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

54d9afa8624f72c8f6f8e3ffc3c4fcb52e42ad11

1,744

py

Python

iri-node/fabfile.py

jinnerbichler/home-automflashion

f93442712322ab819651f453437c11f685640e83

[ "Apache-2.0" ]

8

2018-02-06T15:18:08.000Z

2020-07-12T20:16:22.000Z

iri-node/fabfile.py

jinnerbichler/home-autoflashion

f93442712322ab819651f453437c11f685640e83

[ "Apache-2.0" ]

1

2018-09-02T17:10:57.000Z

2018-10-02T04:14:43.000Z

iri-node/fabfile.py

jinnerbichler/home-autoflashion

f93442712322ab819651f453437c11f685640e83

[ "Apache-2.0" ]

1

2019-08-14T04:39:48.000Z

import time from fabric.api import run, env, task, put, cd, local, sudo env.use_ssh_config = True env.hosts = ['iota_node']

24.222222

113

0.639908

54da3dc2f38e9f403fcf4bc41db3259f59c8f372

1,763

py

Python

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

features.py

ptorresmanque/MachineLearning_v2.0

795e47b9cfc68f4e0fefb700d43af6c59e2f1d73

[ "MIT" ]

null

import sqlite3 from random import randint, choice import numpy as np conn = sqlite3.connect('ej.db') c = conn.cursor() #OBTENIENDO TAMAnOS MAXIMOS MINIMOS Y PROMEDIO# c.execute('SELECT MAX(alto) FROM features') resultado = c.fetchone() if resultado: altoMax = resultado[0] c.execute('SELECT MIN(alto) FROM features') resultado = c.fetchone() if resultado: altoMin = resultado[0] altoProm = abs((altoMax + altoMin) / 2) #print altoMax , altoProm , altoMin arrAlto = [altoMax , altoProm , altoMin] c.execute('SELECT MAX(ancho) FROM features') resultado = c.fetchone() if resultado: anchoMax = resultado[0] c.execute('SELECT MIN(ancho) FROM features') resultado = c.fetchone() if resultado: anchoMin = resultado[0] anchoProm = abs((anchoMax + anchoMin) / 2) anchoMaxProm = abs((anchoMax + anchoProm) / 2) anchoMinProm = abs((anchoMin + anchoProm) / 2) arrAncho = [anchoMax, anchoMaxProm, anchoProm, anchoMinProm, anchoMin] #### CREANDO CLASES NEGATIVAS for i in range(0,3): for j in range(0,5): for _ in range(10): negAncho = arrAncho[j] negAlto = arrAlto[i] rand_alto_max = int(negAlto * 1.5) rand_alto_min = int(negAlto * 0.5) r3 = rand_alto_max * 2 rand_ancho_max = int(negAncho*1.5) rand_ancho_min = int(negAncho*0.5) r33 = rand_ancho_max * 2 f1 = choice([np.random.randint(1, rand_alto_min), np.random.randint(rand_alto_max, r3)]) f2 = choice([np.random.randint(1, rand_ancho_min), np.random.randint(rand_ancho_max, r33)]) c.execute("insert into features (ancho, alto, area, clase) values (?, ?, ?, ?)", (f2, f1, f2*f1, 0)) conn.commit() conn.close()

23.506667

103

0.640953

54da935d3d5cf04aac496677e269b59710d17100

5,503

py

Python

dev/ideas/cython/playing_around.py

achilleas-k/brian2

906563b6b1321585b082f79f74f1b4ab386347ec

[ "BSD-2-Clause" ]

null

dev/ideas/cython/playing_around.py

achilleas-k/brian2

906563b6b1321585b082f79f74f1b4ab386347ec

[ "BSD-2-Clause" ]

null

dev/ideas/cython/playing_around.py

achilleas-k/brian2

906563b6b1321585b082f79f74f1b4ab386347ec

[ "BSD-2-Clause" ]

null

from pylab import * import cython import time, timeit from brian2.codegen.runtime.cython_rt.modified_inline import modified_cython_inline import numpy from scipy import weave import numexpr import theano from theano import tensor as tt tau = 20 * 0.001 N = 1000000 b = 1.2 # constant current mean, the modulation varies freq = 10.0 t = 0.0 dt = 0.0001 _array_neurongroup_a = a = linspace(.05, 0.75, N) _array_neurongroup_v = v = rand(N) ns = {'_array_neurongroup_a': a, '_array_neurongroup_v': v, '_N': N, 'dt': dt, 't': t, 'tau': tau, 'b': b, 'freq': freq,# 'sin': numpy.sin, 'pi': pi, } code = ''' cdef int _idx cdef int _vectorisation_idx cdef int N = <int>_N cdef double a, v, _v #cdef double [:] _cy_array_neurongroup_a = _array_neurongroup_a #cdef double [:] _cy_array_neurongroup_v = _array_neurongroup_v cdef double* _cy_array_neurongroup_a = &(_array_neurongroup_a[0]) cdef double* _cy_array_neurongroup_v = &(_array_neurongroup_v[0]) for _idx in range(N): _vectorisation_idx = _idx a = _cy_array_neurongroup_a[_idx] v = _cy_array_neurongroup_v[_idx] _v = a*sin(2.0*freq*pi*t) + b + v*exp(-dt/tau) + (-a*sin(2.0*freq*pi*t) - b)*exp(-dt/tau) #_v = a*b+0.0001*sin(v) #_v = a*b+0.0001*v v = _v _cy_array_neurongroup_v[_idx] = v ''' f_mod, f_arg_list = modified_cython_inline(code, locals=ns, globals={}) # return theano.function([a, v], # a*tt.sin(2.0*freq*pi*t) + b + v*tt.exp(-dt/tau) + (-a*tt.sin(2.0*freq*pi*t) - b)*tt.exp(-dt/tau)) theano.config.gcc.cxxflags = '-O3 -ffast-math' theano_func = get_theano_func() #print theano.pp(theano_func.maker.fgraph.outputs[0]) #print #theano.printing.debugprint(theano_func.maker.fgraph.outputs[0]) #theano.printing.pydotprint(theano_func, 'func.png') #exit() if __name__=='__main__': funcs = [#timefunc_cython_inline, timefunc_cython_modified_inline, timefunc_numpy, timefunc_numpy_smart, timefunc_numpy_blocked, timefunc_numexpr, timefunc_numexpr_smart, timefunc_weave_slow, timefunc_weave_fast, timefunc_theano, ] if 1: print 'Values' print '======' for f in funcs: check_values(f) print if 1: print 'Times' print '=====' for f in funcs: dotimeit(f)

30.743017

125

0.589678

54db106024a4f46cf548821fe280245ccaf57da7

114

py

Python

azbankgateways/views/__init__.py

lordmahyar/az-iranian-bank-gateways

e9eb7101f2b91318847d63d783c22c4a8d430ba3

[ "MIT" ]

196

2020-12-07T11:29:19.000Z

2022-03-23T09:32:56.000Z

azbankgateways/views/__init__.py

lordmahyar/az-iranian-bank-gateways

e9eb7101f2b91318847d63d783c22c4a8d430ba3

[ "MIT" ]

25

2021-01-13T11:56:35.000Z

2022-03-14T19:41:51.000Z

azbankgateways/views/__init__.py

lordmahyar/az-iranian-bank-gateways

e9eb7101f2b91318847d63d783c22c4a8d430ba3

[ "MIT" ]

44

2021-01-08T18:27:47.000Z

2022-03-22T03:36:04.000Z

from .banks import callback_view, go_to_bank_gateway from .samples import sample_payment_view, sample_result_view

38

60

0.877193

54db89c835de6895b4c1b46df78297a288ccdb1f

3,254

py

Python

dev/unittest/update.py

PowerDNS/exabgp

bbf69f25853e10432fbe588b5bc2f8d9f1e5dda2

[ "BSD-3-Clause" ]

8

2015-01-11T09:57:26.000Z

2019-07-05T05:57:02.000Z

dev/unittest/update.py

Acidburn0zzz/exabgp

bbf69f25853e10432fbe588b5bc2f8d9f1e5dda2

[ "BSD-3-Clause" ]

1

2018-11-15T22:10:09.000Z

2018-11-15T22:20:31.000Z

dev/unittest/update.py

Acidburn0zzz/exabgp

bbf69f25853e10432fbe588b5bc2f8d9f1e5dda2

[ "BSD-3-Clause" ]

6

2015-09-11T01:51:06.000Z

2020-03-10T19:16:18.000Z

#!/usr/bin/env python # encoding: utf-8 """ update.py Created by Thomas Mangin on 2009-09-06. Copyright (c) 2009-2013 Exa Networks. All rights reserved. """ import unittest from exabgp.configuration.environment import environment env = environment.setup('') from exabgp.bgp.message.update.update import * from exabgp.bgp.message.update.attribute.community import to_Community from exabgp.bgp.message.update.attribute.community import Community, Communities # def test_2_ipv4_broken (self): # header = ''.join([chr(c) for c in h]) # message = ''.join([chr(c) for c in m]) # message = ''.join([chr(c) for c in [0x0, 0x0, 0x0, 0xf, 0x40, 0x1, 0x1, 0x0, 0x40, 0x2, 0x4, 0x2, 0x1, 0xfd, 0xe8, 0x0, 0x0, 0x0, 0x0, 0x18, 0xa, 0x0, 0x1]]) # update = new_Update(message) if __name__ == '__main__': unittest.main()

38.282353

313

0.667486

54dbf6330b24d0c6aff3e7ee1c31934c49d43385

12,082

py

Python

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

null

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

1

2019-04-24T12:14:59.000Z

nuscenes/eval/detection/evaluate.py

WJ-Lai/NightFusion

1555692eceb6b85127d21cd43e6fc780b7f91ffd

[ "Apache-2.0" ]

null

# nuScenes dev-kit. # Code written by Holger Caesar & Oscar Beijbom, 2018. # Licensed under the Creative Commons [see licence.txt] import argparse import json import os import random import time from typing import Tuple, Dict, Any import numpy as np from nuscenes import NuScenes from nuscenes.eval.detection.algo import accumulate, calc_ap, calc_tp from nuscenes.eval.detection.config import config_factory from nuscenes.eval.detection.constants import TP_METRICS from nuscenes.eval.detection.data_classes import DetectionConfig, MetricDataList, DetectionMetrics, EvalBoxes from nuscenes.eval.detection.loaders import load_prediction, load_gt, add_center_dist, filter_eval_boxes from nuscenes.eval.detection.render import summary_plot, class_pr_curve, class_tp_curve, dist_pr_curve, visualize_sample if __name__ == "__main__": # Settings. parser = argparse.ArgumentParser(description='Evaluate nuScenes result submission.', formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('result_path', type=str, help='The submission as a JSON file.') parser.add_argument('--output_dir', type=str, default='~/nuscenes-metrics', help='Folder to store result metrics, graphs and example visualizations.') parser.add_argument('--eval_set', type=str, default='val', help='Which dataset split to evaluate on, train, val or test.') parser.add_argument('--dataroot', type=str, default='/data/sets/nuscenes', help='Default nuScenes data directory.') parser.add_argument('--version', type=str, default='v1.0-trainval', help='Which version of the nuScenes dataset to evaluate on, e.g. v1.0-trainval.') parser.add_argument('--config_name', type=str, default='cvpr_2019', help='Name of the configuration to use for evaluation, e.g. cvpr_2019.') parser.add_argument('--plot_examples', type=int, default=10, help='How many example visualizations to write to disk.') parser.add_argument('--render_curves', type=int, default=1, help='Whether to render PR and TP curves to disk.') parser.add_argument('--verbose', type=int, default=1, help='Whether to print to stdout.') args = parser.parse_args() result_path_ = os.path.expanduser(args.result_path) output_dir_ = os.path.expanduser(args.output_dir) eval_set_ = args.eval_set dataroot_ = args.dataroot version_ = args.version config_name_ = args.config_name plot_examples_ = args.plot_examples render_curves_ = bool(args.render_curves) verbose_ = bool(args.verbose) cfg_ = config_factory(config_name_) nusc_ = NuScenes(version=version_, verbose=verbose_, dataroot=dataroot_) nusc_eval = NuScenesEval(nusc_, config=cfg_, result_path=result_path_, eval_set=eval_set_, output_dir=output_dir_, verbose=verbose_) nusc_eval.main(plot_examples=plot_examples_, render_curves=render_curves_)

45.421053

120

0.630525

54dcf21edb2556756e4c18e431858f02788f9d3a

9,520

py

Python

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

tests/get_problem_atcoder.py

aberent/api-client

845e5f1daa02cc7fee5a65234a24bb59a7b71083

[ "MIT" ]

null

import unittest from onlinejudge_api.main import main

36.615385

157

0.411029

54dcf64898b0684c67b6786b86aa9adc1e8b99c7

681

py

Python

odm/libexec/odm_tenant.py

UMCollab/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

2

2019-04-26T13:26:02.000Z

2019-10-18T10:36:52.000Z

odm/libexec/odm_tenant.py

flowerysong/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

1

2020-10-28T00:38:07.000Z

odm/libexec/odm_tenant.py

flowerysong/ODM

95da49939dbcd54318a58a132aa76725fd9c0b5f

[ "MIT" ]

1

2019-02-21T16:41:24.000Z

#!/usr/bin/env python3 # This file is part of ODM and distributed under the terms of the # MIT license. See COPYING. import json import sys import odm.cli if __name__ == '__main__': main()

21.28125

79

0.638767

54dde115e15519f27b695b4a4ec6e5589e225fb7

17,182

py

Python

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

74

2015-12-25T09:43:18.000Z

2022-03-30T00:23:30.000Z

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

184

2016-11-23T15:57:16.000Z

2022-03-15T05:25:59.000Z

tests/test_tag_value_parser.py

quaresmajose/tools-python

53c917a1a2491a373efa23e4ef8570b5e863fabc

[ "Apache-2.0" ]

98

2015-12-13T12:20:34.000Z

2022-03-18T15:28:35.000Z

# Copyright (c) 2014 Ahmed H. Ismail # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, 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 sys from unittest import TestCase import spdx from spdx.parsers.tagvalue import Parser from spdx.parsers.lexers.tagvalue import Lexer from spdx.parsers.tagvaluebuilders import Builder from spdx.parsers.loggers import StandardLogger from spdx.version import Version

49.091429

178

0.650506

54df90a5374a87e257978dcb4c0e1caa9abfa7f7

2,024

py

Python

mount_drives.py

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

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

null

mount_drives.py

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

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

null

mount_drives.py

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

dd3e6e29251000946e34d80704c040b5bcad7f8e

[ "MIT" ]

3

2020-02-27T13:45:19.000Z

2020-03-26T13:38:17.000Z

# Standard library imports from subprocess import call as subprocess_call from utility import fileexists from time import sleep as time_sleep from datetime import datetime mount_try = 1 not_yet = True done = False start_time = datetime.now() if fileexists("/home/rpi4-sftp/usb/drive_present.txt"): when_usba = 0 else: when_usba = -1 if fileexists("/home/duck-sftp/usb/drive_present.txt"): when_usbb = 0 else: when_usbb = -1 if fileexists("/home/pi/mycloud/drive_present.txt"): when_mycloud = 0 else: when_mycloud = -1 while (mount_try < 30) and not_yet: try: usba_mounted = fileexists("/home/rpi4-sftp/usb/drive_present.txt") usbb_mounted = fileexists("/home/duck-sftp/usb/drive_present.txt") mycloud_mounted = fileexists("/home/pi/mycloud/drive_present.txt") if not(usba_mounted and usbb_mounted and mycloud_mounted): print("Something Needs mounting this is try number: ", mount_try) subprocess_call(["sudo", "mount", "-a"]) mount_try += 1 usba_mounted_after = fileexists("/home/rpi4-sftp/usb/drive_present.txt") usbb_mounted_after = fileexists("/home/duck-sftp/usb/drive_present.txt") mycloud_mounted_after = fileexists("/home/pi/mycloud/drive_present.txt") if not(usba_mounted) and usba_mounted_after: when_usba = round((datetime.now() - start_time).total_seconds(),2) if not(usbb_mounted) and usbb_mounted_after: when_usbb = round((datetime.now() - start_time).total_seconds(),2) if not(mycloud_mounted) and mycloud_mounted_after: when_mycloud = round((datetime.now() - start_time).total_seconds(),2) if usba_mounted_after and usbb_mounted_after and mycloud_mounted_after: print("Success at :",when_usba,when_usbb,when_mycloud, " secs from start") not_yet = False done = True except: print("Count: ", count," error") time_sleep(1) if done: print("Great!") else: print("Failed to do all or drive_present.txt file not present; Times :",when_usba,when_usbb,when_mycloud) while True: time_sleep(20000)

