id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
1695944 | from freezegun import freeze_time
from openinghours.tests.tests import OpeningHoursTestCase
class FormsTestCase(OpeningHoursTestCase):
def setUp(self):
super(FormsTestCase, self).setUp()
def tearDown(self):
super(FormsTestCase, self).tearDown()
def test_hours_are_published(self):
... |
1695967 | import logging
import requests
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont, ImageOps
import app.data.firestore as data
logger = logging.getLogger('food-flex')
INTERNAL_RES = (1024, 1024)
OUTPUT_RES = (1024, 1024)
FONT_PATH = 'static/DejaVuSans-Bold.ttf'
FONT_BASE_SIZE = int(0.2 * INTERNAL_RES[1... |
1695975 | from flask import jsonify, request
from flask_security.recoverable import send_reset_password_instructions
from flask_security.views import _security
from http import HTTPStatus
from werkzeug.datastructures import MultiDict
from .blueprint import frontend, security
from ..decorators import anonymous_user_required
@f... |
1696005 | import random
from os import urandom
from typing import Callable, Tuple
from dataclasses import dataclass
from ecc.curve import Curve, Point
@dataclass
class ElGamal:
curve: Curve
def encrypt(self, plaintext: bytes, public_key: Point,
randfunc: Callable = None) -> Tuple[Point, Point]:
... |
1696047 | import os
import sys
import re
import types
import itertools
import matplotlib.pyplot as plt
import numpy
import scipy.stats
import numpy.ma
import Stats
import Histogram
from CGATReport.Tracker import *
from cpgReport import *
##########################################################################
class replica... |
1696085 | from sources.base.interface import DownloadableSource
from utils import file
from downloaders import BaseDownloader
from sources.base import BaseSource
class TextSource(BaseSource,DownloadableSource):
__source_name__ = "text"
def __init__(self, url, headers, filename,filecontent):
self.url = url
... |
1696091 | import torch
from torch import nn
import numpy as np
import cv2
### FB Global Reasoning Block ###
# From: https://github.com/facebookresearch/GloRe
class GCN(nn.Module):
""" Graph convolution unit (single layer)
"""
def __init__(self, num_state, num_node, bias=False):
super(GCN, self).__init__()
... |
1696101 | from xml.dom import minidom
from .svg_to_axes import FigureLayout, repar, tounit, XMLNS, get_elements_by_attr
import copy
import matplotlib.pyplot as plt
import numpy as np
import pkg_resources
def get_empty_svg_document(tmp_filename=".fifi_tmp.svg"):
"""
Creates basic svg template file and saves it to disk... |
1696133 | FILE = 'tests/__init__.py'
MESSAGE = 'This is a test.'
RESPONSE_DATA = {'status': 1, 'message': 'fail'}
SERVERS_AND_FILES = (
('https://vim.cx', FILE), # PrivateBin 1.3
('https://privatebin.gittermann1.de/', FILE), # PrivateBin 1.2
('https://paste.carrade.eu/', FILE), # PrivateBin 1.1
# ('https://pas... |
1696139 | from adafruit_circuitplayground.express import cpx
import time
while True:
print(cpx.button_a)
time.sleep(0.05)
|
1696176 | import pytest
import os, re, io
import helper
import peeringdb
from peeringdb import cli as _cli
CMD = "peeringdb_test"
client = helper.client_fixture("full")
# Run with config dir
class RunCli:
def __init__(self, c):
self.config_dir = str(c)
def __call__(self, *args):
fullargs = [CMD]
... |
1696198 | import random
class Teacher:
"""
A class to implement a teacher that knows the optimal playing strategy.
Teacher returns the best move at any time given the current state of the game.
