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khanhnamle1994/natural-language-processing | 01d450d5ac002b0156ef4cf93a07cb508c1bcdc5 | assignment1/.env/lib/python2.7/site-packages/IPython/core/interactiveshell.py | python | InteractiveShell.clear_main_mod_cache | (self) | Clear the cache of main modules.
Mainly for use by utilities like %reset.
Examples
--------
In [15]: import IPython
In [16]: m = _ip.new_main_mod(IPython.__file__, 'IPython')
In [17]: len(_ip._main_mod_cache) > 0
Out[17]: True
In [18]: _ip.clear_main_mod_cache()
In [19]: len(_ip._main_mod_cache) == 0
Out[19]: True | Clear the cache of main modules. | [
"Clear",
"the",
"cache",
"of",
"main",
"modules",
"."
] | def clear_main_mod_cache(self):
"""Clear the cache of main modules.
Mainly for use by utilities like %reset.
Examples
--------
In [15]: import IPython
In [16]: m = _ip.new_main_mod(IPython.__file__, 'IPython')
In [17]: len(_ip._main_mod_cache) > 0
Out[17]: True
In [18]: _ip.clear_main_mod_cache()
In [19]: len(_ip._main_mod_cache) == 0
Out[19]: True
"""
self._main_mod_cache.clear() | [
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||
EasyIME/PIME | 0f1eee10169c1cb2eaa0b59a77fa6f931ecb33b3 | python/python3/tornado/web.py | python | RequestHandler.get_login_url | (self) | return self.application.settings["login_url"] | Override to customize the login URL based on the request.
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"""Override to customize the login URL based on the request.
By default, we use the ``login_url`` application setting.
"""
self.require_setting("login_url", "@tornado.web.authenticated")
return self.application.settings["login_url"] | [
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|
tendenci/tendenci | 0f2c348cc0e7d41bc56f50b00ce05544b083bf1d | tendenci/libs/model_report/utils.py | python | obj_type_format | (value, instance=None) | return OBJECT_TYPE_DICT.get(value) | [] | def obj_type_format(value, instance=None):
global OBJECT_TYPE_DICT
if not OBJECT_TYPE_DICT:
OBJECT_TYPE_DICT = dict((ct.id, '%s: %s' % (ct.app_label, ct.model))
for ct in ContentType.objects.all().order_by('app_label', 'model'))
return OBJECT_TYPE_DICT.get(value) | [
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|||
IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/CPython/27/Lib/DocXMLRPCServer.py | python | ServerHTMLDoc.markup | (self, text, escape=None, funcs={}, classes={}, methods={}) | return ''.join(results) | Mark up some plain text, given a context of symbols to look for.
Each context dictionary maps object names to anchor names. | Mark up some plain text, given a context of symbols to look for.
Each context dictionary maps object names to anchor names. | [
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"""Mark up some plain text, given a context of symbols to look for.
Each context dictionary maps object names to anchor names."""
escape = escape or self.escape
results = []
here = 0
# XXX Note that this regular expression does not allow for the
# hyperlinking of arbitrary strings being used as method
# names. Only methods with names consisting of word characters
# and '.'s are hyperlinked.
pattern = re.compile(r'\b((http|ftp)://\S+[\w/]|'
r'RFC[- ]?(\d+)|'
r'PEP[- ]?(\d+)|'
r'(self\.)?((?:\w|\.)+))\b')
while 1:
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results.append(escape(text[here:start]))
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if scheme:
url = escape(all).replace('"', '"')
results.append('<a href="%s">%s</a>' % (url, url))
elif rfc:
url = 'http://www.rfc-editor.org/rfc/rfc%d.txt' % int(rfc)
results.append('<a href="%s">%s</a>' % (url, escape(all)))
elif pep:
url = 'http://www.python.org/dev/peps/pep-%04d/' % int(pep)
results.append('<a href="%s">%s</a>' % (url, escape(all)))
elif text[end:end+1] == '(':
results.append(self.namelink(name, methods, funcs, classes))
elif selfdot:
results.append('self.<strong>%s</strong>' % name)
else:
results.append(self.namelink(name, classes))
here = end
results.append(escape(text[here:]))
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|
LumaPictures/pymel | fa88a3f4fa18e09bb8aa9bdf4dab53d984bada72 | pymel/tools/mel2py/melparse.py | python | p_primary_expression | (t) | primary_expression : boolean
| numerical_constant | primary_expression : boolean
| numerical_constant | [
"primary_expression",
":",
"boolean",
"|",
"numerical_constant"
] | def p_primary_expression(t):
'''primary_expression : boolean
| numerical_constant'''
t[0] = assemble(t, 'p_primary_expression')
if t.lexer.verbose >= 2:
print("p_primary_expression", t[0]) | [
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||
meduza-corp/interstellar | 40a801ccd7856491726f5a126621d9318cabe2e1 | gsutil/third_party/boto/boto/mws/connection.py | python | MWSConnection.get_order_reference_details | (self, request, response, **kw) | return self._post_request(request, kw, response) | Returns details about the Order Reference object and its current
state. | Returns details about the Order Reference object and its current
state. | [
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] | def get_order_reference_details(self, request, response, **kw):
"""Returns details about the Order Reference object and its current
state.
"""
return self._post_request(request, kw, response) | [
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|
dpgaspar/Flask-AppBuilder | 557249f33b66d02a48c1322ef21324b815abe18e | flask_appbuilder/baseviews.py | python | expose | (url="/", methods=("GET",)) | return wrap | Use this decorator to expose views on your view classes.
:param url:
Relative URL for the view
:param methods:
Allowed HTTP methods. By default only GET is allowed. | Use this decorator to expose views on your view classes. | [
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] | def expose(url="/", methods=("GET",)):
"""
Use this decorator to expose views on your view classes.
:param url:
Relative URL for the view
:param methods:
Allowed HTTP methods. By default only GET is allowed.
"""
def wrap(f):
if not hasattr(f, "_urls"):
f._urls = []
f._urls.append((url, methods))
return f
return wrap | [
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|
gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/gen/lib/location.py | python | Location.serialize | (self) | return (LocationBase.serialize(self), self.parish) | Convert the object to a serialized tuple of data. | Convert the object to a serialized tuple of data. | [
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] | def serialize(self):
"""
Convert the object to a serialized tuple of data.
"""
return (LocationBase.serialize(self), self.parish) | [
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|
enthought/traits | d22ce1f096e2a6f87c78d7f1bb5bf0abab1a18ff | traits/trait_list_object.py | python | TraitListObject.__delitem__ | (self, key) | Delete self[key].
Parameters
----------
key : integer or slice
Index of the element(s) to be deleted.
Raises
------
IndexError
If key is an integer index and is out of range. | Delete self[key]. | [
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""" Delete self[key].
Parameters
----------
key : integer or slice
Index of the element(s) to be deleted.
Raises
------
IndexError
If key is an integer index and is out of range.
"""
removed_count = len(self[key]) if isinstance(key, slice) else 1
self._validate_length(max(len(self) - removed_count, 0))
super().__delitem__(key) | [
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||
plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/heatmapgl/colorbar/_title.py | python | Title.text | (self) | return self["text"] | Sets the title of the color bar. Note that before the existence
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`title` attribute itself. This behavior has been deprecated.
The 'text' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | Sets the title of the color bar. Note that before the existence
of `title.text`, the title's contents used to be defined as the
`title` attribute itself. This behavior has been deprecated.
The 'text' property is a string and must be specified as:
- A string
- A number that will be converted to a string | [
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|
DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | citrix_hypervisor/datadog_checks/citrix_hypervisor/config_models/defaults.py | python | instance_tls_use_host_header | (field, value) | return False | [] | def instance_tls_use_host_header(field, value):
return False | [
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|||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/pip/_vendor/pkg_resources/__init__.py | python | DefaultProvider._listdir | (self, path) | return os.listdir(path) | [] | def _listdir(self, path):
return os.listdir(path) | [
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|||
SickChill/SickChill | 01020f3636d01535f60b83464d8127ea0efabfc7 | sickchill/adba/aniDBresponses.py | python | BuddyAlreadyAcceptedResponse.__init__ | (self, cmd, restag, rescode, resstr, datalines) | attributes:
data: | attributes: | [
"attributes",
":"
] | def __init__(self, cmd, restag, rescode, resstr, datalines):
"""
attributes:
data:
"""
super().__init__(cmd, restag, rescode, resstr, datalines)
self.codestr = "BUDDY_ALREADY_ACCEPTED"
self.codehead = ()
self.codetail = ()
self.coderep = () | [
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||
planetlabs/planet-client-python | 6aa31e873ef40e73c2c49981f6065d05bfc7b56d | planet/api/client.py | python | ClientV1.create_order | (self, request) | return self.dispatcher.response(models.Request(url, self.auth,
body_type=models.Order,
data=body,
method='POST')
).get_body() | Create an order.
:param asset:
:returns: :py:Class:`planet.api.models.Response` containing a
:py:Class:`planet.api.models.Body` of the asset.
:raises planet.api.exceptions.APIException: On API error. | Create an order. | [
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] | def create_order(self, request):
'''Create an order.
:param asset:
:returns: :py:Class:`planet.api.models.Response` containing a
:py:Class:`planet.api.models.Body` of the asset.
:raises planet.api.exceptions.APIException: On API error.
'''
url = self._url('compute/ops/orders/v2')
body = json.dumps(request)
return self.dispatcher.response(models.Request(url, self.auth,
body_type=models.Order,
data=body,
method='POST')
).get_body() | [
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|
dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/util/decorators.py | python | change_log_level.__enter__ | (self) | [] | def __enter__(self):
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||||
chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/numpy/lib/npyio.py | python | savez_compressed | (file, *args, **kwds) | Save several arrays into a single file in compressed ``.npz`` format.
If keyword arguments are given, then filenames are taken from the keywords.
If arguments are passed in with no keywords, then stored file names are
arr_0, arr_1, etc.
Parameters
----------
file : str
File name of ``.npz`` file.
args : Arguments
Function arguments.
kwds : Keyword arguments
Keywords.
See Also
--------
numpy.savez : Save several arrays into an uncompressed ``.npz`` file format
numpy.load : Load the files created by savez_compressed. | Save several arrays into a single file in compressed ``.npz`` format. | [
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"""
Save several arrays into a single file in compressed ``.npz`` format.
If keyword arguments are given, then filenames are taken from the keywords.
If arguments are passed in with no keywords, then stored file names are
arr_0, arr_1, etc.
Parameters
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file : str
File name of ``.npz`` file.
args : Arguments
Function arguments.
kwds : Keyword arguments
Keywords.
See Also
--------
numpy.savez : Save several arrays into an uncompressed ``.npz`` file format
numpy.load : Load the files created by savez_compressed.
"""
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||
googleapis/python-ndb | e780c81cde1016651afbfcad8180d9912722cf1b | google/cloud/ndb/model.py | python | DateTimeProperty._from_base_type | (self, value) | Convert a value from the "base" value type for this property.
Args:
value (Union[int, datetime.datetime]): The value to be converted.
The value will be `int` for entities retrieved by a projection
query and is a timestamp as the number of nanoseconds since the
epoch.
Returns:
Optional[datetime.datetime]: If ``tzinfo`` is set on this property,
the value converted to the timezone in ``tzinfo``. Otherwise
returns the value without ``tzinfo`` or ``None`` if value did
not have ``tzinfo`` set. | Convert a value from the "base" value type for this property. | [
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"""Convert a value from the "base" value type for this property.
Args:
value (Union[int, datetime.datetime]): The value to be converted.
The value will be `int` for entities retrieved by a projection
query and is a timestamp as the number of nanoseconds since the
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Returns:
Optional[datetime.datetime]: If ``tzinfo`` is set on this property,
the value converted to the timezone in ``tzinfo``. Otherwise
returns the value without ``tzinfo`` or ``None`` if value did
not have ``tzinfo`` set.
