id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
135522 | from PyQt4 import QtGui
from PySide import QtGui
import dictionaries.constants as cs
################################################################################
class InfoDialog(QtGui.QWidget):
def __init__(self, info_message):
super(InfoDialog, self).__init__()
self.build_lab... |
135529 | def is_prime(num, primes):
for prime in primes:
if prime == num:
return True
if not num % prime:
return False
return True
def get_primes(num):
limit = (num // 2) + 1
candidates = list()
primes = list()
for i in range(2, limit):
if is_prime(i, pr... |
135580 | from .checks import check_unique_service_names, check_env_file_exists
from .cli import cli
def main() -> None:
try:
check_unique_service_names()
check_env_file_exists()
except RuntimeError as e:
print(e)
exit(1)
cli()
main()
|
135604 | from armulator.armv6.opcodes.abstract_opcode import AbstractOpcode
from armulator.armv6.shift import shift
class Pkhbt(AbstractOpcode):
def __init__(self, tb_form, m, d, n, shift_t, shift_n):
super(Pkhbt, self).__init__()
self.tb_form = tb_form
self.m = m
self.d = d
self.n ... |
135612 | import os
import numpy as np
import argparse
import time
import torch
import torchvision
import cv2
def yolo_forward_dynamic(output, num_classes, anchors, num_anchors, scale_x_y):
# Output would be invalid if it does not satisfy this assert
# assert (output.size(1) == (5 + num_classes) * num_anchor... |
135625 | from pak.datasets.Dataset import Dataset
import numpy as np
import zipfile
import tarfile
import urllib.request
import shutil
from os import makedirs, listdir
from os.path import join, isfile, isdir, exists, splitext
from scipy.ndimage import imread
from scipy.misc import imresize
from scipy.io import loadmat
from skim... |
135631 | from collections import defaultdict
class Graph:
def __init__(self, vertices):
self.V = vertices
self.graph = []
def addEdge(self, u, v, w):
self.graph.append([u, v, w])
def find(self, parent, i):
if parent[i] == i:
return i
return self.fin... |
135678 | from itty import *
from tropo import Tropo, Result, MachineDetection
@post('/index.json')
def index(request):
t = Tropo()
mc = MachineDetection(introduction="This is a test. Please hold while I determine if you are a Machine or Human. Processing. Finished. THank you for your patience.", voice="Victor").json
t.... |
135686 | import json
import random
from datetime import datetime, timedelta
from flask import current_app
from notifications_utils.s3 import s3upload
from requests import HTTPError, request
from app import notify_celery
from app.aws.s3 import file_exists
from app.celery.process_ses_receipts_tasks import process_ses_results
fr... |
135706 | label_data = open("label", encoding='utf-8').readlines()
label_data = [x.strip() for x in label_data]
print(len(label_data))
label_kinds = set(label_data)
print(label_kinds) |
135787 | import _curses
_capability_names = {_curses.KEY_A1: 'ka1', _curses.KEY_A3: 'ka3', _curses.
KEY_B2: 'kb2', _curses.KEY_BACKSPACE: 'kbs', _curses.KEY_BEG: 'kbeg',
_curses.KEY_BTAB: 'kcbt', _curses.KEY_C1: 'kc1', _curses.KEY_C3: 'kc3',
_curses.KEY_CANCEL: 'kcan', _curses.KEY_CATAB: 'ktbc', _curses.
KEY_CLE... |
135804 | from typing import Dict, List, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from kornia.constants import pi
from kornia.filters import GaussianBlur2d, SpatialGradient
from kornia.geometry.conversions import cart2pol
from kornia.utils import create_meshgrid
# Precomputed coefficient... |
135825 | import torch.nn as nn
from torch.nn.functional import softmax
from torch.nn import CrossEntropyLoss
from typing import List, Any, Dict, Union
from sciwing.data.line import Line
from sciwing.data.label import Label
from wasabi import Printer
from sciwing.utils.class_nursery import ClassNursery
from sciwing.data.datasets... |
135831 | from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class Game(models.Model): #Overall Game Object
name = models.CharField(max_length=200) #name of the game
start_time = models.DateTimeField() #time to start
end_time = models.DateTimeField() #time game ends
... |
135833 | from sample_factory.envs.env_registry import global_env_registry
def create_env(full_env_name, cfg=None, env_config=None):
"""
Factory function that creates environment instances.
