xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

094d973f1a0b76ddedf08b03767accf5c0cfd497

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py

Python

mlcomponents/encoderdecoder.py

microsoft/aaai21-copy-that

7dfb2ebabbbf1165a33c2430ef2f2571e487b4fd

[ "MIT" ]

7

2021-06-21T17:13:23.000Z

2022-02-25T06:28:24.000Z

mlcomponents/encoderdecoder.py

microsoft/aaai21-copy-that

7dfb2ebabbbf1165a33c2430ef2f2571e487b4fd

[ "MIT" ]

null

mlcomponents/encoderdecoder.py

microsoft/aaai21-copy-that

7dfb2ebabbbf1165a33c2430ef2f2571e487b4fd

[ "MIT" ]

2

2021-09-13T12:32:16.000Z

2022-02-19T13:28:35.000Z

import logging from typing import Optional, Dict, Any, List, Tuple, NamedTuple import torch from data.edits import Edit from dpu_utils.ptutils import BaseComponent from mlcomponents.seqdecoding import SeqDecoder from mlcomponents.seqencoder import SequenceEncoder class EncoderDecoder(BaseComponent): ...

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094ecb7e5b2ee93093ff48eabf2ef2a4ed487787

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py

Python

mplStyle/MplTickStyle.py

khanfarhan10/mplStyle

f657f54c6c101811b8bf0c44f4b16d4f4926685d

[ "BSD-3-Clause" ]

39

2015-03-08T23:05:01.000Z

2022-02-07T16:03:35.000Z

mplStyle/MplTickStyle.py

khanfarhan10/mplStyle

f657f54c6c101811b8bf0c44f4b16d4f4926685d

[ "BSD-3-Clause" ]

null

mplStyle/MplTickStyle.py

khanfarhan10/mplStyle

f657f54c6c101811b8bf0c44f4b16d4f4926685d

[ "BSD-3-Clause" ]

23

2015-03-08T19:56:59.000Z

2021-07-15T15:16:26.000Z

#=========================================================================== # # Copyright (c) 2014, California Institute of Technology. # U.S. Government Sponsorship under NASA Contract NAS7-03001 is # acknowledged. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modific...

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095359d3e1736ca0199f424b5cea96012cb5fc24

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py

Python

micolog/cache2.py

tclh123/micolog

9b6fcddb9f147fe20a0cbfe0e89eda07f69d0f68

[ "MIT" ]

null

micolog/cache2.py

tclh123/micolog

9b6fcddb9f147fe20a0cbfe0e89eda07f69d0f68

[ "MIT" ]

null

micolog/cache2.py

tclh123/micolog

9b6fcddb9f147fe20a0cbfe0e89eda07f69d0f68

[ "MIT" ]

null

#------------------------------------------------------------------------------- # Name: cache.py # Purpose: # # Author: xuming # # Created: 23-01-2011 # Copyright: (c) xuming 2011 # Licence: GPL #------------------------------------------------------------------------------- #!/usr/bin/env python...

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095b1d80f095695d78ca8e32322128326b38659a

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py

Python

LeetCode-All-Solution/Python3/LC-0189-Rotate-Array.py

YuweiYin/Algorithm_YuweiYin

28648fac59c5a4e3c907978cbd1b3e662ba18fd5

[ "MIT" ]

null

LeetCode-All-Solution/Python3/LC-0189-Rotate-Array.py

YuweiYin/Algorithm_YuweiYin

28648fac59c5a4e3c907978cbd1b3e662ba18fd5

[ "MIT" ]

null

LeetCode-All-Solution/Python3/LC-0189-Rotate-Array.py

YuweiYin/Algorithm_YuweiYin

28648fac59c5a4e3c907978cbd1b3e662ba18fd5

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding:utf-8 -*- """================================================================= @Project : Algorithm_YuweiYin/LeetCode-All-Solution/Python3 @File : LC-0189-Rotate-Array.py @Author : [YuweiYin](https://github.com/YuweiYin) @Date : 2022-01-02 ======================================...

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null

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095c5cd039268240cc1f5e992dfc55ceb574b9a1

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py

Python

d1/repeatedcharacter.py

jwbat/python-datastructures

82ff91f1ee8c76a382bd5d43cdefe4ffcde00528

[ "MIT" ]

null

d1/repeatedcharacter.py

jwbat/python-datastructures

82ff91f1ee8c76a382bd5d43cdefe4ffcde00528

[ "MIT" ]

null

d1/repeatedcharacter.py

jwbat/python-datastructures

82ff91f1ee8c76a382bd5d43cdefe4ffcde00528

[ "MIT" ]

null

''' One fcn returns the first nonrepeated character from string, s. The other returns the first repeated character from the string. ''' def print_dict(d): for k, v in d.items(): print('\t', k, '=> ', v) def char_count_dict(s): d = dict() for char in s: count = d.get(char, 0) d[char...

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null

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0

095ca8346512b61fba41d3997f22f02f7c9433ae

2,652

py

Python

alipay/aop/api/domain/KoubeiCateringPosDishcateTransferModel.py

snowxmas/alipay-sdk-python-all

96870ced60facd96c5bce18d19371720cbda3317

[ "Apache-2.0" ]

213

2018-08-27T16:49:32.000Z

2021-12-29T04:34:12.000Z

alipay/aop/api/domain/KoubeiCateringPosDishcateTransferModel.py

snowxmas/alipay-sdk-python-all

96870ced60facd96c5bce18d19371720cbda3317

[ "Apache-2.0" ]

29

2018-09-29T06:43:00.000Z

2021-09-02T03:27:32.000Z

alipay/aop/api/domain/KoubeiCateringPosDishcateTransferModel.py

snowxmas/alipay-sdk-python-all

96870ced60facd96c5bce18d19371720cbda3317

[ "Apache-2.0" ]

59

2018-08-27T16:59:26.000Z

2022-03-25T10:08:15.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- import json from alipay.aop.api.constant.ParamConstants import * class KoubeiCateringPosDishcateTransferModel(object): def __init__(self): self._cate_id = None self._cook_id = None self._dish_ids = None self._shop_id = None @prop...

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null

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0961afc6929e36d21b0d3df4440d37f44a042e71

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py

Python

main.py

darshanvjani/Wrapper_EVAI_Pytorch

cd3f11ad8b36f5d512288b8e5f7e15174bd2bbd1

[ "MIT" ]

null

main.py

darshanvjani/Wrapper_EVAI_Pytorch

cd3f11ad8b36f5d512288b8e5f7e15174bd2bbd1

[ "MIT" ]

null

main.py

darshanvjani/Wrapper_EVAI_Pytorch

cd3f11ad8b36f5d512288b8e5f7e15174bd2bbd1

[ "MIT" ]

null

import torch import torchvision import torchvision.transforms as transforms import albumentations import numpy as np # from __future__ import print_function import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torchvision import datasets , transforms import torchvision fr...

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null

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0

117383a0b92d5b2084b9f6d9093f315d7ed4bad1

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py

Python

util/visualizer.py

google/tim-gan

0139ad452b3c74e3c12791ebb719ea5979eb0d1f

[ "Apache-2.0" ]

7

2020-11-17T21:38:46.000Z

2022-02-15T02:33:10.000Z

util/visualizer.py

google/tim-gan

0139ad452b3c74e3c12791ebb719ea5979eb0d1f

[ "Apache-2.0" ]

null

util/visualizer.py

google/tim-gan

0139ad452b3c74e3c12791ebb719ea5979eb0d1f

[ "Apache-2.0" ]

2

2021-01-23T12:13:29.000Z

2021-03-27T21:20:49.000Z

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

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117624463673d5965908bc5b693e638ca894611b

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py

Python

authorize/apis/base_api.py

aryeh/py-authorize

e0a2e8d9828efa2146b22cb855fa28d723913e41

[ "MIT" ]

30

2015-03-13T01:31:52.000Z

2021-06-11T08:49:43.000Z

authorize/apis/base_api.py

aryeh/py-authorize

e0a2e8d9828efa2146b22cb855fa28d723913e41

[ "MIT" ]

41

2015-01-30T20:01:05.000Z

2022-03-31T23:11:56.000Z

authorize/apis/base_api.py

aryeh/py-authorize

e0a2e8d9828efa2146b22cb855fa28d723913e41

[ "MIT" ]

34

2015-01-11T20:22:03.000Z

2022-03-28T20:34:22.000Z

import colander from authorize.exceptions import AuthorizeInvalidError class BaseAPI(object): def __init__(self, api): self.api = api self.config = api.config def _deserialize(self, schema, params={}): try: deserialized = schema.deserialize(params) except colande...

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11766920d1f9e38bf6634e7585ed79d49348e3c1

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py

Python

stable_baselines/trpo_mpi/run_mujoco.py

emadboctorx/stable-baselines

9bce185538e8bf69836371286e23919fd85eec64

[ "MIT" ]

null

stable_baselines/trpo_mpi/run_mujoco.py

emadboctorx/stable-baselines

9bce185538e8bf69836371286e23919fd85eec64

[ "MIT" ]

null

stable_baselines/trpo_mpi/run_mujoco.py

emadboctorx/stable-baselines

9bce185538e8bf69836371286e23919fd85eec64

[ "MIT" ]

null

import stable_baselines.common.tf_util as tf_util from mpi4py import MPI from stable_baselines import logger from stable_baselines.common.cmd_util import make_mujoco_env, mujoco_arg_parser from stable_baselines.common.policies import MlpPolicy from stable_baselines.trpo_mpi import TRPO def train(env_id, num_timesteps...

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null

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1

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11767e77d6369d63f87f78e8e4f1ac800b3e2e86

929

py

Python

Day-16/part1.py

archanpatkar/advent2020

86065eb744c885ce0e29ea8228b8e8ebbd38c939

[ "MIT" ]

null

Day-16/part1.py

archanpatkar/advent2020

86065eb744c885ce0e29ea8228b8e8ebbd38c939

[ "MIT" ]

null

Day-16/part1.py

archanpatkar/advent2020

86065eb744c885ce0e29ea8228b8e8ebbd38c939

[ "MIT" ]

null

import sys sys.path.append("..") from common import * def parse(data): data = list(map(lambda s: s.strip(),filter(lambda s: len(s) > 1,data.split("\n")))) conds = {} for i in range(20): kv = data[i].split(":") cs = kv[1].split("or") conds[kv[0]] = ([int(v) for v in cs[0].split("-")]...

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null

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11791aa64e3598994f4ffc54bf2c561214125d3a

1,931

py

Python

NewQshop/AppStore/Buyer/views.py

bestwishfang/FlaskFrameWork

e5f2af0b82be6d5b32febadc244a72aadceaa58b

[ "MIT" ]

null

NewQshop/AppStore/Buyer/views.py

bestwishfang/FlaskFrameWork

e5f2af0b82be6d5b32febadc244a72aadceaa58b

[ "MIT" ]

3

2020-04-30T15:16:56.000Z

2022-02-13T08:02:39.000Z

NewQshop/AppStore/Buyer/views.py

bestwishfang/FlaskFrameWork

e5f2af0b82be6d5b32febadc244a72aadceaa58b

[ "MIT" ]

null

import time import json import datetime from flask import request from flask import render_template from flask_restful import Resource from . import buyer, apibuyer from AppStore.models import Class_Info @buyer.route('/buyer/index/') def index(): return 'Hello World! This is buyer index.' @buyer.route('/api/b...

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1180dde3665390d3a54ac55203c8a6a39a04cbc1

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py

Python

addpapers.py

tarrow/librarybase-pwb

6c86aba7cbcb6200bfade0170aea8be3593cafec

[ "MIT" ]

1

2017-05-23T14:14:16.000Z

addpapers.py

tarrow/librarybase-pwb

6c86aba7cbcb6200bfade0170aea8be3593cafec

[ "MIT" ]

7

2015-12-09T10:14:37.000Z

2016-01-19T12:55:33.000Z

addpapers.py

tarrow/librarybase-pwb

6c86aba7cbcb6200bfade0170aea8be3593cafec

[ "MIT" ]

null

import queryCiteFile import librarybase import pywikibot from epmclib.getPMCID import getPMCID from epmclib.exceptions import IDNotResolvedException import queue import threading import time def rununthreaded(): citefile = queryCiteFile.CiteFile() citations = citefile.findRowsWithIDType('pmc') ...

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118141ccfae972e74c17e2b33370161c604fe8c4

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py

Python

day18/script2.py

Moremar/advent_of_code_2019

572200ad8c24efd38fb3fac428d086bcd7090ca9

[ "Apache-2.0" ]

null

day18/script2.py

Moremar/advent_of_code_2019

572200ad8c24efd38fb3fac428d086bcd7090ca9

[ "Apache-2.0" ]

null

day18/script2.py

Moremar/advent_of_code_2019

572200ad8c24efd38fb3fac428d086bcd7090ca9

[ "Apache-2.0" ]

null

from day18.script1 import parse_matrix, read_char_matrix, alpha_lower, solve_world # We could use the same logic as part 1 with a state made of a distance and 4 (x, y) pairs (one for each bot) # This works with examples, but there are too many combinations for the real input so it runs for very long # # To get it qui...

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1183ffbe924869fb7a592b3839706503e0ba51ef

1,029

py

Python

test/test_clamp.py

XiaoxuanZhangCM/igakit

71bc4237a561272f6189d067688c182aa705c5eb

[ "BSD-2-Clause" ]

2

2022-03-21T09:38:55.000Z

2022-03-24T23:33:55.000Z

test/test_clamp.py

XiaoxuanZhangCM/igakit

71bc4237a561272f6189d067688c182aa705c5eb

[ "BSD-2-Clause" ]

1

2022-03-24T22:50:35.000Z

2022-03-27T06:33:16.000Z

test/test_clamp.py

XiaoxuanZhangCM/igakit

71bc4237a561272f6189d067688c182aa705c5eb

[ "BSD-2-Clause" ]

null

import numpy as np from igakit.cad import circle, Pi def make_crv(p,u): c = circle(radius=1, angle=Pi/2) c.rotate(Pi/4) c.elevate(0,p-2) c.refine(0,u) return c def check_crv(c): u0, u1 = c.breaks(0)[[0,-1]] u = np.linspace(u0,u1,100) x, y, z = c(u).T r = np.hypot(x,y) return np...

