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import os import unittest from swamp.utils import create_tempfile from swamp.parsers.phaserparser import PhaserParser class PhaserParserTestCase(unittest.TestCase): def test_1(self): file_contents = """REMARK TITLE [no title set] REMARK ENSEMBLE PDB_1 EULER 49.90 83.52 180.06 FRAC -0.288 -0.526 -0.158 ...
[ "unittest.main", "swamp.utils.create_tempfile", "swamp.parsers.phaserparser.PhaserParser" ]
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#!/usr/bin/env python3 import re import unittest import requests import responses import haiker from . import samples URL_INITIATE = 'https://www.hatena.com/oauth/initiate' URL_VERIFY = 'https://www.hatena.com/oauth/token' BODY_INITIATE = 'oauth_token=OAuthToken&oauth_token_secret=OAuthTokenSecret' BODY_VERIFY = 'oa...
[ "re.compile", "responses.add", "haiker.BasicAuth", "haiker.Haiker", "haiker.OAuth" ]
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import types import numpy as np import jax from jax import numpy as jnp from flax import struct import utils DTYPE = jnp.int16 SIZE = 10 one_hot_10 = jax.partial(utils.one_hot, k=SIZE) ACTION_MAP = jnp.stack([ jnp.array((1, 0), dtype=DTYPE), # visually DOWN jnp.array((0, 1), dtype=DTYPE), # visually R...
[ "jax.partial", "flax.struct.field", "jax.numpy.arange", "jax.numpy.array", "numpy.zeros", "jax.jit", "jax.numpy.clip", "jax.numpy.linspace", "jax.vmap", "random.randint" ]
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from typing import Dict, List, Set, Type from uuid import UUID from panek.object_relations import ObjectRelationMapper import byt.middleware.typing as t from byt.ecs.component import IComponent from byt.ecs.entity import Entity from byt.ecs.system import ISystem from byt.middleware.utils import make_iterable class ...
[ "panek.object_relations.ObjectRelationMapper", "byt.middleware.utils.make_iterable", "byt.ecs.entity.Entity" ]
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from os import path import os from flask import Flask, jsonify, render_template, current_app from keras.models import load_model from . import app, db from .controller.news_scanner import NewsScanner from .controller.news_categorization import NewsCategorization import pandas as pd """ Pages management @author: Al...
[ "flask.render_template" ]
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from finetuna.ml_potentials.ocpd_calc import OCPDCalc import torch from torch import nn import torch.nn.functional as F import numpy as np import copy from multiprocessing import Pool from ase.atoms import Atoms class OCPDNNCalc(OCPDCalc): implemented_properties = ["energy", "forces", "stds"] def __init__( ...
[ "numpy.multiply", "torch.nn.Dropout", "copy.deepcopy", "numpy.ones", "torch.optim.lr_scheduler.ReduceLROnPlateau", "numpy.average", "torch.nn.init.xavier_uniform_", "torch.nn.MSELoss", "numpy.zeros", "torch.tensor", "multiprocessing.Pool", "torch.nn.Linear", "numpy.std" ]
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import os, shutil, re from pathlib import Path src = Path('./copyFiles') for folderName, subFolders, fileNames in os.walk(Path(src)): count = 0 for file in fileNames: fileRegex = re.compile(r'(test)(\d+)') mo = fileRegex.search(file) if mo.group(2) == count: ...
[ "re.compile", "pathlib.Path" ]
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import pytest from django_oso.models import AuthorizedModel, authorize_model from django_oso.oso import Oso, reset_oso from django.core.management import call_command from app.models import Post, User @pytest.fixture(autouse=True) def reset(): reset_oso() @pytest.fixture def users(): (manager, _) = User.o...
[ "app.models.User.objects.get_or_create", "django_oso.oso.reset_oso", "app.models.Post.objects.get_or_create", "app.models.Post.objects.authorize", "pytest.fixture" ]
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# SPDX-FileCopyrightText: 2022 <NAME> # SPDX-License-Identifier: Apache-2.0 """Build and installation script for hyper-shell.""" # standard libs import os import re from setuptools import setup, find_packages # long description from README.rst with open('README.rst', mode='r') as readme: long_description = rea...
[ "setuptools.find_packages", "os.environ.get", "re.search" ]
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# Uses python3 import sys def gcd(a,b): if a<b: t=a a=b b=t while True: if b==0: return a remainder=a%b a=b b=remainder if __name__ == "__main__": input = sys.stdin.read() a, b = map(int, input.split()) print(gcd(a, b))...
[ "sys.stdin.read" ]
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'''' Operations ========== Initialisation -------------- - Create veth pairs - Create /var/run/netns - Write ports file - Run container with ${name} - Run read thread - Bind container process pid to namespace ${name}_ns - Move peer ports to namespace - Send trap - Wa...
[ "simple_switch.netutils.configure_interface", "simple_switch.netutils.add_veth_pair", "simple_switch.netutils._run_command", "os.environ.get", "pyroute2.netns.remove", "simple_switch.netutils.set_iface_namespace", "docker.APIClient", "docker.DockerClient", "simple_switch.netutils.restart_avahi" ]
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from passwd import PasswordRequirements def test_min_length(): length_8 = PasswordRequirements(min_length=8) assert length_8.check("abcd1234") assert not length_8.check("abc123") # No minimum characters requirement if not specified assert PasswordRequirements().check("abc<PASSWORD>") def test_...
[ "passwd.PasswordRequirements" ]
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from threading import Thread import time def car(speed, pilot): route = 0 while route <= 100: route += speed time.sleep(0.5) print(f'Pilot: {pilot}, Km {route} \n') t_car1 = Thread(target = car, args = [20, 'Paul']) t_car2 = Thread(target = car, args = [10, 'Del']) t_car1.start() t_c...
[ "threading.Thread", "time.sleep" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import division import sys import re import mrjob import itertools import json from mrjob.protocol import RawProtocol from mrjob.job import MRJob from mrjob.step import MRStep class MRbuildStripes(MRJob): #START SUDENT CODE531_STRIPES # Init Setti...
[ "re.findall", "sys.stderr.write", "mrjob.step.MRStep" ]
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import click from pathlib import Path import datetime from moviepy.editor import * from PIL import Image from PIL import ImageFont from PIL import ImageDraw import numpy as np import xmltodict def make_clips(filelist,timelist,AOI=None): print('loopstart') clips=[] for file, time in zip(filelist, timelist)...
[ "PIL.Image.open", "pathlib.Path", "click.option", "numpy.array", "PIL.ImageDraw.Draw", "click.command" ]
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#!/usr/bin/python3 import hid import traceback hid_max_pkt_size = 64 if __name__ == '__main__': import argparse import sys import binascii parser = argparse.ArgumentParser() parser.add_argument('-d', '--descriptor', help='Print Descriptor', action='store_true') args = parser.parse_args(...
[ "traceback.format_exc", "argparse.ArgumentParser", "binascii.hexlify", "hid.device", "sys.exit", "hid.enumerate" ]
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# encoding: utf-8 import pytest from ckan import model from ckan.lib.create_test_data import CreateTestData from ckan.tests.legacy import TestController as ControllerTestCase from ckan.tests.legacy import url_for @pytest.fixture(autouse=True) def initial_data(clean_db): CreateTestData.create() def test_munge_p...
