content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import time
def acquire_lease(lease_id, client_id, ttl=DEFAULT_LOCK_DURATION_SECONDS, timeout=DEFAULT_ACQUIRE_TIMEOUT_SECONDS):
"""
Try to acquire the lease. If fails, return None, else return lease object. The timeout is crudely implemented with backoffs and retries so the timeout is not precise
:param ... | 77de69b03dab5d529872c66bc2a5648d656c829c | 3,642,000 |
def create_index(conn, column_list, table='perfdata', unique=False):
"""Creates one index on a list of/one database column/s.
"""
table = base2.filter_str(table)
index_name = u'idx_{}'.format(base2.md5sum(table + column_list))
c = conn.cursor()
if unique:
sql = u'CREATE UNIQUE INDEX IF... | 38b71cededb8500452cd3eac53609cc4ee384566 | 3,642,001 |
from typing import Type
from typing import Any
import inspect
def produce_hash(self: Type[PCell], extra: Any = None) -> str:
"""Produces a hash of a PCell instance based on:
1. the source code of the class and its bases.
2. the non-default parameter with which the pcell method is called
3. the name of... | 859f51600a9cc4da8ba546afebf0ecdf20959ec8 | 3,642,002 |
def boxes3d_kitti_fakelidar_to_lidar(boxes3d_lidar):
"""
Args:
boxes3d_fakelidar: (N, 7) [x, y, z, w, l, h, r] in old LiDAR coordinates, z is bottom center
Returns:
boxes3d_lidar: [x, y, z, dx, dy, dz, heading], (x, y, z) is the box center
"""
w, l, h, r = boxes3d_lidar[:, 3:4], bo... | 139a3da3ac8e6c09a376d976d0e96a8d91f9a74a | 3,642,003 |
def combine_per_choice(*args):
"""
Combines two or more per-choice analytics results into one.
"""
args = list(args)
result = args.pop()
new_weight = None
new_averages = None
while args:
other = args.pop()
for key in other:
if key not in result:
result[key] = other[key]
else:... | 63e482a60b521744c94d80b0b8a740ff74f4b197 | 3,642,004 |
import string
def prepare_input(dirty: str) -> str:
"""
Prepare the plaintext by up-casing it
and separating repeated letters with X's
"""
dirty = "".join([c.upper() for c in dirty if c in string.ascii_letters])
clean = ""
if len(dirty) < 2:
return dirty
for i in range(len(d... | 5c55ba770e024b459d483fd168978437b8d48c21 | 3,642,005 |
def calc_center_from_box(box_array):
"""calculate center point of boxes
Args:
box_array (array): N*4 [left_top_x, left_top_y, right_bottom_x, right_bottom_y]
Returns:
array N*2: center points array [x, y]
"""
center_array=[]
for box in box_array:
center_array.append... | 1f713a2f6900678ad1760ea60456bbf44b9f06af | 3,642,006 |
import scipy
def getW3D(coords):
"""
#################################################################
The calculation of 3-D Wiener index based
gemetrical distance matrix optimized
by MOPAC(Not including Hs)
-->W3D
#################################################################
"""
... | 25fb1596b0d818d7f7f120289a79ccbf9b4f1ae4 | 3,642,007 |
from typing import Any
from typing import Sequence
def state_vectors(
draw: Any,
max_num_qudits: int = 3,
allowed_bases: Sequence[int] = (2, 3),
min_num_qudits: int = 1,
) -> StateVector:
"""Hypothesis strategy for generating `StateVector`'s."""
num_qudits, radixes = draw(
num_qudits_a... | b81059843f94cb1c36581ac0a7dd5d3c17f39839 | 3,642,008 |
def ProcessChainsAndLigandsOptionsInfo(ChainsAndLigandsInfo, ChainsOptionName, ChainsOptionValue, LigandsOptionName = None, LigandsOptionValue = None):
"""Process specified chain and ligand IDs using command line options.
Arguments:
ChainsAndLigandsInfo (dict): A dictionary containing information
... | 0bdadbc08512957269a179df24c1202a56870d42 | 3,642,009 |
def oa_filter(x, h, N, mode=0):
"""
Overlap and add transform domain FIR filtering.
This function implements the classical overlap and add method of
transform domain filtering using a length P FIR filter.
Parameters
----------
x : input signal to be filtered as an ndarray
h : F... | 41fa7aaf7a57e0f6c363eb1efa7413b2a1a34d47 | 3,642,010 |
from typing import Optional
from typing import Iterable
import re
def get_languages(translation_dir: str, default_language: Optional[str] = None) -> Iterable[str]:
"""
Get a list of available languages.
