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rail-berkeley/d4rl | 4aff6f8c46f62f9a57f79caa9287efefa45b6688 | d4rl/carla/data_collection_town.py | python | RoamingAgent.run_step | (self) | return control, traffic_light_color | Execute one step of navigation.
:return: carla.VehicleControl | Execute one step of navigation.
:return: carla.VehicleControl | [
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] | def run_step(self):
"""
Execute one step of navigation.
:return: carla.VehicleControl
"""
# is there an obstacle in front of us?
hazard_detected = False
# retrieve relevant elements for safe navigation, i.e.: traffic lights and other vehicles
actor_list = self._world.get_actors()
vehicle_list = actor_list.filter("*vehicle*")
lights_list = actor_list.filter("*traffic_light*")
# check possible obstacles
vehicle_state, vehicle = self._is_vehicle_hazard(vehicle_list)
if vehicle_state:
self._state = AgentState.BLOCKED_BY_VEHICLE
hazard_detected = True
# check for the state of the traffic lights
traffic_light_color = self._is_light_red(lights_list)
if traffic_light_color == 'RED' and self._follow_traffic_lights:
self._state = AgentState.BLOCKED_RED_LIGHT
hazard_detected = True
if hazard_detected:
control = self.emergency_stop()
else:
self._state = AgentState.NAVIGATING
# standard local planner behavior
control = self._local_planner.run_step()
return control, traffic_light_color | [
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fatchord/WaveRNN | 3595219b2f2f5353f0867a7bb59abcb15aba8831 | utils/paths.py | python | Paths.get_voc_named_optim | (self, name) | return self.voc_checkpoints/f'{name}_optim.pyt' | Gets the path for the optimizer state in a named voc checkpoint. | Gets the path for the optimizer state in a named voc checkpoint. | [
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"""Gets the path for the optimizer state in a named voc checkpoint."""
return self.voc_checkpoints/f'{name}_optim.pyt' | [
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ambakick/Person-Detection-and-Tracking | f925394ac29b5cf321f1ce89a71b193381519a0b | meta_architectures/ssd_meta_arch.py | python | SSDMetaArch.restore_map | (self,
fine_tune_checkpoint_type='detection',
load_all_detection_checkpoint_vars=False) | return variables_to_restore | Returns a map of variables to load from a foreign checkpoint.
See parent class for details.
Args:
fine_tune_checkpoint_type: whether to restore from a full detection
checkpoint (with compatible variable names) or to restore from a
classification checkpoint for initialization prior to training.
Valid values: `detection`, `classification`. Default 'detection'.
load_all_detection_checkpoint_vars: whether to load all variables (when
`fine_tune_checkpoint_type='detection'`). If False, only variables
within the appropriate scopes are included. Default False.
Returns:
A dict mapping variable names (to load from a checkpoint) to variables in
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Raises:
ValueError: if fine_tune_checkpoint_type is neither `classification`
nor `detection`. | Returns a map of variables to load from a foreign checkpoint. | [
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fine_tune_checkpoint_type='detection',
load_all_detection_checkpoint_vars=False):
"""Returns a map of variables to load from a foreign checkpoint.
See parent class for details.
Args:
fine_tune_checkpoint_type: whether to restore from a full detection
checkpoint (with compatible variable names) or to restore from a
classification checkpoint for initialization prior to training.
Valid values: `detection`, `classification`. Default 'detection'.
load_all_detection_checkpoint_vars: whether to load all variables (when
`fine_tune_checkpoint_type='detection'`). If False, only variables
within the appropriate scopes are included. Default False.
Returns:
A dict mapping variable names (to load from a checkpoint) to variables in
the model graph.
Raises:
ValueError: if fine_tune_checkpoint_type is neither `classification`
nor `detection`.
"""
if fine_tune_checkpoint_type not in ['detection', 'classification']:
raise ValueError('Not supported fine_tune_checkpoint_type: {}'.format(
fine_tune_checkpoint_type))
variables_to_restore = {}
for variable in tf.global_variables():
var_name = variable.op.name
if (fine_tune_checkpoint_type == 'detection' and
load_all_detection_checkpoint_vars):
variables_to_restore[var_name] = variable
else:
if var_name.startswith(self._extract_features_scope):
if fine_tune_checkpoint_type == 'classification':
var_name = (
re.split('^' + self._extract_features_scope + '/',
var_name)[-1])
variables_to_restore[var_name] = variable
return variables_to_restore | [
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out0fmemory/GoAgent-Always-Available | c4254984fea633ce3d1893fe5901debd9f22c2a9 | server/lib/google/appengine/_internal/antlr3/streams.py | python | ANTLRFileStream.__init__ | (self, fileName, encoding=None) | @param fileName The path to the file to be opened. The file will be
opened with mode 'rb'.
@param encoding If you set the optional encoding argument, then the
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facebookincubator/FCR | d5a629d062060cfa859b848ff54867e7450c04fd | external/common/fb303/py/gen-py/fb303_asyncio/fb303/FacebookService.py | python | Client.aliveSince | (self, ) | return fut | Returns the unix time that the server has been running since | Returns the unix time that the server has been running since | [
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"""
Returns the unix time that the server has been running since
"""
self._seqid += 1
fut = self._futures[self._seqid] = asyncio.Future(loop=self._loop)
self.send_aliveSince()
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quantopian/empyrical | 40f61b4f229df10898d46d08f7b1bdc543c0f99c | versioneer.py | python | render | (pieces, style) | return {"version": rendered, "full-revisionid": pieces["long"],
"dirty": pieces["dirty"], "error": None} | Render the given version pieces into the requested style. | Render the given version pieces into the requested style. | [
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"""Render the given version pieces into the requested style."""
if pieces["error"]:
return {"version": "unknown",
"full-revisionid": pieces.get("long"),
"dirty": None,
"error": pieces["error"]}
if not style or style == "default":
style = "pep440" # the default
if style == "pep440":
rendered = render_pep440(pieces)
elif style == "pep440-pre":
rendered = render_pep440_pre(pieces)
elif style == "pep440-post":
rendered = render_pep440_post(pieces)
elif style == "pep440-old":
rendered = render_pep440_old(pieces)
elif style == "git-describe":
rendered = render_git_describe(pieces)
elif style == "git-describe-long":
rendered = render_git_describe_long(pieces)
else:
raise ValueError("unknown style '%s'" % style)
return {"version": rendered, "full-revisionid": pieces["long"],
"dirty": pieces["dirty"], "error": None} | [
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/importlib/_bootstrap_external.py | python | _path_is_mode_type | (path, mode) | return (stat_info.st_mode & 0o170000) == mode | Test whether the path is the specified mode type. | Test whether the path is the specified mode type. | [
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"""Test whether the path is the specified mode type."""
try:
stat_info = _path_stat(path)
except OSError:
return False
return (stat_info.st_mode & 0o170000) == mode | [
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topydo/topydo | 57d7577c987515d4b49d5500f666da29080ca3c2 | topydo/ui/CLIApplicationBase.py | python | error | (p_string) | Writes an error on the standard error. | Writes an error on the standard error. | [
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etetoolkit/ete | 2b207357dc2a40ccad7bfd8f54964472c72e4726 | ete3/nexml/_nexml.py | python | AAMatrixSeqRow.hasContent_ | (self) | [] | def hasContent_(self):
if (
self.meta or
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mandiant/capa | c0851fc643793c012f5dd764482133c25c3216c8 | capa/rules.py | python | RuleSet._index_rules_by_feature | (rules) | return (easy_rules_by_feature, hard_rules) | split the given rules into two structures:
- "easy rules" are indexed by feature,
such that you can quickly find the rules that contain a given feature.
- "hard rules" are those that contain substring/regex/bytes features or match statements.
these continue to be ordered topologically.
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at this time, a rule evaluator can't do anything special with
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rule, in topological order. | split the given rules into two structures:
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- "hard rules" are those that contain substring/regex/bytes features or match statements.
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split the given rules into two structures:
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such that you can quickly find the rules that contain a given feature.
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these continue to be ordered topologically.
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at this time, a rule evaluator can't do anything special with
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"""
# we'll do a couple phases:
#
# 1. recursively visit all nodes in all rules,
# a. indexing all features
# b. recording the types of features found per rule
# 2. compute the easy and hard rule sets
# 3. remove hard rules from the rules-by-feature index
# 4. construct the topologically ordered list of hard rules
rules_with_easy_features: Set[str] = set()
rules_with_hard_features: Set[str] = set()
rules_by_feature: Dict[Feature, Set[str]] = collections.defaultdict(set)
def rec(rule_name: str, node: Union[Feature, Statement]):
"""
walk through a rule's logic tree, indexing the easy and hard rules,
and the features referenced by easy rules.
"""
if isinstance(
node,
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# these are the "hard features"
# substring: scanning feature
capa.features.common.Substring,
# regex: scanning feature
capa.features.common.Regex,
# bytes: scanning feature
capa.features.common.Bytes,
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capa.features.common.MatchedRule,
),
):
# hard feature: requires scan or match lookup
rules_with_hard_features.add(rule_name)
elif isinstance(node, capa.features.common.Feature):
# easy feature: hash lookup
rules_with_easy_features.add(rule_name)
rules_by_feature[node].add(rule_name)
elif isinstance(node, (ceng.Not)):
# `not:` statements are tricky to deal with.
#
# first, features found under a `not:` should not be indexed,
# because they're not wanted to be found.
# second, `not:` can be nested under another `not:`, or two, etc.
# third, `not:` at the root or directly under an `or:`
# means the rule will match against *anything* not specified there,
# which is a difficult set of things to compute and index.
#
# so, if a rule has a `not:` statement, its hard.
# as of writing, this is an uncommon statement, with only 6 instances in 740 rules.
rules_with_hard_features.add(rule_name)
elif isinstance(node, (ceng.Some)) and node.count == 0:
# `optional:` and `0 or more:` are tricky to deal with.
#
# when a subtree is optional, it may match, but not matching
# doesn't have any impact either.
# now, our rule authors *should* not put this under `or:`
# and this is checked by the linter,
# but this could still happen (e.g. private rule set without linting)
# and would be hard to trace down.
#
# so better to be safe than sorry and consider this a hard case.
rules_with_hard_features.add(rule_name)
elif isinstance(node, (ceng.Range)) and node.min == 0:
# `count(foo): 0 or more` are tricky to deal with.
# because the min is 0,
# this subtree *can* match just about any feature
# (except the given one)
# which is a difficult set of things to compute and index.
rules_with_hard_features.add(rule_name)
elif isinstance(node, (ceng.Range)):
rec(rule_name, node.child)
elif isinstance(node, (ceng.And, ceng.Or, ceng.Some)):
for child in node.children:
rec(rule_name, child)
elif isinstance(node, ceng.Statement):
# unhandled type of statement.
# this should only happen if a new subtype of `Statement`
# has since been added to capa.
#
# ideally, we'd like to use mypy for exhaustiveness checking
# for all the subtypes of `Statement`.
# but, as far as i can tell, mypy does not support this type
# of checking.
#
# in a way, this makes some intuitive sense:
# the set of subtypes of type A is unbounded,
# because any user might come along and create a new subtype B,
# so mypy can't reason about this set of types.
assert False, f"Unhandled value: {node} ({type(node).__name__})"
else:
# programming error
assert_never(node)
for rule in rules:
rule_name = rule.meta["name"]
root = rule.statement
rec(rule_name, root)
# if a rule has a hard feature,
# dont consider it easy, and therefore,
# don't index any of its features.
#
# otherwise, its an easy rule, and index its features
for rules_with_feature in rules_by_feature.values():
rules_with_feature.difference_update(rules_with_hard_features)
easy_rules_by_feature = rules_by_feature
# `rules` is already topologically ordered,
# so extract our hard set into the topological ordering.
hard_rules = []
for rule in rules:
if rule.meta["name"] in rules_with_hard_features:
hard_rules.append(rule.meta["name"])
return (easy_rules_by_feature, hard_rules) | [
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aws-samples/aws-kube-codesuite | ab4e5ce45416b83bffb947ab8d234df5437f4fca | src/kubernetes/client/models/v1_secret_volume_source.py | python | V1SecretVolumeSource.default_mode | (self, default_mode) | Sets the default_mode of this V1SecretVolumeSource.
