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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a33e27da81bb7bce9e69f05f780fb86f4b322234 | 501 | py | Python | tests/test_trinomial.py | caltechlibrary/trinomial | 0313e16400aca50f54bfe79080a10a1977702e9a | [
"BSD-3-Clause"
] | 1 | 2021-05-22T17:29:17.000Z | 2021-05-22T17:29:17.000Z | tests/test_trinomial.py | caltechlibrary/trinomial | 0313e16400aca50f54bfe79080a10a1977702e9a | [
"BSD-3-Clause"
] | null | null | null | tests/test_trinomial.py | caltechlibrary/trinomial | 0313e16400aca50f54bfe79080a10a1977702e9a | [
"BSD-3-Clause"
] | null | null | null | import os
import pytest
import sys
from time import time
try:
thisdir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(thisdir, '..'))
except:
sys.path.append('..')
import trinomial
def test_basic():
trinomial.set_unique_key('x')
assert trinomial.anon('foo@bar.com') == ... | 22.772727 | 56 | 0.686627 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 89 | 0.177645 |
a33e48a10e11e80e4f5b747b61f4474ae03b0923 | 667 | py | Python | openprocurement/tender/openeu/views/award_complaint_document.py | leits/openprocurement.tender.openeu | 6e8b6650a23761cc09794030583206029a2928e8 | [
"Apache-2.0"
] | 1 | 2016-02-02T09:55:08.000Z | 2016-02-02T09:55:08.000Z | openprocurement/tender/openeu/views/award_complaint_document.py | Leits/openprocurement.tender.openeu | 6e8b6650a23761cc09794030583206029a2928e8 | [
"Apache-2.0"
] | 2 | 2021-03-26T00:35:37.000Z | 2022-03-21T22:21:31.000Z | openprocurement/tender/openeu/views/award_complaint_document.py | leits/openprocurement.tender.openeu | 6e8b6650a23761cc09794030583206029a2928e8 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from openprocurement.api.utils import opresource
from openprocurement.tender.openua.views.award_complaint_document import TenderUaAwardComplaintDocumentResource
@opresource(name='Tender EU Award Complaint Documents',
collection_path='/tenders/{tender_id}/awards/{award_id}/complaint... | 51.307692 | 111 | 0.773613 | 94 | 0.14093 | 0 | 0 | 479 | 0.718141 | 0 | 0 | 278 | 0.416792 |
a33e4ece404ced51ee4f1506f207476b0d455c63 | 2,398 | py | Python | pymic/layer/activation.py | vincentme/PyMIC | 5cbbca7d0a19232be647086d4686ceea523f45ee | [
"Apache-2.0"
] | 147 | 2019-12-23T02:52:04.000Z | 2022-03-06T16:30:43.000Z | pymic/layer/activation.py | vincentme/PyMIC | 5cbbca7d0a19232be647086d4686ceea523f45ee | [
"Apache-2.0"
] | 4 | 2020-12-18T12:47:21.000Z | 2021-05-21T02:18:01.000Z | pymic/layer/activation.py | vincentme/PyMIC | 5cbbca7d0a19232be647086d4686ceea523f45ee | [
"Apache-2.0"
] | 32 | 2020-01-08T13:48:50.000Z | 2022-03-12T06:31:13.000Z | # -*- coding: utf-8 -*-
from __future__ import print_function, division
import torch
import torch.nn as nn
def get_acti_func(acti_func, params):
acti_func = acti_func.lower()
if(acti_func == 'relu'):
inplace = params.get('relu_inplace', False)
return nn.ReLU(inplace)
elif(acti_func == 'l... | 31.552632 | 67 | 0.607173 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 483 | 0.201418 |
a33eb973d0edc831eea7bb11066042e56e9c2e88 | 3,359 | py | Python | ui/flowlayout.py | amadotejada/self-portal | c508fb120548f3eb65e872d08a823d3942fc650d | [
"Apache-2.0"
] | 9 | 2022-03-15T02:02:30.000Z | 2022-03-18T16:16:59.000Z | ui/flowlayout.py | amadotejada/self-portal | c508fb120548f3eb65e872d08a823d3942fc650d | [
"Apache-2.0"
] | null | null | null | ui/flowlayout.py | amadotejada/self-portal | c508fb120548f3eb65e872d08a823d3942fc650d | [
"Apache-2.0"
] | null | null | null | # Copyright 2021 Amado Tejada
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | 31.688679 | 112 | 0.575171 | 2,659 | 0.791605 | 0 | 0 | 0 | 0 | 0 | 0 | 578 | 0.172075 |
a340df3cf71eb1be1675fbe29cece65cbcc98d43 | 3,183 | py | Python | methods/smartdumpRJ.py | wdempsey/sense2stop-lvm | ea44d5f9199382d30e4c5a5ff4bd524313ceb5b2 | [
"CECILL-B"
] | 1 | 2020-04-18T11:16:02.000Z | 2020-04-18T11:16:02.000Z | methods/smartdumpRJ.py | wdempsey/sense2stop-lvm | ea44d5f9199382d30e4c5a5ff4bd524313ceb5b2 | [
"CECILL-B"
] | 6 | 2020-04-13T18:38:04.000Z | 2022-03-12T00:55:56.000Z | methods/smartdumpRJ.py | wdempsey/sense2stop-lvm | ea44d5f9199382d30e4c5a5ff4bd524313ceb5b2 | [
"CECILL-B"
] | 1 | 2020-07-02T04:47:00.000Z | 2020-07-02T04:47:00.000Z | # -*- coding: utf-8 -*-
"""
Created on Tue May 26 14:29:26 2020
@author: Walter Dempsey & Jamie Yap
"""
#%%
###############################################################################
# Build a RJMCMC class
###############################################################################
from pymc import Stochast... | 31.514851 | 88 | 0.602576 | 2,729 | 0.857367 | 0 | 0 | 0 | 0 | 0 | 0 | 1,544 | 0.485077 |
a34205264c406b528a6fcfa5ac69debf00a2b02c | 2,021 | py | Python | tests/test_slack_user.py | tomcooperca/mlb-slack-tracker | bbfd8ed6f0c345d5286813a6cd4b04e0557a762a | [
"MIT"
] | null | null | null | tests/test_slack_user.py | tomcooperca/mlb-slack-tracker | bbfd8ed6f0c345d5286813a6cd4b04e0557a762a | [
"MIT"
] | 7 | 2018-09-08T20:07:43.000Z | 2021-12-13T19:54:53.000Z | tests/test_slack_user.py | tomcooperca/mlb-slack-tracker | bbfd8ed6f0c345d5286813a6cd4b04e0557a762a | [
"MIT"
] | null | null | null | from unittest.mock import MagicMock
from slack.user import User
from baseball.team import Team
reusableUser = User(token='blah', id='UB00123', team=None)
testTeam = Team(abbreviation='CN', location='City Name',
full_name='City Name Players', record='0W-162L', division='CL Beast',
wins=0, losses=162, standing=5... | 34.844828 | 74 | 0.730332 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 321 | 0.158832 |
a342151afcda4ba72f2d257247a2de01de22ba98 | 1,934 | py | Python | tmuxp/testsuite/test_workspacefreezer.py | wrongwaycn/tmuxp | 367cca3eb1b3162bb7e4801fe752b520f1f8eefa | [
"BSD-3-Clause"
] | 2 | 2018-02-05T01:27:07.000Z | 2018-06-10T02:02:25.000Z | tmuxp/testsuite/test_workspacefreezer.py | wrongwaycn/tmuxp | 367cca3eb1b3162bb7e4801fe752b520f1f8eefa | [
"BSD-3-Clause"
] | null | null | null | tmuxp/testsuite/test_workspacefreezer.py | wrongwaycn/tmuxp | 367cca3eb1b3162bb7e4801fe752b520f1f8eefa | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function, with_statement
import os
import sys
import logging
import time
import kaptan
from .. import Window, config, exc
from ..workspacebuilder import WorkspaceBuilder, freeze
from .helpers import TmuxTestCase
logger = logging.getLogger... | 23.585366 | 80 | 0.609617 | 1,473 | 0.761634 | 0 | 0 | 0 | 0 | 0 | 0 | 607 | 0.313857 |
a343d4acc1180ec43471b02424e6695cc4893a9e | 9,132 | py | Python | libs/configs/DOTA1.0/dota_train/cfgs_res50_dotatrain_dcl_v15.py | Thinklab-SJTU/DCL_RetinaNet_Tensorflow | 1d14c9800c3eb1975e8832978f7a263783d171ec | [
"Apache-2.0"
] | 36 | 2020-11-19T07:23:42.000Z | 2022-03-30T03:35:57.000Z | libs/configs/DOTA1.0/dota_train/cfgs_res50_dotatrain_dcl_v15.py | Thinklab-SJTU/DCL_RetinaNet_Tensorflow | 1d14c9800c3eb1975e8832978f7a263783d171ec | [
"Apache-2.0"
] | 4 | 2021-01-30T09:49:10.000Z | 2021-12-05T12:49:11.000Z | libs/configs/DOTA1.0/dota_train/cfgs_res50_dotatrain_dcl_v15.py | Thinklab-SJTU/DCL_RetinaNet_Tensorflow | 1d14c9800c3eb1975e8832978f7a263783d171ec | [
"Apache-2.0"
] | 6 | 2020-11-23T07:54:47.000Z | 2021-07-09T07:20:15.000Z | # -*- coding: utf-8 -*-
from __future__ import division, print_function, absolute_import
import os
import tensorflow as tf
import math
"""
GCL + OMEGA = 180 / 512.
{'0.6': {'ground-track-field': 0.573582489319409, 'harbor': 0.3891521609424017, 'bridge': 0.2563337419887201, 'small-vehicle': 0.5648505388890961, 'plane'... | 71.34375 | 583 | 0.727551 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6,726 | 0.736531 |
a34438fcd2d05af774f8b7d208037ebd093f49f3 | 1,488 | py | Python | test.py | KyleJeong/ast_calculator | cf65ad76739839ac4b3df36b82862612d6bd4492 | [
"MIT"
] | 6 | 2016-07-20T07:37:07.000Z | 2022-01-14T06:35:26.000Z | test.py | KyleJeong/ast_calculator | cf65ad76739839ac4b3df36b82862612d6bd4492 | [
"MIT"
] | 1 | 2020-03-29T05:13:58.000Z | 2020-03-29T05:13:58.000Z | test.py | KyleJeong/ast_calculator | cf65ad76739839ac4b3df36b82862612d6bd4492 | [
"MIT"
] | 1 | 2020-03-29T04:29:36.000Z | 2020-03-29T04:29:36.000Z | """
Test cases for AST calculator
"""
from unittest import TestCase
from calc import evaluate
class TestCaclEvaluate(TestCase):
"""
Test cases for AST calculator - evaluation
"""
def test_simple_expression(self):
"""
Test expression without functions or constants
"""
... | 23.619048 | 62 | 0.511425 | 1,390 | 0.93414 | 0 | 0 | 0 | 0 | 0 | 0 | 467 | 0.313844 |
a3446186d570e00d5586a746c5e62060ac9246b6 | 315 | py | Python | app/main/utils.py | tmeftah/e-invoice | 7cfe31e9391eb60ab3d06f0055bd2f1e9a524971 | [
"MIT"
] | 2 | 2019-06-10T19:30:06.000Z | 2020-04-30T01:05:04.000Z | app/main/utils.py | tmeftah/e-invoice | 7cfe31e9391eb60ab3d06f0055bd2f1e9a524971 | [
"MIT"
] | null | null | null | app/main/utils.py | tmeftah/e-invoice | 7cfe31e9391eb60ab3d06f0055bd2f1e9a524971 | [
"MIT"
] | 3 | 2019-01-23T21:37:29.000Z | 2020-04-08T13:22:29.000Z | from flask import request
from app.main.extensions import cache
def clear_cache(key_prefix):
keys = [key for key in cache.cache._cache.keys() if key.startswith(key_prefix)]
cache.delete_many(*keys)
def cache_json_keys():
json_data = tuple(sorted(request.get_json().items()))
return json_data
| 19.6875 | 83 | 0.733333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
a344e089a4efbd0afbd6c50e23cff7269d7dd9c8 | 1,931 | py | Python | gum/managers.py | marcosgabarda/django-gum | 796a496e95391aab9e462bde6d8f775534d5f6c6 | [
"MIT"
] | 16 | 2015-05-04T18:47:33.000Z | 2021-02-03T17:10:40.000Z | gum/managers.py | marcosgabarda/django-gum | 796a496e95391aab9e462bde6d8f775534d5f6c6 | [
"MIT"
] | 4 | 2015-09-08T14:48:31.000Z | 2016-09-09T09:49:41.000Z | gum/managers.py | marcosgabarda/django-gum | 796a496e95391aab9e462bde6d8f775534d5f6c6 | [
"MIT"
] | 2 | 2015-05-04T18:39:23.000Z | 2016-04-18T14:35:47.000Z | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from gum.utils import elasticsearch_connection
class ElasticsearchManager(object):
"""Like a `ModelManager` gives to the user methods to apply queries
to Elasticsearch from a specific model.
