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missionpinball/mpf | 8e6b74cff4ba06d2fec9445742559c1068b88582 | mpf/platforms/spike/spike.py | python | SpikeStepper.stop | (self) | Stop the stepper. | Stop the stepper. | [
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"""Stop the stepper."""
# reconfiguring seems to be used to stop the stepper
self._configure() | [
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hyperledger/aries-cloudagent-python | 2f36776e99f6053ae92eed8123b5b1b2e891c02a | aries_cloudagent/protocols/present_proof/v2_0/routes.py | python | V20PresRequestByFormatSchema.validate_fields | (self, data, **kwargs) | Validate schema fields: data must have at least one format.
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data: The data to validate
Raises:
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Validate schema fields: data must have at least one format.
Args:
data: The data to validate
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ValidationError: if data has no formats
"""
if not any(f.api in data for f in V20PresFormat.Format):
raise ValidationError(
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pip/utils/__init__.py | python | dist_is_local | (dist) | return is_local(dist_location(dist)) | Return True if given Distribution object is installed locally
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Always True if we're not in a virtualenv. | Return True if given Distribution object is installed locally
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Return True if given Distribution object is installed locally
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Always True if we're not in a virtualenv.
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bbc/brave | 88d4454412ee5acfa5ecf2ac5bc8cf75766c7be5 | brave/inputs/input.py | python | Input.dest_connections | (self) | return self.session().connections.get_all_for_source(self) | Returns an array of Connections, describing what this input is connected to.
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'''
Returns an array of Connections, describing what this input is connected to.
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'''
return self.session().connections.get_all_for_source(self) | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/input_datetime/reproduce_state.py | python | is_valid_date | (string: str) | return dt_util.parse_date(string) is not None | Test if string dt is a valid date. | Test if string dt is a valid date. | [
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kanzure/nanoengineer | 874e4c9f8a9190f093625b267f9767e19f82e6c4 | cad/src/model/chunk.py | python | Chunk.copy_full_in_mapping | (self, mapping) | return numol | #doc;
overrides Node method;
only some atom copies get recorded in mapping (if we think it might need them) | #doc;
overrides Node method;
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"""
#doc;
overrides Node method;
only some atom copies get recorded in mapping (if we think it might need them)
"""
# bruce 050526; 060308 major rewrite
numol = self._copy_empty_shell_in_mapping( mapping)
# now copy the atoms, all at once (including all their existing
# singlets, even though those might get revised)
# note: the following code is very similar to
# copy_in_mapping_with_specified_atoms, but not identical.
pairlis = []
ndix = {} # maps old-atom key to corresponding new atom
nuatoms = {}
for a in self.atlist:
# note: self.atlist is now in order of atom.key;
# it might get recomputed right now (along with atpos & basepos if so)
na = a.copy()
# inlined addatom, optimized (maybe put this in a new variant of obs copy_for_mol_copy?)
na.molecule = numol # no need for _changed_parent_Atoms[na.key] = na #bruce 060322
nuatoms[na.key] = na
pairlis.append((a, na))
ndix[a.key] = na
numol.invalidate_atom_lists()
numol.atoms = nuatoms
# note: we don't bother copying atlist, atpos, basepos,
# since it's hard to do correctly (e.g. not copying everything
# which depends on them would cause inval bugs), and it's wasted work
# for callers which plan to move all the atoms after
# the copy
self._copy_atoms_handle_bonds_jigs( pairlis, ndix, mapping)
# note: no way to handle hotspot yet, since how to do that might depend on whether
# extern bonds are broken... so let's copy an explicit one, and tell the mapping
# if we have an implicit one... or, register a cleanup function with the mapping.
copied_hotspot = self.hotspot
# might be None (this uses __getattr__ to ensure the stored one is valid)
if copied_hotspot is not None:
numol.set_hotspot( ndix[copied_hotspot.key])
elif len(self.singlets) == 1:
#e someday it might also work if there are two singlets on the same base atom!
# we have an implicit but unambiguous hotspot:
# might need to make it explicit in the copy [bruce 041123, revised 050524]
copy_of_hotspot = ndix[self.singlets[0].key]
mapping.do_at_end( lambda ch = copy_of_hotspot, numol = numol:
numol._f_preserve_implicit_hotspot(ch) )
return numol | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/Django-1.11.29/django/db/backends/mysql/base.py | python | DatabaseWrapper.check_constraints | (self, table_names=None) | Checks each table name in `table_names` for rows with invalid foreign
key references. This method is intended to be used in conjunction with
`disable_constraint_checking()` and `enable_constraint_checking()`, to
determine if rows with invalid references were entered while constraint
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for table_name in table_names:
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if not primary_key_column_name:
continue
key_columns = self.introspection.get_key_columns(cursor, table_name)
for column_name, referenced_table_name, referenced_column_name in key_columns:
cursor.execute(
"""
SELECT REFERRING.`%s`, REFERRING.`%s` FROM `%s` as REFERRING
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table_name, bad_row[0], table_name, column_name,
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deepgully/me | f7ad65edc2fe435310c6676bc2e322cfe5d4c8f0 | libs/sqlalchemy/engine/reflection.py | python | Inspector.get_table_names | (self, schema=None, order_by=None) | return tnames | Return all table names in referred to within a particular schema.
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Views are instead returned using the :meth:`.Inspector.get_view_names`
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:param schema: Schema name. If ``schema`` is left at ``None``, the
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"""Return all table names in referred to within a particular schema.
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Views are instead returned using the :meth:`.Inspector.get_view_names`
method.
:param schema: Schema name. If ``schema`` is left at ``None``, the
database's default schema is
used, else the named schema is searched. If the database does not
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passed as ``None``. For special quoting, use :class:`.quoted_name`.
:param order_by: Optional, may be the string "foreign_key" to sort
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:attr:`.MetaData.sorted_tables`
"""
if hasattr(self.dialect, 'get_table_names'):
tnames = self.dialect.get_table_names(self.bind,
schema, info_cache=self.info_cache)
else:
tnames = self.engine.table_names(schema)
if order_by == 'foreign_key':
tuples = []
for tname in tnames:
for fkey in self.get_foreign_keys(tname, schema):
if tname != fkey['referred_table']:
tuples.append((fkey['referred_table'], tname))
tnames = list(topological.sort(tuples, tnames))
return tnames | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/numpy-1.16.0-py3.7-macosx-10.9-x86_64.egg/numpy/ma/core.py | python | _recursive_fill_value | (dtype, f) | Recursively produce a fill value for `dtype`, calling f on scalar dtypes | Recursively produce a fill value for `dtype`, calling f on scalar dtypes | [
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"""
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"""
if dtype.names is not None:
vals = tuple(_recursive_fill_value(dtype[name], f) for name in dtype.names)
return np.array(vals, dtype=dtype)[()] # decay to void scalar from 0d
elif dtype.subdtype:
subtype, shape = dtype.subdtype
subval = _recursive_fill_value(subtype, f)
return np.full(shape, subval)
else:
return f(dtype) | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/ip_messaging/v2/__init__.py | python | V2.services | (self) | return self._services | :rtype: twilio.rest.ip_messaging.v2.service.ServiceList | :rtype: twilio.rest.ip_messaging.v2.service.ServiceList | [
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"""
:rtype: twilio.rest.ip_messaging.v2.service.ServiceList
"""
if self._services is None:
self._services = ServiceList(self)
return self._services | [
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sahana/eden | 1696fa50e90ce967df69f66b571af45356cc18da | modules/templates/locations/FI/config.py | python | config | (settings) | Template settings for Finland
- designed to be used in a Cascade with an application template | Template settings for Finland
- designed to be used in a Cascade with an application template | [
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"""
Template settings for Finland
- designed to be used in a Cascade with an application template
"""
#T = current.T
# Pre-Populate
settings.base.prepopulate.append("locations/FI")
# Uncomment to restrict to specific country/countries
settings.gis.countries.append("FI")
# -------------------------------------------------------------------------
# L10n (Localization) settings
settings.L10n.languages["fi"] = "Finnish"
settings.L10n.languages["sv"] = "Swedish"
settings.L10n.languages["smi"] = "Sámi"
# Default Language (put this in custom template if-required)
#settings.L10n.default_language = "fi"
# Default timezone for users
settings.L10n.timezone = "Europe/Helsinki"
# Default Country Code for telephone numbers
settings.L10n.default_country_code = 358
settings.fin.currencies["EUR"] = "Euro"
settings.fin.currency_default = "EUR" | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | dist/lib/python2.7/SimpleHTTPServer.py | python | SimpleHTTPRequestHandler.guess_type | (self, path) | Guess the type of a file.
Argument is a PATH (a filename).
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Argument is a PATH (a filename).
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The default implementation looks the file's extension
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"""
base, ext = posixpath.splitext(path)
if ext in self.extensions_map:
return self.extensions_map[ext]
ext = ext.lower()
if ext in self.extensions_map:
return self.extensions_map[ext]
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... | https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/dist/lib/python2.7/SimpleHTTPServer.py#L179-L201 | ||
apachecn/AiLearning | 228b62a905a2a9bf6066f65c16d53056b10ec610 | src/py3.x/dl/bp.py | python | ConstNode.append_downstream_connection | (self, conn) | Desc:
添加一个到下游节点的连接
Args:
conn --- 到下游节点的连接
Returns:
None | Desc:
添加一个到下游节点的连接
Args:
conn --- 到下游节点的连接
Returns:
None | [
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'''
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添加一个到下游节点的连接
Args:
conn --- 到下游节点的连接
Returns:
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# 使用 list 的 append 方法将包含下游节点的 conn 添加到 downstream 中
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adamchainz/django-mysql | 389594dc078f73c9f204306014332344fe4b6d04 | src/django_mysql/models/fields/dynamic.py | python | KeyTransform.as_sql | (
self, compiler: SQLCompiler, connection: BaseDatabaseWrapper
) | return (
f"COLUMN_GET({lhs}, %s AS {self.data_type})",
tuple(params) + (self.key_name,),
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self, compiler: SQLCompiler, connection: BaseDatabaseWrapper
) -> Tuple[str, Iterable[Any]]:
lhs, params = compiler.compile(self.lhs)
return (
f"COLUMN_GET({lhs}, %s AS {self.data_type})",
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team_log.py | python | EventTypeArg.is_folder_overview_item_unpinned | (self) | return self._tag == 'folder_overview_item_unpinned' | Check if the union tag is ``folder_overview_item_unpinned``.