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:param default_mode: The default_mode of this V1SecretVolumeSource.
:type: int | Sets the default_mode of this V1SecretVolumeSource.
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"""
Sets the default_mode of this V1SecretVolumeSource.
Optional: mode bits to use on created files by default. Must be a value between 0 and 0777. Defaults to 0644. Directories within the path are not affected by this setting. This might be in conflict with other options that affect the file mode, like fsGroup, and the result can be other mode bits set.
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self._default_mode = default_mode | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/html5lib/filters/sanitizer.py | python | Filter.__init__ | (self,
source,
allowed_elements=allowed_elements,
allowed_attributes=allowed_attributes,
allowed_css_properties=allowed_css_properties,
allowed_css_keywords=allowed_css_keywords,
allowed_svg_properties=allowed_svg_properties,
allowed_protocols=allowed_protocols,
allowed_content_types=allowed_content_types,
attr_val_is_uri=attr_val_is_uri,
svg_attr_val_allows_ref=svg_attr_val_allows_ref,
svg_allow_local_href=svg_allow_local_href) | [] | def __init__(self,
source,
allowed_elements=allowed_elements,
allowed_attributes=allowed_attributes,
allowed_css_properties=allowed_css_properties,
allowed_css_keywords=allowed_css_keywords,
allowed_svg_properties=allowed_svg_properties,
allowed_protocols=allowed_protocols,
allowed_content_types=allowed_content_types,
attr_val_is_uri=attr_val_is_uri,
svg_attr_val_allows_ref=svg_attr_val_allows_ref,
svg_allow_local_href=svg_allow_local_href):
super(Filter, self).__init__(source)
self.allowed_elements = allowed_elements
self.allowed_attributes = allowed_attributes
self.allowed_css_properties = allowed_css_properties
self.allowed_css_keywords = allowed_css_keywords
self.allowed_svg_properties = allowed_svg_properties
self.allowed_protocols = allowed_protocols
self.allowed_content_types = allowed_content_types
self.attr_val_is_uri = attr_val_is_uri
self.svg_attr_val_allows_ref = svg_attr_val_allows_ref
self.svg_allow_local_href = svg_allow_local_href | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/idlelib/OutputWindow.py | python | OutputWindow.write | (self, s, tags=(), mark="insert") | [] | def write(self, s, tags=(), mark="insert"):
if isinstance(s, (bytes, bytes)):
s = s.decode(IOBinding.encoding, "replace")
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Nuitka/Nuitka | 39262276993757fa4e299f497654065600453fc9 | nuitka/build/inline_copy/lib/scons-2.3.2/SCons/Variables/PathVariable.py | python | _PathVariableClass.PathExists | (self, key, val, env) | validator to check if Path exists | validator to check if Path exists | [
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] | def PathExists(self, key, val, env):
"""validator to check if Path exists"""
if not os.path.exists(val):
m = 'Path for option %s does not exist: %s'
raise SCons.Errors.UserError(m % (key, val)) | [
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gwpy/gwpy | 82becd78d166a32985cb657a54d0d39f6a207739 | gwpy/timeseries/timeseries.py | python | TimeSeries.csd_spectrogram | (self, other, stride, fftlength=None, overlap=0,
window='hann', nproc=1, **kwargs) | return spectral.average_spectrogram(
(self, other),
spectral.csd,
stride,
fftlength=fftlength,
overlap=overlap,
window=window,
nproc=nproc,
**kwargs
) | Calculate the cross spectral density spectrogram of this
`TimeSeries` with 'other'.
Parameters
----------
other : `~gwpy.timeseries.TimeSeries`
second time-series for cross spectral density calculation
stride : `float`
number of seconds in single PSD (column of spectrogram).
fftlength : `float`
number of seconds in single FFT.
overlap : `float`, optional
number of seconds of overlap between FFTs, defaults to the
recommended overlap for the given window (if given), or 0
window : `str`, `numpy.ndarray`, optional
window function to apply to timeseries prior to FFT,
see :func:`scipy.signal.get_window` for details on acceptable
formats
nproc : `int`
maximum number of independent frame reading processes, default
is set to single-process file reading.
Returns
-------
spectrogram : `~gwpy.spectrogram.Spectrogram`
time-frequency cross spectrogram as generated from the
two input time-series. | Calculate the cross spectral density spectrogram of this
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window='hann', nproc=1, **kwargs):
"""Calculate the cross spectral density spectrogram of this
`TimeSeries` with 'other'.
Parameters
----------
other : `~gwpy.timeseries.TimeSeries`
second time-series for cross spectral density calculation
stride : `float`
number of seconds in single PSD (column of spectrogram).
fftlength : `float`
number of seconds in single FFT.
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number of seconds of overlap between FFTs, defaults to the
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maximum number of independent frame reading processes, default
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time-frequency cross spectrogram as generated from the
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"""
return spectral.average_spectrogram(
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reahl/reahl | 86aac47c3a9b5b98e9f77dad4939034a02d54d46 | reahl-component/reahl/component/dbutils.py | python | SystemControl.initialise_database | (self) | Ensures a new clean database exists, with a schema created. This drops an existing database if one is present. | Ensures a new clean database exists, with a schema created. This drops an existing database if one is present. | [
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self.drop_database()
self.create_database()
self.connect()
try:
self.create_db_tables()
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mcfletch/pyopengl | 02d11dad9ff18e50db10e975c4756e17bf198464 | OpenGL/GLES2/NV/conservative_raster_pre_snap_triangles.py | python | glInitConservativeRasterPreSnapTrianglesNV | () | return extensions.hasGLExtension( _EXTENSION_NAME ) | Return boolean indicating whether this extension is available | Return boolean indicating whether this extension is available | [
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'''Return boolean indicating whether this extension is available'''
from OpenGL import extensions
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weecology/retriever | e5ba505f7b9958c70e60155f3c5495899da27e7e | retriever/lib/engine.py | python | Engine.create_raw_data_dir | (self, path=None) | Check to see if the archive directory exists and creates it if
necessary. | Check to see if the archive directory exists and creates it if
necessary. | [
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"""Check to see if the archive directory exists and creates it if
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path = self.format_data_dir()
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/optparse.py | python | OptionParser.set_default | (self, dest, value) | [] | def set_default(self, dest, value):
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los-cocos/cocos | 3b47281f95d6ee52bb2a357a767f213e670bd601 | cocos/gl_framebuffer_object.py | python | FramebufferObject.__del__ | (self) | Delete the framebuffer from the GPU memory | Delete the framebuffer from the GPU memory | [
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"""Delete the framebuffer from the GPU memory"""
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google/spatial-media | 000cc7e29cd1d906ff7fd393550f462096406630 | spatialmedia/metadata_utils.py | python | spherical_uuid | (metadata) | return uuid_leaf | Constructs a uuid containing spherical metadata.
Args:
metadata: String, xml to inject in spherical tag.
Returns:
uuid_leaf: a box containing spherical metadata. | Constructs a uuid containing spherical metadata. | [
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] | def spherical_uuid(metadata):
"""Constructs a uuid containing spherical metadata.
Args:
metadata: String, xml to inject in spherical tag.
Returns:
uuid_leaf: a box containing spherical metadata.
"""
uuid_leaf = mpeg.Box()
assert(len(SPHERICAL_UUID_ID) == 16)
uuid_leaf.name = mpeg.constants.TAG_UUID
uuid_leaf.header_size = 8
uuid_leaf.content_size = 0
uuid_leaf.contents = SPHERICAL_UUID_ID + metadata.encode("utf-8")
uuid_leaf.content_size = len(uuid_leaf.contents)
return uuid_leaf | [
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gmarull/asyncqt | 5cb38a417608e04256db4bc7eb16dc4db88f7db0 | asyncqt/_windows.py | python | _ProactorEventLoop._process_events | (self, events) | Process events from proactor. | Process events from proactor. | [
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value = callback(transferred, key, ov)
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self._logger.warning('Event callback failed', exc_info=sys.exc_info())
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pip/_vendor/requests/packages/chardet/utf8prober.py | python | UTF8Prober.get_charset_name | (self) | return "utf-8" | [] | def get_charset_name(self):
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ekonda/sketal | 92a829a02973e8822c99c95ca316f85bf20afa3e | plugins/multiuser/chat_random_pair.py | python | PairPlugin.__init__ | (self, *commands, prefixes=None, strict=False, text="❤ Любит ❤ "): | Answers with 2 users separated by text `text` defaults to `❤ Любит ❤ `. | Answers with 2 users separated by text `text` defaults to `❤ Любит ❤ `. | [
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"""Answers with 2 users separated by text `text` defaults to `❤ Любит ❤ `."""
if not commands:
commands = ("кто кого",)
super().__init__(*commands, prefixes=prefixes, strict=strict)
self.text = text
self.set_description() | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/numpy/ma/core.py | python | MaskedArray.__setitem__ | (self, indx, value) | return | x.__setitem__(i, y) <==> x[i]=y
Set item described by index. If value is masked, masks those
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"""
x.__setitem__(i, y) <==> x[i]=y
Set item described by index. If value is masked, masks those
locations.
"""
if self is masked:
raise MaskError('Cannot alter the masked element.')
_data = self._data
_mask = self._mask
if isinstance(indx, basestring):
_data[indx] = value
if _mask is nomask:
self._mask = _mask = make_mask_none(self.shape, self.dtype)
_mask[indx] = getmask(value)
return
_dtype = _data.dtype
nbfields = len(_dtype.names or ())
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if not self._isfield:
self._sharedmask = False
return
# Get the _data part of the new value
dval = value
# Get the _mask part of the new value
mval = getattr(value, '_mask', nomask)
if nbfields and mval is nomask:
mval = tuple([False] * nbfields)
if _mask is nomask:
# Set the data, then the mask
_data[indx] = dval
if mval is not nomask:
_mask = self._mask = make_mask_none(self.shape, _dtype)
_mask[indx] = mval
elif not self._hardmask:
# Unshare the mask if necessary to avoid propagation
# We want to remove the unshare logic from this place in the
# future. Note that _sharedmask has lots of false positives.
if not self._isfield:
if self._sharedmask and not (
# If no one else holds a reference (we have two
# references (_mask and self._mask) -- add one for
# getrefcount) and the array owns its own data
# copying the mask should do nothing.
(sys.getrefcount(_mask) == 3) and _mask.flags.owndata):
# 2016.01.15 -- v1.11.0
warnings.warn(
"setting an item on a masked array which has a shared "
"mask will not copy the mask and also change the "
"original mask array in the future.\n"
"Check the NumPy 1.11 release notes for more "
"information.",
MaskedArrayFutureWarning, stacklevel=2)
self.unshare_mask()
_mask = self._mask
# Set the data, then the mask
_data[indx] = dval
_mask[indx] = mval
elif hasattr(indx, 'dtype') and (indx.dtype == MaskType):
indx = indx * umath.logical_not(_mask)
_data[indx] = dval
else:
if nbfields:
err_msg = "Flexible 'hard' masks are not yet supported."
raise NotImplementedError(err_msg)
mindx = mask_or(_mask[indx], mval, copy=True)
dindx = self._data[indx]
if dindx.size > 1:
np.copyto(dindx, dval, where=~mindx)
elif mindx is nomask:
dindx = dval
_data[indx] = dindx
_mask[indx] = mindx
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leancloud/satori | 701caccbd4fe45765001ca60435c0cb499477c03 | satori-rules/plugin/libs/urllib3/packages/rfc3986/_mixin.py | python | URIMixin.authority_is_valid | (self, require=False) | return validators.authority_is_valid(
self.authority,
host=self.host,
require=require,
) | Determine if the authority component is valid.
.. deprecated:: 1.1.0
Use the :class:`~rfc3986.validators.Validator` object instead.
:param bool require:
Set to ``True`` to require the presence of this component.
:returns:
``True`` if the authority is valid. ``False`` otherwise.
:rtype:
bool | Determine if the authority component is valid. | [
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] | def authority_is_valid(self, require=False):
"""Determine if the authority component is valid.
.. deprecated:: 1.1.0
Use the :class:`~rfc3986.validators.Validator` object instead.
:param bool require:
Set to ``True`` to require the presence of this component.
:returns:
``True`` if the authority is valid. ``False`` otherwise.
