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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/django-auth-ldap-1.3.0/django_auth_ldap/backend.py | python | _LDAPUser._populate_user | (self) | Populates our User object with information from the LDAP directory. | Populates our User object with information from the LDAP directory. | [
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"LDAP",
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] | def _populate_user(self):
"""
Populates our User object with information from the LDAP directory.
"""
self._populate_user_from_attributes()
self._populate_user_from_group_memberships() | [
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django/django | 0a17666045de6739ae1c2ac695041823d5f827f7 | django/db/models/base.py | python | full_clean | (self, exclude=None, validate_unique=True) | Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur. | Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur. | [
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"""
Call clean_fields(), clean(), and validate_unique() on the model.
Raise a ValidationError for any errors that occur.
"""
errors = {}
if exclude is None:
exclude = []
else:
exclude = list(exclude)
try:
self.clean_fields(exclude=exclude)
except ValidationError as e:
errors = e.update_error_dict(errors)
# Form.clean() is run even if other validation fails, so do the
# same with Model.clean() for consistency.
try:
self.clean()
except ValidationError as e:
errors = e.update_error_dict(errors)
# Run unique checks, but only for fields that passed validation.
if validate_unique:
for name in errors:
if name != NON_FIELD_ERRORS and name not in exclude:
exclude.append(name)
try:
self.validate_unique(exclude=exclude)
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errors = e.update_error_dict(errors)
if errors:
raise ValidationError(errors) | [
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boto/boto | b2a6f08122b2f1b89888d2848e730893595cd001 | boto/ec2/connection.py | python | EC2Connection.trim_snapshots | (self, hourly_backups=8, daily_backups=7,
weekly_backups=4, monthly_backups=True) | Trim excess snapshots, based on when they were taken. More current
snapshots are retained, with the number retained decreasing as you
move back in time.
If ebs volumes have a 'Name' tag with a value, their snapshots
will be assigned the same tag when they are created. The values
of the 'Name' tags for snapshots are used by this function to
group snapshots taken from the same volume (or from a series
of like-named volumes over time) for trimming.
For every group of like-named snapshots, this function retains
the newest and oldest snapshots, as well as, by default, the
first snapshots taken in each of the last eight hours, the first
snapshots taken in each of the last seven days, the first snapshots
taken in the last 4 weeks (counting Midnight Sunday morning as
the start of the week), and the first snapshot from the first
day of each month forever.
:type hourly_backups: int
:param hourly_backups: How many recent hourly backups should be saved.
:type daily_backups: int
:param daily_backups: How many recent daily backups should be saved.
:type weekly_backups: int
:param weekly_backups: How many recent weekly backups should be saved.
:type monthly_backups: int
:param monthly_backups: How many monthly backups should be saved. Use True for no limit. | Trim excess snapshots, based on when they were taken. More current
snapshots are retained, with the number retained decreasing as you
move back in time. | [
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weekly_backups=4, monthly_backups=True):
"""
Trim excess snapshots, based on when they were taken. More current
snapshots are retained, with the number retained decreasing as you
move back in time.
If ebs volumes have a 'Name' tag with a value, their snapshots
will be assigned the same tag when they are created. The values
of the 'Name' tags for snapshots are used by this function to
group snapshots taken from the same volume (or from a series
of like-named volumes over time) for trimming.
For every group of like-named snapshots, this function retains
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first snapshots taken in each of the last eight hours, the first
snapshots taken in each of the last seven days, the first snapshots
taken in the last 4 weeks (counting Midnight Sunday morning as
the start of the week), and the first snapshot from the first
day of each month forever.
:type hourly_backups: int
:param hourly_backups: How many recent hourly backups should be saved.
:type daily_backups: int
:param daily_backups: How many recent daily backups should be saved.
:type weekly_backups: int
:param weekly_backups: How many recent weekly backups should be saved.
:type monthly_backups: int
:param monthly_backups: How many monthly backups should be saved. Use True for no limit.
"""
# This function first builds up an ordered list of target times
# that snapshots should be saved for (last 8 hours, last 7 days, etc.).
# Then a map of snapshots is constructed, with the keys being
# the snapshot / volume names and the values being arrays of
# chronologically sorted snapshots.
# Finally, for each array in the map, we go through the snapshot
# array and the target time array in an interleaved fashion,
# deleting snapshots whose start_times don't immediately follow a
# target time (we delete a snapshot if there's another snapshot
# that was made closer to the preceding target time).
now = datetime.utcnow()
last_hour = datetime(now.year, now.month, now.day, now.hour)
last_midnight = datetime(now.year, now.month, now.day)
last_sunday = datetime(now.year, now.month, now.day) - timedelta(days=(now.weekday() + 1) % 7)
start_of_month = datetime(now.year, now.month, 1)
target_backup_times = []
# there are no snapshots older than 1/1/2007
oldest_snapshot_date = datetime(2007, 1, 1)
for hour in range(0, hourly_backups):
target_backup_times.append(last_hour - timedelta(hours=hour))
for day in range(0, daily_backups):
target_backup_times.append(last_midnight - timedelta(days=day))
for week in range(0, weekly_backups):
target_backup_times.append(last_sunday - timedelta(weeks=week))
one_day = timedelta(days=1)
monthly_snapshots_added = 0
while (start_of_month > oldest_snapshot_date and
(monthly_backups is True or
monthly_snapshots_added < monthly_backups)):
# append the start of the month to the list of
# snapshot dates to save:
target_backup_times.append(start_of_month)
monthly_snapshots_added += 1
# there's no timedelta setting for one month, so instead:
# decrement the day by one, so we go to the final day of
# the previous month...
start_of_month -= one_day
# ... and then go to the first day of that previous month:
start_of_month = datetime(start_of_month.year,
start_of_month.month, 1)
temp = []
for t in target_backup_times:
if temp.__contains__(t) == False:
temp.append(t)
# sort to make the oldest dates first, and make sure the month start
# and last four week's start are in the proper order
target_backup_times = sorted(temp)
# get all the snapshots, sort them by date and time, and
# organize them into one array for each volume:
all_snapshots = self.get_all_snapshots(owner = 'self')
all_snapshots.sort(key=lambda x: x.start_time)
snaps_for_each_volume = {}
for snap in all_snapshots:
# the snapshot name and the volume name are the same.
# The snapshot name is set from the volume
# name at the time the snapshot is taken
volume_name = snap.tags.get('Name')
if volume_name:
# only examine snapshots that have a volume name
snaps_for_volume = snaps_for_each_volume.get(volume_name)
if not snaps_for_volume:
snaps_for_volume = []
snaps_for_each_volume[volume_name] = snaps_for_volume
snaps_for_volume.append(snap)
# Do a running comparison of snapshot dates to desired time
#periods, keeping the oldest snapshot in each
# time period and deleting the rest:
for volume_name in snaps_for_each_volume:
snaps = snaps_for_each_volume[volume_name]
snaps = snaps[:-1] # never delete the newest snapshot
time_period_number = 0
snap_found_for_this_time_period = False
for snap in snaps:
check_this_snap = True
while check_this_snap and time_period_number < target_backup_times.__len__():
snap_date = datetime.strptime(snap.start_time,
'%Y-%m-%dT%H:%M:%S.000Z')
if snap_date < target_backup_times[time_period_number]:
# the snap date is before the cutoff date.
# Figure out if it's the first snap in this
# date range and act accordingly (since both
#date the date ranges and the snapshots
# are sorted chronologically, we know this
#snapshot isn't in an earlier date range):
if snap_found_for_this_time_period == True:
if not snap.tags.get('preserve_snapshot'):
# as long as the snapshot wasn't marked
# with the 'preserve_snapshot' tag, delete it:
try:
self.delete_snapshot(snap.id)
boto.log.info('Trimmed snapshot %s (%s)' % (snap.tags['Name'], snap.start_time))
except EC2ResponseError:
boto.log.error('Attempt to trim snapshot %s (%s) failed. Possible result of a race condition with trimming on another server?' % (snap.tags['Name'], snap.start_time))
# go on and look at the next snapshot,
#leaving the time period alone
else:
# this was the first snapshot found for this
#time period. Leave it alone and look at the
# next snapshot:
snap_found_for_this_time_period = True
check_this_snap = False
else:
# the snap is after the cutoff date. Check it
# against the next cutoff date
time_period_number += 1
snap_found_for_this_time_period = False | [
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Jenyay/outwiker | 50530cf7b3f71480bb075b2829bc0669773b835b | plugins/webpage/webpage/libs/soupsieve/css_match.py | python | _DocumentNav.is_iframe | (self, el) | return ((el.name if self.is_xml_tree(el) else util.lower(el.name)) == 'iframe') and self.is_html_tag(el) | Check if element is an `iframe`. | Check if element is an `iframe`. | [
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onetwo1/pinduoduo | 021ed7772373ef382ef7f96f006cc92b4201035a | pin_duoduo/pin_duoduo/randomproxy.py | python | RandomProxy.process_response | (self, request, response, spider) | [] | def process_response(self, request, response, spider):
if response.status == 200:
return response
# 出错会引发异常而进入 process_exception 逻辑, 更换代理重抓
raise ResponseCodeError | [
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simoncadman/CUPS-Cloud-Print | 5d96eaa5ba1d3ffe40845498917879b0e907f6bd | oauth2client/client.py | python | _update_query_params | (uri, params) | return urllib.parse.urlunparse(new_parts) | Updates a URI with new query parameters.
Args:
uri: string, A valid URI, with potential existing query parameters.
params: dict, A dictionary of query parameters.
Returns:
The same URI but with the new query parameters added. | Updates a URI with new query parameters. | [
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] | def _update_query_params(uri, params):
"""Updates a URI with new query parameters.
Args:
uri: string, A valid URI, with potential existing query parameters.
params: dict, A dictionary of query parameters.
Returns:
The same URI but with the new query parameters added.
"""
parts = urllib.parse.urlparse(uri)
query_params = dict(urllib.parse.parse_qsl(parts.query))
query_params.update(params)
new_parts = parts._replace(query=urllib.parse.urlencode(query_params))
return urllib.parse.urlunparse(new_parts) | [
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tableau/rest-api-samples | 0be12fa52c6e66104633ab26e67fdf73ae411b33 | python/users_by_group.py | python | sign_out | (server, auth_token) | return | Destroys the active session and invalidates authentication token.
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Destroys the active session and invalidates authentication token.
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'auth_token' authentication token that grants user access to API calls
"""
url = server + "/api/{0}/auth/signout".format(VERSION)
server_response = requests.post(url, headers={'x-tableau-auth': auth_token})
_check_status(server_response, 204)
return | [
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GRAAL-Research/poutyne | f46e5fe610d175b96a490db24ef2d22b49cc594b | poutyne/framework/callbacks/mlflow_logger.py | python | MLFlowLogger._on_epoch_end_write | (self, epoch_number: int, logs: Dict) | Log the batch and epoch metric. | Log the batch and epoch metric. | [
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"""
Log the batch and epoch metric.
"""
logs.pop("epoch")
for key, value in logs.items():
self.log_metric(key, value, step=epoch_number) | [
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spack/spack | 675210bd8bd1c5d32ad1cc83d898fb43b569ed74 | var/spack/repos/builtin/packages/flex/package.py | python | Flex.symlink_lex | (self) | Install symlinks for lex compatibility. | Install symlinks for lex compatibility. | [
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"""Install symlinks for lex compatibility."""
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for dir, flex, lex in \
((self.prefix.bin, 'flex', 'lex'),
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if os.path.isdir(dir):
with working_dir(dir):
if (os.path.isfile(flex) and not os.path.lexists(lex)):
symlink(flex, lex) | [
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yzhao062/pyod | 13b0cd5f50d5ea5c5321da88c46232ae6f24dff7 | pyod/models/sos.py | python | SOS._x2d | (self, X) | return D | Computes the dissimilarity matrix of a given dataset.
Parameters
----------
X : array-like, shape (n_samples, n_features)
The query sample or samples to compute the dissimilarity matrix
w.r.t. to the training samples.
Returns
-------
D : array, shape (n_samples, )
Returns the dissimilarity matrix. | Computes the dissimilarity matrix of a given dataset.
Parameters
----------
X : array-like, shape (n_samples, n_features)
The query sample or samples to compute the dissimilarity matrix
w.r.t. to the training samples.
