nwo stringlengths 5 106 | sha stringlengths 40 40 | path stringlengths 4 174 | language stringclasses 1
value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
yanzhou/CnkiSpider | 348d7114f3ffee7b0a134cf6c5d01150433f3fde | src/bs4/element.py | python | _alias | (attr) | return alias | Alias one attribute name to another for backward compatibility | Alias one attribute name to another for backward compatibility | [
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"attribute",
"name",
"to",
"another",
"for",
"backward",
"compatibility"
] | def _alias(attr):
"""Alias one attribute name to another for backward compatibility"""
@property
def alias(self):
return getattr(self, attr)
@alias.setter
def alias(self):
return setattr(self, attr)
return alias | [
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ConvLab/ConvLab | a04582a77537c1a706fbf64715baa9ad0be1301a | convlab/lib/util.py | python | write_as_df | (data, data_path) | return data_path | Submethod to write data as DataFrame | Submethod to write data as DataFrame | [
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'''Submethod to write data as DataFrame'''
df = cast_df(data)
ext = get_file_ext(data_path)
df.to_csv(data_path, index=False)
return data_path | [
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sidewalklabs/s2sphere | d1d067e8c06e5fbaf0cc0158bade947b4a03a438 | s2sphere/sphere.py | python | LatLngRect.is_empty | (self) | return self.lat().is_empty() | [] | def is_empty(self):
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conan7882/CNN-Visualization | e08650cc126a3a489f7d633dc18bf3f0009792b1 | lib/models/cam.py | python | BaseCAM._get_optimizer | (self) | return tf.train.AdamOptimizer(
beta1=0.5, learning_rate=self._learning_rate) | [] | def _get_optimizer(self):
return tf.train.AdamOptimizer(
beta1=0.5, learning_rate=self._learning_rate) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/kombu/transport/virtual/base.py | python | Transport.on_message_ready | (self, channel, message, queue) | [] | def on_message_ready(self, channel, message, queue):
if not queue or queue not in self._callbacks:
raise KeyError(
'Message for queue {0!r} without consumers: {1}'.format(
queue, message))
self._callbacks[queue](message) | [
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grow/grow | 97fc21730b6a674d5d33948d94968e79447ce433 | grow/server/manager.py | python | print_server_ready_message | (pod, host, port) | return (url_root, extra_urls) | [] | def print_server_ready_message(pod, host, port):
try:
home_doc = pod.get_home_doc()
root_path = home_doc.url.path if home_doc and home_doc.exists else '/'
except:
# Allow the user to fix the problem without restarting the server manually.
root_path = '/'
pod.logger.exception('Failed to determine root URL path.')
url_base = 'http://{}:{}/'.format(host, port)
url_root = 'http://{}:{}{}'.format(host, port, root_path)
messages = ServerMessages()
messages.add_message('Pod:', pod.root, colors.HIGHLIGHT)
messages.add_message('Server:', url_root, colors.HIGHLIGHT)
# Trigger the dev manager message hook.
extra_urls = pod.extensions_controller.trigger(
'dev_manager_message', messages.add_message, url_base, url_root) or []
messages.add_message(
'Ready.', 'Press ctrl-c to quit.', colors.SUCCESS, colors.SUCCESS)
messages.print(pod.logger.info)
return (url_root, extra_urls) | [
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alicevision/meshroom | 92004286fd0bc8ab36bd3575b4c0166090e665e1 | meshroom/core/node.py | python | nodeFactory | (nodeDict, name=None) | return node | Create a node instance by deserializing the given node data.
If the serialized data matches the corresponding node type description, a Node instance is created.
If any compatibility issue occurs, a NodeCompatibility instance is created instead.
Args:
nodeDict (dict): the serialization of the node
name (str): (optional) the node's name
Returns:
BaseNode: the created node | Create a node instance by deserializing the given node data.
If the serialized data matches the corresponding node type description, a Node instance is created.
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Create a node instance by deserializing the given node data.
If the serialized data matches the corresponding node type description, a Node instance is created.
If any compatibility issue occurs, a NodeCompatibility instance is created instead.
Args:
nodeDict (dict): the serialization of the node
name (str): (optional) the node's name
Returns:
BaseNode: the created node
"""
nodeType = nodeDict["nodeType"]
# retro-compatibility: inputs were previously saved as "attributes"
if "inputs" not in nodeDict and "attributes" in nodeDict:
nodeDict["inputs"] = nodeDict["attributes"]
del nodeDict["attributes"]
# get node inputs/outputs
inputs = nodeDict.get("inputs", {})
outputs = nodeDict.get("outputs", {})
version = nodeDict.get("version", None)
internalFolder = nodeDict.get("internalFolder", None)
position = Position(*nodeDict.get("position", []))
compatibilityIssue = None
nodeDesc = None
try:
nodeDesc = meshroom.core.nodesDesc[nodeType]
except KeyError:
# unknown node type
compatibilityIssue = CompatibilityIssue.UnknownNodeType
if nodeDesc:
# compare serialized node version with current node version
currentNodeVersion = meshroom.core.nodeVersion(nodeDesc)
# if both versions are available, check for incompatibility in major version
if version and currentNodeVersion and Version(version).major != Version(currentNodeVersion).major:
compatibilityIssue = CompatibilityIssue.VersionConflict
# in other cases, check attributes compatibility between serialized node and its description
else:
# check that the node has the exact same set of inputs/outputs as its description
if sorted([attr.name for attr in nodeDesc.inputs]) != sorted(inputs.keys()) or \
sorted([attr.name for attr in nodeDesc.outputs]) != sorted(outputs.keys()):
compatibilityIssue = CompatibilityIssue.DescriptionConflict
# verify that all inputs match their descriptions
for attrName, value in inputs.items():
if not CompatibilityNode.attributeDescFromName(nodeDesc.inputs, attrName, value):
compatibilityIssue = CompatibilityIssue.DescriptionConflict
break
# verify that all outputs match their descriptions
for attrName, value in outputs.items():
if not CompatibilityNode.attributeDescFromName(nodeDesc.outputs, attrName, value):
compatibilityIssue = CompatibilityIssue.DescriptionConflict
break
if compatibilityIssue is None:
node = Node(nodeType, position, **inputs)
else:
logging.warning("Compatibility issue detected for node '{}': {}".format(name, compatibilityIssue.name))
node = CompatibilityNode(nodeType, nodeDict, position, compatibilityIssue)
# retro-compatibility: no internal folder saved
# can't spawn meaningful CompatibilityNode with precomputed outputs
# => automatically try to perform node upgrade
if not internalFolder and nodeDesc:
logging.warning("No serialized output data: performing automatic upgrade on '{}'".format(name))
node = node.upgrade()
return node | [
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/rdfvalues/objects.py | python | SHA256HashID.FromData | (cls, data) | return SHA256HashID(h) | [] | def FromData(cls, data):
h = hashlib.sha256(data).digest()
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niosus/EasyClangComplete | 3b16eb17735aaa3f56bb295fc5481b269ee9f2ef | plugin/clang/cindex35.py | python | Type.element_count | (self) | return result | Retrieve the number of elements in this type.
Returns an int.
If the Type is not an array or vector, this raises. | Retrieve the number of elements in this type. | [
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"""Retrieve the number of elements in this type.
Returns an int.
If the Type is not an array or vector, this raises.
"""
result = conf.lib.clang_getNumElements(self)
if result < 0:
raise Exception('Type does not have elements.')
return result | [
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yiyiliao/deep_marching_cubes | afcad99742435eb0d57d32770befed74faaad2ab | marching_cube/model/table.py | python | get_full_table | () | return [
[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
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[1, 8, 3, 9, 8, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 2, 10, 0, 2, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 8, 3, 2, 10, 8, 10, 9, 8, -1, -1, -1, -1, -1, -1, -1],
[3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 11, 2, 8, 11, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 11, 2, 1, 9, 11, 9, 8, 11, -1, -1, -1, -1, -1, -1, -1],
[3, 10, 1, 11, 10, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 10, 1, 0, 8, 10, 8, 11, 10, -1, -1, -1, -1, -1, -1, -1],
[3, 9, 0, 3, 11, 9, 11, 10, 9, -1, -1, -1, -1, -1, -1, -1],
[9, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 3, 0, 7, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 1, 9, 4, 7, 1, 7, 3, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 4, 7, 3, 0, 4, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1],
[9, 2, 10, 9, 0, 2, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1],
[2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4, -1, -1, -1, -1],
[8, 4, 7, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 4, 7, 11, 2, 4, 2, 0, 4, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 1, 8, 4, 7, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1],
[4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1, -1, -1, -1, -1],
[3, 10, 1, 3, 11, 10, 7, 8, 4, -1, -1, -1, -1, -1, -1, -1],
[1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4, -1, -1, -1, -1],
[4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3, -1, -1, -1, -1],
[4, 7, 11, 4, 11, 9, 9, 11, 10, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 5, 4, 1, 5, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 5, 4, 8, 3, 5, 3, 1, 5, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 1, 2, 10, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1],
[5, 2, 10, 5, 4, 2, 4, 0, 2, -1, -1, -1, -1, -1, -1, -1],
[2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8, -1, -1, -1, -1],
[9, 5, 4, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 11, 2, 0, 8, 11, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1],
[0, 5, 4, 0, 1, 5, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1],
[2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5, -1, -1, -1, -1],
[10, 3, 11, 10, 1, 3, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10, -1, -1, -1, -1],
[5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3, -1, -1, -1, -1],
[5, 4, 8, 5, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1],
[9, 7, 8, 5, 7, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 3, 0, 9, 5, 3, 5, 7, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 7, 8, 0, 1, 7, 1, 5, 7, -1, -1, -1, -1, -1, -1, -1],
[1, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 7, 8, 9, 5, 7, 10, 1, 2, -1, -1, -1, -1, -1, -1, -1],
[10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3, -1, -1, -1, -1],
[8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2, -1, -1, -1, -1],
[2, 10, 5, 2, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1],
[7, 9, 5, 7, 8, 9, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11, -1, -1, -1, -1],
[2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7, -1, -1, -1, -1],
[11, 2, 1, 11, 1, 7, 7, 1, 5, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11, -1, -1, -1, -1],
[5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0, -1],
[11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0, -1],
[11, 10, 5, 7, 11, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 1, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 8, 3, 1, 9, 8, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 5, 2, 6, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 5, 1, 2, 6, 3, 0, 8, -1, -1, -1, -1, -1, -1, -1],
[9, 6, 5, 9, 0, 6, 0, 2, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8, -1, -1, -1, -1],
[2, 3, 11, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 0, 8, 11, 2, 0, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11, -1, -1, -1, -1],
[6, 3, 11, 6, 5, 3, 5, 1, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6, -1, -1, -1, -1],
[3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9, -1, -1, -1, -1],
[6, 5, 9, 6, 9, 11, 11, 9, 8, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 3, 0, 4, 7, 3, 6, 5, 10, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 5, 10, 6, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1],
[10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4, -1, -1, -1, -1],
[6, 1, 2, 6, 5, 1, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7, -1, -1, -1, -1],
[8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6, -1, -1, -1, -1],
[7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9, -1],
[3, 11, 2, 7, 8, 4, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11, -1, -1, -1, -1],
[0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1],
[9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6, -1],
[8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6, -1, -1, -1, -1],
[5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11, -1],
[0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7, -1],
[6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9, -1, -1, -1, -1],
[10, 4, 9, 6, 4, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 10, 6, 4, 9, 10, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1],
[10, 0, 1, 10, 6, 0, 6, 4, 0, -1, -1, -1, -1, -1, -1, -1],
[8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10, -1, -1, -1, -1],
[1, 4, 9, 1, 2, 4, 2, 6, 4, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4, -1, -1, -1, -1],
[0, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 3, 2, 8, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1],
[10, 4, 9, 10, 6, 4, 11, 2, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6, -1, -1, -1, -1],
[3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10, -1, -1, -1, -1],
[6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1, -1],
[9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3, -1, -1, -1, -1],
[8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1, -1],
[3, 11, 6, 3, 6, 0, 0, 6, 4, -1, -1, -1, -1, -1, -1, -1],
