ytzi/the-stack-dedup-python-filtered · Datasets at Hugging Face

426e4afa33488c3f61e9819e1e0e8ab285e730fe

902

py

Python

config.py

rajatomar788/pyblog

d450dc1ceb3a6b3aeb747648a0fb1b4334e4b3ae

[ "MIT" ]

null

config.py

rajatomar788/pyblog

d450dc1ceb3a6b3aeb747648a0fb1b4334e4b3ae

[ "MIT" ]

null

config.py

rajatomar788/pyblog

d450dc1ceb3a6b3aeb747648a0fb1b4334e4b3ae

[ "MIT" ]

null

import os basedir = os.path.abspath(os.path.dirname(__file__))

29.096774

80

0.674058

426e9a71b5a0425ef77735be32bb8398f28a2e1e

45

py

Python

ceefax/fonts/size7extracondensed/__init__.py

mscroggs/CEEFAX

8e7a075de1809064b77360da24ebbbaa409c3bf2

[ "MIT" ]

1

2020-03-28T15:53:22.000Z

ceefax/fonts/size7extracondensed/__init__.py

mscroggs/CEEFAX

8e7a075de1809064b77360da24ebbbaa409c3bf2

[ "MIT" ]

1

2021-02-05T13:43:52.000Z

ceefax/fonts/size7extracondensed/__init__.py

mscroggs/CEEFAX

8e7a075de1809064b77360da24ebbbaa409c3bf2

[ "MIT" ]

null

from .default import size7extracondensedfont

22.5

44

0.888889

426e9a7b517f49d7e52664e4ad563ce95c7c8446

3,433

py

Python

bom/helpers.py

gxyp/indabom

114991be2471eda2cf658c68706ab7bb05b06959

[ "MIT" ]

null

bom/helpers.py

gxyp/indabom

114991be2471eda2cf658c68706ab7bb05b06959

[ "MIT" ]

null

bom/helpers.py

gxyp/indabom

114991be2471eda2cf658c68706ab7bb05b06959

[ "MIT" ]

null

from bom.octopart_parts_match import match_part from bom.models import Part, PartClass, Seller, SellerPart, Subpart, \ Manufacturer, Organization, PartFile

23.040268

77

0.642587

426f6bd9b353f10dd5dac6c8afa818c7319f5d74

8,612

py

Python

keycodes/key/codes/win.py

jonchun/ptoys-mapper

a2dde413d37e897ec41b69ac979e538afb7435f0

[ "MIT" ]

null

keycodes/key/codes/win.py

jonchun/ptoys-mapper

a2dde413d37e897ec41b69ac979e538afb7435f0

[ "MIT" ]

null

keycodes/key/codes/win.py

jonchun/ptoys-mapper

a2dde413d37e897ec41b69ac979e538afb7435f0

[ "MIT" ]

null

# Source: # https://github.com/tpn/winsdk-10/blob/46c66795f49679eb4783377968ce25f6c778285a/Include/10.0.10240.0/um/WinUser.h # # convert all C-style comments to python multi-line string comment # find: (^/\*[\s\S\r]+?\*/) # replace: """\n$1\n""" # # convert all keycode #defines to be python constants # find: #define\s(.+_.+?)\s+([\w]+)(\s*)(/[/*].+)? # replace: $1 = $2$3# $4\n # # clean up results by removing lines with only a single # caused by previous regex # find: ^# $\n # replace: # # clean up duplicate newlines # find: (\s#.+\n)\n # replace: $1 # # clean up multi-line comments. # find: ^(\s{3,})(\S.+) # replace: $1 # $2 from enum import IntEnum

20.407583

114

0.576637

426fdd67326d3cc89802cd8abeba99af022807c1

117

py

Python

application/flicket_errors/__init__.py

abbas0001/flicket

547a5e783cccf157d10df88608440aa2919d7e7b

[ "MIT" ]

null

application/flicket_errors/__init__.py

abbas0001/flicket

547a5e783cccf157d10df88608440aa2919d7e7b

[ "MIT" ]

null

application/flicket_errors/__init__.py

abbas0001/flicket

547a5e783cccf157d10df88608440aa2919d7e7b

[ "MIT" ]

null

#! python3 # -*- coding: utf-8 -*- # from flask import Blueprint bp_errors = Blueprint('flicket-errors', __name__)

14.625

49

0.683761

4270b9f3f72e8e2eb3176ce2f540c1dc258f357c

399

py

Python

SmartBuild/modules/migrations/0003_module_shortcut.py

ampamo/smart-build

a0c9a3871eb7ca06a6cd6d4a15aba70e2291f4fb

[ "CC0-1.0" ]

null

SmartBuild/modules/migrations/0003_module_shortcut.py

ampamo/smart-build

a0c9a3871eb7ca06a6cd6d4a15aba70e2291f4fb

[ "CC0-1.0" ]

null

SmartBuild/modules/migrations/0003_module_shortcut.py

ampamo/smart-build

a0c9a3871eb7ca06a6cd6d4a15aba70e2291f4fb

[ "CC0-1.0" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations

19.95

53

0.601504

4273f06b359f41b03bbac8b02773bc579762c6fd

6,789

py

Python

app/common.py

yxonic/dl-boilerplate

d503716ad514929ddfdc41341e37b0e3f1a1f0f5

[ "MIT" ]

1

2017-09-26T05:13:19.000Z

app/common.py

yxonic/dl-boilerplate

d503716ad514929ddfdc41341e37b0e3f1a1f0f5

[ "MIT" ]

null

app/common.py

yxonic/dl-boilerplate

d503716ad514929ddfdc41341e37b0e3f1a1f0f5

[ "MIT" ]

null

import abc import argparse import logging import pathlib from collections import namedtuple from operator import itemgetter import toml def __str__(self): return str(self.config) def build_model(self): """Build model according to the configurations in current workspace.""" return self.model_cls.build(**self.config) def logger(self, name: str): """Get a logger that logs to a file. Notice that same logger instance is returned for same names. Args: name(str): logger name """ logger = logging.getLogger(name) if logger.handlers: # previously configured, remain unchanged return logger fileFormatter = logging.Formatter('%(levelname)s [%(name)s] ' '%(asctime)s %(message)s', datefmt='%Y-%m-%d %H:%M:%S') fileHandler = logging.FileHandler( str(self.log_path / (name + '.log'))) fileHandler.setFormatter(fileFormatter) logger.addHandler(fileHandler) return logger def _load(self): """Load configuration.""" try: cfg = toml.load((self.path / 'config.toml').open()) self._set_model(cfg['model_name'], cfg[cfg['model_name'].lower()]) except (FileNotFoundError, KeyError): raise NotConfiguredError('config.toml doesn\'t exist or ' 'is incomplete') def _save(self): """Save configuration.""" f = (self.path / 'config.toml').open('w') toml.dump({'model_name': self.model_name, self.model_name.lower(): self.config}, f) f.close() class Command(abc.ABC): """Command interface."""

28.405858

78

0.577405

4274e96e6ce5245f31a18bf5087d02fdafd53341

2,737

py

Python

training/train_pos_dep.py

ex00/spacy-ru

7284d8127dca322fcc2aa9ce0267699cfc9baf38

[ "MIT" ]

null

training/train_pos_dep.py

ex00/spacy-ru

7284d8127dca322fcc2aa9ce0267699cfc9baf38

[ "MIT" ]

null

training/train_pos_dep.py

ex00/spacy-ru

7284d8127dca322fcc2aa9ce0267699cfc9baf38

[ "MIT" ]

null

from __future__ import unicode_literals, print_function import sys from pathlib import Path import spacy from spacy.lang.ru import Russian from spacy.pipeline import Tagger, DependencyParser from spacy.util import fix_random_seed, set_lang_class from models.dep import MyDEP from models.loadvec import get_ft_vec from models.pos import MyPOS from models.t2v import build_tok2vec from training.corpora.syntagrus import get_syntagrus_example, get_syntagrus from training.trainer import Trainer, Extractor from utils.corpus import tag_morphology CFG = {"device": 0, 'verbose': 1} GPU_1 = "-g1" in sys.argv[1:] if GPU_1: CFG["device"] = 1 TESTS = False spacy.require_gpu(CFG['device']) TEST_MODE = "--test" in sys.argv[1:] if TEST_MODE: SynTagRus = get_syntagrus_example(Path("data/syntagrus/")) else: SynTagRus = get_syntagrus(Path("data/syntagrus/")) ft_vectors = get_ft_vec() tok2vec = build_tok2vec(embed_size=2000, vectors={"word_vectors": ft_vectors}) if __name__ == "__main__": main()

27.646465

111

0.700037

4275177baedf41f1ab31ef0704dfda58eb058f5e

1,512

py

Python

tests/test_peephole_optimizations.py

capuanob/angr

4e5bb119965cb282f5bcb3dea5b598e88097f715

[ "BSD-2-Clause" ]

null

tests/test_peephole_optimizations.py

capuanob/angr

4e5bb119965cb282f5bcb3dea5b598e88097f715

[ "BSD-2-Clause" ]

null

tests/test_peephole_optimizations.py

capuanob/angr

4e5bb119965cb282f5bcb3dea5b598e88097f715

[ "BSD-2-Clause" ]

null

# pylint:disable=missing-class-docstring,no-self-use import os import unittest import archinfo import ailment import angr from angr.analyses.decompiler.peephole_optimizations import ConstantDereferences test_location = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', '..', 'binaries', 'tests') if __name__ == "__main__": unittest.main()

38.769231

119

0.683201

42755fd81a38eefae8f526ffb8db205e1141d33b

604

py

Python

PySpace/mysql/mysql_insertdata.py

dralee/LearningRepository

4324d3c5ac1a12dde17ae70c1eb7f3d36a047ba4

[ "Apache-2.0" ]

null

PySpace/mysql/mysql_insertdata.py

dralee/LearningRepository

4324d3c5ac1a12dde17ae70c1eb7f3d36a047ba4

[ "Apache-2.0" ]

null

PySpace/mysql/mysql_insertdata.py

dralee/LearningRepository

4324d3c5ac1a12dde17ae70c1eb7f3d36a047ba4

[ "Apache-2.0" ]

null

#!/usr/bin/python3 # mysql_createtable.py import pymysql # db = pymysql.connect('localhost','root','1234','fdtest') # cursor()cursor cursor = db.cursor() # SQL sql = """INSERT INTO EMPLOYEE( FIRST_NAME,LAST_NAME,AGE,SEX,INCOME) VALUES('Mac2','Mohan2',20,'M',6000)""" """ sql = "INSERT INTO EMPLOYEE(FIRST_NAME, \ LAST_NAME, AGE, SEX, INCOME) \ VALUES ('%s', '%s', '%d', '%c', '%d' )" % \ ('Mac', 'Mohan', 20, 'M', 2000) """ try: # sql cursor.execute(sql) # db.commit() except: # db.rollback() # db.close()

16.777778

56

0.61755

42787867fa3db8b6721924f36a9b0de8973ee0ae

1,572

py

Python

appleseed_python.py

AllegorithmicSAS/sat-scons

3eea609385fb9bdd93562097d302a3707c3c6ebe

[ "BSD-3-Clause" ]

25

2018-09-17T00:10:30.000Z

2021-11-07T06:41:35.000Z

appleseed_python.py

AllegorithmicSAS/sat-scons

3eea609385fb9bdd93562097d302a3707c3c6ebe

[ "BSD-3-Clause" ]

null

appleseed_python.py

AllegorithmicSAS/sat-scons

3eea609385fb9bdd93562097d302a3707c3c6ebe

[ "BSD-3-Clause" ]

3

2018-08-28T15:01:43.000Z

2021-05-04T16:54:51.000Z

import os import subprocess import threading mutex = threading.Lock()

40.307692

125

0.688295

42793637f0ad1d6b8bdb63c8ad74420df516a382

1,327

py

Python

conjureup/ui/views/credentials.py

iMichka/conjure-up

8e4599e6f58b52163384150d8d71e7802462d126

[ "MIT" ]

1

2019-06-26T23:39:13.000Z

conjureup/ui/views/credentials.py

iMichka/conjure-up

8e4599e6f58b52163384150d8d71e7802462d126

[ "MIT" ]

null

conjureup/ui/views/credentials.py

iMichka/conjure-up

8e4599e6f58b52163384150d8d71e7802462d126

[ "MIT" ]

1

2020-10-05T14:42:31.000Z

from ubuntui.utils import Padding from ubuntui.widgets.hr import HR from conjureup.app_config import app from conjureup.ui.views.base import BaseView, SchemaFormView from conjureup.ui.widgets.selectors import MenuSelectButtonList

33.175

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0.694047

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355

py

Python

sleekxmpp/plugins/__init__.py

aristanetworks/SleekXMPP

91f53bf1964a564f6f12477a31884e9ec38cef75

[ "MIT" ]

null

sleekxmpp/plugins/__init__.py

aristanetworks/SleekXMPP

91f53bf1964a564f6f12477a31884e9ec38cef75

[ "MIT" ]

1

2020-04-10T22:09:06.000Z

sleekxmpp/plugins/__init__.py

aristanetworks/SleekXMPP

91f53bf1964a564f6f12477a31884e9ec38cef75

[ "MIT" ]

1

2019-12-05T12:10:16.000Z

""" SleekXMPP: The Sleek XMPP Library Copyright (C) 2010 Nathanael C. Fritz This file is part of SleekXMPP. See the file LICENSE for copying permission. """ __all__ = ['xep_0004', 'xep_0012', 'xep_0030', 'xep_0033', 'xep_0045', 'xep_0050', 'xep_0085', 'xep_0092', 'xep_0199', 'gmail_notify', 'xep_0060', 'xep_0202']

32.272727

74

0.63662

427af261bc83da6fc8ac5c1ea1e2a2473e51e220

5,276

py

Python

main.py

pwillworth/dfkreport

ae10226430a3a74ac3c07ae888cab14dde778db8

[ "Apache-2.0" ]

11

2022-01-18T17:36:12.000Z

2022-03-21T21:09:17.000Z

main.py

pwillworth/dfkreport

ae10226430a3a74ac3c07ae888cab14dde778db8

[ "Apache-2.0" ]

null

main.py

pwillworth/dfkreport

ae10226430a3a74ac3c07ae888cab14dde778db8

[ "Apache-2.0" ]

4

2022-01-18T18:37:48.000Z

2022-01-22T02:14:48.000Z

#!/usr/bin/env python3 import transactions import taxmap import db import settings import datetime import argparse import uuid import pickle import jsonpickle import logging import logging.handlers import traceback if __name__ == "__main__": main()

47.531532

224

0.666035

427b0f2bb086452498a9bfd3a4dc95c14c7879d6

127

py

Python

src/tarski/fstrips/contingent/__init__.py

phoeft670/tarski

7d955e535fbbca012bfd1a12402b97febc6b35b9

[ "Apache-2.0" ]

29

2018-11-26T20:31:04.000Z

2021-12-29T11:08:40.000Z

src/tarski/fstrips/contingent/__init__.py

phoeft670/tarski

7d955e535fbbca012bfd1a12402b97febc6b35b9

[ "Apache-2.0" ]

101

2018-06-07T13:10:01.000Z

2022-03-11T11:54:00.000Z

src/tarski/fstrips/contingent/__init__.py

phoeft670/tarski

7d955e535fbbca012bfd1a12402b97febc6b35b9

[ "Apache-2.0" ]

18

2018-11-01T22:44:39.000Z

2022-02-28T04:57:15.000Z

from .problem import ContingentProblem as Problem from .. action import Action from .sensor import Sensor from . import errors

25.4

49

0.811024

427bd9dc45f6695e499240fef94ddec3e4b3fe88

80

py

Python

p40-49/p48.py

kbrose/project_euler

f582ef1887f44628997e05d88253adad0822d6b9

[ "Unlicense" ]

1

2015-10-11T15:53:00.000Z

p40-49/p48.py

kbrose/project_euler

f582ef1887f44628997e05d88253adad0822d6b9

[ "Unlicense" ]

null

p40-49/p48.py

kbrose/project_euler

f582ef1887f44628997e05d88253adad0822d6b9

[ "Unlicense" ]

null

sum = 0 for i in xrange(1,1001): sum = sum + i**i print sum % 10000000000

11.428571

24

0.6

427dedadfbbcbe3c95d00fdafba41ac3a4018d6f

2,121

py

Python

property_proteome/length/run.py

rrazban/proteomevis_scripts

2b6309a78287ffab4ee745383c21b9f474b93b60

[ "MIT" ]

1

2020-11-11T06:14:10.000Z

property_proteome/length/run.py

rrazban/proteomevis_scripts

2b6309a78287ffab4ee745383c21b9f474b93b60

[ "MIT" ]

null

property_proteome/length/run.py

rrazban/proteomevis_scripts

2b6309a78287ffab4ee745383c21b9f474b93b60

[ "MIT" ]

1

2019-05-28T19:13:24.000Z

#!/usr/bin/python help_msg = 'get uniprot length of entire proteome' import os, sys CWD = os.getcwd() UTLTS_DIR = CWD[:CWD.index('proteomevis_scripts')]+'/proteomevis_scripts/utlts' sys.path.append(UTLTS_DIR) from parse_user_input import help_message from read_in_file import read_in from parse_data import organism from uniprot_api import UniProtAPI from output import writeout if __name__ == "__main__": args = help_message(help_msg, bool_add_verbose = True) d_ref = read_in('Entry', 'Gene names (ordered locus )', filename = 'proteome') uniprot_length = UniProtLength(args.verbose, d_ref) d_output = uniprot_length.run() if organism!='protherm': d_output = {d_ref[uniprot]: res for uniprot, res in d_output.iteritems()} xlabel = 'oln' else: #not supported for ProTherm xlabel = 'uniprot' writeout([xlabel, 'length'], d_output, filename = 'UniProt')

29.054795

87

0.705799

427e1e9e41044ab46aedd645fb3078c3369fa522

2,086

py

Python

machine_learning/torch_time_series_forecasting/src/data/dataset.py

iimuz/til

b100438e8ce2f369331b3be215a4b9cdce9ffda5

[ "MIT" ]

4

2020-07-25T01:20:08.000Z

2020-10-03T12:58:15.000Z

machine_learning/torch_time_series_forecasting/src/data/dataset.py

iimuz/til

b100438e8ce2f369331b3be215a4b9cdce9ffda5

[ "MIT" ]

29

2019-09-30T08:04:14.000Z

2022-03-12T13:51:08.000Z

machine_learning/torch_time_series_forecasting/src/data/dataset.py

iimuz/til

b100438e8ce2f369331b3be215a4b9cdce9ffda5

[ "MIT" ]

1

2020-08-14T05:15:51.000Z

""".""" # default packages import logging import pathlib import traceback import urllib.request as request # third party import pandas as pd import tqdm as tqdm_std # my packages import src.data.directory as directory # logger logger = logging.getLogger(__name__) def _main() -> None: """.""" logging.basicConfig(level=logging.INFO) filepath = get_raw_filepath() if filepath.exists() is False: url = get_raw_url() filepath.parent.mkdir(exist_ok=True, parents=True) with TqdmUpTo( unit="B", unit_scale=True, miniters=1, desc=filepath.name ) as pbar: request.urlretrieve( url, filename=filepath, reporthook=pbar.update_to, data=None ) else: logger.info(f"data already exists: {filepath}") # show dataset description. df = pd.read_csv(filepath) logger.info(df.info()) logger.info(df.head()) logger.info(df.tail()) if __name__ == "__main__": try: _main() except Exception as e: logger.error(e) logger.error(traceback.format_exc())