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null

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1

0

1186952effff0749fbfa4fc2d6b7b1c8935379fb

4,261

py

Python

autoload/vim_ext/vim_opt.py

nielsmadan/venom

87dee312fe8dbaa64fe29fba7a2ccd5f41a55b4a

[ "0BSD" ]

1

2022-01-26T04:57:28.000Z

autoload/vim_ext/vim_opt.py

nielsmadan/venom

87dee312fe8dbaa64fe29fba7a2ccd5f41a55b4a

[ "0BSD" ]

null

autoload/vim_ext/vim_opt.py

nielsmadan/venom

87dee312fe8dbaa64fe29fba7a2ccd5f41a55b4a

[ "0BSD" ]

1

2021-08-19T08:11:58.000Z

import vim _BOOL_OPTS = set(('allowrevins', 'altkeymap', 'antialias', 'autochdir', 'arabic', 'arabicshape', 'autoindent', 'autoread', 'autowrite', 'backup', 'ballooneval', 'binary', 'bioskey', 'bomb', 'buflisted', 'buftype', 'cindent', 'compatible', 'confirm', 'con...

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0.051724

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null

0

null

0

1

0

1188f7d771d6606445861a8c6c54d6fe5f5f1785

40,198

py

Python

statestream/utils/shared_memory.py

boschresearch/statestream

3ea93b2e0434cfaf5d546f37b2068dc0a0b8c281

[ "Apache-2.0", "MIT" ]

9

2019-02-21T14:25:26.000Z

2021-07-21T08:14:32.000Z

statestream/utils/shared_memory.py

VolkerFischer/statestream

3ea93b2e0434cfaf5d546f37b2068dc0a0b8c281

[ "Apache-2.0", "MIT" ]

null

statestream/utils/shared_memory.py

VolkerFischer/statestream

3ea93b2e0434cfaf5d546f37b2068dc0a0b8c281

[ "Apache-2.0", "MIT" ]

1

2019-03-04T03:17:00.000Z

# -*- coding: utf-8 -*- # Copyright (c) 2017 - for information on the respective copyright owner # see the NOTICE file and/or the repository https://github.com/boschresearch/statestream # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License....

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null

0

null

0

1

0

118a041ae6d96652625804e1d8039c4ff86c7d07

3,957

py

Python

core/views.py

MichelAtieno/Rogue-Nation

c4d78b42b5e6312043de2308a591951d0ba297b8

[ "Unlicense" ]

null

core/views.py

MichelAtieno/Rogue-Nation

c4d78b42b5e6312043de2308a591951d0ba297b8

[ "Unlicense" ]

11

2020-06-05T22:42:25.000Z

2022-03-11T23:58:46.000Z

core/views.py

MichelAtieno/Rogue-Nation

c4d78b42b5e6312043de2308a591951d0ba297b8

[ "Unlicense" ]

null

from django.db.models import Count, Q from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger from django.shortcuts import render, get_object_or_404 from .models import NewsItem, SignUp, Artist, Athlete,Category # Create your views here. def search(request): queryset = NewsItem.objects.all() ...

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null

0

null

0

1

0

118a9196e211cb95ce33a333ef7a6481cddafdd3

2,133

py

Python

process-invoices/update_invoice_statuses.py

MITLibraries/alma-scripts

c312692a71a83dc0b5e60761bc3e7b37d7d42099

[ "Apache-2.0" ]

null

process-invoices/update_invoice_statuses.py

MITLibraries/alma-scripts

c312692a71a83dc0b5e60761bc3e7b37d7d42099

[ "Apache-2.0" ]

16

2021-07-23T20:46:29.000Z

2022-03-10T19:34:10.000Z

process-invoices/update_invoice_statuses.py

MITLibraries/alma-scripts

c312692a71a83dc0b5e60761bc3e7b37d7d42099

[ "Apache-2.0" ]

null

import datetime import glob import sys import requests from defusedxml import ElementTree as ET sys.path.append("..") from llama.alma import Alma_API_Client import llama.config as config TODAY = datetime.date.today() count_total_invoices = 0 count_invoices_updated = 0 count_invoice_errors = 0 # Update empty invoice...

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null

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null

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118a963b9511f86ed9bf75aa58347aecde3de782

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py

Python

src/converter/convert_mobilenetv2.py

xiongzhiyao/pytorch-segmentation

a13b1aa1b316d06f050deef29d5be8b6e99460e7

[ "MIT" ]

359

2018-11-22T04:13:19.000Z

2022-03-08T09:05:47.000Z

src/converter/convert_mobilenetv2.py

xiongzhiyao/pytorch-segmentation

a13b1aa1b316d06f050deef29d5be8b6e99460e7

[ "MIT" ]

21

2018-12-07T22:37:09.000Z

2021-01-22T02:18:28.000Z

src/converter/convert_mobilenetv2.py

xiongzhiyao/pytorch-segmentation

a13b1aa1b316d06f050deef29d5be8b6e99460e7

[ "MIT" ]

73

2018-11-22T06:16:54.000Z

2021-03-30T18:26:47.000Z

import argparse from pathlib import Path import tensorflow as tf import torch from models.net import SPPNet def convert_mobilenetv2(ckpt_path, num_classes): def conv_converter(pt_layer, tf_layer_name, depthwise=False, bias=False): if depthwise: pt_layer.weight.data = torch.Tensor( ...

45.744444

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4,117

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0.137208

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117

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0.147059

0

null

0

null

0

1

0

118bb9cc42104087368b917dcb655edae791e512

2,624

py

Python

extract-subimages-videos.py

rzaluska/fcnn-conferences

509946a4d342451f29e7b8706b6ff46b0af20f36

[ "MIT" ]

1

2018-04-07T05:55:48.000Z

extract-subimages-videos.py

rzaluska/fcnn-conferences

509946a4d342451f29e7b8706b6ff46b0af20f36

[ "MIT" ]

null

extract-subimages-videos.py

rzaluska/fcnn-conferences

509946a4d342451f29e7b8706b6ff46b0af20f36

[ "MIT" ]

null

# script for extracting patches from video frames suitable for neural network # training from keras.preprocessing.image import ImageDataGenerator, load_img, img_to_array, array_to_img from PIL import Image import sys import os import glob from PIL import Image from os.path import basename, splitext import numpy as n...

39.164179

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0

0.020376

0.270579

2,624

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null

0

null

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1

0

118d551ca0c80c0e51a840c724d05bb79e776a14

2,113

py

Python

src/extract_cdi/__init__.py

igorgbr/extract_cdi

66d8aa56d0099c04ef491908ab246389b79fdc7e

[ "MIT" ]

null

src/extract_cdi/__init__.py

igorgbr/extract_cdi

66d8aa56d0099c04ef491908ab246389b79fdc7e

[ "MIT" ]

null

src/extract_cdi/__init__.py

igorgbr/extract_cdi

66d8aa56d0099c04ef491908ab246389b79fdc7e

[ "MIT" ]

null

import os import time import json from random import random from datetime import datetime import pandas as pd import seaborn as sns import requests class SearchAndExtractData(object): def __init__(self, file: str, graph_name: str) -> None: self.file = file self.graph_name = graph_name def cr...

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0.043937

0

0.00838

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0

null

0

null

0

1

0

118ff67c852ea38f217b5c566e77f4efa9b7fe30

9,368

py

Python

FirmsLocations/Retrieve/density_assignation.py

tgquintela/Firms_locations

476680cbc3eb1308811633d24810049e215101a0

[ "MIT" ]

null

FirmsLocations/Retrieve/density_assignation.py

tgquintela/Firms_locations

476680cbc3eb1308811633d24810049e215101a0

[ "MIT" ]

null

FirmsLocations/Retrieve/density_assignation.py

tgquintela/Firms_locations

476680cbc3eb1308811633d24810049e215101a0

[ "MIT" ]

null

""" Assign geographically density value to a points. """ from scipy.spatial import KDTree from scipy.spatial.distance import cdist from scipy.stats import norm from scipy.optimize import minimize import numpy as np def general_density_assignation(locs, parameters, values=None, locs2=None): "Density assignation ...

34.315018

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1,214

9,368

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0.135914

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0.473602

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0.289499

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9,368

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false

0

0.026042

0

0.223958

0

null

0

null

0

1

0

1190f1b038385208afbc477445817bdebba87dc5

561

py

Python

nexus/pylon/sources/specific/biorxiv.py

leoll2/hyperboria

30a0ae466b290208f690560160ef1f5c16e4a744

[ "Unlicense" ]

null

nexus/pylon/sources/specific/biorxiv.py

leoll2/hyperboria

30a0ae466b290208f690560160ef1f5c16e4a744

[ "Unlicense" ]

null

nexus/pylon/sources/specific/biorxiv.py

leoll2/hyperboria

30a0ae466b290208f690560160ef1f5c16e4a744

[ "Unlicense" ]

null

from typing import AsyncIterable from nexus.pylon.sources.base import ( DoiSource, PreparedRequest, ) class BiorxivSource(DoiSource): base_url = 'https://dx.doi.org' async def resolve(self) -> AsyncIterable[PreparedRequest]: async with self.get_resolve_session() as session: url =...

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0

0.27451

561

19

85

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0.837838

0

0.099822

0.046346

0

1

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false

0

0.133333

0

0.266667

0

null

0

null

0

1

0

1193d717cb8b9aa0587bf651757ef62435cc6b62

3,645

py

Python

addLatLon.py

amnh-sciviz/amnh-time-machine

c75c75c6bd3ee91d81cb4b0181a292de27eab9c8

[ "MIT" ]

null

addLatLon.py

amnh-sciviz/amnh-time-machine

c75c75c6bd3ee91d81cb4b0181a292de27eab9c8

[ "MIT" ]

null

addLatLon.py

amnh-sciviz/amnh-time-machine

c75c75c6bd3ee91d81cb4b0181a292de27eab9c8

[ "MIT" ]

null

# -*- coding: utf-8 -*- import argparse from difflib import SequenceMatcher import os from pprint import pprint import sys import lib.eac_utils as eac import lib.io_utils as io # input parser = argparse.ArgumentParser() parser.add_argument('-in', dest="INPUT_FILE", default="data/eac_dates.csv", help="File with EAC d...

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0.019149

0.015319

0

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0.195885

3,645

101

200

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0

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0

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false

0

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0.012821

0.230769

0.025641

0

null

0

null

0

1

0

11958f77466ed28b0ddf34aab10041bc97b2f55d

912

py

Python

Solutions/problem07.py

WalrusCow/euler

b5bfa67c87c7043f521cde32e7212c0fffdbacd9

[ "MIT" ]

null

Solutions/problem07.py

WalrusCow/euler

b5bfa67c87c7043f521cde32e7212c0fffdbacd9

[ "MIT" ]

null

Solutions/problem07.py

WalrusCow/euler

b5bfa67c87c7043f521cde32e7212c0fffdbacd9

[ "MIT" ]

null

# Project Euler Problem 7 # Created on: 2012-06-13 # Created by: William McDonald import math import time # Short list of prime numbers under 20 primeList = [2, 3, 5, 7, 9, 11, 13, 17, 19] # Returns True if n is prime, otherwise False def isPrime(n): prime = True for i in primeList: if ...

24

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0.083499

0.087475

0

0.058043

0.338816

912

38

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0

0.074074

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1

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false

0

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0.259259

0.074074

0

null

0

null

0

1

0

119622f084f9dfff43411b649a9c89be1e105982

1,820

py

Python

cogs/ban.py

QuentiumYT/QuentiumBot

1673d24d93f13f464b1175424529c4d58abb5c00

[ "MIT" ]

9

2019-11-14T10:12:00.000Z

2021-12-17T13:05:40.000Z

cogs/ban.py

QuentiumYT/QuentiumBot

1673d24d93f13f464b1175424529c4d58abb5c00

[ "MIT" ]

null

cogs/ban.py

QuentiumYT/QuentiumBot

1673d24d93f13f464b1175424529c4d58abb5c00

[ "MIT" ]

4

2020-08-20T21:24:52.000Z

2021-12-17T13:05:17.000Z

import discord from discord.ext import commands from QuentiumBot import HandleData, get_translations # Basic command configs cmd_name = "ban" tran = get_translations() aliases = [] if not tran[cmd_name]["fr"]["aliases"] else tran[cmd_name]["fr"]["aliases"].split("/") class BanAdminRights(commands.Cog): """Ban com...

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null

0

null

0

1

0

119816fffb1e07970d7a5eddf0acda8930b0e4b4

3,057

py

Python

tpp_tensorflow/models/semisparse.py

gfrogat/tpp_tensorflow

711dd8cc0a8155ce6b6e5663afb2331b55748d30

[ "MIT" ]

null

tpp_tensorflow/models/semisparse.py

gfrogat/tpp_tensorflow

711dd8cc0a8155ce6b6e5663afb2331b55748d30

[ "MIT" ]

null

tpp_tensorflow/models/semisparse.py

gfrogat/tpp_tensorflow

711dd8cc0a8155ce6b6e5663afb2331b55748d30

[ "MIT" ]

null

from tensorflow.keras import Model, layers, regularizers class SemiSparseInput(Model): def __init__(self, params): super(SemiSparseInput, self).__init__() # Correctly handle SELU dropout = layers.AlphaDropout if params.activation == "selu" else layers.Dropout kernel_init = ( ...

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0

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0

0.0625

0

null

0

null

0

1

0

119876ff369ecd32448c59ea7ad56ae2b54cfef2

4,628

py

Python

AT/neo4j_functions.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

AT/neo4j_functions.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

AT/neo4j_functions.py

seakers/daphne-brain

1d703d468cd503a21395f986dd72e67b6e556451

[ "MIT" ]

null

# Testing for neo4j query functions from neo4j import GraphDatabase, basic_auth # setup neo4j database connection driver = GraphDatabase.driver("bolt://13.58.54.49:7687", auth=basic_auth("neo4j", "goSEAKers!")) session = driver.session() # Function that can take the intersection of multiple symptom queries # Fabricat...

