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

c51c826bcad9a887b4123c7790037f70e652cfae

1,250

py

Python

fix_ccJSON.py

boada/wmh

f2abe5ff2aeeae6eebab2e8c40803b3fcec9ac3a

[ "MIT" ]

null

fix_ccJSON.py

boada/wmh

f2abe5ff2aeeae6eebab2e8c40803b3fcec9ac3a

[ "MIT" ]

null

fix_ccJSON.py

boada/wmh

f2abe5ff2aeeae6eebab2e8c40803b3fcec9ac3a

[ "MIT" ]

null

import pandas as pd import sys if __name__ == "__main__": fix(sys.argv[1])

24.038462

60

0.508

c51deae5ca13775e3c2ef4b77c14c0ca5e33d193

1,184

py

Python

01-Lesson-Plans/03-Python-Pandas/1/Activities/12-functions-02/Unsolved/functions-02.py

tatianegercina/FinTech

b40687aa362d78674e223eb15ecf14bc59f90b62

[ "ADSL" ]

1

2021-04-13T07:14:34.000Z

01-Lesson-Plans/03-Python-Pandas/1/Activities/12-functions-02/Unsolved/functions-02.py

tatianegercina/FinTech

b40687aa362d78674e223eb15ecf14bc59f90b62

[ "ADSL" ]

2

2021-06-02T03:14:19.000Z

2022-02-11T23:21:24.000Z

01-Lesson-Plans/03-Python-Pandas/1/Activities/12-functions-02/Unsolved/functions-02.py

tatianegercina/FinTech

b40687aa362d78674e223eb15ecf14bc59f90b62

[ "ADSL" ]

1

2021-05-07T13:26:50.000Z

# Define a function "warble" that takes in a string as an argument, adds " arglebargle" to the end of it, and returns the result. # Print the result of calling your "warble" function with the argument "hello". # Define a function "wibble" that takes a string as an argument, prints the argument, prepends "wibbly " to the argument, and returns the result # Print the result of calling your "wibble" function with the argument "bibbly" # Define a function "print_sum" that takes in two numbers as arguments and prints the sum of those two numbers. # Define a function "return_sum" that takes in two numbers as arguments and returns the sum of those two numbers # Using either "return_sum" and no mathematical operators, define a function "triple_sum" that takes in 3 arguments and returns the sum of those 3 numbers. # Define a function "dance_party" that takes in a string as an argument, that prints "dance!", updates the string from calling "wibble" function with that argument, updates the string from calling "warble" function with that argument, returns the updated string # Print the result of calling your "dance_party" function with your name as the argument

43.851852

261

0.771115

c51e6be205213ab9c3f0f822b11808c56b8e2982

1,003

py

Python

Section 6 - Modular Programming/Green eggs and ham v4.py

gitjot/python-for-lccs

a8a4ae8847abbc33361f80183c06d57b20523382

[ "CC0-1.0" ]

10

2020-02-14T14:28:15.000Z

2022-02-02T18:44:11.000Z

Section 6 - Modular Programming/Green eggs and ham v4.py

gitjot/python-for-lccs

a8a4ae8847abbc33361f80183c06d57b20523382

[ "CC0-1.0" ]

null

Section 6 - Modular Programming/Green eggs and ham v4.py

gitjot/python-for-lccs

a8a4ae8847abbc33361f80183c06d57b20523382

[ "CC0-1.0" ]

8

2020-03-25T09:27:42.000Z

2021-11-03T15:24:38.000Z

# Event: LCCS Python Fundamental Skills Workshop # Date: Dec 2018 # Author: Joe English, PDST # eMail: computerscience@pdst.ie # Purpose: To find (and fix) two syntax errors # A program to display Green Eggs and Ham (v4) # Program execution starts here showChorus() displayVerse1() # SYNTAX ERROR 1 - function 'displayVerse1' does not exist showChorus() showVerse2() # SYNTAX ERROR 2 - function 'showVerse2' does not exist showChorus()

30.393939

75

0.658026

c51e94a6e708f618911c4ecc6deceed3e193e44e

1,107

py

Python

internal/handlers/singapore.py

fillingthemoon/cartogram-web

58b645bca0c22b9bccdb2a5a8213a5a24a7e5958

[ "MIT" ]

null

internal/handlers/singapore.py

fillingthemoon/cartogram-web

58b645bca0c22b9bccdb2a5a8213a5a24a7e5958

[ "MIT" ]

null

internal/handlers/singapore.py

fillingthemoon/cartogram-web

58b645bca0c22b9bccdb2a5a8213a5a24a7e5958

[ "MIT" ]

null

import settings import handlers.base_handler import csv

29.918919

292

0.641373

c51f18d40b89343f5d2cfddd15750839af888439

1,247

py

Python

code.py

aashray18521/parallelModifiedGrepPython

afad79662e59e1e6fc5f491ba988995a312dc205

[ "MIT" ]

null

code.py

aashray18521/parallelModifiedGrepPython

afad79662e59e1e6fc5f491ba988995a312dc205

[ "MIT" ]

3

2020-11-23T15:37:43.000Z

2020-11-23T15:38:51.000Z

code.py

aashray18521/parallelModifiedGrepPython

afad79662e59e1e6fc5f491ba988995a312dc205

[ "MIT" ]

null

import multiprocessing import os import time rootdir = input() keyword = input() batch_size = 1 the_queue = multiprocessing.Queue() walk_dirs(rootdir, batch_size) the_pool = multiprocessing.Pool(3, worker_main,(the_queue,))

31.974359

87

0.644747

c51f3d08b27846ef7d07616f6d207a8d88638159

1,316

py

Python

flask_youku/__init__.py

xiaoyh121/program

6826f024cce7a4250a1dab8dba145c1f0d713286

[ "Apache-2.0" ]

176

2016-12-11T03:24:41.000Z

2021-12-10T11:44:37.000Z

flask_youku/__init__.py

xiaoyh121/program

6826f024cce7a4250a1dab8dba145c1f0d713286

[ "Apache-2.0" ]

4

2018-02-07T03:31:13.000Z

2021-12-25T13:03:49.000Z

flask_youku/__init__.py

xiaoyh121/program

6826f024cce7a4250a1dab8dba145c1f0d713286

[ "Apache-2.0" ]

76

2016-11-13T08:57:38.000Z

2021-12-25T12:02:05.000Z

from flask import Blueprint, Markup from flask import render_template def youku(*args, **kwargs): """Define the Jinja function.""" video = Video(*args, **kwargs) return video.html

24.830189

59

0.609422

c51fefbd501d6ac95a99920e7040a7192440ef23

26,061

py

Python

main.py

DasAnish/TutorMatch

1b2cf3a71e859f519d645dc33edf72a975661066

[ "MIT" ]

null

main.py

DasAnish/TutorMatch

1b2cf3a71e859f519d645dc33edf72a975661066

[ "MIT" ]

null

main.py

DasAnish/TutorMatch

1b2cf3a71e859f519d645dc33edf72a975661066

[ "MIT" ]

1

2021-09-19T15:00:59.000Z

from backend import Backend, Tutor, Parent from kivy.app import App from kivy.base import Builder from kivy.uix.widget import Widget from kivy.uix.label import Label from kivy.uix.button import Button from kivy.properties import ObjectProperty from kivy.core.window import Window from kivy.uix.image import Image from kivy.config import Config from kivy.graphics import * from kivy.animation import * from kivy.graphics import RoundedRectangle from kivy.uix.gridlayout import GridLayout from kivy.uix.textinput import TextInput from kivy.uix.slider import Slider from kivy.uix.togglebutton import ToggleButton from kivy.uix.popup import Popup from backend import Backend, Match, Level import os #Builder.load_file("kivyFiles/main.kv") photoHeight = 550 photoWidth = 340 parent = {'username':'kelvincfleung', 'password':'hello123', 'fname':'Kelvin', 'lname':'Leung1', 'rateMin':10, 'rateMax':20, 'subject':'maths', 'level':1} parentObj = Parent('61467ec2c2c5a2e917994d69') parentObj.updateInfo(parent) # KELVIN GO HERE #360*640 if __name__ == '__main__': Config.set('graphics', 'width', '360') Config.set('graphics', 'height', '640') Config.set('graphics', 'resizable', False) MainApp().run()

40.784038

192

0.610683

c520331bf38c88e653e41aa4b2d7c402d30d7649

374

py

Python

routes/routes.py

aryan9600/SimpleMath-Flask

855120ba7e7f36435045840ab1c6672308fae7e5

[ "MIT" ]

null

routes/routes.py

aryan9600/SimpleMath-Flask

855120ba7e7f36435045840ab1c6672308fae7e5

[ "MIT" ]

null

routes/routes.py

aryan9600/SimpleMath-Flask

855120ba7e7f36435045840ab1c6672308fae7e5

[ "MIT" ]

null

from flask import Blueprint, request router = Blueprint("router", __name__)

22

48

0.697861

c5203ec4fd880de88723d9ad07ee74058b1d23cf

1,592

py

Python

configs/repdet/repdet_repvgg_b1g2_nanopan_nanohead_1x_coco.py

karthiksharma98/mmdetection

295145d41a74598db98a037224f0f82c074f3fff

[ "Apache-2.0" ]

null

configs/repdet/repdet_repvgg_b1g2_nanopan_nanohead_1x_coco.py

karthiksharma98/mmdetection

295145d41a74598db98a037224f0f82c074f3fff

[ "Apache-2.0" ]

null

configs/repdet/repdet_repvgg_b1g2_nanopan_nanohead_1x_coco.py

karthiksharma98/mmdetection

295145d41a74598db98a037224f0f82c074f3fff

[ "Apache-2.0" ]

null

_base_ = [ '../_base_/models/repdet_repvgg_pafpn.py', '../_base_/datasets/coco_detection.py', '../_base_/schedules/schedule_poly.py', '../_base_/default_runtime.py' ] # model settings model = dict( type='RepDet', pretrained='/data/kartikes/repvgg_models/repvgg_b1g2.pth', backbone=dict( type='RepVGG', arch='B1g2', out_stages=[1, 2, 3, 4], activation='ReLU', last_channel=1024, deploy=False), neck=dict( type='NanoPAN', in_channels=[128, 256, 512, 1024], out_channels=256, num_outs=5, start_level=1, add_extra_convs='on_input'), bbox_head=dict( type='NanoDetHead', num_classes=80, in_channels=256, stacked_convs=2, feat_channels=256, share_cls_reg=True, reg_max=10, norm_cfg=dict(type='BN', requires_grad=True), anchor_generator=dict( type='AnchorGenerator', ratios=[1.0], octave_base_scale=8, scales_per_octave=1, strides=[8, 16, 32]), loss_cls=dict( type='QualityFocalLoss', use_sigmoid=True, beta=2.0, loss_weight=1.0), loss_dfl=dict(type='DistributionFocalLoss', loss_weight=0.25), loss_bbox=dict(type='GIoULoss', loss_weight=2.0)) ) optimizer = dict(type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0001) data = dict( samples_per_gpu=4, workers_per_gpu=2) find_unused_parameters=True runner = dict(type='EpochBasedRunner', max_epochs=12)

28.945455

74

0.594849

c5206e72ad25192f5a2ed7316aa7ced0c3105161

436

py

Python

tests/test_calculate_branch.py

ivergara/python-abc

b5bb87b80315f8e5ecd2d6f35b7208f0a7df9c3a

[ "Unlicense" ]

2

2021-07-25T20:12:21.000Z

2021-07-25T21:19:23.000Z

tests/test_calculate_branch.py

ivergara/python-abc

b5bb87b80315f8e5ecd2d6f35b7208f0a7df9c3a

[ "Unlicense" ]

1

2021-12-28T22:07:05.000Z

tests/test_calculate_branch.py

ivergara/python-abc

b5bb87b80315f8e5ecd2d6f35b7208f0a7df9c3a

[ "Unlicense" ]

1

2021-12-07T19:53:45.000Z

import pytest from tests import assert_source_returns_expected BRANCH_CASES = [ # Call ('print("hello world")', 'b | print("hello world")'), # Await ("await noop()", "b | await noop()"), # Class instantiation ("Noop()", "b | Noop()"), ]

22.947368

68

0.669725

c52074b71855ef72867102bc5564df2ba1896c19

4,619

py

Python

client/src/obc.py

estcube/telemetry-forwarding-client

be659c8dd8e4bd26d1d1974d63f90acffd150e34

[ "MIT" ]

3

2020-06-11T12:34:25.000Z

2020-09-16T12:06:32.000Z

client/src/obc.py

estcube/telemetry-forwarding-client

be659c8dd8e4bd26d1d1974d63f90acffd150e34

[ "MIT" ]

57

2020-09-16T09:11:04.000Z

2022-02-28T01:32:13.000Z

client/src/obc.py

estcube/Telemetry-Forwarding-Client

be659c8dd8e4bd26d1d1974d63f90acffd150e34

[ "MIT" ]

null

# This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild from pkg_resources import parse_version from kaitaistruct import __version__ as ks_version, KaitaiStruct, KaitaiStream, BytesIO if parse_version(ks_version) < parse_version('0.7'): raise Exception("Incompatible Kaitai Struct Python API: 0.7 or later is required, but you have %s" % (ks_version))

52.488636

118

0.657285

c522238afd1828d1190c7360573f7b8dc442a5a0

1,537

py

Python

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

6

2019-07-09T19:40:01.000Z

2022-01-24T12:01:37.000Z

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

null

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

1

2020-11-07T13:06:58.000Z

import io import struct

25.616667

74

0.573845

c52372bcbf3ae907ef32ccf5713d1759604af330

483

py

Python

scripts/npc/holyStone.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

54

2019-04-16T23:24:48.000Z

2021-12-18T11:41:50.000Z

scripts/npc/holyStone.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

3

2019-05-19T15:19:41.000Z

2020-04-27T16:29:16.000Z

scripts/npc/holyStone.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

49

2020-11-25T23:29:16.000Z

2022-03-26T16:20:24.000Z

# Holy Stone - Holy Ground at the Snowfield (3rd job) questIDs = [1431, 1432, 1433, 1435, 1436, 1437, 1439, 1440, 1442, 1443, 1445, 1446, 1447, 1448] hasQuest = False for qid in questIDs: if sm.hasQuest(qid): hasQuest = True break if hasQuest: if sm.sendAskYesNo("#b(A mysterious energy surrounds this stone. Do you want to investigate?)"): sm.warpInstanceIn(910540000, 0) else: sm.sendSayOkay("#b(A mysterious energy surrounds this stone)#k")

30.1875

100

0.679089

c523effb8f36813f8d45730c0dbdd83679d7448e

16,256

py

Python

pyvmodule/expr.py

tanhongze/pyvmodule

b88cd35e57893024071306d238ce601341ce3bb4

[ "MIT" ]

null

pyvmodule/expr.py

tanhongze/pyvmodule

b88cd35e57893024071306d238ce601341ce3bb4

[ "MIT" ]

null

pyvmodule/expr.py

tanhongze/pyvmodule

b88cd35e57893024071306d238ce601341ce3bb4

[ "MIT" ]

1

2020-01-20T07:25:40.000Z

#-- coding:utf-8 from .ast import ASTNode from .compute.value import expr_value_calc_funcs,expr_value_prop_funcs from .compute.width import expr_width_calc_funcs,expr_width_fix_funcs from .compute.width import expr_match_width,expr_calc_width from .tools.utility import count_one import warnings __all__ = ['Mux','Concatenate','Expr','wrap_expr', 'BinaryOperator', 'ConstExpr','Hexadecimal','Decimal','Octal','Binary'] class UnaryOperator(Expr): class BinaryOperator(Expr): class Mux(Expr): class MultilineAlignOperator(Expr): def fix_slice(key,width): start = (0 if key.step is None else key.stop-key.step) if key.start is None else key.start stop = (width if key.step is None else key.start+key.start) if key.stop is None else key.stop width = stop - start return start,stop,width class ConstExpr(Expr): _radix_fmtstrs = { 16:lambda width,value:("%d'h{:0>%dx}"%(width,(width+3)//4)).format(value), 10:lambda width,value:("%d'd{:0>d}" % width ).format(value), 8 :lambda width,value:("%d'o{:0>%do}"%(width,(width+2)//3)).format(value), 2 :lambda width,value:("%d'b{:0>%db}"%(width, width )).format(value)} def _set_default(self,typename,n_childs=0): self.comments = [] self.childs = [None]*n_childs self.value = None self.width = None def __init__(self,value,width=None,radix=10): self.typename = 'const' self._value = 0 self._width = None if not width is None:self.width = width self.radix = radix self.value = value def __getitem__(self,key): if isinstance(key,slice): for a in {'start','stop','step'}: if not isinstance(getattr(key,a),(int,type(None))): raise SyntaxError('Invalid fetch format from constant expression.') start = 0 if key.start is None else key.start if not key.step is None:return Hexadecimal(int(self)>>start,width=key.step) elif not key.stop is None:return Hexadecimal(int(self)>>start,width=key.stop-start) return Hexadecimal(int(self)>>start,width=self.width-start) elif isinstance(key,(int,ConstExpr)): loc = int(key) if loc<0:loc += len(self) return Binary((self.value>>loc)&1,width=1) elif isinstance(key,Expr): n = 1<<len(key) v = self.value m = count_one(v) if m==0:return Binary(0,width=1) elif m==n:return Binary(1,width=1) else: if m<=(n>>1): expr = 0 for i in range(n): if ((v>>i)&1)==1:expr|=key//i else: expr = 1 for i in range(n): if ((v>>i)&1)==0:expr&=~(key//i) return expr else:raise TypeError(type(key)) def __str__(self): width = self.width value = self.value if value is None: if width is None:return "'bz" else:return "%d'bz"%width if width is None: if value<0:warnings.warn('Negative value without width declared.') return str(value) result = self._radix_fmtstr(width,value) return result def __int__(self):return self.value def Hexadecimal(x,width=None): if width==0:return None else:return ConstExpr(x,width=width,radix=16) def Binary (x,width=None): if width==0:return None else:return ConstExpr(x,width=width,radix=2 ) def Octal (x,width=None): if width==0:return None else:return ConstExpr(x,width=width,radix=8 ) def Decimal (x,width=None): if width==0:return None else:return ConstExpr(x,width=width,radix=10)

40.237624

123

0.62906

c529b4e8440b64034ec82bd0b0da8014712c8c78

13,936

py

Python

Common_3/Tools/ForgeShadingLanguage/generators/d3d.py

divecoder/The-Forge

e882fbc000b2915b52c98fe3a8c791930490dd3c

[ "Apache-2.0" ]

3,058

2017-10-03T01:33:22.000Z

2022-03-30T22:04:23.000Z

Common_3/Tools/ForgeShadingLanguage/generators/d3d.py

juteman/The-Forge

e882fbc000b2915b52c98fe3a8c791930490dd3c

[ "Apache-2.0" ]

157

2018-01-26T10:18:33.000Z

2022-03-06T10:59:23.000Z

Common_3/Tools/ForgeShadingLanguage/generators/d3d.py

juteman/The-Forge

e882fbc000b2915b52c98fe3a8c791930490dd3c

[ "Apache-2.0" ]

388

2017-12-21T10:52:32.000Z

2022-03-31T18:25:49.000Z

""" GLSL shader generation """ from utils import Stages, getHeader, getShader, getMacro, genFnCall, fsl_assert, get_whitespace from utils import isArray, getArrayLen, getArrayBaseName, getMacroName, DescriptorSets, is_groupshared_decl import os, sys, importlib, re from shutil import copyfile

39.703704

130

0.564581

c52ada24bea0c59c6a12c8a2a1dea577b379a815

1,673

py

Python

test/relationships/test_minhash.py

bateman-research/search-sifter

78b05beac5ca21862d2773609dc4b9395a4982a5

[ "MIT" ]

1

2020-07-20T13:20:00.000Z

test/relationships/test_minhash.py

bateman-research/search-sifter

78b05beac5ca21862d2773609dc4b9395a4982a5

[ "MIT" ]

null

test/relationships/test_minhash.py

bateman-research/search-sifter

78b05beac5ca21862d2773609dc4b9395a4982a5

[ "MIT" ]

null

import pytest import searchsifter.relationships.minhash as mh import searchsifter.relationships.jaccard as jc def test_intersection(a, b, c): assert mh.intersection_signature(a, b) == set(range(50, 100)) assert mh.intersection_signature(a, b, c) == set(range(75, 100)) def test_union(a, b): assert mh.union_signature(a, b, 100) == a assert len(mh.union_signature(a, b, 20)) == 20

22.306667

68

0.550508

c52efabf8d8724ff1df4180be0a678f90bbcc559

1,672

py

Python

tests/integration/test_between_tags.py

liorbass/pydriller

26e6b594102e1f0a3e1029c5389fedec3cc55471

[ "Apache-2.0" ]

583

2018-04-09T09:48:47.000Z

2022-03-23T17:27:10.000Z

tests/integration/test_between_tags.py

liorbass/pydriller

26e6b594102e1f0a3e1029c5389fedec3cc55471

[ "Apache-2.0" ]

195

2018-05-25T08:10:58.000Z

2022-03-29T09:28:37.000Z

tests/integration/test_between_tags.py

liorbass/pydriller

26e6b594102e1f0a3e1029c5389fedec3cc55471

[ "Apache-2.0" ]

134

2018-04-10T12:57:34.000Z

2022-03-29T13:40:35.000Z

# Copyright 2018 Davide Spadini # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from pydriller.repository import Repository import logging logging.basicConfig(format='%(asctime)s - %(levelname)s - %(message)s', level=logging.INFO)

34.122449

91

0.684211

c52f836bfe409a72332984d1519b1c551dfb66b2

847

py

Python

tests/modules/command/button/test_wa_url_parameter.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

null

tests/modules/command/button/test_wa_url_parameter.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

null

tests/modules/command/button/test_wa_url_parameter.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

null

from unittest import TestCase from moceansdk.modules.command.button.wa_url_parameter_button import ( WaUrlParameterButton, )

27.322581

81

0.670602

c52fa39e205177e471e16b57a23781f02f1d2a0d

7,345

py

Python

2019/day21_input.py

coingraham/adventofcode

52b5b3f049242881285d0c2704f44cc1ee2a821e

[ "MIT" ]

5

2020-12-04T04:30:17.000Z

2021-11-12T11:26:22.000Z

2019/day21_input.py

coingraham/adventofcode

52b5b3f049242881285d0c2704f44cc1ee2a821e

[ "MIT" ]

null

2019/day21_input.py

coingraham/adventofcode

52b5b3f049242881285d0c2704f44cc1ee2a821e

[ "MIT" ]

null

input_data = 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7,345

0.687543

c52fa5fe46da648c33fa7618314fa8e93cc98a14

10,860

py

Python

src/python/pants/backend/go/target_types.py

Eric-Arellano/pants

aaa9756bc4f2cc97bb97851a4295a0de85f374b1

[ "Apache-2.0" ]

null

src/python/pants/backend/go/target_types.py

Eric-Arellano/pants

aaa9756bc4f2cc97bb97851a4295a0de85f374b1

[ "Apache-2.0" ]

12

2022-01-06T23:20:22.000Z

2022-03-17T05:06:37.000Z

src/python/pants/backend/go/target_types.py

Eric-Arellano/pants

aaa9756bc4f2cc97bb97851a4295a0de85f374b1

[ "Apache-2.0" ]

null

# Copyright 2021 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from __future__ import annotations import os from dataclasses import dataclass from typing import Sequence from pants.core.goals.package import OutputPathField from pants.core.goals.run import RestartableField from pants.engine.addresses import Address from pants.engine.engine_aware import EngineAwareParameter from pants.engine.fs import GlobExpansionConjunction, GlobMatchErrorBehavior, PathGlobs from pants.engine.target import ( COMMON_TARGET_FIELDS, AsyncFieldMixin, Dependencies, InvalidFieldException, InvalidTargetException, MultipleSourcesField, StringField, StringSequenceField, Target, ) from pants.option.global_options import FilesNotFoundBehavior # ----------------------------------------------------------------------------------------------- # `go_mod` target generator # ----------------------------------------------------------------------------------------------- # TODO: This field probably shouldn't be registered. # TODO(#12953): generalize this? # ----------------------------------------------------------------------------------------------- # `go_first_party_package` target # ----------------------------------------------------------------------------------------------- # ----------------------------------------------------------------------------------------------- # `go_third_party_package` target # ----------------------------------------------------------------------------------------------- # ----------------------------------------------------------------------------------------------- # `go_binary` target # ----------------------------------------------------------------------------------------------- class GoBinaryDependenciesField(Dependencies): # This is only used to inject a dependency from the `GoBinaryMainPackageField`. Users should # add any explicit dependencies to the `go_package`. alias = "_dependencies" class GoBinaryTarget(Target): alias = "go_binary" core_fields = ( *COMMON_TARGET_FIELDS, OutputPathField, GoBinaryMainPackageField, GoBinaryDependenciesField, RestartableField, ) help = "A Go binary."

