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from flask import current_app as app from .cart_product import Cart_Product class Cart: def __init__(self, id, pid, quantity): self.id = id self.pid = pid self.quantity = quantity @staticmethod def get(id): try: rows = app.db.execute(''' SELECT p.id...
[ "flask.current_app.db.execute" ]
[((997, 1063), 'flask.current_app.db.execute', 'app.db.execute', (['"""\n SELECT *\n FROM Cart\n """'], {}), '("""\n SELECT *\n FROM Cart\n """)\n', (1011, 1063), True, 'from flask import current_app as app\n'), ((278, 650), 'flask.current_app.db.execute', 'app.db.execute', (['...
import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="simple_peewee_flask_webapi", version="1.0.0", author="<NAME>", author_email="<EMAIL>", description="Simple peewee Flask WEB-API", long_description=long_description, lon...
[ "setuptools.find_packages" ]
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#!/usr/bin/python import os import io import sys import json import shutil import pandas import dataLib import datetime # PIL - the Python Image Library, used for bitmap image manipulation. import PIL import PIL.ImageFont import PIL.ImageDraw # ReportLab - used for PDF document generation. import reportlab.lib.units ...
[ "pandas.DataFrame", "PIL.Image.new", "os.makedirs", "pandas.read_csv", "dataLib.loadConfig", "dataLib.yearCohortToGroup", "datetime.datetime", "datetime.datetime.strptime", "datetime.timedelta", "shutil.move", "datetime.datetime.now", "os.listdir" ]
[((1375, 1409), 'dataLib.loadConfig', 'dataLib.loadConfig', (["['dataFolder']"], {}), "(['dataFolder'])\n", (1393, 1409), False, 'import dataLib\n'), ((1606, 1645), 'os.makedirs', 'os.makedirs', (['historyRoot'], {'exist_ok': '(True)'}), '(historyRoot, exist_ok=True)\n', (1617, 1645), False, 'import os\n'), ((1656, 172...
from django.http import HttpResponseRedirect from django.core.urlresolvers import reverse from django.contrib.auth.forms import UserCreationForm from django.shortcuts import render, get_object_or_404 from django.contrib.auth.decorators import login_required from main.forms import SignupForm from django.core.paginator i...
[ "main.models.ClubList.objects.get", "django.core.urlresolvers.reverse", "main.models.ClubList.objects.filter", "django.shortcuts.render", "main.forms.SignupForm", "main.models.ClubList.objects.order_by" ]
[((595, 638), 'main.models.ClubList.objects.order_by', 'ClubList.objects.order_by', (['"""-ClubMemberSum"""'], {}), "('-ClubMemberSum')\n", (620, 638), False, 'from main.models import ClubList\n'), ((650, 704), 'django.shortcuts.render', 'render', (['request', '"""index.html"""', "{'clublists': clublist}"], {}), "(requ...
# Copyright (c) 2020 <NAME> # Licensed under the MIT License """A module that contains caching helpers. """ from functools import update_wrapper __all__ = ["cached"] def cached(func): """Decorator that caches result of method or function. """ cache = {} def wrapper(*args, **kwargs): key =...
[ "functools.update_wrapper" ]
[((542, 571), 'functools.update_wrapper', 'update_wrapper', (['wrapper', 'func'], {}), '(wrapper, func)\n', (556, 571), False, 'from functools import update_wrapper\n')]
from collections import deque import random import rank_based class ReplayBuffer(object): def __init__(self, buffer_size, batch_size=32, learn_start=2000, steps=100000, rand_s=False): self.buffer_size = buffer_size self.num_experiences = 0 self.buffer = deque() self.rand_s = rand_...
[ "random.sample", "rank_based.Experience", "collections.deque" ]
[((285, 292), 'collections.deque', 'deque', ([], {}), '()\n', (290, 292), False, 'from collections import deque\n'), ((548, 575), 'rank_based.Experience', 'rank_based.Experience', (['conf'], {}), '(conf)\n', (569, 575), False, 'import rank_based\n'), ((680, 718), 'random.sample', 'random.sample', (['self.buffer', 'batc...
import json import os from google.oauth2 import service_account from googleapiclient.discovery import build SCOPES = [ "https://www.googleapis.com/auth/spreadsheets", "https://www.googleapis.com/auth/drive", ] credentials = service_account.Credentials.from_service_account_info( json.loads(os.environ["GOOG...
[ "googleapiclient.discovery.build", "json.loads" ]
[((381, 427), 'googleapiclient.discovery.build', 'build', (['"""sheets"""', '"""v4"""'], {'credentials': 'credentials'}), "('sheets', 'v4', credentials=credentials)\n", (386, 427), False, 'from googleapiclient.discovery import build\n'), ((293, 341), 'json.loads', 'json.loads', (["os.environ['GOOGLE_SERVICE_ACCOUNT']"]...
import pytest import numpy as np from spexxy.grid import GridAxis, ValuesGrid @pytest.fixture() def number_grid(): # define grid grid = np.array([ [1, 2, 3, 4, 5], [3, 4, 5, 6, 7], [2, 3, 4, 5, 6], [4, 5, 6, 7, 8] ]) # define axes ax1 = GridAxis(name='x', values=l...
[ "numpy.array", "spexxy.grid.ValuesGrid", "pytest.fixture" ]
[((82, 98), 'pytest.fixture', 'pytest.fixture', ([], {}), '()\n', (96, 98), False, 'import pytest\n'), ((147, 225), 'numpy.array', 'np.array', (['[[1, 2, 3, 4, 5], [3, 4, 5, 6, 7], [2, 3, 4, 5, 6], [4, 5, 6, 7, 8]]'], {}), '([[1, 2, 3, 4, 5], [3, 4, 5, 6, 7], [2, 3, 4, 5, 6], [4, 5, 6, 7, 8]])\n', (155, 225), True, 'im...
from CybORG.Agents import BaseAgent from CybORG.Shared import Results from CybORG.Shared.Actions import PrivilegeEscalate, ExploitRemoteService, DiscoverRemoteSystems, Impact, \ DiscoverNetworkServices, Sleep class B_lineAgent(BaseAgent): def __init__(self): self.action = 0 self.target_ip_addr...
[ "CybORG.Shared.Actions.DiscoverNetworkServices", "CybORG.Shared.Actions.Impact", "CybORG.Shared.Actions.ExploitRemoteService", "CybORG.Shared.Actions.DiscoverRemoteSystems", "CybORG.Shared.Actions.PrivilegeEscalate" ]
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import time from .daemon import Daemon def main(): daemon = Daemon() while True: daemon.tick() files = daemon.get_email_files() for file in files: try: daemon.handle_email(file) except Exception: daemon.on_error() time.s...
[ "time.sleep" ]
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from __future__ import division import json from time import time from random import randint, choice from threading import Timer from tornado.ioloop import IOLoop from tornado.web import Application from tornado.websocket import WebSocketHandler class RepeatedTimer(object): def __init__(self, interval, functio...
[ "threading.Timer", "argparse.ArgumentParser", "json.loads", "random.randint", "tornado.ioloop.IOLoop", "random.choice", "json.dumps", "time.time", "tornado.web.Application" ]
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################################################### # # Script to: # - Load the images and extract the patches # - Define the neural network # - define the training # ################################################## import numpy as np import configparser from keras.utils import multi_gpu_model ...
[ "numpy.random.seed", "tensorflow.zeros_like", "keras.models.Model", "keras.layers.Input", "keras.callbacks.LearningRateScheduler", "keras.layers.concatenate", "sys.setrecursionlimit", "keras.layers.Reshape", "keras.backend.pow", "keras.optimizers.SGD", "keras.backend.flatten", "configparser.Ra...
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#!/usr/bin/env python # -*- coding: utf-8 -*- import argparse import os from loglizer import InvariantsMiner, PCA, IsolationForest, OneClassSVM, LogClustering, LR from loglizer import dataloader, preprocessing def main(): parser = argparse.ArgumentParser() parser.add_argument("--output_dir", metavar="DIR", h...
[ "argparse.ArgumentParser", "loglizer.IsolationForest", "loglizer.InvariantsMiner", "loglizer.LR", "loglizer.preprocessing.FeatureExtractor", "loglizer.dataloader.load_data", "loglizer.PCA", "loglizer.LogClustering", "os.path.expanduser", "loglizer.OneClassSVM" ]
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# # Classes representing available types and their P4 equivalent. # from typing import Dict, List, Tuple import ctypes from functools import lru_cache class KnownType: """ Base class of available types. """ pass class uint8_t(KnownType): def get_p4_type() -> str: return 'bit<8>' def...