:rtype:
bool
"""
warnings.warn("Please use rfc3986.validators.Validator instead. "
"This method will be eventually removed.",
DeprecationWarning)
try:
self.authority_info()
except exc.InvalidAuthority:
return False
return validators.authority_is_valid(
self.authority,
host=self.host,
require=require,
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limodou/uliweb | 8bc827fa6bf7bf58aa8136b6c920fe2650c52422 | uliweb/lib/werkzeug/wsgi.py | python | pop_path_info | (environ, charset='utf-8', errors='replace') | return to_unicode(rv, charset, errors, allow_none_charset=True) | Removes and returns the next segment of `PATH_INFO`, pushing it onto
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If the `charset` is set to `None` a bytestring is returned.
If there are empty segments (``'/foo//bar``) these are ignored but
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>>> env = {'SCRIPT_NAME': '/foo', 'PATH_INFO': '/a/b'}
>>> pop_path_info(env)
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>>> env['SCRIPT_NAME']
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>>> pop_path_info(env)
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>>> env['SCRIPT_NAME']
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.. versionadded:: 0.5
.. versionchanged:: 0.9
The path is now decoded and a charset and encoding
parameter can be provided.
:param environ: the WSGI environment that is modified. | Removes and returns the next segment of `PATH_INFO`, pushing it onto
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"""Removes and returns the next segment of `PATH_INFO`, pushing it onto
`SCRIPT_NAME`. Returns `None` if there is nothing left on `PATH_INFO`.
If the `charset` is set to `None` a bytestring is returned.
If there are empty segments (``'/foo//bar``) these are ignored but
properly pushed to the `SCRIPT_NAME`:
>>> env = {'SCRIPT_NAME': '/foo', 'PATH_INFO': '/a/b'}
>>> pop_path_info(env)
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>>> env['SCRIPT_NAME']
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>>> pop_path_info(env)
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>>> env['SCRIPT_NAME']
'/foo/a/b'
.. versionadded:: 0.5
.. versionchanged:: 0.9
The path is now decoded and a charset and encoding
parameter can be provided.
:param environ: the WSGI environment that is modified.
"""
path = environ.get('PATH_INFO')
if not path:
return None
script_name = environ.get('SCRIPT_NAME', '')
# shift multiple leading slashes over
old_path = path
path = path.lstrip('/')
if path != old_path:
script_name += '/' * (len(old_path) - len(path))
if '/' not in path:
environ['PATH_INFO'] = ''
environ['SCRIPT_NAME'] = script_name + path
rv = wsgi_get_bytes(path)
else:
segment, path = path.split('/', 1)
environ['PATH_INFO'] = '/' + path
environ['SCRIPT_NAME'] = script_name + segment
rv = wsgi_get_bytes(segment)
return to_unicode(rv, charset, errors, allow_none_charset=True) | [
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pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/pip-7.1.2-py3.3.egg/pip/_vendor/html5lib/tokenizer.py | python | HTMLTokenizer.__iter__ | (self) | This is where the magic happens.
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"""
self.tokenQueue = deque([])
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while self.tokenQueue:
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OpenEndedGroup/Field | 4f7c8edfb01bb0ccc927b78d3c500f018a4ae37c | Contents/lib/python/xml/sax/xmlreader.py | python | Locator.getLineNumber | (self) | return -1 | Return the line number where the current event ends. | Return the line number where the current event ends. | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-windows/x86/PIL/WebPImagePlugin.py | python | WebPImageFile._reset | (self, reset=True) | [] | def _reset(self, reset=True):
if reset:
self._decoder.reset()
self.__physical_frame = 0
self.__loaded = -1
self.__timestamp = 0 | [
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FreeOpcUa/python-opcua | 67f15551884d7f11659d52483e7b932999ca3a75 | opcua/crypto/uacrypto.py | python | p_sha1 | (secret, seed, sizes=()) | return tuple(parts) | Derive one or more keys from secret and seed.
(See specs part 6, 6.7.5 and RFC 2246 - TLS v1.0)
Lengths of keys will match sizes argument | Derive one or more keys from secret and seed.
(See specs part 6, 6.7.5 and RFC 2246 - TLS v1.0)
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"""
Derive one or more keys from secret and seed.
(See specs part 6, 6.7.5 and RFC 2246 - TLS v1.0)
Lengths of keys will match sizes argument
"""
full_size = 0
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full_size += size
result = b''
accum = seed
while len(result) < full_size:
accum = hmac_sha1(secret, accum)
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parts = []
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dmlc/dgl | 8d14a739bc9e446d6c92ef83eafe5782398118de | examples/pytorch/gatv2/train.py | python | EarlyStopping.save_checkpoint | (self, model) | Saves model when validation loss decrease. | Saves model when validation loss decrease. | [
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tdamdouni/Pythonista | 3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad | markdown/markdown2pdf/reportlab/pdfbase/pdfdoc.py | python | Annotation.cvtdict | (self, d, escape=1) | return d | transform dict args from python form to pdf string rep as needed | transform dict args from python form to pdf string rep as needed | [
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"""transform dict args from python form to pdf string rep as needed"""
Rect = d["Rect"]
if not isStr(Rect):
d["Rect"] = PDFArray(Rect)
d["Contents"] = PDFString(d["Contents"],escape)
return d | [
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xlwings/xlwings | 44395c4d18b46f76249279b7d0965e640291499c | xlwings/main.py | python | Picture.name | (self) | return self.impl.name | Returns or sets the name of the picture.
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"""
Returns or sets the name of the picture.
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tuckerbalch/QSTK | 4981506c37227a72404229d5e1e0887f797a5d57 | Legacy/simulator/Simulator.py | python | Simulator.run | (self) | @summary: Run the simulation | [] | def run(self):
'''
@summary: Run the simulation
'''
optimizer= Optimizer.Optimizer(self.listOfStocks)
#optimizer= curveFittingOptimizer.Optimizer(self.listOfStocks)
timestamps= list(self.dataAccess.getTimestampArray())
portfolioValList= list()
ctr=0
while (timestamps[ctr]< self.startTime):
ctr+=1
#while loop done
self.currTimestamp = timestamps[ctr] #self.startTime
ctr2= ctr
while (timestamps[ctr2]< self.endTime):
ctr2+=1
if (ctr2>= len(timestamps)):
break
#while loop done
if (ctr2>= len (timestamps)):
self.endTime= timestamps[ctr2-1]
else:
self.endTime= timestamps[ctr2]
if timersActive:
print "Simulation timer started at "+ str(self.currTimestamp)
totalTime = time.time()
cycTime = time.clock()
# self.strategyData.currTimestamp = self.currTimestamp
i=1
while self.currTimestamp < self.endTime and self.currTimestamp < time.time(): # and self.currTimestamp < self.strategyData.timestampIndex[len(self.strategyData.timestampIndex)-2]: ************POSSIBLE BUG***** JUST TRYING OUT
# While not yet reached the end timestamp AND not yet caught up to present AND not yet reached the end of the data
# execute the existing orders, then run the strategy and add the new orders
beforeExec=time.clock()
self.execute()
afterExec= time.clock()
# self.addOrders(self.strategy(self.portfolio,self.position,self.currTimestamp,self.strategyData))
# self.addOrders(optimizer.execute(self.portfolio,self.position,self.currTimestamp,self.strategyData))
beforeAddOrders= time.clock()
self.addOrders(optimizer.execute(self.portfolio,self.position,self.currTimestamp,self.strategyData, self.dataAccess))
afterAddOrders= time.clock()
if noisy or timersActive:
print '' #newline
if mtm:
#portValue = self.portfolio.currCash + self.strategyData.calculatePortValue(self.portfolio.currStocks,self.currTimestamp)
portValue= float (0.0)
print "| %i %.2f |"%(self.currTimestamp,portValue) + " Value from portfolio class: " + str (self.portfolio.calcPortfolioValue(self.currTimestamp, self.dataAccess))
if timersActive and not noisy:
print "Strategy at %i took %.4f secs"%(self.currTimestamp,(time.clock()-cycTime))
i+=1
cycTime = time.clock()
if noisy and not timersActive:
portValue = (self.portfolio.calcPortfolioValue(self.currTimestamp, self.dataAccess)) #self.portfolio.currCash + self.strategyData.calculatePortValue(self.portfolio.currStocks,self.currTimestamp)
portfolioValList.append(portValue)
print "Strategy at %d completed successfully." % self.currTimestamp
print "Current cash: " + str(self.portfolio.currCash)
print "Current stocks: %s."%self.portfolio.currStocks
print "Current portfolio value: "+ str(portValue)+"\n\n"
#print "Current portfolio value: %.2f.\n\n"%(portValue)
if noisy and timersActive:
portValue = float (self.portfolio.calcPortfolioValue(self.currTimestamp, self.dataAccess)) #self.portfolio.currCash + self.strategyData.calculatePortValue(self.portfolio.currStocks,self.currTimestamp)
portfolioValList.append(portValue)
print "Strategy at %i took %.4f secs"%(self.currTimestamp,(time.clock()-cycTime))
print "Exec function took: " + str(afterExec - beforeExec)
print "Time for addorders: " + str(afterAddOrders - beforeAddOrders)
print "Strategy at %d completed successfully." % self.currTimestamp
#print "Current cash: %.2f."%(self.portfolio.currCash)
print "Current cash: " + str(self.portfolio.currCash)
print "Current stocks: %s."%self.portfolio.currStocks
#print "Current portfolio value: %.2f.\n\n"%(portValue)
print "Current portfolio value: "+ str(portValue)+"\n\n"
i+=1
cycTime = time.clock()
#self.currTimestamp += self.interval -- Unfortunately this does not work becuase of daylight saving time complications
ctr+=1
self.currTimestamp= timestamps[ctr]
#self.strategyData.currTimestamp = self.currTimestamp
if noisy:
print "Simulation complete."
if timersActive:
print "Simulation complete in %i seconds."%(time.time() - totalTime)
self.portfolio.close()
self.position.close()
self.order.close()
#self.strategyData.close()
#plotting the portfolio value
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot (portfolioValList)
ax.set_title('Portfolio value')
ax.grid(True)
ax.set_xlabel('time')
ax.set_ylabel('$')
canvas.print_figure('portfolio') | [
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v8/services/services/google_ads_service/client.py | python | GoogleAdsServiceClient.parse_keyword_plan_ad_group_keyword_path | (path: str) | return m.groupdict() if m else {} | Parse a keyword_plan_ad_group_keyword path into its component segments. | Parse a keyword_plan_ad_group_keyword path into its component segments. | [
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m = re.match(
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clalancette/oz | 1ab43e88033efa774815c6ebb59ae2841f2980e9 | oz/Windows.py | python | Windows_v5._generate_new_iso | (self) | Method to create a new ISO based on the modified CD/DVD. | Method to create a new ISO based on the modified CD/DVD. | [
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"""
Method to create a new ISO based on the modified CD/DVD.
"""
self.log.debug("Generating new ISO")
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ninja-ide/ninja-ide | 87d91131bd19fdc3dcfd91eb97ad1e41c49c60c0 | ninja_ide/gui/editor/base_editor.py | python | BaseEditor._update_visible_blocks | (self) | Updates the list of visible blocks | Updates the list of visible blocks | [
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append = self.__visible_blocks.append
block = self.firstVisibleBlock()
block_number = block.blockNumber()
top = self.blockBoundingGeometry(block).translated(
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bottom = top + self.blockBoundingRect(block).height()
editor_height = self.height()
while block.isValid():
visible = bottom <= editor_height
if not visible:
break
if block.isVisible():
append((top, block_number, block))
block = block.next()
top = bottom
bottom = top + self.blockBoundingRect(block).height()
block_number += 1 | [
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opendatateam/udata | a295cab3c0e8f086fea1853655011f361ac81b77 | udata/core/user/commands.py | python | create | () | Create a new user | Create a new user | [
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"a",
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] | def create():
'''Create a new user'''
data = {
'first_name': click.prompt('First name'),
'last_name': click.prompt('Last name'),
'email': click.prompt('Email'),
'password': click.prompt('Password', hide_input=True),
'password_confirm': click.prompt('Confirm Password', hide_input=True),
}
# Until https://github.com/mattupstate/flask-security/issues/672 is fixed
with current_app.test_request_context():
form = RegisterForm(MultiDict(data), meta={'csrf': False})
if form.validate():
data['password'] = encrypt_password(data['password'])
del data['password_confirm']
data['confirmed_at'] = datetime.utcnow()
user = datastore.create_user(**data)
success('User(id={u.id} email={u.email}) created'.format(u=user))
return user
errors = '\n'.join('\n'.join([str(m) for m in e]) for e in form.errors.values())
exit_with_error('Error creating user', errors) | [
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OUCMachineLearning/OUCML | 5b54337d7c0316084cb1a74befda2bba96137d4a | One_Day_One_GAN/day4/acgan/acgan.py | python | ACGAN.save_model | (self) | [] | def save_model(self):
def save(model, model_name):
model_path = "saved_model/%s.json" % model_name
weights_path = "saved_model/%s_weights.hdf5" % model_name
options = {"file_arch": model_path,
"file_weight": weights_path}
json_string = model.to_json()
open(options['file_arch'], 'w').write(json_string)
model.save_weights(options['file_weight'])
save(self.generator, "generator")
save(self.discriminator, "discriminator") | [
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facebookresearch/ParlAI | e4d59c30eef44f1f67105961b82a83fd28d7d78b | parlai/chat_service/services/messenger/messenger_manager.py | python | MessengerManager.__init__ | (self, opt) | Create an MessengerManager using the given setup options. | Create an MessengerManager using the given setup options. | [
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"""
Create an MessengerManager using the given setup options.
