content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import urllib
def getEntries(person):
""" Fetch a Advogato member's diary and return a dictionary in the form
{ date : entry, ... }
"""
parser = DiaryParser()
f = urllib.urlopen("http://www.advogato.org/person/%s/diary.xml" % urllib.quote(person))
s = f.read(8192)
while s:
... | 9ed0b46aa694201817fd4c341a992c81d809abf5 | 25,051 |
def sum_values(p, K):
"""
sum the values in ``p``
"""
nv = []
for v in itervalues(p):
nv = dup_add(nv, v, K)
nv.reverse()
return nv | c92ac3492f0aa750879f899dde145918d4a9616d | 25,052 |
def define_permit_price_targeting_constraints(m):
"""Constraints used to get the absolute difference between the permit price and some target"""
# Constraints to minimise difference between permit price and target
m.C_PERMIT_PRICE_TARGET_CONSTRAINT_1 = pyo.Constraint(
expr=m.V_DUMMY_PERMIT_PRICE_TA... | eb31f63963e0a66491e31d3f4f8f816e21c47de9 | 25,053 |
def predict4():
"""Use Xception to label image"""
path = 'static/Images/boxer.jpeg'
img = image.load_img(path,target_size=(299,299))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
preds = model.predict(x)
pclass = decode_predictions(preds, top=5)
... | 033fcde3cb670b8a66b430451f6b341ae2e7b980 | 25,054 |
def augment_data(image, label, seg_label, perform_random_flip_and_rotate,
num_channels, has_seg_labels):
"""
Image augmentation for training. Applies the following operations:
- Horizontally flip the image with probabiliy 0.5
- Vertically flip the image with probability 0.5
... | c243ae36a1d38cd36131bbd2f51347d2d29ca9ff | 25,055 |
def protobuf_open_channel(channel_name, media_type):
"""func"""
open_channel_request = pb.OpenChannelRequest()
open_channel_request.channel_name = channel_name
open_channel_request.content_type = media_type
return open_channel_request.SerializeToString() | 0d665788cbc37d8a15c276c41d2c28e5c12ee2ea | 25,056 |
def action(update, context):
"""A fun command to send bot actions (typing, record audio, upload photo, etc). Action appears at top of main chat.
Done using the /action command."""
bot = context.bot
user_id = update.message.from_user.id
username = update.message.from_user.name
admin = _admin(use... | 5df8260a8787293187bba86712bf07505f915f39 | 25,057 |
def borehole_vec(x, theta):
"""Given x and theta, return vector of values."""
(Hu, Ld_Kw, Treff, powparam) = np.split(theta, theta.shape[1], axis=1)
(rw, Hl) = np.split(x[:, :-1], 2, axis=1)
numer = 2 * np.pi * (Hu - Hl)
denom1 = 2 * Ld_Kw / rw ** 2
denom2 = Treff
f = ((numer / ((deno... | 15f39f80d7ead4bb807dbb5c365acb900bbf405d | 25,059 |
import requests
import json
def read_datastore(resource_id):
"""
Retrieves data when the resource is part of the CKAN DataStore.
Parameters
----------
resource_id: str
Id for resource
Returns
----------
pd.DataFrame:
Data records in table format
"""
r = reque... | 80ff1b26960e7d33b0a68d286769736617353881 | 25,060 |
import hashlib
import binascii
def new_server_session(keys, pin):
"""Create SRP server session."""
context = SRPContext(
"Pair-Setup",
str(pin),
prime=constants.PRIME_3072,
generator=constants.PRIME_3072_GEN,
hash_func=hashlib.sha512,
bits_salt=128,
bits... | 5c3c20269dce31b4f7132d123845d7a46354373f | 25,061 |
def lenzi(df):
"""Check if a pandas series is empty"""
return len(df.index) == 0 | 561705e6ff0da3bfb03407a721f2aff71a4d42a1 | 25,062 |
def m_step(counts, item_classes, psuedo_count):
"""
Get estimates for the prior class probabilities (p_j) and the error
rates (pi_jkl) using MLE with current estimates of true item classes
See equations 2.3 and 2.4 in Dawid-Skene (1979)
Input:
counts: Array of how many times each rating was giv... | 00d93803dd7f3f56af47f8fb455613d223fe0a89 | 25,063 |
from typing import Callable
def make_parser(fn: Callable[[], Parser]) -> Parser:
"""
Make typed parser (required for mypy).
