xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

54d2af6cc6ffcbe94ad442887d35faa47a8ec2cd

1,090

py

Python

source/packages/scs-pm-server/src/python-server/app.py

amittkSharma/scs_predictive_maintenance

105a218b47d81d02f7e799287bd1e9279db452ce

[ "MIT" ]

null

source/packages/scs-pm-server/src/python-server/app.py

amittkSharma/scs_predictive_maintenance

105a218b47d81d02f7e799287bd1e9279db452ce

[ "MIT" ]

1

2022-02-05T17:13:00.000Z

source/packages/scs-pm-server/src/python-server/app.py

amittkSharma/scs_predictive_maintenance

105a218b47d81d02f7e799287bd1e9279db452ce

[ "MIT" ]

null

import json import logging import joblib import pandas as pd from flask import Flask, jsonify, request from flask_cors import CORS, cross_origin app = Flask(__name__) CORS(app) @app.route("/api/machinePrediction", methods=['GET']) def home(): incomingMachineId = request.args.get('machineId') modelPath = requ...

24.222222

67

0.709174

141

1,090

5.319149

0.517731

0.058667

0.074667

0.048

0

0.00222

0.173395

1,090

44

68

24.772727

0.830189

0.031193

0

0.129155

0.020893

0

1

0.034483

false

0

0.206897

0

0.275862

0

null

0

null

0

1

0

54d3039f58743cfa00e492ea3768046369054479

4,411

py

Python

tests/test_remove_from_dependee_chain.py

ess-dmsc/nexus-constructor

ae0026c48f8f2d4d88d3ff00e45cb6591983853b

[ "BSD-2-Clause" ]

3

2019-05-31T08:38:25.000Z

2022-01-06T09:23:21.000Z

tests/test_remove_from_dependee_chain.py

ess-dmsc/nexus-constructor

ae0026c48f8f2d4d88d3ff00e45cb6591983853b

[ "BSD-2-Clause" ]

709

2019-02-06T08:23:07.000Z

2022-03-29T23:03:37.000Z

tests/test_remove_from_dependee_chain.py

ess-dmsc/nexus-constructor

ae0026c48f8f2d4d88d3ff00e45cb6591983853b

[ "BSD-2-Clause" ]

2

2020-03-06T09:58:56.000Z

2020-08-04T18:32:57.000Z

import pytest from PySide2.QtGui import QVector3D from nexus_constructor.model.component import Component from nexus_constructor.model.dataset import Dataset from nexus_constructor.model.instrument import Instrument from nexus_constructor.model.value_type import ValueTypes values = Dataset( name="scalar_value", ...

28.275641

68

0.670143

526

4,411

5.479087

0.119772

0.030534

0.034351

0.030534

0.730396

0.620056

0.546149

0.438584

0.403886

0

0.059478

0.226253

4,411

155

69

28.458065

0.78494

0

0.555556

0

0.043301

0

0.155556

1

0.044444

false

0

0.044444

0.007407

0.096296

0

null

0

null

0

1

0

54d32f6738e6ad2c2884cf8b772cee6a6620a984

11,013

py

Python

fastmvsnet/train1.py

molspace/FastMVS_experiments

b897015d77600687ca2addf99bb6a6f0de524e5f

[ "MIT" ]

null

fastmvsnet/train1.py

molspace/FastMVS_experiments

b897015d77600687ca2addf99bb6a6f0de524e5f

[ "MIT" ]

null

fastmvsnet/train1.py

molspace/FastMVS_experiments

b897015d77600687ca2addf99bb6a6f0de524e5f

[ "MIT" ]

null

#!/usr/bin/env python import argparse import os.path as osp import logging import time import sys sys.path.insert(0, osp.dirname(__file__) + '/..') import torch import torch.nn as nn from fastmvsnet.config import load_cfg_from_file from fastmvsnet.utils.io import mkdir from fastmvsnet.utils.logger import setup_logger...

37.080808

119

0.562608

1,172

11,013

5.013652

0.171502

0.029101

0.022634

0.014466

0.470388

0.462049

0.429204

0.39857

0.382573

0.361811

0

0.005401

0.34432

11,013

296

120

37.206081

0.808337

0.025969

0

0.417021

0

0.05694

0

1

0.021277

false

0

0.076596

0

0.114894

0

null

0

null

0

1

0

54d41bf8d53f9ade04da7c58f9daea5fe0658840

857

py

Python

modulo2/3-detectores/3.2-detector/models.py

fossabot/unifacisa-visao-computacional

14aef22a3e7fe10ee820d31ce12ad21a3cad7b0b

[ "MIT" ]

null

modulo2/3-detectores/3.2-detector/models.py

fossabot/unifacisa-visao-computacional

14aef22a3e7fe10ee820d31ce12ad21a3cad7b0b

[ "MIT" ]

null

modulo2/3-detectores/3.2-detector/models.py

fossabot/unifacisa-visao-computacional

14aef22a3e7fe10ee820d31ce12ad21a3cad7b0b

[ "MIT" ]

1

2021-02-06T00:49:32.000Z

# Estrutura básica para projetos de Machine Learning e Deep Learning # Por Adriano Santos. from torch import nn, relu import torch.nn.functional as F import torch.optim as optim import torch from torchvision import models class ResNet(nn.Module): def __init__(self, saida, pretreinado=True): super(ResNet,...

29.551724

86

0.655776

115

857

4.817391

0.478261

0.021661

0.064982

0.068592

0.083032

0

0.031484

0.221704

857

29

87

29.551724

0.7991

0.10035

0

1

0.1

false

0

0.25

0

0.45

0

null

0

null

0

1

0

54d5248eff89e3f435c1da7e63250cb5c736a60a

3,231

py

Python

python/setup.py

sbrodeur/evert

c7005ba29576145ab650144f9b9230eaf7bec460

[ "BSD-3-Clause" ]

28

2017-10-04T13:58:43.000Z

2021-11-06T10:46:51.000Z

python/setup.py

sbrodeur/evert

c7005ba29576145ab650144f9b9230eaf7bec460

[ "BSD-3-Clause" ]

7

2017-12-04T17:17:55.000Z

2021-07-29T08:58:26.000Z

python/setup.py

sbrodeur/evert

c7005ba29576145ab650144f9b9230eaf7bec460

[ "BSD-3-Clause" ]

10

2017-11-07T14:51:08.000Z

2019-06-05T04:17:44.000Z

#!/usr/bin/env python # Copyright (c) 2017, Simon Brodeur # 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, th...

46.826087

89

0.556484

341

3,231

5.234604

0.557185

0.040336

0.019048

0.02577

0.103081

0.07619

0

0.006167

0.34757

3,231

68

90

47.514706

0.840607

0.501393

0

0.246349

0.045714

0

1

0

false

0

0.032258

0

0.032258

0

null

0

null

0

1

0

54d6049e6360802df5527ba35f15e6ff291748e2

530

py

Python

somegame/fps_osd.py

kodo-pp/somegame-but-not-that-one

6252d34b84fe7c83ada9e699df17688c50dd7596

[ "MIT" ]

null

somegame/fps_osd.py

kodo-pp/somegame-but-not-that-one

6252d34b84fe7c83ada9e699df17688c50dd7596

[ "MIT" ]

null

somegame/fps_osd.py

kodo-pp/somegame-but-not-that-one

6252d34b84fe7c83ada9e699df17688c50dd7596

[ "MIT" ]

null

import pygame from loguru import logger from somegame.osd import OSD class FpsOSD(OSD): def __init__(self, game): super().__init__(game) logger.info('Loading font') self.font = pygame.font.Font(pygame.font.get_default_font(), 32) def draw(self, surface): fps = self.game.get_a...

29.444444

85

0.635849

76

530

4.223684

0.513158

0.049844

0.087227

0

0.033816

0.218868

530

17

86

31.176471

0.741546

0

0.062264

0

1

0.153846

false

0

0.230769

0

0.461538

0

null

0

null

0

1

0

54d6ce148b09071a1e33198868f6c84a03813ea1

11,846

py

Python

python/chronos/test/bigdl/chronos/data/experimental/test_xshardstsdataset.py

sgwhat/BigDL

25b402666fbb26b0bc18fc8100e9a00469844778

[ "Apache-2.0" ]

null

python/chronos/test/bigdl/chronos/data/experimental/test_xshardstsdataset.py

sgwhat/BigDL

25b402666fbb26b0bc18fc8100e9a00469844778

[ "Apache-2.0" ]

null

python/chronos/test/bigdl/chronos/data/experimental/test_xshardstsdataset.py

sgwhat/BigDL

25b402666fbb26b0bc18fc8100e9a00469844778

[ "Apache-2.0" ]

null

# # Copyright 2016 The BigDL Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in ...

46.454902

100

0.593534

1,435

11,846

4.715679

0.168641

0.062066

0.035171

0.052017

0.612236

0.600562

0.58608

0.581646

0.567312

0.556081

0

0.021901

0.286932

11,846

254

101

46.637795

0.779212

0.067871

0

0.510101

0

0.066013

0

0.287879

1

0.055556

false

0.005051

0.085859

0

0.156566

0.005051

0

null

0

null

0

1

0

54d7680f93fc7f5f7a46d60f37723337c7dce6f3

2,603

py

Python

zoom_functions.py

WXSD-Sales/ZoomToWebex

16cc663620e2ef2904b0e2857d709aee96b78eb7

[ "MIT" ]

1

2021-10-21T01:36:33.000Z

zoom_functions.py

WXSD-Sales/integration-samples

2f18be740329f3c35c78c268a6d4544cae5d313e

[ "MIT" ]

null

zoom_functions.py

WXSD-Sales/integration-samples

2f18be740329f3c35c78c268a6d4544cae5d313e

[ "MIT" ]

null

import json import tornado.gen import traceback from base64 import b64encode from tornado.httpclient import AsyncHTTPClient, HTTPRequest, HTTPError from settings import Settings from mongo_db_controller import ZoomUserDB @tornado.gen.coroutine def zoomRefresh(zoom_user): url = "https://zoom.us/oauth/token" p...

38.850746

142

0.661929

325

2,603

5.166154

0.341538

0.085765

0.019655

0.026802

0.147707

0.045265

0

0.01277

0.217826

2,603

66

143

39.439394

0.811886

0.036112

0

0.25

0

0.170722

0.023135

0

1

0.033333

false

0.05

0.116667

0

0.15

0.183333

0

null

0

null

0

1

0

54d83fe60a2207f45c149a5e0cac230756ba7376

1,484

py

Python

crypten/mpc/__init__.py

gmuraru/CrypTen

e39a7aaf65436706321fe4e3fc055308c78b6b92

[ "MIT" ]

null

crypten/mpc/__init__.py

gmuraru/CrypTen

e39a7aaf65436706321fe4e3fc055308c78b6b92

[ "MIT" ]

null

crypten/mpc/__init__.py

gmuraru/CrypTen

e39a7aaf65436706321fe4e3fc055308c78b6b92

[ "MIT" ]

null

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import os from crypten.mpc import primitives # noqa: F401 from crypten.mpc import provider # noqa: F40 from .conte...

28.538462

81

0.768194

185

1,484

5.843243

0.432432

0.194265

0.116559

0.037003

0.142461

0.081406

0

0.004781

0.154313

1,484

51

82

29.098039

0.856574

0.194744

0

0.108769

0.035413

0

0.1

1

0.1

false

0

0.2

0.066667

0.366667

0

null

0

null

0

1

0

54da3dc2f38e9f403fcf4bc41db3259f59c8f372

1,763

py

Python

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

import sqlite3 from random import randint, choice import numpy as np conn = sqlite3.connect('ej.db') c = conn.cursor() #OBTENIENDO TAMAnOS MAXIMOS MINIMOS Y PROMEDIO# c.execute('SELECT MAX(alto) FROM features') resultado = c.fetchone() if resultado: altoMax = resultado[0] c.execute('SELECT MIN(alto) FROM featu...

23.506667

103

0.640953

233

1,763

4.759657

0.309013

0.036069

0.050496

0.079351

0.299369

0.259693

0.164112

0

0.030236

0.230856

1,763

75

104

23.506667

0.787611

0.059558

0

0.181818

0

0.117433

0

1

0

false

0

0.068182

0

0.068182

0

null

0

null

0

1

0

54dbf6330b24d0c6aff3e7ee1c31934c49d43385

12,082

py

Python

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

null

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

1

2019-04-24T12:14:59.000Z

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

null

# nuScenes dev-kit. # Code written by Holger Caesar & Oscar Beijbom, 2018. # Licensed under the Creative Commons [see licence.txt] import argparse import json import os import random import time from typing import Tuple, Dict, Any import numpy as np from nuscenes import NuScenes from nuscenes.eval.detection.algo imp...

45.421053

120

0.630525

1,515

12,082

4.815842

0.206601

0.024945

0.013706

0.020559

0.215872

0.158991

0.122259

0.081277

0.058936

0.029331

0

0.003611

0.266595

12,082

265

121

45.592453

0.819772

0.199388

0

0.073171

0

0.118392

0

0.006098

1

0.030488

false

0

0.085366

0.006098

0.140244

0.060976

0

null

0

null

0

1

0

54dcf21edb2556756e4c18e431858f02788f9d3a

9,520

py

Python

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

import unittest from onlinejudge_api.main import main class DownloadAtCoderTest(unittest.TestCase): def test_icpc2013spring_a(self): """This problem contains both words `Input` and `Output` for the headings for sample outputs. """ url = 'http://jag2013spring.contest.atcoder.jp/tasks/icpc...

