content stringlengths 1 1.04M | input_ids listlengths 1 774k | ratio_char_token float64 0.38 22.9 | token_count int64 1 774k |
|---|---|---|---|
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | [
2,
49962,
284,
262,
24843,
10442,
5693,
357,
1921,
37,
8,
739,
530,
198,
2,
393,
517,
18920,
5964,
11704,
13,
220,
4091,
262,
28536,
2393,
198,
2,
9387,
351,
428,
670,
329,
3224,
1321,
198,
2,
5115,
6634,
9238,
13,
220,
383,
7054,... | 2.985425 | 2,470 |
from osrsmath.general.skills import *
import unittest
| [
6738,
28686,
3808,
11018,
13,
24622,
13,
8135,
2171,
1330,
1635,
201,
198,
11748,
555,
715,
395,
201,
198,
201,
198
] | 2.761905 | 21 |
import socket
import serial
import time
import sys
import glob
import signal
from sys import exit
address = '127.0.0.1'
port = 8080
def serial_ports():
""" Lists serial port names
:raises EnvironmentError:
On unsupported or unknown platforms
:returns:
A list of the s... | [
11748,
17802,
198,
11748,
11389,
198,
11748,
640,
220,
220,
220,
198,
11748,
25064,
198,
11748,
15095,
198,
11748,
6737,
198,
6738,
25064,
1330,
8420,
198,
198,
21975,
796,
705,
16799,
13,
15,
13,
15,
13,
16,
6,
198,
634,
796,
4019,
... | 2.097865 | 1,124 |
import socket
import thread
import time
__author__ = "Sushant Raikar"
__email__ = "sushantraikar123@yahoo.com"
class SocketClient:
"""
=================
Pub Sub Generic Client
=================
Description: This is a generic client implementation. All interaction
with the broker is done throug... | [
11748,
17802,
198,
11748,
4704,
198,
11748,
640,
198,
198,
834,
9800,
834,
796,
366,
50,
1530,
415,
7567,
1134,
283,
1,
198,
834,
12888,
834,
796,
366,
82,
1530,
415,
430,
1134,
283,
10163,
31,
40774,
13,
785,
1,
198,
198,
4871,
4... | 2.565977 | 1,546 |
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... | [
2,
15069,
33448,
43208,
21852,
1766,
1539,
12052,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198... | 3.476974 | 304 |
# Copyright (c) 2013, Web Notes Technologies Pvt. Ltd. and Contributors
# MIT License. See license.txt
from __future__ import unicode_literals
import frappe, re
from frappe.website.website_generator import WebsiteGenerator
from frappe.website.render import clear_cache
from frappe import _
from frappe.utils import to... | [
2,
15069,
357,
66,
8,
2211,
11,
5313,
11822,
21852,
18367,
83,
13,
12052,
13,
290,
25767,
669,
198,
2,
17168,
13789,
13,
4091,
5964,
13,
14116,
198,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
11748,
5... | 3.521739 | 92 |
#Siege
import bs
import bsUtils
import random
| [
2,
50,
14566,
198,
11748,
275,
82,
198,
11748,
275,
82,
18274,
4487,
198,
11748,
4738,
198
] | 2.705882 | 17 |
import serial | [
11748,
11389
] | 6.5 | 2 |
# encoding: utf-8
from __future__ import print_function
from functools import wraps
import numpy as np
import pandas as pd
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
import matplotlib.gridspec as gridspec
import sea... | [
2,
21004,
25,
3384,
69,
12,
23,
198,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
6738,
1257,
310,
10141,
1330,
27521,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
198,
11748,
2603,
... | 2.088223 | 9,374 |
# Copyright (c) 2014-2015, Doug Kelly
# 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 and... | [
2,
15069,
357,
66,
8,
1946,
12,
4626,
11,
15115,
9077,
198,
2,
1439,
2489,
10395,
13,
198,
2,
198,
2,
2297,
396,
3890,
290,
779,
287,
2723,
290,
13934,
5107,
11,
351,
393,
1231,
198,
2,
17613,
11,
389,
10431,
2810,
326,
262,
170... | 3.540117 | 511 |
# from .constants import *
from rcosautomation.discord.constants import MATTERMOST_USERNAME, MATTERMOST_PASSWORD, VOICE_CHANNEL
from rcosautomation.discord.channels import add_channel_if_not_exists
import requests
from mattermostdriver import Driver
# mattermost = Driver({
# 'url': '54.197.25.170',
# 'login_... | [
2,
422,
764,
9979,
1187,
1330,
1635,
198,
6738,
374,
6966,
2306,
296,
341,
13,
15410,
585,
13,
9979,
1187,
1330,
36775,
5781,
44,
10892,
62,
29904,
20608,
11,
36775,
5781,
44,
10892,
62,
47924,
54,
12532,
11,
30578,
8476,
62,
3398,
... | 2.948012 | 327 |
import chess_diagrams
# setup for all tests. See https://docs.pytest.org/en/2.7.3/xunit_setup.html
#
# Test for a single response. See http://flask.pocoo.org/docs/1.0/testing/
#
| [
11748,
19780,
62,
10989,
6713,
82,
628,
198,
2,
9058,
329,
477,
5254,
13,
4091,
3740,
1378,
31628,
13,
9078,
9288,
13,
2398,
14,
268,
14,
17,
13,
22,
13,
18,
14,
87,
20850,
62,
40406,
13,
6494,
198,
2,
628,
198,
2,
6208,
329,
... | 2.520548 | 73 |
import base64
import hashlib
from Crypto import Random
from Crypto.Cipher import DES3
class TDESCipher(object):
"""
Triple DES (Data Encryption Standard)
Enchaine 3 applications successives de l'algorithme DES sur le meme bloc de donnees de 64 bits, avec 2 ou 3 clef DES differentes.