The default language is (generic) English and will always be included. All other languages wil... | a25c9c2672f4f8d96cffc363aa922424b031aea7 | 3,642,011 |
def calculate_direction(a, b):
"""Calculates the direction vector between two points.
Args:
a (list): the position vector of point a.
b (list): the position vector of point b.
Returns:
array: The (unnormalised) direction vector between points a and b. The smallest magnitude of an e... | 9e0297560bb48d57cd4e1d5f12788a62ae7d9b3b | 3,642,012 |
def argmin(a, axis=None, out=None, keepdims=None, combine_size=None):
"""
Returns the indices of the minimum values along an axis.
Parameters
----------
a : array_like
Input tensor.
axis : int, optional
By default, the index is into the flattened tensor, otherwise
along ... | d289cf508720c5d93ef1622d3e960e9063ab5131 | 3,642,013 |
import json
def parse_game_state(gs_json: dict) -> game_state_pb2.GameState:
"""Deserialize a JSON-formatted game state to protobuf."""
if 'provider' not in gs_json:
raise InvalidGameStateException(gs_json)
try:
map_ = parse_map(gs_json.get('map'))
provider = parse_provider(gs_json['provider'])
... | d78868c24807a3cac469b87990e5a74f88876eb5 | 3,642,014 |
def state2bin(s, num_bins, limits):
"""
:param s: a state. (possibly multidimensional) ndarray, with dimension d =
dimensionality of state space.
:param num_bins: the total number of bins in the discretization
:param limits: 2 x d ndarray, where row[0] is a row vector of the lower
limit... | 8c0a1d559a332b1a015bde78c9eca413eeae942c | 3,642,015 |
def _fix_json_agents(ag_obj):
"""Fix the json representation of an agent."""
if isinstance(ag_obj, str):
logger.info("Fixing string agent: %s." % ag_obj)
ret = {'name': ag_obj, 'db_refs': {'TEXT': ag_obj}}
elif isinstance(ag_obj, list):
# Recursive for complexes and similar.
... | be73467edc1dc30ac0be1f6804cdb19cf5f942bf | 3,642,016 |
def vflip(img):
"""Vertically flip the given CV Image.
Args:
img (CV Image): Image to be flipped.
Returns:
CV Image: Vertically flipped image.
"""
if not _is_numpy_image(img):
raise TypeError('img should be CV Image. Got {}'.format(type(img)))
return cv2.flip(img, 1) | 7b678327a15876a98e0622eacc012f86a8ffd432 | 3,642,017 |
def list_pending_tasks():
"""List all pending tasks in celery cluster."""
inspector = celery_app.control.inspect()
return inspector.reserved() | 3d1785dd9ac8fd91f1f0ceb72eeb7df5671b55d5 | 3,642,018 |
def get_attack(attacker, defender):
"""
Returns a value for an attack roll.
Args:
attacker (obj): Character doing the attacking
defender (obj): Character being attacked
Returns:
attack_value (int): Attack roll value, compared against a defense value
to determine whe... | 3ec24ab34a02c2572ee62d1cc18079bdb7ef10ee | 3,642,019 |
def colored(s, color=None, attrs=None):
"""Call termcolor.colored with same arguments if this is a tty and it is available."""
if HAVE_COLOR:
return colored_impl(s, color, attrs=attrs)
return s | a8c4f56e55721ec464728fbe9af4453cd98400ba | 3,642,020 |
def _combine_by_cluster(ad, clust_key='leiden'):
"""
Given a new AnnData object, we want to create a new object
where each element isn't a cell, but rather is a cluster.