"""
# Manager attributes
super().__init__(opt)
self._init_logs()
# Read in Config
self._parse_config(opt)
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/treebeard/mp_tree.py | python | MP_ComplexAddMoveHandler.get_sql_newpath_in_branches | (self, oldpath, newpath) | return sql, vals | :returns: The sql needed to move a branch to another position.
.. note::
The generated sql will only update the depth values if needed. | :returns: The sql needed to move a branch to another position. | [
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] | def get_sql_newpath_in_branches(self, oldpath, newpath):
"""
:returns: The sql needed to move a branch to another position.
.. note::
The generated sql will only update the depth values if needed.
"""
vendor = self.node_cls.get_database_vendor('write')
sql1 = "UPDATE %s SET" % (
connection.ops.quote_name(
get_result_class(self.node_cls)._meta.db_table), )
# <3 "standard" sql
if vendor == 'sqlite':
# I know that the third argument in SUBSTR (LENGTH(path)) is
# awful, but sqlite fails without it:
# OperationalError: wrong number of arguments to function substr()
# even when the documentation says that 2 arguments are valid:
# http://www.sqlite.org/lang_corefunc.html
sqlpath = "%s||SUBSTR(path, %s, LENGTH(path))"
elif vendor == 'mysql':
# hooray for mysql ignoring standards in their default
# configuration!
# to make || work as it should, enable ansi mode
# http://dev.mysql.com/doc/refman/5.0/en/ansi-mode.html
sqlpath = "CONCAT(%s, SUBSTR(path, %s))"
else:
sqlpath = sql_concat("%s", sql_substr("path", "%s", vendor=vendor), vendor=vendor)
sql2 = ["path=%s" % (sqlpath, )]
vals = [newpath, len(oldpath) + 1]
if len(oldpath) != len(newpath) and vendor != 'mysql':
# when using mysql, this won't update the depth and it has to be
# done in another query
# doesn't even work with sql_mode='ANSI,TRADITIONAL'
# TODO: FIND OUT WHY?!?? right now I'm just blaming mysql
sql2.append(("depth=" + sql_length("%s", vendor=vendor) + "/%%s") % (sqlpath, ))
vals.extend([newpath, len(oldpath) + 1, self.node_cls.steplen])
sql3 = "WHERE path LIKE %s"
vals.extend([oldpath + '%'])
sql = '%s %s %s' % (sql1, ', '.join(sql2), sql3)
return sql, vals | [
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pytrainer/pytrainer | 66f3e2b30b48c66e03111248faffc43b8e31c583 | pytrainer/main.py | python | pyTrainer.set_logging_level | (self, level) | Set level of information written to log | Set level of information written to log | [
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] | def set_logging_level(self, level):
'''Set level of information written to log'''
logging.debug("Setting logger to level: %s", level)
logging.getLogger('').setLevel(level)
logging.getLogger('sqlalchemy.engine').setLevel(level) | [
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kivymd/KivyMD | 1cb82f7d2437770f71be7c5a4f7de4b8da61f352 | kivymd/uix/snackbar/snackbar.py | python | BaseSnackbar.on_open | (self, *args) | Called when a dialog is opened. | Called when a dialog is opened. | [
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explosion/spaCy | a784b12eff48df9281b184cb7005e66bbd2e3aca | spacy/cli/project/run.py | python | validate_subcommand | (
commands: Sequence[str], workflows: Sequence[str], subcommand: str
) | Check that a subcommand is valid and defined. Raises an error otherwise.
commands (Sequence[str]): The available commands.
subcommand (str): The subcommand. | Check that a subcommand is valid and defined. Raises an error otherwise. | [
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commands: Sequence[str], workflows: Sequence[str], subcommand: str
) -> None:
"""Check that a subcommand is valid and defined. Raises an error otherwise.
commands (Sequence[str]): The available commands.
subcommand (str): The subcommand.
"""
if not commands and not workflows:
msg.fail(f"No commands or workflows defined in {PROJECT_FILE}", exits=1)
if subcommand not in commands and subcommand not in workflows:
help_msg = []
if commands:
help_msg.append(f"Available commands: {', '.join(commands)}")
if workflows:
help_msg.append(f"Available workflows: {', '.join(workflows)}")
msg.fail(
f"Can't find command or workflow '{subcommand}' in {PROJECT_FILE}",
". ".join(help_msg),
exits=1,
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apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | txweb2/resource.py | python | WrapperResource.getChild | (self, name) | return self.resource.getChild(name) | [] | def getChild(self, name):
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ethereum/web3.py | 6a90a26ea12e5a789834c9cd6a7ae6d302648f88 | ethpm/package.py | python | Package.contract_types | (self) | All contract types included in this package. | All contract types included in this package. | [
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"""
All contract types included in this package.
"""
if 'contractTypes' in self.manifest:
return sorted(self.manifest['contractTypes'].keys())
else:
raise ValueError("No contract types found in manifest; {self.__repr__()}.") | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/bokeh-1.4.0-py3.7.egg/bokeh/layouts.py | python | grid | (children=[], sizing_mode=None, nrows=None, ncols=None) | return grid | Conveniently create a grid of layoutable objects.
Grids are created by using ``GridBox`` model. This gives the most control over
the layout of a grid, but is also tedious and may result in unreadable code in
practical applications. ``grid()`` function remedies this by reducing the level
of control, but in turn providing a more convenient API.
Supported patterns:
1. Nested lists of layoutable objects. Assumes the top-level list represents
a column and alternates between rows and columns in subsequent nesting
levels. One can use ``None`` for padding purpose.
>>> grid([p1, [[p2, p3], p4]])
GridBox(children=[
(p1, 0, 0, 1, 2),
(p2, 1, 0, 1, 1),
(p3, 2, 0, 1, 1),
(p4, 1, 1, 2, 1),
])
2. Nested ``Row`` and ``Column`` instances. Similar to the first pattern, just
instead of using nested lists, it uses nested ``Row`` and ``Column`` models.
This can be much more readable that the former. Note, however, that only
models that don't have ``sizing_mode`` set are used.
>>> grid(column(p1, row(column(p2, p3), p4)))
GridBox(children=[
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(p2, 1, 0, 1, 1),
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])
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be set. The input list will be rearranged into a 2D array accordingly. One
can use ``None`` for padding purpose.
>>> grid([p1, p2, p3, p4], ncols=2)
GridBox(children=[
(p1, 0, 0, 1, 1),
(p2, 0, 1, 1, 1),
(p3, 1, 0, 1, 1),
(p4, 1, 1, 1, 1),
]) | Conveniently create a grid of layoutable objects. | [
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"create",
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"."
] | def grid(children=[], sizing_mode=None, nrows=None, ncols=None):
"""
Conveniently create a grid of layoutable objects.
Grids are created by using ``GridBox`` model. This gives the most control over
the layout of a grid, but is also tedious and may result in unreadable code in
practical applications. ``grid()`` function remedies this by reducing the level
of control, but in turn providing a more convenient API.
Supported patterns:
1. Nested lists of layoutable objects. Assumes the top-level list represents
a column and alternates between rows and columns in subsequent nesting
levels. One can use ``None`` for padding purpose.
>>> grid([p1, [[p2, p3], p4]])
GridBox(children=[
(p1, 0, 0, 1, 2),
(p2, 1, 0, 1, 1),
(p3, 2, 0, 1, 1),
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])
2. Nested ``Row`` and ``Column`` instances. Similar to the first pattern, just
instead of using nested lists, it uses nested ``Row`` and ``Column`` models.
This can be much more readable that the former. Note, however, that only
models that don't have ``sizing_mode`` set are used.
>>> grid(column(p1, row(column(p2, p3), p4)))
GridBox(children=[
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(p2, 1, 0, 1, 1),
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be set. The input list will be rearranged into a 2D array accordingly. One
can use ``None`` for padding purpose.
>>> grid([p1, p2, p3, p4], ncols=2)
GridBox(children=[
(p1, 0, 0, 1, 1),
(p2, 0, 1, 1, 1),
(p3, 1, 0, 1, 1),
(p4, 1, 1, 1, 1),
])
"""
row = namedtuple("row", ["children"])
col = namedtuple("col", ["children"])
def flatten(layout):
Item = namedtuple("Item", ["layout", "r0", "c0", "r1", "c1"])
Grid = namedtuple("Grid", ["nrows", "ncols", "items"])
def gcd(a, b):
a, b = abs(a), abs(b)
while b != 0:
a, b = b, a % b
return a
def lcm(a, *rest):
for b in rest:
a = (a*b) // gcd(a, b)
return a
nonempty = lambda child: child.nrows != 0 and child.ncols != 0
def _flatten(layout):
if isinstance(layout, row):
children = list(filter(nonempty, map(_flatten, layout.children)))
if not children:
return Grid(0, 0, [])
nrows = lcm(*[ child.nrows for child in children ])
ncols = sum([ child.ncols for child in children ])
items = []
offset = 0
for child in children:
factor = nrows//child.nrows
for (layout, r0, c0, r1, c1) in child.items:
items.append((layout, factor*r0, c0 + offset, factor*r1, c1 + offset))
offset += child.ncols
return Grid(nrows, ncols, items)
elif isinstance(layout, col):
children = list(filter(nonempty, map(_flatten, layout.children)))
if not children:
return Grid(0, 0, [])
nrows = sum([ child.nrows for child in children ])
ncols = lcm(*[ child.ncols for child in children ])
items = []
offset = 0
for child in children:
factor = ncols//child.ncols
for (layout, r0, c0, r1, c1) in child.items:
items.append((layout, r0 + offset, factor*c0, r1 + offset, factor*c1))
offset += child.nrows
return Grid(nrows, ncols, items)
else:
return Grid(1, 1, [Item(layout, 0, 0, 1, 1)])
grid = _flatten(layout)
children = []
for (layout, r0, c0, r1, c1) in grid.items:
if layout is not None:
children.append((layout, r0, c0, r1 - r0, c1 - c0))
return GridBox(children=children)
if isinstance(children, list):
if nrows is not None or ncols is not None:
N = len(children)
if ncols is None:
ncols = math.ceil(N/nrows)
layout = col([ row(children[i:i+ncols]) for i in range(0, N, ncols) ])
else:
def traverse(children, level=0):
if isinstance(children, list):
container = col if level % 2 == 0 else row
return container([ traverse(child, level+1) for child in children ])
else:
return children
layout = traverse(children)
elif isinstance(children, LayoutDOM):
def is_usable(child):
return _has_auto_sizing(child) and child.spacing == 0
def traverse(item, top_level=False):
if isinstance(item, Box) and (top_level or is_usable(item)):
container = col if isinstance(item, Column) else row
return container(list(map(traverse, item.children)))
else:
return item
layout = traverse(children, top_level=True)
elif isinstance(children, string_types):
raise NotImplementedError
else:
raise ValueError("expected a list, string or model")
grid = flatten(layout)
if sizing_mode is not None:
grid.sizing_mode = sizing_mode
for child in grid.children:
layout = child[0]
if _has_auto_sizing(layout):
layout.sizing_mode = sizing_mode
return grid | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_vendored_deps/library/oc_scale.py | python | Yedit.parse_value | (inc_value, vtype='') | return inc_value | determine value type passed | determine value type passed | [
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] | def parse_value(inc_value, vtype=''):
'''determine value type passed'''
true_bools = ['y', 'Y', 'yes', 'Yes', 'YES', 'true', 'True', 'TRUE',
'on', 'On', 'ON', ]
false_bools = ['n', 'N', 'no', 'No', 'NO', 'false', 'False', 'FALSE',
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# It came in as a string but you didn't specify value_type as string
# we will convert to bool if it matches any of the above cases
if isinstance(inc_value, str) and 'bool' in vtype:
if inc_value not in true_bools and inc_value not in false_bools:
raise YeditException('Not a boolean type. str=[{}] vtype=[{}]'.format(inc_value, vtype))
elif isinstance(inc_value, bool) and 'str' in vtype:
inc_value = str(inc_value)
# There is a special case where '' will turn into None after yaml loading it so skip
if isinstance(inc_value, str) and inc_value == '':