36.142857

107

0.733202

54e0817402b9c2ce35c6af23684ce91b4042e10a

5,639

py

Python

home/views.py

Kshitij-Kumar-Singh-Chauhan/docon

bff0547e7bbd030e027217a2ca7800a8da529b56

[ "MIT" ]

null

home/views.py

Kshitij-Kumar-Singh-Chauhan/docon

bff0547e7bbd030e027217a2ca7800a8da529b56

[ "MIT" ]

null

home/views.py

Kshitij-Kumar-Singh-Chauhan/docon

bff0547e7bbd030e027217a2ca7800a8da529b56

[ "MIT" ]

2

2021-06-17T05:35:07.000Z

2021-06-17T06:01:23.000Z

from django.http.response import HttpResponse from django.shortcuts import render from django.shortcuts import redirect, render from cryptography.fernet import Fernet from .models import Book, UserDetails from .models import Contact from .models import Book from .models import Report from .models import Diagnostic from datetime import datetime # Create your views here. # def index(request): # context={ 'alpha': 'This is sent'} # if request.method=='POST': # pass # else: return render(request, 'index.html',context) #HttpResponse('This is homepage') # def appointment(request,email,name): # if request.method == "POST": # problem = request.POST.get('problem') # book = Appoint(problem=problem, email=email, name=name) # book.save() # return render(request,"index.html")

33.565476

124

0.567477

54e0ed7eefaaeac2cfcbec8d464ffc806c518afa

9,892

py

Python

compressor/tests/templatetags.py

bigmlcom/django_compressor

66dfda503633018275fdb64ad46ef80dc9a3901d

[ "Apache-2.0" ]

null

compressor/tests/templatetags.py

bigmlcom/django_compressor

66dfda503633018275fdb64ad46ef80dc9a3901d

[ "Apache-2.0" ]

null

compressor/tests/templatetags.py

bigmlcom/django_compressor

66dfda503633018275fdb64ad46ef80dc9a3901d

[ "Apache-2.0" ]

null

from __future__ import with_statement import os import sys from mock import Mock from django.template import Template, Context, TemplateSyntaxError from django.test import TestCase from compressor.conf import settings from compressor.signals import post_compress from compressor.tests.base import css_tag, test_dir def render(template_string, context_dict=None): """ A shortcut for testing template output. """ if context_dict is None: context_dict = {} c = Context(context_dict) t = Template(template_string) return t.render(c).strip() def script(content="", src="", scripttype="text/javascript"): """ returns a unicode text html script element. >>> script('#this is a comment', scripttype="text/applescript") '<script type="text/applescript">#this is a comment</script>' """ out_script = u'<script ' if scripttype: out_script += u'type="%s" ' % scripttype if src: out_script += u'src="%s" ' % src return out_script[:-1] + u'>%s</script>' % content

41.563025

107

0.616761

54e0f7ad3e850fa6d21aab5200a2493a26332352

3,324

py

Python

cle/cle/backends/relocations/generic.py

Ruide/angr-dev

964dc80c758e25c698c2cbcc454ef5954c5fa0a0

[ "BSD-2-Clause" ]

null

cle/cle/backends/relocations/generic.py

Ruide/angr-dev

964dc80c758e25c698c2cbcc454ef5954c5fa0a0

[ "BSD-2-Clause" ]

null

cle/cle/backends/relocations/generic.py

Ruide/angr-dev

964dc80c758e25c698c2cbcc454ef5954c5fa0a0

[ "BSD-2-Clause" ]

null

from ...address_translator import AT from ...errors import CLEOperationError from . import Relocation import struct import logging l = logging.getLogger('cle.relocations.generic')

36.130435

117

0.666968

54e179a25d793c478f7e42c99a00025d13aed6d0

1,438

py

Python

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

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

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

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

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

charlescayno/automation

a4a34d87f372d49fd69740ad3ca46ae19bf2612d

[ "MIT" ]

null

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

25.678571

78

0.684284

54e1fce9e0db363710daf71e66104aba025bc831

477

py

Python

ringapp/migrations/0009_auto_20150116_1759.py

rschwiebert/RingApp

35675b3dd81728d71b7dc70071be3185d7f99bf4

[ "MIT" ]

10

2015-02-02T12:40:05.000Z

2022-01-29T14:11:03.000Z

ringapp/migrations/0009_auto_20150116_1759.py

rschwiebert/RingApp

35675b3dd81728d71b7dc70071be3185d7f99bf4

[ "MIT" ]

22

2015-01-07T21:29:24.000Z

2022-03-19T01:15:13.000Z

ringapp/migrations/0009_auto_20150116_1759.py

rschwiebert/RingApp

35675b3dd81728d71b7dc70071be3185d7f99bf4

[ "MIT" ]

1

2016-08-07T15:41:51.000Z

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

20.73913

47

0.589099

54e218f734c2d85cbff6df8c45d35331a499ae96

654

py

Python

front-end/testsuite-python-lib/Python-3.1/Lib/json/tests/test_dump.py

MalloyPower/parsing-python

b2bca5eed07ea2af7a2001cd4f63becdfb0570be

[ "MIT" ]

1

2020-11-26T18:53:46.000Z

Lib/json/tests/test_dump.py

orestis/python

870a82aac7788ffa105e2a3e4480b3715c93bff6

[ "PSF-2.0" ]

null

Lib/json/tests/test_dump.py

orestis/python

870a82aac7788ffa105e2a3e4480b3715c93bff6

[ "PSF-2.0" ]

2

2018-08-06T04:37:38.000Z

2022-02-27T18:07:12.000Z

from unittest import TestCase from io import StringIO import json

29.727273

69

0.547401

54e3b8446107d9bccd2d0bc314395d7a3117387b

7,069

py

Python

src/resources/clients/python_client/visitstate.py

visit-dav/vis

c08bc6e538ecd7d30ddc6399ec3022b9e062127e

[ "BSD-3-Clause" ]

226

2018-12-29T01:13:49.000Z

2022-03-30T19:16:31.000Z

src/resources/clients/python_client/visitstate.py

visit-dav/vis

c08bc6e538ecd7d30ddc6399ec3022b9e062127e

[ "BSD-3-Clause" ]

5,100

2019-01-14T18:19:25.000Z

2022-03-31T23:08:36.000Z

src/resources/clients/python_client/visitstate.py

visit-dav/vis

c08bc6e538ecd7d30ddc6399ec3022b9e062127e

[ "BSD-3-Clause" ]

84

2019-01-24T17:41:50.000Z

2022-03-10T10:01:46.000Z

import sys

34.651961

54

0.660914

54e459da47af69f9dc842497504519a50554986e

774

py

Python

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

53

2020-02-20T06:56:03.000Z

2022-03-03T03:09:25.000Z

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

6

2020-03-03T03:15:53.000Z

2021-01-29T02:24:06.000Z

tests/__init__.py

zhangyiming07/QT4C

2d8d60efe0a4ad78a2618c5beeb0c456a63da067

[ "BSD-3-Clause" ]

17

2020-02-26T03:51:41.000Z

2022-03-24T02:23:51.000Z

# -*- coding: utf-8 -*- # # Tencent is pleased to support the open source community by making QT4C available. # Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved. # QT4C is licensed under the BSD 3-Clause License, except for the third-party components listed below. # A copy of the BSD 3-Clause License is included in this file. # ''' ''' import unittest import os import sys test_dir = os.path.dirname(os.path.abspath(__file__)) sys.path.insert(0, os.path.dirname(test_dir)) if __name__ == '__main__': main()

28.666667

103

0.719638

54e639174a97601933059aabae1c3acdb2b90d00

323

py

Python

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

null

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

null

brute/brute_build.py

sweetsbeats/starter-snake-python

e7cb56a3a623a324f4b5ef956020990e8c61f871

[ "MIT" ]

2

2019-05-05T00:41:26.000Z

2019-05-05T00:46:45.000Z

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

19

42

0.479876

54e64db782245fc204cf4d668f6d515f9131a03b

2,392

py

Python

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

src/board.py

JNotelddim/python-snake

da95339d3a982040a84422e5f7b95453095a4450

[ "MIT" ]

null

"""Board Module""" import copy from typing import Tuple, List from src.coordinate import Coordinate from src.snake import Snake def get_other_snakes(self, exclude_id) -> List[Snake]: """Get the List of Snakes whose IDs don't match the given ID.""" return [snake for snake in self.snakes if snake.id != exclude_id] def advance_snake_along_path(self, snake_id: str, path: List[Coordinate]): """Return a new board with our snake advanced along given path.""" new_board = copy.deepcopy(self) return new_board.__help_advance_snake_along_path(snake_id, path) def __help_advance_snake_along_path(self, snake_id: str, path: List[Coordinate]): """Do the actual advancement of the snake along the path.""" me = next((snake for snake in self.snakes if snake.id == snake_id), None) if not me: raise ValueError("No snake for given id!") me.coordinates += path me.coordinates = me.coordinates[len(path):] me.coordinates.reverse() me.coordinates.append(me.coordinates[-1]) print("new coords:") for coord in me.coordinates: print(coord) return self

37.375

85

0.633361

54e781207e20bd9e8679af88a83847cfe7947287

2,349

py

Python

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

null

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

1

2022-03-15T23:48:51.000Z

personalized_nlp/datasets/wiki/base.py

CLARIN-PL/personalized-nlp

340294300f93d12cabc59b055ff2548df8f4081a

[ "MIT" ]

null

import os import zipfile from typing import List import pandas as pd import urllib from personalized_nlp.settings import STORAGE_DIR from personalized_nlp.utils.data_splitting import split_texts from personalized_nlp.datasets.datamodule_base import BaseDataModule

32.178082

96

0.638995

54e789caffaeff5bc10488464b0b5f0c11ea3f0e

522

py

Python

App/migrations/0010_remove_user_percentage_preferences_user_preferences.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

null

App/migrations/0010_remove_user_percentage_preferences_user_preferences.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

44

2022-01-21T01:33:59.000Z

2022-03-26T23:35:25.000Z

App/migrations/0010_remove_user_percentage_preferences_user_preferences.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

null

# Generated by Django 4.0 on 2022-03-03 02:15 from django.db import migrations, models

22.695652

71

0.597701

54e901540b5f6fa6fc62f5e51511aa0c656882ca

3,653

py

Python

venv/Lib/site-packages/captcha/conf/settings.py

Rudeus3Greyrat/admin-management

7e81d2b1908afa3ea57a82c542c9aebb1d0ffd23

[ "MIT" ]

1

2020-05-21T06:48:34.000Z

venv/Lib/site-packages/captcha/conf/settings.py

Rudeus3Greyrat/admin-management

7e81d2b1908afa3ea57a82c542c9aebb1d0ffd23

[ "MIT" ]

3

2021-03-19T03:07:36.000Z

2021-04-08T20:33:38.000Z

venv/Lib/site-packages/captcha/conf/settings.py

Rudeus3Greyrat/admin-management

7e81d2b1908afa3ea57a82c542c9aebb1d0ffd23

[ "MIT" ]

1

2020-05-21T06:48:36.000Z

import os import warnings from django.conf import settings CAPTCHA_FONT_PATH = getattr(settings, 'CAPTCHA_FONT_PATH', os.path.normpath(os.path.join(os.path.dirname(__file__), '..', 'fonts/Vera.ttf'))) CAPTCHA_FONT_SIZE = getattr(settings, 'CAPTCHA_FONT_SIZE', 22) CAPTCHA_LETTER_ROTATION = getattr(settings, 'CAPTCHA_LETTER_ROTATION', (-35, 35)) CAPTCHA_BACKGROUND_COLOR = getattr(settings, 'CAPTCHA_BACKGROUND_COLOR', '#ffffff') CAPTCHA_FOREGROUND_COLOR = getattr(settings, 'CAPTCHA_FOREGROUND_COLOR', '#001100') CAPTCHA_CHALLENGE_FUNCT = getattr(settings, 'CAPTCHA_CHALLENGE_FUNCT', 'captcha.helpers.random_char_challenge') CAPTCHA_NOISE_FUNCTIONS = getattr(settings, 'CAPTCHA_NOISE_FUNCTIONS', ('captcha.helpers.noise_arcs', 'captcha.helpers.noise_dots',)) CAPTCHA_FILTER_FUNCTIONS = getattr(settings, 'CAPTCHA_FILTER_FUNCTIONS', ('captcha.helpers.post_smooth',)) CAPTCHA_WORDS_DICTIONARY = getattr(settings, 'CAPTCHA_WORDS_DICTIONARY', '/usr/share/dict/words') CAPTCHA_PUNCTUATION = getattr(settings, 'CAPTCHA_PUNCTUATION', '''_"',.;:-''') CAPTCHA_FLITE_PATH = getattr(settings, 'CAPTCHA_FLITE_PATH', None) CAPTCHA_SOX_PATH = getattr(settings, 'CAPTCHA_SOX_PATH', None) CAPTCHA_TIMEOUT = getattr(settings, 'CAPTCHA_TIMEOUT', 5) # Minutes CAPTCHA_LENGTH = int(getattr(settings, 'CAPTCHA_LENGTH', 4)) # Chars # CAPTCHA_IMAGE_BEFORE_FIELD = getattr(settings, 'CAPTCHA_IMAGE_BEFORE_FIELD', True) CAPTCHA_DICTIONARY_MIN_LENGTH = getattr(settings, 'CAPTCHA_DICTIONARY_MIN_LENGTH', 0) CAPTCHA_DICTIONARY_MAX_LENGTH = getattr(settings, 'CAPTCHA_DICTIONARY_MAX_LENGTH', 99) CAPTCHA_IMAGE_SIZE = getattr(settings, 'CAPTCHA_IMAGE_SIZE', None) CAPTCHA_IMAGE_TEMPLATE = getattr(settings, 'CAPTCHA_IMAGE_TEMPLATE', 'captcha/image.html') CAPTCHA_HIDDEN_FIELD_TEMPLATE = getattr(settings, 'CAPTCHA_HIDDEN_FIELD_TEMPLATE', 'captcha/hidden_field.html') CAPTCHA_TEXT_FIELD_TEMPLATE = getattr(settings, 'CAPTCHA_TEXT_FIELD_TEMPLATE', 'captcha/text_field.html') if getattr(settings, 'CAPTCHA_FIELD_TEMPLATE', None): msg = ("CAPTCHA_FIELD_TEMPLATE setting is deprecated in favor of widget's template_name.") warnings.warn(msg, DeprecationWarning) CAPTCHA_FIELD_TEMPLATE = getattr(settings, 'CAPTCHA_FIELD_TEMPLATE', None) if getattr(settings, 'CAPTCHA_OUTPUT_FORMAT', None): msg = ("CAPTCHA_OUTPUT_FORMAT setting is deprecated in favor of widget's template_name.") warnings.warn(msg, DeprecationWarning) CAPTCHA_OUTPUT_FORMAT = getattr(settings, 'CAPTCHA_OUTPUT_FORMAT', None) CAPTCHA_MATH_CHALLENGE_OPERATOR = getattr(settings, 'CAPTCHA_MATH_CHALLENGE_OPERATOR', '*') CAPTCHA_GET_FROM_POOL = getattr(settings, 'CAPTCHA_GET_FROM_POOL', False) CAPTCHA_GET_FROM_POOL_TIMEOUT = getattr(settings, 'CAPTCHA_GET_FROM_POOL_TIMEOUT', 5) CAPTCHA_TEST_MODE = getattr(settings, 'CAPTCHA_TEST_MODE', False) # Failsafe if CAPTCHA_DICTIONARY_MIN_LENGTH > CAPTCHA_DICTIONARY_MAX_LENGTH: CAPTCHA_DICTIONARY_MIN_LENGTH, CAPTCHA_DICTIONARY_MAX_LENGTH = CAPTCHA_DICTIONARY_MAX_LENGTH, CAPTCHA_DICTIONARY_MIN_LENGTH

52.942029

141

0.800712

54ea3d9d70532f8dc30f4d5946975cecc10f6326

11,009

py

Python

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

pilbox/test/app_test.py

joevandyk/pilbox

b84732a78e5bdb2d24bf7ef4177d45806ac03ea6

[ "Apache-2.0" ]

null

from __future__ import absolute_import, division, print_function, \ with_statement import logging import os.path import time import tornado.escape import tornado.gen import tornado.ioloop from tornado.test.util import unittest from tornado.testing import AsyncHTTPTestCase, gen_test import tornado.web from pilbox.app import PilboxApplication from pilbox.errors import SignatureError, ClientError, HostError, \ BackgroundError, DimensionsError, FilterError, FormatError, ModeError, \ PositionError, QualityError, UrlError, ImageFormatError, FetchError from pilbox.signature import sign from pilbox.test import image_test try: from urllib import urlencode except ImportError: from urllib.parse import urlencode try: import cv except ImportError: cv = None logger = logging.getLogger("tornado.application")