Returns
-------
D : array, shape (n_samples, )
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Parameters
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X : array-like, shape (n_samples, n_features)
The query sample or samples to compute the dissimilarity matrix
w.r.t. to the training samples.
Returns
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D : array, shape (n_samples, )
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(n, d) = X.shape
if self.metric == 'none':
if n != d:
raise ValueError(
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else:
D = X
elif self.metric == 'euclidean':
sumX = np.sum(np.square(X), 1)
# np.abs protects against extremely small negative values
# that may arise due to floating point arithmetic errors
D = np.sqrt(
np.abs(np.add(np.add(-2 * np.dot(X, X.T), sumX).T, sumX)))
else:
try:
from scipy.spatial import distance
except ImportError as e:
raise ImportError(
"Please install scipy if you wish to use a metric "
"other than 'euclidean' or 'none'")
else:
D = distance.squareform(distance.pdist(X, self.metric))
return D | [
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PUNCH-Cyber/stoq | 8bfc78b226ee6500eb78e1bdf361fc83bc5005b7 | stoq/data_classes.py | python | WorkerResponse.__str__ | (self) | return helpers.dumps(self) | [] | def __str__(self) -> str:
return helpers.dumps(self) | [
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] | https://github.com/PUNCH-Cyber/stoq/blob/8bfc78b226ee6500eb78e1bdf361fc83bc5005b7/stoq/data_classes.py#L343-L344 | |||
rwth-i6/returnn | f2d718a197a280b0d5f0fd91a7fcb8658560dddb | returnn/extern/graph_editor/subgraph.py | python | SubGraphView._remove_unused_ops | (self, control_inputs=True) | Remove unused ops in place.
Args:
control_inputs: if True, control inputs are used to detect used ops.
Returns:
A new subgraph view which only contains used operations. | Remove unused ops in place. | [
"Remove",
"unused",
"ops",
"in",
"place",
"."
] | def _remove_unused_ops(self, control_inputs=True):
"""Remove unused ops in place.
Args:
control_inputs: if True, control inputs are used to detect used ops.
Returns:
A new subgraph view which only contains used operations.
"""
ops = select.get_walks_union_ops(
self.connected_inputs,
self.connected_outputs,
within_ops=self._ops,
control_inputs=control_inputs)
self._ops = [op for op in self._ops if op in ops] | [
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cloudera/impyla | 0c736af4cad2bade9b8e313badc08ec50e81c948 | impala/_thrift_gen/hive_metastore/ThriftHiveMetastore.py | python | show_compact_args.__eq__ | (self, other) | return isinstance(other, self.__class__) and self.__dict__ == other.__dict__ | [] | def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__ | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/_internal/django/utils/safestring.py | python | mark_for_escaping | (s) | return EscapeString(str(s)) | Explicitly mark a string as requiring HTML escaping upon output. Has no
effect on SafeData subclasses.
Can be called multiple times on a single string (the resulting escaping is
only applied once). | Explicitly mark a string as requiring HTML escaping upon output. Has no
effect on SafeData subclasses. | [
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] | def mark_for_escaping(s):
"""
Explicitly mark a string as requiring HTML escaping upon output. Has no
effect on SafeData subclasses.
Can be called multiple times on a single string (the resulting escaping is
only applied once).
"""
if isinstance(s, (SafeData, EscapeData)):
return s
if isinstance(s, str) or (isinstance(s, Promise) and s._delegate_str):
return EscapeString(s)
if isinstance(s, (unicode, Promise)):
return EscapeUnicode(s)
return EscapeString(str(s)) | [
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ethereum/trinity | 6383280c5044feb06695ac2f7bc1100b7bcf4fe0 | trinity/protocol/eth/validators.py | python | GetBlockBodiesValidator.__init__ | (self, headers: Sequence[BlockHeaderAPI]) | [] | def __init__(self, headers: Sequence[BlockHeaderAPI]) -> None:
self.headers = headers | [
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1040003585/WebScrapingWithPython | a770fa5b03894076c8c9539b1ffff34424ffc016 | portia_examle/lib/python2.7/site-packages/pip/exceptions.py | python | HashError._requirement_name | (self) | return str(self.req) if self.req else 'unknown package' | Return a description of the requirement that triggered me.
This default implementation returns long description of the req, with
line numbers | Return a description of the requirement that triggered me. | [
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] | def _requirement_name(self):
"""Return a description of the requirement that triggered me.
This default implementation returns long description of the req, with
line numbers
"""
return str(self.req) if self.req else 'unknown package' | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/reports/views.py | python | get_scheduled_report_response | (couch_user, domain, scheduled_report_id,
email=True, attach_excel=False,
send_only_active=False, request=None) | return _render_report_configs(
request,
scheduled_report.configs,
scheduled_report.domain,
scheduled_report.owner_id,
couch_user,
email,
attach_excel=attach_excel,
lang=scheduled_report.language,
send_only_active=send_only_active,
) | This function somewhat confusingly returns a tuple of: (response, excel_files)
If attach_excel is false, excel_files will always be an empty list.
If send_only_active is True, then only ReportConfigs that have a start_date
in the past will be sent. If none of the ReportConfigs are valid, no email will
be sent. | This function somewhat confusingly returns a tuple of: (response, excel_files)
If attach_excel is false, excel_files will always be an empty list.
If send_only_active is True, then only ReportConfigs that have a start_date
in the past will be sent. If none of the ReportConfigs are valid, no email will
be sent. | [
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email=True, attach_excel=False,
send_only_active=False, request=None):
"""
This function somewhat confusingly returns a tuple of: (response, excel_files)
If attach_excel is false, excel_files will always be an empty list.
If send_only_active is True, then only ReportConfigs that have a start_date
in the past will be sent. If none of the ReportConfigs are valid, no email will
be sent.
"""
# todo: clean up this API?
domain_obj = Domain.get_by_name(domain)
if not user_can_view_reports(domain_obj, couch_user):
raise Http404
scheduled_report = ReportNotification.get_report(scheduled_report_id)
if not scheduled_report:
raise Http404
if not (scheduled_report.domain == domain and scheduled_report.can_be_viewed_by(couch_user)):
raise Http404
from django.http import HttpRequest
if not request:
request = HttpRequest()
request.couch_user = couch_user
request.user = couch_user.get_django_user()
request.domain = domain
request.couch_user.current_domain = domain
return _render_report_configs(
request,
scheduled_report.configs,
scheduled_report.domain,
scheduled_report.owner_id,
couch_user,
email,
attach_excel=attach_excel,
lang=scheduled_report.language,
send_only_active=send_only_active,
) | [
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google/diff-match-patch | 62f2e689f498f9c92dbc588c58750addec9b1654 | python2/diff_match_patch.py | python | diff_match_patch.diff_cleanupEfficiency | (self, diffs) | Reduce the number of edits by eliminating operationally trivial
equalities.
Args:
diffs: Array of diff tuples. | Reduce the number of edits by eliminating operationally trivial
equalities. | [
"Reduce",
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"number",
"of",
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"eliminating",
"operationally",
"trivial",
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"."
] | def diff_cleanupEfficiency(self, diffs):
"""Reduce the number of edits by eliminating operationally trivial
equalities.
Args:
diffs: Array of diff tuples.
"""
changes = False
equalities = [] # Stack of indices where equalities are found.
lastEquality = None # Always equal to diffs[equalities[-1]][1]
pointer = 0 # Index of current position.
pre_ins = False # Is there an insertion operation before the last equality.
pre_del = False # Is there a deletion operation before the last equality.
post_ins = False # Is there an insertion operation after the last equality.
post_del = False # Is there a deletion operation after the last equality.
while pointer < len(diffs):
if diffs[pointer][0] == self.DIFF_EQUAL: # Equality found.
if (len(diffs[pointer][1]) < self.Diff_EditCost and
(post_ins or post_del)):
# Candidate found.
equalities.append(pointer)
pre_ins = post_ins
pre_del = post_del
lastEquality = diffs[pointer][1]
else:
# Not a candidate, and can never become one.
equalities = []
lastEquality = None
post_ins = post_del = False
else: # An insertion or deletion.
if diffs[pointer][0] == self.DIFF_DELETE:
post_del = True
else:
post_ins = True
# Five types to be split:
# <ins>A</ins><del>B</del>XY<ins>C</ins><del>D</del>
# <ins>A</ins>X<ins>C</ins><del>D</del>
# <ins>A</ins><del>B</del>X<ins>C</ins>
# <ins>A</del>X<ins>C</ins><del>D</del>
# <ins>A</ins><del>B</del>X<del>C</del>
if lastEquality and ((pre_ins and pre_del and post_ins and post_del) or
((len(lastEquality) < self.Diff_EditCost / 2) and
(pre_ins + pre_del + post_ins + post_del) == 3)):
# Duplicate record.
diffs.insert(equalities[-1], (self.DIFF_DELETE, lastEquality))
# Change second copy to insert.
diffs[equalities[-1] + 1] = (self.DIFF_INSERT,
diffs[equalities[-1] + 1][1])
equalities.pop() # Throw away the equality we just deleted.
lastEquality = None
if pre_ins and pre_del:
# No changes made which could affect previous entry, keep going.
post_ins = post_del = True
equalities = []
else:
if len(equalities):
equalities.pop() # Throw away the previous equality.
if len(equalities):
pointer = equalities[-1]
else:
pointer = -1
post_ins = post_del = False
changes = True
pointer += 1
if changes:
self.diff_cleanupMerge(diffs) | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/zwave_js/light.py | python | ZwaveLight.rgbw_color | (self) | return self._rgbw_color | Return the hs color. | Return the hs color. | [
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] | def rgbw_color(self) -> tuple[int, int, int, int] | None:
"""Return the hs color."""
return self._rgbw_color | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/dynamics/dynamic.py | python | DynamicModel.__init__ | (self, state, action, next_state=None, preprocessors=None, postprocessors=None) | Initialize the dynamic transition probability :math:`p(s_{t+1} | s_t, a_t)`, or dynamic transition function
:math:`s_{t+1} = f(s_t, a_t)`.
Args:
state (State): state inputs.
action (Action): action inputs.
next_state (State, None): state outputs. If None, it will take the state inputs as the outputs.
preprocessors (Processor, list of Processor, None): pre-processors to be applied to the given input
postprocessors (Processor, list of Processor, None): post-processors to be applied to the output | Initialize the dynamic transition probability :math:`p(s_{t+1} | s_t, a_t)`, or dynamic transition function
:math:`s_{t+1} = f(s_t, a_t)`. | [
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"""
Initialize the dynamic transition probability :math:`p(s_{t+1} | s_t, a_t)`, or dynamic transition function
:math:`s_{t+1} = f(s_t, a_t)`.
Args:
state (State): state inputs.
action (Action): action inputs.
next_state (State, None): state outputs. If None, it will take the state inputs as the outputs.
preprocessors (Processor, list of Processor, None): pre-processors to be applied to the given input
postprocessors (Processor, list of Processor, None): post-processors to be applied to the output
"""
# set inputs
self.state = state
self.action = action
# set outputs
self.next_state = next_state
self.state_data = None
# preprocessors and postprocessors
if preprocessors is None:
preprocessors = []
if not isinstance(preprocessors, collections.Iterable):
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self.preprocessors = preprocessors
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postprocessors = []
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SebKuzminsky/pycam | 55e3129f518e470040e79bb00515b4bfcf36c172 | pycam/Utils/iterators.py | python | Iterator.insert | (self, item) | [] | def insert(self, item):
self.seq.insert(self.ind, item)
self.ind += 1 | [
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Chaffelson/nipyapi | d3b186fd701ce308c2812746d98af9120955e810 | nipyapi/registry/models/extension_metadata.py | python | ExtensionMetadata.link_docs | (self) | return self._link_docs | Gets the link_docs of this ExtensionMetadata.
A WebLink to the documentation for this extension.
:return: The link_docs of this ExtensionMetadata.
:rtype: JaxbLink | Gets the link_docs of this ExtensionMetadata.
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] | def link_docs(self):
"""
Gets the link_docs of this ExtensionMetadata.
A WebLink to the documentation for this extension.
:return: The link_docs of this ExtensionMetadata.