pass
# If vtype is not str then go ahead and attempt to yaml load it.
elif isinstance(inc_value, str) and 'str' not in vtype:
try:
inc_value = yaml.safe_load(inc_value)
except Exception:
raise YeditException('Could not determine type of incoming value. ' +
'value=[{}] vtype=[{}]'.format(type(inc_value), vtype))
return inc_value | [
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cortex-lab/phy | 9a330b9437a3d0b40a37a201d147224e6e7fb462 | phy/cluster/views/raster.py | python | RasterView._get_box_index | (self) | return _index_of(cl, self.all_cluster_ids) | Return, for every spike, its row in the raster plot. This depends on the ordering
in self.cluster_ids. | Return, for every spike, its row in the raster plot. This depends on the ordering
in self.cluster_ids. | [
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cl = self.spike_clusters[self.spike_ids]
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etsy/logster | a24249886391a8b885d21c882f6fcaa95e29b015 | logster/parsers/JsonLogster.py | python | JsonLogster.parse_line | (self, line) | This function should digest the contents of one line at a time, updating
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try:
json_data = json.loads(line)
except Exception as e:
raise LogsterParsingException("{0} - {1}".format(type(e), e))
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_openshift/library/oc_process.py | python | OpenShiftCLI._replace | (self, fname, force=False) | return self.openshift_cmd(cmd) | replace the current object with oc replace | replace the current object with oc replace | [
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'''replace the current object with oc replace'''
# We are removing the 'resourceVersion' to handle
# a race condition when modifying oc objects
yed = Yedit(fname)
results = yed.delete('metadata.resourceVersion')
if results[0]:
yed.write()
cmd = ['replace', '-f', fname]
if force:
cmd.append('--force')
return self.openshift_cmd(cmd) | [
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django-nonrel/django-nonrel | 4fbfe7344481a5eab8698f79207f09124310131b | django/contrib/gis/geos/prototypes/errcheck.py | python | check_predicate | (result, func, cargs) | Error checking for unary/binary predicate functions. | Error checking for unary/binary predicate functions. | [
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val = ord(result) # getting the ordinal from the character
if val == 1: return True
elif val == 0: return False
else:
raise GEOSException('Error encountered on GEOS C predicate function "%s".' % func.__name__) | [
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plaid/plaid-python | 8c60fca608e426f3ff30da8857775946d29e122c | plaid/model/transfer_status.py | python | TransferStatus.openapi_types | () | return {
'value': (str,),
} | This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
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"""
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openapi_types (dict): The key is attribute name
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martinRenou/ipycanvas | 53348e3f63153fc80459c9f1e76ce73dc75dcd49 | ipycanvas/canvas.py | python | Canvas.fill_rects | (self, x, y, width, height=None) | Draw filled rectangles of sizes ``(width, height)`` at the ``(x, y)`` positions.
Where ``x``, ``y``, ``width`` and ``height`` arguments are NumPy arrays, lists or scalar values.
If ``height`` is None, it is set to the same value as width. | Draw filled rectangles of sizes ``(width, height)`` at the ``(x, y)`` positions. | [
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"""Draw filled rectangles of sizes ``(width, height)`` at the ``(x, y)`` positions.
Where ``x``, ``y``, ``width`` and ``height`` arguments are NumPy arrays, lists or scalar values.
If ``height`` is None, it is set to the same value as width.
"""
args = []
buffers = []
populate_args(x, args, buffers)
populate_args(y, args, buffers)
populate_args(width, args, buffers)
if height is None:
args.append(args[-1])
else:
populate_args(height, args, buffers)
self._send_canvas_command(COMMANDS['fillRects'], args, buffers) | [
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gnome-terminator/terminator | ca335e45eb1a4ea7c22fe0d515bb270e9a0e12a1 | terminatorlib/util.py | python | shell_lookup | () | Find an appropriate shell for the user | Find an appropriate shell for the user | [
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"""Find an appropriate shell for the user"""
try:
usershell = pwd.getpwuid(os.getuid())[6]
except KeyError:
usershell = None
shells = [usershell, 'bash', 'zsh', 'tcsh', 'ksh', 'csh', 'sh']
for shell in shells:
if shell is None:
continue
elif os.path.isfile(shell):
return(shell)
else:
rshell = path_lookup(shell)
if rshell is not None:
dbg('shell_lookup: Found %s at %s' % (shell, rshell))
return(rshell)
dbg('shell_lookup: Unable to locate a shell') | [
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GoogleChrome/chromium-dashboard | 7ef9184080fc4cdf11efbe29dba27f95f07a20d9 | internals/notifier.py | python | accumulate_reasons | (addr_reasons, user_list, reason) | Add a reason string for each user. | Add a reason string for each user. | [
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"""Add a reason string for each user."""
for user in user_list:
if type(user) == str:
addr_reasons[user].append(reason)
else:
addr_reasons[user.email].append(reason) | [
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zhang-can/ECO-pytorch | 355c3866b35cdaa5d451263c1f3291c150e22eeb | tf_model_zoo/models/neural_gpu/neural_gpu.py | python | sigmoid_cutoff | (x, cutoff) | return tf.minimum(1.0, tf.maximum(0.0, cutoff * y - d)) | Sigmoid with cutoff, e.g., 1.2sigmoid(x) - 0.1. | Sigmoid with cutoff, e.g., 1.2sigmoid(x) - 0.1. | [
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"""Sigmoid with cutoff, e.g., 1.2sigmoid(x) - 0.1."""
y = tf.sigmoid(x)
if cutoff < 1.01: return y
d = (cutoff - 1.0) / 2.0
return tf.minimum(1.0, tf.maximum(0.0, cutoff * y - d)) | [
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fonttools/fonttools | 892322aaff6a89bea5927379ec06bc0da3dfb7df | Lib/fontTools/ttLib/tables/otConverters.py | python | UShort.readArray | (self, reader, font, tableDict, count) | return reader.readUShortArray(count) | [] | def readArray(self, reader, font, tableDict, count):
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dagwieers/mrepo | a55cbc737d8bade92070d38e4dbb9a24be4b477f | up2date_client/rpmUtils.py | python | checkHeaderForFileConfigExcludes | (h,package,ts) | [] | def checkHeaderForFileConfigExcludes(h,package,ts):
fflag = 0
cfg = config.initUp2dateConfig()
# might as well just do this once...
fileNames = h['filenames'] or []
fileMD5s = h['filemd5s'] or []
fileFlags = h['fileflags'] or []
installedHdr = installedHeader(h['name'],ts)
if not installedHdr:
#throw a fault? should this happen?
return None
installedFileNames = installedHdr['filenames'] or []
installedFileMD5s = installedHdr['filemd5s'] or []
# print "installedFileMD5s: %s" % installedFileMD5s
removedList = []
if cfg["forceInstall"]:
return None
# shrug, the apt headers dont have this, not much
# we can do about it... Kind of odd considering how
# paranoid apt is supposed to be about breaking configs...
if not fileMD5s:
return None
if not fileFlags:
return None
fileSkipList = cfg["fileSkipList"]
# bleah, have to use the index here because
# of rpm's storing of filenames and their md5sums in parallel lists
for f_i in range(len(fileNames)):
# code to see if we want to disable this
for pattern in fileSkipList:
if fnmatch.fnmatch(fileNames[f_i],pattern):
# got to get a better string to use here
removedList.append((package, "File Name/pattern"))
fflag = 1
break
# if we found a matching file, no need to
# examine the rest in this package
if fflag:
break
configFilesToIgnore = cfg["configFilesToIgnore"] or []
# cfg reads are a little heavier in this code base, so
# might as well avoid doing them for every single file
noReplaceConfig = cfg["noReplaceConfig"]
for f_i in range(len(fileNames)):
# Deal with config files
if noReplaceConfig:
# check for files that are config files, but skips those that
# arent going to be replaced anyway
# (1 << 4) == rpm.RPMFILE_NOREPLACE if it existed
if fileFlags[f_i] & rpm.RPMFILE_CONFIG and not \
fileFlags[f_i] & (1 << 4):
if fileNames[f_i] not in configFilesToIgnore:
# check if config file and if so, if modified
if checkModified(f_i, fileNames, fileMD5s,
installedFileNames, installedFileMD5s):
removedList.append((package, "Config modified"))
fflag = 1
break
if fflag:
break
if len(removedList):
return removedList
else:
return None | [
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angr/angr | 4b04d56ace135018083d36d9083805be8146688b | angr/angrdb/db.py | python | AngrDB.get_info | (session, key) | return db_info.value | Get an information entry from the database.
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"""
Get an information entry from the database.
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"""
db_info = session.query(DbInformation).filter_by(key=key).scalar()
if db_info is None:
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reviewboard/rbtools | b4838a640b458641ffd233093ae65971d0b4d529 | rbtools/commands/setup_repo.py | python | SetupRepo._display_rb_repositories | (self, closest_paths, repo_paths) | Display all repositories found for a Review Board server.
Args:
closest_paths (list of unicode)
A list of best-matching repositories from a valid
Review Board server.
repo_paths (dict)
A dictionary containing repository metadata. | Display all repositories found for a Review Board server. | [
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] | def _display_rb_repositories(self, closest_paths, repo_paths):
"""Display all repositories found for a Review Board server.
Args:
closest_paths (list of unicode)
A list of best-matching repositories from a valid
Review Board server.
repo_paths (dict)
A dictionary containing repository metadata.
"""
for i, repo_url in enumerate(closest_paths):
repo = repo_paths[repo_url]
self.stdout.write(
'%(num)d) "%(repo_name)s" (%(repo_url)s)'
% {
'num': i + 1,
'repo_name': repo['name'],
'repo_url': repo_url,
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/functions/combinatorial/numbers.py | python | harmonic._eval_rewrite_as_digamma | (self, n, m=1) | return self.rewrite(polygamma) | [] | def _eval_rewrite_as_digamma(self, n, m=1):
from sympy.functions.special.gamma_functions import polygamma
return self.rewrite(polygamma) | [
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lohriialo/photoshop-scripting-python | 6b97da967a5d0a45e54f7c99631b29773b923f09 | api_reference/photoshop_CC_2018.py | python | _PICTFileSaveOptions.__iter__ | (self) | return win32com.client.util.Iterator(ob, None) | Return a Python iterator for this object | Return a Python iterator for this object | [
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"Return a Python iterator for this object"
try:
ob = self._oleobj_.InvokeTypes(-4,LCID,3,(13, 10),())
except pythoncom.error:
raise TypeError("This object does not support enumeration")
return win32com.client.util.Iterator(ob, None) | [
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... | https://github.com/lohriialo/photoshop-scripting-python/blob/6b97da967a5d0a45e54f7c99631b29773b923f09/api_reference/photoshop_CC_2018.py#L5512-L5518 | |
Yelp/py_zipkin | d56d05d8d72f19440d3be8edda80dc4c402a6356 | py_zipkin/encoding/protobuf/__init__.py | python | _hex_to_bytes | (hex_id) | Encodes to hexadecimal ids to big-endian binary.
:param hex_id: hexadecimal id to encode.
:type hex_id: str
:return: binary representation.