Matches full_env_name with env family prefixes registered in the REGISTRY and calls make_env_func()
for the first match.
... |
135877 | import torch
def accuracy(preds, labels, ignore_index=None):
with torch.no_grad():
assert preds.shape[0] == len(labels)
correct = torch.sum(preds == labels)
total = torch.sum(torch.ones_like(labels))
if ignore_index is not None:
# 모델이 맞춘 것 가운데 ignore index에 해당하는 것 제외
... |
135900 | from __future__ import division, print_function
from action_detector_diagnosis import ActionDetectorDiagnosis
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import numpy as np
import pandas as pd
import os
from collections import OrderedDict
from utils import interpolated_prec_rec
from matplotlib i... |
135910 | import shlex
from unittest import TestCase, mock
from compose_flow.commands import Workflow
from tests import BaseTestCase
TEST_PROJECT_NAME = "test_project_name"
@mock.patch("compose_flow.commands.subcommands.env.utils")
@mock.patch("compose_flow.commands.subcommands.env.get_backend")
class WorkflowTestCase(Base... |
135925 | from geocode.geocode import Geocode
from tqdm import tqdm
import pandas as pd
import numpy as np
import ast
from geopy.geocoders import Nominatim
from geopy.extra.rate_limiter import RateLimiter
import os
import logging
import time
logging.basicConfig(level=logging.INFO, format=',%(asctime)s [%(levelname)-5.5s] [%(nam... |
135991 | import pytest
from flask import Flask, render_template_string
from flask_mobility import Mobility
from flask_mobility.decorators import mobile_template, mobilized
class TestDecorators(object):
@pytest.fixture()
def app(self):
app = Flask(__name__)
Mobility(app)
@app.route("/")
... |
136073 | from datetime import date
from random import choice, sample, randint, uniform
from pepper.brain import RdfBuilder
from pepper.framework import UtteranceHypothesis, Context, Face
from pepper.framework.sensor.obj import Object
from pepper.language import Chat, Utterance, UtteranceType
places = ['Office']
friends = ['Pi... |
136096 | from sportsdataverse.nba.nba_loaders import *
from sportsdataverse.nba.nba_pbp import *
from sportsdataverse.nba.nba_schedule import *
from sportsdataverse.nba.nba_teams import * |
136128 | import utils
import argparse
import pathlib
from collections import namedtuple
import itertools
import math
parser = argparse.ArgumentParser(description="Generate run descriptions")
parser.add_argument("base_dir", type=str,
help="Base directory for run descriptions")
args = parser.parse_args()
base... |
136149 | SHORT_DESCRIPTION = "Sorter organises/sorts files using a customised search function to group those that have similar characteristics into a single folder. Similar characteristics include file type, file name or part of the name and file category. You can put all letters documents into one folder, all images with the w... |
136161 | def includeme(config):
""" Set up event subscribers. """
from .models import (
AuthUserMixin,
random_uuid,
lower_strip,
encrypt_password,
)
add_proc = config.add_field_processors
add_proc(
[random_uuid, lower_strip],
model=AuthUserMixin, field='usernam... |
136186 | import unittest
import json
from lax_response_adapter import LaxResponseAdapter
from mock import Mock
from provider.utils import base64_encode_string
FAKE_TOKEN = json.dumps(
{
u"status": u"vor",
u"expanded_folder": u"837411455.1/a8bb05df-2df9-4fce-8f9f-219aca0b0148",
u"version": u"1",
... |
136199 | import librosa
import torch
import torchaudio
from torchaudio.transforms import Resample, Spectrogram
def load(path, sample_rate=22050):
waveform, source_rate = torchaudio.load(path)
if len(waveform) > 1:
waveform = waveform.mean(dim=0)
if source_rate != sample_rate:
resample = Resample(so... |
136252 | from sandbox.crazyflie.src.gcg.envs.GibsonEnv.env_modalities import CameraRobotEnv, BaseRobotEnv
from sandbox.crazyflie.src.gcg.envs.GibsonEnv.env_bases import *
from sandbox.crazyflie.src.gcg.envs.GibsonEnv.robot_locomotors import Quadrotor3
from transforms3d import quaternions
import os
import numpy as np
import sys
... |
136256 | import binascii
import struct
import os
import gevent
import ipaddress
import time
from gevent.lock import RLock
from gevent.event import AsyncResult
from gevent import socket
import collections
import traceback
try:
import color_logging
import logging
logger = logging
except:
import logging
logger... |
136265 | import pytest
import jax.random as jr
import jax.numpy as np
from jax import jit
import numpy as onp
from ssm.factorial_hmm import NormalFactorialHMM
SEED = jr.PRNGKey(0)
@jit
def identity(x):
return x
#### TESTS
def test_normal_factorial_hmm_jit():
fhmm = NormalFactorialHMM(num_states=(3, 4), seed=SEED... |
136291 | def define_display_nodes(tree,nodemap,unscoped_vectors=False,looped_definition=False):
if unscoped_vectors:
s = ''
else:
s = '\t\t\tstd::vector<MPILib::NodeId> display_nodes;\n'
display_nodes = tree.findall('.//Display')
for dn in display_nodes:
node_id = str(nodemap[dn.attrib[... |
136335 | from IMDBDatabase import IMDBData
# GUIDED PRACTICE
# Challenge 1.1 - The first step to data analysis is always to understand the
# database. Just like you can use a for loop to print all the elements in a list,
# use a for loop to print all the movieNames in IMDBData.
for movieName in IMDBData:
print(movieName)
... |
136336 | import os
import matplotlib.pyplot as plt
import pandas as pd
import torch
import torchvision
from matplotlib import rc
from piq import psnr, ssim
from data_management import (
CropOrPadAndResimulate,
Flatten,
Normalize,
RandomMaskDataset,
filter_acquisition_no_fs,
)
from find_adversarial import ... |
136339 | from django.urls import path
from .views import index
app_name = "app"
urlpatterns = [
path("", index, name="index"),
]
|
136347 | from .basic import BasicLoginHandler
from .certificate import CertificateLoginHandler
LOGIN_HANDLERS = [BasicLoginHandler, CertificateLoginHandler]
|
136379 | from lenstronomy.GalKin.numeric_kinematics import NumericKinematics
from lenstronomy.GalKin.analytic_kinematics import AnalyticKinematics
__all__ = ['GalkinModel']
class GalkinModel(object):
"""
this class handles all the kinematic modeling aspects of Galkin
Excluded are observational conditions (seeing,... |
136388 | from .local_diffeo_transform import LocalDiffeoTransform
from .local_diffeo_transformed_distribution import LocalDiffeoTransformedDistribution
from .lie_multipy_transform import (
LieMultiplyTransform,
SO3MultiplyTransform,
SE3MultiplyTransform,
)
from .so3_exp_transform import (
SO3ExpTransform,
SO... |
136391 | from __future__ import absolute_import, division, unicode_literals
import json
import os
from six import iteritems
from six.moves import zip
from tqdm import tqdm
import zipfile
# these may be used by pick_group_fn/postprocess_fn
from six.moves import range # NOQA
from ..utils import download_utils, file_formats, f... |
136423 | from WebUtils.Funcs import htmlForDict
from .AdminSecurity import AdminSecurity
class Config(AdminSecurity):
def title(self):
return 'Config'
def writeContent(self):
self.writeln(htmlForDict(
self.application().config(), topHeading='Application'))
|
136429 | from rdkit.Chem.rdMolDescriptors import CalcPBF
from ._base import Descriptor
__all__ = ("PBF",)
class PBF(Descriptor):
r"""PBF descriptor."""
__slots__ = ()
since = "1.1.2"
require_3D = True
@classmethod
def preset(cls, version):
yield cls()
def description(self):
ret... |
136436 | import torch
import torch.utils.data
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
from torchvision import datasets, transforms
import torch.nn.functional as F
import numpy as np
from dataset.data_loader_kitti_reimpl import KITTIReader_traj
from models.vgg_warper_weak_short... |
136455 | import boto3
import sure # noqa # pylint: disable=unused-import
from moto import mock_guardduty
@mock_guardduty
def test_create_detector():
client = boto3.client("guardduty", region_name="us-east-1")
response = client.create_detector(
Enable=True,
ClientToken="745645734574758463758",
... |
136459 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from common.backbone.resnet.resnet import *
from common.backbone.resnet.resnet import Bottleneck, BasicBlock
from common.backbone.resnet.resnet import model_urls
from common.lib.roi_pooling.roi_pool import ROI... |
136479 | import re
from bs4 import Tag
from ._abstract import AbstractScraper
from ._utils import normalize_string
"""
NOTE: This website has at least 2 prominent layouts styles, so there are two logic blocks and 2 test cases to
support in ingredients and instructions processing sections.