36.615385

157

0.411029

892

9,520

4.338565

0.253363

0.041602

0.065891

0.074677

0.491473

0.451938

0.384496

0.365116

0.347028

0.299742

0

0.104319

0.43813

9,520

259

158

36.756757

0.619181

0.06229

0

0.481982

0

0.031532

0.358086

0.038596

0

0.036036

1

0.036036

false

0

0.009009

0

0.04955

0

null

0

null

0

1

0

54dcf64898b0684c67b6786b86aa9adc1e8b99c7

681

py

Python

odm/libexec/odm_tenant.py

UMCollab/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

2

2019-04-26T13:26:02.000Z

2019-10-18T10:36:52.000Z

odm/libexec/odm_tenant.py

flowerysong/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

1

2020-10-28T00:38:07.000Z

odm/libexec/odm_tenant.py

flowerysong/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

1

2019-02-21T16:41:24.000Z

#!/usr/bin/env python3 # This file is part of ODM and distributed under the terms of the # MIT license. See COPYING. import json import sys import odm.cli def main(): cli = odm.cli.CLI(['action']) client = cli.client if cli.args.action == 'list-users': print(json.dumps(client.list_users(), ind...

21.28125

79

0.638767

98

681

4.326531

0.459184

0.066038

0.122642

0.120283

0.301887

0.132075

0

0.009294

0.209985

681

31

80

21.967742

0.77881

0.162996

0

0.116402

0

1

0.058824

false

0

0.176471

0

0.235294

0

null

0

null

0

1

0

54dde115e15519f27b695b4a4ec6e5589e225fb7

17,182

py

Python

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

74

2015-12-25T09:43:18.000Z

2022-03-30T00:23:30.000Z

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

184

2016-11-23T15:57:16.000Z

2022-03-15T05:25:59.000Z

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

98

2015-12-13T12:20:34.000Z

2022-03-18T15:28:35.000Z

# Copyright (c) 2014 Ahmed H. Ismail # 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...

49.091429

178

0.650506

2,066

17,182

5.277348

0.151016

0.031643

0.095111

0.117491

0.555994

0.478676

0.468403

0.442355

0.364303

0.295515

0

0.052878

0.217437

17,182

349

179

49.232092

0.757995

0.032359

0

0.190164

0

0.02623

0.416912

0.086127

0

0.380328

1

0.055738

false

0

0.036066

0

0.131148

0

null

0

null

0

1

0

54df90a5374a87e257978dcb4c0e1caa9abfa7f7

2,024

py

Python

mount_drives.py

DT-was-an-ET/fanshim-python-pwm

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

null

mount_drives.py

DT-was-an-ET/fanshim-python-pwm

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

null

mount_drives.py

DT-was-an-ET/fanshim-python-pwm

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

3

2020-02-27T13:45:19.000Z

2020-03-26T13:38:17.000Z

# Standard library imports from subprocess import call as subprocess_call from utility import fileexists from time import sleep as time_sleep from datetime import datetime mount_try = 1 not_yet = True done = False start_time = datetime.now() if fileexists("/home/rpi4-sftp/usb/drive_present.txt"): when_usba...

36.142857

107

0.733202

301

2,024

4.694352

0.239203

0.084926

0.106157

0.080679

0.44586

0.401982

0.375088

0.318471

0.290163

0

0.012768

0.148715

2,024

55

108

36.8

0.807313

0.011858

0

0.078431

0

0.252702

0.166752

0

1

0

false

0

0.078431

0

0.078431

0.098039

0

null

0

null

0

1

0

54e179a25d793c478f7e42c99a00025d13aed6d0

1,438

py

Python

codes/Lib/site-packages/openpyxl/writer/tests/test_style.py

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

codes/Lib/site-packages/openpyxl/writer/tests/test_style.py

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

codes/Lib/site-packages/openpyxl/writer/tests/test_style.py

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

# Copyright (c) 2010-2014 openpyxl import pytest from openpyxl.styles.borders import Border, Side from openpyxl.styles.fills import GradientFill from openpyxl.styles.colors import Color from openpyxl.writer.styles import StyleWriter from openpyxl.tests.helper import get_xml, compare_xml class DummyWorkbook: st...

25.678571

78

0.684284

173

1,438

5.566474

0.364162

0.062305

0.056075

0.074766

0.413292

0.328141

0

0.025274

0.174548

1,438

55

79

26.145455

0.786015

0.022253

0

0.4

0

0.36396

0

0.044444

1

0.044444

false

0

0.133333

0

0.222222

0

null

0

null

0

1

0

54e459da47af69f9dc842497504519a50554986e

774

py

Python

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

53

2020-02-20T06:56:03.000Z

2022-03-03T03:09:25.000Z

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

6

2020-03-03T03:15:53.000Z

2021-01-29T02:24:06.000Z

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

17

2020-02-26T03:51:41.000Z

2022-03-24T02:23:51.000Z

# -*- coding: utf-8 -*- # # Tencent is pleased to support the open source community by making QT4C available. # Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved. # QT4C is licensed under the BSD 3-Clause License, except for the third-party components listed below. # A copy of the BSD 3-Cla...

28.666667

103

0.719638

114

774

4.745614

0.692982

0.038817

0.025878

0.048059

0.073937

0

0.021472

0.157623

774

26

104

29.769231

0.808282

0.453488

0

0.046341

0

1

0.090909

false

0

0.272727

0

0.363636

0

null

0

null

0

1

0

54e639174a97601933059aabae1c3acdb2b90d00

323

py

Python

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

null

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

null

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

2

2019-05-05T00:41:26.000Z

2019-05-05T00:46:45.000Z

from cffi import FFI ffibuilder = FFI() ffibuilder.cdef(""" int test(int t); """) ffibuilder.set_source("_pi_cffi", """ #include "brute.h" """, sources=['brute.c']) if __name__ == "__main__": ffibuilder.compile(verbose = Tru...

19

42

0.479876

30

323

4.8

0.766667

0.180556

0

0.374613

323

16

43

20.1875

0.712871

0

0.162055

0

1

0

false

0

0.1

0

0.1

0

null

0

null

0

1

0

54e64db782245fc204cf4d668f6d515f9131a03b

2,392

py

Python

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

"""Board Module""" import copy from typing import Tuple, List from src.coordinate import Coordinate from src.snake import Snake class Board: """Track the cooardinates for all snakes and food in the game.""" def __init__(self, data): self._data = data self._snakes = None self._foods = No...

37.375

85

0.633361

330

2,392

4.439394

0.263636

0.062116

0.01843

0.043003

0.168601

0.148805

0.118771

0.072355

0

0.0017

0.262124

2,392

63

86

37.968254

0.828329

0.192726

0

0.068182

0

0.025464

0

1

0.181818

false

0

0.090909

0

0.454545

0.045455

0

null

0

null

0

1

0

54e781207e20bd9e8679af88a83847cfe7947287

2,349

py

Python

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

null

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

1

2022-03-15T23:48:51.000Z

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

null

import os import zipfile from typing import List import pandas as pd import urllib from personalized_nlp.settings import STORAGE_DIR from personalized_nlp.utils.data_splitting import split_texts from personalized_nlp.datasets.datamodule_base import BaseDataModule class WikiDataModule(BaseDataModule): def __init...

32.178082

96

0.638995

288

2,349

4.920139

0.34375

0.073395

0.038814

0.056457

0.135498

0.084686

0

0.00846

0.245211

2,349

73

97

32.178082

0.79075

0

0.037037

0

0.084681

0.02

0

1

0.111111

false

0

0.148148

0.018519

0.333333

0

null

0

null

0

1

0

54ea3d9d70532f8dc30f4d5946975cecc10f6326

11,009

py

Python

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

from __future__ import absolute_import, division, print_function, \ with_statement import logging import os.path import time import tornado.escape import tornado.gen import tornado.ioloop from tornado.test.util import unittest from tornado.testing import AsyncHTTPTestCase, gen_test import tornado.web from pilbox...

39.887681

79

0.606504

1,433

11,009

4.51291

0.144452

0.064945

0.07345

0.061234

0.639709

0.565796

0.55559

0.552188

0.525282

0.524664

0

0.015445

0.235444

11,009

275

80

40.032727

0.752881

0

0.358407

0

0.126624

0.011173

0

0.137168

1

0.150442

false

0

0.084071

0.013274

0.300885

0.004425

0

null

0

null

0

1

0

54eaca929e4c45b157fe05142cabf897db4cf571

1,202

py

Python

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

6

2017-08-09T09:41:42.000Z

2021-04-22T05:10:17.000Z

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

null

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

5

2015-11-04T12:57:10.000Z

2020-10-18T17:32:25.000Z

#!/usr/bin/env python from scipy import * from pylab import * #from pylab import imshow #! #! Some graphical explorations of the Julia sets with python and pyreport #!######################################################################### #$ #$ We start by defining a function J: #$ \[ J_c : z \rightarrow z^2 + c \] #...

26.130435

75

0.584859

207

1,202

3.371981

0.478261

0.011461

0.04298

0.060172

0.126075

0.094556

0.04298

0

0.096174

0.195507

1,202

45

76

26.711111

0.625646

0.315308

0

0.483871

0

0.031165

0

1

0.032258

false

0

0.064516

0.032258

0.129032

0

null

0

null

0

1

0

54ed860d4a6171f4dc1581a63c75ee95835b9b75

6,287

py

Python

eris/script/ferdian.py

ferdianap/Eris_test

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

1

2015-06-12T04:38:09.000Z

eris/script/ferdian.py

ferdianap/eris

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

null

eris/script/ferdian.py

ferdianap/eris

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # Copyright (c) 2013-2014, Rethink Robotics # 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, # ...

34.543956

77

0.655798

858

6,287

4.69697

0.36014

0.015881

0.013896

0.011414

0.105707

0.087841

0.058065

0

0.007852

0.250517

6,287

181

78

34.734807

0.847411

0.405122

0

0.043011

0

0.112983

0.025967

0

1

0.043011

false

0

0.075269

0

0.172043

0.053763

0

null

0

null

0

1

0

54f048a7a0b7d058cdc56c1d7f2c7462bde0f3d6

4,461

py

Python

core/src/main/python/akdl/entry/base_entry.py

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

3,301

2018-10-01T16:30:44.000Z

2022-03-30T08:07:16.000Z

core/src/main/python/akdl/entry/base_entry.py

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

206

2019-11-27T14:04:42.000Z

2022-03-28T08:02:05.000Z

core/src/main/python/akdl/entry/base_entry.py

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

765

2018-10-09T02:02:19.000Z

2022-03-31T12:06:21.000Z

import abc from typing import Dict, Callable import tensorflow as tf from flink_ml_framework.context import Context from flink_ml_framework.java_file import * from ..runner import tf_helper, io_helper from ..runner.output_writer import DirectOutputWriter try: from flink_ml_tensorflow.tensorflow_context import TF...

36.867769

110

0.647837

546

4,461

5.007326

0.302198

0.043892

0.05267

0.03109

0.13899

0.110461

0.03365

0

0.007268

0.259807

4,461

120

111

37.175

0.820715

0.091011

0

0.082353

0

0.079531

0.012715

0

1

0.070588

false

0.023529

0.141176

0.011765

0.258824

0.058824

0

null

0

null

0

1

0

54f164400ecea40c3dfdfcd5317d3f9f381a79ff

12,450

py

Python

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

1

2021-03-25T01:21:19.000Z

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

null

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

null

import pytest ENCODING = 'utf-8' @pytest.fixture(scope='function', autouse=True) def setup_case(request): def destroy_case(): from corm import annihilate_keyspace_tables, SESSIONS annihilate_keyspace_tables('mykeyspace') for keyspace_name, session in SESSIONS.copy().items(): if...

29.294118

110

0.67245

1,402

12,450

5.767475

0.13766

0.034628

0.027702

0.040811

0.538214

0.51348

0.466362

0.433094

0.421222

0.376824

0

0.011997

0.23004

12,450

424

111

29.363208

0.831525

0.029317

0

0.473016

0

0.06766

0.008696

0

0.002358

0.095238

1

0.053968

false

0.003175

0.168254

0

0.492063

0

null

0

null

0

1

0

54f3bbb19576152c565203e49a32298c3f423ec9

6,337

py

Python

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

2

2017-12-15T23:10:11.000Z

2018-05-07T04:18:03.000Z

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

1

2018-02-26T06:23:32.000Z

2018-02-27T03:34:01.000Z

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

2

2017-10-19T21:50:24.000Z

2018-01-01T03:40:35.000Z

import json import os from utilities.SaveLoadJson import SaveLoadJson as SLJ from utilities.LineCount import LineCount as LC import subprocess from geolite2 import geolite2 class getData: #Get Data Functions ------------------------------------------------------ @staticmethod def getDATA(): resu...

37.276471

97

0.447373

527

6,337

5.377609

0.254269

0.058222

0.063514

0.06175

0.225476

0.175371

0.117149

0.08892

0

0.014523

0.402399

6,337

169

98

37.497041

0.733826

0.046236

0

0.183206

0

0.121644

0

1

0.053435

false

0

0.045802

0

0.160305

0

null

0

null

0

1

0

54f89b5cd05a9ee6ba8e82764ddc7f2a5b7aea7d

1,689

py

Python

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

37

2020-06-15T02:04:37.000Z

2022-02-09T06:26:42.000Z

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

5

2020-08-06T13:16:34.000Z

2022-02-04T07:29:29.000Z

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

11

2020-09-01T23:08:51.000Z

2022-02-09T06:26:44.000Z

import torch def ndcg_binary_at_k_batch_torch(X_pred, heldout_batch, k=100, device='cpu'): """ Normalized Discounted Cumulative Gain@k for for predictions [B, I] and ground-truth [B, I], with binary relevance. ASSUMPTIONS: all the 0's in heldout_batch indicate 0 relevance. """ batch_users = X_pre...

