code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
from pygameImporter import pygame
from Frame.baseFunctions import *
from Frame.gui.Gui import Gui
class ProgressBar(Gui):
def __init__(self, fillPercentage, fillColor, *args, **kwargs):
super().__init__(*args, **kwargs)
output("Progress Bar: Creating " + self.text + " progress bar...", "debug")
... | [
"pygameImporter.pygame.draw.polygon"
] | [((1171, 1235), 'pygameImporter.pygame.draw.polygon', 'pygame.draw.polygon', (['self.window.surface', 'self.fillColor', 'points'], {}), '(self.window.surface, self.fillColor, points)\n', (1190, 1235), False, 'from pygameImporter import pygame\n')] |
from enums.enums import MediusEnum, CallbackStatus
from utils import utils
from medius.mediuspackets.disbandclanresponse import DisbandClanResponseSerializer
class DisbandClanSerializer:
data_dict = [
{'name': 'mediusid', 'n_bytes': 2, 'cast': None},
{'name': 'message_id', 'n_bytes': MediusEnum.MES... | [
"medius.mediuspackets.disbandclanresponse.DisbandClanResponseSerializer.build"
] | [((784, 873), 'medius.mediuspackets.disbandclanresponse.DisbandClanResponseSerializer.build', 'DisbandClanResponseSerializer.build', (["serialized['message_id']", 'CallbackStatus.SUCCESS'], {}), "(serialized['message_id'],\n CallbackStatus.SUCCESS)\n", (819, 873), False, 'from medius.mediuspackets.disbandclanrespons... |
# coding=utf-8
from bs4 import BeautifulSoup
import copy
import time
import json
import LOGIN
import MENU
class PlannedCourseInfo:
def __init__(self, main_num=None, name=None, code=None, margin=None, detail=None, url=None, course_dic=None):
if course_dic is None:
self.num = str(main_num)
... | [
"copy.deepcopy",
"json.load",
"json.dumps",
"time.sleep",
"time.time",
"MENU.MENU",
"LOGIN.Account",
"bs4.BeautifulSoup"
] | [((15458, 15473), 'LOGIN.Account', 'LOGIN.Account', ([], {}), '()\n', (15471, 15473), False, 'import LOGIN\n'), ((1384, 1398), 'json.dumps', 'json.dumps', (['js'], {}), '(js)\n', (1394, 1398), False, 'import json\n'), ((1933, 1961), 'MENU.MENU', 'MENU.MENU', ([], {'menu_dic': 'menu_dic'}), '(menu_dic=menu_dic)\n', (194... |
import os
from bitfield import BitField
from constance import config
from django.db import models
from django.contrib.auth.models import User
from django.conf import settings
from django.core.validators import MaxValueValidator, MinValueValidator
from django.db.models.signals import post_save
import django.db.models.o... | [
"django.db.models.OneToOneField",
"os.remove",
"django.core.validators.MinValueValidator",
"django.dispatch.receiver",
"django.db.models.BooleanField",
"os.path.isfile",
"timezone_field.TimeZoneField",
"bitfield.BitField",
"django.core.validators.MaxValueValidator"
] | [((4974, 5006), 'django.dispatch.receiver', 'receiver', (['post_save'], {'sender': 'User'}), '(post_save, sender=User)\n', (4982, 5006), False, 'from django.dispatch import receiver\n'), ((597, 657), 'django.db.models.BooleanField', 'models.BooleanField', ([], {'verbose_name': '"""публикация"""', 'default': '(True)'}),... |
import os
import numpy as np
from frovedis.exrpc.server import FrovedisServer
from frovedis.matrix.dvector import FrovedisDvector
from frovedis.matrix.dense import FrovedisRowmajorMatrix
FrovedisServer.initialize("mpirun -np 2 {}".format(os.environ['FROVEDIS_SERVER']))
dv = FrovedisDvector([1,2,3,4,5,6,7,8],dtype=np.... | [
"frovedis.exrpc.server.FrovedisServer.shut_down",
"frovedis.matrix.dvector.FrovedisDvector"
] | [((277, 336), 'frovedis.matrix.dvector.FrovedisDvector', 'FrovedisDvector', (['[1, 2, 3, 4, 5, 6, 7, 8]'], {'dtype': 'np.float64'}), '([1, 2, 3, 4, 5, 6, 7, 8], dtype=np.float64)\n', (292, 336), False, 'from frovedis.matrix.dvector import FrovedisDvector\n'), ((346, 372), 'frovedis.exrpc.server.FrovedisServer.shut_down... |
from manageXML.management.commands._giella_xml import GiellaXML
from django.core.management.base import BaseCommand, CommandError
import os, glob, sys
from manageXML.models import *
from django.conf import settings
from collections import defaultdict
ignore_affiliations = False
def create_lexeme(ll: GiellaXML.Item, ... | [
"os.path.basename",
"os.path.isdir",
"manageXML.management.commands._giella_xml.GiellaXML.parse_file",
"collections.defaultdict",
"django.core.management.base.CommandError",
"os.path.join"
] | [((1595, 1625), 'manageXML.management.commands._giella_xml.GiellaXML.parse_file', 'GiellaXML.parse_file', (['filename'], {}), '(filename)\n', (1615, 1625), False, 'from manageXML.management.commands._giella_xml import GiellaXML\n'), ((1760, 1786), 'os.path.basename', 'os.path.basename', (['filename'], {}), '(filename)\... |
import math
import os
import xml.etree.ElementTree
import numpy as np
import paddle
import six
from PIL import Image
from utils import image_util
class Settings(object):
def __init__(self,
label_file_path=None,
resize_h=300,
resize_w=300,
mean_... | [
"numpy.random.uniform",
"utils.image_util.sampler",
"utils.image_util.crop_image",
"utils.image_util.generate_batch_samples",
"PIL.Image.open",
"os.path.exists",
"numpy.array",
"numpy.swapaxes",
"PIL.Image.fromarray",
"utils.image_util.distort_image",
"paddle.reader.multiprocess_reader",
"nump... | [((3440, 3453), 'numpy.array', 'np.array', (['img'], {}), '(img)\n', (3448, 3453), True, 'import numpy as np\n'), ((6376, 6401), 'numpy.random.shuffle', 'np.random.shuffle', (['images'], {}), '(images)\n', (6393, 6401), True, 'import numpy as np\n'), ((3012, 3073), 'utils.image_util.generate_batch_samples', 'image_util... |
#!/usr/bin/python3
# LED Test
import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
LED = 13
GPIO.setup(LED, GPIO.OUT)
try:
print("LED is now flashing..")
print("Exit with CTRL+C")
while True:
GPIO.output(LED,1)
time.sleep(0.5)
GPIO.output(LED,0)
time.sleep(0.5)
excep... | [
"RPi.GPIO.setmode",
"RPi.GPIO.cleanup",
"RPi.GPIO.setup",
"time.sleep",
"RPi.GPIO.output",
"RPi.GPIO.setwarnings"
] | [((67, 89), 'RPi.GPIO.setmode', 'GPIO.setmode', (['GPIO.BCM'], {}), '(GPIO.BCM)\n', (79, 89), True, 'import RPi.GPIO as GPIO\n'), ((90, 113), 'RPi.GPIO.setwarnings', 'GPIO.setwarnings', (['(False)'], {}), '(False)\n', (106, 113), True, 'import RPi.GPIO as GPIO\n'), ((123, 148), 'RPi.GPIO.setup', 'GPIO.setup', (['LED', ... |
from Script.import_emojis import Emojis
from Script.import_functions import create_embed, int_to_str
async def server_info(ctx):
nb_humans = 0
for members in ctx.guild.members:
if members.bot == 0:
nb_humans += 1
nb_bots = 0
for members in ctx.guild.members:
if members.bot ... | [
"Script.import_functions.int_to_str"
] | [((990, 1011), 'Script.import_functions.int_to_str', 'int_to_str', (['nb_humans'], {}), '(nb_humans)\n', (1000, 1011), False, 'from Script.import_functions import create_embed, int_to_str\n'), ((1038, 1057), 'Script.import_functions.int_to_str', 'int_to_str', (['nb_bots'], {}), '(nb_bots)\n', (1048, 1057), False, 'from... |
# Copyright (c) 2011-2021, Camptocamp SA
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions an... | [
"c2cgeoportal_commons.models.DBSession.query",
"typing.cast",
"c2cgeoportal_commons.models.DBSession.expunge",
"c2cgeoportal_geoportal.lib.caching.get_region",
"c2cgeoportal_commons.lib.url.get_url2",
"c2cgeoportal_geoportal.views.proxy.Proxy.__init__",
"pyramid.httpexceptions.HTTPBadRequest",
"loggin... | [((1981, 1998), 'c2cgeoportal_geoportal.lib.caching.get_region', 'get_region', (['"""std"""'], {}), "('std')\n", (1991, 1998), False, 'from c2cgeoportal_geoportal.lib.caching import get_region\n'), ((2005, 2032), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (2022, 2032), False, 'import ... |
import numpy as np
from napari.utils import nbscreenshot
def test_nbscreenshot(viewer_factory):
"""Test taking a screenshot."""
