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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f0aee58dff262da24995b34a28866e048d9466ad | 347 | py | Python | ai for simple games/connect 4/tictoc.py | gustasvs/AI | 23360a8865e8211568594c2b2ced11dcdc9b0006 | [
"MIT"
] | 1 | 2022-02-03T18:21:28.000Z | 2022-02-03T18:21:28.000Z | ai for simple games/connect 4/tictoc.py | gustasvs/AI | 23360a8865e8211568594c2b2ced11dcdc9b0006 | [
"MIT"
] | null | null | null | ai for simple games/connect 4/tictoc.py | gustasvs/AI | 23360a8865e8211568594c2b2ced11dcdc9b0006 | [
"MIT"
] | null | null | null | import time
def tic():
#Homemade version of matlab tic and toc functions
global startTime_for_tictoc
startTime_for_tictoc = time.time()
def toc():
if 'startTime_for_tictoc' in globals():
print("Elapsed time is " + str(time.time() - startTime_for_tictoc) + " seconds.")
else:
print("Toc: start time not set") | 24.785714 | 89 | 0.665706 | 47 | 347 | 4.744681 | 0.574468 | 0.215247 | 0.32287 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.227666 | 347 | 14 | 90 | 24.785714 | 0.83209 | 0.138329 | 0 | 0 | 0 | 0 | 0.227425 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.111111 | 0 | 0.333333 | 0.222222 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
f0c3d53843280be100078a8627ba65bbe0348c16 | 141 | py | Python | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 63 | 2020-08-15T19:02:06.000Z | 2022-03-29T16:19:00.000Z | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 133 | 2020-08-18T03:51:05.000Z | 2022-03-05T13:43:22.000Z | test/example_project/main_package/workflow1.py | Tismas/bigflow | 6a4a14616d66beeaf45700ea340c97d797a1f9e5 | [
"Apache-2.0"
] | 10 | 2020-08-25T05:19:31.000Z | 2022-02-03T10:33:41.000Z | import bigflow as bf
from .job import ExampleJob
workflow1 = bf.Workflow(
workflow_id='workflow1',
definition=[ExampleJob('job1')]) | 20.142857 | 36 | 0.730496 | 17 | 141 | 6 | 0.705882 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02521 | 0.156028 | 141 | 7 | 36 | 20.142857 | 0.831933 | 0 | 0 | 0 | 0 | 0 | 0.091549 | 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 |
f0cb07dafe313489f043d26fe74c8e52bf97cd97 | 99 | py | Python | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | 1 | 2021-01-12T17:13:46.000Z | 2021-01-12T17:13:46.000Z | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | null | null | null | maidwhite/__init__.py | tihtw/maidwhite-python | 0f7613029bf12118c901273aa26aa89e843bd6ed | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from .MaidWhite import MaidWhite
name = "MaidWhite"
__all__ = (MaidWhite) | 16.5 | 32 | 0.676768 | 11 | 99 | 5.727273 | 0.727273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012048 | 0.161616 | 99 | 6 | 33 | 16.5 | 0.746988 | 0.212121 | 0 | 0 | 0 | 0 | 0.116883 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
9bfeddde243de4b1d35ced3b1d4b4c7363007028 | 90 | py | Python | src/rubinlander/parsers/lsstdoc/__init__.py | lsst-sqre/rubin-lander-plugin | f570acb92629493e640baf632bd7ceee78516efd | [
"MIT"
] | null | null | null | src/rubinlander/parsers/lsstdoc/__init__.py | lsst-sqre/rubin-lander-plugin | f570acb92629493e640baf632bd7ceee78516efd | [
"MIT"
] | 6 | 2021-04-19T06:07:06.000Z | 2022-03-07T03:02:22.000Z | src/rubinlander/parsers/lsstdoc/__init__.py | lsst-sqre/rubin-lander-plugin | f570acb92629493e640baf632bd7ceee78516efd | [
"MIT"
] | null | null | null | from rubinlander.parsers.lsstdoc.parser import LsstDocParser
__all__ = ["LsstDocParser"]
| 22.5 | 60 | 0.822222 | 9 | 90 | 7.777778 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088889 | 90 | 3 | 61 | 30 | 0.853659 | 0 | 0 | 0 | 0 | 0 | 0.144444 | 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 |
504a8a1f14c3de8780d56a229c744af8d53c9b27 | 262 | py | Python | app/service/plugin_svc.py | muyenzo/caldera | 408f6d54239aa73832f474136ac8f64faab5be35 | [
"Apache-2.0"
] | null | null | null | app/service/plugin_svc.py | muyenzo/caldera | 408f6d54239aa73832f474136ac8f64faab5be35 | [
"Apache-2.0"
] | null | null | null | app/service/plugin_svc.py | muyenzo/caldera | 408f6d54239aa73832f474136ac8f64faab5be35 | [
"Apache-2.0"
] | null | null | null | from app.service.base_service import BaseService
class PluginService(BaseService):
def __init__(self, plugins):
self.plugins = plugins
self.log = self.add_service('plugin_svc', self)
def get_plugins(self):
return self.plugins
| 21.833333 | 55 | 0.698473 | 32 | 262 | 5.46875 | 0.5625 | 0.188571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.21374 | 262 | 11 | 56 | 23.818182 | 0.849515 | 0 | 0 | 0 | 0 | 0 | 0.038168 | 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 |
5060ee963497faf44238f2e6162528f64a4e0e16 | 2,017 | py | Python | sahara/utils/openstack/nova.py | citrix-openstack-build/sahara | 17e4f4dac5bb321ef4d5a55664cca0857127d7e6 | [
"Apache-2.0"
] | 1 | 2022-02-25T19:14:33.000Z | 2022-02-25T19:14:33.000Z | sahara/utils/openstack/nova.py | citrix-openstack-build/sahara | 17e4f4dac5bb321ef4d5a55664cca0857127d7e6 | [
"Apache-2.0"
] | null | null | null | sahara/utils/openstack/nova.py | citrix-openstack-build/sahara | 17e4f4dac5bb321ef4d5a55664cca0857127d7e6 | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2013 Mirantis 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 novaclient import exceptions as nova_ex
from novaclient.v1_1 import client as nova_client
from sahara import context
import sahara.utils.openstack.base as base
from sahara.utils.openstack import images
def client():
ctx = context.current()
auth_url = base.retrieve_auth_url()
compute_url = base.url_for(ctx.service_catalog, 'compute')
nova = nova_client.Client(username=ctx.username,
api_key=None,
project_id=ctx.tenant_id,
auth_url=auth_url)
nova.client.auth_token = ctx.token
nova.client.management_url = compute_url
nova.images = images.SaharaImageManager(nova)
return nova
def get_flavors():
return [flavor.name for flavor in client().flavors.list()]
def get_flavor(**kwargs):
return client().flavors.find(**kwargs)
def get_images():
return [image.id for image in client().images.list()]
def get_limits():
limits = client().limits.get().absolute
return dict((l.name, l.value) for l in limits)
def get_user_keypair(cluster):
try:
return client().keypairs.get(cluster.user_keypair_id)
except nova_ex.NotFound:
return None
def get_instance_info(instance):
return client().servers.get(instance.instance_id)
def get_network(**kwargs):
try:
return client().networks.find(**kwargs)
except nova_ex.NotFound:
return None
| 27.630137 | 69 | 0.699554 | 281 | 2,017 | 4.907473 | 0.437722 | 0.030457 | 0.018854 | 0.023205 | 0.04351 | 0.04351 | 0 | 0 | 0 | 0 | 0 | 0.006266 | 0.208726 | 2,017 | 72 | 70 | 28.013889 | 0.857769 | 0.27417 | 0 | 0.157895 | 0 | 0 | 0.004831 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.210526 | false | 0 | 0.131579 | 0.105263 | 0.605263 | 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 |
acaad146ce57d3448a856e316aa846e7146bad1e | 207 | py | Python | app/routes.py | apigram/HospitalWaiterAuthService | 9fcff5c215f3ec99658ab2b2d300dd6f511d52fc | [
"Apache-2.0"
] | null | null | null | app/routes.py | apigram/HospitalWaiterAuthService | 9fcff5c215f3ec99658ab2b2d300dd6f511d52fc | [
"Apache-2.0"
] | null | null | null | app/routes.py | apigram/HospitalWaiterAuthService | 9fcff5c215f3ec99658ab2b2d300dd6f511d52fc | [
"Apache-2.0"
] | null | null | null | from app import app
from flask_restful import Api
from app.resources.auth import TokenResource
api = Api(app)
# Token resource
api.add_resource(TokenResource, '/authservice/token', endpoint='auth_token')
| 20.7 | 76 | 0.797101 | 29 | 207 | 5.586207 | 0.482759 | 0.08642 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.115942 | 207 | 9 | 77 | 23 | 0.885246 | 0.067633 | 0 | 0 | 0 | 0 | 0.146597 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.6 | 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 | 1 | 0 | 0 | 0 | 0 | 3 |
acd72b70de8a62feaf26ad1334f4a7736fd2cbd8 | 86,104 | py | Python | save.py | brunnatorino/FEC_app | d9dec2ae0e4a3eb2f44976b1429596c657073a31 | [
"MIT"
] | null | null | null | save.py | brunnatorino/FEC_app | d9dec2ae0e4a3eb2f44976b1429596c657073a31 | [
"MIT"
] | null | null | null | save.py | brunnatorino/FEC_app | d9dec2ae0e4a3eb2f44976b1429596c657073a31 | [
"MIT"
] | null | null | null | import pandas as pd
from gooey import Gooey, GooeyParser
import numpy as np
import xlsxwriter
import xlrd
@Gooey(program_name="FEC FILE FOR FRANCE", required_cols= 4,default_size=(710, 700),navigation='TABBED', header_bg_color = '#48a7fa')
def parse_args():
parser = GooeyParser()
FilesGL = parser.add_argument_group('GL Posted Items')
FilesGL.add_argument('GL',
action='store',
widget='FileChooser',
help="Excel File From SAP G/L View: Normal Items")
FileNOTE = parser.add_argument_group('Entry View Parked Items')
FileNOTE.add_argument('Parked',
action='store',
widget='FileChooser',
help="Excel File From SAP Entry View: Only Parked and Noted Items")
choose = parser.add_argument_group('FEC Name')
choose.add_argument('Choose_File_Name',
action='store',
help="File name with .xlsx in the end. Standard for FEC is 533080222FECYYYYMMDD",
gooey_options={
'validator': {
'test': 'user_input.endswith(".xlsx") == True',
'message': 'Must contain .xlsx at the end!'
}
})
args = parser.parse_args()
return args
def combine(file, file2):
gl_df = pd.read_excel(file)
parked_df = pd.read_excel(file2)
numbers = gl_df['Document Number'].tolist()
gl = gl_df.append(parked_df[~parked_df['Document Number'].isin(numbers)])
gl = gl.reset_index()
return gl
def transform(gl):
gl['JournalCode'] = gl['Document Type']
gl['JournalLib'] = gl['Document Header Text']
gl['EcritureNum'] = gl['Document Number']
gl['EcritureDate'] = gl['Posting Date']
gl['CompteNum'] = gl['G/L Account']
gl['CompteLib'] = gl['G/L Account']
gl['CompAuxLib'] = gl['Offsetting acct no.']
gl['PieceRef'] = gl['Reference']
gl['EcritureLib'] = gl['Text']
gl['Amount'] = gl['Amount in local currency']
gl['MontantDevise'] = ''
gl['Idevise'] = ''
gl['PieceDate'] = gl['Document Date']
gl['ValidDate'] = gl['Entry Date']
gl['EcritureLet'] = gl['Assignment']
gl['DateLet'] = gl['Entry Date']
gl = gl.dropna(subset=['Amount'])
gl.loc[gl["Amount"] < 0 ,'Credit'] = gl['Amount']
gl.loc[gl["Amount"] > 0 ,'Debit'] = gl['Amount']
gl.loc[gl["Debit"].isnull() ,'Debit'] = 0
gl.loc[gl["Credit"].isnull() ,'Credit'] = 0
gl.loc[gl["EcritureLet"].isnull(),'DateLet'] = ''
gl.loc[gl["EcritureLet"].isnull(),'DateLet'] = ''
del gl['Amount']
del gl['Amount in local currency']
accounts = pd.read_excel("mapping-accounts.xlsx")
accounts1 = accounts[['G/L Account #','FrMap']]
accounts2 = accounts[['G/L Account #','FEC Compliant']]
accounts1 = accounts1.set_index('G/L Account #').to_dict()['FrMap']
accounts2 = accounts2.set_index('G/L Account #').to_dict()['FEC Compliant']
gl['CompteLib'] = gl['CompteLib'].replace(accounts2)
gl['CompteNum'] = (gl['CompteNum'].map(accounts1).astype('Int64').astype(str) + gl['CompteNum'].astype(str))
gl['CompteNum'] = gl['CompteNum'].str.replace('\.0$', '')
journals = pd.read_excel("test128.xlsx")
codes = pd.read_excel('mapping-journal.xlsx')
journals = journals.set_index('DocHeader').to_dict()['JournalLib_FR']
codes = codes.set_index('JournalCode').to_dict()["JournalLib_FR"]
gl.loc[gl["JournalLib"].isnull(),'JournalLib'] = gl["JournalCode"].map(str)
gl['JournalLib'] = gl['JournalLib'].replace(journals)
gl['JournalLib'] = gl['JournalLib'].replace(codes)
vendors = pd.read_excel("Vendors1.xlsx")
vendors = vendors.set_index('No').to_dict()['Name']
gl['CompAuxLib'] = gl['CompAuxLib'].map(vendors)
gl['CompAuxNum'] = "F" + gl['CompAuxLib']
gl.loc[(~gl.CompAuxLib.isnull()) & (gl["EcritureLib"].isnull()),'EcritureLib'] = gl['JournalLib'].map(str) + " de " + gl['CompAuxLib'].map(str)
gl.loc[(gl.CompAuxLib.isnull()) & (gl["EcritureLib"].isnull()),'EcritureLib'] = gl['JournalLib'].map(str) + gl['EcritureNum'].map(str)
gl['EcritureLib'] = gl['EcritureLib'].str.replace('^\d+', '')
return gl
def translate(gl):
journals = pd.read_excel("test128.xlsx")
codes = pd.read_excel('mapping-journal.xlsx')
journals = journals.set_index('DocHeader').to_dict()['JournalLib_FR']
codes = codes.set_index('JournalCode').to_dict()["JournalLib_FR"]
mapping_Valuation = {" Valuation on": " Évaluation sur"," Valuation on Reverse":" Évaluation sur Contre Passation",
" Reverse Posting":" Contre-Passation d'Ecriture - Conversion de devise sur",
" Translation Using":" Conversion de devise sur"}
mapping_AA = {"Reclass from": " Reclassification de", "reclass from": " Reclassification de", "ZEE MEDIA":"ZEE MEDIA Campaignes Numériques", "TRAINING CONTRI. ER JANUARY '19":"FORMATION CONTRI. ER JANVIER' 19",
"TAX FEES":"Taxes","SOCIAL SECURITY: URSSAF":"SÉCURITÉ SOCIALE: URSSAF","SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE","RSM":"SERVICES DE PAIE RSM EF18","RSA":"SERVICES DE PAIE RSA OCT-JAN",
"PRIVATE HEALTH":"SANTÉ PRIVÉE: ASSURANCE MÉDICALE-AXA/","PENSION: PENSION CONTRIBUTIONS - REUNICA":"PENSION: COTISATIONS DE RETRAITE-REUNICA","PENSION: LIFE & DISABILITY INSURANCE - R":"PENSION: ASSURANCE VIE & INVALIDITÉ-R",
"PENSION JANUARY '19":"PENSION JANVIER '19",
"ON CALL JANUARY '19":"Disponible Janvier'19",
"NRE + PROJECT INITIATION FEES":"NRE + FRAIS D’INITIATION AU PROJET (PO 750003","NET PAY JANUARY '19":"Payeante Janvier'19","JANUARY'19":"JANVIER'19",
"LUNCH VOUCHER- WITHHOLDING":"BON DÉJEUNER-RETENUE","HOLIDAY BONUS ACCRUAL FY18/19":"CUMUL DES PRIMES DE VACANCES EF18/19",
"GROSS SALARY JANUARY '19":"SALAIRE BRUT JANVIER' 19","EMEA ACCRUAL P8FY19":"P8FY19 D’ACCUMULATION EMEA","COMMISSION RE-ACCRUAL":"COMMISSION RÉ-ACCUMULATION",
"COMMISSION ACCRUAL":"COMMISSION D’ACCUMULATION","MARCH":"MARS","MAY":"MAI","APRIL":"AVRIL","AUDIT FEES":"HONORAIRES D’AUDIT",
"UNSUBMITTED_UNPOSTED BOA ACCRUAL":"Accumulation BOA non soumise non exposée","UNASSIGNED CREDITCARD BOA ACCRUAL":"NON ASSIGNÉ CREDITCARD BOA ACCUMULATION ",
"EMEA ACCRUAL":"ACCUMULATION EMEA","Exhibit Expenses":"Frais d'exposition","Hotel Tax":"Taxe hôtelière","Company Events":"Événements d'entreprise",
"Public Transport":"Transport public", "Agency Booking Fees":"Frais de réservation d'agence","Working Meals (Employees Only)":"Repas de travail (employés seulement)",
"Airfare":"Billet d'avion","Office Supplies":"Fournitures de bureau","Tolls":"Péages",
"write off difference see e-mail attached":"radiation de la différence voir e-mail ci-joint",
"Manual P/ment and double payment to be deduct":"P/ment manuel et double paiement à déduire","FX DIFFERENCE ON RSU":"DIFFERENCE FX SUR RSU",
"DEFINED BENEFIT LIABILITY-TRUE UP":"RESPONSABILITÉ À PRESTATIONS DÉTERMINÉES-TRUE UP","EXTRA RELEASE FOR STORAGE REVERSED":"EXTRA LIBERATION POUR STOCKAGE CONTREPASSATION",
"RECLASS BANK CHARGES TO CORRECT COST CEN":"RECLASSER LES FRAIS BANCAIRES POUR CORRIGER","PAYROLL INCOME TAXES":"IMPÔTS SUR LES SALAIRES",
"TRAINING TAX TRUE UP":"TAXE DE FORMATION", "FX DIFFERENCE ON STOCK OPTION EXERCISES":"FX DIFFERENCE SUR LES EXERCICES D'OPTIONS STOCK",
"Airline Frais":"Frais de Transport Aérien","Agency Booking Fees":"Frais de Réservation d'Agence","Computer Supplies":"Fournitures informatiques",
"AUDIT FEES":"FRAIS D'AUDIT", "HOLIDAY BONUS ACCRUAL ":"ACCUMULATION DE BONUS DE VACANCES","TAX FEES":"FRAIS D'IMPÔT",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUITION À L’APPRENTISSAGE",
"SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION", "TRAVEL COST":"FRAIS DE VOYAGE", "HOUSING TAX":"TAXE SUR LE LOGEMENT",
"PAYROLL INCOME TAXES":"IMPÔTS SUR LE REVENU DE LA PAIE","INCOME TAX-PAS":"IMPÔT SUR LE REVENU-PAS", "IC SETTLEMENT":"Règlement Interentreprises",
"VACATION TAKEN":"VACANCES PRISES", "SOCIAL SECURITY: APPR. CONTR.":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE",
"POST OF AVRIL DEC IN CORRECT SIGN":"CORRECTION D'ECRITURE AVRIL DEC"}
gl = gl.replace({"EcritureLib":mapping_Valuation}, regex=True)
gl = gl.replace({"EcritureLib":mapping_AA}, regex=True)
gl['EcritureLib'] = gl["EcritureLib"].str.replace('COST-PLUS', 'Revient Majoré')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('PRITVAE HEALTH: MEDICAL INSURANCE', 'SANTÉ PRIVÉE: ASSURANCE MÉDICALE')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('MEDICAL INSURANCE', 'ASSURANCE MÉDICALE')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('UNASSIGNED', 'NON ATTRIBUÉ')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('Payout', 'Paiement')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('FRINGE COST', 'COÛT MARGINAL')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('PROJECT INITIATION', 'LANCEMENT DU PROJET')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('ACCRUAL', 'ACCUMULATION')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('CREDITCARD', 'CARTE DE CRÉDIT')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('ACCR ', 'ACCUM ')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('VAT ', 'TVA ')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('SOCIAL SECURITY ', 'SÉCURITÉ SOCIALE')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('SEPTEMBER', 'SEPT')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('TAXBACK', 'Reboursement')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('REPORT', '')
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Reverse Posting", "Contre Passation d'Ecriture")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("BASE RENT", "Location Base")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Rent ", "Location ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RENT ", "Location ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CLEARING", "compensation ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("clearing", "compensation ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("BILLING CHARGES", "FRAIS DE FACTURATION ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("UNPAID", "NON PAYÉ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PROPERTY TAX", "IMPÔT FONCIER ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Trans. Using", "Conversion sur")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("SALARIES", "Salaires")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Refund", "Remboursement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("REFUND", "Remboursement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("no invoice", "pas de facture")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("COST-PLUS SERVICE REVENUE", "Revenus de service Revient Majoré")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("SETTLEMENT", "RÈGLEMENT ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PURCHASE", "ACHAT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("NON-CP SETTLE", "RÈGLEMENT NON-CP")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PAID ", " Payé ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FEES ", "Frais")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("January", "Janvier")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("February", "Février")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("March", "Mars")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("April", "Avril")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("May", "Mai")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("June", "Juin")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("July", "Juillet")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("September", "Septembre")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Aug.", "Août")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("JANUARY", "Janvier")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FEBRUARY", "Février")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("MARCH", "Mars")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("APRIL", "Avril")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("MAY", "Mai")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("JUNE", "Juin")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("JULY", "Juillet")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("SEPTEMBER", "Septembre")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("AUGUST.", "Août")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("NOVEMBER.", "Novembre")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("DECEMBER.", "Décembre")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("December", "Décembre")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Feb.", "Fév.")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Mar.", "Mars")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Apr.", "Avril")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Aug.", "Août")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Aug.", "Août")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Reverse ", "Contre-passation ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INTEREST CHARGE", "CHARGE D'INTÉRÊT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("-SICK LEAVE PAY", "-Paiement congé maladie")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECLASSEMENTIFICATION", "RECLASSIFICATION")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INSTALMENT", "VERSEMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FIRST", "1ere")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FINE LATE PAY.", "Amende pour retard de paiement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("-PATERNITY PAY", "Indemnités de paternité")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("SOCIAL SECURITY:", "SÉCURITÉ SOCIALE:")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Trip from", "Voyage de:")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" To ", " à")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Shipping", "Livraison")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("VOXEET INTEGRATION COSTS", "COÛTS D'INTÉGRATION DE VOXEET")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INCOME TAX", "IMPÔT SUR LE REVENU")
gl['EcritureLib'] = gl["EcritureLib"].str.replace('Rideshare', 'Covoiturage')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('Travel Meals', 'Repas de Travail')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('Fees', 'Frais')
gl['EcritureLib'] = gl["EcritureLib"].str.replace('Phone', 'Téléphone')
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Books", "Abonnements")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Subcriptions", "Location Base")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Meals", "Repas")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Entertainment", "divertissement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Third Party", "tiers ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Training Fees", "Frais d0 Formation")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Conferences/Tradeshows Registratio", "Conférences/Tradeshows Enregistrement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FOR", "POUR")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ROUNDING", "ARRONDISSEMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("STORAGE", "STOCKAGE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("VACATION ACCURAL", "Vacances Accumulées")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECEIVABLE ", "Recevables")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("AFTER PAYOUT ", "APRÈS PAIEMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CLEAN UP ", "APUREMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("EMPLOYEE TRAVEL INSUR ", "ASSURANCE DE VOYAGE DES EMPLOYÉS")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CORRECTION OF", "CORRECTION DE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("TAXES PAYROLL", "IMPÔTS SUR LA MASSE SALARIALE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ACCOUNT", "COMPTE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("TAX", "Impôt")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("life disab", "Incapacité de vie")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("HOUSING TAX","TAXE D'HABITATION")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("GROSS SALARY","SALAIRE BRUT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Cleaning Services","Nettoyage")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Freight","Fret")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Membership","adhésion")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Air cooling Maintenance","Entretien de refroidissement de l'air")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Power on Demand Platform","Plateforme d'energie à la demande")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Sanitaire room installation"," Installation de la salle sanitaire")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("subscription","abonnement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Coffee supplies "," Fournitures de café")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Duty and Tax ","Devoir et fiscalité")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Electricity ","Electricité ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Security monitoring","Surveillance de la sécurité")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Water", "L'EAU")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Statutory Audit", "Audit statutaire")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" Meeting room screen installation", "Installation de l'écran de la salle de réunion")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Water", "L'EAU")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Water", "L'EAU")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Tax Credit FY 2016", "Crédit d'impôt Exercice 2016")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Bank of America Merill Lynch-T&E statement","Déclaration de Merill Lynch")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("English Translation", "Traduction anglaise")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Office Rent", "Location de Bureau")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Annual Electrical Verification", "Vérification électrique annuelle ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Health costs ", "Coûts santé")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Unlimited-receipt and policy audit", "Vérification illimitée des reçus et audites")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Water fountain ", "Fontaine d'eau")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Quartely control visit", "Visite de contrôle trimestrielle")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Fire extinguishers annual check", "Vérification annuelle des extincteurs")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("showroom rent", "location de salle d'exposition")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("AND ACTUAL RECEIV","ET RECETTES RÉELLES")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FILING","DÉPÔT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ORDERS","ORDRES")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("EXCLUDED -DUMMY CREDIT","EXCLU")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RELARING TO","RELATIF À")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CLEAN UP-","APUREMENT-")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("2ND INSTALLEMENT","2ème versement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("DOUBLE PAYMENT","DOUBLE PAIEMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CLEAN UP-","APUREMENT-")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("DUTIES","DROITS")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Previous balance","Solde Précédent")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Cash fx","Cash FX")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PAYROLL INCOME","REVENU DE PAIE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("TELEPHONE CHARGES","Frais de Téléphone")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Clearing","Compensation")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Hotel","Hôtel")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Miscellaneous","Divers")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Corporate Card-Out-of-Poc","")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Traveling Dolby Empl","Employé itinérant de Dolby")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Tools-Equipment-Lab Supplies","Outils-Equipement-Fournitures de laboratoire")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("rounding","Arrondissement")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Building Supplies-Maintenance","Matériaux de construction-Entretien")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Expensed Furniture","Mobilier Dépensé")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Credit for Charges","Crédit pour frais")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Manual P-ment and double payment to be deduct","P-mnt manuel et double paiement à déduire")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Employee insurance travel","Assurance de voyage des employés 2019")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Rent ","Location ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Store Room ","Chambre Stocke")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Evaluation ","Évaluation ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Charges ","Frais ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("On Line ","En ligne ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Building Supplies/Maintenance","/ Matériaux de construction / Entretien")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Music Instruments","Instruments Musicales")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Employee Awards/Recognition", "/ Récompenses des employés / Reconnaissance")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Daily Allowance","/Indemnité journalière")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECLASS ", "RECLASSIFICATION ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Purchase Accounting", "Comptabilité d'achat")
gl['EcritureLib'] = gl["EcritureLib"].str.replace( "EXPAT ", " Expatrié ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("FROM ", "DE ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INVOICE", "FACTURE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CLEANUP", "APUREMENT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Repayment", "Restitution")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Office Furniture", "Meubles de bureau")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("anti-stress treatments", "traitements anti-stress")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("UK Tax Return", "Décl. d'impôt Royaume-Uni")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Office Location", "Location de bureau")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Deliver Service", "Service de livraison")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Foreign Office Support", "Soutien aux bureaux étrangères")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Showroom", "Salle d'exposition")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("aditional Services", "Services supplémentaires ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Cofee consumption Paris office", "Consommation de café Bureau de Paris")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Consultant ", "Expert-conseil")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INVOICE", "FACTURE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Rent-", "Location-")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Corporate", "Entreprise")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("COST ", "COÛT ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("TRAINING", "Formation")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("LIFE DISAB", "Invalidité")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INSU ", "ASSURANCE ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PATENT AWARD", "BREVET")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("EQUIVALENT POUR UNUSED VACATION POUR LEAVE", "CONGÉ DE VACANCES INUTILISÉS")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("SPOT ", "")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("AIRFARE TRANSFER TO PREPAIDS", "TRANSFERT DE TRANSPORT AÉRIEN À PAYÉ D'AVANCE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("WITHHOLDING", "RETRAIT")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Clear ", "Reglement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Clear ", "Reglement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Rent/", "Location/")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Pay ", "Paiement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PAYMENT", "Paiement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("French Income Tax Return;", "Déclaration de revenus française;")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("REVESERVICES", "SERVICES")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("INCLUDED DOUBLE", "DOUBLE INCLUS")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Bank", "Banque")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Promotional Expenses", "/Frais de promotion")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" ACTIVITY ", " activité ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" DEFINED BENEFIT LIABILITY", "PASSIF À AVANTAGES DÉTERMINÉES")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("COÛT PLUS ", "Revient Majoré")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Airline Frais", "/Tarifs aériens")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Tools/Equipment/Lab Supplies", "/Outils / Équipement / Fournitures de laboratoire")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Rent/", "Location/")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Payment Posting", "Paiements")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("COMMISSION D’ACCUMULATION", "ACCUMULATIONS DE COMISSIONS")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ImpôtE", "Impôt")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("MED.INSU", "MED.ASSURANCE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("APPRENTICESHIP_CONTRIBUTIONS_TRUE_UP", "CONTRIBUTIONS À L'APPRENTISSAGE/TRUE UP")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("NET PAY", "SALAIRE NET")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("CASH ", "ARGENT ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Repayment ", "Repaiement ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Acct. ", "Comptab. ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ACCR ", "ACC ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Accr ", "Acc.")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Cash Balance", "Solde de caisse")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECLASS ", "RECLASSEMENT ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("VAT FILING ", "Dépôt de TVA ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Needs to be re-booked due", "KI")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("reclass from", "reclasser de")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECLASS FROM", "reclasser de")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("PAYROLL", "PAIE")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("RECLASS ", "Reclasser")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("DEDICTION","DEDUCTION")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Cash","Argent ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("cash ","argent ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ReclasserIFICATIO","RECLASSEMENT ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("ImpôtS ","Impôts ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Working Repas (Employees Only) ","Repas de travail (employés seulement) ")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("/Banque Frais","/Frais Bancaires")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("MED. INS.","ASSURANCE MED.")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("Facture - Brut'","Facture - Brute'")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20181130_ MK063850","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20181130_ MS063849","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20181130_ MB063846","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20181231_ MK063850","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20181231_ MK063850","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20190228_ MK063850","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20190331_ MB063846","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20190430_ MS063849","FACTURE COUPA")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("_20190430_ MB063846","FACTURE COUPA")
gl['EcritureLib'] = gl['EcritureLib'].str.replace('-', '')
gl['EcritureLib'] = gl['EcritureLib'].str.replace('/', '')
gl['EcritureLib'] = gl['EcritureLib'].str.replace('Contre Passation', 'CP')
mapping_Valuation1 = {" Valuation on": " Évaluation sur"," Valuation on Reverse":" Évaluation sur Contre Passation",
" Reverse Posting":" Contre-Passation d'Ecriture - Conversion de devise sur",
" Translation Using":" Conversion de devise sur"}
mapping_AA1 = {"Reclass from": " Reclassification de", "reclass from": " Reclassification de", "ZEE MEDIA":"ZEE MEDIA Campaignes Numériques", "TRAINING CONTRI. ER JANUARY '19":"FORMATION CONTRI. ER JANVIER' 19",
"TAX FEES":"Taxes","SOCIAL SECURITY: URSSAF":"SÉCURITÉ SOCIALE: URSSAF","SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE","RSM":"SERVICES DE PAIE RSM EF18","RSA":"SERVICES DE PAIE RSA OCT-JAN",
"PRIVATE HEALTH":"SANTÉ PRIVÉE: ASSURANCE MÉDICALE-AXA/","PENSION: PENSION CONTRIBUTIONS - REUNICA":"PENSION: COTISATIONS DE RETRAITE-REUNICA","PENSION: LIFE & DISABILITY INSURANCE - R":"PENSION: ASSURANCE VIE & INVALIDITÉ-R",
"PENSION JANUARY '19":"PENSION JANVIER '19",
"ON CALL JANUARY '19":"Disponible Janvier'19",
"NRE + PROJECT INITIATION FEES":"NRE + FRAIS D’INITIATION AU PROJET (PO 750003","NET PAY JANUARY '19":"Payeante Janvier'19","JANUARY'19":"JANVIER'19",
"LUNCH VOUCHER- WITHHOLDING":"BON DÉJEUNER-RETENUE","HOLIDAY BONUS ACCRUAL FY18/19":"CUMUL DES PRIMES DE VACANCES EF18/19",
"GROSS SALARY JANUARY '19":"SALAIRE BRUT JANVIER' 19","EMEA ACCRUAL P8FY19":"P8FY19 D’ACCUMULATION EMEA","COMMISSION RE-ACCRUAL":"COMMISSION RÉ-ACCUMULATION",
"COMMISSION ACCRUAL":"COMMISSION D’ACCUMULATION","MARCH":"MARS","MAY":"MAI","APRIL":"AVRIL","AUDIT FEES":"HONORAIRES D’AUDIT",
"UNSUBMITTED_UNPOSTED BOA ACCRUAL":"Accumulation BOA non soumise non exposée","UNASSIGNED CREDITCARD BOA ACCRUAL":"NON ASSIGNÉ CREDITCARD BOA ACCUMULATION ",
"EMEA ACCRUAL":"ACCUMULATION EMEA","Exhibit Expenses":"Frais d'exposition","Hotel Tax":"Taxe hôtelière","Company Events":"Événements d'entreprise",
"Public Transport":"Transport public", "Agency Booking Fees":"Frais de réservation d'agence","Working Meals (Employees Only)":"Repas de travail (employés seulement)",
"Airfare":"Billet d'avion","Office Supplies":"Fournitures de bureau","Tolls":"Péages",
"write off difference see e-mail attached":"radiation de la différence voir e-mail ci-joint",
"Manual P/ment and double payment to be deduct":"P/ment manuel et double paiement à déduire","FX DIFFERENCE ON RSU":"DIFFERENCE FX SUR RSU",
"DEFINED BENEFIT LIABILITY-TRUE UP":"RESPONSABILITÉ À PRESTATIONS DÉTERMINÉES-TRUE UP","EXTRA RELEASE FOR STORAGE REVERSED":"EXTRA LIBERATION POUR STOCKAGE CONTREPASSATION",
"RECLASS BANK CHARGES TO CORRECT COST CEN":"RECLASSER LES FRAIS BANCAIRES POUR CORRIGER","PAYROLL INCOME TAXES":"IMPÔTS SUR LES SALAIRES",
"TRAINING TAX TRUE UP":"TAXE DE FORMATION", "FX DIFFERENCE ON STOCK OPTION EXERCISES":"FX DIFFERENCE SUR LES EXERCICES D'OPTIONS STOCK",
"Airline Frais":"Frais de Transport Aérien","Agency Booking Fees":"Frais de Réservation d'Agence","Computer Supplies":"Fournitures informatiques",
"AUDIT FEES":"FRAIS D'AUDIT", "HOLIDAY BONUS ACCRUAL ":"ACCUMULATION DE BONUS DE VACANCES","TAX FEES":"FRAIS D'IMPÔT",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUITION À L’APPRENTISSAGE",
"SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION", "TRAVEL COST":"FRAIS DE VOYAGE", "HOUSING TAX":"TAXE SUR LE LOGEMENT",
"PAYROLL INCOME TAXES":"IMPÔTS SUR LE REVENU DE LA PAIE","INCOME TAX-PAS":"IMPÔT SUR LE REVENU-PAS", "IC SETTLEMENT":"Règlement Interentreprises",
"VACATION TAKEN":"VACANCES PRISES", "SOCIAL SECURITY: APPR. CONTR.":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE",
"POST OF AVRIL DEC IN CORRECT SIGN":"CORRECTION D'ECRITURE AVRIL DEC"}
gl = gl.replace({"JournalLib":mapping_Valuation1}, regex=True)
gl = gl.replace({"JournalLib":mapping_AA1}, regex=True)
gl['JournalLib'] = gl["JournalLib"].str.replace('COST-PLUS', 'Revient Majoré')
gl['JournalLib'] = gl["JournalLib"].str.replace('PRITVAE HEALTH: MEDICAL INSURANCE', 'SANTÉ PRIVÉE: ASSURANCE MÉDICALE')
gl['JournalLib'] = gl["JournalLib"].str.replace('MEDICAL INSURANCE', 'ASSURANCE MÉDICALE')
gl['JournalLib'] = gl["JournalLib"].str.replace('UNASSIGNED', 'NON ATTRIBUÉ')
gl['JournalLib'] = gl["JournalLib"].str.replace('Payout', 'Paiement')
gl['JournalLib'] = gl["JournalLib"].str.replace('FRINGE COST', 'COÛT MARGINAL')
gl['JournalLib'] = gl["JournalLib"].str.replace('PROJECT INITIATION', 'LANCEMENT DU PROJET')
gl['JournalLib'] = gl["JournalLib"].str.replace('ACCRUAL', 'ACCUMULATION')
gl['JournalLib'] = gl["JournalLib"].str.replace('CREDITCARD', 'CARTE DE CRÉDIT')
gl['JournalLib'] = gl["JournalLib"].str.replace('ACCR ', 'ACCUM ')
gl['JournalLib'] = gl["JournalLib"].str.replace('VAT ', 'TVA ')
gl['JournalLib'] = gl["JournalLib"].str.replace('SOCIAL SECURITY ', 'SÉCURITÉ SOCIALE')
gl['JournalLib'] = gl["JournalLib"].str.replace('SEPTEMBER', 'SEPT')
gl['JournalLib'] = gl["JournalLib"].str.replace('TAXBACK', 'Reboursement')
gl['JournalLib'] = gl["JournalLib"].str.replace('REPORT', '')
gl['JournalLib'] = gl["JournalLib"].str.replace("Reverse Posting", "Contre Passation d'Ecriture")
gl['JournalLib'] = gl["JournalLib"].str.replace("BASE RENT", "Location Base")
gl['JournalLib'] = gl["JournalLib"].str.replace("Rent ", "Location ")
gl['JournalLib'] = gl["JournalLib"].str.replace("RENT ", "Location ")
gl['JournalLib'] = gl["JournalLib"].str.replace("CLEARING", "compensation ")
gl['JournalLib'] = gl["JournalLib"].str.replace("clearing", "compensation ")
gl['JournalLib'] = gl["JournalLib"].str.replace("BILLING CHARGES", "FRAIS DE FACTURATION ")
gl['JournalLib'] = gl["JournalLib"].str.replace("UNPAID", "NON PAYÉ")
gl['JournalLib'] = gl["JournalLib"].str.replace("PROPERTY TAX", "IMPÔT FONCIER ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Trans. Using", "Conversion sur")
gl['JournalLib'] = gl["JournalLib"].str.replace("SALARIES", "Salaires")
gl['JournalLib'] = gl["JournalLib"].str.replace("Refund", "Remboursement")
gl['JournalLib'] = gl["JournalLib"].str.replace("REFUND", "Remboursement")
gl['JournalLib'] = gl["JournalLib"].str.replace("no invoice", "pas de facture")
gl['JournalLib'] = gl["JournalLib"].str.replace("COST-PLUS SERVICE REVENUE", "Revenus de service Revient Majoré")
gl['JournalLib'] = gl["JournalLib"].str.replace("SETTLEMENT", "RÈGLEMENT ")
gl['JournalLib'] = gl["JournalLib"].str.replace("PURCHASE", "ACHAT")
gl['JournalLib'] = gl["JournalLib"].str.replace("NON-CP SETTLE", "RÈGLEMENT NON-CP")
gl['JournalLib'] = gl["JournalLib"].str.replace("PAID ", " Payé ")
gl['JournalLib'] = gl["JournalLib"].str.replace("FEES ", "Frais")
gl['JournalLib'] = gl["JournalLib"].str.replace("January", "Janvier")
gl['JournalLib'] = gl["JournalLib"].str.replace("February", "Février")
gl['JournalLib'] = gl["JournalLib"].str.replace("March", "Mars")
gl['JournalLib'] = gl["JournalLib"].str.replace("April", "Avril")
gl['JournalLib'] = gl["JournalLib"].str.replace("May", "Mai")
gl['JournalLib'] = gl["JournalLib"].str.replace("June", "Juin")
gl['JournalLib'] = gl["JournalLib"].str.replace("July", "Juillet")
gl['JournalLib'] = gl["JournalLib"].str.replace("September", "Septembre")
gl['JournalLib'] = gl["JournalLib"].str.replace("Aug.", "Août")
gl['JournalLib'] = gl["JournalLib"].str.replace("JANUARY", "Janvier")
gl['JournalLib'] = gl["JournalLib"].str.replace("FEBRUARY", "Février")
gl['JournalLib'] = gl["JournalLib"].str.replace("MARCH", "Mars")
gl['JournalLib'] = gl["JournalLib"].str.replace("APRIL", "Avril")
gl['JournalLib'] = gl["JournalLib"].str.replace("MAY", "Mai")
gl['JournalLib'] = gl["JournalLib"].str.replace("JUNE", "Juin")
gl['JournalLib'] = gl["JournalLib"].str.replace("JULY", "Juillet")
gl['JournalLib'] = gl["JournalLib"].str.replace("SEPTEMBER", "Septembre")
gl['JournalLib'] = gl["JournalLib"].str.replace("AUGUST.", "Août")
gl['JournalLib'] = gl["JournalLib"].str.replace("NOVEMBER.", "Novembre")
gl['JournalLib'] = gl["JournalLib"].str.replace("DECEMBER.", "Décembre")
gl['JournalLib'] = gl["JournalLib"].str.replace("December", "Décembre")
gl['JournalLib'] = gl["JournalLib"].str.replace("Feb.", "Fév.")
