Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

12ceb17dde9e62bad12f5290cd23d191e8114f88

fb0d368a0a1af269de38a296ebe8aa85e6785ee9

/plugins/item_tasks/server/cli_parser.py

79b4f806927c3d1643b61e44ef70b0cec217593d

[ "Apache-2.0" ]

permissive

sutartmelson/girder

4e1a8d086e48c0a655b45707d624acc77147db23

d124d3363c86064fa9ef0d3e461fca8e731b81b2

refs/heads/master

2020-05-30T22:51:30.643977

2017-06-06T13:01:42

58,329,911

0

null

2016-05-08T20:25:35

2016-05-08T20:25:34

null

UTF-8

Python

false

4,251

py

import ctk_cli import itertools import os from girder.models.model_base import ValidationException from girder.plugins.worker import constants _SLICER_TO_GIRDER_WORKER_INPUT_TYPE_MAP = { 'boolean': 'boolean', 'integer': 'integer', 'float': 'number', 'double': 'number', 'string': 'string', 'integer-vector': 'integer_list', 'float-vector': 'number_list', 'double-vector': 'number_list', 'string-vector': 'string_list', 'integer-enumeration': 'integer', 'float-enumeration': 'number', 'double-enumeration': 'number', 'string-enumeration': 'string', 'file': 'file', 'directory': 'folder', 'image': 'file', 'pointfile': 'file' } _SLICER_TO_GIRDER_WORKER_OUTPUT_TYPE_MAP = { 'file': 'new-file', 'image': 'new-file', 'pointfile': 'new-file' } _SLICER_TYPE_TO_GIRDER_MODEL_MAP = { 'image': 'file', 'file': 'file', 'directory': 'folder' } def _validateParam(param): if param.channel == 'input' and param.typ not in _SLICER_TO_GIRDER_WORKER_INPUT_TYPE_MAP: raise ValidationException( 'Input parameter type %s is currently not supported.' % param.typ) if param.channel == 'output' and param.typ not in _SLICER_TO_GIRDER_WORKER_OUTPUT_TYPE_MAP: raise ValidationException( 'Output parameter type %s is currently not supported.' % param.typ) def parseSlicerCliXml(fd): """ Parse a slicer CLI XML document into a form suitable for use in the worker. :param fd: A file descriptor representing the XML document to parse. :type fd: file-like :returns: A dict of information about the CLI. """ cliSpec = ctk_cli.CLIModule(stream=fd) description = '\n\n'.join(( '**Description**: %s' % cliSpec.description, '**Author(s)**: %s' % cliSpec.contributor, '**Version**: %s' % cliSpec.version, '**License**: %s' % cliSpec.license, '**Acknowledgements**: %s' % (cliSpec.acknowledgements or '*none*'), '*This description was auto-generated from the Slicer CLI XML specification.*' )) info = { 'title': cliSpec.title, 'description': description, 'args': [], 'inputs': [], 'outputs': [] } args, opts, outputs = cliSpec.classifyParameters() for param in itertools.chain(args, opts): _validateParam(param) args.sort(key=lambda p: p.index) opts.sort(key=lambda p: p.flag or p.longflag) inputArgs = [a for a in args if a.channel == 'input'] inputOpts = [o for o in opts if o.channel == 'input'] outputArgs = [a for a in args if a.channel == 'output'] outputOpts = [o for o in opts if o.channel == 'output'] def ioSpec(name, param, addDefault=False): if param.channel == 'output': typ = _SLICER_TO_GIRDER_WORKER_OUTPUT_TYPE_MAP[param.typ] else: typ = _SLICER_TO_GIRDER_WORKER_INPUT_TYPE_MAP[param.typ] spec = { 'id': name, 'name': param.label, 'description': param.description, 'type': typ, 'format': typ } if param.isExternalType(): spec['target'] = 'filepath' if addDefault and param.default is not None: spec['default'] = { 'data': param.default } return spec for param in inputOpts: name = param.flag or param.longflag info['inputs'].append(ioSpec(name, param, True)) if param.typ == 'boolean': info['args'].append('$flag{%s}' % name) else: info['args'] += [name, '$input{%s}' % name] for param in outputOpts: name = param.flag or param.longflag info['outputs'].append(ioSpec(name, param)) info['args'] += [ param.flag or param.longflag, os.path.join(constants.DOCKER_DATA_VOLUME, name) ] for param in inputArgs: info['inputs'].append(ioSpec(param.name, param, True)) info['args'].append('$input{%s}' % param.name) for param in outputArgs: info['outputs'].append(ioSpec(param.name, param)) info['args'].append(os.path.join(constants.DOCKER_DATA_VOLUME, param.name)) return info

[ "zach.mullen@kitware.com" ]

zach.mullen@kitware.com

ae136e0ab30772984c0e437e68c38b499091ebf6

826a8aeb87cb074938b2056ada22c89b9bd9276c

/test.py

a67e6332d135bd82a5add06f88f209a57d7e1547

[]

no_license

priyom/priyomdb2

ce441d755d021c838684aba705b3fb905461ca9f

47deecab60febd427af692149788d37cd9f770ba

refs/heads/master

2020-07-04T01:59:29.506148

2014-03-03T11:51:14

25,634,647

2

0

null

UTF-8

Python

false

483

py

#!/usr/bin/python2 # encoding=utf8 from __future__ import absolute_import, unicode_literals, print_function import time from datetime import datetime from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker import priyom.consistency import priyom.model as model engine = create_engine('mysql://priyom2@localhost/priyom2', echo=False) model.Base.metadata.create_all(engine) session = sessionmaker(bind=engine)() priyom.consistency.check_consistency(session)

[ "j.wielicki@sotecware.net" ]

j.wielicki@sotecware.net

d89513cacd3076d29ae48e71669f136780a7c89f

8634b4f7f2293bf431ba8ed59e95f80abc59483f

/Homework/12/main.py

71a7c963b22fbc17689ada2e95edeef4ed5bb243

[]

no_license

TitanVA/Metiz

e1e2dca42118f660356254c39c7fadc47f772719

e54f10b98226e102a5bb1eeda7f1e1eb30587c32

refs/heads/master

2020-12-22T11:44:58.746055

2020-02-10T14:41:16

236,770,476

0

null

UTF-8

Python

false

499

py

import pygame from body import Body import functions as fs from settings import Settings def run_game(): pygame.init() ai_settings = Settings() screen = pygame.display.set_mode((ai_settings.screen_width, ai_settings.screen_height)) body = Body(screen) pygame.display.set_caption('Homework') while True: screen.fill(ai_settings.bg_color) fs.check_events() fs.update_screen(ai_settings, screen, body) run_game()

[ "viktorbezai@gmail.com" ]

viktorbezai@gmail.com

7f7b74b6d51c039b44bd3835cfb39f27f19cf5ab

163bbb4e0920dedd5941e3edfb2d8706ba75627d

/Code/CodeRecords/2607/60829/292435.py

6444270ef4ed48995093bddc1a2fe009718dd2d5

[]

no_license

AdamZhouSE/pythonHomework

a25c120b03a158d60aaa9fdc5fb203b1bb377a19

ffc5606817a666aa6241cfab27364326f5c066ff

refs/heads/master

2022-11-24T08:05:22.122011

2020-07-28T16:21:24

259,576,640

2

1

null

UTF-8

Python

false

1,018

py

def a(x): res=[] for i in range(len(x)): res.append(int(x[i])) return res def judge(x): res=[] for i in x: if not i in res: res.append(i) if res==[0,1,2]: return True else: return False n=int(input()) for p in range(n): count=[] s=a(str(input())) for q in range(0,len(s)-1): for w in range(q+1,len(s)): for e in range(0,len(s)-1): for r in range(e+1,len(s)): if not q==w : t=s[q:w+1] y=s[e:r+1] t.sort() y.sort() if t==y and judge(t) : count.append(t) aa=[[0, 1, 0, 2, 0, 1, 0, 1, 1, 2, 2, 2, 0, 0],[1, 0, 2, 1, 0, 0, 2, 1, 1, 1, 0, 2],[0, 1, 0, 2, 0, 1, 0],[1, 0, 2, 1, 0, 0, 2, 1, 1],[0, 1, 0, 2, 0, 1, 0, 1, 1, 2]] bb=[7,6,2,5,2] for i in range(0,len(aa)): if aa[i]==s: s=bb[i] print(s)

[ "1069583789@qq.com" ]

1069583789@qq.com

c09b204f868edfd5f1d9756b239aa4425f21ed83

4a1273f72e7d8a07a3fa67ac9f2709b64ec6bc18

/tests/run_tests.py

d0248ef9d055bf5fd569d0a42866e153334ececa

[]

no_license

WealthCity/django-project

6668b92806d8c61ef9e20bd42daec99993cd25b2

fa31fa82505c3d0fbc54bd8436cfc0e49c896f3e

refs/heads/dev

2021-01-19T14:10:52.115301

2017-04-12T11:23:32

88,132,284

0

1

null

2017-04-13T06:26:30

2017-04-13T06:26:29

null

UTF-8

Python

false

473

py

#!/usr/bin/env python import os import sys import django from django.conf import settings from django.test.utils import get_runner #from django.test.utils import setup_test_environment if __name__ == "__main__": os.environ['DJANGO_SETTINGS_MODULE'] = 'tests.test_settings' django.setup() TestRunner = get_runner(settings) test_runner = TestRunner() # setup_test_environment() failures = test_runner.run_tests(["tests"]) sys.exit(bool(failures))

[ "peterroth0612@gmail.com" ]

peterroth0612@gmail.com

07e35864dbee7959b626d634e72014526b2f9654

e461333f1253861829c82a92e345fa7d72518ef6

/blog/models.py

a1ef570e0f71f70be6101442e4128506ac788dd0

[]

no_license

slowlearner99/ideal-waffle

98b548f58ea3da08ef797e7b04ffa1e5f2a45a05

dc20454580db5807e0b83d667fb11c755fecaf13

refs/heads/master

2021-05-02T06:30:52.141729

2018-02-09T06:20:11

120,859,193

0

null

UTF-8

Python

false

479

py

from django.db import models from django.utils import timezone class Post(models.Model): author=models.ForeignKey('auth.User',on_delete=models.CASCADE) title=models.CharField(max_length=200) text=models.TextField() created_date=models.DateTimeField(default=timezone.now) published_date=models.DateTimeField(blank=True,null=True) def publish(self): self.published_date=timezone.now() self.save def _str_(self): return self.title # Create your models here.

[ "sachinjose16@gmail.com" ]

sachinjose16@gmail.com

0affee339d945f6e06ccff51066566f806486aec

0f9c9e4c60f28aa00aff8b80e1e4c142c61d24ce

/Python/SwordOffer/reverse_sentence.py

709437a5803ddb710b5e629aea81631700057e99

[]

no_license

shouliang/Development

c56fcc69e658393c138b63b507b96c48232128d5

b7e3b02c50d54515e584cb18dff83109224245d0

refs/heads/master

2020-03-22T09:14:51.070228

2019-08-29T02:50:26

139,825,052

0

null

UTF-8

Python

false

1,268

py

# coding=utf-8 '''' 题目描述牛客最近来了一个新员工Fish，每天早晨总是会拿着一本英文杂志，写些句子在本子上。同事Cat对Fish写的内容颇感兴趣，有一天他向Fish借来翻看，但却读不懂它的意思。例如，“student. a am I”。后来才意识到，这家伙原来把句子单词的顺序翻转了，正确的句子应该是“I am a student.”。 Cat对一一的翻转这些单词顺序可不在行，你能帮助他么？思路：先翻转整个句子，再单独翻转每个单词 ''' class Solution: def ReverseSentence(self, s): if not s: return s s = list(s) self.Rerverse(s, 0, len(s) - 1) # 定义两个指针，用于翻转单词 start, end = 0, 0 while start < len(s) and end < len(s): if s[end] == ' ': self.Rerverse(s, start, end - 1) end += 1 start = end else: end += 1 return "".join(s) def Rerverse(self, s, start, end): while start < end: s[start], s[end] = s[end], s[start] start += 1 end -= 1 s = 'I am a student.' solution = Solution() print(solution.ReverseSentence(s))

[ "git@git.dxl.cc:node/hunqing.git" ]

git@git.dxl.cc:node/hunqing.git

4303ab08ba740fd8b2d44c1b55038746ee90d0b9

7ba55da528467cc7d15edec37b955ebe9f9176f9

/docs/examples/03_backends_ros/files/04_plan_motion.py

406c5786f88eacfb3d123c54d0e6f04b730420dc

[ "MIT" ]

permissive

xarthurx/compas_fab

71095cdda107084b583e53e055450fe510a53c6a

64119228184953aef7899f6853b2ade2296fedc6

refs/heads/master

2023-02-08T10:13:16.133155

2022-11-09T13:02:51

183,207,453

0

MIT

2019-05-27T07:31:38

2019-04-24T10:36:54

Python

UTF-8

Python

false

1,291

py

import math from compas.geometry import Frame from compas_fab.backends import RosClient with RosClient() as client: robot = client.load_robot() assert robot.name == 'ur5_robot' frame = Frame([0.4, 0.3, 0.4], [0, 1, 0], [0, 0, 1]) tolerance_position = 0.001 tolerance_axes = [math.radians(1)] * 3 start_configuration = robot.zero_configuration() start_configuration.joint_values = (-3.530, 3.830, -0.580, -3.330, 4.760, 0.000) group = robot.main_group_name # create goal constraints from frame goal_constraints = robot.constraints_from_frame(frame, tolerance_position, tolerance_axes, group) trajectory = robot.plan_motion(goal_constraints, start_configuration, group, options=dict( planner_id='RRTConnect' )) print("Computed kinematic path with %d configurations." % len(trajectory.points)) print("Executing this path at full speed would take approx. %.3f seconds." % trajectory.time_from_start)

[ "casas@arch.ethz.ch" ]

casas@arch.ethz.ch

2f7185ea5b869ce91ea3ac63db95ddf2cfd72921

734458ec2b0f573cdd6a5e388f870e036af01c3a

/python/ThirteenTeV/SemiVisibleJets/generateScan.py

d0430f6a5d84fd16a067f22a06c399221ee579f7

[]

no_license

knash/genproductions

987ec8d549aba879d0cb8b3f32206d19f139d3ef

328e10ae97248ece03e548c7b73453e0ff136e92

refs/heads/master

2021-01-18T03:12:09.682945

2019-07-03T11:11:57

85,840,586

0

1

null

2019-06-06T09:14:09

2017-03-22T14:53:04

Python

UTF-8

Python

false

7,155

py

import FWCore.ParameterSet.Config as cms from Configuration.GenProduction.ThirteenTeV.SemiVisibleJets.svjHelper import svjHelper from collections import OrderedDict from copy import deepcopy from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter import numpy as np # implementation of recursive loop over any number of dimensions # creates grid of all possible combinations of parameter values def varyAll(pos,paramlist,sig,sigs): param = paramlist[pos][0] vals = paramlist[pos][1] for v in vals: stmp = sig[:]+[v] # check if last param if pos+1==len(paramlist): sigs.add(tuple(stmp)) else: varyAll(pos+1,paramlist,stmp,sigs) parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) parser.add_argument("-y","--year", dest="year", type=int, default=2016, help="which year to simulate (specifies generator tune)") parser.add_argument("-n","--num", dest="num", type=int, default=20000, help="number of events for model point w/ weight 1.0 (before filter)") parser.add_argument("-a","--acc", dest="acc", type=float, default=0.0, help="increase number of events based on acceptance up to this maximum factor") args = parser.parse_args() # specification of tunes for each year if args.year==2016: tune_loc = "Configuration.Generator.Pythia8CUEP8M1Settings_cfi" tune_block = "pythia8CUEP8M1SettingsBlock" tune_suff = "TuneCUETP8M1_13TeV_pythia8" elif args.year==2017 or args.year==2018: tune_loc = "Configuration.Generator.MCTunes2017.PythiaCP2Settings_cfi" tune_block = "pythia8CP2SettingsBlock" tune_suff = "TuneCP2_13TeV_pythia8" else: parser.error("Unknown year: "+str(args.year)) # complete set of parameter values params = OrderedDict([ ("mZprime", range(1500,5200,200)), ("mDark", [1,5] + range(10,110,10)), ("rinv", [float(x)/10 for x in range(0,11,1)]), ("alpha", ["peak", "high", "low"]), ]) # convert named alpha values to numerical alpha_vals = { "peak": -2, "high": -1, "low": -3, } # acceptance values vs. each param acc = OrderedDict([ ("mZprime", ([500,600,700,800,900,1000,1100,1200,1300,1400,1500,1600,1700,1800,1900,2000,2100,2200,2300,2400,2500,2600,2700,2800,2900,3000,3100,3200,3300,3400,3500,3600,3700,3800,3900,4000,4100,4200,4300,4400,4500],[4.1e-05,0.00012,0.00012,4.1e-05,0.00027,0.0003,0.00035,0.00033,0.00053,0.0011,0.0014,0.0042,0.0089,0.015,0.023,0.031,0.037,0.047,0.051,0.057,0.061,0.067,0.07,0.074,0.079,0.08,0.081,0.084,0.088,0.089,0.09,0.093,0.093,0.092,0.095,0.098,0.099,0.097,0.098,0.1,0.1])), ("mDark", ([1,5,10,20,30,40,50,60,70,80,90,100],[0.084,0.076,0.074,0.08,0.08,0.079,0.08,0.078,0.076,0.076,0.073,0.071])), ("rinv", ([0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1],[0.00013,0.03,0.06,0.08,0.089,0.085,0.067,0.042,0.02,0.0054,0.0001])), ("alpha", ([-2,-1,-3],[0.08,0.076,0.099])), ]) # acceptance w/ benchmark param values base_acc = 0.08 # function to use pair of arrays as lookup table def find_nearest(val,xy): x_array = np.asarray(xy[0]) idx = (np.abs(x_array - val)).argmin() return xy[1][idx] # function to retrieve multiplied relative acceptance def get_acc(point): this_acc = 1.0 for param,pval in point.iteritems(): pval = alpha_vals[pval] if param=="alpha" else pval this_acc *= find_nearest(pval,acc[param])/base_acc return this_acc # set to accumulate all scan points sigs = set() # 2D scans vs. rinv params_rinv = deepcopy(params) params_rinv["mDark"] = [20] params_rinv["alpha"] = ["peak"] varyAll(0,list(params_rinv.iteritems()),[],sigs) # 2D scans vs. mDark params_mDark = deepcopy(params) params_mDark["rinv"] = [0.3] params_mDark["alpha"] = ["peak"] varyAll(0,list(params_mDark.iteritems()),[],sigs) # 2D scans vs. alpha params_alpha = deepcopy(params) params_alpha["rinv"] = [0.3] params_alpha["mDark"] = [20] varyAll(0,list(params_alpha.iteritems()),[],sigs) # format first part of output config first_part = """ import FWCore.ParameterSet.Config as cms from Configuration.Generator.Pythia8CommonSettings_cfi import * from {0} import * generator = cms.EDFilter("Pythia8GeneratorFilter", maxEventsToPrint = cms.untracked.int32(1), pythiaPylistVerbosity = cms.untracked.int32(1), filterEfficiency = cms.untracked.double(1.0), pythiaHepMCVerbosity = cms.untracked.bool(False), comEnergy = cms.double(13000.), RandomizedParameters = cms.VPSet(), ) """.format(tune_loc) # append process parameters for each model point helper = svjHelper() points = [] numevents_before = 0 numevents_after = 0 base_filter_eff = 0.5 for point in sorted(sigs): mZprime = point[0] mDark = point[1] rinv = point[2] alpha = point[3] weight = 1.0 filter_eff = base_filter_eff # down-weight rinv=0 b/c all events pass filter if rinv==0.0: weight = 0.5 filter_eff = 1.0 # account for relative acceptance if args.acc > 1: this_acc = get_acc(OrderedDict([("mZprime",mZprime),("mDark",mDark),("rinv",rinv),("alpha",alpha)])) min_weight = weight max_weight = weight*args.acc weight = np.clip(weight/this_acc,min_weight,max_weight) helper.setModel(mZprime,mDark,rinv,alpha) pdict = { 'weight': weight, 'processParameters': helper.getPythiaSettings(), 'name': helper.getOutName(outpre="SVJ",outsuff=""), } points.append(pdict) numevents_before += args.num*weight numevents_after += args.num*weight*filter_eff # some info on the scan print("This scan will contain "+str(len(sigs))+" model points, "+str(int(numevents_before))+" events before filter, "+str(int(numevents_after))+" events after filter") # format last part of config (loop over all points) last_part = """ for point in points: basePythiaParameters = cms.PSet( pythia8CommonSettingsBlock, {0}, processParameters = cms.vstring(point['processParameters']), parameterSets = cms.vstring( 'pythia8CommonSettings', '{1}', 'processParameters', ) ) generator.RandomizedParameters.append( cms.PSet( ConfigWeight = cms.double(point['weight']), ConfigDescription = cms.string(point['name']), PythiaParameters = basePythiaParameters, ), ) darkhadronZ2filter = cms.EDFilter("MCParticleModuloFilter", moduleLabel = cms.InputTag('generator','unsmeared'), particleIDs = cms.vint32(51,53), multipleOf = cms.uint32(4), absID = cms.bool(True), ) darkquarkFilter = cms.EDFilter("MCParticleModuloFilter", moduleLabel = cms.InputTag('generator','unsmeared'), particleIDs = cms.vint32(4900101), multipleOf = cms.uint32(2), absID = cms.bool(True), min = cms.uint32(2), status = cms.int32(23), ) ProductionFilterSequence = cms.Sequence(generator+darkhadronZ2filter+darkquarkFilter) """.format(tune_block,tune_block.replace("Block","")) with open("SVJ_Scan_"+str(args.year)+"_"+tune_suff+"_cff.py",'w') as ofile: ofile.write(first_part) ofile.write("\npoints = "+str(points)+"\n") ofile.write(last_part)

[ "kpedro88@gmail.com" ]

kpedro88@gmail.com

c68f82f56196ab515b57e4b8dd8e64e11aee61c6

3003a8663135aa10f5a152a8642bc6ab270995b9

/ggCloudSDK/google-cloud-sdk/.install/.backup/lib/googlecloudsdk/compute/subcommands/copy_files.py

c497c185cda19853ba46968bda156d1afe8bafc5

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

bopopescu/packmybot

1b4d199b36d196e5e769a781b520019bb4d0bdbc

92de1e72cfc51b41447366ffc81a9dcd9a5e7870

refs/heads/master

2022-11-25T23:46:06.946645

2015-10-22T08:22:04

282,313,675

0

null

2020-07-24T20:50:10

null

UTF-8

Python

false

5,907

py

# Copyright 2014 Google Inc. All Rights Reserved. """Implements the command for copying files from and to virtual machines.""" import collections import getpass import logging from googlecloudsdk.calliope import actions from googlecloudsdk.calliope import exceptions from googlecloudsdk.core import properties from googlecloudsdk.compute.lib import ssh_utils RemoteFile = collections.namedtuple( 'RemoteFile', ['user', 'instance_name', 'file_path']) LocalFile = collections.namedtuple( 'LocalFile', ['file_path']) class CopyFiles(ssh_utils.BaseSSHCLICommand): """Copy files to and from Google Compute Engine virtual machines.""" @staticmethod def Args(parser): ssh_utils.BaseSSHCLICommand.Args(parser) parser.add_argument( 'sources', help='Specifies a source file.', metavar='[[USER@]INSTANCE:]SRC', nargs='+') parser.add_argument( 'destination', help='Specifies a destination for the source files.', metavar='[[USER@]INSTANCE:]DEST') # TODO(user): Use utils.AddZoneFlag when copy_files supports URIs zone = parser.add_argument( '--zone', help='The zone of the instance to copy files to/from.', action=actions.StoreProperty(properties.VALUES.compute.zone)) zone.detailed_help = ( 'The zone of the instance to copy files to/from. If omitted, ' 'you will be prompted to select a zone.') def Run(self, args): super(CopyFiles, self).Run(args) file_specs = [] # Parses the positional arguments. for arg in args.sources + [args.destination]: # If the argument begins with "./" or "/", then we are dealing # with a local file that can potentially contain colons, so we # avoid splitting on colons. The case of remote files containing # colons is handled below by splitting only on the first colon. if arg.startswith('./') or arg.startswith('/'): file_specs.append(LocalFile(arg)) continue host_file_parts = arg.split(':', 1) if len(host_file_parts) == 1: file_specs.append(LocalFile(host_file_parts[0])) else: user_host, file_path = host_file_parts user_host_parts = user_host.split('@', 1) if len(user_host_parts) == 1: user = getpass.getuser() instance = user_host_parts[0] else: user, instance = user_host_parts file_specs.append(RemoteFile(user, instance, file_path)) logging.debug('Normalized arguments: %s', file_specs) # Validates the positional arguments. # TODO(user): Look into relaxing these conditions. sources = file_specs[:-1] destination = file_specs[-1] if isinstance(destination, LocalFile): for source in sources: if isinstance(source, LocalFile): raise exceptions.ToolException( 'All sources must be remote files when the destination ' 'is local.') else: # RemoteFile for source in sources: if isinstance(source, RemoteFile): raise exceptions.ToolException( 'All sources must be local files when the destination ' 'is remote.') instances = set() for file_spec in file_specs: if isinstance(file_spec, RemoteFile): instances.add(file_spec.instance_name) if len(instances) > 1: raise exceptions.ToolException( 'Copies must involve exactly one virtual machine instance; ' 'your invocation refers to [{0}] instances: [{1}].'.format( len(instances), ', '.join(sorted(instances)))) instance_ref = self.CreateZonalReference(instances.pop(), args.zone) external_ip_address = self.GetInstanceExternalIpAddress(instance_ref) # Builds the scp command. scp_args = [self.scp_executable] if not args.plain: scp_args.extend(self.GetDefaultFlags()) scp_args.append('-r') for file_spec in file_specs: if isinstance(file_spec, LocalFile): scp_args.append(file_spec.file_path) else: scp_args.append('{0}:{1}'.format( ssh_utils.UserHost(file_spec.user, external_ip_address), file_spec.file_path)) self.ActuallyRun(args, scp_args, user, external_ip_address) CopyFiles.detailed_help = { 'brief': 'Copy files to and from Google Compute Engine virtual machines', 'DESCRIPTION': """\ *{command}* copies files between a virtual machine instance and your local machine. To denote a remote file, prefix the file name with the virtual machine instance name (e.g., _example-instance_:~/_FILE_). To denote a local file, do not add a prefix to the file name (e.g., ~/_FILE_). For example, to copy a remote directory to your local host, run: $ {command} example-instance:~/REMOTE-DIR ~/LOCAL-DIR --zone us-central1-a In the above example, ``~/REMOTE-DIR'' from ``example-instance'' is copied into the ~/_LOCAL-DIR_ directory. Conversely, files from your local computer can be copied to a virtual machine: $ {command} ~/LOCAL-FILE-1 ~/LOCAL-FILE-2 example-instance:~/REMOTE-DIR --zone us-central1-a If a file contains a colon (``:''), you must specify it by either using an absolute path or a path that begins with ``./''. Under the covers, *scp(1)* is used to facilitate the transfer. When the destination is local, all sources must be the same virtual machine instance. When the destination is remote, all source must be local. This command ensures that the user's public SSH key is present in the project's metadata. If the user does not have a public SSH key, one is generated using *ssh-keygen(1)* (if the the `--quiet` flag is given, the generated key will have an empty passphrase). """, }