view, viewer = viewer_factory()
np.random.seed(0)
data = np.random.random((10, 15))
viewer.add_image(data)
rich_display_object = nbscreenshot(viewer)
assert ha... | [
"numpy.random.random",
"numpy.random.seed",
"napari.utils.nbscreenshot"
] | [((176, 193), 'numpy.random.seed', 'np.random.seed', (['(0)'], {}), '(0)\n', (190, 193), True, 'import numpy as np\n'), ((205, 231), 'numpy.random.random', 'np.random.random', (['(10, 15)'], {}), '((10, 15))\n', (221, 231), True, 'import numpy as np\n'), ((286, 306), 'napari.utils.nbscreenshot', 'nbscreenshot', (['view... |
import base64
import random
import time
from RGUtil.RGCodeUtil import RGResCode
def get_data_with_request(_request):
if _request.is_json:
return _request.json
return _request.values
# if _request.method == "POST":
# return _request.form
# elif _request.json:
# return _request.... | [
"unicodedata.numeric",
"time.time_ns"
] | [((1285, 1307), 'unicodedata.numeric', 'unicodedata.numeric', (['s'], {}), '(s)\n', (1304, 1307), False, 'import unicodedata\n'), ((3331, 3345), 'time.time_ns', 'time.time_ns', ([], {}), '()\n', (3343, 3345), False, 'import time\n')] |
from ..files import ObjectReader
from ..streams import EndianBinaryWriter
from ..helpers import ImportHelper
from .. import files
from ..enums import FileType, ClassIDType
import os
from .. import environment
def save_ptr(obj, writer: EndianBinaryWriter):
if isinstance(obj, PPtr):
writer.write_int(obj.file... | [
"os.path.join",
"os.listdir"
] | [((1922, 1938), 'os.listdir', 'os.listdir', (['path'], {}), '(path)\n', (1932, 1938), False, 'import os\n'), ((2045, 2078), 'os.path.join', 'os.path.join', (['path', 'external_name'], {}), '(path, external_name)\n', (2057, 2078), False, 'import os\n')] |
import os
import numpy as np
import torch
import torch.nn as nn
import matplotlib.pyplot as plt
from medpy.metric import binary
#use gpu if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
class AE(nn.Module):
def __init__(self, latent_size=100):
super().__init__()
self.init_... | [
"matplotlib.pyplot.title",
"torch.nn.Dropout",
"os.mkdir",
"torch.cat",
"numpy.mean",
"torch.nn.Softmax",
"torch.no_grad",
"torch.nn.MSELoss",
"numpy.copy",
"medpy.metric.binary.dc",
"matplotlib.pyplot.show",
"matplotlib.pyplot.legend",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d",
"torch.c... | [((8627, 8663), 'matplotlib.pyplot.plot', 'plt.plot', (['losses', '"""-x"""'], {'label': '"""loss"""'}), "(losses, '-x', label='loss')\n", (8635, 8663), True, 'import matplotlib.pyplot as plt\n'), ((8666, 8685), 'matplotlib.pyplot.xlabel', 'plt.xlabel', (['"""epoch"""'], {}), "('epoch')\n", (8676, 8685), True, 'import ... |
# -*- coding: utf-8 -*-
# Copyright (c) 2010-2016, MIT Probabilistic Computing Project
#
# 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... | [
"bayeslite.core.bayesdb_generator_table",
"bayeslite.backends.cgpm_backend.CGPM_Backend",
"test_csv.bayesdb_csv_file",
"bayeslite.bayesdb_open",
"bayeslite.bayesdb_read_csv",
"bayeslite.compiler.compile_query",
"bayeslite.guess.bayesdb_guess_population",
"StringIO.StringIO",
"test_core.t1_data",
"... | [((9123, 9159), 'stochastic.stochastic', 'stochastic', ([], {'max_runs': '(2)', 'min_passes': '(1)'}), '(max_runs=2, min_passes=1)\n', (9133, 9159), False, 'from stochastic import stochastic\n'), ((10593, 10629), 'stochastic.stochastic', 'stochastic', ([], {'max_runs': '(2)', 'min_passes': '(1)'}), '(max_runs=2, min_pa... |
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 30 20:15:18 2019
@author: autol
"""
#%%
from plotxy import plot_gd_xy,iters_gd_plot,plot_gd_contour
from initdata import init_data,init_data1,data_b,init_data_house
from func import gradient_descent_f
from varclass import VarSetX
from sklearn.model_selection import Param... | [
"numpy.stack",
"numpy.random.uniform",
"varclass.VarSetX",
"plotxy.plot_gd_contour",
"numpy.ones",
"initdata.data_b",
"plotxy.iters_gd_plot",
"numpy.amax",
"initdata.init_data1",
"func.gradient_descent_f",
"matplotlib.pyplot.subplots"
] | [((402, 412), 'numpy.ones', 'np.ones', (['(2)'], {}), '(2)\n', (409, 412), True, 'import numpy as np\n'), ((419, 444), 'initdata.init_data1', 'init_data1', (['n', '(45)', 'w'], {'b': '(0)'}), '(n, 45, w, b=0)\n', (429, 444), False, 'from initdata import init_data, init_data1, data_b, init_data_house\n'), ((502, 511), '... |
# ServiceSchema.py
from __future__ import print_function
from __future__ import absolute_import
from optparse import OptionParser, OptionValueError
import os
import platform as plat
import sys
if sys.version_info >= (3, 8) and plat.system().lower() == "windows":
# pylint: disable=no-member
with os.add_dll_dir... | [
"blpapi.AuthUser.createWithManualOptions",
"optparse.OptionParser",
"blpapi.AuthOptions.createWithUserAndApp",
"blpapi.AuthOptions.createWithUser",
"blpapi.AuthOptions.createWithApp",
"blpapi.SessionOptions",
"blpapi.Name",
"platform.system",
"blpapi.Session",
"blpapi.AuthUser.createWithActiveDire... | [((429, 465), 'blpapi.Name', 'blpapi.Name', (['"""ReferenceDataResponse"""'], {}), "('ReferenceDataResponse')\n", (440, 465), False, 'import blpapi\n'), ((2930, 2944), 'optparse.OptionParser', 'OptionParser', ([], {}), '()\n', (2942, 2944), False, 'from optparse import OptionParser, OptionValueError\n'), ((7587, 7610),... |
from oraclecxcommerce.modules import ProfilesModule
import pytest
def test_instantiate_profile_module_class_should_return_not_implemented_error():
with pytest.raises(NotImplementedError):
occ = ProfilesModule()
| [
"oraclecxcommerce.modules.ProfilesModule",
"pytest.raises"
] | [((158, 192), 'pytest.raises', 'pytest.raises', (['NotImplementedError'], {}), '(NotImplementedError)\n', (171, 192), False, 'import pytest\n'), ((208, 224), 'oraclecxcommerce.modules.ProfilesModule', 'ProfilesModule', ([], {}), '()\n', (222, 224), False, 'from oraclecxcommerce.modules import ProfilesModule\n')] |
from aws_cdk import aws_iam, aws_sqs, core
from common.common_stack import CommonStack
from common.region_aware_stack import RegionAwareStack
class SqsStack(RegionAwareStack):
def __init__(self, scope: core.Construct, id: str, common_stack: CommonStack, **kwargs) -> None:
super().__init__(scope, id, **kwa... | [
"aws_cdk.aws_iam.PolicyStatement",
"aws_cdk.aws_sqs.Queue"
] | [((464, 507), 'aws_cdk.aws_sqs.Queue', 'aws_sqs.Queue', (['self', '"""integ_test_sqs_queue"""'], {}), "(self, 'integ_test_sqs_queue')\n", (477, 507), False, 'from aws_cdk import aws_iam, aws_sqs, core\n'), ((532, 689), 'aws_cdk.aws_iam.PolicyStatement', 'aws_iam.PolicyStatement', ([], {'effect': 'aws_iam.Effect.ALLOW',... |
##########################################################
# pytorch-kaldi v.0.1
# <NAME>, <NAME>
# Mila, University of Montreal
# October 2018
#
# Description: This script generates kaldi ark files containing raw features.
# The file list must be a file containing "snt_id file.wav".
# Note that only wav files are supp... | [
"data_io.write_mat",
"numpy.abs",
"os.makedirs",
"os.stat",
"data_io.read_vec_int_ark",
"numpy.asarray",
"numpy.zeros",
"math.floor"
] | [((1797, 1816), 'os.stat', 'os.stat', (['out_folder'], {}), '(out_folder)\n', (1804, 1816), False, 'import os\n'), ((3554, 3575), 'numpy.asarray', 'np.asarray', (['frame_all'], {}), '(frame_all)\n', (3564, 3575), True, 'import numpy as np\n'), ((3670, 3724), 'data_io.write_mat', 'write_mat', (['out_folder', 'out_file',... |
#!/usr/bin/env python3
import re
from .codes import codes
class Emoji:
def __init__(self, const):
if len(const) == 1:
self.__fromUnicode(const)
elif const[0] == ":":
self.__fromAlias(const)
else:
self.__fromEscape(const)
self.aliases = codes[self.escape]
self.alias = self.alia... | [
"re.sub"
] | [((1293, 1337), 're.sub', 're.sub', (['""":([^s:]?[\\\\w-]+):"""', 'replAlias', 'text'], {}), "(':([^s:]?[\\\\w-]+):', replAlias, text)\n", (1299, 1337), False, 'import re\n')] |
# -*- coding:utf-8 -*-
# __author__ = '<NAME>'
# Link Model
from flask_boilerplate.extensions import db
# 表前缀
prefix = 'flask_boilerplate'
class Link(db.Model):
__tablename__ = '%s_link' % prefix
id = db.Column(db.Integer, primary_key=True)
sitename = db.Column(db.VARCHAR(30), nullable=False, default='... | [
"flask_boilerplate.extensions.db.Enum",
"flask_boilerplate.extensions.db.Column",
"flask_boilerplate.extensions.db.VARCHAR"
] | [((214, 253), 'flask_boilerplate.extensions.db.Column', 'db.Column', (['db.Integer'], {'primary_key': '(True)'}), '(db.Integer, primary_key=True)\n', (223, 253), False, 'from flask_boilerplate.extensions import db\n'), ((545, 593), 'flask_boilerplate.extensions.db.Column', 'db.Column', (['db.Integer'], {'nullable': '(F... |
"""
Download civil war ships and their complements from dbpedia
"""
from os import path
import json
from SPARQLWrapper import SPARQLWrapper, JSON
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
select distinct ?ship, ?complement where {
{
{?ship dcterms:subject category:Ships_of_the_Union_Navy... | [
"SPARQLWrapper.SPARQLWrapper"
] | [((157, 199), 'SPARQLWrapper.SPARQLWrapper', 'SPARQLWrapper', (['"""http://dbpedia.org/sparql"""'], {}), "('http://dbpedia.org/sparql')\n", (170, 199), False, 'from SPARQLWrapper import SPARQLWrapper, JSON\n')] |
import autograd.numpy as np
import autograd
import os
from autograd import grad
from autograd import jacobian
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import cm
from scipy.linalg import pinv
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--functio... | [
"autograd.numpy.arange",
"argparse.ArgumentParser",
"matplotlib.pyplot.plot",
"autograd.numpy.zeros_like",
"os.makedirs",
"matplotlib.pyplot.legend",
"autograd.numpy.meshgrid",
"autograd.numpy.array",
"autograd.grad",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.rcParams.update",
"matplotlib... | [((264, 289), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (287, 289), False, 'import argparse\n'), ((3820, 3858), 'matplotlib.pyplot.rcParams.update', 'plt.rcParams.update', (["{'font.size': 14}"], {}), "({'font.size': 14})\n", (3839, 3858), True, 'import matplotlib.pyplot as plt\n'), ((3939... |
import re
import math