Note: things are a bit more hard-coded here, as this was not the main focus of
the exercise so I did not spend as ... |
1696208 | from pathlib import Path
from numpy import array
from manim import *
class VectorAddition(Scene):
def construct(self):
VECT1 = np.array([3, 2, 0])
VECT2 = np.array([2, -1, 0])
VECT1_COLOR = "#b9b28b"
VECT2_COLOR = "#b98b99"
VECT3_COLOR = "#8ba7b9"
vect1 = Line(st... |
1696264 | import argparse
import format_helper
import madlibber
import path_helper
import word_helper
def parse_args():
"""Returns parsed arguments."""
parser = argparse.ArgumentParser()
parser.add_argument(
'-input_words',
type=str,
required=True,
help='The input words to substitute into templat... |
1696275 | from django import forms
from ftp.models import Account
from web.models import VHost
class AccountCreateForm(forms.ModelForm):
password = forms.CharField(widget=forms.widgets.PasswordInput)
vhost = forms.ModelChoiceField(queryset=VHost.objects.all(), empty_label="/", required=False)
class Meta:
model = Account... |
1696288 | import math
from pyjamas.chart import GChartUtil
from pyjamas.chart.GChart import GChart
from pyjamas.chart import AnnotationLocation
from pyjamas.chart import SymbolType
from pyjamas.ui.Button import Button
from pyjamas.ui.FocusPanel import FocusPanel
from pyjamas.ui.Grid import Grid
from pyjamas.ui import KeyboardL... |
1696293 | from typing import Dict, Union
import os
import torch
import tqdm
import onnx
from torch.utils.data import DataLoader
from torchvision.datasets import ImageFolder, ImageNet
from furiosa_sdk_quantizer.evaluator.model_caller import ModelCaller
from furiosa_sdk_quantizer.evaluator.data_loader import random_subset
from f... |
1696303 | import unittest
import sys
from PyQt5.QtWidgets import QApplication, QDialog
from ui import FetchProgressDialog
app = QApplication(sys.argv)
fetch_progress_dialog = QDialog()
fetch_progress_dialog_ui = FetchProgressDialog.Ui_FetchProgressDialog()
fetch_progress_dialog_ui.setupUi(fetch_progress_dialog)
class FetchPr... |
1696306 | import os
import time
import numpy as np
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import ray
from ray.util.sgd import TorchTrainer
from ray.util.sgd.utils import AverageMeterCollection
from ray.util.sgd.torch import TrainingOperator
import dgl
from dgl.data import RedditData... |
1696473 | from django.contrib import admin
from django.db import models
from django_summernote.widgets import SummernoteWidget, SummernoteInplaceWidget
from django_summernote.models import Attachment
from django_summernote.settings import summernote_config
__widget__ = SummernoteWidget if summernote_config['iframe'] \
else ... |
1696487 | from rated_statistic_storage import *
from constraint_item import *
class Constraint(object):
"""Contains the whole constraint with corresponding reactions.
"""
def __init__(
self, name, constraint_root, planned_reaction,
min_reaction_interval, reaction_timeout):
super(Co... |
1696523 | from django.contrib.auth.models import User
from django.core.urlresolvers import reverse
from django.test import TestCase
from post.models import Channel, Question
from post.forms import post_form
class TestPostViews(TestCase):
@classmethod
def setUpTestData(cls):
user = User.objects.create_user(username="usern... |
1696630 | from ...scheme import Scheme
from ..schemeinfo import SchemeInfoDialog
from ...gui import test
class TestSchemeInfo(test.QAppTestCase):
def test_scheme_info(self):
scheme = Scheme(title="A Scheme", description="A String\n")
dialog = SchemeInfoDialog()
dialog.setScheme(scheme)
stat... |
1696649 | from ..filters import run_filters, cheap_filters, all_filters
from ..utils.misc import invert, values_map_to_same_key, one_hot
from ..utils.graph_ops import get_node_cover
from .alldiffs import count_alldiffs
import numpy as np
from functools import reduce
# TODO: count how many isomorphisms each background node parti... |
1696664 | import datetime
import json
from nose.tools import eq_, ok_
import mock
from django.conf import settings
from django.contrib.auth.models import Group
from django.utils import timezone
from django.core.urlresolvers import reverse
from airmozilla.main.models import (
Event,
EventTweet,
Location,
Approv... |
1696679 | from torch import optim
from contextlib import contextmanager
class Trainer:
r"""Abstract base class for training models.
