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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
697f6486b8e21013351bc2c5662ea00e53746a08 | 15 | py | Python | base/secret_code.py | ashutoshpurushottam/wishper-blog | 670c409798a88c5a828218221902d8b401dbea77 | [
"Apache-2.0"
] | null | null | null | base/secret_code.py | ashutoshpurushottam/wishper-blog | 670c409798a88c5a828218221902d8b401dbea77 | [
"Apache-2.0"
] | null | null | null | base/secret_code.py | ashutoshpurushottam/wishper-blog | 670c409798a88c5a828218221902d8b401dbea77 | [
"Apache-2.0"
] | null | null | null | secret = "ashu" | 15 | 15 | 0.666667 | 2 | 15 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 15 | 1 | 15 | 15 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0.25 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
6990b0a29b50c68d4d28c4ac3eda53cf9dfeeb04 | 641 | py | Python | tests/conftest.py | donalrinho/zfit | 9769ef7d56a6be9a5d438e47b80ea5a8f772bc24 | [
"BSD-3-Clause"
] | null | null | null | tests/conftest.py | donalrinho/zfit | 9769ef7d56a6be9a5d438e47b80ea5a8f772bc24 | [
"BSD-3-Clause"
] | null | null | null | tests/conftest.py | donalrinho/zfit | 9769ef7d56a6be9a5d438e47b80ea5a8f772bc24 | [
"BSD-3-Clause"
] | null | null | null | """Used to make pytest functions available globally"""
# Copyright (c) 2020 zfit
#
#
# def pytest_generate_tests(metafunc):
# if metafunc.config.option.all_jit_levels:
#
# # We're going to duplicate these tests by parametrizing them,
# # which requires that each test has a fixture to accept the parameter.
# # We can add a new fixture like so:
# metafunc.fixturenames.append('tmp_ct')
#
# # Now we parametrize. This is what happens when we do e.g.,
# # @pytest.mark.parametrize('tmp_ct', range(count))
# # def test_foo(): pass
# metafunc.parametrize('tmp_ct', range(2))
| 35.611111 | 80 | 0.648986 | 87 | 641 | 4.689655 | 0.747126 | 0.036765 | 0.078431 | 0.102941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010267 | 0.24025 | 641 | 17 | 81 | 37.705882 | 0.827515 | 0.932917 | 0 | null | 1 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
6992e5f7fd086eb383e3e2efbd84f3e597529cfe | 1,147 | py | Python | orchestra/contrib/saas/serializers.py | RubenPX/django-orchestra | 5ab4779e1ae12ec99569d682601b7810587ed381 | [
"Unlicense"
] | 68 | 2015-02-09T10:28:44.000Z | 2022-03-12T11:08:36.000Z | orchestra/contrib/saas/serializers.py | RubenPX/django-orchestra | 5ab4779e1ae12ec99569d682601b7810587ed381 | [
"Unlicense"
] | 17 | 2015-05-01T18:10:03.000Z | 2021-03-19T21:52:55.000Z | orchestra/contrib/saas/serializers.py | RubenPX/django-orchestra | 5ab4779e1ae12ec99569d682601b7810587ed381 | [
"Unlicense"
] | 29 | 2015-03-31T04:51:03.000Z | 2022-02-17T02:58:50.000Z | from django.forms import widgets
from django.core.validators import RegexValidator
from django.utils.translation import ugettext_lazy as _
from rest_framework import serializers
from orchestra.api.serializers import SetPasswordHyperlinkedSerializer
from orchestra.contrib.accounts.serializers import AccountSerializerMixin
from orchestra.core import validators
from .models import SaaS
class SaaSSerializer(AccountSerializerMixin, SetPasswordHyperlinkedSerializer):
data = serializers.DictField(required=False)
password = serializers.CharField(write_only=True, required=False,
style={'widget': widgets.PasswordInput},
validators=[
validators.validate_password,
RegexValidator(r'^[^"\'\\]+$',
_('Enter a valid password. '
'This value may contain any ascii character except for '
' \'/"/\\/ characters.'), 'invalid'),
])
class Meta:
model = SaaS
fields = ('url', 'id', 'name', 'service', 'is_active', 'data', 'password')
postonly_fields = ('name', 'service', 'password')
| 39.551724 | 85 | 0.666957 | 106 | 1,147 | 7.141509 | 0.603774 | 0.03963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.231909 | 1,147 | 28 | 86 | 40.964286 | 0.859251 | 0 | 0 | 0 | 0 | 0 | 0.130776 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.347826 | 0.347826 | 0 | 0.521739 | 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 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 3 |
6994976a52f0273b5abb9242055b6e34f052f618 | 249 | py | Python | lib/util/file_utils.py | overholts/tuner | 761a40d152d3c7afc681aaaecf1660bc93d68a97 | [
"MIT"
] | 1 | 2020-12-26T21:56:50.000Z | 2020-12-26T21:56:50.000Z | lib/util/file_utils.py | overholts/tuner | 761a40d152d3c7afc681aaaecf1660bc93d68a97 | [
"MIT"
] | 3 | 2019-10-28T18:16:25.000Z | 2019-11-23T07:50:28.000Z | lib/util/file_utils.py | overholts/tuner | 761a40d152d3c7afc681aaaecf1660bc93d68a97 | [
"MIT"
] | null | null | null | import os
import shutil
from pathlib import Path
def copy(source: Path, destination: Path):
os.makedirs(destination.parent, 0o755, exist_ok=True)
shutil.copy(str(source), str(destination))
def remove(target: Path):
os.remove(target)
| 19.153846 | 57 | 0.73494 | 35 | 249 | 5.2 | 0.542857 | 0.065934 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018957 | 0.15261 | 249 | 12 | 58 | 20.75 | 0.843602 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.375 | 0 | 0.625 | 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 | 0 | 1 | 0 | 0 | 3 |
699a15451c3ddcbb4167810748ccb98dca475d3d | 78 | py | Python | Python/Fundamentals/Strange Zoo.py | EduardV777/Softuni-Python-Exercises | 79db667028aea7dfecb3dbbd834c752180c50f44 | [
"Unlicense"
] | null | null | null | Python/Fundamentals/Strange Zoo.py | EduardV777/Softuni-Python-Exercises | 79db667028aea7dfecb3dbbd834c752180c50f44 | [
"Unlicense"
] | null | null | null | Python/Fundamentals/Strange Zoo.py | EduardV777/Softuni-Python-Exercises | 79db667028aea7dfecb3dbbd834c752180c50f44 | [
"Unlicense"
] | null | null | null | tail=input(); body=input(); head=input()
body=[head,body,tail]
print(body)
| 19.5 | 41 | 0.666667 | 12 | 78 | 4.333333 | 0.416667 | 0.346154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.102564 | 78 | 3 | 42 | 26 | 0.742857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
699ade1a7eeab2bcf96cb57b4bf3d8094aee37e2 | 188 | py | Python | sagas/tests/basic/test_fixtures.py | samlet/stack | 47db17fd4fdab264032f224dca31a4bb1d19b754 | [
"Apache-2.0"
] | 3 | 2020-01-11T13:55:38.000Z | 2020-08-25T22:34:15.000Z | sagas/tests/basic/test_fixtures.py | samlet/stack | 47db17fd4fdab264032f224dca31a4bb1d19b754 | [
"Apache-2.0"
] | null | null | null | sagas/tests/basic/test_fixtures.py | samlet/stack | 47db17fd4fdab264032f224dca31a4bb1d19b754 | [
"Apache-2.0"
] | 1 | 2021-01-01T05:21:44.000Z | 2021-01-01T05:21:44.000Z | """
$ pytest -q test_fixtures.py
"""
import pytest
@pytest.fixture()
def hello():
return "hello"
def test_string(hello):
assert hello == "hello", "fixture should return hello"
| 13.428571 | 58 | 0.664894 | 24 | 188 | 5.125 | 0.541667 | 0.178862 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.18617 | 188 | 13 | 59 | 14.461538 | 0.803922 | 0.148936 | 0 | 0 | 0 | 0 | 0.245033 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 1 | 0.333333 | false | 0 | 0.166667 | 0.166667 | 0.666667 | 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 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
69b2b6d82ab1ad7e440cde8afce2c3415b6294ed | 305 | py | Python | django_settings/config.py | aderugin/django-settings | ba4a062eb64a8aa826b02ea6996e4fcab1de454b | [
"MIT"
] | null | null | null | django_settings/config.py | aderugin/django-settings | ba4a062eb64a8aa826b02ea6996e4fcab1de454b | [
"MIT"
] | null | null | null | django_settings/config.py | aderugin/django-settings | ba4a062eb64a8aa826b02ea6996e4fcab1de454b | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from django.conf import settings
SETTINGS_TITLE = getattr(settings, 'DJANGO_SETTINGS_TITLE', u'Настройки сайта')
MODEL = getattr(settings, 'DJANGO_SETTINGS_MODEL', None)
if not MODEL:
raise Exception("You have to define DJANGO_SETTINGS_MODEL variable in your settings file")
| 33.888889 | 94 | 0.767213 | 42 | 305 | 5.404762 | 0.642857 | 0.185022 | 0.185022 | 0.255507 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003774 | 0.131148 | 305 | 8 | 95 | 38.125 | 0.85283 | 0.068852 | 0 | 0 | 0 | 0 | 0.453901 | 0.223404 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.2 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
69c5e8fb6e120abc97f935ab661f0d85156a95fe | 256 | py | Python | eots/serializers.py | lextoumbourou/eyeofthestorm | bbcb5b535c0a051e63ad1949b7107bc617094279 | [
"Unlicense"
] | null | null | null | eots/serializers.py | lextoumbourou/eyeofthestorm | bbcb5b535c0a051e63ad1949b7107bc617094279 | [
"Unlicense"
] | null | null | null | eots/serializers.py | lextoumbourou/eyeofthestorm | bbcb5b535c0a051e63ad1949b7107bc617094279 | [
"Unlicense"
] | null | null | null | """
Eventually we'll probably want to add some decent serialization support.
For now - this is a pass through. Patches accepted :)
"""
class Serializer(object):
def serialize(cls, obj):
return obj
def is_valid(self):
return True
| 19.692308 | 72 | 0.675781 | 35 | 256 | 4.914286 | 0.885714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.238281 | 256 | 12 | 73 | 21.333333 | 0.882051 | 0.496094 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0 | 0.4 | 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 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
69eee8eadab9abbe0ac89fcc874ab36e92b8ac42 | 2,430 | py | Python | tests/mem/test_magic_memset_tlb_miss.py | capt-hb/cheritest | d3b3637a81a0005ee7272eca0f33a9f9911fdb32 | [
"Apache-2.0"
] | null | null | null | tests/mem/test_magic_memset_tlb_miss.py | capt-hb/cheritest | d3b3637a81a0005ee7272eca0f33a9f9911fdb32 | [
"Apache-2.0"
] | 2 | 2020-06-02T13:44:55.000Z | 2020-06-02T14:06:29.000Z | tests/mem/test_magic_memset_tlb_miss.py | capt-hb/cheritest | d3b3637a81a0005ee7272eca0f33a9f9911fdb32 | [
"Apache-2.0"
] | null | null | null | #-
# Copyright (c) 2018 Alex Richardson
# All rights reserved.
#
# This software was developed by the University of Cambridge Computer
# Laboratory as part of the Rigorous Engineering of Mainstream Systems (REMS)
# project, funded by EPSRC grant EP/K008528/1.
#
# @BERI_LICENSE_HEADER_START@
#
# Licensed to BERI Open Systems C.I.C. (BERI) under one or more contributor
# license agreements. See the NOTICE file distributed with this work for
# additional information regarding copyright ownership. BERI licenses this
# file to you under the BERI Hardware-Software License, Version 1.0 (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.beri-open-systems.org/legal/license-1-0.txt
#
# Unless required by applicable law or agreed to in writing, Work 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.
#
# @BERI_LICENSE_HEADER_END@
#
from beritest_tools import BaseBERITestCase, attr, HexInt
@attr("qemu_magic_nops")
class test_magic_memset_tlb_miss(BaseBERITestCase):
EXPECTED_EXCEPTIONS = 1
def test_badvaddr(self):
self.assertRegisterEqual(self.MIPS.s0, self.MIPS.a4, "Wrong BadVaddr")
def test_context(self):
self.assertRegisterEqual(self.MIPS.s1, (self.MIPS.a4 & 0xffffe000)>>9, "Wrong Context") # TODO test page table base
def test_xcontext(self):
self.assertRegisterEqual(self.MIPS.s2, (self.MIPS.a4 & 0xffffe000)>>9, "Wrong XContext") # TODO test page table base
def test_entryhi(self):
self.assertRegisterMaskEqual(self.MIPS.a4, 0xfffff000, self.MIPS.s3, "Wrong EntryHi")
def test_status(self):
self.assertRegisterMaskEqual(self.MIPS.s4, 2, 2, "Wrong EXL")
def test_epc(self):
'''Test EPC after TLB Invalid exception'''
# plus 12 since check_instruction_traps uses 3 instructions before invoking the actual insn
self.assertRegisterEqual(self.MIPS.a6 + 12, self.MIPS.s6, "Wrong EPC")
def test_testdata(self):
self.assertRegisterEqual(self.MIPS.a7, 0xfedcba9876543210, "Wrong testdata")
def test_trap_info(self):
self.assertCompressedTrapInfo(self.MIPS.s5, mips_cause=self.MIPS.Cause.TLB_Store, trap_count=1)
| 41.186441 | 124 | 0.743621 | 343 | 2,430 | 5.186589 | 0.510204 | 0.062957 | 0.075885 | 0.087128 | 0.183249 | 0.060708 | 0.031478 | 0 | 0 | 0 | 0 | 0.030617 | 0.166667 | 2,430 | 58 | 125 | 41.896552 | 0.847901 | 0.513992 | 0 | 0 | 0 | 0 | 0.088056 | 0 | 0 | 0 | 0.041848 | 0.017241 | 0.4 | 1 | 0.4 | false | 0 | 0.05 | 0 | 0.55 | 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 | 0 | 1 | 0 | 0 | 3 |
0e07c9e354ebece1a10554ccf30b3c030751ef46 | 89 | py | Python | test.py | rwinslow/cellanalysis | cc933c5e169d1b7baed204208373e84e3f32dde7 | [
"Unlicense"
] | 1 | 2020-10-23T09:20:41.000Z | 2020-10-23T09:20:41.000Z | test.py | rwinslow/cellanalysis | cc933c5e169d1b7baed204208373e84e3f32dde7 | [
"Unlicense"
] | null | null | null | test.py | rwinslow/cellanalysis | cc933c5e169d1b7baed204208373e84e3f32dde7 | [
"Unlicense"
] | null | null | null | import ardustat as a
test = a.Ardustat('test.dat')
test.plot_capacity()
test.plot_power() | 22.25 | 29 | 0.764045 | 15 | 89 | 4.4 | 0.6 | 0.242424 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.089888 | 89 | 4 | 30 | 22.25 | 0.814815 | 0 | 0 | 0 | 0 | 0 | 0.088889 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
386724eb8880a1ca361d93d965e3d83920503a7f | 411 | py | Python | LeetCode/0812. Largest Triangle Area/solution.py | InnoFang/oh-my-algorithms | f559dba371ce725a926725ad28d5e1c2facd0ab2 | [
"Apache-2.0"
] | 1 | 2017-03-31T15:24:01.000Z | 2017-03-31T15:24:01.000Z | LeetCode/0812. Largest Triangle Area/solution.py | InnoFang/Algorithm-Library | 1896b9d8b1fa4cd73879aaecf97bc32d13ae0169 | [
"Apache-2.0"
] | null | null | null | LeetCode/0812. Largest Triangle Area/solution.py | InnoFang/Algorithm-Library | 1896b9d8b1fa4cd73879aaecf97bc32d13ae0169 | [
"Apache-2.0"
] | null | null | null | """
57 / 57 test cases passed.
Runtime: 104 ms
Memory Usage: 14.9 MB
"""
class Solution:
def largestTriangleArea(self, points: List[List[int]]) -> float:
def triangleArea(x1, y1, x2, y2, x3, y3):
return abs(x1 * y2 + x2 * y3 + x3 * y1 - x1 * y3 - x2 * y1 - x3 * y2) / 2
return max(triangleArea(x1, y1, x2, y2, x3, y3) for (x1, y1), (x2, y2), (x3, y3) in combinations(points, 3))
| 37.363636 | 116 | 0.579075 | 66 | 411 | 3.606061 | 0.545455 | 0.05042 | 0.07563 | 0.10084 | 0.252101 | 0.252101 | 0.201681 | 0 | 0 | 0 | 0 | 0.137255 | 0.255474 | 411 | 10 | 117 | 41.1 | 0.640523 | 0.155718 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0 | 0.2 | 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 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
3884703674d725ea9a283168def22c677cc0f51d | 58 | py | Python | credentials.py | Tawfiq-MoonHacker/metis_video | 8d63ac458b8b6bfa48a1ec5476dc47be1987f42a | [
"Apache-2.0"
] | null | null | null | credentials.py | Tawfiq-MoonHacker/metis_video | 8d63ac458b8b6bfa48a1ec5476dc47be1987f42a | [
"Apache-2.0"
] | null | null | null | credentials.py | Tawfiq-MoonHacker/metis_video | 8d63ac458b8b6bfa48a1ec5476dc47be1987f42a | [
"Apache-2.0"
] | null | null | null | email_user = ''
email_password = ''
address_owner = ''
| 14.5 | 20 | 0.637931 | 6 | 58 | 5.666667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.206897 | 58 | 3 | 21 | 19.333333 | 0.73913 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.333333 | 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 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
3889caf94688acf693a126febe14a32273a0de1d | 322 | py | Python | catkin_ws/src/simple_robot/src/ros_simple_robot_node.py | delmann/simple_robot_world | e55e95529b48054eedc1edf5c80881ea7947f73c | [
"MIT"
] | null | null | null | catkin_ws/src/simple_robot/src/ros_simple_robot_node.py | delmann/simple_robot_world | e55e95529b48054eedc1edf5c80881ea7947f73c | [
"MIT"
] | null | null | null | catkin_ws/src/simple_robot/src/ros_simple_robot_node.py | delmann/simple_robot_world | e55e95529b48054eedc1edf5c80881ea7947f73c | [
"MIT"
] | null | null | null | #!/usr/bin/env python
import rospy
def spam():
rospy.loginfo("spam foo")
def eggs():
rospy.loginfo("eggs foo")
if __name__ == '__main__':
try:
rospy.loginfo("do something")
except rospy.ROSInterruptException:
spam()
eggs()
rospy.loginfo("something went wrong!")
pass
finally:
rospy.loginfo("finished")
| 16.1 | 40 | 0.692547 | 41 | 322 | 5.243902 | 0.585366 | 0.27907 | 0.148837 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152174 | 322 | 19 | 41 | 16.947368 | 0.787546 | 0.062112 | 0 | 0 | 0 | 0 | 0.215947 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.133333 | true | 0.066667 | 0.066667 | 0 | 0.2 | 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 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
388c17907e13f1a313ab074390c2c4033910f33e | 12,060 | py | Python | large-repo-master/test-3/nb24.py | victorsun123/numpy | 1fb036758b4035ab2c132d26f420e5bc3ffc917e | [
"BSD-3-Clause"
] | null | null | null | large-repo-master/test-3/nb24.py | victorsun123/numpy | 1fb036758b4035ab2c132d26f420e5bc3ffc917e | [
"BSD-3-Clause"
] | null | null | null | large-repo-master/test-3/nb24.py | victorsun123/numpy | 1fb036758b4035ab2c132d26f420e5bc3ffc917e | [
"BSD-3-Clause"
] | null | null | null | # Databricks notebook source
HLRIOWYITKFDP
GOQFOEKSZNF
BQRYZYCEYRHRVDKCQSN
BELVHHTEWWKFYTNTWJIIYUQTBHUMOCJNDBBIPBOVCDIKTUPVXZRIUC
AUVGECGGHDZPJPMFEZWDFYYDXYGEMHXRHYXXGEMXTCZOPGPGSRCIQNPHCUONPPCBOWTFOZEYCXCQKKUNDSXSBAKSMWIPUKICUWX
HDCWKJXOZHPPXWBBPLIGLXMBATYPTDTCAACKEEWURDREVIIUPRJXDFNDLSHBZEBMWQOMYFWARMGERQAXVLFREGTYUXPABORSDUP
XPSNALKIEEH
TNRJVKVUADXUMYRVMHWANRYEQXHWTJQWRWKSYUM
JZXPNGKLOBUHKSQBTCTPEDKMXFIBBGGHRJQHBBORPGAUUQJRVXCIPMMFYYLRYN
KGQOIYGOLOQKPGZJQOZBYIDIZHPVDGNQIBWMZKLFVEICEQCZJBCOJNRCFYZBKW
XUCXWMRZSJZGGPFDQVRHQYDXFQAKRUAMZMPYIXPFUWMHCMC
HXYLXLGHGJHSABRRKKPNEFJQTIUKHUWMRZSWZBPACLASFINSC
# COMMAND ----------
MGRAAFOYIJMFRVFOSRGMGFXXEKYADNRPHTYWJOWZMVBJ
PWDILGWYEWDFNEZFZBSMBFRSQHNLFXXJUYMSTDBXBZOLDBSROW
VJZKPBXNXVNNTANWQWAUITCXBBBVPROZOINGKOJBTSWCDOPYBLDTEKAQGMWCUARJGWQY
ZPFVDMMLPYPQAMSJLQQWEDSYPZHXSYKENJIJMLMRAAFISKLL
ROYFOFXVCMBAZZIRVCWXHAWKILJJYAWWISQPHOVCWIGSYJ
# COMMAND ----------
YEGVKOKXNRAKWSMIJGQICYIXPZDXALZLGNOTGYHVESTP
# COMMAND ----------
EUIJSXZYUPDQQFSWCACJADRNZGSJIYRAJ
# COMMAND ----------
UGFQNBEQJETM
PUPRVDQIOHSKMQPCGUNVESHCJHXEIFWUQSSWSEQKNNTNTRKRZMGONRPFCVLHTPHBXYLRHZFAIGHWOLLWFDZNMEUGIWAKGTAVBKZFUAQLEGNUKNDZBMSOQSLCDALHWSQO
IPFRYPASTQSOMGKIAEUMKUMOCUVDHIVXZUOXHYOUQNZOLJSMRJDCMJTPLRHWDOKLBBXNBCTLUSFYRRHZDCASUGABWYSQ
UQAVLZHFFQGREDQGYLLDKMRWGIKJHXTGBIAVZDZSXLFBNERWVEKHOMZAGGXWWNAGGYGIESTGFCNWGZKXZWICBDCWXYQDABJSDCOEN
QWQQEHTLBUKHKBMGSNSJIAIMEXKQBVECIGTODUHRROXAIMVKIQXBBFICPJAVMYVPZVBLSMDBYTFHNAMXNITSIMHFQNBIPYAOLR
GHUYEXMAQAHQFFYPWBUBRHJVKXAFDGVHXBYXPZLLTKQHWXIHIDAPURJUFJRDIIDEMMXOZSSWHLGQRTRFWHJMMDZECZRBCF
G
# COMMAND ----------
HLYXINLAZVEFIXCTTQNFUVRS
# COMMAND ----------
TTXHRRLOCWDLVNKZRCVYWBLCAOTMQCDWHXEUCNSBCOKEM
UYQEGQGRHRAEDNYXMPSRZETETIVYAN
RSINMZPJMBPZSJMEAEZLKHAKSHDWUFVBFAXM
UIDJIHTYSNFGCQEHGBAETBNXDTHDOQXKNHCBPT
KRUNMFOIWPIPZUMRGXYSXJPRPRQBXANWXYYZZVN
# COMMAND ----------
KXOYFKLPJZVZENIQOONHWZLDRJ
# COMMAND ----------
HNJKYFTKQDDCVXTULFGJJLCSTCFFYWMCJDVMRAKICWPFPRHGYF
WXHCWSXVEAMYVSGRVDLBHWJVQDYRSQKDLONEFRNKEIWWWOYGXLRBBMRLRLUMZMNUNTXHGQPDGW
WWXGRBQDFHU
VJNXHAEWBZKVZTQFIRAIBHGWLQHAHJUSDKRQMRYCMJQERHNFMICNFRMDYKPICZEKGCPKXSDVDFKBBYQKZYRWHQKTZKQWAHUNCIHJERDIDNTVMHZRQTTP
STBEHDGYLALHLMPNDDEHDHLFJUJPTQUEHCGBWVZQCRTEKOYFVNMYFKDWX
NNGJGRTQDUNZAODUBXPZSOB
QWPRIYUUQUDGEBX
CDDTEPCISHNGHQIOGWTUKGQQQUYHMVTOXA
QJSQFZXSMQJYFSHKIXGTUIE
YIRDQUCWCLADQDOTVN
# COMMAND ----------
XJUMTZMHQRTHEJMKZZYQ
# COMMAND ----------
HRLMTGAHKAHAIIEEPNJVTJEWY
# COMMAND ----------
SLZUQJQUPAXEEIIRIBUDGNZJS
YIEONXHQAYNVRXJERVXEDKEIBPJXEHYODJBDWBQWHTAHCAHZHKFPYSMXPEKQHQGRUQTUNIPGBSSXQEGCONRSWPRUBWNSJENSJAASJJSRHMWNIJVGGUXVJHTWKHPFHXBAPQQBEWAAKZDMEIXSQJWCMJPZRBBKIWQRXBSJQRAUBHF
DWKHDARZBRTZGJQNOXRRXOSOVWUWMVNFDXZOE
BGOIUSLOKNQCFDRBHBUCBSVEPGTHAHPYVBCYIGEFBMNJTAXZDUAPPCSWONVOUCLBVALGDKDMCSPSOOESVMYRYTNEPDCLEMKQGVPPWOWDKFJSNUQTFKMOQUOUZIMUZFIHPIYDKDAAOGQSFDPLGJRQDIURASFLJFKFRCJKFWMDOWUHASNRBOVMTWSKQDSAMYDWUUNYYOBHHOJHIHAXLPJFEGRSLZTZWXW
LSICUAWWGUNUVLTZQXWAQVU
PPDELDMMFZMMLYPRAPSRRTKDOIZWSCWVMMKHM
ZGEMVCHIFFGIJKPHDSWPOGNVIBOCRKZGFVX
BWRYOJLMTQGPRDWRBJGFBFUBAISPWJAQIHKWOU
# COMMAND ----------
VIFVDLALCKTCPHTRMEJZGVAZHAQCXIEHAHGHDMKSCRYKNXBJCDQPO
HRTQEDHPCHCAHHPYEMYBPYRTQOJUBIPXZZYFVAIVIYBMPHBWKZLOUCSLQFHCWFRZFTDTGQXILVXRETJIBFPJFZRRFFYY
BYEBDPVEFSQYDONJZZJVQHGBMUYDE
SRERPGRVVQNDCSOCQVQCRHBSTHFAWMSMDNVIGBCJAGLFISOIGSSDFDPTHAED
PNDKPXBJVTKTMIBMVGHNRLFMYGGYHGDQVBVJDVNRXQURFGWO
MELCTFIXAKTOGXIQSKQNOZVVXPES
# COMMAND ----------
AIHJL
VRGPJGNIYGKMYDTFGGRJEJHTNANVRWBHSRMUU
EVSSYCGUYDDPHYLYDRACLZKWDQSUZIWUYBJ
EIOYQFELGXGWZXXNDQBAMBKUVRVISOYNMAGZCMDTKD
FIRHJUJHKJTAZAWMPOJQZXYPXHSGNQSSZXZULZGANE
RWPPRADKIDSOTXOPDYXMDLDVBFXSBIGMOZH
JRAUFKLITEUKHQURJSYLRVWPIPSIZ
OYGOHZVFTKRGLVBACJYWSQQRGEAKPJJXBMPTSUSFYEAVAYU
TEFQFNEWNFTXXMHKSVASRAYDRFANOFNN
KAQUXECQRTKJSKVOMDZKHUSYLOUPNIYEJ
ZPXPYEQTJIYBESQVRGHFFTJCGMLIUWBZJYHXKFLQUNWMVTHZQFHEYYMTOODMGJBIUIQRTGREHIQETWJZTBQJQDRHT
TNPXYMMBEAEBTSUNAVXUSHVDJKAYYELBMXUIALPQAOEBNPGPTMQVHPDLDZWFMQ
ZBZDBURQQVMTWUXUCYYBLZLHTXXVULVQWGJHCCCIPJANAQYLYQODC
ZOLPYJRNAARTFFFFYGIOSYPOYGKSQQSWUFOBHHAULQEDIKBHOXCEWOWPHR
BQSPSPPKJYEBRABXVPDGQWZQBPJNLXXNTQJSJNIAXLBROXVATFNCMMYIHYOTZFPAHSMWBMBQASHQPMNDJKZAMWPARUDMGJYMN
ZCASMFRILFCRHYNSNPI
FXNBRWYBFAWDJGXGXMHIVYALOHGFVPEDLYZMXNLHTJHQRPENLNWXZEYVXUHETCTMLQCDEVN
GTRXQFGWDDQNNOSAFQRTWCMPITIRZQOWNHFCFONPVGRNQTRXRVUKLDXLFFWKGCQIMMDAMRV
BCSIMCHGYDQBHNCNZRVMRFDNFCZYRIB
GIAVLZDNAFEGNUNXXWQKXAMIPCEXRALZHUSVFXRIIOVHPWXWVGQJDZIQRDAWMHSMZFFWMNBAIFICIPCUHIIHLOJYRJSXGQOQUS
OALQOFHQFNFBUOPDEDDSTMWMGSNBAAPHVMIWVAHYSWMGPUMEPZBDVTAMZSLOQTXKFAINYQPNSGPZHGHKROCLXFUZKETLR
ESVNERUCXQPFHOICQARUMSWGLYLTIHLVIJHIYHGRRZVMJWSYHOIOXNHMDLGXWMHIFYEKIFDLRXCHCJFXDKVCMDU
KQEIBKXAOATCNPVTWLVVZGDHXXRTLETKXDWJWSHWXCIQRXJEVRRUFSHYAUXK
WMCVHVIQYRHDBRTYJBFJXGKFHFPHIDWSWUKSIXCILQBKBEZYAKIKYNQBAPGHLOPPHQGDOC
XHIIGAMOSXVHTJZIWIJHNXMLFGQGTXSJDALDJWFCJDBSCTCAKMRVNIDJVONYDO
QRRUTDRYRWINKFBYWDSHFMZZIFOOFUFUHJLRTUVLSOQXIREYFNTZJDGDORQRHQLMRDJA
HXHOTUNTLSLELWLILUKKANAHSQZFXGUPISRGUFJGR
ONZRYCXPHSIAXFSNLGUEUAFGOAYKYSTYKZGFZAJMTJPJCUFARTYODQRVG
PKLEQJLGHKPFNHNCYHLAPUWYAGXCKEUUKNVWONEXPMBQX
HSSBACYPEZCHNGZJAQBQURACUMBTGITBCDA
ZIDANRQYEQWAABYWBPMXSWYQZTODHJAHZCZNEXHMFTNWHMSRVFVDBZEPZCLBZDJCJQVPTBGZAVNPLOF
CIUDURAWGQQWCGMPFJGNMMWPQQXTPBZDHSLEHHXVYMHCWFYGMECFNGQFIOGHHUPMNLOIWUTRSBULHEBZ
KAQLMKOTQZRNMBPMXDCSXEIFYZLUZZLUDAWWS
NFFFAWDLRYUVKZQCTJPHHN
CINNNGJTVWRPQWWERLSVWQE
ERKZANUAMBPQRWUIBQFQKMJMWOPDCKZVBSHBXUXNJWEMGW
MFLNVKMJYZTZZKKMRJBAGSXGRJYEKXMUK
XBTHDVCTDUVZVBMNRWOHETTAWANCLAQPVYQAFOKAAZMNVQCYMTNKNXXKFZTGRGAYHTVXRUDMBUHTVXLJYQXQNMZPRXNNRK
IKSUFLZSEDKQRDACPSBIHBK
IBXXDEJPSXRPGDDAYUAQVHWUYROWDSJAI
FFYWSYQJDMJTTHDAHKMBQRFDQMGERXKHNCBTTSETANWUVOHWSMZKKZAEMPITYDIJUHRYXRYHVQUXONLWQMZUADRNY
PEPOGORZKBHKDYQRCHDHHSFLGMVILJRVJRRXFJZECZOADPGSPMWFQLXRSOAQGFFBRI
YUJAVPQVOKQHMFESFBPUTBSNNJIJHFOEIWVAGLIDOKHNSEKGTEPUZNRGWACQWPKZGTPFTNGMVHLIKVZAL
WMDYVMTQHGYNEMMGOBGMARSZINCZFSC
AZDFXEDLDRYTPKLJXABAABXMBXAUYUWKLEDWVNXSCQELPGFJMCDJZNCQAJOQQBEACDT
# COMMAND ----------
IPPSZAEXXYOUKLMEPDOGXJHNCDFZHWDCVKA
# COMMAND ----------
VLEG
NKYHPROGHFOJHNCNXLIQBZG
HYLQPUFVADJJBONIUQYXOHSRJUEXXWWFVJOSIJBWHQXXFCLZIXZUHSKKWBGHLLBJNFLIWQOLUSMBPLJDEFMHXHWSIUOQZURJNNP
NDJOQXHQRDFEICUZYEGWJILNOKXKLGZI
MLTBEAYEKUNLEOJPHZGRZEEJFKDLIENRQRNHXCQFVHQXZNYNJUOMBBZYHSDRBKH
TDITMWIHYWWMEKNNRPUZWNAKDIFQXJAUNJEIJ
HSETBLSOCMUIMKKIUCNSLXDLXZBYYWNFKWSETOTXYSARBGUQZWRADHVQNWRQNJENPPTBNTOTNUCBCRLVDIYAHOYJ
WZNPVJWJVLPVZLWHOFSTXLBE
OKIEUNGRUHVDFXKQKKKAFZMFKJRLTREAHQNEV
SQUJJWYONOAWOOMUCXSXNYJQGVEZIHECASJHQXGWSRYBXWX
AONVSXVKWLFMNJAWPSOT
ZXDCQQIOOJGNLKAEUMPXDWPBXDHMFXVVJCUURICJAXPFGTFDWCFITDJVQNMZZTTVDFYLECVXJSTFRWAXHFLAZ
SWTXLXOQZUYMINIAQPUSUORBYHOBFHKFEFQUISUNISXHATPIPVWUIONSLFRKNQHZLEDLZIHGRBZULZBYQTDXLIUGDFCNMTWRDCPQATTRMVZDADIYVUHYTZDCRBJTUONKDLEXDHDQEZPGPORNHGSKWZFZWTIFXVLFWXGOOFFOA
CWZEBRESMUGUCRYTHQFZHLBCYBYCFWIRBKJEOAAKUEXLU
USIIFVVBQETYIFOOWNXLACNBXXKFMACXSVKTEZZEWAREADAKUZGLXTOCRDVBHYXWVQQJTGYSCKNHTRHFIIDULKJZWBTVYLGDTSIQLFNHFVSTPQEFEHACMR
IRGLRXDQDBZBQZITNZHFXZAUCJREGJRPHZZBWQZISARTKXTDTS
TFCNLZTRFCHBULAAQCLKSVYUQMDNACFGYEDCVWECMKMIYUPXMSPLKVPOTIISMUHGQIVLYUOFQJLXGYBNBMCIXYLHA
YGCUBGLLFJWZVBILCADQEOYZCQNJHHBYEYFIJXYQXROPNDBTCZRRSQO
EBOXGMVANYBABVJQPCPAQLNUWCQPBPFAYZ
WNGYNILQBBNKIOLVCNZRXBLNDUHEFLMGKKILSIMHAQDGPMYRAJBQRMUWWTB
WYDXHERKOOTFQBTQJYNZYWIAJHNUERQEZJQYTTEVAKQKFWJCOQWEFHTFORVLIDCBEAYGHEOY
RXJJCGJYEVUPVGCSLRIGJFOXEFWEATXKQUVWYHBKIPLDZWGHXURWDWLZBLKIHJXHBECQZYN
QHZJVAPISQDQDUWVQVNBT
HZVVAPCVUZMXUFEWKSWVQMWWQBLMMIYKJEOACLTYTNXIATZZUGJTKAKNGWWVYVPLWTDRWEPWJLW
UVNXUUATPKWWUGBNTEQNQQDBFTIHWKYJGWXIGZAAUMQAFUCHZQOSSEULCKRIXIESWYPBSAW
MJDNPNHWJEKANJZYROBTIAVIPH
EFBJVVEPQCLANXLDUFOVFIRGEUKVFNUUSIHAHJMACPTCNKFBBAA
DVUOKEVLWXYRGUFFROWKLIILZLQLJFILKGJNXGFDTEVWAUJYJGCRUGXEYUVAAUUJ
KNQKUBXOK
HEVVIDPNOPHQMINJEPFNVEJULXOYGXBXORPSNGEYUQCHJMUFRMEJCSRIXFGYQSBYFMLIPUJSOHBAU
DLIZWNVENFSFITBMFDXUV
TZVVREDOLTWCYYLGKADIJZVXMSOBBCTDJPTSOZVDKFFYUJLTLLMQOTWCIYFLAPBBZEDIKHHAQUJWLF
YEJDVKFBVFVCZSOYYFPSRWLGXJPUUXNBYHDXYXMDMDMTBRYDUNYGOWVEXAAGDCGBGXZOBMR
LMMWWAWDEOXWIQVQZPQEDAFC
YNETHXOIFXBAYHAUMFKGKMWUZUXLIEXUJCNBXYCOEMVENVBPGYJOTKLXJBXMYK
VYPCSXM
IALGXLMGZFIWSZWZVBC
CQRVHHHXDBSSSYHENOTOESXKKUANSWNJUOBMTTIUMBWVLPHALJTWABFRNBQYLQWOEXGOJVZYSRIW
TDCVKCKHRXRPQFLYIWZWBOGSURJDNELLJFCAFRXKQILDNFYTQHMAKPSAWKABUIOVJLJLI
RUJOAIUXVXIFURLXMBNDAW
LMFXKLJOURZFXATWNSXYRTENCJEMHXAODECMKGXBMRAJGD
XBSOERUBNDFOAIZVJJUFWZOJMOUXARHEI
MSBDAQICHNEGMUHMGYDHJUODAHMVDSDWHULJZKBWATRDTZGDYKZGYZUSCJJOVRMUBIZMYVUUAOTJZQMTPDMLNFVAAOKBYT
OXYDAWCVDQEDPTYTEOMKFLD
DQMZLLSQXCMNELFYIMTKMCMSYJMFZVHKX
YCZTUYYDPKQIDXBOSRJOOBWYZZOJJRNKDIJVUXVKXAKJIKAJTNHQJEZSJFBKZNQXRIGONFHXGNLCQUBEIJRZFCFSS
GNURMKMZNWKLHYKGMXWHGYUSKZOJYBQWCJMAZKPGZNSQWTKXXYOPKNKAUMVRJSNGVC
ESKLCRUQPWEISOCASCIHBZPBIGWXIFEOXEWZRQRLNZKOQJFEJWHORQLSNIOEFTQKBTNIXOKFPSFXTXNXB
JCMUPPHQALLXHCWAGZLRLBSSVXZADTX
MNMVBTMVGMORBUUYJWWYFBQDRZIZNEOQIQYWUTGULBRLQEKXVVIITZDPGUDGBLHNPRO
# COMMAND ----------
VEWFGZQTZIXFACEPSFAVDIUZEBAMTVGIKAKXLXNAXE
# COMMAND ----------
GCAQAIWAIQBDSKUDFHIIIYQMMLUZWEDWFMWYSBRQSIIBOPZMZIXWOOYBQQEJCGNQUZTKJSENKFBNQFPYSDCZPPMUHKKWCLPLOVLFDTHKDUO
# COMMAND ----------
PQVBRQWXGNGENRXSAMKBIDFXYHUTUIQOTKFNHZMQ
FUATNEBFFTCFGJPTKSXHKFPXGWQBUOTUCVKTFDLLBKCDHPAMGJOCRQZOCNJKJLBSPJEQLDHGBDZSCHQBRKKVKVJUALFLQOSSCANGUKCIEFIHXCNFXCAZIMBINHHZJ
# COMMAND ----------
ATWW
AOPFSGPGURGCOAOHTXYQYU
LWOIJDBDAJEBPJETJXBBMTNZ
CHIYGGKMRUOXFFKTKNN
NDIPKHEKMERMBCWDPKEQJVOOKSZKFRMFAAMELDKJFUOPJVZXZSHKZSNHMPENJFDMEXBJAWSBPTUFSZAAEDKARMERGQNWYBQJDIXBEDFDMOQBKKOEIOAMDKZXPECSMLQPDWCRULMPZTVSILXZMXQNNMSVAESQQWRBSVUMRCTLF
PRARYINYZFHKIHLOZSIDGEWCIXEZGDQBXVEZOFJRQOQ
NRGCVJRTAIYQQEIUFQPGTPFBPDEAXYYT
KUXCZSETLNTMSJOSBAPEUSASMWUABXPDH
RWRONSWHLGIGITTRVTGOKAJCTDJVWDMFNMFUHZKNUNXEJFQTPCGPVVYHKBCAVEASLXSYJCPVGBHSLQJLIXTNFXIMBQOWPXORJNDXZYSZQQE
KDDBTOWG
QOJSCXPLHRWOMPJZNMTCWBMWAZDVKMCHAYFNSMPYSZQUZEKPJUQQEHVMYRJRNJXSXODJAXBOTSQOTHTUZLYIQSLB
XDSNTQYVPEUQOXUGANGJPGPRVYKUQOYKCJWFTCCIH
VQVUGKASQYIIBBMHKTYANDXXZSXZMHGFYRQMMZIEVHNUAEXBWVKIPOKAVBGENSBQHYOEWJNXHSCELAOLLGIBERIRNDEKVYZZQTDAYLVOYQJYEQLWDQMLRIHLGDTETLVDDZZSBAZSUPDFOJDAWRXQBQPBSIWCEQHIBMJAGQBZQRATPGHM
POTSDJDGXSZLXPCTVGUQGCNGAODHTPKZRTIEGBG
ETQXYFBKTJELNYBVCYXRAYKJVEQMWZTMPKCEXRQBETQOZPQVINNGYSIVZGULFLDYIZQWNCDFTMFNSYZERLBHTEUSFDZRPVBVUXIAKERCCRJ
RIGNLZFHJGWVUOSJRPWSFVYCRJRWPZDOBAQHHLJYBKMWYYEXBMSFRNFNWUVOFTGURSRMWIPLVQMHBFAGPI
CJZQZXKBOCQFZXKQIYDJQAGJSKCLWWKVRILFPASPCPYWFWCPMEFTSSPUNYHQZHTKVCFYVMKEFAGSLYDZCVZHPQEPG
VHJDAFAYUYLSWCFHLQOCJKQUEXGKFIQH
QAEOMQK
EVMCXBXTUJNQKWMHBUNRFVRNWQYPGVCJYJPHANESXMWVNPKAZZQTJRSFPXJFEDGACFZDQMAMWFLKVLHNEJHVYWQ
DUIWQPHWDSYQSMQOPFSNAMTASGRWXTEDHPKUCAYV
HKGDBUHPDVKTFTRVQHWWNRNCWGQXEFWHIEIVMOKUENDYBNHSXAZMIDBCBHHCYLZLFPZCVOKNOMTWHQCNJOLKVZENVBEOHVCIYWVCZBMNECMTUUHVDLEBQVMTXKESGSYKVPABBKLXHOEFTLMSRVFRIIOAEBLXUFSJXQCGNWCOCWMIFMW
OYBROLJWMAGYYHYUUBDHQEJJMQCKVGTRFMFGYQ
OWETFBSQXWRXFCRZDKEMAELCDZPHBRUSHCSGJSLCFIYIIICBMTFYGGBPRZGBRXZJBDQQEZHUEQDFEQFXTTEPOXUOMDVVPVOJSNAXQMEDGX
KBTVCFEVCTMZBDPNFEWXKDPPIKXBSYJHCASLRRGKOTNODLMVDKATWOAVYETRHWBMWRTSEOCPUBWEAYRQZ
QDIBWLZNGTIEBHTYRGKOPCMUTDHOCKGEOFTDUACZINUDVYSRHLYCOPZMIEPPGTMZXGGOIXOQGTANMKKYITQEBCZC
SKAQFUFOPMRPTZBRDLTWYSGZSUEFCDJ
FDZUPE
JNELVMFAWZJZYPLKRGIKMCZYIOBCLJEPLNCSANGDAGPDTQHSRKQBPQDNGAOIUC
KBGFRVLEJWJIQFVIJLFGQT
UKPSHDPBDOYSSEETQJAPNLBBGENTGLCYHCVZWVGGXSYUEM
ZNLSDNFHATMZMUDUNJECNOWTLDDQPUHCN
FZQQTLNELEVMAOBIURFJRCHVTIJROEHXBONWBFEOAOFFHFEFHDPVUXASUNCTYVZNQSVZHSLHAURMLRLMNTOYHMJEBLZLRA
FUIZYPUFUHYPNGQZEVLNJRM
RPAZKAACOMSTWJOSOXSHDZMXXAINYXIYM
XDDKWJUKVVEQGYJQOCIKLHMHAKGBIQ
JVEDEHNYAMSATUGVAHOMEMBQLJWIPDXTQSCSHJYZZWXAUCMPKOSMDPSNEZNJHZXDLGBTRQOZJTUJEEANTNEINJZKE
FKEIGQOIZREFLTLFOIJNOWKXBNEOTAWXUOFJNOQDHWPLCHXCZOJJEXBVISOAWMKWNF
CFMEUOWFOIGOKVAUAAEFTREATXGHSXAHWDMLFJWGSDPCRPDLLDGTUEWDPWTOSIWAJBMRMIGCXPRKDDLQN
NYCZPLFBNFCEOQNMDERNLXFHVFPRBGB
NGFPWVKYWHFAZROCPCIQGOMKFRQVKCNRJCSBPLLDURZLLFVPVHDHLZGYCSNMFVOFDLR
# COMMAND ----------
UKZXZUEPDEPUJMJPKLZZHMJGNWHBVCMRHEDUSDBOBWVSTHIYFRKOIBKVORNRLGCUPKSXQLNRWJPRBRII
ASQHRUROYUSINQWRBDTXJUSOKOBZACFFAWDWEREVAUCLILARUWYHKULERWCTZAUJFQ
FWHFQOMZGEMRZZSCJAZJPTICZZUVORFEERPPQMBACIGCOMTRIWRIEKXVHBFBVDKZTINQNZAJKLBWVJMWO
LRDLGVNCRARLYWVJUQJVOFVESVFVDSP
ELJBIAZHUEZBFFJCEIUZEDYVVGUCSXSTDTSPUCWQHAYKOWBDKDKNXMTNACFLYZGKXBCUAQHKNXNJQZANGZUXRFPZVJZC
JVEUTEBRDFTQAOGHHARDX
OFNHZGSVOQPLGCMIVZKODBVBLQRZK | 44.501845 | 223 | 0.955721 | 230 | 12,060 | 50.113043 | 0.917391 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025954 | 12,060 | 271 | 224 | 44.501845 | 0.981187 | 0.033665 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 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 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
3897cdb9f49467dc943611bbcb5a995975d64568 | 254 | py | Python | aula69/main.py | jessicsous/Curso_Python | 94c9b70ec03022b21ac23bf85918aa20ce4cfdd1 | [
"MIT"
] | 1 | 2021-09-21T01:50:10.000Z | 2021-09-21T01:50:10.000Z | aula69/main.py | jessicsous/Curso_Python | 94c9b70ec03022b21ac23bf85918aa20ce4cfdd1 | [
"MIT"
] | null | null | null | aula69/main.py | jessicsous/Curso_Python | 94c9b70ec03022b21ac23bf85918aa20ce4cfdd1 | [
"MIT"
] | 1 | 2021-10-04T19:49:04.000Z | 2021-10-04T19:49:04.000Z | import uma_linhas
import varias_linhas
import funçoes
import funcoes_2
import typehints
import classes
#help(uma_linhas)
#help(varias_linhas)
#help(funçoes)
#help(funcoes_2)
#help(funcoes_2.multiplica)
#print(funcoes_2.multiplica.__doc__)
#help(classes) | 18.142857 | 36 | 0.830709 | 37 | 254 | 5.378378 | 0.351351 | 0.160804 | 0.120603 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017021 | 0.074803 | 254 | 14 | 37 | 18.142857 | 0.829787 | 0.53937 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
