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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f0b1d2bc676f5219d5c50eeed54f3ef0c2068b76 | 243 | py | Python | contrib/enginedesign/openmdao.examples.enginedesign/openmdao/examples/enginedesign/releaseinfo.py | mjfwest/OpenMDAO-Framework | a5521f47ad7686c25b203de74e1c7dff5fd7a52b | [
"Apache-2.0"
] | 69 | 2015-01-02T19:10:08.000Z | 2021-11-14T04:42:28.000Z | contrib/enginedesign/openmdao.examples.enginedesign/openmdao/examples/enginedesign/releaseinfo.py | jcchin/OpenMDAO-Framework | 038e89b06da1c74f00918f4c6fbd8bd365e25657 | [
"Apache-2.0"
] | 3 | 2015-01-15T23:08:18.000Z | 2015-03-11T16:57:35.000Z | contrib/enginedesign/openmdao.examples.enginedesign/openmdao/examples/enginedesign/releaseinfo.py | jcchin/OpenMDAO-Framework | 038e89b06da1c74f00918f4c6fbd8bd365e25657 | [
"Apache-2.0"
] | 31 | 2015-09-16T00:37:35.000Z | 2022-01-10T06:27:55.000Z |
# This file is automatically generated
__version__ = '0.10.3.2'
__comments__ = """too many spaces :/
Merge pull request #1848 from swryan/work"""
__date__ = '2014-11-15 09:50:34 -0500'
__commit__ = '97c66aaecfad3451bc6a0b1cae1fce4c0595037a'
| 27 | 55 | 0.753086 |
f0b1f9e76ce0827997c1af6729dbd897a8b9fe82 | 779 | py | Python | Utils/get_skeleton.py | Kohulan/DECIMER-Image-Segmentation | 68ee9a9693e5bad5c41826d28e2d6558a20fe21f | [
"MIT"
] | 29 | 2021-01-08T13:48:18.000Z | 2022-01-17T08:29:00.000Z | Utils/get_skeleton.py | Kohulan/DECIMER-Image-Segmentation | 68ee9a9693e5bad5c41826d28e2d6558a20fe21f | [
"MIT"
] | 23 | 2021-01-07T21:43:21.000Z | 2022-03-14T21:52:17.000Z | Utils/get_skeleton.py | Kohulan/DECIMER-Image-Segmentation | 68ee9a9693e5bad5c41826d28e2d6558a20fe21f | [
"MIT"
] | 8 | 2021-01-08T05:39:21.000Z | 2022-02-14T10:06:38.000Z | '''
* This Software is under the MIT License
* Refer to LICENSE or https://opensource.org/licenses/MIT for more information
* Written by Kohulan Rajan 2020
'''
from skimage import img_as_float
from skimage import io, color, morphology
import matplotlib.pyplot as plt
| 32.458333 | 79 | 0.770218 |
f0b23ace85262a4a9788725f73969adf1044950b | 1,328 | py | Python | Task/CSV-to-HTML-translation/Python/csv-to-html-translation-5.py | mullikine/RosettaCodeData | 4f0027c6ce83daa36118ee8b67915a13cd23ab67 | [
"Info-ZIP"
] | 1 | 2021-05-05T13:42:20.000Z | 2021-05-05T13:42:20.000Z | Task/CSV-to-HTML-translation/Python/csv-to-html-translation-5.py | seanwallawalla-forks/RosettaCodeData | 9ad63ea473a958506c041077f1d810c0c7c8c18d | [
"Info-ZIP"
] | null | null | null | Task/CSV-to-HTML-translation/Python/csv-to-html-translation-5.py | seanwallawalla-forks/RosettaCodeData | 9ad63ea473a958506c041077f1d810c0c7c8c18d | [
"Info-ZIP"
] | null | null | null | from csv import DictReader
from xml.etree import ElementTree as ET
htmltxt = csv2html_robust(csvtxt, True, {
'TABLE': {'border': "1", 'summary': "csv2html extra program output"},
'THEAD': {'bgcolor': "yellow"},
'TBODY': {'bgcolor': "orange"}
})
print(htmltxt.decode('utf8'))
| 34.947368 | 73 | 0.618223 |
f0b260ad5df3102bf13fd8cb7dbdddf25e662251 | 2,763 | py | Python | src/gausskernel/dbmind/tools/sqldiag/load_sql_from_wdr.py | opengauss-mirror/openGauss-graph | 6beb138fd00abdbfddc999919f90371522118008 | [
"MulanPSL-1.0"
] | null | null | null | src/gausskernel/dbmind/tools/sqldiag/load_sql_from_wdr.py | opengauss-mirror/openGauss-graph | 6beb138fd00abdbfddc999919f90371522118008 | [
"MulanPSL-1.0"
] | null | null | null | src/gausskernel/dbmind/tools/sqldiag/load_sql_from_wdr.py | opengauss-mirror/openGauss-graph | 6beb138fd00abdbfddc999919f90371522118008 | [
"MulanPSL-1.0"
] | null | null | null | import os
import re
import sys
import argparse
from preprocessing import templatize_sql
from utils import DBAgent, check_time_legality
__description__ = "Get sql information based on wdr."
if __name__ == '__main__':
args = parse_args()
start_time, finish_time = args.start_time, args.finish_time
port... | 40.043478 | 113 | 0.641694 |
f0b3c832cf8e1ee83bee7a2645bdcc49172d3621 | 344 | py | Python | program_train/hachina1.py | zhujisheng/HAComponent | 29c44a5ea3090d748738830a50e2d25c07e1bac8 | [
"Apache-2.0"
] | 39 | 2017-12-17T13:51:13.000Z | 2022-02-25T02:57:39.000Z | program_train/hachina1.py | vitc-123/HAComponent | 29c44a5ea3090d748738830a50e2d25c07e1bac8 | [
"Apache-2.0"
] | 5 | 2019-05-30T07:09:49.000Z | 2021-07-15T02:53:49.000Z | program_train/hachina1.py | vitc-123/HAComponent | 29c44a5ea3090d748738830a50e2d25c07e1bac8 | [
"Apache-2.0"
] | 28 | 2018-01-05T10:48:28.000Z | 2021-12-07T13:59:22.000Z | """
hachina.py.
.
"""
def setup(hass, config):
"""HomeAssistanthachinahachina.pysetup."""
# hachina.Hello_World
# 1
# 2
hass.states.set("hachina.hello_world", "")
# True
return True
| 20.235294 | 72 | 0.671512 |
f0b5d4652c83e4ec1fe94bf488284b069e276dc7 | 4,263 | py | Python | simple_ddl_parser/dialects/hql.py | swiatek25/simple-ddl-parser | b46f99b4e1838718bc4024cd281a66cd1b78b165 | [
"MIT"
] | null | null | null | simple_ddl_parser/dialects/hql.py | swiatek25/simple-ddl-parser | b46f99b4e1838718bc4024cd281a66cd1b78b165 | [
"MIT"
] | null | null | null | simple_ddl_parser/dialects/hql.py | swiatek25/simple-ddl-parser | b46f99b4e1838718bc4024cd281a66cd1b78b165 | [
"MIT"
] | null | null | null | from simple_ddl_parser.utils import check_spec, remove_par
| 31.345588 | 74 | 0.524513 |
f0b7d59823b393f5c64dfa9a82c8f3f19e0a14bc | 5,627 | py | Python | pydaemon/tx_sms_service_.py | tmkasun/pysmsgate | 42c06f1e8e3598697844fd9b098f314a24709777 | [
"Apache-2.0"
] | null | null | null | pydaemon/tx_sms_service_.py | tmkasun/pysmsgate | 42c06f1e8e3598697844fd9b098f314a24709777 | [
"Apache-2.0"
] | null | null | null | pydaemon/tx_sms_service_.py | tmkasun/pysmsgate | 42c06f1e8e3598697844fd9b098f314a24709777 | [
"Apache-2.0"
] | null | null | null | import json
import sys
import time
from twisted.internet.task import deferLater
from twisted.web import http
from twisted.web.resource import Resource
from twisted.web.server import Site
from twisted.internet import reactor
from gsmmodem.modem import GsmModem, SentSms
from gsmmodem.exceptions import TimeoutException,... | 30.917582 | 103 | 0.602808 |
f0b7dafc2a4cbe01ebdeb4efbbb1605f26910088 | 391 | py | Python | plugins/vad/snr_vad/test_snr_vad.py | kowo-zahl/Naomi | 476cfc42036a1ac88e33451431fc64d5ea1aa49a | [
"MIT"
] | 194 | 2018-07-28T14:54:35.000Z | 2022-03-18T12:40:10.000Z | plugins/vad/snr_vad/test_snr_vad.py | HoltTechnologyCorporation/Naomi | 16d5f6ba03ea96c3fa13ed4e2c1f082041d9de31 | [
"MIT"
] | 239 | 2018-07-13T16:15:25.000Z | 2022-03-31T17:55:01.000Z | plugins/vad/snr_vad/test_snr_vad.py | Longshotpro2/Naomi | 9330c63fe24606dc45194d297c665f37a4ec10f7 | [
"MIT"
] | 64 | 2018-07-26T02:18:33.000Z | 2022-01-07T06:53:01.000Z | # -*- coding: utf-8 -*-
from naomi import testutils
from . import snr_vad
| 24.4375 | 52 | 0.641944 |
f0b832955eefe7451229c65ceb69048f96000730 | 13,243 | py | Python | dali/test/python/test_operator_rotate.py | L-Net-1992/DALI | 982224d8b53e1156ae092f73f5a7d600982a1eb9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | dali/test/python/test_operator_rotate.py | L-Net-1992/DALI | 982224d8b53e1156ae092f73f5a7d600982a1eb9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | dali/test/python/test_operator_rotate.py | L-Net-1992/DALI | 982224d8b53e1156ae092f73f5a7d600982a1eb9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | # Copyright (c) 2019-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... | 37.945559 | 131 | 0.671751 |
f0b8a938a5d0cde1b5aa321a0fcf6ce1d6ace0f2 | 524 | py | Python | graph/templatetags/helpers.py | Soaring-Outliers/news_graph | ae7cde461e49b6ee8fe932fcf6c581f3a5574da4 | [
"MIT"
] | 1 | 2015-04-19T08:26:34.000Z | 2015-04-19T08:26:34.000Z | graph/templatetags/helpers.py | Soaring-Outliers/news_graph | ae7cde461e49b6ee8fe932fcf6c581f3a5574da4 | [
"MIT"
] | 5 | 2015-04-28T07:31:22.000Z | 2015-05-11T12:47:57.000Z | graph/templatetags/helpers.py | Soaring-Outliers/news_graph | ae7cde461e49b6ee8fe932fcf6c581f3a5574da4 | [
"MIT"
] | null | null | null | from django import template
import bleach
# import the logging library
import logging
# Get an instance of a logger
logger = logging.getLogger(__name__)
register = template.Library() | 23.818182 | 79 | 0.725191 |
f0b9a9734fc82602ebc66cd8758b5aacd1abcb0d | 17,679 | py | Python | rbf/linalg.py | aaronbalzac/rbf-neural-network | 69c86ccb4e8041fdfb7ce9eff1e4db98648d6b5f | [
"MIT"
] | 1 | 2021-05-12T06:52:11.000Z | 2021-05-12T06:52:11.000Z | rbf/linalg.py | 0x41head/rbf-neural-network | 69c86ccb4e8041fdfb7ce9eff1e4db98648d6b5f | [
"MIT"
] | null | null | null | rbf/linalg.py | 0x41head/rbf-neural-network | 69c86ccb4e8041fdfb7ce9eff1e4db98648d6b5f | [
"MIT"
] | null | null | null | '''
Module for linear algebra routines.