:rtype: JaxbLink
"""
return self._link_docs | [
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rm-hull/luma.examples | 3a5110ab27a2d4f10cd62dc0156f439f4decd1e7 | examples/scrolling_pixelart.py | python | scroll_left | (virtual, pos) | return (x, y) | [] | def scroll_left(virtual, pos):
x, y = pos
while x >= 0:
virtual.set_position((x, y))
x -= 1
x = 0
return (x, y) | [
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OmkarPathak/pygorithm | be35813729a0151da1ac9ba013453a61ffa249b8 | pygorithm/fibonacci/goldenratio.py | python | sequence | (n) | return [fib(value) for value in range(n + 1)] | Return sequence of Fibonacci values as list. | Return sequence of Fibonacci values as list. | [
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] | def sequence(n):
"""
Return sequence of Fibonacci values as list.
"""
return [fib(value) for value in range(n + 1)] | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/middleware/csrf.py | python | CsrfViewMiddleware.process_response | (self, request, response) | return response | [] | def process_response(self, request, response):
if not getattr(request, 'csrf_cookie_needs_reset', False):
if getattr(response, 'csrf_cookie_set', False):
return response
if not request.META.get("CSRF_COOKIE_USED", False):
return response
# Set the CSRF cookie even if it's already set, so we renew
# the expiry timer.
self._set_token(request, response)
response.csrf_cookie_set = True
return response | [
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aiidateam/aiida-core | c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2 | aiida/cmdline/commands/cmd_verdi.py | python | VerdiCommandGroup.add_verbosity_option | (cmd) | return cmd | Apply the ``verbosity`` option to the command, which is common to all ``verdi`` commands. | Apply the ``verbosity`` option to the command, which is common to all ``verdi`` commands. | [
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] | def add_verbosity_option(cmd):
"""Apply the ``verbosity`` option to the command, which is common to all ``verdi`` commands."""
# Only apply the option if it hasn't been already added in a previous call.
if cmd is not None and 'verbosity' not in [param.name for param in cmd.params]:
cmd = options.VERBOSITY()(cmd)
return cmd | [
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lazylibrarian/LazyLibrarian | ae3c14e9db9328ce81765e094ab2a14ed7155624 | cherrypy/_cptools.py | python | Tool.__call__ | (self, *args, **kwargs) | return tool_decorator | Compile-time decorator (turn on the tool in config).
For example::
@tools.proxy()
def whats_my_base(self):
return cherrypy.request.base
whats_my_base.exposed = True | Compile-time decorator (turn on the tool in config). | [
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"""Compile-time decorator (turn on the tool in config).
For example::
@tools.proxy()
def whats_my_base(self):
return cherrypy.request.base
whats_my_base.exposed = True
"""
if args:
raise TypeError("The %r Tool does not accept positional "
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% self._name)
def tool_decorator(f):
if not hasattr(f, "_cp_config"):
f._cp_config = {}
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f._cp_config[subspace + "on"] = True
for k, v in kwargs.items():
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/plexapi/mixins.py | python | StyleMixin.removeStyle | (self, styles, locked=True) | Remove a style tag(s).
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styles (list): List of strings.
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styles (list): List of strings.
locked (bool): True (default) to lock the field, False to unlock the field.
"""
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/south/creator/actions.py | python | ChangeField.console_line | (self) | return " ~ Changed field %s on %s.%s" % (
self.new_field.name,
self.model._meta.app_label,
self.model._meta.object_name,
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return " ~ Changed field %s on %s.%s" % (
self.new_field.name,
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wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/agw/foldpanelbar.py | python | FoldPanelItem.Reposition | (self, pos) | return self.GetPanelLength() | Repositions this :class:`FoldPanelItem` and reports the length occupied
for the next :class:`FoldPanelItem` in the list.
:param `pos`: the new item position. | Repositions this :class:`FoldPanelItem` and reports the length occupied
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Repositions this :class:`FoldPanelItem` and reports the length occupied
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:param `pos`: the new item position.
"""
# NOTE: Call Resize before Reposition when an item is added, because the new
# size needed will be calculated by Resize. Of course the relative position
# of the controls have to be correct in respect to the caption bar
self.Freeze()
vertical = self.IsVertical()
xpos = (vertical and [-1] or [pos])[0]
ypos = (vertical and [pos] or [-1])[0]
self.SetSize(xpos, ypos, -1, -1, wx.SIZE_USE_EXISTING)
self._itemPos = pos
self.Thaw()
return self.GetPanelLength() | [
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007gzs/dingtalk-sdk | 7979da2e259fdbc571728cae2425a04dbc65850a | dingtalk/client/api/taobao.py | python | TbMiaoJie.alibaba_mos_store_getitemsrecommended | (
self,
item_id,
screen_no
) | return self._top_request(
"alibaba.mos.store.getitemsrecommended",
{
"item_id": item_id,
"screen_no": screen_no
}
) | 根据商品id获取推荐商品列表
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=35537
:param item_id: 商品id
:param screen_no: 屏编号 | 根据商品id获取推荐商品列表
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=35537 | [
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self,
item_id,
screen_no
):
"""
根据商品id获取推荐商品列表
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=35537
:param item_id: 商品id
:param screen_no: 屏编号
"""
return self._top_request(
"alibaba.mos.store.getitemsrecommended",
{
"item_id": item_id,
"screen_no": screen_no
}
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007gzs/dingtalk-sdk | 7979da2e259fdbc571728cae2425a04dbc65850a | dingtalk/client/api/taobao.py | python | TbDuJiaShangPinGuanLi.taobao_alitrip_travel_item_sku_override | (
self,
skus,
item_id='',
out_product_id=''
) | return self._top_request(
"taobao.alitrip.travel.item.sku.override",
{
"skus": skus,
"item_id": item_id,
"out_product_id": out_product_id
},
result_processor=lambda x: x["travel_item"]
) | 【API3.0】商品级别日历价格库存修改，全量覆盖
旅行度假新商品日历价格库存信息修改接口 第三版。提供商家通过TOP API方式修改商品sku信息。
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=25759
:param skus: 商品日历价格库存套餐
:param item_id: 商品id。itemId和outProductId至少填写一个
:param out_product_id: 商品 外部商家编码。itemId和outProductId至少填写一个 | 【API3.0】商品级别日历价格库存修改，全量覆盖
旅行度假新商品日历价格库存信息修改接口 第三版。提供商家通过TOP API方式修改商品sku信息。
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=25759 | [
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self,
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item_id='',
out_product_id=''
):
"""
【API3.0】商品级别日历价格库存修改，全量覆盖
旅行度假新商品日历价格库存信息修改接口 第三版。提供商家通过TOP API方式修改商品sku信息。
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=25759
:param skus: 商品日历价格库存套餐
:param item_id: 商品id。itemId和outProductId至少填写一个
:param out_product_id: 商品 外部商家编码。itemId和outProductId至少填写一个
"""
return self._top_request(
"taobao.alitrip.travel.item.sku.override",
{
"skus": skus,
"item_id": item_id,
"out_product_id": out_product_id
},
result_processor=lambda x: x["travel_item"]
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whyliam/whyliam.workflows.youdao | 2dfa7f1de56419dab1c2e70c1a27e5e13ba25a5c | workflow/notify.py | python | convert_image | (inpath, outpath, size) | Convert an image file using ``sips``.
Args:
inpath (str): Path of source file.
outpath (str): Path to destination file.
size (int): Width and height of destination image in pixels.
Raises:
RuntimeError: Raised if ``sips`` exits with non-zero status. | Convert an image file using ``sips``. | [
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"""Convert an image file using ``sips``.
Args:
inpath (str): Path of source file.
outpath (str): Path to destination file.
size (int): Width and height of destination image in pixels.
Raises:
RuntimeError: Raised if ``sips`` exits with non-zero status.
"""
cmd = [
b'sips',
b'-z', str(size), str(size),
inpath,
b'--out', outpath]
# log().debug(cmd)
with open(os.devnull, 'w') as pipe:
retcode = subprocess.call(cmd, stdout=pipe, stderr=subprocess.STDOUT)
if retcode != 0:
raise RuntimeError('sips exited with %d' % retcode) | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/form_processor/reprocess.py | python | _perfom_post_save_actions | (form, save=True) | [] | def _perfom_post_save_actions(form, save=True):
interface = FormProcessorInterface(form.domain)
cache = interface.casedb_cache(
domain=form.domain, lock=False, deleted_ok=True, xforms=[form],
load_src="reprocess_form_post_save",
)
with cache as casedb:
case_stock_result = SubmissionPost.process_xforms_for_cases([form], casedb)
case_models = case_stock_result.case_models
forms = ProcessedForms(form, None)
stock_result = case_stock_result.stock_result
try:
FormProcessorSQL.publish_changes_to_kafka(forms, case_models, stock_result)
except Exception:
error_message = "Error publishing to kafka"
return ReprocessingResult(form, None, None, error_message)
try:
save and SubmissionPost.do_post_save_actions(casedb, [form], case_stock_result)
except PostSaveError:
error_message = "Error performing post save operations"
return ReprocessingResult(form, None, None, error_message)
return ReprocessingResult(form, case_models, None, None) | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/taskrouter/v1/workspace/workflow/workflow_cumulative_statistics.py | python | WorkflowCumulativeStatisticsInstance._proxy | (self) | return self._context | Generate an instance context for the instance, the context is capable of
performing various actions. All instance actions are proxied to the context
:returns: WorkflowCumulativeStatisticsContext for this WorkflowCumulativeStatisticsInstance
:rtype: twilio.rest.taskrouter.v1.workspace.workflow.workflow_cumulative_statistics.WorkflowCumulativeStatisticsContext | Generate an instance context for the instance, the context is capable of
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"""
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performing various actions. All instance actions are proxied to the context
:returns: WorkflowCumulativeStatisticsContext for this WorkflowCumulativeStatisticsInstance
:rtype: twilio.rest.taskrouter.v1.workspace.workflow.workflow_cumulative_statistics.WorkflowCumulativeStatisticsContext
"""
if self._context is None:
self._context = WorkflowCumulativeStatisticsContext(
self._version,
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workflow_sid=self._solution['workflow_sid'],
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return self._context | [
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HHammond/PrettyPandas | 639c5c48b657c02570a7f423e8a3c4a1572f969b | prettypandas/summarizer.py | python | PrettyPandas.summary | (self,
func=methodcaller('sum'),
title='Total',
axis=0,
subset=None,
*args,
**kwargs) | Add multiple summary rows or columns to the dataframe.
Parameters
----------
:param func: function to be used for a summary.
:param titles: Title for this summary column.
:param axis:
Same as numpy and pandas axis argument. A value of None will cause
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:param args: Positional arguments passed to all the functions.
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title='Total',
axis=0,
subset=None,
*args,
**kwargs):
"""Add multiple summary rows or columns to the dataframe.
Parameters
----------
:param func: function to be used for a summary.
:param titles: Title for this summary column.
:param axis:
Same as numpy and pandas axis argument. A value of None will cause
the summary to be applied to both rows and columns.
:param args: Positional arguments passed to all the functions.
:param kwargs: Keyword arguments passed to all the functions.
