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baidu/CUP | 79ab2f3ad6eaab1461aa3b4cca37d3262240194a | cup/storage/obj.py | python | ObjectInterface.put | (self, dest, localfile) | :param dest:
system path
:param localfile:
localfile
:return:
{
'returncode': 0 for success, others for failure,
'msg': 'if any'
} | :param dest:
system path
:param localfile:
localfile | [
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"""
:param dest:
system path
:param localfile:
localfile
:return:
{
'returncode': 0 for success, others for failure,
'msg': 'if any'
}
""" | [
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||
openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | lms/djangoapps/instructor_task/subtasks.py | python | SubtaskStatus.__repr__ | (self) | return f'SubtaskStatus<{self.to_dict()!r}>' | Return print representation of a SubtaskStatus object. | Return print representation of a SubtaskStatus object. | [
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"""Return print representation of a SubtaskStatus object."""
return f'SubtaskStatus<{self.to_dict()!r}>' | [
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|
enthought/traitsui | b7c38c7a47bf6ae7971f9ddab70c8a358647dd25 | traitsui/qt4/button_editor.py | python | SimpleEditor.dispose | (self) | Disposes of the contents of an editor. | Disposes of the contents of an editor. | [
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"""Disposes of the contents of an editor."""
if self.factory.values_trait:
self.object.observe(
self._update_menu,
self.factory.values_trait + ".items",
remove=True,
)
if self.control is not None:
self.control.clicked.disconnect(self.update_object)
super().dispose() | [
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||
SigmaHQ/sigma | 6f7d28b52a6468b2430e8d7dfefb79dc01e2f1af | tools/sigma/backends/humio.py | python | HumioBackend.generateANDNode | (self, node) | [] | def generateANDNode(self, node):
generated = [self.generateNode(val) for val in node]
filtered = [g for g in generated if g is not None]
if filtered:
if self.sort_condition_lists:
filtered = sorted(filtered)
if any([item for item in filtered if "regex" in item]):
res = ""
for item in filtered:
if item.startswith("regex"):
if res.endswith(" | "):
res = res.rstrip(" | ")
res += " | %s | " % item.strip(" | ")
else:
res += item
return res.strip(" | ")
return self.andToken.join(filtered)
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return None | [
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||||
pycket/pycket | 05ebd9885efa3a0ae54e77c1a1f07ea441b445c6 | pycket/small_list.py | python | inline_small_list | (sizemax=11, sizemin=0, immutable=False, unbox_num=False, nonull=False,
attrname="list", factoryname="make", listgettername="_get_full_list",
listsizename="_get_size_list", gettername="_get_list",
settername="_set_list") | return wrapper | This function is helpful if you have a class with a field storing a
list and the list is often very small. Calling this function will inline
the list into instances for the small sizes. This works by adding the
following methods (names customizable) to the class:
_get_list(self, i): return ith element of the list
_set_list(self, i, val): set ith element of the list
_get_full_list(self): returns a copy of the full list
_get_size_list(self): returns the length of the list
@staticmethod
make(listcontent, *args): makes a new instance with the list's content set to listcontent | This function is helpful if you have a class with a field storing a
list and the list is often very small. Calling this function will inline
the list into instances for the small sizes. This works by adding the
following methods (names customizable) to the class: | [
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attrname="list", factoryname="make", listgettername="_get_full_list",
listsizename="_get_size_list", gettername="_get_list",
settername="_set_list"):
"""
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list and the list is often very small. Calling this function will inline
the list into instances for the small sizes. This works by adding the
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_get_list(self, i): return ith element of the list
_set_list(self, i, val): set ith element of the list
_get_full_list(self): returns a copy of the full list
_get_size_list(self): returns the length of the list
@staticmethod
make(listcontent, *args): makes a new instance with the list's content set to listcontent
"""
if not config.type_size_specialization:
sizemin = sizemax = 0
unbox_num = False
def wrapper(cls):
_immutable_ = getattr(cls, "_immutable_", False)
def make_class(size):
attrs = ["_%s_%s" % (attrname, i) for i in range(size)]
unrolling_enumerate_attrs = unrolling_iterable(enumerate(attrs))
def _get_size_list(self):
return size
def _get_list(self, i):
for j, attr in unrolling_enumerate_attrs:
if j == i:
result = getattr(self, attr)
if nonull:
debug.check_annotation(result, _not_null)
return result
raise IndexError
def _get_full_list(self):
res = [None] * size
for i, attr in unrolling_enumerate_attrs:
elem = getattr(self, attr)
if nonull:
debug.check_annotation(elem, _not_null)
res[i] = getattr(self, attr)
return res
def _set_list(self, i, val):
if nonull:
assert val is not None
for j, attr in unrolling_enumerate_attrs:
if j == i:
setattr(self, attr, val)
return
raise IndexError
def _init(self, elems, *args):
assert len(elems) == size
for i, attr in unrolling_enumerate_attrs:
val = elems[i]
if nonull:
assert val is not None
setattr(self, attr, elems[i])
cls.__init__(self, *args)
# Methods for the new class being built
methods = {
gettername : _get_list,
listsizename : _get_size_list,
listgettername : _get_full_list,
settername : _set_list,
"__init__" : _init,
}
newcls = type(cls)("%sSize%s" % (cls.__name__, size), (cls, ), methods)
if _immutable_:
setattr(newcls, "_immutable_", True)
newcls = add_clone_method(newcls)
if immutable:
setattr(newcls, "_immutable_fields_", attrs)
newcls = add_clone_method(newcls)
if "_attrs_" in cls.__dict__:
setattr(newcls, "_attrs_", attrs)
return newcls
classes = map(make_class, range(sizemin, sizemax))
# Build the arbitrary sized variant
def _get_arbitrary(self, i):
return getattr(self, attrname)[i]
def _get_size_list_arbitrary(self):
return len(getattr(self, attrname))
def _get_list_arbitrary(self):
return getattr(self, attrname)
def _set_arbitrary(self, i, val):
if nonull:
assert val is not None
getattr(self, attrname)[i] = val
def _init(self, elems, *args):
debug.make_sure_not_resized(elems)
setattr(self, attrname, elems)
cls.__init__(self, *args)
methods = {
gettername : _get_arbitrary,
listsizename : _get_size_list_arbitrary,
listgettername : _get_list_arbitrary,
settername : _set_arbitrary,
"__init__" : _init,
}
cls_arbitrary = type(cls)("%sArbitrary" % cls.__name__, (cls, ), methods)
if _immutable_:
setattr(cls_arbitrary, "_immutable_", True)
cls_arbitrary = add_clone_method(cls_arbitrary)
if immutable:
setattr(cls_arbitrary, "_immutable_fields_", ["%s[*]" % (attrname,)])
cls_arbitrary = add_clone_method(cls_arbitrary)
if "_attrs_" in cls.__dict__:
setattr(cls_arbitrary, "_attrs_", attrname)
def make(elems, *args):
if classes:
if (elems is None or len(elems) == 0):
return make0(*args)
else:
if elems is None:
elems = []
if sizemin <= len(elems) < sizemax:
cls = classes[len(elems) - sizemin]
else:
cls = cls_arbitrary
return cls(elems, *args)
# XXX those could be done more nicely
def make0(*args):
if not classes: # no type specialization
return make([], *args)
result = objectmodel.instantiate(classes[0])
cls.__init__(result, *args)
return result
def make1(elem, *args):
if not classes: # no type specialization
return make([elem], *args)
result = objectmodel.instantiate(classes[1])
result._set_list(0, elem)
cls.__init__(result, *args)
return result
def make2(elem1, elem2, *args):
if not classes: # no type specialization
return make([elem1, elem2], *args)
result = objectmodel.instantiate(classes[2])
result._set_list(0, elem1)
result._set_list(1, elem2)
cls.__init__(result, *args)
return result
def make_n(size, *args):
if sizemin <= size < sizemax:
subcls = classes[size - sizemin]
else:
subcls = cls_arbitrary
result = objectmodel.instantiate(subcls)
if subcls is cls_arbitrary:
assert isinstance(result, subcls)
setattr(result, attrname, [None] * size)
cls.__init__(result, *args)
return result
if unbox_num:
assert _immutable_ or immutable, "unboxing is only supported for immutable objects"
make, make1, make2 = _add_num_classes(cls, make, make0, make1, make2, immut=_immutable_)
setattr(cls, factoryname, staticmethod(make))
setattr(cls, factoryname + "0", staticmethod(make0))
setattr(cls, factoryname + "1", staticmethod(make1))
setattr(cls, factoryname + "2", staticmethod(make2))
setattr(cls, factoryname + "_n", staticmethod(make_n))
return cls
return wrapper | [
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|
hzlzh/AlfredWorkflow.com | 7055f14f6922c80ea5943839eb0caff11ae57255 | Sources/Workflows/快递速查/requests/sessions.py | python | Session.request | (self, method, url,
params=None,
data=None,
headers=None,
cookies=None,
files=None,
auth=None,
timeout=None,
allow_redirects=True,
proxies=None,
hooks=None,
stream=None,
verify=None,
cert=None) | return resp | Constructs a :class:`Request <Request>`, prepares it and sends it.
Returns :class:`Response <Response>` object.
:param method: method for the new :class:`Request` object.
:param url: URL for the new :class:`Request` object.
:param params: (optional) Dictionary or bytes to be sent in the query
string for the :class:`Request`.
:param data: (optional) Dictionary or bytes to send in the body of the
:class:`Request`.
:param headers: (optional) Dictionary of HTTP Headers to send with the
:class:`Request`.
:param cookies: (optional) Dict or CookieJar object to send with the
:class:`Request`.
:param files: (optional) Dictionary of 'filename': file-like-objects
for multipart encoding upload.
:param auth: (optional) Auth tuple or callable to enable
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:param timeout: (optional) Float describing the timeout of the
request.
:param allow_redirects: (optional) Boolean. Set to True by default.
:param proxies: (optional) Dictionary mapping protocol to the URL of
the proxy.
:param stream: (optional) whether to immediately download the response
content. Defaults to ``False``.
:param verify: (optional) if ``True``, the SSL cert will be verified.
A CA_BUNDLE path can also be provided.
:param cert: (optional) if String, path to ssl client cert file (.pem).
If Tuple, ('cert', 'key') pair. | Constructs a :class:`Request <Request>`, prepares it and sends it.
Returns :class:`Response <Response>` object. | [
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allow_redirects=True,
proxies=None,
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"""
cookies = cookies or {}
proxies = proxies or {}
# Bootstrap CookieJar.
if not isinstance(cookies, cookielib.CookieJar):
cookies = cookiejar_from_dict(cookies)
# Merge with session cookies
merged_cookies = self.cookies.copy()
merged_cookies.update(cookies)
cookies = merged_cookies
# Gather clues from the surrounding environment.
if self.trust_env:
# Set environment's proxies.
env_proxies = get_environ_proxies(url) or {}
for (k, v) in env_proxies.items():
proxies.setdefault(k, v)
# Set environment's basic authentication.
if not auth:
auth = get_netrc_auth(url)
# Look for configuration.
if not verify and verify is not False:
verify = os.environ.get('REQUESTS_CA_BUNDLE')
# Curl compatibility.
if not verify and verify is not False:
verify = os.environ.get('CURL_CA_BUNDLE')
# Merge all the kwargs.
params = merge_kwargs(params, self.params)
headers = merge_kwargs(headers, self.headers)
auth = merge_kwargs(auth, self.auth)
proxies = merge_kwargs(proxies, self.proxies)
hooks = merge_kwargs(hooks, self.hooks)
stream = merge_kwargs(stream, self.stream)
verify = merge_kwargs(verify, self.verify)
cert = merge_kwargs(cert, self.cert)
# Create the Request.
req = Request()
req.method = method.upper()
req.url = url
req.headers = headers
req.files = files
req.data = data
req.params = params
req.auth = auth
req.cookies = cookies
req.hooks = hooks
# Prepare the Request.
prep = req.prepare()
# Send the request.
send_kwargs = {
'stream': stream,
'timeout': timeout,
'verify': verify,
'cert': cert,
'proxies': proxies,
'allow_redirects': allow_redirects,
}
resp = self.send(prep, **send_kwargs)
return resp | [
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|
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/bin/x86/Debug/Lib/pprint.py | python | pprint | (object, stream=None, indent=1, width=80, depth=None) | Pretty-print a Python object to a stream [default is sys.stdout]. | Pretty-print a Python object to a stream [default is sys.stdout]. | [
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"""Pretty-print a Python object to a stream [default is sys.stdout]."""
printer = PrettyPrinter(
stream=stream, indent=indent, width=width, depth=depth)
printer.pprint(object) | [
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||
dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/aggregate_ucrs/models.py | python | AggregateTableDefinition.get_secondary_tables_and_adapters | (self) | return [
(table, get_indicator_adapter(table.data_source).get_table())
for table in self.secondary_tables.all()
] | [] | def get_secondary_tables_and_adapters(self):
return [
(table, get_indicator_adapter(table.data_source).get_table())
for table in self.secondary_tables.all()
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|||
PaddlePaddle/PGL | e48545f2814523c777b8a9a9188bf5a7f00d6e52 | legacy/pgl/graph_wrapper.py | python | StaticGraphWrapper.__create_graph_node_feat | (self, node_feat, collector) | Convert node features into paddlepaddle tensor. | Convert node features into paddlepaddle tensor. | [
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"""Convert node features into paddlepaddle tensor.
"""
for node_feat_name, node_feat_value in node_feat.items():
node_feat_shape = node_feat_value.shape
node_feat_dtype = node_feat_value.dtype
self.node_feat_tensor_dict[
node_feat_name], init = paddle_helper.constant(
name=self._data_name_prefix + '/node_feat/' +
node_feat_name,
dtype=node_feat_dtype,
value=node_feat_value)
collector.append(init) | [
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||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/werkzeug/contrib/cache.py | python | RedisCache.clear | (self) | return status | [] | def clear(self):
status = False
if self.key_prefix:
keys = self._client.keys(self.key_prefix + '*')
if keys:
status = self._client.delete(*keys)
else:
status = self._client.flushdb()
return status | [
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|||
LinOTP/LinOTP | bb3940bbaccea99550e6c063ff824f258dd6d6d7 | linotp/lib/resolver.py | python | _flush_user_resolver_cache | (resolver_spec) | flush the user realm cache
in case of a change of the resolver, all realms which use
this resolver must be flushed
:param resolver_spec: the resolve which has been updated
:return: - nothing - | flush the user realm cache
in case of a change of the resolver, all realms which use
this resolver must be flushed | [
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] | def _flush_user_resolver_cache(resolver_spec):
"""
flush the user realm cache
in case of a change of the resolver, all realms which use
this resolver must be flushed
:param resolver_spec: the resolve which has been updated
:return: - nothing -
"""
from linotp.lib.user import (
delete_realm_resolver_cache,
delete_resolver_user_cache,
)
delete_resolver_user_cache(resolver_spec)
config = context["Config"]
realms = config.getRealms()
# if a resolver is redefined, we have to refresh the related realm cache
for realm_name, realm_spec in list(realms.items()):
resolvers = realm_spec.get("useridresolver", [])
if resolver_spec in resolvers:
delete_realm_resolver_cache(realm_name) | [
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||
eandersson/amqpstorm | 7f57cf1291c8b3817527c10aae317aa1702654bc | amqpstorm/io.py | python | IO._process_incoming_data | (self) | Retrieve and process any incoming data.