Le TDES est crypto... | [
11748,
2779,
2414,
198,
11748,
12234,
8019,
198,
198,
6738,
36579,
1330,
14534,
198,
6738,
36579,
13,
34,
10803,
1330,
22196,
18,
198,
198,
4871,
13320,
1546,
34,
10803,
7,
15252,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1... | 2.773504 | 234 |
import os
from pymodm import fields, MongoModel, connect
from pymodm.errors import DoesNotExist
from passlib.hash import pbkdf2_sha256
connect("mongodb://localhost:27017/database")
def add_user(username, password):
"""Creates new user if user does not exist in the mongo database
:param username: user e... | [
11748,
28686,
198,
6738,
12972,
4666,
76,
1330,
7032,
11,
42591,
17633,
11,
2018,
198,
6738,
12972,
4666,
76,
13,
48277,
1330,
8314,
3673,
3109,
396,
198,
6738,
1208,
8019,
13,
17831,
1330,
279,
65,
74,
7568,
17,
62,
26270,
11645,
198... | 2.623011 | 1,634 |
from flask import Flask, request, send_from_directory, jsonify
import nltk
nltk.download('vader_lexicon')
from nltk.sentiment.vader import SentimentIntensityAnalyzer
app = Flask(__name__, static_url_path='/static')
@app.route('/js/<path:path>')
@app.route("/")
@app.route("/get_sentiment", methods=['GET', 'POST']... | [
6738,
42903,
1330,
46947,
11,
2581,
11,
3758,
62,
6738,
62,
34945,
11,
33918,
1958,
198,
11748,
299,
2528,
74,
198,
77,
2528,
74,
13,
15002,
10786,
85,
5067,
62,
2588,
4749,
11537,
198,
6738,
299,
2528,
74,
13,
34086,
3681,
13,
85,
... | 2.644928 | 138 |
from __future__ import unicode_literals
import pytest
@pytest.fixture(autouse=True)
@pytest.fixture
@pytest.fixture(autouse=True)
@pytest.fixture(autouse=True)
| [
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
11748,
12972,
9288,
628,
198,
31,
9078,
9288,
13,
69,
9602,
7,
2306,
1076,
28,
17821,
8,
628,
198,
31,
9078,
9288,
13,
69,
9602,
628,
198,
31,
9078,
9288,
13,
6... | 2.560606 | 66 |
from model.group import Group
testdata = [
Group(name='Name1', header='header1', footer='footer1'),
Group(name='Name2', header='header2', footer='footer2')
] | [
6738,
2746,
13,
8094,
1330,
4912,
198,
198,
9288,
7890,
796,
685,
198,
220,
220,
220,
4912,
7,
3672,
11639,
5376,
16,
3256,
13639,
11639,
25677,
16,
3256,
2366,
263,
11639,
5898,
263,
16,
33809,
198,
220,
220,
220,
4912,
7,
3672,
11... | 2.766667 | 60 |
##### This script splits of the assembly in subcontigs wherever there is a "N" stretch longer than 30N
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from Bio.Alphabet import IUPAC
import glob
Assemblies = glob.glob("/media/avneesh/AneeshHDDfat/AssembledScaffolds/*")
N_stretch_len... | [
198,
4242,
2,
770,
4226,
30778,
286,
262,
10474,
287,
850,
3642,
9235,
14530,
612,
318,
257,
366,
45,
1,
7539,
2392,
621,
1542,
45,
198,
198,
6738,
16024,
1330,
1001,
80,
9399,
198,
6738,
16024,
13,
4653,
80,
1330,
1001,
80,
198,
... | 2.047236 | 995 |
from flask import Blueprint, render_template, request, jsonify
from helpers.database import db
from model.models import Project, Component
comp = Blueprint('component', __name__)
@comp.route('/component', methods=['GET'])
@comp.route('/component', methods=['POST'])
@comp.route('/component', methods=['PUT'])
@c... | [
6738,
42903,
1330,
39932,
11,
8543,
62,
28243,
11,
2581,
11,
33918,
1958,
198,
6738,
49385,
13,
48806,
1330,
20613,
198,
6738,
2746,
13,
27530,
1330,
4935,
11,
35100,
198,
198,
5589,
796,
39932,
10786,
42895,
3256,
11593,
3672,
834,
8,
... | 3.37963 | 108 |
from cloudferry.lib.base.action import action
| [
6738,
6279,
2232,
563,
13,
8019,
13,
8692,
13,
2673,
1330,
2223,
628
] | 3.615385 | 13 |
import ice
import torch
from ice.core.loss import LossNode
from ice.core.metric import MetricNode
from torch import autocast, nn
from torch.nn import functional as F
from torch.optim import Adam
from torchvision.datasets import CIFAR10
from torchvision.transforms import Compose, Normalize, ToTensor
# arguments
ice.ar... | [
11748,
4771,
198,
11748,
28034,
198,
6738,
4771,
13,
7295,
13,
22462,
1330,
22014,
19667,
198,
6738,
4771,
13,
7295,
13,
4164,
1173,
1330,
3395,
1173,
19667,
198,
6738,
28034,
1330,
1960,
420,
459,
11,
299,
77,
198,
6738,
28034,
13,
2... | 2.33122 | 631 |
import requests
| [
11748,
7007,
628
] | 5.666667 | 3 |
"""Contract test cases for main."""
from typing import Any
import pytest
import requests
@pytest.mark.contract
def test_main(http_service: Any) -> None:
"""Should return 200 and html."""
url = f"{http_service}"
response = requests.get(url)
assert response.status_code == 200
assert response.heade... | [
37811,
45845,
1332,
2663,
329,
1388,
526,
15931,
198,
6738,
19720,
1330,
4377,
198,
198,
11748,
12972,
9288,
198,
11748,
7007,
628,
198,
31,
9078,
9288,
13,
4102,
13,
28484,
198,
4299,
1332,
62,
12417,
7,
4023,
62,
15271,
25,
4377,
8,... | 3.014925 | 134 |
"""ESI slack bot for tweetfleet."""
import os
import time
from slackclient import SlackClient
from esi_bot import ESI
from esi_bot import ESI_CHINA
from esi_bot import LOG
from esi_bot import request
from esi_bot.processor import Processor
from esi_bot.commands import ( # noqa: F401; # pylint: disable=unused-impor... | [