[6, 4, 8, 11, 6, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 10, 6, 7, 8, 10, 8, 9, 10, -1, -1, -1, -1, -1, -1, -1],
[0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10, -1, -1, -1, -1],
[10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0, -1, -1, -1, -1],
[10, 6, 7, 10, 7, 1, 1, 7, 3, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7, -1, -1, -1, -1],
[2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9, -1],
[7, 8, 0, 7, 0, 6, 6, 0, 2, -1, -1, -1, -1, -1, -1, -1],
[7, 3, 2, 6, 7, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7, -1, -1, -1, -1],
[2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7, -1],
[1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11, -1],
[11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1, -1, -1, -1, -1],
[8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6, -1],
[0, 9, 1, 11, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0, -1, -1, -1, -1],
[7, 11, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 6, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 1, 9, 8, 3, 1, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1],
[10, 1, 2, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 3, 0, 8, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1],
[2, 9, 0, 2, 10, 9, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1],
[6, 11, 7, 2, 10, 3, 10, 8, 3, 10, 9, 8, -1, -1, -1, -1],
[7, 2, 3, 6, 2, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 0, 8, 7, 6, 0, 6, 2, 0, -1, -1, -1, -1, -1, -1, -1],
[2, 7, 6, 2, 3, 7, 0, 1, 9, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 2, 1, 8, 6, 1, 9, 8, 8, 7, 6, -1, -1, -1, -1],
[10, 7, 6, 10, 1, 7, 1, 3, 7, -1, -1, -1, -1, -1, -1, -1],
[10, 7, 6, 1, 7, 10, 1, 8, 7, 1, 0, 8, -1, -1, -1, -1],
[0, 3, 7, 0, 7, 10, 0, 10, 9, 6, 10, 7, -1, -1, -1, -1],
[7, 6, 10, 7, 10, 8, 8, 10, 9, -1, -1, -1, -1, -1, -1, -1],
[6, 8, 4, 11, 8, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 6, 11, 3, 0, 6, 0, 4, 6, -1, -1, -1, -1, -1, -1, -1],
[8, 6, 11, 8, 4, 6, 9, 0, 1, -1, -1, -1, -1, -1, -1, -1],
[9, 4, 6, 9, 6, 3, 9, 3, 1, 11, 3, 6, -1, -1, -1, -1],
[6, 8, 4, 6, 11, 8, 2, 10, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 3, 0, 11, 0, 6, 11, 0, 4, 6, -1, -1, -1, -1],
[4, 11, 8, 4, 6, 11, 0, 2, 9, 2, 10, 9, -1, -1, -1, -1],
[10, 9, 3, 10, 3, 2, 9, 4, 3, 11, 3, 6, 4, 6, 3, -1],
[8, 2, 3, 8, 4, 2, 4, 6, 2, -1, -1, -1, -1, -1, -1, -1],
[0, 4, 2, 4, 6, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 2, 3, 4, 2, 4, 6, 4, 3, 8, -1, -1, -1, -1],
[1, 9, 4, 1, 4, 2, 2, 4, 6, -1, -1, -1, -1, -1, -1, -1],
[8, 1, 3, 8, 6, 1, 8, 4, 6, 6, 10, 1, -1, -1, -1, -1],
[10, 1, 0, 10, 0, 6, 6, 0, 4, -1, -1, -1, -1, -1, -1, -1],
[4, 6, 3, 4, 3, 8, 6, 10, 3, 0, 3, 9, 10, 9, 3, -1],
[10, 9, 4, 6, 10, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 5, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 4, 9, 5, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 0, 1, 5, 4, 0, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1],
[11, 7, 6, 8, 3, 4, 3, 5, 4, 3, 1, 5, -1, -1, -1, -1],
[9, 5, 4, 10, 1, 2, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1],
[6, 11, 7, 1, 2, 10, 0, 8, 3, 4, 9, 5, -1, -1, -1, -1],
[7, 6, 11, 5, 4, 10, 4, 2, 10, 4, 0, 2, -1, -1, -1, -1],
[3, 4, 8, 3, 5, 4, 3, 2, 5, 10, 5, 2, 11, 7, 6, -1],
[7, 2, 3, 7, 6, 2, 5, 4, 9, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, 0, 8, 6, 0, 6, 2, 6, 8, 7, -1, -1, -1, -1],
[3, 6, 2, 3, 7, 6, 1, 5, 0, 5, 4, 0, -1, -1, -1, -1],
[6, 2, 8, 6, 8, 7, 2, 1, 8, 4, 8, 5, 1, 5, 8, -1],
[9, 5, 4, 10, 1, 6, 1, 7, 6, 1, 3, 7, -1, -1, -1, -1],
[1, 6, 10, 1, 7, 6, 1, 0, 7, 8, 7, 0, 9, 5, 4, -1],
[4, 0, 10, 4, 10, 5, 0, 3, 10, 6, 10, 7, 3, 7, 10, -1],
[7, 6, 10, 7, 10, 8, 5, 4, 10, 4, 8, 10, -1, -1, -1, -1],
[6, 9, 5, 6, 11, 9, 11, 8, 9, -1, -1, -1, -1, -1, -1, -1],
[3, 6, 11, 0, 6, 3, 0, 5, 6, 0, 9, 5, -1, -1, -1, -1],
[0, 11, 8, 0, 5, 11, 0, 1, 5, 5, 6, 11, -1, -1, -1, -1],
[6, 11, 3, 6, 3, 5, 5, 3, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 9, 5, 11, 9, 11, 8, 11, 5, 6, -1, -1, -1, -1],
[0, 11, 3, 0, 6, 11, 0, 9, 6, 5, 6, 9, 1, 2, 10, -1],
[11, 8, 5, 11, 5, 6, 8, 0, 5, 10, 5, 2, 0, 2, 5, -1],
[6, 11, 3, 6, 3, 5, 2, 10, 3, 10, 5, 3, -1, -1, -1, -1],
[5, 8, 9, 5, 2, 8, 5, 6, 2, 3, 8, 2, -1, -1, -1, -1],
[9, 5, 6, 9, 6, 0, 0, 6, 2, -1, -1, -1, -1, -1, -1, -1],
[1, 5, 8, 1, 8, 0, 5, 6, 8, 3, 8, 2, 6, 2, 8, -1],
[1, 5, 6, 2, 1, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 3, 6, 1, 6, 10, 3, 8, 6, 5, 6, 9, 8, 9, 6, -1],
[10, 1, 0, 10, 0, 6, 9, 5, 0, 5, 6, 0, -1, -1, -1, -1],
[0, 3, 8, 5, 6, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[10, 5, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 5, 10, 7, 5, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 5, 10, 11, 7, 5, 8, 3, 0, -1, -1, -1, -1, -1, -1, -1],
[5, 11, 7, 5, 10, 11, 1, 9, 0, -1, -1, -1, -1, -1, -1, -1],
[10, 7, 5, 10, 11, 7, 9, 8, 1, 8, 3, 1, -1, -1, -1, -1],
[11, 1, 2, 11, 7, 1, 7, 5, 1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 1, 2, 7, 1, 7, 5, 7, 2, 11, -1, -1, -1, -1],
[9, 7, 5, 9, 2, 7, 9, 0, 2, 2, 11, 7, -1, -1, -1, -1],
[7, 5, 2, 7, 2, 11, 5, 9, 2, 3, 2, 8, 9, 8, 2, -1],
[2, 5, 10, 2, 3, 5, 3, 7, 5, -1, -1, -1, -1, -1, -1, -1],
[8, 2, 0, 8, 5, 2, 8, 7, 5, 10, 2, 5, -1, -1, -1, -1],
[9, 0, 1, 5, 10, 3, 5, 3, 7, 3, 10, 2, -1, -1, -1, -1],
[9, 8, 2, 9, 2, 1, 8, 7, 2, 10, 2, 5, 7, 5, 2, -1],
[1, 3, 5, 3, 7, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 7, 0, 7, 1, 1, 7, 5, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 3, 9, 3, 5, 5, 3, 7, -1, -1, -1, -1, -1, -1, -1],
[9, 8, 7, 5, 9, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[5, 8, 4, 5, 10, 8, 10, 11, 8, -1, -1, -1, -1, -1, -1, -1],
[5, 0, 4, 5, 11, 0, 5, 10, 11, 11, 3, 0, -1, -1, -1, -1],
[0, 1, 9, 8, 4, 10, 8, 10, 11, 10, 4, 5, -1, -1, -1, -1],
[10, 11, 4, 10, 4, 5, 11, 3, 4, 9, 4, 1, 3, 1, 4, -1],
[2, 5, 1, 2, 8, 5, 2, 11, 8, 4, 5, 8, -1, -1, -1, -1],
[0, 4, 11, 0, 11, 3, 4, 5, 11, 2, 11, 1, 5, 1, 11, -1],
[0, 2, 5, 0, 5, 9, 2, 11, 5, 4, 5, 8, 11, 8, 5, -1],
[9, 4, 5, 2, 11, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 5, 10, 3, 5, 2, 3, 4, 5, 3, 8, 4, -1, -1, -1, -1],
[5, 10, 2, 5, 2, 4, 4, 2, 0, -1, -1, -1, -1, -1, -1, -1],
[3, 10, 2, 3, 5, 10, 3, 8, 5, 4, 5, 8, 0, 1, 9, -1],
[5, 10, 2, 5, 2, 4, 1, 9, 2, 9, 4, 2, -1, -1, -1, -1],
[8, 4, 5, 8, 5, 3, 3, 5, 1, -1, -1, -1, -1, -1, -1, -1],
[0, 4, 5, 1, 0, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 4, 5, 8, 5, 3, 9, 0, 5, 0, 3, 5, -1, -1, -1, -1],
[9, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 11, 7, 4, 9, 11, 9, 10, 11, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 4, 9, 7, 9, 11, 7, 9, 10, 11, -1, -1, -1, -1],
[1, 10, 11, 1, 11, 4, 1, 4, 0, 7, 4, 11, -1, -1, -1, -1],
[3, 1, 4, 3, 4, 8, 1, 10, 4, 7, 4, 11, 10, 11, 4, -1],
[4, 11, 7, 9, 11, 4, 9, 2, 11, 9, 1, 2, -1, -1, -1, -1],
[9, 7, 4, 9, 11, 7, 9, 1, 11, 2, 11, 1, 0, 8, 3, -1],
[11, 7, 4, 11, 4, 2, 2, 4, 0, -1, -1, -1, -1, -1, -1, -1],
[11, 7, 4, 11, 4, 2, 8, 3, 4, 3, 2, 4, -1, -1, -1, -1],
[2, 9, 10, 2, 7, 9, 2, 3, 7, 7, 4, 9, -1, -1, -1, -1],
[9, 10, 7, 9, 7, 4, 10, 2, 7, 8, 7, 0, 2, 0, 7, -1],
[3, 7, 10, 3, 10, 2, 7, 4, 10, 1, 10, 0, 4, 0, 10, -1],
[1, 10, 2, 8, 7, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 1, 4, 1, 7, 7, 1, 3, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 1, 4, 1, 7, 0, 8, 1, 8, 7, 1, -1, -1, -1, -1],
[4, 0, 3, 7, 4, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 8, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 10, 8, 10, 11, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 9, 3, 9, 11, 11, 9, 10, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 10, 0, 10, 8, 8, 10, 11, -1, -1, -1, -1, -1, -1, -1],
[3, 1, 10, 11, 3, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 11, 1, 11, 9, 9, 11, 8, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 9, 3, 9, 11, 1, 2, 9, 2, 11, 9, -1, -1, -1, -1],
[0, 2, 11, 8, 0, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 2, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 3, 8, 2, 8, 10, 10, 8, 9, -1, -1, -1, -1, -1, -1, -1],
[9, 10, 2, 0, 9, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 3, 8, 2, 8, 10, 0, 1, 8, 1, 10, 8, -1, -1, -1, -1],
[1, 10, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 3, 8, 9, 1, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 9, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 3, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
] | Return the look-up-table of the Marching Cubes algorithm | Return the look-up-table of the Marching Cubes algorithm | [
"Return",
"the",
"look",
"-",
"up",
"-",
"table",
"of",
"the",
"Marching",
"Cubes",
"algorithm"
] | def get_full_table():
"""Return the look-up-table of the Marching Cubes algorithm"""
return [
[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 8, 3, 9, 8, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 2, 10, 0, 2, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 8, 3, 2, 10, 8, 10, 9, 8, -1, -1, -1, -1, -1, -1, -1],
[3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 11, 2, 8, 11, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 11, 2, 1, 9, 11, 9, 8, 11, -1, -1, -1, -1, -1, -1, -1],
[3, 10, 1, 11, 10, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 10, 1, 0, 8, 10, 8, 11, 10, -1, -1, -1, -1, -1, -1, -1],
[3, 9, 0, 3, 11, 9, 11, 10, 9, -1, -1, -1, -1, -1, -1, -1],
[9, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 3, 0, 7, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 1, 9, 4, 7, 1, 7, 3, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 4, 7, 3, 0, 4, 1, 2, 10, -1, -1, -1, -1, -1, -1, -1],
[9, 2, 10, 9, 0, 2, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1],
[2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4, -1, -1, -1, -1],
[8, 4, 7, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 4, 7, 11, 2, 4, 2, 0, 4, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 1, 8, 4, 7, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1],
[4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1, -1, -1, -1, -1],
[3, 10, 1, 3, 11, 10, 7, 8, 4, -1, -1, -1, -1, -1, -1, -1],
[1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4, -1, -1, -1, -1],
[4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3, -1, -1, -1, -1],
[4, 7, 11, 4, 11, 9, 9, 11, 10, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 5, 4, 1, 5, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 5, 4, 8, 3, 5, 3, 1, 5, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 1, 2, 10, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1],
[5, 2, 10, 5, 4, 2, 4, 0, 2, -1, -1, -1, -1, -1, -1, -1],
[2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8, -1, -1, -1, -1],
[9, 5, 4, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 11, 2, 0, 8, 11, 4, 9, 5, -1, -1, -1, -1, -1, -1, -1],
[0, 5, 4, 0, 1, 5, 2, 3, 11, -1, -1, -1, -1, -1, -1, -1],
[2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5, -1, -1, -1, -1],
[10, 3, 11, 10, 1, 3, 9, 5, 4, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10, -1, -1, -1, -1],
[5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3, -1, -1, -1, -1],
[5, 4, 8, 5, 8, 10, 10, 8, 11, -1, -1, -1, -1, -1, -1, -1],
[9, 7, 8, 5, 7, 9, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 3, 0, 9, 5, 3, 5, 7, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 7, 8, 0, 1, 7, 1, 5, 7, -1, -1, -1, -1, -1, -1, -1],
[1, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 7, 8, 9, 5, 7, 10, 1, 2, -1, -1, -1, -1, -1, -1, -1],
[10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3, -1, -1, -1, -1],
[8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2, -1, -1, -1, -1],
[2, 10, 5, 2, 5, 3, 3, 5, 7, -1, -1, -1, -1, -1, -1, -1],
[7, 9, 5, 7, 8, 9, 3, 11, 2, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11, -1, -1, -1, -1],
[2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7, -1, -1, -1, -1],
[11, 2, 1, 11, 1, 7, 7, 1, 5, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11, -1, -1, -1, -1],
[5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0, -1],
[11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0, -1],
[11, 10, 5, 7, 11, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 1, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 8, 3, 1, 9, 8, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 5, 2, 6, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 5, 1, 2, 6, 3, 0, 8, -1, -1, -1, -1, -1, -1, -1],
[9, 6, 5, 9, 0, 6, 0, 2, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8, -1, -1, -1, -1],
[2, 3, 11, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 0, 8, 11, 2, 0, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11, -1, -1, -1, -1],
[6, 3, 11, 6, 5, 3, 5, 1, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6, -1, -1, -1, -1],
[3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9, -1, -1, -1, -1],
[6, 5, 9, 6, 9, 11, 11, 9, 8, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 3, 0, 4, 7, 3, 6, 5, 10, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 5, 10, 6, 8, 4, 7, -1, -1, -1, -1, -1, -1, -1],
[10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4, -1, -1, -1, -1],
[6, 1, 2, 6, 5, 1, 4, 7, 8, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7, -1, -1, -1, -1],
[8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6, -1, -1, -1, -1],
[7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9, -1],
[3, 11, 2, 7, 8, 4, 10, 6, 5, -1, -1, -1, -1, -1, -1, -1],
[5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11, -1, -1, -1, -1],
[0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6, -1, -1, -1, -1],
[9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6, -1],
[8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6, -1, -1, -1, -1],
[5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11, -1],
[0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7, -1],
[6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9, -1, -1, -1, -1],
[10, 4, 9, 6, 4, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 10, 6, 4, 9, 10, 0, 8, 3, -1, -1, -1, -1, -1, -1, -1],
[10, 0, 1, 10, 6, 0, 6, 4, 0, -1, -1, -1, -1, -1, -1, -1],
[8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10, -1, -1, -1, -1],
[1, 4, 9, 1, 2, 4, 2, 6, 4, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4, -1, -1, -1, -1],
[0, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 3, 2, 8, 2, 4, 4, 2, 6, -1, -1, -1, -1, -1, -1, -1],