"""
def __init__(self, model=None, mapping_ty... | 32.183333 | 86 | 0.658726 | 1,813 | 0.938892 | 0 | 0 | 0 | 0 | 0 | 0 | 810 | 0.419472 |
a34991845be5613841f0b124224655a27cd95755 | 1,732 | py | Python | app.py | u-aaa/House-_prediction_model | 4808b4aefb802520a7ccd878c342699093e6942d | [
"MIT"
] | null | null | null | app.py | u-aaa/House-_prediction_model | 4808b4aefb802520a7ccd878c342699093e6942d | [
"MIT"
] | null | null | null | app.py | u-aaa/House-_prediction_model | 4808b4aefb802520a7ccd878c342699093e6942d | [
"MIT"
] | 1 | 2021-09-23T19:42:36.000Z | 2021-09-23T19:42:36.000Z | import pickle
import json
import numpy as np
from flask import Flask, request, jsonify
app = Flask(__name__)
with open('models/regressor.pkl', 'rb') as f:
model = pickle.load(f)
def __process_input(posted_data) -> np.array:
'''
transforms JSON type data acquired from request and transforms it into 2D ... | 28.393443 | 105 | 0.639723 | 0 | 0 | 0 | 0 | 758 | 0.437644 | 0 | 0 | 500 | 0.288684 |
a34ab44ceb198f7ffec0e7a91a4d37823eb68330 | 4,734 | py | Python | sobit_bringup/src/joint_state_listner.py | Choi-Laboratory/sobit_blue | 81a228390e1726653d54f33afb3fbb1c1fdb5b24 | [
"Apache-2.0"
] | null | null | null | sobit_bringup/src/joint_state_listner.py | Choi-Laboratory/sobit_blue | 81a228390e1726653d54f33afb3fbb1c1fdb5b24 | [
"Apache-2.0"
] | null | null | null | sobit_bringup/src/joint_state_listner.py | Choi-Laboratory/sobit_blue | 81a228390e1726653d54f33afb3fbb1c1fdb5b24 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python
# -*- coding: utf-8 -*-
import rospy
import math
from sensor_msgs.msg import *
from geometry_msgs.msg import *
from sobit_bringup.msg import *
#---グローバル変数-----------------------------
motion = [0]*21
TIME = 0.1
serial_joint = Serial_motion()
state_jointstate = JointState()
state_jointstate.name =["... | 37.872 | 322 | 0.603929 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,869 | 0.383778 |
a34d2a23f38ff576e6a5ef0f805165729d2fc6ef | 2,789 | py | Python | scalex/metrics.py | jsxlei/SCALEX | 021c6d35a0cebeaa1f59ea53b9b9e22015ce6e5f | [
"MIT"
] | 11 | 2021-04-09T02:46:29.000Z | 2022-01-04T16:42:44.000Z | scale/metrics.py | QingZhan98/SCALE_v2 | 69bb02beee40ec085684335f356798d4dcb53fbc | [
"MIT"
] | 2 | 2021-04-18T02:30:18.000Z | 2022-03-05T10:40:00.000Z | scale/metrics.py | QingZhan98/SCALE_v2 | 69bb02beee40ec085684335f356798d4dcb53fbc | [
"MIT"
] | 4 | 2021-03-29T12:34:47.000Z | 2022-03-06T12:42:45.000Z | #!/usr/bin/env python
"""
# Author: Xiong Lei
# Created Time : Thu 10 Jan 2019 07:38:10 PM CST
# File Name: metrics.py
# Description:
"""
import numpy as np
import scipy
from sklearn.neighbors import NearestNeighbors, KNeighborsRegressor
def batch_entropy_mixing_score(data, batches, n_neighbors=100, n_pools=100, n... | 34.8625 | 114 | 0.639656 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,248 | 0.447472 |
a34d8a9377344d0edaae44dd4947affb31816584 | 189 | py | Python | src/miu/colorbilding.py | memowe/miniciti-user | ce1cbccdb693c4916217e1395eacb14f06d536a1 | [
"MIT"
] | null | null | null | src/miu/colorbilding.py | memowe/miniciti-user | ce1cbccdb693c4916217e1395eacb14f06d536a1 | [
"MIT"
] | null | null | null | src/miu/colorbilding.py | memowe/miniciti-user | ce1cbccdb693c4916217e1395eacb14f06d536a1 | [
"MIT"
] | null | null | null | from miniciti.bilding import Bilding
class ColorBilding(Bilding):
def __init__(self, color="bli"):
self.color = color
def isBli(self):
return self.color == "bli"
| 18.9 | 36 | 0.650794 | 150 | 0.793651 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0.05291 |
a34e461868bd92e65252352e4554823a69ea35c7 | 2,603 | py | Python | examples/data/create_data.py | fdabek1/EHR-Functions | e6bd0b6fa213930358c4a19be31c459ac7430ca9 | [
"MIT"
] | null | null | null | examples/data/create_data.py | fdabek1/EHR-Functions | e6bd0b6fa213930358c4a19be31c459ac7430ca9 | [
"MIT"
] | null | null | null | examples/data/create_data.py | fdabek1/EHR-Functions | e6bd0b6fa213930358c4a19be31c459ac7430ca9 | [
"MIT"
] | null | null | null | import pandas as pd
import random
import time
# Source: https://stackoverflow.com/a/553320/556935
def str_time_prop(start, end, date_format, prop):
"""Get a time at a proportion of a range of two formatted times.
start and end should be strings specifying times formated in the
given format (strftime-styl... | 31.743902 | 102 | 0.579332 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 900 | 0.345755 |
a350ecde028977958b337223398f9351c3e4bbec | 1,317 | py | Python | contests/ccpc20qhd/f超时.py | yofn/pyacm | e573f8fdeea77513711f00c42f128795cbba65a6 | [
"Apache-2.0"
] | null | null | null | contests/ccpc20qhd/f超时.py | yofn/pyacm | e573f8fdeea77513711f00c42f128795cbba65a6 | [
"Apache-2.0"
] | null | null | null | contests/ccpc20qhd/f超时.py | yofn/pyacm | e573f8fdeea77513711f00c42f128795cbba65a6 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
'''
#ccpc20qhd-f => 最大联通子图
#如果都是联通的,所有节点都要放进去,
#友好值=联通子图中边的个数-点的个数
#应该所有(友好值>0)联通子图加起来?
#DFS搜索,或者是并查集? 数一数有多少联通块?
#最短路用广搜，全部解用深搜
连通图的复杂度是O(V+E)..
为什么会Runtime Error?
分析:
解法1: DFS做联通块
解法2: 看不包含哪些人，相当于走个捷径!
'''
def f(n,l):
el = [[] for _ in range(n)]
for x,y in l:
if x>y... | 23.105263 | 82 | 0.430524 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 629 | 0.404502 |
a3525d2e36b057b387fd2a242a0be1258c2a7481 | 2,920 | py | Python | test/feature_extraction/list_counter_test.py | tmhatton/MLinPractice | 759706e13181cec864d6aa8ece9ae7042f083e4c | [
"MIT"
] | null | null | null | test/feature_extraction/list_counter_test.py | tmhatton/MLinPractice | 759706e13181cec864d6aa8ece9ae7042f083e4c | [
"MIT"
] | 1 | 2021-10-19T08:09:44.000Z | 2021-10-19T08:09:44.000Z | test/feature_extraction/list_counter_test.py | tmhatton/MLinPractice | 759706e13181cec864d6aa8ece9ae7042f083e4c | [
"MIT"
] | null | null | null | import unittest
import pandas as pd
from code.feature_extraction.list_counter import PhotosNum, URLsNum, HashtagNum, MentionNum, TokenNum
from code.util import COLUMN_PHOTOS, COLUMN_URLS, COLUMN_HASHTAGS, COLUMN_MENTIONS
class PhotosNumTest(unittest.TestCase):
def setUp(self) -> None:
self.INPUT_COLUMN ... | 30.736842 | 161 | 0.667466 | 2,634 | 0.902055 | 0 | 0 | 0 | 0 | 0 | 0 | 404 | 0.138356 |
a352f55dcd4b6a9dcf2653a39663d590b4d79e27 | 926 | py | Python | tests/test_2_promethee.py | qanastek/EasyMCDM | 7fa2e2dfe9397834ca9f50211ea2717a16785394 | [
"MIT"
] | 4 | 2022-03-05T20:51:38.000Z | 2022-03-15T17:10:22.000Z | tests/test_2_promethee.py | qanastek/EasyMCDM | 7fa2e2dfe9397834ca9f50211ea2717a16785394 | [
"MIT"
] | null | null | null | tests/test_2_promethee.py | qanastek/EasyMCDM | 7fa2e2dfe9397834ca9f50211ea2717a16785394 | [
"MIT"
] | 1 | 2022-03-08T13:45:22.000Z | 2022-03-08T13:45:22.000Z | import unittest
from operator import index
from EasyMCDM.models.Promethee import Promethee
class TestPrometheeMethods(unittest.TestCase):
def test_str_str_str(self):
d = "data/partiels_donnees.csv"
p = Promethee(data=d, verbose=False)
res = p.solve(
weights=[0.3, ... | 42.090909 | 161 | 0.565875 | 779 | 0.841253 | 0 | 0 | 0 | 0 | 0 | 0 | 221 | 0.238661 |
a354ea47baa38abfde41024d2fd179d6d96966cf | 1,207 | py | Python | testbed_frontend/api/emulation/emulation_handler.py | Ncu-software-research-center/IIOT-testbed | b4c8f91d1fd1e596d2262152ce99afeb22976f7a | [
"Apache-2.0"
] | 1 | 2021-05-25T09:33:28.000Z | 2021-05-25T09:33:28.000Z | testbed_frontend/api/emulation/emulation_handler.py | Ncu-software-research-center/IIOT-testbed | b4c8f91d1fd1e596d2262152ce99afeb22976f7a | [
"Apache-2.0"
] | 6 | 2020-06-06T01:59:09.000Z | 2021-06-10T20:17:56.000Z | testbed_frontend/api/emulation/emulation_handler.py | Ncu-software-research-center/IIOT-testbed | b4c8f91d1fd1e596d2262152ce99afeb22976f7a | [
"Apache-2.0"
] | null | null | null | '''
Vortex OpenSplice
This software and documentation are Copyright 2006 to TO_YEAR ADLINK
Technology Limited, its affiliated companies and licensors. All rights
reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the Lice... | 32.621622 | 92 | 0.729909 | 0 | 0 | 0 | 0 | 371 | 0.307374 | 0 | 0 | 707 | 0.58575 |
a3551761361e06ddd937cee500aed18df74cd70f | 2,027 | py | Python | torchtraining/functional/metrics/regression.py | szymonmaszke/torchtraining | 1ddf169325b7239d6d6686b20072a406b69a0180 | [
"MIT"
] | 3 | 2020-08-26T06:11:58.000Z | 2020-08-27T08:11:15.000Z | torchtraining/functional/metrics/regression.py | klaudiapalasz/torchtraining | 7ac54009eea2fd84aa635b6f3cbfe306f317d087 | [
"MIT"
] | 1 | 2020-08-25T19:19:43.000Z | 2020-08-25T19:19:43.000Z | torchtraining/functional/metrics/regression.py | klaudiapalasz/torchtraining | 7ac54009eea2fd84aa635b6f3cbfe306f317d087 | [
"MIT"
] | 1 | 2021-04-15T18:55:57.000Z | 2021-04-15T18:55:57.000Z | import typing
import torch
from .. import utils
@utils.docs
def regression_of_squares(
output: torch.Tensor,
target: torch.Tensor,
reduction: typing.Callable[[torch.Tensor,], torch.Tensor,] = torch.sum,
) -> torch.Tensor:
return reduction(output - torch.mean(target)) ** 2
@utils.docs
def squares_o... | 27.026667 | 84 | 0.693143 | 0 | 0 | 0 | 0 | 1,950 | 0.962013 | 0 | 0 | 12 | 0.00592 |
a3552615d55b8131f79fc858dd41da8c30cf2d71 | 6,028 | py | Python | Source/game/systems/puzzle/hold.py | LucXyMan/starseeker | b5c3365514c982734da7d95621e6b85af550ce82 | [
"BSD-3-Clause"
] | null | null | null | Source/game/systems/puzzle/hold.py | LucXyMan/starseeker | b5c3365514c982734da7d95621e6b85af550ce82 | [
"BSD-3-Clause"
] | null | null | null | Source/game/systems/puzzle/hold.py | LucXyMan/starseeker | b5c3365514c982734da7d95621e6b85af550ce82 | [
"BSD-3-Clause"
] | 1 | 2019-11-27T18:00:00.000Z | 2019-11-27T18:00:00.000Z | #!/usr/bin/env python2.7
# -*- coding:UTF-8 -*-2
u"""hold.py
Copyright (c) 2019 Yukio Kuro
This software is released under BSD license.
