hexsha string | size int64 | ext string | lang string | max_stars_repo_path string | max_stars_repo_name string | max_stars_repo_head_hexsha string | max_stars_repo_licenses list | max_stars_count int64 | max_stars_repo_stars_event_min_datetime string | max_stars_repo_stars_event_max_datetime string | max_issues_repo_path string | max_issues_repo_name string | max_issues_repo_head_hexsha string | max_issues_repo_licenses list | max_issues_count int64 | max_issues_repo_issues_event_min_datetime string | max_issues_repo_issues_event_max_datetime string | max_forks_repo_path string | max_forks_repo_name string | max_forks_repo_head_hexsha string | max_forks_repo_licenses list | max_forks_count int64 | max_forks_repo_forks_event_min_datetime string | max_forks_repo_forks_event_max_datetime string | content string | avg_line_length float64 | max_line_length int64 | alphanum_fraction float64 | qsc_code_num_words_quality_signal int64 | qsc_code_num_chars_quality_signal float64 | qsc_code_mean_word_length_quality_signal float64 | qsc_code_frac_words_unique_quality_signal float64 | qsc_code_frac_chars_top_2grams_quality_signal float64 | qsc_code_frac_chars_top_3grams_quality_signal float64 | qsc_code_frac_chars_top_4grams_quality_signal float64 | qsc_code_frac_chars_dupe_5grams_quality_signal float64 | qsc_code_frac_chars_dupe_6grams_quality_signal float64 | qsc_code_frac_chars_dupe_7grams_quality_signal float64 | qsc_code_frac_chars_dupe_8grams_quality_signal float64 | qsc_code_frac_chars_dupe_9grams_quality_signal float64 | qsc_code_frac_chars_dupe_10grams_quality_signal float64 | qsc_code_frac_chars_replacement_symbols_quality_signal float64 | qsc_code_frac_chars_digital_quality_signal float64 | qsc_code_frac_chars_whitespace_quality_signal float64 | qsc_code_size_file_byte_quality_signal float64 | qsc_code_num_lines_quality_signal float64 | qsc_code_num_chars_line_max_quality_signal float64 | qsc_code_num_chars_line_mean_quality_signal float64 | qsc_code_frac_chars_alphabet_quality_signal float64 | qsc_code_frac_chars_comments_quality_signal float64 | qsc_code_cate_xml_start_quality_signal float64 | qsc_code_frac_lines_dupe_lines_quality_signal float64 | qsc_code_cate_autogen_quality_signal float64 | qsc_code_frac_lines_long_string_quality_signal float64 | qsc_code_frac_chars_string_length_quality_signal float64 | qsc_code_frac_chars_long_word_length_quality_signal float64 | qsc_code_frac_lines_string_concat_quality_signal float64 | qsc_code_cate_encoded_data_quality_signal float64 | qsc_code_frac_chars_hex_words_quality_signal float64 | qsc_code_frac_lines_prompt_comments_quality_signal float64 | qsc_code_frac_lines_assert_quality_signal float64 | qsc_codepython_cate_ast_quality_signal float64 | qsc_codepython_frac_lines_func_ratio_quality_signal float64 | qsc_codepython_cate_var_zero_quality_signal bool | qsc_codepython_frac_lines_pass_quality_signal float64 | qsc_codepython_frac_lines_import_quality_signal float64 | qsc_codepython_frac_lines_simplefunc_quality_signal float64 | qsc_codepython_score_lines_no_logic_quality_signal float64 | qsc_codepython_frac_lines_print_quality_signal float64 | qsc_code_num_words int64 | qsc_code_num_chars int64 | qsc_code_mean_word_length int64 | qsc_code_frac_words_unique null | qsc_code_frac_chars_top_2grams int64 | qsc_code_frac_chars_top_3grams int64 | qsc_code_frac_chars_top_4grams int64 | qsc_code_frac_chars_dupe_5grams int64 | qsc_code_frac_chars_dupe_6grams int64 | qsc_code_frac_chars_dupe_7grams int64 | qsc_code_frac_chars_dupe_8grams int64 | qsc_code_frac_chars_dupe_9grams int64 | qsc_code_frac_chars_dupe_10grams int64 | qsc_code_frac_chars_replacement_symbols int64 | qsc_code_frac_chars_digital int64 | qsc_code_frac_chars_whitespace int64 | qsc_code_size_file_byte int64 | qsc_code_num_lines int64 | qsc_code_num_chars_line_max int64 | qsc_code_num_chars_line_mean int64 | qsc_code_frac_chars_alphabet int64 | qsc_code_frac_chars_comments int64 | qsc_code_cate_xml_start int64 | qsc_code_frac_lines_dupe_lines int64 | qsc_code_cate_autogen int64 | qsc_code_frac_lines_long_string int64 | qsc_code_frac_chars_string_length int64 | qsc_code_frac_chars_long_word_length int64 | qsc_code_frac_lines_string_concat null | qsc_code_cate_encoded_data int64 | qsc_code_frac_chars_hex_words int64 | qsc_code_frac_lines_prompt_comments int64 | qsc_code_frac_lines_assert int64 | qsc_codepython_cate_ast int64 | qsc_codepython_frac_lines_func_ratio int64 | qsc_codepython_cate_var_zero int64 | qsc_codepython_frac_lines_pass int64 | qsc_codepython_frac_lines_import int64 | qsc_codepython_frac_lines_simplefunc int64 | qsc_codepython_score_lines_no_logic int64 | qsc_codepython_frac_lines_print int64 | effective string | hits int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ce2a982a0e4d8995d7542eb89ba80c55fc2409b2 | 131 | py | Python | extra_old_code/even_odd.py | ugo-en/some-python-code | 95ca7d9f34ab175dc25556b1c0485134c49b0370 | [
"MIT"
] | null | null | null | extra_old_code/even_odd.py | ugo-en/some-python-code | 95ca7d9f34ab175dc25556b1c0485134c49b0370 | [
"MIT"
] | null | null | null | extra_old_code/even_odd.py | ugo-en/some-python-code | 95ca7d9f34ab175dc25556b1c0485134c49b0370 | [
"MIT"
] | null | null | null | test = int(input("Enter a whole number"))
if (test % 2 ==00):
print(test, "is even.")
else:
print(test, ""odd number")
| 21.833333 | 42 | 0.572519 | 20 | 131 | 3.75 | 0.75 | 0.24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029703 | 0.229008 | 131 | 5 | 43 | 26.2 | 0.712871 | 0 | 0 | 0 | 0 | 0 | 0.221374 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.4 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
02187df5c6da5220dd248bf10d57174be096541f | 207 | py | Python | we-web/scripts/prepare_db.py | h-qub/wordeater-web | 9a336d1e467d08c6b3875bd8b83dea0dc3b9236d | [
"MIT"
] | null | null | null | we-web/scripts/prepare_db.py | h-qub/wordeater-web | 9a336d1e467d08c6b3875bd8b83dea0dc3b9236d | [
"MIT"
] | 3 | 2016-03-11T08:43:47.000Z | 2016-11-01T13:07:48.000Z | we-web/scripts/prepare_db.py | h-qub/wordeater-web | 9a336d1e467d08c6b3875bd8b83dea0dc3b9236d | [
"MIT"
] | null | null | null | # coding=utf-8
__author__ = 'Warlock'
from flask.ext.script import Command
from services.users import UserService
from domain.model import db
class CreatDatabase(Command):
def run(self):
pass
| 17.25 | 38 | 0.743961 | 28 | 207 | 5.357143 | 0.821429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005882 | 0.178744 | 207 | 11 | 39 | 18.818182 | 0.876471 | 0.057971 | 0 | 0 | 0 | 0 | 0.036269 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0.142857 | 0.428571 | 0 | 0.714286 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 4 |
02272b50731feb5f67d123e7b6ab5d8223364afb | 43 | py | Python | rsvm/__init__.py | Doctorado-ML/RSvm | 42c2e40000d9dded4c80a827aeda236ab91a0cd3 | [
"MIT"
] | 1 | 2021-05-23T16:47:00.000Z | 2021-05-23T16:47:00.000Z | rsvm/__init__.py | Doctorado-ML/RSvm | 42c2e40000d9dded4c80a827aeda236ab91a0cd3 | [
"MIT"
] | null | null | null | rsvm/__init__.py | Doctorado-ML/RSvm | 42c2e40000d9dded4c80a827aeda236ab91a0cd3 | [
"MIT"
] | null | null | null | from .RSvm import RSvm
__all__ = ["RSvm"]
| 10.75 | 22 | 0.674419 | 6 | 43 | 4.166667 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.186047 | 43 | 3 | 23 | 14.333333 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0.093023 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
026960fa41d2f5ee17dfac2dee8257f82957df3a | 560 | py | Python | Pothos/InputPort.py | pothosware/PothosPython | c6d7ed4ef7578a5534ec6a4ba3159a9683970bd3 | [
"BSL-1.0"
] | 7 | 2018-01-02T14:21:08.000Z | 2021-07-08T19:44:24.000Z | Pothos/InputPort.py | BelmY/PothosPython | b597d9e2d914f8e8e31b7335fe2db17af6b88e55 | [
"BSL-1.0"
] | 7 | 2015-12-17T03:27:49.000Z | 2017-02-10T17:37:55.000Z | Pothos/InputPort.py | BelmY/PothosPython | b597d9e2d914f8e8e31b7335fe2db17af6b88e55 | [
"BSL-1.0"
] | 4 | 2018-05-24T21:28:53.000Z | 2022-03-24T06:20:15.000Z | # Copyright (c) 2014-2016 Josh Blum
# SPDX-License-Identifier: BSL-1.0
from . PothosModule import *
from . Label import Label, LabelIteratorRange
from . Buffer import pointer_to_ndarray
from . Buffer import dtype_to_numpy
import numpy
class InputPort(object):
def __init__(self, port):
self._port = port
def __getattr__(self, name):
return lambda *args: self._port.call(name, *args)
def labels(self):
return LabelIteratorRange(self._port.labels())
def dtype(self):
return dtype_to_numpy(self._port.dtype())
| 25.454545 | 57 | 0.707143 | 74 | 560 | 5.108108 | 0.5 | 0.10582 | 0.084656 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.022173 | 0.194643 | 560 | 21 | 58 | 26.666667 | 0.815965 | 0.117857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.357143 | 0.214286 | 0.928571 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 4 |
5a0626942a56258102798b86dfbb8c0d2c9be433 | 216 | py | Python | bin/sa_haveibeenpwned/aob_py3/backports/__init__.py | hRun/SA-haveibeenpwned | 2a8ae3dedc405dc3c8dac1cb6a705a70f574afdb | [
"Apache-2.0"
] | 2 | 2020-08-17T07:52:48.000Z | 2020-12-18T16:39:32.000Z | bin/sa_haveibeenpwned/aob_py2/backports/__init__.py | hRun/SA-haveibeenpwned | 2a8ae3dedc405dc3c8dac1cb6a705a70f574afdb | [
"Apache-2.0"
] | 5 | 2020-12-15T23:40:14.000Z | 2022-02-23T15:43:18.000Z | bin/sa_haveibeenpwned/aob_py2/backports/__init__.py | hRun/SA-haveibeenpwned | 2a8ae3dedc405dc3c8dac1cb6a705a70f574afdb | [
"Apache-2.0"
] | 4 | 2019-05-16T09:57:33.000Z | 2021-07-14T12:31:21.000Z | # A Python "namespace package" http://www.python.org/dev/peps/pep-0382/
# This always goes inside of a namespace package's __init__.py
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
| 36 | 72 | 0.768519 | 33 | 216 | 4.484848 | 0.757576 | 0.216216 | 0.189189 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021505 | 0.138889 | 216 | 5 | 73 | 43.2 | 0.774194 | 0.601852 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
5a095fd0da5e24afe585557d1aac0166773fdcbd | 1,063 | py | Python | test.py | BraunPhilipp/sentiment-analyzer | de1528c924b7015bafda56196b264523b64dc7c1 | [
"MIT"
] | 4 | 2016-09-24T22:09:49.000Z | 2017-05-17T12:51:48.000Z | test.py | BraunPhilipp/sentiment-analyzer | de1528c924b7015bafda56196b264523b64dc7c1 | [
"MIT"
] | 2 | 2016-11-29T05:50:01.000Z | 2021-02-13T18:07:20.000Z | test.py | BraunPhilipp/sentiment-analyzer | de1528c924b7015bafda56196b264523b64dc7c1 | [
"MIT"
] | null | null | null | from logger import logger
from api import api
## Tracker
#api.tracker().create('donald trump')
#api.tracker().delete('ruby')
#print(api.tracker().next())
## Reviews
# import reviews.walmart as walmart
#
# for i in range(1, 1000000):
# rt = walmart.walmart().data
# print(rt)
#
# if len(rt) > 0:
# api.review().create(rt)
#print(api.review().search('en-us'))
## Sentiment
# from sentiment import sentiment
#
# data = ['i love roses', 'dude this is really bad', 'i hate you', 'do not like this', """don't do it"""]
#
# for s in data:
# print(s + str(sentiment.get(s)))
# print(api.tracker().next())
## Tweets
# from twitter import twitter
#
# track = api.tracker().next()
# twitter.twitter(track['keyword'], track['id'], track['min_id'], track['max_id']).loopTweets()
#
## 5 amazon
# import reviews.amazon as amazon
#
# for i in range(1, 1000000):
# rt = amazon.amazon().search()
# print(rt)
#
# if len(rt) > 0:
# mysql.reviews().add(rt)
#print(api.tweet_data().search('ruby'))
#print(api.tracker().get())
| 18.649123 | 105 | 0.618062 | 152 | 1,063 | 4.302632 | 0.407895 | 0.107034 | 0.068807 | 0.058104 | 0.110092 | 0.110092 | 0.06422 | 0 | 0 | 0 | 0 | 0.021814 | 0.180621 | 1,063 | 56 | 106 | 18.982143 | 0.729047 | 0.863594 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
5a125550803bc179b384fa5344ab20371c2e644e | 2,296 | py | Python | cogs/connect_four/buttons.py | Gumbachi/HallBot | eb779507ffd2f17b7f9776c3dda2a55de34cae6e | [
"MIT"
] | null | null | null | cogs/connect_four/buttons.py | Gumbachi/HallBot | eb779507ffd2f17b7f9776c3dda2a55de34cae6e | [
"MIT"
] | null | null | null | cogs/connect_four/buttons.py | Gumbachi/HallBot | eb779507ffd2f17b7f9776c3dda2a55de34cae6e | [
"MIT"
] | null | null | null | """Module holds buttons for connect four."""
import discord
from discord.enums import ButtonStyle
from discord.ui import Button
class Emoji:
RIGHT = "▶️"
LEFT = "◀️"
BIGLEFT = "⏪"
BIGRIGHT = "⏩"
SUBMIT = "✅"
class RightButton(Button):
def __init__(self, game):
super().__init__(emoji=Emoji.RIGHT, style=ButtonStyle.gray)
self.game = game
async def callback(self, interaction: discord.Interaction):
if self.game.cursor_position == 6:
return
self.game.cursor_position += 1
await interaction.response.edit_message(embed=self.game.embed)
class LeftButton(Button):
def __init__(self, game):
super().__init__(emoji=Emoji.LEFT, style=ButtonStyle.gray)
self.game = game
async def callback(self, interaction: discord.Interaction):
if self.game.cursor_position == 0:
return
self.game.cursor_position -= 1
await interaction.response.edit_message(embed=self.game.embed)
class BigRightButton(Button):
def __init__(self, game):
super().__init__(emoji=Emoji.BIGRIGHT, style=ButtonStyle.gray)
self.game = game
async def callback(self, interaction: discord.Interaction):
if self.game.cursor_position == 6:
return
self.game.cursor_position = 6
await interaction.response.edit_message(embed=self.game.embed)
class BigLeftButton(Button):
def __init__(self, game):
super().__init__(emoji=Emoji.BIGLEFT, style=ButtonStyle.gray)
self.game = game
async def callback(self, interaction: discord.Interaction):
if self.game.cursor_position == 0:
return
self.game.cursor_position = 0
await interaction.response.edit_message(embed=self.game.embed)
class SubmitButton(Button):
def __init__(self, game):
super().__init__(emoji=Emoji.SUBMIT, style=ButtonStyle.green)
self.game = game
async def callback(self, interaction: discord.Interaction):
# Check if move is legal
if all(self.game.get_column(self.game.cursor_position)):
return
self.game.submit_move()
self.game.check_win()
self.game.swap_turn()
await interaction.response.edit_message(embed=self.game.embed)
| 28.7 | 70 | 0.662456 | 276 | 2,296 | 5.326087 | 0.228261 | 0.152381 | 0.085714 | 0.134694 | 0.738776 | 0.737415 | 0.737415 | 0.737415 | 0.737415 | 0.565306 | 0 | 0.004522 | 0.22953 | 2,296 | 79 | 71 | 29.063291 | 0.822499 | 0.027003 | 0 | 0.517857 | 0 | 0 | 0.003142 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.089286 | false | 0 | 0.053571 | 0 | 0.428571 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
5a27afa28c35dce754027e37c079003105cad2c6 | 23 | py | Python | trimesh/version.py | carolina-mesquita-hp/trimesh | 90af69803958bdffee55a7fa3f43bdadfac95415 | [
"MIT"
] | null | null | null | trimesh/version.py | carolina-mesquita-hp/trimesh | 90af69803958bdffee55a7fa3f43bdadfac95415 | [
"MIT"
] | null | null | null | trimesh/version.py | carolina-mesquita-hp/trimesh | 90af69803958bdffee55a7fa3f43bdadfac95415 | [
"MIT"
] | null | null | null | __version__ = '3.8.11'
| 11.5 | 22 | 0.652174 | 4 | 23 | 2.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 0.130435 | 23 | 1 | 23 | 23 | 0.35 | 0 | 0 | 0 | 0 | 0 | 0.26087 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
5a3a5579128f977cdcd0b197818631bfffc9f348 | 26 | py | Python | neo/__init__.py | nunojusto/neo-python | 1f54bca9d14fa547290f278f0539a4d4b0c13195 | [
"MIT"
] | null | null | null | neo/__init__.py | nunojusto/neo-python | 1f54bca9d14fa547290f278f0539a4d4b0c13195 | [
"MIT"
] | null | null | null | neo/__init__.py | nunojusto/neo-python | 1f54bca9d14fa547290f278f0539a4d4b0c13195 | [
"MIT"
] | null | null | null | __version__ = '0.7.9-dev'
| 13 | 25 | 0.653846 | 5 | 26 | 2.6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.130435 | 0.115385 | 26 | 1 | 26 | 26 | 0.434783 | 0 | 0 | 0 | 0 | 0 | 0.346154 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
5a4aaa71df111c41cf05bca7a92cd681604282e7 | 2,410 | py | Python | src/metamodels/troll_rng.py | VivaLaPanda/bayeslite-server | a6056a7cc2ea77c5b6d818d46ae3c574a9fd5a88 | [
"Apache-2.0"
] | 1 | 2019-10-31T04:03:38.000Z | 2019-10-31T04:03:38.000Z | src/metamodels/troll_rng.py | VivaLaPanda/bayeslite-server | a6056a7cc2ea77c5b6d818d46ae3c574a9fd5a88 | [
"Apache-2.0"
] | null | null | null | src/metamodels/troll_rng.py | VivaLaPanda/bayeslite-server | a6056a7cc2ea77c5b6d818d46ae3c574a9fd5a88 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# Copyright (c) 2010-2016, MIT Probabilistic Computing Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""The Troll Model posits that all data values are equal to 9.
Reference: http://dilbert.com/strip/2001-10-25
This is an example of the simplest possible population model.
This module implements the :class:`bayeslite.IBayesDBMetamodel`
interface for the Troll Model.
"""
import bayeslite.metamodel as metamodel
class TrollMetamodel(metamodel.IBayesDBMetamodel):
"""Troll metamodel for BayesDB.
The metamodel is named ``troll_rng`` in BQL::
CREATE GENERATOR t_troll FOR t USING troll_rng(..)
"""
def __init__(self): pass
def name(self): return 'troll_rng'
def register(self, bdb):
bdb.sql_execute('''
INSERT INTO bayesdb_metamodel (name, version)
VALUES (?, 1)
''', (self.name(),))
def create_generator(self, bdb, generator_id, schema, **kwargs):
pass
def drop_generator(self, *args, **kwargs): pass
def rename_column(self, *args, **kwargs): pass
def initialize_models(self, *args, **kwargs): pass
def drop_models(self, *args, **kwargs): pass
def analyze_models(self, *args, **kwargs): pass
def simulate_joint(self, _bdb, _generator_id, _modelnos, rowid, targets,
_constraints, num_samples=1):
return [[9 for _ in targets]] * num_samples
def logpdf_joint(self, _bdb, _generator_id, _modelnos, rowid, targets,
constraints):
for (_, value) in constraints:
if not value == 9:
return float("nan")
for (_, value) in targets:
if not value == 9:
return float("-inf")
# TODO This is only correct wrt counting measure. What's the
# base measure of numericals?
return 0
def infer(self, *args, **kwargs): pass
| 36.515152 | 76 | 0.663485 | 318 | 2,410 | 4.924528 | 0.490566 | 0.03129 | 0.049808 | 0.068966 | 0.175607 | 0.148787 | 0.068966 | 0.068966 | 0.068966 | 0 | 0 | 0.015226 | 0.236929 | 2,410 | 65 | 77 | 37.076923 | 0.836324 | 0.461411 | 0 | 0.068966 | 0 | 0 | 0.089825 | 0 | 0 | 0 | 0 | 0.015385 | 0 | 1 | 0.413793 | false | 0.275862 | 0.034483 | 0.068966 | 0.62069 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 |
5a539efadb82ab5bc90c66e8927c2d8d67cc6778 | 2,066 | py | Python | encodings/mac_farsi.py | theclashingfritz/Cog-Invasion-Online-Dump | 2561abbacb3e2e288e06f3f04b935b5ed589c8f8 | [
"Apache-2.0"
] | 1 | 2020-03-12T16:44:10.000Z | 2020-03-12T16:44:10.000Z | encodings/mac_farsi.py | theclashingfritz/Cog-Invasion-Online-Dump | 2561abbacb3e2e288e06f3f04b935b5ed589c8f8 | [
"Apache-2.0"
] | null | null | null | encodings/mac_farsi.py | theclashingfritz/Cog-Invasion-Online-Dump | 2561abbacb3e2e288e06f3f04b935b5ed589c8f8 | [
"Apache-2.0"
] | null | null | null | # uncompyle6 version 3.2.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 2.7.15 (v2.7.15:ca079a3ea3, Apr 30 2018, 16:30:26) [MSC v.1500 64 bit (AMD64)]
# Embedded file name: encodings.mac_farsi
import codecs
class Codec(codecs.Codec):
def encode(self, input, errors='strict'):
return codecs.charmap_encode(input, errors, encoding_table)
def decode(self, input, errors='strict'):
return codecs.charmap_decode(input, errors, decoding_table)
class IncrementalEncoder(codecs.IncrementalEncoder):
def encode(self, input, final=False):
return codecs.charmap_encode(input, self.errors, encoding_table)[0]
class IncrementalDecoder(codecs.IncrementalDecoder):
def decode(self, input, final=False):
return codecs.charmap_decode(input, self.errors, decoding_table)[0]
class StreamWriter(Codec, codecs.StreamWriter):
pass
class StreamReader(Codec, codecs.StreamReader):
pass
def getregentry():
return codecs.CodecInfo(name='mac-farsi', encode=Codec().encode, decode=Codec().decode, incrementalencoder=IncrementalEncoder, incrementaldecoder=IncrementalDecoder, streamreader=StreamReader, streamwriter=StreamWriter)
decoding_table = u'\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f !"#$%&\'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~\x7f\xc4\xa0\xc7\xc9\xd1\xd6\xdc\xe1\xe0\xe2\xe4\u06ba\xab\xe7\xe9\xe8\xea\xeb\xed\u2026\xee\xef\xf1\xf3\xbb\xf4\xf6\xf7\xfa\xf9\xfb\xfc !"#$\u066a&\'()*+\u060c-./\u06f0\u06f1\u06f2\u06f3\u06f4\u06f5\u06f6\u06f7\u06f8\u06f9:\u061b<=>\u061f\u274a\u0621\u0622\u0623\u0624\u0625\u0626\u0627\u0628\u0629\u062a\u062b\u062c\u062d\u062e\u062f\u0630\u0631\u0632\u0633\u0634\u0635\u0636\u0637\u0638\u0639\u063a[\\]^_\u0640\u0641\u0642\u0643\u0644\u0645\u0646\u0647\u0648\u0649\u064a\u064b\u064c\u064d\u064e\u064f\u0650\u0651\u0652\u067e\u0679\u0686\u06d5\u06a4\u06af\u0688\u0691{|}\u0698\u06d2'
encoding_table = codecs.charmap_build(decoding_table) | 50.390244 | 823 | 0.75605 | 294 | 2,066 | 5.261905 | 0.666667 | 0.038785 | 0.049127 | 0.023271 | 0.129282 | 0.10084 | 0.10084 | 0 | 0 | 0 | 0 | 0.198417 | 0.082769 | 2,066 | 41 | 824 | 50.390244 | 0.617942 | 0.094385 | 0 | 0.1 | 0 | 0.1 | 0.313337 | 0.297804 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.1 | 0.05 | 0.25 | 0.8 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 4 |
5a7da4057286feb7bb84f5d0c8b296070337ad84 | 24 | py | Python | php_tc.py | akshatvg/So-Many-Languages | 7dc1aa59c2798e4d4ae77cde818dd45e9e93399e | [
"MIT"
] | 7 | 2019-09-07T03:36:19.000Z | 2021-02-21T20:57:24.000Z | php_tc.py | Nirmitjatana/So-Many-Languages | 82c62082aab8c69c26a5e9a7e4f687f3ecc5cbf0 | [
"MIT"
] | 6 | 2020-03-23T08:45:28.000Z | 2020-08-11T02:27:32.000Z | php_tc.py | Nirmitjatana/So-Many-Languages | 82c62082aab8c69c26a5e9a7e4f687f3ecc5cbf0 | [
"MIT"
] | 6 | 2019-09-08T12:28:58.000Z | 2020-10-09T05:18:13.000Z | n= input()
print('hey')
| 8 | 12 | 0.583333 | 4 | 24 | 3.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 24 | 2 | 13 | 12 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0.125 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
ce706378e6f944c4f5daa17d147fb4a04e3d6119 | 105 | py | Python | scripts/config.py | ekungurov/devops-school-website-v1 | 72ce08d3c928cb1413b3deaa607692ab7c536e6b | [
"MIT"
] | null | null | null | scripts/config.py | ekungurov/devops-school-website-v1 | 72ce08d3c928cb1413b3deaa607692ab7c536e6b | [
"MIT"
] | null | null | null | scripts/config.py | ekungurov/devops-school-website-v1 | 72ce08d3c928cb1413b3deaa607692ab7c536e6b | [
"MIT"
] | null | null | null | DB_HOSTNAME = "localhost"
DB_LOGIN = "db_login"
DB_PASSWORD = "some_secret_password"
DB_NAME = "db_name"
| 21 | 36 | 0.771429 | 16 | 105 | 4.5625 | 0.5 | 0.191781 | 0.246575 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114286 | 105 | 4 | 37 | 26.25 | 0.784946 | 0 | 0 | 0 | 0 | 0 | 0.419048 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.25 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
ce94dc507341659dacff3113d79fb923b468fceb | 108 | py | Python | temp.py | UTCSheffield/PiTemp | a84f72569c8686ff6c2153a1b6fa331183693048 | [
"MIT"
] | null | null | null | temp.py | UTCSheffield/PiTemp | a84f72569c8686ff6c2153a1b6fa331183693048 | [
"MIT"
] | 8 | 2018-05-02T11:26:30.000Z | 2018-05-09T10:58:54.000Z | temp.py | UTCSheffield/PiTemp | a84f72569c8686ff6c2153a1b6fa331183693048 | [
"MIT"
] | null | null | null | from envirophat import weather
import time
while True:
print(weather.temperature())
time.sleep(15)
| 15.428571 | 32 | 0.740741 | 14 | 108 | 5.714286 | 0.785714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.022472 | 0.175926 | 108 | 6 | 33 | 18 | 0.876404 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.4 | 0 | 0.4 | 0.2 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
ceb235b389f2033eda5d59eb8440bb234b7e8ef2 | 14 | py | Python | Genetic Algorithm/genetic_algorithm.py | armandwayoff/Graph-Optimization | 9a7472d023935a49e270f1d1d7191af26ca6ffe9 | [
"MIT"
] | 1 | 2021-12-07T18:03:27.000Z | 2021-12-07T18:03:27.000Z | Genetic Algorithm/genetic_algorithm.py | armandwayoff/Graph-Optimization | 9a7472d023935a49e270f1d1d7191af26ca6ffe9 | [
"MIT"
] | null | null | null | Genetic Algorithm/genetic_algorithm.py | armandwayoff/Graph-Optimization | 9a7472d023935a49e270f1d1d7191af26ca6ffe9 | [
"MIT"
] | null | null | null | # to complete
| 7 | 13 | 0.714286 | 2 | 14 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.214286 | 14 | 1 | 14 | 14 | 0.909091 | 0.785714 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
cec5e6b740bb52f8bfb38b02fa1598024af1c53f | 254 | py | Python | server/service/slack/workflow/helper.py | EtienneTurc/IChooseYou | 9ea7767b793ba6ef389f7cc806a02db2e1434c70 | [
"MIT"
] | 4 | 2022-01-10T10:04:12.000Z | 2022-01-10T18:05:48.000Z | server/service/slack/workflow/helper.py | EtienneTurc/IChooseYou | 9ea7767b793ba6ef389f7cc806a02db2e1434c70 | [
"MIT"
] | null | null | null | server/service/slack/workflow/helper.py | EtienneTurc/IChooseYou | 9ea7767b793ba6ef389f7cc806a02db2e1434c70 | [
"MIT"
] | null | null | null | from server.service.slack.workflow.enum import OutputVariable
def create_select_item_name(index: int) -> str:
return f"{OutputVariable.SELECTED_ITEM.value}_{index}"
def create_value_dict(value: any) -> dict[str, any]:
return {"value": value}
| 25.4 | 61 | 0.748031 | 35 | 254 | 5.228571 | 0.628571 | 0.098361 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125984 | 254 | 9 | 62 | 28.222222 | 0.824324 | 0 | 0 | 0 | 0 | 0 | 0.192913 | 0.173228 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0.2 | 0.4 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
0c66a2d3f85e6730dba8436522307c43ba5009c3 | 2,090 | py | Python | test_WiFiClientSecure/test_tenki.py | t-ikegami/WioTerminal-CircuitPython | efbdc2e13ad969fe009d88f7ec4b836ca61ae973 | [
"MIT"
] | null | null | null | test_WiFiClientSecure/test_tenki.py | t-ikegami/WioTerminal-CircuitPython | efbdc2e13ad969fe009d88f7ec4b836ca61ae973 | [
"MIT"
] | 1 | 2022-01-19T00:16:02.000Z | 2022-01-26T03:43:34.000Z | test_WiFiClientSecure/test_tenki.py | t-ikegami/WioTerminal-CircuitPython | efbdc2e13ad969fe009d88f7ec4b836ca61ae973 | [
"MIT"
] | null | null | null | from wifi_connect import wifi_connect
from wio_terminal_rtl.WiFiClientSecure import WiFiClientSecure
from wio_terminal_rtl.rpc import ssl
wifi_connect()
c = WiFiClientSecure()
c.rootCA = """-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----
"""
c.connect("tenki.jp", 443)
c.write("""GET /lite/forecast/3/16/4410/13101/ HTTP/1.1
HOST: tenki.jp
""")
res = c.read()
while res != None :
print(res.decode(), end = "")
res = c.read()
c.stop()
| 43.541667 | 64 | 0.903828 | 115 | 2,090 | 16.365217 | 0.747826 | 0.017535 | 0.01594 | 0.019129 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.112444 | 0.042584 | 2,090 | 47 | 65 | 44.468085 | 0.828086 | 0 | 0 | 0.046512 | 0 | 0 | 0.84067 | 0.780383 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.069767 | 0 | 0.069767 | 0.023256 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0c701a73487c810b67b79f6b0c9d9613598c12d8 | 201 | py | Python | models/__init__.py | bckim92/sequential-knowledge-transformer | 1e9c47bb61291a0b15e5b1e6901eafebc73db8db | [
"MIT"
] | 135 | 2020-01-03T08:35:35.000Z | 2022-03-28T03:19:55.000Z | models/__init__.py | bckim92/sequential-knowledge-transformer | 1e9c47bb61291a0b15e5b1e6901eafebc73db8db | [
"MIT"
] | 7 | 2020-01-17T16:02:28.000Z | 2021-02-02T14:11:19.000Z | models/__init__.py | bckim92/sequential-knowledge-transformer | 1e9c47bb61291a0b15e5b1e6901eafebc73db8db | [
"MIT"
] | 12 | 2020-01-29T12:17:07.000Z | 2022-02-24T16:18:44.000Z | from models.base import BaseModel
from models.sequential_knowledge_transformer import SequentialKnowledgeTransformer
MODELS = {
'SequentialKnowledgeTransformer': SequentialKnowledgeTransformer,
}
| 28.714286 | 82 | 0.860697 | 15 | 201 | 11.4 | 0.6 | 0.116959 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.094527 | 201 | 6 | 83 | 33.5 | 0.93956 | 0 | 0 | 0 | 0 | 0 | 0.149254 | 0.149254 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
0c7623ef1e018b4dccc74df1960a3250f22f08fa | 89 | py | Python | Newline.py | mcjohnchristopher/Python_Samples | 738f3b7d9baa7f4e396647f380118eba66ea645c | [
"CC0-1.0"
] | null | null | null | Newline.py | mcjohnchristopher/Python_Samples | 738f3b7d9baa7f4e396647f380118eba66ea645c | [
"CC0-1.0"
] | null | null | null | Newline.py | mcjohnchristopher/Python_Samples | 738f3b7d9baa7f4e396647f380118eba66ea645c | [
"CC0-1.0"
] | null | null | null | Stuff = 'Hello\nWorld'
stuff
print stuff
stuff = 'X\nY'
print stuff
len(stuff)
| 9.888889 | 23 | 0.640449 | 13 | 89 | 4.384615 | 0.538462 | 0.350877 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.247191 | 89 | 8 | 24 | 11.125 | 0.850746 | 0 | 0 | 0.333333 | 0 | 0 | 0.197531 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.333333 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0ca086bd28170a535a3dbd9141d7e087d3a2f3f3 | 377 | bzl | Python | cargo/defs.bzl | yesudeep/rules_rust | cdca6ed5eb9609cbc3f6b5d8f760e46e3b0596a2 | [
"Apache-2.0"
] | 349 | 2016-03-15T20:38:00.000Z | 2022-03-28T07:03:02.000Z | cargo/defs.bzl | yesudeep/rules_rust | cdca6ed5eb9609cbc3f6b5d8f760e46e3b0596a2 | [
"Apache-2.0"
] | 872 | 2016-03-18T06:40:26.000Z | 2022-03-31T16:04:04.000Z | cargo/defs.bzl | yesudeep/rules_rust | cdca6ed5eb9609cbc3f6b5d8f760e46e3b0596a2 | [
"Apache-2.0"
] | 231 | 2016-03-16T11:34:47.000Z | 2022-03-25T23:01:35.000Z | """Common definitions for the `@rules_rust//cargo` package"""
load(":cargo_bootstrap.bzl", _cargo_bootstrap_repository = "cargo_bootstrap_repository", _cargo_env = "cargo_env")
load(":cargo_build_script.bzl", _cargo_build_script = "cargo_build_script")
cargo_bootstrap_repository = _cargo_bootstrap_repository
cargo_env = _cargo_env
cargo_build_script = _cargo_build_script
| 37.7 | 114 | 0.822281 | 49 | 377 | 5.714286 | 0.306122 | 0.25 | 0.285714 | 0.414286 | 0.685714 | 0.685714 | 0.457143 | 0.457143 | 0.457143 | 0.457143 | 0 | 0 | 0.076923 | 377 | 9 | 115 | 41.888889 | 0.804598 | 0.145889 | 0 | 0 | 0 | 0 | 0.303797 | 0.155063 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0ccbfa3e52248109ec725450a3d0fb66bbd972b6 | 986 | py | Python | gameComponents/weaponChoose.py | Chavezgabo11/Rock-Paper-Scissors-Game | 56c29db7b553e63cbf2785a83aae6c088e6f86a5 | [
"Unlicense"
] | null | null | null | gameComponents/weaponChoose.py | Chavezgabo11/Rock-Paper-Scissors-Game | 56c29db7b553e63cbf2785a83aae6c088e6f86a5 | [
"Unlicense"
] | null | null | null | gameComponents/weaponChoose.py | Chavezgabo11/Rock-Paper-Scissors-Game | 56c29db7b553e63cbf2785a83aae6c088e6f86a5 | [
"Unlicense"
] | null | null | null | from gameComponents import gameVars
def weapon():
if gameVars.computer_choice == gameVars.player_choice:
print("tie")
elif gameVars.computer_choice == "rock":
if gameVars.player_choice == "scissors":
gameVars.player_lives -= 1
print("you lose! player lives:", gameVars.player_lives)
else:
print("you win!")
gameVars.computer_lives -= 1
elif gameVars.computer_choice == "paper":
if gameVars.player_choice == "rock":
gameVars.player_lives -= 1
print("you lose! player lives:", gameVars.player_lives)
else:
print("you win!")
gameVars.computer_lives -= 1
elif gameVars.computer_choice == "scissors":
if gameVars.player_choice == "paper":
gameVars.player_lives -= 1
print("you lose! player lives:", gameVars.player_lives)
else:
print("you win!")
gameVars.computer_lives -= 1 | 37.923077 | 67 | 0.593306 | 105 | 986 | 5.409524 | 0.209524 | 0.246479 | 0.200704 | 0.137324 | 0.614437 | 0.614437 | 0.614437 | 0.614437 | 0.614437 | 0.614437 | 0 | 0.008658 | 0.29716 | 986 | 26 | 68 | 37.923077 | 0.810967 | 0 | 0 | 0.6 | 0 | 0 | 0.131712 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.04 | true | 0 | 0.04 | 0 | 0.08 | 0.28 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0cdba52b2aec708bc1a72ef1393ec1c8e8d3d5e0 | 202 | py | Python | arithmatic.py | ASTYWY/PY | 6d073fb1af67e0cd1bbc39dd586f7239873910bf | [
"MIT"
] | null | null | null | arithmatic.py | ASTYWY/PY | 6d073fb1af67e0cd1bbc39dd586f7239873910bf | [
"MIT"
] | null | null | null | arithmatic.py | ASTYWY/PY | 6d073fb1af67e0cd1bbc39dd586f7239873910bf | [
"MIT"
] | null | null | null | a=float(input("Введите сторону a: "))
b=float(input("Введите сторону b: "))
c=float(input("Введите сторону c: "))
p=(a+b+c) /2
s1=p*(p-a)*(p-b)*(p-c)
s=s1**(0.5)
print("Плошадь треугольника равна: ", s) | 28.857143 | 40 | 0.628713 | 40 | 202 | 3.175 | 0.425 | 0.23622 | 0.401575 | 0.566929 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.027473 | 0.09901 | 202 | 7 | 40 | 28.857143 | 0.67033 | 0 | 0 | 0 | 0 | 0 | 0.418719 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.142857 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0b543b0da3b0e11c755c6952ff335f1157d45b6a | 165 | py | Python | Week 7/django/bin/django-admin.py | bpgc-cte/python2017 | c1eed0201039c6b4daf857dd1f08c47a7b1e3f45 | [
"MIT"
] | 23 | 2017-09-02T08:15:17.000Z | 2019-11-20T04:30:52.000Z | Week 7/django/bin/django-admin.py | carlosal1015/python2017 | c1eed0201039c6b4daf857dd1f08c47a7b1e3f45 | [
"MIT"
] | 2 | 2017-08-24T06:53:33.000Z | 2017-08-24T06:54:42.000Z | Week 7/django/bin/django-admin.py | bpgc-cte/python2017 | c1eed0201039c6b4daf857dd1f08c47a7b1e3f45 | [
"MIT"
] | 22 | 2017-08-22T08:01:09.000Z | 2019-11-20T04:30:56.000Z | #!/Users/sebastinsanty/Desktop/CS/cte/django/bin/python3.6
from django.core import management
if __name__ == "__main__":
management.execute_from_command_line()
| 27.5 | 58 | 0.787879 | 22 | 165 | 5.409091 | 0.863636 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.013333 | 0.090909 | 165 | 5 | 59 | 33 | 0.78 | 0.345455 | 0 | 0 | 0 | 0 | 0.074766 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
0b858ac57a336f9995b60b57a77138eb9c4f12c3 | 1,270 | py | Python | tools/leetcode.044.Wildcard Matching/leetcode.044.Wildcard Matching.submission5.py | tedye/leetcode | 975d7e3b8cb9b6be9e80e07febf4bcf6414acd46 | [
"MIT"
] | 4 | 2015-10-10T00:30:55.000Z | 2020-07-27T19:45:54.000Z | tools/leetcode.044.Wildcard Matching/leetcode.044.Wildcard Matching.submission5.py | tedye/leetcode | 975d7e3b8cb9b6be9e80e07febf4bcf6414acd46 | [
"MIT"
] | null | null | null | tools/leetcode.044.Wildcard Matching/leetcode.044.Wildcard Matching.submission5.py | tedye/leetcode | 975d7e3b8cb9b6be9e80e07febf4bcf6414acd46 | [
"MIT"
] | null | null | null | class Solution:
# @param s, an input string
# @param p, a pattern string
# @return a boolean
def isMatch(self, s, p):
if '*' not in p:
if len(s) != len(p):
return False
else:
for i in range(len(s)):
if s[i] != p[i] and p[i] != '?':
return False
return True
lp = len(p)
p += '#'
isStar = False
pre_s = 0
pre_p = 0
index0 = index1 = 0
while index0 < len(s):
if s[index0] == p[index1] or p[index1] == '?':
index1 += 1
index0 += 1
else:
if p[index1] == '*':
while index1 < lp and p[index1] == '*':
index1 += 1
if index1 == lp:
return True
pre_s = index0
pre_p = index1
isStar = True
elif isStar:
pre_s += 1
index0 = pre_s
index1 = pre_p
else: return False
while index1 < lp and p[index1] == '*':
index1 += 1
return index1 == lp
| 1,270 | 1,270 | 0.355118 | 131 | 1,270 | 3.389313 | 0.274809 | 0.094595 | 0.087838 | 0.094595 | 0.135135 | 0.135135 | 0.135135 | 0.135135 | 0 | 0 | 0 | 0.050347 | 0.546457 | 1,270 | 1 | 1,270 | 1,270 | 0.720486 | 0.055118 | 0 | 0.297297 | 0 | 0 | 0.005848 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.027027 | false | 0 | 0 | 0 | 0.189189 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0b884ac9defe7c5ae34ac88da7c4f78d79100173 | 106 | py | Python | RiskQuantLib/Set/__init__.py | SyuyaMurakami/RiskQuantLib-Doc | 2503befc24c2e422e51f8b9f468c8d8439e11c65 | [
"MIT"
] | 1 | 2021-12-29T12:18:45.000Z | 2021-12-29T12:18:45.000Z | RiskQuantLib/Set/__init__.py | SyuyaMurakami/RiskQuantLib-Doc | 2503befc24c2e422e51f8b9f468c8d8439e11c65 | [
"MIT"
] | null | null | null | RiskQuantLib/Set/__init__.py | SyuyaMurakami/RiskQuantLib-Doc | 2503befc24c2e422e51f8b9f468c8d8439e11c65 | [
"MIT"
] | 1 | 2021-12-08T02:14:34.000Z | 2021-12-08T02:14:34.000Z | """
This is the automatically built module. Any source code will be replaced
for each building action.