37811,
1546,
40,
30740,
10214,
329,
6126,
33559,
526,
15931,
198,
198,
11748,
28686,
198,
11748,
640,
198,
198,
6738,
30740,
16366,
1330,
36256,
11792,
198,
198,
6738,
1658,
72,
62,
13645,
1330,
412,
11584,
198,
6738,
1658,
72,
62,
1364... | 2.313821 | 615 |
# Copyright (c) 2017 The Regents of the University of Michigan
# All rights reserved.
# This software is licensed under the BSD 3-Clause License.
import itertools
from . import scheduler
from signac.common.six import with_metaclass
import uuid
# def _fn_bundle(self, bundle_id):
# return os.path.join(self.root_dire... | [
2,
15069,
357,
66,
8,
2177,
383,
3310,
658,
286,
262,
2059,
286,
7055,
198,
2,
1439,
2489,
10395,
13,
198,
2,
770,
3788,
318,
11971,
739,
262,
347,
10305,
513,
12,
2601,
682,
13789,
13,
198,
11748,
340,
861,
10141,
198,
6738,
764,... | 2.329803 | 661 |
import cv2 as cv
img = cv.imread("testeOpenCV.jpg")
cinza = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
print(cinza.shape)
cv.imshow("Joelma Cinza", cinza)
cv.waitKey(0)
| [
11748,
269,
85,
17,
355,
269,
85,
198,
9600,
796,
269,
85,
13,
320,
961,
7203,
9288,
68,
11505,
33538,
13,
9479,
4943,
198,
17879,
4496,
796,
269,
85,
13,
33967,
83,
10258,
7,
9600,
11,
269,
85,
13,
46786,
62,
33,
10761,
17,
38,... | 2 | 81 |
import pandas as pd
import matplotlib.pyplot as plt
plt.switch_backend('Qt4Agg')
import os
data_folder = "C:\\Users\\jeroe\\PycharmProjects\\PythonDataScienceWorkshops\\data"
os.chdir(data_folder)
temp = pd.read_csv("mean_temperature.csv", delimiter="\t", header=None)
print(temp.head()) | [
11748,
19798,
292,
355,
279,
67,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
489,
83,
13,
31943,
62,
1891,
437,
10786,
48,
83,
19,
46384,
11537,
198,
198,
11748,
28686,
198,
7890,
62,
43551,
796,
366,
34,
25,
... | 2.675926 | 108 |
from .stats_influx import StatsInflux
from pymongo import MongoClient, database, collection
from urllib.parse import quote_plus
| [
6738,
764,
34242,
62,
10745,
22564,
1330,
20595,
18943,
22564,
198,
6738,
279,
4948,
25162,
1330,
42591,
11792,
11,
6831,
11,
4947,
198,
6738,
2956,
297,
571,
13,
29572,
1330,
9577,
62,
9541,
628,
628,
628,
628,
628,
628,
628,
628,
62... | 3.395349 | 43 |
from torchvision.models.resnet import ResNet, Bottleneck, model_urls
| [
6738,
28034,
10178,
13,
27530,
13,
411,
3262,
1330,
1874,
7934,
11,
14835,
43163,
11,
2746,
62,
6371,
82,
628
] | 3.5 | 20 |
s = raw_input()
n = len(s)
global dp
dp = [[False]*n for x in range(n)]
count = 0
for i in range(n-1):
if s[i:i+2] in ["()","??","(?","?)"]:
# print "NEtered"
dp[i][i+1] = True
#for i in range(n):
# for j in range(n):
# if dp[i][j]:count+=1;print i,j,s[i:j+1]
if n%2==0:
recur(s,n,0,n-1)
for i i... | [
198,
82,
796,
8246,
62,
15414,
3419,
198,
77,
796,
18896,
7,
82,
8,
198,
20541,
288,
79,
198,
26059,
796,
16410,
25101,
60,
9,
77,
329,
2124,
287,
2837,
7,
77,
15437,
198,
9127,
796,
657,
198,
1640,
1312,
287,
2837,
7,
77,
12,
... | 1.571429 | 553 |
from .element import Element
from .mixin import ReqInjectScriptMixin
from .menu import Menu, MenuItem
from .icon import Icon
class SideBar(Element, ReqInjectScriptMixin):
"""Sidebar widget (sidebar_menu, nav_menu, content)
Example: append sidebar_menu::
sidebar = uio.SideBar()
sidebar... | [
6738,
764,
30854,
1330,
11703,
198,
6738,
764,
19816,
259,
1330,
797,
80,
818,
752,
7391,
35608,
259,
198,
6738,
764,
26272,
1330,
21860,
11,
21860,
7449,
198,
6738,
764,
4749,
1330,
26544,
198,
198,
4871,
12075,
10374,
7,
20180,
11,
... | 2.092157 | 510 |
from datetime import datetime
from freezegun import freeze_time
import doccron
def foo() -> None:
"""
This function prints "foo"
/etc/crontab::
* * * * * 2021
* * * * * 2020
:returns: None
"""
print("foo")
def bar() -> None:
"""
/etc/crontab::
* * * ... | [
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
6738,
1479,
89,
1533,
403,
1330,
16611,
62,
2435,
198,
198,
11748,
2205,
66,
1313,
628,
198,
4299,
22944,
3419,
4613,
6045,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
770,
2163,
... | 2.125 | 248 |
# Authors: Gavin Niendorf <gavinniendorf@gmail.com>
#
# Classes and methods for defining rays and their propagation rules.
#
# License: MIT
import numpy as np
from .transforms import *
from .exceptions import NormalizationError, NotOnSurfaceError
class ray:
"""Class for rays and their propagation through surface... | [
2,
46665,
25,
30857,
11556,
18738,
69,
1279,
70,
615,
3732,
72,
18738,
69,
31,
14816,
13,
785,
29,
198,
2,
198,
2,
38884,
290,
5050,
329,
16215,
24823,
290,
511,
43594,
3173,
13,
198,
2,
198,
2,
13789,
25,
17168,
198,
198,
11748,
... | 2.213173 | 3,401 |
#!/usr/bin/env python3
# -*- encoding: utf-8 -*-
'''
@author: yuejl
@application:
@contact: lewyuejian@163.com
@file: strutil.py
@time: 2021/7/3 0003 22:19
@desc:
'''
import ujson
import re
import random
import string
import uuid | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
21004,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
7061,
6,
198,
31,
9800,
25,
331,
518,
20362,
198,
31,
31438,
25,
198,
31,
32057,
25,
443,
21768,
518,
73,
666,
... | 2.385417 | 96 |
import numpy as np
from numba import jitclass
from numba import int32, float32
spec = [
('value', int32),
('array', float32[:]),
]
@jitclass(spec)
| [
11748,
299,
32152,
355,
45941,
198,
198,
6738,
997,
7012,
1330,
474,
270,
4871,
198,
6738,
997,
7012,
1330,
493,
2624,
11,
12178,
2624,
628,
198,
16684,
796,
685,
198,
220,
220,
220,
19203,
8367,
3256,
493,
2624,
828,
198,
220,
220,
... | 2.580645 | 62 |
import random
| [
11748,
4738,
628,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198
] | 1.666667 | 18 |
"""
Patrons file incoming from IS&T in a version 1 schema to a version 2 schema
written by J Ammerman [jwacooks] (2015-10-09)
edited by A Sawyer [atla5] (2019-09-04)
"""
# coding: utf-8
# requires python 3.x
# load required modules
import codecs
import os
import xml.etree.ElementTree as ET
import glob
from zipfil... | [
37811,
198,
12130,
12212,
2393,
15619,
422,
3180,
5,
51,
287,
257,
2196,
352,
32815,
284,
257,
2196,
362,
32815,
198,
220,
3194,
416,
449,
1703,
647,
805,
685,
73,
86,
330,
31085,
60,
357,
4626,
12,
940,
12,
2931,
8,
198,
220,
130... | 2.305677 | 1,145 |
from extract_image_features.video_utils import *
import numpy as np
from extract_image_features.keras_pretrained_models.imagenet_utils import preprocess_input
from keras.models import Model
from keras.preprocessing import image
from extract_image_features.keras_pretrained_models.vgg19 import VGG19
# file saving and lo... | [
6738,
7925,
62,
9060,
62,
40890,
13,
15588,
62,
26791,
1330,
1635,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
7925,
62,
9060,
62,
40890,
13,
6122,
292,
62,
5310,
13363,
62,
27530,
13,
320,
11286,
316,
62,
26791,
1330,
662,
14681,
... | 2.488764 | 1,780 |
import sqlite3 | [
11748,
44161,
578,
18
] | 3.5 | 4 |
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next | [
2,
30396,
329,
1702,
306,
12,
25614,
1351,
13,
198,
2,
1398,
7343,
19667,
25,
198,
2,
220,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
1188,
28,
15,
11,
1306,
28,
14202,
2599,
198,
2,
220,
220,
220,
220,
220,
220,
220,
... | 2.272727 | 66 |
"""Allows to configure custom shell commands to turn a value for a sensor."""