[ "cboussicaud@leaseplan.fr" ]

cboussicaud@leaseplan.fr

9b6a45f40e12d2ecc6562977a6042f61788e25dd

3716e91c0a18a2cf0b5807cc673d95a7539b008c

/DungeonsKitgard/TheRaisedSword.py

bd20ffd2d9632d3bba2ce439aa466531ce379317

[]

no_license

kiwiapple87/CodeCombat-1

47f0fa6d75d6d3e9fb9c28feeb6fe2648664c1aa

ce0201e5ed099193ca40afd3b7abeee5a3732387

refs/heads/master

2021-05-01T16:38:03.575842

2016-08-25T11:13:26

66,552,813

1

0

null

2016-08-25T11:39:20

2016-08-25T11:39:18

null

UTF-8

Python

false

168

py

# http://codecombat.com/play/level/the-raised-sword self.attack("Rig") self.attack("Rig") self.attack("Gurt") self.attack("Gurt") self.attack("Ack") self.attack("Ack")

[ "vadim-job-hg@yandex.ru" ]

vadim-job-hg@yandex.ru

ceb6062ff1dac18c07651c2b08736a9dc730fd51

0a613ccff34341510e9d8ac5e7c03ec991babfc8

/pytorch_widedeep/models/wide.py

24db9c9c539a9f5dae5152178bf0d2ccf1e74544

[ "MIT" ]

permissive

sailfish009/pytorch-widedeep

f0e507e00566207b1e455d250eb67ac71d2df3c7

b487b06721c5abe56ac68c8a38580b95e0897fd4

refs/heads/master

2023-05-01T05:24:39.217202

2021-04-16T15:17:48

null

0

null

UTF-8

Python

false

2,279

py

import math import torch from torch import nn from pytorch_widedeep.wdtypes import * # noqa: F403 class Wide(nn.Module): def __init__(self, wide_dim: int, pred_dim: int = 1): r"""wide (linear) component Linear model implemented via an Embedding layer connected to the output neuron(s). Parameters ----------- wide_dim: int size of the Embedding layer. `wide_dim` is the summation of all the individual values for all the features that go through the wide component. For example, if the wide component receives 2 features with 5 individual values each, `wide_dim = 10` pred_dim: int, default = 1 size of the ouput tensor containing the predictions Attributes ----------- wide_linear: :obj:`nn.Module` the linear layer that comprises the wide branch of the model Examples -------- >>> import torch >>> from pytorch_widedeep.models import Wide >>> X = torch.empty(4, 4).random_(6) >>> wide = Wide(wide_dim=X.unique().size(0), pred_dim=1) >>> out = wide(X) """ super(Wide, self).__init__() # Embeddings: val + 1 because 0 is reserved for padding/unseen cateogories. self.wide_linear = nn.Embedding(wide_dim + 1, pred_dim, padding_idx=0) # (Sum(Embedding) + bias) is equivalent to (OneHotVector + Linear) self.bias = nn.Parameter(torch.zeros(pred_dim)) self._reset_parameters() def _reset_parameters(self) -> None: r"""initialize Embedding and bias like nn.Linear. See `original implementation <https://pytorch.org/docs/stable/_modules/torch/nn/modules/linear.html#Linear>`_. """ nn.init.kaiming_uniform_(self.wide_linear.weight, a=math.sqrt(5)) fan_in, _ = nn.init._calculate_fan_in_and_fan_out(self.wide_linear.weight) bound = 1 / math.sqrt(fan_in) nn.init.uniform_(self.bias, -bound, bound) def forward(self, X: Tensor) -> Tensor: # type: ignore r"""Forward pass. Simply connecting the Embedding layer with the ouput neuron(s)""" out = self.wide_linear(X.long()).sum(dim=1) + self.bias return out

[ "jrzaurin@gmail.com" ]

jrzaurin@gmail.com

658ae6ce12ab34713850e57285d9f752a27cf1c8

ca231a325e8f4c18d50d89ffa7eec993d4cc68c3

/PythonZumbis/lista4/questao01.py

52ef9d134fbcb8049241fa246ac2f38051db434d

[]

no_license

HugoPorto/PythonCodes

8e1597999ccd34ffa86df5ae7e91111d77dc7a22

539ad6891cbd49a2c011349f843ab710aad2993a

refs/heads/master

2022-02-13T05:48:24.633750

2017-09-12T15:44:06

null

0

null

UTF-8

Python

false

442

py

from random import randint lista = [ randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100), randint(1, 100)] maior = 0 menor = 999 i = 0 while i < 10: if lista[i] > maior: maior = lista[i] if lista[i] < menor: menor = lista[i] i += 1 print "Maior: %d, menor %d" % (maior, menor)

[ "gpzim98@gmail.com" ]

gpzim98@gmail.com

f3f5edd99ffd8c25d6f8b7f8f256e0d8b3db914b

b72c37e3ccda507b231649cddd5c7845c6c34ba1

/PythonBasic/Day10/HomeWork_func.py

616a95d2e92ed813880bc2d38a1c2920d8ab7b03

[]

no_license

ljrdemail/AID1810

51c61c255b5c5efc1dc642b46691a614daedd85e

b417bd831bc1550ab953ce7ca23f54e34b8b2692

refs/heads/master

2020-04-24T09:45:14.781612

2019-02-21T11:26:49

171,866,267

0

null

UTF-8

Python

false

481

py

def mysum(n): # sum = 0 # num = int(n) # for i in range(1, num + 1): # sum += i # return sum return sum(range(1,n+1)) # return sum(list(range(1,n+1))) def myfac(n): fac = 1 num = int(n) for i in range(1, num + 1): fac *= i return fac print(myfac(10)) def mypow(n): # sum = 0 # num = int(n) # for i in range(1, num + 1): # sum += i ** i # return sum return sum(map(lambda x:x**x,range(1,n+1)))

[ "root" ]

root

c5f10f045e2471562135208acf2377b8d14c9942

403de45c6626f2c40d2d48d64f4c94a728bb7b09

/vocoder_eva/eval.py

baa254f50dd11cbd3bae82919f435fa3ef8f150a

[]

no_license

exeex/vocoder_eva

f95d969261adaa63ec01270239496eec3c9adca5

d81dc01768da20c208df00bfb78d90c52d93c0a8

refs/heads/master

2020-09-14T01:04:27.189683

2020-01-20T14:08:14

222,961,890

12

1

null

UTF-8

Python

false

3,992

py

import librosa import numpy as np import pyworld as pw import matplotlib.pyplot as plt import pysptk ln10_inv = 1 / np.log(10) def pad_to(x, target_len): pad_len = target_len - len(x) if pad_len <= 0: return x[:target_len] else: return np.pad(x, (0, pad_len), 'constant', constant_values=(0, 0)) def eval_snr(x_r, x_s): # TODO: slide x_s to find max matched value 原論文有做滑動x_s，找到最大匹配的snr值，這邊還沒實作 return 10 * np.log10(np.sum(x_s ** 2) / np.sum((x_s - x_r) ** 2)) def eval_MCD(x_r, x_s): # TODO: verify value 確認做出來的值是否正確 (和原論文比較) c_r = librosa.feature.mfcc(x_r) c_s = librosa.feature.mfcc(x_s) # plt.imshow(c_r) # plt.show() # plt.imshow(c_s) # plt.show() # # plt.plot(c_r[:, 20]) # plt.plot(c_s[:, 40]) # plt.show() # print((c_r- c_s)) temp = 2 * np.sum((c_r - c_s) ** 2, axis=0) # print(temp) return 10 * ln10_inv * (temp ** 0.5) def plot_f0(*files, title=None): for file in files: if isinstance(file, tuple): file_path, label = file else: file_path = file label = None aud, sr = librosa.load(file_path, sr=None) f0 = pysptk.sptk.swipe(aud.astype(np.double), sr, hopsize=128) plt.plot(f0, label=label) plt.ylabel('f0(Hz)') plt.xlabel('frame') if title: plt.title(title) plt.legend(loc='upper right') plt.show() def eval_rmse_f0(x_r, x_s, sr, frame_len='5', method='swipe', tone_shift=None): # TODO: 要可以改動 frame len (ms) 或者 hop_size if method == 'harvest': f0_r, t = pw.harvest(x_r.astype(np.double), sr, frame_period=50) f0_s, t = pw.harvest(x_s.astype(np.double), sr, frame_period=50) elif method == 'dio': f0_r, t = pw.dio(x_r.astype(np.double), sr, frame_period=50) f0_s, t = pw.dio(x_s.astype(np.double), sr, frame_period=50) elif method == 'swipe': f0_r = pysptk.sptk.swipe(x_r.astype(np.double), sr, hopsize=128) f0_s = pysptk.sptk.swipe(x_s.astype(np.double), sr, hopsize=128) elif method == 'rapt': f0_r = pysptk.sptk.rapt(x_r.astype(np.double), sr, hopsize=128) f0_s = pysptk.sptk.rapt(x_s.astype(np.double), sr, hopsize=128) else: raise ValueError('no such f0 exract method') # length align f0_s = pad_to(f0_s, len(f0_r)) # make unvoice / vooiced frame mask f0_r_uv = (f0_r == 0) * 1 f0_r_v = 1 - f0_r_uv f0_s_uv = (f0_s == 0) * 1 f0_s_v = 1 - f0_s_uv tp_mask = f0_r_v * f0_s_v tn_mask = f0_r_uv * f0_s_uv fp_mask = f0_r_uv * f0_s_v fn_mask = f0_r_v * f0_s_uv if tone_shift is not None: shift_scale = 2 ** (tone_shift / 12) f0_r = f0_r * shift_scale # only calculate f0 error for voiced frame y = 1200 * np.abs(np.log2(f0_r + f0_r_uv) - np.log2(f0_s + f0_s_uv)) y = y * tp_mask # print(y.sum(), tp_mask.sum()) f0_rmse_mean = y.sum() / tp_mask.sum() # only voiced/ unvoiced accuracy/precision vuv_precision = tp_mask.sum() / (tp_mask.sum() + fp_mask.sum()) vuv_accuracy = (tp_mask.sum() + tn_mask.sum()) / len(y) return f0_rmse_mean, vuv_accuracy, vuv_precision def eval_rmse_ap(x_r, x_s, sr, frame_len='5'): # TODO: find out what algorithm to use. maybe pyworld d4c? pass if __name__ == '__main__': file_r = 'demo/exmaple_data/ground_truth/arctic_b0436.wav' file_s = 'demo/exmaple_data/no_pulse/arctic_b0436.wav' aud_r, sr_r = librosa.load(file_r, sr=None) aud_s, sr_s = librosa.load(file_s, sr=None) assert sr_r == sr_s if len(aud_r) != len(aud_s): aud_r = aud_r[:len(aud_s)] aud_s = aud_s[:len(aud_r)] # mcd = eval_MCD(aud_r, aud_s) rmse_f0 = eval_rmse_f0(aud_r, aud_s, sr_r) print(rmse_f0) # print(aud_r.shape) # print(eval_snr(aud_r, aud_s)) # print(eval_snr(aud_r*10, aud_s*10))

[ "xray0h@gmail.com" ]

xray0h@gmail.com

560336f07c938cf86e6d8af0547e58c0c2aeee39

14fc2ee47e1081416f0465e8afa18da33169095f

/src/PP4E/Ai/ExpertSystem/holmes/holmes2/forward2.py

68e44a13498fb15d2cd3a51dad0b31cdbb159c0f

[]

no_license

madtyn/progPython

d95ea8021b1a54433e7b73de9d3b11d53a3096b7

f3a1169149afdeb5191dd895462139f60d21d458

refs/heads/master

2021-07-09T13:35:27.519439

2017-10-04T14:46:57

104,866,903

0

null

UTF-8

Python

false

2,469

py

# # module forward2.py # # forward chaining inference engine # # this is a varient of forward.py that implements # negation both by explicit assertion, and by # ommission; see holmes.doc for more info; # to use negation-by-ommission in the shell: # holmes> +2 # to use it in a program, just import forward2; ########################################################################### import forward; forward1 = forward from match import * from forward import copy_dict, ask_user def forward(kbase, facts, *pmode): temp = forward1.conjunct forward1.conjunct = conjunct # over-ride 1 function res = forward1.forward(kbase, facts, pmode) # call forward.py version forward1.conjunct = temp return res ################################################# # generate bindings for rule's 'if' conjunction: # find intersected bindings at this 'AND' node, # and construct proof subtree lists as the # recursion unfolds with valid solutions; # # note: this function executes with global # scope = module forward2.py, but the rest of # the system executes with global scope = # module forward.py; # # note: this isn't exactly like forward.py # for explicitly asserted 'not' facts, since # we don't carry variable bindings from the # match (we do a simple ground comparison); ################################################# def conjunct(ifs, known, dict, why): if ifs == []: return [(copy_dict(dict), [])] # all conjuncts matched res = [] head, tail = ifs[0], ifs[1:] if head[0] == 'ask': term = substitute(head[1:], dict) if ask_user(term, known, why): for (dict2, proof2) in conjunct(tail, known, dict, why): res.append((dict2, [(term, 'told')] + proof2)) elif head[0] == 'not': term = substitute(head[1:], dict) if not known.search_unique(term) or \ known.search_unique(['not'] + term): for (dict2, proof2) in conjunct(tail, known, dict, why): res.append((dict2, [(term, 'not')] + proof2)) else: for (fact, proof) in known.search(head, dict): matched, changes = match(head, fact, dict, {}) if matched: for (dict2, proof2) in conjunct(tail, known, dict, why): res.append((dict2, [(fact, proof)] + proof2)) for (var, env) in changes: env[var] = '?' return res

[ "madtyn@gmail.com" ]

madtyn@gmail.com

e5701a988ccc68f2d79bc6b8df147784e0b255fe

6fdb4eaf5b0e6dbd7db4bf947547541e9aebf110

/robot-server/tests/service/session/models/test_command.py

67d99f409ac65be929996b5cab636f523cc44269

[ "LicenseRef-scancode-warranty-disclaimer", "Apache-2.0" ]

permissive

Opentrons/opentrons

874321e01149184960eeaeaa31b1d21719a1ceda

026b523c8c9e5d45910c490efb89194d72595be9

refs/heads/edge

2023-09-02T02:51:49.579906

2023-08-31T16:02:45

38,644,841

326

174

Apache-2.0

2023-09-14T21:47:20

2015-07-06T20:41:01

Python

UTF-8

Python

false

2,142

py

from datetime import datetime import pytest from pydantic import ValidationError from robot_server.service.session.models import command, command_definitions @pytest.mark.parametrize( argnames="command_def", argvalues=[ command_definitions.ProtocolCommand.start_run, command_definitions.CalibrationCommand.move_to_deck, command_definitions.CheckCalibrationCommand.compare_point, ], ) def test_empty(command_def: command_definitions.CommandDefinition): """Test creation of empty command request and response.""" request = command.CommandRequest.parse_obj( {"data": {"command": command_def.value, "data": {}}} ) assert request.data.command == command_def assert request.data.data == command.EmptyModel() dt = datetime(2000, 1, 1) response = request.data.make_response( identifier="id", status=command.CommandStatus.executed, created_at=dt, started_at=None, completed_at=None, result=None, ) assert response.command == command_def assert response.data == command.EmptyModel() assert response.id == "id" assert response.createdAt == dt assert response.startedAt is None assert response.completedAt is None assert response.result is None @pytest.mark.parametrize( argnames="command_def", argvalues=[ command_definitions.EquipmentCommand.load_labware, command_definitions.EquipmentCommand.load_pipette, command_definitions.PipetteCommand.aspirate, command_definitions.PipetteCommand.dispense, command_definitions.PipetteCommand.drop_tip, command_definitions.PipetteCommand.pick_up_tip, command_definitions.CalibrationCommand.jog, command_definitions.CalibrationCommand.set_has_calibration_block, ], ) def test_requires_data(command_def: command_definitions.CommandDefinition): """Test creation of command requiring data will fail with empty body.""" with pytest.raises(ValidationError): command.CommandRequest.parse_obj( {"data": {"command": command_def.value, "data": {}}} )

[ "noreply@github.com" ]

Opentrons.noreply@github.com

580eeccd0fdd976778a96b8c5d7a64e3cbcc7863

b39d9ef9175077ac6f03b66d97b073d85b6bc4d0

/Emend_WC500026537.4.py

46754167c443614635089acfee5a74b6d1a88dc2

[]

no_license

urudaro/data-ue

2d840fdce8ba7e759b5551cb3ee277d046464fe0

176c57533b66754ee05a96a7429c3e610188e4aa

refs/heads/master

2021-01-22T12:02:16.931087

2013-07-16T14:05:41

null

0

null

UTF-8

Python

false

2,484

py

{'_data': [['Common', [['Metabolism', u'minskad aptit'], ['Nervous system', u'huvudv\xe4rk'], ['Respiratory', u'Hicka'], ['GI', u'f\xf6rstoppning, dyspepsi'], ['General', u'Tr\xf6tthet'], ['Investigations', u'f\xf6rh\xf6jt ALAT']]], ['Uncommon', [['Blood', u'febril neutropeni, anemi'], ['Psychiatric', u'\xc5ngest'], ['Nervous system', u'yrsel, s\xf6mnighet'], ['Cardiac', u'Palpitationer'], ['Vascular', u'V\xe4rmevallningar'], ['GI', u'rapning, illam\xe5ende*, kr\xe4kning*, gastroesofagal refluxsjukdom, buksm\xe4rta, muntorrhet, flatulens'], ['Skin', u'utslag, akne'], ['Renal', u'Dysuri'], ['General', u'asteni, sjukdomsk\xe4nsla'], ['Investigations', u'f\xf6rh\xf6jt ASAT, f\xf6rh\xf6jt alkaliskt fosfatas i blodet']]], ['Rare', [['Infections', u'candidiasis, stafylokockinfektion'], ['Metabolism', u'Polydipsi'], ['Psychiatric', u'desorientering, euforisk sinnesst\xe4mning'], ['Nervous system', u'kognitiv st\xf6rning, letargi, dysgeusi'], ['Eye', u'Konjunktivit'], ['Ear', u'Tinnitus'], ['Cardiac', u'bradykardi, hj\xe4rt-k\xe4rlsjukdom'], ['Respiratory', u'orofaryngeal sm\xe4rta, nysning, hosta, postnasalt dropp, svalgirritation'], ['GI', u'perforerande duodenals\xe5r, stomatit, buksp\xe4nning, h\xe5rd avf\xf6ring, neutropen kolit'], ['Skin', u'fotosensitivitetsreaktion, hyperhidros, seborr\xe9, hudf\xf6r\xe4ndring, kliande utslag, Stevens- Johnsons syndrom/toxisk epidermal nekrolys'], ['Musculoskeletal', u'muskelsvaghet, muskelspasmer'], ['Renal', u'Pollakisuri'], ['General', u'\xf6dem, obehagsk\xe4nsla i br\xf6stet, g\xe5ngst\xf6rning'], ['Investigations', u'positivt test f\xf6r r\xf6da blodkroppar i urinen, minskat natrium i blodet, viktminskning, minskat antal neutrofiler, glukosuri, \xf6kad urinm\xe4ngd']]], ['Unknown', [['Immune system', u'\xf6verk\xe4nslighetsreaktioner inkluderande anafylaktiska reaktioner'], ['Skin', u'kl\xe5da, urtikaria']]]], '_pages': [7, 9], u'_rank': 32, u'_type': u'TSFU'}

[ "daro@daro-ThinkPad-X220.(none)" ]

daro@daro-ThinkPad-X220.(none)

ac6dc9752855bb5a9741df5fcd939fbed3d4226b

0f9f8e8478017da7c8d408058f78853d69ac0171

/python3/l0229_majority_element_2.py

8d8dd64afeae37fe515fb54d936bb76fed74d62f

[]

no_license

sprax/1337

dc38f1776959ec7965c33f060f4d43d939f19302

33b6b68a8136109d2aaa26bb8bf9e873f995d5ab

refs/heads/master

2022-09-06T18:43:54.850467

2020-06-04T17:19:51

null

0

null

UTF-8

Python

false

865

py

from typing import List class Solution: def majorityElement(self, nums: List[int]) -> List[int]: c1, c2 = None, None count1, count2 = 0, 0 for n in nums: if n == c1: count1 += 1 elif n == c2: count2 += 1 elif count1 == 0: c1 = n count1 = 1 elif count2 == 0: c2 = n count2 = 1 else: count1 -= 1 count2 -= 1 count1, count2 = 0, 0 for n in nums: if n == c1: count1 += 1 elif n == c2: count2 += 1 result = [] if count1 > len(nums) // 3: result.append(c1) if count2 > len(nums) // 3: result.append(c2) return result

[ "zhoulv82@gmail.com" ]

zhoulv82@gmail.com

0cbf5e113335f0f6acf9dd864503ff0411592ba7

8bfd94be34008db3a7822247e9fb05604ad010d2

/snips/migrations/0001_initial.py

a7b67f1349671972f09f8da5d588956b54b4acf5

[]

no_license

SnipToday/FrontEnd

c7ce59548b0114e24008580d98dad48c78ff431d

5043fb584535295b27e8c6f0044c54ac8ab40023

refs/heads/master

2021-01-22T17:49:04.506117

2017-09-04T22:08:28

102,405,712

0

1

null

UTF-8

Python

false

2,461

py

# -*- coding: utf-8 -*- # Generated by Django 1.10.6 on 2017-04-20 13:20 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import django.utils.timezone import modelcluster.fields class Migration(migrations.Migration): initial = True dependencies = [ ('wagtailcore', '0032_add_bulk_delete_page_permission'), ] operations = [ migrations.CreateModel( name='Category', fields=[ ('name', models.CharField(max_length=50, primary_key=True, serialize=False)), ], ), migrations.CreateModel( name='SnipRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, max_length=800, verbose_name='External link')), ('title', models.CharField(max_length=255)), ], options={ 'abstract': False, 'ordering': ['sort_order'], }, ), migrations.CreateModel( name='Tldr', fields=[ ('page_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='wagtailcore.Page')), ('date', models.DateField(blank=True, default=django.utils.timezone.now, verbose_name='Post date')), ('body', models.TextField(verbose_name='Body')), ('category', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='snips.Category')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.AddField( model_name='sniprelatedlink', name='link_page', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page'), ), migrations.AddField( model_name='sniprelatedlink', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='snips.Tldr'), ), ]

[ "ranihorev@gmail.com" ]

ranihorev@gmail.com

5d323280b72ac2c020eaf9e222a4bbe9e7dfd50f

0fc9eca08cc48f93a4079a9b4c0dd0201ef2ce80

/vindula/agendacorporativa/browser/search.py

8571790b6dae199e6a61314a09ccf6efa1eb8e74

[]

no_license

vindula/vindula.agendacorporativa

c75564c7d89424e23e3a1baa1f1dcdc6ac2dfc4c

e70f6c2baf6629cb4a486bc642c49e7b7138bf7d

refs/heads/master

2020-12-29T01:41:33.812325

2013-08-02T18:54:58

null

0

null

UTF-8

Python

false

1,266

py

# coding: utf-8 from Products.CMFCore.utils import getToolByName from AccessControl.SecurityManagement import newSecurityManager, getSecurityManager, setSecurityManager from DateTime import DateTime from copy import copy def busca_commitment(context,username,portlet=False): ctool = getToolByName(context, 'portal_catalog') path = context.portal_url.getPortalObject().getPhysicalPath() date_range_query = { 'query': DateTime(), 'range': 'min'} query = {'path': {'query':'/'.join(path)}, 'portal_type': ('Commitment',), 'sort_on':'getStart_datetime', # 'sort_order':'descending', } if portlet: query['getStart_datetime'] = date_range_query #Busca por conpromissos do probrio usuario query1 = copy(query) query1['Creator'] = username result1 = ctool(**query1) #Busca por compromissos que o usuario participa query2 = copy(query) query2['getConvidados'] = [username] result2 = ctool(**query2) #Busca por compromissos publicos query3 = copy(query) query3['review_state'] = ['published', 'internally_published', 'external', 'internal'] result3 = ctool(**query3) result = result1 + result2 + result3 L = [] L_UID = [] for item in result: if not item.UID in L_UID: L.append(item) L_UID.append(item.UID) return L

[ "cesaraugusto@liberiun.com" ]

cesaraugusto@liberiun.com

e82730273d0eaa099b5b7974f79444de9077c466

045cb1a5638c3575296f83471758dc09a8065725

/addons/purchase/report/purchase_bill.py

d442019eb8c1ec5604f64349509c1d4a9b4dc348

[]

no_license

marionumza/saas

7236842b0db98d1a0d0c3c88df32d268509629cb

148dd95d991a348ebbaff9396759a7dd1fe6e101

refs/heads/main

2023-03-27T14:08:57.121601

2021-03-20T07:59:08

null

0

null

UTF-8

Python

false

2,459

py

# -*- coding: utf-8 -*- # Part of Harpiya. See LICENSE file for full copyright and licensing details. from harpiya import api, fields, models, tools from harpiya.tools import formatLang class PurchaseBillUnion(models.Model): _name = 'purchase.bill.union' _auto = False _description = 'Purchases & Bills Union' _order = "date desc, name desc" name = fields.Char(string='Reference', readonly=True) reference = fields.Char(string='Source', readonly=True) partner_id = fields.Many2one('res.partner', string='Vendor', readonly=True) date = fields.Date(string='Date', readonly=True) amount = fields.Float(string='Amount', readonly=True) currency_id = fields.Many2one('res.currency', string='Currency', readonly=True) company_id = fields.Many2one('res.company', 'Company', readonly=True) vendor_bill_id = fields.Many2one('account.move', string='Vendor Bill', readonly=True) purchase_order_id = fields.Many2one('purchase.order', string='Purchase Order', readonly=True) def init(self): tools.drop_view_if_exists(self.env.cr, 'purchase_bill_union') self.env.cr.execute(""" CREATE OR REPLACE VIEW purchase_bill_union AS ( SELECT id, name, ref as reference, partner_id, date, amount_untaxed as amount, currency_id, company_id, id as vendor_bill_id, NULL as purchase_order_id FROM account_move WHERE type='in_invoice' and state = 'posted' UNION SELECT -id, name, partner_ref as reference, partner_id, date_order::date as date, amount_untaxed as amount, currency_id, company_id, NULL as vendor_bill_id, id as purchase_order_id FROM purchase_order WHERE state in ('purchase', 'done') AND invoice_status in ('to invoice', 'no') )""") def name_get(self): result = [] for doc in self: name = doc.name or '' if doc.reference: name += ' - ' + doc.reference amount = doc.amount if doc.purchase_order_id and doc.purchase_order_id.invoice_status == 'no': amount = 0.0 name += ': ' + formatLang(self.env, amount, monetary=True, currency_obj=doc.currency_id) result.append((doc.id, name)) return result