[ "ctypes.c_uint8", "ctypes.c_uint16", "functools.lru_cache", "ctypes.c_uint64", "ctypes.c_uint32" ]
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"""Tests for gdrive_sync tasks""" from datetime import datetime import pytest import pytz from gdrive_sync import tasks from gdrive_sync.conftest import LIST_FILE_RESPONSES, LIST_VIDEO_RESPONSES from gdrive_sync.constants import ( DRIVE_API_FILES, DRIVE_FILE_FIELDS, DRIVE_FOLDER_FILES_FINAL, DRIVE_FOL...
[ "gdrive_sync.tasks.transcode_drive_file_video.delay", "gdrive_sync.factories.DriveFileFactory.create_batch", "gdrive_sync.tasks.stream_drive_file_to_s3.delay", "gdrive_sync.tasks.import_website_files.delay", "gdrive_sync.tasks.import_recent_files.delay", "gdrive_sync.factories.DriveApiQueryTrackerFactory....
[((697, 754), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""shared_id"""', "[None, 'testDrive']"], {}), "('shared_id', [None, 'testDrive'])\n", (720, 754), False, 'import pytest\n'), ((756, 822), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""drive_creds"""', '[None, \'{"key": "value"}\']'], ...
# -*- coding: utf-8 -*- from setuptools import setup import os from setuptools import setup, find_packages import versioneer long_description = open("README.md").read() install_requires = [] setup( name="exdir", packages=find_packages(), include_package_data=True, version=versioneer.get_version(), ...
[ "versioneer.get_version", "setuptools.find_packages", "versioneer.get_cmdclass" ]
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from discord.ext import commands from PIL import Image import discord, datetime, re import PIL, shutil, os, random class MineBase: def __init__(self, member): self.grid = [[0 for x in range(12)] for y in range(12)] self.grid_show = [[0 for x in range(12)] for y in range(12)] self.file = f"...
[ "os.remove", "discord.ext.commands.command", "random.randint", "discord.File", "PIL.Image.open", "shutil.copy" ]
[((2463, 2481), 'discord.ext.commands.command', 'commands.command', ([], {}), '()\n', (2479, 2481), False, 'from discord.ext import commands\n'), ((385, 432), 'shutil.copy', 'shutil.copy', (['"""assets/mine/board.png"""', 'self.file'], {}), "('assets/mine/board.png', self.file)\n", (396, 432), False, 'import PIL, shuti...
#!/usr/bin/env python from setuptools import Command, setup import sys class PyPandoc(Command): description = 'Generates the documentation in reStructuredText format.' user_options = [] def initialize_options(self): pass def finalize_options(self): pass def convert(self, infile...
[ "pypandoc.convert" ]
[((415, 446), 'pypandoc.convert', 'pypandoc.convert', (['infile', '"""rst"""'], {}), "(infile, 'rst')\n", (431, 446), False, 'import pypandoc\n')]
import pytest from core import WordsRepository @pytest.mark.parametrize( "input_words,forget_letters,remaining_words", [ ("urger,ribat,anorn,stram,sofar", "ugo", "ribat,stram") ] ) def test_forget_letters(input_words, forget_letters, remaining_words): input_words = tuple(input_words.split(','...
[ "pytest.mark.parametrize", "core.WordsRepository" ]
[((51, 184), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""input_words,forget_letters,remaining_words"""', "[('urger,ribat,anorn,stram,sofar', 'ugo', 'ribat,stram')]"], {}), "('input_words,forget_letters,remaining_words', [(\n 'urger,ribat,anorn,stram,sofar', 'ugo', 'ribat,stram')])\n", (74, 184), Fals...
import os import sys import numpy as np import pandas as pd import matplotlib.pyplot as plt from keras.applications.resnet50 import ResNet50 from keras.applications.inception_v3 import InceptionV3 from keras.applications.xception import Xception # from efficientnet.keras import EfficientNetB3 from keras_preprocessing.i...
[ "keras.applications.xception.Xception", "keras.layers.Dropout", "keras.models.Model", "keras.layers.GlobalAveragePooling2D", "keras.applications.resnet50.ResNet50", "keras.layers.Dense", "keras.layers.Conv2D", "keras.applications.inception_v3.InceptionV3", "keras.layers.MaxPooling2D" ]
[((2085, 2122), 'keras.models.Model', 'Model', (['base_model.input', 'last_Dense_2'], {}), '(base_model.input, last_Dense_2)\n', (2090, 2122), False, 'from keras.models import Model\n'), ((774, 832), 'keras.applications.resnet50.ResNet50', 'ResNet50', ([], {'include_top': 'include_top', 'input_shape': 'input_shape'}), ...
import numpy as np from copy import copy from .base import Simplifier from ... import operations from ...analyzers import SplitAnalysis class ConvertBatchNorm(Simplifier): ANALYSES = {"is_split": SplitAnalysis} def visit_BatchNormalization(self, operation: operations.BatchNormalization): input_op =...
[ "numpy.zeros", "numpy.diag", "copy.copy", "numpy.sqrt" ]
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# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
[ "mindspore.ops.ReduceMean", "mindspore.ops.ReduceMax", "mindspore.nn.Dropout", "mindspore.ops.Identity", "mindspore.nn.Dense" ]
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# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'layouts/base_project_main.ui' # # Created by: PyQt4 UI code generator 4.12.1 # # WARNING! All changes made in this file will be lost! from PyQt4 import QtCore, QtGui try: _fromUtf8 = QtCore.QString.fromUtf8 except AttributeError: d...
[ "PyQt4.QtGui.QWidget", "PyQt4.QtGui.QLabel", "PyQt4.QtGui.QCheckBox", "PyQt4.QtGui.QVBoxLayout", "PyQt4.QtGui.QSizePolicy", "PyQt4.QtGui.QFont", "PyQt4.QtGui.QGroupBox", "PyQt4.QtGui.QApplication.translate", "PyQt4.QtGui.QSlider", "PyQt4.QtGui.QMenu", "PyQt4.QtGui.QDockWidget", "PyQt4.QtGui.QA...
[((467, 531), 'PyQt4.QtGui.QApplication.translate', 'QtGui.QApplication.translate', (['context', 'text', 'disambig', '_encoding'], {}), '(context, text, disambig, _encoding)\n', (495, 531), False, 'from PyQt4 import QtCore, QtGui\n'), ((849, 924), 'PyQt4.QtGui.QSizePolicy', 'QtGui.QSizePolicy', (['QtGui.QSizePolicy.Pre...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Aug 29 14:54:12 2018 @author: maximov """ import torch import torch.nn as nn import torch.utils.data from torch.nn import functional as F from arch.base_network import BaseNetwork from arch.normalization import get_nonspade_norm_layer from arch.archi...
[ "torch.nn.ReflectionPad2d", "torch.nn.functional.avg_pool2d", "torch.nn.Conv2d", "torch.nn.InstanceNorm2d", "torch.cat", "torch.nn.Upsample", "arch.architecture.SPADEResnetBlock", "torch.nn.Linear", "torch.nn.functional.relu", "torch.nn.LeakyReLU" ]
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import logging from pkg.compiler import compile_template logger = logging.getLogger() logger.setLevel(logging.INFO) def lambda_handler(event: dict, context: object) -> dict: # event = { # "requestId": "1234567890", # "fragment": {...} # } ret = event.copy() try: ret["fragment"]...
[ "pkg.compiler.compile_template", "logging.getLogger" ]
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import tensorflow as tf import numpy as np import chess #load the saved model model=tf.keras.models.load_model('openlock_model') #rest explained in nntest.py probmodel=tf.keras.Sequential([ model, tf.keras.layers.Softmax() ]) PieceNum={'p':'0','n':'1','b':'2','r':'3','q':'4','k':'5','.':'6'} def numreprgen(re...
[ "tensorflow.keras.models.load_model", "numpy.argmax", "tensorflow.keras.layers.Softmax", "chess.Board", "chess.BaseBoard" ]
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import json import functools from os import path, mkdir, getcwd from flask import Flask, request from flask_sqlalchemy import SQLAlchemy from sqlalchemy import TypeDecorator, Unicode from sqlalchemy_media import Image, ImageValidator, ImageProcessor, ImageAnalyzer, StoreManager, \ FileSystemStore from sqlalchemy_...