""" | 26.5 | 72 | 0.764151 | 16 | 106 | 5.0625 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.160377 | 106 | 4 | 73 | 26.5 | 0.910112 | 0.924528 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0b976c0e65730ca8712b0ca38dd5b59042acb45d | 321 | py | Python | study/w3resource/exercises/python-basic/031 - 060/python-basic - 036.py | gustavomarquezinho/python | e36779aa5c4bfaf88c587f05db5bd447fd41e4a2 | [
"MIT"
] | null | null | null | study/w3resource/exercises/python-basic/031 - 060/python-basic - 036.py | gustavomarquezinho/python | e36779aa5c4bfaf88c587f05db5bd447fd41e4a2 | [
"MIT"
] | null | null | null | study/w3resource/exercises/python-basic/031 - 060/python-basic - 036.py | gustavomarquezinho/python | e36779aa5c4bfaf88c587f05db5bd447fd41e4a2 | [
"MIT"
] | null | null | null | # 036 - Write a Python program to add two objects if both objects are an integer type.
def sumInteger(pNum1, pNum2):
if (int(pNum1) != pNum1) or (int(pNum2) != pNum2):
return "Inputs must be integers"
return pNum1 + pNum2
print(sumInteger(10, 20))
print(sumInteger(10.5, 20))
print(sumInteger(10, 20.5)) | 32.1 | 86 | 0.685358 | 50 | 321 | 4.4 | 0.6 | 0.204545 | 0.231818 | 0.172727 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.096154 | 0.190031 | 321 | 10 | 87 | 32.1 | 0.75 | 0.261682 | 0 | 0 | 0 | 0 | 0.097458 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0 | 0 | 0 | 0.428571 | 0.428571 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
0b9820ad588a613ce4983a334d943c959a69db7b | 798 | py | Python | rsolve/hm/hm.py | thautwarm/python-csp | f1735de5445983532d32bf5508e971455de8e6a4 | [
"MIT"
] | 4 | 2019-09-27T10:53:03.000Z | 2019-09-28T08:25:43.000Z | rsolve/hm/hm.py | thautwarm/python-csp | f1735de5445983532d32bf5508e971455de8e6a4 | [
"MIT"
] | 1 | 2019-10-01T16:00:11.000Z | 2019-10-01T16:00:11.000Z | rsolve/hm/hm.py | thautwarm/python-csp | f1735de5445983532d32bf5508e971455de8e6a4 | [
"MIT"
] | null | null | null | from enum import Enum, auto as _auto
import abc
import typing as t
from dataclasses import dataclass
T = t.TypeVar('T', )
class HMT(t.Generic[T]):
pass
@dataclass(frozen=True, order=True)
class TNom(HMT[T]):
nom:T
pass
@dataclass(frozen=True, order=True)
class TVar(HMT[T]):
i:int
pass
@dataclass(frozen=True, order=True)
class TFresh(HMT[T]):
s:str
pass
@dataclass(frozen=True, order=True)
class TArrow(HMT[T]):
dom:HMT[T]
codom:HMT[T]
pass
@dataclass(frozen=True, order=True)
class TTup(HMT[T]):
elts:t.Tuple[HMT[T],...]
pass
@dataclass(frozen=True, order=True)
class TForall(HMT[T]):
vars:t.FrozenSet[str]
inst:HMT[T]
pass
@dataclass(frozen=True, order=True)
class TApp(HMT[T]):
fn:HMT[T]
arg:HMT[T]
pass
| 14 | 36 | 0.646617 | 127 | 798 | 4.055118 | 0.307087 | 0.108738 | 0.258252 | 0.312621 | 0.530097 | 0.530097 | 0.530097 | 0.386408 | 0.238835 | 0 | 0 | 0 | 0.199248 | 798 | 56 | 37 | 14.25 | 0.805947 | 0 | 0 | 0.394737 | 0 | 0 | 0.001253 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.210526 | 0.105263 | 0 | 0.578947 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 |
e7f4f64e3aae1a766136704fce7588f40eb5b3c3 | 56,696 | py | Python | unit1-database.py | Jawn-Blue/HTSK-Listening-Practice | ea5e93cc9aff6db0f64f7f6e56a849bde6ccbf46 | [
"MIT"
] | null | null | null | unit1-database.py | Jawn-Blue/HTSK-Listening-Practice | ea5e93cc9aff6db0f64f7f6e56a849bde6ccbf46 | [
"MIT"
] | 3 | 2021-01-27T23:44:07.000Z | 2021-01-31T00:46:04.000Z | unit1-database.py | Jawn-Blue/HTSK-Listening-Practice | ea5e93cc9aff6db0f64f7f6e56a849bde6ccbf46 | [
"MIT"
] | null | null | null | # All text/sentences in this file are copy-pasted from
# the example sentence dictionary included with the Unit 1
# audio files package.
import numpy as np
#class TextTranslation:
# def __init__(self, korean, english):
# self.korean = korean
# self.english = english
#
L7arr = np.array([["나는 집을 지어", "I build a house"], ["저는 집을 지었어요", "I built a house"], ["저는 웃었어요", "I laughed"], ["저는 저의 옷을 벗었어요", "I took off my clothes"], ["저는 저의 손을 씻었어요", "I washed my hands"], ["저는 걸어요", "I walk"], ["저는 걸었어요", "I walked"], ["돈을 받았어요", "I received money"], ["저는 저의 강아지를 묻었어요", "I buried my dog"], ["저는 문을 닫았어요", "I closed the door"], ["그것은 쉬워", "That thing is easy"], ["그것은 어려워요", "That is difficult"], ["그 여자는 귀여워요", "That girl is cute"], ["저는 저의 어머니를 도왔어요", "I helped my mother"], ["사과는 크다", "Apples are big"], ["나는 큰 사과를 좋아한다", "I like big apples"], ["저는 귀여운 여자를 좋아해요", "I like cute girls"], ["저는 쉬운 일을 했어요", "I did easy work"], ["나는 부드러운 손이 있어= I have soft hands"], ["저는 추운 날씨를 좋아해요", "I like cold weather"], ["그 여자는 아름다워요", "That girl is beautiful"], ["그 학교는 새로워요", "That school is new"], ["그것은 새로운 학교예요", "That (thing) is a new school"], ["이 방은 좁아요", "This room is narrow"], ["이 방은 넓어요", "This room is wide"], ["저는 공을 잡았어요", "I caught the ball"], ["저는 문을 잠갔어요", "I locked the door"], ["저는 바빠요", "I am busy"], ["그 여자는 예뻐요", "That girl is pretty"], ["그 집은 커요", "That house is big"], ["저는 아주 슬퍼요", "I am very sad"], ["저는 머리를 긁었어요", "I scratched my head"], ["저는 쥐를 들었어요", "I heard a mouse"], ["그것은 달라요", "That thing is different"], ["그 남자는 빨라요", "That man is fast"], ["저는 저의 누나를 불렀어요", "I called my sister"], ["저는 긴 거리를 건넜어요", "I crossed the long street"], ["저는 먼 병원에 갔어요", "I went to a far away hospital"], ["나는 케이크를 만든다", "I make a cake"], ["저는 집에 갑니다", "I go home 41.. 저는 밥을 먹습니다", "I eat rice"], ["그 여자는 예쁩니다", "That girl is beautiful"], ["이 방은 넓습니다", "This room is big wide"], ["저는 문을 엽니다", "I open the door"], ["저는 케이크를 만듭니다", "I make a cake"], ["그 병원은 멉니다", "That hospital is far"], ["그 여자의 머리카락은 깁니다", "That girl’s hair is long"]], dtype='object')
L8arr = np.array([["저는 병원을 지었어요", "I built a hospital"], ["저는 병원에 갔어요", "I went to the hospital"], ["저는 병원을 공원 옆에 지었어요", "I built a hospital beside the park"], ["저는 화요일에 가겠어요", "I will go on Tuesday"], ["저는 저녁에 공부했어요", "I studied in the evening"], ["저는 가을에 공원 옆에 병원을 지었어요", "I built a hospital beside the park in the fall"], ["여름에 저는 공부하겠어요", "I will study in the summer"], ["저는 한국에 오늘 도착했어요", "I arrived in Korea today"], ["저는 도서관에 어제 갔어요", "I went to the library yesterday"], ["저는 내일 한국어를 공부하겠어요", "I will study Korean tomorrow"], ["저는 저의 친구를 자주 만나요", "I meet my friend often"], ["저는 밥을 많이 먹었어요", "I ate a lot of food (rice)"], ["저는 집에 바로 갔어요", "I went home immediately"], ["저는 숙제를 빨리 했어요", "I did my homework quickly"], ["저는 많은 밥을 먹었어요", "I ate a lot of rice"], ["저는 밥을 많이 먹었어요", "I ate a lot of rice"], ["저는 조용하게 먹었어요", "I ate quietly"], ["저는 거리를 안전하게 건넜어요", "I crossed the street safely"], ["저는 행복하게 살았어요", "I lived happily"], ["저는 매우 빨리 달렸어요", "I ran really quickly"], ["저는 빨리 먹었어요", "I ate fast"], ["저는 바로 떠났어요", "I left immediately"], ["저는 저의 친구를 목요일에 자주 만나요", "I often meet my friend on Thursday"], ["저는 가끔 너무 많이 먹어요", "I eat too much sometimes"], ["그 여자는 안 예뻐요", "That girl isn’t pretty"], ["저는 생선을 안 좋아해요", "I don’t like fish"], ["저는 내일 학교에 안 가겠어요", "I’m not going to school tomorrow"], ["그 여자는 예쁘지 않아요", "That girl isn’t pretty"], ["저는 생선을 좋아하지 않아요", "I don’t like fish"], ["저는 내일 학교에 가지 않겠어요", "I’m not going to school tomorrow"], ["저는 공부를 안 했어요", "I didn’t study"], ["저는 실수를 안 했어요", "I didn’t make a mistake"], ["저는 여행을 안 했어요", "I didn’t travel"], ["저는 공부하지 않았어요", "I didn’t study"], ["저는 공부를 하지 않았어요", "I didn’t study"], ["저는 실수하지 않았어요", "I didn’t make a mistake"], ["저는 실수를 하지 않았어요", "I didn’t’t make a mistake"], ["저는 여행하지 않았어요", "I didn’t travel"], ["저는 여행을 하지 않았어요", "I didn’t travel"], ["저는 안 행복해요", "I am not happy"], ["저는 행복하지 않아요", "I’m not happy"], ["저는 밥을 천천히 먹었어요= I ate rice slowly"], ["저는 선생님이 아니에요", "I am not a teacher (You haven’t learned this conjugation yet)"], ["나는 너의 친구가 아니야", "I am not your friend (You haven’t learned this conjugation yet)"], ["저는 대학생이 아니에요", "I am not a university student (You haven’t learned this conjugation yet)"], ["저는 돈이 없어요", "I don’t have money"], ["저는 시간이 없어요", "I don’t have time"], ["우리는 차가 없어요", "We don’t have a car"], ["저의 친구는 지금 한국에 없어요", "My friend is not in Korea now"], ["사람이 없었어요", "There was no people"], ["저는 과일을 싫어해요", "I dislike fruit"], ["저는 과일을 좋아해요", "I like fruit"], ["저는 과일이 싫어요", "I dislike fruit"]], dtype='object')
L9arr = np.array([["나는 좋은 학생이야", "I am a good student"], ["그것은 책이야", "That thing is a book"], ["나는 선생님이야", "I am a teacher"], ["이것은 여권이야", "This is a passport"], ["그것은 사과야", "That thing is an apple"], ["나는 의사야", "I am a doctor"], ["야구는 좋은 스포츠야", "Baseball is a good sport"], ["나는 학생이 아니야", "I am not a student"], ["그것은 책이 아니야", "That thing is not a book"], ["그것은 사진이에요", "That thing is a picture"], ["저는 선생님이에요", "I am a teacher"], ["저는 좋은 학생이에요", "I am a good student"], ["이 사람은 저의 누나예요", "This (person) is my sister"], ["저는 의사예요", "I am a doctor"], ["저것은 사과예요", "That thing is an apple"], ["저는 학생이 아니에요", "I am not a student"], ["저는 의사입니다", "I am a doctor"], ["그 사람은 저의 형입니다", "That person is my brother"], ["저는 선생님입니다", "I am a teacher"], ["저는 좋은 학생입니다", "I am a good student"], ["이 고기는 돼지고기입니다", "This meat is pork"], ["저는 의사가 아닙니다", "I am not a doctor"], ["저는 학생이 아닙니다", "I am not a student"], ["그것은 저의 직업이 아닙니다", "That (thing) is not my job"], ["그것은 저의 여권이 아닙니다", "That (thing) is not my passport"], ["그 건물은 극장이 아닙니다", "That building is not a theater"], ["나는 바쁜 선생님이었어", "I was a busy teacher"], ["나는 학생이었어", "I was a student"], ["나는 선생님이었어", "I was a teacher"], ["나는 나쁜 애기였어", "I was a bad baby"], ["나는 나쁜 의사였어", "I was a bad doctor"], ["그것은 큰 비밀이었어요", "That was a big secret"], ["저는 선생님이었어요", "I was a teacher"], ["저는 의사였어요", "I was a doctor"], ["저는 나쁜 애기였어요", "I was a bad baby"], ["나는 선생님이었다", "I was a teacher"], ["나는 의사였다", "I was a doctor"], ["저는 선생님이었습니다", "I was a teacher"], ["저는 의사였습니다", "I was a doctor"], ["나는 학생이 아니었어", "I was not a student"]], dtype='object')
L10arr = np.array([["나는 학생이 아니었다", "I was not a student"], ["저는 학생이 아니었어요", "I was not a student"], ["저는 학생이 아니었습니다", "I was not a student"], ["저는 밥을 먹을 것이에요", "I will eat rice"], ["저는 밥을 먹을 거예요", "I will eat rice"], ["나는 내일 친구를 만날 것이야", "I will meet my friend tomorrow"], ["나는 내일 친구를 만날 거야", "I will meet my friend tomorrow"], ["저는 내일 학교에 갈 것입니다", "I will go to school tomorrow"], ["저는 영어를 공부할 거예요", "I will study English"], ["저는 문을 열 거예요", "I will open the door"], ["저는 곧 선생님이 될 것입니다", "I will become a teacher soon"], ["저는 곧 선생님일 거예요", "I will be a teacher soon"], ["나는 미래에 의사가 될 거야", "I will become a doctor in the future"], ["나는 미래에 의사일 거야", "I will be a doctor in the future"], ["한국이 곧 좋은 나라가 될 것이다", "Korea will become a good country soon"], ["한국이 곧 좋은 나라일 것이다", "Korea will be a good country soon"], ["이 장소는 공원이 될 것이다", "This place will become a park"], ["이 장소는 공원일 것이다", "This place will be a park"], ["그 사람이 의사일 거예요", "That person is probably a doctor"], ["그것은 여권일 거예요", "That thing is probably a passport"], ["문제는 돈일 거예요", "The problem is probably money"], ["그 사람이 의사가 아닐 거야", "That person is probably not a doctor"], ["그것은 여권이 아닐 거야", "That thing is probably not a passport"], ["문제는 돈이 아닐 거야", "The problem is probably not money"]], dtype='object')
L11arr = np.array([["저는 10분 동안 걸었어요", "I walked for 10 minutes"], ["저는 30분 동안 공부했어요", "I studied for 30 minutes"], ["저는 10분 동안 걸었어요", "I walked for (a period of) 10 minutes"], ["저는 30분 동안 공부했어요", "I studied for (a period of) 30 minutes"], ["저는 이틀 동안 안 잤어요", "I didn’t sleep for two days"], ["저는 세 시간 동안 잤어요", "I slept for 3 hours"], ["저는 한 시간 동안 달렸어요", "I ran for one hour"], ["저는 여덟 시간 동안 운전했어요", "I drove for eight hours"], ["저는 어제 한 시간 동안 야구를 했어요", "I played baseball for an hour yesterday"], ["저는 어제 두 시간 동안 TV를 봤어요", "I watched TV for two hours yesterday"], ["저는 2초 동안 달렸어요", "I ran for 2 seconds"], ["저는 그 사람을 10초 동안 만났어요", "I met that person for 10 seconds"], ["1분은 60초입니다", "One minute is sixty seconds"], ["저는 지난 주에 영화를 봤어요", "I saw a movie last week"], ["저는 지난 주에 캐나다에 갔어요", "I went to Canada last week"], ["저는 지난 수업을 안 들었어요", "I didn’t go to/attend the last class"], ["저는 그것을 지난 시간에 배웠어요", "I learned that (thing) last time"], ["저는 그것을 지난 번에 배웠어요", "I learned that (thing) last time"], ["우리가 지난 번에 계획이 없었어요", "We didn’t have plans last time"], ["우리는 지난 번에 돼지고기를 먹었어요", "We ate pork last time"], ["저는 다음 주에 영화를 볼 거예요", "I will see a movie next week"], ["저는 다음 주에 캐나다에 갈 거예요", "I will go to Canada next week"], ["우리는 다음 번에 학교에 갈 거예요", "We will go to school next time"], ["우리는 다음 시간에 학교에 갈 거예요", "We will go to school next time"], ["나는 너를 다음 번에 방문할 거야", "I will visit you next time"], ["나는 너를 다음 시간에 방문할 거야", "I will visit you next time"], ["나는 3일 동안 공부했어", "I studied for 3 days"], ["나는 3일 동안 학교에 안 갔어", "I didn’t go to school for 3 days"], ["저는 5일 동안 계획이 없을 거예요", "I won’t have plans for 5 days"], ["우리는 6일 동안 만나지 않았어요", "We didn’t meet for 6 days"], ["저는 하루 동안 여행했어요", "I traveled for 1 day"], ["저는 사흘 동안 밥을 안 먹었어요", "I didn’t eat rice for 3 days"], ["저는 삼일 동안 밥을 안 먹었어요", "I didn’t eat rice for 3 days"], ["우리는 이틀 동안 미국에 있었어요", "We were in America for two days"], ["우리는 10일 동안 한국에 있을 거예요", "We will be in Korea for ten days"], ["나는 3일에 수업을 들었어", "I went to class on the 3rd"], ["나는 3일 동안 수업을 들었어", "I went to class for three days"], ["저는 8월 15일에 도착할 거예요", "I will arrive on August 15th"], ["저는 이 여권을 1월 2일에 받았어요", "I received my passport on January 2nd"], ["저는 그 날에 갔어요", "I went on that day"], ["저는 그 날에 계획이 있어요", "I have plans on that day"], ["저는 그 날에 선생님이 되었어요", "I became a teacher on that day"], ["우리는 그 날에 시작할 거예요", "We will start on that day"], ["우리는 두 번째 날에 서울에 갔어요", "We went to Seoul on the second day"], ["우리는 둘째 날에 서울에 갔어요", "We went to Seoul on the second day"], ["우리는 세 번째 날에 안 만났어요", "We didn’t meet on the third day"], ["우리는 셋째 날에 안 만났어요", "We didn’t meet on the third day"], ["저는 네 번째 날에 계획이 없어요", "I have no plans on the fourth day"], ["저는 넷째 날에 계획이 없어요", "I have no plans on the fourth day"], ["저는 첫날에 명동에 갔어요", "I went to 명동 on the first day"], ["저는 첫날에 그 여자를 만났어요", "I met that girl on the first day"], ["저는 다음 주에 미국에 갈 거예요", "I will go to the US next week"], ["지난 주에 저는 계획이 많았어요", "I had a lot of plans last week"], ["저는 2주 동안 한식을 안 먹었어요", "I didn’t eat Korean food for 2 weeks"], ["저는 4주 동안 여자친구를 안 만났어요", "I didn’t meet my girlfriend for 4 weeks"], ["저는 2주일 동안 한식을 안 먹었어요", "I didn’t eat Korean food for two weeks"], ["저는 4주일 동안 여자친구를 안 만났어요", "I didn’t meet my girlfriend for four weeks"], ["저는 두 달 동안 한국어 수업을 들었어요", "I took a Korean class for 2 months"], ["저는 2개월 동안 한국어 수업을 들었어요", "I took a Korean class for 2 months"], ["저는 3년 동안 형을 안 만났어요", "I didn’t meet my brother for 3 years"], ["저는 10년 동안 한국어를 공부했어요", "I studied Korean for 10 years"], ["나는 내년에 한국에 갈 거야", "I will go to Korea next year"], ["그 사람은 작년에 죽었어요", "That person died last year"], ["저는 이번 주에 계획이 없어요", "I have no plans this week"], ["저의 어머니는 올해 한국에 올 것입니다", "My mom will come to Korea this year"], ["우리는 이번 시간에 많이 배웠어", "We learned a lot this time"], ["나는 너를 이번에 안 만날 거야", "I won’t meet you this time"], ["저는 박물관에 다음 번에 갈 거예요", "I will go to the museum next time"], ["저는 박물관에 지난 번에 갔어요", "I went to the museum last time"], ["저는 이 약을 하루에 두 번 먹어요", "I eat (take) this medicine twice per day"], ["저는 그 친구를 1주일에 한 번 만나요", "I meet that friend once per week"], ["저는 여기에 한 달에 세 번 와요", "I come here three times per month"], ["저는 1년에 두 번 미국에 가요", "I go to America twice per year"]], dtype='object')
L12arr = np.array([["아침식사를 안 먹었어요", "I didn’t eat breakfast"], ["나는 사과를 샀어", "I bought apples"], ["나는 사과 한 개를 샀어", "I bought one apple"], ["나는 사과 몇 개를 샀어", "I bought SOME apples"], ["나는 몇 개의 펜을 샀어", "I bought some pens"], ["나는 몇 명의 사람을 만났어", "I met some people"], ["나는 학교에 몇 번 갔어", "I went to school a few times"], ["의사들은 돈이 많아", "Doctors have a lot of money"], ["선생님은 내일 학생들을 만날 거야", "The teacher will meet the students tomorrow"], ["배우들은 그들의 영화를 보통 좋아하지 않아", "Actors usually don’t like their movies"], ["나는 물만 마셔", "I only drink water"], ["나만 그 여자를 좋아해", "Only I like that girl"], ["나는 그 여자만 좋아해", "I only like that girl"], ["나만 사과를 샀어", "Only I bought apples"], ["나는 사과만 샀어", "I only bought apples"], ["나는 사과 한 개만 샀어", "I only bought 1 apple"], ["저는 차 두 대만 있어요", "I only have two cars"], ["저는 친구 한 명만 만났어요", "I only met one friend"], ["저는 공부만 했어요", "I only studied"], ["저는 어제 일만 했어요", "Yesterday, I only worked"], ["우리는 학교에만 갔어요", "We only went to school"], ["학생들은 교실 안에만 있어요", "The students are only in their classrooms"], ["저는 밤에만 운동해요", "I exercise only at night"], ["저는 커피를 낮에만 마셔요", "I drink coffee only during the day"], ["저는 그 여자를 그때만 사랑했어요", "I loved her only at that time"], ["저는 학교에서 공부할 거예요", "I will study at school"], ["저는 저의 친구를 병원에서 봤어요", "I saw my friend at the hospital"], ["저는 남편을 공원에서 만날 거예요", "I will meet my husband at the park"], ["저는 한국어를 한국에서 배웠어요", "I learned Korean in Korea"], ["저는 방에서 탁자에 병을 놓았어요", "I placed the bottle on the table in the room"], ["과일은 비싸요", "Fruit is expensive"], ["과일은 한국에서 비싸요", "Fruit is expensive in Korea"], ["저는 학교에서 추웠어요", "I was cold at school"], ["고등학교는 한국에서 어려워요", "High school is difficult in Korea"], ["녹차는 한국에서 유명해요", "Green Tea is famous in Korea"], ["저는 집에 있어요", "I’m at home"], ["저는 차 안에 있어요", "I’m in the car"], ["저는 한국에서 갈 거예요", "I will go from Korea"], ["다음 버스는 저 정류장에서 출발할 거예요", "The next bus will depart from that station"], ["저는 서울역에서 내릴 거예요", "I will get off at (from) Seoul station"], ["학생은 교실에서 나왔어요", "the student came out of the classroom"], ["저는 캐나다에서 왔어요", "I come from Canada"], ["3시까지 기다릴 거예요", "I will wait until 3:00"], ["그 여자를 지금까지 좋아했어요", "I liked that girl until now"], ["저는 그 회사에서 5월까지 일할 거예요", "I will work at that company until May"], ["저는 그때까지 김치를 먹지 않았어요", "I hadn’t eaten Kimchi until that time"], ["저는 오늘 이 책을 여기까지 읽었어요", "Today, I read up to here in this book"], ["저는 한강까지 달렸어요", "I ran until (I reached) the Han River"], ["나는 인천에서 서울까지 갈 거야", "I will depart from Incheon and go to (until) Seoul"], ["나는 인천부터 서울까지 갈 거야", "I will go from Incheon to Seoul"], ["다음 버스는 저 정류장에서 출발할 거예요", "The next bus will leave from that stop"], ["저는 어제부터 아팠어요", "I have been sick since (from) yesterday"], ["저는 내일부터 한국어를 공부할 거예요", "I’m going to study Korean from tomorrow"], ["내년부터 우리는 서울에서 살 거예요", "From next year, we will be living in Seoul"], ["저는 3시부터 학교에 있을 거예요", "I will be at school from 300"], ["저는 작년부터 한국어를 배웠어요", "I have been learning Korean since last year"], ["저는 아침부터 밤까지 공부만 했어요", "From morning to night, I only studied"], ["나는 캐나다에 1일부터 8일까지 있을 거야", "I will be in Canada from the 1st to the 8th"], ["그들은 저를 처음부터 싫어했어요", "They didn’t like me from the start"], ["우리는 그 일을 처음부터 시작할 거예요", "We will start that job/task from the beginning"], ["저는 그 상황을 처음부터 끝까지 몰랐어요", "I didn’t know that situation from start to finish"], ["저는 그것을 처음부터 끝까지 복습했어요", "I reviewed that from start to finish"], ["저는 그 책을 처음부터 끝까지 읽었어요", "I read that book from start to finish"], ["나는 우리 집을 나무로 지었어", "I built our house out of wood"], ["배로 제주에 갈 거야", "I will go to Je-ju by boat"], ["저는 그것을 손으로 만들었어요", "I built that with my hands"], ["저는 그 문장을 한국어로 말했어요", "I said that sentence (using) in Korean"], ["저는 그것을 영어로 할 거예요", "I will say that (using) in English"], ["저는 아침식사로 밥을 먹었어요", "I ate rice for breakfast"], ["저는 보통 점심식사로 과일만 먹었어요", "I usually only ate fruit for lunch"], ["저는 그것을 두 번째로 했어요", "I did that second"], ["저는 학교에 두 번째로 왔어요", "I came to school second"], ["저는 그것을 첫 번째로 할 거예요", "I will go (do it) first"], ["저는 집으로 갈 거예요", "I will go in the direction of home"], ["저는 집에 갈 거예요", "I will go home"], ["저의 친구는 저 쪽으로 갔어요", "My friend went that way"], ["학생들은 교실 쪽으로 걸어요", "Students walk towards their class"], ["저는 집 안 쪽으로 달렸어요", "I ran inside the house"], ["저는 집 안에서 달렸어요", "I ran inside the house"]], dtype='object')
L13arr = np.array([["우리는 밥과 빵을 팔아요", "We sell rice and bread"], ["나는 사과와 바나나를 샀어", "I bought apples and bananas"], ["나는 인천이랑 서울에 갈 거야", "I will go to Seoul and Incheon"], ["형하고 아버지는 영화를 봤어", "My brother and dad saw a movie"], ["저는 약과 녹차만 샀어요", "I only bought medicine and green tea"], ["나는 사과와 바나나를 샀어", "I bought apples and bananas"], ["나는 친구와 갔어", "I went with my friend"], ["저는 친구와 집에 갔어요", "I went home with my friend"], ["나는 아버지랑 공원에 갈 거야", "I will go to the park with my dad"], ["선생님은 학생들과 박물관에 갔다", "The teacher went to the museum with the students"], ["요즘에 사람들이 친구들이랑 매운 음식을 먹지 않아요", "These days, people don’t eat spicy food with their friends"], ["저는 밥을 친구랑 저의 어머니랑 먹었어요", "I ate (rice) with my mom and my friend"], ["우리는 빵을 같이 먹었어요", "We ate bread together"], ["우리는 빵을 함께 먹었어요", "We ate bread together"], ["우리는 집에 같이 들어갔어요", "We went into the house together"], ["우리는 집에 함께 들어갔어요", "We went into the house together"], ["우리는 음악을 같이 들었어요", "We listened to music together"], ["우리는 음악을 함께 들었어요", "We listened to music together"], ["저는 빵을 친구랑 같이 먹었어요", "I ate bread with a friend (together)"], ["저는 빵을 친구와 함께 먹었어요", "I ate bread with a friend (together)"], ["저는 빵을 친구랑 먹었어요", "I ate bread with a friend"], ["저는 빵을 친구와 먹었어요", "I ate bread with a friend"], ["저는 녹차를 엄마랑 같이 마셨어요", "I drank green tea with my mom"], ["저는 엄마랑 유명한 영화를 같이 봤어요", "I watched a famous movie with my mom"], ["저는 선생님과 함께 공부했어요", "I studied with my teacher"], ["저는 여자 친구와 함께 영화를 봤어요", "I watched a movie with my girlfriend"], ["나는 친구랑 같이 있어", "I’m with my friend"], ["저는 친구와 집에 함께 있어요", "I’m with a friend at home"], ["아버지는 아들에게 돈을 준다", "The father gives money to his son"], ["나는 학생들한테 한국어를 가르쳤어", "I taught Korean to the students"], ["저는 부장님께 그 사실을 말할 거예요", "I will tell that (fact) to my boss"], ["나는 책을 교장선생님께 줬어", "I gave the principal a book"], ["나는 나의 여자친구에게서 편지를 받았어", "I received a letter from my girlfriend"], ["저는 교감선생님에게서 한국어를 배웠어요", "I learned Korean from my vice principal"], ["저는 그것을 친구한테서 들었어요", "I heard that from my friend"], ["나는 나의 여자친구로부터 편지를 받았어", "I received a letter from my girlfriend"], ["저는 교감선생님으로부터 한국어를 배웠어요", "I learned Korean from my vice principal"], ["저는 그것을 친구로부터 들었어요", "I heard that from my friend"], ["저는 친구들로부터 사랑을 많이 받았어요", "I received a lot of love from friends"], ["아버지로부터 선물이 왔어요", "A present came from my father"], ["나는 돈을 정부로부터 받았어", "I received money from the government"], ["이것을 하늘로부터 받았어요", "I received this from the sky (heaven)"], ["나는 나의 여자 친구를 위해서 꽃을 샀어", "I bought flowers for my girlfriend"], ["나는 부장님을 위해 이것을 썼어", "I wrote this for my boss"], ["저는 친구를 위해 빵을 만들었어요", "I made bread for my friend"], ["아버지를 위해 시원한 물을 준비했어요", "I prepared cool water for my father"], ["저는 회사를 위해 열심히 일할 거예요", "I will work hard for the company"], ["나는 너에 대해 생각했어", "I thought about you"], ["나는 나의 아버지에 대해 말했어", "I spoke about my father"], ["나는 그것에 대해 책을 쓸 거야", "I will write a book about it"], ["그 회계사는 정부에 대해 나쁜 말을 했어요", "That accountant said bad things about the government"]], dtype='object')
L14arr = np.array([["이 값은 세금을 포함해요", "This price includes tax"], ["세금은 포함돼요", "The tax is included"], ["저는 점심을 준비했어요", "I prepared (the) lunch"], ["점심이 준비되었어요", "(The) lunch was prepared"], ["회사는 기계를 대체했어", "The company replaced the machine"], ["기계는 대체되었어", "The machine was replaced"], ["그것은 이해되었어", "It was understood"], ["그것은 학생들에게 이해되었어", "It was understood by the students"], ["집은 청소되었어", "The house was cleaned"], ["집은 아버지에게 청소되었어", "The house was cleaned by my dad"], ["학생들은 그것을 이해했어요", "The students understood that"], ["아버지는 집을 청소했어요", "My dad cleaned the house"], ["저는 집을 청소기로 청소했어요", "I cleaned the house with a vacuum cleaner"], ["집은 청소기로 청소되었어", "The house was cleaned by a vacuum cleaner"], ["세금은 포함돼요", "The tax is included"], ["세금은 값에 포함된다", "The tax is included in the price"], ["저는 저의 형을 존경해요", "I respect my brother"], ["저의 형은 존경 받아요", "My brother is respected"], ["교장선생님은 선생님들에게 존경 받아요", "The principal is respected by the teachers"], ["나는 너의 말에 감동받았어", "I was impressed with what you said"], ["밥은 학교에 의해 제공된다", "Food is provided by the school"], ["밥은 학교에 의해 제공되었다", "Food was provided by the school"], ["문은 바람에 의해 닫혔어요", "The door was closed by the wind"], ["저는 컴퓨터를 켰어요", "I turned the computer on"], ["컴퓨터가 켜져 있어요", "The computer is (in the state of) on"], ["저는 TV를 껐어요", "I turned the TV off"], ["TV가 꺼져 있어요", "The TV is (in the state of) off"], ["저는 문을 잠갔어요", "I locked the door"], ["문이 잠겨 있어요", "The door is (in the state of) locked"], ["저는 문을 닫았어요", "I closed the door"], ["문이 닫혔어요", "The door was closed"], ["문이 바람에 닫혔어요", "The door was closed by the wind"], ["문이 닫혀 있었어요", "The door was closed"], ["저는 문을 닫아요", "I close the door"], ["문이 닫혀요", "The door closes"], ["문이 닫혀 있어요", "The door is closed"], ["문이 닫힐 거예요", "The door will close"], ["문이 닫혀 있을 거예요", "The door will be closed"], ["나는 친구를 속였어", "I tricked my friend"], ["나는 친구에게 속았어", "I was tricked by my friend"], ["펜이 탁자에 놓여 있었어요", "The pen was laying on the table"], ["숙제는 끝났어요", "My homework is finished"], ["컴퓨터는 고장 났어요", "The computer is broken"], ["저는 숙제를 끝냈어요", "I finished my homework"], ["저는 컴퓨터를 고장 냈어요", "I broke the computer"], ["아! 그것이 기억났다!", "Ah! I remember that!"], ["좋은 생각이 났어요!", "I have a good idea"], ["그 가방에서 냄새가 났어요", "That bag is smelly"], ["그 방에서 냄새가 났어요", "That room is smelly"], ["큰 일 났어요!", "Something bad just happened!"], ["땀이 났어요", "I’m sweating"], ["땀이 나요", "Sweat is literally currently coming out of my body"], ["저는 그것이 기억 났어요", "I remembered that"], ["저는 그것이 기억 나요", "That memory is literally currently just coming to my mind"], ["나는 그때 기억이 안 났어", "I didn’t remember (that) at that time"], ["나는 그것이 기억 안 나", "I don’t remember that"], ["기회가 주어졌어요", "I was given a chance"], ["그 집은 한국에서 지어졌어요", "That house was built in Korea"]], dtype='object')
L15arr = np.array([["저는 좋은 김치를 먹었어요", "I ate good kimchi"], ["김치는 좋아요", "Kimchi is good"], ["저는 김치를 좋아해요", "I like Kimchi"], ["김치는 싫어요", "Kimchi is bad/not good"], ["저는 김치를 싫어해요", "I don’t like Kimchi"], ["김치가 좋아요", "I like Kimchi"], ["김치가 싫어요", "I don’t like Kimchi"], ["학교가 좋아요", "I like school"], ["학교가 싫어요", "I don’t like school"], ["맥주가 좋아요", "I like beer"], ["맥주가 싫어요", "I don’t like beer"], ["저는 김치를 먹었어요", "I ate kimchi"], ["저는 김치가 좋아요", "I like kimchi"], ["저는 한국 음식이 그리워요", "I miss Korean food"], ["나는 네가 자랑스러워", "I am proud of you"], ["나는 그 사람이 싫어", "I don’t like that person"], ["저는 한국이 좋아요", "I like Korea"], ["저는 그것이 기억나요!", "I remember that!"], ["저는 땀이 나요!", "I’m sweating!"], ["저는 화가 났어요", "I was angry"], ["나는 동아리에 들었어", "I joined a club"], ["잠이 들었다", "I fell asleep"], ["저는 그 그림이 마음에 들어요", "I like that picture"], ["저는 손을 들었어요", "I raised my hand"], ["저는 가방을 들었어요", "I carried the bag"], ["아버지는 은행에 들어갔어요", "My dad went into the bank"], ["남자는 방에 들어왔어요", "A man came into the room"], ["저는 집에서 나갔어요", "I went out of home (I left home)"], ["학생은 학교에서 나왔어요", "The student came out of school"], ["나는 나의 숙제를 가져왔어", "I brought my homework"], ["그 학생은 숙제를 가져오지 않았어", "That student didn’t bring his homework"], ["저는 저의 모자를 가져갈 거예요", "I will bring my hat"], ["저는 9월 1일에 캐나다에 돌아갈 거예요", "I will go back to Canada on September 1st"], ["저는 친구에게 책을 돌려줬어요", "I gave my friend back his book"], ["그것은 비슷해요", "That is similar"], ["우리는 매우 달라요", "We are so different"], ["우리는 똑같아요", "We are exactly the same"], ["저는 친구와 비슷해요", "I am similar to my friend"], ["저는 결과가 만족스러웠어요", "I was satisfied with the results"], ["저는 음식이 만족스러웠어요", "I was satisfied with the food"], ["저는 만족스러웠어요", "I was satisfied"], ["저는 그 여자를 사랑해요", "I love that girl"], ["그 여자는 사랑스러워요", "That girl is lovely"], ["저는 저의 한국어 실력을 자랑했어요", "I showed off my Korean skills"], ["저는 저의 딸이 아주 자랑스러워요", "I am very proud of my daughter"], ["저는 학생들이 자랑스러워요", "I am proud of the students"], ["우리 딸은 사랑스러운 여자예요", "Our daughter is a lovely girl"], ["그는 한국어를 자연스럽게 말해요", "He speaks Korean naturally"], ["저는 그를 사랑스럽게 봤어요", "I looked at him lovingly"], ["그는 실망스럽게 행동했어요", "He acted disappointingly (in a disappointing way)"], ["저는 일을 만족스럽게 끝냈어요", "I finished the job satisfactorily"]], dtype='object')
L16arr = np.array([["한국은 지난 50년 동안 문화적으로 많이 변했어요", "Korea has changed a lot culturally during the past 50 years"], ["그것은 경제적으로 가능하지 않아요", "That isn’t economically possible"], ["한국과 미국은 역사적으로 좋은 관계가 있다", "Historically, Korea and the US have had a good relationship"], ["그들은 그 문제를 과학적으로 풀었다", "They solved that problem scientifically"], ["저는 자주 옷을 충동적으로 사요", "I often buy clothes impulsively"], ["미국은 대통령을 민주적으로 선출해요", "America elects its president democratically"], ["캐나다와 미국은 문화적인 차이가 있다", "Canada and the US have a cultural difference"], ["미국은 경제적인 결정을 했어요", "The US made an economical decision"], ["저 학교는 역사적인 건물이에요", "That school is a historical building"], ["이것은 과학적인 문제예요", "This is a scientific problem"], ["저는 너무 충동적이에요", "I’m too impulsive 12 미국은 민주적인 나라예요", "The US is a democratic nation"], ["북한에는 민주적 정부가 없습니다", "There is not a democratic government in North Korea"], ["경제적 문제가 있다", "There is a financial problem"], ["경제적인 문제가 있다", "There is a financial problem"], ["캐나다와 미국은 문화적 차이가 있다", "Canada and the US have a cultural difference"], ["나는 개인적 문제로 회사를 그만두었다", "I quit the company due to personal reasons"], ["나는 개인적인 문제로 회사를 그만두었다", "I quit the company due to personal reasons"], ["이 건물은 역사적 건물이다", "This building is a historical building"], ["이 건물은 역사적인 건물이다", "This building is a historical building"], ["그 여자가 아주 사랑스러워요", "That girl is something “with the properties of love”"], ["그 여자의 머리 색깔은 자연스러워", "That girl’s hair color has “the properties of nature”"], ["저는 실망했어요", "I was disappointed"], ["우리 아버지는 어제 실망했어요", "Our dad was disappointed yesterday"], ["저는 친구에게 실망했어요", "I was disappointed in my friend"], ["우리 아버지는 저에게 실망했어요", "Our dad was disappointed in me yesterday"], ["저는 영화에 실망했어요", "I was disappointed in the movie"], ["우리 아버지는 식당에 실망했어요", "Our dad was disappointed in the restaurant"], ["결과는 조금 실망스러웠어요", "The result was a little bit disappointing"], ["그 영화는 조금 실망스러웠어요", "The movie was a little bit disappointing"], ["저는 실망스러웠어요", "I am disappointed"], ["저는 친구가 실망스러워요", "I am disappointed in my friend"], ["저는 학생들이 실망스러웠어요", "I was disappointed in the students"], ["저는 그 영화가 실망스러웠어요", "I was disappointed in the movie"], ["저는 만족해요", "I am satisfied"], ["그는 만족해요", "He is satisfied"], ["결과는 만족스러웠어요", "The results were satisfactory"], ["저는 결과가 만족스러웠어요", "I was satisfied with the results"], ["저는 음식이 만족스러웠어요", "I was satisfied with the food"], ["저는 만족스러웠어요", "I was satisfied"], ["저는 그 여자를 사랑해요", "I love that girl"], ["그 여자는 사랑스러워요", "That girl is lovely"], ["저는 저의 한국어 실력을 자랑했어요", "I showed off my Korean skills"], ["저는 저의 딸이 아주 자랑스러워요", "I am very proud of my daughter"], ["저는 학생들이 자랑스러워요", "I am proud of the students"], ["우리 딸은 사랑스러운 여자예요", "Our daughter is a lovely girl"], ["그는 한국어를 자연스럽게 말해요", "He speaks Korean naturally"], ["저는 그를 사랑스럽게 봤어요", "I looked at him lovingly"], ["그는 실망스럽게 행동했어요", "He acted disappointingly (in a disappointing way)"], ["저는 일을 만족스럽게 끝냈어요", "I finished the job satisfactorily"]], dtype='object')
L17arr = np.array([["저는 밥을 먹고 갈 거예요", "I will eat then go"], ["저는 자고 한국어를 공부했어요", "I slept then studied Korean"], ["저는 책을 읽고 바로 잤어요", "I read a book then slept immediately"], ["저는 10분 동안 쉬고 갈 거예요", "I will rest for 10 minutes then go"], ["애기가 1분 동안 울고 배를 먹었어요", "The baby cried for 1 minute and then ate a pear"], ["저는 당근을 칼로 자르고 냉장고에 넣었어요", "I cut the carrots with the knife then put (them) in the fridge"], ["우리는 서울에서 2일 동안 머무르고 부산에 갈 거예요", "We will stay in Seoul for two days, then go to Busan"], ["저는 숙제를 끝내고 나서 집으로 갈 거예요", "I will finish my homework and then go home"], ["저는 친구를 만나고 나서 은행에 갈 거예요", "I will meet a friend and then go to the bank"], ["저는 과일도 좋아하고 야채도 좋아해요", "I like fruit, and I like vegetables too"], ["저는 과일과 야채도 좋아해요", "I like fruit and vegetables too"], ["그 사람은 착하고 똑똑해요", "That person is kind and smart"], ["저의 여자 친구는 귀엽고 예뻐요", "My girlfriend is cute and pretty"], ["오늘 고객이 많고 분위기가 좋아요", "Today there are a lot of customers, and the atmosphere is good"], ["저는 열심히 공부했고 의사가 되었어요", "I studied hard and (then) became a doctor"], ["저는 영어 문법을 열심히 공부했고 시험을 잘 봤어요", "I studied English grammar hard and then did well on the test"], ["저는 방학 동안 영어 문법을 많이 공부했고 영어 신문도 많이 읽었어요", "During vacation I studied a lot of English grammar, and I also read a lot of English newspapers"], ["이 산은 높고 저 산은 낮아요", "This mountain is high, but that mountain is low"], ["문법은 어렵고 단어는 쉬워요", "Grammar is hard, but words are easy"], ["이 사람은 부자이고 저 사람은 가난해요", "That person is rich, but that person is poor"], ["이분은 저의 아버지이고 이분은 저의 어머니입니다", "This person is my father, and this person is my mother"], ["저는 당근을 칼로 잘라서 냉장고에 넣었어요", "I cut carrots with a knife and then put them into the fridge"], ["저는 학교에 가서 공부할 거예요", "I will go to school and then study"], ["우리는 집에 와서 바로 잤어요", "We came home and went to sleep immediately"], ["우리는 맛있는 고기를 골라서 같이 먹었어요", "We chose delicious meat then ate together"], ["문을 열어서 밖으로 나갔어요", "I opened the door and then went outside"], ["혜원도 오고.. 슬기도 오고… 승하도 오고… 지혜도 오고…", "혜원 came, 슬기 came, 승하 came, 지혜 came"], ["저는 누워서 책을 읽었어요", "I lied down and read a book"], ["나는 앉아서 쉴 거야", "I’m going to sit down and relax"], ["저는 줄에 서서 순서를 기다렸어요", "I stood in line and waited for my turn"], ["저는 한국어를 배우고 싶어요", "I want to study Korean"], ["저는 캐나다에 가고 싶어요", "I want to go to Canada"], ["저는 여자친구를 위해 편지를 쓰고 싶어요", "I want to write a letter for my girlfriend"], ["저는 새로운 차를 사고 싶어요", "I want to buy a new car"], ["저는 내일 쉬고 싶어요", "I want to rest tomorrow"], ["저는 저의 친구를 파티에 초대하고 싶어요", "I want to invite my friend to the party"], ["저는 방학 동안 책 두 권을 읽고 싶어요", "I want to read two books during vacation"], ["저는 선생님이 되고 싶어요", "I want to become a teacher"], ["저는 선생님이 되고 싶었어요", "I wanted to be a teacher"], ["그 여자는 나랑 결혼하고 싶었어", "That girl wanted to marry me"], ["저는 친구를 보고 싶어요", "I miss my friend"], ["저는 그 책을 원해요", "I want that book"], ["저는 그 책을 읽고 싶어요", "I want to read that book"], ["저는 술을 안 마시고 싶어요", "I don’t want to drink alcohol"], ["저는 울고 싶지 않아요", "I don’t want to cry"], ["나는 너를 파티에 초대하고 싶지 않아", "I don’t want to invite you to the party"], ["저는 부자가 되고 싶지 않아요", "I don’t want to become a rich man"], ["방학 동안 저는 학교에 있고 싶지 않아요", "I don’t want to be at school during vacation"]], dtype='object')