38a35c0cb099169eca536a7938acf9b4c0509abf | 488 | py | Python | SimG4CMS/Calo/python/GeometryAPD_cff.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 852 | 2015-01-11T21:03:51.000Z | 2022-03-25T21:14:00.000Z | SimG4CMS/Calo/python/GeometryAPD_cff.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 30,371 | 2015-01-02T00:14:40.000Z | 2022-03-31T23:26:05.000Z | SimG4CMS/Calo/python/GeometryAPD_cff.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 3,240 | 2015-01-02T05:53:18.000Z | 2022-03-31T17:24:21.000Z | import FWCore.ParameterSet.Config as cms
#
# Geometry master configuration
# forStandalone APD
#
# Ideal geometry, needed for simulation
from Geometry.EcalTestBeam.APDXML_cfi import *
# Calorimeters
from Geometry.CaloEventSetup.CaloTopology_cfi import *
from Geometry.CaloEventSetup.CaloGeometry_cff import *
from Geometry.CaloEventSetup.EcalTrigTowerConstituents_cfi import *
from Geometry.EcalMapping.EcalMapping_cfi import *
from Geometry.EcalMapping.EcalMappingRecord_cfi import *
| 30.5 | 67 | 0.846311 | 53 | 488 | 7.679245 | 0.509434 | 0.176904 | 0.176904 | 0.154791 | 0.157248 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.098361 | 488 | 15 | 68 | 32.533333 | 0.925 | 0.202869 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
38b6f93829450fa507ee573e9222533b77f9b80a | 150 | py | Python | assign_2.3.py | tramontana-software/Python_Coding_Carlos | 9bba043e54ebc1604b39b0b81dbc3d4a313f5927 | [
"MIT"
] | null | null | null | assign_2.3.py | tramontana-software/Python_Coding_Carlos | 9bba043e54ebc1604b39b0b81dbc3d4a313f5927 | [
"MIT"
] | 6 | 2021-05-24T23:27:02.000Z | 2021-05-26T12:12:13.000Z | assign_2.3.py | tramontana-software/Python_Coding_Carlos | 9bba043e54ebc1604b39b0b81dbc3d4a313f5927 | [
"MIT"
] | null | null | null | # My Script:
hrs=input('Enter Hours: ')
hrs=float(hrs)
rph=input('Enter your rate per hour: ')
rph=float(rph)
pay=hrs*rph
print('Pay:', pay)
| 16.666667 | 40 | 0.64 | 25 | 150 | 3.84 | 0.56 | 0.208333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.173333 | 150 | 8 | 41 | 18.75 | 0.774194 | 0.066667 | 0 | 0 | 0 | 0 | 0.330769 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.166667 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
38b76deeed27bce887a10f8f4d3f7928d80bdec2 | 5,030 | py | Python | src/ast_node.py | ethe/elanus | 528ef897f8bad80bcda072206e8e01516532ed75 | [
"MIT"
] | 4 | 2016-10-29T10:37:23.000Z | 2020-09-22T13:13:10.000Z | src/ast_node.py | ethe/elanus | 528ef897f8bad80bcda072206e8e01516532ed75 | [
"MIT"
] | null | null | null | src/ast_node.py | ethe/elanus | 528ef897f8bad80bcda072206e8e01516532ed75 | [
"MIT"
] | 1 | 2020-07-13T03:18:51.000Z | 2020-07-13T03:18:51.000Z | # -*- coding: utf-8 -*-
from utils.singleton import Singleton
class Node(object):
def __init__(self, line=0):
self.line = line
class Expressions(Node):
def __init__(self, expressions, line=0):
super(Expressions, self).__init__(line)
self.expressions = expressions
def __eq__(self, another):
if not isinstance(another, Expressions):
return False
return self.expressions == another.expressions
def __getitem__(self, key):
return self.expressions.__getitem__(key)
def __repr__(self):
return "<Expressions {}>".format(self.expressions)
class Expression(Node):
def __repr__(self):
return "<{} {}>".format(self.__class__, self.value if hasattr(self, "value") else self.__hash__())
class Function(Expression):
def __init__(self, name=None, args=[], expressions=Expressions([]), line=0):
self.name = name
self.args = args
self.expressions = expressions
def __eq__(self, another):
if not isinstance(another, Function):
return False
return self.name == another.name and self.args == another.args and self.expressions == another.expressions
def __repr__(self):
return "<Function {}>".format(self.name)
class Call(Expression):
def __init__(self, name="", args=[], line=0):
super(Call, self).__init__(line)
self.name = name
self.args = args
def __eq__(self, another):
if not isinstance(another, Call):
return False
return self.name == another.name and self.args == another.args
def __repr__(self):
return "<Call {} {}>".format(self.name, self.args)
class Bind(Expression):
def __init__(self, name, value, line=0):
super(Expression, self).__init__(line)
self.name = name
self.value = value
def __eq__(self, another):
if not isinstance(another, Bind):
return False
return self.name == another.name and self.value == another.value
def __repr__(self):
return "<Bind {} {}>".format(self.name, self.value)
class Unit(Expression):
def __init__(self, call=None, line=0):
super(Expression, self).__init__(line)
self.call = call
def __eq__(self, another):
if not isinstance(another, Unit):
return False
return self.call == another.call
def __repr__(self):
return "<Unit {}>".format(self.call)
class Number(Expression):
def __init__(self, number, line=0):
super(Number, self).__init__(line)
self.value = number
def __eq__(self, another):
if not isinstance(another, Number):
return False
return self.value == another.value
def __repr__(self):
return str(self.value)
class Int(Number):
def __init__(self, number, line=0):
super(Int, self).__init__(int(number), line)
class Float(Number):
def __init__(self, number, line=0):
super(Float, self).__init__(float(number), line)
class Return(Expression):
def __init__(self, expression, line=0):
self.expression = expression
self.line = line
def __repr__(self):
return "<Return {}>".format(self.expression)
def __eq__(self, another):
if isinstance(another, Return):
return self.expression == self.expression
return False
class Void(Expression):
def __init__(self, line=0):
self.line = line
def __repr__(self):
return "<Void void>"
def __eq__(self, another):
if isinstance(another, Void):
return True
return False
class Nil(Singleton, Expression):
def __init__(self, line=0):
self.line = line
def __repr__(self):
return 'nil'
def __eq__(self, another):
return self is another
class Bool(Singleton, Expression):
def __init__(self, line=0):
self.line = line
def __eq__(self, another):
return self is another
class TrueType(Bool):
def __init__(self, line=0):
super(TrueType, self).__init__(line=line)
self.value = True
def __repr__(self):
return "true"
class FalseType(Bool):
def __init__(self, line=0):
super(FalseType, self).__init__(line=line)
self.value = False
def __repr__(self):
return "false"
class Closure(object):
def __init__(self, function, environment):
self.function = function
self.environment = environment
def __repr__(self):
return "<Closure {}>".format(self.function.name)
class BuiltinFunction(Function):
def __init__(self, name=None, args=[], expressions=Expressions([]), line=0):
super(BuiltinFunction, self).__init__(name=name, args=args, expressions=expressions, line=line)
def call(self, interpret, environment):
self.values = []
for i in self.args:
self.values.append(interpret(environment[i], environment).value)
return self.oprate()
| 25.532995 | 114 | 0.625249 | 589 | 5,030 | 4.972835 | 0.105263 | 0.040628 | 0.063844 | 0.075452 | 0.496074 | 0.451007 | 0.423011 | 0.349266 | 0.216115 | 0.175145 | 0 | 0.00453 | 0.253877 | 5,030 | 196 | 115 | 25.663265 | 0.775913 | 0.004175 | 0 | 0.42963 | 0 | 0 | 0.023966 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.311111 | false | 0 | 0.007407 | 0.118519 | 0.696296 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
38bb8b71c3fbc113ab45d267a429ad198c879ced | 2,260 | py | Python | sdp_2021_03/model/user.py | iproduct/intro-python | 8fcf682286dad3fc65f46ccff33aefab9c601306 | [
"Apache-2.0"
] | 3 | 2022-01-10T07:56:37.000Z | 2022-02-14T16:37:56.000Z | sdp_2021_03/model/user.py | iproduct/intro-python | 8fcf682286dad3fc65f46ccff33aefab9c601306 | [
"Apache-2.0"
] | null | null | null | sdp_2021_03/model/user.py | iproduct/intro-python | 8fcf682286dad3fc65f46ccff33aefab9c601306 | [
"Apache-2.0"
] | 1 | 2022-02-14T16:36:46.000Z | 2022-02-14T16:36:46.000Z | from functools import total_ordering
# from decorators import trace_get_attributes
import decorators as dec
# @dec.trace_get_attributes
@total_ordering
class User:
next_id = 0
# @staticmethod
# def increment_next_id():
# User.next_id += 1
@classmethod
def increment_next_id(cls):
cls.next_id += 1
def __init__(self, name, email, password, role = 'user'):
self.__class__.increment_next_id()
self.id = self.__class__.next_id
self.name = name
self.email = email
self.password = password
self.role = role
def __str__(self):
return f'ID: {self.id}, Name: {self.name}, Email: {self.email}, Role: {self.role}'
def __repr__(self):
return f'User[ ID: {self.id}, Name: {self.name}, Email: {self.email}, Role: {self.role}]'
def __eq__(self, other):
return self.id == other.id
def __lt__(self, other):
return (self.name, self.id) < (other.name, other.id)
def check_password(self, password: str) -> bool:
return password == self.password
class Author(User):
def __init__(self, name, email, password, rank = 'beginner'):
super().__init__(name, email, password, 'user')
self.rank = rank
def __str__(self):
return f'Author({super().__str__()}, Rank: {self.rank})'
class Admin(User):
def __init__(self, name, email, password, phone):
super().__init__(name, email, password, 'admin')
self.phone = phone
def __str__(self):
return f'Admin({super().__str__()}, Phone: {self.phone})'
default_admin = Admin('Admin Admin', 'admin@mycompany.com', 'admin123', '35928976564')
if __name__ == '__main__':
users: list[User] = [
Author('Ivan Petrov', 'ivanp@abv.bg', 'ivanp123'),
Admin('Admin Admin', 'admin@mycompany.com', 'admin123', '35928976564'),
Admin('Nadezda Hristova', 'nadia@mycompany.com', 'nadia123', '3592754632'),
Admin('Admin Admin', 'admin2@mycompany.com', 'admin123', '3592897655'),
]
for user in sorted(users):
print(user)
print(users[0].check_password('ivanp123')) # True
print(users[0].check_password('ivanpetrov')) # False
# print(users[0].__dict__)
# print(User.__dict__)
| 30.540541 | 97 | 0.627876 | 280 | 2,260 | 4.725 | 0.260714 | 0.068027 | 0.068027 | 0.034014 | 0.334845 | 0.220711 | 0.199546 | 0.151172 | 0.074074 | 0.074074 | 0 | 0.038068 | 0.221239 | 2,260 | 73 | 98 | 30.958904 | 0.713636 | 0.082743 | 0 | 0.061224 | 0 | 0.040816 | 0.25303 | 0.025691 | 0 | 0 | 0 | 0 | 0 | 1 | 0.22449 | false | 0.204082 | 0.040816 | 0.142857 | 0.489796 | 0.061224 | 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 | 0 | 0 | 0 | 3 |
38c26ce1ae370cab839ce8dd7dc6845e62f0610f | 115 | py | Python | dashboard/code/dashboard/events/urls.py | thedeo/terraform-aws-trailwatch | c0852d40c4c5d7524d9e61486d2b2c6d936a445b | [
"Apache-2.0"
] | null | null | null | dashboard/code/dashboard/events/urls.py | thedeo/terraform-aws-trailwatch | c0852d40c4c5d7524d9e61486d2b2c6d936a445b | [
"Apache-2.0"
] | null | null | null | dashboard/code/dashboard/events/urls.py | thedeo/terraform-aws-trailwatch | c0852d40c4c5d7524d9e61486d2b2c6d936a445b | [
"Apache-2.0"
] | null | null | null | from django.conf.urls import url
from events import views
urlpatterns = [
url('', views.search, name='events'),
] | 19.166667 | 38 | 0.721739 | 16 | 115 | 5.1875 | 0.6875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.13913 | 115 | 6 | 39 | 19.166667 | 0.838384 | 0 | 0 | 0 | 0 | 0 | 0.051724 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
2a04baa0aa3d9d81fa12d31e345c4566eac2e1dd | 964 | py | Python | sonia_hardware_states/src/sonia_hardware_states/imu_tare.py | sonia-auv/sonia-behaviors | 28519551f954616e83b474e6cab6ba3762d238f2 | [
"BSD-3-Clause"
] | null | null | null | sonia_hardware_states/src/sonia_hardware_states/imu_tare.py | sonia-auv/sonia-behaviors | 28519551f954616e83b474e6cab6ba3762d238f2 | [
"BSD-3-Clause"
] | 1 | 2022-02-16T01:31:51.000Z | 2022-02-21T22:30:46.000Z | sonia_hardware_states/src/sonia_hardware_states/imu_tare.py | sonia-auv/sonia-behaviors | 28519551f954616e83b474e6cab6ba3762d238f2 | [
"BSD-3-Clause"
] | 1 | 2021-11-09T13:34:43.000Z | 2021-11-09T13:34:43.000Z | #!/usr/bin/env python
#-*- coding: utf-8 -*-
import rospy
from flexbe_core import EventState, Logger
from sonia_common.srv import ImuTareSrv
class imu_tare(EventState):
'''
State to tare the IMU
<= continue Activation successful
<= failed Failed to call the service
'''
def __init__(self):
super(imu_tare, self).__init__(outcomes=['continue', 'failed'])
def on_enter(self, userdata):
rospy.wait_for_service('/provider_imu/tare')
self.tare = rospy.ServiceProxy('/provider_imu/tare', ImuTareSrv)
try:
self.tare({})
except rospy.ServiceException as exc:
rospy.loginfo('Service did not process request: ' + str(exc))
return 'failed'
def execute(self, userdata):
Logger.log('Tare completed', Logger.REPORT_HINT)
return 'continue'
def end(self, userdata):
pass | 26.054054 | 73 | 0.595436 | 107 | 964 | 5.196262 | 0.570093 | 0.05036 | 0.039568 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001477 | 0.297718 | 964 | 37 | 74 | 26.054054 | 0.819793 | 0.192946 | 0 | 0 | 0 | 0 | 0.149798 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.210526 | false | 0.052632 | 0.157895 | 0 | 0.526316 | 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 | 0 | 1 | 0 | 0 | 3 |
2a0df5b7e14464d8d34a7ffff0c0e04638149606 | 633 | py | Python | python/scripts/print_toto_3.py | dzertus/Helpers-Interface | e242fb4b387addc6d34c8e07dea3184eed235002 | [
"MIT"
] | null | null | null | python/scripts/print_toto_3.py | dzertus/Helpers-Interface | e242fb4b387addc6d34c8e07dea3184eed235002 | [
"MIT"
] | null | null | null | python/scripts/print_toto_3.py | dzertus/Helpers-Interface | e242fb4b387addc6d34c8e07dea3184eed235002 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
import os
from models import model_abstract
class Script(model_abstract.ScriptAbstract):
def __init__(self, path):
super().__init__(path)
self.path = path
self.name = 'Print Toto 3'
self.dcc = ['maya']
self.icon = os.path.join(r"C:\Users\youss\Documents\GitHub\Maya-Helper-Interface\icons",
'{0}.{1}'.format(self.module_name, 'png'))
def run(self):
print('Print Toto 3')
def get_name(self):
return type(self)
def get_dcc(self):
return self.dcc
def get_icon(self):
return self.icon
| 24.346154 | 96 | 0.592417 | 84 | 633 | 4.297619 | 0.52381 | 0.049862 | 0.055402 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010941 | 0.278041 | 633 | 25 | 97 | 25.32 | 0.778993 | 0.033175 | 0 | 0 | 0 | 0 | 0.158756 | 0.096563 | 0 | 0 | 0 | 0 | 0 | 1 | 0.277778 | false | 0 | 0.111111 | 0.166667 | 0.611111 | 0.055556 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
2a0f751c5788f70289f4d29c7040df8d7f01e1bb | 115 | py | Python | answers/x_8_1.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | null | null | null | answers/x_8_1.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | 4 | 2021-09-23T03:19:52.000Z | 2021-11-13T10:38:21.000Z | answers/x_8_1.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | null | null | null | # x_8_1
#
# 実行する度にランダムで「num」の値が変わります。1〜６の数字から選ばれるように修正してください
import random
num = random.randint(1, 6)
print(num)
| 12.777778 | 50 | 0.756522 | 18 | 115 | 4.777778 | 0.722222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.059406 | 0.121739 | 115 | 8 | 51 | 14.375 | 0.782178 | 0.469565 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0.333333 | 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 | 0 | 0 | 0 | 3 |
2a415878bf55853722c7ad918d5a7a0aab83fd74 | 977 | py | Python | savu/plugins/segmentation/morphological_operations/morph_proc_tools.py | elainehoml/Savu | e4772704606f71d6803d832084e10faa585e7358 | [
"Apache-2.0"
] | 39 | 2015-03-30T14:03:42.000Z | 2022-03-16T16:50:33.000Z | savu/plugins/segmentation/morphological_operations/morph_proc_tools.py | elainehoml/Savu | e4772704606f71d6803d832084e10faa585e7358 | [
"Apache-2.0"
] | 670 | 2015-02-11T11:08:09.000Z | 2022-03-21T09:27:57.000Z | savu/plugins/segmentation/morphological_operations/morph_proc_tools.py | elainehoml/Savu | e4772704606f71d6803d832084e10faa585e7358 | [
"Apache-2.0"
] | 54 | 2015-02-13T14:09:52.000Z | 2022-01-24T13:57:09.000Z | from savu.plugins.plugin_tools import PluginTools
class MorphProcTools(PluginTools):
"""A Plugin to perform morphological operations on grayscale images
(use: erosion, dilation, opening, closing) or binary images
(use: binary_erosion, binary_dilation, binary_opening, binary_closing)
"""
def define_parameters(self):
"""
disk_radius:
visibility: basic
dtype: int
description: The radius of the disk-shaped structuring element for morphology.
default: 5
morph_operation:
visibility: intermediate
dtype: int
description: The type of morphological operation.
default: 'binary_opening'
options: [binary_erosion, binary_dilation, binary_opening, binary_closing]
pattern:
visibility: intermediate
dtype: str
description: Pattern to apply this to.
default: 'VOLUME_XZ'
""" | 33.689655 | 90 | 0.63869 | 97 | 977 | 6.28866 | 0.56701 | 0.063934 | 0.062295 | 0.088525 | 0.17377 | 0.17377 | 0.17377 | 0.17377 | 0 | 0 | 0 | 0.00146 | 0.298874 | 977 | 29 | 91 | 33.689655 | 0.889051 | 0.711361 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 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 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
2a563032b2110392e8d225778510ff4eae0390b4 | 16,002 | py | Python | jaxbo/mcmc_models.py | PredictiveIntelligenceLab/JAX-BO | 0b78cce465f808149c88cb8a49c5702c8449ec84 | [
"Apache-2.0"
] | 27 | 2021-05-12T03:34:19.000Z | 2022-03-18T16:27:07.000Z | jaxbo/mcmc_models.py | PredictiveIntelligenceLab/JAX-BO | 0b78cce465f808149c88cb8a49c5702c8449ec84 | [
"Apache-2.0"
] | null | null | null | jaxbo/mcmc_models.py | PredictiveIntelligenceLab/JAX-BO | 0b78cce465f808149c88cb8a49c5702c8449ec84 | [
"Apache-2.0"
] | null | null | null | import jax.numpy as np
import jax.random as random
from jax import vmap, jit
from jax.scipy.linalg import cholesky, solve_triangular
from jax.scipy.special import expit as sigmoid
from jaxbo.models import GPmodel
import jaxbo.kernels as kernels
from numpyro import sample, deterministic, handlers
import numpyro.distributions as dist
from numpyro.infer import MCMC, NUTS
from functools import partial
# A minimal MCMC model class (inherits from GPmodel)
class MCMCmodel(GPmodel):
# Initialize the class
def __init__(self, options):
super().__init__(options)
# helper function for doing hmc inference
def train(self, batch, rng_key, settings, verbose = False):
kernel = NUTS(self.model,
target_accept_prob = settings['target_accept_prob'])
mcmc = MCMC(kernel,
num_warmup = settings['num_warmup'],
num_samples = settings['num_samples'],
num_chains = settings['num_chains'],
progress_bar=True,
jit_model_args=True)
mcmc.run(rng_key, batch)
if verbose:
mcmc.print_summary()
return mcmc.get_samples()
@partial(jit, static_argnums=(0,))
def predict(self, X_star, **kwargs):
# Normalize to [0,1]
bounds = kwargs['bounds']
X_star = (X_star - bounds['lb'])/(bounds['ub'] - bounds['lb'])
# Vectorized predictions
rng_keys = kwargs['rng_keys']
samples = kwargs['samples']
sample_fn = lambda key, sample: self.posterior_sample(key,
sample,
X_star,
**kwargs)
means, predictions = vmap(sample_fn)(rng_keys, samples)
mean_prediction = np.mean(means, axis=0)
std_prediction = np.std(predictions, axis=0)
return mean_prediction, std_prediction
# A minimal Gaussian process regression class (inherits from MCMCmodel)
class GP(MCMCmodel):
# Initialize the class
def __init__(self, options):
super().__init__(options)
def model(self, batch):
X = batch['X']
y = batch['y']
N, D = X.shape
# set uninformative log-normal priors
var = sample('kernel_var', dist.LogNormal(0.0, 10.0))
length = sample('kernel_length', dist.LogNormal(np.zeros(D), 10.0*np.ones(D)))
noise = sample('noise_var', dist.LogNormal(0.0, 10.0))
theta = np.concatenate([np.array([var]), np.array(length)])
# compute kernel
K = self.kernel(X, X, theta) + np.eye(N)*(noise + 1e-8)
# sample Y according to the standard gaussian process formula
sample("y", dist.MultivariateNormal(loc=np.zeros(N), covariance_matrix=K), obs=y)
@partial(jit, static_argnums=(0,))
def compute_cholesky(self, params, batch):
X = batch['X']
N, D = X.shape
# Fetch params
sigma_n = params[-1]
theta = params[:-1]
# Compute kernel
K = self.kernel(X, X, theta) + np.eye(N)*(sigma_n + 1e-8)
L = cholesky(K, lower=True)
return L
@partial(jit, static_argnums=(0,))
def posterior_sample(self, key, sample, X_star, **kwargs):
# Fetch training data
norm_const = kwargs['norm_const']
batch = kwargs['batch']
X, y = batch['X'], batch['y']
# Fetch params
var = sample['kernel_var']
length = sample['kernel_length']
noise = sample['noise_var']
params = np.concatenate([np.array([var]), np.array(length), np.array([noise])])
theta = params[:-1]
# Compute kernels
k_pp = self.kernel(X_star, X_star, theta) + np.eye(X_star.shape[0])*(noise + 1e-8)
k_pX = self.kernel(X_star, X, theta)
L = self.compute_cholesky(params, batch)
alpha = solve_triangular(L.T,solve_triangular(L, y, lower=True))
beta = solve_triangular(L.T,solve_triangular(L, k_pX.T, lower=True))
# Compute predictive mean, std
mu = np.matmul(k_pX, alpha)
cov = k_pp - np.matmul(k_pX, beta)
std = np.sqrt(np.clip(np.diag(cov), a_min=0.))
sample = mu + std * random.normal(key, mu.shape)
mu = mu*norm_const['sigma_y'] + norm_const['mu_y']
sample = sample*norm_const['sigma_y'] + norm_const['mu_y']
return mu, sample
# A minimal Gaussian process classification class (inherits from MCMCmodel)
class GPclassifier(MCMCmodel):
# Initialize the class
def __init__(self, options):
super().__init__(options)
def model(self, batch):
X = batch['X']
y = batch['y']
N, D = X.shape
# set uninformative log-normal priors
var = sample('kernel_var', dist.LogNormal(0.0, 1.0), sample_shape = (1,))
length = sample('kernel_length', dist.LogNormal(0.0, 1.0), sample_shape = (D,))
theta = np.concatenate([var, length])
# compute kernel
K = self.kernel(X, X, theta) + np.eye(N)*1e-8
L = cholesky(K, lower=True)
# Generate latent function
beta = sample('beta', dist.Normal(0.0, 1.0))
eta = sample('eta', dist.Normal(0.0, 1.0), sample_shape=(N,))
f = np.matmul(L, eta) + beta
# Bernoulli likelihood
sample('y', dist.Bernoulli(logits=f), obs=y)
@partial(jit, static_argnums=(0,))
def posterior_sample(self, key, sample, X_star, **kwargs):
# Fetch training data
batch = kwargs['batch']
X = batch['X']
# Fetch params
var = sample['kernel_var']
length = sample['kernel_length']
beta = sample['beta']
eta = sample['eta']
theta = np.concatenate([var, length])
# Compute kernels
K_xx = self.kernel(X, X, theta) + np.eye(X.shape[0])*1e-8
k_pp = self.kernel(X_star, X_star, theta) + np.eye(X_star.shape[0])*1e-8
k_pX = self.kernel(X_star, X, theta)
L = cholesky(K_xx, lower=True)
f = np.matmul(L, eta) + beta
tmp_1 = solve_triangular(L.T,solve_triangular(L, f, lower=True))
tmp_2 = solve_triangular(L.T,solve_triangular(L, k_pX.T, lower=True))
# Compute predictive mean
mu = np.matmul(k_pX, tmp_1)
cov = k_pp - np.matmul(k_pX, tmp_2)
std = np.sqrt(np.clip(np.diag(cov), a_min=0.))
sample = mu + std * random.normal(key, mu.shape)
return mu, sample
# A minimal Gaussian process classification class (inherits from MCMCmodel)
class MultifidelityGPclassifier(MCMCmodel):
# Initialize the class
def __init__(self, options):
super().__init__(options)
def model(self, batch):
XL, XH = batch['XL'], batch['XH']
y = batch['y']
NL, NH = XL.shape[0], XH.shape[0]
D = XH.shape[1]
# set uninformative log-normal priors for low-fidelity kernel
var_L = sample('kernel_var_L', dist.LogNormal(0.0, 1.0), sample_shape = (1,))
length_L = sample('kernel_length_L', dist.LogNormal(0.0, 1.0), sample_shape = (D,))
theta_L = np.concatenate([var_L, length_L])
# set uninformative log-normal priors for high-fidelity kernel
var_H = sample('kernel_var_H', dist.LogNormal(0.0, 1.0), sample_shape = (1,))
length_H = sample('kernel_length_H', dist.LogNormal(0.0, 1.0), sample_shape = (D,))
theta_H = np.concatenate([var_H, length_H])
# prior for rho
rho = sample('rho', dist.Normal(0.0, 10.0), sample_shape = (1,))
# Compute kernels
K_LL = self.kernel(XL, XL, theta_L) + np.eye(NL)*1e-8
K_LH = rho*self.kernel(XL, XH, theta_L)
K_HH = rho**2 * self.kernel(XH, XH, theta_L) + \
self.kernel(XH, XH, theta_H) + np.eye(NH)*1e-8
K = np.vstack((np.hstack((K_LL,K_LH)),
np.hstack((K_LH.T,K_HH))))
L = cholesky(K, lower=True)
# Generate latent function
beta_L = sample('beta_L', dist.Normal(0.0, 1.0))
beta_H = sample('beta_H', dist.Normal(0.0, 1.0))
eta_L = sample('eta_L', dist.Normal(0.0, 1.0), sample_shape=(NL,))
eta_H = sample('eta_H', dist.Normal(0.0, 1.0), sample_shape=(NH,))
beta = np.concatenate([beta_L*np.ones(NL), beta_H*np.ones(NH)])
eta = np.concatenate([eta_L, eta_H])
f = np.matmul(L, eta) + beta
# Bernoulli likelihood
sample('y', dist.Bernoulli(logits=f), obs=y)
@partial(jit, static_argnums=(0,))
def posterior_sample(self, key, sample, X_star, **kwargs):
# Fetch training data
batch = kwargs['batch']
XL, XH = batch['XL'], batch['XH']
NL, NH = XL.shape[0], XH.shape[0]
# Fetch params
var_L = sample['kernel_var_L']
var_H = sample['kernel_var_H']
length_L = sample['kernel_length_L']
length_H = sample['kernel_length_H']
beta_L = sample['beta_L']
beta_H = sample['beta_H']
eta_L = sample['eta_L']
eta_H = sample['eta_H']
rho = sample['rho']
theta_L = np.concatenate([var_L, length_L])
theta_H = np.concatenate([var_H, length_H])
beta = np.concatenate([beta_L*np.ones(NL), beta_H*np.ones(NH)])
eta = np.concatenate([eta_L, eta_H])
# Compute kernels
k_pp = rho**2 * self.kernel(X_star, X_star, theta_L) + \
self.kernel(X_star, X_star, theta_H) + \
np.eye(X_star.shape[0])*1e-8
psi1 = rho*self.kernel(X_star, XL, theta_L)
psi2 = rho**2 * self.kernel(X_star, XH, theta_L) + \
self.kernel(X_star, XH, theta_H)
k_pX = np.hstack((psi1,psi2))
# Compute K_xx
K_LL = self.kernel(XL, XL, theta_L) + np.eye(NL)*1e-8
K_LH = rho*self.kernel(XL, XH, theta_L)
K_HH = rho**2 * self.kernel(XH, XH, theta_L) + \
self.kernel(XH, XH, theta_H) + np.eye(NH)*1e-8
K_xx = np.vstack((np.hstack((K_LL,K_LH)),
np.hstack((K_LH.T,K_HH))))
L = cholesky(K_xx, lower=True)
# Sample latent function
f = np.matmul(L, eta) + beta
tmp_1 = solve_triangular(L.T,solve_triangular(L, f, lower=True))
tmp_2 = solve_triangular(L.T,solve_triangular(L, k_pX.T, lower=True))
# Compute predictive mean
mu = np.matmul(k_pX, tmp_1)
cov = k_pp - np.matmul(k_pX, tmp_2)
std = np.sqrt(np.clip(np.diag(cov), a_min=0.))
sample = mu + std * random.normal(key, mu.shape)
return mu, sample
# A minimal Gaussian process regression class (inherits from MCMCmodel)
class BayesianMLP(MCMCmodel):
# Initialize the class
def __init__(self, options, layers):
super().__init__(options)
self.layers = layers
def model(self, batch):
X = batch['X']
y = batch['y']
N, D = X.shape
H = X
# Forward pass
num_layers = len(self.layers)
for l in range(0,num_layers-2):
D_X, D_H = self.layers[l], self.layers[l+1]
W = sample('w%d' % (l+1), dist.Normal(np.zeros((D_X, D_H)), np.ones((D_X, D_H))))
b = sample('b%d' % (l+1), dist.Normal(np.zeros(D_H), np.ones(D_H)))
H = np.tanh(np.add(np.matmul(H, W), b))
D_X, D_H = self.layers[-2], self.layers[-1]
# Output mean
W = sample('w%d_mu' % (num_layers-1), dist.Normal(np.zeros((D_X, D_H)), np.ones((D_X, D_H))))
b = sample('b%d_mu' % (num_layers-1), dist.Normal(np.zeros(D_H), np.ones(D_H)))
mu = np.add(np.matmul(H, W), b)
# Output std
W = sample('w%d_std' % (num_layers-1), dist.Normal(np.zeros((D_X, D_H)), np.ones((D_X, D_H))))
b = sample('b%d_std' % (num_layers-1), dist.Normal(np.zeros(D_H), np.ones(D_H)))
sigma = np.exp(np.add(np.matmul(H, W), b))
mu, sigma = mu.flatten(), sigma.flatten()
# Likelihood
sample("y", dist.Normal(mu, sigma), obs=y)
@partial(jit, static_argnums=(0,))
def forward(self, H, sample):
num_layers = len(self.layers)
for l in range(0,num_layers-2):
W = sample['w%d'%(l+1)]
b = sample['b%d'%(l+1)]
H = np.tanh(np.add(np.matmul(H, W), b))
W = sample['w%d_mu'%(num_layers-1)]
b = sample['b%d_mu'%(num_layers-1)]
mu = np.add(np.matmul(H, W), b)
W = sample['w%d_std'%(num_layers-1)]
b = sample['b%d_std'%(num_layers-1)]
sigma = np.exp(np.add(np.matmul(H, W), b))
return mu, sigma
@partial(jit, static_argnums=(0,))
def posterior_sample(self, key, sample, X_star, **kwargs):
mu, sigma = self.forward(X_star, sample)
sample = mu + np.sqrt(sigma) * random.normal(key, mu.shape)
# De-normalize
norm_const = kwargs['norm_const']
mu = mu*norm_const['sigma_y'] + norm_const['mu_y']
sample = sample*norm_const['sigma_y'] + norm_const['mu_y']
return mu.flatten(), sample.flatten()
# A minimal Gaussian process regression class (inherits from MCMCmodel)
# Work in progress..
class MissingInputsGP(MCMCmodel):
# Initialize the class
def __init__(self, options, dim_H, latent_bounds):
super().__init__(options)
self.dim_H = dim_H
self.latent_bounds = latent_bounds
def model(self, batch):
X = batch['X']
y = batch['y']
N = y.shape[0]
dim_X = X.shape[1]
dim_H = self.dim_H
D = dim_X + dim_H
# Generate latent inputs
H = sample('H', dist.Normal(np.zeros((N, dim_H)), np.ones((N, dim_H))))
X = np.concatenate([X, H], axis = 1)
# set uninformative log-normal priors on GP hyperparameters
var = sample('kernel_var', dist.LogNormal(0.0, 10.0))
length = sample('kernel_length', dist.LogNormal(np.zeros(D), 10.0*np.ones(D)))
noise = sample('noise_var', dist.LogNormal(0.0, 10.0))
theta = np.concatenate([np.array([var]), np.array(length)])
# compute kernel
K = self.kernel(X, X, theta) + np.eye(N)*(noise + 1e-8)
# sample Y according to the GP likelihood
sample("y", dist.MultivariateNormal(loc=np.zeros(N), covariance_matrix=K), obs=y)
@partial(jit, static_argnums=(0,))
def compute_cholesky(self, params, batch):
X = batch['X']
N, D = X.shape
# Fetch params
sigma_n = params[-1]
theta = params[:-1]
# Compute kernel
K = self.kernel(X, X, theta) + np.eye(N)*(sigma_n + 1e-8)
L = cholesky(K, lower=True)
return L
@partial(jit, static_argnums=(0,))
def posterior_sample(self, key, sample, X_star, **kwargs):
batch = kwargs['batch']
X, y = batch['X'], batch['y']
# Fetch missing inputs
H = sample['H']
X = np.concatenate([X, H], axis=1)
# Fetch GP params
var = sample['kernel_var']
length = sample['kernel_length']
noise = sample['noise_var']
params = np.concatenate([np.array([var]), np.array(length), np.array([noise])])
theta = params[:-1]
# Compute kernels
k_pp = self.kernel(X_star, X_star, theta) + np.eye(X_star.shape[0])*(noise + 1e-8)
k_pX = self.kernel(X_star, X, theta)
L = self.compute_cholesky(params, batch)
alpha = solve_triangular(L.T,solve_triangular(L, y, lower=True))
beta = solve_triangular(L.T,solve_triangular(L, k_pX.T, lower=True))
# Compute predictive mean, std
mu = np.matmul(k_pX, alpha)
cov = k_pp - np.matmul(k_pX, beta)
std = np.sqrt(np.clip(np.diag(cov), a_min=0.))