[ "pytest.fixture", "ckan.tests.legacy.url_for", "ckan.lib.create_test_data.CreateTestData.create" ]
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""" Usefull functions for loading files etc. -AN """ import os import pickle import zipfile, lzma import numpy as np import matplotlib.pyplot as plt from collections import OrderedDict # saves dict to csv using keys as headers def saveToCSV(savedict, filename = "", path = ""): try: #print(sav...
[ "numpy.abs", "collections.OrderedDict", "numpy.convolve", "pickle.dump", "zipfile.ZipFile", "os.makedirs", "matplotlib.pyplot.plot", "os.path.join", "os.getcwd", "os.path.isdir", "numpy.shape", "os.walk", "matplotlib.pyplot.show" ]
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import keras import keras.backend as K IMG_SIZE = 160 DENSE_SHAPE = 4096 def oneshot_bsm(): """ pre-trained baseline model :return: a keras model object """ pre_model = keras.applications.mobilenet_v2.MobileNetV2(include_top=False, weights='imagenet', input_shape=[IMG_SIZE, IMG_SIZE, 3]) flat ...
[ "keras.optimizers.Adam", "keras.layers.Conv2D", "keras.layers.Flatten", "keras.Model", "keras.layers.Concatenate", "keras.layers.Lambda", "keras.initializers.truncated_normal", "keras.backend.abs", "keras.backend.square", "keras.Input", "keras.backend.log", "keras.applications.mobilenet_v2.Mob...
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import pytest import xia2.Experts.LatticeExpert def test_lattice_expert(): cell, dist = xia2.Experts.LatticeExpert.ApplyLattice( "oP", (23.0, 24.0, 25.0, 88.9, 90.0, 90.1) ) assert cell == (23.0, 24.0, 25.0, 90.0, 90.0, 90.0) assert dist == pytest.approx(1.2) def test_SortLattices(): la...
[ "pytest.approx" ]
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from tkinter import * from PIL import Image, ImageTk import random import requests import json import time import pandas as pd import matplotlib matplotlib.use("TkAgg") # allow matplotlib to display on tkinter import matplotlib.pyplot as plt import seaborn as sns from speech import * import duckduckgo import re import...
[ "matplotlib.pyplot.ylabel", "re.search", "seaborn.set", "collections.deque", "matplotlib.pyplot.plot", "matplotlib.pyplot.style.use", "matplotlib.pyplot.close", "time.localtime", "PIL.ImageTk.PhotoImage", "json.loads", "random.choice", "matplotlib.pyplot.savefig", "matplotlib.pyplot.xticks",...
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import send_email send_email.send('testing')
[ "send_email.send" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- """ MagnetCommunication.py Author: <NAME> Created on Mon Dec 18 15:35:21 2017 Last Edited: 06.12.2018 Python Version: 3.6.5 4G Magnet Power Supply Class for sending commands to 4G Magnet Power Supply IMPORTANT: Magnet has to be in remote mode, can only be set locally ...
[ "socket.socket" ]
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""" ----------------------------------------------------------------------- Harmoni: a Novel Method for Eliminating Spurious Neuronal Interactions due to the Harmonic Components in Neuronal Data <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME> https://doi.org/10.1101/2021.10.06.463319 ----------------------------...
[ "numpy.abs", "tools_signal.plot_fft", "scipy.signal.filtfilt", "tools_signal.hilbert_", "matplotlib.pyplot.plot", "tools_connectivity.compute_phase_connectivity", "matplotlib.pyplot.legend", "numpy.array", "numpy.linspace", "scipy.signal.sawtooth", "matplotlib.pyplot.figure", "matplotlib.pyplo...
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import copy import torch import numpy as np from torch.utils.data import DataLoader from src.cli import get_args from src.utils import capitalize_first_letter, load from src.data import get_data, get_glove_emotion_embs from src.trainers.sentiment import SentiTrainer from src.trainers.emotion import MoseiEmoTrainer, Iem...
[ "torch.manual_seed", "torch.optim.lr_scheduler.ReduceLROnPlateau", "src.models.mult.MULTModel", "copy.deepcopy", "torch.nn.CrossEntropyLoss", "torch.nn.BCEWithLogitsLoss", "torch.nn.L1Loss", "src.data.get_data", "torch.nn.MSELoss", "torch.cuda.is_available", "torch.nn.Parameter", "numpy.random...
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# 日志系统 import os import time import random # 步骤组模板 stepsTemplate = """ 步骤组: {name} 开始时间: {startTime} ---------------------------------------------- {stepLog} 步骤结束 {errorLog} 结束时间: {endTime} 总耗时: {time}ms """ # 步骤模板 # TODO: 步骤组带s, 步骤不带s stepTemplate = """ 步骤{index}: {name} {runLog} 结果: {result} 开始时间: {startTime} 结束时...
[ "os.path.exists", "os.makedirs", "os.getcwd", "time.localtime", "random.randint" ]
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import pygame import numpy as np import random import copy from astar import astar from constants import DISPLAY_WIDTH, DISPLAY_HEIGHT, PIXEL_SIZE, BLACK, GREEN class Snake: def __init__(self): self.x = round(random.randrange(0, DISPLAY_WIDTH - PIXEL_SIZE) / 20.0) * 20 self.y = round(random.randra...
[ "random.randrange", "pygame.draw.rect", "astar.astar", "copy.deepcopy" ]
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# -*- coding: utf-8 -*- # Copyright 2016 CloudFlare, Inc. All rights reserved. # # The contents of this file are 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...
[ "iosxr_eznc.decorators.wrap_xml", "iosxr_eznc.decorators.qualify" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- """ @Time : 2019/5/15 @Author : AnNing """ from __future__ import print_function import os import sys import numpy as np from initialize import load_yaml_file from load import ReadAhiL1 TEST = True def ndsi(in_file_l1, in_file_geo, in_file_cloud): # ----------...
[ "numpy.sqrt", "numpy.arccos", "initialize.load_yaml_file", "numpy.logical_and.reduce", "sys.exit", "numpy.sin", "load.ReadAhiL1", "numpy.maximum", "numpy.round", "numpy.abs", "numpy.ones", "os.path.dirname", "numpy.isnan", "numpy.cos", "numpy.minimum", "numpy.logical_and", "os.path.j...
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import setuptools import nltk with open('requirements.txt') as f: required = f.read().splitlines() with open("README.md") as fh: long_description = fh.read() nltk.download("punkt") setuptools.setup( name='multiner', version="0.0.1", description="multilingual named entity recognition with xlm-rob...
[ "setuptools.find_packages", "nltk.download" ]
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# encoding: utf-8 import argparse, getpass, pymysql, sys, csv def generateDescriptionReport(connection): cursor = connection.cursor() cursor.execute("SET CHARACTER_SET_RESULTS='latin1'") cursor.execute('''SELECT biomarkers.id, biomarkers.name, biomarkers.description FROM biomarkers''') with open('res...
[ "csv.writer", "pymysql.connect", "argparse.ArgumentParser", "sys.exit" ]
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from cs50 import get_string def get_text(): # Prompt for text. If user enters an empty string, prompt again. while True: word = get_string("Text: ") if word != "": return word def text_parser(text): # Helper function for parse input text. letters = count_letters(text) ...