[ "functools.partial", "os.mkdir", "json.loads", "os.getcwd", "flask.Flask", "os.path.exists", "json.dumps", "flask_sqlalchemy.SQLAlchemy", "sqlalchemy_media.ImageProcessor", "sqlalchemy_media.ImageAnalyzer", "sqlalchemy_media.ImageValidator", "os.path.join" ]
[((401, 444), 'os.path.join', 'path.join', (['WORKING_DIR', '"""static"""', '"""avatars"""'], {}), "(WORKING_DIR, 'static', 'avatars')\n", (410, 444), False, 'from os import path, mkdir, getcwd\n'), ((452, 467), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (457, 467), False, 'from flask import Flask, req...
# Copyright (c) Facebook, Inc. and its affiliates. # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import torch.nn as nn import torch.nn.functional as F from foundations import hparams from lottery.desc import LotteryDesc from models import ...
[ "torch.nn.Sequential", "foundations.hparams.ModelHparams", "lottery.desc.LotteryDesc", "foundations.hparams.TrainingHparams", "torch.nn.Conv2d", "torch.nn.CrossEntropyLoss", "torch.nn.BatchNorm2d", "pruning.sparse_global.PruningHparams", "torch.nn.Linear", "torch.nn.functional.relu", "foundation...
[((1672, 1736), 'torch.nn.Conv2d', 'nn.Conv2d', (['(3)', '(32)'], {'kernel_size': '(3)', 'stride': '(1)', 'padding': '(1)', 'bias': '(False)'}), '(3, 32, kernel_size=3, stride=1, padding=1, bias=False)\n', (1681, 1736), True, 'import torch.nn as nn\n'), ((1755, 1773), 'torch.nn.BatchNorm2d', 'nn.BatchNorm2d', (['(32)']...
# Utilities import pickle from math import pi, cos, sin, asin, sqrt def saveFile(filename, data): with open(filename, "wb") as f: pickle.dump(data, f) def loadFile(filename): with open(filename, "rb") as f: return pickle.load(f) def coordToDeg(coord): return coord[0] + coord[1] / 60 + co...
[ "pickle.dump", "math.asin", "math.sqrt", "math.sin", "pickle.load", "math.cos" ]
[((937, 944), 'math.cos', 'cos', (['y1'], {}), '(y1)\n', (940, 944), False, 'from math import pi, cos, sin, asin, sqrt\n'), ((954, 961), 'math.cos', 'cos', (['y2'], {}), '(y2)\n', (957, 961), False, 'from math import pi, cos, sin, asin, sqrt\n'), ((998, 1021), 'math.sqrt', 'sqrt', (['(f1 + f2 * f3 * f4)'], {}), '(f1 + ...
#!/usr/bin/env python3 from navicatGA.selfies_solver import SelfiesGenAlgSolver from navicatGA.score_modifiers import score_modifier from navicatGA.wrappers_selfies import ( sc2smiles, sc2mol_structure, mol_structure2depictions, ) from navicatGA.quantum_wrappers_selfies import sc2gap from navicatGA.wrapper...
[ "navicatGA.wrappers_selfies.sc2mw", "navicatGA.quantum_wrappers_selfies.sc2gap", "navicatGA.wrappers_selfies.sc2smiles", "navicatGA.wrappers_selfies.sc2logp", "navicatGA.wrappers_selfies.mol_structure2depictions", "navicatGA.wrappers_selfies.sc2mol_structure" ]
[((2011, 2052), 'navicatGA.wrappers_selfies.sc2mol_structure', 'sc2mol_structure', (['solver.best_individual_'], {}), '(solver.best_individual_)\n', (2027, 2052), False, 'from navicatGA.wrappers_selfies import sc2smiles, sc2mol_structure, mol_structure2depictions\n'), ((2057, 2106), 'navicatGA.wrappers_selfies.mol_stru...
import madlib for i in range(0, 100): print(madlib.get_madlib())
[ "madlib.get_madlib" ]
[((49, 68), 'madlib.get_madlib', 'madlib.get_madlib', ([], {}), '()\n', (66, 68), False, 'import madlib\n')]
from karabo.simulation.coordinate_helper import east_north_to_long_lat from karabo.simulation.east_north_coordinate import EastNorthCoordinate class Station: def __init__(self, position: EastNorthCoordinate, parent_longitude: float = 0, parent_latitude: float = 0, ...
[ "karabo.simulation.coordinate_helper.east_north_to_long_lat" ]
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import numpy as np import matplotlib.pyplot as plt import timeit import random import math def insertionSort(a): for i in range(1,len(a)): value = a[i] pos = i while (pos > 0 and value < a[pos-1]): a[pos] = a[pos-1] pos = pos-1 a[pos] = value def countingSort(a,max): m = max+1 co...
[ "matplotlib.pyplot.show", "random.randint", "matplotlib.pyplot.plot", "timeit.default_timer", "matplotlib.pyplot.axis", "numpy.append", "numpy.mean", "numpy.random.randint", "numpy.array" ]
[((1790, 1822), 'numpy.random.randint', 'np.random.randint', (['(101)'], {'size': '(128)'}), '(101, size=128)\n', (1807, 1822), True, 'import numpy as np\n'), ((1927, 1939), 'numpy.array', 'np.array', (['[]'], {}), '([])\n', (1935, 1939), True, 'import numpy as np\n'), ((1945, 1957), 'numpy.array', 'np.array', (['[]'],...
from .Const import Const import requests from bs4 import BeautifulSoup from selenium import webdriver from selenium.webdriver.chrome.service import Service from selenium.webdriver.support import expected_conditions as ec from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.common.by import By...
[ "selenium.webdriver.chrome.service.Service", "selenium.webdriver.support.expected_conditions.presence_of_element_located", "selenium.webdriver.ChromeOptions", "requests.get", "bs4.BeautifulSoup", "selenium.webdriver.support.ui.WebDriverWait" ]
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# -*- coding: utf-8 -*- import unittest from openprocurement.auctions.tessel.tests.base import BaseTesselAuctionWebTest from openprocurement.auctions.core.tests.base import snitch from openprocurement.auctions.core.tests.document import ( AuctionDocumentResourceTestMixin, AuctionDocumentWithDSResourceTestMixin...
[ "unittest.main", "openprocurement.auctions.core.tests.base.snitch", "unittest.makeSuite", "unittest.TestSuite" ]
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# This file is part of astro_metadata_translator. # # Developed for the LSST Data Management System. # This product includes software developed by the LSST Project # (http://www.lsst.org). # See the LICENSE file at the top-level directory of this distribution # for details of code ownership. # # Use of this source code...
[ "astropy.coordinates.EarthLocation.from_geodetic", "re.match", "posixpath.join", "astropy.io.fits.open", "astropy.coordinates.Angle", "astropy.coordinates.EarthLocation.of_site" ]
[((1121, 1170), 'posixpath.join', 'posixpath.join', (['CORRECTIONS_RESOURCE_ROOT', '"""CFHT"""'], {}), "(CORRECTIONS_RESOURCE_ROOT, 'CFHT')\n", (1135, 1170), False, 'import posixpath\n'), ((1431, 1447), 'astropy.coordinates.Angle', 'Angle', (['(0 * u.deg)'], {}), '(0 * u.deg)\n', (1436, 1447), False, 'from astropy.coor...
import logging from rich.logging import RichHandler from rich.traceback import install install(max_frames=1) FORMAT = '%(message)s' logging.basicConfig( level='INFO', format=FORMAT, datefmt='[%X]', handlers=[RichHandler(rich_tracebacks=True)] ) log = logging.getLogger('rich')
[ "rich.traceback.install", "rich.logging.RichHandler", "logging.getLogger" ]
[((89, 110), 'rich.traceback.install', 'install', ([], {'max_frames': '(1)'}), '(max_frames=1)\n', (96, 110), False, 'from rich.traceback import install\n'), ((271, 296), 'logging.getLogger', 'logging.getLogger', (['"""rich"""'], {}), "('rich')\n", (288, 296), False, 'import logging\n'), ((227, 260), 'rich.logging.Rich...
# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals from django.conf.urls import url from . import views urlpatterns = [ url( regex=r'^$', view=views.program_list, name='program_list' ), url( regex=r'(?P<program_slug>[-\w]+)/$', view=vi...
[ "django.conf.urls.url" ]
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"""Custom TestCase and helpers for connectmessages tests.""" # -*- coding: utf-8 -*- from django.core.urlresolvers import reverse from django.contrib.auth import get_user_model from django.contrib.messages.storage.fallback import FallbackStorage from django.test import RequestFactory from django.utils.timezone import ...
[ "model_mommy.mommy.make", "django.core.urlresolvers.reverse", "django.test.RequestFactory", "django.utils.timezone.now", "django.contrib.auth.get_user_model", "django.contrib.messages.storage.fallback.FallbackStorage" ]
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from django.urls import include, path from videos.views import manage_videos, manage_videos_search app_name = 'videos' urlpatterns = [ path('videos', manage_videos, name='manage_videos'), path('videos/search', manage_videos_search, name='manage_videos_search') ]
[ "django.urls.path" ]
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# coding=utf-8 from __future__ import absolute_import import logging def init_logging(debug): logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s') if debug: logging.getLogger().setLevel(logging.DEBUG) else: logging.getLogger('eodatasets').setLevel(logging.INFO)
[ "logging.getLogger", "logging.basicConfig" ]
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from typing import Iterable, Sized, Collection, Callable, Tuple from typing import Union, Optional, overload from labml.internal.monitor import monitor_singleton as _internal def clear(): _internal().clear() def func(name, *, is_silent: bool = False, is_timed: bool = True, is_partial...
[ "labml.internal.monitor.monitor_singleton" ]
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import sys from django.shortcuts import render, get_object_or_404 from bleet.models import Bleet from users.models import Follow, Profile from django.contrib.auth.models import User from django.views.generic import ( ListView, DetailView, CreateView, UpdateView, DeleteView, ) from django.contrib.aut...
[ "bleet.models.Bleet.objects.all", "users.models.Follow.objects.filter", "bleet.models.Bleet.objects.filter" ]
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# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import tensorflow as tf import numpy as np import PIL.Image as Image import time import cv2 from pyfirmata import Ar...
[ "tensorflow.train.import_meta_graph", "numpy.argmax", "cv2.waitKey", "tensorflow.Session", "time.sleep", "cv2.VideoCapture", "time.time", "pyfirmata.Arduino", "cv2.setMouseCallback", "cv2.destroyWindow", "PIL.Image.fromarray", "tensorflow.get_default_graph", "cv2.imshow", "cv2.namedWindow"...
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from unittest import TestCase from class_odd_and_prime_number import Number class TestNumber(TestCase): def test_number_init(self): valid_number = Number(5) self.assertEqual(valid_number.value, 5)
[ "class_odd_and_prime_number.Number" ]
[((162, 171), 'class_odd_and_prime_number.Number', 'Number', (['(5)'], {}), '(5)\n', (168, 171), False, 'from class_odd_and_prime_number import Number\n')]
import setuptools with open("README.md", "r", encoding="utf-8") as fh: long_description = fh.read() setuptools.setup( name="shazamio", version="0.0.5", author="dotX12", description="Is a FREE asynchronous library from reverse engineered Shazam API written in Python 3.6+ with asyncio and aiohttp. I...
[ "setuptools.find_packages" ]
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#!/usr/bin/env python # coding: utf-8 # Copyright 2020 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import argparse import errno import filecmp import os import plistlib import shutil import stat import subprocess impo...
[ "os.mkdir", "argparse.ArgumentParser", "os.lchmod", "plistlib.dump", "shutil.rmtree", "filecmp.cmp", "os.path.join", "os.utime", "subprocess.check_call", "os.path.exists", "shutil.copyfile", "stat.S_ISDIR", "stat.S_ISLNK", "stat.S_ISREG", "os.stat", "os.path.basename", "os.listdir", ...
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from .metric import Metric, metric_path import pandas as pd import math class JobMakespanMetric(Metric): def __init__(self, plot, scenarios): super().__init__(plot, scenarios) self.name = "job_makespan" self.x_axis_label = "Job makespan (seconds)" def get_data(self, scenario): ...
[ "math.isnan" ]
[((905, 925), 'math.isnan', 'math.isnan', (['makespan'], {}), '(makespan)\n', (915, 925), False, 'import math\n')]
from sg.StanfordGap import StanfordGap import numpy as np import matplotlib.pyplot as plt from sklearn.cluster import KMeans from sklearn import datasets class StanfordGapDemo(object): def run(self): """ Run the Stanford Gap Statistic Analysis on the iris data set presented in http://sciki...
[ "sklearn.datasets.load_iris", "numpy.random.seed", "matplotlib.pyplot.show", "matplotlib.pyplot.plot", "sklearn.cluster.KMeans", "matplotlib.pyplot.legend", "numpy.zeros", "numpy.arange", "matplotlib.pyplot.xlabel", "sg.StanfordGap.StanfordGap" ]
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import logging import numpy as np import glob from beis_indicators import project_dir from beis_indicators.geo import NutsCoder, LepCoder from beis_indicators.indicators import points_to_indicator, save_indicator from beis_indicators.travel.travel_work_processing import get_travel_work_data import pandas a...
[ "pandas.read_csv", "beis_indicators.indicators.save_indicator", "beis_indicators.travel.travel_work_processing.get_travel_work_data", "beis_indicators.indicators.points_to_indicator", "beis_indicators.geo.LepCoder", "logging.getLogger", "beis_indicators.geo.NutsCoder" ]
[((337, 364), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (354, 364), False, 'import logging\n'), ((484, 506), 'beis_indicators.travel.travel_work_processing.get_travel_work_data', 'get_travel_work_data', ([], {}), '()\n', (504, 506), False, 'from beis_indicators.travel.travel_work_pro...
from collections import defaultdict from os.path import abspath from os.path import expanduser from os.path import isdir from os.path import isfile from os.path import join import sys from types import ModuleType from typing import Any from typing import Callable from typing import DefaultDict from typing import Dict f...
[ "ddtrace.internal.utils.get_argument_value", "os.path.abspath", "ddtrace.internal.logger.get_logger", "sys.meta_path.insert", "os.path.isdir", "typing.cast", "importlib.util.find_spec", "collections.defaultdict", "sys.modules._add_to_meta_path", "os.path.isfile", "sys.modules.values", "sys.met...
[((621, 641), 'ddtrace.internal.logger.get_logger', 'get_logger', (['__name__'], {}), '(__name__)\n', (631, 641), False, 'from ddtrace.internal.logger import get_logger\n'), ((1062, 1109), 'ddtrace.internal.utils.get_argument_value', 'get_argument_value', (['args', 'kwargs', '(3)', '"""mod_name"""'], {}), "(args, kwarg...
#!/usr/bin/env python3 from typing import Optional, Tuple import torch from .. import settings from ..distributions import Delta, MultivariateNormal from ..lazy import DiagLazyTensor, MatmulLazyTensor, SumLazyTensor, lazify from ..module import Module from ..utils import linear_cg from ..utils.broadcasting import _m...
[ "torch.ones_like", "torch.randn_like", "torch.cat", "torch.zeros_like" ]
[((3044, 3081), 'torch.zeros_like', 'torch.zeros_like', (['interp_mean[..., 0]'], {}), '(interp_mean[..., 0])\n', (3060, 3081), False, 'import torch\n'), ((7576, 7598), 'torch.ones_like', 'torch.ones_like', (['zeros'], {}), '(zeros)\n', (7591, 7598), False, 'import torch\n'), ((8373, 8412), 'torch.cat', 'torch.cat', ([...
# Generated by Django 3.0.6 on 2020-06-26 09:42 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('sessions', '0001_initial'), ('core', '0004_auto_20200603_1414'), ] operations = [ migrations.Create...
[ "django.db.models.CharField", "django.db.models.ForeignKey", "django.db.models.EmailField", "django.db.models.AutoField", "django.db.models.DateTimeField" ]
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from . import Loader import pandas as pd class SOFROISLoader(Loader): dataset = 'SOFR' fileglob = 'SOFR_OIS_*.csv' columns = ['Trade Date', 'Exchange Code', 'Currency','Commodity Code', 'Short Description','Long Description', 'Curve Date', 'Offset', 'Discount Factor', 'Fo...