sample = mu + std * random.normal(key, mu.shape)
# De-normalize
norm_const = kwargs['norm_const']
mu = mu*norm_const['sigma_y'] + norm_const['mu_y']
sample = sample*norm_const['sigma_y'] + norm_const['mu_y']
return mu, sample
| 42.110526 | 102 | 0.577928 | 2,324 | 16,002 | 3.813683 | 0.090361 | 0.016924 | 0.021099 | 0.005416 | 0.779194 | 0.760916 | 0.703825 | 0.685772 | 0.627214 | 0.61108 | 0 | 0.015769 | 0.274778 | 16,002 | 379 | 103 | 42.221636 | 0.747953 | 0.102925 | 0 | 0.611684 | 0 | 0 | 0.044291 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.072165 | false | 0 | 0.037801 | 0 | 0.164948 | 0.003436 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
2a5904bad4ef014ffd79ef6c66230986bc0739bf | 1,194 | py | Python | utils/log.py | skal1ozz/AI-WordOfWarcraft-Bot | 1d9659e76d1107909d6ca27b573d0dd83a25fce4 | [
"Apache-2.0"
] | null | null | null | utils/log.py | skal1ozz/AI-WordOfWarcraft-Bot | 1d9659e76d1107909d6ca27b573d0dd83a25fce4 | [
"Apache-2.0"
] | null | null | null | utils/log.py | skal1ozz/AI-WordOfWarcraft-Bot | 1d9659e76d1107909d6ca27b573d0dd83a25fce4 | [
"Apache-2.0"
] | null | null | null | import logging
import traceback
class Log(object):
loggers = {}
@staticmethod
def log(level, tag, source, message="", exc_info=None):
logger = Log.loggers.get(tag, logging.getLogger(tag))
line = "{source}{message}{ex}"
ex = ""
if isinstance(exc_info, (list, tuple)):
ex_type, ex_value, ex_traceback = exc_info
ex = ": " + ''.join(
traceback.format_exception(ex_type, ex_value, ex_traceback)
)
message = "::{}".format(message) if message else ""
logger.log(level, line.format(source=source, message=message, ex=ex))
@staticmethod
def w(tag, source, message="", exc_info=None):
return Log.log(logging.WARN, tag, source, message, exc_info)
@staticmethod
def d(tag, source, message="", exc_info=None):
return Log.log(logging.DEBUG, tag, source, message, exc_info)
@staticmethod
def i(tag, source, message="", exc_info=None):
return Log.log(logging.INFO, tag, source, message, exc_info)
@staticmethod
def e(tag, source, message="error", exc_info=None):
return Log.log(logging.ERROR, tag, source, message, exc_info)
| 32.27027 | 77 | 0.621441 | 150 | 1,194 | 4.826667 | 0.26 | 0.197514 | 0.198895 | 0.209945 | 0.524862 | 0.493094 | 0.389503 | 0.190608 | 0.190608 | 0.190608 | 0 | 0 | 0.241206 | 1,194 | 36 | 78 | 33.166667 | 0.799117 | 0 | 0 | 0.178571 | 0 | 0 | 0.026801 | 0.017588 | 0 | 0 | 0 | 0 | 0 | 1 | 0.178571 | false | 0 | 0.071429 | 0.142857 | 0.464286 | 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 | 0 | 1 | 0 | 0 | 0 | 3 |
2a67f05d2d906a0c73f9a73e7830d3055c520156 | 173 | py | Python | src/waldur_pid/apps.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 26 | 2017-10-18T13:49:58.000Z | 2021-09-19T04:44:09.000Z | src/waldur_pid/apps.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 14 | 2018-12-10T14:14:51.000Z | 2021-06-07T10:33:39.000Z | src/waldur_pid/apps.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 32 | 2017-09-24T03:10:45.000Z | 2021-10-16T16:41:09.000Z | from django.apps import AppConfig
class PIDConfig(AppConfig):
name = 'waldur_pid'
verbose_name = 'PID'
service_name = 'PID'
def ready(self):
pass
| 15.727273 | 33 | 0.647399 | 21 | 173 | 5.190476 | 0.761905 | 0.12844 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.260116 | 173 | 10 | 34 | 17.3 | 0.851563 | 0 | 0 | 0 | 0 | 0 | 0.092486 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0.142857 | 0.142857 | 0 | 0.857143 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
2a75d7332e66dd251223ccdf53c0f9dec35541d0 | 398 | py | Python | graviti/__init__.py | Lee-000/graviti-python-sdk | 46b19a4a74949a957da3e72261b1403bbeeac01a | [
"MIT"
] | 12 | 2022-01-26T06:51:02.000Z | 2022-03-22T21:28:35.000Z | graviti/__init__.py | Lee-000/graviti-python-sdk | 46b19a4a74949a957da3e72261b1403bbeeac01a | [
"MIT"
] | 51 | 2022-02-22T07:19:34.000Z | 2022-03-31T11:39:51.000Z | graviti/__init__.py | Lee-000/graviti-python-sdk | 46b19a4a74949a957da3e72261b1403bbeeac01a | [
"MIT"
] | 5 | 2022-01-26T06:51:49.000Z | 2022-03-08T03:41:11.000Z | #!/usr/bin/env python3
#
# Copyright 2022 Graviti. Licensed under MIT License.
#
"""Graviti Python SDK."""
from graviti.__version__ import __version__
from graviti.dataframe import ColumnSeriesBase as Series
from graviti.dataframe import DataFrame
from graviti.utility import engine
from graviti.workspace import Workspace
__all__ = ["__version__", "DataFrame", "Workspace", "Series", "engine"]
| 26.533333 | 71 | 0.78392 | 47 | 398 | 6.297872 | 0.510638 | 0.185811 | 0.135135 | 0.175676 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.014245 | 0.11809 | 398 | 14 | 72 | 28.428571 | 0.82906 | 0.233668 | 0 | 0 | 0 | 0 | 0.138514 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.833333 | 0 | 0.833333 | 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 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
2a7ac6fe891c65d9cce3b235087c8a6511328586 | 200 | py | Python | rwb/kwbrowser/__main__.py | boakley/robotframework-workbench | 92f15845d6fa4baedd4f3c4346fb8ff5cf9149a6 | [
"Apache-2.0"
] | 11 | 2015-03-09T01:53:21.000Z | 2021-03-29T08:33:05.000Z | rwb/kwbrowser/__main__.py | boakley/robotframework-workbench | 92f15845d6fa4baedd4f3c4346fb8ff5cf9149a6 | [
"Apache-2.0"
] | 1 | 2016-08-24T06:20:11.000Z | 2016-08-24T06:20:11.000Z | rwb/kwbrowser/__main__.py | boakley/robotframework-workbench | 92f15845d6fa4baedd4f3c4346fb8ff5cf9149a6 | [
"Apache-2.0"
] | 5 | 2016-03-03T15:27:09.000Z | 2019-03-26T13:05:32.000Z | import sys
from app import KwBrowserApp
import rwb
try:
rwb.app = KwBrowserApp()
rwb.app.mainloop()
except KeyboardInterrupt:
print "program quit at request of the user"
sys.exit(0)
| 16.666667 | 47 | 0.715 | 28 | 200 | 5.107143 | 0.714286 | 0.083916 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006329 | 0.21 | 200 | 11 | 48 | 18.181818 | 0.898734 | 0 | 0 | 0 | 0 | 0 | 0.175879 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.333333 | null | null | 0.111111 | 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 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
2a8351dfd55d24c60482315c8afa231ac08a7f4f | 240 | py | Python | grepUrl.py | andrebalen/mineNugget | 0399cd666a81bc6136c9bd09e1574fd83885f9ea | [
"Apache-2.0"
] | null | null | null | grepUrl.py | andrebalen/mineNugget | 0399cd666a81bc6136c9bd09e1574fd83885f9ea | [
"Apache-2.0"
] | null | null | null | grepUrl.py | andrebalen/mineNugget | 0399cd666a81bc6136c9bd09e1574fd83885f9ea | [
"Apache-2.0"
] | null | null | null | import re
import urllib2
stuff = urllib2.urlopen('http://python.org').read() # stuff will contain the *entire* page
# Replace the string Python with your desired regex
results = re.findall('(Python)',stuff)
for i in results:
print i
| 24 | 91 | 0.725 | 36 | 240 | 4.833333 | 0.722222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00995 | 0.1625 | 240 | 9 | 92 | 26.666667 | 0.855721 | 0.358333 | 0 | 0 | 0 | 0 | 0.165563 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.333333 | null | null | 0.166667 | 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 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
aa68b18b77b5bc5459c4f5ef85ab6a8f377f5920 | 72 | py | Python | calm/dsl/providers/plugins/existing_vm/__init__.py | opywan/calm-dsl | 1d89436d039a39265a0ae806022be5b52e757ac0 | [
"Apache-2.0"
] | 37 | 2019-12-23T15:23:20.000Z | 2022-03-15T11:12:11.000Z | calm/dsl/providers/plugins/existing_vm/__init__.py | opywan/calm-dsl | 1d89436d039a39265a0ae806022be5b52e757ac0 | [
"Apache-2.0"
] | 144 | 2020-03-09T11:22:09.000Z | 2022-03-28T21:34:09.000Z | calm/dsl/providers/plugins/existing_vm/__init__.py | opywan/calm-dsl | 1d89436d039a39265a0ae806022be5b52e757ac0 | [
"Apache-2.0"
] | 46 | 2020-01-23T14:28:04.000Z | 2022-03-09T04:17:10.000Z | from .main import ExistingVmProvider
__all__ = ["ExistingVmProvider"]
| 14.4 | 36 | 0.791667 | 6 | 72 | 8.833333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 72 | 4 | 37 | 18 | 0.84127 | 0 | 0 | 0 | 0 | 0 | 0.25 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
aa89fe01a87ed3712385d7e934e60a0af15ebe15 | 32,103 | py | Python | test/test_snap_schedule.py | point85/PyShift | 46d0e1c23d3c570416633f68d416abd587b8e22f | [
"MIT"
] | null | null | null | test/test_snap_schedule.py | point85/PyShift | 46d0e1c23d3c570416633f68d416abd587b8e22f | [
"MIT"
] | null | null | null | test/test_snap_schedule.py | point85/PyShift | 46d0e1c23d3c570416633f68d416abd587b8e22f | [
"MIT"
] | null | null | null | from datetime import datetime, time, timedelta
from PyShift.test.base_test import BaseTest
from PyShift.workschedule.work_schedule import WorkSchedule
class TestSnapSchedule(BaseTest):
def testLowNight(self):
description = "Low night demand"
self.workSchedule = WorkSchedule("Low Night Demand Plan", description)
# 3 shifts
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=8))
swing = self.workSchedule.createShift("Swing", "Swing shift", time(15, 0, 0), timedelta(hours=8))
night = self.workSchedule.createShift("Night", "Night shift", time(23, 0, 0), timedelta(hours=8))
# Team rotation
rotation = self.workSchedule.createRotation("Low night demand", "Low night demand")
rotation.addSegment(day, 3, 0)
rotation.addSegment(swing, 4, 3)
rotation.addSegment(day, 4, 0)
rotation.addSegment(swing, 3, 4)
rotation.addSegment(day, 3, 0)
rotation.addSegment(night, 4, 3)
rotation.addSegment(day, 4, 0)
rotation.addSegment(night, 3, 4)
# 6 teams
self.workSchedule.createTeam("Team1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team2", "Second team", rotation, self.referenceDate - timedelta(days=21))
self.workSchedule.createTeam("Team3", "Third team", rotation, self.referenceDate - timedelta(days=7))
self.workSchedule.createTeam("Team4", "Fourth team", rotation, self.referenceDate - timedelta(days=28))
self.workSchedule.createTeam("Team5", "Fifth team", rotation, self.referenceDate - timedelta(days=14))
self.workSchedule.createTeam("Team6", "Sixth team", rotation, self.referenceDate - timedelta(days=35))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 896 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 6048 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 1344 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 1008 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 22.22, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 224 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 37.33, 2)
self.runBaseTest(timedelta(hours=224), timedelta(days=42))
def test3TeamFixed24(self):
description = "Fire departments"
self.workSchedule = WorkSchedule("3 Team Fixed 24 Plan", description)
# starts at 00:00 for 24 hours
shift = self.workSchedule.createShift("24 Hour", "24 hour shift", time(0, 0, 0), timedelta(hours=24))
# Team rotation
rotation = self.workSchedule.createRotation("3 Team Fixed 24 Plan", "3 Team Fixed 24 Plan")
rotation.addSegment(shift, 1, 1)
rotation.addSegment(shift, 1, 1)
rotation.addSegment(shift, 1, 4)
# 3 teams
self.workSchedule.createTeam("Team1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team2", "Second team", rotation, self.referenceDate - timedelta(days=3))
self.workSchedule.createTeam("Team3", "Third team", rotation, self.referenceDate - timedelta(days=6))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 672 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 648 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 216 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 216 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 33.33, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 72 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 56, 1)
self.runBaseTest(timedelta(hours=72), timedelta(days=9))
def test549(self):
description = "Compressed work workSchedule."
self.workSchedule = WorkSchedule("5/4/9 Plan", description)
# 1 starts at 07:00 for 9 hours
day1 = self.workSchedule.createShift("Day1", "Day shift #1", time(7, 0, 0), timedelta(hours=9))
# 2 starts at 07:00 for 8 hours
day2 = self.workSchedule.createShift("Day2", "Day shift #2", time(7, 0, 0), timedelta(hours=8))
# Team rotation (28 days)
rotation = self.workSchedule.createRotation("5/4/9 ", "5/4/9 ")
rotation.addSegment(day1, 4, 0)
rotation.addSegment(day2, 1, 3)
rotation.addSegment(day1, 4, 3)
rotation.addSegment(day1, 4, 2)
rotation.addSegment(day1, 4, 0)
rotation.addSegment(day2, 1, 2)
# 2 teams
self.workSchedule.createTeam("Team1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team2", "Second team", rotation, self.referenceDate - timedelta(days=14))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 320 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 1344 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 320 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 672 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 23.81, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 160 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 40, 1)
self.runBaseTest(timedelta(hours=160), timedelta(days=28))
def test9to5(self):
description = "This is the basic 9 to 5 workSchedule plan for office employees. Every employee works 8 hrs a day from Monday to Friday."
self.workSchedule = WorkSchedule("9 To 5 Plan", description)
# starts at 09:00 for 8 hours
day = self.workSchedule.createShift("Day", "Day shift", time(9, 0, 0), timedelta(hours=8))
# Team1 rotation (5 days)
rotation = self.workSchedule.createRotation("9 To 5 ", "9 To 5 ")
rotation.addSegment(day, 5, 2)
# 1 team, 1 shift
self.workSchedule.createTeam("Team", "One team", rotation, self.referenceDate)
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 160 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 168 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 40 * 3600)
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=1), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 168 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 23.81, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 40 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 40, 1)
self.runBaseTest(timedelta(hours=40), timedelta(days=7))
def test8Plus12(self):
description = "This is a fast rotation plan that uses 4 teams and a combination of three 8-hr shifts on weekdays and two 12-hr shifts on weekends to provide 24/7 coverage."
self.workSchedule = WorkSchedule("8 Plus 12 Plan", description)
# Day shift #1, starts at 07:00 for 12 hours
day1 = self.workSchedule.createShift("Day1", "Day shift #1", time(7, 0, 0), timedelta(hours=12))
# Day shift #2, starts at 07:00 for 8 hours
day2 = self.workSchedule.createShift("Day2", "Day shift #2", time(7, 0, 0), timedelta(hours=8))
# Swing shift, starts at 15:00 for 8 hours
swing = self.workSchedule.createShift("Swing", "Swing shift", time(15, 0, 0), timedelta(hours=8))
# Night shift #1, starts at 19:00 for 12 hours
night1 = self.workSchedule.createShift("Night1", "Night shift #1", time(19, 0, 0), timedelta(hours=12))
# Night shift #2, starts at 23:00 for 8 hours
night2 = self.workSchedule.createShift("Night2", "Night shift #2", time(23, 0, 0), timedelta(hours=8))
# shift rotation (28 days)
rotation = self.workSchedule.createRotation("8 Plus 12", "8 Plus 12")
rotation.addSegment(day2, 5, 0)
rotation.addSegment(day1, 2, 3)
rotation.addSegment(night2, 2, 0)
rotation.addSegment(night1, 2, 0)
rotation.addSegment(night2, 3, 4)
rotation.addSegment(swing, 5, 2)
# 4 teams, rotating through 5 shifts
self.workSchedule.createTeam("Team 1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", rotation, self.referenceDate - timedelta(days=7))
self.workSchedule.createTeam("Team 3", "Third team", rotation, self.referenceDate - timedelta(days=14))
self.workSchedule.createTeam("Team 4", "Fourth team", rotation, self.referenceDate - timedelta(days=21))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 672 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 2688 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 672 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 672 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 25.00, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 168 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 42, 1)
self.runBaseTest(timedelta(hours=168), timedelta(days=28))
def testICUInterns(self):
description = "This plan supports a combination of 14-hr day shift , 15.5-hr cross-cover shift , and a 14-hr night shift for medical interns. "
description = description + "The day shift and the cross-cover shift have the same start time (7:00AM). "
description = description + "The night shift starts at around 10:00PM and ends at 12:00PM on the next day."
self.workSchedule = WorkSchedule("ICU Interns Plan", description)
# Day shift #1, starts at 07:00 for 15.5 hours
crossover = self.workSchedule.createShift("Crossover", "Day shift #1 cross-over", time(7, 0, 0),
timedelta(hours=15) + timedelta(minutes=30))
# Day shift #2, starts at 07:00 for 14 hours
day = self.workSchedule.createShift("Day", "Day shift #2", time(7, 0, 0), timedelta(hours=14))
# Night shift, starts at 22:00 for 14 hours
night = self.workSchedule.createShift("Night", "Night shift", time(22, 0, 0), timedelta(hours=14))
# Team1 rotation
rotation = self.workSchedule.createRotation("ICU", "ICU")
rotation.addSegment(day, 1, 0)
rotation.addSegment(crossover, 1, 0)
rotation.addSegment(night, 1, 1)
self.workSchedule.createTeam("Team 1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", rotation, self.referenceDate - timedelta(days=3))
self.workSchedule.createTeam("Team 3", "Third team", rotation, self.referenceDate - timedelta(days=2))
self.workSchedule.createTeam("Team 4", "Forth team", rotation, self.referenceDate - timedelta(days=1))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 1223 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 384 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 174 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 96 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 45.31, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 43 * 3600 + 30 * 60)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 76.125, 1)
self.runBaseTest(timedelta(minutes=2610), timedelta(days=4))
def testDupont(self):
description = "The DuPont 12-hour rotating shift workSchedule uses 4 teams (crews) and 2 twelve-hour shifts to provide 24/7 coverage. "
description = description + "It consists of a 4-week cycle where each team works 4 consecutive night shifts, "
description = description + "followed by 3 days off duty, works 3 consecutive day shifts, followed by 1 day off duty, works 3 consecutive night shifts, "
description = description + "followed by 3 days off duty, work 4 consecutive day shift, then have 7 consecutive days off duty. "
description = description + "Personnel works an average 42 hours per week."
self.workSchedule = WorkSchedule("DuPont Schedule", description)
# Day shift, starts at 07:00 for 12 hours
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=12))
# Night shift, starts at 19:00 for 12 hours
night = self.workSchedule.createShift("Night", "Night shift", time(19, 0, 0), timedelta(hours=12))
# Team1 rotation
rotation =self.workSchedule.createRotation("DuPont", "DuPont")
rotation.addSegment(night, 4, 3)
rotation.addSegment(day, 3, 1)
rotation.addSegment(night, 3, 3)
rotation.addSegment(day, 4, 7)
self.workSchedule.createTeam("Team 1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", rotation, self.referenceDate - timedelta(days=7))
self.workSchedule.createTeam("Team 3", "Third team", rotation, self.referenceDate - timedelta(days=14))
self.workSchedule.createTeam("Team 4", "Forth team", rotation, self.referenceDate - timedelta(days=21))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 672 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 2688 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 672 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 672 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 25.00, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 168 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 42.0, 1)
self.runBaseTest(timedelta(hours=168), timedelta(days=28))
def testDNO(self):
description = "This is a fast rotation plan that uses 3 teams and two 12-hr shifts to provide 24/7 coverage. "
description = description + "Each team rotates through the following sequence every three days: 1 day shift, 1 night shift, and 1 day off."
self.workSchedule = WorkSchedule("DNO Plan", description)
# Day shift, starts at 07:00 for 12 hours
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=12))
# Night shift, starts at 19:00 for 12 hours
night = self.workSchedule.createShift("Night", "Night shift", time(19, 0, 0), timedelta(hours=12))
# rotation
rotation = self.workSchedule.createRotation("DNO", "DNO")
rotation.addSegment(day, 1, 0)
rotation.addSegment(night, 1, 1)
self.workSchedule.createTeam("Team 1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", rotation, self.referenceDate - timedelta(days=1))
self.workSchedule.createTeam("Team 3", "Third team", rotation, self.referenceDate - timedelta(days=2))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 672 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 216 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 72 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 72 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 33.33, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 24 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 56.0, 1)
self.runBaseTest(timedelta(hours=24), timedelta(days=3))
def test21TeamFixed(self):
description = "".join(["This plan is a fixed (no rotation) plan that uses 21 teams and three 8-hr shifts to provide 24/7 coverage. "
,"It maximizes the number of consecutive days off while still averaging 40 hours per week. "
,"Over a 7 week cycle, each employee has two 3 consecutive days off and is required to work 6 consecutive days on 5 of the 7 weeks. "
,"On any given day, 15 teams will be scheduled to work and 6 teams will be off. "
,"Each shift will be staffed by 5 teams so the minimum number of employees per shift is five. "])
self.workSchedule = WorkSchedule("21 Team Fixed 8 6D Plan", description)
# Day shift, starts at 07:00 for 8 hours
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=8))
# Swing shift, starts at 15:00 for 8 hours
swing = self.workSchedule.createShift("Swing", "Swing shift", time(15, 0, 0), timedelta(hours=8))
# Night shift, starts at 15:00 for 8 hours
night = self.workSchedule.createShift("Night", "Night shift", time(23, 0, 0), timedelta(hours=8))
# day rotation
dayRotation = self.workSchedule.createRotation("Day", "Day")
dayRotation.addSegment(day, 6, 3)
dayRotation.addSegment(day, 5, 3)
dayRotation.addSegment(day, 6, 2)
dayRotation.addSegment(day, 6, 2)
dayRotation.addSegment(day, 6, 2)
dayRotation.addSegment(day, 6, 2)
# swing rotation
swingRotation = self.workSchedule.createRotation("Swing", "Swing")
swingRotation.addSegment(swing, 6, 3)
swingRotation.addSegment(swing, 5, 3)
swingRotation.addSegment(swing, 6, 2)
swingRotation.addSegment(swing, 6, 2)
swingRotation.addSegment(swing, 6, 2)
swingRotation.addSegment(swing, 6, 2)
# night rotation
nightRotation = self.workSchedule.createRotation("Night", "Night")
nightRotation.addSegment(night, 6, 3)
nightRotation.addSegment(night, 5, 3)
nightRotation.addSegment(night, 6, 2)
nightRotation.addSegment(night, 6, 2)
nightRotation.addSegment(night, 6, 2)
nightRotation.addSegment(night, 6, 2)
# day teams
self.workSchedule.createTeam("Team 1", "1st day team", dayRotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "2nd day team", dayRotation, self.referenceDate + timedelta(days=7))
self.workSchedule.createTeam("Team 3", "3rd day team", dayRotation, self.referenceDate + timedelta(days=14))
self.workSchedule.createTeam("Team 4", "4th day team", dayRotation, self.referenceDate + timedelta(days=21))
self.workSchedule.createTeam("Team 5", "5th day team", dayRotation, self.referenceDate + timedelta(days=28))
self.workSchedule.createTeam("Team 6", "6th day team", dayRotation, self.referenceDate + timedelta(days=35))
self.workSchedule.createTeam("Team 7", "7th day team", dayRotation, self.referenceDate + timedelta(days=42))
# swing teams
self.workSchedule.createTeam("Team 8", "1st swing team", swingRotation, self.referenceDate)
self.workSchedule.createTeam("Team 9", "2nd swing team", swingRotation, self.referenceDate + timedelta(days=7))
self.workSchedule.createTeam("Team 10", "3rd swing team", swingRotation, self.referenceDate + timedelta(days=14))
self.workSchedule.createTeam("Team 11", "4th swing team", swingRotation, self.referenceDate + timedelta(days=21))
self.workSchedule.createTeam("Team 12", "5th swing team", swingRotation, self.referenceDate + timedelta(days=28))
self.workSchedule.createTeam("Team 13", "6th swing team", swingRotation, self.referenceDate + timedelta(days=35))
self.workSchedule.createTeam("Team 14", "7th swing team", swingRotation, self.referenceDate + timedelta(days=42))
# night teams
self.workSchedule.createTeam("Team 15", "1st night team", nightRotation, self.referenceDate)
self.workSchedule.createTeam("Team 16", "2nd night team", nightRotation, self.referenceDate + timedelta(days=7))
self.workSchedule.createTeam("Team 17", "3rd night team", nightRotation, self.referenceDate + timedelta(days=14))
self.workSchedule.createTeam("Team 18", "4th night team", nightRotation, self.referenceDate + timedelta(days=21))
self.workSchedule.createTeam("Team 19", "5th night team", nightRotation, self.referenceDate + timedelta(days=28))
self.workSchedule.createTeam("Team 20", "6th night team", nightRotation, self.referenceDate + timedelta(days=35))
self.workSchedule.createTeam("Team 21", "7th night team", nightRotation, self.referenceDate + timedelta(days=42))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 3360 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 24696 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 5880 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 1176 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 23.81, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 280 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 40.0, 1)
self.runBaseTest(timedelta(hours=280), timedelta(days=49), self.referenceDate + timedelta(days=49))
def testTwoTeam(self):
description = "".join(["This is a fixed (no rotation) plan that uses 2 teams and two 12-hr shifts to provide 24/7 coverage. "
,"One team will be permanently on the day shift and the other will be on the night shift."])
self.workSchedule = WorkSchedule("2 Team Fixed 12 Plan", description)
# Day shift, starts at 07:00 for 12 hours
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=12))
# Night shift, starts at 19:00 for 12 hours
night = self.workSchedule.createShift("Night", "Night shift", time(19, 0, 0), timedelta(hours=12))
# Team1 rotation
team1Rotation = self.workSchedule.createRotation("Team1", "Team1")
team1Rotation.addSegment(day, 1, 0)
# Team1 rotation
team2Rotation = self.workSchedule.createRotation("Team2", "Team2")
team2Rotation.addSegment(night, 1, 0)
self.workSchedule.createTeam("Team 1", "First team", team1Rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", team2Rotation, self.referenceDate)
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 1320 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 48 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 24 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 24 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 50.00, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 12 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 84.0, 1)
self.runBaseTest(timedelta(hours=12), timedelta(days=1))
def testPanama(self):
description = "".join(["This is a slow rotation plan that uses 4 teams and two 12-hr shifts to provide 24/7 coverage. "
, "The working and non-working days follow this pattern: 2 days on, 2 days off, 3 days on, 2 days off, 2 days on, 3 days off. "
, "Each team works the same shift (day or night) for 28 days then switches over to the other shift for the next 28 days. "
, "After 56 days, the same sequence starts over."])
self.workSchedule = WorkSchedule("Panama", description)
# Day shift, starts at 07:00 for 12 hours
day = self.workSchedule.createShift("Day", "Day shift", time(7, 0, 0), timedelta(hours=12))
# Night shift, starts at 19:00 for 12 hours
night = self.workSchedule.createShift("Night", "Night shift", time(19, 0, 0), timedelta(hours=12))
# rotation
rotation = self.workSchedule.createRotation("Panama",
"2 days on, 2 days off, 3 days on, 2 days off, 2 days on, 3 days off")
# 2 days on, 2 off, 3 on, 2 off, 2 on, 3 off (and repeat)
rotation.addSegment(day, 2, 2)
rotation.addSegment(day, 3, 2)
rotation.addSegment(day, 2, 3)
rotation.addSegment(day, 2, 2)
rotation.addSegment(day, 3, 2)
rotation.addSegment(day, 2, 3)
# 2 nights on, 2 off, 3 on, 2 off, 2 on, 3 off (and repeat)
rotation.addSegment(night, 2, 2)
rotation.addSegment(night, 3, 2)
rotation.addSegment(night, 2, 3)
rotation.addSegment(night, 2, 2)
rotation.addSegment(night, 3, 2)
rotation.addSegment(night, 2, 3)
self.workSchedule.createTeam("Team 1", "First team", rotation, self.referenceDate)
self.workSchedule.createTeam("Team 2", "Second team", rotation, self.referenceDate - timedelta(days=28))
self.workSchedule.createTeam("Team 3", "Third team", rotation, self.referenceDate - timedelta(days=7))
self.workSchedule.createTeam("Team 4", "Fourth team", rotation, self.referenceDate - timedelta(days=35))
# specific checks
fromDateTime = datetime.combine(self.laterDate, self.laterTime)
toDateTime = datetime.combine(self.laterDate + timedelta(days=28), self.laterTime)
workingTime = self.workSchedule.calculateWorkingTime(fromDateTime, toDateTime)
nonWorkingTime = self.workSchedule.calculateNonWorkingTime(fromDateTime, toDateTime)
self.assertTrue(workingTime.total_seconds() == 672 * 3600)
self.assertTrue(nonWorkingTime.total_seconds() == 0)
self.assertTrue(self.workSchedule.getRotationDuration().total_seconds() == 5376 * 3600)
self.assertTrue(self.workSchedule.getRotationWorkingTime().total_seconds() == 1344 * 3600)
for team in self.workSchedule.teams:
self.assertTrue(team.rotation.getDuration().total_seconds() == 1344 * 3600)
self.assertAlmostEqual(team.getPercentageWorked(), 25.00, 2)
self.assertTrue(team.rotation.getWorkingTime().total_seconds() == 336 * 3600)
self.assertAlmostEqual(team.getAverageHoursWorkedPerWeek(), 42.0, 1)
self.runBaseTest(timedelta(hours=336), timedelta(days=56))
| 56.321053 | 180 | 0.674392 | 3,635 | 32,103 | 5.937276 | 0.07868 | 0.119359 | 0.065054 | 0.059772 | 0.81012 | 0.77472 | 0.748355 | 0.699935 | 0.655871 | 0.595867 | 0 | 0.053527 | 0.210884 | 32,103 | 570 | 181 | 56.321053 | 0.798405 | 0.047784 | 0 | 0.462162 | 0 | 0.040541 | 0.135327 | 0 | 0 | 0 | 0 | 0 | 0.237838 | 1 | 0.02973 | false | 0 | 0.008108 | 0 | 0.040541 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 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 | 3 |
aa97aff8076d9999a2f8046ae42aa369d313d0ed | 1,119 | py | Python | kArmedBandit/envs/TenArmedBanditGaussianReward_env.py | SasankYadati/kArmedBandit | ed9aacad48b2063661f7281b288ae269d2a8120e | [
"MIT"
] | null | null | null | kArmedBandit/envs/TenArmedBanditGaussianReward_env.py | SasankYadati/kArmedBandit | ed9aacad48b2063661f7281b288ae269d2a8120e | [
"MIT"
] | null | null | null | kArmedBandit/envs/TenArmedBanditGaussianReward_env.py | SasankYadati/kArmedBandit | ed9aacad48b2063661f7281b288ae269d2a8120e | [
"MIT"
] | null | null | null | import gym
from gym import error, spaces, utils
from gym.utils import seeding
import numpy as np
import random
class TenArmedBanditGaussianRewardEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self, seed=42):
self._seed(seed)
self.num_bandits = 10
# each reward distribution is a gaussian described using mean and standard deviation
self.reward_dist = [[random.uniform(0, 1), 0.5] for _ in range(self.num_bandits)]
self.action_space = spaces.Discrete(self.num_bandits)
self.observation_space = spaces.Discrete(1)
def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def step(self, action):
assert self.action_space.contains(action)
done = True
# sample reward using the corresponding reward distribution
reward = np.random.normal(self.reward_dist[action][0], self.reward_dist[action][1])
return 0, reward, done, {}
def reset(self):
return 0
def render(self, mode='human'):
pass
def close(self):
pass
| 28.692308 | 92 | 0.659517 | 147 | 1,119 | 4.897959 | 0.442177 | 0.033333 | 0.058333 | 0.05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015294 | 0.240393 | 1,119 | 38 | 93 | 29.447368 | 0.831765 | 0.125112 | 0 | 0.074074 | 0 | 0 | 0.022541 | 0 | 0 | 0 | 0 | 0 | 0.037037 | 1 | 0.222222 | false | 0.074074 | 0.185185 | 0.037037 | 0.592593 | 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 | 0 | 1 | 0 | 0 | 3 |
aa99aad1fdc79542ef3470565bb0f1459823e3f0 | 94 | py | Python | 3.3homework/py04.py | beautyShang/learn-python | ee133ba4b81281f5b69a96010c540efc711af289 | [
"Apache-2.0"
] | null | null | null | 3.3homework/py04.py | beautyShang/learn-python | ee133ba4b81281f5b69a96010c540efc711af289 | [
"Apache-2.0"
] | null | null | null | 3.3homework/py04.py | beautyShang/learn-python | ee133ba4b81281f5b69a96010c540efc711af289 | [
"Apache-2.0"
] | null | null | null | a = "Hello World"
b = a[3]
c = a[-2]
d = a[5::]
e = a[:5]
print(b)
print(c)
print(d)
print(e)
| 9.4 | 17 | 0.5 | 23 | 94 | 2.043478 | 0.478261 | 0.085106 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.054054 | 0.212766 | 94 | 9 | 18 | 10.444444 | 0.581081 | 0 | 0 | 0 | 0 | 0 | 0.117021 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.444444 | 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 | 0 | 0 | 0 | 1 | 0 | 3 |
aac7208cf43e5ab16cbe5f17432b6ef825d613f0 | 296 | py | Python | semseg/models/heads/__init__.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 196 | 2021-08-22T10:01:34.000Z | 2022-03-29T09:59:51.000Z | semseg/models/heads/__init__.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 21 | 2021-08-22T09:59:02.000Z | 2022-03-29T15:22:46.000Z | semseg/models/heads/__init__.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 36 | 2021-08-22T08:59:40.000Z | 2022-03-28T10:13:20.000Z | from .upernet import UPerHead
from .segformer import SegFormerHead
from .sfnet import SFHead
from .fpn import FPNHead
from .fapn import FaPNHead
from .fcn import FCNHead
from .condnet import CondHead
__all__ = ['UPerHead', 'SegFormerHead', 'SFHead', 'FPNHead', 'FaPNHead', 'FCNHead', 'CondHead'] | 32.888889 | 95 | 0.773649 | 36 | 296 | 6.25 | 0.472222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 296 | 9 | 95 | 32.888889 | 0.868726 | 0 | 0 | 0 | 0 | 0 | 0.191919 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.875 | 0 | 0.875 | 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 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
2a9fd6737b08cddb91b3c59b26c31580c9c4ae56 | 6,762 | py | Python | temboo/core/Library/Utilities/Dates/GetTimestamp.py | jordanemedlock/psychtruths | 52e09033ade9608bd5143129f8a1bfac22d634dd | [
"Apache-2.0"
] | 7 | 2016-03-07T02:07:21.000Z | 2022-01-21T02:22:41.000Z | temboo/core/Library/Utilities/Dates/GetTimestamp.py | jordanemedlock/psychtruths | 52e09033ade9608bd5143129f8a1bfac22d634dd | [
"Apache-2.0"
] | null | null | null | temboo/core/Library/Utilities/Dates/GetTimestamp.py | jordanemedlock/psychtruths | 52e09033ade9608bd5143129f8a1bfac22d634dd | [
"Apache-2.0"
] | 8 | 2016-06-14T06:01:11.000Z | 2020-04-22T09:21:44.000Z | # -*- coding: utf-8 -*-
###############################################################################
#
# GetTimestamp
# Returns the current date and time, expressed as seconds or milliseconds since January 1, 1970 (epoch time).
#
# Python versions 2.6, 2.7, 3.x
#
# Copyright 2014, Temboo Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
# either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
#
#
###############################################################################
from temboo.core.choreography import Choreography
from temboo.core.choreography import InputSet
from temboo.core.choreography import ResultSet
from temboo.core.choreography import ChoreographyExecution
import json
class GetTimestamp(Choreography):
def __init__(self, temboo_session):
"""
Create a new instance of the GetTimestamp Choreo. A TembooSession object, containing a valid
set of Temboo credentials, must be supplied.
"""
super(GetTimestamp, self).__init__(temboo_session, '/Library/Utilities/Dates/GetTimestamp')
def new_input_set(self):
return GetTimestampInputSet()
def _make_result_set(self, result, path):
return GetTimestampResultSet(result, path)
def _make_execution(self, session, exec_id, path):
return GetTimestampChoreographyExecution(session, exec_id, path)
class GetTimestampInputSet(InputSet):
"""
An InputSet with methods appropriate for specifying the inputs to the GetTimestamp
Choreo. The InputSet object is used to specify input parameters when executing this Choreo.
"""
def set_AddDays(self, value):
"""
Set the value of the AddDays input for this Choreo. ((optional, integer) Adds the specified number of days to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddDays', value)
def set_AddHours(self, value):
"""
Set the value of the AddHours input for this Choreo. ((optional, integer) Adds the specified number of hours to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddHours', value)
def set_AddMinutes(self, value):
"""
Set the value of the AddMinutes input for this Choreo. ((optional, integer) Adds the specified number of minutes to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddMinutes', value)
def set_AddMonths(self, value):
"""
Set the value of the AddMonths input for this Choreo. ((optional, integer) Adds the specified number of months to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddMonths', value)
def set_AddSeconds(self, value):
"""
Set the value of the AddSeconds input for this Choreo. ((optional, integer) Adds the specified number of seconds to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddSeconds', value)
def set_AddYears(self, value):
"""
Set the value of the AddYears input for this Choreo. ((optional, integer) Adds the specified number of years to the specified date serial number. A negative number will subtract.)
"""
super(GetTimestampInputSet, self)._set_input('AddYears', value)
def set_Granularity(self, value):
"""
Set the value of the Granularity input for this Choreo. ((optional, string) Set to "seconds" to return the number of seconds since the epoch. Defaults to "milliseconds".)
"""
super(GetTimestampInputSet, self)._set_input('Granularity', value)
def set_SetDay(self, value):
"""
Set the value of the SetDay input for this Choreo. ((optional, integer) Sets the day of month (1-31) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetDay', value)
def set_SetHour(self, value):
"""
Set the value of the SetHour input for this Choreo. ((optional, integer) Sets the hours (0-23) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetHour', value)
def set_SetMinute(self, value):
"""
Set the value of the SetMinute input for this Choreo. ((optional, integer) Sets the minutes (0-59) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetMinute', value)
def set_SetMonth(self, value):
"""
Set the value of the SetMonth input for this Choreo. ((optional, integer) Sets the month (1-12) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetMonth', value)
def set_SetSecond(self, value):
"""
Set the value of the SetSecond input for this Choreo. ((optional, integer) Sets the seconds (0-59) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetSecond', value)
def set_SetYear(self, value):
"""
Set the value of the SetYear input for this Choreo. ((optional, integer) Sets the year (such as 1989) of the specified date serial number.)
"""
super(GetTimestampInputSet, self)._set_input('SetYear', value)
class GetTimestampResultSet(ResultSet):
"""
A ResultSet with methods tailored to the values returned by the GetTimestamp Choreo.
The ResultSet object is used to retrieve the results of a Choreo execution.
"""
def getJSONFromString(self, str):
return json.loads(str)
def get_Timestamp(self):
"""
Retrieve the value for the "Timestamp" output from this Choreo execution. ((date) A the current timestamp, expressed as the number of seconds or milliseconds since January 1, 1970 (epoch time). The Granularity input is used to indicate seconds or milliseconds.)