46.747475

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0

null

0

null

0

1

0

119a0cbab86f26fb6ab15f22092ddf49f71f6f94

5,486

py

Python

build.py

refaim/wots

dad9918c603293982a598fb5d6c73ade1a6080e1

[ "MIT" ]

2

2018-07-14T19:45:38.000Z

2019-04-21T07:17:20.000Z

build.py

refaim/wots

dad9918c603293982a598fb5d6c73ade1a6080e1

[ "MIT" ]

155

2018-07-07T00:33:31.000Z

2021-08-16T17:55:05.000Z

build.py

refaim/wots

dad9918c603293982a598fb5d6c73ade1a6080e1

[ "MIT" ]

null

import datetime import math import os import sys import PyQt5 import dotenv from PyInstaller.archive.pyz_crypto import PyiBlockCipher from PyInstaller.building.api import PYZ, EXE, COLLECT from PyInstaller.building.build_main import Analysis from app import version from app.core.utils import OsUtils, PathUtils APP_N...

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0

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0.138889

0

null

0

null

0

1

0

119a349c2ca5822591f4b6677156eec1b27631d0

1,939

py

Python

server/constants.py

chrononyan/ok

1c83e419dd8d5ef64c1e03a7f8a218e65a9fb7cf

[ "Apache-2.0" ]

148

2018-07-03T02:08:30.000Z

2022-03-26T04:03:35.000Z

server/constants.py

chrononyan/ok

1c83e419dd8d5ef64c1e03a7f8a218e65a9fb7cf

[ "Apache-2.0" ]

856

2015-01-10T04:27:20.000Z

2018-06-27T14:43:23.000Z

server/constants.py

chrononyan/ok

1c83e419dd8d5ef64c1e03a7f8a218e65a9fb7cf

[ "Apache-2.0" ]

69

2015-01-26T08:06:55.000Z

2018-06-25T12:46:03.000Z

"""App constants""" import os STUDENT_ROLE = 'student' GRADER_ROLE = 'grader' STAFF_ROLE = 'staff' INSTRUCTOR_ROLE = 'instructor' LAB_ASSISTANT_ROLE = 'lab assistant' ROLE_DISPLAY_NAMES = { STUDENT_ROLE: 'Student', GRADER_ROLE: 'Reader', STAFF_ROLE: 'Teaching Assistant', INSTRUCTOR_ROLE: 'Instructor', ...

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null

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null

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119efd61f102f9d7b866310597894dc025bd5e5a

466

py

Python

AlgoritimoRandomize.py

falluk/algoritimoDeBuscas

6dbca79ef60f2820f5e81110bc4104bdc46496b1

[ "MIT" ]

1

2021-07-05T13:24:04.000Z

AlgoritimoRandomize.py

falluk/algoritimoDeBuscas

6dbca79ef60f2820f5e81110bc4104bdc46496b1

[ "MIT" ]

null

AlgoritimoRandomize.py

falluk/algoritimoDeBuscas

6dbca79ef60f2820f5e81110bc4104bdc46496b1

[ "MIT" ]

null

#Criado para randomizar uma lsita de 20mil Colaboradores retornando apenas 1000 colaboradores vários cargos distintos. import pandas as pd import random base = pd.read_excel("usuarios - energisa.xlsx", encoding="ISO-8859-1",error_bad_lines=False) sort1 = base.sample(15000) sort2 = sort1.sample(10000) sort3 = sort2...

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null

0

null

0

1

0

11a158752080d596792054d55693dc41df752af9

7,625

py

Python

app.py

Build-Week-2106FT-AirBnB-3/front-end

0df6f9814387a36002a1aaa8feff1f17fcb30b78

[ "CC0-1.0" ]

null

app.py

Build-Week-2106FT-AirBnB-3/front-end

0df6f9814387a36002a1aaa8feff1f17fcb30b78

[ "CC0-1.0" ]

1

2021-06-24T00:17:40.000Z

2021-06-24T00:18:42.000Z

app.py

Build-Week-2106FT-AirBnB-3/pricing

0df6f9814387a36002a1aaa8feff1f17fcb30b78

[ "CC0-1.0" ]

null

# -*- coding: utf-8 -*- # https://towardsdatascience.com/build-a-machine-learning-simulation-tool-with-dash-b3f6fd512ad6 # We start with the import of standard ML librairies import pandas as pd import numpy as np from sklearn.datasets import make_regression from sklearn.ensemble import RandomForestRegressor # We ad...

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0.291667

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null

0

null

0

1

0

11a1d2a8f067924755b1bb004f5652117e69edcd

1,787

py

Python

balloon_learning_environment/env/gym.py

johannah/balloon-learning-environment

cdb2e582f2b03c41f037bf76142d31611f5e0316

[ "Apache-2.0" ]

64

2021-11-09T08:49:02.000Z

2022-03-30T17:33:54.000Z

balloon_learning_environment/env/gym.py

johannah/balloon-learning-environment

cdb2e582f2b03c41f037bf76142d31611f5e0316

[ "Apache-2.0" ]

null

balloon_learning_environment/env/gym.py

johannah/balloon-learning-environment

cdb2e582f2b03c41f037bf76142d31611f5e0316

[ "Apache-2.0" ]

5

2021-11-14T18:56:42.000Z

2022-03-18T16:22:31.000Z

# coding=utf-8 # Copyright 2022 The Balloon Learning Environment Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless require...

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0

null

0

null

0

1

0

11a1e1b730dc4e433d8e1358594ee3d9a8526d1b

15,181

py

Python

models/multimodal_transformer.py

XiaoJake/MTTR

c383c5b151e3c97aeb45cd2fb4bf08719016498b

[ "Apache-2.0" ]

516

2021-11-30T03:22:41.000Z

2022-03-31T19:48:59.000Z

models/multimodal_transformer.py

codwest/MTTR

c383c5b151e3c97aeb45cd2fb4bf08719016498b

[ "Apache-2.0" ]

15

2021-12-07T02:43:24.000Z

2022-03-27T15:59:32.000Z

models/multimodal_transformer.py

codwest/MTTR

c383c5b151e3c97aeb45cd2fb4bf08719016498b

[ "Apache-2.0" ]

57

2021-11-30T08:49:51.000Z

2022-03-25T19:41:08.000Z

""" MTTR Multimodal Transformer class. Modified from DETR https://github.com/facebookresearch/detr """ import copy import os from typing import Optional import torch import torch.nn.functional as F from torch import nn, Tensor from einops import rearrange, repeat from transformers import RobertaModel, RobertaTokenizerF...

44.259475

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0.625585

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15,181

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0.131633

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0.059

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0.448708

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0

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0.015038

0.221805

0

null

0

null

0

1

0

11a22b195401a97025bc1265b213cb97ff210032

403

py

Python

docker_sdk_api/shared/helpers/get_model_zip.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

20

2021-07-13T13:08:57.000Z

2022-03-29T09:38:00.000Z

docker_sdk_api/shared/helpers/get_model_zip.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

null

docker_sdk_api/shared/helpers/get_model_zip.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

2

2021-07-12T08:42:53.000Z

2022-03-04T18:41:25.000Z

import os from typing import Dict def get_downloadable_zip(folder_path: str) -> Dict[str, str]: servable_models: Dict[str, str] = {} for root, dirs, files in os.walk(folder_path): for directory in dirs: for f in os.listdir(os.path.join(root, directory)): if f.endswith(".zip...

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0.4

0

null

0

null

0

1

0

11a302e0300bce122a82770aa16b84ca6e8d73b5

6,065

py

Python

groups/views.py

3crabs/class-book

f5de12be816aa9be889d8413007be8eb4abdf45f

[ "WTFPL" ]

1

2020-11-19T14:49:41.000Z

groups/views.py

3crabs/class-book

f5de12be816aa9be889d8413007be8eb4abdf45f

[ "WTFPL" ]

null

groups/views.py

3crabs/class-book

f5de12be816aa9be889d8413007be8eb4abdf45f

[ "WTFPL" ]

null

from django.core.mail import EmailMessage from django.http import HttpResponse, HttpResponseRedirect from django.shortcuts import render from accounting.models import Attendance, Result from accounting.templatetags import my_tags from class_book import settings from groups.models import Group, Student from subjects.mo...

32.433155

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0.616983

755

6,065

4.886093

0.156291

0.024397

0.0553

0.060721

0.580645

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0.506912

0.446191

0.384657

0.31987

0

0.005342

0.259192

6,065

186

116

32.607527

0.815713

0

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0

1

0.05625

false

0

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0.18125

0.00625

0

null

0

null

0

1

0

11a8090bef6d5fb982bc2e421b4aadbc73c27dfc

3,861

py

Python

src/tree/tree_builder.py

rpSebastian/LeducPoker

5bbdf61d885bcb23490410ef871de924c58bbf01

[ "MIT" ]

1

2020-05-22T15:45:22.000Z

src/tree/tree_builder.py

rpSebastian/LeducPoker

5bbdf61d885bcb23490410ef871de924c58bbf01

[ "MIT" ]

null

src/tree/tree_builder.py

rpSebastian/LeducPoker

5bbdf61d885bcb23490410ef871de924c58bbf01

[ "MIT" ]

1

2020-05-31T03:01:42.000Z

from settings import constants from game import bet_sizing, card_tools, card_to_string from base import Node import torch class PokerTreeBuilder(): def __init__(self): pass def build_tree(self, params): root = Node() root.street = params.root_node.street root.bets = params.roo...

38.227723

98

0.644911

474

3,861

4.934599

0.154008

0.111159

0.047884

0.046174

0.22018

0.197093

0.140231

0.107738

0.082086

0.053869

0

0.007854

0.27454

3,861

100

99

38.61

0.827205

0.034447

0

0.121951

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0.007256

0

1

0.073171

false

0.012195

0.04878

0

0.207317

0

null

0

null

0

1

0

11ab85dad8fb08a5c5eee01b9be2f4e803d8712c

50,062

py

Python

src/htsql/core/tr/bind.py

sirex/htsql

52275f6a584b412c109822d2ed2a5e69ac522cdf

[ "Apache-2.0" ]

null

src/htsql/core/tr/bind.py

sirex/htsql

52275f6a584b412c109822d2ed2a5e69ac522cdf

[ "Apache-2.0" ]

null

src/htsql/core/tr/bind.py

sirex/htsql

52275f6a584b412c109822d2ed2a5e69ac522cdf

[ "Apache-2.0" ]

null

# # Copyright (c) 2006-2013, Prometheus Research, LLC # """ :mod:`htsql.core.tr.bind` ========================= This module implements the binding process. """ from ..util import maybe, listof, tupleof, similar from ..adapter import Adapter, Protocol, adapt, adapt_many from ..domain import (Domain, BooleanDomain, ...

37.028107

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0.583716

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50,062

5.524678

0.111773

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0.017207

0.01241

0.390969

0.315118

0.243056

0.199673

0.169187

0.142212

0

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0.335184

50,062

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false

0

0.012586

0.011442

0.202517

0

null

0

null

0

1

0

11ad8fe6bba3193be56826f292aa054b4c5199e3

2,226

py

Python

locuszoom_plotting_service/gwas/tests/factories.py

statgen/locuszoom-hosted

ecfcc5f48fefe2869ab277202a661c2575af6abb

[ "MIT" ]

null

locuszoom_plotting_service/gwas/tests/factories.py

statgen/locuszoom-hosted

ecfcc5f48fefe2869ab277202a661c2575af6abb

[ "MIT" ]

14

2021-01-01T17:16:23.000Z

2022-02-28T19:37:28.000Z

locuszoom_plotting_service/gwas/tests/factories.py

statgen/locuszoom-hosted

ecfcc5f48fefe2869ab277202a661c2575af6abb

[ "MIT" ]

null

import os import random from django.db.models import signals from django.utils import timezone import factory from factory.django import DjangoModelFactory from locuszoom_plotting_service.users.tests.factories import UserFactory from .. import constants as lz_constants from .. import models as lz_models def choose_...

29.68

108

0.709344

267

2,226

5.741573

0.501873

0.020874

0.027397

0.031311

0.092629

0.078278

0.043053

0

0.006232

0.207098

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74

109

30.081081

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0.142857

0

0.098039

0

0.08307

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0

1

0.039216

false

0

0.176471

0.039216

0.627451

0

null

0

null

0

1

0

11b627ad398f9ae3625b734210d1a5d1347b9bf2

1,700

py

Python

pantofola_search/management/commands/_private.py

phingage/pantofola.io

f41036d2e568a45f328e2a7ca81d76a27cd134dc

[ "WTFPL" ]

1

2018-06-09T22:20:00.000Z

pantofola_search/management/commands/_private.py

phingage/pantofola.io

f41036d2e568a45f328e2a7ca81d76a27cd134dc

[ "WTFPL" ]

4

2020-02-11T22:01:16.000Z

2021-06-10T17:38:56.000Z

pantofola_search/management/commands/_private.py

phingage/pantofola.io

f41036d2e568a45f328e2a7ca81d76a27cd134dc

[ "WTFPL" ]

null

from pantofola_search.models import * from pantofola_search.tools.imdb_fetcher import ImdbFetcher def update_new_movie_info(clean_title, imdb_id, torrent, is_imdb=False): my_imdb = ImdbFetcher() if not Movie.objects.filter(pk=imdb_id).exists(): # #[imdb_id,year,max_ratio,[titles[1]]] movie_inf...

36.956522

78

0.648824

239

1,700

4.322176

0.317992

0.087125

0.029042

0.023233

0

0.011848

0.255294

1,700

46

79

36.956522

0.804107

0.086471

0

0.052632

0

1

0.052632

false

0

0.052632

0

0.157895

0

null

0

null

0

1

0

11b6a22d0d9d730ae6441343ec296d67f55adf10

7,663

py

Python

ArcLint.py

namur007/ArcLint

b17b39cf7fdfeff144339b6f3494d9120eafde90

[ "MIT" ]

null

ArcLint.py

namur007/ArcLint

b17b39cf7fdfeff144339b6f3494d9120eafde90

[ "MIT" ]

4

2020-07-17T18:11:54.000Z

2020-07-26T12:34:57.000Z

ArcLint.py

namur007/ArcLint

b17b39cf7fdfeff144339b6f3494d9120eafde90

[ "MIT" ]

null

import json import re import datetime import os import arcpy regex_flag_dict = { # 'ASCII' re.A, # this is py3 only so wont work in arcgis desktop 'IGNORECASE': re.I, 'LOCALE': re.L, "MULTILINE": re.M, "DOTMATCH": re.S, "UNICODE": re.U, "VERBOSE": re.X, } def main(json_path, feature, outp...