36.813559

98

0.617127

c52fbd848e1acb3cd166434a5aa79fb5ec3b969e

9,623

py

Python

iris/src/iris/main.py

headma5ter/wall-e

da7624cd58ee3e61b847af6a389cc919e1f2a8d1

[ "MIT" ]

null

iris/src/iris/main.py

headma5ter/wall-e

da7624cd58ee3e61b847af6a389cc919e1f2a8d1

[ "MIT" ]

null

iris/src/iris/main.py

headma5ter/wall-e

da7624cd58ee3e61b847af6a389cc919e1f2a8d1

[ "MIT" ]

null

from matplotlib import pyplot as plt import matplotlib.lines as lines from statistics import mode, StatisticsError from csv import QUOTE_ALL import pandas as pd import pathlib import json from iris import logger from iris import config from iris import classifier from iris.helpers.utils import log_function # TODO: change to ceres COLUMN_NAMES = ["w", "x", "y", "z"] if __name__ == "__main__": # Get relevant paths data_path = getattr(config, f"{config.stage}_data_path") centroid_path = config.centroid_serial_path mapping_path = config.mapping_serial_path centroids = None mapping = dict() if config.stage == "testing": if not centroid_path.is_file() or not mapping_path.is_file(): logger.warn( "No training data to be read -- could result in poor model performance" ) else: # Get centroids and species mapping from training data centroids = read_data(serial_path=centroid_path) mapping = read_data(serial_path=mapping_path) # Classify data set data = read_data(csv_path=data_path) data, centroids = classify_clusters(data, initial_centroids=centroids) if config.stage == "training": # Map species to cluster mapping = map_cluster_to_species(data) if config.serialize: # Save data serialize_data(centroids, config.centroid_serial_path) serialize_data(mapping, config.mapping_serial_path) # Add the model's species classification to data data = map_species_onto_data(data, mapping) if config.save: # Save testing results to files write_to_csv(data, config.results_path) if config.visualize: # Plot data plot_clusters(data, mapping) calculate_statistics(data, mapping) logger.info(f"Process complete\n\t{config.summary}")

32.731293

103

0.618622

c530c5e8d4407688c79bec94a667aec813211585

2,328

py

Python

data_loader/util.py

lixiaoyu0575/physionet_challenge2020_pytorch

39b5aeeead440eaa88d6fdaf4a8a70c15373e062

[ "MIT" ]

1

2021-05-24T08:09:30.000Z

data_loader/util.py

lixiaoyu0575/physionet_challenge2020_pytorch

39b5aeeead440eaa88d6fdaf4a8a70c15373e062

[ "MIT" ]

null

data_loader/util.py

lixiaoyu0575/physionet_challenge2020_pytorch

39b5aeeead440eaa88d6fdaf4a8a70c15373e062

[ "MIT" ]

null

from scipy.io import loadmat import numpy as np import os import torch from torch.utils.data import Dataset, TensorDataset from torchvision import transforms # Find unique classes. # Load challenge data. # Customed TensorDataset def custom_collate_fn(batch): data = [item[0].unsqueeze(0) for item in batch] target = [item[1].unsqueeze(0) for item in batch] return [data, target]

28.390244

78

0.608247

c538cf5b43e938d74b89e921d97d1ef0493292ec

317

py

Python

solutions/binarysearch.io/hard/collecting-coins/main.py

zwliew/ctci

871f4fc957be96c6d0749d205549b7b35dc53d9e

[ "MIT" ]

4

2020-11-07T14:38:02.000Z

2022-01-03T19:02:36.000Z

solutions/binarysearch.io/hard/collecting-coins/main.py

zwliew/ctci

871f4fc957be96c6d0749d205549b7b35dc53d9e

[ "MIT" ]

1

2019-04-17T06:55:14.000Z

solutions/binarysearch.io/hard/collecting-coins/main.py

zwliew/ctci

871f4fc957be96c6d0749d205549b7b35dc53d9e

[ "MIT" ]

null

3 from functools import lru_cache 4 @lru_cache(None) 6 if i < 0 or j < 0: 7 return 0 8 return max(dp(i - 1, j), dp(i, j - 1)) + matrix[i][j] 9 return dp(len(matrix) - 1, len(matrix[0]) - 1)

31.7

66

0.498423

c53adeb9103721e86c1c98d5836be2d9b0c044bf

12,074

py

Python

Python 3/First_steps_on_machine_learning/Maze_using_Bellman_equation/Test_Maze.py

DarkShadow4/python

4cd94e0cf53ee06c9c31e9272572ca9656697c30

[ "MIT" ]

null

Python 3/First_steps_on_machine_learning/Maze_using_Bellman_equation/Test_Maze.py

DarkShadow4/python

4cd94e0cf53ee06c9c31e9272572ca9656697c30

[ "MIT" ]

null

Python 3/First_steps_on_machine_learning/Maze_using_Bellman_equation/Test_Maze.py

DarkShadow4/python

4cd94e0cf53ee06c9c31e9272572ca9656697c30

[ "MIT" ]

1

2020-08-19T17:25:22.000Z

import pygame, sys, maze_builder, random def move(a=(0, 0), b=(0, 0)): a = (a[0] + b[0], a[1] + b[1]) return(a) runner = Maze_runner() # s p p # b g # e p p maze = Maze( 1000, 1000, (3, 3)) test_node_00 = maze_builder.Node(position=(0, 0), right = True, special="start") test_node_10 = maze_builder.Node(position=(1, 0), left = True, down = True, right = True) test_node_20 = maze_builder.Node(position=(2, 0), down = True, left = True) test_node_11 = maze_builder.Node(position=(1, 1), down = True, up = True, right = True, special="bad") test_node_21 = maze_builder.Node(position=(2, 1), left = True, up=True, down=True, special="good") test_node_22 = maze_builder.Node(position=(2, 2), up = True, left = True) test_node_12 = maze_builder.Node(position=(1, 2), up = True, left = True, right = True) test_node_02 = maze_builder.Node(position=(0, 2), right = True, special="end") maze.add_node(test_node_00) maze.add_node(test_node_20) maze.add_node(test_node_10) maze.add_node(test_node_11) maze.add_node(test_node_21) maze.add_node(test_node_22) maze.add_node(test_node_12) maze.add_node(test_node_02) maze.add_runner(runner) # maze.work_out_values(maze.end) # maze.get_value(maze.start) maze.run() # maze.solve_random() # x x # x x # maze = Maze( 1000, 1000, (2, 2)) # test_node_00 = maze_builder.Node(position=(0, 0), right = True, up = True, special="start") # test_node_10 = maze_builder.Node(position=(1, 0), left = True, down = True) # test_node_11 = maze_builder.Node(position=(1, 1), up = True, left = True) # test_node_01 = maze_builder.Node(position=(0, 1), right = True, down = True, special="end") # maze.add_node(test_node_00) # maze.add_node(test_node_10) # maze.add_node(test_node_11) # maze.add_node(test_node_01) # maze.add_runner(runner) # maze.run()

46.79845

265

0.595826

c53b663532da343a9e761b6ebf1b05f4670a34a6

13,679

py

Python

powderday/nebular_emission/abund.py

mccbc/powderday

604b4a242216db0e93dc2e50a77bc20dc5cfb10f

[ "BSD-3-Clause" ]

null

powderday/nebular_emission/abund.py

mccbc/powderday

604b4a242216db0e93dc2e50a77bc20dc5cfb10f

[ "BSD-3-Clause" ]

null

powderday/nebular_emission/abund.py

mccbc/powderday

604b4a242216db0e93dc2e50a77bc20dc5cfb10f

[ "BSD-3-Clause" ]

null

from __future__ import (division, print_function, absolute_import, unicode_literals) import numpy as np from scipy.interpolate import InterpolatedUnivariateSpline as InterpUS from powderday.nebular_emission.cloudy_tools import sym_to_name """ ------------------------------------------------------------------------------------------ From cloudyfsps written by Nell Byler. (Source https://github.com/nell-byler/cloudyfsps/blob/master/cloudyfsps/nebAbundTools.py retrieved in October 2019) ------------------------------------------------------------------------------------------ """ def getNebAbunds(set_name, logZ, dust=True, re_z=False, **kwargs): """ neb_abund.get_abunds(set_name, logZ, dust=True, re_z=False) set_name must be 'dopita', 'newdopita', 'cl01' or 'yeh' """ allowed_names = ['dopita', 'newdopita', 'cl01', 'yeh', 'varyNO', 'gutkin', 'UVbyler', 'varyCO'] if set_name in allowed_names: return eval('{}({}, dust={}, re_z={})'.format(set_name, logZ, dust, re_z)) else: raise IOError(allowed_names) def load_abund(set_name): if set_name == 'dopita': adict = dict(He=-1.01, C=-3.44, N=-3.95, O=-3.07, Ne=-3.91, Mg=-4.42, Si=-4.45, S=-4.79, Ar=-5.44, Ca=-5.64, Fe=-4.33, F=-7.52, Na=-5.69, Al=-5.53, P=-6.43, Cl=-6.73, K=-6.87, Ti=-6.96, Cr=-6.32, Mn=-6.47, Co=-7.08, Ni=-5.75, Cu=-7.73, Zn=-7.34) elif set_name == 'newdopita': adict = dict(He=-1.01, C=-3.57, N=-4.60, O=-3.31, Ne=-4.07, Na=-5.75, Mg=-4.40, Al=-5.55, Si=-4.49, S=-4.86, Cl=-6.63, Ar=-5.60, Ca=-5.66, Fe=-4.50, Ni=-5.78, F=-7.44, P=-6.59, K=-6.97, Cr=-6.36, Ti=-7.05, Mn=-6.57, Co=-7.01, Cu=-7.81, Zn=-7.44) elif set_name == 'UVbyler': adict = dict(He=-1.01, C=-3.57, N=-4.17, O=-3.31, Ne=-4.07, Na=-5.75, Mg=-4.40, Al=-5.55, Si=-4.49, S=-4.86, Cl=-6.63, Ar=-5.60, Ca=-5.66, Fe=-4.50, Ni=-5.78, F=-7.44, P=-6.59, K=-6.97, Cr=-6.36, Ti=-7.05, Mn=-6.57, Co=-7.01, Cu=-7.81, Zn=-7.44) elif set_name == 'gutkin': adict = dict(He=-1.01, C=-3.53, N=-4.32, O=-3.17, F=-7.47, Ne=-4.01, Na=-5.70, Mg=-4.45, Al=-5.56, Si=-4.48, P=-6.57, S=-4.87, Cl=-6.53, Ar=-5.63, K=-6.92, Ca=-5.67, Sc=-8.86, Ti=-7.01, V=-8.03, Cr=-6.36, Mn=-6.64, Fe=-4.51, Co=-7.11, Ni=-5.78, Cu=-7.82, Zn=-7.43) return adict def load_depl(set_name): if set_name == 'dopita': ddict = dict(C=-0.30, N=-0.22, O=-0.22, Ne=0.0, Mg=-0.70, Si=-1.0, S=0.0, Ar=0.0, Ca=-2.52, Fe=-2.0, F=0.0, Na=0.0, Al=0.0, P=0.0, Cl=0.0, K=0.0, Ti=0.0, Cr=0.0, Mn=0.0, Co=0.0, Ni=0.0, Cu=0.0, Zn=0.0) elif set_name == 'newdopita': ddict = dict(He=0.00, C=-0.30, N=-0.05, O=-0.07, Ne=0.00, Na=-1.00, Mg=-1.08, Al=-1.39, Si=-0.81, S=0.00, Cl=-1.00, Ar=0.00, Ca=-2.52, Fe=-1.31, Ni=-2.00, F=0.0, P=0.0, K=0.0, Cr=0.0, Ti=0.0, Mn=0.0, Co=0.0, Cu=0.0, Zn=0.0) elif set_name == 'UVbyler': ddict = dict(He=0.00, C=-0.30, N=-0.05, O=-0.07, Ne=0.00, Na=-1.00, Mg=-1.08, Al=-1.39, Si=-0.81, S=0.00, Cl=-1.00, Ar=0.00, Ca=-2.52, Fe=-1.31, Ni=-2.00, F=0.0, P=0.0, K=0.0, Cr=0.0, Ti=0.0, Mn=0.0, Co=0.0, Cu=0.0, Zn=0.0) elif set_name == 'gutkin': ddict = dict(He=0.00, Li=-0.8, C=-0.30, O=-0.15, Na=-0.60, Mg=-0.70, Al=-1.70, Si=-1.00, Cl=-0.30, Ca=-2.52, Fe=-2.00, Ni=-1.40) return ddict

31.159453

90

0.370934

c53b92a47fb947f6f8b829b01647aa8c055f8973

644

py

Python

character/migrations/0004_alter_character_alignment.py

scottBowles/dnd

a1ef333f1a865d51b5426dc4b3493e8437584565

[ "MIT" ]

null

character/migrations/0004_alter_character_alignment.py

scottBowles/dnd

a1ef333f1a865d51b5426dc4b3493e8437584565

[ "MIT" ]

null

character/migrations/0004_alter_character_alignment.py

scottBowles/dnd

a1ef333f1a865d51b5426dc4b3493e8437584565

[ "MIT" ]

null

# Generated by Django 3.2.5 on 2021-08-12 02:00 from django.db import migrations, models

33.894737

300

0.591615

c53bcf309d42be5b0611b4932b04593b5fb3c79b

818

py

Python

graphs_trees/check_balance/test_check_balance.py

filippovitale/interactive-coding-challenges

8380a7aa98618c3cc9c0271c30bd320937d431ad

[ "Apache-2.0" ]

null

graphs_trees/check_balance/test_check_balance.py

filippovitale/interactive-coding-challenges

8380a7aa98618c3cc9c0271c30bd320937d431ad

[ "Apache-2.0" ]

null

graphs_trees/check_balance/test_check_balance.py

filippovitale/interactive-coding-challenges

8380a7aa98618c3cc9c0271c30bd320937d431ad

[ "Apache-2.0" ]

1

2019-12-13T12:57:44.000Z

from nose.tools import assert_equal if __name__ == '__main__': main()

20.974359

48

0.570905

c53bd8529e678df43ecc3a88f38641a5587a1587

1,129

py

Python

D_predict.py

shanqu91/microseismic_event_detection_via_CNN

ff9f0de135d14741c057a2a78e1fd69db18ae1d2

[ "MIT" ]

null

D_predict.py

shanqu91/microseismic_event_detection_via_CNN

ff9f0de135d14741c057a2a78e1fd69db18ae1d2

[ "MIT" ]

null

D_predict.py

shanqu91/microseismic_event_detection_via_CNN

ff9f0de135d14741c057a2a78e1fd69db18ae1d2

[ "MIT" ]

1

2021-10-05T08:41:15.000Z

import keras from keras.models import Sequential, load_model, Model from keras.layers import Dense, Dropout, Flatten from keras.layers import Conv2D, MaxPooling2D from scipy import io mat_contents = io.loadmat('Data/X_test_0.mat') X_test_0 = mat_contents['X_test_0'] mat_contents = io.loadmat('Data/X_test_1.mat') X_test_1 = mat_contents['X_test_1'] batch_size = 40 num_classes = 2 test_datasize, patch_rows, patch_cols = X_test_0.shape[0], X_test_0.shape[1], X_test_0.shape[2] X_test_0 = X_test_0.reshape(test_datasize, patch_rows, patch_cols, 1) test_datasize, patch_rows, patch_cols = X_test_1.shape[0], X_test_1.shape[1], X_test_1.shape[2] X_test_1 = X_test_1.reshape(test_datasize, patch_rows, patch_cols, 1) print('X_test_0 shape:', X_test_0.shape) print('X_test_1 shape:', X_test_1.shape) # load trained model model = load_model('Data/trained_model.h5') # prediction Y_test_0 = model.predict(X_test_0, batch_size=batch_size, verbose=1) Y_test_1 = model.predict(X_test_1, batch_size=batch_size, verbose=1) io.savemat('Data/Y_test_0.mat', {'Y_test_0':Y_test_0}) io.savemat('Data/Y_test_1.mat', {'Y_test_1':Y_test_1})

35.28125

95

0.782108

c53d72e1616e580f62f88e5fc1f0a262cb103728

94

py

Python

app/db_manager/apps.py

PragmaticCoder/Linkedin-Analytics

a990b5cae02f0d758bc3123bde643d13a439efa3

[ "MIT" ]

13

2018-07-31T15:37:47.000Z

2021-12-20T04:48:13.000Z

app/db_manager/apps.py

PragmaticCoder/Linkedin-Analytics

a990b5cae02f0d758bc3123bde643d13a439efa3

[ "MIT" ]

25

2019-12-10T20:03:48.000Z

2022-03-11T23:26:11.000Z

app/db_manager/apps.py

PragmaticCoder/Linkedin-Analytics

a990b5cae02f0d758bc3123bde643d13a439efa3

[ "MIT" ]

4

2020-03-24T20:13:50.000Z

2022-02-05T20:40:48.000Z

from django.apps import AppConfig

15.666667

33

0.765957

c53d83148b42eaa02961efd8a515c82ec643034c

813

py

Python

examples/dialogs.py

tgolsson/appJar

5e2f8bff44e927e7c2bae17fccddc6dbf79952f0

[ "Apache-2.0" ]

666

2016-11-14T18:17:40.000Z

2022-03-29T03:53:22.000Z

examples/dialogs.py

tgolsson/appJar

5e2f8bff44e927e7c2bae17fccddc6dbf79952f0

[ "Apache-2.0" ]

598

2016-10-20T21:04:09.000Z

2022-03-15T22:44:49.000Z

examples/dialogs.py

tgolsson/appJar

5e2f8bff44e927e7c2bae17fccddc6dbf79952f0

[ "Apache-2.0" ]

95

2017-01-19T12:23:58.000Z

2022-03-06T18:16:21.000Z

from appJar import gui app=gui() app.addButtons(["info", "error", "warning", "yesno", "question"], press) app.addButtons(["ok", "retry", "text", "number"], press) app.go()

45.166667

74

0.607626

c53d9c366f6302c3f4189f86bcaf5a05f084763e

19,136

py

Python

src_RealData/Nets/ObjectOriented.py

XYZsake/DRFNS

73fc5683db5e9f860846e22c8c0daf73b7103082

[ "MIT" ]

42

2018-10-07T08:19:01.000Z

2022-02-08T17:41:24.000Z

src_RealData/Nets/ObjectOriented.py

XYZsake/DRFNS

73fc5683db5e9f860846e22c8c0daf73b7103082

[ "MIT" ]

11

2018-12-22T00:15:46.000Z

2021-12-03T10:29:32.000Z

src_RealData/Nets/ObjectOriented.py

XYZsake/DRFNS

73fc5683db5e9f860846e22c8c0daf73b7103082

[ "MIT" ]

14

2018-08-26T06:47:06.000Z

2021-07-24T11:52:58.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- import tensorflow as tf import numpy as np import os from sklearn.metrics import confusion_matrix from datetime import datetime

38.272

215

0.570861

c53e560dfa34e9fcc79e711abf7084717bfce494

1,571

py

Python

flaskr/test/unit/webapp/test_change_light_color.py

UnibucProjects/SmartAquarium

6f3c16fb7a45218e763b46223568f6c3e5b66bfd

[ "MIT" ]

6

2022-02-02T19:37:57.000Z

2022-02-03T15:12:32.000Z

flaskr/test/unit/webapp/test_change_light_color.py

UnibucProjects/SmartAquarium

6f3c16fb7a45218e763b46223568f6c3e5b66bfd

[ "MIT" ]

18

2022-01-29T22:47:46.000Z

2022-02-03T15:30:28.000Z

flaskr/test/unit/webapp/test_change_light_color.py

UnibucProjects/SmartAquarium

6f3c16fb7a45218e763b46223568f6c3e5b66bfd

[ "MIT" ]

null

from flask import request import pytest import json from app import create_app, create_rest_api from db import get_db from change_light import is_aquarium_id_valid

26.627119

78

0.706556

c53e6e767c955b2bf53a179312e0dc8ac8e05972

4,293

py

Python

commands/inventory.py

zbylyrcxr/DennisMUD

cb9be389e3be3e267fd78b1520ed2902941742da

[ "MIT" ]

2

2022-02-21T17:55:03.000Z

2022-02-22T06:25:04.000Z

commands/inventory.py

zbylyrcxr/DennisMUD

cb9be389e3be3e267fd78b1520ed2902941742da

[ "MIT" ]

3

2022-02-09T18:18:29.000Z

2022-03-07T08:15:54.000Z

commands/inventory.py

zbylyrcxr/DennisMUD

cb9be389e3be3e267fd78b1520ed2902941742da

[ "MIT" ]

1

2022-03-07T08:10:59.000Z

####################### # Dennis MUD # # inventory.py # # Copyright 2018-2020 # # Michael D. Reiley # ####################### # ********** # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to # deal in the Software without restriction, including without limitation the # rights to use, copy, modify, merge, publish, distribute, sublicense, and/or # sell copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS # IN THE SOFTWARE. # ********** from lib.litnumbers import * from lib.vigenere import * import random NAME = "inventory" CATEGORIES = ["items"] ALIASES = ["inv", "i"] USAGE = "inventory" DESCRIPTION = "List all of the items in your inventory."