"""
return self._output.get('Timestamp', None)
class GetTimestampChoreographyExecution(ChoreographyExecution):
def _make_result_set(self, response, path):
return GetTimestampResultSet(response, path)
| 47.286713 | 269 | 0.683673 | 844 | 6,762 | 5.402844 | 0.223934 | 0.023026 | 0.034211 | 0.042763 | 0.483333 | 0.432675 | 0.432675 | 0.361404 | 0.308772 | 0.288158 | 0 | 0.008048 | 0.209849 | 6,762 | 142 | 270 | 47.619718 | 0.845405 | 0.522626 | 0 | 0 | 0 | 0 | 0.058336 | 0.013925 | 0 | 0 | 0 | 0 | 0 | 1 | 0.408163 | false | 0 | 0.102041 | 0.102041 | 0.714286 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
2aa03f33d960179a0bb79d6a45adc86bd9f35336 | 76 | py | Python | finmath/__init__.py | renanamp/FinanceHub | 55b06577a431e7e53de17183444456d28a096bc1 | [
"MIT"
] | 1 | 2019-09-23T22:00:18.000Z | 2019-09-23T22:00:18.000Z | finmath/__init__.py | renanamp/FinanceHub | 55b06577a431e7e53de17183444456d28a096bc1 | [
"MIT"
] | null | null | null | finmath/__init__.py | renanamp/FinanceHub | 55b06577a431e7e53de17183444456d28a096bc1 | [
"MIT"
] | null | null | null | __all__ = ['SwapCurve']
from finmath.SwapCurve.SwapCurve import SwapCurve
| 15.2 | 49 | 0.789474 | 8 | 76 | 7 | 0.625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.118421 | 76 | 4 | 50 | 19 | 0.835821 | 0 | 0 | 0 | 0 | 0 | 0.12 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
2aa1d4e0efc50466a1cc284317c5ad15c071d1fc | 89 | py | Python | Mathematics/Exponentiation.py | charlie219/CSES-Solutions | e082380cbb3ad74eaa9a55f71a2f9df904477ef2 | [
"MIT"
] | null | null | null | Mathematics/Exponentiation.py | charlie219/CSES-Solutions | e082380cbb3ad74eaa9a55f71a2f9df904477ef2 | [
"MIT"
] | null | null | null | Mathematics/Exponentiation.py | charlie219/CSES-Solutions | e082380cbb3ad74eaa9a55f71a2f9df904477ef2 | [
"MIT"
] | null | null | null | n=int(input())
while n:
n-=1
print(pow(*map(int,input().split()),10**9+7))
| 14.833333 | 50 | 0.505618 | 16 | 89 | 2.8125 | 0.75 | 0.355556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.071429 | 0.213483 | 89 | 5 | 51 | 17.8 | 0.571429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
2aa7a1c3c3e3ec2b8d1afbc91b85d7cc5e637af1 | 301 | py | Python | ex036 - analisador triangulos.py | fblaz/Python-ex---curso-em-video | 794d1f7b9fa0803b168aaf973007906b66a02e2d | [
"MIT"
] | null | null | null | ex036 - analisador triangulos.py | fblaz/Python-ex---curso-em-video | 794d1f7b9fa0803b168aaf973007906b66a02e2d | [
"MIT"
] | null | null | null | ex036 - analisador triangulos.py | fblaz/Python-ex---curso-em-video | 794d1f7b9fa0803b168aaf973007906b66a02e2d | [
"MIT"
] | null | null | null | x = float(input('digite o segmento 1: '))
y = float(input('digite o segmento 2: '))
z = float(input('digite o segmento 3: '))
if x < y + z and y < x + z and z < x + y:
print(f'os segmentos {x, y, z} formam um Triangulo')
else:
print(f'os segmentos {x, y, z} NÃO formam um Triangulo')
| 33.444444 | 61 | 0.594684 | 55 | 301 | 3.254545 | 0.4 | 0.044693 | 0.268156 | 0.284916 | 0.642458 | 0.223464 | 0.223464 | 0 | 0 | 0 | 0 | 0.013216 | 0.245847 | 301 | 8 | 62 | 37.625 | 0.77533 | 0 | 0 | 0 | 0 | 0 | 0.515358 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.285714 | 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 | 0 | 0 | 3 |
2ab09eabfe924117e3d3a652ef2a8ea813d9dea2 | 1,115 | py | Python | client/channellog.py | heartsoso/Discline | e2cee4322d8e9ff3d269954ebc5ceb812473d79b | [
"WTFPL"
] | 535 | 2017-12-11T12:42:03.000Z | 2019-07-27T18:09:26.000Z | client/channellog.py | heartsoso/Discline | e2cee4322d8e9ff3d269954ebc5ceb812473d79b | [
"WTFPL"
] | 54 | 2017-12-11T13:39:39.000Z | 2019-07-20T23:14:31.000Z | client/channellog.py | heartsoso/Discline | e2cee4322d8e9ff3d269954ebc5ceb812473d79b | [
"WTFPL"
] | 33 | 2017-12-22T09:07:56.000Z | 2019-07-21T16:00:02.000Z | # Wrapper class to make dealing with logs easier
class ChannelLog():
__channel = ""
__logs = []
unread = False
mentioned_in = False
# the index of where to start printing the messages
__index = 0
def __init__(self, channel, logs):
self.__channel = channel
self.__logs = list(logs)
def get_server(self): return self.__channel.server
def get_channel(self): return self.__channel
def get_logs(self):
return self.__logs
def get_name(self):
return self.__channel.name
def get_server_name(self):
return self.__channel.server.name
def append(self, message):
self.__logs.append(message)
def index(self, message):
return self.__logs.index(message)
def insert(self, i, message):
self.__logs.insert(i, message)
def len(self):
return len(self.__logs)
def get_index(self):
return self.__index
def set_index(self, int):
self.__index = int
def inc_index(self, int):
self.__index += int
def dec_index(self, int):
self.__index -= int
| 22.3 | 55 | 0.632287 | 145 | 1,115 | 4.510345 | 0.268966 | 0.107034 | 0.12844 | 0.12844 | 0.246177 | 0.119266 | 0.082569 | 0 | 0 | 0 | 0 | 0.001235 | 0.273543 | 1,115 | 49 | 56 | 22.755102 | 0.806173 | 0.086099 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.424242 | false | 0 | 0 | 0.242424 | 0.787879 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
2ab99af9bb6c3090ad786980e8ef1ad5ab34acb2 | 1,093 | py | Python | game/opengl/interface.py | cassiersg/elec-2103 | f0152c81e8d808a1ab62c78e9324fb99b341638a | [
"Apache-2.0"
] | null | null | null | game/opengl/interface.py | cassiersg/elec-2103 | f0152c81e8d808a1ab62c78e9324fb99b341638a | [
"Apache-2.0"
] | null | null | null | game/opengl/interface.py | cassiersg/elec-2103 | f0152c81e8d808a1ab62c78e9324fb99b341638a | [
"Apache-2.0"
] | null | null | null |
import pygame
import cubes
import time
import font
import PIL
t0 = time.time()
grid = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [3, 3, 0, 0, 0, 3, 3, 0, 3, 3, 0, 0, 0, 3, 3], [3, 3, 0, 0, 0, 3, 3, 3, 3, 4, 0, 0, 0, 3, 3], [3, 3, 0, 0, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [3, 3, 4, 0, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]]
grid = bytearray(x for y in grid for x in y)
t1 = time.time()
cubes.cubes_init()
t2 = time.time()
cubes.draw_cubes(grid, cubes.n, cubes.m, 0, 1, 14, 1, 2, 20000, 0xffffff)
buf = bytearray(cubes.width*cubes.height*4)
cubes.cubes_image_export(buf)
mask = font.render_text('a')
font.blit_mask(buf, 800, 480, mask, 100, 200, 0xff0000)
t3 = time.time()
cubes.cubes_exit()
pygame.init()
s = pygame.display.set_mode((800, 480))
s.fill((0, 0, 0))
b = s.get_buffer()
t4 = time.time()
b.write(bytes(buf))
pygame.display.flip()
t5 = time.time()
print("dt gen_grid", t1-t0)
print("dt init_cubes", t2-t1)
print("dt draw&recover buf", t3-t2)
print("dt blit buf", t5-t4)
time.sleep(10)
| 28.763158 | 336 | 0.58097 | 246 | 1,093 | 2.536585 | 0.256098 | 0.205128 | 0.269231 | 0.326923 | 0.168269 | 0.168269 | 0.165064 | 0.165064 | 0.152244 | 0.113782 | 0 | 0.180383 | 0.188472 | 1,093 | 37 | 337 | 29.540541 | 0.523112 | 0 | 0 | 0 | 0 | 0 | 0.050366 | 0 | 0 | 0 | 0.014652 | 0 | 0 | 1 | 0 | false | 0 | 0.16129 | 0 | 0.16129 | 0.129032 | 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 | 0 | 0 | 3 |
2af316434f459e01963799b897bd4f6d92aa7dfb | 232 | py | Python | linguistics/document/Sentence.py | idin/mercurius | 48a4ed7843fb5d1946ef8051f23da7b32ab52ca3 | [
"MIT"
] | 7 | 2019-02-24T16:56:46.000Z | 2022-01-30T03:26:49.000Z | linguistics/document/Sentence.py | idin/mercurius | 48a4ed7843fb5d1946ef8051f23da7b32ab52ca3 | [
"MIT"
] | 1 | 2020-07-14T21:00:57.000Z | 2021-02-25T07:12:11.000Z | linguistics/document/Sentence.py | idin/linguistics | ab9568d81b225928beab353174fd97ccb0fe369c | [
"MIT"
] | null | null | null | from .TokenSpan import TokenSpan
class Sentence(TokenSpan):
def __init__(self, obj, document):
super().__init__(obj=obj, document=document)
@property
def id(self):
return self.document.id, 'sentence', self.start, self.end
| 21.090909 | 59 | 0.741379 | 31 | 232 | 5.290323 | 0.516129 | 0.134146 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.12931 | 232 | 10 | 60 | 23.2 | 0.811881 | 0 | 0 | 0 | 0 | 0 | 0.034483 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.142857 | 0.142857 | 0.714286 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
2af663664e00135c4ce97ed2eecd5d71b7b19c64 | 787 | py | Python | Section2/strings.py | joranbeasley/Getting-Started-with-Modern-Python | f9ac143fa5f23ea087b8af73f6665b58273b1697 | [
"MIT"
] | 8 | 2018-07-09T16:08:19.000Z | 2021-11-08T13:10:38.000Z | Section2/strings.py | joranbeasley/Getting-Started-with-Modern-Python | f9ac143fa5f23ea087b8af73f6665b58273b1697 | [
"MIT"
] | null | null | null | Section2/strings.py | joranbeasley/Getting-Started-with-Modern-Python | f9ac143fa5f23ea087b8af73f6665b58273b1697 | [
"MIT"
] | 7 | 2018-06-16T20:16:13.000Z | 2019-03-20T05:05:43.000Z | "{variable_name:format_description}"
print('{a:<10}|{a:^10}|{a:>10}'.format(a='test'))
print('{a:~<10}|{a:~^10}|{a:~>10}'.format(a='test'))
person = {"first":"Joran","last":"Beasley"}
print("{p[first]} {p[last]}".format(p=person))
data = range(100)
print("{d[0]}...{d[99]}".format(d=data))
print("normal:{num:d}".format(num=33))
print("normal:{num:f}".format(num=33))
print("binary:{num:b}".format(num=33))
print("binary:{num:08b}".format(num=33))
print("hex:{num:x}".format(num=33))
print("hex:0x{num:0<4x}".format(num=33))
print("octal:{num:o}".format(num=33))
print("{num:f}".format(num=22/7))
print("${num:0.2f}".format(num=22/7))
print("{num:.2e}".format(num=22/7))
print("{num:.1%}".format(num=22/7))
print("{num:g}".format(num=5.1200001))
variable=27
print(f"{variable}")
| 26.233333 | 52 | 0.620076 | 140 | 787 | 3.471429 | 0.3 | 0.222222 | 0.158436 | 0.230453 | 0.44856 | 0.37037 | 0.102881 | 0.102881 | 0.102881 | 0.102881 | 0 | 0.083665 | 0.043202 | 787 | 29 | 53 | 27.137931 | 0.561753 | 0.043202 | 0 | 0 | 0 | 0 | 0.380892 | 0.105732 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.809524 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
2af849686285c5c0193e91508af6e0ba66ab21b6 | 329 | py | Python | yt/fake-random-on-to-derived.py | lindsayad/python | 4b63a8b02de6a7c0caa7bb770f3f22366e066a7f | [
"MIT"
] | null | null | null | yt/fake-random-on-to-derived.py | lindsayad/python | 4b63a8b02de6a7c0caa7bb770f3f22366e066a7f | [
"MIT"
] | null | null | null | yt/fake-random-on-to-derived.py | lindsayad/python | 4b63a8b02de6a7c0caa7bb770f3f22366e066a7f | [
"MIT"
] | null | null | null | import yt
from yt.testing import fake_random_ds, assert_equal
def _test(field, data):
return data[('stream', 'velocity_x')]
ds = fake_random_ds()
ds.add_field(('stream, density'), function=_test, units='cm/s', force_override=True)
assert_equal(ds.all_data()[('stream', 'density')], ds.all_data()[('stream', 'velocity_x')])
| 32.9 | 91 | 0.717325 | 50 | 329 | 4.44 | 0.54 | 0.135135 | 0.108108 | 0.171171 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.094225 | 329 | 9 | 92 | 36.555556 | 0.744966 | 0 | 0 | 0 | 0 | 0 | 0.194529 | 0 | 0 | 0 | 0 | 0 | 0.285714 | 1 | 0.142857 | false | 0 | 0.285714 | 0.142857 | 0.571429 | 0 | 0 | 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 | 0 | 1 | 0 | 0 | 0 | 3 |
2af88c30ff1cf39c8df7fd5cec63d28d34537561 | 267 | py | Python | project_template/project_name/rentals/adminx.py | glasslion/django-sakila | 4a8b3419b649767e7d215590b2bb9824b6685edb | [
"MIT"
] | 5 | 2017-10-20T06:19:53.000Z | 2020-05-30T02:12:18.000Z | project_template/project_name/rentals/adminx.py | glasslion/django-sakila | 4a8b3419b649767e7d215590b2bb9824b6685edb | [
"MIT"
] | null | null | null | project_template/project_name/rentals/adminx.py | glasslion/django-sakila | 4a8b3419b649767e7d215590b2bb9824b6685edb | [
"MIT"
] | 3 | 2015-09-05T03:11:25.000Z | 2020-05-30T02:12:24.000Z | import xadmin
from .models import Customer, Inventory, Rental, Payment, Staff, Store
xadmin.site.register(Customer)
xadmin.site.register(Inventory)
xadmin.site.register(Rental)
xadmin.site.register(Payment)
xadmin.site.register(Staff)
xadmin.site.register(Store)
| 22.25 | 71 | 0.808989 | 35 | 267 | 6.171429 | 0.342857 | 0.277778 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.078652 | 267 | 11 | 72 | 24.272727 | 0.878049 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.25 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 1 | 1 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
6309cb248b1b826e1979d5aeac8da58bb5211bd7 | 887 | py | Python | codemaster/models/actors/npcs/__init__.py | japinol7/the-codemaster | 35f1c53a431b2fddf851c7fbf155cae968f1bad7 | [
"MIT"
] | null | null | null | codemaster/models/actors/npcs/__init__.py | japinol7/the-codemaster | 35f1c53a431b2fddf851c7fbf155cae968f1bad7 | [
"MIT"
] | null | null | null | codemaster/models/actors/npcs/__init__.py | japinol7/the-codemaster | 35f1c53a431b2fddf851c7fbf155cae968f1bad7 | [
"MIT"
] | null | null | null | """Package npcs."""
from codemaster.models.actors.npcs.bats import (
BatBlue,
BatLilac,
BatRed,
BatBlack,
)
from codemaster.models.actors.npcs.skulls import (
SkullGreen,
SkullBlue,
SkullYellow,
SkullRed,
)
from codemaster.models.actors.npcs.ghosts import (
GhostGreen,
GhostBlue,
GhostYellow,
GhostRed,
)
from codemaster.models.actors.npcs.vampires import (
VampireMale,
VampireFemale,
)
from codemaster.models.actors.npcs.demons import (
DemonMale,
)
from codemaster.models.actors.npcs.wolfmen import (
WolfManMale,
)
from codemaster.models.actors.npcs.terminator_eyes import (
TerminatorEyeGreen,
TerminatorEyeBlue,
TerminatorEyeYellow,
TerminatorEyeRed,
)
from codemaster.models.actors.npcs.snakes import (
SnakeGreen,
SnakeBlue,
SnakeYellow,
SnakeRed,
)
| 21.119048 | 59 | 0.692221 | 83 | 887 | 7.385542 | 0.481928 | 0.182708 | 0.261011 | 0.339315 | 0.391517 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.218715 | 887 | 41 | 60 | 21.634146 | 0.88456 | 0.014656 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.2 | 0 | 0.2 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
630b8bdc1ca9842989623aa8a26806eb73524765 | 221 | py | Python | healthgen/data_access/preprocessing/base_processor.py | simonbing/HealthGen | d5886a5a41dc36c6a70dece3dba3c60a90bf1fdd | [
"MIT"
] | null | null | null | healthgen/data_access/preprocessing/base_processor.py | simonbing/HealthGen | d5886a5a41dc36c6a70dece3dba3c60a90bf1fdd | [
"MIT"
] | null | null | null | healthgen/data_access/preprocessing/base_processor.py | simonbing/HealthGen | d5886a5a41dc36c6a70dece3dba3c60a90bf1fdd | [
"MIT"
] | null | null | null | """
2021 Simon Bing, ETHZ, MPI IS
"""
import numpy as np
from absl import flags
class BaseProcessor(object):
def __init__(self):
self.name = None
def transform(self, x):
raise NotImplementedError | 18.416667 | 33 | 0.669683 | 29 | 221 | 4.965517 | 0.862069 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02381 | 0.239819 | 221 | 12 | 33 | 18.416667 | 0.833333 | 0.131222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.285714 | 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 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
63232cbcd99d62acdd24af24172c2125ae6ba020 | 58 | py | Python | Types/Enums/Preprocessing_Mode.py | SBCV/PythonUtility | 0062e1e60dc151776b963d13bc4c1763eb90d333 | [
"MIT"
] | 2 | 2019-02-20T14:56:13.000Z | 2020-05-19T12:31:53.000Z | Types/Enums/Preprocessing_Mode.py | SBCV/PythonUtility | 0062e1e60dc151776b963d13bc4c1763eb90d333 | [
"MIT"
] | null | null | null | Types/Enums/Preprocessing_Mode.py | SBCV/PythonUtility | 0062e1e60dc151776b963d13bc4c1763eb90d333 | [
"MIT"
] | 1 | 2021-01-07T08:32:07.000Z | 2021-01-07T08:32:07.000Z | class PreprocessingMode:
VIDEO = 1
FOLDER_LIST = 2 | 19.333333 | 24 | 0.689655 | 7 | 58 | 5.571429 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.046512 | 0.258621 | 58 | 3 | 25 | 19.333333 | 0.860465 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
63255499e65964a28a12c77f2be3fdd224d73d23 | 8,565 | py | Python | tests/test_all.py | waadnakhleh/pythonformatter | 5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f | [
"MIT"
] | null | null | null | tests/test_all.py | waadnakhleh/pythonformatter | 5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f | [
"MIT"
] | 19 | 2020-12-28T17:17:12.000Z | 2021-12-22T20:44:42.000Z | tests/test_all.py | waadnakhleh/pythonformatter | 5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f | [
"MIT"
] | 1 | 2021-03-20T17:41:14.000Z | 2021-03-20T17:41:14.000Z | import filecmp
import os
import pathlib
import pytest
from lib import _rewrite
from _exceptions import NoSolutionError
import main
def confirm(output):
compare_to = "modified_file.py"
try:
assert filecmp.cmp(output, compare_to)
except AssertionError as e:
with open(compare_to) as f:
if not os.path.isdir("logs"):
os.mkdir("logs")
lines = f.readlines()
lines = [l for l in lines]
with open(
f"logs/log_{output[:len(output)-len('/output.py')]}.py", "w"
) as f1:
f1.writelines(lines)
raise e
finally:
open(compare_to, "w").close() # Empty file
def make_test(
input_file,
output_file,
max_line=88,
space_between_arguments=False,
multiple_imports=False,
vertical_definition_lines=2,
nested_lines=1,
):
input_file = pathlib.Path(__file__).parent.absolute().joinpath(input_file)
output_file = pathlib.Path(__file__).parent.absolute().joinpath(output_file)
args = (
"--target-file",
input_file,
"--max-line",
max_line,
"--vertical-definition-lines",
vertical_definition_lines,
"--nested-lines",
nested_lines,
)
if space_between_arguments:
args = args + ("--space-between-arguments",)
if multiple_imports:
args = args + ("--multiple-imports",)
main.main(*args)
confirm(output_file)
_rewrite.file = open("modified_file.py", "a")
def test_syntax_error():
with pytest.raises(SyntaxError):
input_file = "syntax_error/file.py"
input_file = pathlib.Path(__file__).parent.absolute().joinpath(input_file)
main.main("--target-file", input_file)
def test_import():
input_file, output_file = "test_import/input.py", "test_import/output.py"
make_test(input_file, output_file)
def test_from_import():
input_file, output_file = "test_from_import/input.py", "test_from_import/output.py"
make_test(input_file, output_file)
def test_constant():
# TODO: fix bug, binary and hex values change to decimal.
input_file, output_file = "test_constant/input.py", "test_constant/output.py"
make_test(input_file, output_file)
def test_unaryop():
input_file, output_file = "test_unaryop/input.py", "test_unaryop/output.py"
make_test(input_file, output_file)
def test_name():
input_file, output_file = "test_name/input.py", "test_name/output.py"
make_test(input_file, output_file)
def test_boolop():
input_file, output_file = "test_boolop/input.py", "test_boolop/output.py"
make_test(input_file, output_file)
def test_list():
input_file, output_file = "test_list/input.py", "test_list/output.py"
make_test(input_file, output_file)
def test_tuple():
input_file, output_file = "test_tuple/input.py", "test_tuple/output.py"
make_test(input_file, output_file)
def test_pass():
input_file, output_file = "test_pass/input.py", "test_pass/output.py"
make_test(input_file, output_file)
def test_assignment():
input_file, output_file = "test_assignment/input.py", "test_assignment/output.py"
make_test(input_file, output_file)
def test_binop():
input_file, output_file = "test_binop/input.py", "test_binop/output.py"
make_test(input_file, output_file)
def test_namedexpr():
input_file, output_file = "test_namedexpr/input.py", "test_namedexpr/output.py"
make_test(input_file, output_file)
def test_compare():
input_file, output_file = "test_compare/input.py", "test_compare/output.py"
make_test(input_file, output_file)
def test_assert():
input_file, output_file = "test_assert/input.py", "test_assert/output.py"
make_test(input_file, output_file)
def test_if():
input_file, output_file = "test_if/input.py", "test_if/output.py"
make_test(input_file, output_file)
def test_while():
input_file, output_file = "test_while/input.py", "test_while/output.py"
make_test(input_file, output_file)
def test_break():
input_file, output_file = "test_break/input.py", "test_break/output.py"
make_test(input_file, output_file)
def test_continue():
input_file, output_file = "test_continue/input.py", "test_continue/output.py"
make_test(input_file, output_file)
def test_return():
input_file, output_file = "test_return/input.py", "test_return/output.py"
make_test(input_file, output_file)
def test_call():
input_file, output_file = "test_call/input.py", "test_call/output.py"
make_test(input_file, output_file)
def test_functiondef():
input_file, output_file = "test_functiondef/input.py", "test_functiondef/output.py"
make_test(input_file, output_file)
def test_for():
input_file, output_file = "test_for/input.py", "test_for/output.py"
make_test(input_file, output_file)
def test_augassign():
input_file, output_file = "test_augassign/input.py", "test_augassign/output.py"
make_test(input_file, output_file)
def test_classdef():
input_file, output_file = "test_classdef/input.py", "test_classdef/output.py"
make_test(input_file, output_file)
def test_with():
input_file, output_file = "test_with/input.py", "test_with/output.py"
make_test(input_file, output_file)
def test_delete():
input_file, output_file = "test_delete/input.py", "test_delete/output.py"
make_test(input_file, output_file)
def test_attribute():
input_file, output_file = "test_attribute/input.py", "test_attribute/output.py"
make_test(input_file, output_file)
def test_try():
input_file, output_file = "test_try/input.py", "test_try/output.py"
make_test(input_file, output_file)
def test_raise():
input_file, output_file = "test_raise/input.py", "test_raise/output.py"
make_test(input_file, output_file)
def test_global():
input_file, output_file = "test_global/input.py", "test_global/output.py"
make_test(input_file, output_file)
def test_nonlocal():
input_file, output_file = "test_nonlocal/input.py", "test_nonlocal/output.py"
make_test(input_file, output_file)
def test_subscript():
input_file, output_file = "test_subscript/input.py", "test_subscript/output.py"
make_test(input_file, output_file)
def test_listcomp():
input_file, output_file = "test_listcomp/input.py", "test_listcomp/output.py"
make_test(input_file, output_file)
def test_docstring():
input_file, output_file = "test_docstring/input.py", "test_docstring/output.py"
make_test(input_file, output_file)
def test_ifexpr():
input_file, output_file = "test_ifexpr/input.py", "test_ifexpr/output.py"
make_test(input_file, output_file)
def test_dict():
input_file, output_file = "test_dict/input.py", "test_dict/output.py"
make_test(input_file, output_file)
def test_general():
input_file, output_file = "test_general/input.py", "test_general/output.py"
make_test(input_file, output_file)
def test_command_line_args():
input_file, output_file = (
"test_command_line_args/input.py",
"test_command_line_args/output.py",
)
make_test(input_file, output_file, max_line=100)
def test_bad_arguments():
with pytest.raises(ValueError, match="unknown argument --unsupported-argument"):
main.main("--target-file", "input_file", "--unsupported-argument", "")
def test_bad_max_line_length():
input_file, output_file = (
"test_command_line_args/input.py",
"test_command_line_args/output.py",
)
with pytest.raises(NoSolutionError, match="check maximum line length"):
make_test(input_file, output_file, max_line=30)
def test_space_arguments():
input_file, output_file = (
"test_space_arguments/input.py",
"test_space_arguments/output.py",
)
make_test(input_file, output_file, max_line=100, space_between_arguments=True)
def test_multiple_imports():
input_file, output_file = (
"test_multiple_imports/input.py",
"test_multiple_imports/output.py",
)
make_test(input_file, output_file, multiple_imports=True)
def test_vertical_definition_lines():
input_file, output_file = (
"test_vertical_definition_lines/input.py",
"test_vertical_definition_lines/output.py",
)
make_test(input_file, output_file, vertical_definition_lines=3)
def test_nested_lines():
input_file, output_file = (
"test_nested_lines/input.py",
"test_nested_lines/output.py",
)
make_test(input_file, output_file, nested_lines=3)
| 28.174342 | 87 | 0.709165 | 1,208 | 8,565 | 4.664735 | 0.105132 | 0.15173 | 0.23425 | 0.296717 | 0.569654 | 0.407098 | 0.377285 | 0.370009 | 0.35173 | 0.337533 | 0 | 0.002255 | 0.171629 | 8,565 | 303 | 88 | 28.267327 | 0.791966 | 0.007706 | 0 | 0.245192 | 0 | 0 | 0.267067 | 0.166314 | 0 | 0 | 0 | 0.0033 | 0.019231 | 1 | 0.225962 | false | 0.009615 | 0.086538 | 0 | 0.3125 | 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 | 0 | 0 | 0 | 3 |
6326c7a8a208e98565f72a4a6b233c7a564c35a3 | 123 | py | Python | cride/rides/apps.py | LhernerRemon/Rider | 30783cf58513698d23730f5fa477dfeddda8ee6b | [
"MIT"
] | null | null | null | cride/rides/apps.py | LhernerRemon/Rider | 30783cf58513698d23730f5fa477dfeddda8ee6b | [
"MIT"
] | null | null | null | cride/rides/apps.py | LhernerRemon/Rider | 30783cf58513698d23730f5fa477dfeddda8ee6b | [
"MIT"
] | null | null | null | #Django
from django.apps import AppConfig
class RidesAppConfig(AppConfig):
name="cride.rides"
verbose_name="Rides" | 20.5 | 33 | 0.764228 | 15 | 123 | 6.2 | 0.733333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.138211 | 123 | 6 | 34 | 20.5 | 0.877358 | 0.04878 | 0 | 0 | 0 | 0 | 0.136752 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
2d5e4f9e64b8f31e4730fca32c36434095cee023 | 15,971 | py | Python | models.py | perSEVERE-5962/SEVEREscout | f2191bdf52a0d7302666ce38fe3cc31f64b0216a | [
"MIT"
] | null | null | null | models.py | perSEVERE-5962/SEVEREscout | f2191bdf52a0d7302666ce38fe3cc31f64b0216a | [
"MIT"
] | 2 | 2021-02-08T20:42:33.000Z | 2021-04-30T21:08:27.000Z | models.py | perSEVERE-5962/SEVEREscout | f2191bdf52a0d7302666ce38fe3cc31f64b0216a | [
"MIT"
] | 1 | 2020-02-22T17:25:03.000Z | 2020-02-22T17:25:03.000Z | from app import db
from sqlalchemy.sql import func
from sqlalchemy.dialects.postgresql import ARRAY
class PitReport(db.Model):
__tablename__ = "pit_report"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
# team relationship
team_id = db.Column(db.Integer, db.ForeignKey("team.id"), nullable=False)
# metadata
event = db.Column(db.String)
time_created = db.Column(db.DateTime(timezone=True), server_default=func.now())
time_updated = db.Column(db.DateTime(timezone=True), onupdate=func.now())
created_by = db.Column(db.String)
# drivetrain
drivetrain_type = db.Column(db.String)
drivetrain_type_other = db.Column(db.String)
wheel_type = db.Column((ARRAY(db.String)))
wheel_type_other = db.Column(db.String)
wheel_number = db.Column(db.Integer)
motor_type = db.Column((ARRAY(db.String)))
motor_type_other = db.Column(db.String)
motor_number = db.Column(db.String)
drivetrain_notes = db.Column(db.String)
# physical characteristics
weight = db.Column(db.Float)
height = db.Column(db.Float)
width = db.Column(db.Float)
length = db.Column(db.Float)
speed = db.Column(db.Float)
# auto
auto_move = db.Column(db.Boolean)
auto_score_bottom = db.Column(db.Boolean)
auto_score_outer = db.Column(db.Boolean)
auto_score_inner = db.Column(db.Boolean)
auto_collect_balls = db.Column(db.Boolean)
auto_consistency = db.Column(db.Integer)
auto_prefered_position = db.Column((ARRAY(db.String)))
# teleop
teleop_score_bottom = db.Column(db.Boolean)
teleop_score_outer = db.Column(db.Boolean)
teleop_score_inner = db.Column(db.Boolean)
teleop_consistency = db.Column(db.Integer)
teleop_ball_capacity = db.Column(db.Integer)
teleop_prefered_position = db.Column(db.String)
# control panel
control_panel_rotation = db.Column(db.Boolean)
control_panel_position = db.Column(db.Boolean)
# hang
hang_able = db.Column(db.Boolean)
hang_level = db.Column(db.Boolean)
hang_prefered_position = db.Column((ARRAY(db.String)))
hang_consistency = db.Column(db.Integer)
hang_time = db.Column(db.Float)
hang_active = db.Column(db.Boolean)
# personnel
personnel_honesty = db.Column(db.Integer)
personnel_answering = db.Column(db.Integer)
personnel_notes = db.Column(db.String)
# notes
notes = db.Column(db.String)
class Match(db.Model):
__tablename__ = "match"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
match = db.Column(db.Integer)
event = db.Column(db.String)
match_reports = db.relationship("MatchReport", backref="match", lazy=True)
class MatchReport(db.Model):
__tablename__ = "match_report"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
# match relationship
match_id = db.Column(db.Integer, db.ForeignKey("match.id"), nullable=False)
# team relationship
team_id = db.Column(db.Integer, db.ForeignKey("team.id"), nullable=False)
# metadata
alliance = db.Column(db.String)
station = db.Column(db.Integer)
time_created = db.Column(db.DateTime(timezone=True), server_default=func.now())
time_updated = db.Column(db.DateTime(timezone=True), onupdate=func.now())
created_by = db.Column(db.String)
# auto
auto_move = db.Column(db.Boolean)
auto_score_bottom = db.Column(db.Integer)
auto_score_upper = db.Column(db.Integer)
auto_collect_balls = db.Column(db.Boolean)
auto_points = db.Column(db.Integer)
# teleop
teleop_score_bottom = db.Column(db.Integer)
teleop_score_upper = db.Column(db.Integer)
teleop_points = db.Column(db.Integer)
teleop_attempts = db.Column (db.Integer)
teleop_success_rate = db.Column(db.Float)
# control panel
control_panel_rotation = db.Column(db.Boolean)
control_panel_position = db.Column(db.Boolean)
control_panel_points = db.Column(db.Integer)
# hang
hang_able = db.Column(db.Boolean)
hang_level = db.Column(db.Boolean)
hang_position = db.Column(db.String)
hang_active = db.Column(db.Boolean)
hang_points = db.Column(db.Integer)
# defense
defense_performance = db.Column(db.Integer)
defense_penalties = db.Column(db.Integer)
# comms
connection_issues = db.Column(db.Boolean)
brownouts = db.Column(db.Boolean)
emergency_stop = db.Column(db.Boolean)
#notes
notes = db.Column(db.String)
class Bookmark(db.Model):
__tablename__ = "bookmark"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
team_number = db.Column(db.Integer)
time_created = db.Column(db.DateTime(timezone=True), server_default=func.now())
user_id = db.Column(db.Integer, db.ForeignKey("user.id"), nullable=False)
class User(db.Model):
__tablename__ = "user"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
user_id = db.Column(db.String)
first_name = db.Column(db.String)
last_name = db.Column(db.String)
bookmarks = db.relationship("Bookmark", backref="user", lazy=True)
alliance_suggestions = db.relationship("AllianceSuggestion", backref="user", lazy=True)
team_photos = db.relationship("TeamPhoto", backref="user", lazy=True)
class AllianceSuggestion(db.Model):
__tablename__ = "alliance_suggestion"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
pick_number = db.Column(db.Integer)
team_number = db.Column(db.Integer)
time_created = db.Column(db.DateTime(timezone=True), server_default=func.now())
already_selected = db.Column(db.Boolean, default=False)
accepted = db.Column(db.Boolean, default=False)
denied = db.Column(db.Boolean, default = False)
user_id = db.Column(db.Integer, db.ForeignKey("user.id"), nullable=False)
team_id = db.Column(db.Integer, db.ForeignKey("team.id"), nullable=False)
class Team(db.Model):
__tablename__ = "team"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
team_number = db.Column(db.Integer)
team_stats = db.relationship("TeamStats", backref="team", lazy=True)
alliance_suggestions = db.relationship("AllianceSuggestion", backref="team", lazy=True)
pit_reports = db.relationship("PitReport", backref="team", lazy=True)
match_reports = db.relationship("MatchReport", backref="team", lazy=True)
team_photos = db.relationship("TeamPhoto", backref="team", lazy=True)
class TeamPhoto(db.Model):
__tablename__ = "team_photo"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
team_id = db.Column(db.Integer, db.ForeignKey("team.id"), nullable=False)
user_id = db.Column(db.Integer, db.ForeignKey("user.id"), nullable=False)
url = db.Column(db.String)
height = db.Column(db.Integer)
width = db.Column(db.Integer)
public_id = db.Column(db.String)
format = db.Column(db.String)
version = db.Column(db.String)
class TeamStats(db.Model):
__tablename__ = "team_stats"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
team_id = db.Column(db.Integer, db.ForeignKey("team.id"), nullable=False)
auto_points = db.Column(db.Integer)
auto_points_avg = db.Column(db.Float)
teleop_points = db.Column(db.Integer)
teleop_points_avg = db.Column(db.Float)
teleop_score_bottom = db.Column(db.Integer)
teleop_score_bottom_avg = db.Column(db.Float)
teleop_score_upper = db.Column(db.Integer)
teleop_score_upper_avg = db.Column(db.Float)
teleop_successful_attempts = db.Column(db.Integer)
teleop_attempts = db.Column(db.Integer)
teleop_success_rate = db.Column(db.Float)
control_panel_points = db.Column(db.Integer)
control_panel_points_avg = db.Column(db.Float)
hang_points = db.Column(db.Integer)
hang_points_avg = db.Column(db.Float)
hang_able = db.Column(db.Integer)
hang_success_rate = db.Column(db.Float)
defense_penalties = db.Column(db.Integer)
defense_penalties_avg = db.Column(db.Float)
connection_issues = db.Column(db.Integer)
connection_issues_avg = db.Column(db.Float)
brownouts = db.Column(db.Integer)
brownouts_avg = db.Column(db.Float)
emergency_stops = db.Column(db.Integer)
emergency_stops_avg = db.Column(db.Float)
num_matches = db.Column(db.Integer)
"""
class TeamPit(db.Model):
__tablname__ = "team_pit"
id = db.Column(db.Integer, primary_key=True)
team_number = db.Column(db.Integer)
auto = db.relationship("Auto", back_populates="team_pit")
drivetrain_configuration_id = db.Column(db.Integer,
db.ForeignKey("drivetrain_configuration.id"))
drivetrain_configuration = db.relationship("drivetrain_configuration", backref="team_pit")
physical_characteristics_id = db.Column(db.Integer,
db.ForeignKey("physical_characteristics.id"))
physical_characteristics = db.relationship("physical_characteristics", backref="team_pit")
teleop_id = db.Column(db.Integer, db.ForeignKey("teleop.id"))
teleop = db.relationship("teleop", backref="team_pit")
hang_id = db.Column(db.Integer, db.ForeignKey("hang.id"))
hang = db.relationship("hang", backref="team_pit")
personnel_id = db.Column(db.Integer, db.ForeignKey("personnel.id"))
personnel = db.relationship("personnel", backref="team_pit")
control_panel_id = db.Column(db.Integer, db.ForeignKey("control_panel.id"))
control_panel = db.relationship("control_panel", backref="team_pit")
event_id = db.Column(db.Integer, db.ForeignKey("event.id"))
event = db.relationship("event", backref="team_pit")
notes = db.Column(db.String)
def __repr__(self):
return(self.id)
class DrivetrainType(db.Model):
__tablename__ = "drivetrain_type"
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String)
def __repr__(self):
return(self.id)
class WheelType(db.Model):
__tablename__ = "wheel_type"
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String)
def __repr__(self):
return(self.id)
class MotorType(db.Model):
__tablename__ = "motor_type"
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String)
def __repr__(self):
return(self.id)
class DrivetrainConfiguration(db.Model):
__tablename__ = "drivetrain_configuration"
id = db.Column(db.Integer, primary_key=True)
drivetrain_type_id = db.Column(db.Integer, db.ForeignKey("drivetrain_type.id"))
drivetrain_type = db.relationship("drivetrain_type")
wheel_type_id = db.Column(db.Integer, db.ForeignKey("wheel_type.id"))
wheel_type = db.relationship("wheel_type")
motor_type_id = db.Column(db.Integer, db.ForeignKey("motor_type.id"))
motor_type = db.relationship("motor_type")
notes = db.Column(db.String)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class PhysicalCharacteristics(db.Model):
__tablename__ = "physical_characteristics"
id = db.Column(db.Integer, primary_key=True)
weight = db.Column(db.Float)
height = db.Column(db.Float)
width = db.Column(db.Float)
length = db.Column(db.Float)
speed = db.Column(db.Float)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class Auto(db.Model):
__tablename__ = "auto"
id = db.Column(db.Integer, primary_key=True)
move = db.Column(db.Boolean)
score_bottom = db.Column(db.Boolean)
score_outer = db.Column(db.Boolean)
score_inner = db.Column(db.Boolean)
collect_balls = db.Column(db.Boolean)
consistency = db.Column(db.Integer)
starting_position = db.Column(db.String)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
team_pit = db.relationship("Parent", back_populates="children")
def __repr__(self):
return(self.id)
class Teleop(db.Model):
__tablename__ = "teleop"
id = db.Column(db.Integer, primary_key=True)
score_bottom = db.Column(db.Boolean)
score_outer = db.Column(db.Boolean)
score_inner = db.Column(db.Boolean)
consistency = db.Column(db.Integer)
shooting_position db.Column(db.String)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class ControlPanel(db.Model):
__tablename__ = "control_panel"
id = db.Column(db.Integer, primary_key=True)
rotation = db.Column(db.Boolean)
postition = db.Column(db.Boolean)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class Hang(db.Model):
__tablename__ = "hang"
id = db.Column(db.Integer, primary_key=True)
able = db.Column(db.Boolean)
level = db.Column(db.Boolean)
prefered_position = db.Column(db.String)
consistency = db.Column(db.Integer)
time = db.Column(db.Float)
active = db.Column(db.Boolean)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class Event(db.Model):
__tablename__ = "event"
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class Personnel(db.Model):
__tablename__ = "personnel"
id = db.Column(db.Integer, primary_key=True)
honest = db.Column(db.Integer)
answer = db.Column(db.Integer)
notes = db.Column(db.String)
team_pit_id = db.Column(db.Integer, db.ForeignKey("team_pit.id"))
def __repr__(self):
return(self.id)
class Match(db.Model):
__tablename__ = "match"
id = db.Column(db.Integer, primary_key=True)
auto = db.Column(db.Integer,
db.ForeignKey("drivetrain_configuration.id"))
drivetrain_configuration = db.relationship("drivetrain_configuration", backref="team_pit")
notes = db.Column(db.String)
class TeamMatch(db.Model):
__tablename__ = "team_match"
id = db.Column(db.Integer, primary_key=True)
team_number = db.Column(db.Integer)
notes = db.Column(db.String)
class Alliance(db.Model):
__tablename__ = "alliance"
id = db.Column(db.Integer, primary_key=True)
color = db.Column(db.String)
class Station(db.Model):
__tablename__ = "station"
id = db.Column(db.Integer, primary_key=True)
number = db.Column(db.Integer)
class AutoPoints(db.Model):
__tablename__ = "auto_points"
id = db.Column(db.Integer, primary_key=True)
move = db.Column(db.Boolean)
score_bottom = db.Column(db.Integer)
score_upper = db.Column(db.Integer)
collect_balls = db.Column(db.Boolean)
points = db.Column(db.Integer)
class TeleopPoints(db.Model):
__tablename__ = "auto_points"
id = db.Column(db.Integer, primary_key=True)
score_bottom = db.Column(db.Integer)
score_upper = db.Column(db.Integer)
points = db.Column(db.Integer)
attempts = db.Column (db.Integer)
class ControlPanelPoints(db.Model):
__tablename__ = "control_panel_points"
id = db.Column(db.Integer, primary_key=True)
rotation = db.Column(db.Boolean)
position = db.Column(db.Boolean)
class HangPoints(db.Model):
__tablename__ = "hang_points"
id = db.Column(db.Integer, primary_key=True)
able = db.Column(db.Boolean)
level = db.Column(db.Boolean)
position = db.Column(db.String)
active = db.Column(db.Boolean)
class Defense(db.Model):
__tablename__ = "defense"
id = db.Column(db.Integer, primary_key=True)
performance = db.Column(db.Integer)
penalties = db.Column(db.Integer)
class Comms(db.Model):
__tablename__ = "comms"
id = db.Column(db.Integer, primary_key=True)
connection_issues = db.Column(db.Integer)
brownouts = db.Column(db.Integer)
emergency_stop = db.Column(db.Integer)
""" | 38.391827 | 94 | 0.700019 | 2,180 | 15,971 | 4.911009 | 0.072477 | 0.177097 | 0.217635 | 0.188959 | 0.79731 | 0.691575 | 0.597702 | 0.516533 | 0.442462 | 0.4221 | 0 | 0 | 0.168994 | 15,971 | 416 | 95 | 38.391827 | 0.806661 | 0.012836 | 0 | 0.385542 | 0 | 0 | 0.035312 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.018072 | 0 | 1 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
2d602eee31f100a10c2cbb071beeed48aa7e25eb | 323 | py | Python | sources/dashboard/application/dataclasses.py | variasov/classic_demo_low_difficulty | 3a07743a8e78ac35aa3f98cfa9c138dbcdef0494 | [
"MIT"
] | 5 | 2021-10-08T08:33:02.000Z | 2022-03-31T20:11:11.000Z | sources/dashboard/application/dataclasses.py | variasov/classic_demo_low_difficulty | 3a07743a8e78ac35aa3f98cfa9c138dbcdef0494 | [
"MIT"
] | null | null | null | sources/dashboard/application/dataclasses.py | variasov/classic_demo_low_difficulty | 3a07743a8e78ac35aa3f98cfa9c138dbcdef0494 | [
"MIT"
] | null | null | null | from dataclasses import dataclass
from datetime import date
@dataclass
class DayOrdersInfo:
report_date: date
total_orders: int
total_lines: int
total_cost: float
@dataclass
class PeriodOrdersInfo:
start_date: date
end_date: date
total_orders: int
total_lines: int
total_cost: float
| 16.15 | 33 | 0.736842 | 41 | 323 | 5.585366 | 0.439024 | 0.139738 | 0.113537 | 0.165939 | 0.427948 | 0.427948 | 0.427948 | 0.427948 | 0.427948 | 0.427948 | 0 | 0 | 0.22291 | 323 | 19 | 34 | 17 | 0.912351 | 0 | 0 | 0.533333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.133333 | 0 | 0.866667 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
2d7ce3e4150423d1eded4ee73951d019d237148e | 62 | py | Python | code/learn-AI/pandas/A_Series/create/D_create_from_number.py | lsieun/learn-AI | 0a164bc2e6317de3aa03c747c0e6f15d93e7f49a | [
"Apache-2.0"
] | 1 | 2019-03-27T23:22:44.000Z | 2019-03-27T23:22:44.000Z | code/learn-AI/pandas/A_Series/create/D_create_from_number.py | lsieun/learn-AI | 0a164bc2e6317de3aa03c747c0e6f15d93e7f49a | [
"Apache-2.0"
] | null | null | null | code/learn-AI/pandas/A_Series/create/D_create_from_number.py | lsieun/learn-AI | 0a164bc2e6317de3aa03c747c0e6f15d93e7f49a | [
"Apache-2.0"
] | null | null | null | import pandas as pd
s = pd.Series(5,index=[0,1,3,3])
print(s) | 15.5 | 32 | 0.66129 | 15 | 62 | 2.733333 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.092593 | 0.129032 | 62 | 4 | 33 | 15.5 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0.333333 | 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 | 0 | 0 | 0 | 3 |
2d984dc3cb6885ecd9e043074f12f3165a197cba | 196 | py | Python | pkg/Python27/Lib/site-packages/clint/textui/__init__.py | jkolokotronis/ds_mod_tools | d9fd4def34f6adfd0e2b176d0a9bf2a3dfd43f93 | [
"MIT"
] | null | null | null | pkg/Python27/Lib/site-packages/clint/textui/__init__.py | jkolokotronis/ds_mod_tools | d9fd4def34f6adfd0e2b176d0a9bf2a3dfd43f93 | [
"MIT"
] | null | null | null | pkg/Python27/Lib/site-packages/clint/textui/__init__.py | jkolokotronis/ds_mod_tools | d9fd4def34f6adfd0e2b176d0a9bf2a3dfd43f93 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
clint.textui
~~~~~~~~~~~~
This module provides the text output helper system.