27.66426

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964

7,663

4.431535

0.190871

0.02809

0.026217

0.01779

0.160346

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0.071161

0.04073

0.020131

0

0.002025

0.291139

7,663

276

137

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0

0.087209

0

0.102556

0.01356

0

1

0.098837

false

0

0.02907

0.011628

0.209302

0

null

0

null

0

1

0

11b7d8f84ea9074863867abdbc15c4a61c060614

1,710

py

Python

files/persona_dao.py

DaletWolff/Curso_postgresql

a9d716236b1a840f104c98a4982eab9b1ad641ba

[ "Unlicense" ]

null

files/persona_dao.py

DaletWolff/Curso_postgresql

a9d716236b1a840f104c98a4982eab9b1ad641ba

[ "Unlicense" ]

null

files/persona_dao.py

DaletWolff/Curso_postgresql

a9d716236b1a840f104c98a4982eab9b1ad641ba

[ "Unlicense" ]

null

from persona import Persona from logger_base import log from cursor import Cursor class PersonaDAO: _SELECCIONAR = 'SELECT * FROM persona ORDER BY id_persona' _INSERTAR = 'INSERT INTO persona(nombre, apellido, email) VALUES(%s, %s, %s)' _ACTUALIZAR = 'UPDATE persona SET nombre=%s, apellido=%s, ema...

38

92

0.612281

181

1,710

5.707182

0.292818

0.043562

0.046467

0.0697

0.387222

0.320426

0.185866

0.145208

0

0.003309

0.292982

1,710

45

93

38

0.851117

0

0.282051

0

0.179964

0

1

0.102564

false

0

0.076923

0

0.410256

0

null

0

null

0

1

0

11c058f314fcdf27f630e4e67e934c957629b5a4

1,000

py

Python

pype9/cmd/convert.py

tclose/Pype9

23f96c0885fd9df12d9d11ff800f816520e4b17a

[ "MIT" ]

null

pype9/cmd/convert.py

tclose/Pype9

23f96c0885fd9df12d9d11ff800f816520e4b17a

[ "MIT" ]

null

pype9/cmd/convert.py

tclose/Pype9

23f96c0885fd9df12d9d11ff800f816520e4b17a

[ "MIT" ]

1

2021-04-08T12:46:21.000Z

""" Tool to convert 9ML files between different supported formats (e.g. XML_, JSON_, YAML_) and 9ML versions. """ from argparse import ArgumentParser from pype9.utils.arguments import nineml_document from pype9.utils.logging import logger def argparser(): parser = ArgumentParser(prog='pype9 convert', ...

33.333333

77

0.664

127

1,000

5.055118

0.503937

0.042056

0.079439

0

0.007673

0.218

1,000

29

78

34.482759

0.813299

0.105

0

0.166855

0

1

0.1

false

0

0.15

0

0.3

0

null

0

null

0

1

0

11c365d4ccc71a94837656d754364a0fe60f8958

3,615

py

Python

Tools/MakeHDF.py

Kadantte/VideoSuperResolution

4c86e49d81c7a9bea1fe0780d651afc126768df3

[ "MIT" ]

1,447

2018-06-04T08:44:07.000Z

2022-03-29T06:19:10.000Z

Tools/MakeHDF.py

Evergreengyq/VideoSuperResolution

1d0c54fafaf7a02f0d69408502f90c55f0f76536

[ "MIT" ]

96

2018-08-29T01:02:45.000Z

2022-01-12T06:00:01.000Z

Tools/MakeHDF.py

Evergreengyq/VideoSuperResolution

1d0c54fafaf7a02f0d69408502f90c55f0f76536

[ "MIT" ]

307

2018-06-26T13:35:54.000Z

2022-01-21T09:01:54.000Z

# Copyright (c): Wenyi Tang 2017-2019. # Author: Wenyi Tang # Email: wenyi.tang@intel.com # Update Date: 2019/4/3 下午5:03 import argparse import time from pathlib import Path import h5py import numpy as np import tqdm from PIL import Image __all__ = ["gather_videos_vqp", "gather_videos", "print_dataset"] parser ...

30.125

81

0.634302

526

3,615

4.214829

0.302281

0.028417

0.053676

0.027064

0.372576

0.301308

0.277853

0.236355

0

0.015009

0.207469

3,615

119

82

30.378151

0.758813

0.059198

0

0.347826

0

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0

1

0.076087

false

0

0.076087

0

0.163043

0.054348

0

null

0

null

0

1

0

11c45856fc39f00ce8b427bda4629a69a7f9c3b7

1,480

py

Python

modules/ddg_appwv_cookies.py

ItWasDNS/DDG-Parser

fd63099df7b93a603b9fe2ae4259c232f0555a65

[ "MIT" ]

null

modules/ddg_appwv_cookies.py

ItWasDNS/DDG-Parser

fd63099df7b93a603b9fe2ae4259c232f0555a65

[ "MIT" ]

null

modules/ddg_appwv_cookies.py

ItWasDNS/DDG-Parser

fd63099df7b93a603b9fe2ae4259c232f0555a65

[ "MIT" ]

null

""" Process 'com.duckduckgo.mobile.android/app_webview/Cookies' """ import os import sqlite3 from modules.helpers.ddg_path_handler import process_directory_paths query_cookies = """ SELECT host_key, path, name, value, creation_utc, last_access_utc, expires_utc, secure, httponly, persistent, ...

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107

0.663514

190

1,480

4.947368

0.452632

0.042553

0.07234

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0.091489

0

0.008651

0.218919

1,480

56

108

26.428571

0.804498

0.102703

0

0.090909

0

0.323147

0.058824

0

1

0.022727

false

0

0.068182

0

0.136364

0

null

0

null

0

1

0

11c4b04fb594071b02b7ee34e2b0b343fa536a12

3,382

py

Python

scripts/redis_performance_test.py

Robbybp/IDAES-CLC

5498aeab070afe5f3dc57be4cd198250f0f88ff9

[ "MIT" ]

null

scripts/redis_performance_test.py

Robbybp/IDAES-CLC

5498aeab070afe5f3dc57be4cd198250f0f88ff9

[ "MIT" ]

1

2021-06-01T23:42:14.000Z

scripts/redis_performance_test.py

Robbybp/IDAES-CLC

5498aeab070afe5f3dc57be4cd198250f0f88ff9

[ "MIT" ]

null

""" A simple and short Redis performance test. """ __author__ = 'Dan Gunter <dkgunter@lbl.gov>' __date__ = '8/8/16' import argparse import logging import os import redis import subprocess import sys import time _log = logging.getLogger(__name__) _h = logging.StreamHandler() _h.setFormatter(logging.Formatter('%(asctim...

28.661017

104

0.59521

469

3,382

4.121535

0.302772

0.053802

0.032592

0.033626

0.1821

0.148474

0.107087

0.092085

0.065184

0

0.017221

0.24453

3,382

117

105

28.905983

0.739335

0.0411

0

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0

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0

1

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false

0

0.072165

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0.226804

0.020619

0

null

0

null

0

1

0

11c756cc812aa8aa64b2f69c97b3ae507b530f8b

1,323

py

Python

Question-1.py

sowmyamanojna/CS6910-Deep-Learning-Assignment-1

e46d3a82bdfb61d7527ed3daf9250bb4ce228854

[ "MIT" ]

null

Question-1.py

sowmyamanojna/CS6910-Deep-Learning-Assignment-1

e46d3a82bdfb61d7527ed3daf9250bb4ce228854

[ "MIT" ]

null

Question-1.py

sowmyamanojna/CS6910-Deep-Learning-Assignment-1

e46d3a82bdfb61d7527ed3daf9250bb4ce228854

[ "MIT" ]

null

print("Importing packages... ", end="") ############################################################################## import wandb import numpy as np from keras.datasets import fashion_mnist import matplotlib.pyplot as plt wandb.init(project="trail-1") print("Done!") ##################################################...

35.756757

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0.517763

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4.18239

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0.054135

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0.04812

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1,323

36

153

36.75

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0.083333

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1

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false

0

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0.208333

0.166667

0

null

0

null

0

1

0

11c77e0e125890c44783034eeeb3c9b9a0ff0a7d

1,386

py

Python

app/api/v1/task.py

coder-yuan/vue-template-api

135f13d7c32b4a2830366fc0b79a1e2a1eda6923

[ "MIT" ]

null

app/api/v1/task.py

coder-yuan/vue-template-api

135f13d7c32b4a2830366fc0b79a1e2a1eda6923

[ "MIT" ]

null

app/api/v1/task.py

coder-yuan/vue-template-api

135f13d7c32b4a2830366fc0b79a1e2a1eda6923

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Project : icode_flask_be # @Package : task # @Author : jackeroo # @Time : 2019/11/29 5:25 下午 # @File : task.py # @Contact : # @Software : PyCharm # @Desc : from app.extensions import celery from flask_jwt_extended import jwt_required from app.he...

27.72

69

0.554113

159

1,386

4.754717

0.503145

0.063492

0.06746

0.087302

0.115079

0

0.018653

0.303752

1,386

49

70

28.285714

0.764767

0.219336

0

0.242424

0

0.136576

0

1

0.030303

false

0

0.121212

0

0.181818

0.030303

0

null

0

null

0

1

0

11cc4762ea46108968ee8aa2c98fc1627da5eca3

981

py

Python

pypy/jit/codegen/ppc/test/test_rgenop.py

camillobruni/pygirl

ddbd442d53061d6ff4af831c1eab153bcc771b5a

[ "MIT" ]

12

2016-01-06T07:10:28.000Z

2021-05-13T23:02:02.000Z

pypy/jit/codegen/ppc/test/test_rgenop.py

camillobruni/pygirl

ddbd442d53061d6ff4af831c1eab153bcc771b5a

[ "MIT" ]

null

pypy/jit/codegen/ppc/test/test_rgenop.py

camillobruni/pygirl

ddbd442d53061d6ff4af831c1eab153bcc771b5a

[ "MIT" ]

2

2016-07-29T07:09:50.000Z

2016-10-16T08:50:26.000Z

import py from pypy.jit.codegen.ppc.rgenop import RPPCGenOp from pypy.rpython.lltypesystem import lltype from pypy.jit.codegen.test.rgenop_tests import AbstractRGenOpTests, FUNC, FUNC2 from ctypes import cast, c_int, c_void_p, CFUNCTYPE from pypy.jit.codegen.ppc import instruction as insn # for the individual tests se...

29.727273

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0.755352

118

981

6.194915

0.542373

0.043776

0.045144

0.073871

0.057456

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0.004813

0.152905

981

32

80

30.65625

0.87485

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0.056707

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1

0.045455

false

0

0.272727

0

0.772727

0

null

0

null

0

1

0

11cd2cba6c6fa6a758300d6008e0f69f4e32d609

996

py

Python

app/someapp/views.py

artas728/monitoring-example-prometheus-grafana

2d72f29c19e8a280eca82ca1f25a7fa88453559c

[ "MIT" ]

null

app/someapp/views.py

artas728/monitoring-example-prometheus-grafana

2d72f29c19e8a280eca82ca1f25a7fa88453559c

[ "MIT" ]

null

app/someapp/views.py

artas728/monitoring-example-prometheus-grafana

2d72f29c19e8a280eca82ca1f25a7fa88453559c

[ "MIT" ]

null

from django.shortcuts import render from django.views.decorators.csrf import csrf_exempt from django.http import JsonResponse from .models import TestModel import json import redis import time redis_cli = redis.Redis(host='127.0.0.1', port=6379, db=0) @csrf_exempt def save_to_redis(request): data = json.loads(req...

29.294118

73

0.638554

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996

4.815385

0.423077

0.063898

0.0623

0.138978

0.285942

0.127796

0

0.027487

0.232932

996

33

74

30.181818

0.791885

0

0.185185

0

0.108652

0

1

0.111111

false

0

0.259259

0

0.481481

0

null

0

null

0

1

0

11d1192c076a5c79df7f15736899d5d72fa6cb5f

1,401

py

Python

NewEventReporter/blockmanager/blockmanager.py

Deofex/GETNFTBOTV3

0b8f1a77925b8f87224b2eaae93560e154b881b8

[ "MIT" ]

null

NewEventReporter/blockmanager/blockmanager.py

Deofex/GETNFTBOTV3

0b8f1a77925b8f87224b2eaae93560e154b881b8

[ "MIT" ]

null

NewEventReporter/blockmanager/blockmanager.py

Deofex/GETNFTBOTV3

0b8f1a77925b8f87224b2eaae93560e154b881b8

[ "MIT" ]

null

import logging import json import os # Initialize logger logger = logging.getLogger(__name__) class BlockManager(): def __init__(self, config, processedblock=0): logger.info('Initialize Block Manager') self.processedblock = int(processedblock) self.config = config if os.path.isfile...

31.133333

72

0.660243

145

1,401

6.22069

0.4

0.055432

0.10643

0.077605

0

0.012241

0.24197

1,401

44

73

31.840909

0.8371

0.012134

0

0.057143

0

0.149783

0.02026

0

1

0.114286

false

0

0.085714

0.028571

0.285714

0.028571

0

null

0

null

0

1

0

11d3d683bc5376ecd600cfbd620489e72ca787ca

5,299

py

Python

nmf_eval.py

logan-wright/INMF

611ccdfd4608ec37629975d04e013ab97e05ff31

[ "Apache-2.0" ]

2

2017-06-16T19:18:53.000Z

2019-04-18T02:11:45.000Z

nmf_eval.py

logan-wright/INMF

611ccdfd4608ec37629975d04e013ab97e05ff31

[ "Apache-2.0" ]

null

nmf_eval.py

logan-wright/INMF

611ccdfd4608ec37629975d04e013ab97e05ff31

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Mar 23 20:35:49 2017 @author: wrightad """ import numpy as N import matplotlib.pyplot as plt def rmse(v1,v2): ''' rmse(v1,v2) - Calculates the root mean square error between two vectors Version 1.0 Created On: Apr 17, 2017 Last Mo...

