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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import unittest from hiveengine.tokens import Tokens class Testcases(unittest.TestCase): def test_tokens(self): tokens = Tokens() self.assertTrue(tok...
[ "hiveengine.tokens.Tokens" ]
[((284, 292), 'hiveengine.tokens.Tokens', 'Tokens', ([], {}), '()\n', (290, 292), False, 'from hiveengine.tokens import Tokens\n')]
"""Loss layers for keypoints that can be inserted to modules""" import torch import torch.nn as nn __all__ = ['WeightedMSELoss', 'HMFocalLoss'] def _sigmoid(x): y = torch.clamp(x.sigmoid_(), min=1e-4, max=1-1e-4) return y class WeightedMSELoss(nn.Module): """Weighted MSE loss layer""" def __init__(se...
[ "torch.log", "torch.pow" ]
[((877, 905), 'torch.pow', 'torch.pow', (['(1 - gt)', 'self.beta'], {}), '(1 - gt, self.beta)\n', (886, 905), False, 'import torch\n'), ((926, 941), 'torch.log', 'torch.log', (['pred'], {}), '(pred)\n', (935, 941), False, 'import torch\n'), ((944, 975), 'torch.pow', 'torch.pow', (['(1 - pred)', 'self.alpha'], {}), '(1 ...
import unittest from github_network import GithubNetwork class Test_GithubNetwork(unittest.TestCase): def setUp(self): pass if __name__ == '__main__': unittest.main()
[ "unittest.main" ]
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- from .policies import * from .objects import * class BaseAgent(Object): ''' QTable: Q Table state: state of agent last_state: last state init_state: init. state ''' env = None n_steps = 0 total_reward = 0 def next_state(self, act...
[ "pandas.DataFrame", "pickle.load", "pickle.dump", "pathlib.Path" ]
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from py_compile import _get_default_invalidation_mode import threading, queue, random from requests_futures.sessions import FuturesSession import discum class banclass: def __init__(self, user, guild, channel): self.user = user self.guild = guild self.channel = channel d...
[ "requests_futures.sessions.FuturesSession", "discum.Client", "threading.Thread", "queue.Queue", "random.randint" ]
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# requirements.txt: # pyro 1.6.0 # torch 1.8.0 import pyro from pyro.distributions import Normal,Gamma,InverseGamma,Bernoulli,Poisson import matplotlib.pyplot as plt # import pyro.poutine as poutine pyro.set_rng_seed(101) def normal_density_estimation(obs, N): assert obs is None or N==obs.shape[0] loc = pyro....
[ "matplotlib.pyplot.show", "pyro.distributions.Gamma", "pyro.set_rng_seed", "pyro.distributions.Normal", "pyro.plate" ]
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from orders.forms import OrderUpdateForm from django.urls import path from orders import views app_name = 'orders' urlpatterns = [ path('place/<int:sid>/<int:oid>', views.CreateOrder.as_view(), name='place'), path('recommend/<str:plid>', views.Recommend.recommendation_algo, name='recommend'), path(...
[ "orders.views.CreateOrder.as_view", "orders.views.MyOrders.as_view", "django.urls.path", "orders.views.OrderInvoice.as_view", "orders.views.OrderDetails.as_view" ]
[((217, 305), 'django.urls.path', 'path', (['"""recommend/<str:plid>"""', 'views.Recommend.recommendation_algo'], {'name': '"""recommend"""'}), "('recommend/<str:plid>', views.Recommend.recommendation_algo, name=\n 'recommend')\n", (221, 305), False, 'from django.urls import path\n'), ((522, 590), 'django.urls.path'...
#!/usr/bin/env python import numpy as np import tensorflow as tf train_X = np.linspace(-1, 1, 100) train_Y = 2 * train_X + np.random.randn(*train_X.shape) * 0.33 + 10 X = tf.placeholder("float") Y = tf.placeholder("float") w = tf.Variable(0.0, name="weight") b = tf.Variable(0.0, name="bias") cost_op = tf.square(Y -...
[ "tensorflow.initialize_all_variables", "tensorflow.Variable", "tensorflow.placeholder", "tensorflow.Session", "tensorflow.train.GradientDescentOptimizer", "numpy.linspace", "numpy.random.randn", "tensorflow.mul" ]
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"""Meteo-France generic test utils.""" import pytest from tests.async_mock import patch @pytest.fixture(autouse=True) def patch_requests(): """Stub out services that makes requests.""" patch_client = patch("homeassistant.components.meteo_france.meteofranceClient") patch_weather_alert = patch( "ho...
[ "pytest.fixture", "tests.async_mock.patch" ]
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import json from enum import Enum from asgiref.sync import async_to_sync from channels.generic.websocket import WebsocketConsumer from channels.layers import get_channel_layer class MessageType(Enum): ERROR = (0,) WARNING = (1,) INFO = (2,) SUCCESS = 3 def log(message, log_var, log_level): chan...
[ "json.dumps", "asgiref.sync.async_to_sync", "channels.layers.get_channel_layer" ]
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from serif.theory.enumerated_type import MentionType from serif.theory.mention import Mention from serif.theory.parse import Parse from serif.theory.serif_sequence_theory import SerifSequenceTheory from serif.xmlio import _SimpleAttribute, _ReferenceAttribute, _ChildTheoryElementList class MentionSet(SerifSequenceThe...
[ "serif.theory.mention.Mention", "serif.xmlio._SimpleAttribute", "serif.xmlio._ChildTheoryElementList", "serif.xmlio._ReferenceAttribute" ]
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from django.conf.urls import url, include from django.contrib import admin from django.conf import settings from django.conf.urls.static import static from django.views.generic import RedirectView urlpatterns = [ url(r'^$', RedirectView.as_view(url='http://127.0.0.1:8000/login/')), url(r'^admin/', admin.site.u...
[ "django.conf.urls.static.static", "django.conf.urls.include", "django.conf.urls.url", "django.views.generic.RedirectView.as_view" ]
[((292, 323), 'django.conf.urls.url', 'url', (['"""^admin/"""', 'admin.site.urls'], {}), "('^admin/', admin.site.urls)\n", (295, 323), False, 'from django.conf.urls import url, include\n'), ((593, 656), 'django.conf.urls.static.static', 'static', (['settings.STATIC_URL'], {'document_root': 'settings.STATIC_ROOT'}), '(s...
#!/usr/bin/env python3 import argparse import sys from ._const import AnsiBGColor, AnsiFGColor, AnsiStyle from ._truecolor import tcolor def parse_option() -> argparse.Namespace: parser = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter) parser.add_argument("string", help="strin...
[ "argparse.ArgumentParser" ]
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# Copyright (c) OpenMMLab. All rights reserved. import copy import pytest import torch from mmcv import Config from numpy.testing import assert_almost_equal from mmpose.datasets import DATASETS def test_NVGesture_dataset(): dataset = 'NVGestureDataset' dataset_info = Config.fromfile( 'configs/_base...
[ "mmpose.datasets.DATASETS.get", "numpy.testing.assert_almost_equal", "torch.tensor", "pytest.raises", "copy.deepcopy", "mmcv.Config.fromfile", "torch.zeros" ]
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import base64 import gws import gws.common.auth.method import gws.common.auth.error import gws.types as t # @TODO support WWW-Authenticate at some point class Config(t.WithType): """HTTP-basic authorization options""" secure: bool = True #: use only with SSL class Object(gws.common.auth.method.Object):...
[ "gws.as_bytes", "gws.common.auth.error.LoginNotFound" ]
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# Generated by Django 3.1.5 on 2021-01-11 12:21 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('pictures', '0001_initial'), ] operations = [ migrations.AddField( model_name='image', name='image', fiel...