"""
from . import colored
from . import progress
from .core import *
| 12.25 | 52 | 0.576531 | 22 | 196 | 5.136364 | 0.818182 | 0.176991 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006849 | 0.255102 | 196 | 15 | 53 | 13.066667 | 0.767123 | 0.515306 | 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 | 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 | 3 |
2dc44b4a3b103092ec880c849c7d56eb6ea5bb75 | 12,499 | py | Python | nitrogen/pes/library/h2o2_mk2012_ad.py | bchangala/nitrogen | 94f8828a51aa536fe93fe6a8bdd8da04eb6fdce8 | [
"MIT"
] | 7 | 2021-02-09T04:09:58.000Z | 2022-03-13T20:47:27.000Z | nitrogen/pes/library/h2o2_mk2012_ad.py | bchangala/nitrogen | 94f8828a51aa536fe93fe6a8bdd8da04eb6fdce8 | [
"MIT"
] | null | null | null | nitrogen/pes/library/h2o2_mk2012_ad.py | bchangala/nitrogen | 94f8828a51aa536fe93fe6a8bdd8da04eb6fdce8 | [
"MIT"
] | 1 | 2021-10-01T12:42:35.000Z | 2021-10-01T12:42:35.000Z | """
h2o2_mk2012_ad.py
Hydrogen peroxide, H2O2, ground state surface from
Ref [1]_. The coefficients are available from the references
supplementary information as the 'adiabatic PES', which
corresponds to the "V+C+R+H+D" results.
The surface is implemented in internal coordinates.
X1 ... O1 -- H1 bond length (Angstroms)
X2 ... O2 -- H2 bond length ( " " )
X3 ... O1 -- O2 bond length ( " " )
X4 ... O2-O1-H1 bond angle (degrees)
X5 ... O1-O2-H2 bond angle ( " " )
X6 ... dihedral angle ( " " )
References
----------
.. [1] P. Malyszek and J. Koput. J. Comp. Chem. 34, 337-344 (2013).
https://doi.org/10.1002/jcc.23137
"""
import nitrogen as n2
import nitrogen.autodiff.forward as adf
import numpy as np
def Vfun(X, deriv = 0, out = None, var = None):
"""
expected order : r1, r2, R, a1, a2, tau
"""
x = n2.dfun.X2adf(X, deriv, var)
r1 = x[0]
r2 = x[1]
R = x[2]
a1 = x[3]
a2 = x[4]
tau = x[5]
# Define reference values
Re = 1.45538654 # Angstroms
re = 0.96257063 # Angstroms
ae = 101.08307909 # degrees
q1 = (r1 - re) / r1 # Simons-Parr-Finlan coordinates
q2 = (r2 - re) / r2
q3 = (R - Re) / R
q4 = (a1 - ae) * np.pi/180.0 # radians
q5 = (a2 - ae) * np.pi/180.0 # radians
q6 = tau * np.pi/180.0 # radians
# Calculate surface
v = calcsurf([q1,q2,q3,q4,q5,q6]) * n2.constants.Eh
return n2.dfun.adf2array([v], out)
######################################
#
# Define module-scope PES DFun object
#
PES = n2.dfun.DFun(Vfun, nf = 1, nx = 6)
#
#
######################################
def calcsurf(q):
max_pow = [5,5,5,6,6,6] # max_pow[5] is really the max freq. of dihedral
qpow = []
for i in range(5):
qi = [adf.const_like(1.0, q[i]), q[i]]
for p in range(2,max_pow[i]+1):
qi.append(qi[1] * qi[p-1]) # qi ** p
qpow.append(qi)
# Calculate cos(n*q6)
cosq = [ adf.cos(n * q[5]) for n in range(max_pow[5] + 1)]
qpow.append(cosq)
v = 0.0
nterms = powers.shape[0]
for i in range(nterms):
c = coeffs[i]
v += c * \
qpow[0][powers[i,0]] * \
qpow[1][powers[i,1]] * \
qpow[2][powers[i,2]] * \
qpow[3][powers[i,3]] * \
qpow[4][powers[i,4]] * \
qpow[5][powers[i,5]]
return v
powers = np.array([
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 2],
[0, 0, 0, 0, 0, 3],
[0, 0, 0, 0, 0, 4],
[0, 0, 0, 0, 0, 5],
[0, 0, 0, 0, 0, 6],
[0, 0, 2, 0, 0, 0],
[2, 0, 0, 0, 0, 0],
[0, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 0, 0],
[0, 0, 0, 0, 2, 0],
[1, 0, 1, 0, 0, 0],
[0, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 0, 0],
[0, 0, 1, 0, 1, 0],
[1, 1, 0, 0, 0, 0],
[1, 0, 0, 1, 0, 0],
[0, 1, 0, 0, 1, 0],
[1, 0, 0, 0, 1, 0],
[0, 1, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0],
[0, 0, 3, 0, 0, 0],
[3, 0, 0, 0, 0, 0],
[0, 3, 0, 0, 0, 0],
[0, 0, 0, 3, 0, 0],
[0, 0, 0, 0, 3, 0],
[1, 0, 2, 0, 0, 0],
[0, 1, 2, 0, 0, 0],
[0, 0, 2, 1, 0, 0],
[0, 0, 2, 0, 1, 0],
[2, 0, 1, 0, 0, 0],
[0, 2, 1, 0, 0, 0],
[0, 0, 1, 2, 0, 0],
[0, 0, 1, 0, 2, 0],
[1, 2, 0, 0, 0, 0],
[2, 1, 0, 0, 0, 0],
[1, 0, 0, 2, 0, 0],
[0, 1, 0, 0, 2, 0],
[2, 0, 0, 1, 0, 0],
[0, 2, 0, 0, 1, 0],
[1, 0, 0, 0, 2, 0],
[0, 1, 0, 2, 0, 0],
[2, 0, 0, 0, 1, 0],
[0, 2, 0, 1, 0, 0],
[0, 0, 0, 1, 2, 0],
[0, 0, 0, 2, 1, 0],
[1, 1, 1, 0, 0, 0],
[1, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 1, 0],
[1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0],
[1, 1, 0, 1, 0, 0],
[1, 1, 0, 0, 1, 0],
[1, 0, 0, 1, 1, 0],
[0, 1, 0, 1, 1, 0],
[0, 0, 4, 0, 0, 0],
[4, 0, 0, 0, 0, 0],
[0, 4, 0, 0, 0, 0],
[0, 0, 0, 4, 0, 0],
[0, 0, 0, 0, 4, 0],
[2, 0, 2, 0, 0, 0],
[0, 2, 2, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 0, 2, 0],
[2, 2, 0, 0, 0, 0],
[2, 0, 0, 2, 0, 0],
[0, 2, 0, 0, 2, 0],
[0, 0, 0, 2, 2, 0],
[1, 0, 3, 0, 0, 0],
[0, 1, 3, 0, 0, 0],
[0, 0, 3, 1, 0, 0],
[0, 0, 3, 0, 1, 0],
[3, 0, 0, 1, 0, 0],
[0, 3, 0, 0, 1, 0],
[3, 0, 1, 0, 0, 0],
[0, 3, 1, 0, 0, 0],
[0, 0, 1, 3, 0, 0],
[0, 0, 1, 0, 3, 0],
[1, 3, 0, 0, 0, 0],
[3, 1, 0, 0, 0, 0],
[1, 0, 0, 3, 0, 0],
[0, 1, 0, 0, 3, 0],
[1, 0, 0, 0, 3, 0],
[0, 1, 0, 3, 0, 0],
[0, 0, 0, 1, 3, 0],
[0, 0, 0, 3, 1, 0],
[1, 1, 2, 0, 0, 0],
[1, 0, 2, 1, 0, 0],
[0, 1, 2, 0, 1, 0],
[1, 0, 2, 0, 1, 0],
[0, 1, 2, 1, 0, 0],
[0, 0, 2, 1, 1, 0],
[2, 0, 0, 1, 1, 0],
[0, 2, 0, 1, 1, 0],
[1, 0, 1, 2, 0, 0],
[0, 1, 1, 0, 2, 0],
[1, 0, 0, 1, 2, 0],
[0, 1, 0, 2, 1, 0],
[1, 0, 0, 2, 1, 0],
[0, 1, 0, 1, 2, 0],
[0, 0, 5, 0, 0, 0],
[5, 0, 0, 0, 0, 0],
[0, 5, 0, 0, 0, 0],
[0, 0, 0, 5, 0, 0],
[0, 0, 0, 0, 5, 0],
[0, 0, 0, 6, 0, 0],
[0, 0, 0, 0, 6, 0],
[0, 0, 0, 4, 1, 0],
[0, 0, 0, 1, 4, 0],
[0, 0, 0, 3, 2, 0],
[0, 0, 0, 2, 3, 0],
[0, 0, 1, 4, 0, 0],
[0, 0, 1, 0, 4, 0],
[0, 0, 2, 3, 0, 0],
[0, 0, 2, 0, 3, 0],
[1, 0, 0, 4, 0, 0],
[0, 1, 0, 0, 4, 0],
[2, 0, 0, 3, 0, 0],
[0, 2, 0, 0, 3, 0],
[0, 0, 1, 0, 0, 1],
[1, 0, 0, 0, 0, 1],
[0, 1, 0, 0, 0, 1],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 1, 1],
[0, 0, 2, 0, 0, 1],
[2, 0, 0, 0, 0, 1],
[0, 2, 0, 0, 0, 1],
[0, 0, 0, 2, 0, 1],
[0, 0, 0, 0, 2, 1],
[1, 0, 1, 0, 0, 1],
[0, 1, 1, 0, 0, 1],
[0, 0, 1, 1, 0, 1],
[0, 0, 1, 0, 1, 1],
[1, 1, 0, 0, 0, 1],
[1, 0, 0, 1, 0, 1],
[0, 1, 0, 0, 1, 1],
[1, 0, 0, 0, 1, 1],
[0, 1, 0, 1, 0, 1],
[0, 0, 0, 1, 1, 1],
[0, 0, 3, 0, 0, 1],
[3, 0, 0, 0, 0, 1],
[0, 3, 0, 0, 0, 1],
[0, 0, 0, 3, 0, 1],
[0, 0, 0, 0, 3, 1],
[1, 0, 2, 0, 0, 1],
[0, 1, 2, 0, 0, 1],
[0, 0, 2, 1, 0, 1],
[0, 0, 2, 0, 1, 1],
[0, 0, 1, 2, 0, 1],
[0, 0, 1, 0, 2, 1],
[1, 2, 0, 0, 0, 1],
[2, 1, 0, 0, 0, 1],
[1, 0, 0, 2, 0, 1],
[0, 1, 0, 0, 2, 1],
[1, 0, 0, 0, 2, 1],
[0, 1, 0, 2, 0, 1],
[0, 0, 0, 1, 2, 1],
[0, 0, 0, 2, 1, 1],
[1, 1, 1, 0, 0, 1],
[1, 0, 0, 1, 1, 1],
[0, 1, 0, 1, 1, 1],
[0, 0, 0, 4, 0, 1],
[0, 0, 0, 0, 4, 1],
[0, 0, 0, 5, 0, 1],
[0, 0, 0, 0, 5, 1],
[0, 0, 1, 3, 0, 1],
[0, 0, 1, 0, 3, 1],
[0, 0, 2, 2, 0, 1],
[0, 0, 2, 0, 2, 1],
[0, 0, 0, 1, 3, 1],
[0, 0, 0, 3, 1, 1],
[0, 0, 0, 2, 2, 1],
[1, 0, 0, 3, 0, 1],
[0, 1, 0, 0, 3, 1],
[1, 0, 0, 0, 3, 1],
[0, 1, 0, 3, 0, 1],
[2, 0, 0, 2, 0, 1],
[0, 2, 0, 0, 2, 1],
[2, 0, 0, 0, 2, 1],
[0, 2, 0, 2, 0, 1],
[1, 0, 2, 1, 0, 1],
[0, 1, 2, 0, 1, 1],
[2, 0, 1, 1, 0, 1],
[0, 2, 1, 0, 1, 1],
[1, 0, 1, 2, 0, 1],
[0, 1, 1, 0, 2, 1],
[0, 0, 1, 0, 0, 2],
[1, 0, 0, 0, 0, 2],
[0, 1, 0, 0, 0, 2],
[0, 0, 0, 1, 0, 2],
[0, 0, 0, 0, 1, 2],
[0, 0, 2, 0, 0, 2],
[2, 0, 0, 0, 0, 2],
[0, 2, 0, 0, 0, 2],
[0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 2, 2],
[1, 0, 1, 0, 0, 2],
[0, 1, 1, 0, 0, 2],
[0, 0, 1, 1, 0, 2],
[0, 0, 1, 0, 1, 2],
[1, 1, 0, 0, 0, 2],
[1, 0, 0, 1, 0, 2],
[0, 1, 0, 0, 1, 2],
[1, 0, 0, 0, 1, 2],
[0, 1, 0, 1, 0, 2],
[0, 0, 0, 1, 1, 2],
[0, 0, 3, 0, 0, 2],
[3, 0, 0, 0, 0, 2],
[0, 3, 0, 0, 0, 2],
[0, 0, 0, 3, 0, 2],
[0, 0, 0, 0, 3, 2],
[0, 0, 0, 2, 1, 2],
[0, 0, 0, 1, 2, 2],
[0, 0, 1, 2, 0, 2],
[0, 0, 1, 0, 2, 2],
[1, 0, 2, 0, 0, 2],
[0, 1, 2, 0, 0, 2],
[2, 0, 1, 0, 0, 2],
[0, 2, 1, 0, 0, 2],
[0, 0, 0, 4, 0, 2],
[0, 0, 0, 0, 4, 2],
[0, 0, 0, 1, 3, 2],
[0, 0, 0, 3, 1, 2],
[0, 0, 0, 2, 2, 2],
[2, 0, 0, 1, 0, 2],
[0, 2, 0, 0, 1, 2],
[1, 0, 0, 2, 0, 2],
[0, 1, 0, 0, 2, 2],
[1, 0, 0, 0, 2, 2],
[0, 1, 0, 2, 0, 2],
[1, 0, 1, 1, 0, 2],
[0, 1, 1, 0, 1, 2],
[1, 0, 1, 0, 1, 2],
[0, 1, 1, 1, 0, 2],
[0, 0, 1, 3, 0, 2],
[0, 0, 1, 0, 3, 2],
[0, 0, 1, 0, 0, 3],
[1, 0, 0, 0, 0, 3],
[0, 1, 0, 0, 0, 3],
[0, 0, 0, 1, 0, 3],
[0, 0, 0, 0, 1, 3],
[0, 0, 2, 0, 0, 3],
[2, 0, 0, 0, 0, 3],
[0, 2, 0, 0, 0, 3],
[0, 0, 0, 2, 0, 3],
[0, 0, 0, 0, 2, 3],
[0, 0, 0, 1, 1, 3],
[0, 0, 3, 0, 0, 3],
[0, 0, 0, 3, 0, 3],
[0, 0, 0, 0, 3, 3],
[0, 0, 0, 1, 2, 3],
[0, 0, 0, 2, 1, 3],
[0, 0, 1, 1, 0, 3],
[0, 0, 1, 0, 1, 3],
[1, 0, 0, 1, 0, 3],
[0, 1, 0, 0, 1, 3],
[1, 0, 0, 0, 1, 3],
[0, 1, 0, 1, 0, 3],
[0, 0, 2, 1, 0, 3],
[0, 0, 2, 0, 1, 3],
[0, 0, 1, 0, 0, 4],
[1, 0, 0, 0, 0, 4],
[0, 1, 0, 0, 0, 4],
[0, 0, 0, 1, 0, 4],
[0, 0, 0, 0, 1, 4],
[0, 0, 2, 0, 0, 4],
[0, 0, 0, 2, 0, 4],
[0, 0, 0, 0, 2, 4],
[0, 0, 0, 1, 1, 4],
[0, 0, 1, 1, 0, 4],
[0, 0, 1, 0, 1, 4],
[0, 0, 1, 0, 0, 5],
[1, 0, 0, 0, 0, 5],
[0, 1, 0, 0, 0, 5],
[0, 0, 0, 1, 0, 5],
[0, 0, 0, 0, 1, 5]
])
coeffs = np.array([
0.00396159 ,
0.00481490 ,
0.00318934 ,
0.00027018 ,
0.00005307 ,
0.00001047 ,
0.00000198 ,
1.07103383 ,
0.85671785 ,
0.85671785 ,
0.11105339 ,
0.11105339 ,
-0.03876908 ,
-0.03876908 ,
0.18430247 ,
0.18430247 ,
0.00036727 ,
-0.00663756 ,
-0.00663756 ,
-0.00196944 ,
-0.00196944 ,
0.01747081 ,
-1.18343510 ,
-0.23735539 ,
-0.23735539 ,
-0.02611900 ,
-0.02611900 ,
-0.15438002 ,
-0.15438002 ,
-0.35516368 ,
-0.35516368 ,
0.07899067 ,
0.07899067 ,
-0.26776532 ,
-0.26776532 ,
-0.00406083 ,
-0.00406083 ,
-0.01925971 ,
-0.01925971 ,
-0.01107079 ,
-0.01107079 ,
-0.00816282 ,
-0.00816282 ,
0.00337183 ,
0.00337183 ,
-0.01352772 ,
-0.01352772 ,
0.01289325 ,
-0.07449808 ,
-0.07449808 ,
-0.03379136 ,
-0.03379136 ,
-0.01672271 ,
-0.00495469 ,
-0.00495469 ,
-0.00453600 ,
-0.00453600 ,
-0.91033894 ,
-0.38779590 ,
-0.38779590 ,
-0.00503640 ,
-0.00503640 ,
-0.46416302 ,
-0.46416302 ,
0.07527264 ,
0.07527264 ,
-0.00799835 ,
-0.04029912 ,
-0.04029912 ,
0.00364088 ,
0.47561739 ,
0.47561739 ,
-0.41647359 ,
-0.41647359 ,
-0.06425296 ,
-0.06425296 ,
0.26125142 ,
0.26125142 ,
0.10336257 ,
0.10336257 ,
-0.01680055 ,
-0.01680055 ,
0.04984239 ,
0.04984239 ,
0.00354416 ,
0.00354416 ,
0.00452574 ,
0.00452574 ,
-0.05423804 ,
0.06564708 ,
0.06564708 ,
0.03801095 ,
0.03801095 ,
-0.09161667 ,
-0.01589965 ,
-0.01589965 ,
0.01341203 ,
0.01341203 ,
-0.01342635 ,
-0.01342635 ,
-0.00671149 ,
-0.00671149 ,
-0.73562441 ,
-0.30455894 ,
-0.30455894 ,
0.00582616 ,
0.00582616 ,
-0.00547701 ,
-0.00547701 ,
0.00280896 ,
0.00280896 ,
0.00674263 ,
0.00674263 ,
0.06845098 ,
0.06845098 ,
0.04193747 ,
0.04193747 ,
-0.05190213 ,
-0.05190213 ,
0.04168912 ,
0.04168912 ,
-0.01682379 ,
-0.00098759 ,
-0.00098759 ,
-0.01176361 ,
-0.01176361 ,
0.01742527 ,
-0.00533832 ,
-0.00533832 ,
0.00542779 ,
0.00542779 ,
0.00263732 ,
0.00263732 ,
0.01859551 ,
0.01859551 ,
0.00511361 ,
-0.00973834 ,
-0.00973834 ,
-0.00511467 ,
-0.00511467 ,
-0.01356281 ,
0.00352911 ,
-0.00964293 ,
-0.00964293 ,
-0.00113452 ,
-0.00113452 ,
0.01028106 ,
0.01028106 ,
-0.03748145 ,
-0.03748145 ,
-0.00708628 ,
-0.00708628 ,
0.00742831 ,
0.00742831 ,
0.00419281 ,
0.00419281 ,
-0.00555253 ,
-0.00555253 ,
-0.02044897 ,
-0.02044897 ,
-0.02429936 ,
0.00148383 ,
0.00148383 ,
0.00050075 ,
0.00050075 ,
0.00149142 ,
0.00149142 ,
0.02232416 ,
0.02232416 ,
0.07164353 ,
0.07164353 ,
0.01644870 ,
0.01644870 ,
0.01815537 ,
0.01605919 ,
0.01605919 ,
0.00735028 ,
0.00735028 ,
0.02670612 ,
0.02670612 ,
0.01548269 ,
0.01548269 ,
-0.13042235 ,
-0.13042235 ,
0.07364926 ,
0.07364926 ,
-0.08874645 ,
-0.08874645 ,
-0.01177248 ,
0.00172223 ,
0.00172223 ,
-0.00154074 ,
-0.00154074 ,
0.01965194 ,
0.00409752 ,
0.00409752 ,
0.00301573 ,
0.00301573 ,
-0.00734859 ,
-0.00734859 ,
0.00350247 ,
0.00350247 ,
-0.00037121 ,
0.00249543 ,
0.00249543 ,
-0.00168725 ,
-0.00168725 ,
0.00914785 ,
-0.02015559 ,
0.00925238 ,
0.00925238 ,
-0.00593037 ,
-0.00593037 ,
-0.01230679 ,
-0.01230679 ,
0.00829575 ,
0.00829575 ,
0.03735453 ,
0.03735453 ,
-0.04328977 ,
-0.04328977 ,
0.00458548 ,
0.00458548 ,
0.00364501 ,
0.00364501 ,
0.00986809 ,
0.01437361 ,
0.01437361 ,
0.00072674 ,
0.00072674 ,
-0.00158409 ,
-0.00158409 ,
-0.03961996 ,
-0.03961996 ,
-0.01732246 ,
-0.01732246 ,
0.02668498 ,
0.02668498 ,
-0.00188286 ,
0.00052265 ,
0.00052265 ,
-0.00089442 ,
-0.00089442 ,
0.00481644 ,
0.00031496 ,
0.00031496 ,
0.00103249 ,
0.00103249 ,
0.00224998 ,
-0.00366693 ,
-0.00033429 ,
-0.00033429 ,
-0.00319598 ,
-0.00319598 ,
0.00447145 ,
0.00447145 ,
-0.00147544 ,
-0.00147544 ,
-0.00085521 ,
-0.00085521 ,
-0.01099915 ,
-0.01099915 ,
-0.00042972 ,
0.00013538 ,
0.00013538 ,
-0.00019221 ,
-0.00019221 ,
0.00121114 ,
0.00026755 ,
0.00026755 ,
0.00054596 ,
0.00057513 ,
0.00057513 ,
-0.00009041 ,
0.00002274 ,
0.00002274 ,
-0.00004075 ,
-0.00004075
]) | 18.73913 | 76 | 0.435075 | 2,598 | 12,499 | 2.090069 | 0.120477 | 0.208471 | 0.163536 | 0.098711 | 0.316022 | 0.301657 | 0.273112 | 0.243831 | 0.210681 | 0.162063 | 0 | 0.491389 | 0.293864 | 12,499 | 667 | 77 | 18.73913 | 0.123839 | 0.073846 | 0 | 0.393388 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.003306 | false | 0 | 0.004959 | 0 | 0.01157 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
2de4ad0ebff5992a259f8a6bf7ef93b3acf5182a | 102 | py | Python | setup.py | 1ucky40nc3/medicus | 4d72b42abddfde1bded9a2003c11948d6acb390e | [
"MIT"
] | 1 | 2022-03-30T16:58:29.000Z | 2022-03-30T16:58:29.000Z | setup.py | 1ucky40nc3/medicus | 4d72b42abddfde1bded9a2003c11948d6acb390e | [
"MIT"
] | 1 | 2022-03-30T20:43:11.000Z | 2022-03-30T20:43:11.000Z | setup.py | 1ucky40nc3/medicus | 4d72b42abddfde1bded9a2003c11948d6acb390e | [
"MIT"
] | null | null | null | from setuptools import setup
setup(
name="medicus",
version="0.1",
packages=["medicus"]
) | 14.571429 | 28 | 0.637255 | 12 | 102 | 5.416667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.024691 | 0.205882 | 102 | 7 | 29 | 14.571429 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0.165049 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.166667 | 0 | 0.166667 | 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 | 0 | 0 | 0 | 3 |
2dea313a3efcef6e0fdc5c670edb6b0142da5322 | 757 | py | Python | ddtrace/ext/__init__.py | mykytarudenko/new-project | e06a912382239739dd3f93b54d545b9506102372 | [
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | ddtrace/ext/__init__.py | mykytarudenko/new-project | e06a912382239739dd3f93b54d545b9506102372 | [
"Apache-2.0",
"BSD-3-Clause"
] | 1 | 2021-01-27T04:53:24.000Z | 2021-01-27T04:53:24.000Z | ddtrace/ext/__init__.py | mykytarudenko/new-project | e06a912382239739dd3f93b54d545b9506102372 | [
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | from enum import Enum
from ..utils import removed_classproperty
from ..vendor.debtcollector import removals
class SpanTypes(Enum):
CACHE = "cache"
CASSANDRA = "cassandra"
ELASTICSEARCH = "elasticsearch"
GRPC = "grpc"
HTTP = "http"
MONGODB = "mongodb"
REDIS = "redis"
SQL = "sql"
TEMPLATE = "template"
TEST = "test"
WEB = "web"
WORKER = "worker"
@removals.removed_class("AppTypes")
class AppTypes(object):
@removed_classproperty
def web(cls):
return SpanTypes.WEB
@removed_classproperty
def db(cls):
return "db"
@removed_classproperty
def cache(cls):
return SpanTypes.CACHE
@removed_classproperty
def worker(cls):
return SpanTypes.WORKER
| 19.410256 | 43 | 0.647292 | 79 | 757 | 6.126582 | 0.367089 | 0.206612 | 0.190083 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.254954 | 757 | 38 | 44 | 19.921053 | 0.858156 | 0 | 0 | 0.133333 | 0 | 0 | 0.107001 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.133333 | false | 0 | 0.1 | 0.133333 | 0.833333 | 0 | 0 | 0 | 0 | null | 1 | 1 | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
2df065629e404af27259676f8e707e341dda1bff | 188 | py | Python | ex046.py | BrianBeyer/pythonExercicios | 062e2c6a9e6e6f513185f1fb1d4269d8ca1d9e89 | [
"MIT"
] | null | null | null | ex046.py | BrianBeyer/pythonExercicios | 062e2c6a9e6e6f513185f1fb1d4269d8ca1d9e89 | [
"MIT"
] | null | null | null | ex046.py | BrianBeyer/pythonExercicios | 062e2c6a9e6e6f513185f1fb1d4269d8ca1d9e89 | [
"MIT"
] | null | null | null | from time import sleep
print('Contagem regressiva','='*20)
for a in range(10, 0-1, -1):
print(a, end='-')
sleep(1)
print('Fogos estourando \nBOOM!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!')
| 26.857143 | 64 | 0.531915 | 25 | 188 | 4 | 0.76 | 0.12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.049383 | 0.138298 | 188 | 6 | 65 | 31.333333 | 0.567901 | 0 | 0 | 0 | 0 | 0 | 0.404255 | 0.202128 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.166667 | 0 | 0.166667 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
9303b6729128acbb771343c1e9270209cb331506 | 617 | py | Python | ecommerce/api/domain/domain_base.py | MayaraMachado/sns_and_sqs_project | 4fcc5bbb5f6841543ea8dda353dd85a43024f683 | [
"MIT"
] | 5 | 2020-06-22T21:29:54.000Z | 2021-11-01T20:12:04.000Z | ecommerce/api/domain/domain_base.py | MayaraMachado/sns_and_sqs_project | 4fcc5bbb5f6841543ea8dda353dd85a43024f683 | [
"MIT"
] | 5 | 2021-03-30T13:38:15.000Z | 2021-09-22T19:10:27.000Z | ecommerce/api/domain/domain_base.py | MayaraMachado/sns_and_sqs_project | 4fcc5bbb5f6841543ea8dda353dd85a43024f683 | [
"MIT"
] | null | null | null | class DomainServiceBase:
def __init__(self, repository):
self.repository = repository
def update(self, obj, updated_data={}):
self.repository.update(obj, updated_data)
def delete(self, obj):
self.repository.delete(obj)
def create(self, obj):
obj = self.repository.create(obj)
return obj
def get_all(self, query_params={}, orderby=[], select_related=[]):
return self.repository.get_all(query_params, orderby, select_related)
def get(self, query_params={}, select_related=[]):
return self.repository.get(query_params, select_related)
| 30.85 | 77 | 0.67423 | 74 | 617 | 5.405405 | 0.27027 | 0.245 | 0.07 | 0.12 | 0.3025 | 0.18 | 0 | 0 | 0 | 0 | 0 | 0 | 0.205835 | 617 | 19 | 78 | 32.473684 | 0.816327 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.428571 | false | 0 | 0 | 0.142857 | 0.714286 | 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 | 0 | 0 | 0 | 3 |
9342af82f1cb2c17d9d428608f08d06906c8cdc8 | 941 | py | Python | labs/7/py/dashpot.py | Sky-Nik/numerical-analysis | 97e1ab4ee8737e2eaba91084f8775089f13ec4dd | [
"MIT"
] | 1 | 2019-05-19T08:08:41.000Z | 2019-05-19T08:08:41.000Z | labs/7/py/dashpot.py | csc-knu/numerical-analysis | 97e1ab4ee8737e2eaba91084f8775089f13ec4dd | [
"MIT"
] | 4 | 2018-09-02T05:48:27.000Z | 2018-09-02T06:02:22.000Z | labs/7/py/dashpot.py | Sky-Nik/numerical-analysis | 97e1ab4ee8737e2eaba91084f8775089f13ec4dd | [
"MIT"
] | 2 | 2021-05-21T09:12:51.000Z | 2021-06-16T01:06:12.000Z | #!/usr/bin/env python
from math import sqrt
class Dashpot:
def __init__(self, k: float, r_0: float, c: float):
assert r_0 > 0, "r_0 must be positive"
assert k > 0, "k must be positive"
self._k, self._r_0, self._c = k, r_0, c
@property
def k(self):
return self._k
@property
def r_0(self):
return self._r_0
@property
def c(self):
return self._c
def __repr__(self):
return f'Dashpot(k={self.k}, r_0={self.r_0}, c={self.c})'
def r(self, dot_x: float, dot_x_0: float) -> float:
return self.r_0 * (1 + self.c * abs(dot_x - dot_x_0))
def xi(self, r: float, m: float) -> float:
return r / (2 * sqrt(self.k * m))
def xi(self, dot_x: float, dot_x_0: float, m: float) -> float:
return self.r(dot_x, dot_x_0) / (2 * sqrt(self.k * m))
if __name__ == '__main__':
pass # TODO(nsk): write tests and unittest main
| 24.763158 | 66 | 0.57067 | 163 | 941 | 3.02454 | 0.263804 | 0.040568 | 0.048682 | 0.048682 | 0.296146 | 0.093306 | 0.093306 | 0.093306 | 0 | 0 | 0 | 0.028274 | 0.285866 | 941 | 37 | 67 | 25.432432 | 0.705357 | 0.064825 | 0 | 0.12 | 0 | 0 | 0.105923 | 0 | 0 | 0 | 0 | 0.027027 | 0.08 | 1 | 0.32 | false | 0.04 | 0.04 | 0.28 | 0.68 | 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 | 0 | 0 | 0 | 3 |
934dfa4315cb2ff1c9dee478276d4c9eaf722449 | 643 | py | Python | CPAC/nuisance/__init__.py | gkiar/C-PAC | 0926b451dd8622b25eb68c7bcc770f0156238b23 | [
"BSD-3-Clause"
] | 125 | 2015-03-04T09:14:46.000Z | 2022-03-29T07:46:12.000Z | CPAC/nuisance/__init__.py | gkiar/C-PAC | 0926b451dd8622b25eb68c7bcc770f0156238b23 | [
"BSD-3-Clause"
] | 1,018 | 2015-01-04T16:01:29.000Z | 2022-03-31T19:23:09.000Z | CPAC/nuisance/__init__.py | gkiar/C-PAC | 0926b451dd8622b25eb68c7bcc770f0156238b23 | [
"BSD-3-Clause"
] | 117 | 2015-01-10T08:05:52.000Z | 2022-01-18T05:16:51.000Z | from .utils import (
find_offending_time_points,
temporal_variance_mask,
generate_summarize_tissue_mask,
NuisanceRegressor
)
from .nuisance import (
create_regressor_workflow,
create_nuisance_regression_workflow,
filtering_bold_and_regressors
)
from .bandpass import (
bandpass_voxels
)
from .utils.compcor import (
cosine_filter
)
__all__ = [
'create_regressor_workflow',
'create_nuisance_regression_workflow',
'filtering_bold_and_regressors',
'find_offending_time_points',
'temporal_variance_mask',
'generate_summarize_tissue_mask',
'bandpass_voxels',
'cosine_filter'
] | 20.741935 | 42 | 0.757387 | 67 | 643 | 6.671642 | 0.432836 | 0.040268 | 0.076063 | 0.102908 | 0.675615 | 0.675615 | 0.675615 | 0.675615 | 0.675615 | 0.675615 | 0 | 0 | 0.174184 | 643 | 31 | 43 | 20.741935 | 0.841808 | 0 | 0 | 0 | 1 | 0 | 0.302795 | 0.259317 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.111111 | 0.148148 | 0 | 0.148148 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
9358cdc73a349a04ce1de7626c072a050c3ec91a | 58 | py | Python | test_write.py | esspee39/gtest-demo | 844a79d3724e07b72ff1c2dbd049edafd3b392a7 | [
"BSD-3-Clause"
] | null | null | null | test_write.py | esspee39/gtest-demo | 844a79d3724e07b72ff1c2dbd049edafd3b392a7 | [
"BSD-3-Clause"
] | null | null | null | test_write.py | esspee39/gtest-demo | 844a79d3724e07b72ff1c2dbd049edafd3b392a7 | [
"BSD-3-Clause"
] | 1 | 2021-11-20T18:48:23.000Z | 2021-11-20T18:48:23.000Z | with open('test.html',"w+") as f:
f.write("test")
| 19.333333 | 33 | 0.517241 | 10 | 58 | 3 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.224138 | 58 | 2 | 34 | 29 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0.258621 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 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 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
935f559eeb2f80e02f374b96d7b61a3325ced81a | 275 | py | Python | pyleecan/Methods/Machine/LamSquirrelCage/__init__.py | IrakozeFD/pyleecan | 5a93bd98755d880176c1ce8ac90f36ca1b907055 | [
"Apache-2.0"
] | 95 | 2019-01-23T04:19:45.000Z | 2022-03-17T18:22:10.000Z | pyleecan/Methods/Machine/LamSquirrelCage/__init__.py | IrakozeFD/pyleecan | 5a93bd98755d880176c1ce8ac90f36ca1b907055 | [
"Apache-2.0"
] | 366 | 2019-02-20T07:15:08.000Z | 2022-03-31T13:37:23.000Z | pyleecan/Methods/Machine/LamSquirrelCage/__init__.py | IrakozeFD/pyleecan | 5a93bd98755d880176c1ce8ac90f36ca1b907055 | [
"Apache-2.0"
] | 74 | 2019-01-24T01:47:31.000Z | 2022-02-25T05:44:42.000Z | from ....Methods.Machine.LamSlotWind import Lam_WindCheckError
class SquirrelCageCheckError(Lam_WindCheckError):
""" """
pass
class SCC_NotARotor(SquirrelCageCheckError):
""" """
pass
class SCC_WrongCond(SquirrelCageCheckError):
""" """
pass
| 13.75 | 62 | 0.690909 | 22 | 275 | 8.454545 | 0.590909 | 0.182796 | 0.129032 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.189091 | 275 | 19 | 63 | 14.473684 | 0.834081 | 0 | 0 | 0.428571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.428571 | 0.142857 | 0 | 0.571429 | 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 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
93623fa124e1fe3afa3694fbd7e48b33c4e20604 | 1,615 | py | Python | src/tests/test_calculate_chek.py | Almateyko/learn-duet2s | 5004583f629b81bf1eabb5de69f01da202308036 | [
"MIT"
] | null | null | null | src/tests/test_calculate_chek.py | Almateyko/learn-duet2s | 5004583f629b81bf1eabb5de69f01da202308036 | [
"MIT"
] | null | null | null | src/tests/test_calculate_chek.py | Almateyko/learn-duet2s | 5004583f629b81bf1eabb5de69f01da202308036 | [
"MIT"
] | null | null | null | import unittest
from src.main_program import *
class TestMainProgram(unittest.TestCase):
def test_calculate_chek_1(self):
a = dict(gas=0, water=0, electricity=0)
self.assertEqual('Verification was successful', calculate_chek('gas', 3, a))
self.assertEqual('Verification was successful', calculate_chek('water', 12, a))
self.assertEqual('Verification was successful', calculate_chek('electricity', 124, a))
self.assertEqual('Verification was successful', calculate_chek('gas', 10, a))
self.assertEqual('Verification was successful', calculate_chek('water', 88, a))
def test_calculate_chek_2(self):
a = dict(gas=0, water=0, electricity=0)
self.assertEqual('ValueError', calculate_chek('gas', -2, a))
self.assertEqual('ValueError', calculate_chek('water', -20, a))
self.assertEqual('ValueError', calculate_chek('gas', 1342, a))
self.assertEqual('ValueError', calculate_chek('gas', 1042354, a))
self.assertEqual('ValueError', calculate_chek('water', 'a', a))
self.assertEqual('ValueError', calculate_chek('water', 'qwerty', a))
def test_calculate_chek_3(self):
a = dict(gas=0, water=0, electricity=0)
self.assertEqual('TypeError', calculate_chek('gas', [1, 2, 3], a))
self.assertEqual('TypeError', calculate_chek('water', {'one': 12, 15: 'adds'}, a))
def test_calculate_chek_4(self):
a = dict(gas=0, water=0, electricity=0)
self.assertEqual('Verification was unsuccessful', calculate_chek('gas', '', a))
if __name__ == '__main__':
unittest.main()
| 44.861111 | 94 | 0.669969 | 200 | 1,615 | 5.235 | 0.22 | 0.223496 | 0.152818 | 0.17192 | 0.795606 | 0.679083 | 0.65425 | 0.447947 | 0.317096 | 0.204394 | 0 | 0.035365 | 0.17709 | 1,615 | 35 | 95 | 46.142857 | 0.752445 | 0 | 0 | 0.148148 | 0 | 0 | 0.201858 | 0 | 0 | 0 | 0 | 0 | 0.518519 | 1 | 0.148148 | false | 0 | 0.074074 | 0 | 0.259259 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
fa7a17b16277b55311602db31f0a4d9c0e04f12a | 11,375 | py | Python | ninja/router.py | aprilahijriyan/django-ninja | df2716c7f5fc2ec008163048cc9a41103aeebabe | [
"MIT"
] | null | null | null | ninja/router.py | aprilahijriyan/django-ninja | df2716c7f5fc2ec008163048cc9a41103aeebabe | [
"MIT"
] | 1 | 2021-04-25T07:00:55.000Z | 2021-04-25T07:00:55.000Z | ninja/router.py | aprilahijriyan/django-ninja | df2716c7f5fc2ec008163048cc9a41103aeebabe | [
"MIT"
] | null | null | null | from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterator,
List,
Optional,
Tuple,
cast,
)
from django.urls import URLPattern, path as django_path
from ninja.constants import NOT_SET
from ninja.operation import PathView
from ninja.types import TCallable
from ninja.utils import normalize_path
if TYPE_CHECKING:
from ninja import NinjaAPI # pragma: no cover
__all__ = ["Router"]
class Router:
def __init__(
self, *, auth: Any = NOT_SET, tags: Optional[List[str]] = None
) -> None:
self.api: Optional["NinjaAPI"] = None
self.auth = auth
self.tags = tags
self.path_operations: Dict[str, PathView] = {}
self._routers: List[Tuple[str, Router]] = []
def get(
self,
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
return self.api_operation(
["GET"],
path,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
def post(
self,
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
return self.api_operation(
["POST"],
path,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
def delete(
self,
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
return self.api_operation(
["DELETE"],
path,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
def patch(
self,
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
return self.api_operation(
["PATCH"],
path,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
def put(
self,
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
return self.api_operation(
["PUT"],
path,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
def api_operation(
self,
methods: List[str],
path: str,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> Callable[[TCallable], TCallable]:
def decorator(view_func: TCallable) -> TCallable:
self.add_api_operation(
path,
methods,
view_func,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
return view_func
return decorator
def add_api_operation(
self,
path: str,
methods: List[str],
view_func: Callable,
*,
auth: Any = NOT_SET,
response: Any = NOT_SET,
operation_id: Optional[str] = None,
summary: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[List[str]] = None,
deprecated: Optional[bool] = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
url_name: Optional[str] = None,
include_in_schema: bool = True,
) -> None:
if path not in self.path_operations:
path_view = PathView()
self.path_operations[path] = path_view
else:
path_view = self.path_operations[path]
if not url_name:
url_name = view_func.__name__
path_view.add_operation(
path=path,
methods=methods,
view_func=view_func,
auth=auth,
response=response,
operation_id=operation_id,
summary=summary,
description=description,
tags=tags,
deprecated=deprecated,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
url_name=url_name,
include_in_schema=include_in_schema,
)
if self.api:
path_view.set_api_instance(self.api, self)
return None
def set_api_instance(
self, api: "NinjaAPI", parent_router: Optional["Router"] = None
) -> None:
# TODO: check - parent_router seems not used
self.api = api
for path_view in self.path_operations.values():
path_view.set_api_instance(self.api, self)
for _, router in self._routers:
router.set_api_instance(api, self)
def urls_paths(self, prefix: str) -> Iterator[URLPattern]:
for path, path_view in self.path_operations.items():
path = path.replace("{", "<").replace("}", ">")
route = "/".join([i for i in (prefix, path) if i])
# to skip lot of checks we simply treat double slash as a mistake:
route = normalize_path(route)
route = route.lstrip("/")
yield django_path(
route, path_view.get_view(), name=cast(str, path_view.url_name)
)
def add_router(
self,
prefix: str,
router: "Router",
*,
auth: Any = NOT_SET,
tags: Optional[List[str]] = None,
) -> None:
if self.api:
# we are already attached to an api
self.api.add_router(
prefix=prefix, router=router, auth=auth, tags=tags, parent_router=self
)
else:
# we are not attached to an api
if auth != NOT_SET:
router.auth = auth
if tags is not None:
router.tags = tags
self._routers.append((prefix, router))
def build_routers(self, prefix: str) -> List[Tuple[str, "Router"]]:
assert self.api is None
internal_routes = []
for inter_prefix, inter_router in self._routers:
_route = normalize_path("/".join((prefix, inter_prefix))).lstrip("/")
internal_routes.extend(inter_router.build_routers(_route))
return [(prefix, self), *internal_routes]
| 31.422652 | 86 | 0.555165 | 1,185 | 11,375 | 5.098734 | 0.098734 | 0.042867 | 0.069513 | 0.019364 | 0.705561 | 0.702085 | 0.692817 | 0.692817 | 0.681893 | 0.681893 | 0 | 0 | 0.353055 | 11,375 | 361 | 87 | 31.509695 | 0.821035 | 0.016527 | 0 | 0.708709 | 0 | 0 | 0.006171 | 0 | 0 | 0 | 0 | 0.00277 | 0.003003 | 1 | 0.039039 | false | 0 | 0.021021 | 0.015015 | 0.09009 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 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 | 3 |
fa7ef445622742250bd30b58f2eeb1b1ba97d14f | 183 | py | Python | website/forms.py | ksamuel/smit | a7cf54f2953678804f69182951bbe98214d5c9f6 | [
"MIT"
] | null | null | null | website/forms.py | ksamuel/smit | a7cf54f2953678804f69182951bbe98214d5c9f6 | [
"MIT"
] | null | null | null | website/forms.py | ksamuel/smit | a7cf54f2953678804f69182951bbe98214d5c9f6 | [
"MIT"
] | null | null | null | from django.forms import ModelForm
from .models import Settings
class SettingsForm(ModelForm):
class Meta:
model = Settings
exclude = ('id', 'active', 'name')
| 16.636364 | 42 | 0.661202 | 20 | 183 | 6.05 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.240437 | 183 | 10 | 43 | 18.3 | 0.870504 | 0 | 0 | 0 | 0 | 0 | 0.065574 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.666667 | 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 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
fa889b74b7245628083510ed48ce28fb454a0527 | 292 | py | Python | students/k3340/laboratory_works/Nurdinov_Rostislav/laboratory_work_1/conference_engine/conference/admin.py | TonikX/ITMO_ICT_-WebProgramming_2020 | ba566c1b3ab04585665c69860b713741906935a0 | [
"MIT"
] | 10 | 2020-03-20T09:06:12.000Z | 2021-07-27T13:06:02.000Z | students/k3340/laboratory_works/Nurdinov_Rostislav/laboratory_work_1/conference_engine/conference/admin.py | TonikX/ITMO_ICT_-WebProgramming_2020 | ba566c1b3ab04585665c69860b713741906935a0 | [
"MIT"
] | 134 | 2020-03-23T09:47:48.000Z | 2022-03-12T01:05:19.000Z | students/k3340/laboratory_works/Nurdinov_Rostislav/laboratory_work_1/conference_engine/conference/admin.py | TonikX/ITMO_ICT_-WebProgramming_2020 | ba566c1b3ab04585665c69860b713741906935a0 | [
"MIT"
] | 71 | 2020-03-20T12:45:56.000Z | 2021-10-31T19:22:25.000Z | from django.contrib import admin
from .models import *
admin.site.register(Location)
admin.site.register(Conference)
admin.site.register(Section)
admin.site.register(Speaker)
admin.site.register(Lecture)
admin.site.register(Speech)
admin.site.register(Comment)