:type: bytes | Encodes to hexadecimal ids to big-endian binary. | [
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] | def _hex_to_bytes(hex_id):
"""Encodes to hexadecimal ids to big-endian binary.
:param hex_id: hexadecimal id to encode.
:type hex_id: str
:return: binary representation.
:type: bytes
"""
if len(hex_id) <= 16:
int_id = unsigned_hex_to_signed_int(hex_id)
return struct.pack(">q", int_id)
else:
# There's no 16-bytes encoding in Python's struct. So we convert the
# id as 2 64 bit ids and then concatenate the result.
# NOTE: we count 16 chars from the right (:-16) rather than the left so
# that ids with less than 32 chars will be correctly pre-padded with 0s.
high_id = unsigned_hex_to_signed_int(hex_id[:-16])
high_bin = struct.pack(">q", high_id)
low_id = unsigned_hex_to_signed_int(hex_id[-16:])
low_bin = struct.pack(">q", low_id)
return high_bin + low_bin | [
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tosher/Mediawiker | 81bf97cace59bedcb1668e7830b85c36e014428e | lib/Crypto.osx.x64/Crypto/Cipher/DES3.py | python | adjust_key_parity | (key_in) | return key_out | Set the parity bits in a TDES key.
:param key_in: the TDES key whose bits need to be adjusted
:type key_in: byte string
:returns: a copy of ``key_in``, with the parity bits correctly set
:rtype: byte string
:raises ValueError: if the TDES key is not 16 or 24 bytes long
:raises ValueError: if the TDES key degenerates into Single DES | Set the parity bits in a TDES key. | [
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] | def adjust_key_parity(key_in):
"""Set the parity bits in a TDES key.
:param key_in: the TDES key whose bits need to be adjusted
:type key_in: byte string
:returns: a copy of ``key_in``, with the parity bits correctly set
:rtype: byte string
:raises ValueError: if the TDES key is not 16 or 24 bytes long
:raises ValueError: if the TDES key degenerates into Single DES
"""
def parity_byte(key_byte):
parity = 1
for i in range(1, 8):
parity ^= (key_byte >> i) & 1
return (key_byte & 0xFE) | parity
if len(key_in) not in key_size:
raise ValueError("Not a valid TDES key")
key_out = b"".join([ bchr(parity_byte(bord(x))) for x in key_in ])
if key_out[:8] == key_out[8:16] or key_out[-16:-8] == key_out[-8:]:
raise ValueError("Triple DES key degenerates to single DES")
return key_out | [
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Anaconda-Platform/anaconda-project | df5ec33c12591e6512436d38d36c6132fa2e9618 | anaconda_project/project_commands.py | python | ProjectCommand._choose_args_and_shell | (self, environ, extra_args=None) | return (args, shell) | [] | def _choose_args_and_shell(self, environ, extra_args=None):
assert extra_args is None or isinstance(extra_args, list)
args = None
shell = False
if not self.supports_http_options and (self.notebook or self.bokeh_app):
# drop the http arguments
extra_args = _ArgsTransformer().transform_args(extra_args)
if self.notebook is not None:
path = os.path.join(environ['PROJECT_DIR'], self.notebook)
args = ['jupyter-notebook', path]
if self.supports_http_options:
extra_args = _NotebookArgsTransformer(self).transform_args(extra_args)
if self.bokeh_app is not None:
path = os.path.join(environ['PROJECT_DIR'], self.bokeh_app)
args = ['bokeh', 'serve', path]
if self.supports_http_options:
extra_args = _BokehArgsTransformer().transform_args(extra_args)
if self.args is not None:
args = self.args
if args is not None:
if extra_args is not None:
args = args + extra_args
return args, False
command = self._attributes.get(self._shell_field(), None)
if (command is not None) and self.supports_http_options:
args = [_append_extra_args_to_command_line(command, extra_args)]
shell = True
elif command:
shell = True
args = _TemplateArgsTransformer().parse_and_template(command, environ, extra_args)
if args is None:
# see conda.misc::launch for what we're copying
app_entry = self._attributes.get('conda_app_entry', None)
if app_entry is not None:
# conda.misc uses plain split and not shlex or
# anything like that, we need to match its
# interpretation
parsed = app_entry.split()
args = []
for arg in parsed:
if '${PREFIX}' in arg:
arg = arg.replace('${PREFIX}', conda_api.environ_get_prefix(environ))
args.append(arg)
if extra_args is not None:
args = args + extra_args
# args can be None if the command doesn't work on our platform
return (args, shell) | [
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lightkurve/lightkurve | 70d1c4cd1ab30f24c83e54bdcea4dd16624bfd9c | src/lightkurve/seismology/core.py | python | Seismology.estimate_deltanu | (self, method="acf2d", numax=None) | return result | Returns the average value of the large frequency spacing, DeltaNu,
of the seismic oscillations of the target.
At present, the only method supported is based on using an
autocorrelation function (ACF2D). This method is implemented by the
`~lightkurve.seismology.estimate_deltanu_acf2d` function which requires
the parameter `numax`. For details and literature references, please
read the detailed docstring of this function by typing
``lightkurve.seismology.estimate_deltanu_acf2d?`` in a Python terminal or notebook.
Parameters
----------
method : str
Method to use. Only ``"acf2d"`` is supported at this time.
Returns
-------
deltanu : `~lightkurve.seismology.SeismologyQuantity`
DeltaNu of the periodogram, including details on the units and method. | Returns the average value of the large frequency spacing, DeltaNu,
of the seismic oscillations of the target. | [
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] | def estimate_deltanu(self, method="acf2d", numax=None):
"""Returns the average value of the large frequency spacing, DeltaNu,
of the seismic oscillations of the target.
At present, the only method supported is based on using an
autocorrelation function (ACF2D). This method is implemented by the
`~lightkurve.seismology.estimate_deltanu_acf2d` function which requires
the parameter `numax`. For details and literature references, please
read the detailed docstring of this function by typing
``lightkurve.seismology.estimate_deltanu_acf2d?`` in a Python terminal or notebook.
Parameters
----------
method : str
Method to use. Only ``"acf2d"`` is supported at this time.
Returns
-------
deltanu : `~lightkurve.seismology.SeismologyQuantity`
DeltaNu of the periodogram, including details on the units and method.
"""
method = validate_method(method, supported_methods=["acf2d"])
numax = self._validate_numax(numax)
if method == "acf2d":
from .deltanu_estimators import estimate_deltanu_acf2d
result = estimate_deltanu_acf2d(self.periodogram, numax=numax)
self.deltanu = result
return result | [
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google/personfinder | 475f4c0ce916036d39bae2d480cde07126550875 | app/record_writer.py | python | RecordCsvWriter.__init__ | (self, io, fields=None, write_header=True) | Initializer.
Args:
io (io): CSV is written to this.
fields (list of str): A custom list of fields which are written.
write_header (bool): Write the header row at the beginning. | Initializer.
Args:
io (io): CSV is written to this.
fields (list of str): A custom list of fields which are written.
write_header (bool): Write the header row at the beginning. | [
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"""Initializer.
Args:
io (io): CSV is written to this.
fields (list of str): A custom list of fields which are written.
write_header (bool): Write the header row at the beginning.
"""
self.io = io
if fields:
self.fields = fields
self.writer = csv.writer(self.io)
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pycalphad/pycalphad | 631c41c3d041d4e8a47c57d0f25d078344b9da52 | pycalphad/codegen/callables.py | python | build_callables | (dbf, comps, phases, models, parameter_symbols=None,
output='GM', build_gradients=True, build_hessians=False,
additional_statevars=None) | return {output: _callables} | Create a compiled callables dictionary.
Parameters
----------
dbf : Database
A Database object
comps : list
List of component names
phases : list
List of phase names
models : dict
Dictionary of {phase_name: Model subclass}
parameter_symbols : list, optional
List of string or SymPy Symbols that will be overridden in the callables.
output : str, optional
Output property of the particular Model to sample. Defaults to 'GM'
build_gradients : bool, optional
Whether or not to build gradient functions. Defaults to True.
build_hessians : bool, optional
Whether or not to build Hessian functions. Defaults to False.
additional_statevars : set, optional
State variables to include in the callables that may not be in the models (e.g. from conditions)
verbose : bool, optional
Print the name of the phase when its callables are built
Returns
-------
callables : dict
Dictionary of keyword argument callables to pass to equilibrium.
Maps {'output' -> {'function' -> {'phase_name' -> AutowrapFunction()}}.
Notes
-----
*All* the state variables used in calculations must be specified.
If these are not specified as state variables of the models (e.g. often the
case for v.N), then it must be supplied by the additional_statevars keyword
argument.
Examples
--------
>>> from pycalphad import Database, equilibrium, variables as v
>>> from pycalphad.codegen.callables import build_callables
>>> from pycalphad.core.utils import instantiate_models
>>> dbf = Database('AL-NI.tdb')
>>> comps = ['AL', 'NI', 'VA']
>>> phases = ['LIQUID', 'AL3NI5', 'AL3NI2', 'AL3NI']
>>> models = instantiate_models(dbf, comps, phases)
>>> callables = build_callables(dbf, comps, phases, models, additional_statevars={v.P, v.T, v.N})
>>> 'GM' in callables.keys()
True
>>> 'massfuncs' in callables['GM']
True
>>> conditions = {v.P: 101325, v.T: 2500, v.X('AL'): 0.2}
>>> equilibrium(dbf, comps, phases, conditions, callables=callables) | Create a compiled callables dictionary. | [
"Create",
"a",
"compiled",
"callables",
"dictionary",
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] | def build_callables(dbf, comps, phases, models, parameter_symbols=None,
output='GM', build_gradients=True, build_hessians=False,
additional_statevars=None):
"""
Create a compiled callables dictionary.
Parameters
----------
dbf : Database
A Database object
comps : list
List of component names
phases : list
List of phase names
models : dict
Dictionary of {phase_name: Model subclass}
parameter_symbols : list, optional
List of string or SymPy Symbols that will be overridden in the callables.
output : str, optional
Output property of the particular Model to sample. Defaults to 'GM'
build_gradients : bool, optional
Whether or not to build gradient functions. Defaults to True.
build_hessians : bool, optional
Whether or not to build Hessian functions. Defaults to False.
additional_statevars : set, optional
State variables to include in the callables that may not be in the models (e.g. from conditions)
verbose : bool, optional
Print the name of the phase when its callables are built
Returns
-------
callables : dict
Dictionary of keyword argument callables to pass to equilibrium.
Maps {'output' -> {'function' -> {'phase_name' -> AutowrapFunction()}}.
Notes
-----
*All* the state variables used in calculations must be specified.
If these are not specified as state variables of the models (e.g. often the
case for v.N), then it must be supplied by the additional_statevars keyword
argument.