gl['JournalLib'] = gl["JournalLib"].str.replace("Mar.", "Mars")
gl['JournalLib'] = gl["JournalLib"].str.replace("Apr.", "Avril")
gl['JournalLib'] = gl["JournalLib"].str.replace("Aug.", "Août")
gl['JournalLib'] = gl["JournalLib"].str.replace("Aug.", "Août")
gl['JournalLib'] = gl["JournalLib"].str.replace("Reverse ", "Contre-passation ")
gl['JournalLib'] = gl["JournalLib"].str.replace("INTEREST CHARGE", "CHARGE D'INTÉRÊT")
gl['JournalLib'] = gl["JournalLib"].str.replace("-SICK LEAVE PAY", "-Paiement congé maladie")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECLASSEMENTIFICATION", "RECLASSIFICATION")
gl['JournalLib'] = gl["JournalLib"].str.replace("INSTALMENT", "VERSEMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("FIRST", "1ere")
gl['JournalLib'] = gl["JournalLib"].str.replace("FINE LATE PAY.", "Amende pour retard de paiement")
gl['JournalLib'] = gl["JournalLib"].str.replace("-PATERNITY PAY", "Indemnités de paternité")
gl['JournalLib'] = gl["JournalLib"].str.replace("SOCIAL SECURITY:", "SÉCURITÉ SOCIALE:")
gl['JournalLib'] = gl["JournalLib"].str.replace("Trip from", "Voyage de:")
gl['JournalLib'] = gl["JournalLib"].str.replace(" To ", " à")
gl['JournalLib'] = gl["JournalLib"].str.replace("Shipping", "Livraison")
gl['JournalLib'] = gl["JournalLib"].str.replace("VOXEET INTEGRATION COSTS", "COÛTS D'INTÉGRATION DE VOXEET")
gl['JournalLib'] = gl["JournalLib"].str.replace("INCOME TAX", "IMPÔT SUR LE REVENU")
gl['JournalLib'] = gl["JournalLib"].str.replace('Rideshare', 'Covoiturage')
gl['JournalLib'] = gl["JournalLib"].str.replace('Travel Meals', 'Repas de Travail')
gl['JournalLib'] = gl["JournalLib"].str.replace('Fees', 'Frais')
gl['JournalLib'] = gl["JournalLib"].str.replace('Phone', 'Téléphone')
gl['JournalLib'] = gl["JournalLib"].str.replace("Books", "Abonnements")
gl['JournalLib'] = gl["JournalLib"].str.replace("Subcriptions", "Location Base")
gl['JournalLib'] = gl["JournalLib"].str.replace("Meals", "Repas")
gl['JournalLib'] = gl["JournalLib"].str.replace("Entertainment", "divertissement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Third Party", "tiers ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Training Fees", "Frais d0 Formation")
gl['JournalLib'] = gl["JournalLib"].str.replace("Conferences/Tradeshows Registratio", "Conférences/Tradeshows Enregistrement")
gl['JournalLib'] = gl["JournalLib"].str.replace("FOR", "POUR")
gl['JournalLib'] = gl["JournalLib"].str.replace("ROUNDING", "ARRONDISSEMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("STORAGE", "STOCKAGE")
gl['JournalLib'] = gl["JournalLib"].str.replace("VACATION ACCURAL", "Vacances Accumulées")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECEIVABLE ", "Recevables")
gl['JournalLib'] = gl["JournalLib"].str.replace("AFTER PAYOUT ", "APRÈS PAIEMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("CLEAN UP ", "APUREMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("EMPLOYEE TRAVEL INSUR ", "ASSURANCE DE VOYAGE DES EMPLOYÉS")
gl['JournalLib'] = gl["JournalLib"].str.replace("CORRECTION OF", "CORRECTION DE")
gl['JournalLib'] = gl["JournalLib"].str.replace("TAXES PAYROLL", "IMPÔTS SUR LA MASSE SALARIALE")
gl['JournalLib'] = gl["JournalLib"].str.replace("ACCOUNT", "COMPTE")
gl['JournalLib'] = gl["JournalLib"].str.replace("TAX", "Impôt")
gl['JournalLib'] = gl["JournalLib"].str.replace("life disab", "Incapacité de vie")
gl['JournalLib'] = gl["JournalLib"].str.replace("HOUSING TAX","TAXE D'HABITATION")
gl['JournalLib'] = gl["JournalLib"].str.replace("GROSS SALARY","SALAIRE BRUT")
gl['JournalLib'] = gl["JournalLib"].str.replace("Cleaning Services","Nettoyage")
gl['JournalLib'] = gl["JournalLib"].str.replace("Freight","Fret")
gl['JournalLib'] = gl["JournalLib"].str.replace("Membership","adhésion")
gl['JournalLib'] = gl["JournalLib"].str.replace("Air cooling Maintenance","Entretien de refroidissement de l'air")
gl['JournalLib'] = gl["JournalLib"].str.replace("Power on Demand Platform","Plateforme d'energie à la demande")
gl['JournalLib'] = gl["JournalLib"].str.replace("Sanitaire room installation"," Installation de la salle sanitaire")
gl['JournalLib'] = gl["JournalLib"].str.replace("subscription","abonnement")
gl['JournalLib'] = gl["JournalLib"].str.replace("Coffee supplies "," Fournitures de café")
gl['JournalLib'] = gl["JournalLib"].str.replace("Duty and Tax ","Devoir et fiscalité")
gl['JournalLib'] = gl["JournalLib"].str.replace("Electricity ","Electricité ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['JournalLib'] = gl["JournalLib"].str.replace("Security monitoring","Surveillance de la sécurité")
gl['JournalLib'] = gl["JournalLib"].str.replace("Water", "L'EAU")
gl['JournalLib'] = gl["JournalLib"].str.replace("Statutory Audit", "Audit statutaire")
gl['JournalLib'] = gl["JournalLib"].str.replace(" Meeting room screen installation", "Installation de l'écran de la salle de réunion")
gl['JournalLib'] = gl["JournalLib"].str.replace("Water", "L'EAU")
gl['JournalLib'] = gl["JournalLib"].str.replace("Water", "L'EAU")
gl['JournalLib'] = gl["JournalLib"].str.replace("Tax Credit FY 2016", "Crédit d'impôt Exercice 2016")
gl['JournalLib'] = gl["JournalLib"].str.replace("Bank of America Merill Lynch-T&E statement","Déclaration de Merill Lynch")
gl['JournalLib'] = gl["JournalLib"].str.replace("English Translation", "Traduction anglaise")
gl['JournalLib'] = gl["JournalLib"].str.replace("Office Rent", "Location de Bureau")
gl['JournalLib'] = gl["JournalLib"].str.replace("Annual Electrical Verification", "Vérification électrique annuelle ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Health costs ", "Coûts santé")
gl['JournalLib'] = gl["JournalLib"].str.replace("Unlimited-receipt and policy audit", "Vérification illimitée des reçus et audites")
gl['JournalLib'] = gl["JournalLib"].str.replace("Water fountain ", "Fontaine d'eau")
gl['JournalLib'] = gl["JournalLib"].str.replace("Quartely control visit", "Visite de contrôle trimestrielle")
gl['JournalLib'] = gl["JournalLib"].str.replace("Fire extinguishers annual check", "Vérification annuelle des extincteurs")
gl['JournalLib'] = gl["JournalLib"].str.replace("showroom rent", "location de salle d'exposition")
gl['JournalLib'] = gl["JournalLib"].str.replace("AND ACTUAL RECEIV","ET RECETTES RÉELLES")
gl['JournalLib'] = gl["JournalLib"].str.replace("FILING","DÉPÔT")
gl['JournalLib'] = gl["JournalLib"].str.replace("ORDERS","ORDRES")
gl['JournalLib'] = gl["JournalLib"].str.replace("EXCLUDED -DUMMY CREDIT","EXCLU")
gl['JournalLib'] = gl["JournalLib"].str.replace("RELARING TO","RELATIF À")
gl['JournalLib'] = gl["JournalLib"].str.replace("CLEAN UP-","APUREMENT-")
gl['JournalLib'] = gl["JournalLib"].str.replace("2ND INSTALLEMENT","2ème versement")
gl['JournalLib'] = gl["JournalLib"].str.replace("DOUBLE PAYMENT","DOUBLE PAIEMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("CLEAN UP-","APUREMENT-")
gl['JournalLib'] = gl["JournalLib"].str.replace("DUTIES","DROITS")
gl['JournalLib'] = gl["JournalLib"].str.replace("Previous balance","Solde Précédent")
gl['JournalLib'] = gl["JournalLib"].str.replace("Cash fx","Cash FX")
gl['JournalLib'] = gl["JournalLib"].str.replace("PAYROLL INCOME","REVENU DE PAIE")
gl['JournalLib'] = gl["JournalLib"].str.replace("TELEPHONE CHARGES","Frais de Téléphone")
gl['JournalLib'] = gl["JournalLib"].str.replace("Clearing","Compensation")
gl['JournalLib'] = gl["JournalLib"].str.replace("Hotel","Hôtel")
gl['JournalLib'] = gl["JournalLib"].str.replace("Miscellaneous","Divers")
gl['JournalLib'] = gl["JournalLib"].str.replace("Corporate Card-Out-of-Poc","")
gl['JournalLib'] = gl["JournalLib"].str.replace("Traveling Dolby Empl","Employé itinérant de Dolby")
gl['JournalLib'] = gl["JournalLib"].str.replace("Tools-Equipment-Lab Supplies","Outils-Equipement-Fournitures de laboratoire")
gl['JournalLib'] = gl["JournalLib"].str.replace("rounding","Arrondissement")
gl['JournalLib'] = gl["JournalLib"].str.replace("Building Supplies-Maintenance","Matériaux de construction-Entretien")
gl['JournalLib'] = gl["JournalLib"].str.replace("Expensed Furniture","Mobilier Dépensé")
gl['JournalLib'] = gl["JournalLib"].str.replace("Credit for Charges","Crédit pour frais")
gl['JournalLib'] = gl["JournalLib"].str.replace("Manual P-ment and double payment to be deduct","P-mnt manuel et double paiement à déduire")
gl['JournalLib'] = gl["JournalLib"].str.replace("Employee insurance travel","Assurance de voyage des employés 2019")
gl['JournalLib'] = gl["JournalLib"].str.replace("Rent ","Location ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['JournalLib'] = gl["JournalLib"].str.replace("Store Room ","Chambre Stocke")
gl['JournalLib'] = gl["JournalLib"].str.replace("Evaluation ","Évaluation ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Charges ","Frais ")
gl['JournalLib'] = gl["JournalLib"].str.replace("On Line ","En ligne ")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Building Supplies/Maintenance","/ Matériaux de construction / Entretien")
gl['JournalLib'] = gl["JournalLib"].str.replace("Music Instruments","Instruments Musicales")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Employee Awards/Recognition", "/ Récompenses des employés / Reconnaissance")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Daily Allowance","/Indemnité journalière")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECLASS ", "RECLASSIFICATION ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Purchase Accounting", "Comptabilité d'achat")
gl['JournalLib'] = gl["JournalLib"].str.replace( "EXPAT ", " Expatrié ")
gl['JournalLib'] = gl["JournalLib"].str.replace("FROM ", "DE ")
gl['JournalLib'] = gl["JournalLib"].str.replace("INVOICE", "FACTURE")
gl['JournalLib'] = gl["JournalLib"].str.replace("CLEANUP", "APUREMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("Repayment", "Restitution")
gl['JournalLib'] = gl["JournalLib"].str.replace("Office Furniture", "Meubles de bureau")
gl['JournalLib'] = gl["JournalLib"].str.replace("anti-stress treatments", "traitements anti-stress")
gl['JournalLib'] = gl["JournalLib"].str.replace("UK Tax Return", "Décl. d'impôt Royaume-Uni")
gl['JournalLib'] = gl["JournalLib"].str.replace("Office Location", "Location de bureau")
gl['JournalLib'] = gl["JournalLib"].str.replace("Deliver Service", "Service de livraison")
gl['JournalLib'] = gl["JournalLib"].str.replace("Foreign Office Support", "Soutien aux bureaux étrangères")
gl['JournalLib'] = gl["JournalLib"].str.replace("Showroom", "Salle d'exposition")
gl['JournalLib'] = gl["JournalLib"].str.replace("aditional Services", "Services supplémentaires ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Cofee consumption Paris office", "Consommation de café Bureau de Paris")
gl['JournalLib'] = gl["JournalLib"].str.replace("Consultant ", "Expert-conseil")
gl['JournalLib'] = gl["JournalLib"].str.replace("INVOICE", "FACTURE")
gl['JournalLib'] = gl["JournalLib"].str.replace("Rent-", "Location-")
gl['JournalLib'] = gl["JournalLib"].str.replace("Corporate", "Entreprise")
gl['JournalLib'] = gl["JournalLib"].str.replace("COST ", "COÛT ")
gl['JournalLib'] = gl["JournalLib"].str.replace("TRAINING", "Formation")
gl['JournalLib'] = gl["JournalLib"].str.replace("LIFE DISAB", "Invalidité")
gl['JournalLib'] = gl["JournalLib"].str.replace("INSU ", "ASSURANCE ")
gl['JournalLib'] = gl["JournalLib"].str.replace("PATENT AWARD", "BREVET")
gl['JournalLib'] = gl["JournalLib"].str.replace("EQUIVALENT POUR UNUSED VACATION POUR LEAVE", "CONGÉ DE VACANCES INUTILISÉS")
gl['JournalLib'] = gl["JournalLib"].str.replace("SPOT ", "")
gl['JournalLib'] = gl["JournalLib"].str.replace("AIRFARE TRANSFER TO PREPAIDS", "TRANSFERT DE TRANSPORT AÉRIEN À PAYÉ D'AVANCE")
gl['JournalLib'] = gl["JournalLib"].str.replace("WITHHOLDING", "RETRAIT")
gl['JournalLib'] = gl["JournalLib"].str.replace("Clear ", "Reglement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Clear ", "Reglement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Rent/", "Location/")
gl['JournalLib'] = gl["JournalLib"].str.replace("Pay ", "Paiement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("PAYMENT", "Paiement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("French Income Tax Return;", "Déclaration de revenus française;")
gl['JournalLib'] = gl["JournalLib"].str.replace("REVESERVICES", "SERVICES")
gl['JournalLib'] = gl["JournalLib"].str.replace("INCLUDED DOUBLE", "DOUBLE INCLUS")
gl['JournalLib'] = gl["JournalLib"].str.replace("Bank", "Banque")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Promotional Expenses", "/Frais de promotion")
gl['JournalLib'] = gl["JournalLib"].str.replace(" ACTIVITY ", " activité ")
gl['JournalLib'] = gl["JournalLib"].str.replace(" DEFINED BENEFIT LIABILITY", "PASSIF À AVANTAGES DÉTERMINÉES")
gl['JournalLib'] = gl["JournalLib"].str.replace("COÛT PLUS ", "Revient Majoré")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Airline Frais", "/Tarifs aériens")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Tools/Equipment/Lab Supplies", "/Outils / Équipement / Fournitures de laboratoire")
gl['JournalLib'] = gl["JournalLib"].str.replace("Rent/", "Location/")
gl['JournalLib'] = gl["JournalLib"].str.replace("Payment Posting", "Paiements")
gl['JournalLib'] = gl["JournalLib"].str.replace("COMMISSION D’ACCUMULATION", "ACCUMULATIONS DE COMISSIONS")
gl['JournalLib'] = gl["JournalLib"].str.replace("ImpôtE", "Impôt")
gl['JournalLib'] = gl["JournalLib"].str.replace("MED.INSU", "MED.ASSURANCE")
gl['JournalLib'] = gl["JournalLib"].str.replace("APPRENTICESHIP_CONTRIBUTIONS_TRUE_UP", "CONTRIBUTIONS À L'APPRENTISSAGE/TRUE UP")
gl['JournalLib'] = gl["JournalLib"].str.replace("NET PAY", "SALAIRE NET")
gl['JournalLib'] = gl["JournalLib"].str.replace("CASH ", "ARGENT ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Repayment ", "Repaiement ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Acct. ", "Comptab. ")
gl['JournalLib'] = gl["JournalLib"].str.replace("ACCR ", "ACC ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Accr ", "Acc.")
gl['JournalLib'] = gl["JournalLib"].str.replace("Cash Balance", "Solde de caisse")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECLASS ", "RECLASSEMENT ")
gl['JournalLib'] = gl["JournalLib"].str.replace("VAT FILING ", "Dépôt de TVA ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Needs to be re-booked due", "KI")
gl['JournalLib'] = gl["JournalLib"].str.replace("reclass from", "reclasser de")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECLASS FROM", "reclasser de")
gl['JournalLib'] = gl["JournalLib"].str.replace("PAYROLL", "PAIE")
gl['JournalLib'] = gl["JournalLib"].str.replace("RECLASS ", "Reclasser")
gl['JournalLib'] = gl["JournalLib"].str.replace("DEDICTION","DEDUCTION")
gl['JournalLib'] = gl["JournalLib"].str.replace("Cash","Argent ")
gl['JournalLib'] = gl["JournalLib"].str.replace("cash ","argent ")
gl['JournalLib'] = gl["JournalLib"].str.replace("ReclasserIFICATIO","RECLASSEMENT ")
gl['JournalLib'] = gl["JournalLib"].str.replace("ImpôtS ","Impôts ")
gl['JournalLib'] = gl["JournalLib"].str.replace("Working Repas (Employees Only) ","Repas de travail (employés seulement) ")
gl['JournalLib'] = gl["JournalLib"].str.replace("/Banque Frais","/Frais Bancaires")
gl['JournalLib'] = gl["JournalLib"].str.replace("MED. INS.","ASSURANCE MED.")
