content stringlengths 1 1.04M | input_ids listlengths 1 774k | ratio_char_token float64 0.38 22.9 | token_count int64 1 774k |
|---|---|---|---|
import os
import vtkAll as vtk
import math
import time
import numpy as np
from ddapp import callbacks
from ddapp import transformUtils
from ddapp import lcmUtils
from ddapp import objectmodel as om
from ddapp.utime import getUtime
from ddapp import robotstate
import drc as lcmdrc
| [
11748,
28686,
198,
11748,
410,
30488,
3237,
355,
410,
30488,
198,
11748,
10688,
198,
11748,
640,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
49427,
1324,
1330,
869,
10146,
198,
6738,
49427,
1324,
1330,
6121,
18274,
4487,
198,
6738... | 3.337209 | 86 |
import SocketServer
from SimpleTCPDispatcher import SimpleTCPDispatcher
from SimpleTCPRequestHandler import SimpleTCPRequestHandler
__author__ = 'umairghani'
class SimpleTCPServer(SocketServer.TCPServer, SimpleTCPDispatcher):
"""
Simple TCP Server
"""
allow_reuse_address = True
def __init__(se... | [
11748,
47068,
10697,
198,
198,
6738,
17427,
4825,
5760,
271,
8071,
2044,
1330,
17427,
4825,
5760,
271,
8071,
2044,
198,
6738,
17427,
4825,
47,
18453,
25060,
1330,
17427,
4825,
47,
18453,
25060,
198,
198,
834,
9800,
834,
796,
705,
388,
9... | 2.578767 | 292 |
import re
import json
import collections
import traceback
from pathlib import Path
import unicodedata as ucd
from tf.client.make.build import makeSearchClients
from .nena_parser import NenaLexerParser
from .build_tf import NenaTfBuilder
from .build_docs import DocsBuilder
| [
11748,
302,
198,
11748,
33918,
198,
11748,
17268,
198,
11748,
12854,
1891,
198,
6738,
3108,
8019,
1330,
10644,
198,
11748,
28000,
9043,
1045,
355,
334,
10210,
198,
6738,
48700,
13,
16366,
13,
15883,
13,
11249,
1330,
787,
18243,
2601,
2334... | 3.592105 | 76 |
import tensorflow as tf
import numpy as np
x_inp = tf.placeholder(tf.float32, [5, 5])
w_inp = tf.placeholder(tf.float32, [3, 3])
x = tf.reshape(x_inp, [1, 5, 5, 1])
w = tf.reshape(w_inp, [3, 3, 1, 1])
x_valid = tf.nn.conv2d(x, w, strides=[1, 1, 1, 1], padding='VALID')
x_same = tf.nn.conv2d(x, w, strides=[1, 1, 1, 1... | [
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32152,
355,
45941,
628,
198,
87,
62,
259,
79,
796,
48700,
13,
5372,
13829,
7,
27110,
13,
22468,
2624,
11,
685,
20,
11,
642,
12962,
198,
86,
62,
259,
79,
796,
48700,
13,
5372,
... | 1.819536 | 604 |
# Copyright (c) 2021, NVIDIA CORPORATION. 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 appli... | [
2,
15069,
357,
66,
8,
33448,
11,
15127,
23929,
44680,
6234,
13,
220,
1439,
2489,
10395,
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... | 2.232713 | 752 |
from aioftx.session import FTXClientSession
from .schemas import (
AcceptQuoteRequest,
AcceptQuoteResponse,
CancelQuoteRequest,
CancelQuoteResponse,
CreateQuoteRequest,
CreateQuoteResponse,
GetMyQuotesReponse,
GetMyQuotesRequest,
GetQuotesRequest,
GetQuotesResponse,
Quote,
)... | [
6738,
257,
952,
701,
87,
13,
29891,
1330,
19446,
55,
11792,
36044,
198,
198,
6738,
764,
1416,
4411,
292,
1330,
357,
198,
220,
220,
220,
21699,
25178,
18453,
11,
198,
220,
220,
220,
21699,
25178,
31077,
11,
198,
220,
220,
220,
27910,
... | 2.638854 | 803 |
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: hapi/rudder/rudder.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflectio... | [
2,
2980,
515,
416,
262,
8435,
11876,
17050,
13,
220,
8410,
5626,
48483,
0,
198,
2,
2723,
25,
387,
14415,
14,
81,
41686,
14,
81,
41686,
13,
1676,
1462,
198,
198,
11748,
25064,
198,
62,
65,
28,
17597,
13,
9641,
62,
10951,
58,
15,
... | 2.643583 | 13,776 |
from twisted.spread import pb
from twisted.internet import reactor
from twisted.python import util
factory = pb.PBClientFactory()
reactor.connectTCP("localhost", 8789, factory)
d = factory.getRootObject()
a = []
d.addCallback(lambda object: object.callRemote("nextQuote"))
d.addCallback(lambda echo: a.append(echo))
d.a... | [
6738,
19074,
13,
43639,
1330,
279,
65,
198,
6738,
19074,
13,
37675,
1330,
21905,
198,
6738,
19074,
13,
29412,
1330,
7736,
198,
198,
69,
9548,
796,
279,
65,
13,
49079,
11792,
22810,
3419,
198,
260,
11218,
13,
8443,
4825,
47,
7203,
3675... | 3.167939 | 131 |
from subprocess import check_output
| [
6738,
850,
14681,
1330,
2198,
62,
22915,
628,
198
] | 4.222222 | 9 |
# -*- coding: utf-8 -*-
###################################################################
# Object detection - YOLOv5_6.0 - OpenCV dnn
# From : https://github.com/samsu2018/yolov5_6.0_opencvdnn_python
# Modify : Sam Su (1, 11, 2022)
##################################################################
import cv2
import ... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
29113,
29113,
21017,
198,
2,
9515,
13326,
532,
575,
3535,
46,
85,
20,
62,
21,
13,
15,
532,
4946,
33538,
288,
20471,
198,
2,
3574,
1058,
3740,
1378,
12567,
13,
785,
1... | 3.163142 | 331 |
import os
import random
from PIL import Image
from argparse import ArgumentParser
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision.transforms as transforms
import torchvision.utils as vutils
from model.networks import Generator
from utils.tools import get_config, is_image_fil... | [
11748,
28686,
198,
11748,
4738,
198,
6738,
350,
4146,
1330,
7412,
198,
6738,
1822,
29572,
1330,
45751,
46677,
198,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
1891,
2412,
13,
66,
463,
20471,
355... | 3.065672 | 335 |
from cassandra.cluster import Cluster
"""
Function to create a connection object
"""
| [
6738,
30606,
15918,
13,
565,
5819,
1330,
38279,
198,
198,
37811,
198,
220,
15553,
284,
2251,
257,
4637,
2134,
198,
37811,
628
] | 4.045455 | 22 |
""" This is a script to generate prime numbers from a range of numbers.
Or by checking to see if the input number is prime.
