content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def profile(request, profile_slug):
"""
Display profile details.
"""
speaker_profile = get_object_or_404(AttendeeProfile, slug=profile_slug)
if not profile_page_visible(profile=speaker_profile, for_user=request.user):
return TemplateResponse(request, "conference/profiles/profile_unavailable... | a03d10a9c9641f1fdf04810e915e8a483cb4a01b | 38,296 |
def save_file(filename, contents):
"""Save a file from the editor"""
if not filename:
return 0, 0
with open(filename, 'w') as f:
f.write(contents)
return len(contents), hash(contents) | 8e973f67a22a2e7b0836f8db25090c65238492e3 | 38,297 |
def GetDockerImageFromTagOrDigest(image_name):
"""Gets an image object given either a tag or a digest.
Args:
image_name: Either a fully qualified tag or a fully qualified digest.
Defaults to latest if no tag specified.
Returns:
Either a docker_name.Tag or a docker_name.Digest object.
"""
if no... | 7e61f8a3dde64ec5efa833fc72e909e9140f77f9 | 38,298 |
def line_label(ax, pos, label, dir='v', loc='top', xx=None, yy=None, ha=None, va=None,
line_kwargs={}, text_kwargs={}, dashes=None, rot=None):
"""Plot a vertical line, and give it a label outside the axes.
Arguments
---------
ax : `matplotlib.axes.Axes` object
Axes on which to pl... | 9612f2218ce6559f7deffc0f148c4d205b3608b1 | 38,299 |
from typing import Tuple
import hashlib
def hashfile(path: str, blocksize: int = 65536) -> Tuple[str, str]:
"""Calculate the MD5 hash of a given file
Args:
path ()str, os.path): Path to the file to generate a hash for
blocksize (int, optional): Memory size to read in the file
... | e38e6622534f27bed109a2e2b71373503ca4e7b0 | 38,300 |
import torch
def generate_bandit_samples(logging_policy, syn, k=5):
"""Generates partial-labeled bandit samples with the logging policy.
Arguments:
k: The number of items to be sampled for each user.
"""
logging_policy.set_binary(False)
with torch.no_grad():
feats = {}
fea... | 3ec8d36f7e41e779bd4372aadaeac90e1073ec86 | 38,301 |
def get(key):
"""
Retrieve a constant by key. This is just a short cut into a dictionary.
Parameters
----------
key : Python string or unicode
Key in dictionary in `constants`
Returns
-------
constant : `~astropy.units.Constant`
See Also
--------
_constants : Cont... | 1d9a73b7089ebd126855e7edd7fe275dbd59763c | 38,302 |
def compute_qvalues(state_action_reward: np.ndarray, discount: float) -> np.ndarray:
"""Computes the Q-values of `state_action_reward` under deterministic dynamics."""
transitions = build_transitions(*state_action_reward.shape)
reward = build_reward(state_action_reward)
return reward | 06a987b000dc50ed0d02e913fd980c3c2ab97bd6 | 38,303 |
def parse_csr(csr):
"""
Helper function that parses a CSR.
:param csr:
:return:
"""
assert isinstance(csr, str)
return x509.load_pem_x509_csr(csr.encode("utf-8"), default_backend()) | 7de072cce63b8a13c1666013a40b4091418bb1b0 | 38,305 |
def docker_compose_yml(opts):
"""docker-compose.yml for vscode
Args:
opts (dict): given options, see :obj:`create_project` for
an extensive list.
Returns:
str: file content as string
"""
template = get_template("docker_compose_yml")
return template.safe_substitute(o... | e7e40ee3f9f1946944e6f993e7635636a50cd75d | 38,306 |
def get_directory():
"""
Get the name of home directory of usecase. Use the home directory for file
path construction.
"""
home_dir = dirname(
dirname(abspath(__file__))
) # call dirname twice to get parent dir
return home_dir | bfbb234cfcaac0e900f8bf472e0f5cf4ac249fd1 | 38,307 |
import pathlib
def package_data() -> pathlib.Path:
""" Returns the absolute path to the circe/data directory. """
return pathlib.Path(__file__).parents[1].joinpath("data") | 19d8fa28ba872f8633e6efddb310d30264d831e6 | 38,309 |
import re
def changeFileNoInFilePath(path: str, fileNo: int) -> str:
"""replaces the number in the path with the given number."""
separator = r"[0-9]+\."
splitted_path = re.split(separator, path, 1)
new_path = splitted_path[0] + str(fileNo) + "." + splitted_path[1]
return new_path | 070fbe30d2937b57ef601fb764cf68ec219b9c95 | 38,310 |
def common_fill_value(a, b):
"""Return the common filling value of a and b, if any.