[ "pandas.read_csv" ]
[((813, 848), 'pandas.read_csv', 'pd.read_csv', (['file'], {'low_memory': '(False)'}), '(file, low_memory=False)\n', (824, 848), True, 'import pandas as pd\n')]
#!/usr/bin/python import numpy as np import pylab as plt import seaborn as sns sns.set_context("poster") #with open("traj.dat") as f: # data = f.read() # # data = data.split('\n') # # x = [row.split(' ')[0] for row in data] # y = [row.split(' ')[1] for row in data] # # fig = plt.figure() # # ax1 = f...
[ "pylab.show", "numpy.genfromtxt", "pylab.plot", "pylab.subplot", "pylab.savefig", "pylab.ylim", "pylab.xlabel", "pylab.legend", "seaborn.set_context" ]
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""" This example acts as a keyboard to peer devices. """ # import board import sys import time import adafruit_ble from adafruit_ble.advertising import Advertisement from adafruit_ble.advertising.standard import ProvideServicesAdvertisement from adafruit_ble.services.standard.hid import HIDService from adafruit_ble.s...
[ "sys.stdout.write", "sys.stdin.read", "adafruit_hid.keyboard.Keyboard", "adafruit_ble.services.standard.hid.HIDService", "time.sleep", "adafruit_hid.keyboard_layout_us.KeyboardLayoutUS", "adafruit_ble.BLERadio", "adafruit_ble.advertising.Advertisement", "adafruit_ble.services.standard.device_info.De...
[((514, 526), 'adafruit_ble.services.standard.hid.HIDService', 'HIDService', ([], {}), '()\n', (524, 526), False, 'from adafruit_ble.services.standard.hid import HIDService\n'), ((541, 643), 'adafruit_ble.services.standard.device_info.DeviceInfoService', 'DeviceInfoService', ([], {'software_revision': 'adafruit_ble.__v...
""" Defining standard tensorflow optimizers as modules. """ import tensorflow as tf from deeplearning import module from deeplearning import tf_util as U class SGD(module.Optimizer): ninputs = 1 def __init__(self, name, loss, lr=1e-4, momentum=0.0, clip_norm=None): super().__init__(name, loss) ...
[ "deeplearning.tf_util.flatgrad", "tensorflow.placeholder", "tensorflow.Variable", "tensorflow.train.MomentumOptimizer", "tensorflow.gradients", "tensorflow.train.AdamOptimizer", "tensorflow.clip_by_global_norm", "tensorflow.get_default_session" ]
[((495, 543), 'tensorflow.Variable', 'tf.Variable', (['self.lr'], {'name': '"""lr"""', 'trainable': '(False)'}), "(self.lr, name='lr', trainable=False)\n", (506, 543), True, 'import tensorflow as tf\n'), ((575, 625), 'tensorflow.placeholder', 'tf.placeholder', (['tf.float32'], {'shape': '()', 'name': '"""lr_ph"""'}), "...
'''font.py: Class to manage individual fonts.''' import os import codecs from typing import Dict, Any, Optional from fontTools.ttLib import TTFont from fonty.lib.variants import FontAttribute from fonty.lib.font_name_ids import FONT_NAMEID_FAMILY, FONT_NAMEID_FAMILY_PREFFERED, \ FON...
[ "os.path.abspath", "fontTools.ttLib.TTFont", "os.makedirs", "os.path.basename", "os.path.isdir", "codecs.decode", "os.path.dirname", "os.path.exists", "os.path.isfile", "os.path.splitext", "fonty.lib.install.install_fonts", "os.path.join", "fonty.lib.variants.FontAttribute.parse" ]
[((1406, 1425), 'fonty.lib.install.install_fonts', 'install_fonts', (['self'], {}), '(self)\n', (1419, 1425), False, 'from fonty.lib.install import install_fonts\n'), ((2199, 2229), 'fontTools.ttLib.TTFont', 'TTFont', ([], {'file': 'self.path_to_font'}), '(file=self.path_to_font)\n', (2205, 2229), False, 'from fontTool...
from flask import g, abort, redirect, url_for from app.instances import db from app.models.Post import Post from app.models.Answer import Answer from app.models.PostVote import PostVote from app.models.AnswerVote import AnswerVote # noinspection PyUnresolvedReferences import app.routes.post # noinspection PyUnresolve...
[ "app.models.PostVote.PostVote", "app.instances.db.session.commit", "flask.abort", "app.models.Answer.Answer.query.filter_by", "app.models.Post.Post.query.filter_by", "app.models.AnswerVote.AnswerVote.query.filter_by", "app.models.AnswerVote.AnswerVote", "app.instances.db.session.add", "app.models.Po...
[((553, 563), 'flask.abort', 'abort', (['(404)'], {}), '(404)\n', (558, 563), False, 'from flask import g, abort, redirect, url_for\n'), ((914, 924), 'flask.abort', 'abort', (['(404)'], {}), '(404)\n', (919, 924), False, 'from flask import g, abort, redirect, url_for\n'), ((2092, 2102), 'flask.abort', 'abort', (['(401)...
from keras.models import load_model import numpy as np from encoding import encode from encoding import decode model = load_model('Model-0.1.hf') post_title = input("What do you want to know from u/rogersimon10? \n") post_title = "What’s the worst thing you’ve eaten out of politeness?" encoded_title = np.array(encode...
[ "keras.models.load_model", "encoding.decode", "encoding.encode" ]
[((120, 146), 'keras.models.load_model', 'load_model', (['"""Model-0.1.hf"""'], {}), "('Model-0.1.hf')\n", (130, 146), False, 'from keras.models import load_model\n'), ((512, 534), 'encoding.decode', 'decode', (['encoded_answer'], {}), '(encoded_answer)\n', (518, 534), False, 'from encoding import decode\n'), ((314, 34...
import os import sys import numpy as np import pytest from matchms import Spectrum from spec2vec import Spec2Vec from spec2vec import SpectrumDocument path_root = os.path.dirname(os.getcwd()) sys.path.insert(0, os.path.join(path_root, "matchmsextras")) from matchmsextras.library_search import library_matching def te...
[ "matchmsextras.library_search.library_matching", "os.getcwd", "spec2vec.SpectrumDocument", "numpy.array", "pytest.approx", "os.path.join", "numpy.all" ]
[((180, 191), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (189, 191), False, 'import os\n'), ((212, 252), 'os.path.join', 'os.path.join', (['path_root', '"""matchmsextras"""'], {}), "(path_root, 'matchmsextras')\n", (224, 252), False, 'import os\n'), ((1240, 1554), 'matchmsextras.library_search.library_matching', 'libr...
#!/usr/bin/env python # -*- coding: utf-8 -*- """ Unit Tests __author__: <NAME>, <NAME>, <NAME> """ import os import sys import unittest import numpy as np from scipy.io import loadmat sys.path.append(".") from inferactively.distributions import Categorical, Dirichlet # nopep8 class TestDirichlet(unittest.TestCa...
[ "sys.path.append", "unittest.main", "numpy.array_equal", "numpy.log", "scipy.io.loadmat", "inferactively.distributions.Dirichlet", "os.getcwd", "numpy.isclose", "numpy.array", "numpy.random.rand" ]
[((189, 209), 'sys.path.append', 'sys.path.append', (['"""."""'], {}), "('.')\n", (204, 209), False, 'import sys\n'), ((5509, 5524), 'unittest.main', 'unittest.main', ([], {}), '()\n', (5522, 5524), False, 'import unittest\n'), ((368, 379), 'inferactively.distributions.Dirichlet', 'Dirichlet', ([], {}), '()\n', (377, 3...
from sqladmin.helpers import secure_filename def test_secure_filename(monkeypatch): assert secure_filename("My cool movie.mov") == "My_cool_movie.mov" assert secure_filename("../../../etc/passwd") == "etc_passwd" assert ( secure_filename("i contain cool \xfcml\xe4uts.txt") == "i_contain_co...