"""
#Calculate the prime numbers between two numbers
#Allow the user to enter in a range of numbers
#Secondly be able to have the user enter a number to check to see if it is prime
#thirdly have ... | [
37811,
770,
318,
257,
4226,
284,
7716,
6994,
3146,
422,
257,
2837,
286,
3146,
13,
198,
5574,
416,
10627,
284,
766,
611,
262,
5128,
1271,
318,
6994,
13,
198,
37811,
198,
198,
2,
9771,
3129,
378,
262,
6994,
3146,
1022,
734,
3146,
198,... | 3.462069 | 290 |
h, m = map(int, input().split(':'))
t = h*60+m
for i in range(120):
if (t >= 7*60 and t < 10*60) or (t >= 15*60 and t < 19*60):
t += 2
else:
t += 1
h = t//60%24
m = t%60
# print(f'{h:02d}:{m:02d}')
print('%02d:%02d' % (h, m)) | [
71,
11,
285,
796,
3975,
7,
600,
11,
5128,
22446,
35312,
7,
10354,
6,
4008,
201,
198,
83,
796,
289,
9,
1899,
10,
76,
201,
198,
1640,
1312,
287,
2837,
7,
10232,
2599,
201,
198,
197,
361,
357,
83,
18189,
767,
9,
1899,
290,
256,
1... | 1.737589 | 141 |
#!/usr/bin/env python
# This code is part of qiskit-runtime.
#
# (C) Copyright IBM 2021.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
201,
198,
201,
198,
2,
770,
2438,
318,
636,
286,
10662,
1984,
270,
12,
43282,
13,
201,
198,
2,
201,
198,
2,
357,
34,
8,
15069,
19764,
33448,
13,
201,
198,
2,
201,
198,
2,
770,
2438,
... | 3.084058 | 345 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# This file is part of the Wapiti project (http://wapiti.sourceforge.net)
# Copyright (C) 2008-2018 Nicolas Surribas
#
# 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 S... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
770,
2393,
318,
636,
286,
262,
370,
499,
8846,
1628,
357,
4023,
1378,
86,
499,
8846,
13,
10459,
30293,
13,
3... | 2.41154 | 2,097 |
from learn import *
from server import *
| [
6738,
2193,
1330,
1635,
201,
198,
6738,
4382,
1330,
1635,
201,
198,
220,
220,
220,
220,
201,
198
] | 2.722222 | 18 |
from django import forms
| [
198,
6738,
42625,
14208,
1330,
5107,
628,
628
] | 3.625 | 8 |
#!/usr/bin/python3
import cv2
import datetime
import sys
import gflags
import glog
FLAGS = gflags.FLAGS
if __name__ == '__main__':
argv = FLAGS(sys.argv)
sys.exit(main(argv))
| [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
198,
198,
11748,
269,
85,
17,
198,
11748,
4818,
8079,
198,
11748,
25064,
198,
198,
11748,
308,
33152,
198,
11748,
1278,
519,
198,
198,
38948,
50,
796,
308,
33152,
13,
38948,
50,
628,
198,
19... | 2.277108 | 83 |
from django.shortcuts import render
from django.contrib.auth.models import User
from django.http import HttpResponse
from .models import RestaurantReview, Restaurant
from random import randint
# Create your views here.
| [
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
27530,
1330,
11787,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
198,
6738,
764,
27530,
1330,
26078,
14832,
11,
... | 3.894737 | 57 |
# coding=utf-8
from typing import Union
| [
2,
19617,
28,
40477,
12,
23,
198,
198,
6738,
19720,
1330,
4479,
628
] | 3.230769 | 13 |
from __future__ import absolute_import
from .core import (ZmqSubscriber, ZmqPublisher)
from .core import load_config | [
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
198,
6738,
764,
7295,
1330,
357,
57,
76,
80,
7004,
1416,
24735,
11,
1168,
76,
80,
46471,
8,
198,
6738,
764,
7295,
1330,
3440,
62,
11250
] | 3.342857 | 35 |
import subprocess
import textwrap
import pytest
import signal
import socket
import time
import os
PORT = 9000
HOST = 'localhost'
KEY = "testtesttest"
@pytest.fixture(scope="session")
#def test_ancillary_on_s3(minio, tmp_path):
# f = tmp_path / "test.yaml"
# g = tmp_path / "clip.geojson"
# f.write_text(textw... | [
11748,
850,
14681,
198,
11748,
2420,
37150,
198,
11748,
12972,
9288,
198,
11748,
6737,
198,
11748,
17802,
198,
11748,
640,
198,
11748,
28686,
198,
198,
15490,
796,
50138,
198,
39,
10892,
796,
705,
36750,
6,
198,
20373,
796,
366,
9288,
9... | 2.088685 | 327 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
pretrained_model_path = 'pretrained/resnet_gray_weights.pth.tar'
| [
11748,
28034,
201,
198,
11748,
28034,
13,
20471,
355,
299,
77,
201,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
201,
198,
11748,
28034,
10178,
13,
27530,
355,
4981,
201,
198,
201,
198,
5310,
13363,
62,
19849,
62,
6978,
796,
705... | 2.731343 | 67 |
"""Ellipsoid suspended in shear flow (2 hours).