25.13253

85

0.622244

427f14f88f6ffd13fff4e9351ec1d15fe8db0b86

3,320

py

Python

app.py

aracnid/i-xero

2fb2f093a8a92e0ba2f4cdbe440e962a38c09f7e

[ "MIT" ]

null

app.py

aracnid/i-xero

2fb2f093a8a92e0ba2f4cdbe440e962a38c09f7e

[ "MIT" ]

null

app.py

aracnid/i-xero

2fb2f093a8a92e0ba2f4cdbe440e962a38c09f7e

[ "MIT" ]

null

"""Primary application. """ import json import logging import logging.config import os import sys from flask import url_for, render_template, redirect, request from i_xero import Xero2 from i_xero.i_flask import FlaskInterface from utils import jsonify, serialize_model # initialize logging # The SlackBot app doesn't handle logging in the same way. # I tried to pass in a logger object from aracnid_logger, # but it seems to disable all loggers logging_filename = os.environ.get('LOGGING_CONFIG_FILE') command_dir = os.path.dirname(sys.argv[0]) logging_dir = os.path.join(os.getcwd(), command_dir) logging_path = os.path.join(os.getcwd(), logging_filename) with open(logging_path, 'rt') as file: logging_config = json.load(file) formatter = os.environ.get('LOGGING_FORMATTER') logging_config['handlers']['console']['formatter'] = formatter logging.config.dictConfig(logging_config) env_str = os.environ.get('LOG_UNHANDLED_EXCEPTIONS') LOG_UNHANDLED_EXCEPTIONS = env_str.lower() in ('true', 'yes') if env_str else False # configure flask application flask_app = FlaskInterface(__name__).get_app() # configure xero application xero_app = Xero2(flask_app) # start the app locally if __name__ == '__main__': flask_app.run(host='localhost', port=5000)

28.376068

83

0.71506

427fcbdb91cef4c0c0751c48d3eb5d865ef45367

8,023

py

Python

ui/Ui_main.py

realm520/aimless

772e87f5b5a00eeac88be948e424310128fcec1a

[ "MIT" ]

null

ui/Ui_main.py

realm520/aimless

772e87f5b5a00eeac88be948e424310128fcec1a

[ "MIT" ]

null

ui/Ui_main.py

realm520/aimless

772e87f5b5a00eeac88be948e424310128fcec1a

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'F:\work\code\pyqt5\ui\main.ui' # # Created by: PyQt5 UI code generator 5.9 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets if __name__ == "__main__": import sys app = QtWidgets.QApplication(sys.argv) MainWindow = QtWidgets.QMainWindow() ui = Ui_MainWindow() ui.setupUi(MainWindow) MainWindow.show() sys.exit(app.exec_())

52.782895

108

0.720429

4283b88a83b93254b8e97d4642f0ca0d5d69279d

68

py

Python

examples/02_pybind/01_basic/example.py

BlockResearchGroup/WS_interoperability

604ab29c242b30b2ee9125a589afe69010ba1844

[ "MIT" ]

1

2019-07-26T22:25:25.000Z

examples/02_pybind/01_basic/example.py

BlockResearchGroup/WS_interoperability

604ab29c242b30b2ee9125a589afe69010ba1844

[ "MIT" ]

5

2019-04-14T21:07:03.000Z

2019-05-27T21:46:37.000Z

examples/02_pybind/01_basic/example.py

BlockResearchGroup/WS_interoperability

604ab29c242b30b2ee9125a589afe69010ba1844

[ "MIT" ]

null

# example.py import basic result = basic.add(1, 5) print(result)

8.5

24

0.691176

4284396ea1fd88ed33820f0870333abd8149c2de

2,213

py

Python

cocotbext/spi/devices/TI/DRV8304.py

eoshea/cocotbext-spi

9b610ca27945e22e168da5774cab8051304ea90f

[ "MIT" ]

2

2021-08-13T20:10:41.000Z

2022-03-09T19:24:24.000Z

cocotbext/spi/devices/TI/DRV8304.py

eoshea/cocotbext-spi

9b610ca27945e22e168da5774cab8051304ea90f

[ "MIT" ]

3

2021-08-23T15:34:00.000Z

2022-01-18T19:27:26.000Z

cocotbext/spi/devices/TI/DRV8304.py

eoshea/cocotbext-spi

9b610ca27945e22e168da5774cab8051304ea90f

[ "MIT" ]

2

2021-11-12T12:47:45.000Z

2021-11-18T10:35:43.000Z

import cocotb from cocotb.triggers import FallingEdge, RisingEdge, First, Timer, Event from ... import SpiSlaveBase, SpiConfig, SpiFrameError, SpiFrameTimeout

30.315068

89

0.589245

4289d7f6e86034585cd9c9cf37666cc58aab806e

540

py

Python

manage.py

Kenneth-joseph/Blogs

b6c508d36cdf2f874c233485003021d10567de7b

[ "Unlicense" ]

null

manage.py

Kenneth-joseph/Blogs

b6c508d36cdf2f874c233485003021d10567de7b

[ "Unlicense" ]

null

manage.py

Kenneth-joseph/Blogs

b6c508d36cdf2f874c233485003021d10567de7b

[ "Unlicense" ]

1

2021-11-17T11:03:08.000Z

from app import create_app,db from flask_script import Manager,Server from app.models import User,Comment,Blog from flask_migrate import Migrate, MigrateCommand #manage.shell # Creating app instance app = create_app('production') migrate = Migrate(app,db) manager = Manager(app) manager.add_command('db',MigrateCommand) manager.add_command('server',Server) if __name__== '__main__': manager.run() db.create_all()

24.545455

72

0.766667

428a08abf8ca4b32d91aa59e5ac79f8b3eb02d8f

901

py

Python

src/apps/core/migrations/0005_auto_20180417_1219.py

zhiyuli/HydroLearn

b2c2b44e49d37391149d0896ce5124e882f22ee3

[ "BSD-3-Clause" ]

null

src/apps/core/migrations/0005_auto_20180417_1219.py

zhiyuli/HydroLearn

b2c2b44e49d37391149d0896ce5124e882f22ee3

[ "BSD-3-Clause" ]

null

src/apps/core/migrations/0005_auto_20180417_1219.py

zhiyuli/HydroLearn

b2c2b44e49d37391149d0896ce5124e882f22ee3

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.7 on 2018-04-17 17:19 from __future__ import unicode_literals from django.db import migrations import django_extensions.db.fields

33.37037

266

0.657048

428b1f1d92a691f7e032bddbf0f11e16a416cdf3

186

py

Python

syncgateway/__init__.py

ecordell/syncgateway-admin-client

78a8d45ff290b42b5c771b901fb92edcde126ff4

[ "MIT" ]

null

syncgateway/__init__.py

ecordell/syncgateway-admin-client

78a8d45ff290b42b5c771b901fb92edcde126ff4

[ "MIT" ]

1

2015-12-10T20:42:12.000Z

syncgateway/__init__.py

ecordell/syncgateway-admin-client

78a8d45ff290b42b5c771b901fb92edcde126ff4

[ "MIT" ]

null

23.25

52

0.758065

428b51da1bd2717103e2c7bb03266fb5b3a3af22

7,452

py

Python

members/views.py

leonrenkema/makerspaceleiden-crm

36ea20f5b9e263e8f30b1831ae4a2b1d5b926d3c

[ "Apache-2.0" ]

5

2019-03-12T21:38:32.000Z

2021-11-06T15:26:56.000Z

members/views.py

leonrenkema/makerspaceleiden-crm

36ea20f5b9e263e8f30b1831ae4a2b1d5b926d3c

[ "Apache-2.0" ]

33

2019-01-21T15:54:50.000Z

2021-05-18T17:54:52.000Z

members/views.py

leonrenkema/makerspaceleiden-crm

36ea20f5b9e263e8f30b1831ae4a2b1d5b926d3c

[ "Apache-2.0" ]

5

2019-01-21T15:47:26.000Z

2021-09-22T07:14:34.000Z

from django.shortcuts import render, redirect from django.contrib.auth.forms import PasswordResetForm from django.core.mail import EmailMessage from django.template import loader from django.http import HttpResponse from django.contrib.auth.decorators import login_required from django.conf import settings from django.db.utils import IntegrityError from django.urls import reverse from django.template.loader import render_to_string, get_template from .forms import NewUserForm, NewAuditRecordForm from acl.models import Entitlement, PermitType from members.models import Tag, User, clean_tag_string, AuditRecord from mailinglists.models import Mailinglist, Subscription import logging import datetime import sys import re logger = logging.getLogger(__name__) def drop(request): if not request.user.can_escalate_to_priveleged: return HttpResponse("XS denied", status=403, content_type="text/plain") record = AuditRecord( user=request.user, final=True, action="Drop privs from webinterface" ) if request.user.is_privileged: record.changereason = f"DROP in webinterface by {request.user}" else: record.changereason = f"DROP in webinterface by {request.user} - but actual permission had already timed out." record.save() return redirect(request.META["HTTP_REFERER"])

35.485714

118

0.554616

428b5eca1188b78557324447b1ddda687b1af59c

3,911

py

Python

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/views/deprecated/create_ns_view.py

lremember/VFC

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

1

2019-10-10T00:52:18.000Z

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/views/deprecated/create_ns_view.py

lremember/VFC-Files

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

null

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/views/deprecated/create_ns_view.py

lremember/VFC-Files

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

null

# Copyright 2018 ZTE Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging from drf_yasg.utils import swagger_auto_schema from rest_framework import status from rest_framework.response import Response from rest_framework.views import APIView from lcm.ns.biz.ns_create import CreateNSService from lcm.ns.biz.ns_get import GetNSInfoService from lcm.ns.serializers.deprecated.ns_serializers import _CreateNsReqSerializer from lcm.ns.serializers.deprecated.ns_serializers import _CreateNsRespSerializer from lcm.ns.serializers.deprecated.ns_serializers import _QueryNsRespSerializer from lcm.pub.exceptions import NSLCMException from lcm.pub.exceptions import BadRequestException from lcm.pub.utils.values import ignore_case_get from .common import view_safe_call_with_log logger = logging.getLogger(__name__)

41.168421

92

0.692662

428be7b7fc4fa9ed70e9c54b4441f37388d4cbd4

3,304

py

Python

parse_training_input.py

alexpotter1/vulndetect-ml

338fbf919b24520f9107a1604d1c8af48aadff76

[ "MIT" ]

1

2020-02-25T01:53:23.000Z

parse_training_input.py

alexpotter1/vulndetect-ml

338fbf919b24520f9107a1604d1c8af48aadff76

[ "MIT" ]

null

parse_training_input.py

alexpotter1/vulndetect-ml

338fbf919b24520f9107a1604d1c8af48aadff76

[ "MIT" ]

1

2020-10-24T15:30:38.000Z

#!/usr/bin/env python3 import javalang

33.714286

121

0.59776

428caa0f2af4107e3b019feaf07304cc2bf7796d

17,226

py

Python

src/mist/api/rules/models/main.py

SpiralUp/mist.api

a3b5233ab4aa3f6a0a2dea6333ff1e5a260af934

[ "Apache-2.0" ]

6

2017-08-24T00:34:30.000Z

2022-01-16T21:29:22.000Z

src/mist/api/rules/models/main.py

SpiralUp/mist.api

a3b5233ab4aa3f6a0a2dea6333ff1e5a260af934

[ "Apache-2.0" ]

9

2021-03-31T18:50:47.000Z

2022-01-09T23:20:02.000Z

src/mist/api/rules/models/main.py

SpiralUp/mist.api

a3b5233ab4aa3f6a0a2dea6333ff1e5a260af934

[ "Apache-2.0" ]

13

2017-09-21T18:17:02.000Z

2022-02-21T04:29:25.000Z

import uuid import mongoengine as me from mist.api import config from mist.api.exceptions import BadRequestError from mist.api.users.models import Organization from mist.api.selectors.models import SelectorClassMixin from mist.api.rules.base import NoDataRuleController from mist.api.rules.base import ResourceRuleController from mist.api.rules.base import ArbitraryRuleController from mist.api.rules.models import RuleState from mist.api.rules.models import Window from mist.api.rules.models import Frequency from mist.api.rules.models import TriggerOffset from mist.api.rules.models import QueryCondition from mist.api.rules.models import BaseAlertAction from mist.api.rules.models import NotificationAction from mist.api.rules.plugins import GraphiteNoDataPlugin from mist.api.rules.plugins import GraphiteBackendPlugin from mist.api.rules.plugins import InfluxDBNoDataPlugin from mist.api.rules.plugins import InfluxDBBackendPlugin from mist.api.rules.plugins import ElasticSearchBackendPlugin from mist.api.rules.plugins import FoundationDBNoDataPlugin from mist.api.rules.plugins import FoundationDBBackendPlugin from mist.api.rules.plugins import VictoriaMetricsNoDataPlugin from mist.api.rules.plugins import VictoriaMetricsBackendPlugin class ArbitraryRule(Rule): """A rule defined by a single, arbitrary query string. Arbitrary rules permit the definition of complex query expressions by allowing users to define fully qualified queries in "raw mode" as a single string. In such case, a query expression may be a composite query that includes nested aggregations and/or additional queries. An `ArbitraryRule` must define a single `QueryCondition`, whose `target` defines the entire query expression as a single string. """ _controller_cls = ArbitraryRuleController class ResourceRule(Rule, SelectorClassMixin): """A rule bound to a specific resource type. Resource-bound rules are less elastic than arbitrary rules, but allow users to perform quick, more dynamic filtering given a resource object's UUID, tags, or model fields. Every subclass of `ResourceRule` MUST define its `selector_resource_cls` class attribute in order for queries to be executed against the intended mongodb collection. A `ResourceRule` may also apply to multiple resources, which depends on the rule's list of `selectors`. By default such a rule will trigger an alert if just one of its queries evaluates to True. """ _controller_cls = ResourceRuleController # FIXME All following properties are for backwards compatibility. def _populate_rules(): """Populate RULES with mappings from rule type to rule subclass. RULES is a mapping (dict) from rule types to subclasses of Rule. A rule's type is the concat of two strings: <str1>-<str2>, where str1 denotes whether the rule is arbitrary or not and str2 equals the `_data_type_str` class attribute of the rule, which is simply the type of the requesting data, like logs or monitoring metrics. The aforementioned concatenation is simply a way to categorize a rule, such as saying a rule on arbitrary logs or a resource-bound rule referring to the monitoring data of machine A. """ public_rule_map = {} hidden_rule_cls = (ArbitraryRule, ResourceRule, NoDataRule, ) for key, value in list(globals().items()): if not key.endswith('Rule'): continue if value in hidden_rule_cls: continue if not issubclass(value, (ArbitraryRule, ResourceRule, )): continue str1 = 'resource' if issubclass(value, ResourceRule) else 'arbitrary' rule_key = '%s-%s' % (str1, value._data_type_str) public_rule_map[rule_key] = value return public_rule_map RULES = _populate_rules()

35.155102

79

0.673981

428d613a4c439197af5e225dec64ebdd98da7d00

1,685

py

Python

setup.py

andrewwhitehead/django-oidc-rp

233f1daeef96dbe84ecbb37fa31393c84f9c2805

[ "MIT" ]

20

2018-04-16T13:17:35.000Z

2021-06-05T00:08:33.000Z

setup.py

andrewwhitehead/django-oidc-rp

233f1daeef96dbe84ecbb37fa31393c84f9c2805

[ "MIT" ]

9

2018-07-20T18:19:13.000Z

2021-12-22T08:57:18.000Z

setup.py

bcgov/django-oidc-rp

50e6fa143e61b04849b4c66beef078be0d7669de

[ "MIT" ]

21

2018-07-10T16:05:44.000Z

2022-01-24T05:57:09.000Z

# -*- coding: utf-8 -*- import codecs from os.path import abspath from os.path import dirname from os.path import join from setuptools import find_packages from setuptools import setup import oidc_rp def read_relative_file(filename): """ Returns contents of the given file, whose path is supposed relative to this module. """ with codecs.open(join(dirname(abspath(__file__)), filename), encoding='utf-8') as f: return f.read() setup( name='django-oidc-rp', version=oidc_rp.__version__, author='impak Finance', author_email='tech@impakfinance.com', packages=find_packages(exclude=['tests.*', 'tests']), include_package_data=True, url='https://github.com/impak-finance/django-oidc-rp', license='MIT', description='A server side OpenID Connect Relying Party (RP/Client) implementation for Django.', long_description=read_relative_file('README.rst'), keywords='django openidconnect oidc client rp authentication auth', zip_safe=False, install_requires=[ 'django>=1.11', 'jsonfield2', 'pyjwkest>=1.4', 'requests>2.0', ], classifiers=[ 'Development Status :: 4 - Beta', 'Environment :: Web Environment', 'Framework :: Django', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ], )

31.792453

100

0.648071

428e0c3390f490eb7e09d675c22baad9bedb5ba6

171

py

Python

nndet/evaluator/detection/__init__.py

joeranbosma/nnDetection

2ebbf1cdc8a8794c73e325f06fea50632c78ae8c

[ "BSD-3-Clause" ]

242

2021-05-17T12:31:39.000Z

2022-03-31T11:51:29.000Z

nndet/evaluator/detection/__init__.py

joeranbosma/nnDetection

2ebbf1cdc8a8794c73e325f06fea50632c78ae8c

[ "BSD-3-Clause" ]

59

2021-06-02T07:32:10.000Z

2022-03-31T18:45:52.000Z

nndet/evaluator/detection/__init__.py

joeranbosma/nnDetection

2ebbf1cdc8a8794c73e325f06fea50632c78ae8c

[ "BSD-3-Clause" ]

38

2021-05-31T14:01:37.000Z

2022-03-21T08:24:40.000Z

from nndet.evaluator.detection.froc import FROCMetric from nndet.evaluator.detection.coco import COCOMetric from nndet.evaluator.detection.hist import PredictionHistogram

42.75

62

0.877193

428e40b791a018156767a64f9f6283399ebd2b1c

289

py

Python

tests/test_update.py

sosie-js/ankisync2

a41580197eab7f180f02a38a4aa912eb54cfaa93

[ "MIT" ]

39

2020-02-12T23:41:24.000Z

2022-02-28T15:46:23.000Z

tests/test_update.py

sosie-js/ankisync2

a41580197eab7f180f02a38a4aa912eb54cfaa93

[ "MIT" ]

9

2019-08-02T18:25:07.000Z

2022-02-07T23:14:43.000Z

tests/test_update.py

sosie-js/ankisync2

a41580197eab7f180f02a38a4aa912eb54cfaa93

[ "MIT" ]

6

2019-09-09T14:27:48.000Z

2021-08-31T08:13:00.000Z

# from ankisync2.apkg import Apkg, db # Has to be done through normal database methods # def test_update(): # apkg = Apkg("example1.apkg") # for n in db.Notes.filter(db.Notes.data["field1"] == "data1"): # n.data["field3"] = "data2" # n.save() # apkg.close()

24.083333

67

0.598616

428eac96b1905cf94fc5b1f167e60c8c46762f48

16,931

py

Python

lib/place_model.py

ihaeyong/drama-graph

60c3c216cd74bb19efd6baf836f6c7c2b42b764f

[ "MIT" ]

3

2021-04-28T07:19:39.000Z

2022-03-07T09:34:19.000Z

lib/place_model.py

ihaeyong/drama-graph

60c3c216cd74bb19efd6baf836f6c7c2b42b764f

[ "MIT" ]

18

2020-08-24T12:40:38.000Z

2022-03-12T00:47:14.000Z

lib/place_model.py

ihaeyong/drama-graph

60c3c216cd74bb19efd6baf836f6c7c2b42b764f

[ "MIT" ]