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"""
if axis is None:
return (
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func=func,
title=title,
axis=0,
subset=subset,
*args,
**kwargs
)
.summary(
func=func,
title=title,
axis=1,
subset=subset,
*args,
**kwargs
)
)
else:
agg = Aggregate(title, func, subset=subset,
axis=axis, *args, **kwargs)
return self._add_summary(agg) | [
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Vespa314/bilibili-api | 42b6b90aa7c141f5cfb0fdc754435518106f6966 | bilibili-video/GetAssDanmaku.py | python | ProcessComments | (comments, f, width, height, bottomReserved, fontface, fontsize, alpha, lifetime, reduced, progress_callback) | [] | def ProcessComments(comments, f, width, height, bottomReserved, fontface, fontsize, alpha, lifetime, reduced, progress_callback):
styleid = 'Danmaku2ASS_%04x' % random.randint(0, 0xffff)
WriteASSHead(f, width, height, fontface, fontsize, alpha, styleid)
rows = [[None]*(height-bottomReserved+1) for i in range(4)]
for idx, i in enumerate(comments):
if progress_callback and idx % 1000 == 0:
progress_callback(idx, len(comments))
if isinstance(i[4], int):
row = 0
rowmax = height-bottomReserved-i[7]
while row <= rowmax:
freerows = TestFreeRows(rows, i, row, width, height, bottomReserved, lifetime)
if freerows >= i[7]:
MarkCommentRow(rows, i, row)
WriteComment(f, i, row, width, height, bottomReserved, fontsize, lifetime, styleid)
break
else:
row += freerows or 1
else:
if not reduced:
row = FindAlternativeRow(rows, i, height, bottomReserved)
MarkCommentRow(rows, i, row)
WriteComment(f, i, row, width, height, bottomReserved, fontsize, lifetime, styleid)
elif i[4] == 'bilipos':
WriteCommentBilibiliPositioned(f, i, width, height, styleid)
elif i[4] == 'acfunpos':
WriteCommentAcfunPositioned(f, i, width, height, styleid)
elif i[4] == 'sH5Vpos':
WriteCommentSH5VPositioned(f, i, width, height, styleid)
else:
logging.warning(_('Invalid comment: %r') % i[3])
if progress_callback:
progress_callback(len(comments), len(comments)) | [
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HLTCHKUST/Mem2Seq | 4224ccf9e14956115cfdc98814d340d9bd7b953e | utils/utils_babi.py | python | Dataset.preprocess_inde | (self, sequence,src_seq) | return sequence | Converts words to ids. | Converts words to ids. | [
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sequence = sequence + [len(src_seq)-1]
sequence = torch.Tensor(sequence)
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firebase/firebase-admin-python | 7cfb798ca78f706d08a46c3c48028895787d0ea4 | firebase_admin/_messaging_encoder.py | python | MessageEncoder.encode_apns | (cls, apns) | return cls.remove_null_values(result) | Encodes an ``APNSConfig`` instance into JSON. | Encodes an ``APNSConfig`` instance into JSON. | [
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raise ValueError('Message.apns must be an instance of APNSConfig class.')
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tensorflow/data-validation | 6c68c219c5d78d3736fd011d8a7c53fbcb94379c | tensorflow_data_validation/utils/mutual_information_util.py | python | adjusted_mutual_information | (
feature_list0: List[np.ndarray],
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seed: Optional[int] = None,
) | return _adjusted_mi_for_arrays(cf_list0, cf_list1, df_list0, df_list1,
weights, k, estimate_method, seed) | Computes adjusted MI between two lists of features.
Args:
feature_list0: (list(np.ndarray)) a list of features represented as numpy
arrays.
feature_list1: (list(np.ndarray)) a list of features represented as numpy
arrays.
is_categorical_list0: (list(bool)) Whether the first list of features are
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is_categorical_list1: (list(bool)) Whether the second list of features are
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k: (int) The number of nearest neighbors. It has to be an integer no less
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estimate_method: (str) 'smaller_data' or 'larger_data' estimator in the
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weight_feature: (np.ndarray) numpy array that are weights for each example.
filter_feature: (np.ndarray) numpy array that is used as the filter to drop
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filtering is done.
seed: (int) the numpy random seed.
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is_categorical_list0: List[bool],
is_categorical_list1: List[bool],
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estimate_method: str = 'larger_data',
weight_feature: Optional[np.ndarray] = None,
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seed: Optional[int] = None,
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Args:
feature_list0: (list(np.ndarray)) a list of features represented as numpy
arrays.
feature_list1: (list(np.ndarray)) a list of features represented as numpy
arrays.
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is_categorical_list1: (list(bool)) Whether the second list of features are
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filter_feature: (np.ndarray) numpy array that is used as the filter to drop
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filtering is done.
seed: (int) the numpy random seed.
Returns:
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feature_list1.
"""
_validate_args(feature_list0, feature_list1, is_categorical_list0,
is_categorical_list1, k, estimate_method, weight_feature,
filter_feature, False, seed)
cf_list0, cf_list1, df_list0, df_list1, weights = _feature_list_to_numpy_arrays(
feature_list0, feature_list1, is_categorical_list0, is_categorical_list1,
weight_feature, filter_feature)
return _adjusted_mi_for_arrays(cf_list0, cf_list1, df_list0, df_list1,
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PytLab/simpleflow | 72b06c7bca7088352074d6cbdf29578c9c06b657 | simpleflow/operations.py | python | Add.__init__ | (self, x, y, name=None) | Addition constructor.
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_horizontal_pod_autoscaler_status.py | python | V1HorizontalPodAutoscalerStatus.observed_generation | (self) | return self._observed_generation | Gets the observed_generation of this V1HorizontalPodAutoscalerStatus. # noqa: E501
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seemoo-lab/internalblue | ba6ba0b99f835964395d6dd1b1eb7dd850398fd6 | internalblue/core.py | python | InternalBlue.connectToRemoteDevice | (self, bt_addr) | Send a HCI Connect Command to the firmware. This will setup
a connection (inserted into the connection structure) if the
remote device (specified by bt_addr) accepts.
To be exact: This will most likely send
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ahkab/ahkab | 1e8939194b689909b8184ce7eba478b485ff9e3a | ahkab/ekv.py | python | ekv_mos_model.setup_scaling | (self, nq, device) | return | Calculates and stores in self.scaling the following factors:
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007gzs/dingtalk-sdk | 7979da2e259fdbc571728cae2425a04dbc65850a | dingtalk/client/api/taobao.py | python | TbJiuDianShangPin.taobao_xhotel_rooms_update | (
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result_processor=lambda x: x["gids"]
) | 房型共享库存推送接口（批量全量）
此接口用于更新多个集市酒店商品房态信息，根据传入的gids更新商品信息，该商品必须为对应的发布者才能执行更新操作。如果对应的商品在淘宝集市酒店系统中不存在，则会返回错误提示。是全量更新，非增量，会把之前的房态进行覆盖。
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文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=22670
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scrapinghub/frontera | 84f9e1034d2868447db88e865596c0fbb32e70f6 | frontera/worker/components/__init__.py | python | DBWorkerBaseComponent.schedule | (self, delay=0) | Schedule component start with optional delay.
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kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python3-alpha/python-libs/gdata/apps/organization/client.py | python | OrganizationUnitProvisioningClient.retrieve_all_org_units | (self, customer_id, **kwargs) | return self.RetrieveAllOrgUnitsFromUri(uri) | Retrieve all OrgUnits in the customer's domain.
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customer_id: string The ID of the Google Apps customer.
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customer_id: string The ID of the Google Apps customer.
Returns:
gdata.apps.organisation.data.OrgUnitFeed object
"""
uri = self.MakeOrganizationUnitOrgunitProvisioningUri(
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | lms/djangoapps/grades/services.py | python | GradesService.undo_override_subsection_grade | (self, user_id, course_key_or_id, usage_key_or_id,
feature=api.constants.GradeOverrideFeatureEnum.proctoring) | return api.undo_override_subsection_grade(user_id, course_key_or_id, usage_key_or_id, feature=feature) | Delete the override subsection grade row (the PersistentSubsectionGrade model must already exist)
Fires off a recalculate_subsection_grade async task to update the PersistentSubsectionGrade table. If the
override does not exist, no error is raised, it just triggers the recalculation. | Delete the override subsection grade row (the PersistentSubsectionGrade model must already exist) | [
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] | def undo_override_subsection_grade(self, user_id, course_key_or_id, usage_key_or_id,
feature=api.constants.GradeOverrideFeatureEnum.proctoring):
"""
Delete the override subsection grade row (the PersistentSubsectionGrade model must already exist)
Fires off a recalculate_subsection_grade async task to update the PersistentSubsectionGrade table. If the
override does not exist, no error is raised, it just triggers the recalculation.
"""
return api.undo_override_subsection_grade(user_id, course_key_or_id, usage_key_or_id, feature=feature) | [
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aianaconda/TensorFlow_Engineering_Implementation | cb787e359da9ac5a08d00cd2458fecb4cb5a3a31 | code/7-9 mnistkmeans.py | python | inference | (inp, num_clusters, hidden1_units, hidden2_units) | return logits, clustering_loss, kmeans_init, kmeans_training_op | Build the MNIST model up to where it may be used for inference.
Args:
inp: input data
num_clusters: number of clusters of input features to train.
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
logits: Output tensor with the computed logits.
clustering_loss: Clustering loss.
kmeans_training_op: An op to train the clustering. | Build the MNIST model up to where it may be used for inference.
Args:
inp: input data
num_clusters: number of clusters of input features to train.
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
logits: Output tensor with the computed logits.
clustering_loss: Clustering loss.
kmeans_training_op: An op to train the clustering. | [
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"""Build the MNIST model up to where it may be used for inference.
Args:
inp: input data
num_clusters: number of clusters of input features to train.
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
logits: Output tensor with the computed logits.
clustering_loss: Clustering loss.
kmeans_training_op: An op to train the clustering.
"""
# Clustering
kmeans = tf.contrib.factorization.KMeans(
inp,
num_clusters,
distance_metric=tf.contrib.factorization.COSINE_DISTANCE,
# TODO(agarwal): kmeans++ is currently causing crash in dbg mode.
# Enable this after fixing.
# initial_clusters=tf.contrib.factorization.KMEANS_PLUS_PLUS_INIT,
use_mini_batch=True)
(all_scores, _, clustering_scores, _, kmeans_init,
kmeans_training_op) = kmeans.training_graph()
# Some heuristics to approximately whiten this output.
all_scores = (all_scores[0] - 0.5) * 5
# Here we avoid passing the gradients from the supervised objective back to
# the clusters by creating a stop_gradient node.
all_scores = tf.stop_gradient(all_scores)
clustering_loss = tf.reduce_sum(clustering_scores[0])
# Hidden 1
with tf.name_scope('hidden1'):
weights = tf.Variable(
tf.truncated_normal([num_clusters, hidden1_units],
stddev=1.0 / math.sqrt(float(IMAGE_PIXELS))),
name='weights')
biases = tf.Variable(tf.zeros([hidden1_units]),
name='biases')
hidden1 = tf.nn.relu(tf.matmul(all_scores, weights) + biases)
# Hidden 2
with tf.name_scope('hidden2'):
weights = tf.Variable(
tf.truncated_normal([hidden1_units, hidden2_units],
stddev=1.0 / math.sqrt(float(hidden1_units))),
name='weights')
biases = tf.Variable(tf.zeros([hidden2_units]),
name='biases')
hidden2 = tf.nn.relu(tf.matmul(hidden1, weights) + biases)
# Linear
with tf.name_scope('softmax_linear'):
weights = tf.Variable(
tf.truncated_normal([hidden2_units, NUM_CLASSES],
stddev=1.0 / math.sqrt(float(hidden2_units))),
name='weights')
biases = tf.Variable(tf.zeros([NUM_CLASSES]),
name='biases')
logits = tf.matmul(hidden2, weights) + biases
return logits, clustering_loss, kmeans_init, kmeans_training_op | [
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tensorflow/lattice | 784eca50cbdfedf39f183cc7d298c9fe376b69c0 | tensorflow_lattice/python/premade_lib.py | python | _verify_feature_config | (feature_config) | Verifies that feature_config is properly specified.
Args:
feature_config: Feature configuration object describing an input feature to
a model. Should be an instance of `tfl.configs.FeatureConfig`.
Raises:
ValueError: If `feature_config.pwl_calibration_input_keypoints` is not
iterable or contains non-{int/float} values for a numerical feature.
ValueError: If `feature_config.monotonicity` is not an iterable for a
categorical feature.
ValueError: If any element in `feature_config.monotonicity` is not an
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ValueError: If any value in any element in `feature_config.monotonicity` is
not an int for a categorical feature.
ValueError: If any value in any element in `feature_config.monotonicity` is
not in the range `[0, feature_config.num_buckets]` for a categorical
feature. | Verifies that feature_config is properly specified. | [
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] | def _verify_feature_config(feature_config):
"""Verifies that feature_config is properly specified.
Args:
feature_config: Feature configuration object describing an input feature to
a model. Should be an instance of `tfl.configs.FeatureConfig`.
Raises:
ValueError: If `feature_config.pwl_calibration_input_keypoints` is not
iterable or contains non-{int/float} values for a numerical feature.
ValueError: If `feature_config.monotonicity` is not an iterable for a
categorical feature.
ValueError: If any element in `feature_config.monotonicity` is not an
iterable for a categorical feature.
ValueError: If any value in any element in `feature_config.monotonicity` is
not an int for a categorical feature.
ValueError: If any value in any element in `feature_config.monotonicity` is
not in the range `[0, feature_config.num_buckets]` for a categorical
feature.
