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microsoft/debugpy | be8dd607f6837244e0b565345e497aff7a0c08bf | src/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/process.py | python | Process.search | (self, pattern, minAddr = None, maxAddr = None) | Search for the given pattern within the process memory.
@type pattern: str, compat.unicode or L{Pattern}
@param pattern: Pattern to search for.
It may be a byte string, a Unicode string, or an instance of
L{Pattern}.
The following L{Pattern} subclasses are provided by WinAppDbg:
- L{BytePattern}
- L{TextPattern}
- L{RegExpPattern}
- L{HexPattern}
You can also write your own subclass of L{Pattern} for customized
searches.
@type minAddr: int
@param minAddr: (Optional) Start the search at this memory address.
@type maxAddr: int
@param maxAddr: (Optional) Stop the search at this memory address.
@rtype: iterator of tuple( int, int, str )
@return: An iterator of tuples. Each tuple contains the following:
- The memory address where the pattern was found.
- The size of the data that matches the pattern.
- The data that matches the pattern.
@raise WindowsError: An error occurred when querying or reading the
process memory. | Search for the given pattern within the process memory. | [
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"""
Search for the given pattern within the process memory.
@type pattern: str, compat.unicode or L{Pattern}
@param pattern: Pattern to search for.
It may be a byte string, a Unicode string, or an instance of
L{Pattern}.
The following L{Pattern} subclasses are provided by WinAppDbg:
- L{BytePattern}
- L{TextPattern}
- L{RegExpPattern}
- L{HexPattern}
You can also write your own subclass of L{Pattern} for customized
searches.
@type minAddr: int
@param minAddr: (Optional) Start the search at this memory address.
@type maxAddr: int
@param maxAddr: (Optional) Stop the search at this memory address.
@rtype: iterator of tuple( int, int, str )
@return: An iterator of tuples. Each tuple contains the following:
- The memory address where the pattern was found.
- The size of the data that matches the pattern.
- The data that matches the pattern.
@raise WindowsError: An error occurred when querying or reading the
process memory.
"""
if isinstance(pattern, str):
return self.search_bytes(pattern, minAddr, maxAddr)
if isinstance(pattern, compat.unicode):
return self.search_bytes(pattern.encode("utf-16le"),
minAddr, maxAddr)
if isinstance(pattern, Pattern):
return Search.search_process(self, pattern, minAddr, maxAddr)
raise TypeError("Unknown pattern type: %r" % type(pattern)) | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/lib-tk/turtle.py | python | TurtleScreen.delay | (self, delay=None) | Return or set the drawing delay in milliseconds.
Optional argument:
delay -- positive integer
Example (for a TurtleScreen instance named screen):
>>> screen.delay(15)
>>> screen.delay()
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""" Return or set the drawing delay in milliseconds.
Optional argument:
delay -- positive integer
Example (for a TurtleScreen instance named screen):
>>> screen.delay(15)
>>> screen.delay()
15
"""
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capitalone/datacompy | 8418a5c55fa7648764c0bca87931cf778dc19d48 | datacompy/core.py | python | Compare._dataframe_merge | (self, ignore_spaces) | Merge df1 to df2 on the join columns, to get df1 - df2, df2 - df1
and df1 & df2
If ``on_index`` is True, this will join on index values, otherwise it
will join on the ``join_columns``. | Merge df1 to df2 on the join columns, to get df1 - df2, df2 - df1
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"""Merge df1 to df2 on the join columns, to get df1 - df2, df2 - df1
and df1 & df2
If ``on_index`` is True, this will join on index values, otherwise it
will join on the ``join_columns``.
"""
LOG.debug("Outer joining")
if self._any_dupes:
LOG.debug("Duplicate rows found, deduping by order of remaining fields")
# Bring index into a column
if self.on_index:
index_column = temp_column_name(self.df1, self.df2)
self.df1[index_column] = self.df1.index
self.df2[index_column] = self.df2.index
temp_join_columns = [index_column]
else:
temp_join_columns = list(self.join_columns)
# Create order column for uniqueness of match
order_column = temp_column_name(self.df1, self.df2)
self.df1[order_column] = generate_id_within_group(
self.df1, temp_join_columns
)
self.df2[order_column] = generate_id_within_group(
self.df2, temp_join_columns
)
temp_join_columns.append(order_column)
params = {"on": temp_join_columns}
elif self.on_index:
params = {"left_index": True, "right_index": True}
else:
params = {"on": self.join_columns}
if ignore_spaces:
for column in self.join_columns:
if self.df1[column].dtype.kind == "O":
self.df1[column] = self.df1[column].str.strip()
if self.df2[column].dtype.kind == "O":
self.df2[column] = self.df2[column].str.strip()
outer_join = self.df1.merge(
self.df2, how="outer", suffixes=("_df1", "_df2"), indicator=True, **params
)
# Clean up temp columns for duplicate row matching
if self._any_dupes:
if self.on_index:
outer_join.index = outer_join[index_column]
outer_join.drop(index_column, axis=1, inplace=True)
self.df1.drop(index_column, axis=1, inplace=True)
self.df2.drop(index_column, axis=1, inplace=True)
outer_join.drop(order_column, axis=1, inplace=True)
self.df1.drop(order_column, axis=1, inplace=True)
self.df2.drop(order_column, axis=1, inplace=True)
df1_cols = get_merged_columns(self.df1, outer_join, "_df1")
df2_cols = get_merged_columns(self.df2, outer_join, "_df2")
LOG.debug("Selecting df1 unique rows")
self.df1_unq_rows = outer_join[outer_join["_merge"] == "left_only"][
df1_cols
].copy()
self.df1_unq_rows.columns = self.df1.columns
LOG.debug("Selecting df2 unique rows")
self.df2_unq_rows = outer_join[outer_join["_merge"] == "right_only"][
df2_cols
].copy()
self.df2_unq_rows.columns = self.df2.columns
LOG.info(
"Number of rows in df1 and not in df2: {}".format(len(self.df1_unq_rows))
)
LOG.info(
"Number of rows in df2 and not in df1: {}".format(len(self.df2_unq_rows))
)
LOG.debug("Selecting intersecting rows")
self.intersect_rows = outer_join[outer_join["_merge"] == "both"].copy()
LOG.info(
"Number of rows in df1 and df2 (not necessarily equal): {}".format(
len(self.intersect_rows)
)
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ChineseGLUE/ChineseGLUE | 1591b85cf5427c2ff60f718d359ecb71d2b44879 | baselines/models/albert/modeling.py | python | assert_rank | (tensor, expected_rank, name=None) | Raises an exception if the tensor rank is not of the expected rank.
Args:
tensor: A tf.Tensor to check the rank of.
expected_rank: Python integer or list of integers, expected rank.
name: Optional name of the tensor for the error message.
Raises:
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"""Raises an exception if the tensor rank is not of the expected rank.
Args:
tensor: A tf.Tensor to check the rank of.
expected_rank: Python integer or list of integers, expected rank.
name: Optional name of the tensor for the error message.
Raises:
ValueError: If the expected shape doesn't match the actual shape.
"""
if name is None:
name = tensor.name
expected_rank_dict = {}
if isinstance(expected_rank, six.integer_types):
expected_rank_dict[expected_rank] = True
else:
for x in expected_rank:
expected_rank_dict[x] = True
actual_rank = tensor.shape.ndims
if actual_rank not in expected_rank_dict:
scope_name = tf.get_variable_scope().name
raise ValueError(
"For the tensor `%s` in scope `%s`, the actual rank "
"`%d` (shape = %s) is not equal to the expected rank `%s`" %
(name, scope_name, actual_rank, str(tensor.shape), str(expected_rank))) | [
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/IronPython/27/Lib/threading.py | python | Semaphore | (*args, **kwargs) | return _Semaphore(*args, **kwargs) | A factory function that returns a new semaphore.
Semaphores manage a counter representing the number of release() calls minus
the number of acquire() calls, plus an initial value. The acquire() method
blocks if necessary until it can return without making the counter
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"""A factory function that returns a new semaphore.
Semaphores manage a counter representing the number of release() calls minus
the number of acquire() calls, plus an initial value. The acquire() method
blocks if necessary until it can return without making the counter
negative. If not given, value defaults to 1.
"""
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py2neo-org/py2neo | 2e46bbf4d622f53282e796ffc521fc4bc6d0b60d | py2neo/client/__init__.py | python | ConnectionPool._connect | (self) | return cx | Open and return a new connection. | Open and return a new connection. | [
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""" Open and return a new connection.
"""
cx = Connection.open(self.profile, user_agent=self.user_agent,
on_release=lambda c: self.release(c),
on_broken=lambda msg: self.__on_broken(msg))
self._server_agent = cx.server_agent
return cx | [
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tomoncle/Python-notes | ce675486290c3d1c7c2e4890b57e3d0c8a1228cc | crawlers/spider/downloader.py | python | HtmlDownloader.download | (self, url, retry=-1) | return content if code == 200 else '' | :param url:
:param retry: 失败重试
:return: | :param url:
:param retry: 失败重试
:return: | [
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"""
:param url:
:param retry: 失败重试
:return:
"""
code, content = self._request(url)
if retry > 0 and code != 200:
self.download(url, retry - 1)
return content if code == 200 else '' | [
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/importlib/_bootstrap_external.py | python | _path_join | (*path_parts) | return path_sep.join([part.rstrip(path_separators)
for part in path_parts if part]) | Replacement for os.path.join(). | Replacement for os.path.join(). | [
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] | def _path_join(*path_parts):
"""Replacement for os.path.join()."""
return path_sep.join([part.rstrip(path_separators)
for part in path_parts if part]) | [
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Bitmessage/PyBitmessage | 97612b049e0453867d6d90aa628f8e7b007b4d85 | src/shared.py | python | reloadBroadcastSendersForWhichImWatching | () | Reinitialize runtime data for the broadcasts I'm subscribed to
from the config file | Reinitialize runtime data for the broadcasts I'm subscribed to
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"""
Reinitialize runtime data for the broadcasts I'm subscribed to
from the config file
"""
broadcastSendersForWhichImWatching.clear()
MyECSubscriptionCryptorObjects.clear()
queryreturn = sqlQuery('SELECT address FROM subscriptions where enabled=1')
logger.debug('reloading subscriptions...')
for row in queryreturn:
address, = row
# status
addressVersionNumber, streamNumber, hashobj = decodeAddress(address)[1:]
if addressVersionNumber == 2:
broadcastSendersForWhichImWatching[hashobj] = 0
# Now, for all addresses, even version 2 addresses,
# we should create Cryptor objects in a dictionary which we will
# use to attempt to decrypt encrypted broadcast messages.
if addressVersionNumber <= 3:
privEncryptionKey = hashlib.sha512(
encodeVarint(addressVersionNumber)
+ encodeVarint(streamNumber) + hashobj
).digest()[:32]
MyECSubscriptionCryptorObjects[hashobj] = \
highlevelcrypto.makeCryptor(hexlify(privEncryptionKey))
else:
doubleHashOfAddressData = hashlib.sha512(hashlib.sha512(
encodeVarint(addressVersionNumber)
+ encodeVarint(streamNumber) + hashobj
).digest()).digest()
tag = doubleHashOfAddressData[32:]
privEncryptionKey = doubleHashOfAddressData[:32]
MyECSubscriptionCryptorObjects[tag] = \
highlevelcrypto.makeCryptor(hexlify(privEncryptionKey)) | [
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harpribot/deep-summarization | 9b3bb1daae11a1db2386dbe4a71848714e6127f8 | models/stacked_bidirectional.py | python | StackedBidirectional._load_optimizer | (self) | Load the SGD optimizer
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"""
Load the SGD optimizer
:return: None
"""
# loss function
with tf.variable_scope("forward"):
self.loss_fwd = tf.nn.seq2seq.sequence_loss(self.dec_outputs_fwd, self.labels,
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# optimizer
self.optimizer_fwd = tf.train.MomentumOptimizer(self.learning_rate, self.momentum)
self.train_op_fwd = self.optimizer_fwd.minimize(self.loss_fwd)
with tf.variable_scope("backward"):
self.loss_bwd = tf.nn.seq2seq.sequence_loss(self.dec_outputs_bwd, self.labels,
self.weights, self.vocab_size)
# optimizer
self.optimizer_bwd = tf.train.MomentumOptimizer(self.learning_rate, self.momentum)
self.train_op_bwd = self.optimizer_bwd.minimize(self.loss_bwd) | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/smhi/config_flow.py | python | SmhiFlowHandler.async_step_user | (
self, user_input: dict[str, Any] | None = None
) | return await self._show_config_form() | Handle a flow initialized by the user. | Handle a flow initialized by the user. | [
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self, user_input: dict[str, Any] | None = None
) -> FlowResult:
"""Handle a flow initialized by the user."""