'''
import logging
import warnings
import numpy as np
import scipy.sparse as sp
import scipy.sparse.linalg as spla
from scipy.linalg.lapack import (dpotrf, dpotrs, dtrtrs, dgetrf,
dgetrs)
from rbf.sputils import row_norms, divide_rows
LOGGER =... | 23.666667 | 79 | 0.587307 |
f0b9fbfd7322db83b4a975dbad3a4b36576b39d1 | 3,200 | py | Python | week_3/cnn.py | jimichailidis/UVA_AML18 | 620a9aba6651dd4451f5286aa250d7037673f7bf | [
"MIT"
] | null | null | null | week_3/cnn.py | jimichailidis/UVA_AML18 | 620a9aba6651dd4451f5286aa250d7037673f7bf | [
"MIT"
] | null | null | null | week_3/cnn.py | jimichailidis/UVA_AML18 | 620a9aba6651dd4451f5286aa250d7037673f7bf | [
"MIT"
] | null | null | null | #%%
import os
print(os.getcwd())
from Blocks import ReLU, SequentialNN, Dense, Hinge, SGD
from dataset_utils import load_mnist
import numpy as np
from convolution_layer import ConvLayer
from maxpool_layer import MaxPool2x2
from flatten_layer import FlattenLayer
import sys
nn = get_cnn()
loss = Hinge()
optimizer = SGD... | 31.372549 | 81 | 0.672188 |
f0ba87898e06dbbd8420e2f2f2069300ec91a8de | 25,935 | py | Python | methylprep/processing/preprocess.py | WonyoungCho/methylprep | 4e34f62be969158453ba9b05b7629433f9bbba8b | [
"MIT"
] | 5 | 2019-08-28T08:27:16.000Z | 2020-03-11T17:20:01.000Z | methylprep/processing/preprocess.py | WonyoungCho/methylprep | 4e34f62be969158453ba9b05b7629433f9bbba8b | [
"MIT"
] | 16 | 2021-04-08T22:02:58.000Z | 2022-03-18T17:30:50.000Z | methylprep/processing/preprocess.py | WonyoungCho/methylprep | 4e34f62be969158453ba9b05b7629433f9bbba8b | [
"MIT"
] | 3 | 2022-01-26T00:12:19.000Z | 2022-03-09T22:43:22.000Z | # Normal-exponential using out-of-band probes
# normex: negative control probes
# noob: out-of-band Infinium I probes
# Lib
import logging
import numpy as np
import pandas as pd
from statsmodels import robust
from scipy.stats import norm, lognorm
# App
from ..models import ControlType, ArrayType
from ..models.sketchy_... | 51.05315 | 279 | 0.662888 |
f0bac3ba5e39b1d61b8af9133f958f0f2c233ba5 | 5,041 | py | Python | examples/llvm_rl/model/inference_result.py | xtremey/CompilerGym | 2c2ceaebfccae72beb4aaacc74e0c8134c6f2ffe | [
"MIT"
] | null | null | null | examples/llvm_rl/model/inference_result.py | xtremey/CompilerGym | 2c2ceaebfccae72beb4aaacc74e0c8134c6f2ffe | [
"MIT"
] | null | null | null | examples/llvm_rl/model/inference_result.py | xtremey/CompilerGym | 2c2ceaebfccae72beb4aaacc74e0c8134c6f2ffe | [
"MIT"
] | null | null | null | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import List
import numpy as np
from pydantic import BaseModel, validator
from ray.rllib.agents.dqn import ApexTrain... | 39.382813 | 84 | 0.649276 |
f0c2b3418e682549772086df9363fdf46943f5bd | 1,322 | py | Python | fabulous/script_gen.py | FPGA-Research-Manchester/nextpnr-fabulous | 665d13010eb6ea6ccf0c6041bb9df5028983a3bf | [
"0BSD"
] | 1 | 2021-10-01T11:05:52.000Z | 2021-10-01T11:05:52.000Z | fabulous/script_gen.py | FPGA-Research-Manchester/nextpnr-fabulous | 665d13010eb6ea6ccf0c6041bb9df5028983a3bf | [
"0BSD"
] | null | null | null | fabulous/script_gen.py | FPGA-Research-Manchester/nextpnr-fabulous | 665d13010eb6ea6ccf0c6041bb9df5028983a3bf | [
"0BSD"
] | 1 | 2021-10-01T11:05:52.000Z | 2021-10-01T11:05:52.000Z | import re
from array import *
import fileinput
import sys, getopt
import csv
if __name__ == "__main__":
main(sys.argv[1:])
| 28.73913 | 141 | 0.559002 |
f0c3581446d85c97a243b1adbc5978391a877b8e | 269 | py | Python | src/app/buy_btc.py | simondorfman/hello_cb_pro | cdb96ee1390d22753630e24dac9bfdc5e47e788d | [
"MIT"
] | null | null | null | src/app/buy_btc.py | simondorfman/hello_cb_pro | cdb96ee1390d22753630e24dac9bfdc5e47e788d | [
"MIT"
] | null | null | null | src/app/buy_btc.py | simondorfman/hello_cb_pro | cdb96ee1390d22753630e24dac9bfdc5e47e788d | [
"MIT"
] | null | null | null | import os
from cbt.private_client import PrivateClient
from cbt.auth import get_new_private_connection
if __name__ == "__main__":
usd = os.getenv("USD_BUY")
auth = get_new_private_connection()
client = PrivateClient(auth)
client.market_buy_btc(usd)
| 20.692308 | 47 | 0.754647 |
f0c366363d8d56f6982ab28b3008beafae215018 | 4,836 | py | Python | sample/tensor_functions.py | TheLampshady/tensor_tutorial | a5665d05ce7fdefa4975081847ac34d44756a3d0 | [
"MIT"
] | 2 | 2018-04-19T19:33:43.000Z | 2019-03-12T05:59:52.000Z | sample/tensor_functions.py | TheLampshady/tensor_tutorial | a5665d05ce7fdefa4975081847ac34d44756a3d0 | [
"MIT"
] | null | null | null | sample/tensor_functions.py | TheLampshady/tensor_tutorial | a5665d05ce7fdefa4975081847ac34d44756a3d0 | [
"MIT"
] | null | null | null | import numpy as np
from os import getcwd, path
import scipy.misc as misc
import tensorflow as tf
from tensorflow.contrib.tensorboard.plugins import projector
def variable_summaries(var, histogram_name='histogram'):
"""
Attach a lot of summaries to a Tensor (for TensorBoard visualization).
:type var: tf.Va... | 30.225 | 96 | 0.680521 |
f0c3d53843280be100078a8627ba65bbe0348c16 | 141 | py | Python | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 63 | 2020-08-15T19:02:06.000Z | 2022-03-29T16:19:00.000Z | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 133 | 2020-08-18T03:51:05.000Z | 2022-03-05T13:43:22.000Z | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 10 | 2020-08-25T05:19:31.000Z | 2022-02-03T10:33:41.000Z | import bigflow as bf
from .job import ExampleJob
workflow1 = bf.Workflow(
workflow_id='workflow1',
definition=[ExampleJob('job1')]) | 20.142857 | 36 | 0.730496 |
f0c4871928dffeb7e7e0aad03825633ae820c35a | 2,076 | py | Python | hello/migrations/0002_auto_20201116_1409.py | chenyuan99/OwlSavesCats | d8135848db5e6092467ee0d31aa46c36599cace1 | [
"MIT"
] | null | null | null | hello/migrations/0002_auto_20201116_1409.py | chenyuan99/OwlSavesCats | d8135848db5e6092467ee0d31aa46c36599cace1 | [
"MIT"
] | null | null | null | hello/migrations/0002_auto_20201116_1409.py | chenyuan99/OwlSavesCats | d8135848db5e6092467ee0d31aa46c36599cace1 | [
"MIT"
] | null | null | null | # Generated by Django 3.0.8 on 2020-11-16 19:09
from django.db import migrations, models
import django.db.models.deletion
| 32.952381 | 114 | 0.53131 |
f0c48e7fef50233e0f0dc3c44b24dc530a2c32de | 1,307 | py | Python | Curso Em Video-python/PYTHON (MUNDO 1, MUNDO 2 E MUNDO 3)/pythonAulas/Aula18-listas-dentro-listas.py | AlamoVinicius/code-pratice | 924a3ff782caf3695bbeeac39fa02fb23781cd75 | [
"MIT"
] | null | null | null | Curso Em Video-python/PYTHON (MUNDO 1, MUNDO 2 E MUNDO 3)/pythonAulas/Aula18-listas-dentro-listas.py | AlamoVinicius/code-pratice | 924a3ff782caf3695bbeeac39fa02fb23781cd75 | [
"MIT"
] | null | null | null | Curso Em Video-python/PYTHON (MUNDO 1, MUNDO 2 E MUNDO 3)/pythonAulas/Aula18-listas-dentro-listas.py | AlamoVinicius/code-pratice | 924a3ff782caf3695bbeeac39fa02fb23781cd75 | [
"MIT"
] | null | null | null | """ aula sobre lista 18 repare como as listas podem ser incluidas dentro de uma lista. """
teste = []
teste.append('lamo')
teste.append(26)
galera = []
galera.append(teste[:]) # preciso fazer uma cpia com [:] para o sistema no duplicar
teste[0] = 'Francielli'
teste[1] = 22
galera.append(teste)
print(galera[:])
" an... | 34.394737 | 118 | 0.643458 |
f0c50e60679a31772ae1850437c877c7672b05e0 | 3,992 | py | Python | src/flups/io.py | spalato/flups | b878920b01a073938b312dccc1d30a64bc9c30e5 | [
"MIT"
] | null | null | null | src/flups/io.py | spalato/flups | b878920b01a073938b312dccc1d30a64bc9c30e5 | [
"MIT"
] | null | null | null | src/flups/io.py | spalato/flups | b878920b01a073938b312dccc1d30a64bc9c30e5 | [
"MIT"
] | null | null | null | # flups.io: tools for reading and writing files
import re
import logging
import numpy as np
from .calib import load_latest, calibration
logger = logging.getLogger(__name__)
def read_asc(fname):
"""
Read a single `asc` file, the ASCII format from Andor Solis.
"""
logger.debug("Loading `.asc` file: %s",... | 27.342466 | 100 | 0.596443 |
f0c5f63e6ccfe9b9da4d7242b7a76b297f2ab336 | 2,521 | py | Python | tests/test_text_search.py | jdvala/kulhadi | 9031d32070582fa46a74f760203882c213d02605 | [
"MIT"
] | 3 | 2021-10-31T07:02:04.000Z | 2022-01-10T12:55:27.000Z | tests/test_text_search.py | jdvala/kulhadi | 9031d32070582fa46a74f760203882c213d02605 | [
"MIT"
] | 2 | 2021-10-30T11:28:10.000Z | 2021-10-30T11:30:28.000Z | tests/test_text_search.py | jdvala/kawadi | 9031d32070582fa46a74f760203882c213d02605 | [
"MIT"
] | null | null | null | import multiprocessing as mp
import pytest
from kawadi.text_search import SearchInText
def custom_score(**kwargs):
if kwargs["slide_of_text"] == kwargs["text_to_find"]:
return 1.0
else:
return 0.0
def test_search_in_text(input_data, output) -> None:
search_text = SearchInText()
r... | 33.171053 | 459 | 0.714002 |
f0ca3d609391dc32aa46d1c4b4ec4ee3f9a34e0a | 448 | py | Python | cbandits/core/bayesian_nn.py | AlliedToasters/dev_bandits | 7e3655bd5a91854951a52d0f037ee06aefb2922c | [
"MIT"
] | null | null | null | cbandits/core/bayesian_nn.py | AlliedToasters/dev_bandits | 7e3655bd5a91854951a52d0f037ee06aefb2922c | [
"MIT"
] | null | null | null | cbandits/core/bayesian_nn.py | AlliedToasters/dev_bandits | 7e3655bd5a91854951a52d0f037ee06aefb2922c | [
"MIT"
] | null | null | null | """Define the abstract class for Bayesian Neural Networks."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
| 21.333333 | 74 | 0.694196 |
f0cb07dafe313489f043d26fe74c8e52bf97cd97 | 99 | py | Python | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | 1 | 2021-01-12T17:13:46.000Z | 2021-01-12T17:13:46.000Z | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | null | null | null | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from .MaidWhite import MaidWhite
name = "MaidWhite"
__all__ = (MaidWhite) | 16.5 | 32 | 0.676768 |
f0cb537671d132b5a4770577912b310f7cda8e12 | 832 | py | Python | app/main/config.py | leskeylevy/flaskBackend | 1cada27072517234f37991a3ef655f8c63d13867 | [
"MIT"
] | null | null | null | app/main/config.py | leskeylevy/flaskBackend | 1cada27072517234f37991a3ef655f8c63d13867 | [
"MIT"
] | null | null | null | app/main/config.py | leskeylevy/flaskBackend | 1cada27072517234f37991a3ef655f8c63d13867 | [
"MIT"
] | null | null | null | import os
basedir = os.path.abspath(os.path.dirname(__file__))
config_by_name = dict(
dev=DevelopmentConfig,
test=TestingConfig,
prod=ProductionConfig
)
key = Config.SECRET_KEY
| 21.333333 | 95 | 0.742788 |
f0cba37d4b9ac55bb211ec75a31599946da59b48 | 1,654 | py | Python | crosstab/mega_analysis/lateralised_intensities.py | karandahele/Epilepsy-Repository | 58f970b25808c0cdcd0dc44ab107cf00d9de74c2 | [
"MIT"
] | 2 | 2019-11-20T11:12:22.000Z | 2019-12-23T21:19:34.000Z | crosstab/mega_analysis/lateralised_intensities.py | karandahele/Epilepsy-Repository | 58f970b25808c0cdcd0dc44ab107cf00d9de74c2 | [
"MIT"
] | 6 | 2020-01-14T17:13:40.000Z | 2020-04-06T09:19:51.000Z | crosstab/mega_analysis/lateralised_intensities.py | karandahele/Epilepsy-Repository | 58f970b25808c0cdcd0dc44ab107cf00d9de74c2 | [
"MIT"
] | 3 | 2020-01-14T17:12:02.000Z | 2020-04-01T13:08:06.000Z | import pandas as pd
from crosstab.mega_analysis.pivot_result_to_pixel_intensities import *
def lateralisation_to_pixel_intensities(all_combined_gifs, df,
semiology_term,
quantiles, method='non-linear', scale_factor=10,
... | 50.121212 | 109 | 0.663845 |
f0cd195aebcc37de4124760ae9d1f43db09b1611 | 585 | py | Python | requests_test.py | AnakinJiang/PythonDemo | 4e8e8296b098ce541c588fafdf07cf2d6d955d38 | [
"MIT"
] | null | null | null | requests_test.py | AnakinJiang/PythonDemo | 4e8e8296b098ce541c588fafdf07cf2d6d955d38 | [
"MIT"
] | null | null | null | requests_test.py | AnakinJiang/PythonDemo | 4e8e8296b098ce541c588fafdf07cf2d6d955d38 | [
"MIT"
] | null | null | null | '''
@Author: AnakinJiang
@Email: jiangjinpeng319 AT gmail.com
@Descripttion: requestsdemo
@Date: 2019-08-27 15:37:14
@LastEditors: AnakinJiang
@LastEditTime: 2019-08-27 16:55:06
'''
import requests
get_test()
| 19.5 | 43 | 0.659829 |
f0cfaf531119941e8908019c7d9b113afa90346e | 3,536 | py | Python | allennlp/training/learning_rate_schedulers/polynomial_decay.py | alle-pawols/allennlp | 7d4a67263d7a210aca22d4f2b03e8568d3c34a48 | [
"Apache-2.0"
] | 2 | 2022-01-02T12:15:21.000Z | 2022-01-02T12:15:23.000Z | allennlp/training/learning_rate_schedulers/polynomial_decay.py | alle-pawols/allennlp | 7d4a67263d7a210aca22d4f2b03e8568d3c34a48 | [
"Apache-2.0"
] | 35 | 2021-08-11T13:20:30.000Z | 2022-03-29T13:17:39.000Z | allennlp/training/learning_rate_schedulers/polynomial_decay.py | alle-pawols/allennlp | 7d4a67263d7a210aca22d4f2b03e8568d3c34a48 | [
"Apache-2.0"
] | 1 | 2021-03-31T19:50:08.000Z | 2021-03-31T19:50:08.000Z | from overrides import overrides
import torch
from allennlp.common.checks import ConfigurationError
from allennlp.training.learning_rate_schedulers.learning_rate_scheduler import LearningRateScheduler
| 37.221053 | 114 | 0.653281 |
f0cfb602ee2a0f5bc3a7dc61c2685237a493cae5 | 2,983 | py | Python | Scripts/fill_year.py | usuallyunusual/The-Explorer | 1569e8ac01f245cf2e2333070e82ff165abeb118 | [
"MIT"
] | null | null | null | Scripts/fill_year.py | usuallyunusual/The-Explorer | 1569e8ac01f245cf2e2333070e82ff165abeb118 | [
"MIT"
] | 5 | 2021-04-01T09:48:28.000Z | 2021-04-17T09:13:06.000Z | Scripts/fill_year.py | usuallyunusual/The-Explorer | 1569e8ac01f245cf2e2333070e82ff165abeb118 | [
"MIT"
] | 1 | 2020-09-14T11:42:40.000Z | 2020-09-14T11:42:40.000Z |
"""
TO DO:
1. Lot of edge cases not accounted for
2. Could use some unit testing scripts for sanity check
3. What are the bounds for years?
"""
import mysql
from mysql.connector import Error
import re
import numpy as np
| 30.131313 | 162 | 0.526316 |
f0d055f8993a7d6c33e001e9675d7f51424a7021 | 3,505 | py | Python | tests/web/client.py | bigbluedeer/instagram_private_api | e92b6f0b1904d25edf7ad02bc4c270627f461733 | [
"MIT"
] | null | null | null | tests/web/client.py | bigbluedeer/instagram_private_api | e92b6f0b1904d25edf7ad02bc4c270627f461733 | [
"MIT"
] | null | null | null | tests/web/client.py | bigbluedeer/instagram_private_api | e92b6f0b1904d25edf7ad02bc4c270627f461733 | [
"MIT"
] | null | null | null | from ..common import (
WebApiTestBase, WebClientError as ClientError,
WebClientLoginError as ClientLoginError,
WebClient as Client,
compat_mock, compat_urllib_error
)
def test_unauthed_client(self):
api = Client()
self.assertFalse(api.is_authenticated)
with self.assertRais... | 34.362745 | 92 | 0.583452 |
f0d05b63ba5129c1c92a989823c1a16fc9dc7cbf | 842 | py | Python | setup.py | dasmanov/pyEcovent | 97efe1382d1a725135f2476b8e45aaf915121b1e | [
"MIT"
] | null | null | null | setup.py | dasmanov/pyEcovent | 97efe1382d1a725135f2476b8e45aaf915121b1e | [
"MIT"
] | null | null | null | setup.py | dasmanov/pyEcovent | 97efe1382d1a725135f2476b8e45aaf915121b1e | [
"MIT"
] | null | null | null | from setuptools import setup
long_description = None
with open("README.md", 'r') as fp:
long_description = fp.read()
setup(
name = 'pyEcovent',
packages = ['ecovent'],
version='0.8.4',
description='Python3 library for single-room energy recovery ventilators from Vents / Blauberg / Flexit',
lo... | 30.071429 | 109 | 0.648456 |
f0d08e4db132f744024a09a0a079f7e2cb992ed6 | 5,105 | py | Python | voicepuppet/atvgnet/train_atnet.py | taylorlu/voicepuppet | a0d3ca3296aca15abbfe75663a1bf682fb491efa | [
"MIT"
] | 20 | 2020-10-28T07:32:29.000Z | 2022-03-04T07:15:02.000Z | voicepuppet/atvgnet/train_atnet.py | taylorlu/voicepuppet | a0d3ca3296aca15abbfe75663a1bf682fb491efa | [
"MIT"
] | 4 | 2020-11-24T14:42:44.000Z | 2021-08-05T13:31:16.000Z | voicepuppet/atvgnet/train_atnet.py | taylorlu/voicepuppet | a0d3ca3296aca15abbfe75663a1bf682fb491efa | [
"MIT"
] | 11 | 2020-10-29T07:11:22.000Z | 2022-03-28T07:17:35.000Z | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
import tensorflow as tf
import numpy as np
import os
from optparse import OptionParser
import logging
from atnet import ATNet
from dataset.generator import ATNetDataGenerator
from plot import *
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(le... | 35.950704 | 121 | 0.641724 |
f0d0afc35b9e84aba33193038e8752efcd1d32f7 | 1,695 | py | Python | tests/test_errors.py | althonos/pyhmmer | eb6fe7c0e74557e0ae9d647693711583d2d86b68 | [
"MIT"
] | 26 | 2020-11-10T22:57:49.000Z | 2022-03-24T16:58:55.000Z | tests/test_errors.py | althonos/pyhmmer | eb6fe7c0e74557e0ae9d647693711583d2d86b68 | [
"MIT"
] | 13 | 2020-11-12T11:41:08.000Z | 2022-03-09T18:17:48.000Z | tests/test_errors.py | althonos/pyhmmer | eb6fe7c0e74557e0ae9d647693711583d2d86b68 | [
"MIT"
] | 2 | 2021-04-04T05:13:07.000Z | 2021-11-30T09:11:23.000Z | import unittest
from pyhmmer.easel import Alphabet
from pyhmmer.errors import UnexpectedError, AllocationError, EaselError, AlphabetMismatch
| 42.375 | 111 | 0.684366 |
f0d0b9a716fb2240576fa6c1da54c8656e26b395 | 1,196 | py | Python | electrum_gui/common/provider/chains/cfx/sdk/cfx_address/base32.py | BixinKey/electrum | f5de4e74e313b9b569f13ba6ab9142a38bf095f2 | [
"MIT"
] | 12 | 2020-11-12T08:53:05.000Z | 2021-07-06T17:30:39.000Z | electrum_gui/common/provider/chains/cfx/sdk/cfx_address/base32.py | liyanhrxy/electrum | 107608ef201ff1d20d2f6091c257b1ceff9b7362 | [
"MIT"
] | 209 | 2020-09-23T06:58:18.000Z | 2021-11-18T11:25:41.000Z | electrum_gui/common/provider/chains/cfx/sdk/cfx_address/base32.py | liyanhrxy/electrum | 107608ef201ff1d20d2f6091c257b1ceff9b7362 | [
"MIT"
] | 19 | 2020-10-13T11:42:26.000Z | 2022-02-06T01:26:34.000Z | import base64
STANDARD_ALPHABET = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ234567'
CUSTOM_ALPHABET = 'abcdefghjkmnprstuvwxyz0123456789'
ENCODE_TRANS = str.maketrans(STANDARD_ALPHABET, CUSTOM_ALPHABET)
DECODE_TRANS = str.maketrans(CUSTOM_ALPHABET, STANDARD_ALPHABET)
PADDING_LETTER = '='
| 29.9 | 85 | 0.70903 |
f0d117c241c9bb2cd6a66d2e35612733475a8a0e | 437 | py | Python | saefportal/datalakes/models/__init__.py | harry-consulting/SAEF1 | 055d6e492ba76f90e3248b9da2985fdfe0c6b430 | [
"BSD-2-Clause"
] | null | null | null | saefportal/datalakes/models/__init__.py | harry-consulting/SAEF1 | 055d6e492ba76f90e3248b9da2985fdfe0c6b430 | [
"BSD-2-Clause"
] | null | null | null | saefportal/datalakes/models/__init__.py | harry-consulting/SAEF1 | 055d6e492ba76f90e3248b9da2985fdfe0c6b430 | [
"BSD-2-Clause"
] | 1 | 2020-12-16T15:02:52.000Z | 2020-12-16T15:02:52.000Z | from .one_drive_datalake import OneDriveDatalake
from .google_drive_datalake import GoogleDriveDatalake
from .dropbox_datalake import DropboxDatalake
from .google_cloud_storage_datalake import GoogleCloudStorageDatalake
from .azure_blob_storage_datalake import AzureBlobStorageDatalake
from .azure_data_lake_datalake imp... | 48.555556 | 69 | 0.908467 |
f0d3f90aee2a25f409650fff2ffe65e97e26ad3b | 4,319 | py | Python | PathPlanning/AStar/a_star.py | Pythocrates/PythonRobotics | e16f070a59ef9edf7200361d2ab0171a6f540f1e | [
"MIT"
] | null | null | null | PathPlanning/AStar/a_star.py | Pythocrates/PythonRobotics | e16f070a59ef9edf7200361d2ab0171a6f540f1e | [
"MIT"
] | null | null | null | PathPlanning/AStar/a_star.py | Pythocrates/PythonRobotics | e16f070a59ef9edf7200361d2ab0171a6f540f1e | [
"MIT"
] | null | null | null | """
A* grid planning
author: Atsushi Sakai(@Atsushi_twi)
Nikos Kanargias (nkana@tee.gr)
See Wikipedia article (https://en.wikipedia.org/wiki/A*_search_algorithm)
"""
import math
from node import Node
from obstacle_map import Position
| 28.414474 | 77 | 0.538782 |
f0d567896a4d3766c40a65ce7fc805db88f92454 | 1,995 | py | Python | Wordle v3.py | favet/wordle | f0390775baec8534cdab564ed79225b530cbd404 | [
"MIT"
] | null | null | null | Wordle v3.py | favet/wordle | f0390775baec8534cdab564ed79225b530cbd404 | [
"MIT"
] | null | null | null | Wordle v3.py | favet/wordle | f0390775baec8534cdab564ed79225b530cbd404 | [
"MIT"
] | null | null | null | wordle = open("Wordle.txt", "r")
wordList = []
for line in wordle:
stripped_line = line.strip()
wordList.append(stripped_line)
mutableList = []
outcomeList = []
greenLetter("z", 4, wordList)
moreGreenLetter("r", 1, mutableList)
print(wordList)
print(mutableList)
# def checkforyellow(yellowIn, y... | 29.776119 | 56 | 0.507769 |
f0d5a3b8f7ed6257ef4659a0b6e15b5bbbff0987 | 3,945 | py | Python | tests/resources/test_wallet_transactions.py | andreshndz/cuenca-python | ca9f0f078584f1458e71baeb4cd15fcc55b40397 | [
"MIT"
] | 6 | 2020-11-02T21:03:11.000Z | 2022-01-13T23:12:01.000Z | tests/resources/test_wallet_transactions.py | andreshndz/cuenca-python | ca9f0f078584f1458e71baeb4cd15fcc55b40397 | [
"MIT"
] | 220 | 2020-05-13T19:20:57.000Z | 2022-03-30T22:03:03.000Z | tests/resources/test_wallet_transactions.py | andreshndz/cuenca-python | ca9f0f078584f1458e71baeb4cd15fcc55b40397 | [
"MIT"
] | 14 | 2020-07-15T15:32:03.000Z | 2021-09-17T19:11:14.000Z | import datetime as dt
import pytest
from cuenca_validations.types import (
EntryType,
SavingCategory,
TransactionStatus,
WalletTransactionType,
)
from cuenca import BalanceEntry, Saving, WalletTransaction
| 35.223214 | 77 | 0.72218 |
f0d5e0d9829ebe242a427efa144fb271f139091a | 884 | py | Python | xldlib/xlpy/inputs.py | Alexhuszagh/XLDiscoverer | 60937b1f7f2e23af4219eb26519d6b83fb4232d6 | [
"Apache-2.0",
"MIT"
] | null | null | null | xldlib/xlpy/inputs.py | Alexhuszagh/XLDiscoverer | 60937b1f7f2e23af4219eb26519d6b83fb4232d6 | [
"Apache-2.0",
"MIT"
] | null | null | null | xldlib/xlpy/inputs.py | Alexhuszagh/XLDiscoverer | 60937b1f7f2e23af4219eb26519d6b83fb4232d6 | [
"Apache-2.0",
"MIT"
] | null | null | null | '''
XlPy/inputs
___________
Validates input file selection, configurations, and matches file types.