"""
return generate(fn) | 491888a666718d84447ff9de1b215a9e9c0f8ff0 | 25,064 |
def mfcc_htk(y, sr, hop_length=2**10, window_length=22050, nmfcc=13, n_mels=26, fmax=8000, lifterexp=22):
"""
Get MFCCs 'the HTK way' with the help of Essentia
https://github.com/MTG/essentia/blob/master/src/examples/tutorial/example_mfcc_the_htk_way.py
Using all of the default parameters from there exc... | e3beb95a027e963549df6a164b0d99345137540b | 25,065 |
def num_to_int(num):
"""
Checks that a numerical value (e.g. returned by robot) is an integer and
not a float.
Parameters
----------
num : number to check
Returns
-------
integer : num cast to an integer
Raises
------
ValueError : if n is not an integer
"""
if ... | af470940eb035fe8dd0160dfe9614c2b6d060194 | 25,066 |
def shuffle_blocks(wmx_orig, pop_size=800):
"""
Shuffles pop_size*pop_size blocks within the martrix
:param wmx_orig: original weight matrix
:param pop_size: size of the blocks kept together
:return: wmx_modified: modified weight matrix
"""
assert nPCs % pop_size == 0
np.random.seed(123... | aec38fe296b877ab79932aa675c5d04820e391af | 25,067 |
def change():
"""
Change language
"""
lang = request.args.get("lang", None)
my_id = None
if hasattr(g, 'my') and g.my:
my_id = g.my['_id']
data = core.languages.change(lang=lang, my_id=my_id)
return jsonify(data) | a5186669db31b533e1ca9bc146b11d577be4f845 | 25,068 |
import shutil
def make_pkg(pkgname, context):
"""Create a new extension package.
:param pkgname: Name of the package to create.
:param context: Mapping with keys that match the placeholders in the
templates.
:return: True if package creation succeeded or a tuple with False and a... | 6e2be6e991e2061a7b07e5e44a3479dbf0c2f1b1 | 25,069 |
def view_explorer_node(node_hash: str):
"""Build and send an induction query around the given node."""
node = manager.get_node_by_hash_or_404(node_hash)
query = manager.build_query_from_node(node)
return redirect_to_view_explorer_query(query) | 3534d546ba540dcfc6db1110c0a4a1086515dc3d | 25,070 |
import math
def encode_into_any_base(number, base, encoded_num):
"""Encode number into any base 2-36. Can be fractional or whole.
Parameters:
number: float -- integer representation of number (in base 10)
base: int -- base to convert to
encoded_num: str -- representation (so far) of n... | f6dd94e173a3844dc6d858d1c6b360354624d3f1 | 25,071 |
def handle_forbidden(error: Forbidden) -> Response:
"""Render the base 403 error page."""
return respond(error.description, status=HTTPStatus.FORBIDDEN) | 89c59dd66ce63ceef9e60cf8beea0da7895a0394 | 25,072 |
def format_timedelta(tdelta):
"""Return the timedelta as a 'HH:mm:ss' string."""
total_seconds = int(tdelta.total_seconds())
hours, remainder = divmod(total_seconds, 60*60)
minutes, seconds = divmod(remainder, 60)
return "{0:02d}:{1:02d}:{2:02d}".format(hours, minutes, seconds) | 852902e7972bcd13df8b60864ebcb2d75b2b259d | 25,074 |
def video_data_to_df(videos_entries, save_csv):
"""
Creating a dataframe from the video data stored as tuples
:param videos_entries: (list) list of tuples containing topics, subtopics, videos and durations
:param save_csv: (boolean) condition to specify if the df is saved locally as a csv file
:ret... | 11bb3d9293aa3689286cde76aea8bfff72594639 | 25,075 |
def create_mysql_entitySet(username, databaseName):
""" Create a new entity set in the databaseName """
password = get_password(username)
entitySetName = request.json['entitySetName']
attributes = request.json['attributes']
addToSchema(request.get_json(),"mysql")
pks = []
sql = "CREATE TABLE... | 00510e850d4c10f24defe7af070c652d3b390b5c | 25,076 |
def m6(X, Y, Xp, Yp, alpha=1.0, prev='ident', post='ident', **kwargs):
"""Computes a matrix with the values of applying the kernel
:math:`m_4` between each pair of elements in :math:`X` and :math:`Y`.
Args:
X: Numpy matrix.
Y: Numpy matrix.