"""
if isinstance(value, six.integer_types):
# Projection query, value is integer nanoseconds
seconds = value / 1e6
value = datetime.datetime.fromtimestamp(seconds, pytz.utc)
if self._tzinfo is not None:
if value.tzinfo is None:
value = value.replace(tzinfo=pytz.utc)
return value.astimezone(self._tzinfo)
elif value.tzinfo is not None:
return value.replace(tzinfo=None) | [
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OpenNMT/OpenNMT-tf | 59a4dfdb911d0570ba1096b7a0a7b9fc5c7844bf | opennmt/encoders/self_attention_encoder.py | python | SelfAttentionEncoder.__init__ | (
self,
num_layers,
num_units=512,
num_heads=8,
ffn_inner_dim=2048,
dropout=0.1,
attention_dropout=0.1,
ffn_dropout=0.1,
ffn_activation=tf.nn.relu,
position_encoder_class=SinusoidalPositionEncoder,
maximum_relative_position=None,
pre_norm=True,
**kwargs
) | Initializes the parameters of the encoder.
Args:
num_layers: The number of layers.
num_units: The number of hidden units.
num_heads: The number of heads in the multi-head attention.
ffn_inner_dim: The number of units of the inner linear transformation
in the feed forward layer.
dropout: The probability to drop units from the outputs.
attention_dropout: The probability to drop units from the attention.
ffn_dropout: The probability to drop units from the activation output in
the feed forward layer.
ffn_activation: The activation function to apply between the two linear
transformations of the feed forward layer.
position_encoder_class: The :class:`opennmt.layers.PositionEncoder`
class to use for position encoding (or a callable that returns an
instance).
maximum_relative_position: Maximum relative position representation
(from https://arxiv.org/abs/1803.02155).
pre_norm: If ``True``, layer normalization is applied before each
sub-layer. Otherwise it is applied after.
**kwargs: Additional layer arguments. | Initializes the parameters of the encoder. | [
"Initializes",
"the",
"parameters",
"of",
"the",
"encoder",
"."
] | def __init__(
self,
num_layers,
num_units=512,
num_heads=8,
ffn_inner_dim=2048,
dropout=0.1,
attention_dropout=0.1,
ffn_dropout=0.1,
ffn_activation=tf.nn.relu,
position_encoder_class=SinusoidalPositionEncoder,
maximum_relative_position=None,
pre_norm=True,
**kwargs
):
"""Initializes the parameters of the encoder.
Args:
num_layers: The number of layers.
num_units: The number of hidden units.
num_heads: The number of heads in the multi-head attention.
ffn_inner_dim: The number of units of the inner linear transformation
in the feed forward layer.
dropout: The probability to drop units from the outputs.
attention_dropout: The probability to drop units from the attention.
ffn_dropout: The probability to drop units from the activation output in
the feed forward layer.
ffn_activation: The activation function to apply between the two linear
transformations of the feed forward layer.
position_encoder_class: The :class:`opennmt.layers.PositionEncoder`
class to use for position encoding (or a callable that returns an
instance).
maximum_relative_position: Maximum relative position representation
(from https://arxiv.org/abs/1803.02155).
pre_norm: If ``True``, layer normalization is applied before each
sub-layer. Otherwise it is applied after.
**kwargs: Additional layer arguments.
"""
super().__init__(**kwargs)
self.num_units = num_units
self.dropout = dropout
self.position_encoder = None
if position_encoder_class is not None:
self.position_encoder = position_encoder_class()
self.layer_norm = common.LayerNorm() if pre_norm else None
self.layers = [
transformer.SelfAttentionEncoderLayer(
num_units,
num_heads,
ffn_inner_dim,
dropout=dropout,
attention_dropout=attention_dropout,
ffn_dropout=ffn_dropout,
ffn_activation=ffn_activation,
maximum_relative_position=maximum_relative_position,
pre_norm=pre_norm,
)
for i in range(num_layers)
] | [
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||
Yelp/kafka-utils | 74831206648512db1a29426c6ebb428b33820d04 | kafka_utils/kafka_check/commands/command.py | python | KafkaCheckCmd.run_command | (self) | Implement the command logic.
When run_command is called cluster_config, args, and zk are already
initialized. | Implement the command logic.
When run_command is called cluster_config, args, and zk are already
initialized. | [
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] | def run_command(self):
"""Implement the command logic.
When run_command is called cluster_config, args, and zk are already
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"""
raise NotImplementedError("Implement in subclass") | [
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||
hyperspy/hyperspy | 1ffb3fab33e607045a37f30c1463350b72617e10 | hyperspy/io_plugins/bruker.py | python | SFSTreeItem.get_iter_and_properties | (self) | Generate and return the iterator of data chunks and
properties of such chunks such as size and count.
Method detects if data is compressed and uses iterator with
decompression involved, else uses simple iterator of chunks.
Returns:
(iterator, chunk_size, number_of_chunks) | Generate and return the iterator of data chunks and
properties of such chunks such as size and count. | [
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"""Generate and return the iterator of data chunks and
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Returns:
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"""
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||
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_openshift/library/oc_project.py | python | Utils._write | (filename, contents) | Actually write the file contents to disk. This helps with mocking. | Actually write the file contents to disk. This helps with mocking. | [
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''' Actually write the file contents to disk. This helps with mocking. '''
with open(filename, 'w') as sfd:
sfd.write(str(contents)) | [
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||
IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/CPython/27/Lib/idlelib/Debugger.py | python | StackViewer.popup_event | (self, event) | override base method | override base method | [
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triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/Centos_6.4/paramiko/logging22.py | python | logger.log | (self, level, text) | [] | def log(self, level, text):
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MozillaSecurity/peach | e5129cb50ce899e3ad009518d8b7cdc535233bbc | Peach/Engine/common.py | python | StreamBuffer.seekFromStart | (self, pos) | Change current position in data.
NOTE: If the position is past the end of the
existing stream data the data will be expanded
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Change current position in data.
NOTE: If the position is past the end of the
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such that the position exists padded with '\0'
"""
if pos < 0:
raise Exception("StreamBuffer.seekFromStart(%d) results in negative position" % pos)
# Should we expand buffer?
if pos > len(self.data):
self.data += '\0' * (pos - len(self.data))
self.pos = pos | [
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||
unknown-horizons/unknown-horizons | 7397fb333006d26c3d9fe796c7bd9cb8c3b43a49 | horizons/world/units/unit.py | python | Unit.onInstanceActionFinished | (self, instance, action) | @param instance: fife.Instance
@param action: string representing the action that is finished. | [] | def onInstanceActionFinished(self, instance, action):
"""
@param instance: fife.Instance
@param action: string representing the action that is finished.
"""
location = fife.Location(self._instance.getLocation().getLayer())
location.setExactLayerCoordinates(fife.ExactModelCoordinate(
self.position.x + self.position.x - self.last_position.x,
self.position.y + self.position.y - self.last_position.y, 0))
facing_loc = self._instance.getFacingLocation()
if action.getId().startswith('move_'):
# Remember: this means we *ended* a "move" action just now!
facing_loc = location
self.act(self._action, facing_loc=facing_loc, repeating=True) | [
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|||
cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/tablib-0.12.1/tablib/packages/dbfpy3/fields.py | python | DbfFieldDef.decodeValue | (self, value) | Return decoded value from string value.
This method shouldn't be used publicly. It's called from the
`decodeFromRecord` method.
This is an abstract method and it must be overridden in child classes. | Return decoded value from string value. | [
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] | def decodeValue(self, value):
"""Return decoded value from string value.
This method shouldn't be used publicly. It's called from the
`decodeFromRecord` method.
This is an abstract method and it must be overridden in child classes.
"""
raise NotImplementedError | [
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||
Podshot/MCEdit-Unified | 90abfb170c65b877ac67193e717fa3a3ded635dd | utilities/misc.py | python | Singleton.Instance | (self) | Returns the singleton instance. Upon its first call, it creates a
new instance of the decorated class and calls its `__init__` method.
On all subsequent calls, the already created instance is returned. | Returns the singleton instance. Upon its first call, it creates a
new instance of the decorated class and calls its `__init__` method.
On all subsequent calls, the already created instance is returned. | [
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"""
Returns the singleton instance. Upon its first call, it creates a
new instance of the decorated class and calls its `__init__` method.
On all subsequent calls, the already created instance is returned.
"""
try:
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return self._instance | [
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||
trailbehind/DeepOSM | 4361273723ba271105e2401ecc1707556816f20c | src/training_data.py | python | download_and_serialize | (number_of_naips,
randomize_naips,
naip_state,
naip_year,
extract_type,
bands,
tile_size,
pixels_to_fatten_roads,
label_data_files,
tile_overlap) | return raster_data_paths | Download NAIP images, PBF files, and serialize training data. | Download NAIP images, PBF files, and serialize training data. | [
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] | def download_and_serialize(number_of_naips,
randomize_naips,
naip_state,
naip_year,
extract_type,
bands,
tile_size,
pixels_to_fatten_roads,
label_data_files,
tile_overlap):
"""Download NAIP images, PBF files, and serialize training data."""
raster_data_paths = NAIPDownloader(number_of_naips,
randomize_naips,
naip_state,
naip_year).download_naips()
create_tiled_training_data(raster_data_paths,
extract_type,
bands,
tile_size,
pixels_to_fatten_roads,
label_data_files,
tile_overlap,
naip_state)
return raster_data_paths | [
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|
oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/stringprep.py | python | in_table_c7 | (code) | return ord(code) in c7_set | [] | def in_table_c7(code):
return ord(code) in c7_set | [
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|||
gammapy/gammapy | 735b25cd5bbed35e2004d633621896dcd5295e8b | gammapy/estimators/points/sed.py | python | FluxPointsEstimator.run | (self, datasets) | return FluxPoints.from_table(
table=table,
reference_model=model.copy(),
gti=datasets.gti,
format="gadf-sed",
) | Run the flux point estimator for all energy groups.
Parameters
----------
datasets : `~gammapy.datasets.Datasets`
Datasets
Returns
-------
flux_points : `FluxPoints`
Estimated flux points. | Run the flux point estimator for all energy groups. | [
"Run",
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] | def run(self, datasets):
"""Run the flux point estimator for all energy groups.
Parameters
----------
datasets : `~gammapy.datasets.Datasets`
Datasets
Returns
-------
flux_points : `FluxPoints`
Estimated flux points.
"""
datasets = Datasets(datasets=datasets)
rows = []
for energy_min, energy_max in progress_bar(
zip(self.energy_edges[:-1], self.energy_edges[1:]), desc="Energy bins"
):
row = self.estimate_flux_point(
datasets,
energy_min=energy_min,
energy_max=energy_max,
)
rows.append(row)
meta = {
"n_sigma": self.n_sigma,
"n_sigma_ul": self.n_sigma_ul,
"sed_type_init": "likelihood",
}
table = table_from_row_data(rows=rows, meta=meta)
model = datasets.models[self.source]
return FluxPoints.from_table(
table=table,
reference_model=model.copy(),
gti=datasets.gti,
format="gadf-sed",
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|
ronf/asyncssh | ee1714c598d8c2ea6f5484e465443f38b68714aa | asyncssh/saslprep.py | python | _map_saslprep | (s: str) | return ''.join(r) | Map stringprep table B.1 to nothing and C.1.2 to ASCII space | Map stringprep table B.1 to nothing and C.1.2 to ASCII space | [
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"space"
] | def _map_saslprep(s: str) -> str:
"""Map stringprep table B.1 to nothing and C.1.2 to ASCII space"""
r = []
for c in s:
if stringprep.in_table_c12(c):
r.append(' ')
elif not stringprep.in_table_b1(c):
r.append(c)
return ''.join(r) | [
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|
triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/Centos_6.4/Crypto/Hash/hashalgo.py | python | HashAlgo.copy | (self) | return self._hash.copy() | Return a copy ("clone") of the hash object.
The copy will have the same internal state as the original hash
object.
This can be used to efficiently compute the digests of strings that
share a common initial substring.
:Return: A hash object of the same type | Return a copy ("clone") of the hash object. | [
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] | def copy(self):
"""Return a copy ("clone") of the hash object.
The copy will have the same internal state as the original hash
object.
This can be used to efficiently compute the digests of strings that
share a common initial substring.