self._errors = {}
if user_input is not None:
is_ok = await self._check_location(
user_input[CONF_LONGITUDE], user_input[CONF_LATITUDE]
)
if is_ok:
name = slugify(user_input[CONF_NAME])
if not self._name_in_configuration_exists(name):
latitude = user_input[CONF_LATITUDE]
longitude = user_input[CONF_LONGITUDE]
await self.async_set_unique_id(f"{latitude}-{longitude}")
self._abort_if_unique_id_configured()
return self.async_create_entry(
title=user_input[CONF_NAME], data=user_input
)
self._errors[CONF_NAME] = "name_exists"
else:
self._errors["base"] = "wrong_location"
# If hass config has the location set and is a valid coordinate the
# default location is set as default values in the form
if (
not smhi_locations(self.hass)
and await self._homeassistant_location_exists()
):
return await self._show_config_form(
name=HOME_LOCATION_NAME,
latitude=self.hass.config.latitude,
longitude=self.hass.config.longitude,
)
return await self._show_config_form() | [
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garethdmm/gryphon | 73e19fa2d0b64c3fc7dac9e0036fc92e25e5b694 | gryphon/lib/analysis/legacy/volatility.py | python | get_daily_core_fv_series_in_period | (db, start_time, end_time) | return fundamental_value_series | Get the daily close-close price series in this period from our core fv datums.
NOTE that we use close prices for this series, not open prices like for hourly.
Getting this series for the period [Nov 1st, Nov 4th) will give you three
datapoints. | Get the daily close-close price series in this period from our core fv datums.
NOTE that we use close prices for this series, not open prices like for hourly.
Getting this series for the period [Nov 1st, Nov 4th) will give you three
datapoints. | [
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"""
Get the daily close-close price series in this period from our core fv datums.
NOTE that we use close prices for this series, not open prices like for hourly.
Getting this series for the period [Nov 1st, Nov 4th) will give you three
datapoints.
"""
fundamental_value_series = []
# Getting the absolute last core_fv datum in a series of periods efficiently is
# difficult, so this query gets the first datum in the last five minutes of
# every day.
fv_series = db.query(
Datum.time_created,
Datum.numeric_value,
)\
.filter(Datum.time_created >= start_time)\
.filter(Datum.time_created < end_time)\
.filter(func.hour(Datum.time_created) == 23)\
.filter(func.minute(Datum.time_created) > 55)\
.filter(Datum.datum_type.like('%_CORE_FUNDAMENTAL_VALUE'))\
.group_by(func.date(Datum.time_created))\
.all()
# Do a teeny bit of sanity checking on the data
delta = end_time - start_time
assert(len(fv_series) == delta.days)
fundamental_value_series = convert_datum_series_to_time_series(fv_series)
return fundamental_value_series | [
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/gdata/src/gdata/tlslite/integration/AsyncStateMachine.py | python | AsyncStateMachine.setServerHandshakeOp | (self, **args) | Start a handshake operation.
The arguments passed to this function will be forwarded to
L{tlslite.TLSConnection.TLSConnection.handshakeServerAsync}. | Start a handshake operation. | [
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"""Start a handshake operation.
The arguments passed to this function will be forwarded to
L{tlslite.TLSConnection.TLSConnection.handshakeServerAsync}.
"""
handshaker = self.tlsConnection.handshakeServerAsync(**args)
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cgre-aachen/gempy | 6ad16c46fc6616c9f452fba85d31ce32decd8b10 | gempy/plot/_vista.py | python | Vista.plot_surfaces | (self, fmts: Iterable[str] = None, **kwargs) | return meshes | Plot all geomodel surfaces. If given an iterable containing surface
strings, it will plot all surfaces specified in it.
Args:
fmts (List[str], optional): Names of surfaces to plot.
Defaults to None. | Plot all geomodel surfaces. If given an iterable containing surface
strings, it will plot all surfaces specified in it.
Args:
fmts (List[str], optional): Names of surfaces to plot.
Defaults to None. | [
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"""Plot all geomodel surfaces. If given an iterable containing surface
strings, it will plot all surfaces specified in it.
Args:
fmts (List[str], optional): Names of surfaces to plot.
Defaults to None.
"""
colors = self._get_color_lot()
meshes = []
if fmts is None:
fmts = self.model._surfaces.df.surface[:-1].values
fmts = np.atleast_1d(fmts)
for fmt in fmts:
m = self.plot_surface(fmt, colors=colors, **kwargs)
for mesh in m:
meshes.append(mesh)
return meshes | [
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amimo/dcc | 114326ab5a082a42c7728a375726489e4709ca29 | androguard/decompiler/dad/control_flow.py | python | derived_sequence | (graph) | return deriv_seq, deriv_interv | Compute the derived sequence of the graph G
The intervals of G are collapsed into nodes, intervals of these nodes are
built, and the process is repeated iteratively until we obtain a single
node (if the graph is not irreducible) | Compute the derived sequence of the graph G
The intervals of G are collapsed into nodes, intervals of these nodes are
built, and the process is repeated iteratively until we obtain a single
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"""
Compute the derived sequence of the graph G
The intervals of G are collapsed into nodes, intervals of these nodes are
built, and the process is repeated iteratively until we obtain a single
node (if the graph is not irreducible)
"""
deriv_seq = [graph]
deriv_interv = []
single_node = False
while not single_node:
interv_graph, interv_heads = intervals(graph)
deriv_interv.append(interv_heads)
single_node = len(interv_graph) == 1
if not single_node:
deriv_seq.append(interv_graph)
graph = interv_graph
graph.compute_rpo()
return deriv_seq, deriv_interv | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/onnx/convert.py | python | export | (
tokenizer: PreTrainedTokenizer, model: PreTrainedModel, config: OnnxConfig, opset: int, output: Path
) | return matched_inputs, onnx_outputs | Export a PyTorch backed pipeline to ONNX Intermediate Representation (IR
Args:
tokenizer:
model:
config:
opset:
output:
Returns: | Export a PyTorch backed pipeline to ONNX Intermediate Representation (IR | [
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tokenizer: PreTrainedTokenizer, model: PreTrainedModel, config: OnnxConfig, opset: int, output: Path
) -> Tuple[List[str], List[str]]:
"""
Export a PyTorch backed pipeline to ONNX Intermediate Representation (IR
Args:
tokenizer:
model:
config:
opset:
output:
Returns:
"""
if not is_torch_available():
raise ImportError("Cannot convert because PyTorch is not installed. Please install torch first.")
import torch
from torch.onnx import export
from ..file_utils import torch_version
if not is_torch_onnx_dict_inputs_support_available():
raise AssertionError(f"Unsupported PyTorch version, minimum required is 1.8.0, got: {torch_version}")
logger.info(f"Using framework PyTorch: {torch.__version__}")
with torch.no_grad():
model.config.return_dict = True
model.eval()
# Check if we need to override certain configuration item
if config.values_override is not None:
logger.info(f"Overriding {len(config.values_override)} configuration item(s)")
for override_config_key, override_config_value in config.values_override.items():
logger.info(f"\t- {override_config_key} -> {override_config_value}")
setattr(model.config, override_config_key, override_config_value)
# Ensure inputs match
# TODO: Check when exporting QA we provide "is_pair=True"
model_inputs = config.generate_dummy_inputs(tokenizer, framework=TensorType.PYTORCH)
inputs_match, matched_inputs = ensure_model_and_config_inputs_match(model, model_inputs.keys())
onnx_outputs = list(config.outputs.keys())
if not inputs_match:
raise ValueError("Model and config inputs doesn't match")
config.patch_ops()
# export can works with named args but the dict containing named args as to be last element of the args tuple
export(
model,
(model_inputs,),
f=output.as_posix(),
input_names=list(config.inputs.keys()),
output_names=onnx_outputs,
dynamic_axes={name: axes for name, axes in chain(config.inputs.items(), config.outputs.items())},
do_constant_folding=True,
use_external_data_format=config.use_external_data_format(model.num_parameters()),
enable_onnx_checker=True,
opset_version=opset,
)
config.restore_ops()
return matched_inputs, onnx_outputs | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_openshift/library/oc_scale.py | python | Yedit.exists | (self, path, value) | return entry == value | check if value exists at path | check if value exists at path | [
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''' check if value exists at path'''
try:
entry = Yedit.get_entry(self.yaml_dict, path, self.separator)
except KeyError:
entry = None
if isinstance(entry, list):
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keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/clients/client.py | python | BotClient.load_trigger_manager | (self) | [] | def load_trigger_manager(self):
if self._configuration.client_configuration.triggers is not None:
YLogger.debug(None, "Loading Trigger Manager")
self._trigger_mgr = TriggerManager.load_trigger_manager(self._configuration.client_configuration.triggers) | [
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Textualize/rich | d39626143036188cb2c9e1619e836540f5b627f8 | rich/pretty.py | python | _get_attr_fields | (obj: Any) | return _attr_module.fields(type(obj)) if _attr_module is not None else [] | Get fields for an attrs object. | Get fields for an attrs object. | [
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sqlmapproject/sqlmap | 3b07b70864624dff4c29dcaa8a61c78e7f9189f7 | thirdparty/bottle/bottle.py | python | FileUpload.__init__ | (self, fileobj, name, filename, headers=None) | Wrapper for file uploads. | Wrapper for file uploads. | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/Lib/mailbox.py | python | MH.unlock | (self) | Unlock the mailbox if it is locked. | Unlock the mailbox if it is locked. | [
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"""Unlock the mailbox if it is locked."""
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linuxscout/mishkal | 4f4ae0ebc2d6acbeb3de3f0303151ec7b54d2f76 | mishkal/tashkeel.py | python | TashkeelClass._ajust_vocalized_result | (self, text) | return text | Ajust the resulted text after vocalization to correct some case
like 'meeting of two queiscents = ألتقاء الساكنين'
@param text: vocalized text
@type text: unicode
@return: ajusted text.
@rtype: unicode | Ajust the resulted text after vocalization to correct some case
like 'meeting of two queiscents = ألتقاء الساكنين' | [
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"""
Ajust the resulted text after vocalization to correct some case
like 'meeting of two queiscents = ألتقاء الساكنين'
@param text: vocalized text
@type text: unicode
@return: ajusted text.
@rtype: unicode
"""
# min = > mina
text = re.sub(u'\sمِنْ\s+ا', u' مِنَ ا', text)
# man = > mani
text = re.sub(u'\sمَنْ\s+ا', u' مَنِ ا', text)
#An = > ani
text = re.sub(u'\sعَنْ\s+ا', u' عَنِ ا', text)
#sukun + alef = > kasra +alef
text = re.sub(u'\s%s\s+ا'%araby.SUKUN, u' %s ا' % araby.KASRA, text)
#~ text = re.sub(ur'\s%s\s+ا'%araby.SUKUN, u' %s ا' % araby.SUKUN, text)
#ajust pounctuation
text = re.sub(u" ([.?!, :)”—]($| ))", u"\1", text)
#binu = > bin
# temporary, to be analysed by syntaxical analyzer
text = re.sub(u'\sبْنُ\s', u' بْن ', text)
# # # اختصارات مثل حدثنا إلى ثنا وه تكثر في كتب التراث
# text = re.sub(ur'\seثِنَا\s', u' ثَنَا ', text)
return text | [
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/importlib/_bootstrap.py | python | _ModuleLock.has_deadlock | (self) | [] | def has_deadlock(self):
# Deadlock avoidance for concurrent circular imports.
me = _thread.get_ident()
tid = self.owner
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return False
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OpnTec/open-event-server | a48f7e4c6002db6fb4dc06bac6508536a0dc585e | app/models/user.py | python | User.can_create_event | (self) | return True | Checks if User can create an event | Checks if User can create an event | [
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v8/services/services/carrier_constant_service/client.py | python | CarrierConstantServiceClient.parse_common_project_path | (path: str) | return m.groupdict() if m else {} | Parse a project path into its component segments. | Parse a project path into its component segments. | [
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nadineproject/nadine | c41c8ef7ffe18f1853029c97eecc329039b4af6c | nadine/forms.py | python | ProfileImageForm.save | (self) | [] | def save(self):
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if not raw_img_data or len(raw_img_data) == 0:
# Nothing to save here
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img_data = base64.b64decode(raw_img_data)
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filename = "user_photos/%s.jpg" % self.cleaned_data['username']
if user.profile.photo:
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filename = "org_photos/%s.jpg" % self.cleaned_data['username']
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numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/core/tracing.py | python | TLS.__init__ | (self) | [] | def __init__(self):
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nshaud/DeepHyperX | 176e582e53df92a6b4014b022c7f67034b489889 | utils.py | python | padding_image | (image, patch_size=None, mode="symmetric", constant_values=0) | return padded_image | Padding an input image.