:copyright: (c) 2015 The Regents of the University of California.
:license: GNU GPL, see licenses/GNU GPLv3.txt for more details.
'''
# load modules
import operator as op
from xldlib.onstart.main ... | 22.1 | 75 | 0.709276 |
f0d6040d9c0d555d327cb87ba85195c3342a52cf | 4,789 | py | Python | ros/src/tl_detector/mocked_tl_detector.py | nyukhalov/CarND-Capstone | 949713ba7557a9765214a2a02329725b84552d13 | [
"MIT"
] | 3 | 2019-02-11T16:42:03.000Z | 2019-02-11T20:52:48.000Z | ros/src/tl_detector/mocked_tl_detector.py | nyukhalov/CarND-Capstone | 949713ba7557a9765214a2a02329725b84552d13 | [
"MIT"
] | 9 | 2019-02-12T18:38:18.000Z | 2019-02-26T22:20:21.000Z | ros/src/tl_detector/mocked_tl_detector.py | nyukhalov/CarND-Capstone | 949713ba7557a9765214a2a02329725b84552d13 | [
"MIT"
] | 2 | 2019-02-27T20:42:19.000Z | 2019-03-06T13:41:23.000Z | #!/usr/bin/env python
import rospy
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped, Pose
from styx_msgs.msg import TrafficLightArray, TrafficLight
from styx_msgs.msg import Lane
from sensor_msgs.msg import Image
from scipy.spatial import KDTree
import cv2
import yaml
import math
import numpy as... | 33.725352 | 112 | 0.653999 |
f0d71db6f553884c2bb1448ebcb992750a840180 | 2,175 | py | Python | reamber/algorithms/generate/sv/generators/svFuncSequencer.py | Bestfast/reamberPy | 91b76ca6adf11fbe8b7cee7c186481776a4d7aaa | [
"MIT"
] | null | null | null | reamber/algorithms/generate/sv/generators/svFuncSequencer.py | Bestfast/reamberPy | 91b76ca6adf11fbe8b7cee7c186481776a4d7aaa | [
"MIT"
] | null | null | null | reamber/algorithms/generate/sv/generators/svFuncSequencer.py | Bestfast/reamberPy | 91b76ca6adf11fbe8b7cee7c186481776a4d7aaa | [
"MIT"
] | null | null | null | from typing import Callable, List, Union
from numpy import arange
from reamber.algorithms.generate.sv.SvPkg import SvPkg
from reamber.algorithms.generate.sv.SvSequence import SvSequence
def svFuncSequencer(funcs: List[Union[float, Callable[[float], float], None]],
offsets: Union[List[float], flo... | 38.157895 | 114 | 0.630805 |
f0d87d7b32c42472be81003f06fe5e9c4bf5e20f | 1,781 | py | Python | e_secretary/migrations/0010_auto_20190329_2219.py | tsitsikas96/e-secretary | bdda95e17093da730af33acf4b15ed03331c7643 | [
"MIT"
] | null | null | null | e_secretary/migrations/0010_auto_20190329_2219.py | tsitsikas96/e-secretary | bdda95e17093da730af33acf4b15ed03331c7643 | [
"MIT"
] | null | null | null | e_secretary/migrations/0010_auto_20190329_2219.py | tsitsikas96/e-secretary | bdda95e17093da730af33acf4b15ed03331c7643 | [
"MIT"
] | 1 | 2020-03-08T16:12:34.000Z | 2020-03-08T16:12:34.000Z | # Generated by Django 2.1.7 on 2019-03-29 20:19
from django.db import migrations, models
| 27.4 | 91 | 0.522179 |
f0d9cf2dd06e2e64395354f03a64ed4bfa3145d9 | 28,778 | py | Python | catenets/models/jax/pseudo_outcome_nets.py | AliciaCurth/CATENets | aeeae7625e454e97adff37b66ba2acb527dbd275 | [
"BSD-3-Clause"
] | 33 | 2021-02-25T13:50:11.000Z | 2022-03-11T14:31:40.000Z | catenets/models/jax/pseudo_outcome_nets.py | vanderschaarlab/CATENets | d0bc5316fa784fad78d8801367ed57c37193d2c5 | [
"BSD-3-Clause"
] | 2 | 2022-02-21T16:16:32.000Z | 2022-03-23T17:56:29.000Z | catenets/models/jax/pseudo_outcome_nets.py | vanderschaarlab/CATENets | d0bc5316fa784fad78d8801367ed57c37193d2c5 | [
"BSD-3-Clause"
] | 8 | 2021-02-26T10:20:06.000Z | 2021-12-03T16:34:23.000Z | """
Implements Pseudo-outcome based Two-step Nets, namely the DR-learner, the PW-learner and the
RA-learner.
"""
# Author: Alicia Curth
from typing import Callable, Optional, Tuple
import jax.numpy as jnp
import numpy as onp
import pandas as pd
from sklearn.model_selection import StratifiedKFold
import catenets.logge... | 35.267157 | 98 | 0.629057 |
f0db46fd26b0c7315a9b0cf93b8d1fbaf8362e97 | 2,743 | py | Python | gender_converter/logger_aegender.py | roebel/DeepGC | 03eee63ff9d9f4daa34435ddca530b262f097ea6 | [
"MIT"
] | null | null | null | gender_converter/logger_aegender.py | roebel/DeepGC | 03eee63ff9d9f4daa34435ddca530b262f097ea6 | [
"MIT"
] | 1 | 2021-08-11T06:41:56.000Z | 2021-08-11T06:41:56.000Z | gender_converter/logger_aegender.py | roebel/DeepGC | 03eee63ff9d9f4daa34435ddca530b262f097ea6 | [
"MIT"
] | null | null | null | import random
from plotting_utils import plot_spectrogram_to_numpy, image_for_logger, plot_to_image
import numpy as np
import tensorflow as tf
| 55.979592 | 112 | 0.728035 |
f0db6dccf419614f773337c9ea484f5c0bdce823 | 452 | py | Python | itmo/2015-16/final/weight.py | dluschan/olymp | dfbf4352dbc7f6fd7563e7bd19aff6fd67fb50b7 | [
"MIT"
] | null | null | null | itmo/2015-16/final/weight.py | dluschan/olymp | dfbf4352dbc7f6fd7563e7bd19aff6fd67fb50b7 | [
"MIT"
] | null | null | null | itmo/2015-16/final/weight.py | dluschan/olymp | dfbf4352dbc7f6fd7563e7bd19aff6fd67fb50b7 | [
"MIT"
] | 1 | 2018-09-14T18:50:48.000Z | 2018-09-14T18:50:48.000Z | weight = []
diff = 0
n = int(input())
for i in range(n):
q, c = map(int, input().split())
if c == 2:
q *= -1
weight.append(q)
diff += q
min_diff = abs(diff)
for i in range(n):
if abs(diff - 2*weight[i]) < min_diff:
min_diff = abs(diff - 2*weight[i])
for j in range(i+1, n):
... | 25.111111 | 60 | 0.526549 |
f0db8dc49a5a35a6b18b47a43dda531b71b817b6 | 534 | py | Python | open_spiel/python/examples/test.py | ThorvaldAagaard/open_spiel | 58f6584b555b1a1a83bf674f0cbe0162c1251eca | [
"Apache-2.0"
] | null | null | null | open_spiel/python/examples/test.py | ThorvaldAagaard/open_spiel | 58f6584b555b1a1a83bf674f0cbe0162c1251eca | [
"Apache-2.0"
] | null | null | null | open_spiel/python/examples/test.py | ThorvaldAagaard/open_spiel | 58f6584b555b1a1a83bf674f0cbe0162c1251eca | [
"Apache-2.0"
] | null | null | null | import pyspiel
game = pyspiel.load_game('bridge(use_double_dummy_result=false)')
line = '30 32 10 35 50 45 21 7 1 42 39 43 0 16 40 20 36 15 22 44 26 6 4 51 47 46 25 14 29 5 34 11 49 31 37 9 41 13 24 8 28 17 48 23 33 18 3 19 38 2 27 12 56 57 52 63 52 52 52 0 32 48 8 3 51 47 15 44 28 16 4 14 50 2 10 49 5 37 9 36 31 24 2... | 59.333333 | 321 | 0.685393 |
f0dc6c0f1ad89845b0333162183c190359534d22 | 906 | py | Python | texel/keys.py | Xen0byte/texel | 9dcfba163c66e9da5e9b0757c4e587f297b0cfcb | [
"MIT"
] | 119 | 2022-02-06T21:47:55.000Z | 2022-03-21T23:14:30.000Z | texel/keys.py | Xen0byte/texel | 9dcfba163c66e9da5e9b0757c4e587f297b0cfcb | [
"MIT"
] | 3 | 2022-02-07T08:47:20.000Z | 2022-02-09T09:07:17.000Z | texel/keys.py | Xen0byte/texel | 9dcfba163c66e9da5e9b0757c4e587f297b0cfcb | [
"MIT"
] | 5 | 2022-02-07T08:13:11.000Z | 2022-02-12T22:31:37.000Z | import curses
| 25.885714 | 80 | 0.572848 |
f0dd70671137f9276770eb4324b9867b67865ca3 | 51,458 | py | Python | tests/test_number_cleaner.py | theseus-automl/gorgona | a7366d54430caa5a038488432fb93702e1cb83b8 | [
"Apache-2.0"
] | 1 | 2021-12-12T10:47:00.000Z | 2021-12-12T10:47:00.000Z | tests/test_number_cleaner.py | theseus-automl/gorgona | a7366d54430caa5a038488432fb93702e1cb83b8 | [
"Apache-2.0"
] | 5 | 2021-12-12T10:45:04.000Z | 2022-01-17T07:51:14.000Z | tests/test_number_cleaner.py | theseus-automl/gorgona | a7366d54430caa5a038488432fb93702e1cb83b8 | [
"Apache-2.0"
] | null | null | null | import pytest
from gorgona.stages.cleaners import NumberCleaner
... | 39.766615 | 110 | 0.837324 |
f0dd9ec3c005973e7ab2799270be09efd623558e | 9,700 | py | Python | test/test_digitalbitbox.py | matejcik/HWI | f0021502d470660b9d8a5e79fcc440ac809a610f | [
"MIT"
] | 54 | 2018-03-16T14:50:19.000Z | 2019-01-29T19:19:17.000Z | test/test_digitalbitbox.py | matejcik/HWI | f0021502d470660b9d8a5e79fcc440ac809a610f | [
"MIT"
] | 86 | 2018-01-30T18:40:44.000Z | 2019-01-30T20:48:24.000Z | test/test_digitalbitbox.py | matejcik/HWI | f0021502d470660b9d8a5e79fcc440ac809a610f | [
"MIT"
] | 11 | 2017-09-05T17:19:53.000Z | 2019-01-10T19:11:04.000Z | #! /usr/bin/env python3
import argparse
import atexit
import json
import os
import subprocess
import sys
import time
import unittest
from test_device import (
Bitcoind,
DeviceEmulator,
DeviceTestCase,
TestDeviceConnect,
TestGetKeypool,
TestGetDescriptors,
TestSignTx,
)
from hwilib.devices... | 45.971564 | 161 | 0.668454 |
f0de783da190b1f53132dc15989ab3f8990f924d | 560 | py | Python | docs/conf.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 5 | 2016-07-27T16:01:41.000Z | 2020-03-10T21:11:31.000Z | docs/conf.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 14 | 2015-07-22T16:41:58.000Z | 2019-03-28T20:45:17.000Z | docs/conf.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 3 | 2015-07-22T15:14:44.000Z | 2018-04-16T09:49:35.000Z | import os
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
extensions = []
templates_path = ['_templates']
source_suffix = ['.rst', '.md']
master_doc = 'index'
project = u'fiubar'
copyright = u'2008-2018, Maru Berezin'
version = '2.0.0'
release = '2.0.0'
exclude_trees = ['_build']
pygments_style = 'sphinx'
html... | 24.347826 | 62 | 0.707143 |
f0debfa3d1d8a0bacee277563d8f6b144a1f884d | 663 | py | Python | 2021/day9.py | tobeannouncd/AdventOfCode | b4fe6e9b10a0dc191429a90ab351806df03bca10 | [
"MIT"
] | null | null | null | 2021/day9.py | tobeannouncd/AdventOfCode | b4fe6e9b10a0dc191429a90ab351806df03bca10 | [