Xp: Numpy matrix with the probabilities of... | 94d1651500ec9177a14a2c8ad80abc6ca7c3948b | 25,077 |
import time
import json
from unittest.mock import call
def serve_communications_and_statuses(erpnext_support_user, erpnext_support_issues, bench_site):
"""
returns a dict of support issue communications and statuses
response = {
"issue_name_1": {
"communications": [],
"status": "status",
"last_syn... | ceaeeb5a1f5cbe956aeaef681b5e37c3d4ed58d2 | 25,078 |
def answer_view(answerid):
"""route to view a specific answer"""
return jsonify({"answer":"Your updated answer: {} ".format(user_answers[answerid])}) | 82c7697bfe601b54dcb1fd9c8667565886a09c34 | 25,079 |
def jwk_factory(acct_priv_key_path: str) -> _JWKBase:
"""generate jwk object according private key file"""
with open(acct_priv_key_path, 'rb') as f:
acct_priv = serialization.load_pem_private_key(
data=f.read(),
password=None,
backend=default_backend()
)
... | fc08dd7294ddb067534c05a7e13b26e053ac3c42 | 25,080 |
from pathlib import Path
def execute(
scan_definition: str | Path,
df: DataFrame,
*,
soda_server_client: SodaServerClient | None = None,
) -> ScanResult:
"""
Execute a scan on a data frame.
Parameters
----------
scan_definition : Union[str, Path]
The path to a scan file or... | 7bf0bedfb8865de117565110be4225b502e2fed2 | 25,081 |
def jaccard_similarity(emb1: np.ndarray, emb2: np.ndarray) -> float:
""" 计算特征向量的Jaccard系数
:param emb1: shape = [feature,]
:param emb2: shape = [feature,]
:return: Jaccard 系数
"""
up = np.double(np.bitwise_and((emb1 != emb2), np.bitwise_or(emb1 != 0, emb2 != 0)).sum())
down = np.double(np.bit... | 18e95d7f14ca093892770364fc5af75b95bebe2a | 25,082 |
from typing import Tuple
from typing import Dict
from typing import List
def _share_secret_int_indices(s_i: int, n: int, t: int) -> Tuple[Dict[int, int], List[PointG1]]:
""" Computes n shares of a given secret such that at least t + 1 shares are required for recovery
of the secret. Additionally returns t... | b822bd79337be741bbd626751f9d745b4b9e23fc | 25,083 |
def auto_type(key, redis=None, default=None, o=True):
"""Returns datatype instance"""
if redis is None:
redis = config.redis
key = compress_key(key)
if redis.exists(key):
datatype = redis.type(key)
if datatype == 'string':
test_string = RedisString(key, redis=red... | 3d1751c14c4b0c04d11ab265395dce94822558d8 | 25,084 |
from pathlib import Path
def get_user_data_dir(app_name=DEFAULT_APP_NAME, auto_create=True) -> Path:
"""
Get platform specific data folder
"""
return _get_user_dir(
app_name=app_name,
xdg_env_var='XDG_DATA_HOME', win_env_var='APPDATA',
fallback='~/.local/share', win_fallback='~... | 321b885983affcc5cf4d4baf0410ae9ad6b6f443 | 25,085 |
import copy
import numpy
def calculateDominantFrequency(signal, fs, fMin = 0, fMax = None, applyWindow = True,
fftZeroPaddingFactor = 1
):
"""
calculates the dominant frequency of the given signal
@param signal input signal
@param fs sampling frequency
@param fMin the minimum frequency [Hz] that should be con... | ab5f2818d309202f57230197c87c54b67a0f849c | 25,087 |
def check_title(file_path):
"""
return 'has title' if found
no title, None, if not found
file_path is full path with file name and extension
"""
#print('is text file: ', tool.is_utf8_text_file(file_path))
if tool.is_utf8_text_file(file_path):
with open(file_path, 'r') as f:
... | 4559772c1e50e807935c6112cfa6001a857b9dc4 | 25,088 |
from typing import Tuple
import torch
def permute_adjacency_twin(t1,t2) -> Tuple[torch.Tensor,torch.Tensor]:
"""
Makes a permutation of two adjacency matrices together. Equivalent to a renaming of the nodes.
Supposes shape (n,n)
"""
n,_ = t1.shape
perm = torch.randperm(n)
return t1[perm,:]... | df3dc6507b8eae9d148ec9b2e664a427813d93a7 | 25,089 |
from collections import defaultdict,deque
def rad_extract(eventfiles,center,radius_function,return_cols=['PULSE_PHASE'],cuts=None,apply_GTI=True,theta_cut=66.4,zenith_cut=105,return_indices=False):
""" Extract events with a radial cut.
Return specified columns and perform additional boolean cuts.