ホールドピース管理モジュール。
"""
import pieces as _pieces
import utils.const as _const
import utils.layouter as _layouter
class Hold(object):
u"""ホールドピース管理。
"""
__slots__ = (
... | 31.233161 | 77 | 0.535169 | 6,218 | 0.95691 | 0 | 0 | 912 | 0.140351 | 0 | 0 | 1,340 | 0.206217 |
a35602a1c5d4bcf343e77bdb5e4000c799357ee5 | 347 | py | Python | homeworks/kirill_shevchuk/hw05/level04.py | tgrx/Z22 | b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff | [
"Apache-2.0"
] | null | null | null | homeworks/kirill_shevchuk/hw05/level04.py | tgrx/Z22 | b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff | [
"Apache-2.0"
] | 8 | 2019-11-15T18:15:56.000Z | 2020-02-03T18:05:05.000Z | homeworks/kirill_shevchuk/hw05/level04.py | tgrx/Z22 | b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff | [
"Apache-2.0"
] | null | null | null | from urllib.parse import urlparse
def host(url):
if not url:
return ""
data = urlparse(url)
if data.netloc:
return data.netloc
value = data.path.split("/")[0]
if "@" not in value or ":" not in value:
return value
from_ = value.find("@") + 1
for_ = value.find(":")
... | 21.6875 | 44 | 0.570605 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 0.048991 |
a35af943a1738408edb737fd87daf987635bfda0 | 1,554 | py | Python | pertemuan_13/draw_utils.py | Muhammad-Yunus/Jetson-Nano-OpenCV-Learn | 933cb2594539a877030fb82dc3e6867409c1a557 | [
"Apache-2.0"
] | null | null | null | pertemuan_13/draw_utils.py | Muhammad-Yunus/Jetson-Nano-OpenCV-Learn | 933cb2594539a877030fb82dc3e6867409c1a557 | [
"Apache-2.0"
] | null | null | null | pertemuan_13/draw_utils.py | Muhammad-Yunus/Jetson-Nano-OpenCV-Learn | 933cb2594539a877030fb82dc3e6867409c1a557 | [
"Apache-2.0"
] | 2 | 2021-09-28T00:24:21.000Z | 2022-03-09T13:38:29.000Z | import cv2
import numpy as np
# draw_ped() function to draw bounding box with top labeled text
def draw_ped(img, label, x0, y0, xt, yt, font_size=0.4, alpha=0.5, bg_color=(255,0,0), ouline_color=(255,255,255), text_color=(0,0,0)):
overlay = np.zeros_like(img)
y0, yt = max(y0 - 15, 0) , min(yt + 15, img.shape[... | 39.846154 | 135 | 0.47426 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 158 | 0.101673 |
a35b39c11aff2330ec7aa6556e235a658417a015 | 2,204 | py | Python | Sensors/PortStart.py | cybertraining-dsc/boat | 32e4942b69059d1dd48d79c8e0f55bac438eb5e7 | [
"Apache-2.0"
] | null | null | null | Sensors/PortStart.py | cybertraining-dsc/boat | 32e4942b69059d1dd48d79c8e0f55bac438eb5e7 | [
"Apache-2.0"
] | null | null | null | Sensors/PortStart.py | cybertraining-dsc/boat | 32e4942b69059d1dd48d79c8e0f55bac438eb5e7 | [
"Apache-2.0"
] | null | null | null | """
Code modified from:
apps.fishandwhistle.net/archives/1155
"""
from __future__ import print_function
import serial
import sys
import glob
port_list = {}
def identifyPort(port):
"""
tests the port and identifies what device is attached to it from probing it
:param port:
:return: a port list dict w... | 26.878049 | 79 | 0.583031 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 736 | 0.333938 |
a35c7cddf46b7abcc142f392526fdba0c6a3aa7e | 112 | py | Python | test/python/test_utils.py | AdityaSidharta/docker_base | ccdbe7f10e4ddb329dfc106734b3e58226cd0b05 | [
"MIT"
] | null | null | null | test/python/test_utils.py | AdityaSidharta/docker_base | ccdbe7f10e4ddb329dfc106734b3e58226cd0b05 | [
"MIT"
] | null | null | null | test/python/test_utils.py | AdityaSidharta/docker_base | ccdbe7f10e4ddb329dfc106734b3e58226cd0b05 | [
"MIT"
] | null | null | null | from app.python.utils import get_datetime
def test_get_datetime():
assert isinstance(get_datetime(), str)
| 18.666667 | 42 | 0.776786 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
a35f847cfae16fa50a6998fa4b3afcf7165085cb | 883 | py | Python | tests/core/test_registered_plugins.py | MajesticFalcon/nornir | 75f82dbb7f492d0f283abcc5eb6b5fee08db9487 | [
"Apache-2.0"
] | 955 | 2018-05-16T17:10:12.000Z | 2022-03-30T20:14:26.000Z | tests/core/test_registered_plugins.py | MajesticFalcon/nornir | 75f82dbb7f492d0f283abcc5eb6b5fee08db9487 | [
"Apache-2.0"
] | 490 | 2018-05-16T08:00:22.000Z | 2022-03-28T21:14:39.000Z | tests/core/test_registered_plugins.py | MajesticFalcon/nornir | 75f82dbb7f492d0f283abcc5eb6b5fee08db9487 | [
"Apache-2.0"
] | 243 | 2018-05-17T11:07:24.000Z | 2022-03-27T18:01:07.000Z | from nornir.core.plugins.inventory import InventoryPluginRegister
from nornir.core.plugins.runners import RunnersPluginRegister
from nornir.plugins.inventory import SimpleInventory
from nornir.plugins.runners import SerialRunner, ThreadedRunner
from nornir_utils.plugins.inventory import YAMLInventory
class Test:
... | 33.961538 | 65 | 0.737259 | 576 | 0.652322 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 0.056625 |
a3644bcfb5d4ed17d821b83cba8aacde7ddfe23f | 1,411 | py | Python | setup.py | hodgestar/tesseract-control-software | 41f47a4b901a0069f1745c90abe28f0778704b0e | [
"MIT"
] | 2 | 2019-07-13T14:15:30.000Z | 2020-01-04T10:44:47.000Z | setup.py | hodgestar/tesseract-control-software | 41f47a4b901a0069f1745c90abe28f0778704b0e | [
"MIT"
] | null | null | null | setup.py | hodgestar/tesseract-control-software | 41f47a4b901a0069f1745c90abe28f0778704b0e | [
"MIT"
] | null | null | null | from setuptools import setup, find_packages
setup(
name="tessled",
version="0.0.1",
url='http://github.com/hodgestar/tesseract-control-software',
license='MIT',
description="Tesseract control software and simulator.",
long_description=open('README.rst', 'r').read(),
author='Simon Cross',
... | 30.673913 | 65 | 0.593196 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 788 | 0.558469 |
a364c15aa063e5f5b9ce9b053b0dc00b7991aba9 | 45 | py | Python | config.py | grimpy/glunit | ed8b8fabc8539abe94a9bf93418b95d006283066 | [
"MIT"
] | null | null | null | config.py | grimpy/glunit | ed8b8fabc8539abe94a9bf93418b95d006283066 | [
"MIT"
] | null | null | null | config.py | grimpy/glunit | ed8b8fabc8539abe94a9bf93418b95d006283066 | [
"MIT"
] | 1 | 2019-03-02T12:32:40.000Z | 2019-03-02T12:32:40.000Z | GITLAB_URL = "XXXXXX"
GITLAB_TOKEN = "XXXXX"
| 15 | 22 | 0.733333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 0.333333 |
a3670442cb8f6ed8744f92e8d59bbfa74b3455a4 | 481 | py | Python | app/collect/patch.py | luiscape/hdxscraper-unhcr-mediterranean-refugees | 372bd7f565569e1d3a8428e6f09e86a01842bb9c | [
"MIT"
] | null | null | null | app/collect/patch.py | luiscape/hdxscraper-unhcr-mediterranean-refugees | 372bd7f565569e1d3a8428e6f09e86a01842bb9c | [
"MIT"
] | 2 | 2015-10-08T15:41:56.000Z | 2015-10-08T15:50:48.000Z | app/collect/patch.py | luiscape/hdxscraper-unhcr-mediterranean-refugees | 372bd7f565569e1d3a8428e6f09e86a01842bb9c | [
"MIT"
] | null | null | null | #!/usr/bin/python
# -*- coding: utf-8 -*-
import time
def Epoch(data):
'''Patching Epoch timestamps.'''
for record in data:
record['last_updated'] = time.strftime('%Y-%m-%d', time.localtime(record['last_updated']))
return data
def Date(data):
'''Patching date stamps.'''
for record in data:
m = t... | 20.041667 | 94 | 0.619543 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 183 | 0.380457 |
a3686d9e544eb4ac435a125dc81bd7efb5af661e | 1,875 | py | Python | datasets/nlmap/preprocess_nlmap.py | zhuang-li/pyaudio_with_tranx | 934d0431539564bb815c4c2c6399fe9d2fe7db55 | [
"Apache-2.0"
] | null | null | null | datasets/nlmap/preprocess_nlmap.py | zhuang-li/pyaudio_with_tranx | 934d0431539564bb815c4c2c6399fe9d2fe7db55 | [
"Apache-2.0"
] | null | null | null | datasets/nlmap/preprocess_nlmap.py | zhuang-li/pyaudio_with_tranx | 934d0431539564bb815c4c2c6399fe9d2fe7db55 | [
"Apache-2.0"
] | null | null | null | from nltk.tokenize import TweetTokenizer
import io
def read_en_lines(lines):
tknzr = TweetTokenizer()
result = []
for line in lines:
result.append(tknzr.tokenize(line))
return result
def read_mrl_lines(lines):
result = []
for line in lines:
tgt = ''
for i, ch in enume... | 29.296875 | 82 | 0.6208 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 163 | 0.086933 |
a3697ddf813bc6d7c74b1660f1c7cbb233952678 | 2,228 | py | Python | ocr.py | RonLek/ALPR-and-Identification-for-Indian-Vehicles | 2c6cd5d6d883e67ed17a8dbb96830f813c6ab55e | [
"FTL",
"Xnet",
"X11"
] | 13 | 2020-09-25T16:48:06.000Z | 2022-01-31T01:36:33.000Z | ocr.py | RonLek/ALPR-and-Identification-for-Indian-Vehicles | 2c6cd5d6d883e67ed17a8dbb96830f813c6ab55e | [
"FTL",
"Xnet",
"X11"
] | 5 | 2021-01-19T09:36:59.000Z | 2022-03-25T06:56:08.000Z | ocr.py | RonLek/ALPR-and-Identification-for-Indian-Vehicles | 2c6cd5d6d883e67ed17a8dbb96830f813c6ab55e | [
"FTL",
"Xnet",
"X11"
] | 7 | 2020-09-24T01:15:52.000Z | 2022-03-23T06:50:55.000Z | states = ['AP', 'AR', 'AS', 'BR', 'CG', 'GA',
'GJ', 'HR', 'HP', 'JH', 'KA', 'KL',
'MP', 'MH', 'MN', 'ML', 'MZ', 'NL',
'OD', 'PB', 'RJ', 'SK', 'TN', 'TS',
'TR', 'UP', 'UK', 'WB', 'AN', 'CH',
'DD', 'DL', 'JK', 'LA', 'LD', 'PY']
def resultplate(plate):
result=... | 30.520548 | 75 | 0.508528 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 736 | 0.330341 |
a36a1929d767b48efa4751ceab577496580f2e66 | 667 | py | Python | setup.py | LehmRob/photorename | b499b08f225264e5c7be3b51988d8e8fcbeb088f | [
"MIT"
] | null | null | null | setup.py | LehmRob/photorename | b499b08f225264e5c7be3b51988d8e8fcbeb088f | [
"MIT"
] | null | null | null | setup.py | LehmRob/photorename | b499b08f225264e5c7be3b51988d8e8fcbeb088f | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
from setuptools import setup
from distutils.util import convert_path
main_ns = {}
vpath = convert_path('photorename/version.py')
with open(vpath) as vfile:
exec(vfile.read(), main_ns)
setup(
name='photorename',
version=main_ns['__version__'],
description='bulk rename photos in ... | 23.821429 | 58 | 0.667166 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 258 | 0.386807 |
a36a758d49817dccb80abed74b7ead8eedf80c06 | 456 | py | Python | python_loop/groom_lt1.py | hesthers/self-python-practice- | 79e7a86385e599ca430af761f533f6eaf90aa448 | [
"MIT"
] | 1 | 2021-09-07T00:26:56.000Z | 2021-09-07T00:26:56.000Z | python_loop/groom_lt1.py | hesthers/self-python-practice | 79e7a86385e599ca430af761f533f6eaf90aa448 | [
"MIT"
] | null | null | null | python_loop/groom_lt1.py | hesthers/self-python-practice | 79e7a86385e599ca430af761f533f6eaf90aa448 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# UTF-8 encoding when using korean
import numpy as np
import math
input_l = []
while True:
user_input = int(input(''))
input_l.append(user_input)
if len(input_l[1:]) == input_l[0]:
#user_input = user_input.split('\n')
cnt_input = []
for i in range(1, len(input_l)):
if np.sqrt(input... | 17.538462 | 54 | 0.640351 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 95 | 0.208333 |
a36c8b3504ed6254b18b5d9848ed7acfd15782c9 | 454 | py | Python | setup.py | hasangchun/ContextNet | da2515bb506a304186c9f579b251be8f086c541a | [
"Apache-2.0"
] | 8 | 2021-06-20T17:59:22.000Z | 2021-09-15T05:28:45.000Z | setup.py | hasangchun/ContextNet | da2515bb506a304186c9f579b251be8f086c541a | [
"Apache-2.0"
] | 2 | 2021-12-02T20:33:08.000Z | 2021-12-28T14:23:17.000Z | setup.py | hasangchun/ContextNet | da2515bb506a304186c9f579b251be8f086c541a | [
"Apache-2.0"
] | 3 | 2022-02-02T10:36:01.000Z | 2022-03-03T09:04:37.000Z | from setuptools import setup, find_packages
setup(
name='ContextNet',
version='latest',
packages=find_packages(),
description='ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context',
author='Sangchun Ha',
author_email='seomk9896@naver.com',
... | 28.375 | 123 | 0.698238 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 223 | 0.491189 |
a36d0ac9736ee7f0f87c898553b9622f6343c622 | 130 | py | Python | katas/kyu_7/product_of_main_diagonal.py | the-zebulan/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 40 | 2016-03-09T12:26:20.000Z | 2022-03-23T08:44:51.000Z | katas/kyu_7/product_of_main_diagonal.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | null | null | null | katas/kyu_7/product_of_main_diagonal.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 36 | 2016-11-07T19:59:58.000Z | 2022-03-31T11:18:27.000Z | from operator import mul
def main_diagonal_product(matrix):
return reduce(mul, (matrix[a][a] for a in xrange(len(matrix))))
| 21.666667 | 67 | 0.730769 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