32.509202

150

0.60351

749

5,299

4.268358

0.344459

0.027526

0.014076

0.020019

0.357523

0.329371

0.30685

0.238974

0

0.072618

0.308738

5,299

163

151

32.509202

0.799618

0.647481

0

0.027517

0

1

0.086957

false

0

0.043478

0

0.217391

0.021739

0

null

0

null

0

1

0

11d8b360dafd771af3d50fb23f126c256bc27cc5

423

py

Python

recieve.py

RyuYamamoto/inter-process-communication-py

377c73833f230ba1132006c2cda86decd3580a5b

[ "MIT" ]

null

recieve.py

RyuYamamoto/inter-process-communication-py

377c73833f230ba1132006c2cda86decd3580a5b

[ "MIT" ]

null

recieve.py

RyuYamamoto/inter-process-communication-py

377c73833f230ba1132006c2cda86decd3580a5b

[ "MIT" ]

null

import socket with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind(('127.0.0.1', 50007)) s.listen(1) while True: conn, addr = s.accept() with conn: while True: data = conn.recv(1024) if not data: break ...

28.2

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52

423

3.923077

0.615385

0.117647

0

0.061069

0.380615

423

14

62

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0.717557

0

0.153846

0

0.085106

0

1

0

false

0

0.076923

0

0.076923

0

null

0

null

0

1

0

11dc5601e32f2a14e2e6dbd6c443d6cb0fdbc322

4,503

py

Python

utils.py

bbpp222006/elec_nose_plus

d79faa47d3fbb63c697501dd521e834bcc8e4814

[ "MIT" ]

1

2021-04-08T04:17:04.000Z

utils.py

bbpp222006/elec_nose_plus

d79faa47d3fbb63c697501dd521e834bcc8e4814

[ "MIT" ]

null

utils.py

bbpp222006/elec_nose_plus

d79faa47d3fbb63c697501dd521e834bcc8e4814

[ "MIT" ]

null

#!/usr/bin/python # encoding: utf-8 #!/usr/bin/python # encoding: utf-8 import torch import torch.nn as nn from torch.autograd import Variable import collections from tqdm import tqdm import numpy as np import cv2 import os import random from sklearn.cluster import KMeans import matplotlib.pyplot as plt class strL...

27.457317

143

0.584055

628

4,503

4.092357

0.281847

0.045525

0.046693

0.059144

0.224903

0.193774

0.168872

0

0.015105

0.279591

4,503

163

144

27.625767

0.777127

0.282034

0

0.068966

0

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0

1

0.114943

false

0

0.126437

0

0.321839

0

null

0

null

0

1

0

11dc7d7484bc78800544b03df7488f722be7a5ea

2,729

py

Python

down.py

pcahan1/CellNet_Cloud

a228953946b81ccb304fbd068e33766e134103b6

[ "MIT" ]

1

2020-11-13T10:53:27.000Z

down.py

pcahan1/CellNet_Cloud

a228953946b81ccb304fbd068e33766e134103b6

[ "MIT" ]

2

2020-06-28T18:17:59.000Z

2020-12-18T14:11:29.000Z

down.py

pcahan1/CellNet_Cloud

a228953946b81ccb304fbd068e33766e134103b6

[ "MIT" ]

null

#!/usr/bin/env python from __future__ import division import random import argparse import os parser = argparse.ArgumentParser() parser.add_argument("input", help="input FASTQ Directory") parser.add_argument("-n", "--number", type=int, help="number of reads to sample") args = parser.parse_args() random.seed(12) if ...

35.907895

118

0.629901

357

2,729

4.703081

0.366947

0.028588

0.038714

0.02025

0.214413

0.113163

0

0.019307

0.259802

2,729

75

119

36.386667

0.811881

0.027116

0

0.135593

0

0.30279

0

1

0

false

0

0.067797

0

0.067797

0.220339

0

null

0

null

0

1

0

11deda09dc4cd77f3a703e78c0ad5fb515e8de96

3,507

py

Python

CSR/utility.py

MoreNiceJay/CAmanager_web

29c6e35b9b1b9e8d851b2825df18e34699f6c5d2

[ "bzip2-1.0.6" ]

null

CSR/utility.py

MoreNiceJay/CAmanager_web

29c6e35b9b1b9e8d851b2825df18e34699f6c5d2

[ "bzip2-1.0.6" ]

3

2020-02-11T23:59:34.000Z

2021-06-10T21:19:16.000Z

CSR/utility.py

MoreNiceJay/CAmanager_web

29c6e35b9b1b9e8d851b2825df18e34699f6c5d2

[ "bzip2-1.0.6" ]

null

from django.shortcuts import render import sys, json, random, hashlib, calendar,time, datetime, os, random import ast from cryptography.fernet import Fernet from django.shortcuts import redirect from django.http import Http404, HttpResponse import json from cryptography.hazmat.primitives.serialization import Encoding, ...

34.722772

115

0.741374

430

3,507

5.776744

0.267442

0.128824

0.048309

0.030596

0.220209

0.192834

0.167874

0.10628

0

0.03459

0.175649

3,507

101

116

34.722772

0.824628

0.023952

0

0.206897

0

0.017539

0

1

0.126437

false

0

0.16092

0.011494

0.413793

0

null

0

null

0

1

0

11df93a40b853400f38b4c489077ebc7674cd549

51,584

py

Python

uctp_ufabc/src/uctp.py

luizfmgarcia/uctp_ufabc

2342f5431e258a4feffdf4e7931344a9d03a8f9c

[ "MIT" ]

null

uctp_ufabc/src/uctp.py

luizfmgarcia/uctp_ufabc

2342f5431e258a4feffdf4e7931344a9d03a8f9c

[ "MIT" ]

6

2018-10-30T00:37:20.000Z

2019-07-23T00:23:18.000Z

uctp_ufabc/src/uctp.py

luizfmgarcia/uctp_ufabc

2342f5431e258a4feffdf4e7931344a9d03a8f9c

[ "MIT" ]

1

2019-06-06T00:54:13.000Z

# UCTP Main Methods import objects import ioData import random # Set '1' to allow, during the run, the print on terminal of some steps printSteps = 0 #============================================================================================================== # Create the first generation of solutions def start(s...

53.015416

165

0.615462

5,815

51,584

5.386414

0.111264

0.035821

0.011494

0.007375

0.344103

0.279388

0.227189

0.199732

0.189388

0.173233

0

0.011659

0.258413

51,584

972

166

53.069959

0.807131

0.398593

0

0.219298

0

0.009807

0

1

0.063596

false

0

0.006579

0

0.122807

0.02193

0

null

0

null

0

1

0

11e388ebd565f092940b5ad2ddba87b868dac5de

3,171

py

Python

HyperV/WS2012R2/stress/StorVSCIOZoneTest.py

microsoft/FreeBSD-Test-Automation

e96a84054d771ece83908299d37e3c02a19f98b3

[ "Apache-2.0" ]

1

2020-01-16T08:45:59.000Z

HyperV/WS2012R2/stress/StorVSCIOZoneTest.py

LIS/FreeBSD-Test-Automation

e96a84054d771ece83908299d37e3c02a19f98b3

[ "Apache-2.0" ]

null

HyperV/WS2012R2/stress/StorVSCIOZoneTest.py

LIS/FreeBSD-Test-Automation

e96a84054d771ece83908299d37e3c02a19f98b3

[ "Apache-2.0" ]

1

2021-08-03T00:22:40.000Z

#!/usr/bin/env python import sys import os import time import test_class import subprocess class StorVSCIOZoneTest(test_class.TestClass): def _set_up_vm(self, vm_name, args): # this piece of code will be executed first thing after the VM is # booted up args['working_dir'] = self._test_pa...

32.030303

82

0.561337

385

3,171

4.438961

0.387013

0.051492

0.074898

0.021065

0.207139

0.189585

0.148625

0.131071

0

0.006903

0.314727

3,171

98

83

32.357143

0.779567

0.1848

0

0.20339

0

0.143414

0

1

0.152542

false

0.033898

0.084746

0

0.288136

0

null

0

null

0

1

0

11e3f9c5f47a0f678f4c4be381a8ca3e9eaec6d2

16,809

py

Python

LDDMM_Python/lddmm_python/lib/plotly/colors.py

tt6746690/lddmm-ot

98e45d44969221b0fc8206560d9b7a655ef7e137

[ "MIT" ]

48

2017-08-04T03:30:22.000Z

2022-03-09T03:24:11.000Z

LDDMM_Python/lddmm_python/lib/plotly/colors.py

hushunbo/lddmm-ot

5af26fe32ae440c598ed403ce2876e98d6e1c692

[ "MIT" ]

null

LDDMM_Python/lddmm_python/lib/plotly/colors.py

hushunbo/lddmm-ot

5af26fe32ae440c598ed403ce2876e98d6e1c692

[ "MIT" ]

15

2017-09-30T18:55:48.000Z

2021-04-27T18:27:55.000Z

""" colors ===== Functions that manipulate colors and arrays of colors There are three basic types of color types: rgb, hex and tuple: rgb - An rgb color is a string of the form 'rgb(a,b,c)' where a, b and c are floats between 0 and 255 inclusive. hex - A hex color is a string of the form '#xxxxxx' where each x is ...

32.638835

77

0.55268

2,340

16,809

3.881624

0.17906

0.007266

0.028625

0.005285

0.372234

0.320379

0.291754

0.246064

0.205879

0.173511

0

0.129802

0.304718

16,809

514

78

32.702335

0.647386

0.207567

0

0.349544

0

0.20131

0

1

0.039514

false

0

0.009119

0

0.112462

0

null

0

null

0

1

0

11e3feaa8eddda799c32e0dc2f9c36ee4b41ba9c

420

py

Python

nonebot/consts.py

he0119/nonebot2

bd7ee0a1bafc0ea7a7501ba37541349d4a81b73e

[ "MIT" ]

1

2022-01-26T12:52:33.000Z

nonebot/consts.py

he0119/nonebot2

bd7ee0a1bafc0ea7a7501ba37541349d4a81b73e

[ "MIT" ]

null

nonebot/consts.py

he0119/nonebot2

bd7ee0a1bafc0ea7a7501ba37541349d4a81b73e

[ "MIT" ]

null

# used by Matcher RECEIVE_KEY = "_receive_{id}" LAST_RECEIVE_KEY = "_last_receive" ARG_KEY = "{key}" REJECT_TARGET = "_current_target" REJECT_CACHE_TARGET = "_next_target" # used by Rule PREFIX_KEY = "_prefix" CMD_KEY = "command" RAW_CMD_KEY = "raw_command" CMD_ARG_KEY = "command_arg" SHELL_ARGS = "_args" SHELL_ARGV...

20

36

0.757143

60

420

4.7

0.433333

0.042553

0

0.128571

420

20

37

21

0.770492

0.066667

0

0.359897

0

1

0

false

0

null

0

null

0

1

0

11ed16385a989b7c743480e1ee477feb796f62cc

9,845

py

Python

iaso/tests/api/test_token.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

29

2020-12-26T07:22:19.000Z

2022-03-07T13:40:09.000Z

iaso/tests/api/test_token.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

150

2020-11-09T15:03:27.000Z

2022-03-07T15:36:07.000Z

iaso/tests/api/test_token.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

4

2020-11-09T10:38:13.000Z

2021-10-04T09:42:47.000Z

from django.test import tag from django.core.files import File from unittest import mock from iaso import models as m from iaso.test import APITestCase class TokenAPITestCase(APITestCase): @classmethod def setUpTestData(cls): data_source = m.DataSource.objects.create(name="counsil") version ...

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9,845

5.146447

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0

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0

null

0

null

0

1

0

11f229b9297d3ad1a65bef9c394df841a9ccc992

6,552

py

Python

interpro.py

TAMU-CPT/blast-db-download

53261f08d1f9193c4f538fa90983a465502190a9

[ "BSD-3-Clause" ]

null

interpro.py

TAMU-CPT/blast-db-download

53261f08d1f9193c4f538fa90983a465502190a9

[ "BSD-3-Clause" ]

3

2017-09-15T18:58:21.000Z

2020-03-24T19:11:16.000Z

interpro.py

TAMU-CPT/blast-db-download

53261f08d1f9193c4f538fa90983a465502190a9

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python import os import sys import time import datetime import logging import subprocess logging.basicConfig(level=logging.INFO) log = logging.getLogger('dl') NOW = datetime.datetime.now() SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__)) DOWNLOAD_ROOT = os.getcwd() VERSION = '5.22-61.0' PANTHER...

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0.043796

0

0.175182

0

null

0

null

0

1

0

11f3026c5b723ebaca4c3ade5e133a02d8fccef0

6,423

py

Python

Developing.../main01.py

MuhikaThomas/Pro-forma

da97d9a6581f4dfbd06fe4a0db1128ebb7472d81

[ "MIT" ]

null

Developing.../main01.py

MuhikaThomas/Pro-forma

da97d9a6581f4dfbd06fe4a0db1128ebb7472d81

[ "MIT" ]

null

Developing.../main01.py

MuhikaThomas/Pro-forma

da97d9a6581f4dfbd06fe4a0db1128ebb7472d81

[ "MIT" ]

null

import kivy from kivy.app import App from kivy.uix.tabbedpanel import TabbedPanelHeader from kivy.uix.tabbedpanel import TabbedPanel from kivy.uix.floatlayout import FloatLayout from kivy.uix.scrollview import ScrollView from kivy.uix.gridlayout import GridLayout from kivy.uix.textinput import TextInput from kivy.uix....

47.932836

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0.717422

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6,423

5.096886

0.175317

0.120163

0.079203

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0.495135

0.492193

0

0.029226

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0

0.123711

0

0.154639

0

null

0

null

0

1

0

11f30bdb0ea58245a57190b0de64ce5ae30b036d

1,943

py

Python

day8/day8.py

jwhitex/AdventOfCode2018

e552185f7d6413ccdad824911c66a6590e8de9bb

[ "MIT" ]

null

day8/day8.py

jwhitex/AdventOfCode2018

e552185f7d6413ccdad824911c66a6590e8de9bb

[ "MIT" ]

null

day8/day8.py

jwhitex/AdventOfCode2018

e552185f7d6413ccdad824911c66a6590e8de9bb

[ "MIT" ]

null

import itertools from io import StringIO from queue import LifoQueue inputs = "2 3 0 3 10 11 12 1 1 0 1 99 2 1 1 2" #data = [int(v) for v in StringIO(inputs).read().split(' ')] data = [int(v) for v in open("day8.input").read().split(' ')] def parse_packet(idata, lifoq_children, tc_metadata): if not lifoq_childre...