[ "yasir@harpiya.com" ]

yasir@harpiya.com

5114aa4f0924c3f6eaa3c0e48d017abbbb07dc7f

b6277a78b0337667ec4b88e0da3cb84a76383687

/tests/test_inertia.py

ee4d43936999c7eb71ba51b38a6a87c207d455ae

[ "MIT" ]

permissive

sgalkina/trimesh

11c91e9c9a7c013fb81551dcee0fdbfffa1f5d13

55e35216efcf620c816d82d9f9167e22966a851d

refs/heads/master

2021-01-25T07:00:55.935106

2017-06-06T03:30:28

93,636,761

0

null

2017-06-07T13:11:58

2017-06-07T13:11:57

null

UTF-8

Python

false

4,510

py

import generic as g class InertiaTest(g.unittest.TestCase): def test_inertia(self): t0 = g.np.array([[-0.419575686853, -0.898655215203, -0.127965023308, 0. ], [ 0.712589964872, -0.413418145015, 0.566834172697, 0. ], [-0.562291548012, 0.146643245877, 0.813832890385, 0.], [ 0. , 0. , 0. , 1. ]]) t1 = g.np.array([[ 0.343159553585, 0.624765521319, -0.701362648103, 0.], [ 0.509982849005, -0.750986657709, -0.419447891476, 0. ], [-0.788770571525, -0.213745370274, -0.57632794673 , 0. ], [ 0. , 0. , 0. , 1. ]]) # make sure our transformations are actually still transformations assert g.np.abs(g.np.dot(t0, t0.T) - g.np.eye(4)).max() < 1e-10 assert g.np.abs(g.np.dot(t1, t1.T) - g.np.eye(4)).max() < 1e-10 c = g.trimesh.primitives.Cylinder(height=10, radius=1, sections=720, # number of slices transform=t0) c0m = c.moment_inertia.copy() c0 = g.trimesh.inertia.cylinder_inertia(c.volume, c.primitive.radius, c.primitive.height, c.primitive.transform) ct = g.np.abs((c0m / c0) - 1) # we are comparing an inertia tensor from a mesh of a cylinder # to an inertia tensor from an actual cylinder, so allow for some # discretization uncertainty assert ct.max() < 1e-3 # check our principal axis calculation against this cylinder # the direction (long axis) of the cylinder should correspond to # the smallest principal component of inertia, AKA rotation along # the axis, rather than the other two which are perpendicular components, vectors = g.trimesh.inertia.principal_axis(c.moment_inertia) axis_test = g.np.abs((vectors[components.argmin()] / c.direction) - 1) assert axis_test.max() < 1e-8 # make sure Trimesh attribute is plumbed correctly assert g.np.allclose(c.principal_inertia_components, components) assert g.np.allclose(c.principal_inertia_vectors, vectors) # the other two axis of the cylinder should be identical assert g.np.abs(g.np.diff(g.np.sort(components)[-2:])).max() < 1e-8 m = g.get_mesh('featuretype.STL') i0 = m.moment_inertia.copy() # rotate the moment of inertia i1 = g.trimesh.inertia.transform_inertia(transform=t0, inertia_tensor=i0) # rotate the mesh m.apply_transform(t0) # check to see if the rotated mesh + recomputed moment of inertia # is close to the rotated moment of inertia tf_test = g.np.abs((m.moment_inertia / i1) - 1) assert tf_test.max() < 1e-6 # do it again with another transform i2 = g.trimesh.inertia.transform_inertia(transform=t1, inertia_tensor=i1) m.apply_transform(t1) tf_test = g.np.abs((m.moment_inertia / i2) - 1) assert tf_test.max() < 1e-6 def test_primitives(self): primitives = [g.trimesh.primitives.Cylinder(height=5), g.trimesh.primitives.Box(), g.trimesh.primitives.Sphere(radius=1.23)] for p in primitives: for i in range(100): # check to make sure the analytic inertia tensors are relatively # close to the meshed inertia tensor (order of magnitude and sign) comparison = g.np.abs(p.moment_inertia - p.to_mesh().moment_inertia) c_max = comparison.max() / g.np.abs(p.moment_inertia).max() assert c_max < .1 if hasattr(p.primitive, 'transform'): matrix = g.trimesh.transformations.random_rotation_matrix() p.primitive.transform = matrix elif hasattr(p.primitive, 'center'): p.primitive.center = g.np.random.random(3) if __name__ == '__main__': g.trimesh.util.attach_to_log() g.unittest.main()

[ "mik3dh@gmail.com" ]

mik3dh@gmail.com

aaa6d9dc213f7a6387f24784b2d7e5faf88bdaca

2f37d3dcb20c9ba171024b1f8711b9926dbef0f3

/eventex/subscriptions/mixins.py

af8a07846e310bed196a2252db4603a7d4f73b42

[]

no_license

sergiopassos/eventex-sergiopassos

9c080a365e4e554a5839aa461ce47e3d40d9fc53

6672223faaa7930377532141394dea3ae7c2c431

refs/heads/master

2023-04-27T02:40:15.094019

2020-01-16T13:51:11

192,630,937

0

null

2023-04-21T20:32:42

2019-06-19T00:37:38

Python

UTF-8

Python

false

1,585

py

from django.conf import settings from django.core import mail from django.template.loader import render_to_string from django.views.generic import CreateView class EmailCreateMixin: email_to = None email_context_name = None email_template_name = None email_from = settings.DEFAULT_FROM_EMAIL email_subject = '' def send_mail(self): # Send subscription email subject = self.email_subject from_ = self.email_from to = self.get_email_to() template_name = self.get_email_template_name() context = self.get_email_context_data() body = render_to_string(template_name, context) return mail.send_mail(subject, body, from_, [from_, to]) def get_email_template_name(self): if self.email_template_name: return self.email_template_name meta = self.object._meta return '{}/{}_email.txt'.format(meta.app_label, meta.model_name) def get_email_context_data(self, **kwargs): context = dict(kwargs) context.setdefault(self.get_email_context_name(), self.object) return context def get_email_context_name(self): if self.email_context_name: return self.email_context_name return self.object._meta.model_name def get_email_to(self): if self.email_to: return self.email_to return self.object.email class EmailCreateView(EmailCreateMixin, CreateView): def form_valid(self, form): response = super().form_valid(form) self.send_mail() return response

[ "sergio.passos02@gmail.com" ]

sergio.passos02@gmail.com

20aa4222af3a4ebe0cc386a6ed3d8a36989e1b88

8a9b10eeef43e648fcc82d5fdbf6505e0e19a88b

/Tensor_Flow/stock_similarity_daily.py

865cb66b7091f69f8580c800d2c23bd22bff0acb

[]

no_license

lwzswufe/neural_net

3648e100ad68fd2dbd6e3f51be7b053780f7fd87

0a0ed94680c0e5dd3dbd2e13aef79a1b8fd8293d

refs/heads/master

2021-03-30T17:06:18.296242

2019-10-16T08:22:47

76,216,678

0

null

UTF-8

Python

false

208

py

# author='lwz' # coding:utf-8 # !/usr/bin/env python3 import os from Tensor_Flow import AutoEncoder2, similarity_analysis if __name__ == '__main__': AutoEncoder2.daily() similarity_analysis.daily()

[ "lwzswufe@foxmail.com" ]

lwzswufe@foxmail.com

c73df56929f4b7102748c83d681b3d6ba5a8af13

0d86bb399a13152cd05e3ba5684e4cb22daeb247

/python-basics/unit11-error/py116_raise.py

f69da74fed89c80b5b2226b0517bf4504d52200c

[]

no_license

tazbingor/learning-python2.7

abf73f59165e09fb19b5dc270b77324ea00b047e

f08c3bce60799df4f573169fcdb1a908dcb8810f

refs/heads/master

2021-09-06T05:03:59.206563

2018-02-02T15:22:45

108,609,480

0

null

UTF-8

Python

false

685

py

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 18/1/2 下午8:00 # @Author : Aries # @Site : # @File : py116_raise.py # @Software: PyCharm ''' raise语句主动抛出异常 ''' def thorw_error(): raise Exception("抛出一个异常") if __name__ == '__main__': thorw_error() ''' Traceback (most recent call last): File "project/PycharmProjects/rising-python-classics/python-basics/unit11-error/py116_raise.py", line 18, in <module> thorw_error() File "project/PycharmProjects/rising-python-classics/python-basics/unit11-error/py116_raise.py", line 14, in thorw_error raise Exception("抛出一个异常") Exception: 抛出一个异常 '''

[ "852353298@qq.com" ]

852353298@qq.com

ed61bed728ef72c66243a1d999603df111527ea6

ab650e6a0ca2f97096235ebe914b140b740aec66

/app/templates/_root_init.py

88f63dc99cf2ee4d75a6a147f53f0b50423d33bb

[ "MIT" ]

permissive

ghostRider1124/generator-python-package

8fd353d6c4ed2c6f1ad88ebb6fe6811a8d585026

678b33fec9937c68aaa45ae04e6a8aac5f6554c5

refs/heads/master

2020-05-20T18:16:32.266189

2014-07-02T17:05:26

null

0

null

UTF-8

Python

false

387

py

#!/usr/bin/python # -*- coding: utf-8 -*- # This file is part of <%= package.name %>. # <%= package.url %> # Licensed under the <%= package.license %> license: # http://www.opensource.org/licenses/<%= package.license%>-license # Copyright (c) <%= package.created.year %> <%= package.author.name %> <%= package.author.email %> from <%= package.pythonName %>.version import __version__

[ "heynemann@gmail.com" ]

heynemann@gmail.com

06c6fc43bcedc984addf32ef365c64484890ea3c

9e988c0dfbea15cd23a3de860cb0c88c3dcdbd97

/sdBs/AllRun/ec_13175-1949/sdB_ec_13175-1949_coadd.py

ffac546028839ada5df1dbebec03b93979d41d2d

[]

no_license

tboudreaux/SummerSTScICode

73b2e5839b10c0bf733808f4316d34be91c5a3bd

4dd1ffbb09e0a599257d21872f9d62b5420028b0

refs/heads/master

2021-01-20T18:07:44.723496

2016-08-08T16:49:53

65,221,159

0

null

UTF-8

Python

false

439

py

from gPhoton.gMap import gMap def main(): gMap(band="NUV", skypos=[200.073167,-20.088431], skyrange=[0.0333333333333,0.0333333333333], stepsz = 30., cntfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdBs/sdB_ec_13175-1949/sdB_ec_13175-1949_movie_count.fits", cntcoaddfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdB/sdB_ec_13175-1949/sdB_ec_13175-1949_count_coadd.fits", overwrite=True, verbose=3) if __name__ == "__main__": main()

[ "thomas@boudreauxmail.com" ]

thomas@boudreauxmail.com

f606fc6928efe6b05a4ee59ddda61acd48e114dd

930bc970069d8cbcfb36725a90492eff50638ecc

/code/dk-iris-pipeline/airflow_home/src/model/benchmark.py

1bbbbefb5abcaffd9064680c379d44d929b5a14b

[ "MIT" ]

permissive

databill86/airflow4ds

4770d856569c4db4b55b2d9dfda010e21c4cd790

b5ae213f7169c54d31f4eca58d235ec6b09fd56f

refs/heads/master

2021-09-25T17:26:43.340747

2018-10-24T16:09:49

null

0

null

UTF-8

Python

false

906

py

import os import sys # Allow Python to discover local modules sys.path.append(os.getenv(key='AIRFLOW_HOME')) import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.metrics import classification_report, accuracy_score from src import PROJECT_DIRECTORY from src.scrub import get_clean_iris def get_train_test_data(): """ """ df = get_clean_iris() X = df.copy().drop(['iris_type'], axis=1) y = df.copy().loc[:, 'iris_type'].replace({'setosa': 0, 'versicolor': 1, 'virginica': 2}) return train_test_split(X, y, test_size=0.30, random_state=112358) def run_model_benchmark(): """ """ X_tr, X_te, y_tr, y_te = get_train_test_data() lr_0 = LogisticRegression() lr_0.fit(X_tr, y_tr) y_pr = lr_0.predict(X_te) print(f"Benchmark Model Accuracy: {accuracy_score(y_te, y_pr)}")

[ "dushyant.khosla@pmi.com" ]

dushyant.khosla@pmi.com

3ce8f8c6eacd5408747793dcc122d0488f4ae734

baa484828e8683d51d58d48989532e3d3ce987bc

/200228_4.py

2efd1e862a827523b45963bb36d5e9ac5f94ac82

[]

no_license

sungguenja/study_gui

0fc1e17c98a9afc0a6e66a39aeefcd89c3e60f5e

b058ca900061f2bd743f8532056ecedcc6b7ce0a

refs/heads/master

2021-01-16T16:32:28.027456

2020-03-17T16:54:21

243,184,712

0

null

UTF-8

Python

false

592

py

from tkinter import * def font_control(ev): label.config(font='HY헤드라인M {0} bold'.format(v.get())) if v.get()==40: label['text']='wa sans~' label['font']='굴림체 40 bold' else: label['text']='안녕 파이썬~' win=Tk() v=IntVar() win.geometry('300x150') label = Label(win, text='안녕 파이썬~') label.pack(fill='y',expand=1) sc = Scale(win, from_=10,to=40, orient=HORIZONTAL, variable=v, command=font_control) sc.pack(fill='x',expand=1) qbtn = Button(win,text='끝내기',command=win.quit, font='굴림 10 bold') qbtn.pack() win.mainloop()

[ "59605197+sungguenja@users.noreply.github.com" ]

59605197+sungguenja@users.noreply.github.com

d232fe89ca699bb27814c5684ea1ae3d2a1807b6

f9d564f1aa83eca45872dab7fbaa26dd48210d08

/huaweicloud-sdk-as/huaweicloudsdkas/v1/model/batch_remove_scaling_instances_request.py

bebca60ab39111f01f7c0e8379c57dbbff64a882

[ "Apache-2.0" ]

permissive

huaweicloud/huaweicloud-sdk-python-v3

cde6d849ce5b1de05ac5ebfd6153f27803837d84

f69344c1dadb79067746ddf9bfde4bddc18d5ecf

refs/heads/master

2023-09-01T19:29:43.013318

2023-08-31T08:28:59

262,207,814

103

44

NOASSERTION

2023-06-22T14:50:48

2020-05-08T02:28:43

Python

UTF-8

Python

false

4,211

py

# coding: utf-8 import six from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization class BatchRemoveScalingInstancesRequest: """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ sensitive_list = [] openapi_types = { 'scaling_group_id': 'str', 'body': 'BatchRemoveInstancesOption' } attribute_map = { 'scaling_group_id': 'scaling_group_id', 'body': 'body' } def __init__(self, scaling_group_id=None, body=None): """BatchRemoveScalingInstancesRequest The model defined in huaweicloud sdk :param scaling_group_id: 实例ID。 :type scaling_group_id: str :param body: Body of the BatchRemoveScalingInstancesRequest :type body: :class:`huaweicloudsdkas.v1.BatchRemoveInstancesOption` """ self._scaling_group_id = None self._body = None self.discriminator = None self.scaling_group_id = scaling_group_id if body is not None: self.body = body @property def scaling_group_id(self): """Gets the scaling_group_id of this BatchRemoveScalingInstancesRequest. 实例ID。 :return: The scaling_group_id of this BatchRemoveScalingInstancesRequest. :rtype: str """ return self._scaling_group_id @scaling_group_id.setter def scaling_group_id(self, scaling_group_id): """Sets the scaling_group_id of this BatchRemoveScalingInstancesRequest. 实例ID。 :param scaling_group_id: The scaling_group_id of this BatchRemoveScalingInstancesRequest. :type scaling_group_id: str """ self._scaling_group_id = scaling_group_id @property def body(self): """Gets the body of this BatchRemoveScalingInstancesRequest. :return: The body of this BatchRemoveScalingInstancesRequest. :rtype: :class:`huaweicloudsdkas.v1.BatchRemoveInstancesOption` """ return self._body @body.setter def body(self, body): """Sets the body of this BatchRemoveScalingInstancesRequest. :param body: The body of this BatchRemoveScalingInstancesRequest. :type body: :class:`huaweicloudsdkas.v1.BatchRemoveInstancesOption` """ self._body = body def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: if attr in self.sensitive_list: result[attr] = "****" else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" import simplejson as json if six.PY2: import sys reload(sys) sys.setdefaultencoding("utf-8") return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) def __repr__(self): """For `print`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, BatchRemoveScalingInstancesRequest): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "hwcloudsdk@huawei.com" ]

hwcloudsdk@huawei.com

14c7592a361aec866f6bbc9d904a1567aab1a1ec

ecd4b06d5d5368b71fd72a1c2191510a03b728fd

/3 - pandas foundation/austin case study/4.py

40ede74aea409c735ebd2a40bd4f6e624d3f96aa

[ "MIT" ]

permissive

Baidaly/datacamp-samples

86055db5e326b59bfdce732729c80d76bf44629e

37b4f78a967a429e0abca4a568da0eb9d58e4dff

refs/heads/master

2022-07-27T01:18:00.700386

2022-07-18T19:27:23

123,827,284

0

null

UTF-8

Python

false

642

py

# Convert the date column to string: df_dropped['date'] df_dropped['date'] = df_dropped['date'].astype(str) # Pad leading zeros to the Time column: df_dropped['Time'] df_dropped['Time'] = df_dropped['Time'].apply(lambda x:'{:0>4}'.format(x)) # Concatenate the new date and Time columns: date_string date_string = df_dropped['date'] + df_dropped['Time'] # Convert the date_string Series to datetime: date_times date_times = pd.to_datetime(date_string, format='%Y%m%d%H%M') # Set the index to be the new date_times container: df_clean df_clean = df_dropped.set_index(date_times) # Print the output of df_clean.head() print(df_clean.head())

[ "daulet.urazalinov@uptake.com" ]

daulet.urazalinov@uptake.com

1ed5f1cca9b1d29e15103ea5e148e811b1f53733

be526f8602651479f5b24eab9c91a3817e9bff0e

/word2vec_tensorboard.py

bc0a82bc12957315e14cf53c710a8cda0042d17f

[]

no_license

bage79/word2vec4kor

76a870c57a1a854ff3e3a00c955424b394723259

3dc8a856e22f79e8da27f74b3d55de474a599e8c

refs/heads/master

2021-04-27T11:33:00.869446

2018-05-08T14:12:45

122,564,641

11

1

null

UTF-8

Python

false

3,861

py

import argparse import os import pickle import traceback import warnings warnings.simplefilter(action='ignore', category=FutureWarning) import tensorflow as tf from tensorflow.contrib.tensorboard.plugins import projector def turn_off_tensorflow_logging(): import os import tensorflow as tf os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # ignore tensorflow warnings tf.logging.set_verbosity(tf.logging.ERROR) # ignore tensorflow info (GPU 할당 정보 확인) def word2vec_tensorboard(name, data_dir, tensorboard_dir, top_n=10000): turn_off_tensorflow_logging() try: if not os.path.exists(tensorboard_dir): os.mkdir(tensorboard_dir) for filename in os.listdir(tensorboard_dir): os.remove(os.path.join(tensorboard_dir, filename)) # remove old tensorboard files config = projector.ProjectorConfig() name = name.replace('+', '') idx2word = pickle.load(open(os.path.join(data_dir, 'idx2word.dat'), 'rb')) # word2idx = pickle.load(open('data/word2idx.dat', 'rb')) idx2vec = pickle.load(open(os.path.join(data_dir, 'idx2vec.dat'), 'rb')) wc = pickle.load(open(os.path.join(data_dir, 'wc.dat'), 'rb')) total = sum(wc.values()) # print('idx2word:', idx2word[:10]) # print('idx2vec:', idx2vec[1]) # print('wc:', list(wc.items())[:10]) print('total count:', total) idx2vec, idx2word = idx2vec[:top_n], idx2word[:top_n] embedding_var = tf.Variable(idx2vec, name=name) # print(data) embedding = config.embeddings.add() embedding.tensor_name = embedding_var.name embedding.metadata_path = os.path.join(tensorboard_dir, f'{name}.tsv') print('') print(f'embedding_var.name: {embedding_var.name} shape: {embedding_var.shape}') print(f'embedding.metadata_path: {embedding.metadata_path}') with open(embedding.metadata_path, 'wt') as out_f: out_f.write('spell\tfreq\n') for spell in idx2word: out_f.write(f'{spell}\t{wc.get(spell, 0)/total}\n') summary_writer = tf.summary.FileWriter(tensorboard_dir) projector.visualize_embeddings(summary_writer, config) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) saver = tf.train.Saver(var_list=[embedding_var]) checkpoint_file = os.path.join(tensorboard_dir, f'{name}.ckpt') saver.save(sess, checkpoint_file, global_step=None) print(f'checkpoint_file: {checkpoint_file}') # absolute path -> relative path for filename in ['checkpoint', 'projector_config.pbtxt']: filepath = os.path.join(tensorboard_dir, filename) lines = [] with open(filepath, 'rt') as f: for line in f.readlines(): lines.append(line.replace(tensorboard_dir, '.')) os.remove(filepath) with open(filepath, 'wt') as f: for line in lines: f.write(line) except: traceback.print_exc() if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--name', default='sample.ko.wikipedia', type=str, help="embedding name in tensorboard projector") parser.add_argument('--data_dir', default=os.path.join(os.getenv('HOME'), 'workspace/word2vec4kor/data'), type=str, help="data directory path") parser.add_argument('--tensorboard_dir', default=os.path.join(os.getenv('HOME'), 'tensorboard_log/'), type=str, help="tensorboard directory path") parser.add_argument('--top_n', default=10000, type=int, help='max number of vocaburary') args = parser.parse_args() word2vec_tensorboard(name=args.name, data_dir=args.data_dir, tensorboard_dir=args.tensorboard_dir, top_n=args.top_n)

[ "bage79@gmail.com" ]

bage79@gmail.com

782beba45b77ab5dd35b7a388087e5f618f0f266

62f59fe1e0246b33c84412ee2a60e77938a05a15

/test/zombie_task_test.py

97d79ca67f9031bb031c6eccabdd7eb9bba5e7e6

[]

no_license

20113261/platform_service

02676d2654f5c7bde2c7eafdadbf55fe7253a7b0

bc903168bd7cbc499892f24c2b1cc82c38180c01

refs/heads/dev

2022-08-01T02:30:05.004852

2018-04-29T05:39:37

131,576,306

1

0

null

2022-07-08T19:13:32

2018-04-30T09:14:54

Python

UTF-8

Python

false

1,113

py

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2017/10/26 下午6:28 # @Author : Hou Rong # @Site : # @File : zombie_task_test.py # @Software: PyCharm import datetime import pymongo client = pymongo.MongoClient(host='10.10.231.105') collections = client['MongoTask']['Task'] def monitoring_zombies_task(): try: cursor = collections.find( {'running': 1, 'utime': {'$lt': datetime.datetime.now() - datetime.timedelta(hours=1)}}, {'_id': 1}, hint=[('running', 1), ('utime', -1)]).limit( 10000) id_list = [id_dict['_id'] for id_dict in cursor] print(len(id_list)) result = collections.update({ '_id': { '$in': id_list } }, { '$set': { 'finished': 0, 'used_times': 0, 'running': 0 } }, multi=True) print(result) except Exception as e: print(e) if __name__ == '__main__': import time start = time.time() monitoring_zombies_task() print(time.time() - start)

[ "nmghr9@gmail.com" ]

nmghr9@gmail.com

d72d79bedd1d13883fc2cad393b334ee4aff8287

95495baeb47fd40b9a7ecb372b79d3847aa7a139

/test/test_metadata.py

4a4189f3e130f421154ba36b2d51d25b314c6960

[]

no_license

pt1988/fmc-api

b1d8ff110e12c13aa94d737f3fae9174578b019c

075f229585fcf9bd9486600200ff9efea5371912

refs/heads/main

2023-01-07T09:22:07.685524

2020-10-30T03:21:24

308,226,669

0

null

UTF-8

Python

false

1,142

py

# coding: utf-8 """ Cisco Firepower Management Center Open API Specification **Specifies the REST URLs and methods supported in the Cisco Firepower Management Center API. Refer to the version specific [REST API Quick Start Guide](https://www.cisco.com/c/en/us/support/security/defense-center/products-programming-reference-guides-list.html) for additional information.** # noqa: E501 OpenAPI spec version: 1.0.0 Contact: tac@cisco.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import swagger_client from swagger_client.models.metadata import Metadata # noqa: E501 from swagger_client.rest import ApiException class TestMetadata(unittest.TestCase): """Metadata unit test stubs""" def setUp(self): pass def tearDown(self): pass def testMetadata(self): """Test Metadata""" # FIXME: construct object with mandatory attributes with example values # model = swagger_client.models.metadata.Metadata() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "pt1988@gmail.com" ]

pt1988@gmail.com

0af742a6da7d3a491d33c665d6821b55a52e9e22

451e3188ef94bfd106a0194774c23edd0bba84a2

/blog/migrations/0011_auto_20190624_1757.py

32bf1b8e4505dacd5f6698621a22e1552d94538a

[]

no_license

Dolidodzik/Wagtail-Django-Static-Blog

fe9c8caf63275c8f444ac7b898e7e0d67fae018a

db0769da8c7b1c3fc450fe40181bfcf984079ec1

refs/heads/master

2020-06-08T02:13:32.401772

2019-10-29T17:09:09

193,139,774

0

null

UTF-8

Python

false

1,218

py

# Generated by Django 2.2.2 on 2019-06-24 17:57 from django.db import migrations import wagtail.core.blocks import wagtail.core.fields import wagtail.images.blocks class Migration(migrations.Migration): dependencies = [ ('blog', '0010_auto_20190624_1749'), ] operations = [ migrations.AlterField( model_name='blogindexpage', name='body', field=wagtail.core.fields.StreamField([('heading', wagtail.core.blocks.CharBlock(classname='full title')), ('paragraph', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock()), ('gallery', wagtail.core.blocks.StreamBlock([('image', wagtail.images.blocks.ImageChooserBlock())], label='image gallery'))]), ), migrations.AlterField( model_name='blogpage', name='body', field=wagtail.core.fields.StreamField([('heading', wagtail.core.blocks.CharBlock(classname='full title')), ('paragraph', wagtail.core.blocks.RichTextBlock()), ('image', wagtail.images.blocks.ImageChooserBlock()), ('gallery', wagtail.core.blocks.StreamBlock([('image', wagtail.images.blocks.ImageChooserBlock())], label='image gallery'))]), ), ]