"""
class FarmhouseDeliver... |
136484 | import pytest
import random
import collections
import pickle
from uuid import uuid4
import os
import unicodedata
import tempfile
from pkg_resources import parse_version
import gluonnlp
from gluonnlp.data.tokenizers import WhitespaceTokenizer, MosesTokenizer, JiebaTokenizer,\
SpacyTokenizer, SubwordNMTTokenizer, YTT... |
136489 | from django import test
from django_extras.forms import fields
from django_extras.core import validators
class ColorFieldTestCase(test.TestCase):
def test_check_validator_no_alpha(self):
target = fields.ColorField()
self.assertIn(validators.validate_color, target.validators)
def test_check_val... |
136502 | from sqlalchemy import create_engine
from constants import SQLALCHEMY_URL
engine = create_engine(SQLALCHEMY_URL)
|
136505 | from dataclasses import dataclass
from enum import IntEnum, IntFlag, auto
from functools import reduce
from struct import Struct
from typing import Any, Dict, List, Optional, Type
from .datatypes import (
AerospikeDataType,
AerospikeKeyType,
AerospikeValueType,
data_to_aerospike_type,
parse_raw,
)
... |
136545 | import numpy as np
import pandas as pd
l_2d = [[0, 1, 2], [3, 4, 5]]
arr_t = np.array(l_2d).T
print(arr_t)
print(type(arr_t))
# [[0 3]
# [1 4]
# [2 5]]
# <class 'numpy.ndarray'>
l_2d_t = np.array(l_2d).T.tolist()
print(l_2d_t)
print(type(l_2d_t))
# [[0, 3], [1, 4], [2, 5]]
# <class 'list'>
df_t = pd.DataFrame(l... |
136555 | import json
from dispatch.enums import DispatchEnum
from dispatch.incident.models import Incident
from dispatch.feedback.enums import FeedbackRating
class RatingFeedbackBlockId(DispatchEnum):
anonymous = "anonymous_field"
feedback = "feedback_field"
rating = "rating_field"
class RatingFeedbackCallbackI... |
136583 | from enum import Enum
class ModeIndicator(Enum):
INPUT = '+' # use existing variable
OUTPUT = '-' # create new variable (do not reuse existing)
CONSTANT = 'c' # insert constant
|
136584 | from django.db import migrations, models
import two_factor.models
class Migration(migrations.Migration):
dependencies = [
('two_factor', '0005_auto_20160224_0450'),
]
operations = [
migrations.AlterField(
model_name='phonedevice',
name='key',
field=mo... |
136591 | import os
from setka.pipes.logging.progressbar.theme_parser import view_status, format_status
# from setka.pipes.logging.progressbar.theme import main_theme
try:
from IPython.display import display, update_display
except:
pass
def isnotebook():
try:
shell = get_ipython().__class__.__name__
... |
136611 | import csv
import os
import cv2
import random
import argparse
def main(args):
image_path = args.image_path
csv_path = args.csv_path
preprocess(image_path, csv_path)
def preprocess(image_path, csv_path):
print("start preprocess...")
f = open(csv_path, 'w', encoding='utf-8', newli... |
136696 | import spacy
import classy_classification # noqa: F401
from .data import training_data, validation_data
nlp = spacy.blank("en")
nlp.add_pipe("text_categorizer", config={"data": list(training_data.keys()), "cat_type": "zero", "include_sent": True})
print([sent._.cats for sent in nlp(validation_data[0]).sents])
print... |
136726 | import os
import asyncio
import chess
import discord
from discord.ext import commands, tasks
from discord.ext.commands import Context
from cogs.utils.chess_utils import ChessUtils
import berserk
"""
{'type': 'gameState',
'moves': 'g1f3',
'wtime': datetime.datetime(1970, 1, 25, 20, 31, 23, 647000, tzinfo=datetime.t... |
136744 | import time
def timeit(method):
""" Get the time it takes for a method to run.
Args:
method (function): The function to time.
Returns:
Method wrapped with an operation to time it.