[ "cs50.get_string" ]
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""" This module contains the any stats related functions from the NHL API for players or teams. """ import logging import requests from hockeygamebot.helpers import utils # Load configuration file in global scope urls = utils.load_urls() def get_player_career_stats(player_id): """Returns the career stats of an...
[ "hockeygamebot.helpers.utils.load_urls", "logging.error", "requests.get" ]
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''' Created on Jun 3, 2021 @author: immanueltrummer ''' import torch from transformers import AutoTokenizer, AutoModelForSequenceClassification class EntailmentUtil(): """ Methods for checking entailment. """ def __init__(self): """ Initialize models for entailment checks. """ self.tokeni...
[ "transformers.AutoModelForSequenceClassification.from_pretrained", "transformers.AutoTokenizer.from_pretrained" ]
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def dmsg(text_s = '', verbose = False): # Usage : dmsg('any message') if verbose: return import inspect frame = inspect.currentframe() fname = str.split(str(frame.f_back.f_code),'"')[1] # <code object dmsg at 0x7f63ad0a08a0, file "./../src/vps/vps.py", line 47> line = str(frame.f_back.f_line...
[ "inspect.currentframe" ]
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# -*- coding: utf-8 -*- import common as c def q2(): """ Questão 2 """ print ("Cossenos diretores:") print (c.dcos([3, 6], True))
[ "common.dcos" ]
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#!/usr/bin/env python import overpy # "conda install -c conda-forge overpy" -- a Python Wrapper to access the OpenStreepMap Overpass API import csv import time # building_types are defined for key:building:accommodations at https://wiki.openstreetmap.org/wiki/Key:building building_types = ["apartments", ...
[ "csv.writer", "overpy.Overpass", "time.sleep", "csv.DictReader" ]
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# to do: # - read in tidal predictions (if file exists) to validate data import socket import numpy as np def ADCP_read(stage_instance, udp_IP = "", udp_port = 61557, buff_size = 1024, timeout = 5): """ Reads ADCP data continously from the specified port. **EDITING NOTE - break added after timeout** ...
[ "numpy.mean", "socket.socket", "numpy.array", "numpy.resize", "numpy.arctan" ]
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# coding: utf-8 import os import zipfile from contextlib import contextmanager from time import time from ._compat import lru_cache from .logging import get_logger class BaseBackend(object): dbname = None connections = {"default": {}} schema_filename = "dump/schema.sql" initial_setup_files = (schema_...
[ "time.time", "os.path.basename", "zipfile.ZipFile" ]
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import sys import signal import os import subprocess import selectors import importlib logger = importlib.import_module("logger") tun = importlib.import_module("tun") crypto = importlib.import_module("crypto") udp = importlib.import_module("udp") tun_name = "" mode = None addr = None key = None auth_msg = b"Infini...
[ "signal.signal", "importlib.import_module", "os.write", "os.putenv", "subprocess.run", "selectors.DefaultSelector", "os.read" ]
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# -*- coding: utf-8 -*- import argparse as ap import numpy as np class Error: access = 123 class Options: """ Options-parsing class """ keys = [ 'outfile', 'vasprun', 'orbitals', 'ions', 'efermi', 'range', 'labels', 'dpi' ] def __init__(self, *args): """ Initialization of parser, ...
[ "argparse.ArgumentParser" ]
[((379, 440), 'argparse.ArgumentParser', 'ap.ArgumentParser', ([], {'description': '"""Plotting the projected bands"""'}), "(description='Plotting the projected bands')\n", (396, 440), True, 'import argparse as ap\n')]
import unittest from taxonomy import Taxonomy, TaxonomyError class NewickTestCase(unittest.TestCase): def _create_tax(self): # https://en.wikipedia.org/wiki/Newick_format#Examples return Taxonomy.from_newick("(A:0.1,B:0.2,(C:0.3,D:0.4)E:0.5)F;") def setUp(self) -> None: self.tax = se...
[ "unittest.main", "taxonomy.Taxonomy.from_ncbi", "unittest.skip", "taxonomy.Taxonomy.from_newick" ]
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#-*-coding=utf-8-*- """ Momentum Contrast Encoder for CIFAR 10 @author Sentinel @date 2021.9.1 """ import torch from torch import nn from torch.nn.modules.batchnorm import BatchNorm2d from torch.nn.modules.linear import Linear from torchvision.models import resnet18 def makeConvBlock(in_chan:int, out_ch...
[ "torch.nn.BatchNorm2d", "torch.nn.ReLU", "torch.nn.init.constant_", "torch.nn.Sequential", "torch.nn.init.kaiming_normal_", "torchvision.models.resnet18", "torch.nn.Conv2d", "torch.nn.Linear", "torch.nn.AvgPool2d", "torch.nn.init.normal_" ]
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add10 = lambda x: x+10 print(add10(20)) square_of_numbers = lambda x: x*x print(square_of_numbers(9)) add_3_num = lambda x,y,z: x+y+z print(add_3_num(10,50,100)) points2D = [(1, 9), (4, 1), (5, -3), (10, 2)] points2D_sorted = sorted(points2D) print(points2D_sorted) points2D_sorted = sorted(points2D, key = lambda x...
[ "functools.reduce" ]
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#!/usr/bin/python """ Generate a new (and empty) save file with predefined keys. Used to play with externally generated keys. (c) 2015 <NAME> Distributed under the GNU GPL v3 or later, WITHOUT ANY WARRANTY. See the file "LICENSE.md" for license information. Usage: ./make-funny-savefile.py <public key> <private ...
[ "os.urandom", "struct.pack" ]
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import pandas as pd import matplotlib.pyplot as plt data_frame = pd.read_table("../../../r-basic/data/datacrab.txt", sep = " ") data_frame data_frame.describe() data_frame.dropna().describe()
[ "pandas.read_table" ]
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import socket import sys import time # Python 2.x-3.x compatibility try: import cPickle as pickle except ImportError: import pickle class SimpleUDPClient(object): UDP_IP = "127.0.0.1" #UDP_IP = "192.168.42.1" #UDP_IP = "192.168.3.11" UDP_PORT = 5005 sock=None def __init__(self, UDP_IP, UDP_PORT,pickle_prot...
[ "pickle.dumps", "time.time", "socket.socket", "sys.exit" ]
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import math from Implementations.Interfaces.IDeterministicAlgorithm import IDeterministicAlgorithm from Implementations.helpers import Helper from Implementations.helpers.Helper import ListToPolynomial, toNumbers, sumSet class DivideAndConquerRunner(IDeterministicAlgorithm): def __init__(self, label, benchmarkM...
[ "Implementations.helpers.Helper.divideAndConquerSumSet" ]
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from django import template register = template.Library() def get(value, key): return value.get(key) register.filter('get', get)
[ "django.template.Library" ]
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import time import cv2 import mss import numpy frame_width = 800 frame_height = 640 frame_rate = 20.0 VIDEO_OUTPUT = "output.avi" fourcc = cv2.VideoWriter_fourcc(*'XVID') out = cv2.VideoWriter(VIDEO_OUTPUT, fourcc, frame_rate, (frame_width, frame_height)) with mss.mss() as sct: # Part of t...