a36e85cc522d69fee1eb9747d2afca83c85e094a | 1,643 | py | Python | src/ctc/protocols/curve_utils/cli/curve_pools_command.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 94 | 2022-02-15T19:34:49.000Z | 2022-03-26T19:26:22.000Z | src/ctc/protocols/curve_utils/cli/curve_pools_command.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 7 | 2022-03-03T02:58:47.000Z | 2022-03-11T18:41:05.000Z | src/ctc/protocols/curve_utils/cli/curve_pools_command.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 7 | 2022-02-15T17:53:07.000Z | 2022-03-17T19:14:17.000Z | from __future__ import annotations
import toolcli
from ctc.protocols import curve_utils
def get_command_spec() -> toolcli.CommandSpec:
return {
'f': async_curve_pools_command,
'help': 'list curve pools',
'args': [
{
'name': '--verbose',
'help'... | 26.934426 | 80 | 0.593427 | 0 | 0 | 0 | 0 | 0 | 0 | 1,224 | 0.744979 | 433 | 0.263542 |
a3724c66e413effcdf21b1d39aedb643be084706 | 218 | py | Python | constants/db.py | sshikshu/app.cavill.in | 4e9472ea9640dad920f17d29b9625c8485022a5e | [
"MIT"
] | null | null | null | constants/db.py | sshikshu/app.cavill.in | 4e9472ea9640dad920f17d29b9625c8485022a5e | [
"MIT"
] | null | null | null | constants/db.py | sshikshu/app.cavill.in | 4e9472ea9640dad920f17d29b9625c8485022a5e | [
"MIT"
] | null | null | null | """
db constants
"""
DB_HOST = 'localhost'
DB_PORT = 28015
# Database is cavilling
DB_NAME = 'cavilling'
DB_TABLE_CAVILLS = 'cavills'
DB_TABLE_HAIRDOS = 'hairdos'
DB_TABLE_POLRUS = 'polrus'
DB_TABLE_USERS = 'users'
| 14.533333 | 28 | 0.733945 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 98 | 0.449541 |
a3725144f31da3c2b8b26f9fa9ea6b635892f533 | 76,062 | py | Python | socfakerservice/api/api.py | MSAdministrator/soc-faker-service | f3c401f8d6931d1c421f594dc8f1137f2ad984aa | [
"MIT"
] | 1 | 2021-04-11T05:53:38.000Z | 2021-04-11T05:53:38.000Z | socfakerservice/api/api.py | MSAdministrator/soc-faker-service | f3c401f8d6931d1c421f594dc8f1137f2ad984aa | [
"MIT"
] | null | null | null | socfakerservice/api/api.py | MSAdministrator/soc-faker-service | f3c401f8d6931d1c421f594dc8f1137f2ad984aa | [
"MIT"
] | 1 | 2021-04-11T05:53:42.000Z | 2021-04-11T05:53:42.000Z | from flask import Blueprint, render_template, request, abort, jsonify, Response
from socfakerservice import status, HTMLRenderer, set_renderers
from socfakerservice.model import TokenModel
from socfaker import SocFaker
socfaker = SocFaker()
api_bp = Blueprint(
'api',
__name__
)
def validate_request(request)... | 28.349609 | 162 | 0.639623 | 0 | 0 | 0 | 0 | 73,705 | 0.969012 | 0 | 0 | 41,690 | 0.548105 |
a37355a19aa8f440bb3300c6b512a843d8e672aa | 3,494 | py | Python | jdit/trainer/instances/fashionClassParallelTrainer.py | dingguanglei/jdit | ef878e696c9e2fad5069f106496289d4e4cc6154 | [
"Apache-2.0"
] | 28 | 2019-06-18T15:56:53.000Z | 2021-11-09T13:11:13.000Z | jdit/trainer/instances/fashionClassParallelTrainer.py | dingguanglei/jdit | ef878e696c9e2fad5069f106496289d4e4cc6154 | [
"Apache-2.0"
] | 2 | 2018-10-24T01:09:56.000Z | 2018-11-08T07:13:48.000Z | jdit/trainer/instances/fashionClassParallelTrainer.py | dingguanglei/jdit | ef878e696c9e2fad5069f106496289d4e4cc6154 | [
"Apache-2.0"
] | 8 | 2019-01-11T01:12:15.000Z | 2021-03-12T10:15:43.000Z | # coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
from jdit.trainer.single.classification import ClassificationTrainer
from jdit.model import Model
from jdit.optimizer import Optimizer
from jdit.dataset import FashionMNIST
from jdit.parallel import SupParallelTrainer
class SimpleModel(... | 32.351852 | 105 | 0.634516 | 1,523 | 0.43589 | 0 | 0 | 0 | 0 | 0 | 0 | 366 | 0.104751 |
a3741285d787f895d330b0560df8e8e215121b8a | 1,701 | py | Python | examples/plotter/lego.py | adamfazzari/pylgbst | 1ae2b761a9da3d8983a8d3cd9dd3dfd7a0b7540b | [
"MIT"
] | 468 | 2017-09-19T16:59:55.000Z | 2022-03-09T11:52:02.000Z | examples/plotter/lego.py | adamfazzari/pylgbst | 1ae2b761a9da3d8983a8d3cd9dd3dfd7a0b7540b | [
"MIT"
] | 110 | 2017-12-28T14:53:17.000Z | 2022-02-20T12:29:46.000Z | examples/plotter/lego.py | adamfazzari/pylgbst | 1ae2b761a9da3d8983a8d3cd9dd3dfd7a0b7540b | [
"MIT"
] | 120 | 2017-10-09T20:16:52.000Z | 2022-03-29T13:14:28.000Z | def lego(plotter, t):
h = t * 5.0
w = t * 3.0
plotter.move(-t * 2.0, 0)
l(h, plotter, t, w)
plotter.move(0, w + t)
e(h, plotter, t, w)
plotter.move(0, w + t)
g(plotter, t)
plotter.move(0, w + t)
o(plotter, t)
def o(plotter, t):
# O
plotter.move(t, 0)
plotter.line(3... | 20.743902 | 30 | 0.522046 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 0.007055 |
a37644a1e11006bb540b7235f3216f75efbca584 | 5,711 | py | Python | movies_modeling.py | amotter443/movies | ae375d19befb8133c014199dc1bf1ae728fd0147 | [
"MIT"
] | 1 | 2022-01-13T21:46:40.000Z | 2022-01-13T21:46:40.000Z | movies_modeling.py | amotter443/movies | ae375d19befb8133c014199dc1bf1ae728fd0147 | [
"MIT"
] | null | null | null | movies_modeling.py | amotter443/movies | ae375d19befb8133c014199dc1bf1ae728fd0147 | [
"MIT"
] | null | null | null | #Initialize packages
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import sklearn.model_selection as model_selection
from sklearn import linear_model
import sklearn.metrics as metrics
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import Ra... | 38.073333 | 366 | 0.711959 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,136 | 0.374015 |
a3767371ed8f0cd8ffdd0f52e641dd47e92c68df | 1,287 | py | Python | Python/142.py | jaimeliew1/Project_Euler_Solutions | 963c9c6d6571cade8f87341f97a6a2cd1af202bb | [
"MIT"
] | null | null | null | Python/142.py | jaimeliew1/Project_Euler_Solutions | 963c9c6d6571cade8f87341f97a6a2cd1af202bb | [
"MIT"
] | 1 | 2018-04-16T21:01:50.000Z | 2018-04-16T21:01:50.000Z | Python/142.py | jaimeliew1/Project_Euler_Solutions | 963c9c6d6571cade8f87341f97a6a2cd1af202bb | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Solution to Project Euler problem 142 - Perfect Square Collection
Author: Jaime Liew
https://github.com/jaimeliew1/Project_Euler_Solutions
"""
from itertools import combinations
import numpy as np
def run():
N = 1000000
candids = {}
# generate all pairs of squares which differ... | 28.6 | 79 | 0.529915 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 374 | 0.290598 |
a3775d28ecda7be7aab9864818d4a6bf38e3387c | 6,032 | py | Python | garcon/activity.py | mortaliorchard/garcon | 281221c63da0b2ea3ea51174a3d5878d1de8f487 | [
"MIT"
] | null | null | null | garcon/activity.py | mortaliorchard/garcon | 281221c63da0b2ea3ea51174a3d5878d1de8f487 | [
"MIT"
] | null | null | null | garcon/activity.py | mortaliorchard/garcon | 281221c63da0b2ea3ea51174a3d5878d1de8f487 | [
"MIT"
] | null | null | null | """
Activity
========
Activities are self generated classes to which you can pass an identifier,
and a list of tasks to perform. The activities are in between the decider and
the task.
For ease, two types of task runners are available: SyncTasks and AsyncTasks. If
you need something more specific, you should either c... | 28.587678 | 79 | 0.629145 | 2,623 | 0.434847 | 1,464 | 0.242706 | 0 | 0 | 0 | 0 | 3,039 | 0.503813 |
a37b1669512f165099c1e03b767ae6863a2fb2c7 | 7,754 | py | Python | csvdiff.py | bugph0bia/PyCsvDiff | 57d438d50e758e13834affd8d0e46f8a7bfe0ebe | [
"MIT"
] | null | null | null | csvdiff.py | bugph0bia/PyCsvDiff | 57d438d50e758e13834affd8d0e46f8a7bfe0ebe | [
"MIT"
] | null | null | null | csvdiff.py | bugph0bia/PyCsvDiff | 57d438d50e758e13834affd8d0e46f8a7bfe0ebe | [
"MIT"
] | null | null | null | import sys
import csv
import json
import argparse
from collections import namedtuple
# diff info
DiffInfo = namedtuple('DiffInfo', [
'mark', # diff kind (!, -, +)
'address', # row/column addresses of diff
'keyname', # row/column key names of diff
'value', # values of diff
])
def ... | 33.5671 | 131 | 0.554037 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,909 | 0.375161 |
a37e426d249e4fa306b483523b559a9a0ae9cff3 | 2,563 | py | Python | map_reduce/core/data_source.py | HuynhThanhQuan/graph-network | e429a641e7baecad9765700cac580cfbdedbe1bd | [
"MIT"
] | null | null | null | map_reduce/core/data_source.py | HuynhThanhQuan/graph-network | e429a641e7baecad9765700cac580cfbdedbe1bd | [
"MIT"
] | 11 | 2020-11-13T18:29:37.000Z | 2022-02-10T00:25:15.000Z | map_reduce/core/data_source.py | HuynhThanhQuan/graph-network | e429a641e7baecad9765700cac580cfbdedbe1bd | [
"MIT"
] | null | null | null | import os
from time import time
import pandas as pd
from sqlalchemy import create_engine
import logging
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
class AbstractDataSource:
def __int__(self):
pass
class AbstractDataSourcePointer(AbstractDataSource):
def __int__(self):
... | 35.109589 | 106 | 0.587593 | 2,377 | 0.927429 | 545 | 0.212641 | 0 | 0 | 0 | 0 | 358 | 0.13968 |
a37e9163f756c5b933aa7522cfc07f57edae5c1e | 3,431 | py | Python | setup.py | michael-borisov/django-omnibus | 3275ae41dcad5a140433f0bfcea5961dc837e913 | [
"BSD-3-Clause"
] | null | null | null | setup.py | michael-borisov/django-omnibus | 3275ae41dcad5a140433f0bfcea5961dc837e913 | [
"BSD-3-Clause"
] | 4 | 2020-08-19T08:39:55.000Z | 2021-03-31T08:23:26.000Z | setup.py | radiosilence/django-omnibus | c31337306c601e75fbdac9d6b9b62dcc980e04f5 | [
"BSD-3-Clause"
] | null | null | null | import codecs
import os
import sys
from setuptools import setup, find_packages
from setuptools.command.test import test as TestCommand
def read(*parts):
filename = os.path.join(os.path.dirname(__file__), *parts)
with codecs.open(filename, encoding='utf-8') as fp:
return fp.read()
test_requires = [
... | 27.669355 | 86 | 0.575051 | 1,331 | 0.387934 | 0 | 0 | 0 | 0 | 0 | 0 | 1,354 | 0.394637 |
a37f3e393c9a970f74e1fb50bf59be6bc0954abc | 504 | py | Python | scripts/tests/snapshots/snap_etc_test.py | Duroktar/Wolf | c192d5c27eb2098e440f7726eb1bff40ed004db5 | [
"Apache-2.0"
] | 105 | 2018-02-07T22:07:47.000Z | 2022-03-31T18:16:47.000Z | scripts/tests/snapshots/snap_etc_test.py | Duroktar/Wolf | c192d5c27eb2098e440f7726eb1bff40ed004db5 | [
"Apache-2.0"
] | 57 | 2018-02-07T23:07:41.000Z | 2021-11-21T17:14:06.000Z | scripts/tests/snapshots/snap_etc_test.py | Duroktar/Wolf | c192d5c27eb2098e440f7726eb1bff40ed004db5 | [
"Apache-2.0"
] | 10 | 2018-02-24T23:44:51.000Z | 2022-03-02T07:52:27.000Z | # -*- coding: utf-8 -*-
# snapshottest: v1 - https://goo.gl/zC4yUc
from __future__ import unicode_literals
from snapshottest import Snapshot
snapshots = Snapshot()
snapshots['test_etc 1'] = '[{"lineno": 2, "value": "tup = (1, 2, 3)"}, {"lineno": 3, "source": ["tup\\n"], "value": "(1, 2, 3)"}, {"lineno": 5, "value":... | 45.818182 | 335 | 0.56746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 386 | 0.765873 |
a37f43b419e3def4e72bb772a8952c0f709cee66 | 1,823 | py | Python | config.py | greatwallet/cosypose | e72ce7d521ef61870daef267cbbe65aaebe9d24d | [
"MIT"
] | null | null | null | config.py | greatwallet/cosypose | e72ce7d521ef61870daef267cbbe65aaebe9d24d | [
"MIT"
] | null | null | null | config.py | greatwallet/cosypose | e72ce7d521ef61870daef267cbbe65aaebe9d24d | [
"MIT"
] | null | null | null | import cosypose
import os
import yaml
from joblib import Memory
from pathlib import Path
import getpass
import socket
import torch.multiprocessing
torch.multiprocessing.set_sharing_strategy('file_system')
hostname = socket.gethostname()
username = getpass.getuser()
PROJECT_ROOT = Path(cosypose.__file__).... | 30.383333 | 88 | 0.765222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 382 | 0.209545 |
a37f76a50ac5297fbe0ae2e72f8f20c6b13bb7e0 | 2,761 | py | Python | 2018/16/main.py | zelane/advent-of-code-2016 | 72ebda3ec4eca4d1921dd8d94f2f84bbd0566fc5 | [
"MIT"
] | null | null | null | 2018/16/main.py | zelane/advent-of-code-2016 | 72ebda3ec4eca4d1921dd8d94f2f84bbd0566fc5 | [
"MIT"
] | null | null | null | 2018/16/main.py | zelane/advent-of-code-2016 | 72ebda3ec4eca4d1921dd8d94f2f84bbd0566fc5 | [
"MIT"
] | null | null | null | from copy import copy
import re
class Cpu:
def __init__(self, mem):
self.mem = mem
def addr(self, a, b, c):
self.mem[c] = self.mem[a] + self.mem[b]
def addi(self, a, b, c):
self.mem[c] = self.mem[a] + b
def mulr(self, a, b, c):
self.mem[c] = self.mem[a] * self.mem[b]... | 23.801724 | 75 | 0.522637 | 1,273 | 0.461065 | 0 | 0 | 0 | 0 | 0 | 0 | 118 | 0.042738 |
a382674b28c095d002534f7e5a89fab99c7987b3 | 2,700 | py | Python | streamlit/About.py | sarthak815/sage2therescue | b4bc38731a2b43866c545560e850cdddd85a0852 | [
"MIT"