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[pad_width.append([0, 0]) for i in image.shape[2:]]
padded_image = np.pad(image, pad_width, mode=mode, constant_values=constant_values)
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optuna/optuna | 2c44c1a405ba059efd53f4b9c8e849d20fb95c0a | optuna/trial/_frozen.py | python | FrozenTrial.suggest_discrete_uniform | (self, name: str, low: float, high: float, q: float) | return self.suggest_float(name, low, high, step=q) | [] | def suggest_discrete_uniform(self, name: str, low: float, high: float, q: float) -> float:
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PowerScript/KatanaFramework | 0f6ad90a88de865d58ec26941cb4460501e75496 | lib/scapy/scapy/utils6.py | python | in6_cidr2mask | (m) | return ''.join(map(lambda x: struct.pack('!I', x), t)) | Return the mask (bitstring) associated with provided length
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cleverhans-lab/cleverhans | e5d00e537ce7ad6119ed5a8db1f0e9736d1f6e1d | cleverhans_v3.1.0/examples/nips17_adversarial_competition/eval_infra/code/eval_lib/classification_results.py | python | ResultMatrix.__getitem__ | (self, key) | return self._items.get(key, self._default_value) | Returns element of the matrix indexed by given key.
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key: tuple of (row_idx, column_idx)
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Raises:
IndexError: if key is invalid.
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thinkle/gourmet | 8af29c8ded24528030e5ae2ea3461f61c1e5a575 | gourmet/Undo.py | python | MultipleUndoLists.insert | (self,*args,**kwargs) | return self.get_history().insert(*args,**kwargs) | [] | def insert (self,*args,**kwargs): return self.get_history().insert(*args,**kwargs) | [
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stanfordnlp/spinn | f2f95f585328ec5cd7da071753f5e0582e7600a0 | python/spinn/models/classifier.py | python | build_transition_cost | (logits, targets, num_transitions) | return cost, acc | Build a parse action prediction cost function. | Build a parse action prediction cost function. | [
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"""
Build a parse action prediction cost function.
"""
# swap seq_length dimension to front so that we can scan per timestep
logits = T.swapaxes(logits, 0, 1)
targets = targets.T
def cost_t(logits, tgt, num_transitions):
# TODO(jongauthier): Taper down xent cost as we proceed through
# sequence?
predicted_dist = T.nnet.softmax(logits)
cost = T.nnet.categorical_crossentropy(predicted_dist, tgt)
pred = T.argmax(logits, axis=1)
error = T.neq(pred, tgt)
return cost, error
results, _ = theano.scan(cost_t, [logits, targets], non_sequences=[num_transitions])
costs, errors = results
# Create a mask that selects only transitions that involve real data.
unrolling_length = T.shape(costs)[0]
padding = unrolling_length - num_transitions
padding = T.reshape(padding, (1, -1))
rng = T.arange(unrolling_length) + 1
rng = T.reshape(rng, (-1, 1))
mask = T.gt(rng, padding)
# Compute acc using the mask
acc = 1.0 - (T.sum(errors * mask, dtype=theano.config.floatX)
/ T.sum(num_transitions, dtype=theano.config.floatX))
# Compute cost directly, since we *do* want a cost incentive to get the padding
# transitions right.
cost = T.mean(costs)
return cost, acc | [
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_component_status.py | python | V1ComponentStatus.to_str | (self) | return pprint.pformat(self.to_dict()) | Returns the string representation of the model | Returns the string representation of the model | [
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pydata/patsy | 5fc881104b749b720b08e393a5505d6e69d72f95 | patsy/compat_ordereddict.py | python | OrderedDict.iteritems | (self) | od.iteritems -> an iterator over the (key, value) items in od | od.iteritems -> an iterator over the (key, value) items in od | [
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scrapy/scrapy | b04cfa48328d5d5749dca6f50fa34e0cfc664c89 | scrapy/utils/defer.py | python | maybe_deferred_to_future | (d: Deferred) | .. versionadded:: VERSION
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What you can await in Scrapy callables defined as coroutines depends on the
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class MySpider(Spider):
...
async def parse(self, response):
d = treq.get('https://example.com/additional')
extra_response = await maybe_deferred_to_future(d) | .. versionadded:: VERSION | [
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"""
.. versionadded:: VERSION
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...
async def parse(self, response):
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memray/seq2seq-keyphrase | 9145c63ebdc4c3bc431f8091dc52547a46804012 | emolga/dataset/build_dataset.py | python | deserialize_from_file_hdf5 | (path) | return obj | [] | def deserialize_from_file_hdf5(path):
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securityclippy/elasticintel | aa08d3e9f5ab1c000128e95161139ce97ff0e334 | whois_lambda/ipwhois/whois.py | python | Whois.get_nets_other | (self, response) | return nets | The function for parsing network blocks from generic whois data.
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response (:obj:`str`): The response from the whois/rwhois server.
Returns:
list of dict: Mapping of networks with start and end positions.
::
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net = copy.deepcopy(BASE_NET)
net_range = match.group(2).strip()
try:
net['range'] = net['range'] = '{0} - {1}'.format(
ip_network(net_range)[0].__str__(),
ip_network(net_range)[-1].__str__()
) if '/' in net_range else net_range
except ValueError: # pragma: no cover
net['range'] = net_range
if match.group(3) and match.group(4):
addrs = []
addrs.extend(summarize_address_range(
ip_address(match.group(3).strip()),
ip_address(match.group(4).strip())))
cidr = ', '.join(
[i.__str__() for i in collapse_addresses(addrs)]
)
else:
cidr = ip_network(net_range).__str__()
net['cidr'] = cidr
net['start'] = match.start()
net['end'] = match.end()
nets.append(net)
except (ValueError, TypeError):
pass
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"r'^(inetnum|inet6num|route... | https://github.com/securityclippy/elasticintel/blob/aa08d3e9f5ab1c000128e95161139ce97ff0e334/whois_lambda/ipwhois/whois.py#L508-L578 | |
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/idlelib/ColorDelegator.py | python | _color_delegator | (parent) | [] | def _color_delegator(parent): # htest #
from Tkinter import Toplevel, Text
from idlelib.Percolator import Percolator
top = Toplevel(parent)
top.title("Test ColorDelegator")
top.geometry("200x100+%d+%d" % (parent.winfo_rootx() + 200,
parent.winfo_rooty() + 150))
source = "if somename: x = 'abc' # comment\nprint\n"
text = Text(top, background="white")
text.pack(expand=1, fill="both")
text.insert("insert", source)
text.focus_set()
p = Percolator(text)
d = ColorDelegator()
p.insertfilter(d) | [
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gwastro/pycbc | 1e1c85534b9dba8488ce42df693230317ca63dea | pycbc/waveform/ringdown.py | python | format_lmns | (lmns) | return out | Checks if the format of the parameter lmns is correct, returning the
appropriate format if not, and raise an error if nmodes=0.
The required format for the ringdown approximants is a list of lmn modes
as a single whitespace-separated string, with n the number
of overtones desired. Alternatively, a list object may be used,
containing individual strings as elements for the lmn modes.
For instance, lmns = '223 331' are the modes 220, 221, 222, and 330.
Giving lmns = ['223', '331'] is equivalent.
The ConfigParser of a workflow might convert that to a single string
(case 1 below) or a list with a single string (case 2), and this function
will return the appropriate list of strings. If a different format is
given, raise an error. | Checks if the format of the parameter lmns is correct, returning the
appropriate format if not, and raise an error if nmodes=0. | [
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] | def format_lmns(lmns):
"""Checks if the format of the parameter lmns is correct, returning the
appropriate format if not, and raise an error if nmodes=0.
The required format for the ringdown approximants is a list of lmn modes
as a single whitespace-separated string, with n the number
of overtones desired. Alternatively, a list object may be used,
containing individual strings as elements for the lmn modes.
For instance, lmns = '223 331' are the modes 220, 221, 222, and 330.
Giving lmns = ['223', '331'] is equivalent.
The ConfigParser of a workflow might convert that to a single string
(case 1 below) or a list with a single string (case 2), and this function
will return the appropriate list of strings. If a different format is
given, raise an error.
"""
# Catch case of lmns given as float (as int injection values are cast
# to float by pycbc_create_injections), cast to int, then string
if isinstance(lmns, float):
lmns = str(int(lmns))
# Case 1: the lmns are given as a string, e.g. '221 331'
if isinstance(lmns, str):
lmns = lmns.split(' ')
# Case 2: the lmns are given as strings in a list, e.g. ['221', '331']
elif isinstance(lmns, list):
pass
else:
raise ValueError('Format of parameter lmns not recognized. See '
'approximant documentation for more info.')
out = []
# Cycle over the lmns to ensure that we get back a list of strings that
# are three digits long, and that nmodes!=0
for lmn in lmns:
# The following line is to be used with Python3 if the lmns are stored
# as a list of strings in the HDF files and the workflow converts that
# to a string
# lmn = lmn.strip(" b'")
# Try to convert to int and then str, to ensure the right format
lmn = str(int(lmn))
if len(lmn) != 3:
raise ValueError('Format of parameter lmns not recognized. See '
'approximant documentation for more info.')
elif int(lmn[2]) == 0:
raise ValueError('Number of overtones (nmodes) must be greater '
'than zero in lmn={}.'.format(lmn))
out.append(lmn)
return out | [
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zetaops/ulakbus | bcc05abf17bbd6dbeec93809e4ad30885e94e83e | ulakbus/services/personel/hitap/hitap_service.py | python | ZatoHitapService.date_filter_hitap_to_ulakbus | (date_filter_fields, response_payload) | date_filter_ulakbus_to_hitap metodunun tersi icin gereklidir.
Args:
date_filter_fields (list): Zato servisinde bulunan ve
tarih formatinda olan field isimleri listesi
response_payload (dict): gonderilen kayit degerleri | date_filter_ulakbus_to_hitap metodunun tersi icin gereklidir. | [
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] | def date_filter_hitap_to_ulakbus(date_filter_fields, response_payload):
"""
date_filter_ulakbus_to_hitap metodunun tersi icin gereklidir.
Args:
date_filter_fields (list): Zato servisinde bulunan ve
tarih formatinda olan field isimleri listesi
response_payload (dict): gonderilen kayit degerleri
"""
from datetime import datetime
for field in date_filter_fields:
if response_payload[field] == "0001-01-01":
response_payload[field] = '01.01.1900'
else:
date_format = datetime.strptime(response_payload[field], "%Y-%m-%d")
response_payload[field] = date_format.strftime("%d.%m.%Y") | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/priorities/tasks/task.py | python | Task.tasks | (self, tasks) | Set the stack of tasks. | Set the stack of tasks. | [
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] | def tasks(self, tasks):
"""Set the stack of tasks."""