L18arr = np.array([["나는 음악을 듣고 있어", "I am listening to music"], ["저의 아버지는 자고 있어요", "My father is sleeping"], ["여자들은 지금 영화를 보고 있어요", "The girls are watching a movie now"], ["저는 사과를 자르고 있어요", "I am cutting the apple"], ["저는 청구서를 지금 내고 있어요", "I am paying the bill now"], ["저는 밥을 먹고 있었어요", "I was eating"], ["학생들은 수업 시간 동안 자고 있었어요", "The students were sleeping during class"], ["학생들은 자고 있었어요", "The students were sleeping"], ["저는 밥을 먹었어요", "I ate"], ["학생들은 잤어요", "The students slept"], ["저는 백화점에서 쇼핑하고 있었어요", "I was shopping at the department store"], ["대학생은 책상에서 공부를 하고 있었어요", "The university student was studying at his desk"], ["나는 다음 주에 시험 공부를 하고 있을 거야", "Next week, I will be studying for an exam"], ["저는 한국에서 살고 있어요", "I live in Korea"], ["저는 한국에서 살아요", "I live in Korea"], ["저는 한국에 살고 있어요", "I live in Korea"], ["저는 한국에 살아요", "I live in Korea"], ["나는 그것을 알고 있어", "I know that"], ["나는 그것을 알아", "I know that"], ["집에 빨리 와!", "Come home quickly 알았어", "Okay"], ["우리는 내일 6시에 출발 할 거야", "We will leave at 600 tomorrow 알았어", "Okay"], ["이 일을 내일까지 해야 합니다", "You have to finish this work by tomorrow 네, 알겠습니다", "Yes, okay"], ["나는 펜을 가지고 있어", "I have a pen"], ["나는 여자 친구가 있어", "I have a girlfriend"], ["나는 앉아 있어", "I’m sitting"], ["나는 학교 옆에 서 있어", "I’m standing next to the school"], ["나는 침대에 누워 있어", "I’m lying in bed"], ["컴퓨터가 켜져 있어요", "The computer is (in the state of) on"], ["TV가 꺼져 있어요", "The TV is (in the state of) off"], ["문이 잠겨 있어요", "The door is (in the state of) locked"], ["그 돼지는 살아 있어요", "That pig is living (alive)"], ["그 소는 살아 있지 않아요", "That cow isn’t living (alive)"], ["날씨가 매일 밤에 추워져요", "The weather gets cold every night"], ["날씨는 주말에 추워졌어", "The weather got cold over the weekend"], ["기름 값은 비싸졌어요", "The price of oil got expensive"], ["그 사람은 밥을 먹고 나서 행복해졌어요", "That person ate, and then became happy"], ["우리 강아지는 지난 1년 동안 많이 커졌어요", "Our puppy got a lot bigger in the last year"], ["저는 군대에 갔고 똑똑해졌어요", "I went to the army and got smart"], ["대학교 수업은 내년에 어려워질 거예요", "University classes will get difficult next year"], ["저의 여자 친구는 예뻐지고 있어요", "My girlfriend is getting pretty"], ["집 값은 비싸지고 있어", "House prices are getting expensive"], ["피부가 부드러워지고 있어요", "My skin is getting soft"], ["나는 행복해지고 싶어", "I want to become happy"], ["나는 예뻐지고 싶어", "I want to become pretty"]], dtype='object')
L19arr = np.array([["여기는 편해요", "Here is comfortable (it is comfortable here)"], ["라면은 매워요", "Ramen is spicy"], ["여기는 더 편해요", "Here is more comfortable (it is more comfortable here)"], ["라면은 더 매워요", "Ramen is spicier"], ["도심은 더 멀어요", "Downtown is further"], ["이 방은 더 좁아요", "This room is smaller (narrower)"], ["추억은 더 중요해요", "Memories are more important"], ["한식은 더 맛있어요", "Korean food is more delicious"], ["저는 더 특별한 것을 사고 싶어요", "I want to buy something more special"], ["저는 더 넓은 집에서 살고 싶어요", "I want to live in a bigger (wider) house"], ["저는 밥을 더 먹을 거예요", "I will eat more"], ["저는 더 공부할 거예요", "I will study more"], ["저는 더 기다릴 거예요", "I will wait more (longer)"], ["그 회사는 월급을 더 줘요", "That company gives more of a paycheque"], ["우리는 돈을 더 모을 거예요", "We will collect more money"], ["저는 손을 더 씻을 거예요", "I will wash my hands more"], ["저는 더 열심히 공부할 거예요", "I will study harder"], ["저는 밥을 더 건강하게 먹을 거예요", "I will eat healthier"], ["그 학생들은 더 시끄럽게 이야기했어요", "Those students talked louder"], ["이 방은 조금 더 좁아요", "This room is a little bit smaller"], ["저는 조금 더 기다릴 거예요", "I will wait a little bit more"], ["저는 조금 더 열심히 공부할 거예요", "I will study a little bit harder"], ["나는 펜 두 개가 있어", "I have two pens"], ["나는 펜 두 개가 더 있어", "I have two more pens"], ["사람 두 명이 올 거예요", "Two people will come"], ["사람 두 명이 더 올 거예요", "Two more people will come"], ["저의 여동생은 지난 주에 책을 두 권 읽었어요", "My sister read two books last week"], ["저의 여동생은 지난 주에 책을 두 권 더 읽었어요", "My sister read two more books last week"], ["나는 어제 학교에 두 번 갔어", "I went to school two times (twice) yesterday"], ["나는 어제 학교에 두 번 더 갔어", "I went to school two more times yesterday"], ["도심이 더 좋아요", "Downtown is better"], ["그 자세가 더 좋아요", "That position/posture is better"], ["그 학생의 태도가 더 좋아요", "That student’s attitude is better"], ["저는 돈이 더 많아요", "I have more money"], ["여기는 별이 더 많아요", "There are more stars here"], ["나는 더 잘생겼어", "I am more handsome"], ["나는 아버지보다 더 잘생겼어", "I am more handsome than my father"], ["선생님들은 더 똑똑해요", "Teachers are smarter"], ["선생님들은 학생들보다 더 똑똑해요", "Teachers are smarter than students"], ["한식은 더 매워", "Korean food is spicier"], ["한식은 양식보다 더 매워", "Korean food is spicier than western food"], ["오늘은 더 더워", "Today is hotter"], ["오늘은 어제보다 더 더워", "Today is hotter than yesterday"], ["저는 키가 더 커요", "I am taller"], ["저는 남동생보다 키가 더 커요", "I am taller than my brother"], ["추억은 더 중요해요", "Memories are more important"], ["추억은 돈보다 더 중요해요", "Memories are more important than money"], ["나는 밥을 더 먹었어", "I ate more"], ["나는 남동생보다 밥을 더 먹었어", "I ate more than my brother"], ["나는 어제보다 밥을 더 먹었어", "I ate more than yesterday"], ["저는 친구들보다 더 공부할 거예요", "I will study more than my friends"], ["저는 작년보다 더 공부할 거예요", "I will study more than last year"], ["저는 친구들보다 더 열심히 공부할 거예요", "I will study harder than my friends"], ["저는 작년보다 더 열심히 공부할 거예요", "I will study harder than last year"], ["나는 친구보다 펜이 두 개 더 있어", "I have two more pens than my friend"], ["어제보다 두 명 더 올 거예요", "Two more people will come compared to yesterday"], ["저의 여동생은 지난 주보다 이번 주에 책을 두 권 더 읽었어요", "My sister read two more books this week than she read last week"], ["저는 옛날보다 돈이 더 많아요", "I have more money than a long time ago"], ["저는 저의 아버지보다 돈이 더 많아요", "I have more money than my father"], ["그 학생의 태도가 지난 주보다 더 좋아요", "That student’s attitude is better than last week"], ["그 학생의 태도가 지난 주보다 나아요", "That student’s attitude is better than last week"], ["라면보다 밥이 더 나아요", "Rice is better than Ramen"], ["한식보다 양식이 더 나아요", "Western food is better than Korean food"], ["병은 나았어", "I’m better (literally – the sickness/disease is better)"], ["감기는 나았어", "My cold is better"], ["저는 요즘에 평소보다 더 바빠요", "These days, I am busier than usual"], ["나는 평소보다 더 공부하고 있어", "I am studying more than usual"], ["오늘 하늘에 별이 평소보다 더 많아요", "Tonight, there are more stars in the sky than usual"], ["도심은 생각보다 멀어요", "Downtown is further than I thought"], ["별이 생각보다 더 많아요", "There are more stars than I thought"], ["한식은 생각보다 매워요", "Korean food is spicier than I thought"], ["나는 남동생보다 덜 잘생겼어", "I’m less handsome than my brother"], ["한국에서 대학교는 고등학교보다 덜 어려워요", "In Korea, University is not as hard as high school"], ["남동생이 나보다 더 잘생겼어", "My brother is more handsome than me"], ["한국에서 고등학교는 대학교보다 더 어려워요", "In Korea, high school is harder than university"], ["저의 여자 친구는 한국에서 가장 예쁜 여자예요", "My girlfriend is the prettiest girl in Korea"], ["가족은 가장 중요해요", "Family is the most important"], ["나는 가장 빨리 달려", "I run the fastest"], ["우리가 집에 제일 늦게 도착했어요", "We arrived home the latest"], ["나는 그 여자를 가장 좋아해", "I like that girl most (that girl is my favorite)"], ["나는 수학을 가장 좋아해", "I like math most (math is my favorite)"], ["저는 사과를 가장 싫어해요", "I dislike apples the most"], ["저는 사과를 제일 싫어해요", "I dislike apples the most"], ["그 여자는 우리 반에서 가장 예쁘지 않은 여자예요", "That girl is the least pretty in our class"], ["그 여자는 우리 반에서 제일 예쁘지 않은 여자예요", "That girl is the least pretty in our class"], ["그 여자는 우리 반에서 제일 못생긴 여자예요", "That girl is the ugliest in our class"], ["수학은 제일 어려워요", "Math is the hardest"]], dtype='object')
L20arr = np.array([["나는 수영을 잘해", "I am good at swimming"], ["저 학생은 공부를 잘해", "That student studies well"], ["우리 애기는 말을 잘해요", "Our baby speaks well"], ["저는 야구를 잘해요", "I play baseball well"], ["그 주인은 고객님들을 잘 대우해요", "That owner treats the customers well"], ["목소리가 잘 들려", "I hear you well"], ["나는 어젯밤에 잘 잤어", "I slept well last night"], ["나는 공부를 잘해", "I study well"], ["나는 수영을 못해", "I am bad at swimming"], ["저 학생은 공부를 못해", "That student does not study well"], ["저는 어제 못 잤어요", "I didn’t/couldn’t sleep (well) yesterday"], ["저는 어제 시험을 못 봤어요", "I did poorly on the exam yesterday"], ["저는 어제 시험을 잘 못 봤어요", "I didn’t do good on the exam yesterday"], ["저는 어제 학교에 못 갔어요", "I didn't/couldn’t go to school yesterday"], ["저는 답을 잘 못 썼어요", "I didn't/couldn’t answer well"], ["저는 어제 못 공부했어요", "I didn’t/couldn’t study (well) yesterday"], ["저는 어제 공부하지 못했어요", "I didn’t study well yesterday"], ["저는 공부를 못해요", "I am bad at studying"], ["그것은 제 잘못이었어요", "That was my fault/my mistake"], ["우리 아들은 친구들보다 축구를 더 잘해요", "Our (my) son is better than (his) friends at soccer"], ["그 교수는 다른 교수들보다 수업을 더 잘해요", "That professor teaches classes better than other professors"], ["저는 수영을 작년보다 더 잘해요", "I am better at swimming than last year"], ["우리 아들은 축구를 가장 잘해요", "Our (my) son is the best at soccer"], ["그 교수는 수업을 제일 잘해요", "That professor teaches classes the best"], ["저는 축구를 제일 못해요", "I play soccer the worst"], ["저는 수영을 제일 못해요", "I swim the worst"]], dtype='object')
L21arr = np.array([["엄마는 먹었어요?", "Did mom eat?"], ["밥을 먹었어?", "Did (you) eat?"], ["집에 갔어?", "Did (you) go home?"], ["소식을 들었어?", "Did (you) hear the news?"], ["남동생은 울었어요?", "Did your brother cry?"], ["한국은 좋은 나라야?", "Is Korea a good country?"], ["엄마도 올 거야?", "Will mom come too?"], ["방학 동안 집에 안 갔습니까?", "You didn’t go home during vacation?"], ["그 사람을 만나고 싶습니까?", "Do you want to meet that person?"], ["내일 학교에 갈 겁니까?", "Are you going to school tomorrow?"], ["내일 학교에 갈 것입니까?", "Are you going to school tomorrow?"], ["시험을 잘 봤니?", "Did you write the exam well?"], ["서울에 가겠니?", "Are you going to go to Seoul?"], ["몇 반이니?", "What class are you in?"], ["이미 졸업했니?", "Did you already graduate?"], ["뭐 만드니?", "What are you making?"], ["마음에 드니?", "Do you like it?"], ["어디 사니?", "Where do you live?"], ["그 여자는 예쁜가?", "Is that girl pretty?"], ["이것은 너무 작은가요?", "Is this too small?"], ["그 학교가 좋은가?", "Is that school good?"], ["일이 너무 복잡한가요?", "Is this task too complicated?"], ["그 사람이 선생님인가?", "Is that person a teacher?"], ["그 사람이 우리 엄마인가?", "Is that person our mom?"], ["그 여자는 한국에서 가장 예쁜 여자야. 아닌가?", "That girl is the most beautiful girl in Korea isn’t she?"], ["너무 복잡해. 아닌가?", "This is too complicated. Isn’t it?"], ["밥이 있나?", "Is there rice?"], ["사과도 여기서 파나요?", "Do you sell apples here too?"], ["소녀시대 콘서트를 여기서 하나요?", "Is the Girl’s Generation concert here?"], ["지하철을 타고 있나요?", "Are you on (riding) the subway now?"], ["교통카드가 있었나요?", "Did you have your bus (transportation) card?"], ["그 소식을 들었나요?", "Did you hear that news?"], ["만화책을 샀나요?", "Did you buy the comic book?"], ["어제 병원에 입원했나요?", "Did you go to the hospital yesterday?"], ["만화책을 왜 좋아합니까?", "Why do you like comic books?"], ["한국어를 왜 공부하고 있어요?", "Why are you studying Korean?"], ["왜 너무 빨리 먹었어요?", "Why did you eat so fast?"], ["어제 학교에 왜 안 갔어요?", "Why didn’t you go to school yesterday?"], ["슬기야!", "Seulgi! 왜?", "What do you want?"], ["집에 언제 갔어?", "When did you go home?"], ["집에 언제 갈 거야?", "When will you go home?"], ["그 여자가 언제 사라졌어요?", "When did that girl disappear?"], ["낮잠을 언제 잤어요?", "When did you take a nap?"], ["아빠가 언제 왔나요?", "When did dad come?"], ["언제부터 아팠어요?", "Since when have you been sick?"], ["한국에서 언제까지 있을 거예요?", "Until when will you be in Korea?"], ["언제부터 한국어를 공부했어요?", "Since when have you been studying Korean?"], ["결혼식은 언제야?", "When is the wedding?"], ["방학은 언제야?", "When is vacation?"], ["어디 가고 싶어요?", "Where do you want to go?"], ["어디 살아요?", "Where do you live?"], ["그것을 어디서 하고 싶어요?", "Where do you want to do that?"], ["어디에서 왔어요?", "Where are you from?"], ["어디까지 가고 싶어요?", "Until where do you want to go?"], ["지하철을 어디까지 탈 거예요?", "Until where will we ride the subway?"], ["어디야?", "Where are you?"], ["너의 집이 어디야?", "Where is your house?"], ["그곳이 어디야?", "Where is that place?"], ["학교가 어디예요?", "Where is the school"], ["친구가 어디에 있어요?", "Where is your friend?"], ["엄마가 어디에 있어요?", "Where is mom?"], ["펜이 어디에 있어요?", "Where is the pen?"], ["아빠가 어디에 있어?", "Where is dad?"], ["그 만화책이 어디에 있어?", "Where is that comic?"], ["누가 내일 한국어를 공부할 거야?", "Who will study Korean tomorrow?"], ["너는 내일 누구 만날 거야?", "Who will you meet tomorrow?"], ["그 사람은 누구야?", "Who is that person?"]], dtype='object')
L22arr = np.array([["그것을 어떻게 해요?", "How do you do that?"], ["한국어를 어떻게 배웠어요?", "How did you learn Korean?"], ["그 자리를 어떻게 찾았어요?", "How did you find that seat?"], ["그 파일을 어떻게 보낼 거예요?", "How are you going to send that file?"], ["그 여자에 대해 어떻게 생각해요?", "What do you think about that girl?"], ["남자 친구 어때?", "How is your boyfriend?"], ["점심 어때?", "How about lunch?"], ["이 사진이 어때?", "How about this picture?"], ["시험 어땠어요?", "How was the exam?"], ["점심 어땠어요?", "How was the lunch?"], ["뭐 먹었어요?", "What did you eat?"], ["뭐 샀어요?", "What did you buy?"], ["뭐 입었어요?", "What did you put on/wear?"], ["저는 많이 먹었어요", "I ate a lot 뭐를?", "what?"], ["점심을 먹었어?", "Did you eat lunch?"], ["무엇을 먹었어?", "What did you eat?"], ["무엇을 입었어요?", "What did you put on/wear?"], ["무엇을 샀어요?", "What did you buy?"], ["이것이 뭐야?", "What is this?"], ["이름이 뭐예요?", "What is your name?"], ["점심이 뭐야?", "What is (for) lunch?"], ["무슨 영화를 보고 싶어요?", "What movie do you want to see?"], ["그것이 무슨 냄새야?", "What is that smell?"], ["무슨 생각 해?", "What are you thinking?"], ["그것이 무슨 소리야?", "What is that sound?"], ["무슨 말이야?", "What do you mean?"], ["무슨 냄새야?", "What is that smell?"], ["무슨 영화를 보고 싶어요?", "What movie do you want to see?"], ["어떤 영화를 보고 싶어요?", "Which movie do you want to see?"], ["어떤 차를 사고 싶어요?", "Which car do you want to buy?"], ["어떤 남자는 어제 여기에 왔어", "Some man came here yesterday"], ["저는 어떤 책을 읽고 있었어요", "I was reading some book"], ["저는 어떤 건물에 들어갔어요", "I went into some building"], ["어느 영화를 보고 싶어요?", "Which movie do you want to see?"], ["무슨 집에서 살아요?", "What house do you live in?"], ["어떤 집에서 살아요?", "Which house do you live in?"], ["어느 집에서 살아요?", "Which house do you live in?"], ["무슨 대학교를 다녀요?", "What university do you go to?"], ["어떤 대학교를 다녀요?", "Which university do you go to?"], ["어느 대학교를 다녀요?", "Which university do you go to?"], ["무슨 치마를 샀어요?", "What skirt did you buy?"], ["어떤 치마를 샀어요?", "Which skirt did you buy?"], ["어느 치마를 샀어요?", "Which skirt did you buy?"], ["저는 차 두 대가 있어요", "I have two cars"], ["나는 어제 친구 다섯 명을 만났어", "I met five friends yesterday"], ["저는 그 영화를 다섯 번 봤어요", "I saw that movie five times"], ["차가 몇 대 있어요?", "How many cars do you have?"], ["친구를 몇 명 만났어요?", "How many friends did you meet?"], ["어제 학교에 몇 번 갔어요?", "How many times did you go to school yesterday?"], ["파일을 몇 개 보냈어요?", "How many files did you send?"], ["치마를 몇 개 샀어요?", "How many skirts did you buy?"], ["그 종이를 몇 번 찢었어요?", "How many times did you rip that paper?"], ["몇 시예요?", "What time is it?"], ["몇 살이에요?", "How old are you?"], ["너의 남동생은 몇 살이야?", "How old is your younger brother?"], ["한국어를 얼마나 자주 공부해요?", "How often do you study Korean?"], ["여자 친구는 얼마나 예뻐요?", "How pretty is your girlfriend?"], ["축구를 얼마나 잘 해요?", "How well do you play soccer?"], ["빵을 얼마나 먹었어요?", "How much bread did you eat?"], ["그 여자를 얼마나 사랑해요?", "How much do you love that girl?"], ["돈을 얼마나 가져갈 거예요?", "How much money will you bring?"], ["물을 얼마나 마셨어요?", "How much water did you drink?"], ["그 책상은 자리를 얼마나 차지해요?", "How much space does that desk take up?"], ["빵을 얼마나 많이 먹었어요?", "How much bread did you eat?"], ["그 여자를 얼마나 많이 사랑해요?", "How much do you love that girl?"], ["돈을 얼마나 많이 가져갈 거예요?", "How much money will you bring?"], ["물을 얼마나 많이 마셨어요?", "How much water did you drink?"], ["그 책상은 자리를 얼마나 많이 차지해요?", "How much space does that desk take up?"], ["얼마나 많은 빵을 먹었어요?", "How much bread did you eat?"], ["얼마나 많은 돈을 가져갈 거예요?", "How much money will you bring?"], ["얼마나 많은 물을 마셨어요?", "How much water did you drink?"], ["빵을 몇 개 먹었어요?", "How many pieces of bread did you eat?"], ["몇 명의 여자를 사랑해요?", "How many girls do you love?"], ["한국어를 얼마나 자주 공부해요?", "How often do you study Korean?"], ["한국어를 어떻게 배웠어요?", "How did you learn Korean?"], ["그 로션이 얼마예요?", "How much is that lotion?"], ["저 바지가 얼마예요?", "How much are those pants?"], ["벌금은 얼마였어요?", "How much was the fine?"], ["이게 얼마예요?", "How much is this?"]], dtype='object')
L23arr = np.array([["저 노란 집이 예뻐요", "That yellow house is pretty"], ["빨간 사과는 가장 맛있어요", "Red apples are the most delicious"], ["그녀는 빨간 셔츠를 입고 있다", "She is wearing a red shirt"], ["나는 하얀 차를 사고 싶어", "I want to buy a white car"], ["저는 보통 까만 양복을 입어요", "I usually wear black suits"], ["파란 불이 제일 뜨거워요", "The blue flame is the hottest"], ["저 노란색 집이 예뻐요", "That yellow (colored) house is pretty"], ["그녀는 빨간색 셔츠를 입고 있어요", "She is wearing a red (colored) shirt"], ["나는 하얀색 차를 사고 싶어", "I want to buy a white (colored) car"], ["저는 보통 까만색 양복을 입어요", "I usually wear black (colored) suits"], ["파란색 불이 제일 뜨거워요", "The blue (colored) flame is the hottest"], ["대부분의 사람들은 아침밥을 먹지 않아요", "Most people don’t eat breakfast"], ["대부분 사람들은 아침밥을 먹지 않아요", "Most people don’t eat breakfast"], ["대부분의 부부들은 같은 침대에서 자요", "Most couples sleep in the same bed"], ["대부분 부부들은 같은 침대에서 자요", "Most couples sleep in the same bed"], ["대부분의 독자들은 그 작품을 안 좋아해요", "Most readers don’t like that work"], ["대부분 독자들은 그 작품을 안 좋아해요", "Most readers don’t like that work"], ["나는 네 개의 펜을 샀어", "I bought four pens"], ["나는 두 개의 햄버거를 먹었어", "I ate two hamburgers"], ["나는 어제 다섯 명의 친구를 만났어", "I met five friends yesterday"], ["저는 초록색 펜으로 쓰고 싶어요", "I want to write this with a green pen"], ["연두색 바지를 샀어요", "I bought green pants"], ["대부분의 여자들은 분홍색 가방을 골랐어요", "Most girls chose the pink bag"], ["남자 친구가 보라색 꽃 한 송이를 샀어요", "My boyfriend bought one purple flower"], ["불이 노래요", "The light is yellow"], ["얼굴이 왜 빨개요?", "Why is your face red?"], ["유럽 사람의 피부는 하얘요", "European people’s skin is white"], ["그 여자의 머리가 까매요", "That girl’s hair is black"], ["저 남자의 눈이 진짜 파래요", "That man’s eyes are really blue"], ["불이 노란색이에요", "The light is (the color) yellow"], ["얼굴이 왜 빨간색이에요?", "Why is your face (the color) red?"], ["유럽 사람의 피부는 하얀색이에요", "European people’s skin is (the color white)"], ["그 여자의 머리가 까만색이에요", "That girl’s hair is (the color) black"], ["저 남자의 눈이 진짜 파란색이에요", "That man’s eyes are really (the color) blue"], ["이런 일은 위험하다", "This type of work is dangerous"], ["이런 차는 너무 커요", "This type of car is too big"], ["저는 이렇게 하고 싶어요", "I want to do it like this"], ["왜 이렇게 일찍 가요?", "Why are you going so early (like this)?"], ["이 일은 왜 이렇게 어려워요?", "Why is this so hard (like this)?"], ["저는 그런 사람을 믿지 않아요", "I don’t trust that type of person"], ["저는 그런 것을 좋아하지 않아요", "I don’t like that type of thing"], ["저는 그렇게 생각하지 않아요", "I don’t think like that"], ["저는 그렇게 운동하고 싶어요", "I want to exercise like that"], ["저는 저런 여자를 좋아하지 않아요", "I don’t like that kind of girl"], ["저는 저런 차를 사고 싶어요", "I want to buy that type of car"], ["아빠는 왜 저렇게 말하고 있어요?", "Why is dad talking like that?"], ["저 사람이 왜 저렇게 걸어요?", "Why is that person walking like that?"], ["이 학교도 그렇지 않습니까?", "Is this school not like that as well? 네 그렇습니다", "Yes, that is correct"], ["왜 이래?", "Why is it like this? 왜 그래?", "Why is it like that? 왜 저래?", "Why is it like that?"], ["내일 공원에 같이 가고 싶어요?", "Do you want to go to the park together tomorrow? 그래요", "Sure"], ["제가 지금 갈 거예요", "I’m going to go now 그래요", "Sure"], ["저는 내일 회사에 못 와요", "Tomorrow, I can’t come to work 그래요. 월요일에 봐요", "Sure. See you on Monday"], ["저는 지난 주에 캐나다에 있었어요", "I was in Canada last week 그래요? 어디에 갔어요?", "Really!? (It’s like that?) Where did you go?"], ["나는 보통 고기를 안 먹어", "I usually don’t eat meat 그래? 왜 안 먹어?", "Really? (It’s like that?) Why don’t you eat it?"], ["이 물이 맛이 없어", "This water doesn’t taste good 그래?", "Really? (It’s like that?)"]], dtype='object')
L24arr = np.array([["저는 2주 전에 남동생을 만났어요", "I met my brother two weeks ago"], ["구름은 5분 전에 걷혔어요", "The clouds cleared up five minutes ago"], ["나는 오기 전에 밥을 먹었어", "Before I came, I ate"], ["엄마가 오기 전에 나는 먹었어", "Before mom came, I ate"], ["엄마가 오기 전에 나는 먹을 거야", "Before mom comes, I will eat"], ["한국에 오기 전에 저는 한국어를 배웠어요", "I learned Korean before I came to Korea"], ["수박을 먹기 전에 사과를 먹었어요", "Before I ate an apple I ate watermelon"], ["양복을 입기 전에 목욕을 했어요", "Before putting on the suit I took a bath"], ["구름이 걷히기 전에 비가 왔어요", "Before the clouds cleared it rained"], ["집에서 나가기 전에 방을 치웠어요", "Before leaving the house I cleaned my room"], ["제가 아내와 결혼하기 전에 우리는 2년 동안 사귀었어요", "Before marrying my wife, we went outdated for two years"], ["두 시간 후에 갈 거예요", "I will go two hours from now"], ["수업은 2분 후에 끝날 거예요", "Class will finish two minutes from now"], ["숙제가 끝난 후에 나는 집에 갈 거예요", "After my homework is finished, I will go home"], ["밥을 먹은 후에 친구를 만났어요", "After I ate I met a friend"], ["과자를 많이 먹은 후에 배가 아팠어요", "After eating a lot of candy, my stomach was sore"], ["구두를 신은 후에 의자에서 일어났어요", "After putting on my boots, I got up from the chair"], ["방을 치운 후에 밖에 나갔어요", "After cleaning up my room, I went outside"], ["숙제가 끝난 다음에 나는 집에 갈 거예요", "After my homework is finished, I will go home"], ["밥을 먹은 다음에 친구를 만났어요", "After I ate I met a friend"], ["과자를 많이 먹은 다음에 배가 아팠어요", "After eating a lot of candy, my stomach was sore"], ["구두를 신은 다음에 의자에서 일어났어요", "After putting on my boots, I got up from the chair"], ["방을 치운 다음에 밖에 나갔어요", "After cleaning up my room, I went outside"], ["아들이 저녁 먹기 직전에 과자를 먹었어요", "Right before having dinner, he (the son) ate candy"], ["경찰관이 오기 직전에 그 사람이 갔어요", "That person left right before the police came"], ["양복을 입은 직후에 밖에 나갔어요", "Right after I put on the suit, I went outside"], ["전화번호를 받은 직후에 잃어버렸어요", "Right after I got his phone number, I lost it"], ["한국에 온 후에 한국어를 배우고 있어요", "After coming to Korea, I have been learning Korean"], ["열심히 공부한 후에 실력은 빨리 늘었어요", "After studying hard, my skills have been quickly increasing"], ["나는 5년 이내에 외국어 다섯 개를 배우고 싶어", "I want to learn five languages within five years"], ["나는 5년 안에 외국어 다섯 개를 배우고 싶어", "I want to learn five languages within five years"], ["우리는 1년 이내 결혼할 거예요", "We will get married within one year"], ["우리는 1년 안에 결혼할 거예요", "We will get married within one year "]], dtype='object')
L25arr = np.array([["모든 아시아 사람들은 젓가락을 잘 쓴다", "All Asian people use chopsticks well"], ["모든 학생들은 하루 종일 잤어", "All students slept all day"], ["저는 라면을 다 먹었어요", "I ate all the ramen"], ["저는 소설을 다 읽었어요", "I read the whole book"], ["저는 숙제를 다 했어요", "I did all of my homework"], ["저는 월급을 이미 다 썼어요", "I already spent all of my paycheque"], ["사람들이 다 왔어요", "All the people have come"], ["사람들이 다 죽었어요", "All the people died"], ["부모님은 다 그래요", "All parents are like that"], ["남자들은 다 게을러요", "All men are lazy"], ["학생들은 다 공부하고 있어요", "All of the students are studying"], ["애기들이 다 낮잠 자고 있어요", "All the babies are taking a nap"], ["모든 사람들이 왔어요", "All the people have come"], ["모든 사람들이 죽었어요", "All the people died"], ["모든 부모님은 그래요", "All parents are like that"], ["모든 남자들은 게을러요", "All men are lazy"], ["모든 학생들은 공부하고 있어요", "All of the students are studying"], ["모든 애기들이 낮잠을 자고 있어요", "All the babies are taking a nap"], ["사람들이 다 안 왔어요", "Not all the people have come"], ["저는 라면을 다 안 먹었어요", "I didn’t eat all of the ramen"], ["저는 숙제를 다 하지 못했어요", "I couldn’t do all of my homework"], ["그게 다야?", "Is that all?"], ["이게 다가 아니야", "This isn’t all"], ["선생님들은 모두 똑똑해요", "All teachers are smart"], ["선생님들은 다 똑똑해요", "All teachers are smart"], ["모든 선생님들은 똑똑해요", "Every teacher is smart"], ["선생님들은 모두 다 똑똑해요", "All teachers are smart"], ["모두가 이해했어요", "Everybody understood"], ["모두가 산책하고 있어요", "Everybody is going for a walk"], ["나는 모두 이해했어", "I understood everything"], ["저는 모두 먹고 싶어요", "I want to eat everything"], ["저는 가족 모두를 사랑해요", "I love all of my family"], ["저는 학생 모두를 가르쳤어요", "I taught all of the students"], ["가족 모두가 고향에 갔어요", "All of the family went to the hometown"], ["선생님 모두가 회의에 갔어요", "All of the teachers went to a meeting"], ["학생 모두가 기숙사로 갔어요", "All of the students went to the dorm"], ["저는 선물을 모두에게 주었어요", "I gave a present to everybody"], ["나는 한국에서 어디나 여행하고 싶어", "I (would) want to travel everywhere in Korea"], ["우리는 동남아시아에 어디나 갈 거예요", "We will go everywhere in South East Asia"], ["밥은 어디나 맛이 똑같아요", "Rice tastes the same everywhere"], ["그녀는 언제나 늦게 와요", "She comes late every time"], ["저는 언제나 똑같은 메뉴를 먹어요", "I always eat the same menu"], ["저는 언제나 똑같은 시간에 일어나요", "I always wake up at the same time"], ["누구나 그 여자를 알아요", "Everybody knows that girl"], ["누구나 우리 애기를 보고 싶어요", "Everybody wants to see our baby"], ["누구나 한국을 좋아해요", "Everybody likes Korea"], ["나는 방금 뭔가 봤어", "I just saw something a minute ago"], ["등에 뭔가 있어요", "There is something on your back"], ["등에 뭔가 있나요?", "Is there something on my back?"], ["저는 팔에 뭔가 느껴져요", "I feel something on my arm"], ["저는 뭔가 먹고 싶어요", "I want to eat something"], ["저는 뭔가 말하고 싶어요", "I want to say something"], ["열쇠를 어딘가 뒀어", "I left my keys somewhere"], ["전쟁이 아시아 어딘가에서 났어요", "A war broke out somewhere in Asia"], ["피가 어딘가에서 나오고 있어요", "Blood is coming out of somewhere"], ["저는 그릇을 어딘가 두었어요", "I put the bowl in some place"], ["선생님들이 회의를 어딘가에서 하고 있어요", "The teachers are having a meeting somewhere"], ["저는 휴일에 어딘가에 가고 싶어요", "I want to go somewhere on the holiday"], ["저는 어딘가에서 커피를 마시고 싶어요", "I want to drink a cup of coffee somewhere"], ["그 날이 언젠가 올 거예요", "The day will come sometime"], ["구름이 언젠가 걷힐 거예요", "The clouds will clear sometime"], ["저는 언젠가 경찰관이 되고 싶어요", "I want to become a police officer someday"], ["저는 언젠가 중국어도 배우고 싶어요", "I want to learn Chinese as well some day"], ["저는 언젠가 고향에 돌아가고 싶어요", "I want to return (go back) to my hometown some day"], ["누군가 너를 찾고 있어", "Somebody is looking for you"], ["저는 누군가의 열쇠를 찾았어요", "I found somebody’s keys"], ["경찰관들은 누군가와 얘기하고 있어요", "The policemen are talking with somebody"], ["누군가가 지갑을 잃어버렸어요", "Somebody lost their wallet"], ["누군가가 그 파일을 저에게 보냈어요", "Somebody sent that file to me"], ["어느 겨울 꽃이 다 사라졌다", "Some winter, all the flowers disappeared"], ["어느 마을에서 애기 두 명이 태어났다", "Two babies were born in some village"], ["그 다음 날, 할머니가 어느 시장을 구경하고 있었다", "The next day, the grandmother was browsing around some market"], ["뭐 먹었어요?", "What did you eat?"], ["어디 갔어요?", "Where did you go?"], ["누구 만났어요?", "Who did you meet?"], ["뭐 먹었어요?", "Did you eat something?"], ["어디 갔어요?", "Did you go somewhere?"], ["누구 만났어요?", "Did you meet somebody?"], ["나는 아무와나 사귀고 싶어", "I want to go out with anybody"], ["저는 이 선물을 아무에게나 주고 싶어요", "I want to give this present to anybody"], ["저는 아무하고나 축구를 하고 싶어요", "I want to play soccer with anybody"], ["집에 아무도 없어요", "There is nobody at home"], ["저는 아무도 못 봤어요", "I didn’t see anybody"], ["저는 아무도 만나고 싶지 않아요", "I don’t want to meet anybody"], ["아무도 집에 가지 않았어요", "Nobody went home"], ["아무도 나를 좋아하지 않아", "Nobody likes me"], ["저는 그 말을 아무에게도 안 했어요", "I didn’t say that to anybody"], ["저는 아무하고도 얘기하고 싶지 않아요", "I don’t want to talk with anybody"], ["저는 아무 거나 먹고 싶어요", "I want to eat anything"], ["아무 때나 좋아요", "Anytime is good"], ["저는 아무 데나 가고 싶어요", "I want to go anywhere"], ["저는 아무 데서나 먹고 싶어요", "I want to eat (at) anywhere"], ["저는 아무 것도 먹고 싶지 않아요", "I don’t want to eat anything"], ["아기는 아무 데도 가지 않았어", "The baby didn’t go anywhere"], ["저는 아무 버스나 타고 갈 거예요", "I’m going to take any bus and leave"], ["저는 아무 말도 하지 않았어요", "I didn’t say anything"], ["저는 엄마랑 아무 관계도 없어요", "I don’t have any relationship with my mother"], ["그 버스는 10분마다 와요", "That bus comes each/every 10 minutes"], ["학생마다 달라요", "Each student is different"]], dtype='object')
| 1,111.686275 | 5,211 | 0.644243 | 10,819 | 56,696 | 3.376652 | 0.210556 | 0.009033 | 0.009197 | 0.007665 | 0.299409 | 0.234972 | 0.177379 | 0.139439 | 0.117431 | 0.100843 | 0 | 0.003306 | 0.189167 | 56,696 | 50 | 5,212 | 1,133.92 | 0.791151 | 0.004268 | 0 | 0 | 0 | 0 | 0.799752 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.15 | 0.1 | 0 | 0.1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
f002a701c551c450f53e57a7e5daef0c2f3a7a41 | 780 | py | Python | CISSL_cls/lib/datasets/svhn.py | MinsungHyun/Class-Imbalanced-Semi-Supervsied-Learning | fed14a47fa4dda8a72e8f606ad9a21922b4f7ba4 | [
"MIT"
] | 4 | 2021-09-28T09:23:10.000Z | 2022-03-14T11:51:23.000Z | CISSL_cls/lib/datasets/svhn.py | MinsungHyun/Class-Imbalanced-Semi-Supervsied-Learning | fed14a47fa4dda8a72e8f606ad9a21922b4f7ba4 | [
"MIT"
] | null | null | null | CISSL_cls/lib/datasets/svhn.py | MinsungHyun/Class-Imbalanced-Semi-Supervsied-Learning | fed14a47fa4dda8a72e8f606ad9a21922b4f7ba4 | [
"MIT"
] | null | null | null | import numpy as np
import os
class SVHN:
def __init__(self, root, split="l_train"):
self.dataset = np.load(os.path.join(root, "svhn", split+".npy"), allow_pickle=True).item()
def __getitem__(self, idx):
image = self.dataset["images"][idx]
label = self.dataset["labels"][idx]
image = (image/255. - 0.5)/0.5
return image, label
def __len__(self):
return len(self.dataset["images"])
class SVHNTrain:
def __init__(self, dataset):
self.dataset = dataset
def __getitem__(self, idx):
image = self.dataset["images"][idx]
label = self.dataset["labels"][idx]
image = (image/255. - 0.5)/0.5
return image, label
def __len__(self):
return len(self.dataset["images"]) | 26.896552 | 98 | 0.6 | 103 | 780 | 4.291262 | 0.339806 | 0.223982 | 0.153846 | 0.076923 | 0.615385 | 0.615385 | 0.615385 | 0.615385 | 0.615385 | 0.615385 | 0 | 0.023891 | 0.248718 | 780 | 29 | 99 | 26.896552 | 0.730375 | 0 | 0 | 0.636364 | 0 | 0 | 0.065301 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.272727 | false | 0 | 0.090909 | 0.090909 | 0.636364 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
f018a0a26815a77b23f1b3f80f0048c8d4c38508 | 408 | py | Python | envoy.distribution.repo/envoy/distribution/repo/cmd.py | Nordix/pytooling | b48e70e9098c283d0f17db8016d2f32a2b103a57 | [
"Apache-2.0"
] | 1 | 2021-12-09T19:24:48.000Z | 2021-12-09T19:24:48.000Z | envoy.distribution.repo/envoy/distribution/repo/cmd.py | Nordix/pytooling | b48e70e9098c283d0f17db8016d2f32a2b103a57 | [
"Apache-2.0"
] | 392 | 2021-08-24T15:55:32.000Z | 2022-03-28T14:26:22.000Z | envoy.distribution.repo/envoy/distribution/repo/cmd.py | Nordix/pytooling | b48e70e9098c283d0f17db8016d2f32a2b103a57 | [
"Apache-2.0"
] | 3 | 2021-10-06T13:43:11.000Z | 2021-11-29T13:48:56.000Z |
import sys
from typing import Optional
from .deb import DebRepoManager
from .runner import RepoBuildingRunner
def _register_repo_types() -> None:
RepoBuildingRunner.register_repo_type("deb", DebRepoManager)
def main(*args: str) -> Optional[int]:
_register_repo_types()
return RepoBuildingRunner(*args)()
def cmd():
sys.exit(main(*sys.argv[1:]))
if __name__ == "__main__":
cmd()
| 17 | 64 | 0.718137 | 49 | 408 | 5.653061 | 0.530612 | 0.129964 | 0.122744 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.002924 | 0.161765 | 408 | 23 | 65 | 17.73913 | 0.807018 | 0 | 0 | 0 | 0 | 0 | 0.027027 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.230769 | true | 0 | 0.307692 | 0 | 0.615385 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
f0227cd04c5519d0537c492bc589829c9ae0b2da | 1,150 | py | Python | etl/lib/base/scraper.py | Maps-for-Change/events-etl | d803c53f3215fbdb917048d560704244648bc668 | [
"MIT"
] | null | null | null | etl/lib/base/scraper.py | Maps-for-Change/events-etl | d803c53f3215fbdb917048d560704244648bc668 | [
"MIT"
] | 3 | 2017-04-15T05:56:12.000Z | 2017-04-17T23:45:56.000Z | etl/lib/base/scraper.py | Maps-for-Change/events-etl | d803c53f3215fbdb917048d560704244648bc668 | [
"MIT"
] | 1 | 2021-07-09T15:24:19.000Z | 2021-07-09T15:24:19.000Z | # encoding=utf8
import abc
class Scraper(object):
__metaclass__ = abc.ABCMeta
def __init__(self):
self.minified_data = None
self.osdified_data = None
def get_data(self):
return self.minified_data
def get_osdi_data(self):
return self.osdified_data
@classmethod
@abc.abstractmethod
def run(self):
"""
This orchestrates the various methods
"""
@classmethod
@abc.abstractmethod
def retrieve(self):
"""
This is where the items will be processed
by getting the data out
"""
@classmethod
@abc.abstractmethod
def clean(self):
"""
This will clean the information out that is
considered private information
"""
@classmethod
@abc.abstractmethod
def translate(self):
"""
This prepares the data for a singular
cleaned format
"""
@classmethod
@abc.abstractmethod
def osdify(self):
"""
Translate the data to OSDI format
"""
| 20.535714 | 51 | 0.546087 | 112 | 1,150 | 5.473214 | 0.455357 | 0.114193 | 0.228385 | 0.252855 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001408 | 0.382609 | 1,150 | 55 | 52 | 20.909091 | 0.861972 | 0.244348 | 0 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.32 | false | 0 | 0.04 | 0.08 | 0.52 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
f02a7ce465175476a74a0b1723a2385bed9dc276 | 107,687 | py | Python | UI/img_rc.py | BeiChenYx/NetDebug | 55986b59d56bce8c8e02cc764c0fd4233a03be22 | [
"MIT"
] | 9 | 2019-01-12T15:43:21.000Z | 2022-02-17T07:15:04.000Z | UI/img_rc.py | BeiChenYx/NetDebug | 55986b59d56bce8c8e02cc764c0fd4233a03be22 | [
"MIT"
] | null | null | null | UI/img_rc.py | BeiChenYx/NetDebug | 55986b59d56bce8c8e02cc764c0fd4233a03be22 | [
"MIT"
] | 1 | 2020-07-18T14:33:19.000Z | 2020-07-18T14:33:19.000Z | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.11.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 61.818025 | 129 | 0.726216 | 25,985 | 107,687 | 3.00812 | 0.011815 | 0.103626 | 0.124581 | 0.14001 | 0.525689 | 0.515864 | 0.512512 | 0.511706 | 0.50948 | 0.50403 | 0 | 0.338529 | 0.016984 | 107,687 | 1,741 | 130 | 61.853532 | 0.399875 | 0.001412 | 0 | 0.426667 | 0 | 0.923478 | 0.000009 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0.001159 | false | 0 | 0.00058 | 0 | 0.001739 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
f0476f11dd24db6bf1c30cb78ed60d8b9e0b5dc2 | 3,249 | py | Python | xmantissa/test/historic/stub_website5to6.py | jonathanj/mantissa | 53e5502aba23ce99be78b27f923a276593033fe8 | [
"MIT"
] | 6 | 2016-02-17T15:04:53.000Z | 2021-08-20T09:44:10.000Z | xmantissa/test/historic/stub_website5to6.py | jonathanj/mantissa | 53e5502aba23ce99be78b27f923a276593033fe8 | [
"MIT"
] | 62 | 2015-02-04T23:40:55.000Z | 2021-02-18T19:56:02.000Z | xmantissa/test/historic/stub_website5to6.py | jonathanj/mantissa | 53e5502aba23ce99be78b27f923a276593033fe8 | [
"MIT"
] | 8 | 2015-11-15T17:26:42.000Z | 2020-12-02T06:36:52.000Z | # -*- test-case-name: xmantissa.test.historic.test_website5to6 -*-
from axiom.test.historic.stubloader import saveStub
from axiom.plugins.mantissacmd import Mantissa
from axiom.userbase import LoginSystem
from axiom.dependency import installOn
from xmantissa.port import TCPPort, SSLPort
from xmantissa.website import WebSite
cert = (
'-----BEGIN CERTIFICATE-----\n'
'MIICmjCCAgMCBACFAjkwDQYJKoZIhvcNAQEEBQAwgZMxCzAJBgNVBAYTAlVTMRMw\n'
'EQYDVQQDEwpkaXZtb2QuY29tMREwDwYDVQQHEwhOZXcgWW9yazETMBEGA1UEChMK\n'
'RGl2bW9kIExMQzERMA8GA1UECBMITmV3IFlvcmsxITAfBgkqhkiG9w0BCQEWEnN1\n'
'cHBvcnRAZGl2bW9kLm9yZzERMA8GA1UECxMIU2VjdXJpdHkwHhcNMDgwMjIwMjEy\n'
'NDExWhcNMDkwMjE5MjEyNDExWjCBkzELMAkGA1UEBhMCVVMxEzARBgNVBAMTCmRp\n'
'dm1vZC5jb20xETAPBgNVBAcTCE5ldyBZb3JrMRMwEQYDVQQKEwpEaXZtb2QgTExD\n'
'MREwDwYDVQQIEwhOZXcgWW9yazEhMB8GCSqGSIb3DQEJARYSc3VwcG9ydEBkaXZt\n'
'b2Qub3JnMREwDwYDVQQLEwhTZWN1cml0eTCBnzANBgkqhkiG9w0BAQEFAAOBjQAw\n'
'gYkCgYEA3ucaT8gUB7BEp2dfRulWBRT6tTDELA7sJzyk+12E1vxQppJDzwG8VgSj\n'
'sOl8Jw0qnUb/Qoe96UlA8hDYBbmwz0CCvVRSj+1GYj6Ka8NeheME2RU3/benLbyL\n'
'S7HUQ93Mqs3VWrlv2lMbgp29njwJqvqMRt8JGB1ql8xUDSLw4kcCAwEAATANBgkq\n'
'hkiG9w0BAQQFAAOBgQAXxMBJu+VkazQSuOnIn5Ewug2tHmf0sxT7FkcB2nEviQ7U\n'
'e2bb95IL9XqkO0yKEbJ5K8T8SyXW9VNUATce4JO6NNikyVCZzV1dG2+ATDBaaVHK\n'
'S2Beh1p6boFvv0+k2qZ/9JmJYVx4l1xPavc70x95rR2E0kuwhyw4miHpSMqfpA==\n'
'-----END CERTIFICATE-----\n'
'-----BEGIN RSA PRIVATE KEY-----\n'
'MIICXQIBAAKBgQDe5xpPyBQHsESnZ19G6VYFFPq1MMQsDuwnPKT7XYTW/FCmkkPP\n'
'AbxWBKOw6XwnDSqdRv9Ch73pSUDyENgFubDPQIK9VFKP7UZiPoprw16F4wTZFTf9\n'
't6ctvItLsdRD3cyqzdVauW/aUxuCnb2ePAmq+oxG3wkYHWqXzFQNIvDiRwIDAQAB\n'
'AoGAG/YHgeyKPrCo3AsGk6GfjcGk9WeppBE3JHDiDToc+M7r2wlMAkKoem3Yjs+r\n'
'KEbpipMmYBUhCIuM3xCn2IgDmq/9rC+mDmEu7mEvL0Rnl5Ns6m/uw61kYKDAghYg\n'
'K7lD3jlAT/a9I8wB2UO9F6p8166YERU736Qa4GUle4l8irECQQD0V6ZbbW1o5j5s\n'
'IUzhVvBr/flWabpMJ9Vw3eLy695iFjgx+5W0nD+JK1ny8MiwCRsjoRTXldHhdaod\n'
'8VbPz/QJAkEA6YmX6XksIb8JUYFtPk0WodQmz51qzo0jol3COL/rXuPVkTcesyTM\n'
'61S7WSv0G6pMqE9xw0llMBON7Pr24N/XzwJBALW+eFvrEgWDtQyi3FeEXkJFX+/5\n'
'pnu86VMRiByeewREeLoc4ya7TbsOxtIgbXYa39fpmeIda0ajSc0J1UOv71kCQQCO\n'
'q20vx8PrNc7WiTAY4HVUFcxEB5Ipb1X2qjqt+qkrBhsBpN/PZ0r89X2iw1RU1lwQ\n'
'csA4Io17qmaJAORziqxHAkAb2zin9SzS58+X55pGVp8PwhGLmm9cGH/DtWVSIAl2\n'
'q3pqCmcxnimc+IYJJlY6dkk7jtnIVTWz3B9XUOtKGEYF\n'
'-----END RSA PRIVATE KEY-----\n')
def createDatabase(store):
"""
Initialize the given Store for use as a Mantissa webserver.