] | null | null | null | streamlit/About.py | sarthak815/sage2therescue | b4bc38731a2b43866c545560e850cdddd85a0852 | [
"MIT"
] | null | null | null | streamlit/About.py | sarthak815/sage2therescue | b4bc38731a2b43866c545560e850cdddd85a0852 | [
"MIT"
] | 1 | 2022-03-04T09:31:18.000Z | 2022-03-04T09:31:18.000Z | import streamlit as st
def app():
st.title("About")
st.markdown('''
During the Cyclone Fani which hit Odisha in 2019 a lot of places ran out of electricity, water and other basic necessities. During this period most of the rescue workers relied on data accumulated pre disaster to guide rescue services but this was... | 117.391304 | 1,320 | 0.802963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,639 | 0.977407 |
a3842c6138c7e752e05c72628b0129a00a3d511f | 1,617 | py | Python | tests/test_reduce_sum.py | gavinuhma/tf-encrypted | 4e18d78a151bbe91489a1773fb839b889ff5b460 | [
"Apache-2.0"
] | 3 | 2018-10-18T19:36:02.000Z | 2020-07-05T19:46:23.000Z | tests/test_reduce_sum.py | dropoutlabs/tf-encrypted | 48c9dc7419163425e736ad05bb19980d134fc851 | [
"Apache-2.0"
] | null | null | null | tests/test_reduce_sum.py | dropoutlabs/tf-encrypted | 48c9dc7419163425e736ad05bb19980d134fc851 | [
"Apache-2.0"
] | null | null | null | # pylint: disable=missing-docstring
import unittest
import numpy as np
import tensorflow as tf
import tf_encrypted as tfe
class TestReduceSum(unittest.TestCase):
def setUp(self):
tf.reset_default_graph()
def test_reduce_sum_1d(self):
t = [1, 2]
with tf.Session() as sess:
out = tf.reduce_sum(t... | 24.134328 | 54 | 0.650588 | 1,444 | 0.893012 | 0 | 0 | 0 | 0 | 0 | 0 | 45 | 0.027829 |
a38463fb4d443f7e3aa2457876c06216a04ae227 | 1,010 | py | Python | tests/test_nodes.py | simonzabrocki/GraphModels | b43e44a189d663364ae08de9a1d1305320854d63 | [
"MIT"
] | null | null | null | tests/test_nodes.py | simonzabrocki/GraphModels | b43e44a189d663364ae08de9a1d1305320854d63 | [
"MIT"
] | null | null | null | tests/test_nodes.py | simonzabrocki/GraphModels | b43e44a189d663364ae08de9a1d1305320854d63 | [
"MIT"
] | null | null | null |
import pytest
from GraphModels.models.Sarah.model_agricultural_water import AgriculturalWaterNodes
from GraphModels.models.Sarah.model_freshwater_available import FreshwaterAvailableNodes
from GraphModels.models.Sarah.model_municipal_water import MunicipalWaterNodes
nodes_list = AgriculturalWaterNodes + FreshwaterAv... | 37.407407 | 116 | 0.773267 | 0 | 0 | 0 | 0 | 310 | 0.306931 | 0 | 0 | 87 | 0.086139 |
a3859a2bc6f5180117d2aa59a1b851252ca8c8a5 | 1,350 | py | Python | backend/telegram/methods/messages_and_media/get_updated_message_entity_types.py | appheap/social-media-analyzer | 0f9da098bfb0b4f9eb38e0244aa3a168cf97d51c | [
"Apache-2.0"
] | 5 | 2021-09-11T22:01:15.000Z | 2022-03-16T21:33:42.000Z | backend/telegram/methods/messages_and_media/get_updated_message_entity_types.py | iamatlasss/social-media-analyzer | 429d1d2bbd8bfce80c50c5f8edda58f87ace668d | [
"Apache-2.0"
] | null | null | null | backend/telegram/methods/messages_and_media/get_updated_message_entity_types.py | iamatlasss/social-media-analyzer | 429d1d2bbd8bfce80c50c5f8edda58f87ace668d | [
"Apache-2.0"
] | 3 | 2022-01-18T11:06:22.000Z | 2022-02-26T13:39:28.000Z | from django.db import transaction
from db.scaffold import Scaffold
from typing import List
from telegram import models as tg_models
from pyrogram import types
class GetUpdatedMessageEntityTypes(Scaffold):
def get_updated_message_entity_types(
self,
*,
db_message: 'tg_models.M... | 32.926829 | 92 | 0.565926 | 1,187 | 0.879259 | 0 | 0 | 0 | 0 | 0 | 0 | 65 | 0.048148 |
a387303aea958c01ac561cbc1d4a035d79ef4112 | 486 | py | Python | app/user_api/user_api.py | Basselbi/hikma-health-backend | 0f891821a04aa103fff62097443bd585bc342dbc | [
"MIT"
] | null | null | null | app/user_api/user_api.py | Basselbi/hikma-health-backend | 0f891821a04aa103fff62097443bd585bc342dbc | [
"MIT"
] | null | null | null | app/user_api/user_api.py | Basselbi/hikma-health-backend | 0f891821a04aa103fff62097443bd585bc342dbc | [
"MIT"
] | null | null | null | from flask import Blueprint, request, jsonify
from web_util import assert_data_has_keys
from users.user import User
user_api = Blueprint('users_api', __name__, url_prefix='/api/user')
@user_api.route('/reset_password', methods=['POST'])
def sync():
params = assert_data_has_keys(request, {'email', 'password', 'ne... | 34.714286 | 81 | 0.73251 | 0 | 0 | 0 | 0 | 298 | 0.613169 | 0 | 0 | 120 | 0.246914 |
a389bd7328bfeb9809c940787f3815d94a0c7bd6 | 2,783 | py | Python | commands.py | abcxyz618/MovieGeek | 06029ed4202c63d3da4e306eb5d500ab81f2e1cb | [
"MIT"
] | null | null | null | commands.py | abcxyz618/MovieGeek | 06029ed4202c63d3da4e306eb5d500ab81f2e1cb | [
"MIT"
] | null | null | null | commands.py | abcxyz618/MovieGeek | 06029ed4202c63d3da4e306eb5d500ab81f2e1cb | [
"MIT"
] | null | null | null | import discord
from discord.ext import commands
from omdb_api import *
from tmdb_api import *
class Commands(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command()
async def movie(self, ctx, *, in_str=""): # input format: *movie {movie name} / {year}
if in... | 36.618421 | 102 | 0.594682 | 2,626 | 0.943586 | 0 | 0 | 2,511 | 0.902264 | 2,182 | 0.784046 | 421 | 0.151276 |
a38a03f634375d52713a25701814579ff7b6e33e | 92,070 | py | Python | cryptoapis/api/unified_endpoints_api.py | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | c59ebd914850622b2c6500c4c30af31fb9cecf0e | [
"MIT"
] | 5 | 2021-05-17T04:45:03.000Z | 2022-03-23T12:51:46.000Z | cryptoapis/api/unified_endpoints_api.py | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | c59ebd914850622b2c6500c4c30af31fb9cecf0e | [
"MIT"
] | null | null | null | cryptoapis/api/unified_endpoints_api.py | Crypto-APIs/Crypto_APIs_2.0_SDK_Python | c59ebd914850622b2c6500c4c30af31fb9cecf0e | [
"MIT"
] | 2 | 2021-06-02T07:32:26.000Z | 2022-02-12T02:36:23.000Z | """
CryptoAPIs
Crypto APIs 2.0 is a complex and innovative infrastructure layer that radically simplifies the development of any Blockchain and Crypto related applications. Organized around REST, Crypto APIs 2.0 can assist both novice Bitcoin/Ethereum enthusiasts and crypto experts with the development of thei... | 42.704082 | 484 | 0.514945 | 86,921 | 0.944075 | 0 | 0 | 0 | 0 | 0 | 0 | 52,652 | 0.571869 |
a38b317b32dcbc6c9dff08940ace5dc60a5e39cd | 1,853 | py | Python | examples/run_ranch_baseline.py | pinjutien/DeepExplain | a80d85dcd5adc90968b6924a7ef39528170830f0 | [
"MIT"
] | null | null | null | examples/run_ranch_baseline.py | pinjutien/DeepExplain | a80d85dcd5adc90968b6924a7ef39528170830f0 | [
"MIT"
] | null | null | null | examples/run_ranch_baseline.py | pinjutien/DeepExplain | a80d85dcd5adc90968b6924a7ef39528170830f0 | [
"MIT"
] | null | null | null | """
RANdom CHoice baseline (RANCH): random image from the target class
"""
import random
import numpy as np
import tensorflow_datasets as tfds
from tqdm import tqdm
# output_pattern = '/home/ec2-user/gan_submission_1/mnist/mnist_v2/ranch_baselines_%d'
# tfds_name = 'mnist'
# target_size = [28, 28, 1]
# num_class = 1... | 28.953125 | 88 | 0.67674 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 629 | 0.33945 |
a38b4a3c4607025ed47cb0e6994bcee905fa97f0 | 359 | py | Python | pageOne.py | 3bru/qt-tkinter-Test | 41eefe7621c6a0bf3a25b4503df7a7451fc363b2 | [
"MIT"
] | 1 | 2020-05-18T21:59:39.000Z | 2020-05-18T21:59:39.000Z | pageOne.py | 3bru/qt-tkinter-Test | 41eefe7621c6a0bf3a25b4503df7a7451fc363b2 | [
"MIT"
] | null | null | null | pageOne.py | 3bru/qt-tkinter-Test | 41eefe7621c6a0bf3a25b4503df7a7451fc363b2 | [
"MIT"
] | null | null | null | import sqlite3, os
con = sqlite3.connect('database.sqlite')
im = con.cursor()
tablo = """CREATE TABLE IF NOT EXISTS writes(day, topic, texti)"""
deger = """INSERT INTO writes VALUES('oneDay', 'nmap', 'nmaple ilgili bisiler')"""
im.execute(tablo)
im.execute(deger)
con.commit()
im.execute("""SELECT * FROM writes""")
... | 22.4375 | 82 | 0.696379 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 175 | 0.487465 |
a38b9d380fbd10ce2b7350457ab818a75b222fac | 6,075 | py | Python | basicsr/metrics/psnr_ssim.py | BCV-Uniandes/RSR | dad60eedd3560f2655e3d1ed444153ed2616af2e | [
"zlib-acknowledgement"
] | 14 | 2021-08-28T04:15:37.000Z | 2021-12-28T17:00:33.000Z | basicsr/metrics/psnr_ssim.py | BCV-Uniandes/RSR | dad60eedd3560f2655e3d1ed444153ed2616af2e | [
"zlib-acknowledgement"
] | 2 | 2021-09-26T01:27:06.000Z | 2021-12-24T19:06:09.000Z | basicsr/metrics/psnr_ssim.py | BCV-Uniandes/RSR | dad60eedd3560f2655e3d1ed444153ed2616af2e | [
"zlib-acknowledgement"
] | 1 | 2021-10-18T15:48:56.000Z | 2021-10-18T15:48:56.000Z | import cv2
import numpy as np
from basicsr.metrics.metric_util import reorder_image, to_y_channel
def calculate_psnr(img1,
img2,
crop_border,
input_order='HWC',
test_y_channel=False):
"""Calculate PSNR (Peak Signal-to-Noise Ratio).
... | 33.379121 | 80 | 0.596708 | 931 | 0.153251 | 0 | 0 | 318 | 0.052346 | 0 | 0 | 2,398 | 0.394733 |
a38ee10bfa692aa23805d2d2b99b5f0481e7ce48 | 14,224 | py | Python | data/dataset.py | limingwu8/Pneumonia-Detection | 8541e0f34a72f6e94773bf234cfd071732229b2b | [
"MIT"
] | 7 | 2019-01-27T02:30:56.000Z | 2020-04-29T18:47:21.000Z | data/dataset.py | limingwu8/Pneumonia-Detection | 8541e0f34a72f6e94773bf234cfd071732229b2b | [
"MIT"
] | 1 | 2020-01-28T04:40:15.000Z | 2020-05-01T02:37:40.000Z | data/dataset.py | limingwu8/Pneumonia-Detection | 8541e0f34a72f6e94773bf234cfd071732229b2b | [
"MIT"
] | 3 | 2019-08-09T09:16:00.000Z | 2021-07-01T11:45:00.000Z | import os
import numpy as np
import torch
from tqdm import tqdm
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
from skimage import io, transform
from utils.Config import opt
from skimage import exposure
import matplotlib.pylab as plt
from utils import array_tool as at
from sk... | 41.228986 | 113 | 0.646161 | 4,013 | 0.282129 | 0 | 0 | 0 | 0 | 0 | 0 | 6,375 | 0.448186 |
a38f9c51d087930a15e07db3d41e43fedee278f9 | 8,344 | py | Python | make_dataset/kor_sample_dataset.py | park-sungmoo/odqa_baseline_code | 45954be766e5f987bef18e5b8a2e47f1508742cd | [
"Apache-2.0"
] | 67 | 2021-05-12T15:54:28.000Z | 2022-03-12T15:55:35.000Z | make_dataset/kor_sample_dataset.py | park-sungmoo/odqa_baseline_code | 45954be766e5f987bef18e5b8a2e47f1508742cd | [
"Apache-2.0"
] | 71 | 2021-05-01T06:07:37.000Z | 2022-01-28T16:54:46.000Z | make_dataset/kor_sample_dataset.py | park-sungmoo/odqa_baseline_code | 45954be766e5f987bef18e5b8a2e47f1508742cd | [
"Apache-2.0"
] | 14 | 2021-05-24T10:57:27.000Z | 2022-02-18T06:34:11.000Z | import json
import os.path as p
from collections import defaultdict
import pandas as pd
from datasets import load_dataset
from datasets import concatenate_datasets
from datasets import Sequence, Value, Features, Dataset, DatasetDict
from utils.tools import get_args
f = Features(
{
"answers": Sequence(
... | 28.772414 | 112 | 0.65604 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,437 | 0.273636 |
a3927c6d9fb19dc907aa3851f9fb6293c833eaf2 | 1,737 | py | Python | tests/test_simple.py | teosavv/pyembroidery | 00985f423e64ea1a454e5484012c19a64f26eb2c | [
"MIT"
] | 45 | 2018-07-08T09:49:30.000Z | 2022-03-23T07:01:15.000Z | tests/test_simple.py | teosavv/pyembroidery | 00985f423e64ea1a454e5484012c19a64f26eb2c | [
"MIT"
] | 59 | 2018-07-05T22:05:58.000Z | 2022-02-20T01:01:20.000Z | tests/test_simple.py | teosavv/pyembroidery | 00985f423e64ea1a454e5484012c19a64f26eb2c | [
"MIT"
] | 23 | 2018-08-10T17:58:04.000Z | 2022-03-29T03:41:46.000Z | import os
import shutil
import pyembroidery
import test_fractals
def test_simple():
pattern = pyembroidery.EmbPattern()
pattern.add_thread({
"rgb": 0x0000FF,
"name": "Blue Test",
"catalog": "0033",
"brand": "PyEmbroidery Brand Thread"
})
pattern.add_thread({
"... | 31.581818 | 84 | 0.651698 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 451 | 0.259643 |
a392dab4e0208bcba731af6d1b6b1dd6d3c0e78a | 21,317 | py | Python | train.py | eapache/HawkEars | 3b979166ed09de9f9254b830bb57499e1da7a015 | [
"MIT"
] | null | null | null | train.py | eapache/HawkEars | 3b979166ed09de9f9254b830bb57499e1da7a015 | [
"MIT"
] | 1 | 2021-12-17T16:56:12.000Z | 2021-12-19T15:53:55.000Z | train.py | eapache/HawkEars | 3b979166ed09de9f9254b830bb57499e1da7a015 | [
"MIT"
] | 1 | 2021-12-17T16:59:04.000Z | 2021-12-17T16:59:04.000Z | # Train the selected neural network model on spectrograms for birds and a few other classes.