1

2020-10-15T10:09:20.000Z

import torch import torch.nn as nn from torchvision.datasets.vision import VisionDataset from PIL import Image import os, sys, math import os.path import torch import json import torch.utils.model_zoo as model_zoo from Yolo_v2_pytorch.src.utils import * from Yolo_v2_pytorch.src.yolo_net import Yolo from Yolo_v2_pytorch.src.yolo_tunning import YoloD import numpy as np import torch.nn.functional as F from Yolo_v2_pytorch.src.rois_utils import anchorboxes from Yolo_v2_pytorch.src.anotherMissOh_dataset import FaceCLS from lib.person_model import person_model label_dict = {'' : 9, 'beach':0, 'cafe':1, 'car':2, 'convenience store':3, 'garden':4, 'home':5, 'hospital':6, 'kitchen':7, 'livingroom':8, 'none':9, 'office':10, 'park':11, 'playground':12, 'pub':13, 'restaurant':14, 'riverside':15, 'road':16, 'rooftop':17, 'room':18, 'studio':19, 'toilet':20, 'wedding hall':21 } label_dict_wo_none = {'beach':0, 'cafe':1, 'car':2, 'convenience store':3, 'garden':4, 'home':5, 'hospital':6, 'kitchen':7, 'livingroom':8, 'none':9, 'office':10, 'park':11, 'playground':12, 'pub':13, 'restaurant':14, 'riverside':15, 'road':16, 'rooftop':17, 'room':18, 'studio':19, 'toilet':20, 'wedding hall':21 } def conv3x3(in_planes, out_planes, stride=1): """3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False) def accuracy(output, target, topk=(1,)): """Computes the accuracy over the k top predictions for the specified values of k""" with torch.no_grad(): maxk = max(topk) batch_size = target.size(0) _, pred = output.topk(maxk, 1, True, True) pred = pred.t() correct = pred.eq(target.view(1, -1).expand_as(pred)) res = [] for k in topk: correct_k = correct[:k].view(-1).float().sum(0, keepdim=True) res.append(correct_k.mul_(100.0 / batch_size)) return res sample_default = [105, 462, 953, 144, 108, 13, 123, 510, 1690, 19914, 1541, 126, 67, 592, 1010, 53, 2087, 0, 1547, 576, 74, 0] def CB_loss(labels, logits, beta=0.99, gamma=0.5, samples_per_cls=sample_default, no_of_classes=22, loss_type='softmax'): """Compute the Class Balanced Loss between `logits` and the ground truth `labels`. Class Balanced Loss: ((1-beta)/(1-beta^n))*Loss(labels, logits) where Loss is one of the standard losses used for Neural Networks. Args: labels: A int tensor of size [batch]. logits: A float tensor of size [batch, no_of_classes]. samples_per_cls: A python list of size [no_of_classes]. no_of_classes: total number of classes. int loss_type: string. One of "sigmoid", "focal", "softmax". beta: float. Hyperparameter for Class balanced loss. gamma: float. Hyperparameter for Focal loss. Returns: cb_loss: A float tensor representing class balanced loss """ effective_num = 1.0 - np.power(beta, samples_per_cls) weights = (1.0 - beta) / np.array(effective_num) weights = weights / np.sum(weights) * no_of_classes labels_one_hot = F.one_hot(labels, no_of_classes).cpu().float() weights = torch.tensor(weights).float() weights = weights.unsqueeze(0) weights = weights.repeat(labels_one_hot.shape[0],1) * labels_one_hot weights = weights.sum(1) weights = weights.unsqueeze(1) weights = weights.repeat(1,no_of_classes) if loss_type == "focal": cb_loss = focal_loss(labels_one_hot.cuda(), logits, weights.cuda(), gamma) elif loss_type == "sigmoid": cb_loss = F.binary_cross_entropy_with_logits(input = logits,target = labels_one_hot, weights = weights) elif loss_type == "softmax": pred = logits.softmax(dim = 1) cb_loss = F.binary_cross_entropy(input = pred, target = labels_one_hot.cuda(), weight = weights.cuda()) return cb_loss def focal_loss(labels, logits, alpha, gamma): """Compute the focal loss between `logits` and the ground truth `labels`. Focal loss = -alpha_t * (1-pt)^gamma * log(pt) where pt is the probability of being classified to the true class. pt = p (if true class), otherwise pt = 1 - p. p = sigmoid(logit). Args: labels: A float tensor of size [batch, num_classes]. logits: A float tensor of size [batch, num_classes]. alpha: A float tensor of size [batch_size] specifying per-example weight for balanced cross entropy. gamma: A float scalar modulating loss from hard and easy examples. Returns: focal_loss: A float32 scalar representing normalized total loss. """ BCLoss = F.binary_cross_entropy_with_logits(input = logits, target = labels,reduction = "none") if gamma == 0.0: modulator = 1.0 else: modulator = torch.exp(-gamma * labels * logits - gamma * torch.log(1 + torch.exp(-1.0 * logits))) loss = modulator * BCLoss weighted_loss = alpha * loss focal_loss = torch.sum(weighted_loss) focal_loss /= torch.sum(labels) return focal_loss

36.647186

126

0.631268

428f4631d1d991fd823deb6aae84c7555b191363

9,127

py

Python

ch01/challenge.py

laszlokiraly/LearningAlgorithms

032a3cc409546619cf41220821d081cde54bbcce

[ "MIT" ]

null

ch01/challenge.py

laszlokiraly/LearningAlgorithms

032a3cc409546619cf41220821d081cde54bbcce

[ "MIT" ]

null

ch01/challenge.py

laszlokiraly/LearningAlgorithms

032a3cc409546619cf41220821d081cde54bbcce

[ "MIT" ]

null

""" Challenge Exercises for Chapter 1. """ import random import timeit from algs.table import DataTable, ExerciseNum, caption from algs.counting import RecordedItem def partition(A, lo, hi, idx): """ Partition using A[idx] as value. Note lo and hi are INCLUSIVE on both ends and idx must be valid index. Count the number of comparisons by populating A with RecordedItem instances. """ if lo == hi: return lo A[idx],A[lo] = A[lo],A[idx] # swap into position i = lo j = hi + 1 while True: while True: i += 1 if i == hi: break if A[lo] < A[i]: break while True: j -= 1 if j == lo: break if A[j] < A[lo]: break # doesn't count as comparing two values if i >= j: break A[i],A[j] = A[j],A[i] A[lo],A[j] = A[j],A[lo] return j def linear_median(A): """ Efficient implementation that returns median value in arbitrary list, assuming A has an odd number of values. Note this algorithm will rearrange values in A. """ # if len(A) % 2 == 0: # raise ValueError('linear_median() only coded to work with odd number of values.') lo = 0 hi = len(A) - 1 mid = hi // 2 while lo < hi: idx = random.randint(lo, hi) # select valid index randomly j = partition(A, lo, hi, idx) if j == mid: return A[j] if j < mid: lo = j+1 else: hi = j-1 return A[lo] def counting_sort(A, M): """ Update A in place to be sorted in ascending order if all elements are guaranteed to be in the range 0 to and not including M. """ counts = [0] * M for v in A: counts[v] += 1 pos = 0 v = 0 while pos < len(A): for idx in range(counts[v]): A[pos+idx] = v pos += counts[v] v += 1 def counting_sort_improved(A,M): """ Update A in place to be sorted in ascending order if all elements are guaranteed to be in the range 0 to and not including M. """ counts = [0] * M for val in A: counts[val] += 1 pos = 0 val = 0 while pos < len(A): if counts[val] > 0: A[pos:pos+counts[val]] = [val] * counts[val] pos += counts[val] val += 1 def run_counting_sort_trials(max_k=15, output=True): """Generate table for counting sort up to (but not including) max_k=15.""" tbl = DataTable([8,15,15], ['N', 'counting_sort', 'counting_sort_improved'], output=output) M = 20 # arbitrary value, and results are dependent on this value. trials = [2**k for k in range(8, max_k)] for n in trials: t_cs = min(timeit.repeat(stmt='counting_sort(a,{})\nis_sorted(a)'.format(M), setup=''' import random from ch01.challenge import counting_sort from algs.sorting import is_sorted w = [{0}-1] * {1} b = [0] * {1} a = list(range({0})) * {1} random.shuffle(a)'''.format(M,n), repeat=100, number=1)) t_csi = min(timeit.repeat(stmt='counting_sort_improved(a,{})\nis_sorted(a)'.format(M), setup=''' import random from ch01.challenge import counting_sort_improved from algs.sorting import is_sorted w = [{0}-1] * {1} b = [0] * {1} a = list(range({0})) * {1} random.shuffle(a)'''.format(M,n), repeat=100, number=1)) tbl.row([n, t_cs, t_csi]) return tbl def run_median_trial(): """Generate table for Median Trial.""" tbl = DataTable([10,15,15],['N', 'median_time', 'sort_median']) trials = [2**k+1 for k in range(8,20)] for n in trials: t_med = 1000*min(timeit.repeat(stmt='assert(linear_median(a) == {}//2)'.format(n), setup=''' import random from ch01.challenge import linear_median a = list(range({})) random.shuffle(a) '''.format(n), repeat=10, number=5))/5 t_sort = 1000*min(timeit.repeat(stmt='assert(median_from_sorted_list(a) == {0}//2)'.format(n), setup=''' import random from ch01.challenge import median_from_sorted_list a = list(range({})) random.shuffle(a) '''.format(n), repeat=10, number=5))/5 tbl.row([n, t_med, t_sort]) return tbl def run_median_less_than_trial(max_k=20, output=True): """Use RecordedItem to count # of times Less-than invoked up to (but not including) max_k=20.""" tbl = DataTable([10,15,15],['N', 'median_count', 'sort_median_count'], output=output) tbl.format('median_count', ',d') tbl.format('sort_median_count', ',d') trials = [2**k+1 for k in range(8, max_k)] for n in trials: A = list([RecordedItem(i) for i in range(n)]) random.shuffle(A) # Generated external sorted to reuse list RecordedItem.clear() med2 = median_from_sorted_list(A) sort_lt = RecordedItem.report()[1] RecordedItem.clear() med1 = linear_median(A) lin_lt = RecordedItem.report()[1] assert med1 == med2 tbl.row([n, lin_lt, sort_lt]) return tbl def is_palindrome1(w): """Create slice with negative step and confirm equality with w.""" return w[::-1] == w def is_palindrome2(w): """Strip outermost characters if same, return false when mismatch.""" while len(w) > 1: if w[0] != w[-1]: # if mismatch, return False return False w = w[1:-1] # strip characters on either end; repeat return True # must have been a Palindrome def is_palindrome3(w): """iterate from start and from end and compare, without copying arrays""" for i in range(0,round(len(w)/2)): if w[i] != w[-(i+1)]: return False return True # must have been a Palindrome def is_palindrome_letters_only(s): """ Confirm Palindrome, even when string contains non-alphabet letters and ignore capitalization. casefold() method, which was introduced in Python 3.3, could be used instead of this older method, which converts to lower(). """ i = 0 j = hi = len(s) - 1 while i < j: # This type of logic appears in partition. # Find alpha characters and compare while not s[i].isalpha(): i += 1 if i == hi: break while not s[j].isalpha(): j -= 1 if j == 0: break if s[i].lower() != s[j].lower(): return False i += 1 j -= 1 return True def tournament_allows_odd(A): """ Returns two largest values in A. Works for odd lists """ from ch01.largest_two import Match if len(A) < 2: raise ValueError('Must have at least two values') tourn = [] for i in range(0, len(A)-1, 2): tourn.append(Match(A[i], A[i+1])) odd_one_out = None if len(A) % 2 == 1: odd_one_out = A[-1] while len(tourn) > 1: tourn.append(Match.advance(tourn[0], tourn[1])) del tourn[0:2] # Find where second is hiding! m = tourn[0] largest = m.larger second = m.smaller # Wait until the end, and see where it belongs if odd_one_out: if odd_one_out > largest: largest,second = odd_one_out,largest elif odd_one_out > second: second = odd_one_out while m.prior: m = m.prior if second < m.smaller: second = m.smaller return (largest,second) def two_largest_attempt(A): """Failed attempt to implement two largest.""" m1 = max(A[:len(A)//2]) m2 = max(A[len(A)//2:]) if m1 < m2: return (m2, m1) return (m1, m2) ####################################################################### if __name__ == '__main__': chapter = 1 with ExerciseNum(1) as exercise_number: sample = 'A man, a plan, a canal. Panama!' print(sample,'is a palindrome:', is_palindrome_letters_only(sample)) print(caption(chapter, exercise_number), 'Palindrome Detector') with ExerciseNum(2) as exercise_number: run_median_less_than_trial() print() run_median_trial() print(caption(chapter, exercise_number), 'Median Counting') with ExerciseNum(3) as exercise_number: run_counting_sort_trials() print(caption(chapter, exercise_number), 'Counting Sort Trials') with ExerciseNum(4) as exercise_number: print('see tournament_allows_odd in ch01.challenge') print(caption(chapter, exercise_number), 'Odd tournament') with ExerciseNum(5) as exercise_number: print('Should print (9, 8)', two_largest_attempt([9, 3, 5, 7, 8, 1])) print('Fails to print (9, 8)', two_largest_attempt([9, 8, 5, 7, 3, 1])) print(caption(chapter, exercise_number), 'Failed Two largest')

29.066879

102

0.573573

428f6c9308ecfc2aebd2c05427a3eb4c4bcb191b

522

py

Python

exaslct_src/lib/data/dependency_collector/dependency_image_info_collector.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

null

exaslct_src/lib/data/dependency_collector/dependency_image_info_collector.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

1

2019-05-06T07:36:11.000Z

exaslct_src/lib/data/dependency_collector/dependency_image_info_collector.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

1

2019-05-03T08:49:29.000Z

from typing import Dict from exaslct_src.lib.data.image_info import ImageInfo from exaslct_src.lib.data.dependency_collector.dependency_collector import DependencyInfoCollector IMAGE_INFO = "image_info"

29

98

0.764368

42914f6fbdf21a73ae8be4659f5689614360b711

3,131

py

Python

tensorflow_transform/test_case_test.py

LaudateCorpus1/transform

afee306046b8f656355b0170793ee64423f30e23

[ "Apache-2.0" ]

970

2017-02-10T04:33:46.000Z

2022-03-26T08:11:20.000Z

tensorflow_transform/test_case_test.py

LaudateCorpus1/transform

afee306046b8f656355b0170793ee64423f30e23

[ "Apache-2.0" ]

216

2017-02-23T04:50:59.000Z

2022-03-31T13:52:57.000Z

tensorflow_transform/test_case_test.py

LaudateCorpus1/transform

afee306046b8f656355b0170793ee64423f30e23

[ "Apache-2.0" ]

238

2017-02-17T16:30:55.000Z

2022-03-03T20:10:25.000Z

# Copyright 2017 Google Inc. 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 applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for tensorflow_transform.test_case.""" import re from tensorflow_transform import test_case import unittest if __name__ == '__main__': unittest.main()

36.835294

79

0.544874

4293119f4fbe0691576ba0bf3959decad7140860

6,388

py

Python

metageta/icons.py

ssutee/metageta

70b7e572acefcce7a8f4d8de719f936934319064

[ "MIT" ]

null

metageta/icons.py

ssutee/metageta

70b7e572acefcce7a8f4d8de719f936934319064

[ "MIT" ]

null

metageta/icons.py

ssutee/metageta

70b7e572acefcce7a8f4d8de719f936934319064

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Copyright (c) 2013 Australian Government, Department of the Environment # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. ''' base 64 encoded gif images for the GUI buttons '''

63.88

89

0.688009

42934dc5c7b47e76f47a4a49a47981e068b48692

1,417

py

Python

chmp/src/chmp/torch_utils/_test_bayes.py

chmp/misc-exp

2edc2ed598eb59f4ccb426e7a5c1a23343a6974b

[ "MIT" ]

6

2017-10-31T20:54:37.000Z

2020-10-23T19:03:00.000Z

chmp/src/chmp/torch_utils/_test_bayes.py

chmp/misc-exp

2edc2ed598eb59f4ccb426e7a5c1a23343a6974b

[ "MIT" ]

7

2020-03-24T16:14:34.000Z

2021-03-18T20:51:37.000Z

chmp/src/chmp/torch_utils/_test_bayes.py

chmp/misc-exp

2edc2ed598eb59f4ccb426e7a5c1a23343a6974b

[ "MIT" ]

1

2019-07-29T07:55:49.000Z

import torch import pytest # NOTE: also registers the KL divergence from chmp.torch_utils import NormalModule, WeightsHS, fixed

28.918367

73

0.666902

4293fa719a880b9bfe3a700da09a0f285fc6495b

867

py

Python

test/hummingbot/core/utils/test_fixed_rate_source.py

BGTCapital/hummingbot

2c50f50d67cedccf0ef4d8e3f4c8cdce3dc87242

[ "Apache-2.0" ]

3,027

2019-04-04T18:52:17.000Z

2022-03-30T09:38:34.000Z

test/hummingbot/core/utils/test_fixed_rate_source.py

BGTCapital/hummingbot

2c50f50d67cedccf0ef4d8e3f4c8cdce3dc87242

[ "Apache-2.0" ]

4,080

2019-04-04T19:51:11.000Z

2022-03-31T23:45:21.000Z

test/hummingbot/core/utils/test_fixed_rate_source.py

BGTCapital/hummingbot

2c50f50d67cedccf0ef4d8e3f4c8cdce3dc87242

[ "Apache-2.0" ]

1,342

2019-04-04T20:50:53.000Z

2022-03-31T15:22:36.000Z

from decimal import Decimal from unittest import TestCase from hummingbot.core.utils.fixed_rate_source import FixedRateSource

32.111111

83

0.731257

4297be6e9ea671a123810cad1577476fb18a42d0

5,293

py

Python

src/graphnet/models/detector/icecube.py

kaareendrup/gnn-reco

21f4e36ef17c765a04cde0b2e34d5f802a988055

[ "Apache-2.0" ]

null

src/graphnet/models/detector/icecube.py

kaareendrup/gnn-reco

21f4e36ef17c765a04cde0b2e34d5f802a988055

[ "Apache-2.0" ]

null

src/graphnet/models/detector/icecube.py

kaareendrup/gnn-reco

21f4e36ef17c765a04cde0b2e34d5f802a988055

[ "Apache-2.0" ]

null

import torch from torch_geometric.data import Data from graphnet.components.pool import group_pulses_to_dom, group_pulses_to_pmt, sum_pool_and_distribute from graphnet.data.constants import FEATURES from graphnet.models.detector.detector import Detector

33.713376

128

0.575477

429945dde445e0205f0ceeefa695def22a8e1795

450

py

Python

tests/routes_parsing/test1.py

hellojoechip/bambleweeny

ef65f574081eb169aef5a2f7363c3f8ba9ebf028

[ "MIT" ]

22

2018-09-30T12:08:09.000Z

2020-11-18T06:32:01.000Z

tests/routes_parsing/test1.py

hellojoechip/bambleweeny

ef65f574081eb169aef5a2f7363c3f8ba9ebf028

[ "MIT" ]

34

2018-09-13T14:54:21.000Z

2020-03-26T18:26:26.000Z

tests/routes_parsing/test1.py

hellojoechip/bambleweeny

ef65f574081eb169aef5a2f7363c3f8ba9ebf028

[ "MIT" ]

17

2018-10-07T15:41:50.000Z

2021-12-10T10:29:02.000Z

import re t1 = 'Data !@[value1] and also !@[system:uptime] testing.' print("Content: " + t1) if re.search('!@\[[_a-zA-Z0-9:]*\]', t1): print("YES") else: print("NO") o = re.sub('!@\[[_a-zA-Z0-9:]*\]', '_B9yPrsE_\\g<0>_B9yPrsE_', t1) o2 = o.split("_B9yPrsE_") for i in o2: if i.startswith("!@["): i2 = re.sub('[^\w:]', "", i) print("Parse: " + str(i) + " " +str(i2)) else: print("Plain: '" + str(i) + "'")

21.428571

66

0.482222

429a7f070688a75a8c4a4c449d4d3474a9a7088a

5,430

py

Python

internal/notes/builtin-SAVE/packages/suite-sparse/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

1

2019-01-17T20:07:19.000Z

internal/notes/builtin-SAVE/packages/suite-sparse/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

null

internal/notes/builtin-SAVE/packages/suite-sparse/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

2

2019-08-06T18:13:57.000Z

2021-11-05T18:19:49.000Z

############################################################################## # Copyright (c) 2013-2017, Lawrence Livermore National Security, LLC. # Produced at the Lawrence Livermore National Laboratory. # # This file is part of Spack. # Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved. # LLNL-CODE-647188 # # For details, see https://github.com/spack/spack # Please also see the NOTICE and LICENSE files for our notice and the LGPL. # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License (as # published by the Free Software Foundation) version 2.1, February 1999. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and # conditions of the GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA ############################################################################## from spack import *