If a and b have different filling values, returns None.
"""
t1 = get_fill_value(a)
t2 = get_fill_value(b)
if t1 == t2:
return t1
return None | f6d7e06c0553efece9972e023f4d6237f62cdb75 | 38,311 |
def hybrid_to_plevs(var, hyam, hybm, ps, plev):
"""Convert from hybrid pressure coordinate to desired pressure level(s)."""
p0 = 1000. # mb
ps = ps / 100. # convert unit from 'Pa' to mb
levels_orig = cdutil.vertical.reconstructPressureFromHybrid(
ps, hyam, hybm, p0)
levels_orig.units = 'mb... | dce7ff8d3cee56b075b1de63b0d814858d466d5e | 38,312 |
def pentatope():
"""
Vertices of the 5-cell
"""
s = 3.2**-0.5
return np.array([
np.quaternion(1, 0, 0, 0),
np.quaternion(-0.25, s, s, s),
np.quaternion(-0.25, s, -s, -s),
np.quaternion(-0.25, -s, s, -s),
np.quaternion(-0.25, -s, -s, s),
]) | 1315f5f70a01d6112e97461e08917fec5cf1fbb2 | 38,313 |
def checkDaysWeeksElapsed(count, days, weeks):
"""
:param count: the number of checks performed
:param days: the number of days elapsed
:param weeks: the number of weeks elapsed
:return: the number of checks performed (0 if one day has gone).
"""
if (count % 144) == 0:
days += 1
... | ec425653c6ca21a52ff4a98d18326f6278e83a6c | 38,314 |
def spawnpty(cmd, logfile=None, env=None, callback=None,
persistent=False, merge=True, pwent=None, async=False,
devnull=False):
"""Start a child process using a pty.
"""
pm = get_procmanager()
proc = pm.spawnpty(cmd, logfile, env, callback, persistent, merge, pwent,
... | efab388d7f09419272807fdb788bb8794fb92a6c | 38,315 |
import typing
def update_submission_status(
sub_status: SubmissionStatus,
values: typing.Union[Annotations, dict],
status: str = None,
) -> SubmissionStatus:
"""Updates submission status and annotations
Args:
sub_status: A synapseclient.SubmissionStatus
values: A synapseclient.A... | 8ff18d399048350cea7f8043321a5c4dec346924 | 38,317 |
import signal
def get_window_radial(xx, yy, zz=None, wtype='hamming', rmax=None, duration=None,
x0=0, x1=None, y0=0, y1=None, z0=0, z1=None,
n=500):
"""
General method to get a window with shape (xx.shape[:], duration) or (xx.shape[:]) if duration is None
... Wi... | 8d8298716e4e2fd825c4c1bcd4adf97d6fde7f1d | 38,318 |
def ldns_resolver_fail(*args):
"""LDNS buffer."""
return _ldns.ldns_resolver_fail(*args) | c5934c4efbd0786dedf01a800ddfcf72346dc088 | 38,319 |
def get_batch_jdot(selected_source, selected_target, source_data_file, target_data_file, batch_size, n_labels, training_keys_file, validation_keys_file,
data_split=0.8, overwrite_data=False, labels=None, augment=False,
augment_flip=Tr... | c152bfe13fda3d51a8a6a8763e867ffe46b87149 | 38,321 |
from typing import Dict
from typing import List
import uuid
async def _choose_existing_instances(
instance_registrar: InstanceRegistrar,
resources_required_per_job: Resources,
num_jobs: int,
) -> Dict[str, List[str]]:
"""
Chooses existing registered instances to run the specified job(s). The gener... | ec0bf9ed8ae5a1a9b8234cadff4f358bcf2273f4 | 38,322 |
def secret_view(request):
"""Dummy view with redirect to login."""
return {} | 9b0c3a6d2fe0b6aef2328a97d6407b72f8bc3c16 | 38,323 |
def get_data_from_all_ezo_devices(device_list):
"""Returns a list of string output from all EZO devices."""
output = []
for device in device_list:
device.write("R")
sleep(device.long_timeout)
for device in device_list:
output.append(read_data(device))
return output | 0aab931cd5a7f2a6d48cf3d969ad86286d78460c | 38,324 |
def get_moves(board, castling_availability, enpassant_square):
"""List of all moves for white for the given position."""