# Register your models here.
| 22.461538 | 32 | 0.811644 | 40 | 292 | 5.925 | 0.425 | 0.265823 | 0.50211 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.075342 | 292 | 12 | 33 | 24.333333 | 0.877778 | 0.089041 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.222222 | 0 | 0.222222 | 0 | 0 | 0 | 0 | null | 1 | 1 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
fab692eddd82765e94d5136049870945eaab87e9 | 452 | py | Python | dpipe/predict/tests/test_functional.py | samokhinv/deep_pipe | 9461b02f5f32c3e9f24490619ebccf417979cffc | [
"MIT"
] | 38 | 2017-09-08T04:51:17.000Z | 2022-03-29T17:34:22.000Z | dpipe/predict/tests/test_functional.py | samokhinv/deep_pipe | 9461b02f5f32c3e9f24490619ebccf417979cffc | [
"MIT"
] | 41 | 2017-09-29T22:06:21.000Z | 2021-12-03T09:31:57.000Z | dpipe/predict/tests/test_functional.py | samokhinv/deep_pipe | 9461b02f5f32c3e9f24490619ebccf417979cffc | [
"MIT"
] | 12 | 2017-09-08T04:40:39.000Z | 2021-01-19T19:19:37.000Z | from dpipe.predict.functional import *
def test_chain_decorators():
def append(num):
def decorator(func):
def wrapper():
return func() + [num]
return wrapper
return decorator
@append(1)
@append(2)
@append(3)
def f():
return []
chained = chain_decorators(
append(1), append(2), append(3),
predict=lambda: []
)
assert f() == chained()
| 17.384615 | 40 | 0.524336 | 47 | 452 | 4.978723 | 0.468085 | 0.128205 | 0.111111 | 0.119658 | 0.179487 | 0.179487 | 0 | 0 | 0 | 0 | 0 | 0.020478 | 0.35177 | 452 | 25 | 41 | 18.08 | 0.778157 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.055556 | 1 | 0.277778 | false | 0 | 0.055556 | 0.111111 | 0.555556 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
fabc83440c421319a5a249333586d96d3ab74d4d | 180 | py | Python | run.py | yeyintminthuhtut/scoring_engine | 679021c00fcab5032078665d17d4b102346347f1 | [
"MIT"
] | 1 | 2021-01-11T07:10:42.000Z | 2021-01-11T07:10:42.000Z | run.py | yeyintminthuhtut/scoring_engine | 679021c00fcab5032078665d17d4b102346347f1 | [
"MIT"
] | null | null | null | run.py | yeyintminthuhtut/scoring_engine | 679021c00fcab5032078665d17d4b102346347f1 | [
"MIT"
] | null | null | null | from scoring_engine.web import app as application
if __name__ == '__main__':
if application.debug:
application.run()
else:
application.run(host='0.0.0.0')
| 22.5 | 49 | 0.661111 | 24 | 180 | 4.583333 | 0.666667 | 0.054545 | 0.054545 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028571 | 0.222222 | 180 | 7 | 50 | 25.714286 | 0.757143 | 0 | 0 | 0 | 0 | 0 | 0.083333 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.166667 | 0 | 0.166667 | 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 | 0 | 0 | 0 | 3 |
fad080517ecf09ec4a8c3e425b1088d073fd7d94 | 319 | py | Python | flask_app/tests/test_myapp.py | odysseyhack/pines-and-electronics | 82465582fd24bbb249215bdea23ff853fab0b1b4 | [
"Apache-2.0"
] | null | null | null | flask_app/tests/test_myapp.py | odysseyhack/pines-and-electronics | 82465582fd24bbb249215bdea23ff853fab0b1b4 | [
"Apache-2.0"
] | null | null | null | flask_app/tests/test_myapp.py | odysseyhack/pines-and-electronics | 82465582fd24bbb249215bdea23ff853fab0b1b4 | [
"Apache-2.0"
] | null | null | null | from flask_app.camera.gcp_vision_multi_img import proccess_picture
# def test_status(client):
# assert client.get('/api/status').data == b"status"
# # client.get('/api/snap')
#
def test_register_in_ocean(client):
client.get('/api/register')
# def test_process_pictures():
# result = proccess_picture() | 29 | 66 | 0.717868 | 44 | 319 | 4.931818 | 0.613636 | 0.096774 | 0.165899 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.134796 | 319 | 11 | 67 | 29 | 0.786232 | 0.529781 | 0 | 0 | 0 | 0 | 0.090909 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 0.666667 | 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 | 0 | 1 | 0 | 0 | 3 |
fad7cd2725ebf047ccd9dadc546c41e1801922db | 190 | py | Python | wagtail/documents/tests/utils.py | stevedya/wagtail | 52e5abfe62547cdfd90ea7dfeb8bf5a52f16324c | [
"BSD-3-Clause"
] | 1 | 2022-02-09T05:25:30.000Z | 2022-02-09T05:25:30.000Z | wagtail/documents/tests/utils.py | stevedya/wagtail | 52e5abfe62547cdfd90ea7dfeb8bf5a52f16324c | [
"BSD-3-Clause"
] | null | null | null | wagtail/documents/tests/utils.py | stevedya/wagtail | 52e5abfe62547cdfd90ea7dfeb8bf5a52f16324c | [
"BSD-3-Clause"
] | null | null | null | from django.core.files.base import ContentFile
def get_test_document_file():
fake_file = ContentFile(b"A boring example document")
fake_file.name = "test.txt"
return fake_file
| 23.75 | 57 | 0.752632 | 28 | 190 | 4.892857 | 0.714286 | 0.175182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.163158 | 190 | 7 | 58 | 27.142857 | 0.861635 | 0 | 0 | 0 | 0 | 0 | 0.173684 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 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 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
faee6021777a2f82e738f49da5ca5a5102da766a | 718 | py | Python | msldap/external/aiocmd/setup.py | zhuby1973/msldap | 6ff0566112b965d61c43da1dff61b9b8476dded9 | [
"MIT"
] | 6 | 2019-08-20T21:40:28.000Z | 2021-05-22T18:45:41.000Z | msldap/external/aiocmd/setup.py | zhuby1973/msldap | 6ff0566112b965d61c43da1dff61b9b8476dded9 | [
"MIT"
] | 3 | 2020-01-15T17:32:23.000Z | 2021-05-22T04:07:42.000Z | msldap/external/aiocmd/setup.py | zhuby1973/msldap | 6ff0566112b965d61c43da1dff61b9b8476dded9 | [
"MIT"
] | 5 | 2019-08-09T04:03:57.000Z | 2020-03-19T10:22:56.000Z | from setuptools import setup, find_packages
setup(name='aiocmd',
packages=find_packages("."),
version='0.1.4',
author='Dor Green',
author_email='dorgreen1@gmail.com',
description='Coroutine-based CLI generator using prompt_toolkit',
url='http://github.com/KimiNewt/aiocmd',
keywords=['asyncio', 'cmd'],
license='MIT',
install_requires=[
'prompt_toolkit>=2.0.9'
],
classifiers=[
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7'
])
| 31.217391 | 71 | 0.584958 | 75 | 718 | 5.52 | 0.666667 | 0.183575 | 0.241546 | 0.251208 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.026515 | 0.264624 | 718 | 22 | 72 | 32.636364 | 0.757576 | 0 | 0 | 0 | 0 | 0 | 0.47493 | 0.029248 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.05 | 0 | 0.05 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
faef03dc30912b796e9bba0498ce2118d6cfc21c | 2,138 | py | Python | home/models.py | dikshaRaj/Diksha | 0086d89a39c272670e8e499934d7bea93af438c4 | [
"bzip2-1.0.6"
] | null | null | null | home/models.py | dikshaRaj/Diksha | 0086d89a39c272670e8e499934d7bea93af438c4 | [
"bzip2-1.0.6"
] | 8 | 2019-12-04T23:24:47.000Z | 2022-02-10T09:14:21.000Z | home/models.py | dikshaRaj/Diksha | 0086d89a39c272670e8e499934d7bea93af438c4 | [
"bzip2-1.0.6"
] | null | null | null | from django.db import models
import uuid
# Create your models here.
class Book(models.Model):
id = models.UUIDField('Book Id',primary_key=True, default = uuid.uuid4, help_text="generated unique id for book")
name = models.CharField(max_length=100, help_text='Book Name',null=True)
purchase_date = models.DateField(null=True, blank=True)
genre = models.ManyToManyField('Genre', help_text='genre of book')
book_author = models.ForeignKey('Author',on_delete=models.SET_NULL ,help_text='Book Author', null=True)
timestamp = models.DateTimeField(auto_now=True)
def __str__(self):
return self.name
class Author(models.Model):
#id = models.AutoField(primary_key=True)
author_name = models.CharField(max_length=100, help_text='Name of Author',null=True)
numChoice = (
('1','One'),
('2','Two'),
('3','Three'),
('4','Four'),
('5', 'Five')
)
total_book_written = models.CharField(max_length=1, choices=numChoice)
date_of_birth = models.DateField('Birth',null=True, blank=True)
date_of_death = models.DateField('Death',null=True, blank=True)
timestamp = models.DateTimeField(auto_now=True)
def __str__(self):
return self.author_name +' (Written books - '+ self.total_book_written +')'
class Genre(models.Model):
name = models.CharField(max_length=100, help_text='Genre',null=True)
timestamp = models.DateTimeField(auto_now=True)
def __str__(self):
return self.name
class Student(models.Model):
usn = models.IntegerField('USN',primary_key=True, help_text="Enter USN for Student")
name = models.CharField(max_length=100, help_text='Student Name',null=True)
book_name = models.ForeignKey('Book',on_delete=models.SET_NULL, help_text='Book Name',null=True)
purchase_date = models.DateField(null=True, blank=True)
#genre = models.ManyToManyField('Genre', help_text='genre of book')
#book_author = models.ForeignKey('Author',on_delete=models.SET_NULL ,help_text='Book Author', null=True)
timestamp = models.DateTimeField(auto_now=True)
def __str__(self):
return self.name | 44.541667 | 117 | 0.703929 | 291 | 2,138 | 4.965636 | 0.247423 | 0.0609 | 0.062284 | 0.083045 | 0.576471 | 0.576471 | 0.576471 | 0.576471 | 0.459516 | 0.459516 | 0 | 0.010567 | 0.159027 | 2,138 | 48 | 118 | 44.541667 | 0.793103 | 0.108513 | 0 | 0.333333 | 1 | 0 | 0.105152 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.102564 | false | 0 | 0.051282 | 0.102564 | 0.846154 | 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 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
faf67d3deadf4abc84d3fd62b8e391e064c99ddf | 173 | py | Python | Zad_FactoryMethod/BazaDanychOracle.py | Paarzivall/Wzorce-Projektowe | aa4136f140ad02c0fc0de45709b5a01ca42b417f | [
"MIT"
] | null | null | null | Zad_FactoryMethod/BazaDanychOracle.py | Paarzivall/Wzorce-Projektowe | aa4136f140ad02c0fc0de45709b5a01ca42b417f | [
"MIT"
] | null | null | null | Zad_FactoryMethod/BazaDanychOracle.py | Paarzivall/Wzorce-Projektowe | aa4136f140ad02c0fc0de45709b5a01ca42b417f | [
"MIT"
] | null | null | null | from BazaDanych import BazaDanych
class BazaDanychOracle(BazaDanych):
def WykonajSelect(self, zapytanie):
print(f"Oracle\> {zapytanie}\n\tWykonano pomyślnie")
| 24.714286 | 60 | 0.751445 | 18 | 173 | 7.222222 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.150289 | 173 | 6 | 61 | 28.833333 | 0.884354 | 0 | 0 | 0 | 0 | 0 | 0.242775 | 0.132948 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 0.25 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
4f08b890e4ed202f05c786143d67462ade8cd06b | 40,016 | py | Python | MJ_per_SAE_STAT_GRAPH.py | GrantRoss-Tenki/Malawi-CQC-CSC-OSU-Work | a720e0451579945ba10eafdafe2e0d59a86d5cfb | [
"MIT"
] | null | null | null | MJ_per_SAE_STAT_GRAPH.py | GrantRoss-Tenki/Malawi-CQC-CSC-OSU-Work | a720e0451579945ba10eafdafe2e0d59a86d5cfb | [
"MIT"
] | null | null | null | MJ_per_SAE_STAT_GRAPH.py | GrantRoss-Tenki/Malawi-CQC-CSC-OSU-Work | a720e0451579945ba10eafdafe2e0d59a86d5cfb | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu Mar 17 11:02:24 2022
@author: rossgra
"""
import numpy as np
from numpy.core.fromnumeric import std
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import scipy
from scipy.stats import mannwhitneyu
import statistics as stat
metric = input('SAE or Non - ')
# I am goign to bring in the NO- hood section first
#for Megajouels
#No_hood_MJ_path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per SAE - No_Hood.csv" #rossgra or gvros
#Hood_MJ_Path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per SAE - Hood.csv"
#### for FUEL_REMOVED _perd
if metric== 'SAE':
No_hood_MJ_path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/24 Hour Remove SAE - No_Hood.csv" #rossgra or gvros
Hood_MJ_Path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/24 Hour Remove SAE - Hood.csv"
#No_hood_MJ_path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per SAE - No_Hood.csv" #rossgra or gvros
#Hood_MJ_Path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per SAE - Hood.csv"
else:
#No_hood_MJ_path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/24 Hour Remove - No_Hood.csv" #rossgra or gvros
#Hood_MJ_Path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/24 Hour Remove - Hood.csv"
No_hood_MJ_path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per Day - No_Hood.csv" #rossgra or gvros
Hood_MJ_Path = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/MJ per Day - Hood.csv"
######For Fuel removed per 24 hours per SAE
Level_of_confidence = 0.05
No_hood_MJ = pd.read_csv(No_hood_MJ_path)
Hood_MJ = pd.read_csv(Hood_MJ_Path)
#C:\Users\rossgra\Box\Classes\Software Dev C:\Users\rossgra\Box\OSU, CSC, CQC Project files
HH_1N = [x for x in No_hood_MJ.iloc[:, 0] if x != -1]
HH_2N = [x for x in No_hood_MJ.iloc[:, 11] if x != -1]
HH_3N = [x for x in No_hood_MJ.iloc[:, 22] if x != -1]
HH_4N = [x for x in No_hood_MJ.iloc[:, 33] if x != -1]
HH_1H = [x for x in Hood_MJ.iloc[:, 0] if x != -1]
HH_2H = [x for x in Hood_MJ.iloc[:, 11] if x != -1]
HH_3H = [x for x in Hood_MJ.iloc[:, 22] if x != -1]
Mj_1N_Phase = [x for x in No_hood_MJ.iloc[:, 5] if x != -1]
Mj_2N_Phase = [x for x in No_hood_MJ.iloc[:, 16] if x != -1]
Mj_3N_Phase = [x for x in No_hood_MJ.iloc[:, 27] if x != -1]
Mj_4N_Phase = [x for x in No_hood_MJ.iloc[:, 38] if x != -1]
Mj_1H_Phase = [x for x in Hood_MJ.iloc[:, 5] if x != -1]
Mj_2H_Phase = [x for x in Hood_MJ.iloc[:, 16] if x != -1]
Mj_3H_Phase = [x for x in Hood_MJ.iloc[:, 27] if x != -1]
Mj_filter_1N_Phase = [x for x in No_hood_MJ.iloc[:, 6] if x != -1]
Mj_filter_2N_Phase = [x for x in No_hood_MJ.iloc[:, 17] if x != -1]
Mj_filter_3N_Phase = [x for x in No_hood_MJ.iloc[:, 28] if x != -1]
Mj_filter_4N_Phase = [x for x in No_hood_MJ.iloc[:, 39] if x != -1]
Mj_filter_1H_Phase = [x for x in Hood_MJ.iloc[:, 6] if x != -1]
Mj_filter_2H_Phase = [x for x in Hood_MJ.iloc[:, 17] if x != -1]
Mj_filter_3H_Phase = [x for x in Hood_MJ.iloc[:, 28] if x != -1]
Fuel_1N_Phase = [x for x in No_hood_MJ.iloc[:, 3] if x != -1]
Fuel_2N_Phase = [x for x in No_hood_MJ.iloc[:, 14] if x != -1]
Fuel_3N_Phase = [x for x in No_hood_MJ.iloc[:, 25] if x != -1]
Fuel_4N_Phase = [x for x in No_hood_MJ.iloc[:, 36] if x != -1]
Fuel_1H_Phase = [x for x in Hood_MJ.iloc[:, 3] if x != -1]
Fuel_2H_Phase = [x for x in Hood_MJ.iloc[:, 14] if x != -1]
Fuel_3H_Phase = [x for x in Hood_MJ.iloc[:, 25] if x != -1]
Avg_Fuel_1N = [x for x in No_hood_MJ.iloc[:, 2] if x != -1]
Avg_Fuel_2N = [x for x in No_hood_MJ.iloc[:, 13] if x != -1]
Avg_Fuel_3N = [x for x in No_hood_MJ.iloc[:, 24] if x != -1]
Avg_Fuel_4N = [x for x in No_hood_MJ.iloc[:, 35] if x != -1]
Avg_Fuel_1H = [x for x in Hood_MJ.iloc[:, 2] if x != -1]
Avg_Fuel_2H = [x for x in Hood_MJ.iloc[:, 13] if x != -1]
Avg_Fuel_3H = [x for x in Hood_MJ.iloc[:, 24] if x != -1]
Phase_1N_day_count = [x for x in No_hood_MJ.iloc[:, 1] if x != -1]
Phase_2N_day_count = [x for x in No_hood_MJ.iloc[:, 12] if x != -1]
Phase_3N_day_count = [x for x in No_hood_MJ.iloc[:, 23] if x != -1]
Phase_4N_day_count = [x for x in No_hood_MJ.iloc[:, 34] if x != -1]
Phase_1H_day_count = [x for x in Hood_MJ.iloc[:, 1] if x != -1]
Phase_2H_day_count = [x for x in Hood_MJ.iloc[:, 12] if x != -1]
Phase_3H_day_count = [x for x in Hood_MJ.iloc[:, 23] if x != -1]
Filter_1N_day_count = [x for x in No_hood_MJ.iloc[:, 7] if x != -1]
Filter_2N_day_count = [x for x in No_hood_MJ.iloc[:, 18] if x != -1]
Filter_3N_day_count = [x for x in No_hood_MJ.iloc[:, 29] if x != -1]
Filter_4N_day_count = [x for x in No_hood_MJ.iloc[:, 40] if x != -1]
Filter_1H_day_count = [x for x in Hood_MJ.iloc[:, 7] if x != -1]
Filter_2H_day_count = [x for x in Hood_MJ.iloc[:, 18] if x != -1]
Filter_3H_day_count = [x for x in Hood_MJ.iloc[:, 29] if x != -1]
cooking_times_1N = [x for x in No_hood_MJ.iloc[:, 8] if x != -1]
cooking_times_2N = [x for x in No_hood_MJ.iloc[:, 19] if x != -1]
cooking_times_3N = [x for x in No_hood_MJ.iloc[:, 30] if x != -1]
cooking_times_4N = [x for x in No_hood_MJ.iloc[:, 41] if x != -1]
cooking_times_1H = [x for x in Hood_MJ.iloc[:, 8] if x != -1]
cooking_times_2H = [x for x in Hood_MJ.iloc[:, 19] if x != -1]
cooking_times_3H = [x for x in Hood_MJ.iloc[:, 30] if x != -1]
## data frames of metrics
no_hood_df = {'1N': Mj_1N_Phase,'2N':Mj_2N_Phase,'3N':Mj_3N_Phase,'4N':Mj_4N_Phase}
no_hood_filter_df = {'1N':Mj_filter_1N_Phase,'2N':Mj_filter_2N_Phase,'3N':Mj_filter_3N_Phase,'4N':Mj_filter_4N_Phase}
Hood_df = {'1H':Mj_1H_Phase,'2H':Mj_2H_Phase,'3H':Mj_3H_Phase }
Hood_Filter_df = {'1H':Mj_1H_Phase,'2H':Mj_2H_Phase,'3H':Mj_3H_Phase }
# Graphing
if metric== 'SAE':
sns.displot((Mj_1N_Phase, Mj_2N_Phase, Mj_3N_Phase,Mj_4N_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day/SAE No-Hood')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_filter_1N_Phase, Mj_filter_2N_Phase, Mj_filter_3N_Phase,Mj_filter_4N_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day/SAE No-Hood - Filtered')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_1H_Phase, Mj_2H_Phase, Mj_3H_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day/SAE Hood')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_filter_1H_Phase, Mj_filter_2H_Phase, Mj_filter_3H_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day/SAE ood - Filtered')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
else:
sns.displot((Mj_1N_Phase, Mj_2N_Phase, Mj_3N_Phase,Mj_4N_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day No-Hood')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_filter_1N_Phase, Mj_filter_2N_Phase, Mj_filter_3N_Phase,Mj_filter_4N_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day No-Hood - Filtered')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_1H_Phase, Mj_2H_Phase, Mj_3H_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day Hood')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
sns.displot((Mj_filter_1H_Phase, Mj_filter_2H_Phase, Mj_filter_3H_Phase), kind="kde", common_norm=False)
plt.title('Fuel/Day Hood - Filtered')
#plt.legend(labels=['1N', '2N', '3N', '4N'])
plt.show()
#1N to 2N
# for Phase
MJ_Phase_1N_to_2_comon = []
MJ_Phase_2N_to_1_comon = []
Day_count_MJ_Phase_1N_2N = []
count_n = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == str(-1):
break
for row_2N, hh_2N in enumerate(HH_2N):
if hh_1N == hh_2N:
MJ_Phase_1N_to_2_comon.append(Mj_1N_Phase[row_1N])
MJ_Phase_2N_to_1_comon.append(Mj_2N_Phase[row_2N])
Day_count_MJ_Phase_1N_2N.append(Phase_1N_day_count[row_1N] +Phase_2N_day_count[row_2N] )
count_n = count_n + 1
N_MJ_Phase_1N_2N = count_n -1
#for filter
MJ_filter_1N_to_2_comon = []
MJ_filter_2N_to_1_comon = []
Day_count_MJ_filter_1N_2N = []
count_n = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == str(-1):
break
for row_2N, hh_2N in enumerate(HH_2N):
if hh_1N == hh_2N:
MJ_filter_1N_to_2_comon.append(Mj_filter_1N_Phase[row_1N])
MJ_filter_2N_to_1_comon.append(Mj_filter_2N_Phase[row_2N])
Day_count_MJ_filter_1N_2N.append(Filter_1N_day_count[row_1N] +Filter_2N_day_count[row_2N] )
count_n = count_n + 1
N_MJ_filter_1N_2N = count_n -1
#1N to 2N
###################____________________HOOOD
# for Phase
MJ_Phase_1H_to_2_comon = []
MJ_Phase_2H_to_1_comon = []
Day_count_MJ_Phase_1H_2H = []
count_n = 0
for row_1H, hh_1H in enumerate(HH_1H):
if hh_1H == str(-1):
break
for row_2H, hh_2H in enumerate(HH_2H):
if hh_1H == hh_2H:
MJ_Phase_1H_to_2_comon.append(Mj_1H_Phase[row_1H])
MJ_Phase_2H_to_1_comon.append(Mj_2H_Phase[row_2H])
Day_count_MJ_Phase_1H_2H.append(Phase_1H_day_count[row_1H] +Phase_2H_day_count[row_2H] )
count_n = count_n + 1
N_MJ_Phase_1H_2H = count_n -1
#for filter
MJ_filter_1H_to_2_comon = []
MJ_filter_2H_to_1_comon = []
Day_count_MJ_filter_1H_2H = []
count_n = 0
for row_1H, hh_1H in enumerate(HH_1H):
if hh_1H == str(-1):
break
for row_2H, hh_2H in enumerate(HH_2H):
if hh_1H == hh_2H:
MJ_filter_1H_to_2_comon.append(Mj_filter_1H_Phase[row_1H])
MJ_filter_2H_to_1_comon.append(Mj_filter_2H_Phase[row_2H])
Day_count_MJ_filter_1H_2H.append(Filter_1H_day_count[row_1H] +Filter_2H_day_count[row_2H] )
count_n = count_n + 1
N_MJ_filter_1H_2H = count_n -1
#1N to 3N
MJ_Phase_1N_to_3_comon = []
MJ_Phase_3N_to_1_comon = []
Day_count_MJ_Phase_1N_3N = []
count_n = 0
breakme = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == (-1) :
break
for row_3N, hh_3N in enumerate(HH_3N):
if hh_1N == hh_3N:
MJ_Phase_1N_to_3_comon.append(Mj_1N_Phase[row_1N])
MJ_Phase_3N_to_1_comon.append(Mj_3N_Phase[row_3N])
Day_count_MJ_Phase_1N_3N.append(Phase_1N_day_count[row_1N] + Phase_3N_day_count[row_3N])
count_n = count_n + 1
N_MJ_Phase_1N_3N = count_n -1
#for filter
MJ_filter_1N_to_3_comon = []
MJ_filter_3N_to_1_comon = []
Day_count_MJ_filter_1N_3N = []
count_n = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == str(-1):
break
for row_3N, hh_3N in enumerate(HH_3N):
if hh_1N == hh_3N:
MJ_filter_1N_to_3_comon.append(Mj_filter_1N_Phase[row_1N])
MJ_filter_3N_to_1_comon.append(Mj_filter_3N_Phase[row_3N])
Day_count_MJ_filter_1N_3N.append(Filter_1N_day_count[row_1N] +Filter_3N_day_count[row_3N] )
count_n = count_n + 1
N_MJ_filter_1N_3N = count_n -1
#1N to 3N
###################____________________HOOOD
# for Phase
MJ_Phase_1H_to_3_comon = []
MJ_Phase_3H_to_1_comon = []
Day_count_MJ_Phase_1H_3H = []
count_n = 0
breakme = 0
for row_1H, hh_1H in enumerate(HH_1H):
if hh_1H == (-1) :
break
for row_3H, hh_3H in enumerate(HH_3H):
if hh_1H == hh_3H:
MJ_Phase_1H_to_3_comon.append(Mj_1H_Phase[row_1H])
MJ_Phase_3H_to_1_comon.append(Mj_3H_Phase[row_3H])
Day_count_MJ_Phase_1H_3H.append(Phase_1H_day_count[row_1H] + Phase_3H_day_count[row_3H])
count_n = count_n + 1
N_MJ_Phase_1H_3H = count_n -1
#for filter
MJ_filter_1H_to_3_comon = []
MJ_filter_3H_to_1_comon = []
Day_count_MJ_filter_1H_3H = []
count_n = 0
for row_1H, hh_1H in enumerate(HH_1H):
if hh_1H == str(-1):
break
for row_3H, hh_3H in enumerate(HH_3H):
if hh_1H == hh_3H:
MJ_filter_1H_to_3_comon.append(Mj_filter_1H_Phase[row_1H])
MJ_filter_3H_to_1_comon.append(Mj_filter_3H_Phase[row_3H])
Day_count_MJ_filter_1H_3H.append(Filter_1H_day_count[row_1H] +Filter_3H_day_count[row_3H] )
count_n = count_n + 1
N_MJ_filter_1H_3H = count_n -1
#1N to 4N
MJ_Phase_1N_to_4_comon = []
MJ_Phase_4N_to_1_comon = []
Day_count_MJ_Phase_1N_4N = []
count_n = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_1N == hh_4N:
MJ_Phase_1N_to_4_comon.append(Mj_1N_Phase[row_1N])
MJ_Phase_4N_to_1_comon.append(Mj_4N_Phase[row_4N])
Day_count_MJ_Phase_1N_4N.append(Phase_1N_day_count[row_1N] +Phase_4N_day_count[row_4N] )
count_n = count_n + 1
print('length of 1n and 4 n:', len(MJ_Phase_1N_to_4_comon), len(MJ_Phase_4N_to_1_comon) )
N_MJ_Phase_1N_4N = count_n -1
#for filter
MJ_filter_1N_to_4_comon = []
MJ_filter_4N_to_1_comon = []
Day_count_MJ_filter_1N_4N = []
count_n = 0
for row_1N, hh_1N in enumerate(HH_1N):
if hh_1N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_1N == hh_4N:
MJ_filter_1N_to_4_comon.append(Mj_filter_1N_Phase[row_1N])
MJ_filter_4N_to_1_comon.append(Mj_filter_4N_Phase[row_4N])
Day_count_MJ_filter_1N_4N.append(Filter_1N_day_count[row_1N] +Filter_4N_day_count[row_4N] )
count_n = count_n + 1
N_MJ_filter_1N_4N = count_n -1
#2N to 3N
MJ_Phase_2N_to_3_comon = []
MJ_Phase_3N_to_2_comon = []
Day_count_MJ_Phase_2N_3N = []
count_n = 0
for row_2N, hh_2N in enumerate(HH_2N):
if hh_2N == str(-1):
break
for row_3N, hh_3N in enumerate(HH_3N):
if hh_2N == hh_3N:
MJ_Phase_2N_to_3_comon.append(Mj_2N_Phase[row_2N])
MJ_Phase_3N_to_2_comon.append(Mj_3N_Phase[row_3N])
Day_count_MJ_Phase_2N_3N.append(Phase_2N_day_count[row_2N] +Phase_3N_day_count[row_3N] )
print(hh_2N,Mj_2N_Phase[row_2N],hh_3N,Mj_3N_Phase[row_3N])
count_n = count_n + 1
N_MJ_Phase_2N_3N = count_n -1
#for filter
MJ_filter_2N_to_3_comon = []
MJ_filter_3N_to_2_comon = []
Day_count_MJ_filter_2N_3N = []
count_n = 0
for row_2N, hh_2N in enumerate(HH_2N):
if hh_2N == str(-1):
break
for row_3N, hh_3N in enumerate(HH_3N):
if hh_2N == hh_3N:
MJ_filter_2N_to_3_comon.append(Mj_filter_2N_Phase[row_2N])
MJ_filter_3N_to_2_comon.append(Mj_filter_3N_Phase[row_3N])
print(hh_2N,Mj_filter_2N_Phase[row_2N],hh_3N,Mj_filter_3N_Phase[row_3N])
Day_count_MJ_filter_2N_3N.append(Filter_2N_day_count[row_2N] +Filter_3N_day_count[row_3N] )
count_n = count_n + 1
N_MJ_filter_2N_3N = count_n - 1
#2N to 3N
###################____________________HOOOD
# for Phase
MJ_Phase_2H_to_3_comon = []
MJ_Phase_3H_to_2_comon = []
Day_count_MJ_Phase_2H_3H = []
count_n = 0
for row_2H, hh_2H in enumerate(HH_2H):
if hh_2H == str(-1):
break
for row_3H, hh_3H in enumerate(HH_3H):
if hh_2H == hh_3H:
MJ_Phase_2H_to_3_comon.append(Mj_2H_Phase[row_2H])
MJ_Phase_3H_to_2_comon.append(Mj_3H_Phase[row_3H])
Day_count_MJ_Phase_2H_3H.append(Phase_2H_day_count[row_2H] +Phase_3H_day_count[row_3H] )
count_n = count_n + 1
N_MJ_Phase_2H_3H = count_n -1
#for filter
MJ_filter_2H_to_3_comon = []
MJ_filter_3H_to_2_comon = []
Day_count_MJ_filter_2H_3H = []
count_n = 0
for row_2H, hh_2H in enumerate(HH_2H):
if hh_2H == str(-1):
break
for row_3H, hh_3H in enumerate(HH_3H):
if hh_2H == hh_3H:
MJ_filter_2H_to_3_comon.append(Mj_filter_2H_Phase[row_2H])
MJ_filter_3H_to_2_comon.append(Mj_filter_3H_Phase[row_3H])
Day_count_MJ_filter_2H_3H.append(Filter_2H_day_count[row_2H] +Filter_3H_day_count[row_3H] )
count_n = count_n + 1
N_MJ_filter_2H_3H = count_n - 1
#2N to 4N
MJ_Phase_2N_to_4_comon = []
MJ_Phase_4N_to_2_comon = []
Day_count_MJ_Phase_2N_4N = []
count_n = 0
for row_2N, hh_2N in enumerate(HH_2N):
if hh_2N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_2N == hh_4N:
MJ_Phase_2N_to_4_comon.append(Mj_2N_Phase[row_2N])
MJ_Phase_4N_to_2_comon.append(Mj_4N_Phase[row_4N])
Day_count_MJ_Phase_2N_4N.append(Phase_2N_day_count[row_2N] +Phase_4N_day_count[row_4N] )
count_n = count_n + 1
N_MJ_Phase_2N_4N = count_n -1