from tld import get_tld
from Levenshtein import distance
from .suspicious import keywords, tlds
def entropy(string: str) -> float:
"""
Calculates the Shannon entropy of a string
Original code: https://github.com/x0rz/phishing_catcher/blob/master/catch_phishing.py
"""
prob = [... | [
"math.log",
"re.split",
"tld.get_tld"
] | [((1289, 1313), 're.split', 're.split', (['"""\\\\W+"""', 'domain'], {}), "('\\\\W+', domain)\n", (1297, 1313), False, 'import re\n'), ((1101, 1171), 'tld.get_tld', 'get_tld', (['domain'], {'as_object': '(True)', 'fail_silently': '(True)', 'fix_protocol': '(True)'}), '(domain, as_object=True, fail_silently=True, fix_pr... |
import csv
import sqlite3
from tkinter import *
from tkinter import filedialog
"""Tool to compare two reports and provide specific information from matching lines"""
class MatchTool:
UNPLACED_RSL_TEXT = [
"Copy Required Report",
"Ad Copy Status Report",
"Unplaced Spots",
"Required Spots",
]
def __init__(... | [
"sqlite3.connect",
"csv.reader",
"tkinter.filedialog.askopenfilename"
] | [((13046, 13133), 'tkinter.filedialog.askopenfilename', 'filedialog.askopenfilename', ([], {'filetypes': "[('CSV File', '*.csv'), ('All Files', '*.*')]"}), "(filetypes=[('CSV File', '*.csv'), ('All Files',\n '*.*')])\n", (13072, 13133), False, 'from tkinter import filedialog\n'), ((5493, 5528), 'csv.reader', 'csv.re... |
import argparse
import numpy as np
from scipy.io import wavfile
from tqdm import trange
from ar_model import ARmodel
def correctSignal(signal, model, window_size, pred_size, step, treshold=3):
"""Correct signal using AR model
Args:
signal (np.array): signal to correct
model (ARmodel): autoreg... | [
"numpy.abs",
"argparse.ArgumentParser",
"numpy.copy",
"tqdm.trange",
"numpy.std",
"scipy.io.wavfile.read",
"ar_model.ARmodel",
"scipy.io.wavfile.write",
"numpy.linspace"
] | [((711, 726), 'numpy.copy', 'np.copy', (['signal'], {}), '(signal)\n', (718, 726), True, 'import numpy as np\n'), ((741, 798), 'tqdm.trange', 'trange', (['(0)', '(input.shape[0] - window_size - pred_size)', 'step'], {}), '(0, input.shape[0] - window_size - pred_size, step)\n', (747, 798), False, 'from tqdm import trang... |
import io
import json
import os
from typing import Any, Dict, IO, Iterator, Optional, Tuple
from altair_data_server import Provider
from PIL import Image
import pytest
import selenium.webdriver
from selenium.webdriver.remote.webdriver import WebDriver
from altair_saver import HTMLSaver
from altair_saver._utils import... | [
"os.geteuid",
"io.StringIO",
"io.BytesIO",
"json.load",
"os.path.dirname",
"pytest.fixture",
"altair_saver._utils.internet_connected",
"json.dumps",
"altair_data_server.Provider",
"pytest.raises",
"pytest.xfail",
"altair_saver.HTMLSaver",
"pytest.mark.parametrize",
"os.path.join",
"os.li... | [((382, 412), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""module"""'}), "(scope='module')\n", (396, 412), False, 'import pytest\n'), ((475, 505), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""module"""'}), "(scope='module')\n", (489, 505), False, 'import pytest\n'), ((612, 642), 'pytest.fixture', 'p... |
from timeit import default_timer
from parser import wikihandler
import xml.sax as sax
import utility
def main():
# setting path to indices
utility.setIndexPath()
utility.setStatPath()
# parser=sax.make_parser()
# handler = wikihandler()
# parser.setFeature(sax.handler.feature_namespaces,0)
# parser.setContentHa... | [
"parser.wikihandler",
"timeit.default_timer",
"utility.setIndexPath",
"utility.setStatPath",
"xml.sax.make_parser"
] | [((141, 163), 'utility.setIndexPath', 'utility.setIndexPath', ([], {}), '()\n', (161, 163), False, 'import utility\n'), ((165, 186), 'utility.setStatPath', 'utility.setStatPath', ([], {}), '()\n', (184, 186), False, 'import utility\n'), ((1108, 1123), 'timeit.default_timer', 'default_timer', ([], {}), '()\n', (1121, 11... |
import boto3
exceptions = boto3.client('elb').exceptions
AccessPointNotFoundException = exceptions.AccessPointNotFoundException
CertificateNotFoundException = exceptions.CertificateNotFoundException
DependencyThrottleException = exceptions.DependencyThrottleException
DuplicateAccessPointNameException = exceptions.Dup... | [
"boto3.client"
] | [((27, 46), 'boto3.client', 'boto3.client', (['"""elb"""'], {}), "('elb')\n", (39, 46), False, 'import boto3\n')] |
# import os
#
# # path = '/home/yangyang/yangyang/DATA/gxw/dataset/DOTA_split/train'
# # label_file_name = 'labelTxt'
#
# path = '/home/yangyang/yangyang/DATA/gxw/dataset/DOTA_demo/VOC2012'
# label_file_name = 'Annotations'
#
# label_file_path = os.path.join(path, label_file_name)
# filelist = os.listdir(label_file_pat... | [
"os.path.join",
"os.listdir"
] | [((653, 680), 'os.listdir', 'os.listdir', (['label_file_path'], {}), '(label_file_path)\n', (663, 680), False, 'import os\n'), ((716, 746), 'os.path.join', 'os.path.join', (['path', '"""test.txt"""'], {}), "(path, 'test.txt')\n", (728, 746), False, 'import os\n')] |
from pywire.signal import Signal
from tkinter import *
from tkinter.ttk import Separator
from enum import Enum
class BitState(Enum):
TRUE = 1
FALSE = 2
TRUE_FORCED = 3
FALSE_FORCED = 4
UNDEFINED = 5
def bitsToInt(bit_array):
for bit in bit_array:
if bit.state == BitState.UNDEFINED:
... | [
"tkinter.ttk.Separator"
] | [((2652, 2690), 'tkinter.ttk.Separator', 'Separator', (['master'], {'orient': '"""horizontal"""'}), "(master, orient='horizontal')\n", (2661, 2690), False, 'from tkinter.ttk import Separator\n')] |
# Copyright 2020, The TensorFlow Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed t... | [
"tensorflow.test.main",
"functools.partial",
"tensorflow.feature_column.numeric_column",
"tensorflow_privacy.privacy.estimators.test_utils.make_input_fn",
"tensorflow_privacy.privacy.estimators.test_utils.make_input_data",
"tensorflow_privacy.privacy.estimators.v1.dnn.DNNClassifier",
"absl.testing.param... | [((1157, 1263), 'absl.testing.parameterized.named_parameters', 'parameterized.named_parameters', (["('BinaryClassDNN', 2)", "('MultiClassDNN 3', 3)", "('MultiClassDNN 4', 4)"], {}), "(('BinaryClassDNN', 2), ('MultiClassDNN 3', 3\n ), ('MultiClassDNN 4', 4))\n", (1187, 1263), False, 'from absl.testing import paramete... |
import unittest
from numpy import hstack, max, abs, sqrt
from cantera import Solution, gas_constant
import numpy as np
from spitfire import ChemicalMechanismSpec
from os.path import join, abspath
from subprocess import getoutput
test_mech_directory = abspath(join('tests', 'test_mechanisms', 'old_xmls'))
mechs = [x.rep... | [
"unittest.main",
"spitfire.ChemicalMechanismSpec",
"numpy.sum",
"numpy.abs",
"numpy.copy",
"numpy.empty",
"numpy.zeros",
"numpy.ones",
"numpy.hstack",
"numpy.finfo",
"cantera.Solution",
"subprocess.getoutput",
"os.path.join"
] | [((260, 304), 'os.path.join', 'join', (['"""tests"""', '"""test_mechanisms"""', '"""old_xmls"""'], {}), "('tests', 'test_mechanisms', 'old_xmls')\n", (264, 304), False, 'from os.path import join, abspath\n'), ((809, 829), 'numpy.copy', 'np.copy', (['rhs_chem_in'], {}), '(rhs_chem_in)\n', (816, 829), True, 'import numpy... |
from django import forms
from django.forms import ModelForm
from django.conf import settings
from members.models import User
from .models import Unknowntag
class SelectUserForm(forms.Form):
user = forms.ModelChoiceField(queryset=User.objects.all())
activate_doors = forms.BooleanField(initial = True, help_text... | [
"django.forms.BooleanField",
"members.models.User.objects.all"
] | [((276, 388), 'django.forms.BooleanField', 'forms.BooleanField', ([], {'initial': '(True)', 'help_text': '"""Also give this user door permits if they did not have it yet."""'}), "(initial=True, help_text=\n 'Also give this user door permits if they did not have it yet.')\n", (294, 388), False, 'from django import fo... |
from storage_bucket.bucket import get_bucket
def upload_file(
*,
file_content: bytes,
storage_bucket_name: str,
filename: str,
content_type: str = 'application/octet-stream',
**kwargs: dict,
) -> None:
"""
Upload content of file_data to a google cloud storage bucket.
.. versionadd... | [
"storage_bucket.bucket.get_bucket"
] | [((720, 771), 'storage_bucket.bucket.get_bucket', 'get_bucket', ([], {'storage_bucket_name': 'storage_bucket_name'}), '(storage_bucket_name=storage_bucket_name)\n', (730, 771), False, 'from storage_bucket.bucket import get_bucket\n')] |
import pytest
import test.mock_data_gateway
from blades_helper.mission_generator import _get_next_mission_type, _can_use_mission_type, _generate_base_missions
from blades_helper.mission_generator_constants import MissionGeneratorConstants as con
def setup_one_mission_base_build(mock, note, type):
mock.mission_coun... | [
"pytest.raises",
"blades_helper.mission_generator._can_use_mission_type",
"blades_helper.mission_generator._generate_base_missions",
"blades_helper.mission_generator._get_next_mission_type"
] | [((2326, 2375), 'blades_helper.mission_generator._can_use_mission_type', '_can_use_mission_type', (['con.SPECIAL', '[con.SPECIAL]'], {}), '(con.SPECIAL, [con.SPECIAL])\n', (2347, 2375), False, 'from blades_helper.mission_generator import _get_next_mission_type, _can_use_mission_type, _generate_base_missions\n'), ((2387... |
from typing import Any, List
from app.schemas.category import CategoryResponse
from fastapi import APIRouter, Depends, status, HTTPException
from sqlalchemy.orm import Session
from app import crud, schemas
from app.api import deps
router = APIRouter()
@router.get(
"/", response_model=List[schemas.CategoryRespo... | [
"app.crud.create_category",
"app.crud.get_category_by_name",
"fastapi.HTTPException",
"app.crud.read_categories",
"fastapi.Depends",
"fastapi.APIRouter"
] | [((243, 254), 'fastapi.APIRouter', 'APIRouter', ([], {}), '()\n', (252, 254), False, 'from fastapi import APIRouter, Depends, status, HTTPException\n'), ((398, 418), 'fastapi.Depends', 'Depends', (['deps.get_db'], {}), '(deps.get_db)\n', (405, 418), False, 'from fastapi import APIRouter, Depends, status, HTTPException\... |
"""Minimal example dumping whatever event it receives."""