# check type
if tasks is None or (isinstance(tasks, (list, tuple)) and len(tasks) == 0):
tasks = [[]]
if not isinstance(tasks, (list, tuple)):
raise TypeError("Expecting the given 'tasks', to be a list of list of `Task`, instead got: "
"{}".format(type(tasks)))
# go through the stack of tasks
for i, hard_task in enumerate(tasks):
# if the hard task is a list of soft tasks
if isinstance(hard_task, (list, tuple)):
# go through each soft task in the hard task
for j, soft_task in enumerate(hard_task):
if not isinstance(soft_task, Task):
if isinstance(soft_task, Constraint):
# if constraint (must be an equality constraint), try to convert it into a task
tasks[i][j] = prl.priorities.tasks.TaskFromConstraint(soft_task)
else:
raise TypeError("The given task positioned at ({}, {}) is not an instance of `Task`, "
"but: {}".format(i, j, type(soft_task)))
else: # if not, check that the hard task is an instance of Task
if not isinstance(hard_task, Task):
raise TypeError("Expecting the {}th hard task to be an instance of `Task` or a list of `Task`, "
"instead got: {}".format(i, type(hard_task)))
tasks[i] = [task]
# set the stack of tasks
self._tasks = tasks | [
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olist/correios | 5494d7457665fa9a8dffbffa976cdbd2885c54e4 | correios/models/user.py | python | AbstractTaxNumber.__eq__ | (self, other) | return self.number == self._sanitize(other) | [] | def __eq__(self, other):
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/pip/_vendor/packaging/version.py | python | _parse_letter_version | (letter, number) | [] | def _parse_letter_version(letter, number):
if letter:
# We consider there to be an implicit 0 in a pre-release if there is
# not a numeral associated with it.
if number is None:
number = 0
# We normalize any letters to their lower case form
letter = letter.lower()
# We consider some words to be alternate spellings of other words and
# in those cases we want to normalize the spellings to our preferred
# spelling.
if letter == "alpha":
letter = "a"
elif letter == "beta":
letter = "b"
elif letter in ["c", "pre", "preview"]:
letter = "rc"
elif letter in ["rev", "r"]:
letter = "post"
return letter, int(number)
if not letter and number:
# We assume if we are given a number, but we are not given a letter
# then this is using the implicit post release syntax (e.g. 1.0-1)
letter = "post"
return letter, int(number) | [
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freedomofpress/securedrop | f768a1a5aa37e790077dfd38d6e7a0299a4b3a0f | admin/securedrop_admin/__init__.py | python | get_logs | (args: argparse.Namespace) | return 0 | Get logs for forensics and debugging purposes | Get logs for forensics and debugging purposes | [
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] | def get_logs(args: argparse.Namespace) -> int:
"""Get logs for forensics and debugging purposes"""
sdlog.info("Gathering logs for forensics and debugging")
ansible_cmd = [
'ansible-playbook',
os.path.join(args.ansible_path, 'securedrop-logs.yml'),
]
subprocess.check_call(ansible_cmd, cwd=args.ansible_path)
sdlog.info("Please send the encrypted logs to securedrop@freedom.press or "
"upload them to the SecureDrop support portal: " + SUPPORT_URL)
return 0 | [
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simonw/djangopeople.net | ed04d3c79d03b9c74f3e7f82b2af944e021f8e15 | lib/yadis/discover.py | python | DiscoveryResult.usedYadisLocation | (self) | return self.normalized_uri == self.xrds_uri | Was the Yadis protocol's indirection used? | Was the Yadis protocol's indirection used? | [
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return self.normalized_uri == self.xrds_uri | [
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openstack/barbican | a9d2b133c8dc3307974f119f9a2b23a4ba82e8ce | barbican/plugin/snakeoil_ca.py | python | SnakeoilCA.pkcs7 | (self, val) | [] | def pkcs7(self, val):
if self.pkcs7_path:
with open(self.pkcs7_path, 'wb') as pkcs7_fh:
pkcs7_fh.write(val)
else:
self._pkcs7_val = val | [
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/requests/adapters.py | python | HTTPAdapter.close | (self) | Disposes of any internal state.
Currently, this just closes the PoolManager, which closes pooled
connections. | Disposes of any internal state. | [
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] | def close(self):
"""Disposes of any internal state.
Currently, this just closes the PoolManager, which closes pooled
connections.
"""
self.poolmanager.clear() | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/flux_led/light.py | python | FluxLight._async_set_mode | (self, **kwargs: Any) | Set an effect or color mode. | Set an effect or color mode. | [
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"effect",
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"color",
"mode",
"."
] | async def _async_set_mode(self, **kwargs: Any) -> None:
"""Set an effect or color mode."""
brightness = self._async_brightness(**kwargs)
# Handle switch to Effect Mode
if effect := kwargs.get(ATTR_EFFECT):
await self._async_set_effect(effect, brightness)
return
# Handle switch to CCT Color Mode
if color_temp_mired := kwargs.get(ATTR_COLOR_TEMP):
color_temp_kelvin = color_temperature_mired_to_kelvin(color_temp_mired)
if (
ATTR_BRIGHTNESS not in kwargs
and self.color_mode in MULTI_BRIGHTNESS_COLOR_MODES
):
# When switching to color temp from RGBWW or RGB&W mode,
# we do not want the overall brightness of the RGB channels
brightness = max(self._device.rgb)
await self._device.async_set_white_temp(color_temp_kelvin, brightness)
return
# Handle switch to RGB Color Mode
if rgb := kwargs.get(ATTR_RGB_COLOR):
if not self._device.requires_turn_on:
rgb = _min_rgb_brightness(rgb)
red, green, blue = rgb
await self._device.async_set_levels(red, green, blue, brightness=brightness)
return
# Handle switch to RGBW Color Mode
if rgbw := kwargs.get(ATTR_RGBW_COLOR):
if ATTR_BRIGHTNESS in kwargs:
rgbw = rgbw_brightness(rgbw, brightness)
if not self._device.requires_turn_on:
rgbw = _min_rgbw_brightness(rgbw)
await self._device.async_set_levels(*rgbw)
return
# Handle switch to RGBWW Color Mode
if rgbcw := kwargs.get(ATTR_RGBWW_COLOR):
if ATTR_BRIGHTNESS in kwargs:
rgbcw = rgbcw_brightness(kwargs[ATTR_RGBWW_COLOR], brightness)
rgbwc = rgbcw_to_rgbwc(rgbcw)
if not self._device.requires_turn_on:
rgbwc = _min_rgbwc_brightness(rgbwc)
await self._device.async_set_levels(*rgbwc)
return
if (white := kwargs.get(ATTR_WHITE)) is not None:
await self._device.async_set_levels(w=white)
return | [
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/oauthlib/oauth1/rfc5849/utils.py | python | filter_oauth_params | (params) | Removes all non oauth parameters from a dict or a list of params. | Removes all non oauth parameters from a dict or a list of params. | [
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] | def filter_oauth_params(params):
"""Removes all non oauth parameters from a dict or a list of params."""
is_oauth = lambda kv: kv[0].startswith("oauth_")
if isinstance(params, dict):
return list(filter(is_oauth, list(params.items())))
else:
return list(filter(is_oauth, params)) | [
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miyakogi/pyppeteer | f5313d0e7f973c57ed31fa443cea1834e223a96c | pyppeteer/chromium_downloader.py | python | chromium_executable | () | return chromiumExecutable[current_platform()] | Get path of the chromium executable. | Get path of the chromium executable. | [
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] | def chromium_executable() -> Path:
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/modular/hecke/module.py | python | HeckeModule_free_module._eigen_nonzero | (self) | Return the smallest integer `i` such that the `i`-th entries of
the entries of a basis for the dual vector space are not all 0.
EXAMPLES::
sage: M = ModularSymbols(31,2)
sage: M._eigen_nonzero()
0
sage: M.dual_free_module().basis()
[
(1, 0, 0, 0, 0),
(0, 1, 0, 0, 0),
(0, 0, 1, 0, 0),
(0, 0, 0, 1, 0),
(0, 0, 0, 0, 1)
]
sage: M.cuspidal_submodule().minus_submodule()._eigen_nonzero()
1
sage: M.cuspidal_submodule().minus_submodule().dual_free_module().basis()
[
(0, 1, 0, 0, 0),
(0, 0, 1, 0, 0)
] | Return the smallest integer `i` such that the `i`-th entries of
the entries of a basis for the dual vector space are not all 0. | [
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] | def _eigen_nonzero(self):
"""
Return the smallest integer `i` such that the `i`-th entries of
the entries of a basis for the dual vector space are not all 0.
EXAMPLES::
sage: M = ModularSymbols(31,2)
sage: M._eigen_nonzero()
0
sage: M.dual_free_module().basis()
[
(1, 0, 0, 0, 0),
(0, 1, 0, 0, 0),
(0, 0, 1, 0, 0),
(0, 0, 0, 1, 0),
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]
sage: M.cuspidal_submodule().minus_submodule()._eigen_nonzero()
1
sage: M.cuspidal_submodule().minus_submodule().dual_free_module().basis()
[
(0, 1, 0, 0, 0),
(0, 0, 1, 0, 0)
]
"""
try:
return self.__eigen_nonzero
except AttributeError:
pass
V = self.dual_free_module()
B = V.basis()
for i in range(V.degree()):
for b in B:
if b[i] != 0:
self.__eigen_nonzero = i
return i
assert False, 'bug in _eigen_nonzero' | [
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kubeflow-kale/kale | bda9d296822e56ba8fe76b0072e656005da04905 | backend/kale/common/serveutils.py | python | KFServer.__repr__ | (self) | Show an interactive text in notebooks. | Show an interactive text in notebooks. | [
"Show",
"an",
"interactive",
"text",
"in",
"notebooks",
"."
] | def __repr__(self):
"""Show an interactive text in notebooks."""
if utils.is_ipython():
import IPython
html = ('InferenceService <pre>%s</pre> serving requests at host'
' <pre>%s</pre><br>'
'View model <a href="/models/details/%s/%s"'
' target="_blank" >here</a>'
% (self.name,
get_inference_service_host(self.name),
podutils.get_namespace(),
self.name))
IPython.display.display(IPython.display.HTML(html))
return ""
else:
return super(KFServer, self).__repr__() | [
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ycszen/TorchSeg | 62eeb159aee77972048d9d7688a28249d3c56735 | furnace/tools/benchmark/compute_flops.py | python | compute_ReLU_flops | (module, inp, out) | return active_elements_count | [] | def compute_ReLU_flops(module, inp, out):
assert isinstance(module,
(nn.ReLU, nn.ReLU6, nn.PReLU, nn.ELU, nn.LeakyReLU,
nn.Sigmoid))
batch_size = inp.size()[0]
active_elements_count = batch_size
for s in inp.size()[1:]:
active_elements_count *= s
return active_elements_count | [
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... | https://github.com/ycszen/TorchSeg/blob/62eeb159aee77972048d9d7688a28249d3c56735/furnace/tools/benchmark/compute_flops.py#L64-L74 | |||
kubeflow/pipelines | bea751c9259ff0ae85290f873170aae89284ba8e | backend/api/python_http_client/kfp_server_api/api/experiment_service_api.py | python | ExperimentServiceApi.delete_experiment_with_http_info | (self, id, **kwargs) | return self.api_client.call_api(
'/apis/v1beta1/experiments/{id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='object', # 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) | Deletes an experiment without deleting the experiment's runs and jobs. To avoid unexpected behaviors, delete an experiment's runs and jobs before deleting the experiment. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_experiment_with_http_info(id, async_req=True)
>>> result = thread.get()
:param id: The ID of the experiment to be deleted. (required)
:type id: str
:param async_req: Whether to execute the request asynchronously.
:type async_req: bool, optional
:param _return_http_data_only: response data without head status code
and headers
:type _return_http_data_only: bool, optional
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:type _preload_content: bool, optional
: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: Returns the result object.
If the method is called asynchronously,
returns the request thread.