:Return: A hash object of the same type
"""
return self._hash.copy() | [
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|
edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/tencentcloud/vpc/v20170312/models.py | python | DeleteCustomerGatewayResponse.__init__ | (self) | :param RequestId: 唯一请求ID,每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str | :param RequestId: 唯一请求ID,每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str | [
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"""
:param RequestId: 唯一请求ID,每次请求都会返回。定位问题时需要提供该次请求的RequestId。
:type RequestId: str
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self.RequestId = None | [
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||
adonno/Home-AssistantConfig | 8038c0143c6a990e409951202bb1bda149fcbaf7 | custom_components/hacs/sensor.py | python | HACSSensor.async_update | (self) | Update the sensor. | Update the sensor. | [
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] | async def async_update(self):
"""Update the sensor."""
if hacs.system.status.background_task:
return
self.repositories = []
for repository in hacs.repositories:
if repository.pending_upgrade:
self.repositories.append(repository)
self._state = len(self.repositories) | [
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||
HumanCompatibleAI/adversarial-policies | bba910b89149f1274bb9652a6f378b22c3c9b6c5 | src/aprl/configs/multi/train.py | python | _finetune_configs | (envs=None, dual_defense=False) | return configs | Generates configs for finetuning a Zoo model.
Note in this setup, the adversary is the embedded agent, whereas usually the victim is.
:param envs: A list of envs; if set to None, uses all BANSAL_GOOD_ENVS
:param dual_defense: If True, fine-tune against both an adversary and Zoo agent (randomly
selected per episode); if False, fine-tune against just the adversary. | Generates configs for finetuning a Zoo model. | [
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] | def _finetune_configs(envs=None, dual_defense=False):
"""Generates configs for finetuning a Zoo model.
Note in this setup, the adversary is the embedded agent, whereas usually the victim is.
:param envs: A list of envs; if set to None, uses all BANSAL_GOOD_ENVS
:param dual_defense: If True, fine-tune against both an adversary and Zoo agent (randomly
selected per episode); if False, fine-tune against just the adversary.
"""
if envs is None:
envs = BANSAL_GOOD_ENVS
configs = []
adversary_paths = get_adversary_paths()
for env in envs:
original_embed_index = VICTIM_INDEX[env]
num_zoo = gym_compete.num_zoo_policies(env)
for original_victim in range(1, num_zoo + 1):
original_victim = str(original_victim)
load_policy = {"type": "zoo", "path": original_victim}
adversary = _get_policy_path(
adversary_paths, env, str(original_embed_index), original_victim
)
if dual_defense:
# If training both best adversary and Zoo, try each possible Zoo agent
for finetuning_zoo in range(1, num_zoo + 1):
finetuning_zoo = str(finetuning_zoo)
embed_paths = [adversary, finetuning_zoo]
embed_types = ["ppo2", "zoo"]
configs.append(
(env, embed_paths, embed_types, 1 - original_embed_index, load_policy)
)
else:
configs.append((env, [adversary], ["ppo2"], 1 - original_embed_index, load_policy))
return configs | [
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twisted/twisted | dee676b040dd38b847ea6fb112a712cb5e119490 | src/twisted/protocols/amp.py | python | _ParserHelper.parseString | (cls, data) | return cls.parse(BytesIO(data)) | Parse some amp data stored in a string.
@param data: a str holding some amp-encoded data.
@return: a list of AmpBoxes encoded in the given string. | Parse some amp data stored in a string. | [
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] | def parseString(cls, data):
"""
Parse some amp data stored in a string.
@param data: a str holding some amp-encoded data.
@return: a list of AmpBoxes encoded in the given string.
"""
return cls.parse(BytesIO(data)) | [
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mtianyan/VueDjangoAntdProBookShop | fd8fa2151c81edde2f8b8e6df8e1ddd799f940c2 | third_party/qiniu/auth.py | python | Auth.verify_callback | (self, origin_authorization, url, body, content_type='application/x-www-form-urlencoded') | return origin_authorization == authorization | 回调验证
Args:
origin_authorization: 回调时请求Header中的Authorization字段
url: 回调请求的url
body: 回调请求的body
content_type: 回调请求body的Content-Type
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"""回调验证
Args:
origin_authorization: 回调时请求Header中的Authorization字段
url: 回调请求的url
body: 回调请求的body
content_type: 回调请求body的Content-Type
Returns:
返回true表示验证成功,返回false表示验证失败
"""
token = self.token_of_request(url, body, content_type)
authorization = 'QBox {0}'.format(token)
return origin_authorization == authorization | [
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dmnfarrell/pandastable | 9c268b3e2bfe2e718eaee4a30bd02832a0ad1614 | pandastable/headers.py | python | RowHeader.clearSelected | (self) | return | Clear selected rows | Clear selected rows | [
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"""Clear selected rows"""
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|
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/jinja2/runtime.py | python | BlockReference.__init__ | (self, name, context, stack, depth) | [] | def __init__(self, name, context, stack, depth):
self.name = name
self._context = context
self._stack = stack
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||||
mlrun/mlrun | 4c120719d64327a34b7ee1ab08fb5e01b258b00a | mlrun/frameworks/pytorch/mlrun_interface.py | python | PyTorchMLRunInterface._tensor_to_cuda | (
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"""
Send to given tensor to cuda if it is a tensor. If the given object is a dictionary, the dictionary values will
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be sent as well. If the given object is not of type torch.Tensor at the end, nothing will happen.
:param tensor: The batch to sent to cuda.
:return: The copied tensor in cuda memory.
"""
if isinstance(tensor, Tensor) and not tensor.is_cuda:
tensor = tensor.cuda()
if tensor._grad is not None:
tensor._grad.data = tensor._grad.data.cuda()
elif isinstance(tensor, dict):
for key in tensor:
tensor[key] = PyTorchMLRunInterface._tensor_to_cuda(tensor=tensor[key])
elif isinstance(tensor, list):
for index in range(len(tensor)):
tensor[index] = PyTorchMLRunInterface._tensor_to_cuda(
tensor=tensor[index]
)
elif isinstance(tensor, tuple):
cuda_tensor = ()
for value in tensor:
cuda_tensor += (PyTorchMLRunInterface._tensor_to_cuda(tensor=value),)
tensor = cuda_tensor
return tensor | [
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|
entropy1337/infernal-twin | 10995cd03312e39a48ade0f114ebb0ae3a711bb8 | Modules/build/reportlab/src/reportlab/pdfbase/ttfonts.py | python | TTFontMaker.__init__ | (self) | Initializes the generator. | Initializes the generator. | [
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"Initializes the generator."
self.tables = {} | [
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||
catalyst-cooperative/pudl | 40d176313e60dfa9d2481f63842ed23f08f1ad5f | src/pudl/workspace/setup_cli.py | python | main | () | Set up a new default PUDL workspace. | Set up a new default PUDL workspace. | [
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] | def main():
"""Set up a new default PUDL workspace."""
# Display logged output from the PUDL package:
pudl_logger = logging.getLogger("pudl")
log_format = '%(asctime)s [%(levelname)8s] %(name)s:%(lineno)s %(message)s'
coloredlogs.install(fmt=log_format, level='INFO', logger=pudl_logger)
parser = initialize_parser()
args = parser.parse_args(sys.argv[1:])
if not args.pudl_in:
args.pudl_in = args.pudl_dir
if not args.pudl_out:
args.pudl_out = args.pudl_dir
# Given pudl_in and pudl_out, create a user settings file.
pudl_in = pathlib.Path(args.pudl_in).expanduser().resolve()
if not pathlib.Path.is_dir(pudl_in):
raise FileNotFoundError(
f"Directory not found: {pudl_in}")
pudl_out = pathlib.Path(args.pudl_out).expanduser().resolve()
if not pathlib.Path.is_dir(pudl_out):
raise FileNotFoundError(
f"Directory not found: {pudl_out}")
pudl_defaults_file = pathlib.Path.home() / ".pudl.yml"
# Only print out this information and do the defaults setting if that has
# been explicitly requested, or there are no defaults already:
if not pudl_defaults_file.exists() or args.clobber is True:
logger.info(f"Setting default pudl_in: {pudl_in}")
logger.info(f"Setting default pudl_out: {pudl_out}")
logger.info(f"You can update these default values by editing "
f"{pudl_defaults_file}")
pudl.workspace.setup.set_defaults(pudl_in, pudl_out,
clobber=args.clobber)
pudl.workspace.setup.init(pudl_in=pudl_in,
pudl_out=pudl_out,
clobber=args.clobber) | [
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||
cherrypy/cheroot | 75c10f483d7efc87905d955b37150f273ee5ffb2 | cheroot/ssl/builtin.py | python | BuiltinSSLAdapter.context | (self, context) | Set the ssl ``context`` to use. | Set the ssl ``context`` to use. | [
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] | def context(self, context):
"""Set the ssl ``context`` to use."""
self._context = context
# Python 3.7+
# if a context is provided via `cherrypy.config.update` then
# `self.context` will be set after `__init__`
# use a property to intercept it to add an SNI callback
# but don't override the user's callback
# TODO: chain callbacks
with suppress(AttributeError):
if ssl.HAS_SNI and context.sni_callback is None:
context.sni_callback = _sni_callback | [
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aliyun/aliyun-oss-python-sdk | 5f2afa0928a58c7c1cc6317ac147f3637481f6fd | oss2/auth.py | python | StsAuth.__init__ | (self, access_key_id, access_key_secret, security_token, auth_version=AUTH_VERSION_1) | [] | def __init__(self, access_key_id, access_key_secret, security_token, auth_version=AUTH_VERSION_1):
logger.debug("Init StsAuth: access_key_id: {0}, access_key_secret: ******, security_token: ******".format(access_key_id))
credentials_provider = StaticCredentialsProvider(access_key_id, access_key_secret, security_token)
self.__auth = ProviderAuthV2(credentials_provider) if auth_version == AUTH_VERSION_2 else ProviderAuth(credentials_provider) | [
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||||
landlab/landlab | a5dd80b8ebfd03d1ba87ef6c4368c409485f222c | landlab/components/marine_sediment_transport/simple_submarine_diffuser.py | python | SimpleSubmarineDiffuser.calc_diffusion_coef | (self) | return k | Calculate and store diffusion coefficient values.
Returns
-------
k : float array
Diffusion coefficient, m2/y | Calculate and store diffusion coefficient values. | [
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] | def calc_diffusion_coef(self):
"""
Calculate and store diffusion coefficient values.