An example to illustrate 3d pysph rigid_body framework
"""
from __future__ import print_function
import numpy as np
from scipy.integrate import odeint
from pysph.base.nnps import DomainManager
from pysph.base.utils import (get_particle_array_wcsph,
... | [
37811,
30639,
541,
568,
312,
9951,
287,
673,
283,
5202,
357,
17,
2250,
737,
198,
198,
2025,
1672,
284,
19418,
513,
67,
279,
893,
746,
20831,
62,
2618,
9355,
198,
37811,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
11748,
... | 1.794752 | 5,793 |
#tuning Parameter
import numpy as np
import glob
import os
import pandas as pd
import scipy
import matplotlib.pyplot as plt
from sklearn import datasets, linear_model
from scipy.stats import norm
from sklearn.neighbors import KernelDensity
from scipy.stats import poisson
import math
from itertools import permutations
i... | [
2,
28286,
278,
25139,
2357,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
15095,
198,
11748,
28686,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
629,
541,
88,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
6... | 1.689625 | 2,265 |
import json
import os
| [
11748,
33918,
198,
11748,
28686,
198
] | 3.666667 | 6 |
# -*- coding: UTF-8 -*-
# Code generated by lark suite oapi sdk gen
from typing import *
from ....api import Request as APIRequest, Response as APIResponse, set_timeout, set_tenant_key, set_user_access_token, set_path_params, \
set_query_params, set_response_stream, set_is_response_stream, FormData, FormDataFile
... | [
2,
532,
9,
12,
19617,
25,
41002,
12,
23,
532,
9,
12,
198,
2,
6127,
7560,
416,
300,
668,
18389,
267,
15042,
264,
34388,
2429,
198,
198,
6738,
19720,
1330,
1635,
198,
198,
6738,
19424,
15042,
1330,
19390,
355,
7824,
18453,
11,
18261,
... | 2.837079 | 178 |
# import the necessary packages
from imutils import paths
import argparse
import cv2
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--images", required=True,
help="path to input directory of images")
ap.add_argument("-t", "--threshold", type=float, defau... | [
2,
1330,
262,
3306,
10392,
198,
6738,
545,
26791,
1330,
13532,
198,
11748,
1822,
29572,
198,
11748,
269,
85,
17,
628,
198,
198,
2,
5678,
262,
4578,
21136,
290,
21136,
262,
7159,
198,
499,
796,
1822,
29572,
13,
28100,
1713,
46677,
3419... | 2.847328 | 393 |
import tfchain.tests.encoding.rivbin as testrivbin
import tfchain.tests.encoding.siabin as testsiabin
| [
11748,
48700,
7983,
13,
41989,
13,
12685,
7656,
13,
15104,
8800,
355,
1332,
15104,
8800,
198,
11748,
48700,
7983,
13,
41989,
13,
12685,
7656,
13,
13396,
6014,
355,
5254,
72,
6014,
198
] | 3.1875 | 32 |
import numpy as np
| [
11748,
299,
32152,
355,
45941,
198
] | 3.166667 | 6 |
""""writer module handle writing the images to disk"""
import webdataset as wds
import json
import pandas as pd
import pyarrow.parquet as pq
import pyarrow as pa
import fsspec
class BufferedParquetWriter:
"""Write samples to parquet files incrementally with a buffer"""
def flush(self, force=False):
... | [
15931,
15931,
16002,
8265,
5412,
3597,
262,
4263,
284,
11898,
37811,
198,
198,
11748,
3992,
19608,
292,
316,
355,
266,
9310,
198,
11748,
33918,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
12972,
6018,
13,
1845,
21108,
355,
279,
80... | 2.233134 | 1,171 |
import unittest
import mock
from mopidy_gmusic import (
GMusicExtension, backend as backend_lib, scrobbler_frontend)
| [
11748,
555,
715,
395,
198,
198,
11748,
15290,
198,
198,
6738,
285,
404,
19325,
62,
70,
28965,
1330,
357,
198,
220,
220,
220,
6951,
385,
291,
11627,
3004,
11,
30203,
355,
30203,
62,
8019,
11,
629,
305,
11848,
1754,
62,
8534,
437,
8,
... | 2.818182 | 44 |
from PyQt6 import QtCore, QtWidgets
import sys
# ф-ция с основными настройками окна
if __name__ == "__main__":
app = QtWidgets.QApplication(sys.argv)
InfoWindow = QtWidgets.QMainWindow()
ui = UiInfoWindow()
ui.setup_ui(InfoWindow)
InfoWindow.show()
sys.exit(app.exec())
| [
6738,
9485,
48,
83,
21,
1330,
33734,
14055,
11,
33734,
54,
312,
11407,
201,
198,
11748,
25064,
201,
198,
201,
198,
201,
198,
220,
220,
220,
1303,
220,
141,
226,
12,
141,
228,
18849,
40623,
220,
21727,
12466,
122,
21727,
22177,
25443,
... | 1.83908 | 174 |
# -*- coding: utf-8 -*-
# spearmint
#
# Academic and Non-Commercial Research Use Software License and Terms
# of Use
#
# Spearmint is a software package to perform Bayesian optimization
# according to specific algorithms (the “Software”). The Software is
# designed to automatically run experiments (thus the code name
... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
693,
1670,
600,
198,
2,
198,
2,
31421,
290,
8504,
12,
48401,
4992,
5765,
10442,
13789,
290,
17637,
198,
2,
286,
5765,
198,
2,
198,
2,
2531,
1670,
600,
318,
257,
... | 3.162663 | 4,537 |
import os
import networkx as nx
import pandas as pd
import numpy as np
from stellargraph.mapper import (
CorruptedGenerator,
FullBatchNodeGenerator,
)
from stellargraph import StellarGraph
from stellargraph.layer import GCN, DeepGraphInfomax
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.cal... | [
11748,
28686,
198,
11748,
3127,
87,
355,
299,
87,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
336,
695,
853,
1470,
13,
76,
11463,
1330,
357,
198,
220,
220,
220,
2744,
31590,
8645,
1352,
11,
1... | 2.605648 | 1,983 |
# Ignore pictures where the tagged concept has a probability below the threshold
THRESHOLD = 0.9
# Number of pictures to index
MAX_MEDIA = 1000
# Clarifai API details - http://www.clarifai.com/api
CLARIFAI_APP_ID = 'xxx'
CLARIFAI_APP_SECRET = 'xxx'
