENTS) which would trigger wakeups if
# needed.
self._eventlet_send_event.wake()
self._eventlet_recv_event.wake()
return result
# TODO: pyzmq will copy the message buffer and create Message
# objects under some circumstances. We could do that work here
# once to avoid doing it every time the send is retried.
flags |= NOBLOCK
with self._eventlet_send_lock:
while True:
try:
return _Socket_send(self, msg, flags, copy, track)
except ZMQError as e:
if e.errno == EAGAIN:
self._eventlet_send_event.block()
else:
raise
finally:
# The call to send processes 0mq events and may
# make the socket ready to recv. Wake the next
# receiver. (Could check EVENTS for POLLIN here)
self._eventlet_recv_event.wake()
|
[
"def",
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",",
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",",
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"=",
"0",
",",
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"=",
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":",
"result",
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"_Socket_send",
"(",
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",",
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",",
"flags",
",",
"copy",
",",
"track",
")",
"# Instead of calling both wake methods, could call",
"# self.getsockopt(EVENTS) which would trigger wakeups if",
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".",
"_eventlet_send_event",
".",
"wake",
"(",
")",
"self",
".",
"_eventlet_recv_event",
".",
"wake",
"(",
")",
"return",
"result",
"# TODO: pyzmq will copy the message buffer and create Message",
"# objects under some circumstances. We could do that work here",
"# once to avoid doing it every time the send is retried.",
"flags",
"|=",
"NOBLOCK",
"with",
"self",
".",
"_eventlet_send_lock",
":",
"while",
"True",
":",
"try",
":",
"return",
"_Socket_send",
"(",
"self",
",",
"msg",
",",
"flags",
",",
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",",
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")",
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":",
"self",
".",
"_eventlet_send_event",
".",
"block",
"(",
")",
"else",
":",
"raise",
"finally",
":",
"# The call to send processes 0mq events and may",
"# make the socket ready to recv. Wake the next",
"# receiver. (Could check EVENTS for POLLIN here)",
"self",
".",
"_eventlet_recv_event",
".",
"wake",
"(",
")"
] |
https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/eventlet-0.24.1/eventlet/green/zmq.py#L276-L307
|
||
metabrainz/listenbrainz-server
|
391a0b91ac3a48398027467651ce3160765c7f37
|
listenbrainz/webserver/views/user.py
|
python
|
recommendation_playlists
|
(user_name: str)
|
return render_template(
"playlists/playlists.html",
active_section="recommendations",
props=ujson.dumps(props),
user=user
)
|
Show playlists created for user
|
Show playlists created for user
|
[
"Show",
"playlists",
"created",
"for",
"user"
] |
def recommendation_playlists(user_name: str):
""" Show playlists created for user """
offset = request.args.get('offset', 0)
try:
offset = int(offset)
except ValueError:
raise BadRequest("Incorrect int argument offset: %s" %
request.args.get("offset"))
count = request.args.get("count", DEFAULT_NUMBER_OF_PLAYLISTS_PER_CALL)
try:
count = int(count)
except ValueError:
raise BadRequest("Incorrect int argument count: %s" %
request.args.get("count"))
user = _get_user(user_name)
user_data = {
"name": user.musicbrainz_id,
"id": user.id,
}
playlists = []
user_playlists, playlist_count = get_playlists_created_for_user(
user.id, False, count, offset)
for playlist in user_playlists:
playlists.append(serialize_jspf(playlist))
props = {
"playlists": playlists,
"user": user_data,
"active_section": "recommendations",
"playlist_count": playlist_count,
}
return render_template(
"playlists/playlists.html",
active_section="recommendations",
props=ujson.dumps(props),
user=user
)
|
[
"def",
"recommendation_playlists",
"(",
"user_name",
":",
"str",
")",
":",
"offset",
"=",
"request",
".",
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".",
"get",
"(",
"'offset'",
",",
"0",
")",
"try",
":",
"offset",
"=",
"int",
"(",
"offset",
")",
"except",
"ValueError",
":",
"raise",
"BadRequest",
"(",
"\"Incorrect int argument offset: %s\"",
"%",
"request",
".",
"args",
".",
"get",
"(",
"\"offset\"",
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")",
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",",
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"\"Incorrect int argument count: %s\"",
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")",
")",
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"_get_user",
"(",
"user_name",
")",
"user_data",
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"\"name\"",
":",
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".",
"musicbrainz_id",
",",
"\"id\"",
":",
"user",
".",
"id",
",",
"}",
"playlists",
"=",
"[",
"]",
"user_playlists",
",",
"playlist_count",
"=",
"get_playlists_created_for_user",
"(",
"user",
".",
"id",
",",
"False",
",",
"count",
",",
"offset",
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"for",
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"playlists",
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"(",
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"(",
"playlist",
")",
")",
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"{",
"\"playlists\"",
":",
"playlists",
",",
"\"user\"",
":",
"user_data",
",",
"\"active_section\"",
":",
"\"recommendations\"",
",",
"\"playlist_count\"",
":",
"playlist_count",
",",
"}",
"return",
"render_template",
"(",
"\"playlists/playlists.html\"",
",",
"active_section",
"=",
"\"recommendations\"",
",",
"props",
"=",
"ujson",
".",
"dumps",
"(",
"props",
")",
",",
"user",
"=",
"user",
")"
] |
https://github.com/metabrainz/listenbrainz-server/blob/391a0b91ac3a48398027467651ce3160765c7f37/listenbrainz/webserver/views/user.py#L269-L309
|
|
beeware/ouroboros
|
a29123c6fab6a807caffbb7587cf548e0c370296
|
ouroboros/decimal.py
|
python
|
Decimal.to_eng_string
|
(self, context=None)
|
return self.__str__(eng=True, context=context)
|
Convert to engineering-type string.
Engineering notation has an exponent which is a multiple of 3, so there
are up to 3 digits left of the decimal place.
Same rules for when in exponential and when as a value as in __str__.
|
Convert to engineering-type string.
|
[
"Convert",
"to",
"engineering",
"-",
"type",
"string",
"."
] |
def to_eng_string(self, context=None):
"""Convert to engineering-type string.
Engineering notation has an exponent which is a multiple of 3, so there
are up to 3 digits left of the decimal place.
Same rules for when in exponential and when as a value as in __str__.
"""
return self.__str__(eng=True, context=context)
|
[
"def",
"to_eng_string",
"(",
"self",
",",
"context",
"=",
"None",
")",
":",
"return",
"self",
".",
"__str__",
"(",
"eng",
"=",
"True",
",",
"context",
"=",
"context",
")"
] |
https://github.com/beeware/ouroboros/blob/a29123c6fab6a807caffbb7587cf548e0c370296/ouroboros/decimal.py#L1077-L1085
|
|
fonttools/fonttools
|
892322aaff6a89bea5927379ec06bc0da3dfb7df
|
Lib/fontTools/varLib/merger.py
|
python
|
_PairPosFormat2_merge
|
(self, lst, merger)
|
[] |
def _PairPosFormat2_merge(self, lst, merger):
assert allEqual([l.ValueFormat2 == 0 for l in lst if l.Class1Record]), "Report bug against fonttools."
merger.mergeObjects(self, lst,
exclude=('Coverage',
'ClassDef1', 'Class1Count',
'ClassDef2', 'Class2Count',
'Class1Record',
'ValueFormat1', 'ValueFormat2'))
# Align coverages
glyphs, _ = _merge_GlyphOrders(merger.font,
[v.Coverage.glyphs for v in lst])
self.Coverage.glyphs = glyphs
# Currently, if the coverage of PairPosFormat2 subtables are different,
# we do NOT bother walking down the subtable list when filling in new
# rows for alignment. As such, this is only correct if current subtable
# is the last subtable in the lookup. Ensure that.
#
# Note that our canonicalization process merges trailing PairPosFormat2's,
# so in reality this is rare.
for l,subtables in zip(lst,merger.lookup_subtables):
if l.Coverage.glyphs != glyphs:
assert l == subtables[-1]
matrices = _PairPosFormat2_align_matrices(self, lst, merger.font)
self.Class1Record = list(matrices[0]) # TODO move merger to be selfless
merger.mergeLists(self.Class1Record, matrices)
|
[
"def",
"_PairPosFormat2_merge",
"(",
"self",
",",
"lst",
",",
"merger",
")",
":",
"assert",
"allEqual",
"(",
"[",
"l",
".",
"ValueFormat2",
"==",
"0",
"for",
"l",
"in",
"lst",
"if",
"l",
".",
"Class1Record",
"]",
")",
",",
"\"Report bug against fonttools.\"",
"merger",
".",
"mergeObjects",
"(",
"self",
",",
"lst",
",",
"exclude",
"=",
"(",
"'Coverage'",
",",
"'ClassDef1'",
",",
"'Class1Count'",
",",
"'ClassDef2'",
",",
"'Class2Count'",
",",
"'Class1Record'",
",",
"'ValueFormat1'",
",",
"'ValueFormat2'",
")",
")",
"# Align coverages",
"glyphs",
",",
"_",
"=",
"_merge_GlyphOrders",
"(",
"merger",
".",
"font",
",",
"[",
"v",
".",
"Coverage",
".",
"glyphs",
"for",
"v",
"in",
"lst",
"]",
")",
"self",
".",
"Coverage",
".",
"glyphs",
"=",
"glyphs",
"# Currently, if the coverage of PairPosFormat2 subtables are different,",
"# we do NOT bother walking down the subtable list when filling in new",
"# rows for alignment. As such, this is only correct if current subtable",
"# is the last subtable in the lookup. Ensure that.",
"#",
"# Note that our canonicalization process merges trailing PairPosFormat2's,",
"# so in reality this is rare.",
"for",
"l",
",",
"subtables",
"in",
"zip",
"(",
"lst",
",",
"merger",
".",
"lookup_subtables",
")",
":",
"if",
"l",
".",
"Coverage",
".",
"glyphs",
"!=",
"glyphs",
":",
"assert",
"l",
"==",
"subtables",
"[",
"-",
"1",
"]",
"matrices",
"=",
"_PairPosFormat2_align_matrices",
"(",
"self",
",",
"lst",
",",
"merger",
".",
"font",
")",
"self",
".",
"Class1Record",
"=",
"list",
"(",
"matrices",
"[",
"0",
"]",
")",
"# TODO move merger to be selfless",
"merger",
".",
"mergeLists",
"(",
"self",
".",
"Class1Record",
",",
"matrices",
")"
] |
https://github.com/fonttools/fonttools/blob/892322aaff6a89bea5927379ec06bc0da3dfb7df/Lib/fontTools/varLib/merger.py#L491-L520
|
||||
dexy/dexy
|
323c1806e51f75435e11d2265703e68f46c8aef3
|
dexy/node.py
|
python
|
Node.__call__
|
(self, *args, **kw)
|
[] |
def __call__(self, *args, **kw):
for inpt in self.inputs:
for task in inpt:
task()
self.wrapper.current_task = self
self.run()
self.wrapper.current_task = None
|
[
"def",
"__call__",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kw",
")",
":",
"for",
"inpt",
"in",
"self",
".",
"inputs",
":",
"for",
"task",
"in",
"inpt",
":",
"task",
"(",
")",
"self",
".",
"wrapper",
".",
"current_task",
"=",
"self",
"self",
".",
"run",
"(",
")",
"self",
".",
"wrapper",
".",
"current_task",
"=",
"None"
] |
https://github.com/dexy/dexy/blob/323c1806e51f75435e11d2265703e68f46c8aef3/dexy/node.py#L257-L263
|
||||
rwth-i6/returnn
|
f2d718a197a280b0d5f0fd91a7fcb8658560dddb
|
returnn/config.py
|
python
|
network_json_from_config
|
(config, mask=None)
|
return json_content
|
:type config: Config
:param str mask: "unity", "none" or "dropout"
:rtype: dict[str]
|
:type config: Config
:param str mask: "unity", "none" or "dropout"
:rtype: dict[str]
|
[
":",
"type",
"config",
":",
"Config",
":",
"param",
"str",
"mask",
":",
"unity",
"none",
"or",
"dropout",
":",
"rtype",
":",
"dict",
"[",
"str",
"]"
] |
def network_json_from_config(config, mask=None):
"""
:type config: Config
:param str mask: "unity", "none" or "dropout"
:rtype: dict[str]
"""
from returnn.log import log
json_content = None
if config.has("network") and config.is_typed("network"):
json_content = config.typed_value("network")
assert isinstance(json_content, dict)
assert json_content
elif config.network_topology_json:
start_var = config.network_topology_json.find('(config:', 0) # e.g. ..., "n_out" : (config:var), ...
while start_var > 0:
end_var = config.network_topology_json.find(')', start_var)
assert end_var > 0, "invalid variable syntax at " + str(start_var)
var = config.network_topology_json[start_var+8:end_var]
assert config.has(var), "could not find variable " + var
config.network_topology_json = (
config.network_topology_json[:start_var] + config.value(var, "") + config.network_topology_json[end_var+1:])
print("substituting variable %s with %s" % (var, config.value(var, "")), file=log.v4)
start_var = config.network_topology_json.find('(config:', start_var+1)
try:
import json
json_content = json.loads(config.network_topology_json)
except ValueError as e:
print("----- BEGIN JSON CONTENT -----", file=log.v3)
print(config.network_topology_json, file=log.v3)
print("------ END JSON CONTENT ------", file=log.v3)
assert False, "invalid json content, %r" % e
assert isinstance(json_content, dict)
if 'network' in json_content:
json_content = json_content['network']
assert json_content
if not json_content:
if not mask:
if sum(config.float_list('dropout', [0])) > 0.0:
mask = "dropout"
from returnn.network_description import LayerNetworkDescription
description = LayerNetworkDescription.from_config(config)
json_content = description.to_json_content(mask=mask)
return json_content
|
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",",
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"=",
"description",
".",
"to_json_content",
"(",
"mask",
"=",
"mask",
")",
"return",
"json_content"
] |
https://github.com/rwth-i6/returnn/blob/f2d718a197a280b0d5f0fd91a7fcb8658560dddb/returnn/config.py#L584-L626
|
|
francisck/DanderSpritz_docs
|
86bb7caca5a957147f120b18bb5c31f299914904
|
Python/Core/Lib/_abcoll.py
|
python
|
MutableSet.remove
|
(self, value)
|
Remove an element. If not a member, raise a KeyError.
|
Remove an element. If not a member, raise a KeyError.
|
[
"Remove",
"an",
"element",
".",
"If",
"not",
"a",
"member",
"raise",
"a",
"KeyError",
"."
] |
def remove(self, value):
"""Remove an element. If not a member, raise a KeyError."""
if value not in self:
raise KeyError(value)
self.discard(value)
|
[
"def",
"remove",
"(",
"self",
",",
"value",
")",
":",
"if",
"value",
"not",
"in",
"self",
":",
"raise",
"KeyError",
"(",
"value",
")",
"self",
".",
"discard",
"(",
"value",
")"
] |
https://github.com/francisck/DanderSpritz_docs/blob/86bb7caca5a957147f120b18bb5c31f299914904/Python/Core/Lib/_abcoll.py#L271-L275
|
||
IronLanguages/ironpython3
|
7a7bb2a872eeab0d1009fc8a6e24dca43f65b693
|
Src/StdLib/Lib/encodings/iso8859_13.py
|
python
|
getregentry
|
()
|
return codecs.CodecInfo(
name='iso8859-13',
encode=Codec().encode,
decode=Codec().decode,
incrementalencoder=IncrementalEncoder,
incrementaldecoder=IncrementalDecoder,
streamreader=StreamReader,
streamwriter=StreamWriter,
)
|
[] |
def getregentry():
return codecs.CodecInfo(
name='iso8859-13',
encode=Codec().encode,
decode=Codec().decode,
incrementalencoder=IncrementalEncoder,
incrementaldecoder=IncrementalDecoder,
streamreader=StreamReader,
streamwriter=StreamWriter,
)
|
[
"def",
"getregentry",
"(",
")",
":",
"return",
"codecs",
".",
"CodecInfo",
"(",
"name",
"=",
"'iso8859-13'",
",",
"encode",
"=",
"Codec",
"(",
")",
".",
"encode",
",",
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")",
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",",
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"IncrementalDecoder",
",",
"streamreader",
"=",
"StreamReader",
",",
"streamwriter",
"=",
"StreamWriter",
",",
")"
] |
https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/encodings/iso8859_13.py#L33-L42
|
|||
CenterForOpenScience/osf.io
|
cc02691be017e61e2cd64f19b848b2f4c18dcc84
|
osf/models/schema_response.py
|
python
|
SchemaResponse._validate_accept_trigger
|
(self, user)
|
Validate usage of the "accept" trigger on the underlying ApprovalsMachine
"accept" has three valid usages:
First, "accept" is called from within the "approve" trigger once all required approvals
have been granted. This call should receive the user who issued the final "approve"
so that the correct SchemaResponseAction can be logged.