#for filter
MJ_filter_2N_to_4_comon = []
MJ_filter_4N_to_2_comon = []
Day_count_MJ_filter_2N_4N = []
count_n = 0
for row_2N, hh_2N in enumerate(HH_2N):
if hh_2N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_2N == hh_4N:
MJ_filter_2N_to_4_comon.append(Mj_filter_2N_Phase[row_2N])
MJ_filter_4N_to_2_comon.append(Mj_filter_4N_Phase[row_4N])
Day_count_MJ_filter_2N_4N.append(Filter_2N_day_count[row_2N] +Filter_4N_day_count[row_4N] )
count_n = count_n + 1
N_MJ_filter_2N_4N = count_n - 1
#3N to 4N
MJ_Phase_3N_to_4_comon = []
MJ_Phase_4N_to_3_comon = []
Day_count_MJ_Phase_3N_4N = []
count_n = 0
for row_3N, hh_3N in enumerate(HH_3N):
if hh_3N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_3N == hh_4N:
MJ_Phase_3N_to_4_comon.append(Mj_3N_Phase[row_3N])
MJ_Phase_4N_to_3_comon.append(Mj_4N_Phase[row_4N])
Day_count_MJ_Phase_3N_4N.append(Phase_3N_day_count[row_3N] +Phase_4N_day_count[row_4N] )
count_n = count_n + 1
N_MJ_Phase_3N_4N = count_n -1
#for filter
MJ_filter_3N_to_4_comon = []
MJ_filter_4N_to_3_comon = []
Day_count_MJ_filter_3N_4N = []
count_n = 0
for row_3N, hh_3N in enumerate(HH_3N):
if hh_3N == str(-1):
break
for row_4N, hh_4N in enumerate(HH_4N):
if hh_3N == hh_4N:
MJ_filter_3N_to_4_comon.append(Mj_filter_3N_Phase[row_3N])
MJ_filter_4N_to_3_comon.append(Mj_filter_4N_Phase[row_4N])
Day_count_MJ_filter_3N_4N.append(Filter_3N_day_count[row_3N] +Filter_4N_day_count[row_4N] )
count_n = count_n + 1
N_MJ_filter_3N_4N = count_n - 1
T_stat_1N_2N, P_val_1N_2N = scipy.stats.ttest_ind(MJ_Phase_1N_to_2_comon,MJ_Phase_2N_to_1_comon, axis=0, equal_var=True)
degree_1N_2N = (N_MJ_Phase_1N_2N -1) *Level_of_confidence
if degree_1N_2N < abs(T_stat_1N_2N):
print('1N and 2N Phase rejects the null', T_stat_1N_2N,'P-value', P_val_1N_2N,'Sample size N', N_MJ_Phase_1N_2N)
else:
print('1N and 2N Phase accepts the null', T_stat_1N_2N,'P-value', P_val_1N_2N,'Sample size N', N_MJ_Phase_1N_2N)
T_sign_1N_2N, P_sign_1N_2N = scipy.stats.wilcoxon(MJ_Phase_1N_to_2_comon, MJ_Phase_2N_to_1_comon)
T_stat_1N_2N_filter, P_val_1N_2N_filter = scipy.stats.ttest_ind(MJ_filter_1N_to_2_comon,MJ_filter_2N_to_1_comon, axis=0, equal_var=True)
degree_1N_2N_filter = (N_MJ_filter_1N_2N -1) *Level_of_confidence
if degree_1N_2N_filter < abs(T_stat_1N_2N_filter):
print('1N and 2N Filter rejects the null', T_stat_1N_2N_filter,'P-value', P_val_1N_2N_filter,'Sample size N', N_MJ_filter_1N_2N)
else:
print('1N and 2N Filter accepts the null', T_stat_1N_2N_filter,'P-value', P_val_1N_2N_filter,'Sample size N', N_MJ_filter_1N_2N)
T_sign_1N_2N_filter, P_sign_1N_2N_filter = scipy.stats.wilcoxon(MJ_filter_1N_to_2_comon, MJ_filter_2N_to_1_comon)
# 1n to 2n HOOOOOOD
T_stat_1H_2H, P_val_1H_2H = scipy.stats.ttest_ind(MJ_Phase_1H_to_2_comon,MJ_Phase_2H_to_1_comon, axis=0, equal_var=True)
degree_1H_2H = (N_MJ_Phase_1H_2H -1) *Level_of_confidence
if degree_1H_2H < abs(T_stat_1H_2H):
print('1H and 2H Phase rejects the null', T_stat_1H_2H,'P-value', P_val_1H_2H,'Sample size N', N_MJ_Phase_1H_2H)
else:
print('1H and 2H Phase accepts the null', T_stat_1H_2H,'P-value', P_val_1H_2H,'Sample size N', N_MJ_Phase_1H_2H)
T_sign_1H_2H, P_sign_1H_2H = scipy.stats.wilcoxon(MJ_Phase_1H_to_2_comon, MJ_Phase_2H_to_1_comon)
T_stat_1H_2H_filter, P_val_1H_2H_filter = scipy.stats.ttest_ind(MJ_filter_1H_to_2_comon,MJ_filter_2H_to_1_comon, axis=0, equal_var=True)
degree_1H_2H_filter = (N_MJ_filter_1H_2H -1) *Level_of_confidence
if degree_1H_2H_filter < abs(T_stat_1H_2H_filter):
print('1H and 2H Filter rejects the null', T_stat_1H_2H_filter,'P-value', P_val_1H_2H_filter,'Sample size N', N_MJ_filter_1H_2H)
else:
print('1H and 2H Filter accepts the null', T_stat_1H_2H_filter,'P-value', P_val_1H_2H_filter,'Sample size N', N_MJ_filter_1H_2H)
T_sign_1H_2H_filter, P_sign_1H_2H_filter = scipy.stats.wilcoxon(MJ_filter_1H_to_2_comon, MJ_filter_2H_to_1_comon)
T_stat_1N_3N, P_val_1N_3N = scipy.stats.ttest_ind(MJ_Phase_1N_to_3_comon,MJ_Phase_3N_to_1_comon, axis=0, equal_var=True)
degree_1N_3N = (N_MJ_Phase_1N_3N -1) *Level_of_confidence
if degree_1N_3N < abs(T_stat_1N_3N):
print('1N and 3N Phase rejects the null', T_stat_1N_3N,'P-value', P_val_1N_3N,'Sample size N', N_MJ_Phase_1N_3N)
else:
print('1N and 3N Phase accepts the null', T_stat_1N_3N,'P-value', P_val_1N_3N,'Sample size N', N_MJ_Phase_1N_3N)
T_sign_1N_3N, P_sign_1N_3N = scipy.stats.wilcoxon(MJ_Phase_1N_to_3_comon, MJ_Phase_3N_to_1_comon)
T_stat_1N_3N_filter, P_val_1N_3N_filter = scipy.stats.ttest_ind(MJ_filter_1N_to_3_comon,MJ_filter_3N_to_1_comon, axis=0, equal_var=True)
degree_1N_3N_filter = (N_MJ_filter_1N_3N -1) *Level_of_confidence
if degree_1N_3N_filter < abs(T_stat_1N_3N_filter):
print('1N and 3N Filter rejects the null', T_stat_1N_3N_filter,'P-value', P_val_1N_3N_filter,'Sample size N', N_MJ_filter_1N_3N)
else:
print('1N and 3N Filter accepts the null', T_stat_1N_3N_filter,'P-value', P_val_1N_3N_filter,'Sample size N', N_MJ_filter_1N_3N)
T_sign_1N_3N_filter, P_sign_1N_3N_filter = scipy.stats.wilcoxon(MJ_filter_1N_to_3_comon, MJ_filter_3N_to_1_comon)
# 1n to 3n HOOOOOOD
T_stat_1H_3H, P_val_1H_3H = scipy.stats.ttest_ind(MJ_Phase_1H_to_3_comon,MJ_Phase_3H_to_1_comon, axis=0, equal_var=True)
degree_1H_3H = (N_MJ_Phase_1H_3H -1) *Level_of_confidence
if degree_1H_3H < abs(T_stat_1H_3H):
print('1H and 3H Phase rejects the null', T_stat_1H_3H,'P-value', P_val_1H_3H,'Sample size N', N_MJ_Phase_1H_3H)
else:
print('1H and 3H Phase accepts the null', T_stat_1H_3H,'P-value', P_val_1H_3H,'Sample size N', N_MJ_Phase_1H_3H)
T_sign_1H_3H, P_sign_1H_3H = scipy.stats.wilcoxon(MJ_Phase_1H_to_3_comon, MJ_Phase_3H_to_1_comon)
T_stat_1H_3H_filter, P_val_1H_3H_filter = scipy.stats.ttest_ind(MJ_filter_1H_to_3_comon,MJ_filter_3H_to_1_comon, axis=0, equal_var=True)
degree_1H_3H_filter = (N_MJ_filter_1H_3H -1) *Level_of_confidence
if degree_1H_3H_filter < abs(T_stat_1H_3H_filter):
print('1H and 3H Filter rejects the null', T_stat_1H_3H_filter,'P-value', P_val_1H_3H_filter,'Sample size N', N_MJ_filter_1H_3H)
else:
print('1H and 3H Filter accepts the null', T_stat_1H_3H_filter,'P-value', P_val_1H_3H_filter,'Sample size N', N_MJ_filter_1H_3H)
T_sign_1H_3H_filter, P_sign_1H_3H_filter = scipy.stats.wilcoxon(MJ_filter_1H_to_3_comon, MJ_filter_3H_to_1_comon)
T_stat_1N_4N, P_val_1N_4N = scipy.stats.ttest_ind(MJ_Phase_1N_to_4_comon,MJ_Phase_4N_to_1_comon, axis=0, equal_var=True)
degree_1N_4N = (N_MJ_Phase_1N_4N -1) *Level_of_confidence
if degree_1N_4N < abs(T_stat_1N_4N):
print('1N and 4N Phase rejects the null', T_stat_1N_4N,'P-value', P_val_1N_4N,'Sample size N', N_MJ_Phase_1N_4N)
else:
print('1N and 4N Phase accepts the null', T_stat_1N_4N,'P-value', P_val_1N_4N,'Sample size N', N_MJ_Phase_1N_4N)
T_sign_1N_4N, P_sign_1N_4N = scipy.stats.wilcoxon(MJ_Phase_1N_to_4_comon, MJ_Phase_4N_to_1_comon)
T_stat_1N_4N_filter, P_val_1N_4N_filter = scipy.stats.ttest_ind(MJ_filter_1N_to_4_comon,MJ_filter_4N_to_1_comon, axis=0, equal_var=True)
degree_1N_4N_filter = (N_MJ_filter_1N_4N -1) *Level_of_confidence
if degree_1N_4N_filter < abs(T_stat_1N_4N_filter):
print('1N and 4N Filter rejects the null', T_stat_1N_4N_filter,'P-value', P_val_1N_4N_filter,'Sample size N', N_MJ_filter_1N_4N)
else:
print('1N and 4N Filter accepts the null', T_stat_1N_4N_filter,'P-value', P_val_1N_4N_filter,'Sample size N', N_MJ_filter_1N_4N)
T_sign_1N_4N_filter, P_sign_1N_4N_filter = scipy.stats.wilcoxon(MJ_filter_1N_to_4_comon, MJ_filter_4N_to_1_comon)
T_stat_2N_3N, P_val_2N_3N = scipy.stats.ttest_ind(MJ_Phase_2N_to_3_comon,MJ_Phase_3N_to_2_comon, axis=0, equal_var=True)
degree_2N_3N = (N_MJ_Phase_2N_3N -1) *Level_of_confidence
if degree_2N_3N < abs(T_stat_2N_3N):
print('2N and 3N Phase rejects the null', T_stat_2N_3N,'P-value', P_val_2N_3N,'Sample size N', N_MJ_Phase_2N_3N)
else:
print('2N and 3N Phase accepts the null', T_stat_2N_3N,'P-value', P_val_2N_3N,'Sample size N', N_MJ_Phase_2N_3N)
T_sign_2N_3N, P_sign_2N_3N = scipy.stats.wilcoxon(MJ_Phase_2N_to_3_comon, MJ_Phase_3N_to_2_comon)
T_stat_2N_3N_filter, P_val_2N_3N_filter = scipy.stats.ttest_ind(MJ_filter_2N_to_3_comon,MJ_filter_3N_to_2_comon, axis=0, equal_var=True)
degree_2N_3N_filter = (N_MJ_filter_2N_3N -1) *Level_of_confidence
if degree_2N_3N_filter < abs(T_stat_2N_3N_filter):
print('2N and 3N Filter rejects the null', T_stat_2N_3N_filter,'P-value', P_val_2N_3N_filter,'Sample size N', N_MJ_filter_2N_3N)
else:
print('2N and 3N Filter accepts the null', T_stat_2N_3N_filter,'P-value', P_val_2N_3N_filter,'Sample size N', N_MJ_filter_2N_3N)
T_sign_2N_3N_filter, P_sign_2N_3N_filter = scipy.stats.wilcoxon(MJ_filter_2N_to_3_comon, MJ_filter_3N_to_2_comon)
# 2n to 3n HOOOOOOD
T_stat_2H_3H, P_val_2H_3H = scipy.stats.ttest_ind(MJ_Phase_2H_to_3_comon,MJ_Phase_3H_to_2_comon, axis=0, equal_var=True)
degree_2H_3H = (N_MJ_Phase_2H_3H -1) *Level_of_confidence
if degree_2H_3H < abs(T_stat_2H_3H):
print('2H and 3H Phase rejects the null', T_stat_2H_3H,'P-value', P_val_2H_3H,'Sample size N', N_MJ_Phase_2H_3H)
else:
print('2H and 3H Phase accepts the null', T_stat_2H_3H,'P-value', P_val_2H_3H,'Sample size N', N_MJ_Phase_2H_3H)
T_sign_2H_3H, P_sign_2H_3H = scipy.stats.wilcoxon(MJ_Phase_2H_to_3_comon, MJ_Phase_3H_to_2_comon)
T_stat_2H_3H_filter, P_val_2H_3H_filter = scipy.stats.ttest_ind(MJ_filter_2H_to_3_comon,MJ_filter_3H_to_2_comon, axis=0, equal_var=True)
degree_2H_3H_filter = (N_MJ_filter_2H_3H -1) *Level_of_confidence
if degree_2H_3H_filter < abs(T_stat_2H_3H_filter):
print('2H and 3H Filter rejects the null', T_stat_2H_3H_filter,'P-value', P_val_2H_3H_filter,'Sample size N', N_MJ_filter_2H_3H)
else:
print('2H and 3H Filter accepts the null', T_stat_2H_3H_filter,'P-value', P_val_2H_3H_filter,'Sample size N', N_MJ_filter_2H_3H)
T_sign_2H_3H_filter, P_sign_2H_3H_filter = scipy.stats.wilcoxon(MJ_filter_2H_to_3_comon, MJ_filter_3H_to_2_comon)
#2N to 4N
T_stat_2N_4N, P_val_2N_4N = scipy.stats.ttest_ind(MJ_Phase_2N_to_4_comon,MJ_Phase_4N_to_2_comon, axis=0, equal_var=True)
degree_2N_4N = (N_MJ_Phase_2N_4N -1) *Level_of_confidence
if degree_2N_4N < abs(T_stat_2N_4N):
print('2N and 4N Phase rejects the null', T_stat_2N_4N,'P-value', P_val_2N_4N,'Sample size N', N_MJ_Phase_2N_4N)
else:
print('2N and 4N Phase accepts the null', T_stat_2N_4N,'P-value', P_val_2N_4N,'Sample size N', N_MJ_Phase_2N_4N)
T_sign_2N_4N, P_sign_2N_4N = scipy.stats.wilcoxon(MJ_Phase_2N_to_4_comon, MJ_Phase_4N_to_2_comon)
T_stat_2N_4N_filter, P_val_2N_4N_filter = scipy.stats.ttest_ind(MJ_filter_2N_to_4_comon,MJ_filter_4N_to_2_comon, axis=0, equal_var=True)
degree_2N_4N_filter = (N_MJ_filter_2N_4N -1) *Level_of_confidence
if degree_2N_4N_filter < abs(T_stat_2N_4N_filter):
print('2N and 4N Filter rejects the null', T_stat_2N_4N_filter,'P-value', P_val_2N_4N_filter,'Sample size N', N_MJ_filter_2N_4N)
else:
print('2N and 4N Filter accepts the null', T_stat_2N_4N_filter,'P-value', P_val_2N_4N_filter,'Sample size N', N_MJ_filter_2N_4N)
T_sign_2N_4N_filter, P_sign_2N_4N_filter = scipy.stats.wilcoxon(MJ_filter_2N_to_4_comon, MJ_filter_4N_to_2_comon)
#3N to 4N
T_stat_3N_4N, P_val_3N_4N = scipy.stats.ttest_ind(MJ_Phase_3N_to_4_comon,MJ_Phase_4N_to_3_comon, axis=0, equal_var=True)
degree_3N_4N = (N_MJ_Phase_3N_4N -1) *Level_of_confidence
if degree_3N_4N < abs(T_stat_3N_4N):
print('3N and 4N Phase rejects the null', T_stat_3N_4N,'P-value', P_val_3N_4N,'Sample size N', N_MJ_Phase_3N_4N)
else:
print('3N and 4N Phase accepts the null', T_stat_3N_4N,'P-value', P_val_3N_4N,'Sample size N', N_MJ_Phase_3N_4N)
T_sign_3N_4N, P_sign_3N_4N = scipy.stats.wilcoxon(MJ_Phase_3N_to_4_comon, MJ_Phase_4N_to_3_comon)
T_stat_3N_4N_filter, P_val_3N_4N_filter = scipy.stats.ttest_ind(MJ_filter_3N_to_4_comon,MJ_filter_4N_to_3_comon, axis=0, equal_var=True)
degree_3N_4N_filter = (N_MJ_filter_3N_4N -1) *Level_of_confidence
if degree_3N_4N_filter < abs(T_stat_3N_4N_filter):
print('3N and 4N Filter rejects the null', T_stat_3N_4N_filter,'P-value', P_val_3N_4N_filter,'Sample size N', N_MJ_filter_3N_4N)
else:
print('3N and 4N Filter accepts the null', T_stat_3N_4N_filter,'P-value', P_val_3N_4N_filter,'Sample size N', N_MJ_filter_3N_4N)
T_sign_3N_4N_filter, P_sign_3N_4N_filter = scipy.stats.wilcoxon(MJ_filter_3N_to_4_comon, MJ_filter_4N_to_3_comon)
whole_t_stat = [T_stat_1N_2N, T_stat_1N_3N, T_stat_1N_4N, T_stat_2N_3N, T_stat_3N_4N,T_stat_2N_4N]
whole_p_test = [P_val_1N_2N,P_val_1N_3N,P_val_1N_4N,P_val_2N_3N,P_val_3N_4N,P_val_2N_4N]
Whole_sample = [N_MJ_Phase_1N_2N, N_MJ_Phase_1N_3N, N_MJ_Phase_1N_4N, N_MJ_Phase_2N_3N, N_MJ_Phase_3N_4N,N_MJ_Phase_2N_4N]
Whole_degree = [degree_1N_2N, degree_1N_3N, degree_1N_4N, degree_2N_3N, degree_3N_4N, degree_2N_4N]
Whole_sighn_t_stat = [T_sign_1N_2N,T_sign_1N_3N,T_sign_1N_4N,T_sign_2N_3N,T_sign_3N_4N,T_sign_2N_4N]
Whole_sighn_p_test = [P_sign_1N_2N,P_sign_1N_3N,P_sign_1N_4N,P_sign_2N_3N,P_sign_3N_4N, P_sign_3N_4N]
STD_1 = [np.std(MJ_Phase_1N_to_2_comon), np.std(MJ_Phase_1N_to_3_comon),np.std(MJ_Phase_1N_to_4_comon),np.std(MJ_Phase_2N_to_3_comon),np.std(MJ_Phase_3N_to_4_comon),np.std(MJ_Phase_2N_to_4_comon)]
Median_1 = [stat.median(MJ_Phase_1N_to_2_comon), stat.median(MJ_Phase_1N_to_3_comon),stat.median(MJ_Phase_1N_to_4_comon),stat.median(MJ_Phase_2N_to_3_comon),stat.median(MJ_Phase_3N_to_4_comon), stat.median(MJ_Phase_2N_to_4_comon)]
Mean_1 = [np.average(MJ_Phase_1N_to_2_comon),np.average(MJ_Phase_1N_to_3_comon),np.average(MJ_Phase_1N_to_4_comon),np.average(MJ_Phase_2N_to_3_comon),np.average(MJ_Phase_3N_to_4_comon),np.average(MJ_Phase_2N_to_4_comon)]
STD_2 = [np.std(MJ_Phase_2N_to_1_comon), np.std(MJ_Phase_3N_to_1_comon),np.std(MJ_Phase_4N_to_1_comon),np.std(MJ_Phase_3N_to_2_comon),np.std(MJ_Phase_4N_to_3_comon),np.std(MJ_Phase_4N_to_2_comon)]
Median_2 = [stat.median(MJ_Phase_2N_to_1_comon), stat.median(MJ_Phase_3N_to_1_comon),stat.median(MJ_Phase_4N_to_1_comon),stat.median(MJ_Phase_3N_to_2_comon),stat.median(MJ_Phase_4N_to_3_comon),stat.median(MJ_Phase_4N_to_2_comon)]
Mean_2 = [np.average(MJ_Phase_2N_to_1_comon),np.average(MJ_Phase_3N_to_1_comon),np.average(MJ_Phase_4N_to_1_comon),np.average(MJ_Phase_3N_to_2_comon),np.average(MJ_Phase_4N_to_3_comon),np.average(MJ_Phase_4N_to_2_comon)]
No_hood_percent_days_Filtered = [sum(Filter_1N_day_count)/sum(Phase_1N_day_count),sum(Filter_2N_day_count)/sum(Phase_2N_day_count),sum(Filter_3N_day_count)/sum(Phase_3N_day_count),sum(Filter_4N_day_count)/sum(Phase_4N_day_count) ]
hood_percent_days_Filtered = [sum(Filter_1H_day_count)/sum(Phase_1H_day_count),sum(Filter_2H_day_count)/sum(Phase_2H_day_count),sum(Filter_3H_day_count)/sum(Phase_3H_day_count)]
Hood_percentage = {'Phase':['1H','2H','3H'], 'Percentatges of hood filter':hood_percent_days_Filtered}
No_Hood_percentage = {'Phase':['1N','2N','3N','4N'],'Percentatges of No hood filter':No_hood_percent_days_Filtered}
df_percent_hood = pd.DataFrame(Hood_percentage)
df_percent_No_hood = pd.DataFrame(No_Hood_percentage)
whole_t_stat_H = [T_stat_1H_2H, T_stat_1H_3H, T_stat_2H_3H]
whole_p_test_H = [P_val_1H_2H,P_val_1H_3H,P_val_2H_3H]
Whole_sample_H = [N_MJ_Phase_1H_2H, N_MJ_Phase_1H_3H,N_MJ_Phase_2H_3H]
Whole_degree_H = [degree_1H_2H, degree_1H_3H, degree_2H_3H]
Whole_sighn_t_stat_H = [T_sign_1H_2H,T_sign_1H_3H,T_sign_2H_3H]
Whole_sighn_p_test_H = [P_sign_1H_2H,P_sign_1H_3H,P_sign_2H_3H]
STD_1_H = [np.std(MJ_Phase_1H_to_2_comon), np.std(MJ_Phase_1H_to_3_comon),np.std(MJ_Phase_2H_to_3_comon)]
Median_1_H = [stat.median(MJ_Phase_1H_to_2_comon), stat.median(MJ_Phase_1H_to_3_comon),stat.median(MJ_Phase_2H_to_3_comon)]
Mean_1_H = [np.average(MJ_Phase_1H_to_2_comon),np.average(MJ_Phase_1H_to_3_comon),np.average(MJ_Phase_2H_to_3_comon)]
STD_2_H = [np.std(MJ_Phase_2H_to_1_comon), np.std(MJ_Phase_3H_to_1_comon),np.std(MJ_Phase_3H_to_2_comon)]
Median_2_H = [stat.median(MJ_Phase_2H_to_1_comon), stat.median(MJ_Phase_3H_to_1_comon),stat.median(MJ_Phase_3H_to_2_comon)]
Mean_2_H = [np.average(MJ_Phase_2H_to_1_comon),np.average(MJ_Phase_3H_to_1_comon),np.average(MJ_Phase_3H_to_2_comon)]
Non_filtered_no_hood = {'Phase':['1n-2N','1n-3n','1n-4n','2n-3n', '3n-4n','2n-4n'],'T-statistic':whole_t_stat, 'P Value':whole_p_test,
'T-statistic-Sign-Test':Whole_sighn_t_stat, 'P Vaue-Sign Test':Whole_sighn_p_test,
'Deggree of Confidence':Whole_degree, 'Sample Size':Whole_sample,'Std _1':STD_1,'median _1':Median_1,'mean _1':Mean_1,'Std _2':STD_2,'median _2':Median_2,'mean _2':Mean_2 }
df_Non_filtered_no_hood = pd.DataFrame(Non_filtered_no_hood, columns=['Phase','T-statistic','P Value','T-statistic-Sign-Test',
'P Vaue-Sign Test','Deggree of Confidence','Sample Size', 'Std _1','median _1','mean _1','Std _2','median _2','mean _2'])
Non_filtered_hood = {'Phase _Hood':['1H-2H','1H-3H','2H-3H'],'T-statistic':whole_t_stat_H, 'P Value':whole_p_test_H,
'T-statistic-Sign-Test':Whole_sighn_t_stat_H, 'P Vaue-Sign Test':Whole_sighn_p_test_H,
'Deggree of Confidence':Whole_degree_H, 'Sample Size':Whole_sample_H,'Std _1':STD_1_H,'median _1':Median_1_H,'mean _1':Mean_1_H,'Std _2':STD_2_H,'median _2':Median_2_H,'mean _2':Mean_2_H }
df_Non_filtered_hood = pd.DataFrame(Non_filtered_hood, columns=['Phase _Hood','T-statistic','P Value','T-statistic-Sign-Test',
'P Vaue-Sign Test','Deggree of Confidence','Sample Size', 'Std _1','median _1','mean _1','Std _2','median _2','mean _2'])
whole_t_stat_filter = [T_stat_1N_2N_filter, T_stat_1N_3N_filter, T_stat_1N_4N_filter, T_stat_2N_3N_filter, T_stat_3N_4N_filter, T_stat_2N_4N_filter]
whole_p_test_filter = [P_val_1N_2N_filter,P_val_1N_3N_filter,P_val_1N_4N_filter,P_val_2N_3N_filter,P_val_3N_4N_filter, P_val_2N_4N_filter]
Whole_sample_filter = [N_MJ_Phase_1N_2N, N_MJ_Phase_1N_3N, N_MJ_Phase_1N_4N, N_MJ_Phase_2N_3N, N_MJ_Phase_3N_4N, N_MJ_Phase_2N_4N]
Whole_degree_filter = [degree_1N_2N, degree_1N_3N, degree_1N_4N, degree_2N_3N, degree_3N_4N, degree_2N_4N]
Whole_sighn_t_stat_filter = [T_sign_1N_2N_filter,T_sign_1N_3N_filter,T_sign_1N_4N_filter,T_sign_2N_3N_filter,T_sign_3N_4N_filter,T_sign_2N_4N_filter]
Whole_sighn_p_test_filter = [P_sign_1N_2N_filter ,P_sign_1N_3N_filter,P_sign_1N_4N_filter,P_sign_2N_3N_filter,P_sign_3N_4N_filter,P_sign_2N_4N_filter]
whole_t_stat_filter_H = [T_stat_1H_2H_filter, T_stat_1H_3H_filter, T_stat_2H_3H_filter]
whole_p_test_filter_H = [P_val_1H_2H_filter,P_val_1H_3H_filter,P_val_2H_3H_filter]
Whole_sample_filter_H = [N_MJ_Phase_1H_2H, N_MJ_Phase_1H_3H, N_MJ_Phase_2H_3H]
Whole_degree_filter_H = [degree_1H_2H, degree_1H_3H, degree_2H_3H]
Whole_sighn_t_stat_filter_H = [T_sign_1H_2H_filter,T_sign_1H_3H_filter,T_sign_2H_3H_filter]
Whole_sighn_p_test_filter_H = [P_sign_1H_2H_filter ,P_sign_1H_3H_filter,P_sign_2H_3H_filter]
filtered_No_hood = {'Phase Filtered ':['1n-2N - Filter','1n-3n - Filter','1n-4n - Filter','2n-3n - Filter', '3n-4n - Filter','2n-4n - Filter'],'T-statistic':whole_t_stat_filter, 'P Value':whole_p_test_filter,
'T-statistic-Sign-Test':Whole_sighn_t_stat_filter, 'P Vaue-Sign Test':Whole_sighn_p_test_filter,
'Deggree of Confidence':Whole_degree_filter, 'Sample Size':Whole_sample_filter }
df_filtered_No_hood = pd.DataFrame(filtered_No_hood, columns=['Phase Filtered ' ,'T-statistic','P Value','T-statistic-Sign-Test',
'P Vaue-Sign Test','Deggree of Confidence','Sample Size'])
filtered_hood = {'Phase Filtered HOOD':['1H-2H - Filter','1H-3H - Filter','2H-3H - Filter'],'T-statistic':whole_t_stat_filter_H, 'P Value':whole_p_test_filter_H,
'T-statistic-Sign-Test':Whole_sighn_t_stat_filter_H, 'P Vaue-Sign Test':Whole_sighn_p_test_filter_H,
'Deggree of Confidence':Whole_degree_filter_H, 'Sample Size':Whole_sample_filter_H }
df_filtered_hood = pd.DataFrame(filtered_hood, columns=['Phase Filtered HOOD' ,'T-statistic','P Value','T-statistic-Sign-Test',
'P Vaue-Sign Test','Deggree of Confidence','Sample Size'])
Kj_per_sae_no_hood = {'median':[np.median(Mj_1N_Phase),np.median(Mj_2N_Phase),np.median(Mj_3N_Phase),np.median(Mj_4N_Phase)],
'Phase':['1n','2n','3n','4n']}
df_Kj_per_sae_no_hood = pd.DataFrame(Kj_per_sae_no_hood)
print(' this is the median filter for 1N----=-==-=-=-=-=-=-=-',np.mean(Mj_filter_1N_Phase) )
Kj_per_sae_filter_no_hood = {'median filter':[np.median(Mj_filter_1N_Phase),np.median(Mj_filter_2N_Phase),np.median(Mj_filter_3N_Phase),np.median(Mj_filter_4N_Phase)],
'Phase':['1n','2n','3n','4n']}
df_Kj_per_sae_filter_no_hood = pd.DataFrame(Kj_per_sae_filter_no_hood)
Kj_per_sae_mean_filter_no_hood = {'Mean filter':[np.mean(Mj_filter_1N_Phase),np.mean(Mj_filter_2N_Phase),np.mean(Mj_filter_3N_Phase),np.mean(Mj_filter_4N_Phase)],
'Phase':['1n','2n','3n','4n']}
df_Kj_per_sae_mean_filter_no_hood = pd.DataFrame(Kj_per_sae_mean_filter_no_hood)
Kj_per_sae_mean_no_hood = {'mean':[np.mean(Mj_1N_Phase),np.mean(Mj_2N_Phase),np.mean(Mj_3N_Phase),np.mean(Mj_4N_Phase)],
'Phase':['1n','2n','3n','4n']}
df_Kj_per_sae_mean_no_hood = pd.DataFrame(Kj_per_sae_mean_no_hood)
###hood
print('Hood section')
Kj_per_sae_Hood = {'median':[np.median(Mj_1H_Phase),np.median(Mj_2H_Phase),np.median(Mj_3H_Phase)],
'Phase':['1H','2H','3H']}
df_Kj_per_sae_Hood = pd.DataFrame(Kj_per_sae_Hood)
Kj_per_sae_filter_Hood = {'median filter':[np.median(Mj_filter_1H_Phase),np.median(Mj_filter_2H_Phase),np.median(Mj_filter_3H_Phase)],
'Phase':['1H','2H','3H']}
df_Kj_per_sae_filter_Hood = pd.DataFrame(Kj_per_sae_filter_Hood)
Kj_per_sae_mean_filter_Hood = {'Mean filter':[np.mean(Mj_filter_1H_Phase),np.mean(Mj_filter_2H_Phase),np.mean(Mj_filter_3H_Phase)],
'Phase':['1H','2H','3H']}
df_Kj_per_mean_filter_Hood = pd.DataFrame(Kj_per_sae_mean_filter_Hood)
Kj_per_sae_mean_Hood = {'mean':[np.mean(Mj_1H_Phase),np.mean(Mj_2H_Phase),np.mean(Mj_3H_Phase)],
'Phase':['1H','2H','3H']}
df_Kj_per_sae_mean_Hood = pd.DataFrame(Kj_per_sae_mean_Hood)
pATH = "C:/Users/gvros/Box/OSU, CSC, CQC Project files/P_TEST_NO_HOOD_MJ_DAY_CHECH 2N_3N.csv"
df_Non_filtered_no_hood.to_csv(pATH, index=False,mode='a')
df_filtered_No_hood.to_csv(pATH, index=False,mode='a')
df_Non_filtered_hood.to_csv(pATH, index=False,mode='a')
df_filtered_hood.to_csv(pATH, index=False,mode='a')
df_percent_hood.to_csv(pATH, index=False,mode='a')
df_percent_No_hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_no_hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_filter_no_hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_mean_filter_no_hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_mean_no_hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_Hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_filter_Hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_sae_mean_Hood.to_csv(pATH, index=False,mode='a')
df_Kj_per_mean_filter_Hood.to_csv(pATH, index=False,mode='a')
MJ_Phase_1N_to_3_comon
Mj_filter_3N_Phase
| 49.159705 | 230 | 0.735681 | 8,082 | 40,016 | 3.136105 | 0.02487 | 0.055512 | 0.011047 | 0.015466 | 0.920264 | 0.826915 | 0.752111 | 0.659631 | 0.57228 | 0.494989 | 0 | 0.065897 | 0.147491 | 40,016 | 813 | 231 | 49.220172 | 0.677083 | 0.041109 | 0 | 0.297297 | 0 | 0.006757 | 0.104736 | 0.008865 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.013514 | 0 | 0.013514 | 0.069257 | 0 | 0 | 0 | null | 0 | 0 | 0 | 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 | 3 |
877f631146ad69921013186190b9d5db6822a9f0 | 1,088 | py | Python | build/lib/abp/openai/wrappers/reward_wrapper.py | LinearZoetrope/abp | 2459c1b4d77606c1d70715ce8378d738ba102f37 | [
"MIT"
] | null | null | null | build/lib/abp/openai/wrappers/reward_wrapper.py | LinearZoetrope/abp | 2459c1b4d77606c1d70715ce8378d738ba102f37 | [
"MIT"
] | 9 | 2018-11-14T23:35:05.000Z | 2019-05-22T18:31:30.000Z | build/lib/abp/openai/wrappers/reward_wrapper.py | Zaerei/abp | 2459c1b4d77606c1d70715ce8378d738ba102f37 | [
"MIT"
] | 1 | 2018-11-14T22:34:09.000Z | 2018-11-14T22:34:09.000Z | from gym import Wrapper
import inspect
import logging
from functools import partial
logger = logging.getLogger(__name__)
class RewardWrapper(Wrapper):
"""
Adds support for reward decomposition of the environment.
To support reward decompisition the environment has to return reward as a list of dictionary values
Example:
[
{
"id": "unique ID of the type",
"value": integer value indicating the reward got for this type,
"description": description of the type (Can be used for explanation)
}
]
By default returns decomposed reward. It can be turned off by setting decompose_reward = False
"""
def __init__(self, env):
super(RewardWrapper, self).__init__(env)
def step(self, action, decompose_reward = True):
#TODO THIS DOES NOT WORK!!!!
args , _ = inspect.getargspec(self.unwrapped._step, )
if "decompose_reward" in args:
self.unwrapped._step = partial(self.unwrapped._step, decompose_reward = decompose_reward)
return self.env.step(action)
| 29.405405 | 103 | 0.67739 | 133 | 1,088 | 5.383459 | 0.533835 | 0.104749 | 0.071229 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.248162 | 1,088 | 36 | 104 | 30.222222 | 0.875306 | 0.448529 | 0 | 0 | 0 | 0 | 0.02952 | 0 | 0 | 0 | 0 | 0.027778 | 0 | 1 | 0.153846 | false | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
878d95a107f2258d9e8294a80a09f8cc1dd09451 | 6,157 | py | Python | apps/device/models.py | joewen85/mycmdb | b4855192a92c0a1f28f2af84d4f8cf7b215ff27c | [
"Apache-2.0"
] | 2 | 2019-05-24T03:48:10.000Z | 2020-07-01T14:58:31.000Z | apps/device/models.py | joewen85/mycmdb | b4855192a92c0a1f28f2af84d4f8cf7b215ff27c | [
"Apache-2.0"
] | null | null | null | apps/device/models.py | joewen85/mycmdb | b4855192a92c0a1f28f2af84d4f8cf7b215ff27c | [
"Apache-2.0"