import time
import logging
import argparse
from proglove_streams.logging import init_logging
from proglove_streams.client import Client
from proglove_streams.gateway import Gateway, GatewayMessageHandler
from proglove_streams.exception import ProgloveStreamsExc... | [
"logging.error",
"argparse.ArgumentParser",
"proglove_streams.gateway.GatewayMessageHandler",
"time.sleep",
"proglove_streams.gateway.Gateway",
"logging.getLogger"
] | [((647, 674), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (664, 674), False, 'import logging\n'), ((4077, 4120), 'argparse.ArgumentParser', 'argparse.ArgumentParser', (['"""proglove_streams"""'], {}), "('proglove_streams')\n", (4100, 4120), False, 'import argparse\n'), ((4922, 5158), '... |
""" Add an owner to a resource or resources
Usage: add_owner {username} {resource list}
"""
from django.core.management.base import BaseCommand
from django.contrib.auth.models import User
from hs_core.models import BaseResource
from hs_core.hydroshare.utils import get_resource_by_shortkey
from hs_access_control.model... | [
"hs_core.models.BaseResource.objects.filter",
"django.contrib.auth.models.User.objects.get",
"hs_access_control.models.privilege.UserResourcePrivilege.share",
"django.db.transaction.atomic",
"hs_core.hydroshare.utils.get_resource_by_shortkey"
] | [((2177, 2224), 'django.contrib.auth.models.User.objects.get', 'User.objects.get', ([], {'username': "options['new_owner']"}), "(username=options['new_owner'])\n", (2193, 2224), False, 'from django.contrib.auth.models import User\n'), ((2241, 2275), 'django.contrib.auth.models.User.objects.get', 'User.objects.get', ([]... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Test Primitive Data Real
------------------------
"""
import unittest
import struct
import math
from bacpypes.debugging import bacpypes_debugging, ModuleLogger, xtob
from bacpypes.errors import InvalidTag
from bacpypes.primitivedata import Real, Tag
# some debuggin... | [
"bacpypes.primitivedata.Tag",
"bacpypes.primitivedata.Real",
"math.isnan",
"bacpypes.debugging.xtob"
] | [((520, 527), 'bacpypes.debugging.xtob', 'xtob', (['x'], {}), '(x)\n', (524, 527), False, 'from bacpypes.debugging import bacpypes_debugging, ModuleLogger, xtob\n'), ((819, 824), 'bacpypes.primitivedata.Tag', 'Tag', ([], {}), '()\n', (822, 824), False, 'from bacpypes.primitivedata import Real, Tag\n'), ((1101, 1110), '... |
import matplotlib, numpy, pprint
# matplotlib.rcParams['pdf.fonttype'] = 42
# matplotlib.rcParams['ps.fonttype'] = 42
matplotlib.use('Agg')
import matplotlib.pyplot as plot
import gzip, csv, pylab
from collections import namedtuple
from rvs import *
from patch import *
"""
task events table contains the following fie... | [
"matplotlib.pyplot.yscale",
"csv.reader",
"matplotlib.pyplot.step",
"matplotlib.pyplot.figure",
"numpy.mean",
"numpy.arange",
"matplotlib.pyplot.gca",
"csv.writer",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.legend",
"numpy.sort",
"matplotlib.use",
"matplotlib.pyplot.ylabel",
"matplotlib... | [((118, 139), 'matplotlib.use', 'matplotlib.use', (['"""Agg"""'], {}), "('Agg')\n", (132, 139), False, 'import matplotlib, numpy, pprint\n'), ((2584, 2613), 'csv.writer', 'csv.writer', (['wf'], {'delimiter': '""","""'}), "(wf, delimiter=',')\n", (2594, 2613), False, 'import gzip, csv, pylab\n'), ((4766, 4794), 'collect... |
#!/usr/bin/env python
# -*-Python-*-
import argparse
import contextlib
import datetime
import ftplib
import os
import re
import subprocess
import tempfile
def get_valid_filename(s):
"""
Return the given string converted to a string that can be used for a clean
filename. Remove leading and trailing spaces... | [
"subprocess.Popen",
"os.path.join",
"os.path.basename",
"contextlib.suppress",
"datetime.datetime.now",
"tempfile.TemporaryFile",
"datetime.datetime.strptime",
"datetime.timedelta",
"ftplib.FTP",
"os.path.expanduser",
"re.sub"
] | [((588, 617), 're.sub', 're.sub', (['"""(?u)[^-\\\\w.]"""', '""""""', 's'], {}), "('(?u)[^-\\\\w.]', '', s)\n", (594, 617), False, 'import re\n'), ((2695, 2718), 'os.path.basename', 'os.path.basename', (['fname'], {}), '(fname)\n', (2711, 2718), False, 'import os\n'), ((2815, 2845), 'ftplib.FTP', 'ftplib.FTP', (['base_... |
import glob
from pathlib import Path
from typing import List, Union
ARCHIVE_EXTENSIONS = ['tar']
IMG_EXTENSIONS = ['jpeg', 'jpg', 'bmp', 'png']
VID_EXTENSIONS = ['mp4', 'avi', 'mov', 'mkv', 'mts', 'ts', 'webm']
def normalize_path(path: Union[str, Path]) -> Path:
return Path(path).expanduser().resolve()
def fi... | [
"pathlib.Path",
"glob.glob"
] | [((682, 691), 'pathlib.Path', 'Path', (['dir'], {}), '(dir)\n', (686, 691), False, 'from pathlib import Path\n'), ((778, 816), 'glob.glob', 'glob.glob', (['search_path'], {'recursive': '(True)'}), '(search_path, recursive=True)\n', (787, 816), False, 'import glob\n'), ((893, 932), 'glob.glob', 'glob.glob', (['search_pa... |
from bluetooth import *
from time import sleep
import re, uuid
devices = set()
devices_to_update = set()
dev_mac = ':'.join(re.findall('..', '%012x' % uuid.getnode())).upper()
print(dev_mac)
def enable_ble():
print('enabling bluetooth')
try:
os.system('sudo systemctl start bluetooth.service && sudo ... | [
"uuid.getnode",
"time.sleep"
] | [((2263, 2271), 'time.sleep', 'sleep', (['(5)'], {}), '(5)\n', (2268, 2271), False, 'from time import sleep\n'), ((153, 167), 'uuid.getnode', 'uuid.getnode', ([], {}), '()\n', (165, 167), False, 'import re, uuid\n')] |
from functools import wraps
from pastry.models import User
from flask import request, abort, jsonify
def parse_api_key():
key = None
if request.args.get('api_key'):
key = request.args.get('api_key')
elif request.form.get('api_key'):
key = request.form.get('api_key')
return key
def lo... | [
"flask.request.args.get",
"flask.request.headers.get",
"flask.request.form.get",
"pastry.models.User.verify_auth_token",
"flask.abort",
"flask.jsonify",
"pastry.models.User.verify_api_key",
"functools.wraps"
] | [((146, 173), 'flask.request.args.get', 'request.args.get', (['"""api_key"""'], {}), "('api_key')\n", (162, 173), False, 'from flask import request, abort, jsonify\n'), ((342, 350), 'functools.wraps', 'wraps', (['f'], {}), '(f)\n', (347, 350), False, 'from functools import wraps\n'), ((189, 216), 'flask.request.args.ge... |
"""Draw a imdt calendar image."""
from contextlib import contextmanager
from functools import partial
from imperial_calendar import GregorianDateTime, ImperialDateTime, ImperialYearMonth
from imperial_calendar.transform import (
grdt_to_juld,
imdt_to_imsn,
imsn_to_imdt,
imsn_to_mrsd,
juld_to_grdt,
... | [
"functools.partial",
"imperial_calendar.transform.imsn_to_mrsd",
"imperial_calendar.transform.mrsd_to_tert",
"imperial_calendar.transform.mrsd_to_imsn",
"xml.etree.ElementTree.Element",
"imperial_calendar.ImperialDateTime",
"imperial_calendar.transform.tert_to_mrsd",
"imperial_calendar.transform.juld_... | [((1404, 1422), 'imperial_calendar.transform.juld_to_tert', 'juld_to_tert', (['juld'], {}), '(juld)\n', (1416, 1422), False, 'from imperial_calendar.transform import grdt_to_juld, imdt_to_imsn, imsn_to_imdt, imsn_to_mrsd, juld_to_grdt, juld_to_tert, mrsd_to_imsn, mrsd_to_tert, tert_to_juld, tert_to_mrsd\n'), ((1434, 14... |
"""
NamedConf parser - file ``/etc/named.conf``
===========================================
NamedConf parser the file named configuration file.
Named is a name server used by BIND.