Returns
-------
k : float array
Diffusion coefficient, m2/y
"""
sea_level = self.grid.at_grid["sea_level__elevation"]
self._depth[:] = sea_level - self._grid.at_node["topographic__elevation"]
deep_water = self._depth > self._wave_base
land = self._depth < 0.0
k = self.grid.at_node["kd"]
k[:] = self._shallow_water_diffusivity * self.depth_function(self._depth)
k[deep_water] *= np.exp(
-(self._depth[deep_water] - self._wave_base) / self._wave_base
)
k[land] += _TINY_DIFFUSIVITY
return k | [
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|
nightmaredimple/libmot | 23b8e2ac00f8b45d5a0ecabd57af90585966f3ff | libmot/motion/epipolar_geometry.py | python | Epipolar.DrawMatches | (self, src, dst, keypoints1, keypoints2, matches, n = None) | return draw | Draw matches between source image with target image
Parameters
----------
src : ndarray
A HxW matrix of opencv image
dst : ndarray
A HxW matrix of opencv image
keypoints1: ndarray
A Nx2 matrix of keypoints in src image
keypoints2: ndarray
A Nx2 matrix of keypoints in dst image
matches: List of matches
n: int
numbers of matches to be drawn
Returns
-------
draw: ndarray
A Hx2W matrix of opencv image | Draw matches between source image with target image | [
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"""Draw matches between source image with target image
Parameters
----------
src : ndarray
A HxW matrix of opencv image
dst : ndarray
A HxW matrix of opencv image
keypoints1: ndarray
A Nx2 matrix of keypoints in src image
keypoints2: ndarray
A Nx2 matrix of keypoints in dst image
matches: List of matches
n: int
numbers of matches to be drawn
Returns
-------
draw: ndarray
A Hx2W matrix of opencv image
"""
assert src.shape == dst.shape, "source image must be the same format with target image"
if n is None:
n = self.n_points
n = min(n, len(matches))
draw = cv2.drawMatches(src, keypoints1, dst, keypoints2, matches[: n], None, flags = 2)
return draw | [
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|
TengXiaoDai/DistributedCrawling | f5c2439e6ce68dd9b49bde084d76473ff9ed4963 | Lib/site-packages/pip/_vendor/requests/structures.py | python | CaseInsensitiveDict.lower_items | (self) | return (
(lowerkey, keyval[1])
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"""Like iteritems(), but with all lowercase keys."""
return (
(lowerkey, keyval[1])
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in self._store.items()
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|
pymeasure/pymeasure | b4d888e9ead85ef7f7af0031f2dbb44c9ce1825e | pymeasure/experiment/experiment.py | python | get_array_zero | (maxval, step) | return np.concatenate((np.arange(0, maxval, step), np.arange(maxval, -maxval, -step),
np.arange(-maxval, 0, step))) | Returns a numpy array from 0 to maxval to -maxval to 0 | Returns a numpy array from 0 to maxval to -maxval to 0 | [
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"""Returns a numpy array from 0 to maxval to -maxval to 0"""
return np.concatenate((np.arange(0, maxval, step), np.arange(maxval, -maxval, -step),
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Manjaro-WebDad/jde | 91d84df112c00b2eceb5afdaeeca11be347cd99f | src/Jade/Utils.py | python | Session.get_pkg_manager_state | () | return os.path.isfile("/var/lib/pacman/db.lck") | [] | def get_pkg_manager_state():
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|||
virantha/pypdfocr | acc5e13763224267e897865fccafbf51e13725e9 | fabfile.py | python | run_tests | () | [] | def run_tests():
test_dir = "test"
with lcd(test_dir):
# Regenerate the test script
local("py.test --genscript=runtests.py")
t = local("py.test --cov-config .coveragerc --cov=pypdfocr --cov-report=term --cov-report=html", capture=False)
t = local("coveralls") | [
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||||
demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/CheckpointFirewall/Integrations/CheckPointFirewallV2/CheckPointFirewallV2.py | python | Client.logout | (self) | return message | logout from current session, returning the response message | logout from current session, returning the response message | [
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"""logout from current session, returning the response message"""
response = self._http_request(method='POST', url_suffix='logout', headers=self.headers, json_data={})
self.sid = None
demisto.setIntegrationContext({})
self.has_performed_login = False
message = response.get('message')
demisto.debug(f"logout: sid={self.sid}, message={message}")
return message | [
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|
zetaops/ulakbus | bcc05abf17bbd6dbeec93809e4ad30885e94e83e | ulakbus/views/ogrenci/ogrenci.py | python | MazeretliDersKaydi.karar_no_gir | (self) | Mazeretli öğrenci kaydı, fakülte yönetim kurulu kararıyla yapılmaktadır. Bu adımda
kullanıcıdan ilgili karar numarasını girmesi beklenir.
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kullanıcıdan ilgili karar numarasını girmesi beklenir.
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statüsüne sahip olmalıdırlar.
"""
aktif_ogrenci_status_list = [1, 12, 14, 16, 18, 20]
self.current.task_data['program'] = self.current.input['form']['program']
ogrenci_program = OgrenciProgram.objects.get(self.current.input['form']['program'])
if ogrenci_program.ogrencilik_statusu in aktif_ogrenci_status_list:
_form = forms.JsonForm(current=self.current,
title=_(u"Fakülte Yönetim Kurulu Karar No Giriniz"))
_form.karar_no = fields.String(title=_(u"Fakülte Yönetim Kurulu Karar No"))
_form.sec = fields.Button(_(u"Kaydet"))
self.form_out(_form)
else:
self.current.output['msgbox'] = {
'type': 'warning', "title": _(u'Öğrenci Ders Kaydı Yapamaz'),
"msg": _(u'Öğrenci Durum Kodu Ders Kaydı İçin Uygun Değil')
} | [
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||
studioml/studio | ad8d8c7cff8b4ac6f791ceb881be24dafb2a8a55 | studio/encrypted_payload_builder.py | python | EncryptedPayloadBuilder.__init__ | (self, name: str,
receiver_keypath: str,
sender_keypath: str = None) | param: name - payload builder name
param: receiver_keypath - file path to .pem file
with recipient public key
param: sender_keypath - file path to .pem file
with sender private key | param: name - payload builder name
param: receiver_keypath - file path to .pem file
with recipient public key
param: sender_keypath - file path to .pem file
with sender private key | [
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sender_keypath: str = None):
"""
param: name - payload builder name
param: receiver_keypath - file path to .pem file
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param: sender_keypath - file path to .pem file
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"""
super(EncryptedPayloadBuilder, self).__init__(name)
# XXX Set logger verbosity level here
self.logger = logs.get_logger(self.__class__.__name__)
self.recipient_key_path = receiver_keypath
self.recipient_key = None
try:
self.recipient_key =\
RSA.import_key(open(self.recipient_key_path).read())
except:
check_for_kb_interrupt()
msg = "FAILED to import recipient public key from: {0}"\
.format(self.recipient_key_path)
self.logger.error(msg)
raise ValueError(msg)
self.sender_key_path = sender_keypath
self.sender_key: SigningKey = None
self.verify_key: VerifyKey = None
self.sender_fingerprint = None
if self.sender_key_path is None:
self.logger.error("Signing key path must be specified for encrypted payloads. ABORTING.")
raise ValueError()
# We expect ed25519 signing key in "openssh private key" format
try:
public_key_data, private_key_data =\
Ed25519KeyUtil.parse_private_key_file(
self.sender_key_path, self.logger)
if public_key_data is None or private_key_data is None:
self._raise_error(
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.format(self.sender_key_path))
self.sender_key = SigningKey(private_key_data)
self.verify_key = VerifyKey(public_key_data)
except Exception:
self._raise_error("FAILED to open/read private signing key file: {0}"\
.format(self.sender_key_path))
self.sender_fingerprint = \
self._get_fingerprint(public_key_data)
self.simple_builder =\
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] | https://github.com/studioml/studio/blob/ad8d8c7cff8b4ac6f791ceb881be24dafb2a8a55/studio/encrypted_payload_builder.py#L22-L79 |
||
tensorflow/federated | 5a60a032360087b8f4c7fcfd97ed1c0131c3eac3 | tensorflow_federated/python/core/impl/compiler/tree_transformations.py | python | merge_chained_blocks | (comp) | return _apply_transforms(comp, MergeChainedBlocks(comp)) | Merges chained blocks into one block. | Merges chained blocks into one block. | [
"Merges",
"chained",
"blocks",
"into",
"one",
"block",
"."
] | def merge_chained_blocks(comp):
"""Merges chained blocks into one block."""
return _apply_transforms(comp, MergeChainedBlocks(comp)) | [
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|
django/channels | 6af1bc3ab45f55e3f47d0d1d059d5db0a18a9581 | channels/generic/http.py | python | AsyncHttpConsumer.http_request | (self, message) | Async entrypoint - concatenates body fragments and hands off control
to ``self.handle`` when the body has been completely received. | Async entrypoint - concatenates body fragments and hands off control
to ``self.handle`` when the body has been completely received. | [
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"""
Async entrypoint - concatenates body fragments and hands off control
to ``self.handle`` when the body has been completely received.
"""
if "body" in message:
self.body.append(message["body"])
if not message.get("more_body"):
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raise StopConsumer() | [
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||
AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/api/datastore_types.py | python | PropertyValueFromString | (type_,
value_string,
_auth_domain=None) | return type_(value_string) | Returns an instance of a property value given a type and string value.
The reverse of this method is just str() and type() of the python value.
Note that this does *not* support non-UTC offsets in ISO 8601-formatted
datetime strings, e.g. the -08:00 suffix in '2002-12-25 00:00:00-08:00'.
It only supports -00:00 and +00:00 suffixes, which are UTC.
Args:
type_: A python class.
value_string: A string representation of the value of the property.
Returns:
An instance of 'type'.
Raises:
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] | def PropertyValueFromString(type_,
value_string,
_auth_domain=None):
"""Returns an instance of a property value given a type and string value.
The reverse of this method is just str() and type() of the python value.
Note that this does *not* support non-UTC offsets in ISO 8601-formatted
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type_: A python class.
value_string: A string representation of the value of the property.
Returns:
An instance of 'type'.
Raises:
ValueError if type_ is datetime and value_string has a timezone offset.
"""
if type_ == datetime.datetime:
value_string = value_string.strip()
if value_string[-6] in ('+', '-'):
if value_string[-5:] == '00:00':
value_string = value_string[:-6]
else:
raise ValueError('Non-UTC offsets in datetimes are not supported.')
split = value_string.split('.')
iso_date = split[0]
microseconds = 0
if len(split) > 1:
microseconds = int(split[1])
time_struct = time.strptime(iso_date, '%Y-%m-%d %H:%M:%S')[0:6]
value = datetime.datetime(*(time_struct + (microseconds,)))
return value
elif type_ == Rating:
return Rating(int(value_string))
elif type_ == bool:
return value_string == 'True'
elif type_ == users.User:
return users.User(value_string, _auth_domain)
elif type_ == type(None):
return None
return type_(value_string) | [
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|
ydkhatri/mac_apt | 729630c8bbe7a73cce3ca330305d3301a919cb07 | plugins/helpers/apfs_reader.py | python | ApfsContainer.fletcher64_verify_block_num | (self, block_num) | return self.fletcher64_verify_block_data(data, self.block_size) | Fletchers checksum verification for block, given block number | Fletchers checksum verification for block, given block number | [
"Fletchers",
"checksum",
"verification",
"for",
"block",
"given",
"block",
"number"
] | def fletcher64_verify_block_num(self, block_num):
"""Fletchers checksum verification for block, given block number"""
data = self.get_block(block_num)
if not data:
return None
return self.fletcher64_verify_block_data(data, self.block_size) | [
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|
nasa/CrisisMappingToolkit | 0296487974d74cec6aa8be42eafbb5cd24dc6a51 | app_engine/libs/bs4/element.py | python | ContentMetaAttributeValue.encode | (self, encoding) | return self.CHARSET_RE.sub(rewrite, self.original_value) | [] | def encode(self, encoding):
def rewrite(match):
return match.group(1) + encoding
return self.CHARSET_RE.sub(rewrite, self.original_value) | [
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|||
riptideio/pymodbus | c5772b35ae3f29d1947f3ab453d8d00df846459f | pymodbus/server/asynchronous.py | python | ModbusTcpProtocol._send | (self, message) | Send a request (string) to the network
:param message: The unencoded modbus response | Send a request (string) to the network | [
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""" Send a request (string) to the network
:param message: The unencoded modbus response
"""
if message.should_respond:
self.factory.control.Counter.BusMessage += 1
pdu = self.framer.buildPacket(message)
if _logger.isEnabledFor(logging.DEBUG):
_logger.debug('send: %s' % b2a_hex(pdu))
return self.transport.write(pdu) | [
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||
openstack/cinder | 23494a6d6c51451688191e1847a458f1d3cdcaa5 | cinder/volume/volume_utils.py | python | copy_image_to_volume | (driver,
context: context.RequestContext,
volume: 'objects.Volume',
image_meta: dict,
image_location: str,
image_service) | Downloads Glance image to the specified volume. | Downloads Glance image to the specified volume. | [
"Downloads",
"Glance",
"image",
"to",
"the",
"specified",
"volume",
"."