[ "django.db.models.ImageField" ]
[((322, 375), 'django.db.models.ImageField', 'models.ImageField', ([], {'default': '"""jpg"""', 'upload_to': '"""images/"""'}), "(default='jpg', upload_to='images/')\n", (339, 375), False, 'from django.db import migrations, models\n')]
import operator import threading import functools import itertools import contextlib import collections import numpy as np from ..autoray import ( get_lib_fn, infer_backend, get_dtype_name, register_function, astype, ) _EMPTY_DICT = {} class LazyArray: """A lazy array representing a shaped...
[ "itertools.chain", "networkx.draw_networkx_nodes", "matplotlib.colors.to_rgb", "numpy.arange", "networkx.DiGraph", "functools.wraps", "numpy.max", "matplotlib.pyplot.close", "threading.get_ident", "opt_einsum.parser.parse_einsum_input", "functools.reduce", "numpy.log2", "matplotlib.pyplot.sh...
[((20196, 20365), 'collections.defaultdict', 'collections.defaultdict', (['(lambda : materialize_identity)', '{LazyArray: materialize_larray, tuple: materialize_tuple, list:\n materialize_list, dict: materialize_dict}'], {}), '(lambda : materialize_identity, {LazyArray:\n materialize_larray, tuple: materialize_tu...
#-*- coding:utf-8 -*- import urllib.request import ssl from lxml import etree url = 'https://movie.douban.com/top250' context = ssl.SSLContext(ssl.PROTOCOL_TLSv1_1) def fetch_page(url): response = urllib.request.urlopen(url, context=context) return response def parse(url): response = fetch_page(url) ...
[ "ssl.SSLContext", "lxml.etree.HTML" ]
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import re def is_url(possible_url): regex = re.compile(r'[-a-zA-Z0-9@:%._\+~#=]{2,256}\.[a-z]{2,6}\b([-a-zA-Z0-9@:%_\+.~#?&//=]*)') if re.search(regex, possible_url): return True else: return False def message_to_upper(message): words = message.split() rage_message = '' for ...
[ "re.search", "re.compile" ]
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# Generated by Django 3.2.5 on 2021-09-20 13:38 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('payment', '0005_subscription'), ] operations = [ migrations.AddField( model_name='subscription', name='customer_id',...
[ "django.db.models.CharField" ]
[((339, 410), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(200)', 'null': '(True)', 'verbose_name': '"""Customer ID"""'}), "(max_length=200, null=True, verbose_name='Customer ID')\n", (355, 410), False, 'from django.db import migrations, models\n')]
""" Copy of the find command. Missing lots of args """ import argparse import os import glob import sys def main(): """ Main find functionality """ parser = argparse.ArgumentParser() parser.add_argument('dir', type=str, default='/usr/local', nargs='?', help='Path to director...
[ "os.path.exists", "glob.glob", "argparse.ArgumentParser", "sys.exit" ]
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import time S = ")()())" S1 = "()(()" S2 = "(()()()" S3 = "()()" def solution(s): if len(s) <= 1: return 0 left = 0 right = 0 max_length = 0 for i in range(len(s)): if s[i] == ')': right += 1 else: left += 1 if left == right: max...
[ "time.time" ]
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# Copyright (C) 2007-2010 by <NAME> # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distrib...
[ "logging.getLogger", "logging.NullHandler", "socket.getfqdn", "time.sleep", "os.utime", "datetime.datetime.now", "random.random", "os.unlink", "os.getpid", "os.stat", "datetime.timedelta", "random.randint", "os.link" ]
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"""This module contains classes of graphoelements. These graphoelements can be generated by the package "detect". """ from copy import deepcopy class Graphoelement: """Class containing all the events of one type in one dataset. Attributes ---------- chan_name : ndarray (dtype='U') list of c...
[ "copy.deepcopy" ]
[((685, 699), 'copy.deepcopy', 'deepcopy', (['self'], {}), '(self)\n', (693, 699), False, 'from copy import deepcopy\n')]
# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from datetime import date from dateutil import rrule from decimal import Decimal as D import mock from django.test import TestCase from ralph_sc...
[ "ralph_scrooge.models.ServiceEnvironment.objects.all", "dateutil.rrule.rrule", "ralph_scrooge.plugins.cost.pricing_service.PricingServicePlugin._get_service_extra_cost", "ralph_scrooge.models.TeamCost", "ralph_scrooge.tests.utils.factory.UsageTypeFactory", "ralph_scrooge.plugins.cost.pricing_service.Prici...
[((914, 932), 'datetime.date', 'date', (['(2013)', '(10)', '(10)'], {}), '(2013, 10, 10)\n', (918, 932), False, 'from datetime import date\n'), ((954, 971), 'datetime.date', 'date', (['(2013)', '(10)', '(1)'], {}), '(2013, 10, 1)\n', (958, 971), False, 'from datetime import date\n'), ((991, 1009), 'datetime.date', 'dat...
import cv2 as cv import numpy as np img = cv.imread('/home/praveen/Desktop/Python/Deep Learning/Open CV/Resources/Photos/cats.jpg') cv.imshow('cats',img) blank=np.zeros(img.shape,dtype='uint8') cv.imshow('blank',blank) gray=cv.cvtColor(img,cv.COLOR_BGR2GRAY) cv.imshow('gray',gray) blur = cv.GaussianBlur(gray,(5,5),...
[ "cv2.drawContours", "cv2.threshold", "cv2.Canny", "cv2.imshow", "numpy.zeros", "cv2.waitKey", "cv2.cvtColor", "cv2.findContours", "cv2.GaussianBlur", "cv2.imread" ]
[((43, 142), 'cv2.imread', 'cv.imread', (['"""/home/praveen/Desktop/Python/Deep Learning/Open CV/Resources/Photos/cats.jpg"""'], {}), "(\n '/home/praveen/Desktop/Python/Deep Learning/Open CV/Resources/Photos/cats.jpg'\n )\n", (52, 142), True, 'import cv2 as cv\n'), ((133, 155), 'cv2.imshow', 'cv.imshow', (['"""ca...
from gpiozero import TrafficLights, Button from time import sleep tl1 = TrafficLights(13, 19, 26) tl2 = TrafficLights(21, 20, 16) tl3 = TrafficLights(10, 9, 11) tl4 = TrafficLights(7, 8, 25) cross1 = TrafficLights(2, 3, 4) cross2 = TrafficLights(18, 15, 14) btn = Button(5) def pressed(): print("Don't push the but...
[ "time.sleep", "gpiozero.Button", "gpiozero.TrafficLights" ]
[((73, 98), 'gpiozero.TrafficLights', 'TrafficLights', (['(13)', '(19)', '(26)'], {}), '(13, 19, 26)\n', (86, 98), False, 'from gpiozero import TrafficLights, Button\n'), ((105, 130), 'gpiozero.TrafficLights', 'TrafficLights', (['(21)', '(20)', '(16)'], {}), '(21, 20, 16)\n', (118, 130), False, 'from gpiozero import Tr...
# 11/11/18 # Copy files from a CSV named files_map.csv to indicated paths and names. import os import shutil import errno import csv import sys if not os.path.isfile('file_map.csv'): print('Please create a file named file_map.csv in the current directory.') sys.exit() with open('file_map.csv', 'r') as f: ...