CONF_COMMAND_TIMEOUT = "command_timeout"
DEFAULT_TIMEOUT = 15
DOMAIN = "command_line"
PLATFORMS = ["binary_sensor", "cover", "sensor", "switch"]
| [
37811,
34934,
284,
17425,
2183,
7582,
9729,
284,
1210,
257,
1988,
329,
257,
12694,
526,
15931,
198,
198,
10943,
37,
62,
9858,
44,
6981,
62,
34694,
12425,
796,
366,
21812,
62,
48678,
1,
198,
7206,
38865,
62,
34694,
12425,
796,
1315,
19... | 3.068493 | 73 |
import os
import sys
import hashlib
| [
11748,
28686,
198,
11748,
25064,
198,
11748,
12234,
8019,
628,
628,
628,
628,
198
] | 3.142857 | 14 |
# Generated by Django 2.2.10 on 2020-05-29 12:30
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
362,
13,
17,
13,
940,
319,
12131,
12,
2713,
12,
1959,
1105,
25,
1270,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.875 | 32 |
from transformers import ElectraTokenizer, ElectraForSequenceClassification, pipeline
from pprint import pprint
tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-small-finetuned-nsmc")
model = ElectraForSequenceClassification.from_pretrained("monologg/koelectra-small-finetuned-nsmc")
nsmc = pipeline("s... | [
6738,
6121,
364,
1330,
5903,
430,
30642,
7509,
11,
5903,
430,
1890,
44015,
594,
9487,
2649,
11,
11523,
198,
6738,
279,
4798,
1330,
279,
4798,
198,
198,
30001,
7509,
796,
5903,
430,
30642,
7509,
13,
6738,
62,
5310,
13363,
7203,
2144,
9... | 1.371212 | 396 |
from __future__ import division
import numpy as np
import tensorflow as tf
from SIDLoader import SIDLoader
from ModelBuilder import ModelBuilder
from Experiment import Experiment
import time,datetime,os,glob
path_prefix = '.'
checkpoint_dir = path_prefix+'/chk'
dataset_dir = path_prefix+'/dataset'
black_level = 512
se... | [
6738,
11593,
37443,
834,
1330,
7297,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
6738,
311,
2389,
17401,
1330,
311,
2389,
17401,
198,
6738,
9104,
32875,
1330,
9104,
32875,
198,
6738,
29544,
1330,
29... | 2.49938 | 1,614 |
with open('./input.txt') as infile:
jumps = [int(i.rstrip('\n')) for i in infile.readlines()]
steps = 0
idx = 0
while idx < (len(jumps)):
step = jumps[idx]
if step >= 3:
jumps[idx] -= 1
else:
jumps[idx] += 1
idx += step
steps += 1
pr... | [
4480,
1280,
7,
4458,
14,
15414,
13,
14116,
11537,
355,
1167,
576,
25,
198,
220,
220,
220,
18045,
796,
685,
600,
7,
72,
13,
81,
36311,
10786,
59,
77,
6,
4008,
329,
1312,
287,
1167,
576,
13,
961,
6615,
3419,
60,
198,
220,
220,
220... | 1.849162 | 179 |
from geneal.genetic_algorithms import ContinuousGenAlgSolver, BinaryGenAlgSolver
| [
6738,
9779,
282,
13,
5235,
5139,
62,
282,
7727,
907,
1330,
45012,
13746,
2348,
70,
50,
14375,
11,
45755,
13746,
2348,
70,
50,
14375,
628
] | 3.28 | 25 |
# from KK
import matplotlib
matplotlib.use('Agg')
from rnn import RNN
from copy import deepcopy
import time
import os
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
from torch.nn.utils.clip_grad import clip_grad_norm
import torch.nn.functional as F
import torch.optim as optim
from t... | [
2,
422,
509,
42,
198,
11748,
2603,
29487,
8019,
198,
6759,
29487,
8019,
13,
1904,
10786,
46384,
11537,
198,
6738,
374,
20471,
1330,
371,
6144,
198,
6738,
4866,
1330,
2769,
30073,
198,
11748,
640,
198,
11748,
28686,
198,
11748,
28034,
19... | 2.430898 | 2,518 |
# climatology test adpated from Patrick Halsall's
# ftp://ftp.aoml.noaa.gov/phod/pub/bringas/XBT/AQC/AOML_AQC_2018/codes/qc_checks/clima_checker.py
import sys, numpy
import util.AOMLinterpolation as interp_helper
import util.AOMLnetcdf as read_netcdf
def climatology_check(temperature, interpMNTemp, interpSDTemp, sig... | [
2,
5424,
265,
1435,
1332,
512,
79,
515,
422,
9925,
367,
874,
439,
338,
220,
198,
2,
10117,
79,
1378,
701,
79,
13,
64,
296,
75,
13,
3919,
7252,
13,
9567,
14,
746,
375,
14,
12984,
14,
48580,
292,
14,
55,
19313,
14,
32,
48,
34,
... | 2.991202 | 682 |
from django.contrib import admin
from .models import *
admin.site.register(Scientist)
admin.site.register(Employer)
admin.site.register(DataPool)
admin.site.register(DataEntry) | [
6738,
42625,
14208,
13,
3642,
822,
1330,
13169,
198,
6738,
764,
27530,
1330,
1635,
198,
198,
28482,
13,
15654,
13,
30238,
7,
23010,
396,
8,
198,
28482,
13,
15654,
13,
30238,
7,
29733,
263,
8,
198,
28482,
13,
15654,
13,
30238,
7,
660... | 3.218182 | 55 |
"""
Module containing different distance functions.
"""
import numpy as np
from scipy import stats
def linear_distance(data, synth_data):
""" compute linear distance between autocorrelations.
Parameters
-----------
data : 1d array
autocorrelation of real data.
synth_data : 1d array
... | [
37811,
198,
26796,
7268,
1180,
5253,
5499,
13,
220,
198,
37811,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
629,
541,
88,
1330,
9756,
628,
198,
4299,
14174,
62,
30246,
7,
7890,
11,
33549,
62,
7890,
2599,
198,
220,
220,
220,
37227,
... | 2.589005 | 382 |
# Copyright 2013-2014 DataStax, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writi... | [
2,
15069,
2211,
12,
4967,
6060,
1273,
897,
11,
3457,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789... | 3.619512 | 205 |
""" This module contains a class to represent multiple Tichu Cards. """
BOMBS = ['four_bomb', 'straight_bomb']
class Cards():
"""
A class to represent multiple Tichu Cards.