moves = []
points = board.keys()
for start, piece in board.items():
if piece == 'P':
moves.extend(get_pawn_finish(board, start, enpassant_square))
if piece... | 2b18a3d8a100e87a08424fd02defe412ee639e6e | 38,325 |
def get_export_from_line(line):
"""Get export name from import statements"""
if not line.startswith("export * from"):
return None
start = line.find("\"")
if start > 0:
return line[start+1:-3] # remove ";\n
return None | c4a0396dcb238b89e7b7e82479935b1849003f85 | 38,326 |
def all_col(G):
"""
Check if every column of G contains a nonzero entry
Parameters
----------
G : lin_op
operator to check
Returns
-------
Boolean
True if every column of G contains a nonzero entry
"""
ri, ci = G.toCSR().nonzero()
return np.all(np.in1d(np.a... | 484978f90ee6e015ae1027e682c67293f7f42333 | 38,327 |
def get_challenge(request, scopes=["build"]):
"""Given an unauthenticated request, return a challenge in
the Www-Authenticate header
Arguments:
==========
request (requests.Request): the Request object to inspect
repository (str) : the repository name
scopes (list) : li... | 38c8d419c7712ebd8dc3db11663baa793ba06d0f | 38,328 |
import time
def abbn_eva():
"""
Real Name: b'"Ab-bn Eva"'
Original Eqn: b'Max(0,"monthly evp ab-bn" (Time)*"area ab-bn"/1000)'
Units: b''
Limits: (None, None)
Type: component
b''
"""
return np.maximum(0, monthly_evp_abbn(time()) * area_abbn() / 1000) | ba58382353702dd87c451cd199a2e476b8068d2c | 38,329 |
def construct_organisation_role_dict(organisation_roles):
"""Return a dict with 3 keys: organisations, roles, and organisation_roles.
Args:
organisation_roles: an iterable of OrganisationRoles.
"""
data = {}
# Defensive programming: make sure we have a unique set of
# organisation_rol... | b1105832eab9ee89dfa5d1e43b51c05fb569b953 | 38,330 |
def validate_ruletype(t):
"""Validate fs_use_* rule types."""
if t not in ["fs_use_xattr", "fs_use_trans", "fs_use_task"]:
raise exception.InvalidFSUseType("{0} is not a valid fs_use_* type.".format(t))
return t | dd1c33c463f765bb8abe5e5086a9bd0d46b2c7f6 | 38,331 |
async def is_dark_theme(monitor=None, app=None):
"""Return whether or not iTerm2 theme is dark"""
theme=None
if monitor:
theme = await monitor.async_get()
elif app:
theme = await app.async_get_variable("effectiveTheme")
else:
raise ValueError('Need a monitor or app instance t... | 8c356514d19219af83a36f422d78e688351c9f09 | 38,332 |
import json
def load_json(path):
"""Load json from file"""
json_object = json.load(open(path))
return json_object | 17db7327b6dac16aaeaff2354f828646eff695b2 | 38,333 |
def home_url_response(url_endpoint: str) -> Response:
"""Represent response from `home` page"""
return Get(url_endpoint + _home).response() | d8f31c659dfe71c3dcd7b96cdfe5aa86ae96fc03 | 38,334 |
def evidence_download(filename):
"""Download an evidence file
:param filename: Filename to download
:returns t_evidence.f_data: Base64 of file contents
"""
row = db(db.t_evidence.f_evidence == filename).select(db.t_evidence.f_data).first()
if row is None:
return None
return row.f_d... | d8e0265e385039975b3ec9af95546f4c0fc7d628 | 38,336 |
def a_h(P, h, region = 0):
"""Isobaric cubic expansion coefficient [1 / K]"""
if region is 0:
region = idRegion_h(P, h)
if region is 1:
return region1.a_h(P, h)
elif region is 2:
return region2.a_h(P, h)
elif region is 4:
return region4.a_h(P, h)
else:
re... | d2fe0ca5819d01ceb4c1e2573134d71f999412e8 | 38,337 |
def register_data_module(name: str):
"""
New data module types can be added to OpenSpeech with the :func:`register_data_module` function decorator.
For example::
@register_data_module('ksponspeech')
class LightningKsponSpeechDataModule:
(...)