gl['JournalLib'] = gl["JournalLib"].str.replace("AJE WIRE LOG TRAN","AJE VERSEMENT")
gl['JournalLib'] = gl["JournalLib"].str.replace("JUN'","JUIN'")
gl['JournalLib'] = gl["JournalLib"].str.replace("Deferred Rent18 rue de Lo","Loyer différé 18 Rue de Lo")
gl['JournalLib'] = gl["JournalLib"].str.replace("Facture - Brut'","Facture - Brute")
gl['JournalLib'] = gl["JournalLib"].str.replace("T&E","VD")
gl['JournalLib'] = gl["JournalLib"].str.replace("/","")
gl['JournalLib'] = gl["JournalLib"].str.replace("Inv","Facture")
gl['JournalLib'] = gl["JournalLib"].str.replace("2019`","2019")
gl['JournalLib'] = gl["JournalLib"].str.replace("-2014V","")
mapping_Valuation1 = {" Valuation on": " Évaluation sur"," Valuation on Reverse":" Évaluation sur Contre Passation",
" Reverse Posting":" Contre-Passation d'Ecriture - Conversion de devise sur",
" Translation Using":" Conversion de devise sur"}
mapping_AA1 = {"Reclass from": " Reclassification de", "reclass from": " Reclassification de", "ZEE MEDIA":"ZEE MEDIA Campaignes Numériques", "TRAINING CONTRI. ER JANUARY '19":"FORMATION CONTRI. ER JANVIER' 19",
"TAX FEES":"Taxes","SOCIAL SECURITY: URSSAF":"SÉCURITÉ SOCIALE: URSSAF","SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE","RSM":"SERVICES DE PAIE RSM EF18","RSA":"SERVICES DE PAIE RSA OCT-JAN",
"PRIVATE HEALTH":"SANTÉ PRIVÉE: ASSURANCE MÉDICALE-AXA/","PENSION: PENSION CONTRIBUTIONS - REUNICA":"PENSION: COTISATIONS DE RETRAITE-REUNICA","PENSION: LIFE & DISABILITY INSURANCE - R":"PENSION: ASSURANCE VIE & INVALIDITÉ-R",
"PENSION JANUARY '19":"PENSION JANVIER '19",
"ON CALL JANUARY '19":"Disponible Janvier'19",
"NRE + PROJECT INITIATION FEES":"NRE + FRAIS D’INITIATION AU PROJET (PO 750003","NET PAY JANUARY '19":"Payeante Janvier'19","JANUARY'19":"JANVIER'19",
"LUNCH VOUCHER- WITHHOLDING":"BON DÉJEUNER-RETENUE","HOLIDAY BONUS ACCRUAL FY18/19":"CUMUL DES PRIMES DE VACANCES EF18/19",
"GROSS SALARY JANUARY '19":"SALAIRE BRUT JANVIER' 19","EMEA ACCRUAL P8FY19":"P8FY19 D’ACCUMULATION EMEA","COMMISSION RE-ACCRUAL":"COMMISSION RÉ-ACCUMULATION",
"COMMISSION ACCRUAL":"COMMISSION D’ACCUMULATION","MARCH":"MARS","MAY":"MAI","APRIL":"AVRIL","AUDIT FEES":"HONORAIRES D’AUDIT",
"UNSUBMITTED_UNPOSTED BOA ACCRUAL":"Accumulation BOA non soumise non exposée","UNASSIGNED CREDITCARD BOA ACCRUAL":"NON ASSIGNÉ CREDITCARD BOA ACCUMULATION ",
"EMEA ACCRUAL":"ACCUMULATION EMEA","Exhibit Expenses":"Frais d'exposition","Hotel Tax":"Taxe hôtelière","Company Events":"Événements d'entreprise",
"Public Transport":"Transport public", "Agency Booking Fees":"Frais de réservation d'agence","Working Meals (Employees Only)":"Repas de travail (employés seulement)",
"Airfare":"Billet d'avion","Office Supplies":"Fournitures de bureau","Tolls":"Péages",
"write off difference see e-mail attached":"radiation de la différence voir e-mail ci-joint",
"Manual P/ment and double payment to be deduct":"P/ment manuel et double paiement à déduire","FX DIFFERENCE ON RSU":"DIFFERENCE FX SUR RSU",
"DEFINED BENEFIT LIABILITY-TRUE UP":"RESPONSABILITÉ À PRESTATIONS DÉTERMINÉES-TRUE UP","EXTRA RELEASE FOR STORAGE REVERSED":"EXTRA LIBERATION POUR STOCKAGE CONTREPASSATION",
"RECLASS BANK CHARGES TO CORRECT COST CEN":"RECLASSER LES FRAIS BANCAIRES POUR CORRIGER","PAYROLL INCOME TAXES":"IMPÔTS SUR LES SALAIRES",
"TRAINING TAX TRUE UP":"TAXE DE FORMATION", "FX DIFFERENCE ON STOCK OPTION EXERCISES":"FX DIFFERENCE SUR LES EXERCICES D'OPTIONS STOCK",
"Airline Frais":"Frais de Transport Aérien","Agency Booking Fees":"Frais de Réservation d'Agence","Computer Supplies":"Fournitures informatiques",
"AUDIT FEES":"FRAIS D'AUDIT", "HOLIDAY BONUS ACCRUAL ":"ACCUMULATION DE BONUS DE VACANCES","TAX FEES":"FRAIS D'IMPÔT",
"SOCIAL SECURITY: APPRENTICESHIP CONTRIBU":"SÉCURITÉ SOCIALE: CONTRIBUITION À L’APPRENTISSAGE",
"SOCIAL SECURITY: TRAINING CONTRIBUTIONS":"SÉCURITÉ SOCIALE: CONTRIBUTIONS À LA FORMATION", "TRAVEL COST":"FRAIS DE VOYAGE", "HOUSING TAX":"TAXE SUR LE LOGEMENT",
"PAYROLL INCOME TAXES":"IMPÔTS SUR LE REVENU DE LA PAIE","INCOME TAX-PAS":"IMPÔT SUR LE REVENU-PAS", "IC SETTLEMENT":"Règlement Interentreprises",
"VACATION TAKEN":"VACANCES PRISES", "SOCIAL SECURITY: APPR. CONTR.":"SÉCURITÉ SOCIALE: CONTRIBUTION À L’APPRENTISSAGE",
"POST OF AVRIL DEC IN CORRECT SIGN":"CORRECTION D'ECRITURE AVRIL DEC"}
gl = gl.replace({"PieceRef":mapping_Valuation1}, regex=True)
gl = gl.replace({"PieceRef":mapping_AA1}, regex=True)
gl['PieceRef'] = gl["PieceRef"].str.replace('COST-PLUS', 'Revient Majoré')
gl['PieceRef'] = gl["PieceRef"].str.replace('PRITVAE HEALTH: MEDICAL INSURANCE', 'SANTÉ PRIVÉE: ASSURANCE MÉDICALE')
gl['PieceRef'] = gl["PieceRef"].str.replace('MEDICAL INSURANCE', 'ASSURANCE MÉDICALE')
gl['PieceRef'] = gl["PieceRef"].str.replace('UNASSIGNED', 'NON ATTRIBUÉ')
gl['PieceRef'] = gl["PieceRef"].str.replace('Payout', 'Paiement')
gl['PieceRef'] = gl["PieceRef"].str.replace('FRINGE COST', 'COÛT MARGINAL')
gl['PieceRef'] = gl["PieceRef"].str.replace('PROJECT INITIATION', 'LANCEMENT DU PROJET')
gl['PieceRef'] = gl["PieceRef"].str.replace('ACCRUAL', 'ACCUMULATION')
gl['PieceRef'] = gl["PieceRef"].str.replace('CREDITCARD', 'CARTE DE CRÉDIT')
gl['PieceRef'] = gl["PieceRef"].str.replace('ACCR ', 'ACCUM ')
gl['PieceRef'] = gl["PieceRef"].str.replace('VAT ', 'TVA ')
gl['PieceRef'] = gl["PieceRef"].str.replace('SOCIAL SECURITY ', 'SÉCURITÉ SOCIALE')
gl['PieceRef'] = gl["PieceRef"].str.replace('SEPTEMBER', 'SEPT')
gl['PieceRef'] = gl["PieceRef"].str.replace('TAXBACK', 'Reboursement')
gl['PieceRef'] = gl["PieceRef"].str.replace('REPORT', '')
gl['PieceRef'] = gl["PieceRef"].str.replace("Reverse Posting", "Contre Passation d'Ecriture")
gl['PieceRef'] = gl["PieceRef"].str.replace("BASE RENT", "Location Base")
gl['PieceRef'] = gl["PieceRef"].str.replace("Rent ", "Location ")
gl['PieceRef'] = gl["PieceRef"].str.replace("RENT ", "Location ")
gl['PieceRef'] = gl["PieceRef"].str.replace("CLEARING", "compensation ")
gl['PieceRef'] = gl["PieceRef"].str.replace("clearing", "compensation ")
gl['PieceRef'] = gl["PieceRef"].str.replace("BILLING CHARGES", "FRAIS DE FACTURATION ")
gl['PieceRef'] = gl["PieceRef"].str.replace("UNPAID", "NON PAYÉ")
gl['PieceRef'] = gl["PieceRef"].str.replace("PROPERTY TAX", "IMPÔT FONCIER ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Trans. Using", "Conversion sur")
gl['PieceRef'] = gl["PieceRef"].str.replace("SALARIES", "Salaires")
gl['PieceRef'] = gl["PieceRef"].str.replace("Refund", "Remboursement")
gl['PieceRef'] = gl["PieceRef"].str.replace("REFUND", "Remboursement")
gl['PieceRef'] = gl["PieceRef"].str.replace("no invoice", "pas de facture")
gl['PieceRef'] = gl["PieceRef"].str.replace("COST-PLUS SERVICE REVENUE", "Revenus de service Revient Majoré")
gl['PieceRef'] = gl["PieceRef"].str.replace("SETTLEMENT", "RÈGLEMENT ")
gl['PieceRef'] = gl["PieceRef"].str.replace("PURCHASE", "ACHAT")
gl['PieceRef'] = gl["PieceRef"].str.replace("NON-CP SETTLE", "RÈGLEMENT NON-CP")
gl['PieceRef'] = gl["PieceRef"].str.replace("PAID ", " Payé ")
gl['PieceRef'] = gl["PieceRef"].str.replace("FEES ", "Frais")
gl['PieceRef'] = gl["PieceRef"].str.replace("January", "Janvier")
gl['PieceRef'] = gl["PieceRef"].str.replace("February", "Février")
gl['PieceRef'] = gl["PieceRef"].str.replace("March", "Mars")
gl['PieceRef'] = gl["PieceRef"].str.replace("April", "Avril")
gl['PieceRef'] = gl["PieceRef"].str.replace("May", "Mai")
gl['PieceRef'] = gl["PieceRef"].str.replace("June", "Juin")
gl['PieceRef'] = gl["PieceRef"].str.replace("July", "Juillet")
gl['PieceRef'] = gl["PieceRef"].str.replace("September", "Septembre")
gl['PieceRef'] = gl["PieceRef"].str.replace("Aug.", "Août")
gl['PieceRef'] = gl["PieceRef"].str.replace("JANUARY", "Janvier")
gl['PieceRef'] = gl["PieceRef"].str.replace("FEBRUARY", "Février")
gl['PieceRef'] = gl["PieceRef"].str.replace("MARCH", "Mars")
gl['PieceRef'] = gl["PieceRef"].str.replace("APRIL", "Avril")
gl['PieceRef'] = gl["PieceRef"].str.replace("MAY", "Mai")
gl['PieceRef'] = gl["PieceRef"].str.replace("JUNE", "Juin")
gl['PieceRef'] = gl["PieceRef"].str.replace("JULY", "Juillet")
gl['PieceRef'] = gl["PieceRef"].str.replace("SEPTEMBER", "Septembre")
gl['PieceRef'] = gl["PieceRef"].str.replace("AUGUST.", "Août")
gl['PieceRef'] = gl["PieceRef"].str.replace("NOVEMBER.", "Novembre")
gl['PieceRef'] = gl["PieceRef"].str.replace("DECEMBER.", "Décembre")
gl['PieceRef'] = gl["PieceRef"].str.replace("December", "Décembre")
gl['PieceRef'] = gl["PieceRef"].str.replace("Feb.", "Fév.")
gl['PieceRef'] = gl["PieceRef"].str.replace("Mar.", "Mars")
gl['PieceRef'] = gl["PieceRef"].str.replace("Apr.", "Avril")
gl['PieceRef'] = gl["PieceRef"].str.replace("Aug.", "Août")
gl['PieceRef'] = gl["PieceRef"].str.replace("Aug.", "Août")
gl['PieceRef'] = gl["PieceRef"].str.replace("Reverse ", "Contre-passation ")
gl['PieceRef'] = gl["PieceRef"].str.replace("INTEREST CHARGE", "CHARGE D'INTÉRÊT")
gl['PieceRef'] = gl["PieceRef"].str.replace("-SICK LEAVE PAY", "-Paiement congé maladie")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECLASSEMENTIFICATION", "RECLASSIFICATION")
gl['PieceRef'] = gl["PieceRef"].str.replace("INSTALMENT", "VERSEMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("FIRST", "1ere")
gl['PieceRef'] = gl["PieceRef"].str.replace("FINE LATE PAY.", "Amende pour retard de paiement")
gl['PieceRef'] = gl["PieceRef"].str.replace("-PATERNITY PAY", "Indemnités de paternité")
gl['PieceRef'] = gl["PieceRef"].str.replace("SOCIAL SECURITY:", "SÉCURITÉ SOCIALE:")
gl['PieceRef'] = gl["PieceRef"].str.replace("Trip from", "Voyage de:")
gl['PieceRef'] = gl["PieceRef"].str.replace(" To ", " à")
gl['PieceRef'] = gl["PieceRef"].str.replace("Shipping", "Livraison")
gl['PieceRef'] = gl["PieceRef"].str.replace("VOXEET INTEGRATION COSTS", "COÛTS D'INTÉGRATION DE VOXEET")
gl['PieceRef'] = gl["PieceRef"].str.replace("INCOME TAX", "IMPÔT SUR LE REVENU")
gl['PieceRef'] = gl["PieceRef"].str.replace('Rideshare', 'Covoiturage')
gl['PieceRef'] = gl["PieceRef"].str.replace('Travel Meals', 'Repas de Travail')
gl['PieceRef'] = gl["PieceRef"].str.replace('Fees', 'Frais')
gl['PieceRef'] = gl["PieceRef"].str.replace('Phone', 'Téléphone')
gl['PieceRef'] = gl["PieceRef"].str.replace("Books", "Abonnements")
gl['PieceRef'] = gl["PieceRef"].str.replace("Subcriptions", "Location Base")
gl['PieceRef'] = gl["PieceRef"].str.replace("Meals", "Repas")
gl['PieceRef'] = gl["PieceRef"].str.replace("Entertainment", "divertissement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Third Party", "tiers ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Training Fees", "Frais d0 Formation")
gl['PieceRef'] = gl["PieceRef"].str.replace("Conferences/Tradeshows Registratio", "Conférences/Tradeshows Enregistrement")
gl['PieceRef'] = gl["PieceRef"].str.replace("FOR", "POUR")
gl['PieceRef'] = gl["PieceRef"].str.replace("ROUNDING", "ARRONDISSEMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("STORAGE", "STOCKAGE")
gl['PieceRef'] = gl["PieceRef"].str.replace("VACATION ACCURAL", "Vacances Accumulées")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECEIVABLE ", "Recevables")
gl['PieceRef'] = gl["PieceRef"].str.replace("AFTER PAYOUT ", "APRÈS PAIEMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("CLEAN UP ", "APUREMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("EMPLOYEE TRAVEL INSUR ", "ASSURANCE DE VOYAGE DES EMPLOYÉS")
gl['PieceRef'] = gl["PieceRef"].str.replace("CORRECTION OF", "CORRECTION DE")
gl['PieceRef'] = gl["PieceRef"].str.replace("TAXES PAYROLL", "IMPÔTS SUR LA MASSE SALARIALE")
gl['PieceRef'] = gl["PieceRef"].str.replace("ACCOUNT", "COMPTE")
gl['PieceRef'] = gl["PieceRef"].str.replace("TAX", "Impôt")
gl['PieceRef'] = gl["PieceRef"].str.replace("life disab", "Incapacité de vie")
gl['PieceRef'] = gl["PieceRef"].str.replace("HOUSING TAX","TAXE D'HABITATION")
gl['PieceRef'] = gl["PieceRef"].str.replace("GROSS SALARY","SALAIRE BRUT")
gl['PieceRef'] = gl["PieceRef"].str.replace("Cleaning Services","Nettoyage")
gl['PieceRef'] = gl["PieceRef"].str.replace("Freight","Fret")
gl['PieceRef'] = gl["PieceRef"].str.replace("Membership","adhésion")
gl['PieceRef'] = gl["PieceRef"].str.replace("Air cooling Maintenance","Entretien de refroidissement de l'air")
gl['PieceRef'] = gl["PieceRef"].str.replace("Power on Demand Platform","Plateforme d'energie à la demande")
gl['PieceRef'] = gl["PieceRef"].str.replace("Sanitaire room installation"," Installation de la salle sanitaire")
gl['PieceRef'] = gl["PieceRef"].str.replace("subscription","abonnement")
gl['PieceRef'] = gl["PieceRef"].str.replace("Coffee supplies "," Fournitures de café")
gl['PieceRef'] = gl["PieceRef"].str.replace("Duty and Tax ","Devoir et fiscalité")
gl['PieceRef'] = gl["PieceRef"].str.replace("Electricity ","Electricité ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['PieceRef'] = gl["PieceRef"].str.replace("Security monitoring","Surveillance de la sécurité")
gl['PieceRef'] = gl["PieceRef"].str.replace("Water", "L'EAU")
gl['PieceRef'] = gl["PieceRef"].str.replace("Statutory Audit", "Audit statutaire")
gl['PieceRef'] = gl["PieceRef"].str.replace(" Meeting room screen installation", "Installation de l'écran de la salle de réunion")
gl['PieceRef'] = gl["PieceRef"].str.replace("Water", "L'EAU")
gl['PieceRef'] = gl["PieceRef"].str.replace("Water", "L'EAU")
gl['PieceRef'] = gl["PieceRef"].str.replace("Tax Credit FY 2016", "Crédit d'impôt Exercice 2016")
gl['PieceRef'] = gl["PieceRef"].str.replace("Bank of America Merill Lynch-T&E statement","Déclaration de Merill Lynch")
gl['PieceRef'] = gl["PieceRef"].str.replace("English Translation", "Traduction anglaise")
gl['PieceRef'] = gl["PieceRef"].str.replace("Office Rent", "Location de Bureau")
gl['PieceRef'] = gl["PieceRef"].str.replace("Annual Electrical Verification", "Vérification électrique annuelle ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Health costs ", "Coûts santé")
gl['PieceRef'] = gl["PieceRef"].str.replace("Unlimited-receipt and policy audit", "Vérification illimitée des reçus et audites")
gl['PieceRef'] = gl["PieceRef"].str.replace("Water fountain ", "Fontaine d'eau")
gl['PieceRef'] = gl["PieceRef"].str.replace("Quartely control visit", "Visite de contrôle trimestrielle")
gl['PieceRef'] = gl["PieceRef"].str.replace("Fire extinguishers annual check", "Vérification annuelle des extincteurs")
gl['PieceRef'] = gl["PieceRef"].str.replace("showroom rent", "location de salle d'exposition")
gl['PieceRef'] = gl["PieceRef"].str.replace("AND ACTUAL RECEIV","ET RECETTES RÉELLES")
gl['PieceRef'] = gl["PieceRef"].str.replace("FILING","DÉPÔT")
gl['PieceRef'] = gl["PieceRef"].str.replace("ORDERS","ORDRES")
gl['PieceRef'] = gl["PieceRef"].str.replace("EXCLUDED -DUMMY CREDIT","EXCLU")
gl['PieceRef'] = gl["PieceRef"].str.replace("RELARING TO","RELATIF À")
gl['PieceRef'] = gl["PieceRef"].str.replace("CLEAN UP-","APUREMENT-")
gl['PieceRef'] = gl["PieceRef"].str.replace("2ND INSTALLEMENT","2ème versement")
gl['PieceRef'] = gl["PieceRef"].str.replace("DOUBLE PAYMENT","DOUBLE PAIEMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("CLEAN UP-","APUREMENT-")
gl['PieceRef'] = gl["PieceRef"].str.replace("DUTIES","DROITS")
gl['PieceRef'] = gl["PieceRef"].str.replace("Previous balance","Solde Précédent")
gl['PieceRef'] = gl["PieceRef"].str.replace("Cash fx","Cash FX")
gl['PieceRef'] = gl["PieceRef"].str.replace("PAYROLL INCOME","REVENU DE PAIE")
gl['PieceRef'] = gl["PieceRef"].str.replace("TELEPHONE CHARGES","Frais de Téléphone")
gl['PieceRef'] = gl["PieceRef"].str.replace("Clearing","Compensation")
gl['PieceRef'] = gl["PieceRef"].str.replace("Hotel","Hôtel")
gl['PieceRef'] = gl["PieceRef"].str.replace("Miscellaneous","Divers")
gl['PieceRef'] = gl["PieceRef"].str.replace("Corporate Card-Out-of-Poc","")
gl['PieceRef'] = gl["PieceRef"].str.replace("Traveling Dolby Empl","Employé itinérant de Dolby")
gl['PieceRef'] = gl["PieceRef"].str.replace("Tools-Equipment-Lab Supplies","Outils-Equipement-Fournitures de laboratoire")
gl['PieceRef'] = gl["PieceRef"].str.replace("rounding","Arrondissement")
gl['PieceRef'] = gl["PieceRef"].str.replace("Building Supplies-Maintenance","Matériaux de construction-Entretien")
gl['PieceRef'] = gl["PieceRef"].str.replace("Expensed Furniture","Mobilier Dépensé")
gl['PieceRef'] = gl["PieceRef"].str.replace("Credit for Charges","Crédit pour frais")
gl['PieceRef'] = gl["PieceRef"].str.replace("Manual P-ment and double payment to be deduct","P-mnt manuel et double paiement à déduire")
gl['PieceRef'] = gl["PieceRef"].str.replace("Employee insurance travel","Assurance de voyage des employés 2019")
gl['PieceRef'] = gl["PieceRef"].str.replace("Rent ","Location ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Lunch vouchers ","Bons déjeuner")
gl['PieceRef'] = gl["PieceRef"].str.replace("Store Room ","Chambre Stocke")
gl['PieceRef'] = gl["PieceRef"].str.replace("Evaluation ","Évaluation ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Charges ","Frais ")
gl['PieceRef'] = gl["PieceRef"].str.replace("On Line ","En ligne ")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Building Supplies/Maintenance","/ Matériaux de construction / Entretien")
gl['PieceRef'] = gl["PieceRef"].str.replace("Music Instruments","Instruments Musicales")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Employee Awards/Recognition", "/ Récompenses des employés / Reconnaissance")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Daily Allowance","/Indemnité journalière")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECLASS ", "RECLASSIFICATION ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Purchase Accounting", "Comptabilité d'achat")
gl['PieceRef'] = gl["PieceRef"].str.replace( "EXPAT ", " Expatrié ")
gl['PieceRef'] = gl["PieceRef"].str.replace("FROM ", "DE ")
gl['PieceRef'] = gl["PieceRef"].str.replace("INVOICE", "FACTURE")
gl['PieceRef'] = gl["PieceRef"].str.replace("CLEANUP", "APUREMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("Repayment", "Restitution")
gl['PieceRef'] = gl["PieceRef"].str.replace("Office Furniture", "Meubles de bureau")
gl['PieceRef'] = gl["PieceRef"].str.replace("anti-stress treatments", "traitements anti-stress")
gl['PieceRef'] = gl["PieceRef"].str.replace("UK Tax Return", "Décl. d'impôt Royaume-Uni")
gl['PieceRef'] = gl["PieceRef"].str.replace("Office Location", "Location de bureau")
gl['PieceRef'] = gl["PieceRef"].str.replace("Deliver Service", "Service de livraison")
gl['PieceRef'] = gl["PieceRef"].str.replace("Foreign Office Support", "Soutien aux bureaux étrangères")
gl['PieceRef'] = gl["PieceRef"].str.replace("Showroom", "Salle d'exposition")
gl['PieceRef'] = gl["PieceRef"].str.replace("aditional Services", "Services supplémentaires ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Cofee consumption Paris office", "Consommation de café Bureau de Paris")
gl['PieceRef'] = gl["PieceRef"].str.replace("Consultant ", "Expert-conseil")
gl['PieceRef'] = gl["PieceRef"].str.replace("INVOICE", "FACTURE")
gl['PieceRef'] = gl["PieceRef"].str.replace("Rent-", "Location-")
gl['PieceRef'] = gl["PieceRef"].str.replace("Corporate", "Entreprise")
gl['PieceRef'] = gl["PieceRef"].str.replace("COST ", "COÛT ")
gl['PieceRef'] = gl["PieceRef"].str.replace("TRAINING", "Formation")
gl['PieceRef'] = gl["PieceRef"].str.replace("LIFE DISAB", "Invalidité")
gl['PieceRef'] = gl["PieceRef"].str.replace("INSU ", "ASSURANCE ")
gl['PieceRef'] = gl["PieceRef"].str.replace("PATENT AWARD", "BREVET")
gl['PieceRef'] = gl["PieceRef"].str.replace("EQUIVALENT POUR UNUSED VACATION POUR LEAVE", "CONGÉ DE VACANCES INUTILISÉS")
gl['PieceRef'] = gl["PieceRef"].str.replace("SPOT ", "")
gl['PieceRef'] = gl["PieceRef"].str.replace("AIRFARE TRANSFER TO PREPAIDS", "TRANSFERT DE TRANSPORT AÉRIEN À PAYÉ D'AVANCE")
gl['PieceRef'] = gl["PieceRef"].str.replace("WITHHOLDING", "RETRAIT")
gl['PieceRef'] = gl["PieceRef"].str.replace("Clear ", "Reglement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Clear ", "Reglement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Rent/", "Location/")
gl['PieceRef'] = gl["PieceRef"].str.replace("Pay ", "Paiement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("PAYMENT", "Paiement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("French Income Tax Return;", "Déclaration de revenus française;")
gl['PieceRef'] = gl["PieceRef"].str.replace("REVESERVICES", "SERVICES")
gl['PieceRef'] = gl["PieceRef"].str.replace("INCLUDED DOUBLE", "DOUBLE INCLUS")
gl['PieceRef'] = gl["PieceRef"].str.replace("Bank", "Banque")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Promotional Expenses", "/Frais de promotion")
gl['PieceRef'] = gl["PieceRef"].str.replace(" ACTIVITY ", " activité ")
gl['PieceRef'] = gl["PieceRef"].str.replace(" DEFINED BENEFIT LIABILITY", "PASSIF À AVANTAGES DÉTERMINÉES")
gl['PieceRef'] = gl["PieceRef"].str.replace("COÛT PLUS ", "Revient Majoré")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Airline Frais", "/Tarifs aériens")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Tools/Equipment/Lab Supplies", "/Outils / Équipement / Fournitures de laboratoire")
gl['PieceRef'] = gl["PieceRef"].str.replace("Rent/", "Location/")
gl['PieceRef'] = gl["PieceRef"].str.replace("Payment Posting", "Paiements")
gl['PieceRef'] = gl["PieceRef"].str.replace("COMMISSION D’ACCUMULATION", "ACCUMULATIONS DE COMISSIONS")
gl['PieceRef'] = gl["PieceRef"].str.replace("ImpôtE", "Impôt")
gl['PieceRef'] = gl["PieceRef"].str.replace("MED.INSU", "MED.ASSURANCE")
gl['PieceRef'] = gl["PieceRef"].str.replace("APPRENTICESHIP_CONTRIBUTIONS_TRUE_UP", "CONTRIBUTIONS À L'APPRENTISSAGE/TRUE UP")
gl['PieceRef'] = gl["PieceRef"].str.replace("NET PAY", "SALAIRE NET")
gl['PieceRef'] = gl["PieceRef"].str.replace("CASH ", "ARGENT ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Repayment ", "Repaiement ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Acct. ", "Comptab. ")
gl['PieceRef'] = gl["PieceRef"].str.replace("ACCR ", "ACC ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Accr ", "Acc.")
gl['PieceRef'] = gl["PieceRef"].str.replace("Cash Balance", "Solde de caisse")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECLASS ", "RECLASSEMENT ")
gl['PieceRef'] = gl["PieceRef"].str.replace("VAT FILING ", "Dépôt de TVA ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Needs to be re-booked due", "KI")
gl['PieceRef'] = gl["PieceRef"].str.replace("reclass from", "reclasser de")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECLASS FROM", "reclasser de")
gl['PieceRef'] = gl["PieceRef"].str.replace("PAYROLL", "PAIE")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECLASS ", "Reclasser")
gl['PieceRef'] = gl["PieceRef"].str.replace("DEDICTION","DEDUCTION")
gl['PieceRef'] = gl["PieceRef"].str.replace("Cash","Argent ")
gl['PieceRef'] = gl["PieceRef"].str.replace("cash ","argent ")
gl['PieceRef'] = gl["PieceRef"].str.replace("ReclasserIFICATIO","RECLASSEMENT ")
gl['PieceRef'] = gl["PieceRef"].str.replace("ImpôtS ","Impôts ")
gl['PieceRef'] = gl["PieceRef"].str.replace("Working Repas (Employees Only) ","Repas de travail (employés seulement) ")
gl['PieceRef'] = gl["PieceRef"].str.replace("/Banque Frais","/Frais Bancaires")
gl['PieceRef'] = gl["PieceRef"].str.replace("MED. INS.","ASSURANCE MED.")
gl['PieceRef'] = gl["PieceRef"].str.replace("AJE WIRE LOG TRAN","AJE VERSEMENT")
gl['PieceRef'] = gl["PieceRef"].str.replace("JUN'","JUIN'")
gl['PieceRef'] = gl["PieceRef"].str.replace("Deferred Rent18 rue de Lo","Loyer différé 18 Rue de Lo")
gl['PieceRef'] = gl["PieceRef"].str.replace("Facture - Brut'","Facture - Brute")
gl['PieceRef'] = gl["PieceRef"].str.replace("T&E","VD")
gl['PieceRef'] = gl["PieceRef"].str.replace("/","")
gl['PieceRef'] = gl["PieceRef"].str.replace("Inv","Facture")
gl['PieceRef'] = gl["PieceRef"].str.replace("RECUR DEF RENT","LOCATION DIFFÉRÉE RECUR")
gl['PieceRef'] = gl["PieceRef"].str.replace(" NaT ","")
gl['JournalLib'] = gl["JournalLib"].str.replace(" NaT ","")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" NaT ","")
gl['PieceRef'] = gl["PieceRef"].str.replace(" NAN ","")
gl['JournalLib'] = gl["JournalLib"].str.replace(" NAN ","")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" NAN ","")
gl['PieceRef'] = gl["PieceRef"].str.replace(" nan ","")
gl['JournalLib'] = gl["JournalLib"].str.replace(" nan ","")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" nan ","")
gl['PieceRef'] = gl["PieceRef"].str.replace(" nannan ","")
gl['JournalLib'] = gl["JournalLib"].str.replace(" nannan ","")
gl['EcritureLib'] = gl["EcritureLib"].str.replace(" nannan ","")
gl.loc[gl["JournalLib"].str.isnumeric(),'JournalLib'] = gl['JournalCode']
gl['JournalLib'] = gl['JournalLib'].replace(codes)
gl['JournalLib'] = gl["JournalLib"].str.replace("-2014123456789","-2014V")
gl['JournalLib'] = gl["JournalLib"].str.replace("T/&E","VD")
gl['EcritureLib'] = gl["EcritureLib"].str.replace("T/&E","VD")
gl['DocDate'] = gl['Document Date']
gl.loc[gl["PieceRef"].isnull(),'PieceRef'] = gl["JournalLib"].map(str) + " " + gl.DocDate.dt.strftime('%Y%m%d').astype(str)
gl.loc[gl["EcritureLib"].str.isnumeric(),'EcritureLib'] = gl['JournalLib'].map(str) + gl['EcritureNum'].map(str)
gl['Document Date'] = gl['DocDate']
del gl['DocDate']
gl['EcritureLib'] = gl['EcritureLib'].apply(lambda x: x.upper())
gl['Credit'] = gl['Credit'].abs()
gl = gl.sort_values('EcritureNum')
return gl
def save_results(df, output):
del df['Amount in doc. curr.']
del df['Assignment']
del df['Document Date']
del df['Reference']
del df['Text']
del df['Posting Date']
del df['Document Number']
del df['Document Type']
del df['Document currency']
del df['G/L Account']
del df['Local Currency']
del df['Local currency 2']
del df['Offsetting acct no.']
writer = pd.ExcelWriter(output,
engine='xlsxwriter',
datetime_format='yyyymmdd',
date_format='yyyymmdd')
df.to_excel(writer, index = False,sheet_name = ('Sheet 1'), columns =['JournalCode','JournalLib','EcritureNum','EcritureDate','CompteNum',
'CompteLib','CompAuxNum','CompAuxLib','PieceRef','PieceDate','EcritureLib',
'Debit','Credit','EcritureLet','DateLet','ValidDate','MontantDevise','Idevise'])
workbook = writer.book
worksheet = writer.sheets['Sheet 1']
worksheet.set_column('A:AV', 40)
writer.save()
if __name__ == '__main__':
args = parse_args()
gl_items = args.GL
parked = args.Parked
output_file = args.Choose_File_Name
output_df = combine(gl_items,parked)
print("Reading data and combining with parked and deleted items")
print("Separating Debits and Credits")
print("Mapping Vendors")
output_df_transformed = transform(output_df)
output_df_translated = translate(output_df_transformed)
print("Translating to French")
print("Mapping French Accounts")
print("Filling in blanks")
save_results(output_df_translated,output_file)
z = output_df_translated['Debit'].sum(axis = 0,skipna = True)
y = output_df_translated['Credit'].sum(axis = 0, skipna = True)
h = z - y
if h != 0:
print("WARNING: Debits and Credits are not balanced!")
| 75.99647 | 246 | 0.653315 | 9,824 | 86,104 | 5.712643 | 0.085708 | 0.135065 | 0.068958 | 0.119064 | 0.939987 | 0.898398 | 0.765239 | 0.604925 | 0.545375 | 0.490921 | 0 | 0.005587 | 0.151874 | 86,104 | 1,132 | 247 | 76.063604 | 0.76291 | 0 | 0 | 0.167671 | 0 | 0 | 0.548 | 0.005943 | 0 | 0 | 0 | 0 | 0 | 1 | 0.00502 | false | 0.019076 | 0.00502 | 0 | 0.014056 | 0.007028 | 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 |
acd8698ede161e1968a17fca40892216abee09bb | 128 | py | Python | files/build_trigger.py | vexingcodes/vexing.codes-infra | ace315c7fb868f37914573aca353b5454ba7433c | [
"MIT"
] | null | null | null | files/build_trigger.py | vexingcodes/vexing.codes-infra | ace315c7fb868f37914573aca353b5454ba7433c | [
"MIT"
] | null | null | null | files/build_trigger.py | vexingcodes/vexing.codes-infra | ace315c7fb868f37914573aca353b5454ba7433c | [
"MIT"
] | null | null | null | import boto3
def handler(event, _):
boto3.client('codebuild').start_build(
projectName=event['Records'][0]['customData'])
| 25.6 | 50 | 0.71875 | 15 | 128 | 6 | 0.866667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.026087 | 0.101563 | 128 | 4 | 51 | 32 | 0.756522 | 0 | 0 | 0 | 0 | 0 | 0.203125 | 0 | 0 | 0 | 0 | 0 | 0 | 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 |
acf0ea081196fdcaa8448d959385eacc3ae88049 | 202 | py | Python | profiles_api/serializers.py | parth-singh71/profiles-rest-api | c415d2fd6c1c6c51674bca601644bcedb67cf72c | [
"MIT"
] | null | null | null | profiles_api/serializers.py | parth-singh71/profiles-rest-api | c415d2fd6c1c6c51674bca601644bcedb67cf72c | [
"MIT"
] | 4 | 2020-04-15T07:14:27.000Z | 2021-06-04T22:31:09.000Z | profiles_api/serializers.py | parth-singh71/profiles-rest-api | c415d2fd6c1c6c51674bca601644bcedb67cf72c | [
"MIT"
] | null | null | null | from rest_framework import serializers
class HelloSerializer(serializers.Serializer):
"""Serializers a name field for testing our APIView"""
name = serializers.CharField(max_length= 10)
| 25.25 | 58 | 0.757426 | 23 | 202 | 6.565217 | 0.826087 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.011905 | 0.168317 | 202 | 7 | 59 | 28.857143 | 0.886905 | 0.237624 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
c58b2acf5e308231e4fc666a15cea8491b5c0053 | 187 | py | Python | netsuite/constants.py | cart-com/netsuite | 5a4cbbea26c6584348ebea2b4d6de0b9607cea0c | [
"MIT"
] | null | null | null | netsuite/constants.py | cart-com/netsuite | 5a4cbbea26c6584348ebea2b4d6de0b9607cea0c | [
"MIT"
] | null | null | null | netsuite/constants.py | cart-com/netsuite | 5a4cbbea26c6584348ebea2b4d6de0b9607cea0c | [
"MIT"
] | null | null | null | import os
NOT_SET: object = object()
DEFAULT_INI_PATH: str = os.environ.get(
"NETSUITE_CONFIG", os.path.expanduser("~/.config/netsuite.ini"),
)
DEFAULT_INI_SECTION: str = "netsuite"
| 23.375 | 68 | 0.727273 | 26 | 187 | 5 | 0.576923 | 0.153846 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 187 | 7 | 69 | 26.714286 | 0.787879 | 0 | 0 | 0 | 0 | 0 | 0.240642 | 0.117647 | 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 |
c5940979564969266e00ad7e811e6b04f162aae1 | 633 | py | Python | ex4/sigmoidGradient.py | junwon1994/Coursera-ML | 91e96c3c14c058cd6d745a4fada1baf40d91458f | [
"MIT"
] | 3 | 2018-03-16T01:48:14.000Z | 2020-08-14T09:52:58.000Z | ex4/sigmoidGradient.py | junwon1994/Coursera-ML | 91e96c3c14c058cd6d745a4fada1baf40d91458f | [
"MIT"
] | null | null | null | ex4/sigmoidGradient.py | junwon1994/Coursera-ML | 91e96c3c14c058cd6d745a4fada1baf40d91458f | [
"MIT"
] | null | null | null | from ex2.sigmoid import sigmoid
def sigmoidGradient(z):
"""computes the gradient of the sigmoid function
evaluated at z. This should work regardless if z is a matrix or a
vector. In particular, if z is a vector or matrix, you should return
the gradient for each element."""