:return: | Retrieve and process any incoming data. | [
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"incoming",
"data",
"."
] | def _process_incoming_data(self):
"""Retrieve and process any incoming data.
:return:
"""
while self._running.is_set():
if self.poller.is_ready:
self.data_in += self._receive()
self.data_in = self._on_read_impl(self.data_in) | [
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||
msracver/Deformable-ConvNets | 6aeda878a95bcb55eadffbe125804e730574de8d | deeplab/core/module.py | python | Module.load | (prefix, epoch, load_optimizer_states=False, **kwargs) | return mod | Create a model from previously saved checkpoint.
Parameters
----------
prefix : str
path prefix of saved model files. You should have
"prefix-symbol.json", "prefix-xxxx.params", and
optionally "prefix-xxxx.states", where xxxx is the
epoch number.
epoch : int
epoch to load.
load_optimizer_states : bool
whether to load optimizer states. Checkpoint needs
to have been made with save_optimizer_states=True.
data_names : list of str
Default is `('data')` for a typical model used in image classification.
label_names : list of str
Default is `('softmax_label')` for a typical model used in image
classification.
logger : Logger
Default is `logging`.
context : Context or list of Context
Default is `cpu()`.
work_load_list : list of number
Default `None`, indicating uniform workload.
fixed_param_names: list of str
Default `None`, indicating no network parameters are fixed. | Create a model from previously saved checkpoint. | [
"Create",
"a",
"model",
"from",
"previously",
"saved",
"checkpoint",
"."
] | def load(prefix, epoch, load_optimizer_states=False, **kwargs):
"""Create a model from previously saved checkpoint.
Parameters
----------
prefix : str
path prefix of saved model files. You should have
"prefix-symbol.json", "prefix-xxxx.params", and
optionally "prefix-xxxx.states", where xxxx is the
epoch number.
epoch : int
epoch to load.
load_optimizer_states : bool
whether to load optimizer states. Checkpoint needs
to have been made with save_optimizer_states=True.
data_names : list of str
Default is `('data')` for a typical model used in image classification.
label_names : list of str
Default is `('softmax_label')` for a typical model used in image
classification.
logger : Logger
Default is `logging`.
context : Context or list of Context
Default is `cpu()`.
work_load_list : list of number
Default `None`, indicating uniform workload.
fixed_param_names: list of str
Default `None`, indicating no network parameters are fixed.
"""
sym, args, auxs = load_checkpoint(prefix, epoch)
mod = Module(symbol=sym, **kwargs)
mod._arg_params = args
mod._aux_params = auxs
mod.params_initialized = True
if load_optimizer_states:
mod._preload_opt_states = '%s-%04d.states'%(prefix, epoch)
return mod | [
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|
oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/repr.py | python | Repr.repr_set | (self, x, level) | return self._repr_iterable(x, level, 'set([', '])', self.maxset) | [] | def repr_set(self, x, level):
x = _possibly_sorted(x)
return self._repr_iterable(x, level, 'set([', '])', self.maxset) | [
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|||
mlcommons/ck | 558a22c5970eb0d6708d0edc080e62a92566bab0 | ck/repo/module/result/module.py | python | postprocess_html | (i) | return {'return':0, 'html':h} | Input: {
html - html to post-process
original_input (dict) - passing extra parameters from URL
}
Output: {
return - return code = 0, if successful
> 0, if error
(error) - error text if return > 0
html - post-processed html
} | Input: {
html - html to post-process | [
"Input",
":",
"{",
"html",
"-",
"html",
"to",
"post",
"-",
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] | def postprocess_html(i):
"""
Input: {
html - html to post-process
original_input (dict) - passing extra parameters from URL
}
Output: {
return - return code = 0, if successful
> 0, if error
(error) - error text if return > 0
html - post-processed html
}
"""
h=i['html']
# Substitutions
sub={
'ck_html_title':'',
'ck_html_title_main':'',
'ck_html_title_note':'',
'ck_html_end_note':'',
'ck_html_form':''
}
# Check cfg to customize input
oi=i.get('original_input',{})
result_cfg=oi.get('cfg','')
cfg_id=oi.get('cfg_id','')
if result_cfg!='':
r=load_cfg({'cfg':result_cfg, 'cfg_id':cfg_id})
if r['return']>0: return r
dcfg=r['dict']
update_html=dcfg.get('update_html',{})
if len(update_html)>0:
sub.update(update_html)
sub['ck_cfg_uoa']=result_cfg
sub['ck_cfg_id']=r['cfg_id']
sub['ck_html_form']=r['html_selector']
# Check other params in original input and pass them to HTML
for k in common_data_keys + list(common_data_keys2.keys()) + ['user']:
sub['ck_'+k]=oi.get(k,'')
# Update html
for s in sub:
h=h.replace('$#'+s+'#$', sub[s])
return {'return':0, 'html':h} | [
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|
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/django/contrib/gis/db/backends/mysql/schema.py | python | MySQLGISSchemaEditor.remove_field | (self, model, field) | [] | def remove_field(self, model, field):
if isinstance(field, GeometryField) and field.spatial_index:
qn = self.connection.ops.quote_name
sql = self.sql_drop_spatial_index % {
'index': qn(self._create_spatial_index_name(model, field)),
'table': qn(model._meta.db_table),
}
try:
self.execute(sql)
except OperationalError:
logger.error(
"Couldn't remove spatial index: %s (may be expected "
"if your storage engine doesn't support them).", sql
)
super(MySQLGISSchemaEditor, self).remove_field(model, field) | [
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||||
Pylons/substanced | a897f4a0518c51b6e093cc5af39fa326f23752c2 | substanced/event/__init__.py | python | add_content_subscriber | (config, subscriber, iface=None, **predicates) | Configurator directive that works like Pyramid's ``add_subscriber``,
except it wraps the subscriber in something that first adds the
``registry`` attribute to the event being sent before the wrapped
subscriber is called. | Configurator directive that works like Pyramid's ``add_subscriber``,
except it wraps the subscriber in something that first adds the
``registry`` attribute to the event being sent before the wrapped
subscriber is called. | [
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] | def add_content_subscriber(config, subscriber, iface=None, **predicates):
""" Configurator directive that works like Pyramid's ``add_subscriber``,
except it wraps the subscriber in something that first adds the
``registry`` attribute to the event being sent before the wrapped
subscriber is called."""
registry = config.registry
def wrapper(event, *arg): # *arg ignored, XXX it can go away pyr1.4b1+
event.registry = registry
return subscriber(event)
if hasattr(subscriber, '__name__'):
update_wrapper(wrapper, subscriber)
wrapper.wrapped = subscriber
config.add_subscriber(wrapper, iface, **predicates) | [
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||
merkremont/LineVodka | c2fa74107cecf00dd17416b62e4eb579e2c7bbaf | LineAlpha/LineThrift/TalkService.py | python | Client.report | (self, syncOpRevision, category, report) | Parameters:
- syncOpRevision
- category
- report | Parameters:
- syncOpRevision
- category
- report | [
"Parameters",
":",
"-",
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"-",
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] | def report(self, syncOpRevision, category, report):
"""
Parameters:
- syncOpRevision
- category
- report
"""
self.send_report(syncOpRevision, category, report)
self.recv_report() | [
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||
Abjad/abjad | d0646dfbe83db3dc5ab268f76a0950712b87b7fd | abjad/parsers/parser.py | python | LilyPondSyntacticalDefinition.p_post_event_nofinger__Chr94__fingering | (self, p) | post_event_nofinger : '^' fingering | post_event_nofinger : '^' fingering | [
"post_event_nofinger",
":",
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"fingering"
] | def p_post_event_nofinger__Chr94__fingering(self, p):
"post_event_nofinger : '^' fingering"
p[0] = None | [
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||
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/sandpiles/sandpile.py | python | SandpileDivisor.deg | (self) | return self._deg | r"""
The degree of the divisor.
OUTPUT:
integer
EXAMPLES::
sage: S = sandpiles.Cycle(3)
sage: D = SandpileDivisor(S, [1,2,3])
sage: D.deg()
6 | r"""
The degree of the divisor. | [
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"."
] | def deg(self):
r"""
The degree of the divisor.
OUTPUT:
integer
EXAMPLES::
sage: S = sandpiles.Cycle(3)
sage: D = SandpileDivisor(S, [1,2,3])
sage: D.deg()
6
"""
return self._deg | [
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] | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/sandpiles/sandpile.py#L4433-L4448 |
|
FederatedAI/FATE | 32540492623568ecd1afcb367360133616e02fa3 | python/federatedml/ensemble/boosting/homo/homo_secureboosting_aggregator.py | python | DecisionTreeArbiterAggregator.__init__ | (self, verbose=False) | [] | def __init__(self, verbose=False):
self.aggregator = secure_sum_aggregator.Server(enable_secure_aggregate=True)
self.scatter = loss_scatter.Server()
self.verbose = verbose | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/billiard/_win.py | python | get_processtree_pids | (pid, include_parent=True) | return list(pids) | Return a list with all the pids of a process tree | Return a list with all the pids of a process tree | [
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] | def get_processtree_pids(pid, include_parent=True):
"""Return a list with all the pids of a process tree"""
parents = get_all_processes_pids()
all_pids = list(parents.keys())
pids = {pid}
while 1:
pids_new = pids.copy()
for _pid in all_pids:
if parents[_pid] in pids:
pids_new.add(_pid)
if pids_new == pids:
break
pids = pids_new.copy()
if not include_parent:
pids.remove(pid)
return list(pids) | [
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|
iniqua/plecost | ef0d89bfdf1ef870bd11b1d8bdf93a8ce9ec6ca0 | plecost_lib/libs/db.py | python | db_query | (data) | return _actions[data.action](data, db) | Query the database and return a text with the information.
:param data: PlecostDatabaseQuery object
:type data: PlecostDatabaseQuery
:return: results of query
:rtype: str | Query the database and return a text with the information. | [
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] | def db_query(data):
"""
Query the database and return a text with the information.
:param data: PlecostDatabaseQuery object
:type data: PlecostDatabaseQuery
:return: results of query
:rtype: str
"""
if not isinstance(data, PlecostDatabaseQuery):
raise TypeError("Expected PlecostDatabaseQuery, got '%s' instead" % type(data))
_actions = dict(plugin_list=__plugin_list,
cve=__cve_details,
plugin_cves=__plugin_cves)
db = DB(join(get_data_folder(), "cve.db"))
return _actions[data.action](data, db) | [
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|
Alexander-H-Liu/End-to-end-ASR-Pytorch | 1103d144423e8e692f1d18cd9db27a96cb49fb9d | src/asr.py | python | Decoder.forward | (self, x) | return char, x | Decode and transform into vocab | Decode and transform into vocab | [
"Decode",
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"into",
"vocab"
] | def forward(self, x):
''' Decode and transform into vocab '''
if not self.training:
self.layers.flatten_parameters()
x, self.hidden_state = self.layers(x.unsqueeze(1), self.hidden_state)
x = x.squeeze(1)
char = self.char_trans(self.final_dropout(x))
return char, x | [
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|
wannabeOG/Mask-RCNN | b6ce3d8795eeaccbbde6d91ec827a38df3a88a4c | utils.py | python | Dataset.prepare | (self, class_map=None) | Prepares the Dataset class for use.
TODO: class map is not supported yet. When done, it should handle mapping
classes from different datasets to the same class ID. | Prepares the Dataset class for use. | [
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] | def prepare(self, class_map=None):
"""Prepares the Dataset class for use.
TODO: class map is not supported yet. When done, it should handle mapping
classes from different datasets to the same class ID.
"""
def clean_name(name):
"""Returns a shorter version of object names for cleaner display."""
return ",".join(name.split(",")[:1])
# Build (or rebuild) everything else from the info dicts.
self.num_classes = len(self.class_info)
self.class_ids = np.arange(self.num_classes)
self.class_names = [clean_name(c["name"]) for c in self.class_info]
self.num_images = len(self.image_info)
self._image_ids = np.arange(self.num_images)
self.class_from_source_map = {"{}.{}".format(info['source'], info['id']): id
for info, id in zip(self.class_info, self.class_ids)}
# Map sources to class_ids they support
self.sources = list(set([i['source'] for i in self.class_info]))
self.source_class_ids = {}
# Loop over datasets
for source in self.sources:
self.source_class_ids[source] = []
# Find classes that belong to this dataset
for i, info in enumerate(self.class_info):
# Include BG class in all datasets
if i == 0 or source == info['source']:
self.source_class_ids[source].append(i) | [
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] | https://github.com/wannabeOG/Mask-RCNN/blob/b6ce3d8795eeaccbbde6d91ec827a38df3a88a4c/utils.py#L203-L233 |
||
NVlabs/stylegan2 | bf0fe0baba9fc7039eae0cac575c1778be1ce3e3 | dnnlib/tflib/optimizer.py | python | SimpleAdam.apply_gradients | (self, grads_and_vars) | [] | def apply_gradients(self, grads_and_vars):
with tf.name_scope(self.name):
state_vars = []
update_ops = []
# Adjust learning rate to deal with startup bias.
with tf.control_dependencies(None):
b1pow_var = tf.Variable(dtype=tf.float32, initial_value=1, trainable=False)
b2pow_var = tf.Variable(dtype=tf.float32, initial_value=1, trainable=False)
state_vars += [b1pow_var, b2pow_var]
b1pow_new = b1pow_var * self.beta1
b2pow_new = b2pow_var * self.beta2
update_ops += [tf.assign(b1pow_var, b1pow_new), tf.assign(b2pow_var, b2pow_new)]
lr_new = self.learning_rate * tf.sqrt(1 - b2pow_new) / (1 - b1pow_new)
# Construct ops to update each variable.
for grad, var in grads_and_vars:
with tf.control_dependencies(None):
m_var = tf.Variable(dtype=tf.float32, initial_value=tf.zeros_like(var), trainable=False)
v_var = tf.Variable(dtype=tf.float32, initial_value=tf.zeros_like(var), trainable=False)
state_vars += [m_var, v_var]
m_new = self.beta1 * m_var + (1 - self.beta1) * grad
v_new = self.beta2 * v_var + (1 - self.beta2) * tf.square(grad)
var_delta = lr_new * m_new / (tf.sqrt(v_new) + self.epsilon)
update_ops += [tf.assign(m_var, m_new), tf.assign(v_var, v_new), tf.assign_sub(var, var_delta)]
# Group everything together.
self.all_state_vars += state_vars
return tf.group(*update_ops) | [
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] | https://github.com/NVlabs/stylegan2/blob/bf0fe0baba9fc7039eae0cac575c1778be1ce3e3/dnnlib/tflib/optimizer.py#L342-L370 |
||||
ConvLab/ConvLab | a04582a77537c1a706fbf64715baa9ad0be1301a | convlab/modules/dst/state_tracker.py | python | Tracker.init_session | (self) | Init the Tracker to start a new session. | Init the Tracker to start a new session. | [
"Init",
"the",
"Tracker",
"to",
"start",
"a",
"new",
"session",
"."