39.887681

79

0.606504

54eaca929e4c45b157fe05142cabf897db4cf571

1,202

py

Python

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

6

2017-08-09T09:41:42.000Z

2021-04-22T05:10:17.000Z

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

null

hackathon/darkmattertemperaturedistribution/example.py

Neelraj21/phython

68a2cedccae694eb84880f3aa55cc01d458e055e

[ "WTFPL" ]

5

2015-11-04T12:57:10.000Z

2020-10-18T17:32:25.000Z

#!/usr/bin/env python from scipy import * from pylab import * #from pylab import imshow #! #! Some graphical explorations of the Julia sets with python and pyreport #!######################################################################### #$ #$ We start by defining a function J: #$ \[ J_c : z \rightarrow z^2 + c \] #$ [x,y] = ogrid[ -1:1:0.002, -1:1:0.002 ] z = x + y *1j #! If we study the divergence of function J under repeated iteration #! depending on its inital conditions we get a very pretty graph threshTime = zeros_like(z) for i in range(40): z = J(0.285)(z) threshTime += z*conj(z) > 4 figure(0) axes([0,0,1,1]) axis('off') imshow(threshTime) bone() show() #! We can also do that systematicaly for other values of c: axes([0,0,1,1]) axis('off') rcParams.update({'figure.figsize': [10.5,5]}) c_values = (0.285 + 0.013j, 0.45 - 0.1428j, -0.70176 -0.3842j, -0.835-0.2321j, -0.939 +0.167j, -0.986+0.87j) for i,c in enumerate(c_values): threshTime = zeros_like(z) z = x + y *1j for n in range(40): z = J(c)(z) threshTime += z*conj(z) > 4 subplot(2,3,i+1) imshow(threshTime) axis('off') show()

26.130435

75

0.584859

54ec18e7d2fb320aa765697469037a76c03cbf50

535

py

Python

resources/migrations/0126_add_field_disallow_overlapping_reservations_per_user.py

codepointtku/respa

bb9cd8459d5562569f976dbc609ec41ceecc8023

[ "MIT" ]

1

2019-12-17T10:02:17.000Z

resources/migrations/0126_add_field_disallow_overlapping_reservations_per_user.py

codepointtku/respa

bb9cd8459d5562569f976dbc609ec41ceecc8023

[ "MIT" ]

38

2020-01-24T11:30:53.000Z

2022-01-28T12:42:47.000Z

resources/migrations/0126_add_field_disallow_overlapping_reservations_per_user.py

digipointtku/respa

a529e0df4d3f072df7801adb5bf97a5f4abd1243

[ "MIT" ]

14

2020-02-26T08:17:34.000Z

2021-09-14T07:57:21.000Z

# Generated by Django 2.2.21 on 2021-06-23 12:43 from django.db import migrations, models import django.db.models.deletion

26.75

126

0.676636

54eceeb38625ac7f7302479b3298ad5a3adabd40

1,307

py

Python

src/lora_multihop/module_config.py

marv1913/lora_multihop

ef07493c2f763d07161fa25d4b884ef79b94afa4

[ "MIT" ]

null

src/lora_multihop/module_config.py

marv1913/lora_multihop

ef07493c2f763d07161fa25d4b884ef79b94afa4

[ "MIT" ]

1

2022-02-20T13:18:13.000Z

2022-02-24T18:32:23.000Z

src/lora_multihop/module_config.py

marv1913/lora_multihop

ef07493c2f763d07161fa25d4b884ef79b94afa4

[ "MIT" ]

null

import logging from lora_multihop import serial_connection, variables

39.606061

101

0.746748

54ed860d4a6171f4dc1581a63c75ee95835b9b75

6,287

py

Python

eris/script/ferdian.py

ferdianap/Eris_test

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

1

2015-06-12T04:38:09.000Z

eris/script/ferdian.py

ferdianap/eris

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

null

eris/script/ferdian.py

ferdianap/eris

c2a00d65f816ad6d48a65c14b4bea4f3d081b86b

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # Copyright (c) 2013-2014, Rethink Robotics # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # 3. Neither the name of the Rethink Robotics nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. """ copied from Baxter RSDK Joint Position Example: file playback """ from __future__ import print_function import sys import rospy import baxter_interface from baxter_interface import CHECK_VERSION import glob from std_srvs.srv import Empty def clean_line(line, names): """ Cleans a single line of recorded joint positions @param line: the line described in a list to process @param names: joint name keys """ #convert the line of strings to a float or None line = [try_float(x) for x in line.rstrip().split(',')] #zip the values with the joint names combined = zip(names[1:], line[1:]) #take out any tuples that have a none value cleaned = [x for x in combined if x[1] is not None] #convert it to a dictionary with only valid commands command = dict(cleaned) left_command = dict((key, command[key]) for key in command.keys() if key[:-2] == 'left_') right_command = dict((key, command[key]) for key in command.keys() if key[:-2] == 'right_') return (command, left_command, right_command, line) def map_file(filename, loops=1): """ Loops through csv file @param filename: the file to play @param loops: number of times to loop values < 0 mean 'infinite' Does not loop indefinitely, but only until the file is read and processed. Reads each line, split up in columns and formats each line into a controller command in the form of name/value pairs. Names come from the column headers first column is the time stamp """ left = baxter_interface.Limb('left') right = baxter_interface.Limb('right') grip_left = baxter_interface.Gripper('left', CHECK_VERSION) grip_right = baxter_interface.Gripper('right', CHECK_VERSION) rate = rospy.Rate(1000) if grip_left.error(): grip_left.reset() if grip_right.error(): grip_right.reset() if (not grip_left.calibrated() and grip_left.type() != 'custom'): grip_left.calibrate() if (not grip_right.calibrated() and grip_right.type() != 'custom'): grip_right.calibrate() print("Playing back: %s" % (filename,)) with open(filename, 'r') as f: lines = f.readlines() keys = lines[0].rstrip().split(',') l = 0 # If specified, repeat the file playback 'loops' number of times while loops < 1 or l < loops: i = 0 l += 1 print("Moving to start position...") _cmd, lcmd_start, rcmd_start, _raw = clean_line(lines[1], keys) left.move_to_joint_positions(lcmd_start) right.move_to_joint_positions(rcmd_start) start_time = rospy.get_time() for values in lines[1:]: i += 1 loopstr = str(loops) if loops > 0 else "forever" sys.stdout.write("\r Record %d of %d, loop %d of %s" % (i, len(lines) - 1, l, loopstr)) sys.stdout.flush() cmd, lcmd, rcmd, values = clean_line(values, keys) #command this set of commands until the next frame while (rospy.get_time() - start_time) < values[0]: if rospy.is_shutdown(): print("\n Aborting - ROS shutdown") return False if len(lcmd): left.set_joint_positions(lcmd) if len(rcmd): right.set_joint_positions(rcmd) if ('left_gripper' in cmd and grip_left.type() != 'custom'): grip_left.command_position(cmd['left_gripper']) if ('right_gripper' in cmd and grip_right.type() != 'custom'): grip_right.command_position(cmd['right_gripper']) rate.sleep() print return True ### if __name__ == '__main__': main()

34.543956

77

0.655798

54f048a7a0b7d058cdc56c1d7f2c7462bde0f3d6

4,461

py

Python

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

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

3,301

2018-10-01T16:30:44.000Z

2022-03-30T08:07:16.000Z

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

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

206

2019-11-27T14:04:42.000Z

2022-03-28T08:02:05.000Z

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

zhangjun0x01/Alink

c1cd3380bed29a4be4eb058a7462213869c02387

[ "Apache-2.0" ]

765

2018-10-09T02:02:19.000Z

2022-03-31T12:06:21.000Z

import abc from typing import Dict, Callable import tensorflow as tf from flink_ml_framework.context import Context from flink_ml_framework.java_file import * from ..runner import tf_helper, io_helper from ..runner.output_writer import DirectOutputWriter try: from flink_ml_tensorflow.tensorflow_context import TFContext except: from flink_ml_tensorflow2.tensorflow_context import TFContext # noinspection PyUnresolvedReferences from tensorflow_io.core.python.ops import core_ops __all__ = ['TF1_TYPE', 'TF2_TYPE'] TF1_TYPE = 'tf1' TF2_TYPE = 'tf2'

36.867769

110

0.647837

54f164400ecea40c3dfdfcd5317d3f9f381a79ff

12,450

py

Python

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

1

2021-03-25T01:21:19.000Z

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

null

corm-tests/test_corm_api.py

jbcurtin/cassandra-orm

2c5540de36166c81832c1ccd0ee40c52e598e05c

[ "MIT" ]

null

import pytest ENCODING = 'utf-8'

29.294118

110

0.67245

54f3bbb19576152c565203e49a32298c3f423ec9

6,337

py

Python

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

2

2017-12-15T23:10:11.000Z

2018-05-07T04:18:03.000Z

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

1

2018-02-26T06:23:32.000Z

2018-02-27T03:34:01.000Z

src/utilities/getInfo.py

UCSB-dataScience-ProjectGroup/movie_rating_prediction

c0c29c0463dccc6ad286bd59e77993fdf0d05fb2

[ "RSA-MD" ]

2

2017-10-19T21:50:24.000Z

2018-01-01T03:40:35.000Z

import json import os from utilities.SaveLoadJson import SaveLoadJson as SLJ from utilities.LineCount import LineCount as LC import subprocess from geolite2 import geolite2

37.276471

97

0.447373

54f4e0fec59282b2d1c7f1cba1c1b99fa606ce17

70

py

Python

nemo/collections/nlp/losses/__init__.py

KalifiaBillal/NeMo

4fc670ad0c886be2623247921d4311ba30f486f8

[ "Apache-2.0" ]

1

2021-01-26T21:54:36.000Z

nemo/collections/nlp/losses/__init__.py

aiskumo/NeMo

b51a39f9834ad50db77c4246aeb6e2349695add5

[ "Apache-2.0" ]

null

nemo/collections/nlp/losses/__init__.py

aiskumo/NeMo

b51a39f9834ad50db77c4246aeb6e2349695add5

[ "Apache-2.0" ]

2

2021-02-04T14:45:50.000Z

2021-02-04T14:56:05.000Z

from nemo.collections.nlp.losses.sgd_loss import SGDDialogueStateLoss

35

69

0.885714

54f75a0784cdbed72bcde377b44202a6cfd58c51

382

py

Python

netrunner/test_settings.py

MrAGi/netrunner-cambridge

bae0603486c2aa5a980e8e19207452fb01ec2193

[ "MIT" ]

null

netrunner/test_settings.py

MrAGi/netrunner-cambridge

bae0603486c2aa5a980e8e19207452fb01ec2193

[ "MIT" ]

null

netrunner/test_settings.py

MrAGi/netrunner-cambridge

bae0603486c2aa5a980e8e19207452fb01ec2193

[ "MIT" ]

null

# -*- coding: utf-8 -*- from .settings import * DEBUG = True TEMPLATE_DEBUG = DEBUG DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql_psycopg2', 'NAME': os.environ['LOCAL_DB_NAME'], 'USER': os.environ['LOCAL_DB_USER'], 'PASSWORD': os.environ['LOCAL_DB_PASSWORD'], 'HOST': '127.0.0.1', 'PORT': '5432', } }

21.222222

59

0.568063

54f79d31af30b3622247fe2c6abad64bc05814e8

231

py

Python

Python_Exercicios/calcula_terreno.py

thalles-dreissig20/Quebra_Cabeca

eeb9458dbabac72d9867e5ec5d7f1aa9b5993d79

[ "MIT" ]

null

Python_Exercicios/calcula_terreno.py

thalles-dreissig20/Quebra_Cabeca

eeb9458dbabac72d9867e5ec5d7f1aa9b5993d79

[ "MIT" ]

1

2021-11-29T18:37:14.000Z

Python_Exercicios/calcula_terreno.py

thalles-dreissig20/Quebra_Cabeca

eeb9458dbabac72d9867e5ec5d7f1aa9b5993d79

[ "MIT" ]

null

print('Controle de terrenos') print('-' * 20) l = float(input('qual a largura do terreno: ')) c = float(input('qual o comprimento do terreno: ')) area(l , c)

25.666667

51

0.627706

54f7f3b4bb05515aa800aef3ce44e23eb1933bf4

443

py

Python

Desafios/desafio_041.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

Desafios/desafio_041.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

Desafios/desafio_041.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

import datetime ano = (datetime.datetime.now()).year nasc = int(input("Digite o seu ano de nascimento: ")) categoria = 0 if (ano - nasc) <= 9: categoria = str("MIRIM") elif 9 < (ano - nasc) <= 14: categoria = str("INFANTIL") elif 14 < (ano - nasc) <= 19 : categoria = str("JUNIOR") elif 19 < (ano - nasc) <= 25: categoria = str("SNIOR") else: categoria = str("MASTER") print(f"A categoria do atleta {str(categoria)}.")

26.058824

53

0.616253

54f89b5cd05a9ee6ba8e82764ddc7f2a5b7aea7d

1,689

py

Python

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

37

2020-06-15T02:04:37.000Z

2022-02-09T06:26:42.000Z

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

5

2020-08-06T13:16:34.000Z

2022-02-04T07:29:29.000Z

eval/metrics.py

RecoHut-Stanzas/S168471

7e0ac621c36f839e1df6876ec517d0ad00672790

[ "BSD-3-Clause" ]

11

2020-09-01T23:08:51.000Z

2022-02-09T06:26:44.000Z

import torch def ndcg_binary_at_k_batch_torch(X_pred, heldout_batch, k=100, device='cpu'): """ Normalized Discounted Cumulative Gain@k for for predictions [B, I] and ground-truth [B, I], with binary relevance. ASSUMPTIONS: all the 0's in heldout_batch indicate 0 relevance. """ batch_users = X_pred.shape[0] # batch_size _, idx_topk = torch.topk(X_pred, k, dim=1, sorted=True) tp = 1. / torch.log2(torch.arange(2, k + 2, device=device).float()) heldout_batch_nonzero = (heldout_batch > 0).float() DCG = (heldout_batch_nonzero[torch.arange(batch_users, device=device).unsqueeze(1), idx_topk] * tp).sum(dim=1) heldout_nonzero = (heldout_batch > 0).sum(dim=1) # num. of non-zero items per batch. [B] IDCG = torch.tensor([(tp[:min(n, k)]).sum() for n in heldout_nonzero]).to(device) return DCG / IDCG def recall_at_k_batch_torch(X_pred, heldout_batch, k=100): """ Recall@k for predictions [B, I] and ground-truth [B, I]. """ batch_users = X_pred.shape[0] _, topk_indices = torch.topk(X_pred, k, dim=1, sorted=False) # [B, K] X_pred_binary = torch.zeros_like(X_pred) if torch.cuda.is_available(): X_pred_binary = X_pred_binary.cuda() X_pred_binary[torch.arange(batch_users).unsqueeze(1), topk_indices] = 1 X_true_binary = (heldout_batch > 0).float() # .toarray() # [B, I] k_tensor = torch.tensor([k], dtype=torch.float32) if torch.cuda.is_available(): X_true_binary = X_true_binary.cuda() k_tensor = k_tensor.cuda() tmp = (X_true_binary * X_pred_binary).sum(dim=1).float() recall = tmp / torch.min(k_tensor, X_true_binary.sum(dim=1).float()) return recall

44.447368

118

0.674956

54f8ec657caa5b90b66baca8ce435c82f8e1413e

5,029

py

Python

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

172

2019-12-18T22:19:42.000Z

2022-03-29T01:58:25.000Z

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

165

2020-01-10T19:05:16.000Z

2022-03-31T16:08:36.000Z

simba/run_dash_tkinter.py

justinshenk/simba

a58ccd0ceeda201c1452d186033ce6b25fbab564

[ "MIT" ]

80

2019-12-20T00:01:43.000Z

2022-03-29T16:20:10.000Z

# All credit to https://stackoverflow.com/questions/46571448/tkinter-and-a-html-file - thanks DELICA - https://stackoverflow.com/users/7027346/delica from cefpython3 import cefpython as cef import ctypes try: import tkinter as tk from tkinter import messagebox except ImportError: import Tkinter as tk import sys import platform import logging as _logging # Fix for PyCharm hints warnings WindowUtils = cef.WindowUtils() # Platforms WINDOWS = (platform.system() == "Windows") LINUX = (platform.system() == "Linux") MAC = (platform.system() == "Darwin") # Globals logger = _logging.getLogger("tkinter_.py") url = "localhost:8050/" # if __name__ == '__main__': logger.setLevel(_logging.INFO) stream_handler = _logging.StreamHandler() formatter = _logging.Formatter("[%(filename)s] %(message)s") stream_handler.setFormatter(formatter) logger.addHandler(stream_handler) logger.info("CEF Python {ver}".format(ver=cef.__version__)) logger.info("Python {ver} {arch}".format( ver=platform.python_version(), arch=platform.architecture()[0])) logger.info("Tk {ver}".format(ver=tk.Tcl().eval('info patchlevel'))) assert cef.__version__ >= "55.3", "CEF Python v55.3+ required to run this" sys.excepthook = cef.ExceptHook # To shutdown all CEF processes on error root = tk.Tk() app = MainFrame(root) root.protocol("WM_DELETE_WINDOW", on_closing) # Tk must be initialized before CEF otherwise fatal error (Issue #306) cef.Initialize() root.mainloop() # app.mainloop() cef.Shutdown()