"MIT"
] | null | null | null | 2021/day9.py | tobeannouncd/AdventOfCode | b4fe6e9b10a0dc191429a90ab351806df03bca10 | [
"MIT"
] | null | null | null | from io import StringIO
import itertools
import numpy as np
import numpy.ma as ma
inputfile = './input/day9.txt'
# inputfile = StringIO('''2199943210
# 3987894921
# 9856789892
# 8767896789
# 9899965678''')
a = np.genfromtxt(inputfile, dtype='i', delimiter=1)
nRows, nCols = a.shape
b = np.pad(a, ((1, 1), (1, 1)), c... | 22.1 | 68 | 0.616893 |
f0df7eb72b3c3a8b625596cf0e32b466f1260149 | 456 | py | Python | ml-env/examples/train.py | RafalSkolasinski/dockerfiles | 8c8609fda42ad2b55960b64aef12774e00e2a4d4 | [
"MIT"
] | null | null | null | ml-env/examples/train.py | RafalSkolasinski/dockerfiles | 8c8609fda42ad2b55960b64aef12774e00e2a4d4 | [
"MIT"
] | 134 | 2021-02-10T14:32:47.000Z | 2022-03-31T02:16:17.000Z | ml-env/examples/train.py | RafalSkolasinski/dockerfiles | 8c8609fda42ad2b55960b64aef12774e00e2a4d4 | [
"MIT"
] | null | null | null | import numpy as np
import joblib
from sklearn import datasets
from sklearn import svm
from sklearn.model_selection import train_test_split
filename_p = "model.joblib"
if __name__ == "__main__":
digits = datasets.load_digits()
X_train, X_test, y_train, y_test = train_test_split(
digits.data, digit... | 19 | 56 | 0.717105 |
f0dfa56f80d5b88124cdf73fc8c809e7cf604253 | 1,050 | py | Python | vocoder/datasets/__init__.py | ZENGZHEN-TTS/LVCNet | e81e13f3479a4d85f498a02e42338ebe823a8b3d | [
"Apache-2.0"
] | 45 | 2021-02-23T07:43:14.000Z | 2021-06-21T11:33:45.000Z | vocoder/datasets/__init__.py | JackZiLong/LVCNet | e81e13f3479a4d85f498a02e42338ebe823a8b3d | [
"Apache-2.0"
] | 3 | 2021-04-08T05:01:38.000Z | 2021-06-09T17:41:48.000Z | vocoder/datasets/__init__.py | ZENGZHEN-TTS/LVCNet | e81e13f3479a4d85f498a02e42338ebe823a8b3d | [
"Apache-2.0"
] | 11 | 2021-02-25T18:14:12.000Z | 2021-06-21T11:40:41.000Z |
from .audio_mel import PWGAudioMelNoiseDataset, DataLoader
dataset_class_dict = {
"PWGAudioMelNoiseDataset": PWGAudioMelNoiseDataset
}
def create_dataloader(dataset_classname,
dataset_config,
batch_size=1,
collate_fn=None,
s... | 31.818182 | 73 | 0.521905 |
f0dfa6a70f2b05edad087e65290480ef3841bae8 | 911 | py | Python | src/mdfserver/models.py | UCHIC/iUTAHData | 4ffab29ad6b3313416bb2a8b98acf0b2e02c8cab | [
"Unlicense"
] | 2 | 2015-02-25T01:12:51.000Z | 2017-02-08T22:54:41.000Z | src/mdfserver/models.py | UCHIC/iUTAHData | 4ffab29ad6b3313416bb2a8b98acf0b2e02c8cab | [
"Unlicense"
] | 48 | 2015-01-12T18:01:56.000Z | 2021-06-10T20:05:26.000Z | src/mdfserver/models.py | UCHIC/iUTAHData | 4ffab29ad6b3313416bb2a8b98acf0b2e02c8cab | [
"Unlicense"
] | null | null | null | from django.db import models
# from tinymce import models as tinymce_models
#
# # Create your models here.
#
# class Page(models.Model):
# title = models.CharField(max_length=200)
# url = models.CharField(max_length=200)
# content = models.TextField(max_length=20000) #tinymce_models.HTMLField()#forms.CharFi... | 45.55 | 181 | 0.70472 |
f0e0241d9b692b14994b533da81167806bad291d | 2,468 | py | Python | tests/test_connectors_bigquery.py | bbc/foxglove | eb09b23aed51ed615eccf71bf20f2f6b28f4b32f | [
"Apache-2.0"
] | null | null | null | tests/test_connectors_bigquery.py | bbc/foxglove | eb09b23aed51ed615eccf71bf20f2f6b28f4b32f | [
"Apache-2.0"
] | null | null | null | tests/test_connectors_bigquery.py | bbc/foxglove | eb09b23aed51ed615eccf71bf20f2f6b28f4b32f | [
"Apache-2.0"
] | null | null | null | """
Copyright 2019 BBC. Licensed under the terms of the Apache License 2.0.
"""
from unittest.mock import Mock
import pytest
from google.cloud.bigquery import Client
from foxglove.connectors.bigquery import BigQueryConnector
def test_bigquery_engine_url_decode():
engine_url='bigquery://projectId=my_project;da... | 29.73494 | 93 | 0.731361 |
f0e245d926233f4c636eb409d21b940db19ff2c8 | 1,982 | py | Python | activitfinal.py | AjayBadrinath/Python-Stuff | 34bb0339968b943cc63c5dc31721e3504faea157 | [
"MIT"
] | null | null | null | activitfinal.py | AjayBadrinath/Python-Stuff | 34bb0339968b943cc63c5dc31721e3504faea157 | [
"MIT"
] | null | null | null | activitfinal.py | AjayBadrinath/Python-Stuff | 34bb0339968b943cc63c5dc31721e3504faea157 | [
"MIT"
] | null | null | null | import sys
#"splchar":["!","@","#","$",".",",",":","%","^","*"]
splchar=[chr(i) for i in range(33,48)]#ASCII spl charecter range from 33-48 and58-65#and i here is the mapping expression ie the thing thet is executed evry iteration
splchar1=[chr(i) for i in range(58,65)]#Instead of explicit declaration of for loop ... | 48.341463 | 168 | 0.652371 |
f0e44d50b65aca97969715923cd5504c6c2fa654 | 28,838 | py | Python | pytests/backup/ibr.py | ramalingam-cb/testrunner | 81cea7a5a493cf0c67fca7f97c667cd3c6ad2142 | [
"Apache-2.0"
] | null | null | null | pytests/backup/ibr.py | ramalingam-cb/testrunner | 81cea7a5a493cf0c67fca7f97c667cd3c6ad2142 | [
"Apache-2.0"
] | null | null | null | pytests/backup/ibr.py | ramalingam-cb/testrunner | 81cea7a5a493cf0c67fca7f97c667cd3c6ad2142 | [
"Apache-2.0"
] | null | null | null | __author__ = 'ashvinder'
import re
import os
import gc
import logger
import time
from TestInput import TestInputSingleton
from backup.backup_base import BackupBaseTest
from remote.remote_util import RemoteMachineShellConnection
from couchbase_helper.documentgenerator import BlobGenerator
from couchbase_helper.documentg... | 45.485804 | 165 | 0.627055 |
f0e68b0a27260d16ee0b208166b5530ca8b0baef | 963 | py | Python | examples/test_feasibility.py | OllieBoyne/sslap | 02c88a05dee1c33d5e0c9b405f947d522fb0b150 | [
"MIT"
] | 7 | 2021-03-12T17:28:18.000Z | 2022-02-14T08:05:23.000Z | examples/test_feasibility.py | OllieBoyne/sslap | 02c88a05dee1c33d5e0c9b405f947d522fb0b150 | [
"MIT"
] | 6 | 2021-03-12T17:38:21.000Z | 2022-02-16T10:37:33.000Z | examples/test_feasibility.py | OllieBoyne/sslap | 02c88a05dee1c33d5e0c9b405f947d522fb0b150 | [
"MIT"
] | 4 | 2021-03-18T14:25:52.000Z | 2021-12-06T14:38:30.000Z | """Check the feasibility of a bipartite graph by using SSLAP's feasibility module"""
import numpy as np
from sslap import hopcroft_solve
# All 3 methods will use the same input bipartite graph:
# i = 0 connects to j = 0, 1
# i = 1 connects to j = 1, 2
# i = 2 connects to j = 1, 4
# i = 3 connects to j = 2
# i = 4 con... | 24.692308 | 105 | 0.5919 |
f0e6c3af9d104e8e439e1bf9d7509dae91e833dd | 5,933 | py | Python | clot/app.py | elliptical/clot | d1ee8ddc7527b170c0943b567b1cd589d5007b4d | [
"MIT"
] | null | null | null | clot/app.py | elliptical/clot | d1ee8ddc7527b170c0943b567b1cd589d5007b4d | [
"MIT"
] | null | null | null | clot/app.py | elliptical/clot | d1ee8ddc7527b170c0943b567b1cd589d5007b4d | [
"MIT"
] | null | null | null | """A simple command-line interface to the clot.torrent package."""
from argparse import ArgumentParser
from os import path, walk
import shutil
from clot import __version__, torrent
def main():
"""Execute actions according to the command-line arguments."""
args = _parse_command_line()
for source in arg... | 33.331461 | 99 | 0.572055 |
f0e7d6bd1974b95ea4a8abd9c52fb010ef93328b | 475 | py | Python | app/converter/nsl/substance_cv_converter.py | c0d3m0nkey/xml-to-json-converter | 9cf040b591f45031c80dc5bc64d6fbb2c4665d25 | [
"BSD-2-Clause"
] | null | null | null | app/converter/nsl/substance_cv_converter.py | c0d3m0nkey/xml-to-json-converter | 9cf040b591f45031c80dc5bc64d6fbb2c4665d25 | [
"BSD-2-Clause"
] | null | null | null | app/converter/nsl/substance_cv_converter.py | c0d3m0nkey/xml-to-json-converter | 9cf040b591f45031c80dc5bc64d6fbb2c4665d25 | [
"BSD-2-Clause"
] | null | null | null | from lxml import objectify, etree
from operator import itemgetter
from ..xml_converter import XmlConverter
| 36.538462 | 74 | 0.671579 |
f0e89ae2be157a7563b7db3f026034c5b7dec360 | 482 | py | Python | cardiffshop/cardiffshop/urls.py | yigitguler/admin-example | 48a0eacea1d03123fef5e86165749e9c0213e0d8 | [
"MIT"
] | null | null | null | cardiffshop/cardiffshop/urls.py | yigitguler/admin-example | 48a0eacea1d03123fef5e86165749e9c0213e0d8 | [
"MIT"
] | null | null | null | cardiffshop/cardiffshop/urls.py | yigitguler/admin-example | 48a0eacea1d03123fef5e86165749e9c0213e0d8 | [
"MIT"
] | null | null | null | from products.views import ProductDetail
from django.conf import settings
from django.conf.urls.static import static
from django.conf.urls import include, url
from django.contrib import admin
urlpatterns = [
url(r'^admin/', include(admin.site.urls)),
url(r'^products/(?P<slug>[-\w]+)/', ProductDetail.as_view()... | 37.076923 | 88 | 0.761411 |
f0e928a38ffedd9b5a5fdacb57e277620b6e15be | 339 | py | Python | headlineVsHeadline/polls/models.py | bacarpenter/headline-vs-headline | 2dc59e75fadbf7d5bb0a5b15a0bf41784712a290 | [
"MIT"
] | null | null | null | headlineVsHeadline/polls/models.py | bacarpenter/headline-vs-headline | 2dc59e75fadbf7d5bb0a5b15a0bf41784712a290 | [
"MIT"
] | 1 | 2020-12-28T01:28:19.000Z | 2020-12-28T01:56:47.000Z | headlineVsHeadline/polls/models.py | bacarpenter/headline-vs-headline | 2dc59e75fadbf7d5bb0a5b15a0bf41784712a290 | [
"MIT"