[10, 4, 9, 10, 6, 4, 11, 2, 3, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6, -1, -1, -1, -1],
[3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10, -1, -1, -1, -1],
[6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1, -1],
[9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3, -1, -1, -1, -1],
[8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1, -1],
[3, 11, 6, 3, 6, 0, 0, 6, 4, -1, -1, -1, -1, -1, -1, -1],
[6, 4, 8, 11, 6, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 10, 6, 7, 8, 10, 8, 9, 10, -1, -1, -1, -1, -1, -1, -1],
[0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10, -1, -1, -1, -1],
[10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0, -1, -1, -1, -1],
[10, 6, 7, 10, 7, 1, 1, 7, 3, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7, -1, -1, -1, -1],
[2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9, -1],
[7, 8, 0, 7, 0, 6, 6, 0, 2, -1, -1, -1, -1, -1, -1, -1],
[7, 3, 2, 6, 7, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7, -1, -1, -1, -1],
[2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7, -1],
[1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11, -1],
[11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1, -1, -1, -1, -1],
[8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6, -1],
[0, 9, 1, 11, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0, -1, -1, -1, -1],
[7, 11, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 6, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 8, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 9, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[8, 1, 9, 8, 3, 1, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1],
[10, 1, 2, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 3, 0, 8, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1],
[2, 9, 0, 2, 10, 9, 6, 11, 7, -1, -1, -1, -1, -1, -1, -1],
[6, 11, 7, 2, 10, 3, 10, 8, 3, 10, 9, 8, -1, -1, -1, -1],
[7, 2, 3, 6, 2, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[7, 0, 8, 7, 6, 0, 6, 2, 0, -1, -1, -1, -1, -1, -1, -1],
[2, 7, 6, 2, 3, 7, 0, 1, 9, -1, -1, -1, -1, -1, -1, -1],
[1, 6, 2, 1, 8, 6, 1, 9, 8, 8, 7, 6, -1, -1, -1, -1],
[10, 7, 6, 10, 1, 7, 1, 3, 7, -1, -1, -1, -1, -1, -1, -1],
[10, 7, 6, 1, 7, 10, 1, 8, 7, 1, 0, 8, -1, -1, -1, -1],
[0, 3, 7, 0, 7, 10, 0, 10, 9, 6, 10, 7, -1, -1, -1, -1],
[7, 6, 10, 7, 10, 8, 8, 10, 9, -1, -1, -1, -1, -1, -1, -1],
[6, 8, 4, 11, 8, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 6, 11, 3, 0, 6, 0, 4, 6, -1, -1, -1, -1, -1, -1, -1],
[8, 6, 11, 8, 4, 6, 9, 0, 1, -1, -1, -1, -1, -1, -1, -1],
[9, 4, 6, 9, 6, 3, 9, 3, 1, 11, 3, 6, -1, -1, -1, -1],
[6, 8, 4, 6, 11, 8, 2, 10, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 3, 0, 11, 0, 6, 11, 0, 4, 6, -1, -1, -1, -1],
[4, 11, 8, 4, 6, 11, 0, 2, 9, 2, 10, 9, -1, -1, -1, -1],
[10, 9, 3, 10, 3, 2, 9, 4, 3, 11, 3, 6, 4, 6, 3, -1],
[8, 2, 3, 8, 4, 2, 4, 6, 2, -1, -1, -1, -1, -1, -1, -1],
[0, 4, 2, 4, 6, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 9, 0, 2, 3, 4, 2, 4, 6, 4, 3, 8, -1, -1, -1, -1],
[1, 9, 4, 1, 4, 2, 2, 4, 6, -1, -1, -1, -1, -1, -1, -1],
[8, 1, 3, 8, 6, 1, 8, 4, 6, 6, 10, 1, -1, -1, -1, -1],
[10, 1, 0, 10, 0, 6, 6, 0, 4, -1, -1, -1, -1, -1, -1, -1],
[4, 6, 3, 4, 3, 8, 6, 10, 3, 0, 3, 9, 10, 9, 3, -1],
[10, 9, 4, 6, 10, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 5, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 4, 9, 5, 11, 7, 6, -1, -1, -1, -1, -1, -1, -1],
[5, 0, 1, 5, 4, 0, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1],
[11, 7, 6, 8, 3, 4, 3, 5, 4, 3, 1, 5, -1, -1, -1, -1],
[9, 5, 4, 10, 1, 2, 7, 6, 11, -1, -1, -1, -1, -1, -1, -1],
[6, 11, 7, 1, 2, 10, 0, 8, 3, 4, 9, 5, -1, -1, -1, -1],
[7, 6, 11, 5, 4, 10, 4, 2, 10, 4, 0, 2, -1, -1, -1, -1],
[3, 4, 8, 3, 5, 4, 3, 2, 5, 10, 5, 2, 11, 7, 6, -1],
[7, 2, 3, 7, 6, 2, 5, 4, 9, -1, -1, -1, -1, -1, -1, -1],
[9, 5, 4, 0, 8, 6, 0, 6, 2, 6, 8, 7, -1, -1, -1, -1],
[3, 6, 2, 3, 7, 6, 1, 5, 0, 5, 4, 0, -1, -1, -1, -1],
[6, 2, 8, 6, 8, 7, 2, 1, 8, 4, 8, 5, 1, 5, 8, -1],
[9, 5, 4, 10, 1, 6, 1, 7, 6, 1, 3, 7, -1, -1, -1, -1],
[1, 6, 10, 1, 7, 6, 1, 0, 7, 8, 7, 0, 9, 5, 4, -1],
[4, 0, 10, 4, 10, 5, 0, 3, 10, 6, 10, 7, 3, 7, 10, -1],
[7, 6, 10, 7, 10, 8, 5, 4, 10, 4, 8, 10, -1, -1, -1, -1],
[6, 9, 5, 6, 11, 9, 11, 8, 9, -1, -1, -1, -1, -1, -1, -1],
[3, 6, 11, 0, 6, 3, 0, 5, 6, 0, 9, 5, -1, -1, -1, -1],
[0, 11, 8, 0, 5, 11, 0, 1, 5, 5, 6, 11, -1, -1, -1, -1],
[6, 11, 3, 6, 3, 5, 5, 3, 1, -1, -1, -1, -1, -1, -1, -1],
[1, 2, 10, 9, 5, 11, 9, 11, 8, 11, 5, 6, -1, -1, -1, -1],
[0, 11, 3, 0, 6, 11, 0, 9, 6, 5, 6, 9, 1, 2, 10, -1],
[11, 8, 5, 11, 5, 6, 8, 0, 5, 10, 5, 2, 0, 2, 5, -1],
[6, 11, 3, 6, 3, 5, 2, 10, 3, 10, 5, 3, -1, -1, -1, -1],
[5, 8, 9, 5, 2, 8, 5, 6, 2, 3, 8, 2, -1, -1, -1, -1],
[9, 5, 6, 9, 6, 0, 0, 6, 2, -1, -1, -1, -1, -1, -1, -1],
[1, 5, 8, 1, 8, 0, 5, 6, 8, 3, 8, 2, 6, 2, 8, -1],
[1, 5, 6, 2, 1, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[1, 3, 6, 1, 6, 10, 3, 8, 6, 5, 6, 9, 8, 9, 6, -1],
[10, 1, 0, 10, 0, 6, 9, 5, 0, 5, 6, 0, -1, -1, -1, -1],
[0, 3, 8, 5, 6, 10, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[10, 5, 6, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 5, 10, 7, 5, 11, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[11, 5, 10, 11, 7, 5, 8, 3, 0, -1, -1, -1, -1, -1, -1, -1],
[5, 11, 7, 5, 10, 11, 1, 9, 0, -1, -1, -1, -1, -1, -1, -1],
[10, 7, 5, 10, 11, 7, 9, 8, 1, 8, 3, 1, -1, -1, -1, -1],
[11, 1, 2, 11, 7, 1, 7, 5, 1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 3, 1, 2, 7, 1, 7, 5, 7, 2, 11, -1, -1, -1, -1],
[9, 7, 5, 9, 2, 7, 9, 0, 2, 2, 11, 7, -1, -1, -1, -1],
[7, 5, 2, 7, 2, 11, 5, 9, 2, 3, 2, 8, 9, 8, 2, -1],
[2, 5, 10, 2, 3, 5, 3, 7, 5, -1, -1, -1, -1, -1, -1, -1],
[8, 2, 0, 8, 5, 2, 8, 7, 5, 10, 2, 5, -1, -1, -1, -1],
[9, 0, 1, 5, 10, 3, 5, 3, 7, 3, 10, 2, -1, -1, -1, -1],
[9, 8, 2, 9, 2, 1, 8, 7, 2, 10, 2, 5, 7, 5, 2, -1],
[1, 3, 5, 3, 7, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 8, 7, 0, 7, 1, 1, 7, 5, -1, -1, -1, -1, -1, -1, -1],
[9, 0, 3, 9, 3, 5, 5, 3, 7, -1, -1, -1, -1, -1, -1, -1],
[9, 8, 7, 5, 9, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[5, 8, 4, 5, 10, 8, 10, 11, 8, -1, -1, -1, -1, -1, -1, -1],
[5, 0, 4, 5, 11, 0, 5, 10, 11, 11, 3, 0, -1, -1, -1, -1],
[0, 1, 9, 8, 4, 10, 8, 10, 11, 10, 4, 5, -1, -1, -1, -1],
[10, 11, 4, 10, 4, 5, 11, 3, 4, 9, 4, 1, 3, 1, 4, -1],
[2, 5, 1, 2, 8, 5, 2, 11, 8, 4, 5, 8, -1, -1, -1, -1],
[0, 4, 11, 0, 11, 3, 4, 5, 11, 2, 11, 1, 5, 1, 11, -1],
[0, 2, 5, 0, 5, 9, 2, 11, 5, 4, 5, 8, 11, 8, 5, -1],
[9, 4, 5, 2, 11, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[2, 5, 10, 3, 5, 2, 3, 4, 5, 3, 8, 4, -1, -1, -1, -1],
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[9, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 11, 7, 4, 9, 11, 9, 10, 11, -1, -1, -1, -1, -1, -1, -1],
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[3, 1, 4, 3, 4, 8, 1, 10, 4, 7, 4, 11, 10, 11, 4, -1],
[4, 11, 7, 9, 11, 4, 9, 2, 11, 9, 1, 2, -1, -1, -1, -1],
[9, 7, 4, 9, 11, 7, 9, 1, 11, 2, 11, 1, 0, 8, 3, -1],
[11, 7, 4, 11, 4, 2, 2, 4, 0, -1, -1, -1, -1, -1, -1, -1],
[11, 7, 4, 11, 4, 2, 8, 3, 4, 3, 2, 4, -1, -1, -1, -1],
[2, 9, 10, 2, 7, 9, 2, 3, 7, 7, 4, 9, -1, -1, -1, -1],
[9, 10, 7, 9, 7, 4, 10, 2, 7, 8, 7, 0, 2, 0, 7, -1],
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[4, 9, 1, 4, 1, 7, 7, 1, 3, -1, -1, -1, -1, -1, -1, -1],
[4, 9, 1, 4, 1, 7, 0, 8, 1, 8, 7, 1, -1, -1, -1, -1],
[4, 0, 3, 7, 4, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[4, 8, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[9, 10, 8, 10, 11, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[3, 0, 9, 3, 9, 11, 11, 9, 10, -1, -1, -1, -1, -1, -1, -1],
[0, 1, 10, 0, 10, 8, 8, 10, 11, -1, -1, -1, -1, -1, -1, -1],
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[1, 3, 8, 9, 1, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 9, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[0, 3, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
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Dozed12/df-style-worldgen | 937455d54f4b02df9c4b10ae6418f4c932fd97bf | libtcodpy.py | python | image_hflip | (image) | [] | def image_hflip(image) :
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google/trax | d6cae2067dedd0490b78d831033607357e975015 | trax/layers/initializers.py | python | InitializerFromFile | (path) | return Initializer | Loads parameters from .npy file. | Loads parameters from .npy file. | [
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"""Loads parameters from .npy file."""
def Initializer(shape, rng):
del rng
logging.info('Loading pretrained embeddings from %s', path)
with tf.io.gfile.GFile(path, 'rb') as f:
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/envs/env.py | python | Env.reward_range | (self) | return self._rewards.range | Return the range of the reward function; a tuple corresponding to the min and max possible rewards | Return the range of the reward function; a tuple corresponding to the min and max possible rewards | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/wagtail_bak/api/v2/endpoints.py | python | BaseAPIEndpoint.get_meta_fields | (cls, model) | return cls._convert_api_fields(cls.meta_fields + list(getattr(model, 'api_meta_fields', ()))) | [] | def get_meta_fields(cls, model):
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serge-sans-paille/pythran | f9f73aa5a965adc4ebcb91a439784dbe9ef911fa | pythran/analyses/range_values.py | python | RangeValuesBase.visit_Name | (self, node) | return self.add(node, self.result[node.id]) | Get range for parameters for examples or false branching. | Get range for parameters for examples or false branching. | [
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maurosoria/dirsearch | b83e68c8fdf360ab06be670d7b92b263262ee5b1 | thirdparty/requests/cookies.py | python | cookiejar_from_dict | (cookie_dict, cookiejar=None, overwrite=True) | return cookiejar | Returns a CookieJar from a key/value dictionary.
:param cookie_dict: Dict of key/values to insert into CookieJar.
:param cookiejar: (optional) A cookiejar to add the cookies to.
:param overwrite: (optional) If False, will not replace cookies
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] | def cookiejar_from_dict(cookie_dict, cookiejar=None, overwrite=True):
"""Returns a CookieJar from a key/value dictionary.
:param cookie_dict: Dict of key/values to insert into CookieJar.
:param cookiejar: (optional) A cookiejar to add the cookies to.
:param overwrite: (optional) If False, will not replace cookies
already in the jar with new ones.
:rtype: CookieJar
"""
if cookiejar is None:
cookiejar = RequestsCookieJar()
if cookie_dict is not None:
names_from_jar = [cookie.name for cookie in cookiejar]
for name in cookie_dict:
if overwrite or (name not in names_from_jar):
cookiejar.set_cookie(create_cookie(name, cookie_dict[name]))
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jantman/misc-scripts | dba5680bafbc5c5d2d9d4abcc305c57df373cd26 | lastpass2vault.py | python | LastpassToVault._connect_lp | (self, lp_user) | return lp | Connect to LastPass; return the connection.
:param lp_user: LastPass username
:type lp_user: str
:returns: connected LastPass Vault object
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"""
Connect to LastPass; return the connection.
:param lp_user: LastPass username
:type lp_user: str
:returns: connected LastPass Vault object
:rtype: lastpass.vault.Vault
"""
logger.debug('Authenticating to LastPass with username: %s', lp_user)
passwd = getpass('LastPass Password: ').strip()
mfa = input_func(
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).strip()
if mfa == '':
logger.info('Authenticating to LastPass without MFA')
lp = lastpass.Vault.open_remote(lp_user, passwd)
else:
logger.info('Authenticating to LastPass with MFA code %s', mfa)
lp = lastpass.Vault.open_remote(
lp_user, passwd, multifactor_password=mfa)
return lp | [
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samuelclay/NewsBlur | 2c45209df01a1566ea105e04d499367f32ac9ad2 | apps/social/models.py | python | MSocialServices.set_photo | (self, service) | return profile | [] | def set_photo(self, service):
profile = MSocialProfile.get_user(self.user_id)
if service == 'nothing':
service = None
profile.photo_service = service
if not service:
profile.photo_url = None
elif service == 'twitter':
profile.photo_url = self.twitter_picture_url
elif service == 'facebook':
profile.photo_url = self.facebook_picture_url
elif service == 'upload':
profile.photo_url = self.upload_picture_url
elif service == 'gravatar':
user = User.objects.get(pk=self.user_id)
profile.photo_url = "https://www.gravatar.com/avatar/" + \
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profile.save()
return profile | [
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feincms/feincms | be35576fa86083a969ae56aaf848173d1a5a3c5d | feincms/utils/managers.py | python | ActiveAwareContentManagerMixin.active | (self) | return self.apply_active_filters(self) | Return only currently active objects. | Return only currently active objects. | [
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Return only currently active objects.
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visinf/n3net | 5d5883a374aab343ca4091d8a072e83629d53516 | src_correspondences/network.py | python | MyNetwork.comp | (self, data) | Goodie for competitors | Goodie for competitors | [
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"""Goodie for competitors"""
# Run competitors on dataset
for test_mode in ["test", "valid"]:
comp_process(
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getattr(self, "res_dir_" + test_mode[:2]), self.config) | [
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freqtrade/freqtrade | 13651fd3be8d5ce8dcd7c94b920bda4e00b75aca | freqtrade/exchange/exchange.py | python | Exchange.validate_stakecurrency | (self, stake_currency: str) | Checks stake-currency against available currencies on the exchange.
Only runs on startup. If markets have not been loaded, there's been a problem with
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:param stake_currency: Stake-currency to validate
:raise: OperationalException if stake-currency is not available. | Checks stake-currency against available currencies on the exchange.