30.478788

149

0.644064

54fb3d7c53a19a5375f0b43976b42347774b6cca

1,010

py

Python

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

domain_data/mujoco_worlds/make_xml.py

sfpd/rlreloaded

650c64ec22ad45996c8c577d85b1a4f20aa1c692

[ "MIT" ]

null

import re from glob import glob import os.path as osp infiles = glob(osp.join(osp.dirname(__file__),"*.xml.in")) for fname in infiles: with open(fname,"r") as fh: in_lines = fh.readlines() out_lines = do_substitution(in_lines) outfname = fname[:-3] with open(outfname,"w") as fh: fh.writelines(out_lines)

25.897436

68

0.581188

54fbc8636ea0532bcc0fa404a8de1597f6db3f5f

354

py

Python

myproject/apps/events/migrations/0002_alter_eventhero_options.py

cahyareza/django_admin_cookbook

6c82dbd3aebe455b68feb020d5cad7978b8191b7

[ "MIT" ]

null

myproject/apps/events/migrations/0002_alter_eventhero_options.py

cahyareza/django_admin_cookbook

6c82dbd3aebe455b68feb020d5cad7978b8191b7

[ "MIT" ]

null

myproject/apps/events/migrations/0002_alter_eventhero_options.py

cahyareza/django_admin_cookbook

6c82dbd3aebe455b68feb020d5cad7978b8191b7

[ "MIT" ]

null

# Generated by Django 3.2.12 on 2022-03-28 11:57 from django.db import migrations

19.666667

60

0.601695

54fcf0226ece66aeec4bb6bba4646c87e745e2e5

799

py

Python

hilton_sign_in.py

bmintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-12T10:33:13.000Z

2019-02-24T05:01:40.000Z

hilton_sign_in.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

null

hilton_sign_in.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-24T08:16:59.000Z

2019-02-24T04:41:30.000Z

#!/usr/bin/env python3 # encoding: utf-8 import sys import urllib.parse import selenium.webdriver driver = selenium.webdriver.Firefox() # for some reason, detectportal.firefox.com and connectivitycheck.gstatic.com are not blocked # therefore, they cannot be used to detect connectivity # we instead visit another site that is known not to ever have TLS driver.get('http://neverssl.com') if 'neverssl.com' in urllib.parse.urlparse(driver.current_url).netloc: exit() driver.find_element_by_css_selector('label[for="promo_button"]').click() driver.find_element_by_css_selector('input[alt="Next"]').click() driver.find_element_by_css_selector('#PromotionCode').send_keys('lobby18') driver.find_element_by_css_selector('input[alt="Connect"]').click() exit()

30.730769

93

0.779725

54fd38f1410793bf1398c7ca975380689133f595

1,539

py

Python

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

null

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

null

src/figures/trends/leaf_response.py

rhyswhitley/savanna_iav

4eadf29a4e9c05d0b14d3b9c973eb8db3ea7edba

[ "CC0-1.0" ]

1

2019-09-01T04:15:21.000Z

#!/usr/bin/env python import os from collections import OrderedDict import cPickle as pickle import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec from matplotlib.cm import get_cmap from matplotlib import style from scipy import stats from scipy import integrate if __name__ == "__main__": FILEPATH = "~/Savanna/Data/HowardSprings_IAV/pickled/agg/mean_monthly_leaf.pkl" PKLPATH = os.path.expanduser(FILEPATH) main()

23.676923

83

0.684211

54fe1eee5bca5dc248b6bf225d479bd8fc671965

1,041

py

Python

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

app/index.py

vprnet/school-closings

04c63170ea36cabe0a3486f0e58830952e1fd0a8

[ "Apache-2.0" ]

null

#!/usr/local/bin/python2.7 from flask import Flask import sys from flask_frozen import Freezer from upload_s3 import set_metadata from config import AWS_DIRECTORY app = Flask(__name__) app.config.from_object('config') from views import * # Serving from s3 leads to some complications in how static files are served if len(sys.argv) > 1: if sys.argv[1] == 'build': PROJECT_ROOT = '/' + AWS_DIRECTORY elif sys.argv[1] == 'test': PROJECT_ROOT = '/www.vpr.net/' + AWS_DIRECTORY else: PROJECT_ROOT = '/' app.wsgi_app = WebFactionMiddleware(app.wsgi_app) if __name__ == '__main__': if len(sys.argv) > 1 and sys.argv[1] == 'build': app.debug = True freezer = Freezer(app) freezer.freeze() set_metadata() else: app.run(debug=True)

24.209302

76

0.668588

07010f1430c53be8c3d42e4a620d3fc295e28964

1,799

py

Python

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

1

2021-06-05T08:30:21.000Z

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

null

proxyclient/linux.py

modwizcode/m1n1

96d133e854dfe878ea39f9c994545a2026a446a8

[ "MIT" ]

null

#!/usr/bin/python from setup import * payload = open(sys.argv[1], "rb").read() dtb = open(sys.argv[2], "rb").read() if len(sys.argv) > 3: initramfs = open(sys.argv[3], "rb").read() initramfs_size = len(initramfs) else: initramfs = None initramfs_size = 0 compressed_size = len(payload) compressed_addr = u.malloc(compressed_size) dtb_addr = u.malloc(len(dtb)) print("Loading %d bytes to 0x%x..0x%x..." % (compressed_size, compressed_addr, compressed_addr + compressed_size)) iface.writemem(compressed_addr, payload, True) print("Loading DTB to 0x%x..." % dtb_addr) iface.writemem(dtb_addr, dtb) kernel_size = 32 * 1024 * 1024 kernel_base = u.memalign(2 * 1024 * 1024, kernel_size) print("Kernel_base: 0x%x" % kernel_base) assert not (kernel_base & 0xffff) if initramfs is not None: initramfs_base = u.memalign(65536, initramfs_size) print("Loading %d initramfs bytes to 0x%x..." % (initramfs_size, initramfs_base)) iface.writemem(initramfs_base, initramfs, True) p.kboot_set_initrd(initramfs_base, initramfs_size) if p.kboot_prepare_dt(dtb_addr): print("DT prepare failed") sys.exit(1) #kernel_size = p.xzdec(compressed_addr, compressed_size) #if kernel_size < 0: #raise Exception("Decompression header check error!",) #print("Uncompressed kernel size: %d bytes" % kernel_size) print("Uncompressing...") iface.dev.timeout = 40 kernel_size = p.gzdec(compressed_addr, compressed_size, kernel_base, kernel_size) print(kernel_size) if kernel_size < 0: raise Exception("Decompression error!") print("Decompress OK...") p.dc_cvau(kernel_base, kernel_size) p.ic_ivau(kernel_base, kernel_size) print("Ready to boot") daif = u.mrs(DAIF) daif |= 0x3c0 u.msr(DAIF, daif) print("DAIF: %x" % daif) p.kboot_boot(kernel_base) iface.ttymode()

24.310811

114

0.721512

07027cec6982fe1f9197878d8796ee05b6d45b5e

1,313

py

Python

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

1

2021-06-29T03:41:27.000Z

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

null

src/server.py

shizhongpwn/ancypwn

716146e4986c514754492c8503ab196eecb9466d

[ "MIT" ]

1

2021-06-18T05:36:28.000Z

import json import os import multiprocessing import struct import importlib from socketserver import TCPServer, StreamRequestHandler

31.261905

79

0.657273

0704c30e12f5e2ffe2ea17cf59fe41a9fd37e4af

565

py

Python

speech_to_text/views.py

zace3d/video_analysis

9001486ae64160ca497f6b9a99df5d9a5c5422cc

[ "Apache-2.0" ]

null

speech_to_text/views.py

zace3d/video_analysis

9001486ae64160ca497f6b9a99df5d9a5c5422cc

[ "Apache-2.0" ]

9

2019-12-04T22:38:16.000Z

2021-06-10T17:51:32.000Z

speech_to_text/views.py

zace3d/video_analysis

9001486ae64160ca497f6b9a99df5d9a5c5422cc

[ "Apache-2.0" ]

null

from django.shortcuts import render from django.contrib.auth.decorators import login_required from django.http import JsonResponse from django.views.decorators.csrf import csrf_exempt from . import helpers # Create your views here.

25.681818

70

0.766372

070792428b154808490c0fc141036d69c221ccfb

2,981

py

Python

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

4,258

2015-01-04T22:06:10.000Z

2022-03-31T23:40:27.000Z

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

1,013

2015-01-12T02:31:03.000Z

2021-09-16T19:09:03.000Z

security_monkey/watchers/vpc/vpn.py

boladmin/security_monkey

c28592ffd518fa399527d26262683fc860c30eef

[ "Apache-2.0" ]

965

2015-01-11T21:06:07.000Z

2022-03-17T16:53:57.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # 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. """ .. module: security_monkey.watchers.vpc.vpn :platform: Unix .. version:: $$VERSION$$ .. moduleauthor:: Alex Cline <alex.cline@gmail.com> @alex.cline """ from cloudaux.aws.ec2 import describe_vpn_connections from security_monkey.cloudaux_watcher import CloudAuxWatcher from security_monkey.watcher import ChangeItem DATETIME_FORMAT = '%Y-%m-%dT%H:%M:%SZ'

37.2625

115

0.614223

0708030cc6b0ac486ef0bd568029e80e9873483c

2,332

py

Python

particle.py

coush001/Imperial-MSc-Group-Project-2

9309217895802d11c6fe9d2dca9b21f98fbc1c61

[ "MIT" ]

null

particle.py

coush001/Imperial-MSc-Group-Project-2

9309217895802d11c6fe9d2dca9b21f98fbc1c61

[ "MIT" ]

null

particle.py

coush001/Imperial-MSc-Group-Project-2

9309217895802d11c6fe9d2dca9b21f98fbc1c61

[ "MIT" ]

null

from itertools import count import numpy as np

30.285714

107

0.551887

0708b3e7b515fbe0913b6b5bb88c0fbd4c828abe

501

py

Python

app/main/form.py

hussein18149/PITCHBOARD

9aa515f8dd18464830bdf80488a317e8e791bd1b

[ "MIT" ]

null

app/main/form.py

hussein18149/PITCHBOARD

9aa515f8dd18464830bdf80488a317e8e791bd1b

[ "MIT" ]

null

app/main/form.py

hussein18149/PITCHBOARD

9aa515f8dd18464830bdf80488a317e8e791bd1b

[ "MIT" ]

null

from flask_wtf import FlaskForm from wtforms import StringField,TextAreaField,SubmitField from wtforms.validators import Required

31.3125

73

0.754491

07092a144b2a5c13ba5ef9b78acec4dd39f5a15b

4,840

py

Python

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

1

2017-10-31T21:02:59.000Z

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

null

soar_instruments/sami/adclass.py

soar-telescope/dragons-soar

a1c600074f532c1af6bd59bc2cc662a1aecd39c4

[ "MIT" ]

null

import re import astrodata from astrodata import (astro_data_tag, TagSet, astro_data_descriptor, returns_list) from astrodata.fits import FitsLoader, FitsProvider from ..soar import AstroDataSOAR

33.846154

79

0.590083

0709b6cd82b1f84edf49917175e51ec7e1ae9747

264

py

Python

practice/src/design_pattern/TemplateMethod.py

t10471/python

75056454bfb49197eb44f6b4d6a1b0a0b4b408ec

[ "MIT" ]

null

practice/src/design_pattern/TemplateMethod.py

t10471/python

75056454bfb49197eb44f6b4d6a1b0a0b4b408ec

[ "MIT" ]

null

practice/src/design_pattern/TemplateMethod.py

t10471/python

75056454bfb49197eb44f6b4d6a1b0a0b4b408ec

[ "MIT" ]

null

# -*- coding: utf-8 -*- #

15.529412

30

0.556818

070a2f74e288d9e0f7d67adf9e2e415a8758caa2

1,957

py

Python

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

17

2020-07-29T11:08:19.000Z

2021-01-07T11:23:33.000Z

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

5

2020-08-04T02:51:39.000Z

2020-08-21T03:44:08.000Z

yoon/stage1_kernel.py

yoon28/realsr-noise-injection

402679490bf0972d09aaaadee3b5b9850c2a36e4

[ "Apache-2.0" ]

null

import os, sys import numpy as np import cv2 import random import torch from configs import Config from kernelGAN import KernelGAN from data import DataGenerator from learner import Learner import tqdm DATA_LOC = "/mnt/data/NTIRE2020/realSR/track2" # "/mnt/data/NTIRE2020/realSR/track1" DATA_X = "DPEDiphone-tr-x" # "Corrupted-tr-x" DATA_Y = "DPEDiphone-tr-y" # "Corrupted-tr-y" DATA_VAL = "DPEDiphone-va" # "Corrupted-va-x" if __name__ == "__main__": seed_num = 0 torch.manual_seed(seed_num) torch.cuda.manual_seed(seed_num) torch.cuda.manual_seed_all(seed_num) torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False np.random.seed(seed_num) random.seed(seed_num) # exit(0) data = {"X":[os.path.join(DATA_LOC, DATA_X, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_X)) if f[-4:] == ".png"], "Y":[os.path.join(DATA_LOC, DATA_Y, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_Y)) if f[-4:] == ".png"], "val":[os.path.join(DATA_LOC, DATA_VAL, f) for f in os.listdir(os.path.join(DATA_LOC, DATA_VAL)) if f[-4:] == ".png"]} Kernels = [] Noises = [] for f in data["X"]: estimate_kernel(f) print("fin.")

30.107692

130

0.654573

070a513dc67a15b46d7b419d4ba1b638e56fb11a

731

py

Python

test/rdfa/test_non_xhtml.py

RDFLib/PyRDFa

efc24d4940910ca1e65900c25b62047301bbdcc7

[ "BSD-3-Clause" ]

8

2015-04-01T19:55:22.000Z

2020-04-25T08:50:05.000Z

test/rdfa/test_non_xhtml.py

DalavanCloud/PyRDFa

fd5c8826fb9e5f6f5a578564b1149fdae6c40aad

[ "BSD-3-Clause" ]

null

test/rdfa/test_non_xhtml.py

DalavanCloud/PyRDFa

fd5c8826fb9e5f6f5a578564b1149fdae6c40aad

[ "BSD-3-Clause" ]

1

2019-02-12T03:15:00.000Z

from unittest import TestCase from pyRdfa import pyRdfa

33.227273

100

0.682627

070a6926f75c6689b9bf183a8c81961b1ffe5bbd

1,150

py

Python

python/pyoai/setup.py

jr3cermak/robs-kitchensink

74b7eb1b1acd8b700d61c5a9ba0c69be3cc6763a

[ "ECL-2.0", "Apache-2.0" ]

null

python/pyoai/setup.py

jr3cermak/robs-kitchensink

74b7eb1b1acd8b700d61c5a9ba0c69be3cc6763a

[ "ECL-2.0", "Apache-2.0" ]

null

python/pyoai/setup.py

jr3cermak/robs-kitchensink

74b7eb1b1acd8b700d61c5a9ba0c69be3cc6763a

[ "ECL-2.0", "Apache-2.0" ]

null

from setuptools import setup, find_packages from os.path import join, dirname setup( name='pyoai', version='2.4.6.b', author='Infrae', author_email='rob.cermak@gmail.com', url='https://github.com/jr3cermak/robs-kitchensink/tree/master/python/pyoai', classifiers=["Development Status :: 4 - Beta", "Programming Language :: Python", "License :: OSI Approved :: BSD License", "Topic :: Software Development :: Libraries :: Python Modules", "Environment :: Web Environment"], description="""\ The oaipmh module is a Python implementation of an "Open Archives Initiative Protocol for Metadata Harvesting" (version 2) client and server. The protocol is described here: http://www.openarchives.org/OAI/openarchivesprotocol.html """, long_description=(open(join(dirname(__file__), 'README.rst')).read()+ '\n\n'+ open(join(dirname(__file__), 'HISTORY.txt')).read()), packages=find_packages('src'), package_dir = {'': 'src'}, zip_safe=False, license='BSD', keywords='OAI-PMH xml archive', install_requires=['lxml'], )