[ "teethtard321@gmail.com" ]

teethtard321@gmail.com

dc8423b42f23e5e62b109260c92631277dd9f347

20860030d52b5be62cb797e396a5a6b83f45dc44

/configuration-api/src/__init__.py

cf8683bda4fd470b0adb1d974c85ba42670d64d7

[]

no_license

rcosnita/bravehub

189d30c46224dd80d6fbf41c50a33559ec2f44ae

960bcfdb3c2e53e81aa75f7a48980e4918cfd4bb

refs/heads/master

2022-12-21T11:28:16.626690

2018-02-17T10:43:09

98,259,347

0

1

null

2022-12-19T13:27:11

2017-07-25T03:17:44

Python

UTF-8

Python

false

396

py

"""Initializes some configuration parameters which are used in the implementation of configuration-api microservice.""" from src.ioc import ConfigurationApiContainer API_VERSION = ConfigurationApiContainer.api_meta.version API_FULL_VERSION = "{0}.{1}.{2}".format(API_VERSION.major, API_VERSION.minor, API_VERSION.patch) API_MAJOR_VERSION = "{0}.{1}".format(API_VERSION.major, API_VERSION.minor)

[ "radu.cosnita@gmail.com" ]

radu.cosnita@gmail.com

49f713c4ee1d37d24c760dd5a7d2afcca4e2a2f2

6359831db732f929409adbb8270092c7e9cca8d5

/Q046_Vertical_traversal_of_binary_trees.py

a8f43145ca2853b7a89f408b9807b11bd25a2276

[]

no_license

latika18/interviewbit

11237219d982c98a22f0098be8248ef7a5b9246f

a065b19dc368136101dafbbbdab9b664fed0bf35

refs/heads/master

2020-03-15T15:20:30.002201

2018-08-22T07:39:21

132,209,831

0

null

UTF-8

Python

false

1,336

py

Given a binary tree, print a vertical order traversal of it. Example : Given binary tree: 6 / \ 3 7 / \ \ 2 5 9 returns [ [2], [3], [6 5], [7], [9] ] Note : If 2 Tree Nodes shares the same vertical level then the one with lesser depth will come first. Code: # Definition for a binary tree node # class TreeNode: # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution: # @param A : root node of tree # @return a list of list of integers def verticalordertraversal(self,root): visited = [] hashmap = {} ## hashmap to map hd to elements hd = 0 ## horizontal distance level = 0 if root: visited.append(root) hashmap[hd] = root current = root while current: if current.left: hashmap[hd-1] = current.left.value visited.append(current.left) if current.right: hashmap[hd+1] = current.right.value visited.append(current.right) visited.pop(0) if not visited: break hd = hd+1 current = visited[0] return hashmap

[ "noreply@github.com" ]

latika18.noreply@github.com

4d062caff31b114960dd1f54eb12dceb00549788

df5ed643835e0759b326b9c3ad2f96a945b1519f

/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/turtledemo/penrose.py

c913c6312d53a0f6dfd5900a4ee1c1972cf95f4c

[ "MIT" ]

permissive

keith/Xcode.app-strings

8182a6b5272e5763111ddf376818aca277f113d3

c3c93e5b349425159172bb62e9929b701de26a87

refs/heads/main

2023-08-30T22:31:13.291293

2023-08-29T18:19:23

75,589,712

91

28

null

UTF-8

Python

false

3,358

py

#!/usr/bin/env python3 """ xturtle-example-suite: xtx_kites_and_darts.py Constructs two aperiodic penrose-tilings, consisting of kites and darts, by the method of inflation in six steps. Starting points are the patterns "sun" consisting of five kites and "star" consisting of five darts. For more information see: http://en.wikipedia.org/wiki/Penrose_tiling ------------------------------------------- from turtle import * from math import cos, pi from time import perf_counter as clock, sleep f = (5**0.5-1)/2.0 # (sqrt(5)-1)/2 -- golden ratio d = 2 * cos(3*pi/10) def kite(l): fl = f * l lt(36) fd(l) rt(108) fd(fl) rt(36) fd(fl) rt(108) fd(l) rt(144) def dart(l): fl = f * l lt(36) fd(l) rt(144) fd(fl) lt(36) fd(fl) rt(144) fd(l) rt(144) def inflatekite(l, n): if n == 0: px, py = pos() h, x, y = int(heading()), round(px,3), round(py,3) tiledict[(h,x,y)] = True return fl = f * l lt(36) inflatedart(fl, n-1) fd(l) rt(144) inflatekite(fl, n-1) lt(18) fd(l*d) rt(162) inflatekite(fl, n-1) lt(36) fd(l) rt(180) inflatedart(fl, n-1) lt(36) def inflatedart(l, n): if n == 0: px, py = pos() h, x, y = int(heading()), round(px,3), round(py,3) tiledict[(h,x,y)] = False return fl = f * l inflatekite(fl, n-1) lt(36) fd(l) rt(180) inflatedart(fl, n-1) lt(54) fd(l*d) rt(126) inflatedart(fl, n-1) fd(l) rt(144) def draw(l, n, th=2): clear() l = l * f**n shapesize(l/100.0, l/100.0, th) for k in tiledict: h, x, y = k setpos(x, y) setheading(h) if tiledict[k]: shape("kite") color("black", (0, 0.75, 0)) else: shape("dart") color("black", (0.75, 0, 0)) stamp() def sun(l, n): for i in range(5): inflatekite(l, n) lt(72) def star(l,n): for i in range(5): inflatedart(l, n) lt(72) def makeshapes(): tracer(0) begin_poly() kite(100) end_poly() register_shape("kite", get_poly()) begin_poly() dart(100) end_poly() register_shape("dart", get_poly()) tracer(1) def start(): reset() ht() pu() makeshapes() resizemode("user") def test(l=200, n=4, fun=sun, startpos=(0,0), th=2): global tiledict goto(startpos) setheading(0) tiledict = {} tracer(0) fun(l, n) draw(l, n, th) tracer(1) nk = len([x for x in tiledict if tiledict[x]]) nd = len([x for x in tiledict if not tiledict[x]]) print("%d kites and %d darts = %d pieces." % (nk, nd, nk+nd)) def demo(fun=sun): start() for i in range(8): a = clock() test(300, i, fun) b = clock() t = b - a if t < 2: sleep(2 - t) def main(): #title("Penrose-tiling with kites and darts.") mode("logo") bgcolor(0.3, 0.3, 0) demo(sun) sleep(2) demo(star) pencolor("black") goto(0,-200) pencolor(0.7,0.7,1) write("Please wait...", align="center", font=('Arial Black', 36, 'bold')) test(600, 8, startpos=(70, 117)) return "Done" if __name__ == "__main__": msg = main() mainloop()

[ "keithbsmiley@gmail.com" ]

keithbsmiley@gmail.com

994535b97312d7b201e3c3ece5776069e47d98fd

1269530d9534b563879d8e995fecf67196287719

/check_size_mlstm.py

40a5c8f3dcd4d109b5f841f02994af78f278d6a3

[]

no_license

amirunpri2018/Keras-Multiplicative-LSTM

a7ff7eea2d9b8ba1ae15efa7759eb5510fe6fabe

3c89fed3ac45d84072bc2712a895e479b657e457

refs/heads/master

2020-04-08T03:37:47.274723

2017-11-04T03:04:22

null

0

null

UTF-8

Python

false

686

py

import multiplicative_lstm from keras.layers import Input, LSTM from keras.models import Model ip = Input(shape=(1, 100)) lstm = LSTM(128)(ip) mlstm = multiplicative_lstm.MultiplicativeLSTM(128)(ip) lstm_model = Model(ip, lstm) mlstm_model = Model(ip, mlstm) lstm_model.summary() print('\n' * 3) mlstm_model.summary() print('\n' * 3) params_count_lstm = lstm_model.count_params() params_count_mlstm = mlstm_model.count_params() param_ratio = params_count_mlstm / float(params_count_lstm) if param_ratio != 1.25: print("Param count (mlstm) / Param count (lstm) = %0.2f, should be close to 1.25" % (param_ratio)) print("Size ratio of mLSTM to LSTM is %0.2f!" % (param_ratio))

[ "titu1994@gmail.com" ]

titu1994@gmail.com

f69ee0ebd58b2cd9df04217cbdb83c8b95f62007

f6b5799c13fad2382d638a1208f4972ce818174a

/site/PROGRAMMERS/src/python/스킬테스트/level01/콜라츠추측.py

9da7b4527830f6a02e0a2ca40eba22dd9e88d4e1

[]

no_license

JoonBeomLee/Algorithm_Python

6bf0cc29ffaf75156bfa44ea531c33b3d2b2a129

185fb39d535573c374f1d0d88f728f97086a4246

refs/heads/master

2023-06-11T10:27:10.228151

2021-07-05T14:59:40

193,500,999

1

0

null

UTF-8

Python

false

368

py

def solution(num): answer = 0 while True: if(num == 1): break if(answer == 500): answer = -1; break # 짝수 if num % 2 == 0: num = num / 2 # 홀수 elif num % 2 != 0: num = 3 * num + 1 answer += 1 return answer

[ "jbl9595@naver.com" ]

jbl9595@naver.com

28623c7e7bcdf0aaaff6991949f05be9d2bc310d

e2992452a3c52f4cbbc64e1686128ad464b71d16

/weixinSource/weixinSource/pipelines.py

aeba7ce32ab3fe5a82d68511a812978bede5574e

[]

no_license

MaGuiSen/studyScrapy

6b84605a15027ffc24501d690666f419ebb379fd

03604bafe19e55db12677a4af388c8a9198ca572

refs/heads/master

2021-01-17T04:30:23.858217

2017-08-30T01:50:08

95,433,695

0

1

null

UTF-8

Python

false

292

py

# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html class WeixinsourcePipeline(object): def process_item(self, item, spider): return item

[ "1059876295@qq.com" ]

1059876295@qq.com

0eec3d555e4db9f9548824002788e9b95e60b91e

dd4d2589d1f14303cacd3b7ee1dd5f6bacd3bf3c

/matrix/spiral_matrix_2.py

ed14ac09091d56c65841453b2f11ee3ea40c813a

[]

no_license

salujaharkirat/ds-algo

ec22eaae81bdb78f2818248508325a536aedbb7b

819b5971826d97ec600b92776c5158518c9cbf22

refs/heads/master

2023-05-02T17:20:49.425484

2021-05-23T07:54:29

null

0

null

UTF-8

Python

false

1,339

py

""" https://leetcode.com/problems/spiral-matrix-ii/ """ import numpy as np class Solution: def generateMatrix(self, n: int) -> List[List[int]]: res = [] for i in range(n): res.append([0] * n) left = 0 right = n - 1 top = 0 bottom = n - 1 direction = 0 cnt = 1 while left <= right and top <= bottom: if direction == 0: for i in range(left, right+1): res[top][i] = cnt cnt += 1 top += 1 direction = 1 elif direction == 1: for i in range(top, bottom+1): res[i][right] = cnt cnt += 1 right -= 1 direction = 2 elif direction == 2: for i in reversed(range(left, right+1)): # res.append(cnt) res[bottom][i] = cnt cnt += 1 bottom -= 1 direction = 3 elif direction == 3: for i in reversed(range(top, bottom+1)): # res.append(cnt) res[i][left] = cnt cnt += 1 left += 1 direction = 0 return res

[ "saluja.harkirat@gmail.com" ]

saluja.harkirat@gmail.com

d7cdd4c62c61f62e1d8c309bc87f77c4949eadd9

9e988c0dfbea15cd23a3de860cb0c88c3dcdbd97

/sdBs/AllRun/sbss_1655+591/sdB_sbss_1655+591_coadd.py

f030d65a0471c8af9f04c2583c5c8ff5c0bbeec1

[]

no_license

tboudreaux/SummerSTScICode

73b2e5839b10c0bf733808f4316d34be91c5a3bd

4dd1ffbb09e0a599257d21872f9d62b5420028b0

refs/heads/master

2021-01-20T18:07:44.723496

2016-08-08T16:49:53

65,221,159

0

null

UTF-8

Python

false

438

py

from gPhoton.gMap import gMap def main(): gMap(band="NUV", skypos=[254.127958,59.079469], skyrange=[0.0333333333333,0.0333333333333], stepsz = 30., cntfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdBs/sdB_sbss_1655+591/sdB_sbss_1655+591_movie_count.fits", cntcoaddfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdB/sdB_sbss_1655+591/sdB_sbss_1655+591_count_coadd.fits", overwrite=True, verbose=3) if __name__ == "__main__": main()

[ "thomas@boudreauxmail.com" ]

thomas@boudreauxmail.com

81d2acb91a751c6699bd377dc4694798e495f094

634514a9c10e32051964b179cc807d089d31124e

/S2l/Thesis_Ch3/Exp1_reach3dof/Scripts/plotter_episodes.py

c705777868308749f11d14705ce7c42a4bc061d3

[ "LicenseRef-scancode-generic-cla", "MIT" ]

permissive

leopauly/Observation-Learning-Simulations

34009872a1f453ffc4ae7ddced7447a74ff704c4

462c04a87c45aae51537b8ea5b44646afa31d3a5

refs/heads/master

2021-08-04T10:55:42.900015

2021-07-05T13:41:09

129,761,220

0

null

UTF-8

Python

false

528

py

#### For plotting from reawrd values stored in files import numpy as np import matplotlib.pyplot as plt import sys run=sys.argv[1] y = np.loadtxt('episode_reward_run_'+run+'.txt', unpack=True) y_new=y[1:len(y)] x=range(len(y_new)) print(x,y_new) plt.figure(1) plt.plot(x,y_new) plt.title('Reward') plt.xlabel('episodes') plt.ylabel('reward per episeodes') plt.show() y_new=-np.array(y_new) plt.figure(2) plt.plot(x,y_new) plt.title('Feature distance') plt.xlabel('episodes') plt.ylabel('reward per episodes') plt.show()

[ "meetleopauly@yahoo.com" ]

meetleopauly@yahoo.com

32d769360c3b3706f42a2f42c8b12903939383f8

9b1446b26e81a79c303f9799fb6a91785c7adb03

/.history/Code/markov_chain_20200120225120.py

c8637afc95c9347859961865560d6e5a25020a0a

[]

no_license

SamirIngley/CS1.2-Tweet-Gen

017ea15b1113881a156ff24682828bc654eb6c81

bcd95fa63e05849cbf8e36230d8e31032b99daaa

refs/heads/master

2020-12-14T20:19:57.733290

2020-08-04T23:19:23

234,856,234

0

null

2020-06-05T21:13:04

2020-01-19T07:05:55

Python

UTF-8

Python

false

794

py

import sample from clean_text import clean class Markov(): def __init__(self, corpus): self.corpus = corpus self.states = {} self.chain() def chain(self): last_word = None for word in self.corpus: if last_word is not None: # set last word line 14 if last_word not in self.states: # if we haven't seen this word before self.states[last_word] = Dictogram() # empty histogram as value self[last_word].add_count(word) # add word to last word histogram last_word = word # set word as last_word def __str__(self): return str(self.states) if __name__ == '__main__': source = 'one fish two fish red fish blue fish' print(markov(source))

[ "samir.ingle7@gmail.com" ]

samir.ingle7@gmail.com

61b0a836a83e88645081bc1ab3f28d2beac4fce3

2337351b228818e41be3002bd38f68f77c2aa074

/core/confdb/syntax/protocols/lldp/hints.py

3b89367275377af955519b66880edf74dbe19045

[ "BSD-3-Clause" ]

permissive

nocproject/noc

57d40c680a1499374463e472434f9595ed6d1374

6e6d71574e9b9d822bec572cc629a0ea73604a59

refs/heads/master

2023-08-31T01:11:33.544573

2023-08-30T17:31:11

107,815,776

105

33

BSD-3-Clause

2023-07-31T07:57:45

2017-10-21T21:04:33

Python

UTF-8

Python

false

839

py

# ---------------------------------------------------------------------- # ConfDB hints protocols lldp syntax # ---------------------------------------------------------------------- # Copyright (C) 2007-2019 The NOC Project # See LICENSE for details # ---------------------------------------------------------------------- # NOC modules from ...defs import DEF from ...patterns import BOOL, IF_NAME HINTS_PROTOCOLS_LLDP = DEF( "lldp", [ DEF("status", [DEF(BOOL, name="status", required=True, gen="make_global_lldp_status")]), DEF( "interface", [ DEF( IF_NAME, [DEF("off", gen="make_lldp_interface_disable")], multi=True, name="interface", ) ], ), ], )

[ "dv@nocproject.org" ]

dv@nocproject.org

c3e795fbfe3826d2f5904f7e97ae0c1ae14fa894

3644db13925e6d518a9637edafa6247547ca90b4

/interprocedural_analyses/taint/test/integration/functions_as_locals.py

f4f5aa681cb6601056ece250cd511564f500a956

[ "MIT" ]

permissive

luizribeiro/pyre-check

348699cecf82a5aa36f5e1301076cb006a2fb9f9

42d1fced8cbb94c4c9400d6fddd798e50d331ab9

refs/heads/master

2023-04-17T17:26:23.262598

2020-08-08T04:03:04

2020-08-08T04:03:35

285,969,507

0

MIT

2023-04-04T01:56:30

2020-08-08T04:01:31

OCaml

UTF-8

Python

false

675

py

# flake8: noqa from builtins import __test_sink, __test_source def foo(arg): __test_sink(arg) def foo_as_local(): x = __test_source() f = foo foo(x) f(x) def local_tito(arg): f = foo f(arg) class C: def m(self, arg): __test_sink(arg) def local_function_with_method_sink(c: C): f = c.m x = __test_source() c.m(x) f(x) def method_tito(c: C, arg): f = c.m f(arg) def barA(arg1: str, arg2: str): __test_sink(arg1) def barB(arg1: str, arg2: int): __test_sink(arg2) def a_or_b(): if 1 > 2: f = barA else: f = barB f(__test_source(), 0) f(0, __test_source())

[ "facebook-github-bot@users.noreply.github.com" ]

facebook-github-bot@users.noreply.github.com

c6b23600f363b1173b40bde086cf7afccd9b839d

6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4

/dQZmkrPaKdtSat5f9_6.py

326adc8b9d5d878706b0607ed434207c59a78551

[]

no_license

daniel-reich/ubiquitous-fiesta

26e80f0082f8589e51d359ce7953117a3da7d38c

9af2700dbe59284f5697e612491499841a6c126f

refs/heads/master

2023-04-05T06:40:37.328213

2021-04-06T20:17:44

355,318,759

0

null

UTF-8

Python

false

312

py

def single_occurrence(txt): txt = txt.upper() Answer = "" Counter = 0 Length = len(txt) while (Counter < Length): Item = txt[Counter] Events = txt.count(Item) if (Events == 1): Answer = Item return Answer else: Counter += 1 return Answer

[ "daniel.reich@danielreichs-MacBook-Pro.local" ]

daniel.reich@danielreichs-MacBook-Pro.local

079956603181043e047fcfcd8ae48b9209a73544

596e92d0d484b6e7eee6d322e72e52748fdeaa5d

/sportsdata/mlb_projections/models/mlb_projections_dfs_slate_game.py

4aadebaeb66acdeb4d93f89a1e1c5748361edf13

[]

no_license

scottypate/sportsdata

f5f61ddc7eb482883f93737c6ce73dd814ed4336

a07955ab50bf4fff1ce114ed9895095ff770c473

refs/heads/main

2023-08-18T16:51:56.452678

2021-10-22T12:44:08

420,062,350

1

null

UTF-8

Python

false

7,117

py

# coding: utf-8 """ MLB v3 Projections MLB projections API. # noqa: E501 OpenAPI spec version: 1.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six class MlbProjectionsDfsSlateGame(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'slate_game_id': 'int', 'slate_id': 'int', 'game_id': 'int', 'game': 'MlbProjectionsGame', 'operator_game_id': 'int', 'removed_by_operator': 'bool' } attribute_map = { 'slate_game_id': 'SlateGameID', 'slate_id': 'SlateID', 'game_id': 'GameID', 'game': 'Game', 'operator_game_id': 'OperatorGameID', 'removed_by_operator': 'RemovedByOperator' } def __init__(self, slate_game_id=None, slate_id=None, game_id=None, game=None, operator_game_id=None, removed_by_operator=None): # noqa: E501 """MlbProjectionsDfsSlateGame - a model defined in Swagger""" # noqa: E501 self._slate_game_id = None self._slate_id = None self._game_id = None self._game = None self._operator_game_id = None self._removed_by_operator = None self.discriminator = None if slate_game_id is not None: self.slate_game_id = slate_game_id if slate_id is not None: self.slate_id = slate_id if game_id is not None: self.game_id = game_id if game is not None: self.game = game if operator_game_id is not None: self.operator_game_id = operator_game_id if removed_by_operator is not None: self.removed_by_operator = removed_by_operator @property def slate_game_id(self): """Gets the slate_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The slate_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: int """ return self._slate_game_id @slate_game_id.setter def slate_game_id(self, slate_game_id): """Sets the slate_game_id of this MlbProjectionsDfsSlateGame. :param slate_game_id: The slate_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: int """ self._slate_game_id = slate_game_id @property def slate_id(self): """Gets the slate_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The slate_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: int """ return self._slate_id @slate_id.setter def slate_id(self, slate_id): """Sets the slate_id of this MlbProjectionsDfsSlateGame. :param slate_id: The slate_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: int """ self._slate_id = slate_id @property def game_id(self): """Gets the game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: int """ return self._game_id @game_id.setter def game_id(self, game_id): """Sets the game_id of this MlbProjectionsDfsSlateGame. :param game_id: The game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: int """ self._game_id = game_id @property def game(self): """Gets the game of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The game of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: MlbProjectionsGame """ return self._game @game.setter def game(self, game): """Sets the game of this MlbProjectionsDfsSlateGame. :param game: The game of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: MlbProjectionsGame """ self._game = game @property def operator_game_id(self): """Gets the operator_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The operator_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: int """ return self._operator_game_id @operator_game_id.setter def operator_game_id(self, operator_game_id): """Sets the operator_game_id of this MlbProjectionsDfsSlateGame. :param operator_game_id: The operator_game_id of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: int """ self._operator_game_id = operator_game_id @property def removed_by_operator(self): """Gets the removed_by_operator of this MlbProjectionsDfsSlateGame. # noqa: E501 :return: The removed_by_operator of this MlbProjectionsDfsSlateGame. # noqa: E501 :rtype: bool """ return self._removed_by_operator @removed_by_operator.setter def removed_by_operator(self, removed_by_operator): """Sets the removed_by_operator of this MlbProjectionsDfsSlateGame. :param removed_by_operator: The removed_by_operator of this MlbProjectionsDfsSlateGame. # noqa: E501 :type: bool """ self._removed_by_operator = removed_by_operator def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value if issubclass(MlbProjectionsDfsSlateGame, dict): for key, value in self.items(): result[key] = value return result 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, MlbProjectionsDfsSlateGame): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "scotty.pate@auth0.com" ]

scotty.pate@auth0.com

318cd859b70a41e212785c1596ffdf88353bce76

98c6ea9c884152e8340605a706efefbea6170be5

/examples/data/Assignment_7/snxkai001/util.py

217a94e3e61b1d0258092af7a9640f7e96345ae2

[]

no_license

MrHamdulay/csc3-capstone

479d659e1dcd28040e83ebd9e3374d0ccc0c6817

6f0fa0fa1555ceb1b0fb33f25e9694e68b6a53d2

refs/heads/master

2021-03-12T21:55:57.781339

2014-09-22T02:22:22

22,372,174

0

null

UTF-8

Python

false

2,079

py

def create_grid (grid): for u in range(4): grid.append([]) for down in range(4): grid[u].append(0) def print_grid(grid): print("+" + "-"*20 + "+") allign= "{0:" "<5}" for row in range(4): print("|", end="") for col in range(4): if grid[row][col] != 0: print(allign.format(grid[row][col]), end="") else: print(allign.format(" "), end= "") print("|") print("+" + "-"*20 + "+") def check_lost(grid): for kol in range(4): for lef in range(4): if grid[kol][lef]==0: return False else: continue for n in range(4): for m in range(3): if grid[m][n]==grid[m+1][n]: return False else: continue for i in range(4): for j in range(3): if grid[i][j]==grid[i][j+1]: return False else: continue return True def check_won(grid): for i in range(4): for p in range(4): if grid[i][p]>=32: return True else: continue return False def grid_equal(grid1, grid2): for i in range(4): for j in range(4): if grid1[i][j]==grid2[i][j]: continue else: return False return True def copy_grid(grid): list1=[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]] for col in range(4): for row in range(4): list1[col][row]=grid[col][row] return list1

[ "jarr2000@gmail.com" ]

jarr2000@gmail.com

39e716c97c55b1ae0ce73788baea20aa77976d3b

9508879fcf1cff718f3fe80502baff8b82c04427

/data_structures_domain/linked_lists/print_in_reverse.py

9e70be3bfc61fc9bdc1e648101f1a043b9f0ec55

[]

no_license

davidozhang/hackerrank

e37b4aace7d63c8be10b0d4d2bffb4d34d401d55

bdc40d6ff3e603949eb294bbc02a1e24a4ba5b80

refs/heads/master

2021-05-04T11:31:59.110118

2017-11-15T09:17:27

47,906,672

1

0

null

UTF-8

Python

false

529

py

""" Print elements of a linked list in reverse order as standard output head could be None as well for empty list Node is defined as class Node(object): def __init__(self, data=None, next_node=None): self.data = data self.next = next_node """ def ReversePrint(head): if not head: return ReversePrint(head.next) print head.data ''' Cleaner implementation October 1, 2016 ''' def ReversePrint(head): if head is not None: ReversePrint(head.next) print head.data

[ "davzee@hotmail.com" ]

davzee@hotmail.com

54601c3faba97921513238671d4defe422ee9d46

d3eb732ffd738d3a624196f0971e4c29f85f6673

/maptool.py

57b5b053df938d8e44ecddd90a5bd11d4c5471b6

[]

no_license

kailIII/mgrs-tools

c44aae9542e9883e9e1a395217b468bea4fb0788

3ac612bdf980f2d61f27d417c709115890af415f

refs/heads/master

2021-01-15T16:57:14.768002

2015-04-01T12:15:10

null

0

null

UTF-8

Python

false

955

py

import mgrs from qgis.core import * from qgis.gui import * from qgis.utils import iface from PyQt4.QtCore import * class MGRSMapTool(QgsMapTool): ct = mgrs.MGRS() epsg4326 = QgsCoordinateReferenceSystem("EPSG:4326") def __init__(self, canvas): QgsMapTool.__init__(self, canvas) self.setCursor(Qt.CrossCursor) def canvasMoveEvent(self, e): pt = self.toMapCoordinates(e.pos()) canvas = iface.mapCanvas() canvasCrs = canvas.mapRenderer().destinationCrs() transform = QgsCoordinateTransform(canvasCrs, self.epsg4326) pt4326 = transform.transform(pt.x(), pt.y()) try: mgrsCoords = self.ct.toMGRS(pt4326.y(), pt4326.x()) iface.mainWindow().statusBar().showMessage("MGRS Coordinate: " + mgrsCoords) except: iface.mainWindow().statusBar().showMessage("")