"""
clusters = []
X_mean_clust = []
for clust in sorted(set(ad.obs[clust_key])):
cells = ad.obs.loc[ad.obs[clust_k... | 2d48a9f504050604a679f35c06916c175e813ffe | 3,642,021 |
def subsample_data(features, scaled_features, labels, subsamp): # This is only for poker dataset
""" Subsample the data. """
# k is class, will iterate from class 0 to class 1
# v is fraction to sample, i.e. 0.1, sample 10% of the current class being iterated
for k, v in subsamp.items():
ix = n... | 3981fb0c793f64d52fc21cf2bbf87975bf97c786 | 3,642,022 |
def anomary_scores_ae(df_original, df_reduced):
"""AEで再生成された特徴量から異常度を計算する関数"""
"""再構成誤差を計算する異常スコア関数
Args:
df_original(array-like): training data of shape (n_samples, n_features)
df_reduced(array-like): prediction of shape (n_samples, n_features)
Returns:
pd.Series: 各データごとの異常スコア... | f6fe2dca7c10e19ee1e0a03a8d94c663ef5d77fd | 3,642,023 |
import os
def merge_runs(input_dir1, input_dir2, map_df, output, arguments):
"""
:param input_dir1: Directory 1 contains mutation counts files
:param input_dir2: Directory 2 contains mutation counts files
:param map_df: A dataframe that maps the samples to be merged
:param output: output directory... | d2e27bb99d7e6e75110a1ed9a51ab285ee2c39d2 | 3,642,024 |
import logging
def latest_res_ords():
"""Get last decade from reso and ords table"""
filename = 'documentum_scs_council_reso_ordinance_v.csv'
save_path = f"{conf['prod_data_dir']}/documentum_scs_council_reso_ordinance_v"
df = pd.read_csv(f"{conf['prod_data_dir']}/{filename}",
low_memory=False... | c23b26e878887758c6822164bcac33eb7c28f765 | 3,642,025 |
def langevin_coefficients(temperature, dt, friction, masses):
"""
Compute coefficients for langevin dynamics
Parameters
----------
temperature: float
units of Kelvin
dt: float
units of picoseconds
friction: float
collision rate in 1 / picoseconds
masses: array... | a95ba22bda908fdd10171ed63eba1dc7906c0c1f | 3,642,026 |
def get_description():
"""
Read full description from 'README.md'
:return: description
:rtype: str
"""
with open('README.md', 'r', encoding='utf-8') as f:
return f.read() | 9a73c9dbaf88977f8c96eee056f92a7d5ff938fd | 3,642,027 |
def qt_matrices(matrix_dim, selected_pp_indices=[0, 5, 10, 11, 1, 2, 3, 6, 7]):
"""
Get the elements of a special basis spanning the density-matrix space of
a qutrit.
The returned matrices are given in the standard basis of the
density matrix space. These matrices form an orthonormal basis
unde... | 8e444fae5b936f4e20f615404712c91a5bbe3f4c | 3,642,028 |
def get_signed_value(bit_vector):
"""
This function will generate the signed value for a given bit list
bit_vector : list of bits
"""
signed_value = 0
for i in sorted(bit_vector.keys()):
if i == 0:
signed_value = int(bit_vector[i])
else:
signed_... | 6b2b9a968576256738f396eeefba844561e2d2c7 | 3,642,029 |
def values_to_colors(values, cmap, vmin=None, vmax=None):
"""
Function to map a set of values through a colormap
to get RGB values in order to facilitate coloring of meshes.
Parameters
----------
values: array-like, (n_vertices, )
values to pass through colormap
cmap: array-like, (n... | d26bcf4daaeb5247a11576547cdce8417b8d4b19 | 3,642,030 |
from typing import List
import sys
def _clean_sys_argv(pipeline: str) -> List[str]:
"""Values in sys.argv that are not valid option values in Where
"""
reserved_opts = {pipeline, "label", "id", "only_for_rundate", "session", "stage", "station", "writers"}
return [o for o in sys.argv[1:] if o.startswit... | 551f4fdca5d7cc276b03943f3679cc2eff8ce89e | 3,642,031 |
def get_number_from_user_input(prompt: str, min_value: int, max_value: int) -> int:
"""gets a int integer from user input"""
# input loop
user_input = None
while user_input is None or user_input < min_value or user_input > max_value:
raw_input = input(prompt + f" ({min_value}-{max_value})? ")
... | c9df4ac604b3bf8f0f9c2a35added1f23e88048e | 3,642,032 |
def word_saliency(topic_word_distrib, doc_topic_distrib, doc_lengths):
"""
Calculate word saliency according to [Chuang2012]_ as ``saliency(w) = p(w) * distinctiveness(w)`` for a word ``w``.
.. [Chuang2012] J. Chuang, C. Manning, J. Heer. 2012. Termite: Visualization Techniques for Assessing Textual Topic
... | 47acaa848601192837eceef210389ada090b1fec | 3,642,033 |
import json
def parse_cl_items(s):
"""Take a json string of checklist items and make a dict of item objects keyed on
item name (id)"""
dispatch = {"floating":Floating,
"weekly":Weekly,
"monthly": Monthly,
"daily":Daily
}
if len(s) == 0:
... | 274374f8ad3048f7bf9f17ed7d43740a83900a63 | 3,642,034 |
def get_queue(queue, flags=FLAGS.ALL, **conn):
"""
Orchestrates all the calls required to fully fetch details about an SQS Queue:
{
"Arn": ...,
"Region": ...,
"Name": ...,
"Url": ...,
"Attributes": ...,
"Tags": ...,
"DeadLetterSourceQueues": ...,
... | b39ea959835fc3ae32042cabac4bc4f9b5f1c425 | 3,642,035 |
def mixed_float_frame():
"""
Fixture for DataFrame of different float types with index of unique strings
Columns are ['A', 'B', 'C', 'D'].