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"""
Check if the union tag is ``folder_overview_item_unpinned``.
:rtype: bool
"""
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huawei-noah/vega | d9f13deede7f2b584e4b1d32ffdb833856129989 | vega/networks/pytorch/customs/modnas/arch_space/torch/pyramidnet.py | python | BottleneckBlock.forward | (self, x) | return out | Compute network output. | Compute network output. | [
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batch_size = out.size()[0]
residual_channel = out.size()[1]
shortcut_channel = shortcut.size()[1]
if residual_channel != shortcut_channel:
padding = torch.zeros(batch_size, residual_channel - shortcut_channel, featuremap_size[0],
featuremap_size[1]).to(device=x.device)
out += torch.cat((shortcut, padding), 1)
else:
out += shortcut
return out | [
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frappe/frappe | b64cab6867dfd860f10ccaf41a4ec04bc890b583 | frappe/modules/utils.py | python | sync_customizations | (app=None) | Sync custom fields and property setters from custom folder in each app module | Sync custom fields and property setters from custom folder in each app module | [
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'''Sync custom fields and property setters from custom folder in each app module'''
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apps = frappe.get_installed_apps()
for app_name in apps:
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/modules/zoneadm.py | python | clone | (zone, source, snapshot=None) | return ret | Install a zone by copying an existing installed zone.
zone : string
name of the zone
source : string
zone to clone from
snapshot : string
optional name of snapshot to use as source
CLI Example:
.. code-block:: bash
salt '*' zoneadm.clone clementine dolores | Install a zone by copying an existing installed zone. | [
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"""
Install a zone by copying an existing installed zone.
zone : string
name of the zone
source : string
zone to clone from
snapshot : string
optional name of snapshot to use as source
CLI Example:
.. code-block:: bash
salt '*' zoneadm.clone clementine dolores
"""
ret = {"status": True}
## install zone
res = __salt__["cmd.run_all"](
"zoneadm -z {zone} clone {snapshot}{source}".format(
zone=zone,
source=source,
snapshot="-s {} ".format(snapshot) if snapshot else "",
)
)
ret["status"] = res["retcode"] == 0
ret["message"] = res["stdout"] if ret["status"] else res["stderr"]
ret["message"] = ret["message"].replace("zoneadm: ", "")
if ret["message"] == "":
del ret["message"]
return ret | [
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google-research/language | 61fa7260ac7d690d11ef72ca863e45a37c0bdc80 | language/labs/drkit/run_dualencoder_lsf.py | python | _copy_model | (in_path, out_path) | Copy model checkpoint for future use. | Copy model checkpoint for future use. | [
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tf.gfile.Copy(
in_path + ".data-00000-of-00001",
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tf.gfile.Copy(in_path + ".index", out_path + ".index", overwrite=True)
tf.gfile.Copy(in_path + ".meta", out_path + ".meta", overwrite=True) | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/cloud/clouds/profitbricks.py | python | stop | (name, call=None) | return True | stop a machine by name
:param name: name given to the machine
:param call: call value in this case is 'action'
:return: true if successful
CLI Example:
.. code-block:: bash
salt-cloud -a stop vm_name | stop a machine by name
:param name: name given to the machine
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"""
stop a machine by name
:param name: name given to the machine
:param call: call value in this case is 'action'
:return: true if successful
CLI Example:
.. code-block:: bash
salt-cloud -a stop vm_name
"""
datacenter_id = get_datacenter_id()
conn = get_conn()
node = get_node(conn, name)
conn.stop_server(datacenter_id=datacenter_id, server_id=node["id"])
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TheAlgorithms/Python | 9af2eef9b3761bf51580dedfb6fa7136ca0c5c2c | project_euler/problem_206/sol1.py | python | solution | () | return num * 10 | Returns the first integer whose square is of the form 1_2_3_4_5_6_7_8_9_0 | Returns the first integer whose square is of the form 1_2_3_4_5_6_7_8_9_0 | [
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"""
Returns the first integer whose square is of the form 1_2_3_4_5_6_7_8_9_0
"""
num = 138902663
while not is_square_form(num * num):
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num -= 6 # (3 - 6) % 10 = 7
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num -= 4 # (7 - 4) % 10 = 3
return num * 10 | [
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evilhero/mylar | dbee01d7e48e8c717afa01b2de1946c5d0b956cb | lib/cherrypy/wsgiserver/wsgiserver2.py | python | read_headers | (rfile, hdict=None) | return hdict | Read headers from the given stream into the given header dict.
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Headers which are repeated are folded together using a comma if their
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"""Read headers from the given stream into the given header dict.
If hdict is None, a new header dict is created. Returns the populated
header dict.
Headers which are repeated are folded together using a comma if their
specification so dictates.
This function raises ValueError when the read bytes violate the HTTP spec.
You should probably return "400 Bad Request" if this happens.
"""
if hdict is None:
hdict = {}
while True:
line = rfile.readline()
if not line:
# No more data--illegal end of headers
raise ValueError("Illegal end of headers.")
if line == CRLF:
# Normal end of headers
break
if not line.endswith(CRLF):
raise ValueError("HTTP requires CRLF terminators")
if line[0] in (SPACE, TAB):
# It's a continuation line.
v = line.strip()
else:
try:
k, v = line.split(COLON, 1)
except ValueError:
raise ValueError("Illegal header line.")
# TODO: what about TE and WWW-Authenticate?
k = k.strip().title()
v = v.strip()
hname = k
if k in comma_separated_headers:
existing = hdict.get(hname)
if existing:
v = ", ".join((existing, v))
hdict[hname] = v
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Kismuz/btgym | 7fb3316e67f1d7a17c620630fb62fb29428b2cec | btgym/research/model_based/model/rec.py | python | OUEstimator.__init__ | (self, alpha) | Args:
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Notes:
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parameters fitted are: Mu, Log_Theta, Log_Sigma, for process: dX = -Theta *(X - Mu) + Sigma * dW; | [] | def __init__(self, alpha):
"""
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alpha ~ 1 / effective_window_length;
parameters fitted are: Mu, Log_Theta, Log_Sigma, for process: dX = -Theta *(X - Mu) + Sigma * dW;
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self.x_prev = 0.0 | [
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p5py/p5 | 4ef1580b26179f1973c1669751da4522c5823f17 | p5/sketch/Vispy2DRenderer/base.py | python | VispySketch._save_buffer | (self) | Save the renderer buffer to the given file. | Save the renderer buffer to the given file. | [
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beeware/ouroboros | a29123c6fab6a807caffbb7587cf548e0c370296 | ouroboros/imp.py | python | get_magic | () | return util.MAGIC_NUMBER | **DEPRECATED**
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elyra-ai/elyra | 5bb2009a7c475bda63f1cc2767eb8c4dfba9a239 | elyra/cli/pipeline_app.py | python | run | (json_option, pipeline_path) | Run a pipeline in your local environment | Run a pipeline in your local environment | [
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"""
Run a pipeline in your local environment
"""
click.echo()
print_banner("Elyra Pipeline Local Run")
_validate_pipeline_file_extension(pipeline_path)
pipeline_definition = \
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_validate_pipeline_definition(pipeline_definition)
response = _execute_pipeline(pipeline_definition)
if not json_option:
click.echo()
print_banner("Elyra Pipeline Local Run Complete")
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click.echo()
if response:
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | core/error.py | python | _ControlFlow.IsBreak | (self) | return self.token.id == Id.ControlFlow_Break | [] | def IsBreak(self):
# type: () -> bool
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BillBillBillBill/Tickeys-linux | 2df31b8665004c58a5d4ab05277f245267d96364 | tickeys/kivy_32/kivy/lang.py | python | BuilderBase.sync | (self) | Execute all the waiting operations, such as the execution of all the
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.. versionadded:: 1.7.0
'''
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roglew/guppy-proxy | 01df16be71dd9f23d7de415a315821659c29bc63 | guppyproxy/hexteditor.py | python | PrettyPrintWidget.__init__ | (self, *args, **kwargs) | [] | def __init__(self, *args, **kwargs):
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self.data = b''
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self.selector.addItem("JSON", self.VIEW_JSON)
self.selector.addItem("HTML/XML", self.VIEW_HTMLXML)
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/bokeh-1.4.0-py3.7.egg/bokeh/document/events.py | python | ModelChangedEvent.__init__ | (self, document, model, attr, old, new, serializable_new, hint=None, setter=None, callback_invoker=None) | Args:
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'''
Args:
document (Document) :
A Bokeh document that is to be updated.
model (Model) :
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The old value of the attribute
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tcaplusdb/v20190823/models.py | python | VerifyIdlFilesResponse.__init__ | (self) | r"""
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FabriceSalvaire/PySpice | 1fb97dc21abcf04cfd78802671322eef5c0de00b | PySpice/Spice/NgSpice/Server.py | python | SpiceServer._parse_stdout | (self, stdout) | Parse stdout for errors. | Parse stdout for errors. | [
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limodou/uliweb | 8bc827fa6bf7bf58aa8136b6c920fe2650c52422 | uliweb/lib/colorama/ansitowin32.py | python | AnsiToWin32.should_wrap | (self) | return self.convert or self.strip or self.autoreset | True if this class is actually needed. If false, then the output
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deepgully/me | f7ad65edc2fe435310c6676bc2e322cfe5d4c8f0 | libs/simplejson/decoder.py | python | JSONDecoder.__init__ | (self, encoding=None, object_hook=None, parse_float=None,
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RenYurui/StructureFlow | 1ac8f559475452e6b674699671c6b34f000d9ebd | src/network.py | python | Get_image.forward | (self, x) | return self.conv(x) | [] | def forward(self, x):
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/pi_hole/__init__.py | python | async_unload_entry | (hass: HomeAssistant, entry: ConfigEntry) | return unload_ok | Unload Pi-hole entry. | Unload Pi-hole entry. | [
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wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/agw/knobctrl.py | python | KnobCtrlEvent.SetValue | (self, value) | Sets the new :class:`KnobCtrl` value for this event.