[ "mss.mss", "cv2.VideoWriter", "cv2.imshow", "cv2.waitKey", "cv2.destroyAllWindows", "cv2.VideoWriter_fourcc", "cv2.cvtColor", "cv2.resize", "time.time" ]
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations from django.conf import settings class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('notifications', '0003_auto_20150702_1236'...
[ "django.db.models.ForeignKey", "django.db.migrations.AlterModelOptions", "django.db.models.AutoField", "django.db.models.PositiveIntegerField", "django.db.models.DateTimeField", "django.db.migrations.swappable_dependency", "django.db.models.CharField" ]
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# python libraries import numpy as np # matplotlib libraries import matplotlib.pyplot as plt from sklearn.model_selection import StratifiedKFold from sklearn.metrics import f1_score, make_scorer, accuracy_score, average_precision_score, confusion_matrix from sklearn.ensemble import RandomForestClassifier from sklearn....
[ "sys.path.insert", "util.code_truVrest", "matplotlib.pyplot.xticks", "matplotlib.pyplot.ylabel", "numpy.arange", "sklearn.utils.shuffle", "matplotlib.pyplot.legend", "matplotlib.pyplot.plot", "matplotlib.pyplot.xlabel", "numpy.argmax", "sklearn.preprocessing.StandardScaler", "numpy.array", "...
[((444, 483), 'sys.path.insert', 'sys.path.insert', (['(0)', '"""../data+wrangling"""'], {}), "(0, '../data+wrangling')\n", (459, 483), False, 'import sys\n'), ((3532, 3549), 'numpy.argmax', 'np.argmax', (['scores'], {}), '(scores)\n', (3541, 3549), True, 'import numpy as np\n'), ((3930, 3986), 'matplotlib.pyplot.plot'...
#!/usr/bin/env python3 from smbus2 import SMBusWrapper from ubloxI2c import UbloxI2C from ubloxMessage import UbloxMessage import logging import time def extractMessages(data): messages = [] while data is not None: msgFormat, msgData, remainder = UbloxMessage.parse(data, raw=True) print('{} m...
[ "logging.basicConfig", "ubloxMessage.UbloxMessage.parse", "argparse.ArgumentParser", "smbus2.SMBusWrapper", "time.sleep", "ubloxI2c.UbloxI2C" ]
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from django.contrib import admin from finial import models class UserTemplateOverrideAdmin(admin.ModelAdmin): search_fields = ('user', 'override_name', 'override_dir') raw_id_fields = ('user',) list_display = ('user', 'override_name', 'override_dir', 'priority', ) list_filter = ('override_name', 'over...
[ "django.contrib.admin.site.register" ]
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from sklearn import datasets import time from sklearn.decomposition import PCA as SPCA import cupy as cp from mlcu.ml.PCA import * if __name__=="__main__": ''' loaded_data = datasets.load_iris() #加载鸢尾花数据 data = cp.array(loaded_data.data) ''' #此数据测试下cuml运算1.9s,sklearn13.1s X = cp.random.ran...
[ "sklearn.decomposition.PCA", "time.time", "cupy.random.rand" ]
[((307, 335), 'cupy.random.rand', 'cp.random.rand', (['(1000000)', '(100)'], {}), '(1000000, 100)\n', (321, 335), True, 'import cupy as cp\n'), ((369, 380), 'time.time', 'time.time', ([], {}), '()\n', (378, 380), False, 'import time\n'), ((411, 422), 'time.time', 'time.time', ([], {}), '()\n', (420, 422), False, 'impor...
from cobs import cobs from contextlib import contextmanager import os import serial import serial.tools.list_ports import six import sys from threading import Thread import zlib software_root = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(software_root, 'proto_gen')) from proto_gen import s...
[ "serial.tools.list_ports.comports", "six.moves.input", "cobs.cobs.decode", "proto_gen.splitflap_pb2.SplitflapCommand.ModuleCommand", "os.path.join", "proto_gen.splitflap_pb2.ToSplitflap", "serial.Serial", "cobs.cobs.encode", "zlib.crc32", "os.path.abspath", "threading.Thread", "proto_gen.split...
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import argparse import os import sys from PyQt5 import QtWidgets from .rama_analyzer import RamaAnalyzerMain def run(): p = argparse.ArgumentParser(description='Analyze Ramachandran plots of Gromacs trajectories') p.add_argument('-f', action='store', dest='XVGFILE', type=str, help='.xvg file produced by gmx...
[ "os.path.expanduser", "os.path.exists", "argparse.ArgumentParser", "PyQt5.QtWidgets.QApplication" ]
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import os from datetime import datetime import sys try: from hashlib import sha1 except ImportError: sys.exit('ImportError: No module named hashlib\n' 'If you are on python2.4 this library is not part of python. ' 'Please install it. Example: easy_install hashlib') from sqlalchemy imp...
[ "sqlalchemy.orm.relation", "sqlalchemy.types.String", "comcenter.model.DBSession.delete", "sqlalchemy.ForeignKey", "comcenter.model.DBSession.add", "comcenter.model.DBSession.update", "comcenter.model.DBSession.query", "comcenter.model.DBSession.flush", "sys.exit", "sqlalchemy.Column" ]
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import os from html2md import LOCATIONS from html2md.converter.Rule import Rule # TODO: duplicate code, see Transformer.py def _get_class(kls): parts = kls.split('.') module = ".".join(parts[:-1]) m = __import__( module ) for comp in parts[1:]: m = getattr(m, comp) return m class Rules(...
[ "html2md.converter.Rule.Rule" ]
[((749, 763), 'html2md.converter.Rule.Rule', 'Rule', (['selector'], {}), '(selector)\n', (753, 763), False, 'from html2md.converter.Rule import Rule\n')]
#!/usr/bin/python2.7 """ Copyright (C) 2014 Reinventing Geospatial, Inc. 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 ...
[ "operator.attrgetter", "os.path.exists", "scripts.geopackage.srs.geodetic.Geodetic", "scripts.geopackage.core.geopackage_core.GeoPackageCore.create_core_tables", "scripts.geopackage.srs.ellipsoidal_mercator.EllipsoidalMercator", "scripts.geopackage.tiles.tiles_content_entry.TilesContentEntry", "scripts....
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from jumpscale import j print("[-] zerodb started / configured") #zerodb cl = j.clients.zdb.testdb_server_start_client_get(start=True) #starts & resets a zdb in seq mode with name test server = j.servers.gedis.configure(host = "localhost", port = "8000", websockets_port = "8001", ssl = False, \ zdb_insta...
[ "jumpscale.j.servers.gedis.configure", "jumpscale.j.clients.zdb.testdb_server_start_client_get" ]
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from flask import Flask, request from flask_restful import Resource from flask_jwt_extended import jwt_required, get_jwt_identity from ..models import User, Order, MealItem class PostOrder(Resource): @jwt_required def post(self): '''post an order by the user''' data = request.get_json() ...
[ "flask_jwt_extended.get_jwt_identity", "flask.request.get_json" ]
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# Generated by Django 3.1.7 on 2021-04-29 15:19 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('core', '0008_auto_20210426_1518'), ] operations = [ migrations.AddField( model_name='piece', ...