44.876033

122

0.618416

429b606cd5d96a46f963693074a289b595badea4

4,580

py

Python

tick/array/serialize.py

andro2157/tick

d22d0e70c8bb2d5b232ffa7b97426010c2328edc

[ "BSD-3-Clause" ]

null

tick/array/serialize.py

andro2157/tick

d22d0e70c8bb2d5b232ffa7b97426010c2328edc

[ "BSD-3-Clause" ]

null

tick/array/serialize.py

andro2157/tick

d22d0e70c8bb2d5b232ffa7b97426010c2328edc

[ "BSD-3-Clause" ]

null

# License: BSD 3 clause import os import numpy as np import scipy from tick.array.build.array import ( tick_float_array_to_file, tick_float_array2d_to_file, tick_float_sparse2d_to_file, tick_double_array_to_file, tick_double_array2d_to_file, tick_double_sparse2d_to_file, tick_float_array_from_file, tick_float_array2d_from_file, tick_float_sparse2d_from_file, tick_double_array_from_file, tick_double_array2d_from_file, tick_double_sparse2d_from_file, ) def serialize_array(array, filepath): """Save an array on disk on a format that tick C++ modules can read This method is intended to be used by developpers only, mostly for benchmarking in C++ on real datasets imported from Python Parameters ---------- array : `np.ndarray` or `scipy.sparse.csr_matrix` 1d or 2d array filepath : `str` Path where the array will be stored Returns ------- path : `str` Global path of the serialized array """ if array.dtype not in [np.float32, np.float64]: raise ValueError('Only float32/64 arrays can be serrialized') if array.dtype == "float32": if isinstance(array, np.ndarray): if len(array.shape) == 1: serializer = tick_float_array_to_file elif len(array.shape) == 2: serializer = tick_float_array2d_to_file else: raise ValueError('Only 1d and 2d arrays can be serrialized') else: if len(array.shape) == 2: serializer = tick_float_sparse2d_to_file else: raise ValueError('Only 2d sparse arrays can be serrialized') elif array.dtype == "float64" or array.dtype == "double": if isinstance(array, np.ndarray): if len(array.shape) == 1: serializer = tick_double_array_to_file elif len(array.shape) == 2: serializer = tick_double_array2d_to_file else: raise ValueError('Only 1d and 2d arrays can be serrialized') else: if len(array.shape) == 2: serializer = tick_double_sparse2d_to_file else: raise ValueError('Only 2d sparse arrays can be serrialized') else: raise ValueError('Unhandled serrialization type') serializer(filepath, array) return os.path.abspath(filepath) def load_array(filepath, array_type='dense', array_dim=1, dtype="float64"): """Loaf an array from disk from a format that tick C++ modules can read This method is intended to be used by developpers only, mostly for benchmarking in C++ on real datasets imported from Python Parameters ---------- filepath : `str` Path where the array was stored array_type : {'dense', 'sparse'}, default='dense' Expected type of the array array_dim : `int` Expected dimension of the array Returns ------- array : `np.ndarray` or `scipy.sparse.csr_matrix` 1d or 2d array """ abspath = os.path.abspath(filepath) if not os.path.exists(filepath): raise FileNotFoundError('File {} does not exists'.format(abspath)) if dtype == "float32": if array_type == 'dense': if array_dim == 1: reader = tick_float_array_from_file elif array_dim == 2: reader = tick_float_array2d_from_file else: raise ValueError('Only 1d and 2d arrays can be loaded') elif array_type == 'sparse': if array_dim == 2: reader = tick_float_sparse2d_from_file else: raise ValueError('Only 2d sparse arrays can be loaded') else: raise ValueError('Cannot load this class of array') elif dtype == "float64" or dtype == "double": if array_type == 'dense': if array_dim == 1: reader = tick_double_array_from_file elif array_dim == 2: reader = tick_double_array2d_from_file else: raise ValueError('Only 1d and 2d arrays can be loaded') elif array_type == 'sparse': if array_dim == 2: reader = tick_double_sparse2d_from_file else: raise ValueError('Only 2d sparse arrays can be loaded') else: raise ValueError('Cannot load this class of array') else: raise ValueError('Unhandled serrialization type') return reader(filepath)

32.94964

76

0.613974

429b9b03d73a5f7f9bbccc750f09ea936a25f8a0

78

py

Python

__init__.py

bbockelm/glideinWMS

a2b39e3d4ff6c4527efad54b1eefe728a4ec9d18

[ "BSD-3-Clause" ]

null

__init__.py

bbockelm/glideinWMS

a2b39e3d4ff6c4527efad54b1eefe728a4ec9d18

[ "BSD-3-Clause" ]

3

2015-12-02T19:37:45.000Z

2016-01-20T03:21:48.000Z

__init__.py

bbockelm/glideinWMS

a2b39e3d4ff6c4527efad54b1eefe728a4ec9d18

[ "BSD-3-Clause" ]

1

2015-12-01T23:02:41.000Z

__all__=["factory","frontend","lib","tools","creation","install","unittests"]

39

77

0.692308

429beefc88e6c9cf72106405ad5b6e321025f9d6

20,658

py

Python

views/menuVisualizacaoGeral.py

iOsnaaente/Tracker-solar-Supervisorio

9790c34f0d9df283bc1b92f79b2807875dbcfe3e

[ "MIT" ]

2

2022-01-29T21:33:12.000Z

2022-02-01T12:41:35.000Z

views/menuVisualizacaoGeral.py

iOsnaaente/Tracker-solar-Supervisorio

9790c34f0d9df283bc1b92f79b2807875dbcfe3e

[ "MIT" ]

null

views/menuVisualizacaoGeral.py

iOsnaaente/Tracker-solar-Supervisorio

9790c34f0d9df283bc1b92f79b2807875dbcfe3e

[ "MIT" ]

null

import dearpygui.dearpygui as dpg import datetime as dt import math from registry import * SUN_DATA.update_date() # FUNCTIONS # MAIN FUNCTIONS

70.989691

267

0.554265

429cb5fb216dbdf5ec9ff71a33c2d298dd2c8210

4,071

py

Python

python/jwt.py

angelbarranco/passes-rest-samples

93f54e3e7b651bcfd1b269e2bcd5d9bf9d50ad8c

[ "Apache-2.0" ]

95

2019-06-05T12:45:15.000Z

2022-03-30T14:02:27.000Z

python/jwt.py

angelbarranco/passes-rest-samples

93f54e3e7b651bcfd1b269e2bcd5d9bf9d50ad8c

[ "Apache-2.0" ]

21

2019-06-18T15:41:41.000Z

2022-03-04T15:29:57.000Z

python/jwt.py

angelbarranco/passes-rest-samples

93f54e3e7b651bcfd1b269e2bcd5d9bf9d50ad8c

[ "Apache-2.0" ]

45

2019-06-13T20:57:11.000Z

2022-03-21T13:43:31.000Z

""" Copyright 2019 Google Inc. 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 applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import config import time # for jwt signing. see https://google-auth.readthedocs.io/en/latest/reference/google.auth.jwt.html#module-google.auth.jwt from google.auth import crypt as cryptGoogle from google.auth import jwt as jwtGoogle ############################# # # class that defines JWT format for a Google Pay Pass. # # to check the JWT protocol for Google Pay Passes, check: # https://developers.google.com/pay/passes/reference/s2w-reference#google-pay-api-for-passes-jwt # # also demonstrates RSA-SHA256 signing implementation to make the signed JWT used # in links and buttons. Learn more: # https://developers.google.com/pay/passes/guides/get-started/implementing-the-api/save-to-google-pay # #############################

35.4

121

0.747237

429ce61086d20c4c1d15d20e5249184bf0cc61e3

4,714

py

Python

janus.py

caxmd/januus

79208e2450b4c5b1c81346b99814462f6d083b66

[ "MIT" ]

83

2017-12-11T03:33:10.000Z

2022-02-17T15:13:54.000Z

janus.py

caxmd/januus

79208e2450b4c5b1c81346b99814462f6d083b66

[ "MIT" ]

3

2017-12-25T16:15:44.000Z

2018-06-17T11:06:08.000Z

janus.py

caxmd/januus

79208e2450b4c5b1c81346b99814462f6d083b66

[ "MIT" ]

25

2017-12-11T03:51:12.000Z

2022-02-17T15:13:57.000Z

# Includes some code derived from the cpython project. # Source: https://github.com/python/cpython/blob/master/Lib/zipfile.py # Excuse the mess. import argparse from hashlib import sha1 import os import struct from zipfile import _EndRecData, ZipFile from zlib import adler32 _ECD_SIGNATURE = 0 _ECD_DISK_NUMBER = 1 _ECD_DISK_START = 2 _ECD_ENTRIES_THIS_DISK = 3 _ECD_ENTRIES_TOTAL = 4 _ECD_SIZE = 5 _ECD_OFFSET = 6 _ECD_COMMENT_SIZE = 7 structEndArchive = b"<4s4H2LH" stringEndArchive = b"PK\005\006" structCentralDir = "<4s4B4HL2L5H2L" stringCentralDir = b"PK\001\002" _DEX_MAGIC = 0 _DEX_CHECKSUM = 1 _DEX_SIGNATURE = 2 _DEX_FILE_SIZE = 3 structDexHeader = "<8sI20sI" parser = argparse.ArgumentParser(description="Creates an APK exploiting the Janus vulnerability.") parser.add_argument("apk_in", metavar="original-apk", type=str, help="the source apk to use") parser.add_argument("dex_in", metavar="dex-file", type=str, help="the dex file to prepend") parser.add_argument("apk_out", metavar="output-apk", type=str, help="the file to output to") args = parser.parse_args() with ZipFile(args.apk_in, "r") as apk_in_zip, open(args.apk_in, "rb") as apk_in, open(args.dex_in, "rb") as dex_in, open(args.apk_out, "wb") as apk_out: dex_data = dex_in.read() dex_header = get_dex_header(dex_data) dex_size = os.path.getsize(args.dex_in) orig_endrec = get_endrec(apk_in) new_endrec = get_endrec(apk_in) new_endrec[_ECD_OFFSET] = new_endrec[_ECD_OFFSET] + dex_size final_size = os.path.getsize(args.apk_in) + dex_size apk_in_zip.filelist = sorted(apk_in_zip.filelist, key=sort_info) infolist = apk_in_zip.infolist() for info in infolist: info.date_time = (2042, 14, 3, 0, 62, 18) info.header_offset = info.header_offset + dex_size out_bytes = b"" out_bytes += dex_data[0x24:] out_bytes += apk_in.read()[:orig_endrec[_ECD_OFFSET]] out_bytes += get_centdirs(infolist) out_bytes += pack_endrec(new_endrec) out_bytes = make_dex_header(dex_header, out_bytes, final_size) + out_bytes apk_out.write(out_bytes)

31.218543

152

0.655282

429cf2c16bb83449ca0bd5d3338a9cac6d753159

74

py

Python

constants.py

phy1um/tmtc-discord-bot

7d01cd4c1a78dc0b8aa2bb703c8970ff7bb27f92

[ "MIT" ]

null

constants.py

phy1um/tmtc-discord-bot

7d01cd4c1a78dc0b8aa2bb703c8970ff7bb27f92

[ "MIT" ]

null

constants.py

phy1um/tmtc-discord-bot

7d01cd4c1a78dc0b8aa2bb703c8970ff7bb27f92

[ "MIT" ]

null

ANNOUNCEMENT_ROLE = "941805571915513857" GUILD_ID = "878926572235665418"

18.5

40

0.824324

429eedb68c601680755c430f3d242a23508963a5

3,352

py

Python

test/gst-msdk/transcode/mpeg2.py

haribommi/vaapi-fits

cbf2a463bd3b2c9af5c45a1376b0bde2b703ed23

[ "BSD-3-Clause" ]

null

test/gst-msdk/transcode/mpeg2.py

haribommi/vaapi-fits

cbf2a463bd3b2c9af5c45a1376b0bde2b703ed23

[ "BSD-3-Clause" ]

null

test/gst-msdk/transcode/mpeg2.py

haribommi/vaapi-fits

cbf2a463bd3b2c9af5c45a1376b0bde2b703ed23

[ "BSD-3-Clause" ]

null

## ### Copyright (C) 2018-2019 Intel Corporation ### ### SPDX-License-Identifier: BSD-3-Clause ### from ....lib import * from ..util import * from .transcoder import TranscoderTest spec = load_test_spec("mpeg2", "transcode")

38.976744

107

0.683174

42a05049df648190833a6dde333b459a1ed6a363

10,220

py

Python

rusel/base/context.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

rusel/base/context.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

rusel/base/context.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

import os, time, mimetypes, glob from django.utils.translation import gettext_lazy as _ from django.urls import reverse from task.const import * from task.models import Task, detect_group from rusel.base.config import Config from rusel.base.forms import CreateGroupForm from rusel.context import get_base_context from rusel.utils import extract_get_params

40.078431

196

0.531409

42a0a34d1333c63396ab8f94b968a15d8d78c49d

2,046

py

Python

deepdiy/plugins/system/debugger/debugger.py

IEWbgfnYDwHRoRRSKtkdyMDUzgdwuBYgDKtDJWd/diy

080ddece4f982f22f3d5cff8d9d82e12fcd946a1

[ "MIT" ]

57

2019-05-01T05:27:19.000Z

2022-03-06T12:11:55.000Z

deepdiy/plugins/system/debugger/debugger.py

markusj1201/deepdiy

080ddece4f982f22f3d5cff8d9d82e12fcd946a1

[ "MIT" ]

6

2020-01-28T22:42:22.000Z

2022-02-10T00:13:11.000Z

deepdiy/plugins/system/debugger/debugger.py

markusj1201/deepdiy

080ddece4f982f22f3d5cff8d9d82e12fcd946a1

[ "MIT" ]

13

2019-05-08T03:19:58.000Z

2021-08-02T04:24:15.000Z

import os,rootpath rootpath.append(pattern='main.py') # add the directory of main.py to PATH import glob from kivy.app import App from kivy.lang import Builder from kivy.properties import ObjectProperty,DictProperty,ListProperty from kivy.uix.boxlayout import BoxLayout import logging,importlib,pkgutil if __name__ == '__main__': Test().run()

31

106

0.711632

42a141b9ed0d23fd4819a5a6563c8f54190ea8c2

1,885

py

Python

supervised_learning/classification/perceptron/perceptron.py

Ambitious-idiot/python-machine-learning

6c057dd64fb47de3e822b825135d24896ce13a4a

[ "MIT" ]

3

2021-04-15T06:20:31.000Z

2021-05-28T05:26:06.000Z

supervised_learning/classification/perceptron/perceptron.py

Ambitious-idiot/python-machine-learning

6c057dd64fb47de3e822b825135d24896ce13a4a

[ "MIT" ]

null

supervised_learning/classification/perceptron/perceptron.py

Ambitious-idiot/python-machine-learning

6c057dd64fb47de3e822b825135d24896ce13a4a

[ "MIT" ]

null

import numpy as np

40.106383

116

0.682228

42a1c00f35b59908451cfee2563f53a899db2598

901

py

Python

pygama/dsp/_processors/trap_filter.py

sweigart/pygama

3c5fe4c69230814933b2de879b9a305ff0d4ad5e

[ "Apache-2.0" ]

1

2022-01-19T14:31:56.000Z

pygama/dsp/_processors/trap_filter.py

sweigart/pygama

3c5fe4c69230814933b2de879b9a305ff0d4ad5e

[ "Apache-2.0" ]

1

2020-12-08T20:07:24.000Z

pygama/dsp/_processors/trap_filter.py

sweigart/pygama

3c5fe4c69230814933b2de879b9a305ff0d4ad5e

[ "Apache-2.0" ]

null

import numpy as np from numba import guvectorize

37.541667

102

0.558269

42a67cbf934d63272df061aa18d737365bf0fa29

5,109

py

Python

pilferer/engine.py

Sebastian-dm/pilferer

5126377154c7ba08fbea1a9dfad752bf8b1c72a9

[ "MIT" ]

null

pilferer/engine.py

Sebastian-dm/pilferer

5126377154c7ba08fbea1a9dfad752bf8b1c72a9

[ "MIT" ]

null

pilferer/engine.py

Sebastian-dm/pilferer

5126377154c7ba08fbea1a9dfad752bf8b1c72a9

[ "MIT" ]

null

import tcod from input_handlers import handle_keys from game_states import GameStates from render_functions import clear_all, render_all, RenderOrder from map_objects.game_map import GameMap from fov_functions import initialize_fov, recompute_fov from entity import Entity, get_blocking_entity_at_location from components.fighter import Fighter from death_functions import kill_monster, kill_player VERSION = "0.2" FONT = 'assets/arial10x10.png' screen_width = 80 screen_height = 50 map_width = 80 map_height = 45 room_max_size = 10 room_min_size = 6 max_rooms = 30 fov_algorithm = 0 fov_light_walls = False fov_radius = 10 max_monsters_per_room = 3 colors = { 'dark_wall': tcod.Color(0, 0, 0), 'light_wall': tcod.Color(120, 120, 80), 'dark_ground': tcod.Color(150, 150, 150), 'light_ground': tcod.Color(200, 200, 150) } def main(): """ Main game function """ fighter_component = Fighter(hp=30, defense=2, power=5) player = Entity(0, 0, '@', tcod.white, 'Player', blocks=True, render_order=RenderOrder.ACTOR, fighter=fighter_component) entities = [player] # Import font tcod.console_set_custom_font(FONT, tcod.FONT_TYPE_GREYSCALE | tcod.FONT_LAYOUT_TCOD) # Console initialization tcod.console_init_root(screen_width, screen_height, 'Pilferer %s'%VERSION, False, vsync=False) con = tcod.console.Console(screen_width, screen_height) # Mapping game_map = GameMap(map_width, map_height) game_map.make_map(max_rooms, room_min_size, room_max_size, map_width, map_height, player, entities, max_monsters_per_room) # FOV fov_recompute = True fov_map = initialize_fov(game_map) # Variables for holding input key = tcod.Key() mouse = tcod.Mouse() # Game state game_state = GameStates.PLAYERS_TURN # Main game loop while not tcod.console_is_window_closed(): # FOV if fov_recompute: recompute_fov(fov_map, player.x, player.y, fov_radius, fov_light_walls, fov_algorithm) # Draw render_all(con, entities, player, game_map, fov_map, fov_recompute, screen_width, screen_height, colors) fov_recompute = False tcod.console_flush() clear_all(con, entities) # INDPUT HANDLING tcod.sys_check_for_event(tcod.EVENT_KEY_PRESS, key, mouse) action = handle_keys(key) # Command move player_turn_results = [] move = action.get('move') if move and game_state == GameStates.PLAYERS_TURN: dx, dy = move destination_x = player.x + dx destination_y = player.y + dy if not game_map.is_blocked(destination_x, destination_y): target = get_blocking_entity_at_location(entities, destination_x, destination_y) if target: attack_results = player.fighter.attack(target) player_turn_results.extend(attack_results) else: player.move(dx, dy) fov_recompute = True game_state = GameStates.ENEMY_TURN # Command exit exit = action.get('exit') if exit: return True # Command Fullscreen fullscreen = action.get('fullscreen') if fullscreen: tcod.console_set_fullscreen(not tcod.console_is_fullscreen()) # Results for player_turn_result in player_turn_results: message = player_turn_result.get('message') dead_entity = player_turn_result.get('dead') if message: print(message) if dead_entity: if dead_entity == player: message, game_state = kill_player(dead_entity) else: message = kill_monster(dead_entity) print(message) # Monster turns if game_state == GameStates.ENEMY_TURN: for entity in entities: if entity.ai: enemy_turn_results = entity.ai.take_turn(player, fov_map, game_map, entities) for enemy_turn_result in enemy_turn_results: message = enemy_turn_result.get('message') dead_entity = enemy_turn_result.get('dead') if message: print(message) if dead_entity: if dead_entity == player: message, game_state = kill_player(dead_entity) else: message = kill_monster(dead_entity) print(message) if game_state == GameStates.PLAYER_DEAD: break if game_state == GameStates.PLAYER_DEAD: break else: game_state = GameStates.PLAYERS_TURN game_state = GameStates.PLAYERS_TURN if __name__ == '__main__': main()