] | null | null | null | from django.contrib.auth.models import User
from django.db import models
# Create your models here.
class Cloudips(models.Model):
"""服务器运营商"""
cloudipsname = models.CharField(max_length=10, verbose_name="服务器运营商")
describe = models.CharField(max_length=10, verbose_name="描述")
created_at = models.DateTimeField(auto_now_add=True, verbose_name="创建时间")
updated_at = models.DateTimeField(auto_now=True, verbose_name="修改时间")
class Meta:
verbose_name = "服务器运营商"
verbose_name_plural = verbose_name
def __str__(self):
return self.describe
class Envirment(models.Model):
"""服务器环境"""
envname = models.CharField(max_length=20, verbose_name="服务器运行环境")
describe = models.CharField(max_length=20, verbose_name="描述")
created_at = models.DateTimeField(auto_now_add=True, verbose_name="创建时间")
updated_at = models.DateTimeField(auto_now=True, verbose_name="修改时间")
phpbin = models.CharField(max_length=100, verbose_name="PHP环境路径", null=True)
vhost_path = models.CharField(max_length=100, verbose_name="网站虚拟目录路径", null=True)
fastcgi_pass = models.CharField(max_length=64, verbose_name="后端PHP处理方式", null=True, blank=True)
class Meta:
verbose_name = "运行环境"
verbose_name_plural = verbose_name
def __str__(self):
return self.describe
class Jobs(models.Model):
"""任务"""
jid = models.AutoField(primary_key=True)
name = models.CharField(max_length=50, verbose_name="任务名称")
path = models.CharField(max_length=100, verbose_name="任务路径")
describe = models.CharField(max_length=50, verbose_name="描述")
class Meta:
verbose_name = "任务"
verbose_name_plural = verbose_name
def __str__(self):
return self.name
class Device(models.Model):
"""服务器详情"""
hostname = models.CharField(max_length=50, verbose_name="服务器名称", null=False, unique=True, db_index=True)
ipaddress = models.GenericIPAddressField(verbose_name='服务器IP地址', db_index=True)
sshuser = models.CharField(max_length=20, verbose_name="服务器登陆用户")
sshpassword = models.CharField(max_length=50, verbose_name="服务器登陆密码", null=False)
websitepath = models.CharField(max_length=200, verbose_name="网站存放位置", null=False)
envirment = models.ForeignKey(Envirment, verbose_name="运行环境", on_delete=models.DO_NOTHING)
cloudips = models.ForeignKey(Cloudips, verbose_name="服务器运营商", on_delete=models.DO_NOTHING)
customer_name = models.CharField(max_length=50, verbose_name="客户用户名", null=True)
sshport = models.PositiveSmallIntegerField(verbose_name="服务器登陆端口", default=22)
created_at = models.DateTimeField(auto_now_add=True, verbose_name="创建时间")
updated_at = models.DateTimeField(auto_now=True, verbose_name="修改时间")
# is_monitor = models.BooleanField(verbose_name="是否监控")
is_maintenance = models.BooleanField(verbose_name="是否维护", default=0)
maintenance_duration = models.CharField(max_length=25, verbose_name="维护期限", null=True, blank=True)
deploy_times = models.IntegerField(verbose_name="部署队列和计划任务次数", default=0)
deploy_weiqingshop_times = models.SmallIntegerField(verbose_name="部署框架与商城次数", default=0)
deploy_frameworkshop_times = models.SmallIntegerField(verbose_name="部署微擎与商城次数", default=0)
others = models.TextField(verbose_name="其他内容", null=True, blank=True)
paid = models.BooleanField(verbose_name="商城收费客户", default=0)
ftpuser = models.CharField(max_length=32, default='www', verbose_name="ftp用户名")
ftppassword = models.CharField(max_length=32, verbose_name="ftp密码", null=True)
mysqluser = models.CharField(max_length=32, default='root', verbose_name="mysql用户名")
mysqlpassword = models.CharField(max_length=32, verbose_name="mysql密码", null=True)
mysqladdress = models.CharField(max_length=64, default='127.0.0.1', verbose_name="mysql连接地址")
# 商城版本 0为独立版，1为微擎版
shop_version = models.BooleanField(verbose_name="商城版本", default=0)
mongodbuser = models.CharField(max_length=32, verbose_name='mongodb用户名', default='root')
mongodbaddress = models.CharField(max_length=64, verbose_name='mongodb连接地址', default='127.0.0.1')
class Meta:
verbose_name = "用户设备信息"
verbose_name_plural = verbose_name
def __str__(self):
return self.hostname
class Deploy_record(models.Model):
"""部署队列和计划任务记录"""
hostname = models.ForeignKey(Device, related_name='deploy_record', verbose_name="服务器名称", on_delete=models.CASCADE)
# hostname = models.CharField(verbose_name="服务器名称", max_length=32, null=True)
deploy_datetime = models.DateTimeField(auto_now_add=True, verbose_name="部署时间")
desc = models.CharField(max_length=100, verbose_name="描述", null=True)
operator = models.CharField(max_length=20, verbose_name="操作员", null=True)
# operator = models.ForeignKey(User, verbose_name="操作员", on_delete=models.DO_NOTHING, null=True)
remote_ip = models.GenericIPAddressField(verbose_name="远程访问地址", null=True)
# jobname = models.ForeignKey(Jobs, on_delete=models.DO_NOTHING, null=True, verbose_name="任务名称")
jobname = models.CharField(max_length=32, null=True, verbose_name="任务名称")
result = models.TextField(null=True, verbose_name="执行任务结果")
class Meta:
verbose_name = "部署记录"
verbose_name_plural = verbose_name
def __str__(self):
return "结果"
class Password_record(models.Model):
"""独立密码表"""
ipaddress = models.ForeignKey(Device, db_column="server_ip", related_name="PASSWORD", on_delete=models.CASCADE)
sshpassword = models.CharField(max_length=600, verbose_name="服务器登陆密码", null=False)
ftppassword = models.CharField(max_length=600, verbose_name="ftp密码", null=True)
mysqlpassword = models.CharField(max_length=600, verbose_name="mysql密码", null=True)
mongodbpassword = models.CharField(max_length=600, verbose_name="mongodb密码", null=True)
def __str__(self):
return "密码表"
class Meta:
verbose_name = "密码表"
verbose_name_plural = verbose_name
default_permissions = ()
permissions = (
("select_table", "查看密码表"),
("change_table", "修改密码表"),
("decode_password", "解密加密密码")
)
| 44.615942 | 118 | 0.726653 | 769 | 6,157 | 5.572172 | 0.231469 | 0.187398 | 0.126021 | 0.168028 | 0.502217 | 0.392765 | 0.377363 | 0.193932 | 0.144924 | 0.134656 | 0 | 0.017768 | 0.149911 | 6,157 | 137 | 119 | 44.941606 | 0.800917 | 0.065292 | 0 | 0.268041 | 0 | 0 | 0.076587 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.061856 | false | 0.113402 | 0.020619 | 0.061856 | 0.814433 | 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 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
87a1011f125122dd3d04b6f8cf1b937e02c1e3dd | 171 | py | Python | polls/apps.py | lesspointless/Shakal-NG | eee491af94527228735c2bca7644605effd74b37 | [
"MIT"
] | null | null | null | polls/apps.py | lesspointless/Shakal-NG | eee491af94527228735c2bca7644605effd74b37 | [
"MIT"
] | null | null | null | polls/apps.py | lesspointless/Shakal-NG | eee491af94527228735c2bca7644605effd74b37 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.apps import AppConfig
class PollConfig(AppConfig):
name = 'polls'
verbose_name = 'Ankety'
| 17.1 | 39 | 0.736842 | 21 | 171 | 5.714286 | 0.809524 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006897 | 0.152047 | 171 | 9 | 40 | 19 | 0.82069 | 0.122807 | 0 | 0 | 0 | 0 | 0.074324 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 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 | 0 | 0 | 0 | 3 |
87a278be1ccedb0628c9ef1157d19b2e6b3c1e25 | 293 | py | Python | examples/score_info.py | vnpnh/Pyvalo | ca9594ab4eb5620c0c5ef4d0fe0e139353986520 | [
"MIT"
] | null | null | null | examples/score_info.py | vnpnh/Pyvalo | ca9594ab4eb5620c0c5ef4d0fe0e139353986520 | [
"MIT"
] | null | null | null | examples/score_info.py | vnpnh/Pyvalo | ca9594ab4eb5620c0c5ef4d0fe0e139353986520 | [
"MIT"
] | null | null | null | import valorant
from valorant.utils.gameplay import enemy_score_info, own_score_info
import time
custom_config = valorant.config(tesseract=r'D:\Program Files\Tesseract-OCR\tesseract.exe')
time.sleep(1)
print(enemy_score_info(config=custom_config))
print(own_score_info(config=custom_config)) | 32.555556 | 90 | 0.843003 | 45 | 293 | 5.244444 | 0.488889 | 0.152542 | 0.118644 | 0.177966 | 0.228814 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003623 | 0.05802 | 293 | 9 | 91 | 32.555556 | 0.851449 | 0 | 0 | 0 | 0 | 0 | 0.14966 | 0.112245 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.428571 | 0 | 0.428571 | 0.285714 | 0 | 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 | 3 |
87c92d8d5da39b66d6ed707eefdf2818509138ec | 194 | py | Python | mundo1/aula07e.py | dilsonm/CeV | 8043be36b2da187065691d23ed5cb40fd65f806f | [
"MIT"
] | null | null | null | mundo1/aula07e.py | dilsonm/CeV | 8043be36b2da187065691d23ed5cb40fd65f806f | [
"MIT"
] | null | null | null | mundo1/aula07e.py | dilsonm/CeV | 8043be36b2da187065691d23ed5cb40fd65f806f | [
"MIT"
] | null | null | null | #entre com 2 notas e calcule a media
n1 = int(input('Entre com a primeira nota : '))
n2 = int(input('Entre com a segun da nota : '))
m = (n1 + n2) / 2
print('A média das notas é: {}'.format(m))
| 32.333333 | 47 | 0.628866 | 37 | 194 | 3.297297 | 0.594595 | 0.196721 | 0.213115 | 0.262295 | 0.278689 | 0 | 0 | 0 | 0 | 0 | 0 | 0.038961 | 0.206186 | 194 | 5 | 48 | 38.8 | 0.753247 | 0.180412 | 0 | 0 | 0 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 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 | 0 | 0 | 3 |
87d94775dfc269bfd5b53a7776fb318972e95d87 | 413 | py | Python | python/code_challenges/insertion_sort/insertion_sort.py | skrambelled/data-structures-and-algorithms | 8eb55a75ecedd71433d0994b5128a34a3b1df3d1 | [
"MIT"
] | null | null | null | python/code_challenges/insertion_sort/insertion_sort.py | skrambelled/data-structures-and-algorithms | 8eb55a75ecedd71433d0994b5128a34a3b1df3d1 | [
"MIT"
] | null | null | null | python/code_challenges/insertion_sort/insertion_sort.py | skrambelled/data-structures-and-algorithms | 8eb55a75ecedd71433d0994b5128a34a3b1df3d1 | [
"MIT"
] | 1 | 2020-11-19T11:01:14.000Z | 2020-11-19T11:01:14.000Z | def insertion_sort(the_list):
"""
In-place list sorting method
"""
i = 1
while i < len(the_list):
elem = the_list[i]
sorted_iterator = i-1
while elem < the_list[sorted_iterator] and sorted_iterator >= 0:
the_list[sorted_iterator+1] = the_list[sorted_iterator]
sorted_iterator -= 1
the_list[sorted_iterator + 1] = elem
i += 1
| 22.944444 | 72 | 0.585956 | 55 | 413 | 4.127273 | 0.327273 | 0.215859 | 0.229075 | 0.370044 | 0.352423 | 0.317181 | 0.317181 | 0 | 0 | 0 | 0 | 0.024823 | 0.317191 | 413 | 17 | 73 | 24.294118 | 0.780142 | 0.067797 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0 | 0 | 0.1 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
87efad2af17b3cd2adfd43bbf0b9f344bb7234ab | 1,940 | py | Python | notebooks/OtherFiles/test_stats.py | johnnyhchen/EPEtutorials | 861910248e0c47619103332897ff2732fc41c5b5 | [
"MIT"
] | null | null | null | notebooks/OtherFiles/test_stats.py | johnnyhchen/EPEtutorials | 861910248e0c47619103332897ff2732fc41c5b5 | [
"MIT"
] | null | null | null | notebooks/OtherFiles/test_stats.py | johnnyhchen/EPEtutorials | 861910248e0c47619103332897ff2732fc41c5b5 | [
"MIT"
] | null | null | null | from nose.tools import assert_equal, assert_almost_equal, assert_true, \
assert_false, assert_raises, assert_is_instance
from stats import mean, median, mode, std, var
# mean tests
def test_mean1():
obs = mean([0, 0, 0, 0])
exp = 0
assert_equal(obs, exp)
obs = mean([0, 200])
exp = 100
assert_equal(obs, exp)
obs = mean([0, -200])
exp = -100
assert_equal(obs, exp)
obs = mean([0])
exp = 0
assert_equal(obs, exp)
def test_floating_mean1():
obs = mean([1, 2])
exp = 1.5
assert_equal(obs, exp)
# median tests
def test_median1():
obs = median([0, 0, 0, 0])
exp = 0
assert_equal(obs, exp)
obs = median([0, 0, 0, 1])
exp = 0
assert_equal(obs, exp)
obs = median([0, 0, 1, 0, 0])
exp = 0
assert_equal(obs, exp)
obs = median([0, 1, 2, 3, 4])
exp = 2
assert_equal(obs, exp)
obs = median([0, 1, -1, 2, 3])
exp = 1
assert_equal(obs, exp)
obs = median([0, 200])
exp = 100
assert_equal(obs, exp)
obs = median([0, -200])
exp = -100
assert_equal(obs, exp)
obs = median([0])
exp = 0
assert_equal(obs, exp)
def test_floating_median1():
obs = mean([1, 2])
exp = 1.5
assert_equal(obs, exp)
# FIXME Put Mode tests here
def test_std1():
obs = std([0.0, 2.0])
exp = 1.0
assert_equal(obs, exp)
def test_std2():
obs = std([])
exp = 0.0
assert_equal(obs, exp)
def test_std3():
obs = std([0.0, 4.0])
exp = 2.0
assert_equal(obs, exp)
def test_std4():
obs = std([1.0, 3.0])
exp = 1.0
assert_equal(obs, exp)
def test_std5():
obs = std([1.0, 1.0, 1.0])
exp = 0.0
assert_equal(obs, exp)
def test_std6():
obs = std([1e500])
exp = NotImplemented
assert_equal(obs, exp)
def test_std7():
obs = std([0.0, 1e4242])
exp = NotImplemented
assert_equal(obs, exp)
# FIXME Put Variance tests here
| 18.130841 | 72 | 0.568041 | 313 | 1,940 | 3.386581 | 0.153355 | 0.228302 | 0.277358 | 0.336792 | 0.667925 | 0.658491 | 0.572642 | 0.549057 | 0.521698 | 0.466981 | 0 | 0.088235 | 0.281443 | 1,940 | 106 | 73 | 18.301887 | 0.672166 | 0.040722 | 0 | 0.532468 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009434 | 0.298701 | 1 | 0.142857 | false | 0 | 0.025974 | 0 | 0.168831 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
87f46acc417d33549fb22fa8d6f6aaf631b6c130 | 324 | py | Python | stellarobservatory/stellarbeat_test.py | andrenarchy/stellar-observatory | 0e1f6af4cdacae19248353f902686d8192130436 | [
"MIT"
] | 14 | 2019-05-29T09:45:00.000Z | 2021-04-22T20:11:15.000Z | stellarobservatory/stellarbeat_test.py | andrenarchy/stellar-observatory | 0e1f6af4cdacae19248353f902686d8192130436 | [
"MIT"
] | 10 | 2019-05-29T09:47:01.000Z | 2020-09-15T20:34:55.000Z | stellarobservatory/stellarbeat_test.py | andrenarchy/stellar-observatory | 0e1f6af4cdacae19248353f902686d8192130436 | [
"MIT"
] | 5 | 2019-05-29T07:33:02.000Z | 2021-11-24T18:46:03.000Z | """Stellarbeat tests"""
from .stellarbeat import get_nodes_from_stellarbeat
def test_stellarbeat_nodes():
"""Test get_nodes_from_stellarbeat()"""
nodes = get_nodes_from_stellarbeat()
assert isinstance(nodes, list)
for node in nodes:
assert isinstance(node, dict)
assert 'publicKey' in node
| 27 | 51 | 0.719136 | 39 | 324 | 5.692308 | 0.410256 | 0.27027 | 0.162162 | 0.310811 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.188272 | 324 | 11 | 52 | 29.454545 | 0.844106 | 0.157407 | 0 | 0 | 0 | 0 | 0.034351 | 0 | 0 | 0 | 0 | 0 | 0.428571 | 1 | 0.142857 | false | 0 | 0.142857 | 0 | 0.285714 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
87f61bd36c6c7e6b6a9b160a78c2024ba555ea14 | 2,125 | gyp | Python | binding.gyp | satorumpen/node-pdfium-native | 90e5bf8bc69c80620f9f4231ebf8e39ef1178b8c | [
"BSD-2-Clause"
] | 69 | 2015-03-27T14:37:54.000Z | 2022-01-05T10:04:01.000Z | binding.gyp | satorumpen/node-pdfium-native | 90e5bf8bc69c80620f9f4231ebf8e39ef1178b8c | [
"BSD-2-Clause"
] | 15 | 2015-04-03T02:33:53.000Z | 2020-01-28T10:42:29.000Z | binding.gyp | satorumpen/node-pdfium-native | 90e5bf8bc69c80620f9f4231ebf8e39ef1178b8c | [
"BSD-2-Clause"
] | 21 | 2015-05-14T12:59:43.000Z | 2021-12-11T16:31:21.000Z | {
'includes': [
'./common.gypi'
],
'target_defaults': {
'defines' : [
'PNG_PREFIX',
'PNGPREFIX_H',
'PNG_USE_READ_MACROS',
],
# 'include_dirs': [
# '<(DEPTH)/third_party/pdfium',
# '<(DEPTH)/third_party/pdfium/third_party/freetype/include',
# ],
'conditions': [
['OS=="linux"', {
'conditions': [
['target_arch=="x64"', {
'defines' : [ '_FX_CPU_=_FX_X64_', ],
'cflags': [ '-fPIC', ],
}],
['target_arch=="ia32"', {
'defines' : [ '_FX_CPU_=_FX_X86_', ],
}],
],
}]
],
'msvs_disabled_warnings': [
4005, 4018, 4146, 4333, 4345, 4267
]
},
'targets': [
{
'target_name': 'node_pdfium',
'dependencies' : [
'fx_lpng',
'./third_party/pdfium/pdfium.gyp:pdfium'
],
'sources': [
# is like "ls -1 src/*.cc", but gyp does not support direct patterns on
# sources
'<!@(["python", "tools/getSourceFiles.py", "src", "cc"])'
]
},
{
'target_name': 'fx_lpng',
'type': 'static_library',
'dependencies': [
'third_party/pdfium/pdfium.gyp:fxcodec',
],
'include_dirs': [
'third_party/pdfium/core/src/fxcodec/fx_zlib/include/',
],
'sources': [
'third_party/fx_lpng/include/fx_png.h',
'third_party/fx_lpng/src/fx_png.c',
'third_party/fx_lpng/src/fx_pngerror.c',
'third_party/fx_lpng/src/fx_pngget.c',
'third_party/fx_lpng/src/fx_pngmem.c',
'third_party/fx_lpng/src/fx_pngpread.c',
'third_party/fx_lpng/src/fx_pngread.c',
'third_party/fx_lpng/src/fx_pngrio.c',
'third_party/fx_lpng/src/fx_pngrtran.c',
'third_party/fx_lpng/src/fx_pngrutil.c',
'third_party/fx_lpng/src/fx_pngset.c',
'third_party/fx_lpng/src/fx_pngtrans.c',
'third_party/fx_lpng/src/fx_pngwio.c',
'third_party/fx_lpng/src/fx_pngwrite.c',
'third_party/fx_lpng/src/fx_pngwtran.c',
'third_party/fx_lpng/src/fx_pngwutil.c',
]
}
]
}
| 28.333333 | 79 | 0.542118 | 249 | 2,125 | 4.285141 | 0.341365 | 0.206186 | 0.179944 | 0.239925 | 0.355202 | 0.308341 | 0.28866 | 0 | 0 | 0 | 0 | 0.021583 | 0.280471 | 2,125 | 74 | 80 | 28.716216 | 0.676259 | 0.095059 | 0 | 0.220588 | 0 | 0 | 0.580763 | 0.392054 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 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 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
35527caa2b6732da28ddfecea002370d0e3ec4b8 | 287 | py | Python | sshserveraudit/controller/abstract.py | zwiazeksyndykalistowpolski/ssh-server-audit | b493f3ea6117d9567310857cdf567c159f848cf8 | [
"Apache-2.0"
] | 2 | 2018-11-13T17:05:26.000Z | 2019-04-14T08:07:02.000Z | sshserveraudit/controller/abstract.py | zwiazeksyndykalistowpolski/ssh-server-audit | b493f3ea6117d9567310857cdf567c159f848cf8 | [
"Apache-2.0"
] | 4 | 2018-11-05T06:31:22.000Z | 2019-02-10T16:19:23.000Z | sshserveraudit/controller/abstract.py | zwiazeksyndykalistowpolski/ssh-server-audit | b493f3ea6117d9567310857cdf567c159f848cf8 | [
"Apache-2.0"
] | null | null | null |
from ..entity.host import Node
class AbstractLoopController:
configured_nodes = {} # type: dict[Node]
def __init__(self, configured_volumes: dict):
self.configured_nodes = configured_volumes
@staticmethod
def perform_check(node: Node) -> bool:
pass
| 20.5 | 50 | 0.689895 | 31 | 287 | 6.096774 | 0.645161 | 0.15873 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222997 | 287 | 13 | 51 | 22.076923 | 0.847534 | 0.055749 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.125 | 0.125 | 0 | 0.625 | 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 | 0 | 1 | 0 | 0 | 3 |
35618eee2c4b532209dc3ab971e134b0988be776 | 517 | py | Python | thinc/neural/__init__.py | EnjoyLifeFund/py36pkgs | 0ac677fbbfa7b6d8c527fe2c759ba05117b07fd2 | [
"MIT",
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null | thinc/neural/__init__.py | EnjoyLifeFund/py36pkgs | 0ac677fbbfa7b6d8c527fe2c759ba05117b07fd2 | [
"MIT",
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null | thinc/neural/__init__.py | EnjoyLifeFund/py36pkgs | 0ac677fbbfa7b6d8c527fe2c759ba05117b07fd2 | [
"MIT",
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null | from ._classes.model import Model
from ._classes.affine import Affine
from ._classes.relu import ReLu
from ._classes.softmax import Softmax
from ._classes.elu import ELU
from ._classes.maxout import Maxout
from ._classes.embed import Embed
from ._classes.static_vectors import StaticVectors
#from ._classes.embed import HashEmbed
#from .pooling import Pooling, mean_pool, max_pool
from ._classes.convolution import ExtractWindow
#from ._classes.batchnorm import BatchNorm
#from ._classes.difference import Siamese
| 30.411765 | 50 | 0.829787 | 69 | 517 | 6 | 0.333333 | 0.318841 | 0.077295 | 0.10628 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.110251 | 517 | 16 | 51 | 32.3125 | 0.9 | 0.323017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
357769ad55f826125a15326f5ebecefb6630c6b4 | 1,792 | py | Python | tests/test_sets.py | r2evans/rediserver | 329c24f3f57c99b00c25e89387790038c328ed1b | [
"MIT"
] | 28 | 2018-02-13T12:45:00.000Z | 2022-03-16T04:27:07.000Z | tests/test_sets.py | r2evans/rediserver | 329c24f3f57c99b00c25e89387790038c328ed1b | [
"MIT"
] | 1 | 2018-02-16T09:56:50.000Z | 2018-02-16T09:56:50.000Z | tests/test_sets.py | r2evans/rediserver | 329c24f3f57c99b00c25e89387790038c328ed1b | [
"MIT"
] | 2 | 2018-08-12T12:50:23.000Z | 2019-05-10T16:16:49.000Z | import pytest
from redis.exceptions import ResponseError
def test_add(redis):
client = redis.ext.client
assert client.sadd('test_key1', 10) == 1
assert redis.dict == {b'test_key1': {b'10'}}
def test_add_multiple(redis):
client = redis.ext.client
assert client.sadd('test_key1', 10, 11) == 2
assert redis.dict == {b'test_key1': {b'10', b'11'}}
def test_add_existing(redis):
client = redis.ext.client
client.sadd('test_key1', 10, 11)
assert client.sadd('test_key1', 10, 11, 12) == 1
assert redis.dict == {b'test_key1': {b'10', b'11', b'12'}}
def test_add_wrongtype(redis):
client = redis.ext.client
client.set('test_key1', 1)
with pytest.raises(ResponseError, match='WRONGTYPE'):
client.sadd('test_key1', 2)
assert redis.dict == {b'test_key1': b'1'}
assert client.get('test_key1') == b'1'
def test_pop(redis):
client = redis.ext.client
client.sadd('test_key1', 10, 20)
result = client.spop('test_key1')
assert result in (b'10', b'20')
assert redis.dict == {b'test_key1': {b'10', b'20'} - {result}}
def test_pop_to_none(redis):
client = redis.ext.client
client.sadd('test_key1', 20)
client.spop('test_key1')
assert redis.dict == {}
def test_pop_wrongtype(redis):
client = redis.ext.client
client.set('test_key1', 1)
with pytest.raises(ResponseError, match='WRONGTYPE'):
client.spop('test_key1')
assert redis.dict == {b'test_key1': b'1'}
assert client.get('test_key1') == b'1'
def test_pop_empty(redis):
client = redis.ext.client
result = client.spop('test_key1')
assert result is None
assert redis.dict == {}
def test_scard(redis):
client = redis.ext.client
client.sadd('test', 1)
assert client.scard('test') == 1 | 25.239437 | 66 | 0.646205 | 269 | 1,792 | 4.167286 | 0.144981 | 0.149866 | 0.128457 | 0.152542 | 0.820696 | 0.772525 | 0.77074 | 0.639607 | 0.603033 | 0.513827 | 0 | 0.051831 | 0.192522 | 1,792 | 71 | 67 | 25.239437 | 0.722875 | 0 | 0 | 0.469388 | 0 | 0 | 0.133296 | 0 | 0 | 0 | 0 | 0 | 0.326531 | 1 | 0.183673 | false | 0 | 0.040816 | 0 | 0.22449 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 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 | 3 |
3580ac82d171260f7ba3546746c7eb16ebc44c94 | 612 | bzl | Python | source/bazel/deps/buildfarm/get.bzl | luxe/unilang | 6c8a431bf61755f4f0534c6299bd13aaeba4b69e | [
"MIT"
] | 33 | 2019-05-30T07:43:32.000Z | 2021-12-30T13:12:32.000Z | source/bazel/deps/buildfarm/get.bzl | luxe/unilang | 6c8a431bf61755f4f0534c6299bd13aaeba4b69e | [
"MIT"
] | 371 | 2019-05-16T15:23:50.000Z | 2021-09-04T15:45:27.000Z | source/bazel/deps/buildfarm/get.bzl | luxe/unilang | 6c8a431bf61755f4f0534c6299bd13aaeba4b69e | [
"MIT"
] | 6 | 2019-08-22T17:37:36.000Z | 2020-11-07T07:15:32.000Z | # Do not edit this file directly.
# It was auto-generated by: code/programs/reflexivity/reflexive_refresh
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def buildfarm():
http_archive(
name="buildfarm" ,
build_file="//bazel/deps/buildfarm:build.BUILD" ,
sha256="de2a18bbe1e6770be0cd54e93630fb1ee7bce937bff708eed16329033fbfe32b" ,
strip_prefix="bazel-buildfarm-355f816acf3531e9e37d860acf9ebbb89c9041c2" ,
urls = [
"https://github.com/Unilang/bazel-buildfarm/archive/355f816acf3531e9e37d860acf9ebbb89c9041c2.tar.gz",
],
)
| 36 | 113 | 0.718954 | 58 | 612 | 7.465517 | 0.706897 | 0.050808 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166994 | 0.168301 | 612 | 16 | 114 | 38.25 | 0.683694 | 0.165033 | 0 | 0 | 1 | 0 | 0.624016 | 0.389764 | 0 | 0 | 0 | 0 | 0 | 1 | 0.090909 | true | 0 | 0 | 0 | 0.090909 | 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 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
359b88d74a1e486fc0a836a15b483bf67c80bb0d | 1,252 | py | Python | slash/reporting/reporter_interface.py | omergertel/slash | 7dd5710a05822bbbaadc6c6517cefcbaa6397eab | [
"BSD-3-Clause"
] | null | null | null | slash/reporting/reporter_interface.py | omergertel/slash | 7dd5710a05822bbbaadc6c6517cefcbaa6397eab | [
"BSD-3-Clause"
] | null | null | null | slash/reporting/reporter_interface.py | omergertel/slash | 7dd5710a05822bbbaadc6c6517cefcbaa6397eab | [
"BSD-3-Clause"
] | null | null | null | class ReporterInterface(object):
def notify_before_console_output(self):
pass
def notify_after_console_output(self):
pass
def report_session_start(self, session):
pass
def report_session_end(self, session):
pass
def report_file_start(self, filename):
pass
def report_file_end(self, filename):
pass
def report_collection_start(self):
pass
def report_test_collected(self, all_tests, test):
pass
def report_collection_end(self, collected):
pass
def report_test_start(self, test):
pass
def report_test_end(self, test, result):
if result.is_success():
self.report_test_success(test, result)
elif result.is_skip():
self.report_test_skip(test, result)
elif result.is_error():
self.report_test_error(test, result)
else:
assert result.is_failure()
self.report_test_failure(test, result)
def report_test_success(self, test, result):
pass
def report_test_skip(self, test, result):
pass
def report_test_error(self, test, result):
pass
def report_test_failure(self, test, result):
pass
| 22.763636 | 53 | 0.634185 | 154 | 1,252 | 4.863636 | 0.207792 | 0.121495 | 0.208278 | 0.136182 | 0.377837 | 0.124166 | 0.124166 | 0 | 0 | 0 | 0 | 0 | 0.28754 | 1,252 | 54 | 54 | 23.185185 | 0.839686 | 0 | 0 | 0.358974 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025641 | 1 | 0.384615 | false | 0.358974 | 0 | 0 | 0.410256 | 0 | 0 | 0 | 0 | null | 0 | 1 | 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 | 0 | 0 | 0 | 0 | 3 |
35a6d0f5162090af5143cd194d923e57d1d9678d | 3,124 | py | Python | autobahn/wamp/gen/wamp/proto/PublisherFeatures.py | rapyuta-robotics/autobahn-python | c08e9e352d526a7fd0885bb94706366a432ada1a | [
"MIT"
] | 1,670 | 2015-10-12T15:46:22.000Z | 2022-03-30T22:12:53.000Z | autobahn/wamp/gen/wamp/proto/PublisherFeatures.py | rapyuta-robotics/autobahn-python | c08e9e352d526a7fd0885bb94706366a432ada1a | [
"MIT"
] | 852 | 2015-10-16T22:11:03.000Z | 2022-03-27T07:57:01.000Z | autobahn/wamp/gen/wamp/proto/PublisherFeatures.py | rapyuta-robotics/autobahn-python | c08e9e352d526a7fd0885bb94706366a432ada1a | [
"MIT"
] | 790 | 2015-10-15T08:46:12.000Z | 2022-03-30T12:22:13.000Z | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: proto
import flatbuffers
class PublisherFeatures(object):
__slots__ = ['_tab']
@classmethod
def GetRootAsPublisherFeatures(cls, buf, offset):
n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
x = PublisherFeatures()
x.Init(buf, n + offset)
return x
# PublisherFeatures
def Init(self, buf, pos):
self._tab = flatbuffers.table.Table(buf, pos)
# PublisherFeatures
def PublisherIdentification(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
# PublisherFeatures
def PublisherExclusion(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
# PublisherFeatures
def SubscriberBlackwhiteListing(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
# PublisherFeatures
def AcknowledgeEventReceived(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
# PublisherFeatures
def PayloadTransparency(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
# PublisherFeatures
def PayloadEncryptionCryptobox(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
if o != 0:
return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
return False
def PublisherFeaturesStart(builder): builder.StartObject(6)
def PublisherFeaturesAddPublisherIdentification(builder, publisherIdentification): builder.PrependBoolSlot(0, publisherIdentification, 0)
def PublisherFeaturesAddPublisherExclusion(builder, publisherExclusion): builder.PrependBoolSlot(1, publisherExclusion, 0)
def PublisherFeaturesAddSubscriberBlackwhiteListing(builder, subscriberBlackwhiteListing): builder.PrependBoolSlot(2, subscriberBlackwhiteListing, 0)
def PublisherFeaturesAddAcknowledgeEventReceived(builder, acknowledgeEventReceived): builder.PrependBoolSlot(3, acknowledgeEventReceived, 0)
def PublisherFeaturesAddPayloadTransparency(builder, payloadTransparency): builder.PrependBoolSlot(4, payloadTransparency, 0)
def PublisherFeaturesAddPayloadEncryptionCryptobox(builder, payloadEncryptionCryptobox): builder.PrependBoolSlot(5, payloadEncryptionCryptobox, 0)
def PublisherFeaturesEnd(builder): return builder.EndObject()
| 44 | 149 | 0.736236 | 319 | 3,124 | 7.07837 | 0.22884 | 0.058902 | 0.116918 | 0.058459 | 0.405669 | 0.405669 | 0.405669 | 0.405669 | 0.405669 | 0.405669 | 0 | 0.010819 | 0.171575 | 3,124 | 70 | 150 | 44.628571 | 0.861669 | 0.066901 | 0 | 0.367347 | 1 | 0 | 0.001377 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.326531 | false | 0 | 0.020408 | 0.020408 | 0.653061 | 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 | 0 | 0 | 1 | 0 | 0 | 3 |
35ab6bb46d5ea3a3428510a20d49d4e18ba330d8 | 93 | py | Python | setup.py | CerealBoxMedia/chunked_media | 324d9b7d76323fa1ca5296d733b82dc5ab5f98c0 | [
"BSD-2-Clause"
] | null | null | null | setup.py | CerealBoxMedia/chunked_media | 324d9b7d76323fa1ca5296d733b82dc5ab5f98c0 | [
"BSD-2-Clause"
] | null | null | null | setup.py | CerealBoxMedia/chunked_media | 324d9b7d76323fa1ca5296d733b82dc5ab5f98c0 | [
"BSD-2-Clause"
] | null | null | null | from setuptools import setup
setup(
install_requires = [
'wagtail>=2.2',
]
) | 13.285714 | 28 | 0.591398 | 10 | 93 | 5.4 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.030303 | 0.290323 | 93 | 7 | 29 | 13.285714 | 0.787879 | 0 | 0 | 0 | 0 | 0 | 0.12766 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.166667 | 0 | 0.166667 | 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 | 0 | 0 | 0 | 3 |
35b7a9f37db695d8601da7acb4cafce29b1e1fba | 121 | py | Python | Modulo 2/Lista06/6.py | BelfortJoao/Programacao-1 | 2d463744379ad3e4b0f5882ad923aae7ff80197a | [
"MIT"
] | 2 | 2021-08-17T14:02:13.000Z | 2021-08-19T02:37:28.000Z | Modulo 2/Lista06/6.py | BelfortJoao/Programacao-1 | 2d463744379ad3e4b0f5882ad923aae7ff80197a | [
"MIT"
] | null | null | null | Modulo 2/Lista06/6.py | BelfortJoao/Programacao-1 | 2d463744379ad3e4b0f5882ad923aae7ff80197a | [
"MIT"
] | 1 | 2021-09-05T20:18:45.000Z | 2021-09-05T20:18:45.000Z | n = int(input("Qual o tamanho do vetor?"))
x = [int(input()) for x in range(n)]
for i in range(0, n, 2):
print(x[i])
| 24.2 | 42 | 0.578512 | 26 | 121 | 2.692308 | 0.615385 | 0.228571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.020833 | 0.206612 | 121 | 4 | 43 | 30.25 | 0.708333 | 0 | 0 | 0 | 0 | 0 | 0.198347 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 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 | 0 | 0 | 0 | 0 | 0 | 3 |
35b83d6804fa9ceddca70f6c9a575d60a1166523 | 955 | py | Python | Examples/AppKit/CocoaBindings/ControlledPreferences/FontNameToDisplayNameTransformer.py | Khan/pyobjc-framework-Cocoa | f8b015ea2a72d8d78be6084fb12925c4785b8f1f | [
"MIT"
] | 132 | 2015-01-01T10:02:42.000Z | 2022-03-09T12:51:01.000Z | mac/pyobjc-framework-Cocoa/Examples/AppKit/CocoaBindings/ControlledPreferences/FontNameToDisplayNameTransformer.py | mba811/music-player | 7998986b34cfda2244ef622adefb839331b81a81 | [
"BSD-2-Clause"
] | 6 | 2015-01-06T08:23:19.000Z | 2019-03-14T12:22:06.000Z | mac/pyobjc-framework-Cocoa/Examples/AppKit/CocoaBindings/ControlledPreferences/FontNameToDisplayNameTransformer.py | mba811/music-player | 7998986b34cfda2244ef622adefb839331b81a81 | [
"BSD-2-Clause"
] | 27 | 2015-02-23T11:51:43.000Z | 2022-03-07T02:34:18.000Z | #
# FontNameToDisplayNameTransformer.py
# ControlledPreferences
#
# Converted by u.fiedler on 04.02.05.
# with great help from Bob Ippolito - Thank you Bob!
#
# The original version was written in Objective-C by Malcolm Crawford
# at http://homepage.mac.com/mmalc/CocoaExamples/controllers.html
from Foundation import *
from AppKit import *
class FontNameToDisplayNameTransformer(NSValueTransformer):
"""
Takes as input the fontName of a font as stored in user defaults,
returns the displayed font name of the font to show to the user.
"""
def transformedValueClass(cls):
return NSString
transformedValueClass = classmethod(transformedValueClass)
def allowsReverseTransformation(cls):
return False
allowsReverseTransformation = classmethod(allowsReverseTransformation)
def transformedValue_(self, aValue):
font = NSFont.fontWithName_size_(aValue, 12)
return font.displayName()
| 31.833333 | 74 | 0.748691 | 104 | 955 | 6.846154 | 0.711538 | 0.025281 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010283 | 0.18534 | 955 | 29 | 75 | 32.931034 | 0.904884 | 0.433508 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.166667 | 0.166667 | 0.916667 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
35bf440f5db6992617f0af44c679da91411cdc46 | 314 | py | Python | source/ex12.py | aurelo/lphw | 8e1ecddc52a7c91fd0f53d4174c1079c63a10a81 | [
"MIT"
] | null | null | null | source/ex12.py | aurelo/lphw | 8e1ecddc52a7c91fd0f53d4174c1079c63a10a81 | [
"MIT"
] | null | null | null | source/ex12.py | aurelo/lphw | 8e1ecddc52a7c91fd0f53d4174c1079c63a10a81 | [
"MIT"
] | null | null | null | '''
Already did exercise refactoring in file ex11
pydoc => module that automatically generates documentation from Python modules
Usage on this file in windows, assuming file is on path, or you're in the same dir:
python -m pydoc ex12
'''
def dummy():
"""
function documentation
"""
print "dummy"
| 22.428571 | 83 | 0.713376 | 44 | 314 | 5.090909 | 0.795455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016129 | 0.210191 | 314 | 13 | 84 | 24.153846 | 0.887097 | 0 | 0 | 0 | 1 | 0 | 0.131579 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.5 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
35ca4b460f265963556c34b0a78ea63661c41efd | 759 | py | Python | sleap/__init__.py | Tyelab/sleap | 67b4b3e762571e70beadf940a64ed62d9481dafe | [
"BSD-3-Clause-Clear"
] | null | null | null | sleap/__init__.py | Tyelab/sleap | 67b4b3e762571e70beadf940a64ed62d9481dafe | [
"BSD-3-Clause-Clear"
] | null | null | null | sleap/__init__.py | Tyelab/sleap | 67b4b3e762571e70beadf940a64ed62d9481dafe | [
"BSD-3-Clause-Clear"
] | null | null | null | import logging
import sys
# Setup logging to stdout
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
# Import submodules we want available at top-level
from sleap.version import __version__, versions
from sleap.io.dataset import Labels, load_file
from sleap.io.video import Video, load_video
from sleap.instance import LabeledFrame, Instance, PredictedInstance, Track
from sleap.skeleton import Skeleton
import sleap.nn
from sleap.nn.data import pipelines
from sleap.nn import inference
from sleap.nn.inference import load_model
from sleap.nn.system import use_cpu_only, disable_preallocation
from sleap.nn.system import summary as system_summary
from sleap.nn.config import TrainingJobConfig, load_config
from sleap.nn.evals import load_metrics
| 34.5 | 75 | 0.839262 | 114 | 759 | 5.473684 | 0.421053 | 0.173077 | 0.123397 | 0.054487 | 0.073718 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.108037 | 759 | 21 | 76 | 36.142857 | 0.921713 | 0.094862 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.9375 | 0 | 0.9375 | 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 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
35cc3dd135149af2098bb42e7ac3102a5e2dce14 | 137 | py | Python | Medical-Record-Managment-System/notifications/urls.py | AtluriNikhil/College_Projects | 23fa5d05e3c93691faa618a22fca858ba030ee5d | [
"Apache-2.0"
] | null | null | null | Medical-Record-Managment-System/notifications/urls.py | AtluriNikhil/College_Projects | 23fa5d05e3c93691faa618a22fca858ba030ee5d | [
"Apache-2.0"
] | null | null | null | Medical-Record-Managment-System/notifications/urls.py | AtluriNikhil/College_Projects | 23fa5d05e3c93691faa618a22fca858ba030ee5d | [
"Apache-2.0"
] | null | null | null | from django.urls import path
from . import views
urlpatterns = [
path('remainder/', views.notification,name='blog-notifications'),
] | 22.833333 | 69 | 0.737226 | 16 | 137 | 6.3125 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131387 | 137 | 6 | 70 | 22.833333 | 0.84874 | 0 | 0 | 0 | 0 | 0 | 0.202899 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
ea23fdc25062e17a9ab20e8fc93b5205665b4662 | 174 | py | Python | tests/step_1_unit/test_app.py | logikal-code/pyorbs | f43d15efd957c9b3fa68fde64ceab3c54f3016e7 | [
"MIT"
] | 7 | 2019-07-19T15:14:56.000Z | 2019-07-31T01:57:41.000Z | tests/step_1_unit/test_app.py | logikal-code/pyorbs | f43d15efd957c9b3fa68fde64ceab3c54f3016e7 | [
"MIT"
] | 2 | 2019-09-16T07:29:42.000Z | 2020-05-15T13:19:52.000Z | tests/step_1_unit/test_app.py | wbrp/pyorbs | f43d15efd957c9b3fa68fde64ceab3c54f3016e7 | [
"MIT"
] | null | null | null | from pyorbs.app import main
def test_keyboard_interrupt(mocker):
mocker.patch('pyorbs.orbs.Orbs.list', side_effect=KeyboardInterrupt)
assert main(args=['-l']) == 1
| 24.857143 | 72 | 0.735632 | 24 | 174 | 5.208333 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006579 | 0.126437 | 174 | 6 | 73 | 29 | 0.815789 | 0 | 0 | 0 | 0 | 0 | 0.132184 | 0.12069 | 0 | 0 | 0 | 0 | 0.25 | 1 | 0.25 | false | 0 | 0.25 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
ea468d39aa2592702058269c9e67946975d6af2c | 514 | py | Python | class_composition.py | nitinkumar0108/oops | 73302b6fd230fa90ecb5f0981483c2991f05c4b4 | [
"Apache-2.0"
] | 1 | 2021-12-12T18:40:04.000Z | 2021-12-12T18:40:04.000Z | class_composition.py | nitinkumar0108/oops | 73302b6fd230fa90ecb5f0981483c2991f05c4b4 | [
"Apache-2.0"
] | null | null | null | class_composition.py | nitinkumar0108/oops | 73302b6fd230fa90ecb5f0981483c2991f05c4b4 | [
"Apache-2.0"
] | null | null | null | #counter part of inheritance
#inheritance means by this program- a bookself is a book
#composition is -
class Bookself:
def __init__(self, *books):
self.books=books
def __str__(self):
return f"Bookself with {len(self.books)} books."
class Book:
def __init__(self,name):
self.name=name
def __str__(self):
return f"Book {self.name}"
book=Book("Harry potter")
book2=Book("Python")
shelf=Bookself(book,book2)
print(shelf) | 22.347826 | 57 | 0.618677 | 66 | 514 | 4.575758 | 0.454545 | 0.089404 | 0.072848 | 0.10596 | 0.112583 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005362 | 0.274319 | 514 | 23 | 58 | 22.347826 | 0.80429 | 0.190661 | 0 | 0.142857 | 0 | 0 | 0.184143 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0 | 0.142857 | 0.571429 | 0.071429 | 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 | 0 | 1 | 1 | 0 | 0 | 3 |
ea4cd3c26b422f73d8dc31f27b28df537a403e0c | 308 | py | Python | consensus/apps/user/views.py | OmidFarvid/Application-consensus | 546e00991601e5da25ff3f6b4927379f2daec60b | [
"MIT"
] | null | null | null | consensus/apps/user/views.py | OmidFarvid/Application-consensus | 546e00991601e5da25ff3f6b4927379f2daec60b | [
"MIT"
] | null | null | null | consensus/apps/user/views.py | OmidFarvid/Application-consensus | 546e00991601e5da25ff3f6b4927379f2daec60b | [
"MIT"
] | null | null | null | from django.shortcuts import render, redirect
from django.views import View
class IndexView(View):
def get(self, request, *args, **kwargs):
return redirect('/static/index.html')
class LoginView(View):
def get(self, request, *args, **kwargs):
return redirect('/static/index.html')
| 23.692308 | 45 | 0.688312 | 39 | 308 | 5.435897 | 0.538462 | 0.09434 | 0.09434 | 0.132075 | 0.566038 | 0.566038 | 0.566038 | 0.566038 | 0.566038 | 0.566038 | 0 | 0 | 0.178571 | 308 | 12 | 46 | 25.666667 | 0.837945 | 0 | 0 | 0.5 | 0 | 0 | 0.116883 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0.25 | 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 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
ea7a68e4009501e5937a4720cb48410ff4dcd159 | 281 | py | Python | sphecius/__init__.py | douglasdaly/sphecius | df8fc8dd2add157c6360c2b66cb22ac6f0241051 | [
"MIT"
] | 1 | 2019-09-26T01:08:20.000Z | 2019-09-26T01:08:20.000Z | sphecius/__init__.py | douglasdaly/sphecius | df8fc8dd2add157c6360c2b66cb22ac6f0241051 | [
"MIT"
] | null | null | null | sphecius/__init__.py | douglasdaly/sphecius | df8fc8dd2add157c6360c2b66cb22ac6f0241051 | [
"MIT"
] | 1 | 2019-09-26T01:08:19.000Z | 2019-09-26T01:08:19.000Z | #
# Imports
#
from . import alphabets
from . import ciphers
from . import cryptanalysis
from . import translators
from . import data
from .string_helpers import *
#
# All Setup
#
__all__ = [
'alphabets',
'ciphers',
'cryptanalysis',
'translators',
'data'
]
| 13.380952 | 29 | 0.654804 | 28 | 281 | 6.392857 | 0.428571 | 0.27933 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.238434 | 281 | 20 | 30 | 14.05 | 0.836449 | 0.067616 | 0 | 0 | 0 | 0 | 0.173913 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.461538 | 0 | 0.461538 | 0 | 1 | 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 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
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