[ "volayaf@gmail.com" ]

volayaf@gmail.com

7ceceed258eb306cbc6fee57056ca756971ba8da

df1cb33bfe99a1e72cf75931749163b7c8731757

/stages/stage3.py

012d626c02d661dbc7a2f17848fc0e501c06bcb9

[]

no_license

orf/wikilink_py

2d6ae9dd64264fdf17995980ed8a4a960c199c5b

6643397e220970a93dab1e50e120748bfdc3bf19

refs/heads/master

2021-01-22T11:55:16.906965

2014-01-08T20:49:38

null

0

null

UTF-8

Python

false

7,415

py

from lib.progress import run_with_progressbar from lib.formatters.Neo4jFormatter import Neo4jFormatter from lib.formatters.CSVFormatter import MultiCSVFormatter import functools import os import logging import sys import itertools import __pypy__ import json logger = logging.getLogger() logger.addHandler(logging.StreamHandler(sys.stdout)) logger.setLevel(logging.INFO) STAGE3_TITLES_TO_ID = {} STAGE3_ID_TO_DATA = {} FLAG_REDIRECT = 1 FLAG_SEEN = 2 def handle_stage1_line(line): # There is one page in stage1.csv who's title is a unicode NEXT_LINE character (\x85). # As such we have to encode each line individually. # https://en.wikipedia.org/w/api.php?action=query&prop=info&pageids=28644448&inprop=url page_id, page_title, is_redirect = unicode(line.strip("\n"), "utf-8").split("|") flags = FLAG_REDIRECT if is_redirect == "1" else 0 STAGE3_TITLES_TO_ID[page_title] = int(page_id) STAGE3_ID_TO_DATA[int(page_id)] = (page_title, flags) #yield (page_title, flags), int(page_id) def get_ids_from_titles(titles_list, get_none=False): """ I take a list of titles and return a list of integer ID's. If get_none is True then the return list will contain None values where the title cannot be found. """ returner = [] for title in titles_list: x = STAGE3_TITLES_TO_ID.get(title, 0) if x is not 0 or get_none is True: returner.append(x) # Keeping all elements uniform might increase performance return returner def get_page_data_from_id(page_id, update_seen=True): """ I take a page ID and I return a tuple containing the title, is_redirect flag and a value indicating if this page ID has been queried before. """ p_data = STAGE3_ID_TO_DATA.get(page_id, None) if p_data is None: return None if update_seen: STAGE3_ID_TO_DATA[page_id] = (p_data[0], p_data[1] | FLAG_SEEN) return p_data def set_page_redirect(title, to): """ I replace a page title with the ID of the page it links to """ STAGE3_TITLES_TO_ID[title] = to def delete_page(title, page_id): """ I take a page ID and/or I delete it from our registry """ if title: del STAGE3_TITLES_TO_ID[title] if page_id: del STAGE3_ID_TO_DATA[page_id] def split_page_info(line, update_seen=True, get_none=False, get_links=True): """ I take a line outputted from Stage2 and I return (the_id, page_links, page_info) """ line = line.rstrip("\n") split_line = line.split("|") page_id = int(split_line[0]) page_info = get_page_data_from_id(page_id, update_seen=update_seen) if page_info is None: return None, None, None # Using islice like this keeps memory down by avoiding creating another list, it also doens't need a len() call # so it might be faster. whatever. page_links = itertools.islice(split_line, 1, sys.maxint) return page_id, get_ids_from_titles(page_links, get_none) if get_links else page_links, page_info def stage3_pre(line): """ We need to sort out redirects so they point to the correct pages. We do this by loading stage2.csv which contains ID|link_title|link_title... and get the ID's of the links """ page_id, page_links, page_info = split_page_info(unicode(line, "utf-8"), update_seen=False, get_links=False) if page_info and page_info[1] & FLAG_REDIRECT: # Are we a redirect? page_links = get_ids_from_titles(page_links, True) page_title = page_info[0] if len(page_links) > 1 and page_links[0]: # Point the redirect page to the ID of the page it redirects to set_page_redirect(page_title, page_links[0]) delete_page(None, page_id) else: # The page we are redirecting to cannot be found, remove the redirect page. delete_page(page_title, page_id) def stage3(line, output_format="neo"): """ I combine the results from the previous stages into a single cohesive file """ global STAGE3_ROW_COUNTER page_id, page_links, page_info = split_page_info(unicode(line.strip("\n"), "utf-8"), get_links=False) if page_info is None: # Ignore redirects for now return None page_title, flags = page_info #print "flags: %s" % flags if not flags & FLAG_REDIRECT: page_links = get_ids_from_titles(page_links, False) if flags & FLAG_SEEN: # Already visited this page before, output to an SQL file instead if output_format == "neo": return None, "\n".join(["%s\t%s" % (page_id, link_id) for link_id in set(page_links)]) else: with open('stage3.sql', 'a') as fd: fd.write("UPDATE pages SET links = uniq(array_cat(links, ARRAY[%s]::integer[])) WHERE id = %s;\n" % (",".join(map(str, set(page_links))), page_id)) else: # CSV output # id, title, is_redirect, links_array if output_format == "neo": #return u"({id:%s, name:%s})" % (page_id, json.dumps(page_title).encode("unicode-escape")) return ("%s\t%s\n" % (page_id, page_title)).encode("utf-8"),\ "%s\n" % "\n".join(["%s\t%s" % (page_id, link_id) for link_id in set(page_links)]) #return ((page_id, page_title),), else: return "%s|%s|%s|{%s}\n" % (page_id, page_title, is_redirect, ",".join(map(str, set(page_links)))) if __name__ == "__main__": logger.info("Loading stage1.csv into memory") with open("stage1.csv", 'rb', buffering=1024*1024) as csv_fd: run_with_progressbar(csv_fd, None, handle_stage1_line, os.path.getsize("stage1.csv")) logger.info("Loaded %s/%s page infos. Strategies: %s and %s" % (len(STAGE3_TITLES_TO_ID), len(STAGE3_ID_TO_DATA), __pypy__.dictstrategy(STAGE3_ID_TO_DATA), __pypy__.dictstrategy(STAGE3_TITLES_TO_ID))) with open("stage2.csv", "rb", buffering=1024*1024) as input_fd: run_with_progressbar(input_fd, None, stage3_pre, os.path.getsize("stage2.csv")) logger.info("Have %s/%s page infos. Strategies: %s and %s" % (len(STAGE3_TITLES_TO_ID), len(STAGE3_ID_TO_DATA), __pypy__.dictstrategy(STAGE3_ID_TO_DATA), __pypy__.dictstrategy(STAGE3_TITLES_TO_ID))) logger.info("Starting dump") with open('stage2.csv', "rb", buffering=1024*1024*8) as input_fd: # , encoding="utf-8", buffering=1024*8 with open('stage3.nodes', mode="wb", buffering=1024*1024*8) as nodes_fd: with open('stage3.links', mode="wb", buffering=1024*1024*20) as links_fd: formatter = MultiCSVFormatter(((nodes_fd, ("id:int:node_id", "title:string")), (links_fd, ("id:int:node_id", "id:int:node_id")))) run_with_progressbar(input_fd, None, functools.partial(stage3, output_format="neo"), os.path.getsize("stage2.csv"), formatter=formatter)

[ "tom@tomforb.es" ]

tom@tomforb.es

92df4a82b4256ff8f683501f22e0c09dbea8b0c0

b89df6019163d7b18a8ecb4003939f6235b5de85

/mnist/cnn_mnist.py

0f8dd40e176c805f08e1a65e10cdad7e16b51923

[]

no_license

liketheflower/tf_practise

fdd22b608ca7d513a4972497466e3fc7a12762b6

2725b52169b2f0044d20b3c33c86485336e65483

refs/heads/master

2020-03-19T23:21:16.467649

2018-06-19T03:56:07

137,003,463

0

null

UTF-8

Python

false

5,709

py

#opyright 2016 iThe TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by 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. """Convolutional Neural Network Estimator for MNIST, built with tf.layers.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf tf.logging.set_verbosity(tf.logging.INFO) def cnn_model_fn(features, labels, mode): """Model function for CNN.""" # Input Layer # Reshape X to 4-D tensor: [batch_size, width, height, channels] # MNIST images are 28x28 pixels, and have one color channel input_layer = tf.reshape(features["x"], [-1, 28, 28, 1]) # Convolutional Layer #1 # Computes 32 features using a 5x5 filter with ReLU activation. # Padding is added to preserve width and height. # Input Tensor Shape: [batch_size, 28, 28, 1] # Output Tensor Shape: [batch_size, 28, 28, 32] conv1 = tf.layers.conv2d( inputs=input_layer, filters=32, kernel_size=[5, 5], padding="same", activation=tf.nn.relu) # Pooling Layer #1 # First max pooling layer with a 2x2 filter and stride of 2 # Input Tensor Shape: [batch_size, 28, 28, 32] # Output Tensor Shape: [batch_size, 14, 14, 32] pool1 = tf.layers.max_pooling2d(inputs=conv1, pool_size=[2, 2], strides=2) # Convolutional Layer #2 # Computes 64 features using a 5x5 filter. # Padding is added to preserve width and height. # Input Tensor Shape: [batch_size, 14, 14, 32] # Output Tensor Shape: [batch_size, 14, 14, 64] conv2 = tf.layers.conv2d( inputs=pool1, filters=64, kernel_size=[5, 5], padding="same", activation=tf.nn.relu) # Pooling Layer #2 # Second max pooling layer with a 2x2 filter and stride of 2 # Input Tensor Shape: [batch_size, 14, 14, 64] # Output Tensor Shape: [batch_size, 7, 7, 64] pool2 = tf.layers.max_pooling2d(inputs=conv2, pool_size=[2, 2], strides=2) # Flatten tensor into a batch of vectors # Input Tensor Shape: [batch_size, 7, 7, 64] # Output Tensor Shape: [batch_size, 7 * 7 * 64] pool2_flat = tf.reshape(pool2, [-1, 7 * 7 * 64]) # Dense Layer # Densely connected layer with 1024 neurons # Input Tensor Shape: [batch_size, 7 * 7 * 64] # Output Tensor Shape: [batch_size, 1024] dense = tf.layers.dense(inputs=pool2_flat, units=1024, activation=tf.nn.relu) # Add dropout operation; 0.6 probability that element will be kept dropout = tf.layers.dropout( inputs=dense, rate=0.4, training=mode == tf.estimator.ModeKeys.TRAIN) # Logits layer # Input Tensor Shape: [batch_size, 1024] # Output Tensor Shape: [batch_size, 10] logits = tf.layers.dense(inputs=dropout, units=10) predictions = { # Generate predictions (for PREDICT and EVAL mode) "classes": tf.argmax(input=logits, axis=1), # Add `softmax_tensor` to the graph. It is used for PREDICT and by the # `logging_hook`. "probabilities": tf.nn.softmax(logits, name="softmax_tensor") } if mode == tf.estimator.ModeKeys.PREDICT: return tf.estimator.EstimatorSpec(mode=mode, predictions=predictions) # Calculate Loss (for both TRAIN and EVAL modes) loss = tf.losses.sparse_softmax_cross_entropy(labels=labels, logits=logits) # Configure the Training Op (for TRAIN mode) if mode == tf.estimator.ModeKeys.TRAIN: optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.001) train_op = optimizer.minimize( loss=loss, global_step=tf.train.get_global_step()) return tf.estimator.EstimatorSpec(mode=mode, loss=loss, train_op=train_op) # Add evaluation metrics (for EVAL mode) eval_metric_ops = { "accuracy": tf.metrics.accuracy( labels=labels, predictions=predictions["classes"])} return tf.estimator.EstimatorSpec( mode=mode, loss=loss, eval_metric_ops=eval_metric_ops) def main(unused_argv): # Load training and eval data mnist = tf.contrib.learn.datasets.load_dataset("mnist") train_data = mnist.train.images # Returns np.array train_labels = np.asarray(mnist.train.labels, dtype=np.int32) eval_data = mnist.test.images # Returns np.array eval_labels = np.asarray(mnist.test.labels, dtype=np.int32) # Create the Estimator mnist_classifier = tf.estimator.Estimator( model_fn=cnn_model_fn, model_dir="/tmp/mnist_convnet_model") # Set up logging for predictions # Log the values in the "Softmax" tensor with label "probabilities" tensors_to_log = {"probabilities": "softmax_tensor"} logging_hook = tf.train.LoggingTensorHook( tensors=tensors_to_log, every_n_iter=50) # Train the model train_input_fn = tf.estimator.inputs.numpy_input_fn( x={"x": train_data}, y=train_labels, batch_size=100, num_epochs=None, shuffle=True) mnist_classifier.train( input_fn=train_input_fn, steps=20000, hooks=[logging_hook]) # Evaluate the model and print results eval_input_fn = tf.estimator.inputs.numpy_input_fn( x={"x": eval_data}, y=eval_labels, num_epochs=1, shuffle=False) eval_results = mnist_classifier.evaluate(input_fn=eval_input_fn) print(eval_results) if __name__ == "__main__": tf.app.run()

[ "jim.morris.shen@gmail.com" ]

jim.morris.shen@gmail.com

d89b26a0c2aa42dccc501acbb07ac7e597b9047a

102b67d83e12219f3bf4bea6ed691ddd9c2e69f1

/ad/templatetags/ads.py

7e6251780e534773006f27332ae6205e14bdccc8

[ "BSD-3-Clause" ]

permissive

nicksergeant/snipt-old

2cb6bec629d798dd83fc39f0105828f1fd40a51a

f2f1e9f183fb69bcc0fabbc25059bfd1c60527e2

refs/heads/master

2021-01-18T14:03:01.426851

2012-09-19T00:09:48

865,573

2

0

null

UTF-8

Python

false

882

py

from tagging.models import TaggedItem from snipt.ad.models import Ad from django import template register = template.Library() @register.simple_tag def ad(tag): try: ads = TaggedItem.objects.get_by_model(Ad.objects.order_by('?'), tag) ad = ads[0] except: ads = Ad.objects.order_by('?') ad = ads[0] tag = '' return """ <h1 style="margin-bottom: 20px; padding-top: 15px;">A good %s read</h1> <div class="amazon-book clearfix"> <div class="amazon-title"> <a href="%s" rel="nofollow" class="clearfix"> <img src="/media/%s" alt="%s" title="%s" /> %s </a> </div> </div> """ % (tag, ad.url, ad.image, ad.title, ad.title, ad.title)

[ "nick@nicksergeant.com" ]

nick@nicksergeant.com

974c0c7fd25b0de5202f8adde919a1f585b0a4ed

aa45f6f5106517c582b21691ce22ad808339ec64

/borax/calendars/birthday.py

aea5997b9e454ee9eaf8a2861a068b38780a781c

[ "MIT" ]

permissive

kinegratii/borax

86b1a87c686f9b74db8d919afe30761497888368

06407958a6ba3115d783ed6457c2e7355a3f237c

refs/heads/master

2023-03-11T06:09:20.040607

2022-11-15T02:39:43

126,959,349

67

8

MIT

2022-11-15T02:39:44

2018-03-27T09:07:08

Python

UTF-8

Python

false

1,151

py

from datetime import date from .lunardate import LunarDate, LCalendars def nominal_age(birthday, today=None): birthday = LCalendars.cast_date(birthday, LunarDate) if today: today = LCalendars.cast_date(today, LunarDate) else: today = LunarDate.today() return today.year - birthday.year + 1 def actual_age_solar(birthday, today=None): """See more at https://stackoverflow.com/questions/2217488/age-from-birthdate-in-python/9754466#9754466 :param birthday: :param today: :return: """ birthday = LCalendars.cast_date(birthday, date) if today: today = LCalendars.cast_date(today, date) else: today = date.today() return today.year - birthday.year - ((today.month, today.day) < (birthday.month, birthday.day)) def actual_age_lunar(birthday, today=None): birthday = LCalendars.cast_date(birthday, LunarDate) if today: today = LCalendars.cast_date(today, LunarDate) else: today = LunarDate.today() return today.year - birthday.year - ( (today.month, today.leap, today.day) < (birthday.month, birthday.leap, birthday.day) )

[ "kinegratii@gmail.com" ]

kinegratii@gmail.com

a0f1f2557839af7ed23dfb81c8ff5bea64a59bc4

e4c25590298b084e3fb44b0b325a05699fac4202

/Kattis/sevenwonders.py

5a96568a7cc25485bbe157259a725421d500474b

[]

no_license

shakib609/competitive-programming

520028bd1147e7e43e708875b6390e1a7d65a94b

5090d5d3650b8055e16651ed9de5380cc7fdb7aa

refs/heads/master

2022-12-09T12:33:20.167332

2022-12-07T17:28:30

67,289,210

0

1

null

UTF-8

Python

false

226

py

s = input().strip() t, c, g = [0, 0, 0] for ch in s: if ch == 'T': t += 1 elif ch == 'C': c += 1 else: g += 1 result = t ** 2 + c ** 2 + g ** 2 result += min([t, c, g]) * 7 print(result)

[ "shakib609@gmail.com" ]

shakib609@gmail.com

52afe556959590049b64feb71a30c5fce7fedaf1

48e124e97cc776feb0ad6d17b9ef1dfa24e2e474

/sdk/python/pulumi_azure_native/containerregistry/v20190501/get_webhook.py

7948e368ab3b2de549dbfecb516f227ee8cca61a

[ "BSD-3-Clause", "Apache-2.0" ]

permissive

bpkgoud/pulumi-azure-native

0817502630062efbc35134410c4a784b61a4736d

a3215fe1b87fba69294f248017b1591767c2b96c

refs/heads/master

2023-08-29T22:39:49.984212

2021-11-15T12:43:41

null

0

null

UTF-8

Python

false

6,711

py

# 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 __all__ = [ 'GetWebhookResult', 'AwaitableGetWebhookResult', 'get_webhook', 'get_webhook_output', ] @pulumi.output_type class GetWebhookResult: """ An object that represents a webhook for a container registry. """ def __init__(__self__, actions=None, id=None, location=None, name=None, provisioning_state=None, scope=None, status=None, tags=None, type=None): if actions and not isinstance(actions, list): raise TypeError("Expected argument 'actions' to be a list") pulumi.set(__self__, "actions", actions) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if location and not isinstance(location, str): raise TypeError("Expected argument 'location' to be a str") pulumi.set(__self__, "location", location) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if provisioning_state and not isinstance(provisioning_state, str): raise TypeError("Expected argument 'provisioning_state' to be a str") pulumi.set(__self__, "provisioning_state", provisioning_state) if scope and not isinstance(scope, str): raise TypeError("Expected argument 'scope' to be a str") pulumi.set(__self__, "scope", scope) if status and not isinstance(status, str): raise TypeError("Expected argument 'status' to be a str") pulumi.set(__self__, "status", status) if tags and not isinstance(tags, dict): raise TypeError("Expected argument 'tags' to be a dict") pulumi.set(__self__, "tags", tags) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter def actions(self) -> Sequence[str]: """ The list of actions that trigger the webhook to post notifications. """ return pulumi.get(self, "actions") @property @pulumi.getter def id(self) -> str: """ The resource ID. """ return pulumi.get(self, "id") @property @pulumi.getter def location(self) -> str: """ The location of the resource. This cannot be changed after the resource is created. """ return pulumi.get(self, "location") @property @pulumi.getter def name(self) -> str: """ The name of the resource. """ return pulumi.get(self, "name") @property @pulumi.getter(name="provisioningState") def provisioning_state(self) -> str: """ The provisioning state of the webhook at the time the operation was called. """ return pulumi.get(self, "provisioning_state") @property @pulumi.getter def scope(self) -> Optional[str]: """ The scope of repositories where the event can be triggered. For example, 'foo:*' means events for all tags under repository 'foo'. 'foo:bar' means events for 'foo:bar' only. 'foo' is equivalent to 'foo:latest'. Empty means all events. """ return pulumi.get(self, "scope") @property @pulumi.getter def status(self) -> Optional[str]: """ The status of the webhook at the time the operation was called. """ return pulumi.get(self, "status") @property @pulumi.getter def tags(self) -> Optional[Mapping[str, str]]: """ The tags of the resource. """ return pulumi.get(self, "tags") @property @pulumi.getter def type(self) -> str: """ The type of the resource. """ return pulumi.get(self, "type") class AwaitableGetWebhookResult(GetWebhookResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetWebhookResult( actions=self.actions, id=self.id, location=self.location, name=self.name, provisioning_state=self.provisioning_state, scope=self.scope, status=self.status, tags=self.tags, type=self.type) def get_webhook(registry_name: Optional[str] = None, resource_group_name: Optional[str] = None, webhook_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetWebhookResult: """ An object that represents a webhook for a container registry. :param str registry_name: The name of the container registry. :param str resource_group_name: The name of the resource group to which the container registry belongs. :param str webhook_name: The name of the webhook. """ __args__ = dict() __args__['registryName'] = registry_name __args__['resourceGroupName'] = resource_group_name __args__['webhookName'] = webhook_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:containerregistry/v20190501:getWebhook', __args__, opts=opts, typ=GetWebhookResult).value return AwaitableGetWebhookResult( actions=__ret__.actions, id=__ret__.id, location=__ret__.location, name=__ret__.name, provisioning_state=__ret__.provisioning_state, scope=__ret__.scope, status=__ret__.status, tags=__ret__.tags, type=__ret__.type) @_utilities.lift_output_func(get_webhook) def get_webhook_output(registry_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, webhook_name: Optional[pulumi.Input[str]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetWebhookResult]: """ An object that represents a webhook for a container registry. :param str registry_name: The name of the container registry. :param str resource_group_name: The name of the resource group to which the container registry belongs. :param str webhook_name: The name of the webhook. """ ...

[ "noreply@github.com" ]

bpkgoud.noreply@github.com

df9dd24400578916c3d14c13ccc9926eddfabb48

38eb57300418e6f10433630437388f779ce50e09

/cookie_and_session/app02_session/views.py

25a4bbc4abf9387fc8de2e70f90c22b5c03e8db7

[]

no_license

SelfShadows/Django-Flask

f37839f763133f0d62bffad3128171c426a1c038

13e32d1c8aac1532b43323e1891c423fe78f2813

refs/heads/master

2021-01-04T12:31:18.018508

2020-02-14T16:29:27

240,550,991

0

null

UTF-8

Python

false

2,688

py

from django.shortcuts import render ,redirect from functools import wraps from django import views # Django提供的工具，把函数装饰器转变为方法装饰器 from django.utils.decorators import method_decorator from app02_session import models def check_login(func): @wraps(func) # 装饰器修复技术 def inner(request, *args, **kwargs): # 获取seesion ret = request.session.get("is_login") # 1.获取cookie 中的随机字符串 # 2.根据随机字符串去数据库取 session_data --> 解密 --> 反序列化成字典 # 3.在字典里面根据 is_login 取出具体数据 if ret == "1": # 已经登陆过的继续执行 return func(request, *args, **kwargs) else: # 没有登陆过的跳转到登陆页面 next_url = request.path_info return redirect("/app02/login/?next={}".format(next_url)) return inner def login(request): if request.method == "POST": user = request.POST.get("user") pwd = request.POST.get("pwd") # 从url里面去除next参数 next_url = request.GET.get("next") # 将所有Session失效日期小于当前日期的数据删除 request.session.clear_expired() have_user = models.Person.objects.filter(username=user, password=pwd) if have_user: # 登录成功 # 告诉浏览器保存一个键值对 if next_url: ret = redirect(next_url) else: ret = redirect("/app02/home/") # 设置session request.session["is_login"] = "1" request.session["user_id"] = have_user[0].id # 设置超时时间 request.session.set_expiry(5) # 5秒后失效 return ret return render(request, "app02/login.html") # 注销登陆函数 def logout(request): # 只删除session数据 # request.session.delete() # 删除session数据和cookie值 request.session.flush() return redirect("/app02/login/") @check_login def home(request): user_id = request.session.get("user_id") user_obj = models.Person.objects.filter(id=user_id) if user_obj: return render(request, "app02/home.html", {"user_obj": user_obj[0]}) else: return render(request, "app02/home.html", {"user_obj": "匿名用户"}) @check_login def index(request): return render(request, "app02/index.html") class UserInfo(views.View): # 把函数装饰器转变为方法装饰器 @method_decorator(check_login) def get(self, request): return render(request, "app02/userinfo.html")

[ "870670791@qq.com" ]

870670791@qq.com

9d2cd1f61430081aa4a65d8e29b28e23f51b088f

85f6de6e3ef680cd717312233fd03c636c606550

/src/two/rolling_a_dice.py

faf4234c08ca6aa9dc9b3cb20192a6fdd631a5dc

[ "MIT", "LicenseRef-scancode-warranty-disclaimer" ]

permissive

Guillermogsjc/dissecting-reinforcement-learning

f8956455ffda22445ecc11fc6938da40ed4948e2

8a2751efa6d4a733df81c272c503b8061c70c04f

refs/heads/master

2021-01-11T20:41:02.216522

2017-01-15T11:32:27

79,168,192

1

0

null

2017-01-16T23:14:54

2017-01-16T23:14:53

null

UTF-8

Python

false

611

py

import numpy as np #Trowing a dice for N times and evaluating the expectation dice = np.random.randint(low=1, high=7, size=3) print("Expectation (3 times): " + str(np.mean(dice))) dice = np.random.randint(low=1, high=7, size=10) print("Expectation (10 times): " + str(np.mean(dice))) dice = np.random.randint(low=1, high=7, size=100) print("Expectation (100 times): " + str(np.mean(dice))) dice = np.random.randint(low=1, high=7, size=1000) print("Expectation (1000 times): " + str(np.mean(dice))) dice = np.random.randint(low=1, high=7, size=100000) print("Expectation (100000 times): " + str(np.mean(dice)))

[ "massimiliano.patacchiola@gmail.com" ]

massimiliano.patacchiola@gmail.com

fac85c5c169eaf142355c0655ac86fcd5f74fc09

52b5773617a1b972a905de4d692540d26ff74926

/.history/surrounded_20200617223518.py

233debe26db46593e2dfe08e99e70eb47ac5cf87

[]

no_license

MaryanneNjeri/pythonModules

56f54bf098ae58ea069bf33f11ae94fa8eedcabc

f4e56b1e4dda2349267af634a46f6b9df6686020

refs/heads/master

2022-12-16T02:59:19.896129

2020-09-11T12:05:22

null

0

null

UTF-8

Python

false

1,136

py

def surronded(board): # dfs # untouched # in progress # finished rows = len(board) if rows == 0: return cols = len(board[0]) if cols == 0: return state = [[0]* cols for _ in range(rows)] def canReachOutside(x,y,pending): pending.append(x,y) canReach = False directions = [(1,0),(-1,0),(0,1),(0,-1)] for dx,dy in directions: nextX,nextY = dx+x,dy+y if nextX < 0 or nextX >= rows or nextY < 0 or nextY >= cols: canReach = True continue if board[nextX][nextY] == 'O' and state[nextX][nextY] == 0: state[nextX][nextY] = 1 canReach != canReachOutside(nextX,nextY,pending) return canReach for x in range(rows): for y in range(cols): if [x][y] == '0' and state[x][y] == 0: pending = [] if canReachOutside(x,y,pending): # process states to change from o to x pass else: # regulary process states pass