Can either be a hand (i.e. no specific combination)
or a combination (e.g. pair, straight, ...).
The type is determined auto... | [
37811,
770,
8265,
4909,
257,
1398,
284,
2380,
3294,
309,
488,
84,
15824,
13,
37227,
198,
198,
33,
2662,
4462,
796,
37250,
14337,
62,
27657,
3256,
705,
42729,
62,
27657,
20520,
198,
198,
4871,
15824,
33529,
198,
220,
220,
220,
37227,
1... | 1.982524 | 12,131 |
# Copyright Materialize, Inc. and contributors. All rights reserved.
#
# Use of this software is governed by the Business Source License
# included in the LICENSE file at the root of this repository.
#
# As of the Change Date specified in that file, in accordance with
# the Business Source License, use of this software... | [
2,
15069,
14633,
1096,
11,
3457,
13,
290,
20420,
13,
1439,
2489,
10395,
13,
198,
2,
198,
2,
5765,
286,
428,
3788,
318,
21825,
416,
262,
7320,
8090,
13789,
198,
2,
3017,
287,
262,
38559,
24290,
2393,
379,
262,
6808,
286,
428,
16099,
... | 4.115044 | 113 |
import itertools
import Utterance
import PossibleWorld
#this table contains all the possible worlds
#this adds up all of the possible world probabilities in the rows and columns of a table
#re-adds up all of the columns and rows so that normalization is accurate
#important function for normalizing so that we ca... | [
11748,
340,
861,
10141,
198,
11748,
7273,
353,
590,
198,
11748,
33671,
10603,
198,
2,
5661,
3084,
4909,
477,
262,
1744,
11621,
628,
197,
2,
5661,
6673,
510,
477,
286,
262,
1744,
995,
39522,
287,
262,
15274,
290,
15180,
286,
257,
3084,... | 4.395062 | 81 |
# coding=utf-8
"""
dataloader for PASCAL VOC 2012 dataset
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import numpy as np
from PIL import Image
from torchvision import transforms
from torch.utils.data import Dataset
from RMI.dataloaders i... | [
2,
19617,
28,
40477,
12,
23,
198,
198,
37811,
198,
67,
10254,
1170,
263,
329,
350,
42643,
1847,
569,
4503,
2321,
27039,
198,
37811,
198,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
6738,
11593,
37443,
834,
1330,
7297,
19... | 2.474289 | 1,828 |
'''
Dataloader.py
'''
import cv2
import sys,os
import xml.etree.ElementTree as ET
import numpy as np
print(os.listdir())
'''
Gets the coordinates of the bounding box of the object
returns the bounding box
'''
'''
Returns the one hot encoded label list as a numpy array
'''
'''
This is the function th... | [
7061,
6,
201,
198,
35,
10254,
1170,
263,
13,
9078,
201,
198,
7061,
6,
201,
198,
11748,
269,
85,
17,
201,
198,
11748,
25064,
11,
418,
201,
198,
11748,
35555,
13,
316,
631,
13,
20180,
27660,
355,
12152,
201,
198,
11748,
299,
32152,
... | 2.862857 | 175 |
# -*- coding: utf-8 -*-
# Generated by Django 1.9 on 2016-04-10 22:32
from __future__ import unicode_literals
from django.db import migrations, models
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
2980,
515,
416,
37770,
352,
13,
24,
319,
1584,
12,
3023,
12,
940,
2534,
25,
2624,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
6738,
... | 2.781818 | 55 |
# # 1 uzdevums
name = input("Enter your name: ")
age = int(input(name + ", how old are you?"))
import datetime
currentYear = datetime.datetime.now().year
print("You will be 100 in", 100-age, "years and that will be year", currentYear+(100-age))
# name = input("What is your name?")
# age = input (f"What is your age {n... | [
2,
1303,
352,
334,
89,
7959,
5700,
198,
3672,
796,
5128,
7203,
17469,
534,
1438,
25,
366,
8,
198,
496,
796,
493,
7,
15414,
7,
3672,
1343,
33172,
703,
1468,
389,
345,
1701,
4008,
198,
11748,
4818,
8079,
198,
14421,
17688,
796,
4818,
... | 2.788732 | 213 |
# coding: utf-8
import time
import torch
import torch.nn.functional as F
import torchvision
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import sys
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # 均已测试
print(device, torch.__version__)
# 读取内容图像和样式图像
content_img = ... | [
2,
19617,
25,
3384,
69,
12,
23,
198,
198,
11748,
640,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
198,
11748,
28034,
10178,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
350,
4146,
1330,
7412,
198,
11748,
26... | 2.102094 | 764 |
"""Scraping reviews and ratings from goodreads.com
DESCRIPTION:
Scraping the newest reviews from a given goodreads book url. Script works as follows:
1. Get the given url and open with webdriver of selenium.
2. Sort the reviews by newest.
3. Parse the returned web page using BeautifulSoup4... | [
37811,
3351,
2416,
278,
8088,
290,
10109,
422,
922,
40779,
13,
785,
198,
198,
30910,
40165,
25,
628,
220,
220,
220,
1446,
2416,
278,
262,
15530,
8088,
422,
257,
1813,
922,
40779,
1492,
19016,
13,
12327,
2499,
355,
5679,
25,
198,
220,
... | 2.527778 | 324 |
"""Format base class"""
import abc
from typing import Any, BinaryIO, Iterable, Iterator
from wingline.types import Payload
class Format(metaclass=abc.ABCMeta):
"""Base class for a file format."""
mime_type: str
suffixes: Iterable[str] = set()
@property
def reader(self) -> Iterator[dict[str, An... | [
37811,
26227,
2779,
1398,
37811,
198,
198,
11748,
450,
66,
198,
6738,
19720,
1330,
4377,
11,
45755,
9399,
11,
40806,
540,
11,
40806,
1352,
198,
198,
6738,
8539,
1370,
13,
19199,
1330,
7119,
2220,
628,
198,
4871,
18980,
7,
4164,
330,
3... | 2.682099 | 324 |
# Generated by Django 3.0.2 on 2020-03-20 11:48
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
15,
13,
17,
319,
12131,
12,
3070,
12,
1238,
1367,
25,
2780,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
from flask import jsonify, make_response
from api.v1.models.office_model import OfficesModel
from api.v1.models.party_model import PartiesModel
| [
6738,
42903,
1330,
33918,
1958,
11,
787,
62,
26209,
198,
6738,
40391,
13,
85,
16,
13,
27530,
13,
31810,
62,
19849,
1330,
3242,
1063,
17633,
198,
6738,
40391,
13,
85,
16,
13,
27530,
13,
10608,
62,
19849,
1330,
32024,
17633,
628,
198
] | 3.47619 | 42 |
from functools import reduce
from operator import mul
from AoC20.day_16 import data as data, parse
rules, my_ticket, other_tickets = parse(data)
other_tickets = [ticket for ticket in other_tickets if rules.ticket_violation(ticket) is None]
fields = rules.field_deduction(other_tickets)
print(reduce(mul, [my_ticket[id... | [
6738,
1257,
310,
10141,
1330,
4646,
198,
6738,
10088,
1330,
35971,
198,
198,
6738,
27378,
34,
1238,
13,
820,
62,
1433,
1330,
1366,
355,
1366,
11,
21136,
628,
198,
38785,
11,
616,
62,
43350,
11,
584,
62,
83,
15970,
796,
21136,
7,
789... | 3.046875 | 128 |
from django import template
from django.core.urlresolvers import reverse
register = template.Library()
@register.tag
| [
6738,
42625,
14208,
1330,
11055,
198,
6738,
42625,
14208,
13,
7295,
13,
6371,
411,
349,
690,
1330,
9575,
628,
198,
30238,
796,
11055,
13,
23377,
3419,
198,
198,
31,
30238,
13,
12985,
628,
198
] | 3.588235 | 34 |
# Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0
# For details: https://bitbucket.org/ned/coveragepy/src/default/NOTICE.txt
"""OS information for testing."""