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nooperpudd/chinastock | bad839f1177bba21cacbf448ef20391702dbcf01 | httpGet.py | python | httpGetContent | (url, headers=None, charset=None) | httplib2处理请求 | httplib2处理请求 | [
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geometalab/Vector-Tiles-Reader-QGIS-Plugin | a31ae86959c8f3b7d6f332f84191cd7ca4683e1d | ext-libs/shapely/geos.py | python | WKBWriter.__setattr__ | (self, name, value) | Limit setting attributes | Limit setting attributes | [
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vadmium/python-altium | 9e3cf5a16150e74ba2b7e6d1f2895e0ce16b9a05 | vector/svg.py | python | Renderer.hline | (self, a, b=None, *,
width=None, offset=None, colour=None) | [] | def hline(self, a, b=None, *,
width=None, offset=None, colour=None):
a = format(a)
if b is None:
attrs = {"x2": a}
else:
attrs = {"x1": a, "x2": format(b)}
self._line(attrs, width=width, offset=offset, colour=colour) | [
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pavelliavonau/cmakeconverter | ef7afd3c7d8046a25754d679b5b7b97706b7eee4 | cmake_converter/visual_studio/vcxproj/flags.py | python | CPPFlags.__set_calling_convention | (context, flag_name, node) | return flag_values | Set CallingConvention flag: /G** | Set CallingConvention flag: /G** | [
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"""
Set CallingConvention flag: /G**
"""
del context, flag_name, node
flag_values = {
'Cdecl': {cl_flags: '/Gd'},
'FastCall': {cl_flags: '/Gr'},
'StdCall': {cl_flags: '/Gz'},
'VectorCall': {cl_flags: '/Gv'},
default_value: {}
}
return flag_values | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/http/cookies.py | python | BaseCookie.output | (self, attrs=None, header="Set-Cookie:", sep="\015\012") | return sep.join(result) | Return a string suitable for HTTP. | Return a string suitable for HTTP. | [
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] | def output(self, attrs=None, header="Set-Cookie:", sep="\015\012"):
"""Return a string suitable for HTTP."""
result = []
items = sorted(self.items())
for key, value in items:
result.append(value.output(attrs, header))
return sep.join(result) | [
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hak5/nano-tetra-modules | aa43cb5e2338b8dbd12a75314104a34ba608263b | PortalAuth/includes/scripts/libs/email/header.py | python | Header.encode | (self, splitchars=';, ') | return value | Encode a message header into an RFC-compliant format.
There are many issues involved in converting a given string for use in
an email header. Only certain character sets are readable in most
email clients, and as header strings can only contain a subset of
7-bit ASCII, care must be taken to properly convert and encode (with
Base64 or quoted-printable) header strings. In addition, there is a
75-character length limit on any given encoded header field, so
line-wrapping must be performed, even with double-byte character sets.
This method will do its best to convert the string to the correct
character set used in email, and encode and line wrap it safely with
the appropriate scheme for that character set.
If the given charset is not known or an error occurs during
conversion, this function will return the header untouched.
Optional splitchars is a string containing characters to split long
ASCII lines on, in rough support of RFC 2822's `highest level
syntactic breaks'. This doesn't affect RFC 2047 encoded lines. | Encode a message header into an RFC-compliant format. | [
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] | def encode(self, splitchars=';, '):
"""Encode a message header into an RFC-compliant format.
There are many issues involved in converting a given string for use in
an email header. Only certain character sets are readable in most
email clients, and as header strings can only contain a subset of
7-bit ASCII, care must be taken to properly convert and encode (with
Base64 or quoted-printable) header strings. In addition, there is a
75-character length limit on any given encoded header field, so
line-wrapping must be performed, even with double-byte character sets.
This method will do its best to convert the string to the correct
character set used in email, and encode and line wrap it safely with
the appropriate scheme for that character set.
If the given charset is not known or an error occurs during
conversion, this function will return the header untouched.
Optional splitchars is a string containing characters to split long
ASCII lines on, in rough support of RFC 2822's `highest level
syntactic breaks'. This doesn't affect RFC 2047 encoded lines.
"""
newchunks = []
maxlinelen = self._firstlinelen
lastlen = 0
for s, charset in self._chunks:
# The first bit of the next chunk should be just long enough to
# fill the next line. Don't forget the space separating the
# encoded words.
targetlen = maxlinelen - lastlen - 1
if targetlen < charset.encoded_header_len(''):
# Stick it on the next line
targetlen = maxlinelen
newchunks += self._split(s, charset, targetlen, splitchars)
lastchunk, lastcharset = newchunks[-1]
lastlen = lastcharset.encoded_header_len(lastchunk)
value = self._encode_chunks(newchunks, maxlinelen)
if _embeded_header.search(value):
raise HeaderParseError("header value appears to contain "
"an embedded header: {!r}".format(value))
return value | [
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LuxCoreRender/BlendLuxCore | bf31ca58501d54c02acd97001b6db7de81da7cbf | ui/lol/panel.py | python | VIEW3D_PT_LUXCORE_ONLINE_LIBRARY_SCAN_RESULT.draw_addlist | (self, layout, asset, idx) | [] | def draw_addlist(self, layout, asset, idx):
col = layout.column(align=True)
# Upper row (enable/disable, name, remove)
box = col.box()
row = box.row()
col = row.column()
col.prop(asset, "show_settings",
icon=settings_toggle_icon(asset.show_settings),
icon_only=True, emboss=False)
col = row.column()
col.prop(asset, "name", text="")
# op = row.operator("scene.luxcore_ol_remove_asset",
# text="", icon=icons.CLEAR, emboss=False)
# op.index = idx
if asset.show_settings:
col = box.column(align=True)
col.prop(asset, "category")
col = box.column(align=True)
col.label(text="Thumbnail:")
col.prop(asset, "show_thumbnail", icon=icons.IMAGE)
if asset.show_thumbnail:
col.template_ID_preview(asset, "thumbnail", open="image.open")
else:
col.template_ID(asset, "thumbnail", open="image.open")
col = box.column(align=True)
col.enabled = (asset.thumbnail is not None)
op = col.operator("scene.luxcore_ol_add_local", text="Add asset...")
op.asset_index = idx | [
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jayleicn/scipy-lecture-notes-zh-CN | cc87204fcc4bd2f4702f7c29c83cb8ed5c94b7d6 | packages/traits/reservoir_state_property_view.py | python | ReservoirState._get_spillage | (self) | return max(overflow, 0) | [] | def _get_spillage(self):
new_storage = self._storage - self.release + self.inflows
overflow = new_storage - self.max_storage
return max(overflow, 0) | [
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python-telegram-bot/python-telegram-bot | ade1529986f5b6d394a65372d6a27045a70725b2 | telegram/user.py | python | User.copy_message | (
self,
chat_id: Union[int, str],
message_id: int,
caption: str = None,
parse_mode: ODVInput[str] = DEFAULT_NONE,
caption_entities: Union[Tuple['MessageEntity', ...], List['MessageEntity']] = None,
disable_notification: DVInput[bool] = DEFAULT_NONE,
reply_to_message_id: int = None,
allow_sending_without_reply: DVInput[bool] = DEFAULT_NONE,
reply_markup: 'ReplyMarkup' = None,
timeout: ODVInput[float] = DEFAULT_NONE,
api_kwargs: JSONDict = None,
protect_content: bool = None,
) | return self.bot.copy_message(
from_chat_id=self.id,
chat_id=chat_id,
message_id=message_id,
caption=caption,
parse_mode=parse_mode,
caption_entities=caption_entities,
disable_notification=disable_notification,
reply_to_message_id=reply_to_message_id,
allow_sending_without_reply=allow_sending_without_reply,
reply_markup=reply_markup,
timeout=timeout,
api_kwargs=api_kwargs,
protect_content=protect_content,
) | Shortcut for::
bot.copy_message(from_chat_id=update.effective_user.id, *args, **kwargs)
For the documentation of the arguments, please see :meth:`telegram.Bot.copy_message`.
Returns:
:class:`telegram.Message`: On success, instance representing the message posted. | Shortcut for:: | [
"Shortcut",
"for",
"::"
] | def copy_message(
self,
chat_id: Union[int, str],
message_id: int,
caption: str = None,
parse_mode: ODVInput[str] = DEFAULT_NONE,
caption_entities: Union[Tuple['MessageEntity', ...], List['MessageEntity']] = None,
disable_notification: DVInput[bool] = DEFAULT_NONE,
reply_to_message_id: int = None,
allow_sending_without_reply: DVInput[bool] = DEFAULT_NONE,
reply_markup: 'ReplyMarkup' = None,
timeout: ODVInput[float] = DEFAULT_NONE,
api_kwargs: JSONDict = None,
protect_content: bool = None,
) -> 'MessageId':
"""Shortcut for::
bot.copy_message(from_chat_id=update.effective_user.id, *args, **kwargs)
For the documentation of the arguments, please see :meth:`telegram.Bot.copy_message`.
Returns:
:class:`telegram.Message`: On success, instance representing the message posted.
"""
return self.bot.copy_message(
from_chat_id=self.id,
chat_id=chat_id,
message_id=message_id,
caption=caption,
parse_mode=parse_mode,
caption_entities=caption_entities,
disable_notification=disable_notification,
reply_to_message_id=reply_to_message_id,
allow_sending_without_reply=allow_sending_without_reply,
reply_markup=reply_markup,
timeout=timeout,
api_kwargs=api_kwargs,
protect_content=protect_content,
) | [
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conansherry/detectron2 | 72c935d9aad8935406b1038af408aa06077d950a | detectron2/engine/hooks.py | python | PeriodicWriter.__init__ | (self, writers, period=20) | Args:
writers (list[EventWriter]): a list of EventWriter objects
period (int): | Args:
writers (list[EventWriter]): a list of EventWriter objects
period (int): | [
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"""
Args:
writers (list[EventWriter]): a list of EventWriter objects
period (int):
"""
self._writers = writers
for w in writers:
assert isinstance(w, EventWriter), w
self._period = period | [
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datastax/python-driver | 5fdb0061f56f53b9d8d8ad67b99110899653ad77 | cassandra/cqlengine/management.py | python | _get_index_name_by_column | (table, column_name) | Find the index name for a given table and column. | Find the index name for a given table and column. | [
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] | def _get_index_name_by_column(table, column_name):
"""
Find the index name for a given table and column.
"""
protected_name = metadata.protect_name(column_name)
possible_index_values = [protected_name, "values(%s)" % protected_name]
for index_metadata in table.indexes.values():
options = dict(index_metadata.index_options)
if options.get('target') in possible_index_values:
return index_metadata.name | [
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osmr/imgclsmob | f2993d3ce73a2f7ddba05da3891defb08547d504 | tensorflow2/tf2cv/models/mobilenet_cub.py | python | fdmobilenet_w1_cub | (classes=200, **kwargs) | return get_fdmobilenet(classes=classes, width_scale=1.0, model_name="fdmobilenet_w1_cub", **kwargs) | FD-MobileNet 1.0x model for CUB-200-2011 from 'FD-MobileNet: Improved MobileNet with A Fast Downsampling Strategy,'
https://arxiv.org/abs/1802.03750.