] | def init_session(self):
"""Init the Tracker to start a new session."""
pass | [
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"(",
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")",
":",
"pass"
] | https://github.com/ConvLab/ConvLab/blob/a04582a77537c1a706fbf64715baa9ad0be1301a/convlab/modules/dst/state_tracker.py#L27-L29 |
||
pikpikcu/Pentest-Tools-Framework | cd6e6107764a809943dc4e073cde8149c1a2cd03 | modules/xsser/build/bdist.linux-armv7l/egg/core/main.py | python | xsser.get_payloads | (self) | return payloads | Process payload options and make up the payload list for the attack. | Process payload options and make up the payload list for the attack. | [
"Process",
"payload",
"options",
"and",
"make",
"up",
"the",
"payload",
"list",
"for",
"the",
"attack",
"."
] | def get_payloads(self):
"""
Process payload options and make up the payload list for the attack.
"""
options = self.options
# payloading sources
payloads_fuzz = core.fuzzing.vectors.vectors
payloads_dcp = core.fuzzing.DCP.DCPvectors
payloads_dom = core.fuzzing.DOM.DOMvectors
payloads_httpsr = core.fuzzing.HTTPsr.HTTPrs_vectors
manual_payload = [{"payload":options.script, "browser":"[manual_injection]"}]
# sustitute payload for hash to check false positives
self.hashed_payload = self.generate_hash('url')
checker_payload = [{"payload":self.hashed_payload, "browser":"[hashed_precheck_system]"}]
# heuristic parameters
heuristic_params = core.fuzzing.heuristic.heuristic_test
def enable_options_heuristic(payloads):
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
return payloads
if options.fuzz:
payloads = payloads_fuzz
if options.dcp:
payloads = payloads + payloads_dcp
if options.script:
payloads = payloads + manual_payload
if options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.script:
payloads = payloads + manual_payload
if options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payaloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads + payloads_httpsr
if options.hash:
payloads = checker_payload + payloads
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.dcp:
payloads = payloads_dcp
if options.script:
payloads = payloads + manual_payload
if options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + inducedcode
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.script:
payloads = manual_payload
if options.hash:
payloads = checker_payload + payloads
if options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads + payloads_httpsr
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
paylaods = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.inducedcode:
payloads = payloads_httpsr
if options.hash:
payloads = checker_payload + payloads
if options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.heuristic:
payloads = heuristic_params
if options.hash:
payloads = checker_payload + payloads
if options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads + payloads_dom
elif options.dom:
payloads = payloads_dom
elif not options.fuzz and not options.dcp and not options.script and not options.hash and not options.inducedcode and not options.heuristic and not options.dom:
payloads = [{"payload":'">PAYLOAD',
"browser":"[IE7.0|IE6.0|NS8.1-IE] [NS8.1-G|FF2.0] [O9.02]"
}]
else:
payloads = checker_payload
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|
brendano/tweetmotif | 1b0b1e3a941745cd5a26eba01f554688b7c4b27e | everything_else/djfrontend/django-1.0.2/db/models/sql/subqueries.py | python | UpdateQuery.pre_sql_setup | (self) | If the update depends on results from other tables, we need to do some
munging of the "where" conditions to match the format required for
(portable) SQL updates. That is done here.
Further, if we are going to be running multiple updates, we pull out
the id values to update at this point so that they don't change as a
result of the progressive updates. | If the update depends on results from other tables, we need to do some
munging of the "where" conditions to match the format required for
(portable) SQL updates. That is done here. | [
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"""
If the update depends on results from other tables, we need to do some
munging of the "where" conditions to match the format required for
(portable) SQL updates. That is done here.
Further, if we are going to be running multiple updates, we pull out
the id values to update at this point so that they don't change as a
result of the progressive updates.
"""
self.select_related = False
self.clear_ordering(True)
super(UpdateQuery, self).pre_sql_setup()
count = self.count_active_tables()
if not self.related_updates and count == 1:
return
# We need to use a sub-select in the where clause to filter on things
# from other tables.
query = self.clone(klass=Query)
query.bump_prefix()
query.extra_select = {}
first_table = query.tables[0]
if query.alias_refcount[first_table] == 1:
# We can remove one table from the inner query.
query.unref_alias(first_table)
for i in xrange(1, len(query.tables)):
table = query.tables[i]
if query.alias_refcount[table]:
break
join_info = query.alias_map[table]
query.select = [(join_info[RHS_ALIAS], join_info[RHS_JOIN_COL])]
must_pre_select = False
else:
query.select = []
query.add_fields([query.model._meta.pk.name])
must_pre_select = not self.connection.features.update_can_self_select
# Now we adjust the current query: reset the where clause and get rid
# of all the tables we don't need (since they're in the sub-select).
self.where = self.where_class()
if self.related_updates or must_pre_select:
# Either we're using the idents in multiple update queries (so
# don't want them to change), or the db backend doesn't support
# selecting from the updating table (e.g. MySQL).
idents = []
for rows in query.execute_sql(MULTI):
idents.extend([r[0] for r in rows])
self.add_filter(('pk__in', idents))
self.related_ids = idents
else:
# The fast path. Filters and updates in one query.
self.add_filter(('pk__in', query))
for alias in self.tables[1:]:
self.alias_refcount[alias] = 0 | [
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||
Cadene/tensorflow-model-zoo.torch | 990b10ffc22d4c8eacb2a502f20415b4f70c74c2 | models/research/swivel/prep.py | python | words | (line) | return line.strip().split() | Splits a line of text into tokens. | Splits a line of text into tokens. | [
"Splits",
"a",
"line",
"of",
"text",
"into",
"tokens",
"."
] | def words(line):
"""Splits a line of text into tokens."""
return line.strip().split() | [
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|
Teradata/stacki | a8085dce179dbe903f65f136f4b63bcc076cc057 | common/src/stack/pylib/stack/file.py | python | RPMFile.installPackage | (self, root, flags="") | return retval | Installs the RPM at the given root directory. This is
used for patching RPMs into the distribution and making
bootable CDs | Installs the RPM at the given root directory. This is
used for patching RPMs into the distribution and making
bootable CDs | [
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] | def installPackage(self, root, flags=""):
"""Installs the RPM at the given root directory. This is
used for patching RPMs into the distribution and making
bootable CDs"""
pass
dbdir = os.path.join(root, 'var', 'lib', 'rpm')
if not os.path.isdir(dbdir):
os.makedirs(dbdir)
cmd = 'rpm -i --nomd5 --force --nodeps --ignorearch ' + \
'--dbpath %s %s ' % (dbdir, flags)
cmd += '--badreloc --relocate /=%s %s' \
% (root, self.getFullName())
retval = os.system(cmd)
# Crawl up from the end of the dbdir path and prune off
# all the empty directories.
while dbdir:
if not os.listdir(dbdir):
shutil.rmtree(dbdir)
list = dbdir.split(os.sep)
dbdir = os.sep.join(list[:-1])
return retval | [
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|
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/integrals/risch.py | python | integrate_hyperexponential | (a, d, DE, z=None, conds='piecewise') | return (ret, i, b) | Integration of hyperexponential functions.
Given a hyperexponential monomial t over k and f in k(t), return g
elementary over k(t), i in k(t), and a bool b in {True, False} such that
i = f - Dg is in k if b is True or i = f - Dg does not have an elementary
integral over k(t) if b is False.
This function returns a Basic expression for the first argument. If b is
True, the second argument is Basic expression in k to recursively integrate.
If b is False, the second argument is an unevaluated Integral, which has
been proven to be nonelementary. | Integration of hyperexponential functions. | [
"Integration",
"of",
"hyperexponential",
"functions",
"."
] | def integrate_hyperexponential(a, d, DE, z=None, conds='piecewise'):
"""
Integration of hyperexponential functions.
Given a hyperexponential monomial t over k and f in k(t), return g
elementary over k(t), i in k(t), and a bool b in {True, False} such that
i = f - Dg is in k if b is True or i = f - Dg does not have an elementary
integral over k(t) if b is False.
This function returns a Basic expression for the first argument. If b is
True, the second argument is Basic expression in k to recursively integrate.
If b is False, the second argument is an unevaluated Integral, which has
been proven to be nonelementary.
"""
# XXX: a and d must be canceled, or this might return incorrect results
z = z or Dummy("z")
s = list(zip(reversed(DE.T), reversed([f(DE.x) for f in DE.Tfuncs])))
g1, h, r = hermite_reduce(a, d, DE)
g2, b = residue_reduce(h[0], h[1], DE, z=z)
if not b:
i = cancel(a.as_expr()/d.as_expr() - (g1[1]*derivation(g1[0], DE) -
g1[0]*derivation(g1[1], DE)).as_expr()/(g1[1]**2).as_expr() -
residue_reduce_derivation(g2, DE, z))
i = NonElementaryIntegral(cancel(i.subs(s)), DE.x)
return ((g1[0].as_expr()/g1[1].as_expr()).subs(s) +
residue_reduce_to_basic(g2, DE, z), i, b)
# p should be a polynomial in t and 1/t, because Sirr == k[t, 1/t]
# h - Dg2 + r
p = cancel(h[0].as_expr()/h[1].as_expr() - residue_reduce_derivation(g2,
DE, z) + r[0].as_expr()/r[1].as_expr())
pp = as_poly_1t(p, DE.t, z)
qa, qd, b = integrate_hyperexponential_polynomial(pp, DE, z)
i = pp.nth(0, 0)
ret = ((g1[0].as_expr()/g1[1].as_expr()).subs(s) \
+ residue_reduce_to_basic(g2, DE, z))
qas = qa.as_expr().subs(s)
qds = qd.as_expr().subs(s)
if conds == 'piecewise' and DE.x not in qds.free_symbols:
# We have to be careful if the exponent is S.Zero!
# XXX: Does qd = 0 always necessarily correspond to the exponential
# equaling 1?
ret += Piecewise(
(qas/qds, Ne(qds, 0)),
(integrate((p - i).subs(DE.t, 1).subs(s), DE.x), True)
)
else:
ret += qas/qds
if not b:
i = p - (qd*derivation(qa, DE) - qa*derivation(qd, DE)).as_expr()/\
(qd**2).as_expr()
i = NonElementaryIntegral(cancel(i).subs(s), DE.x)
return (ret, i, b) | [
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|
linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pip/pep425tags.py | python | is_manylinux1_compatible | () | return pip.utils.glibc.have_compatible_glibc(2, 5) | [] | def is_manylinux1_compatible():
# Only Linux, and only x86-64 / i686
if get_platform() not in ("linux_x86_64", "linux_i686"):
return False
# Check for presence of _manylinux module
try:
import _manylinux
return bool(_manylinux.manylinux1_compatible)
except (ImportError, AttributeError):
# Fall through to heuristic check below
pass
# Check glibc version. CentOS 5 uses glibc 2.5.
return pip.utils.glibc.have_compatible_glibc(2, 5) | [
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|||
tecladocode/rest-apis-flask-python | d2d40872012dcf1b63ffde4bbd2dd447fec98eca | section2/10_args_and_kwargs.py | python | what_are_args | (*args) | [] | def what_are_args(*args):
print(args) | [
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||||
keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/utils/email/config.py | python | EmailConfiguration.password | (self) | return self._password | [] | def password(self):
return self._password | [
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] | https://github.com/keiffster/program-y/blob/8c99b56f8c32f01a7b9887b5daae9465619d0385/src/programy/utils/email/config.py#L47-L48 |
|||
MDAnalysis/mdanalysis | 3488df3cdb0c29ed41c4fb94efe334b541e31b21 | package/MDAnalysis/coordinates/TRZ.py | python | TRZReader._get_dt | (self) | The amount of time between frames in ps
Assumes that this step is constant (ie. 2 trajectories with different
steps haven't been stitched together).
Returns ``AttributeError`` in case of ``StopIteration``
(which makes :attr:`dt` return 1.0).
.. versionchanged:: 2.1.0
Now returns an ``AttributeError`` if dt can't be obtained from the
time difference between two frames. | The amount of time between frames in ps | [
"The",
"amount",
"of",
"time",
"between",
"frames",
"in",
"ps"
] | def _get_dt(self):
"""The amount of time between frames in ps
Assumes that this step is constant (ie. 2 trajectories with different
steps haven't been stitched together).
Returns ``AttributeError`` in case of ``StopIteration``
(which makes :attr:`dt` return 1.0).
.. versionchanged:: 2.1.0
Now returns an ``AttributeError`` if dt can't be obtained from the
time difference between two frames.
"""
curr_frame = self.ts.frame
try:
t0 = self.ts.time
self.next()
t1 = self.ts.time
dt = t1 - t0
except StopIteration:
raise AttributeError
else:
return dt
finally:
self._read_frame(curr_frame) | [
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||
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/sloane_functions.py | python | A083105.__init__ | (self) | r"""
Second-order linear recurrence sequence with
`a(n) = a(n-1) + a(n-2)`.
`a(0) = 62638280004239857`,
`a(1) = 49463435743205655`. This is the second-order linear
recurrence sequence with `a(0)` and `a(1)`
co-prime. It was found by Donald Knuth in 1990.