[ "sqladmin.helpers.secure_filename" ]
[((97, 133), 'sqladmin.helpers.secure_filename', 'secure_filename', (['"""My cool movie.mov"""'], {}), "('My cool movie.mov')\n", (112, 133), False, 'from sqladmin.helpers import secure_filename\n'), ((168, 206), 'sqladmin.helpers.secure_filename', 'secure_filename', (['"""../../../etc/passwd"""'], {}), "('../../../etc...
import os, sys, time, re import cv2 import deeptool sameImages= [] cachedImages = None def isSameImage(imghist, checkhist): ret = cv2.compareHist(imghist, checkhist, 0) ret2 = cv2.compareHist(imghist, checkhist, 1) ret3 = cv2.compareHist(imghist, checkhist, 2) ret4 = cv2.compareHist(imghist, checkhis...
[ "os.unlink", "os.path.isdir", "cv2.calcHist", "deeptool.listDir", "time.time", "cv2.imread", "sys.stdout.flush", "cv2.compareHist", "cv2.resize", "re.compile" ]
[((137, 175), 'cv2.compareHist', 'cv2.compareHist', (['imghist', 'checkhist', '(0)'], {}), '(imghist, checkhist, 0)\n', (152, 175), False, 'import cv2\n'), ((187, 225), 'cv2.compareHist', 'cv2.compareHist', (['imghist', 'checkhist', '(1)'], {}), '(imghist, checkhist, 1)\n', (202, 225), False, 'import cv2\n'), ((237, 27...
# -*- coding: utf-8 -*- """ Created on Thu Nov 23 14:54:35 2017 @author: user """ from __future__ import unicode_literals from __future__ import print_function from __future__ import division from __future__ import absolute_import from typing import Any from typing import Dict from typing import List ...
[ "rasa_nlu.tokenizers.Token", "yaha.Cuttor", "sys.setdefaultencoding" ]
[((630, 661), 'sys.setdefaultencoding', 'sys.setdefaultencoding', (['"""utf-8"""'], {}), "('utf-8')\n", (652, 661), False, 'import sys\n'), ((798, 806), 'yaha.Cuttor', 'Cuttor', ([], {}), '()\n', (804, 806), False, 'from yaha import Cuttor\n'), ((1689, 1707), 'rasa_nlu.tokenizers.Token', 'Token', (['word', 'start'], {}...
from models import * from utils import * from tensorboard_logger import configure, log_value import os try: os.makedirs('../train_logs') except OSError: pass vgg19_exc = VGG19_extractor(torchvision.models.vgg19(pretrained=True)) vgg19_exc = vgg19_exc.cuda() E1 = Encoder(n_res_blocks=10) D1 = Decoder(n_res_bl...
[ "tensorboard_logger.log_value", "os.makedirs" ]
[((113, 141), 'os.makedirs', 'os.makedirs', (['"""../train_logs"""'], {}), "('../train_logs')\n", (124, 141), False, 'import os\n'), ((4121, 4160), 'tensorboard_logger.log_value', 'log_value', (['"""L2_term"""', 'mean_L2_term', 'eph'], {}), "('L2_term', mean_L2_term, eph)\n", (4130, 4160), False, 'from tensorboard_logg...
import torch import math class Node: def __init__(self, state, probs, value, length, moves, terminal = False): self.state = state self.moves = torch.nonzero(moves) self.P = probs[self.moves].view(-1) self.P = self.P / self.P.sum() self.value = value self.length = len...
[ "torch.zeros", "torch.argmax", "torch.nonzero" ]
[((164, 184), 'torch.nonzero', 'torch.nonzero', (['moves'], {}), '(moves)\n', (177, 184), False, 'import torch\n'), ((402, 438), 'torch.zeros', 'torch.zeros', (['size'], {'dtype': 'torch.int32'}), '(size, dtype=torch.int32)\n', (413, 438), False, 'import torch\n'), ((458, 475), 'torch.zeros', 'torch.zeros', (['size'], ...
# Third-party Libraries from flask_restful import Resource, reqparse import pyvo from astropy.io.votable import parse class Search(Resource): def __init__(self) -> None: super().__init__() self.service = pyvo.dal.TAPService("http://voparis-tap-planeto.obspm.fr/tap") def get(self, database): ...
[ "flask_restful.reqparse.RequestParser", "pyvo.dal.TAPService" ]
[((226, 288), 'pyvo.dal.TAPService', 'pyvo.dal.TAPService', (['"""http://voparis-tap-planeto.obspm.fr/tap"""'], {}), "('http://voparis-tap-planeto.obspm.fr/tap')\n", (245, 288), False, 'import pyvo\n'), ((552, 576), 'flask_restful.reqparse.RequestParser', 'reqparse.RequestParser', ([], {}), '()\n', (574, 576), False, '...
# -*- coding: utf-8 -*- ################################################################################ # | # # | ______________________________________________________________ # # | :~8a.`~888a:::::::::::::::88......88:::::::::...
[ "pysqlite2.dbapi2.connect", "resources.lib.modules.control.makeFile", "hashlib.md5", "time.time" ]
[((5827, 5861), 'resources.lib.modules.control.makeFile', 'control.makeFile', (['control.dataPath'], {}), '(control.dataPath)\n', (5843, 5861), False, 'from resources.lib.modules import control\n'), ((5873, 5902), 'pysqlite2.dbapi2.connect', 'db.connect', (['control.cacheFile'], {}), '(control.cacheFile)\n', (5883, 590...
import torch from utils.model_utils import * #Class conditional loglikelihood! def elbo_recon(prediction,target): error = (prediction - target).view(prediction.size(0), -1) error = error ** 2 error = torch.sum(error, dim=-1) return error def calculate_ELBO(model,real_images): with torch.no_grad():...
[ "torch.logsumexp", "torch.stack", "torch.cat", "torch.no_grad", "torch.sum", "torch.log", "torch.tensor" ]
[((213, 237), 'torch.sum', 'torch.sum', (['error'], {'dim': '(-1)'}), '(error, dim=-1)\n', (222, 237), False, 'import torch\n'), ((304, 319), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (317, 319), False, 'import torch\n'), ((728, 743), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (741, 743), False, 'imp...
import pytest from docs_src.async_constructor import main @pytest.mark.anyio("asyncio") async def test_async_constructor() -> None: await main()
[ "docs_src.async_constructor.main", "pytest.mark.anyio" ]
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from glob import glob import cv2 import os import sys import yaml import matplotlib as mpl import numpy as np from skimage.io import imread import matplotlib.pyplot as plt from ellipses import LSqEllipse # The code is pulled from https://github.com/bdhammel/least-squares-ellipse-fitting import time # This annotation s...
[ "numpy.polyfit", "numpy.argmax", "numpy.argmin", "matplotlib.pyplot.figure", "yaml.safe_load", "os.path.join", "matplotlib.pyplot.close", "os.path.exists", "ellipses.LSqEllipse", "matplotlib.pyplot.subplots", "skimage.io.imread", "matplotlib.pyplot.show", "os.path.basename", "numpy.float",...
[((1337, 1365), 'os.path.basename', 'os.path.basename', (['image_path'], {}), '(image_path)\n', (1353, 1365), False, 'import os\n'), ((8092, 8104), 'matplotlib.pyplot.figure', 'plt.figure', ([], {}), '()\n', (8102, 8104), True, 'import matplotlib.pyplot as plt\n'), ((9034, 9045), 'sys.exit', 'sys.exit', (['(0)'], {}), ...
import numpy as np from VariableUnittest import VariableUnitTest from gwlfe.Output.AvAnimalNSum import AnimalN class TestAnimalN(VariableUnitTest): def test_AnimalN(self): z = self.z np.testing.assert_array_almost_equal( AnimalN.AnimalN_f(z.NYrs, z.NGPctManApp, z.GrazingAnimal_0, z.Nu...
[ "gwlfe.Output.AvAnimalNSum.AnimalN.AnimalN", "gwlfe.Output.AvAnimalNSum.AnimalN.AnimalN_f" ]
[((256, 649), 'gwlfe.Output.AvAnimalNSum.AnimalN.AnimalN_f', 'AnimalN.AnimalN_f', (['z.NYrs', 'z.NGPctManApp', 'z.GrazingAnimal_0', 'z.NumAnimals', 'z.AvgAnimalWt', 'z.AnimalDailyN', 'z.NGAppNRate', 'z.Prec', 'z.DaysMonth', 'z.NGPctSoilIncRate', 'z.GRPctManApp', 'z.GRAppNRate', 'z.GRPctSoilIncRate', 'z.NGBarnNRate', 'z...
import numpy as np from math import log10 from math import sqrt import time import networkx as nx import matplotlib.pyplot as plt import pydot import csv class Graph(object): def __init__(self): self.root = None #root/source node is the start of the graph/tree and multicast source self.nodes = [] ...