"""
def timed(*args, **kw):
ts = time.time()
result = method(*args, **kw)
te... |
136745 | from openstatesapi.jurisdiction import make_jurisdiction
J = make_jurisdiction('mt')
J.url = 'http://montana.gov'
|
136798 | import invoke
import docs
import installers
import shims
namespace = invoke.Collection(docs, installers, shims)
|
136842 | class QueryToken:
"""A placeholder token for dry-run query output"""
def __str__(self) -> str:
return "?"
def __repr__(self) -> str:
return "?"
|
136857 | import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras import layers
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import auc,precision_recall_curve,roc_curve,confusion_matrix
import os,sys
import pickle
def draw_ROC(y_true,y_pred):
fpr,tpr,_... |
136858 | RED, BLACK = True, False
class Node:
def __init__(self, key, value, color, size):
self.k = key
self.v = value
self.left, self.right = None, None
self.color = color
self.size = size
@staticmethod
def is_red(current):
if current is None: return False... |
136867 | import redis
class Redis:
@classmethod
def setex(cls, name, time, value):
r = redis.StrictRedis(host='127.0.0.1', port=6379, db=0)
r.setex(name, time, value)
@classmethod
def get(cls, name):
r = redis.StrictRedis(host='127.0.0.1', port=6379, db=0)
value = r.get(name)
... |
136880 | import numpy
from PIL import Image
import scipy.ndimage
import sys
path = sys.argv[1]
region = sys.argv[2]
x_start = int(sys.argv[3])
y_start = int(sys.argv[4])
x_end = int(sys.argv[5])
y_end = int(sys.argv[6])
out_fname = sys.argv[7]
x_len = x_end - x_start
y_len = y_end - y_start
merged_im = numpy.zeros((x_len * 4... |
136954 | import json
import time
from sqlalchemy import insert
from sqlalchemy.sql.expression import bindparam
from autocnet.io.db.model import Points, Measures
from autocnet.utils.serializers import object_hook
from autocnet.transformation.spatial import reproject, og2oc
def watch_insert_queue(queue, queue_name, counter_nam... |
136959 | from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
extensions = Extension(name='tree_collection',
sources=['py_wrapper.pyx',
'../src/ProblemParser.cc',
'../src/MinSqTr... |
136969 | from .buyback_metrics import *
from .fei_metrics import *
from .fei_volume_metrics import *
from .pcv_metrics import *
|
136970 | from __future__ import print_function
import os
import shutil
import sys
import tempfile
import unittest
import pandas as pd
import pyspark
import pytest
import sklearn.datasets
from sklearn.neighbors import KNeighborsClassifier
from mlflow.pyfunc import load_pyfunc, spark_udf
from mlflow.pyfunc.spark_model_cache im... |
136982 | from secml.testing import CUnitTest
from secml.array import CArray
from secml.data import CDataset
from secml.ml.features import CPreProcess
from secml.optim.function import CFunction
from secml.figure import CFigure
from secml.core.constants import eps
class CClassifierTestCases(CUnitTest):
"""Unittests interfa... |
136985 | import unittest
from pyEpiabm.routine import AbstractPopulationFactory
class TestPopConfig(unittest.TestCase):
"""Test the 'ToyPopConfig' class.
"""
def test_make_pop(self):
"""Tests for a make population method.