INPUT:
- ``n`` -- non negative integer
OUTPUT:
- ``integer`` -- function value
EXAMPLES::
sage: a = sloane.A083105;a
Second-order linear recurrence sequence with a(n) = a(n-1) + a(n-2).
sage: a(1)
49463435743205655
sage: a(2)
112101715747445512
sage: a(3)
161565151490651167
sage: a.offset
0
sage: a(8)
1853029790662436896
sage: a(20)
596510791500513098192
sage: a.list(4)
[62638280004239857, 49463435743205655, 112101715747445512, 161565151490651167]
AUTHORS:
- Jaap Spies (2007-01-23) | r"""
Second-order linear recurrence sequence with
`a(n) = a(n-1) + a(n-2)`. | [
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r"""
Second-order linear recurrence sequence with
`a(n) = a(n-1) + a(n-2)`.
`a(0) = 62638280004239857`,
`a(1) = 49463435743205655`. This is the second-order linear
recurrence sequence with `a(0)` and `a(1)`
co-prime. It was found by Donald Knuth in 1990.
INPUT:
- ``n`` -- non negative integer
OUTPUT:
- ``integer`` -- function value
EXAMPLES::
sage: a = sloane.A083105;a
Second-order linear recurrence sequence with a(n) = a(n-1) + a(n-2).
sage: a(1)
49463435743205655
sage: a(2)
112101715747445512
sage: a(3)
161565151490651167
sage: a.offset
0
sage: a(8)
1853029790662436896
sage: a(20)
596510791500513098192
sage: a.list(4)
[62638280004239857, 49463435743205655, 112101715747445512, 161565151490651167]
AUTHORS:
- Jaap Spies (2007-01-23)
"""
SloaneSequence.__init__(self, offset=0)
self._b = []
self._params = (62638280004239857,49463435743205655,1,1)
self._precompute(2) | [
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||
saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/renderers/stateconf.py | python | state_name | (sname) | return sname.split(".", 1)[0] | Return the name of the state regardless if sname is
just the state name or a state.func name. | Return the name of the state regardless if sname is
just the state name or a state.func name. | [
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"""
Return the name of the state regardless if sname is
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"""
return sname.split(".", 1)[0] | [
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|
JimmXinu/FanFicFare | bc149a2deb2636320fe50a3e374af6eef8f61889 | included_dependencies/html2text/utils.py | python | escape_md | (text) | return config.RE_MD_CHARS_MATCHER.sub(r"\\\1", text) | Escapes markdown-sensitive characters within other markdown
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"""
Escapes markdown-sensitive characters within other markdown
constructs.
"""
return config.RE_MD_CHARS_MATCHER.sub(r"\\\1", text) | [
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|
WeblateOrg/weblate | 8126f3dda9d24f2846b755955132a8b8410866c8 | weblate/utils/ratelimit.py | python | get_cache_key | (scope, request=None, address=None, user=None) | return f"ratelimit-{origin}-{scope}-{key}" | Generate cache key for request. | Generate cache key for request. | [
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] | def get_cache_key(scope, request=None, address=None, user=None):
"""Generate cache key for request."""
if (request and request.user.is_authenticated) or user:
if user:
key = user.id
else:
key = request.user.id
origin = "user"
else:
if address is None:
address = get_ip_address(request)
origin = "ip"
key = calculate_checksum(address)
return f"ratelimit-{origin}-{scope}-{key}" | [
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|
wwqgtxx/wwqLyParse | 33136508e52821babd9294fdecffbdf02d73a6fc | wwqLyParse/lib/python-3.7.2-embed-amd64/Crypto/Util/RFC1751.py | python | key_to_english | (key) | return english[:-1] | Transform an arbitrary key into a string containing English words.
Example::
>>> from Crypto.Util.RFC1751 import key_to_english
>>> key_to_english(b'66666666')
'RAM LOIS GOAD CREW CARE HIT'
Args:
key (byte string):
The key to convert. Its length must be a multiple of 8.
Return:
A string of English words. | Transform an arbitrary key into a string containing English words. | [
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] | def key_to_english (key):
"""Transform an arbitrary key into a string containing English words.
Example::
>>> from Crypto.Util.RFC1751 import key_to_english
>>> key_to_english(b'66666666')
'RAM LOIS GOAD CREW CARE HIT'
Args:
key (byte string):
The key to convert. Its length must be a multiple of 8.
Return:
A string of English words.
"""
english=''
for index in range(0, len(key), 8): # Loop over 8-byte subkeys
subkey=key[index:index+8]
# Compute the parity of the key
skbin=_key2bin(subkey) ; p=0
for i in range(0, 64, 2): p=p+_extract(skbin, i, 2)
# Append parity bits to the subkey
skbin=_key2bin(subkey+bchr((p<<6) & 255))
for i in range(0, 64, 11):
english=english+wordlist[_extract(skbin, i, 11)]+' '
return english[:-1] | [
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|
aceisace/Inkycal | 552744bc5d80769c1015d48fd8b13201683ee679 | inkycal/display/drivers/epd_7_in_5_colour.py | python | EPD.__init__ | (self) | [] | def __init__(self):
self.reset_pin = epdconfig.RST_PIN
self.dc_pin = epdconfig.DC_PIN
self.busy_pin = epdconfig.BUSY_PIN
self.cs_pin = epdconfig.CS_PIN
self.width = EPD_WIDTH
self.height = EPD_HEIGHT | [
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||||
scikit-image/scikit-image | ed642e2bc822f362504d24379dee94978d6fa9de | skimage/morphology/_util.py | python | _resolve_neighborhood | (footprint, connectivity, ndim) | return footprint | Validate or create a footprint (structuring element).
Depending on the values of `connectivity` and `footprint` this function
either creates a new footprint (`footprint` is None) using `connectivity`
or validates the given footprint (`footprint` is not None).
Parameters
----------
footprint : ndarray
The footprint (structuring) element used to determine the neighborhood
of each evaluated pixel (``True`` denotes a connected pixel). It must
be a boolean array and have the same number of dimensions as `image`.
If neither `footprint` nor `connectivity` are given, all adjacent
pixels are considered as part of the neighborhood.
connectivity : int
A number used to determine the neighborhood of each evaluated pixel.
Adjacent pixels whose squared distance from the center is less than or
equal to `connectivity` are considered neighbors. Ignored if
`footprint` is not None.
ndim : int
Number of dimensions `footprint` ought to have.
Returns
-------
footprint : ndarray
Validated or new footprint specifying the neighborhood.
Examples
--------
>>> _resolve_neighborhood(None, 1, 2)
array([[False, True, False],
[ True, True, True],
[False, True, False]])
>>> _resolve_neighborhood(None, None, 3).shape
(3, 3, 3) | Validate or create a footprint (structuring element). | [
"Validate",
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] | def _resolve_neighborhood(footprint, connectivity, ndim):
"""Validate or create a footprint (structuring element).
Depending on the values of `connectivity` and `footprint` this function
either creates a new footprint (`footprint` is None) using `connectivity`
or validates the given footprint (`footprint` is not None).
Parameters
----------
footprint : ndarray
The footprint (structuring) element used to determine the neighborhood
of each evaluated pixel (``True`` denotes a connected pixel). It must
be a boolean array and have the same number of dimensions as `image`.
If neither `footprint` nor `connectivity` are given, all adjacent
pixels are considered as part of the neighborhood.
connectivity : int
A number used to determine the neighborhood of each evaluated pixel.
Adjacent pixels whose squared distance from the center is less than or
equal to `connectivity` are considered neighbors. Ignored if
`footprint` is not None.
ndim : int
Number of dimensions `footprint` ought to have.
Returns
-------
footprint : ndarray
Validated or new footprint specifying the neighborhood.
Examples
--------
>>> _resolve_neighborhood(None, 1, 2)
array([[False, True, False],
[ True, True, True],
[False, True, False]])
>>> _resolve_neighborhood(None, None, 3).shape
(3, 3, 3)
"""
if footprint is None:
if connectivity is None:
connectivity = ndim
footprint = ndi.generate_binary_structure(ndim, connectivity)
else:
# Validate custom structured element
footprint = np.asarray(footprint, dtype=bool)
# Must specify neighbors for all dimensions
if footprint.ndim != ndim:
raise ValueError(
"number of dimensions in image and footprint do not"
"match"
)
# Must only specify direct neighbors
if any(s != 3 for s in footprint.shape):
raise ValueError("dimension size in footprint is not 3")
return footprint | [
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|
LinkedInAttic/indextank-service | 880c6295ce8e7a3a55bf9b3777cc35c7680e0d7e | storefront/boto/vpc/__init__.py | python | VPCConnection.get_all_customer_gateways | (self, customer_gateway_ids=None, filters=None) | return self.get_list('DescribeCustomerGateways', params, [('item', CustomerGateway)]) | Retrieve information about your CustomerGateways. You can filter results to
return information only about those CustomerGateways that match your search
parameters. Otherwise, all CustomerGateways associated with your account
are returned.
:type customer_gateway_ids: list
:param customer_gateway_ids: A list of strings with the desired CustomerGateway ID's
:type filters: list of tuples
:param filters: A list of tuples containing filters. Each tuple
consists of a filter key and a filter value.
Possible filter keys are:
- *state*, the state of the CustomerGateway
(pending,available,deleting,deleted)
- *type*, the type of customer gateway (ipsec.1)
- *ipAddress* the IP address of customer gateway's
internet-routable external inteface
:rtype: list
:return: A list of :class:`boto.vpc.customergateway.CustomerGateway` | Retrieve information about your CustomerGateways. You can filter results to
return information only about those CustomerGateways that match your search
parameters. Otherwise, all CustomerGateways associated with your account
are returned.
:type customer_gateway_ids: list
:param customer_gateway_ids: A list of strings with the desired CustomerGateway ID's
:type filters: list of tuples
:param filters: A list of tuples containing filters. Each tuple
consists of a filter key and a filter value.
Possible filter keys are:
- *state*, the state of the CustomerGateway
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- *type*, the type of customer gateway (ipsec.1)
- *ipAddress* the IP address of customer gateway's
internet-routable external inteface | [
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"""
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return information only about those CustomerGateways that match your search
parameters. Otherwise, all CustomerGateways associated with your account
are returned.
:type customer_gateway_ids: list
:param customer_gateway_ids: A list of strings with the desired CustomerGateway ID's
:type filters: list of tuples
:param filters: A list of tuples containing filters. Each tuple
consists of a filter key and a filter value.
Possible filter keys are:
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(pending,available,deleting,deleted)
- *type*, the type of customer gateway (ipsec.1)
- *ipAddress* the IP address of customer gateway's
internet-routable external inteface
:rtype: list
:return: A list of :class:`boto.vpc.customergateway.CustomerGateway`
"""
params = {}
if customer_gateway_ids:
self.build_list_params(params, customer_gateway_ids, 'CustomerGatewayId')
if filters:
i = 1
for filter in filters:
params[('Filter.%d.Key' % i)] = filter[0]
params[('Filter.%d.Value.1')] = filter[1]
i += 1
return self.get_list('DescribeCustomerGateways', params, [('item', CustomerGateway)]) | [
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|
thatbrguy/Pedestrian-Detection | b11c7d6bed0ff320811726fe1c429be26a87da9e | object_detection/anchor_generators/multiple_grid_anchor_generator.py | python | MultipleGridAnchorGenerator.num_anchors_per_location | (self) | return [len(box_specs) for box_specs in self._box_specs] | Returns the number of anchors per spatial location.
Returns:
a list of integers, one for each expected feature map to be passed to
the Generate function. | Returns the number of anchors per spatial location. | [
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] | def num_anchors_per_location(self):
"""Returns the number of anchors per spatial location.
Returns:
a list of integers, one for each expected feature map to be passed to
the Generate function.
"""
return [len(box_specs) for box_specs in self._box_specs] | [
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Komodo/KomodoEdit | 61edab75dce2bdb03943b387b0608ea36f548e8e | src/python-sitelib/pyxpcomProfiler.py | python | getXPCOMRecorder | (xpcomObject) | return recorder | Return the base xpcom recorder object for this python xpcom object.
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Tries to record all the same xpcom instances for one interface in the same
recorder object.
"""
names = None
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if not names:
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if com_interfaces:
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names = [x.name for x in com_interfaces]
if names is not None:
name = "_".join(names)
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name = repr(xpcomObject)
recorder = xpcom_recordings.get(name)
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recorder = XPCOMRecorder(name)
xpcom_recordings[name] = recorder
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|
quantumlib/Cirq | 89f88b01d69222d3f1ec14d649b7b3a85ed9211f | dev_tools/pr_monitor.py | python | get_repo_ref | (repo: GithubRepository, ref: str) | return payload | Get a given github reference.
References:
https://developer.github.com/v3/git/refs/#get-a-reference
Args:
repo: The github repo to get the reference from.
ref: The id of the reference.
Returns:
The raw response of the request for the reference..
Raises:
RuntimeError: If the request does not return status 200 (success). | Get a given github reference. | [
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] | def get_repo_ref(repo: GithubRepository, ref: str) -> Dict[str, Any]:
"""Get a given github reference.
References:
https://developer.github.com/v3/git/refs/#get-a-reference
Args:
repo: The github repo to get the reference from.
ref: The id of the reference.
Returns:
The raw response of the request for the reference..
Raises:
RuntimeError: If the request does not return status 200 (success).
"""
url = f"https://api.github.com/repos/{repo.organization}/{repo.name}/git/refs/{ref}"
response = repo.get(url)
if response.status_code != 200:
raise RuntimeError(
'Refs get failed. Code: {}. Content: {!r}.'.format(
response.status_code, response.content
)
)
payload = json.JSONDecoder().decode(response.content.decode())
return payload | [
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|
menpo/menpo | a61500656c4fc2eea82497684f13cc31a605550b | menpo/model/linear.py | python | MeanLinearVectorModel.mean | (self) | return self._mean | r"""
Return the mean of the model.
:type: `ndarray` | r"""
Return the mean of the model. | [
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r"""
Return the mean of the model.
:type: `ndarray`
"""
return self._mean | [
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|
Cisco-Talos/GhIDA | a396916ae53e46adf3dca918b810f5db046af015 | ghida_plugin/idaxml.py | python | XmlExporter.export_typeinfo_cmt | (self, cmt) | Exports comment containing type information for data and functions.
Args:
cmt: String containing type info. | Exports comment containing type information for data and functions. | [
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] | def export_typeinfo_cmt(self, cmt):
"""
Exports comment containing type information for data and functions.
Args:
cmt: String containing type info.