39.027273

136

0.642208

c53ebab62d8ce95d55ec92330a072c34d445b216

296

py

Python

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

188

2017-11-27T18:59:34.000Z

2021-12-31T02:28:33.000Z

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

95

2017-11-13T01:21:48.000Z

2020-10-30T06:38:14.000Z

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

16

2018-02-13T04:49:09.000Z

2021-02-06T13:26:46.000Z

import unittest from cozy.polynomials import Polynomial

29.6

84

0.712838

c53ef504f8c908892ab80122b5998f9150c4ae18

823

py

Python

presenters/calculator_presenter.py

RamonWill/portfolio-management-project

ac8ce313f8d62f09810fc1da19d6b252f193871b

[ "MIT" ]

14

2020-01-01T04:59:06.000Z

2022-02-08T06:48:21.000Z

presenters/calculator_presenter.py

linhvien/portfolio-management-project

ac8ce313f8d62f09810fc1da19d6b252f193871b

[ "MIT" ]

null

presenters/calculator_presenter.py

linhvien/portfolio-management-project

ac8ce313f8d62f09810fc1da19d6b252f193871b

[ "MIT" ]

8

2020-10-15T06:52:37.000Z

2021-10-04T06:44:36.000Z

from custom_objects import FinanceCalculator from tkinter import messagebox

34.291667

80

0.647631

c53f341c44f58f7cf080b91299e6c06e76e614e8

1,877

py

Python

core/power_status_monitor.py

kangyifei/CloudSimPy

45912e7ea35086b67941624102e400cb22e549ab

[ "MIT" ]

null

core/power_status_monitor.py

kangyifei/CloudSimPy

45912e7ea35086b67941624102e400cb22e549ab

[ "MIT" ]

null

core/power_status_monitor.py

kangyifei/CloudSimPy

45912e7ea35086b67941624102e400cb22e549ab

[ "MIT" ]

null

import json

33.517857

107

0.606819

c53f7e729f7148ea37a06ebe087c005b16755a1d

25,133

py

Python

maintest.py

thorsilver/ABM-for-social-care

3a47868d2881799980a3f9f24b78c66a31eda194

[ "MIT" ]

null

maintest.py

thorsilver/ABM-for-social-care

3a47868d2881799980a3f9f24b78c66a31eda194

[ "MIT" ]

null

maintest.py

thorsilver/ABM-for-social-care

3a47868d2881799980a3f9f24b78c66a31eda194

[ "MIT" ]

1

2018-01-05T15:42:40.000Z

from sim import Sim import os import cProfile import pylab import math import matplotlib.pyplot as plt import argparse import json import decimal import numpy as np def init_params(): """Set up the simulation parameters.""" p = {} ## The basics: starting population and year, etc. p['initialPop'] = 750 p['startYear'] = 1860 p['endYear'] = 2050 p['thePresent'] = 2012 p['statsCollectFrom'] = 1960 p['minStartAge'] = 20 p['maxStartAge'] = 40 p['verboseDebugging'] = False p['singleRunGraphs'] = True p['favouriteSeed'] = None p['numRepeats'] = 1 p['loadFromFile'] = False ## Mortality statistics p['baseDieProb'] = 0.0001 p['babyDieProb'] = 0.005 p['maleAgeScaling'] = 14.0 p['maleAgeDieProb'] = 0.00021 p['femaleAgeScaling'] = 15.5 p['femaleAgeDieProb'] = 0.00019 p['num5YearAgeClasses'] = 28 ## Transitions to care statistics p['baseCareProb'] = 0.0002 p['personCareProb'] = 0.0008 ##p['maleAgeCareProb'] = 0.0008 p['maleAgeCareScaling'] = 18.0 ##p['femaleAgeCareProb'] = 0.0008 p['femaleAgeCareScaling'] = 19.0 p['numCareLevels'] = 5 p['cdfCareTransition'] = [ 0.7, 0.9, 0.95, 1.0 ] p['careLevelNames'] = ['none','low','moderate','substantial','critical'] p['careDemandInHours'] = [ 0.0, 8.0, 16.0, 30.0, 80.0 ] ## Availability of care statistics p['childHours'] = 5.0 p['homeAdultHours'] = 30.0 p['workingAdultHours'] = 25.0 p['retiredHours'] = 60.0 p['lowCareHandicap'] = 0.5 p['hourlyCostOfCare'] = 20.0 ## Fertility statistics p['growingPopBirthProb'] = 0.215 p['steadyPopBirthProb'] = 0.13 p['transitionYear'] = 1965 p['minPregnancyAge'] = 17 p['maxPregnancyAge'] = 42 ## Class and employment statistics p['numOccupationClasses'] = 3 p['occupationClasses'] = ['lower','intermediate','higher'] p['cdfOccupationClasses'] = [ 0.6, 0.9, 1.0 ] ## Age transition statistics p['ageOfAdulthood'] = 17 p['ageOfRetirement'] = 65 ## Marriage and divorce statistics (partnerships really) p['basicFemaleMarriageProb'] = 0.25 p['femaleMarriageModifierByDecade'] = [ 0.0, 0.5, 1.0, 1.0, 1.0, 0.6, 0.5, 0.4, 0.1, 0.01, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0 ] p['basicMaleMarriageProb'] = 0.3 p['maleMarriageModifierByDecade'] = [ 0.0, 0.16, 0.5, 1.0, 0.8, 0.7, 0.66, 0.5, 0.4, 0.2, 0.1, 0.05, 0.01, 0.0, 0.0, 0.0 ] p['basicDivorceRate'] = 0.06 p['variableDivorce'] = 0.06 p['divorceModifierByDecade'] = [ 0.0, 1.0, 0.9, 0.5, 0.4, 0.2, 0.1, 0.03, 0.01, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0 ] ## Leaving home and moving around statistics p['probApartWillMoveTogether'] = 0.3 p['coupleMovesToExistingHousehold'] = 0.3 p['basicProbAdultMoveOut'] = 0.22 p['probAdultMoveOutModifierByDecade'] = [ 0.0, 0.2, 1.0, 0.6, 0.3, 0.15, 0.03, 0.03, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] p['basicProbSingleMove'] = 0.05 p['probSingleMoveModifierByDecade'] = [ 0.0, 1.0, 1.0, 0.8, 0.4, 0.06, 0.04, 0.02, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] p['basicProbFamilyMove'] = 0.03 p['probFamilyMoveModifierByDecade'] = [ 0.0, 0.5, 0.8, 0.5, 0.2, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1 ] p['agingParentsMoveInWithKids'] = 0.1 p['variableMoveBack'] = 0.1 ## Description of the map, towns, and houses p['mapGridXDimension'] = 8 p['mapGridYDimension'] = 12 p['townGridDimension'] = 40 p['numHouseClasses'] = 3 p['houseClasses'] = ['small','medium','large'] p['cdfHouseClasses'] = [ 0.6, 0.9, 5.0 ] p['ukMap'] = [ [ 0.0, 0.1, 0.2, 0.1, 0.0, 0.0, 0.0, 0.0 ], [ 0.1, 0.1, 0.2, 0.2, 0.3, 0.0, 0.0, 0.0 ], [ 0.0, 0.2, 0.2, 0.3, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.2, 1.0, 0.5, 0.0, 0.0, 0.0, 0.0 ], [ 0.4, 0.0, 0.2, 0.2, 0.4, 0.0, 0.0, 0.0 ], [ 0.6, 0.0, 0.0, 0.3, 0.8, 0.2, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.6, 0.8, 0.4, 0.0, 0.0 ], [ 0.0, 0.0, 0.2, 1.0, 0.8, 0.6, 0.1, 0.0 ], [ 0.0, 0.0, 0.1, 0.2, 1.0, 0.6, 0.3, 0.4 ], [ 0.0, 0.0, 0.5, 0.7, 0.5, 1.0, 1.0, 0.0 ], [ 0.0, 0.0, 0.2, 0.4, 0.6, 1.0, 1.0, 0.0 ], [ 0.0, 0.2, 0.3, 0.0, 0.0, 0.0, 0.0, 0.0 ] ] p['mapDensityModifier'] = 0.6 p['ukClassBias'] = [ [ 0.0, -0.05, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ], [ -0.05, -0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -0.05, -0.05, 0.05, 0.0, 0.0, 0.0, 0.0 ], [ -0.05, 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ], [ -0.05, 0.0, 0.0, -0.05, -0.05, -0.05, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -0.05, -0.05, -0.05, 0.0, 0.0 ], [ 0.0, 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, -0.05, 0.0, -0.05, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -0.05, 0.0, 0.2, 0.15, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.1, 0.2, 0.15, 0.0 ], [ 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0 ] ] ## Graphical interface details p['interactiveGraphics'] = True p['delayTime'] = 0.0 p['screenWidth'] = 1300 p['screenHeight'] = 700 p['bgColour'] = 'black' p['mainFont'] = 'Helvetica 18' p['fontColour'] = 'white' p['dateX'] = 70 p['dateY'] = 20 p['popX'] = 70 p['popY'] = 50 p['pixelsInPopPyramid'] = 2000 p['careLevelColour'] = ['blue','green','yellow','orange','red'] p['houseSizeColour'] = ['brown','purple','yellow'] p['pixelsPerTown'] = 56 p['maxTextUpdateList'] = 22 return p p = init_params() ####################################################### ## A basic single run ####################################################### ## Batch run (no graphics) ####################################################### ## Retirement age run (no graphics) ####################################################### ##runs for sensitivity analysis using GEM-SA ####################################################### ##runs for sensitivity analysis using GEM-SA - LPtau and Maximin LH ####################################################### ##runs for sensitivity analysis using GEM-SA - LPtau and Maximin LH # def sensitivityLarge(runtype, ageingList, careList, retiredHList, retiredAList, baseDieList, babyDieList, personCareList, maleCareList, femaleCareList, \ # childHoursList, homeAdultList, workingAdultList, lowCareList, growingBirthList, basicDivorceList, variableDivorceList, basicMaleMarriageList, \ # basicFemaleMarriageList, probMoveList, moveHouseholdList, probMoveOutList, probMoveBackList, reps): ####################################################### ##runs for sensitivity analysis using GEM-SA - LPtau and Maximin LH, 10 params ####################################################### # Recurrent neural network experiments -- 10 params, outputs recorded per year ####################################################### ## A profiling run; use import pstats then p = pstats.Stats('profile.txt') then p.sort_stats('time').print_stats(10) #cProfile.run('s.run()','profile.txt') ####################################################### ## Parse command line arguments def loadParamFile(file, dict): """ Given a JSON filename and a dictionary, return the dictionary with the file's fields merged into it. Example: if the initial dictionary is dict['bobAge'] = 90 and dict['samAge']=20 and the JSON data is {'age':{'bob':40, 'fred':35}} the returned dictionary contains the following data values: dict['bobAge'] = 40, dict['fredAge'] = 35, dict['samAge'] = 20 """ json_data = open(file).read() data = json.loads(json_data) for group in data: fields = data.get(group) if type({}) == type(fields): # Group of fields - create name from item and group for item in fields: name = item + group[:1].upper() + group[1:] value = data [group][item] dict [name] = value else: # Single data value - naming is assumed to be correct case dict [group] = fields return dict def loadCommandLine(dict): """Process the command line, loading params file (if required). The dict argument will be augmented with data from the user-specified parameters file (if required), otherwise will return the dict argument unchanged""" parser = argparse.ArgumentParser( description='lives v1.0: complex social behaviour simulation.', epilog='Example: "maintest.py -f test.json -n 3" --- run 3 sims with test.json\'s params', formatter_class=argparse.RawTextHelpFormatter, prog='lives', usage='use "%(prog)s -h" for more information') group = parser.add_mutually_exclusive_group() parser.add_argument( '-f', '--file', help='parameters file in JSON format e.g. soylent.json') group.add_argument( '-n', '--num', metavar='N', type=int, default=0, help='number of runs to carry out.') group.add_argument('-r', '--retire', metavar='R', type=int, default=0, help='retirement batch, number of iterations.') group.add_argument('-g', '--gem', metavar='G', type=int, default=0, help='GEM-SA batch for sensitivity analysis, number of iterations.') group.add_argument('-l', '--lptau', metavar='L', type=int, default=0, help='sensitivity analysis batch with LPtau sampling.') group.add_argument('-m', '--maximin', metavar='M', type=int, default=0, help='sensitivity analysis batch with maximin latin hypercube sampling.') group.add_argument('-b', '--bigly', metavar='B', type=int, default=0, help='bigly sensitivity analysis batch with maximin latin hypercube sampling.') group.add_argument('-t', '--tenparams', metavar='T', type=int, default=0, help='10 parameter sensitivity analysis batch with maximin latin hypercube sampling.') group.add_argument('-c', '--recurrent', metavar='C', type=int, default=0, help='10 parameter time-series run for RNN.') args = parser.parse_args() print("~ Filename: {}".format(args.file)) print("~ Number: {}".format(args.num)) print("~ Retire: {}".format(args.retire)) print("~ GEM-SA: {}".format(args.gem)) print("~ LPtau: {}".format(args.lptau)) print("~ Maximin: {}".format(args.maximin)) print("~ Big SA: {}".format(args.bigly)) print("~ Ten Params: {}".format(args.tenparams)) print("~ Ten Params RNN: {}".format(args.recurrent)) if args.file: #agingParentList = json.load(retireList, parse_float=decimal.Decimal) res = loadParamFile (args.file, dict) print ("p = {}".format(dict)) basicRun(dict) elif args.num >= 1: batchRun(args.num) elif args.retire: p['ageingParentList'] = [] res = loadParamFile('retire.json', dict) print("List = {}".format(dict)) retireRun(args.retire) elif args.gem: p['ageingParentList'] = [] p['careProbList'] = [] p['retiredHoursList'] = [] p['retiredAgeList'] = [] res = loadParamFile('gem.json', dict) print("List = {}".format(dict)) gemRun(args.gem) elif args.lptau: sim_array = np.genfromtxt('lptau-4params.txt', delimiter=' ') sim_list = list(sim_array.T) # print(sim_list) ageingParentSettings = sim_list[0] careProbSettings = sim_list[1] retiredHoursSettings = sim_list[2] retiredAgeSettings = sim_list[3] # print(ageingParentSettings) # print(careProbSettings) # print(retiredHoursSettings) # print(retiredAgeSettings) sensitivityRun('LPtau', ageingParentSettings, careProbSettings, retiredHoursSettings, retiredAgeSettings, args.lptau) elif args.maximin: sim_array = np.genfromtxt('latinhypercube-4params.txt', delimiter=' ') sim_list = list(sim_array.T) # print(sim_list) ageingParentSettings = sim_list[0] careProbSettings = sim_list[1] retiredHoursSettings = sim_list[2] retiredAgeSettings = sim_list[3] # print(ageingParentSettings) # print(careProbSettings) # print(retiredHoursSettings) # print(retiredAgeSettings) sensitivityRun('Maximin', ageingParentSettings, careProbSettings, retiredHoursSettings, retiredAgeSettings, args.maximin) elif args.bigly: sim_array = np.genfromtxt('latinhypercube-22params.txt', delimiter=' ') sim_list = list(sim_array.T) #print(sim_list) np.savetxt('hypercube22_GEMSA_inputs.txt', sim_array, fmt='%1.8f', delimiter='\t', newline='\n') sensitivityLarge('hypercube22', sim_list, args.bigly) elif args.tenparams: sim_array = np.genfromtxt('LPtau-10params.txt', delimiter=' ') sim_list = list(sim_array.T) #print(sim_list) np.savetxt('lptau10_GEMSA_inputs.txt', sim_array, fmt='%1.8f', delimiter='\t', newline='\n') sensitivityTenParams('lptau10', sim_list, args.tenparams) elif args.recurrent: sim_array = np.genfromtxt('lptau10round2_GEMSA_inputs.csv', delimiter=',') sim_list = list(sim_array.T) print(sim_list) np.savetxt('lptau10_recurrent_inputs.txt', sim_array, fmt='%1.8f', delimiter='\t', newline='\n') RNNOutputScenario('LPtauRNN', sim_list, args.recurrent) else: basicRun(p) return dict # Load the default values, overwriting and adding to the initial p values loadParamFile("default.json", p) # Load values based upon the command line file passed (if any). loadCommandLine (p) #print ("p = {}".format(p))

40.08453

188

0.56018

c53f83b4724adf9f9dc5fc23447830899cf93a99

2,427

py

Python

mainapp/views.py

MelqonHovhannisyan/weather

455ce90fd480efb6c05002a53ed478fa4014e84b

[ "MIT" ]

null

mainapp/views.py

MelqonHovhannisyan/weather

455ce90fd480efb6c05002a53ed478fa4014e84b

[ "MIT" ]

null

mainapp/views.py

MelqonHovhannisyan/weather

455ce90fd480efb6c05002a53ed478fa4014e84b

[ "MIT" ]

null

from django.shortcuts import render from rest_framework.viewsets import ViewSet from rest_framework.response import Response from .serializers import WeatherSerializer import requests import json import math import os import yaml from rest_framework.decorators import action from django.conf import settings def api_docs(request): """ Base API Docs endpoint function for the Swagger """ file = open(os.path.join(settings.BASE_DIR, 'api.yaml'), encoding='utf8') spec = yaml.safe_load(file.read()) return render(request, template_name="swagger_base.html", context={'data': json.dumps(spec)})

37.338462

180

0.562835

c53f9f1e1c994d952d8c3879b34114ccaf382fd6

5,420

py

Python

tests/test_backtrack.py

nisaruj/algorithms

1e03cd259c2d7ada113eb99843dcada9f20adf54

[ "MIT" ]

6

2018-12-12T09:14:05.000Z

2019-04-29T22:07:28.000Z

tests/test_backtrack.py

nisaruj/algorithms

1e03cd259c2d7ada113eb99843dcada9f20adf54

[ "MIT" ]

null

tests/test_backtrack.py

nisaruj/algorithms

1e03cd259c2d7ada113eb99843dcada9f20adf54

[ "MIT" ]

1

2021-07-16T16:49:35.000Z

from algorithms.backtrack import ( add_operators, permute, permute_iter, anagram, array_sum_combinations, unique_array_sum_combinations, combination_sum, find_words, pattern_match, ) import unittest from algorithms.backtrack.generate_parenthesis import * if __name__ == '__main__': unittest.main()

28.983957

104

0.474908

c542862715caa74d2fd3f0e9e9fcab1cbbe24d4a

284

py

Python

syncless/wscherry.py

irr/python-labs

43bb3a528c151653b2be832c7ff13240a10e18a4

[ "Apache-2.0" ]

4

2015-11-25T09:06:44.000Z

2019-12-11T21:35:21.000Z

syncless/wscherry.py

irr/python-labs

43bb3a528c151653b2be832c7ff13240a10e18a4

[ "Apache-2.0" ]

null

syncless/wscherry.py

irr/python-labs

43bb3a528c151653b2be832c7ff13240a10e18a4

[ "Apache-2.0" ]

2

2015-11-25T09:19:38.000Z

2016-02-26T03:54:06.000Z

import sys sys.path.append("/usr/lib/python2.7/site-packages") import redis _r = redis.Redis(host='localhost', port=6379, db=0) import cherrypy cherrypy.quickstart(Test())

17.75

51

0.661972

c544eb603d7c0e4860f104e7e494d3ae3bdfe615

538

py

Python

server.py

celinekeisja/jobmonitorservice

aaf56dd198c1275439a0f5ed27617fb458f715ac

[ "MIT" ]

null

server.py

celinekeisja/jobmonitorservice

aaf56dd198c1275439a0f5ed27617fb458f715ac

[ "MIT" ]

null

server.py

celinekeisja/jobmonitorservice

aaf56dd198c1275439a0f5ed27617fb458f715ac

[ "MIT" ]

1

2019-11-11T10:26:42.000Z

from flask_script import Manager from flask_migrate import Migrate, MigrateCommand from config import db import config app = config.connex_app app.add_api('swagger.yml') migrate = Migrate(app=app, db=db) manager = Manager(app=app) manager.add_command('db', MigrateCommand) if __name__ == "__main__": manager.run() # app.run(host='localhost', port=5000, debug=True)