32.335443

112

0.603249

42a6cbc1a232b14997c3952e709da0eebe84cd51

2,337

py

Python

galaxy/api/v2/urls.py

SamyCoenen/galaxy

7c17ef45e53b0fc2fe8a2c70a99f3947604e0b0e

[ "Apache-2.0" ]

null

galaxy/api/v2/urls.py

SamyCoenen/galaxy

7c17ef45e53b0fc2fe8a2c70a99f3947604e0b0e

[ "Apache-2.0" ]

null

galaxy/api/v2/urls.py

SamyCoenen/galaxy

7c17ef45e53b0fc2fe8a2c70a99f3947604e0b0e

[ "Apache-2.0" ]

null

# (c) 2012-2019, Ansible by Red Hat # # This file is part of Ansible Galaxy # # Ansible Galaxy is free software: you can redistribute it and/or modify # it under the terms of the Apache License as published by # the Apache Software Foundation, either version 2 of the License, or # (at your option) any later version. # # Ansible Galaxy is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # Apache License for more details. # # You should have received a copy of the Apache License # along with Galaxy. If not, see <http://www.apache.org/licenses/>. from django.urls import path from galaxy.api.v2 import views app_name = 'api' urlpatterns = [ # Collection Imports URLs path('collection-imports/<int:pk>/', views.CollectionImportView.as_view(), name='collection-import-detail'), # Collection Version list URLs path('collections/<int:pk>/versions/', views.VersionListView.as_view(), name='version-list'), path('collections/<str:namespace>/<str:name>/versions/', views.VersionListView.as_view(), name='version-list'), # Collection Version detail URLs path('collection-versions/<int:version_pk>/', views.VersionDetailView.as_view(), name='version-detail'), path('collections/<str:namespace>/<str:name>/versions/<str:version>/', views.VersionDetailView.as_view(), name='version-detail'), # Collection Version Artifact download URLs path('collection-versions/<int:pk>/artifact/', views.CollectionArtifactView.as_view(), name='version-artifact'), path('collections/<namespace>/<name>/versions/<version>/artifact/', views.CollectionArtifactView.as_view(), name='version-artifact'), # Collection URLs path('collections/', views.CollectionListView.as_view(), name='collection-list'), path('collections/<int:pk>/', views.CollectionDetailView.as_view(), name='collection-detail'), # NOTE: needs to come after 'collections/<int:collection_pk>/versions/' path('collections/<str:namespace>/<str:name>/', views.CollectionDetailView.as_view(), name='collection-detail'), ]

35.953846

75

0.682071

42a78f723d388f6c17abd15949a96f2a870ca42a

1,933

py

Python

mindhome_alpha/erpnext/stock/doctype/stock_settings/test_stock_settings.py

Mindhome/field_service

3aea428815147903eb9af1d0c1b4b9fc7faed057

[ "MIT" ]

1

2021-04-29T14:55:29.000Z

mindhome_alpha/erpnext/stock/doctype/stock_settings/test_stock_settings.py

Mindhome/field_service

3aea428815147903eb9af1d0c1b4b9fc7faed057

[ "MIT" ]

null

mindhome_alpha/erpnext/stock/doctype/stock_settings/test_stock_settings.py

Mindhome/field_service

3aea428815147903eb9af1d0c1b4b9fc7faed057

[ "MIT" ]

1

2021-04-29T14:39:01.000Z

42.021739

338

0.698914

42a96ad3b83164695c47573ef1f876f36eb4d891

1,148

py

Python

pybloxy/classes/http.py

R0bl0x10501050/roblox.py

cbbb25878627c2d837caaeb7edf37d0aeda615ae

[ "MIT" ]

null

pybloxy/classes/http.py

R0bl0x10501050/roblox.py

cbbb25878627c2d837caaeb7edf37d0aeda615ae

[ "MIT" ]

null

pybloxy/classes/http.py

R0bl0x10501050/roblox.py

cbbb25878627c2d837caaeb7edf37d0aeda615ae

[ "MIT" ]

null

import logging import requests

26.697674

93

0.722997

42a99e600220ea6f0c20b482db83263664318f69

1,305

py

Python

resources/nuice_simulations/src/layers_sim/layers_sim_node.py

SpyGuyIan/NUice

47991a848dac244b4c476b4a92f7a27a1f9e5dcc

[ "MIT" ]

1

2021-08-17T00:40:42.000Z

resources/nuice_simulations/src/layers_sim/layers_sim_node.py

SpyGuyIan/NUice

47991a848dac244b4c476b4a92f7a27a1f9e5dcc

[ "MIT" ]

1

2021-01-31T17:15:40.000Z

resources/nuice_simulations/src/layers_sim/layers_sim_node.py

NUMarsIce/NUice

47991a848dac244b4c476b4a92f7a27a1f9e5dcc

[ "MIT" ]

null

#!/usr/bin/env python import rospy from std_msgs.msg import Float64 import random possibleLayers = [140, 50, 80, 200, 100] cur_position = 0.0 #Build the layers simulation, then publish material strengths. Lasts 100 seconds. #Get the strength of the next layer from the list of possible layer strengths. #Build the next layer of the simulation. if __name__ == '__main__': runLayersSim()

29

81

0.691954

42a9a106ced30891f6bde30e0be69f4978578110

1,121

py

Python

imagescraper/imagescraper/spiders/image_crawl_spider.py

karthikn2789/Scrapy-Projects

84db4ed1a2f38d6fa03d1bfa6a6ebf9fb527f523

[ "MIT" ]

2

2021-04-08T12:48:10.000Z

2021-06-16T09:42:39.000Z

imagescraper/imagescraper/spiders/image_crawl_spider.py

karthikn2789/Scrapy-Projects

84db4ed1a2f38d6fa03d1bfa6a6ebf9fb527f523

[ "MIT" ]

null

imagescraper/imagescraper/spiders/image_crawl_spider.py

karthikn2789/Scrapy-Projects

84db4ed1a2f38d6fa03d1bfa6a6ebf9fb527f523

[ "MIT" ]

6

2020-08-05T09:45:39.000Z

2021-11-16T14:05:20.000Z

import scrapy import re from scrapy.linkextractors import LinkExtractor from scrapy.spiders import CrawlSpider, Rule from ..items import ImagescraperItem

36.16129

92

0.611954

42a9d7f0de1fb5aee832bc5e97c48ecbdecd3930

10,460

py

Python

scripts/pos_eval.py

ProKil/sparse-text-prototype

e7369dc981fb2c2a94ccb4edca4a7e7c7d7543cd

[ "MIT" ]

19

2020-11-05T12:17:45.000Z

2021-11-17T08:43:50.000Z

scripts/pos_eval.py

ProKil/sparse-text-prototype

e7369dc981fb2c2a94ccb4edca4a7e7c7d7543cd

[ "MIT" ]

1

2021-07-08T13:30:15.000Z

scripts/pos_eval.py

ProKil/sparse-text-prototype

e7369dc981fb2c2a94ccb4edca4a7e7c7d7543cd

[ "MIT" ]

2

2020-12-20T13:19:14.000Z

2021-06-25T20:18:00.000Z

import os import argparse import subprocess import random import edlib from typing import List from collections import Counter import stanza parser = argparse.ArgumentParser(description='Evaluate analysis metrics') parser.add_argument('--prefix', type=str, choices=['inference', 'generation'], help='prediction file prefix') parser.add_argument('--exp-dir', type=str, help='output directory') args = parser.parse_args() fout = open(os.path.join(args.exp_dir, 'analysis_{}_res.txt'.format(args.prefix)), 'w') len_cut = 1000 prototypes, examples = read_file(os.path.join(args.exp_dir, '{}_analysis_input.txt'.format(args.prefix)), len_cut=len_cut) prototype_path = os.path.join(args.exp_dir, 'prototype.txt') prototype_pos_path = os.path.join(args.exp_dir, 'prototype_pos.txt') prototype_rand_path = os.path.join(args.exp_dir, 'prototype_rand.txt') prototype_pos_rand_path = os.path.join(args.exp_dir, 'prototype_pos_rand.txt') example_path = os.path.join(args.exp_dir, 'example.txt') example_pos_path = os.path.join(args.exp_dir, 'example_pos.txt') prototypes_rand = generate_rand_prototype(args.exp_dir, len(examples)) write_file(prototype_path, prototypes) write_file(example_path, examples) write_file(prototype_rand_path, prototypes_rand) # surface BLEU # bleu = subprocess.getoutput( # "./support_prototype/scripts/multi-bleu.perl {} < {}".format(prototype_path, example_rand_path)) bleu = sentence_bleu(prototype_rand_path, example_path) print('Regular BLEU (random baseline): \n{}'.format(bleu)) fout.write('Regular BLEU (random baseline): \n{}'.format(bleu)) fout.write('\n\n\n') # bleu = subprocess.getoutput( # "./support_prototype/scripts/multi-bleu.perl {} < {}".format(prototype_path, example_path)) bleu = sentence_bleu(prototype_path, example_path) print('Regular BLEU: \n{}'.format(bleu)) fout.write('Regular BLEU: \n{}'.format(bleu)) fout.write('\n\n\n') # POS tagging print('POS tagging') nlp = stanza.Pipeline(lang='en', processors='tokenize,mwt,pos', tokenize_pretokenized=True) prototype_doc = nlp('\n'.join(prototypes)) example_doc = nlp('\n'.join(examples)) prototype_rand_doc = nlp('\n'.join(prototypes_rand)) prototypes_pos = [[word.upos for word in sent.words] for sent in prototype_doc.sentences] examples_pos = [[word.upos for word in sent.words] for sent in example_doc.sentences] prototypes_pos_rand = [[word.upos for word in sent.words]for sent in prototype_rand_doc.sentences] write_file(prototype_pos_path, prototypes_pos) write_file(example_pos_path, examples_pos) write_file(prototype_pos_rand_path, prototypes_pos_rand) # POS BLEU # bleu = subprocess.getoutput( # "./support_prototype/scripts/multi-bleu.perl {} < {}".format(prototype_pos_path, example_pos_rand_path)) bleu = sentence_bleu(prototype_pos_rand_path, example_pos_path) print('POS BLEU (random baseline): \n{}'.format(bleu)) fout.write('POS BLEU (random baseline): \n{}'.format(bleu)) fout.write('\n\n\n') # bleu = subprocess.getoutput( # "./support_prototype/scripts/multi-bleu.perl {} < {}".format(prototype_pos_path, example_pos_path)) bleu = sentence_bleu(prototype_pos_path, example_pos_path) print('POS BLEU: \n{}'.format(bleu)) fout.write('POS BLEU: \n{}'.format(bleu)) fout.write('\n\n\n') # break down precision and recall print("compute precision, recall, f1") assert len(prototypes) == len(prototypes_pos) assert len(examples) == len(examples_pos) res = eval_f1(list(prototype_rand_doc.sentences), list(example_doc.sentences)) res = sorted(res.items(), key=lambda item: -item[1].f1) fout.write('random baseline precision-recall\n') fout.write('POS recall precision f1\n') for k, v in res: fout.write('{} {} {} {}\n'.format(k, v.recall, v.precision, v.f1)) fout.write('\n\n\n') res = eval_f1(list(prototype_doc.sentences), list(example_doc.sentences)) res = sorted(res.items(), key=lambda item: -item[1].f1) fout.write('precision-recall\n') fout.write('POS recall precision f1\n') for k, v in res: fout.write('{} {} {} {}\n'.format(k, v.recall, v.precision, v.f1)) fout.write('\n\n\n') # edit operations print("edit analysis") res = eval_edit(list(prototype_doc.sentences), list(example_doc.sentences)) total = sum([sum(v.values()) for k, v in res.items()]) fout.write('total: {}\n'.format(total)) res = sorted(res.items(), key=lambda item: (-sum(item[1].values()))) for k, v in res: fout.write('{}: {}\n'.format(k, sum(v.values()))) for k1, v1 in v.most_common(): fout.write('{}: {} ({:.3f}), '.format(k1, v1, v1 / sum(v.values()))) fout.write('\n\n') fout.close()

33.41853

122

0.603537

42aa82728f6722cbbdd0c68a0e10c8dd5f0958ee

582

py

Python

tests/rules/test_git_stash_pop.py

RogueScholar/thefuck-termux

cc33d5fa0077b2b2323b8a62f3478ff8efef3fba

[ "MIT" ]

null

tests/rules/test_git_stash_pop.py

RogueScholar/thefuck-termux

cc33d5fa0077b2b2323b8a62f3478ff8efef3fba

[ "MIT" ]

null

tests/rules/test_git_stash_pop.py

RogueScholar/thefuck-termux

cc33d5fa0077b2b2323b8a62f3478ff8efef3fba

[ "MIT" ]

null

import pytest from thefuck.rules.git_stash_pop import get_new_command from thefuck.rules.git_stash_pop import match from thefuck.types import Command

26.454545

96

0.707904

42ab556174e9603454893f6f485c837afcd3bad8

3,642

py

Python

src/arima_model.py

SaharCarmel/ARIMA

c54e8554f1c4a95c25687bdf35b4296ed6bd78d6

[ "MIT" ]

null

src/arima_model.py

SaharCarmel/ARIMA

c54e8554f1c4a95c25687bdf35b4296ed6bd78d6

[ "MIT" ]

null

src/arima_model.py

SaharCarmel/ARIMA

c54e8554f1c4a95c25687bdf35b4296ed6bd78d6

[ "MIT" ]

null

""" The ARIMA model. """ import torch import numpy as np

34.358491

77

0.549149

42ab6fa034b5730a8c76b4b76e6056f1b558984c

687

py

Python

problems/slidingwindow/Solution1100.py

akalu/cs-problems-python

9b1bd8e3932be62135a38a77f955ded9a766b654

[ "MIT" ]

null

problems/slidingwindow/Solution1100.py

akalu/cs-problems-python

9b1bd8e3932be62135a38a77f955ded9a766b654

[ "MIT" ]

null

problems/slidingwindow/Solution1100.py

akalu/cs-problems-python

9b1bd8e3932be62135a38a77f955ded9a766b654

[ "MIT" ]

null

""" Sliding window Given a string S, return the number of substrings of length K with no repeated characters. Example 1: Input: S = "havefunonleetcode", K = 5 Output: 6 Explanation: There are 6 substrings they are : 'havef','avefu','vefun','efuno','etcod','tcode'. counter havefunonleetcode IDEA: 1) for each letter in the string setup a counter and 2) update unique counter each time when counter[let] hits 0, 1 or 2 (magic numbers) aaabac ||| 123 0) a:3 unique=0 1) a:2 b:1 unique=1 2) a:2 b:1 unique=1 3) a:2 b:1 c:1 unique=1+2=3 """

18.078947

86

0.58952

42ab8cf968e58717ef4f86c899c0440ef99114b5

26

py

Python

the_file_propagator/__init__.py

joeflack4/the-file-propagator

c72fdad7774c82c8bfa6bf5253b83f6bb1e4e713

[ "MIT" ]

null

the_file_propagator/__init__.py

joeflack4/the-file-propagator

c72fdad7774c82c8bfa6bf5253b83f6bb1e4e713

[ "MIT" ]

null

the_file_propagator/__init__.py

joeflack4/the-file-propagator

c72fdad7774c82c8bfa6bf5253b83f6bb1e4e713

[ "MIT" ]

null

"""The File Propagator"""

13

25

0.653846

42ab9f264f4ecd8a53e0ce06b3bb77538b433100

4,681

py

Python

src/wa_kat/templates/static/js/Lib/site-packages/components/keyword_handler.py

WebArchivCZ/WA-KAT

719f7607222f5a4d917c535b2da6371184222101

[ "MIT" ]

3

2017-03-23T12:59:21.000Z

2017-11-22T08:23:14.000Z

src/wa_kat/templates/static/js/Lib/site-packages/components/keyword_handler.py

WebArchivCZ/WA-KAT

719f7607222f5a4d917c535b2da6371184222101

[ "MIT" ]

89

2015-06-28T22:10:28.000Z

2017-01-30T16:06:05.000Z

src/wa_kat/templates/static/js/Lib/site-packages/components/keyword_handler.py

WebarchivCZ/WA-KAT

719f7607222f5a4d917c535b2da6371184222101

[ "MIT" ]

1

2015-12-17T02:56:59.000Z

#! /usr/bin/env python # -*- coding: utf-8 -*- # # Interpreter version: brython (http://brython.info) (like python3) # # Imports ===================================================================== from os.path import join from browser import window from browser import document # virtual filesystem / modules provided by REST API from virtual_fs import settings # Functions & classes ========================================================= UserKeywordHandler = KeywordListHandler("user_keyword_list") AlephKeywordHandler = KeywordListHandler("aleph_keyword_list") AanalysisKeywordHandler = KeywordListHandler("analysis_keyword_list") KeywordAdder.set_kw_typeahead_input()

29.25625

79

0.580432

42abdb34b5121a34132a5ff61f5b37cf1ca828bc

53

py

Python

scripts/rnn/gru/__init__.py

bfeng/CryptoGRU

65f6fe9eba981fea65fc665ff16938bf3a593001

[ "MIT" ]

1

2022-01-12T03:18:55.000Z

scripts/rnn/gru/__init__.py

bfeng/CryptoGRU

65f6fe9eba981fea65fc665ff16938bf3a593001

[ "MIT" ]

null

scripts/rnn/gru/__init__.py

bfeng/CryptoGRU

65f6fe9eba981fea65fc665ff16938bf3a593001

[ "MIT" ]

null

from .grucell import MyGRUCell from .gru import MyGRU

26.5

30

0.830189

42b002236c965251bc510639be4dce4dd1300339

2,946

py

Python

ZZZ_OtherDemo/00-dyld-832.7.3/testing/kernel-cache-tests/kext-missing-weak-bind/test.py

1079278593/TreasureChest

8b1ebe04ed7c2ed399c4ecf3b75b3fee0a1aced8

[ "MIT" ]

null

ZZZ_OtherDemo/00-dyld-832.7.3/testing/kernel-cache-tests/kext-missing-weak-bind/test.py

1079278593/TreasureChest

8b1ebe04ed7c2ed399c4ecf3b75b3fee0a1aced8

[ "MIT" ]

null

ZZZ_OtherDemo/00-dyld-832.7.3/testing/kernel-cache-tests/kext-missing-weak-bind/test.py

1079278593/TreasureChest

8b1ebe04ed7c2ed399c4ecf3b75b3fee0a1aced8

[ "MIT" ]

null

#!/usr/bin/python2.7 import os import KernelCollection # Check that weak binds can be missing, so long as we check for the magic symbol # [~]> xcrun -sdk iphoneos.internal cc -arch arm64 -Wl,-static -mkernel -nostdlib -Wl,-add_split_seg_info -Wl,-rename_section,__TEXT,__text,__TEXT_EXEC,__text -Wl,-e,__start -Wl,-pagezero_size,0x0 -Wl,-pie -Wl,-sectcreate,__LINKINFO,__symbolsets,SymbolSets.plist -Wl,-segprot,__LINKINFO,r--,r-- main.c -o main.kernel # [~]> xcrun -sdk iphoneos.internal cc -arch arm64 -Wl,-kext -mkernel -nostdlib -Wl,-add_split_seg_info foo.c -o extensions/foo.kext/foo # [~]> xcrun -sdk iphoneos.internal cc -arch arm64 -Wl,-kext -mkernel -nostdlib -Wl,-add_split_seg_info bar.c -o extensions/bar.kext/bar -Wl,-fixup_chains # [~]> rm -r extensions/*.kext/*.ld

62.680851

316

0.681942

42b0f3205382f72fca408d985411165330e27a01

7,453

py

Python

datahub/search/investment/models.py

alixedi/data-hub-api-cd-poc

a5e5ea45bb496c0d2a06635864514af0c7d4291a

[ "MIT" ]

null

datahub/search/investment/models.py

alixedi/data-hub-api-cd-poc

a5e5ea45bb496c0d2a06635864514af0c7d4291a

[ "MIT" ]

16

2020-04-01T15:25:35.000Z

2020-04-14T14:07:30.000Z

datahub/search/investment/models.py

alixedi/data-hub-api-cd-poc

a5e5ea45bb496c0d2a06635864514af0c7d4291a

[ "MIT" ]

null

from elasticsearch_dsl import Boolean, Date, Double, Integer, Keyword, Long, Object, Text from datahub.search import dict_utils from datahub.search import fields from datahub.search.models import BaseESModel DOC_TYPE = 'investment_project' def _related_investment_project_field(): """Field for a related investment project.""" return Object(properties={ 'id': Keyword(), 'name': fields.NormalizedKeyword(), 'project_code': fields.NormalizedKeyword(), })

38.417526

99

0.70106

42b106aaf54e3b2c19e17572d5a63e648baf43b4

1,670

py

Python

robust_sleep_net/models/modulo_net/features_encoder/fully_connected.py

Dreem-Organization/RobustSleepNet

c8ff3f6f857299eb2bf2e9400483084d5ecd4106

[ "MIT" ]

16

2021-04-06T14:04:45.000Z

2022-03-11T14:37:08.000Z

robust_sleep_net/models/modulo_net/features_encoder/fully_connected.py

Dreem-Organization/RobustSleepNet

c8ff3f6f857299eb2bf2e9400483084d5ecd4106

[ "MIT" ]

null

robust_sleep_net/models/modulo_net/features_encoder/fully_connected.py

Dreem-Organization/RobustSleepNet

c8ff3f6f857299eb2bf2e9400483084d5ecd4106

[ "MIT" ]