:rtype: tuple(object, status_code(int), headers(HTTPHeaderDict)) | Deletes an experiment without deleting the experiment's runs and jobs. To avoid unexpected behaviors, delete an experiment's runs and jobs before deleting the experiment. # noqa: E501 | [
"Deletes",
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"#",... | def delete_experiment_with_http_info(self, id, **kwargs): # noqa: E501
"""Deletes an experiment without deleting the experiment's runs and jobs. To avoid unexpected behaviors, delete an experiment's runs and jobs before deleting the experiment. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_experiment_with_http_info(id, async_req=True)
>>> result = thread.get()
:param id: The ID of the experiment to be deleted. (required)
:type id: str
:param async_req: Whether to execute the request asynchronously.
:type async_req: bool, optional
:param _return_http_data_only: response data without head status code
and headers
:type _return_http_data_only: bool, optional
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:type _preload_content: bool, optional
: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: Returns the result object.
If the method is called asynchronously,
returns the request thread.
:rtype: tuple(object, status_code(int), headers(HTTPHeaderDict))
"""
local_var_params = locals()
all_params = [
'id'
]
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 delete_experiment" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'id' is set
if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501
local_var_params['id'] is None): # noqa: E501
raise ApiValueError("Missing the required parameter `id` when calling `delete_experiment`") # noqa: E501
collection_formats = {}
path_params = {}
if 'id' in local_var_params:
path_params['id'] = local_var_params['id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['Bearer'] # noqa: E501
return self.api_client.call_api(
'/apis/v1beta1/experiments/{id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='object', # 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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google/clusterfuzz | f358af24f414daa17a3649b143e71ea71871ef59 | src/clusterfuzz/_internal/metrics/monitor.py | python | initialize | () | Initialize if monitoring is enabled for this bot. | Initialize if monitoring is enabled for this bot. | [
"Initialize",
"if",
"monitoring",
"is",
"enabled",
"for",
"this",
"bot",
"."
] | def initialize():
"""Initialize if monitoring is enabled for this bot."""
global _monitoring_v3_client
global _flusher_thread
if environment.get_value('LOCAL_DEVELOPMENT'):
return
if not local_config.ProjectConfig().get('monitoring.enabled'):
return
if check_module_loaded(monitoring_v3):
_initialize_monitored_resource()
_monitoring_v3_client = monitoring_v3.MetricServiceClient(
credentials=credentials.get_default()[0])
_flusher_thread = _FlusherThread()
_flusher_thread.start() | [
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"(... | https://github.com/google/clusterfuzz/blob/f358af24f414daa17a3649b143e71ea71871ef59/src/clusterfuzz/_internal/metrics/monitor.py#L519-L535 | ||
mmatl/pyrender | 4a289a6205c5baa623cd0e7da1be3d898bcbc4da | pyrender/shader_program.py | python | ShaderProgram.set_uniform | (self, name, value, unsigned=False) | Set a uniform value in the current shader program.
Parameters
----------
name : str
Name of the uniform to set.
value : int, float, or ndarray
Value to set the uniform to.
unsigned : bool
If True, ints will be treated as unsigned values. | Set a uniform value in the current shader program. | [
"Set",
"a",
"uniform",
"value",
"in",
"the",
"current",
"shader",
"program",
"."
] | def set_uniform(self, name, value, unsigned=False):
"""Set a uniform value in the current shader program.
Parameters
----------
name : str
Name of the uniform to set.
value : int, float, or ndarray
Value to set the uniform to.
unsigned : bool
If True, ints will be treated as unsigned values.
"""
try:
# DEBUG
# self._unif_map[name] = 1, (1,)
loc = glGetUniformLocation(self._program_id, name)
if loc == -1:
raise ValueError('Invalid shader variable: {}'.format(name))
if isinstance(value, np.ndarray):
# DEBUG
# self._unif_map[name] = value.size, value.shape
if value.ndim == 1:
if (np.issubdtype(value.dtype, np.unsignedinteger) or
unsigned):
dtype = 'u'
value = value.astype(np.uint32)
elif np.issubdtype(value.dtype, np.integer):
dtype = 'i'
value = value.astype(np.int32)
else:
dtype = 'f'
value = value.astype(np.float32)
self._FUNC_MAP[(value.shape[0], dtype)](loc, 1, value)
else:
self._FUNC_MAP[(value.shape[0], value.shape[1])](
loc, 1, GL_TRUE, value
)
# Call correct uniform function
elif isinstance(value, float):
glUniform1f(loc, value)
elif isinstance(value, int):
if unsigned:
glUniform1ui(loc, value)
else:
glUniform1i(loc, value)
elif isinstance(value, bool):
if unsigned:
glUniform1ui(loc, int(value))
else:
glUniform1i(loc, int(value))
else:
raise ValueError('Invalid data type')
except Exception:
pass | [
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deepset-ai/haystack | 79fdda8a7cf393d774803608a4874f2a6e63cf6f | haystack/document_stores/elasticsearch.py | python | ElasticsearchDocumentStore.update_embeddings | (
self,
retriever,
index: Optional[str] = None,
filters: Optional[Dict[str, List[str]]] = None,
update_existing_embeddings: bool = True,
batch_size: int = 10_000,
headers: Optional[Dict[str, str]] = None
) | Updates the embeddings in the the document store using the encoding model specified in the retriever.
This can be useful if want to add or change the embeddings for your documents (e.g. after changing the retriever config).
:param retriever: Retriever to use to update the embeddings.
:param index: Index name to update
:param update_existing_embeddings: Whether to update existing embeddings of the documents. If set to False,
only documents without embeddings are processed. This mode can be used for
incremental updating of embeddings, wherein, only newly indexed documents
get processed.
:param filters: Optional filters to narrow down the documents for which embeddings are to be updated.
Example: {"name": ["some", "more"], "category": ["only_one"]}
:param batch_size: When working with large number of documents, batching can help reduce memory footprint.
:param headers: Custom HTTP headers to pass to elasticsearch client (e.g. {'Authorization': 'Basic YWRtaW46cm9vdA=='})
Check out https://www.elastic.co/guide/en/elasticsearch/reference/current/http-clients.html for more information.
:return: None | Updates the embeddings in the the document store using the encoding model specified in the retriever.
This can be useful if want to add or change the embeddings for your documents (e.g. after changing the retriever config). | [
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"for",
... | def update_embeddings(
self,
retriever,
index: Optional[str] = None,
filters: Optional[Dict[str, List[str]]] = None,
update_existing_embeddings: bool = True,
batch_size: int = 10_000,
headers: Optional[Dict[str, str]] = None
):
"""
Updates the embeddings in the the document store using the encoding model specified in the retriever.
This can be useful if want to add or change the embeddings for your documents (e.g. after changing the retriever config).
:param retriever: Retriever to use to update the embeddings.
:param index: Index name to update
:param update_existing_embeddings: Whether to update existing embeddings of the documents. If set to False,
only documents without embeddings are processed. This mode can be used for
incremental updating of embeddings, wherein, only newly indexed documents
get processed.
:param filters: Optional filters to narrow down the documents for which embeddings are to be updated.
Example: {"name": ["some", "more"], "category": ["only_one"]}
:param batch_size: When working with large number of documents, batching can help reduce memory footprint.
:param headers: Custom HTTP headers to pass to elasticsearch client (e.g. {'Authorization': 'Basic YWRtaW46cm9vdA=='})
Check out https://www.elastic.co/guide/en/elasticsearch/reference/current/http-clients.html for more information.
:return: None
"""
if index is None:
index = self.index
if self.refresh_type == 'false':
self.client.indices.refresh(index=index, headers=headers)
if not self.embedding_field:
raise RuntimeError("Specify the arg `embedding_field` when initializing ElasticsearchDocumentStore()")
if update_existing_embeddings:
document_count = self.get_document_count(index=index, headers=headers)
logger.info(f"Updating embeddings for all {document_count} docs ...")
else:
document_count = self.get_document_count(index=index, filters=filters,
only_documents_without_embedding=True, headers=headers)
logger.info(f"Updating embeddings for {document_count} docs without embeddings ...")
result = self._get_all_documents_in_index(
index=index,
filters=filters,
batch_size=batch_size,
only_documents_without_embedding=not update_existing_embeddings,
headers=headers
)
logging.getLogger("elasticsearch").setLevel(logging.CRITICAL)
with tqdm(total=document_count, position=0, unit=" Docs", desc="Updating embeddings") as progress_bar:
for result_batch in get_batches_from_generator(result, batch_size):
document_batch = [self._convert_es_hit_to_document(hit, return_embedding=False) for hit in result_batch]
embeddings = retriever.embed_documents(document_batch) # type: ignore
assert len(document_batch) == len(embeddings)
if embeddings[0].shape[0] != self.embedding_dim:
raise RuntimeError(f"Embedding dim. of model ({embeddings[0].shape[0]})"
f" doesn't match embedding dim. in DocumentStore ({self.embedding_dim})."
"Specify the arg `embedding_dim` when initializing ElasticsearchDocumentStore()")
doc_updates = []
for doc, emb in zip(document_batch, embeddings):
update = {"_op_type": "update",
"_index": index,
"_id": doc.id,
"doc": {self.embedding_field: emb.tolist()},
}
doc_updates.append(update)
bulk(self.client, doc_updates, request_timeout=300, refresh=self.refresh_type, headers=headers)
progress_bar.update(batch_size) | [
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lmb-freiburg/netdef_models | 7d3311579cf712b31d05ec29f3dc63df067aa07b | FlowNet3/CSSR-ft-sd/net.py | python | get_env | () | return env | [] | def get_env():
env = FlowNet2f_Environment(net)
return env | [
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] | https://github.com/lmb-freiburg/netdef_models/blob/7d3311579cf712b31d05ec29f3dc63df067aa07b/FlowNet3/CSSR-ft-sd/net.py#L144-L146 | |||
aianaconda/TensorFlow_Engineering_Implementation | cb787e359da9ac5a08d00cd2458fecb4cb5a3a31 | tf2code/Chapter4/code4-10/code4-10-TF2 - 副本.py | python | load_sample | (sample_dir,shuffleflag = True) | 递归读取文件。只支持一级。返回文件名、数值标签、数值对应的标签名 | 递归读取文件。只支持一级。返回文件名、数值标签、数值对应的标签名 | [
"递归读取文件。只支持一级。返回文件名、数值标签、数值对应的标签名"
] | def load_sample(sample_dir,shuffleflag = True):
'''递归读取文件。只支持一级。返回文件名、数值标签、数值对应的标签名'''
print ('loading sample dataset..')
lfilenames = []
labelsnames = []
for (dirpath, dirnames, filenames) in os.walk(sample_dir):#递归遍历文件夹
for filename in filenames: #遍历所有文件名
#print(dirnames)
filename_path = os.sep.join([dirpath, filename])
lfilenames.append(filename_path) #添加文件名
labelsnames.append( dirpath.split('\\')[-1] )#添加文件名对应的标签
lab= list(sorted(set(labelsnames))) #生成标签名称列表
labdict=dict( zip( lab ,list(range(len(lab))) )) #生成字典
labels = [labdict[i] for i in labelsnames]
if shuffleflag == True:
return shuffle(np.asarray( lfilenames),np.asarray( labels)),np.asarray(lab)
else:
return (np.asarray( lfilenames),np.asarray( labels)),np.asarray(lab) | [
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ninuxorg/nodeshot | 2466f0a55f522b2696026f196436ce7ba3f1e5c6 | nodeshot/core/websockets/registrars/nodes.py | python | reconnect | () | reconnect signals | reconnect signals | [
"reconnect",
"signals"
] | def reconnect():
""" reconnect signals """
post_save.connect(node_created_handler, sender=Node)
node_status_changed.connect(node_status_changed_handler)
pre_delete.connect(node_deleted_handler, sender=Node) | [
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joaoventura/pylibui | 2e74db787bfea533f3ae465670963daedcaec344 | pylibui/libui/tab.py | python | uiTabDelete | (tab, index) | Deletes a control from the tab.
:param tab: uiTab
:param index: int
:return: None | Deletes a control from the tab. | [
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Deletes a control from the tab.