"""
Mantissa().installSite(store, u'example.net')
site = store.findUnique(WebSite)
site.httpLog = store.filesdir.child('httpd.log').path
site.hitCount = 123
site.hostname = u'example.net'
tcp = store.findUnique(TCPPort, TCPPort.factory == site)
tcp.portNumber = 8088
ssl = store.findUnique(SSLPort, SSLPort.factory == site)
ssl.portNumber = 6443
ssl.certificatePath.setContent(cert)
loginSystem = store.findUnique(LoginSystem)
account = loginSystem.addAccount(u'testuser', u'localhost', None)
subStore = account.avatars.open()
installOn(WebSite(store=subStore, hitCount=321), subStore)
if __name__ == '__main__':
saveStub(createDatabase, 14982)
| 49.227273 | 72 | 0.805171 | 236 | 3,249 | 11.04661 | 0.567797 | 0.013809 | 0.009973 | 0.01074 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088721 | 0.104955 | 3,249 | 65 | 73 | 49.984615 | 0.807772 | 0.038473 | 0 | 0 | 0 | 0 | 0.623552 | 0.566924 | 0 | 1 | 0 | 0 | 0 | 1 | 0.018182 | false | 0 | 0.109091 | 0 | 0.127273 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
f06c2e616a4a7976d8177957898a0dab76a161e0 | 69 | py | Python | geometry/utilities/test/__init__.py | fR0zTy/geometry | c8cbd3671fd8ac5e86150cdeb297b584a63a9760 | [
"MIT"
] | null | null | null | geometry/utilities/test/__init__.py | fR0zTy/geometry | c8cbd3671fd8ac5e86150cdeb297b584a63a9760 | [
"MIT"
] | null | null | null | geometry/utilities/test/__init__.py | fR0zTy/geometry | c8cbd3671fd8ac5e86150cdeb297b584a63a9760 | [
"MIT"
] | null | null | null | # -*- coding : utf-8 -*-
# init in geometry.utilities.test package
| 13.8 | 41 | 0.637681 | 9 | 69 | 4.888889 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017857 | 0.188406 | 69 | 4 | 42 | 17.25 | 0.767857 | 0.898551 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
f0803fb3f2b9c4e6e18b9ba1351f9b64c0418cad | 4,822 | py | Python | tests/verification/test_checklib.py | stklik/CREST | 7fd97c50b0c6c923e1c477105bed4f0ea032bb99 | [
"MIT"
] | 14 | 2019-08-06T10:17:46.000Z | 2022-03-13T12:50:59.000Z | tests/verification/test_checklib.py | stklik/CREST | 7fd97c50b0c6c923e1c477105bed4f0ea032bb99 | [
"MIT"
] | 16 | 2018-01-20T00:54:24.000Z | 2019-07-24T15:43:42.000Z | tests/verification/test_checklib.py | stklik/CREST | 7fd97c50b0c6c923e1c477105bed4f0ea032bb99 | [
"MIT"
] | 1 | 2021-02-01T15:33:24.000Z | 2021-02-01T15:33:24.000Z | import crestdsl.model as crest
import unittest
from crestdsl.verification import check
class TestEntity(crest.Entity):
res = crest.Resource("float-resource", crest.Types.REAL)
listres = crest.Resource("list-res", ["first", "TWO", "3.14abc"])
port = crest.Local(resource=res, value=314.13)
port2 = crest.Local(resource=listres, value="TWO")
state = current = crest.State()
state2 = crest.State()
class TestStateCheck(unittest.TestCase):
def test_state_check_eq(self):
entity = TestEntity()
c = check(entity) == entity.state
assert c.check()
def test_state_check_neq(self):
entity = TestEntity()
c = check(entity) != entity.state2
assert c.check()
def test_state_check_eq_fails(self):
entity = TestEntity()
c = check(entity) == entity.state2
self.assertFalse(c.check())
def test_state_check_neq_fails(self):
entity = TestEntity()
c = check(entity) != entity.state
self.assertFalse(c.check())
def test_state_check_eq_string(self):
entity = TestEntity()
c = check(entity) == "state"
assert c.check()
def test_state_check_neq_string(self):
entity = TestEntity()
c = check(entity) != "state2"
assert c.check()
class TestPortCheck(unittest.TestCase):
def test_port_check_float_lt(self):
entity = TestEntity()
c = check(entity.port) < 400
assert c.check()
c = check(entity.port) < 200
self.assertFalse(c.check())
c = check(entity.port) < 314.13
self.assertFalse(c.check())
def test_port_check_float_le(self):
entity = TestEntity()
c = check(entity.port) <= 400
assert c.check()
c = check(entity.port) <= 314.13
assert c.check()
c = check(entity.port) <= 200
self.assertFalse(c.check())
def test_port_check_float_eq(self):
entity = TestEntity()
c = check(entity.port) == 314.13
assert c.check()
c = check(entity.port) == 400
self.assertFalse(c.check())
c = check(entity.port) == 200
self.assertFalse(c.check())
def test_port_check_float_ne(self):
entity = TestEntity()
c = check(entity.port) != 314.13
self.assertFalse(c.check())
c = check(entity.port) != 400
assert c.check()
c = check(entity.port) != 200
assert c.check()
def test_port_check_float_gt(self):
entity = TestEntity()
c = check(entity.port) > 200
assert c.check()
c = check(entity.port) > 400
self.assertFalse(c.check())
c = check(entity.port) > 314.13
self.assertFalse(c.check())
def test_port_check_float_ge(self):
entity = TestEntity()
c = check(entity.port) >= 200
assert c.check()
c = check(entity.port) >= 314.13
assert c.check()
c = check(entity.port) >= 400
self.assertFalse(c.check())
""" LIST TYPES """
def test_port_check_list_eq(self):
entity = TestEntity()
c = check(entity.port2) == "TWO"
assert c.check()
c = check(entity.port2) == "first"
self.assertFalse(c.check())
def test_port_check_list_ne(self):
entity = TestEntity()
c = check(entity.port2) != "first"
assert c.check()
c = check(entity.port2) != "TWO"
self.assertFalse(c.check())
class GetAtomicChecksTest(unittest.TestCase):
def test_port_check(self):
entity = TestEntity()
c = check(entity.port2) == "TWO"
self.assertSetEqual(c.get_atomic_checks(), {c})
def test_state_check(self):
entity = TestEntity()
c = check(entity) == entity.state
self.assertSetEqual(c.get_atomic_checks(), {c})
def test_and_check(self):
entity = TestEntity()
c1 = check(entity.port2) == "TWO"
c2 = check(entity) == entity.state
c = c1 & c2
self.assertSetEqual(c.get_atomic_checks(), {c1,c2})
def test_or_check(self):
entity = TestEntity()
c1 = check(entity.port2) == "TWO"
c2 = check(entity) == entity.state
c = c1 | c2
self.assertSetEqual(c.get_atomic_checks(), {c1,c2})
def test_not_check(self):
entity = TestEntity()
c1 = check(entity.port2) == "TWO"
c2 = check(entity) == entity.state
c = -(c1 | c2)
self.assertSetEqual(c.get_atomic_checks(), {c1,c2})
def test_duplicate_check(self):
entity = TestEntity()
c1 = check(entity.port2) == "TWO"
c2 = check(entity) == entity.state
c = -(c1 | c2) & c2
self.assertSetEqual(c.get_atomic_checks(), {c1,c2}) | 29.950311 | 69 | 0.580257 | 585 | 4,822 | 4.649573 | 0.107692 | 0.127941 | 0.132353 | 0.105882 | 0.842279 | 0.815074 | 0.790809 | 0.701838 | 0.580147 | 0.486765 | 0 | 0.032839 | 0.286396 | 4,822 | 161 | 70 | 29.950311 | 0.757629 | 0 | 0 | 0.511628 | 0 | 0 | 0.017066 | 0 | 0 | 0 | 0 | 0 | 0.263566 | 1 | 0.155039 | false | 0 | 0.023256 | 0 | 0.263566 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
b2de3bd58ebdb5fad2bffedf481f1750de79f5f5 | 432 | py | Python | lab_3/task3_utils.py | balolam/university-mpi-python | 92485b6d402c1ed91b6ff08191d34d83dc43717f | [
"Apache-2.0"
] | null | null | null | lab_3/task3_utils.py | balolam/university-mpi-python | 92485b6d402c1ed91b6ff08191d34d83dc43717f | [
"Apache-2.0"
] | null | null | null | lab_3/task3_utils.py | balolam/university-mpi-python | 92485b6d402c1ed91b6ff08191d34d83dc43717f | [
"Apache-2.0"
] | null | null | null | import numpy as np
# noinspection PyShadowingNames
def sum_els_python(arr):
length = len(arr)
if length > 0:
sum_els = 0
index = 1
while index < length:
sum_els = sum_els + arr[index]
return sum_els
else:
return 0
# noinspection PyShadowingNames
def sum_els_c(arr): return np.nansum(arr)
# noinspection PyShadowingNames
def sum_els(arr): return sum_els_c(arr) | 17.28 | 42 | 0.645833 | 59 | 432 | 4.542373 | 0.372881 | 0.179104 | 0.347015 | 0.380597 | 0.414179 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012903 | 0.282407 | 432 | 25 | 43 | 17.28 | 0.851613 | 0.206019 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.230769 | false | 0 | 0.076923 | 0.153846 | 0.461538 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 |
b2e2d4e8730d075ab690727751a7704dc934dd92 | 228 | py | Python | integration_tests/util.py | janneronkko/vcsver | 77020e296a8239ee142213642504c03b9064653f | [
"MIT"
] | 1 | 2020-12-23T19:22:51.000Z | 2020-12-23T19:22:51.000Z | integration_tests/util.py | janneronkko/vcsver | 77020e296a8239ee142213642504c03b9064653f | [
"MIT"
] | null | null | null | integration_tests/util.py | janneronkko/vcsver | 77020e296a8239ee142213642504c03b9064653f | [
"MIT"
] | null | null | null | import subprocess
def run(*cmd, **kwargs):
kwargs.setdefault('stdout', subprocess.DEVNULL)
kwargs.setdefault('stderr', subprocess.PIPE)
return subprocess.run(cmd, **kwargs) # pylint: disable=subprocess-run-check
| 25.333333 | 80 | 0.723684 | 26 | 228 | 6.346154 | 0.576923 | 0.072727 | 0.145455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135965 | 228 | 8 | 81 | 28.5 | 0.837563 | 0.157895 | 0 | 0 | 0 | 0 | 0.063158 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | true | 0 | 0.2 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
6521d3f658a75ab0587bd56761deae48e64f5b7d | 208 | py | Python | bilanci_project/shorturls/models.py | DeppSRL/open_bilanci | a6d94cb5181fddd420c70410cc5271aa9c62bbac | [
"MIT"
] | 6 | 2016-09-29T11:08:33.000Z | 2020-06-24T09:07:34.000Z | bilanci_project/shorturls/models.py | Mavks25/open_bilanci | a6d94cb5181fddd420c70410cc5271aa9c62bbac | [
"MIT"
] | 1 | 2017-07-05T14:10:38.000Z | 2017-07-05T14:10:38.000Z | bilanci_project/shorturls/models.py | Mavks25/open_bilanci | a6d94cb5181fddd420c70410cc5271aa9c62bbac | [
"MIT"
] | 7 | 2016-06-08T10:11:36.000Z | 2022-02-05T14:26:00.000Z | __author__ = 'stefano'
from django.db import models
class ShortUrl(models.Model):
long_url = models.TextField(max_length=3000, null=False)
short_url = models.TextField(max_length=1000, null=False)
| 23.111111 | 61 | 0.759615 | 29 | 208 | 5.172414 | 0.689655 | 0.12 | 0.24 | 0.28 | 0.36 | 0 | 0 | 0 | 0 | 0 | 0 | 0.044444 | 0.134615 | 208 | 8 | 62 | 26 | 0.788889 | 0 | 0 | 0 | 0 | 0 | 0.033816 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
652ea65d5fdc8f7e707b5346fd58c43a5dfc5106 | 172 | py | Python | titanscraper/__init__.py | emileKing/titanscraper | 639d6d1a97a5c55ef2c70b595a93c3dea8d19461 | [
"MIT"
] | null | null | null | titanscraper/__init__.py | emileKing/titanscraper | 639d6d1a97a5c55ef2c70b595a93c3dea8d19461 | [
"MIT"
] | null | null | null | titanscraper/__init__.py | emileKing/titanscraper | 639d6d1a97a5c55ef2c70b595a93c3dea8d19461 | [
"MIT"
] | null | null | null | """
TITANSCRAPER
AUTHOR: Emile DJIDA GONGDEBIYA
COMPANY: TITANWARE Technology
VERSION: 0.0.21
LICENCE: MIT
"""
__version__ = "0.0.21"
from .titanscraper import TitanScraper | 19.111111 | 38 | 0.77907 | 22 | 172 | 5.909091 | 0.681818 | 0.123077 | 0.138462 | 0.169231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.052632 | 0.116279 | 172 | 9 | 38 | 19.111111 | 0.802632 | 0.593023 | 0 | 0 | 0 | 0 | 0.095238 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
e8e4853f1ac875eada525ea06f6402aa30a34681 | 334 | py | Python | vvspy/obj/__init__.py | zaanposni/vvs | c69503c9fd12dcb87f8d98e422d38e3bc12a10fe | [
"MIT"
] | 13 | 2019-12-02T12:47:05.000Z | 2020-01-29T09:56:38.000Z | vvspy/obj/__init__.py | zaanposni/vvspy | c69503c9fd12dcb87f8d98e422d38e3bc12a10fe | [
"MIT"
] | 16 | 2019-12-01T19:20:06.000Z | 2019-12-21T11:50:00.000Z | vvspy/obj/__init__.py | FI18-Trainees/vvs-py | c69503c9fd12dcb87f8d98e422d38e3bc12a10fe | [
"MIT"
] | 2 | 2021-01-30T18:58:33.000Z | 2021-08-30T07:07:22.000Z | from .arrival import Arrival
from .departure import Departure
from .arrival import Arrival
from .trip import Trip
from .serving_line import ServingLine
from .line_operator import LineOperator
from .connection import Connection
from .origin import Origin
from .destination import Destination
from .transportation import Transportation
| 30.363636 | 42 | 0.850299 | 42 | 334 | 6.714286 | 0.333333 | 0.078014 | 0.120567 | 0.170213 | 0.198582 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.11976 | 334 | 10 | 43 | 33.4 | 0.959184 | 0 | 0 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
e8ea3d5cd9306fba32826520339f2ffcda53d7cb | 149 | py | Python | loop_break.py | godontop/python-work | ea22e0df8b0b17605f5a434e556a388d1f75aa47 | [
"MIT"
] | null | null | null | loop_break.py | godontop/python-work | ea22e0df8b0b17605f5a434e556a388d1f75aa47 | [
"MIT"
] | null | null | null | loop_break.py | godontop/python-work | ea22e0df8b0b17605f5a434e556a388d1f75aa47 | [
"MIT"
] | null | null | null | # 在while循环中，break的作用也是一样的。
for i in range(1, 6):
print 'i =', i,
print 'Hello, how',
if i == 3:
break
print 'are you today?'
| 18.625 | 26 | 0.536913 | 22 | 149 | 3.636364 | 0.772727 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029412 | 0.315436 | 149 | 7 | 27 | 21.285714 | 0.754902 | 0.161074 | 0 | 0 | 0 | 0 | 0.219512 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
3364b3c34418b8de4ab932ee92d0994c01ae4166 | 45 | py | Python | maxindex.py | malai001/codebank | 6834107ab683a38a8799102278369a66b1c1b336 | [
"bzip2-1.0.6"
] | 1 | 2017-07-11T05:02:12.000Z | 2017-07-11T05:02:12.000Z | maxindex.py | malai001/codebank | 6834107ab683a38a8799102278369a66b1c1b336 | [
"bzip2-1.0.6"
] | null | null | null | maxindex.py | malai001/codebank | 6834107ab683a38a8799102278369a66b1c1b336 | [
"bzip2-1.0.6"
] | null | null | null | a = 'abab'
b = 'aba'
if b in a:
print b
| 9 | 11 | 0.466667 | 10 | 45 | 2.1 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.377778 | 45 | 4 | 12 | 11.25 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0.170732 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.25 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
682ab3726832c1b37fe5b4a38f3288edb515e9ad | 341 | py | Python | 2021/06_FileIO/Code_Ex_1.py | lfrommelt/monty | e8cabf0e4ac01ab3d97eecee5e699139076d6544 | [
"MIT"
] | null | null | null | 2021/06_FileIO/Code_Ex_1.py | lfrommelt/monty | e8cabf0e4ac01ab3d97eecee5e699139076d6544 | [
"MIT"
] | null | null | null | 2021/06_FileIO/Code_Ex_1.py | lfrommelt/monty | e8cabf0e4ac01ab3d97eecee5e699139076d6544 | [
"MIT"
] | 1 | 2020-03-20T14:26:28.000Z | 2020-03-20T14:26:28.000Z | fun_fact = "This string uses words\nand lines\n"
# the string variable fun_fact
print(fun_fact)
print(type(fun_fact))
# using strip
print(fun_fact.strip())
print(type(fun_fact.strip()))
# using split
print(fun_fact.split())
print(type(fun_fact.split()))
# using splitlines
print(fun_fact.splitlines())
print(type(fun_fact.splitlines()))
| 18.944444 | 48 | 0.753666 | 54 | 341 | 4.574074 | 0.314815 | 0.283401 | 0.194332 | 0.259109 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.096774 | 341 | 17 | 49 | 20.058824 | 0.801948 | 0.202346 | 0 | 0 | 0 | 0 | 0.131086 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.888889 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
686211567cfa275c39866be1b325af1571895f8c | 97 | py | Python | apps/static_page/apps.py | agiledesign2/base-rent | 071c2122cea0501c75f4afd17ea1bbd944694f85 | [
"MIT"
] | null | null | null | apps/static_page/apps.py | agiledesign2/base-rent | 071c2122cea0501c75f4afd17ea1bbd944694f85 | [
"MIT"
] | null | null | null | apps/static_page/apps.py | agiledesign2/base-rent | 071c2122cea0501c75f4afd17ea1bbd944694f85 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class Static_pageConfig(AppConfig):
name = 'static_page'
| 16.166667 | 35 | 0.773196 | 12 | 97 | 6.083333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.154639 | 97 | 5 | 36 | 19.4 | 0.890244 | 0 | 0 | 0 | 0 | 0 | 0.113402 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
68695eea6ece834b0977adeae395013b43373888 | 164 | py | Python | Group/admin.py | deanbi/TasKing | c29eb5f24eacd5c7933a471f04e7fc6f1c798240 | [
"MIT"
] | null | null | null | Group/admin.py | deanbi/TasKing | c29eb5f24eacd5c7933a471f04e7fc6f1c798240 | [
"MIT"
] | null | null | null | Group/admin.py | deanbi/TasKing | c29eb5f24eacd5c7933a471f04e7fc6f1c798240 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import Group
@admin.register(Group)
class GroupAdminConfig(admin.ModelAdmin):
list_display = ('creator','prize')
| 23.428571 | 41 | 0.77439 | 20 | 164 | 6.3 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.115854 | 164 | 6 | 42 | 27.333333 | 0.868966 | 0 | 0 | 0 | 0 | 0 | 0.073171 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
68815cea067b478a918240b10885ba05f4f6b3a9 | 6,540 | py | Python | tests/test_rainfl.py | hustjinghu/metal-fatigue | 29bc3f7079b489314d740bfa55497aa53a376964 | [
"MIT"
] | null | null | null | tests/test_rainfl.py | hustjinghu/metal-fatigue | 29bc3f7079b489314d740bfa55497aa53a376964 | [
"MIT"
] | null | null | null | tests/test_rainfl.py | hustjinghu/metal-fatigue | 29bc3f7079b489314d740bfa55497aa53a376964 | [
"MIT"
] | 1 | 2021-07-18T03:23:40.000Z | 2021-07-18T03:23:40.000Z | import pytest
import sys
sys.path.append("D:\\alexa\\Documents\\metal-fatigue")
import numpy as np
from metal_fatigue import rainfl
def test_binned():
# init bin
values = np.array([[1, 2, 3], [4, 5, 6]])
binsize = np.array([0.5, 10])
minedge = np.array([-1.19, 20])
numbins = np.array([2, 3])
bin1 = np.array([-1.19, -0.69, -0.19])
bin2 = np.array([20., 30., 40., 50.])
bins = np.array((bin1, bin2))
maxedge = np.array([-0.19, 50])
binned_object = rainfl.binned(values, binsize, minedge, numbins)
np.testing.assert_allclose(values, binned_object.values)
np.testing.assert_allclose(binsize, binned_object.binsize)
np.testing.assert_allclose(minedge, binned_object.minedge)
np.testing.assert_allclose(numbins, binned_object.numbins)
np.testing.assert_allclose(maxedge, binned_object.maxedge)
for bins_, mat_bins in zip(bins, binned_object.bins):
np.testing.assert_allclose(bins_, mat_bins)
# multiply_constant
result = values * 5.1
scaled = binned_object.multiply_constant(5.1)
np.testing.assert_allclose(result, scaled.values)
# add_constant
result = values + 5.1
added = binned_object.add_constant(5.1)
np.testing.assert_allclose(result, added.values)
def test_rfm():
values = np.array([[1, 2, 3], [4, 5, 6], [-1, -2, -3]])
binsize = 1.4
xmin = 1
ymin = -5.2
matrixtype = "FromTo"
matrix = rainfl._rfm(values, binsize, xmin, ymin, matrixtype)
np.testing.assert_allclose(values, matrix.values)
np.testing.assert_allclose(binsize, matrix.binsize[0])
np.testing.assert_allclose(binsize, matrix.binsize[1])
np.testing.assert_allclose(xmin, matrix.xmin)
np.testing.assert_allclose(ymin, matrix.ymin)
np.testing.assert_allclose(xmin, matrix.minedge[0])
np.testing.assert_allclose(ymin, matrix.minedge[1])
matrix.plot2d()
assert matrixtype == matrix.matrixtype
def test_from_to():
values = np.array([[1, 2, 3], [4, 5, 6], [-1, -2, -3]])
binsize = 1.4
xmin = 1
ymin = -5.2
numbins = 3
matrix = rainfl.from_to(values, binsize, xmin, ymin)
np.testing.assert_allclose(values, matrix.values)
np.testing.assert_allclose(binsize, matrix.binsize[0])
np.testing.assert_allclose(binsize, matrix.binsize[1])
np.testing.assert_allclose(xmin, matrix.xmin)
np.testing.assert_allclose(ymin, matrix.ymin)
np.testing.assert_allclose(xmin, matrix.minedge[0])
np.testing.assert_allclose(ymin, matrix.minedge[1])
np.testing.assert_allclose(numbins, matrix.numbins[0])
np.testing.assert_allclose(numbins, matrix.numbins[1])
assert "FromTo" == matrix.matrixtype
def test_range_mean():
values = np.array([[1, 2, 3], [4, 5, 6], [-1, -2, -3]])
binsize = 1.4
xmin = 1
ymin = -5.2
matrix = rainfl.range_mean(values, binsize, xmin, ymin)
np.testing.assert_allclose(values, matrix.values)
np.testing.assert_allclose(binsize, matrix.binsize[0])
np.testing.assert_allclose(binsize, matrix.binsize[1])
np.testing.assert_allclose(xmin, matrix.xmin)
np.testing.assert_allclose(ymin, matrix.ymin)
np.testing.assert_allclose(xmin, matrix.minedge[0])
np.testing.assert_allclose(ymin, matrix.minedge[1])
assert "RangeMean" == matrix.matrixtype
def test_zerosrfm_like():
values = np.array([[1, 2, 3], [4, 5, 6], [-1, -2, -3]])
binsize = 1.4
xmin = 1
ymin = -5.2
matrixtype = "FromTo"
matrix = rainfl._rfm(values, binsize, xmin, ymin, matrixtype)
zero_matrix = rainfl.zerosrfm_like(matrix)
np.testing.assert_allclose(np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]]), zero_matrix.values)
np.testing.assert_allclose(binsize, zero_matrix.binsize[0])
np.testing.assert_allclose(binsize, zero_matrix.binsize[1])
np.testing.assert_allclose(xmin, zero_matrix.xmin)
np.testing.assert_allclose(ymin, zero_matrix.ymin)
np.testing.assert_allclose(xmin, zero_matrix.minedge[0])
np.testing.assert_allclose(ymin, zero_matrix.minedge[1])
assert "FromTo" == zero_matrix.matrixtype
def test_onesrfm_like():
values = np.array([[1, 2, 3], [4, 5, 6], [-1, -2, -3]])
binsize = 1.4
xmin = 1
ymin = -5.2
matrixtype = "FromTo"
matrix = rainfl._rfm(values, binsize, xmin, ymin, matrixtype)
zero_matrix = rainfl.zerosrfm_like(matrix)
np.testing.assert_allclose(np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]]), zero_matrix.values)
np.testing.assert_allclose(binsize, zero_matrix.binsize[0])
np.testing.assert_allclose(binsize, zero_matrix.binsize[1])
np.testing.assert_allclose(xmin, zero_matrix.xmin)
np.testing.assert_allclose(ymin, zero_matrix.ymin)
np.testing.assert_allclose(xmin, zero_matrix.minedge[0])
np.testing.assert_allclose(ymin, zero_matrix.minedge[1])
assert "FromTo" == zero_matrix.matrixtype
def test_addrfm():
a = np.random.rand(4, 4)
b = np.random.rand(4, 4)
rfm1 = rainfl.from_to(a, 0.1, -1, 1)
rfm2 = rainfl.from_to(b, 0.1, -1, 1)
result = rainfl.addrfm(rfm1, rfm2)
np.testing.assert_allclose(a + b, result.values)
np.testing.assert_allclose(0.1, result.binsize[0])
np.testing.assert_allclose(-1, result.xmin)
np.testing.assert_allclose(1, result.ymin)
def test_multiplyrfm():
a = np.random.rand(4, 4)
b = np.random.rand(4, 4)
rfm1 = rainfl.from_to(a, 0.1, -1, 1)
rfm2 = rainfl.from_to(b, 0.1, -1, 1)
result = rainfl.mulitplyrfm(rfm1, rfm2)
np.testing.assert_allclose(a * b, result.values)
np.testing.assert_allclose(0.1, result.binsize[0])
np.testing.assert_allclose(-1, result.xmin)
np.testing.assert_allclose(1, result.ymin)
def test_consistency_check():
a = np.random.rand(4, 4)
b = np.random.rand(4, 4)
c = np.random.rand(4, 4)
rfm1 = rainfl.from_to(a, 0.1, -1, 1)
rfm2 = rainfl.from_to(b, 0.1, -1, 2)
rfm3 = rainfl.from_to(c, 0.1, -1, 1)
with pytest.raises(ValueError):
rainfl.consistency_check(rfm1, rfm2, rfm3)
def test_continuous_rainflow():
series = np.array([-2, 1, -3, 5, -1, 3, -4, 4, -2])
meanvals = np.array([-0.5, -1., 1., 1., 1., 0., 0.5])
rangevals = np.array([3, 4, 4, 8, 6, 8, 9])
cyclevals = np.array([0.5, 0.5, 1., 0.5, 0.5, 0.5, 0.5])
res = [5]
ra, mea, cyc, re = rainfl.continuous_rainflow(series)
np.testing.assert_allclose(rangevals, ra)
np.testing.assert_allclose(meanvals, mea)
np.testing.assert_allclose(cyclevals, cyc)
np.testing.assert_allclose(res, re)
if __name__ == '__main__':
pytest.main()
| 36.949153 | 95 | 0.671101 | 992 | 6,540 | 4.290323 | 0.104839 | 0.120536 | 0.200893 | 0.308036 | 0.712406 | 0.679276 | 0.668938 | 0.648731 | 0.630404 | 0.62594 | 0 | 0.049483 | 0.171865 | 6,540 | 176 | 96 | 37.159091 | 0.736337 | 0.005963 | 0 | 0.550336 | 0 | 0 | 0.013545 | 0.005387 | 0 | 0 | 0 | 0 | 0.416107 | 1 | 0.067114 | false | 0 | 0.026846 | 0 | 0.09396 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
6884d1f24b8916b7149ac2fea7212520c8607244 | 206 | py | Python | Exercicios/005-antecessor-sucessor.py | fernandaveiga/Curso-em-Video | ea8956fce6e16cbaa8a83106ffa45071cbdc617e | [
"MIT"
] | null | null | null | Exercicios/005-antecessor-sucessor.py | fernandaveiga/Curso-em-Video | ea8956fce6e16cbaa8a83106ffa45071cbdc617e | [
"MIT"
] | null | null | null | Exercicios/005-antecessor-sucessor.py | fernandaveiga/Curso-em-Video | ea8956fce6e16cbaa8a83106ffa45071cbdc617e | [
"MIT"
] | null | null | null | # 005 - Faça um programa que leia um número inteiro e mostre na tela o seu sucessor e seu antecessor:
num = int(input('Digite um número: '))
print(f'O antecessor de {num} é {num-1} e o sucessor é {num+1}') | 51.5 | 101 | 0.703883 | 40 | 206 | 3.625 | 0.625 | 0.110345 | 0.068966 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029762 | 0.184466 | 206 | 4 | 102 | 51.5 | 0.833333 | 0.480583 | 0 | 0 | 0 | 0.5 | 0.679245 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
688bf2cbda2cbb29740e469320cce1c5b51ca806 | 67 | py | Python | WalletTransition/__init__.py | MasoudHeidary/django-telegram-bot-trade | 7032428e5e04cb02bb081dcc4d86a585a773ada0 | [
"MIT"
] | null | null | null | WalletTransition/__init__.py | MasoudHeidary/django-telegram-bot-trade | 7032428e5e04cb02bb081dcc4d86a585a773ada0 | [
"MIT"
] | null | null | null | WalletTransition/__init__.py | MasoudHeidary/django-telegram-bot-trade | 7032428e5e04cb02bb081dcc4d86a585a773ada0 | [
"MIT"
] | null | null | null | default_app_config = 'WalletTransition.apps.WallettransitionConfig' | 67 | 67 | 0.895522 | 6 | 67 | 9.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029851 | 67 | 1 | 67 | 67 | 0.892308 | 0 | 0 | 0 | 0 | 0 | 0.647059 | 0.647059 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
d799c91469a01ab283047e4b60f84f226de1975f | 1,482 | py | Python | waterpump/pumps/mig_backup/0031_auto_20190816_2301.py | hwan27/WATERPUMP_django | dcc6bf27ae3c0e6ca851e854e51fc512f96eab56 | [
"MIT"
] | null | null | null | waterpump/pumps/mig_backup/0031_auto_20190816_2301.py | hwan27/WATERPUMP_django | dcc6bf27ae3c0e6ca851e854e51fc512f96eab56 | [
"MIT"
] | null | null | null | waterpump/pumps/mig_backup/0031_auto_20190816_2301.py | hwan27/WATERPUMP_django | dcc6bf27ae3c0e6ca851e854e51fc512f96eab56 | [
"MIT"
] | null | null | null | # Generated by Django 2.0.10 on 2019-08-16 14:01
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('pumps', '0030_auto_20190816_2256'),
]
operations = [
migrations.AddField(
model_name='sector',
name='pump_1_operating_rate',
field=models.FloatField(default=12),
preserve_default=False,
),
migrations.AddField(
model_name='sector',
name='pump_2_operating_rate',
field=models.CharField(blank=True, max_length=120),
),
migrations.AddField(
model_name='sector',
name='pump_3_operating_rate',
field=models.CharField(blank=True, max_length=120),
),
migrations.AddField(
model_name='sector',
name='pump_4_operating_rate',
field=models.CharField(blank=True, max_length=120),
),
migrations.AlterField(
model_name='sector',
name='pump_2_freq',
field=models.CharField(blank=True, max_length=120),
),
migrations.AlterField(
model_name='sector',
name='pump_3_freq',
field=models.CharField(blank=True, max_length=120),
),
migrations.AlterField(
model_name='sector',
name='pump_4_freq',
field=models.CharField(blank=True, max_length=120),
),
]
| 29.64 | 63 | 0.569501 | 152 | 1,482 | 5.322368 | 0.328947 | 0.077874 | 0.12979 | 0.1644 | 0.736712 | 0.736712 | 0.729295 | 0.627936 | 0.627936 | 0.572312 | 0 | 0.058416 | 0.318489 | 1,482 | 49 | 64 | 30.244898 | 0.742574 | 0.031039 | 0 | 0.627907 | 1 | 0 | 0.130404 | 0.074616 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.023256 | 0 | 0.093023 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
d79b448ebca9f2b21d455046623172c48c5c3ef0 | 216 | py | Python | mmdet/core/anchor/builder.py | evgps/mmdetection_trashcan | aaf4237c2c0d473425cdc7b741d3009177b79751 | [
"Apache-2.0"
] | 12,377 | 2017-12-04T02:46:57.000Z | 2022-03-31T16:48:31.000Z | mmdet/core/anchor/builder.py | evgps/mmdetection_trashcan | aaf4237c2c0d473425cdc7b741d3009177b79751 | [
"Apache-2.0"
] | 1,851 | 2017-12-05T05:41:23.000Z | 2022-03-30T13:06:22.000Z | mmdet/core/anchor/builder.py | evgps/mmdetection_trashcan | aaf4237c2c0d473425cdc7b741d3009177b79751 | [
"Apache-2.0"
] | 4,198 | 2017-12-05T02:57:19.000Z | 2022-03-30T10:29:37.000Z | from mmcv.utils import Registry, build_from_cfg
ANCHOR_GENERATORS = Registry('Anchor generator')
def build_anchor_generator(cfg, default_args=None):
return build_from_cfg(cfg, ANCHOR_GENERATORS, default_args)
| 27 | 63 | 0.819444 | 30 | 216 | 5.566667 | 0.5 | 0.107784 | 0.143713 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.106481 | 216 | 7 | 64 | 30.857143 | 0.865285 | 0 | 0 | 0 | 0 | 0 | 0.074074 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0.25 | 0.75 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
d7a2de7e7dbcb3b5feb4260b2e64d9689d3988fe | 1,135 | py | Python | tests/kyu_5_tests/test_sum_of_pairs.py | the-zebulan/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 40 | 2016-03-09T12:26:20.000Z | 2022-03-23T08:44:51.000Z | tests/kyu_5_tests/test_sum_of_pairs.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | null | null | null | tests/kyu_5_tests/test_sum_of_pairs.py | akalynych/CodeWars | 1eafd1247d60955a5dfb63e4882e8ce86019f43a | [
"MIT"
] | 36 | 2016-11-07T19:59:58.000Z | 2022-03-31T11:18:27.000Z | import unittest
from katas.kyu_5.sum_of_pairs import sum_pairs
class SumOfPairsTestCase(unittest.TestCase):
def test_equal_1(self):
self.assertEqual(sum_pairs([11, 3, 7, 5], 10), [3, 7])
def test_equal_2(self):
self.assertEqual(sum_pairs([4, 3, 2, 3, 4], 6), [4, 2])
def test_equal_3(self):
self.assertEqual(sum_pairs([10, 5, 2, 3, 7, 5], 10), [3, 7])
def test_equal_4(self):
self.assertEqual(sum_pairs([1, 4, 8, 7, 3, 15], 8), [1, 7])
def test_equal_5(self):
self.assertEqual(sum_pairs([1, -2, 3, 0, -6, 1], -6), [0, -6])
def test_equal_6(self):
self.assertEqual(sum_pairs([1, 2, 3, 4, 1, 0], 2), [1, 1])
def test_equal_7(self):
self.assertEqual(sum_pairs([4, -2, 3, 3, 4], 8), [4, 4])
def test_equal_8(self):
self.assertEqual(sum_pairs([0, 2, 0], 0), [0, 0])
def test_equal_9(self):
self.assertEqual(sum_pairs([5, 9, 13, -3], 10), [13, -3])
def test_is_none_1(self):
self.assertIsNone(sum_pairs([0, 0, -2, 3], 2))
def test_is_none_2(self):
self.assertIsNone(sum_pairs([20, -13, 40], -7))
| 29.102564 | 70 | 0.585903 | 198 | 1,135 | 3.161616 | 0.176768 | 0.153355 | 0.172524 | 0.316294 | 0.552716 | 0.290735 | 0.15655 | 0.15655 | 0.060703 | 0 | 0 | 0.118316 | 0.225551 | 1,135 | 38 | 71 | 29.868421 | 0.593857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.44 | 1 | 0.44 | false | 0 | 0.08 | 0 | 0.56 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
cc00828e7fb8afcfa432a6bc1971a0dae4b142aa | 62 | py | Python | src/retrieve_posts.py | Charcoal-SE/SmokeDetector2 | 02c1b32c05f4c9e44b5a8dd717288d9d567ff13f | [
"Apache-2.0",
"MIT"
] | 7 | 2017-03-29T19:46:55.000Z | 2021-11-11T04:26:25.000Z | src/retrieve_posts.py | Charcoal-SE/SmokeDetector2 | 02c1b32c05f4c9e44b5a8dd717288d9d567ff13f | [
"Apache-2.0",
"MIT"
] | 27 | 2017-03-30T19:22:32.000Z | 2017-04-28T17:09:41.000Z | src/retrieve_posts.py | Charcoal-SE/SmokeDetector2 | 02c1b32c05f4c9e44b5a8dd717288d9d567ff13f | [
"Apache-2.0",
"MIT"
] | 5 | 2017-03-30T18:02:20.000Z | 2021-11-11T04:26:18.000Z | # vim: set filetype=python tabstop=4 shiftwidth=4 expandtab:
| 20.666667 | 60 | 0.774194 | 9 | 62 | 5.333333 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.037037 | 0.129032 | 62 | 2 | 61 | 31 | 0.851852 | 0.935484 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
cc0a952b7488a1363ae4af9f0c2d8759b6c08bf1 | 114 | py | Python | tbx/project_styleguide/apps.py | elviva404/wagtail-torchbox | 718d9e2c4337073f010296932d369c726a01dbd3 | [
"MIT"
] | 103 | 2015-02-24T17:58:21.000Z | 2022-03-23T08:08:58.000Z | tbx/project_styleguide/apps.py | elviva404/wagtail-torchbox | 718d9e2c4337073f010296932d369c726a01dbd3 | [
"MIT"
] | 145 | 2015-01-13T17:13:43.000Z | 2022-03-29T12:56:20.000Z | tbx/project_styleguide/apps.py | elviva404/wagtail-torchbox | 718d9e2c4337073f010296932d369c726a01dbd3 | [
"MIT"
] | 57 | 2015-01-03T12:00:37.000Z | 2022-02-09T13:11:30.000Z | from django.apps import AppConfig
class ProjectStyleguideConfig(AppConfig):
name = "tbx.project_styleguide"
| 19 | 41 | 0.798246 | 12 | 114 | 7.5 | 0.916667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131579 | 114 | 5 | 42 | 22.8 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0.192982 | 0.192982 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
cc1f966beb1ac7200bbdff7b06cf1f51f44ebb6c | 938 | py | Python | donationdb/donations/migrations/0023_auto_20211028_1612.py | emilkauppi/vision.tf.fi | f0d668c6af38bac5575b87d27a1db4ff9864b7de | [
"MIT"
] | null | null | null | donationdb/donations/migrations/0023_auto_20211028_1612.py | emilkauppi/vision.tf.fi | f0d668c6af38bac5575b87d27a1db4ff9864b7de | [
"MIT"
] | null | null | null | donationdb/donations/migrations/0023_auto_20211028_1612.py | emilkauppi/vision.tf.fi | f0d668c6af38bac5575b87d27a1db4ff9864b7de | [
"MIT"
] | null | null | null | # Generated by Django 3.1.7 on 2021-10-28 16:12
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('donations', '0022_auto_20211028_1553'),
]
operations = [
migrations.RemoveField(
model_name='donation',
name='organization_address',
),
migrations.RemoveField(
model_name='donation',
name='organization_city',
),
migrations.RemoveField(
model_name='donation',
name='organization_country',
),
migrations.RemoveField(
model_name='donation',
name='organization_fo_number',
),
migrations.RemoveField(
model_name='donation',
name='organization_name',
),
migrations.RemoveField(
model_name='donation',
name='organization_zip_code',
),
]
| 24.684211 | 49 | 0.558635 | 78 | 938 | 6.5 | 0.474359 | 0.248521 | 0.307692 | 0.35503 | 0.639053 | 0.639053 | 0.639053 | 0 | 0 | 0 | 0 | 0.049919 | 0.337953 | 938 | 37 | 50 | 25.351351 | 0.766506 | 0.047974 | 0 | 0.580645 | 1 | 0 | 0.2211 | 0.074074 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.032258 | 0 | 0.129032 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
cc2273a57e8ede5f98ed2049d6c22c8ef7de3a45 | 482 | py | Python | eventcore/exceptions.py | CasperCL/eventcore | 469724ff189add8055e88a3443d2e08a9e078861 | [
"MIT"
] | null | null | null | eventcore/exceptions.py | CasperCL/eventcore | 469724ff189add8055e88a3443d2e08a9e078861 | [
"MIT"
] | null | null | null | eventcore/exceptions.py | CasperCL/eventcore | 469724ff189add8055e88a3443d2e08a9e078861 | [
"MIT"
] | null | null | null | class ProducerError(Exception):
"""
Exception is thrown when producing fails.