20.692308

54

0.711896

c54618a73487992c76ea8d3ae910cd85c832a27e

4,939

py

Python

website/addons/figshare/views/config.py

harrismendell/osf.io

e2727b1bb2aaa7de494f941be08cb3e9305ae624

[ "Apache-2.0" ]

null

website/addons/figshare/views/config.py

harrismendell/osf.io

e2727b1bb2aaa7de494f941be08cb3e9305ae624

[ "Apache-2.0" ]

null

website/addons/figshare/views/config.py

harrismendell/osf.io

e2727b1bb2aaa7de494f941be08cb3e9305ae624

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import httplib as http from flask import request from framework.exceptions import HTTPError from framework.auth.decorators import must_be_logged_in from website.util import web_url_for from website.project.decorators import ( must_have_addon, must_be_addon_authorizer, must_have_permission, must_not_be_registration, must_be_valid_project ) from ..api import Figshare from ..utils import options_to_hgrid ###### AJAX Config def serialize_settings(node_settings, current_user, client=None): """View helper that returns a dictionary representation of a FigshareNodeSettings record. Provides the return value for the figshare config endpoints. """ current_user_settings = current_user.get_addon('figshare') user_settings = node_settings.user_settings user_has_auth = current_user_settings is not None and current_user_settings.has_auth user_is_owner = user_settings is not None and ( user_settings.owner._primary_key == current_user._primary_key ) valid_credentials = True if user_settings: client = client or Figshare.from_settings(user_settings) articles, status = client.articles(node_settings) if status == 401: valid_credentials = False result = { 'nodeHasAuth': node_settings.has_auth, 'userHasAuth': user_has_auth, 'userIsOwner': user_is_owner, 'urls': serialize_urls(node_settings), 'validCredentials': valid_credentials, } if node_settings.has_auth: # Add owner's profile URL result['urls']['owner'] = web_url_for('profile_view_id', uid=user_settings.owner._primary_key) result['ownerName'] = user_settings.owner.fullname # Show available projects linked = node_settings.linked_content or {'id': None, 'type': None, 'title': None} result['linked'] = linked return result def serialize_urls(node_settings): node = node_settings.owner urls = { 'config': node.api_url_for('figshare_config_put'), 'deauthorize': node.api_url_for('figshare_deauthorize'), 'auth': node.api_url_for('figshare_oauth_start'), 'importAuth': node.api_url_for('figshare_import_user_auth'), 'options': node.api_url_for('figshare_get_options'), 'folders': node.api_url_for('figshare_get_options'), 'files': node.web_url_for('collect_file_trees'), # Endpoint for fetching only folders (including root) 'contents': node.api_url_for('figshare_hgrid_data_contents'), 'settings': web_url_for('user_addons') } return urls

33.371622

90

0.692853

c546f1f9e36c1fc60824e9adb3e2de4e63364611

2,290

py

Python

orquesta/utils/dictionary.py

igcherkaev/orquesta

2baa66d33f53cb04b660b3ce284a52d478ecc528

[ "Apache-2.0" ]

85

2018-07-26T04:29:49.000Z

2022-03-31T10:47:50.000Z

orquesta/utils/dictionary.py

igcherkaev/orquesta

2baa66d33f53cb04b660b3ce284a52d478ecc528

[ "Apache-2.0" ]

149

2018-07-27T22:36:45.000Z

2022-03-31T10:54:32.000Z

orquesta/utils/dictionary.py

igcherkaev/orquesta

2baa66d33f53cb04b660b3ce284a52d478ecc528

[ "Apache-2.0" ]

24

2018-08-07T13:37:41.000Z

2021-12-16T18:12:43.000Z

# Copyright 2019 Extreme Networks, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import six

27.590361

78

0.609607

c549524dfb308c9a530339a9a6c6add82b8d8653

9,114

py

Python

examples/twisted/websocket/auth_persona/server.py

rapyuta-robotics/autobahn-python

c08e9e352d526a7fd0885bb94706366a432ada1a

[ "MIT" ]

1,670

2015-10-12T15:46:22.000Z

2022-03-30T22:12:53.000Z

examples/twisted/websocket/auth_persona/server.py

rapyuta-robotics/autobahn-python

c08e9e352d526a7fd0885bb94706366a432ada1a

[ "MIT" ]

852

2015-10-16T22:11:03.000Z

2022-03-27T07:57:01.000Z

examples/twisted/websocket/auth_persona/server.py

rapyuta-robotics/autobahn-python

c08e9e352d526a7fd0885bb94706366a432ada1a

[ "MIT" ]

790

2015-10-15T08:46:12.000Z

2022-03-30T12:22:13.000Z

############################################################################### # # The MIT License (MIT) # # Copyright (c) Crossbar.io Technologies GmbH # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # ############################################################################### import sys import json import urllib import Cookie from twisted.internet import reactor from twisted.python import log from twisted.web.server import Site from twisted.web.static import File import autobahn from autobahn.util import newid, utcnow from autobahn.websocket import http from autobahn.twisted.websocket import WebSocketServerFactory, \ WebSocketServerProtocol from autobahn.twisted.resource import WebSocketResource if __name__ == '__main__': log.startLogging(sys.stdout) print("Running Autobahn|Python {}".format(autobahn.version)) # our WebSocket server factory factory = PersonaServerFactory("ws://127.0.0.1:8080") # we serve static files under "/" .. root = File(".") # .. and our WebSocket server under "/ws" (note that Twisted uses # bytes for URIs) resource = WebSocketResource(factory) root.putChild(b"ws", resource) # run both under one Twisted Web Site site = Site(root) site.log = lambda _: None # disable any logging reactor.listenTCP(8080, site) reactor.run()

36.456

115

0.585473

c54a392610a02b36eccf6f7a462a2e02a2aa190a

1,681

py

Python

src/ggrc_risks/models/risk.py

Killswitchz/ggrc-core

2460df94daf66727af248ad821462692917c97a9

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

null

src/ggrc_risks/models/risk.py

Killswitchz/ggrc-core

2460df94daf66727af248ad821462692917c97a9

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

null

src/ggrc_risks/models/risk.py

Killswitchz/ggrc-core

2460df94daf66727af248ad821462692917c97a9

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

null

# Copyright (C) 2017 Google Inc. # Licensed under http://www.apache.org/licenses/LICENSE-2.0 <see LICENSE file> from sqlalchemy.ext.declarative import declared_attr from ggrc import db from ggrc.access_control.roleable import Roleable from ggrc.fulltext.mixin import Indexed from ggrc.models.associationproxy import association_proxy from ggrc.models import mixins from ggrc.models.deferred import deferred from ggrc.models.object_document import PublicDocumentable from ggrc.models.object_person import Personable from ggrc.models import reflection from ggrc.models.relationship import Relatable from ggrc.models.track_object_state import HasObjectState

33.62

78

0.732302

c54a493288773ae7775619c9f9c08446cac8b3d2

1,191

py

Python

booknlp/common/calc_coref_metrics.py

ishine/booknlp

2b42ccd40dc2c62097308398d4e08f91ecab4177

[ "MIT" ]

539

2021-11-22T16:29:40.000Z

2022-03-30T17:50:58.000Z

booknlp/common/calc_coref_metrics.py

gxxu-ml/booknlp

2b42ccd40dc2c62097308398d4e08f91ecab4177

[ "MIT" ]

6

2021-12-12T18:21:49.000Z

2022-03-30T20:51:40.000Z

booknlp/common/calc_coref_metrics.py

gxxu-ml/booknlp

2b42ccd40dc2c62097308398d4e08f91ecab4177

[ "MIT" ]

44

2021-11-22T07:22:50.000Z

2022-03-25T20:02:26.000Z

import subprocess, re, sys if __name__ == "__main__": goldFile=sys.argv[1] predFile=sys.argv[2] scorer=sys.argv[3] bcub_f, avg=get_conll(scorer, gold=goldFile, preds=predFile)

31.342105

102

0.686818

c54b7ed70bd070a66a466b8ee7706f4673635759

16,878

py

Python

apps/core/test.py

zjjott/html

68429832d8b022602915a267a62051f4869f430f

[ "MIT" ]

null

apps/core/test.py

zjjott/html

68429832d8b022602915a267a62051f4869f430f

[ "MIT" ]

null

apps/core/test.py

zjjott/html

68429832d8b022602915a267a62051f4869f430f

[ "MIT" ]

null

# coding=utf-8 from __future__ import unicode_literals from tornado.testing import AsyncTestCase from apps.core.models import (ModelBase, _get_master_engine, _get_slave_engine) from tornado.options import options from apps.core.urlutils import urlpattens from apps.auth.views import LoginHandler from apps.views import IndexHandler from apps.core.datastruct import QueryDict, lru_cache from simplejson import loads from tornado.testing import AsyncHTTPTestCase, gen_test from apps.core.httpclient import (RESTfulAsyncClient, SessionClient) from apps.core.crypto import get_random_string from tornado.web import URLSpec import re from tornado.web import Application from apps.core.cache.base import CacheBase, cache as cache_proxy from tornado.gen import sleep from mock import patch from apps.core.timezone import now from concurrent.futures import ThreadPoolExecutor import thread # options.testing = True # mockbase_url

33.159136

77

0.583185

c54bfc8137e477b8a93b0291e14e014c3954ee65

622

py

Python

docker/aws/update_event_mapping.py

uk-gov-mirror/nationalarchives.tdr-jenkins

1bcbee009d4384a777247039d44b2790eba34caa

[ "MIT" ]

null

docker/aws/update_event_mapping.py

uk-gov-mirror/nationalarchives.tdr-jenkins

1bcbee009d4384a777247039d44b2790eba34caa

[ "MIT" ]

34

2020-02-03T14:20:42.000Z

2022-01-26T09:22:09.000Z

docker/aws/update_event_mapping.py

uk-gov-mirror/nationalarchives.tdr-jenkins

1bcbee009d4384a777247039d44b2790eba34caa

[ "MIT" ]

1

2021-04-11T07:11:53.000Z

import sys from sessions import get_session account_number = sys.argv[1] stage = sys.argv[2] function_name = sys.argv[3] version = sys.argv[4] function_arn = f'arn:aws:lambda:eu-west-2:{account_number}:function:{function_name}' boto_session = get_session(account_number, "TDRJenkinsLambdaRole" + stage.capitalize()) client = boto_session.client("lambda") event_mappings = client.list_event_source_mappings()['EventSourceMappings'] uuid = list(filter(lambda x: x['FunctionArn'].startswith(function_arn), event_mappings))[0]['UUID'] client.update_event_source_mapping(UUID=uuid, FunctionName=function_arn + ":" + version)

41.466667

99

0.786174

c54c0437171dca7cbeb276eabca7979dd5dce208

2,202

py

Python

src/python/compressao_huffman.py

willisnou/Algoritmos-e-Estruturas-de-Dados

b70a2f692ccae948576177560e3628b9dece5aee

[ "MIT" ]

653

2015-06-07T14:45:40.000Z

2022-03-25T17:31:58.000Z

src/python/compressao_huffman.py

willisnou/Algoritmos-e-Estruturas-de-Dados

b70a2f692ccae948576177560e3628b9dece5aee

[ "MIT" ]

64

2017-10-29T10:53:37.000Z

2022-03-14T23:49:18.000Z

src/python/compressao_huffman.py

willisnou/Algoritmos-e-Estruturas-de-Dados

b70a2f692ccae948576177560e3628b9dece5aee

[ "MIT" ]

224

2015-06-07T14:46:00.000Z

2022-03-25T17:36:46.000Z

# rvore Huffman # Funo utilitria para imprimir # cdigos huffman para todos os smbolos # na nova rvore huffman que sera criada def printNodes(node, val=''): # cdigo huffman para o n atual newVal = val + str(node.huff) # se o n no pertence ponta da # rvore ento caminha dentro do mesmo # at a ponta if(node.left): printNodes(node.left, newVal) if(node.right): printNodes(node.right, newVal) # Se o n estiver na ponta da rore # ento exibe o cdigo huffman if(not node.left and not node.right): print(f"{node.symbol} -> {newVal}") # caracteres para rvore huffman chars = ['a', 'b', 'c', 'd', 'e', 'f'] # frequncia dos caracteres freq = [5, 9, 12, 13, 16, 45] # lista contendo os ns no utilizados nodes = [] if __name__ == '__main__': # convertendo caracteres e frequncia em # ns da rvore huffman for x in range(len(chars)): nodes.append(node(freq[x], chars[x])) while len(nodes) > 1: # Ordena todos os ns de forma ascendente # baseado em sua frequncia nodes = sorted(nodes, key=lambda x: x.freq) # Seleciona os dois ns menores left = nodes[0] right = nodes[1] # Atribui um valor direcional estes ns # (direita ou esquerda) left.huff = 0 right.huff = 1 # Combina os 2 ns menores para um novo n pai # para eles. newNode = node( left.freq + right.freq, left.symbol + right.symbol, left, right) # remove os 2 ns e adiciona o n pai # como um novo s sobre os outros nodes.remove(left) nodes.remove(right) nodes.append(newNode) # rvore Huffman pronta! printNodes(nodes[0])

24.741573

60

0.584469

c54db6fb5167c6cfc8f323c48a3a8c66fab835af

8,927

py

Python

optiga.py

boraozgen/personalize-optiga-trust

2a158d9fb6cba2bfabce8f5eecb38bc7b81f5bc8

[ "MIT" ]

6

2019-09-27T13:16:29.000Z

2021-04-19T22:00:49.000Z

optiga.py

boraozgen/personalize-optiga-trust

2a158d9fb6cba2bfabce8f5eecb38bc7b81f5bc8

[ "MIT" ]

2

2020-07-10T12:40:59.000Z

2020-08-13T09:26:15.000Z

optiga.py

boraozgen/personalize-optiga-trust

2a158d9fb6cba2bfabce8f5eecb38bc7b81f5bc8

[ "MIT" ]

7

2019-08-23T09:20:52.000Z

2021-06-14T15:01:14.000Z

import argparse import json import base64 import hashlib import sys import binascii from optigatrust.util.types import * from optigatrust.pk import * from optigatrust.x509 import * private_key_slot_map = { 'second': KeyId.ECC_KEY_E0F1, '0xE0E1': KeyId.ECC_KEY_E0F1, '0xE0F1': KeyId.ECC_KEY_E0F1, 'third': KeyId.ECC_KEY_E0F2, '0xE0E2': KeyId.ECC_KEY_E0F2, '0xE0F2': KeyId.ECC_KEY_E0F2, 'fourth': KeyId.ECC_KEY_E0F3, '0xE0E3': KeyId.ECC_KEY_E0F3, '0xE0F3': KeyId.ECC_KEY_E0F3, 'five': KeyId.RSA_KEY_E0FC, '0xE0FC': KeyId.RSA_KEY_E0FC, 'six': KeyId.RSA_KEY_E0FD, '0xE0FD': KeyId.RSA_KEY_E0FD } certificate_slot_map = { 'second': ObjectId.USER_CERT_1, '0xE0E1': ObjectId.USER_CERT_1, '0xE0F1': ObjectId.USER_CERT_1, 'third': ObjectId.USER_CERT_2, '0xE0E2': ObjectId.USER_CERT_2, '0xE0F2': ObjectId.USER_CERT_2, 'fourth': ObjectId.USER_CERT_3, '0xE0E3': ObjectId.USER_CERT_3, '0xE0F3': ObjectId.USER_CERT_3, '0xE0E8': ObjectId.TRUST_ANCHOR_1, '0xE0EF': ObjectId.TRUST_ANCHOR_2 } object_slot_map = { '0xf1d0': ObjectId.DATA_TYPE1_0, '0xf1d1': ObjectId.DATA_TYPE1_1, '0xf1d2': ObjectId.DATA_TYPE1_2, '0xf1d3': ObjectId.DATA_TYPE1_3, '0xf1d4': ObjectId.DATA_TYPE1_4, '0xf1d5': ObjectId.DATA_TYPE1_5, '0xf1d6': ObjectId.DATA_TYPE1_6, '0xf1d7': ObjectId.DATA_TYPE1_7, '0xf1d8': ObjectId.DATA_TYPE1_8, '0xf1d9': ObjectId.DATA_TYPE1_9, '0xf1da': ObjectId.DATA_TYPE1_A, '0xf1db': ObjectId.DATA_TYPE1_B, '0xf1dc': ObjectId.DATA_TYPE1_C, '0xf1dd': ObjectId.DATA_TYPE1_D, '0xf1de': ObjectId.DATA_TYPE1_E, '0xf1e0': ObjectId.DATA_TYPE2_0, '0xf1e1': ObjectId.DATA_TYPE2_1 } allowed_object_ids = [ # Certificate Slots '0xe0e0', '0xe0e1', '0xe0e2', '0xe0e3', # Trust Anchor Slots '0xe0e8', '0xe0ef', # Arbitrary Data Objects '0xf1d0', '0xf1d1', '0xf1d2', '0xf1d3', '0xf1d4', '0xf1d5', '0xf1d6', '0xf1d7', '0xf1d8', '0xf1d9', '0xf1da', '0xf1db', '0xf1dc', '0xf1dd', '0xf1de', '0xf1e0', '0xf1e1' ] ''' ################################################################################################################# ''' parser = argparse.ArgumentParser(description="Communicate with your OPTIGA(TM) Trust sample") group = parser.add_mutually_exclusive_group() group.add_argument("-v", "--verbose", action="store_true") group.add_argument("-q", "--quiet", action="store_true") parser.add_argument("--query", nargs=1, metavar='QUERY_ARGUMENT', help="Define the query argument you want to extract from the output") parser.add_argument("--csr", metavar='CONFIG_FILE', help="Instructs the script to generate a Certificate Signing Request." "Give the script the configuration file for your CSR (fields like Common Name, " "AWS IoT Thing Name, etc)") parser.add_argument("--write", metavar='DATA_TO_WRITE', help="Write provided data to the chip.") parser.add_argument("--read", metavar='OBJECT_ID', choices=allowed_object_ids, help="Certificate Slots: 0xe0e0-0xe0e3\n" "Trust Anchor slots: 0xe0e8 and 0xe0ef\n" "100 bytes: 0xf1d0-0xf1de\n" "1500 bytes: 0xf1e0, 0xf1e1") parser.add_argument("--slot", choices=[ # They all mean the same 'second', '0xe0e1', '0xe0f1', 'third', '0xe0e2', '0xe0f2', 'fourth', '0xe0e3', '0xe0f3', 'five', '0xe0fc', 'six', '0xe0fd', '0xE0E8', '0xE0EF' ], help="Use one the predefined slots; e.g. second, 0xe0e1, or 0xe0f1, they all mean the same") parser.add_argument("--id", metavar='OBJECT_ID', choices=allowed_object_ids, help="USe to define which ID to use with your write command \n" "Certificate Slots: 0xe0e0-0xe0e3\n" "Trust Anchor slots: 0xe0e8 and 0xe0ef\n" "100 bytes: 0xf1d0-0xf1de\n" "1500 bytes: 0xf1e0, 0xf1e1") args = parser.parse_args() if args.csr: parse_csr(args) sys.exit(0) if args.write: parse_write(args) sys.exit(0) else: parser.print_help() sys.exit(0)

39.325991

121

0.596729

c54de03fd28e53eb54540b034a2e8a1f2994146a

3,532

py

Python

graph_test.py

MathewMacDougall/Two-Faced-Type

53fae81a151fd0689ac7328dda6b3e984c9a42e9

[ "MIT" ]

null

graph_test.py

MathewMacDougall/Two-Faced-Type

53fae81a151fd0689ac7328dda6b3e984c9a42e9

[ "MIT" ]

25

2020-11-15T05:30:23.000Z

2020-12-12T22:03:35.000Z

graph_test.py

MathewMacDougall/Two-Faced-Type

53fae81a151fd0689ac7328dda6b3e984c9a42e9

[ "MIT" ]

null

import unittest from graph import Graph if __name__ == '__main__': unittest.main()

34.627451

72

0.610136

c5508e61b45a9bd59041d4ba0c8bea652aa09b89

2,033

py

Python

cfnbootstrap/construction_errors.py

roberthutto/aws-cfn-bootstrap

801a16802a931fa4dae0eba4898fe1ccdb304924

[ "Apache-2.0" ]

null

cfnbootstrap/construction_errors.py

roberthutto/aws-cfn-bootstrap

801a16802a931fa4dae0eba4898fe1ccdb304924

[ "Apache-2.0" ]

null

cfnbootstrap/construction_errors.py

roberthutto/aws-cfn-bootstrap

801a16802a931fa4dae0eba4898fe1ccdb304924

[ "Apache-2.0" ]

3

2017-02-10T13:14:38.000Z

2018-09-20T01:04:20.000Z

#============================================================================== # Copyright 2011 Amazon.com, Inc. or its affiliates. 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. #==============================================================================

28.236111

79

0.619774

c5514806a6a0a0953948700c69152edf438355ea

2,798

py

Python

tests/test_variable.py

snc2/tequila

6767ced9215408f7d055c22df7a66ccd610b00fb

[ "MIT" ]

1

2021-01-11T18:40:47.000Z

tests/test_variable.py

snc2/tequila

6767ced9215408f7d055c22df7a66ccd610b00fb

[ "MIT" ]

1

2020-05-08T13:34:33.000Z

2021-12-06T06:12:37.000Z

tests/test_variable.py

snc2/tequila

6767ced9215408f7d055c22df7a66ccd610b00fb

[ "MIT" ]

null

import pytest from tequila import numpy as np from tequila.circuit.gradient import grad from tequila.objective.objective import Objective, Variable import operator

39.408451

260

0.550751

c55176ac699f36bb549a798358fd9868f0da10c3

7,649

py

Python

getnear/tseries.py

edwardspeyer/getnear

746f3cedc1aed6166423f54d32e208017f660b38

[ "MIT" ]

null

getnear/tseries.py

edwardspeyer/getnear

746f3cedc1aed6166423f54d32e208017f660b38

[ "MIT" ]

null

getnear/tseries.py

edwardspeyer/getnear

746f3cedc1aed6166423f54d32e208017f660b38

[ "MIT" ]

null

from getnear.config import Tagged, Untagged, Ignore from getnear.logging import info from lxml import etree import re import requests import telnetlib

34.61086

92

0.552098

c5524c8d02f3aef3cff31c032990bb8d482aaf1e

16,945

py

Python

Tests/subset/svg_test.py

ThomasRettig/fonttools

629f44b8cc4ed768088b952c9e600190685a90fc

[ "Apache-2.0", "MIT" ]

2,705

2016-09-27T10:02:12.000Z

2022-03-31T09:37:46.000Z

Tests/subset/svg_test.py

ThomasRettig/fonttools

629f44b8cc4ed768088b952c9e600190685a90fc

[ "Apache-2.0", "MIT" ]

1,599

2016-09-27T09:07:36.000Z

2022-03-31T23:04:51.000Z

Tests/subset/svg_test.py

ThomasRettig/fonttools

629f44b8cc4ed768088b952c9e600190685a90fc

[ "Apache-2.0", "MIT" ]