Second, moderators "accept" a SchemaResponse if it belongs to a moderated parent resource.
In this case, the user must have the correct permission on the parent's provider.
Finally, "accept" can be called without a user in order to bypass the need for approvals
(the "internal accept shortcut") to make life easier for OSF scripts and utilities.
"accept" can only be invoked from UNAPPROVED and PENDING_MODERATION, calling from any
other state will result in a MachineError prior to this validation.
|
Validate usage of the "accept" trigger on the underlying ApprovalsMachine
|
[
"Validate",
"usage",
"of",
"the",
"accept",
"trigger",
"on",
"the",
"underlying",
"ApprovalsMachine"
] |
def _validate_accept_trigger(self, user):
"""Validate usage of the "accept" trigger on the underlying ApprovalsMachine
"accept" has three valid usages:
First, "accept" is called from within the "approve" trigger once all required approvals
have been granted. This call should receive the user who issued the final "approve"
so that the correct SchemaResponseAction can be logged.
Second, moderators "accept" a SchemaResponse if it belongs to a moderated parent resource.
In this case, the user must have the correct permission on the parent's provider.
Finally, "accept" can be called without a user in order to bypass the need for approvals
(the "internal accept shortcut") to make life easier for OSF scripts and utilities.
"accept" can only be invoked from UNAPPROVED and PENDING_MODERATION, calling from any
other state will result in a MachineError prior to this validation.
"""
if self.state is ApprovalStates.UNAPPROVED:
# user = None -> internal accept shortcut
# not self.pending_approvers.exists() -> called from within "approve"
if user is None or not self.pending_approvers.exists():
return
raise MachineError(
f'Invalid usage of "accept" trigger from UNAPPROVED state '
f'against SchemaResponse with id [{self._id}]'
)
if not user.has_perm('accept_submissions', self.parent.provider):
raise PermissionsError(
f'User {user} is not a modrator on {self.parent.provider} and does not '
f'have permission to "accept" SchemaResponse with id [{self._id}]'
)
|
[
"def",
"_validate_accept_trigger",
"(",
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",",
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")",
":",
"if",
"self",
".",
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"is",
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"UNAPPROVED",
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"# user = None -> internal accept shortcut",
"# not self.pending_approvers.exists() -> called from within \"approve\"",
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"f'User {user} is not a modrator on {self.parent.provider} and does not '",
"f'have permission to \"accept\" SchemaResponse with id [{self._id}]'",
")"
] |
https://github.com/CenterForOpenScience/osf.io/blob/cc02691be017e61e2cd64f19b848b2f4c18dcc84/osf/models/schema_response.py#L384-L415
|
||
general03/flask-autoindex
|
424246242c9f40aeb9ac2c8c63f4d2234024256e
|
.eggs/click-7.1.1-py3.7.egg/click/decorators.py
|
python
|
help_option
|
(*param_decls, **attrs)
|
return decorator
|
Adds a ``--help`` option which immediately ends the program
printing out the help page. This is usually unnecessary to add as
this is added by default to all commands unless suppressed.
Like :func:`version_option`, this is implemented as eager option that
prints in the callback and exits.
All arguments are forwarded to :func:`option`.
|
Adds a ``--help`` option which immediately ends the program
printing out the help page. This is usually unnecessary to add as
this is added by default to all commands unless suppressed.
|
[
"Adds",
"a",
"--",
"help",
"option",
"which",
"immediately",
"ends",
"the",
"program",
"printing",
"out",
"the",
"help",
"page",
".",
"This",
"is",
"usually",
"unnecessary",
"to",
"add",
"as",
"this",
"is",
"added",
"by",
"default",
"to",
"all",
"commands",
"unless",
"suppressed",
"."
] |
def help_option(*param_decls, **attrs):
"""Adds a ``--help`` option which immediately ends the program
printing out the help page. This is usually unnecessary to add as
this is added by default to all commands unless suppressed.
Like :func:`version_option`, this is implemented as eager option that
prints in the callback and exits.
All arguments are forwarded to :func:`option`.
"""
def decorator(f):
def callback(ctx, param, value):
if value and not ctx.resilient_parsing:
echo(ctx.get_help(), color=ctx.color)
ctx.exit()
attrs.setdefault("is_flag", True)
attrs.setdefault("expose_value", False)
attrs.setdefault("help", "Show this message and exit.")
attrs.setdefault("is_eager", True)
attrs["callback"] = callback
return option(*(param_decls or ("--help",)), **attrs)(f)
return decorator
|
[
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",",
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"*",
"attrs",
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"(",
"f",
")",
"return",
"decorator"
] |
https://github.com/general03/flask-autoindex/blob/424246242c9f40aeb9ac2c8c63f4d2234024256e/.eggs/click-7.1.1-py3.7.egg/click/decorators.py#L309-L333
|
|
Neoteroi/BlackSheep
|
2936cdd3ba6fceacd230a02c99241bde1d06b265
|
blacksheep/client/session.py
|
python
|
_get_default_pools_for_loop
|
(loop)
|
This function is meant to help users of the ClientSession:
to prevent creating many pools, decreasing performance only by
instantiating several ClientSession without a specific HTTP Connections
pools.
|
This function is meant to help users of the ClientSession:
to prevent creating many pools, decreasing performance only by
instantiating several ClientSession without a specific HTTP Connections
pools.
|
[
"This",
"function",
"is",
"meant",
"to",
"help",
"users",
"of",
"the",
"ClientSession",
":",
"to",
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"creating",
"many",
"pools",
"decreasing",
"performance",
"only",
"by",
"instantiating",
"several",
"ClientSession",
"without",
"a",
"specific",
"HTTP",
"Connections",
"pools",
"."
] |
def _get_default_pools_for_loop(loop):
"""
This function is meant to help users of the ClientSession:
to prevent creating many pools, decreasing performance only by
instantiating several ClientSession without a specific HTTP Connections
pools.
"""
loop_id = id(loop)
try:
return _default_pools_by_loop_id[loop_id]
except KeyError:
pools = ClientConnectionPools(loop)
_default_pools_by_loop_id[loop_id] = pools
return pools
|
[
"def",
"_get_default_pools_for_loop",
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"loop",
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":",
"loop_id",
"=",
"id",
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"loop",
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"_default_pools_by_loop_id",
"[",
"loop_id",
"]",
"=",
"pools",
"return",
"pools"
] |
https://github.com/Neoteroi/BlackSheep/blob/2936cdd3ba6fceacd230a02c99241bde1d06b265/blacksheep/client/session.py#L60-L73
|
||
tenpy/tenpy
|
bbdd3dbbdb511948eb0e6ba7ff619ac6ca657fff
|
tenpy/algorithms/mps_common.py
|
python
|
VariationalCompression.run
|
(self)
|
return TruncationError(max_trunc_err, 1. - 2. * max_trunc_err)
|
Run the compression.
The state :attr:`psi` is compressed in place.
.. warning ::
Call this function directly after initializing the class, without modifying `psi`
inbetween. A copy of :attr:`psi` is made during :meth:`init_env`!
Returns
-------
max_trunc_err : :class:`~tenpy.algorithms.truncation.TruncationError`
The maximal truncation error of a two-site wave function.
|
Run the compression.
|
[
"Run",
"the",
"compression",
"."
] |
def run(self):
"""Run the compression.
The state :attr:`psi` is compressed in place.
.. warning ::
Call this function directly after initializing the class, without modifying `psi`
inbetween. A copy of :attr:`psi` is made during :meth:`init_env`!
Returns
-------
max_trunc_err : :class:`~tenpy.algorithms.truncation.TruncationError`
The maximal truncation error of a two-site wave function.
"""
self.options.deprecated_alias("N_sweeps", "max_sweeps",
"Also check out the other new convergence parameters "
"min_N_sweeps and tol_theta_diff!")
max_sweeps = self.options.get("max_sweeps", 2)
min_sweeps = self.options.get("min_sweeps", 1)
tol_diff = self._tol_theta_diff = self.options.get("tol_theta_diff", 1.e-8)
if min_sweeps == max_sweeps and tol_diff is not None:
warnings.warn("VariationalCompression with min_sweeps=max_sweeps: "
"we recommend to set tol_theta_diff=None to avoid overhead")
for i in range(max_sweeps):
self.renormalize = []
self._theta_diff = []
max_trunc_err = self.sweep()
if i + 1 >= min_sweeps and tol_diff is not None:
max_diff = max(self._theta_diff[-(self.psi.L - self.n_optimize):])
if max_diff < tol_diff:
logger.debug("break VariationalCompression after %d sweeps "
"with theta_diff=%.2e", i + 1, max_diff)
break
if self.psi.finite:
self.psi.norm *= max(self.renormalize)
return TruncationError(max_trunc_err, 1. - 2. * max_trunc_err)
|
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"*=",
"max",
"(",
"self",
".",
"renormalize",
")",
"return",
"TruncationError",
"(",
"max_trunc_err",
",",
"1.",
"-",
"2.",
"*",
"max_trunc_err",
")"
] |
https://github.com/tenpy/tenpy/blob/bbdd3dbbdb511948eb0e6ba7ff619ac6ca657fff/tenpy/algorithms/mps_common.py#L1251-L1287
|
|
online-ml/river
|
3732f700da72642afe54095d4b252b05c5018c7d
|
river/tree/hoeffding_tree.py
|
python
|
HoeffdingTree._new_leaf
|
(
self, initial_stats: dict = None, parent: typing.Union[HTLeaf, DTBranch] = None
)
|
Create a new learning node.
The characteristics of the learning node depends on the tree algorithm.
Parameters
----------
initial_stats
Target statistics set from the parent node.
parent
Parent node to inherit from.
Returns
-------
A new learning node.
|
Create a new learning node.
|
[
"Create",
"a",
"new",
"learning",
"node",
"."
] |
def _new_leaf(
self, initial_stats: dict = None, parent: typing.Union[HTLeaf, DTBranch] = None
) -> HTLeaf:
"""Create a new learning node.
The characteristics of the learning node depends on the tree algorithm.
Parameters
----------
initial_stats
Target statistics set from the parent node.
parent
Parent node to inherit from.
Returns
-------
A new learning node.
"""
|
[
"def",
"_new_leaf",
"(",
"self",
",",
"initial_stats",
":",
"dict",
"=",
"None",
",",
"parent",
":",
"typing",
".",
"Union",
"[",
"HTLeaf",
",",
"DTBranch",
"]",
"=",
"None",
")",
"->",
"HTLeaf",
":"
] |
https://github.com/online-ml/river/blob/3732f700da72642afe54095d4b252b05c5018c7d/river/tree/hoeffding_tree.py#L206-L223
|
||
fabiocaccamo/django-maintenance-mode
|
e4102ed35644ab77af250344a37656b3312655ad
|
maintenance_mode/http.py
|
python
|
get_maintenance_response
|
(request)
|
return response
|
Return a '503 Service Unavailable' maintenance response.
|
Return a '503 Service Unavailable' maintenance response.
|
[
"Return",
"a",
"503",
"Service",
"Unavailable",
"maintenance",
"response",
"."
] |
def get_maintenance_response(request):
"""
Return a '503 Service Unavailable' maintenance response.
"""
if settings.MAINTENANCE_MODE_REDIRECT_URL:
return redirect(settings.MAINTENANCE_MODE_REDIRECT_URL)
context = {}
if settings.MAINTENANCE_MODE_GET_TEMPLATE_CONTEXT:
try:
get_request_context_func = import_string(
settings.MAINTENANCE_MODE_GET_TEMPLATE_CONTEXT)
except ImportError:
raise ImproperlyConfigured(
'settings.MAINTENANCE_MODE_GET_TEMPLATE_CONTEXT '
'is not a valid function path.'
)
context = get_request_context_func(request=request)
kwargs = {'context': context}
if django.VERSION < (1, 8):
kwargs = {'context_instance': RequestContext(request, context)}
response = render(request, settings.MAINTENANCE_MODE_TEMPLATE,
status=settings.MAINTENANCE_MODE_STATUS_CODE,
**kwargs)
response['Retry-After'] = settings.MAINTENANCE_MODE_RETRY_AFTER
add_never_cache_headers(response)
return response
|
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"def",
"get_maintenance_response",
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"MAINTENANCE_MODE_REDIRECT_URL",
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"MAINTENANCE_MODE_RETRY_AFTER",
"add_never_cache_headers",
"(",
"response",
")",
"return",
"response"
] |
https://github.com/fabiocaccamo/django-maintenance-mode/blob/e4102ed35644ab77af250344a37656b3312655ad/maintenance_mode/http.py#L34-L64
|
|
securesystemslab/zippy
|
ff0e84ac99442c2c55fe1d285332cfd4e185e089
|
zippy/benchmarks/src/benchmarks/sympy/sympy/core/numbers.py
|
python
|
One._eval_order
|
(self, *symbols)
|
return
|
[] |
def _eval_order(self, *symbols):
return
|
[
"def",
"_eval_order",
"(",
"self",
",",
"*",
"symbols",
")",
":",
"return"
] |
https://github.com/securesystemslab/zippy/blob/ff0e84ac99442c2c55fe1d285332cfd4e185e089/zippy/benchmarks/src/benchmarks/sympy/sympy/core/numbers.py#L1966-L1967
|
|||
sabri-zaki/EasY_HaCk
|
2a39ac384dd0d6fc51c0dd22e8d38cece683fdb9
|
.modules/.sqlmap/thirdparty/bottle/bottle.py
|
python
|
Bottle.add_route
|
(self, route)
|
Add a route object, but do not change the :data:`Route.app`
attribute.
|
Add a route object, but do not change the :data:`Route.app`
attribute.
|
[
"Add",
"a",
"route",
"object",
"but",
"do",
"not",
"change",
"the",
":",
"data",
":",
"Route",
".",
"app",
"attribute",
"."
] |
def add_route(self, route):
""" Add a route object, but do not change the :data:`Route.app`
attribute."""
self.routes.append(route)
self.router.add(route.rule, route.method, route, name=route.name)
if DEBUG: route.prepare()
|
[
"def",
"add_route",
"(",
"self",
",",
"route",
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":",
"self",
".",
"routes",
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"append",
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",",
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"=",
"route",
".",
"name",
")",
"if",
"DEBUG",
":",
"route",
".",
"prepare",
"(",
")"
] |
https://github.com/sabri-zaki/EasY_HaCk/blob/2a39ac384dd0d6fc51c0dd22e8d38cece683fdb9/.modules/.sqlmap/thirdparty/bottle/bottle.py#L834-L839
|
||
w3h/isf
|
6faf0a3df185465ec17369c90ccc16e2a03a1870
|
lib/thirdparty/pyreadline/console/ironpython_console.py
|
python
|
Console.text
|
(self, x, y, text, attr=None)
|
Write text at the given position.
|
Write text at the given position.
|
[
"Write",
"text",
"at",
"the",
"given",
"position",
"."