"""
pass
class MissingProducerError(ProducerError):
"""
Exception is thrown when trying to dispatch without a producer.
"""
pass
class ConsumerError(Exception):
"""
Exception is thrown when consuming fails.
"""
pass
class FatalConsumerError(ConsumerError):
"""
Exception is thrown when consuming fails and is irrecoverable.
"""
pass
| 17.214286 | 67 | 0.6639 | 47 | 482 | 6.808511 | 0.446809 | 0.1375 | 0.2125 | 0.2625 | 0.340625 | 0.21875 | 0 | 0 | 0 | 0 | 0 | 0 | 0.253112 | 482 | 27 | 68 | 17.851852 | 0.888889 | 0.435685 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
cc2e423f7c88e99c1116bcb33eab0346458ccc31 | 132 | py | Python | .ycm_extra_conf.py | Steve-Tod/3D_generation | 75817f91f4a69da06375b4401d4182e932102cd1 | [
"Apache-2.0"
] | null | null | null | .ycm_extra_conf.py | Steve-Tod/3D_generation | 75817f91f4a69da06375b4401d4182e932102cd1 | [
"Apache-2.0"
] | null | null | null | .ycm_extra_conf.py | Steve-Tod/3D_generation | 75817f91f4a69da06375b4401d4182e932102cd1 | [
"Apache-2.0"
] | 1 | 2019-07-24T03:35:27.000Z | 2019-07-24T03:35:27.000Z | def Settings(**kwargs):
return {
'interpreter_path':
'/orion/u/jiangthu/anaconda3/envs/tf_py3/bin/python'
}
| 22 | 60 | 0.613636 | 15 | 132 | 5.266667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019802 | 0.234848 | 132 | 5 | 61 | 26.4 | 0.762376 | 0 | 0 | 0 | 0 | 0 | 0.5 | 0.378788 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | true | 0 | 0 | 0.2 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 4 |
0bcdd466643453d4ba9dd49a9427ac307dc91f4b | 36 | py | Python | Grocery.py | CtrlAltDel668/kuroshiro101 | e84b154b7492b144403f5186008911c4c0660f10 | [
"Apache-2.0"
] | null | null | null | Grocery.py | CtrlAltDel668/kuroshiro101 | e84b154b7492b144403f5186008911c4c0660f10 | [
"Apache-2.0"
] | null | null | null | Grocery.py | CtrlAltDel668/kuroshiro101 | e84b154b7492b144403f5186008911c4c0660f10 | [
"Apache-2.0"
] | null | null | null | for x in range (10):
print (x)
| 9 | 21 | 0.527778 | 7 | 36 | 2.714286 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083333 | 0.333333 | 36 | 3 | 22 | 12 | 0.708333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
0bed488a830e6fc584458a93db308cea51da26eb | 4,033 | py | Python | carball/analysis/stats/stats.py | unitedroguegg/carball | 4767f2c5d195b7d5d60e6a5575415262803acef7 | [
"Apache-2.0"
] | 119 | 2018-09-14T02:14:19.000Z | 2022-03-06T05:06:54.000Z | carball/analysis/stats/stats.py | unitedroguegg/carball | 4767f2c5d195b7d5d60e6a5575415262803acef7 | [
"Apache-2.0"
] | 207 | 2018-09-06T18:53:06.000Z | 2022-02-12T22:39:36.000Z | carball/analysis/stats/stats.py | unitedroguegg/carball | 4767f2c5d195b7d5d60e6a5575415262803acef7 | [
"Apache-2.0"
] | 44 | 2018-09-10T16:54:13.000Z | 2022-02-19T03:07:50.000Z | import logging
from typing import Dict
import pandas as pd
from ...generated.api import game_pb2
from ...generated.api.player_pb2 import Player
from ...generated.api.stats.events_pb2 import Hit
from ...generated.api.stats.player_stats_pb2 import PlayerStats
from ...generated.api.stats.team_stats_pb2 import TeamStats
from ...json_parser.game import Game
class BaseStat:
def __init__(self):
self.logger = logging.getLogger(type(self).__name__)
def calculate_stat(self, proto_stat, game: Game, proto_game: game_pb2.Game, player_map: Dict[str, Player],
data_frame: pd.DataFrame):
"""
Calculates stats that applies to the general game or applies to players + teams at the same time.
:param proto_stat: This is protobuf object for general game stats
:param game: The raw data that has been created from python.
:param proto_game: A protobuf that contains some parsed stats + all metadata for the game.
:param player_map: A map of playerId to the protobuf Player object
:param data_frame: The raw frames of the replay this is the same object as `game.frames`
"""
raise NotImplementedError()
def calculate_player_stat(self, player_stat_map: Dict[str, PlayerStats], game: Game, proto_game: game_pb2.Game,
player_map: Dict[str, Player], data_frame: pd.DataFrame):
"""
Calculates stats that only apply to players.
:param player_stat_map: A map of playerId to the specific proto object for stats for that player.
:param game: The raw data that has been created from python.
:param proto_game: A protobuf that contains some parsed stats + all metadata for the game.
:param player_map: A map of playerId to the protobuf Player object
:param data_frame: The raw frames of the replay this is the same object as `game.frames`
"""
raise NotImplementedError()
def calculate_team_stat(self, team_stat_list: Dict[int, TeamStats], game: Game, proto_game: game_pb2.Game,
player_map: Dict[str, Player], data_frame: pd.DataFrame):
"""
Calculate stats that only applies to teams
:param team_stat_list: I map of team id to the specific proto object for stats for that team
:param game: The raw data that has been created from python.
:param proto_game: A protobuf that contains some parsed stats + all metadata for the game.
:param player_map: A map of playerId to the protobuf Player object
:param data_frame: The raw frames of the replay this is the same object as `game.frames`
"""
raise NotImplementedError()
class HitStat:
def initialize_hit_stat(self, game: Game, player_map: Dict[str, Player], data_frame: pd.DataFrame):
"""
Called only once at the beginning of stat creation.
:param game: The raw data that has been created from python.
:param player_map: A map of playerId to the protobuf Player object
:param data_frame: The raw frames of the replay this is the same object as `game.frames`
"""
raise NotImplementedError()
def calculate_next_hit_stat(self, game: Game, proto_game: game_pb2.Game, saltie_hit: Hit, next_saltie_hit: Hit,
player_map: Dict[str, Player], hit_index: int):
"""
Calculate stats that use only the current hit + the next hit.
:param game: The raw data that has been created from python.
:param proto_game: A protobuf that contains some parsed stats + all metadata for the game.
:param saltie_hit: The current hit we are looking at, this is a protobuf object.
:param next_saltie_hit: The hit that occured after the current one.
:param player_map: A map of playerId to the protobuf Player object
:param hit_index: The index in the list of protobuf hits where the current hit is listed.
"""
raise NotImplementedError()
| 51.705128 | 115 | 0.68733 | 585 | 4,033 | 4.611966 | 0.17265 | 0.033358 | 0.022239 | 0.020015 | 0.616383 | 0.598592 | 0.598592 | 0.581913 | 0.581913 | 0.553002 | 0 | 0.002969 | 0.24845 | 4,033 | 77 | 116 | 52.376623 | 0.887166 | 0.53459 | 0 | 0.259259 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.333333 | 0 | 0.62963 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
0413c0a20778a28cb5c959dae98e948b970583aa | 30 | py | Python | language/_experimental/_thing/_util/__init__.py | jedhsu/language | 3772a4a0ff287e1fc5ebefc716b8d91928d04c72 | [
"MIT"
] | null | null | null | language/_experimental/_thing/_util/__init__.py | jedhsu/language | 3772a4a0ff287e1fc5ebefc716b8d91928d04c72 | [
"MIT"
] | null | null | null | language/_experimental/_thing/_util/__init__.py | jedhsu/language | 3772a4a0ff287e1fc5ebefc716b8d91928d04c72 | [
"MIT"
] | null | null | null | """
Utility decorators.
"""
| 5 | 19 | 0.566667 | 2 | 30 | 8.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 30 | 5 | 20 | 6 | 0.708333 | 0.633333 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
0437c7741f2446b362aab03162a0b7fa059afc5f | 77 | py | Python | server.py | syahrulhamdani/disaster-response-pipeline | b5ce11d0c29972120e500e8effecaa9c44f765d7 | [
"MIT"
] | null | null | null | server.py | syahrulhamdani/disaster-response-pipeline | b5ce11d0c29972120e500e8effecaa9c44f765d7 | [
"MIT"
] | null | null | null | server.py | syahrulhamdani/disaster-response-pipeline | b5ce11d0c29972120e500e8effecaa9c44f765d7 | [
"MIT"
] | null | null | null | from apps.routes import app
app.run(host='0.0.0.0', port=3001, debug=True)
| 15.4 | 46 | 0.701299 | 16 | 77 | 3.375 | 0.75 | 0.111111 | 0.111111 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 0.116883 | 77 | 4 | 47 | 19.25 | 0.676471 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
04578116dd0763a6d8225c1383f320ccf513ab37 | 23 | py | Python | data/studio21_generated/introductory/4186/starter_code.py | vijaykumawat256/Prompt-Summarization | 614f5911e2acd2933440d909de2b4f86653dc214 | [
"Apache-2.0"
] | null | null | null | data/studio21_generated/introductory/4186/starter_code.py | vijaykumawat256/Prompt-Summarization | 614f5911e2acd2933440d909de2b4f86653dc214 | [
"Apache-2.0"
] | null | null | null | data/studio21_generated/introductory/4186/starter_code.py | vijaykumawat256/Prompt-Summarization | 614f5911e2acd2933440d909de2b4f86653dc214 | [
"Apache-2.0"
] | null | null | null | def sum_of_threes(n):
| 11.5 | 21 | 0.73913 | 5 | 23 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.130435 | 23 | 2 | 22 | 11.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
f0b215157442d7a62f0dfbc5e7bb6a33474ea742 | 12,104 | py | Python | src/selena/services/migrations/0002_auto__del_field_service_service_not_working_min_probes_count__del_fiel.py | deejay1/selena | 16189ee57c8197ab4375727ef8a905d4f4561eb7 | [
"Apache-2.0"
] | 23 | 2015-01-10T18:17:58.000Z | 2021-12-21T03:01:38.000Z | src/selena/services/migrations/0002_auto__del_field_service_service_not_working_min_probes_count__del_fiel.py | deejay1/selena | 16189ee57c8197ab4375727ef8a905d4f4561eb7 | [
"Apache-2.0"
] | 20 | 2015-01-10T14:05:42.000Z | 2016-08-09T07:48:50.000Z | src/selena/services/migrations/0002_auto__del_field_service_service_not_working_min_probes_count__del_fiel.py | deejay1/selena | 16189ee57c8197ab4375727ef8a905d4f4561eb7 | [
"Apache-2.0"
] | 3 | 2015-01-10T18:27:30.000Z | 2020-04-07T16:17:43.000Z | # -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Deleting field 'Service.service_not_working_min_probes_count'
db.delete_column(u'services_service', 'service_not_working_min_probes_count')
# Deleting field 'Service.performance_issues_min_probes_count'
db.delete_column(u'services_service', 'performance_issues_min_probes_count')
# Adding field 'Service.service_working_min_probes_count'
db.add_column(u'services_service', 'service_working_min_probes_count',
self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=5),
keep_default=False)
def backwards(self, orm):
# Adding field 'Service.service_not_working_min_probes_count'
db.add_column(u'services_service', 'service_not_working_min_probes_count',
self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=8),
keep_default=False)
# Adding field 'Service.performance_issues_min_probes_count'
db.add_column(u'services_service', 'performance_issues_min_probes_count',
self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=8),
keep_default=False)
# Deleting field 'Service.service_working_min_probes_count'
db.delete_column(u'services_service', 'service_working_min_probes_count')
models = {
u'services.additionalrequestparam': {
'Meta': {'object_name': 'AdditionalRequestParam'},
'get': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '250'}),
'post': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}),
'referer': ('django.db.models.fields.URLField', [], {'max_length': '200', 'null': 'True', 'blank': 'True'}),
'service': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Service']"}),
'useragent': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'})
},
u'services.agent': {
'Meta': {'object_name': 'Agent'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}),
'is_main': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}),
'queue': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Queue']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}),
'salt': ('django.db.models.fields.CharField', [], {'max_length': '16'})
},
u'services.monitoredphrase': {
'Meta': {'object_name': 'MonitoredPhrase'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}),
'phrase': ('django.db.models.fields.CharField', [], {'max_length': '250'}),
'service': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Service']"}),
'shall_not_be': ('django.db.models.fields.BooleanField', [], {'default': 'False'})
},
u'services.queue': {
'Meta': {'object_name': 'Queue'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'})
},
u'services.service': {
'Meta': {'ordering': "[u'name']", 'object_name': 'Service'},
'additional_agents': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': u"orm['services.Agent']", 'null': 'True', 'blank': 'True'}),
'auth_method': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_index': 'True'}),
'auth_pass': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}),
'auth_user': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}),
'base_referer': ('django.db.models.fields.URLField', [], {'default': "u''", 'max_length': '200', 'null': 'True', 'blank': 'True'}),
'base_useragent': ('django.db.models.fields.CharField', [], {'default': "u'Mozilla/5.0 (X11; U; Linux x86_64; pl-PL; rv:1.9.2.3) Gecko/20100423 Ubuntu/10.04 (lucid) Firefox/3.6.3'", 'max_length': '250'}),
'comments': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}),
'connection_timeout': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '30'}),
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'hosting': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}),
'is_core_service': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}),
'is_technical_break': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}),
'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'auto_now_add': 'True', 'blank': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '200', 'db_index': 'True'}),
'order': ('django.db.models.fields.PositiveIntegerField', [], {'default': '100'}),
'performance_issues_time': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '15'}),
'response_code': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '200'}),
'sensitivity': ('django.db.models.fields.DecimalField', [], {'default': "'0.5'", 'max_digits': '3', 'decimal_places': '2'}),
'service_working_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '5'}),
'time_delta': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '3'}),
'url': ('django.db.models.fields.URLField', [], {'max_length': '200'})
},
u'services.servicehistory': {
'Meta': {'ordering': "[u'-created']", 'object_name': 'ServiceHistory'},
'agent_id': ('django.db.models.fields.PositiveIntegerField', [], {}),
'connect_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'db_index': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'main_probe': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0', 'db_index': 'True'}),
'namelookup_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'num_connects': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}),
'pretransfer_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'redirect_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}),
'redirect_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'request_params_id': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}),
'response_code': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}),
'response_state': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_index': 'True'}),
'response_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'service_id': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}),
'size_download': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'speed_download': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'starttransfer_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'tick_failed': ('django.db.models.fields.BooleanField', [], {'default': 'False'})
},
u'services.servicehistoryarchive': {
'Meta': {'ordering': "[u'-created']", 'object_name': 'ServiceHistoryArchive'},
'agent_id': ('django.db.models.fields.PositiveIntegerField', [], {}),
'connect_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'created': ('django.db.models.fields.DateTimeField', [], {'db_index': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'namelookup_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'num_connects': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}),
'pretransfer_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'redirect_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}),
'redirect_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}),
'response_time': ('django.db.models.fields.DecimalField', [], {'max_digits': '5', 'decimal_places': '2'}),
'service_id': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}),
'size_download': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'speed_download': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'starttransfer_time': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'})
},
u'services.servicehistoryextra': {
'Meta': {'object_name': 'ServiceHistoryExtra'},
'effective_url': ('django.db.models.fields.URLField', [], {'max_length': '500', 'null': 'True', 'blank': 'True'}),
'error_msg': ('django.db.models.fields.CharField', [], {'max_length': '500', 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'service_history_id': ('django.db.models.fields.BigIntegerField', [], {'db_index': 'True'}),
'wordchecks_errors': ('django.db.models.fields.CharField', [], {'max_length': '500', 'null': 'True', 'blank': 'True'})
}
}
complete_apps = ['services'] | 82.90411 | 216 | 0.58997 | 1,272 | 12,104 | 5.445755 | 0.134434 | 0.098167 | 0.16977 | 0.242529 | 0.82229 | 0.797315 | 0.724412 | 0.685867 | 0.628122 | 0.567345 | 0 | 0.012702 | 0.180436 | 12,104 | 146 | 217 | 82.90411 | 0.685585 | 0.031147 | 0 | 0.299213 | 0 | 0.007874 | 0.585154 | 0.320307 | 0 | 0 | 0 | 0 | 0 | 1 | 0.015748 | false | 0.007874 | 0.031496 | 0 | 0.070866 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
f0b323066656f0790fc19e48ba4944d82214ebaf | 1,090 | py | Python | bcb/utils.py | gcunharodrigues/python-bcb | 1fc28daa0307b33ef005541c9eaab3b6f854c1e4 | [
"MIT"
] | 12 | 2021-12-28T12:30:23.000Z | 2022-03-30T17:20:22.000Z | bcb/utils.py | gcunharodrigues/python-bcb | 1fc28daa0307b33ef005541c9eaab3b6f854c1e4 | [
"MIT"
] | 6 | 2021-12-29T10:08:07.000Z | 2022-02-07T18:55:23.000Z | bcb/utils.py | gcunharodrigues/python-bcb | 1fc28daa0307b33ef005541c9eaab3b6f854c1e4 | [
"MIT"
] | 4 | 2021-05-18T07:13:33.000Z | 2022-01-19T23:00:18.000Z |
from datetime import datetime, date
class Date:
def __init__(self, d=None, format='%Y-%m-%d', mindate=date(1900, 1, 1)):
d = d if d else mindate
if isinstance(d, str):
if d == 'now' or d == 'today':
d = date.today()
else:
d = datetime.strptime(d, format).date()
elif isinstance(d, datetime):
d = d.date()
elif isinstance(d, Date):
d = d.date
elif isinstance(d, date):
pass
else:
raise ValueError()
self.date = d
def format(self, fmts='%Y-%m-%d'):
return datetime.strftime(self.date, fmts)
def __gt__(self, other):
return self.date > other.date
def __ge__(self, other):
return self.date >= other.date
def __lt__(self, other):
return self.date < other.date
def __le__(self, other):
return self.date <= other.date
def __eq__(self, other):
return self.date == other.date
def __repr__(self):
return self.format()
__str__ = __repr__
| 24.222222 | 76 | 0.534862 | 138 | 1,090 | 3.963768 | 0.275362 | 0.102377 | 0.137112 | 0.173675 | 0.411335 | 0.411335 | 0.411335 | 0.319927 | 0 | 0 | 0 | 0.008368 | 0.342202 | 1,090 | 44 | 77 | 24.772727 | 0.754533 | 0 | 0 | 0.060606 | 0 | 0 | 0.022039 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.242424 | false | 0.030303 | 0.030303 | 0.212121 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
f0b8aac48ea83edc98f4f58b750f0e1c7623383f | 2,576 | py | Python | tensorflow_model_analysis/utils/beam_util.py | rtg0795/model-analysis | 0f73989a2dfe1e56548f1ccd0001d98846f89e05 | [
"Apache-2.0"
] | null | null | null | tensorflow_model_analysis/utils/beam_util.py | rtg0795/model-analysis | 0f73989a2dfe1e56548f1ccd0001d98846f89e05 | [
"Apache-2.0"
] | null | null | null | tensorflow_model_analysis/utils/beam_util.py | rtg0795/model-analysis | 0f73989a2dfe1e56548f1ccd0001d98846f89e05 | [
"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, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utilities for working the Apache Beam APIs."""
from typing import Any, Iterable, TypeVar
import apache_beam as beam
_AccumulatorType = TypeVar('_AccumulatorType')
class DelegatingCombineFn(beam.CombineFn):
"""CombineFn which wraps and delegates to another CombineFn.
This is useful as a base class for other CombineFn wrappers that need to do
instance-level overriding. By subclassing DelegatingCombineFn and overriding
only the methods which need to be changed, a subclass can rely on
DelegatingCombineFn to appropriately delegate all of the other CombineFn API
methods. The contract of this base class is that the functionality of
combiner c = MyCombineFn(), will be identical to the behavior of the wrapped
combiner d = DelegatingCombineFn(c).
Note that it is important that this class delegate all of the CombineFn APIs,
as otherwise the contract would be broken and calls to the DelegatingCombineFn
would not be forwarded to the wrapped CombineFn.
TODO(b/194704747): Find ways to mitigate risk of future CombineFn API changes.
"""
def __init__(self, combine_fn: beam.CombineFn):
self._combine_fn = combine_fn
def setup(self, *args, **kwargs):
self._combine_fn.setup(*args, **kwargs)
def create_accumulator(self):
return self._combine_fn.create_accumulator()
def add_input(self, accumulator: _AccumulatorType,
element: Any) -> _AccumulatorType:
return self._combine_fn.add_input(accumulator, element)
def merge_accumulators(
self, accumulators: Iterable[_AccumulatorType]) -> _AccumulatorType:
return self._combine_fn.merge_accumulators(accumulators)
def compact(self, accumulator: _AccumulatorType) -> _AccumulatorType:
return self._combine_fn.compact(accumulator)
def extract_output(self, accumulator: _AccumulatorType) -> _AccumulatorType:
return self._combine_fn.extract_output(accumulator)
def teardown(self, *args, **kwargs):
return self._combine_fn.teardown(*args, **kwargs)
| 39.030303 | 80 | 0.767857 | 347 | 2,576 | 5.582133 | 0.429395 | 0.046464 | 0.060403 | 0.058854 | 0.108931 | 0.091378 | 0.066082 | 0.066082 | 0 | 0 | 0 | 0.007889 | 0.163432 | 2,576 | 65 | 81 | 39.630769 | 0.890951 | 0.550854 | 0 | 0 | 0 | 0 | 0.014427 | 0 | 0 | 0 | 0 | 0.015385 | 0 | 1 | 0.363636 | false | 0 | 0.090909 | 0.272727 | 0.772727 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
f0bcb79f1f0b673aff363ebe39eef1ef648c47e9 | 94 | py | Python | Test_xiao.py | xiao19950825/Phone-elves | 084c3da348ade3a6aea512251f5e807ef2ed2166 | [
"Apache-2.0"
] | null | null | null | Test_xiao.py | xiao19950825/Phone-elves | 084c3da348ade3a6aea512251f5e807ef2ed2166 | [
"Apache-2.0"
] | null | null | null | Test_xiao.py | xiao19950825/Phone-elves | 084c3da348ade3a6aea512251f5e807ef2ed2166 | [
"Apache-2.0"
] | null | null | null |
import sklearn
def add():
pass
print("test git")
print("login")
print('1111111111') | 7.230769 | 19 | 0.638298 | 12 | 94 | 5 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 0.202128 | 94 | 13 | 19 | 7.230769 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0.247312 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | true | 0.166667 | 0.166667 | 0 | 0.333333 | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 4 |
f0c65e4d4c77a9bf5804b3a079ace263611c86bb | 264 | py | Python | day02/hw/yb/exercise4-10.py | zsh2401/hello-python | 6082071335123251cc653cf5667bce02031bb91f | [
"MulanPSL-1.0"
] | 1 | 2020-08-07T12:05:40.000Z | 2020-08-07T12:05:40.000Z | day02/hw/yb/exercise4-10.py | zsh2401/hello-python | 6082071335123251cc653cf5667bce02031bb91f | [
"MulanPSL-1.0"
] | null | null | null | day02/hw/yb/exercise4-10.py | zsh2401/hello-python | 6082071335123251cc653cf5667bce02031bb91f | [
"MulanPSL-1.0"
] | null | null | null | '''
Name:YB
Time:2020.8.6
'''
nums = [1,2,3,4,5,6,7,8,9]
print("Teh first three items in the list are : " + str(nums[:3]))
print("Three items from the middle of the list are : " + str(nums[3:6]))
print("Teh last three items in the list are : " + str(nums[-3:]))
| 26.4 | 73 | 0.617424 | 54 | 264 | 3.018519 | 0.518519 | 0.184049 | 0.184049 | 0.239264 | 0.478528 | 0.478528 | 0.368098 | 0.368098 | 0.368098 | 0 | 0 | 0.087156 | 0.174242 | 264 | 9 | 74 | 29.333333 | 0.66055 | 0.079545 | 0 | 0 | 0 | 0 | 0.53617 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.75 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
f0f5e5b2100c270eb39ea98ebf3a90874f87681b | 53 | py | Python | interface.py | abhi270595/Poker | fe0c94142466b703567fdf99a81df32bfbf12f5c | [
"MIT"
] | null | null | null | interface.py | abhi270595/Poker | fe0c94142466b703567fdf99a81df32bfbf12f5c | [
"MIT"
] | null | null | null | interface.py | abhi270595/Poker | fe0c94142466b703567fdf99a81df32bfbf12f5c | [
"MIT"
] | null | null | null | from game import Game
game = Game( "./input.txt" ) | 17.666667 | 28 | 0.641509 | 8 | 53 | 4.25 | 0.625 | 0.470588 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.207547 | 53 | 3 | 28 | 17.666667 | 0.809524 | 0 | 0 | 0 | 0 | 0 | 0.211538 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
9bc3b1c6c269694a5c854e97363840c90e52e90c | 627 | py | Python | build/lib.linux-x86_64-2.7_ucs4/mx/BeeBase/BeeIndex.py | mkubux/egenix-mx-base | 3e6f9186334d9d73743b0219ae857564c7208247 | [
"eGenix"
] | null | null | null | build/lib.linux-x86_64-2.7_ucs4/mx/BeeBase/BeeIndex.py | mkubux/egenix-mx-base | 3e6f9186334d9d73743b0219ae857564c7208247 | [
"eGenix"
] | null | null | null | build/lib.linux-x86_64-2.7_ucs4/mx/BeeBase/BeeIndex.py | mkubux/egenix-mx-base | 3e6f9186334d9d73743b0219ae857564c7208247 | [
"eGenix"
] | null | null | null | """ BeeIndex - A B++ Tree implementation.
Based on source code published in:
SORTING AND SEARCHING ALGORITHMS: A COOKBOOK
by THOMAS NIEMANN Portland, Oregon
email: thomasn@jps.net
home: http://members.xoom.com/thomasn/s_man.htm
Copyright (c) 1998-2000, Marc-Andre Lemburg; mailto:mal@lemburg.com
Copyright (c) 2000-2015, eGenix.com Software GmbH; mailto:info@egenix.com
See the documentation for further information on copyrights,
or contact the author. All Rights Reserved.
"""
# Import the needed parts from the C extension
from mxBeeBase import *
from mxBeeBase import __version__
| 31.35 | 77 | 0.736842 | 88 | 627 | 5.193182 | 0.761364 | 0.043764 | 0.083151 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031373 | 0.186603 | 627 | 19 | 78 | 33 | 0.864706 | 0.832536 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
9bcc86392d7f7c7935123930940e7b08781ffbb5 | 9,074 | py | Python | tests/api/endpoints/test_upload_links.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 420 | 2015-01-03T11:34:46.000Z | 2022-03-10T07:15:41.000Z | tests/api/endpoints/test_upload_links.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 735 | 2015-01-04T21:22:51.000Z | 2022-03-31T09:26:07.000Z | tests/api/endpoints/test_upload_links.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 379 | 2015-01-05T17:08:03.000Z | 2022-03-06T00:11:50.000Z | # -*- coding: utf-8 -*-
import json
from mock import patch
from dateutil.relativedelta import relativedelta
from django.utils import timezone
from django.urls import reverse
from tests.common.utils import upload_file_test, randstring
from seaserv import seafile_api
from seahub.test_utils import BaseTestCase
from seahub.share.models import UploadLinkShare
from seahub.api2.permissions import CanGenerateUploadLink
try:
from seahub.settings import LOCAL_PRO_DEV_ENV
except ImportError:
LOCAL_PRO_DEV_ENV = False
class UploadLinksTest(BaseTestCase):
def setUp(self):
self.user_name = self.user.username
self.admin_name = self.admin.username
self.repo_id = self.repo.id
self.folder_path= self.folder
self.url = reverse('api-v2.1-upload-links')
def tearDown(self):
self.remove_repo()
def _add_upload_link(self, expire_date=None):
upload_link = UploadLinkShare.objects.create_upload_link_share(self.user_name,
self.repo_id, self.folder_path, None, expire_date=expire_date)
return upload_link.token
def _remove_upload_link(self, token):
link = UploadLinkShare.objects.get(token=token)
link.delete()
def test_get_upload_link(self):
self.login_as(self.user)
token = self._add_upload_link()
resp = self.client.get(self.url + '?path=' + self.folder_path + '&repo_id=' + self.repo_id)
self.assertEqual(200, resp.status_code)
json_resp = json.loads(resp.content)
assert json_resp[0]['link'] is not None
assert json_resp[0]['token'] is not None
assert json_resp[0]['is_expired'] is not None
assert token in json_resp[0]['link']
assert 'u/d' in json_resp[0]['link']
assert token == json_resp[0]['token']
self._remove_upload_link(token)
def test_get_expired_upload_link(self):
self.login_as(self.user)
# create a upload link expired one day ago.
expire_date = timezone.now() + relativedelta(days=-1)
token = self._add_upload_link(expire_date=expire_date)
resp = self.client.get(self.url + '?path=' + self.folder_path + '&repo_id=' + self.repo_id)
self.assertEqual(200, resp.status_code)
json_resp = json.loads(resp.content)
assert json_resp[0]['is_expired'] == True
self._remove_upload_link(token)
@patch.object(CanGenerateUploadLink, 'has_permission')
def test_get_link_with_invalid_user_role_permission(self, mock_has_permission):
self.login_as(self.user)
mock_has_permission.return_value = False
resp = self.client.get(self.url)
self.assertEqual(403, resp.status_code)
def test_create_upload_link(self):
self.login_as(self.user)
resp = self.client.post(self.url, {'path': self.folder_path, 'repo_id': self.repo_id})
self.assertEqual(200, resp.status_code)
json_resp = json.loads(resp.content)
assert json_resp['link'] is not None
assert json_resp['token'] is not None
assert json_resp['token'] in json_resp['link']
assert 'u/d' in json_resp['link']
self._remove_upload_link(json_resp['token'])
@patch.object(CanGenerateUploadLink, 'has_permission')
def test_create_link_with_invalid_user_role_permission(self, mock_has_permission):
self.login_as(self.user)
mock_has_permission.return_value = False
resp = self.client.post(self.url, {'path': self.folder_path, 'repo_id': self.repo_id})
self.assertEqual(403, resp.status_code)
def test_create_link_with_rw_permission_folder(self):
if not LOCAL_PRO_DEV_ENV:
return
self.set_user_folder_rw_permission_to_admin()
# login with admin to create upload link in user's repo
self.login_as(self.admin)
data = {'path': self.folder_path, 'repo_id': self.repo_id}
resp = self.client.post(self.url, data)
self.assertEqual(200, resp.status_code)
def test_create_link_with_rw_permission_folder_in_group(self):
self.share_repo_to_group_with_rw_permission()
self.add_admin_to_group()
# login with admin to create upload link in user's repo
self.login_as(self.admin)
data = {'path': self.folder_path, 'repo_id': self.repo_id}
resp = self.client.post(self.url, data)
self.assertEqual(200, resp.status_code)
def test_can_not_create_link_with_r_permission_folder(self):
if not LOCAL_PRO_DEV_ENV:
return
self.set_user_folder_r_permission_to_admin()
# login with admin to create upload link in user's repo
self.login_as(self.admin)
data = {'path': self.folder_path, 'repo_id': self.repo_id}
resp = self.client.post(self.url, data)
self.assertEqual(403, resp.status_code)
def test_can_not_create_link_with_r_permission_folder_in_group(self):
self.share_repo_to_group_with_r_permission()
self.add_admin_to_group()
# login with admin to create upload link in user's repo
self.login_as(self.admin)
data = {'path': self.folder_path, 'repo_id': self.repo_id}
resp = self.client.post(self.url, data)
self.assertEqual(403, resp.status_code)
def test_delete_upload_link(self):
self.login_as(self.user)
token = self._add_upload_link()
url = reverse('api-v2.1-upload-link', args=[token])
resp = self.client.delete(url, {}, 'application/x-www-form-urlencoded')
self.assertEqual(200, resp.status_code)
json_resp = json.loads(resp.content)
assert json_resp['success'] is True
@patch.object(CanGenerateUploadLink, 'has_permission')
def test_delete_link_with_invalid_user_role_permission(self, mock_has_permission):
token = self._add_upload_link()
self.login_as(self.user)
mock_has_permission.return_value = False
url = reverse('api-v2.1-upload-link', args=[token])
resp = self.client.delete(url, {}, 'application/x-www-form-urlencoded')
self.assertEqual(403, resp.status_code)
def test_delete_link_if_not_owner(self):
self.login_as(self.admin)
token = self._add_upload_link()
url = reverse('api-v2.1-upload-link', args=[token])
resp = self.client.delete(url, {}, 'application/x-www-form-urlencoded')
self.assertEqual(403, resp.status_code)
class UploadLinkUploadTest(BaseTestCase):
def setUp(self):
self.user_name = self.user.username
self.admin_name = self.admin.username
self.repo_id = self.repo.id
self.folder_path= self.folder
self.invalid_token = '00000000000000000000'
def _add_upload_link(self, password=None):
fs = UploadLinkShare.objects.create_upload_link_share(
self.user_name, self.repo_id, self.folder_path, password, None)
return fs.token
def _remove_upload_link(self, token):
link = UploadLinkShare.objects.get(token=token)
link.delete()
def test_get_upload_link(self):
token = self._add_upload_link()
url = reverse('api-v2.1-upload-link-upload', args=[token])
resp = self.client.get(url)
self.assertEqual(200, resp.status_code)
json_resp = json.loads(resp.content)
assert '8082' in json_resp['upload_link']
assert 'upload' in json_resp['upload_link']
# test upload file via `upload_link`
upload_file_test(json_resp['upload_link'], parent_dir=self.folder_path)
self._remove_upload_link(token)
def test_can_not_get_upload_link_with_invalid_token(self):
url = reverse('api-v2.1-upload-link-upload',
args=[self.invalid_token])
resp = self.client.get(url)
self.assertEqual(404, resp.status_code)
def test_can_not_get_upload_link_for_encrypted_upload_link_share(self):
token = self._add_upload_link(password=randstring(10))
url = reverse('api-v2.1-upload-link-upload', args=[token])
resp = self.client.get(url)
self.assertEqual(403, resp.status_code)
def test_can_not_get_upload_link_with_invalid_creator_repo_permission(self):
# user share repo to admin
seafile_api.share_repo(self.repo_id, self.user_name, self.admin_name, 'rw')
# admin create upload link
upload_link = UploadLinkShare.objects.create_upload_link_share(
self.admin_name, self.repo_id, '/', None, None)
token = upload_link.token
# can get url for upload file
url = reverse('api-v2.1-upload-link-upload', args=[token])
resp = self.client.get(url)
self.assertEqual(200, resp.status_code)
# user unshare repo
seafile_api.remove_share(self.repo_id, self.user_name, self.admin_name)
# can not get url for upload file
url = reverse('api-v2.1-upload-link-upload', args=[token])
resp = self.client.get(url)
self.assertEqual(403, resp.status_code)
| 33.732342 | 99 | 0.679524 | 1,261 | 9,074 | 4.616971 | 0.107851 | 0.084164 | 0.034352 | 0.028856 | 0.794744 | 0.764857 | 0.752319 | 0.701477 | 0.663689 | 0.613707 | 0 | 0.014755 | 0.215781 | 9,074 | 268 | 100 | 33.858209 | 0.803401 | 0.048711 | 0 | 0.569767 | 0 | 0 | 0.06973 | 0.029586 | 0 | 0 | 0 | 0 | 0.180233 | 1 | 0.133721 | false | 0.017442 | 0.069767 | 0 | 0.238372 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
9bd0c3a3329fc69a16ffe3eca5ffb5a52da20fe3 | 654 | py | Python | web-app/src/repositories/abstracts/AbcRepository.py | philipp-mos/iubh-quiz-app | 3ea4a6b673bba6df0ece273e17e65c8fe5edc341 | [
"MIT"
] | null | null | null | web-app/src/repositories/abstracts/AbcRepository.py | philipp-mos/iubh-quiz-app | 3ea4a6b673bba6df0ece273e17e65c8fe5edc341 | [
"MIT"
] | 65 | 2021-06-01T15:52:12.000Z | 2021-10-01T15:44:50.000Z | web-app/src/repositories/abstracts/AbcRepository.py | philipp-mos/iubh-quiz-app | 3ea4a6b673bba6df0ece273e17e65c8fe5edc341 | [
"MIT"
] | 1 | 2022-03-29T14:13:45.000Z | 2022-03-29T14:13:45.000Z | from abc import ABC, abstractmethod
class AbcRepository(ABC):
@abstractmethod
def get_all():
raise NotImplementedError
@abstractmethod
def find_by_id(id):
raise NotImplementedError
@abstractmethod
def add_and_commit(item) -> None:
raise NotImplementedError
@abstractmethod
def delete_and_commit(item) -> None:
raise NotImplementedError
@abstractmethod
def add(item) -> None:
raise NotImplementedError
@abstractmethod
def delete(item) -> None:
raise NotImplementedError
@abstractmethod
def commit() -> None:
raise NotImplementedError
| 19.818182 | 40 | 0.671254 | 60 | 654 | 7.2 | 0.333333 | 0.275463 | 0.527778 | 0.569444 | 0.631944 | 0.523148 | 0.409722 | 0.268519 | 0 | 0 | 0 | 0 | 0.264526 | 654 | 32 | 41 | 20.4375 | 0.898129 | 0 | 0 | 0.608696 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.304348 | false | 0 | 0.043478 | 0 | 0.391304 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
9bd251abff14c0e91b9946b9708b769d236acbc4 | 362 | py | Python | python/matrix/matrix.py | whitepeaony/exercism-python | 5c947ba5c589f1969bcb754e88969420262c457e | [
"MIT"
] | null | null | null | python/matrix/matrix.py | whitepeaony/exercism-python | 5c947ba5c589f1969bcb754e88969420262c457e | [
"MIT"
] | 20 | 2019-08-02T13:59:21.000Z | 2022-01-22T10:08:23.000Z | python/matrix/matrix.py | whitepeaony/exercism-python | 5c947ba5c589f1969bcb754e88969420262c457e | [
"MIT"
] | null | null | null | class Matrix(object):
def __init__(self, matrix_string):
self.matrix = []
for i in matrix_string.split('\n'):
b = [int(l) for l in i.split()]
self.matrix.append(b)
def row(self, index):
return self.matrix[index - 1]
def column(self, index):
return [ r[index - 1] for r in self.matrix] | 27.846154 | 51 | 0.546961 | 51 | 362 | 3.764706 | 0.431373 | 0.260417 | 0.15625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00813 | 0.320442 | 362 | 13 | 51 | 27.846154 | 0.772358 | 0 | 0 | 0 | 0 | 0 | 0.00551 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.3 | false | 0 | 0 | 0.2 | 0.6 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
9bd98da2f540920efb003a7b689a2510bdcb13d9 | 61,730 | py | Python | crypto_primitives/slow_hash_lgplv3.py | wkta/ReadableCryptoReader | a09c92a9ac4c526cc4bda1508f661fbaeff4fef4 | [
"MIT"
] | 14 | 2018-05-13T20:15:57.000Z | 2021-09-28T18:12:24.000Z | crypto_primitives/slow_hash_lgplv3.py | ArdeshirV/ReadableCryptoMiner | a09c92a9ac4c526cc4bda1508f661fbaeff4fef4 | [
"MIT"
] | 2 | 2019-05-07T14:19:45.000Z | 2021-08-16T14:10:47.000Z | crypto_primitives/slow_hash_lgplv3.py | ArdeshirV/ReadableCryptoMiner | a09c92a9ac4c526cc4bda1508f661fbaeff4fef4 | [
"MIT"
] | 7 | 2018-07-25T22:42:35.000Z | 2021-12-16T16:50:05.000Z | #!/usr/bin/env python
__author__ = "Patrik Lundin / Thomas Iwaszko"
__copyright__ = "Copyright 2018, nothisispatrik.com"
__license__ = "LGPL v3. Algorithms/constants may be (C) 2014-2018 The Monero project or (C) 2012-2014 The Cryptonote Developers. All code is original"
__email__ = "patrik@nothisispatrik.com / thomas@gaudia-tech.com"
__status__ = "Prototype"
__doc__ = """
This is a Python implementation of the cryptonight slow hash. It includes a
short run_tests() with an example call. It is based on (and was checked against)
the original Monero Project code (https://github.com/monero-project/monero)
with and without the 2018 April hard fork variant.
First version was written for Python 2.7 by Patrik Lundin,
port to Python 3.6 + several tweaks were brought by Thomas Iwaszko (wkta on github)
The cryptonight algorithm remains extremely slow,
around 0.03 hashes per second on a regular i5 CPU.
As such, it's meant more as a consise summary
of the algorithm than usefully runnable code. It's not particularly
optimized, and where possible prior optimization has been removed.
There are no outside dependencies (except "time" which is only used
in the example) with everything reimplemented in pure python, including
AES, Keccak, Blake, Groestl, JH, and Skein.