# Algolia API details = http://www.clarifai.com/api
ALGOLIA_APP_ID = ... | [
2,
41032,
5986,
810,
262,
30509,
3721,
468,
257,
12867,
2174,
262,
11387,
198,
4221,
19535,
39,
15173,
796,
657,
13,
24,
198,
2,
7913,
286,
5986,
284,
6376,
198,
22921,
62,
30733,
3539,
796,
8576,
198,
198,
2,
15420,
361,
1872,
7824... | 2.573684 | 190 |
import numpy as np
| [
11748,
299,
32152,
355,
45941,
628,
198
] | 3 | 7 |
# DESAFIO 067
# Faça um programa que mostre a tabuada de vários números, um de cada vez, para cada valor digitado
# pelo usuário. O programa será interrompido quando o número solicitado for negativo.
while True:
num = int(input('Digite um número para ver sua tabuada: '))
print('-' * 30)
if num < 0:
... | [
2,
22196,
8579,
9399,
657,
3134,
198,
2,
18350,
50041,
23781,
1430,
64,
8358,
749,
260,
257,
7400,
84,
4763,
390,
410,
6557,
380,
418,
299,
21356,
647,
418,
11,
23781,
390,
269,
4763,
1569,
89,
11,
31215,
269,
4763,
1188,
273,
16839... | 2.212264 | 212 |
from __future__ import division #brings in Python 3.0 mixed type calculations
import numpy as np
import os
import pandas as pd
import sys
#find parent directory and import model
parentddir = os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir))
sys.path.append(parentddir)
from base.uber_model impo... | [
6738,
11593,
37443,
834,
1330,
7297,
220,
1303,
1671,
654,
287,
11361,
513,
13,
15,
7668,
2099,
16765,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28686,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
25064,
198,
198,
2,
19796,
... | 1.918086 | 18,080 |
# Generated by Django 3.1.5 on 2021-02-16 20:41
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
20,
319,
33448,
12,
2999,
12,
1433,
1160,
25,
3901,
198,
198,
6738,
42625,
14208,
13,
10414,
1330,
6460,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
198,
11748,
42625,
14... | 3.04918 | 61 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
# Custom
from src.normalisation import channel, instance
if __name__ == "__main__":
C = 8
y = torch.randn([3,C,16,16])
y_dims = y.size()
G = Generator(y_dims[1:], y_dims[0], C=C, n_residual_blocks=3, sample_noise=... | [
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
198,
11748,
299,
32152,
355,
45941,
198,
198,
2,
8562,
198,
6738,
12351,
13,
11265,
5612,
1330,
6518,
11,
4554,
628,
198,
198... | 2.308176 | 159 |
import pandas as pd
from django.http import response
from django.shortcuts import render,HttpResponse
from .models import Person,report,management,Person_without_Aadhar
import datetime
from django.utils.timezone import utc
from rest_framework import serializers, status,viewsets
from rest_framework.views import APIView
... | [
11748,
19798,
292,
355,
279,
67,
198,
6738,
42625,
14208,
13,
4023,
1330,
2882,
198,
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
11,
43481,
31077,
198,
6738,
764,
27530,
1330,
7755,
11,
13116,
11,
27604,
11,
15439,
62,
19419,
62,
... | 3.765 | 200 |
from exceptions.exceptions import ArgumentInvalid, ObjectsNotExist
from typing import Generator, Optional
from sqlalchemy import and_
from configures.const import POST_MINIMUM_WORDS
from handlers import BaseHandler
from models.database_models import Comment
from models.database_models.post_model import Post
from mode... | [
6738,
13269,
13,
1069,
11755,
1330,
45751,
44651,
11,
35832,
3673,
3109,
396,
198,
6738,
19720,
1330,
35986,
11,
32233,
198,
198,
6738,
44161,
282,
26599,
1330,
290,
62,
198,
198,
6738,
4566,
942,
13,
9979,
1330,
24582,
62,
23678,
3955,... | 4.173913 | 115 |
#!/usr/bin/env python
"""
Cubic spline peak finder.
Hazen 03/16
"""
import pickle
import numpy
import tifffile
import storm_analysis.sa_library.analysis_io as analysisIO
import storm_analysis.sa_library.fitting as fitting
import storm_analysis.sa_library.ia_utilities_c as utilC
import storm_analysis.sa_library.matc... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
37811,
198,
43632,
291,
4328,
500,
9103,
1064,
263,
13,
198,
198,
39,
1031,
268,
7643,
14,
1433,
198,
37811,
198,
198,
11748,
2298,
293,
198,
11748,
299,
32152,
198,
198,
11748,
256,
... | 2.272038 | 1,055 |
import pandas as pd
url = "https://en.wikipedia.org/wiki/Road_safety_in_Europe"
target_table_name = "European Union Road Safety Facts and Figures"
# Fetch all tables on webpage that match
# provided table name and return as list
df = pd.read_html(url, match=target_table_name)
# Grab the first table
df = df[0] if le... | [
11748,
19798,
292,
355,
279,
67,
198,
198,
6371,
796,
366,
5450,
1378,
268,
13,
31266,
13,
2398,
14,
15466,
14,
29197,
62,
44708,
62,
259,
62,
16112,
1,
198,
16793,
62,
11487,
62,
3672,
796,
366,
22030,
4479,
5567,
11233,
26972,
290... | 2.554593 | 577 |
import csv
data = loaddata()
for k,v in data.iteritems():
print len(k), k + ":" + v
#return 0 if not a place
#return 1 if it's region
#return 2 if it's a province
#return 3 if it's a munincipality
| [
11748,
269,
21370,
198,
198,
7890,
796,
3440,
7890,
3419,
198,
1640,
479,
11,
85,
287,
1366,
13,
2676,
23814,
33529,
198,
220,
220,
220,
3601,
18896,
7,
74,
828,
479,
1343,
366,
11097,
1343,
410,
220,
198,
220,
220,
220,
1303,
7783,... | 2.494505 | 91 |
"""Test suite for the bootstrap_elasticsearch view of richie's search app."""
import json
from unittest import mock
from django.contrib.messages import get_messages
from cms.test_utils.testcases import CMSTestCase
from richie.apps.core.factories import UserFactory
class BootstrapElasticsearchViewTestCase(CMSTestCa... | [
37811,
14402,
18389,
329,
262,
6297,
26418,
62,
417,
3477,
12947,
1570,
286,
5527,
494,
338,
2989,
598,
526,
15931,
198,
11748,
33918,
198,
6738,
555,
715,
395,
1330,
15290,
198,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
37348,
1095,
... | 2.621279 | 1,579 |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import time
from django.db import models
from django.utils.translation import ugettext_lazy as _
from app.core.models import Domain, Mailbox
EXT_LIST_TYPE = (
('general', _(u'普通邮件列表')),
('dept', _(u'部门邮件列表')),
('sys', _(u'系统邮件列表'))
)
EXT_LIST_... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
11748,
640,
198,
6738,
42625,
14208,
13,
9945,
1330,
4981,
198,
6738,
42625,
14208,
13,
26791,
13,
41519,
... | 1.79682 | 566 |
#!/usr/bin/env python3
'''
@description : Given a gnomAD VCF, shortlist SNPs for a capture-based panel to detect allelic imbalance
@created : 09/16/2020
@author : Cyriac Kandoth
'''
from __future__ import division, print_function
import os, sys, argparse, time, pysam
if __name__ == "__main__":
start_time = time.t... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
7061,
6,
198,
31,
11213,
1058,
11259,
257,
19967,
296,
2885,
569,
22495,
11,
1790,
4868,
11346,
12016,
329,
257,
8006,
12,
3106,
6103,
284,
4886,
28654,
677,
32556,
198,
31,
25598,... | 2.703488 | 172 |
import socket
import json
import os
import sys
from threading import Thread