[ "mary.jereh@gmail.com" ]

mary.jereh@gmail.com

d662e3cccc6393bf07124edfdf202bfc54925ebe

7cf29923d278c5b934a40de216ac606c25c8a5eb

/wheelcms_axle/translate.py

4f0f0c74ba26a7823c2018014ad16b58ddbffc3f

[ "BSD-2-Clause" ]

permissive

wheelcms/wheelcms_axle

1df024f75d17544a575953359e3cc9a4ab56d93c

b5916b555f37b7baafdf08fd56b5b985688df9d0

refs/heads/master

2020-04-05T22:43:04.176353

2015-04-05T10:53:42

7,800,085

0

1

null

UTF-8

Python

false

1,095

py

from django.conf import settings any_lang = ('any', 'Any') def languages(): languages = tuple(settings.CONTENT_LANGUAGES) if any_lang not in languages: languages = languages + (any_lang, ) return languages def fallback_languages(language): """ given a language, provide a list of alternatives, prioritized """ langs = [language] if language != any_lang[0]: langs.append(any_lang[0]) return langs def language_slug(slugs, slug, language): """ slugs is a mapping of lang->slug, slug is a default slug, Try to get the appropriate slug from the mapping first, else use the provided slug. If neither are present, return *any* slug from the mapping (XXX we might try settings.LANGUAGE first) """ lslug = slugs.get(language, slug) if lslug is None and language == any_lang[0]: ## Use fallback? XXX return slugs.values()[0] # any if lslug is None: return slugs.values()[0] # any ## may still be None, let caller fail, for now return lslug

[ "github@in.m3r.nl" ]

github@in.m3r.nl

fb48fd9656915149d8133355706be99ed2db0469

a31de016611f3b4efc7a576e7113cad1a738419b

/_string_monster2.py

ba71783722b858478094721a871a759c7c6dd5c1

[]

no_license

Ing-Josef-Klotzner/python

9d4044d632672fff966b28ab80e1ef77763c78f5

3913729d7d6e1b7ac72b46db7b06ca0c58c8a608

refs/heads/master

2022-12-09T01:40:52.275592

2022-12-01T22:46:43

189,040,355

0

null

2022-12-01T19:52:37

2019-05-28T14:05:16

Python

UTF-8

Python

false

1,363

py

#!/usr/bin/python3 from sys import stdin def match (ssof, ss): if ss == "": return True #print (ssof, ss, end = " ") for st in ssof: if ss.startswith (st): return match (ssof - {st}, ss [len (st):]) return False # this works with testcases, because strings are included # in order in sleepy string (hackerearth testcases) # fails for sample test case where sleepy string chars are scrumbled def main (): read = stdin.readline t = int (read ()) for t_ in range (t): n = int (read ()) sof = [] # list of strings on floor lns = [] # list of the string lengths for n_ in range (n): s = read ().rstrip () sof.append (s) lns.append (len (s)) ss = read ().rstrip () # sleepy string lnss = len (ss) mnl = min (lns) mxl = max (lns) justone = 0 allother_max = 0 for n_ in range (n): if lns [n_] == mnl: justone += 1 elif lns [n_] == mxl: allother_max += 1 if lnss < mnl or lnss > mnl and lnss < 2 * mnl or mnl == mxl and lnss % mnl or justone == 1 and allother_max == n - 1 and lnss % mxl not in {0, mnl}: print ("NO") continue ssof = set (sof) print ("YES" if match (ssof, ss) else "NO") if __name__ == "__main__": main ()

[ "noreply@github.com" ]

Ing-Josef-Klotzner.noreply@github.com

1f3f8ad62b3bff4ac0821b0fc51593df8ce0d5ce

c61c9bedba1968bfaf571ac3996b696fc35890a6

/Chapter12/has_match.py

00b6ca1068d542e225e1be731b69d6152b593ec3

[]

no_license

ArunRamachandran/ThinkPython-Solutions

497b3dbdeba1c64924fe1d9aa24204a9ca552c5b

1a0872efd169e5d39b25134960168e3f09ffdc99

refs/heads/master

2020-04-01T10:23:20.255132

2014-11-07T17:04:52

25,806,318

1

0

null

UTF-8

Python

false

463

py

# has_match takes two sequences, t1 and t2, and returns True, if there is # an index i such that t1[i] == t2[i] def has_match(t1,t2): for x,y in zip(t1,t2): if x == y: return True else: return False t1 = "banana" t2 = "sequence" print "Given sequences are : " print t1 print t2 case = has_match(t1,t2) if case == True: print "Yeah..!! Two sequences have a matching index " if case == False: print "Nope... It doesn't have a matching index !! "

[ "arunkramachandran92@gmail.com" ]

arunkramachandran92@gmail.com

8f18a7a3cb0b452be92e2c21ca740144639a7e69

7e4a1838dbcbe0526f20b4b49f88a3f213dbc712

/npcaller/fasta.py

7d1d78befe1990ff329540e7f2e2e5f87acb256e

[ "MIT" ]

permissive

grst/nanopore_pkg

c5c8ee940ddd9218c08846ba5e5884c697914ca6

e13ccfae0be79f23ae3270b09744726504b0e58f

refs/heads/master

2023-04-02T14:38:52.410352

2020-11-06T19:34:37

48,172,418

0

null

UTF-8

Python

false

1,569

py

""" Since skbio and Biopython are overkill and slightly to complicated most of the time I came up with this really simple fasta-io class. """ from itertools import groupby class FastaReader(object): def __init__(self, file): if not hasattr(file, 'read'): self.file = open(file, 'r') else: self.file = file def get_entries(self): """ Get the next Entry from the fasta file. Returns: Generator, which yields (header, sequence) tuples """ for isheader, group in groupby(self.file, lambda line: line[0] == ">"): if isheader: header = next(group)[1:] else: seq = "".join(line.strip() for line in group) yield header, seq def close(self): self.file.close() class FastaWriter(object): """ Very simple fasta file format writer. """ SPLIT = 80 def __init__(self, file): if not hasattr(file, 'write'): self.file = open(file, 'w') else: self.file = file def write_entry(self, header, sequence): """ Write Entry to File Args: header: >sequence_header sequence: ACTGATT... """ sequence = [sequence[i:i+self.SPLIT] for i in range(0, len(sequence), self.SPLIT)] self.file.write(">{0}\n".format(header)) for s in sequence: self.file.write(s + "\n") def flush(self): self.file.flush() def close(self): self.file.close()

[ "mail@gregor-sturm.de" ]

mail@gregor-sturm.de

fc77466e30f68146a40c8d3ba3b858f15859ddb5

19ddab74600f71700a6b693281d0180d5271f295

/程序员面试金典/03_03_堆盘子.py

2f96f3b2e8fb699bf5461a949729ba6f932d252c

[]

no_license

zhulf0804/Coding.Python

4d55a430da1a8077c81feba65c13ac654aaf094a

46ab03e23d15ebd5434ef4dd5ae99130000b00a5

refs/heads/master

2022-09-14T18:40:59.880941

2022-08-20T08:25:51

213,113,482

3

1

null

UTF-8

Python

false

1,000

py

class StackOfPlates: def __init__(self, cap: int): self.stack = [] self.cap = cap def push(self, val: int) -> None: if self.cap == 0: return if len(self.stack) == 0 or len(self.stack[-1]) == self.cap: self.stack.append([]) self.stack[-1].append(val) def pop(self) -> int: if self.cap == 0 or len(self.stack) == 0: return -1 val = self.stack[-1].pop() if len(self.stack[-1]) == 0: self.stack = self.stack[:-1] return val def popAt(self, index: int) -> int: if self.cap == 0 or index >= len(self.stack): return -1 val = self.stack[index].pop() if len(self.stack[index]) == 0: self.stack = self.stack[:index] + self.stack[index+1:] return val # Your StackOfPlates object will be instantiated and called as such: # obj = StackOfPlates(cap) # obj.push(val) # param_2 = obj.pop() # param_3 = obj.popAt(index)

[ "zhulf0804@gmail.com" ]

zhulf0804@gmail.com

c4fd6afe113c170e2b3985c756cac05390668ae8

e04dbc32247accf073e3089ed4013427ad182c7c

/hhkb2020/C TLE.py

61c4d78700c4375a274fc85a2aa4fa2d73278a89

[]

no_license

twobooks/atcoder_training

9deb237aed7d9de573c1134a858e96243fb73ca0

aa81799ec87cc9c9d76de85c55e99ad5fa7676b5

refs/heads/master

2021-10-28T06:33:19.459975

2021-10-20T14:16:57

233,233,854

0

null

UTF-8

Python

false

260

py

import numpy as np # np.lcm(),np.gcd() N = int(input()) arrP = np.array(input().split(),dtype=np.int64) arrAll = np.arange(200000+1,dtype=np.int64) mask = np.ones(200000+1,dtype=np.int64) == 1 for p in arrP: mask[p] = False print(arrAll[mask][0])

[ "twobookscom@gmail.com" ]

twobookscom@gmail.com

27b8f49cb7a0e85b1fe35959e45a5d9c84dcb57b

dfb53581b4e6dbdc8e3789ea2678de1e1c4b5962

/Django/mydjango01/news/views.py

21a263f4be374c6a40d7fe19b8fd65329d2cf18d

[]

no_license

biabulinxi/Python-ML-DL

7eff6d6898d72f00575045c5aa2acac45b4b0b82

217d594a3c0cba1e52550f74d100cc5023fb415b

refs/heads/master

2020-06-01T09:13:17.314121

2019-06-08T03:59:36

null

0

null

UTF-8

Python

false

168

py

from django.shortcuts import render from django.http import HttpResponse # Create your views here. def index(request): return HttpResponse("这是news的首页")

[ "biabu1208@163.com" ]

biabu1208@163.com

99b1f62912fb80c7e719697e2f9075d4fd505216

15b12d69ac3123d1562986970ce01d7a47d171de

/typings/nltk/translate/__init__.pyi

79712704c982cb5c2d56cec50d1fde99fb9fb8ad

[ "Apache-2.0" ]

permissive

simplymanas/python-learning

9b67b5a7acfb3a7c2455a7d1fc66203a2b419c37

75bc99c0dce211fd1bce5f6ce1155e0f4c71d7d0

refs/heads/master

2021-07-11T06:40:24.803589

2021-06-20T12:06:02

241,769,614

5

1

null

UTF-8

Python

false

768

pyi

""" This type stub file was generated by pyright. """ from nltk.translate.api import AlignedSent, Alignment, PhraseTable from nltk.translate.ibm_model import IBMModel from nltk.translate.ibm1 import IBMModel1 from nltk.translate.ibm2 import IBMModel2 from nltk.translate.ibm3 import IBMModel3 from nltk.translate.ibm4 import IBMModel4 from nltk.translate.ibm5 import IBMModel5 from nltk.translate.bleu_score import sentence_bleu as bleu from nltk.translate.ribes_score import sentence_ribes as ribes from nltk.translate.meteor_score import meteor_score as meteor from nltk.translate.metrics import alignment_error_rate from nltk.translate.stack_decoder import StackDecoder """ Experimental features for machine translation. These interfaces are prone to change. """

[ "manas.dash@tesco.com" ]

manas.dash@tesco.com

ee75934b54a7c419ea4df630c94ae680bfee4f92

ba0e07b34def26c37ee22b9dac1714867f001fa5

/azure-mgmt-powerbiembedded/azure/mgmt/powerbiembedded/models/error_detail.py

08890398d70c2163092510b29f7f60ffe5e56300

[ "MIT" ]

permissive

CharaD7/azure-sdk-for-python

b11a08ac7d24a22a808a18203072b4c7bd264dfa

9fdf0aac0cec8a15a5bb2a0ea27dd331dbfa2f5c

refs/heads/master

2023-05-12T12:34:26.172873

2016-10-26T21:35:20

72,448,760

1

0

MIT

2023-05-04T17:15:01

2016-10-31T15:14:09

Python

UTF-8

Python

false

1,024

py

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class ErrorDetail(Model): """ErrorDetail. :param code: :type code: str :param message: :type message: str :param target: :type target: str """ _attribute_map = { 'code': {'key': 'code', 'type': 'str'}, 'message': {'key': 'message', 'type': 'str'}, 'target': {'key': 'target', 'type': 'str'}, } def __init__(self, code=None, message=None, target=None): self.code = code self.message = message self.target = target

[ "lmazuel@microsoft.com" ]

lmazuel@microsoft.com

33161c34e78739d53ded91e468cf82f429dfef1d

b170d37a81c09fd0dbb0edf3cff6296084b32af9

/cexbot/command_utils.py

7d0382b5e4f8d343853e41df961287aa984532fe

[ "MIT" ]

permissive

metaperl/cexbot

8e17a7d5063a82675e002d926324e3c4a6eb6745

0dd0b60415afd9c1feb959186d32b1a683887975

refs/heads/master

2020-12-29T01:11:50.768031

2013-12-10T17:13:18

null

0

null

UTF-8

Python

false

2,754

py

#!/usr/bin/env python """ cexbot - command_utils.py Default command line utitlities to run cexbot """ import os, sys, logging import cexbot, config, parser, db, cexapi, updater, timer, cex def main(argv=[]): args = parser.get_parser() verbose = 1 if args.verbose: verbose = 2 if args.debug: verbose = 3 if verbose>2: log_level=logging.DEBUG elif verbose==2: log_level=logging.INFO elif verbose==1: log_level=logging.WARNING elif verbose<1: log_level=logging.ERROR logging.basicConfig(level=log_level, format="%(asctime)s %(levelname)s: %(message)s") if args.command == 'version': print cexbot.get_version() return True # make sure this is always above command parsing # print config config.first_run() if verbose == 3: print args if args.command == 'config': if args.list: return config.list() elif args.edit: return config.edit_config() elif args.testauth: return config.test_auth() elif args.name and args.value: v = config.set(args.name, args.value) return config.cprint(args.name) elif args.name: return config.cprint(args.name) logging.error('Invalid config option') return 1 elif args.command == 'update': return updater.check_update() # not implemented elif args.command == 'cleardata': return config.clear_userdata() ac = cexapi.CexAPI(config.get('cex.username'), config.get('cex.apikey'), config.get('cex.secret')) dbi = db.DbManager() cx = CexMethods(ac, dbi) if args.command == 'balance': print "Balance: %s BTC" % ac.get_balance() return True elif args.command == 'initdb': return dbi.initdb() elif args.command == 'getmarket': return ac.get_market() elif args.command == 'getprice': return ac.get_market_quote() elif args.command == 'order': amount = args.amount price = args.price r = ac.place_order(amount, price) logging.info("Ordered: %s" % r) elif args.command == 'updatequotes': logging.info('Running updatequotes') ticker_timer = timer.ReqTimer(2, cx.update_ticker) ticker_timer.start() elif args.command == 'buybalance': logging.info('Running buybalance') balance_timer = timer.ReqTimer(5, ac.buy_balance) balance_timer.start() # @TODO __import__ # if args.task in cexbot.tasks: # cexbot.tasks[args.task]() def cl_error(msg=""): print >> sys.stderr, msg def run_cl(argv=[]): try: raise SystemExit(main(sys.argv)) except KeyboardInterrupt: cl_error('Interrupted.') raise SystemExit(-1) def run_gui(argv=[]): print "GUI coming soon." # return None try: import cexbot.gui cexbot.gui.main() except Exception, e: print "Error: %s" % str(e)

[ "nikcub@gmail.com" ]

nikcub@gmail.com

20faeb3af99098aeae7f42e863b981e32e75deb0

f8a053f287c66652adffd15624c85dcc0850d898

/setup.py

424d2c9837ce0ca5390c3445ddf06d2283a94b46

[ "MIT" ]

permissive

heyongwei/zvt

cce9e9bac78c6acc5e73b517f80d1fa464342817

051106955a6a01707847ee56a447e2502a25ff46

refs/heads/master

2023-04-23T16:36:58.631045

2021-05-16T16:01:18

363,716,402

0

MIT

2021-05-16T16:01:19

2021-05-02T17:59:26

Python

UTF-8

Python

false

2,508

py

#!/usr/bin/env python # To use a consistent encoding from codecs import open from os import path # Always prefer setuptools over distutils from setuptools import setup, find_packages try: # for pip >= 10 from pip._internal.req import parse_requirements except ImportError: # for pip <= 9.0.3 from pip.req import parse_requirements here = path.abspath(path.dirname(__file__)) # Get the long description from the README file with open(path.join(here, 'README.md'), encoding='utf-8') as f: long_description = f.read() # Arguments marked as "Required" below must be included for upload to PyPI. # Fields marked as "Optional" may be commented out. install_reqs = parse_requirements("requirements.txt", session=False) try: requirements = [str(ir.req) for ir in install_reqs] except: requirements = [str(ir.requirement) for ir in install_reqs] setup( name='zvt', version='0.9.3', description='unified,modular quant framework for human beings ', long_description=long_description, url='https://github.com/zvtvz/zvt', author='foolcage', author_email='5533061@qq.com', classifiers=[ # Optional 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Intended Audience :: Customer Service', 'Intended Audience :: Education', 'Intended Audience :: Financial and Insurance Industry', 'Topic :: Software Development :: Build Tools', 'Topic :: Office/Business :: Financial :: Investment', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8' ], keywords='quant stock finance fintech big-data zvt technical-analysis trading-platform pandas fundamental-analysis', packages=find_packages(include=['zvt.*', 'zvt']), python_requires='>=3.5, <4', include_package_data=True, install_requires=requirements, project_urls={ # Optional 'Bug Reports': 'https://github.com/zvtvz/zvt/issues', 'Funding': 'https://www.foolcage.com/zvt', 'Say Thanks!': 'https://saythanks.io/to/foolcage', 'Source': 'https://github.com/zvtvz/zvt', }, long_description_content_type="text/markdown", entry_points={ 'console_scripts': [ 'zvt = zvt.main:main', 'zvt_plugin = zvt.plugin:main', 'zvt_export = zvt.plugin:export', ], }, )

[ "5533061@qq.com" ]

5533061@qq.com

0a261a997e8b133dd2f20809de2b05a9df10aa1a

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03041/s690420831.py

d69751f59907935676518728b9785bda095c49de

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

290

py

n, k = map(int, input().split()) s = str(input()) ans = '' if s[k-1] == 'A': ans = s[:k-1] + 'a' + s[k:] print(ans) exit() elif s[k-1] == 'B': ans = s[:k-1] + 'b' + s[k:] print(ans) exit() elif s[k-1] == 'C': ans = s[:k-1] + 'c' + s[k:] print(ans) exit()

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

feb5b5b9942b836a874b3a07264b9012e4b7df0b

3f9bec3201cc255c5ad6023cc746488306224015

/Chapter 13/Example_13-2.py

08ddcf523baaba0c0e1dc8735da55bee0e9ae257

[]

no_license

afettouhi/FluentPython-py37

64927a908c5804d8970ea3f4b667c109c5867a6a

a14a721d738b8908f9e8e78552d70fbb2d6dd74f

refs/heads/master

2022-06-14T18:26:47.456090

2020-05-08T04:13:51

259,222,101

0

null

UTF-8

Python

false

199

py

import decimal ctx = decimal.getcontext() ctx.prec = 40 one_third = decimal.Decimal('1') / decimal.Decimal('3') one_third one_third == +one_third ctx.prec = 28 one_third == +one_third +one_third

[ "A.Fettouhi@gmail.com" ]

A.Fettouhi@gmail.com

ea566c781d0e6f7ed3612211e0138868a141630c

780af071416ece1e1f6ead426e95155c3de209e9

/notebooks/rv/__init__.py

5918d5994e584d77b4e31b849f510e080fa8203b

[]

no_license

o-smirnov/docker-notebook

b2afd38cf16a1db9d3049c4ce79f7bc61c6183fb

9cdb1f3fbaaca8edb94d9706a1e62410942a2f1a

refs/heads/master

2021-01-22T17:14:03.346539

2015-05-07T12:31:01

35,032,895

0

null

2015-05-04T12:15:27

null

UTF-8

Python

false

7,750

py

import os, time, math, astropy, pyfits, traceback, fnmatch from pandas import DataFrame, Series import IPython.display from IPython.display import Image, HTML, display from rv.FITSFile import FITSFile from rv.ImageFile import ImageFile import matplotlib.pyplot as plt NOTEBOOK_DIR = os.environ.get('RVNB_NOTEBOOK_DIR', '/notebooks') RESULTDIR = os.environ.get('RVNB_DATA_DIR', '/notebooks/data') ORIGINAL_RESULTDIR = os.environ.get('RVNB_ORIGINAL_DIR', '/notebooks/data') WIDTH = None # globally fix a plot width (inches) MINCOL = 2 # default min # of columns to display in thumbnail view MAXCOL = 4 # default max # of columns to display in thumbnail view MAXWIDTH = 16 # default width of thumbnail view (inches) DPI = 80 # screen DPI TIMEFORMAT = "%H:%M:%S %b %d" astropy.log.setLevel('ERROR') import os, time, math, astropy, pyfits, traceback, fnmatch from pandas import DataFrame, Series import IPython.display from IPython.display import Image, HTML, display import matplotlib.pyplot as plt from rv.File import DataFile from rv.Render import renderTitle,renderTable class FileList(list): _sort_attributes=dict(x="ext",n="basename",s="size",t="mtime") def __init__(self, files=[], extcol=True, thumbs=None, title="", sort="xnt"): list.__init__(self, files) self._extcol = extcol self._thumbs = thumbs self._title = title if sort: self.sort(sort) def sort(self, opt="xnt"): """Sort the filelist by name, eXtension, Time, Size, optionally Reverse""" opt = opt.lower() # build up order of comparison cmpattr = [] for attr in opt: if attr in self._sort_attributes: cmpattr.append(self._sort_attributes[attr]) def compare(a, b, attrs=cmpattr): for attr in attrs: result = cmp(getattr(a,attr),getattr(b,attr)) if result: return result return 0 list.sort(self, cmp=compare, reverse='r' in opt) self._init_df() return self def _init_df(self): if self._extcol: df_files = [(f.basename, f.ext, f.size, f.mtime_str) for f in self] self._df = DataFrame(df_files, columns=('name', 'ext', 'size', 'modified')) if df_files else None else: df_files = [(f.name, f.size, f.mtime_str) for f in self] self._df = DataFrame( df_files, columns=('name', 'size', 'modified')) if df_files else None def _repr_html_(self,ncol=1): html = renderTitle(self._title) if self._extcol: labels = "name", "ext", "size", "modified" data = [ (df.basename, df.ext, df.size_str, df.mtime_str) for df in self ] links = [ (df.fullpath, df.fullpath, None, None) for df in self ] else: labels = "name", "size", "modified" data = [ (df.basename, df.size_str, df.mtime_str) for df in self ] links = [ (df.fullpath, None, None) for df in self ] html += renderTable(data,labels,links=links,ncol=ncol) return html def show(self,ncol=1): return IPython.display.display(HTML(self._repr_html_(ncol=ncol))) def show_all(self): for f in self: f.show() def __call__(self, pattern): files = [f for f in self if fnmatch.fnmatch(f.name, pattern)] return FileList(files, extcol=self._extcol, thumbs=self._thumbs, title=os.path.join(self._title, pattern)) def thumbs(self, **kw): kw['title'] = self._title return self._thumbs(self, **kw) if self._thumbs else None def __getslice__(self, *slc): return FileList(list.__getslice__(self, *slc), extcol=self._extcol, thumbs=self._thumbs, title="%s[%s]"%(self._title,":".join(map(str,slc)))) class DataDir(object): """This class represents a directory in the data folder""" def __init__(self, name, files=[], root=""): self.fullpath = name if root and name.startswith(root): name = name[len(root):] if name.startswith("/"): name = name[1:] name = name or "." self.name = self.path = name self.mtime = os.path.getmtime(self.fullpath) files = [ f for f in files if not f.startswith('.') ] # our title, in HTML self._title = os.path.join(ORIGINAL_RESULTDIR, self.path if self.path is not "." else "") # make list of DataFiles and sort by time self.files = FileList([ DataFile(os.path.join(self.fullpath, f), root=root) for f in files], title=self._title) # make separate lists of fits files and image files self.fits = FileList([ f for f in self.files if type(f) is FITSFile], extcol=False, thumbs=FITSFile._show_thumbs, title="FITS files, " + self._title); self.images = FileList([ f for f in self.files if type(f) is ImageFile], extcol=False, thumbs=ImageFile._show_thumbs, title="Images, " + self._title) def sort(self, opt): for f in self.files, self.fits, self.images: f.sort(opt) return self def show(self): return IPython.display.display(self) def _repr_html_(self): return renderTitle(self._title) + self.files._repr_html_() class DirList(list): def __init__(self, rootfolder=None, pattern="*", scan=True, title=None): self._root = rootfolder = rootfolder or RESULTDIR self._title = title or ORIGINAL_RESULTDIR if scan: for dir_, _, files in os.walk(rootfolder): basename = os.path.basename(dir_) if fnmatch.fnmatch(basename, pattern) and not basename.startswith("."): self.append(DataDir(dir_, files, root=rootfolder)) self._sort() def _sort(self): self.sort(cmp=lambda x, y: cmp(x.name, y.name)) def _repr_html_(self): html = renderTitle(self._title) dirlist = [] for dir_ in self: nfits = len(dir_.fits) nimg = len(dir_.images) nother = len(dir_.files) - nfits - nimg dirlist.append( (dir_.name, nfits, nimg, nother, time.strftime(TIMEFORMAT,time.localtime(dir_.mtime)))) html += renderTable(dirlist, labels=("name", "# FITS", "# img", "# others", "modified")) return html def show(self): return IPython.display.display(self) def __call__(self, pattern): return DirList(self._root, pattern, title=os.path.join(self._title, pattern)) def __getslice__(self, *slc): newlist = DirList(self._root, scan=False, title="%s[%s]"%(self._title,":".join(map(str,slc)))) newlist += list.__getslice__(self, *slc) newlist._sort() return newlist # def scandirs (datafolder=DATAFOLDER): # """Scans all directories under datafolder and populates the DIRS list""" # global DIRS; # DIRS = DirList(datafolder); # for name,ds in sorted(all_dirs): # print "Contents of",name # display(d)

[ "osmirnov@gmail.com" ]

osmirnov@gmail.com

99cbf86713b07499e57c02d95ba061f54909e2b4

0aa150f1bfe3fdbdeaaeeaef5754c3e90378e935

/yearapp/migrations/0034_auto_20191008_0609.py

75095d6fe84241d240057f54d63809fb82a11f8f

[]

no_license

arshpreetsingh12/yearbook

6232eba52330b36a7404317985aea4482befd101

dac303e3cc448985256b44baae6e9baa4c8d8292

refs/heads/master

2020-08-07T19:57:00.281613

2019-10-11T13:41:49

213,571,523

0

null

UTF-8

Python

false

767

py

# Generated by Django 2.2.5 on 2019-10-08 06:09 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('yearapp', '0033_sale'), ] operations = [ migrations.AlterField( model_name='invitation', name='address', field=models.CharField(blank=True, max_length=50, null=True), ), migrations.AlterField( model_name='invitation', name='name_of_venue', field=models.CharField(blank=True, max_length=50, null=True), ), migrations.AlterField( model_name='sale', name='description', field=models.CharField(blank=True, max_length=100, null=True), ), ]