] |
def text(self, x, y, text, attr=None):
'''Write text at the given position.'''
self.pos(x, y)
self.write_color(text, attr)
|
[
"def",
"text",
"(",
"self",
",",
"x",
",",
"y",
",",
"text",
",",
"attr",
"=",
"None",
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":",
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"(",
"x",
",",
"y",
")",
"self",
".",
"write_color",
"(",
"text",
",",
"attr",
")"
] |
https://github.com/w3h/isf/blob/6faf0a3df185465ec17369c90ccc16e2a03a1870/lib/thirdparty/pyreadline/console/ironpython_console.py#L260-L263
|
||
saltstack/salt
|
fae5bc757ad0f1716483ce7ae180b451545c2058
|
salt/modules/osquery.py
|
python
|
file_
|
(attrs=None, where=None)
|
return _osquery_cmd(table="file", attrs=attrs, where=where)
|
Return file information from osquery
CLI Example:
.. code-block:: bash
salt '*' osquery.file
|
Return file information from osquery
|
[
"Return",
"file",
"information",
"from",
"osquery"
] |
def file_(attrs=None, where=None):
"""
Return file information from osquery
CLI Example:
.. code-block:: bash
salt '*' osquery.file
"""
return _osquery_cmd(table="file", attrs=attrs, where=where)
|
[
"def",
"file_",
"(",
"attrs",
"=",
"None",
",",
"where",
"=",
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")",
":",
"return",
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"table",
"=",
"\"file\"",
",",
"attrs",
"=",
"attrs",
",",
"where",
"=",
"where",
")"
] |
https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/modules/osquery.py#L1016-L1026
|
|
analysiscenter/batchflow
|
294747da0bca309785f925be891441fdd824e9fa
|
batchflow/pipeline.py
|
python
|
Pipeline.delete_all_variables
|
(self)
|
Delete all variables
|
Delete all variables
|
[
"Delete",
"all",
"variables"
] |
def delete_all_variables(self):
""" Delete all variables """
self.variables = VariableDirectory()
|
[
"def",
"delete_all_variables",
"(",
"self",
")",
":",
"self",
".",
"variables",
"=",
"VariableDirectory",
"(",
")"
] |
https://github.com/analysiscenter/batchflow/blob/294747da0bca309785f925be891441fdd824e9fa/batchflow/pipeline.py#L661-L663
|
||
pytorch/ignite
|
e452884afa36b63447b9029c4773f6f59cf41340
|
ignite/engine/__init__.py
|
python
|
supervised_training_step_tpu
|
(
model: torch.nn.Module,
optimizer: torch.optim.Optimizer,
loss_fn: Union[Callable, torch.nn.Module],
device: Optional[Union[str, torch.device]] = None,
non_blocking: bool = False,
prepare_batch: Callable = _prepare_batch,
output_transform: Callable[[Any, Any, Any, torch.Tensor], Any] = lambda x, y, y_pred, loss: loss.item(),
gradient_accumulation_steps: int = 1,
)
|
return update
|
Factory function for supervised training using ``torch_xla``.
Args:
model: the model to train.
optimizer: the optimizer to use.
loss_fn: the loss function to use.
device: device type specification (default: None).
Applies to batches after starting the engine. Model *will not* be moved.
Device can be CPU, TPU.
non_blocking: if True and this copy is between CPU and GPU, the copy may occur asynchronously
with respect to the host. For other cases, this argument has no effect.
prepare_batch: function that receives `batch`, `device`, `non_blocking` and outputs
tuple of tensors `(batch_x, batch_y)`.
output_transform: function that receives 'x', 'y', 'y_pred', 'loss' and returns value
to be assigned to engine's state.output after each iteration. Default is returning `loss.item()`.
gradient_accumulation_steps: Number of steps the gradients should be accumulated across.
(default: 1 (means no gradient accumulation))
Returns:
Callable: update function.
Examples:
.. code-block:: python
from ignite.engine import Engine, supervised_training_step_tpu
model = ...
optimizer = ...
loss_fn = ...
update_fn = supervised_training_step_tpu(model, optimizer, loss_fn, 'xla')
trainer = Engine(update_fn)
.. versionadded:: 0.4.5
.. versionchanged:: 0.5.0
Added Gradient Accumulation argument for all supervised training methods.
|
Factory function for supervised training using ``torch_xla``.
|
[
"Factory",
"function",
"for",
"supervised",
"training",
"using",
"torch_xla",
"."
] |
def supervised_training_step_tpu(
model: torch.nn.Module,
optimizer: torch.optim.Optimizer,
loss_fn: Union[Callable, torch.nn.Module],
device: Optional[Union[str, torch.device]] = None,
non_blocking: bool = False,
prepare_batch: Callable = _prepare_batch,
output_transform: Callable[[Any, Any, Any, torch.Tensor], Any] = lambda x, y, y_pred, loss: loss.item(),
gradient_accumulation_steps: int = 1,
) -> Callable:
"""Factory function for supervised training using ``torch_xla``.
Args:
model: the model to train.
optimizer: the optimizer to use.
loss_fn: the loss function to use.
device: device type specification (default: None).
Applies to batches after starting the engine. Model *will not* be moved.
Device can be CPU, TPU.
non_blocking: if True and this copy is between CPU and GPU, the copy may occur asynchronously
with respect to the host. For other cases, this argument has no effect.
prepare_batch: function that receives `batch`, `device`, `non_blocking` and outputs
tuple of tensors `(batch_x, batch_y)`.
output_transform: function that receives 'x', 'y', 'y_pred', 'loss' and returns value
to be assigned to engine's state.output after each iteration. Default is returning `loss.item()`.
gradient_accumulation_steps: Number of steps the gradients should be accumulated across.
(default: 1 (means no gradient accumulation))
Returns:
Callable: update function.
Examples:
.. code-block:: python
from ignite.engine import Engine, supervised_training_step_tpu
model = ...
optimizer = ...
loss_fn = ...
update_fn = supervised_training_step_tpu(model, optimizer, loss_fn, 'xla')
trainer = Engine(update_fn)
.. versionadded:: 0.4.5
.. versionchanged:: 0.5.0
Added Gradient Accumulation argument for all supervised training methods.
"""
try:
import torch_xla.core.xla_model as xm
except ModuleNotFoundError:
raise ModuleNotFoundError("torch_xla cannot be imported, please install PyTorch XLA.")
if gradient_accumulation_steps <= 0:
raise ValueError(
"Gradient_accumulation_steps must be strictly positive. "
"No gradient accumulation if the value set to one (default)."
)
def update(engine: Engine, batch: Sequence[torch.Tensor]) -> Union[Any, Tuple[torch.Tensor]]:
model.train()
x, y = prepare_batch(batch, device=device, non_blocking=non_blocking)
y_pred = model(x)
loss = loss_fn(y_pred, y)
if gradient_accumulation_steps > 1:
loss = loss / gradient_accumulation_steps
loss.backward()
if engine.state.iteration % gradient_accumulation_steps == 0:
xm.optimizer_step(optimizer, barrier=True)
optimizer.zero_grad()
return output_transform(x, y, y_pred, loss)
return update
|
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",",
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] |
https://github.com/pytorch/ignite/blob/e452884afa36b63447b9029c4773f6f59cf41340/ignite/engine/__init__.py#L275-L346
|
|
cloudera/hue
|
23f02102d4547c17c32bd5ea0eb24e9eadd657a4
|
desktop/core/ext-py/Django-1.11.29/django/db/backends/base/base.py
|
python
|
BaseDatabaseWrapper.ensure_timezone
|
(self)
|
return False
|
Ensure the connection's timezone is set to `self.timezone_name` and
return whether it changed or not.
|
Ensure the connection's timezone is set to `self.timezone_name` and
return whether it changed or not.
|
[
"Ensure",
"the",
"connection",
"s",
"timezone",
"is",
"set",
"to",
"self",
".",
"timezone_name",
"and",
"return",
"whether",
"it",
"changed",
"or",
"not",
"."
] |
def ensure_timezone(self):
"""
Ensure the connection's timezone is set to `self.timezone_name` and
return whether it changed or not.
"""
return False
|
[
"def",
"ensure_timezone",
"(",
"self",
")",
":",
"return",
"False"
] |
https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/Django-1.11.29/django/db/backends/base/base.py#L103-L108
|
|
kuri65536/python-for-android
|
26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891
|
python-modules/twisted/twisted/lore/tree.py
|
python
|
getFirstAncestorWithSectionHeader
|
(entry)
|
return []
|
Visit the ancestors of C{entry} until one with at least one C{h2} child
node is found, then return all of that node's C{h2} child nodes.
@type entry: A DOM Node
@param entry: The node from which to begin traversal. This node itself is
excluded from consideration.
@rtype: C{list} of DOM Nodes
@return: All C{h2} nodes of the ultimately selected parent node.
|
Visit the ancestors of C{entry} until one with at least one C{h2} child
node is found, then return all of that node's C{h2} child nodes.
|
[
"Visit",
"the",
"ancestors",
"of",
"C",
"{",
"entry",
"}",
"until",
"one",
"with",
"at",
"least",
"one",
"C",
"{",
"h2",
"}",
"child",
"node",
"is",
"found",
"then",
"return",
"all",
"of",
"that",
"node",
"s",
"C",
"{",
"h2",
"}",
"child",
"nodes",
"."
] |
def getFirstAncestorWithSectionHeader(entry):
"""
Visit the ancestors of C{entry} until one with at least one C{h2} child
node is found, then return all of that node's C{h2} child nodes.
@type entry: A DOM Node
@param entry: The node from which to begin traversal. This node itself is
excluded from consideration.
@rtype: C{list} of DOM Nodes
@return: All C{h2} nodes of the ultimately selected parent node.
"""
for a in domhelpers.getParents(entry)[1:]:
headers = domhelpers.findNodesNamed(a, "h2")
if len(headers) > 0:
return headers
return []
|
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">",
"0",
":",
"return",
"headers",
"return",
"[",
"]"
] |
https://github.com/kuri65536/python-for-android/blob/26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891/python-modules/twisted/twisted/lore/tree.py#L522-L538
|
|
celery/django-celery
|
c679b05b2abc174e6fa3231b120a07b49ec8f911
|
djcelery/schedulers.py
|
python
|
DatabaseScheduler.delete_task
|
(cls, name)
|
[] |
def delete_task(cls, name):
PeriodicTask._default_manager.get(name=name).delete()
|
[
"def",
"delete_task",
"(",
"cls",
",",
"name",
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":",
"PeriodicTask",
".",
"_default_manager",
".",
"get",
"(",
"name",
"=",
"name",
")",
".",
"delete",
"(",
")"
] |
https://github.com/celery/django-celery/blob/c679b05b2abc174e6fa3231b120a07b49ec8f911/djcelery/schedulers.py#L284-L285
|
||||
ctxis/canape
|
5f0e03424577296bcc60c2008a60a98ec5307e4b
|
CANAPE.Scripting/Lib/xml/dom/pulldom.py
|
python
|
DOMEventStream._emit
|
(self)
|
return rc
|
Fallback replacement for getEvent() that emits
the events that _slurp() read previously.
|
Fallback replacement for getEvent() that emits
the events that _slurp() read previously.
|
[
"Fallback",
"replacement",
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"()",
"that",
"emits",
"the",
"events",
"that",
"_slurp",
"()",
"read",
"previously",
"."
] |
def _emit(self):
""" Fallback replacement for getEvent() that emits
the events that _slurp() read previously.
"""
rc = self.pulldom.firstEvent[1][0]
self.pulldom.firstEvent[1] = self.pulldom.firstEvent[1][1]
return rc
|
[
"def",
"_emit",
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"self",
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":",
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"pulldom",
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"pulldom",
".",
"firstEvent",
"[",
"1",
"]",
"[",
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"]",
"return",
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https://github.com/ctxis/canape/blob/5f0e03424577296bcc60c2008a60a98ec5307e4b/CANAPE.Scripting/Lib/xml/dom/pulldom.py#L280-L286
|
|
FriedAppleTeam/FRAPL
|
89c14d57e0cc77b915fe1e95f60e9e1847699103
|
Framework/FridaLink/FridaLink.py
|
python
|
TargetInfoCallable.__call__
|
(self)
|
[] |
def __call__(self):
self.request = self.engine.handleTargetInfo(self.platform, self.arch)
|
[
"def",
"__call__",
"(",
"self",
")",
":",
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"engine",
".",
"handleTargetInfo",
"(",
"self",
".",
"platform",
",",
"self",
".",
"arch",
")"
] |
https://github.com/FriedAppleTeam/FRAPL/blob/89c14d57e0cc77b915fe1e95f60e9e1847699103/Framework/FridaLink/FridaLink.py#L73-L74
|
||||
spack/spack
|
675210bd8bd1c5d32ad1cc83d898fb43b569ed74
|
lib/spack/spack/modules/lmod.py
|
python
|
make_layout
|
(spec, module_set_name)
|
return LmodFileLayout(conf)
|
Returns the layout information for spec
|
Returns the layout information for spec
|
[
"Returns",
"the",
"layout",
"information",
"for",
"spec"
] |
def make_layout(spec, module_set_name):
"""Returns the layout information for spec """
conf = make_configuration(spec, module_set_name)
return LmodFileLayout(conf)
|
[
"def",
"make_layout",
"(",
"spec",
",",
"module_set_name",
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"=",
"make_configuration",
"(",
"spec",
",",
"module_set_name",
")",
"return",
"LmodFileLayout",
"(",
"conf",
")"
] |
https://github.com/spack/spack/blob/675210bd8bd1c5d32ad1cc83d898fb43b569ed74/lib/spack/spack/modules/lmod.py#L47-L50
|
|
adamreeve/npTDMS
|
bf4d2f65872347fde4fe7fcbb4135f466e87323e
|
nptdms/tdms.py
|
python
|
TdmsChannel.__len__
|
(self)
|
return self._length
|
Returns the number of values in this channel
|
Returns the number of values in this channel
|
[
"Returns",
"the",
"number",
"of",
"values",
"in",
"this",
"channel"
] |
def __len__(self):
""" Returns the number of values in this channel
"""
return self._length
|
[
"def",
"__len__",
"(",
"self",
")",
":",
"return",
"self",
".",
"_length"
] |
https://github.com/adamreeve/npTDMS/blob/bf4d2f65872347fde4fe7fcbb4135f466e87323e/nptdms/tdms.py#L454-L457
|
|
MarioVilas/winappdbg
|
975a088ac54253d0bdef39fe831e82f24b4c11f6
|
winappdbg/win32/kernel32.py
|
python
|
Handle.__copy__
|
(self)
|
return self.dup()
|
Duplicates the Win32 handle when copying the Python object.
@rtype: L{Handle}
@return: A new handle to the same Win32 object.
|
Duplicates the Win32 handle when copying the Python object.
|
[
"Duplicates",
"the",
"Win32",
"handle",
"when",
"copying",
"the",
"Python",
"object",
"."
] |
def __copy__(self):
"""
Duplicates the Win32 handle when copying the Python object.
@rtype: L{Handle}
@return: A new handle to the same Win32 object.