"""
from insights.specs import Specs
from insights.core.plugins import parser
from insights.parsers import SkipException
from insights.pa... | [
"insights.core.plugins.parser",
"insights.parsers.SkipException"
] | [((367, 391), 'insights.core.plugins.parser', 'parser', (['Specs.named_conf'], {}), '(Specs.named_conf)\n', (373, 391), False, 'from insights.core.plugins import parser\n'), ((1395, 1445), 'insights.parsers.SkipException', 'SkipException', (['"""Syntax error of include directive"""'], {}), "('Syntax error of include di... |
from readwrite import get_data
import pandas as pd
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
import numpy as np
def scatter(path, name):
data = get_data(path)
pd_data = pd.DataFrame(data)
plt.title("column 0 " + name)
plt.plot(pd_data[0])
plt.show()
plt.title("column 1 " + name)
plt... | [
"pandas.DataFrame",
"matplotlib.pyplot.title",
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.boxplot",
"scipy.stats.gaussian_kde",
"numpy.linspace",
"readwrite.get_data"
] | [((173, 187), 'readwrite.get_data', 'get_data', (['path'], {}), '(path)\n', (181, 187), False, 'from readwrite import get_data\n'), ((199, 217), 'pandas.DataFrame', 'pd.DataFrame', (['data'], {}), '(data)\n', (211, 217), True, 'import pandas as pd\n'), ((220, 249), 'matplotlib.pyplot.title', 'plt.title', (["('column 0 ... |
# Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
import onnx
from onnx import helper, TensorProto
QUERY_TENSOR = helper.make_tensor_value_info('query_tensor', TensorProto.FLOAT, ['batch', 4])
ATTRIBUTE_TENSOR = helper.make_tensor_value_info('attribute_tensor', Ten... | [
"onnx.helper.make_node",
"onnx.save",
"onnx.helper.make_tensor_value_info",
"onnx.OperatorSetIdProto",
"onnx.helper.make_graph"
] | [((169, 247), 'onnx.helper.make_tensor_value_info', 'helper.make_tensor_value_info', (['"""query_tensor"""', 'TensorProto.FLOAT', "['batch', 4]"], {}), "('query_tensor', TensorProto.FLOAT, ['batch', 4])\n", (198, 247), False, 'from onnx import helper, TensorProto\n'), ((267, 343), 'onnx.helper.make_tensor_value_info', ... |
import time
current_time = time.localtime()
hour = current_time.tm_hour
print('The hour is', hour)
| [
"time.localtime"
] | [((28, 44), 'time.localtime', 'time.localtime', ([], {}), '()\n', (42, 44), False, 'import time\n')] |
from datetime import timedelta
DEFAULT_REQUIRED_CONFIRMATIONS: int = 10
MAX_FILTER_INTERVAL: int = 100_000
DEFAULT_GAS_BUFFER_FACTOR: int = 10
DEFAULT_GAS_CHECK_BLOCKS: int = 100
KEEP_MRS_WITHOUT_CHANNEL: timedelta = timedelta(minutes=15)
# A LockedTransfer message is roughly 1kb. Having 1000/min = 17/sec will be
# h... | [
"datetime.timedelta"
] | [((218, 239), 'datetime.timedelta', 'timedelta', ([], {'minutes': '(15)'}), '(minutes=15)\n', (227, 239), False, 'from datetime import timedelta\n'), ((550, 570), 'datetime.timedelta', 'timedelta', ([], {'minutes': '(5)'}), '(minutes=5)\n', (559, 570), False, 'from datetime import timedelta\n')] |
import re
# TO-DO: refactor validators as below
# https://pydantic-docs.helpmanual.io/usage/validators/
# Email regex mostly following RFC2822 specification. Covers ~99% of emails in use today
# Allows groups of alphanumerics and some special characters separated by dots,
# followed by a @,
# followed by groups of al... | [
"re.compile"
] | [((402, 561), 're.compile', 're.compile', (['"""[a-z0-9!#$%&\'*+/=?^_`{|}~-]+(?:\\\\.[a-z0-9!#$%&\'*+/=?^_`{|}~-]+)*@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\\\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?"""'], {}), '(\n "[a-z0-9!#$%&\'*+/=?^_`{|}~-]+(?:\\\\.[a-z0-9!#$%&\'*+/=?^_`{|}~-]+)*@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\\\.)+... |
#!/usr/bin/env python
"""
# Author: <NAME>
# Created Time : Tue 29 Sep 2020 01:41:23 PM CST
# File Name: function.py
# Description:
"""
import torch
import numpy as np
import os
import scanpy as sc
from anndata import AnnData
from .data import load_data
from .net.vae import VAE
from .net.utils import EarlyStopping
... | [
"scanpy.tl.umap",
"numpy.random.seed",
"os.makedirs",
"torch.manual_seed",
"torch.load",
"scanpy.pp.neighbors",
"scanpy.read_h5ad",
"scanpy.pl.umap",
"torch.save",
"scanpy.tl.leiden",
"sklearn.neighbors.KNeighborsClassifier",
"torch.cuda.is_available",
"torch.cuda.set_device",
"anndata.Ann... | [((3790, 3810), 'numpy.random.seed', 'np.random.seed', (['seed'], {}), '(seed)\n', (3804, 3810), True, 'import numpy as np\n'), ((3822, 3845), 'torch.manual_seed', 'torch.manual_seed', (['seed'], {}), '(seed)\n', (3839, 3845), False, 'import torch\n'), ((3854, 3879), 'torch.cuda.is_available', 'torch.cuda.is_available'... |
from vyperlogix.hash import lists
code_error = -404
code_noUpdate = -100
code_isUpdate = 400
code_revoked = -500
code_updated = 100
code_accepted = 200
code_valid = 300
code_invalid = -301
_info_site_address = 'www.VyperLogix.com'
d_responses = lists.HashedLists2({code_error:'Warning: Unable to process your Registra... | [
"vyperlogix.hash.lists.HashedLists2"
] | [((248, 979), 'vyperlogix.hash.lists.HashedLists2', 'lists.HashedLists2', (["{code_error: 'Warning: Unable to process your Registration.', code_invalid:\n 'Your registration is not valid. Please make sure your payment has processed.'\n , code_noUpdate: 'You have the latest version.', code_revoked:\n 'Your prod... |
import os
from distutils.core import setup
from setuptools import find_packages, setup
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
def requirements(fname):
for line in open(os.path.join(os.path.dirname(__file__), fname)):
yield line.strip()
setup(
name=... | [
"os.path.dirname",
"setuptools.find_packages"
] | [((431, 446), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (444, 446), False, 'from setuptools import find_packages, setup\n'), ((239, 264), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (254, 264), False, 'import os\n'), ((136, 161), 'os.path.dirname', 'os.path.dirname', (... |
# Generated by Django 2.2.13 on 2020-10-25 12:06
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('stream', '0002_viewcounter_name'),
]
operations = [
migrations.AlterField(
model_name='view',
name='token',
... | [
"django.db.models.CharField"
] | [((331, 375), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(20)', 'unique': '(True)'}), '(max_length=20, unique=True)\n', (347, 375), False, 'from django.db import migrations, models\n')] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 10 14:19:04 2020
@author: corkep
"""
import numpy as np
import numpy.testing as nt
import unittest
from math import pi
import math
from scipy.linalg import logm, expm
from spatialmath.base.transformsNd import *
from spatialmath.base.transforms3d ... | [
"unittest.main",
"spatialmath.base.transforms3d.rotx",
"spatialmath.base.transforms2d.ishom2",
"spatialmath.base.transforms2d.isrot2",
"numpy.testing.assert_almost_equal",
"spatialmath.base.transforms2d.rot2",
"numpy.zeros",
"spatialmath.base.transforms3d.isrot",
"spatialmath.base.transforms2d.trot2... | [((10322, 10337), 'unittest.main', 'unittest.main', ([], {}), '()\n', (10335, 10337), False, 'import unittest\n'), ((994, 1003), 'spatialmath.base.transforms3d.rotx', 'rotx', (['(0.3)'], {}), '(0.3)\n', (998, 1003), False, 'from spatialmath.base.transforms3d import trotx, transl, rotx, isrot, ishom\n'), ((1031, 1086), ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 27 16:40:49 2020
@author: krugefr1
"""
import numpy as np
import os
try:
import arthor
except ImportError:
arthor = None
from rdkit import Chem
from rdkit.Chem import rdSubstructLibrary
import pickle
import random
import pandas as pd
import... | [
"rdkit.Chem.PatternFingerprint",
"os.mkdir",
"pickle.dump",
"numpy.argmax",
"rdkit.Chem.MolToSmiles",
"pandas.DataFrame",
"os.path.exists",
"random.seed",
"rdkit.Chem.rdSubstructLibrary.PatternHolder",
"copy.deepcopy",
"automated_series_classification.Butinaclustering.ApplyButina",
"automated_... | [((1502, 1653), 'automated_series_classification.utilsDataPrep.PrepareData', 'utilsDataPrep.PrepareData', (['self.proj', 'self.datapath', 'filename'], {'distMeasure': '"""Tanimoto"""', 'FP': '"""Morgan2"""', 'calcDists': 'self.calcDists', 'smilesCol': 'smilesCol'}), "(self.proj, self.datapath, filename, distMeasure=\n ... |
import openliveq as olq
import pytest
import os
from .test_base import TestBase
class TestCollection(TestBase):
def test_df(self, c):
result = c.df
assert result["社会保険事務所"] == 1
assert result["国民年金"] == 4
def test_cf(self, c):
result = c.cf
assert result["社会保険事務所"] > 1
... | [
"openliveq.Collection",
"openliveq.FeatureFactory"
] | [((427, 443), 'openliveq.Collection', 'olq.Collection', ([], {}), '()\n', (441, 443), True, 'import openliveq as olq\n'), ((583, 603), 'openliveq.FeatureFactory', 'olq.FeatureFactory', ([], {}), '()\n', (601, 603), True, 'import openliveq as olq\n')] |
# Copyright (c) 2010 Resolver Systems Ltd.
# All Rights Reserved
#
try:
import unittest2 as unittest
except ImportError:
import unittest
from functionaltest import FunctionalTest
import key_codes
from textwrap import dedent
class Test_2734_ClearCells(FunctionalTest):
def test_delete_key_clears_selected... | [
"textwrap.dedent"
] | [((3424, 3819), 'textwrap.dedent', 'dedent', (['"""\n worksheet.a1.error = \'harold puts a deliberate pointless error in\'\n\n worksheet.a1.clear()\n\n worksheet.b1.formula = str(worksheet.a1.value)\n worksheet.b2.formula = str(worksheet.a1.formula)\n worksheet.b3.... |
"""
Helper script to create config files for BlenderProc.