# Train the selected neural network model on spectrograms for birds and a few other classes.
# To see command-line arguments, run the script with -h argument.
import argparse
import math
import matplotlib.pyplot as plt
import ... | 47.476615 | 233 | 0.598208 | 16,394 | 0.769058 | 0 | 0 | 0 | 0 | 0 | 0 | 5,718 | 0.268237 |
a3943fc348baced6fa934c762ac87be734e9ae13 | 2,002 | py | Python | limix/heritability/estimate.py | fpcasale/limix | a6bc2850f243fe779991bb53a24ddbebe0ab74d2 | [
"Apache-2.0"
] | null | null | null | limix/heritability/estimate.py | fpcasale/limix | a6bc2850f243fe779991bb53a24ddbebe0ab74d2 | [
"Apache-2.0"
] | null | null | null | limix/heritability/estimate.py | fpcasale/limix | a6bc2850f243fe779991bb53a24ddbebe0ab74d2 | [
"Apache-2.0"
] | null | null | null | from __future__ import division
from numpy import ascontiguousarray, copy, ones, var
from numpy_sugar.linalg import economic_qs
from glimix_core.glmm import GLMMExpFam
def estimate(pheno, lik, K, covs=None, verbose=True):
r"""Estimate the so-called narrow-sense heritability.
It supports Normal, Bernoulli, ... | 24.414634 | 76 | 0.580919 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,154 | 0.576424 |
a394632989f95d229e000f46db6a73bbdcda0cf3 | 2,739 | py | Python | pyrat/__main__.py | gitmarek/pyrat | cbf918d5c23d5d39e62e00bb64b6d0596170c68b | [
"MIT"
] | null | null | null | pyrat/__main__.py | gitmarek/pyrat | cbf918d5c23d5d39e62e00bb64b6d0596170c68b | [
"MIT"
] | null | null | null | pyrat/__main__.py | gitmarek/pyrat | cbf918d5c23d5d39e62e00bb64b6d0596170c68b | [
"MIT"
] | null | null | null | import argparse, importlib, sys
import pyrat
from pyrat import name, version, logger
# This returns a function to be called by a subparser below
# We assume in the tool's submodule there's a function called 'start(args)'
# That takes over the execution of the program.
def tool_(tool_name):
def f(args):
s... | 36.039474 | 78 | 0.683826 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,210 | 0.441767 |
a394774a260348220f0663c39347cf191a6da686 | 485 | py | Python | zof/event.py | byllyfish/pylibofp | 8e96caf83f57cab930b45a78eb4a8eaa6d9d0408 | [
"MIT"
] | 4 | 2017-09-20T19:10:51.000Z | 2022-01-10T04:02:00.000Z | zof/event.py | byllyfish/pylibofp | 8e96caf83f57cab930b45a78eb4a8eaa6d9d0408 | [
"MIT"
] | 2 | 2017-09-02T22:53:03.000Z | 2018-01-01T03:27:48.000Z | zof/event.py | byllyfish/pylibofp | 8e96caf83f57cab930b45a78eb4a8eaa6d9d0408 | [
"MIT"
] | null | null | null | from .objectview import to_json, from_json
def load_event(event):
try:
return from_json(event)
except ValueError as ex:
# Report malformed JSON input.
if event == b'':
return {'event': 'EXCEPTION', 'reason': 'EOF', 'input': event}
return {'event': 'EXCEPTION', 'reas... | 26.944444 | 74 | 0.610309 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 118 | 0.243299 |
a3955ee346d7a3a5338cd528fa6afbec24d5527c | 2,007 | py | Python | python/projecteuler/src/longest_collatz_sequence.py | christopher-burke/warmups | 140c96ada87ec5e9faa4622504ddee18840dce4a | [
"MIT"
] | null | null | null | python/projecteuler/src/longest_collatz_sequence.py | christopher-burke/warmups | 140c96ada87ec5e9faa4622504ddee18840dce4a | [
"MIT"
] | 2 | 2022-03-10T03:49:14.000Z | 2022-03-14T00:49:54.000Z | python/projecteuler/src/longest_collatz_sequence.py | christopher-burke/warmups | 140c96ada87ec5e9faa4622504ddee18840dce4a | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
"""Longest Collatz sequence.
The following iterative sequence is defined
for the set of positive integers:
n → n/2 (n is even)
n → 3n + 1 (n is odd)
Using the rule above and starting with 13,
we generate the following sequence:
13 → 40 → 20 → 10 → 5 → 16 → 8 → 4 → 2 → 1
It can be seen that... | 23.611765 | 71 | 0.659691 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,156 | 0.569178 |
a396aa841a074ff27cad63b9fc597eb1d7fa8b7c | 1,823 | py | Python | examples/classify_pose.py | scottamain/aiy-maker-kit | 4cdb973067b83d27cf0601c811d887877d1bc253 | [
"Apache-2.0"
] | null | null | null | examples/classify_pose.py | scottamain/aiy-maker-kit | 4cdb973067b83d27cf0601c811d887877d1bc253 | [
"Apache-2.0"
] | null | null | null | examples/classify_pose.py | scottamain/aiy-maker-kit | 4cdb973067b83d27cf0601c811d887877d1bc253 | [
"Apache-2.0"
] | null | null | null | # Copyright 2021 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | 35.745098 | 80 | 0.785518 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,267 | 0.695008 |
a396f80d3df39bc129b954b6343810b69c00e0ea | 291 | py | Python | weldx/tags/measurement/source.py | CagtayFabry/weldx | 463f949d4fa54b5edafa2268cb862716865a62c2 | [
"BSD-3-Clause"
] | 13 | 2020-02-20T07:45:02.000Z | 2021-12-10T13:15:47.000Z | weldx/tags/measurement/source.py | BAMWelDX/weldx | ada4e67fa00cdb80a0b954057f4e685b846c9fe5 | [
"BSD-3-Clause"
] | 675 | 2020-02-20T07:47:00.000Z | 2022-03-31T15:17:19.000Z | weldx/tags/measurement/source.py | CagtayFabry/weldx | 463f949d4fa54b5edafa2268cb862716865a62c2 | [
"BSD-3-Clause"
] | 5 | 2020-09-02T07:19:17.000Z | 2021-12-05T08:57:50.000Z | from weldx.asdf.util import dataclass_serialization_class
from weldx.measurement import SignalSource
__all__ = ["SignalSource", "SignalSourceConverter"]
SignalSourceConverter = dataclass_serialization_class(
class_type=SignalSource, class_name="measurement/source", version="0.1.0"
)
| 29.1 | 77 | 0.821306 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 64 | 0.219931 |
a39715724a34e51cf7b15a4f030411898b87a5ec | 1,706 | py | Python | test/test_entities_api.py | iknaio/graphsense-python | b61c66b6ec0bb9720036ae61777e90ce63a971cc | [
"MIT"
] | null | null | null | test/test_entities_api.py | iknaio/graphsense-python | b61c66b6ec0bb9720036ae61777e90ce63a971cc | [
"MIT"
] | 1 | 2022-02-24T11:21:49.000Z | 2022-02-24T11:21:49.000Z | test/test_entities_api.py | iknaio/graphsense-python | b61c66b6ec0bb9720036ae61777e90ce63a971cc | [
"MIT"
] | null | null | null | """
GraphSense API
GraphSense API # noqa: E501
The version of the OpenAPI document: 0.5.1
Generated by: https://openapi-generator.tech
"""
import unittest
import graphsense
from graphsense.api.entities_api import EntitiesApi # noqa: E501
class TestEntitiesApi(unittest.TestCase):
"""Entities... | 21.871795 | 73 | 0.623681 | 1,393 | 0.81653 | 0 | 0 | 0 | 0 | 0 | 0 | 997 | 0.584408 |
a39afee8e197b6834391bc0d4c2a7ba0f29e4cdf | 622 | py | Python | tests/test_versions_in_sync.py | simon-graham/pure_interface | da7bf05151c1c906c753987fbf7e3251905b4ba0 | [
"MIT"
] | 10 | 2018-08-27T04:15:53.000Z | 2021-08-18T09:45:35.000Z | tests/test_versions_in_sync.py | simon-graham/pure_interface | da7bf05151c1c906c753987fbf7e3251905b4ba0 | [
"MIT"
] | 35 | 2018-08-27T04:17:44.000Z | 2021-09-22T05:39:57.000Z | tests/test_versions_in_sync.py | tim-mitchell/pure_interface | 46a2de2574f4543980303cafd89cfcbdb643fbbb | [
"MIT"
] | 3 | 2018-09-19T21:32:01.000Z | 2020-11-17T00:58:55.000Z | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function, unicode_literals
import os
import unittest
import pure_interface
class TestVersionsMatch(unittest.TestCase):
def test_versions(self):
setup_py = os.path.join(os.path.dirname(__file__), '..', 'setup.cfg')
wit... | 29.619048 | 82 | 0.636656 | 463 | 0.744373 | 0 | 0 | 0 | 0 | 0 | 0 | 86 | 0.138264 |
a39ce7f687dbc4302e562228dd957da1ccaaa084 | 315 | py | Python | catalog/bindings/wfs/get_capabilities_2.py | NIVANorge/s-enda-playground | 56ae0a8978f0ba8a5546330786c882c31e17757a | [
"Apache-2.0"
] | null | null | null | catalog/bindings/wfs/get_capabilities_2.py | NIVANorge/s-enda-playground | 56ae0a8978f0ba8a5546330786c882c31e17757a | [
"Apache-2.0"
] | null | null | null | catalog/bindings/wfs/get_capabilities_2.py | NIVANorge/s-enda-playground | 56ae0a8978f0ba8a5546330786c882c31e17757a | [
"Apache-2.0"
] | null | null | null | from dataclasses import dataclass
from bindings.wfs.get_capabilities_type_2 import GetCapabilitiesType2
__NAMESPACE__ = "http://www.opengis.net/wfs/2.0"
@dataclass
class GetCapabilities2(GetCapabilitiesType2):
class Meta:
name = "GetCapabilities"
namespace = "http://www.opengis.net/wfs/2.0"
| 26.25 | 69 | 0.755556 | 147 | 0.466667 | 0 | 0 | 158 | 0.501587 | 0 | 0 | 81 | 0.257143 |
a39d78970a2b5428929cac47bbcd677dcd4fd411 | 2,169 | py | Python | timeStamps/admin.py | zandegran/django-timeStamp | 2c598d5543dc9b9198f41f0712406f22e60d5fa6 | [
"MIT"
] | 1 | 2017-12-15T17:36:58.000Z | 2017-12-15T17:36:58.000Z | timeStamps/admin.py | zandegran/django-timeStamp | 2c598d5543dc9b9198f41f0712406f22e60d5fa6 | [
"MIT"
] | null | null | null | timeStamps/admin.py | zandegran/django-timeStamp | 2c598d5543dc9b9198f41f0712406f22e60d5fa6 | [
"MIT"
] | null | null | null | """
This module is to define how TimeStamp model is represented in the Admin site
It also registers the model to be shown in the admin site
.. seealso:: :class:`..models.TimeStamp`
"""
from django.contrib import admin
from .models import TimeStamp
class FilterUserAdmin(admin.ModelAdmin):
"""
Makes the ... | 32.863636 | 125 | 0.654219 | 1,784 | 0.822499 | 0 | 0 | 0 | 0 | 0 | 0 | 1,020 | 0.470263 |
a39e36cdbd6fb2489b1dabdf74c900884f32c597 | 718 | py | Python | setup.py | Gearheart-team/django-accounts | e0c2f12d350846fa31143b6dbdb0cf6fa713fb11 | [
"MIT"
] | null | null | null | setup.py | Gearheart-team/django-accounts | e0c2f12d350846fa31143b6dbdb0cf6fa713fb11 | [
"MIT"
] | null | null | null | setup.py | Gearheart-team/django-accounts | e0c2f12d350846fa31143b6dbdb0cf6fa713fb11 | [
"MIT"
] | null | null | null | from setuptools import setup, find_packages
setup(
name='izeni-django-accounts',
version='1.1.2a',
namespace_packages=['izeni', 'izeni.django'],
packages=find_packages(),
include_package_data=True,
author='Izeni, Inc.',
author_email='django-accounts@izeni.com',
description=open('README.... | 29.916667 | 107 | 0.637883 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 358 | 0.498607 |
a39ece0f6a490b1cd3625b5fef325786496075c3 | 2,973 | py | Python | train.py | Saaaber/urban-segmentation | fc893feb9208d3206d7c5329b1ccf4cfab97ed31 | [
"MIT"
] | 3 | 2020-11-16T20:21:25.000Z | 2021-06-11T13:09:30.000Z | train.py | Saaaber/urban-segmentation | fc893feb9208d3206d7c5329b1ccf4cfab97ed31 | [
"MIT"
] | null | null | null | train.py | Saaaber/urban-segmentation | fc893feb9208d3206d7c5329b1ccf4cfab97ed31 | [
"MIT"
] | 3 | 2020-11-11T23:43:15.000Z | 2022-03-17T09:03:42.000Z | # Copyright (c) Ville de Montreal. All rights reserved.