44.447368

118

0.674956

271

1,689

3.9631

0.284133

0.055866

0.05121

0.024209

0.284916

0.251397

0.16946

0.122905

0.063315

0

0.020231

0.18058

1,689

37

119

45.648649

0.75578

0.184725

0

0.16

0

0.002242

0

1

0.08

false

0

0.04

0

0.2

0

null

0

null

0

1

0

54f8ec657caa5b90b66baca8ce435c82f8e1413e

5,029

py

Python

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

172

2019-12-18T22:19:42.000Z

2022-03-29T01:58:25.000Z

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

165

2020-01-10T19:05:16.000Z

2022-03-31T16:08:36.000Z

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

80

2019-12-20T00:01:43.000Z

2022-03-29T16:20:10.000Z

# All credit to https://stackoverflow.com/questions/46571448/tkinter-and-a-html-file - thanks DELICA - https://stackoverflow.com/users/7027346/delica from cefpython3 import cefpython as cef import ctypes try: import tkinter as tk from tkinter import messagebox except ImportError: import Tkinter as tk impo...

30.478788

149

0.644064

596

5,029

5.263423

0.342282

0.084157

0.02869

0.035065

0.079056

0.042078

0

0.015686

0.239411

5,029

164

150

30.664634

0.804444

0.096838

0

0.07563

0

0.101041

0.026811

0

0.001329

0.006098

0.016807

1

0.134454

false

0

0.07563

0

0.268908

0

null

0

null

0

1

0

54fb3d7c53a19a5375f0b43976b42347774b6cca

1,010

py

Python

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

import re def do_substitution(in_lines): lines_iter = iter(in_lines) defn_lines = [] while True: try: line = lines_iter.next() except StopIteration: raise RuntimeError("didn't find line starting with ---") if line.startswith('---'): break e...

25.897436

68

0.581188

135

1,010

4.192593

0.481481

0.061837

0.056537

0.074205

0

0.004138

0.282178

1,010

38

69

26.578947

0.776552

0

0.059406

0

1

0.030303

false

0

0.090909

0

0.151515

0

null

0

null

0

1

0

54fcf0226ece66aeec4bb6bba4646c87e745e2e5

799

py

Python

hilton_sign_in.py

bmintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-12T10:33:13.000Z

2019-02-24T05:01:40.000Z

hilton_sign_in.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

null

hilton_sign_in.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-24T08:16:59.000Z

2019-02-24T04:41:30.000Z

#!/usr/bin/env python3 # encoding: utf-8 import sys import urllib.parse import selenium.webdriver def exit(): driver.quit() sys.exit(0) driver = selenium.webdriver.Firefox() # for some reason, detectportal.firefox.com and connectivitycheck.gstatic.com are not blocked # therefore, they cannot be used to detect con...

30.730769

93

0.779725

119

799

5.07563

0.630252

0.066225

0.112583

0.125828

0.241722

0.192053

0.125828

0

0.006859

0.08761

799

25

94

31.96

0.821674

0.310388

0

0.133333

0

0.208791

0.045788

0

1

0.066667

false

0

0.2

0

0.266667

0

null

0

null

0

1

0

54fd38f1410793bf1398c7ca975380689133f595

1,539

py

Python

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

null

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

null

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

1

2019-09-01T04:15:21.000Z

#!/usr/bin/env python import os from collections import OrderedDict import cPickle as pickle import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec from matplotlib.cm import get_cmap from matplotlib import style from scipy import stats from scipy import integrate ...

23.676923

83

0.684211

219

1,539

4.666667

0.420091

0.039139

0.054795

0.07045

0

0.020717

0.184535

1,539

64

84

24.046875

0.793626

0.066277

0

0.05

0

0.101257

0.046089

0

1

0.05

false

0

0.275

0

0.375

0

null

0

null

0

1

0

54fe1eee5bca5dc248b6bf225d479bd8fc671965

1,041

py

Python

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

#!/usr/local/bin/python2.7 from flask import Flask import sys from flask_frozen import Freezer from upload_s3 import set_metadata from config import AWS_DIRECTORY app = Flask(__name__) app.config.from_object('config') from views import * # Serving from s3 leads to some complications in how static files are served i...

24.209302

76

0.668588

142

1,041

4.640845

0.450704

0.053111

0.060698

0.036419

0.039454

0

0.01107

0.21902

1,041

42

77

24.785714

0.799508

0.096061

0

0.066667

0

0.057508

0

1

0.066667

false

0

0.2

0

0.333333

0

null

0

null

0

1

0

07010f1430c53be8c3d42e4a620d3fc295e28964

1,799

py

Python

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

1

2021-06-05T08:30:21.000Z

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

null

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

null

#!/usr/bin/python from setup import * payload = open(sys.argv[1], "rb").read() dtb = open(sys.argv[2], "rb").read() if len(sys.argv) > 3: initramfs = open(sys.argv[3], "rb").read() initramfs_size = len(initramfs) else: initramfs = None initramfs_size = 0 compressed_size = len(payload) compressed_addr...

24.310811

114

0.721512

269

1,799

4.635688

0.301115

0.096231

0.076985

0.067362

0.110666

0.070569

0

0.027724

0.137854

1,799

73

115

24.643836

0.776273

0.111173

0

0.128607

0

0.006901

0

0.022727

1

0

false

0

0.022727

0

0.022727

0.227273

0

null

0

null

0

1

0

07027cec6982fe1f9197878d8796ee05b6d45b5e

1,313

py

Python

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

1

2021-06-29T03:41:27.000Z

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

null

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

1

2021-06-18T05:36:28.000Z

import json import os import multiprocessing import struct import importlib from socketserver import TCPServer, StreamRequestHandler def plugin_module_import(name): try: return importlib.import_module(name) except ModuleNotFoundError as e: prompt = 'plugin {} not found, please install it first...

31.261905

79

0.657273

140

1,313

6.035714

0.478571

0.028402

0.042604

0

0.002947

0.224676

1,313

41

80

32.02439

0.827112

0

0.113481

0

1

0.121212

false

0

0.272727

0

0.484848

0

null

0

null

0

1

0

0703c45ad1851ac29ed524b5ee1616259ba14bdb

537

py

Python

pytorch_utils/collection_utils.py

c-hofer/pytorch_utils

55278272690937ff1180c8d549bc866a63a5ac51

[ "MIT" ]

null

pytorch_utils/collection_utils.py

c-hofer/pytorch_utils

55278272690937ff1180c8d549bc866a63a5ac51

[ "MIT" ]

null

pytorch_utils/collection_utils.py

c-hofer/pytorch_utils

55278272690937ff1180c8d549bc866a63a5ac51

[ "MIT" ]

null

def keychain_value_iter(d, key_chain=None, allowed_values=None): key_chain = [] if key_chain is None else list(key_chain).copy() if not isinstance(d, dict): if allowed_values is not None: assert isinstance(d, allowed_values), 'Value needs to be of type {}!'.format( allowed_v...

38.357143

89

0.588454

72

537

4.166667

0.444444

0.16

0.113333

0

0.324022

537

14

90

38.357143

0.826446

0

0.053903

0

0.076923

1

0.076923

false

0

0.076923

0

null

0

null

0

1

0

070792428b154808490c0fc141036d69c221ccfb

2,981

py

Python

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

4,258

2015-01-04T22:06:10.000Z

2022-03-31T23:40:27.000Z

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

1,013

2015-01-12T02:31:03.000Z

2021-09-16T19:09:03.000Z

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

965

2015-01-11T21:06:07.000Z

2022-03-17T16:53:57.000Z

# 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, software # ...

37.2625

115

0.614223

334

2,981

5.353293

0.47006

0.033557

0.014541

0.017897

0

0.004632

0.275746

2,981

79

116

37.734177

0.823529

0.300235

0

0.175872

0.07655

0

1

0.116279

false

0

0.069767

0.023256

0.395349

0

null

0

null

0

1

0

07092a144b2a5c13ba5ef9b78acec4dd39f5a15b

4,840

py

Python

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

1

2017-10-31T21:02:59.000Z

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

null

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

null

import re import astrodata from astrodata import (astro_data_tag, TagSet, astro_data_descriptor, returns_list) from astrodata.fits import FitsLoader, FitsProvider from ..soar import AstroDataSOAR class AstroDataSAMI(AstroDataSOAR): __keyword_dict = dict(data_section='DATASEC', gain='GAIN'...

33.846154

79

0.590083

612

4,840

4.576797

0.320261

0.038558

0.064263

0.052481

0.262406

0.209568

0.165655

0.131382

0.079971

0

0.004763

0.305992

4,840

143

80

33.846154

0.829116

0.35186

0

0.151515

0

0.097991

0

1

0.19697

false

0

0.075758

0.030303

0.484848

0

null

0

null

0

1

0

070a2f74e288d9e0f7d67adf9e2e415a8758caa2

1,957

py

Python

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

17

2020-07-29T11:08:19.000Z

2021-01-07T11:23:33.000Z

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

5

2020-08-04T02:51:39.000Z

2020-08-21T03:44:08.000Z

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

null

import os, sys import numpy as np import cv2 import random import torch from configs import Config from kernelGAN import KernelGAN from data import DataGenerator from learner import Learner import tqdm DATA_LOC = "/mnt/data/NTIRE2020/realSR/track2" # "/mnt/data/NTIRE2020/realSR/track1" DATA_X = "DPEDiphone-tr-x" # ...

30.107692

130

0.654573

294

1,957

4.156463

0.329932

0.03928

0.0491

0.06874

0.201309

0.141571

0.090835

0

0.014678

0.199285

1,957

64

131

30.578125

0.765156

0.048033

0

0.095315

0.017771

0

1

0.038462

false

0

0.192308

0

0.25

0.019231

0

null

0

null

0

1

0

070dfc39dd180a0fc71b0110b529e2e8beee6cea

10,971

py

Python

python/zzz/v1-all_feat_cnn/components/features.py

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

1

2019-09-03T13:38:08.000Z

python/zzz/v1-all_feat_cnn/components/features.py

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

null

python/zzz/v1-all_feat_cnn/components/features.py

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

null

from abc import * import numpy as np ########################################################### class AbstractFeatureExtractor(object): @abstractmethod def extract(self, object): return ########################################################### class EntityFeatureExtractor(AbstractFeatureExtractor...

44.417004

120

0.668854

1,420

10,971

4.93662

0.107042

0.03495

0.046362

0.055777

0.385307

0.324964

0.25321

0.203852

0.189301

0.161626

0

0.009853

0.232158

10,971

246

121

44.597561

0.822293

0.090329

0

0.052326

0

0.000821

0

1

0.127907

false

0

0.011628

0.034884

0.284884

0

null

0

null

0

1

0

071099c9cb76fe44fe601d2109b5cad6021d0a3d

2,420

py

Python

_ar/masking_provement.py

TomKingsfordUoA/ResidualMaskingNetwork

6ce5ddf70f8ac8f1e6da2746b0bbeb9e457ceb7d

[ "MIT" ]

242

2020-01-09T11:06:21.000Z

2022-03-26T14:51:48.000Z

_ar/masking_provement.py

huyhnueit68/ResidualMaskingNetwork

b77abb6e548b9a09b5c96b1592d71332b45d050e

[ "MIT" ]

33

2020-01-09T08:42:10.000Z

2022-03-23T07:52:56.000Z

_ar/masking_provement.py

huyhnueit68/ResidualMaskingNetwork

b77abb6e548b9a09b5c96b1592d71332b45d050e

[ "MIT" ]

61

2020-01-19T02:20:37.000Z

2022-03-25T13:08:48.000Z

import os import glob import cv2 import numpy as np import torch from torchvision.transforms import transforms from natsort import natsorted from models import resmasking_dropout1 from utils.datasets.fer2013dataset import EMOTION_DICT from barez import show transform = transforms.Compose( [ transforms.ToPI...

26.021505

85

0.647934

343

2,420

4.457726

0.344023

0.014388

0.034009

0.010464

0.153695

0.064748

0.043165

0

0.057903

0.207851

2,420

92

86

26.304348

0.739697

0.183471

0

0.061538

0

0.064796

0.063265

0

1

0.015385

false

0

0.153846

0

0.184615

0.015385

0

null

0

null

0

1

0

07112b5b2ca5ebda12c4c78461b67e41243aa4a8

1,727

py

Python

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

1

2022-03-03T23:19:57.000Z

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

null

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

null

import time import colorama def gerenciador_de_pagamento(): preço = float(str(input('Preço das compras: R$'))) print('''Escolha de pagamento: [ 1 ]A vista dinheiro/cheque: 10% de desconto. [ 2 ]A vista no cartão: 5% de desconto. [ 3 ]Em até duas 2x no cartão: preço formal. [ 4 ]3x ou mais no car...