.. note:: All vocabs must imple... | 31ee6d841c41887b831d96ac879108eb5ac9c2c7 | 38,338 |
def _bin_labels_to_segments(bin_labels: list) -> list[tuple]:
"""
Convert bin labels (time-axis list data) to segment data
>>> _bin_labels_to_segments(['female'] * 5 + ['male'] * 10 + ['noise'] * 5)
[('f', 0, 5), ('bbb', 5, 15), ('v', 15, 20)]
"""
if len(bin_labels) == 0:
return []
... | 6b0eafdaf6affee33a3b655ba8ae7aebf2b38746 | 38,339 |
def get_winners(post_link, MEDIA_LINK, bot):
"""It creates a list of winners."""
favorite_comments = get_favorite_comments(post_link, MEDIA_LINK, bot)
maybe_winners = defaultdict(list)
for user_id, username, text in favorite_comments:
usernames_from_comment = get_usernames_from_comment(text)
... | dcffc9ab9c225e4536a05d4ab8ecf83c465cdbf5 | 38,340 |
def get_latest_layer_version(package="boto3", region="ap-southeast-1"):
"""
return:
layer_version (int): returns latest layer version as an integer!
"""
client = session.client("dynamodb")
pk = f"lyr#{region}.{package}"
sk = "lyrVrsn0#"
response = client.get_item(
TableName... | 1568bdb5f921e4e33f0b782723e1d7a4d2febacb | 38,341 |
def build_efficiencies(efficiencies, species_names, default_efficiency=1.0):
"""Creates line with list of third-body species efficiencies.
Parameters
----------
efficiencies : dict
Dictionary of species efficiencies
species_names : dict of str
List of all species names
default_e... | a8f8912cd290b86697c67465b4aed18220a8c889 | 38,342 |
import time
def sudo_password_needed(session: SessionBase) -> bool:
"""
Check whether password reentry is necessary for sudo actions
"""
timestamp = int(session.get(SUDO_SESSION_KEY, '0'))
time_diff = time.time() - timestamp
return time_diff >= SUDO_TIMEOUT_SEC or time_diff < 0 | 5a72a2bdf87e133994768bee170fb2841ebe9142 | 38,344 |
import copy
def increment_1(time, seconds):
""" Pure function，不會修改引數，大多會產出結果。 """
new_time = copy.deepcopy(time)
new_time.second += seconds
modify_time(new_time)
return new_time | f43a7666f10d594feb18dac05126b4a0883ad4e3 | 38,345 |
def generate_county_dcids(countyfips):
"""
Args:
countyfips: a county FIPS code
Returns:
the matching dcid for the FIPS code
"""
if countyfips != 59:
dcid = "dcid:geoId/" + str(countyfips).zfill(5)
else:
dcid = "dcid:country/USA"
return dcid | ae294e5467b9c735e175d4a69ff30f8ca189c71f | 38,346 |
from allennlp.models.archival import load_archive # import here to avoid circular imports
from typing import Type
from re import T
from typing import Any
from typing import Dict
from typing import List
from typing import Tuple
from typing import Set
from typing import Union
def construct_arg(cls: Type[T], # pylint: ... | 35a21d9e4efcf88758552017c741ff61d4e45d0a | 38,347 |
def xy2r(x, y, data, xc, yc):
"""Convert (x, y) values to distance of a (xc, yc) position."""
r = np.hypot((x-xc), (y-yc))
return np.ravel(r), np.ravel(data) | 22354dc1925f418f6d1ba55a7a7b45a7671a8f8d | 38,349 |
def _inverse_lookup(dictionary, value):
"""Does an inverse lookup of key from value"""
return [key for key in dictionary if dictionary[key] == value] | 4ad34b27fbc35b3bae95bcb8442d1a2f7df94e9f | 38,350 |
def list_delivery_models(request, network):
"""Propose to create a delivery based on a previous delivery."""
nw = m.Network.objects.get(id=network)
vars = {
'user': request.user,
'nw': nw,
'deliveries': m.Delivery.objects.filter(network=nw).order_by("-id")
}
return render_to_... | d802fef9f0cbc5e70ded037bc26f61c72366d3c6 | 38,351 |
import re
def tags_score(tags, kw):
"""
checks library tags
see http://www.boost.org/doc/libs/1_35_0/more/getting_started/unix-variants.html 6.1
"""
score = 0
needed_tags = {
'threading': kw['tag_threading'],
'abi': kw['tag_abi'],
'toolset': kw['tag_toolset'],
'version': kw['tag_version'],
... | 1ca7ed14bde46e7971f2b0a0f011f93221333653 | 38,352 |
def access_userPosition(request):
"""
NOTE:
id from users databases
must in or equal to users position databases
"""
user_data = UsersDataSet.getUsersRawData()
position_data = UsersDataSet.getUsersPositionData()
new_data = []
# almost same, we need some params to access it
che... | 18a2bea637db4041de6f3d2d99cd9bcd1966a8ef | 38,353 |
def column_to_image(columns, images_shape, filter_shape, stride, padding):
"""Rearrange columns into image blocks.