"""
from functools import reduce
# Single AES round, no round key (can be xor:ed in after)
# Here implemented using TBoxes, which is relativily fast, but
# vulnerable to cache-timing attacks. Not safe for other purposes.
def round(b):
def col(c1, c2, c3, c4):
t = S1[c1] ^ S2[c2] ^ S3[c3] ^ S4[c4]
t1 = t >> 0 & 255
t2 = t >> 8 & 255
t3 = t >> 16 & 255
t4 = t >> 24 & 255
return (
t1, t2, t3, t4)
b = col(b[0], b[5], b[10], b[15]) + col(b[4], b[9], b[14], b[3]) + col(b[8], b[13], b[2], b[7]) + col(b[12], b[1], b[6], b[11])
return b
# AES key expansion.
# Specific to CN:s ten rounds. Presumes that round keys follow
# rc(n+1) = rc(n)<<1, which isn't true generally.
def kexp(k):
xk = [
0] * 160
xk[:32] = k[:32]
cs = 32
rc = 1
while cs < 160:
t = xk[cs - 4:cs]
if cs % 32 == 0:
t = [
SBox[t[1]] ^ rc, SBox[t[2]], SBox[t[3]], SBox[t[0]]]
rc *= 2
else:
if cs % 32 == 16:
t = [
SBox[t[0]], SBox[t[1]], SBox[t[2]], SBox[t[3]]]
xk[cs:(cs + 4)] = [
xk[cs - 32 + 0] ^ t[0],
xk[cs - 32 + 1] ^ t[1],
xk[cs - 32 + 2] ^ t[2],
xk[cs - 32 + 3] ^ t[3]]
cs += 4
return xk
# expand result from initial Keccac into a 2Mb scratchad by
# repeatedly 10 round AES:ing a chunk of data.
def asplode(kec):
xkey = kexp(kec[:32])
st = kec[64:192]
xk = [ xkey[i:i + 16] for i in range(0, len(xkey), 16) ]
pad = []
while len(pad) < 2097152:
for j in range(0, len(st), 16):
t = st[j:j + 16]
for i in range(10):
t = round(t)
t = [ a ^ b for a, b in zip(t, xk[i]) ]
pad.extend(t)
st = pad[-128:]
return pad
# combine final scratchpad into a single block again by xoring and
# then 10 round AESing the blocks over each other one at a time
def implode(pad,kec):
xkey = kexp(kec[32:64])
xk = [ xkey[i:i + 16] for i in range(0, len(xkey), 16) ]
st = kec[64:192]
for p in range(0,len(pad),128):
for i in range(128):
st[i] ^= pad[p+i]
for i in range(0,128,16):
for r in range(10):
st[i:i+16] = round(st[i:i+16])
for j in range(16):
st[i+j] ^= xk[r][j]
kec[64:192] = st
return kec
# Do the memhard loop. Starting two blocks, read another from scratch pad
# do an AES round on it, xor it by some things, write it back. Then use
# a value from that to read another block, do two 64 bit mul:s and two
# 64 bit adds, some more xors, and write that back. Start over and do it
# again 1<<19 times.
def memhrd(pad, kec, variant=0, tw=[0]*8):
# convert a series of bytes into two 64 bit words and multiply them
# return as 8 bytes
def mul(a, b):
t1 = a[0] << 0 | a[1] << 8 | a[2] << 16 | a[3] << 24 | a[4] << 32 | a[5] << 40 | a[6] << 48 | a[7] << 56
t2 = b[0] << 0 | b[1] << 8 | b[2] << 16 | b[3] << 24 | b[4] << 32 | b[5] << 40 | b[6] << 48 | b[7] << 56
r = t1 * t2
r1 = r >> 64
r2 = r & 0xffffffffffffffff
return [ r1&255, (r1>>8)&255, (r1>>16)&255, (r1>>24)&255, (r1>>32)&255, (r1>>40)&255, (r1>>48)&255, (r1>>56)&255, r2&0xff, (r2>>8)&255, (r2>>16)&255,(r2>>24)&255, (r2>>32)&255, (r2>>40)&255, (r2>>48)&255, (r2>>56)&255 ]
# Convert two blocks into four 64 bit numbers and pairwise add them,
# no overflow. Swap order and convert back into bytes
def sumhlf(a, b):
ta1 = a[0] << 0 | a[1] << 8 | a[2] << 16 | a[3] << 24 | a[4] << 32 | a[5] << 40 | a[6] << 48 | a[7] << 56
ta2 = a[8] << 0 | a[9] << 8 | a[10] << 16 | a[11] << 24 | a[12] << 32 | a[13] << 40 | a[14] << 48 | a[15] << 56
tb1 = b[0] << 0 | b[1] << 8 | b[2] << 16 | b[3] << 24 | b[4] << 32 | b[5] << 40 | b[6] << 48 | b[7] << 56
tb2 = b[8] << 0 | b[9] << 8 | b[10] << 16 | b[11] << 24 | b[12] << 32 | b[13] << 40 | b[14] << 48 | b[15] << 56
r1,r2 = (ta1 + tb1 & 18446744073709551615, ta2 + tb2 & 18446744073709551615)
return [ r1&255, (r1>>8)&255, (r1>>16)&255, (r1>>24)&255, (r1>>32)&255, (r1>>40)&255, (r1>>48)&255, (r1>>56)&255, r2&0xff, (r2>>8)&255, (r2>>16)&255,(r2>>24)&255, (r2>>32)&255, (r2>>40)&255, (r2>>48)&255, (r2>>56)&255 ]
# xor two blocks
def blxor(a, b):
return [ t1 ^ t2 for t1, t2 in zip(a, b) ]
# pull 17 bits from a block for use as an address in the scratchpad.
# Zeroes out the 4 LSB rather than dividing, making it useful as an
# index in the pad directly. >>4 instead of &.. would give a block
# index, which could then later be <<4 to give an actual location.
def toaddr(a):
return (a[2] << 16 | a[1] << 8 | a[0]) & 2097136
# make the first two indexes
A = blxor(kec[0:16], kec[32:48])
B = blxor(kec[16:32], kec[48:64])
for i in range(1<<19):
t = toaddr(A)
C = pad[t:t + 16]
C = round(C)
C = blxor(C, A)
pad[t:(t + 16)] = blxor(B, C)
# After the Apr 2018 hardfork, this will be/was
# added to the loop. This is equivalent to VARIANT1_1
# in the original C.
if variant:
a = pad[t+11]
a = (~a&1)<<4 | ((~a&1)<<4 & a)<<1 | (a&32)>>1
pad[t+11] ^= a
B = C
t = toaddr(C)
C = pad[t:t + 16]
P = mul(B, C)
A = sumhlf(A, P)
pad[t:(t + 16)] = A
# this is the second variant add in, equivalent of VARIENT1_2 in
# C.
if variant:
for i in range(8):
pad[t+i+8] ^= tw[i]
A = blxor(A, C)
return pad
# Calculate 1600 bit keccak hash from a 200b input.
# This isn't equivalent to the final SHA3 version.
# I don't remember how exactly, but don't expect it to be.
def keccak(inp):
def rol(b,n):
return ((b<<n) & 0xffffffffffffffff) | (b>>(64-n))
s = [sum(a[i]<<(i<<3) for i in range(8)) for a in [inp[i:i+8] for i in range(0,200,8)]]
xo = [ 0x0000000000000001, 0x0000000000008082, 0x800000000000808a,
0x8000000080008000, 0x000000000000808b, 0x0000000080000001,
0x8000000080008081, 0x8000000000008009, 0x000000000000008a,
0x0000000000000088, 0x0000000080008009, 0x000000008000000a,
0x000000008000808b, 0x800000000000008b, 0x8000000000008089,
0x8000000000008003, 0x8000000000008002, 0x8000000000000080,
0x000000000000800a, 0x800000008000000a, 0x8000000080008081,
0x8000000000008080, 0x0000000080000001, 0x8000000080008008 ]
ro = [ 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 2, 14,
27, 41, 56, 8, 25, 43, 62, 18, 39, 61, 20, 44 ]
pn = [ 10, 7, 11, 17, 18, 3, 5, 16, 8, 21, 24, 4,
15, 23, 19, 13, 12, 2, 20, 14, 22, 9, 6, 1 ]
for r in range(24):
b0 = s[0]^s[5]^s[10]^s[15]^s[20]
b1 = s[1]^s[6]^s[11]^s[16]^s[21]
b2 = s[2]^s[7]^s[12]^s[17]^s[22]
b3 = s[3]^s[8]^s[13]^s[18]^s[23]
b4 = s[4]^s[9]^s[14]^s[19]^s[24]
t = b4 ^ rol(b1,1)
s[0] ^=t ; s[5] ^=t ; s[10] ^=t ; s[15] ^=t ; s[20] ^=t
t = b0 ^ rol(b2,1)
s[1] ^=t ; s[6] ^=t ; s[11] ^=t ; s[16] ^=t ; s[21] ^=t
t = b1 ^ rol(b3,1)
s[2] ^=t ; s[7] ^=t ; s[12] ^=t ; s[17] ^=t ; s[22] ^=t
t = b2 ^ rol(b4,1)
s[3] ^=t ; s[8] ^=t ; s[13] ^=t ; s[18] ^=t ; s[23] ^=t
t = b3 ^ rol(b0,1)
s[4] ^=t ; s[9] ^=t ; s[14] ^=t ; s[19] ^=t ; s[24] ^=t
t = s[1]
for i in range(24):
j = pn[i]
t2 = s[j]
s[j] = rol(t, ro[i])
t = t2
for j in range(0,24,5):
b0 = s[j ];
b1 = s[j + 1];
b2 = s[j + 2];
b3 = s[j + 3];
b4 = s[j + 4];
s[j ] ^= (b1^0xffffffffffffffff) & b2;
s[j + 1] ^= (b2^0xffffffffffffffff) & b3;
s[j + 2] ^= (b3^0xffffffffffffffff) & b4;
s[j + 3] ^= (b4^0xffffffffffffffff) & b0;
s[j + 4] ^= (b0^0xffffffffffffffff) & b1;
s[0] ^= xo[r]
b = reduce(lambda a,b:a+b,[[((a>>(c<<3))&255) for c in range(8)] for a in s])
return b
# Blake hash. Assumes 200b input, produces 32b output
def blake(data):
K=[0x243F6A88,0x85A308D3,0x13198A2E,0x03707344,0xA4093822,0x299F31D0,0x082EFA98,0xEC4E6C89,0x452821E6,0x38D01377,0xBE5466CF,0x34E90C6C,0xC0AC29B7,0xC97C50DD,0x3F84D5B5,0xB5470917]
h=[0x6A09E667,0xBB67AE85,0x3C6EF372,0xA54FF53A,0x510E527F,0x9B05688C,0x1F83D9AB,0x5BE0CD19]
S = blakeS # Constant from bottom of file
data = data+[0x80] + [0x00]*46 + [0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x06,0x40]
for (o,t) in [(0,512), (64,1024), (128,1536), (192,1600)]:
m = [ ((data[o+i+0]<<24))|
((data[o+i+1]<<16))|
((data[o+i+2]<<8))|
((data[o+i+3]<<0)) for i in range(0,64,4)]
v = [0]*16
v[ 0: 8] = [h[i] for i in range(8)]
v[ 8:16] = [K[i] for i in range(8)]
v[ 8:12] = [v[8+i] for i in range(4)]
v[12] = v[12] ^ t
v[13] = v[13] ^ t
ror = lambda x,n: (x >> n) | ((x << (32-n)) & 0xFFFFFFFF)
for round in range(14):
i = 0
for (a, b, c, d) in [
( 0, 4, 8,12), ( 1, 5, 9,13), ( 2, 6,10,14),
( 3, 7,11,15), ( 0, 5,10,15), ( 1, 6,11,12),
( 2, 7, 8,13), ( 3, 4, 9,14) ]:
p,q = S[round][i], S[round][i+1]
i += 2
v[a] = ((v[a] + v[b]) + (m[p] ^ K[q]) ) & 0xFFFFFFFF
v[d] = ror( v[d] ^ v[a], 16)
v[c] = (v[c] + v[d]) & 0xFFFFFFFF
v[b] = ror( v[b] ^ v[c], 12)
v[a] = ((v[a] + v[b]) + (m[q] ^ K[p]) ) & 0xFFFFFFFF
v[d] = ror( v[d] ^ v[a], 8)
v[c] = (v[c] + v[d]) & 0xFFFFFFFF
v[b] = ror( v[b] ^ v[c], 7)
h = [h[i]^v[i]^v[i+8] for i in range(8)]
rv = reduce(lambda a,b:a+b,[[(h[i]>>24)&255, (h[i]>>16)&255, (h[i]>>8)&255, (h[i]>>0)&255] for i in range(8)])
return rv
# Groestl hash. Assumes 200b input, produces 32b output
def groestl(inp):
def col(x,y,i,c0,c1,c2,c3,c4,c5,c6,c7):
T = groestlT # Constant from bottom of file
y[i] = T[0*256+((x[c0]>>0 )&255)] ^ T[1*256+((x[c1]>>8 )&255)] ^ T[2*256+((x[c2]>>16)&255)] ^ T[3*256+((x[c3]>>24)&255)] ^ T[4*256+((x[c4]>>0 )&255)] ^ T[5*256+((x[c5]>>8 )&255)] ^ T[6*256+((x[c6]>>16)&255)] ^ T[7*256+((x[c7]>>24)&255)]
def P(x,y,r):
x[ 0] ^= 0x00000000^r
x[ 2] ^= 0x00000010^r
x[ 4] ^= 0x00000020^r
x[ 6] ^= 0x00000030^r
x[ 8] ^= 0x00000040^r
x[10] ^= 0x00000050^r
x[12] ^= 0x00000060^r
x[14] ^= 0x00000070^r
col(x,y, 0, 0, 2, 4, 6, 9, 11, 13, 15)
col(x,y, 1, 9, 11, 13, 15, 0, 2, 4, 6)
col(x,y, 2, 2, 4, 6, 8, 11, 13, 15, 1)
col(x,y, 3, 11, 13, 15, 1, 2, 4, 6, 8)
col(x,y, 4, 4, 6, 8, 10, 13, 15, 1, 3)
col(x,y, 5, 13, 15, 1, 3, 4, 6, 8, 10)
col(x,y, 6, 6, 8, 10, 12, 15, 1, 3, 5)
col(x,y, 7, 15, 1, 3, 5, 6, 8, 10, 12)
col(x,y, 8, 8, 10, 12, 14, 1, 3, 5, 7)
col(x,y, 9, 1, 3, 5, 7, 8, 10, 12, 14)
col(x,y,10, 10, 12, 14, 0, 3, 5, 7, 9)
col(x,y,11, 3, 5, 7, 9, 10, 12, 14, 0)
col(x,y,12, 12, 14, 0, 2, 5, 7, 9, 11)
col(x,y,13, 5, 7, 9, 11, 12, 14, 0, 2)
col(x,y,14, 14, 0, 2, 4, 7, 9, 11, 13)
col(x,y,15, 7, 9, 11, 13, 14, 0, 2, 4)
def Q(x,y,r):
x[ 0] = x[ 0] ^ 0xffffffff
x[ 1] ^= 0xffffffff^r
x[ 2] = x[ 2] ^ 0xffffffff
x[ 3] ^= 0xefffffff^r
x[ 4] = x[ 4] ^ 0xffffffff
x[ 5] ^= 0xdfffffff^r
x[ 6] = x[ 6] ^ 0xffffffff
x[ 7] ^= 0xcfffffff^r
x[ 8] = x[ 8] ^ 0xffffffff
x[ 9] ^= 0xbfffffff^r
x[10] = x[10] ^ 0xffffffff
x[11] ^= 0xafffffff^r
x[12] = x[12] ^ 0xffffffff
x[13] ^= 0x9fffffff^r
x[14] = x[14] ^ 0xffffffff
x[15] ^= 0x8fffffff^r
col(x,y, 0, 2, 6, 10, 14, 1, 5, 9, 13)
col(x,y, 1, 1, 5, 9, 13, 2, 6, 10, 14)
col(x,y, 2, 4, 8, 12, 0, 3, 7, 11, 15)
col(x,y, 3, 3, 7, 11, 15, 4, 8, 12, 0)
col(x,y, 4, 6, 10, 14, 2, 5, 9, 13, 1)
col(x,y, 5, 5, 9, 13, 1, 6, 10, 14, 2)
col(x,y, 6, 8, 12, 0, 4, 7, 11, 15, 3)
col(x,y, 7, 7, 11, 15, 3, 8, 12, 0, 4)
col(x,y, 8, 10, 14, 2, 6, 9, 13, 1, 5)
col(x,y, 9, 9, 13, 1, 5, 10, 14, 2, 6)
col(x,y,10, 12, 0, 4, 8, 11, 15, 3, 7)
col(x,y,11, 11, 15, 3, 7, 12, 0, 4, 8)
col(x,y,12, 14, 2, 6, 10, 13, 1, 5, 9)
col(x,y,13, 13, 1, 5, 9, 14, 2, 6, 10)
col(x,y,14, 0, 4, 8, 12, 15, 3, 7, 11)
col(x,y,15, 15, 3, 7, 11, 0, 4, 8, 12)
def F(h,m):
Ptmp = [0]*16;
Qtmp = [0]*16;
y = [0]*16;
z = [0]*16;
for i in range(16):
z[i] = m[i]
Ptmp[i] = h[i]^m[i]
Q(z, y, 0x00000000)
Q(y, z, 0x01000000)
Q(z, y, 0x02000000)
Q(y, z, 0x03000000)
Q(z, y, 0x04000000)
Q(y, z, 0x05000000)
Q(z, y, 0x06000000)
Q(y, z, 0x07000000)
Q(z, y, 0x08000000)
Q(y, Qtmp, 0x09000000)
P(Ptmp, y, 0x00000000)
P(y, z, 0x00000001)
P(z, y, 0x00000002)
P(y, z, 0x00000003)
P(z, y, 0x00000004)
P(y, z, 0x00000005)
P(z, y, 0x00000006)
P(y, z, 0x00000007)
P(z, y, 0x00000008)
P(y, Ptmp, 0x00000009)
for i in range(16):
h[i] ^= Ptmp[i]^Qtmp[i]
buf = [0]*16
tmp = [0]*16
y = [0]*16
z = [0]*16
d = [0]*16
d[15] = 0x00010000
data = [
(inp[i+3]<<24)| (inp[i+2]<<16)| (inp[i+1]<<8)| (inp[i+0]<<0)
for i in range(0,len(inp),4) ] + [0x80] + [0]*12 + [4<<24]
F(d,data[0:16])
F(d,data[16:32])
F(d,data[32:48])
F(d,data[48:64])
tmp = d[:16]
P(tmp, y, 0x00000000)
P(y, z, 0x00000001)
P(z, y, 0x00000002)
P(y, z, 0x00000003)
P(z, y, 0x00000004)
P(y, z, 0x00000005)
P(z, y, 0x00000006)
P(y, z, 0x00000007)
P(z, y, 0x00000008)
P(y, tmp, 0x00000009)
rv = [d[j] ^ tmp[j] for j in range(8,16)]
rv = reduce(lambda a,b:a+b,[[a&255,(a>>8)&255, (a>>16)&255, (a>>24)&255] for a in rv])
return rv
# JH hash, Assumes 200b input, produces 32b output
def jh(data):
hashval = [32]
A = [0]*256
rc = [0]*64
rcx = [0]*256
tmp = [0]*256
S = [[9,0,4,11,13,12,3,15,1,10,2,6,7,5,8,14],[3,12,6,13,5,7,1,9,15,2,0,4,11,10,14,8]]
rc0 = [0x6,0xa,0x0,0x9,0xe,0x6,0x6,0x7,0xf,0x3,0xb,0xc,0xc,0x9,0x0,0x8,0xb,0x2,0xf,0xb,0x1,0x3,0x6,0x6,0xe,0xa,0x9,0x5,0x7,0xd,0x3,0xe,0x3,0xa,0xd,0xe,0xc,0x1,0x7,0x5,0x1,0x2,0x7,0x7,0x5,0x0,0x9,0x9,0xd,0xa,0x2,0xf,0x5,0x9,0x0,0xb,0x0,0x6,0x6,0x7,0x3,0x2,0x2,0xa]
d = [254,0,64,128,255,254]
H = [1]+[0]*127
for b in d:
if b<=128:
for i in range(64):
H[i] ^= data[b+i]
elif b==255:
H[:8] = [H[i]^data[192+i] for i in range(8)]
H[8] ^= 128
rc = rc0[:]
for i in range(256):
t0 = (H[i>>3] >> (7 - (i & 7)) ) & 1
t1 = (H[(i+256)>>3] >> (7 - (i & 7)) ) & 1
t2 = (H[(i+512 )>>3] >> (7 - (i & 7)) ) & 1
t3 = (H[(i+768 )>>3] >> (7 - (i & 7)) ) & 1
tmp[i] = (t0 << 3) | (t1 << 2) | (t2 << 1) | (t3 << 0)
for i in range(128):
A[i << 1] = tmp[i]
A[(i << 1)+1] = tmp[i+128]
for r in range(42):
for i in range(256):
rcx[i] = (rc[i >> 2] >> (3 - (i & 3)) ) & 1
for i in range(256):
tmp[i] = S[rcx[i]][A[i]]
for i in range(0,256,2):
t0 = tmp[i+1]^(((tmp[i]<<1)^(tmp[i]>>3)^((tmp[i]>>2)&2))&0xf)
t1 = tmp[i+0]^(((t0<<1)^(t0>>3)^((t0>>2)&2))&0xf)
t2 = (i>>1)&1
tmp[i+t2^1] = t0
tmp[i+t2] = t1
for i in range(128):
A[i] = tmp[i<<1]
A[(i+128)^1] = tmp[(i<<1)+1]
for i in range(64):
tmp[i] = S[0][rc[i]]
for i in range(0,64,2):
tmp[i+1] ^= ((tmp[i]<<1)^(tmp[i]>>3)^((tmp[i]>>2)&2))&0xf
tmp[i] ^= ((tmp[i+1]<<1)^(tmp[i+1]>>3)^((tmp[i+1]>>2)&2))&0xf
for i in range(0,64,4):
t = tmp[i+2]
tmp[i+2] = tmp[i+3]
tmp[i+3] = t
for i in range(32):
rc[i] = tmp[i<<1]
rc[(i+32)^1] = tmp[(i<<1)+1]
for i in range(128):
tmp[i] = A[i << 1]
tmp[i+128] = A[(i << 1)+1]
for i in range(128):
H[i] = 0
for i in range(256):
t0 = (tmp[i] >> 3) & 1
t1 = (tmp[i] >> 2) & 1
t2 = (tmp[i] >> 1) & 1
t3 = (tmp[i] >> 0) & 1
H[i>>3] |= t0 << (7 - (i & 7))
H[(i + 256)>>3] |= t1 << (7 - (i & 7))
H[(i + 512)>>3] |= t2 << (7 - (i & 7))
H[(i + 768)>>3] |= t3 << (7 - (i & 7))
if b<=128:
for i in range(64):
H[i+64] ^= data[b+i]
elif(b==255):
for i in range(8):
H[64+i] ^= data[192+i]
H[8+64] ^= 128
H[63] ^= 64
H[62] ^= 6
H[127] ^= 64
H[126] ^= 6
return H[96:]
# Skein hash. Assumes 200b input, produces 32b output
def skein(data):
def M(x): # Mask down to 64 bin
return x & 0xffffffffffffffff
def R64(x, p, n): # Rotate left, 64 bit
x[p] = M((x[p] << n) | (x[p] >> (64-n)))
def Add(x, a, b): # 64 bit add, no overflow
x[a] = M(x[a]+x[b])
def R512(X,p0,p1,p2,p3,p4,p5,p6,p7,q):
Rk = [ [46, 36, 19, 37], [33, 27, 14, 42], [17, 49, 36, 39], [44, 9, 54, 56], [39, 30, 34, 24], [13, 50, 10, 17], [25, 29, 39, 43], [ 8, 35, 56, 22]]
Add(X,p0,p1)
R64(X,p1,Rk[q][0])
X[p1] ^= X[p0]
Add(X,p2,p3)
R64(X,p3,Rk[q][1])
X[p3] ^= X[p2]
Add(X,p4,p5)
R64(X,p5,Rk[q][2])
X[p5] ^= X[p4]
Add(X,p6,p7)
R64(X,p7,Rk[q][3])
X[p7] ^= X[p6]
# Skein types and lengths. Since it's just five blocks, always
# same length and such, they're constant. Here as TYPE | LEN,
# as it is stored in Skeins T(2)
LC = [ 0x7000000000000040, 0x3000000000000080, 0x30000000000000c0,
0xb0000000000000c8, 0xff00000000000008 ]
# Init vector. Specific to 512-256 hash
L = [ 0,0,0, 0xCCD044A12FDB3E13, 0xE83590301A79A9EB,
0x55AEA0614F816E6F, 0x2A2767A4AE9B94DB, 0xEC06025E74DD7683,
0xE7A436CDC4746251, 0xC36FBAF9393AD185, 0x3EEDBA1833EDFC13, 0]
# Keeper of data. Extra length so that after the 200b we send,
# there's enough zeros for another full block, and, for the
# OUT+FINAL block, one with all zeros.
b = [0]*35
# Offset to current data. Hops around
w = 0
# Temp state data
X = [0]*8;
# fill b up with 8b words
for i in range(25):
b[i] = (
(data[(i*8)+0]<<0)|
(data[(i*8)+1]<<8)|
(data[(i*8)+2]<<16)|
(data[(i*8)+3]<<24)|
(data[(i*8)+4]<<32)|
(data[(i*8)+5]<<40)|
(data[(i*8)+6]<<48)|
(data[(i*8)+7]<<56))
# Each block..
for i in range(5):
# T2 = T1^T0, like we stored
L[2] = LC[i]
# T0 = length. Extract with &0xff
L[0] = L[2]&255;
# T2 = type+flags. Exract by removing T0
L[1] = L[2]^L[0];
# Parity + magic constant.
L[11] = L[3]^L[4]^L[5]^L[6]^L[7]^L[8]^L[9]^L[10]^0x1BD11BDAA9FC1A22;
# Next chunk
w = ((i&3)<<3)+25*(i>>2);
# Init X
for R in range(8):
X[R]= M(b[w+R] + L[R+3])
X[5]=M(X[5]+L[0])
X[6]=M(X[6]+L[1])
# Rounds
for R in range(0,18,2):
R512(X,0,1,2,3,4,5,6,7,0)
R512(X,2,1,4,7,6,5,0,3,1)
R512(X,4,1,6,3,0,5,2,7,2)
R512(X,6,1,0,7,2,5,4,3,3)
for j in range(8):
X[j] = M(X[j]+L[3+((R+j+1)%9)])
X[5] = M(X[5]+L[(R+1)%3])
X[6] = M(X[6]+L[(R+2)%3])
X[7] = M(X[7]+R+1)
R512(X,0,1,2,3,4,5,6,7,4)
R512(X,2,1,4,7,6,5,0,3,5)
R512(X,4,1,6,3,0,5,2,7,6)
R512(X,6,1,0,7,2,5,4,3,7)
for j in range(8):
X[j] = M(X[j]+L[3+((R+j+2)%9)])
X[5] = M(X[5]+L[(R+2)%3])
X[6] = M(X[6]+L[(R+3)%3])
X[7] = M(X[7]+R+2)
# Back into state w/ round results
for R in range(8):
L[3+R] = X[R] ^ b[w+R]
# Done, convert to bytes and shove into h
h = []
for i in range(4):
h.extend( [
(L[i+3]>>0)&255,
(L[i+3]>>8)&255,
(L[i+3]>>16)&255,
(L[i+3]>>24)&255,
(L[i+3]>>32)&255,
(L[i+3]>>40)&255,
(L[i+3]>>48)&255,
(L[i+3]>>56)&255] )
return h
# All of the preceeding hash functions are de-generalized to presume
# input length and to only produce specific output length. The will not
# function correctly under other circumstances.
# The main cryptonight hash function. Takes 76 bytes input (without
# verifying that) and outputs the final 32 byte hash. Both input
# and output are arrays of 8 bit integers. If "quiet" is set False,
# it'll print what it's doing through off and on the steps. If
# "variant" is set to 1, it'll work as it's supposed to after the
# Apr 2018 hard fork, otherwise as it's supposed to before.
def cn_slow_hash(inp,quiet=0,variant=0):
tw = [0]*8
if(not quiet):
print("Keccac..")
# Padding
inp = inp + [0x01] + [0x00]*58 + [0x80] + [0x00]*64
kec = keccak(inp)
# Equivalent to VARIANT*INIT* in C. Stores the last 8 bytes after
# keccak xor the current Nonce, which will later be xored in thoughout
# the memhard loop (in the equivalent of VARIANT1_2).
if variant:
tw = [a^b for (a,b) in zip(kec[192:],inp[35:35+8])]
if(not quiet):
print("Expanding scratchpad..")
pad = asplode(kec)
if(not quiet):
print("Memhard..")
memhrd(pad, kec, variant, tw)
if(not quiet):
print("Imploding..")
imp = implode(pad, kec)
if(not quiet):
print("Keccac again..")
kec = keccak(imp)
h = kec[0]&3
if h==0:
if(not quiet):
print("Blake..")
r = blake(kec)
elif h==1:
if(not quiet):
print("Groestl..")
r = groestl(kec)
elif h==2:
if(not quiet):
print("Jh..")
r = jh(kec)
else:
if(not quiet):
print("Skein..")
r = skein(kec)
return r
def slow_hash_glue_func(output_buffer, inp_data_intli_form, input_len):
tmp_res = cn_slow_hash(inp_data_intli_form, quiet=1, variant=1)
for k in range(len(output_buffer)): # regular copy
output_buffer[k] = tmp_res[k]
import time # only used in main
# run_tests(). This runs a single case and checks it against one of two
# precalculated results depending on "variant". This isn't particularly
# sufficient for testing it, but it's at least a single runnable example
def run_tests():
inp = [
0x05, 0x05, 0x84, 0xe2, 0xfa, 0xcc, 0x05, 0xfe,
0x5c, 0x31, 0x96, 0xe9, 0x95, 0xae, 0x88, 0x31,
0x0b, 0xa8, 0x6e, 0xae, 0x4a, 0xb6, 0x25, 0xab,
0xd2, 0x6e, 0x19, 0x2f, 0x26, 0xf3, 0x2c, 0x7d,
0xcb, 0x6d, 0xb1, 0xd1, 0x08, 0xd7, 0x68, 0x5d,
0x00, 0x08, 0x57, 0xd6, 0x62, 0xea, 0x60, 0x02,
0xe5, 0x19, 0xa2, 0x76, 0xb9, 0xd6, 0x9a, 0xb9,
0xf0, 0xdf, 0x14, 0xc9, 0xf5, 0x86, 0xe1, 0x1a,
0xe4, 0x57, 0xb1, 0xb5, 0x74, 0x05, 0xaf, 0xbf,
0x9c, 0xc0, 0xcb, 0x06 ]
st = time.time()
variant = 1 # change to run other version
r = cn_slow_hash(inp, False, variant)
et = time.time()
print(' '.join("%.2x"%(a) for a in r))
print("Total %ds (%f H/s)"%(et-st, 1./(et-st)))
correct_result_old = [0x2a,0x26,0x47,0x75,0x7c,0xf6,0x20,0xa9,0x9a,0xf4,0xf8,0x3f,0xe5,0x9f,0x98,0x5d,0x3e,0x3b,0x8d,0x63,0xa7,0x5e,0x01,0x20,0x75,0x6f,0x8b,0xff,0xa4,0x8e,0x00,0x00]
correct_result_new = [0xfc,0x24,0x23,0x8f,0x96,0x0c,0x14,0x72,0x73,0x86,0x29,0x5b,0xd0,0xfc,0xec,0xba,0xce,0x8f,0x2a,0xef,0x74,0xad,0x71,0x08,0x77,0x1c,0x7c,0x83,0x2b,0x0a,0x9f,0x00]
if variant:
print("Pass" if correct_result_new==r else "Fail")
else:
print("Pass" if correct_result_old==r else "Fail")
# Constants ahoy!
# Tboxes, Sbox (generated from TBox), Blake and Groestl constant lists
# Other constants are sprinkled thought their respective functions, these
# are here to somewhat improve readabillity.
# There's nothing below them besides the if __name__.. to call main
S1 = [0xa56363c6,0x847c7cf8,0x997777ee,0x8d7b7bf6,0x0df2f2ff,0xbd6b6bd6,0xb16f6fde,0x54c5c591,0x50303060,0x03010102,0xa96767ce,0x7d2b2b56,0x19fefee7,0x62d7d7b5,0xe6abab4d,0x9a7676ec,0x45caca8f,0x9d82821f,0x40c9c989,0x877d7dfa,0x15fafaef,0xeb5959b2,0xc947478e,0x0bf0f0fb,0xecadad41,0x67d4d4b3,0xfda2a25f,0xeaafaf45,0xbf9c9c23,0xf7a4a453,0x967272e4,0x5bc0c09b,0xc2b7b775,0x1cfdfde1,0xae93933d,0x6a26264c,0x5a36366c,0x413f3f7e,0x02f7f7f5,0x4fcccc83,0x5c343468,0xf4a5a551,0x34e5e5d1,0x08f1f1f9,0x937171e2,0x73d8d8ab,0x53313162,0x3f15152a,0x0c040408,0x52c7c795,0x65232346,0x5ec3c39d,0x28181830,0xa1969637,0x0f05050a,0xb59a9a2f,0x0907070e,0x36121224,0x9b80801b,0x3de2e2df,0x26ebebcd,0x6927274e,0xcdb2b27f,0x9f7575ea,0x1b090912,0x9e83831d,0x742c2c58,0x2e1a1a34,0x2d1b1b36,0xb26e6edc,0xee5a5ab4,0xfba0a05b,0xf65252a4,0x4d3b3b76,0x61d6d6b7,0xceb3b37d,0x7b292952,0x3ee3e3dd,0x712f2f5e,0x97848413,0xf55353a6,0x68d1d1b9,0x00000000,0x2cededc1,0x60202040,0x1ffcfce3,0xc8b1b179,0xed5b5bb6,0xbe6a6ad4,0x46cbcb8d,0xd9bebe67,0x4b393972,0xde4a4a94,0xd44c4c98,0xe85858b0,0x4acfcf85,0x6bd0d0bb,0x2aefefc5,0xe5aaaa4f,0x16fbfbed,0xc5434386,0xd74d4d9a,0x55333366,0x94858511,0xcf45458a,0x10f9f9e9,0x06020204,0x817f7ffe,0xf05050a0,0x443c3c78,0xba9f9f25,0xe3a8a84b,0xf35151a2,0xfea3a35d,0xc0404080,0x8a8f8f05,0xad92923f,0xbc9d9d21,0x48383870,0x04f5f5f1,0xdfbcbc63,0xc1b6b677,0x75dadaaf,0x63212142,0x30101020,0x1affffe5,0x0ef3f3fd,0x6dd2d2bf,0x4ccdcd81,0x140c0c18,0x35131326,0x2fececc3,0xe15f5fbe,0xa2979735,0xcc444488,0x3917172e,0x57c4c493,0xf2a7a755,0x827e7efc,0x473d3d7a,0xac6464c8,0xe75d5dba,0x2b191932,0x957373e6,0xa06060c0,0x98818119,0xd14f4f9e,0x7fdcdca3,0x66222244,0x7e2a2a54,0xab90903b,0x8388880b,0xca46468c,0x29eeeec7,0xd3b8b86b,0x3c141428,0x79dedea7,0xe25e5ebc,0x1d0b0b16,0x76dbdbad,0x3be0e0db,0x56323264,0x4e3a3a74,0x1e0a0a14,0xdb494992,0x0a06060c,0x6c242448,0xe45c5cb8,0x5dc2c29f,0x6ed3d3bd,0xefacac43,0xa66262c4,0xa8919139,0xa4959531,0x37e4e4d3,0x8b7979f2,0x32e7e7d5,0x43c8c88b,0x5937376e,0xb76d6dda,0x8c8d8d01,0x64d5d5b1,0xd24e4e9c,0xe0a9a949,0xb46c6cd8,0xfa5656ac,0x07f4f4f3,0x25eaeacf,0xaf6565ca,0x8e7a7af4,0xe9aeae47,0x18080810,0xd5baba6f,0x887878f0,0x6f25254a,0x722e2e5c,0x241c1c38,0xf1a6a657,0xc7b4b473,0x51c6c697,0x23e8e8cb,0x7cdddda1,0x9c7474e8,0x211f1f3e,0xdd4b4b96,0xdcbdbd61,0x868b8b0d,0x858a8a0f,0x907070e0,0x423e3e7c,0xc4b5b571,0xaa6666cc,0xd8484890,0x05030306,0x01f6f6f7,0x120e0e1c,0xa36161c2,0x5f35356a,0xf95757ae,0xd0b9b969,0x91868617,0x58c1c199,0x271d1d3a,0xb99e9e27,0x38e1e1d9,0x13f8f8eb,0xb398982b,0x33111122,0xbb6969d2,0x70d9d9a9,0x898e8e07,0xa7949433,0xb69b9b2d,0x221e1e3c,0x92878715,0x20e9e9c9,0x49cece87,0xff5555aa,0x78282850,0x7adfdfa5,0x8f8c8c03,0xf8a1a159,0x80898909,0x170d0d1a,0xdabfbf65,0x31e6e6d7,0xc6424284,0xb86868d0,0xc3414182,0xb0999929,0x772d2d5a,0x110f0f1e,0xcbb0b07b,0xfc5454a8,0xd6bbbb6d,0x3a16162c]
S2 = [0x6363c6a5,0x7c7cf884,0x7777ee99,0x7b7bf68d,0xf2f2ff0d,0x6b6bd6bd,0x6f6fdeb1,0xc5c59154,0x30306050,0x01010203,0x6767cea9,0x2b2b567d,0xfefee719,0xd7d7b562,0xabab4de6,0x7676ec9a,0xcaca8f45,0x82821f9d,0xc9c98940,0x7d7dfa87,0xfafaef15,0x5959b2eb,0x47478ec9,0xf0f0fb0b,0xadad41ec,0xd4d4b367,0xa2a25ffd,0xafaf45ea,0x9c9c23bf,0xa4a453f7,0x7272e496,0xc0c09b5b,0xb7b775c2,0xfdfde11c,0x93933dae,0x26264c6a,0x36366c5a,0x3f3f7e41,0xf7f7f502,0xcccc834f,0x3434685c,0xa5a551f4,0xe5e5d134,0xf1f1f908,0x7171e293,0xd8d8ab73,0x31316253,0x15152a3f,0x0404080c,0xc7c79552,0x23234665,0xc3c39d5e,0x18183028,0x969637a1,0x05050a0f,0x9a9a2fb5,0x07070e09,0x12122436,0x80801b9b,0xe2e2df3d,0xebebcd26,0x27274e69,0xb2b27fcd,0x7575ea9f,0x0909121b,0x83831d9e,0x2c2c5874,0x1a1a342e,0x1b1b362d,0x6e6edcb2,0x5a5ab4ee,0xa0a05bfb,0x5252a4f6,0x3b3b764d,0xd6d6b761,0xb3b37dce,0x2929527b,0xe3e3dd3e,0x2f2f5e71,0x84841397,0x5353a6f5,0xd1d1b968,0x00000000,0xededc12c,0x20204060,0xfcfce31f,0xb1b179c8,0x5b5bb6ed,0x6a6ad4be,0xcbcb8d46,0xbebe67d9,0x3939724b,0x4a4a94de,0x4c4c98d4,0x5858b0e8,0xcfcf854a,0xd0d0bb6b,0xefefc52a,0xaaaa4fe5,0xfbfbed16,0x434386c5,0x4d4d9ad7,0x33336655,0x85851194,0x45458acf,0xf9f9e910,0x02020406,0x7f7ffe81,0x5050a0f0,0x3c3c7844,0x9f9f25ba,0xa8a84be3,0x5151a2f3,0xa3a35dfe,0x404080c0,0x8f8f058a,0x92923fad,0x9d9d21bc,0x38387048,0xf5f5f104,0xbcbc63df,0xb6b677c1,0xdadaaf75,0x21214263,0x10102030,0xffffe51a,0xf3f3fd0e,0xd2d2bf6d,0xcdcd814c,0x0c0c1814,0x13132635,0xececc32f,0x5f5fbee1,0x979735a2,0x444488cc,0x17172e39,0xc4c49357,0xa7a755f2,0x7e7efc82,0x3d3d7a47,0x6464c8ac,0x5d5dbae7,0x1919322b,0x7373e695,0x6060c0a0,0x81811998,0x4f4f9ed1,0xdcdca37f,0x22224466,0x2a2a547e,0x90903bab,0x88880b83,0x46468cca,0xeeeec729,0xb8b86bd3,0x1414283c,0xdedea779,0x5e5ebce2,0x0b0b161d,0xdbdbad76,0xe0e0db3b,0x32326456,0x3a3a744e,0x0a0a141e,0x494992db,0x06060c0a,0x2424486c,0x5c5cb8e4,0xc2c29f5d,0xd3d3bd6e,0xacac43ef,0x6262c4a6,0x919139a8,0x959531a4,0xe4e4d337,0x7979f28b,0xe7e7d532,0xc8c88b43,0x37376e59,0x6d6ddab7,0x8d8d018c,0xd5d5b164,0x4e4e9cd2,0xa9a949e0,0x6c6cd8b4,0x5656acfa,0xf4f4f307,0xeaeacf25,0x6565caaf,0x7a7af48e,0xaeae47e9,0x08081018,0xbaba6fd5,0x7878f088,0x25254a6f,0x2e2e5c72,0x1c1c3824,0xa6a657f1,0xb4b473c7,0xc6c69751,0xe8e8cb23,0xdddda17c,0x7474e89c,0x1f1f3e21,0x4b4b96dd,0xbdbd61dc,0x8b8b0d86,0x8a8a0f85,0x7070e090,0x3e3e7c42,0xb5b571c4,0x6666ccaa,0x484890d8,0x03030605,0xf6f6f701,0x0e0e1c12,0x6161c2a3,0x35356a5f,0x5757aef9,0xb9b969d0,0x86861791,0xc1c19958,0x1d1d3a27,0x9e9e27b9,0xe1e1d938,0xf8f8eb13,0x98982bb3,0x11112233,0x6969d2bb,0xd9d9a970,0x8e8e0789,0x949433a7,0x9b9b2db6,0x1e1e3c22,0x87871592,0xe9e9c920,0xcece8749,0x5555aaff,0x28285078,0xdfdfa57a,0x8c8c038f,0xa1a159f8,0x89890980,0x0d0d1a17,0xbfbf65da,0xe6e6d731,0x424284c6,0x6868d0b8,0x414182c3,0x999929b0,0x2d2d5a77,0x0f0f1e11,0xb0b07bcb,0x5454a8fc,0xbbbb6dd6,0x16162c3a]