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f"Available currencies are: {', '.join(quote_currencies)}") | [
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mathics/Mathics | 318e06dea8f1c70758a50cb2f95c9900150e3a68 | mathics/builtin/numbers/algebra.py | python | CoefficientList.apply_noform | (self, expr, evaluation) | return evaluation.message("CoefficientList", "argtu") | CoefficientList[expr_] | CoefficientList[expr_] | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/gui/editors/displaytabs/citationembedlist.py | python | CitationEmbedList._handle_drag | (self, row, handle) | A CITATION_LINK has been dragged | A CITATION_LINK has been dragged | [
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"""
A CITATION_LINK has been dragged
"""
if handle:
objct = self.dbstate.db.get_citation_from_handle(handle)
if isinstance(objct, Citation):
try:
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EditCitation(self.dbstate, self.uistate, self.track,
objct, callback=self.add_callback,
callertitle=self.callertitle)
except WindowActiveError:
from ...dialog import WarningDialog
WarningDialog(_("Cannot share this reference"),
self.__blocked_text(),
parent=self.uistate.window)
else:
raise ValueError("selection must be either source or citation") | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/operator.py | python | truth | (a) | return True if a else False | Return True if a is true, False otherwise. | Return True if a is true, False otherwise. | [
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] | https://github.com/Source-Python-Dev-Team/Source.Python/blob/d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb/addons/source-python/Python3/operator.py#L57-L59 | |
allegroai/clearml | 5953dc6eefadcdfcc2bdbb6a0da32be58823a5af | examples/frameworks/scikit-learn/sklearn_matplotlib_example.py | python | plot_learning_curve | (estimator, title, X, y, axes=None, ylim=None, cv=None, n_jobs=None,
train_sizes=np.linspace(.1, 1.0, 5)) | return plt | Generate 3 plots: the test and training learning curve, the training
samples vs fit times curve, the fit times vs score curve.
Parameters
----------
estimator : object type that implements the "fit" and "predict" methods
An object of that type which is cloned for each validation.
title : string
Title for the chart.
X : array-like, shape (n_samples, n_features)
Training vector, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape (n_samples) or (n_samples, n_features), optional
Target relative to X for classification or regression;
None for unsupervised learning.
axes : array of 3 axes, optional (default=None)
Axes to use for plotting the curves.
ylim : tuple, shape (ymin, ymax), optional
Defines minimum and maximum yvalues plotted.
cv : int, cross-validation generator or an iterable, optional
Determines the cross-validation splitting strategy.
Possible inputs for cv are:
- None, to use the default 5-fold cross-validation,
- integer, to specify the number of folds.
- :term:`CV splitter`,
- An iterable yielding (train, test) splits as arrays of indices.
For integer/None inputs, if ``y`` is binary or multiclass,
:class:`StratifiedKFold` used. If the estimator is not a classifier
or if ``y`` is neither binary nor multiclass, :class:`KFold` is used.
Refer :ref:`User Guide <cross_validation>` for the various
cross-validators that can be used here.
n_jobs : int or None, optional (default=None)
Number of jobs to run in parallel.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
train_sizes : array-like, shape (n_ticks,), dtype float or int
Relative or absolute numbers of training examples that will be used to
generate the learning curve. If the dtype is float, it is regarded as a
fraction of the maximum size of the training set (that is determined
by the selected validation method), i.e. it has to be within (0, 1].
Otherwise it is interpreted as absolute sizes of the training sets.
Note that for classification the number of samples usually have to
be big enough to contain at least one sample from each class.
(default: np.linspace(0.1, 1.0, 5)) | Generate 3 plots: the test and training learning curve, the training
samples vs fit times curve, the fit times vs score curve. | [
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] | def plot_learning_curve(estimator, title, X, y, axes=None, ylim=None, cv=None, n_jobs=None,
train_sizes=np.linspace(.1, 1.0, 5)):
"""
Generate 3 plots: the test and training learning curve, the training
samples vs fit times curve, the fit times vs score curve.
Parameters
----------
estimator : object type that implements the "fit" and "predict" methods
An object of that type which is cloned for each validation.
title : string
Title for the chart.
X : array-like, shape (n_samples, n_features)
Training vector, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape (n_samples) or (n_samples, n_features), optional
Target relative to X for classification or regression;
None for unsupervised learning.
axes : array of 3 axes, optional (default=None)
Axes to use for plotting the curves.
ylim : tuple, shape (ymin, ymax), optional
Defines minimum and maximum yvalues plotted.
cv : int, cross-validation generator or an iterable, optional
Determines the cross-validation splitting strategy.
Possible inputs for cv are:
- None, to use the default 5-fold cross-validation,
- integer, to specify the number of folds.
- :term:`CV splitter`,
- An iterable yielding (train, test) splits as arrays of indices.
For integer/None inputs, if ``y`` is binary or multiclass,
:class:`StratifiedKFold` used. If the estimator is not a classifier
or if ``y`` is neither binary nor multiclass, :class:`KFold` is used.
Refer :ref:`User Guide <cross_validation>` for the various
cross-validators that can be used here.
n_jobs : int or None, optional (default=None)
Number of jobs to run in parallel.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
train_sizes : array-like, shape (n_ticks,), dtype float or int
Relative or absolute numbers of training examples that will be used to
generate the learning curve. If the dtype is float, it is regarded as a
fraction of the maximum size of the training set (that is determined
by the selected validation method), i.e. it has to be within (0, 1].
Otherwise it is interpreted as absolute sizes of the training sets.
Note that for classification the number of samples usually have to
be big enough to contain at least one sample from each class.
(default: np.linspace(0.1, 1.0, 5))
"""
if axes is None:
_, axes = plt.subplots(1, 3, figsize=(20, 5))
axes[0].set_title(title)
if ylim is not None:
axes[0].set_ylim(*ylim)
axes[0].set_xlabel("Training examples")
axes[0].set_ylabel("Score")
train_sizes, train_scores, test_scores, fit_times, _ = \
learning_curve(estimator, X, y, cv=cv, n_jobs=n_jobs,
train_sizes=train_sizes,
return_times=True)
train_scores_mean = np.mean(train_scores, axis=1)
train_scores_std = np.std(train_scores, axis=1)
test_scores_mean = np.mean(test_scores, axis=1)
test_scores_std = np.std(test_scores, axis=1)
fit_times_mean = np.mean(fit_times, axis=1)
fit_times_std = np.std(fit_times, axis=1)
# Plot learning curve
axes[0].grid()
axes[0].fill_between(train_sizes, train_scores_mean - train_scores_std,
train_scores_mean + train_scores_std, alpha=0.1,
color="r")
axes[0].fill_between(train_sizes, test_scores_mean - test_scores_std,
test_scores_mean + test_scores_std, alpha=0.1,
color="g")
axes[0].plot(train_sizes, train_scores_mean, 'o-', color="r",
label="Training score")
axes[0].plot(train_sizes, test_scores_mean, 'o-', color="g",
label="Cross-validation score")
axes[0].legend(loc="best")
# Plot n_samples vs fit_times
axes[1].grid()
axes[1].plot(train_sizes, fit_times_mean, 'o-')
axes[1].fill_between(train_sizes, fit_times_mean - fit_times_std,
fit_times_mean + fit_times_std, alpha=0.1)
axes[1].set_xlabel("Training examples")
axes[1].set_ylabel("fit_times")
axes[1].set_title("Scalability of the model")
# Plot fit_time vs score
axes[2].grid()
axes[2].plot(fit_times_mean, test_scores_mean, 'o-')
axes[2].fill_between(fit_times_mean, test_scores_mean - test_scores_std,
test_scores_mean + test_scores_std, alpha=0.1)
axes[2].set_xlabel("fit_times")
axes[2].set_ylabel("Score")
axes[2].set_title("Performance of the model")
return plt | [
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nextml/NEXT | 4c8f4d5a66376a18c047f4c9409f73c75925bf07 | apps/PoolBasedTripletMDS/algs/UncertaintySampling/utilsMDS.py | python | computeEmbedding | (n,d,S,num_random_restarts=0,max_num_passes=0,max_iter_GD=0,max_norm=0,epsilon=0.01,verbose=False) | return X_old,emp_loss_old | Computes an embedding of n objects in d dimensions usin the triplets of S.
S is a list of triplets such that for each q in S, q = [i,j,k] means that
object k should be closer to i than j.
Inputs:
(int) n : number of objects in embedding
(int) d : desired dimension
(list [(int) i, (int) j,(int) k]) S : list of triplets, i,j,k must be in [n].
(int) num_random_restarts : number of random restarts (nonconvex
optimization, may converge to local minima). E.g., 9 random restarts
means take the best of 10 runs of the optimization routine.
(int) max_num_passes : maximum number of passes over data SGD makes before proceeding to GD (default equals 16)
(int) max_iter_GD: maximum number of GD iteration (default equals 50)
(float) max_norm : the maximum allowed norm of any one object (default equals 10*d)
(float) epsilon : parameter that controls stopping condition, smaller means more accurate (default = 0.01)
(boolean) verbose : outputs some progress (default equals False)
Outputs:
(numpy.ndarray) X : output embedding
(float) gamma : Equal to a/b where a is max row norm of the gradient matrix and b is the avg row norm of the centered embedding matrix X. This is a means to determine how close the current solution is to the "best" solution. | Computes an embedding of n objects in d dimensions usin the triplets of S.
S is a list of triplets such that for each q in S, q = [i,j,k] means that
object k should be closer to i than j. | [
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"""
Computes an embedding of n objects in d dimensions usin the triplets of S.
S is a list of triplets such that for each q in S, q = [i,j,k] means that
object k should be closer to i than j.
Inputs:
(int) n : number of objects in embedding
(int) d : desired dimension
(list [(int) i, (int) j,(int) k]) S : list of triplets, i,j,k must be in [n].
(int) num_random_restarts : number of random restarts (nonconvex
optimization, may converge to local minima). E.g., 9 random restarts
means take the best of 10 runs of the optimization routine.
(int) max_num_passes : maximum number of passes over data SGD makes before proceeding to GD (default equals 16)
(int) max_iter_GD: maximum number of GD iteration (default equals 50)
(float) max_norm : the maximum allowed norm of any one object (default equals 10*d)
(float) epsilon : parameter that controls stopping condition, smaller means more accurate (default = 0.01)
(boolean) verbose : outputs some progress (default equals False)
Outputs:
(numpy.ndarray) X : output embedding
(float) gamma : Equal to a/b where a is max row norm of the gradient matrix and b is the avg row norm of the centered embedding matrix X. This is a means to determine how close the current solution is to the "best" solution.
"""
if max_num_passes==0:
max_num_passes_SGD = 16
else:
max_num_passes_SGD = max_num_passes
if max_iter_GD ==0:
max_iter_GD = 50
X_old = None
emp_loss_old = float('inf')
num_restarts = -1
while num_restarts < num_random_restarts:
num_restarts += 1
ts = time.time()
X,acc = computeEmbeddingWithEpochSGD(n,d,S,max_num_passes=max_num_passes_SGD,max_norm=max_norm,epsilon=epsilon,verbose=verbose)
te_sgd = time.time()-ts
ts = time.time()
X_new,emp_loss_new,hinge_loss_new,acc_new = computeEmbeddingWithGD(X,S,max_iters=max_iter_GD,max_norm=max_norm,epsilon=epsilon,verbose=verbose)
te_gd = time.time()-ts
if emp_loss_new<emp_loss_old:
X_old = X_new
emp_loss_old = emp_loss_new
if verbose:
print "restart %d: emp_loss = %f, hinge_loss = %f, duration=%f+%f" %(num_restarts,emp_loss_new,hinge_loss_new,te_sgd,te_gd)
return X_old,emp_loss_old | [
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/dev/pipelines/pipeline_run.py | python | pipeline_run_add_tag | (run_id, tags, organization=None, project=None, detect=None) | return tags | Add tag(s) for a pipeline run.
:param run_id: ID of the pipeline run.
:type run_id: int
:param tags: Tag(s) to be added to the pipeline run. [Comma seperated values]
:type tags: str
:rtype: list of str | Add tag(s) for a pipeline run.
:param run_id: ID of the pipeline run.
:type run_id: int
:param tags: Tag(s) to be added to the pipeline run. [Comma seperated values]
:type tags: str
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"t... | def pipeline_run_add_tag(run_id, tags, organization=None, project=None, detect=None):
""" Add tag(s) for a pipeline run.
:param run_id: ID of the pipeline run.
:type run_id: int
:param tags: Tag(s) to be added to the pipeline run. [Comma seperated values]
:type tags: str
:rtype: list of str
"""
organization, project = resolve_instance_and_project(detect=detect,
organization=organization,
project=project)
client = get_build_client(organization)
tags = list(map(str, tags.split(',')))
if len(tags) == 1:
tags = client.add_build_tag(
project=project, build_id=run_id, tag=tags[0])
else:
tags = client.add_build_tags(
tags=tags, project=project, build_id=run_id)
return tags | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/preview/deployed_devices/fleet/deployment.py | python | DeploymentList.stream | (self, limit=None, page_size=None) | return self._version.stream(page, limits['limit']) | Streams DeploymentInstance records from the API as a generator stream.
This operation lazily loads records as efficiently as possible until the limit
is reached.
The results are returned as a generator, so this operation is memory efficient.
:param int limit: Upper limit for the number of records to return. stream()
guarantees to never return more than limit. Default is no limit
:param int page_size: Number of records to fetch per request, when not set will use
the default value of 50 records. If no page_size is defined
but a limit is defined, stream() will attempt to read the
limit with the most efficient page size, i.e. min(limit, 1000)
:returns: Generator that will yield up to limit results
:rtype: list[twilio.rest.preview.deployed_devices.fleet.deployment.DeploymentInstance] | Streams DeploymentInstance records from the API as a generator stream.
This operation lazily loads records as efficiently as possible until the limit
is reached.
The results are returned as a generator, so this operation is memory efficient. | [
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"""
Streams DeploymentInstance records from the API as a generator stream.
This operation lazily loads records as efficiently as possible until the limit
is reached.
The results are returned as a generator, so this operation is memory efficient.
:param int limit: Upper limit for the number of records to return. stream()
guarantees to never return more than limit. Default is no limit
:param int page_size: Number of records to fetch per request, when not set will use
the default value of 50 records. If no page_size is defined
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:returns: Generator that will yield up to limit results
:rtype: list[twilio.rest.preview.deployed_devices.fleet.deployment.DeploymentInstance]
"""
limits = self._version.read_limits(limit, page_size)
page = self.page(page_size=limits['page_size'], )
return self._version.stream(page, limits['limit']) | [
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PanJinquan/tensorflow_models_learning | e7a2773d526e01c76fc8366868099ca3d7a819b4 | slim/datasets/download_and_convert_mnist.py | python | _extract_labels | (filename, num_labels) | return labels | Extract the labels into a vector of int64 label IDs.
Args:
filename: The path to an MNIST labels file.
num_labels: The number of labels in the file.
Returns:
A numpy array of shape [number_of_labels] | Extract the labels into a vector of int64 label IDs. | [
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] | def _extract_labels(filename, num_labels):
"""Extract the labels into a vector of int64 label IDs.
Args:
filename: The path to an MNIST labels file.
num_labels: The number of labels in the file.
Returns:
A numpy array of shape [number_of_labels]
"""
print('Extracting labels from: ', filename)
with gzip.open(filename) as bytestream:
bytestream.read(8)
buf = bytestream.read(1 * num_labels)
labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)
return labels | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/yaml/__init__.py | python | safe_dump_all | (documents, stream=None, **kwds) | return dump_all(documents, stream, Dumper=SafeDumper, **kwds) | Serialize a sequence of Python objects into a YAML stream.
Produce only basic YAML tags.
If stream is None, return the produced string instead. | Serialize a sequence of Python objects into a YAML stream.
Produce only basic YAML tags.
If stream is None, return the produced string instead. | [
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"""
Serialize a sequence of Python objects into a YAML stream.
Produce only basic YAML tags.
If stream is None, return the produced string instead.