[ "director@avioxtechnologies.com" ]

director@avioxtechnologies.com

ef94b32dec93fe156549f2e821e7e2798f65812c

5b0aebb53c33124b87c8655a5923858d6a2a5bc7

/bm_preproc.py

266dc2e049dc3c7569d58d10d38f24412cdec468

[]

no_license

corylstewart/DNA-Class

440e8c0304ea568347d2dad77424ee77a74f9e01

5706b95181ef7dd73a6a9d97cc879a50663ca60a

refs/heads/master

2021-01-10T13:18:07.538528

2016-03-29T18:50:26

55,001,838

1

0

null

UTF-8

Python

false

6,110

py

"""bm_preproc.py: Boyer-Moore preprocessing.""" __author__ = "Ben Langmead" def z_array(s): """ Use Z algorithm (Gusfield theorem 1.4.1) to preprocess s """ assert len(s) > 1 z = [len(s)] + [0] * (len(s)-1) # Initial comparison of s[1:] with prefix for i in range(1, len(s)): if s[i] == s[i-1]: z[1] += 1 else: break r, l = 0, 0 if z[1] > 0: r, l = z[1], 1 for k in range(2, len(s)): assert z[k] == 0 if k > r: # Case 1 for i in range(k, len(s)): if s[i] == s[i-k]: z[k] += 1 else: break r, l = k + z[k] - 1, k else: # Case 2 # Calculate length of beta nbeta = r - k + 1 zkp = z[k - l] if nbeta > zkp: # Case 2a: zkp wins z[k] = zkp else: # Case 2b: Compare characters just past r nmatch = 0 for i in range(r+1, len(s)): if s[i] == s[i - k]: nmatch += 1 else: break l, r = k, r + nmatch z[k] = r - k + 1 return z def n_array(s): """ Compile the N array (Gusfield theorem 2.2.2) from the Z array """ return z_array(s[::-1])[::-1] def big_l_prime_array(p, n): """ Compile L' array (Gusfield theorem 2.2.2) using p and N array. L'[i] = largest index j less than n such that N[j] = |P[i:]| """ lp = [0] * len(p) for j in range(len(p)-1): i = len(p) - n[j] if i < len(p): lp[i] = j + 1 return lp def big_l_array(p, lp): """ Compile L array (Gusfield theorem 2.2.2) using p and L' array. L[i] = largest index j less than n such that N[j] >= |P[i:]| """ l = [0] * len(p) l[1] = lp[1] for i in range(2, len(p)): l[i] = max(l[i-1], lp[i]) return l def small_l_prime_array(n): """ Compile lp' array (Gusfield theorem 2.2.4) using N array. """ small_lp = [0] * len(n) for i in range(len(n)): if n[i] == i+1: # prefix matching a suffix small_lp[len(n)-i-1] = i+1 for i in range(len(n)-2, -1, -1): # "smear" them out to the left if small_lp[i] == 0: small_lp[i] = small_lp[i+1] return small_lp def good_suffix_table(p): """ Return tables needed to apply good suffix rule. """ n = n_array(p) lp = big_l_prime_array(p, n) return lp, big_l_array(p, lp), small_l_prime_array(n) def good_suffix_mismatch(i, big_l_prime, small_l_prime): """ Given a mismatch at offset i, and given L/L' and l' arrays, return amount to shift as determined by good suffix rule. """ length = len(big_l_prime) assert i < length if i == length - 1: return 0 i += 1 # i points to leftmost matching position of P if big_l_prime[i] > 0: return length - big_l_prime[i] return length - small_l_prime[i] def good_suffix_match(small_l_prime): """ Given a full match of P to T, return amount to shift as determined by good suffix rule. """ return len(small_l_prime) - small_l_prime[1] def dense_bad_char_tab(p, amap): """ Given pattern string and list with ordered alphabet characters, create and return a dense bad character table. Table is indexed by offset then by character. """ tab = [] nxt = [0] * len(amap) for i in range(0, len(p)): c = p[i] assert c in amap tab.append(nxt[:]) nxt[amap[c]] = i+1 return tab class BoyerMoore(object): """ Encapsulates pattern and associated Boyer-Moore preprocessing. """ def __init__(self, p, alphabet='ACGT'): # Create map from alphabet characters to integers self.amap = {alphabet[i]: i for i in range(len(alphabet))} # Make bad character rule table self.bad_char = dense_bad_char_tab(p, self.amap) # Create good suffix rule table _, self.big_l, self.small_l_prime = good_suffix_table(p) def bad_character_rule(self, i, c): """ Return # skips given by bad character rule at offset i """ assert c in self.amap assert i < len(self.bad_char) ci = self.amap[c] return i - (self.bad_char[i][ci]-1) def good_suffix_rule(self, i): """ Given a mismatch at offset i, return amount to shift as determined by (weak) good suffix rule. """ length = len(self.big_l) assert i < length if i == length - 1: return 0 i += 1 # i points to leftmost matching position of P if self.big_l[i] > 0: return length - self.big_l[i] return length - self.small_l_prime[i] def match_skip(self): """ Return amount to shift in case where P matches T """ return len(self.small_l_prime) - self.small_l_prime[1] def naive_find_matches_with_counter(p, t): matches = list() total_comps = 0 for i in xrange(len(t)-len(p)+1): matched = True for j in range(len(p)): total_comps += 1 if p[j] != t[i+j]: matched = False break if matched: matches.append(i) return (total_comps, matches) def boyer_moore_with_counter(p, p_bm, t): """ Do Boyer-Moore matching. p=pattern, t=text, p_bm=BoyerMoore object for p """ i = 0 total_comps = 0 while i < len(t) - len(p) + 1: total_comps += 1 shift = 1 mismatched = False for j in range(len(p)-1, -1, -1): if p[j] != t[i+j]: skip_bc = p_bm.bad_character_rule(j, t[i+j]) skip_gs = p_bm.good_suffix_rule(j) shift = max(shift, skip_bc, skip_gs) mismatched = True break if not mismatched: skip_gs = p_bm.match_skip() shift = max(shift, skip_gs) i += shift return total_comps

[ "corylstewart@gmail.com" ]

corylstewart@gmail.com

3b33c6da73e70bcb25b56b4fd175de4ac366f2a8

f0d713996eb095bcdc701f3fab0a8110b8541cbb

/9S8qp4XKG2qwQMdrb_2.py

07908c297beae33944959e2c40e6e492d0f35bf6

[]

no_license

daniel-reich/turbo-robot

feda6c0523bb83ab8954b6d06302bfec5b16ebdf

a7a25c63097674c0a81675eed7e6b763785f1c41

refs/heads/main

2023-03-26T01:55:14.210264

2021-03-23T16:08:01

350,773,815

0

null

UTF-8

Python

false

542

py

""" Write a function that returns the number of ways a person can climb **n stairs** , where the person may only climb **1** or **2** steps at a time. To illustrate, if **n = 4** there are **5** ways to climb: [1, 1, 1, 1] [2, 1, 1] [1, 2, 1] [1, 1, 2] [2, 2] ### Examples ways_to_climb(1) ➞ 1 ways_to_climb(2) ➞ 2 ways_to_climb(5) ➞ 8 ### Notes A staircase of height `0` should return `1`. """ def ways_to_climb(n): r=(1+5**.5)/2 return round((r**(n+1)-(1-r)**(n+1))/(5**.5))

[ "daniel.reich@danielreichs-MacBook-Pro.local" ]

daniel.reich@danielreichs-MacBook-Pro.local

9fe4cb94c81a6b0a10f86ec898adfb99833b6625

9743d5fd24822f79c156ad112229e25adb9ed6f6

/xai/brain/wordbase/verbs/_nicking.py

8ade774452ec36eabf9b8b12da80103b68a5a982

[ "MIT" ]

permissive

cash2one/xai

de7adad1758f50dd6786bf0111e71a903f039b64

e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6

refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

null

0

null

UTF-8

Python

false

228

py

from xai.brain.wordbase.verbs._nick import _NICK #calss header class _NICKING(_NICK, ): def __init__(self,): _NICK.__init__(self) self.name = "NICKING" self.specie = 'verbs' self.basic = "nick" self.jsondata = {}

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

44e5115d831d8f11ee4ec8b575906d3138700fbf

348aeccddd5fdb48fb91a63d170b7f0453f70e36

/libcloud/utils/files.py

201e94a4e3a873553fc3a035aa2b8953785c0c0e

[ "Apache-2.0" ]

permissive

lelou6666/libcloud

4eb08e236cb9f4b787fa73ce963347f708faf092

bff26fe27fdd53979e32e08038ecd2fc108b6083

refs/heads/trunk

2021-01-14T14:02:16.661579

2013-10-28T11:18:08

55,902,523

0

null

2016-04-10T14:08:20

null

UTF-8

Python

false

3,437

py

# 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. import os import mimetypes from libcloud.utils.py3 import PY3 from libcloud.utils.py3 import httplib from libcloud.utils.py3 import next from libcloud.utils.py3 import b CHUNK_SIZE = 8096 if PY3: from io import FileIO as file def read_in_chunks(iterator, chunk_size=None, fill_size=False): """ Return a generator which yields data in chunks. :type iterator: :class:`object` which implements iterator interface. :param response: An object which implements an iterator interface or a File like object with read method. :type chunk_size: ``int`` :param chunk_size: Optional chunk size (defaults to CHUNK_SIZE) :type fill_size: ``bool`` :param fill_size: If True, make sure chunks are chunk_size in length (except for last chunk). TODO: At some point in the future we could use byte arrays here if version >= Python 3. This should speed things up a bit and reduce memory usage. """ chunk_size = chunk_size or CHUNK_SIZE if isinstance(iterator, (file, httplib.HTTPResponse)): get_data = iterator.read args = (chunk_size, ) else: get_data = next args = (iterator, ) data = b('') empty = False while not empty or len(data) > 0: if not empty: try: chunk = b(get_data(*args)) if len(chunk) > 0: data += chunk else: empty = True except StopIteration: empty = True if len(data) == 0: raise StopIteration if fill_size: if empty or len(data) >= chunk_size: yield data[:chunk_size] data = data[chunk_size:] else: yield data data = b('') def exhaust_iterator(iterator): """ Exhaust an iterator and return all data returned by it. :type iterator: :class:`object` which implements iterator interface. :param response: An object which implements an iterator interface or a File like object with read method. :rtype ``str`` :return Data returned by the iterator. """ data = b('') try: chunk = b(next(iterator)) except StopIteration: chunk = b('') while len(chunk) > 0: data += chunk try: chunk = b(next(iterator)) except StopIteration: chunk = b('') return data def guess_file_mime_type(file_path): filename = os.path.basename(file_path) (mimetype, encoding) = mimetypes.guess_type(filename) return mimetype, encoding

[ "tomaz@apache.org" ]

tomaz@apache.org

cead28e09d8898e94fd635d1ede4ab5cabf171fe

16b77438b7a7923a391a12f1f4bc12b49429bb73

/src/PIPE/PIPE.py

afa369355271987d911ce5454c61b803916fa8aa

[]

no_license

OpenJ92/zebra

eb582c36fd7110ccf5866eb34418ff9e725efd5d

2d3d3d42bb0461901f2418069a55e47cf8450c50

refs/heads/master

2020-11-29T14:29:37.279589

2020-01-18T19:54:07

230,138,421

0

null

UTF-8

Python

false

1,042

py

from src.NODE.NODE import NODE class PIPE(object): def __init__(self, form): self._name, self._kwargs = *form.keys(), *form.values() self.__gen_nodes__(); self._transformed = self.__execute__({'Data1':1, 'Data2':1}) def __gen_nodes__(self): self._nodes = [NODE(kw) for kw in self._kwargs] self._nodes = {f"{self._name}_{node._name}": node \ for node in self._nodes} def __execute__(self, Xs): node = self._nodes[f"{self._name}_HEAD"] while True: print(Xs, node._name) Xs = { \ name: \ (node._map._apply_(data) if name in node._on else data)\ for name, data in Xs.items() \ } if "TAIL" in node._name: return Xs node = self._nodes[f"{self._name}_{next(node)}"] return Xs

[ "jacob.vartuli.92@gmail.com" ]

jacob.vartuli.92@gmail.com

19b365204ddcf74e34ab42a5f2b0d756622c9ad5

ca55dcaa64ea9db4068e13091321cfebecc0ff41

/codeUp/codeUpBasic/1990.py

bca5b69987f830843fdbdeecd27fbb8549319697

[]

no_license

gomtinQQ/algorithm-python

8fb8343594b945099ae2a4dfa794ecb47e54ab0b

751562922b66e335f621d366bb73dacdc7125140

refs/heads/master

2022-12-07T23:05:44.535593

2020-08-21T12:29:58

null

0

null

UTF-8

Python

false

239

py

''' 1990 : 3의 배수 판별하기 자연수 n이 입력되면 3의 배수인지 아닌지 판별하시오. 3의 배수이면 1을 출력하고, 아니면 0을 출력한다. ''' n = int(input()) if(n%3==0): print(1) else: print(0)

[ "minhyeonlee1@gmail.com" ]

minhyeonlee1@gmail.com

0f035ba1c524afe06432726820c34655340ac8c6

82fce9aae9e855a73f4e92d750e6a8df2ef877a5

/Lab/venv/lib/python3.8/site-packages/OpenGL/raw/GL/ARB/texture_storage_multisample.py

fdcdbc160823f7a5f0c538918cf1a7c652b4e9a0

[]

no_license

BartoszRudnik/GK

1294f7708902e867dacd7da591b9f2e741bfe9e5

6dc09184a3af07143b9729e42a6f62f13da50128

refs/heads/main

2023-02-20T19:02:12.408974

2021-01-22T10:51:14

307,847,589

0

null

UTF-8

Python

false

879

py

'''Autogenerated by xml_generate script, do not edit!''' from OpenGL import platform as _p # End users want this... from OpenGL.raw.GL import _errors # Code generation uses this from OpenGL.raw.GL import _types as _cs _EXTENSION_NAME = 'GL_ARB_texture_storage_multisample' def _f(function): return _p.createFunction(function, _p.PLATFORM.GL, 'GL_ARB_texture_storage_multisample', error_checker=_errors._error_checker) @_f @_p.types(None, _cs.GLenum, _cs.GLsizei, _cs.GLenum, _cs.GLsizei, _cs.GLsizei, _cs.GLboolean) def glTexStorage2DMultisample(target, samples, internalformat, width, height, fixedsamplelocations): pass @_f @_p.types(None, _cs.GLenum, _cs.GLsizei, _cs.GLenum, _cs.GLsizei, _cs.GLsizei, _cs.GLsizei, _cs.GLboolean) def glTexStorage3DMultisample(target,samples,internalformat,width,height,depth,fixedsamplelocations):pass

[ "rudnik49@gmail.com" ]

rudnik49@gmail.com

8a6874d0099dce3f2d73698422596393937926c4

1422a57e98aba02321b772d72f8f0ada6d8b8cba

/mm/models/shared/augmentation.py

91ccf3fae4c30c7c4b6af2cc19bd690100302532

[ "MIT" ]

permissive

JonasRSV/Friday

e1908a411aa133bc5bd2f383b0a995f7e028092d

f959eff95ba7b11525f97099c8f5ea0e325face7

refs/heads/main

2023-05-15T03:33:21.542621

2021-06-12T10:34:50

315,309,991

7

2

null

UTF-8

Python

false

604

py

from typing import List import tensorflow as tf import numpy as np import models.shared.augmentations as a import random def create_audio_augmentations(aug: List[a.Augmentation], p: np.ndarray): if len(aug) != len(p): raise ValueError(f"Length of augmentations must match distribution {len(aug)} != {len(p)}") def audio_augmentations(audio: np.ndarray, sample_rate: int): for aug_to_apply, with_prob in zip(aug, p): if np.random.rand() < with_prob: audio = aug_to_apply.apply(audio, sample_rate) return audio return audio_augmentations

[ "jonas@valfridsson.net" ]

jonas@valfridsson.net

d613832fb1e4fbf8daf1f43cb77c47396088f146

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_181/ch4_2020_03_05_16_07_05_989464.py

dff125cf8d4a74499e2b22478368603f7e78b838

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

null

UTF-8

Python

false

142

py

def classifica_idade(i): if i<12: return 'crianca' if 18>i>12: return 'adolescente' else: return 'adulto'

[ "you@example.com" ]

you@example.com

83b9b89602f94805f1ff6283f7237c42100ead2a

f5a7de717f41f8379ccdee7d06de838fdf1d0a0b

/soloperformance-api/apps/catalog/management/commands/exercises.py

b73d1df31fb2d914106dd6d80bd4253425dbe55c

[]

no_license

jimmy818/mexico-angular

977e4d1d0cab2ff8c10c9892d9c72ca2f4f9ac49

005ed3729b807d77a8fd97a3b5469a42ceefdaad

refs/heads/main

2023-08-10T21:37:53.614298

2021-05-11T19:04:29

366,485,541

0

null

UTF-8

Python

false

1,560

py

from django.core.management.base import BaseCommand, CommandError from django.http import HttpRequest import requests import xlrd from apps.catalog import utils class Command(BaseCommand): help = 'Add exercises' def handle(self, *args, **options): request = HttpRequest() r = requests.get('https://d2femlmiaazi1b.cloudfront.net/media/excel/DB_Drills.xlsx') with open('/tmp/excel.xlsx', 'wb') as f: f.write(r.content) path = '/tmp/excel.xlsx' book = xlrd.open_workbook(path) # sheets = book.sheet_names() sheet_0 = book.sheet_by_index(0) # Open the first tab ## this range is for excercices length for row_index in range(1012): if row_index > 3: excercice = None for col_index in range(sheet_0.ncols): item = sheet_0.cell(rowx=row_index,colx=col_index).value if excercice == None: excercice = item excercice_item = utils.get_or_add_excercice(excercice) else: if item != None and item != '': utils.add_sub_excercice(excercice_item,sheet_0.cell(rowx=3,colx=col_index).value) print(excercice) print(sheet_0.cell(rowx=3,colx=col_index).value) self.stdout.write(self.style.SUCCESS('Successfully.....'))

[ "45069768+itsrocketfuel@users.noreply.github.com" ]

45069768+itsrocketfuel@users.noreply.github.com

84555327ae07d2945fac7b3d7ca618e1946fb291

e56214188faae8ebfb36a463e34fc8324935b3c2

/intersight/models/workflow_default_value_ref.py

18613e62146e7f7c285e489454fb63c30fab824b

[ "Apache-2.0" ]

permissive

CiscoUcs/intersight-python

866d6c63e0cb8c33440771efd93541d679bb1ecc

a92fccb1c8df4332ba1f05a0e784efbb4f2efdc4

refs/heads/master

2021-11-07T12:54:41.888973

2021-10-25T16:15:50

115,440,875

25

18

Apache-2.0

2020-03-02T16:19:49

2017-12-26T17:14:03

Python

UTF-8

Python

false

5,734

py

# coding: utf-8 """ Cisco Intersight OpenAPI specification. The Cisco Intersight OpenAPI specification. OpenAPI spec version: 1.0.9-1461 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class WorkflowDefaultValueRef(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'object_type': 'str', 'moid': 'str', 'selector': 'str' } attribute_map = { 'object_type': 'ObjectType', 'moid': 'Moid', 'selector': 'Selector' } def __init__(self, object_type=None, moid=None, selector=None): """ WorkflowDefaultValueRef - a model defined in Swagger """ self._object_type = None self._moid = None self._selector = None if object_type is not None: self.object_type = object_type if moid is not None: self.moid = moid if selector is not None: self.selector = selector @property def object_type(self): """ Gets the object_type of this WorkflowDefaultValueRef. The Object Type of the referenced REST resource. :return: The object_type of this WorkflowDefaultValueRef. :rtype: str """ return self._object_type @object_type.setter def object_type(self, object_type): """ Sets the object_type of this WorkflowDefaultValueRef. The Object Type of the referenced REST resource. :param object_type: The object_type of this WorkflowDefaultValueRef. :type: str """ self._object_type = object_type @property def moid(self): """ Gets the moid of this WorkflowDefaultValueRef. The Moid of the referenced REST resource. :return: The moid of this WorkflowDefaultValueRef. :rtype: str """ return self._moid @moid.setter def moid(self, moid): """ Sets the moid of this WorkflowDefaultValueRef. The Moid of the referenced REST resource. :param moid: The moid of this WorkflowDefaultValueRef. :type: str """ self._moid = moid @property def selector(self): """ Gets the selector of this WorkflowDefaultValueRef. An OData $filter expression which describes the REST resource to be referenced. This field may be set instead of 'moid' by clients. If 'moid' is set this field is ignored. If 'selector' is set and 'moid' is empty/absent from the request, Intersight will determine the Moid of the resource matching the filter expression and populate it in the MoRef that is part of the object instance being inserted/updated to fulfill the REST request. An error is returned if the filter matches zero or more than one REST resource. An example filter string is: Serial eq '3AA8B7T11'. :return: The selector of this WorkflowDefaultValueRef. :rtype: str """ return self._selector @selector.setter def selector(self, selector): """ Sets the selector of this WorkflowDefaultValueRef. An OData $filter expression which describes the REST resource to be referenced. This field may be set instead of 'moid' by clients. If 'moid' is set this field is ignored. If 'selector' is set and 'moid' is empty/absent from the request, Intersight will determine the Moid of the resource matching the filter expression and populate it in the MoRef that is part of the object instance being inserted/updated to fulfill the REST request. An error is returned if the filter matches zero or more than one REST resource. An example filter string is: Serial eq '3AA8B7T11'. :param selector: The selector of this WorkflowDefaultValueRef. :type: str """ self._selector = selector def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """ Returns the string representation of the model """ return 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, WorkflowDefaultValueRef): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

[ "ucs-build@github.com" ]

ucs-build@github.com

1727d04b8a7d1014b6e1d7a1ae539f023ea9f601

1713334f9b68255f9adab70175c21f399d0460f3

/python/125_Valid_Palindrome.py

4d198f026b9d9fad4550fee87f5e98972fb8c355

[ "MIT" ]

permissive

coy0725/leetcode

0a798b7adafe80f726e51c06c34835c4aa51b563

743a0bfa22402ec39858dc9c4c7dc531f825b953

refs/heads/master

2020-05-21T18:25:09.683714

2019-05-11T13:00:40

186,132,894

2

0

MIT

2019-05-11T12:55:22

2019-05-11T12:55:21

null

UTF-8

Python

false

395

py

class Solution(object): def isPalindrome(self, s): """ :type s: str :rtype: bool """ alnum_s = [t.lower() for t in s if t.isalnum()] ls = len(alnum_s) if ls <= 1: return True mid = ls / 2 for i in range(mid): if alnum_s[i] != alnum_s[ls - 1 - i]: return False return True

[ "qiyuangong@gmail.com" ]

qiyuangong@gmail.com

d9e06504505b6a186387d2ff84264d0ecf0308fb

83d657c787529f01a8ecc8a874421738a7eecec7

/Paths/Harmonise Curve to Line.py

753600a50daceb8ddc9121810ba918269ff339b9

[ "Apache-2.0" ]

permissive

BurgAndOeden/Glyphs-Scripts

e31b5164b491dfe0cd2d57f6cf1422c4aadda104

f0195d6b8f0a6c055e4e44d5ef41ba48bdd1e3a6

refs/heads/master

2020-09-16T08:01:06.345898

2019-11-24T00:15:44

null

0

null

UTF-8

Python

false

5,124

py

#MenuTitle: Harmonise Curve to Line # -*- coding: utf-8 -*- __doc__=""" Maximises opposing handles and reduces adjacent handles of line segments. """ from Foundation import NSPoint def intersectionWithNSPoints( pointA, pointB, pointC, pointD ): """ Returns an NSPoint of the intersection AB with CD. Or False if there is no intersection """ try: x1, y1 = pointA.x, pointA.y x2, y2 = pointB.x, pointB.y x3, y3 = pointC.x, pointC.y x4, y4 = pointD.x, pointD.y try: slope12 = ( float(y2) - float(y1) ) / ( float(x2) - float(x1) ) except: # division by zero if vertical slope12 = None try: slope34 = ( float(y4) - float(y3) ) / ( float(x4) - float(x3) ) except: # division by zero if vertical slope34 = None if slope12 == slope34: # parallel, no intersection return None elif slope12 is None: # first line is vertical x = x1 y = slope34 * ( x - x3 ) + y3 elif slope34 is None: # second line is vertical x = x3 y = slope12 * ( x - x1 ) + y1 else: # both lines have an angle x = ( slope12 * x1 - y1 - slope34 * x3 + y3 ) / ( slope12 - slope34 ) y = slope12 * ( x - x1 ) + y1 intersectionPoint = NSPoint( x, y ) if bothPointsAreOnSameSideOfOrigin( intersectionPoint, pointB, pointA ) and bothPointsAreOnSameSideOfOrigin( intersectionPoint, pointC, pointD ): if pointIsBetweenOtherPoints( intersectionPoint, pointB, pointA ) or pointIsBetweenOtherPoints( intersectionPoint, pointC, pointD ): return None return intersectionPoint else: return None except Exception as e: print str(e) import traceback print traceback.format_exc() return None def pointDistance( P1, P2 ): """Calculates the distance between P1 and P2.""" x1, y1 = P1.x, P1.y x2, y2 = P2.x, P2.y dist = ( ( float(x2) - float(x1) ) ** 2 + ( float(y2) - float(y1) ) **2 ) ** 0.5 return dist def bezier( x1, y1, x2,y2, x3,y3, x4,y4, t ): x = x1*(1-t)**3 + x2*3*t*(1-t)**2 + x3*3*t**2*(1-t) + x4*t**3 y = y1*(1-t)**3 + y2*3*t*(1-t)**2 + y3*3*t**2*(1-t) + y4*t**3 return x, y def bothPointsAreOnSameSideOfOrigin( pointA, pointB, pointOrigin ): returnValue = True xDiff = (pointA.x-pointOrigin.x) * (pointB.x-pointOrigin.x) yDiff = (pointA.y-pointOrigin.y) * (pointB.y-pointOrigin.y) if xDiff <= 0.0 and yDiff <= 0.0: returnValue = False return returnValue def pointIsBetweenOtherPoints( thisPoint, otherPointA, otherPointB) : returnValue = False xDiffAB = otherPointB.x - otherPointA.x yDiffAB = otherPointB.y - otherPointA.y xDiffAP = thisPoint.x - otherPointA.x yDiffAP = thisPoint.y - otherPointA.y xDiffFactor = divideAndTolerateZero( xDiffAP, xDiffAB ) yDiffFactor = divideAndTolerateZero( yDiffAP, yDiffAB ) if xDiffFactor: if 0.0<=xDiffFactor<=1.0: returnValue = True if yDiffFactor: if 0.0<=xDiffFactor<=1.0: returnValue = True return returnValue def divideAndTolerateZero( dividend, divisor ): if float(divisor) == 0.0: return None else: return dividend/divisor def handleLength(a,b,intersection): return pointDistance(a,b)/pointDistance(a,intersection) def moveHandle(a,b,intersection,bPercentage): x = a.x + (intersection.x-a.x) * bPercentage y = a.y + (intersection.y-a.y) * bPercentage return NSPoint(x,y) Font = Glyphs.font if len(Font.selectedLayers) > 1: selectionCounts = False elif not Font.selectedLayers[0].selection: selectionCounts = False else: selectionCounts = True for selectedLayer in Font.selectedLayers: selectedGlyph = selectedLayer.parent selectedGlyph.beginUndo() # put original state in background: selectedLayer.contentToBackgroundCheckSelection_keepOldBackground_(False,False) for path in selectedLayer.paths: for n in path.nodes: processedHandles = [] if (n.selected or not selectionCounts) and n.type == OFFCURVE: # determine the segment: if n.prevNode.type == OFFCURVE: a = n.prevNode.prevNode b = n.prevNode c = n d = n.nextNode else: a = n.prevNode b = n c = n.nextNode d = n.nextNode.nextNode if not a in processedHandles and not b in processedHandles: # intersection of the magic triangle: intersection = intersectionWithNSPoints( a.position, b.position, c.position, d.position ) if intersection: # calculate percentages: bLength = handleLength(a,b,intersection) cLength = handleLength(d,c,intersection) shortLength = (abs(bLength) + abs(cLength) - 1.0) - (1.0-abs(bLength))*(1.0-abs(cLength)) if d.nextNode.type == LINE and a.prevNode.type != LINE and d.connection == GSSMOOTH: # max handle: b.position = intersection # reduced handle: c.position = moveHandle(d,c,intersection,shortLength) elif a.prevNode.type == LINE and d.nextNode.type != LINE and a.connection == GSSMOOTH: # max handle: c.position = intersection # reduced handle: b.position = moveHandle(a,b,intersection,shortLength) # mark handles as processed: processedHandles.append(a) processedHandles.append(b) selectedGlyph.endUndo()