from coverage import env
if env.WINDOWS:
# Windows implementation
def process_ram():
"""How much RAM is this pr... | [
2,
49962,
739,
262,
24843,
13789,
25,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
1114,
3307,
25,
3740,
1378,
2545,
27041,
316,
13,
2398,
14,
2817,
14,
1073,
1857,
9078,
14,
... | 2.069523 | 1,237 |
import random
# for declaring function using def
test_function()
test_function_parameter("teste parameter")
# function type get type variable
list = ["ade"]
print(type(list))
# function int formating string to int
string = "10"
print(int(string))
# function input receive a value entry from the user in version... | [
11748,
4738,
628,
198,
2,
329,
18684,
2163,
1262,
825,
628,
198,
9288,
62,
8818,
3419,
628,
198,
198,
9288,
62,
8818,
62,
17143,
2357,
7203,
9288,
68,
11507,
4943,
198,
198,
2,
2163,
2099,
651,
2099,
7885,
198,
4868,
796,
14631,
671... | 3.043624 | 596 |
#
# --------------------------------------------------------------------------------------------------------------------
# <copyright company="Aspose" file="base_test_context.py">
# Copyright (c) 2020 Aspose.Tasks Cloud
# </copyright>
# <summary>
# Permission is hereby granted, free of charge, to any person obtaini... | [
2,
198,
2,
16529,
3880,
19351,
198,
2,
1279,
22163,
4766,
1664,
2625,
1722,
3455,
1,
2393,
2625,
8692,
62,
9288,
62,
22866,
13,
9078,
5320,
198,
2,
220,
220,
15069,
357,
66,
8,
12131,
1081,
3455,
13,
51,
6791,
10130,
198,
2,
7359,... | 4.095477 | 398 |
"""Tests for :py:mod:`katsdpdisp.data`."""
import numpy as np
from numpy.testing import assert_array_equal
from katsdpdisp.data import SparseArray
def test_sparsearray(fullslots=100,fullbls=10,fullchan=5,nslots=10,maxbaselines=6,islot_new_bls=6):
"""Simulates the assignment and retrieval of data as it happens in ... | [
37811,
51,
3558,
329,
1058,
9078,
25,
4666,
25,
63,
74,
1381,
26059,
6381,
79,
13,
7890,
63,
526,
15931,
198,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
299,
32152,
13,
33407,
1330,
6818,
62,
18747,
62,
40496,
198,
6738,
479,
13... | 2.310642 | 1,043 |
import requests
from urllib.parse import urlencode
from_mate = "http://172.16.0.69:3000"
to_mate = "http://mete.cloud.cccfr"
for category in ("users", "drinks"):
items = get_items(category)
for item in items:
set_item(item, category)
| [
11748,
7007,
198,
6738,
2956,
297,
571,
13,
29572,
1330,
2956,
11925,
8189,
198,
198,
6738,
62,
9830,
796,
366,
4023,
1378,
23628,
13,
1433,
13,
15,
13,
3388,
25,
23924,
1,
198,
1462,
62,
9830,
796,
366,
4023,
1378,
4164,
68,
13,
... | 2.52 | 100 |
#!/usr/bin/python
import fire
import os
import re
import requests
from configparser import ConfigParser
from datetime import datetime
HTTP_OK_200 = 200
HTTP_CREATED_201 = 201
HTTP_AUTHORIZATION_401 = 401
HTTP_NOT_FOUND_404 = 404
class Github(object):
'''Base class to interface with Github.com.
'''
usern... | [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
11748,
2046,
198,
11748,
28686,
198,
11748,
302,
198,
11748,
7007,
198,
6738,
4566,
48610,
1330,
17056,
46677,
198,
6738,
4818,
8079,
1330,
4818,
8079,
628,
198,
40717,
62,
11380,
62,
2167,
796... | 2.035565 | 1,912 |
"""Helper to check if path is safe to remove."""
from pathlib import Path
from custom_components.racelandshop.share import get_racelandshop
def is_safe_to_remove(path: str) -> bool:
"""Helper to check if path is safe to remove."""
racelandshop = get_racelandshop()
paths = [
Path(f"{racelandshop.c... | [
37811,
47429,
284,
2198,
611,
3108,
318,
3338,
284,
4781,
526,
15931,
198,
6738,
3108,
8019,
1330,
10644,
198,
198,
6738,
2183,
62,
5589,
3906,
13,
11510,
8822,
24643,
13,
20077,
1330,
651,
62,
11510,
8822,
24643,
628,
198,
4299,
318,
... | 2.585014 | 347 |
#!/usr/bin/env python
#-*- coding:utf-8 -*-
# Ref:
# https://www.reddit.com/r/learnpython/comments/9oc0mu/just_an_interesting_thing_i_found/
# https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments
a = f()
b = f()
a.append(3)
b.append(4)
print(b)
# Solution
# Ref: https://docs.python-guide.org/w... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
12,
9,
12,
19617,
25,
40477,
12,
23,
532,
9,
12,
198,
198,
2,
6524,
25,
220,
198,
2,
3740,
1378,
2503,
13,
10748,
13,
785,
14,
81,
14,
35720,
29412,
14,
15944,
14,
24,
420,
... | 2.431579 | 190 |
"""
Created on Thu Oct 26 14:19:44 2017
@author: Utku Ozbulak - github.com/utkuozbulak
"""
import os
import numpy as np
import torch
from torch.optim import SGD
from cnn_visualization.misc_functions import preprocess_image, recreate_image, save_image
import argparse
import torch.nn as nn
class ClassSpecificImageGe... | [
37811,
198,
41972,
319,
26223,
2556,
2608,
1478,
25,
1129,
25,
2598,
2177,
198,
198,
31,
9800,
25,
7273,
23063,
440,
14969,
377,
461,
532,
33084,
13,
785,
14,
315,
23063,
8590,
15065,
461,
198,
37811,
198,
11748,
28686,
198,
11748,
29... | 2.277802 | 2,293 |
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | [
2,
15069,
12131,
3012,
11419,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
733... | 1.672961 | 5,984 |
"""
A Python module containing various utility functions, classes, decorators or
whatever.