The Trainer class makes it incredibly simple and convinient to train,
monitor, debug and checkpoint entire Deep Learning projects.
Simply define your training loop by
implemen... |
1696733 | import csv
from Bio.Blast import NCBIWWW
from Bio.Blast import NCBIXML
from Bio import SeqIO
import shutil
import re
import os
from collections import defaultdict
from time import sleep
class CalculateReferenceProteomeSimilarity:
def __init__(self, input_file, input_fasta, output_file, match_length=8, species='hum... |
1696745 | import math
import torch
import torch.nn as nn
class PositionEncoding(nn.Module):
"""
Add positional information to input tensor.
:Examples:
>>> model = PositionEncoding(d_model=6, max_len=10, dropout=0)
>>> test_input1 = torch.zeros(3, 10, 6)
>>> output1 = model(test_input1)
... |
1696843 | from utils import youtube_authenticate, get_video_id_by_url, get_channel_id_by_url
def get_comments(youtube, **kwargs):
return youtube.commentThreads().list(
part="snippet",
**kwargs
).execute()
if __name__ == "__main__":
# authenticate to YouTube API
youtube = youtube_authe... |
1696851 | from enum import auto
from functools import lru_cache
from typing import Any, Dict, Optional
import sqlalchemy as sa
from pydantic import validator
from fastapi_auth.fastapi_util.settings.base_api_settings import BaseAPISettings
from fastapi_auth.fastapi_util.util.enums import StrEnum
class DatabaseBackend(StrEnum)... |
1696869 | logs = {
"img": [
"[INFO] Loading input image: {}",
"[ERROR] On '{}': you need to pass the image path!",
"\te.g. --img='Pictures/notNord.jpg'"
],
"out": [
"[INFO] Set output image name: {}",
"[ERROR] On '{}': no output filename specify!",
"\te.g. --out='Pict... |
1696891 | import abc
import typing as t
from .protocols import UserLike
class UserProvider(abc.ABC): # pragma: no cover
"""User provides perform user look ups over data storages.
These classes are consumed by Authenticator instances
and are not designed to be a part of login or logout process."""
async def f... |
1696896 | from collections import OrderedDict
import pytest
from deepspeech.data.alphabet import Alphabet
SYMBOLS = OrderedDict([(symbol, index) for index, symbol in enumerate('abcd')])
@pytest.fixture
def alphabet():
return Alphabet(SYMBOLS.keys())
def test_duplicate_symbol_raise_valuerror():
with pytest.raises(... |
1696920 | import numpy as np
import tools
import warnings
class Alpha():
"""
Docstring for ALPHA.
Alpha is the an influence coefficient matrix
Influence coefficient matrix is a representation of the change of vibration
vector in a measuring point when putting a unit weight on a balancing plane.