from multiprocessing import Process
from queue import Queue
from logging import Formatter,getLogger,FileHandler
from logging.handlers import TimedRotatingFileHandler,RotatingFileHandler
import logging
import time
from functools import reduce
l... | [
11748,
17802,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
25064,
198,
6738,
4704,
278,
1330,
14122,
198,
6738,
18540,
305,
919,
278,
1330,
10854,
198,
6738,
16834,
1330,
4670,
518,
198,
6738,
18931,
1330,
5178,
1436,
11,
1136,
11187... | 3.296875 | 192 |
from je_editor.utils.file.open.open_file import read_file
def open_last_edit_file(file_from_output_content, code_editor):
"""
:param file_from_output_content: readied file from output content
:param code_editor the editor to insert file content
:return readied file
open last edit file
if succe... | [
6738,
11223,
62,
35352,
13,
26791,
13,
7753,
13,
9654,
13,
9654,
62,
7753,
1330,
1100,
62,
7753,
628,
198,
4299,
1280,
62,
12957,
62,
19312,
62,
7753,
7,
7753,
62,
6738,
62,
22915,
62,
11299,
11,
2438,
62,
35352,
2599,
198,
220,
2... | 2.642553 | 235 |
from __future__ import print_function
import zmq
import time
ADDR='tcp://127.0.0.1:11155'
ctx = zmq.Context()
srv = ctx.socket(zmq.REP)
srv.bind(ADDR)
#srv.setsockopt(zmq.RCVTIMEO, 3000);
while True:
try:
msg = srv.recv()
except Exception as e:
print('zmq socket revc timedout:', e)
else:
print('cl... | [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
11748,
1976,
76,
80,
198,
11748,
640,
198,
198,
2885,
7707,
11639,
83,
13155,
1378,
16799,
13,
15,
13,
15,
13,
16,
25,
1157,
18742,
6,
198,
198,
49464,
796,
1976,
76,
80,
13,
219... | 2.176796 | 181 |
from __future__ import annotations
from typing import Dict, Any, List, TYPE_CHECKING
if TYPE_CHECKING:
from xml.etree.ElementTree import Element
| [
6738,
11593,
37443,
834,
1330,
37647,
198,
198,
6738,
19720,
1330,
360,
713,
11,
4377,
11,
7343,
11,
41876,
62,
50084,
2751,
198,
198,
361,
41876,
62,
50084,
2751,
25,
198,
220,
220,
220,
422,
35555,
13,
316,
631,
13,
20180,
27660,
... | 3.377778 | 45 |
import os
import sys
from pathlib import Path
from tkinter import *
from tkinter import filedialog
from os import listdir
from os.path import isfile, join
from nltk.tokenize.regexp import RegexpTokenizer
from make_story import get_next_words, load_data_from_file
BUTTONS_PER_COL = 8
DATA_PATH = "./data/"
data = None
... | [
11748,
28686,
198,
11748,
25064,
198,
6738,
3108,
8019,
1330,
10644,
198,
6738,
256,
74,
3849,
1330,
1635,
198,
6738,
256,
74,
3849,
1330,
5717,
498,
519,
198,
6738,
28686,
1330,
1351,
15908,
198,
6738,
28686,
13,
6978,
1330,
318,
7753,... | 2.417431 | 654 |
from __future__ import absolute_import
from __future__ import print_function
import os
import sys
import six
from conversion_imagenet import TestModels
if __name__ == '__main__':
test_mxnet()
| [
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
2237,
198,
6738,
11315,
62,
320,
11286,
316,
1330,
6208,
5841,
1424,
628,
198,
19... | 3.295082 | 61 |
# coding=utf-8
#
# created by kpe on 15.Mar.2019 at 12:52
#
from __future__ import absolute_import, division, print_function
import tensorflow as tf
from tensorflow.python import keras
from tensorflow.python.keras import backend as K
from bert.layer import Layer
| [
2,
19617,
28,
40477,
12,
23,
198,
2,
198,
2,
2727,
416,
479,
431,
319,
1315,
13,
7676,
13,
23344,
379,
1105,
25,
4309,
198,
2,
198,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
11,
7297,
11,
3601,
62,
8818,
198,
198,
117... | 3.152941 | 85 |
# postgresql/pg8000.py
# Copyright (C) 2005-2021 the SQLAlchemy authors and contributors <see AUTHORS
# file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
r"""
.. dialect:: postgresql+pg8000
:name: pg8000
:dbapi: pg8000
:co... | [
2,
1281,
34239,
13976,
14,
6024,
33942,
13,
9078,
198,
2,
15069,
357,
34,
8,
5075,
12,
1238,
2481,
262,
16363,
2348,
26599,
7035,
290,
20420,
1279,
3826,
37195,
20673,
198,
2,
2393,
29,
198,
2,
198,
2,
770,
8265,
318,
636,
286,
16... | 3.023392 | 855 |
from tempfile import NamedTemporaryFile
from cbmail.base import Attachment, BaseMail
from cbmail.mixins import MailingListMixin
from django.test import SimpleTestCase
from mock import patch
| [
6738,
20218,
7753,
1330,
34441,
12966,
5551,
8979,
198,
198,
6738,
269,
65,
4529,
13,
8692,
1330,
3460,
15520,
11,
7308,
25804,
198,
6738,
269,
65,
4529,
13,
19816,
1040,
1330,
11099,
278,
8053,
35608,
259,
198,
6738,
42625,
14208,
13,
... | 3.62963 | 54 |
from django.urls import path
from . import views
urlpatterns = [
path('', views.index, name='index'),
path('check_db_connection', views.get_time, name="check_db"),
]
| [
6738,
42625,
14208,
13,
6371,
82,
1330,
3108,
198,
198,
6738,
764,
1330,
5009,
198,
198,
6371,
33279,
82,
796,
685,
198,
220,
220,
220,
3108,
10786,
3256,
5009,
13,
9630,
11,
1438,
11639,
9630,
33809,
198,
220,
220,
220,
3108,
10786,
... | 2.793651 | 63 |
# coding=utf-8
import re
import json
import requests
from bs4 import BeautifulSoup
if __name__ == '__main__':
print(get())
| [
2,
19617,
28,
40477,
12,
23,
198,
11748,
302,
198,
11748,
33918,
198,
11748,
7007,
198,
6738,
275,
82,
19,
1330,
23762,
50,
10486,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
3601,
7,... | 2.826087 | 46 |
import ast
import operator
import typing
from collections import defaultdict
from codegen import raml_types
from codegen.generate_abstract import AbstractModuleGenerator
from codegen.utils import reorder_class_definitions
FIELD_TYPES = {
"string": "marshmallow.fields.String",
"object": "marshmallow.fields.Dic... | [
11748,
6468,
198,
11748,
10088,
198,
11748,
19720,
198,
6738,
17268,
1330,
4277,
11600,
198,
198,
6738,
2438,
5235,
1330,
15770,
75,
62,
19199,
198,
6738,
2438,
5235,
13,
8612,
378,
62,
397,
8709,
1330,
27741,
26796,
8645,
1352,
198,
67... | 1.988262 | 1,789 |
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
from .batchnorm import SynchronizedBatchNorm1d, SynchronizedBatchNorm2d, SynchronizedBatchNorm3d
from .batchnorm import patch_sync_batchnorm, convert_model
from .replicate... | [
2,
770,
2393,
318,
636,
286,
16065,
11413,
1143,
12,
33,
963,
35393,
12,
20519,
15884,
354,
13,
198,
2,
3740,
1378,
12567,
13,
785,
14,
85,
330,
3883,
14,
50,
24871,
1143,
12,
33,
963,
35393,
12,
20519,
15884,
354,
198,
2,
4307,
... | 3.25641 | 117 |
# -*- coding: utf-8 -*-
# vim: sw=4:ts=4:expandtab
"""
riko.bado.io
~~~~~~~~~~~~
Provides functions for asynchronously reading files and urls
Examples:
basic usage::
>>> from riko import get_path
>>> from riko.bado.io import async_url_open
"""
import pygogo as gogo
from io import open
from tempfi... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
43907,
25,
1509,
28,
19,
25,
912,
28,
19,
25,
11201,
392,
8658,
198,
37811,
198,
380,
7204,
13,
65,
4533,
13,
952,
198,
15116,
8728,
198,
15946,
1460,
5499,
329,
... | 2.856742 | 356 |
#!/usr/bin/env python3
'''Search or create POTCAR file.