30.359375

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0.5965

284

1,943

3.866197

0.228873

0.095628

0.065574

0.040073

0.663024

0.601093

0.468124

0.327869

0

0.029608

0.304683

1,943

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0.783124

0.124035

0

0.5

0

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0

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0.041667

false

0

0.0625

0

0.145833

0.020833

0

null

0

null

0

1

0

11f3952caf0eac585e166a957bfe31975eafdc39

2,971

py

Python

dataset_utils/roi.py

kocurvik/retinanet_traffic_3D

592ceac767750c65bb3d6678b36e6880a7bb0403

[ "Apache-2.0" ]

12

2021-04-06T00:50:41.000Z

2022-03-23T03:27:02.000Z

dataset_utils/roi.py

kocurvik/retinanet_traffic_3D

592ceac767750c65bb3d6678b36e6880a7bb0403

[ "Apache-2.0" ]

7

2021-07-13T12:47:41.000Z

2022-03-05T15:08:51.000Z

dataset_utils/roi.py

kocurvik/retinanet_traffic_3D

592ceac767750c65bb3d6678b36e6880a7bb0403

[ "Apache-2.0" ]

4

2021-07-15T12:22:06.000Z

2022-03-01T03:12:36.000Z

import json import os import cv2 import numpy as np from dataset_utils.geometry import computeCameraCalibration def line_to_point(p1, p2, p3): return np.abs(np.cross(p2 - p1, p3 - p1, axis=2) / np.linalg.norm(p2 - p1, axis=2)) def get_pts(vid_dir, json_path): video_path = os.path.join(vid_dir, 'video.avi')...

32.648352

126

0.582969

413

2,971

4.062954

0.324455

0.032181

0.019666

0.015495

0.06913

0

0.073838

0.261528

2,971

90

127

33.011111

0.690975

0.152137

0

0.017241

0.103668

0.066986

0

0.001595

0

1

0.034483

false

0

0.086207

0.017241

0.137931

0

null

0

null

0

1

0

11f661d7ecc4156688dc11d7e9f3988ffd85ee03

1,292

py

Python

src/ansible_remote_checks/modules/check_process.py

davidvoit/ansible_remote_checks

491f31855c96297e5466b238e648fa57c1e646d0

[ "MIT" ]

null

src/ansible_remote_checks/modules/check_process.py

davidvoit/ansible_remote_checks

491f31855c96297e5466b238e648fa57c1e646d0

[ "MIT" ]

null

src/ansible_remote_checks/modules/check_process.py

davidvoit/ansible_remote_checks

491f31855c96297e5466b238e648fa57c1e646d0

[ "MIT" ]

1

2019-08-20T13:19:16.000Z

#!/usr/bin/python2 import re import subprocess from ansible.module_utils.basic import AnsibleModule def get_procs(process_regex, cmdline_regex): cmd=["ps","-hax","-o","comm pid args"] process = subprocess.Popen(cmd, stdout=subprocess.PIPE) output, error = process.communicate() lines = output.splitlines() pr...

23.490909

127

0.69195

164

1,292

5.280488

0.493902

0.069284

0.034642

0.046189

0.073903

0

0.003784

0.181889

1,292

54

128

23.925926

0.815516

0.053406

0

0.05

0

0.048321

0

1

0.05

false

0.025

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0

0.15

0

null

0

null

0

1

0

11f7ea214def9b4195dd57f26ec40b4d4be26bb2

972

py

Python

RESSPyLab/modified_cholesky.py

ioannis-vm/RESSPyLab

306fc24d5f8ece8f2f2de274b56b80ba2019f605

[ "MIT" ]

7

2019-10-15T09:16:41.000Z

2021-09-24T11:28:45.000Z

RESSPyLab/modified_cholesky.py

ioannis-vm/RESSPyLab

306fc24d5f8ece8f2f2de274b56b80ba2019f605

[ "MIT" ]

3

2020-10-22T14:27:22.000Z

2021-11-15T17:46:49.000Z

RESSPyLab/modified_cholesky.py

ioannis-vm/RESSPyLab

306fc24d5f8ece8f2f2de274b56b80ba2019f605

[ "MIT" ]

6

2019-07-22T05:47:10.000Z

2021-10-24T02:06:26.000Z

"""@package modified_cholesky Function to perform the modified Cholesky decomposition. """ import numpy as np import numpy.linalg as la def modified_cholesky(a): """ Returns the matrix A if A is positive definite, or returns a modified A that is positive definite. :param np.array a: (n, n) The symmetric matr...

31.354839

106

0.653292

137

972

4.540146

0.481752

0.11254

0.057878

0

0.026171

0.253086

972

30

107

32.4

0.830579

0.385802

0

0.005291

0

1

0.058824

false

0

0.117647

0

0.235294

0

null

0

null

0

1

0

11f9627891295b2fef341d114f820b8acfae0f4d

1,713

py

Python

estudo/bingo/bingo.py

PedroMoreira87/python

7f8ed2d17ba12a8089618477b2738e3b1c809e74

[ "MIT" ]

null

estudo/bingo/bingo.py

PedroMoreira87/python

7f8ed2d17ba12a8089618477b2738e3b1c809e74

[ "MIT" ]

null

estudo/bingo/bingo.py

PedroMoreira87/python

7f8ed2d17ba12a8089618477b2738e3b1c809e74

[ "MIT" ]

null

# Entregar arquivo com o código da função teste_cartela # # Verificador de cartela de bingo # # CRIAR UMA FUNÇÃO DO TIPO: # # def teste_cartela(numeros_bilhete,numeros_sorteados): #numeros_bilhete e numeros_sorteados tipo lista com valores inteiros # # ... # # return([bingo,n_acertos,p_acertos,[numeros_acertados],[nume...

23.148649

124

0.669002

273

1,713

4.07326

0.344322

0.08813

0.013489

0.017986

0.371403

0.357914

0.341727

0.197842

0

0.123153

0.170461

1,713

73

125

23.465753

0.659395

0.472271

0

1

0.055556

false

0

0.111111

0.055556

0

null

0

null

0

1

0

11fc76302eb18d7762bad32d8a7fb8d4acc13c44

3,033

py

Python

word_breakdown.py

imjeffhi4/word-breakdown

7edf823fbc49ac56a5dc356067938d3828edc014

[ "MIT" ]

null

word_breakdown.py

imjeffhi4/word-breakdown

7edf823fbc49ac56a5dc356067938d3828edc014

[ "MIT" ]

null

word_breakdown.py

imjeffhi4/word-breakdown

7edf823fbc49ac56a5dc356067938d3828edc014

[ "MIT" ]

null

from transformers import GPTNeoForCausalLM, GPT2Tokenizer from fastapi import FastAPI import re import json from pydantic import BaseModel from typing import Optional import torch app = FastAPI() device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") morph_path = './Model' morph_tokenizer = GPT2Toke...

40.986486

155

0.636334

362

3,033

5.185083

0.298343

0.057539

0.025573

0.038359

0.101225

0

0.006811

0.177052

3,033

73

156

41.547945

0.745192

0.092648

0

0.035088

0

0.22922

0.05346

0

1

0.070175

false

0

0.122807

0

0.298246

0

null

0

null

0

1

0

f506803cc0725d8f77786e4264a390f804bf912b

447

py

Python

ping_pong.py

kpbochenek/codewarz

20f600623bddd269fb845d06b1826c9e50b49594

[ "Apache-2.0" ]

null

ping_pong.py

kpbochenek/codewarz

20f600623bddd269fb845d06b1826c9e50b49594

[ "Apache-2.0" ]

null

ping_pong.py

kpbochenek/codewarz

20f600623bddd269fb845d06b1826c9e50b49594

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 import sys import requests ping = sys.argv[1] pong = sys.argv[2] word = sys.argv[3] if not ping.startswith('http'): ping = 'http://' + ping if not pong.startswith('http'): pong = 'http://' + pong while True: r = requests.post(ping, data={'food': word}) answer = r.text if ...

17.88

48

0.592841

65

447

4.076923

0.492308

0.079245

0

0.014706

0.239374

447

24

49

18.625

0.764706

0.04698

0

0.077647

0

1

0

false

0

0.117647

0

0.117647

0.058824

0

null

0

null

0

1

0

f506a97a368ef7e32d2a9750ae1f1a3c19762e70

437

py

Python

fenixstroy/shop/forms.py

wiky-avis/fenixstroy_shop

9e5ed0425e8fc5bcd77b7a0a640484a87c2f888c

[ "MIT" ]

null

fenixstroy/shop/forms.py

wiky-avis/fenixstroy_shop

9e5ed0425e8fc5bcd77b7a0a640484a87c2f888c

[ "MIT" ]

3

2021-09-22T18:44:30.000Z

2022-03-12T00:58:02.000Z

fenixstroy/shop/forms.py

wiky-avis/fenixstroy_shop

9e5ed0425e8fc5bcd77b7a0a640484a87c2f888c

[ "MIT" ]

null

from django import forms from .models import Comment, Rating, RatingStar class RatingForm(forms.ModelForm): star = forms.ModelChoiceField( queryset=RatingStar.objects.all(), widget=forms.RadioSelect(), empty_label=None ) class Meta: model = Rating fields = ('star'...

19.863636

47

0.631579

44

437

6.25

0.613636

0.101818

0

0.265446

437

21

48

20.809524

0.856698

0

0.133333

0

0.032037

0

1

0

false

0

0.133333

0

0.466667

0

null

0

null

0

1

0

ee921704bb61e5ef659b3c250a5774e67e1fc9fd

3,433

py

Python

lib/aquilon/consistency/checks/branch.py

ned21/aquilon

6562ea0f224cda33b72a6f7664f48d65f96bd41a

[ "Apache-2.0" ]

7

2015-07-31T05:57:30.000Z

2021-09-07T15:18:56.000Z

lib/aquilon/consistency/checks/branch.py

ned21/aquilon

6562ea0f224cda33b72a6f7664f48d65f96bd41a

[ "Apache-2.0" ]

115

2015-03-03T13:11:46.000Z

2021-09-20T12:42:24.000Z

lib/aquilon/consistency/checks/branch.py

ned21/aquilon

6562ea0f224cda33b72a6f7664f48d65f96bd41a

[ "Apache-2.0" ]

13

2015-03-03T11:17:59.000Z

2021-09-09T09:16:41.000Z

#!/usr/bin/env python # -*- cpy-indent-level: 4; indent-tabs-mode: nil -*- # ex: set expandtab softtabstop=4 shiftwidth=4: # # Copyright (C) 2013,2014,2017 Contributor # # 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...

42.9125

84

0.637635

437

3,433

4.947368

0.416476

0.044403

0.030065

0.023589

0.108233

0.06013

0.035153

0

0.007603

0.272065

3,433

79

85

43.455696

0.857543

0.377221

0

0.111111

0

0.155577

0.011967

0

1

0.027778

false

0

0.138889

0

0.194444

0

null

0

null

0

1

0

ee92be80023074621572bda99d5be62e1b63d427

1,418

py

Python

server.py

aoii103/magicworld

cad0df6aa872cd5dcd4142f83ea9fde821652551

[ "MIT" ]

7

2018-02-05T03:14:08.000Z

2019-07-28T18:49:41.000Z

server.py

aoii103/magicworld

cad0df6aa872cd5dcd4142f83ea9fde821652551

[ "MIT" ]

null

server.py

aoii103/magicworld

cad0df6aa872cd5dcd4142f83ea9fde821652551

[ "MIT" ]

3

2019-05-21T08:58:32.000Z

2019-12-26T17:03:07.000Z

import json import os from extra import MainStart import threading import moment from jinja2 import Environment, PackageLoader from sanic import Sanic, response from sanic.log import logger from termcolor import colored from conf import config from spider import bot env = Environment(loader=PackageLoad...

26.754717

81

0.648096

180

1,418

4.983333

0.45

0.06243

0.031215

0.046823

0.06243

0

0.005391

0.215092

1,418

52

82

27.269231

0.800539

0

0.101025

0.024158

0

1

0.025

false

0

0.275

0

0.4

0

null

0

null

0

1

0

ee9c514425fe52fb6f66f62ee9d6108d08382363

5,332

py

Python

solutions/solution_14.py

claudiobierig/adventofcode19

40dabd7c780ab1cd8bad4292550cd9dd1d178365

[ "MIT" ]

null

solutions/solution_14.py

claudiobierig/adventofcode19

40dabd7c780ab1cd8bad4292550cd9dd1d178365

[ "MIT" ]

null

solutions/solution_14.py

claudiobierig/adventofcode19

40dabd7c780ab1cd8bad4292550cd9dd1d178365

[ "MIT" ]

null

#!/usr/bin/env python import math def read_input(path): with open(path) as file: reactions = [line.strip().split('=>') for line in file.readlines()] reactions2 = [[r[0].strip().split(","), r[1].strip()] for r in reactions] result = {} for reaction in reactions2: goal = ...

45.186441

693

0.564891

715

5,332

4.106294

0.202797

0.057902

0.049046

0.067439

0.438011

0.396117

0.361035

0.344005

0

0.054568

0.240435

5,332

117

694

45.57265

0.67037

0.370968

0

0.125

0

0.022685

0

1

0.05

false

0

0.0125

0

0.1125

0.05

0

null

0

null

0

1

0

ee9daa8c3f24ee0e5956c82c505b318b5493b1d6

471

py

Python

src/actions/action_sleep.py

JohnVillalovos/webhook-proxy

fbb2df31b10a0c3ffb9572a0abde4df7e1ad2ef3

[ "MIT" ]

null

src/actions/action_sleep.py

JohnVillalovos/webhook-proxy

fbb2df31b10a0c3ffb9572a0abde4df7e1ad2ef3

[ "MIT" ]

null

src/actions/action_sleep.py

JohnVillalovos/webhook-proxy

fbb2df31b10a0c3ffb9572a0abde4df7e1ad2ef3

[ "MIT" ]

null

import time from actions import Action, action @action("sleep") class SleepAction(Action): def __init__( self, seconds, output="Waiting {{ seconds }} seconds before continuing ..." ): self.seconds = seconds self.output_format = output def _run(self): seconds = float(self....