S3 = [0x63c6a563,0x7cf8847c,0x77ee9977,0x7bf68d7b,0xf2ff0df2,0x6bd6bd6b,0x6fdeb16f,0xc59154c5,0x30605030,0x01020301,0x67cea967,0x2b567d2b,0xfee719fe,0xd7b562d7,0xab4de6ab,0x76ec9a76,0xca8f45ca,0x821f9d82,0xc98940c9,0x7dfa877d,0xfaef15fa,0x59b2eb59,0x478ec947,0xf0fb0bf0,0xad41ecad,0xd4b367d4,0xa25ffda2,0xaf45eaaf,0x9c23bf9c,0xa453f7a4,0x72e49672,0xc09b5bc0,0xb775c2b7,0xfde11cfd,0x933dae93,0x264c6a26,0x366c5a36,0x3f7e413f,0xf7f502f7,0xcc834fcc,0x34685c34,0xa551f4a5,0xe5d134e5,0xf1f908f1,0x71e29371,0xd8ab73d8,0x31625331,0x152a3f15,0x04080c04,0xc79552c7,0x23466523,0xc39d5ec3,0x18302818,0x9637a196,0x050a0f05,0x9a2fb59a,0x070e0907,0x12243612,0x801b9b80,0xe2df3de2,0xebcd26eb,0x274e6927,0xb27fcdb2,0x75ea9f75,0x09121b09,0x831d9e83,0x2c58742c,0x1a342e1a,0x1b362d1b,0x6edcb26e,0x5ab4ee5a,0xa05bfba0,0x52a4f652,0x3b764d3b,0xd6b761d6,0xb37dceb3,0x29527b29,0xe3dd3ee3,0x2f5e712f,0x84139784,0x53a6f553,0xd1b968d1,0x00000000,0xedc12ced,0x20406020,0xfce31ffc,0xb179c8b1,0x5bb6ed5b,0x6ad4be6a,0xcb8d46cb,0xbe67d9be,0x39724b39,0x4a94de4a,0x4c98d44c,0x58b0e858,0xcf854acf,0xd0bb6bd0,0xefc52aef,0xaa4fe5aa,0xfbed16fb,0x4386c543,0x4d9ad74d,0x33665533,0x85119485,0x458acf45,0xf9e910f9,0x02040602,0x7ffe817f,0x50a0f050,0x3c78443c,0x9f25ba9f,0xa84be3a8,0x51a2f351,0xa35dfea3,0x4080c040,0x8f058a8f,0x923fad92,0x9d21bc9d,0x38704838,0xf5f104f5,0xbc63dfbc,0xb677c1b6,0xdaaf75da,0x21426321,0x10203010,0xffe51aff,0xf3fd0ef3,0xd2bf6dd2,0xcd814ccd,0x0c18140c,0x13263513,0xecc32fec,0x5fbee15f,0x9735a297,0x4488cc44,0x172e3917,0xc49357c4,0xa755f2a7,0x7efc827e,0x3d7a473d,0x64c8ac64,0x5dbae75d,0x19322b19,0x73e69573,0x60c0a060,0x81199881,0x4f9ed14f,0xdca37fdc,0x22446622,0x2a547e2a,0x903bab90,0x880b8388,0x468cca46,0xeec729ee,0xb86bd3b8,0x14283c14,0xdea779de,0x5ebce25e,0x0b161d0b,0xdbad76db,0xe0db3be0,0x32645632,0x3a744e3a,0x0a141e0a,0x4992db49,0x060c0a06,0x24486c24,0x5cb8e45c,0xc29f5dc2,0xd3bd6ed3,0xac43efac,0x62c4a662,0x9139a891,0x9531a495,0xe4d337e4,0x79f28b79,0xe7d532e7,0xc88b43c8,0x376e5937,0x6ddab76d,0x8d018c8d,0xd5b164d5,0x4e9cd24e,0xa949e0a9,0x6cd8b46c,0x56acfa56,0xf4f307f4,0xeacf25ea,0x65caaf65,0x7af48e7a,0xae47e9ae,0x08101808,0xba6fd5ba,0x78f08878,0x254a6f25,0x2e5c722e,0x1c38241c,0xa657f1a6,0xb473c7b4,0xc69751c6,0xe8cb23e8,0xdda17cdd,0x74e89c74,0x1f3e211f,0x4b96dd4b,0xbd61dcbd,0x8b0d868b,0x8a0f858a,0x70e09070,0x3e7c423e,0xb571c4b5,0x66ccaa66,0x4890d848,0x03060503,0xf6f701f6,0x0e1c120e,0x61c2a361,0x356a5f35,0x57aef957,0xb969d0b9,0x86179186,0xc19958c1,0x1d3a271d,0x9e27b99e,0xe1d938e1,0xf8eb13f8,0x982bb398,0x11223311,0x69d2bb69,0xd9a970d9,0x8e07898e,0x9433a794,0x9b2db69b,0x1e3c221e,0x87159287,0xe9c920e9,0xce8749ce,0x55aaff55,0x28507828,0xdfa57adf,0x8c038f8c,0xa159f8a1,0x89098089,0x0d1a170d,0xbf65dabf,0xe6d731e6,0x4284c642,0x68d0b868,0x4182c341,0x9929b099,0x2d5a772d,0x0f1e110f,0xb07bcbb0,0x54a8fc54,0xbb6dd6bb,0x162c3a16]
S4 = [0xc6a56363,0xf8847c7c,0xee997777,0xf68d7b7b,0xff0df2f2,0xd6bd6b6b,0xdeb16f6f,0x9154c5c5,0x60503030,0x02030101,0xcea96767,0x567d2b2b,0xe719fefe,0xb562d7d7,0x4de6abab,0xec9a7676,0x8f45caca,0x1f9d8282,0x8940c9c9,0xfa877d7d,0xef15fafa,0xb2eb5959,0x8ec94747,0xfb0bf0f0,0x41ecadad,0xb367d4d4,0x5ffda2a2,0x45eaafaf,0x23bf9c9c,0x53f7a4a4,0xe4967272,0x9b5bc0c0,0x75c2b7b7,0xe11cfdfd,0x3dae9393,0x4c6a2626,0x6c5a3636,0x7e413f3f,0xf502f7f7,0x834fcccc,0x685c3434,0x51f4a5a5,0xd134e5e5,0xf908f1f1,0xe2937171,0xab73d8d8,0x62533131,0x2a3f1515,0x080c0404,0x9552c7c7,0x46652323,0x9d5ec3c3,0x30281818,0x37a19696,0x0a0f0505,0x2fb59a9a,0x0e090707,0x24361212,0x1b9b8080,0xdf3de2e2,0xcd26ebeb,0x4e692727,0x7fcdb2b2,0xea9f7575,0x121b0909,0x1d9e8383,0x58742c2c,0x342e1a1a,0x362d1b1b,0xdcb26e6e,0xb4ee5a5a,0x5bfba0a0,0xa4f65252,0x764d3b3b,0xb761d6d6,0x7dceb3b3,0x527b2929,0xdd3ee3e3,0x5e712f2f,0x13978484,0xa6f55353,0xb968d1d1,0x00000000,0xc12ceded,0x40602020,0xe31ffcfc,0x79c8b1b1,0xb6ed5b5b,0xd4be6a6a,0x8d46cbcb,0x67d9bebe,0x724b3939,0x94de4a4a,0x98d44c4c,0xb0e85858,0x854acfcf,0xbb6bd0d0,0xc52aefef,0x4fe5aaaa,0xed16fbfb,0x86c54343,0x9ad74d4d,0x66553333,0x11948585,0x8acf4545,0xe910f9f9,0x04060202,0xfe817f7f,0xa0f05050,0x78443c3c,0x25ba9f9f,0x4be3a8a8,0xa2f35151,0x5dfea3a3,0x80c04040,0x058a8f8f,0x3fad9292,0x21bc9d9d,0x70483838,0xf104f5f5,0x63dfbcbc,0x77c1b6b6,0xaf75dada,0x42632121,0x20301010,0xe51affff,0xfd0ef3f3,0xbf6dd2d2,0x814ccdcd,0x18140c0c,0x26351313,0xc32fecec,0xbee15f5f,0x35a29797,0x88cc4444,0x2e391717,0x9357c4c4,0x55f2a7a7,0xfc827e7e,0x7a473d3d,0xc8ac6464,0xbae75d5d,0x322b1919,0xe6957373,0xc0a06060,0x19988181,0x9ed14f4f,0xa37fdcdc,0x44662222,0x547e2a2a,0x3bab9090,0x0b838888,0x8cca4646,0xc729eeee,0x6bd3b8b8,0x283c1414,0xa779dede,0xbce25e5e,0x161d0b0b,0xad76dbdb,0xdb3be0e0,0x64563232,0x744e3a3a,0x141e0a0a,0x92db4949,0x0c0a0606,0x486c2424,0xb8e45c5c,0x9f5dc2c2,0xbd6ed3d3,0x43efacac,0xc4a66262,0x39a89191,0x31a49595,0xd337e4e4,0xf28b7979,0xd532e7e7,0x8b43c8c8,0x6e593737,0xdab76d6d,0x018c8d8d,0xb164d5d5,0x9cd24e4e,0x49e0a9a9,0xd8b46c6c,0xacfa5656,0xf307f4f4,0xcf25eaea,0xcaaf6565,0xf48e7a7a,0x47e9aeae,0x10180808,0x6fd5baba,0xf0887878,0x4a6f2525,0x5c722e2e,0x38241c1c,0x57f1a6a6,0x73c7b4b4,0x9751c6c6,0xcb23e8e8,0xa17cdddd,0xe89c7474,0x3e211f1f,0x96dd4b4b,0x61dcbdbd,0x0d868b8b,0x0f858a8a,0xe0907070,0x7c423e3e,0x71c4b5b5,0xccaa6666,0x90d84848,0x06050303,0xf701f6f6,0x1c120e0e,0xc2a36161,0x6a5f3535,0xaef95757,0x69d0b9b9,0x17918686,0x9958c1c1,0x3a271d1d,0x27b99e9e,0xd938e1e1,0xeb13f8f8,0x2bb39898,0x22331111,0xd2bb6969,0xa970d9d9,0x07898e8e,0x33a79494,0x2db69b9b,0x3c221e1e,0x15928787,0xc920e9e9,0x8749cece,0xaaff5555,0x50782828,0xa57adfdf,0x038f8c8c,0x59f8a1a1,0x09808989,0x1a170d0d,0x65dabfbf,0xd731e6e6,0x84c64242,0xd0b86868,0x82c34141,0x29b09999,0x5a772d2d,0x1e110f0f,0x7bcbb0b0,0xa8fc5454,0x6dd6bbbb,0x2c3a1616]
SBox = [a&255 for a in S3]
groestlT = [
0xa5f432c6,0x84976ff8,0x99b05eee,0x8d8c7af6,0x0d17e8ff,0xbddc0ad6,0xb1c816de,0x54fc6d91,0x50f09060,0x03050702,0xa9e02ece,0x7d87d156,0x192bcce7,0x62a613b5,0xe6317c4d,0x9ab559ec,0x45cf408f,0x9dbca31f,0x40c04989,0x879268fa,0x153fd0ef,0xeb2694b2,0xc940ce8e,0x0b1de6fb,0xec2f6e41,0x67a91ab3,0xfd1c435f,0xea256045,0xbfdaf923,0xf7025153,0x96a145e4,0x5bed769b,0xc25d2875,0x1c24c5e1,0xaee9d43d,0x6abef24c,0x5aee826c,0x41c3bd7e,0x0206f3f5,0x4fd15283,0x5ce48c68,0xf4075651,0x345c8dd1,0x0818e1f9,0x93ae4ce2,0x73953eab,0x53f59762,0x3f416b2a,0x0c141c08,0x52f66395,0x65afe946,0x5ee27f9d,0x28784830,0xa1f8cf37,0x0f111b0a,0xb5c4eb2f,0x091b150e,0x365a7e24,0x9bb6ad1b,0x3d4798df,0x266aa7cd,0x69bbf54e,0xcd4c337f,0x9fba50ea,0x1b2d3f12,0x9eb9a41d,0x749cc458,0x2e724634,0x2d774136,0xb2cd11dc,0xee299db4,0xfb164d5b,0xf601a5a4,0x4dd7a176,0x61a314b7,0xce49347d,0x7b8ddf52,0x3e429fdd,0x7193cd5e,0x97a2b113,0xf504a2a6,0x68b801b9,0x00000000,0x2c74b5c1,0x60a0e040,0x1f21c2e3,0xc8433a79,0xed2c9ab6,0xbed90dd4,0x46ca478d,0xd9701767,0x4bddaf72,0xde79ed94,0xd467ff98,0xe82393b0,0x4ade5b85,0x6bbd06bb,0x2a7ebbc5,0xe5347b4f,0x163ad7ed,0xc554d286,0xd762f89a,0x55ff9966,0x94a7b611,0xcf4ac08a,0x1030d9e9,0x060a0e04,0x819866fe,0xf00baba0,0x44ccb478,0xbad5f025,0xe33e754b,0xf30eaca2,0xfe19445d,0xc05bdb80,0x8a858005,0xadecd33f,0xbcdffe21,0x48d8a870,0x040cfdf1,0xdf7a1963,0xc1582f77,0x759f30af,0x63a5e742,0x30507020,0x1a2ecbe5,0x0e12effd,0x6db708bf,0x4cd45581,0x143c2418,0x355f7926,0x2f71b2c3,0xe13886be,0xa2fdc835,0xcc4fc788,0x394b652e,0x57f96a93,0xf20d5855,0x829d61fc,0x47c9b37a,0xacef27c8,0xe73288ba,0x2b7d4f32,0x95a442e6,0xa0fb3bc0,0x98b3aa19,0xd168f69e,0x7f8122a3,0x66aaee44,0x7e82d654,0xabe6dd3b,0x839e950b,0xca45c98c,0x297bbcc7,0xd36e056b,0x3c446c28,0x798b2ca7,0xe23d81bc,0x1d273116,0x769a37ad,0x3b4d96db,0x56fa9e64,0x4ed2a674,0x1e223614,0xdb76e492,0x0a1e120c,0x6cb4fc48,0xe4378fb8,0x5de7789f,0x6eb20fbd,0xef2a6943,0xa6f135c4,0xa8e3da39,0xa4f7c631,0x37598ad3,0x8b8674f2,0x325683d5,0x43c54e8b,0x59eb856e,0xb7c218da,0x8c8f8e01,0x64ac1db1,0xd26df19c,0xe03b7249,0xb4c71fd8,0xfa15b9ac,0x0709faf3,0x256fa0cf,0xafea20ca,0x8e897df4,0xe9206747,0x18283810,0xd5640b6f,0x888373f0,0x6fb1fb4a,0x7296ca5c,0x246c5438,0xf1085f57,0xc7522173,0x51f36497,0x2365aecb,0x7c8425a1,0x9cbf57e8,0x21635d3e,0xdd7cea96,0xdc7f1e61,0x86919c0d,0x85949b0f,0x90ab4be0,0x42c6ba7c,0xc4572671,0xaae529cc,0xd873e390,0x050f0906,0x0103f4f7,0x12362a1c,0xa3fe3cc2,0x5fe18b6a,0xf910beae,0xd06b0269,0x91a8bf17,0x58e87199,0x2769533a,0xb9d0f727,0x384891d9,0x1335deeb,0xb3cee52b,0x33557722,0xbbd604d2,0x709039a9,0x89808707,0xa7f2c133,0xb6c1ec2d,0x22665a3c,0x92adb815,0x2060a9c9,0x49db5c87,0xff1ab0aa,0x7888d850,0x7a8e2ba5,0x8f8a8903,0xf8134a59,0x809b9209,0x1739231a,0xda751065,0x315384d7,0xc651d584,0xb8d303d0,0xc35edc82,0xb0cbe229,0x7799c35a,0x11332d1e,0xcb463d7b,0xfc1fb7a8,0xd6610c6d,0x3a4e622c,
0xf432c6c6,0x976ff8f8,0xb05eeeee,0x8c7af6f6,0x17e8ffff,0xdc0ad6d6,0xc816dede,0xfc6d9191,0xf0906060,0x05070202,0xe02ecece,0x87d15656,0x2bcce7e7,0xa613b5b5,0x317c4d4d,0xb559ecec,0xcf408f8f,0xbca31f1f,0xc0498989,0x9268fafa,0x3fd0efef,0x2694b2b2,0x40ce8e8e,0x1de6fbfb,0x2f6e4141,0xa91ab3b3,0x1c435f5f,0x25604545,0xdaf92323,0x02515353,0xa145e4e4,0xed769b9b,0x5d287575,0x24c5e1e1,0xe9d43d3d,0xbef24c4c,0xee826c6c,0xc3bd7e7e,0x06f3f5f5,0xd1528383,0xe48c6868,0x07565151,0x5c8dd1d1,0x18e1f9f9,0xae4ce2e2,0x953eabab,0xf5976262,0x416b2a2a,0x141c0808,0xf6639595,0xafe94646,0xe27f9d9d,0x78483030,0xf8cf3737,0x111b0a0a,0xc4eb2f2f,0x1b150e0e,0x5a7e2424,0xb6ad1b1b,0x4798dfdf,0x6aa7cdcd,0xbbf54e4e,0x4c337f7f,0xba50eaea,0x2d3f1212,0xb9a41d1d,0x9cc45858,0x72463434,0x77413636,0xcd11dcdc,0x299db4b4,0x164d5b5b,0x01a5a4a4,0xd7a17676,0xa314b7b7,0x49347d7d,0x8ddf5252,0x429fdddd,0x93cd5e5e,0xa2b11313,0x04a2a6a6,0xb801b9b9,0x00000000,0x74b5c1c1,0xa0e04040,0x21c2e3e3,0x433a7979,0x2c9ab6b6,0xd90dd4d4,0xca478d8d,0x70176767,0xddaf7272,0x79ed9494,0x67ff9898,0x2393b0b0,0xde5b8585,0xbd06bbbb,0x7ebbc5c5,0x347b4f4f,0x3ad7eded,0x54d28686,0x62f89a9a,0xff996666,0xa7b61111,0x4ac08a8a,0x30d9e9e9,0x0a0e0404,0x9866fefe,0x0baba0a0,0xccb47878,0xd5f02525,0x3e754b4b,0x0eaca2a2,0x19445d5d,0x5bdb8080,0x85800505,0xecd33f3f,0xdffe2121,0xd8a87070,0x0cfdf1f1,0x7a196363,0x582f7777,0x9f30afaf,0xa5e74242,0x50702020,0x2ecbe5e5,0x12effdfd,0xb708bfbf,0xd4558181,0x3c241818,0x5f792626,0x71b2c3c3,0x3886bebe,0xfdc83535,0x4fc78888,0x4b652e2e,0xf96a9393,0x0d585555,0x9d61fcfc,0xc9b37a7a,0xef27c8c8,0x3288baba,0x7d4f3232,0xa442e6e6,0xfb3bc0c0,0xb3aa1919,0x68f69e9e,0x8122a3a3,0xaaee4444,0x82d65454,0xe6dd3b3b,0x9e950b0b,0x45c98c8c,0x7bbcc7c7,0x6e056b6b,0x446c2828,0x8b2ca7a7,0x3d81bcbc,0x27311616,0x9a37adad,0x4d96dbdb,0xfa9e6464,0xd2a67474,0x22361414,0x76e49292,0x1e120c0c,0xb4fc4848,0x378fb8b8,0xe7789f9f,0xb20fbdbd,0x2a694343,0xf135c4c4,0xe3da3939,0xf7c63131,0x598ad3d3,0x8674f2f2,0x5683d5d5,0xc54e8b8b,0xeb856e6e,0xc218dada,0x8f8e0101,0xac1db1b1,0x6df19c9c,0x3b724949,0xc71fd8d8,0x15b9acac,0x09faf3f3,0x6fa0cfcf,0xea20caca,0x897df4f4,0x20674747,0x28381010,0x640b6f6f,0x8373f0f0,0xb1fb4a4a,0x96ca5c5c,0x6c543838,0x085f5757,0x52217373,0xf3649797,0x65aecbcb,0x8425a1a1,0xbf57e8e8,0x635d3e3e,0x7cea9696,0x7f1e6161,0x919c0d0d,0x949b0f0f,0xab4be0e0,0xc6ba7c7c,0x57267171,0xe529cccc,0x73e39090,0x0f090606,0x03f4f7f7,0x362a1c1c,0xfe3cc2c2,0xe18b6a6a,0x10beaeae,0x6b026969,0xa8bf1717,0xe8719999,0x69533a3a,0xd0f72727,0x4891d9d9,0x35deebeb,0xcee52b2b,0x55772222,0xd604d2d2,0x9039a9a9,0x80870707,0xf2c13333,0xc1ec2d2d,0x665a3c3c,0xadb81515,0x60a9c9c9,0xdb5c8787,0x1ab0aaaa,0x88d85050,0x8e2ba5a5,0x8a890303,0x134a5959,0x9b920909,0x39231a1a,0x75106565,0x5384d7d7,0x51d58484,0xd303d0d0,0x5edc8282,0xcbe22929,0x99c35a5a,0x332d1e1e,0x463d7b7b,0x1fb7a8a8,0x610c6d6d,0x4e622c2c,
0x32c6c6a5,0x6ff8f884,0x5eeeee99,0x7af6f68d,0xe8ffff0d,0x0ad6d6bd,0x16dedeb1,0x6d919154,0x90606050,0x07020203,0x2ececea9,0xd156567d,0xcce7e719,0x13b5b562,0x7c4d4de6,0x59ecec9a,0x408f8f45,0xa31f1f9d,0x49898940,0x68fafa87,0xd0efef15,0x94b2b2eb,0xce8e8ec9,0xe6fbfb0b,0x6e4141ec,0x1ab3b367,0x435f5ffd,0x604545ea,0xf92323bf,0x515353f7,0x45e4e496,0x769b9b5b,0x287575c2,0xc5e1e11c,0xd43d3dae,0xf24c4c6a,0x826c6c5a,0xbd7e7e41,0xf3f5f502,0x5283834f,0x8c68685c,0x565151f4,0x8dd1d134,0xe1f9f908,0x4ce2e293,0x3eabab73,0x97626253,0x6b2a2a3f,0x1c08080c,0x63959552,0xe9464665,0x7f9d9d5e,0x48303028,0xcf3737a1,0x1b0a0a0f,0xeb2f2fb5,0x150e0e09,0x7e242436,0xad1b1b9b,0x98dfdf3d,0xa7cdcd26,0xf54e4e69,0x337f7fcd,0x50eaea9f,0x3f12121b,0xa41d1d9e,0xc4585874,0x4634342e,0x4136362d,0x11dcdcb2,0x9db4b4ee,0x4d5b5bfb,0xa5a4a4f6,0xa176764d,0x14b7b761,0x347d7dce,0xdf52527b,0x9fdddd3e,0xcd5e5e71,0xb1131397,0xa2a6a6f5,0x01b9b968,0x00000000,0xb5c1c12c,0xe0404060,0xc2e3e31f,0x3a7979c8,0x9ab6b6ed,0x0dd4d4be,0x478d8d46,0x176767d9,0xaf72724b,0xed9494de,0xff9898d4,0x93b0b0e8,0x5b85854a,0x06bbbb6b,0xbbc5c52a,0x7b4f4fe5,0xd7eded16,0xd28686c5,0xf89a9ad7,0x99666655,0xb6111194,0xc08a8acf,0xd9e9e910,0x0e040406,0x66fefe81,0xaba0a0f0,0xb4787844,0xf02525ba,0x754b4be3,0xaca2a2f3,0x445d5dfe,0xdb8080c0,0x8005058a,0xd33f3fad,0xfe2121bc,0xa8707048,0xfdf1f104,0x196363df,0x2f7777c1,0x30afaf75,0xe7424263,0x70202030,0xcbe5e51a,0xeffdfd0e,0x08bfbf6d,0x5581814c,0x24181814,0x79262635,0xb2c3c32f,0x86bebee1,0xc83535a2,0xc78888cc,0x652e2e39,0x6a939357,0x585555f2,0x61fcfc82,0xb37a7a47,0x27c8c8ac,0x88babae7,0x4f32322b,0x42e6e695,0x3bc0c0a0,0xaa191998,0xf69e9ed1,0x22a3a37f,0xee444466,0xd654547e,0xdd3b3bab,0x950b0b83,0xc98c8cca,0xbcc7c729,0x056b6bd3,0x6c28283c,0x2ca7a779,0x81bcbce2,0x3116161d,0x37adad76,0x96dbdb3b,0x9e646456,0xa674744e,0x3614141e,0xe49292db,0x120c0c0a,0xfc48486c,0x8fb8b8e4,0x789f9f5d,0x0fbdbd6e,0x694343ef,0x35c4c4a6,0xda3939a8,0xc63131a4,0x8ad3d337,0x74f2f28b,0x83d5d532,0x4e8b8b43,0x856e6e59,0x18dadab7,0x8e01018c,0x1db1b164,0xf19c9cd2,0x724949e0,0x1fd8d8b4,0xb9acacfa,0xfaf3f307,0xa0cfcf25,0x20cacaaf,0x7df4f48e,0x674747e9,0x38101018,0x0b6f6fd5,0x73f0f088,0xfb4a4a6f,0xca5c5c72,0x54383824,0x5f5757f1,0x217373c7,0x64979751,0xaecbcb23,0x25a1a17c,0x57e8e89c,0x5d3e3e21,0xea9696dd,0x1e6161dc,0x9c0d0d86,0x9b0f0f85,0x4be0e090,0xba7c7c42,0x267171c4,0x29ccccaa,0xe39090d8,0x09060605,0xf4f7f701,0x2a1c1c12,0x3cc2c2a3,0x8b6a6a5f,0xbeaeaef9,0x026969d0,0xbf171791,0x71999958,0x533a3a27,0xf72727b9,0x91d9d938,0xdeebeb13,0xe52b2bb3,0x77222233,0x04d2d2bb,0x39a9a970,0x87070789,0xc13333a7,0xec2d2db6,0x5a3c3c22,0xb8151592,0xa9c9c920,0x5c878749,0xb0aaaaff,0xd8505078,0x2ba5a57a,0x8903038f,0x4a5959f8,0x92090980,0x231a1a17,0x106565da,0x84d7d731,0xd58484c6,0x03d0d0b8,0xdc8282c3,0xe22929b0,0xc35a5a77,0x2d1e1e11,0x3d7b7bcb,0xb7a8a8fc,0x0c6d6dd6,0x622c2c3a,
0xc6c6a597,0xf8f884eb,0xeeee99c7,0xf6f68df7,0xffff0de5,0xd6d6bdb7,0xdedeb1a7,0x91915439,0x606050c0,0x02020304,0xcecea987,0x56567dac,0xe7e719d5,0xb5b56271,0x4d4de69a,0xecec9ac3,0x8f8f4505,0x1f1f9d3e,0x89894009,0xfafa87ef,0xefef15c5,0xb2b2eb7f,0x8e8ec907,0xfbfb0bed,0x4141ec82,0xb3b3677d,0x5f5ffdbe,0x4545ea8a,0x2323bf46,0x5353f7a6,0xe4e496d3,0x9b9b5b2d,0x7575c2ea,0xe1e11cd9,0x3d3dae7a,0x4c4c6a98,0x6c6c5ad8,0x7e7e41fc,0xf5f502f1,0x83834f1d,0x68685cd0,0x5151f4a2,0xd1d134b9,0xf9f908e9,0xe2e293df,0xabab734d,0x626253c4,0x2a2a3f54,0x08080c10,0x95955231,0x4646658c,0x9d9d5e21,0x30302860,0x3737a16e,0x0a0a0f14,0x2f2fb55e,0x0e0e091c,0x24243648,0x1b1b9b36,0xdfdf3da5,0xcdcd2681,0x4e4e699c,0x7f7fcdfe,0xeaea9fcf,0x12121b24,0x1d1d9e3a,0x585874b0,0x34342e68,0x36362d6c,0xdcdcb2a3,0xb4b4ee73,0x5b5bfbb6,0xa4a4f653,0x76764dec,0xb7b76175,0x7d7dcefa,0x52527ba4,0xdddd3ea1,0x5e5e71bc,0x13139726,0xa6a6f557,0xb9b96869,0x00000000,0xc1c12c99,0x40406080,0xe3e31fdd,0x7979c8f2,0xb6b6ed77,0xd4d4beb3,0x8d8d4601,0x6767d9ce,0x72724be4,0x9494de33,0x9898d42b,0xb0b0e87b,0x85854a11,0xbbbb6b6d,0xc5c52a91,0x4f4fe59e,0xeded16c1,0x8686c517,0x9a9ad72f,0x666655cc,0x11119422,0x8a8acf0f,0xe9e910c9,0x04040608,0xfefe81e7,0xa0a0f05b,0x787844f0,0x2525ba4a,0x4b4be396,0xa2a2f35f,0x5d5dfeba,0x8080c01b,0x05058a0a,0x3f3fad7e,0x2121bc42,0x707048e0,0xf1f104f9,0x6363dfc6,0x7777c1ee,0xafaf7545,0x42426384,0x20203040,0xe5e51ad1,0xfdfd0ee1,0xbfbf6d65,0x81814c19,0x18181430,0x2626354c,0xc3c32f9d,0xbebee167,0x3535a26a,0x8888cc0b,0x2e2e395c,0x9393573d,0x5555f2aa,0xfcfc82e3,0x7a7a47f4,0xc8c8ac8b,0xbabae76f,0x32322b64,0xe6e695d7,0xc0c0a09b,0x19199832,0x9e9ed127,0xa3a37f5d,0x44446688,0x54547ea8,0x3b3bab76,0x0b0b8316,0x8c8cca03,0xc7c72995,0x6b6bd3d6,0x28283c50,0xa7a77955,0xbcbce263,0x16161d2c,0xadad7641,0xdbdb3bad,0x646456c8,0x74744ee8,0x14141e28,0x9292db3f,0x0c0c0a18,0x48486c90,0xb8b8e46b,0x9f9f5d25,0xbdbd6e61,0x4343ef86,0xc4c4a693,0x3939a872,0x3131a462,0xd3d337bd,0xf2f28bff,0xd5d532b1,0x8b8b430d,0x6e6e59dc,0xdadab7af,0x01018c02,0xb1b16479,0x9c9cd223,0x4949e092,0xd8d8b4ab,0xacacfa43,0xf3f307fd,0xcfcf2585,0xcacaaf8f,0xf4f48ef3,0x4747e98e,0x10101820,0x6f6fd5de,0xf0f088fb,0x4a4a6f94,0x5c5c72b8,0x38382470,0x5757f1ae,0x7373c7e6,0x97975135,0xcbcb238d,0xa1a17c59,0xe8e89ccb,0x3e3e217c,0x9696dd37,0x6161dcc2,0x0d0d861a,0x0f0f851e,0xe0e090db,0x7c7c42f8,0x7171c4e2,0xccccaa83,0x9090d83b,0x0606050c,0xf7f701f5,0x1c1c1238,0xc2c2a39f,0x6a6a5fd4,0xaeaef947,0x6969d0d2,0x1717912e,0x99995829,0x3a3a2774,0x2727b94e,0xd9d938a9,0xebeb13cd,0x2b2bb356,0x22223344,0xd2d2bbbf,0xa9a97049,0x0707890e,0x3333a766,0x2d2db65a,0x3c3c2278,0x1515922a,0xc9c92089,0x87874915,0xaaaaff4f,0x505078a0,0xa5a57a51,0x03038f06,0x5959f8b2,0x09098012,0x1a1a1734,0x6565daca,0xd7d731b5,0x8484c613,0xd0d0b8bb,0x8282c31f,0x2929b052,0x5a5a77b4,0x1e1e113c,0x7b7bcbf6,0xa8a8fc4b,0x6d6dd6da,0x2c2c3a58,
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0xf4a5f432,0x9784976f,0xb099b05e,0x8c8d8c7a,0x170d17e8,0xdcbddc0a,0xc8b1c816,0xfc54fc6d,0xf050f090,0x05030507,0xe0a9e02e,0x877d87d1,0x2b192bcc,0xa662a613,0x31e6317c,0xb59ab559,0xcf45cf40,0xbc9dbca3,0xc040c049,0x92879268,0x3f153fd0,0x26eb2694,0x40c940ce,0x1d0b1de6,0x2fec2f6e,0xa967a91a,0x1cfd1c43,0x25ea2560,0xdabfdaf9,0x02f70251,0xa196a145,0xed5bed76,0x5dc25d28,0x241c24c5,0xe9aee9d4,0xbe6abef2,0xee5aee82,0xc341c3bd,0x060206f3,0xd14fd152,0xe45ce48c,0x07f40756,0x5c345c8d,0x180818e1,0xae93ae4c,0x9573953e,0xf553f597,0x413f416b,0x140c141c,0xf652f663,0xaf65afe9,0xe25ee27f,0x78287848,0xf8a1f8cf,0x110f111b,0xc4b5c4eb,0x1b091b15,0x5a365a7e,0xb69bb6ad,0x473d4798,0x6a266aa7,0xbb69bbf5,0x4ccd4c33,0xba9fba50,0x2d1b2d3f,0xb99eb9a4,0x9c749cc4,0x722e7246,0x772d7741,0xcdb2cd11,0x29ee299d,0x16fb164d,0x01f601a5,0xd74dd7a1,0xa361a314,0x49ce4934,0x8d7b8ddf,0x423e429f,0x937193cd,0xa297a2b1,0x04f504a2,0xb868b801,0x00000000,0x742c74b5,0xa060a0e0,0x211f21c2,0x43c8433a,0x2ced2c9a,0xd9bed90d,0xca46ca47,0x70d97017,0xdd4bddaf,0x79de79ed,0x67d467ff,0x23e82393,0xde4ade5b,0xbd6bbd06,0x7e2a7ebb,0x34e5347b,0x3a163ad7,0x54c554d2,0x62d762f8,0xff55ff99,0xa794a7b6,0x4acf4ac0,0x301030d9,0x0a060a0e,0x98819866,0x0bf00bab,0xcc44ccb4,0xd5bad5f0,0x3ee33e75,0x0ef30eac,0x19fe1944,0x5bc05bdb,0x858a8580,0xecadecd3,0xdfbcdffe,0xd848d8a8,0x0c040cfd,0x7adf7a19,0x58c1582f,0x9f759f30,0xa563a5e7,0x50305070,0x2e1a2ecb,0x120e12ef,0xb76db708,0xd44cd455,0x3c143c24,0x5f355f79,0x712f71b2,0x38e13886,0xfda2fdc8,0x4fcc4fc7,0x4b394b65,0xf957f96a,0x0df20d58,0x9d829d61,0xc947c9b3,0xefacef27,0x32e73288,0x7d2b7d4f,0xa495a442,0xfba0fb3b,0xb398b3aa,0x68d168f6,0x817f8122,0xaa66aaee,0x827e82d6,0xe6abe6dd,0x9e839e95,0x45ca45c9,0x7b297bbc,0x6ed36e05,0x443c446c,0x8b798b2c,0x3de23d81,0x271d2731,0x9a769a37,0x4d3b4d96,0xfa56fa9e,0xd24ed2a6,0x221e2236,0x76db76e4,0x1e0a1e12,0xb46cb4fc,0x37e4378f,0xe75de778,0xb26eb20f,0x2aef2a69,0xf1a6f135,0xe3a8e3da,0xf7a4f7c6,0x5937598a,0x868b8674,0x56325683,0xc543c54e,0xeb59eb85,0xc2b7c218,0x8f8c8f8e,0xac64ac1d,0x6dd26df1,0x3be03b72,0xc7b4c71f,0x15fa15b9,0x090709fa,0x6f256fa0,0xeaafea20,0x898e897d,0x20e92067,0x28182838,0x64d5640b,0x83888373,0xb16fb1fb,0x967296ca,0x6c246c54,0x08f1085f,0x52c75221,0xf351f364,0x652365ae,0x847c8425,0xbf9cbf57,0x6321635d,0x7cdd7cea,0x7fdc7f1e,0x9186919c,0x9485949b,0xab90ab4b,0xc642c6ba,0x57c45726,0xe5aae529,0x73d873e3,0x0f050f09,0x030103f4,0x3612362a,0xfea3fe3c,0xe15fe18b,0x10f910be,0x6bd06b02,0xa891a8bf,0xe858e871,0x69276953,0xd0b9d0f7,0x48384891,0x351335de,0xceb3cee5,0x55335577,0xd6bbd604,0x90709039,0x80898087,0xf2a7f2c1,0xc1b6c1ec,0x6622665a,0xad92adb8,0x602060a9,0xdb49db5c,0x1aff1ab0,0x887888d8,0x8e7a8e2b,0x8a8f8a89,0x13f8134a,0x9b809b92,0x39173923,0x75da7510,0x53315384,0x51c651d5,0xd3b8d303,0x5ec35edc,0xcbb0cbe2,0x997799c3,0x3311332d,0x46cb463d,0x1ffc1fb7,0x61d6610c,0x4e3a4e62]
blakeS=[[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],[14,10,4,8,9,15,13,6,1,12,0,2,11,7,5,3],[11,8,12,0,5,2,15,13,10,14,3,6,7,1,9,4],[7,9,3,1,13,12,11,14,2,6,5,10,4,0,15,8],[9,0,5,7,2,4,10,15,14,1,11,12,6,8,3,13],[2,12,6,10,0,11,8,3,4,13,7,5,15,14,1,9],[12,5,1,15,14,13,4,10,0,7,6,3,9,2,8,11],[13,11,7,14,12,1,3,9,5,0,15,4,8,6,2,10],[6,15,14,9,11,3,0,8,12,2,13,7,1,4,10,5],[10,2,8,4,7,6,1,5,15,11,9,14,3,12,13,0],[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],[14,10,4,8,9,15,13,6,1,12,0,2,11,7,5,3],[11,8,12,0,5,2,15,13,10,14,3,6,7,1,9,4],[7,9,3,1,13,12,11,14,2,6,5,10,4,0,15,8],[9,0,5,7,2,4,10,15,14,1,11,12,6,8,3,13],[2,12,6,10,0,11,8,3,4,13,7,5,15,14,1,9],[12,5,1,15,14,13,4,10,0,7,6,3,9,2,8,11],[13,11,7,14,12,1,3,9,5,0,15,4,8,6,2,10],[6,15,14,9,11,3,0,8,12,2,13,7,1,4,10,5],[10,2,8,4,7,6,1,5,15,11,9,14,3,12,13,0]]
if __name__ == '__main__':
run_tests()
| 81.437995 | 2,822 | 0.713656 | 8,040 | 61,730 | 5.470398 | 0.479975 | 0.008754 | 0.00532 | 0.009754 | 0.063139 | 0.048793 | 0.043109 | 0.039289 | 0.031922 | 0.031104 | 0 | 0.435884 | 0.148664 | 61,730 | 757 | 2,823 | 81.545575 | 0.401024 | 0.06462 | 0 | 0.124567 | 0 | 0.00173 | 0.023346 | 0.000815 | 0 | 0 | 0.576265 | 0 | 0 | 1 | 0.046713 | false | 0.00346 | 0.00346 | 0.00692 | 0.081315 | 0.022491 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
9bddc5f2fa49fa8170a523c2069f52453c62874e | 162 | wsgi | Python | trac.wsgi | CGI-define-and-primeportal/trac-plugin-trac-plugin-sharepoint | 165dec6a2559d873ea436d09a3366a5d3809b4a7 | [
"BSD-3-Clause"
] | 2 | 2015-05-07T10:04:31.000Z | 2015-05-12T14:07:37.000Z | trac.wsgi | CGI-define-and-primeportal/trac-plugin-trac-plugin-sharepoint | 165dec6a2559d873ea436d09a3366a5d3809b4a7 | [
"BSD-3-Clause"
] | 3 | 2015-05-07T15:08:04.000Z | 2015-05-12T15:18:57.000Z | trac.wsgi | CGI-define-and-primeportal/trac-plugin-trac-plugin-sharepoint | 165dec6a2559d873ea436d09a3366a5d3809b4a7 | [
"BSD-3-Clause"
] | null | null | null | import os
os.environ['TRAC_ENV'] = '/var/local/trac/'
os.environ['PYTHON_EGG_CACHE'] = '/tmp'
import trac.web.main
application = trac.web.main.dispatch_request
| 20.25 | 44 | 0.740741 | 25 | 162 | 4.64 | 0.64 | 0.155172 | 0.189655 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.092593 | 162 | 7 | 45 | 23.142857 | 0.789116 | 0 | 0 | 0 | 0 | 0 | 0.271605 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
9be348723a86c9d59ad74d31cc9497434a5de3af | 263 | py | Python | Desafio11.py | ricksmc/Python-projects | 1740d1cbafb0aebfffeb0bfdb4ccccf0dbd14093 | [
"MIT"
] | null | null | null | Desafio11.py | ricksmc/Python-projects | 1740d1cbafb0aebfffeb0bfdb4ccccf0dbd14093 | [
"MIT"
] | null | null | null | Desafio11.py | ricksmc/Python-projects | 1740d1cbafb0aebfffeb0bfdb4ccccf0dbd14093 | [
"MIT"
] | null | null | null | l = float(input('Digite a largura da parede em metros: '))
h = float(input('Digite a altura da parede em metros: '))
a = l * h
q = a/2
print('A área da parede é de {}'.format(a))
print('Para pintar toda a parede, serão necessários {} litros de tinta'.format(q)) | 32.875 | 82 | 0.673004 | 48 | 263 | 3.6875 | 0.541667 | 0.135593 | 0.180791 | 0.19209 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00463 | 0.178707 | 263 | 8 | 82 | 32.875 | 0.814815 | 0 | 0 | 0 | 0 | 0 | 0.613636 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.333333 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
501ec9ad0cba370745d544a906e80bb06e521739 | 89 | py | Python | RadiAIDD/Backend/UI/__init__.py | jo-mueller/RadiAiDD | 1c73cca9035c71556ce525aa8e404c2012720221 | [
"MIT"
] | 7 | 2021-06-18T06:16:32.000Z | 2022-01-25T05:51:11.000Z | RadiAIDD/Backend/__init__.py | jo-mueller/RadiAiDD | 1c73cca9035c71556ce525aa8e404c2012720221 | [
"MIT"
] | 18 | 2020-08-24T13:45:35.000Z | 2022-01-14T15:55:58.000Z | RadiAIDD/Backend/__init__.py | jo-mueller/RadiAiDD | 1c73cca9035c71556ce525aa8e404c2012720221 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 15 14:47:44 2018
@author: muellejoh
"""
| 11.125 | 35 | 0.58427 | 14 | 89 | 3.714286 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.183099 | 0.202247 | 89 | 7 | 36 | 12.714286 | 0.549296 | 0.876404 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
503a54b32c708af3b6dbbc5dcc405e0c232617a8 | 213 | py | Python | py2md/classes/__init__.py | Xero64/py2md | d35f7163863bb3012d7285207c7e4378df20ffa5 | [
"MIT"
] | 4 | 2019-06-30T11:29:00.000Z | 2021-09-04T19:27:40.000Z | py2md/classes/__init__.py | Xero64/py2md | d35f7163863bb3012d7285207c7e4378df20ffa5 | [
"MIT"
] | null | null | null | py2md/classes/__init__.py | Xero64/py2md | d35f7163863bb3012d7285207c7e4378df20ffa5 | [
"MIT"
] | null | null | null | from .mdlist import MDList
from .mdtable import MDTable
from .mdheading import MDHeading
from .mdmatrix import MDMatrix
from .mdstring import MDString
from .mdreport import MDReport
from .mdfigure import MDFigure
| 26.625 | 32 | 0.835681 | 28 | 213 | 6.357143 | 0.321429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131455 | 213 | 7 | 33 | 30.428571 | 0.962162 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
5044bfcb34fe8172862f77ee97c78d74d875df71 | 974 | py | Python | src/pyrin/security/services.py | wilsonGmn/pyrin | 25dbe3ce17e80a43eee7cfc7140b4c268a6948e0 | [
"BSD-3-Clause"
] | null | null | null | src/pyrin/security/services.py | wilsonGmn/pyrin | 25dbe3ce17e80a43eee7cfc7140b4c268a6948e0 | [
"BSD-3-Clause"
] | null | null | null | src/pyrin/security/services.py | wilsonGmn/pyrin | 25dbe3ce17e80a43eee7cfc7140b4c268a6948e0 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
"""
security services module.
"""
from pyrin.application.services import get_component
from pyrin.security import SecurityPackage
def get_password_hash(password, **options):
"""
gets the given password's hash.
:param str password: password to get it's hash.
:keyword bool is_encrypted: specifies that given password is encrypted.
defaults to False if not provided.
:raises InvalidPasswordLengthError: invalid password length error.
:rtype: str
"""
return get_component(SecurityPackage.COMPONENT_NAME).get_password_hash(password, **options)
def encrypt(text, **options):
"""
encrypts the given text and returns the encrypted value.
:param str text: text to be encrypted.
:raises InvalidEncryptionTextLengthError: invalid encryption text length error.