"""
import os
import yaml
import random
import numpy as np
import binascii
# these paths have to be manually set before creating a config
BLENDERPROC_ROOT = '' # /path/to/BlenderProc
SHAPENET_ROOT = '' # /path/to/ShapeNetCore.v2
SUNCG_ROOT = '' # /path/to/s... | [
"numpy.random.uniform",
"yaml.load",
"os.makedirs",
"binascii.hexlify",
"yaml.dump",
"random.choice",
"numpy.random.randint",
"os.path.join",
"os.urandom"
] | [((7027, 7051), 'numpy.random.randint', 'np.random.randint', (['(5)', '(12)'], {}), '(5, 12)\n', (7044, 7051), True, 'import numpy as np\n'), ((8462, 8476), 'os.urandom', 'os.urandom', (['(20)'], {}), '(20)\n', (8472, 8476), False, 'import os\n'), ((8497, 8528), 'binascii.hexlify', 'binascii.hexlify', (['output_prefix'... |
import sys
sys.setrecursionlimit(10000000)
class LowestCommonAncedtor:
def __init__(self, G, root):
self.n = len(G)
self.tour = [0] * (2 * self.n - 1)
self.depth_list = [0] * (2 * self.n - 1)
self.id = [0] * self.n
self.visit_id = 0
self.dfs(G, root, -1, 0)
... | [
"sys.setrecursionlimit"
] | [((12, 43), 'sys.setrecursionlimit', 'sys.setrecursionlimit', (['(10000000)'], {}), '(10000000)\n', (33, 43), False, 'import sys\n')] |
import h5py
import numpy as np
def load_data(fname):
# load in an hdf5 file and return the X and y values
data_file = h5py.File(fname)
# load in X and y training data, fully into memory
X = data_file['X'][:].reshape(-1, 1) # each row is a data point
y = data_file['y'][:]
return X, y
def eval... | [
"h5py.File",
"numpy.abs"
] | [((127, 143), 'h5py.File', 'h5py.File', (['fname'], {}), '(fname)\n', (136, 143), False, 'import h5py\n'), ((395, 418), 'numpy.abs', 'np.abs', (['(y_pred - y_true)'], {}), '(y_pred - y_true)\n', (401, 418), True, 'import numpy as np\n')] |
import sys
import os
import urllib.parse
import urllib.request
import xml.etree.ElementTree as ET
import shutil
import sqlite3
def fetch_database(filename):
r = urllib.request.urlopen('https://nzsl-assets.vuw.ac.nz/dnzsl/freelex/publicsearch?xmldump=1')
with open(filename, "wb") as f:
f.write(r.read())... | [
"os.makedirs",
"os.unlink",
"os.path.isdir",
"os.rename",
"os.path.dirname",
"os.path.exists",
"os.system",
"os.path.isfile",
"sqlite3.connect",
"shutil.rmtree",
"os.path.join"
] | [((3322, 3347), 'os.path.exists', 'os.path.exists', (['"""nzsl.db"""'], {}), "('nzsl.db')\n", (3336, 3347), False, 'import os\n'), ((3387, 3413), 'sqlite3.connect', 'sqlite3.connect', (['"""nzsl.db"""'], {}), "('nzsl.db')\n", (3402, 3413), False, 'import sqlite3\n'), ((3916, 3939), 'os.path.isdir', 'os.path.isdir', (['... |
from setuptools import find_packages, setup
setup(
name='src',
packages=find_packages(),
version='0.1.0',
description='tweet analyzer',
author='<NAME>',
license='',
)
| [
"setuptools.find_packages"
] | [((81, 96), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (94, 96), False, 'from setuptools import find_packages, setup\n')] |
import time
import logging
import cv2
import numpy as np
from deep_sort_realtime.deep_sort import nn_matching
from deep_sort_realtime.deep_sort.detection import Detection
from deep_sort_realtime.deep_sort.tracker import Tracker
from deep_sort_realtime.utils.nms import non_max_suppression
log_level = logging.DEBUG
d... | [
"deep_sort_realtime.deep_sort.tracker.Tracker",
"deep_sort_realtime.utils.nms.non_max_suppression",
"cv2.bitwise_and",
"deep_sort_realtime.deep_sort.detection.Detection",
"logging.StreamHandler",
"numpy.zeros",
"cv2.fillPoly",
"logging.Formatter",
"deep_sort_realtime.embedder.embedder_pytorch.Mobile... | [((336, 365), 'logging.getLogger', 'logging.getLogger', (['"""DeepSORT"""'], {}), "('DeepSORT')\n", (353, 365), False, 'import logging\n'), ((411, 434), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (432, 434), False, 'import logging\n'), ((475, 534), 'logging.Formatter', 'logging.Formatter', (['"... |
import pymysql
conn = pymysql.connect(host='127.0.0.1',
user='root',
passwd='<PASSWORD>',
db='all0504')
def get_user_set():
user_set = set()
with open('../facebook/KOL_audience') as input_user_file:
for line in input_user_file:
if line.strip() == '':
continue
... | [
"pymysql.connect"
] | [((23, 109), 'pymysql.connect', 'pymysql.connect', ([], {'host': '"""127.0.0.1"""', 'user': '"""root"""', 'passwd': '"""<PASSWORD>"""', 'db': '"""all0504"""'}), "(host='127.0.0.1', user='root', passwd='<PASSWORD>', db=\n 'all0504')\n", (38, 109), False, 'import pymysql\n')] |
import pytest
from cutadapt.__main__ import main, parse_cutoffs, parse_lengths, CommandLineError, setup_logging
def test_help():
with pytest.raises(SystemExit) as e:
main(["--help"])
assert e.value.args[0] == 0
def test_parse_cutoffs():
assert parse_cutoffs("5") == (0, 5)
assert parse_cutof... | [
"cutadapt.__main__.parse_cutoffs",
"cutadapt.__main__.main",
"cutadapt.__main__.parse_lengths",
"pytest.raises",
"cutadapt.__main__.setup_logging",
"logging.getLogger"
] | [((1244, 1271), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1261, 1271), False, 'import logging\n'), ((1276, 1363), 'cutadapt.__main__.setup_logging', 'setup_logging', (['logger'], {'log_to_stderr': '(False)', 'quiet': '(False)', 'minimal': '(False)', 'debug': '(False)'}), '(logger, l... |
from pdf417 import encode, render_image, render_svg
import io
class BarcodeGen():
#OWN CLASS - BarcodeGen
def generateBarcode(self, text):
codes = encode(text, columns=7, security_level=4)
image = render_image(codes, scale=4, ratio=3, fg_color="black", bg_color="#FFFFFF")
image.show()
def generateBarcodeForW... | [
"pdf417.render_image",
"pdf417.encode"
] | [((152, 193), 'pdf417.encode', 'encode', (['text'], {'columns': '(7)', 'security_level': '(4)'}), '(text, columns=7, security_level=4)\n', (158, 193), False, 'from pdf417 import encode, render_image, render_svg\n'), ((204, 279), 'pdf417.render_image', 'render_image', (['codes'], {'scale': '(4)', 'ratio': '(3)', 'fg_col... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('seaborn-deep')
# Importing the dataset
dataset = pd.read_csv('Salary_Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 1].values
# Training/testing
from sklearn.model_selection import train_test_split
X_train, X_test,... | [
"matplotlib.pyplot.title",
"matplotlib.pyplot.show",
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.scatter",
"sklearn.linear_model.LinearRegression",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel"
] | [((71, 100), 'matplotlib.pyplot.style.use', 'plt.style.use', (['"""seaborn-deep"""'], {}), "('seaborn-deep')\n", (84, 100), True, 'import matplotlib.pyplot as plt\n'), ((137, 167), 'pandas.read_csv', 'pd.read_csv', (['"""Salary_Data.csv"""'], {}), "('Salary_Data.csv')\n", (148, 167), True, 'import pandas as pd\n'), ((3... |
"""Generated client library for firestore version v1beta1."""
# NOTE: This file is autogenerated and should not be edited by hand.
from apitools.base.py import base_api
from googlecloudsdk.third_party.apis.firestore.v1beta1 import firestore_v1beta1_messages as messages
class FirestoreV1beta1(base_api.BaseApiClient):
... | [
"apitools.base.py.base_api.ApiMethodInfo"
] | [((2906, 3458), 'apitools.base.py.base_api.ApiMethodInfo', 'base_api.ApiMethodInfo', ([], {'flat_path': 'u"""v1beta1/projects/{projectsId}/databases/{databasesId}/documents:batchGet"""', 'http_method': 'u"""POST"""', 'method_id': 'u"""firestore.projects.databases.documents.batchGet"""', 'ordered_params': "[u'database']... |
from django.conf.urls import url
from .views import (subjectpool_index, manage_experiment_session, get_session_events, manage_participant_attendance,
send_invitations, get_invitations_count, invite_email_preview, experiment_session_signup,
submit_experiment_session_signup, cance... | [
"django.conf.urls.url"
] | [((436, 490), 'django.conf.urls.url', 'url', (['"""^$"""', 'subjectpool_index'], {'name': '"""subjectpool_index"""'}), "('^$', subjectpool_index, name='subjectpool_index')\n", (439, 490), False, 'from django.conf.urls import url\n'), ((497, 603), 'django.conf.urls.url', 'url', (['"""^session/manage/(?P<pk>\\\\-?\\\\d+)... |
import math
from vectors import Vector2
from vectors import Vector3
def get_car_facing_vector(car):
pitch = float(car.rotation.pitch)
yaw = float(car.rotation.yaw)
facing_x = math.cos(pitch) * math.cos(yaw)
facing_y = math.cos(pitch) * math.sin(yaw)
return Vector2(facing_x, facing_y)
def get_own... | [
"math.exp",
"vectors.Vector2",
"math.radians",
"math.sin",
"math.cos",
"math.degrees",
"vectors.Vector3"
] | [((280, 307), 'vectors.Vector2', 'Vector2', (['facing_x', 'facing_y'], {}), '(facing_x, facing_y)\n', (287, 307), False, 'from vectors import Vector2\n'), ((479, 519), 'vectors.Vector3', 'Vector3', (['field_info.goals[team].location'], {}), '(field_info.goals[team].location)\n', (486, 519), False, 'from vectors import ... |
import cv2
import os
import numpy as np
from PIL import Image
import picamera.array
from picamera import PiCamera
class Face(object):
training_count = 5
threshold = 30
def __init__(self, casc_path, path="./passwords", camera_port=0):
self.path = path
self._cascade = cv2.CascadeClassifi... | [
"cv2.cv.cvtColor",
"cv2.imwrite",
"PIL.Image.open",
"cv2.face.createLBPHFaceRecognizer",
"numpy.array",
"cv2.CascadeClassifier",
"cv2.destroyAllWindows",
"os.path.join",
"os.listdir",
"picamera.PiCamera"
] | [((301, 333), 'cv2.CascadeClassifier', 'cv2.CascadeClassifier', (['casc_path'], {}), '(casc_path)\n', (322, 333), False, 'import cv2\n'), ((399, 422), 'cv2.destroyAllWindows', 'cv2.destroyAllWindows', ([], {}), '()\n', (420, 422), False, 'import cv2\n'), ((2335, 2370), 'cv2.face.createLBPHFaceRecognizer', 'cv2.face.cre... |
# -*- coding: utf-8 -*-
'''
Mrknow TV Add-on
Copyright (C) 2016 mrknow
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) an... | [
"resources.lib.lib.control.setting",
"resources.lib.lib.control.log",
"json.loads",
"resources.lib.lib.control.addonInfo",
"resources.lib.lib.control.lang",
"resources.lib.lib.control.get_setting",
"datetime.datetime.now",
"time.sleep",
"urlparse.urljoin",
"datetime.timedelta",
"urllib.urlencode... | [((4747, 4785), 'resources.lib.lib.control.setting', 'control.setting', (['"""pierwszatv.password"""'], {}), "('pierwszatv.password')\n", (4762, 4785), False, 'from resources.lib.lib import control\n'), ((1075, 1118), 'urlparse.urljoin', 'urlparse.urljoin', (['"""http://pierwsza.tv"""', 'url'], {}), "('http://pierwsza.... |
# Generated by Django 3.2.11 on 2022-02-02 01:04
import django.contrib.gis.db.models.fields
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Property',
fiel... | [
"django.db.models.BigAutoField",
"django.db.models.PositiveIntegerField",
"django.db.models.CharField"
] | [((348, 444), 'django.db.models.BigAutoField', 'models.BigAutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (367, 444), False, 'from django.db import migrations, m... |
#!/usr/bin/env python
import requests
import re
import sys
import dlrnapi_client
import influxdb_utils
import json
from promoter_utils import get_dlrn_instance_for_release
from diskcache import Cache
cache = Cache('/tmp/skipped_promotions_cache')
cache.expire()
promoter_skipping_regex = re.compile(
('.*promoter ... | [
"promoter_utils.get_dlrn_instance_for_release",
"influxdb_utils.format_ts_from_str",
"dlrnapi_client.Params2",
"diskcache.Cache",
"re.compile"
] | [((210, 248), 'diskcache.Cache', 'Cache', (['"""/tmp/skipped_promotions_cache"""'], {}), "('/tmp/skipped_promotions_cache')\n", (215, 248), False, 'from diskcache import Cache\n'), ((291, 401), 're.compile', 're.compile', (['""".*promoter Skipping promotion of (.*) from (.*) to (.*), missing successful jobs: (.*)"""'],... |
from __future__ import print_function
import argparse
import os
import csv
import numpy as np
import random
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from data_utils.data_util import PointcloudScaleAndTran... | [
"os.mkdir",
"torch.optim.lr_scheduler.StepLR",
"argparse.ArgumentParser",
"numpy.argmax",
"models.rscnn.RSCNN",
"data_utils.ModelNetDataLoader.ModelNetDataLoader",
"models.pointnet.PointNetCls",
"sys.path.append",
"models.pointnet2.PointNet2ClsMsg",
"random.randint",
"torch.utils.data.DataLoader... | [((637, 662), 'sys.path.append', 'sys.path.append', (['"""./emd/"""'], {}), "('./emd/')\n", (652, 662), False, 'import sys\n'), ((882, 905), 'os.path.exists', 'os.path.exists', (['logname'], {}), '(logname)\n', (896, 905), False, 'import os\n'), ((4609, 4634), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], ... |
import random
from flask import Flask
app = Flask(__name__)
@app.route('/')
def index():
a = random.randrange(1, 10)
b = random.randrange(1, 10)
return f'{a} * {b} = {a * b}'
| [
"flask.Flask",
"random.randrange"
] | [((46, 61), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (51, 61), False, 'from flask import Flask\n'), ((101, 124), 'random.randrange', 'random.randrange', (['(1)', '(10)'], {}), '(1, 10)\n', (117, 124), False, 'import random\n'), ((133, 156), 'random.randrange', 'random.randrange', (['(1)', '(10)'], {}... |
"""Generate a summary of a previously trained vowel recognition model.