23.55

83

0.673036

54

471

5.62963

0.444444

0.144737

0.105263

0.144737

0

0.218684

471

19

84

24.789474

0.826087

0

0.118896

0

1

0.153846

false

0

0.153846

0

0.384615

0.076923

0

null

0

null

0

1

0

ee9fab028e33102060e656a46df7bd6afed90358

1,262

py

Python

a1d05eba1/special_fields/choice_filter.py

dorey/a1d05eba1

eb6f66a946f3c417ab6bf9047ba9715be071967c

[ "0BSD" ]

null

a1d05eba1/special_fields/choice_filter.py

dorey/a1d05eba1

eb6f66a946f3c417ab6bf9047ba9715be071967c

[ "0BSD" ]

28

2020-06-23T19:00:58.000Z

2021-03-26T22:13:07.000Z

a1d05eba1/special_fields/choice_filter.py

dorey/a1d05eba1

eb6f66a946f3c417ab6bf9047ba9715be071967c

[ "0BSD" ]

null

from ..utils.kfrozendict import kfrozendict from ..utils.kfrozendict import kassertfrozen class ChoiceFilter: ROW_KEYS = { '1': ['choice_filter'], '2': ['choice_filter'], } EXPORT_KEY = 'choice_filter' @classmethod def in_row(kls, row, schema): return 'choice_filter' in ro...

28.044444

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1,262

5.071429

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0.169014

0.067606

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44

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28.681818

0.79684

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0.111111

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0.108927

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0.361111

0

null

0

null

0

1

0

ee9ff38e8ac3eaab8a58f8de6b4ed70735c17d0f

3,878

py

Python

hamster_control_test_version.py

iamnotmarcel/HamsterModell

ce8391e8e120e2cf957f9d49e812be3c4f757f75

[ "MIT" ]

null

hamster_control_test_version.py

iamnotmarcel/HamsterModell

ce8391e8e120e2cf957f9d49e812be3c4f757f75

[ "MIT" ]

1

2022-03-26T17:27:30.000Z

hamster_control_test_version.py

iamnotmarcel/HamsterModell

ce8391e8e120e2cf957f9d49e812be3c4f757f75

[ "MIT" ]

null

''' Author: Marcel Miljak Klasse: 5aHEL - HTL Anichstraße Diplomarbeit: Entwicklung eines Hamster Roboters Jahrgang: 2021/22 ''' import time from time import sleep import RPi.GPIO as GPIO DIR_2 = 18 # Direction-Pin vom 2ten Modul DIR_1 = 24 # Direction-pin vom 1sten Modul STEP_1 = 25 # ...

22.678363

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3,878

4.250958

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0.063091

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0.166291

0.136548

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3,878

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71

22.678363

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0.043956

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null

0

null

0

1

0

eea2f57d28acf6796635f1259b4f5d6adad79071

7,980

py

Python

codeball/tests/test_models.py

metrica-sports/codeball

60bfe54b7898bed87cbbbae9dfc0f3bc49d31025

[ "MIT" ]

54

2020-09-16T13:09:03.000Z

2022-03-28T12:32:19.000Z

codeball/tests/test_models.py

metrica-sports/codeball

60bfe54b7898bed87cbbbae9dfc0f3bc49d31025

[ "MIT" ]

null

codeball/tests/test_models.py

metrica-sports/codeball

60bfe54b7898bed87cbbbae9dfc0f3bc49d31025

[ "MIT" ]

9

2021-03-28T13:02:57.000Z

2022-03-24T11:19:06.000Z

import os import pandas as pd from kloppy import ( load_epts_tracking_data, to_pandas, load_metrica_json_event_data, load_xml_code_data, ) from codeball import ( GameDataset, DataType, TrackingFrame, EventsFrame, CodesFrame, PossessionsFrame, BaseFrame, Zones, Area...

30.930233

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938

7,980

4.76226

0.168444

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0.028655

0.046564

0.533244

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0.46116

0.40094

0.376091

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0.014925

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0.00995

0.129353

0

null

0

null

0

1

0

eea44ef30a81ba67ad14a68694b3cdcb38fe067e

1,686

py

Python

cv_workshops/6-day/2-clazz.py

afterloe/opencv-practice

83d76132d004ebbc96d99d34a0fd3fc37a044f9f

[ "MIT" ]

5

2020-03-13T07:34:30.000Z

2021-10-01T03:03:05.000Z

cv_workshops/6-day/2-clazz.py

afterloe/Opencv-practice

83d76132d004ebbc96d99d34a0fd3fc37a044f9f

[ "MIT" ]

null

cv_workshops/6-day/2-clazz.py

afterloe/Opencv-practice

83d76132d004ebbc96d99d34a0fd3fc37a044f9f

[ "MIT" ]

1

2020-03-01T13:21:43.000Z

#!/usr/bin/env python3 # -*- coding=utf-8 -*- import cv2 as cv import numpy as np """ 使用几何矩计算轮廓中心与横纵波比对过滤对二值图像的各个轮廓进行计算获得对应的几何矩，根据几何矩计算轮廓点的中心位置。 cv.moments(contours, binaryImage) - contours: 轮廓点集 - binaryImage: bool, default False；二值图返回 """ def main(): ...

31.811321

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0.027778

0

null

0

null

0

1

0

eea747f6a5f58fa9f7cb6e82312ed9dadca75ac3

1,967

py

Python

war.py

Eduardojvr/Space_Atack_Game

f37e1891bf00af71f3c1758a0288a6b0b830bb9e

[ "MIT" ]

null

war.py

Eduardojvr/Space_Atack_Game

f37e1891bf00af71f3c1758a0288a6b0b830bb9e

[ "MIT" ]

null

war.py

Eduardojvr/Space_Atack_Game

f37e1891bf00af71f3c1758a0288a6b0b830bb9e

[ "MIT" ]

null

from settings import Settings from ship import Ship import pygame import sys from trap import Trap from time import clock from random import randint def run_game(): tela1 = Settings() screen = pygame.display.set_mode((tela1.altura, tela1.largura)) background = Settings() pygame.display.set_caption("Spa...

32.245902

101

0.516523

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1,967

4.379913

0.323144

0.02991

0.069791

0.074776

0.229312

0.207378

0.065803

0

0.034215

0.346213

1,967

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32.783333

0.745723

0.016268

0

0.0625

0

0.015533

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1

0.020833

false

0

0.145833

0

0.166667

0

null

0

null

0

1

0

eea8fc748971275806d47350049795a3a98b474a

1,463

py

Python

Project-2/doc/contingency_mat_parser.py

TooSchoolForCool/EE219-Larger-Scale-Data-Mining

9a42c88169ace88f9b652d0e174c7f641fcc522e

[ "Apache-2.0" ]

null

Project-2/doc/contingency_mat_parser.py

TooSchoolForCool/EE219-Larger-Scale-Data-Mining

9a42c88169ace88f9b652d0e174c7f641fcc522e

[ "Apache-2.0" ]

12

2020-01-28T22:09:15.000Z

2022-03-11T23:16:26.000Z

Project-2/doc/contingency_mat_parser.py

TooSchoolForCool/EE219-Larger-Scale-Data-Mining

9a42c88169ace88f9b652d0e174c7f641fcc522e

[ "Apache-2.0" ]

null

import sys import argparse def read_in(file_path): try: file = open(file_path, 'r') except: sys.stderr.write("[ERROR] read_in(): Cannot open file '%s'\n" % file_path) exit(1) file_content = [] for line in file: file_content.append(line) i = 0 while i < len(fi...

21.835821

82

0.514012

189

1,463

3.830688

0.354497

0.106354

0.062155

0.066298

0.176796

0

0.010101

0.323308

1,463

67

83

21.835821

0.721212

0

0.12766

0

0.117486

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1

0.06383

false

0

0.042553

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0.148936

0.106383

0

null

0

null

0

1

0

eea9326c5e16b9ddd8185aff0917cab86602e465

5,426

py

Python

voldemort_client/helper.py

mirko-lelansky/voldemort-client

a2839a0cc50ca4fdc5bdb36b2df3a3cf7f7d9db9

[ "Apache-2.0" ]

null

voldemort_client/helper.py

mirko-lelansky/voldemort-client

a2839a0cc50ca4fdc5bdb36b2df3a3cf7f7d9db9

[ "Apache-2.0" ]

null

voldemort_client/helper.py

mirko-lelansky/voldemort-client

a2839a0cc50ca4fdc5bdb36b2df3a3cf7f7d9db9

[ "Apache-2.0" ]

null

# Copyright 2017 Mirko Lelansky <mlelansky@mail.de> # # 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 a...

29.32973

82

0.651493

712

5,426

4.837079

0.247191

0.076655

0.042683

0.027584

0.360046

0.308653

0.265679

0.230836

0.207317

0

0.003255

0.263914

5,426

184

83

29.48913

0.859039

0.490232

0

0.096154

0

0.144118

0.022689

0

1

0.134615

false

0

0.057692

0

0.326923

0

null

0

null

0

1

0

eea9c161475ffd63195c5ca94c42455b4deb9625

1,581

py

Python

src/reddack/exceptions.py

diatomicDisaster/Reddit-Slackbot

4f22af110e72eab19d9162a4428800a1895303f3

[ "MIT" ]

null

src/reddack/exceptions.py

diatomicDisaster/Reddit-Slackbot

4f22af110e72eab19d9162a4428800a1895303f3

[ "MIT" ]

10

2022-02-21T01:11:20.000Z

2022-02-22T18:13:00.000Z

src/reddack/exceptions.py

diatomicDisaster/redack

4f22af110e72eab19d9162a4428800a1895303f3

[ "MIT" ]

null

from __future__ import ( annotations, ) class ModFromSlackError(Exception): """Base class for modfromslack errors""" def __init__( self, message: str, *, preamble: str | None = None, afterword: str | None = None ) -> None: if preamble is not None: ...

26.79661

86

0.573688

153

1,581

5.640523

0.392157

0.06489

0.050985

0.044032

0.229432

0.099652

0

0.324478

1,581

58

87

27.258621

0.808052

0.117647

0

0.416667

0

0.132213

0.017531

0

1

0.0625

false

0

0.020833

0

0.1875

0

null

0

null

0

1

0

eeaa2be76b33b3286d73455fcb963e240ddf8af4

7,276

py

Python

cid/cli/cli_generator.py

zeljko-bal/CID

52ecc445c441ec63386c9f092b226090588a3789

[ "MIT" ]

1

2017-09-15T06:14:54.000Z

cid/cli/cli_generator.py

zeljko-bal/CID

52ecc445c441ec63386c9f092b226090588a3789

[ "MIT" ]

null

cid/cli/cli_generator.py

zeljko-bal/CID

52ecc445c441ec63386c9f092b226090588a3789

[ "MIT" ]

null

from collections import defaultdict from os import makedirs from os.path import realpath, join, dirname, isdir, exists from shutil import copy from jinja2 import Environment, FileSystemLoader from cid.cli.cli_model_specs import CliModelSpecs from cid.cli import cli_post_processing from cid.parser.cid_parser import pa...

42.8

177

0.67276

827

7,276

5.625151

0.170496

0.054385

0.061264

0.027085

0.344153

0.280739

0.269132

0.231298

0.126397

0.092003

0

0.000518

0.204233

7,276

169

178

43.053254

0.802936

0.03807

0

0.128205

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0.128414

0.057343

0

1

0.076923

false

0

0.08547

0.017094

0.213675

0.076923

0

null

0

null

0

1

0

eeaa72a12bf7e9c9d8b1d3537dc9a129425ee115

2,037

py

Python

container/sample-inf1/inf1_mx.py

yunma10/neo-ai-dlr

1f5c65d9bf7155c016e5d2f78d273755760a4f2a

[ "Apache-2.0" ]

446

2019-01-24T02:04:17.000Z

2022-03-16T13:45:32.000Z

container/sample-inf1/inf1_mx.py

yunma10/neo-ai-dlr

1f5c65d9bf7155c016e5d2f78d273755760a4f2a

[ "Apache-2.0" ]

179

2019-01-24T10:03:34.000Z

2022-03-19T02:06:56.000Z

container/sample-inf1/inf1_mx.py

yunma10/neo-ai-dlr

1f5c65d9bf7155c016e5d2f78d273755760a4f2a

[ "Apache-2.0" ]

111

2019-01-24T20:51:45.000Z

2022-02-18T06:22:40.000Z

import mxnet as mx #import neomxnet import os import json import numpy as np from collections import namedtuple import os dtype='float32' Batch = namedtuple('Batch', ['data']) ctx = mx.neuron() is_gpu = False def model_fn(model_dir): print("param {}".format(os.environ.get('MODEL_NAME_CUSTOM'))) print("ctx {}".form...

37.722222

121

0.675994

307

2,037

4.348534

0.413681

0.031461

0.026217

0.025468

0.142322

0.101873

0.061423

0

0.058507

0.177712

2,037

53

122

38.433962

0.738507

0.192931

0

0.052632

0

0.046354

0

1

0.052632

false

0

0.157895

0

0.263158

0.052632

0

null

0

null

0

1

0

eeab90972c87f9c41713b77c4809b4a9c645a33d

4,040

py

Python

data/process_data.py

KCKhoo/disaster_response_dashboard

ee337125121664503675bfb5bf01af85c7c1a8ca

[ "FTL", "CNRI-Python", "blessing" ]

null

data/process_data.py

KCKhoo/disaster_response_dashboard

ee337125121664503675bfb5bf01af85c7c1a8ca

[ "FTL", "CNRI-Python", "blessing" ]

null

data/process_data.py

KCKhoo/disaster_response_dashboard

ee337125121664503675bfb5bf01af85c7c1a8ca

[ "FTL", "CNRI-Python", "blessing" ]

null

import sys import pandas as pd from sqlalchemy import create_engine def load_data(messages_filepath, categories_filepath): ''' Load and merge two CSV files - one containing messages and the other containing categories Args: messages_filepath (str): Path to the CSV file containing messages ...