] | null | null | null | from django.db import models
# Create your models here.
| 33.9 | 57 | 0.755162 |
f0ea161b0bdb8c1460310c8cf5b767d1b7345d34 | 1,678 | py | Python | plot_result.py | PrimordialOcean/diffusion-plagioclase | f85a9c9a348435ca162de2da3ae9290b56d66807 | [
"MIT"
] | null | null | null | plot_result.py | PrimordialOcean/diffusion-plagioclase | f85a9c9a348435ca162de2da3ae9290b56d66807 | [
"MIT"
] | null | null | null | plot_result.py | PrimordialOcean/diffusion-plagioclase | f85a9c9a348435ca162de2da3ae9290b56d66807 | [
"MIT"
] | null | null | null | import matplotlib.pyplot as plt
import pandas as pd
if __name__ == "__main__":
main() | 34.244898 | 79 | 0.557211 |
f0ec35912039f91ed3134032fb990304ca7ef9ce | 2,685 | py | Python | tests/unit/test_core_context.py | nickchen-mitac/fork | 64dab56012da47465b4923f30f26925476c87afc | [
"Apache-2.0"
] | null | null | null | tests/unit/test_core_context.py | nickchen-mitac/fork | 64dab56012da47465b4923f30f26925476c87afc | [
"Apache-2.0"
] | null | null | null | tests/unit/test_core_context.py | nickchen-mitac/fork | 64dab56012da47465b4923f30f26925476c87afc | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function, unicode_literals
import pytest
from pydispatch import dispatcher
from ava.core.context import Context, get_core_context
| 26.85 | 88 | 0.642831 |
f0ed814c5e8a404bf3c7bc581d0b6d473446eadd | 5,736 | py | Python | Nitesh-Bhosle-Visualization-for-company-stakeholders/code.py | Niteshnupur/greyatom-python-for-data-science | fc8fd221f9ca1b256740b201dff2a806047644e5 | [
"MIT"
] | 3 | 2020-05-21T13:40:35.000Z | 2020-05-21T15:05:04.000Z | Nitesh-Bhosle-Visualization-for-company-stakeholders/code.py | Niteshnupur/greyatom-python-for-data-science | fc8fd221f9ca1b256740b201dff2a806047644e5 | [
"MIT"
] | null | null | null | Nitesh-Bhosle-Visualization-for-company-stakeholders/code.py | Niteshnupur/greyatom-python-for-data-science | fc8fd221f9ca1b256740b201dff2a806047644e5 | [
"MIT"
] | 1 | 2020-05-14T04:11:22.000Z | 2020-05-14T04:11:22.000Z | # --------------
# Loan Status
# Loan Status
# Let's start with the simple task of visualizing the company's record with respect to loan approvals.
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# The path to the dataset has been stored in a variable path
# Lo... | 25.493333 | 214 | 0.719317 |
f0ef146504402ffb34754f9067bbfa37ee601926 | 649 | py | Python | tests/migration_tests.py | psbsgic/rabbitai | 769e120ba605d56ac076f810a549c38dac410c8e | [
"Apache-2.0"
] | null | null | null | tests/migration_tests.py | psbsgic/rabbitai | 769e120ba605d56ac076f810a549c38dac410c8e | [
"Apache-2.0"
] | null | null | null | tests/migration_tests.py | psbsgic/rabbitai | 769e120ba605d56ac076f810a549c38dac410c8e | [
"Apache-2.0"
] | 1 | 2021-07-09T16:29:50.000Z | 2021-07-09T16:29:50.000Z | import json
from rabbitai.migrations.versions.fb13d49b72f9_better_filters import (
Slice,
upgrade_slice,
)
from .base_tests import RabbitaiTestCase
| 25.96 | 70 | 0.640986 |
f0f04e94a81beb88cb190deaab3f4d7bf4be0477 | 125 | py | Python | pyaz/mariadb/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | null | null | null | pyaz/mariadb/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | null | null | null | pyaz/mariadb/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | 1 | 2022-02-03T09:12:01.000Z | 2022-02-03T09:12:01.000Z | '''
Manage Azure Database for MariaDB servers.
'''
from .. pyaz_utils import _call_az
from . import db, server, server_logs
| 17.857143 | 42 | 0.744 |
f0f24b597dd5dc011330fa8b6f22b56989bc02be | 19,805 | py | Python | utils/pvacapi/controllers/database.py | mrichters/pVACtools | 1e86411055b3da9f81f966e83578dfadc3883498 | [
"BSD-3-Clause-Clear"
] | 96 | 2017-11-06T18:53:19.000Z | 2022-02-28T07:36:12.000Z | utils/pvacapi/controllers/database.py | mrichters/pVACtools | 1e86411055b3da9f81f966e83578dfadc3883498 | [
"BSD-3-Clause-Clear"
] | 521 | 2017-11-29T16:27:54.000Z | 2022-03-30T13:57:38.000Z | utils/pvacapi/controllers/database.py | mrichters/pVACtools | 1e86411055b3da9f81f966e83578dfadc3883498 | [
"BSD-3-Clause-Clear"
] | 53 | 2017-11-29T19:40:27.000Z | 2022-01-14T16:51:12.000Z | import os
import re
import csv
import sys
import json
import yaml
import time
import socket
import connexion
import postgresql as psql
from flask import current_app
from urllib.parse import urlencode
from hashlib import md5
from bokeh.embed import server_document
from .processes import fetch_process, is_running, proce... | 38.833333 | 142 | 0.533401 |
f0f336d7a75970c20e9d6a476b0d5df71d22aa9a | 3,327 | py | Python | BiasedPUlearning/nnPUSB/model.py | XINGXIAOYU/PUlearning | 3401b77ccdd653d39f4f3a6258a42c7938fa9ede | [
"MIT"
] | 24 | 2019-10-06T08:05:29.000Z | 2021-12-20T10:52:17.000Z | BiasedPUlearning/nnPUSB/model.py | XINGXIAOYU/PUlearning | 3401b77ccdd653d39f4f3a6258a42c7938fa9ede | [
"MIT"
] | 2 | 2020-09-29T22:34:25.000Z | 2020-09-29T22:43:01.000Z | BiasedPUlearning/nnPUSB/model.py | MasaKat0/PUlearning | 3401b77ccdd653d39f4f3a6258a42c7938fa9ede | [
"MIT"
] | 13 | 2019-05-20T06:29:52.000Z | 2022-02-03T15:31:20.000Z | import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, Variable
from chainer import optimizers, serializers, utils
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
| 28.930435 | 64 | 0.502254 |
f0f42be3894dc386d19ebedd7a5a49fac7cfc1f4 | 1,597 | py | Python | scripts/set_examples_to_doc.py | sasmirnov/numba-dppy | 6ec41a5adab3034ddcfba2df312117afd6e2327b | [
"Apache-2.0"
] | null | null | null | scripts/set_examples_to_doc.py | sasmirnov/numba-dppy | 6ec41a5adab3034ddcfba2df312117afd6e2327b | [
"Apache-2.0"
] | null | null | null | scripts/set_examples_to_doc.py | sasmirnov/numba-dppy | 6ec41a5adab3034ddcfba2df312117afd6e2327b | [
"Apache-2.0"
] | null | null | null | """ This script is needed to convert gdb scripts from commands to documentation
"""
import os
if __name__ == "__main__":
convert_commands_to_docs()
| 36.295455 | 85 | 0.469004 |
f0f438b51d2d508d57dd917ca013391d3e1a093f | 6,672 | py | Python | Phidget22/Devices/Accelerometer.py | keysie/python-fast-data-visualization | ebf392fe6d8d25bd5c178edbf095cf29e0daa4af | [
"MIT"
] | 1 | 2020-02-26T12:43:07.000Z | 2020-02-26T12:43:07.000Z | Phidget22/Devices/Accelerometer.py | keysie/phidget-python-interface | ebf392fe6d8d25bd5c178edbf095cf29e0daa4af | [
"MIT"
] | null | null | null | Phidget22/Devices/Accelerometer.py | keysie/phidget-python-interface | ebf392fe6d8d25bd5c178edbf095cf29e0daa4af | [
"MIT"
] | 1 | 2020-02-26T12:43:12.000Z | 2020-02-26T12:43:12.000Z | import sys
import ctypes
from Phidget22.PhidgetSupport import PhidgetSupport
from Phidget22.PhidgetException import PhidgetException
from Phidget22.Phidget import Phidget
| 27.012146 | 145 | 0.77473 |
f0f5116f620313599917f1b146e0c00251125aed | 728 | py | Python | prickly-pufferfish/python_questions/merge_ranges.py | Vthechamp22/summer-code-jam-2021 | 0a8bf1f22f6c73300891fd779da36efd8e1304c1 | [
"MIT"
] | 40 | 2020-08-02T07:38:22.000Z | 2021-07-26T01:46:50.000Z | prickly-pufferfish/python_questions/merge_ranges.py | Vthechamp22/summer-code-jam-2021 | 0a8bf1f22f6c73300891fd779da36efd8e1304c1 | [
"MIT"
] | 134 | 2020-07-31T12:15:45.000Z | 2020-12-13T04:42:19.000Z | prickly-pufferfish/python_questions/merge_ranges.py | Vthechamp22/summer-code-jam-2021 | 0a8bf1f22f6c73300891fd779da36efd8e1304c1 | [
"MIT"
] | 101 | 2020-07-31T12:00:47.000Z | 2021-11-01T09:06:58.000Z | """
In HiCal, a meeting is stored as tuples of integers (start_time, end_time). /
These integers represent the number of 30-minute blocks past 9:00am. /
For example: /
(2, 3) # meeting from 10:00 - 10:30 am /
(6, 9) # meeting from 12:00 - 1:30 pm /
Write a function merge_ranges() that /
takes a list of meeting time ran... | 28 | 77 | 0.539835 |
f0f5c3172c842de383a43edeab846b0154a88fb9 | 1,209 | py | Python | tests/tokenizers.py | theeluwin/textrankr | ec692be8d952dc0d88c74001e77f5a9be20a12d3 | [
"MIT"
] | 219 | 2016-05-03T08:38:36.000Z | 2022-03-08T04:40:09.000Z | tests/tokenizers.py | theeluwin/textrankr | ec692be8d952dc0d88c74001e77f5a9be20a12d3 | [
"MIT"
] | 11 | 2016-05-03T11:25:03.000Z | 2020-12-18T00:10:31.000Z | tests/tokenizers.py | theeluwin/textrankr | ec692be8d952dc0d88c74001e77f5a9be20a12d3 | [
"MIT"
] | 44 | 2016-07-02T05:18:49.000Z | 2022-03-08T08:14:26.000Z | import json
import requests
from typing import List
from konlpy.tag import Okt
from requests.models import Response
| 28.116279 | 165 | 0.647643 |
f0f5e1e9645a14c12d5c5d93830c5d22ebcb474f | 823 | py | Python | Module/engine.py | NoahSchiro/physics-engine | c96d96eeaf823583ac1035d58fb69d7d47019f87 | [
"MIT"
] | null | null | null | Module/engine.py | NoahSchiro/physics-engine | c96d96eeaf823583ac1035d58fb69d7d47019f87 | [
"MIT"
] | null | null | null | Module/engine.py | NoahSchiro/physics-engine | c96d96eeaf823583ac1035d58fb69d7d47019f87 | [
"MIT"
] | null | null | null | from free_bodies import *
# This is the actual engine which is apply physics to objects
| 28.37931 | 84 | 0.584447 |
f0f736be57d784d43416f82badd0762190fea39d | 96 | py | Python | venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/psapi.py | GiulianaPola/select_repeats | 17a0d053d4f874e42cf654dd142168c2ec8fbd11 | [
"MIT"
] | 2 | 2022-03-13T01:58:52.000Z | 2022-03-31T06:07:54.000Z | venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/psapi.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | 19 | 2021-11-20T04:09:18.000Z | 2022-03-23T15:05:55.000Z | venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/psapi.py | DesmoSearch/Desmobot | b70b45df3485351f471080deb5c785c4bc5c4beb | [
"MIT"