Parameters:
----------
classes : int, default 200
Number of classification classes.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.tensorflow/models'
Location for keeping the model parameters. | FD-MobileNet 1.0x model for CUB-200-2011 from 'FD-MobileNet: Improved MobileNet with A Fast Downsampling Strategy,'
https://arxiv.org/abs/1802.03750. | [
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"""
FD-MobileNet 1.0x model for CUB-200-2011 from 'FD-MobileNet: Improved MobileNet with A Fast Downsampling Strategy,'
https://arxiv.org/abs/1802.03750.
Parameters:
----------
classes : int, default 200
Number of classification classes.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.tensorflow/models'
Location for keeping the model parameters.
"""
return get_fdmobilenet(classes=classes, width_scale=1.0, model_name="fdmobilenet_w1_cub", **kwargs) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/mailbox.py | python | Maildir.add | (self, message) | return uniq | Add message and return assigned key. | Add message and return assigned key. | [
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"."
] | def add(self, message):
"""Add message and return assigned key."""
tmp_file = self._create_tmp()
try:
self._dump_message(message, tmp_file)
except BaseException:
tmp_file.close()
os.remove(tmp_file.name)
raise
_sync_close(tmp_file)
if isinstance(message, MaildirMessage):
subdir = message.get_subdir()
suffix = self.colon + message.get_info()
if suffix == self.colon:
suffix = ''
else:
subdir = 'new'
suffix = ''
uniq = os.path.basename(tmp_file.name).split(self.colon)[0]
dest = os.path.join(self._path, subdir, uniq + suffix)
if isinstance(message, MaildirMessage):
os.utime(tmp_file.name,
(os.path.getatime(tmp_file.name), message.get_date()))
# No file modification should be done after the file is moved to its
# final position in order to prevent race conditions with changes
# from other programs
try:
if hasattr(os, 'link'):
os.link(tmp_file.name, dest)
os.remove(tmp_file.name)
else:
os.rename(tmp_file.name, dest)
except OSError, e:
os.remove(tmp_file.name)
if e.errno == errno.EEXIST:
raise ExternalClashError('Name clash with existing message: %s'
% dest)
else:
raise
return uniq | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/scf/v20180416/scf_client.py | python | ScfClient.UpdateNamespace | (self, request) | 更新命名空间
:param request: Request instance for UpdateNamespace.
:type request: :class:`tencentcloud.scf.v20180416.models.UpdateNamespaceRequest`
:rtype: :class:`tencentcloud.scf.v20180416.models.UpdateNamespaceResponse` | 更新命名空间 | [
"更新命名空间"
] | def UpdateNamespace(self, request):
"""更新命名空间
:param request: Request instance for UpdateNamespace.
:type request: :class:`tencentcloud.scf.v20180416.models.UpdateNamespaceRequest`
:rtype: :class:`tencentcloud.scf.v20180416.models.UpdateNamespaceResponse`
"""
try:
params = request._serialize()
body = self.call("UpdateNamespace", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.UpdateNamespaceResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | [
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holoviz/datashader | 25578abde75c7fa28c6633b33cb8d8a1e433da67 | datashader/utils.py | python | compute_coords | (width, height, x_range, y_range, res) | return xs, ys | Computes DataArray coordinates at bin centers
Parameters
----------
width : int
Number of coordinates along the x-axis
height : int
Number of coordinates along the y-axis
x_range : tuple
Left and right edge of the coordinates
y_range : tuple
Bottom and top edges of the coordinates
res : tuple
Two-tuple (int, int) which includes x and y resolutions (aka "grid/cell
sizes"), respectively. Used to determine coordinate orientation.
Returns
-------
xs : numpy.ndarray
1D array of x-coordinates
ys : numpy.ndarray
1D array of y-coordinates | Computes DataArray coordinates at bin centers | [
"Computes",
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] | def compute_coords(width, height, x_range, y_range, res):
"""
Computes DataArray coordinates at bin centers
Parameters
----------
width : int
Number of coordinates along the x-axis
height : int
Number of coordinates along the y-axis
x_range : tuple
Left and right edge of the coordinates
y_range : tuple
Bottom and top edges of the coordinates
res : tuple
Two-tuple (int, int) which includes x and y resolutions (aka "grid/cell
sizes"), respectively. Used to determine coordinate orientation.
Returns
-------
xs : numpy.ndarray
1D array of x-coordinates
ys : numpy.ndarray
1D array of y-coordinates
"""
(x0, x1), (y0, y1) = x_range, y_range
xd = (x1-x0)/float(width)
yd = (y1-y0)/float(height)
xpad, ypad = abs(xd/2.), abs(yd/2.)
x0, x1 = x0+xpad, x1-xpad
y0, y1 = y0+ypad, y1-ypad
xs = np.linspace(x0, x1, width)
ys = np.linspace(y0, y1, height)
if res[0] < 0: xs = xs[::-1]
if res[1] > 0: ys = ys[::-1]
return xs, ys | [
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rytilahti/python-miio | b6e53dd16fac77915426e7592e2528b78ef65190 | miio/toiletlid.py | python | Toiletlid.get_all_user_info | (self) | return users | Get All bind user. | Get All bind user. | [
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numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/cuda/cudadrv/driver.py | python | _pin_finalizer | (memory_manager, ptr, alloc_key, mapped) | return core | Finalize temporary page-locking of host memory by `context.mempin`.
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airbnb/streamalert | 26cf1d08432ca285fd4f7410511a6198ca104bbb | streamalert/classifier/payload/payload_base.py | python | PayloadRecord.__bool__ | (self) | return self._parser is not None | Valid if there is a parser, and the parser itself is valid
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bashtage/linearmodels | 9256269f01ff8c5f85e65342d66149a5636661b6 | linearmodels/iv/model.py | python | _IVModelBase.predict | (
self,
params: ArrayLike,
*,
exog: Optional[IVDataLike] = None,
endog: Optional[IVDataLike] = None,
data: DataFrame = None,
eval_env: int = 4,
) | return pred | Predict values for additional data
Parameters
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params : array_like
Model parameters (nvar by 1)
exog : array_like
Exogenous regressors (nobs by nexog)
endog : array_like
Endogenous regressors (nobs by nendog)
data : DataFrame
Values to use when making predictions from a model constructed
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eval_env : int
Depth of use when evaluating formulas.
Returns
-------
DataFrame
Fitted values from supplied data and parameters
Notes
-----
The number of parameters must satisfy nvar = nexog + nendog.
When using `exog` and `endog`, regressor matrix is constructed as
`[exog, endog]` and so parameters must be aligned to this structure.
The the the same structure used in model estimation.
If `data` is not none, then `exog` and `endog` must be none.
Predictions from models constructed using formulas can
be computed using either `exog` and `endog`, which will treat these are
arrays of values corresponding to the formula-processed data, or using
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values corresponding to the original model specification. | Predict values for additional data | [
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self,
params: ArrayLike,
*,
exog: Optional[IVDataLike] = None,
endog: Optional[IVDataLike] = None,
data: DataFrame = None,
eval_env: int = 4,
) -> DataFrame:
"""
Predict values for additional data
Parameters
----------
params : array_like
Model parameters (nvar by 1)
exog : array_like
Exogenous regressors (nobs by nexog)
endog : array_like
Endogenous regressors (nobs by nendog)
data : DataFrame
Values to use when making predictions from a model constructed
from a formula
eval_env : int
Depth of use when evaluating formulas.
Returns
-------
DataFrame
Fitted values from supplied data and parameters
Notes
-----
The number of parameters must satisfy nvar = nexog + nendog.
When using `exog` and `endog`, regressor matrix is constructed as
`[exog, endog]` and so parameters must be aligned to this structure.
The the the same structure used in model estimation.
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be computed using either `exog` and `endog`, which will treat these are
arrays of values corresponding to the formula-processed data, or using
`data` which will be processed using the formula used to construct the
values corresponding to the original model specification.
"""
if data is not None and self.formula is None:
raise ValueError(
"Unable to use data when the model was not " "created using a formula."
)
if data is not None and (exog is not None or endog is not None):
raise ValueError(
"Predictions can only be constructed using one "
"of exog/endog or data, but not both."
)
if exog is not None or endog is not None:
exog = IVData(exog).pandas
endog = IVData(endog).pandas
elif data is not None:
parser = IVFormulaParser(self.formula, data, eval_env=eval_env)
exog = parser.exog
endog = parser.endog
exog_endog = concat([exog, endog], axis=1)
x = asarray(exog_endog)
params = atleast_2d(asarray(params))
if params.shape[0] == 1:
params = params.T
pred = DataFrame(x @ params, index=exog_endog.index, columns=["predictions"])
return pred | [
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | ext/requests/utils.py | python | add_dict_to_cookiejar | (cj, cookie_dict) | return cookiejar_from_dict(cookie_dict, cj) | Returns a CookieJar from a key/value dictionary.
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nilmtk/nilmtk | d183c8bde7a5d3465ba72b38b7964d57d84f53c2 | nilmtk/elecmeter.py | python | ElecMeter.total_energy | (self, **loader_kwargs) | return self._get_stat_from_cache_or_compute(
nodes, TotalEnergy.results_class(), loader_kwargs) | Parameters
----------
full_results : bool, default=False
**loader_kwargs : key word arguments for DataStore.load()
Returns
-------
if `full_results` is True then return TotalEnergyResults object
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Parameters
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full_results : bool, default=False
**loader_kwargs : key word arguments for DataStore.load()
Returns
-------
if `full_results` is True then return TotalEnergyResults object
else returns a pd.Series with a row for each AC type.
"""
nodes = [Clip, TotalEnergy]
return self._get_stat_from_cache_or_compute(
nodes, TotalEnergy.results_class(), loader_kwargs) | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/encodings/iso8859_13.py | python | IncrementalDecoder.decode | (self, input, final=False) | return codecs.charmap_decode(input,self.errors,decoding_table)[0] | [] | def decode(self, input, final=False):
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readthedocs/sphinx-autoapi | 71c6ceebe0b02c34027fcd3d56c8641e9b94c7af | autoapi/mappers/python/objects.py | python | PythonClass.docstring | (self) | return docstring | [] | def docstring(self):
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openai/baselines | ea25b9e8b234e6ee1bca43083f8f3cf974143998 | baselines/deepq/replay_buffer.py | python | ReplayBuffer.sample | (self, batch_size) | return self._encode_sample(idxes) | Sample a batch of experiences.