"""
df = DataFrame(tm.getSeriesData())
df.A = df.A.astype('float32')
df.B = df.B.astype('float32')
df.C = df.C.astype('float16')
df.D = df.D.ast... | aaef420666cf714c45bb87bf7e1eb484a4c06f69 | 3,642,036 |
import unittest
def create_parsetestcase(durationstring, expectation, format, altstr):
"""
Create a TestCase class for a specific test.
This allows having a separate TestCase for each test tuple from the
PARSE_TEST_CASES list, so that a failed test won't stop other tests.
"""
class TestParse... | b74dbb969743bc98e22bfd80677da7f02891391e | 3,642,037 |
import time
import traceback
def draw_data_from_db(host, port=None, pid=None, startTime=None, endTime=None, system=None, disk=None):
"""
Get data from InfluxDB, and visualize
:param host: client IP, required
:param port: port, visualize port data; optional, choose one from port, pid and system
:pa... | 73aa86b18dff59fdf88eff0b173e32fa4f3ed3ed | 3,642,038 |
def get_sample_generator(filenames, batch_size, model_config):
"""Set data loader generator according to different tasks.
Args:
filenames(list): filenames of the input data.
batch_size(int): size of the each batch.
model_config(dict): the dictionary containing model configuration.
... | 2033e081addf26a8f9074591b2f8992f39ed86c1 | 3,642,039 |
def execute_batch(table_type, bulk, count, topic_id, topic_name):
"""
Execute bulk operation. return true if operation completed successfully
False otherwise
"""
errors = False
try:
result = bulk.execute()
if result['nModified'] != count:
print(
"bulk ... | 954de6b5bfefcea7a7bfdebdc7cb7b1b1ba1dd95 | 3,642,040 |
def process_domain_assoc(url, domain_map):
"""
Replace domain name with a more fitting tag for that domain.
User defined. Mapping comes from provided config file
Mapping in yml file is as follows:
tag:
- url to map to tag
- ...
A small example domain_assoc.yml is included
"... | 29c0f81a4959d97cd91f839cbe511eb46872b5ec | 3,642,041 |
def process_auc(gt_list, pred_list):
"""
Process AUC (AUROC) over lists.
:param gt_list: Ground truth list
:type gt_list: np.array
:param pred_list: Predictions list
:type pred_list: np.array
:return: Mean AUC over the lists
:rtype: float
"""
res = []
for i, gt in enumerate(... | 2f1de3ba0d5f1154ef4a5888d01d398fd8533793 | 3,642,042 |
def transform(
Y,
transform_type=None,
dtype=np.float32):
""" Transform STFT feature
Args:
Y: STFT
(n_frames, n_bins)-shaped np.complex array
transform_type:
None, "log"
dtype: output data type
np.float32 is expected
Return... | 96613eb77c20c1a09a3e41af176a36d2ce4d8080 | 3,642,043 |
def tol_vif_table(df, n = 5):
"""
:param df: dataframe
:param n: number of pairs to show
:return: table of correlations, tolerances, and VIF
"""
cor = get_top_abs_correlations(df, n)
tol = 1 - cor ** 2
vif = 1 / tol
cor_table = pd.concat([cor, tol, vif], axis=1)
cor_table.column... | 94cf5715951892375e92ada019476b9ae3d09577 | 3,642,044 |
import random
def shuffled(iterable):
"""Randomly shuffle a copy of iterable."""