"""
# older versions of IDAPython returned a '\n' at end of cmt
if(len(cmt) > 0):
while cmt[-1] == '\n':
cmt = cmt[:-1]
self.write_comment_element(TYPEINFO_CMT, cmt) | [
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||
cloudera/impyla | 0c736af4cad2bade9b8e313badc08ec50e81c948 | impala/_thrift_gen/hive_metastore/ThriftHiveMetastore.py | python | Iface.alter_table_with_environment_context | (self, dbname, tbl_name, new_tbl, environment_context) | Parameters:
- dbname
- tbl_name
- new_tbl
- environment_context | Parameters:
- dbname
- tbl_name
- new_tbl
- environment_context | [
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"""
Parameters:
- dbname
- tbl_name
- new_tbl
- environment_context
"""
pass | [
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||
keras-team/keras | 5caa668b6a415675064a730f5eb46ecc08e40f65 | keras/saving/saved_model/base_serialization.py | python | SavedModelSaver.list_extra_dependencies_for_serialization | (self, serialization_cache) | return self.objects_to_serialize(serialization_cache) | Lists extra dependencies to serialize to SavedModel.
By overriding this method, extra dependencies can be attached to the
serialized Layer. For example, this is used to save the list of `variables`
and `trainable_variables`, which are python properties in a Layer object,
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A dictionary mapping attribute names to trackable objects. The entire list
of attributes are listed in the `saved_model._LayerAttributes` class. | Lists extra dependencies to serialize to SavedModel. | [
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"""Lists extra dependencies to serialize to SavedModel.
By overriding this method, extra dependencies can be attached to the
serialized Layer. For example, this is used to save the list of `variables`
and `trainable_variables`, which are python properties in a Layer object,
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Args:
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Returns:
A dictionary mapping attribute names to trackable objects. The entire list
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"""
if not utils.should_save_traces():
return {}
return self.objects_to_serialize(serialization_cache) | [
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|
jobovy/galpy | 8e6a230bbe24ce16938db10053f92eb17fe4bb52 | galpy/df/surfaceSigmaProfile.py | python | expSurfaceSigmaProfile.sigma2Derivative | (self,R,log=False) | NAME:
sigmaDerivative
PURPOSE:
return the derivative wrt R of the sigma_R^2 profile at this R
INPUT:
R - Galactocentric radius (/ro)
log - if True, return the derivative of the log (default: False)
OUTPUT:
Sigma_R^2'(R) or (log Sigma_R^2(r) )'
HISTORY:
2011-03-24 - Written - Bovy (NYU) | NAME:
sigmaDerivative
PURPOSE:
return the derivative wrt R of the sigma_R^2 profile at this R
INPUT:
R - Galactocentric radius (/ro)
log - if True, return the derivative of the log (default: False)
OUTPUT:
Sigma_R^2'(R) or (log Sigma_R^2(r) )'
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2011-03-24 - Written - Bovy (NYU) | [
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R - Galactocentric radius (/ro)
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s-leger/archipack | 5a6243bf1edf08a6b429661ce291dacb551e5f8a | pygeos/op_relate.py | python | RelateComputer.labelIsolatedNode | (self, node, targetIndex: int) | * Label an isolated node with its relationship to the target geometry. | * Label an isolated node with its relationship to the target geometry. | [
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"""
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"""
loc = self.ptLocator.locate(node.coord, self.arg[targetIndex].geom)
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redhat-imaging/imagefactory | 176f6e045e1df049d50f33a924653128d5ab8b27 | imgfac/rest/bottle.py | python | BaseTemplate.search | (cls, name, lookup=[]) | Search name in all directories specified in lookup.
First without, then with common extensions. Return first hit. | Search name in all directories specified in lookup.
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""" Search name in all directories specified in lookup.
First without, then with common extensions. Return first hit. """
if not lookup:
depr('The template lookup path list should not be empty.') #0.12
lookup = ['.']
if os.path.isabs(name) and os.path.isfile(name):
depr('Absolute template path names are deprecated.') #0.12
return os.path.abspath(name)
for spath in lookup:
spath = os.path.abspath(spath) + os.sep
fname = os.path.abspath(os.path.join(spath, name))
if not fname.startswith(spath): continue
if os.path.isfile(fname): return fname
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joerick/pyinstrument | d3c45164a385021f366c1081baec18a1a226a573 | pyinstrument/renderers/speedscope.py | python | SpeedscopeRenderer.render_frame | (self, frame: BaseFrame | None) | return events_array | Builds up a list of speedscope events that are used to populate the
"events" array in speedscope-formatted JSON.
This method has two notable side effects:
* it populates the self._frame_to_index dictionary that matches
speedscope frames with their positions in the "shared" array of
speedscope output; this dictionary will be used to write this
"shared" array in the render method
* it accumulates a running total of time elapsed by
accumulating the self_time spent in each pyinstrument frame;
this running total is used by speedscope events to construct
a flame chart. | Builds up a list of speedscope events that are used to populate the
"events" array in speedscope-formatted JSON. | [
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"""
Builds up a list of speedscope events that are used to populate the
"events" array in speedscope-formatted JSON.
This method has two notable side effects:
* it populates the self._frame_to_index dictionary that matches
speedscope frames with their positions in the "shared" array of
speedscope output; this dictionary will be used to write this
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* it accumulates a running total of time elapsed by
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"""
# if frame is None, recursion bottoms out; no event frames
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sframe = SpeedscopeFrame(frame.function, frame.file_path, frame.line_no)
if sframe not in self._frame_to_index:
self._frame_to_index[sframe] = len(self._frame_to_index)
# Get the frame index and add a speedscope event corresponding
# to opening a stack frame.
sframe_index = self._frame_to_index[sframe]
open_event = SpeedscopeEvent(SpeedscopeEventType.OPEN, self._event_time, sframe_index)
events_array: list[SpeedscopeEvent] = [open_event]
# Add stack frame open and close events for all child frames
# of this frame.
for child in frame.children:
events_array.extend(self.render_frame(child))
# Update event time for closing this stack frame.
#
# If number of frames approaches 1e16 * desired accuracy
# level, consider using Neumaier-Kahan summation; improves
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# summation quadruples operation count of sum, and Neumaier
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# summation isn't an option here because a running total is
# needed.
self._event_time += frame.self_time
# Add event closing this stack frame.
close_event = SpeedscopeEvent(SpeedscopeEventType.CLOSE, self._event_time, sframe_index)
events_array.append(close_event)
return events_array | [
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|
NVIDIA/DeepLearningExamples | 589604d49e016cd9ef4525f7abcc9c7b826cfc5e | PyTorch/Translation/Transformer/fairseq/data/dictionary.py | python | Dictionary.update | (self, new_dict) | Updates counts from new dictionary. | Updates counts from new dictionary. | [
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] | def update(self, new_dict):
"""Updates counts from new dictionary."""
for word in new_dict.symbols:
idx2 = new_dict.indices[word]
if word in self.indices:
idx = self.indices[word]
self.count[idx] = self.count[idx] + new_dict.count[idx2]
else:
idx = len(self.symbols)
self.indices[word] = idx
self.symbols.append(word)
self.count.append(new_dict.count[idx2]) | [
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||
feisuzhu/thbattle | ac0dee1b2d86de7664289cf432b157ef25427ba1 | src/pyglet/font/base.py | python | Glyph.draw_quad_vertices | (self) | Debug method.
Use the higher level APIs for performance and kerning. | Debug method. | [
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] | def draw_quad_vertices(self):
'''Debug method.
Use the higher level APIs for performance and kerning.
'''
glTexCoord3f(*self.tex_coords[:3])
glVertex2f(self.vertices[0], self.vertices[1])
glTexCoord3f(*self.tex_coords[3:6])
glVertex2f(self.vertices[2], self.vertices[1])
glTexCoord3f(*self.tex_coords[6:9])
glVertex2f(self.vertices[2], self.vertices[3])
glTexCoord3f(*self.tex_coords[9:12])
glVertex2f(self.vertices[0], self.vertices[3]) | [
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||
IdentityPython/pysaml2 | 6badb32d212257bd83ffcc816f9b625f68281b47 | src/saml2/authn_context/ppt.py | python | identification_type__from_string | (xml_string) | return saml2.create_class_from_xml_string(IdentificationType_, xml_string) | [] | def identification_type__from_string(xml_string):
return saml2.create_class_from_xml_string(IdentificationType_, xml_string) | [
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|||
aws/sagemaker-tensorflow-training-toolkit | 38db16c9d3fcbda6f9d8bc31261398fb4617bfc8 | benchmarks/horovod-resnet/train_imagenet_resnet_hvd.py | python | LayerBuilder.dense_linear | (self, inputs, units, **kwargs) | return tf.layers.dense(inputs, units, activation=None) | [] | def dense_linear(self, inputs, units, **kwargs):
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|||
openembedded/bitbake | 98407efc8c670abd71d3fa88ec3776ee9b5c38f3 | lib/bb/pysh/pyshyacc.py | python | parse | (input, eof=False, debug=False) | return yacc.parse(lexer=lexer, debug=debug), remaining | Parse a whole script at once and return the generated AST and unconsumed
data in a tuple.
NOTE: eof is probably meaningless for now, the parser being unable to work
in pull mode. It should be set to True. | Parse a whole script at once and return the generated AST and unconsumed
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NOTE: eof is probably meaningless for now, the parser being unable to work
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"""Parse a whole script at once and return the generated AST and unconsumed
data in a tuple.
NOTE: eof is probably meaningless for now, the parser being unable to work
in pull mode. It should be set to True.
"""
lexer = pyshlex.PLYLexer()
remaining = lexer.add(input, eof)
if lexer.is_empty():
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if debug:
debug = 2
return yacc.parse(lexer=lexer, debug=debug), remaining | [
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|
rndusr/stig | 334f03e2e3eda7c1856dd5489f0265a47b9861b6 | stig/client/filters/utils.py | python | _either_past_or_future | (item_value, user_value) | return item_value_in_future == user_value_in_future | Return True if `item_value` and `user_value` are equal, both in the past or
both in the future, False otherwise | Return True if `item_value` and `user_value` are equal, both in the past or
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"""
Return True if `item_value` and `user_value` are equal, both in the past or
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"""
type_item_value = type(item_value)
type_user_value = type(user_value)
if type_user_value is Timestamp:
user_value_in_future = user_value.in_future
elif type_user_value is Timedelta:
user_value_in_future = user_value > 0
if type_item_value is Timestamp:
item_value_in_future = item_value.in_future
elif type_item_value is Timedelta:
item_value_in_future = item_value > 0
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|
python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/idlelib/config.py | python | IdleConf.__GetRawExtensionKeys | (self,extensionName) | return extKeys | Return dict {configurable extensionName event : keybinding list}.
Events come from default config extension_cfgBindings section.
Keybindings list come from the splitting of GetOption, which
tries user config before default config. | Return dict {configurable extensionName event : keybinding list}. | [
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] | def __GetRawExtensionKeys(self,extensionName):
"""Return dict {configurable extensionName event : keybinding list}.
Events come from default config extension_cfgBindings section.
Keybindings list come from the splitting of GetOption, which
tries user config before default config.
"""
keysName = extensionName+'_cfgBindings'
extKeys = {}
if self.defaultCfg['extensions'].has_section(keysName):
eventNames = self.defaultCfg['extensions'].GetOptionList(keysName)
for eventName in eventNames:
binding = self.GetOption(
'extensions', keysName, eventName, default='').split()
event = '<<' + eventName + '>>'
extKeys[event] = binding
return extKeys | [
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|
IBM/lale | b4d6829c143a4735b06083a0e6c70d2cca244162 | lale/lib/lale/observing.py | python | observe | (f) | return wrapper | [] | def observe(f):
@wraps(f)
def wrapper(self, *args, **kwds):
name = f.__name__
self.startObserving(name, *args, **kwds)
try:
ret = f(self, *args, **kwds)
self.endObserving(name, ret)
except BaseException as e:
self.failObserving(name, e)
raise
return ret
return wrapper | [
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|||
emmetio/livestyle-sublime-old | c42833c046e9b2f53ebce3df3aa926528f5a33b5 | tornado/web.py | python | TemplateModule._get_resources | (self, key) | return (r[key] for r in self._resource_list if key in r) | [] | def _get_resources(self, key):
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|||
pcyin/NL2code | f9732f1f5caafa73a0f767cc4f5ce9f5961c46d6 | lang/py/parse.py | python | parse | (code) | return tree | parse a python code into a tree structure
code -> AST tree -> AST tree to internal tree structure | parse a python code into a tree structure
code -> AST tree -> AST tree to internal tree structure | [
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"""
parse a python code into a tree structure
code -> AST tree -> AST tree to internal tree structure
"""
code = canonicalize_code(code)
py_ast = ast.parse(code)
tree = python_ast_to_parse_tree(py_ast.body[0])
tree = add_root(tree)
return tree | [
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|
JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/lockfile/symlinklockfile.py | python | SymlinkLockFile.release | (self) | [] | def release(self):
if not self.is_locked():
raise NotLocked("%s is not locked" % self.path)
elif not self.i_am_locking():
raise NotMyLock("%s is locked, but not by me" % self.path)
os.unlink(self.lock_file) | [
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||||
wbond/asn1crypto | 9ae350f212532dfee7f185f6b3eda24753249cf3 | asn1crypto/core.py | python | OctetString.set | (self, value) | Sets the value of the object
:param value:
A byte string | Sets the value of the object | [
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] | def set(self, value):
"""
Sets the value of the object
:param value:
A byte string
"""
if not isinstance(value, byte_cls):
raise TypeError(unwrap(
'''
%s value must be a byte string, not %s
''',
type_name(self),
type_name(value)
))
self._bytes = value
self.contents = value
self._header = None
if self._indefinite:
self._indefinite = False
self.method = 0
if self._trailer != b'':
self._trailer = b'' | [
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||
eriklindernoren/PyTorch-GAN | 36d3c77e5ff20ebe0aeefd322326a134a279b93e | implementations/munit/models.py | python | MultiDiscriminator.compute_loss | (self, x, gt) | return loss | Computes the MSE between model output and scalar gt | Computes the MSE between model output and scalar gt | [
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"""Computes the MSE between model output and scalar gt"""
loss = sum([torch.mean((out - gt) ** 2) for out in self.forward(x)])
return loss | [
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|
GraylinKim/sc2reader | d69feb4e0be597581040588193579d29e8241431 | sc2reader/decoders.py | python | ByteDecoder.__init__ | (self, contents, endian) | Accepts both strings and files implementing ``read()`` and
decodes them in the specified endian format. | Accepts both strings and files implementing ``read()`` and
decodes them in the specified endian format. | [
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""" Accepts both strings and files implementing ``read()`` and
decodes them in the specified endian format.