[ "shutil.copy2", "os.path.isfile", "os.path.dirname", "sys.exit", "csv.reader" ]
[((153, 183), 'os.path.isfile', 'os.path.isfile', (['"""file_map.csv"""'], {}), "('file_map.csv')\n", (167, 183), False, 'import os\n'), ((268, 278), 'sys.exit', 'sys.exit', ([], {}), '()\n', (276, 278), False, 'import sys\n'), ((327, 370), 'csv.reader', 'csv.reader', (['f'], {'delimiter': '""","""', 'quotechar': '"""\...
import os import re from pathlib import Path from typing import Dict, List, Tuple, Match, Optional, Set import matplotlib.pyplot as plt import pandas as pd import seaborn as sns from matplotlib.axes import Axes from matplotlib.figure import Figure from artificial_bias_experiments.evaluation.confidence_comparison.df_u...
[ "artificial_bias_experiments.evaluation.confidence_comparison.df_utils.get_df_diffs_between_true_conf_and_confidence_estimators_melted", "re.compile", "kbc_pul.data_structures.rule_wrapper.RuleWrapper.get_columns_header_without_amie", "artificial_bias_experiments.evaluation.confidence_comparison.df_utils.Colu...
[((1668, 1694), 'seaborn.set', 'sns.set', ([], {'style': '"""whitegrid"""'}), "(style='whitegrid')\n", (1675, 1694), True, 'import seaborn as sns\n'), ((1720, 1782), 're.compile', 're.compile', (['"""s_prop([0-1]\\\\.?[0-9]*)_ns_prop([0-1]\\\\.?[0-9]*)"""'], {}), "('s_prop([0-1]\\\\.?[0-9]*)_ns_prop([0-1]\\\\.?[0-9]*)'...
from setuptools import find_packages, setup from disturbia.version import VERSION with open("README.md", encoding="utf-8") as readme_file: long_description = readme_file.read() setup( name="disturbia", author="<NAME>", description="Library for set of simple methods regarding distribution.", long...
[ "setuptools.find_packages" ]
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# -*- coding: utf-8 -*- # Author: <NAME> <<EMAIL>> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is...
[ "PyQt5.QtWidgets.QDialog.__init__", "PyQt5.QtCore.pyqtSignal", "logging.getLogger", "logging.basicConfig" ]
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# --- # jupyter: # jupytext: # cell_markers: region,endregion # formats: ipynb,py:light # text_representation: # extension: .py # format_name: light # format_version: '1.4' # jupytext_version: 1.1.1 # kernelspec: # display_name: Python 3 # language: python # name: pyt...
[ "sklearn.preprocessing.LabelEncoder", "pandas.read_csv", "sklearn.neighbors.KNeighborsClassifier", "matplotlib.pyplot.annotate", "numpy.array", "nltk.corpus.stopwords.words", "sklearn.feature_extraction.text.CountVectorizer", "gensim.models.Word2Vec.load", "IPython.display.Image", "numpy.asarray",...
[((1526, 1660), 'pandas.read_csv', 'pd.read_csv', (['"""../twitter_data/train2017.tsv"""'], {'sep': '"""\t+"""', 'escapechar': '"""\\\\"""', 'engine': '"""python"""', 'names': "['ID_1', 'ID_2', 'Label', 'Text']"}), "('../twitter_data/train2017.tsv', sep='\\t+', escapechar='\\\\',\n engine='python', names=['ID_1', 'I...
#!/usr/bin/env python import sys import rospy import rosbag from scipy.interpolate import interp1d import matplotlib import matplotlib.pylab as plt matplotlib.rcParams['mathtext.fontset'] = 'custom' matplotlib.rcParams['mathtext.rm'] = 'Bitstream Vera Sans' matplotlib.rcParams['mathtext.it'] = 'Bitstream Vera Sans:i...
[ "matplotlib.pylab.figure", "matplotlib.pylab.title", "matplotlib.pylab.xlabel", "scipy.interpolate.interp1d", "rosbag.Bag", "matplotlib.pylab.show", "matplotlib.pylab.plot", "matplotlib.pylab.close", "matplotlib.pylab.ylabel" ]
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import numpy as np import scipy.fftpack as fftpack import audio_dspy as adsp def tf2minphase(h, normalize=True): """Converts a transfer function to minimum phase Parameters ---------- h : ndarray Numpy array containing the original transfer function Returns ------- h_min : ndarra...
[ "numpy.mean", "numpy.abs", "audio_dspy.normalize", "numpy.fft.fft", "numpy.log", "numpy.exp", "numpy.linspace", "numpy.fft.ifft" ]
[((964, 977), 'numpy.fft.fft', 'np.fft.fft', (['h'], {}), '(h)\n', (974, 977), True, 'import numpy as np\n'), ((986, 1014), 'numpy.linspace', 'np.linspace', (['(0)', '(2 * np.pi)', 'N'], {}), '(0, 2 * np.pi, N)\n', (997, 1014), True, 'import numpy as np\n'), ((1033, 1060), 'numpy.exp', 'np.exp', (['(-1.0j * (N / 2) * w...
import tensorflow as tf a = tf.constant(120, name="a") b = tf.constant(130, name="b") c = tf.constant(140, name="c") v = tf.Variable(0, name="v" ) calc_op = a + b + c assign_op = tf.assign(v, calc_op) session = tf.Session() session.run(assign_op) o = session.run(v) print(o)
[ "tensorflow.assign", "tensorflow.Session", "tensorflow.constant", "tensorflow.Variable" ]
[((28, 54), 'tensorflow.constant', 'tf.constant', (['(120)'], {'name': '"""a"""'}), "(120, name='a')\n", (39, 54), True, 'import tensorflow as tf\n'), ((59, 85), 'tensorflow.constant', 'tf.constant', (['(130)'], {'name': '"""b"""'}), "(130, name='b')\n", (70, 85), True, 'import tensorflow as tf\n'), ((90, 116), 'tensor...
import os import sys from random import randrange from azure.servicebus import ServiceBusClient from azure.servicebus import Message from azure.servicebus.common.constants import ReceiveSettleMode def get_live_servicebus_config(): config = {} config['hostname'] = os.environ['SERVICE_BUS_HOSTNAME'] config[...
[ "azure.servicebus.ServiceBusClient" ]
[((550, 724), 'azure.servicebus.ServiceBusClient', 'ServiceBusClient', ([], {'service_namespace': "sb_config['hostname']", 'shared_access_key_name': "sb_config['key_name']", 'shared_access_key_value': "sb_config['access_key']", 'debug': '(False)'}), "(service_namespace=sb_config['hostname'],\n shared_access_key_name...
import time from io import BytesIO from multiprocessing import Process,Pipe import threading class mp4frag(threading.Thread): ''' Creates a stream transform for piping a fmp4 (fragmented mp4) from ffmpeg. Can be used to generate a fmp4 m3u8 HLS playlist and compatible file fragments. Can also be used for storing p...
[ "threading.Thread.__init__", "multiprocessing.Pipe", "time.time", "time.sleep" ]
[((1732, 1763), 'threading.Thread.__init__', 'threading.Thread.__init__', (['self'], {}), '(self)\n', (1757, 1763), False, 'import threading\n'), ((2855, 2872), 'multiprocessing.Pipe', 'Pipe', ([], {'duplex': '(True)'}), '(duplex=True)\n', (2859, 2872), False, 'from multiprocessing import Process, Pipe\n'), ((3265, 328...
"""Load config from disk.""" def obtain_config(logging): """Import YAML based configs.""" import yaml import sys try: with open('data/config.yaml', 'r') as myconfig: config = yaml.load(myconfig.read(), Loader=yaml.FullLoader) except FileNotFoundError: from utils.create_...