... | bb0a5f96764c0a1edec1f408f283a2473ed630bf | 25,090 |
import re
def list_to_exp(str_list, term_padding_exp=r'\b', compile=True):
"""
Returns a regular expression (compiled or not) that will catch any of the strings of the str_list.
Each string of the str_list will be surrounded by term_padding_exp (default r'\b' forces full word matches).
Note: Also orde... | f9a1d7002a36f0348179b9997c5dec672455f077 | 25,092 |
def prepare_ddp_loader(loader: DataLoader, num_processes: int, process_index: int) -> DataLoader:
"""
Transfers loader to distributed mode. Experimental feature.
Args:
loader: pytorch dataloder
num_processes (:obj:`int`, `optional`, defaults to 1):
The number of processes runnin... | 4f57b1888fdf43fcb910d802faee8ba997ee095f | 25,093 |
import logging
def __validate_exchange(value: str) -> str:
"""
Check to see if passed string is in the list of possible Exchanges.
:param value: Exchange name.
:return: Passed value or No Return
"""
valid_values = EXCHANGE_VALUES
if value in valid_values:
return value
else:
... | 001472e1485da0fc410dceafa67b78fe5dfe1058 | 25,094 |
def main(content, title="", classes=[]):
"""Generate a 'Material for MkDocs' admonition.
"""
md = markdown.markdown(content)
return '<div class="admonition {0}">\n'.format(" ".join(classes)) + \
' <p class="admonition-title">{0}</p>\n'.format(title) + \
' <p>{0}</p>\n'.format... | e29942de52b73d8652a54c64dd22c8bac6e8496c | 25,095 |
def get_bprop_matrix_set_diag(self):
"""Generate bprop for MatrixSetDiag"""
get_dtype = P.DType()
def bprop(x, y, z, out, dout):
input_shape = F.shape(x)
batch_shape = input_shape[:-2]
matrix_shape = input_shape[-2:]
diag_shape = batch_shape + (_get_min(matrix_shape),)
... | c35f69a957b30bcefeba858e7e9bd4ee9e4591b8 | 25,096 |
from yt import load_particles
def fake_sph_grid_ds(hsml_factor=1.0):
"""Returns an in-memory SPH dataset useful for testing
This dataset should have 27 particles with the particles arranged uniformly
on a 3D grid. The bottom left corner is (0.5,0.5,0.5) and the top right
corner is (2.5,2.5,2.5). All ... | 9f32616d325fde7941cbcea814b3133fbcc988e5 | 25,097 |
async def _async_get_image_sessions(device: Device) -> dict[str, ImageSession]:
"""Return image events for the device."""
events = await device.event_media_manager.async_image_sessions()
return {e.event_token: e for e in events} | 4406abc1ac08d39bb0127be1d02f5c664c167e04 | 25,098 |
def make_element_weight_parser(weight_column):
""" Parameterize with the column - this allows us
to generate data from different analysis result types.
"""
def parse_element_weight(csv_row):
name = csv_row[0]
weight = float(csv_row[weight_column]) # Assert not zero?
return name, weight
return parse_element... | ddc3a4f82ecd0fe4833683759b1a1c4296839a54 | 25,099 |
def jitterer(out, z):
"""This function jitters the x axis
1: matrix of layer activations of the form:
2. which layer number to do
outputs a transposed matrix of no of neurons rows and no of data columns"""
Jx=np.ones(out[z].T.shape)
for i in range(out[z].T.shape[0]):
'this is the number... | 65b1337e42dab802a0c91bc27d93249171569281 | 25,100 |
from typing import Tuple
def deconstruct_full_path(filename: str) -> Tuple[str, str]:
"""
Returns a tuple with the parent folder of the file and the file's name.
Parameters
----------
filename : str
The path (with filename) that will be deconstructed.
Returns
-------
Tupl... | d33a8fc71beb39d56dc0aa9bf94264164e8bf1a9 | 25,101 |
def bbx_to_world(cords, vehicle):
"""
Convert bounding box coordinate at vehicle reference to world reference.
Parameters
----------
cords : np.ndarray
Bounding box coordinates with 8 vertices, shape (8, 4)
vehicle : opencda object
Opencda ObstacleVehicle.
Returns
-----... | 3d7438beccca9635fc15b266d2e8ada6bbc053c7 | 25,102 |
def load_data():
""" Loading data and padding """
training_set, testing_set = imdb.load_data(num_words = 10000)
x_train, y_train = training_set
x_test, y_test = testing_set
x_train_padded = sequence.pad_sequences(x_train, maxlen = 100)
x_test_padded = sequence.pad_sequences(x_test, maxlen = 100)... | ca52118f7038a70386e9ca552faf24dac6be9faf | 25,103 |
def rotate_to_calibrated_axis(
data: np.ndarray, ref_val_0: complex, ref_val_1: complex
) -> np.ndarray:
"""
Rotates, normalizes and offsets complex valued data based on calibration points.