The elements can be parsed manually, or read from POSCAR.
'''
import os
import sys
from argparse import ArgumentParser, RawDescriptionHelpFormatter
from mykit.core.utils import trim_after
from mykit.vasp.poscar import Poscar
from mykit.vasp.potcar import Potcar... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
7061,
6,
18243,
393,
2251,
350,
2394,
20034,
2393,
13,
198,
198,
464,
4847,
460,
307,
44267,
14500,
11,
393,
1100,
422,
28069,
20034,
13,
198,
7061,
6,
198,
198,
11748,
28686,
19... | 2.930769 | 130 |
from typing import List, Optional
from cloudrail.knowledge.context.aws.lambda_.lambda_alias import create_lambda_function_arn
from cloudrail.knowledge.context.aws.iam.policy_statement import PolicyStatement
from cloudrail.knowledge.context.aws.iam.policy import Policy
from cloudrail.knowledge.context.aws.service_name ... | [
6738,
19720,
1330,
7343,
11,
32233,
198,
198,
6738,
6279,
30224,
13,
45066,
13,
22866,
13,
8356,
13,
50033,
44807,
50033,
62,
26011,
1330,
2251,
62,
50033,
62,
8818,
62,
1501,
198,
6738,
6279,
30224,
13,
45066,
13,
22866,
13,
8356,
13... | 3.003546 | 282 |
# automatically generated by the FlatBuffers compiler, do not modify
# namespace: flat
import flatbuffers
| [
2,
6338,
7560,
416,
262,
21939,
36474,
364,
17050,
11,
466,
407,
13096,
198,
198,
2,
25745,
25,
6228,
198,
198,
11748,
6228,
36873,
364,
198
] | 4.153846 | 26 |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'qt_window_test_ui.ui'
#
# Created: Fri Jan 16 22:18:17 2015
# by: PyQt4 UI code generator 4.9.1
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
exce... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
2,
5178,
7822,
7560,
422,
3555,
334,
72,
2393,
705,
39568,
62,
17497,
62,
9288,
62,
9019,
13,
9019,
6,
198,
2,
198,
2,
15622,
25,
19480,
2365,
1467,
2534,
25,
... | 2.520548 | 146 |
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-LOG 蓝鲸日志平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-LOG 蓝鲸日志平台 is licensed under the MIT License.
License for BK-LOG 蓝鲸日志平台:
------------------------------------------------... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
24893,
1087,
318,
10607,
284,
1104,
262,
1280,
2723,
2055,
416,
1642,
347,
42,
12,
25294,
5525,
241,
251,
165,
110,
116,
33768,
98,
33232,
245,
33176,
111,
... | 3.296636 | 654 |
"""Time humanizing functions."""
from __future__ import annotations
import datetime as dt
import enum
import functools
import math
from typing import Any
import human_readable.i18n as i18n
_ = i18n.gettext
P_ = i18n.pgettext
N_ = i18n.ngettext
@functools.total_ordering
class Unit(enum.Enum):
"""Enum for minim... | [
37811,
7575,
1692,
2890,
5499,
526,
15931,
198,
6738,
11593,
37443,
834,
1330,
37647,
198,
198,
11748,
4818,
8079,
355,
288,
83,
198,
11748,
33829,
198,
11748,
1257,
310,
10141,
198,
11748,
10688,
198,
6738,
19720,
1330,
4377,
198,
198,
... | 2.430688 | 10,597 |
from django.utils.translation import gettext_lazy
from rest_framework import serializers
from rest_framework.settings import api_settings
from datahub.search.apps import get_global_search_apps_as_mapping
from datahub.search.query_builder import MAX_RESULTS
from datahub.search.utils import SearchOrdering, SortDirection... | [
6738,
42625,
14208,
13,
26791,
13,
41519,
1330,
651,
5239,
62,
75,
12582,
198,
6738,
1334,
62,
30604,
1330,
11389,
11341,
198,
6738,
1334,
62,
30604,
13,
33692,
1330,
40391,
62,
33692,
198,
198,
6738,
4818,
993,
549,
13,
12947,
13,
18... | 2.774515 | 1,907 |
### Load arguments
import sys, getopt
if __name__ == "__main__":
new_seq, model_ID = main(sys.argv[1:])
### Load libraries
from keras.layers.convolutional import Conv1D, MaxPooling1D
from keras.layers.core import Dropout, Reshape, Dense, Activation, Flatten
from keras.layers import BatchNormalization, InputLay... | [
198,
21017,
8778,
7159,
198,
198,
11748,
25064,
11,
651,
8738,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
649,
62,
41068,
11,
2746,
62,
2389,
796,
1388,
7,
17597,
13,
853,
85,
58,
16,
25,
129... | 2.721284 | 592 |
j,i=65,-2
for I in range (1,14):
J= j-5
I=i+3
print('I=%d J=%d' %(I,J))
j=J
i=I | [
220,
198,
73,
11,
72,
28,
2996,
12095,
17,
198,
1640,
314,
287,
2837,
357,
16,
11,
1415,
2599,
198,
220,
220,
220,
449,
28,
474,
12,
20,
198,
220,
220,
220,
314,
28,
72,
10,
18,
198,
220,
220,
220,
3601,
10786,
40,
28,
4,
67... | 1.402778 | 72 |
#!/usr/bin/env python
import argparse
import copy
import logging
import os
import random
import time
from typing import Dict, List, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
from torch.utils.data import DataLoader
from torchvision import models
from ut... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
1822,
29572,
198,
11748,
4866,
198,
11748,
18931,
198,
11748,
28686,
198,
11748,
4738,
198,
11748,
640,
198,
6738,
19720,
1330,
360,
713,
11,
7343,
11,
309,
29291,
198,
198,
... | 2.12045 | 1,511 |
"""
Real time AEmotion (env: 'torch')
"""
# %% Import libs
import pyaudio
import numpy as np
# import pickle
# import librosa
import keract
import sys
sys.path.append('..')
from src.modeling.tcn.tcn import TCN
import os
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
from tensorflow.keras.models i... | [
37811,
198,
15633,
640,
317,
10161,
9650,
357,
24330,
25,
705,
13165,
354,
11537,
198,
37811,
198,
2,
43313,
17267,
9195,
82,
198,
11748,
12972,
24051,
198,
11748,
299,
32152,
355,
45941,
198,
2,
1330,
2298,
293,
198,
2,
1330,
9195,
4... | 2.897674 | 215 |
# Charlotte Capitanchik
# 25.04.18
# Based on fastCLIP tRNA strategy
# input is SAM of tRNA mapping
# and .fai of what is was mapped to
import pysam
from collections import defaultdict
import operator
from collections import Counter
import sys
import statistics
import random
import re
# input #
#trna_fai = sys.argv... | [
2,
14685,
4476,
270,
3702,
1134,
198,
2,
1679,
13,
3023,
13,
1507,
198,
2,
13403,
319,
3049,
5097,
4061,
256,
27204,
4811,
198,
2,
5128,
318,
28844,
286,
256,
27204,
16855,
198,
2,
290,
764,
69,
1872,
286,
644,
318,
373,
27661,
28... | 2.545491 | 5,034 |
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 13 11:10:35 2021
@author: Clau
"""
'''
Paper: Energy sufficiency, lowlands.