[ "utils.create_config.create_config", "sys.exit" ]
[((429, 444), 'utils.create_config.create_config', 'create_config', ([], {}), '()\n', (442, 444), False, 'from utils.create_config import TEMPLATE, create_config\n'), ((453, 464), 'sys.exit', 'sys.exit', (['(1)'], {}), '(1)\n', (461, 464), False, 'import sys\n'), ((592, 603), 'sys.exit', 'sys.exit', (['(1)'], {}), '(1)...
#!/usr/bin/env python # -*- coding: utf-8 -*- """ API for proxy """ from core import exceptions from core.web import WebHandler from service.proxy.proxy import proxy_srv from service.proxy.serializers import ProxySerializer from utils import log as logger from utils.routes import route from utils.tools import subdic...
[ "core.exceptions.ValidationError", "service.proxy.serializers.ProxySerializer", "utils.tools.subdict", "service.proxy.proxy.proxy_srv.query", "service.proxy.proxy.proxy_srv.new_proxy", "service.proxy.proxy.proxy_srv.keys_by_dict", "core.exceptions.NotFound", "utils.log.exception", "utils.routes.rout...
[((420, 441), 'utils.routes.route', 'route', (['"""/api/proxy/$"""'], {}), "('/api/proxy/$')\n", (425, 441), False, 'from utils.routes import route\n'), ((2285, 2313), 'utils.routes.route', 'route', (['"""/api/proxy/report/$"""'], {}), "('/api/proxy/report/$')\n", (2290, 2313), False, 'from utils.routes import route\n'...
from flask_restx import Resource, Namespace # https://flask-restx.readthedocs.io/en/latest/quickstart.html from core.mcq_generator import McqGenerator import os import copy from db import DRVideoNotFound from db.factory import create_repository from settings import REPOSITORY_NAME, REPOSITORY_SETTINGS # DB repository...
[ "flask_restx.Namespace", "db.factory.create_repository", "core.mcq_generator.McqGenerator" ]
[((323, 378), 'db.factory.create_repository', 'create_repository', (['REPOSITORY_NAME', 'REPOSITORY_SETTINGS'], {}), '(REPOSITORY_NAME, REPOSITORY_SETTINGS)\n', (340, 378), False, 'from db.factory import create_repository\n'), ((397, 472), 'flask_restx.Namespace', 'Namespace', (['"""mcq_generator"""'], {'description': ...
from infobip.clients import send_multiple_textual_sms_advanced from infobip.api.model.sms.mt.send.textual.SMSAdvancedTextualRequest import SMSAdvancedTextualRequest from infobip.api.model.sms.mt.send.SMSData import SMSData from infobip.api.model.sms.mt.send.IsFlash import IsFlash from infobip.api.model.sms.Destinat...
[ "infobip.api.model.sms.mt.send.IsFlash.IsFlash", "infobip.api.model.sms.mt.send.textual.SMSAdvancedTextualRequest.SMSAdvancedTextualRequest", "infobip.clients.send_multiple_textual_sms_advanced", "infobip.api.model.sms.Destination.Destination", "infobip.api.model.sms.mt.send.SMSData.SMSData" ]
[((400, 449), 'infobip.clients.send_multiple_textual_sms_advanced', 'send_multiple_textual_sms_advanced', (['configuration'], {}), '(configuration)\n', (434, 449), False, 'from infobip.clients import send_multiple_textual_sms_advanced\n'), ((460, 473), 'infobip.api.model.sms.Destination.Destination', 'Destination', ([]...
import os import argparse import json import logging import traceback from flask import Flask, redirect, request, jsonify, render_template from pymongo import MongoClient from telegram import Bot dir_path = os.path.dirname(os.path.realpath(__file__)) # Logging logger = logging.getLogger() logger.setLevel(logging.INF...
[ "logging.getLogger", "flask.render_template", "argparse.ArgumentParser", "flask.Flask", "logging.Formatter", "os.urandom", "telegram.Bot", "os.path.realpath", "json.load", "pymongo.MongoClient", "traceback.print_exc" ]
[((273, 292), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (290, 292), False, 'import logging\n'), ((336, 398), 'logging.Formatter', 'logging.Formatter', (['"""%(asctime)s - %(levelname)s - %(message)s"""'], {}), "('%(asctime)s - %(levelname)s - %(message)s')\n", (353, 398), False, 'import logging\n'), (...
import pytest from radix import Bin, Num def test_2s_compl(): n1 = Bin(-13) assert n1.twos_compl() == '10011' n2 = Bin(19) assert n2.twos_compl() == '010011' n3 = Bin(-10.75) assert n3.twos_compl() == '10101.01' def test_1s_compl(): n1 = Bin(-25) assert n1.ones_compl() == '10011...
[ "radix.Bin.from_Num", "radix.Bin", "pytest.raises", "radix.Num" ]
[((75, 83), 'radix.Bin', 'Bin', (['(-13)'], {}), '(-13)\n', (78, 83), False, 'from radix import Bin, Num\n'), ((132, 139), 'radix.Bin', 'Bin', (['(19)'], {}), '(19)\n', (135, 139), False, 'from radix import Bin, Num\n'), ((189, 200), 'radix.Bin', 'Bin', (['(-10.75)'], {}), '(-10.75)\n', (192, 200), False, 'from radix i...
#!/usr/bin/env python3 import argparse import json import os from pathlib import Path FILENAME = "latest.json" def main(): parser = argparse.ArgumentParser() parser.add_argument("source", help="Path to directory of JSONs") parser.add_argument("destination", help="Path to destination JSON") args = par...
[ "os.listdir", "argparse.ArgumentParser", "pathlib.Path", "json.load", "json.dump" ]
[((139, 164), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (162, 164), False, 'import argparse\n'), ((352, 369), 'pathlib.Path', 'Path', (['args.source'], {}), '(args.source)\n', (356, 369), False, 'from pathlib import Path\n'), ((414, 433), 'os.listdir', 'os.listdir', (['dirname'], {}), '(di...
import sys sys.path.append("..") from .Mesure import * from Ordonnancement import * import numpy as np from scipy import stats class EvalIRModel: """Evaluation d'un modèle d'appariement avec une mesure d'evaluation. ----------------------------------------------------- Parameters: - model : modè...
[ "numpy.square", "numpy.array", "numpy.sum", "scipy.stats.ttest_ind", "sys.path.append" ]
[((11, 32), 'sys.path.append', 'sys.path.append', (['""".."""'], {}), "('..')\n", (26, 32), False, 'import sys\n'), ((2481, 2514), 'scipy.stats.ttest_ind', 'stats.ttest_ind', (['scores1', 'scores2'], {}), '(scores1, scores2)\n', (2496, 2514), False, 'from scipy import stats\n'), ((1952, 1967), 'numpy.array', 'np.array'...
from api.dataset.models import DataSchema, Dataset def verify_settings(model, p_key, settings): details = eval(model).get(p_key) for key, setting in settings.items(): print(getattr(details, key), setting) setting = setting if setting else None assert getattr(details, key) == setting ...
[ "api.dataset.models.Dataset", "api.dataset.models.DataSchema", "api.dataset.models.DataSchema.create_table" ]
[((417, 503), 'api.dataset.models.DataSchema.create_table', 'DataSchema.create_table', ([], {'read_capacity_units': '(1)', 'write_capacity_units': '(1)', 'wait': '(True)'}), '(read_capacity_units=1, write_capacity_units=1, wait\n =True)\n', (440, 503), False, 'from api.dataset.models import DataSchema, Dataset\n'), ...
import functools def my_map(fun, seq): def apply_function_and_aggregate_as_list(accumulator, current_elt): accumulator.append(fun(current_elt)) return accumulator return functools.reduce(apply_function_and_aggregate_as_list, seq, []) print("Puissances de 2 des nombres entre 1 à 9 avec my_ma...