"""
... |
1696923 | class Player:
def __init__(
self,
username: str,
player_class,
):
self.username = username
self.invetory = Inventory()
self.player_class = player_class
self.skills = None
self.gender = None
self._count = 0
self.direction... |
1696976 | from __future__ import absolute_import
from __future__ import print_function
import glob
import gc
import numpy as np
from lmatools.stream.subset import coroutine
from lmatools.density_tools import unique_vectors
import logging
log = logging.getLogger(__name__)
log.addHandler(logging.NullHandler())
# ---------------... |
1696981 | import tensorflow as tf
import model as M
bn_training = True
def conv_layers(inp,reuse=False):
global bn_training
with tf.variable_scope('enc',reuse=reuse):
mod = M.Model(inp)
mod.set_bn_training(bn_training)
mod.convLayer(7,16,stride=2,activation=M.PARAM_LRELU,batch_norm=True) #128
mod.convLayer(5,32,str... |
1697069 | import tensorflow as tf
class NodeSequenceTest(tf.test.TestCase):
def test_node_sequence(self):
neighborhood = tf.constant([
[1, 0, 3, -1],
[2, 1, 0, -1],
])
nodes = tf.constant([
[0.5, 0.5, 0.5],
[1.5, 1.5, 1.5],
[2.5, 2.5, 2.5... |
1697101 | import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from matplotlib import gridspec
sns.set_style("whitegrid")
def plot_residuals(predicted_series,
actual_series,
time_vector,
num_training_points,
num_validation_points,
... |
1697124 | import pandas as pd
import numpy as np
from typing import List, Optional
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings("ignore")
class Indices:
"""
Price Technical Indicators
"""
def __init__(
self, df: pd.DataFrame, date_col: str = "date", price_col: str = "price"
... |
1697170 | import torch
import torch.nn.functional as F
def to_tensor(x):
if type(x).__name__ == 'ndarray':
return torch.Tensor(x)
else:
return x
def clipwise_binary_crossentropy(output_dict, target_dict):
'''Weakly labelled loss. The output and target have shape of:
(batch_size, classes_num)
... |
1697175 | from collections import defaultdict
from ..config_new import ID_RESOLVING_APIS
from ..utils.common import getPrefixFromCurie, getValFromCurie
class CurieGroup:
def __init__(self, semanticType, curies):
self.semanticType = semanticType
self.curies = curies
@staticmethod
def _findAPI(seman... |
1697177 | from torch.nn import Sequential, Conv2d, BatchNorm2d, ReLU
from ..utils import RichRepr
class Bottleneck(RichRepr, Sequential):
r"""
A 1x1 convolutional layer, followed by Batch Normalization and ReLU
"""
def __init__(self, in_channels: int, out_channels: int):
super(Bottleneck, self).__init... |
1697211 | import pytest
from brownie import network, AdvancedCollectible
def test_can_create_advanced_collectible(
get_account,
get_vrf_coordinator,
get_keyhash,
get_link_token,
chainlink_fee,
get_seed,
):
# Arrange
if network.show_active() not in ["development"] or "fork" in network.show_active... |
1697233 | import pickle
from blinker._utilities import symbol
def test_symbols():
foo = symbol('foo')
assert foo.name == 'foo'
assert foo is symbol('foo')
bar = symbol('bar')
assert foo is not bar
assert foo != bar
assert not foo == bar
assert repr(foo) == 'foo'
def test_pickled_symbols():
... |
1697279 | import math
class Queue(object):
def __init__(self):
self.__values = []
def enqueue(self, v):
self.__values.insert(0, v)
def dequeue(self):
if len(self.__values) == 0:
return None
else:
return self.__values.pop()
def len(self):
return l... |
1697282 | from ._operation import RingQK, RingAV
from .layers import TransformerSelfAttentionRing
__all__ = ['TransformerSelfAttentionRing', 'RingAV', 'RingQK']
|
1697339 | import abc
import enum
from typing import Any, Dict, List, Tuple, Union
import numpy as np
import pandas as pd
Record = Dict[str, Any]
Records = List[Record]
InputRecords = Union[Records, pd.DataFrame]
DataRecord = Tuple[Dict[str, Union[np.ndarray, float]], ...]
BatchDataRecords = Tuple[Dict[str, np.ndarray], ...]
... |
1697395 | SECRET_KEY = 'tests'
INSTALLED_APPS = [
"drynk",
"drynk.tests",
]
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': 'drynk.sqlite3',
}
}
|
1697402 | import json
import functools
IOS_OSS_APPS_DATASET = "../oss_ios_apps/contents_july_2018.json"
@functools.lru_cache()
def get_project(gh_user, gh_project):
"""Ola."""