"""
from collections import namedtuple, Iterable
import sys
import functools
import inspect
from bs4 import BeautifulSoup
import logging
import time
import random
import os
import errno
# Constants
# =========
USER_AGENTS = [... | [
37811,
198,
32,
11361,
8265,
7268,
2972,
10361,
5499,
11,
6097,
11,
11705,
2024,
393,
198,
39664,
13,
198,
37811,
198,
198,
6738,
17268,
1330,
3706,
83,
29291,
11,
40806,
540,
198,
11748,
25064,
198,
11748,
1257,
310,
10141,
198,
11748,... | 2.517676 | 2,857 |
import argparse
import subprocess
import random
import os
import tensorflow as tf
import sys
#os.environ["CUDA_VISIBLE_DEVICES"]="0,1,2,3,4,5,6,7"
from tensorflow.python.client import device_lib
if __name__ == '__main__':
main()
| [
11748,
1822,
29572,
198,
11748,
850,
14681,
198,
11748,
4738,
198,
11748,
28686,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
25064,
198,
2,
418,
13,
268,
2268,
14692,
43633,
5631,
62,
29817,
34563,
62,
39345,
34444,
8973,
2625,... | 2.651685 | 89 |
from typing import Any
import numpy as np
| [
6738,
19720,
1330,
4377,
198,
198,
11748,
299,
32152,
355,
45941,
628
] | 3.666667 | 12 |
import requests
from bs4 import BeautifulSoup
headers = {
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Methods': 'GET',
'Access-Control-Allow-Headers': 'Content-Type',
'Access-Control-Max-Age': '3600',
'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:52.0) Gecko/20100101 Fire... | [
11748,
7007,
198,
6738,
275,
82,
19,
1330,
23762,
50,
10486,
628,
198,
50145,
796,
1391,
198,
220,
220,
220,
705,
15457,
12,
15988,
12,
35265,
12,
39688,
10354,
705,
9,
3256,
198,
220,
220,
220,
705,
15457,
12,
15988,
12,
35265,
12,... | 2.5 | 192 |
"""
Modified example from:
https://github.com/pytorch/examples
"""
from __future__ import print_function
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
from torch.optim.lr_scheduler import StepLR
| [
37811,
198,
5841,
1431,
1672,
422,
25,
198,
5450,
1378,
12567,
13,
785,
14,
9078,
13165,
354,
14,
1069,
12629,
198,
37811,
198,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
14601,
198,
198,
11748,
28034,
198,
1... | 3.516854 | 89 |
from utils.primes import is_prime
# By listing the first six prime numbers: 2, 3, 5, 7, 11, and 13, we can see that the 6th prime is 13.
#
# What is the 10 001st prime number?
#
# Answer: 104743
| [
6738,
3384,
4487,
13,
1050,
999,
1330,
318,
62,
35505,
628,
198,
2,
2750,
13487,
262,
717,
2237,
6994,
3146,
25,
362,
11,
513,
11,
642,
11,
767,
11,
1367,
11,
290,
1511,
11,
356,
460,
766,
326,
262,
718,
400,
6994,
318,
1511,
13... | 2.855072 | 69 |
# -*- coding:utf-8 -*-
__author__ = 'Leo.Z'
'''
image_name.jpg x y x2 y2 c x y x2 y2 c xy为左上角坐标，x2y2为右下角坐标
'''
import os
import os.path
import random
import numpy as np
import torch
import torch.utils.data as data
import torchvision.transforms as transforms
import cv2
| [
2,
532,
9,
12,
19617,
25,
40477,
12,
23,
532,
9,
12,
198,
834,
9800,
834,
796,
705,
3123,
78,
13,
57,
6,
198,
198,
7061,
6,
198,
9060,
62,
3672,
13,
9479,
2124,
331,
2124,
17,
331,
17,
269,
2124,
331,
2124,
17,
331,
17,
269,... | 2.044444 | 135 |
__version__ = '0.0.dev5'
| [
834,
9641,
834,
796,
705,
15,
13,
15,
13,
7959,
20,
6,
198
] | 1.923077 | 13 |
# from config import conf
#import telegram
#
# tg_token=conf['telegram_token']
# bot = telegram.Bot(token=tg_token)
# print(tg_token)
#
# #proxy list: https://50na50.net/ru/proxy/socks5list
#
# proxy_url='socks5://66.33.210.203:24475'
#
# pp = telegram.utils.request.Request(proxy_url=proxy_url)
# bot = telegram.Bot(to... | [
198,
2,
422,
4566,
1330,
1013,
198,
2,
11748,
573,
30536,
198,
2,
198,
2,
256,
70,
62,
30001,
28,
10414,
17816,
660,
30536,
62,
30001,
20520,
198,
2,
10214,
796,
573,
30536,
13,
20630,
7,
30001,
28,
25297,
62,
30001,
8,
198,
2,
... | 2.466667 | 675 |
# -*- coding: utf-8 -*-
"""
Microsoft-Windows-Forwarding
GUID : 699e309c-e782-4400-98c8-e21d162d7b7b
"""
from construct import Int8sl, Int8ul, Int16ul, Int16sl, Int32sl, Int32ul, Int64sl, Int64ul, Bytes, Double, Float32l, Struct
from etl.utils import WString, CString, SystemTime, Guid
from etl.dtyp import Sid
from etl.... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
15905,
12,
11209,
12,
39746,
278,
198,
38,
27586,
1058,
718,
2079,
68,
26895,
66,
12,
68,
46519,
12,
2598,
405,
12,
4089,
66,
23,
12,
68,
2481,
67,
25061... | 2.015817 | 569 |
import numpy as np
from tqdm.auto import tqdm
COLS_GROUP1 = 24
COLS_GROUP2 = 47
COLS_GROUP3 = 24*13
COLS_GROUP4 = 55
COLS_TOTAL = COLS_GROUP1 + COLS_GROUP2 + COLS_GROUP3 + COLS_GROUP4
same_color_suit = {'C':'S', 'D':'H', 'H':'D', 'S':'C'}
COLS_TARGET = 24
def format_data(data, usetqdm=True, start=0, stop=None, count=N... | [
11748,
299,
32152,
355,
45941,
198,
6738,
256,
80,
36020,
13,
23736,
1330,
256,
80,
36020,
198,
198,
25154,
50,
62,
46846,
16,
796,
1987,
198,
25154,
50,
62,
46846,
17,
796,
6298,
198,
25154,
50,
62,
46846,
18,
796,
1987,
9,
1485,
... | 2.237612 | 5,025 |
"""Vectordump configuration information.