[ "functools.reduce" ]
[((197, 260), 'functools.reduce', 'functools.reduce', (['apply_function_and_aggregate_as_list', 'seq', '[]'], {}), '(apply_function_and_aggregate_as_list, seq, [])\n', (213, 260), False, 'import functools\n')]
import json import torch from torch.nn import functional as F from torch.utils.data import DataLoader from tqdm import tqdm from helpers.text import devectorize from helpers.training import load_checkpoint from models.translate import prior_model_from_checkpoint from modules.data.collates import Seq2SeqCollate from m...
[ "modules.data.datasets.TranslationDataset", "modules.data.collates.Seq2SeqCollate", "models.translate.prior_model_from_checkpoint", "torch.softmax", "modules.data.datasets.SequenceDataset", "torch.nn.functional.cross_entropy", "torch.no_grad", "helpers.training.load_checkpoint", "helpers.text.devect...
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import requests import json from pprint import pprint import sqlite3 from typing import Sequence, Union, Optional import datetime from datetime import datetime from ..api import ApiConfig ENDPOINT_BASE = 'https://data.jmnel.com/api/v1/' ENDPOINT_AUTH = ENDPOINT_BASE + 'topk/authenticate?api={}' ENDPOINT_EXPORT = ENDP...
[ "json.loads", "requests.Session", "datetime.datetime.strptime", "json.dumps", "datetime.datetime.strftime", "pprint.pprint" ]
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from torchtext import data from torch.utils.data import DataLoader from graph import MTInferBatcher, get_mt_dataset, MTDataset, DocumentMTDataset from modules import make_translate_infer_model from utils import tensor_to_sequence, average_model import torch as th import argparse import yaml max_length = 1024 def run...
[ "graph.get_mt_dataset", "torchtext.data.Field", "argparse.ArgumentParser", "utils.tensor_to_sequence", "yaml.load", "graph.DocumentMTDataset", "graph.MTDataset", "modules.make_translate_infer_model", "torch.utils.data.DataLoader", "torch.no_grad", "torch.device" ]
[((3360, 3551), 'modules.make_translate_infer_model', 'make_translate_infer_model', (['vocab_sizes', 'dim_model', 'dim_ff', 'num_heads', 'n_layers', 'm_layers'], {'dropouti': 'dropouti', 'dropouth': 'dropouth', 'dropouta': 'dropouta', 'dropoutc': 'dropoutc', 'rel_pos': 'rel_pos'}), '(vocab_sizes, dim_model, dim_ff, num...
#!/usr/bin/env python3 import requests from SPARQLWrapper import SPARQLWrapper, JSON endpoint = "https://query.wikidata.org/bigdata/namespace/wdq/sparqlba" sparql = SPARQLWrapper(endpoint) sparql.setQuery(""" SELECT DISTINCT ?floss ?label ?repo WHERE { { ?floss p:P31/ps:P31/wdt:P279* wd:Q506883. } Union { ...
[ "requests.get", "SPARQLWrapper.SPARQLWrapper" ]
[((169, 192), 'SPARQLWrapper.SPARQLWrapper', 'SPARQLWrapper', (['endpoint'], {}), '(endpoint)\n', (182, 192), False, 'from SPARQLWrapper import SPARQLWrapper, JSON\n'), ((1367, 1388), 'requests.get', 'requests.get', (['license'], {}), '(license)\n', (1379, 1388), False, 'import requests\n')]
import numpy as np from scipy.spatial.distance import squareform from random import randint # there are more efficient algorithms for this # https://people.csail.mit.edu/virgi/6.890/papers/APBP.pdf def max_min(A, B): '''max-min product of two square matrices params: A, B: NxN numpy arrays ''' asse...
[ "numpy.abs", "scipy.spatial.distance.squareform", "numpy.minimum", "numpy.random.choice", "numpy.max", "numpy.diag", "numpy.linalg.norm", "numpy.all", "random.randint" ]
[((1327, 1340), 'numpy.max', 'np.max', (['dists'], {}), '(dists)\n', (1333, 1340), True, 'import numpy as np\n'), ((360, 400), 'numpy.minimum', 'np.minimum', (['A[:, :, None]', 'B[None, :, :]'], {}), '(A[:, :, None], B[None, :, :])\n', (370, 400), True, 'import numpy as np\n'), ((1158, 1187), 'random.randint', 'randint...
import functools import FreeCAD from PyFlow.Packages.AnimationFreeCAD.Class.FenetreErreur import FenetreErreur from PyFlow.Packages.AnimationFreeCAD.Class.Mouvement import * from PyFlow.Core import NodeBase from PyFlow.Core.Common import * from PySide import QtCore class TranslationDecelere(NodeBase): def __init...
[ "functools.partial", "PySide.QtCore.QTimer", "PyFlow.Packages.AnimationFreeCAD.Class.FenetreErreur.FenetreErreur" ]
[((1512, 1527), 'PySide.QtCore.QTimer', 'QtCore.QTimer', ([], {}), '()\n', (1525, 1527), False, 'from PySide import QtCore\n'), ((1584, 1629), 'functools.partial', 'functools.partial', (['self.mouvementDeceleration'], {}), '(self.mouvementDeceleration)\n', (1601, 1629), False, 'import functools\n'), ((918, 1013), 'PyFl...
#!/usr/bin/env python3 ''' # tgf-cli.py # interactive search of player_game_finder # shows defense vs. position (team totals) ''' import logging import click from nfl.tgf import TeamGameFinder @click.command() @click.option('-y', '--seas', default=None, type=click.IntRange(2010, 2021), help='NFL ...
[ "logging.getLogger", "click.Choice", "click.IntRange", "click.option", "logging.Formatter", "logging.FileHandler", "nfl.tgf.TeamGameFinder", "click.command", "click.FloatRange" ]
[((200, 215), 'click.command', 'click.command', ([], {}), '()\n', (213, 215), False, 'import click\n'), ((459, 528), 'click.option', 'click.option', (['"""-o"""', '"""--opp"""'], {'type': 'str', 'default': 'None', 'help': '"""Team code"""'}), "('-o', '--opp', type=str, default=None, help='Team code')\n", (471, 528), Fa...
import torch import torchvision.models as models import os,sys import numpy as np from matplotlib import pyplot as plt from tqdm import tqdm pwd = os.path.abspath('.') MP3D_build_path = os.path.join(pwd, 'MP3D_Sim', 'build') DASA_path = os.path.join(pwd, 'DASA') sys.path.append(MP3D_build_path) os.chdir(DA...
[ "numpy.radians", "MatterSim.Simulator", "torch.load", "tqdm.tqdm", "os.path.join", "torch.stack", "torch.cuda.set_device", "os.chdir", "numpy.array", "numpy.max", "torchvision.models.resnet152", "numpy.min", "os.path.abspath", "torch.no_grad", "numpy.load", "sys.path.append" ]
[((156, 176), 'os.path.abspath', 'os.path.abspath', (['"""."""'], {}), "('.')\n", (171, 176), False, 'import os, sys\n'), ((196, 234), 'os.path.join', 'os.path.join', (['pwd', '"""MP3D_Sim"""', '"""build"""'], {}), "(pwd, 'MP3D_Sim', 'build')\n", (208, 234), False, 'import os, sys\n'), ((248, 273), 'os.path.join', 'os....
import myffmpeg.ffprobe as probe import myffmpeg.convert as convert from pytest import approx def test_duration(): fnin = 'myvid.mp4' fnout = 'myvid480.mp4' orig_meta = probe.ffprobe(fnin) orig_duration = float(orig_meta['streams'][0]['duration']) convert(fnin, fnout, 480) meta_480 = probe.f...