"""
return dump_all(documents, stream, Dumper=SafeDumper, **kwds) | [
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baidu/DuReader | 43577e29435f5abcb7b02ce6a0019b3f42b1221d | DuReader-2.0/paddle/vocab.py | python | Vocab.get_token | (self, idx) | gets the token corresponding to idx, returns unk token if idx is not in vocab
Args:
idx: an integer
returns:
a token string | gets the token corresponding to idx, returns unk token if idx is not in vocab
Args:
idx: an integer
returns:
a token string | [
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"""
gets the token corresponding to idx, returns unk token if idx is not in vocab
Args:
idx: an integer
returns:
a token string
"""
try:
return self.id2token[idx]
except KeyError:
return self.unk_token | [
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] | https://github.com/baidu/DuReader/blob/43577e29435f5abcb7b02ce6a0019b3f42b1221d/DuReader-2.0/paddle/vocab.py#L82-L93 | ||
benedekrozemberczki/GAM | cd66582215d6f06441ce93981e76af0214b292f3 | src/utils.py | python | tab_printer | (args) | Function to print the logs in a nice tabular format.
:param args: Parameters used for the model. | Function to print the logs in a nice tabular format.
:param args: Parameters used for the model. | [
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] | def tab_printer(args):
"""
Function to print the logs in a nice tabular format.
:param args: Parameters used for the model.
"""
args = vars(args)
keys = sorted(args.keys())
t = Texttable()
t.add_rows([["Parameter", "Value"]])
t.add_rows([[k.replace("_", " ").capitalize(), args[k]] for k in keys])
print(t.draw()) | [
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francisck/DanderSpritz_docs | 86bb7caca5a957147f120b18bb5c31f299914904 | Python/Core/Lib/sysconfig.py | python | get_config_vars | (*args) | With no arguments, return a dictionary of all configuration
variables relevant for the current platform.
On Unix, this means every variable defined in Python's installed Makefile;
On Windows and Mac OS it's a much smaller set.
With arguments, return a list of values that result from looking up
each argument in the configuration variable dictionary. | With no arguments, return a dictionary of all configuration
variables relevant for the current platform.
On Unix, this means every variable defined in Python's installed Makefile;
On Windows and Mac OS it's a much smaller set.
With arguments, return a list of values that result from looking up
each argument in the configuration variable dictionary. | [
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"""With no arguments, return a dictionary of all configuration
variables relevant for the current platform.
On Unix, this means every variable defined in Python's installed Makefile;
On Windows and Mac OS it's a much smaller set.
With arguments, return a list of values that result from looking up
each argument in the configuration variable dictionary.
"""
global _CONFIG_VARS
import re
if _CONFIG_VARS is None:
_CONFIG_VARS = {}
_CONFIG_VARS['prefix'] = _PREFIX
_CONFIG_VARS['exec_prefix'] = _EXEC_PREFIX
_CONFIG_VARS['py_version'] = _PY_VERSION
_CONFIG_VARS['py_version_short'] = _PY_VERSION_SHORT
_CONFIG_VARS['py_version_nodot'] = _PY_VERSION[0] + _PY_VERSION[2]
_CONFIG_VARS['base'] = _PREFIX
_CONFIG_VARS['platbase'] = _EXEC_PREFIX
_CONFIG_VARS['projectbase'] = _PROJECT_BASE
if os.name in ('nt', 'os2'):
_init_non_posix(_CONFIG_VARS)
if os.name == 'posix':
_init_posix(_CONFIG_VARS)
_CONFIG_VARS['userbase'] = _getuserbase()
if 'srcdir' not in _CONFIG_VARS:
_CONFIG_VARS['srcdir'] = _PROJECT_BASE
if _PYTHON_BUILD and os.name == 'posix':
base = _PROJECT_BASE
try:
cwd = os.getcwd()
except OSError:
cwd = None
if not os.path.isabs(_CONFIG_VARS['srcdir']) and base != cwd:
srcdir = os.path.join(base, _CONFIG_VARS['srcdir'])
_CONFIG_VARS['srcdir'] = os.path.normpath(srcdir)
if sys.platform == 'darwin':
kernel_version = os.uname()[2]
major_version = int(kernel_version.split('.')[0])
if major_version < 8:
for key in ('LDFLAGS', 'BASECFLAGS', 'CFLAGS', 'PY_CFLAGS', 'BLDSHARED'):
flags = _CONFIG_VARS[key]
flags = re.sub('-arch\\s+\\w+\\s', ' ', flags)
flags = re.sub('-isysroot [^ \t]*', ' ', flags)
_CONFIG_VARS[key] = flags
else:
if 'ARCHFLAGS' in os.environ:
arch = os.environ['ARCHFLAGS']
for key in ('LDFLAGS', 'BASECFLAGS', 'CFLAGS', 'PY_CFLAGS', 'BLDSHARED'):
flags = _CONFIG_VARS[key]
flags = re.sub('-arch\\s+\\w+\\s', ' ', flags)
flags = flags + ' ' + arch
_CONFIG_VARS[key] = flags
CFLAGS = _CONFIG_VARS.get('CFLAGS', '')
m = re.search('-isysroot\\s+(\\S+)', CFLAGS)
if m is not None:
sdk = m.group(1)
if not os.path.exists(sdk):
for key in ('LDFLAGS', 'BASECFLAGS', 'CFLAGS', 'PY_CFLAGS',
'BLDSHARED'):
flags = _CONFIG_VARS[key]
flags = re.sub('-isysroot\\s+\\S+(\\s|$)', ' ', flags)
_CONFIG_VARS[key] = flags
if args:
vals = []
for name in args:
vals.append(_CONFIG_VARS.get(name))
return vals
else:
return _CONFIG_VARS
return | [
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ahmetcemturan/SFACT | 7576e29ba72b33e5058049b77b7b558875542747 | fabmetheus_utilities/geometry/geometry_utilities/matrix.py | python | getTransformedVector3 | (tetragrid, vector3) | return getTransformedVector3Blindly(tetragrid, vector3) | Get the vector3 multiplied by a matrix. | Get the vector3 multiplied by a matrix. | [
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] | def getTransformedVector3(tetragrid, vector3):
'Get the vector3 multiplied by a matrix.'
if getIsIdentityTetragridOrNone(tetragrid):
return vector3.copy()
return getTransformedVector3Blindly(tetragrid, vector3) | [
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akshaybahadur21/Digit-Recognizer | 703fa8728d4a053af37fe07a97169b776520e01b | Digit-Recognizer/Digit_Recognizer_DL.py | python | softmax | (z) | return sm, cache | [] | def softmax(z):
cache = z
z -= np.max(z)
sm = (np.exp(z).T / np.sum(np.exp(z), axis=1))
return sm, cache | [
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vertexproject/synapse | 8173f43cb5fba5ca2648d12a659afb432139b0a7 | synapse/lib/hive.py | python | Hive.open | (self, full) | return await self._getHiveNode(full) | Open and return a hive Node().
Args:
full (tuple): A full path tuple.
Returns:
Node: A Hive node. | Open and return a hive Node(). | [
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] | async def open(self, full):
'''
Open and return a hive Node().
Args:
full (tuple): A full path tuple.
Returns:
Node: A Hive node.
'''
return await self._getHiveNode(full) | [
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andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/plugins/attack/db/sqlmap/tamper/versionedmorekeywords.py | python | tamper | (payload, **kwargs) | return retVal | Encloses each keyword with versioned MySQL comment
Requirement:
* MySQL >= 5.1.13
Tested against:
* MySQL 5.1.56, 5.5.11
Notes:
* Useful to bypass several web application firewalls when the
back-end database management system is MySQL
>>> tamper('1 UNION ALL SELECT NULL, NULL, CONCAT(CHAR(58,122,114,115,58),IFNULL(CAST(CURRENT_USER() AS CHAR),CHAR(32)),CHAR(58,115,114,121,58))#')
'1/*!UNION*//*!ALL*//*!SELECT*//*!NULL*/,/*!NULL*/,/*!CONCAT*/(/*!CHAR*/(58,122,114,115,58),/*!IFNULL*/(CAST(/*!CURRENT_USER*/()/*!AS*//*!CHAR*/),/*!CHAR*/(32)),/*!CHAR*/(58,115,114,121,58))#' | Encloses each keyword with versioned MySQL comment | [
"Encloses",
"each",
"keyword",
"with",
"versioned",
"MySQL",
"comment"
] | def tamper(payload, **kwargs):
"""
Encloses each keyword with versioned MySQL comment
Requirement:
* MySQL >= 5.1.13
Tested against:
* MySQL 5.1.56, 5.5.11
Notes:
* Useful to bypass several web application firewalls when the
back-end database management system is MySQL
>>> tamper('1 UNION ALL SELECT NULL, NULL, CONCAT(CHAR(58,122,114,115,58),IFNULL(CAST(CURRENT_USER() AS CHAR),CHAR(32)),CHAR(58,115,114,121,58))#')
'1/*!UNION*//*!ALL*//*!SELECT*//*!NULL*/,/*!NULL*/,/*!CONCAT*/(/*!CHAR*/(58,122,114,115,58),/*!IFNULL*/(CAST(/*!CURRENT_USER*/()/*!AS*//*!CHAR*/),/*!CHAR*/(32)),/*!CHAR*/(58,115,114,121,58))#'
"""
def process(match):
word = match.group('word')
if word.upper() in kb.keywords and word.upper() not in IGNORE_SPACE_AFFECTED_KEYWORDS:
return match.group().replace(word, "/*!%s*/" % word)
else:
return match.group()
retVal = payload
if payload:
retVal = re.sub(r"(?<=\W)(?P<word>[A-Za-z_]+)(?=\W|\Z)", lambda match: process(match), retVal)
retVal = retVal.replace(" /*!", "/*!").replace("*/ ", "*/")
return retVal | [
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Yuliang-Liu/Box_Discretization_Network | 5b3a30c97429ef8e5c5e1c4e2476c7d9abdc03e6 | maskrcnn_benchmark/utils/c2_model_loading.py | python | load_resnet_c2_format | (cfg, f) | return dict(model=state_dict) | [] | def load_resnet_c2_format(cfg, f):
state_dict = _load_c2_pickled_weights(f)
conv_body = cfg.MODEL.BACKBONE.CONV_BODY
arch = conv_body.replace("-C4", "").replace("-C5", "").replace("-FPN", "")
arch = arch.replace("-RETINANET", "").replace("-PAN", "")
stages = _C2_STAGE_NAMES[arch]
state_dict = _rename_weights_for_resnet(state_dict, stages)
return dict(model=state_dict) | [
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apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | twistedcaldav/method/report_common.py | python | responseForHref | (request, responses, href, resource, propertiesForResource, propertyreq, isowner=True, calendar=None, timezone=None, vcard=None) | return d | Create an appropriate property status response for the given resource.
@param request: the L{IRequest} for the current request.
@param responses: the list of responses to append the result of this method to.
@param href: the L{HRef} element of the resource being targeted.
@param resource: the L{CalDAVResource} for the targeted resource.
@param calendar: the L{Component} for the calendar for the resource. This may be None
if the calendar has not already been read in, in which case the resource
will be used to get the calendar if needed.
@param vcard: the L{Component} for the vcard for the resource. This may be None
if the vcard has not already been read in, in which case the resource
will be used to get the vcard if needed.
@param propertiesForResource: the method to use to get the list of
properties to return. This is a callable object with a signature
matching that of L{allPropertiesForResource}.
@param propertyreq: the L{PropertyContainer} element for the properties of interest.
@param isowner: C{True} if the authorized principal making the request is the DAV:owner,
C{False} otherwise. | Create an appropriate property status response for the given resource. | [
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"for",
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"given",
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] | def responseForHref(request, responses, href, resource, propertiesForResource, propertyreq, isowner=True, calendar=None, timezone=None, vcard=None):
"""
Create an appropriate property status response for the given resource.
@param request: the L{IRequest} for the current request.
@param responses: the list of responses to append the result of this method to.
@param href: the L{HRef} element of the resource being targeted.
@param resource: the L{CalDAVResource} for the targeted resource.
@param calendar: the L{Component} for the calendar for the resource. This may be None
if the calendar has not already been read in, in which case the resource
will be used to get the calendar if needed.
@param vcard: the L{Component} for the vcard for the resource. This may be None
if the vcard has not already been read in, in which case the resource
will be used to get the vcard if needed.
@param propertiesForResource: the method to use to get the list of
properties to return. This is a callable object with a signature
matching that of L{allPropertiesForResource}.
@param propertyreq: the L{PropertyContainer} element for the properties of interest.
@param isowner: C{True} if the authorized principal making the request is the DAV:owner,
C{False} otherwise.
"""
def _defer(properties_by_status):
propstats = []
for status in properties_by_status:
properties = properties_by_status[status]
if properties:
xml_status = element.Status.fromResponseCode(status)
xml_container = element.PropertyContainer(*properties)
xml_propstat = element.PropertyStatus(xml_container, xml_status)
propstats.append(xml_propstat)
# Always need to have at least one propstat present (required by Prefer header behavior)
if len(propstats) == 0:
propstats.append(element.PropertyStatus(
element.PropertyContainer(),
element.Status.fromResponseCode(responsecode.OK)
))
if propstats:
responses.append(element.PropertyStatusResponse(href, *propstats))
d = propertiesForResource(request, propertyreq, resource, calendar, timezone, vcard, isowner)
d.addCallback(_defer)
return d | [
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pyfa-org/Pyfa | feaa52c36beeda21ab380fc74d8f871b81d49729 | eos/gamedata.py | python | Effect.activeByDefault | (self, value) | Just assign the input values to the activeByDefault attribute.
You *could* do something more interesting here if you wanted. | Just assign the input values to the activeByDefault attribute.
You *could* do something more interesting here if you wanted. | [
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] | def activeByDefault(self, value):
"""
Just assign the input values to the activeByDefault attribute.
You *could* do something more interesting here if you wanted.
"""
self.__activeByDefault = value | [
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khanhnamle1994/natural-language-processing | 01d450d5ac002b0156ef4cf93a07cb508c1bcdc5 | assignment1/.env/lib/python2.7/site-packages/pip/vcs/git.py | python | Git.get_short_refs | (self, location) | return rv | Return map of named refs (branches or tags) to commit hashes. | Return map of named refs (branches or tags) to commit hashes. | [
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"""Return map of named refs (branches or tags) to commit hashes."""
rv = {}
for commit, ref in self.get_full_refs(location):
ref_name = None
if self.is_ref_remote(ref):
ref_name = ref[len('refs/remotes/'):]
elif self.is_ref_branch(ref):
ref_name = ref[len('refs/heads/'):]
elif self.is_ref_tag(ref):
ref_name = ref[len('refs/tags/'):]
if ref_name is not None:
rv[ref_name] = commit
return rv | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/logging/__init__.py | python | PlaceHolder.__init__ | (self, alogger) | Initialize with the specified logger being a child of this placeholder. | Initialize with the specified logger being a child of this placeholder. | [
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"""
Initialize with the specified logger being a child of this placeholder.
"""
#self.loggers = [alogger]
self.loggerMap = { alogger : None } | [
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amymcgovern/pyparrot | bf4775ec1199b282e4edde1e4a8e018dcc8725e0 | pyparrot/utils/vlc.py | python | libvlc_log_unset | (p_instance) | return f(p_instance) | Unsets the logging callback.
This function deregisters the logging callback for a LibVLC instance.
This is rarely needed as the callback is implicitly unset when the instance
is destroyed.
@note: This function will wait for any pending callbacks invocation to
complete (causing a deadlock if called from within the callback).
@param p_instance: libvlc instance.
@version: LibVLC 2.1.0 or later. | Unsets the logging callback.
This function deregisters the logging callback for a LibVLC instance.