"""
return self.dup()
|
[
"def",
"__copy__",
"(",
"self",
")",
":",
"return",
"self",
".",
"dup",
"(",
")"
] |
https://github.com/MarioVilas/winappdbg/blob/975a088ac54253d0bdef39fe831e82f24b4c11f6/winappdbg/win32/kernel32.py#L645-L652
|
|
microsoft/malmo-challenge
|
a1dec75d0eb4cccc91f9d818a4ecae5fa1ac906f
|
malmopy/environment/malmo/malmo.py
|
python
|
MalmoEnvironment._await_next_obs
|
(self)
|
Ensure that an update to the world state is received
:return:
|
Ensure that an update to the world state is received
:return:
|
[
"Ensure",
"that",
"an",
"update",
"to",
"the",
"world",
"state",
"is",
"received",
":",
"return",
":"
] |
def _await_next_obs(self):
"""
Ensure that an update to the world state is received
:return:
"""
# Wait until we have everything we need
current_state = self._agent.peekWorldState()
while not self.is_valid(current_state) or not self._ready_to_act(current_state):
if current_state.has_mission_begun and not current_state.is_mission_running:
if not current_state.is_mission_running and len(current_state.mission_control_messages) > 0:
# Parse the mission ended message:
mission_end_tree = xml.etree.ElementTree.fromstring(current_state.mission_control_messages[-1].text)
ns_dict = {"malmo": "http://ProjectMalmo.microsoft.com"}
hr_stat = mission_end_tree.find("malmo:HumanReadableStatus", ns_dict).text
self._end_result = hr_stat
break
# Peek fresh world state from socket
current_state = self._agent.peekWorldState()
# Flush current world as soon as we have the entire state
self._world = self._agent.getWorldState()
if self._world.is_mission_running:
new_world = json.loads(self._world.observations[-1].text)
if new_world is not None:
self._world_obs = new_world
# Update video frames if any
if hasattr(self._world, 'video_frames') and len(self._world.video_frames) > 0:
self._last_frame = self._world.video_frames[-1]
|
[
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"=",
"self",
".",
"_world",
".",
"video_frames",
"[",
"-",
"1",
"]"
] |
https://github.com/microsoft/malmo-challenge/blob/a1dec75d0eb4cccc91f9d818a4ecae5fa1ac906f/malmopy/environment/malmo/malmo.py#L323-L354
|
||
khanhnamle1994/natural-language-processing
|
01d450d5ac002b0156ef4cf93a07cb508c1bcdc5
|
assignment1/.env/lib/python2.7/site-packages/pytz/__init__.py
|
python
|
UTC.localize
|
(self, dt, is_dst=False)
|
return dt.replace(tzinfo=self)
|
Convert naive time to local time
|
Convert naive time to local time
|
[
"Convert",
"naive",
"time",
"to",
"local",
"time"
] |
def localize(self, dt, is_dst=False):
'''Convert naive time to local time'''
if dt.tzinfo is not None:
raise ValueError('Not naive datetime (tzinfo is already set)')
return dt.replace(tzinfo=self)
|
[
"def",
"localize",
"(",
"self",
",",
"dt",
",",
"is_dst",
"=",
"False",
")",
":",
"if",
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".",
"tzinfo",
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"None",
":",
"raise",
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"(",
"'Not naive datetime (tzinfo is already set)'",
")",
"return",
"dt",
".",
"replace",
"(",
"tzinfo",
"=",
"self",
")"
] |
https://github.com/khanhnamle1994/natural-language-processing/blob/01d450d5ac002b0156ef4cf93a07cb508c1bcdc5/assignment1/.env/lib/python2.7/site-packages/pytz/__init__.py#L223-L227
|
|
GNOME/gnome-music
|
b7b55c8519f9cc613ca60c01a5ab8cef6b58c92e
|
gnomemusic/widgets/artstack.py
|
python
|
ArtStack._on_thumbnail_changed
|
(self, coreobject, uri)
|
[] |
def _on_thumbnail_changed(self, coreobject, uri):
self._disconnect_cache()
self._handler_id = self._cache.connect(
"finished", self._on_cache_result)
self._async_queue.queue(
self._cache, coreobject, self._size, self.props.scale_factor)
|
[
"def",
"_on_thumbnail_changed",
"(",
"self",
",",
"coreobject",
",",
"uri",
")",
":",
"self",
".",
"_disconnect_cache",
"(",
")",
"self",
".",
"_handler_id",
"=",
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".",
"_cache",
".",
"connect",
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"\"finished\"",
",",
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"_on_cache_result",
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"_async_queue",
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"_cache",
",",
"coreobject",
",",
"self",
".",
"_size",
",",
"self",
".",
"props",
".",
"scale_factor",
")"
] |
https://github.com/GNOME/gnome-music/blob/b7b55c8519f9cc613ca60c01a5ab8cef6b58c92e/gnomemusic/widgets/artstack.py#L131-L138
|
||||
learningequality/ka-lite
|
571918ea668013dcf022286ea85eff1c5333fb8b
|
kalite/packages/bundled/django/core/files/storage.py
|
python
|
Storage.path
|
(self, name)
|
Returns a local filesystem path where the file can be retrieved using
Python's built-in open() function. Storage systems that can't be
accessed using open() should *not* implement this method.
|
Returns a local filesystem path where the file can be retrieved using
Python's built-in open() function. Storage systems that can't be
accessed using open() should *not* implement this method.
|
[
"Returns",
"a",
"local",
"filesystem",
"path",
"where",
"the",
"file",
"can",
"be",
"retrieved",
"using",
"Python",
"s",
"built",
"-",
"in",
"open",
"()",
"function",
".",
"Storage",
"systems",
"that",
"can",
"t",
"be",
"accessed",
"using",
"open",
"()",
"should",
"*",
"not",
"*",
"implement",
"this",
"method",
"."
] |
def path(self, name):
"""
Returns a local filesystem path where the file can be retrieved using
Python's built-in open() function. Storage systems that can't be
accessed using open() should *not* implement this method.
"""
raise NotImplementedError("This backend doesn't support absolute paths.")
|
[
"def",
"path",
"(",
"self",
",",
"name",
")",
":",
"raise",
"NotImplementedError",
"(",
"\"This backend doesn't support absolute paths.\"",
")"
] |
https://github.com/learningequality/ka-lite/blob/571918ea668013dcf022286ea85eff1c5333fb8b/kalite/packages/bundled/django/core/files/storage.py#L79-L85
|
||
PYFTS/pyFTS
|
ad3e857024d0da068feb0d7eae214b55a038a9ca
|
pyFTS/benchmarks/Measures.py
|
python
|
UStatistic
|
(targets, forecasts)
|
return np.sqrt(np.divide(np.nansum(y), np.nansum(naive)))
|
Theil's U Statistic
:param targets:
:param forecasts:
:return:
|
Theil's U Statistic
|
[
"Theil",
"s",
"U",
"Statistic"
] |
def UStatistic(targets, forecasts):
"""
Theil's U Statistic
:param targets:
:param forecasts:
:return:
"""
if not isinstance(forecasts, (list, np.ndarray)):
forecasts = np.array([forecasts])
else:
forecasts = np.array(forecasts)
if not isinstance(targets, (list, np.ndarray)):
targets = np.array([targets])
else:
targets = np.array(targets)
l = forecasts.size
l = 2 if l == 1 else l
naive = []
y = []
for k in np.arange(0, l - 1):
y.append(np.subtract(forecasts[k], targets[k]) ** 2)
naive.append(np.subtract(targets[k + 1], targets[k]) ** 2)
return np.sqrt(np.divide(np.nansum(y), np.nansum(naive)))
|
[
"def",
"UStatistic",
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",",
"forecasts",
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":",
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")",
",",
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"nansum",
"(",
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")",
")",
")"
] |
https://github.com/PYFTS/pyFTS/blob/ad3e857024d0da068feb0d7eae214b55a038a9ca/pyFTS/benchmarks/Measures.py#L112-L139
|
|
datafolklabs/cement
|
2d44d2c1821bda6bdfcfe605d244dc2dfb0b19a6
|
cement/cli/contrib/jinja2/bccache.py
|
python
|
Bucket.load_bytecode
|
(self, f)
|
Loads bytecode from a file or file like object.
|
Loads bytecode from a file or file like object.
|
[
"Loads",
"bytecode",
"from",
"a",
"file",
"or",
"file",
"like",
"object",
"."
] |
def load_bytecode(self, f):
"""Loads bytecode from a file or file like object."""
# make sure the magic header is correct
magic = f.read(len(bc_magic))
if magic != bc_magic:
self.reset()
return
# the source code of the file changed, we need to reload
checksum = pickle.load(f)
if self.checksum != checksum:
self.reset()
return
# if marshal_load fails then we need to reload
try:
self.code = marshal_load(f)
except (EOFError, ValueError, TypeError):
self.reset()
return
|
[
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"(",
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] |
https://github.com/datafolklabs/cement/blob/2d44d2c1821bda6bdfcfe605d244dc2dfb0b19a6/cement/cli/contrib/jinja2/bccache.py#L79-L96
|
||
openai/multiagent-competition
|
b2e081a192429913b7d21a89525901d59c85e7f3
|
gym-compete/gym_compete/new_envs/agents/agent.py
|
python
|
Agent.set_margin
|
(self, margin)
|
[] |
def set_margin(self, margin):
agent_geom_ids = [i for i, name in enumerate(self.env.model.geom_names)
if self.in_scope(name)]
m = self.env.model.geom_margin.copy()
print("Resetting", self.scope, "margins to", margin)
m[agent_geom_ids] = margin
self.env.model.__setattr__('geom_margin', m)
|
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"def",
"set_margin",
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"env",
".",
"model",
".",
"__setattr__",
"(",
"'geom_margin'",
",",
"m",
")"
] |
https://github.com/openai/multiagent-competition/blob/b2e081a192429913b7d21a89525901d59c85e7f3/gym-compete/gym_compete/new_envs/agents/agent.py#L247-L253
|
||||
google/TensorNetwork
|
e12580f1749493dbe05f474d2fecdec4eaba73c5
|
tensornetwork/block_sparse/linalg.py
|
python
|
eigh
|
(matrix: BlockSparseTensor,
UPLO: Optional[Text] = 'L')
|
return E, V
|
Compute the eigen decomposition of a hermitian `M` by `M` matrix `matrix`.
Args:
matrix: A matrix (i.e. a rank-2 tensor) of type `BlockSparseTensor`
Returns:
(ChargeArray,BlockSparseTensor): The eigenvalues and eigenvectors
|
Compute the eigen decomposition of a hermitian `M` by `M` matrix `matrix`.
Args:
matrix: A matrix (i.e. a rank-2 tensor) of type `BlockSparseTensor`
|
[
"Compute",
"the",
"eigen",
"decomposition",
"of",
"a",
"hermitian",
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"by",
"M",
"matrix",
"matrix",
".",
"Args",
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"matrix",
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"A",
"matrix",
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".",
"e",
".",
"a",
"rank",
"-",
"2",
"tensor",
")",
"of",
"type",
"BlockSparseTensor"
] |
def eigh(matrix: BlockSparseTensor,
UPLO: Optional[Text] = 'L') -> Tuple[ChargeArray, BlockSparseTensor]:
"""
Compute the eigen decomposition of a hermitian `M` by `M` matrix `matrix`.
Args:
matrix: A matrix (i.e. a rank-2 tensor) of type `BlockSparseTensor`
Returns:
(ChargeArray,BlockSparseTensor): The eigenvalues and eigenvectors
"""
if matrix.ndim != 2:
raise NotImplementedError("eigh currently supports only rank-2 tensors.")
flat_charges = matrix._charges
flat_flows = matrix._flows
flat_order = matrix.flat_order
tr_partition = len(matrix._order[0])
blocks, charges, shapes = _find_transposed_diagonal_sparse_blocks(
flat_charges, flat_flows, tr_partition, flat_order)
eigvals = []
v_blocks = []
for n, block in enumerate(blocks):
e, v = np.linalg.eigh(np.reshape(matrix.data[block], shapes[:, n]), UPLO)
eigvals.append(e)
v_blocks.append(v)
tmp_labels = [
np.full(len(eigvals[n]), fill_value=n, dtype=np.int16)
for n in range(len(eigvals))
]
if len(tmp_labels) > 0:
eigvalscharge_labels = np.concatenate(tmp_labels)
else:
eigvalscharge_labels = np.empty(0, dtype=np.int16)
eigvalscharge = charges[eigvalscharge_labels]
if len(eigvals) > 0:
all_eigvals = np.concatenate(eigvals)
else:
all_eigvals = np.empty(0, dtype=get_real_dtype(matrix.dtype))
E = ChargeArray(all_eigvals, [eigvalscharge], [False])
charges_v = [eigvalscharge] + [matrix._charges[o] for o in matrix._order[0]]
order_v = [[0]] + [list(np.arange(1, len(matrix._order[0]) + 1))]
flows_v = [True] + [matrix._flows[o] for o in matrix._order[0]]
if len(v_blocks) > 0:
all_v_blocks = np.concatenate([np.ravel(v.T) for v in v_blocks])
else:
all_v_blocks = np.empty(0, dtype=matrix.dtype)
V = BlockSparseTensor(
all_v_blocks,
charges=charges_v,
flows=flows_v,
order=order_v,
check_consistency=False).transpose()
return E, V
|
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] |
https://github.com/google/TensorNetwork/blob/e12580f1749493dbe05f474d2fecdec4eaba73c5/tensornetwork/block_sparse/linalg.py#L395-L451
|
|
IronLanguages/ironpython3
|
7a7bb2a872eeab0d1009fc8a6e24dca43f65b693
|
Src/StdLib/Lib/wsgiref/validate.py
|
python
|
ErrorWrapper.flush
|
(self)
|
[] |
def flush(self):
self.errors.flush()
|
[
"def",
"flush",
"(",
"self",
")",
":",
"self",
".",
"errors",
".",
"flush",
"(",
")"
] |
https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/wsgiref/validate.py#L235-L236
|
||||
googlefonts/fontbakery
|
cb8196c3a636b63654f8370636cb3f438b60d5b1
|
Lib/fontbakery/profiles/typenetwork.py
|
python
|
io_github_abysstypeco_check_ytlc_sanity
|
(ttFont)
|
Check if ytlc values are sane in vf
|
Check if ytlc values are sane in vf
|
[
"Check",
"if",
"ytlc",
"values",
"are",
"sane",
"in",
"vf"
] |
def io_github_abysstypeco_check_ytlc_sanity(ttFont):
"""Check if ytlc values are sane in vf"""
passed = True
for axis in ttFont['fvar'].axes:
if not axis.axisTag == 'ytlc': continue
if axis.minValue < 0 or axis.maxValue > 1000:
passed = False
yield FAIL,\
Message("invalid-range",
f'The range of ytlc values ({axis.minValue} - {axis.maxValue})'
f'does not conform to the expected range of ytlc which should be min value 0 to max value 1000')
if passed:
yield PASS, 'ytlc is sane'
|
[
"def",
"io_github_abysstypeco_check_ytlc_sanity",
"(",
"ttFont",
")",
":",
"passed",
"=",
"True",
"for",
"axis",
"in",
"ttFont",
"[",
"'fvar'",
"]",
".",
"axes",
":",
"if",
"not",
"axis",
".",
"axisTag",
"==",
"'ytlc'",
":",
"continue",
"if",
"axis",
".",
"minValue",
"<",
"0",
"or",
"axis",
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"maxValue",
">",
"1000",
":",
"passed",
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"FAIL",
",",
"Message",
"(",
"\"invalid-range\"",
",",
"f'The range of ytlc values ({axis.minValue} - {axis.maxValue})'",
"f'does not conform to the expected range of ytlc which should be min value 0 to max value 1000'",
")",
"if",
"passed",
":",
"yield",
"PASS",
",",
"'ytlc is sane'"
] |
https://github.com/googlefonts/fontbakery/blob/cb8196c3a636b63654f8370636cb3f438b60d5b1/Lib/fontbakery/profiles/typenetwork.py#L28-L42
|
||
jazzband/tablib
|
94ffe67e50eb5bfd99d73a4f010e463478a98928
|
src/tablib/packages/dbfpy/header.py
|
python
|
DbfHeader.ignoreErrors
|
(self, value)
|
Update `ignoreErrors` flag on self and all fields
|
Update `ignoreErrors` flag on self and all fields
|
[
"Update",
"ignoreErrors",
"flag",
"on",
"self",
"and",
"all",
"fields"
] |
def ignoreErrors(self, value):
"""Update `ignoreErrors` flag on self and all fields"""
self._ignore_errors = value = bool(value)
for _field in self.fields:
_field.ignoreErrors = value
|
[
"def",
"ignoreErrors",
"(",
"self",
",",
"value",
")",
":",
"self",
".",
"_ignore_errors",
"=",
"value",
"=",
"bool",
"(",
"value",
")",
"for",
"_field",
"in",
"self",
".",
"fields",
":",
"_field",
".",
"ignoreErrors",
"=",
"value"
] |
https://github.com/jazzband/tablib/blob/94ffe67e50eb5bfd99d73a4f010e463478a98928/src/tablib/packages/dbfpy/header.py#L142-L146
|
||
ducksboard/libsaas
|
615981a3336f65be9d51ae95a48aed9ad3bd1c3c
|
libsaas/services/github/repos.py
|
python
|
Repo.commit
|
(self, sha)
|
return repocommits.RepoCommit(self, sha)
|
Return a resource corresponding to a single commit in this repo.
|
Return a resource corresponding to a single commit in this repo.
|
[
"Return",
"a",
"resource",
"corresponding",
"to",
"a",
"single",
"commit",
"in",
"this",
"repo",
"."
] |
def commit(self, sha):
"""
Return a resource corresponding to a single commit in this repo.
"""
return repocommits.RepoCommit(self, sha)
|
[
"def",
"commit",
"(",
"self",
",",
"sha",
")",
":",
"return",
"repocommits",
".",
"RepoCommit",
"(",
"self",
",",
"sha",
")"
] |
https://github.com/ducksboard/libsaas/blob/615981a3336f65be9d51ae95a48aed9ad3bd1c3c/libsaas/services/github/repos.py#L200-L204
|
|
keiohta/tf2rl
|
43523930b3328b28fcf2ce64e6a9a8cf4a403044
|
tf2rl/tools/img_tools.py
|
python
|
random_crop
|
(input_imgs, output_size)
|
return np.transpose(cropped_imgs, (0, 2, 3, 1))
|
Args:
input_imgs: np.ndarray
Images whose shape is (batch_size, width, height, channels)
output_size: Int
Output width and height size.