38.377778

105

0.59062

237

1,727

4.278481

0.341772

0.04142

0.043393

0.063116

0.2357

0.195266

0.149901

0

0.038613

0.2652

1,727

44

106

39.25

0.760441

0

0.119048

0

0.047619

0.522319

0

1

0.02381

false

0.02381

0.047619

0

0.095238

0.309524

0

null

0

null

0

1

0

0714065ddc085782b982ec392f121b65f95bc048

911

py

Python

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

429

2015-01-06T18:44:20.000Z

2022-03-19T22:22:11.000Z

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

254

2015-01-01T18:11:57.000Z

2022-03-22T09:55:51.000Z

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

102

2015-01-17T11:41:16.000Z

2022-02-24T23:47:30.000Z

""" wrapper for ccmake command line tool """ import subprocess name = 'ccmake' platforms = ['linux', 'osx'] optional = True not_found = "required for 'fips config' functionality" #------------------------------------------------------------------------------- def check_exists(fips_dir) : """test if ccmake is in t...

26.794118

80

0.535675

93

911

5.172043

0.602151

0.049896

0.04158

0.049896

0.079002

0

0.001376

0.201976

911

33

81

27.606061

0.660248

0.453348

0

0.170732

0

1

0.142857

false

0

0.071429

0

0.428571

0

null

0

null

0

1

0

07167e515430a27837434e8e166dc173dffdcc37

1,914

py

Python

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

from Test import Test, Test as test ''' Complete the solution so that it strips all text that follows any of a set of comment markers passed in. Any whitespace at the end of the line should also be stripped out. Example: Given an input string of: apples, pears # and bananas grapes bananas !apples The output expecte...

31.9

171

0.640021

273

1,914

4.47619

0.384615

0.05401

0.03437

0.051555

0.104746

0.081833

0

0.001341

0.221003

1,914

59

172

32.440678

0.818243

0.143678

0

0.346154

0

0.198055

0.040672

0

0.115385

1

0.115385

false

0

0.038462

0

0.269231

0

null

0

null

0

1

0

0718f25c782fcd74f5e9c8f0ae638c3321dd5b08

6,221

py

Python

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

5

2020-09-09T09:44:31.000Z

2021-07-02T09:49:21.000Z

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

null

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

3

2020-07-10T17:51:47.000Z

2021-04-13T16:33:44.000Z

# -*- coding: utf-8 -*- """ 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, Versi...

37.70303

96

0.649735

758

6,221

5.24934

0.201847

0.030158

0.019603

0.03619

0.476502

0.463433

0.403368

0.353606

0.339533

0.306358

0

0.003289

0.266999

6,221

164

97

37.932927

0.869298

0.307185

0

0.536842

0

0.008219

0

0.010526

1

0.031579

false

0

0.042105

0

0.147368

0

null

0

null

0

1

0

0719b950e4a48282eaf1194cb80f0583e44f000f

2,061

py

Python

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

# Authors: Robert Luke <mail@robertluke.net> # # License: BSD (3-clause) import numpy as np from mne import Annotations, create_info from mne.io import RawArray def simulate_nirs_raw(sfreq=3., amplitude=1., sig_dur=300., stim_dur=5., isi_min=15., isi_max=45.): """ ...

29.442857

78

0.606016

251

2,061

4.828685

0.454183

0.044554

0.018152

0.021452

0.151815

0.108911

0.070957

0

0.011822

0.30228

2,061

69

79

29.869565

0.831015

0.327511

0

0.036378

0

1

0.033333

false

0

0.166667

0

0.233333

0

null

0

null

0

1

0

071b7fe4a170335142cb957704dfc31f09df575c

1,125

py

Python

FeView/pstaticwidget.py

motiurce/FeView

8897b37062be88dd5ead2c8524f6b3b73451e25d

[ "MIT" ]

10

2021-04-09T02:32:23.000Z

2022-03-12T15:21:41.000Z

FeView/pstaticwidget.py

ElsevierSoftwareX/SOFTX-D-21-00063

50eca2a003e6281dea3f1cf43fee221b61f53978

[ "MIT" ]

2

2021-08-07T09:02:21.000Z

2022-02-25T09:30:22.000Z

FeView/pstaticwidget.py

motiurce/FeView

8897b37062be88dd5ead2c8524f6b3b73451e25d

[ "MIT" ]

7

2021-04-09T02:32:25.000Z

2022-03-12T15:21:45.000Z

from PyQt5.QtWidgets import * from matplotlib.backends.backend_qt5agg import FigureCanvas from matplotlib.figure import Figure from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar class PstaticWidget(QWidget): def __init__(self, parent=None): QWidget.__init__(self...

46.875

89

0.728889

133

1,125

5.902256

0.406015

0.101911

0.173248

0.107006

0.254777

0.183439

0

0.023835

0.179556

1,125

24

90

46.875

0.826652

0

0.009066

0

1

0.047619

false

0

0.190476

0

0.285714

0

null

0

null

0

1

0

071b9acd086c7ba6412ea5c6a8e8d3fc44d05f5c

1,719

py

Python

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

import numpy as np from pymoo.core.algorithm import Algorithm from pymoo.core.population import Population from pymoo.util.termination.no_termination import NoTermination from pyallocation.allocation import FastAllocation from pyallocation.problem import AllocationProblem def exhaustively(problem): alloc = FastA...

26.859375

75

0.623618

221

1,719

4.760181

0.357466

0.072243

0.091255

0.076996

0.129278

0.102662

0.041825

0

0.014809

0.253636

1,719

63

76

27.285714

0.805144

0

0.044444

0

0.022222

1

0.133333

false

0

0.133333

0

0.355556

0.022222

0

null

0

null

0

1

0

071ec6aa5cdf0ac5081a189dd02a7abf4954448d

3,571

py

Python

pykrev/formula/find_intersections.py

Kzra/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

4

2021-02-18T10:19:13.000Z

2021-10-04T16:17:30.000Z

pykrev/formula/find_intersections.py

erikafreeman/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

null

pykrev/formula/find_intersections.py

erikafreeman/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

1

2021-09-23T16:03:03.000Z

import itertools import numpy as np import pandas as pd def find_intersections(formula_lists,group_labels,exclusive = True): """ Docstring for function pyKrev.find_intersections ==================== This function compares n lists of molecular formula and outputs a dictionary containing the intersections...

46.376623

143

0.633436

463

3,571

4.794816

0.336933

0.044595

0.031081

0.021622

0

0.008297

0.291235

3,571

77

144

46.376623

0.868827

0.434332

0

0.111111

0

0.027806

0

1

0.044444

false

0.022222

0.066667

0

0.2

0

null

0

null

0

1

0

071ee3300e784ba72ea76c1cd34d240a111eb588

5,386

py

Python

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

import os import glob import shutil from tinytag import TinyTag """ root = 'C:/' copy_to = '/copy to/folder' tag = TinyTag.get('C:/Users/jchap/OneDrive/Pictures/(VERYRAREBOYZ) (feat. $ki Mask The Slump God and Drugz).mp3') print(tag.artist) print('song duration: '+str(tag.duration)) """ f = [] f=glob.gl...

35.668874

133

0.604716

553

5,386

5.858951

0.271248

0.030864

0.044444

0.02963

0.108642

0.094444

0.051235

0

0.003913

0.28834

5,386

151

134

35.668874

0.841378

0.131823

0

0.120879

0

0.073177

0.006958

0

1

0

false

0.010989

0.043956

0

0.043956

0.230769

0

null

0

null

0

1

0

071fd543532fedf42da52e8b37bdf2f56e668e0e

1,636

py

Python

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

#import modules import os import csv #input csvpath = os.path.join('Resources', 'budget_data.csv') #output outfile = os.path.join('Analysis', 'pybankstatements.txt') #declare variables months = []; total_m = 1; net_total = 0; total_change = 0; monthly_changes = []; greatest_inc = ['', 0]; greatest_dec = ['', 0] #open...

28.206897

127

0.621027

224

1,636

4.330357

0.290179

0.079381

0.037113

0.041237

0.098969

0.065979

0

0.019747

0.226161

1,636

58

128

28.206897

0.746446

0.037286

0

0.211465

0.048408

0

1

0

false

0

0.052632

0

0.052632

0

null

0

null

0

1

0

07201c5460a410eeac1f4cdd74f83fabb16f4ba2

3,993

py

Python

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

import random import fire import json import os import numpy as np import tensorflow as tf import pytumblr import mysql.connector import datetime from random import seed import model, sample, encoder def interact_model( model_name='1558M', seed=None, nsamples=1, batch_size=1, length=None, tempe...

30.953488

143

0.599048

471

3,993

4.951168

0.447983

0.038593

0.046312

0.047599

0.070326

0.046312

0

0.008514

0.294015

3,993

128

144

31.195313

0.81873

0.121463

0

0.04902

0

0.092444

0

0.009804

0

0.009804

1

0.009804

false

0.009804

0.107843

0

0.117647

0.098039

0

null

0

null

0

1

0

072173681d53ec2482387460364698d940573600

3,839

py

Python

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

6

2021-01-26T17:22:53.000Z

2022-02-15T10:09:03.000Z

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

5

2020-12-24T14:29:23.000Z

2021-08-10T10:32:18.000Z

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

2

2020-12-24T14:13:39.000Z

2020-12-30T16:48:52.000Z

from rest_framework import serializers from cms.api.serializers import UniCMSContentTypeClass, UniCMSCreateUpdateSerializer from cms.medias.serializers import MediaSerializer from . models import Carousel, CarouselItem, CarouselItemLink, CarouselItemLinkLocalization, CarouselItemLocalization class CarouselForeignK...

35.546296

117

0.657202

328

3,839

7.429878

0.204268

0.040624

0.032007

0.049241

0.551498

0.517029

0.436602

0.399261

0

0.260745

3,839

107

118

35.878505

0.858703

0.013024

0

0.602564

0

0.084016

0.005548

0

1

0.064103

false

0

0.051282

0

0.461538

0

null

0

null

0

1

0

072216b7c95085e52120d7afc6bcf448dd8b5843

7,298

py

Python

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 """ Copyright (c) 2018-2021 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applic...

43.183432

109

0.639216

992

7,298

4.510081

0.298387

0.017211

0.018105

0.034198

0.09924

0.085829

0.075548

0.057667

0

0.021978

0.239381

7,298

168

110

43.440476

0.784003

0.080707

0

0.066667

0

0.152294

0.008071

0

0.016667

1

0.016667

false

0

0.091667

0

0.116667

0

null

0

null

0

1

0

07223524f59210dbb5356506e6de9ffb41f47883

8,174

py

Python

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

# coding: utf-8 """ [AHOI cookbook](/ahoi/docs/cookbook/index.html) [Data Privacy](/sandboxmanager/#/privacy) [Terms of Service](/sandboxmanager/#/terms) [Imprint](https://sparkassen-hub.com/impressum/) © 2016&dash;2017 Starfinanz - Ein Unternehmen der Finanz Informatik # noqa: E501 OpenAPI sp...

28.186207

277

0.565207

1,014

8,174

4.435897

0.162722

0.076478

0.08715

0.084037

0.483993

0.437305

0.417074

0.284349

0.197199

0.11205

0

0.032802

0.332395

8,174

289

278

28.283737

0.791461

0.390751

0

0.073171

0

0.101563

0

1

0.162602

false

0

0.03252

0

0.325203

0.01626

0

null

0

null

0

1

0

07224ff81e97b5ee51932d0d9bca20ab01f96757

10,366

py

Python

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

1

2020-11-30T16:14:02.000Z

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

null

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

null

# Copyright 2015-2017 ARM Limited, Google and contributors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...

38.535316

88

0.644125

1,295

10,366

4.987645

0.255598

0.031584

0.038706

0.041802

0.323115

0.297569

0.264747

0.216752

0.156681

0.129432

0

0.034637

0.267509

10,366

268

89

38.679104

0.816015

0.285067

0

0.262411

0

0.063126

0.002882

0

0.148936

1

0.092199

false

0

0.092199

0

0.198582

0.007092

0

null

0

null

0

1

0

072578f31e8482a3127fc3b417aa642b8388a425

2,343

py

Python

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

6

2021-02-02T23:00:02.000Z

2022-01-13T03:13:51.000Z

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

from __future__ import print_function import argparse import torch import torch.utils.data import matplotlib.pyplot as plt from torch import nn, optim from torch.nn import functional as F from torchvision import datasets, transforms from torchvision.utils import save_image from torch.utils.tensorboard import SummaryWri...

32.09589

83

0.681605

294

2,343

5.285714

0.401361

0.034749

0.054698

0.025097

0.182754

0.063063

0

0.018359

0.20956

2,343

72

84

32.541667

0.820734

0

0.065574

0

0.130231

0

1

0

false

0

0.213115

0

0.213115

0.016393

0

null

0

null

0

1

0

07257aac63bf6240cc82f0f082448d6a6953f3dc

1,567

py

Python

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

31

2017-07-05T07:25:31.000Z

2021-01-18T22:21:57.000Z

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

48

2017-06-27T15:48:29.000Z

2021-01-26T21:02:27.000Z

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

17

2017-07-05T07:25:38.000Z

2021-01-20T14:52:29.000Z

from __future__ import absolute_import, division, print_function from appr.auth import ApprAuth from appr.commands.command_base import CommandBase, PackageSplit class LogoutCmd(CommandBase): name = 'logout' help_message = "logout" def __init__(self, options): super(LogoutCmd, self).__init__(opti...