This is rarely needed as the callback is implicitly unset when the instance
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'''Unsets the logging callback.
This function deregisters the logging callback for a LibVLC instance.
This is rarely needed as the callback is implicitly unset when the instance
is destroyed.
@note: This function will wait for any pending callbacks invocation to
complete (causing a deadlock if called from within the callback).
@param p_instance: libvlc instance.
@version: LibVLC 2.1.0 or later.
'''
f = _Cfunctions.get('libvlc_log_unset', None) or \
_Cfunction('libvlc_log_unset', ((1,),), None,
None, Instance)
return f(p_instance) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/pip/_vendor/requests/packages/chardet/escprober.py | python | EscCharSetProber.__init__ | (self) | [] | def __init__(self):
CharSetProber.__init__(self)
self._mCodingSM = [
CodingStateMachine(HZSMModel),
CodingStateMachine(ISO2022CNSMModel),
CodingStateMachine(ISO2022JPSMModel),
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/nova/nova/cells/messaging.py | python | MessageRunner.instance_destroy_at_top | (self, ctxt, instance) | Destroy an instance at the top level cell. | Destroy an instance at the top level cell. | [
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"""Destroy an instance at the top level cell."""
message = _BroadcastMessage(self, ctxt, 'instance_destroy_at_top',
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jimmysong/programmingbitcoin | 3fba6b992ece443e4256df057595cfbe91edda75 | code-ch08/tx.py | python | Tx.hash | (self) | return hash256(self.serialize())[::-1] | Binary hash of the legacy serialization | Binary hash of the legacy serialization | [
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bloomberg/phabricator-tools | 09bd1587fe8945d93a891162fd4c89640c6fada7 | py/abd/abdt_branchmock.py | python | BranchMock.verify_review_branch_base | (self) | Raise exception if review branch has invalid base. | Raise exception if review branch has invalid base. | [
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self._data.review_branch,
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johntruckenbrodt/pyroSAR | efac51134ba42d20120b259f968afe5a4ddcc46a | pyroSAR/gamma/parser_demo.py | python | ph_slope_base | (int_in, SLC_par, OFF_par, base, int_out, int_type='-', inverse='-', logpath=None, outdir=None,
shellscript=None) | | Subtract/add interferogram flat-Earth phase trend as estimated from initial baseline
| Copyright 2006, Gamma Remote Sensing, v4.4 3-Nov-2006 clw
Parameters
----------
int_in:
(input) interferogram (FCOMPLEX) or unwrapped phase (FLOAT) (unflattened)
SLC_par:
(input) ISP parameter file for the reference SLC
OFF_par:
(input) ISP offset/interferogram parameter file
base:
(input) baseline file
int_out:
(output) interferogram (FCOMPLEX) or unwrapped phase (FLOAT) with phase trend subtracted/added
int_type:
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inverse:
subtract/add inversion flag (0=subtract phase ramp, 1=add phase ramp (default=0)
logpath: str or None
a directory to write command logfiles to
outdir: str or None
the directory to execute the command in
shellscript: str or None
a file to write the Gamma commands to in shell format | | Subtract/add interferogram flat-Earth phase trend as estimated from initial baseline
| Copyright 2006, Gamma Remote Sensing, v4.4 3-Nov-2006 clw | [
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shellscript=None):
"""
| Subtract/add interferogram flat-Earth phase trend as estimated from initial baseline
| Copyright 2006, Gamma Remote Sensing, v4.4 3-Nov-2006 clw
Parameters
----------
int_in:
(input) interferogram (FCOMPLEX) or unwrapped phase (FLOAT) (unflattened)
SLC_par:
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a file to write the Gamma commands to in shell format
"""
process(
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FSecureLABS/Jandroid | e31d0dab58a2bfd6ed8e0a387172b8bd7c893436 | src/plugins/android/graph_helper_worker.py | python | GraphHelperWorker.fn_get_class_method_desc_from_string | (self, input_string) | return [class_part, method_part, desc_part] | Gets class/method/descriptor parts from a string.
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'type': str(os.path.basename(__file__))
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/numpy-1.16.0-py3.7-macosx-10.9-x86_64.egg/numpy/ma/core.py | python | masked_invalid | (a, copy=True) | return result | Mask an array where invalid values occur (NaNs or infs).
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Only applies to arrays with a dtype where NaNs or infs make sense
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See Also
--------
masked_where : Mask where a condition is met.
Examples
--------
>>> import numpy.ma as ma
>>> a = np.arange(5, dtype=float)
>>> a[2] = np.NaN
>>> a[3] = np.PINF
>>> a
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>>> ma.masked_invalid(a)
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fill_value=1e+20) | Mask an array where invalid values occur (NaNs or infs). | [
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See Also
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masked_where : Mask where a condition is met.
Examples
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>>> import numpy.ma as ma
>>> a = np.arange(5, dtype=float)
>>> a[2] = np.NaN
>>> a[3] = np.PINF
>>> a
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Chaffelson/nipyapi | d3b186fd701ce308c2812746d98af9120955e810 | nipyapi/nifi/models/versioned_controller_service.py | python | VersionedControllerService.component_type | (self) | return self._component_type | Gets the component_type of this VersionedControllerService.
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brython-dev/brython | 9cba5fb7f43a9b52fff13e89b403e02a1dfaa5f3 | www/src/Lib/cmath.py | python | cos | (x) | return cosh(complex(-x.imag, x.real)) | Return the cosine of x. | Return the cosine of x. | [
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DxCx/plugin.video.9anime | 34358c2f701e5ddf19d3276926374a16f63f7b6a | resources/lib/ui/js2py/es6/babel.py | python | PyJs_anonymous_3559_ | (require, module, exports, this, arguments, var=var) | [] | def PyJs_anonymous_3559_(require, module, exports, this, arguments, var=var):
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def PyJsHoisted_basePullAll_(array, values, iteratee, comparator, this, arguments, var=var):
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fastnlp/fitlog | ba9547a56f4855a2d9cf26ae709d01922befa077 | fitlog/fastserver/line_app.py | python | line_index | () | return render_template('line.html', data=data, column_order=column_order, column_dict=column_dict,
hidden_columns=hidden_columns) | [] | def line_index():
ids = request.values['ids']
# 取出所有的logs
flat_logs = [all_data['data'][id].copy() for id in ids.split(',')]
hidden_columns = all_data['hidden_columns'].copy()
# 删除不是共有的部分
value_dict_count = defaultdict(list) # 每个key有多少个
for log in flat_logs:
for key in log.keys():
value_dict_count[key] += [log[key]]
for key, _lst in list(value_dict_count.items()):
if len(_lst) != len(flat_logs): # 有些没有这个值
for log in flat_logs:
log.pop(key, None)
if len(set(_lst)) == 1: # 只有一个值
hidden_columns[key] = 1
logs = [expand_dict([log])[0] for log in flat_logs]
# column_order, column_dict, hidden_columns, settings, logs
hidden_columns['id'] = 1
hidden_columns['memo'] = 1
hidden_columns['meta'] = 1
res = generate_columns(logs, hidden_columns=hidden_columns, column_order=all_data['column_order'], editable_columns={},
exclude_columns={}, ignore_unchanged_columns=False,
str_max_length=20, round_to=6, num_extra_log=0)
column_order = res['column_order']
column_order.pop('id')
column_order['OrderKeys'].remove('id')
if 'metric' in column_order: # 将metric放在第一的位置
column_order['OrderKeys'].remove('metric')
column_order['OrderKeys'].insert(0, 'metric')
column_dict = res['column_dict']
column_dict.pop('id')
hidden_columns = res['hidden_columns']
data = res['data']
for key, log in data.items():
log.pop('id')
return render_template('line.html', data=data, column_order=column_order, column_dict=column_dict,
hidden_columns=hidden_columns) | [
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twisted/twisted | dee676b040dd38b847ea6fb112a712cb5e119490 | src/twisted/mail/mail.py | python | DomainWithDefaultDict.__len__ | (self) | return len(self.domains) | Return the number of domains in this dictionary.
@rtype: L{int}
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"""
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@rtype: L{int}
@return: The number of domains in this dictionary.
"""
return len(self.domains) | [
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rcorcs/NatI | fdf014f4292afdc95250add7b6658468043228e1 | en/wordnet/wordnet.py | python | Word.__str__ | (self) | return self.form + "(" + abbrs[self.pos] + ")" | Return a human-readable representation.
>>> str(N['dog'])
'dog(n.)' | Return a human-readable representation.
>>> str(N['dog'])
'dog(n.)' | [
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"""Return a human-readable representation.
>>> str(N['dog'])
'dog(n.)'
"""
abbrs = {NOUN: 'n.', VERB: 'v.', ADJECTIVE: 'adj.', ADVERB: 'adv.'}
return self.form + "(" + abbrs[self.pos] + ")" | [
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markovmodel/PyEMMA | e9d08d715dde17ceaa96480a9ab55d5e87d3a4b3 | pyemma/coordinates/data/_base/datasource.py | python | DataSourceIterator.return_traj_index | (self, value) | Setter for return_traj_index, determining if the trajectory index gets returned in the iteration loop.
Parameters
----------
value : bool
True if it should be returned, otherwise False | Setter for return_traj_index, determining if the trajectory index gets returned in the iteration loop.
Parameters
----------
value : bool
True if it should be returned, otherwise False | [
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value : bool
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"""
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Xonshiz/anime-dl | d40f0ca11b894dbbf17edbb9d0f069e741be902f | anime_dl/external/utils.py | python | get_elements_by_attribute | (attribute, value, html, escape_value=True) | return retlist | Return the content of the tag with the specified attribute in the passed HTML document | Return the content of the tag with the specified attribute in the passed HTML document | [
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"""Return the content of the tag with the specified attribute in the passed HTML document"""
value = re.escape(value) if escape_value else value
retlist = []
for m in re.finditer(r'''(?xs)
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(?:\s+[a-zA-Z0-9:._-]+(?:=[a-zA-Z0-9:._-]*|="[^"]*"|='[^']*'))*?
\s+%s=['"]?%s['"]?
(?:\s+[a-zA-Z0-9:._-]+(?:=[a-zA-Z0-9:._-]*|="[^"]*"|='[^']*'))*?
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</\1>
''' % (re.escape(attribute), value), html):
res = m.group('content')
if res.startswith('"') or res.startswith("'"):
res = res[1:-1]
retlist.append(unescapeHTML(res))
return retlist | [
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pyeve/eve | 30a7cc80e9a1b40665cd7e7ef93a470ae692da02 | eve/flaskapp.py | python | Eve.validate_methods | (self, allowed, proposed, item) | Compares allowed and proposed methods, raising a `ConfigException`
when they don't match.
:param allowed: a list of supported (allowed) methods.
:param proposed: a list of proposed methods.
:param item: name of the item to which the methods would be applied.
Used when raising the exception. | Compares allowed and proposed methods, raising a `ConfigException`
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] | def validate_methods(self, allowed, proposed, item):
"""Compares allowed and proposed methods, raising a `ConfigException`
when they don't match.
:param allowed: a list of supported (allowed) methods.
:param proposed: a list of proposed methods.
:param item: name of the item to which the methods would be applied.
Used when raising the exception.
"""
diff = set(proposed) - set(allowed)
if diff:
raise ConfigException(
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"Supported: %s" % (item, ", ".join(diff), ", ".join(allowed))
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WikidPad/WikidPad | 558109638807bc76b4672922686e416ab2d5f79c | WikidPad/lib/pwiki/customtreectrl.py | python | CustomTreeCtrl.GetNextVisible | (self, item) | return None | Returns the next visible item. | Returns the next visible item. | [
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"""Returns the next visible item."""
if not item:
raise Exception("\nERROR: Invalid Tree Item. ")
id = item
while id:
id = self.GetNext(id)
if id and self.IsVisible(id):
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tensorflow/mesh | 57ed4018e6a173952501b074daabad32b6449f3d | mesh_tensorflow/transformer/transformer_layers.py | python | relative_position_spans | (context, num_sentinels=gin.REQUIRED) | return dec_to_enc_pos - encoder_pos | Compute relative positions between inputs and targets.
Used by enc_dec_attention_bias.
Assumes that inputs and targets were generated by a span-filling objective:
The inputs consist of the original text with some spans removed and replaced
by single sentinels.
The targets consist of the dropped spans, each preceded by a single sentinel.
Sentinels are the last tokens in the vocabulary.
e.g.
inputs: A B C <S> F G H <S>
shifted-targets: <BOS> <S> D E <S> I J K
Relative positions are computed by identifying a target token with the
corresponding sentinel in the input and returning the distance between these
two tokens in the input.
Target tokens which precede all sentinels get identified with the beginning of
the input. So if we apply this to a problem with no sentinels, all target
tokens will be indentified with the beginning of the input. We assume this is
the case during incremental decoding, so this code will not work properly to
incrementally decode a problem with sentinels. This may not be an issue,
since the span-filling objective is primarily used for unsupervised
pre-training.
Args:
context: a Context
num_sentinels: an integer. Should have the same value as
SentencePieceVocabulary.extra_ids
Returns:
a Tensor | Compute relative positions between inputs and targets. | [
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] | def relative_position_spans(context, num_sentinels=gin.REQUIRED):
"""Compute relative positions between inputs and targets.
Used by enc_dec_attention_bias.
Assumes that inputs and targets were generated by a span-filling objective:
The inputs consist of the original text with some spans removed and replaced
by single sentinels.
The targets consist of the dropped spans, each preceded by a single sentinel.
Sentinels are the last tokens in the vocabulary.
e.g.
inputs: A B C <S> F G H <S>
shifted-targets: <BOS> <S> D E <S> I J K
Relative positions are computed by identifying a target token with the
corresponding sentinel in the input and returning the distance between these
two tokens in the input.
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the input. So if we apply this to a problem with no sentinels, all target
tokens will be indentified with the beginning of the input. We assume this is
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since the span-filling objective is primarily used for unsupervised
pre-training.
Args:
context: a Context
num_sentinels: an integer. Should have the same value as
SentencePieceVocabulary.extra_ids
Returns:
a Tensor
"""
decoder_id = context.inputs
encoder_id = context.encoder_inputs
decoder_length = context.length_dim
encoder_length = context.encoder_length_dim
mesh = encoder_id.mesh
encoder_pos = mtf.range(mesh, encoder_length, tf.int32)
if decoder_length not in decoder_id.shape.dims:
# we are doing incremental decoding.
# Map the target token to the beginning of the input.
dec_to_enc_pos = 0
else:
vocab_size = context.model.input_vocab_size_unpadded
def sentinel_mask(t):
return mtf.cast(mtf.greater_equal(
t, vocab_size - num_sentinels), tf.int32)
decoder_is_sentinel = sentinel_mask(decoder_id)
encoder_is_sentinel = sentinel_mask(encoder_id)
encoder_segment_id = mtf.cumsum(encoder_is_sentinel, encoder_length)
decoder_segment_id = mtf.cumsum(decoder_is_sentinel, decoder_length)
encoder_sequence_id = context.encoder_sequence_id
decoder_sequence_id = context.sequence_id
if encoder_sequence_id is not None:
# distinguish segments from different sequences
multiplier = max(encoder_length.size, decoder_length.size)
encoder_segment_id += encoder_sequence_id * multiplier
decoder_segment_id += decoder_sequence_id * multiplier
dec_to_enc_pos = mtf.reduce_sum(
mtf.cast(mtf.less(encoder_segment_id, decoder_segment_id), tf.int32),
reduced_dim=encoder_length)
return dec_to_enc_pos - encoder_pos | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/simulators/middlewares/ros.py | python | ROS.load_config_file | (filename, namespace=None) | Load a control configuration YAML file.