"""
if not feature_config.num_buckets:
# Validate PWL Calibration configuration.
if (not np.iterable(feature_config.pwl_calibration_input_keypoints) or
any(not isinstance(x, (int, float))
for x in feature_config.pwl_calibration_input_keypoints)):
raise ValueError('Input keypoints are invalid for feature {}: {}'.format(
feature_config.name, feature_config.pwl_calibration_input_keypoints))
elif feature_config.monotonicity and feature_config.monotonicity != 'none':
# Validate Categorical Calibration configuration.
if not np.iterable(feature_config.monotonicity):
raise ValueError('Monotonicity is not a list for feature {}: {}'.format(
feature_config.name, feature_config.monotonicity))
for i, t in enumerate(feature_config.monotonicity):
if not np.iterable(t):
raise ValueError(
'Element {} is not a list/tuple for feature {} monotonicty: {}'
.format(i, feature_config.name, t))
for j, val in enumerate(t):
if not isinstance(val, int):
raise ValueError(
'Element {} for list/tuple {} for feature {} monotonicity is '
'not an index: {}'.format(j, i, feature_config.name, val))
if val < 0 or val >= feature_config.num_buckets:
raise ValueError(
'Element {} for list/tuple {} for feature {} monotonicity is '
'an invalid index not in range [0, num_buckets - 1]: {}'.format(
j, i, feature_config.name, val)) | [
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thu-coai/ConvLab-2 | ad32b76022fa29cbc2f24cbefbb855b60492985e | convlab2/evaluator/multiwoz_eval.py | python | MultiWozEvaluator.domain_success | (self, domain, ref2goal=True) | judge if the domain (subtask) is successfully completed | judge if the domain (subtask) is successfully completed | [
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"""
judge if the domain (subtask) is successfully completed
"""
if domain not in self.goal:
return None
if ref2goal:
goal = {}
goal[domain] = self._expand(self.goal)[domain]
else:
goal = {}
goal[domain] = {'info': {}, 'book': {}, 'reqt': []}
if 'book' in self.goal[domain]:
goal[domain]['book'] = self.goal[domain]['book']
for da in self.usr_da_array:
d, i, s, v = da.split('-', 3)
if d != domain:
continue
if i in ['inform', 'recommend', 'offerbook', 'offerbooked'] and s in mapping[d]:
goal[d]['info'][mapping[d][s]] = v
elif i == 'request':
goal[d]['reqt'].append(s)
book_rate = self._book_rate_goal(goal, self.booked, [domain])
book_rate = np.mean(book_rate) if book_rate else None
inform = self._inform_F1_goal(goal, self.sys_da_array, [domain])
try:
inform_rec = inform[0] / (inform[0] + inform[2])
except ZeroDivisionError:
inform_rec = None
if (book_rate == 1 and inform_rec == 1) \
or (book_rate == 1 and inform_rec is None) \
or (book_rate is None and inform_rec == 1):
return 1
else:
return 0 | [
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algorithmiaio/algorithmia-python | 7fd688d75baafe071beb964e250450fd738ca17c | Algorithmia/data.py | python | DataObject.get_type | (self) | return self.data_object_type | Returns type of this DataObject | Returns type of this DataObject | [
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] | def get_type(self):
'''Returns type of this DataObject'''
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | common/lib/xmodule/xmodule/modulestore/mongo/base.py | python | CachingDescriptorSystem.get_subtree_edited_on | (self, xblock) | return xblock._edit_info.get('subtree_edited_on') | See :class: cms.lib.xblock.runtime.EditInfoRuntimeMixin | See :class: cms.lib.xblock.runtime.EditInfoRuntimeMixin | [
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"""
See :class: cms.lib.xblock.runtime.EditInfoRuntimeMixin
"""
return xblock._edit_info.get('subtree_edited_on') | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/plugins/lib/libtreebase.py | python | Page.is_blank | (self) | return self.boxes == [] and self.lines == [] | Am I a blank page? Notes and Titles are boxes too | Am I a blank page? Notes and Titles are boxes too | [
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""" Am I a blank page? Notes and Titles are boxes too """
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henkelis/sonospy | 841f52010fd6e1e932d8f1a8896ad4e5a0667b8a | web2py/gluon/sneaky3.py | python | Sneaky.set_listen_queue_size | (self) | tries a listen argument that works | tries a listen argument that works | [
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] | def set_listen_queue_size(self):
"""tries a listen argument that works"""
if self.request_queue_size:
self.socket.listen(self.request_queue_size)
else:
for request_queue_size in [1024,128,5,1]:
try:
self.socket.listen(request_queue_size)
break
except:
pass | [
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pynag/pynag | e72cf7ce2395263e2b3080cae0ece2b03dbbfa27 | pynag/Utils/metrics.py | python | PerfDataMetric.__repr__ | (self) | return "'%s'=%s%s;%s;%s;%s;%s" % (
self.label,
self.value,
self.uom,
self.warn,
self.crit,
self.min,
self.max,
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return "'%s'=%s%s;%s;%s;%s;%s" % (
self.label,
self.value,
self.uom,
self.warn,
self.crit,
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burke-software/schooldriver | a07262ba864aee0182548ecceb661e49c925725f | appy/fields/pod.py | python | Pod.getTemplateName | (self, obj, fileName) | return res | Gets the name of a template given its p_fileName. | Gets the name of a template given its p_fileName. | [
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] | def getTemplateName(self, obj, fileName):
'''Gets the name of a template given its p_fileName.'''
res = None
if self.templateName:
# Use the method specified in self.templateName.
res = self.templateName(obj, fileName)
# Else, deduce a nice name from p_fileName.
if not res:
name = os.path.splitext(os.path.basename(fileName))[0]
res = gutils.produceNiceMessage(name)
return res | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/mailcap.py | python | listmailcapfiles | () | return mailcaps | Return a list of all mailcap files found on the system. | Return a list of all mailcap files found on the system. | [
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"""Return a list of all mailcap files found on the system."""
# This is mostly a Unix thing, but we use the OS path separator anyway
if 'MAILCAPS' in os.environ:
pathstr = os.environ['MAILCAPS']
mailcaps = pathstr.split(os.pathsep)
else:
if 'HOME' in os.environ:
home = os.environ['HOME']
else:
# Don't bother with getpwuid()
home = '.' # Last resort
mailcaps = [home + '/.mailcap', '/etc/mailcap',
'/usr/etc/mailcap', '/usr/local/etc/mailcap']
return mailcaps | [
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abunsen/Paython | 22f7467e1307b8c005609526af6ec4c252a1bae3 | paython/lib/utils.py | python | is_valid_email | (email) | return re.search(pat, email, re.IGNORECASE) | Based on "The Perfect E-Mail Regex" : http://fightingforalostcause.net/misc/2006/compare-email-regex.php | Based on "The Perfect E-Mail Regex" : http://fightingforalostcause.net/misc/2006/compare-email-regex.php | [
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] | def is_valid_email(email):
"""
Based on "The Perfect E-Mail Regex" : http://fightingforalostcause.net/misc/2006/compare-email-regex.php
"""
pat = '^([\w\!\#$\%\&\'\*\+\-\/\=\?\^\`{\|\}\~]+\.)*[\w\!\#$\%\&\'\*\+\-\/\=\?\^\`{\|\}\~]+@((((([a-z0-9]{1}[a-z0-9\-]{0,62}[a-z0-9]{1})|[a-z])\.)+[a-z]{2,6})|(\d{1,3}\.){3}\d{1,3}(\:\d{1,5})?)$'
return re.search(pat, email, re.IGNORECASE) | [
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nltk/nltk | 3f74ac55681667d7ef78b664557487145f51eb02 | nltk/corpus/reader/framenet.py | python | FramenetCorpusReader.semtype | (self, key) | return st | >>> from nltk.corpus import framenet as fn
>>> fn.semtype(233).name
'Temperature'
>>> fn.semtype(233).abbrev
'Temp'
>>> fn.semtype('Temperature').ID
233
:param key: The name, abbreviation, or id number of the semantic type
:type key: string or int
:return: Information about a semantic type
:rtype: dict | >>> from nltk.corpus import framenet as fn
>>> fn.semtype(233).name
'Temperature'
>>> fn.semtype(233).abbrev
'Temp'
>>> fn.semtype('Temperature').ID
233 | [
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>>> from nltk.corpus import framenet as fn
>>> fn.semtype(233).name
'Temperature'
>>> fn.semtype(233).abbrev
'Temp'
>>> fn.semtype('Temperature').ID
233
:param key: The name, abbreviation, or id number of the semantic type
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:return: Information about a semantic type
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"""
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ni/nidaqmx-python | 62fc6b48cbbb330fe1bcc9aedadc86610a1269b6 | nidaqmx/_task_modules/channels/ci_channel.py | python | CIChannel.ci_two_edge_sep_second_dig_fltr_min_pulse_width | (self) | return val.value | float: Specifies in seconds the minimum pulse width the filter
recognizes. | float: Specifies in seconds the minimum pulse width the filter
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"""
float: Specifies in seconds the minimum pulse width the filter
recognizes.
"""
val = ctypes.c_double()
cfunc = (lib_importer.windll.
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if cfunc.argtypes is None:
with cfunc.arglock:
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cfunc.argtypes = [
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ctypes.POINTER(ctypes.c_double)]
error_code = cfunc(
self._handle, self._name, ctypes.byref(val))
check_for_error(error_code)
return val.value | [
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reahl/reahl | 86aac47c3a9b5b98e9f77dad4939034a02d54d46 | reahl-webdev/reahl/webdev/webserver.py | python | ReahlWebServer.in_background | (self, wait_till_done_serving=True) | Returns a context manager. Within the context of this context manager, the webserver is temporarily run
in a separate thread. After the context managed by this context manager is exited, the server reverts to
handling requests in the current (test) thread.
:keyword wait_till_done_serving: If True, wait for the server to finish its background job before exiting the context block. | Returns a context manager. Within the context of this context manager, the webserver is temporarily run
in a separate thread. After the context managed by this context manager is exited, the server reverts to
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in a separate thread. After the context managed by this context manager is exited, the server reverts to
handling requests in the current (test) thread.
:keyword wait_till_done_serving: If True, wait for the server to finish its background job before exiting the context block.
"""
self.restore_handlers()
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try:
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finally:
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/html5lib/_tokenizer.py | python | HTMLTokenizer.beforeAttributeValueState | (self) | return True | [] | def beforeAttributeValueState(self):
data = self.stream.char()
if data in spaceCharacters:
self.stream.charsUntil(spaceCharacters, True)
elif data == "\"":
self.state = self.attributeValueDoubleQuotedState
elif data == "&":
self.state = self.attributeValueUnQuotedState
self.stream.unget(data)
elif data == "'":
self.state = self.attributeValueSingleQuotedState
elif data == ">":
self.tokenQueue.append({"type": tokenTypes["ParseError"], "data":
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self.emitCurrentToken()
elif data == "\u0000":
self.tokenQueue.append({"type": tokenTypes["ParseError"],
"data": "invalid-codepoint"})
self.currentToken["data"][-1][1] += "\uFFFD"
self.state = self.attributeValueUnQuotedState
elif data in ("=", "<", "`"):
self.tokenQueue.append({"type": tokenTypes["ParseError"], "data":
"equals-in-unquoted-attribute-value"})
self.currentToken["data"][-1][1] += data
self.state = self.attributeValueUnQuotedState
elif data is EOF:
self.tokenQueue.append({"type": tokenTypes["ParseError"], "data":
"expected-attribute-value-but-got-eof"})
self.state = self.dataState
else:
self.currentToken["data"][-1][1] += data
self.state = self.attributeValueUnQuotedState
return True | [
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google/transitfeed | d727e97cb66ac2ca2d699a382ea1d449ee26c2a1 | transitfeed/schedule.py | python | Schedule.GetServicePeriod | (self, service_id) | return self.service_periods[service_id] | Returns the ServicePeriod object with the given ID. | Returns the ServicePeriod object with the given ID. | [
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DingGuodong/LinuxBashShellScriptForOps | d5727b985f920292a10698a3c9751d5dff5fc1a3 | projects/LinuxSystemOps/AutoDevOps/Ansible/pyAnsibleGatheringFacts.py | python | get_bin_path | (arg, required=False, opt_dirs=None) | return bin_path | find system executable in PATH.
Optional arguments:
- required: if executable is not found and required is true
- opt_dirs: optional list of directories to search in addition to PATH
if found return full path; otherwise return None | find system executable in PATH.