Parameters
----------
columns
images_shape : tuple(n_images, n_channels, height, width)
filter_shape : tuple(height, _width)
stride : tuple(height, width)
padding : tuple(h... | 535ca6a945fac65bc7ca02c6f250b347ab17ad2e | 38,354 |
def horizontal_shear(origin_img, sh = 0.5):
"""Shears an image horizontal
Parameters:
----------
origin_img
original image to shear iamge horizontally
sv: float, optional
shearing percentage
Returns:
-----
out_img
horizontally sheared image
"""
# find he... | c56e190b08e9656953fecfd3c3863006a70d1ac5 | 38,356 |
def isentropic_beta(tab, spec, *XYf):
"""Isentropic bulk modulus"""
return XYf[0]*tab.q['Cs2', spec](*XYf) | 3592e31612c94e0000d80f8be13369338fb6b329 | 38,357 |
import itertools
def tensor_combinations_phases(matrices, repeat, phases):
"""Compute a list of tensor products for the iteration of matrices,
with additional rotation along the z-axis
"""
products = itertools.product(matrices, repeat=repeat)
tensor_products = []
for mats in products:
... | d737b8e22229edbff79ec40cb428ba7ed0e16e97 | 38,358 |
def cluster_verification_get(context, verification_id):
"""Return verification with the specified verification_id."""
return IMPL.cluster_verification_get(context, verification_id) | cdd87710e29baa637d3f2afcb11918fd43b76d62 | 38,360 |
def __sub_tree(self, root_node):
"""
Extract the sub tree rooted in the given node of the current tree.
The result is a new tree :math:`st` and a node map :math:`nm` such that:
- the node map associates each node of the sub tree :math:`st` to its corresponding node in the original tree
- the order... | bae4371722a04d33dac6a301a88521aeb26717c9 | 38,362 |
def irls_one_step(pdf: pd.DataFrame, alpha_value: Float, n_cov: Int) -> NDArray[Float]:
"""
Performs one step of the IRLS algorithm using the components found in pdf and a value of alpha.
Returns the resulting coefficient values. If n_cov > 0, then the first n_cov columns from the design matrix X
are a... | cc3f4f78857a0099830424ecb44bd47875a7f597 | 38,363 |
def get_alns_instance(repair_operators=None, destroy_operators=None, seed=None):
"""
Test helper method.
"""
alns = ALNS(rnd.RandomState(seed))
if repair_operators is not None:
for idx, repair_operator in enumerate(repair_operators):
alns.add_repair_operator(repair_operator, nam... | b56c60e1b9d07fdda994874e06938c2569f2add4 | 38,364 |
import random
import string
def create_key(holder: str) -> AuthKey:
"""Function for creating an authentication key."""
key: str = ''.join(random.choice(string.ascii_letters) for _ in range(100))
return AuthKey(value = key, holder = holder) | 938a60c227f0e5a344a0e3603a883c828b95095c | 38,365 |
import functools
def dictify(f):
"""Convert generator output to a dict"""
@functools.wraps(f)
def dictify_helper(*args, **kwargs):
output = f(*args, **kwargs)
if kwargs.get('as_generator'):
return output
elif output is not None:
return dict(output)
... | 0da4b552a8757c698060c6bee54509163e210988 | 38,367 |
import re
def get_song_id(url: str):
"""Get soundcloud id from website."""
html = session.get(url)
match = re.search(r"soundcloud://sounds:(\d+)", html.text)
if match:
return match.group(1)
else:
raise RuntimeError(f"Invalid url, {url}") | 9389af0e7d8af7acab76fe4d0c5eede1d52dc245 | 38,368 |
def checkdeplaid(incidence):
"""
Given an incidence angle, select the appropriate deplaid method.