Args:
filename (str): path to the YAML file.
namespace (str): default namespace.
Returns:
list[dict[str,dict[str:dict[str:dict]]], str]: [{robot_name: {param_name: value}}, namespace] | Load a control configuration YAML file. | [
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"""
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Args:
filename (str): path to the YAML file.
namespace (str): default namespace.
Returns:
list[dict[str,dict[str:dict[str:dict]]], str]: [{robot_name: {param_name: value}}, namespace]
"""
params = rosparam.load_file(filename, default_namespace=namespace)
params = params[0]
namespace = params[1] + 'rrbot/' # TODO: replace rrbot
params = params[0]['rrbot']
for key, value in params.items():
rosparam.upload_params(ns=namespace + key, values=value) | [
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SanPen/GridCal | d3f4566d2d72c11c7e910c9d162538ef0e60df31 | src/GridCal/Engine/IO/zip_interface.py | python | get_frames_from_zip | (file_name_zip, text_func=None, progress_func=None, logger=Logger()) | return data | Open the csv files from a zip file
:param file_name_zip: name of the zip file
:param text_func: pointer to function that prints the names
:param progress_func: pointer to function that prints the progress 0~100
:param logger:
:return: list of DataFrames | Open the csv files from a zip file
:param file_name_zip: name of the zip file
:param text_func: pointer to function that prints the names
:param progress_func: pointer to function that prints the progress 0~100
:param logger:
:return: list of DataFrames | [
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"""
Open the csv files from a zip file
:param file_name_zip: name of the zip file
:param text_func: pointer to function that prints the names
:param progress_func: pointer to function that prints the progress 0~100
:param logger:
:return: list of DataFrames
"""
# open the zip file
try:
zip_file_pointer = zipfile.ZipFile(file_name_zip)
except zipfile.BadZipFile:
return None
names = zip_file_pointer.namelist()
n = len(names)
data = dict()
# for each file in the zip file...
for i, file_name in enumerate(names):
# split the file name into name and extension
name, extension = os.path.splitext(file_name)
if text_func is not None:
text_func('Unpacking ' + name + ' from ' + file_name_zip)
if progress_func is not None:
progress_func((i + 1) / n * 100)
# create a buffer to read the file
file_pointer = zip_file_pointer.open(file_name)
if name.lower() == "config":
df = read_data_frame_from_zip(file_pointer, extension, index_col=0, logger=logger)
data = parse_config_df(df, data)
else:
# make pandas read the file
df = read_data_frame_from_zip(file_pointer, extension, logger=logger)
# append the DataFrame to the list
if df is not None:
data[name] = df
return data | [
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/pickle.py | python | _Pickler.__init__ | (self, file, protocol=None, *, fix_imports=True,
buffer_callback=None) | This takes a binary file for writing a pickle data stream.
The optional *protocol* argument tells the pickler to use the
given protocol; supported protocols are 0, 1, 2, 3, 4 and 5.
The default protocol is 4. It was introduced in Python 3.4, and
is incompatible with previous versions.
Specifying a negative protocol version selects the highest
protocol version supported. The higher the protocol used, the
more recent the version of Python needed to read the pickle
produced.
The *file* argument must have a write() method that accepts a
single bytes argument. It can thus be a file object opened for
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If *buffer_callback* is None (the default), buffer views are
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If *buffer_callback* is not None, then it can be called any number
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buffer is serialized in-band, i.e. inside the pickle stream.
It is an error if *buffer_callback* is not None and *protocol*
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] | def __init__(self, file, protocol=None, *, fix_imports=True,
buffer_callback=None):
"""This takes a binary file for writing a pickle data stream.
The optional *protocol* argument tells the pickler to use the
given protocol; supported protocols are 0, 1, 2, 3, 4 and 5.
The default protocol is 4. It was introduced in Python 3.4, and
is incompatible with previous versions.
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protocol version supported. The higher the protocol used, the
more recent the version of Python needed to read the pickle
produced.
The *file* argument must have a write() method that accepts a
single bytes argument. It can thus be a file object opened for
binary writing, an io.BytesIO instance, or any other custom
object that meets this interface.
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will try to map the new Python 3 names to the old module names
used in Python 2, so that the pickle data stream is readable
with Python 2.
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serialized into *file* as part of the pickle stream.
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(such as None), the given buffer is out-of-band; otherwise the
buffer is serialized in-band, i.e. inside the pickle stream.
It is an error if *buffer_callback* is not None and *protocol*
is None or smaller than 5.
"""
if protocol is None:
protocol = DEFAULT_PROTOCOL
if protocol < 0:
protocol = HIGHEST_PROTOCOL
elif not 0 <= protocol <= HIGHEST_PROTOCOL:
raise ValueError("pickle protocol must be <= %d" % HIGHEST_PROTOCOL)
if buffer_callback is not None and protocol < 5:
raise ValueError("buffer_callback needs protocol >= 5")
self._buffer_callback = buffer_callback
try:
self._file_write = file.write
except AttributeError:
raise TypeError("file must have a 'write' attribute")
self.framer = _Framer(self._file_write)
self.write = self.framer.write
self._write_large_bytes = self.framer.write_large_bytes
self.memo = {}
self.proto = int(protocol)
self.bin = protocol >= 1
self.fast = 0
self.fix_imports = fix_imports and protocol < 3 | [
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mcfletch/pyopengl | 02d11dad9ff18e50db10e975c4756e17bf198464 | OpenGL/GL/INTEL/performance_query.py | python | glInitPerformanceQueryINTEL | () | 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
return extensions.hasGLExtension( _EXTENSION_NAME ) | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/cinder/tools/hacking.py | python | cinder_import_module_only | (logical_line) | Check for import module only.
cinder HACKING guide recommends importing only modules:
Do not import objects, only modules
N302 import only modules
N303 Invalid Import
N304 Relative Import | Check for import module only. | [
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] | def cinder_import_module_only(logical_line):
"""Check for import module only.
cinder HACKING guide recommends importing only modules:
Do not import objects, only modules
N302 import only modules
N303 Invalid Import
N304 Relative Import
"""
def importModuleCheck(mod, parent=None, added=False):
"""
If can't find module on first try, recursively check for relative
imports
"""
current_path = os.path.dirname(pep8.current_file)
try:
with warnings.catch_warnings():
warnings.simplefilter('ignore', DeprecationWarning)
valid = True
if parent:
if is_import_exception(parent):
return
parent_mod = __import__(parent,
globals(),
locals(),
[mod],
-1)
valid = inspect.ismodule(getattr(parent_mod, mod))
else:
__import__(mod, globals(), locals(), [], -1)
valid = inspect.ismodule(sys.modules[mod])
if not valid:
if added:
sys.path.pop()
added = False
return (logical_line.find(mod),
("CINDER N304: No "
"relative imports. '%s' is a relative import"
% logical_line))
return (logical_line.find(mod),
("CINDER N302: import only "
"modules. '%s' does not import a module"
% logical_line))
except (ImportError, NameError) as exc:
if not added:
added = True
sys.path.append(current_path)
return importModuleCheck(mod, parent, added)
else:
name = logical_line.split()[1]
if name not in _missingImport:
if VERBOSE_MISSING_IMPORT:
print >> sys.stderr, ("ERROR: import '%s' failed: %s" %
(name, exc))
_missingImport.add(name)
added = False
sys.path.pop()
return
except AttributeError:
# Invalid import
return logical_line.find(mod), ("CINDER N303: Invalid import, "
"AttributeError raised")
# convert "from x import y" to " import x.y"
# convert "from x import y as z" to " import x.y"
import_normalize(logical_line)
split_line = logical_line.split()
if (logical_line.startswith("import ") and
"," not in logical_line and
(len(split_line) == 2 or
(len(split_line) == 4 and split_line[2] == "as"))):
mod = split_line[1]
rval = importModuleCheck(mod)
if rval is not None:
yield rval | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/pycryptodomex-3.9.7/lib/Cryptodome/Cipher/_mode_gcm.py | python | GcmMode.decrypt | (self, ciphertext, output=None) | return self._cipher.decrypt(ciphertext, output=output) | Decrypt data with the key and the parameters set at initialization.
A cipher object is stateful: once you have decrypted a message
you cannot decrypt (or encrypt) another message with the same
object.
The data to decrypt can be broken up in two or
more pieces and `decrypt` can be called multiple times.
That is, the statement:
>>> c.decrypt(a) + c.decrypt(b)
is equivalent to:
>>> c.decrypt(a+b)
This function does not remove any padding from the plaintext.
:Parameters:
ciphertext : bytes/bytearray/memoryview
The piece of data to decrypt.
It can be of any length.
:Keywords:
output : bytearray/memoryview
The location where the plaintext must be written to.
If ``None``, the plaintext is returned.
:Return:
If ``output`` is ``None``, the plaintext as ``bytes``.
Otherwise, ``None``. | Decrypt data with the key and the parameters set at initialization. | [
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"""Decrypt data with the key and the parameters set at initialization.
A cipher object is stateful: once you have decrypted a message
you cannot decrypt (or encrypt) another message with the same
object.
The data to decrypt can be broken up in two or
more pieces and `decrypt` can be called multiple times.
That is, the statement:
>>> c.decrypt(a) + c.decrypt(b)
is equivalent to:
>>> c.decrypt(a+b)
This function does not remove any padding from the plaintext.
:Parameters:
ciphertext : bytes/bytearray/memoryview
The piece of data to decrypt.
It can be of any length.
:Keywords:
output : bytearray/memoryview
The location where the plaintext must be written to.
If ``None``, the plaintext is returned.
:Return:
If ``output`` is ``None``, the plaintext as ``bytes``.
Otherwise, ``None``.
"""
if self.decrypt not in self._next:
raise TypeError("decrypt() can only be called"
" after initialization or an update()")
self._next = [self.decrypt, self.verify]
if self._status == MacStatus.PROCESSING_AUTH_DATA:
self._pad_cache_and_update()
self._status = MacStatus.PROCESSING_CIPHERTEXT
self._update(ciphertext)
self._msg_len += len(ciphertext)
return self._cipher.decrypt(ciphertext, output=output) | [
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cuthbertLab/music21 | bd30d4663e52955ed922c10fdf541419d8c67671 | music21/stream/makeNotation.py | python | moveNotesToVoices | (source: 'music21.stream.Stream', classFilterList=('GeneralNote',)) | Move notes into voices. Happens inplace always. Returns None | Move notes into voices. Happens inplace always. Returns None | [
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"Happens",
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] | def moveNotesToVoices(source: 'music21.stream.Stream', classFilterList=('GeneralNote',)):
'''
Move notes into voices. Happens inplace always. Returns None
'''
from music21.stream import Voice
dst = Voice()
# cast to list so source can be edited.
affectedElements = list(source.getElementsByClass(classFilterList))
for e in affectedElements:
dst.insert(source.elementOffset(e), e)
source.remove(e)
source.insert(0, dst) | [
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wummel/linkchecker | c2ce810c3fb00b895a841a7be6b2e78c64e7b042 | linkcheck/plugins/parseword.py | python | open_wordfile | (app, filename) | return app.Documents.Open(filename, ReadOnly=True,
AddToRecentFiles=False, Visible=False, NoEncodingDialog=True) | Open given Word file with application object. | Open given Word file with application object. | [
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] | def open_wordfile (app, filename):
"""Open given Word file with application object."""
return app.Documents.Open(filename, ReadOnly=True,
AddToRecentFiles=False, Visible=False, NoEncodingDialog=True) | [
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selfteaching/selfteaching-python-camp | 9982ee964b984595e7d664b07c389cddaf158f1e | exercises/1901010064/d12/mymodule/stats_word.py | python | stats_text_cn | (text,count) | 统计参数中每个中文汉字出现的次数，最后返回一个按字频降序排列的数组 | 统计参数中每个中文汉字出现的次数，最后返回一个按字频降序排列的数组 | [
"统计参数中每个中文汉字出现的次数，最后返回一个按字频降序排列的数组"
] | def stats_text_cn(text,count):
"""统计参数中每个中文汉字出现的次数，最后返回一个按字频降序排列的数组"""
if isinstance(text,str):
string=text
text_0=re.sub('[a-zA-Z0-9’!"#$%&\'()*+,-.：/:;<=>?@，。?★、…【】《》？“”‘’！[\\]^_`{|}~\s]+', "", string)
seg_list_0 = list(jieba.cut(text_0,cut_all=False))
seg_list_1=[]
for i in seg_list_0:
if len(i) >=2:
seg_list_1.append(i)
x=int(count)
y=len(seg_list_1)
x <= y
tuple_1=tuple(seg_list_1)
return collections.Counter(tuple_1).most_common(100) | [
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douban/pymesos | 047c7bac8ca98772f63192aed063148fdf399b55 | pymesos/interface.py | python | OperatorMaster.agentAdded | (self, agent_info) | Sent whenever an agent becomes known to it. This can happen when an agent registered for the first time, or
reregistered after a master failover. | Sent whenever an agent becomes known to it. This can happen when an agent registered for the first time, or
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"""
Sent whenever an agent becomes known to it. This can happen when an agent registered for the first time, or
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""" | [
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CoinAlpha/hummingbot | 36f6149c1644c07cd36795b915f38b8f49b798e7 | hummingbot/connector/exchange/hitbtc/hitbtc_exchange.py | python | HitbtcExchange.__init__ | (self,
hitbtc_api_key: str,
hitbtc_secret_key: str,
trading_pairs: Optional[List[str]] = None,
trading_required: bool = True
) | :param hitbtc_api_key: The API key to connect to private HitBTC APIs.
:param hitbtc_secret_key: The API secret.
:param trading_pairs: The market trading pairs which to track order book data.
:param trading_required: Whether actual trading is needed. | :param hitbtc_api_key: The API key to connect to private HitBTC APIs.
:param hitbtc_secret_key: The API secret.
:param trading_pairs: The market trading pairs which to track order book data.
:param trading_required: Whether actual trading is needed. | [
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hitbtc_api_key: str,
hitbtc_secret_key: str,
trading_pairs: Optional[List[str]] = None,
trading_required: bool = True
):
"""
:param hitbtc_api_key: The API key to connect to private HitBTC APIs.
:param hitbtc_secret_key: The API secret.
:param trading_pairs: The market trading pairs which to track order book data.
:param trading_required: Whether actual trading is needed.
"""
super().__init__()
self._trading_required = trading_required
self._trading_pairs = trading_pairs
self._hitbtc_auth = HitbtcAuth(hitbtc_api_key, hitbtc_secret_key)
self._order_book_tracker = HitbtcOrderBookTracker(trading_pairs=trading_pairs)
self._user_stream_tracker = HitbtcUserStreamTracker(self._hitbtc_auth, trading_pairs)
self._ev_loop = asyncio.get_event_loop()
self._shared_client = None
self._poll_notifier = asyncio.Event()
self._last_timestamp = 0
self._in_flight_orders = {} # Dict[client_order_id:str, HitbtcInFlightOrder]
self._order_not_found_records = {} # Dict[client_order_id:str, count:int]
self._trading_rules = {} # Dict[trading_pair:str, TradingRule]
self._status_polling_task = None
self._user_stream_event_listener_task = None
self._trading_rules_polling_task = None
self._last_poll_timestamp = 0 | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/filters/histogram_filter.py | python | HistogramFilter.measurement_update | (self, h, z) | return self.p | Predict (a posteriori) the next state by incorporating the measurement :math:`z_t`.