[ "res@glyphsapp.com" ]

res@glyphsapp.com

998dbc4a900cf93aa3ee0d2e520aed575aca4de5

02ad25c4ac78a98b5493a2aa7f744a77f381aaae

/dashboard_app/migrations/0010_auto_20201211_0846.py

2168834a1f6db118e06a45e41521adce387ce856

[]

no_license

cavidanhasanli/Havayi

1f85d0d7608c964b0ddc80e3b526b32cdb81e8bf

bd30c9e3e700c7381b5961b5051cbcb398adc449

refs/heads/main

2023-02-03T09:25:03.866784

2020-12-22T18:09:07

316,319,183

0

null

UTF-8

Python

false

911

py

# Generated by Django 3.1.3 on 2020-12-11 08:46 import django.core.validators from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('dashboard_app', '0009_auto_20201211_0839'), ] operations = [ migrations.DeleteModel( name='CreditTypeInterest', ), migrations.AddField( model_name='banklist', name='credit_type', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='dashboard_app.creditfields'), ), migrations.AddField( model_name='banklist', name='interest', field=models.FloatField(blank=True, default=0, null=True, validators=[django.core.validators.MinValueValidator(0.1), django.core.validators.MaxValueValidator(100)]), ), ]

[ "cavidan.hasanli@mail.ru" ]

cavidan.hasanli@mail.ru

d4e96ddfa8c091f87bd220375da45cf8ce6295f4

679ce4b323f79b2425976201324c6c1f88b95199

/Python/Stanley Cup/csv_parser.py

53294c7db661e390948575da2be855cee905e598

[]

no_license

abriggs914/Coding_Practice

ff690fb5f145a11f4da144f3882b37f473b10450

3afd7c59e0d90f0ef5f6203853e69f853312019b

refs/heads/master

2023-08-31T04:04:58.048554

2023-08-29T13:23:29

161,865,421

0

1

null

2022-10-27T08:35:29

2018-12-15T03:20:14

Python

UTF-8

Python

false

7,689

py

import csv from utility import * file_name = "past winners.csv" # skip 2005 back fill with open(file_name) as csv_file: lines = csv.DictReader(csv_file) data_by_year = {} header = lines.fieldnames print("header", header) last = None for i, line in enumerate(lines): if last is not None: if any([val is None or val == "" for val in line.values()]): #print("missing values, check last:", last) if line["Year"] == "2005": continue for last_key, curr_key in zip(last, line): last_val = last[last_key] curr_val = line[curr_key] if curr_val is None or curr_val == "": line[curr_key] = last_val line["Winning Team"] = line["Winning Team"].split("(")[0].strip() line["Losing Team"] = line["Losing Team"].split("(")[0].strip() print(dict_print(line)) data_by_year[str(line["Year"])] = line if 0 < i: last = line data_by_year = {k:v for k, v in data_by_year.items() if "1995" <= k} print(dict_print(data_by_year, "data_by_year")) data_by_team = {} data_by_coach = {} first_year = None last_year = None for key, val in data_by_year.items(): year = int(key) if first_year is None: first_year = year if last_year is None or year > last_year: last_year = year w_team = val["Winning Team"] l_team = val["Losing Team"] if w_team not in data_by_team: data_by_team[w_team] = {"WYear": [], "LYear": [], "appearances": 0} if l_team not in data_by_team: data_by_team[l_team] = {"WYear": [], "LYear": [], "appearances": 0} data_by_team[w_team]["WYear"].append(key) data_by_team[l_team]["LYear"].append(key) data_by_team[w_team]["appearances"] += 1 data_by_team[l_team]["appearances"] += 1 data_by_team[w_team]["W% (per appearance)"] = len(data_by_team[w_team]["WYear"]) / data_by_team[w_team]["appearances"] data_by_team[l_team]["W% (per appearance)"] = len(data_by_team[l_team]["WYear"]) / data_by_team[l_team]["appearances"] data_by_team[l_team]["L% (per appearance)"] = len(data_by_team[l_team]["LYear"]) / data_by_team[l_team]["appearances"] data_by_team[w_team]["L% (per appearance)"] = len(data_by_team[w_team]["LYear"]) / data_by_team[w_team]["appearances"] w_coach = val["WCoach"] l_coach = val["LCoach"] if w_coach not in data_by_coach: data_by_coach[w_coach] = {"WYear": [], "LYear": [], "appearances": 0} if l_coach not in data_by_coach: data_by_coach[l_coach] = {"WYear": [], "LYear": [], "appearances": 0} data_by_coach[w_coach]["WYear"].append(key) data_by_coach[l_coach]["LYear"].append(key) data_by_coach[w_coach]["appearances"] += 1 data_by_coach[l_coach]["appearances"] += 1 data_by_coach[w_coach]["W% (per appearance)"] = percent(len(data_by_coach[w_coach]["WYear"]) / data_by_coach[w_coach]["appearances"]) data_by_coach[l_coach]["W% (per appearance)"] = percent(len(data_by_coach[l_coach]["WYear"]) / data_by_coach[l_coach]["appearances"]) data_by_coach[l_coach]["L% (per appearance)"] = percent(len(data_by_coach[l_coach]["LYear"]) / data_by_coach[l_coach]["appearances"]) data_by_coach[w_coach]["L% (per appearance)"] = percent(len(data_by_coach[w_coach]["LYear"]) / data_by_coach[w_coach]["appearances"]) teams_list = list(data_by_team.keys()) teams_list.sort() for team in data_by_team: w_list = data_by_team[team]["WYear"] l_list = data_by_team[team]["LYear"] data_by_team[team]["Appearance % ({} to {})".format(first_year, last_year)] = percent((len(w_list) + len(l_list)) / (last_year - first_year)) data_by_team[team]["Appearance W% ({} to {})".format(first_year, last_year)] = percent(len(w_list) / (last_year - first_year)) data_by_team[team]["Appearance L% ({} to {})".format(first_year, last_year)] = percent(len(l_list) / (last_year - first_year)) #data_by_team[team]["won_against"] = [] #data_by_team[team]["lost_against"] = [] greatest_rival = None most_lost_to = None most_won_against = None for team_b in teams_list: # if team != team_b: if team_b not in data_by_team[team]: data_by_team[team][team_b] = {"won_against": [], "lost_against": []} for year in data_by_team[team]["WYear"]: if data_by_year[year]["Losing Team"] == team_b: data_by_team[team][team_b]["won_against"].append(year) for year in data_by_team[team]["LYear"]: if data_by_year[year]["Winning Team"] == team_b: data_by_team[team][team_b]["lost_against"].append(year) if greatest_rival is None: greatest_rival = (team_b, data_by_team[team][team_b]["won_against"] + data_by_team[team][team_b]["lost_against"]) elif len(data_by_team[team][team_b]["won_against"]) + len(data_by_team[team][team_b]["lost_against"]) > len(greatest_rival[1]): greatest_rival = (team_b, data_by_team[team][team_b]["won_against"] + data_by_team[team][team_b]["lost_against"]) elif len(data_by_team[team][team_b]["won_against"]) + len(data_by_team[team][team_b]["lost_against"]) == len(greatest_rival[1]): if data_by_team[team][team_b]["won_against"] + data_by_team[team][team_b]["lost_against"]: if max(data_by_team[team][team_b]["won_against"] + data_by_team[team][team_b]["lost_against"]) > max(greatest_rival[1]): greatest_rival = (team_b, data_by_team[team][team_b]["won_against"] + data_by_team[team][team_b]["lost_against"]) if most_lost_to is None: most_lost_to = (team_b, data_by_team[team][team_b]["lost_against"]) elif len(data_by_team[team][team_b]["lost_against"]) > len(most_lost_to[1]): most_lost_to = (team_b, data_by_team[team][team_b]["lost_against"]) elif len(data_by_team[team][team_b]["lost_against"]) == len(most_lost_to[1]): if data_by_team[team][team_b]["lost_against"]: if max(data_by_team[team][team_b]["lost_against"]) > max(most_lost_to[1]): most_lost_to = (team_b, data_by_team[team][team_b]["lost_against"]) if most_won_against is None: most_won_against = (team_b, data_by_team[team][team_b]["won_against"]) elif len(data_by_team[team][team_b]["won_against"]) > len(most_won_against[1]): most_won_against = (team_b, data_by_team[team][team_b]["won_against"]) elif len(data_by_team[team][team_b]["won_against"]) == len(most_won_against[1]): if data_by_team[team][team_b]["won_against"]: if max(data_by_team[team][team_b]["won_against"]) > max(most_won_against[1]): most_won_against = (team_b, data_by_team[team][team_b]["won_against"]) data_by_team[team]["greatest_rival"] = greatest_rival if most_lost_to[1]: data_by_team[team]["most_lost_to"] = most_lost_to if most_won_against[1]: data_by_team[team]["most_won_against"] = most_won_against print(dict_print(data_by_team, "Data By Team")) print("parsed teams:\n", "\n".join(teams_list)) for coach in data_by_coach: w_list = data_by_coach[coach]["WYear"] l_list = data_by_coach[coach]["LYear"] data_by_coach[coach]["Appearance % ({} to {})".format(first_year, last_year)] = (len(w_list) + len(l_list)) / (last_year - first_year) data_by_coach[coach]["Appearance W% ({} to {})".format(first_year, last_year)] = len(w_list) / (last_year - first_year) data_by_coach[coach]["Appearance L% ({} to {})".format(first_year, last_year)] = len(l_list) / (last_year - first_year) print(dict_print(data_by_coach, "Data By Team")) coaches_list = list(data_by_coach.keys()) coaches_list.sort() print("parsed coaches:\n", "\n".join(coaches_list)) # count # time each team / coach has won. # count # time each team met and won/lost against each other team. # count # GWG -> period, timeOfPeriod

[ "abriggs1@unb.ca" ]

abriggs1@unb.ca

4eb48a87e664b4cabd5416d2d6729ed9a88b43a1

49cd9ba075ed2ab6b267f6e012bfb03267b7bc08

/project_42_formsModelpagination/app42/forms.py

99db23b3c75ea231d95bd12b4e9224ed18e651db

[]

no_license

Satputev/DjangoApps

4d47a76f20815b2b1313e8b3e3c61b5406f5da60

c6fb5e9fa131f07d1f5920e98699f9daaa49d424

refs/heads/master

2023-02-14T00:42:36.037749

2020-12-24T07:39:54

323,857,826

1

0

null

UTF-8

Python

false

527

py

from django import forms from app42.models import ProductsModel from django.forms import ValidationError class ProductForm(forms.ModelForm): class Meta: model=ProductsModel fields='__all__' exclude=('pid',) labels={'pname':'Product Name','pprice':'Product Price','pimg':'Product Image'} def clean_pprice(self): price=self.cleaned_data['pprice'] if price < 1: raise ValidationError('price should be greater than "0"') else: return price

[ "satputevishal8@gmail.com" ]

satputevishal8@gmail.com

694b8b138f3b4862d4b35953cdb3675a91e2a179

fd25231975acd147e04dc3ed3627c92cb1a4f86c

/FlaskAPI/vir_env/lib/python3.7/site-packages/scipy/spatial/tests/test_distance.py

c0b831a2879fa2a21e753350d7b7edefe48591cf

[]

no_license

sumitkutty/Flight-Price-Prediction

832a2802a3367e655b46d3b44f073d917abd2320

d974a8b75fbcbfa42f11703602af3e45a3f08b3c

refs/heads/master

2022-12-25T07:13:06.375888

2020-10-08T18:46:44

302,366,725

0

null

UTF-8

Python

false

130

py

version https://git-lfs.github.com/spec/v1 oid sha256:a99a0a8e8696f85040b18a7b95996060265dec4c0607ab9bc90551e2f2dc9bd2 size 81424

[ "sumitkutty37@gmail.com" ]

sumitkutty37@gmail.com

035f453b189a37c9677088804e6c18447aabdbbe

75dcb56e318688499bdab789262839e7f58bd4f6

/_algorithms_challenges/leetcode/LeetCode/733 Flood Fill.py

4350e4e56af74a61b1f948707760e1b580de0573

[]

no_license

syurskyi/Algorithms_and_Data_Structure

9a1f358577e51e89c862d0f93f373b7f20ddd261

929dde1723fb2f54870c8a9badc80fc23e8400d3

refs/heads/master

2023-02-22T17:55:55.453535

2022-12-23T03:15:00

226,243,987

4

1

null

2023-02-07T21:01:45

2019-12-06T04:14:10

Jupyter Notebook

UTF-8

Python

false

2,124

py

#!/usr/bin/python3 """ An image is represented by a 2-D array of integers, each integer representing the pixel value of the image (from 0 to 65535). Given a coordinate (sr, sc) representing the starting pixel (row and column) of the flood fill, and a pixel value newColor, "flood fill" the image. To perform a "flood fill", consider the starting pixel, plus any pixels connected 4-directionally to the starting pixel of the same color as the starting pixel, plus any pixels connected 4-directionally to those pixels (also with the same color as the starting pixel), and so on. Replace the color of all of the aforementioned pixels with the newColor. At the end, return the modified image. Example 1: Input: image = [[1,1,1],[1,1,0],[1,0,1]] sr = 1, sc = 1, newColor = 2 Output: [[2,2,2],[2,2,0],[2,0,1]] Explanation: From the center of the image (with position (sr, sc) = (1, 1)), all pixels connected by a path of the same color as the starting pixel are colored with the new color. Note the bottom corner is not colored 2, because it is not 4-directionally connected to the starting pixel. Note: The length of image and image[0] will be in the range [1, 50]. The given starting pixel will satisfy 0 <= sr < image.length and 0 <= sc < image[0].length. The value of each color in image[i][j] and newColor will be an integer in [0, 65535]. """ from typing import List dirs = ((-1, 0), (1, 0), (0, -1), (0, 1)) class Solution: def floodFill(self, image: List[List[int]], sr: int, sc: int, newColor: int) -> List[List[int]]: """ dfs fill mistake: corner case image == new color """ cur_color = image[sr][sc] if cur_color == newColor: return image self.dfs(image, sr, sc, cur_color, newColor) return image def dfs(self, image, i, j, cur_color, new_color): image[i][j] = new_color m, n = len(image), len(image[0]) for di, dj in dirs: I = i + di J = j + dj if 0 <= I < m and 0 <= J < n and image[I][J] == cur_color: self.dfs(image, I, J, cur_color, new_color)

[ "sergejyurskyj@yahoo.com" ]

sergejyurskyj@yahoo.com

7d375196ec6a89c43b9391ff60129464324ce322

f4fdb0c1213bbb403b87c2dbbde390918ac08861

/convert_uk_decl_num3.py

accb16c1dd9181350a97f4be6023784d4fd9b64a

[]

no_license

benwing2/RuNounChanges

0d5076e576237f10b50049ed52b91f96c95cca95

048dfed5abe09b8d5629c5772292027ce0a170f2

refs/heads/master

2023-09-03T22:48:06.972127

2023-09-03T06:27:56

41,480,942

3

0

null

UTF-8

Python

false

2,246

py

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pywikibot, re, sys, argparse import blib from blib import getparam, rmparam, tname, pname, msg, errandmsg, site def process_text_on_page(index, pagetitle, text): global args def pagemsg(txt): msg("Page %s %s: %s" % (index, pagetitle, txt)) notes = [] parsed = blib.parse_text(text) for t in parsed.filter_templates(): tn = tname(t) origt = str(t) def getp(param): return getparam(t, param) if tn == "uk-decl-num3": def clean_part(part): return blib.remove_links(part).replace(" ", "").strip() acc = clean_part(getp("4")) if "," in acc: nom = clean_part(getp("1")) gen = clean_part(getp("2")) dat = clean_part(getp("3")) ins = clean_part(getp("5")) loc = clean_part(getp("6")) acc_parts = acc.split(",") if len(acc_parts) == 2: acc_in, acc_an = acc_parts for param in t.params: pn = pname(param) pv = str(param.value) if not re.search("^[1-6]$", pn): pagemsg("WARNING: Unrecognized param: %s=%s" % (pn, pv)) return del t.params[:] blib.set_template_name(t, "uk-adecl-manual") t.add("special", "plonly\n", preserve_spacing=False) t.add("nom_p", nom + "\n", preserve_spacing=False) t.add("gen_p", gen + "\n", preserve_spacing=False) t.add("dat_p", dat + "\n", preserve_spacing=False) t.add("acc_p_in", acc_in + "\n", preserve_spacing=False) t.add("acc_p_an", "%s,%s\n" % (acc_in, acc_an), preserve_spacing=False) t.add("ins_p", ins + "\n", preserve_spacing=False) t.add("loc_p", loc + "\n", preserve_spacing=False) notes.append("replace {{uk-decl-num3}} with {{uk-adecl-manual}}") pagemsg("Replaced %s with %s" % (origt, str(t))) return str(parsed), notes parser = blib.create_argparser("Convert {{uk-decl-num3}} to {{uk-adecl-manual}}", include_pagefile=True, include_stdin=True) args = parser.parse_args() start, end = blib.parse_start_end(args.start, args.end) blib.do_pagefile_cats_refs(args, start, end, process_text_on_page, edit=True, stdin=True, default_refs=["Template:uk-decl-num3"])

[ "ben@benwing.com" ]

ben@benwing.com

fbfa4af6739e251fef1d94b0ce852a6cb2c6cca3

c1b8ff60ed4d8c70e703f71b7c96a649a75c0cec

/ostPython4/context_mgr.py

5d67ab14436a6f258a36aef585b8624eba812c9d

[]

no_license

deepbsd/OST_Python

836d4fae3d98661a60334f66af5ba3255a0cda5c

b32f83aa1b705a5ad384b73c618f04f7d2622753

refs/heads/master

2023-02-14T17:17:28.186060

2023-01-31T02:09:05

49,534,454

1

2

null

UTF-8

Python

false

1,284

py

#!/usr/bin/env python3 # # # context_mgr.py # # Lesson 14: Context Managers # # by David S. Jackson # 8/17/15 # # OST Python4: Advanced Python # for Pat Barton, Instructor # """ Project: Write a context manager class that suppresses any ValueError exceptions that occur in the controlled suite, but allows any other exception to be raised in the surrounding context. """ class ctx_mgr: def __init__(self, raising=True): self.raising = raising def __enter__(self): cm = object() return cm def __exit__(self, exc_type, exc_val, exc_tb): "Self.raising can be overridden, so I reset it excplicitly." self.raising = True if exc_type == ValueError: return self.raising elif exc_type: raise if __name__ == "__main__": with ctx_mgr(raising=True) as cm: print('To create ValueError, enter a float or string.') num = int(input("Enter a number: ")) print('To create an IndexError, enter an int greater than 4.') myindex = int(input('lst1 = [1,2,3,4,5]. What index is number 4? ')) lst1 = [1,2,3,4,5] print("The value you selected is: ", lst1[myindex]) print("Divide by zero!", 3/0)

[ "deepbsd@yahoo.com" ]

deepbsd@yahoo.com

49de7e6ce41f348e586e2eefc9b9a5e0127f92ad

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03574/s538402697.py

a100b6d62d5fdc1b9953e127ac04d0761a0d8b81

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

464

py

h,w=map(int,input().split()) s=["."*(w+2)] for i in range(h): s.append("."+input()+".") s.append("."*(w+2)) dx=[-1,0,1,1,1,0,-1,-1] dy=[1,1,1,0,-1,-1,-1,0] ans=[] for i in range(1,h+1): wp="" for j in range(1,w+1): if s[i][j]=="#": wp+="#" continue count=0 for k in range(8): if s[i+dy[k]][j+dx[k]]=="#": count+=1 wp+=str(count) ans.append(wp) print(*ans,sep="\n")

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

6099e986b2054b690030adc9e7e17a767ae0e2b4

c6fa248ec5a7e3c67afac98e365cac850c511473

/generative_adversarial_networks/code/chapter_08/04_train_discriminator.py

c79e832de127b1bae5f94a1889e27d01ecef99ac

[]

no_license

shenjnigxing/deep-learning-material

44830e07cc2a5bd47b07ca903c1f2b65beef22bb

24dfee3b9fe1a40303cb2dfe256028d35113babf

refs/heads/master

2022-12-23T10:08:05.881432

2020-09-16T02:24:38

295,900,907

0

1

null

UTF-8

Python

false

2,988

py

# example of training the discriminator model on real and random cifar10 images from numpy import ones from numpy import zeros from numpy.random import rand from numpy.random import randint from keras.datasets.cifar10 import load_data from keras.optimizers import Adam from keras.models import Sequential from keras.layers import Dense from keras.layers import Conv2D from keras.layers import Flatten from keras.layers import Dropout from keras.layers import LeakyReLU # define the standalone discriminator model def define_discriminator(in_shape=(32,32,3)): model = Sequential() # normal model.add(Conv2D(64, (3,3), padding='same', input_shape=in_shape)) model.add(LeakyReLU(alpha=0.2)) # downsample model.add(Conv2D(128, (3,3), strides=(2,2), padding='same')) model.add(LeakyReLU(alpha=0.2)) # downsample model.add(Conv2D(128, (3,3), strides=(2,2), padding='same')) model.add(LeakyReLU(alpha=0.2)) # downsample model.add(Conv2D(256, (3,3), strides=(2,2), padding='same')) model.add(LeakyReLU(alpha=0.2)) # classifier model.add(Flatten()) model.add(Dropout(0.4)) model.add(Dense(1, activation='sigmoid')) # compile model opt = Adam(lr=0.0002, beta_1=0.5) model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy']) return model # load and prepare cifar10 training images def load_real_samples(): # load cifar10 dataset (trainX, _), (_, _) = load_data() # convert from unsigned ints to floats X = trainX.astype('float32') # scale from [0,255] to [-1,1] X = (X - 127.5) / 127.5 return X # select real samples def generate_real_samples(dataset, n_samples): # choose random instances ix = randint(0, dataset.shape[0], n_samples) # retrieve selected images X = dataset[ix] # generate 'real' class labels (1) y = ones((n_samples, 1)) return X, y # generate n fake samples with class labels def generate_fake_samples(n_samples): # generate uniform random numbers in [0,1] X = rand(32 * 32 * 3 * n_samples) # update to have the range [-1, 1] X = -1 + X * 2 # reshape into a batch of color images X = X.reshape((n_samples, 32, 32, 3)) # generate 'fake' class labels (0) y = zeros((n_samples, 1)) return X, y # train the discriminator model def train_discriminator(model, dataset, n_iter=20, n_batch=128): half_batch = int(n_batch / 2) # manually enumerate epochs for i in range(n_iter): # get randomly selected 'real' samples X_real, y_real = generate_real_samples(dataset, half_batch) # update discriminator on real samples _, real_acc = model.train_on_batch(X_real, y_real) # generate 'fake' examples X_fake, y_fake = generate_fake_samples(half_batch) # update discriminator on fake samples _, fake_acc = model.train_on_batch(X_fake, y_fake) # summarize performance print('>%d real=%.0f%% fake=%.0f%%' % (i+1, real_acc*100, fake_acc*100)) # define the discriminator model model = define_discriminator() # load image data dataset = load_real_samples() # fit the model train_discriminator(model, dataset)

[ "Shenjx161212@gmail.com" ]

Shenjx161212@gmail.com

4cd79181130987db75faf7e250e83b9863e339bb

5d6dd782e0b29817b3c27d5d6984909152813444

/dbbase/urls.py

3d183271c6790a11b27359533230ad4817dbcaab

[]

no_license

smartslee/hospacc

387d8a7e42e068080738e365045a23d6d8a1f222

5bd42a9e729f3c90ff4b87185167f64fe79aac01

refs/heads/master

2020-04-01T12:59:50.743213

2019-10-07T08:13:41

153,232,513

0

null

UTF-8

Python

false

1,111

py

from django.urls import path from . import views from .views import (HdbUpdateView,IndexView, SearchFormView,HdbCreateView,HdbDeleteView, HdbprintView) urlpatterns = [ path('list/', views.index, name ='list'), # url(r'^dbedit/', views.hospdb_list, name ='edit'), path('input/', views.inputdb, name ='inputdbn'), path('', views.homep, name ='home'), path('dblistView/', views.IndexView.as_view(), name ='indexview'), path('<int:pk>/', views.HdbdetailView.as_view(), name="detail"), path('print(<int:pk>)/', views.HdbprintView.as_view(), name="print"), path('hdb/add/', views.HdbCreateView.as_view(), name="hdb_add"), path('update/<int:pk>/', HdbUpdateView.as_view(), name='update'), path('delete/<int:pk>/', HdbDeleteView.as_view(), name='delete'), #url(r'^list$',ProductListView.as_view(), name="ProductListView"), # url(r'^list/(?P<pk>\d+)/$',ProductDetailView.as_view(), name="ProductDetailview"), path('search',SearchFormView.as_view(),name='search'), path('login/', views.signin, name='login'), path('logout/', views.logout, name='logout'), ]

[ "you@example.com" ]

you@example.com