36.44186

94

0.640077

178

1,567

5.421348

0.410112

0.091192

0.082902

0.039378

0

0.25016

1,567

42

95

37.309524

0.821277

0

0.123165

0.017869

0

1

0.147059

false

0.029412

0.088235

0.058824

0.382353

0.029412

0

null

0

null

0

1

0

072775cafe9ec9921c429b5df6eb75f74e95605d

10,370

py

Python

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

115

2015-01-09T06:18:19.000Z

2021-12-28T07:07:45.000Z

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

47

2015-04-15T20:23:44.000Z

2022-03-22T11:25:01.000Z

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

46

2015-01-26T16:42:10.000Z

2022-01-04T15:26:57.000Z

#!/usr/bin/env python '''tzwhere.py - time zone computation from latitude/longitude. Ordinarily this is loaded as a module and instances of the tzwhere class are instantiated and queried directly ''' import collections try: import ujson as json # loads 2 seconds faster than normal json except: try: i...

39.884615

130

0.610993

985

10,370

6.322843

0.26802

0.009634

0.037091

0.007707

0.189949

0.159602

0.100514

0.086063

0

0.003374

0.314079

10,370

259

131

40.03861

0.872206

0.137608

0

0.176796

0

0.024763

0.005249

0

0.005525

1

0.049724

false

0

0.066298

0

0.19337

0

null

0

null

0

1

0

072aa22d56a355822d78b2d3df97e983fe4fb836

4,783

py

Python

source/statuscodes.py

woody2371/fishbowl-api

f34ff9267436b1278985870fbf19863febdb391b

[ "MIT" ]

6

2016-04-26T01:24:21.000Z

2021-05-13T07:48:15.000Z

source/statuscodes.py

USDev01/fishbowl-api

4d47e20d3385d5ebc001feec44aad321467a6d92

[ "MIT" ]

3

2015-10-29T21:34:39.000Z

2021-11-08T15:22:30.000Z

source/statuscodes.py

USDev01/fishbowl-api

4d47e20d3385d5ebc001feec44aad321467a6d92

[ "MIT" ]

12

2015-02-20T08:21:05.000Z

2021-11-06T22:27:04.000Z

#!/usr/bin/python # -*- coding: utf-8 -*- def getstatus(code): if code == "1000": value = "Success!" elif code == "1001": value = "Unknown Message Received" elif code == "1002": value = "Connection to Fishbowl Server was lost" elif code == "1003": value = "Some Requests ...

37.367188

177

0.572653

596

4,783

4.595638

0.357383

0.172326

0.029573

0.035049

0.117196

0.045272

0.026287

0

0.076739

0.30253

4,783

127

178

37.661417

0.744305

0.007945

0

0.016129

0.480287

0

1

0.008065

false

0.016129

0.024194

0

0.040323

0

null

0

null

0

1

0

072b648fd224e151f6b9509016ac18b01f0c89c9

2,383

py

Python

preinstall_setup/makedeb-11.0.1-1-stable/src/makedeb/utils/missing_apt_dependencies.py

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

preinstall_setup/makedeb-11.0.1-1-stable/src/makedeb/utils/missing_apt_dependencies.py

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

preinstall_setup/makedeb-11.0.1-1-stable/src/makedeb/utils/missing_apt_dependencies.py

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 import apt_pkg import sys from apt_pkg import CURSTATE_INSTALLED, version_compare from operator import lt, le, eq, ge, gt # Function mappings for relationship operators. relation_operators = {"<<": lt, "<=": le, "=": eq, ">=": ge, ">>": gt} # Set up APT cache. apt_pkg.init() cache = apt_pkg.Ca...

29.419753

118

0.661771

295

2,383

5.145763

0.342373

0.144928

0.065876

0.057312

0.081686

0.068511

0

0.004474

0.249685

2,383

80

119

29.7875

0.844519

0.206462

0

0.115385

0

0.038237

0.018056

0

1

0

false

0

0.076923

0

0.076923

0.019231

0

null

0

null

0

1

0

072cc767332977c77810de1909be8f9a35cce2f6

3,784

py

Python

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

null

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

1

2020-09-08T11:10:53.000Z

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

null

from django.contrib.auth.mixins import LoginRequiredMixin from django.views.generic.edit import CreateView, UpdateView, DeleteView from django.views.generic import DetailView, ListView from projects.models import Project from status.models import Status from .models import Task from .forms import TaskForm, FilterForm ...

31.798319

79

0.636628

421

3,784

5.534442

0.220903

0.037768

0.036481

0.027039

0.239056

0.169957

0.111588

0.054936

0

0.252907

3,784

118

80

32.067797

0.824195

0

0.268041

0

0.081395

0.011628

0

1

0.082474

false

0

0.072165

0

0.463918

0

null

0

null

0

1

0

072d2f9675748ff1a2131801c4afa2c1d8506223

2,083

py

Python

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

import os import math import time import geohash import geojson from geojson import MultiLineString from shapely import geometry import shapefile import numpy import datetime as dt import pandas as pd import logging logger = logging.getLogger(__name__) source_shape_file_path = "C:/temp/2018/" threshold = 60*60 cols = ...

45.282609

133

0.610178

275

2,083

4.396364

0.334545

0.06617

0.049628

0.062862

0.332506

0.263027

0.168734

0.079404

0

0.023889

0.276524

2,083

46

134

45.282609

0.778368

0.037446

0

0.086327

0

1

0

false

0

0.3

0

0.3

0

null

0

null

0

1

0

072d38a7e1316c182e6d46a18839cb0047e95249

3,965

py

Python

notes/OOBall/OOBall/main-demo.py

KRHS-GameProgramming-2015/Manpac

959bf7f5195a4edb528fbbf25b8896fcb28d5327

[ "BSD-2-Clause" ]

null

notes/OOBall/OOBall/main-demo.py

KRHS-GameProgramming-2015/Manpac

959bf7f5195a4edb528fbbf25b8896fcb28d5327

[ "BSD-2-Clause" ]

3

2016-01-19T17:26:16.000Z

2016-02-10T16:59:25.000Z

notes/OOBall/main-demo.py

KRHS-GameProgramming-2015/Manpac

959bf7f5195a4edb528fbbf25b8896fcb28d5327

[ "BSD-2-Clause" ]

null

import pygame_sdl2 pygame_sdl2.import_as_pygame() import pygame import os import random import math from Ball import Ball def save_state(balls): """ Saves the game state. """ stateString = "" with open("state.txt", "w") as f: for ball in balls: stateString += "{} {} {} {} {}".f...

28.941606

89

0.49256

427

3,965

4.498829

0.379391

0.01874

0.021864

0.086934

0.043207

0

0.028145

0.408575

3,965

136

90

29.154412

0.791045

0.097604

0

0.138298

0

0.025092

0

1

0.042553

false

0

0.074468

0

0.138298

0

null

0

null

0

1

0

072ddb9bbab8925228b0922af5e12f46301684b7

6,408

py

Python

sprt.py

vdbergh/pentanomial

d046e74acde3f961c7afd22fc4f82fa5aeb4c0fd

[ "MIT" ]

3

2020-02-05T12:39:59.000Z

2021-01-04T15:41:40.000Z

sprt.py

vdbergh/pentanomial

d046e74acde3f961c7afd22fc4f82fa5aeb4c0fd

[ "MIT" ]

2

2020-02-17T20:09:56.000Z

2021-11-21T12:47:33.000Z

sprt.py

vdbergh/pentanomial

d046e74acde3f961c7afd22fc4f82fa5aeb4c0fd

[ "MIT" ]

null

from __future__ import division import math, copy import argparse from brownian import Brownian import scipy import LLRcalc class sprt: def __init__(self, alpha=0.05, beta=0.05, elo0=0, elo1=5, elo_model="logistic"): assert elo_model in ("logistic", "normalized") self.elo_model = elo_model ...

33.726316

85

0.523096

821

6,408

3.970767

0.239951

0.039264

0.036503

0.020859

0.157669

0.096933

0.07362

0.030675

0

0.037343

0.339732

6,408

189

86

33.904762

0.73316

0.082553

0

0.089172

0

0.149307

0

0.019108

1

0.044586

false

0

0.038217

0

0.146497

0.095541

0

null

0

null

0

1

0

072e395e8cbf167e556a1f0e76894f388e49246e

17,956

py

Python

tools/hci_throughput/hci.py

t3zeng/mynewt-nimble

e910132947d6b3cd61ef4732867382634178aa08

[ "Apache-2.0" ]

null

tools/hci_throughput/hci.py

t3zeng/mynewt-nimble

e910132947d6b3cd61ef4732867382634178aa08

[ "Apache-2.0" ]

null

tools/hci_throughput/hci.py

t3zeng/mynewt-nimble

e910132947d6b3cd61ef4732867382634178aa08

[ "Apache-2.0" ]

null

# # 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...

29.630363

80

0.695868

2,576

17,956

4.428183

0.117236

0.012273

0.014728

0.030245

0.467432

0.371263

0.3312

0.304199

0.272903

0.250022

0

0.028414

0.219926

17,956

605

81

29.679339

0.785964

0.047783

0

0.409664

0

0.009939

0

0.012542

0

1

0.107143

false

0

0.008403

0.004202

0.407563

0

null

0

null

0

1

0

072e3ac42c4ae28edac6abdd5c5b9e36d1f69c84

1,253

py

Python

examples/dataproc/query.py

populationgenomics/analysis-runner

f42bedb1dc430a813350fb4b5514bcc7b845f0fc

[ "MIT" ]

null

examples/dataproc/query.py

populationgenomics/analysis-runner

f42bedb1dc430a813350fb4b5514bcc7b845f0fc

[ "MIT" ]

51

2021-01-26T07:09:54.000Z

2022-03-29T03:44:01.000Z

examples/dataproc/query.py

populationgenomics/analysis-runner

f42bedb1dc430a813350fb4b5514bcc7b845f0fc

[ "MIT" ]

2

2021-12-07T17:12:07.000Z

2022-03-23T00:50:44.000Z

"""Simple Hail query example.""" import click import hail as hl from bokeh.io.export import get_screenshot_as_png from analysis_runner import output_path GNOMAD_HGDP_1KG_MT = ( 'gs://gcp-public-data--gnomad/release/3.1/mt/genomes/' 'gnomad.genomes.v3.1.hgdp_1kg_subset_dense.mt' ) @click.command() @click.op...

30.560976

81

0.695132

194

1,253

4.175258

0.463918

0.069136

0.059259

0.044444

0.064198

0

0.016537

0.179569

1,253

40

82

31.325

0.771401

0.073424

0

0.171304

0.083478

0

1

0.035714

false

0

0.142857

0

0.178571

0

null

0

null

0

1

0

072e6fc797520341c47d9f0dd007069870cb1147

17,420

py

Python

ptpip/ptpip.py

darkarnium/ptpip

c54eed4d7509ecfc6973a00496a9e80fb7473fa2

[ "Apache-2.0" ]

null

ptpip/ptpip.py

darkarnium/ptpip

c54eed4d7509ecfc6973a00496a9e80fb7473fa2

[ "Apache-2.0" ]

null

ptpip/ptpip.py

darkarnium/ptpip

c54eed4d7509ecfc6973a00496a9e80fb7473fa2

[ "Apache-2.0" ]

null

import uuid import time import socket import struct class PtpIpConnection(object): """docstring for PtpIP""" def __init__(self): super(PtpIpConnection, self).__init__() self.session = None self.session_events = None self.session_id = None self.cmd_queue = [] se...

34.701195

99

0.644259

1,991

17,420

5.457559

0.220994

0.055678

0.044174

0.016749

0.361495

0.32818

0.298086

0.259249

0.246825

0.233757

0

0.054413

0.268886

17,420

501

100

34.770459

0.798759

0.231745

0

0.274368

0

0.023696

0.004833

0

0.007639

0.001996

0

1

0.115523

false

0.00722

0.01444

0.263538

0.021661

0

null

0

null

0

1

0

072f5247503c271ee10d989b45781d7bce312d75

19,888

py

Python

tensorflow/python/compiler/tensorrt/model_tests/model_handler.py

sboshin/tensorflow

77689016fb4c1373abeca36360f7b2dd9434c547

[ "Apache-2.0" ]

null

tensorflow/python/compiler/tensorrt/model_tests/model_handler.py

sboshin/tensorflow

77689016fb4c1373abeca36360f7b2dd9434c547

[ "Apache-2.0" ]

88

2020-11-24T08:18:10.000Z

2022-03-25T20:28:30.000Z

tensorflow/python/compiler/tensorrt/model_tests/model_handler.py

sboshin/tensorflow

77689016fb4c1373abeca36360f7b2dd9434c547

[ "Apache-2.0" ]

1

2020-12-18T08:51:32.000Z

# Copyright 2020 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...

38.026769

86

0.71611

2,473

19,888

5.446826

0.140315

0.046028

0.03801

0.027765

0.552116

0.451596

0.409577

0.384558

0.363029

0.341203

0

0.006251

0.195646

19,888

522

87

38.099617

0.835782

0.150342

0

0.372283

0

0.043089

0.0015

0

1

0.130435

false

0

0.070652

0.05163

0.342391

0

null

0

null

0

1

0

073032049203bfdc6f84f748cd2128bbc2872806

2,959

py

Python

kpca_iris.py

syamkakarla98/Kernel-PCA-Using-Different-Kernels-With-Classification

03302843bff9b0d87e2983bed1f37bc329e716c1

[ "MIT" ]

10

2018-07-12T11:46:21.000Z

2021-03-13T06:47:01.000Z

kpca_iris.py

syamkakarla98/Kernel-PCA-Using-Different-Kernels-With-Classification

03302843bff9b0d87e2983bed1f37bc329e716c1

[ "MIT" ]

null

kpca_iris.py

syamkakarla98/Kernel-PCA-Using-Different-Kernels-With-Classification

03302843bff9b0d87e2983bed1f37bc329e716c1

[ "MIT" ]

9

2018-09-19T11:57:44.000Z

2021-03-13T06:47:04.000Z

import numpy as np import matplotlib.pyplot as plt import pandas as pd # load dataset into Pandas DataFrame df = pd.read_csv("D:\Python_programs\ML\Iris Data\KPCA\iris.csv") #df.to_csv('iris.csv') from sklearn.preprocessing import StandardScaler features = ['sepal length', 'sepal width', 'petal length', 'petal width...