35.9375

81

0.650435

070b402dc83b92f4ca29c79684b3e9fb26a6238f

4,201

py

Python

utils/functions.py

Roozbeh-Bazargani/CPSC-533R-project

453f093b23d2363f09c61079d1d4fbd878abf3be

[ "MIT" ]

null

utils/functions.py

Roozbeh-Bazargani/CPSC-533R-project

453f093b23d2363f09c61079d1d4fbd878abf3be

[ "MIT" ]

null

utils/functions.py

Roozbeh-Bazargani/CPSC-533R-project

453f093b23d2363f09c61079d1d4fbd878abf3be

[ "MIT" ]

null

import torch from torch import nn import math #0 left hip #1 left knee #2 left foot #3 right hip #4 right knee #5 right foot #6 middle hip #7 neck #8 nose #9 head #10 left shoulder #11 left elbow #12 left wrist #13 right shoulder #14 right elbow #15 right wrist ''' def temporal_loss(J, K, J_R, K_R): # J is J3d at time t and K is J3d at time t+k. J_R means the reversed rotation of J return torch.norm(J - K - J_R + K_R, dim=1)**2 ''' ''' def random_rotation(J3d): # J = torch.transpose(J3d, 1, 2) J = J3d root = torch.zeros(J.shape[0:2]) for i in range(J.shape[0]): theta = torch.rand(1).cuda() * 2*torch.tensor(math.pi).cuda() # random theta root[i] = J[i,:,8] # joint 8 = nose is root temp = rotation(J[i,:,:], theta, root[i].unsqueeze(1), False) # print(temp.shape) J[i,:,:] = temp return J, theta, root # need these values in the code def rotation(J, theta, root, is_reversed): # rotation over y axis by theta D = root[2] # absolute depth of the root joint v_t = torch.tensor([[0], [0], [D]]).cuda() # translation vector if is_reversed: root, v_t = v_t, root # swap theta = -theta # R = torch.tensor([[torch.cos(theta), -torch.sin(theta), 0], [torch.sin(theta), torch.cos(theta), 0], [0, 0, 1]]) # rotation matrix over z by theta degrees R = torch.tensor([[torch.cos(theta), 0, torch.sin(theta)], [0, 1, 0], [-torch.sin(theta), 0, torch.cos(theta)]]).cuda() # rotation matrix over y by theta degrees # R = torch.tensor([[1, 0, 0], [0, torch.cos(theta), -torch.sin(theta)], [0, torch.sin(theta), torch.cos(theta)]]) # rotation matrix over x by theta degrees J_R = torch.matmul(R, J.cuda() - root.cuda()) + v_t # rotation return J_R def reverse_rotation(J3d_R, theta, root): # J = torch.transpose(J3d_R, 1, 2) J = J3d_R for i in range(J.shape[0]): J[i,:,:] = rotation(J[i,:,:].cuda(), theta.cuda(), root[i].unsqueeze(1).cuda(), True) return J '''

42.434343

181

0.633183

070c8541550d5f85dceb7ec0adf8c900bec0c786

303

py

Python

Desafio Python/Aula 22 des109.py

ayresmajor/Curso-python

006229cec38ea365bf43b19e3ce93fbd32e1dca6

[ "MIT" ]

null

Desafio Python/Aula 22 des109.py

ayresmajor/Curso-python

006229cec38ea365bf43b19e3ce93fbd32e1dca6

[ "MIT" ]

null

Desafio Python/Aula 22 des109.py

ayresmajor/Curso-python

006229cec38ea365bf43b19e3ce93fbd32e1dca6

[ "MIT" ]

null

from des109 import moeda preco = float(input('Digite o preo pretendido: ')) print(f'''A metade do preo {(moeda.metade(preco))} O dobro do preo {(moeda.dobra(preco))} Aumentando o preo 10% temos {(moeda.aumentar(preco, 10))} Diminuindo o preo 13% temos {(moeda.aumentar(preco, 13))}''')

37.875

64

0.693069

070d242ccbb22625007056e552b13c344fbecb38

474

py

Python

Chapter13_code/ch13_r05_using_the_rpc_api/xmlrpc.py

PacktPublishing/Odoo-Development-Cookbook

5553110c0bc352c4541f11904e236cad3c443b8b

[ "MIT" ]

55

2016-05-23T16:05:50.000Z

2021-07-19T00:16:46.000Z

Chapter13_code/ch13_r05_using_the_rpc_api/xmlrpc.py

kogkog098/Odoo-Development-Cookbook

166c9b98efbc9108b30d719213689afb1f1c294d

[ "MIT" ]

1

2016-12-09T02:14:21.000Z

2018-07-02T09:02:20.000Z

Chapter13_code/ch13_r05_using_the_rpc_api/xmlrpc.py

kogkog098/Odoo-Development-Cookbook

166c9b98efbc9108b30d719213689afb1f1c294d

[ "MIT" ]

52

2016-06-01T20:03:59.000Z

2020-10-31T23:58:25.000Z

#!/usr/bin/env python2 import xmlrpclib db = 'odoo9' user = 'admin' password = 'admin' uid = xmlrpclib.ServerProxy('http://localhost:8069/xmlrpc/2/common')\ .authenticate(db, user, password, {}) odoo = xmlrpclib.ServerProxy('http://localhost:8069/xmlrpc/2/object') installed_modules = odoo.execute_kw( db, uid, password, 'ir.module.module', 'search_read', [[('state', '=', 'installed')], ['name']], {}) for module in installed_modules: print module['name']

31.6

69

0.681435

070dfc39dd180a0fc71b0110b529e2e8beee6cea

10,971

py

Python

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

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

1

2019-09-03T13:38:08.000Z

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

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

null

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

emorynlp/character-identification-old

f6519166dd30bd8140f05aa3e43225ab27c2ea6d

[ "Apache-2.0" ]

null

from abc import * import numpy as np ########################################################### ########################################################### ###########################################################

44.417004

120

0.668854

070fb86171845062c7fc24a28acd90660006212e

521

py

Python

ufdl-core-app/src/ufdl/core_app/models/mixins/_UserRestrictedQuerySet.py

waikato-ufdl/ufdl-backend

776fc906c61eba6c2f2e6324758e7b8a323e30d7

[ "Apache-2.0" ]

null

ufdl-core-app/src/ufdl/core_app/models/mixins/_UserRestrictedQuerySet.py

waikato-ufdl/ufdl-backend

776fc906c61eba6c2f2e6324758e7b8a323e30d7

[ "Apache-2.0" ]

85

2020-07-24T00:04:28.000Z

2022-02-10T10:35:15.000Z

ufdl-core-app/src/ufdl/core_app/models/mixins/_UserRestrictedQuerySet.py

waikato-ufdl/ufdl-backend

776fc906c61eba6c2f2e6324758e7b8a323e30d7

[ "Apache-2.0" ]

null

from django.db import models

28.944444

79

0.658349

071028fc162506887f63334754f84e376a76520e

31,879

py

Python

sdk/python/pulumi_azure_native/eventgrid/partner_registration.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/eventgrid/partner_registration.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/eventgrid/partner_registration.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._enums import * __all__ = ['PartnerRegistrationArgs', 'PartnerRegistration'] def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, authorized_azure_subscription_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, customer_service_uri: Optional[pulumi.Input[str]] = None, location: Optional[pulumi.Input[str]] = None, logo_uri: Optional[pulumi.Input[str]] = None, long_description: Optional[pulumi.Input[str]] = None, partner_customer_service_extension: Optional[pulumi.Input[str]] = None, partner_customer_service_number: Optional[pulumi.Input[str]] = None, partner_name: Optional[pulumi.Input[str]] = None, partner_registration_name: Optional[pulumi.Input[str]] = None, partner_resource_type_description: Optional[pulumi.Input[str]] = None, partner_resource_type_display_name: Optional[pulumi.Input[str]] = None, partner_resource_type_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, setup_uri: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, visibility_state: Optional[pulumi.Input[Union[str, 'PartnerRegistrationVisibilityState']]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = PartnerRegistrationArgs.__new__(PartnerRegistrationArgs) __props__.__dict__["authorized_azure_subscription_ids"] = authorized_azure_subscription_ids __props__.__dict__["customer_service_uri"] = customer_service_uri __props__.__dict__["location"] = location __props__.__dict__["logo_uri"] = logo_uri __props__.__dict__["long_description"] = long_description __props__.__dict__["partner_customer_service_extension"] = partner_customer_service_extension __props__.__dict__["partner_customer_service_number"] = partner_customer_service_number __props__.__dict__["partner_name"] = partner_name __props__.__dict__["partner_registration_name"] = partner_registration_name __props__.__dict__["partner_resource_type_description"] = partner_resource_type_description __props__.__dict__["partner_resource_type_display_name"] = partner_resource_type_display_name __props__.__dict__["partner_resource_type_name"] = partner_resource_type_name if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__.__dict__["resource_group_name"] = resource_group_name __props__.__dict__["setup_uri"] = setup_uri __props__.__dict__["tags"] = tags __props__.__dict__["visibility_state"] = visibility_state __props__.__dict__["name"] = None __props__.__dict__["provisioning_state"] = None __props__.__dict__["system_data"] = None __props__.__dict__["type"] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:eventgrid:PartnerRegistration"), pulumi.Alias(type_="azure-native:eventgrid/v20200401preview:PartnerRegistration"), pulumi.Alias(type_="azure-nextgen:eventgrid/v20200401preview:PartnerRegistration"), pulumi.Alias(type_="azure-native:eventgrid/v20201015preview:PartnerRegistration"), pulumi.Alias(type_="azure-nextgen:eventgrid/v20201015preview:PartnerRegistration")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(PartnerRegistration, __self__).__init__( 'azure-native:eventgrid:PartnerRegistration', resource_name, __props__, opts)

51.584142

454

0.685624

071099c9cb76fe44fe601d2109b5cad6021d0a3d

2,420

py

Python

_ar/masking_provement.py

TomKingsfordUoA/ResidualMaskingNetwork

6ce5ddf70f8ac8f1e6da2746b0bbeb9e457ceb7d

[ "MIT" ]

242

2020-01-09T11:06:21.000Z

2022-03-26T14:51:48.000Z

_ar/masking_provement.py

huyhnueit68/ResidualMaskingNetwork

b77abb6e548b9a09b5c96b1592d71332b45d050e

[ "MIT" ]

33

2020-01-09T08:42:10.000Z

2022-03-23T07:52:56.000Z

_ar/masking_provement.py

huyhnueit68/ResidualMaskingNetwork

b77abb6e548b9a09b5c96b1592d71332b45d050e

[ "MIT" ]

61

2020-01-19T02:20:37.000Z

2022-03-25T13:08:48.000Z

import os import glob import cv2 import numpy as np import torch from torchvision.transforms import transforms from natsort import natsorted from models import resmasking_dropout1 from utils.datasets.fer2013dataset import EMOTION_DICT from barez import show transform = transforms.Compose( [ transforms.ToPILImage(), transforms.ToTensor(), ] ) model = resmasking_dropout1(3, 7) # state = torch.load('./saved/checkpoints/resmasking_dropout1_rot30_2019Nov17_14.33') state = torch.load("./saved/checkpoints/Z_resmasking_dropout1_rot30_2019Nov30_13.32") model.load_state_dict(state["net"]) model.cuda() model.eval() for image_path in natsorted( glob.glob("/home/z/research/bkemo/images/**/*.png", recursive=True) ): image_name = os.path.basename(image_path) print(image_name) # image_path = '/home/z/research/bkemo/images/disgust/0.0_dc10a3_1976_0.png' image = cv2.imread(image_path) image = cv2.resize(image, (224, 224)) tensor = transform(image) tensor = torch.unsqueeze(tensor, 0) tensor = tensor.cuda() # output = model(tensor) x = model.conv1(tensor) # 112 x = model.bn1(x) x = model.relu(x) x = model.maxpool(x) # 56 x = model.layer1(x) # 56 m = model.mask1(x) x = x * (1 + m) x = model.layer2(x) # 28 m = model.mask2(x) x = x * (1 + m) x = model.layer3(x) # 14 heat_1 = activations_mask(x) m = model.mask3(x) x = x * (1 + m) # heat_2 = activations_mask(m) x = model.layer4(x) # 7 m = model.mask4(x) x = x * (1 + m) x = model.avgpool(x) x = torch.flatten(x, 1) output = model.fc(x) # print(np.sum(heat_1 - heat_2)) # show(np.concatenate((image, heat_1, heat_2), axis=1)) cv2.imwrite( "./masking_provements/{}".format(image_name), np.concatenate((image, heat_1), axis=1), ) # np.concatenate((image, heat_1, heat_2), axis=1)) # output = output.cpu().numpy() # print(EMOTION_DICT[torch.argmax(output, 1).item()])

26.021505

85

0.647934

07112b5b2ca5ebda12c4c78461b67e41243aa4a8

1,727

py

Python

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

1

2022-03-03T23:19:57.000Z

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

null

Python/Gerenciador de pagamentos.py

Kauan677/Projetos-Python

62f6b476e6d250d9ff31c95808b31ebd3ab4fdbb

[ "MIT" ]

null

import time import colorama while True: consulta = gerenciador_de_pagamento() consulta = str(input('Quer consultar novamente? ')) if consulta in ['sim', 'Sim', 'SIM']: pass elif consulta in ['no', 'nao','No', 'Nao', 'NAO','NO']: break else: break

38.377778

105

0.59062

0711bae755946fd50e5034659184b298bbe243f6

1,786

py

Python

src/scs_core/osio/data/abstract_topic.py

seoss/scs_core

0d4323c5697a39eb44a887f179ba5dca3716c1d2

[ "MIT" ]

3

2019-03-12T01:59:58.000Z

2020-09-12T07:27:42.000Z

src/scs_core/osio/data/abstract_topic.py

seoss/scs_core

0d4323c5697a39eb44a887f179ba5dca3716c1d2

[ "MIT" ]

1

2018-04-20T07:58:38.000Z

2021-03-27T08:52:45.000Z

src/scs_core/osio/data/abstract_topic.py

seoss/scs_core

0d4323c5697a39eb44a887f179ba5dca3716c1d2

[ "MIT" ]

4

2017-09-29T13:08:43.000Z

2019-10-09T09:13:58.000Z

""" Created on 2 Apr 2017 @author: Bruno Beloff (bruno.beloff@southcoastscience.com) """ from collections import OrderedDict from scs_core.data.json import JSONable # --------------------------------------------------------------------------------------------------------------------

23.194805

118

0.403135

0711c47f68c0681b184df5cde182256dcc62322f

11,286

py

Python

sdk/python/pulumi_azure_native/notificationhubs/latest/get_namespace.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/notificationhubs/latest/get_namespace.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/notificationhubs/latest/get_namespace.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = [ 'GetNamespaceResult', 'AwaitableGetNamespaceResult', 'get_namespace', ] warnings.warn("""The 'latest' version is deprecated. Please migrate to the function in the top-level module: 'azure-native:notificationhubs:getNamespace'.""", DeprecationWarning) def get_namespace(namespace_name: Optional[str] = None, resource_group_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetNamespaceResult: """ Description of a Namespace resource. Latest API Version: 2017-04-01. :param str namespace_name: The namespace name. :param str resource_group_name: The name of the resource group. """ pulumi.log.warn("""get_namespace is deprecated: The 'latest' version is deprecated. Please migrate to the function in the top-level module: 'azure-native:notificationhubs:getNamespace'.""") __args__ = dict() __args__['namespaceName'] = namespace_name __args__['resourceGroupName'] = resource_group_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:notificationhubs/latest:getNamespace', __args__, opts=opts, typ=GetNamespaceResult).value return AwaitableGetNamespaceResult( created_at=__ret__.created_at, critical=__ret__.critical, data_center=__ret__.data_center, enabled=__ret__.enabled, id=__ret__.id, location=__ret__.location, metric_id=__ret__.metric_id, name=__ret__.name, namespace_type=__ret__.namespace_type, provisioning_state=__ret__.provisioning_state, region=__ret__.region, scale_unit=__ret__.scale_unit, service_bus_endpoint=__ret__.service_bus_endpoint, sku=__ret__.sku, status=__ret__.status, subscription_id=__ret__.subscription_id, tags=__ret__.tags, type=__ret__.type, updated_at=__ret__.updated_at)

37.003279

329

0.641148

0713544bf0325f76443f346f91d5551b3d2799f3

393

py

Python

chue/utils.py

naren-m/chue

6f77ad990c911353524c5c99bcf6e30155edaf97

[ "MIT" ]

null

chue/utils.py

naren-m/chue

6f77ad990c911353524c5c99bcf6e30155edaf97

[ "MIT" ]

null

chue/utils.py

naren-m/chue

6f77ad990c911353524c5c99bcf6e30155edaf97

[ "MIT" ]

null

import json from pygments import highlight from pygments.lexers import JsonLexer from pygments.formatters import TerminalFormatter

28.071429

64

0.793893

0713bf1d16fde855bda0ed021b030d08feadd022

3,486

py

Python

selfdrive/car/chrysler/radar_interface.py

919bot/Tessa

9b48ff9020e8fb6992fc78271f2720fd19e01093

[ "MIT" ]