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How many transitions to sample.
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batch of observations
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batch of actions executed given obs_batch
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obs_batch: np.array
batch of observations
act_batch: np.array
batch of actions executed given obs_batch
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quantOS-org/JAQS | 959762a518c22592f96433c573d1f99ec0c89152 | jaqs/trade/livetrade.py | python | EventLiveTradeInstance.run | (self) | Listen to certain events and run the EventEngine.
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ales-tsurko/cells | 4cf7e395cd433762bea70cdc863a346f3a6fe1d0 | packaging/macos/python/lib/python3.7/site-packages/pip/_vendor/requests/help.py | python | info | () | return {
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"""Generate information for a bug report."""
try:
platform_info = {
'system': platform.system(),
'release': platform.release(),
}
except IOError:
platform_info = {
'system': 'Unknown',
'release': 'Unknown',
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implementation_info = _implementation()
urllib3_info = {'version': urllib3.__version__}
chardet_info = {'version': chardet.__version__}
pyopenssl_info = {
'version': None,
'openssl_version': '',
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if OpenSSL:
pyopenssl_info = {
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system_ssl_info = {
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aws-samples/aws-kube-codesuite | ab4e5ce45416b83bffb947ab8d234df5437f4fca | src/kubernetes/client/models/v1_node_system_info.py | python | V1NodeSystemInfo.kernel_version | (self, kernel_version) | Sets the kernel_version of this V1NodeSystemInfo.
Kernel Version reported by the node from 'uname -r' (e.g. 3.16.0-0.bpo.4-amd64).
:param kernel_version: The kernel_version of this V1NodeSystemInfo.
:type: str | Sets the kernel_version of this V1NodeSystemInfo.
Kernel Version reported by the node from 'uname -r' (e.g. 3.16.0-0.bpo.4-amd64). | [
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"""
Sets the kernel_version of this V1NodeSystemInfo.
Kernel Version reported by the node from 'uname -r' (e.g. 3.16.0-0.bpo.4-amd64).
:param kernel_version: The kernel_version of this V1NodeSystemInfo.
:type: str
"""
if kernel_version is None:
raise ValueError("Invalid value for `kernel_version`, must not be `None`")
self._kernel_version = kernel_version | [
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PINTO0309/PINTO_model_zoo | 2924acda7a7d541d8712efd7cc4fd1c61ef5bddd | 119_M-LSD/demo/demo_mlsd-lines_tflite.py | python | main | () | [] | def main():
args = get_args()
cap_device = args.device
filepath = args.file
model = args.model
input_shape = [int(i) for i in args.input_shape.split(',')]
score_thr = args.score_thr
dist_thr = args.dist_thr
# Initialize video capture
cap = None
if filepath is None:
cap = cv.VideoCapture(cap_device)
else:
cap = cv.VideoCapture(filepath)
# Load model
interpreter = tf.lite.Interpreter(model_path=model, num_threads=2)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
while True:
start_time = time.time()
# Capture read
ret, frame = cap.read()
if not ret:
break
debug_image = copy.deepcopy(frame)
# Inference execution
lines = pred_lines(
frame,
interpreter,
input_details,
output_details,
input_shape=input_shape,
score_thr=score_thr,
dist_thr=dist_thr,
)
elapsed_time = time.time() - start_time
# Draw
debug_image = draw_debug(
debug_image,
elapsed_time,
lines,
)
cv.imshow('M-LSD(Lines) Demo', debug_image)
key = cv.waitKey(1)
if key == 27: # ESC
break
cap.release()
cv.destroyAllWindows() | [
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apache/incubator-spot | 2d60a2adae7608b43e90ce1b9ec0adf24f6cc8eb | spot-oa/api/resources/configurator.py | python | SecHead.__init__ | (self, fp) | [] | def __init__(self, fp):
self.fp = fp
self.sechead = '[conf]\n' | [
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lazylibrarian/LazyLibrarian | ae3c14e9db9328ce81765e094ab2a14ed7155624 | cherrypy/lib/auth_digest.py | python | get_ha1_dict | (user_ha1_dict) | return get_ha1 | Returns a get_ha1 function which obtains a HA1 password hash from a
dictionary of the form: {username : HA1}.
If you want a dictionary-based authentication scheme, but with
pre-computed HA1 hashes instead of plain-text passwords, use
get_ha1_dict(my_userha1_dict) as the value for the get_ha1
argument to digest_auth(). | Returns a get_ha1 function which obtains a HA1 password hash from a
dictionary of the form: {username : HA1}. | [
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"""Returns a get_ha1 function which obtains a HA1 password hash from a
dictionary of the form: {username : HA1}.
If you want a dictionary-based authentication scheme, but with
pre-computed HA1 hashes instead of plain-text passwords, use
get_ha1_dict(my_userha1_dict) as the value for the get_ha1
argument to digest_auth().
"""
def get_ha1(realm, username):
return user_ha1_dict.get(username)
return get_ha1 | [
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salesforce/hassh | 7e7658819d9722875316ca591d1a09f9fd21ed8c | python/hassh.py | python | server_hassh | (packet) | return record | returns HASSHServer (i.e. SSH Server Fingerprint)
HASSHServer = md5(KEX;EASTC;MASTC;CASTC) | returns HASSHServer (i.e. SSH Server Fingerprint)
HASSHServer = md5(KEX;EASTC;MASTC;CASTC) | [
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"""returns HASSHServer (i.e. SSH Server Fingerprint)
HASSHServer = md5(KEX;EASTC;MASTC;CASTC)
"""
srcip = packet.ip.src
dstip = packet.ip.dst
sport = packet.tcp.srcport
dport = packet.tcp.srcport
protocol = None
key = '{}:{}_{}:{}'.format(srcip, sport, dstip, dport)
if key in protocol_dict:
protocol = protocol_dict[key]
# hasshServer fields
skex = seastc = smastc = scastc = ""
if 'kex_algorithms' in packet.ssh.field_names:
skex = packet.ssh.kex_algorithms
if 'encryption_algorithms_server_to_client' in packet.ssh.field_names:
seastc = packet.ssh.encryption_algorithms_server_to_client
if 'mac_algorithms_server_to_client' in packet.ssh.field_names:
smastc = packet.ssh.mac_algorithms_server_to_client
if 'compression_algorithms_server_to_client' in packet.ssh.field_names:
scastc = packet.ssh.compression_algorithms_server_to_client
# Log other kexinit fields (only in JSON)
slcts = slstc = seacts = smacts = scacts = sshka = ""
if 'languages_client_to_server' in packet.ssh.field_names:
slcts = packet.ssh.languages_client_to_server
if 'languages_server_to_client' in packet.ssh.field_names:
slstc = packet.ssh.languages_server_to_client
if 'encryption_algorithms_client_to_server' in packet.ssh.field_names:
seacts = packet.ssh.encryption_algorithms_client_to_server
if 'mac_algorithms_client_to_server' in packet.ssh.field_names:
smacts = packet.ssh.mac_algorithms_client_to_server
if 'compression_algorithms_client_to_server' in packet.ssh.field_names:
scacts = packet.ssh.compression_algorithms_client_to_server
if 'server_host_key_algorithms' in packet.ssh.field_names:
sshka = packet.ssh.server_host_key_algorithms
# Create hasshServer
hasshs_str = ';'.join([skex, seastc, smastc, scastc])
hasshs = md5(hasshs_str.encode()).hexdigest()
record = {"timestamp": packet.sniff_time.isoformat(),
"sourceIp": packet.ip.src,
"destinationIp": packet.ip.dst,
"sourcePort": packet.tcp.srcport,
"destinationPort": packet.tcp.dstport,
"server": protocol,
"hasshServer": hasshs,
"hasshServerAlgorithms": hasshs_str,
"hasshVersion": HASSH_VERSION,
"skex": skex,
"seastc": seastc,
"smastc": smastc,
"scastc": scastc,
"slcts": slcts,
"slstc": slstc,
"seacts": seacts,
"smacts": smacts,
"scacts": scacts,
"sshka": sshka}
return record | [
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pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/pandas-0.17.0-py3.3-win-amd64.egg/pandas/core/index.py | python | Index.to_native_types | (self, slicer=None, **kwargs) | return values._format_native_types(**kwargs) | slice and dice then format | slice and dice then format | [
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""" slice and dice then format """
values = self
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values = values[slicer]
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Mendeley/mrec | d299e3b9490703843b041e6585643b7e42e229f0 | mrec/__init__.py | python | read_recommender_description | (filepath) | return BaseRecommender.read_recommender_description(filepath) | Read a recommender model description from file after it has
been saved by save_recommender(), without loading all the
associated data into memory.
Parameters
----------
filepath : str
The filepath to read from. | Read a recommender model description from file after it has
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"""
Read a recommender model description from file after it has
been saved by save_recommender(), without loading all the
associated data into memory.
Parameters
----------
filepath : str
The filepath to read from.
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beville/ComicStreamer | 62eb914652695ea41a5e1f0cfbd044cbc6854e84 | libs/comictaggerlib/utils.py | python | getLanguageFromISO | ( iso ) | [] | def getLanguageFromISO( iso ):
if iso == None:
return None
else:
return lang_dict[ iso ] | [
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django/django | 0a17666045de6739ae1c2ac695041823d5f827f7 | django/utils/cache.py | python | get_cache_key | (request, key_prefix=None, method='GET', cache=None) | Return a cache key based on the request URL and query. It can be used
in the request phase because it pulls the list of headers to take into
account from the global URL registry and uses those to build a cache key
to check against.
If there isn't a headerlist stored, return None, indicating that the page
needs to be rebuilt. | Return a cache key based on the request URL and query. It can be used
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"""
Return a cache key based on the request URL and query. It can be used
in the request phase because it pulls the list of headers to take into
account from the global URL registry and uses those to build a cache key
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If there isn't a headerlist stored, return None, indicating that the page
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"""
if key_prefix is None:
key_prefix = settings.CACHE_MIDDLEWARE_KEY_PREFIX
cache_key = _generate_cache_header_key(key_prefix, request)
if cache is None:
cache = caches[settings.CACHE_MIDDLEWARE_ALIAS]
headerlist = cache.get(cache_key)
if headerlist is not None:
return _generate_cache_key(request, method, headerlist, key_prefix)
else:
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tav/pylibs | 3c16b843681f54130ee6a022275289cadb2f2a69 | pycrypto/lib/Crypto/Random/_UserFriendlyRNG.py | python | RNGFile.__exit__ | (self) | PEP 343 support | PEP 343 support | [
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self.close() | [
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omriher/CapTipper | 3fb2836c0afe60eb6bd5902b4214f564268e9b4d | jsontemplate/jsontemplate.py | python | expand | (template_str, dictionary, **kwargs) | return t.expand(dictionary) | Free function to expands a template string with a data dictionary.