Parameters
----------
data
An array of complex valued data points.
ref_val_0
The refe... | 82adf83c9565ec56ae6f13e1eec15c1be90f5dc4 | 25,104 |
from typing import Optional
from typing import Tuple
from typing import List
def filter_graph_data(df: pd.DataFrame, x_col: str, x_range: Optional[Tuple[int, int]], file_cols: List[str],
file_tuple: FileTuple) -> Optional[pd.DataFrame]:
"""
Filter data relevant for the graph from the dat... | 200e19d73ae04c4ceabae6d0d65ccd034f368e15 | 25,105 |
def get_question_summary_from_model(question_summary_model):
"""Returns a domain object for an Oppia question summary given a
question summary model.
Args:
question_summary_model: QuestionSummaryModel. The QuestionSummary model
object to fetch corresponding QuestionSummary domain object... | 65cce3d4440ebea81f5a777dcdec80c61b06e83b | 25,106 |
def refraction(alt_degrees, temperature_C, pressure_mbar):
"""Given an observed altitude, return how much the image is refracted.
Zero refraction is returned both for objects very near the zenith,
as well as for objects more than one degree below the horizon.
"""
r = 0.016667 / tan((alt_degrees + ... | d413aba8e238b81c5a8076460cc35ae56617f148 | 25,108 |
def reduce_mem_usage(df):
"""
iterate through all the columns of a dataframe and modify the data type to reduce memory usage.
"""
start_mem = df.memory_usage().sum() / 1024**2
logger.info('Memory usage of dataframe is {:.2f} MB'.format(start_mem))
for col in df.columns:
col... | d78e0de83c85bc7495141be428bd54a0b86a2564 | 25,109 |
def retry_pattern():
"""Retry pattern decorator used when connecting to snowflake
"""
return backoff.on_exception(backoff.expo,
snowflake.connector.errors.OperationalError,
max_tries=5,
on_backoff=log_backoff_att... | 78375f5f634f2826edd9c72fa20e2bb2d760b534 | 25,110 |
def get_vrf_route_targets(
device, address_family, rt_type, vrf=None, route_distinguisher=None
):
""" Get route target value from a device
Args:
address_family ('str'): address family value
rt_type ('str'): route target type
ex.) rt_type = 'import' OR
... | d06b40220c8cc5c44c5ef4ab1e7a60057791dda5 | 25,111 |
def _format_field(value, parts, conv, spec, want_bytes=False):
"""Format a replacement field."""
for k, part, _ in parts:
if k:
if part.isdigit():
value = value[int(part)]
else:
value = value[part]
else:
value = getattr(value, p... | d7c7bdf86b3b09800a4147d166584e81d7300c4f | 25,113 |
def mixed_string_list_one_valid():
"""Return mixed strings."""
return _MIXED_STRING_LISTS_ONE_VALID_ | c1f0ae91f761213a6d7674ec80e24befc0b959a4 | 25,114 |
def make_parser():
"""Create the argument parser, derived from the general scripts parser."""
parser = get_parser(
__doc__,
('A file containing a list of files/file paths to be read. These '
'should be nxml or txt files.')
)
parser.add_argument(
dest='output_name',
... | 4bb2320708728bbf277bd9de380bdf6b1ead5a8b | 25,115 |
import pathlib
def script_names():
"""Returns the sequence of example script names."""
result = [str(pathlib.Path(s).with_suffix('.py')) for s in _stem_names()]
return result | cdb4ab63718135fa98adbfbe8a1a237f6f5ad031 | 25,116 |
def lovasz_grad(gt_sorted):
"""
Computes gradient of the Lovasz extension w.r.t sorted errors
See Alg. 1 in paper
"""
p = len(gt_sorted)
gts = gt_sorted.sum()
intersection = gts - gt_sorted.float().cumsum(0)
union = gts + (1 - gt_sorted).float().cumsum(0)
jaccard = 1. - intersection ... | 5226660a77d5753346bedaecf786644eda296b74 | 25,117 |
def expand_image(_img, block, stride, deform=True):
"""
Args:
_img: numpy array
block: size of the blocks required
stride: step size
Returns: array of blocks
"""
if deform:
_img=_img.astype('float32')
ims_Z=np.zeros([_img.shape[0],block[1],block[0]... | 0ffbbfe2691be69980a334d1d32f4743dfd79de0 | 25,118 |
def disabled(reason='No reason given'):
"""Decorator that disables a command."""