"""
if hasattr(contents, 'read'):
self._contents = contents.read()
else:
self._contents = contents
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self.length = len(self._contents)
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self._unpack_bytes = lambda bytes: bytes if self.endian == '>' else bytes[::-1] | [
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||
aws-samples/aws-kube-codesuite | ab4e5ce45416b83bffb947ab8d234df5437f4fca | src/kubernetes/client/apis/authorization_v1beta1_api.py | python | AuthorizationV1beta1Api.create_subject_access_review_with_http_info | (self, body, **kwargs) | return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='V1beta1SubjectAccessReview',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats) | create a SubjectAccessReview
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.create_subject_access_review_with_http_info(body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param V1beta1SubjectAccessReview body: (required)
:param str pretty: If 'true', then the output is pretty printed.
:return: V1beta1SubjectAccessReview
If the method is called asynchronously,
returns the request thread. | create a SubjectAccessReview
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.create_subject_access_review_with_http_info(body, callback=callback_function) | [
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"""
create a SubjectAccessReview
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.create_subject_access_review_with_http_info(body, callback=callback_function)
:param callback function: The callback function
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:param V1beta1SubjectAccessReview body: (required)
:param str pretty: If 'true', then the output is pretty printed.
:return: V1beta1SubjectAccessReview
If the method is called asynchronously,
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"""
all_params = ['body', 'pretty']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method create_subject_access_review" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'body' is set
if ('body' not in params) or (params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `create_subject_access_review`")
collection_formats = {}
resource_path = '/apis/authorization.k8s.io/v1beta1/subjectaccessreviews'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'pretty' in params:
query_params['pretty'] = params['pretty']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/yaml', 'application/vnd.kubernetes.protobuf'])
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['*/*'])
# Authentication setting
auth_settings = ['BearerToken']
return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='V1beta1SubjectAccessReview',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
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|
hyperspy/hyperspy | 1ffb3fab33e607045a37f30c1463350b72617e10 | hyperspy/events.py | python | Events.__delattr__ | (self, name) | Magic to enable having `Event`s as attributes, and keeping them
separate from other attributes.
Deletes attribute from self._events if present, otherwise delete
attribute in normal way. | Magic to enable having `Event`s as attributes, and keeping them
separate from other attributes. | [
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"""
Magic to enable having `Event`s as attributes, and keeping them
separate from other attributes.
Deletes attribute from self._events if present, otherwise delete
attribute in normal way.
"""
if name in self._events:
del self._events[name]
self._update_doc()
else:
super(Events, self).__delattr__(name) | [
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||
google/turbinia | 4559d4af9267762a8995cfc415099a80a22ee4d3 | turbinia/workers/analysis/wordpress_creds.py | python | WordpressCredsAnalysisTask._analyse_wordpress_creds | (self, creds, hashnames, timeout=300) | return (report, priority, summary) | Attempt to brute force extracted Wordpress credentials.
Args:
creds (list): List of strings containing raw extracted credentials
hashnames (dict): Dict mapping hash back to username for convenience.
timeout (int): How long to spend cracking.
Returns:
Tuple(
report_text(str): The report data
report_priority(int): The priority of the report (0 - 100)
summary(str): A summary of the report (used for task status)
) | Attempt to brute force extracted Wordpress credentials. | [
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] | def _analyse_wordpress_creds(self, creds, hashnames, timeout=300):
"""Attempt to brute force extracted Wordpress credentials.
Args:
creds (list): List of strings containing raw extracted credentials
hashnames (dict): Dict mapping hash back to username for convenience.
timeout (int): How long to spend cracking.
Returns:
Tuple(
report_text(str): The report data
report_priority(int): The priority of the report (0 - 100)
summary(str): A summary of the report (used for task status)
)
"""
report = []
summary = 'No weak passwords found'
priority = Priority.LOW
# 1000 is "phpass"
weak_passwords = bruteforce_password_hashes(
creds, tmp_dir=self.tmp_dir, timeout=timeout,
extra_args='--username -m 400')
if weak_passwords:
priority = Priority.CRITICAL
summary = 'Wordpress analysis found {0:d} weak password(s)'.format(
len(weak_passwords))
report.insert(0, fmt.heading4(fmt.bold(summary)))
line = '{0:n} weak password(s) found:'.format(len(weak_passwords))
report.append(fmt.bullet(fmt.bold(line)))
for password_hash, plaintext in weak_passwords:
if password_hash in hashnames:
line = """User '{0:s}' with password '{1:s}'""".format(
hashnames[password_hash], plaintext)
report.append(fmt.bullet(line, level=2))
report = '\n'.join(report)
return (report, priority, summary) | [
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|
isce-framework/isce2 | 0e5114a8bede3caf1d533d98e44dfe4b983e3f48 | contrib/stack/topsStack/VRTManager.py | python | VRTConstructor.addBurst | (self, burst, infile, yoff, xoff, band=1, validOnly=True) | Add one burst to the VRT. | Add one burst to the VRT. | [
"Add",
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] | def addBurst(self, burst, infile, yoff, xoff, band=1, validOnly=True):
'''
Add one burst to the VRT.
'''
tysize = burst.numberOfLines
txsize = burst.numberOfSamples
if validOnly:
tyoff = int(burst.firstValidLine)
txoff = int(burst.firstValidSample)
wysize = int(burst.numValidLines)
wxsize = int(burst.numValidSamples)
fyoff = int(yoff + burst.firstValidLine)
fxoff = int(xoff + burst.firstValidSample)
else:
tyoff = 0
txoff = 0
wysize = tysize
wxsize = txsize
fyoff = int(yoff)
fxoff = int(xoff)
tmpl = ''' <SimpleSource>
<SourceFilename relativeToVRT="1">{tiff}</SourceFilename>
<SourceBand>{band}</SourceBand>
<SourceProperties RasterXSize="{txsize}" RasterYSize="{tysize}" DataType="{dtype}"/>
<SrcRect xOff="{txoff}" yOff="{tyoff}" xSize="{wxsize}" ySize="{wysize}"/>
<DstRect xOff="{fxoff}" yOff="{fyoff}" xSize="{wxsize}" ySize="{wysize}"/>
</SimpleSource>
'''
self.vrt += tmpl.format( tyoff=tyoff, txoff=txoff,
fyoff=fyoff, fxoff=fxoff,
wxsize=wxsize, wysize=wysize,
tiff=infile+'.vrt', dtype=self.dtype,
tysize=tysize, txsize=txsize,
band=band) | [
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||
rwth-i6/returnn | f2d718a197a280b0d5f0fd91a7fcb8658560dddb | returnn/util/basic.py | python | hdf5_dimension | (filename, dimension) | return res | :param str filename:
:param str dimension:
:rtype: numpy.ndarray|int | :param str filename:
:param str dimension:
:rtype: numpy.ndarray|int | [
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] | def hdf5_dimension(filename, dimension):
"""
:param str filename:
:param str dimension:
:rtype: numpy.ndarray|int
"""
fin = h5py.File(filename, "r")
if '/' in dimension:
res = fin['/'.join(dimension.split('/')[:-1])].attrs[dimension.split('/')[-1]]
else:
res = fin.attrs[dimension]
fin.close()
return res | [
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|
spyder-ide/spyder | 55da47c032dfcf519600f67f8b30eab467f965e7 | spyder/widgets/reporterror.py | python | DescriptionWidget.keyPressEvent | (self, event) | Reimplemented Qt Method to avoid removing the header. | Reimplemented Qt Method to avoid removing the header. | [
"Reimplemented",
"Qt",
"Method",
"to",
"avoid",
"removing",
"the",
"header",
"."
] | def keyPressEvent(self, event):
"""Reimplemented Qt Method to avoid removing the header."""
event, text, key, ctrl, shift = restore_keyevent(event)
cursor_position = self.get_position('cursor')
if cursor_position < self.header_end_pos:
self.restrict_cursor_position(self.header_end_pos, 'eof')
elif key == Qt.Key_Backspace:
if self.has_selected_text():
self.remove_text()
elif self.header_end_pos == cursor_position:
return
else:
self.stdkey_backspace()
elif key == Qt.Key_X and ctrl:
self.cut()
else:
super().keyPressEvent(event) | [
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||
pandas-dev/pandas | 5ba7d714014ae8feaccc0dd4a98890828cf2832d | pandas/core/indexes/datetimes.py | python | bdate_range | (
start=None,
end=None,
periods: int | None = None,
freq="B",
tz=None,
normalize: bool = True,
name: Hashable = None,
weekmask=None,
holidays=None,
closed: lib.NoDefault = lib.no_default,
inclusive: str | None = None,
**kwargs,
) | return date_range(
start=start,
end=end,
periods=periods,
freq=freq,
tz=tz,
normalize=normalize,
name=name,
closed=closed,
inclusive=inclusive,
**kwargs,
) | Return a fixed frequency DatetimeIndex, with business day as the default
frequency.
Parameters
----------
start : str or datetime-like, default None
Left bound for generating dates.
end : str or datetime-like, default None
Right bound for generating dates.
periods : int, default None
Number of periods to generate.
freq : str or DateOffset, default 'B' (business daily)
Frequency strings can have multiples, e.g. '5H'.
tz : str or None
Time zone name for returning localized DatetimeIndex, for example
Asia/Beijing.
normalize : bool, default False
Normalize start/end dates to midnight before generating date range.
name : str, default None
Name of the resulting DatetimeIndex.
weekmask : str or None, default None
Weekmask of valid business days, passed to ``numpy.busdaycalendar``,
only used when custom frequency strings are passed. The default
value None is equivalent to 'Mon Tue Wed Thu Fri'.
holidays : list-like or None, default None
Dates to exclude from the set of valid business days, passed to
``numpy.busdaycalendar``, only used when custom frequency strings
are passed.
closed : str, default None
Make the interval closed with respect to the given frequency to
the 'left', 'right', or both sides (None).
.. deprecated:: 1.4.0
Argument `closed` has been deprecated to standardize boundary inputs.
Use `inclusive` instead, to set each bound as closed or open.
inclusive : {"both", "neither", "left", "right"}, default "both"
Include boundaries; Whether to set each bound as closed or open.
.. versionadded:: 1.4.0
**kwargs
For compatibility. Has no effect on the result.
Returns
-------
DatetimeIndex
Notes
-----
Of the four parameters: ``start``, ``end``, ``periods``, and ``freq``,
exactly three must be specified. Specifying ``freq`` is a requirement
for ``bdate_range``. Use ``date_range`` if specifying ``freq`` is not
desired.
To learn more about the frequency strings, please see `this link
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
Examples
--------
Note how the two weekend days are skipped in the result.
>>> pd.bdate_range(start='1/1/2018', end='1/08/2018')
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
'2018-01-05', '2018-01-08'],
dtype='datetime64[ns]', freq='B') | Return a fixed frequency DatetimeIndex, with business day as the default
frequency. | [
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"a",
"fixed",
"frequency",
"DatetimeIndex",
"with",
"business",
"day",
"as",
"the",
"default",
"frequency",
"."
] | def bdate_range(
start=None,
end=None,
periods: int | None = None,
freq="B",
tz=None,
normalize: bool = True,
name: Hashable = None,
weekmask=None,
holidays=None,
closed: lib.NoDefault = lib.no_default,
inclusive: str | None = None,
**kwargs,
) -> DatetimeIndex:
"""
Return a fixed frequency DatetimeIndex, with business day as the default
frequency.
Parameters
----------
start : str or datetime-like, default None
Left bound for generating dates.
end : str or datetime-like, default None
Right bound for generating dates.
periods : int, default None
Number of periods to generate.
freq : str or DateOffset, default 'B' (business daily)
Frequency strings can have multiples, e.g. '5H'.
tz : str or None
Time zone name for returning localized DatetimeIndex, for example
Asia/Beijing.
normalize : bool, default False
Normalize start/end dates to midnight before generating date range.
name : str, default None
Name of the resulting DatetimeIndex.
weekmask : str or None, default None
Weekmask of valid business days, passed to ``numpy.busdaycalendar``,
only used when custom frequency strings are passed. The default
value None is equivalent to 'Mon Tue Wed Thu Fri'.
holidays : list-like or None, default None
Dates to exclude from the set of valid business days, passed to
``numpy.busdaycalendar``, only used when custom frequency strings
are passed.
closed : str, default None
Make the interval closed with respect to the given frequency to
the 'left', 'right', or both sides (None).
.. deprecated:: 1.4.0
Argument `closed` has been deprecated to standardize boundary inputs.
Use `inclusive` instead, to set each bound as closed or open.
inclusive : {"both", "neither", "left", "right"}, default "both"
Include boundaries; Whether to set each bound as closed or open.
.. versionadded:: 1.4.0
**kwargs
For compatibility. Has no effect on the result.
Returns
-------
DatetimeIndex
Notes
-----
Of the four parameters: ``start``, ``end``, ``periods``, and ``freq``,
exactly three must be specified. Specifying ``freq`` is a requirement
for ``bdate_range``. Use ``date_range`` if specifying ``freq`` is not
desired.
To learn more about the frequency strings, please see `this link
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
Examples
--------
Note how the two weekend days are skipped in the result.
>>> pd.bdate_range(start='1/1/2018', end='1/08/2018')
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
'2018-01-05', '2018-01-08'],
dtype='datetime64[ns]', freq='B')
"""
if freq is None:
msg = "freq must be specified for bdate_range; use date_range instead"
raise TypeError(msg)
if isinstance(freq, str) and freq.startswith("C"):
try:
weekmask = weekmask or "Mon Tue Wed Thu Fri"
freq = prefix_mapping[freq](holidays=holidays, weekmask=weekmask)
except (KeyError, TypeError) as err:
msg = f"invalid custom frequency string: {freq}"
raise ValueError(msg) from err
elif holidays or weekmask:
msg = (
"a custom frequency string is required when holidays or "
f"weekmask are passed, got frequency {freq}"
)
raise ValueError(msg)
return date_range(
start=start,
end=end,
periods=periods,
freq=freq,
tz=tz,
normalize=normalize,
name=name,
closed=closed,
inclusive=inclusive,
**kwargs,
) | [
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|
learnables/learn2learn | c664e3c8643efb1cc1cf7bb11668843e2ee8ebbe | learn2learn/vision/benchmarks/fc100_benchmark.py | python | fc100_tasksets | (
train_ways=5,
train_samples=10,
test_ways=5,
test_samples=10,
root='~/data',
device=None,
**kwargs,
) | return _datasets, _transforms | Tasksets for FC100 benchmarks. | Tasksets for FC100 benchmarks. | [
"Tasksets",
"for",
"FC100",
"benchmarks",
"."