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:return: None
"""
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jbuehl/solaredge | e1c199160488c30dc8e4ba3a839afece3c0d7e25 | se/data.py | python | parseOffsetLength | (data) | return {"offset": offset, "length": length, "data": data[8:]} | [] | def parseOffsetLength(data):
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logger.data("offset: %08x", offset)
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MoyuScript/bilibili-api | a40d743089b70a0d0c73207690eb33a38cf28804 | bilibili_api/dynamic.py | python | Dynamic.__init__ | (self, dynamic_id: int, credential: Credential = None) | Args:
dynamic_id (int): 动态 ID
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mongomock/mongomock | 9772f5d7e02ae96b08506abb4004a45a5f388bdf | mongomock/filtering.py | python | iter_key_candidates | (key, doc) | return iter_key_candidates(sub_key, sub_doc) | Get possible subdocuments or lists that are referred to by the key in question
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if doc is None:
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sub_key = '.'.join(key_parts[1:])
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disqus/gutter | d686fa3cd0551cacfc5630c8e7b5fa75e6dcfdf5 | gutter/client/arguments/variables.py | python | Base.to_python | (value) | return value | [] | def to_python(value):
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ralphm/wokkel | 76edbf80f0d314e314e2d4d1510c6e5438a538f7 | wokkel/iwokkel.py | python | IPubSubService.create | (requestor, service, nodeIdentifier) | Called when a node creation request has been received.
@param requestor: The entity the request originated from.
@type requestor: L{JID<twisted.words.protocols.jabber.jid.JID>}
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@return: A deferred that fires with a C{unicode} that represents
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Called when a node creation request has been received.
@param requestor: The entity the request originated from.
@type requestor: L{JID<twisted.words.protocols.jabber.jid.JID>}
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@type service: L{JID<twisted.words.protocols.jabber.jid.JID>}
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@return: A deferred that fires with a C{unicode} that represents
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PacktPublishing/Artificial-Intelligence-with-Python | 03e0f39e3c0949ee219ec91e0145fdabe8ed7810 | Chapter 09/code/easyAI/AI/TT.py | python | TT.lookup | (self, game) | return self.d.get(game.ttentry(), None) | Requests the entry in the table. Returns None if the
entry has not been previously stored in the table. | Requests the entry in the table. Returns None if the
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joxeankoret/diaphora | dcb5a25ac9fe23a285b657e5389cf770de7ac928 | diaphora_ida.py | python | CIDABinDiff.import_selected | (self, items, selected, only_auto) | [] | def import_selected(self, items, selected, only_auto):
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self.import_til()
# Import all the struct and enum definitions
self.import_definitions()
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_api_service_spec.py | python | V1APIServiceSpec.group_priority_minimum | (self, group_priority_minimum) | Sets the group_priority_minimum of this V1APIServiceSpec.
GroupPriorityMininum is the priority this group should have at least. Higher priority means that the group is preferred by clients over lower priority ones. Note that other versions of this group might specify even higher GroupPriorityMininum values such that the whole group gets a higher priority. The primary sort is based on GroupPriorityMinimum, ordered highest number to lowest (20 before 10). The secondary sort is based on the alphabetical comparison of the name of the object. (v1.bar before v1.foo) We'd recommend something like: *.k8s.io (except extensions) at 18000 and PaaSes (OpenShift, Deis) are recommended to be in the 2000s # noqa: E501
:param group_priority_minimum: The group_priority_minimum of this V1APIServiceSpec. # noqa: E501
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:param group_priority_minimum: The group_priority_minimum of this V1APIServiceSpec. # noqa: E501
:type: int
"""
if self.local_vars_configuration.client_side_validation and group_priority_minimum is None: # noqa: E501
raise ValueError("Invalid value for `group_priority_minimum`, must not be `None`") # noqa: E501
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s-leger/archipack | 5a6243bf1edf08a6b429661ce291dacb551e5f8a | pygeos/algorithms.py | python | Angle.normalizePositive | (angle: float) | return angle | * Computes the normalized value of an angle, which is the
* equivalent angle in the range ( -Pi, Pi ].
* @param angle the angle to normalize
* @return an equivalent angle in the range (-Pi, Pi] | * Computes the normalized value of an angle, which is the
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TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e | deep-learning/udacity-deeplearning/face_generation/helper.py | python | get_image | (image_path, width, height, mode) | return np.array(image.convert(mode)) | Read image from image_path
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:param mode: Mode of image
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image = Image.open(image_path)
if image.size != (width, height): # HACK - Check if image is from the CELEBA dataset
# Remove most pixels that aren't part of a face
face_width = face_height = 108
j = (image.size[0] - face_width) // 2
i = (image.size[1] - face_height) // 2
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Refefer/Dampr | 340580afeff23d1f43e23019c7e3a879468aad8d | dampr/base.py | python | BlockMapper.finish | (self) | return () | Mapping is finished. In the case of aggregations, this should yield out
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stopstalk/stopstalk-deployment | 10c3ab44c4ece33ae515f6888c15033db2004bb1 | aws_lambda/spoj_aws_lambda_function/lambda_code/requests/packages/urllib3/filepost.py | python | iter_fields | (fields) | return ((k, v) for k, v in fields) | .. deprecated:: 1.6
Iterate over fields.
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obsolete. Instead, use :func:`iter_field_objects`, which returns
:class:`~urllib3.fields.RequestField` objects.
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"""
.. deprecated:: 1.6
Iterate over fields.
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obsolete. Instead, use :func:`iter_field_objects`, which returns
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Supports list of (k, v) tuples and dicts.
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/wsgiref/handlers.py | python | BaseHandler.send_preamble | (self) | Transmit version/status/date/server, via self._write() | Transmit version/status/date/server, via self._write() | [
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ProgVal/Limnoria | 181e34baf90a8cabc281e8349da6e36e1e558608 | plugins/User/plugin.py | python | User.identify | (self, irc, msg, args, user, password) | <name> <password>
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not in a channel.
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ircdb.users.setUser(user, flush=False)
irc.replySuccess()
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python/mypy | 17850b3bd77ae9efb5d21f656c4e4e05ac48d894 | mypy/dmypy/client.py | python | do_kill | (args: argparse.Namespace) | Kill daemon process with SIGKILL. | Kill daemon process with SIGKILL. | [
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] | def do_kill(args: argparse.Namespace) -> None:
"""Kill daemon process with SIGKILL."""
pid, _ = get_status(args.status_file)
try:
kill(pid)
except OSError as err:
fail(str(err))
else:
print("Daemon killed") | [
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... | https://github.com/python/mypy/blob/17850b3bd77ae9efb5d21f656c4e4e05ac48d894/mypy/dmypy/client.py#L319-L327 | ||
0vercl0k/stuffz | 2ff82f4739d7e215c6140d4987efa8310db39d55 | ollydbg2-udd-files/udd.py | python | breakpoint_type_to_access | (ty) | return ''.join(a if (ty & mask) == mask else '-' for mask, a in flags) | 0x00200000|0x00400000|0x00800000 -> rwx | 0x00200000|0x00400000|0x00800000 -> rwx | [
"0x00200000|0x00400000|0x00800000",
"-",
">",
"rwx"
] | def breakpoint_type_to_access(ty):
'''0x00200000|0x00400000|0x00800000 -> rwx'''
flags = [
(0x00200000, 'r'),
(0x00400000, 'w'),
(0x00800000, 'x')
]
return ''.join(a if (ty & mask) == mask else '-' for mask, a in flags) | [
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0xdea/tactical-exploitation | 231146ac5b4caa44ed73fade0ec29767d28b20b5 | seitan.py | python | get_targets | (args) | return [t.rstrip() for t in args.f] | Get targets from command line or file | Get targets from command line or file | [
"Get",
"targets",
"from",
"command",
"line",
"or",
"file"
] | def get_targets(args):
"""
Get targets from command line or file
"""
if args.t: return [args.t]
return [t.rstrip() for t in args.f] | [
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] | https://github.com/0xdea/tactical-exploitation/blob/231146ac5b4caa44ed73fade0ec29767d28b20b5/seitan.py#L257-L263 | |
rowliny/DiffHelper | ab3a96f58f9579d0023aed9ebd785f4edf26f8af | Tool/SitePackages/nltk/sem/logic.py | python | LogicParser.handle | (self, tok, context) | This method is intended to be overridden for logics that
use different operators or expressions | This method is intended to be overridden for logics that
use different operators or expressions | [
"This",
"method",
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"to",
"be",
"overridden",
"for",
"logics",
"that",
"use",
"different",
"operators",
"or",
"expressions"
] | def handle(self, tok, context):
"""This method is intended to be overridden for logics that
use different operators or expressions"""
if self.isvariable(tok):
return self.handle_variable(tok, context)
elif tok in Tokens.NOT_LIST:
return self.handle_negation(tok, context)
elif tok in Tokens.LAMBDA_LIST:
return self.handle_lambda(tok, context)
elif tok in Tokens.QUANTS:
return self.handle_quant(tok, context)
elif tok == Tokens.OPEN:
return self.handle_open(tok, context) | [
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":",... | https://github.com/rowliny/DiffHelper/blob/ab3a96f58f9579d0023aed9ebd785f4edf26f8af/Tool/SitePackages/nltk/sem/logic.py#L296-L312 | ||
theotherp/nzbhydra | 4b03d7f769384b97dfc60dade4806c0fc987514e | libs/werkzeug/contrib/cache.py | python | BaseCache.get_dict | (self, *keys) | return dict(zip(keys, self.get_many(*keys))) | Like :meth:`get_many` but return a dict::
d = cache.get_dict("foo", "bar")
foo = d["foo"]
bar = d["bar"]
:param keys: The function accepts multiple keys as positional
arguments. | Like :meth:`get_many` but return a dict:: | [
"Like",
":",
"meth",
":",
"get_many",
"but",
"return",
"a",
"dict",
"::"
] | def get_dict(self, *keys):
"""Like :meth:`get_many` but return a dict::
d = cache.get_dict("foo", "bar")
foo = d["foo"]
bar = d["bar"]
:param keys: The function accepts multiple keys as positional
arguments.
"""
return dict(zip(keys, self.get_many(*keys))) | [
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celery/kombu | 853b13f1d018ebfe7ad2d064a3111cac9fcf5383 | kombu/transport/qpid.py | python | Channel.queue_purge | (self, queue, **kwargs) | return self._purge(queue) | Remove all undelivered messages from queue.
Purge all undelivered messages from a queue specified by name. If the
queue does not exist an exception is raised. The queue message
depth is first checked, and then the broker is asked to purge that
number of messages. The integer number of messages requested to be
purged is returned. The actual number of messages purged may be
different than the requested number of messages to purge.
Sometimes delivered messages are asked to be purged, but are not.
This case fails silently, which is the correct behavior when a
message that has been delivered to a different consumer, who has
not ACKed the message, and still has an active session with the
broker. Messages in that case are not safe for purging and will be
retained by the broker. The client is unable to change this
delivery behavior.
Internally, this method relies on :meth:`_purge`.
:param queue: The name of the queue which should have all messages
removed.
:type queue: str
:return: The number of messages requested to be purged.
:rtype: int
:raises: :class:`qpid.messaging.exceptions.NotFound` if the queue
being purged cannot be found. | Remove all undelivered messages from queue. | [
"Remove",
"all",
"undelivered",
"messages",
"from",
"queue",
"."
] | def queue_purge(self, queue, **kwargs):
"""Remove all undelivered messages from queue.
Purge all undelivered messages from a queue specified by name. If the
queue does not exist an exception is raised. The queue message
depth is first checked, and then the broker is asked to purge that
number of messages. The integer number of messages requested to be
purged is returned. The actual number of messages purged may be
different than the requested number of messages to purge.
Sometimes delivered messages are asked to be purged, but are not.
This case fails silently, which is the correct behavior when a
message that has been delivered to a different consumer, who has
not ACKed the message, and still has an active session with the
broker. Messages in that case are not safe for purging and will be
retained by the broker. The client is unable to change this
delivery behavior.
Internally, this method relies on :meth:`_purge`.
:param queue: The name of the queue which should have all messages
removed.
:type queue: str
:return: The number of messages requested to be purged.
:rtype: int
:raises: :class:`qpid.messaging.exceptions.NotFound` if the queue
being purged cannot be found.