This is useful for cases where you don't care about saving the result of
compilation (similar to re.match('.*', s) vs DOT_STAR.match(s)) | Free function to expands a template string with a data dictionary. | [
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"""Free function to expands a template string with a data dictionary.
This is useful for cases where you don't care about saving the result of
compilation (similar to re.match('.*', s) vs DOT_STAR.match(s))
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t = Template(template_str, **kwargs)
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pypr/pysph | 9cb9a859934939307c65a25cbf73e4ecc83fea4a | pysph/solver/controller.py | python | CommandManager.cont | (self) | continue after a pause command | continue after a pause command | [
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eirannejad/pyRevit | 49c0b7eb54eb343458ce1365425e6552d0c47d44 | site-packages/sqlalchemy/sql/selectable.py | python | HasPrefixes.prefix_with | (self, *expr, **kw) | r"""Add one or more expressions following the statement keyword, i.e.
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stmt = table.insert().prefix_with("LOW_PRIORITY", dialect="mysql")
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liuyubobobo/Play-with-Linear-Algebra | e86175adb908b03756618fbeeeadb448a3551321 | 03-More-about-Vectors/05-Implementations-of-Dot-Product/playLA/Vector.py | python | Vector.norm | (self) | return math.sqrt(sum(e**2 for e in self)) | 返回向量的模 | 返回向量的模 | [
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etetoolkit/ete | 2b207357dc2a40ccad7bfd8f54964472c72e4726 | ete3/tools/ete_build_lib/curses_gui.py | python | main | (scr) | return | [] | def main(scr):
curses.init_pair(1, curses.COLOR_WHITE, curses.COLOR_BLACK)
curses.init_pair(2, curses.COLOR_MAGENTA, curses.COLOR_BLACK)
curses.init_pair(3, curses.COLOR_GREEN, curses.COLOR_BLACK)
curses.init_pair(4, curses.COLOR_YELLOW, curses.COLOR_BLACK)
curses.init_pair(5, curses.COLOR_RED, curses.COLOR_BLACK)
curses.init_pair(6, curses.COLOR_RED, curses.COLOR_WHITE)
dbg_h = 40
WIN = {}
WIN[0] = scr
h, w = WIN[0].getmaxyx()
WIN[1] = curses.newwin(h-2, w/2, 1,1)
WIN[2] = curses.newwin(h-dbg_h, (w/2)-1, 1, (w/2)+2)
WIN[3] = curses.newwin(dbg_h, (w/2)-1, h-dbg_h-1, (w/2)-2)
p = curses.newpad(1000, 1000)
p.addstr("HOLA\n")
p.addstr("AMIGO\n")
p.addstr("DE VIGO")
p.refresh(0, 0, 5, 30, 5, 35)
key = p.getch()
return
for w in list(WIN.values()):
w.keypad(1)
w.idlok(True)
w.scrollok(True)
p.refresh(0, 0, 10, 10, 20, 20)
return
C = CursesList(WIN[2])
for line in open("/var/log/Xorg.0.log"):
C.add_item(line.strip())
C.refresh()
#WIN[1].addstr("(%d)" %len(C._items))
while 1:
key = WIN[2].getch()
WIN[1].addstr("%s (%d)" %(key, C._top))
WIN[1].refresh()
if key == 113:
break
elif key == curses.KEY_UP:
C.scroll(-1)
elif key == curses.KEY_DOWN:
C.scroll(1)
elif key == curses.KEY_NPAGE:
C.scroll(10)
elif key == curses.KEY_PPAGE:
C.scroll(-10)
elif key == curses.KEY_END:
C.goto_end()
elif key == curses.KEY_HOME:
C.goto_start()
else:
C.refresh() | [
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google-research/language | 61fa7260ac7d690d11ef72ca863e45a37c0bdc80 | language/serene/wiki_index.py | python | ShardedEmbPaths.files | (self, tmp = False) | return sharded_files | Return the files for the sharded embeddings.
Args:
tmp: Whether to return paths in /tmp or not
Returns:
Paths of all sharded files. | Return the files for the sharded embeddings. | [
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"""Return the files for the sharded embeddings.
Args:
tmp: Whether to return paths in /tmp or not
Returns:
Paths of all sharded files.
"""
sharded_files = []
for shard in range(self._n_shards):
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/timeit.py | python | Timer.repeat | (self, repeat=default_repeat, number=default_number) | return r | Call timeit() a few times.
This is a convenience function that calls the timeit()
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specifies how many times to call timeit(), defaulting to 3;
the second argument specifies the timer argument, defaulting
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Note: it's tempting to calculate mean and standard deviation
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"""Call timeit() a few times.
This is a convenience function that calls the timeit()
repeatedly, returning a list of results. The first argument
specifies how many times to call timeit(), defaulting to 3;
the second argument specifies the timer argument, defaulting
to one million.
Note: it's tempting to calculate mean and standard deviation
from the result vector and report these. However, this is not
very useful. In a typical case, the lowest value gives a
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snippet; higher values in the result vector are typically not
caused by variability in Python's speed, but by other
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r = []
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TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e | Projects/Word2Word/make.py | python | normalize | (tokens, ignore_first_word) | return tokens | If ignore_firs_word is True,
We drop the first word or token
because its true case is unclear. | If ignore_firs_word is True,
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'''If ignore_firs_word is True,
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because its true case is unclear.'''
if ignore_first_word:
tokens = tokens[1:]
return tokens | [
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ivre/ivre | 5728855b51c0ae2e59450a1c3a782febcad2128b | ivre/web/app.py | python | post_nmap | (subdb) | return {"count": count} | Add records to Nmap & View databases
:param str subdb: database to query (must be "scans" or "view")
:form categories: a coma-separated list of categories
:form source: the source of the scan results (mandatory)
:form result: scan results (as XML or JSON files)
:status 200: no error
:status 400: invalid referer, source or username missing
:>json int count: number of inserted results | Add records to Nmap & View databases | [
"Add",
"records",
"to",
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"&",
"View",
"databases"
] | def post_nmap(subdb):
"""Add records to Nmap & View databases
:param str subdb: database to query (must be "scans" or "view")
:form categories: a coma-separated list of categories
:form source: the source of the scan results (mandatory)
:form result: scan results (as XML or JSON files)
:status 200: no error
:status 400: invalid referer, source or username missing
:>json int count: number of inserted results
"""
referer, source, categories, files = parse_form()
count = import_files(subdb, source, categories, files)
if request.params.get("output") == "html":
response.set_header("Refresh", "5;url=%s" % referer)
return """<html>
<head>
<title>IVRE Web UI</title>
</head>
<body style="padding-top: 2%%; padding-left: 2%%">
<h1>%d result%s uploaded</h1>
</body>
</html>""" % (
count,
"s" if count > 1 else "",
)
return {"count": count} | [
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kalliope-project/kalliope | 7b2bb4671c8fbfa0ea9f768c84994fe75da974eb | kalliope/core/ConfigurationManager/SettingLoader.py | python | SettingLoader._get_settings | (self) | return setting_object | Class Methods which loads default or the provided YAML file and return a Settings Object
:return: The loaded Settings
:rtype: Settings
:Example:
settings = SettingLoader.get_settings(file_path="/var/tmp/settings.yml")
.. seealso:: Settings
.. warnings:: Class Method | Class Methods which loads default or the provided YAML file and return a Settings Object | [
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"""
Class Methods which loads default or the provided YAML file and return a Settings Object
:return: The loaded Settings
:rtype: Settings
:Example:
settings = SettingLoader.get_settings(file_path="/var/tmp/settings.yml")
.. seealso:: Settings
.. warnings:: Class Method
"""
# create a new setting
setting_object = Settings()
# Get the setting parameters
settings = self._get_yaml_config()
default_stt_name = self._get_default_speech_to_text(settings)
default_tts_name = self._get_default_text_to_speech(settings)
default_trigger_name = self._get_default_trigger(settings)
default_player_name = self._get_default_player(settings)
stts = self._get_stts(settings)
ttss = self._get_ttss(settings)
triggers = self._get_triggers(settings)
players = self._get_players(settings)
rest_api = self._get_rest_api(settings)
cache_path = self._get_cache_path(settings)
resources = self._get_resources(settings)
variables = self._get_variables(settings)
options = self._get_options(settings)
hooks = self._get_hooks(settings)
tracker_anonymous_usage_stats_id = self._get_anonymous_usage_stats(settings)
# Load the setting singleton with the parameters
setting_object.default_tts_name = default_tts_name
setting_object.default_stt_name = default_stt_name
setting_object.default_trigger_name = default_trigger_name
setting_object.default_player_name = default_player_name
setting_object.stts = stts
setting_object.ttss = ttss
setting_object.triggers = triggers
setting_object.players = players
setting_object.rest_api = rest_api
setting_object.cache_path = cache_path
setting_object.resources = resources
setting_object.variables = variables
setting_object.options = options
setting_object.hooks = hooks
setting_object.tracker_anonymous_usage_stats_id = tracker_anonymous_usage_stats_id
return setting_object | [
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aws/aws-iot-device-sdk-python | 90d7b05749e2da7a13193024c720e3c8d9bf1157 | AWSIoTPythonSDK/core/protocol/paho/client.py | python | Client.reconnect | (self) | return self._send_connect(self._keepalive, self._clean_session) | Reconnect the client after a disconnect. Can only be called after
connect()/connect_async(). | Reconnect the client after a disconnect. Can only be called after
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] | def reconnect(self):
"""Reconnect the client after a disconnect. Can only be called after
connect()/connect_async()."""
if len(self._host) == 0:
raise ValueError('Invalid host.')
if self._port <= 0:
raise ValueError('Invalid port number.')