User: Health Center
'''
from core import User, np
User_list = []
#Definig users
HC = User("Health center", 1)
User_list.append(HC)
HC_indoor_bulb = HC.Appliance(HC,20,7,2,... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
201,
198,
37811,
201,
198,
41972,
319,
2892,
8621,
1511,
1367,
25,
940,
25,
2327,
33448,
201,
198,
201,
198,
31,
9800,
25,
1012,
559,
201,
198,
37811,
201,
198,
201,
198,
... | 1.909091 | 1,199 |
"""
Estimate Lasso and Elastic-Net regression models on a manually generated sparse
signal corrupted with an additive noise.
"""
# %%
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import r2_score
from sklearn.model_selection import train_test_split
np.random.seed(42)
n_samples, n_features = 5... | [
37811,
198,
22362,
1920,
406,
28372,
290,
48567,
12,
7934,
20683,
4981,
319,
257,
14500,
7560,
29877,
198,
12683,
282,
26940,
351,
281,
38298,
7838,
13,
198,
37811,
198,
2,
43313,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29... | 1.980237 | 1,012 |
"""This module solves kata https://www.codewars.com/kata/n-th-fibonacci."""
def original_solution(n):
"""Return the nth fibonacci number."""
if n == 1:
return 0
a, b = 0, 1
for i in range(1, n - 1):
a, b = b, (a + b)
return b
#better solution
def nth_fib(n):
"""Return the nth f... | [
37811,
1212,
8265,
39107,
479,
1045,
3740,
1378,
2503,
13,
19815,
413,
945,
13,
785,
14,
74,
1045,
14,
77,
12,
400,
12,
69,
571,
261,
44456,
526,
15931,
198,
198,
4299,
2656,
62,
82,
2122,
7,
77,
2599,
198,
220,
220,
220,
37227,
... | 2.220339 | 236 |
import random_functions, colorama, Forensics_tool_redesigned_using_oops
import sqlite3, getpass, os
#module 5 - Browser Forensics
#chrome_tool_start
#chrome_tool_end
#mozilla_tool_start
#mozilla_tool_end | [
11748,
4738,
62,
12543,
2733,
11,
3124,
1689,
11,
4558,
49242,
62,
25981,
62,
445,
274,
3916,
62,
3500,
62,
44860,
201,
198,
11748,
44161,
578,
18,
11,
651,
6603,
11,
28686,
201,
198,
201,
198,
2,
21412,
642,
532,
34270,
4558,
49242... | 2.266055 | 109 |
# -*- coding: utf-8 -*-
"""
@author:XuMing(xuming624@qq.com)
@description:
"""
import sys
import unittest
sys.path.append('..')
from text2vec import SBert
from text2vec import BM25
from sentence_transformers.util import cos_sim
sbert_model = SBert('paraphrase-multilingual-MiniLM-L12-v2')
if __name__ == '__main_... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
31,
9800,
25,
55,
84,
44,
278,
7,
87,
12595,
21,
1731,
31,
38227,
13,
785,
8,
198,
31,
11213,
25,
220,
198,
37811,
198,
11748,
25064,
198,
11748,
555,
... | 2.510949 | 137 |
#!/usr/bin/env python3
import sys
import argparse
from nltk import sent_tokenize
from nltk import word_tokenize
from nltk import ngrams as nltk_ngrams
from functools import partial
LPAD_SYMBOL = "<s>"
RPAD_SYMBOL = "</s>"
nltk_ngrams = partial(nltk_ngrams,
pad_right=True, pad_left=True,
right_pad_symbol=RPA... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
11748,
25064,
198,
11748,
1822,
29572,
198,
198,
6738,
299,
2528,
74,
1330,
1908,
62,
30001,
1096,
198,
6738,
299,
2528,
74,
1330,
1573,
62,
30001,
1096,
198,
6738,
299,
2528,... | 2.389785 | 372 |
"""
Usage:
python small_satrn_inference.py vedastr/test.jpg
"""
import argparse
import os
import sys
import cv2
from vedastr.runners import InferenceRunner
from vedastr.utils import Config
from pathlib import Path
from vedastr.helper import download_drive_file
home = str(Path.home())
if __name__ == '__main__':
... | [
37811,
198,
28350,
25,
198,
29412,
1402,
62,
49720,
35906,
62,
259,
4288,
13,
9078,
410,
276,
459,
81,
14,
9288,
13,
9479,
198,
37811,
198,
11748,
1822,
29572,
198,
11748,
28686,
198,
11748,
25064,
198,
198,
11748,
269,
85,
17,
198,
... | 2.877193 | 114 |
'''
给定一个二叉树和一个目标和，判断该树中是否存在根节点到叶子节点的路径，这条路径上所有节点值相加等于目标和。
说明: 叶子节点是指没有子节点的节点。
返回值：布尔值
'''
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
from collections import deque
| [
7061,
6,
198,
163,
119,
247,
22522,
248,
31660,
10310,
103,
12859,
234,
20998,
231,
43718,
239,
161,
240,
234,
31660,
10310,
103,
33566,
106,
43718,
229,
161,
240,
234,
171,
120,
234,
26344,
97,
23877,
255,
46237,
98,
43718,
239,
4079... | 1.087452 | 263 |
"""Two way (mutual nearest neighbor) matcher.
Authors: Ayush Baid
"""
from typing import Tuple
import cv2 as cv
import numpy as np
from enum import Enum
from gtsfm.common.keypoints import Keypoints
from gtsfm.frontend.matcher.matcher_base import MatcherBase
class MatchingDistanceType(Enum):
"""Type of distance... | [
37811,
7571,
835,
357,
21973,
723,
16936,
4780,
8,
2603,
2044,
13,
198,
198,
30515,
669,
25,
13709,
1530,
347,
1698,
198,
37811,
198,
6738,
19720,
1330,
309,
29291,
198,
198,
11748,
269,
85,
17,
355,
269,
85,
198,
11748,
299,
32152,
... | 2.292884 | 1,335 |
import scrapy
from scrapy.loader import ItemLoader
from mercadolibre.items import CelularItem
## #comment_js_7me > div > div > div > div:nth-child(2) > div > div > div > div.UFICommentContent > div._26f8 > div > span
| [
11748,
15881,
88,
198,
6738,
15881,
88,
13,
29356,
1330,
9097,
17401,
628,
198,
6738,
11991,
324,
349,
571,
260,
13,
23814,
1330,
15248,
934,
7449,
628,
198,
198,
2235,
1303,
23893,
62,
8457,
62,
22,
1326,
1875,
2659,
1875,
2659,
1875... | 2.846154 | 78 |
import aiohttp
| [
11748,
257,
952,
4023,
628
] | 3.2 | 5 |
"""This module will update a binary feature matrix Z."""