"""
with self.assertRaises(NotImplementedError):
Abstrac... |
137012 | import argparse
import sys, os
parser = argparse.ArgumentParser()
parser.add_argument('pyqlabpath', help='path to PyQLab directory')
parser.add_argument('nbrSegments', type=int, help='nbrSegments')
args = parser.parse_args()
sys.path.append(args.pyqlabpath)
from Libraries import instrumentLib
if 'X6' not in instrumen... |
137037 | from ray import tune
def get_config():
return {
# === Environment ===
"env": "Navigation",
"env_config": tune.grid_search(
[
{"deceleration_zones": None},
{"deceleration_zones": {"center": [[0.0, 0.0]], "decay": [2.0]}},
]
),
... |
137040 | def test_bounds():
from pyvmmonitor_core.math_utils import Bounds
bounds = Bounds()
assert not bounds.is_valid()
bounds.add_point((10, 10))
assert bounds.is_valid()
assert bounds.width == 0
assert bounds.height == 0
bounds.add_point((0, 0))
assert bounds.nodes == ((0, 0)... |
137084 | import os
from unittest import mock
import pytest
from iotedgedev.envvars import EnvVars
from iotedgedev.output import Output
pytestmark = pytest.mark.unit
def test_get_envvar__valid():
envvars = EnvVars(Output())
deployment_template = envvars.get_envvar("DEPLOYMENT_CONFIG_TEMPLATE_FILE")
assert deploym... |
137176 | from ctypes import c_int, c_char_p, c_void_p, CFUNCTYPE
from ctypes import POINTER as _P
from .dll import _bind, SDLFunc, AttributeDict
__all__ = [
# Defines
"SDL_MAX_LOG_MESSAGE",
# Enums
"SDL_LogCategory",
"SDL_LOG_CATEGORY_APPLICATION",
"SDL_LOG_CATEGORY_ERROR", "SDL_LOG_CATEGORY_ASSER... |
137190 | def lazyproperty(fn):
attr_name = '__' + fn.__name__
@property
def _lazyprop(self):
if not hasattr(self, attr_name):
setattr(self, attr_name, fn(self))
return getattr(self, attr_name)
return _lazyprop
|
137204 | from kubernetes import client
from kubernetes.client.rest import ApiException
from .load_kube_config import kubeConfig
kubeConfig.load_kube_config()
apps = client.AppsV1Api()
class K8sStatefulSet:
def get_sts(ns, logger):
try:
if ns != 'all':
logger.info ("Fetching {} namespace... |
137210 | import pandas as pd
import torch
from typing import Callable, List
from torch.utils.data import TensorDataset
class CsvDataset(TensorDataset):
data: pd
y_cols: List
x_cols: List
transform: Callable
test_fraction: float = 0.0
train: bool
def __init__(self, file_path: str, y_cols: List, x... |
137213 | from .base_menu import Menu
from .tasks import buyAirtime
class Airtime(Menu):
def get_phone_number(self): # 10
if self.user_response == '1':
self.session["phone_number"] = self.phone_number
menu_text = "Buy Airtime\nPlease Enter Amount(Ksh)"
self.session['level'] = 12... |
137223 | from __future__ import absolute_import, print_function, division
import copy
import unittest
# Skip test if cuda_ndarray is not available.
from nose.plugins.skip import SkipTest
import numpy
from six.moves import xrange
import theano
import theano.sandbox.cuda as cuda_ndarray
from theano.tensor.basic import _allclose... |
137265 | from .generic_indicator import GenericIndicator
from pyti.average_true_range import average_true_range as atr
# params: period
# https://github.com/kylejusticemagnuson/pyti/blob/master/pyti/average_true_range.py
class PytiAverageTrueRange(GenericIndicator):
def __init__(self, market, interval, periods, params=No... |
137277 | import re
from collections import namedtuple
Help = namedtuple('Help', 'options')
opt_pattern = re.compile(r'((--[a-zA-Z\-]+)|(-[a-zA-Z])\b)')
def parse_help(helpstr):
# Contains options, e.g. --help, --verbose, -o
options = [match[1] for match in opt_pattern.finditer(helpstr)]
return Help(options=options)
|
137300 | from keras_audio.library.utility.audio_utils import compute_melgram
from keras_audio.library.utility.gtzan_loader import download_gtzan_genres_if_not_found
import numpy as np
def load_audio_path_label_pairs(max_allowed_pairs=None):
download_gtzan_genres_if_not_found('../very_large_data/gtzan')
audio_paths = []... |
137306 | import requests
from ..utils.exceptions import BestBuyAPIError
from ..constants import (
API_SEARCH_PARAMS,
BASE_URL,
BULK_API,
STORE_SEARCH_PARAMS,
PRODUCT_SEARCH_PARAMS,
)
class BestBuyCore(object):
def __init__(self, api_key):
"""API's base class
:params:
:api_key (... |
137326 | from brownie import *
from .settings import *
from .contracts import *
from .contract_addresses import *
import time
def main():
load_accounts()
# Initialise Project
operator = accounts[0]
wallet = accounts[1]
# GP: Split into public and miso access control
access_control = deploy_access_con... |
137372 | from .abstract import AbstractHealthcheck
class DummyHealthcheck(AbstractHealthcheck):
status = True
def __init__(self, config=None):
pass
async def is_healthy(self, vm):
return self.status
def set_status(self, healthy):
self.status = healthy
|
137375 | from .xframeoptionsdirective import XFrameOptionsDirective
from .xframeoptions import XFrameOptions
__all__ = ['XFrameOptionsDirective','XFrameOptions']
|
137377 | from django.core.exceptions import ValidationError
from django.db import models
from django.utils.unittest import TestCase
class ValidationMessagesTest(TestCase):
def test_autofield_field_raises_error_message(self):
f = models.AutoField(primary_key=True)
self.assertRaises(ValidationError, f.clean... |
137384 | import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
def vis_causal_net(adata, key='RDI', layout = 'circular', top_n_edges = 10, edge_color = 'gray', figsize=(6, 6)):
"""Visualize inferred causal regulatory network
This plotting function visualize the inferred causal regulatory network inf... |
137388 | from collections import namedtuple
import numpy as np
import pytest
from numpy.testing import assert_allclose
from pytest_lazyfixture import lazy_fixture
from emukit.quadrature.methods.warpings import IdentityWarping, SquareRootWarping
def create_fixture_parameters():
return [pytest.param(lazy_fixture(warping.n... |
137404 | from wsgiref.simple_server import make_server
from pyramid.config import Configurator
from pyramid.response import Response
def hello_world(request):
return Response('Hello World!')