Returns:
|
[] |
def random_crop(input_imgs, output_size):
"""
Args:
input_imgs: np.ndarray
Images whose shape is (batch_size, width, height, channels)
output_size: Int
Output width and height size.
Returns:
"""
assert input_imgs.ndim == 4, f"The dimension of input images must be 4, not {len(input_imgs)}"
batch_size = input_imgs.shape[0]
img_size = input_imgs.shape[1]
assert img_size > output_size
crop_max = img_size - output_size
topleft_x = np.random.randint(0, crop_max, batch_size)
topleft_y = np.random.randint(0, crop_max, batch_size)
# creates all sliding windows combinations of size (output_size)
windows = view_as_windows(
input_imgs, (1, output_size, output_size, 1))[..., 0, :, :, 0]
# selects a random window for each batch element
cropped_imgs = windows[np.arange(batch_size), topleft_x, topleft_y]
return np.transpose(cropped_imgs, (0, 2, 3, 1))
|
[
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"4",
",",
"f\"The dimension of input images must be 4, not {len(input_imgs)}\"",
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",",
"(",
"0",
",",
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",",
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",",
"1",
")",
")"
] |
https://github.com/keiohta/tf2rl/blob/43523930b3328b28fcf2ce64e6a9a8cf4a403044/tf2rl/tools/img_tools.py#L6-L33
|
||
cournape/Bento
|
37de23d784407a7c98a4a15770ffc570d5f32d70
|
bento/private/_yaku/yaku/build_context.py
|
python
|
BuildContext.__init__
|
(self)
|
[] |
def __init__(self):
self.object_tasks = []
self.cache = {}
self.env = {}
|
[
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"object_tasks",
"=",
"[",
"]",
"self",
".",
"cache",
"=",
"{",
"}",
"self",
".",
"env",
"=",
"{",
"}"
] |
https://github.com/cournape/Bento/blob/37de23d784407a7c98a4a15770ffc570d5f32d70/bento/private/_yaku/yaku/build_context.py#L14-L17
|
||||
unipacker/unipacker
|
3e6b94013292fbfbc35ff940bd75ca26acbacdb1
|
unipacker/shell.py
|
python
|
Shell.do_r
|
(self, args)
|
Start execution
|
Start execution
|
[
"Start",
"execution"
] |
def do_r(self, args):
"""Start execution"""
if self.started:
print("Emulation already started. Interpreting as 'c'")
self.do_c(args)
return
self.shell_event.clear()
threading.Thread(target=self.engine.emu).start()
self.shell_event.wait()
|
[
"def",
"do_r",
"(",
"self",
",",
"args",
")",
":",
"if",
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".",
"started",
":",
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"\"Emulation already started. Interpreting as 'c'\"",
")",
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"do_c",
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".",
"shell_event",
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"clear",
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"emu",
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".",
"start",
"(",
")",
"self",
".",
"shell_event",
".",
"wait",
"(",
")"
] |
https://github.com/unipacker/unipacker/blob/3e6b94013292fbfbc35ff940bd75ca26acbacdb1/unipacker/shell.py#L613-L621
|
||
ipython/ipyparallel
|
d35d4fb9501da5b3280b11e83ed633a95f17be1d
|
ipyparallel/util.py
|
python
|
_execute
|
(code)
|
helper method for implementing `client.execute` via `client.apply`
|
helper method for implementing `client.execute` via `client.apply`
|
[
"helper",
"method",
"for",
"implementing",
"client",
".",
"execute",
"via",
"client",
".",
"apply"
] |
def _execute(code):
"""helper method for implementing `client.execute` via `client.apply`"""
user_ns = get_ipython().user_global_ns
exec(code, user_ns)
|
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"def",
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")",
".",
"user_global_ns",
"exec",
"(",
"code",
",",
"user_ns",
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] |
https://github.com/ipython/ipyparallel/blob/d35d4fb9501da5b3280b11e83ed633a95f17be1d/ipyparallel/util.py#L330-L333
|
||
smartbgp/yabgp
|
f073633a813899cd9b413bc28ea2f7737deee141
|
yabgp/message/attribute/community.py
|
python
|
Community.parse
|
(cls, value)
|
return community
|
parse BGP community.
:param value:
|
parse BGP community.
:param value:
|
[
"parse",
"BGP",
"community",
".",
":",
"param",
"value",
":"
] |
def parse(cls, value):
"""
parse BGP community.
:param value:
"""
community = []
if value:
try:
length = len(value) / 2
value_list = list(struct.unpack('!%dH' % length, value))
while value_list:
value_type = value_list[0] * 16 * 16 * 16 * 16 + value_list[1]
if value_type in bgp_cons.WELL_KNOW_COMMUNITY_INT_2_STR:
community.append(bgp_cons.WELL_KNOW_COMMUNITY_INT_2_STR[value_type])
else:
community.append("%s:%s" % (value_list[0], value_list[1]))
value_list = value_list[2:]
except Exception:
raise excep.UpdateMessageError(
sub_error=bgp_cons.ERR_MSG_UPDATE_ATTR_LEN,
data=value)
return community
|
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https://github.com/smartbgp/yabgp/blob/f073633a813899cd9b413bc28ea2f7737deee141/yabgp/message/attribute/community.py#L40-L61
|
|
pyparallel/pyparallel
|
11e8c6072d48c8f13641925d17b147bf36ee0ba3
|
Lib/site-packages/tornado-4.3b2-py3.3-win-amd64.egg/tornado/locks.py
|
python
|
Event.is_set
|
(self)
|
return self._future.done()
|
Return ``True`` if the internal flag is true.
|
Return ``True`` if the internal flag is true.
|
[
"Return",
"True",
"if",
"the",
"internal",
"flag",
"is",
"true",
"."
] |
def is_set(self):
"""Return ``True`` if the internal flag is true."""
return self._future.done()
|
[
"def",
"is_set",
"(",
"self",
")",
":",
"return",
"self",
".",
"_future",
".",
"done",
"(",
")"
] |
https://github.com/pyparallel/pyparallel/blob/11e8c6072d48c8f13641925d17b147bf36ee0ba3/Lib/site-packages/tornado-4.3b2-py3.3-win-amd64.egg/tornado/locks.py#L200-L202
|
|
rucio/rucio
|
6d0d358e04f5431f0b9a98ae40f31af0ddff4833
|
lib/rucio/api/rse.py
|
python
|
get_rse_usage
|
(rse, issuer, source=None, per_account=False, vo='def')
|
return [api_update_return_dict(u) for u in usages]
|
get RSE usage information.
:param rse: The RSE name.
:param issuer: The issuer account.
:param source: dictionary of attributes by which the results should be filtered
:param vo: The VO to act on.
:returns: List of RSE usage data.
|
get RSE usage information.
|
[
"get",
"RSE",
"usage",
"information",
"."
] |
def get_rse_usage(rse, issuer, source=None, per_account=False, vo='def'):
"""
get RSE usage information.
:param rse: The RSE name.
:param issuer: The issuer account.
:param source: dictionary of attributes by which the results should be filtered
:param vo: The VO to act on.
:returns: List of RSE usage data.
"""
rse_id = rse_module.get_rse_id(rse=rse, vo=vo)
usages = rse_module.get_rse_usage(rse_id=rse_id, source=source, per_account=per_account)
for u in usages:
if 'account_usages' in u:
for account_usage in u['account_usages']:
account_usage['account'] = account_usage['account'].external
return [api_update_return_dict(u) for u in usages]
|
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https://github.com/rucio/rucio/blob/6d0d358e04f5431f0b9a98ae40f31af0ddff4833/lib/rucio/api/rse.py#L299-L317
|
|
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/smartthings/__init__.py
|
python
|
async_setup
|
(hass: HomeAssistant, config: ConfigType)
|
return True
|
Initialize the SmartThings platform.
|
Initialize the SmartThings platform.
|
[
"Initialize",
"the",
"SmartThings",
"platform",
"."
] |
async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool:
"""Initialize the SmartThings platform."""
await setup_smartapp_endpoint(hass)
return True
|
[
"async",
"def",
"async_setup",
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"hass",
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"HomeAssistant",
",",
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":",
"ConfigType",
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"->",
"bool",
":",
"await",
"setup_smartapp_endpoint",
"(",
"hass",
")",
"return",
"True"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/smartthings/__init__.py#L55-L58
|
|
saltstack/salt
|
fae5bc757ad0f1716483ce7ae180b451545c2058
|
salt/cloud/clouds/azurearm.py
|
python
|
_get_block_blob_service
|
(kwargs=None)
|
return BlockBlobService(
storage_account,
storage_key,
sas_token=sas_token,
endpoint_suffix=endpoint_suffix,
)
|
Get the block blob storage service.
|
Get the block blob storage service.
|
[
"Get",
"the",
"block",
"blob",
"storage",
"service",
"."
] |
def _get_block_blob_service(kwargs=None):
"""
Get the block blob storage service.
"""
resource_group = kwargs.get("resource_group") or config.get_cloud_config_value(
"resource_group", get_configured_provider(), __opts__, search_global=False
)
sas_token = kwargs.get("sas_token") or config.get_cloud_config_value(
"sas_token", get_configured_provider(), __opts__, search_global=False
)
storage_account = kwargs.get("storage_account") or config.get_cloud_config_value(
"storage_account", get_configured_provider(), __opts__, search_global=False
)
storage_key = kwargs.get("storage_key") or config.get_cloud_config_value(
"storage_key", get_configured_provider(), __opts__, search_global=False
)
if not resource_group:
raise SaltCloudSystemExit("A resource group must be specified")
if not storage_account:
raise SaltCloudSystemExit("A storage account must be specified")
if not storage_key:
storconn = get_conn(client_type="storage")
storage_keys = storconn.storage_accounts.list_keys(
resource_group, storage_account
)
storage_keys = {v.key_name: v.value for v in storage_keys.keys}
storage_key = next(iter(storage_keys.values()))
cloud_env = _get_cloud_environment()
endpoint_suffix = cloud_env.suffixes.storage_endpoint
return BlockBlobService(
storage_account,
storage_key,
sas_token=sas_token,
endpoint_suffix=endpoint_suffix,
)
|
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] |
https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/cloud/clouds/azurearm.py#L1583-L1623
|
|
lightning-power-users/node-launcher
|
5a2a646b01803fe284fa18bee99c13c7cbf04498
|
node_launcher/node_set/lnd/lnd_client/rpc_pb2_grpc.py
|
python
|
LightningServicer.ListInvoices
|
(self, request, context)
|
* lncli: `listinvoices`
ListInvoices returns a list of all the invoices currently stored within the
database. Any active debug invoices are ignored. It has full support for
paginated responses, allowing users to query for specific invoices through
their add_index. This can be done by using either the first_index_offset or
last_index_offset fields included in the response as the index_offset of the
next request. The reversed flag is set by default in order to paginate
backwards. If you wish to paginate forwards, you must explicitly set the
flag to false. If none of the parameters are specified, then the last 100
invoices will be returned.
|
* lncli: `listinvoices`
ListInvoices returns a list of all the invoices currently stored within the
database. Any active debug invoices are ignored. It has full support for
paginated responses, allowing users to query for specific invoices through
their add_index. This can be done by using either the first_index_offset or
last_index_offset fields included in the response as the index_offset of the
next request. The reversed flag is set by default in order to paginate
backwards. If you wish to paginate forwards, you must explicitly set the
flag to false. If none of the parameters are specified, then the last 100
invoices will be returned.
|
[
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":",
"listinvoices",
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"last",
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"invoices",
"will",
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"returned",
"."
] |
def ListInvoices(self, request, context):
"""* lncli: `listinvoices`
ListInvoices returns a list of all the invoices currently stored within the
database. Any active debug invoices are ignored. It has full support for
paginated responses, allowing users to query for specific invoices through
their add_index. This can be done by using either the first_index_offset or
last_index_offset fields included in the response as the index_offset of the
next request. The reversed flag is set by default in order to paginate
backwards. If you wish to paginate forwards, you must explicitly set the
flag to false. If none of the parameters are specified, then the last 100
invoices will be returned.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
|
[
"def",
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"(",
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")",
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"NotImplementedError",
"(",
"'Method not implemented!'",
")"
] |
https://github.com/lightning-power-users/node-launcher/blob/5a2a646b01803fe284fa18bee99c13c7cbf04498/node_launcher/node_set/lnd/lnd_client/rpc_pb2_grpc.py#L610-L624
|
||
DataDog/integrations-core
|
934674b29d94b70ccc008f76ea172d0cdae05e1e
|
gitlab_runner/datadog_checks/gitlab_runner/config_models/defaults.py
|
python
|
instance_metrics
|
(field, value)
|
return get_default_field_value(field, value)
|
[] |
def instance_metrics(field, value):
return get_default_field_value(field, value)
|
[
"def",
"instance_metrics",
"(",
"field",
",",
"value",
")",
":",
"return",
"get_default_field_value",
"(",
"field",
",",
"value",
")"
] |
https://github.com/DataDog/integrations-core/blob/934674b29d94b70ccc008f76ea172d0cdae05e1e/gitlab_runner/datadog_checks/gitlab_runner/config_models/defaults.py#L149-L150
|
|||
google/apitools
|
31cad2d904f356872d2965687e84b2d87ee2cdd3
|
apitools/base/py/base_api.py
|
python
|
BaseApiService.__ConstructQueryParams
|
(self, query_params, request, global_params)
|
return query_info
|
Construct a dictionary of query parameters for this request.
|
Construct a dictionary of query parameters for this request.
|
[
"Construct",
"a",
"dictionary",
"of",
"query",
"parameters",
"for",
"this",
"request",
"."
] |
def __ConstructQueryParams(self, query_params, request, global_params):
"""Construct a dictionary of query parameters for this request."""
# First, handle the global params.
global_params = self.__CombineGlobalParams(
global_params, self.__client.global_params)
global_param_names = util.MapParamNames(
[x.name for x in self.__client.params_type.all_fields()],
self.__client.params_type)
global_params_type = type(global_params)
query_info = dict(
(param,
self.__FinalUrlValue(getattr(global_params, param),
getattr(global_params_type, param)))
for param in global_param_names)
# Next, add the query params.
query_param_names = util.MapParamNames(query_params, type(request))
request_type = type(request)
query_info.update(
(param,
self.__FinalUrlValue(getattr(request, param, None),
getattr(request_type, param)))
for param in query_param_names)
query_info = dict((k, v) for k, v in query_info.items()
if v is not None)
query_info = self.__EncodePrettyPrint(query_info)
query_info = util.MapRequestParams(query_info, type(request))
return query_info
|
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https://github.com/google/apitools/blob/31cad2d904f356872d2965687e84b2d87ee2cdd3/apitools/base/py/base_api.py#L553-L579
|
|
andresriancho/w3af
|
cd22e5252243a87aaa6d0ddea47cf58dacfe00a9
|
w3af/core/ui/gui/confpanel.py
|
python
|
OnlyOptions._changedAnyWidget
|
(self, like_initial)
|
Adjust the save/revert buttons and alert the tree of the change.
:param like_initial: if the widgets are modified or not.
It only will be called if any widget changed its state, through
a propagation buffer.
|
Adjust the save/revert buttons and alert the tree of the change.
|
[
"Adjust",
"the",
"save",
"/",
"revert",
"buttons",
"and",
"alert",
"the",
"tree",
"of",
"the",
"change",
"."
] |
def _changedAnyWidget(self, like_initial):
"""Adjust the save/revert buttons and alert the tree of the change.
:param like_initial: if the widgets are modified or not.
It only will be called if any widget changed its state, through
a propagation buffer.