# Licensed under the MIT license.
# See LICENSE file in the project root for full license information.
import os
import json
import torch
import argparse
import datetime
from utils.factories import ModelFactory, OptimizerFactory, TrainerFactory
if __name__ == "... | 33.784091 | 83 | 0.636731 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 999 | 0.336024 |
a3a01913f52507b8c2e9c60bffcef520ae43b4db | 1,036 | py | Python | pypeit/core/wavecal/spectrographs/templ_soar_goodman.py | rcooke-ast/PYPIT | 0cb9c4cb422736b855065a35aefc2bdba6d51dd0 | [
"BSD-3-Clause"
] | null | null | null | pypeit/core/wavecal/spectrographs/templ_soar_goodman.py | rcooke-ast/PYPIT | 0cb9c4cb422736b855065a35aefc2bdba6d51dd0 | [
"BSD-3-Clause"
] | null | null | null | pypeit/core/wavecal/spectrographs/templ_soar_goodman.py | rcooke-ast/PYPIT | 0cb9c4cb422736b855065a35aefc2bdba6d51dd0 | [
"BSD-3-Clause"
] | null | null | null | """ Generate the wavelength templates for SOAR Goodman"""
import os
from pypeit.core.wavecal import templates
from IPython import embed
def soar_goodman_400(overwrite=False):
binspec = 2
outroot = 'soar_goodman_400_SYZY.fits'
# PypeIt fits
wpath = os.path.join(templates.template_path, 'SOAR_Goodman',... | 31.393939 | 85 | 0.638031 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 217 | 0.209459 |
a3a1c89d1bcdd899b6c1712a17770e89aa6ef0b0 | 5,062 | py | Python | vivarium/lidar.py | Pyrofoux/vivarium | 90c07384929f6c34915f053fd8e95e91358c4e58 | [
"MIT"
] | 2 | 2020-10-30T15:28:06.000Z | 2022-01-31T17:13:25.000Z | vivarium/lidar.py | Pyrofoux/vivarium | 90c07384929f6c34915f053fd8e95e91358c4e58 | [
"MIT"
] | null | null | null | vivarium/lidar.py | Pyrofoux/vivarium | 90c07384929f6c34915f053fd8e95e91358c4e58 | [
"MIT"
] | null | null | null | from simple_playgrounds.entities.agents.sensors.sensor import *
from simple_playgrounds.entities.agents.sensors.semantic_sensors import *
from collections import defaultdict
from pymunk.vec2d import Vec2d
import math
#@SensorGenerator.register('lidar')
class LidarSensor(SemanticSensor):
def __init__(self, anchor... | 34.435374 | 111 | 0.600356 | 4,806 | 0.949427 | 0 | 0 | 0 | 0 | 0 | 0 | 1,483 | 0.292967 |
a3a2b31e0b527f3675dc65a92359c7b90836c880 | 511 | py | Python | apilos_settings/models.py | MTES-MCT/apilos | 6404b94b0f668e39c1dc12a6421aebd26ef1c98b | [
"MIT"
] | null | null | null | apilos_settings/models.py | MTES-MCT/apilos | 6404b94b0f668e39c1dc12a6421aebd26ef1c98b | [
"MIT"
] | 2 | 2021-12-15T05:10:43.000Z | 2021-12-15T05:11:00.000Z | apilos_settings/models.py | MTES-MCT/apilos | 6404b94b0f668e39c1dc12a6421aebd26ef1c98b | [
"MIT"
] | 1 | 2021-12-28T13:06:06.000Z | 2021-12-28T13:06:06.000Z | from django.db import models
class Departement(models.Model):
id = models.AutoField(primary_key=True)
nom = models.CharField(max_length=255, unique=True)
code_insee = models.CharField(max_length=3, unique=True)
code_postal = models.CharField(max_length=3)
def natural_key(self):
return (s... | 26.894737 | 60 | 0.700587 | 479 | 0.937378 | 0 | 0 | 0 | 0 | 0 | 0 | 33 | 0.064579 |
a3a3cd19889c828efa32a912a6cda2aa73fb4ca6 | 4,310 | py | Python | bin/allplots.py | Gabaldonlab/karyon | ba81828921b83b553f126892795253be1fd941ba | [
"MIT"
] | null | null | null | bin/allplots.py | Gabaldonlab/karyon | ba81828921b83b553f126892795253be1fd941ba | [
"MIT"
] | 2 | 2021-07-07T08:40:56.000Z | 2022-01-06T16:10:27.000Z | bin/allplots.py | Gabaldonlab/karyon | ba81828921b83b553f126892795253be1fd941ba | [
"MIT"
] | null | null | null | #!/bin/python
import sys, os, re, subprocess, math
import argparse
import psutil
from pysam import pysam
from Bio import SeqIO
import numpy as np
import numpy.random
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
#import seaborn as sns
import pandas as pd
import scipy.stats
from scipy.stats imp... | 35.916667 | 236 | 0.710905 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,143 | 0.265197 |
a3a50e8b6b7936872866a8a4572b115958922c08 | 713 | py | Python | console/middleware.py | laincloud/Console | 9d4fb68ad5378279697803ca45a4eda58d72d9a3 | [
"MIT"
] | 11 | 2016-05-04T11:55:01.000Z | 2018-09-29T01:00:05.000Z | console/middleware.py | laincloud/Console | 9d4fb68ad5378279697803ca45a4eda58d72d9a3 | [
"MIT"
] | 21 | 2016-05-25T06:54:44.000Z | 2019-06-06T00:38:38.000Z | console/middleware.py | laincloud/Console | 9d4fb68ad5378279697803ca45a4eda58d72d9a3 | [
"MIT"
] | 16 | 2016-05-13T08:20:43.000Z | 2021-12-31T09:23:14.000Z | # -*- coding: utf-8
from django.http import JsonResponse, HttpResponse
# from commons.settings import ARCHON_HOST
class CORSMiddleware:
def process_request(self, request):
if request.method == 'OPTIONS':
r = HttpResponse('', content_type='text/plain', status=200)
r['Access-Contro... | 32.409091 | 100 | 0.605891 | 594 | 0.8331 | 0 | 0 | 0 | 0 | 0 | 0 | 267 | 0.374474 |
a3a546b361a588aac685878f310be185f371649f | 538 | py | Python | pypxl/errors.py | Kile/pypxl | 0aabe5492386bffc1e246100cb55448bbac521ec | [
"MIT"
] | 1 | 2021-04-02T09:05:33.000Z | 2021-04-02T09:05:33.000Z | pypxl/errors.py | Kile/pypxl | 0aabe5492386bffc1e246100cb55448bbac521ec | [
"MIT"
] | null | null | null | pypxl/errors.py | Kile/pypxl | 0aabe5492386bffc1e246100cb55448bbac521ec | [
"MIT"
] | null | null | null | class PxlapiException(Exception):
"""
The base exception for anything related to pypxl
"""
pass
class InvalidFlag(PxlapiException):
pass
class InvalidFilter(PxlapiException):
pass
class InvalidEyes(PxlapiException):
pass
class TooManyCharacters(PxlapiException):
pass
class InvalidSa... | 18.551724 | 75 | 0.728625 | 524 | 0.973978 | 0 | 0 | 0 | 0 | 0 | 0 | 151 | 0.280669 |
a3a5bb350e05522589702afb78e2a9430fe6a8c4 | 1,061 | py | Python | test.py | vinsmokemau/NQueens | 7c9291f655b8e4f0ce4c6c5d07a80440f8f2c0a8 | [
"MIT"
] | null | null | null | test.py | vinsmokemau/NQueens | 7c9291f655b8e4f0ce4c6c5d07a80440f8f2c0a8 | [
"MIT"
] | null | null | null | test.py | vinsmokemau/NQueens | 7c9291f655b8e4f0ce4c6c5d07a80440f8f2c0a8 | [
"MIT"
] | null | null | null | import unittest
from algorithm import NQueens
class TestNQueens(unittest.TestCase):
def test_1_queen(self):
self.assertEqual(NQueens(1).solutions, 1)
def test_2_queen(self):
self.assertEqual(NQueens(2).solutions, 0)
def test_3_queen(self):
self.assertEqual(NQueens(3).solutions, ... | 25.878049 | 65 | 0.673893 | 1,011 | 0.952875 | 0 | 0 | 0 | 0 | 0 | 0 | 24 | 0.02262 |
6e55e971b17323a0b8342354a7a6ad601469f01e | 18,524 | py | Python | syntropynac/resolve.py | SyntropyNet/syntropy-nac | 8beddcd606d46fd909f51d0c53044be496cec995 | [
"MIT"
] | 3 | 2021-01-06T08:24:47.000Z | 2021-02-27T08:08:07.000Z | syntropynac/resolve.py | SyntropyNet/syntropy-nac | 8beddcd606d46fd909f51d0c53044be496cec995 | [
"MIT"
] | null | null | null | syntropynac/resolve.py | SyntropyNet/syntropy-nac | 8beddcd606d46fd909f51d0c53044be496cec995 | [
"MIT"
] | null | null | null | import functools
from dataclasses import dataclass
from itertools import combinations
import click
import syntropy_sdk as sdk
from syntropy_sdk import utils
from syntropynac.exceptions import ConfigureNetworkError
from syntropynac.fields import ALLOWED_PEER_TYPES, ConfigFields, PeerState, PeerType
@dataclass
class ... | 36.608696 | 125 | 0.589721 | 1,401 | 0.075632 | 0 | 0 | 1,965 | 0.106079 | 0 | 0 | 5,662 | 0.305658 |
6e56c45295d74ab6452768ca7c9600d73e511225 | 10,298 | py | Python | idact/detail/nodes/node_impl.py | garstka/idact | b9c8405c94db362c4a51d6bfdf418b14f06f0da1 | [
"MIT"
] | 5 | 2018-12-06T15:40:34.000Z | 2019-06-19T11:22:58.000Z | idact/detail/nodes/node_impl.py | garstka/idact | b9c8405c94db362c4a51d6bfdf418b14f06f0da1 | [
"MIT"
] | 9 | 2018-12-06T16:35:26.000Z | 2019-04-28T19:01:40.000Z | idact/detail/nodes/node_impl.py | garstka/idact | b9c8405c94db362c4a51d6bfdf418b14f06f0da1 | [
"MIT"
] | 2 | 2019-04-28T19:18:58.000Z | 2019-06-17T06:56:28.000Z | """This module contains the implementation of the cluster node interface."""
import datetime
from typing import Optional, Any, Callable
import bitmath
import fabric.operations
import fabric.tasks
import fabric.decorators
from fabric.exceptions import CommandTimeout
from fabric.state import env
from idact.core.retry ... | 37.721612 | 79 | 0.583026 | 8,652 | 0.840163 | 0 | 0 | 1,732 | 0.168188 | 0 | 0 | 1,457 | 0.141484 |
6e5770f83af2ce49e0548c12ebb2126470694c34 | 2,012 | py | Python | geoportal/LUX_alembic/versions/17fb1559a5cd_create_table_for_hierarchy_of_accounts.py | arnaud-morvan/geoportailv3 | b9d676cf78e45e12894f7d1ceea99b915562d64f | [
"MIT"
] | 17 | 2015-01-14T08:40:22.000Z | 2021-05-08T04:39:50.000Z | geoportal/LUX_alembic/versions/17fb1559a5cd_create_table_for_hierarchy_of_accounts.py | arnaud-morvan/geoportailv3 | b9d676cf78e45e12894f7d1ceea99b915562d64f | [
"MIT"
] | 1,477 | 2015-01-05T09:58:41.000Z | 2022-03-18T11:07:09.000Z | geoportal/LUX_alembic/versions/17fb1559a5cd_create_table_for_hierarchy_of_accounts.py | arnaud-morvan/geoportailv3 | b9d676cf78e45e12894f7d1ceea99b915562d64f | [
"MIT"
] | 14 | 2015-07-24T07:33:13.000Z | 2021-03-02T13:51:48.000Z | """create table for hierarchy of accounts
Revision ID: 17fb1559a5cd
Revises: 3b7de32aebed
Create Date: 2015-09-16 14:20:30.972593
"""
# revision identifiers, used by Alembic.
revision = '17fb1559a5cd'
down_revision = '3b7de32aebed'
branch_labels = None
depends_on = None
from alembic import op, context
import sqlalc... | 27.944444 | 73 | 0.611332 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,033 | 0.513419 |
6e596f23ab56bd2dd8dd6ce01540892f3e46cdad | 1,076 | py | Python | tests/test_migrate.py | tvcsantos/Flexget | e08ce2957dd4f0668911d1e56347369939e4d0a5 | [
"MIT"
] | 1 | 2017-08-25T07:17:04.000Z | 2017-08-25T07:17:04.000Z | tests/test_migrate.py | tvcsantos/Flexget | e08ce2957dd4f0668911d1e56347369939e4d0a5 | [
"MIT"
] | 1 | 2018-06-09T18:03:35.000Z | 2018-06-09T18:03:35.000Z | tests/test_migrate.py | tvcsantos/Flexget | e08ce2957dd4f0668911d1e56347369939e4d0a5 | [
"MIT"
] | null | null | null | from __future__ import unicode_literals, division, absolute_import
import os
from tests import FlexGetBase
class TestMigrate(FlexGetBase):
__yaml__ = """
tasks:
test:
mock:
- {title: 'foobar'}
accept_all: yes
"""
def setup(self):
import log... | 31.647059 | 132 | 0.636617 | 966 | 0.89777 | 0 | 0 | 0 | 0 | 0 | 0 | 529 | 0.491636 |
6e5a5481a3630f1bb09ba60f327038cb691a80cf | 2,422 | py | Python | src/challenges/CtCI/dynamic/P1_triple_step.py | Ursidours/pythonic_interviews | a88e10b82ed2a163dfcc0bfd1d01a9e9e606c045 | [
"MIT"
] | 2 | 2021-11-13T01:30:25.000Z | 2022-02-11T18:17:22.000Z | src/challenges/CtCI/dynamic/P1_triple_step.py | arnaudblois/pythonic_interviews | a88e10b82ed2a163dfcc0bfd1d01a9e9e606c045 | [
"MIT"
] | null | null | null | src/challenges/CtCI/dynamic/P1_triple_step.py | arnaudblois/pythonic_interviews | a88e10b82ed2a163dfcc0bfd1d01a9e9e606c045 | [
"MIT"
] | null | null | null | """
Problem 1 of Chapter 8 in CtCi
Triple Step: A child is running up a staircase with N steps and can hop either
1 step, 2 steps, or 3 steps at a time. Return the number of possible ways exist
this can be done.