85

2019-06-14T17:51:31.000Z

2022-02-09T22:18:20.000Z

selfdrive/car/chrysler/radar_interface.py

919bot/Tessa

9b48ff9020e8fb6992fc78271f2720fd19e01093

[ "MIT" ]

4

2020-04-12T21:34:03.000Z

2020-04-15T22:22:15.000Z

selfdrive/car/chrysler/radar_interface.py

919bot/Tessa

9b48ff9020e8fb6992fc78271f2720fd19e01093

[ "MIT" ]

73

2018-12-03T19:34:42.000Z

2020-07-27T05:10:23.000Z

#!/usr/bin/env python3 import os from opendbc.can.parser import CANParser from cereal import car from selfdrive.car.interfaces import RadarInterfaceBase RADAR_MSGS_C = list(range(0x2c2, 0x2d4+2, 2)) # c_ messages 706,...,724 RADAR_MSGS_D = list(range(0x2a2, 0x2b4+2, 2)) # d_ messages LAST_MSG = max(RADAR_MSGS_C + RADAR_MSGS_D) NUMBER_MSGS = len(RADAR_MSGS_C) + len(RADAR_MSGS_D)

37.085106

98

0.645439

0714065ddc085782b982ec392f121b65f95bc048

911

py

Python

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

429

2015-01-06T18:44:20.000Z

2022-03-19T22:22:11.000Z

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

254

2015-01-01T18:11:57.000Z

2022-03-22T09:55:51.000Z

mod/tools/ccmake.py

mattiasljungstrom/fips

8775e299f710ae5b977d49dc0672b607f2a10378

[ "MIT" ]

102

2015-01-17T11:41:16.000Z

2022-02-24T23:47:30.000Z

""" wrapper for ccmake command line tool """ import subprocess name = 'ccmake' platforms = ['linux', 'osx'] optional = True not_found = "required for 'fips config' functionality" #------------------------------------------------------------------------------- def check_exists(fips_dir) : """test if ccmake is in the path :returns: True if ccmake is in the path """ try: out = subprocess.check_output(['ccmake', '--version']) return True except (OSError, subprocess.CalledProcessError): return False #------------------------------------------------------------------------------- def run(build_dir) : """run ccmake to configure cmake project :param build_dir: directory where ccmake should run :returns: True if ccmake returns successful """ res = subprocess.call('ccmake .', cwd=build_dir, shell=True) return res == 0

26.794118

80

0.535675

071593280ef30a4532ccbb4b6f3c6b4f7d728fa5

4,251

py

Python

image_quality/handlers/data_generator.py

mbartoli/image-quality-assessment

b957c781ac8a11f8668f58345524f33503338b3b

[ "Apache-2.0" ]

1

2021-03-27T15:09:30.000Z

image_quality/handlers/data_generator.py

welcotravel/image-quality-assessment

b9e17de93578220e5ae142725d9153098759e7c8

[ "Apache-2.0" ]

null

image_quality/handlers/data_generator.py

welcotravel/image-quality-assessment

b9e17de93578220e5ae142725d9153098759e7c8

[ "Apache-2.0" ]

1

2020-10-05T03:20:53.000Z

import os import numpy as np import tensorflow as tf from image_quality.utils import utils

40.485714

106

0.713479

07167e515430a27837434e8e166dc173dffdcc37

1,914

py

Python

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

codewars/4 kyu/strip-comments.py

sirken/coding-practice

9c5e23b2c24f525a89a5e1d15ce3aec3ad1a01ab

[ "MIT" ]

null

from Test import Test, Test as test ''' Complete the solution so that it strips all text that follows any of a set of comment markers passed in. Any whitespace at the end of the line should also be stripped out. Example: Given an input string of: apples, pears # and bananas grapes bananas !apples The output expected would be: apples, pears grapes bananas The code would be called like so: result = solution("apples, pears # and bananas\ngrapes\nbananas !apples", ["#", "!"]) # result should == "apples, pears\ngrapes\nbananas" ''' # Split by rows, then find earliest marker and extract string before it # Top solution, split list by \n, edit in place # Top solution expanded Test.assert_equals(solution("apples, pears # and bananas\ngrapes\nbananas !apples", ["#", "!"]), "apples, pears\ngrapes\nbananas") Test.assert_equals(solution("a #b\nc\nd $e f g", ["#", "$"]), "a\nc\nd") Test.assert_equals(solution('= - avocados oranges pears cherries\nlemons apples\n- watermelons strawberries', ['#', '?', '=', ',', '.', '-', '!']), '\nlemons apples\n')

31.9

171

0.640021

0718f25c782fcd74f5e9c8f0ae638c3321dd5b08

6,221

py

Python

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

5

2020-09-09T09:44:31.000Z

2021-07-02T09:49:21.000Z

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

null

qat/interop/qiskit/quantum_channels.py

myQLM/myqlm-interop

9d77cb7c719f82be05d9f88493522940b8142124

[ "Apache-2.0" ]

3

2020-07-10T17:51:47.000Z

2021-04-13T16:33:44.000Z

# -*- coding: utf-8 -*- """ Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, 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. """ from qiskit.quantum_info.operators.channel import Choi, PTM, Kraus, Chi, SuperOp import numpy as np from qat.comm.quops.ttypes import QuantumChannel, RepresentationType from qat.comm.datamodel.ttypes import Matrix, ComplexNumber def array_to_matrix(array): """ Transform a two dimmentional numpy array to a myqlm Matrix. Args: array: (ndarray) a two dimmentional numpy array Returns: (Matrix): a myqlm Matrix """ assert len(array.shape) == 2, "The array must be two dimmentional" data = [] for arr in array: for elem in arr: data.append(ComplexNumber(np.real(elem), np.imag(elem))) matri = Matrix(array.shape[0], array.shape[1], data) return matri def qiskit_to_qchannel(representation): """ Create a myqlm representation of quantum channel from a qiskit representation of a quantum channel. Args: representation: (Kraus|Choi|Chi|SuperOp|PTM) qiskit representation of a quantum channel. Returns: (QuantumChannel): myqlm representation of a quantum channel. """ qchannel = None qiskit_data = representation.data # Find what representation it is. # Then create the corresponding matrix (kraus_ops|basis|matrix)from the data # of the representation. # Finally, create the QuantumChannel with the RepresentationType, the arity # (got from the qiskit representation) and the matrix. if isinstance(representation, Kraus): kraus_ops = [] for arr in qiskit_data: kraus_ops.append(array_to_matrix(arr)) qchannel = QuantumChannel( representation=RepresentationType.KRAUS, arity=representation.num_qubits, kraus_ops=kraus_ops) elif isinstance(representation, Chi): basis = [] basis.append(array_to_matrix(qiskit_data)) qchannel = QuantumChannel( representation=RepresentationType.CHI, arity=representation.num_qubits, basis=basis) elif isinstance(representation, SuperOp): basis = [] basis.append(array_to_matrix(qiskit_data)) qchannel = QuantumChannel( representation=RepresentationType.SUPEROP, arity=representation.num_qubits, basis=basis) elif isinstance(representation, PTM): matri = array_to_matrix(qiskit_data) qchannel = QuantumChannel( representation=RepresentationType.PTM, arity=representation.num_qubits, matrix=matri) elif isinstance(representation, Choi): matri = array_to_matrix(qiskit_data) qchannel = QuantumChannel( representation=RepresentationType.CHOI, arity=representation.num_qubits, matrix=matri) return qchannel def qchannel_to_qiskit(representation): """ Create a qiskit representation of quantum channel from a myqlm representation of a quantum channel. Args: representation: (QuantumChannel) myqlm representation of a quantum channel. Returns: (Kraus|Choi|Chi|SuperOp|PTM): qiskit representation of a quantum channel. """ rep = representation.representation # Find what representation it is. # Then create the corresponding matrix and shape it like qiskit is expecting it. # Finally, create the qiskit representation from that matrix. if rep in (RepresentationType.PTM, RepresentationType.CHOI): matri = representation.matrix data_re = [] data_im = [] for i in range(matri.nRows): for j in range(matri.nCols): data_re.append(matri.data[i * matri.nRows + j].re + 0.j) data_im.append(matri.data[i * matri.nRows + j].im) data = np.array(data_re) data.imag = np.array(data_im) data = data.reshape((matri.nRows, matri.nCols)) return PTM(data) if (rep == RepresentationType.PTM) else Choi(data) if rep in (RepresentationType.CHI, RepresentationType.SUPEROP): final_data = [] for matri in representation.basis: data_re = [] data_im = [] for i in range(matri.nRows): for j in range(matri.nCols): data_re.append(matri.data[i * matri.nRows + j].re + 0.j) data_im.append(matri.data[i * matri.nRows + j].im) data = np.array(data_re) data.imag = np.array(data_im) data = data.reshape((matri.nRows, matri.nCols)) final_data.append(data) if rep == RepresentationType.CHI: return Chi(final_data) if len(final_data) > 1 else Chi(final_data[0]) return SuperOp(final_data) if len(final_data) > 1 else SuperOp(final_data[0]) if rep == RepresentationType.KRAUS: final_data = [] for matri in representation.kraus_ops: data_re = [] data_im = [] for i in range(matri.nRows): for j in range(matri.nCols): data_re.append(matri.data[i * matri.nRows + j].re + 0.j) data_im.append(matri.data[i * matri.nRows + j].im) data = np.array(data_re) data.imag = np.array(data_im) data = data.reshape((matri.nRows, matri.nCols)) final_data.append(data) return Kraus(final_data) return None

37.70303

96

0.649735

0719b950e4a48282eaf1194cb80f0583e44f000f

2,061

py

Python

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

mne_nirs/simulation/_simulation.py

mshader/mne-nirs

d59a5436d162108226f31b33b194dfecada40d72

[ "BSD-3-Clause" ]

null

# Authors: Robert Luke <mail@robertluke.net> # # License: BSD (3-clause) import numpy as np from mne import Annotations, create_info from mne.io import RawArray def simulate_nirs_raw(sfreq=3., amplitude=1., sig_dur=300., stim_dur=5., isi_min=15., isi_max=45.): """ Create simulated data. .. warning:: Work in progress: I am trying to think on the best API. Parameters ---------- sfreq : Number The sample rate. amplitude : Number The amplitude of the signal to simulate in uM. sig_dur : Number The length of the signal to generate in seconds. stim_dur : Number The length of the stimulus to generate in seconds. isi_min : Number The minimum duration of the inter stimulus interval in seconds. isi_max : Number The maximum duration of the inter stimulus interval in seconds. Returns ------- raw : instance of Raw The generated raw instance. """ from nilearn.stats.first_level_model import make_first_level_design_matrix from pandas import DataFrame frame_times = np.arange(sig_dur * sfreq) / sfreq onset = 0. onsets = [] conditions = [] durations = [] while onset < sig_dur - 60: onset += np.random.uniform(isi_min, isi_max) + stim_dur onsets.append(onset) conditions.append("A") durations.append(stim_dur) events = DataFrame({'trial_type': conditions, 'onset': onsets, 'duration': durations}) dm = make_first_level_design_matrix(frame_times, events, drift_model='polynomial', drift_order=0) annotations = Annotations(onsets, durations, conditions) info = create_info(ch_names=['Simulated'], sfreq=sfreq, ch_types=['hbo']) raw = RawArray(dm[["A"]].to_numpy().T * amplitude * 1.e-6, info, verbose=False) raw.set_annotations(annotations) return raw

29.442857

78

0.606016

071a7e610b94fdc4f5c933fd228639d190c83b96

3,650

py

Python

build/lib/dataaccess/TransactionRepository.py

athanikos/cryptodataaccess

6189a44c65a9b03c02822a534e865740ab488809

[ "MIT" ]

null

build/lib/dataaccess/TransactionRepository.py

athanikos/cryptodataaccess

6189a44c65a9b03c02822a534e865740ab488809

[ "MIT" ]

null

build/lib/dataaccess/TransactionRepository.py

athanikos/cryptodataaccess

6189a44c65a9b03c02822a534e865740ab488809

[ "MIT" ]

null

from cryptomodel.cryptostore import user_notification, user_channel, user_transaction, operation_type from mongoengine import Q from cryptodataaccess import helpers from cryptodataaccess.helpers import if_none_raise, if_none_raise_with_id

42.44186

120

0.670137

071afc12457e1373ac1b61126e3c5e710f213fb9

1,536

py

Python

app/util/auth2.py

FSU-ACM/Contest-Server

00a71cdcee1a7e4d4e4d8e33b5d6decf27f02313

[ "MIT" ]

8

2019-01-13T21:57:53.000Z

2021-11-29T12:32:48.000Z

app/util/auth2.py

FSU-ACM/Contest-Server

00a71cdcee1a7e4d4e4d8e33b5d6decf27f02313

[ "MIT" ]

73

2018-02-13T00:58:39.000Z

2022-02-10T11:59:53.000Z

app/util/auth2.py

FSU-ACM/Contest-Server

00a71cdcee1a7e4d4e4d8e33b5d6decf27f02313

[ "MIT" ]

4

2018-02-08T18:56:54.000Z

2019-02-13T19:01:53.000Z

""" util.auth2: Authentication tools This module is based off of util.auth, except with the action paradigm removed. """ from flask import session from app.models import Account from app.util import course as course_util # Session keys SESSION_EMAIL = 'email' def create_account(email: str, password: str, first_name: str, last_name: str, fsuid: str, course_list: list = []): """ Creates an account for a single user. :email: Required, the email address of the user. :password: Required, user's chosen password. :first_name: Required, user's first name. :last_name: Required, user's last name. :fsuid: Optional, user's FSUID. :course_list: Optional, courses being taken by user :return: Account object. """ account = Account( email=email, first_name=first_name, last_name=last_name, fsuid=fsuid, is_admin=False ) # Set user's extra credit courses course_util.set_courses(account, course_list) account.set_password(password) account.save() return account def get_account(email: str=None): """ Retrieves account via email (defaults to using session), otherwise redirects to login page. :email: Optional email string, if not provided will use session['email'] :return: Account if email is present in session, None otherwise. """ try: email = email or session['email'] return Account.objects.get_or_404(email=email) except: return None

26.033898

76

0.670573

071b7fe4a170335142cb957704dfc31f09df575c

1,125

py

Python

FeView/pstaticwidget.py

motiurce/FeView

8897b37062be88dd5ead2c8524f6b3b73451e25d

[ "MIT" ]

10

2021-04-09T02:32:23.000Z

2022-03-12T15:21:41.000Z

FeView/pstaticwidget.py

ElsevierSoftwareX/SOFTX-D-21-00063

50eca2a003e6281dea3f1cf43fee221b61f53978

[ "MIT" ]

2

2021-08-07T09:02:21.000Z

2022-02-25T09:30:22.000Z

FeView/pstaticwidget.py

motiurce/FeView

8897b37062be88dd5ead2c8524f6b3b73451e25d

[ "MIT" ]

7

2021-04-09T02:32:25.000Z

2022-03-12T15:21:45.000Z

from PyQt5.QtWidgets import * from matplotlib.backends.backend_qt5agg import FigureCanvas from matplotlib.figure import Figure from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar

46.875

89

0.728889

071b9acd086c7ba6412ea5c6a8e8d3fc44d05f5c

1,719

py

Python

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

pyallocation/solvers/exhaustive.py

julesy89/pyallocation

af80a8e2367a006121dd0702b55efa7b954bb039

[ "Apache-2.0" ]

null

import numpy as np from pymoo.core.algorithm import Algorithm from pymoo.core.population import Population from pymoo.util.termination.no_termination import NoTermination from pyallocation.allocation import FastAllocation from pyallocation.problem import AllocationProblem

26.859375

75

0.623618

071d3f55a7b2c99140b70a77b17ee7b9f4ba705d

602

py

Python

config.py

yasminbraga/ufopa-reports

6d8b213eb0dfce6775d0bb0fd277e8dc09da041c

[ "MIT" ]

null

config.py

yasminbraga/ufopa-reports

6d8b213eb0dfce6775d0bb0fd277e8dc09da041c

[ "MIT" ]

null

config.py

yasminbraga/ufopa-reports

6d8b213eb0dfce6775d0bb0fd277e8dc09da041c

[ "MIT" ]

2

2019-11-24T13:30:35.000Z

2022-01-12T11:47:11.000Z

import os

27.363636

212

0.752492

071dbe42fd5b14449158462daf2a890df418a73d

2,651

py

Python

heat/api/openstack/v1/views/stacks_view.py

noironetworks/heat

7cdadf1155f4d94cf8f967635b98e4012a7acfb7

[ "Apache-2.0" ]

265

2015-01-02T09:33:22.000Z

2022-03-26T23:19:54.000Z

heat/api/openstack/v1/views/stacks_view.py

noironetworks/heat

7cdadf1155f4d94cf8f967635b98e4012a7acfb7

[ "Apache-2.0" ]