self._in_packet = {
"command": 0,
"have_remaining": 0,
"remaining_count": [],
"remaining_mult": 1,
"remaining_length": 0,
"packet": b"",
"to_process": 0,
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self._out_packet_mutex.acquire()
self._out_packet = []
self._out_packet_mutex.release()
self._current_out_packet_mutex.acquire()
self._current_out_packet = None
self._current_out_packet_mutex.release()
self._msgtime_mutex.acquire()
self._last_msg_in = time.time()
self._last_msg_out = time.time()
self._msgtime_mutex.release()
self._ping_t = 0
self._state_mutex.acquire()
self._state = mqtt_cs_new
self._state_mutex.release()
if self._ssl:
self._ssl.close()
self._ssl = None
self._sock = None
elif self._sock:
self._sock.close()
self._sock = None
# Put messages in progress in a valid state.
self._messages_reconnect_reset()
try:
if self._socket_factory:
sock = self._socket_factory()
elif (sys.version_info[0] == 2 and sys.version_info[1] < 7) or (sys.version_info[0] == 3 and sys.version_info[1] < 2):
sock = socket.create_connection((self._host, self._port))
else:
sock = socket.create_connection((self._host, self._port), source_address=(self._bind_address, 0))
except socket.error as err:
if err.errno != errno.EINPROGRESS and err.errno != errno.EWOULDBLOCK and err.errno != EAGAIN:
raise
verify_hostname = self._tls_insecure is False # Decide whether we need to verify hostname
if self._tls_ca_certs is not None:
if self._useSecuredWebsocket:
# Never assign to ._ssl before wss handshake is finished
# Non-None value for ._ssl will allow ops before wss-MQTT connection is established
rawSSL = ssl.wrap_socket(sock, ca_certs=self._tls_ca_certs, cert_reqs=ssl.CERT_REQUIRED) # Add server certificate verification
rawSSL.setblocking(0) # Non-blocking socket
self._ssl = SecuredWebSocketCore(rawSSL, self._host, self._port, self._AWSAccessKeyIDCustomConfig, self._AWSSecretAccessKeyCustomConfig, self._AWSSessionTokenCustomConfig) # Override the _ssl socket
# self._ssl.enableDebug()
elif self._alpn_protocols is not None:
# SSLContext is required to enable ALPN support
# Assuming Python 2.7.10+/3.5+ till the end of this elif branch
ssl_context = SSLContextBuilder()\
.with_ca_certs(self._tls_ca_certs)\
.with_cert_key_pair(self._tls_certfile, self._tls_keyfile)\
.with_cert_reqs(self._tls_cert_reqs)\
.with_check_hostname(True)\
.with_ciphers(self._tls_ciphers)\
.with_alpn_protocols(self._alpn_protocols)\
.build()
self._ssl = ssl_context.wrap_socket(sock, server_hostname=self._host, do_handshake_on_connect=False)
verify_hostname = False # Since check_hostname in SSLContext is already set to True, no need to verify it again
self._ssl.do_handshake()
else:
self._ssl = ssl.wrap_socket(
sock,
certfile=self._tls_certfile,
keyfile=self._tls_keyfile,
ca_certs=self._tls_ca_certs,
cert_reqs=self._tls_cert_reqs,
ssl_version=self._tls_version,
ciphers=self._tls_ciphers)
if verify_hostname:
if sys.version_info[0] < 3 or (sys.version_info[0] == 3 and sys.version_info[1] < 5): # No IP host match before 3.5.x
self._tls_match_hostname()
else:
ssl.match_hostname(self._ssl.getpeercert(), self._host)
self._sock = sock
if self._ssl and not self._useSecuredWebsocket:
self._ssl.setblocking(0) # For X.509 cert mutual auth.
elif not self._ssl:
self._sock.setblocking(0) # For plain socket
else:
pass # For MQTT over WebSocket
return self._send_connect(self._keepalive, self._clean_session) | [
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rspivak/lsbasi | 07e1a14516156a21ebe2d82e0bae4bba5ad73dd6 | part16/spi.py | python | Parser.parse | (self) | return node | program : PROGRAM variable SEMI block DOT
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| variable
variable: ID | program : PROGRAM variable SEMI block DOT | [
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"""
program : PROGRAM variable SEMI block DOT
block : declarations compound_statement
declarations : (VAR (variable_declaration SEMI)+)? procedure_declaration*
variable_declaration : ID (COMMA ID)* COLON type_spec
procedure_declaration :
PROCEDURE ID (LPAREN formal_parameter_list RPAREN)? SEMI block SEMI
formal_params_list : formal_parameters
| formal_parameters SEMI formal_parameter_list
formal_parameters : ID (COMMA ID)* COLON type_spec
type_spec : INTEGER | REAL
compound_statement : BEGIN statement_list END
statement_list : statement
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factor : PLUS factor
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| LPAREN expr RPAREN
| variable
variable: ID
"""
node = self.program()
if self.current_token.type != TokenType.EOF:
self.error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self.current_token,
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return node | [
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hankcs/HanLP | 6c02812969c4827d74b404c3ad4207f71ca9165a | hanlp/common/torch_component.py | python | TorchComponent.save | (self, save_dir: str, **kwargs) | Save this component to a directory.
Args:
save_dir: The directory to save this component.
**kwargs: Not used. | Save this component to a directory. | [
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"""Save this component to a directory.
Args:
save_dir: The directory to save this component.
**kwargs: Not used.
"""
self.save_config(save_dir)
self.save_vocabs(save_dir)
self.save_weights(save_dir) | [
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geometalab/Vector-Tiles-Reader-QGIS-Plugin | a31ae86959c8f3b7d6f332f84191cd7ca4683e1d | ext-libs/google/protobuf/descriptor_pool.py | python | DescriptorPool.FindEnumTypeByName | (self, full_name) | return self._enum_descriptors[full_name] | Loads the named enum descriptor from the pool.
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full_name: The full name of the enum descriptor to load.
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"""Loads the named enum descriptor from the pool.
Args:
full_name: The full name of the enum descriptor to load.
Returns:
The enum descriptor for the named type.
"""
full_name = _NormalizeFullyQualifiedName(full_name)
if full_name not in self._enum_descriptors:
self.FindFileContainingSymbol(full_name)
return self._enum_descriptors[full_name] | [
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PokemonGoF/PokemonGo-Bot-Desktop | 4bfa94f0183406c6a86f93645eff7abd3ad4ced8 | build/pywin/Lib/mutex.py | python | mutex.lock | (self, function, argument) | Lock a mutex, call the function with supplied argument
when it is acquired. If the mutex is already locked, place
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/scatterpolar/marker/colorbar/_title.py | python | Title.__init__ | (self, arg=None, font=None, side=None, text=None, **kwargs) | Construct a new Title object
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arg
dict of properties compatible with this constructor or
an instance of :class:`plotly.graph_objs.scatterpolar.m
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Sets this color bar's title font. Note that the title's
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dict of properties compatible with this constructor or
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super(Title, self).__init__("title")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = _copy.copy(arg)
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# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
# Populate data dict with properties
# ----------------------------------
_v = arg.pop("font", None)
_v = font if font is not None else _v
if _v is not None:
self["font"] = _v
_v = arg.pop("side", None)
_v = side if side is not None else _v
if _v is not None:
self["side"] = _v
_v = arg.pop("text", None)
_v = text if text is not None else _v
if _v is not None:
self["text"] = _v
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False | [
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ChintanTrivedi/DeepGamingAI_FIFA | b79a5b670756056b7b6aedd2c5c84fd5f59d569e | utils/dataset_util.py | python | read_examples_list | (path) | return [line.strip().split(' ')[0] for line in lines] | Read list of training or validation examples.
The file is assumed to contain a single example per line where the first
token in the line is an identifier that allows us to find the image and
annotation xml for that example.
For example, the line:
xyz 3
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token in the line is an identifier that allows us to find the image and
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For example, the line:
xyz 3
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with tf.gfile.GFile(path) as fid:
lines = fid.readlines()
return [line.strip().split(' ')[0] for line in lines] | [
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FitMachineLearning/FitML | a60f49fce1799ca4b11b48307441325b6272719a | ParameterNoising/Tensorflow/BipedalWalker_v1.0.py | python | actor_experience_replay | (memSA,memR,memS,memA,memW,num_epoch=1) | train_B = train_B[tW.flatten()>0]
#print("%8d were better results than pr"%np.alen(tX_train))
tX = tX[train_B,:]
tY = tY[train_B,:]
tW = tW[train_B,:]
tR = tR[train_B,:]
#print("tW",tW) | train_B = train_B[tW.flatten()>0] | [
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tSA = (memSA)
tR = (memR)
tX = (memS)
tY = (memA)
tW = (memW)
target = tR.mean() #+ math.fabs( tR.mean() - tR.max() )/2 #+ math.fabs( tR.mean() - tR.max() )/4
train_C = np.arange(np.alen(tR))
train_C = train_C[tR.flatten()>target]
tX = tX[train_C,:]
tY = tY[train_C,:]
tW = tW[train_C,:]
tR = tR[train_C,:]
train_A = np.random.randint(tY.shape[0],size=int(min(experience_replay_size,np.alen(tR) )))
tX = tX[train_A,:]
tY = tY[train_A,:]
tW = tW[train_A,:]
tR = tR[train_A,:]
train_B = np.arange(np.alen(tR))
tX_train = np.zeros(shape=(1,num_env_variables))
tY_train = np.zeros(shape=(1,num_env_actions))
for i in range(np.alen(train_B)):
#pr = predictTotalRewards(tX[i],tY[i])
''' YOU CAN"T USE predictTotalRewards
IF YOU DON"T TRAIN THE QMODEL
if tR[i][0] < pr:
tW[i][0] = -1
else:
'''
d = math.fabs( memoryR.max() - target)
tW[i] = math.fabs(tR[i]-(target+0.000000000005)) / d
#tW[i] = math.exp(1-(1/tW[i]**2))
tW[i]= 0.0000000000000005
if (tR[i]>target):
tW[i]=0.5
if (tR[i]>max_game_average):
tW[i] = 1
if tW[i]> np.random.rand(1):
tX_train = np.vstack((tX_train,tX[i]))
tY_train = np.vstack((tY_train,tY[i]))
#print ("tW",tW[i],"exp", math.exp(1-(1/tW[i]**2)))
#tW[i] = math.exp(1-(1/tW[i]**2))
#tW[i] = 1
#print("tW[i] %3.1f tR %3.2f target %3.2f max_game_average %3.2f "%(tW[i],tR[i],target,max_game_average))
'''
train_B = train_B[tW.flatten()>0]
#print("%8d were better results than pr"%np.alen(tX_train))
tX = tX[train_B,:]
tY = tY[train_B,:]
tW = tW[train_B,:]
tR = tR[train_B,:]
#print("tW",tW)
'''
#print("%8d were better results than pr"%np.alen(tX_train))
''' REMOVE FIRST ELEMENT BEFORE TRAINING '''
tX_train = tX_train[1:]
tY_train = tY_train[1:]
#print("%8d were better After removing first element"%np.alen(tX_train))
if np.alen(tX_train)>0:
#tW = scale_weights(tR,tW)
#print("# setps short listed ", np.alen(tR))
#action_predictor_model.fit(tX_train,tY_train, batch_size=mini_batch, nb_epoch=num_epochs,verbose=0)
for num_epoch in range(training_epochs):
sess.run(aptrain_op, feed_dict={apdataX: tX_train, apdataY: tY_train}) | [
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OpenMDAO/OpenMDAO-Framework | f2e37b7de3edeaaeb2d251b375917adec059db9b | openmdao.main/src/openmdao/main/datatypes/array.py | python | Array.validate | (self, obj, name, value) | return new_val | Validates that a specified value is valid for this trait.