[ "django.db.models.ForeignKey" ]
[((371, 561), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'blank': '(True)', 'help_text': '"""The turn during which this piece was destroyed."""', 'null': '(True)', 'on_delete': 'django.db.models.deletion.CASCADE', 'related_name': '"""+"""', 'to': '"""core.turn"""'}), "(blank=True, help_text=\n 'The tu...
"""The TrueNAS integration.""" import abc import asyncio import async_timeout import logging import voluptuous as vol from aiotruenas_client import CachingMachine as Machine from aiotruenas_client.disk import Disk from aiotruenas_client.virtualmachine import VirtualMachine from homeassistant.config_entries import Co...
[ "logging.getLogger", "async_timeout.timeout", "voluptuous.Schema", "aiotruenas_client.CachingMachine.create", "homeassistant.util.slugify", "homeassistant.helpers.update_coordinator.UpdateFailed", "datetime.timedelta" ]
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# coding=utf8 import json import math from numpy.ma import arange from data_utils import build_data_loader from model_utils import load_vocabulary, build_model, model_evaluate with open('config.json') as config_file: config = json.load(config_file) MIN_EPOCH = config['SELECTOR']['MIN_EPOCH'] MAX_EPOCH = config[...
[ "model_utils.model_evaluate", "data_utils.build_data_loader", "numpy.ma.arange", "model_utils.load_vocabulary", "json.load", "math.exp" ]
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import os import numpy as np from scipy.stats import rankdata from scipy.special import binom #faster than comb import dynamicTreeCut.df_apply from functools import partial from dynamicTreeCut.R_func import * chunkSize = 100 #Function to index flat matrix as squareform matrix def dist_index(i, j, matrix, l, n): ...
[ "numpy.sqrt", "numpy.argsort", "numpy.array", "numpy.arange", "numpy.mean", "numpy.repeat", "numpy.max", "numpy.min", "numpy.argmin", "numpy.round", "os.path.isfile", "numpy.isnan", "numpy.unique", "numpy.logical_and", "scipy.stats.rankdata", "numpy.logical_or", "numpy.append", "nu...
[((3209, 3238), 'numpy.mean', 'np.mean', (['CoreAverageDistances'], {}), '(CoreAverageDistances)\n', (3216, 3238), True, 'import numpy as np\n'), ((3289, 3304), 'numpy.round', 'np.round', (['index'], {}), '(index)\n', (3297, 3304), True, 'import numpy as np\n'), ((4419, 4449), 'numpy.round', 'np.round', (['(nMerge * re...
#from django.utils.translation import ugettext as _ import datetime from django.db import models from django.db.models import Q from django.contrib.auth.models import User from model_utils.models import TimeStampedModel from django.utils.timezone import now from model_utils import Choices from django.utils import t...
[ "model_utils.Choices", "datetime.time", "django.db.models.ForeignKey", "django.db.models.IntegerField", "django.db.models.BooleanField", "django.utils.timezone.now", "datetime.datetime.now", "django.db.models.SlugField", "django.db.models.DateTimeField", "django.db.models.DecimalField", "django....
[((378, 422), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(50)', 'unique': '(True)'}), '(max_length=50, unique=True)\n', (394, 422), False, 'from django.db import models\n'), ((434, 488), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(25)', 'null': '(True)', 'blank': ...
import requests, time, sys, schedule # https://requests.readthedocs.io/en/master/ from bs4 import BeautifulSoup # https://www.crummy.com/software/BeautifulSoup/bs4/doc/ import smtplib # Import the email modules we'll need from email.message import EmailMessage # Get list of offers # https://boise.craigslist.org/search...
[ "smtplib.SMTP", "time.sleep", "requests.get", "bs4.BeautifulSoup", "email.message.EmailMessage" ]
[((1705, 1722), 'requests.get', 'requests.get', (['url'], {}), '(url)\n', (1717, 1722), False, 'import requests, time, sys, schedule\n'), ((1734, 1776), 'bs4.BeautifulSoup', 'BeautifulSoup', (['page.content', '"""html.parser"""'], {}), "(page.content, 'html.parser')\n", (1747, 1776), False, 'from bs4 import BeautifulSo...
import sqlite3 as sql def intialDatabaseCreation(): conn = sql.connect('database.db') print("Opened database successfully"); conn.execute('CREATE TABLE contacts (name TEXT, addr TEXT, city TEXT, email TEXT)') conn.execute('CREATE TABLE qrCodes (account TEXT, query TEXT, uses integer )') print("Table crea...
[ "sqlite3.connect" ]
[((62, 88), 'sqlite3.connect', 'sql.connect', (['"""database.db"""'], {}), "('database.db')\n", (73, 88), True, 'import sqlite3 as sql\n'), ((420, 446), 'sqlite3.connect', 'sql.connect', (['"""database.db"""'], {}), "('database.db')\n", (431, 446), True, 'import sqlite3 as sql\n'), ((778, 804), 'sqlite3.connect', 'sql....
#!/usr/bin/env python import rospy from pb_msgs.msg import LocalizationEstimate from pb_msgs.msg import PerceptionObstacles from pb_msgs.msg import LaneMarkers from pb_msgs.msg import LaneMarker from math import radians ''' LaneMarkers { optional LaneMarker left_lane_marker = 1; optional LaneMarker right_lane_ma...
[ "pb_msgs.msg.LocalizationEstimate", "rospy.is_shutdown", "rospy.init_node", "math.radians", "rospy.Rate", "rospy.Publisher" ]
[((419, 431), 'math.radians', 'radians', (['(220)'], {}), '(220)\n', (426, 431), False, 'from math import radians\n'), ((560, 604), 'rospy.init_node', 'rospy.init_node', (['"""test_node"""'], {'anonymous': '(True)'}), "('test_node', anonymous=True)\n", (575, 604), False, 'import rospy\n'), ((629, 698), 'rospy.Publisher...
from rest_framework import serializers from social.models import Post, Comment, UserProfile class CommentSerializer(serializers.ModelSerializer): class Meta: model = Comment fields = '__all__' class PostSerializer(serializers.ModelSerializer): comments = CommentSerializer(many=True, requir...
[ "rest_framework.serializers.SlugField", "rest_framework.serializers.DateTimeField", "rest_framework.serializers.ReadOnlyField", "rest_framework.serializers.TimeField", "rest_framework.serializers.ImageField", "rest_framework.serializers.CharField" ]
[((344, 395), 'rest_framework.serializers.ReadOnlyField', 'serializers.ReadOnlyField', ([], {'source': '"""author.username"""'}), "(source='author.username')\n", (369, 395), False, 'from rest_framework import serializers\n'), ((408, 444), 'rest_framework.serializers.CharField', 'serializers.CharField', ([], {'required'...
# Generated by Django 2.1.2 on 2018-12-26 15:45 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('contacts', '0001_initial'), ] operations = [ migrations.AlterUniqueTogether( name='contact', unique_together={('email',)}, ...