# ====================== YOUR CODE HERE ======================
# Instructions: Compute the gradient of the sigmoid function evaluated at
# each value of z (z can be a matrix, vector or scalar).
g = sigmoid(z) * (1 - sigmoid(z))
# =============================================================
return g
| 37.235294 | 77 | 0.554502 | 80 | 633 | 4.3875 | 0.525 | 0.094017 | 0.074074 | 0.091168 | 0.239316 | 0.239316 | 0.239316 | 0.239316 | 0 | 0 | 0 | 0.00409 | 0.227488 | 633 | 16 | 78 | 39.5625 | 0.713701 | 0.751975 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0625 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 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 |
c596d357a3ee4b4fab32730d15cc0655102ec33a | 10,199 | py | Python | psets/ZHH_HHToTauTauGG_GenSim_pset_cfg.py | bsathian/Hgg-MC-Generation | 5f44503b6d5c57aef862299cbcd5a9910a4f8ab8 | [
"MIT"
] | null | null | null | psets/ZHH_HHToTauTauGG_GenSim_pset_cfg.py | bsathian/Hgg-MC-Generation | 5f44503b6d5c57aef862299cbcd5a9910a4f8ab8 | [
"MIT"
] | null | null | null | psets/ZHH_HHToTauTauGG_GenSim_pset_cfg.py | bsathian/Hgg-MC-Generation | 5f44503b6d5c57aef862299cbcd5a9910a4f8ab8 | [
"MIT"
] | 1 | 2021-05-17T22:24:09.000Z | 2021-05-17T22:24:09.000Z | # Auto generated configuration file
# using:
# Revision: 1.19
# Source: /local/reps/CMSSW/CMSSW/Configuration/Applications/python/ConfigBuilder.py,v
# with command line options: Configuration/GenProduction/python/HIG-RunIIFall17wmLHEGS-05498-fragment.py --python_filename HIG-RunIIFall17wmLHEGS-05498_1_cfg.py --eventcontent RAWSIM,LHE --customise Configuration/DataProcessing/Utils.addMonitoring --datatier GEN-SIM,LHE --fileout file:HIG-RunIIFall17wmLHEGS-05498.root --conditions 93X_mc2017_realistic_v3 --beamspot Realistic25ns13TeVEarly2017Collision --customise_commands process.RandomNumberGeneratorService.externalLHEProducer.initialSeed=int(99) --step LHE,GEN,SIM --geometry DB:Extended --era Run2_2017 --no_exec --mc -n 643 --nThreads 1
import FWCore.ParameterSet.Config as cms
from Configuration.StandardSequences.Eras import eras
process = cms.Process('SIM',eras.Run2_2017)
# import of standard configurations
process.load('Configuration.StandardSequences.Services_cff')
process.load('SimGeneral.HepPDTESSource.pythiapdt_cfi')
process.load('FWCore.MessageService.MessageLogger_cfi')
process.load('Configuration.EventContent.EventContent_cff')
process.load('SimGeneral.MixingModule.mixNoPU_cfi')
process.load('Configuration.StandardSequences.GeometryRecoDB_cff')
process.load('Configuration.StandardSequences.GeometrySimDB_cff')
process.load('Configuration.StandardSequences.MagneticField_cff')
process.load('Configuration.StandardSequences.Generator_cff')
process.load('IOMC.EventVertexGenerators.VtxSmearedRealistic25ns13TeVEarly2017Collision_cfi')
process.load('GeneratorInterface.Core.genFilterSummary_cff')
process.load('Configuration.StandardSequences.SimIdeal_cff')
process.load('Configuration.StandardSequences.EndOfProcess_cff')
process.load('Configuration.StandardSequences.FrontierConditions_GlobalTag_cff')
process.maxEvents = cms.untracked.PSet(
input = cms.untracked.int32(643)
)
# Input source
process.source = cms.Source("EmptySource")
process.options = cms.untracked.PSet(
)
# Production Info
process.configurationMetadata = cms.untracked.PSet(
annotation = cms.untracked.string('Configuration/GenProduction/python/HIG-RunIIFall17wmLHEGS-05498-fragment.py nevts:643'),
name = cms.untracked.string('Applications'),
version = cms.untracked.string('$Revision: 1.19 $')
)
# Output definition
process.RAWSIMoutput = cms.OutputModule("PoolOutputModule",
SelectEvents = cms.untracked.PSet(
SelectEvents = cms.vstring('generation_step')
),
compressionAlgorithm = cms.untracked.string('LZMA'),
compressionLevel = cms.untracked.int32(9),
dataset = cms.untracked.PSet(
dataTier = cms.untracked.string('GEN-SIM'),
filterName = cms.untracked.string('')
),
eventAutoFlushCompressedSize = cms.untracked.int32(20971520),
fileName = cms.untracked.string('file:GENSIM.root'),
outputCommands = process.RAWSIMEventContent.outputCommands,
splitLevel = cms.untracked.int32(0)
)
process.LHEoutput = cms.OutputModule("PoolOutputModule",
dataset = cms.untracked.PSet(
dataTier = cms.untracked.string('LHE'),
filterName = cms.untracked.string('')
),
fileName = cms.untracked.string('file:GENSIM_inLHE.root'),
outputCommands = process.LHEEventContent.outputCommands,
splitLevel = cms.untracked.int32(0)
)
# Additional output definition
# Other statements
process.XMLFromDBSource.label = cms.string("Extended")
process.genstepfilter.triggerConditions=cms.vstring("generation_step")
from Configuration.AlCa.GlobalTag import GlobalTag
process.GlobalTag = GlobalTag(process.GlobalTag, '93X_mc2017_realistic_v3', '')
process.generator = cms.EDFilter("Pythia8HadronizerFilter",
PythiaParameters = cms.PSet(
parameterSets = cms.vstring('pythia8CommonSettings',
'pythia8CP5Settings',
'pythia8PSweightsSettings',
'processParameters'),
processParameters = cms.vstring('25:m0 = 125.0',
'25:onMode = off',
'25:onIfMatch = 15 -15',
'25:onIfMatch = 22 22',
'ResonanceDecayFilter:filter = on',
'ResonanceDecayFilter:exclusive = on', #off: require at least the specified number of daughters, on: require exactly the specified number of daughters
'ResonanceDecayFilter:mothers = 25', #list of mothers not specified => count all particles in hard process+resonance decays (better to avoid specifying mothers when including leptons from the lhe in counting, since intermediate resonances are not gauranteed to appear in general
'ResonanceDecayFilter:daughters = 15,15,22,22' #
),
pythia8CP5Settings = cms.vstring('Tune:pp 14',
'Tune:ee 7',
'MultipartonInteractions:ecmPow=0.03344',
'PDF:pSet=20',
'MultipartonInteractions:bProfile=2',
'MultipartonInteractions:pT0Ref=1.41',
'MultipartonInteractions:coreRadius=0.7634',
'MultipartonInteractions:coreFraction=0.63',
'ColourReconnection:range=5.176',
'SigmaTotal:zeroAXB=off',
'SpaceShower:alphaSorder=2',
'SpaceShower:alphaSvalue=0.118',
'SigmaProcess:alphaSvalue=0.118',
'SigmaProcess:alphaSorder=2',
'MultipartonInteractions:alphaSvalue=0.118',
'MultipartonInteractions:alphaSorder=2',
'TimeShower:alphaSorder=2',
'TimeShower:alphaSvalue=0.118'),
pythia8CommonSettings = cms.vstring('Tune:preferLHAPDF = 2',
'Main:timesAllowErrors = 10000',
'Check:epTolErr = 0.01',
'Beams:setProductionScalesFromLHEF = off',
'SLHA:keepSM = on',
'SLHA:minMassSM = 1000.',
'ParticleDecays:limitTau0 = on',
'ParticleDecays:tau0Max = 10',
'ParticleDecays:allowPhotonRadiation = on'),
pythia8PSweightsSettings = cms.vstring('UncertaintyBands:doVariations = on',
'UncertaintyBands:List = {isrRedHi isr:muRfac=0.707,fsrRedHi fsr:muRfac=0.707,isrRedLo isr:muRfac=1.414,fsrRedLo fsr:muRfac=1.414,isrDefHi isr:muRfac=0.5,fsrDefHi fsr:muRfac=0.5,isrDefLo isr:muRfac=2.0,fsrDefLo fsr:muRfac=2.0,isrConHi isr:muRfac=0.25,fsrConHi fsr:muRfac=0.25,isrConLo isr:muRfac=4.0,fsrConLo fsr:muRfac=4.0,fsr_G2GG_muR_dn fsr:G2GG:muRfac=0.5,fsr_G2GG_muR_up fsr:G2GG:muRfac=2.0,fsr_G2QQ_muR_dn fsr:G2QQ:muRfac=0.5,fsr_G2QQ_muR_up fsr:G2QQ:muRfac=2.0,fsr_Q2QG_muR_dn fsr:Q2QG:muRfac=0.5,fsr_Q2QG_muR_up fsr:Q2QG:muRfac=2.0,fsr_X2XG_muR_dn fsr:X2XG:muRfac=0.5,fsr_X2XG_muR_up fsr:X2XG:muRfac=2.0,fsr_G2GG_cNS_dn fsr:G2GG:cNS=-2.0,fsr_G2GG_cNS_up fsr:G2GG:cNS=2.0,fsr_G2QQ_cNS_dn fsr:G2QQ:cNS=-2.0,fsr_G2QQ_cNS_up fsr:G2QQ:cNS=2.0,fsr_Q2QG_cNS_dn fsr:Q2QG:cNS=-2.0,fsr_Q2QG_cNS_up fsr:Q2QG:cNS=2.0,fsr_X2XG_cNS_dn fsr:X2XG:cNS=-2.0,fsr_X2XG_cNS_up fsr:X2XG:cNS=2.0,isr_G2GG_muR_dn isr:G2GG:muRfac=0.5,isr_G2GG_muR_up isr:G2GG:muRfac=2.0,isr_G2QQ_muR_dn isr:G2QQ:muRfac=0.5,isr_G2QQ_muR_up isr:G2QQ:muRfac=2.0,isr_Q2QG_muR_dn isr:Q2QG:muRfac=0.5,isr_Q2QG_muR_up isr:Q2QG:muRfac=2.0,isr_X2XG_muR_dn isr:X2XG:muRfac=0.5,isr_X2XG_muR_up isr:X2XG:muRfac=2.0,isr_G2GG_cNS_dn isr:G2GG:cNS=-2.0,isr_G2GG_cNS_up isr:G2GG:cNS=2.0,isr_G2QQ_cNS_dn isr:G2QQ:cNS=-2.0,isr_G2QQ_cNS_up isr:G2QQ:cNS=2.0,isr_Q2QG_cNS_dn isr:Q2QG:cNS=-2.0,isr_Q2QG_cNS_up isr:Q2QG:cNS=2.0,isr_X2XG_cNS_dn isr:X2XG:cNS=-2.0,isr_X2XG_cNS_up isr:X2XG:cNS=2.0}',
'UncertaintyBands:nFlavQ = 4',
'UncertaintyBands:MPIshowers = on',
'UncertaintyBands:overSampleFSR = 10.0',
'UncertaintyBands:overSampleISR = 10.0',
'UncertaintyBands:FSRpTmin2Fac = 20',
'UncertaintyBands:ISRpTmin2Fac = 1')
),
comEnergy = cms.double(13000.0),
filterEfficiency = cms.untracked.double(1.0),
maxEventsToPrint = cms.untracked.int32(1),
pythiaHepMCVerbosity = cms.untracked.bool(False),
pythiaPylistVerbosity = cms.untracked.int32(1)
)
process.externalLHEProducer = cms.EDProducer("ExternalLHEProducer",
args = cms.vstring('/cvmfs/cms.cern.ch/phys_generator/gridpacks/pre2017/13TeV/madgraph/V5_2.6.0/ZHH_CV_1_0_C2V_1_0_C3_1_0_13TeV-madgraph/v1/ZHH_CV_1_0_C2V_1_0_C3_1_0_13TeV-madgraph_slc6_amd64_gcc630_CMSSW_9_3_8_tarball.tar.xz'),
nEvents = cms.untracked.uint32(643),
numberOfParameters = cms.uint32(1),
outputFile = cms.string('cmsgrid_final.lhe'),
scriptName = cms.FileInPath('GeneratorInterface/LHEInterface/data/run_generic_tarball_cvmfs.sh')
)
# Path and EndPath definitions
process.lhe_step = cms.Path(process.externalLHEProducer)
process.generation_step = cms.Path(process.pgen)
process.simulation_step = cms.Path(process.psim)
process.genfiltersummary_step = cms.EndPath(process.genFilterSummary)
process.endjob_step = cms.EndPath(process.endOfProcess)
process.RAWSIMoutput_step = cms.EndPath(process.RAWSIMoutput)
process.LHEoutput_step = cms.EndPath(process.LHEoutput)
# Schedule definition
process.schedule = cms.Schedule(process.lhe_step,process.generation_step,process.genfiltersummary_step,process.simulation_step,process.endjob_step,process.RAWSIMoutput_step,process.LHEoutput_step)
from PhysicsTools.PatAlgos.tools.helpers import associatePatAlgosToolsTask
associatePatAlgosToolsTask(process)
# filter all path with the production filter sequence
for path in process.paths:
if path in ['lhe_step']: continue
getattr(process,path)._seq = process.generator * getattr(process,path)._seq
# customisation of the process.
# Automatic addition of the customisation function from Configuration.DataProcessing.Utils
from Configuration.DataProcessing.Utils import addMonitoring
#call to customisation function addMonitoring imported from Configuration.DataProcessing.Utils
process = addMonitoring(process)
# End of customisation functions
# Customisation from command line
process.RandomNumberGeneratorService.externalLHEProducer.initialSeed=int(99)
# Add early deletion of temporary data products to reduce peak memory need
from Configuration.StandardSequences.earlyDeleteSettings_cff import customiseEarlyDelete
process = customiseEarlyDelete(process)
# End adding early deletion
| 55.12973 | 1,451 | 0.755956 | 1,255 | 10,199 | 6.000797 | 0.297211 | 0.041429 | 0.010623 | 0.043553 | 0.169035 | 0.115257 | 0.038773 | 0.038773 | 0.007702 | 0.007702 | 0 | 0.051035 | 0.133543 | 10,199 | 184 | 1,452 | 55.429348 | 0.801177 | 0.165703 | 0 | 0.07971 | 1 | 0.014493 | 0.471122 | 0.402876 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.043478 | 0 | 0.043478 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
c5c61d26183ce293ac95d3678eb8c57a71b32702 | 2,767 | py | Python | modules/boost/simd/arithmetic/script/average.py | timblechmann/nt2 | 6c71f7063ca4e5975c9c019877e6b2fe07c9e4ce | [
"BSL-1.0"
] | 2 | 2016-09-14T00:23:53.000Z | 2018-01-14T12:51:18.000Z | modules/boost/simd/arithmetic/script/average.py | timblechmann/nt2 | 6c71f7063ca4e5975c9c019877e6b2fe07c9e4ce | [
"BSL-1.0"
] | null | null | null | modules/boost/simd/arithmetic/script/average.py | timblechmann/nt2 | 6c71f7063ca4e5975c9c019877e6b2fe07c9e4ce | [
"BSL-1.0"
] | null | null | null | [ ## this file was manually modified by jt
{
'functor' : {
'description' : [ "The function always returns a value of the same type than the entry.",
"Take care that for integers the value returned can differ by one unit",
"from \c ceil((a+b)/2.0) or \c floor((a+b)/2.0), but is always one of",
"the two"
],
'module' : 'boost',
'arity' : '2',
'call_types' : [],
'ret_arity' : '0',
'rturn' : {
'default' : 'T',
},
'simd_types' : ['real_'],
'type_defs' : [],
'types' : ['real_', 'signed_int_', 'unsigned_int_'],
},
'info' : 'manually modified',
'unit' : {
'global_header' : {
'first_stamp' : 'modified by jt the 28/11/2010',
'included' : [],
'notes' : ['for integer values average does not,coincide with (a0+a1)/2 by at most one unit.'],
'stamp' : 'modified by jt the 13/12/2010',
},
'ranges' : {
'real_' : [['T(-100)', 'T(100)'], ['T(-100)', 'T(100)']],
'signed_int_' : [['T(-100)', 'T(100)'], ['T(-100)', 'T(100)']],
'unsigned_int_' : [['T(0)', 'T(100)'], ['T(0)', 'T(100)']],
},
'specific_values' : {
'default' : {
},
'real_' : {
'boost::simd::Inf<T>()' : 'boost::simd::Inf<T>()',
'boost::simd::Minf<T>()' : 'boost::simd::Minf<T>()',
'boost::simd::Mone<T>()' : 'boost::simd::Mone<T>()',
'boost::simd::Nan<T>()' : 'boost::simd::Nan<T>()',
'boost::simd::One<T>()' : 'boost::simd::One<T>()',
'boost::simd::Zero<T>()' : 'boost::simd::Zero<T>()',
},
'signed_int_' : {
'boost::simd::Mone<T>()' : 'boost::simd::Mone<T>()',
'boost::simd::One<T>()' : 'boost::simd::One<T>()',
'boost::simd::Zero<T>()' : 'boost::simd::Zero<T>()',
},
'unsigned_int_' : {
'boost::simd::One<T>()' : 'boost::simd::One<T>()',
'boost::simd::Zero<T>()' : 'boost::simd::Zero<T>()',
},
},
'verif_test' : {
'property_call' : {
'default' : ['boost::simd::average(a0,a1)'],
},
'property_value' : {
'default' : ['(a0+a1)/2'],
},
'ulp_thresh' : {
'default' : ['1'],
'real_' : ['0'],
},
},
},
'version' : '0.1',
},
]
| 39.528571 | 108 | 0.37116 | 271 | 2,767 | 3.686347 | 0.346863 | 0.207207 | 0.19019 | 0.048048 | 0.37037 | 0.33033 | 0.305305 | 0.26026 | 0.228228 | 0.228228 | 0 | 0.040342 | 0.408746 | 2,767 | 69 | 109 | 40.101449 | 0.570293 | 0.013372 | 0 | 0.115942 | 0 | 0.028986 | 0.475248 | 0.183718 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 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 |
c5d4fff93384a7b4f91ff88b98ec480412a4e7d8 | 753 | py | Python | tox_docker/tests/util.py | tkdchen/tox-docker | 8d450ecf28a50f39d1a573c876756bddb9d4ae99 | [
"BSD-3-Clause"
] | null | null | null | tox_docker/tests/util.py | tkdchen/tox-docker | 8d450ecf28a50f39d1a573c876756bddb9d4ae99 | [
"BSD-3-Clause"
] | null | null | null | tox_docker/tests/util.py | tkdchen/tox-docker | 8d450ecf28a50f39d1a573c876756bddb9d4ae99 | [
"BSD-3-Clause"
] | null | null | null | import os
from docker.models.containers import Container
import docker
import pytest
from tox_docker.config import runas_name
def find_container(instance_name: str) -> Container:
# TODO: refactor this as a pytest fixture
# this is running in a child-process of the tox instance which
# spawned the container; so we need to pass the parent pid to
# get the right runas_name()
running_name = runas_name(instance_name, pid=os.getppid())
client = docker.from_env(version="auto")
for container in client.containers.list():
container.attrs["Config"].get("Labels", {})
if container.name == running_name:
return container
pytest.fail(f"No running container with instance name {running_name!r}")
| 31.375 | 76 | 0.718459 | 107 | 753 | 4.953271 | 0.523364 | 0.050943 | 0.084906 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.197875 | 753 | 23 | 77 | 32.73913 | 0.877483 | 0.24834 | 0 | 0 | 0 | 0 | 0.128342 | 0 | 0 | 0 | 0 | 0.043478 | 0 | 1 | 0.076923 | false | 0 | 0.384615 | 0 | 0.538462 | 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 |
c5e5cecdf9201e00eb336ee9b2d39e6ed8ce5136 | 10,854 | py | Python | tensorcircuit/backends.py | refraction-ray/tensorcircuit | 666154f4dbdb25164c0e778a96ee56ac22323a6c | [
"MIT"
] | 21 | 2020-04-19T23:29:11.000Z | 2022-03-12T12:12:57.000Z | tensorcircuit/backends.py | refraction-ray/tensorcircuit | 666154f4dbdb25164c0e778a96ee56ac22323a6c | [
"MIT"
] | 3 | 2020-10-19T12:18:44.000Z | 2022-02-10T01:24:46.000Z | tensorcircuit/backends.py | refraction-ray/tensorcircuit | 666154f4dbdb25164c0e778a96ee56ac22323a6c | [
"MIT"
] | 7 | 2020-07-15T18:08:00.000Z | 2021-12-30T08:17:13.000Z | """
backend magic inherited from tensornetwork
"""
from typing import Union, Text, Any, Optional, Callable, Sequence
from functools import partial
from scipy.linalg import expm
import numpy as np
import warnings
from tensornetwork.backends.tensorflow import tensorflow_backend
from tensornetwork.backends.numpy import numpy_backend
from tensornetwork.backends.jax import jax_backend
from tensornetwork.backends.shell import shell_backend
from tensornetwork.backends.pytorch import pytorch_backend
from tensornetwork.backends import base_backend
Tensor = Any
libjax: Any
jnp: Any
jsp: Any
torchlib: Any
tf: Any
class NumpyBackend(numpy_backend.NumPyBackend): # type: ignore
def expm(self, a: Tensor) -> Tensor:
return expm(a)
def abs(self, a: Tensor) -> Tensor:
return np.abs(a)
def sin(self, a: Tensor) -> Tensor:
return np.sin(a)
def cos(self, a: Tensor) -> Tensor:
return np.cos(a)
def i(self, dtype: Any = None) -> Tensor:
if not dtype:
dtype = npdtype # type: ignore
if isinstance(dtype, str):
dtype = getattr(np, dtype)
return np.array(1j, dtype=dtype)
def is_tensor(self, a: Any) -> bool:
if isinstance(a, np.ndarray):
return True
return False
def real(self, a: Tensor) -> Tensor:
return np.real(a)
def cast(self, a: Tensor, dtype: str) -> Tensor:
return a.astype(getattr(np, dtype))
def grad(self, f: Callable[..., Any]) -> Callable[..., Any]:
raise NotImplementedError("numpy backend doesn't support AD")
def jit(self, f: Callable[..., Any]) -> Callable[..., Any]:
warnings.warn("numpy backend has no parallel as jit, just do nothing")
return f
# raise NotImplementedError("numpy backend doesn't support jit compiling")
def vmap(self, f: Callable[..., Any]) -> Any:
warnings.warn(
"numpy backend has no intrinsic vmap like interface"
", use vectorize instead (plain for loop)"
)
return np.vectorize(f)
class JaxBackend(jax_backend.JaxBackend): # type: ignore
# Jax doesn't support 64bit dtype, unless claim
# from jax.config import config
# config.update("jax_enable_x64", True)
# at very beginning, i.e. before import tensorcircuit
def __init__(self) -> None:
global libjax # Jax module
global jnp # jax.numpy module
global jsp # jax.scipy module
super(JaxBackend, self).__init__()
try:
import jax
except ImportError:
raise ImportError(
"Jax not installed, please switch to a different "
"backend or install Jax."
)
libjax = jax
jnp = libjax.numpy
jsp = libjax.scipy
self.name = "jax"
# it is already child of numpy backend, and self.np = self.jax.np
def convert_to_tensor(self, tensor: Tensor) -> Tensor:
result = jnp.asarray(tensor)
return result
def abs(self, a: Tensor) -> Tensor:
return jnp.abs(a)
def sin(self, a: Tensor) -> Tensor:
return jnp.sin(a)
def cos(self, a: Tensor) -> Tensor:
return jnp.cos(a)
def i(self, dtype: Any = None) -> Tensor:
if not dtype:
dtype = npdtype # type: ignore
if isinstance(dtype, str):
dtype = getattr(jnp, dtype)
return np.array(1j, dtype=dtype)
def real(self, a: Tensor) -> Tensor:
return jnp.real(a)
def cast(self, a: Tensor, dtype: str) -> Tensor:
return a.astype(getattr(jnp, dtype))
def expm(self, a: Tensor) -> Tensor:
return jsp.linalg.expm(a)
# currently expm in jax doesn't support AD, it will raise an AssertError, see https://github.com/google/jax/issues/2645
def is_tensor(self, a: Any) -> bool:
if not isinstance(a, jnp.ndarray):
return False
# isinstance(np.eye(1), jax.numpy.ndarray) = True!
if getattr(a, "_value", None) is not None:
return True
return False
def grad(
self, f: Callable[..., Any], argnums: Union[int, Sequence[int]] = 0
) -> Any:
# TODO
return libjax.grad(f, argnums=argnums)
def jit(self, f: Callable[..., Any]) -> Any:
return libjax.jit(f)
def vmap(self, f: Callable[..., Any]) -> Any:
return libjax.vmap(f)
# since tf doesn't support in&out axes options, we don't support them in universal backend
class TensorFlowBackend(tensorflow_backend.TensorFlowBackend): # type: ignore
def __init__(self) -> None:
global tf
super(TensorFlowBackend, self).__init__()
try:
import tensorflow
except ImportError:
raise ImportError(
"Tensorflow not installed, please switch to a "
"different backend or install Tensorflow."
)
tf = tensorflow
self.name = "tensorflow"
def expm(self, a: Tensor) -> Tensor:
return tf.linalg.expm(a)
def sin(self, a: Tensor) -> Tensor:
return tf.math.sin(a)
def cos(self, a: Tensor) -> Tensor:
return tf.math.cos(a)
def i(self, dtype: Any = None) -> Tensor:
if not dtype:
dtype = getattr(tf, dtypestr) # type: ignore
if isinstance(dtype, str):
dtype = getattr(tf, dtype)
return tf.constant(1j, dtype=dtype)
def is_tensor(self, a: Any) -> bool:
if isinstance(a, tf.Tensor) or isinstance(a, tf.Variable):
return True
return False
def abs(self, a: Tensor) -> Tensor:
return tf.math.abs(a)
def real(self, a: Tensor) -> Tensor:
return tf.math.real(a)
def cast(self, a: Tensor, dtype: str) -> Tensor:
return tf.cast(a, dtype=getattr(tf, dtype))
def grad(
self, f: Callable[..., Any], argnums: Union[int, Sequence[int]] = 0
) -> Callable[..., Any]:
# experimental attempt
# Note: tensorflow grad is gradient while jax grad is derivative, they are different with a conjugate!
def wrapper(*args: Any, **kws: Any) -> Any:
with tf.GradientTape() as t:
t.watch(args)
y = f(*args, **kws)
if isinstance(argnums, int):
x = args[argnums]
else:
x = [args[i] for i in argnums]
g = t.gradient(y, x)
return g
return wrapper
def jit(self, f: Callable[..., Any]) -> Any:
return tf.function(f)
def vmap(self, f: Callable[..., Any]) -> Any:
def wrapper(f: Callable[..., Any], args: Sequence[Any]) -> Any:
return f(*args)
wrapper = partial(wrapper, f)
def own_vectorized_map(f: Callable[..., Any], *args: Any) -> Any:
return tf.vectorized_map(f, args)
return partial(own_vectorized_map, wrapper)
class PyTorchBackend(pytorch_backend.PyTorchBackend): # type: ignore
def __init__(self) -> None:
super(PyTorchBackend, self).__init__()
global torchlib
try:
import torch
except ImportError:
raise ImportError(
"PyTorch not installed, please switch to a different "
"backend or install PyTorch."
)
torchlib = torch
self.name = "pytorch"
def expm(self, a: Tensor) -> Tensor:
raise NotImplementedError("pytorch backend doesn't support expm")
# in 2020, torch has no expm, hmmm. but that's ok, it doesn't support complex numbers which is more severe issue.
# see https://github.com/pytorch/pytorch/issues/9983
def sin(self, a: Tensor) -> Tensor:
return torchlib.sin(a)
def cos(self, a: Tensor) -> Tensor:
return torchlib.cos(a)
def i(self, dtype: Any = None) -> Tensor:
raise NotImplementedError(
"pytorch backend doesn't support imaginary numbers at all!"
)
def real(self, a: Tensor) -> Tensor:
return a
# hmm, in torch, everyone is real.
def is_tensor(self, a: Any) -> bool:
if isinstance(a, torchlib.Tensor):
return True
return False
def cast(self, a: Tensor, dtype: str) -> Tensor:
return a.type(getattr(torchlib, dtype))
def grad(
self, f: Callable[..., Any], argnums: Union[int, Sequence[int]] = 0
) -> Callable[..., Any]:
def wrapper(*args: Any, **kws: Any) -> Any:
x = []
if isinstance(argnums, int):
argnumsl = [argnums]
# if you also call lhs as argnums, something weird may happen
# the reason is that python then take it as local vars
else:
argnumsl = argnums # type: ignore
for i, arg in enumerate(args):
if i in argnumsl:
x.append(arg.requires_grad_(True))
else:
x.append(arg)
y = f(*x, **kws)
y.backward()
gs = [x[i].grad for i in argnumsl]
if len(gs) == 1:
gs = gs[0]
return gs
return wrapper
def vmap(self, f: Callable[..., Any]) -> Any:
warnings.warn(
"pytorch backend has no intrinsic vmap like interface"
", use plain for loop for compatibility"
)
# the vmap support is vey limited, f must return one tensor
# nested list of tensor as return is not supported
def vmapf(*args: Tensor, **kws: Any) -> Tensor:
r = []
for i in range(args[0].shape[0]):
nargs = [arg[i] for arg in args]
r.append(f(*nargs, **kws))
return torchlib.stack(r)
return vmapf
# raise NotImplementedError("pytorch backend doesn't support vmap")
# There seems to be no map like architecture in pytorch for now
# see https://discuss.pytorch.org/t/fast-way-to-use-map-in-pytorch/70814
def jit(self, f: Callable[..., Any]) -> Any:
return f # do nothing here until I figure out what torch.jit is for and how does it work
# see https://github.com/pytorch/pytorch/issues/36910
_BACKENDS = {
"tensorflow": TensorFlowBackend,
"numpy": NumpyBackend,
"jax": JaxBackend,
"shell": shell_backend.ShellBackend, # no intention to maintain this one
"pytorch": PyTorchBackend, # no intention to fully maintain this one
}
def get_backend(
backend: Union[Text, base_backend.BaseBackend]
) -> base_backend.BaseBackend:
if isinstance(backend, base_backend.BaseBackend):
return backend
if backend not in _BACKENDS:
raise ValueError("Backend '{}' does not exist".format(backend))
return _BACKENDS[backend]()
| 32.4 | 127 | 0.586788 | 1,359 | 10,854 | 4.643856 | 0.196468 | 0.021391 | 0.040089 | 0.05118 | 0.42006 | 0.402472 | 0.379179 | 0.26747 | 0.19062 | 0.14245 | 0 | 0.004902 | 0.304588 | 10,854 | 334 | 128 | 32.497006 | 0.831214 | 0.156348 | 0 | 0.371901 | 0 | 0 | 0.07418 | 0 | 0 | 0 | 0 | 0.002994 | 0 | 1 | 0.219008 | false | 0 | 0.082645 | 0.119835 | 0.53719 | 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 |
c5e955f6a5fb02a343d52d2f8212c94c8ad218bb | 204 | py | Python | vivisect/tests/vivbins.py | mubix/vivisect | 2900c0bf59838cb9fc398a8668f76f887b7f54e7 | [
"ECL-2.0",
"Apache-2.0"
] | 1 | 2017-11-12T03:50:06.000Z | 2017-11-12T03:50:06.000Z | vivisect/tests/vivbins.py | mubix/vivisect | 2900c0bf59838cb9fc398a8668f76f887b7f54e7 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | vivisect/tests/vivbins.py | mubix/vivisect | 2900c0bf59838cb9fc398a8668f76f887b7f54e7 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | import os
import unittest
def require(f):
def skipit(*args, **kwargs):
raise unittest.SkipTest('VIVBINS env var...')
if os.getenv('VIVBINS') == None:
return skipit
return f
| 17 | 53 | 0.617647 | 26 | 204 | 4.846154 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.254902 | 204 | 11 | 54 | 18.545455 | 0.828947 | 0 | 0 | 0 | 0 | 0 | 0.122549 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 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 |
c5ea213be6b9121c63848b236674311dd3d54793 | 32 | py | Python | src/machine_learning/collaborative_filtering/__init__.py | przemek1990/machine-learning | d278b867757cf9223e079ff77cdd8e1b4a9b3f36 | [
"Apache-2.0"
] | null | null | null | src/machine_learning/collaborative_filtering/__init__.py | przemek1990/machine-learning | d278b867757cf9223e079ff77cdd8e1b4a9b3f36 | [
"Apache-2.0"
] | null | null | null | src/machine_learning/collaborative_filtering/__init__.py | przemek1990/machine-learning | d278b867757cf9223e079ff77cdd8e1b4a9b3f36 | [
"Apache-2.0"
] | null | null | null | __author__ = 'przemyslaw.pioro'
| 16 | 31 | 0.78125 | 3 | 32 | 7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.09375 | 32 | 1 | 32 | 32 | 0.724138 | 0 | 0 | 0 | 0 | 0 | 0.5 | 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 |
c5fe482fddeda64ee08226bdb2b25edc133236ff | 380 | py | Python | src/tests/tests.py | veleritas/mychem.info | bb22357d4cbbc3c4865da224bf998f2cbc59f8f2 | [
"Apache-2.0"
] | 1 | 2021-05-09T04:51:28.000Z | 2021-05-09T04:51:28.000Z | src/tests/tests.py | veleritas/mychem.info | bb22357d4cbbc3c4865da224bf998f2cbc59f8f2 | [
"Apache-2.0"
] | null | null | null | src/tests/tests.py | veleritas/mychem.info | bb22357d4cbbc3c4865da224bf998f2cbc59f8f2 | [
"Apache-2.0"
] | null | null | null | import sys
import os
# Add this directory to python path (contains nosetest_config)
sys.path.append(os.path.dirname(os.path.realpath(__file__)))
from biothings.tests import BiothingTest
from biothings.tests.settings import NosetestSettings
ns = NosetestSettings()
class {% nosetest_settings_class %}(BiothingTest):
__test__ = True
# Add extra nosetests here
pass
| 22.352941 | 62 | 0.776316 | 48 | 380 | 5.916667 | 0.625 | 0.042254 | 0.126761 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.144737 | 380 | 16 | 63 | 23.75 | 0.873846 | 0.223684 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.111111 | 0.444444 | null | null | 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 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 3 |
681045cfaacc2418fa853c78810b9368726344ac | 717 | py | Python | chaospy/distributions/copulas/__init__.py | lblonk/chaospy | 1759a4307c6134b74ce63ff44973195f1e185f94 | [
"MIT"
] | null | null | null | chaospy/distributions/copulas/__init__.py | lblonk/chaospy | 1759a4307c6134b74ce63ff44973195f1e185f94 | [
"MIT"
] | null | null | null | chaospy/distributions/copulas/__init__.py | lblonk/chaospy | 1759a4307c6134b74ce63ff44973195f1e185f94 | [
"MIT"
] | null | null | null | r"""
Copulas are a type dependency structure imposed on independent variables to
achieve to more complex problems without adding too much complexity.