"""
self.save_btn.set_sensitive(not like_initial)
self.rvrt_btn.set_sensitive(not like_initial)
self.parentwidg.config_changed(like_initial)
self.saved_successfully = False
|
[
"def",
"_changedAnyWidget",
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"self",
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"parentwidg",
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"config_changed",
"(",
"like_initial",
")",
"self",
".",
"saved_successfully",
"=",
"False"
] |
https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/core/ui/gui/confpanel.py#L158-L169
|
||
gbeced/pyalgotrade
|
ad2bcc6b25c06c66eee4a8d522ce844504d8ec62
|
pyalgotrade/tools/quandl.py
|
python
|
download_daily_bars
|
(sourceCode, tableCode, year, csvFile, authToken=None)
|
Download daily bars from Quandl for a given year.
:param sourceCode: The dataset's source code.
:type sourceCode: string.
:param tableCode: The dataset's table code.
:type tableCode: string.
:param year: The year.
:type year: int.
:param csvFile: The path to the CSV file to write.
:type csvFile: string.
:param authToken: Optional. An authentication token needed if you're doing more than 50 calls per day.
:type authToken: string.
|
Download daily bars from Quandl for a given year.
|
[
"Download",
"daily",
"bars",
"from",
"Quandl",
"for",
"a",
"given",
"year",
"."
] |
def download_daily_bars(sourceCode, tableCode, year, csvFile, authToken=None):
"""Download daily bars from Quandl for a given year.
:param sourceCode: The dataset's source code.
:type sourceCode: string.
:param tableCode: The dataset's table code.
:type tableCode: string.
:param year: The year.
:type year: int.
:param csvFile: The path to the CSV file to write.
:type csvFile: string.
:param authToken: Optional. An authentication token needed if you're doing more than 50 calls per day.
:type authToken: string.
"""
bars = download_csv(sourceCode, tableCode, datetime.date(year, 1, 1), datetime.date(year, 12, 31), "daily", authToken)
f = open(csvFile, "w")
f.write(bars)
f.close()
|
[
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"csvFile",
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"(",
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https://github.com/gbeced/pyalgotrade/blob/ad2bcc6b25c06c66eee4a8d522ce844504d8ec62/pyalgotrade/tools/quandl.py#L49-L67
|
||
mypaint/mypaint
|
90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33
|
gui/cursor.py
|
python
|
CustomCursorMaker._get_overlay_cursor
|
(self, icon_pixbuf, cursor_name=Name.ARROW)
|
return cursor
|
Returns an overlay cursor. Not cached.
:param icon_pixbuf: a GdkPixbuf.Pixbuf containing a small (~22px)
image, or None
:param cursor_name: name of a pixmaps/ cursor image to use for the
pointer part, minus the .png
The overlay icon will be overlaid to the bottom and right of the
returned cursor image.
|
Returns an overlay cursor. Not cached.
|
[
"Returns",
"an",
"overlay",
"cursor",
".",
"Not",
"cached",
"."
] |
def _get_overlay_cursor(self, icon_pixbuf, cursor_name=Name.ARROW):
"""Returns an overlay cursor. Not cached.
:param icon_pixbuf: a GdkPixbuf.Pixbuf containing a small (~22px)
image, or None
:param cursor_name: name of a pixmaps/ cursor image to use for the
pointer part, minus the .png
The overlay icon will be overlaid to the bottom and right of the
returned cursor image.
"""
pointer_pixbuf = getattr(self.app.pixmaps, cursor_name)
pointer_w = pointer_pixbuf.get_width()
pointer_h = pointer_pixbuf.get_height()
hot_x, hot_y = self.CURSOR_HOTSPOTS.get(cursor_name, (None, None))
if hot_x is None:
hot_x = 1
hot_y = 1
cursor_pixbuf = GdkPixbuf.Pixbuf.new(GdkPixbuf.Colorspace.RGB, True,
8, 32, 32)
cursor_pixbuf.fill(0x00000000)
pointer_pixbuf.composite(
cursor_pixbuf, 0, 0, pointer_w, pointer_h, 0, 0, 1, 1,
GdkPixbuf.InterpType.NEAREST, 255
)
if icon_pixbuf is not None:
icon_w = icon_pixbuf.get_width()
icon_h = icon_pixbuf.get_height()
icon_x = 32 - icon_w
icon_y = 32 - icon_h
icon_pixbuf.composite(
cursor_pixbuf, icon_x, icon_y, icon_w, icon_h,
icon_x, icon_y, 1, 1, GdkPixbuf.InterpType.NEAREST, 255
)
display = self.app.drawWindow.get_display()
cursor = Gdk.Cursor.new_from_pixbuf(display, cursor_pixbuf,
hot_x, hot_y)
return cursor
|
[
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] |
https://github.com/mypaint/mypaint/blob/90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33/gui/cursor.py#L313-L355
|
|
pyparallel/pyparallel
|
11e8c6072d48c8f13641925d17b147bf36ee0ba3
|
Lib/distutils/command/install.py
|
python
|
install.handle_extra_path
|
(self)
|
Set `path_file` and `extra_dirs` using `extra_path`.
|
Set `path_file` and `extra_dirs` using `extra_path`.
|
[
"Set",
"path_file",
"and",
"extra_dirs",
"using",
"extra_path",
"."
] |
def handle_extra_path(self):
"""Set `path_file` and `extra_dirs` using `extra_path`."""
if self.extra_path is None:
self.extra_path = self.distribution.extra_path
if self.extra_path is not None:
if isinstance(self.extra_path, str):
self.extra_path = self.extra_path.split(',')
if len(self.extra_path) == 1:
path_file = extra_dirs = self.extra_path[0]
elif len(self.extra_path) == 2:
path_file, extra_dirs = self.extra_path
else:
raise DistutilsOptionError(
"'extra_path' option must be a list, tuple, or "
"comma-separated string with 1 or 2 elements")
# convert to local form in case Unix notation used (as it
# should be in setup scripts)
extra_dirs = convert_path(extra_dirs)
else:
path_file = None
extra_dirs = ''
# XXX should we warn if path_file and not extra_dirs? (in which
# case the path file would be harmless but pointless)
self.path_file = path_file
self.extra_dirs = extra_dirs
|
[
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"path_file",
"=",
"path_file",
"self",
".",
"extra_dirs",
"=",
"extra_dirs"
] |
https://github.com/pyparallel/pyparallel/blob/11e8c6072d48c8f13641925d17b147bf36ee0ba3/Lib/distutils/command/install.py#L517-L545
|
||
dimagi/commcare-hq
|
d67ff1d3b4c51fa050c19e60c3253a79d3452a39
|
corehq/apps/reports/filters/select.py
|
python
|
SelectOpenCloseFilter.options
|
(self)
|
return [
('open', _("Only Open")),
('closed', _("Only Closed")),
]
|
[] |
def options(self):
return [
('open', _("Only Open")),
('closed', _("Only Closed")),
]
|
[
"def",
"options",
"(",
"self",
")",
":",
"return",
"[",
"(",
"'open'",
",",
"_",
"(",
"\"Only Open\"",
")",
")",
",",
"(",
"'closed'",
",",
"_",
"(",
"\"Only Closed\"",
")",
")",
",",
"]"
] |
https://github.com/dimagi/commcare-hq/blob/d67ff1d3b4c51fa050c19e60c3253a79d3452a39/corehq/apps/reports/filters/select.py#L95-L99
|
|||
aertslab/pySCENIC
|
c66455cdc0d736d67963b218a8ebce61dc4eef82
|
src/pyscenic/rss.py
|
python
|
regulon_specificity_scores
|
(auc_mtx, cell_type_series)
|
return pd.DataFrame(data=rss_values, index=cell_types, columns=regulons)
|
Calculates the Regulon Specificty Scores (RSS). [doi: 10.1016/j.celrep.2018.10.045]
:param auc_mtx: The dataframe with the AUC values for all cells and regulons (n_cells x n_regulons).
:param cell_type_series: A pandas Series object with cell identifiers as index and cell type labels as values.
:return: A pandas dataframe with the RSS values (cell type x regulon).
|
Calculates the Regulon Specificty Scores (RSS). [doi: 10.1016/j.celrep.2018.10.045]
|
[
"Calculates",
"the",
"Regulon",
"Specificty",
"Scores",
"(",
"RSS",
")",
".",
"[",
"doi",
":",
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".",
"1016",
"/",
"j",
".",
"celrep",
".",
"2018",
".",
"10",
".",
"045",
"]"
] |
def regulon_specificity_scores(auc_mtx, cell_type_series):
"""
Calculates the Regulon Specificty Scores (RSS). [doi: 10.1016/j.celrep.2018.10.045]
:param auc_mtx: The dataframe with the AUC values for all cells and regulons (n_cells x n_regulons).
:param cell_type_series: A pandas Series object with cell identifiers as index and cell type labels as values.
:return: A pandas dataframe with the RSS values (cell type x regulon).
"""
cell_types = list(cell_type_series.unique())
n_types = len(cell_types)
regulons = list(auc_mtx.columns)
n_regulons = len(regulons)
rss_values = np.empty(shape=(n_types, n_regulons), dtype=np.float)
def rss(aucs, labels):
# jensenshannon function provides distance which is the sqrt of the JS divergence.
return 1.0 - jensenshannon(aucs / aucs.sum(), labels / labels.sum())
for cidx, regulon_name in enumerate(regulons):
for ridx, cell_type in enumerate(cell_types):
rss_values[ridx, cidx] = rss(auc_mtx[regulon_name], (cell_type_series == cell_type).astype(int))
return pd.DataFrame(data=rss_values, index=cell_types, columns=regulons)
|
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https://github.com/aertslab/pySCENIC/blob/c66455cdc0d736d67963b218a8ebce61dc4eef82/src/pyscenic/rss.py#L8-L31
|
|
edisonlz/fastor
|
342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3
|
base/site-packages/tencentcloud/partners/v20180321/models.py
|
python
|
DescribeAgentBillsResponse.__init__
|
(self)
|
:param TotalCount: 符合查询条件列表总数量
:type TotalCount: int
:param AgentBillSet: 业务明细列表
:type AgentBillSet: list of AgentBillElem
:param RequestId: 唯一请求ID，每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str
|
:param TotalCount: 符合查询条件列表总数量
:type TotalCount: int
:param AgentBillSet: 业务明细列表
:type AgentBillSet: list of AgentBillElem
:param RequestId: 唯一请求ID，每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str
|
[
":",
"param",
"TotalCount",
":",
"符合查询条件列表总数量",
":",
"type",
"TotalCount",
":",
"int",
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":",
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":",
"type",
"RequestId",
":",
"str"
] |
def __init__(self):
"""
:param TotalCount: 符合查询条件列表总数量
:type TotalCount: int
:param AgentBillSet: 业务明细列表
:type AgentBillSet: list of AgentBillElem
:param RequestId: 唯一请求ID，每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str
"""
self.TotalCount = None
self.AgentBillSet = None
self.RequestId = None
|
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https://github.com/edisonlz/fastor/blob/342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3/base/site-packages/tencentcloud/partners/v20180321/models.py#L217-L228
|
||
PokemonGoF/PokemonGo-Bot-Desktop
|
4bfa94f0183406c6a86f93645eff7abd3ad4ced8
|
build/pywin/Lib/decimal.py
|
python
|
Decimal._power_exact
|
(self, other, p)
|
return _dec_from_triple(0, str_xc+'0'*zeros, xe-zeros)
|
Attempt to compute self**other exactly.
Given Decimals self and other and an integer p, attempt to
compute an exact result for the power self**other, with p
digits of precision. Return None if self**other is not
exactly representable in p digits.
Assumes that elimination of special cases has already been
performed: self and other must both be nonspecial; self must
be positive and not numerically equal to 1; other must be
nonzero. For efficiency, other._exp should not be too large,
so that 10**abs(other._exp) is a feasible calculation.
|
Attempt to compute self**other exactly.
|
[
"Attempt",
"to",
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"**",
"other",
"exactly",
"."
] |
def _power_exact(self, other, p):
"""Attempt to compute self**other exactly.
Given Decimals self and other and an integer p, attempt to
compute an exact result for the power self**other, with p
digits of precision. Return None if self**other is not
exactly representable in p digits.
Assumes that elimination of special cases has already been
performed: self and other must both be nonspecial; self must
be positive and not numerically equal to 1; other must be
nonzero. For efficiency, other._exp should not be too large,
so that 10**abs(other._exp) is a feasible calculation."""
# In the comments below, we write x for the value of self and y for the
# value of other. Write x = xc*10**xe and abs(y) = yc*10**ye, with xc
# and yc positive integers not divisible by 10.
# The main purpose of this method is to identify the *failure*
# of x**y to be exactly representable with as little effort as
# possible. So we look for cheap and easy tests that
# eliminate the possibility of x**y being exact. Only if all
# these tests are passed do we go on to actually compute x**y.
# Here's the main idea. Express y as a rational number m/n, with m and
# n relatively prime and n>0. Then for x**y to be exactly
# representable (at *any* precision), xc must be the nth power of a
# positive integer and xe must be divisible by n. If y is negative
# then additionally xc must be a power of either 2 or 5, hence a power
# of 2**n or 5**n.
#
# There's a limit to how small |y| can be: if y=m/n as above
# then:
#
# (1) if xc != 1 then for the result to be representable we
# need xc**(1/n) >= 2, and hence also xc**|y| >= 2. So
# if |y| <= 1/nbits(xc) then xc < 2**nbits(xc) <=
# 2**(1/|y|), hence xc**|y| < 2 and the result is not
# representable.
#
# (2) if xe != 0, |xe|*(1/n) >= 1, so |xe|*|y| >= 1. Hence if
# |y| < 1/|xe| then the result is not representable.
#
# Note that since x is not equal to 1, at least one of (1) and
# (2) must apply. Now |y| < 1/nbits(xc) iff |yc|*nbits(xc) <
# 10**-ye iff len(str(|yc|*nbits(xc)) <= -ye.
#
# There's also a limit to how large y can be, at least if it's
# positive: the normalized result will have coefficient xc**y,
# so if it's representable then xc**y < 10**p, and y <
# p/log10(xc). Hence if y*log10(xc) >= p then the result is
# not exactly representable.
# if len(str(abs(yc*xe)) <= -ye then abs(yc*xe) < 10**-ye,
# so |y| < 1/xe and the result is not representable.
# Similarly, len(str(abs(yc)*xc_bits)) <= -ye implies |y|
# < 1/nbits(xc).
x = _WorkRep(self)
xc, xe = x.int, x.exp
while xc % 10 == 0:
xc //= 10
xe += 1
y = _WorkRep(other)
yc, ye = y.int, y.exp
while yc % 10 == 0:
yc //= 10
ye += 1
# case where xc == 1: result is 10**(xe*y), with xe*y
# required to be an integer
if xc == 1:
xe *= yc
# result is now 10**(xe * 10**ye); xe * 10**ye must be integral
while xe % 10 == 0:
xe //= 10
ye += 1
if ye < 0:
return None
exponent = xe * 10**ye
if y.sign == 1:
exponent = -exponent
# if other is a nonnegative integer, use ideal exponent
if other._isinteger() and other._sign == 0:
ideal_exponent = self._exp*int(other)
zeros = min(exponent-ideal_exponent, p-1)
else:
zeros = 0
return _dec_from_triple(0, '1' + '0'*zeros, exponent-zeros)
# case where y is negative: xc must be either a power
# of 2 or a power of 5.
if y.sign == 1:
last_digit = xc % 10
if last_digit in (2,4,6,8):
# quick test for power of 2
if xc & -xc != xc:
return None
# now xc is a power of 2; e is its exponent
e = _nbits(xc)-1
# We now have:
#
# x = 2**e * 10**xe, e > 0, and y < 0.
#
# The exact result is:
#
# x**y = 5**(-e*y) * 10**(e*y + xe*y)
#
# provided that both e*y and xe*y are integers. Note that if
# 5**(-e*y) >= 10**p, then the result can't be expressed
# exactly with p digits of precision.
#
# Using the above, we can guard against large values of ye.
# 93/65 is an upper bound for log(10)/log(5), so if
#
# ye >= len(str(93*p//65))
#
# then
#
# -e*y >= -y >= 10**ye > 93*p/65 > p*log(10)/log(5),
#
# so 5**(-e*y) >= 10**p, and the coefficient of the result
# can't be expressed in p digits.
# emax >= largest e such that 5**e < 10**p.
emax = p*93//65
if ye >= len(str(emax)):
return None
# Find -e*y and -xe*y; both must be integers
e = _decimal_lshift_exact(e * yc, ye)
xe = _decimal_lshift_exact(xe * yc, ye)
if e is None or xe is None:
return None
if e > emax:
return None
xc = 5**e
elif last_digit == 5:
# e >= log_5(xc) if xc is a power of 5; we have
# equality all the way up to xc=5**2658
e = _nbits(xc)*28//65
xc, remainder = divmod(5**e, xc)
if remainder:
return None
while xc % 5 == 0:
xc //= 5
e -= 1
# Guard against large values of ye, using the same logic as in
# the 'xc is a power of 2' branch. 10/3 is an upper bound for
# log(10)/log(2).
emax = p*10//3
if ye >= len(str(emax)):
return None
e = _decimal_lshift_exact(e * yc, ye)
xe = _decimal_lshift_exact(xe * yc, ye)
if e is None or xe is None:
return None
if e > emax:
return None
xc = 2**e
else:
return None
if xc >= 10**p:
return None
xe = -e-xe
return _dec_from_triple(0, str(xc), xe)
# now y is positive; find m and n such that y = m/n
if ye >= 0:
m, n = yc*10**ye, 1
else:
if xe != 0 and len(str(abs(yc*xe))) <= -ye:
return None
xc_bits = _nbits(xc)
if xc != 1 and len(str(abs(yc)*xc_bits)) <= -ye:
return None
m, n = yc, 10**(-ye)
while m % 2 == n % 2 == 0:
m //= 2
n //= 2
while m % 5 == n % 5 == 0:
m //= 5
n //= 5
# compute nth root of xc*10**xe
if n > 1:
# if 1 < xc < 2**n then xc isn't an nth power
if xc != 1 and xc_bits <= n:
return None
xe, rem = divmod(xe, n)
if rem != 0:
return None
# compute nth root of xc using Newton's method
a = 1L << -(-_nbits(xc)//n) # initial estimate
while True:
q, r = divmod(xc, a**(n-1))
if a <= q:
break
else:
a = (a*(n-1) + q)//n
if not (a == q and r == 0):
return None
xc = a
# now xc*10**xe is the nth root of the original xc*10**xe
# compute mth power of xc*10**xe
# if m > p*100//_log10_lb(xc) then m > p/log10(xc), hence xc**m >
# 10**p and the result is not representable.
if xc > 1 and m > p*100//_log10_lb(xc):
return None
xc = xc**m
xe *= m
if xc > 10**p:
return None
# by this point the result *is* exactly representable
# adjust the exponent to get as close as possible to the ideal
# exponent, if necessary
str_xc = str(xc)
if other._isinteger() and other._sign == 0:
ideal_exponent = self._exp*int(other)
zeros = min(xe-ideal_exponent, p-len(str_xc))
else:
zeros = 0
return _dec_from_triple(0, str_xc+'0'*zeros, xe-zeros)
|
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] |
https://github.com/PokemonGoF/PokemonGo-Bot-Desktop/blob/4bfa94f0183406c6a86f93645eff7abd3ad4ced8/build/pywin/Lib/decimal.py#L1936-L2171
|
|
saltstack/salt
|
fae5bc757ad0f1716483ce7ae180b451545c2058
|
salt/modules/kmod.py
|
python
|
_new_mods
|
(pre_mods, post_mods)
|
return post - pre
|
Return a list of the new modules, pass an lsmod dict before running
modprobe and one after modprobe has run
|
Return a list of the new modules, pass an lsmod dict before running
modprobe and one after modprobe has run
|
[
"Return",
"a",
"list",
"of",
"the",
"new",
"modules",
"pass",
"an",
"lsmod",
"dict",
"before",
"running",
"modprobe",
"and",
"one",
"after",
"modprobe",
"has",
"run"
] |
def _new_mods(pre_mods, post_mods):
"""
Return a list of the new modules, pass an lsmod dict before running
modprobe and one after modprobe has run
"""
pre = set()
post = set()
for mod in pre_mods:
pre.add(mod["module"])
for mod in post_mods:
post.add(mod["module"])
return post - pre
|
[
"def",
"_new_mods",
"(",
"pre_mods",
",",
"post_mods",
")",
":",
"pre",
"=",
"set",
"(",
")",
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"add",
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"mod",
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"\"module\"",
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"post",
".",
"add",
"(",
"mod",
"[",
"\"module\"",
"]",
")",
"return",
"post",
"-",
"pre"
] |
https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/modules/kmod.py#L22-L33
|
|
openshift/openshift-tools
|
1188778e728a6e4781acf728123e5b356380fe6f
|
openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_openshift/library/oc_objectvalidator.py
|
python
|
main
|
()
|
ansible oc module for validating OpenShift objects
|
ansible oc module for validating OpenShift objects
|
[
"ansible",
"oc",
"module",
"for",
"validating",
"OpenShift",
"objects"
] |
def main():
'''
ansible oc module for validating OpenShift objects
'''
module = AnsibleModule(
argument_spec=dict(
kubeconfig=dict(default='/etc/origin/master/admin.kubeconfig', type='str'),
),
supports_check_mode=False,
)
rval = OCObjectValidator.run_ansible(module.params)
if 'failed' in rval:
module.fail_json(**rval)
module.exit_json(**rval)
|
[
"def",
"main",
"(",
")",
":",
"module",
"=",
"AnsibleModule",
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"argument_spec",
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"dict",
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"dict",
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"default",
"=",
"'/etc/origin/master/admin.kubeconfig'",
",",
"type",
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",",
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"*",
"*",
"rval",
")",
"module",
".",
"exit_json",
"(",
"*",
"*",
"rval",
")"
] |
https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_openshift/library/oc_objectvalidator.py#L1506-L1523
|
||
qiyuangong/leetcode
|
790f9ee86dcc7bf85be1bd9358f4c069b4a4c2f5
|
python/259_3Sum_Smaller.py
|
python
|
Solution.threeSumSmaller
|
(self, nums, target)
|
return res
|
:type nums: List[int]
:type target: int
:rtype: int
|
:type nums: List[int]
:type target: int
:rtype: int
|
[
":",
"type",
"nums",
":",
"List",
"[",
"int",
"]",
":",
"type",
"target",
":",
"int",
":",
"rtype",
":",
"int"
] |
def threeSumSmaller(self, nums, target):
"""
:type nums: List[int]
:type target: int
:rtype: int
"""
# https://leetcode.com/articles/3sum-smaller/#approach-2-binary-search-accepted
nums.sort()
ls = len(nums)
res = 0
for i in range(ls - 1):
res += self.twoSumSmaller(nums, i + 1, target - nums[i])
return res
|
[
"def",
"threeSumSmaller",
"(",
"self",
",",
"nums",
",",
"target",
")",
":",
"# https://leetcode.com/articles/3sum-smaller/#approach-2-binary-search-accepted",
"nums",
".",
"sort",
"(",
")",
"ls",
"=",
"len",
"(",
"nums",
")",
"res",
"=",
"0",
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"(",
"ls",
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":",
"res",
"+=",
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"twoSumSmaller",
"(",
"nums",
",",
"i",
"+",
"1",
",",
"target",
"-",
"nums",
"[",
"i",
"]",
")",
"return",
"res"
] |
https://github.com/qiyuangong/leetcode/blob/790f9ee86dcc7bf85be1bd9358f4c069b4a4c2f5/python/259_3Sum_Smaller.py#L34-L46
|
|
oleg-yaroshevskiy/quest_qa_labeling
|
730a9632314e54584f69f909d5e2ef74d843e02c
|
packages/fairseq-hacked/fairseq/models/masked_lm.py
|
python
|
MaskedLMEncoder.max_positions
|
(self)
|
return self.max_positions
|
Maximum output length supported by the encoder.
|
Maximum output length supported by the encoder.
|
[
"Maximum",
"output",
"length",
"supported",
"by",
"the",
"encoder",
"."
] |
def max_positions(self):
"""Maximum output length supported by the encoder."""
return self.max_positions
|
[
"def",
"max_positions",
"(",
"self",
")",
":",
"return",
"self",
".",
"max_positions"
] |
https://github.com/oleg-yaroshevskiy/quest_qa_labeling/blob/730a9632314e54584f69f909d5e2ef74d843e02c/packages/fairseq-hacked/fairseq/models/masked_lm.py#L294-L296
|
|
tanghaibao/jcvi
|
5e720870c0928996f8b77a38208106ff0447ccb6
|
jcvi/graphics/base.py
|
python
|
discrete_rainbow
|
(N=7, cmap=cm.Set1, usepreset=True, shuffle=False, plot=False)
|
return mpl.colors.LinearSegmentedColormap("colormap", cdict, 1024), palette
|
Return a discrete colormap and the set of colors.
modified from
<http://www.scipy.org/Cookbook/Matplotlib/ColormapTransformations>
cmap: colormap instance, eg. cm.jet.
N: Number of colors.
Example
>>> x = resize(arange(100), (5,100))
>>> djet = cmap_discretize(cm.jet, 5)
>>> imshow(x, cmap=djet)
See available matplotlib colormaps at:
<http://dept.astro.lsa.umich.edu/~msshin/science/code/matplotlib_cm/>
If N>20 the sampled colors might not be very distinctive.
If you want to error and try anyway, set usepreset=False
|
Return a discrete colormap and the set of colors.
|
[
"Return",
"a",
"discrete",
"colormap",
"and",
"the",
"set",
"of",
"colors",
"."
] |
def discrete_rainbow(N=7, cmap=cm.Set1, usepreset=True, shuffle=False, plot=False):
"""
Return a discrete colormap and the set of colors.
modified from
<http://www.scipy.org/Cookbook/Matplotlib/ColormapTransformations>
cmap: colormap instance, eg. cm.jet.
N: Number of colors.
Example
>>> x = resize(arange(100), (5,100))
>>> djet = cmap_discretize(cm.jet, 5)
>>> imshow(x, cmap=djet)
See available matplotlib colormaps at:
<http://dept.astro.lsa.umich.edu/~msshin/science/code/matplotlib_cm/>
If N>20 the sampled colors might not be very distinctive.
If you want to error and try anyway, set usepreset=False
"""
import random
from scipy import interpolate
if usepreset:
if 0 < N <= 5:
cmap = cm.gist_rainbow
elif N <= 20:
cmap = cm.Set1
else:
sys.exit(discrete_rainbow.__doc__)
cdict = cmap._segmentdata.copy()
# N colors
colors_i = np.linspace(0, 1.0, N)
# N+1 indices
indices = np.linspace(0, 1.0, N + 1)
rgbs = []
for key in ("red", "green", "blue"):
# Find the N colors
D = np.array(cdict[key])
I = interpolate.interp1d(D[:, 0], D[:, 1])
colors = I(colors_i)
rgbs.append(colors)
# Place these colors at the correct indices.
A = np.zeros((N + 1, 3), float)
A[:, 0] = indices
A[1:, 1] = colors
A[:-1, 2] = colors
# Create a tuple for the dictionary.
L = []
for l in A:
L.append(tuple(l))
cdict[key] = tuple(L)
palette = zip(*rgbs)
if shuffle:
random.shuffle(palette)
if plot:
print_colors(palette)
# Return (colormap object, RGB tuples)
return mpl.colors.LinearSegmentedColormap("colormap", cdict, 1024), palette
|
[
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"discrete_rainbow",
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"=",
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",",
"cmap",
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"True",
",",
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",",
"cdict",
",",
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",",
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] |
https://github.com/tanghaibao/jcvi/blob/5e720870c0928996f8b77a38208106ff0447ccb6/jcvi/graphics/base.py#L474-L538
|
|
NoGameNoLife00/mybolg
|
afe17ea5bfe405e33766e5682c43a4262232ee12
|
libs/werkzeug/__init__.py
|
python
|
module.__dir__
|
(self)
|
return result
|
Just show what we want to show.
|
Just show what we want to show.
|
[
"Just",
"show",
"what",
"we",
"want",
"to",
"show",
"."
] |
def __dir__(self):
"""Just show what we want to show."""
result = list(new_module.__all__)
result.extend(('__file__', '__path__', '__doc__', '__all__',
'__docformat__', '__name__', '__path__',
'__package__', '__version__'))
return result
|
[
"def",
"__dir__",
"(",
"self",
")",
":",
"result",
"=",
"list",
"(",
"new_module",
".",
"__all__",
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"result",
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"(",
"(",
"'__file__'",
",",
"'__path__'",
",",
"'__doc__'",
",",
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",",
"'__docformat__'",
",",
"'__name__'",
",",
"'__path__'",
",",
"'__package__'",
",",
"'__version__'",
")",
")",
"return",
"result"
] |
https://github.com/NoGameNoLife00/mybolg/blob/afe17ea5bfe405e33766e5682c43a4262232ee12/libs/werkzeug/__init__.py#L127-L133
|
|
nipy/nipype
|
cd4c34d935a43812d1756482fdc4034844e485b8
|
nipype/algorithms/misc.py
|
python
|
calc_moments
|
(timeseries_file, moment)
|
return np.where(zero, 0, m3 / m2 ** (moment / 2.0))
|
Returns nth moment (3 for skewness, 4 for kurtosis) of timeseries
(list of values; one per timeseries).
Keyword arguments:
timeseries_file -- text file with white space separated timepoints in rows
|
Returns nth moment (3 for skewness, 4 for kurtosis) of timeseries
(list of values; one per timeseries).
|
[
"Returns",
"nth",
"moment",
"(",
"3",
"for",
"skewness",
"4",
"for",
"kurtosis",
")",
"of",
"timeseries",
"(",
"list",
"of",
"values",
";",
"one",
"per",
"timeseries",
")",
"."
] |
def calc_moments(timeseries_file, moment):
"""Returns nth moment (3 for skewness, 4 for kurtosis) of timeseries
(list of values; one per timeseries).
Keyword arguments:
timeseries_file -- text file with white space separated timepoints in rows
"""
import scipy.stats as stats
timeseries = np.genfromtxt(timeseries_file)
m2 = stats.moment(timeseries, 2, axis=0)
m3 = stats.moment(timeseries, moment, axis=0)
zero = m2 == 0
return np.where(zero, 0, m3 / m2 ** (moment / 2.0))
|
[
"def",
"calc_moments",
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",",
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"scipy",
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"(",
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"/",
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")"
] |
https://github.com/nipy/nipype/blob/cd4c34d935a43812d1756482fdc4034844e485b8/nipype/algorithms/misc.py#L945-L960
|
|
skylander86/lambda-text-extractor
|
6da52d077a2fc571e38bfe29c33ae68f6443cd5a
|
lib-linux_x64/odf/odf2xhtml.py
|
python
|
ODF2XHTML.s_text_s
|
(self, tag, attrs)
|
Generate a number of spaces. ODF has an element; HTML uses
We use   so we can send the output through an XML parser if we desire to
|
Generate a number of spaces. ODF has an element; HTML uses
We use   so we can send the output through an XML parser if we desire to
|
[
"Generate",
"a",
"number",
"of",
"spaces",
".",
"ODF",
"has",
"an",
"element",
";",
"HTML",
"uses",
" ",
";",
"We",
"use",
" ",
";",
"so",
"we",
"can",
"send",
"the",
"output",
"through",
"an",
"XML",
"parser",
"if",
"we",
"desire",
"to"
] |
def s_text_s(self, tag, attrs):
""" Generate a number of spaces. ODF has an element; HTML uses
We use   so we can send the output through an XML parser if we desire to
"""
c = attrs.get( (TEXTNS,'c'),"1")
for x in range(int(c)):
self.writeout(' ')
|
[
"def",
"s_text_s",
"(",
"self",
",",
"tag",
",",
"attrs",
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":",
"c",
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"attrs",
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"(",
"c",
")",
")",
":",
"self",
".",
"writeout",
"(",
"' '",
")"
] |
https://github.com/skylander86/lambda-text-extractor/blob/6da52d077a2fc571e38bfe29c33ae68f6443cd5a/lib-linux_x64/odf/odf2xhtml.py#L1381-L1387
|
||
replit-archive/empythoned
|
977ec10ced29a3541a4973dc2b59910805695752
|
dist/lib/python2.7/weakref.py
|
python
|
WeakKeyDictionary.keyrefs
|
(self)
|
return self.data.keys()
|
Return a list of weak references to the keys.