"""
import torch
import wavetorch
import argparse
import yaml
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
try:
from helpers.plot import mpl_set_latex
mpl_set_latex()
except ImportError:
impor... | [
"matplotlib.ticker.MultipleLocator",
"matplotlib.pyplot.show",
"argparse.ArgumentParser",
"torch.manual_seed",
"yaml.dump",
"wavetorch.io.load_model",
"wavetorch.data.load_all_vowels",
"helpers.plot.mpl_set_latex",
"wavetorch.data.select_vowel_sample",
"matplotlib.pyplot.figure",
"matplotlib.tic... | [((457, 482), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (480, 482), False, 'import argparse\n'), ((275, 290), 'helpers.plot.mpl_set_latex', 'mpl_set_latex', ([], {}), '()\n', (288, 290), False, 'from helpers.plot import mpl_set_latex\n'), ((974, 1012), 'wavetorch.io.load_model', 'wavetorch... |
import math
import numpy as np
import torch
import torch.nn as nn
import itertools
class FuzzyLayer(nn.Module):
def __init__(self, fuzzynum,channel):
super(FuzzyLayer,self).__init__()
self.n = fuzzynum
self.channel = channel
self.conv1 = nn.Conv2d(self.channel,1,3,padding=1)
self.conv2 = nn.Conv2d(1,self.c... | [
"torch.nn.ReLU",
"torch.nn.ConvTranspose2d",
"math.sqrt",
"torch.nn.Conv2d",
"torch.randn",
"torch.exp",
"torch.nn.BatchNorm2d",
"torch.nn.MaxPool2d"
] | [((249, 289), 'torch.nn.Conv2d', 'nn.Conv2d', (['self.channel', '(1)', '(3)'], {'padding': '(1)'}), '(self.channel, 1, 3, padding=1)\n', (258, 289), True, 'import torch.nn as nn\n'), ((302, 342), 'torch.nn.Conv2d', 'nn.Conv2d', (['(1)', 'self.channel', '(3)'], {'padding': '(1)'}), '(1, self.channel, 3, padding=1)\n', (... |
import argparse
import json
from gensim.models import Word2Vec
from tensorflow_core.python.keras.models import load_model
import convert
import extract
import predict
import vectorize
from annotation import annotate
def main(input_file: str, output_file: str):
extracted_jsdoc = extract.extract_from_file(input_f... | [
"json.load",
"argparse.ArgumentParser",
"vectorize.df_to_vec",
"extract.extract_from_file",
"tensorflow_core.python.keras.models.load_model",
"predict.predict",
"convert.convert_func_to_df",
"gensim.models.Word2Vec.load",
"annotation.annotate.annotate"
] | [((287, 324), 'extract.extract_from_file', 'extract.extract_from_file', (['input_file'], {}), '(input_file)\n', (312, 324), False, 'import extract\n'), ((334, 377), 'convert.convert_func_to_df', 'convert.convert_func_to_df', (['extracted_jsdoc'], {}), '(extracted_jsdoc)\n', (360, 377), False, 'import convert\n'), ((398... |
# coding=utf8
"""
方便调试使用
"""
from lofka import LofkaHandler,LofkaAsyncHandler
import logging
import traceback
handler = LofkaAsyncHandler()
logger = logging.getLogger('test')
logger.addHandler(handler)
def __debug_method():
try:
raise Exception("TestException")
except Exception as ex:
traceb... | [
"lofka.LofkaAsyncHandler",
"traceback.format_exc",
"logging.getLogger"
] | [((122, 141), 'lofka.LofkaAsyncHandler', 'LofkaAsyncHandler', ([], {}), '()\n', (139, 141), False, 'from lofka import LofkaHandler, LofkaAsyncHandler\n'), ((151, 176), 'logging.getLogger', 'logging.getLogger', (['"""test"""'], {}), "('test')\n", (168, 176), False, 'import logging\n'), ((314, 336), 'traceback.format_exc... |
from bs4 import BeautifulSoup
import requests
#from webdriver import keep_alive
import discord
import time
from discord.ext import commands
bot = commands.Bot(command_prefix='!')
bot.remove_command("help")
@bot.event
async def on_ready():
await bot.change_presence(status=discord.Status.online, activity=discord.Activ... | [
"discord.Activity",
"discord.ext.commands.command",
"time.sleep",
"requests.get",
"discord.ext.commands.Bot",
"bs4.BeautifulSoup"
] | [((147, 179), 'discord.ext.commands.Bot', 'commands.Bot', ([], {'command_prefix': '"""!"""'}), "(command_prefix='!')\n", (159, 179), False, 'from discord.ext import commands\n'), ((412, 441), 'discord.ext.commands.command', 'commands.command', ([], {'name': '"""ebay"""'}), "(name='ebay')\n", (428, 441), False, 'from di... |
import time
# print( time.time())
def timmer(func):
def wrapper():
start_time = time.time()
func()
stop_time = time.time()
print("运行时间是 %s 秒 " % (stop_time - start_time))
return wrapper
@timmer
def i_can_sleep():
time.sleep(3)
# start_time = time.time()
i_can_sleep()... | [
"time.time",
"time.sleep"
] | [((262, 275), 'time.sleep', 'time.sleep', (['(3)'], {}), '(3)\n', (272, 275), False, 'import time\n'), ((94, 105), 'time.time', 'time.time', ([], {}), '()\n', (103, 105), False, 'import time\n'), ((141, 152), 'time.time', 'time.time', ([], {}), '()\n', (150, 152), False, 'import time\n')] |
#!/usr/bin/python3
import cv2
import cv2IP
if __name__ == '__main__':
IP = cv2IP.BaseIP()
img = IP.ImRead("img/test.jpg")
IP.ImWindow("foreGround")
IP.ImShow("foreGround", img)
cv2.waitKey(0)
del IP
| [
"cv2.waitKey",
"cv2IP.BaseIP"
] | [((81, 95), 'cv2IP.BaseIP', 'cv2IP.BaseIP', ([], {}), '()\n', (93, 95), False, 'import cv2IP\n'), ((199, 213), 'cv2.waitKey', 'cv2.waitKey', (['(0)'], {}), '(0)\n', (210, 213), False, 'import cv2\n')] |
from __future__ import print_function, division
import torch
import os
import pandas as pd
from skimage import io, transform
import numpy as np
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
import sklearn
import sklearn.metrics as sklm
import csv
import argparse
import torc... | [
"pandas.read_csv",
"numpy.empty",
"torch.get_rng_state",
"torch.cuda.device_count",
"numpy.mean",
"torchvision.transforms.Normalize",
"numpy.nanmean",
"torch.nn.BCELoss",
"torch.utils.data.DataLoader",
"torchvision.transforms.Scale",
"numpy.std",
"CXRDataset.CXRDataset",
"torch.load",
"os.... | [((673, 698), 'torch.cuda.is_available', 'torch.cuda.is_available', ([], {}), '()\n', (696, 698), False, 'import torch\n'), ((885, 896), 'importlib.reload', 'reload', (['CXR'], {}), '(CXR)\n', (891, 896), False, 'from importlib import reload\n'), ((897, 906), 'importlib.reload', 'reload', (['E'], {}), '(E)\n', (903, 90... |