To construct a copula one needs a copula transformation and the
Copula wrapper::
>>> dist = chaospy.Iid(chaospy.Uniform(), 2)
>>> copula = chaospy.Gumbel(dist, theta=1.5)
The resulting copula is then ready for use::
>>> print(numpy.around(copula.sample(5), 4))
[[0.6536 0.115 0.9503 0.4822 0.8725]
[0.6286 0.0654 0.96 0.5073 0.9705]]
"""
from .baseclass import Copula
from .archimedean import Archimedean
from .gumbel import Gumbel
from .clayton import Clayton
from .joe import Joe
from .nataf import Nataf
from .t_copula import TCopula
| 27.576923 | 75 | 0.732218 | 112 | 717 | 4.678571 | 0.616071 | 0.026718 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.087838 | 0.174338 | 717 | 25 | 76 | 28.68 | 0.797297 | 0.705718 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.875 | 0 | 0.875 | 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 |
a840832e20eb91945756ce9b6d98a5d6d6a25541 | 1,689 | py | Python | rest_framework_auth0/models.py | robindebois/djangorestframework-auth0 | a203dcd9e067bc411b852b9f3ad3e7b1d0b843aa | [
"MIT"
] | 107 | 2016-03-28T22:45:40.000Z | 2021-06-28T01:46:38.000Z | rest_framework_auth0/models.py | robindebois/djangorestframework-auth0 | a203dcd9e067bc411b852b9f3ad3e7b1d0b843aa | [
"MIT"
] | 41 | 2016-09-03T05:15:47.000Z | 2021-01-02T12:47:36.000Z | rest_framework_auth0/models.py | robindebois/djangorestframework-auth0 | a203dcd9e067bc411b852b9f3ad3e7b1d0b843aa | [
"MIT"
] | 26 | 2016-04-16T22:01:29.000Z | 2021-05-07T14:01:55.000Z | # Just to keep things like ./manage.py test happy
from django.contrib.auth.models import AbstractUser
# class Group(models.Model):
# """
# Groups are a generic way of categorizing users to apply permissions, or
# some other label, to those users. A user can belong to any number of
# groups.
# A user in a group automatically has all the permissions granted to that
# group. For example, if the group Site editors has the permission
# can_edit_home_page, any user in that group will have that permission.
# Beyond permissions, groups are a convenient way to categorize users to
# apply some label, or extended functionality, to them. For example, you
# could create a group 'Special users', and you could write code that would
# do special things to those users -- such as giving them access to a
# members-only portion of your site, or sending them members-only email
# messages.
# """
# name = models.CharField(_('name'), max_length=80, unique=True)
# permissions = models.ManyToManyField(
# Permission,
# verbose_name=_('permissions'),
# blank=True,
# )
#
# objects = GroupManager()
#
# class Meta:
# verbose_name = _('group')
# verbose_name_plural = _('groups')
#
# def __str__(self):
# return self.name
#
# def natural_key(self):
# return (self.name,)
# class User(AbstractUser):
# """
# Users within the Django authentication system are represented by this
# model.
# Username, password and email are required. Other fields are optional.
# """
# class Meta(AbstractUser.Meta):
# swappable = 'AUTH_USER_MODEL'
| 36.717391 | 79 | 0.666075 | 219 | 1,689 | 5.050228 | 0.525114 | 0.029837 | 0.018083 | 0.03255 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001569 | 0.245115 | 1,689 | 45 | 80 | 37.533333 | 0.865882 | 0.917703 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
a86da01bc5deadfbef4d95de97a5e5217a078c02 | 500 | py | Python | spotify_dashboard/spotify/models.py | timmyomahony/spotify-picture-frame | 259799b27da331341b0d860885be0aec091e32ff | [
"MIT"
] | 1 | 2020-11-03T11:04:22.000Z | 2020-11-03T11:04:22.000Z | spotify_dashboard/spotify/models.py | timmyomahony/spotify-picture-frame | 259799b27da331341b0d860885be0aec091e32ff | [
"MIT"
] | null | null | null | spotify_dashboard/spotify/models.py | timmyomahony/spotify-picture-frame | 259799b27da331341b0d860885be0aec091e32ff | [
"MIT"
] | null | null | null | import time
from django.db import models
from django.utils.timesince import timesince
class Track(models.Model):
id = models.CharField(max_length=30, primary_key=True)
artist = models.CharField(max_length=500)
album = models.CharField(max_length=500)
title = models.CharField(max_length=500)
image = models.URLField()
href = models.URLField()
data = models.JSONField()
published = models.BooleanField(default=True)
def __str__(self):
return self.title
| 26.315789 | 58 | 0.722 | 64 | 500 | 5.5 | 0.546875 | 0.170455 | 0.204545 | 0.272727 | 0.230114 | 0 | 0 | 0 | 0 | 0 | 0 | 0.026764 | 0.178 | 500 | 18 | 59 | 27.777778 | 0.829684 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.071429 | false | 0 | 0.214286 | 0.071429 | 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 |
a8723c707610ff2d371e0e72d391d934a953ce69 | 238 | py | Python | LAMARCK_ML/metrics/__init__.py | JonasDHomburg/LAMARCK | 0e372c908ff59effc6fd68e6477d04c4d89e6c26 | [
"Apache-2.0",
"BSD-3-Clause"
] | 3 | 2019-09-20T08:03:47.000Z | 2021-05-10T11:02:09.000Z | LAMARCK_ML/metrics/__init__.py | JonasDHomburg/LAMARCK_ML | 0e372c908ff59effc6fd68e6477d04c4d89e6c26 | [
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | LAMARCK_ML/metrics/__init__.py | JonasDHomburg/LAMARCK_ML | 0e372c908ff59effc6fd68e6477d04c4d89e6c26 | [
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null | from .implementations import Accuracy, \
FlOps, \
Nodes, \
TimeMetric, \
MemoryMetric, \
Parameters, \
LayoutCrossingEdges, \
LayoutDistanceX, \
LayoutDistanceY, \
CartesianFitness
from .interface import MetricInterface
| 19.833333 | 40 | 0.731092 | 17 | 238 | 10.235294 | 0.882353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184874 | 238 | 11 | 41 | 21.636364 | 0.896907 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.181818 | 0 | 0.181818 | 0 | 1 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
a89fc07496dfb31710239a16f1bdafb72d4ca886 | 6,242 | py | Python | databricks/koalas/missing/window.py | HG1112/koalas | 580f48c81d3d2236c399063ce453f9170d88b954 | [
"Apache-2.0"
] | 1 | 2019-12-06T05:01:34.000Z | 2019-12-06T05:01:34.000Z | databricks/koalas/missing/window.py | HG1112/koalas | 580f48c81d3d2236c399063ce453f9170d88b954 | [
"Apache-2.0"
] | null | null | null | databricks/koalas/missing/window.py | HG1112/koalas | 580f48c81d3d2236c399063ce453f9170d88b954 | [
"Apache-2.0"
] | null | null | null | #
# Copyright (C) 2019 Databricks, 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 databricks.koalas.missing import _unsupported_function, _unsupported_property
def unsupported_function_expanding(method_name, deprecated=False, reason=""):
return _unsupported_function(class_name='pandas.core.window.Expanding', method_name=method_name,
deprecated=deprecated, reason=reason)
def unsupported_property_expanding(property_name, deprecated=False, reason=""):
return _unsupported_property(
class_name='pandas.core.window.Expanding', property_name=property_name,
deprecated=deprecated, reason=reason)
def unsupported_function_rolling(method_name, deprecated=False, reason=""):
return _unsupported_function(class_name='pandas.core.window.Rolling', method_name=method_name,
deprecated=deprecated, reason=reason)
def unsupported_property_rolling(property_name, deprecated=False, reason=""):
return _unsupported_property(
class_name='pandas.core.window.Rolling', property_name=property_name,
deprecated=deprecated, reason=reason)
class _MissingPandasLikeExpanding(object):
agg = unsupported_function_expanding("agg")
aggregate = unsupported_function_expanding("aggregate")
apply = unsupported_function_expanding("apply")
corr = unsupported_function_expanding("corr")
count = unsupported_function_expanding("count")
cov = unsupported_function_expanding("cov")
kurt = unsupported_function_expanding("kurt")
max = unsupported_function_expanding("max")
mean = unsupported_function_expanding("mean")
median = unsupported_function_expanding("median")
min = unsupported_function_expanding("min")
quantile = unsupported_function_expanding("quantile")
skew = unsupported_function_expanding("skew")
std = unsupported_function_expanding("std")
sum = unsupported_function_expanding("sum")
validate = unsupported_function_expanding("validate")
var = unsupported_function_expanding("var")
exclusions = unsupported_property_expanding("exclusions")
is_datetimelike = unsupported_property_expanding("is_datetimelike")
is_freq_type = unsupported_property_expanding("is_freq_type")
ndim = unsupported_property_expanding("ndim")
class _MissingPandasLikeRolling(object):
agg = unsupported_property_rolling("agg")
aggregate = unsupported_property_rolling("aggregate")
apply = unsupported_property_rolling("apply")
corr = unsupported_property_rolling("corr")
count = unsupported_property_rolling("count")
cov = unsupported_property_rolling("cov")
kurt = unsupported_property_rolling("kurt")
max = unsupported_property_rolling("max")
mean = unsupported_property_rolling("mean")
median = unsupported_property_rolling("median")
min = unsupported_property_rolling("min")
quantile = unsupported_property_rolling("quantile")
skew = unsupported_property_rolling("skew")
std = unsupported_property_rolling("std")
sum = unsupported_property_rolling("sum")
validate = unsupported_property_rolling("validate")
var = unsupported_property_rolling("var")
exclusions = unsupported_property_rolling("exclusions")
is_datetimelike = unsupported_property_rolling("is_datetimelike")
is_freq_type = unsupported_property_rolling("is_freq_type")
ndim = unsupported_property_rolling("ndim")
class _MissingPandasLikeExpandingGroupby(object):
agg = unsupported_function_expanding("agg")
aggregate = unsupported_function_expanding("aggregate")
apply = unsupported_function_expanding("apply")
corr = unsupported_function_expanding("corr")
count = unsupported_function_expanding("count")
cov = unsupported_function_expanding("cov")
kurt = unsupported_function_expanding("kurt")
max = unsupported_function_expanding("max")
mean = unsupported_function_expanding("mean")
median = unsupported_function_expanding("median")
min = unsupported_function_expanding("min")
quantile = unsupported_function_expanding("quantile")
skew = unsupported_function_expanding("skew")
std = unsupported_function_expanding("std")
sum = unsupported_function_expanding("sum")
validate = unsupported_function_expanding("validate")
var = unsupported_function_expanding("var")
exclusions = unsupported_property_expanding("exclusions")
is_datetimelike = unsupported_property_expanding("is_datetimelike")
is_freq_type = unsupported_property_expanding("is_freq_type")
ndim = unsupported_property_expanding("ndim")
class _MissingPandasLikeRollingGroupby(object):
agg = unsupported_function_rolling("agg")
aggregate = unsupported_function_rolling("aggregate")
apply = unsupported_function_rolling("apply")
corr = unsupported_function_rolling("corr")
count = unsupported_function_rolling("count")
cov = unsupported_function_rolling("cov")
kurt = unsupported_function_rolling("kurt")
max = unsupported_function_rolling("max")
mean = unsupported_function_rolling("mean")
median = unsupported_function_rolling("median")
min = unsupported_function_rolling("min")
quantile = unsupported_function_rolling("quantile")
skew = unsupported_function_rolling("skew")
std = unsupported_function_rolling("std")
sum = unsupported_function_rolling("sum")
validate = unsupported_function_rolling("validate")
var = unsupported_function_rolling("var")
exclusions = unsupported_property_rolling("exclusions")
is_datetimelike = unsupported_property_rolling("is_datetimelike")
is_freq_type = unsupported_property_rolling("is_freq_type")
ndim = unsupported_property_rolling("ndim")
| 44.585714 | 100 | 0.768343 | 660 | 6,242 | 6.915152 | 0.168182 | 0.233129 | 0.214724 | 0.021911 | 0.586328 | 0.586328 | 0.579316 | 0.576249 | 0.551709 | 0.551709 | 0 | 0.001491 | 0.14034 | 6,242 | 139 | 101 | 44.906475 | 0.84905 | 0.089234 | 0 | 0.543689 | 0 | 0 | 0.103016 | 0.019051 | 0 | 0 | 0 | 0 | 0 | 1 | 0.038835 | false | 0 | 0.009709 | 0.038835 | 0.941748 | 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 | 0 | 1 | 0 | 0 | 3 |
a8b203712862c05aef3aa6e6577ae93f4675e284 | 387 | py | Python | tests/test_version.py | datatags/pyCraft | 769d903e90a704ae860e16d74bc7c73437028ee8 | [
"Apache-2.0"
] | 759 | 2015-01-30T13:04:58.000Z | 2022-03-30T22:42:40.000Z | tests/test_version.py | datatags/pyCraft | 769d903e90a704ae860e16d74bc7c73437028ee8 | [
"Apache-2.0"
] | 220 | 2015-03-17T17:26:48.000Z | 2022-03-17T21:42:39.000Z | tests/test_version.py | datatags/pyCraft | 769d903e90a704ae860e16d74bc7c73437028ee8 | [
"Apache-2.0"
] | 284 | 2015-03-23T16:24:48.000Z | 2022-03-24T15:37:22.000Z | from distutils.version import StrictVersion as SV
import unittest
import minecraft
class VersionTest(unittest.TestCase):
def test_module_version_is_a_valid_pep_386_strict_version(self):
SV(minecraft.__version__)
def test_protocol_version_is_an_int(self):
for version in minecraft.SUPPORTED_PROTOCOL_VERSIONS:
self.assertTrue(type(version) is int)
| 27.642857 | 68 | 0.780362 | 51 | 387 | 5.529412 | 0.607843 | 0.095745 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009288 | 0.165375 | 387 | 13 | 69 | 29.769231 | 0.863777 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 1 | 0.222222 | 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 |
a8d2869f1b9f1c0b78363d4c3113427c11c89cfc | 8,982 | py | Python | packages/robot/odahuflow/robot/libraries/sdk_wrapper.py | odahu/odahuflow | 58c3220a266a61bb893cf79c4b994569e3445097 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | packages/robot/odahuflow/robot/libraries/sdk_wrapper.py | odahu/odahuflow | 58c3220a266a61bb893cf79c4b994569e3445097 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | packages/robot/odahuflow/robot/libraries/sdk_wrapper.py | odahu/odahuflow | 58c3220a266a61bb893cf79c4b994569e3445097 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | # for class Model
import json
from odahuflow.sdk import config
from odahuflow.sdk.clients.api_aggregated import parse_resources_file_with_one_item
from odahuflow.sdk.clients.configuration import ConfigurationClient
from odahuflow.sdk.clients.connection import ConnectionClient
from odahuflow.sdk.clients.deployment import ModelDeploymentClient
from odahuflow.sdk.clients.model import ModelClient
from odahuflow.sdk.clients.packaging import ModelPackagingClient
from odahuflow.sdk.clients.packaging_integration import PackagingIntegrationClient
from odahuflow.sdk.clients.route import ModelRouteClient
from odahuflow.sdk.clients.toolchain_integration import ToolchainIntegrationClient
from odahuflow.sdk.clients.training import ModelTrainingClient
from odahuflow.sdk.clients.batch_service import BatchInferenceServiceClient
from odahuflow.sdk.clients.batch_job import BatchInferenceJobClient
from odahuflow.sdk.clients.api import EntityAlreadyExists
from odahuflow.sdk.clients.user_info import UserInfoClient
class Login:
@staticmethod
def reload_config():
config._INI_FILE_TRIED_TO_BE_LOADED = False
config.reinitialize_variables()
class Configuration:
@staticmethod
def config_get(**kwargs):
return ConfigurationClient(**kwargs).get()
class Connection:
@staticmethod
def connection_get():
return ConnectionClient().get_all()
@staticmethod
def connection_get_id(conn_id: str):
return ConnectionClient().get(conn_id)
@staticmethod
def connection_get_id_decrypted(conn_id: str):
return ConnectionClient().get_decrypted(conn_id)
@staticmethod
def connection_put(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ConnectionClient().edit(api_object)
@staticmethod
def connection_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ConnectionClient().create(api_object)
@staticmethod
def connection_delete(conn_id: str):
return ConnectionClient().delete(conn_id)
class ModelDeployment:
@staticmethod
def deployment_get():
return ModelDeploymentClient().get_all()
@staticmethod
def deployment_get_id(dep_id: str):
return ModelDeploymentClient().get(dep_id)
@staticmethod
def deployment_put(payload_file, image=None):
api_object = parse_resources_file_with_one_item(payload_file).resource
if image:
api_object.spec.image = image
return ModelDeploymentClient().edit(api_object)
@staticmethod
def deployment_post(payload_file, *, id_=None, image=None):
api_object = parse_resources_file_with_one_item(payload_file).resource
if id_:
api_object.id = id_
if image:
api_object.spec.image = image
return ModelDeploymentClient().create(api_object)
@staticmethod
def deployment_delete(dep_id: str):
return ModelDeploymentClient().delete(dep_id)
@staticmethod
def deployment_get_default_route(dep_id: str):
return ModelDeploymentClient().get_default_route(dep_id)
class ModelPackaging:
@staticmethod
def packaging_get():
return ModelPackagingClient().get_all()
@staticmethod
def packaging_get_id(pack_id: str):
return ModelPackagingClient().get(pack_id)
@staticmethod
def packaging_put(payload_file, artifact_name=None):
api_object = parse_resources_file_with_one_item(payload_file).resource
if artifact_name:
api_object.spec.artifact_name = artifact_name
return ModelPackagingClient().edit(api_object)
@staticmethod
def packaging_post(payload_file, artifact_name=None):
api_object = parse_resources_file_with_one_item(payload_file).resource
if artifact_name:
api_object.spec.artifact_name = artifact_name
return ModelPackagingClient().create(api_object)
@staticmethod
def packaging_delete(pack_id: str):
return ModelPackagingClient().delete(pack_id)
@staticmethod
def packaging_get_log(pack_id):
log_generator = ModelPackagingClient().log(pack_id, follow=False)
# logs_list will be list of log lines
logs_list = list(log_generator)
text = "\n".join(logs_list)
return text
class ModelTraining:
@staticmethod
def training_get():
return ModelTrainingClient().get_all()
@staticmethod
def training_get_id(train_id: str):
return ModelTrainingClient().get(train_id)
@staticmethod
def training_put(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ModelTrainingClient().edit(api_object)
@staticmethod
def training_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ModelTrainingClient().create(api_object)
@staticmethod
def training_delete(train_id: str):
return ModelTrainingClient().delete(train_id)
@staticmethod
def training_get_log(train_id):
log_generator = ModelTrainingClient().log(train_id, follow=False)
# logs_list will be list of log lines
logs_list = list(log_generator)
text = "\n".join(logs_list)
return text
class ModelRoute:
@staticmethod
def route_get():
return ModelRouteClient().get_all()
@staticmethod
def route_get_id(route_id: str):
return ModelRouteClient().get(route_id)
@staticmethod
def route_put(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ModelRouteClient().edit(api_object)
@staticmethod
def route_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ModelRouteClient().create(api_object)
@staticmethod
def route_delete(route_id: str):
return ModelRouteClient().delete(route_id)
class Packager:
@staticmethod
def packager_get():
return PackagingIntegrationClient().get_all()
@staticmethod
def packager_get_id(pi_id: str):
return PackagingIntegrationClient().get(pi_id)
@staticmethod
def packager_put(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return PackagingIntegrationClient().edit(api_object)
@staticmethod
def packager_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return PackagingIntegrationClient().create(api_object)
@staticmethod
def packager_delete(pi_id: str):
return PackagingIntegrationClient().delete(pi_id)
class Toolchain:
@staticmethod
def toolchain_get():
return ToolchainIntegrationClient().get_all()
@staticmethod
def toolchain_get_id(ti_id: str):
return ToolchainIntegrationClient().get(ti_id)
@staticmethod
def toolchain_put(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ToolchainIntegrationClient().edit(api_object)
@staticmethod
def toolchain_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
return ToolchainIntegrationClient().create(api_object)
@staticmethod
def toolchain_delete(ti_id: str):
return ToolchainIntegrationClient().delete(ti_id)
class UserInfo:
@staticmethod
def user_info_get():
return UserInfoClient().get()
class Model:
@staticmethod
def model_get(base_url, model_route=None, model_deployment=None, url_prefix=None, **kwargs):
return ModelClient(
base_url,
model_route=model_route,
model_deployment=model_deployment,
url_prefix=url_prefix,
token=config.API_TOKEN
).info()
@staticmethod
def model_post(base_url, model_route=None, model_deployment=None, url_prefix=None, json_input=None, **kwargs):
return ModelClient(
base_url,
model_route=model_route,
model_deployment=model_deployment,
url_prefix=url_prefix,
token=config.API_TOKEN
).invoke(**json.loads(json_input))
class InferenceService:
@staticmethod
def service_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
try:
BatchInferenceServiceClient().create(api_object)
except EntityAlreadyExists:
pass
class InferenceJob:
@staticmethod
def job_post(payload_file):
api_object = parse_resources_file_with_one_item(payload_file).resource
en = BatchInferenceJobClient().create(api_object)
return en.id
@staticmethod
def job_get_id(id_: str):
return BatchInferenceJobClient().get(id_)
| 29.352941 | 114 | 0.725006 | 1,011 | 8,982 | 6.120673 | 0.11276 | 0.11393 | 0.049451 | 0.06044 | 0.620071 | 0.388817 | 0.36086 | 0.36086 | 0.36086 | 0.34276 | 0 | 0 | 0.200289 | 8,982 | 305 | 115 | 29.44918 | 0.861478 | 0.009686 | 0 | 0.406393 | 0 | 0 | 0.00045 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.214612 | false | 0.004566 | 0.073059 | 0.127854 | 0.552511 | 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 |
764dae1c165deea13176d04ddf5d9c3e1390137e | 643 | py | Python | lazytorch/layers/__init__.py | mgmalek/lazytorch | 9950b8841488471e147d5dbb86a446663b6c15dc | [
"MIT"
] | null | null | null | lazytorch/layers/__init__.py | mgmalek/lazytorch | 9950b8841488471e147d5dbb86a446663b6c15dc | [
"MIT"
] | null | null | null | lazytorch/layers/__init__.py | mgmalek/lazytorch | 9950b8841488471e147d5dbb86a446663b6c15dc | [
"MIT"
] | null | null | null | from .conv import LazyExpansionConv2d, LazyReductionConv2d
from .conv_norm_activ import ConvNormActivation, LazyConvNormActivation
from .depth_sep_conv import (
DepthwiseConv2d,
PointwiseConv2d,
DepthSepConv2d,
LazyDepthwiseConv2d,
LazyPointwiseConv2d,
LazyExpansionPointwiseConv2d,
LazyReductionPointwiseConv2d,
LazyDepthSepConv2d,
LazyExpansionDepthSepConv2d,
LazyReductionDepthSepConv2d,
)
from .squeeze_excitation import SqueezeExcitation, LazySqueezeExcitation
from .bottleneck import BottleneckBlock, LazyBottleneckBlock
from .inverted_bottleneck import InvertedBottleneck, LazyInvertedBottleneck
| 35.722222 | 75 | 0.839813 | 44 | 643 | 12.136364 | 0.704545 | 0.029963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021314 | 0.124417 | 643 | 17 | 76 | 37.823529 | 0.927176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.352941 | 0 | 0.352941 | 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 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
764ff5611043a9510a54937a0ad6a65d0156e951 | 845 | py | Python | functions_legacy/PathsCauchy.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | 6 | 2021-04-10T13:24:30.000Z | 2022-03-26T08:20:42.000Z | functions_legacy/PathsCauchy.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | null | null | null | functions_legacy/PathsCauchy.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | 6 | 2019-08-13T22:02:17.000Z | 2022-02-09T17:49:12.000Z | from numpy import ones, cumsum, diff, tile, r_
from numpy.random import rand
from scipy.stats import t
def PathsCauchy(x0,mu,sigma,tau,j_):
# This function generates paths for the process x such that the increments
# dx are iid Cauchy distributed.
# INPUTS
# x0 :[scalar] initial value of process x at time zero
# mu :[scalar] location parameter of Cauchy distribution
# sigma :[scalar] dispersion arameter of Cauchy distribution
# tau :[row vector] vector of times for simulations
# j_ :[scalar] total number of paths
# OPS
# x :[matrix](j_ x tau_) array with paths on the rows
## Code
t_ = len(tau)
r = rand(j_,t_-1)
dx = t.ppf(r,1,tile(mu*diff(tau,1),(j_,1)),tile(sigma*diff(tau,1),(j_,1)))
x = r_['-1',x0*ones((j_,1)), x0+cumsum(dx,axis=1)]
return x
| 33.8 | 78 | 0.64142 | 135 | 845 | 3.925926 | 0.496296 | 0.011321 | 0.075472 | 0.033962 | 0.037736 | 0 | 0 | 0 | 0 | 0 | 0 | 0.020249 | 0.240237 | 845 | 24 | 79 | 35.208333 | 0.805296 | 0.527811 | 0 | 0 | 1 | 0 | 0.005181 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0.333333 | 0 | 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 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
7652996e6f5ffb51a7d0df902af01221997efaae | 728 | py | Python | app/models.py | evantoh/news-article | 54976a3b1b5f6a141bbe13e8ab3a49dfd46d8500 | [
"Unlicense"
] | null | null | null | app/models.py | evantoh/news-article | 54976a3b1b5f6a141bbe13e8ab3a49dfd46d8500 | [
"Unlicense"
] | null | null | null | app/models.py | evantoh/news-article | 54976a3b1b5f6a141bbe13e8ab3a49dfd46d8500 | [
"Unlicense"
] | null | null | null |
class Articles:
def __init__(self,id,name,author, title, description, url, urlToImage,publishedAt):
self.id = id
self.name = name
self.author = author
self.title = title
self.description = description
self.url = url
self.urlToImage = urlToImage
self.publishedAt = publishedAt
class Source:
"""
Source class to define news source object
"""
def __init__(self, id, name, author, title, url, urlToImage, publishedAt):
self.id = id
self.name = name
self.author = author
self.title = title
self.url = url
self.urlToImage = urlToImage
self.publishedAt = publishedAt
| 21.411765 | 87 | 0.587912 | 77 | 728 | 5.454545 | 0.233766 | 0.057143 | 0.052381 | 0.061905 | 0.780952 | 0.780952 | 0.780952 | 0.647619 | 0.647619 | 0.371429 | 0 | 0 | 0.331044 | 728 | 33 | 88 | 22.060606 | 0.862423 | 0.056319 | 0 | 0.736842 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.105263 | false | 0 | 0 | 0 | 0.210526 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 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 |
769cd151bfff35e599b6b4d6a430fabc5c061bb9 | 56 | py | Python | web/code/mmg/jobtrak/util/__init__.py | 559Labs/JobTrak | 5b118248e9b6e62f479a335b5a23b7062b6f2368 | [
"Apache-2.0"
] | 1 | 2015-01-27T00:41:31.000Z | 2015-01-27T00:41:31.000Z | web/code/mmg/jobtrak/util/__init__.py | andrewmarconi/JobTrak | 5b118248e9b6e62f479a335b5a23b7062b6f2368 | [
"Apache-2.0"
] | 118 | 2015-01-26T14:02:52.000Z | 2015-01-29T18:35:07.000Z | web/code/mmg/jobtrak/util/__init__.py | MarconiMediaGroup/JobTrak | 5b118248e9b6e62f479a335b5a23b7062b6f2368 | [
"Apache-2.0"
] | null | null | null | default_app_config = 'mmg.jobtrak.util.apps.LocalConfig' | 56 | 56 | 0.839286 | 8 | 56 | 5.625 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.035714 | 56 | 1 | 56 | 56 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0.578947 | 0.578947 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
769f8f43c009cc26df35b8f606d1b914ff167485 | 670 | py | Python | ibt/context.py | rcook/ibt | 6ab5bda2067ef053874938a4ec445ea0e54b30f2 | [
"MIT"
] | null | null | null | ibt/context.py | rcook/ibt | 6ab5bda2067ef053874938a4ec445ea0e54b30f2 | [
"MIT"
] | 13 | 2018-08-08T15:40:54.000Z | 2021-06-22T21:00:36.000Z | ibt/context.py | rcook/ibt | 6ab5bda2067ef053874938a4ec445ea0e54b30f2 | [
"MIT"
] | null | null | null | ###############################################################################