[ "csv.writer", "numpy.zeros", "pydot.Dot", "math.log10", "pydot.Edge" ]
[((11302, 11331), 'pydot.Dot', 'pydot.Dot', ([], {'graph_type': '"""graph"""'}), "(graph_type='graph')\n", (11311, 11331), False, 'import pydot\n'), ((15441, 15472), 'numpy.zeros', 'np.zeros', (['(200, 200)'], {'dtype': '"""f"""'}), "((200, 200), dtype='f')\n", (15449, 15472), True, 'import numpy as np\n'), ((15965, 15...
#!/usr/bin/env python # -*- coding: utf-8 -*- import ytu def test_is_youtube(): tests = [ ('http://youtu.be/zoLVUxKCWhY', True), ('http://www.youtube.com/watch?v=VvRC0wxM-yM', True), ('http://wwwwwwyoutube.com/watch?v=VvRC0wxM-yM', False), ('http://example.com/zoLVUxKCWhY', False) ...
[ "ytu.is_youtube", "ytu.video_id" ]
[((362, 382), 'ytu.is_youtube', 'ytu.is_youtube', (['t[0]'], {}), '(t[0])\n', (376, 382), False, 'import ytu\n'), ((2048, 2066), 'ytu.video_id', 'ytu.video_id', (['t[0]'], {}), '(t[0])\n', (2060, 2066), False, 'import ytu\n')]
import mock import unittest import dbt.adapters import dbt.flags as flags from pyhive import hive from dbt.adapters.spark import SparkAdapter import agate from .utils import config_from_parts_or_dicts, inject_adapter class TestSparkAdapter(unittest.TestCase): def setUp(self): flags.STRICT_MODE = True ...
[ "dbt.adapters.spark.SparkAdapter", "mock.patch.object" ]
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from rest_framework import permissions from drf_yasg.views import get_schema_view from drf_yasg import openapi ShemaView = get_schema_view( openapi.Info( title='Multauth Example API', default_version='v1', description='Authentication flow: email, password and passcode (using Google Authenticator...
[ "drf_yasg.openapi.Info" ]
[((146, 333), 'drf_yasg.openapi.Info', 'openapi.Info', ([], {'title': '"""Multauth Example API"""', 'default_version': '"""v1"""', 'description': '"""Authentication flow: email, password and passcode (using Google Authenticator or similar app)"""'}), "(title='Multauth Example API', default_version='v1',\n descriptio...
# -*- coding: utf-8 -*- """ Created on Wed Nov 4 00:22:32 2020 @author: <NAME> """ import os import copy from typing import Union, Any try: import simplejson as json except ImportError: import json from .plugins.base_file import BaseFilePlugin, _info from .exceptions.file_exceptions impo...
[ "copy.deepcopy", "os.path.exists", "os.path.splitext", "os.path.join", "os.listdir" ]
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#!/usr/bin/python3 # driver_trips.py: summarize miles per driver and show a list for each # driver of the trips they took. # Two approaches are demonstrated: # - Two queries. First query retrieves the summary values, second the # list entries. Print the list entries, preceding the list for each # driver with the...
[ "cookbook.connect" ]
[((589, 607), 'cookbook.connect', 'cookbook.connect', ([], {}), '()\n', (605, 607), False, 'import cookbook\n')]
# Generated by Django 3.1.6 on 2021-02-12 07:40 import django.core.validators from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Region',...
[ "django.db.models.CharField", "django.db.models.ForeignKey", "django.db.models.PositiveIntegerField", "django.db.models.AutoField", "django.db.models.DecimalField", "django.db.models.DateField" ]
[((365, 458), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (381, 458), False, 'from django.db import migrations, models\...
from unicodedata import normalize def normalizar(texto: str) -> str: """ Normalize um texto qualquer. Substitui os caracteres especiais do texto. Exemplo: >>> normalizar(' AçúcAR ') 'acucar' """ texto = normalize('NFKD', texto) texto = texto.encode('iso-8859-1', 'ignore').decode(...
[ "unicodedata.normalize" ]
[((239, 263), 'unicodedata.normalize', 'normalize', (['"""NFKD"""', 'texto'], {}), "('NFKD', texto)\n", (248, 263), False, 'from unicodedata import normalize\n')]
import multiprocessing as mp import itertools QUEUE = mp.Queue() class Routine(mp.Process): def __init__(self, number: int, *args, **kwargs): mp.Process.__init__(self, *args, **kwargs) self.number = number def target(self, number: int) -> int: return 2 * number def run(self): result = self.target(s...
[ "multiprocessing.Process.__init__", "multiprocessing.Queue" ]
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import subprocess import json def main(set_path): for (problem_id, line) in enumerate(open(set_path).readlines()): if line.strip() == "": continue problem_id = problem_id + 1 submission_id, globalist_source_problem = line.split(' ') globalist_source_problem = int(globa...
[ "json.dump", "subprocess.run", "fire.Fire" ]
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import cv2 import matplotlib.pyplot as plt import numpy as np from functions_feat_extraction import image_to_features from project_5_utils import stitch_together def draw_labeled_bounding_boxes(img, labeled_frame, num_objects): """ Starting from labeled regions, draw enclosing rectangles in the original colo...
[ "cv2.rectangle", "functions_feat_extraction.image_to_features", "cv2.imshow", "project_5_utils.stitch_together", "numpy.copy", "cv2.cvtColor", "numpy.max", "numpy.int", "matplotlib.pyplot.subplots", "cv2.resize", "matplotlib.pyplot.show", "cv2.waitKey", "numpy.min", "numpy.concatenate", ...
[((1030, 1068), 'numpy.zeros', 'np.zeros', ([], {'shape': '(h, w)', 'dtype': 'np.uint8'}), '(shape=(h, w), dtype=np.uint8)\n', (1038, 1068), True, 'import numpy as np\n'), ((1393, 1455), 'cv2.threshold', 'cv2.threshold', (['heatmap', 'threshold', '(255)'], {'type': 'cv2.THRESH_BINARY'}), '(heatmap, threshold, 255, type...
import os from mpl_toolkits import mplot3d from matplotlib import cm import matplotlib.pyplot as plt import pandas as pd def plot_3d(data, x, y, z): ax = plt.axes(projection="3d") ax.plot_trisurf(df[x], df[y], df[z], cmap=cm.Blues) ax.set_xticks(df[x].values) ax.set_yticks(df[y].values) ax.set_xl...
[ "matplotlib.pyplot.show", "matplotlib.pyplot.axes", "pandas.read_csv", "os.path.dirname", "matplotlib.pyplot.figure" ]
[((160, 185), 'matplotlib.pyplot.axes', 'plt.axes', ([], {'projection': '"""3d"""'}), "(projection='3d')\n", (168, 185), True, 'import matplotlib.pyplot as plt\n'), ((446, 497), 'pandas.read_csv', 'pd.read_csv', (['"""../data/csv/calculation.csv"""'], {'sep': '""";"""'}), "('../data/csv/calculation.csv', sep=';')\n", (...
from factory import Faker from factory.django import DjangoModelFactory class IntegerInputDefinitionFactory(DjangoModelFactory): key = Faker("pystr", min_chars=3, max_chars=50) required = Faker("pybool") description = Faker("sentence") min_value = Faker("pyint", min_value=-20, max_value=-10) max_v...
[ "factory.Faker" ]
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# Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Provides the web interface for changing internal_only property of a Bot.""" import logging from google.appengine.api import taskqueue from google.appeng...
[ "dashboard.common.stored_object.Get", "google.appengine.api.taskqueue.add", "dashboard.models.anomaly.Anomaly.GetAlertsForTest", "dashboard.common.datastore_hooks.SetPrivilegedRequest", "dashboard.common.utils.OldStyleTestKey", "dashboard.models.graph_data.TestMetadata.query", "logging.info", "dashboa...