# coding: utf-8
#
# This code is part of lattpy.
#
# Copyright (c) 2021, <NAME>
#
# This code is licensed under the MIT License. The copyright notice in the
# LICENSE file in the root directory and this permission notice shall
# be included in all copies or substantial portions of the Software.
"""Contains miscellaneo... | [
"numpy.zeros_like",
"numpy.abs",
"logging.StreamHandler",
"logging.getLogger",
"logging.Formatter",
"numpy.min_scalar_type",
"numpy.min",
"numpy.max",
"numpy.unique"
] | [((851, 878), 'logging.getLogger', 'logging.getLogger', (['"""lattpy"""'], {}), "('lattpy')\n", (868, 878), False, 'import logging\n'), ((886, 909), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (907, 909), False, 'import logging\n'), ((1038, 1086), 'logging.Formatter', 'logging.Formatter', (['_FR... |
# -*- coding: utf-8 -*-
from django.db import models
from django.urls import reverse
from django.utils.translation import ugettext_lazy as _
from django.contrib.auth import get_user_model
from model_utils.models import TimeStampedModel
from annoying.fields import JSONField
from geolite2 import geolite2
from .utils ... | [
"django.db.models.URLField",
"django.db.models.ForeignKey",
"django.db.models.CharField",
"geolite2.geolite2.close",
"django.contrib.auth.get_user_model",
"geolite2.geolite2.reader",
"django.db.models.SlugField",
"annoying.fields.JSONField",
"django.urls.reverse",
"django.db.models.IntegerField",
... | [((529, 590), 'django.db.models.SlugField', 'models.SlugField', ([], {'max_length': '(6)', 'primary_key': '(True)', 'unique': '(True)'}), '(max_length=6, primary_key=True, unique=True)\n', (545, 590), False, 'from django.db import models\n'), ((606, 650), 'django.db.models.URLField', 'models.URLField', ([], {'max_lengt... |
from __future__ import annotations
import decimal
import logging
from typing import Any, Callable, Dict, Mapping, Optional, Set
import workflows
MessageCallback = Callable[[Mapping[str, Any], Any], None]
class CommonTransport:
"""A common transport class, containing e.g. the logic to manage
subscriptions a... | [
"workflows.Error",
"logging.getLogger"
] | [((536, 576), 'logging.getLogger', 'logging.getLogger', (['"""workflows.transport"""'], {}), "('workflows.transport')\n", (553, 576), False, 'import logging\n'), ((3795, 3860), 'workflows.Error', 'workflows.Error', (['"""Attempting to unsubscribe unknown subscription"""'], {}), "('Attempting to unsubscribe unknown subs... |
import numpy as np
import torch
import torch.optim as optim
import torch.nn as nn
from torch.autograd import Variable
import skimage.io as io
import argparse
import os
import sys
import time
# Allow python3 to search for modules outside of this directory
sys.path.append("../")
from models.skip import skip3d
from vo... | [
"argparse.ArgumentParser",
"torch.randn",
"torch.cos",
"tools.Ops.volume_proj",
"os.path.join",
"tools.Ops.rotate_volume",
"sys.path.append",
"os.path.exists",
"torch.zeros",
"tools.Ops.load_binvox",
"tools.Ops.tvloss3d",
"torch.nn.ConstantPad3d",
"torch.optim.Adam",
"torch.clamp",
"nump... | [((257, 279), 'sys.path.append', 'sys.path.append', (['"""../"""'], {}), "('../')\n", (272, 279), False, 'import sys\n'), ((714, 785), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Reconstruciton using deep prior."""'}), "(description='Reconstruciton using deep prior.')\n", (737, 785), ... |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
"""Logging related module."""
import os
import logging
from logging import _checkLevel
from fastseq.config import FASTSEQ_DEFAULT_LOG_LEVEL, FASTSEQ_LOG_LEVEL, FASTSEQ_LOG_FORMAT
def set_default_log_level():
"""Set the default log level ... | [
"logging._checkLevel",
"logging.getLogger",
"logging.basicConfig"
] | [((619, 690), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'fastseq_log_level', 'format': 'FASTSEQ_LOG_FORMAT'}), '(level=fastseq_log_level, format=FASTSEQ_LOG_FORMAT)\n', (638, 690), False, 'import logging\n'), ((1017, 1035), 'logging._checkLevel', '_checkLevel', (['level'], {}), '(level)\n', (1028, 10... |
#!/usr/bin/env python
import argparse
from ast import parse
import numpy as np
import bitstring
def to_fixed(x, args):
F = args.fixed_point_bits[0] - args.fixed_point_bits[1]
return np.round(x * 2**F)
def to_float(x, args):
F = args.fixed_point_bits[0] - args.fixed_point_bits[1]
return x * 2**-F
def ... | [
"numpy.load",
"numpy.save",
"numpy.flip",
"argparse.ArgumentParser",
"bitstring.pack",
"numpy.round"
] | [((191, 211), 'numpy.round', 'np.round', (['(x * 2 ** F)'], {}), '(x * 2 ** F)\n', (199, 211), True, 'import numpy as np\n'), ((1090, 1180), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Parse numpy file to FPGA testing for MP7 board"""'}), "(description=\n 'Parse numpy file to FPGA ... |
"""
@brief This file holds classes that store information about the endoscopic images that are
going to be segmented.
@author <NAME> (<EMAIL>).
@date 25 Aug 2015.
"""
import numpy as np
import os
import cv2
# import caffe
import sys
import random
import matplotlib.pyplot as plt
import scipy.misc
import imut... | [
"numpy.sum",
"numpy.ones",
"matplotlib.pyplot.figure",
"numpy.arange",
"common.randbin",
"cv2.imencode",
"cv2.filter2D",
"cv2.cvtColor",
"matplotlib.pyplot.imshow",
"cv2.imwrite",
"numpy.max",
"cv2.LUT",
"cv2.minEnclosingCircle",
"numpy.flipud",
"numpy.min",
"cv2.createCLAHE",
"numpy... | [((533, 553), 'numpy.random.seed', 'np.random.seed', (['seed'], {}), '(seed)\n', (547, 553), True, 'import numpy as np\n'), ((562, 587), 'numpy.arange', 'np.arange', (['(256)'], {'dtype': 'int'}), '(256, dtype=int)\n', (571, 587), True, 'import numpy as np\n'), ((594, 614), 'numpy.random.shuffle', 'np.random.shuffle', ... |
#!/usr/bin/python2
import sys, os
op = os.path.basename(sys.argv[0])
mypath = os.path.abspath(os.path.dirname(sys.argv[0]))
PATH = os.getenv('PATH').split(':')
if op == 'mv':
# copy much cleaner than move in a build (immutable inputs)
op = 'cp'
# Delete ourselves from the PATH
if mypath in PATH:
del PATH... | [
"os.getpid",
"os.path.basename",
"os.getcwd",
"os.path.dirname",
"os.setpgid",
"os.execvp",
"os.getenv"
] | [((40, 69), 'os.path.basename', 'os.path.basename', (['sys.argv[0]'], {}), '(sys.argv[0])\n', (56, 69), False, 'import sys, os\n'), ((410, 441), 'os.getenv', 'os.getenv', (['"""TRACE_LOG_LOCATION"""'], {}), "('TRACE_LOG_LOCATION')\n", (419, 441), False, 'import sys, os\n'), ((595, 611), 'os.setpgid', 'os.setpgid', (['(... |
# Copyright 2019 The TensorFlow Authors. 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 applica... | [
"tensorflow.python.ops.math_ops.argmin",
"tensorflow.python.ipu.config.IPUConfig",
"tensorflow.python.ops.math_ops.argmax",
"numpy.argmax",
"numpy.dtype",
"numpy.argmin",
"tensorflow.python.platform.googletest.main",
"os.environ.get",
"test_utils.ReportJSON",
"tensorflow.python.framework.ops.devic... | [((1394, 1426), 'numpy.issubdtype', 'np.issubdtype', (['dtype', 'np.integer'], {}), '(dtype, np.integer)\n', (1407, 1426), True, 'import numpy as np\n'), ((1730, 1772), 'absl.testing.parameterized.named_parameters', 'parameterized.named_parameters', (['*TESTCASES'], {}), '(*TESTCASES)\n', (1760, 1772), False, 'from abs... |
# coding=utf-8
"""
백준 11279번 : 최대 힙
"""
import heapq
import sys
N = int(sys.stdin.readline())
heap = []
for _ in range(N):
num = int(sys.stdin.readline())
if num == 0:
if len(heap) != 0:
print(heapq.heappop(heap)[1])
else:
print(0)
else:
heapq.heappush(heap,... | [
"heapq.heappush",
"sys.stdin.readline",
"heapq.heappop"
] | [((73, 93), 'sys.stdin.readline', 'sys.stdin.readline', ([], {}), '()\n', (91, 93), False, 'import sys\n'), ((139, 159), 'sys.stdin.readline', 'sys.stdin.readline', ([], {}), '()\n', (157, 159), False, 'import sys\n'), ((300, 333), 'heapq.heappush', 'heapq.heappush', (['heap', '(-num, num)'], {}), '(heap, (-num, num))\... |
import pyHiChi as pfc
import numpy as np
import math as ma
def valueEx(x, y, z):
Ex = 0 #for x or y
#Ex=np.sin(z) #for z
return Ex
def valueEy(x, y, z):
#Ey = 0 #for y or z
#Ey = np.sin(x) #for x
Ey = np.sin(x - z) #for xz
return Ey
def valueEz(x, y, z):
Ez = 0 #for x or z or xz
#Ez = np.sin(y) #for y
retur... | [
"matplotlib.pyplot.show",
"numpy.zeros",
"pyHiChi.PeriodicalBC",
"matplotlib.animation.FuncAnimation",
"numpy.sin",
"numpy.arange",
"pyHiChi.vector3d",
"pyHiChi.YeeGrid",
"numpy.sqrt",
"matplotlib.pyplot.subplots",
"pyHiChi.FDTD"
] | [((902, 926), 'pyHiChi.vector3d', 'pfc.vector3d', (['(20)', '(20)', '(20)'], {}), '(20, 20, 20)\n', (914, 926), True, 'import pyHiChi as pfc\n'), ((939, 966), 'pyHiChi.vector3d', 'pfc.vector3d', (['(0.0)', '(0.0)', '(0.0)'], {}), '(0.0, 0.0, 0.0)\n', (951, 966), True, 'import pyHiChi as pfc\n'), ((979, 1024), 'pyHiChi.... |
"""
* Copyright (c) 2021, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law... | [
"tensorflow.nn.compute_average_loss",
"hugectr_tf_ops.create_embedding",
"hugectr_tf_ops.fprop_v4",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.optimizers.SGD",
"tensorflow.concat",
"tensorflow.keras.losses.BinaryCrossentropy",
"tensorflow.shape",
"tensorflow.python.distribute.values.PerRepli... | [((5341, 5366), 'tensorflow.keras.optimizers.SGD', 'tf.keras.optimizers.SGD', ([], {}), '()\n', (5364, 5366), True, 'import tensorflow as tf\n'), ((5599, 5699), 'tensorflow.keras.losses.BinaryCrossentropy', 'tf.keras.losses.BinaryCrossentropy', ([], {'from_logits': '(False)', 'reduction': 'tf.keras.losses.Reduction.NON... |