34.406977

78

0.584657

384

2,959

4.432292

0.385417

0.035253

0.03819

0.039953

0.077556

0.044653

0

0.021375

0.193647

2,959

85

79

34.811765

0.691953

0.224062

0

0.074074

0

0.155673

0.021108

0

1

0.018519

false

0

0.092593

0

0.111111

0

null

0

null

0

1

0

0730d1a99c54c1eeab8095b4f4102da12e701b30

4,704

py

Python

pydbrepo/drivers/sqlite.py

danteay/pydbrepo

665ad5fe64a00697128f9943e0fc831ae485f136

[ "MIT" ]

2

2021-09-03T10:54:01.000Z

2022-01-08T18:48:20.000Z

pydbrepo/drivers/sqlite.py

danteay/pydbrepo

665ad5fe64a00697128f9943e0fc831ae485f136

[ "MIT" ]

null

pydbrepo/drivers/sqlite.py

danteay/pydbrepo

665ad5fe64a00697128f9943e0fc831ae485f136

[ "MIT" ]

1

2021-12-28T17:34:40.000Z

"""SQLite Driver implementation.""" # pylint: disable=R0201 import os import sqlite3 from typing import Any, AnyStr, List, NoReturn, Optional, Tuple from pydbrepo.drivers.driver import Driver class SQLite(Driver): """SQLite Driver connection class. Environment variables: DATABASE_URL: Database fil...

28.682927

99

0.605655

524

4,704

5.276718

0.234733

0.023146

0.01736

0.404702

0.384448

0.347559

0

0.001775

0.281463

4,704

163

100

28.858896

0.816272

0.359694

0

0.323944

0

0.042779

0

1

0.197183

false

0

0.056338

0

0.366197

0

null

0

null

0

1

0

07311f534338364dbf730b4dc400d2a729b73016

3,036

py

Python

Modules/BatchNormND.py

EmilPi/PuzzleLib

31aa0fab3b5e9472b9b9871ca52e4d94ea683fa9

[ "Apache-2.0" ]

52

2020-02-28T20:40:15.000Z

2021-08-25T05:35:17.000Z

Modules/BatchNormND.py

EmilPi/PuzzleLib

31aa0fab3b5e9472b9b9871ca52e4d94ea683fa9

[ "Apache-2.0" ]

2

2021-02-14T15:57:03.000Z

2021-10-05T12:21:34.000Z

Modules/BatchNormND.py

EmilPi/PuzzleLib

31aa0fab3b5e9472b9b9871ca52e4d94ea683fa9

[ "Apache-2.0" ]

8

2020-02-28T20:40:11.000Z

2020-07-09T13:27:23.000Z

import numpy as np from PuzzleLib import Config from PuzzleLib.Backend import gpuarray, Blas from PuzzleLib.Backend.Dnn import batchNormNd, batchNormNdBackward from PuzzleLib.Variable import Variable from PuzzleLib.Modules.Module import ModuleError, Module class BatchNormND(Module): def __init__(self, nd, maps, e...

27.351351

111

0.706522

421

3,036

5.066508

0.251781

0.030005

0.024379

0.048758

0.307548

0.212846

0.152836

0.054384

0

0.010998

0.161397

3,036

110

112

27.6

0.826787

0

0.171053

0

0.051713

0

1

0.105263

false

0

0.078947

0.026316

0.236842

0

null

0

null

0

1

0

0731748ca4b74185c74c8c4352a8260f73831cf9

6,038

py

Python

model/server/server.py

waltzofpearls/reckon

533e47fd05f685024083ce7a823e9c26c35dd824

[ "MIT" ]

8

2019-09-01T12:57:38.000Z

2022-03-25T21:54:19.000Z

model/server/server.py

waltzofpearls/reckon

533e47fd05f685024083ce7a823e9c26c35dd824

[ "MIT" ]

3

2021-08-12T13:18:42.000Z

2022-03-12T00:59:15.000Z

model/server/server.py

waltzofpearls/reckon

533e47fd05f685024083ce7a823e9c26c35dd824

[ "MIT" ]

2

2021-12-22T06:56:56.000Z

2022-03-25T21:58:19.000Z

from concurrent import futures from forecaster.prophet import Forecaster as ProphetForecaster from multiprocessing import Event, Process, cpu_count from pythonjsonlogger import jsonlogger import contextlib import grpc import logging import model.api.forecast_pb2_grpc as grpc_lib import os import signal import socket im...

41.07483

101

0.625704

728

6,038

4.978022

0.287088

0.060706

0.030905

0.038631

0.203918

0.166943

0.085541

0.060706

0.022627

0

0.006806

0.269957

6,038

146

102

41.356164

0.815336

0.05217

0

0.086614

0

0.092405

0.024151

0

1

0.086614

false

0

0.102362

0

0.267717

0

null

0

null

0

1

0

0733497e7a5accdfb3af9d8db6169c656322604e

14,221

py

Python

launchpad/launch/worker_manager.py

LaudateCorpus1/launchpad

6068bbaff9da6d9d520c01314ef920d0d4978afc

[ "Apache-2.0" ]

null

launchpad/launch/worker_manager.py

LaudateCorpus1/launchpad

6068bbaff9da6d9d520c01314ef920d0d4978afc

[ "Apache-2.0" ]

1

2021-10-05T16:06:38.000Z

launchpad/launch/worker_manager.py

LaudateCorpus1/launchpad

6068bbaff9da6d9d520c01314ef920d0d4978afc

[ "Apache-2.0" ]

null

# Copyright 2020 DeepMind Technologies Limited. 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 ...

33.779097

81

0.660713

1,774

14,221

5.071026

0.192221

0.022232

0.026456

0.016674

0.2241

0.16663

0.108382

0.093264

0.060805

0.056247

0

0.002841

0.257507

14,221

420

82

33.859524

0.849133

0.224738

0

0.327586

0

0.038401

0

0.002381

0.010345

1

0.089655

false

0.017241

0.055172

0.003448

0.172414

0.017241

0

null

0

null

0

1

0

07340b73d70dfdc6b284b1403d39e1bbdf13bf8f

1,054

py

Python

mmdeploy/backend/tensorrt/init_plugins.py

hanrui1sensetime/mmdeploy

f2594c624b67910e55e24418832bd96685425b2f

[ "Apache-2.0" ]

1

2021-12-30T06:29:46.000Z

mmdeploy/backend/tensorrt/init_plugins.py

wwjwy/mmdeploy

c6fccd0121618c8c4dc07f49823c377003475040

[ "Apache-2.0" ]

null

mmdeploy/backend/tensorrt/init_plugins.py

wwjwy/mmdeploy

c6fccd0121618c8c4dc07f49823c377003475040

[ "Apache-2.0" ]

1

2022-02-10T04:31:10.000Z

# Copyright (c) OpenMMLab. All rights reserved. import ctypes import glob import logging import os def get_ops_path() -> str: """Get path of the TensorRT plugin library. Returns: str: A path of the TensorRT plugin library. """ wildcard = os.path.abspath( os.path.join( os.p...

26.35

77

0.642315

138

1,054

4.768116

0.42029

0.074468

0.095745

0.051672

0.091185

0

0.002554

0.257116

1,054

39

78

27.025641

0.837803

0.239089

0

0.128105

0.060131

0

1

0.086957

false

0

0.173913

0

0.347826

0

null

0

null

0

1

0

0734297119899a9bd812848f57a6fbe4c63a3822

16,800

py

Python

reagent/test/world_model/test_seq2reward.py

dmitryvinn/ReAgent

f98825b9d021ec353a1f9087840a05fea259bf42

[ "BSD-3-Clause" ]

null

reagent/test/world_model/test_seq2reward.py

dmitryvinn/ReAgent

f98825b9d021ec353a1f9087840a05fea259bf42

[ "BSD-3-Clause" ]

null

reagent/test/world_model/test_seq2reward.py

dmitryvinn/ReAgent

f98825b9d021ec353a1f9087840a05fea259bf42

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. import logging import os import random import unittest from typing import Optional import numpy as np import pytorch_lightning as pl import torch import torch.nn as nn from parameterized import parameterized from reagent.co...

35.66879

88

0.65619

2,080

16,800

4.944712

0.15625

0.028585

0.010695

0.014584

0.430724

0.352747

0.291784

0.26456

0.235002

0.215654

0

0.022562

0.26131

16,800

470

89

35.744681

0.806205

0.070536

0

0.258065

0

0.010441

0

0.002128

0.037634

1

0.043011

false

0

0.061828

0

0.13172

0

null

0

null

0

1

0

0735c43eb0b2d2d58ca5e330e9b0ab738257e5f2

18,432

py

Python

kolibri/core/auth/management/commands/sync.py

reubenjacob/kolibri

028bb2ad63e438c832ff657d37f7b05c3400f2da

[ "MIT" ]

null

kolibri/core/auth/management/commands/sync.py

reubenjacob/kolibri

028bb2ad63e438c832ff657d37f7b05c3400f2da

[ "MIT" ]

8

2021-05-21T15:31:24.000Z

2022-02-24T15:02:14.000Z

kolibri/core/auth/management/commands/sync.py

kuboginichimaru/kolibri

18b398f62baa1c60f8456f7f9c6d6c9447068f69

[ "MIT" ]

1

2019-10-05T11:14:40.000Z

import json import logging import math import re from contextlib import contextmanager from django.core.management import call_command from django.core.management.base import CommandError from morango.models import Filter from morango.models import InstanceIDModel from morango.models import ScopeDefinition from morang...

34.711864

138

0.598307

1,907

18,432

5.53592

0.160986

0.021786

0.017713

0.018187

0.405987

0.341195

0.324903

0.309084

0.296296

0.263427

0

0.002111

0.331923

18,432

530

139

34.777358

0.855205

0.103353

0

0.350877

0

0.002506

0.09992

0.004078

0

1

0.042607

false

0.015038

0.070175

0

0.122807

0

null

0

null

0

1

0

0735ef32022db6fd8f2cae3cf86a392fe7526086

5,787

py

Python

warp.py

RezaFirouzii/fum-delta-vision

0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2

[ "MIT" ]

null

warp.py

RezaFirouzii/fum-delta-vision

0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2

[ "MIT" ]

null

warp.py

RezaFirouzii/fum-delta-vision

0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2

[ "MIT" ]

null

import math import imageio import cv2 as cv import numpy as np import transformer def fix_rotation(img): img_copy = img.copy() img = cv.cvtColor(img, cv.COLOR_BGR2GRAY) rows, cols = img.shape img = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY_INV, 15, 9) kernel = cv.g...

35.286585

122

0.556247

798

5,787

3.922306

0.243108

0.025559

0.01278

0.018211

0.307668

0.260064

0.247923

0

0.057283

0.294107

5,787

164

123

35.286585

0.708935

0.214273

0

0.176471

0

0.021248

0

1

0.009804

false

0

0.04902

0

0.058824

0.009804

0

null

0

null

0

1

0

0736759453528b8e50d3977ed9f783e1f7d2c291

2,318

py

Python

sdssobstools/boss_data.py

sdss/ObserverTools

7f9949341edc91a79dac69d79e24af09e8558ffa

[ "BSD-3-Clause" ]

null

sdssobstools/boss_data.py

sdss/ObserverTools

7f9949341edc91a79dac69d79e24af09e8558ffa

[ "BSD-3-Clause" ]

null

sdssobstools/boss_data.py

sdss/ObserverTools

7f9949341edc91a79dac69d79e24af09e8558ffa

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 """ A tool to grab a single BOSS image and pull a few items from its header. It is used in bin/sloan_log.py, but it could be used directly as well. """ import argparse from pathlib import Path from astropy.time import Time import fitsio class BOSSRaw: """A class to parse raw data from APOG...

34.088235

78

0.603538

303

2,318

4.518152

0.511551

0.021914

0.039445

0.029218

0.122717

0

0.002921

0.261432

2,318

67

79

34.597015

0.796729

0.227351

0

0.086957

0

0.162883

0

1

0.043478

false

0

0.086957

0

0.152174

0.021739

0

null

0

null

0

1

0

0736f9344c10dda2615d756c67d64d15dd48a036

955

py

Python

capitulo-08/ex13b.py

bryan-lima/exercicios-livro-introd-prog-python-3ed

b6bc26dced9728510865704a80cb0d97f81f756b

[ "MIT" ]

3

2021-11-09T17:54:10.000Z

2022-01-30T22:32:25.000Z

capitulo-08/ex13b.py

bryan-lima/exercicios-livro-introd-prog-python-3ed

b6bc26dced9728510865704a80cb0d97f81f756b

[ "MIT" ]

null

capitulo-08/ex13b.py

bryan-lima/exercicios-livro-introd-prog-python-3ed

b6bc26dced9728510865704a80cb0d97f81f756b

[ "MIT" ]

null

# Altere o Programa 8.20 de forma que o usuário tenha três chances de acertar o número # O programa termina se o usuário acertar ou errar três vezes # Programa 8.20 do livro, página 184 # Programa 8.20 - Adivinhando o número # # import random # # n = random.randint(1, 10) # x = int(input('Escolha um número entre 1 e 1...