project_name = f"{gh_user}/{gh_project}"
datastore = _read_app_dataset()
projects = datastore['projects']
return next(
(proj... |
1697470 | import struct
from typing import Optional
from bxgateway import ont_constants
from bxgateway.messages.ont.ont_message import OntMessage
from bxgateway.messages.ont.ont_message_type import OntMessageType
class VerAckOntMessage(OntMessage):
MESSAGE_TYPE = OntMessageType.VERACK
def __init__(self, magic: Option... |
1697486 | import pytest
import shutil
from pathlib import Path
from click.testing import CliRunner
from bnmutils import ConfigParser
from bnmutils.novelty import cd
from logme.exceptions import LogmeError
from logme.utils import get_logger_config
from logme import __version__
from logme import cli
class TestCli:
@clas... |
1697488 | from .base import *
import dj_database_url
ALLOWED_HOSTS = ['.herokuapp.com']
DEBUG = False
STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles')
# overide database settings
db_from_env = dj_database_url.config(conn_max_age=500)
DATABASES['default'].update(db_from_env) |
1697563 | import ipaddress
import sys
from contextlib import contextmanager
from types import SimpleNamespace
from typing import (
Any,
Awaitable,
Callable,
Dict,
Generator,
Iterable,
Optional,
Set,
cast,
)
import aiohttp
from aiohttp import (
TraceRequestEndParams,
TraceRequestExcept... |
1697576 | import demistomock as demisto
from CommonServerPython import *
from CommonServerUserPython import *
CLI_ADD = "add backup local"
BASH_ADD = '/etc/cli.sh -c "' + CLI_ADD + '"'
def main():
res = []
tbl = []
devices = demisto.get(demisto.args(), 'devices')
devicesBackupStarted = []
devicesBackupErr... |
1697601 | from sqlalchemy.orm.exc import NoResultFound
from flask_rest_jsonapi import ResourceDetail, ResourceList, ResourceRelationship
from flask_rest_jsonapi.exceptions import ObjectNotFound
from commandment.apps.schema import ApplicationManifestSchema, ApplicationSchema, ManagedApplicationSchema
from commandment.apps.models ... |
1697605 | from collections import defaultdict
def count_extra_contrib(sufficient_count, n):
extra = 0
for i in range(sufficient_count):
extra += (n-(i+1))
return extra
for _ in range(int(input())):
n = int(input())
count_of_pattern = defaultdict(int)
non_sufficient_patterns = []
extra = 0
cnt = 0
sufficient_count =... |
1697656 | import random
from adsimulator.utils.principals import get_cn, get_sid_from_rid, get_dn
from adsimulator.utils.users import get_user_timestamp, generate_sid_history
from adsimulator.utils.boolean import generate_boolean_value
from adsimulator.utils.parameters import get_perc_param_value, print_user_generation_parameter... |
1697688 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import sys
import os
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
ROOT_DIR = os.path.dirname(BASE_DIR)
sys.path.append(os.path.join(ROOT_DIR, 'utils'))
from .losses import smoothl1_loss, l1_loss, SigmoidFocalClassificationLo... |
1697696 | def get_job_definition(account, region, container_name, job_def_name, job_param_s3uri_destination, memoryInMB, ncpus,
role_name):
"""
This is the job definition for this sample job.