Parameters
----------
incidence : float
incidence angle extracted from the campt results.
"""
if incidence >= 95 and incidence <= 180:
return 'night'
elif incidence... | 806ef360e7b5b3d7138d88be2f83267e7668d71e | 38,369 |
def error_test(true, predict):
"""
Function for classifcation of errors.
"""
if true == predict:
return 1
else:
return 0 | 87c1a56ffb52e1cec61a9ce3cab870b7c70fa059 | 38,370 |
def determine_high_cor_pair(correlation_row, sorted_correlation_pairs):
"""Select highest correlated variable given a correlation row with columns:
["pair_a", "pair_b", "correlation"]. For use in a pandas.apply().
Parameters
----------
correlation_row : pandas.core.series.series
Pandas seri... | 36eccfe0ffb0ac43caf49fe4db8c35c58d0fa29c | 38,371 |
def sgd_optim(config = None, global_step = None):
"""
Performs vanilla stochastic gradient descent.
config format:
lr_base: Scalar learning rate.
"""
learning_rate = config["learning_rate"]
train_step = tf.train.GradientDescentOptimizer(learning_rate)
#train_step = tf.train.Gradi... | e2c45e72b76b8209d876ab756cb82a3d8eae0228 | 38,372 |
from re import T
def customise_pr_person_controller(**attr):
"""
Customise pr_person controller
"""
s3 = current.response.s3
# Custom prep
standard_prep = s3.prep
def custom_prep(r):
# Call standard prep
if callable(standard_prep):
result = standard_prep(r... | 7a951ca49f212d62c5e52b2d80a37e614e5e61cb | 38,373 |
def get_file_content(file_name):
"""获取文件的内容"""
try:
f = open(file_name, 'rb')
file_content = f.read()
f.close()
except Exception as e:
print("打开文件异常")
else:
return file_content | 329eb747a6513899b7ccfaf70754fad721f8d88d | 38,374 |
def create_task_a_model():
"""
Initializes the mode. Edit the code below if you would like to change the model.
"""
model = nn.Sequential(
nn.Flatten(), # Flattens the image from shape (batch_size, C, Height, width) to (batch_size, C*height*width)
nn.Linear(28*28*1, 10)
# No... | 1330fbe52a047d3c6c16f9122899ab1947906765 | 38,375 |
def title_case(sentence):
"""
Convert a string to title case.
Parameters
----------
sentence: string
String to be converted to title case
Returns
----------
ret : string
String converted to title case.
Example
----------
>>> title_case('ThIS iS a StrInG to ... | 4a284854d14e655bd09db8d3ae2d254cfb1e4021 | 38,377 |
def preprocess_img(img):
"""
Images are converted from RGB to grayscale and downsampled by a factor of
2. Deepmind actually used a final 84x84 image by cropping since their GPU
wanted a square input for convolutions. We do not preprocess, rather we
store as uint8 for the sake of memory.
:param i... | 0fcd15035f1eb74ca7b343d0de524dd030c6702f | 38,381 |
def logits_fn(features, feature_columns, params):
"""Calculate logits."""
input_layer = {col.name: tf.keras.layers.DenseFeatures(col)(features)
for col in feature_columns}
input_layer_mf_user, input_layer_mlp_user = tf.split(
input_layer["user_id_embedding"], [params["mf_dim"], params["mlp... | 43d185e5e1ded2b38bdb112c6d633cad6884c2c0 | 38,382 |
def processoutgoing(raw, format):
"""Process outgoing data"""
process = mapping.get(format)
if not process:
return None
return process.outgoing(raw) | 2375c77a104dd441b7d9131f0aa48acb18cdcd06 | 38,384 |
def create_nonlocal_gateway_cluster_name(namespace: str) -> str:
"""Create the cluster name for the non-local namespace that uses a gateway."""
return "remote-{0}-gateway".format(namespace) | 9ca9758a7ee68ede6e57a7f50f2d772b45ee844b | 38,385 |
def add_position_network_count_entries_for_one_organization(voter_id, organization_we_vote_id,
google_civic_election_id=0):
"""
This is called when a voter follows an organization.