27.285714

86

0.642932

140

955

4.385714

0.492857

0.039088

0.053746

0.052117

0.055375

0

0.040166

0.243979

955

34

87

28.088235

0.810249

0.393717

0

0.235294

0

0.39469

0

1

0

false

0

0.058824

0

0.058824

0.294118

0

null

0

null

0

1

0

0737de527d56f865ee1256abea29660c8dca454e

894

py

Python

setup.py

shb84/ATM76

433179bde8935abeaf2ace52fe17dedb7a313487

[ "MIT" ]

null

setup.py

shb84/ATM76

433179bde8935abeaf2ace52fe17dedb7a313487

[ "MIT" ]

null

setup.py

shb84/ATM76

433179bde8935abeaf2ace52fe17dedb7a313487

[ "MIT" ]

null

import setuptools # To use a consistent encoding from codecs import open from os import path here = path.abspath(path.dirname(__file__)) with open(path.join(here, 'README.md'), encoding='utf-8') as f: long_description = f.read() setuptools.setup( name="atm76", version="0.1.0", author="Steven H. Berg...

27.9375

63

0.680089

109

894

5.422018

0.706422

0.101523

0.064298

0.101523

0

0.027248

0.178971

894

31

64

28.83871

0.777929

0.03132

0

0.310185

0.02662

0

1

0

false

0

0.115385

0

0.115385

0

null

0

null

0

1

0

073976d41a2a2bee70b7facb5e914072923e6d0f

4,065

py

Python

agent/check_plugins/download_speed.py

indigos33k3r/god-eye

b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76

[ "BSD-3-Clause" ]

1

2019-04-01T01:59:22.000Z

agent/check_plugins/download_speed.py

indigos33k3r/god-eye

b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76

[ "BSD-3-Clause" ]

null

agent/check_plugins/download_speed.py

indigos33k3r/god-eye

b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76

[ "BSD-3-Clause" ]

null

import logging import asyncio from agent.check_plugins import AbstractCheckPlugin # Do khong biet dung thu vien asyncio ntn ca nen em dung thu vien request # python import requests import sys import time from datetime import datetime logger = logging.getLogger(__name__) class Download(AbstractCheckPlugin): @as...

32.007874

116

0.571218

467

4,065

4.813705

0.321199

0.080071

0.019573

0.024021

0.218416

0.160142

0.100534

0.034698

0

0.01518

0.335547

4,065

127

117

32.007874

0.817105

0.294219

0

0.19403

0

0.065749

0

0.007874

0

1

0.074627

false

0

0.104478

0

0.283582

0

null

0

null

0

1

0

073aa245c28c69910b8c705ef18f357b5c9e4c5f

5,846

py

Python

GA/train.py

jcordell/keras-optimization

cbda84bcf3b31928d829af4afc82af1886877341

[ "MIT" ]

1

2017-05-29T13:48:22.000Z

GA/train.py

jcordell/keras-optimization

cbda84bcf3b31928d829af4afc82af1886877341

[ "MIT" ]

null

GA/train.py

jcordell/keras-optimization

cbda84bcf3b31928d829af4afc82af1886877341

[ "MIT" ]

null

""" Utility used by the Network class to actually train. Based on: https://github.com/fchollet/keras/blob/master/examples/mnist_mlp.py """ from keras.datasets import mnist, cifar10 from keras.models import Sequential from keras.layers import Dense, Dropout from keras.utils.np_utils import to_categorical from kera...

33.028249

113

0.653609

849

5,846

4.250883

0.23086

0.030479

0.016625

0.024383

0.455805

0.382377

0.307287

0.259906

0.237739

0

0.030637

0.223914

5,846

176

114

33.215909

0.764823

0.164728

0

0.219298

0

0.085452

0.005002

0

0.005682

0

1

0.04386

false

0

0.078947

0

0.175439

0.026316

0

null

0

null

0

1

0

073cf557d5c1841920fb8cd559522daa79d5440d

3,272

py

Python

ssl_context_builder/http_impl/requests_wrapper/secure_session.py

mbjahnoon/ssl_context_builder

e73530f900b56710c705675e8e657f0bd17f7c07

[ "Apache-2.0" ]

1

2022-03-01T16:27:33.000Z

ssl_context_builder/http_impl/requests_wrapper/secure_session.py

mbjahnoon/ssl_context_builder

e73530f900b56710c705675e8e657f0bd17f7c07

[ "Apache-2.0" ]

null

ssl_context_builder/http_impl/requests_wrapper/secure_session.py

mbjahnoon/ssl_context_builder

e73530f900b56710c705675e8e657f0bd17f7c07

[ "Apache-2.0" ]

null

import weakref import os import requests import ssl from ssl import SSLContext import logging from ssl_context_builder.builder.builder import SslContextBuilder from ssl_context_builder.http_impl.requests_wrapper.ssl_adapter import SslAdapter class RequestsSecureSession: def __init__(self, ssl_context: SSLContex...

34.808511

120

0.637531

415

3,272

4.814458

0.33012

0.075075

0.048048

0.04004

0.171171

0.121121

0.094094

0

0.002136

0.284535

3,272

93

121

35.182796

0.851346

0.225856

0

0.196721

0

0.097304

0.032013

0

1

0.114754

false

0

0.131148

0.016393

0.327869

0

null

0

null

0

1

0

073ddb35cfd257b4fe7bee31f410bb17b18b0611

621

py

Python

tiny_scripts/select_cifar_10.py

jiaqiangwjq/python_workhouse

c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9

[ "Unlicense" ]

null

tiny_scripts/select_cifar_10.py

jiaqiangwjq/python_workhouse

c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9

[ "Unlicense" ]

null

tiny_scripts/select_cifar_10.py

jiaqiangwjq/python_workhouse

c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9

[ "Unlicense" ]

null

''' Selected cifar-10. The .csv file format: class_index,data_index 3,0 8,1 8,2 ... ''' import pickle import pandas as pd file = 'E:\pycharm\LEARN\data\cifar-10\cifar-10-batches-py\\test_batch' with open(file, 'rb') as f: dict = pickle.load(f, encoding='bytes') dict.keys() batch_label = dict[b'batch_label'] ...

18.818182

71

0.710145

105

621

4.057143

0.485714

0.093897

0.098592

0.089202

0

0.025878

0.128824

621

33

72

18.818182

0.761553

0.128824

0

0.0625

0.262664

0.116323

0

1

0

false

0

0.125

0

0.125

0

null

0

null

0

1

0

074082800249cdc23669711e86fb83230db924ee

940

py

Python

codebox/scripts/fixture.py

disqus/codebox

9f8e1a9c08c6a79bf3519782be483ff9763c4b4e

[ "Apache-2.0" ]

5

2015-09-24T19:53:02.000Z

2019-05-14T11:56:07.000Z

codebox/scripts/fixture.py

disqus/codebox

9f8e1a9c08c6a79bf3519782be483ff9763c4b4e

[ "Apache-2.0" ]

null

codebox/scripts/fixture.py

disqus/codebox

9f8e1a9c08c6a79bf3519782be483ff9763c4b4e

[ "Apache-2.0" ]

null

# Ghetto Fixtures from codebox import app from codebox.apps.auth.models import User from codebox.apps.snippets.models import Snippet from codebox.apps.organizations.models import Organization, OrganizationMember from flask import g client = app.test_client() _ctx = app.test_request_context() _ctx.push() app.preproces...

29.375

99

0.75

132

940

5.295455

0.401515

0.130186

0.114449

0.157368

0.25608

0.217454

0

0.009401

0.094681

940

31

100

30.322581

0.811986

0.075532

0

0.1777

0.029036

0

1

0

false

0

0.294118

0

0.294118

0.058824

0

null

0

null

0

1

0

0740a865caa54dd6749985e9ca6d8ad7824f4098

3,062

py

Python

corehq/apps/linked_domain/tests/test_views.py

akashkj/commcare-hq

b00a62336ec26cea1477dfb8c048c548cc462831

[ "BSD-3-Clause" ]

null

corehq/apps/linked_domain/tests/test_views.py

akashkj/commcare-hq

b00a62336ec26cea1477dfb8c048c548cc462831

[ "BSD-3-Clause" ]

null

corehq/apps/linked_domain/tests/test_views.py

akashkj/commcare-hq

b00a62336ec26cea1477dfb8c048c548cc462831

[ "BSD-3-Clause" ]

null

from unittest.mock import Mock, patch from django.test import SimpleTestCase from corehq.apps.domain.exceptions import DomainDoesNotExist from corehq.apps.linked_domain.exceptions import ( DomainLinkAlreadyExists, DomainLinkError, DomainLinkNotAllowed, ) from corehq.apps.linked_domain.views import link_do...

48.603175

112

0.736447

362

3,062

5.89779

0.18232

0.074941

0.112412

0.154567

0.623888

0.59719

0.583138

0.528806

0

0.171457

3,062

62

113

49.387097

0.841545

0

0.22449

0

0.230242

0.224363

0

0.102041

1

0.163265

false

0

0.102041

0.020408

0.306122

0

null

0

null

0

1

0

0740e77524f70aef71e87bb08ca6fba979752644

2,207

py

Python

pyingest/parsers/zenodo.py

golnazads/adsabs-pyingest

37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e

[ "MIT" ]

1

2020-06-04T20:09:03.000Z

pyingest/parsers/zenodo.py

golnazads/adsabs-pyingest

37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e

[ "MIT" ]

81

2017-11-16T16:07:21.000Z

2022-03-08T14:05:37.000Z

pyingest/parsers/zenodo.py

golnazads/adsabs-pyingest

37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e

[ "MIT" ]

17

2016-04-13T17:03:25.000Z

2021-12-22T15:26:54.000Z

#!/usr/bin/python # # from __future__ import absolute_import import json import re import logging from .datacite import DataCiteParser class WrongPublisherException(Exception): pass class ZenodoParser(DataCiteParser): def get_references(self, r): # as of version 3.1 of datacite schema, "References...

30.232877

101

0.566833

266

2,207

4.616541

0.481203

0.009772

0.013029

0.014658

0.035831

0

0.005875

0.305845

2,207

72

102

30.652778

0.795692

0.32986

0

0.055556

0

0.143448

0

1

0.083333

false

0.027778

0.138889

0

0.388889

0

null

0

null

0

1

0

07421cfb41d4ae2f25674d5123c3192c8a85313e

25,223

py

Python

src/fullnode.py

AmeyaDaddikar/vjtichain

2a9b68d475fe5cc2babdf3f5b463a685e8423f05

[ "MIT" ]

1

2019-05-26T12:36:37.000Z

src/fullnode.py

AmeyaDaddikar/vjtichain

2a9b68d475fe5cc2babdf3f5b463a685e8423f05

[ "MIT" ]

null

src/fullnode.py

AmeyaDaddikar/vjtichain

2a9b68d475fe5cc2babdf3f5b463a685e8423f05

[ "MIT" ]

null

import json import time from functools import lru_cache from multiprocessing import Pool, Process from threading import Thread, Timer from typing import Any, Dict, List from datetime import datetime import hashlib import inspect import requests import waitress from bottle import BaseTemplate, Bottle, request, response,...

34.223881

203

0.632082

3,214

25,223

4.80336

0.138768

0.022153

0.02021

0.030768

0.364749

0.294274

0.246858

0.200544

0.152157

0.129097

0

0.011567

0.239107

25,223

736

204

34.27038

0.79283

0.10768

0

0.243446

0

0.001873

0.168754

0.016577

0.011236

0

0.001359

0

1

0.08427

false

0.007491

0.037453

0.007491

0.235955

0

null

0

null

0

1

0

074273af8a268ef926e75f5dce65175c9bfb7048

5,914

py

Python

deepexplain/tf/v1_x/main.py

alexus37/MasterThesisCode

a7eada603686de75968acc8586fd307a91b0491b

[ "MIT" ]

1

2020-04-23T15:39:27.000Z

deepexplain/tf/v1_x/main.py

alexus37/DeepExplain

a7eada603686de75968acc8586fd307a91b0491b

[ "MIT" ]

null

deepexplain/tf/v1_x/main.py

alexus37/DeepExplain

a7eada603686de75968acc8586fd307a91b0491b

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf from tensorflow.python.framework import ops from collections import OrderedDict import warnings, logging from deepexplain.tf.v1_x import constants from deepexplain.tf.v1_x.baseClasses i...

46.566929

153

0.672979

711

5,914

5.369902

0.278481

0.034573

0.057622

0.070718

0.197486

0.102672

0.064955

0.022525

0

0.004706

0.245519

5,914

127

154

46.566929

0.850964

0.101623

0

0.09

0

0.154139

0.00647

0

1

0.08

false

0

0.12

0.01

0.27

0.02

0

null

0

null

0

1

0

074414b6699fea23b4050feee569e12a24d49670

1,457

py

Python

util/mem_usage.py

robinupham/cnn_lensing

f5d4defc7e2c5b7a23744051da904526d04c27c8

[ "MIT" ]

null

util/mem_usage.py

robinupham/cnn_lensing

f5d4defc7e2c5b7a23744051da904526d04c27c8

[ "MIT" ]

null

util/mem_usage.py

robinupham/cnn_lensing

f5d4defc7e2c5b7a23744051da904526d04c27c8

[ "MIT" ]

null

""" Get the memory usage of a Keras model. From https://stackoverflow.com/a/46216013. """ def get_model_memory_usage(batch_size, model): """ Get the memory usage of a Keras model in GB. From https://stackoverflow.com/a/46216013. """ import numpy as np try: from keras import backend a...