352

2016-10-07T04:18:15.000Z

2022-03-30T07:35:01.000Z

from string import ascii_letters import textwrap from fontTools.misc.testTools import getXML from fontTools import subset from fontTools.fontBuilder import FontBuilder from fontTools.pens.ttGlyphPen import TTGlyphPen from fontTools.ttLib import TTFont, newTable from fontTools.subset.svg import NAMESPACES, ranges import pytest etree = pytest.importorskip("lxml.etree") # This contains a bunch of cross-references between glyphs, paths, gradients, etc. # Note the path coordinates are completely made up and not meant to be rendered. # We only care about the tree structure, not it's visual content. COMPLEX_SVG = """\ <svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <defs> <linearGradient id="lg1" x1="50" x2="50" y1="80" y2="80" gradientUnits="userSpaceOnUse"> <stop stop-color="#A47B62" offset="0"/> <stop stop-color="#AD8264" offset="1.0"/> </linearGradient> <radialGradient id="rg2" cx="50" cy="50" r="10" gradientUnits="userSpaceOnUse"> <stop stop-color="#A47B62" offset="0"/> <stop stop-color="#AD8264" offset="1.0"/> </radialGradient> <radialGradient id="rg3" xlink:href="#rg2" r="20"/> <radialGradient id="rg4" xlink:href="#rg3" cy="100"/> <path id="p1" d="M3,3"/> <clipPath id="c1"> <circle cx="10" cy="10" r="1"/> </clipPath> </defs> <g id="glyph1"> <g id="glyph2"> <path d="M0,0"/> </g> <g> <path d="M1,1" fill="url(#lg1)"/> <path d="M2,2"/> </g> </g> <g id="glyph3"> <use xlink:href="#p1"/> </g> <use id="glyph4" xlink:href="#glyph1" x="10"/> <use id="glyph5" xlink:href="#glyph2" y="-10"/> <g id="glyph6"> <use xlink:href="#p1" transform="scale(2, 1)"/> </g> <g id="group1"> <g id="glyph7"> <path id="p2" d="M4,4"/> </g> <g id=".glyph7"> <path d="M4,4"/> </g> <g id="glyph8"> <g id=".glyph8"> <path id="p3" d="M5,5"/> <path id="M6,6"/> </g> <path d="M7,7"/> </g> <g id="glyph9"> <use xlink:href="#p2"/> </g> <g id="glyph10"> <use xlink:href="#p3"/> </g> </g> <g id="glyph11"> <path d="M7,7" fill="url(#rg4)"/> </g> <g id="glyph12"> <path d="M7,7" style="fill:url(#lg1);stroke:red;clip-path:url(#c1)"/> </g> </svg> """

34.652352

110

0.477781

c552f157bcec716a7f87d20bd21cf1b7b813d8da

211

py

Python

models/dl-weights.py

diegoinacio/object-detection-flask-opencv

bc012e884138e9ead04115b8550e833bed134074

[ "MIT" ]

16

2020-03-01T07:35:35.000Z

2022-02-01T16:34:24.000Z

models/dl-weights.py

girish008/Real-Time-Object-Detection-Using-YOLOv3-OpenCV

6af4c550f6128768b646f5923af87c2f654cd1bd

[ "MIT" ]

6

2020-02-13T12:50:24.000Z

2022-02-02T03:22:30.000Z

models/dl-weights.py

girish008/Real-Time-Object-Detection-Using-YOLOv3-OpenCV

6af4c550f6128768b646f5923af87c2f654cd1bd

[ "MIT" ]

8

2020-06-22T10:23:58.000Z

2022-01-14T21:17:50.000Z

""" This script downloads the weight file """ import requests URL = "https://pjreddie.com/media/files/yolov3.weights" r = requests.get(URL, allow_redirects=True) open('yolov3_t.weights', 'wb').write(r.content)

23.444444

55

0.739336

c55412d74acd62e5e8c97c0f510ea4a9a80e5595

1,786

py

Python

utim-esp32/modules/utim/utilities/process_device.py

connax-utim/utim-micropython

23c30f134af701a44a8736b09c8c201e13760d18

[ "Apache-2.0" ]

null

utim-esp32/modules/utim/utilities/process_device.py

connax-utim/utim-micropython

23c30f134af701a44a8736b09c8c201e13760d18

[ "Apache-2.0" ]

null

utim-esp32/modules/utim/utilities/process_device.py

connax-utim/utim-micropython

23c30f134af701a44a8736b09c8c201e13760d18

[ "Apache-2.0" ]

null

""" Subprocessor for device messages """ import logging from ..utilities.tag import Tag from ..workers import device_worker_forward from ..workers import device_worker_startup from ..utilities.address import Address from ..utilities.status import Status from ..utilities.data_indexes import SubprocessorIndex _SubprocessorIndex = SubprocessorIndex() logger = logging.Logger('utilities.process_device')

33.074074

80

0.663494

c556608e317003e7eff23a5318cc565b380cac29

174

py

Python

TrainAndTest/Fbank/LSTMs/__init__.py

Wenhao-Yang/DeepSpeaker-pytorch

99eb8de3357c85e2b7576da2a742be2ffd773ead

[ "MIT" ]

8

2020-08-26T13:32:56.000Z

2022-01-18T21:05:46.000Z

TrainAndTest/Fbank/LSTMs/__init__.py

Wenhao-Yang/DeepSpeaker-pytorch

99eb8de3357c85e2b7576da2a742be2ffd773ead

[ "MIT" ]

1

2020-07-24T17:06:16.000Z

TrainAndTest/Fbank/LSTMs/__init__.py

Wenhao-Yang/DeepSpeaker-pytorch

99eb8de3357c85e2b7576da2a742be2ffd773ead

[ "MIT" ]

5

2020-12-11T03:31:15.000Z

2021-11-23T15:57:55.000Z

#!/usr/bin/env python # encoding: utf-8 """ @Author: yangwenhao @Contact: 874681044@qq.com @Software: PyCharm @File: __init__.py.py @Time: 2020/3/27 10:43 AM @Overview: """

14.5

26

0.689655

c556a7e2e7f0a44508e2fef82666c7378cbf88cf

226

py

Python

ninja/security/__init__.py

lsaavedr/django-ninja

caa182007368bb0fed85b184fb0583370e9589b4

[ "MIT" ]

null

ninja/security/__init__.py

lsaavedr/django-ninja

caa182007368bb0fed85b184fb0583370e9589b4

[ "MIT" ]

null

ninja/security/__init__.py

lsaavedr/django-ninja

caa182007368bb0fed85b184fb0583370e9589b4

[ "MIT" ]

null

from ninja.security.apikey import APIKeyQuery, APIKeyCookie, APIKeyHeader from ninja.security.http import HttpBearer, HttpBasicAuth

28.25

73

0.800885

c5596189b90b1ffb040eef3bc2ba25c968d94c71

1,160

py

Python

migrations/versions/66d4be40bced_add_attribute_to_handle_multiline_.py

eubr-bigsea/limonero

54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5

[ "Apache-2.0" ]

1

2018-01-01T20:35:43.000Z

migrations/versions/66d4be40bced_add_attribute_to_handle_multiline_.py

eubr-bigsea/limonero

54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5

[ "Apache-2.0" ]

37

2017-02-24T17:07:25.000Z

2021-09-02T14:49:19.000Z

migrations/versions/66d4be40bced_add_attribute_to_handle_multiline_.py

eubr-bigsea/limonero

54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5

[ "Apache-2.0" ]

2

2019-11-05T13:45:45.000Z

2020-11-13T22:02:37.000Z

"""Add attribute to handle multiline information Revision ID: 66d4be40bced Revises: 6a809295d586 Create Date: 2018-05-16 12:13:32.023450 """ import sqlalchemy as sa from alembic import op from limonero.migration_utils import is_sqlite # revision identifiers, used by Alembic. revision = '66d4be40bced' down_revision = '6a809295d586' branch_labels = None depends_on = None

29.74359

108

0.668103

c559db70f1ddb6f54d717326e423cfde57c7f2af

247

py

Python

config.py

kxxoling/horus

a3c4b6c40a1064fffa595976f10358178dd65367

[ "MIT" ]

null

config.py

kxxoling/horus

a3c4b6c40a1064fffa595976f10358178dd65367

[ "MIT" ]

null

config.py

kxxoling/horus

a3c4b6c40a1064fffa595976f10358178dd65367

[ "MIT" ]

null

import os BASE_DIR = os.path.abspath(os.path.dirname(__file__)) CSRF_ENABLED = True SECRET_KEY = 'you-will-never-guess' SQLITE = 'db.sqlite3' SQLALCHEMY_DATABASE_URI = 'sqlite:///' + os.path.join(BASE_DIR, SQLITE) + '?check_same_thread=False'

22.454545

100

0.740891

c55a4b523b8ba2e29366bb76e2448cbced42c61f

4,372

py

Python

tests/test_lp_problem.py

LovisAnderson/flipy

bde898e46e34cdfba39cecb75586fa3f4d816520

[ "Apache-2.0" ]

null

tests/test_lp_problem.py

LovisAnderson/flipy

bde898e46e34cdfba39cecb75586fa3f4d816520

[ "Apache-2.0" ]

null

tests/test_lp_problem.py

LovisAnderson/flipy

bde898e46e34cdfba39cecb75586fa3f4d816520

[ "Apache-2.0" ]

null

import pytest from flipy.lp_problem import LpProblem from flipy.lp_objective import LpObjective, Maximize from flipy.lp_variable import LpVariable from flipy.lp_expression import LpExpression from flipy.lp_constraint import LpConstraint from io import StringIO

41.638095

205

0.665599

c55a6c83c0c4deda47ef169a2a79ced739a7f4c8

106

py

Python

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

from django.apps import AppConfig

17.666667

39

0.792453

c55b87c8df2b77ae553d466bad5d103ac2336d62

5,893

py

Python

tests/components/tectonics/test_listric_kinematic_extender.py

amanaster2/landlab

ea17f8314eb12e3fc76df66c9b6ff32078caa75c

[ "MIT" ]

257

2015-01-13T16:01:21.000Z

2022-03-29T22:37:43.000Z

tests/components/tectonics/test_listric_kinematic_extender.py

amanaster2/landlab

ea17f8314eb12e3fc76df66c9b6ff32078caa75c

[ "MIT" ]

1,222

2015-02-05T21:36:53.000Z

2022-03-31T17:53:49.000Z

tests/components/tectonics/test_listric_kinematic_extender.py

amanaster2/landlab

ea17f8314eb12e3fc76df66c9b6ff32078caa75c

[ "MIT" ]

274

2015-02-11T19:56:08.000Z

2022-03-28T23:31:07.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Mar 5 08:42:24 2021 @author: gtucker """ from numpy.testing import assert_array_almost_equal, assert_array_equal, assert_raises from landlab import HexModelGrid, RadialModelGrid, RasterModelGrid from landlab.components import Flexure, ListricKinematicExtender def test_hangingwall_nodes(): """Test the correct identification of hangingwall nodes.""" grid = RasterModelGrid((3, 7), xy_spacing=2500.0) grid.add_zeros("topographic__elevation", at="node") extender = ListricKinematicExtender(grid, fault_location=2500.0) assert_array_equal( extender._hangwall, [2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20] ) def test_subsidence_and_horiz_shift(): """Test that elev subsides then shifts after 2 time steps.""" grid = RasterModelGrid((3, 7), xy_spacing=2500.0) topo = grid.add_zeros("topographic__elevation", at="node") extender = ListricKinematicExtender( grid, extension_rate=0.01, fault_location=2500.0 ) # Run long enough to extend by half a grid cell extender.run_one_step(dt=125000.0) assert_array_almost_equal( topo[7:14], [0.0, 0.0, -1404.156819, -910.66907, -590.616478, -383.045648, -248.425118], ) # Now extend another half cell, so cumulative extension is one cell and # elevations should get shifted by one cell extender.run_one_step(dt=125000.0) assert_array_almost_equal( topo[7:14], [0.0, 0.0, -3514.477461, -2808.313638, -1821.338140, -1181.232956, -766.091296], ) # Another step, and this time the hangingwall edge has moved by one cell, # so the first 3 cells in this row should not further subside. extender.run_one_step(dt=125000.0) assert_array_almost_equal( topo[7:14], [ 0.0, 0.0, -3514.477461, -3718.982708, -2411.954617, -1564.278603, -1014.516414, ], ) def test_with_flexure(): """Test integrating with flexure.""" crust_density = 2700.0 # density of crustal column, kg/m3 dx = 2500.0 # grid spacing, m dt = 125000.0 # time step, y upper_crust_base_depth = 10000.0 # m grid = RasterModelGrid((3, 7), xy_spacing=dx) topo = grid.add_zeros("topographic__elevation", at="node") load = grid.add_zeros("lithosphere__overlying_pressure_increment", at="node") thickness = grid.add_zeros("upper_crust_thickness", at="node") upper_crust_base = grid.add_zeros("upper_crust_base__elevation", at="node") extender = ListricKinematicExtender( grid, extension_rate=0.01, fault_location=2500.0, track_crustal_thickness=True, ) flexer = Flexure(grid, eet=5000.0, method="flexure") deflection = grid.at_node["lithosphere_surface__elevation_increment"] topo[ grid.x_of_node <= 7500.0 ] = 1000.0 # this will force thickness to be 1 km greater at left upper_crust_base[:] = -upper_crust_base_depth thickness[:] = topo - upper_crust_base unit_wt = crust_density * flexer.gravity load[:] = unit_wt * thickness # loading pressure # Get the initial deflection, which we'll need to calculate total current # deflection flexer.update() init_deflection = deflection.copy() # Run extension for half a grid cell. Elevations change, but thickness # doesn't, so deflection should not change. We should be able to recover # elevation from: # # topo = thickness + crust base - (deflection + subsidence) # extender.run_one_step(dt=dt) flexer.update() net_deflection = deflection - init_deflection assert_array_almost_equal( net_deflection[7:14], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], ) test_topo = thickness + upper_crust_base - (net_deflection + extender._cum_subs) assert_array_almost_equal(topo, test_topo) # Now extend for another half cell, which should force a shift. The # cumulative subsidence will be subtracted from the thickness field, # representing thinning as the hangingwall slides to the "right". This # will cause net upward isostatic deflection. extender.run_one_step(dt=dt) load[:] = unit_wt * thickness flexer.update() net_deflection = deflection - init_deflection assert_array_almost_equal( thickness[7:14], [ 11000.0, 11000.0, 8191.686362, # greatest subsidence: lost nearly 3 km 9178.66186, 9818.767044, # thicker because shifted (only lost <200 m) 9233.908704, 9503.149763, ], ) assert_array_almost_equal( net_deflection[7:14], [ -59.497362, -65.176276, -69.222531, -70.334462, -68.608952, -64.912352, -59.743080, ], )

33.293785

88

0.659426

c55c22b2cd2bfee50cd66031731dbde75ccb7354

22,485

py

Python

unbalanced_dataset/under_sampling.py

designer357/IGBB

89a60ec38fa9dab54175c24c347ee43232825504

[ "MIT" ]

1

2021-08-20T17:14:28.000Z

unbalanced_dataset/under_sampling.py

designer357/IGBB

89a60ec38fa9dab54175c24c347ee43232825504

[ "MIT" ]

null

unbalanced_dataset/under_sampling.py

designer357/IGBB

89a60ec38fa9dab54175c24c347ee43232825504

[ "MIT" ]

1

2018-09-13T23:26:23.000Z

from __future__ import print_function from __future__ import division import numpy as np from numpy import logical_not, ones from numpy.random import seed, randint from numpy import concatenate from random import sample from collections import Counter from .unbalanced_dataset import UnbalancedDataset

34.806502

104

0.558417

c55c65db8051ee9fdf9ceac3a9490b6f81b381e7

931

py

Python

wikipron/extract/cmn.py

Alireza-Sampour/wikipron

ac821c5d0a7d70e7e700f45f9d01b2dfb4ecae9d

[ "Apache-2.0" ]

1

2021-08-01T20:31:27.000Z

wikipron/extract/cmn.py

Alireza-Sampour/wikipron

ac821c5d0a7d70e7e700f45f9d01b2dfb4ecae9d

[ "Apache-2.0" ]

null

wikipron/extract/cmn.py

Alireza-Sampour/wikipron

ac821c5d0a7d70e7e700f45f9d01b2dfb4ecae9d

[ "Apache-2.0" ]

null

"""Word and pron extraction for (Mandarin) Chinese.""" import itertools import typing import requests from wikipron.extract.default import yield_pron, IPA_XPATH_SELECTOR if typing.TYPE_CHECKING: from wikipron.config import Config from wikipron.typing import Iterator, Word, Pron, WordPronPair # Select pron from within this li _PRON_XPATH_TEMPLATE = """ //div[@class="vsHide"] //ul //li[(a[@title="w:Mandarin Chinese"])] """

25.162162

71

0.71536

c55ca719e407ecd982eeb52d8e27fa9690f85669

420

py

Python

iis/tests/test_e2e.py

tcpatterson/integrations-core

3692601de09f8db60f42612b0d623509415bbb53

[ "BSD-3-Clause" ]

null

iis/tests/test_e2e.py

tcpatterson/integrations-core

3692601de09f8db60f42612b0d623509415bbb53

[ "BSD-3-Clause" ]

null

iis/tests/test_e2e.py

tcpatterson/integrations-core

3692601de09f8db60f42612b0d623509415bbb53

[ "BSD-3-Clause" ]

null

# (C) Datadog, Inc. 2022-present # All rights reserved # Licensed under Simplified BSD License (see LICENSE) import pytest from datadog_checks.dev.testing import requires_py3 from datadog_checks.iis import IIS

26.25

76

0.797619

c560c444067061f2f72e5a0dd18c1c1230d2f961

1,174

py

Python

scripts/utils/param_grid_to_files.py

bagustris/emotion

5bd83d3ca8a6eb930f449b7a990fefd75d0c7d36

[ "MIT" ]

3

2020-11-03T14:54:22.000Z

2021-04-12T12:23:10.000Z

scripts/utils/param_grid_to_files.py

bagustris/emotion

5bd83d3ca8a6eb930f449b7a990fefd75d0c7d36

[ "MIT" ]

null

scripts/utils/param_grid_to_files.py

bagustris/emotion

5bd83d3ca8a6eb930f449b7a990fefd75d0c7d36

[ "MIT" ]

2

2020-12-03T06:21:59.000Z

2021-01-16T04:47:12.000Z

from pathlib import Path import click import yaml from sklearn.model_selection import ParameterGrid from ertk.utils import PathlibPath, get_arg_mapping if __name__ == "__main__": main()

32.611111

76

0.67632

c5610fccc549a5c9d69f6c3b166e598fbe0653b9

6,172

py

Python

mangabee_parsers.py

ta-dachi/mangaget

4ef39df0a6cceb2817d3bd0ad4d8290b8f576341

[ "MIT" ]

null

mangabee_parsers.py

ta-dachi/mangaget

4ef39df0a6cceb2817d3bd0ad4d8290b8f576341

[ "MIT" ]

null

mangabee_parsers.py

ta-dachi/mangaget

4ef39df0a6cceb2817d3bd0ad4d8290b8f576341

[ "MIT" ]

null

from html.parser import HTMLParser

35.883721

124

0.545366

c5630abd4f13c6d9b9fd911d42b444b3c07c02dd

1,831

py

Python

bme280/reader.py

budrom/dht2eleasticsearch

286974c0f4096ae3fb2f1f700b761051b09c47cf

[ "MIT" ]

null

bme280/reader.py

budrom/dht2eleasticsearch

286974c0f4096ae3fb2f1f700b761051b09c47cf

[ "MIT" ]

null

bme280/reader.py

budrom/dht2eleasticsearch

286974c0f4096ae3fb2f1f700b761051b09c47cf

[ "MIT" ]

null

#!/usr/bin/python3 import os import threading import sys from Adafruit_BME280 import * from datetime import datetime from elasticsearch import Elasticsearch def send2es(data): """ Initiate connection to Elasticsearch and send data as a single document. data - dictionary/JSON to be sent """ i = 'metrics_{}'.format(datetime.now().strftime('%m.%y')) es.index(index=i, doc_type='measurement', body=data) if __name__ == "__main__": print("Script started") try: es_host = os.environ['ELASTICSEARCH_URL'] es_user = os.environ['ELASTICSEARCH_USER'] es_pass = os.environ['ELASTICSEARCH_PASSWORD'] es = Elasticsearch(es_host, http_auth=(es_user, es_pass)) except KeyError: es_host = None try: t_compensation = float(os.environ['T_COMPENSATION']) except KeyError: t_compensation = 0 sensor = BME280(t_mode=BME280_OSAMPLE_2, p_mode=BME280_OSAMPLE_8, h_mode=BME280_OSAMPLE_1, filter=BME280_FILTER_16, address=0x76) threading.Timer(60-float(datetime.utcnow().strftime('%S.%f')), readSensor).start() print("Waiting for next minute to start loop...")