33.94958

98

0.658168

506

4,040

5.140316

0.3083

0.040369

0.017301

0.052288

0.117647

0.089965

0.05767

0.02922

0

0.007002

0.257673

4,040

119

99

33.94958

0.860287

0.392822

0

0.218709

0.019056

0

1

0.088889

false

0

0.066667

0

0.2

0.111111

0

null

0

null

0

1

0

eeacff18635731300c340b2e253ce1bf7ee2b4e0

3,432

py

Python

pycle/bicycle-scrapes/bike-data-scrape/scraperMulti.py

fusuyfusuy/School-Projects

8e38f19da90f63ac9c9ec91e550fc5aaab3d0234

[ "MIT" ]

null

pycle/bicycle-scrapes/bike-data-scrape/scraperMulti.py

fusuyfusuy/School-Projects

8e38f19da90f63ac9c9ec91e550fc5aaab3d0234

[ "MIT" ]

null

pycle/bicycle-scrapes/bike-data-scrape/scraperMulti.py

fusuyfusuy/School-Projects

8e38f19da90f63ac9c9ec91e550fc5aaab3d0234

[ "MIT" ]

null

from bs4 import BeautifulSoup import os import csv bicycles = [] basepath = 'HTMLFiles/' outputFile = open('scraped.py','a') outputFile.write("list=[") len1 = len(os.listdir(basepath)) counter1 = 0 for entry in os.listdir(basepath): counter2 = 0 len2 = len(os.listdir(basepath+'/'+entry)) for folder in os....

28.840336

106

0.456002

300

3,432

5.183333

0.4

0.038585

0.04373

0.025723

0.195498

0.155627

0

0.00917

0.36451

3,432

119

107

28.840336

0.703806

0.059149

0

0.083333

0

0.315447

0.024504

0

1

0

false

0

0.041667

0

0.041667

0

null

0

null

0

1

0

eeb69df1582f775092e1af736d2173a50d2365bb

484

py

Python

tests/test_lines_count.py

MacHu-GWU/single_file_module-project

01f7a6b250853bebfd73de275895bf274325cfc1

[ "MIT" ]

3

2017-02-27T05:07:46.000Z

2022-01-17T06:46:20.000Z

tests/test_lines_count.py

MacHu-GWU/single_file_module-project

01f7a6b250853bebfd73de275895bf274325cfc1

[ "MIT" ]

null

tests/test_lines_count.py

MacHu-GWU/single_file_module-project

01f7a6b250853bebfd73de275895bf274325cfc1

[ "MIT" ]

1

2017-09-05T14:05:55.000Z

# -*- coding: utf-8 -*- import os import pytest from sfm import lines_count def test_lines_count(): assert lines_count.count_lines(__file__) >= 22 def test_lines_stats(): n_files, n_lines = lines_count.lines_stats( os.path.dirname(__file__), lines_count.filter_python_script) assert n_files >= 1...

20.166667

68

0.688017

68

484

4.367647

0.470588

0.16835

0.080808

0

0.022901

0.188017

484

23

69

21.043478

0.732824

0.043388

0

0.142857

0

0.045553

0

0.214286

1

0.142857

false

0

0.285714

0

0.428571

0

null

0

null

0

1

0

eebdcac25970fd8db9e1b4ca1a89af16a4e7a240

803

py

Python

slushtools/string/__init__.py

ZackPaceCoder/slushtools

32bfee028d30fd8fd88e332bdd744a71e51d6dcc

[ "MIT" ]

null

slushtools/string/__init__.py

ZackPaceCoder/slushtools

32bfee028d30fd8fd88e332bdd744a71e51d6dcc

[ "MIT" ]

null

slushtools/string/__init__.py

ZackPaceCoder/slushtools

32bfee028d30fd8fd88e332bdd744a71e51d6dcc

[ "MIT" ]

null

# Slush Tools STRING Module class String: bu = None dat = None def __init__(str): if str == None: print("String argument required.") exit() else: dat = str bu = str return dat def reset(): dat = bu return dat def format(type="custom",args={}): if type == "cus...

20.075

48

0.523039

106

803

3.924528

0.377358

0.129808

0.086538

0.072115

0

0.354919

803

39

49

20.589744

0.803089

0.031133

0

0.27027

0

0.07732

0

1

0.162162

false

0

0.027027

0.459459

0.054054

0

null

0

null

0

1

0

eebe3ee2689c486643e9c66684f0834e67a050c1

2,001

py

Python

lib/gams/general_utils.py

zzzace2000/nodegam

79c8675e65d75237f2e853ae55bbc40ae7124ee9

[ "MIT" ]

7

2021-11-06T14:26:07.000Z

2022-03-17T10:27:17.000Z

lib/gams/general_utils.py

zzzace2000/node

4501233177173ee9b246a5a5e462afd3b1d51bbb

[ "MIT" ]

1

2022-03-22T01:08:27.000Z

2022-03-22T17:19:50.000Z

lib/gams/general_utils.py

zzzace2000/node

4501233177173ee9b246a5a5e462afd3b1d51bbb

[ "MIT" ]

1

2021-11-06T14:27:05.000Z

import time, os import numpy as np import json class Timer: def __init__(self, name, remove_start_msg=True): self.name = name self.remove_start_msg = remove_start_msg def __enter__(self): self.start_time = time.time() print('Run "%s".........' % self.name, end='\r' if self.remo...

35.105263

111

0.592704

300

2,001

3.71

0.303333

0.043127

0.022462

0.031447

0.055705

0.045822

0.034142

0

0.00766

0.282359

2,001

56

112

35.732143

0.767409

0

0.085957

0

1

0.119048

false

0

0.071429

0

0.238095

0.119048

0

null

0

null

0

1

0

eec036acad92775b225df98eed2eda788c78e178

32,553

py

Python

mindaffectBCI/decoder/utils.py

rohitvk1/pymindaffectBCI

0348784d9b0fbd9d595e31ae46d2e74632399507

[ "MIT" ]

44

2020-02-07T15:01:47.000Z

2022-03-21T14:36:15.000Z

mindaffectBCI/decoder/utils.py

CkiChen/pymindaffectBCI

0119145a8b280c776f4c4e6cd776fed0f0156404

[ "MIT" ]

17

2020-02-07T17:11:23.000Z

2022-02-20T18:01:42.000Z

mindaffectBCI/decoder/utils.py

CkiChen/pymindaffectBCI

0119145a8b280c776f4c4e6cd776fed0f0156404

[ "MIT" ]

19

2020-02-07T17:13:22.000Z

2022-03-17T01:22:35.000Z

# Copyright (c) 2019 MindAffect B.V. # Author: Jason Farquhar <jason@mindaffect.nl> # This file is part of pymindaffectBCI <https://github.com/mindaffect/pymindaffectBCI>. # # pymindaffectBCI is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published b...

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py

Python

model/test.py

yacoubb/lang-classifier

d39a342cf8ad64b191ea235f9af3f833033f254a

[ "MIT" ]

1

2019-07-03T11:28:55.000Z

model/test.py

yacoubb/lang-classifier

d39a342cf8ad64b191ea235f9af3f833033f254a

[ "MIT" ]

null

model/test.py

yacoubb/lang-classifier

d39a342cf8ad64b191ea235f9af3f833033f254a

[ "MIT" ]

null

from tensorflow import keras import os import numpy as np import sys import json sys.path.append("/".join(os.path.abspath(__file__).split("/")[:-2])) from model.dataset import utils, test_sampler def estimate_model_accuracy(model): def predict(word): word = utils.total_conversion(word) word = wor...

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eec22817edf6f5ff4caafda2c75d1273cb9edbb8

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py

Python

crawler/crawler2.py

labcontext/image-inpainting-oldpaper

da4683a2c58d662e443ea24ab93fd9d8fcb96bda

[ "Apache-2.0" ]

null

crawler/crawler2.py

labcontext/image-inpainting-oldpaper

da4683a2c58d662e443ea24ab93fd9d8fcb96bda

[ "Apache-2.0" ]

3

2021-03-19T11:16:57.000Z

2022-01-13T02:18:17.000Z

crawler/crawler2.py

labcontext/image-inpainting-oldpaper

da4683a2c58d662e443ea24ab93fd9d8fcb96bda

[ "Apache-2.0" ]

null

import requests import urllib.request import os import pickle import argparse # file read folder path = 'http://db.itkc.or.kr//data/imagedb/BOOK/ITKC_{0}/ITKC_{0}_{1}A/ITKC_{0}_{1}A_{2}{5}_{3}{4}.JPG' # Manual label = ['BT', 'MO'] middle = 1400 last = ['A', 'V'] # A ~400 V ~009 num = 10 num1 = 400 fin = ['A', 'B',...

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eeca3c40e6643d64e2cc7861e9484fa8ec9bd6f8

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py

Python

main.py

Arnav-Ghatti/Tkinter-Money-Tracker

365dcafc78522d03062a8f062fa8167b9c015583

[ "MIT" ]

null

main.py

Arnav-Ghatti/Tkinter-Money-Tracker

365dcafc78522d03062a8f062fa8167b9c015583

[ "MIT" ]

null

main.py

Arnav-Ghatti/Tkinter-Money-Tracker

365dcafc78522d03062a8f062fa8167b9c015583

[ "MIT" ]

null

import tkinter as tk from tkinter import messagebox import json # Constants FONT_NAME = "Open Sans" BG_COLOR = "#f9f7f7" FONT_COLOR = "#112d4e" ACCENT = "#dbe2ef" root = tk.Tk() root.title("Money Tracker") root.config(bg=BG_COLOR) root.resizable(0, 0) root.iconbitmap("C:\\Users\\ASUA\\Desktop\\Tests\\MoneyTransactio...

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null

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null

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eeca73f0a33396739525615f94801665b147bf27

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py

Python

empire_cellular_automaton/dataset_processing.py

ThomasMiller01/ProofOfConcept

021bf29743309224628682d0f82b0be80ae83c95

[ "MIT" ]

1

2019-12-18T13:49:22.000Z

empire_cellular_automaton/dataset_processing.py

ThomasMiller01/Experiments

021bf29743309224628682d0f82b0be80ae83c95

[ "MIT" ]

null

empire_cellular_automaton/dataset_processing.py

ThomasMiller01/Experiments

021bf29743309224628682d0f82b0be80ae83c95

[ "MIT" ]

1

2021-08-29T09:22:52.000Z

import json import matplotlib import matplotlib.pyplot as plt import numpy as np import os import time def people_distribution_map(data, file): unique, indices, counts = np.unique( data[:, 0], return_index=True, return_counts=True) generations = list(zip(unique, indices, counts)) plt_size_x = int(...

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0

null

0

null

0

1

0

eed48753201aaf2076987680b987b0334df7af1f

4,653

py

Python

cliff/lister.py

tivaliy/cliff

a04a48f4f7dc72b1bcc95a5c6a550c7650e35ab3

[ "Apache-2.0" ]

187

2015-01-13T04:07:41.000Z

2022-03-10T14:12:27.000Z

cliff/lister.py

tivaliy/cliff

a04a48f4f7dc72b1bcc95a5c6a550c7650e35ab3

[ "Apache-2.0" ]

3

2016-01-05T20:52:55.000Z

2020-10-01T06:16:58.000Z

cliff/lister.py

tivaliy/cliff

a04a48f4f7dc72b1bcc95a5c6a550c7650e35ab3

[ "Apache-2.0" ]

69

2015-02-01T01:28:37.000Z

2021-11-15T08:28:53.000Z

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

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null

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null

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eed5699e06d3cac61b4a945b53a1004046c608f3

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py

Python

task3/task3.py

ksmirenko/ml-homework

a5e558352ffc332ad5e40526dda21f205718a203

[ "MIT" ]

1

2020-08-05T08:06:33.000Z

task3/task3.py

ksmirenko/ml-homework

a5e558352ffc332ad5e40526dda21f205718a203

[ "MIT" ]

null

task3/task3.py

ksmirenko/ml-homework

a5e558352ffc332ad5e40526dda21f205718a203

[ "MIT" ]

null

from PIL import Image import numpy as np # Works when launched from terminal # noinspection PyUnresolvedReferences from k_means import k_means input_image_file = 'lena.jpg' output_image_prefix = 'out_lena' n_clusters = [2, 3, 5] max_iterations = 100 launch_count = 3 def main(): # Read input image image = np...

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0

null

0

null

0

1

0

eed63ef06321c79002e85fdaeb08205c4299ea39

3,389

py

Python

dcrnn_train.py

syin3/cs224w-traffic

284836b49404bfd38ae23b31f89f8e617548e286

[ "MIT" ]

9

2019-03-20T01:02:07.000Z

2020-11-25T06:45:30.000Z

dcrnn_train.py

syin3/cs224w-traffic

284836b49404bfd38ae23b31f89f8e617548e286

[ "MIT" ]

null

dcrnn_train.py

syin3/cs224w-traffic

284836b49404bfd38ae23b31f89f8e617548e286

[ "MIT" ]

2

2020-09-24T07:03:58.000Z

2020-11-09T04:43:03.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function import argparse import tensorflow as tf import yaml from model.dcrnn_supervisor import DCRNNSupervisor def main(args): with open(args.config_filename) as f: supervisor_config = yaml.load(f) ...

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null

0

null

0

1

0

eed698cee32da7af7d7cb366130b591986c4feae

1,035

py

Python

train.py

k2sebeom/DeepLOLCourt

630f1eee1729c06f686abc7c2a7ecbdfe66803b3

[ "MIT" ]

null

train.py

k2sebeom/DeepLOLCourt

630f1eee1729c06f686abc7c2a7ecbdfe66803b3

[ "MIT" ]

null

train.py

k2sebeom/DeepLOLCourt

630f1eee1729c06f686abc7c2a7ecbdfe66803b3

[ "MIT" ]

null

import torch.optim as optim from torch import nn from data.match_dataset import MatchDataset from torch.utils.data import DataLoader from models.lol_result_model import LOLResultModel import torch if __name__ == '__main__': EPOCH = 50 BATCH_SIZE = 32 loader = DataLoader(MatchDataset('dataset/train_data....

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