items = list(iterable)
random.shuffle(items)
return items | cd554d4a31e042dc1d2b4c7b246528a5184d558e | 3,642,045 |
from ray.autoscaler._private.constants import RAY_PROCESSES
from typing import Optional
from typing import List
from typing import Tuple
import psutil
import subprocess
import tempfile
import yaml
def get_local_ray_processes(archive: Archive,
processes: Optional[List[Tuple[str, bool]]] = N... | 7ed76d4e93198ce0afef0fbf5cf5b37a7b92e0ed | 3,642,046 |
def test_rule(rule_d, ipv6=False):
""" Return True if the rule is a well-formed dictionary, False otherwise """
try:
_encode_iptc_rule(rule_d, ipv6=ipv6)
return True
except:
return False | 7435cb900117e4c273b4157b2f25ba56aefd1355 | 3,642,047 |
def intersects(hp, sphere):
"""
The closed, upper halfspace intersects the sphere
(i.e. there exists a spatial relation between the two)
"""
return signed_distance(sphere.center, hp) + sphere.radius >= 0.0 | 9366824f03a269d0fa9e96f34260c621ad610d16 | 3,642,048 |
def invert_center_scale(X_cs, X_center, X_scale):
"""
This function inverts whatever centering and scaling was done by
``center_scale`` function:
.. math::
\mathbf{X} = \mathbf{X_{cs}} \\cdot \mathbf{D} + \mathbf{C}
**Example:**
.. code:: python
from PCAfold import center_sc... | e37d82e7da932ea760981bb5a472799cd5a4d3d9 | 3,642,049 |
def weighted_smoothing(image, diffusion_weight=1e-4, data_weight=1.0,
weight_function_parameters={}):
"""Weighted smoothing of images: smooth regions, preserve sharp edges.
Parameters
----------
image : NumPy array
diffusion_weight : float or NumPy array, optional
The... | 3c861b9a8878f2d85d581d8f8d1f62cf017a7920 | 3,642,050 |
import random
def get_random_tablature(tablature : Tablature, constants : Constants):
"""make a copy of the tablature under inspection and generate new random tablatures"""
new_tab = deepcopy(tablature)
for tab_instance, new_tab_instance in zip(tablature.tablature, new_tab.tablature):
if tab_insta... | befa3a488e2ca53e37032ed102a12b250594bd90 | 3,642,051 |
def _staticfy(value):
"""
Allows to keep backward compatibility with instances of OpenWISP which
were using the previous implementation of OPENWISP_ADMIN_THEME_LINKS
and OPENWISP_ADMIN_THEME_JS which didn't automatically pre-process
those lists of static files with django.templatetags.static.static(... | 2ac932a178a86d301dbb15602f3b59edb39cf3c1 | 3,642,052 |
def compare_rep(topic, replication_factor):
# type: (str, int) -> bool
"""Compare replication-factor in the playbook with the one actually set.
Keyword arguments:
topic -- topicname
replication_factor -- number of replications
Return:
bool -- True if change is needed, else False
"""
... | 882b028d078e507f9673e3ead6549da100a83226 | 3,642,053 |
def verbosity_option_parser() -> ArgumentParser:
"""
Creates a parser suitable to parse the verbosity option in different subparsers
"""
parser = ArgumentParser(add_help=False)
parser.add_argument('--verbosity', dest=VERBOSITY_ARGNAME, type=str.upper,
choices=ALLOWED_VERBOSIT... | c24f0704f1632cc0af416cf2c0a3e65c6845566f | 3,642,054 |
import snappi
def b2b_config(api):
"""Demonstrates creating a back to back configuration of tx and rx
ports, devices and a single flow using those ports as endpoints for
transmit and receive.
"""
config = api.config()
config = snappi.Api().config()
config.options.port_options.location_pre... | 60a838885c058f5c65d3b331082f525b2e04b5c7 | 3,642,055 |
import os
def apply_patch(ffrom, fpatch, fto):
"""Apply given normal patch `fpatch` to `ffrom` to create
`fto`. Returns the size of the created to-data.
All arguments are file-like objects.
>>> ffrom = open('foo.mem', 'rb')
>>> fpatch = open('foo.patch', 'rb')
>>> fto = open('foo.new', 'wb')... | b847f7641bdd34c935d2f88fd8ca114abb0b4033 | 3,642,056 |
def fib(n):
"""Return the n'th Fibonacci number."""
if n < 0:
raise ValueError("Fibonacci number are only defined for n >= 0")
return _fib(n) | 4aee5fbb4c9a497ffc4f63529b226ad3b08c0ef4 | 3,642,057 |
def gen(n):
"""
Compute the n-th generator polynomial.
That is, compute (x + 2 ** 1) * (x + 2 ** 2) * ... * (x + 2 ** n).
"""
p = Poly([GF(1)])
two = GF(1)
for i in range(1, n + 1):
two *= GF(2)
p *= Poly([two, GF(1)])
return p | 29e6b1f164d93b21a2d98352ff60c8cf7a8d5864 | 3,642,058 |
def get_prefix(bot, message):
"""A callable Prefix for our bot. This could be edited to allow per server prefixes."""
# Notice how you can use spaces in prefixes. Try to keep them simple though.
prefixes = ['!']