8

2015-09-01T15:43:19.000Z

2021-12-14T05:18:23.000Z

heat/api/openstack/v1/views/stacks_view.py

noironetworks/heat

7cdadf1155f4d94cf8f967635b98e4012a7acfb7

[ "Apache-2.0" ]

295

2015-01-06T07:00:40.000Z

2021-09-06T08:05:06.000Z

# # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # 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 itertools from heat.api.openstack.v1 import util from heat.api.openstack.v1.views import views_common from heat.rpc import api as rpc_api _collection_name = 'stacks' basic_keys = ( rpc_api.STACK_ID, rpc_api.STACK_NAME, rpc_api.STACK_DESCRIPTION, rpc_api.STACK_STATUS, rpc_api.STACK_STATUS_DATA, rpc_api.STACK_CREATION_TIME, rpc_api.STACK_DELETION_TIME, rpc_api.STACK_UPDATED_TIME, rpc_api.STACK_OWNER, rpc_api.STACK_PARENT, rpc_api.STACK_USER_PROJECT_ID, rpc_api.STACK_TAGS, )

33.556962

78

0.659751

071ec6aa5cdf0ac5081a189dd02a7abf4954448d

3,571

py

Python

pykrev/formula/find_intersections.py

Kzra/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

4

2021-02-18T10:19:13.000Z

2021-10-04T16:17:30.000Z

pykrev/formula/find_intersections.py

erikafreeman/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

null

pykrev/formula/find_intersections.py

erikafreeman/pykrev

1a328fccded962f309e951c8509b87a82c3d3ae6

[ "MIT" ]

1

2021-09-23T16:03:03.000Z

import itertools import numpy as np import pandas as pd def find_intersections(formula_lists,group_labels,exclusive = True): """ Docstring for function pyKrev.find_intersections ==================== This function compares n lists of molecular formula and outputs a dictionary containing the intersections between each list. Use ---- find_intersections([list_1,..,list_n],['group_1',...,'group_n']) Returns a dictionary in which each key corresponds to a combination of group labels and the corresponding value is a set containing the intersections between the groups in that combination. Parameters ---------- formula_lists: a list containing n lists of molecular formula. Each item in the sub list should be a formula string. group_labels: a list containing n strings of corresponding group labels. exclusive: True or False, depending on whether you want the intersections to contain only unique values. """ if len(formula_lists) != len(group_labels): raise InputError('formula_lists and group_labels must be of equal length') combinations = [seq for i in range(0,len(group_labels)+1) for seq in itertools.combinations(group_labels,i) if len(seq) > 0] combinations = sorted(combinations,key = lambda c : len(c),reverse = True) # sort combinations by length if exclusive == True: assigned_formula = set() #create a set that will hold all the formula already assigned to a group amb = pd.DataFrame(data = formula_lists).T amb.columns = group_labels intersections = dict() for combo in combinations: queries = [] for c in combo: formula = list(filter(None,amb[c])) #Remove None entries introduced by dataframe queries.append(set(formula)) if len(queries) == 1: #if there is only one query find the unique elements in it q_set = frozenset(queries[0]) #qset is a frozen set, so it will not be mutated by changes to queries[0] for f_list in formula_lists: #cycle all formula in formula_lists set_f = frozenset(f_list) #convert f_list to sets, must be frozen so type matches q_set if set_f == q_set: # ignore the set that corresponds to the query pass else: queries[0] = queries[0] - set_f #delete any repeated elements in fset intersections[combo] = queries[0] elif len(queries) > 1: if exclusive == True: q_intersect = intersect(queries) intersections[combo] = q_intersect - assigned_formula #remove any elements from q_intersect that have already been assigned assigned_formula.update(q_intersect) #update the assigned_set with q_intersect else: intersections[combo] = intersect(queries) return intersections def intersect(samples,counter=0): """ This command uses recursion to find the intersections between a variable number of sets given in samples. Where samples = [set_1,set_2,...,set_n] """ if len(samples) == 1: return samples[0] a = samples[counter] b = samples[counter+1::] if len(b) == 1: #check to see whether the recursion has reached the final element return a & b[0] else: counter += 1 return a & intersect(samples,counter)

46.376623

143

0.633436

071ee3300e784ba72ea76c1cd34d240a111eb588

5,386

py

Python

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

Create Playlist.py

j4ck64/PlaylistDirectories

4a7caf0923620a84aea9bb91e643011e7ee118db

[ "MIT" ]

null

import os import glob import shutil from tinytag import TinyTag """ root = 'C:/' copy_to = '/copy to/folder' tag = TinyTag.get('C:/Users/jchap/OneDrive/Pictures/(VERYRAREBOYZ) (feat. $ki Mask The Slump God and Drugz).mp3') print(tag.artist) print('song duration: '+str(tag.duration)) """ f = [] f=glob.glob('C:/Users/jchap/OneDrive/*.mp3') print(f) musicDirectory=[] musicFiles =[] # tag = TinyTag.get(f[0]) # print(tag.artist) # for root, dirs, files in os.walk("C:/Users/jchap/OneDrive/"): for root, dirs, files in os.walk("C:/"): for file in files: if file.endswith(".mp3"): musicFiles.append(file) musicDirectory.append(os.path.join(root, file)) #print(os.path.join(root, file)) print('files'+str(musicFiles)) tag = TinyTag.get(musicDirectory[0]) print('Artist',tag.artist) print('Album Artist',tag.albumartist) print('Title',tag.title) print('Biterate',tag.bitrate) print('music directory'+str(musicDirectory)) print(len(musicDirectory)) currentDirectory =os.path.dirname(__file__) with open(currentDirectory+'/The_Krabby_Patty Formula_.m3u', "r") as f: content_list = [word.strip() for word in f] """ my_file = open(currentDirectory+'/The_Krabby_Patty Formula_.m3u', "r") content_list = my_file. readlines() """ # print('playlist contents') # print(content_list) musicDirectory musicWithoutDuplicates = [] duplicatesList = [] count =0 # check for tags equal to none #musicDirectory =[x for x in musicDirectory j = TinyTag.get(x) if x != 'wdg'] #remove tracks without albumn artist or title for track in reversed(range(len(musicDirectory))): try: trackTag = TinyTag.get(musicDirectory[track]) if str(trackTag.albumartist)== 'None' or str(trackTag.title)=='None': print('albumArtist = none',musicDirectory[track]) print('removing track and adding to log file') musicDirectory.remove(musicDirectory[track]) except IndexError: break #check for duplicates for j in range(len(musicDirectory)): musicDtag = TinyTag.get(musicDirectory[j]) duplicateL=[] duplicateLBiterate=[] for duplicate in range(len(musicDirectory)): duplicateTag = TinyTag.get(musicDirectory[duplicate]) musicWithoutDuplicates.append(musicDirectory[j]) if duplicateTag.albumartist == musicDtag.albumartist or duplicateTag.albumartist in musicDtag.albumartist: if duplicateTag.title == musicDtag.title or duplicateTag.title in musicDtag.title : #check if last iteration if duplicate>=len(musicDirectory)-1: print("found a duplicate!",musicDirectory[duplicate],duplicateTag.albumartist,duplicateTag.title) if len(duplicateLBiterate)==1:## did something here may need to change the conditional statement or add another print('biterate') #[x for x in duplicateL if TinyTag.get(musicDirectory[x]).bitrate > musicDirectory[x]] print("Current duplicate Bite rate", duplicateLBiterate) for x in range(len(duplicateL)): if TinyTag.get(duplicateL[x]).bitrate == max(duplicateLBiterate): #REMOVE ONE WITH THE BEST BITERATE duplicateL.remove(duplicateL[x]) print('duplicate list',duplicateL) #Add duplicatesList = duplicatesList + duplicateL else: print("found a duplicate!",musicDirectory[duplicate],duplicateTag.albumartist,duplicateTag.title) duplicateL.append(musicDirectory[duplicate]) duplicateLBiterate.append(duplicateTag.bitrate) print('dup ',duplicatesList) #remove duplicates from list for u in range(len(duplicatesList)): for i in range(len(musicDirectory)): if duplicatesList[u]==musicDirectory[i]: musicDirectory.remove(musicDirectory[i]) print('music ',musicDirectory) #create playlist newPlaylist = open("Test.m3u", "w") #add file path to the respective track in the new playlist for content in enumerate(content_list): # split strings into artist and title trackNumber=content[0] trackArray =str(content[1]).split('-') albumArtist= trackArray[0].strip() title=trackArray[1].strip() print('title:',title) print('albumArtist:',albumArtist) for trackDirectory in range(len(musicDirectory)): trackTag = TinyTag.get(musicDirectory[trackDirectory]) if trackTag.albumartist == albumArtist or trackTag.albumartist in albumArtist: if trackTag.title == title or trackTag.title in title: newPlaylist.write(trackDirectory + " " + content) newPlaylist.close() try: while True: content.next() except StopIteration: pass break else: print() else: print()

35.668874

133

0.604716

071fd543532fedf42da52e8b37bdf2f56e668e0e

1,636

py

Python

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

PyBank/main.py

Alexis-Kepano/python_challenge

2d86e0d891c549d5fba99bd48d612be80746e34b

[ "ADSL" ]

null

#import modules import os import csv #input csvpath = os.path.join('Resources', 'budget_data.csv') #output outfile = os.path.join('Analysis', 'pybankstatements.txt') #declare variables months = []; total_m = 1; net_total = 0; total_change = 0; monthly_changes = []; greatest_inc = ['', 0]; greatest_dec = ['', 0] #open & read csv with open(csvpath) as csvfile: csvreader = csv.reader(csvfile, delimiter=',') header = next(csvreader) first_row = next(csvreader) previous_row = int(first_row[1]) net_total = int(first_row[1]) #loop for row in csvreader: net_total += int(row[1]) total_m = total_m+1 current_value = int(row[1]) change_value = int(current_value-previous_row) monthly_changes.append(change_value) months.append(row[0]) previous_row = int(row[1]) total_change = total_change + change_value if change_value > greatest_inc[1]: greatest_inc[0] = str(row[0]) greatest_inc[1] = change_value if change_value < greatest_dec[1]: greatest_dec[0] = str(row[0]) greatest_dec[1] = change_value avg_change = total_change/len(months) output = ( f"\n Financial Analysis \n" f"------------------------------\n" f"Total Months: {total_m}\n" f"Total: ${net_total}\n" f"Average Change: ${avg_change:.2f}\n" f"Greatest Increase in Profits: {greatest_inc[0]} (${greatest_inc[1]})\n" f"Greatest Decrease in Profits: {greatest_dec[0]} (${greatest_dec[1]})\n") with open(outfile, "w") as txt_file: txt_file.write(output) outfile

28.206897

127

0.621027

072012e3a0677e91ae06d829a2d1c70bfa487fe4

1,502

py

Python

bot/constants/messages.py

aasw0ng/thornode-telegram-bot

5f73b882381548f45fc9e690c6e4845def9600b7

[ "MIT" ]

15

2020-04-21T07:51:26.000Z

2021-11-02T05:45:48.000Z

bot/constants/messages.py

aasw0ng/thornode-telegram-bot

5f73b882381548f45fc9e690c6e4845def9600b7

[ "MIT" ]

78

2020-04-13T23:01:16.000Z

2021-05-09T11:46:25.000Z

bot/constants/messages.py

aasw0ng/thornode-telegram-bot

5f73b882381548f45fc9e690c6e4845def9600b7

[ "MIT" ]

5

2020-09-03T21:19:16.000Z

2021-11-20T00:17:56.000Z

from enum import Enum from constants.globals import HEALTH_EMOJIS NETWORK_ERROR = ' There was an error while getting data \nAn API endpoint is down!' HEALTH_LEGEND = f'\n*Node health*:\n{HEALTH_EMOJIS[True]} - *healthy*\n{HEALTH_EMOJIS[False]} - *unhealthy*\n' \ f'{HEALTH_EMOJIS[None]} - *unknown*\n' NETWORK_HEALTHY_AGAIN = "The network is safe and efficient again! "

35.761905

112

0.631158

07201c5460a410eeac1f4cdd74f83fabb16f4ba2

3,993

py

Python

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

src/interactive_conditional_samples.py

RanHerOver/cometaai

02d459da5bbc58536112cfe6343f5ceef4ff2356

[ "MIT" ]

null

import random import fire import json import os import numpy as np import tensorflow as tf import pytumblr import mysql.connector import datetime from random import seed import model, sample, encoder if __name__ == '__main__': fire.Fire(interact_model())

30.953488

143

0.599048

0720bde47f5a6d668b162186b490b208d369a3a2

233

py

Python

desktop/core/ext-py/pyasn1-0.1.8/pyasn1/compat/iterfunc.py

kokosing/hue

2307f5379a35aae9be871e836432e6f45138b3d9

[ "Apache-2.0" ]

422

2015-01-08T14:08:08.000Z

2022-02-07T11:47:37.000Z

desktop/core/ext-py/pyasn1-0.1.8/pyasn1/compat/iterfunc.py

zks888/hue

93a8c370713e70b216c428caa2f75185ef809deb

[ "Apache-2.0" ]

581

2015-01-01T08:07:16.000Z

2022-02-23T11:44:37.000Z

desktop/core/ext-py/pyasn1-0.1.8/pyasn1/compat/iterfunc.py

zks888/hue

93a8c370713e70b216c428caa2f75185ef809deb

[ "Apache-2.0" ]

115

2015-01-08T14:41:00.000Z

2022-02-13T12:31:17.000Z

from sys import version_info if version_info[0] <= 2 and version_info[1] <= 4: else: all = all

21.181818

49

0.579399

072173681d53ec2482387460364698d940573600

3,839

py

Python

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

6

2021-01-26T17:22:53.000Z

2022-02-15T10:09:03.000Z

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

5

2020-12-24T14:29:23.000Z

2021-08-10T10:32:18.000Z

src/cms/carousels/serializers.py

UniversitaDellaCalabria/uniCMS

b0af4e1a767867f0a9b3c135a5c84587e713cb71

[ "Apache-2.0" ]

2

2020-12-24T14:13:39.000Z

2020-12-30T16:48:52.000Z

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

35.546296

117

0.657202

072216b7c95085e52120d7afc6bcf448dd8b5843

7,298

py

Python

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

demos/colorization_demo/python/colorization_demo.py

mzegla/open_model_zoo

092576b4c598c1e301ebc38ad74b323972e54f3e

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 """ Copyright (c) 2018-2021 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by 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. """ from openvino.runtime import Core, get_version import cv2 as cv import numpy as np import logging as log from time import perf_counter import sys from argparse import ArgumentParser, SUPPRESS from pathlib import Path sys.path.append(str(Path(__file__).resolve().parents[2] / 'common/python')) sys.path.append(str(Path(__file__).resolve().parents[2] / 'common/python/openvino/model_zoo')) import monitors from images_capture import open_images_capture from model_api.performance_metrics import PerformanceMetrics log.basicConfig(format='[ %(levelname)s ] %(message)s', level=log.DEBUG, stream=sys.stdout) if __name__ == "__main__": args = build_arg().parse_args() sys.exit(main(args) or 0)

43.183432

109

0.639216

07223524f59210dbb5356506e6de9ffb41f47883

8,174

py

Python

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

swagger_client/models/transfer.py

chbndrhnns/ahoi-client

8bd25f541c05af17c82904fa250272514b7971f2

[ "MIT" ]

null

# coding: utf-8 """ [AHOI cookbook](/ahoi/docs/cookbook/index.html) [Data Privacy](/sandboxmanager/#/privacy) [Terms of Service](/sandboxmanager/#/terms) [Imprint](https://sparkassen-hub.com/impressum/) © 2016&dash;2017 Starfinanz - Ein Unternehmen der Finanz Informatik # noqa: E501 OpenAPI spec version: 2.1.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six from swagger_client.models.amount import Amount # noqa: F401,E501 def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, Transfer): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

28.186207

277

0.565207

07224ff81e97b5ee51932d0d9bca20ab01f96757

10,366

py

Python

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

1

2020-11-30T16:14:02.000Z

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

null

external/trappy/tests/test_caching.py

vdonnefort/lisa

38e5f246e6c94201a60a8698e7f29277f11c425e

[ "Apache-2.0" ]

null

# Copyright 2015-2017 ARM Limited, Google and contributors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by 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. # from __future__ import unicode_literals from __future__ import division from __future__ import print_function from builtins import chr import os import json import shutil import sys import unittest import utils_tests import trappy from trappy.ftrace import GenericFTrace from trappy.systrace import SysTrace