#
# IBT: Isolated Build Tool
# Copyright (C) 2016, Richard Cook. All rights reserved.
#
# Simple wrappers around Docker etc. for fully isolated build environments
#
###############################################################################
from __future__ import print_function
from ibt.util import get_user_info
class Context(object):
def __init__(self, working_dir):
self._working_dir = working_dir
self._user_info = get_user_info(working_dir)
@property
def working_dir(self): return self._working_dir
def user_info(self): return self._user_info
| 29.130435 | 79 | 0.568657 | 72 | 670 | 4.930556 | 0.541667 | 0.169014 | 0.11831 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006957 | 0.141791 | 670 | 22 | 80 | 30.454545 | 0.610435 | 0.226866 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.222222 | 0.222222 | 0.666667 | 0.111111 | 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 |
76c5d6ceadd233d09e6617cd9a2eac6fd428af2a | 183 | py | Python | src/python/starpattern.py | DHANUSHXENO/a-patterns | 701ce22fdb1ac54b71943167edb97db89b7f311b | [
"MIT"
] | null | null | null | src/python/starpattern.py | DHANUSHXENO/a-patterns | 701ce22fdb1ac54b71943167edb97db89b7f311b | [
"MIT"
] | null | null | null | src/python/starpattern.py | DHANUSHXENO/a-patterns | 701ce22fdb1ac54b71943167edb97db89b7f311b | [
"MIT"
] | null | null | null | def star_pattern(n):
for i in range(n):
for j in range(i+1):
print("*",end=" ")
print()
star_pattern(5)
'''
star_pattern(5)
*
* *
* * *
* * * *
* * * * *
'''
| 10.764706 | 24 | 0.437158 | 24 | 183 | 3.208333 | 0.541667 | 0.428571 | 0.311688 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02381 | 0.311475 | 183 | 16 | 25 | 11.4375 | 0.587302 | 0 | 0 | 0 | 0 | 0 | 0.01626 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0 | 0 | 0.166667 | 0.333333 | 1 | 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 | 0 | 0 | 0 | 0 | 3 |
4f20762324b6b2fc448e38806dd6a4f57cbf8e18 | 119 | py | Python | example/test_problem/ELBDM/DiscHeating/plot_script/FieldList.py | CliffLinTw/gamer | 6974d0b19133f253f2b867542f97b2acf1e9d756 | [
"BSD-3-Clause"
] | null | null | null | example/test_problem/ELBDM/DiscHeating/plot_script/FieldList.py | CliffLinTw/gamer | 6974d0b19133f253f2b867542f97b2acf1e9d756 | [
"BSD-3-Clause"
] | null | null | null | example/test_problem/ELBDM/DiscHeating/plot_script/FieldList.py | CliffLinTw/gamer | 6974d0b19133f253f2b867542f97b2acf1e9d756 | [
"BSD-3-Clause"
] | null | null | null | import yt
ds = yt.load("/work1/clifflin/gamer-fork/bin/Plummer/Data_000000")
for i in sorted(ds.field_list):
print(i)
| 23.8 | 66 | 0.747899 | 22 | 119 | 3.954545 | 0.863636 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.064815 | 0.092437 | 119 | 4 | 67 | 29.75 | 0.740741 | 0 | 0 | 0 | 0 | 0 | 0.420168 | 0.420168 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 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 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
4f27e94364e886c37f053be2d331525eebc5847a | 74 | py | Python | constants.py | texdarkstar/py3bot | 05a60c49894415e00a59bbe086a58c4e6b331fb5 | [
"MIT"
] | 1 | 2021-11-21T02:02:44.000Z | 2021-11-21T02:02:44.000Z | constants.py | texdarkstar/py3bot | 05a60c49894415e00a59bbe086a58c4e6b331fb5 | [
"MIT"
] | null | null | null | constants.py | texdarkstar/py3bot | 05a60c49894415e00a59bbe086a58c4e6b331fb5 | [
"MIT"
] | 1 | 2021-11-21T02:02:47.000Z | 2021-11-21T02:02:47.000Z | from telnetlib import IAC, WILL, TTYPE, SB, SE
IS = chr(0).encode()
| 14.8 | 47 | 0.635135 | 12 | 74 | 3.916667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017544 | 0.22973 | 74 | 4 | 48 | 18.5 | 0.807018 | 0 | 0 | 0 | 0 | 0 | 0 | 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 |
4f2c289d320d89598f93fc9d4f19d5ebb552c658 | 3,386 | py | Python | gen.nginx.py | Frozen12/OnlineIDE | be89c6f13846e48e0e97ed655ff13be414d326be | [
"Apache-2.0"
] | 2 | 2022-01-16T15:55:24.000Z | 2022-01-22T15:06:54.000Z | gen.nginx.py | Frozen12/OnlineIDE | be89c6f13846e48e0e97ed655ff13be414d326be | [
"Apache-2.0"
] | 1 | 2021-05-13T18:49:31.000Z | 2021-05-18T07:31:01.000Z | gen.nginx.py | Frozen12/OnlineIDE | be89c6f13846e48e0e97ed655ff13be414d326be | [
"Apache-2.0"
] | 6 | 2021-05-13T17:14:29.000Z | 2022-01-30T07:20:12.000Z | import os
print("""
##
# You should look at the following URL's in order to grasp a solid understanding
# of Nginx configuration files in order to fully unleash the power of Nginx.
# https://www.nginx.com/resources/wiki/start/
# https://www.nginx.com/resources/wiki/start/topics/tutorials/config_pitfalls/
# https://wiki.debian.org/Nginx/DirectoryStructure
#
# In most cases, administrators will remove this file from sites-enabled/ and
# leave it as reference inside of sites-available where it will continue to be
# updated by the nginx packaging team.
#
# This file will automatically load configuration files provided by other
# applications, such as Drupal or Wordpress. These applications will be made
# available underneath a path with that package name, such as /drupal8.
#
# Please see /usr/share/doc/nginx-doc/examples/ for more detailed examples.
##
# Default server configuration
#
server {
listen %s default_server;
listen [::]:%s default_server;
# SSL configuration
#
# listen 443 ssl default_server;
# listen [::]:443 ssl default_server;
#
# Note: You should disable gzip for SSL traffic.
# See: https://bugs.debian.org/773332
#
# Read up on ssl_ciphers to ensure a secure configuration.
# See: https://bugs.debian.org/765782
#
# Self signed certs generated by the ssl-cert package
# Don't use them in a production server!
#
# include snippets/snakeoil.conf;
root /var/www/html;
error_page 404 /notfound;
# Add index.php to the list if you are using PHP
index index.html index.htm index.nginx-debian.html;
server_name _;
location / {
proxy_pass http://0.0.0.0:8000/;
}
location /terminal {
proxy_pass http://0.0.0.0:8001/;
}
location /terminal/ws {
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header Host $host;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
proxy_pass http://0.0.0.0:8001/ws;
}
location /preview {
proxy_pass http://0.0.0.0:5000/;
}
location /notfound {
root /krypton/worker;
}
# pass PHP scripts to FastCGI server
#
#location ~ \.php$ {
# include snippets/fastcgi-php.conf;
#
# # With php-fpm (or other unix sockets):
# fastcgi_pass unix:/run/php/php7.3-fpm.sock;
# # With php-cgi (or other tcp sockets):
# fastcgi_pass 127.0.0.1:9000;
#}
# deny access to .htaccess files, if Apache's document root
# concurs with nginx's one
#
#location ~ /\.ht {
# deny all;
#}
}
# Virtual Host configuration for example.com
#
# You can move that to a different file under sites-available/ and symlink that
# to sites-enabled/ to enable it.
#
#server {
# listen 80;
# listen [::]:80;
#
# server_name example.com;
#
# root /var/www/example.com;
# index index.html;
#
# location / {
# try_files $uri $uri/ =404;
# }
#}
"""%(os.environ.get("PORT"), os.environ.get("PORT"))) | 30.781818 | 80 | 0.603662 | 433 | 3,386 | 4.646651 | 0.448037 | 0.012922 | 0.011928 | 0.027833 | 0.140159 | 0.071571 | 0.071571 | 0.020875 | 0 | 0 | 0 | 0.031433 | 0.295334 | 3,386 | 110 | 81 | 30.781818 | 0.811819 | 0 | 0 | 0.06 | 0 | 0.02 | 0.980809 | 0.054621 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.07 | 0.01 | 0 | 0.01 | 0.01 | 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 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
4f5001e8746107e356347ba4628bb42d71a639be | 1,124 | py | Python | src/main.py | mmData/Hack4Good | 61d79a4c56872ed5fabb280b8e9f91c4c4f71ece | [
"RSA-MD"
] | null | null | null | src/main.py | mmData/Hack4Good | 61d79a4c56872ed5fabb280b8e9f91c4c4f71ece | [
"RSA-MD"
] | null | null | null | src/main.py | mmData/Hack4Good | 61d79a4c56872ed5fabb280b8e9f91c4c4f71ece | [
"RSA-MD"
] | null | null | null | """
Created on Wed Nov 07 2018
@author: Analytics Club at ETH internal@analytics-club.org
Example structure of the main file
"""
from src.data_extraction import load_data, save_data, merging, xml2df
from src.preprocessing import text_process, anonymization, clean_up, detect_language
def extract_data(program, mode):
"""
function to extract data
"""
print('Starting data extraction ...')
print('Program {}, mode {}'.format(program, mode))
def preprocess(program, mode):
"""
function for preprocessing
"""
print("Doing preprocessing")
print('Program {}, mode {}'.format(program, mode))
def train(program, mode):
"""
function to train the model
"""
print('Program {}, mode {}'.format(program, mode))
print('Training the model...')
def predict(program, mode):
"""
function to do predictions
"""
print('Program {}, mode {}'.format(program, mode))
print('Do prediction...')
def test(program, mode):
"""
function to do tests
"""
print('Program {}, mode {}'.format(program, mode))
print('Doing tests...')
| 18.42623 | 84 | 0.636121 | 131 | 1,124 | 5.40458 | 0.435115 | 0.233051 | 0.134181 | 0.155367 | 0.327684 | 0.262712 | 0.262712 | 0 | 0 | 0 | 0 | 0.007946 | 0.216192 | 1,124 | 60 | 85 | 18.733333 | 0.795687 | 0.22242 | 0 | 0.294118 | 0 | 0 | 0.247119 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.294118 | false | 0 | 0.117647 | 0 | 0.411765 | 0.588235 | 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 | 0 | 0 | 1 | 0 | 3 |
4f530bbd9256fee9929035d49abd45c5563302e2 | 389 | py | Python | misc/context_processors.py | ilblackdragon/django-misc | 0accd2dc97de656a1c9e275be81e817f78a2eb9d | [
"MIT"
] | 6 | 2015-05-13T14:56:30.000Z | 2019-06-27T13:24:04.000Z | misc/context_processors.py | ilblackdragon/django-misc | 0accd2dc97de656a1c9e275be81e817f78a2eb9d | [
"MIT"
] | null | null | null | misc/context_processors.py | ilblackdragon/django-misc | 0accd2dc97de656a1c9e275be81e817f78a2eb9d | [
"MIT"
] | null | null | null | from django.conf import settings
def useful_constants(request):
"""
This workaround useful if you want use {% if var == None %}, because
{% if not var %} First {% else %} Second {% endif %} will show the result:
var = None => First
var = False => First
var = True => True
"""
return {'True': True, 'False': False, 'None': None, 'settings': settings}
| 29.923077 | 78 | 0.59383 | 49 | 389 | 4.693878 | 0.612245 | 0.06087 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.262211 | 389 | 12 | 79 | 32.416667 | 0.801394 | 0.534704 | 0 | 0 | 0 | 0 | 0.14094 | 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 |
4f57c9a375f9390d8eda45711f1d8f3c5ab13554 | 349 | py | Python | Python/FromUniversity/sqlite3/select.py | programmer-666/Codes | fdffe38a789ba3636dff7ceaa9f1b4113ae17c2b | [
"MIT"
] | null | null | null | Python/FromUniversity/sqlite3/select.py | programmer-666/Codes | fdffe38a789ba3636dff7ceaa9f1b4113ae17c2b | [
"MIT"
] | null | null | null | Python/FromUniversity/sqlite3/select.py | programmer-666/Codes | fdffe38a789ba3636dff7ceaa9f1b4113ae17c2b | [
"MIT"
] | 1 | 2021-09-16T14:24:29.000Z | 2021-09-16T14:24:29.000Z | import sqlite3 as slt
""" fetchone - tek tek alır. fetchmany - belirtilen sayı kadar alır. """
db = slt.connect("user.db")
print(db.cursor().execute("SELECT * FROM USERPASSWORDS").fetchall())
#print(db.cursor().execute("SELECT * FROM USERNAMES").fetchmany(2))
#print(db.cursor().execute("SELECT * FROM USERNAMES").fetchone())
db.commit();db.close()
| 43.625 | 72 | 0.710602 | 47 | 349 | 5.276596 | 0.531915 | 0.084677 | 0.157258 | 0.241935 | 0.435484 | 0.435484 | 0.314516 | 0 | 0 | 0 | 0 | 0.006329 | 0.094556 | 349 | 7 | 73 | 49.857143 | 0.778481 | 0.372493 | 0 | 0 | 0 | 0 | 0.234483 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.25 | 0.25 | 0 | 0.25 | 0.25 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
4f5a68bc57b03b9960b5f5024d7514c44569ccf0 | 18,957 | py | Python | RestPy/ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/pimsm/router/interface/joinprune/joinprune.py | ralfjon/IxNetwork | c0c834fbc465af69c12fd6b7cee4628baba7fff1 | [
"MIT"
] | null | null | null | RestPy/ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/pimsm/router/interface/joinprune/joinprune.py | ralfjon/IxNetwork | c0c834fbc465af69c12fd6b7cee4628baba7fff1 | [
"MIT"
] | null | null | null | RestPy/ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/pimsm/router/interface/joinprune/joinprune.py | ralfjon/IxNetwork | c0c834fbc465af69c12fd6b7cee4628baba7fff1 | [
"MIT"
] | null | null | null |
# Copyright 1997 - 2018 by IXIA Keysight
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
from ixnetwork_restpy.base import Base
from ixnetwork_restpy.files import Files
class JoinPrune(Base):
"""The JoinPrune class encapsulates a user managed joinPrune node in the ixnetwork hierarchy.
An instance of the class can be obtained by accessing the JoinPrune property from a parent instance.
The internal properties list will be empty when the property is accessed and is populated from the server using the find method.
The internal properties list can be managed by the user by using the add and remove methods.
"""
_SDM_NAME = 'joinPrune'
def __init__(self, parent):
super(JoinPrune, self).__init__(parent)
@property
def LearnedMgrState(self):
"""An instance of the LearnedMgrState class.
Returns:
obj(ixnetwork_restpy.testplatform.sessions.ixnetwork.vport.protocols.pimsm.router.interface.joinprune.learnedmgrstate.learnedmgrstate.LearnedMgrState)
Raises:
NotFoundError: The requested resource does not exist on the server
ServerError: The server has encountered an uncategorized error condition
"""
from ixnetwork_restpy.testplatform.sessions.ixnetwork.vport.protocols.pimsm.router.interface.joinprune.learnedmgrstate.learnedmgrstate import LearnedMgrState
return LearnedMgrState(self)
@property
def DiscardRegisterStates(self):
"""If checked, the Learned Join States sent by the RP (DUT) in response to this specific Register Message will be discarded - and will not be displayed in the table of the Register Range window.
Returns:
bool
"""
return self._get_attribute('discardRegisterStates')
@DiscardRegisterStates.setter
def DiscardRegisterStates(self, value):
self._set_attribute('discardRegisterStates', value)
@property
def Enabled(self):
"""Enables the use of this join/prune.
Returns:
bool
"""
return self._get_attribute('enabled')
@Enabled.setter
def Enabled(self, value):
self._set_attribute('enabled', value)
@property
def EnabledDataMdt(self):
"""If enabled, pimsmLearnedDataMdt will be available. (default = disabled)
Returns:
bool
"""
return self._get_attribute('enabledDataMdt')
@EnabledDataMdt.setter
def EnabledDataMdt(self, value):
self._set_attribute('enabledDataMdt', value)
@property
def FlapEnabled(self):
"""Enables emulated flapping of this multicast group range. NOTE: Flapping is not supported for the Switchover (*, G) -> (S, G) range type.
Returns:
bool
"""
return self._get_attribute('flapEnabled')
@FlapEnabled.setter
def FlapEnabled(self, value):
self._set_attribute('flapEnabled', value)
@property
def FlapInterval(self):
"""Defines the join/prune flapping interval.
Returns:
number
"""
return self._get_attribute('flapInterval')
@FlapInterval.setter
def FlapInterval(self, value):
self._set_attribute('flapInterval', value)
@property
def GroupAddress(self):
"""An IPv4 or IPv6 address used with the group mask to create a range of multicast addresses.
Returns:
str
"""
return self._get_attribute('groupAddress')
@GroupAddress.setter
def GroupAddress(self, value):
self._set_attribute('groupAddress', value)
@property
def GroupCount(self):
"""The number of multicast group addresses to be included in the multicast group range. The maximum number of valid possible addresses depends on the values for the group address and the group mask width.
Returns:
number
"""
return self._get_attribute('groupCount')
@GroupCount.setter
def GroupCount(self, value):
self._set_attribute('groupCount', value)
@property
def GroupMappingMode(self):
"""Sets the type of mapping that occurs when routes are advertised. This only applies for (S, G) and switchover types for MGR and is meaningful for RR.
Returns:
str(fullyMeshed|oneToOne)
"""
return self._get_attribute('groupMappingMode')
@GroupMappingMode.setter
def GroupMappingMode(self, value):
self._set_attribute('groupMappingMode', value)
@property
def GroupMaskWidth(self):
"""The number of bits in the mask applied to the group address. (The masked bits in the group address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type.
Returns:
number
"""
return self._get_attribute('groupMaskWidth')
@GroupMaskWidth.setter
def GroupMaskWidth(self, value):
self._set_attribute('groupMaskWidth', value)
@property
def GroupRange(self):
"""The multicast group range type.
Returns:
str(rp|g|sg|sptSwitchOver|registerTriggeredSg)
"""
return self._get_attribute('groupRange')
@GroupRange.setter
def GroupRange(self, value):
self._set_attribute('groupRange', value)
@property
def NumRegToReceivePerSg(self):
"""If rangeType is set to pimsmJoinsPrunesTypeRegisterTriggeredSG, then this is the count of register messages received that will trigger transmission of a (S,G) message. (default = 10)
Returns:
number
"""
return self._get_attribute('numRegToReceivePerSg')
@NumRegToReceivePerSg.setter
def NumRegToReceivePerSg(self, value):
self._set_attribute('numRegToReceivePerSg', value)
@property
def PackGroupsEnabled(self):
"""If enabled, multiple groups can be included within a single packet.
Returns:
bool
"""
return self._get_attribute('packGroupsEnabled')
@PackGroupsEnabled.setter
def PackGroupsEnabled(self, value):
self._set_attribute('packGroupsEnabled', value)
@property
def PruneSourceAddress(self):
"""ONLY used for (*,G) Type to send (S,G,rpt) Prune Messages. (Multicast addresses are invalid.)
Returns:
str
"""
return self._get_attribute('pruneSourceAddress')
@PruneSourceAddress.setter
def PruneSourceAddress(self, value):
self._set_attribute('pruneSourceAddress', value)
@property
def PruneSourceCount(self):
"""The number of prune source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width. The default value is 0. ONLY used for (*,G) type to send (S,G,rpt) prune messages.
Returns:
number
"""
return self._get_attribute('pruneSourceCount')
@PruneSourceCount.setter
def PruneSourceCount(self, value):
self._set_attribute('pruneSourceCount', value)
@property
def PruneSourceMaskWidth(self):
"""The number of bits in the mask applied to the prune source address. (The masked bits in the prune source address form the address prefix.)
Returns:
number
"""
return self._get_attribute('pruneSourceMaskWidth')
@PruneSourceMaskWidth.setter
def PruneSourceMaskWidth(self, value):
self._set_attribute('pruneSourceMaskWidth', value)
@property
def RpAddress(self):
"""The IP address of the Rendezvous Point (RP) router.
Returns:
str
"""
return self._get_attribute('rpAddress')
@RpAddress.setter
def RpAddress(self, value):
self._set_attribute('rpAddress', value)
@property
def SourceAddress(self):
"""The Multicast Source Address. Used for (S,G) Type and (S,G, rpt) only. (Multicast addresses are invalid.)
Returns:
str
"""
return self._get_attribute('sourceAddress')
@SourceAddress.setter
def SourceAddress(self, value):
self._set_attribute('sourceAddress', value)
@property
def SourceCount(self):
"""The number of multicast source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width.
Returns:
number
"""
return self._get_attribute('sourceCount')
@SourceCount.setter
def SourceCount(self, value):
self._set_attribute('sourceCount', value)
@property
def SourceMaskWidth(self):
"""The number of bits in the mask applied to the source address. (The masked bits in the source address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type. Used for (S,G) Type and (S,G, rpt) only.
Returns:
number
"""
return self._get_attribute('sourceMaskWidth')
@SourceMaskWidth.setter
def SourceMaskWidth(self, value):
self._set_attribute('sourceMaskWidth', value)
@property
def SptSwitchoverInterval(self):
"""The time interval (in seconds) allowed for the switch from using the RP tree to using a Source-specific tree - from (*,G) to (S,G). The default value is 0.
Returns:
number
"""
return self._get_attribute('sptSwitchoverInterval')
@SptSwitchoverInterval.setter
def SptSwitchoverInterval(self, value):
self._set_attribute('sptSwitchoverInterval', value)
def add(self, DiscardRegisterStates=None, Enabled=None, EnabledDataMdt=None, FlapEnabled=None, FlapInterval=None, GroupAddress=None, GroupCount=None, GroupMappingMode=None, GroupMaskWidth=None, GroupRange=None, NumRegToReceivePerSg=None, PackGroupsEnabled=None, PruneSourceAddress=None, PruneSourceCount=None, PruneSourceMaskWidth=None, RpAddress=None, SourceAddress=None, SourceCount=None, SourceMaskWidth=None, SptSwitchoverInterval=None):
"""Adds a new joinPrune node on the server and retrieves it in this instance.
Args:
DiscardRegisterStates (bool): If checked, the Learned Join States sent by the RP (DUT) in response to this specific Register Message will be discarded - and will not be displayed in the table of the Register Range window.
Enabled (bool): Enables the use of this join/prune.
EnabledDataMdt (bool): If enabled, pimsmLearnedDataMdt will be available. (default = disabled)
FlapEnabled (bool): Enables emulated flapping of this multicast group range. NOTE: Flapping is not supported for the Switchover (*, G) -> (S, G) range type.
FlapInterval (number): Defines the join/prune flapping interval.
GroupAddress (str): An IPv4 or IPv6 address used with the group mask to create a range of multicast addresses.
GroupCount (number): The number of multicast group addresses to be included in the multicast group range. The maximum number of valid possible addresses depends on the values for the group address and the group mask width.
GroupMappingMode (str(fullyMeshed|oneToOne)): Sets the type of mapping that occurs when routes are advertised. This only applies for (S, G) and switchover types for MGR and is meaningful for RR.
GroupMaskWidth (number): The number of bits in the mask applied to the group address. (The masked bits in the group address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type.
GroupRange (str(rp|g|sg|sptSwitchOver|registerTriggeredSg)): The multicast group range type.
NumRegToReceivePerSg (number): If rangeType is set to pimsmJoinsPrunesTypeRegisterTriggeredSG, then this is the count of register messages received that will trigger transmission of a (S,G) message. (default = 10)
PackGroupsEnabled (bool): If enabled, multiple groups can be included within a single packet.
PruneSourceAddress (str): ONLY used for (*,G) Type to send (S,G,rpt) Prune Messages. (Multicast addresses are invalid.)
PruneSourceCount (number): The number of prune source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width. The default value is 0. ONLY used for (*,G) type to send (S,G,rpt) prune messages.
PruneSourceMaskWidth (number): The number of bits in the mask applied to the prune source address. (The masked bits in the prune source address form the address prefix.)
RpAddress (str): The IP address of the Rendezvous Point (RP) router.
SourceAddress (str): The Multicast Source Address. Used for (S,G) Type and (S,G, rpt) only. (Multicast addresses are invalid.)
SourceCount (number): The number of multicast source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width.
SourceMaskWidth (number): The number of bits in the mask applied to the source address. (The masked bits in the source address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type. Used for (S,G) Type and (S,G, rpt) only.
SptSwitchoverInterval (number): The time interval (in seconds) allowed for the switch from using the RP tree to using a Source-specific tree - from (*,G) to (S,G). The default value is 0.
Returns:
self: This instance with all currently retrieved joinPrune data using find and the newly added joinPrune data available through an iterator or index
Raises:
ServerError: The server has encountered an uncategorized error condition
"""
return self._create(locals())
def remove(self):
"""Deletes all the joinPrune data in this instance from server.
Raises:
NotFoundError: The requested resource does not exist on the server
ServerError: The server has encountered an uncategorized error condition
"""
self._delete()
def find(self, DiscardRegisterStates=None, Enabled=None, EnabledDataMdt=None, FlapEnabled=None, FlapInterval=None, GroupAddress=None, GroupCount=None, GroupMappingMode=None, GroupMaskWidth=None, GroupRange=None, NumRegToReceivePerSg=None, PackGroupsEnabled=None, PruneSourceAddress=None, PruneSourceCount=None, PruneSourceMaskWidth=None, RpAddress=None, SourceAddress=None, SourceCount=None, SourceMaskWidth=None, SptSwitchoverInterval=None):
"""Finds and retrieves joinPrune data from the server.
All named parameters support regex and can be used to selectively retrieve joinPrune data from the server.
By default the find method takes no parameters and will retrieve all joinPrune data from the server.
Args:
DiscardRegisterStates (bool): If checked, the Learned Join States sent by the RP (DUT) in response to this specific Register Message will be discarded - and will not be displayed in the table of the Register Range window.
Enabled (bool): Enables the use of this join/prune.
EnabledDataMdt (bool): If enabled, pimsmLearnedDataMdt will be available. (default = disabled)
FlapEnabled (bool): Enables emulated flapping of this multicast group range. NOTE: Flapping is not supported for the Switchover (*, G) -> (S, G) range type.
FlapInterval (number): Defines the join/prune flapping interval.
GroupAddress (str): An IPv4 or IPv6 address used with the group mask to create a range of multicast addresses.
GroupCount (number): The number of multicast group addresses to be included in the multicast group range. The maximum number of valid possible addresses depends on the values for the group address and the group mask width.
GroupMappingMode (str(fullyMeshed|oneToOne)): Sets the type of mapping that occurs when routes are advertised. This only applies for (S, G) and switchover types for MGR and is meaningful for RR.
GroupMaskWidth (number): The number of bits in the mask applied to the group address. (The masked bits in the group address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type.
GroupRange (str(rp|g|sg|sptSwitchOver|registerTriggeredSg)): The multicast group range type.
NumRegToReceivePerSg (number): If rangeType is set to pimsmJoinsPrunesTypeRegisterTriggeredSG, then this is the count of register messages received that will trigger transmission of a (S,G) message. (default = 10)
PackGroupsEnabled (bool): If enabled, multiple groups can be included within a single packet.
PruneSourceAddress (str): ONLY used for (*,G) Type to send (S,G,rpt) Prune Messages. (Multicast addresses are invalid.)
PruneSourceCount (number): The number of prune source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width. The default value is 0. ONLY used for (*,G) type to send (S,G,rpt) prune messages.
PruneSourceMaskWidth (number): The number of bits in the mask applied to the prune source address. (The masked bits in the prune source address form the address prefix.)
RpAddress (str): The IP address of the Rendezvous Point (RP) router.
SourceAddress (str): The Multicast Source Address. Used for (S,G) Type and (S,G, rpt) only. (Multicast addresses are invalid.)
SourceCount (number): The number of multicast source addresses to be included. The maximum number of valid possible addresses depends on the values for the source address and the source mask width.
SourceMaskWidth (number): The number of bits in the mask applied to the source address. (The masked bits in the source address form the address prefix.)The default value is 32. The valid range is 1 to 128, depending on address family type. Used for (S,G) Type and (S,G, rpt) only.
SptSwitchoverInterval (number): The time interval (in seconds) allowed for the switch from using the RP tree to using a Source-specific tree - from (*,G) to (S,G). The default value is 0.
Returns:
self: This instance with matching joinPrune data retrieved from the server available through an iterator or index
Raises:
ServerError: The server has encountered an uncategorized error condition
"""
return self._select(locals())
def read(self, href):
"""Retrieves a single instance of joinPrune data from the server.