31.033898

125

0.688695

c565a1b2f5a20a17f2045f38225c4233abda30b9

456

py

Python

tests/web/backend_pytest.py

brumar/eel-for-transcrypt

28cf5e0aa55a3c885b63d79d1ffae1370be644d2

[ "MIT" ]

1

2019-12-31T13:53:05.000Z

tests/web/backend_pytest.py

brumar/eel-for-transcrypt

28cf5e0aa55a3c885b63d79d1ffae1370be644d2

[ "MIT" ]

1

2021-11-15T17:48:03.000Z

tests/web/backend_pytest.py

brumar/eel-for-transcrypt

28cf5e0aa55a3c885b63d79d1ffae1370be644d2

[ "MIT" ]

null

import eel_for_transcrypt as eel from web.common import InventoryItem

16.888889

48

0.756579

c565d028bd9c69f1d86bec597f86ad7c3dad14ce

6,989

py

Python

tests/test_polygon.py

tilezen/mapbox-vector-tile

4e3a65a6f98c317048266260b8e7aac705e31e6f

[ "MIT" ]

121

2016-07-14T00:44:54.000Z

2022-03-19T00:49:14.000Z

tests/test_polygon.py

tilezen/mapbox-vector-tile

4e3a65a6f98c317048266260b8e7aac705e31e6f

[ "MIT" ]

53

2016-07-05T14:35:06.000Z

2021-05-20T22:31:02.000Z

tests/test_polygon.py

tilezen/mapbox-vector-tile

4e3a65a6f98c317048266260b8e7aac705e31e6f

[ "MIT" ]

34

2016-07-27T23:45:05.000Z

2022-01-02T20:37:58.000Z

# -*- coding: utf-8 -*- """ Tests for vector_tile/polygon.py """ import unittest from mapbox_vector_tile.polygon import make_it_valid from shapely import wkt import os

34.945

78

0.529976

c567553f0cf12169873a1f6859559b2967a6ea7a

275

py

Python

snake_debug.py

xlrobotics/PPOC-balance-bot

41dae4b2bbfce94ed04841fa9ba122eb57459e5a

[ "MIT" ]

3

2020-11-10T01:45:35.000Z

2021-09-27T11:39:06.000Z

snake_debug.py

xlrobotics/PPOC-balance-bot

41dae4b2bbfce94ed04841fa9ba122eb57459e5a

[ "MIT" ]

null

snake_debug.py

xlrobotics/PPOC-balance-bot

41dae4b2bbfce94ed04841fa9ba122eb57459e5a

[ "MIT" ]

2

2020-01-25T17:26:33.000Z

2021-02-16T16:39:38.000Z

import gym # from stable_baselines import DQN as deepq from stable_baselines import A2C as ac from stable_baselines.common.policies import MlpLnLstmPolicy import snake_bot if __name__ == '__main__': env = gym.make("snakebot-v0") env.debug_mode() exit(0)

27.5

61

0.741818

c5675771c49be7e9f7d6d764c6141228f78fdc9d

2,179

py

Python

easy/572_subtree_of_another_tree.py

niki4/leetcode_py3

794f560a09a8950da21bd58ea222e0c74449ffa6

[ "MIT" ]

null

easy/572_subtree_of_another_tree.py

niki4/leetcode_py3

794f560a09a8950da21bd58ea222e0c74449ffa6

[ "MIT" ]

null

easy/572_subtree_of_another_tree.py

niki4/leetcode_py3

794f560a09a8950da21bd58ea222e0c74449ffa6

[ "MIT" ]

null

""" Given the roots of two binary trees root and subRoot, return true if there is a subtree of root with the same structure and node values of subRoot and false otherwise. A subtree of a binary tree tree is a tree that consists of a node in tree and all of this node's descendants. The tree tree could also be considered as a subtree of itself. Example 1: 3 (root) /\ 4 5 4 (subroot) / \ / \ 1 2 1 2 Input: root = [3,4,5,1,2], subRoot = [4,1,2] Output: true Example 2: 3 (root) /\ 4 5 4 (subroot) / \ / \ 1 2 1 2 / 0 Input: root = [3,4,5,1,2,null,null,null,null,0], subRoot = [4,1,2] Output: false Constraints: The number of nodes in the root tree is in the range [1, 2000]. The number of nodes in the subRoot tree is in the range [1, 1000]. -104 <= root.val <= 104 -104 <= subRoot.val <= 104 """ from tools.binary_tree import TreeNode

33.523077

119

0.592015

c567629ea21a15f16d30ea7895f7a40e8e344679

80,085

py

Python

pyeccodes/defs/grib2/localConcepts/cnmc/name_def.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

7

2020-04-14T09:41:17.000Z

2021-08-06T09:38:19.000Z

pyeccodes/defs/grib2/localConcepts/cnmc/name_def.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

null

pyeccodes/defs/grib2/localConcepts/cnmc/name_def.py

ecmwf/pyeccodes

dce2c72d3adcc0cb801731366be53327ce13a00b

[ "Apache-2.0" ]

3

2020-04-30T12:44:48.000Z

2020-12-15T08:40:26.000Z

import pyeccodes.accessors as _

66.7375

355

0.700893

c56762e2edaef44daca6ab74ffdc3c598a3d259d

2,038

py

Python

perspective_transform.py

shengchen-liu/CarND-Advanced_Lane_Finding

e23a3f5021e59f3acef4e8fec48537fffab0f1b3

[ "MIT" ]

null

perspective_transform.py

shengchen-liu/CarND-Advanced_Lane_Finding

e23a3f5021e59f3acef4e8fec48537fffab0f1b3

[ "MIT" ]

null

perspective_transform.py

shengchen-liu/CarND-Advanced_Lane_Finding

e23a3f5021e59f3acef4e8fec48537fffab0f1b3

[ "MIT" ]

null

import numpy as np import cv2 import matplotlib.pyplot as plt from calibration_utils import calibrate_camera, undistort import glob import matplotlib.image as mpimg import pickle from threshold import binarize def perspective_transform(img, verbose=False): """ Execute perspective transform """ img_size = (img.shape[1], img.shape[0]) # algorithm to automatically pick? # https: // knowledge.udacity.com / questions / 22331 src = np.float32( [[200, 720], [1100, 720], [595, 450], [685, 450]]) dst = np.float32( [[300, 720], [980, 720], [300, 0], [980, 0]]) m = cv2.getPerspectiveTransform(src, dst) m_inv = cv2.getPerspectiveTransform(dst, src) warped = cv2.warpPerspective(img, m, img_size, flags=cv2.INTER_LINEAR) unwarped = cv2.warpPerspective(warped, m_inv, (warped.shape[1], warped.shape[0]), flags=cv2.INTER_LINEAR) # DEBUG if verbose: f, axarray = plt.subplots(1, 2) f.set_facecolor('white') axarray[0].set_title('Before perspective transform') axarray[0].imshow(img, cmap='gray') for point in src: axarray[0].plot(*point, '.') axarray[1].set_title('After perspective transform') axarray[1].imshow(warped, cmap='gray') for point in dst: axarray[1].plot(*point, '.') for axis in axarray: axis.set_axis_off() plt.show() return warped, m, m_inv if __name__ == '__main__': with open('calibrate_camera.p', 'rb') as f: save_dict = pickle.load(f) mtx = save_dict['mtx'] dist = save_dict['dist'] # show result on test images for test_img in glob.glob('test_images/*.jpg'): img = cv2.imread(test_img) img_undistorted = undistort(img, mtx, dist, verbose=False) img_binary = binarize(img_undistorted, verbose=False) img_birdeye, M, Minv = perspective_transform(cv2.cvtColor(img_undistorted, cv2.COLOR_BGR2RGB), verbose=True)

29.114286

118

0.628557

c5681f32ba0443d6943fe18106423ebafc204c78

12,733

py

Python

epgrefresh/src/plugin.py

builder08/enigma2-plugins_2

f8f08b947e23c1c86b011492a7323125774c3482

[ "OLDAP-2.3" ]

null

epgrefresh/src/plugin.py

builder08/enigma2-plugins_2

f8f08b947e23c1c86b011492a7323125774c3482

[ "OLDAP-2.3" ]

null

epgrefresh/src/plugin.py

builder08/enigma2-plugins_2

f8f08b947e23c1c86b011492a7323125774c3482

[ "OLDAP-2.3" ]

null

from __future__ import print_function # for localized messages from . import _, NOTIFICATIONDOMAIN # Config from Components.config import config, ConfigYesNo, ConfigNumber, ConfigSelection, \ ConfigSubsection, ConfigClock, ConfigYesNo, ConfigInteger, NoSave from Screens.MessageBox import MessageBox from Screens.Standby import TryQuitMainloop from Tools.BoundFunction import boundFunction from boxbranding import getImageDistro from Components.SystemInfo import SystemInfo from Components.NimManager import nimmanager # Error-print from traceback import print_exc from sys import stdout # Calculate default begin/end from time import time, localtime, mktime now = localtime() begin = mktime(( now.tm_year, now.tm_mon, now.tm_mday, 07, 30, 0, now.tm_wday, now.tm_yday, now.tm_isdst) ) end = mktime(( now.tm_year, now.tm_mon, now.tm_mday, 20, 00, 0, now.tm_wday, now.tm_yday, now.tm_isdst) ) #Configuration config.plugins.epgrefresh = ConfigSubsection() config.plugins.epgrefresh.enabled = ConfigYesNo(default=False) config.plugins.epgrefresh.begin = ConfigClock(default=int(begin)) config.plugins.epgrefresh.end = ConfigClock(default=int(end)) config.plugins.epgrefresh.interval_seconds = ConfigNumber(default=120) config.plugins.epgrefresh.delay_standby = ConfigNumber(default=10) config.plugins.epgrefresh.inherit_autotimer = ConfigYesNo(default=False) config.plugins.epgrefresh.afterevent = ConfigYesNo(default=False) config.plugins.epgrefresh.force = ConfigYesNo(default=False) config.plugins.epgrefresh.skipProtectedServices = ConfigSelection(choices=[ ("bg_only", _("Background only")), ("always", _("Foreground also")), ], default="bg_only" ) config.plugins.epgrefresh.enablemessage = ConfigYesNo(default=True) config.plugins.epgrefresh.wakeup = ConfigYesNo(default=False) config.plugins.epgrefresh.lastscan = ConfigNumber(default=0) config.plugins.epgrefresh.parse_autotimer = ConfigSelection(choices=[ ("always", _("Yes")), ("never", _("No")), ("bg_only", _("Background only")), ("ask_yes", _("Ask default Yes")), ("ask_no", _("Ask default No")), ], default="never" ) config.plugins.epgrefresh.erase = ConfigYesNo(default=False) adapter_choices = [("main", _("Main Picture"))] if SystemInfo.get("NumVideoDecoders", 1) > 1: adapter_choices.append(("pip", _("Picture in Picture"))) adapter_choices.append(("pip_hidden", _("Picture in Picture (hidden)"))) if len(nimmanager.nim_slots) > 1: adapter_choices.append(("record", _("Fake recording"))) config.plugins.epgrefresh.adapter = ConfigSelection(choices=adapter_choices, default="main") config.plugins.epgrefresh.show_in_extensionsmenu = ConfigYesNo(default=False) config.plugins.epgrefresh.show_run_in_extensionsmenu = ConfigYesNo(default=True) if getImageDistro() in ("openatv", "openvix",): config.plugins.epgrefresh.show_in_plugins = ConfigYesNo(default=False) else: config.plugins.epgrefresh.show_in_plugins = ConfigYesNo(default=True) config.plugins.epgrefresh.show_help = ConfigYesNo(default=True) config.plugins.epgrefresh.wakeup_time = ConfigInteger(default=-1) config.plugins.epgrefresh.showadvancedoptions = NoSave(ConfigYesNo(default=False)) # convert previous parameters config.plugins.epgrefresh.background = ConfigYesNo(default=False) if config.plugins.epgrefresh.background.value: config.plugins.epgrefresh.adapter.value = "pip_hidden" config.plugins.epgrefresh.background.value = False config.plugins.epgrefresh.save() config.plugins.epgrefresh.interval = ConfigNumber(default=2) if config.plugins.epgrefresh.interval.value != 2: config.plugins.epgrefresh.interval_seconds.value = config.plugins.epgrefresh.interval.value * 60 config.plugins.epgrefresh.interval.value = 2 config.plugins.epgrefresh.save() #pragma mark - Help try: from Components.Language import language from Plugins.SystemPlugins.MPHelp import registerHelp, XMLHelpReader from Tools.Directories import resolveFilename, SCOPE_PLUGINS, fileExists lang = language.getLanguage()[:2] HELPPATH = resolveFilename(SCOPE_PLUGINS, "Extensions/EPGRefresh") if fileExists(HELPPATH + "/locale/" + str(lang) + "/mphelp.xml"): helpfile = HELPPATH + "/locale/" + str(lang) + "/mphelp.xml" else: helpfile = HELPPATH + "/mphelp.xml" reader = XMLHelpReader(helpfile) epgrefreshHelp = registerHelp(*reader) except Exception as e: print("[EPGRefresh] Unable to initialize MPHelp:", e, "- Help not available!") epgrefreshHelp = None #pragma mark - # Notification-Domain # Q: Do we really need this or can we do this better? from Tools import Notifications try: Notifications.notificationQueue.registerDomain(NOTIFICATIONDOMAIN, _("EPGREFRESH_NOTIFICATION_DOMAIN"), deferred_callable=True) except Exception as e: EPGRefreshNotificationKey = "" #print("[EPGRefresh] Error registering Notification-Domain:", e) # Plugin from EPGRefresh import epgrefresh from EPGRefreshService import EPGRefreshService # Plugins from Components.PluginComponent import plugins from Plugins.Plugin import PluginDescriptor #pragma mark - Workaround for unset clock from enigma import eDVBLocalTimeHandler def timeCallback(isCallback=True): """Time Callback/Autostart management.""" thInstance = eDVBLocalTimeHandler.getInstance() if isCallback: # NOTE: this assumes the clock is actually ready when called back # this may not be true, but we prefer silently dying to waiting forever thInstance.m_timeUpdated.get().remove(timeCallback) elif not thInstance.ready(): thInstance.m_timeUpdated.get().append(timeCallback) return epgrefresh.start() # Autostart # Mainfunction # Eventinfo # XXX: we need this helper function to identify the descriptor # Extensions menu extSetupDescriptor = PluginDescriptor(_("EPG-Refresh_SetUp"), description=_("Automatically refresh EPG"), where=PluginDescriptor.WHERE_EXTENSIONSMENU, fnc=extensionsmenu, needsRestart=False) extRunDescriptor = PluginDescriptor(_("EPG-Refresh_Refresh now"), description=_("Start EPGrefresh immediately"), where=PluginDescriptor.WHERE_EXTENSIONSMENU, fnc=forceRefresh, needsRestart=False) extStopDescriptor = PluginDescriptor(_("EPG-Refresh_Stop Refresh"), description=_("Stop Running EPG-refresh"), where=PluginDescriptor.WHERE_EXTENSIONSMENU, fnc=stopRunningRefresh, needsRestart=False) extPendingServDescriptor = PluginDescriptor(_("EPG-Refresh_Pending Services"), description=_("Show the pending Services for refresh"), where=PluginDescriptor.WHERE_EXTENSIONSMENU, fnc=showPendingServices, needsRestart=False) extPluginDescriptor = PluginDescriptor( name=_("EPGRefresh"), description=_("Automatically refresh EPG"), where=PluginDescriptor.WHERE_PLUGINMENU, fnc=main, icon="EPGRefresh.png", needsRestart=False) config.plugins.epgrefresh.show_in_plugins.addNotifier(housekeepingExtensionsmenu, initial_call=False, immediate_feedback=True) config.plugins.epgrefresh.show_in_extensionsmenu.addNotifier(housekeepingExtensionsmenu, initial_call=False, immediate_feedback=True) config.plugins.epgrefresh.show_run_in_extensionsmenu.addNotifier(housekeepingExtensionsmenu, initial_call=False, immediate_feedback=True)

35.766854

224

0.783162

c56a7f8daf694ac42476f66c3d71841a3dd5c679

29,709

py

Python

ongoing/prescriptors/bandit/bandit_prescriptor.py

bradyneal/covid-xprize-comp

d515f58b009a0a3e2421bc83e7ac893f3c3a1ece

[ "Apache-2.0" ]

null

ongoing/prescriptors/bandit/bandit_prescriptor.py

bradyneal/covid-xprize-comp

d515f58b009a0a3e2421bc83e7ac893f3c3a1ece

[ "Apache-2.0" ]

null

ongoing/prescriptors/bandit/bandit_prescriptor.py

bradyneal/covid-xprize-comp

d515f58b009a0a3e2421bc83e7ac893f3c3a1ece

[ "Apache-2.0" ]

null

import numpy as np import pandas as pd import os from copy import deepcopy import datetime import pickle import time import copy os.system('export PYTHONPATH="$(pwd):$PYTHONPATH"') from ongoing.prescriptors.base import BasePrescriptor, PRED_CASES_COL, CASES_COL, NPI_COLUMNS, NPI_MAX_VALUES import ongoing.prescriptors.base as base from bandit import CCTSB # np.warnings.filterwarnings('error', category=np.VisibleDeprecationWarning) ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) TMP_PRED_FILE_NAME = os.path.join(ROOT_DIR, 'tmp_predictions_for_prescriptions', 'preds.csv') TMP_PRESCRIPTION_FILE = os.path.join(ROOT_DIR, 'tmp_prescription.csv') MODEL_FILE = os.path.join(ROOT_DIR, 'bandits.pkl') # Number of iterations of training for the bandit. # Each iteration presents the bandit with a new context. # Each iteration trains the bandit for the entire prediction window. NB_ITERATIONS = 2 EXPLORE_ITERATIONS = 1 CHOICE = 'fixed' # Number of days the prescriptors will look at in the past. # Larger values here may make convergence slower, but give # prescriptors more context. The number of inputs of each neat # network will be NB_LOOKBACK_DAYS * (NPI_COLUMNS + 1) + NPI_COLUMNS. # The '1' is for previous case data, and the final NPI_COLUMNS # is for IP cost information. # NB_LOOKBACK_DAYS = 14 # Number of countries to use for training. Again, lower numbers # here will make training faster, since there will be fewer # input variables, but could potentially miss out on useful info. # NB_EVAL_COUNTRIES = 10 # Range of days the prescriptors will be evaluated on. # To save time during training, this range may be significantly # shorter than the maximum days a prescriptor can be evaluated on. # EVAL_START_DATE = '2020-08-01' # EVAL_END_DATE = '2020-08-02' # Number of prescriptions to make per country. # This can be set based on how many solutions in PRESCRIPTORS_FILE # we want to run and on time constraints. NB_PRESCRIPTIONS = 10 # OBJECTIVE_WEIGHTS = [0.01, 0.1, 0.2, 0.3, 0.4, 0.6, 0.7, 0.8, 0.9, 0.99] OBJECTIVE_WEIGHTS = [0.5, 1.0] LOAD = True if __name__ == '__main__': prescriptor = Bandit(seed=42) output_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), os.pardir, os.pardir, os.pardir, 'prescriptions') ofile_path = os.path.abspath(os.path.join(output_dir, 'bandit_evaluate.csv')) print(ofile_path) print() prescriptor.evaluate(output_file_path=ofile_path)

46.492958

188

0.586321

c56aa8051395c03cfefdb6b4c31ba197b3b0d2c8

1,876

py

Python

examples/server.py

zaibon/tcprouter

7e9d2590e1b1d9d984ac742bd82fcbcf3d42b3ef

[ "BSD-3-Clause" ]

5

2019-05-30T23:36:05.000Z

2019-10-10T21:37:53.000Z

examples/server.py

zaibon/tcprouter

7e9d2590e1b1d9d984ac742bd82fcbcf3d42b3ef

[ "BSD-3-Clause" ]

7

2019-06-12T11:55:46.000Z

2019-11-18T22:53:06.000Z

examples/server.py

xmonader/eltcprouter

b3435733d102c2435e9f62aa469d34c475cc31bd

[ "BSD-3-Clause" ]

1

2021-01-05T20:09:51.000Z

from gevent import monkey; monkey.patch_all() import logging from gevent.server import StreamServer logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def Handler(receiver_class): """ A basic connection handler that applies a receiver object to each connection. """ return handle server = StreamServer(('0.0.0.0', 9092), Handler(EchoReceiver), keyfile='server.key', certfile='server.crt') logger.info('Server running') server.serve_forever()

25.351351

108

0.601812

c56c42d080d6ecfdd85da2bc93ed1de36bb3b713

9,289

py

Python

starter.py

device42/DOQL_scripts_examples

55cdf3868768cb4f609011575b1051d7a69c19c5

[ "Apache-2.0" ]

7

2017-10-25T13:54:18.000Z

2022-01-25T16:16:53.000Z

starter.py

RomanNyschuk/DOQL_scripts_examples

1ec20426dcbe586c9b93ec77002a048c6563dca6

[ "Apache-2.0" ]

2

2018-11-19T18:17:35.000Z

2020-10-09T19:38:53.000Z

starter.py

RomanNyschuk/DOQL_scripts_examples

1ec20426dcbe586c9b93ec77002a048c6563dca6

[ "Apache-2.0" ]

6

2018-10-18T14:39:08.000Z

2021-04-15T19:06:01.000Z

# encoding: utf-8 import os import ssl import sys import csv import json import time import base64 from datetime import datetime from datetime import timedelta try: import pyodbc except ImportError: pass # PYTHON 2 FALLBACK # try: from urllib.request import urlopen, Request from urllib.parse import urlencode from io import StringIO python = 3 except ImportError: from urllib import urlencode from urllib2 import urlopen, Request from StringIO import StringIO reload(sys) sys.setdefaultencoding('utf8') python = 2 # PYTHON 2 FALLBACK # ctx = ssl.create_default_context() ctx.check_hostname = False ctx.verify_mode = ssl.CERT_NONE global _debug _debug = True if __name__ == "__main__": if len(sys.argv) < 2: print('Please use "python starter.py query.json".') sys.exit() main() print('Done!') sys.exit()

34.531599

262

0.518247

c56c7f75c3a3c13e0936e45885df9754bb813e14

5,001

py

Python

docs/conf.py

donatelli01/donatelli_documentations

6bf851014a96cd54c16d7d56b5677b081ca0d4e3

[ "CC-BY-4.0" ]

null

docs/conf.py

donatelli01/donatelli_documentations

6bf851014a96cd54c16d7d56b5677b081ca0d4e3

[ "CC-BY-4.0" ]

null

docs/conf.py

donatelli01/donatelli_documentations

6bf851014a96cd54c16d7d56b5677b081ca0d4e3

[ "CC-BY-4.0" ]

null

# -*- coding: utf-8 -*- import sys, os sys.path.insert(0, os.path.abspath('extensions')) extensions = ['sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.todo', 'sphinx.ext.coverage', 'sphinx.ext.pngmath', 'sphinx.ext.ifconfig', 'epub2', 'mobi', 'autoimage', 'code_example'] todo_include_todos = True templates_path = ['_templates'] source_suffix = '.rst' master_doc = 'index' exclude_patterns = [] add_function_parentheses = True #add_module_names = True # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] project = u'Music for Geeks and Nerds' copyright = u'2012, Pedro Kroger' version = '' release = '' # -- Options for HTML output --------------------------------------------------- html_theme = 'book' html_theme_path = ['themes'] html_title = "Music for Geeks and Nerds" #html_short_title = None #html_logo = None #html_favicon = None html_static_path = ['_static'] html_domain_indices = False html_use_index = False html_show_sphinx = False htmlhelp_basename = 'MusicforGeeksandNerdsdoc' html_show_sourcelink = False # -- Options for LaTeX output -------------------------------------------------- latex_elements = { 'papersize': '', 'fontpkg': '', 'fncychap': '', 'maketitle': '\\cover', 'pointsize': '', 'preamble': '', 'releasename': "", 'babel': '', 'printindex': '', 'fontenc': '', 'inputenc': '', 'classoptions': '', 'utf8extra': '', } latex_additional_files = ["mfgan-bw.sty", "mfgan.sty", "_static/cover.png"] latex_documents = [ ('index', 'music-for-geeks-and-nerds.tex', u'Music for Geeks and Nerds', u'Pedro Kroger', 'manual'), ] latex_show_pagerefs = False latex_domain_indices = False latex_use_modindex = False #latex_logo = None #latex_show_urls = False # -- Options for Epub output --------------------------------------------------- epub_title = u'Music for Geeks and Nerds' epub_author = u'Pedro Kroger' epub_publisher = u'Pedro Kroger' epub_copyright = u'2012, Pedro Kroger' epub_theme = 'epub2' # The scheme of the identifier. Typical schemes are ISBN or URL. #epub_scheme = '' # The unique identifier of the text. This can be a ISBN number # or the project homepage. #epub_identifier = '' # A unique identification for the text. #epub_uid = '' # A tuple containing the cover image and cover page html template filenames. epub_cover = ("_static/cover.png", "epub-cover.html") # HTML files that should be inserted before the pages created by sphinx. # The format is a list of tuples containing the path and title. #epub_pre_files = [] # HTML files shat should be inserted after the pages created by sphinx. # The format is a list of tuples containing the path and title. #epub_post_files = [] # A list of files that should not be packed into the epub file. epub_exclude_files = ['_static/opensearch.xml', '_static/doctools.js', '_static/jquery.js', '_static/searchtools.js', '_static/underscore.js', '_static/basic.css', 'search.html', '_static/websupport.js'] # The depth of the table of contents in toc.ncx. epub_tocdepth = 2 # Allow duplicate toc entries. epub_tocdup = False # -- Options for Mobi output --------------------------------------------------- mobi_theme = "mobi" mobi_title = u'Music for Geeks and Nerds' mobi_author = u'Pedro Kroger' mobi_publisher = u'Pedro Kroger' mobi_copyright = u'2012, Pedro Kroger' # The scheme of the identifier. Typical schemes are ISBN or URL. #mobi_scheme = '' # The unique identifier of the text. This can be a ISBN number # or the project homepage. #mobi_identifier = '' # A unique identification for the text. #mobi_uid = '' mobi_cover = "_static/cover.png" # HTML files that should be inserted before the pages created by sphinx. # The format is a list of tuples containing the path and title. #mobi_pre_files = [] # HTML files shat should be inserted after the pages created by sphinx. # The format is a list of tuples containing the path and title. #mobi_post_files = [] # A list of files that should not be packed into the mobi file. mobi_exclude_files = ['_static/opensearch.xml', '_static/doctools.js', '_static/jquery.js', '_static/searchtools.js', '_static/underscore.js', '_static/basic.css', 'search.html', '_static/websupport.js'] # The depth of the table of contents in toc.ncx. mobi_tocdepth = 2 # Allow duplicate toc entries. mobi_tocdup = False mobi_add_visible_links = False # -- Options for Code Examples output --------------------------------------------------- code_example_dir = "code-example" code_add_python_path = ["../py"] ################################################################################