Optional arguments:
- required: if executable is not found and required is true
- opt_dirs: optional list of directories to search in addition to PATH
if found return full path; otherwise return None | [
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"""
find system executable in PATH.
Optional arguments:
- required: if executable is not found and required is true
- opt_dirs: optional list of directories to search in addition to PATH
if found return full path; otherwise return None
"""
sbin_paths = ['/sbin', '/usr/sbin', '/usr/local/sbin']
paths = []
# https://stackoverflow.com/questions/9039191/mutable-default-method-arguments-in-python
# https://stackoverflow.com/questions/1132941/least-astonishment-and-the-mutable-default-argument
if not opt_dirs:
opt_dirs = []
for d in opt_dirs:
if d is not None and os.path.exists(d):
paths.append(d)
paths += os.environ.get('PATH', '').split(os.pathsep)
bin_path = None
# mangle PATH to include /sbin dirs
for p in sbin_paths:
if p not in paths and os.path.exists(p):
paths.append(p)
for d in paths:
if not d:
continue
path = os.path.join(d, arg)
if os.path.exists(path) and not os.path.isdir(path) and is_executable(path):
bin_path = path
break
if required and bin_path is None:
print 'Failed to find required executable %s in paths: %s' % (arg, os.pathsep.join(paths))
return bin_path | [
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HaloOrangeWang/NoiseMaker | c4adb1e4e5055b0c26f80060a9fe9920fa93e03b | MakerSrc/validations/melody.py | python | ShiftConfidenceCheck.train_1song | (self, **kwargs) | 获取主旋律连续两小节（不跨越乐段）的音高变化得分 分数为（音高变化/时间差）的平方和
kwargs['section_data']: 这首歌的乐段数据
kwargs['raw_melody_data']: 一首歌的主旋律数据 | 获取主旋律连续两小节（不跨越乐段）的音高变化得分 分数为（音高变化/时间差）的平方和
kwargs['section_data']: 这首歌的乐段数据
kwargs['raw_melody_data']: 一首歌的主旋律数据 | [
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"""
获取主旋律连续两小节（不跨越乐段）的音高变化得分 分数为（音高变化/时间差）的平方和
kwargs['section_data']: 这首歌的乐段数据
kwargs['raw_melody_data']: 一首歌的主旋律数据
"""
raw_melody_data = kwargs['raw_melody_data']
sec_data = kwargs['section_data']
section_data = copy.deepcopy(sec_data)
score_ary = []
if section_data: # 训练集中的部分歌没有乐段
section_data.sort() # 按照小节先后顺序排序
for bar_it in range(0, len(raw_melody_data) // 32 - 1):
shift_score = 0
sec_dx = -1 # 记录这一拍属于这首歌的第几个乐段
if section_data: # 有乐段的情况下 当这个小节和下一小节均不为空且不跨越乐段时进行收录
for sec_it in range(len(section_data)):
if section_data[sec_it][0] * 4 + section_data[sec_it][1] > bar_it * 4: # 将区段的起始拍和当前拍进行比较 如果起始拍在当前拍之前则说明是属于这个区段
sec_dx = sec_it - 1
break
if sec_dx == -1:
sec_dx = len(section_data) - 1 # 属于这首歌的最后一个区段
if section_data[sec_dx][2] == DEF_SEC_EMPTY: # 这个乐段是间奏 不进行分数选择
continue
if sec_dx != len(section_data) - 1:
if section_data[sec_dx + 1][0] * 4 + section_data[sec_dx + 1][1] < (bar_it + 2) * 4:
continue # 出现跨越乐段的情况，不收录
else:
if raw_melody_data[bar_it * 32: (bar_it + 1) * 32] == [0] * 32 or raw_melody_data[(bar_it + 1) * 32: (bar_it + 2) * 32] == [0] * 32:
continue # 没有乐段的情况下 这一小节和下一小节均不能为空
last_note = -1 # 上一个音符的音高
last_note_step = -1 # 上一个音符所在的位置
note_count = 0 # 两小节一共多少音符
# for cal_bar_it in range(bar_it, bar_it + 2):
for step_it in range(64):
if raw_melody_data[bar_it * 32 + step_it] != 0: # 计算变化分
if last_note > 0:
step_diff = step_it - last_note_step
shift_score += (raw_melody_data[bar_it * 32 + step_it] - last_note) * (raw_melody_data[bar_it * 32 + step_it] - last_note) / (step_diff * step_diff)
last_note = raw_melody_data[bar_it * 32 + step_it]
last_note_step = step_it
note_count += 1
if note_count == 1: # 只有一个音符的情况下，音高差异分为0分
score_ary.append(0)
elif note_count > 1:
score_ary.append(shift_score / (note_count - 1))
self.evaluating_score_list.extend(score_ary) | [
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ronf/asyncssh | ee1714c598d8c2ea6f5484e465443f38b68714aa | asyncssh/stream.py | python | SSHStreamSession.readuntil | (self, separator: object, datatype: DataType) | Read data from the channel until a separator is seen | Read data from the channel until a separator is seen | [
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if not separator:
raise ValueError('Separator cannot be empty')
buf = cast(AnyStr, '' if self._encoding else b'')
recv_buf = self._recv_buf[datatype]
if separator is _NEWLINE:
seplen = 1
separators = cast(AnyStr, '\n' if self._encoding else b'\n')
elif isinstance(separator, (bytes, str)):
seplen = len(separator)
separators = cast(AnyStr, separator)
else:
bar = cast(AnyStr, '|' if self._encoding else b'|')
seplist = list(cast(Iterable[AnyStr], separator))
seplen = max(len(sep) for sep in seplist)
separators = bar.join(re.escape(sep) for sep in seplist)
pat = re.compile(separators)
curbuf = 0
buflen = 0
async with self._read_locks[datatype]:
while True:
while curbuf < len(recv_buf):
if isinstance(recv_buf[curbuf], Exception):
if buf:
recv_buf[:curbuf] = []
self._recv_buf_len -= buflen
raise asyncio.IncompleteReadError(
cast(bytes, buf), None)
else:
exc = recv_buf.pop(0)
if isinstance(exc, SoftEOFReceived):
return buf
else:
raise cast(Exception, exc)
newbuf = cast(AnyStr, recv_buf[curbuf])
buf += newbuf
start = max(buflen + 1 - seplen, 0)
match = pat.search(buf, start)
if match:
idx = match.end()
recv_buf[:curbuf] = []
recv_buf[0] = buf[idx:]
buf = buf[:idx]
self._recv_buf_len -= idx
if not recv_buf[0]:
recv_buf.pop(0)
self._maybe_resume_reading()
return buf
buflen += len(newbuf)
curbuf += 1
if self._read_paused or self._eof_received:
recv_buf[:curbuf] = []
self._recv_buf_len -= buflen
self._maybe_resume_reading()
raise asyncio.IncompleteReadError(cast(bytes, buf), None)
await self._block_read(datatype) | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/utils/decorators/__init__.py | python | Depends.__init__ | (self, *dependencies, **kwargs) | The decorator is instantiated with a list of dependencies (string of
global name)
An example use of this would be:
.. code-block:: python
@depends('modulename')
def test():
return 'foo'
OR
@depends('modulename', fallback_function=function)
def test():
return 'foo'
.. code-block:: python
This can also be done with the retcode of a command, using the
``retcode`` argument:
@depends('/opt/bin/check_cmd', retcode=0)
def test():
return 'foo'
It is also possible to check for any nonzero retcode using the
``nonzero_retcode`` argument:
@depends('/opt/bin/check_cmd', nonzero_retcode=True)
def test():
return 'foo'
.. note::
The command must be formatted as a string, not a list of args.
Additionally, I/O redirection and other shell-specific syntax are
not supported since this uses shell=False when calling
subprocess.Popen(). | The decorator is instantiated with a list of dependencies (string of
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"""
The decorator is instantiated with a list of dependencies (string of
global name)
An example use of this would be:
.. code-block:: python
@depends('modulename')
def test():
return 'foo'
OR
@depends('modulename', fallback_function=function)
def test():
return 'foo'
.. code-block:: python
This can also be done with the retcode of a command, using the
``retcode`` argument:
@depends('/opt/bin/check_cmd', retcode=0)
def test():
return 'foo'
It is also possible to check for any nonzero retcode using the
``nonzero_retcode`` argument:
@depends('/opt/bin/check_cmd', nonzero_retcode=True)
def test():
return 'foo'
.. note::
The command must be formatted as a string, not a list of args.
Additionally, I/O redirection and other shell-specific syntax are
not supported since this uses shell=False when calling
subprocess.Popen().
"""
log.trace(
"Depends decorator instantiated with dep list of %s and kwargs %s",
dependencies,
kwargs,
)
self.dependencies = dependencies
self.params = kwargs | [
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simoncadman/CUPS-Cloud-Print | 5d96eaa5ba1d3ffe40845498917879b0e907f6bd | oauth2client/locked_file.py | python | LockedFile.filename | (self) | return self._opener._filename | Return the filename we were constructed with. | Return the filename we were constructed with. | [
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"""Return the filename we were constructed with."""
return self._opener._filename | [
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kivy/kivy-designer | 20343184a28c2851faf0c1ab451d0286d147a441 | designer/core/project_manager.py | python | ProjectWatcher.stop_watching | (self) | To stop watching currently watched directory. This will also call
join() on the thread created by Observer. | To stop watching currently watched directory. This will also call
join() on the thread created by Observer. | [
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'''To stop watching currently watched directory. This will also call
join() on the thread created by Observer.
'''
if self._observer:
self._observer.unschedule_all()
self._observer.stop()
self._observer.join()
self._observer = None | [
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phonopy/phonopy | 816586d0ba8177482ecf40e52f20cbdee2260d51 | phonopy/harmonic/dynamical_matrix.py | python | DynamicalMatrixNAC.nac_method | (self) | return self._method | Return NAC method name. | Return NAC method name. | [
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"""Return NAC method name."""
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spotify/luigi | c3b66f4a5fa7eaa52f9a72eb6704b1049035c789 | luigi/execution_summary.py | python | _get_number_of_tasks_for | (status, group_tasks) | return _get_number_of_tasks(group_tasks[status]) | [] | def _get_number_of_tasks_for(status, group_tasks):
if status == "still_pending":
return (_get_number_of_tasks(group_tasks["still_pending_ext"]) +
_get_number_of_tasks(group_tasks["still_pending_not_ext"]))
return _get_number_of_tasks(group_tasks[status]) | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/pandas/core/series.py | python | Series.ftype | (self) | return self._data.ftype | Return if the data is sparse|dense. | Return if the data is sparse|dense. | [
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"""
Return if the data is sparse|dense.
"""
return self._data.ftype | [
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realpython/book2-exercises | cde325eac8e6d8cff2316601c2e5b36bb46af7d0 | web2py-rest/gluon/contrib/pymysql/connections.py | python | Connection.literal | (self, obj) | return escape_item(obj, self.charset) | Alias for escape() | Alias for escape() | [
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] | def literal(self, obj):
''' Alias for escape() '''
return escape_item(obj, self.charset) | [
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joe42/CloudFusion | c4b94124e74a81e0634578c7754d62160081f7a1 | cloudfusion/third_party/requests_1_2_3/requests/api.py | python | put | (url, data=None, **kwargs) | return request('put', url, data=data, **kwargs) | Sends a PUT request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
:param \*\*kwargs: Optional arguments that ``request`` takes. | Sends a PUT request. Returns :class:`Response` object. | [
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] | def put(url, data=None, **kwargs):
"""Sends a PUT request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
:param \*\*kwargs: Optional arguments that ``request`` takes.