if __name__ == '__main__':
with Configurator() as config:
config.add_route('hello', '/')
config.add_view(hello_w... |
137411 | import copy
import os
import tempfile
import tarfile
import pytest
import torch
from allennlp.version import _MAJOR, _MINOR
from allennlp.commands.train import train_model
from allennlp.common import Params
from allennlp.common.meta import Meta
from allennlp.common.checks import ConfigurationError
from allennlp.commo... |
137454 | import unittest
import hcl2
from checkov.terraform.checks.resource.linode.user_email_set import check
from checkov.common.models.enums import CheckResult
class Testuser_email_set(unittest.TestCase):
def test_success(self):
hcl_res = hcl2.loads("""
resource "linode_user" "test" {
email="<... |
137471 | import asyncio
import functools
import secrets
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import TimeoutError as FutureTimeoutError
from logging import Logger, getLogger
from typing import TYPE_CHECKING, Any, Dict, Tuple
from urllib.parse import urlparse
from broadcaster._backends.base i... |
137514 | import os
import cv2
import matplotlib.pyplot as plt
import numpy as np
import pykitti
import torch
import torchvision.transforms.functional as F
from torch import hub
from torchvision.datasets import Cityscapes
from autolabeling import autolabel
from autolabeling.classes import get_lidar_colormap
from lilanet.utils ... |
137519 | import arrayfire as af
import typing as tp
from ._array import ndarray, _wrap_af_array
def count_nonzero(a: ndarray,
axis: tp.Optional[int] = None) \
-> tp.Union[int, ndarray]:
return _wrap_af_array(af.count(a._af_array, dim=axis))
def diff(a: ndarray,
n: int = 1,
ax... |
137520 | from unittest import TestCase
class TestDukeMTMC(TestCase):
def test_all(self):
import os.path as osp
from reid.datasets import DukeMTMC
from reid.utils.serialization import read_json
root, split_id, num_val = '/tmp/open-reid/dukemtmc', 0, 100
dataset = DukeMTMC(root, spli... |
137539 | from __future__ import absolute_import, division, print_function
import cctbx.xray.targets
from cctbx.array_family import flex
from libtbx.test_utils import approx_equal
from six.moves import range
def calc_k(f_obs, i_calc):
fc = flex.sqrt(i_calc)
num = flex.sum(f_obs * fc)
den = flex.sum(fc * fc)
assert den !... |
137553 | import FWCore.ParameterSet.Config as cms
from PhysicsTools.IsolationAlgos.tkIsoDeposits_cff import *
EcalIsolationForTracks = cms.EDProducer("IsolationProducerForTracks",
highPtTracks = cms.InputTag("highPtTracks"),
tracks = cms.InputTag("goodTracks"),
isoDeps = cms.InputTag("tkIsoDepositCalByAssociatorTow... |
137673 | import os
import sys
import mxnet as mx
def cifar100_iterator(cfg, kv):
train_rec = os.path.join(cfg.dataset.data_dir, "cifar100_train.rec")
val_rec = os.path.join(cfg.dataset.data_dir, "cifar100_test.rec")
mean = [129.31, 124.11, 112.4]
std = [68.21, 65.41, 70.41]
train = mx.io.ImageRecordIter... |
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