28.577143

89

0.642072

c56cd8896de2c6a2a8be34144a21660a056501d9

17,031

py

Python

sapphire/simulation.py

alexanderzimmerman/sapphire

1236000d201b8ff44296b0428ef31e5ff0e6078f

[ "MIT" ]

10

2019-04-26T16:23:49.000Z

2022-02-01T22:44:29.000Z

sapphire/simulation.py

alexanderzimmerman/sapphire

1236000d201b8ff44296b0428ef31e5ff0e6078f

[ "MIT" ]

35

2018-12-10T08:55:59.000Z

2019-03-21T10:48:57.000Z

sapphire/simulation.py

alexanderzimmerman/sapphire

1236000d201b8ff44296b0428ef31e5ff0e6078f

[ "MIT" ]

4

2019-04-11T16:49:48.000Z

2021-03-15T00:58:09.000Z

"""Provides a class for constructing simulations based on Firedrake. Simulations proceed forward in time by solving a sequence of Initial Boundary Values Problems (IBVP's). Using the Firedrake framework, the PDE's are discretized in space with Finite Elements (FE). The symbolic capabilities of Firedrake are used to automatically implement backward difference formula (BDF) time discretizations and to automatically linearize nonlinear problems with Newton's method. Nonlinear and linear solvers are provided by PETSc and are accessed via the Firedrake interface. This module imports `firedrake` as `fe` and its documentation writes `fe` instead of `firedrake`. """ import typing import pathlib import ufl import firedrake as fe import sapphire.time_discretization import sapphire.output def unit_vectors(mesh) -> typing.Tuple[ufl.tensors.ListTensor]: """Returns the mesh's spatial unit vectors in each dimension. Args: mesh (fe.Mesh): The mesh for the spatial discretization. """ dim = mesh.geometric_dimension() return tuple([fe.unit_vector(i, dim) for i in range(dim)]) def time_discrete_terms( solutions: typing.List[fe.Function], timestep_size: fe.Constant) \ -> typing.Union[ ufl.core.operator.Operator, typing.List[ufl.core.operator.Operator]]: """Returns backward difference time discretization. The backward difference formula's stencil size is determine by the number of solutions provided, i.e. `len(solutions)`. For example, if `len(solutions == 3)`, then the second-order BDF2 method will be used, because it involves solutions at three discrete times. The return type depends on whether or not the solution is based on a mixed finite element. For mixed finite elements, a list of time discrete terms will be returned, each item corresponding to one of the sub-elements of the mixed element. Otherwise, a single term will be returned. """ """ The return type design choice was made, rather than always returning a list (e.g. with only one item if not using a mixed element), so that it would be more intuitive when not using mixed elements. """ """ This implementation assumes constant time step size. Variable time step sizes change the BDF formula for all except first order. """ time_discrete_terms = [ sapphire.time_discretization.bdf( [fe.split(solutions[n])[i] for n in range(len(solutions))], timestep_size = timestep_size) for i in range(len(solutions[0].split()))] return time_discrete_terms

36.391026

86

0.575245

c56d0b93bb067141c9ac8d852c7ba2ad1f8b703b

16,389

py

Python

lookmlint/lookmlint.py

kingfink/lookmlint

5fd76328b3ad6917e649a28abed05f64707422b6

[ "Apache-2.0" ]

null

lookmlint/lookmlint.py

kingfink/lookmlint

5fd76328b3ad6917e649a28abed05f64707422b6

[ "Apache-2.0" ]

1

2020-02-25T16:01:31.000Z

lookmlint/lookmlint.py

kingfink/lookmlint

5fd76328b3ad6917e649a28abed05f64707422b6

[ "Apache-2.0" ]

null

from collections import Counter import json import os import re import subprocess import attr import yaml def read_lint_config(repo_path): # read .lintconfig.yml full_path = os.path.expanduser(repo_path) config_filepath = os.path.join(full_path, '.lintconfig.yml') acronyms = [] abbreviations = [] if os.path.isfile(config_filepath): with open(config_filepath) as f: config = yaml.load(f) acronyms = config.get('acronyms', acronyms) abbreviations = config.get('abbreviations', abbreviations) lint_config = {'acronyms': acronyms, 'abbreviations': abbreviations} return lint_config def parse_repo(full_path): cmd = ( f'cd {full_path} && ' 'lookml-parser --input="*.lkml" --whitespace=2 > /tmp/lookmlint.json' ) process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE) output, error = process.communicate() def lookml_from_repo_path(repo_path): full_path = os.path.expanduser(repo_path) parse_repo(full_path) lkml = LookML('/tmp/lookmlint.json') return lkml def label_issues(label, acronyms=[], abbreviations=[]): acronyms_used = [ a.upper() for a in acronyms if _contains_bad_acronym_usage(label, a) ] abbreviations_used = [ a.title() for a in abbreviations if _contains_bad_abbreviation_usage(label, a) ] return acronyms_used + abbreviations_used def lint_labels(lkml, acronyms, abbreviations): # check for acronym and abbreviation issues explore_label_issues = {} for m in lkml.models: issues = m.explore_label_issues(acronyms, abbreviations) if issues != {}: explore_label_issues[m.name] = issues explore_view_label_issues = {} for m in lkml.models: for e in m.explores: issues = e.view_label_issues(acronyms, abbreviations) if issues != {}: if m.name not in explore_view_label_issues: explore_view_label_issues[m.name] = {} explore_view_label_issues[m.name][e.name] = issues field_label_issues = {} for v in lkml.views: issues = v.field_label_issues(acronyms, abbreviations) if issues != {}: field_label_issues[v.name] = issues # create overall labels issues dict label_issues = {} if explore_label_issues != {}: label_issues['explores'] = explore_label_issues if explore_view_label_issues != {}: label_issues['explore_views'] = explore_view_label_issues if field_label_issues != {}: label_issues['fields'] = field_label_issues return label_issues def lint_duplicate_view_labels(lkml): issues = {} for m in lkml.models: for e in m.explores: dupes = e.duplicated_view_labels() if dupes == {}: continue if m.name not in issues: issues[m.name] = {} if e.name not in issues[m.name]: issues[m.name][e.name] = dupes return issues def lint_sql_references(lkml): # check for raw SQL field references raw_sql_refs = {} for m in lkml.models: for e in m.explores: for v in e.views: if not v.contains_raw_sql_ref(): continue if m.name not in raw_sql_refs: raw_sql_refs[m.name] = {} if e.name not in raw_sql_refs[m.name]: raw_sql_refs[m.name][e.name] = {} raw_sql_refs[m.name][e.name][v.name] = v.sql_on return raw_sql_refs def lint_view_primary_keys(lkml): # check for missing primary keys views_missing_primary_keys = [v.name for v in lkml.views if not v.has_primary_key()] return views_missing_primary_keys def lint_missing_drill_fields(lkml): # check for measures missing drill fields measures_missing_drill_fields = [] for v in lkml.views: measures_missing_drill_fields += [(v.name, m.name) for m in v.measures if not m.has_drill_fields()] return sorted(list(set(measures_missing_drill_fields))) def lint_unused_includes(lkml): # check for unused includes unused_includes = { m.name: m.unused_includes() for m in lkml.models if m.unused_includes() != [] } return unused_includes def lint_unused_view_files(lkml): # check for unused view files unused_view_files = lkml.unused_view_files() return unused_view_files def lint_missing_view_sql_definitions(lkml): return [ v.name for v in lkml.views if not v.has_sql_definition() and v.extends == [] and any(f.sql and '${TABLE}' in f.sql for f in v.fields) ] def lint_semicolons_in_derived_table_sql(lkml): return [v.name for v in lkml.views if v.derived_table_contains_semicolon()] def lint_select_star_in_derived_table_sql(lkml): return [v.name for v in lkml.views if v.derived_table_contains_select_star()] def lint_mismatched_view_names(lkml): return lkml.mismatched_view_names()

34.430672

175

0.626945

c56d395d346db6cdbf6e9c0543fb7e6ccd0a31e0

4,306

py

Python

book-code/numpy-ml/numpy_ml/utils/testing.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

null

book-code/numpy-ml/numpy_ml/utils/testing.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

null

book-code/numpy-ml/numpy_ml/utils/testing.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

null

"""Utilities for writing unit tests""" import numbers import numpy as np ####################################################################### # Assertions # ####################################################################### def is_symmetric(X): """Check that an array `X` is symmetric along its main diagonal""" return np.allclose(X, X.T) def is_symmetric_positive_definite(X): """Check that a matrix `X` is a symmetric and positive-definite.""" if is_symmetric(X): try: # if matrix is symmetric, check whether the Cholesky decomposition # (defined only for symmetric/Hermitian positive definite matrices) # exists np.linalg.cholesky(X) return True except np.linalg.LinAlgError: return False return False def is_stochastic(X): """True if `X` contains probabilities that sum to 1 along the columns""" msg = "Array should be stochastic along the columns" assert len(X[X < 0]) == len(X[X > 1]) == 0, msg assert np.allclose(np.sum(X, axis=1), np.ones(X.shape[0])), msg return True def is_number(a): """Check that a value `a` is numeric""" return isinstance(a, numbers.Number) def is_one_hot(x): """Return True if array `x` is a binary array with a single 1""" msg = "Matrix should be one-hot binary" assert np.array_equal(x, x.astype(bool)), msg assert np.allclose(np.sum(x, axis=1), np.ones(x.shape[0])), msg return True def is_binary(x): """Return True if array `x` consists only of binary values""" msg = "Matrix must be binary" assert np.array_equal(x, x.astype(bool)), msg return True ####################################################################### # Data Generators # ####################################################################### def random_one_hot_matrix(n_examples, n_classes): """Create a random one-hot matrix of shape (`n_examples`, `n_classes`)""" X = np.eye(n_classes) X = X[np.random.choice(n_classes, n_examples)] return X def random_stochastic_matrix(n_examples, n_classes): """Create a random stochastic matrix of shape (`n_examples`, `n_classes`)""" X = np.random.rand(n_examples, n_classes) X /= X.sum(axis=1, keepdims=True) return X def random_tensor(shape, standardize=False): """ Create a random real-valued tensor of shape `shape`. If `standardize` is True, ensure each column has mean 0 and std 1. """ offset = np.random.randint(-300, 300, shape) X = np.random.rand(*shape) + offset if standardize: eps = np.finfo(float).eps X = (X - X.mean(axis=0)) / (X.std(axis=0) + eps) return X def random_binary_tensor(shape, sparsity=0.5): """ Create a random binary tensor of shape `shape`. `sparsity` is a value between 0 and 1 controlling the ratio of 0s to 1s in the output tensor. """ return (np.random.rand(*shape) >= (1 - sparsity)).astype(float) def random_paragraph(n_words, vocab=None): """ Generate a random paragraph consisting of `n_words` words. If `vocab` is not None, words will be drawn at random from this list. Otherwise, words will be sampled uniformly from a collection of 26 Latin words. """ if vocab is None: vocab = [ "at", "stet", "accusam", "aliquyam", "clita", "lorem", "ipsum", "dolor", "dolore", "dolores", "sit", "amet", "consetetur", "sadipscing", "elitr", "sed", "diam", "nonumy", "eirmod", "duo", "ea", "eos", "erat", "est", "et", "gubergren", ] return [np.random.choice(vocab) for _ in range(n_words)] ####################################################################### # Custom Warnings # #######################################################################

29.902778

80

0.510683

c56da321682df09ceea1c41371b833fb49044e9e

1,373

py

Python

test/test_googleoauth2.py

GallopLabs/libsaas

80b2d51b81a769eacafc3847cc33700ac80e66fc

[ "MIT" ]

null

test/test_googleoauth2.py

GallopLabs/libsaas

80b2d51b81a769eacafc3847cc33700ac80e66fc

[ "MIT" ]

null

test/test_googleoauth2.py

GallopLabs/libsaas

80b2d51b81a769eacafc3847cc33700ac80e66fc

[ "MIT" ]

null

import unittest from libsaas.executors import test_executor from libsaas.services import googleoauth2

32.690476

66

0.584122

c56df3f7bc34ea2a6465e6d328eeae9b03525f21

5,654

py

Python

post_office/migrations/0001_initial.py

carrerasrodrigo/django-post_office

0257a39f9f2d20c1a42c58e8fd4dfaf591221132

[ "MIT" ]

null

post_office/migrations/0001_initial.py

carrerasrodrigo/django-post_office

0257a39f9f2d20c1a42c58e8fd4dfaf591221132

[ "MIT" ]

null

post_office/migrations/0001_initial.py

carrerasrodrigo/django-post_office

0257a39f9f2d20c1a42c58e8fd4dfaf591221132

[ "MIT" ]

null

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

49.596491

155

0.583658

c56e81e80b9caed3db5600ddbb8cc958f425902d

3,890

py

Python

ic_gan/data_utils/store_kmeans_indexes.py

ozcelikfu/IC-GAN_fMRI_Reconstruction

31b0dc7659afbf8d12b1e460a38ab6d8d9a4296c

[ "MIT" ]

null

ic_gan/data_utils/store_kmeans_indexes.py

ozcelikfu/IC-GAN_fMRI_Reconstruction

31b0dc7659afbf8d12b1e460a38ab6d8d9a4296c

[ "MIT" ]

null

ic_gan/data_utils/store_kmeans_indexes.py

ozcelikfu/IC-GAN_fMRI_Reconstruction

31b0dc7659afbf8d12b1e460a38ab6d8d9a4296c

[ "MIT" ]

null

# Copyright (c) Facebook, Inc. and its affiliates. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. """Store dataset indexes of datapoints selected by k-means algorithm.""" from argparse import ArgumentParser import numpy as np import os import h5py as h5 import faiss if __name__ == "__main__": parser = ArgumentParser( description="Storing cluster indexes for k-means-based data subsampling" ) parser.add_argument( "--resolution", type=int, default=64, help="Data resolution (default: %(default)s)", ) parser.add_argument( "--which_dataset", type=str, default="imagenet", help="Dataset choice." ) parser.add_argument( "--data_root", type=str, default="data", help="Default location where data is stored (default: %(default)s)", ) parser.add_argument( "--feature_extractor", type=str, default="classification", choices=["classification", "selfsupervised"], help="Choice of feature extractor", ) parser.add_argument( "--backbone_feature_extractor", type=str, default="resnet50", choices=["resnet50"], help="Choice of feature extractor backbone", ) parser.add_argument( "--kmeans_subsampled", type=int, default=-1, help="Number of k-means centers if using subsampled training instances" " (default: %(default)s)", ) parser.add_argument( "--gpu", action="store_true", default=False, help="Use faiss with GPUs (default: %(default)s)", ) args = vars(parser.parse_args()) main(args)

29.029851

100

0.607198

c570fd6a05953760ae560c4fbed0f8ac9f2fd02d

100

py

Python

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

from cattr.errors import StructureHandlerNotFoundError __all__ = ["StructureHandlerNotFoundError"]

25

54

0.86

c5744b17de40e44fcacba60862bc64a6577cf8bb

4,873

py

Python

plugins/funcs.py

prxpostern/URLtoTG003

b41ef5e756193798d8f92ccaa55c0fd7ab5ef931

[ "MIT" ]

null

plugins/funcs.py

prxpostern/URLtoTG003

b41ef5e756193798d8f92ccaa55c0fd7ab5ef931

[ "MIT" ]

null

plugins/funcs.py

prxpostern/URLtoTG003

b41ef5e756193798d8f92ccaa55c0fd7ab5ef931

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from main import Config from pyrogram import filters from pyrogram import Client #from pyrogram.types import InlineKeyboardMarkup, InlineKeyboardButton from urllib.parse import quote_plus, unquote import math, os, time, datetime, aiohttp, asyncio, mimetypes, logging from helpers.download_from_url import download_file, get_size from helpers.file_handler import send_to_transfersh_async, progress from hachoir.parser import createParser from hachoir.metadata import extractMetadata from helpers.display_progress import progress_for_pyrogram, humanbytes from helpers.tools import execute from helpers.ffprobe import stream_creator from helpers.thumbnail_video import thumb_creator from helpers.url_uploader import leecher2 from helpers.video_renamer import rnv2 from helpers.audio_renamer import rna2 from helpers.file_renamer import rnf2 from helpers.vconverter import to_video2 from helpers.media_info import cinfo2 from helpers.link_info import linfo2 logger = logging.getLogger(__name__) HELP_TXT = """ A Simple Telegram Bot to Upload Files From **Direct** and **Google Drive** and **Youtube** Links, Convert Document Media to Video, and Rename Audio/Video/Document Files. /upload : reply to your url . `http://aaa.bbb.ccc/ddd.eee` | **fff.ggg** or `http://aaa.bbb.ccc/ddd.eee` /c2v : reply to your document to convert it into streamable video. /rnv : reply to your video. Example: `/rnv | videoname` /rna : reply to your audio. \"`-`\" : leave without change. `/rna | audioname | title | artists` `/rna | audioname` `/rna | - | title` `/rna | - | - | artists` /rnf : reply to your document. Example: `/rnf | filename.ext` """

36.916667

195

0.692592

c574ba0d5085fcc10f94dc14bafe60401b5587a7

2,304

py

Python

git_code_debt/repo_parser.py

cclauss/git-code-debt

6ced089857d3ccda4a00d274e85d7f26de0bdefd

[ "MIT" ]

null

git_code_debt/repo_parser.py

cclauss/git-code-debt

6ced089857d3ccda4a00d274e85d7f26de0bdefd

[ "MIT" ]

null

git_code_debt/repo_parser.py

cclauss/git-code-debt

6ced089857d3ccda4a00d274e85d7f26de0bdefd

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import unicode_literals import collections import contextlib import shutil import subprocess import tempfile from git_code_debt.util.iter import chunk_iter from git_code_debt.util.subprocess import cmd_output Commit = collections.namedtuple('Commit', ('sha', 'date')) Commit.blank = Commit('0' * 40, 0) COMMIT_FORMAT = '--format=%H%n%ct'

26.790698

74

0.588542

c574d6290b0c40bcbc5696cd5ebb36152641b976

215

py

Python

func_one.py

FoxProklya/Step-Python

67514509655e552fc5adcc7963b971ef6f0bb46a

[ "MIT" ]

null

func_one.py

FoxProklya/Step-Python

67514509655e552fc5adcc7963b971ef6f0bb46a

[ "MIT" ]

null

func_one.py

FoxProklya/Step-Python

67514509655e552fc5adcc7963b971ef6f0bb46a

[ "MIT" ]

null

x = int(input()) print(f(x))

14.333333

26

0.316279

c576551072f708a32f1945826e72ae5d21285cce

2,605

py

Python

scripts/multiprocess_tokenizer/worker.py

talolard/vampire

e2ae46112fda237b072453c9f1c5e89bd7b4135b

[ "Apache-2.0" ]

null

scripts/multiprocess_tokenizer/worker.py

talolard/vampire

e2ae46112fda237b072453c9f1c5e89bd7b4135b

[ "Apache-2.0" ]

null

scripts/multiprocess_tokenizer/worker.py

talolard/vampire

e2ae46112fda237b072453c9f1c5e89bd7b4135b

[ "Apache-2.0" ]

null

import typing from typing import Any import json import os from multiprocessing import Process, Queue from allennlp.data.tokenizers.word_splitter import SpacyWordSplitter from spacy.tokenizer import Tokenizer import spacy from tqdm.auto import tqdm import time nlp = spacy.load("en")