General idea of the solution: At any step N, the child must necessarily come
from the steps N-3, N-2 or N-1... | 31.454545 | 79 | 0.641618 | 0 | 0 | 0 | 0 | 530 | 0.218827 | 0 | 0 | 1,193 | 0.492568 |
6e5a95d6b33481e439c3c6dd74b69db486074c51 | 117 | py | Python | lib/JumpScale/lib/docker/__init__.py | Jumpscale/jumpscale6_core | 0502ddc1abab3c37ed982c142d21ea3955d471d3 | [
"BSD-2-Clause"
] | 1 | 2015-10-26T10:38:13.000Z | 2015-10-26T10:38:13.000Z | lib/JumpScale/lib/docker/__init__.py | Jumpscale/jumpscale6_core | 0502ddc1abab3c37ed982c142d21ea3955d471d3 | [
"BSD-2-Clause"
] | null | null | null | lib/JumpScale/lib/docker/__init__.py | Jumpscale/jumpscale6_core | 0502ddc1abab3c37ed982c142d21ea3955d471d3 | [
"BSD-2-Clause"
] | null | null | null | from JumpScale import j
j.base.loader.makeAvailable(j, 'tools')
from Docker import Docker
j.tools.docker = Docker()
| 19.5 | 39 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0.059829 |
6e5ab1e623f341546ab1d75882702a30b02894e2 | 3,704 | py | Python | scenes/capture/motor_pi/stepper/motorclient.py | tum-pbs/reconstructScalarFlows | 948efeaa99b90c3879f9fb544da9a596b0cb5852 | [
"Apache-2.0"
] | null | null | null | scenes/capture/motor_pi/stepper/motorclient.py | tum-pbs/reconstructScalarFlows | 948efeaa99b90c3879f9fb544da9a596b0cb5852 | [
"Apache-2.0"
] | 1 | 2020-02-20T12:37:38.000Z | 2020-02-20T17:04:53.000Z | scenes/capture/motor_pi/stepper/motorclient.py | tum-pbs/reconstructScalarFlows | 948efeaa99b90c3879f9fb544da9a596b0cb5852 | [
"Apache-2.0"
] | 3 | 2020-01-23T04:32:46.000Z | 2020-02-20T05:48:36.000Z | #!/usr/bin/env python2
import sys
import socket
import datetime
import math
import time
from time import sleep
# The c binary for controlling the stepper motor is loaded via ctypes
from ctypes import *
stepper_lib = cdll.LoadLibrary('./stepper.so')
# buffer containing the incomplete commands
recvBuffer = str()
# ... | 23.896774 | 78 | 0.560475 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,435 | 0.387419 |
6e5d48ba91cb1100ebbf354d7f7d6405aa099be0 | 20,335 | py | Python | bots/invaders/agent.py | alv67/Lux-AI-challenge | 4fdd623a8ff578f769a6925ec0200170f84d4737 | [
"MIT"
] | null | null | null | bots/invaders/agent.py | alv67/Lux-AI-challenge | 4fdd623a8ff578f769a6925ec0200170f84d4737 | [
"MIT"
] | 27 | 2021-10-17T22:46:41.000Z | 2021-12-05T23:41:19.000Z | bots/invaders/agent.py | alv67/Lux-AI-challenge | 4fdd623a8ff578f769a6925ec0200170f84d4737 | [
"MIT"
] | 3 | 2021-11-14T19:22:16.000Z | 2021-12-04T06:46:33.000Z | import os
import math
import sys
from typing import List, Tuple
# for kaggle-environments
from abn.game_ext import GameExtended
from abn.jobs import Task, Job, JobBoard
from abn.actions import Actions
from lux.game_map import Position, Cell, RESOURCE_TYPES
from lux.game_objects import City
from lux.game_constants impo... | 47.847059 | 126 | 0.503369 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4,336 | 0.213218 |
6e5de644fd911fb842013165cff69e62361a9159 | 12,503 | py | Python | PySRCG/src/Tabs/cyberware_tab.py | apampuch/PySRCG | bb3777aed3517b473e5860336c015e2e8d0905e9 | [
"MIT"
] | null | null | null | PySRCG/src/Tabs/cyberware_tab.py | apampuch/PySRCG | bb3777aed3517b473e5860336c015e2e8d0905e9 | [
"MIT"
] | null | null | null | PySRCG/src/Tabs/cyberware_tab.py | apampuch/PySRCG | bb3777aed3517b473e5860336c015e2e8d0905e9 | [
"MIT"
] | null | null | null | from copy import copy
from tkinter import *
from tkinter import ttk
from src import app_data
from src.CharData.augment import Cyberware
from src.Tabs.notebook_tab import NotebookTab
from src.statblock_modifier import StatMod
from src.utils import treeview_get, recursive_treeview_fill, calculate_attributes, get_variabl... | 38.589506 | 116 | 0.589698 | 11,965 | 0.95697 | 0 | 0 | 362 | 0.028953 | 0 | 0 | 2,406 | 0.192434 |
6e5f43493f76b33f089dfbae79e524b7b68ad4b5 | 337 | py | Python | myapp/mymetric/my-metric.py | affoliveira/hiring-engineers | 4064d8c7b6cead9a88197e95fcd6a0f2395e4d44 | [
"Apache-2.0"
] | null | null | null | myapp/mymetric/my-metric.py | affoliveira/hiring-engineers | 4064d8c7b6cead9a88197e95fcd6a0f2395e4d44 | [
"Apache-2.0"
] | null | null | null | myapp/mymetric/my-metric.py | affoliveira/hiring-engineers | 4064d8c7b6cead9a88197e95fcd6a0f2395e4d44 | [
"Apache-2.0"
] | null | null | null | from datadog import initialize, statsd
import time
import random
import os
options = {
'statsd_host':os.environ['DD_AGENT_HOST'],
'statsd_port':8125
}
initialize(**options)
i = 0
while(1):
i += 1
r = random.randint(0, 1000)
statsd.gauge('mymetric',r , tags=["environment:dev"])
time.sleep(int(os.envi... | 17.736842 | 55 | 0.68546 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 78 | 0.231454 |
6e5f8bfb8859c97984af510e67f81278396d3ad6 | 277 | py | Python | 1 ano/logica-de-programacao/list-telefone-lucio.py | ThiagoPereira232/tecnico-informatica | 6b55ecf34501b38052943acf1b37074e3472ce6e | [
"MIT"
] | 1 | 2021-09-24T16:26:04.000Z | 2021-09-24T16:26:04.000Z | 1 ano/logica-de-programacao/list-telefone-lucio.py | ThiagoPereira232/tecnico-informatica | 6b55ecf34501b38052943acf1b37074e3472ce6e | [
"MIT"
] | null | null | null | 1 ano/logica-de-programacao/list-telefone-lucio.py | ThiagoPereira232/tecnico-informatica | 6b55ecf34501b38052943acf1b37074e3472ce6e | [
"MIT"
] | null | null | null | n = [0,0,0,0,0,0,0,0,0,0]
t = [0,0,0,0,0,0,0,0,0,0]
c=0
while(c<10):
n[c]=input("Digite o nome")
t[c]=input("Digite o telefone")
c+=1
const=""
while(const!="fim"):
cons=input("Digite nome a consultar")
if(n[c]==const):
print(f"TEl: {t[c]}")
c+=1 | 21.307692 | 41 | 0.516245 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 0.288809 |
6e61986199cea39f158bd8be59e6773d5f58be23 | 8,979 | py | Python | serve_tiny_performance_mdrnn.py | cpmpercussion/robojam | 8f9524be0ad850bdfc0c3459b0e4b677f5f70a84 | [
"MIT"
] | 10 | 2017-11-18T04:01:03.000Z | 2022-03-06T21:07:09.000Z | serve_tiny_performance_mdrnn.py | cpmpercussion/robojam | 8f9524be0ad850bdfc0c3459b0e4b677f5f70a84 | [
"MIT"
] | 17 | 2018-06-12T20:54:40.000Z | 2022-02-09T23:27:24.000Z | serve_tiny_performance_mdrnn.py | cpmpercussion/robojam | 8f9524be0ad850bdfc0c3459b0e4b677f5f70a84 | [
"MIT"
] | 2 | 2017-12-05T23:39:42.000Z | 2018-06-13T13:46:33.000Z | #!/usr/bin/env python3
"""A flask server for Robojam"""
import json
import time
from io import StringIO
import pandas as pd
import tensorflow as tf
import robojam
from tensorflow.compat.v1.keras import backend as K
from flask import Flask, request
from flask_cors import CORS
# Start server.
tf.compat.v1.logging.set_v... | 121.337838 | 1,670 | 0.702639 | 0 | 0 | 0 | 0 | 1,221 | 0.135984 | 0 | 0 | 7,251 | 0.807551 |
6e63b1a8022fa7d3c4dd2cc0d17b00043e002831 | 1,024 | py | Python | youtube_sync/tasks.py | abhayagiri/youtube-sync | ce3861f1b0c1448b1d48e5ba17925f5c082f04a2 | [
"MIT"
] | null | null | null | youtube_sync/tasks.py | abhayagiri/youtube-sync | ce3861f1b0c1448b1d48e5ba17925f5c082f04a2 | [
"MIT"
] | null | null | null | youtube_sync/tasks.py | abhayagiri/youtube-sync | ce3861f1b0c1448b1d48e5ba17925f5c082f04a2 | [
"MIT"
] | null | null | null | from datetime import datetime
import os
import re
import subprocess
from . import app, celery, db
from .database import Job
@celery.task()
def make_audio(youtube_id):
worker_path = os.path.join(app.root_path, 'worker.sh')
env = {
'DYNAMIC_AUDIO_NORMALIZER_BIN': app.config['DYNAMIC_AUDIO_NORMALIZER_BI... | 26.947368 | 84 | 0.682617 | 0 | 0 | 0 | 0 | 321 | 0.313477 | 0 | 0 | 128 | 0.125 |
6e6b8e97a66c01a64f2cca3a534d23843f440130 | 560 | py | Python | setup.py | garethrylance/python-sdk-example | 3f21c3a6c28f46050688ce1be66e33433a801e7c | [
"CC0-1.0"
] | null | null | null | setup.py | garethrylance/python-sdk-example | 3f21c3a6c28f46050688ce1be66e33433a801e7c | [
"CC0-1.0"
] | null | null | null | setup.py | garethrylance/python-sdk-example | 3f21c3a6c28f46050688ce1be66e33433a801e7c | [
"CC0-1.0"
] | null | null | null | from setuptools import setup
setup(
name="python-sdk-example",
version="0.1",
description="The dispatch model loader - lambda part.",
url="https://github.com/garethrylance/python-sdk-example",
author="Gareth Rylance",
author_email="gareth@rylance.me.uk",
packages=["example_sdk"],
instal... | 31.111111 | 82 | 0.671429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 271 | 0.483929 |
6e6bf3bcb9f6b04ecf66cf6829603687c806b677 | 4,140 | py | Python | markov.py | themichaelusa/zuckerkov | d68780f987b3f032d6382ea75118c84e7f205a39 | [
"MIT"
] | 1 | 2020-03-17T23:34:17.000Z | 2020-03-17T23:34:17.000Z | markov.py | themichaelusa/zuckerkov | d68780f987b3f032d6382ea75118c84e7f205a39 | [
"MIT"
] | null | null | null | markov.py | themichaelusa/zuckerkov | d68780f987b3f032d6382ea75118c84e7f205a39 | [
"MIT"
] | null | null | null | ### IMPORTS
import json
import glob
import string
import random
import spacy
from spacy.lang.en.stop_words import STOP_WORDS
import markovify
### CONSTANTS/GLOBALS/LAMBDAS
SYMBOLS_TO_RM = tuple(list(string.punctuation) + ['\xad'])
NUMBERS_TO_RM = tuple(string.digits)
spacy.prefer_gpu()
NLP_ENGINE = spacy.load("en_c... | 23 | 67 | 0.717874 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,176 | 0.284058 |
6e6ceb4b1bd05af797219ac67e3f71b01f520394 | 6,211 | py | Python | src/cnf_shuffler.py | jreeves3/BiPartGen-Artifact | d7c6db628cad25701a398da67ab87bb725513a61 | [
"MIT"
] | null | null | null | src/cnf_shuffler.py | jreeves3/BiPartGen-Artifact | d7c6db628cad25701a398da67ab87bb725513a61 | [
"MIT"
] | null | null | null | src/cnf_shuffler.py | jreeves3/BiPartGen-Artifact | d7c6db628cad25701a398da67ab87bb725513a61 | [
"MIT"
] | null | null | null | #/**********************************************************************************
# Copyright (c) 2021 Joseph Reeves and Cayden Codel, Carnegie Mellon University
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
# associated documentation files (the "Software"), t... | 34.893258 | 101 | 0.605378 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,694 | 0.433747 |
6e6dbb5cefe12073382965816c2a9d3f10ed725c | 4,171 | py | Python | test/app_page_scraper_test.py | googleinterns/betel | 2daa56081ccc753f5b7eafbd1e9a48e3aca4b657 | [
"Apache-2.0"
] | 1 | 2020-09-21T12:52:33.000Z | 2020-09-21T12:52:33.000Z | test/app_page_scraper_test.py | googleinterns/betel | 2daa56081ccc753f5b7eafbd1e9a48e3aca4b657 | [
"Apache-2.0"
] | null | null | null | test/app_page_scraper_test.py | googleinterns/betel | 2daa56081ccc753f5b7eafbd1e9a48e3aca4b657 | [
"Apache-2.0"
] | 1 | 2020-07-31T09:55:33.000Z | 2020-07-31T09:55:33.000Z | import pathlib
import pytest
from betel import app_page_scraper
from betel import betel_errors
from betel import utils
ICON_HTML = """
<img src="%s" class="T75of sHb2Xb">
"""
CATEGORY_HTML = """
<a itemprop="genre">Example</a>
"""
FILTERED_CATEGORY_HTML = """
<a itemprop="genre">Filtered</a>
"""
SIMPLE_HTML = """
<... | 28.182432 | 86 | 0.714217 | 2,783 | 0.667226 | 0 | 0 | 459 | 0.110046 | 0 | 0 | 479 | 0.114841 |