] | def fc100_tasksets(
train_ways=5,
train_samples=10,
test_ways=5,
test_samples=10,
root='~/data',
device=None,
**kwargs,
):
"""Tasksets for FC100 benchmarks."""
data_transform = tv.transforms.ToTensor()
train_dataset = l2l.vision.datasets.FC100(root=root,
transform=data_transform,
mode='train',
download=True)
valid_dataset = l2l.vision.datasets.FC100(root=root,
transform=data_transform,
mode='validation',
download=True)
test_dataset = l2l.vision.datasets.FC100(root=root,
transform=data_transform,
mode='test',
download=True)
if device is not None:
train_dataset = l2l.data.OnDeviceDataset(
dataset=train_dataset,
device=device,
)
valid_dataset = l2l.data.OnDeviceDataset(
dataset=valid_dataset,
device=device,
)
test_dataset = l2l.data.OnDeviceDataset(
dataset=test_dataset,
device=device,
)
train_dataset = l2l.data.MetaDataset(train_dataset)
valid_dataset = l2l.data.MetaDataset(valid_dataset)
test_dataset = l2l.data.MetaDataset(test_dataset)
train_transforms = [
NWays(train_dataset, train_ways),
KShots(train_dataset, train_samples),
LoadData(train_dataset),
RemapLabels(train_dataset),
ConsecutiveLabels(train_dataset),
]
valid_transforms = [
NWays(valid_dataset, test_ways),
KShots(valid_dataset, test_samples),
LoadData(valid_dataset),
ConsecutiveLabels(valid_dataset),
RemapLabels(valid_dataset),
]
test_transforms = [
NWays(test_dataset, test_ways),
KShots(test_dataset, test_samples),
LoadData(test_dataset),
RemapLabels(test_dataset),
ConsecutiveLabels(test_dataset),
]
_datasets = (train_dataset, valid_dataset, test_dataset)
_transforms = (train_transforms, valid_transforms, test_transforms)
return _datasets, _transforms | [
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|
kupferlauncher/kupfer | 1c1e9bcbce05a82f503f68f8b3955c20b02639b3 | oldplugins/vim/plugin.py | python | stop_plugin_service | (plugin_id) | Return True if it was running and was stopped | Return True if it was running and was stopped | [
"Return",
"True",
"if",
"it",
"was",
"running",
"and",
"was",
"stopped"
] | def stop_plugin_service(plugin_id):
"""
Return True if it was running and was stopped
"""
plug_iface = get_plugin_service_obj(plugin_id, activate=False)
if plug_iface:
plug_iface.Exit(reply_handler=_dummy_handler,
error_handler=_dummy_handler) | [
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||
HuangYG123/CurricularFace | 68c8727fb7cd2243ecbfd7e09c35efc87c6e2de4 | backbone/model_irse.py | python | IR_101 | (input_size) | return model | Constructs a ir-101 model. | Constructs a ir-101 model. | [
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"-",
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"model",
"."
] | def IR_101(input_size):
"""Constructs a ir-101 model.
"""
model = Backbone(input_size, 100, 'ir')
return model | [
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|
omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib/site-packages/sqlalchemy/ext/declarative/api.py | python | declarative_base | (bind=None, metadata=None, mapper=None, cls=object,
name='Base', constructor=_declarative_constructor,
class_registry=None,
metaclass=DeclarativeMeta) | return metaclass(name, bases, class_dict) | Construct a base class for declarative class definitions.
The new base class will be given a metaclass that produces
appropriate :class:`~sqlalchemy.schema.Table` objects and makes
the appropriate :func:`~sqlalchemy.orm.mapper` calls based on the
information provided declaratively in the class and any subclasses
of the class.
:param bind: An optional
:class:`~sqlalchemy.engine.Connectable`, will be assigned
the ``bind`` attribute on the :class:`~sqlalchemy.schema.MetaData`
instance.
:param metadata:
An optional :class:`~sqlalchemy.schema.MetaData` instance. All
:class:`~sqlalchemy.schema.Table` objects implicitly declared by
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:class:`~sqlalchemy.schema.MetaData` instance will be available via the
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:param mapper:
An optional callable, defaults to :func:`~sqlalchemy.orm.mapper`. Will
be used to map subclasses to their Tables.
:param cls:
Defaults to :class:`object`. A type to use as the base for the generated
declarative base class. May be a class or tuple of classes.
:param name:
Defaults to ``Base``. The display name for the generated
class. Customizing this is not required, but can improve clarity in
tracebacks and debugging.
:param constructor:
Defaults to
:func:`~sqlalchemy.ext.declarative._declarative_constructor`, an
__init__ implementation that assigns \**kwargs for declared
fields and relationships to an instance. If ``None`` is supplied,
no __init__ will be provided and construction will fall back to
cls.__init__ by way of the normal Python semantics.
:param class_registry: optional dictionary that will serve as the
registry of class names-> mapped classes when string names
are used to identify classes inside of :func:`.relationship`
and others. Allows two or more declarative base classes
to share the same registry of class names for simplified
inter-base relationships.
:param metaclass:
Defaults to :class:`.DeclarativeMeta`. A metaclass or __metaclass__
compatible callable to use as the meta type of the generated
declarative base class.
.. seealso::
:func:`.as_declarative` | Construct a base class for declarative class definitions. | [
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name='Base', constructor=_declarative_constructor,
class_registry=None,
metaclass=DeclarativeMeta):
"""Construct a base class for declarative class definitions.
The new base class will be given a metaclass that produces
appropriate :class:`~sqlalchemy.schema.Table` objects and makes
the appropriate :func:`~sqlalchemy.orm.mapper` calls based on the
information provided declaratively in the class and any subclasses
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Defaults to ``Base``. The display name for the generated
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:param constructor:
Defaults to
:func:`~sqlalchemy.ext.declarative._declarative_constructor`, an
__init__ implementation that assigns \**kwargs for declared
fields and relationships to an instance. If ``None`` is supplied,
no __init__ will be provided and construction will fall back to
cls.__init__ by way of the normal Python semantics.
:param class_registry: optional dictionary that will serve as the
registry of class names-> mapped classes when string names
are used to identify classes inside of :func:`.relationship`
and others. Allows two or more declarative base classes
to share the same registry of class names for simplified
inter-base relationships.
:param metaclass:
Defaults to :class:`.DeclarativeMeta`. A metaclass or __metaclass__
compatible callable to use as the meta type of the generated
declarative base class.
.. seealso::
:func:`.as_declarative`
"""
lcl_metadata = metadata or MetaData()
if bind:
lcl_metadata.bind = bind
if class_registry is None:
class_registry = weakref.WeakValueDictionary()
bases = not isinstance(cls, tuple) and (cls,) or cls
class_dict = dict(_decl_class_registry=class_registry,
metadata=lcl_metadata)
if constructor:
class_dict['__init__'] = constructor
if mapper:
class_dict['__mapper_cls__'] = mapper
return metaclass(name, bases, class_dict) | [
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|
ghostop14/sparrow-wifi | 4b8289773ea4304872062f65a6ffc9352612b08e | plugins/falconwifi.py | python | FalconWirelessEngine.testWEPCapture | (apMacAddr, capFile) | [] | def testWEPCapture(apMacAddr, capFile):
# aircrack-ng -a2 -b D8:EB:97:2F:DD:CE -w /opt/wordlists/TopPasswords3-2.txt falconcap-01.cap
params = ['aircrack-ng','-f','4','-1','-b', apMacAddr, capFile]
result = subprocess.run(params, stdout=subprocess.PIPE,stderr=subprocess.DEVNULL)
testResult = result.stdout.decode('ASCII')
iv=re.compile(' +([0-9]+) IVs')
regexresult=iv.search(testResult)
if regexresult:
try:
ivstr = regexresult.group(1)
ivstr = ivstr.replace('IVs', '')
ivstr = ivstr.replace(' ', '')
ivcount = int(ivstr)
except:
ivcount = 0
else:
ivcount = 0
# Please specify a dictionary comes back when aircrack-ng recognizes it as WPA, not wep,
# No matching network found means you have the wrong bssid or a packet hasn't been seen yet
if result.returncode == 0 and 'KEY FOUND' in testResult:
passwords = []
p = re.compile('KEY FOUND\! \[(.*?)\].*')
lines = testResult.split('\n')
for curLine in lines:
try:
if 'KEY FOUND' in curLine:
fieldValue = p.search(curLine).group(1)
else:
fieldValue = ""
except:
fieldValue = ""
if len(fieldValue) > 0:
fieldValue = fieldValue.strip()
if fieldValue not in passwords:
passwords.append(fieldValue)
return True, passwords, ivcount
else:
return False, [], ivcount | [
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||||
EtienneCmb/visbrain | b599038e095919dc193b12d5e502d127de7d03c9 | visbrain/gui/brain/interface/ui_elements/ui_objects.py | python | UiObjects._fcn_obj_name | (self) | Change object name. | Change object name. | [
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"object",
"name",
"."
] | def _fcn_obj_name(self):
"""Change object name."""
idx_type = self._obj_type_lst.currentIndex()
if idx_type == 4: # Sources
fcn = self._sources_to_gui
elif idx_type == 5: # Connectivity
fcn = self._connect_to_gui
elif idx_type == 6: # time-series
fcn = self._ts_to_gui
elif idx_type == 7: # pictures
fcn = self._pic_to_gui
elif idx_type == 8: # vectors
fcn = self._vec_to_gui
# if idx_type > 4:
self._obj_run_method = False
fcn()
self._obj_run_method = True | [
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||
aws-cloudformation/cfn-lint | 16df5d0ca0d8ebcf9330ebea701e83d883b47217 | src/cfnlint/rules/resources/elb/Elb.py | python | Elb.__init__ | (self) | Init | Init | [
"Init"
] | def __init__(self):
""" Init """
super(Elb, self).__init__()
self.resource_property_types = ['AWS::ElasticLoadBalancingV2::LoadBalancer'] | [
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||
chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pip/_vendor/lockfile/__init__.py | python | SQLiteFileLock | (*args, **kwds) | return _fl_helper(sqlitelockfile.SQLiteLockFile, "lockfile.sqlitelockfile",
*args, **kwds) | Factory function provided for backwards compatibility.
Do not use in new code. Instead, import SQLiteLockFile from the
lockfile.mkdirlockfile module. | Factory function provided for backwards compatibility. | [
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] | def SQLiteFileLock(*args, **kwds):
"""Factory function provided for backwards compatibility.
Do not use in new code. Instead, import SQLiteLockFile from the
lockfile.mkdirlockfile module.
"""
from . import sqlitelockfile
return _fl_helper(sqlitelockfile.SQLiteLockFile, "lockfile.sqlitelockfile",
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|
donnemartin/viz | dc1ed0690ed3d8cb515c9dbac43bafc59a704789 | site/fabfile.py | python | rebuild | () | `clean` then `build` | `clean` then `build` | [
"clean",
"then",
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] | def rebuild():
"""`clean` then `build`"""
clean()
build() | [
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||
jimmysong/pb-exercises | c5e64075c47503a40063aa836c06a452af14246d | session3/answers.py | python | parse_txin | (cls, s) | return cls(prev_tx, prev_index, script_sig, sequence) | Takes a byte stream and parses the tx_input at the start
return a TxIn object | Takes a byte stream and parses the tx_input at the start
return a TxIn object | [
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'''Takes a byte stream and parses the tx_input at the start
return a TxIn object
'''
prev_tx = s.read(32)[::-1]
prev_index = little_endian_to_int(s.read(4))
script_sig = Script.parse(s)
sequence = little_endian_to_int(s.read(4))
return cls(prev_tx, prev_index, script_sig, sequence) | [
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|
KoreLogicSecurity/mastiff | 04d569e4fa59513572e77c74b049cad82f9b0310 | mastiff/core.py | python | Mastiff.__del__ | (self) | Class destructor. | Class destructor. | [
"Class",
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] | def __del__(self):
"""
Class destructor.
"""
# Close down all logging file handles so we don't have any open file descriptors
log = logging.getLogger("Mastiff")
handles = list(log.handlers)
for file_handle in handles:
log.removeHandler(file_handle)
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||
TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tiia/v20190529/models.py | python | RecognizeCarRequest.__init__ | (self) | r"""
:param ImageUrl: 图片URL地址。
图片限制：
• 图片格式：PNG、JPG、JPEG。
• 图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
建议：
• 图片像素：大于50*50像素，否则影响识别效果；
• 长宽比：长边：短边<5；
接口响应时间会受到图片下载时间的影响，建议使用更可靠的存储服务，推荐将图片存储在腾讯云COS。
:type ImageUrl: str
:param ImageBase64: 图片经过base64编码的内容。最大不超过4M。与ImageUrl同时存在时优先使用ImageUrl字段。
**注意：图片需要base64编码，并且要去掉编码头部。**
支持的图片格式：PNG、JPG、JPEG、BMP，暂不支持GIF格式。支持的图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
:type ImageBase64: str | r"""
:param ImageUrl: 图片URL地址。
图片限制：
• 图片格式：PNG、JPG、JPEG。
• 图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
建议：
• 图片像素：大于50*50像素，否则影响识别效果；
• 长宽比：长边：短边<5；
接口响应时间会受到图片下载时间的影响，建议使用更可靠的存储服务，推荐将图片存储在腾讯云COS。
:type ImageUrl: str
:param ImageBase64: 图片经过base64编码的内容。最大不超过4M。与ImageUrl同时存在时优先使用ImageUrl字段。
**注意：图片需要base64编码，并且要去掉编码头部。**
支持的图片格式：PNG、JPG、JPEG、BMP，暂不支持GIF格式。支持的图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
:type ImageBase64: str | [
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r"""
:param ImageUrl: 图片URL地址。
图片限制：
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• 图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
建议：
• 图片像素：大于50*50像素，否则影响识别效果；
• 长宽比：长边：短边<5；
接口响应时间会受到图片下载时间的影响，建议使用更可靠的存储服务，推荐将图片存储在腾讯云COS。
:type ImageUrl: str
:param ImageBase64: 图片经过base64编码的内容。最大不超过4M。与ImageUrl同时存在时优先使用ImageUrl字段。
**注意：图片需要base64编码，并且要去掉编码头部。**
支持的图片格式：PNG、JPG、JPEG、BMP，暂不支持GIF格式。支持的图片大小：所下载图片经Base64编码后不超过4M。图片下载时间不超过3秒。
:type ImageBase64: str
"""
self.ImageUrl = None
self.ImageBase64 = None | [
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||
qutebrowser/qutebrowser | 3a2aaaacbf97f4bf0c72463f3da94ed2822a5442 | qutebrowser/browser/history.py | python | debug_dump_history | (dest) | Dump the history to a file in the old pre-SQL format.