Args:
h (callable class/function): probabilistic (nonlinear) measurement function to see measurement from
region k. This function should return an array of the same shape as the one provided in argument
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region k. This function should return an array of the same shape as the one provided in argument
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self.p = h(z, self.p.shape) * self.p
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andrewgodwin/channels-examples | 5fa86dff822f411e1e6f01765c71eaf8d4f19977 | news_collector/collector/views.py | python | index | (request) | return render(request, "index.html", {}) | Main page is just a template | Main page is just a template | [
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"""
Main page is just a template
"""
return render(request, "index.html", {}) | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/contrib/auth/management/__init__.py | python | get_system_username | () | return result | Try to determine the current system user's username.
:returns: The username as a unicode string, or an empty string if the
username could not be determined. | Try to determine the current system user's username. | [
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] | def get_system_username():
"""
Try to determine the current system user's username.
:returns: The username as a unicode string, or an empty string if the
username could not be determined.
"""
try:
result = getpass.getuser()
except (ImportError, KeyError):
# KeyError will be raised by os.getpwuid() (called by getuser())
# if there is no corresponding entry in the /etc/passwd file
# (a very restricted chroot environment, for example).
return ''
if six.PY2:
try:
result = result.decode(DEFAULT_LOCALE_ENCODING)
except UnicodeDecodeError:
# UnicodeDecodeError - preventive treatment for non-latin Windows.
return ''
return result | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/nova/nova/api/openstack/wsgi.py | python | deserializers | (**deserializers) | return decorator | Attaches deserializers to a method.
This decorator associates a dictionary of deserializers with a
method. Note that the function attributes are directly
manipulated; the method is not wrapped. | Attaches deserializers to a method. | [
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] | def deserializers(**deserializers):
"""Attaches deserializers to a method.
This decorator associates a dictionary of deserializers with a
method. Note that the function attributes are directly
manipulated; the method is not wrapped.
"""
def decorator(func):
if not hasattr(func, 'wsgi_deserializers'):
func.wsgi_deserializers = {}
func.wsgi_deserializers.update(deserializers)
return func
return decorator | [
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Qirky/FoxDot | 76318f9630bede48ff3994146ed644affa27bfa4 | FoxDot/lib/OSC.py | python | OSCRequestHandler.finish | (self) | Finish handling OSCMessage.
Send any reply returned by the callback(s) back to the originating client
as an OSCMessage or OSCBundle | Finish handling OSCMessage.
Send any reply returned by the callback(s) back to the originating client
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aiidateam/aiida-core | c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2 | aiida/cmdline/utils/echo.py | python | echo | (message: str, fg: str = None, bold: bool = False, nl: bool = True, err: bool = False) | Log a message to the cmdline logger.
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"""Log a message to the cmdline logger.
.. note:: The message will be logged at the ``REPORT`` level but always without the log level prefix.
:param message: the message to log.
:param fg: if provided this will become the foreground color.
:param bold: whether to print the messaformat bold.
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message = click.style(message, fg=fg, bold=bold)
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pulp/pulp | a0a28d804f997b6f81c391378aff2e4c90183df9 | nodes/common/pulp_node/manifest.py | python | RemoteManifest.fetch | (self) | Fetch the manifest file using the specified URL.
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Chaffelson/nipyapi | d3b186fd701ce308c2812746d98af9120955e810 | nipyapi/nifi/models/system_diagnostics_snapshot_dto.py | python | SystemDiagnosticsSnapshotDTO.content_repository_storage_usage | (self, content_repository_storage_usage) | Sets the content_repository_storage_usage of this SystemDiagnosticsSnapshotDTO.
The content repository storage usage.
:param content_repository_storage_usage: The content_repository_storage_usage of this SystemDiagnosticsSnapshotDTO.
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Sets the content_repository_storage_usage of this SystemDiagnosticsSnapshotDTO.
The content repository storage usage.
:param content_repository_storage_usage: The content_repository_storage_usage of this SystemDiagnosticsSnapshotDTO.
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self._content_repository_storage_usage = content_repository_storage_usage | [
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open-telemetry/opentelemetry-python | f5d872050204685b5ef831d02ec593956820ebe6 | exporter/opentelemetry-exporter-jaeger-proto-grpc/src/opentelemetry/exporter/jaeger/proto/grpc/translate/__init__.py | python | _get_double_key_value | (key: str, value: float) | return model_pb2.KeyValue(
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | opy/compiler2/transformer.py | python | Transformer.if_stmt | (self, nodelist) | return If(tests, elseNode, lineno=nodelist[0][2]) | [] | def if_stmt(self, nodelist):
# if: test ':' suite ('elif' test ':' suite)* ['else' ':' suite]
tests = []
for i in range(0, len(nodelist) - 3, 4):
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suiteNode = self.com_node(nodelist[i + 3])
tests.append((testNode, suiteNode))
if len(nodelist) % 4 == 3:
elseNode = self.com_node(nodelist[-1])
## elseNode.lineno = nodelist[-1][1][2]
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return If(tests, elseNode, lineno=nodelist[0][2]) | [
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pydanny/django-uni-form | 159f539e2fb98752b7964d75e955fc62881c28fb | uni_form/layout.py | python | BaseInput.render | (self, form, form_style, context) | return render_to_string(self.template, Context({'input': self})) | Renders an `<input />` if container is used as a Layout object | Renders an `<input />` if container is used as a Layout object | [
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deanishe/alfred-convert | 97407f4ec8dbca5abbc6952b2b56cf3918624177 | src/pint/registry.py | python | BaseRegistry._convert | (self, value, src, dst, inplace=False, check_dimensionality=True) | return value | Convert value from some source to destination units.
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:param src: source units.
:type src: UnitsContainer
:param dst: destination units.
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"""
if check_dimensionality:
src_dim = self._get_dimensionality(src)
dst_dim = self._get_dimensionality(dst)
# If the source and destination dimensionality are different,
# then the conversion cannot be performed.
if src_dim != dst_dim:
raise DimensionalityError(src, dst, src_dim, dst_dim)
# Here src and dst have only multiplicative units left. Thus we can
# convert with a factor.
factor, units = self._get_root_units(src / dst)
# factor is type float and if our magnitude is type Decimal then
# must first convert to Decimal before we can '*' the values
if isinstance(value, Decimal):
factor = Decimal(str(factor))
elif isinstance(value, Fraction):
factor = Fraction(str(factor))
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krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit /tools/sqli/plugins/dbms/maxdb/fingerprint.py | python | Fingerprint.__init__ | (self) | [] | def __init__(self):
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easyw/kicadStepUpMod | 9d78e59b97cedc4915ee3a290126a88dcdf11277 | fcad_parser/sexp_parser/sexp_parser.py | python | Sexp._exportValue | (self,out,value,prefix,indent) | Called by `_export()` to export each individual value
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can override this method to customize the behavior
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p = getattr(value,'_export',None)
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isnowfy/pydown | 71ecc891868cd2a34b7e5fe662c99474f2d0fd7f | markdown/odict.py | python | OrderedDict.items | (self) | return zip(self.keyOrder, self.values()) | [] | def items(self):
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/devops_sdk/v6_0/identity/identity_client.py | python | IdentityClient.add_member | (self, container_id, member_id) | return self._deserialize('bool', response) | AddMember.
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:param str container_id:
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route_values = {}
if container_id is not None:
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route_values['memberId'] = self._serialize.url('member_id', member_id, 'str')
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randy3k/SendCode | 6775b40613bb4911ba0499ff8a600c41f48a62c2 | code_getter/getter.py | python | CodeGetter.get_code | (self) | return cmd | [] | def get_code(self):
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aws-quickstart/quickstart-redhat-openshift | 2b87dd38b72e7e4c439a606c5a9ea458d72da612 | functions/source/KeyGen/asn1crypto/core.py | python | Concat.__copy__ | (self) | return new_obj | Implements the copy.copy() interface
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new_obj = self.__class__()
new_obj._copy(self, copy.copy)
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django-nonrel/django-nonrel | 4fbfe7344481a5eab8698f79207f09124310131b | django/contrib/gis/geos/geometry.py | python | GEOSGeometry.simple | (self) | return capi.geos_issimple(self.ptr) | Returns false if the Geometry not simple. | Returns false if the Geometry not simple. | [
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fniephaus/alfred-pocket | c8ff8b23d708a746cce2888398cc566bef687a14 | src/workflow/workflow.py | python | Workflow.clear_data | (self, filter_func=lambda f: True) | Delete all files in workflow's :attr:`datadir`.
:param filter_func: Callable to determine whether a file should be
deleted or not. ``filter_func`` is called with the filename
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:type filter_func: ``callable``
"""
self._delete_directory_contents(self.datadir, filter_func) | [
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inasafe/inasafe | 355eb2ce63f516b9c26af0c86a24f99e53f63f87 | extras/xml_tools.py | python | dom2object | (node) | return X | Convert DOM representation to XML_object hierarchy. | Convert DOM representation to XML_object hierarchy. | [
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"""Convert DOM representation to XML_object hierarchy.
"""
value = []
textnode_encountered = None
for n in node.childNodes:
if n.nodeType == 3:
# Child is a text element - omit the dom tag #text and
# go straight to the text value.
# Note - only the last text value will be recorded
msg = 'Text element has child nodes - this shouldn\'t happen'
verify(len(n.childNodes) == 0, msg)
x = n.nodeValue.strip()
if len(x) == 0:
# Skip empty text children
continue
textnode_encountered = value = x
else:
# XML element
if textnode_encountered is not None:
msg = 'A text node was followed by a non-text tag. This is not allowed.\n'
msg += 'Offending text node: "%s" ' %str(textnode_encountered)
msg += 'was followed by node named: "<%s>"' %str(n.nodeName)
raise Exception, msg
value.append(dom2object(n))
# Deal with empty elements
if len(value) == 0: value = ''
if node.nodeType == 9:
# Root node (document)
tag = None
else:
# Normal XML node
tag = node.nodeName
X = XML_element(tag=tag,
value=value)
return X | [
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KristianOellegaard/django-hvad | b4fb1ff3674bd8309530ed5dcb95e9c3afd53a10 | hvad/admin.py | python | TranslatableInlineModelAdmin.response_change | (self, request, obj) | return redirect | [] | def response_change(self, request, obj):
redirect = super(TranslatableAdmin, self).response_change(request, obj)
uri = iri_to_uri(request.path)
if redirect['Location'] in (uri, "../add/"):
if self.query_language_key in request.GET:
redirect['Location'] = '%s?%s=%s' % (redirect['Location'],
self.query_language_key, request.GET[self.query_language_key])
return redirect | [
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F8LEFT/DecLLVM | d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c | python/idaapi.py | python | py_clinked_object_t.__del__ | (self) | Delete the link upon object destruction (only if not static) | Delete the link upon object destruction (only if not static) | [
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"""
Delete the link upon object destruction (only if not static)
"""
self._free() | [
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] | https://github.com/F8LEFT/DecLLVM/blob/d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c/python/idaapi.py#L200-L204 | ||
mrkipling/maraschino | c6be9286937783ae01df2d6d8cebfc8b2734a7d7 | lib/werkzeug/http.py | python | http_date | (timestamp=None) | return _dump_date(timestamp, ' ') | Formats the time to match the RFC1123 date format.
Accepts a floating point number expressed in seconds since the epoch in, a
datetime object or a timetuple. All times in UTC. The :func:`parse_date`
function can be used to parse such a date.
Outputs a string in the format ``Wdy, DD Mon YYYY HH:MM:SS GMT``.
:param timestamp: If provided that date is used, otherwise the current. | Formats the time to match the RFC1123 date format. | [
"Formats",
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"to",
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"the",
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"date",
"format",
"."
] | def http_date(timestamp=None):
"""Formats the time to match the RFC1123 date format.
Accepts a floating point number expressed in seconds since the epoch in, a
datetime object or a timetuple. All times in UTC. The :func:`parse_date`
function can be used to parse such a date.
Outputs a string in the format ``Wdy, DD Mon YYYY HH:MM:SS GMT``.
:param timestamp: If provided that date is used, otherwise the current.
"""
return _dump_date(timestamp, ' ') | [
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scanny/python-pptx | 71d1ca0b2b3b9178d64cdab565e8503a25a54e0b | pptx/oxml/dml/fill.py | python | CT_GradientFillProperties._new_gsLst | (self) | return CT_GradientStopList.new_gsLst() | Override default to add minimum subtree. | Override default to add minimum subtree. | [
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"subtree",
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] | def _new_gsLst(self):
"""Override default to add minimum subtree."""
return CT_GradientStopList.new_gsLst() | [
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jeetsukumaran/DendroPy | 29fd294bf05d890ebf6a8d576c501e471db27ca1 | src/dendropy/calculate/statistics.py | python | rank | (value_to_be_ranked, value_providing_rank) | return len(num_lesser) | Returns the rank of ``value_to_be_ranked`` in set of values, ``values``.
Works even if ``values`` is a non-orderable collection (e.g., a set).
A binary search would be an optimized way of doing this if we can constrain
``values`` to be an ordered collection. | Returns the rank of ``value_to_be_ranked`` in set of values, ``values``.
Works even if ``values`` is a non-orderable collection (e.g., a set).
A binary search would be an optimized way of doing this if we can constrain
``values`` to be an ordered collection. | [
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"""
Returns the rank of ``value_to_be_ranked`` in set of values, ``values``.
Works even if ``values`` is a non-orderable collection (e.g., a set).
A binary search would be an optimized way of doing this if we can constrain
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"""
num_lesser = [v for v in value_providing_rank if v < value_to_be_ranked]
return len(num_lesser) | [
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nipy/heudiconv | 80a65385ef867124611d037fceac27d27e30f480 | heudiconv/due.py | python | InactiveDueCreditCollector._donothing | (self, *args, **kwargs) | Perform no good and no bad | Perform no good and no bad | [
"Perform",
"no",
"good",
"and",
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] | def _donothing(self, *args, **kwargs):
"""Perform no good and no bad"""
pass | [
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] | https://github.com/nipy/heudiconv/blob/80a65385ef867124611d037fceac27d27e30f480/heudiconv/due.py#L32-L34 | ||
ydkhatri/mac_apt | 729630c8bbe7a73cce3ca330305d3301a919cb07 | plugins/helpers/macinfo.py | python | MountedMacInfo._GetDarwinFoldersInfo | (self) | Gets DARWIN_*_DIR paths | Gets DARWIN_*_DIR paths | [
"Gets",
"DARWIN_",
"*",
"_DIR",
"paths"
] | def _GetDarwinFoldersInfo(self):
'''Gets DARWIN_*_DIR paths '''
if not self.is_windows:
# Unix/Linux or Mac mounted disks should preserve UID/GID, so we can read it normally from the files.
super()._GetDarwinFoldersInfo()
return
for user in self.users:
if user.UUID != '' and user.UID not in ('', '-2', '1', '201'): # Users nobody, daemon, guest don't have one
darwin_path = '/private/var/folders/' + GetDarwinPath2(user.UUID, user.UID)
if not self.IsValidFolderPath(darwin_path):
darwin_path = '/private/var/folders/' + GetDarwinPath(user.UUID, user.UID)
if not self.IsValidFolderPath(darwin_path):
if user.user_name.startswith('_') and user.UUID.upper().startswith('FFFFEEEE'):
pass
else:
log.warning(f'Could not find DARWIN_PATH for user {user.user_name}, uid={user.UID}, uuid={user.UUID}')
continue
user.DARWIN_USER_DIR = darwin_path + '/0'
user.DARWIN_USER_CACHE_DIR = darwin_path + '/C'
user.DARWIN_USER_TEMP_DIR = darwin_path + '/T' | [
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... | https://github.com/ydkhatri/mac_apt/blob/729630c8bbe7a73cce3ca330305d3301a919cb07/plugins/helpers/macinfo.py#L1485-L1505 |
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