:param account:
:param region:
:param container_name:
:param job_def_name:
:param memoryInM... |
1697711 | from UE4Parse.BinaryReader import BinaryStream
from UE4Parse.Assets.Objects.FText import FText
class FNavAgentSelectorCustomization:
SupportedDesc: FText
def __init__(self, reader: BinaryStream):
self.SupportedDesc = FText(reader)
|
1697728 | import pandas as pd
from shapely.geometry import LineString, Point
from syspy.spatial import spatial, zoning
from syspy.transitfeed import feed_links
# seconds
def to_seconds(time_string):
return pd.to_timedelta(time_string).total_seconds()
def point_geometry(row):
return Point(row['stop_lon'], row['stop_la... |
1697738 | import pytest
from unittest import mock
from nesta.packages.novelty.lolvelty import lolvelty
def test_lolvelty():
es = mock.MagicMock()
es.count.return_value = {'count': 100}
# Very novel
es.search.return_value = {'hits': {'hits':[{'_score':100},
{'_score'... |
1697752 | from pathlib import Path
from manim import *
class Determinant(Scene):
def construct(self):
text_color = "#333"
vect1_color = "#b98b99"
vect2_color = "#b9b28b"
numberplane = NumberPlane(
background_line_style={
"stroke_opacity": 0.4
}
... |
1697762 | from ctypes import byref, sizeof, c_uint32
from typing import Optional, List, Callable
import gc
from .vimba_object import VimbaObject
from .vimba_exception import VimbaException
from .frame import Frame
from . import vimba_c
SINGLE_FRAME = 'SingleFrame'
CONTINUOUS = 'Continuous'
def _camera_infos() -> List[vimba_... |
1697801 | import FWCore.ParameterSet.Config as cms
process = cms.Process('RERECO')
# this is to avoid the postpathendrun probem with same process name (only with http reader)
process.options = cms.untracked.PSet(
IgnoreCompletely = cms.untracked.vstring('Configuration')
# SkipEvent = cms.untracked.vstring('Configuration... |
1697809 | from typing import Dict, List, Tuple, Union, Any, TypeVar
from scipy.sparse.csr import csr_matrix
from numpy import memmap
from sqlitedict import SqliteDict
from tempfile import mkdtemp
from DocumentFeatureSelection.init_logger import logger
from numpy import ndarray, int32, int64
import pickle
import json
import csv
i... |
1697811 | personas = int(input("¿Cuantas personas hay en su grupo de cena?"))
if personas > 8:
print("Tendran que esperar una mesa")
else:
print("Su mesa esta lista") |
1697821 | from django.conf.urls.defaults import *
urlpatterns = patterns('saved_searches.views',
url(r'^most_recent/$', 'most_recent', name='saved_searches_most_recent'),
url(r'^most_recent/username/(?P<username>[\w\d._-]+)/$', 'most_recent', name='saved_searches_most_recent_by_user'),
url(r'^most_recent/area/(?P<s... |
1697848 | from typing import Any, Dict
from sovereign.sources.lib import Source
from sovereign.config_loader import Loadable
class File(Source):
def __init__(self, config: Dict[str, Any], scope: str = "default"):
super(File, self).__init__(config, scope)
try:
self.path = Loadable.from_legacy_fmt... |
1697856 | import json
import os
import typing
from pathlib import Path
import reseval
###############################################################################
# Get subjective evaluation results
###############################################################################
def results(
name: str,
directory: ... |
1697892 | import tkinter as tk
count=0
def reset():
global count
count=0
def EXIT():
window.destroy()
def counter():
global count
if(count>=10 and count<20):
label2.config(text=str(count),fg='green')
elif(count>=20):
label2.config(text=str(count),fg='red2')
... |
1697921 | class BaseClass:
"""Simple BaseClass with a name."""
def __init__(self, name: str):
self.name = name
def say_hi(self):
print(f"I'm {self.name} of type {type(self)}")
def short_desc(self) -> str:
return f"BaseClass({self.name})"
class ChildClass(BaseClass):
"""Simple chil... |
1697975 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import os
import logging
import argparse
import random
from tqdm import tqdm, trange
import dill
from collections import defaultdict
import numpy as np
import pandas as pd
import torch
from torch.ut... |
1697984 | from bs4 import BeautifulSoup
from datetime import datetime
from threading import Lock
mutex = Lock()
class AdapterXinhua:
def __init__(self):
self.clear()
def clear(self):
self.name = 'xinhua'
self.headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) Appl... |
1697986 | import os
import dill
import numpy as np
def get_function_path(base_path=None, experiment_name=None, make=True):
"""
This function gets the path to where the function is expected to be stored.