Args:
href (str): An href to the instance to be retrieved
Returns:
self: This instance with the joinPrune data from the server available through an iterator or index
Raises:
NotFoundError: The requested resource does not exist on the server
ServerError: The server has encountered an uncategorized error condition
"""
return self._read(href)
| 49.238961 | 444 | 0.752862 | 2,563 | 18,957 | 5.530238 | 0.124073 | 0.004233 | 0.018343 | 0.031043 | 0.71356 | 0.669395 | 0.627205 | 0.625229 | 0.616199 | 0.613377 | 0 | 0.003965 | 0.17508 | 18,957 | 384 | 445 | 49.367188 | 0.902417 | 0.69684 | 0 | 0.152174 | 0 | 0 | 0.107366 | 0.01547 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.021739 | 0 | 0.543478 | 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 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
4f5fad3d63a59d5dec2ec21bc023ae1c47bc19d2 | 371 | py | Python | Scripts/console/script.py | sporiyano/graphiti | 56d85e5262b76dc6ce4f213a4d80486e015de1b7 | [
"BSD-2-Clause"
] | 93 | 2015-01-01T17:49:53.000Z | 2022-02-24T21:25:15.000Z | Scripts/console/script.py | sporiyano/graphiti | 56d85e5262b76dc6ce4f213a4d80486e015de1b7 | [
"BSD-2-Clause"
] | 13 | 2015-03-30T18:01:05.000Z | 2018-05-28T03:47:33.000Z | Scripts/console/script.py | ThibaultReuille/graphiti | 56d85e5262b76dc6ce4f213a4d80486e015de1b7 | [
"BSD-2-Clause"
] | 31 | 2015-01-14T12:16:13.000Z | 2022-02-24T21:25:16.000Z | from Scripts import graphiti as og
from Scripts import std
from Scripts import nx
import sys
import argparse
import os.path
import glob
import fnmatch
import itertools
import random
import math
import json
class Script(object):
def __init__(self, console):
self.console = console
def run(self, args):
self.console.log("Error: run() method not implemented!") | 14.84 | 58 | 0.770889 | 55 | 371 | 5.127273 | 0.581818 | 0.117021 | 0.180851 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.16442 | 371 | 25 | 58 | 14.84 | 0.909677 | 0 | 0 | 0 | 0 | 0 | 0.096774 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.117647 | false | 0 | 0.705882 | 0 | 0.882353 | 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 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
4f6a761a21c5baeb65fb9380c05c0978f29b2265 | 327 | py | Python | src/search_items/models.py | janakparajuli/Survey_Office | 1d5eb673eef67f923bf4c2b24156bea76f5fc32d | [
"Apache-2.0"
] | null | null | null | src/search_items/models.py | janakparajuli/Survey_Office | 1d5eb673eef67f923bf4c2b24156bea76f5fc32d | [
"Apache-2.0"
] | null | null | null | src/search_items/models.py | janakparajuli/Survey_Office | 1d5eb673eef67f923bf4c2b24156bea76f5fc32d | [
"Apache-2.0"
] | null | null | null | from __future__ import unicode_literals
from django.conf import settings
from django.db import models
# Create your models here.
class Search(models.Model):
name = models.CharField(max_length=120)
link = models.CharField(max_length=120)
def __unicode__(self):
return self.name
def __str__(self):
return self.name
| 19.235294 | 40 | 0.776758 | 47 | 327 | 5.085106 | 0.553191 | 0.083682 | 0.150628 | 0.200837 | 0.225941 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021429 | 0.143731 | 327 | 16 | 41 | 20.4375 | 0.832143 | 0.073395 | 0 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.3 | 0.2 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
4f804d5a0e36342ad2a4e48d3e16c64fd9394410 | 746 | py | Python | unifrakturmaguntia/src/generate.py | graffitiMSX/msxpower-googlefontdirectory | 1e201a68c8181698c143279734c4677f194855d8 | [
"Apache-2.0"
] | 1 | 2016-06-05T07:51:16.000Z | 2016-06-05T07:51:16.000Z | unifrakturmaguntia/src/generate.py | graffitiMSX/msxpower-googlefontdirectory | 1e201a68c8181698c143279734c4677f194855d8 | [
"Apache-2.0"
] | null | null | null | unifrakturmaguntia/src/generate.py | graffitiMSX/msxpower-googlefontdirectory | 1e201a68c8181698c143279734c4677f194855d8 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python
#
# With the SFDs in the current directory, run this with
# $ python generate.py
import fontforge, sys
required_version = "20090923"
if fontforge.version() < required_version:
print ("Your version of FontForge is too old - %s or newer is required" % (required_version));
print ("Current fontforge version:")
print fontforge.version()
files = [
'UnifrakturMaguntia.sfd',
]
# smart features in fea/gdl/mif sources to be integrated into the buildpath
for font in files:
f = fontforge.open(font)
print ("Building ") + f.fullname + ( " ") + f.weight + (" from sfd sources with fontforge")
f.generate(f.fontname + '-' + f.weight + '.ttf')
f.close
print ("font version:")
print (f.version)
print ("Done");
| 24.064516 | 98 | 0.686327 | 101 | 746 | 5.039604 | 0.544554 | 0.117878 | 0.078585 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.013093 | 0.180965 | 746 | 30 | 99 | 24.866667 | 0.819967 | 0.22118 | 0 | 0 | 1 | 0 | 0.321181 | 0.038194 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.058824 | null | null | 0.411765 | 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 |
4f88238f777db0f4e648169070250612e0996459 | 1,885 | py | Python | Client/utils/listFileLumis.py | vkuznet/DBS | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | [
"Apache-2.0"
] | 8 | 2015-08-14T04:01:32.000Z | 2021-06-03T00:56:42.000Z | Client/utils/listFileLumis.py | yuyiguo/DBS | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | [
"Apache-2.0"
] | 162 | 2015-01-07T21:34:47.000Z | 2021-10-13T09:42:41.000Z | Client/utils/listFileLumis.py | yuyiguo/DBS | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | [
"Apache-2.0"
] | 16 | 2015-01-22T15:27:29.000Z | 2021-04-28T09:23:28.000Z | from __future__ import print_function
#DBS-3 imports
import time
from dbs.apis.dbsClient import *
url="https://cmsweb.cern.ch/dbs/prod/global/DBSReader/"
#url="https://dbs3-test2.cern.ch/dbs/dev/global/DBSReader/"
# API Object
dbs3api = DbsApi(url=url)
# will throw error because no lfn or block_name provided
run_num = 297723
#print (dbs3api.listFileLumis(run_num=run_num))
lfn = '/store/relval/CMSSW_9_2_3_patch2/DoubleEG/RECO/2017_07_11_19_22_PRref_92X_dataRun2_Prompt_RefGT_week28_2017-v1/00000/B6DEF099-6366-E711-94F9-0025905A6104.root'
#print (dbs3api.listFileLumis(logical_file_name=lfn))
#print (dbs3api.listFileLumis(block_name="/DoubleEG/CMSSW_9_2_3_patch2-2017_07_11_19_22_PRref_92X_dataRun2_Prompt_RefGT_week28_2017-v1/RECO#69d88304-6678-11e7-ab2c-02163e00d7b3"))
# We are testing listFileLumiArray
lfn_list = ['/store/relval/CMSSW_9_3_0_pre2/RelValMinBias_13/GEN-SIM-RECO/92X_upgrade2017_design_IdealBS_v7-v1/00000/FC2FFB7B-BF68-E711-9779-0CC47A4D75EC.root',
'/store/relval/CMSSW_9_3_0_pre2/RelValMinBias_13/GEN-SIM-RECO/92X_upgrade2017_design_IdealBS_v7-v1/00000/388DDB84-BF68-E711-BB04-0CC47A4D76D2.root',
'/store/relval/CMSSW_9_2_3_patch2/DoubleEG/RECO/2017_07_11_19_22_PRref_92X_dataRun2_Prompt_RefGT_week28_2017-v1/00000/B6DEF099-6366-E711-94F9-0025905A6104.root']
print(dbs3api.listFileLumiArray(logical_file_name=lfn_list, validFileOnly=0))
#print(dbs3api.listFileLumiArray(run_num=[297723, 100], logical_file_name=lfn, validFileOnly=0))
# will throw exception because cannot be two list.
#print(dbs3api.listFileLumiArray(run_num=[297723, 100], logical_file_name=lfn_list, validFileOnly=0))
# will throw exceprion because block_name is not supported.
#print(dbs3api.listFileLumiArray(block_name="/DoubleEG/CMSSW_9_2_3_patch2-2017_07_11_19_22_PRref_92X_dataRun2_Prompt_RefGT_week28_2017-v1/RECO#69d88304-6678-11e7-ab2c-02163e00d7b3", validFileOnly=0))
| 55.441176 | 199 | 0.838196 | 298 | 1,885 | 4.956376 | 0.355705 | 0.056872 | 0.043331 | 0.046039 | 0.590386 | 0.58497 | 0.58497 | 0.548409 | 0.548409 | 0.548409 | 0 | 0.181666 | 0.050928 | 1,885 | 33 | 200 | 57.121212 | 0.643935 | 0.503448 | 0 | 0 | 0 | 0.363636 | 0.711184 | 0.65798 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.272727 | 0 | 0.272727 | 0.181818 | 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 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
4f934a58ff2ca49d71df3afac1a02ffb913fa343 | 260 | py | Python | resources/libExamples/python_class/reader1.py | andy897221/Proof-of-Play-Flow-Demo | 018ec382801f1363711b7680e728535a2ac94d26 | [
"MIT"
] | null | null | null | resources/libExamples/python_class/reader1.py | andy897221/Proof-of-Play-Flow-Demo | 018ec382801f1363711b7680e728535a2ac94d26 | [
"MIT"
] | null | null | null | resources/libExamples/python_class/reader1.py | andy897221/Proof-of-Play-Flow-Demo | 018ec382801f1363711b7680e728535a2ac94d26 | [
"MIT"
] | null | null | null | import time
from concurrent.futures import ThreadPoolExecutor
import read2
import data_class
executor = ThreadPoolExecutor(1)
executor.submit(read2.test)
print(data_class.data.a)
data_class.data.a = "reader 1 received!"
time.sleep(3)
print(data_class.data.a) | 21.666667 | 49 | 0.815385 | 39 | 260 | 5.333333 | 0.487179 | 0.173077 | 0.1875 | 0.201923 | 0.182692 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021097 | 0.088462 | 260 | 12 | 50 | 21.666667 | 0.85654 | 0 | 0 | 0.2 | 0 | 0 | 0.068966 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0.2 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
4f9ca017d8993f316f0c7fd3c1640c6b4667a2cc | 1,002 | py | Python | djangae/contrib/googleauth/backends/base.py | sleepyjames/djangae | 79a9e42c09c3be1189464870f008f8af7060bd9c | [
"BSD-3-Clause"
] | 467 | 2015-01-02T22:35:37.000Z | 2022-02-22T23:13:36.000Z | djangae/contrib/googleauth/backends/base.py | sleepyjames/djangae | 79a9e42c09c3be1189464870f008f8af7060bd9c | [
"BSD-3-Clause"
] | 743 | 2015-01-02T15:55:34.000Z | 2021-01-29T09:43:19.000Z | djangae/contrib/googleauth/backends/base.py | sleepyjames/djangae | 79a9e42c09c3be1189464870f008f8af7060bd9c | [
"BSD-3-Clause"
] | 154 | 2015-01-01T17:05:59.000Z | 2021-12-09T06:40:07.000Z | """
This is duplicated from Django 3.0 to avoid
starting an import chain that ends up with
ContentTypes which may not be installed in a
Djangae project.
"""
class BaseBackend:
def authenticate(self, request, **kwargs):
return None
@classmethod
def can_authenticate(cls, request):
"""
This is a pre-check to see if the credentials are
available to try to authenticate.
"""
return True
def get_user(self, user_id):
return None
def get_user_permissions(self, user_obj, obj=None):
return set()
def get_group_permissions(self, user_obj, obj=None):
return set()
def get_all_permissions(self, user_obj, obj=None):
return {
*self.get_user_permissions(user_obj, obj=obj),
*self.get_group_permissions(user_obj, obj=obj),
}
def has_perm(self, user_obj, perm, obj=None):
return perm in self.get_all_permissions(user_obj, obj=obj)
| 26.368421 | 66 | 0.636727 | 136 | 1,002 | 4.522059 | 0.433824 | 0.087805 | 0.097561 | 0.107317 | 0.317073 | 0.2 | 0.2 | 0.143089 | 0.143089 | 0.143089 | 0 | 0.002774 | 0.280439 | 1,002 | 37 | 67 | 27.081081 | 0.850208 | 0.231537 | 0 | 0.210526 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.368421 | false | 0 | 0 | 0.315789 | 0.789474 | 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 |
4f9ee549c0660d61b100be39690bb3e9a1b75160 | 2,800 | py | Python | CALCI PROGRAM TKINTER.py | Madmaxcoder2612/Programming-Codes | f70c06ed4a7892ed55673f66c1585370d3f1169f | [
"MIT"
] | null | null | null | CALCI PROGRAM TKINTER.py | Madmaxcoder2612/Programming-Codes | f70c06ed4a7892ed55673f66c1585370d3f1169f | [
"MIT"
] | null | null | null | CALCI PROGRAM TKINTER.py | Madmaxcoder2612/Programming-Codes | f70c06ed4a7892ed55673f66c1585370d3f1169f | [
"MIT"
] | null | null | null | # GUI Development using Tkinter
import tkinter as tk
app = tk.Tk()
app.geometry('340x310')
app.title("Calculator")
entry = tk.Entry(app,text='0',font=('arial',20,'normal'))
entry.place(x=20,y=15)
def number(n):
if n=="C":
entry.delete(0,'end')
elif n=="ans":
k2 = entry.get()
entry.delete(0,'end')
entry.insert('end',eval(k2))
elif n=='del':
entry.delete(len(entry.get())-1)
else:
entry.insert('end',n)
one_button = tk.Button(app,text = "7",font=('arial',10,'bold'),command = lambda:number(7),width = 6).place(x=30,y=70)
one_button = tk.Button(app,text = "8",font=('arial',10,'bold'),command = lambda:number(8),width = 6).place(x=100,y=70)
one_button = tk.Button(app,text = "9",font=('arial',10,'bold'),command = lambda:number(9),width = 6).place(x=170,y=70)
one_button = tk.Button(app,text = "+",font=('arial',10,'bold'),command = lambda:number('+'),width = 6).place(x=250,y=70)
one_button = tk.Button(app,text = "4",font=('arial',10,'bold'),command = lambda:number(4),width = 6).place(x=30,y=120)
one_button = tk.Button(app,text = "5",font=('arial',10,'bold'),command = lambda:number(5),width = 6).place(x=100,y=120)
one_button = tk.Button(app,text = "6",font=('arial',10,'bold'),command = lambda:number(6),width = 6).place(x=170,y=120)
one_button = tk.Button(app,text = "-",font=('arial',10,'bold'),command = lambda:number('-'),width = 6).place(x=250,y=120)
one_button = tk.Button(app,text = "1",font=('arial',10,'bold'),command = lambda:number(1),width = 6).place(x=30,y=170)
one_button = tk.Button(app,text = "2",font=('arial',10,'bold'),command = lambda:number(2),width = 6).place(x=100,y=170)
one_button = tk.Button(app,text = "3",font=('arial',10,'bold'),command = lambda:number(3),width = 6).place(x=170,y=170)
one_button = tk.Button(app,text = "*",font=('arial',10,'bold'),command = lambda:number('*'),width = 6).place(x=250,y=170)
one_button = tk.Button(app,text = "C",font=('arial',10,'bold'),command = lambda:number("C"),width = 6).place(x=30,y=220)
one_button = tk.Button(app,text = "0",font=('arial',10,'bold'),command = lambda:number(0),width = 6).place(x=100,y=220)
one_button = tk.Button(app,text = "=",font=('arial',10,'bold'),command = lambda:number('ans'),width = 6).place(x=170,y=220)
one_button = tk.Button(app,text = "/",font=('arial',10,'bold'),command = lambda:number('/'),width = 6).place(x=250,y=220)
one_button = tk.Button(app,text = ".",font=('arial',10,'bold'),command = lambda:number('.'),width = 6).place(x=30,y=270)
one_button = tk.Button(app,text = "00",font=('arial',10,'bold'),command = lambda:number("00"),width = 6).place(x=100,y=270)
one_button = tk.Button(app,text = "del",font=('arial',10,'bold'),command = lambda:number('del'),width = 6).place(x=170,y=270)
app.mainloop()
| 51.851852 | 126 | 0.639286 | 481 | 2,800 | 3.681913 | 0.135135 | 0.079051 | 0.118012 | 0.182383 | 0.829475 | 0.819311 | 0.687747 | 0.438171 | 0.245624 | 0.245624 | 0 | 0.08134 | 0.104286 | 2,800 | 53 | 127 | 52.830189 | 0.624801 | 0.010357 | 0 | 0.054054 | 0 | 0 | 0.093888 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.027027 | false | 0 | 0.027027 | 0 | 0.054054 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 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 |
4fa7c8aae2cd758336fcea63483f62b6c22958c0 | 135 | py | Python | 0/2/2752/2752.py | chr0m3/boj-codes | d71d0a22d0a3ae62c225f382442461275f56fe8f | [
"MIT"
] | 3 | 2017-07-08T16:29:06.000Z | 2020-07-20T00:17:45.000Z | 0/2/2752/2752.py | chr0m3/boj-codes | d71d0a22d0a3ae62c225f382442461275f56fe8f | [
"MIT"
] | null | null | null | 0/2/2752/2752.py | chr0m3/boj-codes | d71d0a22d0a3ae62c225f382442461275f56fe8f | [
"MIT"
] | 2 | 2017-11-20T14:06:06.000Z | 2020-07-20T00:17:47.000Z | numbers = list(map(int, input().split())).sort()
numbers.sort()
print(str(numbers[0]) + ' ' + str(numbers[1]) + ' ' + str(numbers[2]))
| 33.75 | 70 | 0.592593 | 19 | 135 | 4.210526 | 0.631579 | 0.375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02521 | 0.118519 | 135 | 3 | 71 | 45 | 0.647059 | 0 | 0 | 0 | 0 | 0 | 0.014815 | 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 |
4faa95c6d247e311aedbaf9ff405c3309caa0c17 | 146 | py | Python | glucose_app/glicemy/apps.py | luciano-s/glucose_app | f8b8d97f96bfbc5106fdce0f3de9694486b97f16 | [
"MIT"
] | null | null | null | glucose_app/glicemy/apps.py | luciano-s/glucose_app | f8b8d97f96bfbc5106fdce0f3de9694486b97f16 | [
"MIT"
] | null | null | null | glucose_app/glicemy/apps.py | luciano-s/glucose_app | f8b8d97f96bfbc5106fdce0f3de9694486b97f16 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class GlicemyConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'glicemy'
| 20.857143 | 56 | 0.760274 | 17 | 146 | 6.411765 | 0.882353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.150685 | 146 | 6 | 57 | 24.333333 | 0.879032 | 0 | 0 | 0 | 0 | 0 | 0.246575 | 0.19863 | 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 |
96e90e29c3780580d721f8e007e8c29d7b8c4d6c | 55 | py | Python | apps/sitemap/__init__.py | MySmile/mysmile | 5abe4baa7970674d1f8365d875519283c2e29dae | [
"BSD-3-Clause"
] | 5 | 2015-05-03T09:51:32.000Z | 2019-05-21T14:19:02.000Z | apps/sitemap/__init__.py | MySmile/mysmile | 5abe4baa7970674d1f8365d875519283c2e29dae | [
"BSD-3-Clause"
] | 24 | 2015-04-05T16:28:08.000Z | 2022-03-11T23:36:56.000Z | apps/sitemap/__init__.py | MySmile/mysmile | 5abe4baa7970674d1f8365d875519283c2e29dae | [
"BSD-3-Clause"
] | 1 | 2017-01-23T23:00:11.000Z | 2017-01-23T23:00:11.000Z | default_app_config = 'apps.sitemap.apps.SitemapConfig'
| 27.5 | 54 | 0.836364 | 7 | 55 | 6.285714 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.054545 | 55 | 1 | 55 | 55 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0.563636 | 0.563636 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
96fb71abe1597b3445be3baa69638e7080246d4f | 207 | py | Python | src/Blog/settings/production.py | sadmanbd/wagtailblog | adeccb29826200cb1bedc658a0f1c57c2f705d0e | [
"MIT"
] | 1 | 2020-04-20T05:38:01.000Z | 2020-04-20T05:38:01.000Z | src/Blog/settings/production.py | sadmanbd/wagtailblog | adeccb29826200cb1bedc658a0f1c57c2f705d0e | [
"MIT"
] | 8 | 2020-02-11T21:41:52.000Z | 2022-01-13T00:33:02.000Z | src/Blog/settings/production.py | sadmanbd/wagtailblog | adeccb29826200cb1bedc658a0f1c57c2f705d0e | [
"MIT"
] | null | null | null | from __future__ import absolute_import, unicode_literals
import os
from .base import *
DEBUG = False
SECRET_KEY = os.environ.get("SECRET_KEY")
try:
from .local import *
except ImportError:
pass
| 13.8 | 56 | 0.743961 | 28 | 207 | 5.214286 | 0.678571 | 0.123288 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.183575 | 207 | 14 | 57 | 14.785714 | 0.863905 | 0 | 0 | 0 | 0 | 0 | 0.048309 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.111111 | 0.555556 | 0 | 0.555556 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 3 |
96ff65371ea5fac719ab021f858179bf05875269 | 607 | py | Python | blaze/expr/scalar/interface.py | chdoig/blaze | caa5a497e1ca1ceb1cf585483312ff4cd74d0bda | [
"BSD-3-Clause"
] | 1 | 2015-01-18T23:59:57.000Z | 2015-01-18T23:59:57.000Z | blaze/expr/scalar/interface.py | chdoig/blaze | caa5a497e1ca1ceb1cf585483312ff4cd74d0bda | [
"BSD-3-Clause"
] | null | null | null | blaze/expr/scalar/interface.py | chdoig/blaze | caa5a497e1ca1ceb1cf585483312ff4cd74d0bda | [
"BSD-3-Clause"
] | null | null | null | from __future__ import absolute_import, division, print_function
from ..core import Expr
from datashape import dshape
from .boolean import BooleanInterface
from .numbers import NumberInterface
class ScalarSymbol(NumberInterface, BooleanInterface):
__slots__ = '_name', 'dtype'
def __init__(self, name, dtype='real'):
self._name = name
self.dtype = dshape(dtype)
@property
def name(self):
return self._name
@property
def dshape(self):
return dshape(self.dtype)
def __str__(self):
return str(self._name)
__hash__ = Expr.__hash__
| 21.678571 | 64 | 0.693575 | 69 | 607 | 5.666667 | 0.405797 | 0.081841 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.224053 | 607 | 27 | 65 | 22.481481 | 0.830149 | 0 | 0 | 0.105263 | 0 | 0 | 0.023064 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.210526 | false | 0 | 0.263158 | 0.157895 | 0.789474 | 0.052632 | 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 |
8c11280fc4fa1a1f5cf0b54ef39c72d2dd65d7b4 | 7,824 | py | Python | clearKeys.py | kylephan/Utilities | 21b025a1cf71b4ced95243cc0cf1a8be4d316f5e | [
"MIT"
] | null | null | null | clearKeys.py | kylephan/Utilities | 21b025a1cf71b4ced95243cc0cf1a8be4d316f5e | [
"MIT"
] | null | null | null | clearKeys.py | kylephan/Utilities | 21b025a1cf71b4ced95243cc0cf1a8be4d316f5e | [
"MIT"
] | null | null | null | import maya.cmds as mc
def letsClear(*args):
obj = mc.ls(sl=True)
if all == True:
for o in obj:
clearTX(o)
clearTY(o)
clearTZ(o)
clearRX(o)
clearRY(o)
clearRZ(o)
else:
for o in obj:
clear(o,type)
def allOn(*args):
global all
all = True
mc.optionMenu(opt, e = True, enable = False)
def allOff(*args):
global all
all = False
mc.optionMenu(opt, e = True, enable = True)
def changeAttr(item):
global type
type = ''
if (item == 'Rotate X'):
type = 'rotateX'
if (item == 'Rotate Y'):
type = 'rotateY'
if (item == 'Rotate Z'):
type = 'rotateZ'
if (item == 'Translate X'):
type = 'translateX'
if (item == 'Translate Y'):
type = 'translateY'
if (item == 'Translate Z'):
type = 'translateZ'
def clear(o, type):
count = mc.keyframe(o, query=True,attribute=type, keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute=type)
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = type, valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = type, index = indexRange)
def clearTX(o):
count = mc.keyframe(o, query=True,attribute='translateX', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='translateX')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'translateX', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'translateX', index = indexRange)
def clearTY(o):
count = mc.keyframe(o, query=True,attribute='translateY', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='translateY')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'translateY', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'translateY', index = indexRange)
def clearTZ(o):
count = mc.keyframe(o, query=True,attribute='translateZ', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='translateZ')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'translateZ', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'translateZ', index = indexRange)
def clearRX(o):
count = mc.keyframe(o, query=True,attribute='rotateX', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='rotateX')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'rotateX', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'rotateX', index = indexRange)
def clearRY(o):
count = mc.keyframe(o, query=True,attribute='rotateY', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='rotateY')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'rotateY', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'rotateY', index = indexRange)
def clearRZ(o):
count = mc.keyframe(o, query=True,attribute='rotateZ', keyframeCount = True)
transX = mc.keyframe(o, query=True,attribute='rotateZ')
c = 0
emptyList = []
while c < count:
test = 0
up = c + 1
down = c - 1
value = mc.keyframe(o, query=True,attribute = 'rotateZ', valueChange=True)
if c == 0 or c == (len(value)-1):
test = test + 1
else:
if value[c] == value[up] and value[c] == value[down]:
emptyList.append(c)
c = c + 1
print value
if len(emptyList) != 0:
emptyList.reverse()
indexRange=[(index,) for index in emptyList]
mc.cutKey(o, option = 'keys', attribute = 'rotateZ', index = indexRange)
windowID = 'deleteKeys'
if mc.window( windowID, exists = True):
mc.deleteUI(windowID)
mc.window( windowID, title = 'Delete Key' )
mc.rowColumnLayout(numberOfColumns=3)
opt = mc.optionMenu( changeCommand = changeAttr)
mc.menuItem(label = 'Choose an attribute')
mc.menuItem(label = 'Rotate X')
mc.menuItem(label = 'Rotate Y')
mc.menuItem(label = 'Rotate Z')
mc.menuItem(label = 'Translate X')
mc.menuItem(label = 'Translate Y')
mc.menuItem(label = 'Translate Z')
mc.checkBox(label = 'All Attribute', onCommand = allOn, offCommand = allOff)
mc.button(label = 'Lets clear', command = letsClear)
mc.showWindow()
| 32.330579 | 107 | 0.484279 | 863 | 7,824 | 4.390498 | 0.112399 | 0.055424 | 0.060966 | 0.088678 | 0.716548 | 0.716548 | 0.702824 | 0.650304 | 0.59488 | 0.498812 | 0 | 0.013514 | 0.394683 | 7,824 | 242 | 108 | 32.330579 | 0.786529 | 0 | 0 | 0.585 | 0 | 0 | 0.060522 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.005 | null | null | 0.035 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
8c386151db19fdbccad2e5d5ef88164358f52445 | 181 | py | Python | Chapter 01/Chap01_Example1.92.py | Anancha/Programming-Techniques-using-Python | e80c329d2a27383909d358741a5cab03cb22fd8b | [
"MIT"
] | null | null | null | Chapter 01/Chap01_Example1.92.py | Anancha/Programming-Techniques-using-Python | e80c329d2a27383909d358741a5cab03cb22fd8b | [
"MIT"
] | null | null | null | Chapter 01/Chap01_Example1.92.py | Anancha/Programming-Techniques-using-Python | e80c329d2a27383909d358741a5cab03cb22fd8b | [
"MIT"
] | null | null | null | # reading 2 numbers from the keyboard and printing maximum value
r = int(input("Enter the first number: "))
s = int(input("Enter the second number: "))
x = r if r>s else s
print(x)
| 30.166667 | 64 | 0.701657 | 33 | 181 | 3.848485 | 0.666667 | 0.125984 | 0.204724 | 0.251969 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006757 | 0.18232 | 181 | 5 | 65 | 36.2 | 0.851351 | 0.342541 | 0 | 0 | 0 | 0 | 0.418803 | 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 |
8c3e725f70992e52faf86f3d51a34179d2a39e52 | 853 | py | Python | day3/test_crossed_wires_part2.py | capsulecorplab/adventofcode2019 | a1a27f37dde23662bdca6950680d159a42035c36 | [
"MIT"
] | null | null | null | day3/test_crossed_wires_part2.py | capsulecorplab/adventofcode2019 | a1a27f37dde23662bdca6950680d159a42035c36 | [
"MIT"
] | null | null | null | day3/test_crossed_wires_part2.py | capsulecorplab/adventofcode2019 | a1a27f37dde23662bdca6950680d159a42035c36 | [
"MIT"
] | null | null | null | from crossed_wires import FuelManagementSystem
import pytest
class Test1:
@pytest.fixture
def fms(self):
return FuelManagementSystem("R8,U5,L5,D3", "U7,R6,D4,L4")
def test_steps_combined_min(self, fms):
assert fms.steps_combined_min() == 30
class Test2:
@pytest.fixture
def fms(self):
return FuelManagementSystem(
"R75,D30,R83,U83,L12,D49,R71,U7,L72", "U62,R66,U55,R34,D71,R55,D58,R83"
)
def test_steps_combined_min(self, fms):
assert fms.steps_combined_min() == 610
class Test3:
@pytest.fixture
def fms(self):
return FuelManagementSystem(
"R98,U47,R26,D63,R33,U87,L62,D20,R33,U53,R51",
"U98,R91,D20,R16,D67,R40,U7,R15,U6,R7",
)
def test_steps_combined_min(self, fms):
assert fms.steps_combined_min() == 410
| 24.371429 | 83 | 0.640094 | 119 | 853 | 4.453782 | 0.537815 | 0.14717 | 0.181132 | 0.107547 | 0.588679 | 0.588679 | 0.588679 | 0.311321 | 0.311321 | 0.311321 | 0 | 0.139357 | 0.234467 | 853 | 34 | 84 | 25.088235 | 0.672282 | 0 | 0 | 0.44 | 0 | 0.04 | 0.194607 | 0.168816 | 0 | 0 | 0 | 0 | 0.12 | 1 | 0.24 | false | 0 | 0.08 | 0.12 | 0.56 | 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 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
8c4acb5101a7563401d0c3e1503f91e74c7f281d | 392 | py | Python | server/ffstore/ErrorInfo.py | AsherYang/ThreeLine | 351dc8bfd1c0a536ffbf36ce8b1af953cc71f93a | [
"Apache-2.0"
] | 1 | 2017-05-02T10:02:28.000Z | 2017-05-02T10:02:28.000Z | server/ffstore/ErrorInfo.py | AsherYang/ThreeLine | 351dc8bfd1c0a536ffbf36ce8b1af953cc71f93a | [
"Apache-2.0"
] | null | null | null | server/ffstore/ErrorInfo.py | AsherYang/ThreeLine | 351dc8bfd1c0a536ffbf36ce8b1af953cc71f93a | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python
# -*- coding: utf-8 -*-
class OpenError(StandardError):
def __init__(self, error_code, error, error_info):
self.error_code = error_code
self.error = error
self.error_info = error_info
StandardError.__init__(self, error)
def __str__(self):
return 'Error: %s: %s, request: %s' % (self.error_code, self.error, self.error_info) | 30.153846 | 92 | 0.645408 | 51 | 392 | 4.568627 | 0.372549 | 0.309013 | 0.167382 | 0.154506 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003268 | 0.219388 | 392 | 13 | 92 | 30.153846 | 0.75817 | 0.096939 | 0 | 0 | 0 | 0 | 0.073654 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0.125 | 0.5 | 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 |
8c549c95fea72c967f3e44d56696e639a9c44785 | 12,339 | py | Python | bayesian_deep_learning/libs/distribution_shift_generator.py | mandt-lab/variational-beam-search | 61f217ed6ac6fdda0123f2b3bda37fa42fb4b4c2 | [
"MIT"
] | 1 | 2022-03-16T09:50:10.000Z | 2022-03-16T09:50:10.000Z | bayesian_deep_learning/libs/distribution_shift_generator.py | mandt-lab/variational-beam-search | 61f217ed6ac6fdda0123f2b3bda37fa42fb4b4c2 | [
"MIT"
] | null | null | null | bayesian_deep_learning/libs/distribution_shift_generator.py | mandt-lab/variational-beam-search | 61f217ed6ac6fdda0123f2b3bda37fa42fb4b4c2 | [
"MIT"
] | null | null | null | import struct
import sys
import pickle
import abc
import gzip
from copy import deepcopy
import numpy as np
import cv2
from albumentations import ShiftScaleRotate, ElasticTransform, HorizontalFlip
from albumentations import VerticalFlip, Compose
# if we want to apply deterministic elastic transformations, use the following
# API and set the numpy random number generator
from albumentations.augmentations.functional import elastic_transform
import tensorflow as tf
import random
class LongShiftScaleRotateTransformedGenerator(abc.ABC):
"""Abstract class with sequential transformation declared.
After initiated with specific dataset, it can generates batches of examples
with declared transformations.
"""
@property
@abc.abstractmethod
def X_train(self):
pass
@property
@abc.abstractmethod
def Y_train(self):
pass
@property
@abc.abstractmethod
def X_test(self):
pass
@property
@abc.abstractmethod
def Y_test(self):
pass
@property
@abc.abstractmethod
def out_dim(self):
# Total number of unique classes
pass
def __init__(self, rng=None, changerate=1, max_iter=10, task_size=2048,
validation=False):
self.max_iter = max_iter
self.cur_iter = 0
if rng is None:
rng = np.random.RandomState(1234)
self.rng = rng
self.validation = validation
change_pos = list(range(0, max_iter+1, changerate))
change_pos = change_pos[1:]
# at these indices the dataset will be permuted
self.switch_points = [j for j in change_pos if j <= self.max_iter]
self.tasks_to_test = [0] + self.switch_points
self.examples_per_iter = task_size # 1 # 2048 # 10000 # 2048 # 1024
# for demonstrations
scale_limits, rotate_limits, shift_limits = [], [], []
# First task is without transformations
self.transformers = [None]
for i, _ in enumerate(self.switch_points):
scale_limit = self.rng.normal(0, 0.3)
# rotate_limit = self.rng.uniform(-180, 180) # -180~180
rotate_limit = self.rng.normal(0, 10) # -30~30
shift_limit = self.rng.choice([-1, 1]) * self.rng.beta(1, 10)
scale_limits.append(scale_limit)
rotate_limits.append(rotate_limit)
shift_limits.append(shift_limit)
ssr = ShiftScaleRotate(
shift_limit=(shift_limit, shift_limit),
scale_limit=(scale_limit, scale_limit),
rotate_limit=(rotate_limit, rotate_limit),
border_mode=cv2.BORDER_CONSTANT,
value=0.0,
p=1.0,
)
pipe = ssr
self.transformers.append(pipe)
# First task is (unpermuted) MNIST, subsequent tasks are random
# permutations of pixels
self.perm_indices = [list(range(self.X_train.shape[1]))]
for i, _ in enumerate(self.switch_points):
perm_inds = list(range(self.X_train.shape[1]))
self.rng.shuffle(perm_inds)
self.perm_indices.append(perm_inds)
# make sure they are different permutations
assert(len(set(tuple(perm_inds) for perm_inds in self.perm_indices))
== len(self.perm_indices))
self.idx_map = {}
self.batch_indices = []
last_switch_point = 0
for i, switch_point in enumerate((self.switch_points
+ [self.max_iter])):
batch_inds = list(range(self.X_train.shape[0]))
self.rng.shuffle(batch_inds)
batch_inds = np.tile(batch_inds, 2) # for repetition
for j in range(last_switch_point, switch_point):
self.idx_map[j] = i
# deal with repetition
lbd = (j-last_switch_point)*self.examples_per_iter
ubd = (j-last_switch_point+1)*self.examples_per_iter
redundant_len = ((lbd//self.X_train.shape[0])
* self.X_train.shape[0])
# update lower and upper bound
lbd = lbd - redundant_len
ubd = ubd - redundant_len
self.batch_indices.append(batch_inds[lbd:ubd])
last_switch_point = switch_point
# np.save('./transform_params.npy',
# np.asarray([scale_limits, rotate_limits, shift_limits]))
def get_dims(self):
# Get data input and output dimensions
return self.X_train.shape[1], self.out_dim
def transform(self, transformer, images):
'''
Parameters:
transformer - transformation taken from `albumentations'
images - numpy array of shape (?, height*width) and assume
height==width for MNIST
'''
if transformer is None:
# do not transform
return images
else:
res_images = []
for image in images:
image = transformer(image=image)['image']
res_images.append(image)
return np.asarray(res_images)
def next_task(self):
if self.cur_iter >= self.max_iter:
raise Exception('Number of tasks exceeded!')
else:
transformer = self.transformers[self.idx_map[self.cur_iter]]
batch_inds = self.batch_indices[self.cur_iter]
# Retrieve train data
next_x_train = self.transform(
transformer,
deepcopy(self.X_train[batch_inds, ...])