:rtype: str
"""
return get_component(SecurityPackage.COMPONENT_NAME).encrypt(text, **options)
| 24.974359 | 95 | 0.706366 | 112 | 974 | 6.053571 | 0.473214 | 0.053097 | 0.044248 | 0.067847 | 0.280236 | 0.19174 | 0.19174 | 0.19174 | 0.19174 | 0.19174 | 0 | 0.001294 | 0.206366 | 974 | 38 | 96 | 25.631579 | 0.875809 | 0.551335 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0.333333 | 0.333333 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 4 |
505c89e3dacd9a09e02feb08b854da6f4841bf25 | 98 | py | Python | brilschema-run.py | xiezhen/brilws | e3652dd4506dff9d713184ff623b59bc11fbe2c7 | [
"MIT"
] | 1 | 2017-03-23T16:26:06.000Z | 2017-03-23T16:26:06.000Z | brilschema-run.py | xiezhen/brilws | e3652dd4506dff9d713184ff623b59bc11fbe2c7 | [
"MIT"
] | 1 | 2017-03-24T15:02:20.000Z | 2017-10-02T13:43:26.000Z | brilschema-run.py | xiezhen/brilws | e3652dd4506dff9d713184ff623b59bc11fbe2c7 | [
"MIT"
] | 1 | 2019-12-06T09:23:01.000Z | 2019-12-06T09:23:01.000Z | #!/usr/bin/env python
from brilws import cli
if __name__ == '__main__':
cli.brilschema_main()
| 19.6 | 26 | 0.714286 | 14 | 98 | 4.357143 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.153061 | 98 | 4 | 27 | 24.5 | 0.73494 | 0.204082 | 0 | 0 | 0 | 0 | 0.103896 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
ac99d860f0e836d3ce3ca1d301d69c460fed3281 | 525 | py | Python | archive/pim/api/json_adapters.py | aarongreenwald/pim | 425fb2e3708286ebbfe60c74a2fcdf2a30d748bb | [
"MIT"
] | null | null | null | archive/pim/api/json_adapters.py | aarongreenwald/pim | 425fb2e3708286ebbfe60c74a2fcdf2a30d748bb | [
"MIT"
] | 7 | 2020-09-25T17:26:33.000Z | 2022-02-19T06:33:27.000Z | archive/pim/api/json_adapters.py | aarongreenwald/pim | 425fb2e3708286ebbfe60c74a2fcdf2a30d748bb | [
"MIT"
] | null | null | null | from pyramid.renderers import JSON
import decimal
import datetime
def number_adapter(obj, request):
return float(obj)
def datetime_adapter(obj, request):
return datetime.datetime.isoformat(obj)
def date_adapter(obj, request):
return datetime_adapter(datetime.datetime(obj.year, obj.month, obj.day), request)
json_renderer = JSON()
json_renderer.add_adapter(decimal.Decimal, number_adapter)
json_renderer.add_adapter(datetime.datetime, datetime_adapter)
json_renderer.add_adapter(datetime.date, date_adapter) | 30.882353 | 83 | 0.809524 | 71 | 525 | 5.788732 | 0.295775 | 0.155718 | 0.124088 | 0.167883 | 0.3309 | 0.180049 | 0 | 0 | 0 | 0 | 0 | 0 | 0.099048 | 525 | 17 | 84 | 30.882353 | 0.868922 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.230769 | false | 0 | 0.230769 | 0.230769 | 0.692308 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
acaddd7b4fe703ef5bd137f65432fe0e7750999f | 43 | py | Python | python/testData/completion/identifiersInPlainDocstring.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 2 | 2018-12-29T09:53:39.000Z | 2018-12-29T09:53:42.000Z | python/testData/completion/identifiersInPlainDocstring.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 173 | 2018-07-05T13:59:39.000Z | 2018-08-09T01:12:03.000Z | python/testData/completion/identifiersInPlainDocstring.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 2 | 2020-03-15T08:57:37.000Z | 2020-04-07T04:48:14.000Z | def foo(bar):
""" Variable b<caret> """ | 21.5 | 29 | 0.534884 | 6 | 43 | 3.833333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.209302 | 43 | 2 | 29 | 21.5 | 0.676471 | 0.395349 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | false | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
acd01c9d2bbf4874b745fd9c4fc447ee75a2fe08 | 64 | py | Python | icevision_dashboards/plotting/__init__.py | ZivotJeKrasny/icevision_dashboards | 40d6b508e7684144c02c6d507c730415781207c7 | [
"Apache-2.0"
] | 10 | 2020-11-27T11:38:38.000Z | 2021-03-04T14:57:06.000Z | icevision_dashboards/plotting/__init__.py | ZivotJeKrasny/icevision_dashboards | 40d6b508e7684144c02c6d507c730415781207c7 | [
"Apache-2.0"
] | 5 | 2021-06-16T11:53:31.000Z | 2022-03-07T19:27:15.000Z | icevision_dashboards/plotting/__init__.py | ZivotJeKrasny/icevision_dashboards | 40d6b508e7684144c02c6d507c730415781207c7 | [
"Apache-2.0"
] | 2 | 2021-06-15T20:23:15.000Z | 2022-01-15T18:36:51.000Z | from .core import *
from . import utils
from .controls import *
| 16 | 23 | 0.734375 | 9 | 64 | 5.222222 | 0.555556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1875 | 64 | 3 | 24 | 21.333333 | 0.903846 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
acd937ae414d83549c78ad112adb18f95718455e | 272 | py | Python | accounts/admin.py | Bryson69/Customer-Management | ca23a9d504ea679961f8013e255cc607534695f4 | [
"MIT"
] | null | null | null | accounts/admin.py | Bryson69/Customer-Management | ca23a9d504ea679961f8013e255cc607534695f4 | [
"MIT"
] | null | null | null | accounts/admin.py | Bryson69/Customer-Management | ca23a9d504ea679961f8013e255cc607534695f4 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import *
# Import the class Customer
# Register your models here.
# Registering the table from the class Customer
admin.site.register(Customer)
admin.site.register(Product)
admin.site.register(Tag)
admin.site.register(Order)
| 24.727273 | 47 | 0.801471 | 39 | 272 | 5.589744 | 0.461538 | 0.165138 | 0.311927 | 0.229358 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.113971 | 272 | 10 | 48 | 27.2 | 0.904564 | 0.360294 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
acf274059275c3f98e94de651e6dfcdabe29711f | 227 | py | Python | utils/__init__.py | snuffle-PX/2048-api | a43c74c3cfcf47e3f79ab631705b46ddbe3add1e | [
"Apache-2.0"
] | null | null | null | utils/__init__.py | snuffle-PX/2048-api | a43c74c3cfcf47e3f79ab631705b46ddbe3add1e | [
"Apache-2.0"
] | null | null | null | utils/__init__.py | snuffle-PX/2048-api | a43c74c3cfcf47e3f79ab631705b46ddbe3add1e | [
"Apache-2.0"
] | null | null | null | from .move import try_to_move
from .rot_invariance import get_train_data, get_train_data_12
from .onehot import conv_to_onehot, conv_log_to_onehot, flatten_onehot, conv_to_onehot_12
from .memory import ReplayMemory, Transition
| 45.4 | 89 | 0.867841 | 38 | 227 | 4.736842 | 0.473684 | 0.133333 | 0.133333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019417 | 0.092511 | 227 | 4 | 90 | 56.75 | 0.854369 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
4a116353f68e1495d84e07ad19415a1580342eee | 101 | py | Python | allennlp_models/tokenizers/spacy_tokenizer.py | alvinwatner/allennlp-models | 7e767f00da836c5af59e39dc74852b484b45ef46 | [
"Apache-2.0"
] | null | null | null | allennlp_models/tokenizers/spacy_tokenizer.py | alvinwatner/allennlp-models | 7e767f00da836c5af59e39dc74852b484b45ef46 | [
"Apache-2.0"
] | null | null | null | allennlp_models/tokenizers/spacy_tokenizer.py | alvinwatner/allennlp-models | 7e767f00da836c5af59e39dc74852b484b45ef46 | [
"Apache-2.0"
] | null | null | null | # from allennlp.data.tokenizers import Token, Tokenizer, SpacyTokenizer
#
# SpacyTokenizer(language=) | 33.666667 | 71 | 0.811881 | 10 | 101 | 8.2 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.089109 | 101 | 3 | 72 | 33.666667 | 0.891304 | 0.940594 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
c5932a0a177924ead52f616b0ba3ad362dc2034d | 2,576 | py | Python | dfirtrack_main/tests/casetype/test_casetype_models.py | thomas-kropeit/dfirtrack | b1e0e659af7bc8085cfe2d269ddc651f9f4ba585 | [
"Apache-2.0"
] | 273 | 2018-04-18T22:09:15.000Z | 2021-06-04T09:15:48.000Z | dfirtrack_main/tests/casetype/test_casetype_models.py | stuhli/dfirtrack | 9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e | [
"Apache-2.0"
] | 75 | 2018-08-31T11:05:37.000Z | 2021-06-08T14:15:07.000Z | dfirtrack_main/tests/casetype/test_casetype_models.py | thomas-kropeit/dfirtrack | b1e0e659af7bc8085cfe2d269ddc651f9f4ba585 | [
"Apache-2.0"
] | 61 | 2018-11-12T22:55:48.000Z | 2021-06-06T15:16:16.000Z | from django.test import TestCase
from dfirtrack_main.models import Casetype
class CasetypeModelTestCase(TestCase):
"""casetype model tests"""
@classmethod
def setUpTestData(cls):
# create object
Casetype.objects.create(casetype_name='casetype_1')
def test_casetype_string(self):
"""test string representation"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# compare
self.assertEqual(str(casetype_1), 'casetype_1')
def test_casetype_id_attribute_label(self):
"""test attribute label"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get label
field_label = casetype_1._meta.get_field('casetype_id').verbose_name
# compare
self.assertEqual(field_label, 'casetype id')
def test_casetype_name_attribute_label(self):
"""test attribute label"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get label
field_label = casetype_1._meta.get_field('casetype_name').verbose_name
# compare
self.assertEqual(field_label, 'casetype name')
def test_casetype_note_attribute_label(self):
"""test attribute label"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get label
field_label = casetype_1._meta.get_field('casetype_note').verbose_name
# compare
self.assertEqual(field_label, 'casetype note')
def test_casetype_slug_attribute_label(self):
"""test attribute label"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get label
field_label = casetype_1._meta.get_field('casetype_slug').verbose_name
# compare
self.assertEqual(field_label, 'casetype slug')
def test_casetype_name_length(self):
"""test for max length"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get max length
max_length = casetype_1._meta.get_field('casetype_name').max_length
# compare
self.assertEqual(max_length, 255)
def test_casetype_slug_length(self):
"""test for max length"""
# get object
casetype_1 = Casetype.objects.get(casetype_name='casetype_1')
# get max length
max_length = casetype_1._meta.get_field('casetype_slug').max_length
# compare
self.assertEqual(max_length, 255)
| 31.414634 | 78 | 0.662267 | 303 | 2,576 | 5.326733 | 0.135314 | 0.128253 | 0.099133 | 0.104089 | 0.766419 | 0.736679 | 0.736679 | 0.726766 | 0.547088 | 0.547088 | 0 | 0.014826 | 0.240683 | 2,576 | 81 | 79 | 31.802469 | 0.810327 | 0.151009 | 0 | 0.272727 | 0 | 0 | 0.101599 | 0 | 0 | 0 | 0 | 0 | 0.212121 | 1 | 0.242424 | false | 0 | 0.060606 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
c5e5fc0d40bbe79523f31c1ae89b60a7e5458c9d | 43 | py | Python | input_words.py | Nocryset/VoKeep | 8812264ded073ef7a0a546441f2ef4768a207cb4 | [
"MIT"
] | null | null | null | input_words.py | Nocryset/VoKeep | 8812264ded073ef7a0a546441f2ef4768a207cb4 | [
"MIT"
] | null | null | null | input_words.py | Nocryset/VoKeep | 8812264ded073ef7a0a546441f2ef4768a207cb4 | [
"MIT"
] | null | null | null | user = [{name:""}]
select user
insert user | 10.75 | 18 | 0.651163 | 6 | 43 | 4.666667 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.162791 | 43 | 4 | 19 | 10.75 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
68014721e55827192a363b5512abd9fe3933270f | 8,499 | py | Python | tests/dicts/io/test_io_dict_csv.py | next-franciscoalgaba/python-benedict | 81ff459304868327238c322a0a8a203d9d5d4314 | [
"MIT"
] | 365 | 2019-05-21T05:50:30.000Z | 2022-03-29T11:35:35.000Z | tests/dicts/io/test_io_dict_csv.py | next-franciscoalgaba/python-benedict | 81ff459304868327238c322a0a8a203d9d5d4314 | [
"MIT"
] | 78 | 2019-11-16T12:22:54.000Z | 2022-03-14T12:21:30.000Z | tests/dicts/io/test_io_dict_csv.py | next-franciscoalgaba/python-benedict | 81ff459304868327238c322a0a8a203d9d5d4314 | [
"MIT"
] | 26 | 2019-12-16T06:34:12.000Z | 2022-02-28T07:16:41.000Z | # -*- coding: utf-8 -*-
from benedict.dicts.io import IODict
from .test_io_dict import io_dict_test_case
class io_dict_csv_test_case(io_dict_test_case):
def test_from_csv_with_valid_data(self):
s = """id,name,age,height,weight
1,Alice,20,62,120.6
2,Freddie,21,74,190.6
3,Bob,17,68,120.0
4,François,32,75,110.05
"""
r = {
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
}
# static method
d = IODict.from_csv(s)
self.assertTrue(isinstance(d, dict))
self.assertEqual(d, r)
# constructor
d = IODict(s, format='csv')
self.assertTrue(isinstance(d, dict))
self.assertEqual(d, r)
# def test_from_csv_with_invalid_data(self):
# s = 'Lorem ipsum est in ea occaecat nisi officia.'
# # static method
# with self.assertRaises(ValueError):
# print(IODict.from_csv(s))
# # constructor
# with self.assertRaises(ValueError):
# IODict(s, format='csv')
def test_from_csv_with_valid_file_valid_content(self):
filepath = self.input_path('valid-content.csv')
# static method
d = IODict.from_csv(filepath)
self.assertTrue(isinstance(d, dict))
# constructor
d = IODict(filepath, format='csv')
self.assertTrue(isinstance(d, dict))
# def test_from_csv_with_valid_file_valid_content_invalid_format(self):
# filepath = self.input_path('valid-content.base64')
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# filepath = self.input_path('valid-content.qs')
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# filepath = self.input_path('valid-content.toml')
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# filepath = self.input_path('valid-content.xml')
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# filepath = self.input_path('valid-content.yml')
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# def test_from_csv_with_valid_file_invalid_content(self):
# filepath = self.input_path('invalid-content.csv')
# # static method
# with self.assertRaises(ValueError):
# IODict.from_csv(filepath)
# # constructor
# with self.assertRaises(ValueError):
# IODict(filepath, format='csv')
def test_from_csv_with_invalid_file(self):
filepath = self.input_path('invalid-file.csv')
# static method
with self.assertRaises(ValueError):
IODict.from_csv(filepath)
# constructor
with self.assertRaises(ValueError):
IODict(filepath, format='csv')
# TODO: python 2.7 max compatibility
# def test_from_csv_with_valid_url_valid_content(self):
# url = self.input_url('valid-content.csv')
# # static method
# d = IODict.from_csv(url)
# self.assertTrue(isinstance(d, dict))
# # constructor
# d = IODict(url, format='csv')
# self.assertTrue(isinstance(d, dict))
# def test_from_csv_with_valid_url_invalid_content(self):
# url = 'https://github.com/fabiocaccamo/python-benedict'
# # static method
# with self.assertRaises(ValueError):
# IODict.from_csv(url)
# # constructor
# with self.assertRaises(ValueError):
# IODict(url, format='csv')
def test_from_csv_with_invalid_url(self):
url = 'https://github.com/fabiocaccamo/python-benedict-invalid'
# static method
with self.assertRaises(ValueError):
IODict.from_csv(url)
# constructor
with self.assertRaises(ValueError):
IODict(url, format='csv')
def test_to_csv(self):
d = IODict({
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
s = d.to_csv()
r = """age,height,id,name,weight
20,62,1,Alice,120.6
21,74,2,Freddie,190.6
17,68,3,Bob,120.0
32,75,4,François,110.05
"""
self.assertEqual(s, r)
def test_to_csv_with_custom_columns(self):
d = IODict({
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
s = d.to_csv(key='values', columns=['id', 'name', 'family_name', 'age', 'height', 'gender', 'weight'])
r = """id,name,family_name,age,height,gender,weight
1,Alice,,20,62,,120.6
2,Freddie,,21,74,,190.6
3,Bob,,17,68,,120.0
4,François,,32,75,,110.05
"""
self.assertEqual(s, r)
def test_to_csv_with_custom_delimiter_and_quotes(self):
d = IODict({
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
s = d.to_csv(columns=['id', 'name', 'age', 'height', 'weight'], delimiter=";", quote=True)
r = """"id";"name";"age";"height";"weight"
"1";"Alice";"20";"62";"120.6"
"2";"Freddie";"21";"74";"190.6"
"3";"Bob";"17";"68";"120.0"
"4";"François";"32";"75";"110.05"
"""
self.assertEqual(s, r)
def test_to_csv_with_custom_key_valid(self):
d = IODict({
'results': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
s = d.to_csv('results', columns=['id', 'name', 'age', 'height', 'weight'])
r = """id,name,age,height,weight
1,Alice,20,62,120.6
2,Freddie,21,74,190.6
3,Bob,17,68,120.0
4,François,32,75,110.05
"""
self.assertEqual(s, r)
def test_to_csv_with_custom_key_invalid(self):
d = IODict({
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
with self.assertRaises(KeyError):
s = d.to_csv('invalid_values', columns=['id', 'name', 'age', 'height', 'weight'])
def test_to_csv_file(self):
d = IODict({
'values': [
{ 'id':'1', 'name':'Alice', 'age':'20', 'height':'62', 'weight':'120.6', },
{ 'id':'2', 'name':'Freddie', 'age':'21', 'height':'74', 'weight':'190.6', },
{ 'id':'3', 'name':'Bob', 'age':'17', 'height':'68', 'weight':'120.0', },
{ 'id':'4', 'name':'François', 'age':'32', 'height':'75', 'weight':'110.05', },
],
})
filepath = self.output_path('test_to_csv_file.csv')
d.to_csv(filepath=filepath)
self.assertFileExists(filepath)
self.assertEqual(d, IODict.from_csv(filepath))
| 40.089623 | 110 | 0.525944 | 1,045 | 8,499 | 4.149282 | 0.099522 | 0.037131 | 0.073801 | 0.103782 | 0.8381 | 0.831181 | 0.757841 | 0.726476 | 0.645756 | 0.592943 | 0 | 0.071417 | 0.260266 | 8,499 | 211 | 111 | 40.279621 | 0.61826 | 0.237557 | 0 | 0.597015 | 0 | 0 | 0.30485 | 0.074068 | 0 | 0 | 0 | 0.004739 | 0.126866 | 1 | 0.074627 | false | 0 | 0.014925 | 0 | 0.097015 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
6814885b3ce6b60ff916b9932ef895fc1012cad9 | 42 | py | Python | create_system_announcement.py | ultirian/USW_CW2_PYTHON_SQL_IMPLEMENT | 4826cac6411254bf85222171d405d3c77c0dbf81 | [
"Unlicense"
] | null | null | null | create_system_announcement.py | ultirian/USW_CW2_PYTHON_SQL_IMPLEMENT | 4826cac6411254bf85222171d405d3c77c0dbf81 | [
"Unlicense"
] | null | null | null | create_system_announcement.py | ultirian/USW_CW2_PYTHON_SQL_IMPLEMENT | 4826cac6411254bf85222171d405d3c77c0dbf81 | [
"Unlicense"
] | null | null | null | # coding=utf-8
# Libraries
# Functions
| 10.5 | 15 | 0.666667 | 5 | 42 | 5.6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.030303 | 0.214286 | 42 | 3 | 16 | 14 | 0.818182 | 0.761905 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a83bd811eeba69896e238b9e187178a4e652f68c | 10,031 | py | Python | build_framework/environment.py | kdschlosser/wxAnimation | ad472719a77a081da5e51280d469cfd5d5bfcd3c | [
"MIT"
] | 2 | 2020-03-23T11:29:56.000Z | 2021-11-24T22:10:07.000Z | build_framework/environment.py | kdschlosser/wxAnimation | ad472719a77a081da5e51280d469cfd5d5bfcd3c | [
"MIT"
] | null | null | null | build_framework/environment.py | kdschlosser/wxAnimation | ad472719a77a081da5e51280d469cfd5d5bfcd3c | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import print_function
import sys
import os
from distutils.spawn import find_executable
def check_packages():
pkg_config = find_executable("pkg-config")
print("Found pkg-config : {0}".format(pkg_config))
if pkg_config:
from . import pkgconfig
packages = ['']
for package in pkgconfig.list_all():
if len(packages[-1] + package + ', ') > 78:
packages += ['']
packages[len(packages) - 1] += package + ', '
packages = '\n'.join(' ' + pkg for pkg in packages)[:-2]
print('Installed packages:')
print(packages)
def setup():
if sys.platform.startswith('win'):
from . import msvc
print(msvc.environment)
os.environ['LD'] = 'lib.exe'
os.environ['AR'] = 'link.exe'
os.environ['CXX'] = 'cl.exe'
os.environ['CC'] = 'cl.exe'
os.environ['RANLIB'] = ''
elif sys.platform.startswith("cygwin"):
gcc = find_executable("gcc")
gpp = find_executable("g++")
ar = find_executable('ar')
ld = find_executable('ld')
ranlib = find_executable('ranlib')
cc = os.environ.get('CC', '')
cxx = os.environ.get('CXX', '')
ar_env = os.environ.get('AR', '')
ld_env = os.environ.get('LD', '')
ranlib_env = os.environ.get('RANLIB', '')
if ld:
if ld != ld_env and ar_env.endswith('ld'):
ld = ld_env
else:
os.environ['LD'] = ld
elif ld_env.endswith('ld'):
ld = ld_env
else:
raise RuntimeError('Unable to locate ld')
if ranlib:
if ranlib != ranlib_env and ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
os.environ['RANLIB'] = ranlib
elif ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
raise RuntimeError('Unable to locate ranlib')
if ar:
if ar != ar_env and ar_env.endswith('ar'):
ar = ar_env
else:
os.environ['AR'] = ar
elif ar_env.endswith('ar'):
ar = ar_env
else:
raise RuntimeError('Unable to locate ar')
if gcc:
if gcc != cc and cc.endswith('gcc'):
gcc = cc
else:
os.environ['CC'] = gcc
elif cc.endswith('gcc'):
gcc = cc
else:
raise RuntimeError('Unable to locate gcc')
print("Found gcc : {0}".format(gcc))
if gpp:
if gpp != cxx and cxx.endswith('g++'):
gpp = cxx
else:
os.environ['CXX'] = gpp
elif cxx.endswith('g++'):
gpp = cxx
else:
raise RuntimeError('Unable to locate g++')
print("Found g++ : {0}".format(gpp))
print("Found ar : {0}".format(ar))
print("Found ld : {0}".format(ld))
print("Found ranlib : {0}".format(ranlib))
check_packages()
elif sys.platform.startswith("darwin"):
clang = find_executable("clang")
clang_pp = find_executable("clang++")
ar = find_executable('ar')
ld = find_executable('ld')
ranlib = find_executable('ranlib')
cc = os.environ.get('CC', '')
cxx = os.environ.get('CXX', '')
ar_env = os.environ.get('AR', '')
ld_env = os.environ.get('LD', '')
ranlib_env = os.environ.get('RANLIB', '')
if ranlib:
ranlib = 'ranlib'
if ranlib != ranlib_env and ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
os.environ['RANLIB'] = 'ranlib'
elif ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
raise RuntimeError('Unable to locate ranlib')
if ar:
if ar != ar_env and ar_env.endswith('ar'):
ar = ar_env
else:
os.environ['AR'] = 'ar'
elif ar_env.endswith('ar'):
ar = ar_env
else:
raise RuntimeError('Unable to locate ar')
if clang:
if clang != cc and cc.endswith('clang'):
clang = cc
else:
os.environ['CC'] = clang
elif cc.endswith('clang'):
clang = cc
else:
raise RuntimeError('Unable to locate clang')
print("Found clang : {0}".format(clang))
if clang_pp:
if clang_pp != cxx and cxx.endswith('clang++'):
clang_pp = cxx
else:
os.environ['CXX'] = clang_pp
elif cxx.endswith('clang++'):
clang_pp = cxx
else:
raise RuntimeError('Unable to locate clang++')
if ld:
if ld != ld_env and ar_env.endswith('ld'):
ld = ld_env
else:
os.environ['LD'] = 'ld'
elif ld_env.endswith('ld'):
ld = ld_env
else:
ld = 'ld'
os.environ['LD'] = 'ld'
print("Found clang : {0}".format(clang))
print("Found clang++ : {0}".format(clang_pp))
print("Found ar : {0}".format(ar))
print("Found ld : {0}".format(ld))
print("Found ranlib : {0}".format(ranlib))
check_packages()
elif sys.platform.startswith('freebsd'):
c = find_executable("cc")
cpp = find_executable("c++")
gmake = find_executable("gmake")
cc = os.environ.get('CC', '')
cxx = os.environ.get('CXX', '')
if not gmake:
raise RuntimeError('Unable to locate gmake')
if c:
if c != cc and cc.endswith('cc'):
c = cc
else:
os.environ['CC'] = c
elif cc.endswith('cc'):
c = cc
else:
raise RuntimeError('Unable to locate cc')
print("Found cc : {0}".format(c))
if cpp:
if cpp != cxx and cxx.endswith('c++'):
cpp = cxx
else:
os.environ['CXX'] = cpp
elif cxx.endswith('c++'):
cpp = cxx
else:
raise RuntimeError('Unable to locate c++')
print("Found c++ : {0}".format(cpp))
print("Found gmake : {0}".format(gmake))
check_packages()
os.environ['LD'] = cpp
os.environ['AR'] = 'ar'
os.environ['RANLIB'] = 'ranlib'
elif sys.platform.startswith('sunos'):
gcc = find_executable("gcc")
gpp = find_executable("g++")
make = find_executable("make")
cc = os.environ.get('CC', '')
cxx = os.environ.get('CXX', '')
if not make:
raise RuntimeError('Unable to locate make')
if gcc:
if gcc != cc and cc.endswith('gcc'):
gcc = cc
else:
os.environ['CC'] = gcc
elif cc.endswith('gcc'):
gcc = cc
else:
raise RuntimeError('Unable to locate gcc')
print("Found gcc : {0}".format(gcc))
if gpp:
if gpp != cxx and cxx.endswith('g++'):
gpp = cxx
else:
os.environ['CXX'] = gpp
elif cxx.endswith('g++'):
gpp = cxx
else:
raise RuntimeError('Unable to locate g++')
print("Found g++ : {0}".format(gpp))
print("Found make : {0}".format(make))
check_packages()
os.environ['LD'] = gpp
os.environ['AR'] = 'ar'
os.environ['RANLIB'] = 'ranlib'
elif sys.platform.startswith('linux'):
gcc = find_executable("gcc")
gpp = find_executable("g++")
ar = find_executable('ar')
ld = find_executable('ld')
ranlib = find_executable('ranlib')
cc = os.environ.get('CC', '')
cxx = os.environ.get('CXX', '')
ar_env = os.environ.get('AR', '')
ld_env = os.environ.get('LD', '')
ranlib_env = os.environ.get('RANLIB', '')
if ranlib:
ranlib = 'ranlib'
if ranlib != ranlib_env and ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
os.environ['RANLIB'] = 'ranlib'
elif ranlib_env.endswith('ranlib'):
ranlib = ranlib_env
else:
raise RuntimeError('Unable to locate ranlib')
if ar:
if ar != ar_env and ar_env.endswith('ar'):
ar = ar_env
else:
os.environ['AR'] = 'ar'
elif ar_env.endswith('ar'):
ar = ar_env
else:
raise RuntimeError('Unable to locate ar')
if gcc:
if gcc != cc and cc.endswith('gcc'):
gcc = cc
else:
os.environ['CC'] = 'gcc'
elif cc.endswith('gcc'):
gcc = cc
else:
raise RuntimeError('Unable to locate gcc')
print("Found gcc : {0}".format(gcc))
if gpp:
if gpp != cxx and cxx.endswith('g++'):
gpp = cxx
else:
os.environ['CXX'] = 'g++'
elif cxx.endswith('g++'):
gpp = cxx
else:
raise RuntimeError('Unable to locate g++')
if ld:
if ld != ld_env and ar_env.endswith('ld'):
ld = ld_env
else:
os.environ['LD'] = 'ld'
elif ld_env.endswith('ld'):
ld = ld_env
else:
ld = gpp
os.environ['LD'] = 'g++'
print("Found gcc : {0}".format(gcc))
print("Found g++ : {0}".format(gpp))
print("Found ar : {0}".format(ar))
print("Found ld : {0}".format(ld))
print("Found ranlib : {0}".format(ranlib))
check_packages()
else:
raise RuntimeError(
"No Library available for platform {0}".format(sys.platform)
)
| 29.159884 | 72 | 0.478218 | 1,132 | 10,031 | 4.150177 | 0.071555 | 0.097701 | 0.048531 | 0.101107 | 0.789485 | 0.749681 | 0.715624 | 0.651128 | 0.64304 | 0.64304 | 0 | 0.004984 | 0.379922 | 10,031 | 343 | 73 | 29.244898 | 0.750322 | 0.002094 | 0 | 0.722222 | 0 | 0 | 0.131894 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.006944 | false | 0 | 0.020833 | 0 | 0.027778 | 0.097222 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a83ff4d27c7a01bf1b5d4deac419883f6e680639 | 338 | py | Python | tests/test_happy_number.py | dhanraj-vedanth/Leetcode | b8b3283fc443b9ead769f8e3c720fc6c5d7633a6 | [
"MIT"
] | null | null | null | tests/test_happy_number.py | dhanraj-vedanth/Leetcode | b8b3283fc443b9ead769f8e3c720fc6c5d7633a6 | [
"MIT"
] | null | null | null | tests/test_happy_number.py | dhanraj-vedanth/Leetcode | b8b3283fc443b9ead769f8e3c720fc6c5d7633a6 | [
"MIT"
] | null | null | null | import unittest
from happy_number_202.main import Solution
class HappyTest(unittest.TestCase):
def test_true(self):
self.solution = Solution()
self.assertEqual(self.solution.isHappy(19), True)
def test_false(self):
self.solution = Solution()
self.assertEqual(self.solution.isHappy(5), False)
| 26 | 57 | 0.695266 | 41 | 338 | 5.634146 | 0.487805 | 0.207792 | 0.138528 | 0.207792 | 0.502165 | 0.502165 | 0.502165 | 0.502165 | 0.502165 | 0 | 0 | 0.022222 | 0.201183 | 338 | 12 | 58 | 28.166667 | 0.833333 | 0 | 0 | 0.222222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222222 | 1 | 0.222222 | false | 0 | 0.222222 | 0 | 0.555556 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
a842d05a77e1f952c3df462f79a7e8fea624e157 | 23 | py | Python | horovod/__init__.py | fossabot/horovod | 4eaae291fae03e9f854630088187dba7594457e7 | [
"BSD-3-Clause"
] | 30 | 2015-01-13T22:06:37.000Z | 2022-02-06T18:45:45.000Z | horovod/__init__.py | fossabot/horovod | 4eaae291fae03e9f854630088187dba7594457e7 | [
"BSD-3-Clause"
] | 72 | 2018-08-20T14:36:53.000Z | 2019-11-20T17:41:03.000Z | horovod/__init__.py | fossabot/horovod | 4eaae291fae03e9f854630088187dba7594457e7 | [
"BSD-3-Clause"
] | 22 | 2015-08-04T16:33:04.000Z | 2021-05-25T20:26:07.000Z | __version__ = '0.15.0'
| 11.5 | 22 | 0.652174 | 4 | 23 | 2.75 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 0.130435 | 23 | 1 | 23 | 23 | 0.35 | 0 | 0 | 0 | 0 | 0 | 0.26087 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a85ddee17472b9f637869764bc63a5f97c21801f | 270 | py | Python | api/barriers/migrations/0019_merge_20181023_1423.py | cad106uk/market-access-api | a357c33bbec93408b193e598a5628634126e9e99 | [
"MIT"
] | null | null | null | api/barriers/migrations/0019_merge_20181023_1423.py | cad106uk/market-access-api | a357c33bbec93408b193e598a5628634126e9e99 | [
"MIT"
] | 51 | 2018-05-31T12:16:31.000Z | 2022-03-08T09:36:48.000Z | api/barriers/migrations/0019_merge_20181023_1423.py | cad106uk/market-access-api | a357c33bbec93408b193e598a5628634126e9e99 | [
"MIT"
] | 2 | 2019-12-24T09:47:42.000Z | 2021-02-09T09:36:51.000Z | # Generated by Django 2.1.2 on 2018-10-23 14:23
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("barriers", "0018_auto_20181022_2148"),
("barriers", "0018_auto_20181012_1426"),
]
operations = []
| 19.285714 | 48 | 0.662963 | 33 | 270 | 5.242424 | 0.757576 | 0.138728 | 0.184971 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.221698 | 0.214815 | 270 | 13 | 49 | 20.769231 | 0.59434 | 0.166667 | 0 | 0 | 1 | 0 | 0.278027 | 0.206278 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
a867c20639cba5d5a7c794d3e26da5a16d3c4a00 | 317 | py | Python | pymnn/pip_package/MNN/tools/utils/opname.py | GHLab/MNN | 9f1555ffdde9df84faf41dcf6beecba8f0e227f4 | [
"Apache-2.0"
] | 3 | 2019-12-27T01:10:32.000Z | 2021-05-14T08:10:40.000Z | pymnn/pip_package/MNN/tools/utils/opname.py | GHLab/MNN | 9f1555ffdde9df84faf41dcf6beecba8f0e227f4 | [
"Apache-2.0"
] | 10 | 2019-07-04T01:40:13.000Z | 2019-10-30T02:38:42.000Z | pymnn/pip_package/MNN/tools/utils/opname.py | chrisYooh/MNN | 9f1555ffdde9df84faf41dcf6beecba8f0e227f4 | [
"Apache-2.0"
] | 1 | 2019-12-06T06:53:51.000Z | 2019-12-06T06:53:51.000Z | # Copyright @ 2019 Alibaba. All rights reserved.
# Created by ruhuan on 2019.09.09
""" python OP API """
import MNN.tools.mnn_fb.OpType as OpType
import MNN.tools.utils.getkey as GetKey
def optype_to_name(op_type):
"""convert from op type to op name """
return GetKey.get_key(OpType.OpType.__dict__, op_type)
| 35.222222 | 58 | 0.741325 | 53 | 317 | 4.245283 | 0.603774 | 0.08 | 0.124444 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.04461 | 0.15142 | 317 | 8 | 59 | 39.625 | 0.791822 | 0.400631 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.5 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
a86e0eb7bc1d3efa50617454237ad2528cc74377 | 260 | py | Python | Pyton_curso/Python_introducao.py | HigorAnjos/Fundamentos-VI | e0aa3cb37e4c54d24ac7123ea3bd8038196e0edb | [
"MIT"
] | null | null | null | Pyton_curso/Python_introducao.py | HigorAnjos/Fundamentos-VI | e0aa3cb37e4c54d24ac7123ea3bd8038196e0edb | [
"MIT"
] | null | null | null | Pyton_curso/Python_introducao.py | HigorAnjos/Fundamentos-VI | e0aa3cb37e4c54d24ac7123ea3bd8038196e0edb | [
"MIT"
] | null | null | null | # https://anandology.com/python-practice-book/working-with-data.html
# https://www.youtube.com/watch?v=vmEHCJofslg&ab_channel=KeithGalli
# https://www.youtube.com/watch?v=hp-FGSKVPy4&list=PLyqOvdQmGdTR46HUxDA6Ymv4DGsIjvTQ-&index=13&ab_channel=Did%C3%A1ticaTech | 86.666667 | 123 | 0.819231 | 37 | 260 | 5.702703 | 0.72973 | 0.075829 | 0.14218 | 0.170616 | 0.227488 | 0.227488 | 0 | 0 | 0 | 0 | 0 | 0.035294 | 0.019231 | 260 | 3 | 123 | 86.666667 | 0.792157 | 0.976923 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a871f5aef53747e11eb01ec78be6c56466b3ce53 | 9,550 | py | Python | pot/invoke_saving_pot.py | punica-box/saving-pot-box | 8824e3621b21a8e06ac398c29e7ec07ac1442d1f | [
"MIT"
] | 1 | 2018-11-17T10:37:38.000Z | 2018-11-17T10:37:38.000Z | pot/invoke_saving_pot.py | NashMiao/saving-pot-box | 0ea7b0ee4be8aadf069faacf1d862d7412d5b4da | [
"MIT"
] | null | null | null | pot/invoke_saving_pot.py | NashMiao/saving-pot-box | 0ea7b0ee4be8aadf069faacf1d862d7412d5b4da | [
"MIT"
] | 1 | 2018-11-10T15:56:58.000Z | 2018-11-10T15:56:58.000Z | # !/usr/bin/env python3
# -*- coding: utf-8 -*-
import binascii
import time
from ontology.exception.exception import SDKException
from ontology.ont_sdk import OntologySdk
from ontology.account.account import Account
from ontology.smart_contract.neo_contract.abi.abi_info import AbiInfo
from pot.pot_exception import (
PotException,
PotError
)
class InvokeSavingPot(object):
def __init__(self, sdk: OntologySdk, abi: dict, hex_contract_address: str):
if not isinstance(sdk, OntologySdk):
raise PotException(PotError.invalid_sdk)
if not isinstance(abi, dict):
raise PotException(PotError.invalid_abi_type)
if not isinstance(hex_contract_address, str):
raise PotException(PotError.invalid_contract_address_hex_type)
if len(hex_contract_address) != 40:
raise PotException(PotError.invalid_contract_address_hex_len)
self.__sdk = sdk
self.__contract_address_hex = hex_contract_address
self.__contract_address_bytearray = bytearray(binascii.a2b_hex(hex_contract_address))
self.__contract_address_bytearray.reverse()
self.__abi = abi
entry_point = self.__abi.get('entrypoint', '')
functions = self.__abi['abi']['functions']
events = self.__abi.get('events', list())
self.__abi_info = AbiInfo(hex_contract_address, entry_point, functions, events)
def get_contract_address_hex(self):
return self.__contract_address_hex
def create_ont_pot(self, from_acct: Account, time_limit: int, gas_limit: int = 20000000, gas_price: int = 500):
create_function = self.__abi_info.get_function('create_ont_pot')
create_function.set_params_value((from_acct.get_address().to_array(), time_limit))
try:
tx_hash = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, create_function, False)
return tx_hash
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ont_pot_failed)
def create_ong_pot(self, from_acct: Account, time_limit: int, gas_limit: int, gas_price: int):
create_function = self.__abi_info.get_function('create_ong_pot')
create_function.set_params_value((from_acct.get_address().to_array(), time_limit))
try:
tx_hash = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, create_function, False)
return tx_hash
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def put_ont_pot_tx_hash(self, from_acct: Account, tx_hash: str, gas_limit: int, gas_price: int):
put_ont_pot_tx_hash = self.__abi_info.get_function('put_ont_pot_tx_hash')
put_ont_pot_tx_hash.set_params_value((from_acct.get_address().to_array(), tx_hash))
try:
tx_hash = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, put_ont_pot_tx_hash, False)
return tx_hash
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def get_ont_pot_tx_hash(self, bytearray_address: bytearray):
get_ont_pot_tx_hash = self.__abi_info.get_function('get_ont_pot_tx_hash')
get_ont_pot_tx_hash.set_params_value((bytearray_address,))
try:
data = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, None, None,
0, 0, get_ont_pot_tx_hash, True)
data = binascii.a2b_hex(data).decode('ascii')
return data
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def put_ong_pot_tx_hash(self, from_acct: Account, tx_hash: str, gas_limit: int, gas_price: int):
put_ont_pot_tx_hash = self.__abi_info.get_function('put_ong_pot_tx_hash')
put_ont_pot_tx_hash.set_params_value((from_acct.get_address().to_array(), tx_hash))
try:
return self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, put_ont_pot_tx_hash, False)
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def get_ong_pot_tx_hash(self, bytearray_address: bytearray):
get_ont_pot_tx_hash = self.__abi_info.get_function('get_ong_pot_tx_hash')
get_ont_pot_tx_hash.set_params_value((bytearray_address,))
try:
data = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, None, None,
0, 0, get_ont_pot_tx_hash, True)
data = binascii.a2b_hex(data).decode('ascii')
return data
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def saving_ont(self, from_acct: Account, amount: int, gas_limit: int, gas_price: int):
saving_ont = self.__abi_info.get_function('saving_ont')
saving_ont.set_params_value((from_acct.get_address().to_array(), amount))
try:
return self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, saving_ont, False)
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def saving_ong(self, from_acct: Account, amount: int, gas_limit: int, gas_price: int):
saving_ong = self.__abi_info.get_function('saving_ong')
saving_ong.set_params_value((from_acct.get_address().to_array(), amount))
try:
return self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, saving_ong, False)
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def take_ong_out(self, from_acct: Account, gas_limit: int, gas_price: int):
take_ong_out = self.__abi_info.get_function('take_ong_out')
take_ong_out.set_params_value((from_acct.get_address().to_array(),))
try:
tx_hash = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, from_acct, from_acct,
gas_limit, gas_price, take_ong_out, False)
return tx_hash
except SDKException as e:
if 'vm execute state fault' in e.args[1]:
return False
else:
raise PotException(PotError.create_ong_pot_failed)
def query_ont_pot_saving_time(self, address_bytes: bytes) -> int:
query_function = self.__abi_info.get_function('query_ont_pot_saving_time')
query_function.set_params_value((address_bytes,))
saving_time = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, None, None, 0, 0,
query_function, True)
saving_time = int(''.join(reversed([saving_time[i:i + 2] for i in range(0, len(saving_time), 2)])), 16)
return saving_time
def query_ong_pot_saving_time(self, address_bytes: bytes) -> int:
query_function = self.__abi_info.get_function('query_ong_pot_saving_time')
query_function.set_params_value((address_bytes,))
saving_time = self.__sdk.neo_vm().send_transaction(self.__contract_address_bytearray, None, None, 0, 0,
query_function, True)
saving_time = int(''.join(reversed([saving_time[i:i + 2] for i in range(0, len(saving_time), 2)])), 16)
return saving_time
def query_create_pot_event(self, tx_hash: str):
event = self.__sdk.rpc.get_smart_contract_event_by_tx_hash(tx_hash)
if event == '':
return list()
event = event.get('Notify', list())
if len(event) == 0:
return event
event = event[0].get('States', list())
if len(event) == 0:
return event
event[0] = binascii.a2b_hex(event[0]).decode('ascii')
event[1] = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(
int(''.join(reversed([event[1][i:i + 2] for i in range(0, len(event[1]), 2)])), 16)))
return event
| 51.069519 | 115 | 0.631414 | 1,227 | 9,550 | 4.503667 | 0.098615 | 0.038002 | 0.032573 | 0.034745 | 0.777778 | 0.767463 | 0.752262 | 0.732175 | 0.68802 | 0.677705 | 0 | 0.008569 | 0.279058 | 9,550 | 186 | 116 | 51.344086 | 0.794045 | 0.004503 | 0 | 0.584337 | 0 | 0 | 0.04798 | 0.005261 | 0 | 0 | 0 | 0 | 0 | 1 | 0.084337 | false | 0 | 0.042169 | 0.006024 | 0.283133 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a89be80466b1409eab24151286163d56743169af | 201 | py | Python | tests/syntax/assign_to_function_call_3.py | friendly-traceback/friendly-traceback | 4f6785f14c271a4d6412ef19c140f9d380cdbcbf | [
"MIT"
] | 45 | 2021-07-06T03:30:20.000Z | 2022-03-16T17:30:58.000Z | tests/syntax/assign_to_function_call_3.py | friendly-traceback/friendly-traceback | 4f6785f14c271a4d6412ef19c140f9d380cdbcbf | [
"MIT"
] | 110 | 2021-06-28T11:48:46.000Z | 2022-03-25T20:41:25.000Z | tests/syntax/assign_to_function_call_3.py | friendly-traceback/friendly-traceback | 4f6785f14c271a4d6412ef19c140f9d380cdbcbf | [
"MIT"
] | 4 | 2021-07-05T20:56:39.000Z | 2021-11-11T20:24:34.000Z | """Should raise SyntaxError: can't assign to function call
Python 3.8: SyntaxError: cannot assign to function call
"""
# tests for continuation marker
a = f(1, 2, # this is a comment
3, 4) = 5
| 25.125 | 58 | 0.686567 | 33 | 201 | 4.181818 | 0.787879 | 0.115942 | 0.231884 | 0.289855 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.044304 | 0.21393 | 201 | 7 | 59 | 28.714286 | 0.829114 | 0.233831 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a8a632c63764485ae787602f43b246f27cbb4e79 | 784 | py | Python | nets/CitationGraphs_node_classification/load_net.py | sejunssi/benchmarking_gnns | 881c92850f5366f7f8ca008da375037a41936681 | [
"MIT"
] | 1 | 2020-04-06T14:54:09.000Z | 2020-04-06T14:54:09.000Z | nets/CitationGraphs_node_classification/load_net.py | sejunssi/benchmarking_gnns | 881c92850f5366f7f8ca008da375037a41936681 | [
"MIT"
] | null | null | null | nets/CitationGraphs_node_classification/load_net.py | sejunssi/benchmarking_gnns | 881c92850f5366f7f8ca008da375037a41936681 | [
"MIT"
] | null | null | null | """
Utility file to select GraphNN model as
selected by the user
"""
from nets.CitationGraphs_node_classification.gcn_net import GCNNet
from nets.CitationGraphs_node_classification.gat_net import GATNet
from nets.CitationGraphs_node_classification.graphsage_net import GraphSageNet
from nets.CitationGraphs_node_classification.mlp_net import MLPNet
def GCN(net_params):
return GCNNet(net_params)
def GAT(net_params):
return GATNet(net_params)
def GraphSage(net_params):
return GraphSageNet(net_params)
def MLP(net_params):
return MLPNet(net_params)
def gnn_model(MODEL_NAME, net_params):
models = {
'GCN': GCN,
'GAT': GAT,
'GraphSage': GraphSage,
'MLP': MLP,
}
return models[MODEL_NAME](net_params)
| 23.058824 | 78 | 0.734694 | 101 | 784 | 5.455446 | 0.316832 | 0.163339 | 0.15971 | 0.188748 | 0.290381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1875 | 784 | 33 | 79 | 23.757576 | 0.864992 | 0.076531 | 0 | 0 | 0 | 0 | 0.025424 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.2 | 0.2 | 0.7 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
a8a864b4853a7507052408418708caf6ad58628c | 38 | py | Python | s3netcdfapi/export/shapefile.py | meracan/s3-netcdf-api | 920d09ef7b1a205230ea2c76eabcb4853616992c | [
"MIT"
] | 1 | 2020-08-30T01:47:45.000Z | 2020-08-30T01:47:45.000Z | s3netcdfapi/export/shapefile.py | meracan/s3-netcdf-api | 920d09ef7b1a205230ea2c76eabcb4853616992c | [
"MIT"
] | null | null | null | s3netcdfapi/export/shapefile.py | meracan/s3-netcdf-api | 920d09ef7b1a205230ea2c76eabcb4853616992c | [
"MIT"
] | null | null | null | # pyshape
def shapefile(data):
None | 9.5 | 20 | 0.710526 | 5 | 38 | 5.4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184211 | 38 | 4 | 21 | 9.5 | 0.870968 | 0.184211 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a8b0db2d6c78c554dbf03cf253e74f1713639d20 | 1,025 | py | Python | pynitrokey/nethsm/client/__init__.py | sgued/pynitrokey | 0499b4283739de5ac451916a22527fa5151ab5db | [
"Apache-2.0",
"MIT"
] | 15 | 2020-08-05T14:37:37.000Z | 2022-02-20T13:47:41.000Z | pynitrokey/nethsm/client/__init__.py | sgued/pynitrokey | 0499b4283739de5ac451916a22527fa5151ab5db | [
"Apache-2.0",
"MIT"
] | 153 | 2020-06-22T13:09:41.000Z | 2022-03-31T10:25:14.000Z | pynitrokey/nethsm/client/__init__.py | sgued/pynitrokey | 0499b4283739de5ac451916a22527fa5151ab5db | [
"Apache-2.0",
"MIT"
] | 4 | 2021-04-06T07:08:59.000Z | 2022-02-14T14:26:38.000Z | # flake8: noqa
"""
NetHSM
All endpoints expect exactly the specified JSON. Additional properties will cause a Bad Request Error (400). All HTTP errors contain a JSON structure with an explanation of type string. All <a href=\"https://tools.ietf.org/html/rfc4648#section-4\">base64</a> encoded values are Big Endian. # noqa: E501
The version of the OpenAPI document: v1
Generated by: https://openapi-generator.tech
"""
__version__ = "1.0.0"
# import ApiClient
from pynitrokey.nethsm.client.api_client import ApiClient
# import Configuration
from pynitrokey.nethsm.client.configuration import Configuration
# import exceptions
from pynitrokey.nethsm.client.exceptions import OpenApiException
from pynitrokey.nethsm.client.exceptions import ApiAttributeError
from pynitrokey.nethsm.client.exceptions import ApiTypeError
from pynitrokey.nethsm.client.exceptions import ApiValueError
from pynitrokey.nethsm.client.exceptions import ApiKeyError
from pynitrokey.nethsm.client.exceptions import ApiException
| 36.607143 | 307 | 0.805854 | 132 | 1,025 | 6.219697 | 0.522727 | 0.136419 | 0.194884 | 0.25335 | 0.306943 | 0.306943 | 0 | 0 | 0 | 0 | 0 | 0.02 | 0.121951 | 1,025 | 27 | 308 | 37.962963 | 0.892222 | 0.453659 | 0 | 0 | 0 | 0 | 0.009416 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.888889 | 0 | 0.888889 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
a8d7618788c23c6cf12fd99da772de2a74e2c57f | 209 | py | Python | src/meteringpoints_shared/bus.py | RasmusGodske/po-meteringpoints | 0723a891423c68241b7eb78e0de7756f99ea4b6d | [
"Apache-2.0"
] | null | null | null | src/meteringpoints_shared/bus.py | RasmusGodske/po-meteringpoints | 0723a891423c68241b7eb78e0de7756f99ea4b6d | [
"Apache-2.0"
] | null | null | null | src/meteringpoints_shared/bus.py | RasmusGodske/po-meteringpoints | 0723a891423c68241b7eb78e0de7756f99ea4b6d | [
"Apache-2.0"
] | null | null | null | from energytt_platform.bus import get_default_broker
from meteringpoints_shared.config import MESSAGE_BUS_SERVERS
broker = get_default_broker(
group='meteringpoints',
servers=MESSAGE_BUS_SERVERS,
)
| 20.9 | 60 | 0.827751 | 26 | 209 | 6.269231 | 0.538462 | 0.122699 | 0.196319 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.119617 | 209 | 9 | 61 | 23.222222 | 0.88587 | 0 | 0 | 0 | 0 | 0 | 0.066986 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
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