] | def copy_image_to_volume(driver,
context: context.RequestContext,
volume: 'objects.Volume',
image_meta: dict,
image_location: str,
image_service) -> None:
"""Downloads Glance image to the specified volume."""
image_id = image_meta['id']
LOG.debug("Attempting download of %(image_id)s (%(image_location)s)"
" to volume %(volume_id)s.",
{'image_id': image_id, 'volume_id': volume.id,
'image_location': image_location})
try:
image_encryption_key = image_meta.get('cinder_encryption_key_id')
if volume.encryption_key_id and image_encryption_key:
# If the image provided an encryption key, we have
# already cloned it to the volume's key in
# _get_encryption_key_id, so we can do a direct copy.
driver.copy_image_to_volume(
context, volume, image_service, image_id)
elif volume.encryption_key_id:
# Creating an encrypted volume from a normal, unencrypted,
# image.
driver.copy_image_to_encrypted_volume(
context, volume, image_service, image_id)
else:
driver.copy_image_to_volume(
context, volume, image_service, image_id)
except processutils.ProcessExecutionError as ex:
LOG.exception("Failed to copy image %(image_id)s to volume: "
"%(volume_id)s",
{'volume_id': volume.id, 'image_id': image_id})
raise exception.ImageCopyFailure(reason=ex.stderr)
except (exception.ImageUnacceptable, exception.ImageTooBig):
with excutils.save_and_reraise_exception():
LOG.exception("Failed to copy image %(image_id)s to volume: "
"%(volume_id)s",
{'volume_id': volume.id, 'image_id': image_id})
except Exception as ex:
LOG.exception("Failed to copy image %(image_id)s to "
"volume: %(volume_id)s",
{'volume_id': volume.id, 'image_id': image_id})
if not isinstance(ex, exception.ImageCopyFailure):
raise exception.ImageCopyFailure(reason=ex)
else:
raise
LOG.debug("Downloaded image %(image_id)s (%(image_location)s)"
" to volume %(volume_id)s successfully.",
{'image_id': image_id, 'volume_id': volume.id,
'image_location': image_location}) | [
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||
lebedov/scikit-cuda | 5d3c74f926fe7ce67ecfc85e9623aab7bc0b344f | skcuda/cusparse.py | python | cusparseGetVersion | (handle) | return version.value | Return CUSPARSE library version.
Returns the version number of the CUSPARSE library.
Parameters
----------
handle : int
CUSPARSE library context.
Returns
-------
version : int
CUSPARSE library version number. | Return CUSPARSE library version. | [
"Return",
"CUSPARSE",
"library",
"version",
"."
] | def cusparseGetVersion(handle):
"""
Return CUSPARSE library version.
Returns the version number of the CUSPARSE library.
Parameters
----------
handle : int
CUSPARSE library context.
Returns
-------
version : int
CUSPARSE library version number.
"""
version = ctypes.c_int()
status = _libcusparse.cusparseGetVersion(handle,
ctypes.byref(version))
cusparseCheckStatus(status)
return version.value | [
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|
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/PIL/ImageDraw.py | python | ImageDraw.__init__ | (self, im, mode=None) | Create a drawing instance.
:param im: The image to draw in.
:param mode: Optional mode to use for color values. For RGB
images, this argument can be RGB or RGBA (to blend the
drawing into the image). For all other modes, this argument
must be the same as the image mode. If omitted, the mode
defaults to the mode of the image. | Create a drawing instance. | [
"Create",
"a",
"drawing",
"instance",
"."
] | def __init__(self, im, mode=None):
"""
Create a drawing instance.
:param im: The image to draw in.
:param mode: Optional mode to use for color values. For RGB
images, this argument can be RGB or RGBA (to blend the
drawing into the image). For all other modes, this argument
must be the same as the image mode. If omitted, the mode
defaults to the mode of the image.
"""
im.load()
if im.readonly:
im._copy() # make it writeable
blend = 0
if mode is None:
mode = im.mode
if mode != im.mode:
if mode == "RGBA" and im.mode == "RGB":
blend = 1
else:
raise ValueError("mode mismatch")
if mode == "P":
self.palette = im.palette
else:
self.palette = None
self.im = im.im
self.draw = Image.core.draw(self.im, blend)
self.mode = mode
if mode in ("I", "F"):
self.ink = self.draw.draw_ink(1, mode)
else:
self.ink = self.draw.draw_ink(-1, mode)
if mode in ("1", "P", "I", "F"):
# FIXME: fix Fill2 to properly support matte for I+F images
self.fontmode = "1"
else:
self.fontmode = "L" # aliasing is okay for other modes
self.fill = 0
self.font = None | [
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||
OmegaK2/PyPoE | 97479f3aea2385b196b1a900e06caa253bb5c72d | PyPoE/cli/handler.py | python | ConfigHandler.get | (self, args) | return 0 | Prints the config setting for the specified var.
Parameters
----------
args : argparse.Namespace
namespace object as passed from argument parser
Returns
-------
int
success code | Prints the config setting for the specified var. | [
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] | def get(self, args):
"""
Prints the config setting for the specified var.
Parameters
----------
args : argparse.Namespace
namespace object as passed from argument parser
Returns
-------
int
success code
"""
console('Config setting "%s" is currently set to:\n%s' % (args.variable, self.config.option[args.variable]))
return 0 | [
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|
Breakthrough/PySceneDetect | f1724075498f66712a9082abe8b3c7446b19790a | scenedetect/scene_detector.py | python | SparseSceneDetector.process_frame | (self, frame_num, frame_img) | return [] | Process Frame: Computes/stores metrics and detects any scene changes.
Prototype method, no actual detection.
Returns:
List[Tuple[int,int]]: List of frame pairs representing individual scenes
to be added to the output scene list directly. | Process Frame: Computes/stores metrics and detects any scene changes. | [
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# type: (int, numpy.ndarray) -> List[Tuple[int, int]]
""" Process Frame: Computes/stores metrics and detects any scene changes.
Prototype method, no actual detection.
Returns:
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"""
return [] | [
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|
saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/cloud/clouds/xen.py | python | destroy_vm_vdis | (name=None, session=None, call=None) | return ret | Get virtual block devices on VM
.. code-block:: bash
salt-cloud -a destroy_vm_vdis xenvm01 | Get virtual block devices on VM | [
"Get",
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"""
Get virtual block devices on VM
.. code-block:: bash
salt-cloud -a destroy_vm_vdis xenvm01
"""
if session is None:
session = _get_session()
ret = {}
# get vm object
vms = session.xenapi.VM.get_by_name_label(name)
if len(vms) == 1:
# read virtual block device (vdb)
vbds = session.xenapi.VM.get_VBDs(vms[0])
if vbds is not None:
x = 0
for vbd in vbds:
vbd_record = session.xenapi.VBD.get_record(vbd)
if vbd_record["VDI"] != "OpaqueRef:NULL":
# read vdi on vdb
vdi_record = session.xenapi.VDI.get_record(vbd_record["VDI"])
if "iso" not in vdi_record["name_label"]:
session.xenapi.VDI.destroy(vbd_record["VDI"])
ret["vdi-{}".format(x)] = vdi_record["name_label"]
x += 1
return ret | [
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|
krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit - MAC OSX/scripts/sshbackdoors/target.py | python | Target.conn | (self) | [] | def conn(self):
#print("Opening SSH connection to target...")
self.ssh = paramiko.SSHClient()#use ssh.exec_command("") to perform an action.
self.ssh.load_system_host_keys()
self.ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
self.ssh.connect(self.hostname, port=self.port, username=self.uname, password=self.pword)
self.scp = SCPClient(self.ssh.get_transport())#don't call this, but use the above function instead.
self.is_open = True | [
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||||
ARM-DOE/pyart | 72affe5b669f1996cd3cc39ec7d8dd29b838bd48 | pyart/core/radar.py | python | Radar.get_gate_x_y_z | (self, sweep, edges=False, filter_transitions=False) | return antenna_vectors_to_cartesian(
self.range['data'], azimuths, elevations, edges=edges) | Return the x, y and z gate locations in meters for a given sweep.
With the default parameter this method returns the same data as
contained in the gate_x, gate_y and gate_z attributes but this method
performs the gate location calculations only for the specified sweep
and therefore is more efficient than accessing this data through these
attribute.
When used with :py:func:`get_field` this method can be used to obtain
the data needed for plotting a radar field with the correct spatial
context.
Parameters
----------
sweep : int
Sweep number to retrieve gate locations from, 0 based.
edges : bool, optional
True to return the locations of the gate edges calculated by
interpolating between the range, azimuths and elevations.
False (the default) will return the locations of the gate centers
with no interpolation.
filter_transitions : bool, optional
True to remove rays where the antenna was in transition between
sweeps. False will include these rays. No rays will be removed
if the antenna_transition attribute is not available (set to None).
Returns
-------
x, y, z : 2D array
Array containing the x, y and z, distances from the radar in
meters for the center (or edges) for all gates in the sweep. | Return the x, y and z gate locations in meters for a given sweep. | [
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] | def get_gate_x_y_z(self, sweep, edges=False, filter_transitions=False):
"""
Return the x, y and z gate locations in meters for a given sweep.
With the default parameter this method returns the same data as
contained in the gate_x, gate_y and gate_z attributes but this method
performs the gate location calculations only for the specified sweep
and therefore is more efficient than accessing this data through these
attribute.
When used with :py:func:`get_field` this method can be used to obtain
the data needed for plotting a radar field with the correct spatial
context.
Parameters
----------
sweep : int
Sweep number to retrieve gate locations from, 0 based.
edges : bool, optional
True to return the locations of the gate edges calculated by
interpolating between the range, azimuths and elevations.
False (the default) will return the locations of the gate centers
with no interpolation.
filter_transitions : bool, optional
True to remove rays where the antenna was in transition between
sweeps. False will include these rays. No rays will be removed
if the antenna_transition attribute is not available (set to None).
Returns
-------
x, y, z : 2D array
Array containing the x, y and z, distances from the radar in
meters for the center (or edges) for all gates in the sweep.
"""
azimuths = self.get_azimuth(sweep)
elevations = self.get_elevation(sweep)
if filter_transitions and self.antenna_transition is not None:
sweep_slice = self.get_slice(sweep)
valid = self.antenna_transition['data'][sweep_slice] == 0
azimuths = azimuths[valid]
elevations = elevations[valid]
return antenna_vectors_to_cartesian(
self.range['data'], azimuths, elevations, edges=edges) | [
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|
florath/rmtoo | 6ffe08703451358dca24b232ee4380b1da23bcad | rmtoo/lib/vcs/Git.py | python | Git.__get_tree_direct | (self, base_tree, directory) | Return the tree of the given directory.
This does not walk down the directory structure.
It just checks the current hierarchy. | Return the tree of the given directory.
This does not walk down the directory structure.
It just checks the current hierarchy. | [
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] | def __get_tree_direct(self, base_tree, directory):
'''Return the tree of the given directory.
This does not walk down the directory structure.
It just checks the current hierarchy.'''
for tree in base_tree.trees:
if tree.name == directory:
return tree
raise RMTException(108, "directory entry [%s] not found in tree "
"[%s]." % (directory, base_tree.name)) | [
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||
ktbyers/netmiko | 4c3732346eea1a4a608abd9e09d65eeb2f577810 | netmiko/dell/dell_os10_ssh.py | python | DellOS10FileTransfer.check_file_exists | (self, remote_cmd: str = "dir home") | Check if the dest_file already exists on the file system (return boolean). | Check if the dest_file already exists on the file system (return boolean). | [
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] | def check_file_exists(self, remote_cmd: str = "dir home") -> bool:
"""Check if the dest_file already exists on the file system (return boolean)."""
if self.direction == "put":
remote_out = self.ssh_ctl_chan._send_command_str(remote_cmd)
search_string = r"Directory contents .*{}".format(self.dest_file)
return bool(re.search(search_string, remote_out, flags=re.DOTALL))
elif self.direction == "get":
return os.path.exists(self.dest_file)
else:
raise ValueError("self.direction is set to an invalid value") | [
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||
foxmask/django-th | 29aa84f8d4aa945dbef6cf580593b435cc708e31 | th_rss/lib/conditionchecker/conditionchecker.py | python | Condition.check | (self, datas, *filers) | this method permits to reduce the quantity of information to read
by applying some filtering
here '*filers' can receive a list of properties to be filtered | this method permits to reduce the quantity of information to read
by applying some filtering
here '*filers' can receive a list of properties to be filtered | [
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'''
this method permits to reduce the quantity of information to read
by applying some filtering
here '*filers' can receive a list of properties to be filtered
'''
# special case : no filter : want to read all the feed
if self.match == "" and self.does_not_match == '':
yield datas
# let's filtering :
else:
condition1 = False
condition2 = False
# arg contain the property from which we want to check the 'data'
for prop in filers:
# check if my datas contains my property
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# filter to find only this data
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if condition2:
continue
if condition1 and condition2 is False:
yield datas | [
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||
llSourcell/AI_Artist | 3038c06c2e389b9c919c881c9a169efe2fd7810e | lib/python2.7/site-packages/pip/_vendor/requests/cookies.py | python | RequestsCookieJar.itervalues | (self) | Dict-like itervalues() that returns an iterator of values of cookies
from the jar. See iterkeys() and iteritems(). | Dict-like itervalues() that returns an iterator of values of cookies
from the jar. See iterkeys() and iteritems(). | [
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josauder/procedural_city_generation | e53d9a48440c914f9aad65455b3aebc13d90bc98 | procedural_city_generation/building_generation/roofs.py | python | houseroof | (walls, currentheight, roofheight, texture) | return [Polygon3D(verts, faces, texture)] | Creates a "classic" roof with two triangles and two rectangles.