:param voter_id:
:param organization_we_vote_id:
:param goo... | fde029043bd824ba346feba46d93f1573602b8e6 | 38,386 |
def GetDefaultExecutor():
"""Creates a new instance of the configured executor if none exists and returns it"""
global DEFAULT_EXECUTOR
if DEFAULT_EXECUTOR is not None:
return DEFAULT_EXECUTOR
executor_name = configuration.conf.get('core', 'EXECUTOR')
DEFAULT_EXECUTOR = _get_executor(exec... | 0c80b1c5fa3f07a3a94f1d6ef7b55e571cf2bd0a | 38,387 |
from typing import List
async def get_normalized_node_handler(curie: List[str] = Query(['MESH:D014867', 'NCIT:C34373'])):
"""
Get value(s) for key(s) using redis MGET
"""
normalized_nodes = await get_normalized_nodes(app, curie)
if not normalized_nodes:
raise HTTPException(detail='No matc... | 8d30b6361dd9f3d2afa93933454748e7bd737683 | 38,389 |
def parse_coords(ifile, ctype=_ctype):
"""Parses a list of coordinate pairs."""
points = [tuple(map(ctype, pair.split(", "))) for pair in ifile if pair]
points = [Point(*pair) for pair in points]
return points | 057d1395580f5bf313f0e48504adc4a88943f8b6 | 38,390 |
def bytecode_from_blockchain(creation_tx_hash, ipc, rpc_host='127.0.0.1', rpc_port=8545, rpc_tls=False):
"""Load bytecode from a local node via
creation_tx_hash = ID of transaction that created the contract.
"""
if ipc:
eth = EthIpc()
else:
eth = EthJsonRpc(rpc_host, rpc_port, rpc_t... | bc07cfc6e645c93fb4c1b67acdca0a4292ab0f64 | 38,391 |
def geometric_estimation(algo='ml', data=None, **kwargs):
"""
"""
return _estimation(algo,
data,
dict(ml = GeometricDistributionMLEstimation.Estimator),
**kwargs) | 63f087e60bdb877a9c0417f67085872070656c55 | 38,392 |
def get_go2parents_isa(go2obj):
"""Get set of immediate parents GO IDs"""
go2parents = {}
for goid_main, goterm in go2obj.items():
parents_goids = set(o.id for o in goterm.parents)
if parents_goids:
go2parents[goid_main] = parents_goids
return go2parents | 1a7d79e1233e497dce109690d3e2105f442bc3b9 | 38,393 |
def flatten_dict(value):
# type: (typing.Mapping[str, Any]) -> Dict[str, Any]
"""Adds dots to all nested fields in dictionaries.
Raises an error if there are entries which are represented
with different forms of nesting. (ie {"a": {"b": 1}, "a.b": 2})
"""
top_level = {}
for key, val in value... | 093371728d76ef3d5e8c27d6023b41e282e67e23 | 38,394 |
from datetime import datetime
def new_text():
""" Write a new text post page """
form = CreatePostForm()
if form.validate_on_submit():
t = datetime.utcnow()
textpost = TextPost(author=current_user._get_current_object(),
title=form.title.data,
timestamp=t,
tex... | 91f69c4648c1af411bfec0d26424981432441cbd | 38,395 |
def Created_Session(msg):
"""
创建会话并返回会话id
"""
try:
response = core.create_session()
except grpc.RpcError as e:
details = e.details()
logger.error("error details:{details}")
return {"flag": False, "details": details, }
session_id = response.session_id
logger.i... | 628fcfa39746451401ab44fdffeb8716a06d13c9 | 38,396 |
from typing import Optional
def get_steering_policy_attachment(steering_policy_attachment_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetSteeringPolicyAttachmentResult:
"""
This data source provides details about a specific Steering Pol... | 3ee09c995dd9cb620ee0cff1580682333e3345f8 | 38,397 |
def get_parsing_plan_log_str(obj_on_fs_to_parse, desired_type, log_only_last: bool, parser):
"""
Utility method used by several classes to log a message indicating that a given file object is planned to be parsed
to the given object type with the given parser. It is in particular used in str(ParsingPlan), b... | 9932894d5184c2e0ed4948d214206307bea4a612 | 38,399 |
from typing import Optional
def original_text_sector(
run: Optional[Run] = None,
clustered: bool = True,
):
"""the text sector for each company from the
original clustering. If the companies were not included in that
the text sector clustering, this will be `None` for each company."""
run = ru... | 8a92cc66954d90651bb2562afc84e42131a599d1 | 38,401 |
from typing import Union
from typing import Dict
from typing import List
def flatten_errors(error_message: Union[Dict, List, str]) -> str:
"""Flatten Cerberus' error messages."""
def flatten_dict(error_dict: Dict) -> str:
"""Return a string version of the dict."""
return ", ".join([f"{key}: {f... | ab6f359cc214a5a1929254e6066fdc6740938f09 | 38,402 |
def get_byuserid(u_id, categories):
"""Render all gifts created by a user of id u_id.