Examples
--------
>>> from pycalphad import Database, equilibrium, variables as v
>>> from pycalphad.codegen.callables import build_callables
>>> from pycalphad.core.utils import instantiate_models
>>> dbf = Database('AL-NI.tdb')
>>> comps = ['AL', 'NI', 'VA']
>>> phases = ['LIQUID', 'AL3NI5', 'AL3NI2', 'AL3NI']
>>> models = instantiate_models(dbf, comps, phases)
>>> callables = build_callables(dbf, comps, phases, models, additional_statevars={v.P, v.T, v.N})
>>> 'GM' in callables.keys()
True
>>> 'massfuncs' in callables['GM']
True
>>> conditions = {v.P: 101325, v.T: 2500, v.X('AL'): 0.2}
>>> equilibrium(dbf, comps, phases, conditions, callables=callables)
"""
additional_statevars = set(additional_statevars) if additional_statevars is not None else set()
parameter_symbols = parameter_symbols if parameter_symbols is not None else []
parameter_symbols = sorted([wrap_symbol(x) for x in parameter_symbols], key=str)
comps = sorted(unpack_components(dbf, comps))
pure_elements = get_pure_elements(dbf, comps)
_callables = {
'massfuncs': {},
'massgradfuncs': {},
'masshessfuncs': {},
'formulamolefuncs': {},
'formulamolegradfuncs': {},
'formulamolehessfuncs': {},
'callables': {},
'grad_callables': {},
'hess_callables': {},
'internal_cons_func': {},
'internal_cons_jac': {},
'internal_cons_hess': {},
}
state_variables = get_state_variables(models=models)
state_variables |= additional_statevars
if not {v.T, v.P, v.N}.issubset(state_variables):
warnings.warn("State variables in `build_callables` are not {{N, P, T}}, but {}. This can lead to incorrectly "
"calculated values if the state variables used to call the generated functions do not match the "
"state variables used to create them. State variables can be added with the "
"`additional_statevars` argument.".format(state_variables))
state_variables = sorted(state_variables, key=str)
for name in phases:
mod = models[name]
site_fracs = mod.site_fractions
try:
out = getattr(mod, output)
except AttributeError:
raise AttributeError('Missing Model attribute {0} specified for {1}'
.format(output, mod.__class__))
# Build the callables of the output
# Only force undefineds to zero if we're not overriding them
undefs = {x for x in out.free_symbols if not isinstance(x, v.StateVariable)} - set(parameter_symbols)
undef_vals = repeat(0., len(undefs))
out = out.xreplace(dict(zip(undefs, undef_vals)))
build_output = build_functions(out, tuple(state_variables + site_fracs), parameters=parameter_symbols,
include_grad=build_gradients, include_hess=build_hessians)
cf, gf, hf = build_output.func, build_output.grad, build_output.hess
_callables['callables'][name] = cf
_callables['grad_callables'][name] = gf
_callables['hess_callables'][name] = hf
# Build the callables for mass
# TODO: In principle, we should also check for undefs in mod.moles()
mcf, mgf, mhf = zip(*[build_functions(mod.moles(el), state_variables + site_fracs,
include_obj=True,
include_grad=build_gradients,
include_hess=build_hessians,
parameters=parameter_symbols)
for el in pure_elements])
_callables['massfuncs'][name] = mcf
_callables['massgradfuncs'][name] = mgf
_callables['masshessfuncs'][name] = mhf
# Build the callables for moles per formula unit
# TODO: In principle, we should also check for undefs in mod.moles()
fmcf, fmgf, fmhf = zip(*[build_functions(mod.moles(el, per_formula_unit=True), state_variables + site_fracs,
include_obj=True,
include_grad=build_gradients,
include_hess=build_hessians,
parameters=parameter_symbols)
for el in pure_elements])
_callables['formulamolefuncs'][name] = fmcf
_callables['formulamolegradfuncs'][name] = fmgf
_callables['formulamolehessfuncs'][name] = fmhf
return {output: _callables} | [
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cea-sec/miasm | 09376c524aedc7920a7eda304d6095e12f6958f4 | miasm/core/objc.py | python | CTypesManagerNotPacked.union_compute_align_size | (self, align_max, size) | return align_max, size | Compute the alignment and size of the current union
(not packed) | Compute the alignment and size of the current union
(not packed) | [
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"""Compute the alignment and size of the current union
(not packed)"""
return align_max, size | [
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vslavik/bakefile | 0757295c3e4ac23cd1e0767c77c14c2256ed16e1 | 3rdparty/antlr3/python-runtime/antlr3/tree.py | python | TreeNodeStream.replaceChildren | (self, parent, startChildIndex, stopChildIndex, t) | Replace from start to stop child index of parent with t, which might
be a list. Number of children may be different
after this call. The stream is notified because it is walking the
tree and might need to know you are monkeying with the underlying
tree. Also, it might be able to modify the node stream to avoid
restreaming for future phases.
If parent is null, don't do anything; must be at root of overall tree.
Can't replace whatever points to the parent externally. Do nothing. | Replace from start to stop child index of parent with t, which might
be a list. Number of children may be different
after this call. The stream is notified because it is walking the
tree and might need to know you are monkeying with the underlying
tree. Also, it might be able to modify the node stream to avoid
restreaming for future phases. | [
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"""
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be a list. Number of children may be different
after this call. The stream is notified because it is walking the
tree and might need to know you are monkeying with the underlying
tree. Also, it might be able to modify the node stream to avoid
restreaming for future phases.
If parent is null, don't do anything; must be at root of overall tree.
Can't replace whatever points to the parent externally. Do nothing.
"""
raise NotImplementedError | [
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nipy/nibabel | 4703f4d8e32be4cec30e829c2d93ebe54759bb62 | nibabel/nicom/csareader.py | python | get_vector | (csa_dict, tag_name, n) | return np.array(items) | [] | def get_vector(csa_dict, tag_name, n):
try:
items = csa_dict['tags'][tag_name]['items']
except KeyError:
return None
if len(items) == 0:
return None
if len(items) != n:
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ales-tsurko/cells | 4cf7e395cd433762bea70cdc863a346f3a6fe1d0 | packaging/macos/python/lib/python3.7/multiprocessing/managers.py | python | Server.number_of_objects | (self, c) | return len(self.id_to_refcount) | Number of shared objects | Number of shared objects | [
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google/tf_mesh_renderer | 7564430975d8239a8a9cdf0c0959d7ac723b9a08 | mesh_renderer/camera_utils.py | python | euler_matrices | (angles) | return tf.transpose(reshaped, [2, 0, 1]) | Computes a XYZ Tait-Bryan (improper Euler angle) rotation.
Returns 4x4 matrices for convenient multiplication with other transformations.
Args:
angles: a [batch_size, 3] tensor containing X, Y, and Z angles in radians.
Returns:
a [batch_size, 4, 4] tensor of matrices. | Computes a XYZ Tait-Bryan (improper Euler angle) rotation. | [
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"""Computes a XYZ Tait-Bryan (improper Euler angle) rotation.
Returns 4x4 matrices for convenient multiplication with other transformations.
Args:
angles: a [batch_size, 3] tensor containing X, Y, and Z angles in radians.
Returns:
a [batch_size, 4, 4] tensor of matrices.
"""
s = tf.sin(angles)
c = tf.cos(angles)
# Rename variables for readability in the matrix definition below.
c0, c1, c2 = (c[:, 0], c[:, 1], c[:, 2])
s0, s1, s2 = (s[:, 0], s[:, 1], s[:, 2])
zeros = tf.zeros_like(s[:, 0])
ones = tf.ones_like(s[:, 0])
# pyformat: disable
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c2 * c1, c2 * s1 * s0 - c0 * s2, s2 * s0 + c2 * c0 * s1, zeros,
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reshaped = tf.reshape(flattened, [4, 4, -1])
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mathics/Mathics | 318e06dea8f1c70758a50cb2f95c9900150e3a68 | mathics/builtin/intfns/combinatorial.py | python | _BooleanDissimilarity.apply | (self, u, v, evaluation) | return self._compute(len(py_u), *counts) | %(name)s[u_List, v_List] | %(name)s[u_List, v_List] | [
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benediktschmitt/py-ts3 | 043a6a896169d39464f6f754e2afd300f74eefa5 | ts3/response.py | python | TS3Response.__getitem__ | (self, index) | return self.parsed[index] | [] | def __getitem__(self, index):
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CLUEbenchmark/CLUE | 5bd39732734afecb490cf18a5212e692dbf2c007 | baselines/models/bert/tokenization.py | python | convert_tokens_to_ids | (vocab, tokens) | return convert_by_vocab(vocab, tokens) | [] | def convert_tokens_to_ids(vocab, tokens):
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/webapp2-2.3/webapp2_extras/appengine/auth/models.py | python | User.get_by_auth_id | (cls, auth_id) | return cls.query(cls.auth_ids == auth_id).get() | Returns a user object based on a auth_id.
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:param auth_id:
String representing a unique id for the user. Examples:
- own:username
- google:username
:returns:
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"""
return cls.query(cls.auth_ids == auth_id).get() | [
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aiogram/aiogram | 4d2d81138681d730270819579f22b3a0001c43a5 | aiogram/bot/api.py | python | check_result | (method_name: str, content_type: str, status_code: int, body: str) | Checks whether `result` is a valid API response.
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log.debug('Response for %s: [%d] "%r"', method_name, status_code, body)
if content_type != 'application/json':
raise exceptions.NetworkError(f"Invalid response with content type {content_type}: \"{body}\"")
try:
result_json = json.loads(body)
except ValueError:
result_json = {}
description = result_json.get('description') or body
parameters = types.ResponseParameters(**result_json.get('parameters', {}) or {})
if HTTPStatus.OK <= status_code <= HTTPStatus.IM_USED:
return result_json.get('result')
elif parameters.retry_after:
raise exceptions.RetryAfter(parameters.retry_after)
elif parameters.migrate_to_chat_id:
raise exceptions.MigrateToChat(parameters.migrate_to_chat_id)
elif status_code == HTTPStatus.BAD_REQUEST:
exceptions.BadRequest.detect(description)
elif status_code == HTTPStatus.NOT_FOUND:
exceptions.NotFound.detect(description)
elif status_code == HTTPStatus.CONFLICT:
exceptions.ConflictError.detect(description)
elif status_code in (HTTPStatus.UNAUTHORIZED, HTTPStatus.FORBIDDEN):
exceptions.Unauthorized.detect(description)
elif status_code == HTTPStatus.REQUEST_ENTITY_TOO_LARGE:
raise exceptions.NetworkError('File too large for uploading. '
'Check telegram api limits https://core.telegram.org/bots/api#senddocument')
elif status_code >= HTTPStatus.INTERNAL_SERVER_ERROR:
if 'restart' in description:
raise exceptions.RestartingTelegram()
raise exceptions.TelegramAPIError(description)
raise exceptions.TelegramAPIError(f"{description} [{status_code}]") | [
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IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/datetime.py | python | _call_tzinfo_method | (tzinfo, methname, tzinfoarg) | return getattr(tzinfo, methname)(tzinfoarg) | [] | def _call_tzinfo_method(tzinfo, methname, tzinfoarg):
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fortharris/Pcode | 147962d160a834c219e12cb456abc130826468e4 | rope/base/pyobjectsdef.py | python | PyFunction.__init__ | (self, pycore, ast_node, parent) | [] | def __init__(self, pycore, ast_node, parent):
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fortharris/Pcode | 147962d160a834c219e12cb456abc130826468e4 | rope/refactor/patchedast.py | python | _PatchingASTWalker._is_elif | (self, node) | return 'elif' in (word, alt_word) | [] | def _is_elif(self, node):
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word = self.source[offset:offset + 4]
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mne-tools/mne-python | f90b303ce66a8415e64edd4605b09ac0179c1ebf | mne/viz/circle.py | python | plot_channel_labels_circle | (labels, colors=None, picks=None, **kwargs) | return _plot_connectivity_circle(con, node_names, **kwargs) | Plot labels for each channel in a circle plot.
.. note:: This primarily makes sense for sEEG channels where each
channel can be assigned an anatomical label as the electrode
passes through various brain areas.
Parameters
----------
labels : dict
Lists of labels (values) associated with each channel (keys).
colors : dict
The color (value) for each label (key).
picks : list | tuple
The channels to consider.
**kwargs : kwargs
Keyword arguments for ``plot_connectivity_circle``.
Returns
-------
fig : instance of matplotlib.figure.Figure
The figure handle.
axes : instance of matplotlib.projections.polar.PolarAxes
The subplot handle. | Plot labels for each channel in a circle plot. | [
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"""Plot labels for each channel in a circle plot.
.. note:: This primarily makes sense for sEEG channels where each
channel can be assigned an anatomical label as the electrode
passes through various brain areas.
Parameters
----------
labels : dict
Lists of labels (values) associated with each channel (keys).
colors : dict
The color (value) for each label (key).
picks : list | tuple
The channels to consider.
**kwargs : kwargs
Keyword arguments for ``plot_connectivity_circle``.
Returns
-------
fig : instance of matplotlib.figure.Figure
The figure handle.
axes : instance of matplotlib.projections.polar.PolarAxes
The subplot handle.