# pylint:disable=missing-docstring,unused-argument
def actual_decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
raise DisabledCommandException('This command is disabled: %s' % reason)
... | 32753d4d58ee11f12eb32acabdb692640b93bab7 | 25,119 |
def get_tensor_model_parallel_group():
"""Get the tensor model parallel group the caller rank belongs to."""
assert _TENSOR_MODEL_PARALLEL_GROUP is not None, \
'intra_layer_model parallel group is not initialized'
return _TENSOR_MODEL_PARALLEL_GROUP | ecf9e212995f09fe9d6a5482213dba3d1071ba80 | 25,120 |
import re
import string
def normalize(data):
"""Normalizes the values of incoming data
Args:
data (dict): Dictionary of response data
Returns:
dict
"""
normalized_data = {}
for key in data:
value = str(data[key])
key = key.lower()
# Strip all fields... | ed88050001e6ea65b77d8381b2fd247918ed8f37 | 25,121 |
def five_fold(data_set):
"""[summary]
Args:
data_set (List of Sample objects): The Samples to be partitioned
Returns:
fold: where fold is list of len n in n-fold of (train,test) where train and test are lists of Samples
"""
partition_index = int( len(data_set) / 5 )
s = 0
fol... | d4179c238da3e9ebe05ab3513b80bcce982c8728 | 25,122 |
import re
def get_english_info(content_section):
"""
The english source section can have multiple publishers and volume counts. The criteria is that
the publisher with the largest volume count is most likely the one we want so sort the lines in
the section and grab data from the first line.
"""
... | c71751d863a4407fa409b18d7cced44c6044cb10 | 25,124 |
import numpy
def load_factual_vec(fname, vocab, k):
"""
Loads 300x1 word vecs from FACTBANK compiled word embeddings
"""
word_vecs = {}
with open(fname, "rb") as f:
header = f.readline()
vocab_size, layer1_size = map(int, header.split())
binary_len = numpy.dtype('float32'... | f37e030b4b8412a96652e67a673204e13c3cb3dc | 25,125 |
from datetime import datetime
def vaccine(date):
"""
Auxiliary function.
Download data about vaccination in Cantabria from the Ministry of Health, Consumer Affairs and Social Welfare.
https://www.mscbs.gob.es
Args:
date(str): Date in format %Y%m%d
Returns: DataFrame with vaccination d... | 5e3f9ffc3106b76ab637ab23fb6e8e6f487a48f1 | 25,126 |
def cache(f):
"""A decorator to cache results for a given function call.
Note: The caching is only done on the first argument, usually "self".
"""
ret = {}
def _Wrapper(*args, **kwargs):
self = args[0]
if self not in ret:
ret[self] = f(*args, **kwargs)
return ret... | 786218b8c248bcb7c9d519a843dd4542a9b612b0 | 25,127 |
def home():
"""Return the home page."""
response = flask.render_template(
'index.html',
metrics=SUPPORTED_METRICS.keys())
return response, 200 | aeb98484b580ceab6f45d7f52e05dda0b97ddb2b | 25,128 |
def data_to_segments_uniform(x, n_segments, segment_ranges=True):
""" Split data into segments of equal size (number of observations)."""
return split_equal_bins(x, n_segments) | d787bdad8604f4dbf327576f655a9e408b314766 | 25,129 |
from pathlib import Path
def load_all_sheets(file_name):
"""
Load from a xls(x) file all its sheets to a pandas.DataFrame as values to sheet_names as keys in a dictionary
Parameters
----------
file_name : str, Path
file_name to load from
Returns
-------
dict
dictionary... | 84452af6d81c7b44c0669af637950e8b1c1dbda8 | 25,130 |
from datetime import datetime
def rate_limit(limit=1000, interval=60):
"""Rate limit for API endpoints.
If the user has exceeded the limit, then return the response 429.
"""
def rate_limit_decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
key: str = f"Limit::{req... | 3f609d2bfe4a90fcf822df50e6c81032ad7d0d03 | 25,131 |
def filter_factory(global_conf, **local_conf):
"""Returns a WSGI filter app for use with paste.deploy."""
conf = global_conf.copy()
conf.update(local_conf)
def auth_filter(filteredapp):
return AuthProtocol(filteredapp, conf)
return auth_filter | b4b3b64093998865cf6a1846935c1a10db37b0ea | 25,132 |
def parse(stylesheet):
"""Parse a stylesheet using tinycss2 and return a StyleSheet instance.