4

2021-06-10T06:48:33.000Z

2022-03-26T22:29:07.000Z

from collections import OrderedDict import torch from torch import nn

32.115385

96

0.426946

35e91cbc49c53f3ff38da3a05748e14783d919ce

2,968

py

Python

data/rawdata_dataset.py

weiyw16/pytorch-CycleGAN-and-pix2pix

432a91ee6ca8dc606ba0116b27b0948abc48f295

[ "BSD-3-Clause" ]

null

data/rawdata_dataset.py

weiyw16/pytorch-CycleGAN-and-pix2pix

432a91ee6ca8dc606ba0116b27b0948abc48f295

[ "BSD-3-Clause" ]

null

data/rawdata_dataset.py

weiyw16/pytorch-CycleGAN-and-pix2pix

432a91ee6ca8dc606ba0116b27b0948abc48f295

[ "BSD-3-Clause" ]

null

#import import os #import torch #import torch.nn as nn import torch.utils.data as Data #import torchvision import matplotlib.pyplot as plt import h5py #from torch.autograd import Variable import numpy as np import torch #%hist -f rawdata_dataset.py

38.545455

97

0.597035

35eca7541efb5afc537b44ba4b6a0fc5cf5a30dd

310

py

Python

pythons/pythons/pythons_app/urls.py

BoyanPeychinov/python_web_framework

bb3a78c36790821d8b3a2b847494a1138d063193

[ "MIT" ]

null

pythons/pythons/pythons_app/urls.py

BoyanPeychinov/python_web_framework

bb3a78c36790821d8b3a2b847494a1138d063193

[ "MIT" ]

null

pythons/pythons/pythons_app/urls.py

BoyanPeychinov/python_web_framework

bb3a78c36790821d8b3a2b847494a1138d063193

[ "MIT" ]

null

from django.urls import path from . import views from .views import IndexView urlpatterns = [ # path('', views.index, name="index"), path('', IndexView.as_view(), name="index"), # path('create/', views.create, name="create"), path('create/', views.PythonCreateView.as_view(), name="create"), ]

31

69

0.66129

35ed1f868aeb38f0c96a30ed7f9536e255837e20

356

py

Python

tests/python/text_utility.py

Noxsense/mCRL2

dd2fcdd6eb8b15af2729633041c2dbbd2216ad24

[ "BSL-1.0" ]

61

2018-05-24T13:14:05.000Z

2022-03-29T11:35:03.000Z

tests/python/text_utility.py

Noxsense/mCRL2

dd2fcdd6eb8b15af2729633041c2dbbd2216ad24

[ "BSL-1.0" ]

229

2018-05-28T08:31:09.000Z

2022-03-21T11:02:41.000Z

tests/python/text_utility.py

Noxsense/mCRL2

dd2fcdd6eb8b15af2729633041c2dbbd2216ad24

[ "BSL-1.0" ]

28

2018-04-11T14:09:39.000Z

2022-02-25T15:57:39.000Z

29.666667

82

0.691011

35ed5dd8d0b8879efae47e20f5661656b1666fbb

159

py

Python

Dumper/temp.py

NeerajGulia/kafka-monitor

cfcd39a37d22c86d3cebffe289687a030bb84353

[ "Apache-2.0" ]

null

Dumper/temp.py

NeerajGulia/kafka-monitor

cfcd39a37d22c86d3cebffe289687a030bb84353

[ "Apache-2.0" ]

null

Dumper/temp.py

NeerajGulia/kafka-monitor

cfcd39a37d22c86d3cebffe289687a030bb84353

[ "Apache-2.0" ]

null

import datetime t1 = datetime.datetime(2019, 3, 9, 10, 55, 30, 991882) t2 = datetime.datetime(2019, 3, 10, 10, 55, 30, 991882) print((t2-t1).total_seconds())

26.5

55

0.685535

35ee497682f551e6df5ef747e053a1c6578b24fe

1,401

py

Python

listools/llogic/is_descending.py

jgarte/listools

17ef56fc7dde701890213f248971d8dc7a6e6b7c

[ "MIT" ]

2

2019-01-22T03:50:43.000Z

2021-04-22T16:12:17.000Z

listools/llogic/is_descending.py

jgarte/listools

17ef56fc7dde701890213f248971d8dc7a6e6b7c

[ "MIT" ]

2

2019-01-22T03:57:49.000Z

2021-04-22T22:03:47.000Z

listools/llogic/is_descending.py

jgarte/listools

17ef56fc7dde701890213f248971d8dc7a6e6b7c

[ "MIT" ]

1

2021-04-22T21:13:00.000Z

def is_descending(input_list: list, step: int = -1) -> bool: r"""llogic.is_descending(input_list[, step]) This function returns True if the input list is descending with a fixed step, otherwise it returns False. Usage: >>> alist = [3, 2, 1, 0] >>> llogic.is_descending(alist) True The final value can be other than zero: >>> alist = [12, 11, 10] >>> llogic.is_descending(alist) True The list can also have negative elements: >>> alist = [2, 1, 0, -1, -2] >>> llogic.is_descending(alist) True It will return False if the list is not ascending: >>> alist = [6, 5, 9, 2] >>> llogic.is_descending(alist) False By default, the function uses steps of size 1 so the list below is not considered as ascending: >>> alist = [7, 5, 3, 1] >>> llogic.is_descending(alist) False But the user can set the step argument to any value less than one: >>> alist = [7, 5, 3, 1] >>> step = -2 >>> llogic.is_descending(alist, step) True """ if not isinstance(input_list, list): raise TypeError('\'input_list\' must be \'list\'') if not isinstance(step, int): raise TypeError('\'step\' must be \'int\'') if step > 1: raise ValueError('\'step\' must be < 0') aux_list = list(range(max(input_list), min(input_list)-1, step)) return input_list == aux_list

27.470588

75

0.608851

35ef2ec3e738f6a7d680ddbb0d8cfed8a80181c4

384

py

Python

blazer/hpc/local/__init__.py

radiantone/blazer

4f369729a72a397a5a472f081002bf24cf22b69c

[ "CC0-1.0" ]

4

2022-02-11T13:37:03.000Z

2022-02-26T00:25:13.000Z

blazer/hpc/local/__init__.py

radiantone/blazer

4f369729a72a397a5a472f081002bf24cf22b69c

[ "CC0-1.0" ]

null

blazer/hpc/local/__init__.py

radiantone/blazer

4f369729a72a397a5a472f081002bf24cf22b69c

[ "CC0-1.0" ]

null

from functools import partial from pipe import select, where from pydash import chunk from pydash import filter_ as filter from pydash import flatten, get, omit from .primitives import parallel, pipeline, scatter __all__ = ( "parallel", "scatter", "pipeline", "partial", "select", "where", "flatten", "chunk", "omit", "get", "filter", )

16.695652

51

0.648438

35f130f559ed7cd7af033555dccc66ba4d2035c4

304

py

Python

resumebuilder/resumebuilder.py

kinshuk4/ResumeBuilder

2c997f73b522c0668f3a66afb372bd91c6408b3c

[ "MIT" ]

1

2020-01-04T05:54:19.000Z

resumebuilder/resumebuilder.py

kinshuk4/ResumeBuilder

2c997f73b522c0668f3a66afb372bd91c6408b3c

[ "MIT" ]

null

resumebuilder/resumebuilder.py

kinshuk4/ResumeBuilder

2c997f73b522c0668f3a66afb372bd91c6408b3c

[ "MIT" ]

null

import yaml if __name__ == '__main__': main()

17.882353

45

0.664474

35f16309c334902b0ed8ed87b8f07d61caa46a9a

6,025

py

Python

backend/tests/unittests/metric_source/test_report/junit_test_report_tests.py

ICTU/quality-report

f6234e112228ee7cfe6476c2d709fe244579bcfe

[ "Apache-2.0" ]

25

2016-11-25T10:41:24.000Z

2021-07-03T14:02:49.000Z

backend/tests/unittests/metric_source/test_report/junit_test_report_tests.py

ICTU/quality-report

f6234e112228ee7cfe6476c2d709fe244579bcfe

[ "Apache-2.0" ]

783

2016-09-19T12:10:21.000Z

2021-01-04T20:39:15.000Z

backend/tests/unittests/metric_source/test_report/junit_test_report_tests.py

ICTU/quality-report

f6234e112228ee7cfe6476c2d709fe244579bcfe

[ "Apache-2.0" ]

15

2015-03-25T13:52:49.000Z

2021-03-08T17:17:56.000Z

""" Copyright 2012-2019 Ministerie van Sociale Zaken en Werkgelegenheid 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 distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import datetime import unittest from unittest.mock import Mock import urllib.error from dateutil.tz import tzutc, tzlocal from hqlib.metric_source import JunitTestReport

47.81746

113

0.64249

35f24e93301e26ad076b53b869df2630d390d615

965

py

Python

lang/Python/compare-sorting-algorithms-performance-6.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

1

2018-11-09T22:08:38.000Z

lang/Python/compare-sorting-algorithms-performance-6.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

null

lang/Python/compare-sorting-algorithms-performance-6.py

ethansaxenian/RosettaDecode

8ea1a42a5f792280b50193ad47545d14ee371fb7

[ "MIT" ]

1

2018-11-09T22:08:40.000Z

sort_functions = [ builtinsort, # see implementation above insertion_sort, # see [[Insertion sort]] insertion_sort_lowb, # ''insertion_sort'', where sequential search is replaced # by lower_bound() function qsort, # see [[Quicksort]] qsortranlc, # ''qsort'' with randomly choosen ''pivot'' # and the filtering via list comprehension qsortranpart, # ''qsortranlc'' with filtering via ''partition'' function qsortranpartis, # ''qsortranpart'', where for a small input sequence lengths ] # ''insertion_sort'' is called if __name__=="__main__": import sys sys.setrecursionlimit(10000) write_timings(npoints=100, maxN=1024, # 1 <= N <= 2**10 an input sequence length sort_functions=sort_functions, sequence_creators = (ones, range, shuffledrange)) plot_timings()

50.789474

85

0.598964

35f445a5ba07dee2c2143db897f87a8a3259db16

6,300

py

Python

server/organization/tests.py

NicholasNagy/ALTA

ca07627481ee91f2969b0fc8e8f15e2a37b3e992

[ "Apache-2.0" ]

3

2020-09-09T23:26:29.000Z

2020-10-17T22:58:34.000Z

server/organization/tests.py

NicholasNagy/ALTA

ca07627481ee91f2969b0fc8e8f15e2a37b3e992

[ "Apache-2.0" ]

294

2020-09-27T17:20:50.000Z

2021-06-23T01:44:09.000Z

server/organization/tests.py

NicholasNagy/ALTA

ca07627481ee91f2969b0fc8e8f15e2a37b3e992

[ "Apache-2.0" ]

10

2020-10-07T05:25:30.000Z

2021-05-01T05:32:59.000Z

from rest_framework import status from rest_framework.test import APITestCase from rest_framework.test import APIClient from django.db.models import signals import factory from user_account.models import CustomUser from .models import Organization

45.985401

161

0.686667

35f470bfac10a58409ff19aa1d364eb85ab7359d

1,656

py

Python

src/mumblecode/convert.py

Mumbleskates/mumblecode

0221c33a09df154bf80ece73ff907c51d2a971f0

[ "MIT" ]

1

2016-05-17T23:07:38.000Z

src/mumblecode/convert.py

Mumbleskates/mumblecode

0221c33a09df154bf80ece73ff907c51d2a971f0

[ "MIT" ]

null

src/mumblecode/convert.py

Mumbleskates/mumblecode

0221c33a09df154bf80ece73ff907c51d2a971f0

[ "MIT" ]

null

# coding=utf-8 from math import log2, ceil # valid chars for a url path component: a-z A-Z 0-9 .-_~!$&'()*+,;=:@ # For the default set here (base 72) we have excluded $'();:@ radix_alphabet = ''.join(sorted( "0123456789" "abcdefghijklmnopqrstuvwxyz" "ABCDEFGHIJKLMNOPQRSTUVWXYZ" ".-_~!&*+,=" )) radix = len(radix_alphabet) radix_lookup = {ch: i for i, ch in enumerate(radix_alphabet)} length_limit = ceil(128 / log2(radix)) # don't decode numbers much over 128 bits # TODO: add radix alphabet as parameter # TODO: fix format so length conveys m ore information (e.g. 0 and 00 and 000 are different with decimal alphabet) def natural_to_url(n): """Accepts an int and returns a url-compatible string representing it""" # map from signed int to positive int url = "" while n: n, digit = divmod(n, radix) url += radix_alphabet[digit] return url or radix_alphabet[0] def url_to_natural(url): """Accepts a string and extracts the int it represents in this radix encoding""" if not url or len(url) > length_limit: return None n = 0 try: for ch in reversed(url): n = n * radix + radix_lookup[ch] except KeyError: return None return n

24.352941

114

0.634662

35f52784cb920f6695ea0214e66ce046c4ba0969

961

py

Python

flaskapp/routes.py

vijay0707/Send-Email-Flask

3e8f981c5ef4c4051f61b5229eb3e56a35142bc7

[ "MIT" ]

null

flaskapp/routes.py

vijay0707/Send-Email-Flask

3e8f981c5ef4c4051f61b5229eb3e56a35142bc7

[ "MIT" ]

null

flaskapp/routes.py

vijay0707/Send-Email-Flask

3e8f981c5ef4c4051f61b5229eb3e56a35142bc7

[ "MIT" ]

null

from flaskapp import app, db, mail from flask import render_template, url_for from flask import request, flash, redirect # from flaskapp.model import User from flaskapp.form import SurveyForm from flask_mail import Message

32.033333

97

0.632674

35f622ff3fa5187c3265b7d1252636eaf5af175d

5,708

py

Python

tests/test_camera.py

Gokender/kameramera

7ebd9a196809c1e7ab117bb11b90bcea8d1eb8e7

[ "MIT" ]

null

tests/test_camera.py

Gokender/kameramera

7ebd9a196809c1e7ab117bb11b90bcea8d1eb8e7

[ "MIT" ]

null

tests/test_camera.py

Gokender/kameramera

7ebd9a196809c1e7ab117bb11b90bcea8d1eb8e7

[ "MIT" ]

null

import unittest from kameramera import camera

31.711111

82

0.637176

35f678cde08c5ff864121819c46adfa1fdba45f0

887

py

Python

app/coordinates.py

krasch/simply_landmarks

8a5c3f2ff476377e44646a00e61b8287a53260e3

[ "MIT" ]

14

2020-02-03T22:30:48.000Z

2021-11-01T09:41:34.000Z

app/coordinates.py

krasch/simply_landmarks

8a5c3f2ff476377e44646a00e61b8287a53260e3

[ "MIT" ]

3

2020-11-28T17:24:28.000Z

2022-01-26T19:56:35.000Z

app/coordinates.py

krasch/simply_landmarks

8a5c3f2ff476377e44646a00e61b8287a53260e3

[ "MIT" ]

4

2020-10-11T21:26:53.000Z

2021-09-14T03:59:20.000Z

from pathlib import Path from PIL import Image # coordinates are sent as slightly weird URL parameters (e.g. 0.png?214,243) # parse them, will crash server if they are coming in unexpected format # image was not displayed in original size -> need to convert the coordinates

27.71875

77

0.67982

35f6bdfd466ccfcc3ec731821bd0d70b92cb5b92

2,851

py

Python

lib/tool_images.py

KTingLee/image-training

c02c7caa81a55b61e935d07ead27bcaed468eb0a

[ "MIT" ]

null

lib/tool_images.py

KTingLee/image-training

c02c7caa81a55b61e935d07ead27bcaed468eb0a

[ "MIT" ]

2

2021-01-22T09:10:33.000Z

2021-01-22T14:22:09.000Z

lib/tool_images.py

KTingLee/image-training

c02c7caa81a55b61e935d07ead27bcaed468eb0a

[ "MIT" ]

1

2021-01-22T08:56:34.000Z

import matplotlib.pyplot as plt import numpy as np import math import cv2 kernel = np.ones((3, 3), np.int8) # # # # threshold1,2 # # if __name__ == '__main__': pic = cv2.imread('../captcha_Images/0.png') print(pic) cv2.imshow('pic', pic) cv2.waitKey(0) erosion = eraseImage(pic) blured = blurImage(erosion) edged = edgedImage(blured) dilated = dilateImage(edged) charBox = getCharBox(dilated) showCharBox(dilated, charBox) dilated = dilateImage(edged, (4, 4)) chars = resizeImage(dilated, charBox) # input("Press Enter to continue.") # c = result[0][0][0][0] # print(c) # plt.plot(c) cv2.waitKey(0) cv2.destroyAllWindows()

25.684685

88

0.62785

35f6e6f91f9e05d76fd7957364cd9c3157a56978

2,965

py

Python

Code/geneset_testing.py

dylkot/EbolaSC

d363f9d2c10911f01c7b1d22fec2b192df2569b1

[ "MIT" ]

2

2020-09-28T09:27:33.000Z

2021-01-04T09:16:42.000Z

Code/geneset_testing.py

dylkot/SC-Ebola

d363f9d2c10911f01c7b1d22fec2b192df2569b1

[ "MIT" ]

null

Code/geneset_testing.py

dylkot/SC-Ebola

d363f9d2c10911f01c7b1d22fec2b192df2569b1

[ "MIT" ]

null

import pandas as pd import numpy as np from scipy.stats import mannwhitneyu, fisher_exact, ranksums def load_geneset(gmtfn, genes=None, minsize=0): ''' Load genesets stored in gmt format (e.g. as provided by msigdb) gmtfn : str path to gmt file genes : list, optional only include genes in this input minsize : int, optional minimum geneset size to keep Returns ------- gsets : dict gene_set_name : set of genes allsetgenes : set set of genes found in all genesets combined ''' allsetgenes = set() if genes is not None: genes = set(genes) gsets = {} effect_min_size = minsize+2 # account for gset name cols with open(gmtfn) as F: for l in F.readlines(): words = [x for x in l.rstrip().split('\t')] gsetname = words[0] setgenes = words[2:] if genes is not None: setgenes = set(setgenes).intersection(genes) else: setgenes = set(setgenes[2:]) if len(setgenes) >= effect_min_size: gsets[gsetname] = setgenes allsetgenes = allsetgenes.union(setgenes) return(gsets, allsetgenes)

29.949495

89

0.57774

35f85f5cb5fab6226fab7a5a01b0882ca5ca7ca9

54

py

Python

tests/src/import_func.py

bayashi-cl/expander

b3623b656a71801233797e05781295a6101fefd8

[ "CC0-1.0" ]

null

tests/src/import_func.py

bayashi-cl/expander

b3623b656a71801233797e05781295a6101fefd8

[ "CC0-1.0" ]

1

2022-03-12T20:41:21.000Z

2022-03-13T06:34:30.000Z

tests/src/import_func.py

bayashi-cl/expander

b3623b656a71801233797e05781295a6101fefd8

[ "CC0-1.0" ]

null

from testlib_a.main_a import print_name print_name()

13.5

39

0.833333

35f901a5b14d9bb965c94938ad6cacba20eb8f77

2,167

py

Python

nn_wtf/parameter_optimizers/brute_force_optimizer.py

lene/nn-wtf

4696f143d936e0c0c127847e3bb1e93a6e756d35

[ "Apache-2.0" ]

null

nn_wtf/parameter_optimizers/brute_force_optimizer.py

lene/nn-wtf

4696f143d936e0c0c127847e3bb1e93a6e756d35

[ "Apache-2.0" ]

20

2016-02-20T12:43:04.000Z

2016-12-23T13:57:25.000Z

nn_wtf/parameter_optimizers/brute_force_optimizer.py

lene/nn-wtf

4696f143d936e0c0c127847e3bb1e93a6e756d35

[ "Apache-2.0" ]

null

import pprint from nn_wtf.parameter_optimizers.neural_network_optimizer import NeuralNetworkOptimizer __author__ = 'Lene Preuss <lene.preuss@gmail.com>'

38.696429

119

0.677434

35f926086eaca9043bf3f10e9c0ac0804430ebb4

1,856

py

Python

tests/test_get_value.py

mdpiper/bmi-example-python

e6b1e9105daef44fe1f0adba5b857cde1bbd032a

[ "MIT" ]

3

2020-10-20T08:59:19.000Z

2021-10-18T17:57:06.000Z

tests/test_get_value.py

mdpiper/bmi-example-python

e6b1e9105daef44fe1f0adba5b857cde1bbd032a

[ "MIT" ]