Used only for houses and assumes that the house has 4 sides.
Parameters
-----------
walls : procedural_city_generation.building_generation.Walls object
currentheight : float
Current height, Z coordinate of the base of the roof
roofheight : float
Height of the roof itself
texture : procedural_city_generation.building_generation.Texture object
Returns
-------
list<procedural_city_generation.building_generation.Polygon3D object> | Creates a "classic" roof with two triangles and two rectangles.
Used only for houses and assumes that the house has 4 sides. | [
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"""Creates a "classic" roof with two triangles and two rectangles.
Used only for houses and assumes that the house has 4 sides.
Parameters
-----------
walls : procedural_city_generation.building_generation.Walls object
currentheight : float
Current height, Z coordinate of the base of the roof
roofheight : float
Height of the roof itself
texture : procedural_city_generation.building_generation.Texture object
Returns
-------
list<procedural_city_generation.building_generation.Polygon3D object>
"""
#Differentiation: the shorter of the first two walls is to be cut in half
if not np.linalg.norm(np.diff(walls.getWalls()[0], axis=0))<np.linalg.norm(np.diff(walls.getWalls()[1], axis=0)):
walls=Walls(np.roll(walls.vertices, 1, axis=0), walls.l)
h_low=np.array([0, 0, currentheight])
h_high=h_low+np.array([0, 0, roofheight])
#The gable coordinates
c1, c2=sum(walls.getWalls()[0]/2), sum(walls.getWalls()[2]/2)
#Verts are the vertices of the wall and the vertices of the gable
verts=[x+h_low for x in walls.vertices]+[c1+h_high, c2+h_high]
#Faces are two rectangles and two triangles
faces=[(0, 1, 5, 4), (3, 2, 5, 4), (0, 3, 4), (1, 2, 5)]
return [Polygon3D(verts, faces, texture)] | [
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|
tensorflow/federated | 5a60a032360087b8f4c7fcfd97ed1c0131c3eac3 | tensorflow_federated/python/core/impl/types/computation_types.py | python | Type.__eq__ | (self, other) | Determines whether two type definitions are identical.
Note that this notion of equality is stronger than equivalence. Two types
with equivalent definitions may not be identical, e.g., if they represent
templates with differently named type variables in their definitions.
Args:
other: The other type to compare against.
Returns:
`True` iff type definitions are syntatically identical (as defined above),
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Raises:
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Note that this notion of equality is stronger than equivalence. Two types
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templates with differently named type variables in their definitions.
Args:
other: The other type to compare against.
Returns:
`True` iff type definitions are syntatically identical (as defined above),
or `False` otherwise.
Raises:
NotImplementedError: If not implemented in the derived class.
"""
raise NotImplementedError | [
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andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/core/controllers/profiling/memory_usage.py | python | stop_memory_profiling | () | We cancel the save thread and dump objects for the last time. | We cancel the save thread and dump objects for the last time. | [
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"""
We cancel the save thread and dump objects for the last time.
"""
cancel_thread(SAVE_THREAD_PTR)
dump_objects() | [
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||
toandaominh1997/EfficientDet.Pytorch | fbe56e58c9a2749520303d2d380427e5f01305ba | models/efficientnet.py | python | EfficientNet.extract_features | (self, inputs) | return P | Returns output of the final convolution layer | Returns output of the final convolution layer | [
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""" Returns output of the final convolution layer """
# Stem
x = self._swish(self._bn0(self._conv_stem(inputs)))
P = []
index = 0
num_repeat = 0
# Blocks
for idx, block in enumerate(self._blocks):
drop_connect_rate = self._global_params.drop_connect_rate
if drop_connect_rate:
drop_connect_rate *= float(idx) / len(self._blocks)
x = block(x, drop_connect_rate=drop_connect_rate)
num_repeat = num_repeat + 1
if(num_repeat == self._blocks_args[index].num_repeat):
num_repeat = 0
index = index + 1
P.append(x)
return P | [
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|
ungarj/label_centerlines | ec1ac69414ae7b4aa8e353b233b782583df97caf | label_centerlines/_src.py | python | _yield_ridge_vertices | (vor, geometry, dist=False) | Yield Voronoi ridge vertices within geometry. | Yield Voronoi ridge vertices within geometry. | [
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] | def _yield_ridge_vertices(vor, geometry, dist=False):
"""Yield Voronoi ridge vertices within geometry."""
for x, y in vor.ridge_vertices:
if x < 0 or y < 0:
continue
point1 = Point(vor.vertices[[x, y]][0])
point2 = Point(vor.vertices[[x, y]][1])
# Eliminate all points outside our geometry.
if point1.within(geometry) and point2.within(geometry):
if dist:
yield x, y, point1.distance(point2)
else:
yield x, y | [
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||
AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/webapp2-2.3/webapp2_extras/sessions.py | python | SessionDict.get_flashes | (self, key='_flash') | return self.pop(key, []) | Returns a flash message. Flash messages are deleted when first read.
:param key:
Name of the flash key stored in the session. Default is '_flash'.
:returns:
The data stored in the flash, or an empty list. | Returns a flash message. Flash messages are deleted when first read. | [
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Name of the flash key stored in the session. Default is '_flash'.
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sametmax/Django--an-app-at-a-time | 99eddf12ead76e6dfbeb09ce0bae61e282e22f8a | ignore_this_directory/django/template/defaulttags.py | python | firstof | (parser, token) | return FirstOfNode([parser.compile_filter(bit) for bit in bits], asvar) | Output the first variable passed that is not False.
Output nothing if all the passed variables are False.
Sample usage::
{% firstof var1 var2 var3 as myvar %}
This is equivalent to::
{% if var1 %}
{{ var1 }}
{% elif var2 %}
{{ var2 }}
{% elif var3 %}
{{ var3 }}
{% endif %}
but obviously much cleaner!
You can also use a literal string as a fallback value in case all
passed variables are False::
{% firstof var1 var2 var3 "fallback value" %}
If you want to disable auto-escaping of variables you can use::
{% autoescape off %}
{% firstof var1 var2 var3 "<strong>fallback value</strong>" %}
{% autoescape %}
Or if only some variables should be escaped, you can use::
{% firstof var1 var2|safe var3 "<strong>fallback value</strong>"|safe %} | Output the first variable passed that is not False. | [
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"""
Output the first variable passed that is not False.
Output nothing if all the passed variables are False.
Sample usage::
{% firstof var1 var2 var3 as myvar %}
This is equivalent to::
{% if var1 %}
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but obviously much cleaner!
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{% firstof var1 var2 var3 "fallback value" %}
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{% autoescape off %}
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{% autoescape %}
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{% firstof var1 var2|safe var3 "<strong>fallback value</strong>"|safe %}
"""
bits = token.split_contents()[1:]
asvar = None
if not bits:
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asvar = bits[-1]
bits = bits[:-2]
return FirstOfNode([parser.compile_filter(bit) for bit in bits], asvar) | [
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|
sympy/sympy | d822fcba181155b85ff2b29fe525adbafb22b448 | sympy/integrals/intpoly.py | python | integration_reduction | (facets, index, a, b, expr, dims, degree) | return value/(len(dims) + degree - 1) | Helper method for main_integrate. Returns the value of the input
expression evaluated over the polytope facet referenced by a given index.
Parameters
===========
facets :
List of facets of the polytope.
index :
Index referencing the facet to integrate the expression over.
a :
Hyperplane parameter denoting direction.
b :
Hyperplane parameter denoting distance.
expr :
The expression to integrate over the facet.
dims :
List of symbols denoting axes.
degree :
Degree of the homogeneous polynomial.
Examples
========
>>> from sympy.abc import x, y
>>> from sympy.integrals.intpoly import integration_reduction,\
hyperplane_parameters
>>> from sympy.geometry.point import Point
>>> from sympy.geometry.polygon import Polygon
>>> triangle = Polygon(Point(0, 3), Point(5, 3), Point(1, 1))
>>> facets = triangle.sides
>>> a, b = hyperplane_parameters(triangle)[0]
>>> integration_reduction(facets, 0, a, b, 1, (x, y), 0)
5 | Helper method for main_integrate. Returns the value of the input
expression evaluated over the polytope facet referenced by a given index. | [
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"""Helper method for main_integrate. Returns the value of the input
expression evaluated over the polytope facet referenced by a given index.
Parameters
===========
facets :
List of facets of the polytope.
index :
Index referencing the facet to integrate the expression over.
a :
Hyperplane parameter denoting direction.
b :
Hyperplane parameter denoting distance.
expr :
The expression to integrate over the facet.
dims :
List of symbols denoting axes.
degree :
Degree of the homogeneous polynomial.
Examples
========
>>> from sympy.abc import x, y
>>> from sympy.integrals.intpoly import integration_reduction,\
hyperplane_parameters
>>> from sympy.geometry.point import Point
>>> from sympy.geometry.polygon import Polygon
>>> triangle = Polygon(Point(0, 3), Point(5, 3), Point(1, 1))
>>> facets = triangle.sides
>>> a, b = hyperplane_parameters(triangle)[0]
>>> integration_reduction(facets, 0, a, b, 1, (x, y), 0)
5
"""
expr = _sympify(expr)
if expr.is_zero:
return expr
value = S.Zero
x0 = facets[index].points[0]
m = len(facets)
gens = (x, y)
inner_product = diff(expr, gens[0]) * x0[0] + diff(expr, gens[1]) * x0[1]
if inner_product != 0:
value += integration_reduction(facets, index, a, b,
inner_product, dims, degree - 1)
value += left_integral2D(m, index, facets, x0, expr, gens)
return value/(len(dims) + degree - 1) | [
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|
fabioz/PyDev.Debugger | 0f8c02a010fe5690405da1dd30ed72326191ce63 | pydevd_attach_to_process/winappdbg/thread.py | python | Thread.kill | (self, dwExitCode = 0) | Terminates the thread execution.
@note: If the C{lpInjectedMemory} member contains a valid pointer,
the memory is freed.
@type dwExitCode: int
@param dwExitCode: (Optional) Thread exit code. | Terminates the thread execution. | [
"Terminates",
"the",
"thread",
"execution",
"."
] | def kill(self, dwExitCode = 0):
"""
Terminates the thread execution.
@note: If the C{lpInjectedMemory} member contains a valid pointer,
the memory is freed.
@type dwExitCode: int
@param dwExitCode: (Optional) Thread exit code.
"""
hThread = self.get_handle(win32.THREAD_TERMINATE)
win32.TerminateThread(hThread, dwExitCode)
# Ugliest hack ever, won't work if many pieces of code are injected.
# Seriously, what was I thinking? :(
if self.pInjectedMemory is not None:
try:
self.get_process().free(self.pInjectedMemory)
self.pInjectedMemory = None
except Exception:
## raise # XXX DEBUG
pass | [
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||
replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | dist/lib/python2.7/multiprocessing/util.py | python | log_to_stderr | (level=None) | return _logger | Turn on logging and add a handler which prints to stderr | Turn on logging and add a handler which prints to stderr | [
"Turn",
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"and",
"add",
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"handler",
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] | def log_to_stderr(level=None):
'''
Turn on logging and add a handler which prints to stderr
'''
global _log_to_stderr
import logging
logger = get_logger()
formatter = logging.Formatter(DEFAULT_LOGGING_FORMAT)
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
if level:
logger.setLevel(level)
_log_to_stderr = True
return _logger | [
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|
pantsbuild/pants | 2e126e78ffc40cb108408316b90e8beebee1df9e | src/python/pants/base/exception_sink.py | python | SignalHandler.signal_handler_mapping | (self) | return {
signal.SIGINT: self._handle_sigint_if_enabled,
signal.SIGQUIT: self.handle_sigquit,
signal.SIGTERM: self.handle_sigterm,
} | A dict mapping (signal number) -> (a method handling the signal). | A dict mapping (signal number) -> (a method handling the signal). | [
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] | def signal_handler_mapping(self) -> Dict[signal.Signals, Callable]:
"""A dict mapping (signal number) -> (a method handling the signal)."""