[ "pytest.approx", "myffmpeg.convert", "myffmpeg.ffprobe.ffprobe" ]
[((183, 202), 'myffmpeg.ffprobe.ffprobe', 'probe.ffprobe', (['fnin'], {}), '(fnin)\n', (196, 202), True, 'import myffmpeg.ffprobe as probe\n'), ((271, 296), 'myffmpeg.convert', 'convert', (['fnin', 'fnout', '(480)'], {}), '(fnin, fnout, 480)\n', (278, 296), True, 'import myffmpeg.convert as convert\n'), ((313, 333), 'm...
from game import * import ai import pygame if __name__ == '__main__': # If this module had been imported, __name__ would be 'flappybird'. # It was executed (e.g. by double-clicking the file), so call main. # Do these now to save time display_surface = pygame.display.set_mode((WIN_WIDTH, WIN_HEIGH...
[ "pygame.display.set_mode", "pygame.quit", "ai.AI" ]
[((275, 323), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(WIN_WIDTH, WIN_HEIGHT)'], {}), '((WIN_WIDTH, WIN_HEIGHT))\n', (298, 323), False, 'import pygame\n'), ((373, 391), 'ai.AI', 'ai.AI', ([], {'silent': '(True)'}), '(silent=True)\n', (378, 391), False, 'import ai\n'), ((507, 520), 'pygame.quit', 'pygam...
# -*- coding: utf-8 -*- """ Tencent is pleased to support the open source community by making BK-BASE 蓝鲸基础平台 available. Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved. BK-BASE 蓝鲸基础平台 is licensed under the MIT License. License for BK-BASE 蓝鲸基础平台: ------------------------------------------...
[ "django.utils.translation.ugettext_lazy" ]
[((1699, 1719), 'django.utils.translation.ugettext_lazy', '_', (['"""请求参数必须包含{param}"""'], {}), "('请求参数必须包含{param}')\n", (1700, 1719), True, 'from django.utils.translation import ugettext_lazy as _\n'), ((1737, 1752), 'django.utils.translation.ugettext_lazy', '_', (['"""查看相关参数是否存在"""'], {}), "('查看相关参数是否存在')\n", (1738, ...
#!/usr/bin/python3 import pyaudio import os import numpy as np from scipy.interpolate import UnivariateSpline from scipy.signal import butter, lfilter, filtfilt, resample from scipy.optimize import curve_fit import scipy as sp import time import pygame from pygame.locals import * from pygame import gfxdraw from pygame ...
[ "numpy.log10", "numpy.sqrt", "pygame.init", "SC18IS602B.SC18IS602B", "numpy.column_stack", "time.sleep", "pygame.event.Event", "pygame.time.set_timer", "pygame.font.Font", "RPi.GPIO.setmode", "numpy.arange", "numpy.mean", "pygame.display.set_mode", "os.putenv", "numpy.fft.fft", "pygame...
[((8367, 8384), 'pyaudio.PyAudio', 'pyaudio.PyAudio', ([], {}), '()\n', (8382, 8384), False, 'import pyaudio\n'), ((8581, 8616), 'MCP230XX.MCP230XX', 'MCP230XX', (['"""MCP23008"""'], {'i2cAddress': '(32)'}), "('MCP23008', i2cAddress=32)\n", (8589, 8616), False, 'from MCP230XX import MCP230XX\n'), ((8625, 8647), 'LTC138...
# Generated by Django 3.2.6 on 2021-10-28 19:56 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('store', '0001_initial'), ] operations = [ migrations.AlterField( model_name='product', name='avg_rate', ...
[ "django.db.models.DecimalField" ]
[((326, 403), 'django.db.models.DecimalField', 'models.DecimalField', ([], {'blank': '(True)', 'decimal_places': '(1)', 'default': 'None', 'max_digits': '(1)'}), '(blank=True, decimal_places=1, default=None, max_digits=1)\n', (345, 403), False, 'from django.db import migrations, models\n')]
# -*- coding: utf-8 -*- # Copyright (C) 2010-2014 Mag. <NAME> All rights reserved # Glasauergasse 32, A--1130 Wien, Austria. <EMAIL> # **************************************************************************** # This module is part of the package GTW.OMP.SWP. # # This module is licensed under the terms of the BSD 3-C...
[ "_GTW.GTW.OMP.SWP._Export" ]
[((1572, 1596), '_GTW.GTW.OMP.SWP._Export', 'GTW.OMP.SWP._Export', (['"""*"""'], {}), "('*')\n", (1591, 1596), False, 'from _GTW import GTW\n')]
from imgaug import augmenters as iaa import matplotlib.pyplot as plt from itertools import cycle from scipy import interp import tensorflow as tf import itertools import numpy as np import json import argparse import warnings import os from synth.utils import datagenerate from sklearn.metrics import roc_curve, auc, a...
[ "matplotlib.pyplot.ylabel", "sklearn.metrics.classification_report", "sklearn.metrics.auc", "sklearn.metrics.roc_curve", "tensorflow.cast", "synth.utils.datagenerate", "matplotlib.pyplot.imshow", "os.path.exists", "scipy.interp", "matplotlib.pyplot.xlabel", "matplotlib.pyplot.plot", "matplotli...
[((623, 637), 'synth.utils.datagenerate', 'datagenerate', ([], {}), '()\n', (635, 637), False, 'from synth.utils import datagenerate\n'), ((651, 676), 'tensorflow.cast', 'tf.cast', (['images', 'tf.uint8'], {}), '(images, tf.uint8)\n', (658, 676), True, 'import tensorflow as tf\n'), ((943, 982), 'os.path.join', 'os.path...
from django.core.management.base import BaseCommand, CommandError from django.conf import settings from pathlib import Path from template_data.models import TemplateData from template_data.management.commands.add_data import DataMixin import json class Command(DataMixin, BaseCommand): """Install the theme""" ...
[ "json.load", "traceback.print_exc" ]
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from concurrent import futures from functools import partial from itertools import product import os import numpy as np from pyx import color, deco, graph, path, text def mandelbrot_iteration(niter, *args): nx, ny, c = args[0] z = np.zeros_like(c) for n in range(niter): z = z**2+c return nx, ny...
[ "numpy.abs", "pyx.graph.axis.lin", "pyx.text.set", "pyx.text.preamble", "pyx.graph.data.points", "pyx.color.grey", "pyx.path.rect", "pyx.graph.style.density", "functools.partial", "concurrent.futures.ProcessPoolExecutor", "os.getpid", "pyx.color.transparency", "numpy.zeros_like" ]
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from django.conf.urls import url from . import views urlpatterns = [ url(r'^(?P<id>\d{10})/' r'(?P<accion>\d+)/$', views.accion, name='accion' ), ]
[ "django.conf.urls.url" ]
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# -*- coding: utf-8 -*- """ """ import torch import torch.nn as nn from torch.autograd import Variable import torch.nn.functional as F dtype = torch.float class RNN(nn.Module): def __init__(self, input_size, hidden_size, num_layers, device=torch.device("cpu")): super(RNN, self).__init__()...