4

2019-04-19T20:07:15.000Z

2021-01-28T23:34:35.000Z

tests/test_get_value.py

mdpiper/bmi-example-python

e6b1e9105daef44fe1f0adba5b857cde1bbd032a

[ "MIT" ]

7

2020-08-05T17:25:34.000Z

2021-09-08T21:38:33.000Z

#!/usr/bin/env python from numpy.testing import assert_array_almost_equal, assert_array_less import numpy as np from heat import BmiHeat

24.746667

82

0.715517

35fac5891884a7fafbd906447065470f94dbe9cf

9,158

py

Python

tensorflow/dgm/exp.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

tensorflow/dgm/exp.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

tensorflow/dgm/exp.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

import numpy as np import tensorflow as tf import sys, os sys.path.extend(['alg/', 'models/']) from visualisation import plot_images from encoder_no_shared import encoder, recon from utils import init_variables, save_params, load_params, load_data from eval_test_ll import construct_eval_func dimZ = 50 dimH = 500 n_channel = 128 batch_size = 50 lr = 1e-4 K_mc = 10 checkpoint = -1 if __name__ == '__main__': data_name = str(sys.argv[1]) method = str(sys.argv[2]) assert method in ['noreg', 'laplace', 'ewc', 'si', 'onlinevi'] if method == 'onlinevi': lbd = 1.0 # some placeholder, doesn't matter else: lbd = float(sys.argv[3]) main(data_name, method, dimZ, dimH, n_channel, batch_size, K_mc, checkpoint, lbd)

40.166667

102

0.597183

35fb641cc4c232d5e95579ae3bf4fec4904fbdf7

1,663

py

Python

src/cltl/combot/infra/config/k8config.py

leolani/cltl-combot

7008742ba9db782166f79322658a8cb49890d61b

[ "MIT" ]

1

2020-11-21T18:53:22.000Z

src/cltl/combot/infra/config/k8config.py

leolani/cltl-combot

7008742ba9db782166f79322658a8cb49890d61b

[ "MIT" ]

null

src/cltl/combot/infra/config/k8config.py

leolani/cltl-combot

7008742ba9db782166f79322658a8cb49890d61b

[ "MIT" ]

null

import logging import os import cltl.combot.infra.config.local as local_config logger = logging.getLogger(__name__) K8_CONFIG_DIR = "/cltl_k8_config" K8_CONFIG = "config/k8.config"

36.955556

116

0.710764

35fb6a7aec8441ab62bd7a834d5a31a1a31bbbcf

17,640

py

Python

act_map/scripts/exp_compare_diff_maps.py

debugCVML/rpg_information_field

56f9ffba83aaee796502116e1cf651c5bc405bf6

[ "MIT" ]

149

2020-06-23T12:08:47.000Z

2022-03-31T08:18:52.000Z

act_map/scripts/exp_compare_diff_maps.py

debugCVML/rpg_information_field

56f9ffba83aaee796502116e1cf651c5bc405bf6

[ "MIT" ]

4

2020-08-28T07:51:15.000Z

2021-04-09T13:18:49.000Z

act_map/scripts/exp_compare_diff_maps.py

debugCVML/rpg_information_field

56f9ffba83aaee796502116e1cf651c5bc405bf6

[ "MIT" ]

34

2020-06-26T14:50:34.000Z

2022-03-04T06:45:55.000Z

#!/usr/bin/env python import os import argparse import yaml import numpy as np from colorama import init, Fore, Style from matplotlib import rc import matplotlib.pyplot as plt import plot_utils as pu init(autoreset=True) rc('font', **{'serif': ['Cardo'], 'size': 20}) rc('text', usetex=True) kMetrics = ['det', 'mineig', 'trace'] kMetricsLabels = ['$\det$', '$\lambda_{min}$', '${Tr}$'] kSecToUs = 1.0e6 kPallete = [ 'blue', 'green', 'red', 'gold', 'purple', 'gray', 'cyan', 'midnightblue', 'lime', 'lightcoral', 'darkgoldenrod', 'violet', 'dimgray', 'darkorange', 'black' ] if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--res_dir', required=True) parser.add_argument('--analyze_config', required=True) parser.add_argument('--save_dir', type=str, default='analysis_results') parser.add_argument('--pc_res_key', type=str, default='quad_info_0p5') parser.set_defaults(map_names=['quad_info', 'quad_trace', 'gp_info', 'gp_trace']) args = parser.parse_args() print(Fore.YELLOW + args.__dict__.__str__()) with open(args.analyze_config, 'r') as f: cfg = yaml.load(f, Loader=yaml.FullLoader) print("Read configurations:\n{}".format(cfg)) map_names = [] map_nm_to_label = {} for d in cfg['all_maps']: map_nm_to_label.update(d) for k in d: map_names.append(k) print(Fore.GREEN + "Maps to compare:\n- {}".format('\n- '.join(map_names))) print(Fore.GREEN + "Labels:\n{}".format(map_nm_to_label)) fim_map_nms = [v for v in map_names if 'info' in v] compare_orient_map_nms = [v for v in map_names if 'info' in v] compare_cont_motion_map_nms = [v for v in map_names if 'info' in v] print("Will analyze FIM for {}".format(fim_map_nms)) print("Will compare orientations for {}".format(compare_orient_map_nms)) print("Will compare cont. motion for {}".format(compare_cont_motion_map_nms)) save_dir = os.path.join(args.res_dir, args.save_dir) if not os.path.exists(save_dir): os.makedirs(save_dir) else: print(Fore.RED + "Save folder exists, will re-use and overwrite.") print("Going to save to {}".format(save_dir)) map_nm_to_res = {} for map_nm in map_names: print(Fore.GREEN + "====> Reading {}...".format(map_nm)) map_nm_to_res[map_nm] = readResults(args.res_dir, map_nm) print(Fore.YELLOW + Style.BRIGHT + "Start analysis.") print(Fore.GREEN + "1. Table of complexity.") _writeComplexityTable(map_nm_to_res, args.pc_res_key, map_names, map_nm_to_label, os.path.join(save_dir, 'complexity_table.txt')) print(Fore.GREEN + "2. FIM difference.") map_nm_to_fim_diff_perc = _computeAndWriteFIMDiff( map_nm_to_res, fim_map_nms, map_nm_to_label, save_dir) _boxplotFIMDiffs(map_nm_to_fim_diff_perc, fim_map_nms, map_nm_to_label, save_dir) print(Fore.GREEN + "3. Optimal views.") map_nm_to_orient_diff = _computeAndWriteOptimalOrientDiff( map_nm_to_res, compare_orient_map_nms, map_nm_to_label, save_dir) _boxplotOrientDiffs(map_nm_to_orient_diff, compare_orient_map_nms, map_nm_to_label, save_dir) print(Fore.GREEN + "4. Continous motion.") _compareContinuousMotion(map_nm_to_res, compare_cont_motion_map_nms, map_nm_to_label, save_dir) print(Fore.GREEN + Style.BRIGHT + "Start processing specified subsets...") sel_dir = os.path.join(save_dir, 'selected_results') if not os.path.exists(sel_dir): os.makedirs(sel_dir) if 'sel_complexity_table_entries' in cfg: print(Fore.GREEN + "- complexity table") _writeComplexityTable(map_nm_to_res, args.pc_res_key, cfg['sel_complexity_table_entries'], map_nm_to_label, os.path.join( sel_dir, 'complexity_table.txt')) if 'sel_fro_norm_table_entries' in cfg: print(Fore.GREEN + "- FIM diff. table") sel_fim_nms = cfg['sel_fro_norm_table_entries'] sel_nm_to_fim_diff = _computeAndWriteFIMDiff( map_nm_to_res, sel_fim_nms, map_nm_to_label, sel_dir) _boxplotFIMDiffs(sel_nm_to_fim_diff, sel_fim_nms, map_nm_to_label, sel_dir) if 'sel_hist_orient_entries' in cfg: sel_orient_nms = cfg['sel_hist_orient_entries'] print(Fore.GREEN + "- Orientation diff.") sel_nm_to_orient_diff = _computeAndWriteOptimalOrientDiff( map_nm_to_res, sel_orient_nms, map_nm_to_label, sel_dir) _boxplotOrientDiffs(sel_nm_to_orient_diff, sel_orient_nms, map_nm_to_label, sel_dir) if 'sel_cont_motion_plot' in cfg: print(Fore.GREEN + "- continuous motion") _compareContinuousMotion( map_nm_to_res, cfg['sel_cont_motion_plot'], map_nm_to_label, sel_dir)

41.505882

129

0.626361

35fbe8e8b4f1e1aa102f85306945ce878960b4de

52

py

Python

tests/conftest.py

grintor/Hello-Wolrd-CI

1f1b8c40f55d0b35cd73601ed90567a84abf03db

[ "Apache-2.0" ]

null

tests/conftest.py

grintor/Hello-Wolrd-CI

1f1b8c40f55d0b35cd73601ed90567a84abf03db

[ "Apache-2.0" ]

null

tests/conftest.py

grintor/Hello-Wolrd-CI

1f1b8c40f55d0b35cd73601ed90567a84abf03db

[ "Apache-2.0" ]

null

# see: https://stackoverflow.com/a/34520971/3238695

26

51

0.769231

35fc69cf4551ec557452a3db41e67d9efead2ebf

1,318

py

Python

Files/SpeechRecognition/speechDandR.py

JahnaviDoneria/HomeAutomationSystem

0419ba4a0fefd16b9a5c7a19fef7897d76850dc2

[ "MIT" ]

null

Files/SpeechRecognition/speechDandR.py

JahnaviDoneria/HomeAutomationSystem

0419ba4a0fefd16b9a5c7a19fef7897d76850dc2

[ "MIT" ]

null

Files/SpeechRecognition/speechDandR.py

JahnaviDoneria/HomeAutomationSystem

0419ba4a0fefd16b9a5c7a19fef7897d76850dc2

[ "MIT" ]

1

2020-01-20T13:04:55.000Z

import json import apiai import speech_recognition as sr #speechRecognition()

23.122807

63

0.651745

35fcbb05f8e3b57b8ab5311822807b3114647a9f

4,667

py

Python

mylib/dataset/coco.py

duducheng/deeplabv3p_gluon

fd8e3e8d834838a9a221785b825499c62cee578f

[ "Apache-2.0" ]

66

2018-07-20T04:01:41.000Z

2021-11-08T10:40:49.000Z

mylib/dataset/coco.py

duducheng/deeplabv3p_gluon

fd8e3e8d834838a9a221785b825499c62cee578f

[ "Apache-2.0" ]

6

2018-08-16T08:06:39.000Z

2020-11-28T13:07:21.000Z

mylib/dataset/coco.py

duducheng/deeplabv3p_gluon

fd8e3e8d834838a9a221785b825499c62cee578f

[ "Apache-2.0" ]

11

2018-07-20T18:00:29.000Z

2020-04-28T15:21:58.000Z

# raise NotImplementedError("Did not check!") """MSCOCO Semantic Segmentation pretraining for VOC.""" import os from tqdm import trange from PIL import Image, ImageOps, ImageFilter import numpy as np import pickle from gluoncv.data.segbase import SegmentationDataset

40.582609

92

0.555817

35fd4da34b0954ed2f821de46d87379191733efa

1,045

py

Python

find_other_news_sources.py

sr33/OtherNewsSources

17857381a5690d5e89d4a034f1fc60f61c2377dc

[ "MIT" ]

10

2015-07-17T09:57:38.000Z

2020-05-24T20:09:20.000Z

find_other_news_sources.py

sr33/OtherNewsSources

17857381a5690d5e89d4a034f1fc60f61c2377dc

[ "MIT" ]

null

find_other_news_sources.py

sr33/OtherNewsSources

17857381a5690d5e89d4a034f1fc60f61c2377dc

[ "MIT" ]

null

# __author__ = 'sree' import urllib2 from lxml import html import requests

40.192308

119

0.702392

35fda7f9b73a414c879824f59fa81da72f267f5a

35,235

py

Python

code/client/munkilib/adobeutils/adobeinfo.py

Rippling/munki

115832687d4411ca825202ec82d9a27053fef7c8

[ "Apache-2.0" ]

1

2021-10-06T12:56:14.000Z

code/client/munkilib/adobeutils/adobeinfo.py

Rippling/munki

115832687d4411ca825202ec82d9a27053fef7c8

[ "Apache-2.0" ]

null

code/client/munkilib/adobeutils/adobeinfo.py

Rippling/munki

115832687d4411ca825202ec82d9a27053fef7c8

[ "Apache-2.0" ]