[ "django.db.migrations.AlterUniqueTogether" ]
[((217, 293), 'django.db.migrations.AlterUniqueTogether', 'migrations.AlterUniqueTogether', ([], {'name': '"""contact"""', 'unique_together': "{('email',)}"}), "(name='contact', unique_together={('email',)})\n", (247, 293), False, 'from django.db import migrations\n')]
import cv2, torch from dl.data.txtrecog import datasets from dl.models import FOTSRes50 from dl.data.utils.converter import toVisualizeQuadsTextRGBimg if __name__ == '__main__': model = FOTSRes50(chars=datasets.SynthText_char_labels_without_upper_blank, input_shape=(None, None, 3), feature_height=8).cuda() mo...
[ "dl.models.FOTSRes50", "cv2.cvtColor", "cv2.resize", "cv2.waitKey", "cv2.imread" ]
[((772, 785), 'cv2.waitKey', 'cv2.waitKey', ([], {}), '()\n', (783, 785), False, 'import cv2, torch\n'), ((1576, 1589), 'cv2.waitKey', 'cv2.waitKey', ([], {}), '()\n', (1587, 1589), False, 'import cv2, torch\n'), ((634, 687), 'cv2.imread', 'cv2.imread', (['"""../../scripts/fots/assets/download.jpeg"""'], {}), "('../../...
import os, sys import shutil from pathlib import Path import pandas as pd import urllib import configparser try: from bing import Bing except ImportError: # Python 3 from .bing import Bing def download(query, limit=100, output_dir='dataset', adult_filter_off=False, force_replace=False, timeout=60, verbose...
[ "bing.Bing", "sys.exit", "pathlib.Path", "shutil.rmtree", "pathlib.Path.is_dir", "pathlib.Path.mkdir", "pandas.read_excel", "pathlib.Path.isdir", "pandas.isna", "configparser.RawConfigParser", "urllib.parse.quote_plus" ]
[((943, 1006), 'bing.Bing', 'Bing', (['query', 'limit', 'image_dir', 'adult', 'timeout', 'filters', 'verbose'], {}), '(query, limit, image_dir, adult, timeout, filters, verbose)\n', (947, 1006), False, 'from bing import Bing\n'), ((1117, 1147), 'configparser.RawConfigParser', 'configparser.RawConfigParser', ([], {}), '...
import torch.nn as nn import torch import cv2 import numpy as np def eval_net( net, dataset, gpu=True, vis=None, vis_im=None, vis_gt=None, loss=nn.MSELoss() ): criterion = loss net.eval() losses = 0 torch.cuda.empty_cache() for iteration, data in enumerate(dataset): img = data["image"]...
[ "torch.nn.MSELoss", "torch.cuda.empty_cache" ]
[((150, 162), 'torch.nn.MSELoss', 'nn.MSELoss', ([], {}), '()\n', (160, 162), True, 'import torch.nn as nn\n'), ((221, 245), 'torch.cuda.empty_cache', 'torch.cuda.empty_cache', ([], {}), '()\n', (243, 245), False, 'import torch\n')]
''' Max Of Three Exercise 28 Implement a function that takes as input three variables, and returns the largest of the three. Do this without using the Python max() function ''' import random def max_of_three(a, b, c): if a>b: if a>c: return a else: return c else: ...
[ "random.randint" ]
[((556, 581), 'random.randint', 'random.randint', (['(-100)', '(100)'], {}), '(-100, 100)\n', (570, 581), False, 'import random\n'), ((590, 615), 'random.randint', 'random.randint', (['(-100)', '(100)'], {}), '(-100, 100)\n', (604, 615), False, 'import random\n'), ((624, 649), 'random.randint', 'random.randint', (['(-1...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ This is the script with the main code of the application """ import json import logging import aiohttp.web import connexion async def index(request): """ Redirecting root to index.html """ raise aiohttp.web.HTTPFound('/index.html') def go(): "...
[ "logging.getLogger", "connexion.AioHttpApp", "logging.basicConfig" ]
[((365, 434), 'connexion.AioHttpApp', 'connexion.AioHttpApp', (['__name__'], {'port': '(80)', 'specification_dir': '"""/app/web"""'}), "(__name__, port=80, specification_dir='/app/web')\n", (385, 434), False, 'import connexion\n'), ((662, 686), 'logging.getLogger', 'logging.getLogger', (['"""app"""'], {}), "('app')\n",...
from types import TracebackType from typing import Dict, Optional, Type, Union try: from typing import Literal except ImportError: from typing_extensions import Literal from aiohttp.client import ClientSession from warnings import warn from neispy.error import ExceptionsMapping class NeispyRequest: BASE...
[ "warnings.warn", "aiohttp.client.ClientSession" ]
[((637, 680), 'warnings.warn', 'warn', (['"""API키가 없습니다, 샘플키로 요청합니다"""', 'UserWarning'], {}), "('API키가 없습니다, 샘플키로 요청합니다', UserWarning)\n", (641, 680), False, 'from warnings import warn\n'), ((1350, 1365), 'aiohttp.client.ClientSession', 'ClientSession', ([], {}), '()\n', (1363, 1365), False, 'from aiohttp.client import...
import pickle import numpy as np import pygame from time import sleep #Duplicate of the Arduino map function (needed for processing autoencoder data) def map(x, in_min, in_max, out_min, out_max): return (x - in_min) * (out_max - out_min) // (in_max - in_min) + out_min class number: def __init__(self, imag...
[ "numpy.reshape", "pygame.init", "pygame.quit", "pygame.event.get", "pygame.display.set_mode", "pygame.display.flip", "pickle.load", "time.sleep", "pygame.draw.rect", "pygame.display.set_caption", "pygame.font.Font" ]
[((4453, 4467), 'pickle.load', 'pickle.load', (['f'], {}), '(f)\n', (4464, 4467), False, 'import pickle\n'), ((1205, 1218), 'pygame.init', 'pygame.init', ([], {}), '()\n', (1216, 1218), False, 'import pygame\n'), ((1261, 1310), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(screenSize, screenSize)'], {}), '(...
from argparse import ArgumentParser from environment import Environment from modules.migration.managers.migration_manager import MigrationManager """ Script for running database migrations """ def parse_args(): """Parses argument parameters """ parser = ArgumentParser() parser.add_argument( '...
[ "environment.Environment", "modules.migration.managers.migration_manager.MigrationManager", "argparse.ArgumentParser" ]
[((269, 285), 'argparse.ArgumentParser', 'ArgumentParser', ([], {}), '()\n', (283, 285), False, 'from argparse import ArgumentParser\n'), ((1207, 1220), 'environment.Environment', 'Environment', ([], {}), '()\n', (1218, 1220), False, 'from environment import Environment\n'), ((1519, 1537), 'modules.migration.managers.m...
from __future__ import unicode_literals from django.core.urlresolvers import reverse from django.db import models from django.utils.translation import ugettext_lazy as _ from django.utils.encoding import python_2_unicode_compatible from base.models import ActiveManager, StandardMetadata @python_2_unicode_compatible...
[ "base.models.ActiveManager", "django.db.models.Manager", "django.core.urlresolvers.reverse", "django.utils.translation.ugettext_lazy" ]
[((783, 799), 'django.db.models.Manager', 'models.Manager', ([], {}), '()\n', (797, 799), False, 'from django.db import models\n'), ((813, 828), 'base.models.ActiveManager', 'ActiveManager', ([], {}), '()\n', (826, 828), False, 'from base.models import ActiveManager, StandardMetadata\n'), ((689, 698), 'django.utils.tra...
import random import sqlite3 def globalrecommendations(): globalrecommendationslist=list() handle= open("static/recommendation_files/global.txt") rankingdict=dict() for line in handle: terms=line.strip() rankingdict[terms]= rankingdict.get(terms,0)+1 sorted_ranking = sorted(rankingd...