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/esp8266_clients/venv/lib/python2.7/site-packages/pip/vcs/__init__.py | python | VersionControl.get_url | (self, location) | Return the url used at location
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/v5_1/git/git_client_base.py | python | GitClientBase.create_annotated_tag | (self, tag_object, project, repository_id) | return self._deserialize('GitAnnotatedTag', response) | CreateAnnotatedTag.
[Preview API] Create an annotated tag.
:param :class:`<GitAnnotatedTag> <azure.devops.v5_1.git.models.GitAnnotatedTag>` tag_object: Object containing details of tag to be created.
:param str project: Project ID or project name
:param str repository_id: ID or name of the repository.
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[Preview API] Create an annotated tag.
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:param str project: Project ID or project name
:param str repository_id: ID or name of the repository.
:rtype: :class:`<GitAnnotatedTag> <azure.devops.v5_1.git.models.GitAnnotatedTag>` | [
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[Preview API] Create an annotated tag.
:param :class:`<GitAnnotatedTag> <azure.devops.v5_1.git.models.GitAnnotatedTag>` tag_object: Object containing details of tag to be created.
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meetbill/zabbix_manager | 739e5b51facf19cc6bda2b50f29108f831cf833e | ZabbixTool/lib_zabbix/w_lib/mylib/xlwt/Cell.py | python | FormulaCell.__init__ | (self, rowx, colx, xf_idx, frmla, calc_flags=0) | [] | def __init__(self, rowx, colx, xf_idx, frmla, calc_flags=0):
self.rowx = rowx
self.colx = colx
self.xf_idx = xf_idx
self.frmla = frmla
self.calc_flags = calc_flags | [
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hzlzh/AlfredWorkflow.com | 7055f14f6922c80ea5943839eb0caff11ae57255 | Sources/Workflows/Toggl-Time-Tracking/alp/request/requests/packages/oauthlib/oauth2/draft25/parameters.py | python | parse_authorization_code_response | (uri, state=None) | return params | Parse authorization grant response URI into a dict.
If the resource owner grants the access request, the authorization
server issues an authorization code and delivers it to the client by
adding the following parameters to the query component of the
redirection URI using the "application/x-www-form-urlencoded" format:
code
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REQUIRED if the "state" parameter was present in the client
authorization request. The exact value received from the
client.
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sending the following HTTP response:
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Location: https://client.example.com/cb?code=SplxlOBeZQQYbYS6WxSbIA
&state=xyz | Parse authorization grant response URI into a dict. | [
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"""Parse authorization grant response URI into a dict.
If the resource owner grants the access request, the authorization
server issues an authorization code and delivers it to the client by
adding the following parameters to the query component of the
redirection URI using the "application/x-www-form-urlencoded" format:
code
REQUIRED. The authorization code generated by the
authorization server. The authorization code MUST expire
shortly after it is issued to mitigate the risk of leaks. A
maximum authorization code lifetime of 10 minutes is
RECOMMENDED. The client MUST NOT use the authorization code
more than once. If an authorization code is used more than
once, the authorization server MUST deny the request and SHOULD
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HTTP/1.1 302 Found
Location: https://client.example.com/cb?code=SplxlOBeZQQYbYS6WxSbIA
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"""
query = urlparse.urlparse(uri).query
params = dict(urlparse.parse_qsl(query))
if not u'code' in params:
raise KeyError("Missing code parameter in response.")
if state and params.get(u'state', None) != state:
raise ValueError("Mismatching or missing state in response.")
return params | [
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"if",... | https://github.com/hzlzh/AlfredWorkflow.com/blob/7055f14f6922c80ea5943839eb0caff11ae57255/Sources/Workflows/Toggl-Time-Tracking/alp/request/requests/packages/oauthlib/oauth2/draft25/parameters.py#L95-L136 | |
naftaliharris/tauthon | 5587ceec329b75f7caf6d65a036db61ac1bae214 | Lib/logging/__init__.py | python | exception | (msg, *args, **kwargs) | Log a message with severity 'ERROR' on the root logger,
with exception information. | Log a message with severity 'ERROR' on the root logger,
with exception information. | [
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] | def exception(msg, *args, **kwargs):
"""
Log a message with severity 'ERROR' on the root logger,
with exception information.
"""
kwargs['exc_info'] = 1
error(msg, *args, **kwargs) | [
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yuantiku/fairseq-gec | 10aafebc482706346f768e4f18a9813153cb1ecc | fairseq/optim/lr_scheduler/fairseq_lr_scheduler.py | python | FairseqLRScheduler.step_update | (self, num_updates) | return self.optimizer.get_lr() | Update the learning rate after each update. | Update the learning rate after each update. | [
"Update",
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"learning",
"rate",
"after",
"each",
"update",
"."
] | def step_update(self, num_updates):
"""Update the learning rate after each update."""
return self.optimizer.get_lr() | [
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timkpaine/tributary | 90acb236d96a23c0c4794fd0f2da82c66060f737 | tributary/lazy/node.py | python | Node.__call__ | (self, node_tweaks=None, *positional_tweaks, **keyword_tweaks) | return self.value() | Lazily re-evaluate the node
Args:
node_tweaks (dict): A dict mapping node to tweaked value
positional_tweaks (VAR_POSITIONAL): A tuple of positional tweaks to apply
keyword_tweaks (VAR_KEYWORD): A dict of keyword tweaks to apply
How it works: The "original caller" is the node being evaluted w/ tweaks.
It will consume the positional_tweaks` and `keyword_tweaks`, which look like:
(1, 2,) , {"a": 5, "b": 10}
and join them with `node_tweaks` in a dict mapping node->tweaked value, e.g.
{Node1: 1, Node2: 2, NodeA: 5, NodeB: 10}
and pass this dict up the call tree in `node_tweaks`.
This dict is carried through all node operations through the entire call tree.
If a node is being evaluated and is in `node_tweaks`, it ignores recalculation
and returns the tweaked value.
Returns:
Any: the value, either via re-evaluation (if self or upstream dirty),
or the previously computed value | Lazily re-evaluate the node | [
"Lazily",
"re",
"-",
"evaluate",
"the",
"node"
] | def __call__(self, node_tweaks=None, *positional_tweaks, **keyword_tweaks):
"""Lazily re-evaluate the node
Args:
node_tweaks (dict): A dict mapping node to tweaked value
positional_tweaks (VAR_POSITIONAL): A tuple of positional tweaks to apply
keyword_tweaks (VAR_KEYWORD): A dict of keyword tweaks to apply
How it works: The "original caller" is the node being evaluted w/ tweaks.
It will consume the positional_tweaks` and `keyword_tweaks`, which look like:
(1, 2,) , {"a": 5, "b": 10}
and join them with `node_tweaks` in a dict mapping node->tweaked value, e.g.
{Node1: 1, Node2: 2, NodeA: 5, NodeB: 10}
and pass this dict up the call tree in `node_tweaks`.
This dict is carried through all node operations through the entire call tree.
If a node is being evaluated and is in `node_tweaks`, it ignores recalculation
and returns the tweaked value.
Returns:
Any: the value, either via re-evaluation (if self or upstream dirty),
or the previously computed value
"""
node_tweaks = node_tweaks or {}
if not isinstance(node_tweaks, dict):
# treat node_tweak argument as positional tweak
positional_tweaks = list(positional_tweaks) + [node_tweaks]
node_tweaks = {}
# instantiate tweaks
tweaks = {}
# update with provided
tweaks.update(node_tweaks)
for i, positional_tweak in enumerate(positional_tweaks):
tweaks[self._get_arg(i)] = positional_tweak
for k, keyword_tweak in keyword_tweaks.items():
tweaks[self._get_kwarg(k)] = keyword_tweak
# tweak self
if tweaks:
self._tweak(tweaks)
# calculate new value
computed = self._recompute(tweaks)
if tweaks:
# untweak self
self._untweak()
# return the calculation result, not my current value
return computed
# otherwise return my permanent value, should equal computed
# assert self.value() == computed
return self.value() | [
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... | https://github.com/timkpaine/tributary/blob/90acb236d96a23c0c4794fd0f2da82c66060f737/tributary/lazy/node.py#L615-L671 | |
OpenMDAO/OpenMDAO1 | 791a6fbbb7d266f3dcbc1f7bde3ae03a70dc1317 | openmdao/components/exec_comp.py | python | ExecComp.solve_nonlinear | (self, params, unknowns, resids) | Executes this component's assignment statemens.
Args
----
params : `VecWrapper`, optional
`VecWrapper` containing parameters. (p)
unknowns : `VecWrapper`, optional
`VecWrapper` containing outputs and states. (u)
resids : `VecWrapper`, optional
`VecWrapper` containing residuals. (r) | Executes this component's assignment statemens. | [
"Executes",
"this",
"component",
"s",
"assignment",
"statemens",
"."
] | def solve_nonlinear(self, params, unknowns, resids):
"""
Executes this component's assignment statemens.
Args
----
params : `VecWrapper`, optional
`VecWrapper` containing parameters. (p)
unknowns : `VecWrapper`, optional
`VecWrapper` containing outputs and states. (u)
resids : `VecWrapper`, optional
`VecWrapper` containing residuals. (r)
"""
for expr in self._codes:
exec(expr, _expr_dict, _UPDict(unknowns, params, self._to_colons)) | [
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