38.535316

88

0.644125

07229c65c61816346ca75d9d08af09c5eb62b6ff

6,813

py

Python

src/mf_horizon_client/client/pipelines/blueprints.py

MF-HORIZON/mf-horizon-python-client

67a4a094767cb8e5f01956f20f5ca7726781614a

[ "MIT" ]

null

src/mf_horizon_client/client/pipelines/blueprints.py

MF-HORIZON/mf-horizon-python-client

67a4a094767cb8e5f01956f20f5ca7726781614a

[ "MIT" ]

null

src/mf_horizon_client/client/pipelines/blueprints.py

MF-HORIZON/mf-horizon-python-client

67a4a094767cb8e5f01956f20f5ca7726781614a

[ "MIT" ]

null

from enum import Enum

39.842105

122

0.57405

0723f800260b47fe29201f275a3497c9e0250212

6,758

py

Python

pyChess/olaf/views.py

An-Alone-Cow/pyChess

2729a3a89e4d7d79659488ecb1b0bff9cac281a3

[ "MIT" ]

null

pyChess/olaf/views.py

An-Alone-Cow/pyChess

2729a3a89e4d7d79659488ecb1b0bff9cac281a3

[ "MIT" ]

18

2017-02-05T17:52:41.000Z

2017-02-16T09:04:39.000Z

pyChess/olaf/views.py

An-Alone-Cow/pyChess

2729a3a89e4d7d79659488ecb1b0bff9cac281a3

[ "MIT" ]

null

from django.contrib.auth.decorators import login_required from django.contrib.auth.models import User from django.shortcuts import render from django.urls import reverse from django.http import HttpResponseRedirect, HttpResponse from django.utils import timezone from olaf.models import * from olaf.forms import * from olaf.utility import usertools from olaf.chess.controller import proccess_move form_operation_dict = { 'login' : ( usertools.login_user, LoginForm, 'olaf/login.html', {}, 'index', { 'message' : "You're logged in. :)"} ), 'register' : ( usertools.register_user, RegisterForm, 'olaf/register.html', {}, 'index', { 'message' : "An activation email has been sent to you" } ), 'password_reset_request' : ( usertools.init_pass_reset_token, ForgotPasswordUsernameOrEmailForm, 'olaf/password_reset_request.html', {}, 'index', { 'message' : "An email containing the password reset link will be sent to your email"} ), 'reset_password' : ( usertools.reset_password_action, PasswordChangeForm, 'olaf/reset_password.html', {}, 'olaf:login', { 'message' : "Password successfully changed, you can login now" } ), 'resend_activation_email' : ( usertools.resend_activation_email, ResendActivationUsernameOrEmailForm, 'olaf/resend_activation_email.html', {}, 'index', { 'message' : "Activation email successfully sent to your email" } ), } #view functions

31.877358

175

0.683042

072578f31e8482a3127fc3b417aa642b8388a425

2,343

py

Python

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

6

2021-02-02T23:00:02.000Z

2022-01-13T03:13:51.000Z

ce_vae_test/main_cetrainer.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

from __future__ import print_function import argparse import torch import torch.utils.data import matplotlib.pyplot as plt from torch import nn, optim from torch.nn import functional as F from torchvision import datasets, transforms from torchvision.utils import save_image from torch.utils.tensorboard import SummaryWriter from ce_vae_test.networks.min_vae import MinVae from ce_vae_test.trainer.ce_trainer import CeVaeTrainer from ce_vae_test.sampler.dataset_sampler import SamplerDatasetWithReplacement parser = argparse.ArgumentParser(description='VAE MNIST Example') parser.add_argument('--batch-size', type=int, default=128, metavar='N', help='input batch size for training (default: 128)') parser.add_argument('--epochs', type=int, default=10, metavar='N', help='number of epochs to train (default: 10)') parser.add_argument('--no-cuda', action='store_true', default=False, help='enables CUDA training') parser.add_argument('--seed', type=int, default=1, metavar='S', help='random seed (default: 1)') parser.add_argument('--log-interval', type=int, default=10, metavar='N', help='how many batches to wait before logging training status') args = parser.parse_args() args.cuda = not args.no_cuda and torch.cuda.is_available() torch.manual_seed(args.seed) device = torch.device("cuda" if args.cuda else "cpu") writer = SummaryWriter() kwargs = {'num_workers': 1, 'pin_memory': True} if args.cuda else {} train_sampler = SamplerDatasetWithReplacement( dataset=datasets.MNIST('../data', train=True, download=True, transform=transforms.ToTensor()), batch_size=args.batch_size ) test_sampler = SamplerDatasetWithReplacement( dataset=datasets.MNIST('../data', train=False, transform=transforms.ToTensor()), batch_size=args.batch_size * 10 ) cevae = MinVae( input_size=28 * 28, output_size=10, latent_dim=2, hidden_sizes_dec=[5], device=device ).to(device) trainer = CeVaeTrainer( vae=cevae, num_epochs=300, train_loader=train_sampler, test_loader=test_sampler, writer=writer, device=device, alpha=0.90, lamda=0.22 ) trainer.run()

32.09589

83

0.681605

07257aac63bf6240cc82f0f082448d6a6953f3dc

1,567

py

Python

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

31

2017-07-05T07:25:31.000Z

2021-01-18T22:21:57.000Z

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

48

2017-06-27T15:48:29.000Z

2021-01-26T21:02:27.000Z

appr/commands/logout.py

sergeyberezansky/appr

03168addf05c3efd779dad5168fb0a80d0512100

[ "Apache-2.0" ]

17

2017-07-05T07:25:38.000Z

2021-01-20T14:52:29.000Z

from __future__ import absolute_import, division, print_function from appr.auth import ApprAuth from appr.commands.command_base import CommandBase, PackageSplit

36.44186

94

0.640077

072580ae43bbd8ecd21160183d85274cfcb19e54

87

py

Python

musica/apps.py

webnowone/albumMusical

b9532ff0ef47b610f0f2b565f0dd77e54d638772

[ "Apache-2.0" ]

1

2021-02-02T03:58:48.000Z

musica/apps.py

webnowone/albumMusical

b9532ff0ef47b610f0f2b565f0dd77e54d638772

[ "Apache-2.0" ]

52

2020-02-25T09:56:54.000Z

2021-09-22T18:40:50.000Z

musica/apps.py

webnowone/albumMusical

b9532ff0ef47b610f0f2b565f0dd77e54d638772

[ "Apache-2.0" ]

null

from django.apps import AppConfig

14.5

33

0.747126

072775cafe9ec9921c429b5df6eb75f74e95605d

10,370

py

Python

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

115

2015-01-09T06:18:19.000Z

2021-12-28T07:07:45.000Z

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

47

2015-04-15T20:23:44.000Z

2022-03-22T11:25:01.000Z

tzwhere/tzwhere.py

tuxiqae/pytzwhere

32d2bef9ff2d784741471fddb35fbb6732f556d5

[ "MIT" ]

46

2015-01-26T16:42:10.000Z

2022-01-04T15:26:57.000Z

#!/usr/bin/env python '''tzwhere.py - time zone computation from latitude/longitude. Ordinarily this is loaded as a module and instances of the tzwhere class are instantiated and queried directly ''' import collections try: import ujson as json # loads 2 seconds faster than normal json except: try: import json except ImportError: import simplejson as json import math import gzip import os import shapely.geometry as geometry import shapely.prepared as prepared # We can save about 222MB of RAM by turning our polygon lists into # numpy arrays rather than tuples, if numpy is installed. try: import numpy WRAP = numpy.asarray COLLECTION_TYPE = numpy.ndarray except ImportError: WRAP = tuple COLLECTION_TYPE = tuple # for navigation and pulling values/files this_dir, this_filename = os.path.split(__file__) BASE_DIR = os.path.dirname(this_dir) def read_tzworld(path): reader = read_json return reader(path) def read_json(path): with gzip.open(path, "rb") as f: featureCollection = json.loads(f.read().decode("utf-8")) return featureCollection def feature_collection_polygons(featureCollection): """Turn a feature collection into an iterator over polygons. Given a featureCollection of the kind loaded from the json input, unpack it to an iterator which produces a series of (tzname, polygon) pairs, one for every polygon in the featureCollection. Here tzname is a string and polygon is a list of floats. """ for feature in featureCollection['features']: tzname = feature['properties']['TZID'] if feature['geometry']['type'] == 'Polygon': exterior = feature['geometry']['coordinates'][0] interior = feature['geometry']['coordinates'][1:] yield (tzname, (exterior, interior)) if __name__ == "__main__": prepareMap()

39.884615

130

0.610993

07283cf3af01e90d346a6f3a53d9608574682da0

706

py

Python

tests/home_assistant/custom_features.py

jre21/mindmeld

6a88e4b0dfc7971f6bf9ae406b89dbc76f68af81

[ "Apache-2.0" ]

1

2021-01-06T23:39:57.000Z

tests/home_assistant/custom_features.py

jre21/mindmeld

6a88e4b0dfc7971f6bf9ae406b89dbc76f68af81

[ "Apache-2.0" ]

1

2021-02-02T22:53:01.000Z

tests/home_assistant/custom_features.py

jre21/mindmeld

6a88e4b0dfc7971f6bf9ae406b89dbc76f68af81

[ "Apache-2.0" ]

null

from mindmeld.models.helpers import register_query_feature

35.3

89

0.729462

072aa22d56a355822d78b2d3df97e983fe4fb836

4,783

py

Python

source/statuscodes.py

woody2371/fishbowl-api

f34ff9267436b1278985870fbf19863febdb391b

[ "MIT" ]

6

2016-04-26T01:24:21.000Z

2021-05-13T07:48:15.000Z

source/statuscodes.py

USDev01/fishbowl-api

4d47e20d3385d5ebc001feec44aad321467a6d92

[ "MIT" ]

3

2015-10-29T21:34:39.000Z

2021-11-08T15:22:30.000Z

source/statuscodes.py

USDev01/fishbowl-api

4d47e20d3385d5ebc001feec44aad321467a6d92

[ "MIT" ]

12

2015-02-20T08:21:05.000Z

2021-11-06T22:27:04.000Z

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

37.367188

177

0.572653

072b5dc94ce99e8f35df268838491f8bfa5d061f

239

py

Python

app/src/server/hoge/hoge_api.py

jacob327/docker-flask-nginx-uwsgi-mysql

4b0731f746d6fda7bfecd082ddef53a9c5ec8f75

[ "MIT" ]

null

app/src/server/hoge/hoge_api.py

jacob327/docker-flask-nginx-uwsgi-mysql

4b0731f746d6fda7bfecd082ddef53a9c5ec8f75

[ "MIT" ]

null

app/src/server/hoge/hoge_api.py

jacob327/docker-flask-nginx-uwsgi-mysql

4b0731f746d6fda7bfecd082ddef53a9c5ec8f75

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- # [Import start] from flask import Blueprint, jsonify # [Import end] app = Blueprint( 'hoge', __name__, url_prefix='/hoge' )

13.277778

36

0.606695

072b648fd224e151f6b9509016ac18b01f0c89c9

2,383

py

Python

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

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

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

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

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

chipbuster/Energy-Languages-Setup

5b6192e1cc73f701a2310ac72520ed540d86c1ae

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 import apt_pkg import sys from apt_pkg import CURSTATE_INSTALLED, version_compare from operator import lt, le, eq, ge, gt # Function mappings for relationship operators. relation_operators = {"<<": lt, "<=": le, "=": eq, ">=": ge, ">>": gt} # Set up APT cache. apt_pkg.init() cache = apt_pkg.Cache(None) missing_packages = [] for i in sys.argv[1:]: # Build the package relationship string for use by 'apt-get satisfy'. relationship_operator = None for j in ["<=", ">=", "<", ">", "="]: if j in i: relationship_operator = j break if relationship_operator is not None: if relationship_operator in ["<", ">"]: relationship_operator_formatted = j + j else: relationship_operator_formatted = j package = i.split(relationship_operator) pkgname = package[0] pkgver = package[1] package_string = f"{pkgname} ({relationship_operator_formatted} {pkgver})" else: pkgname = i pkgver = None package_string = pkgname # Check if the package is in the cache. try: pkg = cache[pkgname] except KeyError: missing_packages += [package_string] continue # Get the list of installed and provided packages that are currently installed. installed_pkg_versions = [] if pkg.current_state == CURSTATE_INSTALLED: installed_pkg_versions += [pkg] for i in pkg.provides_list: parent_pkg = i[2].parent_pkg if parent_pkg.current_state == CURSTATE_INSTALLED: installed_pkg_versions += [parent_pkg] # If an installed package was found and no relationship operators were used, the dependency has been satisfied. if (len(installed_pkg_versions) != 0) and (relationship_operator is None): continue # Otherwise, check all matching installed packages and see if any of them fit the specified relationship operator. matched_pkg = False for i in installed_pkg_versions: installed_version = i.current_ver.ver_str version_result = version_compare(installed_version, pkgver) if relation_operators[relationship_operator_formatted](version_result, 0): matched_pkg = True if not matched_pkg: missing_packages += [package_string] for i in missing_packages: print(i) exit(0)

29.419753

118

0.661771

072bd117dea823ba3412148c4dbda51e774d2a1f

11,707

py

Python

cohorts_proj/datasets/migrations/0009_auto_20200824_0617.py

zferic/harmonization-website

f6a081481df3a3a62cb075fbb63ad0470b0d4e06

[ "MIT" ]

1

2020-09-20T02:32:01.000Z

cohorts_proj/datasets/migrations/0009_auto_20200824_0617.py

zferic/harmonization-website

f6a081481df3a3a62cb075fbb63ad0470b0d4e06

[ "MIT" ]

20

2020-04-17T14:01:41.000Z

2022-03-12T00:30:23.000Z

cohorts_proj/datasets/migrations/0009_auto_20200824_0617.py

zferic/harmonization-website

f6a081481df3a3a62cb075fbb63ad0470b0d4e06

[ "MIT" ]

3

2020-10-08T00:24:51.000Z

2021-06-02T20:07:30.000Z

# Generated by Django 3.0.7 on 2020-08-24 06:17 from django.db import migrations, models

33.353276

154

0.522337

072ca26b4d1e4960c6363441b38a038bbb510a99

107

py

Python

test_hello.py

skvel/pynet_testx

46566e059e076cb763f8a10ed7f6ff9eac5b63b1

[ "Apache-2.0" ]

null

test_hello.py

skvel/pynet_testx

46566e059e076cb763f8a10ed7f6ff9eac5b63b1

[ "Apache-2.0" ]

null

test_hello.py

skvel/pynet_testx

46566e059e076cb763f8a10ed7f6ff9eac5b63b1

[ "Apache-2.0" ]

null

print "Hello World!" print "Trying my hand at Git!" print "Something else" for i in range(10): print i

17.833333

30

0.691589

072cc767332977c77810de1909be8f9a35cce2f6

3,784

py

Python

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

null

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

1

2020-09-08T11:10:53.000Z

tasks/views.py

TheDim0n/ProjectManager

50d36e7e3fc71655aa5a82bb19eacc07172ba5e4

[ "MIT" ]

null

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

31.798319

79

0.636628

072d2f9675748ff1a2131801c4afa2c1d8506223

2,083

py

Python

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

smoke/noaa/get_smokeplume_counts.py

minnieteng/smoke_project

cc3c8f16f7759fe29e46d3cec32a3ed6ca86bd5f

[ "Apache-2.0" ]

null

import os import math import time import geohash import geojson from geojson import MultiLineString from shapely import geometry import shapefile import numpy import datetime as dt import pandas as pd import logging logger = logging.getLogger(__name__) source_shape_file_path = "C:/temp/2018/" threshold = 60*60 cols = ['start', 'end','start_epoch_round','end_epoch_round','start_epoch_round_dt','end_epoch_round_dt'] times = [] for root,dirs,files in os.walk(source_shape_file_path): for file in files: with open(os.path.join(root,file),"r") as auto: if file.endswith(".shp"): try: filename = file.replace(".shp","") shape=shapefile.Reader(source_shape_file_path+filename+"/"+file) for r in shape.iterRecords(): start_time = dt.datetime.strptime(r[1], '%Y%j %H%M') end_time = dt.datetime.strptime(r[2], '%Y%j %H%M') epoch_s = dt.datetime.timestamp(dt.datetime.strptime(r[1], '%Y%j %H%M')) epoch_e = dt.datetime.timestamp(dt.datetime.strptime(r[2], '%Y%j %H%M')) # sometimes start is later than end time, we'll assume the earlier time is start epoch_end_round = round(max(epoch_s,epoch_e) / threshold) * threshold epoch_start_round = round(min(epoch_s,epoch_e) / threshold) * threshold epoch_end_round_dt = dt.datetime.utcfromtimestamp(3600 * ((max(epoch_s,epoch_e) + 1800) // 3600)) epoch_start_round_dt = dt.datetime.utcfromtimestamp(3600 * ((min(epoch_s,epoch_e) + 1800) // 3600)) times.append([start_time,end_time,epoch_start_round,epoch_end_round,epoch_start_round_dt,epoch_end_round_dt]) break except: logger.error('failed to parse file:'+source_shape_file_path+filename+"/") continue df = pd.DataFrame(times, columns=cols) df.to_csv('noaa_times.csv')

45.282609

133

0.610178