"""
from matplotlib.colors import LinearSegmentedColormap
_validate_type(labels, dict, 'labels')
_validate_type(colors, (dict, None), 'colors')
_validate_type(picks, (list, tuple, None), 'picks')
if picks is not None:
labels = {k: v for k, v in labels.items() if k in picks}
ch_names = list(labels.keys())
all_labels = list(set([label for val in labels.values()
for label in val]))
n_labels = len(all_labels)
if colors is not None:
for label in all_labels:
if label not in colors:
raise ValueError(f'No color provided for {label} in `colors`')
# update all_labels, there may be unconnected labels in colors
all_labels = list(colors.keys())
n_labels = len(all_labels)
# make colormap
label_colors = [colors[label] for label in all_labels]
node_colors = ['black'] * len(ch_names) + label_colors
label_cmap = LinearSegmentedColormap.from_list(
'label_cmap', label_colors, N=len(label_colors))
else:
node_colors = None
node_names = ch_names + all_labels
con = np.zeros((len(node_names), len(node_names))) * np.nan
for idx, ch_name in enumerate(ch_names):
for label in labels[ch_name]:
node_idx = node_names.index(label)
label_color = all_labels.index(label) / n_labels
con[idx, node_idx] = con[node_idx, idx] = label_color # symmetric
# plot
node_order = ch_names + all_labels[::-1]
node_angles = circular_layout(node_names, node_order, start_pos=90,
group_boundaries=[0, len(ch_names)])
# provide defaults but don't overwrite
if 'node_angles' not in kwargs:
kwargs.update(node_angles=node_angles)
if 'colorbar' not in kwargs:
kwargs.update(colorbar=False)
if 'node_colors' not in kwargs:
kwargs.update(node_colors=node_colors)
if 'vmin' not in kwargs:
kwargs.update(vmin=0)
if 'vmax' not in kwargs:
kwargs.update(vmax=1)
if 'colormap' not in kwargs:
kwargs.update(colormap=label_cmap)
return _plot_connectivity_circle(con, node_names, **kwargs) | [
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samuelclay/NewsBlur | 2c45209df01a1566ea105e04d499367f32ac9ad2 | apps/feed_import/models.py | python | OPMLExporter.__init__ | (self, user) | [] | def __init__(self, user):
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keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/parser/aiml_parser.py | python | AIMLParser.pattern_parser | (self) | return self._pattern_parser | [] | def pattern_parser(self):
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plone/Products.CMFPlone | 83137764e3e7e4fe60d03c36dfc6ba9c7c543324 | Products/CMFPlone/interfaces/constrains.py | python | IConstrainTypes.getLocallyAllowedTypes | () | Get the list of FTI ids for the types which should be allowed to be
added in this container. | Get the list of FTI ids for the types which should be allowed to be
added in this container. | [
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Get the list of FTI ids for the types which should be allowed to be
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GeospatialPython/pyshp | 05e18f5171a6346a675646cb8bc7a8f84ed8d5d6 | shapefile.py | python | Writer.__enter__ | (self) | return self | Enter phase of context manager. | Enter phase of context manager. | [
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Enter phase of context manager.
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buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | runtime/python/lib/python2.7/site-packages/_xmlplus/xpath/CoreFunctions.py | python | Not | (context, object) | return (not Conversions.BooleanValue(object) and boolean.true) or boolean.false | Function: <boolean> not(<boolean>) | Function: <boolean> not(<boolean>) | [
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] | def Not(context, object):
"""Function: <boolean> not(<boolean>)"""
return (not Conversions.BooleanValue(object) and boolean.true) or boolean.false | [
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ansible-collections/community.general | 3faffe8f47968a2400ba3c896c8901c03001a194 | plugins/modules/storage/vexata/vexata_volume.py | python | get_volume | (module, array) | Retrieve a named volume if it exists, None if absent. | Retrieve a named volume if it exists, None if absent. | [
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] | def get_volume(module, array):
"""Retrieve a named volume if it exists, None if absent."""
name = module.params['name']
try:
vols = array.list_volumes()
vol = filter(lambda v: v['name'] == name, vols)
if len(vol) == 1:
return vol[0]
else:
return None
except Exception:
module.fail_json(msg='Error while attempting to retrieve volumes.') | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/lib-tk/ttk.py | python | Style.__init__ | (self, master=None) | [] | def __init__(self, master=None):
master = setup_master(master)
if not getattr(master, '_tile_loaded', False):
# Load tile now, if needed
_load_tile(master)
self.master = master
self.tk = self.master.tk | [
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facebookresearch/mobile-vision | f40401a44e86bb3ba9c1b66e7700e15f96b880cb | mobile_cv/arch/layers/misc.py | python | Conv2d.cast | (cls, module: "Conv2d") | return module | Cast mobile_cv.arch.layers.Conv2d to a normal conv2d | Cast mobile_cv.arch.layers.Conv2d to a normal conv2d | [
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] | def cast(cls, module: "Conv2d"):
"""Cast mobile_cv.arch.layers.Conv2d to a normal conv2d"""
assert type(module) == cls
module = copy.deepcopy(module)
assert module.norm is None
assert module.activation is None
module.__class__ = torch.nn.Conv2d
return module | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/astropy-4.0-py3.7-macosx-10.9-x86_64.egg/astropy/table/index.py | python | TableLoc.__getitem__ | (self, item) | return self.table[rows] | Retrieve Table rows by value slice.
Parameters
----------
item : column element, list, ndarray, slice or tuple
Can be a value of the table primary index, a list/ndarray
of such values, or a value slice (both endpoints are included).
If a tuple is provided, the first element must be
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second element must be as above. | Retrieve Table rows by value slice. | [
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] | def __getitem__(self, item):
"""
Retrieve Table rows by value slice.
Parameters
----------
item : column element, list, ndarray, slice or tuple
Can be a value of the table primary index, a list/ndarray
of such values, or a value slice (both endpoints are included).
If a tuple is provided, the first element must be
an index to use instead of the primary key, and the
second element must be as above.
"""
rows = self._get_rows(item)
if len(rows) == 0: # no matches found
raise KeyError(f'No matches found for key {item}')
elif len(rows) == 1: # single row
return self.table[rows[0]]
return self.table[rows] | [
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subbarayudu-j/TheAlgorithms-Python | bb29dc55faf5b98b1e9f0b1f11a9dd15525386a3 | Maths/absMin.py | python | absMin | (x) | return j | # >>>absMin([0,5,1,11])
0
# >>absMin([3,-10,-2])
-2 | # >>>absMin([0,5,1,11])
0
# >>absMin([3,-10,-2])
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] | def absMin(x):
"""
# >>>absMin([0,5,1,11])
0
# >>absMin([3,-10,-2])
-2
"""
j = x[0]
for i in x:
if absVal(i) < absVal(j):
j = i
return j | [
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art-programmer/PlaneNet | ccc4423d278388d01cb3300be992b951b90acc7a | html.py | python | TestCase.test_unicode | (self) | make sure unicode input works and results in unicode output | make sure unicode input works and results in unicode output | [
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] | def test_unicode(self):
'make sure unicode input works and results in unicode output'
h = HTML(newlines=False)
# Python 3 compat
try:
unicode = unicode
TEST = 'euro \xe2\x82\xac'.decode('utf8')
except:
unicode = str
TEST = 'euro €'
h.p(TEST)
self.assertEquals(unicode(h), '<p>%s</p>' % TEST) | [
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wbond/asn1crypto | 9ae350f212532dfee7f185f6b3eda24753249cf3 | asn1crypto/crl.py | python | CertificateList.authority_key_identifier_value | (self) | return self._authority_key_identifier_value | This extension helps in identifying the public key with which to
validate the authenticity of the CRL.
:return:
None or an AuthorityKeyIdentifier object | This extension helps in identifying the public key with which to
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] | def authority_key_identifier_value(self):
"""
This extension helps in identifying the public key with which to
validate the authenticity of the CRL.
:return:
None or an AuthorityKeyIdentifier object
"""
if self._processed_extensions is False:
self._set_extensions()
return self._authority_key_identifier_value | [
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suavecode/SUAVE | 4f83c467c5662b6cc611ce2ab6c0bdd25fd5c0a5 | trunk/SUAVE/Methods/Weights/Correlations/Raymer/prop_system.py | python | nacelle_Raymer | (vehicle, WENG) | return WNAC * Units.lbs | Calculates the nacelle weight based on the Raymer method
Assumptions:
1) All nacelles are identical
2) The number of nacelles is the same as the number of engines
Source:
Aircraft Design: A Conceptual Approach (2nd edition)
Inputs:
vehicle - data dictionary with vehicle properties [dimensionless]
-.ultimate_load: ultimate load factor of aircraft
nacelle - data dictionary for the specific nacelle that is being estimated [dimensionless]
-lenght: total length of engine [m]
-diameter: diameter of nacelle [m]
WENG - dry engine weight [kg]
Outputs:
WNAC: nacelle weight [kg]
Properties Used:
N/A | Calculates the nacelle weight based on the Raymer method
Assumptions:
1) All nacelles are identical
2) The number of nacelles is the same as the number of engines
Source:
Aircraft Design: A Conceptual Approach (2nd edition) | [
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"same",
"as",
"the",
"number",
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"engines... | def nacelle_Raymer(vehicle, WENG):
""" Calculates the nacelle weight based on the Raymer method
Assumptions:
1) All nacelles are identical
2) The number of nacelles is the same as the number of engines
Source:
Aircraft Design: A Conceptual Approach (2nd edition)
Inputs:
vehicle - data dictionary with vehicle properties [dimensionless]
-.ultimate_load: ultimate load factor of aircraft
nacelle - data dictionary for the specific nacelle that is being estimated [dimensionless]
-lenght: total length of engine [m]
-diameter: diameter of nacelle [m]
WENG - dry engine weight [kg]
Outputs:
WNAC: nacelle weight [kg]
Properties Used:
N/A
"""
nacelle_tag = list(vehicle.nacelles.keys())[0]
ref_nacelle = vehicle.nacelles[nacelle_tag]
NENG = len(vehicle.nacelles)
Kng = 1 # assuming the engine is not pylon mounted
Nlt = ref_nacelle.length / Units.ft
Nw = ref_nacelle.diameter / Units.ft
Wec = 2.331 * WENG ** 0.901 * 1.18
Sn = 2 * np.pi * Nw/2 * Nlt + np.pi * Nw**2/4 * 2
WNAC = 0.6724 * Kng * Nlt ** 0.1 * Nw ** 0.294 * vehicle.envelope.ultimate_load ** 0.119 \
* Wec ** 0.611 * NENG * 0.984 * Sn ** 0.224
return WNAC * Units.lbs | [
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andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/plugins/infrastructure/server_header.py | python | server_header.get_long_desc | (self) | return """
This plugin GETs the server header and saves the result to the
knowledge base.
Nothing strange, just do a GET request to the url and save the server
headers to the kb. A smarter way to check the server type is with the
hmap plugin.
""" | :return: A DETAILED description of the plugin functions and features. | :return: A DETAILED description of the plugin functions and features. | [
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] | def get_long_desc(self):
"""
:return: A DETAILED description of the plugin functions and features.
"""
return """
This plugin GETs the server header and saves the result to the
knowledge base.
Nothing strange, just do a GET request to the url and save the server
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XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | python3.8.2/Lib/OpenSSL/SSL.py | python | Connection.bio_read | (self, bufsiz) | return _ffi.buffer(buf, result)[:] | If the Connection was created with a memory BIO, this method can be
used to read bytes from the write end of that memory BIO. Many
Connection methods will add bytes which must be read in this manner or
the buffer will eventually fill up and the Connection will be able to
take no further actions.
:param bufsiz: The maximum number of bytes to read
:return: The string read. | If the Connection was created with a memory BIO, this method can be
used to read bytes from the write end of that memory BIO. Many
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the buffer will eventually fill up and the Connection will be able to
take no further actions. | [
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Connection methods will add bytes which must be read in this manner or
the buffer will eventually fill up and the Connection will be able to
take no further actions.
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buf = _no_zero_allocator("char[]", bufsiz)
result = _lib.BIO_read(self._from_ssl, buf, bufsiz)
if result <= 0:
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return _ffi.buffer(buf, result)[:] | [
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n1nj4sec/pupy | a5d766ea81fdfe3bc2c38c9bdaf10e9b75af3b39 | pupy/pupylib/PupyJob.py | python | Thread._get_my_tid | (self) | determines this (self's) thread id | determines this (self's) thread id | [
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if not self.isAlive():
raise threading.ThreadError("the thread is not active")
# do we have it cached?
if hasattr(self, "_thread_id"):
return self._thread_id
# no, look for it in the _active dict
for tid, tobj in threading._active.items():
if tobj is self:
self._thread_id = tid
return tid
raise AssertionError("could not determine the thread's id") | [
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