:param stylesheet: A string of an existing stylesheet.
"""
parsed_stylesheet = tinycss2.parse_stylesheet(
stylesheet, skip_comments=True, skip_whitespace=True
)
css = qstylizer.style.StyleShee... | 3df3901c06e861b03746c21a056bae51bb93ebd6 | 25,133 |
import unittest
def test_suite():
"""Returns a test suite of all the tests in this module."""
test_classes = [TestNetCDFPointUtilsConstructor,
TestNetCDFPointUtilsFunctions1,
TestNetCDFPointUtilsGridFunctions
]
suite_list = map(unittest.default... | ebe3b28968def1131be19aedc963263f3277a5fb | 25,134 |
from typing import List
def compute_max_cut(n: int, nodes: List[int]) -> int:
"""Compute (inefficiently) the max cut, exhaustively."""
max_cut = -1000
for bits in helper.bitprod(n):
# Collect in/out sets.
iset = []
oset = []
for idx, val in enumerate(bits):
ise... | 30acd71267cd213e559bf43b8296333530736624 | 25,135 |
def get_capacity_potential_from_enspreso(tech: str) -> pd.Series:
"""
Return capacity potential (in GW) per NUTS2 region for a given technology, based on the ENSPRESO dataset.
Parameters
----------
tech : str
Technology name among 'wind_onshore', 'wind_offshore', 'wind_floating', 'pv_utilit... | 4daaf38ca9f54aa162b79682ed981d3ba3ab3167 | 25,136 |
import time
import urllib
import json
def use_nearby_search(url, next_page=False, request_count=0):
"""Call nearby search API request.
Parameters
----------
url: str
URL to use to send a Nearby Search Request in Google Maps Place Search API
next_page: boolean, optional(default=False)
... | f579288356c4330a3af5ec2ac94cf31242669ba8 | 25,137 |
import urllib
def _GetGoogleAuthtoken(account_type, user, password, service, source):
"""This function authenticates the user in the specified service using
the provided authentication data.
Args:
account_type: Type of the account to login, could be GOOGLE or any other
string if the account is exte... | 9852968100d116e27cf50f4b047661ef3135074d | 25,138 |
def trim_filters(response):
"""Trim the leading and trailing zeros from a 1-D array or sequence, leaving
one zero on each side. This is a modified version of numpy.trim_zeros.
Parameters
----------
response : 1-D array or sequence
Input array.
Returns
-------
first : int
... | 2582c5821bd5c8487c0f9d2f55d2d982767d2669 | 25,139 |
def is_spanning(graph, subgraph):
"""
Return True or False by passing graph and subgraph through function V
to check if the subgraph uses all verticies of the original graph
Parameters
----------
graph = A networkx graph.
subgraph = A networkx subgraph of 'graph'.
... | 371388bd6657165451216c4c65c5ea43ef19fed5 | 25,140 |
from bs4 import BeautifulSoup
import re
def clean_text(text):
"""
A function to pre-process text
Parameters
----------
text : string
the string to be processed
Returns
-------
text : string
a clean string
"""
tok = WordPunctTokenizer()
pat1 = r'@[A-Za-z0-9]... | dc9d243d4c57ec1ea1af20325be57db536ec4286 | 25,144 |
def test_alias_function():
"""Test 4: Generate markup based on an element using an (alias w/function) parameter to explicitly correlate data and elements"""
template = get_template('contacts-alias')
def alias_name(p, e, k, v):
eq_(k, 'name')
return 'foo'
weld(template('.contact')[0], d... | 69275c3e6676ac7b0473676fc7fe65d387edfecd | 25,146 |
def baseurl(request):
"""
Return a BASE_URL template context for the current request.
"""
if request.is_secure():
scheme = 'https://'
else:
scheme = 'http://'
return {'BASE_URL': scheme + request.get_host(), } | 76f3d75008eb996d1da226dbb4a7bd6e228fbcd1 | 25,147 |
import requests
def geolocate(address, bounds=None, country=None, administrative_area=None, sensor=False):
"""
Resolves address using Google Maps API, and performs some massaging to the output result.