] | null | null | null | /home/runner/.cache/pip/pool/57/99/fd/1d22e7d1fbf9ab07bcdf332318605c4de276c282734bf85d8c6421a6ce | 96 | 96 | 0.895833 |
f0f901df9fc78d9208f11171a838b27095f77671 | 5,044 | py | Python | tests/test_spi.py | petermankowski510/python-periphery-master | 11e76632d4a58a77db71cb2e35815ef7ebc5e5dc | [
"MIT"
] | null | null | null | tests/test_spi.py | petermankowski510/python-periphery-master | 11e76632d4a58a77db71cb2e35815ef7ebc5e5dc | [
"MIT"
] | null | null | null | tests/test_spi.py | petermankowski510/python-periphery-master | 11e76632d4a58a77db71cb2e35815ef7ebc5e5dc | [
"MIT"
] | null | null | null | import sys
import periphery
from .asserts import AssertRaises
if sys.version_info[0] == 3:
raw_input = input
spi_device = None
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: python -m tests.test_spi <SPI device>")
print("")
print("[1/4] Arguments test: No requirem... | 28.822857 | 117 | 0.634615 |
f0fb0c535a2388e4de96ced030b5de23be03985e | 12,129 | py | Python | src/shapiro/language.py | roskakori/shapiro | 55c702cb20b85cbfcc33e82964849414817339d0 | [
"MIT"
] | 2 | 2018-07-28T13:00:35.000Z | 2019-01-07T08:57:34.000Z | src/shapiro/language.py | roskakori/shapiro | 55c702cb20b85cbfcc33e82964849414817339d0 | [
"MIT"
] | 26 | 2018-07-28T10:39:36.000Z | 2018-08-05T20:37:20.000Z | src/shapiro/language.py | roskakori/shapiro | 55c702cb20b85cbfcc33e82964849414817339d0 | [
"MIT"
] | 5 | 2018-07-28T10:51:55.000Z | 2018-07-28T13:58:45.000Z | """
Language specific settings
"""
from typing import Dict, Set
from shapiro.common import Rating, ranged_rating
from shapiro.tools import log, signum
from spacy.tokens import Token
_log = log
def language_sentiment_for(language_code: str) -> LanguageSentiment:
base_code = language_code.split('_')[0]
if ... | 31.260309 | 113 | 0.480419 |
f0fe1edc9a050c8494f0a0d7ffeb0068529e480f | 3,053 | py | Python | sources/zmp_feedforwad_control.py | ekorudiawan/ZMP_Preview_Control_WPG | 7a0574e1ff991aafb9324eb82d0b9e66e96737f1 | [
"MIT"
] | 8 | 2020-04-08T19:36:26.000Z | 2022-01-29T18:13:58.000Z | sources/zmp_feedforwad_control.py | ekorudiawan/ZMP_Preview_Control_WPG | 7a0574e1ff991aafb9324eb82d0b9e66e96737f1 | [
"MIT"
] | null | null | null | sources/zmp_feedforwad_control.py | ekorudiawan/ZMP_Preview_Control_WPG | 7a0574e1ff991aafb9324eb82d0b9e66e96737f1 | [
"MIT"
] | 5 | 2020-10-19T12:10:52.000Z | 2022-02-17T03:03:47.000Z | # ZMP preview control simulation with Python
# By : Eko Rudiawan Jamzuri
# Email : eko.rudiawan@gmail.com
# This is an implementation of ZMP preview control with feedforward method
# This Python program will calculating CoM trajectory based on ZMP trajectory input
# The Gain parameter Gi, Gx, and Gd is imported from ma... | 30.838384 | 103 | 0.523092 |
f0fe907e32be0b4e9c4019c39f5c30195bfaa907 | 458 | py | Python | algorithms/sorting/counting_sort.py | abhishektyagi2912/python-dsa | 8f51f15a091ee76e00fb34abc232c23cb68440cb | [
"MIT"
] | 1 | 2021-05-02T05:43:34.000Z | 2021-05-02T05:43:34.000Z | algorithms/sorting/counting_sort.py | abhishektyagi2912/python-dsa | 8f51f15a091ee76e00fb34abc232c23cb68440cb | [
"MIT"
] | null | null | null | algorithms/sorting/counting_sort.py | abhishektyagi2912/python-dsa | 8f51f15a091ee76e00fb34abc232c23cb68440cb | [
"MIT"
] | null | null | null |
test_array = [3, 3, 2, 6, 4, 7, 9, 7, 8]
counting_sort(test_array)
print(test_array)
| 21.809524 | 46 | 0.591703 |
0b0149c561d9b693e298cce2051643d984729630 | 154 | py | Python | Python/8 kyu/Grasshopper - Terminal Game Move Function/solution.py | Hsins/CodeWars | 7e7b912fdd0647c0af381d8b566408e383ea5df8 | [
"MIT"
] | 1 | 2020-01-09T21:47:56.000Z | 2020-01-09T21:47:56.000Z | Python/8 kyu/Grasshopper - Terminal Game Move Function/solution.py | Hsins/CodeWars | 7e7b912fdd0647c0af381d8b566408e383ea5df8 | [
"MIT"
] | 1 | 2020-01-20T12:39:03.000Z | 2020-01-20T12:39:03.000Z | Python/8 kyu/Grasshopper - Terminal Game Move Function/solution.py | Hsins/CodeWars | 7e7b912fdd0647c0af381d8b566408e383ea5df8 | [
"MIT"
] | null | null | null | # [8 kyu] Grasshopper - Terminal Game Move Function
#
# Author: Hsins
# Date: 2019/12/20
| 17.111111 | 51 | 0.649351 |
0b04026c6e3cfd8fd000afa2890bd940e623cf60 | 2,501 | py | Python | server/app/__init__.py | trungkienbkhn/nmt-wizard | dcf1f20d92e0f9788a811e79093ac0d917ae9e4e | [
"MIT"
] | null | null | null | server/app/__init__.py | trungkienbkhn/nmt-wizard | dcf1f20d92e0f9788a811e79093ac0d917ae9e4e | [
"MIT"
] | null | null | null | server/app/__init__.py | trungkienbkhn/nmt-wizard | dcf1f20d92e0f9788a811e79093ac0d917ae9e4e | [
"MIT"
] | null | null | null | import os
import logging.config
import redis
from flask import Flask
from nmtwizard import common
from nmtwizard import configuration as config
from utils.database_utils import DatabaseUtils
from flask_session import Session
VERSION = "1.12.0"
app = Flask(__name__)
app.request_id = 1
system_config = config.get_... | 29.423529 | 107 | 0.754498 |
0b04b5673e663cf9c8fc8da92d1c7bd8d879657a | 1,152 | py | Python | Neural_Networks/Multilayer/Neural_Multi_pybrain.py | jeffreire/Deep_Learning | 960142080dc63ea103b326ea3d6d17bd44ae0f51 | [
"MIT"
] | null | null | null | Neural_Networks/Multilayer/Neural_Multi_pybrain.py | jeffreire/Deep_Learning | 960142080dc63ea103b326ea3d6d17bd44ae0f51 | [
"MIT"
] | null | null | null | Neural_Networks/Multilayer/Neural_Multi_pybrain.py | jeffreire/Deep_Learning | 960142080dc63ea103b326ea3d6d17bd44ae0f51 | [
"MIT"
] | null | null | null | # from pybrain.datasets import SupervisedDataSet
# from pybrain.supervised.trainers import BackpropTrainer
# from pybrain.structure.modules import SoftmaxLayer
# from pybrain.structure.modules import SigmoidLayer
# from pybrain.tools.s import buildNetwork
# (x,y,z) = x a quantidade de camadas de entrada, y a q... | 39.724138 | 123 | 0.664931 |
0b058e034e1693406e04d820118fb4291f6395b3 | 4,213 | py | Python | aries_cloudagent/protocols/present_proof/dif/tests/test_pres_request.py | kuraakhilesh8230/aries-cloudagent-python | ee384d1330f6a50ff45a507392ce54f92900f23a | [
"Apache-2.0"
] | 4 | 2019-07-01T13:12:50.000Z | 2019-07-02T20:01:37.000Z | aries_cloudagent/protocols/present_proof/dif/tests/test_pres_request.py | kuraakhilesh8230/aries-cloudagent-python | ee384d1330f6a50ff45a507392ce54f92900f23a | [
"Apache-2.0"
] | 51 | 2021-01-12T05:50:50.000Z | 2022-03-25T06:03:13.000Z | aries_cloudagent/protocols/present_proof/dif/tests/test_pres_request.py | kuraakhilesh8230/aries-cloudagent-python | ee384d1330f6a50ff45a507392ce54f92900f23a | [
"Apache-2.0"
] | 12 | 2019-06-24T22:17:44.000Z | 2019-07-02T19:49:31.000Z | from unittest import TestCase
from ..pres_request_schema import DIFProofRequestSchema
| 38.651376 | 101 | 0.350344 |
0b066a126354f8b346cb7cd4adb064a1438b7f2c | 1,190 | py | Python | datadog/api/screenboards.py | gust/datadogpy | 94f7dfeed87849a615916a5f171b25400b7c6cc5 | [
"BSD-3-Clause"
] | null | null | null | datadog/api/screenboards.py | gust/datadogpy | 94f7dfeed87849a615916a5f171b25400b7c6cc5 | [
"BSD-3-Clause"
] | null | null | null | datadog/api/screenboards.py | gust/datadogpy | 94f7dfeed87849a615916a5f171b25400b7c6cc5 | [
"BSD-3-Clause"
] | null | null | null | from datadog.api.resources import GetableAPIResource, CreateableAPIResource, \
UpdatableAPIResource, DeletableAPIResource, ActionAPIResource, ListableAPIResource
| 31.315789 | 90 | 0.668908 |
0b07019b4136badacad9043f3524e2c6ae411079 | 10,525 | py | Python | models/TCNet.py | sjenni/LCI | 5313fe9eb43fce8f0352828094369bc153d98eb1 | [
"MIT"
] | 13 | 2020-05-01T12:55:20.000Z | 2021-09-30T14:44:33.000Z | models/TCNet.py | sjenni/LCI | 5313fe9eb43fce8f0352828094369bc153d98eb1 | [
"MIT"
] | 1 | 2020-06-25T23:19:07.000Z | 2020-06-25T23:19:07.000Z | models/TCNet.py | sjenni/LCI | 5313fe9eb43fce8f0352828094369bc153d98eb1 | [
"MIT"
] | 8 | 2020-05-25T19:13:25.000Z | 2021-09-24T05:34:36.000Z | from .alexnet import alexnet_V2
import tensorflow.compat.v1 as tf
import tensorflow.contrib.slim as slim
from utils import montage_tf
from .lci_nets import patch_inpainter, patch_discriminator
import tensorflow.contrib as contrib
# Average pooling params for imagenet linear classifier experiments
AVG_POOL_PARAMS = {'... | 41.113281 | 120 | 0.618622 |
0b07d80b933132232b4df2d891725e4a81593fd0 | 1,486 | py | Python | dbs/dal/Whiteport.py | xinghejd/opencanary_web | 0d7eec70e154ad2d172175ab3bff48ba8999d5d9 | [
"BSD-3-Clause"
] | 633 | 2018-09-04T03:55:10.000Z | 2022-03-18T07:21:01.000Z | dbs/dal/Whiteport.py | fankeji/opencanary_web | 71156ef8d7f86e2bb380a69f584de9603bfba93a | [
"BSD-3-Clause"
] | 51 | 2018-12-27T15:46:33.000Z | 2022-03-03T03:16:16.000Z | dbs/dal/Whiteport.py | fankeji/opencanary_web | 71156ef8d7f86e2bb380a69f584de9603bfba93a | [
"BSD-3-Clause"
] | 233 | 2018-09-04T05:59:50.000Z | 2022-03-10T06:00:30.000Z | #!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Author: pirogue
Purpose:
Site: http://pirogue.org
Created: 2018-08-03 17:32:54
"""
from dbs.initdb import DBSession
from dbs.models.Whiteport import Whiteport
from sqlalchemy import desc,asc
from sqlalchemy.exc import InvalidRequestError
# import sys
# sys... | 24.360656 | 73 | 0.596231 |
0b080bc190d330770740d83db0e379029d019b52 | 789 | py | Python | anyconfig/singleton.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | anyconfig/singleton.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | anyconfig/singleton.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | #
# Copyright (C) 2018 Satoru SATOH <ssato @ redhat.com>
# License: MIT
#
r"""Singleton class
.. versionadded:: 0.9.8
- Add to make a kind of manager instancne later to manage plugins.