null

# encoding: utf-8 # Copyright 2009-2020 Greg Neagle. # # 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 # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ adobeutils.adobeinfo Created by Greg Neagle on 2017-01-06. Utilities to get info about Adobe installers/uninstallers """ from __future__ import absolute_import, print_function import os import json import sqlite3 from glob import glob from xml.dom import minidom from .. import osutils from .. import pkgutils def find_install_app(dirpath): '''Searches dirpath and enclosed directories for Install.app. Returns the path to the actual executable.''' for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith("Install.app"): setup_path = os.path.join(path, "Contents", "MacOS", "Install") if os.path.exists(setup_path): return setup_path return '' def find_setup_app(dirpath): '''Search dirpath and enclosed directories for Setup.app. Returns the path to the actual executable.''' for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith("Setup.app"): setup_path = os.path.join(path, "Contents", "MacOS", "Setup") if os.path.exists(setup_path): return setup_path return '' def find_adobepatchinstaller_app(dirpath): '''Searches dirpath and enclosed directories for AdobePatchInstaller.app. Returns the path to the actual executable.''' for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith("AdobePatchInstaller.app"): setup_path = os.path.join( path, "Contents", "MacOS", "AdobePatchInstaller") if os.path.exists(setup_path): return setup_path return '' def find_adobe_deployment_manager(dirpath): '''Searches dirpath and enclosed directories for AdobeDeploymentManager. Returns path to the executable.''' for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith("pkg/Contents/Resources"): dm_path = os.path.join(path, "AdobeDeploymentManager") if os.path.exists(dm_path): return dm_path return '' def find_acrobat_patch_app(dirpath): '''Attempts to find an AcrobatPro patching application in dirpath. If found, returns the path to the bundled patching script.''' for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith(".app"): # look for Adobe's patching script patch_script_path = os.path.join( path, 'Contents', 'Resources', 'ApplyOperation.py') if os.path.exists(patch_script_path): return path return '' def get_payload_info(dirpath): '''Parses Adobe payloads, pulling out info useful to munki. .proxy.xml files are used if available, or for CC-era updates which do not contain one, the Media_db.db file, which contains identical XML, is instead used. CS3/CS4: contain only .proxy.xml CS5/CS5.5/CS6: contain both CC: contain only Media_db.db''' payloadinfo = {} # look for .proxy.xml file dir if os.path.isdir(dirpath): proxy_paths = glob(os.path.join(dirpath, '*.proxy.xml')) if proxy_paths: xmlpath = proxy_paths[0] dom = minidom.parse(xmlpath) # if there's no .proxy.xml we should hope there's a Media_db.db else: db_path = os.path.join(dirpath, 'Media_db.db') if os.path.exists(db_path): conn = sqlite3.connect(db_path) cur = conn.cursor() cur.execute("SELECT value FROM PayloadData WHERE " "PayloadData.key = 'PayloadInfo'") result = cur.fetchone() cur.close() if result: info_xml = result[0].encode('UTF-8') dom = minidom.parseString(info_xml) else: # no xml, no db, no payload info! return payloadinfo payload_info = dom.getElementsByTagName('PayloadInfo') if payload_info: installer_properties = payload_info[0].getElementsByTagName( 'InstallerProperties') if installer_properties: properties = installer_properties[0].getElementsByTagName( 'Property') for prop in properties: if 'name' in list(prop.attributes.keys()): propname = prop.attributes['name'].value.encode('UTF-8') propvalue = '' for node in prop.childNodes: propvalue += node.nodeValue if propname == 'AdobeCode': payloadinfo['AdobeCode'] = propvalue if propname == 'ProductName': payloadinfo['display_name'] = propvalue if propname == 'ProductVersion': payloadinfo['version'] = propvalue installmetadata = payload_info[0].getElementsByTagName( 'InstallDestinationMetadata') if installmetadata: totalsizes = installmetadata[0].getElementsByTagName( 'TotalSize') if totalsizes: installsize = '' for node in totalsizes[0].childNodes: installsize += node.nodeValue payloadinfo['installed_size'] = int(int(installsize)/1024) return payloadinfo def get_adobe_setup_info(installroot): '''Given the root of mounted Adobe DMG, look for info about the installer or updater''' info = {} payloads = [] # look for all the payloads folders for (path, dummy_dirs, dummy_files) in os.walk(installroot): if path.endswith('/payloads'): driverfolder = '' media_signature = '' setupxml = os.path.join(path, 'setup.xml') if os.path.exists(setupxml): dom = minidom.parse(setupxml) drivers = dom.getElementsByTagName('Driver') if drivers: driver = drivers[0] if 'folder' in list(driver.attributes.keys()): driverfolder = driver.attributes[ 'folder'].value.encode('UTF-8') if driverfolder == '': # look for mediaSignature (CS5 AAMEE install) setup_elements = dom.getElementsByTagName('Setup') if setup_elements: media_signature_elements = setup_elements[ 0].getElementsByTagName('mediaSignature') if media_signature_elements: element = media_signature_elements[0] for node in element.childNodes: media_signature += node.nodeValue for item in osutils.listdir(path): payloadpath = os.path.join(path, item) payloadinfo = get_payload_info(payloadpath) if payloadinfo: payloads.append(payloadinfo) if ((driverfolder and item == driverfolder) or (media_signature and payloadinfo['AdobeCode'] == media_signature)): info['display_name'] = payloadinfo['display_name'] info['version'] = payloadinfo['version'] info['AdobeSetupType'] = 'ProductInstall' if not payloads: # look for an extensions folder; almost certainly this is an Updater for (path, dummy_dirs, dummy_files) in os.walk(installroot): if path.endswith("/extensions"): for item in osutils.listdir(path): #skip LanguagePacks if item.find("LanguagePack") == -1: itempath = os.path.join(path, item) payloadinfo = get_payload_info(itempath) if payloadinfo: payloads.append(payloadinfo) # we found an extensions dir, # so no need to keep walking the install root break if payloads: if len(payloads) == 1: info['display_name'] = payloads[0]['display_name'] info['version'] = payloads[0]['version'] else: if 'display_name' not in info: info['display_name'] = "ADMIN: choose from payloads" if 'version' not in info: info['version'] = "ADMIN please set me" info['payloads'] = payloads installed_size = 0 for payload in payloads: installed_size = installed_size + payload.get('installed_size', 0) info['installed_size'] = installed_size return info def get_adobe_package_info(installroot): '''Gets the package name from the AdobeUberInstaller.xml file; other info from the payloads folder''' info = get_adobe_setup_info(installroot) info['description'] = "" installerxml = os.path.join(installroot, "AdobeUberInstaller.xml") if os.path.exists(installerxml): description = '' dom = minidom.parse(installerxml) installinfo = dom.getElementsByTagName("InstallInfo") if installinfo: packagedescriptions = \ installinfo[0].getElementsByTagName("PackageDescription") if packagedescriptions: prop = packagedescriptions[0] for node in prop.childNodes: description += node.nodeValue if description: description_parts = description.split(' : ', 1) info['display_name'] = description_parts[0] if len(description_parts) > 1: info['description'] = description_parts[1] else: info['description'] = "" return info else: installerxml = os.path.join(installroot, "optionXML.xml") if os.path.exists(installerxml): dom = minidom.parse(installerxml) installinfo = dom.getElementsByTagName("InstallInfo") if installinfo: pkgname_elems = installinfo[0].getElementsByTagName( "PackageName") if pkgname_elems: prop = pkgname_elems[0] pkgname = "" for node in prop.childNodes: pkgname += node.nodeValue info['display_name'] = pkgname if not info.get('display_name'): info['display_name'] = os.path.basename(installroot) return info def get_xml_text_element(dom_node, name): '''Returns the text value of the first item found with the given tagname''' value = None subelements = dom_node.getElementsByTagName(name) if subelements: value = '' for node in subelements[0].childNodes: value += node.nodeValue return value def parse_option_xml(option_xml_file): '''Parses an optionXML.xml file and pulls the items of interest, returning them in a dictionary''' info = {} dom = minidom.parse(option_xml_file) installinfo = dom.getElementsByTagName('InstallInfo') if installinfo: if 'id' in list(installinfo[0].attributes.keys()): info['packager_id'] = installinfo[0].attributes['id'].value if 'version' in list(installinfo[0].attributes.keys()): info['packager_version'] = installinfo[ 0].attributes['version'].value info['package_name'] = get_xml_text_element( installinfo[0], 'PackageName') info['package_id'] = get_xml_text_element(installinfo[0], 'PackageID') info['products'] = [] # CS5 to CC 2015.0-2015.2 releases use RIBS, and we retrieve a # display name, version and 'mediaSignature' for building installs # items. SAPCode is also stored so that we can later search by this # key across both RIBS and HyperDrive installer metadata. medias_elements = installinfo[0].getElementsByTagName('Medias') if medias_elements: media_elements = medias_elements[0].getElementsByTagName('Media') if media_elements: for media in media_elements: product = {} product['prodName'] = get_xml_text_element( media, 'prodName') product['prodVersion'] = get_xml_text_element( media, 'prodVersion') product['SAPCode'] = get_xml_text_element(media, 'SAPCode') setup_elements = media.getElementsByTagName('Setup') if setup_elements: media_signature_elements = setup_elements[ 0].getElementsByTagName('mediaSignature') if media_signature_elements: product['mediaSignature'] = '' element = media_signature_elements[0] for node in element.childNodes: product['mediaSignature'] += node.nodeValue info['products'].append(product) # HD (HyperDrive) media for new mid-June 2016 products. We need the # SAP codes, versions, and which ones are MediaType 'Product'. Support # payloads seem to all be 'STI', and are listed as STIDependencies under # the main product. hd_medias_elements = installinfo[0].getElementsByTagName('HDMedias') if hd_medias_elements: hd_media_elements = hd_medias_elements[0].getElementsByTagName( 'HDMedia') if hd_media_elements: for hd_media in hd_media_elements: product = {} product['hd_installer'] = True # productVersion is the 'full' version number # prodVersion seems to be the "customer-facing" version for # this update # baseVersion is the first/base version for this standalone # product/channel/LEID, # not really needed here so we don't copy it for elem in [ 'mediaLEID', 'prodVersion', 'productVersion', 'SAPCode', 'MediaType', 'TargetFolderName']: product[elem] = get_xml_text_element(hd_media, elem) info['products'].append(product) return info def get_hd_installer_info(hd_payload_root, sap_code): '''Attempts to extract some information from a HyperDrive payload application.json file and return a reduced set in a dict''' hd_app_info = {} app_json_path = os.path.join(hd_payload_root, sap_code, 'Application.json') json_info = json.loads(open(app_json_path, 'r').read()) # Copy some useful top-level keys, useful later for: # - Name: display_name pkginfo key # - ProductVersion: version pkginfo key and uninstall XML location # - SAPCode: an uninstallXml for an installs item if it's a 'core' Type # - BaseVersion and version: not currently used but may be useful once # there are more HD installers in the future for key in ['BaseVersion', 'Name', 'ProductVersion', 'SAPCode', 'version']: hd_app_info[key] = json_info[key] hd_app_info['SAPCode'] = json_info['SAPCode'] # Adobe puts an array of dicts in a dict with one key called 'Package' pkgs = [pkg for pkg in json_info['Packages']['Package']] hd_app_info['Packages'] = pkgs return hd_app_info def get_cs5_media_signature(dirpath): '''Returns the CS5 mediaSignature for an AAMEE CS5 install. dirpath is typically the root of a mounted dmg''' payloads_dir = "" # look for a payloads folder for (path, dummy_dirs, dummy_files) in os.walk(dirpath): if path.endswith('/payloads'): payloads_dir = path # return empty-handed if we didn't find a payloads folder if not payloads_dir: return '' # now look for setup.xml setupxml = os.path.join(payloads_dir, 'Setup.xml') if os.path.exists(setupxml) and os.path.isfile(setupxml): # parse the XML dom = minidom.parse(setupxml) setup_elements = dom.getElementsByTagName('Setup') if setup_elements: media_signature_elements = ( setup_elements[0].getElementsByTagName('mediaSignature')) if media_signature_elements: element = media_signature_elements[0] elementvalue = '' for node in element.childNodes: elementvalue += node.nodeValue return elementvalue return "" def get_cs5_uninstall_xml(option_xml_file): '''Gets the uninstall deployment data from a CS5 installer''' xml = '' dom = minidom.parse(option_xml_file) deployment_info = dom.getElementsByTagName('DeploymentInfo') if deployment_info: for info_item in deployment_info: deployment_uninstall = info_item.getElementsByTagName( 'DeploymentUninstall') if deployment_uninstall: deployment_data = deployment_uninstall[0].getElementsByTagName( 'Deployment') if deployment_data: deployment = deployment_data[0] xml += deployment.toxml('UTF-8') return xml def count_payloads(dirpath): '''Attempts to count the payloads in the Adobe installation item. Used for rough percent-done progress feedback.''' count = 0 for (path, dummy_dirs, files) in os.walk(dirpath): if path.endswith("/payloads"): # RIBS-style installers for subitem in osutils.listdir(path): subitempath = os.path.join(path, subitem) if os.path.isdir(subitempath): count = count + 1 elif "/HD/" in path and "Application.json" in files: # we're inside an HD installer directory. The payloads/packages # are .zip files zip_file_count = len( [item for item in files if item.endswith(".zip")]) count = count + zip_file_count return count def get_adobe_install_info(installdir): '''Encapsulates info used by the Adobe Setup/Install app.''' adobe_install_info = {} if installdir: adobe_install_info['media_signature'] = get_cs5_media_signature( installdir) adobe_install_info['payload_count'] = count_payloads(installdir) option_xml_file = os.path.join(installdir, "optionXML.xml") if os.path.exists(option_xml_file): adobe_install_info['uninstallxml'] = get_cs5_uninstall_xml( option_xml_file) return adobe_install_info # Disable PyLint complaining about 'invalid' camelCase names # pylint: disable=invalid-name def getAdobeCatalogInfo(mountpoint, pkgname=""): '''Used by makepkginfo to build pkginfo data for Adobe installers/updaters''' # look for AdobeDeploymentManager (AAMEE installer) deploymentmanager = find_adobe_deployment_manager(mountpoint) if deploymentmanager: dirpath = os.path.dirname(deploymentmanager) option_xml_file = os.path.join(dirpath, 'optionXML.xml') option_xml_info = {} if os.path.exists(option_xml_file): option_xml_info = parse_option_xml(option_xml_file) cataloginfo = get_adobe_package_info(dirpath) if cataloginfo: # add some more data if option_xml_info.get('packager_id') == u'CloudPackager': # CCP package cataloginfo['display_name'] = option_xml_info.get( 'package_name', 'unknown') cataloginfo['name'] = cataloginfo['display_name'].replace( ' ', '') cataloginfo['uninstallable'] = True cataloginfo['uninstall_method'] = "AdobeCCPUninstaller" cataloginfo['installer_type'] = "AdobeCCPInstaller" cataloginfo['minimum_os_version'] = "10.6.8" mediasignatures = [ item['mediaSignature'] for item in option_xml_info.get('products', []) if 'mediaSignature' in item] else: # AAMEE package cataloginfo['name'] = cataloginfo['display_name'].replace( ' ', '') cataloginfo['uninstallable'] = True cataloginfo['uninstall_method'] = "AdobeCS5AAMEEPackage" cataloginfo['installer_type'] = "AdobeCS5AAMEEPackage" cataloginfo['minimum_os_version'] = "10.5.0" cataloginfo['adobe_install_info'] = get_adobe_install_info( installdir=dirpath) mediasignature = cataloginfo['adobe_install_info'].get( "media_signature") mediasignatures = [mediasignature] # Determine whether we have HD media as well in this installer hd_metadata_dirs = [ product['TargetFolderName'] for product in option_xml_info['products'] if product.get('hd_installer')] hd_app_infos = [] for sap_code in hd_metadata_dirs: hd_app_info = get_hd_installer_info( os.path.join(dirpath, 'HD'), sap_code) hd_app_infos.append(hd_app_info) # 'installs' array will be populated if we have either RIBS # or HD installers, which may be mixed together in one # CCP package. # Acrobat Pro DC doesn't currently generate any useful installs # info if it's part of a CCP package. installs = [] # media signatures are used for RIBS (CS5 to CC mid-2015) if mediasignatures: # make a default <key>installs</key> array uninstalldir = "/Library/Application Support/Adobe/Uninstall" for mediasignature in mediasignatures: signaturefile = mediasignature + ".db" filepath = os.path.join(uninstalldir, signaturefile) installitem = {} installitem['path'] = filepath installitem['type'] = 'file' installs.append(installitem) # Custom installs items for HD installers seem to need only HDMedias # from optionXML.xml with a MediaType of 'Product' and their # 'core' packages (e.g. language packs are 'non-core') if hd_app_infos: if 'payloads' not in cataloginfo: cataloginfo['payloads'] = [] cataloginfo['payloads'].extend(hd_app_infos) # Calculate installed_size by counting packages in payloads # in these indexed HD medias. installed_size may exist already # if this package contained RIBS payloads, so try reading it # and default to 0. This will typically include several very # small packages (language or regional recommended settings) # which would not actually get installed. These seem to be # no larger than a few MB, so in practice it increases the # 'installed_size' value by only ~1%. installed_size = cataloginfo.get('installed_size', 0) for hd_payload in hd_app_infos: for package in hd_payload['Packages']: # Generally, all app installs will include 1-3 'core' # packages and then additional language/settings/color # packages which are regional or language-specific. # If we filter this by including both unconditional # installs and those which are language/region specific, # we get a rough approximation of the total size of # supplemental packages, as their equivalents for other # languages are very close to the same size. We also # get one included language package which would be the # case for any install. # # Because InDesign CC 2017 is not like any other package # and contains a 'Condition' key but as an empty # string, we explicitly test this case as well. if ('Condition' not in list(package.keys()) or package.get('Condition') == '' or '[installLanguage]==en_US' in package.get('Condition', '')): installed_size += int(package.get( 'ExtractSize', 0) / 1024) # We get much closer to Adobe's "HDSetup" calculated # install space requirement if we include both the # DownloadSize and ExtractSize data # (DownloadSize is just the zip file size) installed_size += int(package.get( 'DownloadSize', 0) / 1024) # Add another 300MB for the CC app and plumbing in case they've # never been installed on the system installed_size += 307200 cataloginfo['installed_size'] = installed_size uninstalldir = ( '/Library/Application Support/Adobe/Installers/uninstallXml' ) product_saps = [ prod['SAPCode'] for prod in option_xml_info['products'] if prod.get('MediaType') == 'Product' ] product_app_infos = [app for app in hd_app_infos if app['SAPCode'] in product_saps] # if we had only a single HD and no legacy apps, set a sane # version and display_name derived from the app's metadata if (len(product_app_infos) == 1) and not mediasignatures: cataloginfo.update({ 'display_name': product_app_infos[0]['Name'], 'version': product_app_infos[0]['ProductVersion'], }) for app_info in product_app_infos: for pkg in app_info['Packages']: # Don't assume 'Type' key always exists. At least the #'AdobeIllustrator20-Settings' # package doesn't have this key set. if pkg.get('Type') == 'core': # We can't use 'ProductVersion' from # Application.json for the part following the # SAPCode, because it's usually too specific and # won't match the "short" product version. # We can take 'prodVersion' from the optionXML.xml # instead. # We filter out any non-HD installers to avoid # matching up the wrong versions for packages that # may contain multiple different major versions of # a given SAPCode pkg_prod_vers = [ prod['prodVersion'] for prod in option_xml_info['products'] if prod.get('hd_installer') and prod['SAPCode'] == app_info['SAPCode']][0] uninstall_file_name = '_'.join([ app_info['SAPCode'], pkg_prod_vers.replace('.', '_'), pkg['PackageName'], pkg['PackageVersion']]) + '.pimx' filepath = os.path.join( uninstalldir, uninstall_file_name) installitem = {} installitem['path'] = filepath installitem['type'] = 'file' installs.append(installitem) if installs: cataloginfo['installs'] = installs return cataloginfo # Look for Install.app (Bare metal CS5 install) # we don't handle this type, but we'll report it # back so makepkginfo can provide an error message # installapp = find_install_app(mountpoint) # if installapp: # cataloginfo = {} # cataloginfo['installer_type'] = "AdobeCS5Installer" # return cataloginfo # Look for AdobePatchInstaller.app (CS5 updater) installapp = find_adobepatchinstaller_app(mountpoint) if os.path.exists(installapp): # this is a CS5 updater disk image cataloginfo = get_adobe_package_info(mountpoint) if cataloginfo: # add some more data cataloginfo['name'] = cataloginfo['display_name'].replace(' ', '') cataloginfo['uninstallable'] = False cataloginfo['installer_type'] = "AdobeCS5PatchInstaller" if pkgname: cataloginfo['package_path'] = pkgname # make some (hopefully functional) installs items from the payloads installs = [] uninstalldir = "/Library/Application Support/Adobe/Uninstall" # first look for a payload with a display_name matching the # overall display_name for payload in cataloginfo.get('payloads', []): if (payload.get('display_name', '') == cataloginfo['display_name']): if 'AdobeCode' in payload: dbfile = payload['AdobeCode'] + ".db" filepath = os.path.join(uninstalldir, dbfile) installitem = {} installitem['path'] = filepath installitem['type'] = 'file' installs.append(installitem) break if installs == []: # didn't find a payload with matching name # just add all of the non-LangPack payloads # to the installs list. for payload in cataloginfo.get('payloads', []): if 'AdobeCode' in payload: if ("LangPack" in payload.get("display_name") or "Language Files" in payload.get( "display_name")): # skip Language Packs continue dbfile = payload['AdobeCode'] + ".db" filepath = os.path.join(uninstalldir, dbfile) installitem = {} installitem['path'] = filepath installitem['type'] = 'file' installs.append(installitem) cataloginfo['installs'] = installs return cataloginfo # Look for AdobeUberInstaller items (CS4 install) pkgroot = os.path.join(mountpoint, pkgname) adobeinstallxml = os.path.join(pkgroot, "AdobeUberInstaller.xml") if os.path.exists(adobeinstallxml): # this is a CS4 Enterprise Deployment package cataloginfo = get_adobe_package_info(pkgroot) if cataloginfo: # add some more data cataloginfo['name'] = cataloginfo['display_name'].replace(' ', '') cataloginfo['uninstallable'] = True cataloginfo['uninstall_method'] = "AdobeUberUninstaller" cataloginfo['installer_type'] = "AdobeUberInstaller" if pkgname: cataloginfo['package_path'] = pkgname return cataloginfo # maybe this is an Adobe update DMG or CS3 installer # look for Adobe Setup.app setuppath = find_setup_app(mountpoint) if setuppath: cataloginfo = get_adobe_setup_info(mountpoint) if cataloginfo: # add some more data cataloginfo['name'] = cataloginfo['display_name'].replace(' ', '') cataloginfo['installer_type'] = "AdobeSetup" if cataloginfo.get('AdobeSetupType') == "ProductInstall": cataloginfo['uninstallable'] = True cataloginfo['uninstall_method'] = "AdobeSetup" else: cataloginfo['description'] = "Adobe updater" cataloginfo['uninstallable'] = False cataloginfo['update_for'] = ["PleaseEditMe-1.0.0.0.0"] return cataloginfo # maybe this is an Adobe Acrobat 9 Pro patcher? acrobatpatcherapp = find_acrobat_patch_app(mountpoint) if acrobatpatcherapp: cataloginfo = {} cataloginfo['installer_type'] = "AdobeAcrobatUpdater" cataloginfo['uninstallable'] = False plist = pkgutils.getBundleInfo(acrobatpatcherapp) cataloginfo['version'] = pkgutils.getVersionString(plist) cataloginfo['name'] = "AcrobatPro9Update" cataloginfo['display_name'] = "Adobe Acrobat Pro Update" cataloginfo['update_for'] = ["AcrobatPro9"] cataloginfo['RestartAction'] = 'RequireLogout' cataloginfo['requires'] = [] cataloginfo['installs'] = [ {'CFBundleIdentifier': 'com.adobe.Acrobat.Pro', 'CFBundleName': 'Acrobat', 'CFBundleShortVersionString': cataloginfo['version'], 'path': '/Applications/Adobe Acrobat 9 Pro/Adobe Acrobat Pro.app', 'type': 'application'} ] return cataloginfo # didn't find any Adobe installers/updaters we understand return None # pylint: enable=invalid-name if __name__ == '__main__': print('This is a library of support tools for the Munki Suite.')

44.657795

80

0.565319

35fe055b65de9e34581ebd9b036ec7f195d41986

645

py

Python

mandrel/config/helpers.py

gf-atebbe/python-mandrel

64b90e3265a522ff72019960752bcc716533347f

[ "MIT" ]

null

mandrel/config/helpers.py

gf-atebbe/python-mandrel

64b90e3265a522ff72019960752bcc716533347f

[ "MIT" ]

null

mandrel/config/helpers.py

gf-atebbe/python-mandrel

64b90e3265a522ff72019960752bcc716533347f

[ "MIT" ]

null

from .. import util

25.8

81

0.626357

35ff001cebfbaa2f16c6208ca4d5a99ce422a736

1,606

py

Python

Components/MoveComponent.py

RuoxiQin/Unmanned-Aerial-Vehicle-Tracking

49a0a32abcce42fc6bf9e71f5b098ec708373153

[ "Apache-2.0" ]

13

2018-06-16T12:52:18.000Z

2021-08-14T02:43:24.000Z

Components/MoveComponent.py

RuoxiQin/Unmanned-Aerial-Vehicle-Tracking

49a0a32abcce42fc6bf9e71f5b098ec708373153

[ "Apache-2.0" ]

null

Components/MoveComponent.py

RuoxiQin/Unmanned-Aerial-Vehicle-Tracking

49a0a32abcce42fc6bf9e71f5b098ec708373153

[ "Apache-2.0" ]

6

2019-06-20T21:06:01.000Z

2021-08-14T02:43:28.000Z

#!/usr/bin/python #-*-coding:utf-8-*- from Component import Component

34.170213

104

0.52802

35ff5a9fe6f25456cafae5f86dcd151f7638267e

35,016

py

Python

poshc2/server/Tasks.py

slackr/PoshC2

d4804f1f534dac53b95dd6dd6578431beaf79360

[ "BSD-3-Clause" ]

1,504

2016-07-12T04:14:00.000Z

2022-03-31T02:59:30.000Z

poshc2/server/Tasks.py

PhilKeeble/PoshC2

498b30097e12e46b5aa454feaeaa4bbae3c04c0d

[ "BSD-3-Clause" ]

139

2016-10-13T10:41:18.000Z

2022-03-31T13:22:47.000Z

poshc2/server/Tasks.py

PhilKeeble/PoshC2

498b30097e12e46b5aa454feaeaa4bbae3c04c0d

[ "BSD-3-Clause" ]

377

2016-07-12T03:10:03.000Z

2022-03-31T10:04:13.000Z

import datetime, hashlib, base64, traceback, os, re import poshc2.server.database.DB as DB from poshc2.Colours import Colours from poshc2.server.Config import ModulesDirectory, DownloadsDirectory, ReportsDirectory from poshc2.server.Implant import Implant from poshc2.server.Core import decrypt, encrypt, default_response, decrypt_bytes_gzip, number_of_days, process_mimikatz, print_bad from poshc2.server.Core import load_module, load_module_sharp, encrypt, default_response from poshc2.server.payloads.Payloads import Payloads from poshc2.server.PowerStatus import translate_power_status from poshc2.Utils import randomuri

64.486188

474

0.499714

c4005a008048988474573247edb485bd20d1bb6d

1,029

py

Python

Leetcode/89.grayCode.py

Song2017/Leetcode_python

99d9f3cec0e47ddab6ec107392a6b33bf6c1d046

[ "MIT" ]

1

2019-05-14T00:55:30.000Z

LeetcodeView/89.grayCode.md

Song2017/Leetcode_python

99d9f3cec0e47ddab6ec107392a6b33bf6c1d046

[ "MIT" ]

null

LeetcodeView/89.grayCode.md

Song2017/Leetcode_python

99d9f3cec0e47ddab6ec107392a6b33bf6c1d046

[ "MIT" ]

null

s = Solution() print(s.grayCode(3))

25.725

62

0.433431