Parameters
----------
base_path : str
Path to the directory where the experiments are to be sto... |
1698092 | from PyHook import wait_for_process, on_credential_submit, log
import frida
import sys
hook_process_name = "explorer"
def logger(message):
log(hook_process_name, message)
def wait_for():
hook()
def hook():
try:
logger("Trying To Hook Into Explorer")
session = frida.attach("explorer.ex... |
1698109 | import numpy as np
from scipy.sparse import linalg
def weighted_mean(x, w):
# numpy.average can do the same computation
assert(x.shape == w.shape)
s = w.sum()
if s == 0:
raise ValueError("Sum of weights is zero")
return (x * w).sum() / s
def get_solver_(method, **kwargs):
def lstsq... |
1698138 | import numpy as np
import pandas as pd
import quantipy as qp
import copy
import re
import warnings
from quantipy.core.tools.dp.query import uniquify_list
from quantipy.core.helpers.functions import (
emulate_meta,
cpickle_copy,
get_rules_slicer,
get_rules,
paint_dataframe
)
from quantipy.core.tool... |
1698204 | import sys
import urllib3
import certifi
import re
import os
import random
import time
from json import loads
import socket
from urllib3.contrib.socks import SOCKSProxyManager
from bs4 import BeautifulSoup
from tqdm import tqdm
import asyncio
import aiohttp
import sqlite3
# setup colored output
from colorama import i... |
1698250 | import geopandas as gpd
import networkx as nx
import pandas as pd
import shapely
from shapely.ops import cascaded_union
from syspy.spatial import polygons, spatial
from syspy.syspy_utils import neighbors, pandas_utils, syscolors
from tqdm import tqdm
def compute_coverage_layer(layer, buffer, extensive_cols=[]):
"... |
1698261 | from messagebird.base import Base
from messagebird.call_data import CallData
CALL_STATUS_STARTING = "starting"
CALL_STATUS_ONGOING = "ongoing"
CALL_STATUS_ENDED = "ended"
class Call(Base):
def __init__(self):
self.id = None
self._data = None
@property
def data(self):
return self... |
1698269 | from PIL import Image, ImageStat
import numpy as np
def is_color_image(file, thumb_size=50, MSE_cutoff=140, adjust_color_bias=True):
try:
pil_img = Image.open(file)
except:
print 'Couldn\'t open file %s'%file
return False
np_img = np.array(pil_img)
if len(np_img.shape) > 2 and ... |
1698278 | from __future__ import absolute_import
import inspect
import logging
import warnings
import threading
import lore.env
import lore.estimators
from lore.util import timed, before_after_callbacks
lore.env.require(
lore.dependencies.XGBOOST +
lore.dependencies.SKLEARN
)
import xgboost
logger = logging.getLogge... |
1698282 | import time, os, json, sys
start_time = time.time()
from modules.main import ArgParse
from modules.logging import Logger
from modules import process as k8s
from modules.get_svc_acc import K8sSvcAcc
class ServiceAccount:
def __init__(self, namespace, logger):
self.namespace = namespace
self.logger =... |
1698294 | import torch
# torch.manual_seed(0)
import torch.nn as nn
from modelZoo.resNet import ResNet, Bottleneck, BasicBlock
from modelZoo.DyanOF import creatRealDictionary
from utils import generateGridPoles, gridRing,fista
import numpy as np
def load_preTrained_model(pretrained, newModel):
'load pretrained resnet-X to s... |
1698306 | import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pytest
from SphereVoxelization_fft import compute_2d, compute_3d
import freud
matplotlib.use("agg")
class TestSphereVoxelization:
def test_random_points_2d(self):
width = 100
r_max = 10.0
num_points = 10
... |
1698312 | from __future__ import absolute_import, division, print_function
# LIBTBX_SET_DISPATCHER_NAME iotbx.pdb.split_models
from libtbx.utils import Sorry, Usage, null_out
import os
import sys
master_phil = """
split_models