# If we are in a guild, we allow for the user to mention us or use any of the prefixes in ... | 35567d49b747f51961fad861e00d9f9524126641 | 3,642,059 |
def parse_discontinuous_phrase(phrase: str) -> str:
"""
Transform discontinuous phrase into a regular expression. Discontinuity is
interpreted as taking place at any whitespace outside of terms grouped by
parentheses. That is, the whitespace indicates that anything can be in between
the left side an... | 58fe394a08931e7e79afc00b9bb0e8e9981f3c81 | 3,642,060 |
def preprocess(frame):
"""
Preprocess the images before they are sent into the model
"""
#Read the image
bgr_img = frame.astype(np.float32)
#Opencv reads the picture as (N) HWC to get the HW value
orig_shape = bgr_img.shape[:2]
#Normalize the picture
bgr_img = bgr_img / 255.0
#Co... | 33a24a31ae9e25efb080037a807897f2762656c0 | 3,642,061 |
def draw_roc_curve(y_true, y_score, annot=True, name=None, ax=None):
"""Draws a ROC (Receiver Operating Characteristic) curve using class rankings predicted by a classifier.
Args:
y_true (array-like): True class labels (0: negative; 1: positive)
y_score (array-like): Predicted probability o... | cf59a02c5f72f728b0d9179a4eee3f012da564df | 3,642,062 |
def make_links_absolute(soup, base_url):
"""
Replace relative links with absolute links.
This one modifies the soup object.
"""
assert base_url is not None
#
for tag in soup.findAll('a', href=True):
tag['href'] = urljoin(base_url, tag['href'])
return soup | 52d328c944d4a80b4f0a027a3b72f2fcebc152a9 | 3,642,063 |
def get_predictions(model, dataloader):
"""takes a trained model and validation or test dataloader
and applies the model on the data producing predictions
binary version
"""
model.eval()
all_y_hats = []
all_preds = []
all_true = []
all_attention = []
for batch_id, (data, label... | f58a5863c211a24665db7348606d39232ad8af19 | 3,642,064 |
def _getPymelType(arg, name) :
""" Get the correct Pymel Type for an object that can be a MObject, PyNode or name of an existing Maya object,
if no correct type is found returns DependNode by default.
If the name of an existing object is passed, the name and MObject will be returned
If a va... | b303bebfc5c97ac6a969c151cb78de7f28523476 | 3,642,065 |
def _parse_objective(objective):
"""
Modified from deephyper/nas/run/util.py function compute_objective
"""
if isinstance(objective, str):
negate = (objective[0] == '-')
if negate:
objective = objective[1:]
split_objective = objective.split('__')
kind = split... | df8f23464cd04be9a3c61a2969200a0c98c4471e | 3,642,066 |
def redirect_path_context_processor(request):
"""Procesador para generar el redirect_to para la localización en el selector de idiomas"""
return {'language_select_redirect_to': translate_url(request.path, settings.LANGUAGE_CODE)} | fdb62f3079079d63c280d2b887468c7893aafcf8 | 3,642,067 |
def RightCenter(cell=None):
"""Take up horizontal and vertical space, and place the cell on the right center of it."""
return FillSpace(cell, "right", "center") | ce64a346658813ab281168864e357cec1ba09c0b | 3,642,068 |
def name_standard(name):
""" return the Standard version of the input word
:param name: the name that should be standard
:return name: the standard form of word
"""
reponse_name = name[0].upper() + name[1:].lower()
return reponse_name | 65273cafaaa9aceb803877c2071dc043a0d598eb | 3,642,069 |
def getChildElementsListWithTagAttribValueMatch(parent, tag, attrib, value):
"""
This method takes a parent element as input and finds all the sub elements (children)
containing specified tag and an attribute with the specified value.
Returns a list of child elements.
Arguments:
parent = paren... | cae87e6548190ad0a675019b397eeb88289533ee | 3,642,070 |
def f_engine (air_volume, energy_MJ):
"""Прямоточный воздушно реактивный двигатель.
Набегающий поток воздуха попадает в нагреватель, где расширяется,
А затем выбрасывается из сопла реактивной струёй.
"""
# Рабочее вещество, это атмосферный воздух:
working_mass = air_volume * AIR_DENSITY
... | 3d307622fca17f16f03e49bd7f8b5b742217ee37 | 3,642,071 |
def not_numbers():
"""Non-numbers for (i)count."""
return [None, [1, 2], {-3, 4}, (6, 9.7)] | 31f935916c8463f6192d0b2770c1034ee70a4fc5 | 3,642,072 |
import requests
def get_agol_token():
"""requests and returns an ArcGIS Token for the pre-registered application.
Client id and secrets are managed through the ArcGIS Developer's console.