[((1456, 1492), 'logging.info', 'logging.info', (['"""MASTERS: %s"""', 'masters'], {}), "('MASTERS: %s', masters)\n", (1468, 1492), False, 'import logging\n'), ((2562, 2600), 'dashboard.common.datastore_hooks.SetPrivilegedRequest', 'datastore_hooks.SetPrivilegedRequest', ([], {}), '()\n', (2598, 2600), False, 'from das...
import json import ueimporter.version as version def test_ueimporter_json_with_tag_will_succeed(): version_dict = { 'GitReleaseTag': '4.27.1-release' } assert version.UEImporterJson( version_dict).git_release_tag == '4.27.1-release' def test_ueimporter_json_without_key_will_yield_empty_...
[ "ueimporter.version.UEImporterJson", "ueimporter.version.from_git_release_tag", "ueimporter.version.from_build_version_json", "json.dumps" ]
[((678, 714), 'ueimporter.version.UEImporterJson', 'version.UEImporterJson', (['version_dict'], {}), '(version_dict)\n', (700, 714), True, 'import ueimporter.version as version\n'), ((1638, 1714), 'json.dumps', 'json.dumps', (["{'MajorVersion': '4', 'MinorVersion': '27', 'PatchVersion': '1'}"], {}), "({'MajorVersion': ...
#################### # ES-DOC CIM Questionnaire # Copyright (c) 2015 ES-DOC. All rights reserved. # # University of Colorado, Boulder # http://cires.colorado.edu/ # # This project is distributed according to the terms of the MIT license [http://www.opensource.org/licenses/MIT]. #################### __author_...
[ "django.core.urlresolvers.reverse", "Q.questionnaire.q_utils.FuzzyInt", "ipdb.set_trace" ]
[((2621, 2637), 'ipdb.set_trace', 'ipdb.set_trace', ([], {}), '()\n', (2635, 2637), False, 'import ipdb\n'), ((2006, 2068), 'django.core.urlresolvers.reverse', 'reverse', (['"""project"""'], {'kwargs': "{'project_name': 'current_project'}"}), "('project', kwargs={'project_name': 'current_project'})\n", (2013, 2068), Fa...
import argparse import csv def findCategory(status): # Received state if "Fingerprint Fee Was Received" in status: return 1 elif "Expedite Request Denied" in status: return 1 elif "Case Was Received" in status: return 1 elif "Case Was Reopened" in status: return 1 ...
[ "csv.writer", "csv.reader", "argparse.ArgumentParser" ]
[((3411, 3436), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (3434, 3436), False, 'import argparse\n'), ((3714, 3753), 'csv.reader', 'csv.reader', (['inputcsvfile'], {'delimiter': '""","""'}), "(inputcsvfile, delimiter=',')\n", (3724, 3753), False, 'import csv\n'), ((3774, 3853), 'csv.writer'...
import json import pandas as pd import plotly.express as px import dash import dash_bootstrap_components as dbc import dash_core_components as dcc import dash_html_components as html from dash.dependencies import Input, Output from urllib.request import urlopen app = dash.Dash(external_stylesheets=[dbc.t...
[ "json.load", "dash.Dash", "dash_core_components.DatePickerSingle", "pandas.read_csv", "dash_html_components.Div", "urllib.request.urlopen", "dash_core_components.RadioItems", "dash_bootstrap_components.Button", "dash.dependencies.Input", "dash_html_components.P", "dash_core_components.Graph", ...
[((283, 337), 'dash.Dash', 'dash.Dash', ([], {'external_stylesheets': '[dbc.themes.BOOTSTRAP]'}), '(external_stylesheets=[dbc.themes.BOOTSTRAP])\n', (292, 337), False, 'import dash\n'), ((763, 935), 'dash_core_components.RadioItems', 'dcc.RadioItems', ([], {'id': '"""datatype"""', 'options': "[{'label': 'Infection Rate...
from __future__ import annotations import threading import numpy as np from astropy.coordinates import SkyCoord import astropy.units as u from typing import Tuple, List import random from pyobs.object import Object from pyobs.utils.enums import MotionStatus class SimTelescope(Object): """A simulated telescope o...
[ "numpy.radians", "threading.RLock", "random.gauss", "astropy.coordinates.SkyCoord", "pyobs.object.Object.__init__", "numpy.sqrt" ]
[((1494, 1532), 'pyobs.object.Object.__init__', 'Object.__init__', (['self', '*args'], {}), '(self, *args, **kwargs)\n', (1509, 1532), False, 'from pyobs.object import Object\n'), ((2538, 2555), 'threading.RLock', 'threading.RLock', ([], {}), '()\n', (2553, 2555), False, 'import threading\n'), ((4115, 4153), 'astropy.c...
# -*- coding: utf-8 -*- import random import scrapy from scrapy import Request from ip_proxies.spiders.base import BaseSpider from ip_proxies.items import IpProxiesItem from ip_proxies.settings import TEST_URLS, LOG_FILE class JiangxianliSpider(BaseSpider): name = 'jiangxianli' # allowed_domains = ['jiangxian...
[ "random.choice", "ip_proxies.settings.LOG_FILE.replace", "ip_proxies.items.IpProxiesItem", "scrapy.Request" ]
[((429, 473), 'ip_proxies.settings.LOG_FILE.replace', 'LOG_FILE.replace', (['"""log/"""', 'f"""log/{name}__"""', '(1)'], {}), "('log/', f'log/{name}__', 1)\n", (445, 473), False, 'from ip_proxies.settings import TEST_URLS, LOG_FILE\n'), ((819, 834), 'ip_proxies.items.IpProxiesItem', 'IpProxiesItem', ([], {}), '()\n', (...
# coding: utf-8 """ Main commands available for flatisfy. """ from __future__ import absolute_import, print_function, unicode_literals import collections import logging import os import flatisfy.filters from flatisfy import database from flatisfy import email from flatisfy.models import flat as flat_model from flatis...
[ "flatisfy.web.app.get_app", "flatisfy.fetch.load_flats_from_db", "flatisfy.filters.metadata.init", "flatisfy.fetch.fetch_details", "flatisfy.email.send_notification", "collections.defaultdict", "flatisfy.fetch.fetch_flats", "os.utime", "flatisfy.database.init_db", "os.path.join", "flatisfy.model...
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import uvicorn from fastapi import FastAPI, Depends from sqlalchemy.orm import declarative_base, sessionmaker from fastapi_quickcrud import CrudMethods from fastapi_quickcrud import crud_router_builder from fastapi_quickcrud import sqlalchemy_to_pydantic from fastapi_quickcrud.misc.memory_sql import sync_memory_db ap...
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############################################################################## # # Copyright (c) 2009 Zope Foundation and Contributors. # All Rights Reserved. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOF...
[ "relstorage.tests.mock.Mock", "relstorage.tests.MockCursor" ]
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r""" Definition ---------- The scattering intensity $I(q)$ is calculated as .. math:: I(q) = \begin{cases} A q^{-m1} + \text{background} & q <= q_c \\ C q^{-m2} + \text{background} & q > q_c \end{cases} where $q_c$ = the location of the crossover from one slope to the other, $A$ = the scaling coeffi...
[ "numpy.empty", "numpy.errstate", "numpy.power" ]
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#!/usr/bin/env python # # manage.py 用于启动程序以及其他的程序任务 import os # from flask import Flask # from flask_sqlalchemy import SQLAlchemy from flask_script import Manager from flask_migrate import Migrate, MigrateCommand from app import app, db from flask_debugtoolbar import DebugToolbarExtension app.config.from_object(os.en...
[ "flask_script.Manager", "flask_migrate.Migrate", "flask_debugtoolbar.DebugToolbarExtension", "app.app.config.from_object" ]
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import ShuntingYard_RE import ThompsonConstruct def runTests(): # List of ["Regular Expression", ["Strings"...]] # (Infix Regular Expressions) tests = [ ["(a.b|b*)", ["", "ab", "b", "bb", "a"]], ["a.(b.b)*.a", ["aa", "bb", "abba", "aba"]], ["1.(0.0)*.1", ["11",...
[ "ThompsonConstruct.toNFA", "ShuntingYard_RE.toPostfix" ]
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import os import pickle from googleapiclient.discovery import build from google_auth_oauthlib.flow import InstalledAppFlow from google.auth.transport.requests import Request from googleapiclient.errors import HttpError SCOPES = ['https://www.googleapis.com/auth/calendar.events', 'https://www.googleap...
[ "pickle.dump", "google.auth.transport.requests.Request", "os.path.exists", "pickle.load", "google_auth_oauthlib.flow.InstalledAppFlow.from_client_secrets_file" ]
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