28.315217

97

0.6119

c578aaaded2e7b75110f4c69848a9fb001f45ff0

5,823

py

Python

MC-Fisher.py

hosua/Minecraft-Fisher

416c476cd6e5ef0c6bb978aacd9816aa9ba36f7e

[ "MIT" ]

null

MC-Fisher.py

hosua/Minecraft-Fisher

416c476cd6e5ef0c6bb978aacd9816aa9ba36f7e

[ "MIT" ]

null

MC-Fisher.py

hosua/Minecraft-Fisher

416c476cd6e5ef0c6bb978aacd9816aa9ba36f7e

[ "MIT" ]

null

# For larger scale projects, I really should learn to use classes... lol from PIL import ImageGrab, ImageTk, Image import keyboard import pyautogui import tkinter as tk import os import time, datetime import text_redirect as TR import sys # GUI stuff TITLE = "Minecraft-Fisher - Made by Hoswoo" DARK_BLUE = '#0A3D62' LIGHT_BLUE = "#7ddeff" DARK_GREY = "#2C3335" CONSOLE_BG = '#A1AAB5' FONT_BIG = ('calibre', 12, 'bold') FONT = ('calibre', 10, 'bold') FONT_CONSOLE = ('Times', 10, 'normal') SIZE = ("400x500") root = tk.Tk() root.configure(bg=DARK_BLUE) root.title(TITLE) root.geometry(SIZE) root_dir = os.getcwd() # GUI Console console_frame = tk.Frame(root, bg=DARK_BLUE, height=250, width=200) console_sub_frame = tk.Frame(console_frame, bg=DARK_BLUE) console_text = tk.Text(root, height=12, width=60, bg=CONSOLE_BG, fg=DARK_GREY, font=FONT_CONSOLE) console_text.config(state="disabled") console_text.see("end") sys.stdout = TR.TextRedirector(console_text) # Send console output to textbox instead of actual console. # sys.stderr = TR.TextRedirector(console_text) # Errors will output in console print("PLEASE READ BEFORE USING:\n") print("The bot works by detecting a specific shade of red on the bobber. With that being said...") print("Before you use the bot, you should turn your brightness all the way up.") print("You will also have to map your right-mouse-click to 'r'. (This was a workaround due to the mouse input causing issues)") print("For best results, ensure you are in a very well lit area and that the fish bobber appears within your capture region!") print("NOTE: If your health hearts are in the capture region, it will falsely detect the bobber.") # Global constants BOBBER_COLOR = (208, 41, 41, 255) BOBBER_COLOR_NIGHT = (206, 40, 39, 255) region_var = tk.StringVar() region_var.set(300) # Default to 300, should work for most people. BOX_SIZE = int(region_var.get()) # get box size from spinbox FILENAME = "pic.png" x = 0 y = 0 region_label = tk.Label(root, text="Region size", bg=DARK_BLUE, fg=LIGHT_BLUE, font=FONT) region_spinbox = tk.Spinbox(root, from_=25, to=1000, increment=25, textvariable=region_var, width=6) range_validation = root.register(validate) region_spinbox.config(validate="key", validatecommand=(range_validation, '% P')) # Absolutely no idea how this works lol pic_frame = tk.Frame(root, bg="#FFFFFF", height=BOX_SIZE, width=BOX_SIZE) #img = ImageTk.PhotoImage(Image.open(FILENAME)) pic_frame_label = tk.Label(pic_frame) pic_frame_label.pack() pic_frame.pack() running = False times_not_detected = 0 start_btn = tk.Button(root, text="Start (~)", bg=DARK_GREY, fg=LIGHT_BLUE, command=start_task, width=10) stop_btn = tk.Button(root, text="Stop (F1)", bg=DARK_GREY, fg=LIGHT_BLUE, command=stop_task, width=10) region_label.pack() region_spinbox.pack() start_btn.pack() stop_btn.pack() console_frame.pack() console_sub_frame.pack() console_text.pack() keyboard.add_hotkey('`', start_task) keyboard.add_hotkey('F1', stop_task) root.mainloop()

34.052632

127

0.665636

3d63dfe6fe9f0bef4a7c9bfd9c4a5ff955fbcafe

1,248

py

Python

ModelAnalysis/biomodel_iterator.py

BioModelTools/ModelAnalysis

89d6426ec9fbbb6836897889266848793d109dcc

[ "MIT" ]

null

ModelAnalysis/biomodel_iterator.py

BioModelTools/ModelAnalysis

89d6426ec9fbbb6836897889266848793d109dcc

[ "MIT" ]

3

2017-09-04T20:06:45.000Z

2017-09-07T01:57:45.000Z

ModelAnalysis/biomodel_iterator.py

BioModelTools/ModelAnalysis

89d6426ec9fbbb6836897889266848793d109dcc

[ "MIT" ]

null

""" Iterates through a collection of BioModels """ from sbml_shim import SBMLShim import sys import os.path ################################################ # Classes that count pattern occurrences ################################################ if __name__ == '__main__': main(sys.argv)

25.469388

80

0.584936

3d640bec431e81affc07c61301d5e5f1d49c75e8

411

py

Python

app/domain/company/models.py

JBizarri/fast-api-crud

3eb0391c1a1f2e054092de717b73898c7efed5cb

[ "MIT" ]

null

app/domain/company/models.py

JBizarri/fast-api-crud

3eb0391c1a1f2e054092de717b73898c7efed5cb

[ "MIT" ]

null

app/domain/company/models.py

JBizarri/fast-api-crud

3eb0391c1a1f2e054092de717b73898c7efed5cb

[ "MIT" ]

null

from __future__ import annotations from typing import TYPE_CHECKING, List from sqlalchemy import Column, String from sqlalchemy.orm import relationship from ...database import BaseModel if TYPE_CHECKING: from ..user.models import User

20.55

63

0.737226

3d66a81186dceebace0295ecba9cdcb9533d8966

1,913

py

Python

tools/captcha_image_downloader.py

metormaon/signum-py

7c6eaf11025f77c4cfbe6fb9aa77b5dadb485d8c

[ "MIT" ]

null

tools/captcha_image_downloader.py

metormaon/signum-py

7c6eaf11025f77c4cfbe6fb9aa77b5dadb485d8c

[ "MIT" ]

1

2020-08-01T23:28:38.000Z

tools/captcha_image_downloader.py

metormaon/signum-py

7c6eaf11025f77c4cfbe6fb9aa77b5dadb485d8c

[ "MIT" ]

null

# -*- coding: utf-8 -*- from os import path from google_images_download import google_images_download for keyword in [ "dog", "cat", "bird", "elephant", "fork", "knife", "spoon", "carrot", "orange", "turnip", "tomato", "potato", "water", "hair", "table", "chair", "house", "factory", "microwave", "cigarette", "ashtray", "brush", "battery", "comb", "box", "book", "bag", "calendar", "computer", "lipstick", "pencil", "perfume", "telephone", "television", "headset", "angry", "apple", "armour", "baby", "bag", "ball", "bank", "basket", "bath", "bear", "bean", "bell", "blue", "bottle", "bread", "bridge", "bus", "cake", "candle", "car", "card", "cheese", "chicken", "chocolate", "circle", "clock", "cloud", "coffee", "coat", "coin", "cook", "corn", "cup", "dance", "deer", "desk", "door", "dress", "duck", "happy", "smile", "yellow", "ear", "earth", "mars", "saturn", "jupiter", "egg", "eight", "one", "two", "three", "four", "five", "six", "seven", "nine", "ten", "electricity", "piano", "guitar", "flute", "drum", "exit", "dark", "excited", "surprise", "eye", "nose", "mouth", "leg", "hand", "face", "family", "farm", "fat", "fear", "finger", "fire", "flag", "flower", "fly", "food", "football", "forest", "fox", "friend", "garden", "game", "gate" ]: if not path.exists("../captcha-images/" + keyword): response = google_images_download.googleimagesdownload() arguments = {"keywords": keyword, "limit": 15, "print_urls": True, "usage_rights": "labeled-for-reuse", "output_directory": "../captcha-images", "safe_search": True, "format": "jpg", "size": "medium" } paths = response.download(arguments) print(paths) else: print("Skipping " + keyword)

51.702703

119

0.526398

3d6b7691e8c5eed4e135eafd2eed629b0d7310de

4,752

py

Python

ott2butKAMA1/jessetkdata/dnafiles/BNB-USDT 2018-02-15 2021-01-01.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

38

2021-09-18T15:33:28.000Z

2022-02-21T17:29:08.000Z

ott2butKAMA1/jessetkdata/dnafiles/BNB-USDT 2018-02-15 2021-01-01.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

4

2022-01-02T14:46:12.000Z

2022-02-16T18:39:41.000Z

ott2butKAMA1/jessetkdata/dnafiles/BNB-USDT 2018-02-15 2021-01-01.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

11

2021-10-19T06:21:43.000Z

2022-02-21T17:29:10.000Z

dnas = [ ['jVXfX<', 37, 64, 24.67, 14, 7, -4.53, {'ott_len': 42, 'ott_percent': 508, 'stop_loss': 263, 'risk_reward': 65, 'chop_rsi_len': 31, 'chop_bandwidth': 83}], ['o:JK9p', 50, 62, 32.74, 37, 8, -0.2, {'ott_len': 45, 'ott_percent': 259, 'stop_loss': 201, 'risk_reward': 41, 'chop_rsi_len': 12, 'chop_bandwidth': 274}], ['tGVME/', 35, 74, 20.06, 20, 10, -4.75, {'ott_len': 48, 'ott_percent': 375, 'stop_loss': 254, 'risk_reward': 43, 'chop_rsi_len': 20, 'chop_bandwidth': 36}], ['a<<sMo', 59, 27, 25.74, 33, 6, -1.06, {'ott_len': 36, 'ott_percent': 277, 'stop_loss': 139, 'risk_reward': 76, 'chop_rsi_len': 24, 'chop_bandwidth': 271}], ['`Ol@gL', 29, 65, 9.47, 25, 8, -2.95, {'ott_len': 36, 'ott_percent': 446, 'stop_loss': 351, 'risk_reward': 31, 'chop_rsi_len': 40, 'chop_bandwidth': 142}], ['SWJi?Y', 36, 73, 32.8, 37, 8, -0.92, {'ott_len': 28, 'ott_percent': 516, 'stop_loss': 201, 'risk_reward': 68, 'chop_rsi_len': 16, 'chop_bandwidth': 190}], ['v@WLkU', 46, 47, 45.51, 20, 10, -4.43, {'ott_len': 49, 'ott_percent': 313, 'stop_loss': 258, 'risk_reward': 42, 'chop_rsi_len': 43, 'chop_bandwidth': 175}], ['lR\\iHN', 38, 62, 35.84, 28, 7, -4.01, {'ott_len': 43, 'ott_percent': 472, 'stop_loss': 280, 'risk_reward': 68, 'chop_rsi_len': 21, 'chop_bandwidth': 149}], ['l7\\gc^', 60, 35, 42.7, 25, 8, -1.2, {'ott_len': 43, 'ott_percent': 233, 'stop_loss': 280, 'risk_reward': 66, 'chop_rsi_len': 38, 'chop_bandwidth': 208}], ['wLXY\\1', 36, 71, 20.85, 14, 7, -4.76, {'ott_len': 50, 'ott_percent': 419, 'stop_loss': 263, 'risk_reward': 53, 'chop_rsi_len': 34, 'chop_bandwidth': 43}], ['i7nMgb', 54, 24, 28.38, 0, 4, -2.04, {'ott_len': 41, 'ott_percent': 233, 'stop_loss': 360, 'risk_reward': 43, 'chop_rsi_len': 40, 'chop_bandwidth': 223}], ['F/0eI[', 40, 154, 33.68, 42, 21, 2.91, {'ott_len': 20, 'ott_percent': 162, 'stop_loss': 85, 'risk_reward': 64, 'chop_rsi_len': 22, 'chop_bandwidth': 197}], ['\\ERgMp', 53, 28, 16.3, 33, 6, -2.59, {'ott_len': 33, 'ott_percent': 357, 'stop_loss': 236, 'risk_reward': 66, 'chop_rsi_len': 24, 'chop_bandwidth': 274}], ['_7@QqN', 44, 87, 28.24, 46, 15, 3.21, {'ott_len': 35, 'ott_percent': 233, 'stop_loss': 156, 'risk_reward': 46, 'chop_rsi_len': 46, 'chop_bandwidth': 149}], ['OEJO,F', 41, 105, 33.62, 20, 10, -4.61, {'ott_len': 25, 'ott_percent': 357, 'stop_loss': 201, 'risk_reward': 45, 'chop_rsi_len': 4, 'chop_bandwidth': 120}], ['5swn)a', 30, 86, 13.25, 8, 12, -6.03, {'ott_len': 9, 'ott_percent': 765, 'stop_loss': 400, 'risk_reward': 72, 'chop_rsi_len': 3, 'chop_bandwidth': 219}], ['4juD3[', 36, 95, 32.91, 14, 7, -3.13, {'ott_len': 8, 'ott_percent': 685, 'stop_loss': 391, 'risk_reward': 35, 'chop_rsi_len': 9, 'chop_bandwidth': 197}], ['91u6iJ', 33, 163, 31.1, 25, 27, -3.59, {'ott_len': 12, 'ott_percent': 180, 'stop_loss': 391, 'risk_reward': 22, 'chop_rsi_len': 41, 'chop_bandwidth': 135}], ['c3rg61', 39, 91, 11.05, 27, 11, -1.18, {'ott_len': 38, 'ott_percent': 197, 'stop_loss': 378, 'risk_reward': 66, 'chop_rsi_len': 11, 'chop_bandwidth': 43}], ['\\BAZGb', 40, 71, 22.33, 36, 11, -3.44, {'ott_len': 33, 'ott_percent': 330, 'stop_loss': 161, 'risk_reward': 54, 'chop_rsi_len': 21, 'chop_bandwidth': 223}], ['H<XF,l', 40, 98, 31.16, 16, 12, -5.22, {'ott_len': 21, 'ott_percent': 277, 'stop_loss': 263, 'risk_reward': 37, 'chop_rsi_len': 4, 'chop_bandwidth': 260}], ['5Bl/TL', 32, 153, 26.35, 28, 21, 0.03, {'ott_len': 9, 'ott_percent': 330, 'stop_loss': 351, 'risk_reward': 16, 'chop_rsi_len': 29, 'chop_bandwidth': 142}], ['DFRlX-', 38, 112, 21.16, 27, 11, -1.95, {'ott_len': 18, 'ott_percent': 366, 'stop_loss': 236, 'risk_reward': 70, 'chop_rsi_len': 31, 'chop_bandwidth': 28}], ['1EkquE', 33, 156, 45.58, 27, 18, -1.61, {'ott_len': 7, 'ott_percent': 357, 'stop_loss': 347, 'risk_reward': 75, 'chop_rsi_len': 49, 'chop_bandwidth': 116}], ['D9YmB.', 35, 139, 12.09, 42, 14, -1.17, {'ott_len': 18, 'ott_percent': 251, 'stop_loss': 267, 'risk_reward': 71, 'chop_rsi_len': 18, 'chop_bandwidth': 32}], ['_(KrZG', 40, 145, 18.09, 28, 21, -4.73, {'ott_len': 35, 'ott_percent': 100, 'stop_loss': 205, 'risk_reward': 76, 'chop_rsi_len': 32, 'chop_bandwidth': 124}], ['1CndgF', 34, 156, 49.82, 41, 17, 2.8, {'ott_len': 7, 'ott_percent': 339, 'stop_loss': 360, 'risk_reward': 63, 'chop_rsi_len': 40, 'chop_bandwidth': 120}], ['tutp,b', 50, 40, 52.45, 0, 5, -5.75, {'ott_len': 48, 'ott_percent': 782, 'stop_loss': 387, 'risk_reward': 74, 'chop_rsi_len': 4, 'chop_bandwidth': 223}], ['07t1iJ', 30, 199, 23.05, 26, 30, -1.64, {'ott_len': 6, 'ott_percent': 233, 'stop_loss': 387, 'risk_reward': 18, 'chop_rsi_len': 41, 'chop_bandwidth': 135}], ['75\\adC', 37, 200, 68.9, 21, 32, -4.78, {'ott_len': 10, 'ott_percent': 215, 'stop_loss': 280, 'risk_reward': 61, 'chop_rsi_len': 38, 'chop_bandwidth': 109}], ]

144

159

0.619529

3d6d1e7bb92fb8ada9eb142b244859a83f2f343d

2,909

py

Python

modules/winrm/isodate/__init__.py

frankyrumple/smc

975945ddcff754dd95f2e1a8bd4bf6e43a0f91f6

[ "MIT" ]

null

modules/winrm/isodate/__init__.py

frankyrumple/smc

975945ddcff754dd95f2e1a8bd4bf6e43a0f91f6

[ "MIT" ]

null

modules/winrm/isodate/__init__.py

frankyrumple/smc

975945ddcff754dd95f2e1a8bd4bf6e43a0f91f6

[ "MIT" ]

null

############################################################################## # Copyright 2009, Gerhard Weis # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # * Neither the name of the authors nor the names of its contributors # may be used to endorse or promote products derived from this software # without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT ############################################################################## ''' Import all essential functions and constants to re-export them here for easy access. This module contains also various pre-defined ISO 8601 format strings. ''' from .isodates import parse_date, date_isoformat from .isotime import parse_time, time_isoformat from .isodatetime import parse_datetime, datetime_isoformat from .isoduration import parse_duration, duration_isoformat, Duration from .isoerror import ISO8601Error from .isotzinfo import parse_tzinfo, tz_isoformat from .tzinfo import UTC, FixedOffset, LOCAL from .duration import Duration from .isostrf import strftime from .isostrf import DATE_BAS_COMPLETE, DATE_BAS_ORD_COMPLETE from .isostrf import DATE_BAS_WEEK, DATE_BAS_WEEK_COMPLETE from .isostrf import DATE_CENTURY, DATE_EXT_COMPLETE from .isostrf import DATE_EXT_ORD_COMPLETE, DATE_EXT_WEEK from .isostrf import DATE_EXT_WEEK_COMPLETE, DATE_MONTH, DATE_YEAR from .isostrf import TIME_BAS_COMPLETE, TIME_BAS_MINUTE from .isostrf import TIME_EXT_COMPLETE, TIME_EXT_MINUTE from .isostrf import TIME_HOUR from .isostrf import TZ_BAS, TZ_EXT, TZ_HOUR from .isostrf import DT_BAS_COMPLETE, DT_EXT_COMPLETE from .isostrf import DT_BAS_ORD_COMPLETE, DT_EXT_ORD_COMPLETE from .isostrf import DT_BAS_WEEK_COMPLETE, DT_EXT_WEEK_COMPLETE from .isostrf import D_DEFAULT, D_WEEK, D_ALT_EXT, D_ALT_BAS from .isostrf import D_ALT_BAS_ORD, D_ALT_EXT_ORD

51.946429

78

0.77243

3d6fef82415cc33c1f679313aef262f6b3b670a9

17,848

py

Python

sbvat/utils.py

thudzj/BVAT

2c7073cb7967583035eece7f4819821b313d73e6

[ "MIT" ]

3

2019-08-04T03:05:51.000Z

2021-04-24T02:35:05.000Z

sbvat/utils.py

thudzj/BVAT

2c7073cb7967583035eece7f4819821b313d73e6

[ "MIT" ]

null

sbvat/utils.py

thudzj/BVAT

2c7073cb7967583035eece7f4819821b313d73e6

[ "MIT" ]

1

2019-12-29T13:49:22.000Z

import numpy as np import pickle as pkl import networkx as nx import scipy.sparse as sp from scipy.sparse.linalg.eigen.arpack import eigsh import sys import tensorflow as tf import os import time import json from networkx.readwrite import json_graph from sklearn.metrics import f1_score import multiprocessing def parse_index_file(filename): """Parse index file.""" index = [] for line in open(filename): index.append(int(line.strip())) return index def sample_mask(idx, l): """Create mask.""" mask = np.zeros(l) mask[idx] = 1 return np.array(mask, dtype=np.bool) def sparse_to_tuple(sparse_mx): """Convert sparse matrix to tuple representation.""" if isinstance(sparse_mx, list): for i in range(len(sparse_mx)): sparse_mx[i] = to_tuple(sparse_mx[i]) else: sparse_mx = to_tuple(sparse_mx) return sparse_mx def preprocess_features(features, sparse=True): """Row-normalize feature matrix and convert to tuple representation""" rowsum = np.array(features.sum(1)) r_inv = np.power(rowsum, -1).flatten() r_inv[np.isinf(r_inv)] = 0. r_mat_inv = sp.diags(r_inv) features = r_mat_inv.dot(features) if sparse: return sparse_to_tuple(features) else: return features.toarray() def normalize_adj(adj): """Symmetrically normalize adjacency matrix.""" adj = sp.coo_matrix(adj) rowsum = np.array(adj.sum(1)) d_inv_sqrt = np.power(rowsum, -0.5).flatten() d_inv_sqrt[np.isinf(d_inv_sqrt)] = 0. d_mat_inv_sqrt = sp.diags(d_inv_sqrt) return adj.dot(d_mat_inv_sqrt).transpose().dot(d_mat_inv_sqrt).tocoo() def preprocess_adj(adj): """Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation.""" adj_normalized = normalize_adj(adj + sp.eye(adj.shape[0])) return sparse_to_tuple(adj_normalized) def construct_feed_dict(features, support, labels, labels_mask, placeholders, nbrs): """Construct feed dictionary.""" feed_dict = dict() feed_dict.update({placeholders['labels']: labels}) feed_dict.update({placeholders['labels_mask']: labels_mask}) feed_dict.update({placeholders['features']: features}) feed_dict.update({placeholders['support']: support}) feed_dict.update({placeholders['num_features_nonzero']: features[1].shape}) r1 = sample_nodes(nbrs) feed_dict.update({placeholders['adv_mask1']: r1}) return feed_dict def chebyshev_polynomials(adj, k): """Calculate Chebyshev polynomials up to order k. Return a list of sparse matrices (tuple representation).""" print("Calculating Chebyshev polynomials up to order {}...".format(k)) adj_normalized = normalize_adj(adj) laplacian = sp.eye(adj.shape[0]) - adj_normalized largest_eigval, _ = eigsh(laplacian, 1, which='LM') scaled_laplacian = (2. / largest_eigval[0]) * laplacian - sp.eye(adj.shape[0]) t_k = list() t_k.append(sp.eye(adj.shape[0])) t_k.append(scaled_laplacian) for i in range(2, k+1): t_k.append(chebyshev_recurrence(t_k[-1], t_k[-2], scaled_laplacian)) return sparse_to_tuple(t_k)

38.218415

200

0.601244

3d71bcc45f53747aca6197878307201d4f4b2564

506

py

Python

tags/models.py

yuyuyuhaoshi/Blog-BE

a485d5159076d619d4fd6019fe9b96ac04020d4d

[ "Apache-2.0" ]

null

tags/models.py

yuyuyuhaoshi/Blog-BE

a485d5159076d619d4fd6019fe9b96ac04020d4d

[ "Apache-2.0" ]

null

tags/models.py

yuyuyuhaoshi/Blog-BE

a485d5159076d619d4fd6019fe9b96ac04020d4d

[ "Apache-2.0" ]

null

from django.db import models from django.utils.timezone import now from django.contrib.auth.models import User from utils.base_model import SoftDeletionModel

26.631579

88

0.717391