# Could use an enum here, but we never end up doing any matching on the specific signal value,
# instead just iterating over the registered signals to set handlers, so a dict is probably
# better.
return {
signal.SIGINT: self._handle_sigint_if_enabled,
signal.SIGQUIT: self.handle_sigquit,
signal.SIGTERM: self.handle_sigterm,
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|
delira-dev/delira | cd3ad277d6fad5f837d6c5147e6eee2ada648596 | delira/training/backends/sklearn/trainer.py | python | SklearnEstimatorTrainer._update_state | (self, new_state) | return super()._update_state(new_state) | Update the state from a given new state
Parameters
----------
new_state : dict
new state to update internal state from
Returns
-------
:class:`SkLearnEstimatorTrainer`
the trainer with a modified state | Update the state from a given new state | [
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] | def _update_state(self, new_state):
"""
Update the state from a given new state
Parameters
----------
new_state : dict
new state to update internal state from
Returns
-------
:class:`SkLearnEstimatorTrainer`
the trainer with a modified state
"""
if "model" in new_state:
self.module = new_state.pop("model")
if "epoch" in new_state:
self.start_epoch = new_state.pop("epoch")
return super()._update_state(new_state) | [
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trakt/Plex-Trakt-Scrobbler | aeb0bfbe62fad4b06c164f1b95581da7f35dce0b | Trakttv.bundle/Contents/Libraries/Linux/aarch64/ucs2/cryptography/hazmat/backends/openssl/encode_asn1.py | python | _encode_sk_name_entry | (backend, attributes) | return stack | The sk_X50_NAME_ENTRY created will not be gc'd. | The sk_X50_NAME_ENTRY created will not be gc'd. | [
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] | def _encode_sk_name_entry(backend, attributes):
"""
The sk_X50_NAME_ENTRY created will not be gc'd.
"""
stack = backend._lib.sk_X509_NAME_ENTRY_new_null()
for attribute in attributes:
name_entry = _encode_name_entry(backend, attribute)
res = backend._lib.sk_X509_NAME_ENTRY_push(stack, name_entry)
backend.openssl_assert(res == 1)
return stack | [
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|
IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/Scripts/generate_reflected_calls.py | python | get_type_names | (i) | return ['T' + str(x) for x in range(i)] | [] | def get_type_names(i):
if i == 1: return ['T0']
return ['T' + str(x) for x in range(i)] | [
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|||
andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/plugins/attack/db/sqlmap/thirdparty/bottle/bottle.py | python | BaseRequest.__repr__ | (self) | return '<%s: %s %s>' % (self.__class__.__name__, self.method, self.url) | [] | def __repr__(self):
return '<%s: %s %s>' % (self.__class__.__name__, self.method, self.url) | [
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|||
GalSim-developers/GalSim | a05d4ec3b8d8574f99d3b0606ad882cbba53f345 | galsim/config/value_random.py | python | _GenerateFromRandomPoisson | (config, base, value_type) | return val, False | Return a random value drawn from a Poisson distribution | Return a random value drawn from a Poisson distribution | [
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"value",
"drawn",
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"Poisson",
"distribution"
] | def _GenerateFromRandomPoisson(config, base, value_type):
"""Return a random value drawn from a Poisson distribution
"""
rng = GetRNG(config, base)
req = { 'mean' : float }
kwargs, safe = GetAllParams(config, base, req=req)
mean = kwargs['mean']
dev = PoissonDeviate(rng,mean=mean)
val = dev()
#print(base['obj_num'],'RandomPoisson: ',val)
return val, False | [
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|
jmg/crawley | 3953dcaac6d0828a03b353c6eced34acd7220c77 | crawley/manager/utils.py | python | generate_template | (tm_name, project_name, output_dir, new_extension=None) | Generates a project's file from a template | Generates a project's file from a template | [
"Generates",
"a",
"project",
"s",
"file",
"from",
"a",
"template"
] | def generate_template(tm_name, project_name, output_dir, new_extension=None):
"""
Generates a project's file from a template
"""
tm_name, ext = os.path.splitext(tm_name)
if not ext:
ext = ".tm"
if new_extension is None:
new_extension = '.py'
with open(os.path.join(TEMPLATES_DIR, "%s%s" % (tm_name, ext)), 'r') as f:
template = f.read()
data = template % { 'project_name' : project_name }
with open(os.path.join(output_dir, "%s%s" % (tm_name, new_extension)), 'w') as f:
f.write(data) | [
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||
misterch0c/shadowbroker | e3a069bea47a2c1009697941ac214adc6f90aa8d | windows/Resources/Python/Core/Lib/decimal.py | python | Decimal.from_float | (cls, f) | Converts a float to a decimal number, exactly.
Note that Decimal.from_float(0.1) is not the same as Decimal('0.1').
Since 0.1 is not exactly representable in binary floating point, the
value is stored as the nearest representable value which is
0x1.999999999999ap-4. The exact equivalent of the value in decimal
is 0.1000000000000000055511151231257827021181583404541015625.
>>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal.from_float(float('nan'))
Decimal('NaN')
>>> Decimal.from_float(float('inf'))
Decimal('Infinity')
>>> Decimal.from_float(-float('inf'))
Decimal('-Infinity')
>>> Decimal.from_float(-0.0)
Decimal('-0') | Converts a float to a decimal number, exactly.
Note that Decimal.from_float(0.1) is not the same as Decimal('0.1').
Since 0.1 is not exactly representable in binary floating point, the
value is stored as the nearest representable value which is
0x1.999999999999ap-4. The exact equivalent of the value in decimal
is 0.1000000000000000055511151231257827021181583404541015625.
>>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal.from_float(float('nan'))
Decimal('NaN')
>>> Decimal.from_float(float('inf'))
Decimal('Infinity')
>>> Decimal.from_float(-float('inf'))
Decimal('-Infinity')
>>> Decimal.from_float(-0.0)
Decimal('-0') | [
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] | def from_float(cls, f):
"""Converts a float to a decimal number, exactly.
Note that Decimal.from_float(0.1) is not the same as Decimal('0.1').
Since 0.1 is not exactly representable in binary floating point, the
value is stored as the nearest representable value which is
0x1.999999999999ap-4. The exact equivalent of the value in decimal
is 0.1000000000000000055511151231257827021181583404541015625.
>>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal.from_float(float('nan'))
Decimal('NaN')
>>> Decimal.from_float(float('inf'))
Decimal('Infinity')
>>> Decimal.from_float(-float('inf'))
Decimal('-Infinity')
>>> Decimal.from_float(-0.0)
Decimal('-0')
"""
if isinstance(f, (int, long)):
return cls(f)
else:
if _math.isinf(f) or _math.isnan(f):
return cls(repr(f))
if _math.copysign(1.0, f) == 1.0:
sign = 0
else:
sign = 1
n, d = abs(f).as_integer_ratio()
k = d.bit_length() - 1
result = _dec_from_triple(sign, str(n * 5 ** k), -k)
if cls is Decimal:
return result
return cls(result) | [
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semirook/snaql | 9e3987e19e677725f8d4882cb15882be6366db09 | snaql/factory.py | python | JinjaSQLExtension.parse | (self, parser) | return nodes.CallBlock(call_node, [], [], body) | [] | def parse(self, parser):
lineno = next(parser.stream).lineno
expr = parser.parse_expression()
args = [expr]
kwargs = [nodes.Keyword('func', expr)]
if parser.stream.skip_if('comma'):
# Optional 'note' for function docstring
if (
parser.stream.current.type == 'name' and
parser.stream.current.value in (
'note', 'cond_for', 'depends_on'
)
):
stream_type = parser.stream.current.value
next(parser.stream)
parser.stream.expect('assign')
# Depends meta is always a list
if stream_type == 'depends_on':
c_expr = parser.parse_list()
else:
c_expr = parser.parse_expression()
args.append(c_expr)
kwargs.append(nodes.Keyword(stream_type, c_expr))
body = parser.parse_statements(
['name:endsql', 'name:endquery'], drop_needle=True
)
raw_template = self.environment.sql_params['raws'][parser.name]
# Lines range of original raw template
raw_lines = slice(lineno, parser.stream.current.lineno-1)
self.environment.sql_params.setdefault('funcs', {}).update({
expr.value: {'raw_sql': '\n '.join(raw_template[raw_lines])}
})
call_node = nodes.Call(
self.attr('_sql_process', lineno=lineno),
args, kwargs, None, None
)
return nodes.CallBlock(call_node, [], [], body) | [
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|||
bshao001/ChatLearner | 4b7d8a617bb0cc5c2a792a3e87d7be7bf6364b43 | webui/server/tornadows/soaphandler.py | python | SoapHandler._parseParams | (self,elements,types=None,args=None) | return values | Private method to parse a Body element of SOAP Envelope and extract
the values of the request document like parameters for the soapmethod,
this method return a list values of parameters. | Private method to parse a Body element of SOAP Envelope and extract
the values of the request document like parameters for the soapmethod,
this method return a list values of parameters. | [
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""" Private method to parse a Body element of SOAP Envelope and extract
the values of the request document like parameters for the soapmethod,
this method return a list values of parameters.
"""
values = []
for tagname in args:
type = types[tagname]
values += self._findValues(tagname,type,elements)
return values | [
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|
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/algebras/lie_algebras/onsager.py | python | OnsagerAlgebraACE._repr_generator | (self, m) | return 'B[{}]'.format(m[1]) | Return a string representation of the generator indexed by ``m``.
EXAMPLES::
sage: O = lie_algebras.OnsagerAlgebra(QQ).alternating_central_extension()
sage: O._repr_generator((0,-2))
'A[-2]'
sage: O._repr_generator((1,4))
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"Return",
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"""
Return a string representation of the generator indexed by ``m``.
EXAMPLES::
sage: O = lie_algebras.OnsagerAlgebra(QQ).alternating_central_extension()
sage: O._repr_generator((0,-2))
'A[-2]'
sage: O._repr_generator((1,4))
'B[4]'
"""
if m[0] == 0:
return 'A[{}]'.format(m[1])
return 'B[{}]'.format(m[1]) | [
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|
liyibo/text-classification-demos | 2bc3f56e0eb2b028565881c91db26a589b050db8 | cnn_model.py | python | main | () | [] | def main():
word_to_id, id_to_word = word_2_id(vocab_dir)
cat_to_id, id_to_cat = cat_2_id()
x_train, y_train = process_file(train_dir, word_to_id, cat_to_id, max_length)
x_val, y_val = process_file(val_dir, word_to_id, cat_to_id, max_length)
epochs = 5
best_acc_val = 0.0 # 最佳验证集准确率
train_steps = 0
val_loss = 0.0
val_acc = 0.0
with tf.Graph().as_default():
seq_length = 512
num_classes = 10
vocab_size = 5000
cnn_model = TextCNN(seq_length, num_classes, vocab_size)
saver = tf.train.Saver()
sess = tf.Session()
with sess.as_default():
sess.run(tf.global_variables_initializer())
for epoch in range(epochs):
print('Epoch:', epoch + 1)
batch_train = batch_iter(x_train, y_train, 32)
for x_batch, y_batch in batch_train:
train_steps += 1
learn_rate = 0.001
# learning rate vary
feed_dict = {cnn_model.input_x: x_batch, cnn_model.input_y: y_batch,
cnn_model.drop_prob: 0.5, cnn_model.learning_rate: learn_rate}
_, train_loss, train_acc = sess.run([cnn_model.optim, cnn_model.loss,
cnn_model.acc], feed_dict=feed_dict)
if train_steps % 1000 == 0:
val_loss, val_acc = evaluate(sess, cnn_model, x_val, y_val)
if val_acc > best_acc_val:
# 保存最好结果
best_acc_val = val_acc
last_improved = train_steps
saver.save(sess, "./model/cnn/model", global_step=train_steps)
# saver.save(sess=session, save_path=save_path)
improved_str = '*'
else:
improved_str = ''
now_time = datetime.now()
msg = 'Iter: {0:>6}, Train Loss: {1:>6.2}, Train Acc: {2:>7.2%},' \
+ ' Val Loss: {3:>6.2}, Val Acc: {4:>7.2%}, Time: {5} {6}'
print(msg.format(train_steps, train_loss, train_acc, val_loss, val_acc, now_time, improved_str)) | [
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||||
almarklein/visvis | 766ed97767b44a55a6ff72c742d7385e074d3d55 | core/axes.py | python | Legend.SetStrings | (self, *stringList) | SetStrings(*stringList)
Set the strings of the legend labels. | SetStrings(*stringList)
Set the strings of the legend labels. | [
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] | def SetStrings(self, *stringList):
""" SetStrings(*stringList)
Set the strings of the legend labels.