"""
return request('put', url, data=data, **kwargs) | [
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PySimpleGUI/PySimpleGUI | 6c0d1fb54f493d45e90180b322fbbe70f7a5af3c | PySimpleGUI.py | python | _fixed_map | (style, style_name, option, highlight_colors=(None, None)) | return new_map | [] | def _fixed_map(style, style_name, option, highlight_colors=(None, None)):
# Fix for setting text colour for Tkinter 8.6.9
# From: https://core.tcl.tk/tk/info/509cafafae
# default_map = [elm for elm in style.map("Treeview", query_opt=option) if '!' not in elm[0]]
# custom_map = [elm for elm in style.map(style_name, query_opt=option) if '!' not in elm[0]]
default_map = [elm for elm in style.map("Treeview", query_opt=option) if '!' not in elm[0] and 'selected' not in elm[0]]
custom_map = [elm for elm in style.map(style_name, query_opt=option) if '!' not in elm[0] and 'selected' not in elm[0]]
if option == 'background':
custom_map.append(('selected', highlight_colors[1] if highlight_colors[1] is not None else ALTERNATE_TABLE_AND_TREE_SELECTED_ROW_COLORS[1]))
elif option == 'foreground':
custom_map.append(('selected', highlight_colors[0] if highlight_colors[0] is not None else ALTERNATE_TABLE_AND_TREE_SELECTED_ROW_COLORS[0]))
new_map = custom_map + default_map
return new_map | [
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | openedx/core/djangoapps/user_authn/views/password_reset.py | python | PasswordResetTokenValidation.post | (self, request) | return Response({'is_valid': is_valid}) | HTTP end-point to validate password reset token. | HTTP end-point to validate password reset token. | [
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""" HTTP end-point to validate password reset token. """
is_valid = False
token = request.data.get('token')
try:
token = token.split('-', 1)
uid_int = base36_to_int(token[0])
if request.user.is_authenticated and request.user.id != uid_int:
return Response({'is_valid': is_valid})
user = User.objects.get(id=uid_int)
if UserRetirementRequest.has_user_requested_retirement(user):
return Response({'is_valid': is_valid})
is_valid = default_token_generator.check_token(user, token[1])
if is_valid and not user.is_active:
user.is_active = True
user.save()
except Exception: # pylint: disable=broad-except
AUDIT_LOG.exception("Invalid password reset confirm token")
return Response({'is_valid': is_valid}) | [
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pculture/miro | d8e4594441939514dd2ac29812bf37087bb3aea5 | tv/lib/frontends/widgets/widgetutil.py | python | circular_rect_negative | (context, x, y, width, height) | The same path as ``circular_rect()``, but going counter clockwise. | The same path as ``circular_rect()``, but going counter clockwise. | [
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] | def circular_rect_negative(context, x, y, width, height):
"""The same path as ``circular_rect()``, but going counter clockwise.
"""
radius = height / 2.0
inner_width = width - height
inner_y = y + radius
inner_x1 = x + radius
inner_x2 = inner_x1 + inner_width
context.move_to(inner_x1, y)
context.arc_negative(inner_x1, inner_y, radius, -PI/2, PI/2)
context.rel_line_to(inner_width, 0)
context.arc_negative(inner_x2, inner_y, radius, PI/2, -PI/2)
context.rel_line_to(-inner_width, 0) | [
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F8LEFT/DecLLVM | d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c | python/idaapi.py | python | vdui_t.set_num_enum | (self, *args) | return _idaapi.vdui_t_set_num_enum(self, *args) | set_num_enum(self) -> bool | set_num_enum(self) -> bool | [
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"""
set_num_enum(self) -> bool
"""
return _idaapi.vdui_t_set_num_enum(self, *args) | [
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IJDykeman/wangTiles | 7c1ee2095ebdf7f72bce07d94c6484915d5cae8b | experimental_code/tiles_3d/venv_mac/lib/python2.7/site-packages/pkg_resources/__init__.py | python | get_build_platform | () | return plat | Return this platform's string for platform-specific distributions
XXX Currently this is the same as ``distutils.util.get_platform()``, but it
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] | def get_build_platform():
"""Return this platform's string for platform-specific distributions
XXX Currently this is the same as ``distutils.util.get_platform()``, but it
needs some hacks for Linux and Mac OS X.
"""
try:
# Python 2.7 or >=3.2
from sysconfig import get_platform
except ImportError:
from distutils.util import get_platform
plat = get_platform()
if sys.platform == "darwin" and not plat.startswith('macosx-'):
try:
version = _macosx_vers()
machine = os.uname()[4].replace(" ", "_")
return "macosx-%d.%d-%s" % (
int(version[0]), int(version[1]),
_macosx_arch(machine),
)
except ValueError:
# if someone is running a non-Mac darwin system, this will fall
# through to the default implementation
pass
return plat | [
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CyberZHG/keras-bert | f8bb7ab399f62832badf4c618520264bc91bdff1 | keras_bert/bert.py | python | get_custom_objects | () | return custom_objects | Get all custom objects for loading saved models. | Get all custom objects for loading saved models. | [
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"""Get all custom objects for loading saved models."""
custom_objects = get_encoder_custom_objects()
custom_objects['PositionEmbedding'] = PositionEmbedding
custom_objects['TokenEmbedding'] = TokenEmbedding
custom_objects['EmbeddingSimilarity'] = EmbeddingSimilarity
custom_objects['TaskEmbedding'] = TaskEmbedding
custom_objects['Masked'] = Masked
custom_objects['Extract'] = Extract
custom_objects['AdamWarmup'] = AdamWarmup
return custom_objects | [
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adobe/NLP-Cube | 8c8590f9c4c44569b95778c131d4bf1f19761555 | _cube/io_utils/model_store.py | python | ModelStore.delete_model | (self, lang_code, version) | Deletes a local model. Also checks for associated embeddings file and cleans it up as well only if not referenced by any other local model | Deletes a local model. Also checks for associated embeddings file and cleans it up as well only if not referenced by any other local model | [
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"""
Deletes a local model. Also checks for associated embeddings file and cleans it up as well only if not referenced by any other local model
"""
model = lang_code+"-"+str(version)
model_folder = os.path.join(self.disk_path,model)
# check if model exists
if not os.path.isdir(model_folder):
print("Model "+model+" not found! Nothing to delete.")
return
# determine which embedding file we need to delete
model_metadata = ModelMetadata()
model_metadata.read(os.path.join(model_folder,"metadata.json"))
embeddings_file_to_delete = model_metadata.embeddings_file_name
# delete the model
import shutil
try:
shutil.rmtree(model_folder)
except OSError as e:
print ("Error removing folder from local disk: %s - %s." % (e.filename, e.strerror))
# search in other models for referenced embeddings file
found_in_other_models = False
lang_models = self._list_folders()
for lang_model in lang_models:
metadata_file_path = os.path.join(self.disk_path, lang_model, "metadata.json")
if not os.path.exists(metadata_file_path):
continue # this is not a model folder, so skip it
model_metadata.read(os.path.join(self.disk_path, lang_model, "metadata.json"))
other_embeddings_file = model_metadata.embeddings_file_name
if other_embeddings_file == embeddings_file_to_delete:
found_in_other_models = True
print("Embeddings file "+embeddings_file_to_delete+" is still being used by model "+ lang_model+" so it will not be deleted.")
break
if not found_in_other_models:
try:
embeddings_file_to_delete_abs_path = os.path.join(self.disk_path,"embeddings",embeddings_file_to_delete)
os.remove(embeddings_file_to_delete_abs_path)
print("Removed embeddings file "+embeddings_file_to_delete)
except OSError as e: ## if failed, report it back to the user ##
print ("Error removing embeddings file: %s - %s." % (e.filename, e.strerror))
print("Model cleanup successful.") | [
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line/line-bot-sdk-python | d97d488876d504ab3cb6ecfc1574ea42bd669565 | linebot/models/imagemap.py | python | URIImagemapAction.__init__ | (self, link_uri=None, area=None, **kwargs) | __init__ method.
:param str link_uri: Webpage URL
:param area: Defined tappable area
:type area: :py:class:`linebot.models.imagemap.ImagemapArea`
:param kwargs: | __init__ method. | [
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"""__init__ method.
:param str link_uri: Webpage URL
:param area: Defined tappable area
:type area: :py:class:`linebot.models.imagemap.ImagemapArea`
:param kwargs:
"""
super(URIImagemapAction, self).__init__(**kwargs)
self.type = 'uri'
self.link_uri = link_uri
self.area = self.get_or_new_from_json_dict(area, ImagemapArea) | [
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pypa/pipenv | b21baade71a86ab3ee1429f71fbc14d4f95fb75d | pipenv/vendor/urllib3/response.py | python | GzipDecoder.__init__ | (self) | [] | def __init__(self):
self._obj = zlib.decompressobj(16 + zlib.MAX_WBITS)
self._state = GzipDecoderState.FIRST_MEMBER | [
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shichao-an/leetcode-python | 6c523ef4759a57433e10271b584eece16f9f05f3 | minimum_window_substring/solution.py | python | Solution.minWindow | (self, S, T) | return s[res_left:res_right + 1] | [] | def minWindow(self, S, T):
s = S
t = T
d = {}
td = {}
for c in t:
td[c] = td.get(c, 0) + 1
left = 0
right = 0
lefts = []
rights = []
for i, c in enumerate(s):
if c in td:
d[c] = d.get(c, 0) + 1
if self.contains(d, td): # Contains all characters
right = i
# Move left pointers
cc = s[left]
while left <= right and (cc not in d or d[cc] > td[cc]):
if cc in d:
d[cc] -= 1
left += 1
cc = s[left]
lefts.append(left)
rights.append(right)
if not lefts:
return ''
res_left = lefts[0]
res_right = rights[0]
n = len(lefts)
for i in range(1, n):
if rights[i] - lefts[i] < res_right - res_left:
res_left = lefts[i]
res_right = rights[i]
return s[res_left:res_right + 1] | [
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teemu-l/execution-trace-viewer | d2d99e92decb3526efc1f5bd4bae350aa4c7c0d2 | core/trace_files.py | python | save_as_tv_trace | (trace_data, filename) | Saves trace data in a default Trace Viewer format
Args:
trace_data: TraceData object
filename: name of trace file | Saves trace data in a default Trace Viewer format | [
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] | def save_as_tv_trace(trace_data, filename):
"""Saves trace data in a default Trace Viewer format
Args:
trace_data: TraceData object
filename: name of trace file
"""
try:
f = open(filename, "wb")
except IOError:
print("Error, could not write to file.")
else:
with f:
trace = trace_data.trace
f.write(b"TVTR")
file_info = {"arch": trace_data.arch, "version": "1.0"}
if trace_data.pointer_size:
pointer_size = trace_data.pointer_size
elif trace_data.arch == "x64":
pointer_size = 8
else:
pointer_size = 4
file_info["pointer_size"] = pointer_size
file_info["regs"] = list(trace_data.regs.keys())
file_info["ip_reg"] = trace_data.ip_reg
json_blob = json.dumps(file_info)
json_blob_length = len(json_blob)
f.write((json_blob_length).to_bytes(4, byteorder="little"))
f.write(json_blob.encode())
for i, t in enumerate(trace):
f.write(b"\x00")
disasm = t["disasm"][:255] # limit length to 0xff
f.write((len(disasm)).to_bytes(1, byteorder="little"))
f.write(disasm.encode())
comment = t["comment"][:255]
f.write((len(comment)).to_bytes(1, byteorder="little"))
f.write(comment.encode())
reg_change_newdata = []
reg_change_positions = []
pos = 0
for reg_index, reg_value in enumerate(t["regs"]):
if i == 0 or reg_value != trace[i - 1]["regs"][reg_index]:
reg_change_newdata.append(reg_value) # value changed
reg_change_positions.append(pos)
pos = -1
pos += 1
reg_changes = len(reg_change_positions) & 0xFF
f.write((reg_changes).to_bytes(1, byteorder="little"))
memory_accesses = len(t["mem"]) & 0xFF
f.write((memory_accesses).to_bytes(1, byteorder="little"))
flag = 0
opcodes = bytes.fromhex(t["opcodes"])
opcode_size = len(opcodes)
if "thread" in t:
flag = flag | (1 << 7)
flags_and_opcode_size = flag | opcode_size
f.write((flags_and_opcode_size).to_bytes(1, byteorder="little"))
if "thread" in t:
f.write((t["thread"]).to_bytes(4, byteorder="little"))
f.write(opcodes)
for pos in reg_change_positions:
f.write((pos).to_bytes(1, byteorder="little"))
for newdata in reg_change_newdata:
f.write((newdata).to_bytes(pointer_size, byteorder="little"))
mem_access_flags = []
mem_access_addresses = []
mem_access_data = []
for mem_access in t["mem"]:
flag = 0
if mem_access["access"].lower() == "write":
flag = 1
mem_access_flags.append(flag)
mem_access_data.append(mem_access["value"])
mem_access_addresses.append(mem_access["addr"])
for flag in mem_access_flags:
f.write((flag).to_bytes(1, byteorder="little"))
for addr in mem_access_addresses:
f.write((addr).to_bytes(pointer_size, byteorder="little"))
for data in mem_access_data:
f.write((data).to_bytes(pointer_size, byteorder="little"))
for bookmark in trace_data.bookmarks:
f.write(b"\x01")
f.write((bookmark.startrow).to_bytes(4, byteorder="little"))
f.write((bookmark.endrow).to_bytes(4, byteorder="little"))
disasm = bookmark.disasm[:255]
disasm_length = len(disasm)
f.write((disasm_length).to_bytes(1, byteorder="little"))
f.write(disasm.encode())
comment = bookmark.comment[:255]
comment_length = len(comment)
f.write((comment_length).to_bytes(1, byteorder="little"))
f.write(comment.encode())
addr = bookmark.addr[:255]
addr_length = len(addr)
f.write((addr_length).to_bytes(1, byteorder="little"))
f.write(addr.encode()) | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.5/django/contrib/gis/gdal/geometries.py | python | OGRGeometry.geom_count | (self) | return capi.get_geom_count(self.ptr) | The number of elements in this Geometry. | The number of elements in this Geometry. | [
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] | def geom_count(self):
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/calendar.py | python | _localized_day.__init__ | (self, format) | [] | def __init__(self, format):
self.format = format | [
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CGATOxford/cgat | 326aad4694bdfae8ddc194171bb5d73911243947 | CGAT/Expression.py | python | ExperimentalDesign._update | (self) | parse design file and fill class attributes.