"""
#: MONGO URI
MONGO_URI = 'mongodb://localhost:27017/'
| [
37811,
53,
478,
585,
931,
8398,
1321,
13,
198,
37811,
198,
198,
2,
25,
25000,
11230,
43975,
198,
27857,
11230,
62,
47269,
796,
705,
31059,
375,
65,
1378,
36750,
25,
1983,
29326,
14,
6,
198
] | 2.857143 | 35 |
import math
#TODO: WRITEME sciNum | [
11748,
10688,
198,
198,
2,
51,
3727,
46,
25,
11342,
2043,
3620,
36,
20681,
33111
] | 2.266667 | 15 |
import os
from special_math.common_utilities import SpecialMathCalc, RequestUtils
from special_math import MAX_SPECIAL_NUMBER_ENTRY
import logging
from flask import Blueprint
bp = Blueprint('specialmath', __name__, url_prefix='/specialmath')
logger = logging.getLogger(__name__)
logger.setLevel(os.getenv("LOG_LEVEL",... | [
11748,
28686,
198,
6738,
2041,
62,
11018,
13,
11321,
62,
315,
2410,
1330,
6093,
37372,
9771,
66,
11,
19390,
18274,
4487,
198,
6738,
2041,
62,
11018,
1330,
25882,
62,
48451,
12576,
62,
41359,
13246,
62,
3525,
18276,
198,
11748,
18931,
19... | 2.207831 | 996 |
import Qt as Qt
import Qt.QtGui as QtGui
import Qt.QtCore as QtCore
from qtLearn.nodes import Node
import qtLearn.uiUtils as uiUtils
############################################################################
############################################################################ | [
11748,
33734,
355,
33734,
198,
11748,
33734,
13,
48,
83,
8205,
72,
355,
33734,
8205,
72,
198,
11748,
33734,
13,
48,
83,
14055,
355,
33734,
14055,
198,
198,
6738,
10662,
83,
20238,
13,
77,
4147,
1330,
19081,
198,
11748,
10662,
83,
2023... | 4.271429 | 70 |
# Полуавтоматические тесты
#
# list_temp = [1,2,3,'abc']
#
# print(test_function(list_temp))
# теперь пишем полуавтоматическую фун-ю
function_test()
list_temp = [1, 2, 3,'5', 'abc', 4]
list_out = test_function(list_temp)
print(list_out)
| [
2,
12466,
253,
25443,
119,
35072,
16142,
38857,
20375,
25443,
120,
16142,
20375,
18849,
141,
229,
16843,
21727,
31583,
18849,
16843,
220,
20375,
16843,
21727,
20375,
45035,
198,
2,
198,
2,
1351,
62,
29510,
796,
685,
16,
11,
17,
11,
18,
... | 1.596026 | 151 |
# -*- coding: utf-8 -*-
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198
] | 1.714286 | 14 |
import certifi
import ftplib
import hatanaka
import os
import urllib.request
import pycurl
import time
import tempfile
from datetime import datetime
from urllib.parse import urlparse
from io import BytesIO
from .constants import SECS_IN_HR, SECS_IN_DAY, SECS_IN_WEEK
from .gps_time import GPSTime
dir_path = os.path.d... | [
11748,
5051,
22238,
198,
11748,
10117,
489,
571,
198,
11748,
6877,
272,
8130,
198,
11748,
28686,
198,
11748,
2956,
297,
571,
13,
25927,
198,
11748,
12972,
66,
6371,
198,
11748,
640,
198,
11748,
20218,
7753,
198,
198,
6738,
4818,
8079,
1... | 2.744373 | 622 |
import urllib2
import json
import MySQLdb
conn = MySQLdb.connect(host= "localhost", user="root", passwd="", db="hackerone_reports")
x = conn.cursor()
hackerone = "https://hackerone.com/programs/search?query=bounties%3Ayes&sort=name%3Aascending&limit=1000"
opener = urllib2.build_opener()
opener.addheaders = [('Accept... | [
198,
11748,
2956,
297,
571,
17,
198,
11748,
33918,
198,
11748,
33476,
9945,
198,
198,
37043,
796,
33476,
9945,
13,
8443,
7,
4774,
28,
366,
36750,
1600,
2836,
2625,
15763,
1600,
1208,
16993,
2625,
1600,
20613,
2625,
71,
10735,
505,
62,
... | 2.849445 | 631 |
import logging
import re
from pathlib import Path
from subprocess import check_output, CalledProcessError, STDOUT
from typing import Any, Dict, List, Optional, Tuple, Union
from .common import convert_external_variables
_RULE_BLOCK_REGEX = re.compile(r'^(?P<rule>\w+)\s+\[(?P<raw_meta>.*)\]\s+(?P<scanned_file>.*)\n(?... | [
11748,
18931,
198,
11748,
302,
198,
6738,
3108,
8019,
1330,
10644,
198,
6738,
850,
14681,
1330,
2198,
62,
22915,
11,
34099,
18709,
12331,
11,
48571,
12425,
198,
6738,
19720,
1330,
4377,
11,
360,
713,
11,
7343,
11,
32233,
11,
309,
29291,... | 2.467161 | 944 |
# BOJ 2448
| [
2,
16494,
41,
1987,
2780,
198
] | 1.833333 | 6 |
"""
A script for finding equal or near-equal partitions in a group.
Do parts a, b, and g
"""
from itertools import combinations
import random
import numpy as np
from matplotlib import pyplot as plt
from pathlib import Path
from progressbar import progressbar as pbar
DIR = Path(__file__).parent
group1 = [10, 13, 23, 6... | [
37811,
198,
32,
4226,
329,
4917,
4961,
393,
1474,
12,
40496,
43869,
287,
257,
1448,
13,
198,
5211,
3354,
257,
11,
275,
11,
290,
308,
198,
37811,
198,
6738,
340,
861,
10141,
1330,
17790,
198,
11748,
4738,
198,
11748,
299,
32152,
355,
... | 2.681373 | 204 |
from matplotlib import pyplot as plt
import io
from PIL import Image
import cv2
import torch
import os
WIDTH = 1280
HEIGHT = 760
model = torch.hub.load("ultralytics/yolov5", "custom", path="./best.pt")
# results_pandas structure
# xmin ymin xmax ymax confidence class name
cap = cv2.VideoCapture("./driving_v... | [
6738,
2603,
29487,
8019,
1330,
12972,
29487,
355,
458,
83,
198,
11748,
33245,
198,
6738,
350,
4146,
1330,
7412,
198,
11748,
269,
85,
17,
198,
11748,
28034,
198,
11748,
28686,
628,
198,
54,
2389,
4221,
796,
37674,
198,
13909,
9947,
796,
... | 2.09589 | 511 |
import runs
import optimization as opt
| [
11748,
4539,
198,
11748,
23989,
355,
2172,
628
] | 5 | 8 |