[ "sqlite3.connect", "random.randint" ]
[((942, 971), 'random.randint', 'random.randint', (['(0)', 'termscount'], {}), '(0, termscount)\n', (956, 971), False, 'import random\n'), ((1064, 1100), 'sqlite3.connect', 'sqlite3.connect', (['"""static/catalog.db"""'], {}), "('static/catalog.db')\n", (1079, 1100), False, 'import sqlite3\n'), ((1391, 1427), 'sqlite3....
# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'resources\ui\mainwindow.ui' # # Created: Sat Jul 15 12:57:34 2017 # by: pyside-uic 0.2.15 running on PySide 1.2.4 # # WARNING! All changes made in this file will be lost! from PySide import QtCore, QtGui class Ui_MainWindow(object): ...
[ "PySide.QtGui.QGridLayout", "PySide.QtCore.QMetaObject.connectSlotsByName", "PySide.QtGui.QFont", "PySide.QtGui.QTableWidget", "PySide.QtCore.QSize", "PySide.QtGui.QSizePolicy", "PySide.QtGui.QPushButton", "PySide.QtGui.QVBoxLayout", "PySide.QtGui.QWidget", "PySide.QtGui.QLabel", "PySide.QtGui.Q...
[((458, 531), 'PySide.QtGui.QSizePolicy', 'QtGui.QSizePolicy', (['QtGui.QSizePolicy.Preferred', 'QtGui.QSizePolicy.Minimum'], {}), '(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Minimum)\n', (475, 531), False, 'from PySide import QtCore, QtGui\n'), ((886, 911), 'PySide.QtGui.QWidget', 'QtGui.QWidget', (['MainWindow']...
from comet_ml import experiment from data_loader.uts_regression_data_loader import UtsRegressionDataLoader from models.uts_regression_model import UtsRegressionModel from trainers.uts_regression_trainer import UtsRegressionModelTrainer from evaluater.uts_regression_evaluater import UtsRegressionEvaluater from utils.con...
[ "data_loader.uts_regression_data_loader.UtsRegressionDataLoader", "utils.config.process_config_UtsRegression", "models.uts_regression_model.UtsRegressionModel", "trainers.uts_regression_trainer.UtsRegressionModelTrainer", "evaluater.uts_regression_evaluater.UtsRegressionEvaluater", "utils.utils.get_args",...
[((799, 888), 'utils.dirs.create_dirs', 'create_dirs', (['[config.callbacks.tensorboard_log_dir, config.callbacks.checkpoint_dir]'], {}), '([config.callbacks.tensorboard_log_dir, config.callbacks.\n checkpoint_dir])\n', (810, 888), False, 'from utils.dirs import create_dirs\n'), ((943, 974), 'data_loader.uts_regress...
import datetime from nose.tools import ( assert_raises, eq_, set_trace, ) from . import DatabaseTest from bot import Bot from model import ( InvalidPost, Post, _now, ) class TestBot(DatabaseTest): def test_publishable_posts(self): bot = self._bot(config=dict( state_...
[ "nose.tools.eq_", "model.Post.from_content", "nose.tools.assert_raises", "model._now", "datetime.timedelta" ]
[((382, 411), 'nose.tools.eq_', 'eq_', (['(False)', 'bot.state_updated'], {}), '(False, bot.state_updated)\n', (385, 411), False, 'from nose.tools import assert_raises, eq_, set_trace\n'), ((622, 661), 'nose.tools.eq_', 'eq_', (['new_post.content', 'bot.new_posts[0]'], {}), '(new_post.content, bot.new_posts[0])\n', (62...
from __future__ import unicode_literals from __future__ import print_function from __future__ import division from __future__ import absolute_import from future import standard_library standard_library.install_aliases() import os import sys import hysds_commons.linux_utils def get_container_host_ip(): """Return ...
[ "future.standard_library.install_aliases", "sys.platform.startswith" ]
[((185, 219), 'future.standard_library.install_aliases', 'standard_library.install_aliases', ([], {}), '()\n', (217, 219), False, 'from future import standard_library\n'), ((465, 497), 'sys.platform.startswith', 'sys.platform.startswith', (['"""linux"""'], {}), "('linux')\n", (488, 497), False, 'import sys\n')]
import dataclasses from typing import Any, ClassVar, Dict, Iterable, Optional from dbdaora.data_sources.fallback import FallbackDataSource @dataclasses.dataclass class DictFallbackDataSource(FallbackDataSource[str]): db: Dict[Optional[str], Dict[str, Any]] = dataclasses.field( default_factory=dict ) ...
[ "dataclasses.field" ]
[((266, 305), 'dataclasses.field', 'dataclasses.field', ([], {'default_factory': 'dict'}), '(default_factory=dict)\n', (283, 305), False, 'import dataclasses\n')]
import torch import torch.nn as nn from collections import Counter class GraphNorm(nn.Module): def __init__(self, latent_dim): super().__init__() self.weight = nn.Parameter(torch.ones(latent_dim)) self.bias = nn.Parameter(torch.zeros(latent_dim)) self.mean_scale = nn.Parameter(torch...
[ "torch.Tensor", "torch.zeros", "torch.ones" ]
[((194, 216), 'torch.ones', 'torch.ones', (['latent_dim'], {}), '(latent_dim)\n', (204, 216), False, 'import torch\n'), ((251, 274), 'torch.zeros', 'torch.zeros', (['latent_dim'], {}), '(latent_dim)\n', (262, 274), False, 'import torch\n'), ((315, 337), 'torch.ones', 'torch.ones', (['latent_dim'], {}), '(latent_dim)\n'...
#!/usr/bin/python import os os.system("cgx -bg blisk_pre.fbd") os.system("ccx blisk") os.system("cgx -bg blisk_post.fbd")
[ "os.system" ]
[((29, 63), 'os.system', 'os.system', (['"""cgx -bg blisk_pre.fbd"""'], {}), "('cgx -bg blisk_pre.fbd')\n", (38, 63), False, 'import os\n'), ((64, 86), 'os.system', 'os.system', (['"""ccx blisk"""'], {}), "('ccx blisk')\n", (73, 86), False, 'import os\n'), ((87, 122), 'os.system', 'os.system', (['"""cgx -bg blisk_post....
# DATA 515 - Spring 2017 # Homework 4 # <NAME> # 4/23/17 ##### FUNCTIONS ##### import os import requests def get_data(url): ''' Downloads the data if it is not present locally. Takes no action if the data are already present. Throws an exception if the URL does not exist. arguments -----...
[ "os.path.exists", "os.path.basename", "requests.get", "os.remove" ]
[((506, 527), 'os.path.basename', 'os.path.basename', (['url'], {}), '(url)\n', (522, 527), False, 'import os\n'), ((564, 588), 'os.path.exists', 'os.path.exists', (['filename'], {}), '(filename)\n', (578, 588), False, 'import os\n'), ((1666, 1687), 'os.path.basename', 'os.path.basename', (['url'], {}), '(url)\n', (168...