"""
# Note that setting the .visible property will invoke a draw
# test
if len(stringList)==1 and isinstance(stringList[0],(tuple,list)):
stringList = stringList[0]
for value in stringList:
if not isinstance(value, basestring):
raise ValueError("Legend string list should only contain strings.")
# store
self._stringList = stringList
# clean up labels and lines
for line in [line for line in self._wobjects]:
line.Destroy()
for label in self.children:
label.Destroy()
# find axes and figure
axes = self.parent
while axes and not isinstance(axes, Axes):
axes = axes.parent
if not axes:
return
fig = axes.GetFigure()
# collect line objects
lines = []
twoPoints = False
for ob in axes._wobjects:
if len(self._wobjects) >= len(stringList):
break
if isinstance(ob, Line):
# Add line props
tmp = ob.ls, ob.lc, ob.lw, ob.ms, ob.mc, ob.mw, ob.mec, ob.mew
lines.append(tmp)
# Set whether to use two points
twoPoints = twoPoints or bool(ob.ls and ob.lc and ob.lw)
# create new lines and labels
maxWidth = 0
nr = -1
for lineProps in lines:
nr += 1
if nr >= len(stringList):
break
# get new line and label
text = stringList[nr]
yspacing = self._yspacing * fig._relativeFontSize
line, label = self._AddLineAndLabel(text, yspacing, twoPoints)
# apply line properties
line.ls, line.lc, line.lw = lineProps[0:3]
line.ms, line.mc, line.mw = lineProps[3:6]
line.mec, line.mew = lineProps[6:8]
# correct label size and store max
deltax, deltay = label.GetVertexLimits()
label.position.w = (deltax[1]-deltax[0])+2
maxWidth = max([maxWidth, label.position.w ])
# make own size ok
if self._wobjects:
pos = label.position
self.position.w = maxWidth + pos.x + self._xoffset
#self.position.h = pos.bottom + self._yoffset
deltax, deltay = label.GetVertexLimits()
labelHeight = deltay[1]# - deltay[0]
self.position.h = pos.top + labelHeight + self._yoffset + 2
self.visible = True
else:
self.visible = False | [
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||
istresearch/scrapy-cluster | 01861c2dca1563aab740417d315cc4ebf9b73f72 | utils/scutils/zookeeper_watcher.py | python | ZookeeperWatcher.watch_file | (self, event) | Fired when changes made to the file | Fired when changes made to the file | [
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"to",
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] | def watch_file(self, event):
'''
Fired when changes made to the file
'''
if not self.update_file(self.my_file):
self.threaded_start() | [
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||
jerryli27/TwinGAN | 4e5593445778dfb77af9f815b3f4fcafc35758dc | datasets/dataset_factory.py | python | get_dataset | (name, split_name, dataset_dir, file_pattern=None, reader=None) | return dataset | Given a dataset name and a split_name returns a Dataset.
Args:
name: String, the name of the dataset.
split_name: A train/test split name.
dataset_dir: The directory where the dataset files are stored.
file_pattern: The file pattern to use for matching the dataset source files.
reader: The subclass of tf.ReaderBase. If left as `None`, then the default
reader defined by each dataset is used.
Returns:
A `Dataset` class.
Raises:
ValueError: If the dataset `name` is unknown. | Given a dataset name and a split_name returns a Dataset. | [
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"""Given a dataset name and a split_name returns a Dataset.
Args:
name: String, the name of the dataset.
split_name: A train/test split name.
dataset_dir: The directory where the dataset files are stored.
file_pattern: The file pattern to use for matching the dataset source files.
reader: The subclass of tf.ReaderBase. If left as `None`, then the default
reader defined by each dataset is used.
Returns:
A `Dataset` class.
Raises:
ValueError: If the dataset `name` is unknown.
"""
if name not in datasets_map:
raise ValueError('Name of dataset unknown %s' % name)
dataset = datasets_map[name].get_split(
split_name,
dataset_dir,
file_pattern,
reader)
dataset.name = name
if FLAGS.train_size and split_name == 'train':
dataset.num_samples = FLAGS.train_size
else:
if FLAGS.validation_size:
dataset.num_samples = FLAGS.validation_size
return dataset | [
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|
googleapis/python-dialogflow | e48ea001b7c8a4a5c1fe4b162bad49ea397458e9 | google/cloud/dialogflow_v2/services/documents/transports/grpc_asyncio.py | python | DocumentsGrpcAsyncIOTransport.operations_client | (self) | return self._operations_client | Create the client designed to process long-running operations.
This property caches on the instance; repeated calls return the same
client. | Create the client designed to process long-running operations. | [
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"""Create the client designed to process long-running operations.
This property caches on the instance; repeated calls return the same
client.
"""
# Sanity check: Only create a new client if we do not already have one.
if self._operations_client is None:
self._operations_client = operations_v1.OperationsAsyncClient(
self.grpc_channel
)
# Return the client from cache.
return self._operations_client | [
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|
pytorchbearer/torchbearer | 9d97c60ec4deb37a0627311ddecb9c6f1429cd82 | torchbearer/callbacks/printer.py | python | Tqdm.on_end_validation | (self, state) | Update the bar with the terminal validation metrics and then close.
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state (dict): The :class:`.Trial` state | Update the bar with the terminal validation metrics and then close. | [
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"""Update the bar with the terminal validation metrics and then close.
Args:
state (dict): The :class:`.Trial` state
"""
if not self._on_epoch:
self._close(state) | [
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||
clcarwin/sphereface_pytorch | e2f11f0b0f394cf75b9f65ce8d353e4390b0948c | matlab_cp2tform.py | python | findSimilarity | (uv, xy, options=None) | Function:
----------
Find Reflective Similarity Transform Matrix 'trans':
u = uv[:, 0]
v = uv[:, 1]
x = xy[:, 0]
y = xy[:, 1]
[x, y, 1] = [u, v, 1] * trans
Parameters:
----------
@uv: Kx2 np.array
source points each row is a pair of coordinates (x, y)
@xy: Kx2 np.array
each row is a pair of inverse-transformed
@option: not used, keep it as None
Returns:
----------
@trans: 3x3 np.array
transform matrix from uv to xy
@trans_inv: 3x3 np.array
inverse of trans, transform matrix from xy to uv
Matlab:
----------
% The similarities are a superset of the nonreflective similarities as they may
% also include reflection.
%
% let sc = s*cos(theta)
% let ss = s*sin(theta)
%
% [ sc -ss
% [u v] = [x y 1] * ss sc
% tx ty]
%
% OR
%
% [ sc ss
% [u v] = [x y 1] * ss -sc
% tx ty]
%
% Algorithm:
% 1) Solve for trans1, a nonreflective similarity.
% 2) Reflect the xy data across the Y-axis,
% and solve for trans2r, also a nonreflective similarity.
% 3) Transform trans2r to trans2, undoing the reflection done in step 2.
% 4) Use TFORMFWD to transform uv using both trans1 and trans2,
% and compare the results, Returnsing the transformation corresponding
% to the smaller L2 norm.
% Need to reset options.K to prepare for calls to findNonreflectiveSimilarity.
% This is safe because we already checked that there are enough point pairs. | Function:
----------
Find Reflective Similarity Transform Matrix 'trans':
u = uv[:, 0]
v = uv[:, 1]
x = xy[:, 0]
y = xy[:, 1]
[x, y, 1] = [u, v, 1] * trans | [
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"""
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u = uv[:, 0]
v = uv[:, 1]
x = xy[:, 0]
y = xy[:, 1]
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----------
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transform matrix from uv to xy
@trans_inv: 3x3 np.array
inverse of trans, transform matrix from xy to uv
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% The similarities are a superset of the nonreflective similarities as they may
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%
% let sc = s*cos(theta)
% let ss = s*sin(theta)
%
% [ sc -ss
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% tx ty]
%
% Algorithm:
% 1) Solve for trans1, a nonreflective similarity.
% 2) Reflect the xy data across the Y-axis,
% and solve for trans2r, also a nonreflective similarity.
% 3) Transform trans2r to trans2, undoing the reflection done in step 2.
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% and compare the results, Returnsing the transformation corresponding
% to the smaller L2 norm.
% Need to reset options.K to prepare for calls to findNonreflectiveSimilarity.
% This is safe because we already checked that there are enough point pairs.
"""
options = {'K': 2}
# uv = np.array(uv)
# xy = np.array(xy)
# Solve for trans1
trans1, trans1_inv = findNonreflectiveSimilarity(uv, xy, options)
# Solve for trans2
# manually reflect the xy data across the Y-axis
xyR = xy
xyR[:, 0] = -1 * xyR[:, 0]
trans2r, trans2r_inv = findNonreflectiveSimilarity(uv, xyR, options)
# manually reflect the tform to undo the reflection done on xyR
TreflectY = np.array([
[-1, 0, 0],
[0, 1, 0],
[0, 0, 1]
])
trans2 = np.dot(trans2r, TreflectY)
# Figure out if trans1 or trans2 is better
xy1 = tformfwd(trans1, uv)
norm1 = norm(xy1 - xy)
xy2 = tformfwd(trans2, uv)
norm2 = norm(xy2 - xy)
if norm1 <= norm2:
return trans1, trans1_inv
else:
trans2_inv = inv(trans2)
return trans2, trans2_inv | [
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||
nortikin/sverchok | 7b460f01317c15f2681bfa3e337c5e7346f3711b | menu.py | python | SverchNodeItem.make_add_operator | (self) | Create operator class which adds specific type of node.
Tooltip (docstring) for that operator is copied from
node class docstring. | Create operator class which adds specific type of node.
Tooltip (docstring) for that operator is copied from
node class docstring. | [
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"""
Create operator class which adds specific type of node.
Tooltip (docstring) for that operator is copied from
node class docstring.
"""
global node_add_operators
class SverchNodeAddOperator(bl_operators.node.NodeAddOperator, bpy.types.Operator):
"""Wrapper for node.add_node operator to add specific node"""
bl_idname = "node.sv_add_" + self.get_idname()
bl_label = "Add {} node".format(self.label)
bl_options = {'REGISTER', 'UNDO'}
def execute(operator, context):
# please not be confused: "operator" here references to
# SverchNodeAddOperator instance, and "self" references to
# SverchNodeItem instance.
operator.use_transform = True
operator.type = self.nodetype
node = operator.create_node(context)
apply_default_preset(node)
return {'FINISHED'}
node_class = self.get_node_class()
SverchNodeAddOperator.__name__ = node_class.__name__
if hasattr(node_class, "docstring"):
SverchNodeAddOperator.__doc__ = node_class.docstring.get_tooltip()
else:
SverchNodeAddOperator.__doc__ = node_class.__doc__
node_add_operators[self.get_idname()] = SverchNodeAddOperator
bpy.utils.register_class(SverchNodeAddOperator) | [
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