30.354167

104

0.649279

210

1,457

4.204762

0.338095

0.05436

0.047565

0.071348

0.353341

0.305776

0.165345

0.097395

0

0.034419

0.262183

1,457

47

105

31

0.786977

0.117364

0

0.015091

0

1

0.032258

false

0

0.129032

0

0.193548

0

null

0

null

0

1

0

0745c582ad840fd55885e6625d498a1f4e1e1d0a

799

py

Python

setup.py

statisticianinstilettos/recommender_metrics

82091ec53eb8b3527f95755006237658deb03c18

[ "MIT" ]

null

setup.py

statisticianinstilettos/recommender_metrics

82091ec53eb8b3527f95755006237658deb03c18

[ "MIT" ]

null

setup.py

statisticianinstilettos/recommender_metrics

82091ec53eb8b3527f95755006237658deb03c18

[ "MIT" ]

null

import io import os from setuptools import setup def read(file_name): """Read a text file and return the content as a string.""" with io.open(os.path.join(os.path.dirname(__file__), file_name), encoding='utf-8') as f: return f.read() setup( name='recmetrics', url='https://gi...

25.774194

73

0.644556

95

799

5.284211

0.694737

0.031873

0

0.00639

0.216521

799

30

74

26.633333

0.795527

0.065081

0

0.318489

0.02834

0

1

0.04

false

0

0.12

0

0.2

0

null

0

null

0

1

0

07461f1a486f88f500aad5210c29f31d3c93dac1

1,174

py

Python

module2-sql-for-analysis/rpg_db.py

TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases

306d2252b3756a501e2412fcb5eddbdebc16a362

[ "MIT" ]

null

module2-sql-for-analysis/rpg_db.py

TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases

306d2252b3756a501e2412fcb5eddbdebc16a362

[ "MIT" ]

null

module2-sql-for-analysis/rpg_db.py

TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases

306d2252b3756a501e2412fcb5eddbdebc16a362

[ "MIT" ]

null

import sqlite3 import os import psycopg2 from dotenv import load_dotenv load_dotenv() DB_NAME2 = os.getenv("DB_NAME3") DB_USER2 = os.getenv("DB_USER3") DB_PASS2 = os.getenv("DB_PASS3") DB_HOST2 = os.getenv("DB_HOST3") conn = psycopg2.connect(dbname=DB_NAME2, user=DB_USER2, ...

22.150943

94

0.698467

154

1,174

5.116883

0.415584

0.040609

0.050761

0.063452

0

0.022317

0.198467

1,174

52

95

22.576923

0.81509

0

0.095238

0

0.374787

0.022147

0

1

0

false

0.047619

0.095238

0

0.095238

0.02381

0

null

0

null

0

1

0

0748c347781432c41ed5dc21b2a78b229eb50e78

24,232

py

Python

sws_comp_wiki_gen.py

moff-wildfire/sws-battlefy

04b12b54f91e450980c2c57eed57f0504abec1bb

[ "Unlicense" ]

1

2021-12-10T01:36:36.000Z

sws_comp_wiki_gen.py

moff-wildfire/sws-battlefy

04b12b54f91e450980c2c57eed57f0504abec1bb

[ "Unlicense" ]

null

sws_comp_wiki_gen.py

moff-wildfire/sws-battlefy

04b12b54f91e450980c2c57eed57f0504abec1bb

[ "Unlicense" ]

null

import battlefy_data import battlefy_wiki_linkings from datetime import datetime from operator import itemgetter from pathlib import Path import calcup_roster_tracking def create_sidebar(data, wiki_name): sidebar = '{{Infobox league' + '\n' sidebar += '|liquipediatier=' + '\n' sidebar += '|name=' + data[...

42.812721

119

0.560333

2,701

24,232

4.818215

0.151425

0.021515

0.011526

0.023974

0.413708

0.337175

0.280237

0.242739

0.194329

0.183495

0

0.020891

0.27897

24,232

565

120

42.888496

0.723958

0.077088

0

0.219731

0

0.004484

0.230966

0.053475

0.06278

0

0.00177

0

1

0.024664

false

0

0.013453

0

0.065022

0.004484

0

null

0

null

0

1

0

074906b7cce1eac2c3d5b9dbf7a25ead70cb372d

11,662

py

Python

training_xgboost_model.py

MighTy-Weaver/Inefficient-AC-detection

8229f19accd1569ba7b48f77f71783173393d9ed

[ "Apache-2.0" ]

2

2021-02-21T13:28:30.000Z

2021-07-10T05:24:05.000Z

training_xgboost_model.py

MighTy-Weaver/Inefficient-AC-detection

8229f19accd1569ba7b48f77f71783173393d9ed

[ "Apache-2.0" ]

null

training_xgboost_model.py

MighTy-Weaver/Inefficient-AC-detection

8229f19accd1569ba7b48f77f71783173393d9ed

[ "Apache-2.0" ]

null

# This is the code to train the xgboost model with cross-validation for each unique room in the dataset. # Models are dumped into ./models and results are dumped into two csv files in the current work directory. import argparse import json import math import os import pickle import warnings from typing import Tuple i...

51.149123

120

0.667038

1,648

11,662

4.509709

0.215413

0.026911

0.038482

0.025565

0.334499

0.294672

0.264801

0.237217

0.213402

0.202637

0

0.015043

0.207683

11,662

227

121

51.374449

0.789286

0.163608

0

0.173077

0

0.177632

0.022307

0

0.012821

1

0.019231

false

0

0.115385

0

0.153846

0.019231

0

null

0

null

0

1

0

0749f9a616656fe35e1c0d2532a8c8a5e40dc4ab

1,042

py

Python

vaping/config.py

josephburnett/vaping

16f9092f0b3c1692e6d1a040f746e1277e197353

[ "Apache-2.0" ]

null

vaping/config.py

josephburnett/vaping

16f9092f0b3c1692e6d1a040f746e1277e197353

[ "Apache-2.0" ]

null

vaping/config.py

josephburnett/vaping

16f9092f0b3c1692e6d1a040f746e1277e197353

[ "Apache-2.0" ]

null

import re import munge def parse_interval(val): """ converts a string to float of seconds .5 = 500ms 90 = 1m30s **Arguments** - val (`str`) """ re_intv = re.compile(r"([\d\.]+)([a-zA-Z]+)") val = val.strip() total = 0.0 for match in re_intv.findall(val): ...

20.84

86

0.46833

115

1,042

4.191304

0.573913

0.103734

0

0.042879

0.373321

1,042

49

87

21.265306

0.695253

0.114203

0

0.159817

0

1

0.033333

false

0

0.066667

0

0.2

0

null

0

null

0

1

0

074c422d6b8b108e68ca3caffc0062b15b80774b

1,333

py

Python

examples/scripts/segmentation/nnet3-segmenter.py

mxmpl/pykaldi

0570307138c5391cc47b019450d08bcb9686dd98

[ "Apache-2.0" ]

916

2017-11-22T19:33:36.000Z

2022-03-31T11:51:58.000Z

examples/scripts/segmentation/nnet3-segmenter.py

mxmpl/pykaldi

0570307138c5391cc47b019450d08bcb9686dd98

[ "Apache-2.0" ]

268

2018-01-16T22:06:45.000Z

2022-03-29T03:24:41.000Z

examples/scripts/segmentation/nnet3-segmenter.py

mxmpl/pykaldi

0570307138c5391cc47b019450d08bcb9686dd98

[ "Apache-2.0" ]

260

2018-01-23T18:39:40.000Z

2022-03-24T08:17:39.000Z

#!/usr/bin/env python from __future__ import print_function from kaldi.segmentation import NnetSAD, SegmentationProcessor from kaldi.nnet3 import NnetSimpleComputationOptions from kaldi.util.table import SequentialMatrixReader # Construct SAD model = NnetSAD.read_model("final.raw") post = NnetSAD.read_average_poster...

37.027778

77

0.775694

177

1,333

5.627119

0.485876

0.11747

0.072289

0.044177

0.118474

0

0.011121

0.123031

1,333

35

78

38.085714

0.84089

0.066017

0

0.038462

0.10556

0.017728

0

1

0

false

0

0.153846

0

0.153846

0

null

0

null

0

1

0

074cdaf58b71e5a0a7b4da96e1a1535d7fb91e4b

987

py

Python

helper_tools/raspi_OMX-Player_Howto_demo.py

stko/Schnipsl

824572c657e48f18950f584b9529661ff5bb8069

[ "MIT" ]

null

helper_tools/raspi_OMX-Player_Howto_demo.py

stko/Schnipsl

824572c657e48f18950f584b9529661ff5bb8069

[ "MIT" ]

29

2020-08-30T15:07:50.000Z

2022-02-19T03:41:26.000Z

helper_tools/raspi_OMX-Player_Howto_demo.py

wifitvbox/Schnipsl

553ce8de3dda26fb92297ad76e92f4a363070e4e

[ "MIT" ]

1

2020-12-28T05:46:17.000Z

#!/usr/bin/python # mp4museum.org by julius schmiedel 2019 import os import sys import glob from subprocess import Popen, PIPE import RPi.GPIO as GPIO FNULL = open(os.devnull, "w") # setup GPIO pin GPIO.setmode(GPIO.BOARD) GPIO.setup(11, GPIO.IN, pull_up_down = GPIO.PUD_DOWN) GPIO.setup(13, GPIO.IN, pull_up_down = ...

25.973684

97

0.73151

152

987

4.684211

0.532895

0.033708

0.02809

0.033708

0.238764

0.160112

0.075843

0

0.02765

0.120567

987

37

98

26.675676

0.792627

0.177305

0

0.095238

0

0.095652

0.027329

0

1

0.095238

false

0

0.238095

0

0.333333

0

null

0

null

0

1

0

074ce069ee533cbcb1f8fc2b612416adfbbf158a

4,549

py

Python

dash_app/compare_alg.py

zeyu2001/ICT1002-Python

76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7

[ "MIT" ]

1

2020-10-31T06:57:01.000Z

dash_app/compare_alg.py

zeyu2001/ICT1002-Python

76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7

[ "MIT" ]

null

dash_app/compare_alg.py

zeyu2001/ICT1002-Python

76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7

[ "MIT" ]

1

2021-12-04T10:02:16.000Z

""" Comparison between the efficiency of the Boyer-Moore algorithm and the naive substring search algorithm. The runtimes for both algorithms are plotted on the same axes. """ import matplotlib.pyplot as plt import numpy as np import string import time import random from bm_alg import boyer_moore_match, naive_match #...

28.254658

104

0.585843

623

4,549

4.130016

0.216693

0.090944

0.04625

0.031092

0.516129

0.506024

0.427517

0.340459

0.31714

0

0.009491

0.305122

4,549

160

105

28.43125

0.804492

0.196747

0

0.43

0

0.131184

0

1

0.04

false

0

0.06

0

0.11

0.09

0

null

0

null

0

1

0

074fa8cb751dc3e01a0d7cf156f12acfd22b5c7b

616

py

Python

TSIS_3/3774.py

GMKanat/PP2_spring

423617d559c5690f689741aaa152b9fee5082baf

[ "MIT" ]

null

TSIS_3/3774.py

GMKanat/PP2_spring

423617d559c5690f689741aaa152b9fee5082baf

[ "MIT" ]

null

TSIS_3/3774.py

GMKanat/PP2_spring

423617d559c5690f689741aaa152b9fee5082baf

[ "MIT" ]

null

ans = dict() pairs = dict() def create_tree(p): if p in ans: return ans[p] else: try: res = 0 if p in pairs: for ch in pairs[p]: res += create_tree(ch) + 1 ans[p] = res return res except: pass...

22.814815

46

0.469156

86

616

3.325581

0.383721

0.097902

0.034965

0

0.013812

0.412338

616

27

47

22.814815

0.776243

0

0.074074

0

1

0.037037

false

0.037037

0

0.111111

0.037037

0

null

0

null

0

1

0

075329f4475d143e6e7eeffda251a30feb1872ce

404

py

Python

italicizer.py

Dorijan-Cirkveni/Miniprojects

2109275c9c1b9f5e7a286604cbb1b7966dff9798

[ "MIT" ]

null

italicizer.py

Dorijan-Cirkveni/Miniprojects

2109275c9c1b9f5e7a286604cbb1b7966dff9798

[ "MIT" ]

null

italicizer.py

Dorijan-Cirkveni/Miniprojects

2109275c9c1b9f5e7a286604cbb1b7966dff9798

[ "MIT" ]

null

def italicize(s): b = False res = '' for e in s: if e == '"': if b: res += '{\\i}' + e else: res += e + '{i}' b=not b else: res += e return res def main(): F=open('test_in.txt','r') X=F.read() F...

15.538462

34

0.368812

50

404

2.8

0.5

0.1

0.114286

0

0.467822

404

25

35

16.16

0.651163

0

0.095238

0

0.071782

0

1

0.095238

false

0

0.190476

0.047619

0

null

0

null

0

1

0