Arguments:
u_id (int): the id of the desired user.
categories (object): generally passed through the
@include_categories decorator,
contains all categories in the data... | 615d12e32fc30ab18ea9b1010516ec94e8b17815 | 38,404 |
def index(request):
"""
This view redirects user to home if logged in else it redirects user
to login page.
"""
if request.user.is_authenticated:
return HttpResponseRedirect('home')
return HttpResponseRedirect('login') | f89da15db58f1ae6e4d206086cac36dd3396acb4 | 38,405 |
def _classname(class_):
"""Returns the full name for a class. Has option for overriding
some class names to hide internal details. The overrides are
stored in the `_class_aliases` dictionaries.
"""
rawname = "{}.{}".format(class_.__module__, class_.__name__)
if rawname in _class_aliases:
... | ca1e7f66646e5e9dfa3b8ddb4749ebf45dc0f17a | 38,406 |
def fracsimplify(numerator, denominator):
"""
Simplify a fraction.
:type numerator: integer
:param numerator: The numerator of the fraction to simplify
:type denominator: integer
:param denominator: The denominator of the fraction to simplify
:return: The simplified fraction
... | 9f1decc8d9021ea988f6eb28342da8ecc2ceb607 | 38,407 |
def polar_adjust_scale(lon, lat, s=1):
"""Rescale lon, lat by contracting or expanding from the north pole.
This is necessary to compensate for the not quite complete coverage of the projection
For the test PufferSphere, s=0.833 is a good compensation
s sets the scaling factor. """
r = (np.pi/2... | 2c294430bc62dfd06ebfcc1d5b5d81d12d08dd8e | 38,408 |
def process_jobs_output(final_df):
"""
preprocess the dataframe before creating pdf
:param final_df: final dataframe
:type final_df: pandas.DataFrame
:return: processed dataframe
"""
output_df = final_df.copy()
output_df['job_title'] = np.where(output_df['job_title'].str.len() > 30, o... | d833af76ebe05a856c567e47ef7411e116d2cae1 | 38,409 |
def _vector2xy(v, pole):
"""Return stereographic coordinates (X, Y) of 3D unit vectors.
(X, Y) is both zero for vectors with z equal to the projection pole.
Parameters
----------
v : Vector3d
If it's not a unit vector, it will be made into one.
pole : int
-1 or 1, where -1 (1) ... | c1df4ddd024ffa4d4ba457ece365f015eadfa3f8 | 38,411 |
def defer_group_class(node: c.SchemaNode, kw: dict) -> t.Type[IGroupModel]:
"""Colander helper deferred to assign the current group model.
:param node: Colander SchemaNode
:param kw: Keyword arguments.
:return: IGroupModel
"""
request = kw.get("request")
assert request, "To use this widget ... | 59c5da9d2f9c0f79125cd1fa26d242f0dc897a63 | 38,413 |
async def search_roles_count(conn, search_query):
"""Get a count of all search fields for roles in one query."""
resource = (
await roles_search_name(search_query)
.union(roles_search_description(search_query))
.distinct()
.count()
.run(conn)
)
return resource | ba43e3c38f28bb9bc10ac757e6b5d2c0cabbfbdb | 38,414 |
def get_db_engine() -> Engine:
"""
Opens a new database connection if there is none yet for the
current application context.
"""
if not hasattr(g, "dbengine"):
engine = create_engine(application.config["SQLALCHEMY_DATABASE_URI"], echo=ENV_LOG_FLAG)
engine.connect()
g.dbengine... | 844bce3fc30bc4a3c77a27934107d20d597ae793 | 38,416 |
def get_subset(container, subset_bounds):
"""Returns a subset of the given list with respect to the list of bounds"""
subset = []
for bound in subset_bounds:
subset += container[bound[0]: bound[1]]
return subset | 4932ecba987c4936f9f467f270c6c07fd8681840 | 38,417 |
def _encode_decimal128(name, value, dummy0, dummy1):
"""Encode bson.decimal128.Decimal128."""
return b"\x13" + name + value.bid | f0d72f1fdef51559eb66dd2ac65ba6a43a91bf85 | 38,418 |
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