#!/usr/bin/env python # encoding: utf-8 ''' @project : MSRGCN @file : config.py @author : Droliven @contact : <EMAIL> @ide : PyCharm @time : 2021-07-27 16:56 ''' import os import getpass import torch import numpy as np class Config(): def __init__(self, exp_name="h36m", input_n=10, output_n=10, dct_n=1...
[ "getpass.getuser", "numpy.array", "os.path.join" ]
[((397, 414), 'getpass.getuser', 'getpass.getuser', ([], {}), '()\n', (412, 414), False, 'import getpass\n'), ((5601, 5692), 'os.path.join', 'os.path.join', (['"""./ckpt/"""', 'exp_name', "('short_term' if self.output_n == 10 else 'long_term')"], {}), "('./ckpt/', exp_name, 'short_term' if self.output_n == 10 else\n ...
import numpy as np import pandas as pd from numpy.testing import assert_array_equal from numpy.testing import assert_array_almost_equal from auxiliary.functions_daniel import ( rastrigin_instance, griewank_instance, levi_no_13_instance, rosenbrock_instance, ) def test_rastrigin(): inputs = crea...
[ "auxiliary.functions_daniel.rosenbrock_instance", "auxiliary.functions_daniel.rastrigin_instance", "numpy.testing.assert_array_almost_equal", "auxiliary.functions_daniel.levi_no_13_instance", "auxiliary.functions_daniel.griewank_instance", "numpy.array" ]
[((347, 368), 'auxiliary.functions_daniel.rastrigin_instance', 'rastrigin_instance', (['(3)'], {}), '(3)\n', (365, 368), False, 'from auxiliary.functions_daniel import rastrigin_instance, griewank_instance, levi_no_13_instance, rosenbrock_instance\n'), ((389, 433), 'numpy.array', 'np.array', (['[15, 111, 139, 31, 2, 46...
# Copyright 2018 Blade Team of Tencent. All Rights Reserved. # # 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 applicab...
[ "tensorflow.python.platform.app.run", "tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef", "argparse.ArgumentParser", "tensorflow.python.training.saver.checkpoint_exists", "tensorflow.python.tools.saved_model_utils.get_meta_graph_def", "tensorflow.python.platform.gfile.FastGFile", "sys.exc_info", "...
[((2533, 2547), 'tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef', 'MetaGraphDef', ([], {}), '()\n', (2545, 2547), False, 'from tensorflow.core.protobuf.meta_graph_pb2 import MetaGraphDef\n'), ((5678, 5787), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Check whether a TensorFlow m...
from kivy.app import App from kivy.uix.gridlayout import GridLayout from kivy.uix.label import Label from kivy.uix.textinput import TextInput from kivy.uix.button import Button from kivy.uix.popup import Popup class Screen(GridLayout): def __init__(self) -> None: super().__init__() self.add_widge...
[ "kivy.uix.label.Label" ]
[((322, 345), 'kivy.uix.label.Label', 'Label', ([], {'text': '"""Tela Base"""'}), "(text='Tela Base')\n", (327, 345), False, 'from kivy.uix.label import Label\n')]
# Copyright (C) <NAME> 2020. # Distributed under the MIT License (see the accompanying README.md and LICENSE files). import numpy as np import utils.clicks as clk def oracle_doc_variance( expected_reward, doc_values, rel_prob, obs_prob, sampled_inv_rankings): n_doc...
[ "numpy.mean", "numpy.tile", "numpy.exp", "numpy.sum", "utils.clicks.bernoilli_sample_from_probs", "numpy.zeros", "numpy.add.at", "numpy.amax", "numpy.arange" ]
[((360, 407), 'numpy.mean', 'np.mean', (['obs_prob[sampled_inv_rankings]'], {'axis': '(0)'}), '(obs_prob[sampled_inv_rankings], axis=0)\n', (367, 407), True, 'import numpy as np\n'), ((643, 664), 'numpy.mean', 'np.mean', (['doc_variance'], {}), '(doc_variance)\n', (650, 664), True, 'import numpy as np\n'), ((1262, 1309...
import pytest from pytest import ( raises, ) from lark.exceptions import ( UnexpectedToken, ) valid_dicts = [ """ a = {a: b} """, """ a = {1: 2} """, """ { 1: 2, 3: 4 } """ ] @pytest.mark.parametrize('good_code', valid_dicts) def test_grammar_good_dicts(good_code, lark_gramma...
[ "pytest.mark.parametrize", "pytest.raises" ]
[((220, 269), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""good_code"""', 'valid_dicts'], {}), "('good_code', valid_dicts)\n", (243, 269), False, 'import pytest\n'), ((488, 538), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""bad_code"""', 'invalid_dicts'], {}), "('bad_code', invalid_dicts)\...
#------------------------------------------------------------------------------ # Copyright 2013 Esri # 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/LICENS...
[ "arcpy.GetMessages", "os.path.join", "os.path.basename", "arcpy.SetMosaicDatasetProperties_management" ]
[((1661, 1685), 'os.path.basename', 'os.path.basename', (['mdPath'], {}), '(mdPath)\n', (1677, 1685), False, 'import arcpy, os, sys\n'), ((5536, 6370), 'arcpy.SetMosaicDatasetProperties_management', 'arcpy.SetMosaicDatasetProperties_management', (['mdPath', 'maxRequestSizex', 'maxRequestSizey', 'allowedCompression', 'd...
''' GUI for the COVID-19 chatbot. Enter the query and it returns the list of top 5 papers which can answer the query. ''' from tkinter import * root_path = '/Users/Janjua/Desktop/Projects/Octofying-COVID19-Literature/dataset/CORD-19-research-challenge/' from sentence_transformers import SentenceTransf...
[ "pickle.load", "sentence_transformers.SentenceTransformer", "pandas.read_csv" ]
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# -*- coding: utf-8 -*- from openerp import SUPERUSER_ID from openerp.osv import osv, orm, fields from openerp.tools.translate import _ class sale_order_line(osv.Model): _inherit = "sale.order.line" _columns = { 'linked_line_id': fields.many2one('sale.order.line', 'Linked Order Line', domain="[('orde...
[ "openerp.osv.fields.many2one", "openerp.tools.translate._", "openerp.osv.fields.one2many" ]
[((249, 368), 'openerp.osv.fields.many2one', 'fields.many2one', (['"""sale.order.line"""', '"""Linked Order Line"""'], {'domain': '"""[(\'order_id\',\'!=\',order_id)]"""', 'ondelete': '"""cascade"""'}), '(\'sale.order.line\', \'Linked Order Line\', domain=\n "[(\'order_id\',\'!=\',order_id)]", ondelete=\'cascade\')\...
import ftplib import os.path host = 'localhost' username = 'mory' password = '<PASSWORD>' server = ftplib.FTP(host) server.login(username, password) def upload(server, filename, bufsize=1024): pwd = server.pwd() basename = os.path.basename(filename) ftp_path = os.path.join(pwd, f"ftp_{basename}") wi...
[ "ftplib.FTP" ]
[((101, 117), 'ftplib.FTP', 'ftplib.FTP', (['host'], {}), '(host)\n', (111, 117), False, 'import ftplib\n')]