"""
params = {
'client_id': app.config['ESRI_APP_CLIENT_ID'],
'client_secret': app.config['ESRI_AP... | 7b240ef57264c1a88f10f4c06c9492a71dac8c11 | 3,642,073 |
def default_validate(social_account):
"""
Функция по-умолчанию для ONESOCIAL_VALIDATE_FUNC. Ничего не делает.
"""
return None | 634382dbfe64eeed38225f8dca7e16105c40f7c2 | 3,642,074 |
import requests
def pull_early_late_by_stop(line_number,SWIFTLY_API_KEY, dateRange, timeRange):
"""
Pulls from the Swiftly APIS to get OTP.
Follow the docs: http://dashboard.goswift.ly/vta/api-guide/docs/otp
"""
line_table = pd.read_csv('line_table.csv')
line_table.rename(columns={"DirNum":"di... | a64ad2e5fe84ee5ab5a49c8122f28b693382cf8e | 3,642,075 |
def create_build_job(user, project, config, code_reference):
"""Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
If the image does not exists, and the job is already done we force create a new job.
Returns:
t... | 879ed02f142326b4a793bef2d8bcbc1de4faf64c | 3,642,076 |
import json
def create(ranger_client: RangerClient, config: str):
"""
Creates a new Apache Ranger service repository.
"""
return ranger_client.create_service(json.loads(config)) | a53fa80f94960f89410a60aae04a04417491f332 | 3,642,077 |
def populate_glue_catalogue_from_metadata(table_metadata, db_metadata, check_existence = True):
"""
Take metadata and make requisite calls to AWS API using boto3
"""
database_name = db_metadata["name"]
database_description = ["description"]
table_name = table_metadata["table_name"]
tbl_de... | c09af0344b523213010af8fdbcc0ed35328f165e | 3,642,078 |
def choose_komoot_tour_live():
"""
Login with user credentials, download tour information,
choose a tour, and download it. Can be passed to
:func:`komoog.gpx.convert_tour_to_gpx_tracks`
afterwards.
"""
tours, session = get_tours_and_session()
for idx in range(len(tours)):
print... | 3be625643d6861c9aaff910506dce53e3f336e40 | 3,642,079 |
def root():
"""
The root stac page links to each collection (product) catalog
"""
return _stac_response(
dict(
**stac_endpoint_information(),
links=[
dict(
title="Collections",
description="All product collections",
... | 0904122654a1ce71264489590a2a1813dad31689 | 3,642,080 |
def recursive_dict_of_lists(d, helper=None, prev_key=None):
"""
Builds dictionary of lists by recursively traversing a JSON-like
structure.
Arguments:
d (dict): JSON-like dictionary.
prev_key (str): Prefix used to create dictionary keys like: prefix_key.
Passed by recursive ... | c615582febbd043adae6788585d004aabf1ac7e3 | 3,642,081 |
def same_shape(shape1, shape2):
"""
Checks if two shapes are the same
Parameters
----------
shape1 : tuple
First shape
shape2 : tuple
Second shape
Returns
-------
flag : bool
True if both shapes are the same (same length and dimensions)
"""
if len(shap... | 9452f7973e510532cee587f2bf49a146fb8cc46e | 3,642,082 |
def get_reference():
"""Get DrugBank references."""
return _get_model(drugbank.Reference) | b4d26c24559883253f3894a1c56151e1809e4050 | 3,642,083 |
import collections
def __parse_search_results(collected_results, raise_exception_finally):
"""
Parses locally the results collected from the __mapped_pattern_matching:
- list of ( scores, matched_intervals, unprocessed_interval,
rank_superwindow, <meta info>, <error_info>)
Th... | 5e7bad5a745d76b6d0a9b45a3c36df846051c1bc | 3,642,084 |
def decode_matrix_fbs(fbs):
"""
Given an FBS-encoded Matrix, return a Pandas DataFrame the contains the data and indices.
"""
matrix = Matrix.Matrix.GetRootAsMatrix(fbs, 0)
n_rows = matrix.NRows()
n_cols = matrix.NCols()
if n_rows == 0 or n_cols == 0:
return pd.DataFrame()
if m... | d3ffdd5f0d74a6e07b47fac175dae4ad6035cda8 | 3,642,085 |
async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool:
"""Track states and offer events for sensors."""