"""
return self._purge(queue) | [
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] | https://github.com/celery/kombu/blob/853b13f1d018ebfe7ad2d064a3111cac9fcf5383/kombu/transport/qpid.py#L795-L826 | |
tdamdouni/Pythonista | 3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad | stash/shellista-Transistor1.py | python | Shell.do_ls | (self, line) | list directory contents | list directory contents | [
"list",
"directory",
"contents"
] | def do_ls(self, line):
"""list directory contents"""
files = self.bash(line)
if files is None:
return
elif (not files):
files = ['.']
files_for_path = dict()
for filef in files:
full_file = os.path.normpath(os.path.abspath(filef))
file_name = os.path.basename(full_file)
dir_name = os.path.normpath(os.path.dirname(full_file))
if (not os.path.exists(full_file)):
print("! Error: Skipped, missing -", self.pprint(filef))
continue
if (os.path.isdir(full_file)):
# Need to add this as a key and all the files contained inside it
_dirs = files_for_path.get(full_file, set())
for new_file in os.listdir(full_file):
_dirs.add(os.path.normpath(full_file) + '/' + os.path.normpath(new_file))
files_for_path[full_file] = _dirs
else:
_dirs = files_for_path.get(dir_name, set())
_dirs.add(full_file)
files_for_path[dir_name] = _dirs
# Iterate over the paths, in alphabetical order:
paths = sorted(files_for_path.keys())
cwd = os.path.normpath(os.getcwd())
in_cwd = False
if (cwd in paths):
# Move cwd to the front, mark that it's present
paths.remove(cwd)
paths = [cwd] + paths
in_cwd = True
for i,path in enumerate(paths):
if (i > 0):
print("\n" + self.pprint(path) + "/:")
elif (not in_cwd):
print(self.pprint(path) + "/:")
for filef in sorted(list(files_for_path[path])):
full_file = os.path.normpath(os.path.abspath(filef))
file_name = os.path.basename(full_file)
if (os.path.isdir(full_file)):
print(file_name + "/")
else:
try:
print(file_name + (" (%s)" % (self.sizeof_fmt(os.stat(full_file).st_size))))
except OSError:
print(file_name + " (OSError)") | [
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Nandaka/PixivUtil2 | 3495f52c8889a45af29a0356045f230248abc177 | PixivHelper.py | python | convert_ugoira | (ugoira_file, exportname, ffmpeg, codec, param, extension, image=None) | modified based on https://github.com/tsudoko/ugoira-tools/blob/master/ugoira2webm/ugoira2webm.py | modified based on https://github.com/tsudoko/ugoira-tools/blob/master/ugoira2webm/ugoira2webm.py | [
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"/",
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"/",
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"/",
"ugoira2webm",
"/",
"ugoira2webm",
".",
"py"
] | def convert_ugoira(ugoira_file, exportname, ffmpeg, codec, param, extension, image=None):
''' modified based on https://github.com/tsudoko/ugoira-tools/blob/master/ugoira2webm/ugoira2webm.py '''
# if not os.path.exists(os.path.abspath(ffmpeg)):
# raise PixivException(f"Cannot find ffmpeg executables => {ffmpeg}", errorCode=PixivException.MISSING_CONFIG)
d = tempfile.mkdtemp(prefix="convert_ugoira")
d = d.replace(os.sep, '/')
# Issue #1035
if not os.path.exists(d):
new_temp = os.path.abspath(f"ugoira_{int(datetime.now().timestamp())}")
new_temp = new_temp.replace(os.sep, '/')
os.makedirs(new_temp)
print_and_log("warn", f"Cannot create temp folder at {d}, using current folder as the temp location => {new_temp}")
d = new_temp
# check again if still fail
if not os.path.exists(d):
raise PixivException(f"Cannot create temp folder => {d}", errorCode=PixivException.OTHER_ERROR)
if exportname is None or len(exportname) == 0:
name = '.'.join(ugoira_file.split('.')[:-1])
exportname = f"{os.path.basename(name)}.{extension}"
tempname = d + "/temp." + extension
cmd = f"{ffmpeg} -y -safe 0 -i \"{d}/i.ffconcat\" -c:v {codec} {param} \"{tempname}\""
if codec is None:
cmd = f"{ffmpeg} -y -safe 0 -i \"{d}/i.ffconcat\" {param} \"{tempname}\""
try:
frames = {}
ffconcat = "ffconcat version 1.0\n"
with zipfile.ZipFile(ugoira_file) as f:
f.extractall(d)
with open(d + "/animation.json") as f:
frames = json.load(f)['frames']
for i in frames:
ffconcat += "file " + i['file'] + '\n'
ffconcat += "duration " + str(float(i['delay']) / 1000) + '\n'
# Fix ffmpeg concat demuxer as described in issue #381
# this will increase the frame count, but will fix the last frame timestamp issue.
ffconcat += "file " + frames[-1]['file'] + '\n'
with open(d + "/i.ffconcat", "w") as f:
f.write(ffconcat)
ffmpeg_args = shlex.split(cmd)
get_logger().info(f"[convert_ugoira()] running with cmd: {cmd}")
p = subprocess.Popen(ffmpeg_args, stderr=subprocess.PIPE)
# progress report
chatter = ""
print_and_log('info', f"Start encoding {exportname}")
while p.stderr:
buff = p.stderr.readline().decode('utf-8').rstrip('\n')
chatter += buff
if buff.endswith("\r"):
if _config.verboseOutput:
print(chatter.strip())
elif chatter.find("frame=") > 0 \
or chatter.lower().find("stream") > 0:
print(chatter.strip())
elif chatter.lower().find("error") > 0 \
or chatter.lower().find("could not") > 0 \
or chatter.lower().find("unknown") > 0 \
or chatter.lower().find("invalid") > 0 \
or chatter.lower().find("trailing options") > 0 \
or chatter.lower().find("cannot") > 0 \
or chatter.lower().find("can't") > 0:
print_and_log("error", chatter.strip())
chatter = ""
if len(buff) == 0:
break
ret = p.wait()
if(p.returncode != 0):
print_and_log("error", f"Failed when converting image using {cmd} ==> ffmpeg return exit code={p.returncode}, expected to return 0.")
else:
print_and_log("info", f"- Done with status = {ret}")
shutil.move(tempname, exportname)
# set last-modified and last-accessed timestamp
if image is not None and _config.setLastModified and exportname is not None and os.path.isfile(exportname):
ts = time.mktime(image.worksDateDateTime.timetuple())
os.utime(exportname, (ts, ts))
except FileNotFoundError:
print_and_log("error", f"Failed when converting, ffmpeg command used: {cmd}")
raise
finally:
if os.path.exists(d):
shutil.rmtree(d)
print() | [
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huawei-noah/Pretrained-Language-Model | d4694a134bdfacbaef8ff1d99735106bd3b3372b | PMLM/tokenization.py | python | BasicTokenizer._tokenize_chinese_chars | (self, text) | return "".join(output) | Adds whitespace around any CJK character. | Adds whitespace around any CJK character. | [
"Adds",
"whitespace",
"around",
"any",
"CJK",
"character",
"."
] | def _tokenize_chinese_chars(self, text):
"""Adds whitespace around any CJK character."""
output = []
for char in text:
cp = ord(char)
if self._is_chinese_char(cp):
output.append(" ")
output.append(char)
output.append(" ")
else:
output.append(char)
return "".join(output) | [
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... | https://github.com/huawei-noah/Pretrained-Language-Model/blob/d4694a134bdfacbaef8ff1d99735106bd3b3372b/PMLM/tokenization.py#L252-L263 | |
googleads/googleads-python-lib | b3b42a6deedbe6eaa1c9b30183a9eae3f9e9a7ee | examples/adwords/v201809/campaign_management/add_draft.py | python | main | (client, base_campaign_id) | [] | def main(client, base_campaign_id):
draft_service = client.GetService('DraftService', version='v201809')
draft = {
'baseCampaignId': base_campaign_id,
'draftName': 'Test Draft #%s' % uuid.uuid4()
}
draft_operation = {'operator': 'ADD', 'operand': draft}
draft = draft_service.mutate([draft_operation])['value'][0]
draft_campaign_id = draft['draftCampaignId']
# Once the draft is created, you can modify the draft campaign as if it were a
# real campaign. For example, you may add criteria, adjust bids, or even
# include additional ads. Adding a criteria is shown here.
campaign_criterion_service = client.GetService('CampaignCriterionService',
version='v201809')
criterion = {
'xsi_type': 'Language',
'id': 1003 # Spanish
}
criterion_operation = {
# Make sure to use the draftCampaignId when modifying the virtual draft
# campaign.
'operator': 'ADD',
'operand': {
'campaignId': draft_campaign_id,
'criterion': criterion
}
}
criterion = campaign_criterion_service.mutate([criterion_operation])[
'value'][0]
print('Draft updated to include criteria in campaign with ID %d' %
draft_campaign_id) | [
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... | https://github.com/googleads/googleads-python-lib/blob/b3b42a6deedbe6eaa1c9b30183a9eae3f9e9a7ee/examples/adwords/v201809/campaign_management/add_draft.py#L37-L74 | ||||
apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | twistedcaldav/database.py | python | AbstractADBAPIDatabase.__repr__ | (self) | return "<%s %r>" % (self.__class__.__name__, self.pool) | [] | def __repr__(self):
return "<%s %r>" % (self.__class__.__name__, self.pool) | [
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] | https://github.com/apple/ccs-calendarserver/blob/13c706b985fb728b9aab42dc0fef85aae21921c3/twistedcaldav/database.py#L98-L99 | |||
Theano/Theano | 8fd9203edfeecebced9344b0c70193be292a9ade | theano/_version.py | python | run_command | (commands, args, cwd=None, verbose=False, hide_stderr=False,
env=None) | return stdout, p.returncode | Call the given command(s). | Call the given command(s). | [
"Call",
"the",
"given",
"command",
"(",
"s",
")",
"."
] | def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False,
env=None):
"""Call the given command(s)."""
assert isinstance(commands, list)
p = None
for c in commands:
try:
dispcmd = str([c] + args)
# remember shell=False, so use git.cmd on windows, not just git
p = subprocess.Popen([c] + args, cwd=cwd, env=env,
stdout=subprocess.PIPE,
stderr=(subprocess.PIPE if hide_stderr
else None))
break
except EnvironmentError:
e = sys.exc_info()[1]
if e.errno == errno.ENOENT:
continue
if verbose:
print("unable to run %s" % dispcmd)
print(e)
return None, None
else:
if verbose:
print("unable to find command, tried %s" % (commands,))
return None, None
stdout = p.communicate()[0].strip()
if sys.version_info[0] >= 3:
stdout = stdout.decode()
if p.returncode != 0:
if verbose:
print("unable to run %s (error)" % dispcmd)
print("stdout was %s" % stdout)
return None, p.returncode
return stdout, p.returncode | [
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fonttools/fonttools | 892322aaff6a89bea5927379ec06bc0da3dfb7df | Lib/fontTools/cffLib/specializer.py | python | _GeneralizerDecombinerCommandsMap.vhcurveto | (args) | [] | def vhcurveto(args):
if len(args) < 4 or len(args) % 8 not in {0,1,4,5}: raise ValueError(args)
last_args = None
if len(args) % 2 == 1:
lastStraight = len(args) % 8 == 5
args, last_args = args[:-5], args[-5:]
it = _everyN(args, 4)
try:
while True:
args = next(it)
yield ('rrcurveto', [0, args[0], args[1], args[2], args[3], 0])
args = next(it)
yield ('rrcurveto', [args[0], 0, args[1], args[2], 0, args[3]])
except StopIteration:
pass
if last_args:
args = last_args
if lastStraight:
yield ('rrcurveto', [0, args[0], args[1], args[2], args[3], args[4]])
else:
yield ('rrcurveto', [args[0], 0, args[1], args[2], args[4], args[3]]) | [
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... | https://github.com/fonttools/fonttools/blob/892322aaff6a89bea5927379ec06bc0da3dfb7df/Lib/fontTools/cffLib/specializer.py#L238-L258 | ||||
donnemartin/gitsome | d7c57abc7cb66e9c910a844f15d4536866da3310 | xonsh/tools.py | python | deprecated | (deprecated_in=None, removed_in=None) | return decorated | Parametrized decorator that deprecates a function in a graceful manner.