import numpy as np
import numpy.random as nr
from . import logPX
from . import logPV
from . import sampleV # slice sampler
def sampleZ(X, Z, A, sigma_x, sigma_a, alpha, K, N, D, realvaluedZ, proposeNewfeature):
"""Drawing Z using an uncollapsed Gibbs sampl... | [
37811,
1212,
8265,
481,
4296,
257,
13934,
3895,
17593,
1168,
526,
15931,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
299,
32152,
13,
25120,
355,
299,
81,
198,
6738,
764,
1330,
2604,
47,
55,
198,
6738,
764,
1330,
2604,
47,
53,
198,... | 1.86618 | 1,644 |
from cbutil import Path
from pathinfo import *
for p in source_file_paths + header_file_paths:
content = None
with p.open('r') as fr:
content = fr.read()
if content != None and '\r' in content:
print(p)
with p.open('w', encoding = 'UTF-8') as fw:
fw.write(content)
... | [
6738,
269,
4360,
346,
1330,
10644,
198,
6738,
3108,
10951,
1330,
1635,
628,
198,
1640,
279,
287,
2723,
62,
7753,
62,
6978,
82,
1343,
13639,
62,
7753,
62,
6978,
82,
25,
198,
220,
220,
220,
2695,
796,
6045,
198,
220,
220,
220,
351,
... | 2.182432 | 148 |
# -*- coding: utf-8 -*-
# Generated by Django 1.9.2 on 2016-04-10 03:18
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,
13,
17,
319,
1584,
12,
3023,
12,
940,
7643,
25,
1507,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
19... | 2.719298 | 57 |
import logging
import argparse
import sys
import os
import json
import time
import datetime
from writers import csv_writer
from writers import json_writer
from utils import get_memory
from utils import memory_limit
from accessors.pride_data import get_filelist, get_projectlist, write_archive_file, download_projectli... | [
11748,
18931,
198,
11748,
1822,
29572,
198,
11748,
25064,
198,
11748,
28686,
198,
11748,
33918,
198,
11748,
640,
198,
11748,
4818,
8079,
198,
198,
6738,
8786,
1330,
269,
21370,
62,
16002,
198,
6738,
8786,
1330,
33918,
62,
16002,
198,
198,... | 2.60431 | 2,042 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Contains test cases for the utils.py module."""
import locale
import sys
import unittest
from pathlib import Path
from unittest import mock
PATH = Path(__file__).parent
sys.path.insert(0, str(PATH.parent))
from youtube_dl_gui import utils
class TestUtils(unittest.... | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
37811,
4264,
1299,
1332,
2663,
329,
262,
3384,
4487,
13,
9078,
8265,
526,
15931,
628,
198,
11748,
36693,
198,
1174... | 2.531044 | 757 |
__version__ = "0.0.6"
from .core import * | [
834,
9641,
834,
796,
366,
15,
13,
15,
13,
21,
1,
198,
6738,
764,
7295,
1330,
1635
] | 2.411765 | 17 |
import os
from jinja2 import Environment, FileSystemLoader
import pypandoc
import click
import pathlib
import re
BEFORE="""{% extends 'layouts/main.html' %}
{% block content %}
"""
AFTER="""
{% endblock %}
"""
# add option for substitution
@click.command()
@click.option('--var', '-v', multiple=True)
@click.argumen... | [
11748,
28686,
198,
6738,
474,
259,
6592,
17,
1330,
9344,
11,
9220,
11964,
17401,
198,
11748,
279,
4464,
392,
420,
198,
11748,
3904,
198,
11748,
3108,
8019,
198,
11748,
302,
628,
198,
12473,
30818,
2625,
15931,
90,
4,
14582,
705,
10724,
... | 2.22504 | 631 |
'''
Created on Oct 18, 2012
@author: mmunn
Unit test : EUCA-2244 Default launch permission for user image (account resource)
The fix for this issue changes the database so euca_conf --initialize
must have been run with the fix present for this test to pass.
setUp ... | [
7061,
6,
198,
41972,
319,
2556,
1248,
11,
2321,
198,
31,
9800,
25,
285,
6199,
77,
198,
26453,
1332,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
4576,
8141,
12,
24137,
19,
15161,
4219,
7170,
329,
2836,
2939,
357,
23317,
8271,
... | 2.530086 | 349 |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.3 on 2017-08-09 19:01
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
import django_remote_submission.models
import model_utils.fields
impor... | [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
2980,
515,
416,
37770,
352,
13,
1157,
13,
18,
319,
2177,
12,
2919,
12,
2931,
678,
25,
486,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
1... | 3.037037 | 108 |
import os,urllib, urllib2
import raid
path = '/home/lorenzo/projects/assets/GCF_52/'
#testMultiple()
#testOne('20674984470_1')
#testOne('20675014450_1')
#testOne('20673569920_1')
testWS('20673569920_1')
| [
11748,
28686,
11,
333,
297,
571,
11,
2956,
297,
571,
17,
198,
11748,
9513,
198,
198,
6978,
796,
31051,
11195,
14,
75,
29578,
10872,
14,
42068,
14,
19668,
14,
15916,
37,
62,
4309,
14,
6,
198,
198,
2,
9288,
31217,
3419,
198,
2,
9288... | 2.204301 | 93 |
import os
import paho.mqtt.client as mqtt
import time
import mysql.connector
import json
print("Starting up!")
sql_host = os.environ['SQL_HOST']
sql_user = os.environ['SQL_USER']
sql_passwd = os.environ['SQL_PASSWD']
sql_database = os.environ['SQL_DATABASE']
mqtt_host = os.environ['MQTT_HOST']
mqtt_user = os.en... | [
11748,
28686,
198,
11748,
279,
17108,
13,
76,
80,
926,
13,
16366,
355,
285,
80,
926,
198,
11748,
640,
198,
11748,
48761,
13,
8443,
273,
198,
11748,
33918,
628,
220,
220,
220,
220,
198,
4798,
7203,
22851,
510,
2474,
8,
198,
198,
2541... | 2.398034 | 407 |
import os
import pdfkit
PAGE_SIZE = "A4" | [
11748,
28686,
198,
11748,
37124,
15813,
198,
198,
4537,
8264,
62,
33489,
796,
366,
32,
19,
1
] | 2.411765 | 17 |
import matplotlib.pyplot as plt
from numpy import arange
import pandas as pd
import os
import logging
logging.basicConfig()
logger = logging.getLogger('PlotEvalNumBar')
logger.setLevel('INFO')
if __name__ == '__main__':
csv_path = r"../../../tests/mf_param_opt_tests/output/FidelityLevelTest.csv"
bar_path = ... | [
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
6738,
299,
32152,
1330,
610,
858,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
28686,
198,
11748,
18931,
198,
198,
6404,
2667,
13,
35487,
16934,
3419,
198,
6404,
1362,
... | 2.533333 | 210 |