component = hass.data[DOMAIN] = EntityComponent(
_LOGGER, DOMAIN, hass, SCAN_INTERVAL
)
await component.async_setup(config)
return True | eaeee6df6c8b632fb331884236f7b3b47d551683 | 3,642,086 |
def _all_lists_equal_lenght(values: t.List[t.List[str]]) -> bool:
"""
Tests to see if all the lengths of all the elements are the same
"""
for vn in values:
if len(values[0]) != len(vn):
return False
return True | 9fd7db874658822d7a48d5f27340e0dfd5a2d177 | 3,642,087 |
def wind_shear(
shear: str, unit_alt: str = "ft", unit_wind: str = "kt", spoken: bool = False
) -> str:
"""Translate wind shear into a readable string
Ex: Wind shear 2000ft from 140 at 30kt
"""
if not shear or "WS" not in shear or "/" not in shear:
return ""
shear = shear[2:].rstrip(uni... | b7aaf5253e251393a508de2d8080a5b3458c45f6 | 3,642,088 |
def root_hash(hashes):
"""
Compute the root hash of a merkle tree with the given list of leaf hashes
"""
# the number of hashes must be a power of two
assert len(hashes) & (len(hashes) - 1) == 0
while len(hashes) > 1:
hashes = [sha256(l + r).digest() for l, r in zip(*[iter(hashes)] * 2)]... | 9036414c71e192a62968a9939d56f9523359c877 | 3,642,089 |
import json
def DumpStr(obj, pretty=False, newline=None, **json_dumps_kwargs):
"""Serialize a Python object to a JSON string.
Args:
obj: a Python object to be serialized.
pretty: True to output in human-friendly pretty format.
newline: True to append a newline in the end of result, default to the
... | 97ed8c722d8d9e545f29214fbc8a817e6cf4ca1a | 3,642,090 |
def snake_case(s: str):
"""
Transform into a lower case string with underscores between words.
Parameters
----------
s : str
Original string to transform.
Returns
-------
Transformed string.
"""
return _change_case(s, '_', str.lower) | c4dc65445e424101b3b5264c2f14e0aa0d7bcd22 | 3,642,091 |
def multiple_workers_thread(worker_fn, queue_capacity_input=1000, queue_capacity_output=1000, n_worker=3):
"""
:param worker_fn: lambda (tid, queue): pass
:param queue_capacity:
:param n_worker:
:return:
"""
threads = []
queue_input = Queue.Queue(queue_capacity_input)
queue_output = ... | b9a989404b6f7e3aa6b028af5e55719364c62fd8 | 3,642,092 |
from typing import List
from typing import Any
def reorder(list_1: List[Any]) -> List[Any]:
"""This function takes a list and returns it in sorted order"""
new_list: list = []
for ele in list_1:
new_list.append(ele)
temp = new_list.index(ele)
while temp > 0:
if new_li... | 2e7dad8fa138b1a9a140deab4223eea4a09cdf91 | 3,642,093 |
def is_extended_markdown(view):
"""True if the view contains 'Markdown Extended'
syntax'ed text.
"""
return view.settings().get("syntax").endswith(
"Markdown Extended.sublime-syntax") | 5c870fd277910f6fa48f2b8ae0dfd304fdbddff0 | 3,642,094 |
from typing import Dict
from typing import List
from typing import Any
import random
import logging
def _generate_graph(rule_dict: Dict[int, List[PartRule]], upper_bound: int) -> Any:
"""
Create a new graph from the VRG at random
Returns None if the nodes in generated graph exceeds upper_bound
:return... | 8bcc3c93c0ff7f1f895f3970b9aa16c7f6293e68 | 3,642,095 |
def match_command_to_alias(command, aliases, match_multiple=False):
"""
Match the text against an action and return the action reference.
"""
results = []
for alias in aliases:
formats = list_format_strings_from_aliases([alias], match_multiple)
for format_ in formats:
tr... | 74712b70cb5995c30c7948991d60954732e4bc16 | 3,642,096 |
def dan_acf(x, axis=0, fast=False):
"""
DFM's acf function
Estimate the autocorrelation function of a time series using the FFT.
:param x:
The time series. If multidimensional, set the time axis using the
``axis`` keyword argument and the function will be computed for every
other... | ec258af743184c09e1962f1445ec6971b4d0cfab | 3,642,097 |
import re
def set_selenium_local_session(proxy_address,
proxy_port,
proxy_username,
proxy_password,
proxy_chrome_extension,
headless_browser,
... | 4f70baeea220c8e4e21097a5a9d9d54a47f55c2e | 3,642,098 |
def match():
"""Show a timer of the match length and an upload button"""
player_west = request.form['player_west']
player_east = request.form['player_east']
start_time = dt.datetime.now().strftime('%Y%m%d%H%M')
# generate filename to save video to
filename = '{}_vs_{}_{}.h264'.format(playe... | 7d2e51ddfaafdff903a31b5662093ab423d8f3a1 | 3,642,099 |
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