Updates the decorated function's docstring to mention the version
that deprecation occurred in and the version it will be removed
in if both of these values are passed.
When removed_in is not a release equal to or less than the current
release, call ``warnings.warn`` with details, while raising
``DeprecationWarning``.
When removed_in is a release equal to or less than the current release,
raise an ``AssertionError``.
Parameters
----------
deprecated_in : str
The version number that deprecated this function.
removed_in : str
The version number that this function will be removed in. | Parametrized decorator that deprecates a function in a graceful manner. | [
"Parametrized",
"decorator",
"that",
"deprecates",
"a",
"function",
"in",
"a",
"graceful",
"manner",
"."
] | def deprecated(deprecated_in=None, removed_in=None):
"""Parametrized decorator that deprecates a function in a graceful manner.
Updates the decorated function's docstring to mention the version
that deprecation occurred in and the version it will be removed
in if both of these values are passed.
When removed_in is not a release equal to or less than the current
release, call ``warnings.warn`` with details, while raising
``DeprecationWarning``.
When removed_in is a release equal to or less than the current release,
raise an ``AssertionError``.
Parameters
----------
deprecated_in : str
The version number that deprecated this function.
removed_in : str
The version number that this function will be removed in.
"""
message_suffix = _deprecated_message_suffix(deprecated_in, removed_in)
if not message_suffix:
message_suffix = ""
def decorated(func):
warning_message = "{} has been deprecated".format(func.__name__)
warning_message += message_suffix
@functools.wraps(func)
def wrapped(*args, **kwargs):
_deprecated_error_on_expiration(func.__name__, removed_in)
func(*args, **kwargs)
warnings.warn(warning_message, DeprecationWarning)
wrapped.__doc__ = (
"{}\n\n{}".format(wrapped.__doc__, warning_message)
if wrapped.__doc__
else warning_message
)
return wrapped
return decorated | [
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... | https://github.com/donnemartin/gitsome/blob/d7c57abc7cb66e9c910a844f15d4536866da3310/xonsh/tools.py#L2381-L2424 | |
cea-sec/miasm | 09376c524aedc7920a7eda304d6095e12f6958f4 | miasm/analysis/dse.py | python | DSEEngine.add_handler | (self, addr, callback) | Add a @callback for address @addr before any state update.
The state IS NOT updated after returning from the callback
@addr: int
@callback: func(dse instance) | Add a | [
"Add",
"a"
] | def add_handler(self, addr, callback):
"""Add a @callback for address @addr before any state update.
The state IS NOT updated after returning from the callback
@addr: int
@callback: func(dse instance)"""
self.handler[addr] = callback | [
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] | https://github.com/cea-sec/miasm/blob/09376c524aedc7920a7eda304d6095e12f6958f4/miasm/analysis/dse.py#L243-L248 | ||
PyCQA/pylint | 3fc855f9d0fa8e6410be5a23cf954ffd5471b4eb | pylint/pyreverse/inspector.py | python | IdGeneratorMixIn.generate_id | (self) | return self.id_count | generate a new identifier | generate a new identifier | [
"generate",
"a",
"new",
"identifier"
] | def generate_id(self):
"""generate a new identifier"""
self.id_count += 1
return self.id_count | [
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] | https://github.com/PyCQA/pylint/blob/3fc855f9d0fa8e6410be5a23cf954ffd5471b4eb/pylint/pyreverse/inspector.py#L77-L80 | |
JonnyHaystack/i3-resurrect | 80e3fd6d048fe473c8cb8b2dfb75b1ace3846408 | i3_resurrect/main.py | python | restore_workspace | (workspace, numeric, directory, profile, target) | Restore i3 workspace layout and programs. | Restore i3 workspace layout and programs. | [
"Restore",
"i3",
"workspace",
"layout",
"and",
"programs",
"."
] | def restore_workspace(workspace, numeric, directory, profile, target):
"""
Restore i3 workspace layout and programs.
"""
i3 = i3ipc.Connection()
if workspace is None:
workspace = i3.get_tree().find_focused().workspace().name
directory = util.resolve_directory(directory, profile)
if numeric and not workspace.isdigit():
util.eprint('Invalid workspace number.')
sys.exit(1)
# Get layout name from file.
workspace_layout = layout.read(workspace, directory, profile)
if 'name' in workspace_layout and profile is None:
workspace_name = workspace_layout['name']
else:
workspace_name = workspace
# Switch to the workspace which we are loading.
i3.command(f'workspace --no-auto-back-and-forth "{workspace_name}"')
if target != 'programs_only':
# Load workspace layout.
layout.restore(workspace_name, workspace_layout)
if target != 'layout_only':
# Restore programs.
saved_programs = programs.read(workspace, directory, profile)
programs.restore(workspace_name, saved_programs) | [
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... | https://github.com/JonnyHaystack/i3-resurrect/blob/80e3fd6d048fe473c8cb8b2dfb75b1ace3846408/i3_resurrect/main.py#L91-L123 | ||
Lookyloo/lookyloo | 45ec8efe64d4b549e2598bee0300bb8ffb33ea91 | lookyloo/default/helpers.py | python | get_config | (config_type: str, entry: str, quiet: bool=False) | return sample_config[entry] | Get an entry from the given config_type file. Automatic fallback to the sample file | Get an entry from the given config_type file. Automatic fallback to the sample file | [
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"an",
"entry",
"from",
"the",
"given",
"config_type",
"file",
".",
"Automatic",
"fallback",
"to",
"the",
"sample",
"file"
] | def get_config(config_type: str, entry: str, quiet: bool=False) -> Any:
"""Get an entry from the given config_type file. Automatic fallback to the sample file"""
global configs
if not configs:
load_configs()
if config_type in configs:
if entry in configs[config_type]:
return configs[config_type][entry]
else:
if not quiet:
logger.warning(f'Unable to find {entry} in config file.')
else:
if not quiet:
logger.warning(f'No {config_type} config file available.')
if not quiet:
logger.warning(f'Falling back on sample config, please initialize the {config_type} config file.')
with (get_homedir() / 'config' / f'{config_type}.json.sample').open() as _c:
sample_config = json.load(_c)
return sample_config[entry] | [
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"confi... | https://github.com/Lookyloo/lookyloo/blob/45ec8efe64d4b549e2598bee0300bb8ffb33ea91/lookyloo/default/helpers.py#L61-L79 | |
sympy/sympy | d822fcba181155b85ff2b29fe525adbafb22b448 | sympy/physics/quantum/trace.py | python | Tr.__new__ | (cls, *args) | Construct a Trace object.
Parameters
==========
args = SymPy expression
indices = tuple/list if indices, optional | Construct a Trace object. | [
"Construct",
"a",
"Trace",
"object",
"."
] | def __new__(cls, *args):
""" Construct a Trace object.
Parameters
==========
args = SymPy expression
indices = tuple/list if indices, optional
"""
# expect no indices,int or a tuple/list/Tuple
if (len(args) == 2):
if not isinstance(args[1], (list, Tuple, tuple)):
indices = Tuple(args[1])
else:
indices = Tuple(*args[1])
expr = args[0]
elif (len(args) == 1):
indices = Tuple()
expr = args[0]
else:
raise ValueError("Arguments to Tr should be of form "
"(expr[, [indices]])")
if isinstance(expr, Matrix):
return expr.trace()
elif hasattr(expr, 'trace') and callable(expr.trace):
#for any objects that have trace() defined e.g numpy
return expr.trace()
elif isinstance(expr, Add):
return Add(*[Tr(arg, indices) for arg in expr.args])
elif isinstance(expr, Mul):
c_part, nc_part = expr.args_cnc()
if len(nc_part) == 0:
return Mul(*c_part)
else:
obj = Expr.__new__(cls, Mul(*nc_part), indices )
#this check is needed to prevent cached instances
#being returned even if len(c_part)==0
return Mul(*c_part)*obj if len(c_part) > 0 else obj
elif isinstance(expr, Pow):
if (_is_scalar(expr.args[0]) and
_is_scalar(expr.args[1])):
return expr
else:
return Expr.__new__(cls, expr, indices)
else:
if (_is_scalar(expr)):
return expr
return Expr.__new__(cls, expr, indices) | [
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... | https://github.com/sympy/sympy/blob/d822fcba181155b85ff2b29fe525adbafb22b448/sympy/physics/quantum/trace.py#L110-L161 | ||
oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | opy/pytree.py | python | WildcardPattern.match | (self, node, results=None) | return self.match_seq([node], results) | Does this pattern exactly match a node? | Does this pattern exactly match a node? | [
"Does",
"this",
"pattern",
"exactly",
"match",
"a",
"node?"
] | def match(self, node, results=None):
"""Does this pattern exactly match a node?"""
return self.match_seq([node], results) | [
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")"
] | https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/opy/pytree.py#L628-L630 | |
heynemann/pyccuracy | 0bbe3bcff4d13a6501bf77d5af9457f6a1491ab6 | pyccuracy/drivers/core/selenium_webdriver.py | python | SeleniumWebdriver.radio_uncheck | (self, radio_selector) | return self.checkbox_uncheck(radio_selector) | [] | def radio_uncheck(self, radio_selector):
return self.checkbox_uncheck(radio_selector) | [
"def",
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")",
":",
"return",
"self",
".",
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"(",
"radio_selector",
")"
] | https://github.com/heynemann/pyccuracy/blob/0bbe3bcff4d13a6501bf77d5af9457f6a1491ab6/pyccuracy/drivers/core/selenium_webdriver.py#L134-L135 | |||
MillionIntegrals/vel | f3ce7da64362ad207f40f2c0d58d9300a25df3e8 | vel/api/data/image_ops.py | python | lighting | (im, b, c) | return np.clip((im-mu)*c+mu+b,0.,1.).astype(np.float32) | adjusts image's balance and contrast | adjusts image's balance and contrast | [
"adjusts",
"image",
"s",
"balance",
"and",
"contrast"
] | def lighting(im, b, c):
''' adjusts image's balance and contrast'''
if b==0 and c==1: return im
mu = np.average(im)
return np.clip((im-mu)*c+mu+b,0.,1.).astype(np.float32) | [
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"*... | https://github.com/MillionIntegrals/vel/blob/f3ce7da64362ad207f40f2c0d58d9300a25df3e8/vel/api/data/image_ops.py#L80-L84 | |
JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/db/backends/sqlite3/creation.py | python | DatabaseCreation._create_test_db | (self, verbosity, autoclobber, keepdb=False) | return test_database_name | [] | def _create_test_db(self, verbosity, autoclobber, keepdb=False):
test_database_name = self._get_test_db_name()
if keepdb:
return test_database_name
if not self.is_in_memory_db(test_database_name):
# Erase the old test database
if verbosity >= 1:
print("Destroying old test database for alias %s..." % (
self._get_database_display_str(verbosity, test_database_name),
))
if os.access(test_database_name, os.F_OK):
if not autoclobber:
confirm = input(
"Type 'yes' if you would like to try deleting the test "
"database '%s', or 'no' to cancel: " % test_database_name
)
if autoclobber or confirm == 'yes':
try:
os.remove(test_database_name)
except Exception as e:
sys.stderr.write("Got an error deleting the old test database: %s\n" % e)
sys.exit(2)
else:
print("Tests cancelled.")
sys.exit(1)
return test_database_name | [
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IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/importlib/_bootstrap.py | python | _install | (sys_module, _imp_module) | Install importlib as the implementation of import. | Install importlib as the implementation of import. | [
"Install",
"importlib",
"as",
"the",
"implementation",
"of",
"import",
"."
] | def _install(sys_module, _imp_module):
"""Install importlib as the implementation of import."""
_setup(sys_module, _imp_module)
supported_loaders = _get_supported_file_loaders()
sys.path_hooks.extend([FileFinder.path_hook(*supported_loaders)])
sys.meta_path.append(BuiltinImporter)
sys.meta_path.append(FrozenImporter)
if _os.__name__ == 'nt':
sys.meta_path.append(WindowsRegistryFinder)
sys.meta_path.append(PathFinder) | [
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"... | https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/importlib/_bootstrap.py#L2452-L2461 |
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