[ "torch.nn.ReLU", "torch.nn.Dropout", "torch.nn.Softmax", "torch.nn.LeakyReLU", "torch.nn.LSTM", "torch.transpose", "torch.nn.Linear", "torch.squeeze", "torch.bmm", "torch.randn", "torch.cat", "torch.device" ]
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import os import unittest import jwt from dataservice.app import app from flask_webtest import TestApp as _TestApp _HERE = os.path.dirname(__file__) with open(os.path.join(_HERE, 'privkey.pem')) as f: _KEY = f.read() def create_token(data): return jwt.encode(data, _KEY, algorithm='RS512') _TOKEN = {'iss':...
[ "flask_webtest.TestApp", "os.path.dirname", "os.path.join", "jwt.encode" ]
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from MLlib.models import Agglomerative_clustering import numpy as np X = np.genfromtxt('datasets/agglomerative_clustering.txt') model = Agglomerative_clustering() model.work(X, 4) model.plot(X)
[ "numpy.genfromtxt", "MLlib.models.Agglomerative_clustering" ]
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import sys import argparse import math import cv2 import pdb import os from os import listdir from os.path import isfile, join def pngImgDirs(x_args): #pdb.set_trace() in_path = os.path.abspath(x_args.indir) out_path = os.path.abspath(x_args.outdir) if(x_args.opt == 'test'): eval_...
[ "os.listdir", "argparse.ArgumentParser", "os.makedirs", "os.path.join", "cv2.cvtColor", "os.path.abspath", "os.stat", "cv2.imread" ]
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from __future__ import annotations import copy import dataclasses import functools import getpass import json import logging import logging.handlers import os import platform import queue as queue_module import socket import sys import typing import warnings from .utils import get_fully_qualified_domain_name # The s...
[ "logging.getLogger", "dataclasses.dataclass", "os.environ.get", "platform.uname", "queue.Queue", "logging.getLevelName", "functools.partial", "getpass.getuser", "copy.copy", "sys.modules.items" ]
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# convert the downscaled data archive def run( x ): ''' simple wrapper to open and return a 2-D array from a geotiff ''' import rasterio return rasterio.open(x).read(1) def sort_files( files, split_on='_', elem_month=-2, elem_year=-1 ): ''' sort a list of files properly using the month and year parsed from the...
[ "os.path.exists", "time.ctime", "argparse.ArgumentParser", "os.makedirs", "rasterio.open", "os.path.join", "numpy.swapaxes", "affine.Affine.translation", "multiprocessing.Pool", "pyproj.Proj", "numpy.min", "pandas.DataFrame", "time.time", "numpy.arange", "numpy.vectorize" ]
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__author__ = 'Reem' # This file contains the main functions that deal with caching the diff # at different levels of details # detail (as detail), middle (as count), overview (as ratios) from diff_finder import Table, DiffFinder, Diff, Levels, Ratios import caleydo_server.dataset as dataset import timeit import json ...
[ "hashlib.md5", "ujson.dumps", "timeit.default_timer", "os.path.isfile", "diff_finder.Ratios", "caleydo_server.dataset.get", "json.load", "diff_finder.DiffFinder", "json.dump" ]
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import configparser import spotipy from spotipy.oauth2 import SpotifyOAuth class Spotify: SCOPE = "playlist-read-private playlist-modify-private user-library-modify user-library-read" def __init__(self): config = configparser.ConfigParser() config.read("config.ini") self.client = sp...
[ "configparser.ConfigParser", "spotipy.oauth2.SpotifyOAuth" ]
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import unittest import libraries.morflessLibs as libs # import test values and expected outputs # main includes sidebar data import unit.read_schematic_test_io.read_schematic_1_test_io as tv1 import unit.read_schematic_test_io.read_schematic_2_test_io as tv2 import unit.read_schematic_test_io.read_schematic_3_test_io ...
[ "libraries.morflessLibs.read_schematic.pcom_process_inserts", "libraries.morflessLibs.read_schematic.pcom_determine_placement", "libraries.morflessLibs.read_schematic.polimorf_determine_schematic_reference", "libraries.morflessLibs.read_schematic.pcom_get_schematic_tags", "libraries.morflessLibs.read_schema...
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#!/usr/bin/env python # -*- coding: utf-8 -*- """Tests for AuthService.""" import pytest from webodm import NonFieldErrors, LOCAL_HOST from webodm.services import AuthService @pytest.fixture def authservice(): return AuthService(LOCAL_HOST) class MockResponse: def __init__(self, json_data, status_code): ...
[ "webodm.services.AuthService", "pytest.raises" ]
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# Copyright 2020 Google LLC # # 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 # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, sof...
[ "yamlformat.validator.base_lib.GetTreeLocation", "absl.testing.absltest.main", "yamlformat.validator.base_lib.ComponentType.FromString" ]
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import numpy as np class Node(): def __init__(self, params=[]): self.in_nodes = params self.value = 0 def forward(self): return NotImplementedError def backward(self): return NotImplementedError class Input_Node(Node): def __init__(self, value ...
[ "numpy.array", "numpy.sum" ]
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import pickle def get_users(): users_file = open("users_file", "rb") try: users = pickle.load(users_file) except: import pdb;pdb.set_trace() username_table = {u.username: u for u in users} return username_table class User: def __init__(self, user_id, username, password): ...
[ "pickle.load", "pdb.set_trace" ]
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from time import perf_counter_ns as ns def solution(s): d = {n: str(i) for i, n in enumerate('zero one two three four ' 'five six seven eight nine'.split())} for k, v in d.items(): s = s.replace(k, v) return int(s) if __name__ == '__main__': ITERATION...
[ "time.perf_counter_ns" ]
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# **************************************************************** # AULA: Visão Computacional # Prof: <NAME>, DSc. # **************************************************************** # Importando a biblioteca OpenCV import cv2 import numpy as np # Imagem aquivo = "./imagens/raposa.jpg" # Carregando a imagem imagem =...
[ "cv2.waitKey", "cv2.imread", "cv2.cvtColor", "cv2.imshow" ]
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# -*- encoding: utf-8 -*- """ Provide a class for orchestrating the rush of some yielding callable. """ from __future__ import absolute_import import sys from collections import defaultdict from datetime import timedelta from threading import Condition, Event, Thread from time import time __all__ = ['Rusher', 'rush',...
[ "datetime.timedelta", "threading.Event", "collections.defaultdict", "threading.Thread", "threading.Condition", "time.time" ]
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""" state, observation and action spaces """ from collections import namedtuple, OrderedDict from io import BytesIO from itertools import product from os.path import join import pkg_resources import numpy as np import pandas as pd import energypy as ep from energypy.common.spaces import DiscreteSpace, ContinuousSpac...
[ "collections.namedtuple", "itertools.product", "io.BytesIO", "os.path.join", "numpy.max", "numpy.array", "numpy.random.randint", "numpy.min" ]
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# import XML libraries import xml.etree.ElementTree as ET import xml.dom.minidom as minidom import HTMLParser # Function to create an XML structure def make_problem_XML( problem_title='Missing title', problem_text=False, label_text='Enter your answer below.', description_text=False, answers=[{'corr...
[ "xml.etree.ElementTree.Element", "xml.etree.ElementTree.SubElement", "HTMLParser.HTMLParser", "xml.etree.ElementTree.ElementTree" ]
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import os os.system("pip3 install GitPython") os.system("pip3 install PyYAML") os.system("pip3 install nltk") os.system("python3 -m nltk.downloader stopwords") os.system("python3 -m nltk.downloader wordnet") os.system("pip3 install psycopg2-binary")
[ "os.system" ]
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import pynini import tqdm class Alphabet: """ Represents mapping between phonemes in IPA and representations in text files """ def __init__(self): self.symbols class Vocabulary: """ Get ... """ class Allophony: """ Multiplies the vocabulary by ta...