Args:
dest: Where to write the file to. | Dump the history to a file in the old pre-SQL format. | [
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"""Dump the history to a file in the old pre-SQL format.
Args:
dest: Where to write the file to.
"""
dest = os.path.expanduser(dest)
lines = (f'{int(x.atime)}{"-r" * x.redirect} {x.url} {x.title}'
for x in web_history.select(sort_by='atime', sort_order='asc'))
try:
with open(dest, 'w', encoding='utf-8') as f:
f.write('\n'.join(lines))
message.info(f"Dumped history to {dest}")
except OSError as e:
raise cmdutils.CommandError(f'Could not write history: {e}') | [
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||
1012598167/flask_mongodb_game | 60c7e0351586656ec38f851592886338e50b4110 | python_flask/venv/Lib/site-packages/itsdangerous/_compat.py | python | _constant_time_compare | (val1, val2) | return result == 0 | Return ``True`` if the two strings are equal, ``False``
otherwise.
The time taken is independent of the number of characters that
match. Do not use this function for anything else than comparision
with known length targets.
This is should be implemented in C in order to get it completely
right.
This is an alias of :func:`hmac.compare_digest` on Python>=2.7,3.3. | Return ``True`` if the two strings are equal, ``False``
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] | def _constant_time_compare(val1, val2):
"""Return ``True`` if the two strings are equal, ``False``
otherwise.
The time taken is independent of the number of characters that
match. Do not use this function for anything else than comparision
with known length targets.
This is should be implemented in C in order to get it completely
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This is an alias of :func:`hmac.compare_digest` on Python>=2.7,3.3.
"""
len_eq = len(val1) == len(val2)
if len_eq:
result = 0
left = val1
else:
result = 1
left = val2
for x, y in izip(bytearray(left), bytearray(val2)):
result |= x ^ y
return result == 0 | [
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|
openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/twisted/twisted/protocols/tls.py | python | TLSMemoryBIOProtocol.getHandle | (self) | return self._tlsConnection | Return the L{OpenSSL.SSL.Connection} object being used to encrypt and
decrypt this connection.
This is done for the benefit of L{twisted.internet.ssl.Certificate}'s
C{peerFromTransport} and C{hostFromTransport} methods only. A
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C{peerFromTransport} and C{hostFromTransport} methods only. A
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|
tav/pylibs | 3c16b843681f54130ee6a022275289cadb2f2a69 | paramiko/sftp_file.py | python | SFTPFile._check_exception | (self) | if there's a saved exception, raise & clear it | if there's a saved exception, raise & clear it | [
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self._saved_exception = None
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||
scikit-learn/scikit-learn | 1d1aadd0711b87d2a11c80aad15df6f8cf156712 | sklearn/_loss/glm_distribution.py | python | ExponentialDispersionModel.unit_variance | (self, y_pred) | r"""Compute the unit variance function.
The unit variance :math:`v(y_\textrm{pred})` determines the variance as
a function of the mean :math:`y_\textrm{pred}` by
:math:`\mathrm{Var}[Y_i] = \phi/s_i*v(y_\textrm{pred}_i)`.
It can also be derived from the unit deviance
:math:`d(y,y_\textrm{pred})` as
.. math:: v(y_\textrm{pred}) = \frac{2}{
\frac{\partial^2 d(y,y_\textrm{pred})}{
\partialy_\textrm{pred}^2}}\big|_{y=y_\textrm{pred}}
See also :func:`variance`.
Parameters
----------
y_pred : array of shape (n_samples,)
Predicted mean. | r"""Compute the unit variance function. | [
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] | def unit_variance(self, y_pred):
r"""Compute the unit variance function.
The unit variance :math:`v(y_\textrm{pred})` determines the variance as
a function of the mean :math:`y_\textrm{pred}` by
:math:`\mathrm{Var}[Y_i] = \phi/s_i*v(y_\textrm{pred}_i)`.
It can also be derived from the unit deviance
:math:`d(y,y_\textrm{pred})` as
.. math:: v(y_\textrm{pred}) = \frac{2}{
\frac{\partial^2 d(y,y_\textrm{pred})}{
\partialy_\textrm{pred}^2}}\big|_{y=y_\textrm{pred}}
See also :func:`variance`.
Parameters
----------
y_pred : array of shape (n_samples,)
Predicted mean.
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||
jstockwin/py-pdf-parser | 29d4656799876b35d95c82fd1230a2a92d24d6a6 | py_pdf_parser/components.py | python | PDFElement.font | (self) | return self.__font | The name and size of the font, separated by a comma with no spaces.
This will be taken from the pdf itself, using the first character in the
element.
If you have provided a font_mapping, this is the string you should map. If
the string is mapped in your font_mapping then the mapped value will be
returned. font_mapping can have regexes as keys.
Returns:
str: The font of the element. | The name and size of the font, separated by a comma with no spaces. | [
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"""
The name and size of the font, separated by a comma with no spaces.
This will be taken from the pdf itself, using the first character in the
element.
If you have provided a font_mapping, this is the string you should map. If
the string is mapped in your font_mapping then the mapped value will be
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Returns:
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"""
if self.__font is not None:
return self.__font
font = f"{self.font_name},{self.font_size}"
if self.document._font_mapping_is_regex:
for pattern, font_name in self.document._font_mapping.items():
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return self.__font
self.__font = self.document._font_mapping.get(font) or font
return self.__font | [
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|
googlearchive/appengine-flask-skeleton | 8c25461d003a0bd99a9ff3b339c2791ee6919242 | lib/jinja2/bccache.py | python | Bucket.load_bytecode | (self, f) | Loads bytecode from a file or file like object. | Loads bytecode from a file or file like object. | [
"Loads",
"bytecode",
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"a",
"file",
"or",
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"like",
"object",
"."
] | def load_bytecode(self, f):
"""Loads bytecode from a file or file like object."""
# make sure the magic header is correct
magic = f.read(len(bc_magic))
if magic != bc_magic:
self.reset()
return
# the source code of the file changed, we need to reload
checksum = pickle.load(f)
if self.checksum != checksum:
self.reset()
return
# if marshal_load fails then we need to reload
try:
self.code = marshal_load(f)
except (EOFError, ValueError, TypeError):
self.reset()
return | [
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||
G-Wang/WaveRNN-Pytorch | 7149631c777ad9c64d502e3628250830c30cefda | preprocess.py | python | process_data | (wav_dir, output_path, mel_path, wav_path) | given wav directory and output directory, process wav files and save quantized wav and mel
spectrogram to output directory | given wav directory and output directory, process wav files and save quantized wav and mel
spectrogram to output directory | [
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"and",
"mel",
"spectrogram",
"to",
"output",
"directory"
] | def process_data(wav_dir, output_path, mel_path, wav_path):
"""
given wav directory and output directory, process wav files and save quantized wav and mel
spectrogram to output directory
"""
dataset_ids = []
# get list of wav files
wav_files = os.listdir(wav_dir)
# check wav_file
assert len(wav_files) != 0 or wav_files[0][-4:] == '.wav', "no wav files found!"
# create training and testing splits
test_wav_files = wav_files[:4]
wav_files = wav_files[4:]
for i, wav_file in enumerate(tqdm(wav_files)):
# get the file id
file_id = '{:d}'.format(i).zfill(5)
wav, mel = get_wav_mel(os.path.join(wav_dir,wav_file))
# save
np.save(os.path.join(mel_path,file_id+".npy"), mel)
np.save(os.path.join(wav_path,file_id+".npy"), wav)
# add to dataset_ids
dataset_ids.append(file_id)
# save dataset_ids
with open(os.path.join(output_path,'dataset_ids.pkl'), 'wb') as f:
pickle.dump(dataset_ids, f)
# process testing_wavs
test_path = os.path.join(output_path,'test')
os.makedirs(test_path, exist_ok=True)
for i, wav_file in enumerate(test_wav_files):
wav, mel = get_wav_mel(os.path.join(wav_dir,wav_file))
# save test_wavs
np.save(os.path.join(test_path,"test_{}_mel.npy".format(i)),mel)
np.save(os.path.join(test_path,"test_{}_wav.npy".format(i)),wav)
print("\npreprocessing done, total processed wav files:{}.\nProcessed files are located in:{}".format(len(wav_files), os.path.abspath(output_path))) | [
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||
twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/messaging/v1/service/us_app_to_person.py | python | UsAppToPersonInstance._proxy | (self) | return self._context | Generate an instance context for the instance, the context is capable of
performing various actions. All instance actions are proxied to the context
:returns: UsAppToPersonContext for this UsAppToPersonInstance
:rtype: twilio.rest.messaging.v1.service.us_app_to_person.UsAppToPersonContext | Generate an instance context for the instance, the context is capable of
performing various actions. All instance actions are proxied to the context | [
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] | def _proxy(self):
"""
Generate an instance context for the instance, the context is capable of
performing various actions. All instance actions are proxied to the context
:returns: UsAppToPersonContext for this UsAppToPersonInstance
:rtype: twilio.rest.messaging.v1.service.us_app_to_person.UsAppToPersonContext
"""
if self._context is None:
self._context = UsAppToPersonContext(
self._version,
messaging_service_sid=self._solution['messaging_service_sid'],
sid=self._solution['sid'],
)
return self._context | [
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|
xinntao/EDVR | b02e63a0fc5854cad7b11a87f74601612e356eff | basicsr/data/data_util.py | python | paired_paths_from_meta_info_file | (folders, keys, meta_info_file,
filename_tmpl) | return paths | Generate paired paths from an meta information file.
Each line in the meta information file contains the image names and
image shape (usually for gt), separated by a white space.
Example of an meta information file:
```
0001_s001.png (480,480,3)
0001_s002.png (480,480,3)
```
Args:
folders (list[str]): A list of folder path. The order of list should
be [input_folder, gt_folder].
keys (list[str]): A list of keys identifying folders. The order should
be in consistent with folders, e.g., ['lq', 'gt'].
meta_info_file (str): Path to the meta information file.
filename_tmpl (str): Template for each filename. Note that the
template excludes the file extension. Usually the filename_tmpl is
for files in the input folder.
Returns:
list[str]: Returned path list. | Generate paired paths from an meta information file. | [
"Generate",
"paired",
"paths",
"from",
"an",
"meta",
"information",
"file",
"."
] | def paired_paths_from_meta_info_file(folders, keys, meta_info_file,
filename_tmpl):
"""Generate paired paths from an meta information file.
Each line in the meta information file contains the image names and
image shape (usually for gt), separated by a white space.
Example of an meta information file:
```
0001_s001.png (480,480,3)
0001_s002.png (480,480,3)
```
Args:
folders (list[str]): A list of folder path. The order of list should
be [input_folder, gt_folder].
keys (list[str]): A list of keys identifying folders. The order should
be in consistent with folders, e.g., ['lq', 'gt'].
meta_info_file (str): Path to the meta information file.
filename_tmpl (str): Template for each filename. Note that the
template excludes the file extension. Usually the filename_tmpl is
for files in the input folder.
Returns:
list[str]: Returned path list.
"""
assert len(folders) == 2, (
'The len of folders should be 2 with [input_folder, gt_folder]. '
f'But got {len(folders)}')
assert len(keys) == 2, (
'The len of keys should be 2 with [input_key, gt_key]. '
f'But got {len(keys)}')
input_folder, gt_folder = folders
input_key, gt_key = keys
with open(meta_info_file, 'r') as fin:
gt_names = [line.split(' ')[0] for line in fin]
paths = []
for gt_name in gt_names:
basename, ext = osp.splitext(osp.basename(gt_name))
input_name = f'{filename_tmpl.format(basename)}{ext}'
input_path = osp.join(input_folder, input_name)
gt_path = osp.join(gt_folder, gt_name)
paths.append(
dict([(f'{input_key}_path', input_path),
(f'{gt_key}_path', gt_path)]))
return paths | [
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|
mdiazcl/fuzzbunch-debian | 2b76c2249ade83a389ae3badb12a1bd09901fd2c | windows/Resources/Python/Core/Lib/lib-tk/Tkinter.py | python | OptionMenu.__init__ | (self, master, variable, value, *values, **kwargs) | Construct an optionmenu widget with the parent MASTER, with
the resource textvariable set to VARIABLE, the initially selected
value VALUE, the other menu values VALUES and an additional
keyword argument command. | Construct an optionmenu widget with the parent MASTER, with
the resource textvariable set to VARIABLE, the initially selected
value VALUE, the other menu values VALUES and an additional
keyword argument command. | [
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] | def __init__(self, master, variable, value, *values, **kwargs):
"""Construct an optionmenu widget with the parent MASTER, with
the resource textvariable set to VARIABLE, the initially selected
value VALUE, the other menu values VALUES and an additional
keyword argument command."""
kw = {'borderwidth': 2,'textvariable': variable,'indicatoron': 1,
'relief': RAISED,'anchor': 'c','highlightthickness': 2
}
Widget.__init__(self, master, 'menubutton', kw)
self.widgetName = 'tk_optionMenu'
menu = self.__menu = Menu(self, name='menu', tearoff=0)
self.menuname = menu._w
callback = kwargs.get('command')
if 'command' in kwargs:
del kwargs['command']
if kwargs:
raise TclError, 'unknown option -' + kwargs.keys()[0]
menu.add_command(label=value, command=_setit(variable, value, callback))
for v in values:
menu.add_command(label=v, command=_setit(variable, v, callback))
self['menu'] = menu | [
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||
GoogleCloudPlatform/gsutil | 5be882803e76608e2fd29cf8c504ccd1fe0a7746 | gslib/utils/hashing_helper.py | python | _CrcMultiply | (p, q) | return result | Multiplies two polynomials together modulo CASTAGNOLI_POLY.
Args:
p: The first polynomial.
q: The second polynomial.
Returns:
Result of the multiplication. | Multiplies two polynomials together modulo CASTAGNOLI_POLY. | [
"Multiplies",
"two",
"polynomials",
"together",
"modulo",
"CASTAGNOLI_POLY",
"."
] | def _CrcMultiply(p, q):
"""Multiplies two polynomials together modulo CASTAGNOLI_POLY.
Args:
p: The first polynomial.
q: The second polynomial.
Returns:
Result of the multiplication.
"""
result = 0
top_bit = 1 << DEGREE
for _ in range(DEGREE):
if p & 1:
result ^= q
q <<= 1
if q & top_bit:
q ^= CASTAGNOLI_POLY
p >>= 1
return result | [
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