Call this function whenever self.table changes. | parse design file and fill class attributes. | [
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] | def _update(self):
"""parse design file and fill class attributes.
Call this function whenever self.table changes.
"""
# remove all entries that should not be included
self.table = self.table[self.table["include"] != 0]
# define attributes
self.conditions = self.table['group'].tolist()
self.pairs = self.table['pair'].tolist()
# TS - use OrderedDict to retain order in unique
self.groups = (list(collections.OrderedDict.fromkeys(
self.conditions)))
self.samples = self.table.index.tolist()
# Test if replicates exist, i.e at least one group has multiple samples
# TS - does this need to be extended to check whether replicates exist
# for each group?
max_per_group = max([self.conditions.count(x) for x in self.groups])
self.has_replicates = max_per_group >= 2
# Test if pairs exist:
npairs = len(set(self.pairs))
has_pairs = npairs == 2
# ..if so, at least two samples are required per pair
if has_pairs:
min_per_pair = min([self.pairs.count(x) for x in set(self.pairs)])
self.has_pairs = min_per_pair >= 2
else:
self.has_pairs = False
# all columns except "include" may be considered as factors
self.factors = self.table.drop(["include"], axis=1)
# remove "pair" from factor if design does not include pairs
if not self.has_pairs:
self.factors.drop("pair", inplace=True, axis=1) | [
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ScottfreeLLC/AlphaPy | e6419cc811c2a3abc1ad522a85a888c8ef386056 | alphapy/plots.py | python | plot_scatter | (df, features, target, tag='eda', directory=None) | r"""Plot a scatterplot matrix, also known as a pair plot.
Parameters
----------
df : pandas.DataFrame
The dataframe containing the features.
features: list of str
The features to compare in the scatterplot.
target : str
The target variable for contrast.
tag : str
Unique identifier for the plot.
directory : str, optional
The full specification of the plot location.
Returns
-------
None : None.
References
----------
https://seaborn.pydata.org/examples/scatterplot_matrix.html | r"""Plot a scatterplot matrix, also known as a pair plot. | [
"r",
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"scatterplot",
"matrix",
"also",
"known",
"as",
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"pair",
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"."
] | def plot_scatter(df, features, target, tag='eda', directory=None):
r"""Plot a scatterplot matrix, also known as a pair plot.
Parameters
----------
df : pandas.DataFrame
The dataframe containing the features.
features: list of str
The features to compare in the scatterplot.
target : str
The target variable for contrast.
tag : str
Unique identifier for the plot.
directory : str, optional
The full specification of the plot location.
Returns
-------
None : None.
References
----------
https://seaborn.pydata.org/examples/scatterplot_matrix.html
"""
logger.info("Generating Scatter Plot")
# Get the feature subset
features.append(target)
df = df[features]
# Generate the pair plot
sns.set()
sns_plot = sns.pairplot(df, hue=target)
# Save the plot
write_plot('seaborn', sns_plot, 'scatter_plot', tag, directory) | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/lib-tk/ttk.py | python | Notebook.select | (self, tab_id=None) | return self.tk.call(self._w, "select", tab_id) | Selects the specified tab.
The associated child window will be displayed, and the
previously-selected window (if different) is unmapped. If tab_id
is omitted, returns the widget name of the currently selected
pane. | Selects the specified tab. | [
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] | def select(self, tab_id=None):
"""Selects the specified tab.
The associated child window will be displayed, and the
previously-selected window (if different) is unmapped. If tab_id
is omitted, returns the widget name of the currently selected
pane."""
return self.tk.call(self._w, "select", tab_id) | [
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freedomofpress/securedrop | f768a1a5aa37e790077dfd38d6e7a0299a4b3a0f | securedrop/journalist_app/utils.py | python | validate_hotp_secret | (user: Journalist, otp_secret: str) | return True | Validates and sets the HOTP provided by a user
:param user: the change is for this instance of the User object
:param otp_secret: the new HOTP secret
:return: True if it validates, False if it does not | Validates and sets the HOTP provided by a user
:param user: the change is for this instance of the User object
:param otp_secret: the new HOTP secret
:return: True if it validates, False if it does not | [
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"""
Validates and sets the HOTP provided by a user
:param user: the change is for this instance of the User object
:param otp_secret: the new HOTP secret
:return: True if it validates, False if it does not
"""
strip_whitespace = otp_secret.replace(' ', '')
secret_length = len(strip_whitespace)
if secret_length != HOTP_SECRET_LENGTH:
flash(ngettext(
'HOTP secrets are 40 characters long - you have entered {num}.',
'HOTP secrets are 40 characters long - you have entered {num}.',
secret_length
).format(num=secret_length), "error")
return False
try:
user.set_hotp_secret(otp_secret)
except (binascii.Error, TypeError) as e:
if "Non-hexadecimal digit found" in str(e):
flash(gettext(
"Invalid HOTP secret format: "
"please only submit letters A-F and numbers 0-9."),
"error")
return False
else:
flash(gettext(
"An unexpected error occurred! "
"Please inform your admin."), "error")
current_app.logger.error(
"set_hotp_secret '{}' (id {}) failed: {}".format(
otp_secret, user.id, e))
return False
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home-assistant/supervisor | 69c2517d5211b483fdfe968b0a2b36b672ee7ab2 | supervisor/resolution/evaluations/container.py | python | EvaluateContainer.known_images | (self) | return {
self.sys_homeassistant.image,
self.sys_supervisor.image,
*(plugin.image for plugin in self.sys_plugins.all_plugins),
*(addon.image for addon in self.sys_addons.installed),
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] | def known_images(self) -> set[str]:
"""Return a set of all known images."""
return {
self.sys_homeassistant.image,
self.sys_supervisor.image,
*(plugin.image for plugin in self.sys_plugins.all_plugins),
*(addon.image for addon in self.sys_addons.installed),
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/multiprocessing/connection.py | python | _ConnectionBase.closed | (self) | return self._handle is None | True if the connection is closed | True if the connection is closed | [
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | cms/djangoapps/contentstore/management/commands/export_olx.py | python | export_course_to_directory | (course_key, root_dir) | return export_dir | Export course into a directory | Export course into a directory | [
"Export",
"course",
"into",
"a",
"directory"
] | def export_course_to_directory(course_key, root_dir):
"""Export course into a directory"""
store = modulestore()
course = store.get_course(course_key)
if course is None:
raise CommandError("Invalid course_id")
# The safest characters are A-Z, a-z, 0-9, <underscore>, <period> and <hyphen>.
# We represent the first four with \w.
# TODO: Once we support courses with unicode characters, we will need to revisit this.
replacement_char = '-'
course_dir = replacement_char.join([course.id.org, course.id.course, course.id.run])
course_dir = re.sub(r'[^\w\.\-]', replacement_char, course_dir)
export_course_to_xml(store, None, course.id, root_dir, course_dir)
export_dir = path(root_dir) / course_dir
return export_dir | [
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venth/aws-adfs | 73810a6f60b1a0b1f00921889f163654954fd06f | aws_adfs/reset.py | python | _clear_credentials | (config, profile) | [] | def _clear_credentials(config, profile):
def store_config(config_location, storer):
config_file = configparser.RawConfigParser()
config_file.read(config_location)
if not config_file.has_section(profile):
config_file.add_section(profile)
storer(config_file)
with open(config_location, 'w+') as f:
try:
config_file.write(f)
finally:
f.close()
def profile_remover(config_file):
config_file.remove_section(profile)
config_file.remove_section('profile {}'.format(profile))
store_config(config.aws_credentials_location, profile_remover)
store_config(config.aws_config_location, profile_remover) | [
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ingolemo/python-lenses | 82f9d2755425ba0fdae1c23f0fd912b31d61cd2d | lenses/ui/__init__.py | python | BoundLens.get | (self) | return self._optic.to_list_of(self._state)[0] | Get the first value focused by the lens.
>>> from lenses import bind
>>> bind([1, 2, 3]).get()
[1, 2, 3]
>>> bind([1, 2, 3])[0].get()
1 | Get the first value focused by the lens. | [
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"""Get the first value focused by the lens.
>>> from lenses import bind
>>> bind([1, 2, 3]).get()
[1, 2, 3]
>>> bind([1, 2, 3])[0].get()
1
"""
return self._optic.to_list_of(self._state)[0] | [
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fake-name/ReadableWebProxy | ed5c7abe38706acc2684a1e6cd80242a03c5f010 | WebMirror/management/rss_parser_funcs/feed_parse_extractEggdroptlWordpressCom.py | python | extractEggdroptlWordpressCom | (item) | return False | Parser for 'eggdroptl.wordpress.com' | Parser for 'eggdroptl.wordpress.com' | [
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"eggdroptl",
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"wordpress",
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"com"
] | def extractEggdroptlWordpressCom(item):
'''
Parser for 'eggdroptl.wordpress.com'
'''
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or "preview" in item['title'].lower():
return None
tagmap = [
('tvhss', 'The Villain Has Something to Say', 'translated'),
('PRC', 'PRC', 'translated'),
('Loiterous', 'Loiterous', 'oel'),
]
for tagname, name, tl_type in tagmap:
if tagname in item['tags']:
return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type)
return False | [
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"i... | https://github.com/fake-name/ReadableWebProxy/blob/ed5c7abe38706acc2684a1e6cd80242a03c5f010/WebMirror/management/rss_parser_funcs/feed_parse_extractEggdroptlWordpressCom.py#L1-L21 | |
MrH0wl/Cloudmare | 65e5bc9888f9d362ab2abfb103ea6c1e869d67aa | thirdparty/beautifulsoup/BeautifulSoup.py | python | Tag.get | (self, key, default=None) | return self._getAttrMap().get(key, default) | Returns the value of the 'key' attribute for the tag, or
the value given for 'default' if it doesn't have that
attribute. | Returns the value of the 'key' attribute for the tag, or
the value given for 'default' if it doesn't have that
attribute. | [
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"""Returns the value of the 'key' attribute for the tag, or
the value given for 'default' if it doesn't have that
attribute."""
return self._getAttrMap().get(key, default) | [
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open-cogsci/OpenSesame | c4a3641b097a80a76937edbd8c365f036bcc9705 | libqtopensesame/items/qtitem.py | python | qtitem.rename | (self, from_name, to_name) | desc:
Handles renaming of an item (not necesarrily the current item).
arguments:
from_name:
desc: The old item name.
type: unicode
to_name:
desc: The new item name
type: unicode | desc:
Handles renaming of an item (not necesarrily the current item). | [
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"""
desc:
Handles renaming of an item (not necesarrily the current item).
arguments:
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desc: The old item name.
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to_name:
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if self.name != from_name:
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self.name = to_name
if self.container_widget is None:
return
self.container_widget.__item__ = self.name
self.header.set_name(to_name)
index = self.tabwidget.indexOf(self.widget())
if index is not None:
self.tabwidget.setTabText(index, to_name) | [
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