"""
from __future__ import absolute_import
import threading
# vim:sw=4:ts=4:et:
| 22.542857 | 73 | 0.6109 |
0b0815c2d6a9cafe4678f5aa35ab346506fdf7c6 | 4,937 | py | Python | geophires_simulation/main.py | tuw-eeg/GEOPHIRES-simulation | 14343cefd7c373f240e610a5a5a1143457a4f8d4 | [
"Apache-2.0"
] | null | null | null | geophires_simulation/main.py | tuw-eeg/GEOPHIRES-simulation | 14343cefd7c373f240e610a5a5a1143457a4f8d4 | [
"Apache-2.0"
] | null | null | null | geophires_simulation/main.py | tuw-eeg/GEOPHIRES-simulation | 14343cefd7c373f240e610a5a5a1143457a4f8d4 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Tue Sep 9 10:37:24 2020
@author: fallahnejad
Important Note: all the costs provided in EUR should be multiplied by EUR2USD factor before providing to the GEOPHIRES
"""
import os
import re
import shutil
import pandas as pd
from .cm.geophires.GEOPHIRESv2 import geophires
| 40.801653 | 119 | 0.625886 |
0b08ce05031842d1b1da5e73875c7ace68953124 | 6,040 | py | Python | mydb/test_postgres.py | dappsunilabs/DB4SCI | 54bdd03aaa12957e622c921b263e187740a8b2ae | [
"Apache-2.0"
] | 7 | 2018-12-05T19:18:20.000Z | 2020-11-21T07:27:54.000Z | mydb/test_postgres.py | dappsunilabs/DB4SCI | 54bdd03aaa12957e622c921b263e187740a8b2ae | [
"Apache-2.0"
] | 8 | 2018-04-25T06:02:41.000Z | 2020-09-08T21:55:56.000Z | mydb/test_postgres.py | FredHutch/DB4SCI | cc950a36b6b678fe16c1c91925ec402581636fc0 | [
"Apache-2.0"
] | 2 | 2019-11-14T02:09:09.000Z | 2021-12-28T19:05:51.000Z | #!/usr/bin/python
import time
import psycopg2
import argparse
import postgres_util
import container_util
import admin_db
import volumes
from send_mail import send_mail
from config import Config
if __name__ == "__main__":
dbtype = 'Postgres'
con_name = 'postgres-test'
params = setup(dbtype, con_name)
... | 36.606061 | 86 | 0.565728 |
0b09670421913d5dc655e11f02bde1b874775f20 | 4,742 | py | Python | perfectextractor/tests/test_extractor.py | UUDigitalHumanitieslab/time-in-translation | 2b1a3ef2d382b725ec87f0266fc726fbeb818e7b | [
"MIT"
] | 3 | 2020-04-22T15:12:58.000Z | 2021-05-31T16:36:23.000Z | perfectextractor/tests/test_extractor.py | UUDigitalHumanitieslab/time-in-translation | 2b1a3ef2d382b725ec87f0266fc726fbeb818e7b | [
"MIT"
] | 13 | 2017-08-17T13:31:40.000Z | 2022-03-11T10:29:22.000Z | perfectextractor/tests/test_extractor.py | UUDigitalHumanitieslab/time-in-translation | 2b1a3ef2d382b725ec87f0266fc726fbeb818e7b | [
"MIT"
] | 1 | 2020-04-16T10:33:05.000Z | 2020-04-16T10:33:05.000Z | # -*- coding: utf-8 -*-
import unittest
from lxml import etree
from perfectextractor.apps.extractor.models import Perfect
from perfectextractor.corpora.opus.perfect import OPUSPerfectExtractor
| 43.907407 | 110 | 0.653522 |
0b09bab5310470d71a60ceebe7eea1ff4b9be3ca | 4,303 | py | Python | python/tvm/tensor_graph/core/auto_schedule/utils.py | QinHan-Erin/AMOS | 634bf48edf4015e4a69a8c32d49b96bce2b5f16f | [
"Apache-2.0"
] | 22 | 2022-03-18T07:29:31.000Z | 2022-03-23T14:54:32.000Z | python/tvm/tensor_graph/core/auto_schedule/utils.py | QinHan-Erin/AMOS | 634bf48edf4015e4a69a8c32d49b96bce2b5f16f | [
"Apache-2.0"
] | null | null | null | python/tvm/tensor_graph/core/auto_schedule/utils.py | QinHan-Erin/AMOS | 634bf48edf4015e4a69a8c32d49b96bce2b5f16f | [
"Apache-2.0"
] | 2 | 2022-03-18T08:26:34.000Z | 2022-03-20T06:02:48.000Z | import tvm
from functools import reduce
from ..utils import to_int, to_int_or_None
def tile_axes(sch, op, axes, need_tile, split_factors, inner_to_outer=False):
"""Tile axes according to need_tile and split_factors
"""
axis_map = {}
count_axis = 0
split_axis_list = []
split_factor_list = []
for axis,... | 28.496689 | 115 | 0.660702 |
0b0b1a7b4c5a81ec7957c24cfd67e9ce4f84e8eb | 7,311 | py | Python | SCALA_library/Lower_level_tools/pyCorner260.py | snfactory/scala | f046d0e458bc4146546e80df16e15259f6019f93 | [
"Apache-2.0"
] | null | null | null | SCALA_library/Lower_level_tools/pyCorner260.py | snfactory/scala | f046d0e458bc4146546e80df16e15259f6019f93 | [
"Apache-2.0"
] | null | null | null | SCALA_library/Lower_level_tools/pyCorner260.py | snfactory/scala | f046d0e458bc4146546e80df16e15259f6019f93 | [
"Apache-2.0"
] | null | null | null | ###########################################################
# LOWER LEVEL LIBRARY THAT TALKS TO THE MONOCHROMATON #
###########################################################
import subprocess
import time
# -- See pyserial
import serial
if __name__ == '__main__':
cs = CornerStone260( port = '/... | 36.193069 | 95 | 0.562987 |
0b0d5b4aaea543cf63af89cd9a03e2708a9fbab7 | 4,845 | py | Python | resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/AutoDockTools/autoflex4Commands.py | J-E-J-S/aaRS-Pipeline | 43f59f28ab06e4b16328c3bc405cdddc6e69ac44 | [
"MIT"
] | 8 | 2021-12-14T21:30:01.000Z | 2022-02-14T11:30:03.000Z | resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/AutoDockTools/autoflex4Commands.py | J-E-J-S/aaRS-Pipeline | 43f59f28ab06e4b16328c3bc405cdddc6e69ac44 | [
"MIT"
] | null | null | null | resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/AutoDockTools/autoflex4Commands.py | J-E-J-S/aaRS-Pipeline | 43f59f28ab06e4b16328c3bc405cdddc6e69ac44 | [
"MIT"
] | null | null | null | #############################################################################
#
# Author: Ruth HUEY, Michel F. SANNER
#
# Copyright: M. Sanner TSRI 2008
#
#############################################################################
# $Header: /opt/cvs/python/packages/share1.5/AutoDockTools/autoflex4Commands.py,v 1.1 ... | 36.984733 | 118 | 0.707327 |
0b0e2f1e049e622e46932ea64784ee002a5a6564 | 6,801 | py | Python | cohesity_management_sdk/models/net_app_volume_information.py | sachinthakare-cohesity/management-sdk-python | c95f67b7d387d5bab8392be43190e598280ae7b5 | [
"MIT"
] | null | null | null | cohesity_management_sdk/models/net_app_volume_information.py | sachinthakare-cohesity/management-sdk-python | c95f67b7d387d5bab8392be43190e598280ae7b5 | [
"MIT"
] | null | null | null | cohesity_management_sdk/models/net_app_volume_information.py | sachinthakare-cohesity/management-sdk-python | c95f67b7d387d5bab8392be43190e598280ae7b5 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Copyright 2019 Cohesity Inc.
import cohesity_management_sdk.models.cifs_share_information
import cohesity_management_sdk.models.volume_security_information
| 43.877419 | 200 | 0.641964 |
0b0f14dc9edd917b5943eaee8fa4e20472331f44 | 170 | py | Python | src/matlab2cpp/node/__init__.py | neilferg/matlab2cpp | aa26671fc73dad297c977511053b076e05bdd2df | [
"BSD-3-Clause"
] | null | null | null | src/matlab2cpp/node/__init__.py | neilferg/matlab2cpp | aa26671fc73dad297c977511053b076e05bdd2df | [
"BSD-3-Clause"
] | null | null | null | src/matlab2cpp/node/__init__.py | neilferg/matlab2cpp | aa26671fc73dad297c977511053b076e05bdd2df | [
"BSD-3-Clause"
] | null | null | null | """
The module contains the following submodules.
"""
from .frontend import Node
__all__ = ["Node"]
if __name__ == "__main__":
import doctest
doctest.testmod()
| 15.454545 | 45 | 0.688235 |
0b0f2186008ea5990d722ee460df30182fea5006 | 1,088 | py | Python | ipsc/2016/f.py | csferng/competitive-programming | f7ae710392c0fd606f735df6efcfca5e8fbd3501 | [
"MIT"
] | null | null | null | ipsc/2016/f.py | csferng/competitive-programming | f7ae710392c0fd606f735df6efcfca5e8fbd3501 | [
"MIT"
] | null | null | null | ipsc/2016/f.py | csferng/competitive-programming | f7ae710392c0fd606f735df6efcfca5e8fbd3501 | [
"MIT"
] | null | null | null | import collections
import itertools
import re
import sys
read_str = lambda : sys.stdin.readline().strip()
read_str_list = lambda : sys.stdin.readline().strip().split()
read_int = lambda : int(read_str())
read_int_list = lambda : map(int, read_str_list())
read_float = lambda : float(read_str())
read_float_list = lambda... | 21.76 | 76 | 0.581801 |
0b1003b9ec3ab93ffe28039b6241e37c51da92c6 | 5,958 | py | Python | mcpython/common/data/gen/TextureDataGen.py | mcpython4-coding/core | e4c4f59dab68c90e2028db3add2e5065116bf4a6 | [
"CC0-1.0",
"MIT"
] | 2 | 2019-11-02T05:26:11.000Z | 2019-11-03T08:52:18.000Z | mcpython/common/data/gen/TextureDataGen.py | mcpython4-coding/core | e4c4f59dab68c90e2028db3add2e5065116bf4a6 | [
"CC0-1.0",
"MIT"
] | 25 | 2019-11-02T05:24:29.000Z | 2022-02-09T14:09:08.000Z | mcpython/common/data/gen/TextureDataGen.py | mcpython4-coding/core | e4c4f59dab68c90e2028db3add2e5065116bf4a6 | [
"CC0-1.0",
"MIT"
] | 5 | 2019-11-09T05:36:06.000Z | 2021-11-28T13:07:08.000Z | """
mcpython - a minecraft clone written in python licenced under the MIT-licence
(https://github.com/mcpython4-coding/core)
Contributors: uuk, xkcdjerry (inactive)
Based on the game of fogleman (https://github.com/fogleman/Minecraft), licenced under the MIT-licence
Original game "minecraft" by Mojang Studios (www.m... | 35.891566 | 125 | 0.544982 |
0b10cab889db1a04677f05bcfb228ad6218dea84 | 9,537 | py | Python | qinling/tests/unit/api/controllers/v1/test_webhook.py | goldyfruit/qinling | 7e1391056cc90c274f063ea25b59bb138fdfef94 | [
"Apache-2.0"
] | null | null | null | qinling/tests/unit/api/controllers/v1/test_webhook.py | goldyfruit/qinling | 7e1391056cc90c274f063ea25b59bb138fdfef94 | [
"Apache-2.0"
] | null | null | null | qinling/tests/unit/api/controllers/v1/test_webhook.py | goldyfruit/qinling | 7e1391056cc90c274f063ea25b59bb138fdfef94 | [
"Apache-2.0"
] | null | null | null | # Copyright 2018 Catalyst IT Limited
#
# 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... | 35.585821 | 79 | 0.624934 |
0b112c171eb02964d852f653ff119690933ba7a7 | 314 | py | Python | setup.py | elcolumbio/goofy | f922db2b9662fcc5e26529a2d428feaabede6b42 | [
"Apache-2.0"
] | 1 | 2018-06-29T06:03:17.000Z | 2018-06-29T06:03:17.000Z | setup.py | elcolumbio/goofy | f922db2b9662fcc5e26529a2d428feaabede6b42 | [
"Apache-2.0"
] | null | null | null | setup.py | elcolumbio/goofy | f922db2b9662fcc5e26529a2d428feaabede6b42 | [
"Apache-2.0"
] | null | null | null | from setuptools import setup
setup(name='goofy',
version='0.1',
description='A goofy ebay bot.',
url='github.com/elcolumbio/goofy',
author='Florian Benk',
author_email='f.benkoe@innotrade24.de',
license='Apache License, Version 2.0 (the "License")',
packages=['goofy'])
| 28.545455 | 60 | 0.640127 |
0b114a97cf42ee5a0905829c9063503a14dd4b05 | 1,820 | py | Python | nxt/main.py | TeamGalileoRobotics/qLearning | 70333f45373abc72a489e1ac4089f8e3db34c6a8 | [
"MIT"
] | 4 | 2017-09-27T16:16:58.000Z | 2019-11-27T09:26:54.000Z | nxt/main.py | TeamGalileoRobotics/qLearning | 70333f45373abc72a489e1ac4089f8e3db34c6a8 | [
"MIT"
] | null | null | null | nxt/main.py | TeamGalileoRobotics/qLearning | 70333f45373abc72a489e1ac4089f8e3db34c6a8 | [
"MIT"
] | null | null | null | import random
import os
import traceback
import json
from environment import Environment
from environment import Action
# 0 <= GAMMA < 1
# GAMMA = 0 -> only consider immediate rewards
# GAMMA = 1 -> consider future rewards
GAMMA = 0.8
confidence = 0
# initialize "brain"
brain = open("brainFile", "r")
if(os.stat(".... | 21.162791 | 104 | 0.638462 |