.short_caption = Split multi-model PDB file
.caption = This utility will separate a multi-model P... |
1698336 | import asyncio
import json
import logging
import random
from contextlib import suppress
import pmdefaults as PM
try:
import aiohttp
from aiohttp import web
except ImportError as e:
web = None
logging.warning("aiohttp in required to start the REST interface, but it is not installed")
try:
resthelp... |
1698339 | from pyhafas import HafasClient
from pyhafas.profile import VSNProfile
def test_vsn_locations_request():
client = HafasClient(VSNProfile())
locations = client.locations(term="Göttingen Bahnhof/ZOB")
assert len(locations) >= 1
|
1698344 | from typing import Callable
import pytest
from tests.taxonomy.conftest import TestDirectory, validate_taxonomy
@pytest.mark.parametrize(
"defect",
[(1, 79), (2, 120), (3, 122), (4, 86), (5, 40)],
)
def test_xbps(defect, defect_path: Callable[[int, int], TestDirectory], gitenv):
index, case = defect
... |
1698357 | import requests, os
import json
is_prod = True
webhook_url = os.environ.get('SLACKBOT_WEBHOOK_URL', '')
def post_health(message):
if not is_prod:
return
r = requests.post(webhook_url, data=json.dumps({"text": message}), headers={'content-type':'application/json'})
return r
|
1698376 | from time import time
import numpy as np
from cd4ml.get_encoder import get_trained_encoder
from cd4ml.logger.fluentd_logging import FluentdLogger
from cd4ml.model_tracking import tracking
from cd4ml.model_tracking.validation_metrics import get_validation_metrics
from cd4ml.utils.problem_utils import Specification
from ... |
1698384 | import numpy as np
import scipy.interpolate as si
def euclidean_distance(a, b):
diff = a - b
return np.sqrt(np.dot(diff, diff))
# source: https://stackoverflow.com/questions/34803197/fast-b-spline-algorithm-with-numpy-scipy
def bspline(cv, n=100, degree=3, periodic=False):
"""Calculate n samples on a bs... |
1698393 | from __future__ import with_statement
import datetime
import sys
import os
try:
from urllib.parse import parse_qsl
except ImportError:
from urlparse import parse_qsl
import requests
import requests_mock
from requests.exceptions import ConnectTimeout
from akismet import Akismet, SpamStatus, AKISMET_CHECK_URL... |
1698403 | from protocols import participant_1_0_0
from protocols import participant_1_0_3
from protocols.migration import BaseMigration
class MigrationParticipants103To100(BaseMigration):
old_model = participant_1_0_3
new_model = participant_1_0_0
def migrate_cancer_participant(self, cancer_participant):
m... |
1698415 | from aiogram.dispatcher.filters.state import State, StatesGroup
class ConfigFlow(StatesGroup):
waiting_for_api_key = State()
class SettingsFlow(StatesGroup):
waiting_for_setting_select = State()
waiting_for_new_key = State()
|
1698468 | from typing import AnyStr, List
from pyre_extensions import safe_json
from backend.common.datafeed_parsers.exceptions import ParserInputException
from backend.common.models.alliance import EventAlliance
from backend.common.models.keys import TeamKey
from backend.common.models.team import Team
class JSONAllianceSele... |
1698507 | MOCK_USERS = [{"email": "<EMAIL>", "salt": "8Fb23mMNHD5Zb8pr2qWA3PE9bH0=", "hashed":
"1736f83698df3f8153c1fbd6ce2840f8aace4f200771a46672635374073cc876cf0aa6a31f780e576578f791b5555b50df46303f0c3a7f2d21f91aa1429ac22e"}]
class MockDBHelper:
def get_user(self, email):
user = [x for x in MOCK_U... |
1698585 | from carriage import Row, X
def test_basic():
assert X.y(Row(x=2, y=3)) == 3
assert X['x'](dict(x=4, y=5)) == 4
assert (X + 3)(5) == 8
assert (X - 2)(6) == 4
assert (X * 3)(4) == 12
assert (X / 2)(9) == 4.5
assert (X // 2)(9) == 4
assert (X % 3)(5) == 2
assert (divmod(X, 3))(5) == ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.