The references are not guaranteed to be 'live' at the time
they are used, so the result of calling the references needs
to be checked before being used. This can be used to avoid
creating references that will cause the garbage collector to
keep the keys around longer than needed.
|
Return a list of weak references to the keys.
|
[
"Return",
"a",
"list",
"of",
"weak",
"references",
"to",
"the",
"keys",
"."
] |
def keyrefs(self):
"""Return a list of weak references to the keys.
The references are not guaranteed to be 'live' at the time
they are used, so the result of calling the references needs
to be checked before being used. This can be used to avoid
creating references that will cause the garbage collector to
keep the keys around longer than needed.
"""
return self.data.keys()
|
[
"def",
"keyrefs",
"(",
"self",
")",
":",
"return",
"self",
".",
"data",
".",
"keys",
"(",
")"
] |
https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/dist/lib/python2.7/weakref.py#L338-L348
|
|
hyperledger/aries-cloudagent-python
|
2f36776e99f6053ae92eed8123b5b1b2e891c02a
|
aries_cloudagent/protocols/present_proof/dif/pres_exch_handler.py
|
python
|
DIFPresExchHandler.apply_constraint_received_cred
|
(
self, constraint: Constraints, cred_dict: dict
)
|
return True
|
Evaluate constraint from the request against received credential.
|
Evaluate constraint from the request against received credential.
|
[
"Evaluate",
"constraint",
"from",
"the",
"request",
"against",
"received",
"credential",
"."
] |
async def apply_constraint_received_cred(
self, constraint: Constraints, cred_dict: dict
) -> bool:
"""Evaluate constraint from the request against received credential."""
fields = constraint._fields
field_paths = []
credential = self.create_vcrecord(cred_dict)
is_limit_disclosure = constraint.limit_disclosure == "required"
for field in fields:
if is_limit_disclosure:
field = await self.get_updated_field(field, cred_dict)
if not await self.filter_by_field(field, credential):
return False
field_paths = field_paths + (
await self.restrict_field_paths_one_of_filter(
field_paths=field.paths, cred_dict=cred_dict
)
)
# Selective Disclosure check
if is_limit_disclosure:
field_paths = set([path.replace("$.", "") for path in field_paths])
mandatory_paths = {
"@context",
"type",
"issuanceDate",
"issuer",
"proof",
"credentialSubject",
"id",
}
to_remove_from_field_paths = set()
nested_field_paths = {"credentialSubject": {"id", "type"}}
for field_path in field_paths:
if field_path.count(".") >= 1:
split_field_path = field_path.split(".")
key = ".".join(split_field_path[:-1])
value = split_field_path[-1]
nested_field_paths = self.build_nested_paths_dict(
key, value, nested_field_paths, cred_dict
)
to_remove_from_field_paths.add(field_path)
for to_remove_path in to_remove_from_field_paths:
field_paths.remove(to_remove_path)
field_paths = set.union(mandatory_paths, field_paths)
for attrs in cred_dict.keys():
if attrs not in field_paths:
return False
for nested_attr_key in nested_field_paths:
nested_attr_values = nested_field_paths[nested_attr_key]
extracted = self.nested_get(cred_dict, nested_attr_key)
if isinstance(extracted, dict):
if not self.check_attr_in_extracted_dict(
extracted, nested_attr_values
):
return False
elif isinstance(extracted, list):
for extracted_dict in extracted:
if not self.check_attr_in_extracted_dict(
extracted_dict, nested_attr_values
):
return False
return True
|
[
"async",
"def",
"apply_constraint_received_cred",
"(",
"self",
",",
"constraint",
":",
"Constraints",
",",
"cred_dict",
":",
"dict",
")",
"->",
"bool",
":",
"fields",
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"constraint",
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"_fields",
"field_paths",
"=",
"[",
"]",
"credential",
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"self",
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"create_vcrecord",
"(",
"cred_dict",
")",
"is_limit_disclosure",
"=",
"constraint",
".",
"limit_disclosure",
"==",
"\"required\"",
"for",
"field",
"in",
"fields",
":",
"if",
"is_limit_disclosure",
":",
"field",
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"await",
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"get_updated_field",
"(",
"field",
",",
"cred_dict",
")",
"if",
"not",
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"self",
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"filter_by_field",
"(",
"field",
",",
"credential",
")",
":",
"return",
"False",
"field_paths",
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"field_paths",
"+",
"(",
"await",
"self",
".",
"restrict_field_paths_one_of_filter",
"(",
"field_paths",
"=",
"field",
".",
"paths",
",",
"cred_dict",
"=",
"cred_dict",
")",
")",
"# Selective Disclosure check",
"if",
"is_limit_disclosure",
":",
"field_paths",
"=",
"set",
"(",
"[",
"path",
".",
"replace",
"(",
"\"$.\"",
",",
"\"\"",
")",
"for",
"path",
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"field_paths",
"]",
")",
"mandatory_paths",
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"{",
"\"@context\"",
",",
"\"type\"",
",",
"\"issuanceDate\"",
",",
"\"issuer\"",
",",
"\"proof\"",
",",
"\"credentialSubject\"",
",",
"\"id\"",
",",
"}",
"to_remove_from_field_paths",
"=",
"set",
"(",
")",
"nested_field_paths",
"=",
"{",
"\"credentialSubject\"",
":",
"{",
"\"id\"",
",",
"\"type\"",
"}",
"}",
"for",
"field_path",
"in",
"field_paths",
":",
"if",
"field_path",
".",
"count",
"(",
"\".\"",
")",
">=",
"1",
":",
"split_field_path",
"=",
"field_path",
".",
"split",
"(",
"\".\"",
")",
"key",
"=",
"\".\"",
".",
"join",
"(",
"split_field_path",
"[",
":",
"-",
"1",
"]",
")",
"value",
"=",
"split_field_path",
"[",
"-",
"1",
"]",
"nested_field_paths",
"=",
"self",
".",
"build_nested_paths_dict",
"(",
"key",
",",
"value",
",",
"nested_field_paths",
",",
"cred_dict",
")",
"to_remove_from_field_paths",
".",
"add",
"(",
"field_path",
")",
"for",
"to_remove_path",
"in",
"to_remove_from_field_paths",
":",
"field_paths",
".",
"remove",
"(",
"to_remove_path",
")",
"field_paths",
"=",
"set",
".",
"union",
"(",
"mandatory_paths",
",",
"field_paths",
")",
"for",
"attrs",
"in",
"cred_dict",
".",
"keys",
"(",
")",
":",
"if",
"attrs",
"not",
"in",
"field_paths",
":",
"return",
"False",
"for",
"nested_attr_key",
"in",
"nested_field_paths",
":",
"nested_attr_values",
"=",
"nested_field_paths",
"[",
"nested_attr_key",
"]",
"extracted",
"=",
"self",
".",
"nested_get",
"(",
"cred_dict",
",",
"nested_attr_key",
")",
"if",
"isinstance",
"(",
"extracted",
",",
"dict",
")",
":",
"if",
"not",
"self",
".",
"check_attr_in_extracted_dict",
"(",
"extracted",
",",
"nested_attr_values",
")",
":",
"return",
"False",
"elif",
"isinstance",
"(",
"extracted",
",",
"list",
")",
":",
"for",
"extracted_dict",
"in",
"extracted",
":",
"if",
"not",
"self",
".",
"check_attr_in_extracted_dict",
"(",
"extracted_dict",
",",
"nested_attr_values",
")",
":",
"return",
"False",
"return",
"True"
] |
https://github.com/hyperledger/aries-cloudagent-python/blob/2f36776e99f6053ae92eed8123b5b1b2e891c02a/aries_cloudagent/protocols/present_proof/dif/pres_exch_handler.py#L1410-L1473
|
|
TensorMSA/tensormsa
|
c36b565159cd934533636429add3c7d7263d622b
|
cluster/common/common_node.py
|
python
|
WorkFlowCommonNode.set_net_id
|
(self, net_id)
|
set flag for tree search
:return:
|
set flag for tree search
:return:
|
[
"set",
"flag",
"for",
"tree",
"search",
":",
"return",
":"
] |
def set_net_id(self, net_id):
"""
set flag for tree search
:return:
"""
self.net_id = net_id
|
[
"def",
"set_net_id",
"(",
"self",
",",
"net_id",
")",
":",
"self",
".",
"net_id",
"=",
"net_id"
] |
https://github.com/TensorMSA/tensormsa/blob/c36b565159cd934533636429add3c7d7263d622b/cluster/common/common_node.py#L66-L71
|
||
CedricGuillemet/Imogen
|
ee417b42747ed5b46cb11b02ef0c3630000085b3
|
bin/Lib/asyncio/base_events.py
|
python
|
BaseEventLoop.run_until_complete
|
(self, future)
|
return future.result()
|
Run until the Future is done.
If the argument is a coroutine, it is wrapped in a Task.
WARNING: It would be disastrous to call run_until_complete()
with the same coroutine twice -- it would wrap it in two
different Tasks and that can't be good.
Return the Future's result, or raise its exception.
|
Run until the Future is done.
|
[
"Run",
"until",
"the",
"Future",
"is",
"done",
"."
] |
def run_until_complete(self, future):
"""Run until the Future is done.
If the argument is a coroutine, it is wrapped in a Task.
WARNING: It would be disastrous to call run_until_complete()
with the same coroutine twice -- it would wrap it in two
different Tasks and that can't be good.
Return the Future's result, or raise its exception.
"""
self._check_closed()
new_task = not futures.isfuture(future)
future = tasks.ensure_future(future, loop=self)
if new_task:
# An exception is raised if the future didn't complete, so there
# is no need to log the "destroy pending task" message
future._log_destroy_pending = False
future.add_done_callback(_run_until_complete_cb)
try:
self.run_forever()
except:
if new_task and future.done() and not future.cancelled():
# The coroutine raised a BaseException. Consume the exception
# to not log a warning, the caller doesn't have access to the
# local task.
future.exception()
raise
finally:
future.remove_done_callback(_run_until_complete_cb)
if not future.done():
raise RuntimeError('Event loop stopped before Future completed.')
return future.result()
|
[
"def",
"run_until_complete",
"(",
"self",
",",
"future",
")",
":",
"self",
".",
"_check_closed",
"(",
")",
"new_task",
"=",
"not",
"futures",
".",
"isfuture",
"(",
"future",
")",
"future",
"=",
"tasks",
".",
"ensure_future",
"(",
"future",
",",
"loop",
"=",
"self",
")",
"if",
"new_task",
":",
"# An exception is raised if the future didn't complete, so there",
"# is no need to log the \"destroy pending task\" message",
"future",
".",
"_log_destroy_pending",
"=",
"False",
"future",
".",
"add_done_callback",
"(",
"_run_until_complete_cb",
")",
"try",
":",
"self",
".",
"run_forever",
"(",
")",
"except",
":",
"if",
"new_task",
"and",
"future",
".",
"done",
"(",
")",
"and",
"not",
"future",
".",
"cancelled",
"(",
")",
":",
"# The coroutine raised a BaseException. Consume the exception",
"# to not log a warning, the caller doesn't have access to the",
"# local task.",
"future",
".",
"exception",
"(",
")",
"raise",
"finally",
":",
"future",
".",
"remove_done_callback",
"(",
"_run_until_complete_cb",
")",
"if",
"not",
"future",
".",
"done",
"(",
")",
":",
"raise",
"RuntimeError",
"(",
"'Event loop stopped before Future completed.'",
")",
"return",
"future",
".",
"result",
"(",
")"
] |
https://github.com/CedricGuillemet/Imogen/blob/ee417b42747ed5b46cb11b02ef0c3630000085b3/bin/Lib/asyncio/base_events.py#L538-L573
|
|
keiffster/program-y
|
8c99b56f8c32f01a7b9887b5daae9465619d0385
|
src/programy/clients/args.py
|
python
|
ClientArguments.noloop
|
(self)
|
return self._no_loop
|
[] |
def noloop(self):
return self._no_loop
|
[
"def",
"noloop",
"(",
"self",
")",
":",
"return",
"self",
".",
"_no_loop"
] |
https://github.com/keiffster/program-y/blob/8c99b56f8c32f01a7b9887b5daae9465619d0385/src/programy/clients/args.py#L58-L59
|
|||
avocado-framework/avocado
|
1f9b3192e8ba47d029c33fe21266bd113d17811f
|
avocado/utils/softwareraid.py
|
python
|
SoftwareRaid.is_recovering
|
(self)
|
return False
|
Checks if raid is recovering.
:return: True if recovering, False otherwise.
:rtype: bool
|
Checks if raid is recovering.
|
[
"Checks",
"if",
"raid",
"is",
"recovering",
"."
] |
def is_recovering(self):
"""
Checks if raid is recovering.
:return: True if recovering, False otherwise.
:rtype: bool
"""
LOG.debug("RECOVERY")
for line in self.get_detail().splitlines():
if 'State' in line and 'recovering' in line:
return True
return False
|
[
"def",
"is_recovering",
"(",
"self",
")",
":",
"LOG",
".",
"debug",
"(",
"\"RECOVERY\"",
")",
"for",
"line",
"in",
"self",
".",
"get_detail",
"(",
")",
".",
"splitlines",
"(",
")",
":",
"if",
"'State'",
"in",
"line",
"and",
"'recovering'",
"in",
"line",
":",
"return",
"True",
"return",
"False"
] |
https://github.com/avocado-framework/avocado/blob/1f9b3192e8ba47d029c33fe21266bd113d17811f/avocado/utils/softwareraid.py#L134-L145
|
|
linxid/Machine_Learning_Study_Path
|
558e82d13237114bbb8152483977806fc0c222af
|
Machine Learning In Action/Chapter8-Regression/venv/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/distlib/version.py
|
python
|
NormalizedVersion.is_prerelease
|
(self)
|
return any(t[0] in self.PREREL_TAGS for t in self._parts if t)
|
[] |
def is_prerelease(self):
return any(t[0] in self.PREREL_TAGS for t in self._parts if t)
|
[
"def",
"is_prerelease",
"(",
"self",
")",
":",
"return",
"any",
"(",
"t",
"[",
"0",
"]",
"in",
"self",
".",
"PREREL_TAGS",
"for",
"t",
"in",
"self",
".",
"_parts",
"if",
"t",
")"
] |
https://github.com/linxid/Machine_Learning_Study_Path/blob/558e82d13237114bbb8152483977806fc0c222af/Machine Learning In Action/Chapter8-Regression/venv/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/distlib/version.py#L286-L287
|
|||
SteveDoyle2/pyNastran
|
eda651ac2d4883d95a34951f8a002ff94f642a1a
|
pyNastran/dev/bdf_vectorized/bdf_interface2/add_card.py
|
python
|
AddCard._add_bset_object
|
(self, set_obj)
|
adds an BSET/BSET1 object
|
adds an BSET/BSET1 object
|
[
"adds",
"an",
"BSET",
"/",
"BSET1",
"object"
] |
def _add_bset_object(self, set_obj):
"""adds an BSET/BSET1 object"""
self.bsets.append(set_obj)
|
[
"def",
"_add_bset_object",
"(",
"self",
",",
"set_obj",
")",
":",
"self",
".",
"bsets",
".",
"append",
"(",
"set_obj",
")"
] |
https://github.com/SteveDoyle2/pyNastran/blob/eda651ac2d4883d95a34951f8a002ff94f642a1a/pyNastran/dev/bdf_vectorized/bdf_interface2/add_card.py#L454-L456
|
||
pallets/werkzeug
|
9efe8c00dcb2b6fc086961ba304729db01912652
|
examples/shorty/utils.py
|
python
|
Pagination.pages
|
(self)
|
return max(0, self.count - 1) // self.per_page + 1
|
Return the number of pages.
|
Return the number of pages.
|
[
"Return",
"the",
"number",
"of",
"pages",
"."
] |
def pages(self):
"""Return the number of pages."""
return max(0, self.count - 1) // self.per_page + 1
|
[
"def",
"pages",
"(",
"self",
")",
":",
"return",
"max",
"(",
"0",
",",
"self",
".",
"count",
"-",
"1",
")",
"//",
"self",
".",
"per_page",
"+",
"1"
] |
https://github.com/pallets/werkzeug/blob/9efe8c00dcb2b6fc086961ba304729db01912652/examples/shorty/utils.py#L109-L111
|
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