Provided for convenience, as Uber relies on this heavily, and the desire to give a simple 'batteries incl... | 71edf37429aa10420e070d0cacf4e9ade1e6a75f | 25,148 |
def _cmdy_hook_class(cls):
"""Put hooks into the original class for extending"""
# store the functions with the same name
# that defined by different plugins
# Note that current (most recently added) is not in the stack
cls._plugin_stacks = {}
def _original(self, fname):
"""Get the orig... | 5653a71aeafc184751edcb8fddecd503c4aa2ee9 | 25,149 |
def load_data(
datapath=None,
minstorms=3,
minbmps=3,
combine_nox=True,
combine_WB_RP=True,
remove_grabs=True,
grab_ok_bmps="default",
balanced_only=True,
fix_PFCs=True,
excluded_bmps=None,
excluded_params=None,
as_dataframe=False,
**dc_kwargs
):
"""Prepare data f... | 72c7e6be0eabddeba79c681c5da30e0b855b6496 | 25,152 |
def parser_IBP_Descriptor(data,i,length,end):
"""\
parser_IBP_Descriptor(data,i,length,end) -> dict(parsed descriptor elements).
This descriptor is not parsed at the moment. The dict returned is:
{ "type": "IBP", "contents" : unparsed_descriptor_contents }
(Defined in ISO 13818-1 specif... | 12379af2260dd461751c59e2023b7e5e9d68b979 | 25,155 |
import logging
def build_county_list(state):
"""
Build the and return the fips list
"""
state_obj = us.states.lookup(state)
logging.info(f"Get fips list for state {state_obj.name}")
df_whitelist = load_data.load_whitelist()
df_whitelist = df_whitelist[df_whitelist["inference_ok"] == True]... | b11a0b831b7b89d04896ed1914acf993ef1d48ba | 25,156 |
import bs4
def is_comment(obj):
"""Is comment."""
return isinstance(obj, bs4.Comment) | e56749b3d5f95754a031cc7286229d942333a22e | 25,157 |
from typing import Tuple
import sqlite3
def insert_user(username: str) -> Tuple[int, str]:
"""
Inserts a new user. If the desired username is already taken,
appends integers incrementally until an open name is found.
:param username: The desired username for the new user.
:return A tuple contai... | 9eeeb6755251183de5ad775acfceef17c9f582a3 | 25,158 |
def get_gateway(ctx, name):
"""Get the sdk's gateway resource.
It will restore sessions if expired. It will read the client and vdc
from context and make get_gateway call to VDC for gateway object.
"""
restore_session(ctx, vdc_required=True)
client = ctx.obj['client']
vdc_href = ctx.obj['pr... | 998f1a6a600797164c3e053eed206d99d20b338c | 25,159 |
def fn_getdatetime(fn):
"""Extract datetime from input filename
"""
dt_list = fn_getdatetime_list(fn)
if dt_list:
return dt_list[0]
else:
return None | efea54154d318e0e5ef71c6147057b461696c677 | 25,160 |
def greenplum_kill_process(process_id):
"""
:param process_id: int
:return: None
"""
query = """
select pg_cancel_backend({0});
select pg_terminate_backend({0});
""".format(process_id)
return greenplum_read(query) | 1bcd362bf2ed3d4cb5773c5539d0e9bb43bc96ab | 25,161 |
import base64
import re
def check_app_auth(headers):
"""Authenticate an application from Authorization HTTP header"""
try:
auth_header = headers["Authorization"]
except KeyError:
return False
# Only handle HTTP Basic authentication
m = re.match("Basic (\w+==)", auth_header)
i... | 5378f70041294fdad591ffbb941991cb03a7fb3d | 25,162 |
def setupConnection():
"""
Create connection to database, to be shared by table classes. The file
will be created if it does not exist.
"""
dbPath = conf.get('db', 'path')
conn = builder()(dbPath)
return conn | 3437cf04622acf32b974b1ecc406daa594d30650 | 25,163 |
def max_pool(ip):
"""does a 2x2 max pool, crops off ends if not divisible by 2
ip is DxHxW
op is DxH/2xW/2
"""
height = ip.shape[1] - ip.shape[1]%2
width = ip.shape[2] - ip.shape[2]%2
h_max = np.maximum(ip[:,:height:2,:], ip[:,1:height:2,:])
op = np.maximum(h_max[:,:,:width:2], h_max[:,... | c270c4128842e33e69e0861f0010b0903c9728d3 | 25,164 |
import torch
def get_bin_vals(global_config):
"""
Creates bin values for grasping widths according to bounds defined in config
Arguments:
global_config {dict} -- config
Returns:
tf.constant -- bin value tensor
"""
bins_bounds = np.array(global_config['DATA']['labels']['offset... | 07acdcb0329c1002983ca021fbc84c60f7474758 | 25,165 |
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