[ "pynini.pdt_shortestpath", "pynini.compose", "tqdm.tqdm", "pynini.Fst" ]
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# Generated by Django 3.0.8 on 2020-12-04 17:53 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('auctions', '0006_auto_20201203_1859'), ] operations = [ migrations.AlterFi...
[ "django.db.models.ForeignKey" ]
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# --*-- coding: utf-8 --*-- import os import datetime import sys WORK_PATH = os.getcwd() LOG_PATH = os.path.join(WORK_PATH, 'Logs') class Logger(object): def __init__(self, file_name): if not os.path.exists(LOG_PATH): os.makedirs(LOG_PATH) date = datetime.datetime.now() self.file_path = os.path.join(LOG_P...
[ "os.path.exists", "os.makedirs", "os.path.join", "os.getcwd", "datetime.datetime.now" ]
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#!/usr/bin/env python3 # # Copyright (c) 2021 @marbocub <<EMAIL>> # Released under the MIT license # import os, pathlib, hashlib, time, sys, re from typing import Callable, List, Tuple import dotenv from database import FileBase, File, Dir, DatabaseInterface, DatabasePostgreSQL #-------------------------...
[ "os.path.exists", "hashlib.sha256", "database.DatabasePostgreSQL", "os.listdir", "pathlib.Path", "os.path.join", "os.environ.get", "os.getcwd", "dotenv.load_dotenv", "os.chdir", "sys.exit", "os.stat", "time.time" ]
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import serial import MySQLdb device = '/dev/ttyACM0' #ser = serial.Serial('/dev/ttyACM1', 9600) arduino = serial.Serial(device, 9600) data = arduino.readline() print('Encoded Serial Databyte'+ data) temp = data.decode('UTF-8') print(temp) #Make DB connection dbConn = MySQLdb.connect("localhost", "root", "password...
[ "MySQLdb.connect", "serial.Serial" ]
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# ============LICENSE_START========================================== # org.onap.vvp/engagementmgr # =================================================================== # Copyright © 2017 AT&T Intellectual Property. All rights reserved. # =================================================================== # # Unless ot...
[ "datetime.datetime", "django.db.models.EmailField", "django.db.models.DateField", "django.db.models.TextField", "django.db.models.ForeignKey", "django.db.models.IntegerField", "django.db.models.ManyToManyField", "django.db.models.BooleanField", "django.db.models.AutoField", "django.db.models.Binar...
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import unittest import pickle import sys import tempfile from pathlib import Path class TestUnpickleDeletedModule(unittest.TestCase): def test_loading_pickle_with_no_module(self): """Create a module that uses Numba, import a function from it. Then delete the module and pickle the function. The fun...
[ "tempfile.TemporaryDirectory", "pathlib.Path", "pickle.dumps", "pickle.loads", "sys.path.append" ]
[((1548, 1566), 'pickle.dumps', 'pickle.dumps', (['inc1'], {}), '(inc1)\n', (1560, 1566), False, 'import pickle\n'), ((1579, 1596), 'pickle.loads', 'pickle.loads', (['pkl'], {}), '(pkl)\n', (1591, 1596), False, 'import pickle\n'), ((998, 1027), 'tempfile.TemporaryDirectory', 'tempfile.TemporaryDirectory', ([], {}), '()...
from selenium import webdriver driver = webdriver.Chrome(executable_path='/home/denoh/Programs/Webdriver/chromedriver') driver.implicitly_wait(0.5) driver.get("https://www.tutorialspoint.com/index.htm") # identify element # l= driver.find_elements_by_css_selector("body > div:nth-child(2) > div > h4") l = driver.find_e...
[ "selenium.webdriver.Chrome" ]
[((41, 120), 'selenium.webdriver.Chrome', 'webdriver.Chrome', ([], {'executable_path': '"""/home/denoh/Programs/Webdriver/chromedriver"""'}), "(executable_path='/home/denoh/Programs/Webdriver/chromedriver')\n", (57, 120), False, 'from selenium import webdriver\n')]
""" Pylibui test suite. """ from pylibui.controls import Combobox from tests.utils import WindowTestCase class ComboboxTest(WindowTestCase): def setUp(self): super().setUp() self.combobox = Combobox() def test_set_selected(self): """Tests the set_selected method of the combobox."""...
[ "pylibui.controls.Combobox" ]
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import datetime import random import threading import consul from loadbalance.consulconfig import ConsulConfig, ConsulDiscoverConfig, AppConfig from tool.networktool import * service_cache = {} def reload_service_cache(): if service_cache is not None and len(service_cache)>0: for key in service_cache.ke...
[ "random.uniform", "threading.Timer", "loadbalance.consulconfig.ConsulConfig.load_config", "consul.Consul", "datetime.datetime.now", "loadbalance.consulconfig.AppConfig.load_config", "consul.Check.http", "loadbalance.consulconfig.ConsulDiscoverConfig.load_config" ]
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from util import db from util import getFilteredQuery from flask import jsonify from flask_restful import Resource from flask_restful import reqparse from urllib.parse import unquote _weaponsCollection = db.weapons class WeaponsListApi(Resource): def get(self): return jsonify(getFilteredQue...
[ "util.getFilteredQuery", "flask_restful.reqparse.RequestParser", "urllib.parse.unquote" ]
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import numpy as np, matplotlib.pyplot as plt, seaborn as sns from rdkit import Chem from dataclasses import dataclass from utils.exp import BaseArgs, BaseExpLog from utils.data import remove_processed_data import torch from torch_geometric.data import DataLoader from data.data_processors.ts_gen_processor import TSGenDa...
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import requests class UnauthenticatedError(Exception): pass class InvalidTokenError(Exception): pass class InvalidResponseError(Exception): pass class NetworkManager: def __init__(self, endpoint): self.endpoint = endpoint self.token = "" def register_device(self, hardware_id...
[ "requests.get" ]
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#!/usr/bin/env python """Script used to generate a cuboid dataset with cubes and rectangles under various shapes, rotations, translations following the general format of ShapeNet. """ import argparse import random import os from string import ascii_letters, digits import sys import numpy as np from progress.bar import...
[ "os.path.exists", "os.listdir", "pyquaternion.Quaternion.random", "numpy.random.rand", "argparse.ArgumentParser", "os.makedirs", "numpy.random.random", "random.choice", "os.path.join", "learnable_primitives.mesh.MeshFromOBJ", "shapes.Shape.from_shapes", "numpy.array", "numpy.linspace", "sh...
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import os # If server, need to use osmesa for pyopengl/pyrender if os.cpu_count() > 20: os.environ['PYOPENGL_PLATFORM'] = 'osmesa' # https://github.com/marian42/mesh_to_sdf/issues/13 # https://pyrender.readthedocs.io/en/latest/install/index.html?highlight=ssh#getting-pyrender-working-with-osmesa else: os.environ[...
[ "numpy.random.get_state", "torch.optim.lr_scheduler.MultiStepLR", "yaml.load", "src.dataset_grasp.TrainDataset", "torch.from_numpy", "torch.nn.MSELoss", "src.pointnet_encoder.PointNetEncoder", "numpy.array", "torch.get_rng_state", "os.cpu_count", "logging.info", "multiprocessing.set_start_meth...
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from urllib.parse import quote_plus from flask import url_for from sopy import db from sopy.ext.models import IDModel from sopy.se_data.models import ChatMessage class Transcript(IDModel): title = db.Column(db.String, nullable=False) ts = db.Column(db.DateTime, nullable=False) body = db.Column(db.String, ...
[ "sopy.db.Column", "sopy.db.ForeignKey", "sopy.db.relationship", "flask.url_for" ]
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