)
next_y_train = self.Y_train[batch_inds]
# Retrieve test data
next_x_test = self.transform(
transformer,
deepcopy(self.X_test)
)
next_y_test = self.Y_test
if self.validation:
# use first 5000 images as validation set
next_x_test = next_x_test[:5000]
next_y_test = next_y_test[:5000]
print("Use first 5000 test images as validation set.")
else:
next_x_test = next_x_test[5000:]
next_y_test = next_y_test[5000:]
self.cur_iter += 1
return next_x_train, next_y_train, next_x_test, next_y_test
def reset(self):
self.cur_iter = 0
class LongElasticTransformedGenerator(abc.ABC):
"""Abstract class with sequential transformation declared.
After initiated with specific dataset, it can generates batches of examples
with declared transformations.
"""
@property
@abc.abstractmethod
def X_train(self):
pass
@property
@abc.abstractmethod
def Y_train(self):
pass
@property
@abc.abstractmethod
def X_test(self):
pass
@property
@abc.abstractmethod
def Y_test(self):
pass
@property
@abc.abstractmethod
def out_dim(self):
# Total number of unique classes
pass
def __init__(self, rng=None, changerate=1, max_iter=10, task_size=2048):
self.max_iter = max_iter
self.cur_iter = 0
if rng is None:
rng = np.random.RandomState(1234)
self.rng = rng
change_pos = list(range(0, max_iter+1, changerate))
change_pos = change_pos[1:]
# at these indices the dataset will be permuted
self.switch_points = [j for j in change_pos if j <= self.max_iter]
self.tasks_to_test = [0] + self.switch_points
self.examples_per_iter = task_size # 1 # 2048 # 10000 # 2048 # 1024
# First task is without transformations
self.transformer_rng_seeds = [None]
for i, switch_id in enumerate(self.switch_points):
# use the step as seed
self.transformer_rng_seeds.append(switch_id)
np.save('./transform_seeds.npy', self.transformer_rng_seeds)
self.idx_map = {}
self.batch_indices = []
last_switch_point = 0
for i, switch_point in enumerate((self.switch_points
+ [self.max_iter])):
batch_inds = list(range(self.X_train.shape[0]))
self.rng.shuffle(batch_inds)
batch_inds = np.tile(batch_inds, 2) # for repetition
for j in range(last_switch_point, switch_point):
self.idx_map[j] = i
# deal with repetition
lbd = (j-last_switch_point)*self.examples_per_iter
ubd = (j-last_switch_point+1)*self.examples_per_iter
redundant_len = ((lbd//self.X_train.shape[0])
* self.X_train.shape[0])
# update lower and upper bound
lbd = lbd - redundant_len
ubd = ubd - redundant_len
self.batch_indices.append(batch_inds[lbd:ubd])
last_switch_point = switch_point
def get_dims(self):
# Get data input and output dimensions
return self.X_train.shape[1], self.out_dim
def transform(self, rng_seed, images):
'''
Parameters:
rng_seed - seed for numpy.random.RandomState(). It ensures all
images use the same deterministic transformation.
images - numpy array of shape (?, height*width) and assume
height==width for MNIST
'''
if rng_seed is None:
# do not transform
return images
else:
res_images = []
for image in images:
# reset to enable deterministic behaviour
self.rng.seed(rng_seed)
image = elastic_transform(
image,
sigma=4,
alpha=34,
alpha_affine=1,
random_state=self.rng
)
res_images.append(image)
return np.asarray(res_images)
def next_task(self):
if self.cur_iter >= self.max_iter:
raise Exception('Number of tasks exceeded!')
else:
rng_seed = self.transformer_rng_seeds[self.idx_map[self.cur_iter]]
batch_inds = self.batch_indices[self.cur_iter]
# Retrieve train data
next_x_train = self.transform(
rng_seed,
deepcopy(self.X_train[batch_inds, ...])
)
next_y_train = self.Y_train[batch_inds]
# Retrieve test data
next_x_test = self.transform(
rng_seed,
deepcopy(self.X_test)
)
next_y_test = self.Y_test
self.cur_iter += 1
return next_x_train, next_y_train, next_x_test, next_y_test
def reset(self):
self.cur_iter = 0
class LongTransformedCifar10Generator(LongShiftScaleRotateTransformedGenerator):
# load data
(x_train, y_train), (x_test, y_test) = \
tf.keras.datasets.cifar10.load_data()
x_train = x_train.astype('float32')
y_train = np.squeeze(y_train)
x_test = x_test.astype('float32')
y_test = np.squeeze(y_test)
x_train /= 255
x_test /= 255
# Define train and test data
X_train = x_train
Y_train = y_train
X_test = x_test
Y_test = y_test
# Total number of unique classes
out_dim = 10
def __init__(self, rng=None, changerate=1, max_iter=10, task_size=2048,
validation=False):
super().__init__(rng, changerate, max_iter, task_size, validation)
class LongTransformedSvhnGenerator(LongShiftScaleRotateTransformedGenerator):
# load data
(x_train, y_train), (x_test, y_test) = np.load("./dataset/svhn.npy",
allow_pickle=True)
x_train = x_train.astype('float32')
y_train = np.squeeze(y_train)
x_test = x_test.astype('float32')
y_test = np.squeeze(y_test)
x_train /= 255
x_test /= 255
# Define train and test data
X_train = x_train
Y_train = y_train
X_test = x_test
Y_test = y_test
# Total number of unique classes
out_dim = 10
def __init__(self, rng=None, changerate=1, max_iter=10, task_size=2048,
validation=False):
super().__init__(rng, changerate, max_iter, task_size, validation)
| 33.529891 | 80 | 0.591863 | 1,502 | 12,339 | 4.62783 | 0.153795 | 0.025896 | 0.01899 | 0.040282 | 0.740469 | 0.7163 | 0.692131 | 0.673428 | 0.666811 | 0.666811 | 0 | 0.022937 | 0.325148 | 12,339 | 367 | 81 | 33.621253 | 0.811817 | 0.161358 | 0 | 0.701961 | 0 | 0 | 0.016439 | 0.002067 | 0 | 0 | 0 | 0 | 0.003922 | 1 | 0.086275 | false | 0.039216 | 0.05098 | 0.007843 | 0.254902 | 0.003922 | 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 |
4fbf0c0afa244b2e383a987015bb42d2b03c6628 | 1,956 | py | Python | apps/users/views.py | chenyifaerfans/fafaer-apis | 896db11116fc78c597ebc1a90f547dc15004438d | [
"MIT"
] | null | null | null | apps/users/views.py | chenyifaerfans/fafaer-apis | 896db11116fc78c597ebc1a90f547dc15004438d | [
"MIT"
] | null | null | null | apps/users/views.py | chenyifaerfans/fafaer-apis | 896db11116fc78c597ebc1a90f547dc15004438d | [
"MIT"
] | 1 | 2019-03-17T12:46:20.000Z | 2019-03-17T12:46:20.000Z | from django.contrib.auth.backends import ModelBackend
from django.contrib.auth import get_user_model
from django.db.models import Q
from rest_framework import mixins
from rest_framework import viewsets
from rest_framework.permissions import IsAuthenticated
from rest_framework.authentication import SessionAuthentication
from rest_framework_jwt.authentication import JSONWebTokenAuthentication
from common.permissions import IsOwnerOrReadOnly
from .serializers import UserSerializer
User = get_user_model()
class CustomBackend(ModelBackend):
def authenticate(self, request, username=None, password=None, **kwargs):
try:
user = User.objects.get(Q(username=username)|Q(mobile=username))
if user.check_password(password):
return user
except Exception as e:
return None
class UserViewset(mixins.RetrieveModelMixin, viewsets.GenericViewSet):
"""
retrieve:
获取某一个用户信息
"""
queryset = User.objects.filter(is_del=0)
serializer_class = UserSerializer
permission_classes = (IsAuthenticated, IsOwnerOrReadOnly)
authentication_classes = (JSONWebTokenAuthentication, SessionAuthentication)
def page_forbidden(request):
"""
全局403处理函数
:param request:
:return:
"""
from django.shortcuts import render_to_response
response = render_to_response('403.html', {})
response.status_code = 403
return response
def page_not_found(request):
"""
全局404处理函数
:param request:
:return:
"""
from django.shortcuts import render_to_response
response = render_to_response('404.html', {})
response.status_code = 404
return response
def server_error(request):
"""
全局500处理函数
:param request:
:return:
"""
from django.shortcuts import render_to_response
response = render_to_response('500.html', {})
response.status_code = 500
return response | 27.549296 | 80 | 0.716258 | 207 | 1,956 | 6.603865 | 0.386473 | 0.043892 | 0.070227 | 0.048281 | 0.182151 | 0.182151 | 0.182151 | 0.182151 | 0.182151 | 0.182151 | 0 | 0.018053 | 0.207055 | 1,956 | 71 | 81 | 27.549296 | 0.863314 | 0.063395 | 0 | 0.153846 | 0 | 0 | 0.014019 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.102564 | false | 0.051282 | 0.333333 | 0 | 0.717949 | 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 |
4fd1ce32a10f30a9038b645d55203323aae7bf99 | 2,297 | py | Python | fn_mcafee_esm/setup.py | nickpartner-goahead/resilient-community-apps | 097c0dbefddbd221b31149d82af9809420498134 | [
"MIT"
] | 65 | 2017-12-04T13:58:32.000Z | 2022-03-24T18:33:17.000Z | fn_mcafee_esm/setup.py | nickpartner-goahead/resilient-community-apps | 097c0dbefddbd221b31149d82af9809420498134 | [
"MIT"
] | 48 | 2018-03-02T19:17:14.000Z | 2022-03-09T22:00:38.000Z | fn_mcafee_esm/setup.py | nickpartner-goahead/resilient-community-apps | 097c0dbefddbd221b31149d82af9809420498134 | [
"MIT"
] | 95 | 2018-01-11T16:23:39.000Z | 2022-03-21T11:34:29.000Z | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# (c) Copyright IBM Corp. 2010, 2018. All Rights Reserved.
from setuptools import setup, find_packages
setup(
name='fn_mcafee_esm',
version='1.0.2',
license='MIT',
author='IBM Resilient',
author_email='support@resilientsystems.com',
description="Resilient Circuits Components for 'fn_mcafee_esm'",
long_description="""The McAfee ESM integration with the Resilient platform allows for the escalation and enrichment
of cases between McAfee and the Resilient platform. The integration includes a poller and 6 functions. The
returned results can be used to make customized updates to the Resilient platform, such as updating incidents,
data tables and so on. The integration can also be used to make updates to McAfee ESM cases.""",
install_requires=[
'resilient_circuits>=30.0.0',
'resilient-lib'
],
packages=find_packages(),
include_package_data=True,
platforms='any',
classifiers=[
'Programming Language :: Python',
],
entry_points={
"resilient.circuits.components": [
"McafeeEsmGetCaseDetailFunctionComponent = fn_mcafee_esm.components.mcafee_esm_get_case_detail:FunctionComponent",
"McafeeEsmGetListOfCasesFunctionComponent = fn_mcafee_esm.components.mcafee_esm_get_list_of_cases:FunctionComponent",
"McafeeEsmGetCaseEvenstsDetailFunctionComponent = fn_mcafee_esm.components.mcafee_esm_get_case_events_detail:FunctionComponent",
"McafeeEsmEditCaseFunctionComponent = fn_mcafee_esm.components.mcafee_esm_edit_case:FunctionComponent",
"McafeeEsmGetTriggeredAlarms = fn_mcafee_esm.components.mcafee_esm_get_triggered_alarms:FunctionComponent",
"McafeeEsmQueryLogs = fn_mcafee_esm.components.mcafee_esm_query:FunctionComponent",
"McafeeEsmCasePolling = fn_mcafee_esm.components.mcafee_esm_case_polling:ESM_CasePolling"
],
"resilient.circuits.configsection": ["gen_config = fn_mcafee_esm.util.config:config_section_data"],
"resilient.circuits.customize": ["customize = fn_mcafee_esm.util.customize:customization_data"],
"resilient.circuits.selftest": ["selftest = fn_mcafee_esm.util.selftest:selftest_function"]
}
) | 54.690476 | 140 | 0.742273 | 255 | 2,297 | 6.431373 | 0.466667 | 0.115244 | 0.080488 | 0.089634 | 0.140244 | 0.140244 | 0.085366 | 0.045122 | 0 | 0 | 0 | 0.008919 | 0.170222 | 2,297 | 42 | 141 | 54.690476 | 0.851522 | 0.0431 | 0 | 0.081081 | 0 | 0 | 0.739982 | 0.441257 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.027027 | 0 | 0.027027 | 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 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
4ffa72e790a3d4b20f49619940efed81b8845cf5 | 1,659 | py | Python | src/utils/url_parsers.py | googleinterns/connectivity-test | 789183797c831f683064e10d19132a183286dd05 | [
"Apache-2.0"
] | null | null | null | src/utils/url_parsers.py | googleinterns/connectivity-test | 789183797c831f683064e10d19132a183286dd05 | [
"Apache-2.0"
] | null | null | null | src/utils/url_parsers.py | googleinterns/connectivity-test | 789183797c831f683064e10d19132a183286dd05 | [
"Apache-2.0"
] | null | null | null | # Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
def GetSegmentOfUrl(url: str, prefix: str) -> str:
"""
Get the next segment from url following prefix. The return value is a segment without slash.
For example, url = "projects/test-project/global/networks/n1",
and prefix = "networks/", then the return value is "n1".
"""
if not url: return ""
if not prefix: return ""
if not prefix.endswith("/"): prefix += "/"
offset = url.find(prefix)
if offset == -1: return ""
offset += len(prefix)
end = url.find("/", offset)
if end == -1: end = len(url)
return url[offset:end]
def ParseProjectFromUrl(url: str) -> str:
return GetSegmentOfUrl(url, "projects/")
def ParseNetworkFromUrl(url: str) -> str:
return GetSegmentOfUrl(url, "/networks/")
def ParseRegionFromUrl(url: str) -> str:
return GetSegmentOfUrl(url, "/regions/")
def ParseSubnetFromUrl(url: str) -> str:
return GetSegmentOfUrl(url, "/subnetworks/")
def ParseInstanceFromUrl(url: str) -> str:
return GetSegmentOfUrl(url, "/instances/")
| 30.163636 | 97 | 0.667872 | 214 | 1,659 | 5.17757 | 0.462617 | 0.054152 | 0.040614 | 0.06769 | 0.148917 | 0.148917 | 0 | 0 | 0 | 0 | 0 | 0.009281 | 0.220615 | 1,659 | 54 | 98 | 30.722222 | 0.847641 | 0.459916 | 0 | 0 | 0 | 0 | 0.068238 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.3 | false | 0 | 0 | 0.25 | 0.6 | 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 |
4ffae6ac0dd7d09c0ccad1471a8a046844a4cefd | 1,325 | py | Python | python/dlbs/exceptions.py | robertengelmann/dlcookbook-dlbs | c871372a8cb869f5f33b79d1211d8583707434e2 | [
"Apache-2.0"
] | 1 | 2021-03-19T06:51:11.000Z | 2021-03-19T06:51:11.000Z | python/dlbs/exceptions.py | robertengelmann/dlcookbook-dlbs | c871372a8cb869f5f33b79d1211d8583707434e2 | [
"Apache-2.0"
] | null | null | null | python/dlbs/exceptions.py | robertengelmann/dlcookbook-dlbs | c871372a8cb869f5f33b79d1211d8583707434e2 | [
"Apache-2.0"
] | null | null | null | # (c) Copyright [2017] Hewlett Packard Enterprise Development LP
#
# 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.
""" Module implements exception classes that can be thrown by the DLBS."""
class DLBSError(Exception):
"""Base class for all exceptions."""
pass
class ConfigurationError(DLBSError):
"""This exception is thrown whenever error is found in an input configuration.
Several examples of situations in which this exception gets thrown:
- Cyclic dependency is found during variable expansion.
- Variable cannot be expanded.
- Un-parsable JSON value found in an input configuration.
"""
pass
class LogicError(DLBSError):
"""This exception indicates a bug in a program.
This exception in theory must never be thrown unless there is a bug in the
program.
"""
pass
| 34.868421 | 82 | 0.738113 | 188 | 1,325 | 5.202128 | 0.595745 | 0.06135 | 0.026585 | 0.03272 | 0.055215 | 0 | 0 | 0 | 0 | 0 | 0 | 0.007512 | 0.196226 | 1,325 | 37 | 83 | 35.810811 | 0.910798 | 0.833208 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
8b364fcc96d5ff47ae2f83f96ec7196a4d269a7f | 657 | py | Python | test_credentials.py | kuya-ui/Password-Locker | 17d281d878d2de31d33eba1c17657e18820ac36b | [
"MIT"
] | null | null | null | test_credentials.py | kuya-ui/Password-Locker | 17d281d878d2de31d33eba1c17657e18820ac36b | [
"MIT"
] | null | null | null | test_credentials.py | kuya-ui/Password-Locker | 17d281d878d2de31d33eba1c17657e18820ac36b | [
"MIT"
] | null | null | null | import unittest
from credentials import Credential
class TestCredential(unittest.TestCase):
"""
Test class that defines test cases for the credential class behaviours,
the arguments help in creating test cases.
"""
def setUp(self):
"""
this method runs before each test case, carries the instructions of what is to be done
"""
self.new_password = Credential("max")
def test_init(self):
"""
used to test if the objects have been initialized properly
"""
self.assertEqual(self.new_password.credential_detail,"max")
if __name__ == '__main__':
unittest.main() | 22.655172 | 94 | 0.657534 | 79 | 657 | 5.316456 | 0.64557 | 0.071429 | 0.071429 | 0.119048 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.261796 | 657 | 29 | 95 | 22.655172 | 0.865979 | 0.395738 | 0 | 0 | 0 | 0 | 0.042169 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 1 | 0.222222 | false | 0.222222 | 0.222222 | 0 | 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 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
8b4494f9af64d71ff00c8c9896f66e6b5599aac3 | 296 | py | Python | dht22_sensor.py | mikrogravitation/humiditemp5000 | 7e5e837b18142333c90eab82a5b46d702654a436 | [
"MIT"
] | null | null | null | dht22_sensor.py | mikrogravitation/humiditemp5000 | 7e5e837b18142333c90eab82a5b46d702654a436 | [
"MIT"
] | null | null | null | dht22_sensor.py | mikrogravitation/humiditemp5000 | 7e5e837b18142333c90eab82a5b46d702654a436 | [
"MIT"
] | null | null | null | import dht
class DHT22Sensor:
provides = ["temperature", "humidity"]
def __init__(self, port):
self._sensor = dht.DHT22(port)
def readout(self):
self._sensor.measure()
return {"temperature": self._sensor.temperature(), "humidity": self._sensor.humidity()}
| 22.769231 | 95 | 0.648649 | 31 | 296 | 5.935484 | 0.516129 | 0.217391 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017094 | 0.209459 | 296 | 12 | 96 | 24.666667 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0.128378 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.125 | 0 | 0.75 | 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 | 0 | 1 | 0 | 0 | 3 |
8c6cfc38e57f86eab7797d375f99dd296d63319a | 1,276 | py | Python | wrappers/SpellbookWrapper.py | WouterGlorieux/BitcoinSpellbook-v0.2 | 93b5480f87f4dc41c2d71093aa98d1fbdd83625c | [
"MIT"
] | null | null | null | wrappers/SpellbookWrapper.py | WouterGlorieux/BitcoinSpellbook-v0.2 | 93b5480f87f4dc41c2d71093aa98d1fbdd83625c | [
"MIT"
] | null | null | null | wrappers/SpellbookWrapper.py | WouterGlorieux/BitcoinSpellbook-v0.2 | 93b5480f87f4dc41c2d71093aa98d1fbdd83625c | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from BlockDataWrapper import BlockDataWrapper
from BlockInputsWrapper import BlockInputsWrapper
from BlockLinkerWrapper import BlockLinkerWrapper
from BlockRandomWrapper import BlockRandomWrapper
from BlockVoterWrapper import BlockVoterWrapper
from BlockForwardWrapper import BlockForwardWrapper
from BlockDistributeWrapper import BlockDistributeWrapper
from BlockTriggerWrapper import BlockTriggerWrapper
from BlockWriterWrapper import BlockWriterWrapper
class SpellbookWrapper():
def __init__(self, url='http://bitcoinspellbook.appspot.com'):
self.url = url
def blockdata(self):
return BlockDataWrapper(self.url)
def blockinputs(self):
return BlockInputsWrapper(self.url)
def blocklinker(self):
return BlockLinkerWrapper(self.url)
def blockrandom(self):
return BlockRandomWrapper(self.url)
def blockvoter(self):
return BlockVoterWrapper(self.url)
def blockforward(self):
return BlockForwardWrapper(self.url)
def blockdistribute(self):
return BlockDistributeWrapper(self.url)
def blocktrigger(self):
return BlockTriggerWrapper(self.url)
def blockwriter(self):
return BlockWriterWrapper(self.url) | 27.73913 | 66 | 0.760972 | 119 | 1,276 | 8.12605 | 0.319328 | 0.079628 | 0.08273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000947 | 0.172414 | 1,276 | 46 | 67 | 27.73913 | 0.914773 | 0.032915 | 0 | 0 | 0 | 0 | 0.028386 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.3 | 0.3 | 0.966667 | 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 |
8c733c8dc3e476d059bcd63aa89a02b021245600 | 107 | py | Python | frameioclient/config.py | Frameio/python-frameio-client | 005020fd369245627e376fb8a5eaa3064a33438e | [
"MIT"
] | 33 | 2018-07-29T14:04:54.000Z | 2022-03-18T16:22:10.000Z | frameioclient/config.py | Frameio/python-frameio-client | 005020fd369245627e376fb8a5eaa3064a33438e | [
"MIT"
] | 31 | 2019-07-23T16:11:45.000Z | 2021-08-03T01:32:41.000Z | frameioclient/config.py | Frameio/python-frameio-client | 005020fd369245627e376fb8a5eaa3064a33438e | [
"MIT"
] | 16 | 2018-10-04T10:53:20.000Z | 2022-03-04T09:11:15.000Z | class Config:
api_host = "https://api.frame.io"
default_page_size = 50
default_concurrency = 5
| 21.4 | 37 | 0.682243 | 15 | 107 | 4.6 | 0.866667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.035714 | 0.214953 | 107 | 4 | 38 | 26.75 | 0.785714 | 0 | 0 | 0 | 0 | 0 | 0.186916 | 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 |
8c73ebefbe371ef44942ff7124e0d58fc2510cfb | 13,342 | py | Python | source/rttov_test/profile-datasets-py/div83/073.py | bucricket/projectMAScorrection | 89489026c8e247ec7c364e537798e766331fe569 | [
"BSD-3-Clause"
] | null | null | null | source/rttov_test/profile-datasets-py/div83/073.py | bucricket/projectMAScorrection | 89489026c8e247ec7c364e537798e766331fe569 | [
"BSD-3-Clause"
] | 1 | 2022-03-12T12:19:59.000Z | 2022-03-12T12:19:59.000Z | source/rttov_test/profile-datasets-py/div83/073.py | bucricket/projectMAScorrection | 89489026c8e247ec7c364e537798e766331fe569 | [
"BSD-3-Clause"
] | null | null | null | """
Profile ../profile-datasets-py/div83/073.py
file automaticaly created by prof_gen.py script
"""
self["ID"] = "../profile-datasets-py/div83/073.py"
self["Q"] = numpy.array([ 1.956946, 2.801132, 4.230252, 5.419981, 6.087733,
6.419039, 6.547807, 6.548787, 6.504738, 6.432189,
6.370779, 6.31601 , 6.30854 , 6.30967 , 6.3021 ,
6.284641, 6.249721, 6.198102, 6.145852, 6.099373,
6.058663, 5.986194, 5.884295, 5.747187, 5.574639,
5.373091, 5.135734, 4.845567, 4.50543 , 4.128883,
3.740616, 3.373579, 3.08385 , 2.839622, 2.645253,
2.513544, 2.431584, 2.357084, 2.259045, 2.163875,
2.110346, 2.096796, 2.099166, 2.141685, 2.178575,
2.199215, 2.274125, 2.462204, 2.771892, 3.16592 ,
3.663737, 4.257632, 4.884156, 6.018014, 7.350006,
8.070105, 8.34401 , 8.37078 , 8.312201, 8.323041,
8.553217, 9.130147, 10.2062 , 11.93486 , 14.44259 ,
17.91218 , 22.60939 , 28.81827 , 34.92618 , 38.93378 ,
56.09235 , 71.77225 , 85.79204 , 102.7434 , 118.9449 ,
125.5382 , 132.4874 , 122.411 , 122.1301 , 128.6215 ,
118.193 , 100.195 , 96.30662 , 102.0976 , 123.4148 ,
225.838 , 205.4768 , 199.0024 , 192.8198 , 186.9111 ,
181.2631 , 175.8601 , 170.6889 , 165.7365 , 160.9931 ,
156.4465 , 152.0869 , 147.9041 , 143.8903 , 140.0354 ,
136.3324 ])
self["P"] = numpy.array([ 5.00000000e-03, 1.61000000e-02, 3.84000000e-02,
7.69000000e-02, 1.37000000e-01, 2.24400000e-01,
3.45400000e-01, 5.06400000e-01, 7.14000000e-01,
9.75300000e-01, 1.29720000e+00, 1.68720000e+00,
2.15260000e+00, 2.70090000e+00, 3.33980000e+00,
4.07700000e+00, 4.92040000e+00, 5.87760000e+00,
6.95670000e+00, 8.16550000e+00, 9.51190000e+00,
1.10038000e+01, 1.26492000e+01, 1.44559000e+01,
1.64318000e+01, 1.85847000e+01, 2.09224000e+01,
2.34526000e+01, 2.61829000e+01, 2.91210000e+01,
3.22744000e+01, 3.56505000e+01, 3.92566000e+01,
4.31001000e+01, 4.71882000e+01, 5.15278000e+01,
5.61260000e+01, 6.09895000e+01, 6.61253000e+01,
7.15398000e+01, 7.72396000e+01, 8.32310000e+01,
8.95204000e+01, 9.61138000e+01, 1.03017000e+02,
1.10237000e+02, 1.17778000e+02, 1.25646000e+02,
1.33846000e+02, 1.42385000e+02, 1.51266000e+02,
1.60496000e+02, 1.70078000e+02, 1.80018000e+02,
1.90320000e+02, 2.00989000e+02, 2.12028000e+02,
2.23442000e+02, 2.35234000e+02, 2.47408000e+02,
2.59969000e+02, 2.72919000e+02, 2.86262000e+02,
3.00000000e+02, 3.14137000e+02, 3.28675000e+02,
3.43618000e+02, 3.58966000e+02, 3.74724000e+02,
3.90893000e+02, 4.07474000e+02, 4.24470000e+02,
4.41882000e+02, 4.59712000e+02, 4.77961000e+02,
4.96630000e+02, 5.15720000e+02, 5.35232000e+02,
5.55167000e+02, 5.75525000e+02, 5.96306000e+02,
6.17511000e+02, 6.39140000e+02, 6.61192000e+02,
6.83667000e+02, 7.06565000e+02, 7.29886000e+02,
7.53628000e+02, 7.77790000e+02, 8.02371000e+02,
8.27371000e+02, 8.52788000e+02, 8.78620000e+02,
9.04866000e+02, 9.31524000e+02, 9.58591000e+02,
9.86067000e+02, 1.01395000e+03, 1.04223000e+03,
1.07092000e+03, 1.10000000e+03])
self["CO2"] = numpy.array([ 373.9833, 373.985 , 373.9884, 373.995 , 374.0057, 374.0216,
374.0366, 374.0466, 374.0776, 374.1326, 374.2046, 374.2866,
374.3886, 374.5236, 374.6526, 374.7416, 374.8237, 374.8957,
374.9497, 374.9817, 374.9777, 374.8958, 374.7168, 374.3068,
373.8689, 373.399 , 373.1931, 373.0142, 372.9923, 372.9705,
372.9696, 372.9687, 372.9958, 373.0249, 373.093 , 373.1831,
373.3081, 373.5051, 373.7122, 374.0992, 374.5252, 375.0212,
375.5992, 376.2002, 376.6862, 377.1942, 377.6051, 377.9581,
378.329 , 378.7248, 379.1366, 379.5774, 380.0341, 380.4167,
380.7802, 381.0429, 381.2468, 381.3648, 381.4278, 381.4508,
381.4547, 381.4305, 381.3971, 381.3314, 381.2585, 381.1682,
381.0824, 381.001 , 380.9507, 380.9132, 380.8856, 380.8667,
380.8483, 380.8259, 380.7977, 380.7672, 380.7296, 380.6944,
380.6635, 380.66 , 380.705 , 380.7848, 380.8093, 380.8081,
380.801 , 380.763 , 380.7717, 380.7742, 380.7766, 380.7788,
380.781 , 380.783 , 380.785 , 380.7869, 380.7887, 380.7904,
380.7921, 380.7937, 380.7952, 380.7967, 380.7981])
self["CO"] = numpy.array([ 3.371623 , 3.275051 , 3.089317 , 2.793105 , 2.386455 ,
1.898358 , 1.286632 , 0.6786696 , 0.2446264 , 0.1117883 ,
0.07406993, 0.06797857, 0.06665738, 0.06541499, 0.0627382 ,
0.05708244, 0.05198118, 0.0482764 , 0.04517182, 0.04224734,
0.04012826, 0.03841507, 0.03688128, 0.0355552 , 0.035034 ,
0.03503531, 0.03689901, 0.03936141, 0.0440788 , 0.0492937 ,
0.04925202, 0.04920743, 0.04473116, 0.04025199, 0.0366714 ,
0.03351052, 0.03137962, 0.03123803, 0.03108933, 0.03244993,
0.03412033, 0.03639812, 0.03949292, 0.04300421, 0.0464721 ,
0.05039819, 0.05490918, 0.06008545, 0.06627392, 0.07433206,
0.08375509, 0.0936498 , 0.1051005 , 0.1153623 , 0.1259091 ,
0.1348409 , 0.1428668 , 0.1493407 , 0.1547317 , 0.1586747 ,
0.1618646 , 0.1637585 , 0.1653183 , 0.165877 , 0.1662896 ,
0.166244 , 0.1661372 , 0.1659742 , 0.1657402 , 0.1654906 ,
0.1652257 , 0.1649732 , 0.1647089 , 0.1644201 , 0.1640755 ,
0.1636954 , 0.1632974 , 0.1629001 , 0.1624932 , 0.1620122 ,
0.1613979 , 0.1608719 , 0.1609615 , 0.1616045 , 0.162019 ,
0.1622284 , 0.1622896 , 0.1621097 , 0.1619268 , 0.1617408 ,
0.1615517 , 0.1613596 , 0.1611645 , 0.1609663 , 0.1607661 ,
0.1605619 , 0.1603556 , 0.1601463 , 0.159934 , 0.1597186 ,
0.1595013 ])
self["T"] = numpy.array([ 182.651, 193.018, 211.533, 232.314, 250.519, 264.537,
275.437, 284.487, 292.885, 299.567, 304.326, 304.11 ,
298.775, 290.318, 281.349, 274.469, 269.03 , 262.729,
255.232, 247.095, 239.554, 233.573, 228.85 , 225.016,
221.726, 218.548, 214.604, 211.054, 207.796, 204.77 ,
202.096, 200.364, 198.049, 195.456, 192.937, 190.933,
189.903, 190.14 , 191.564, 193.628, 195.422, 195.904,
194.759, 193.011, 191.99 , 192.292, 193.427, 194.638,
195.439, 196.086, 196.942, 197.885, 198.685, 199.239,
199.659, 200.124, 200.563, 200.928, 201.22 , 201.562,
202.071, 202.831, 203.902, 205.287, 206.924, 208.756,
210.742, 212.832, 214.977, 217.117, 219.157, 221.102,
223.008, 224.906, 226.796, 228.809, 230.866, 232.815,
234.6 , 236.299, 237.853, 239.205, 240.549, 241.851,
242.628, 240.741, 240.155, 240.155, 240.155, 240.155,
240.155, 240.155, 240.155, 240.155, 240.155, 240.155,
240.155, 240.155, 240.155, 240.155, 240.155])
self["N2O"] = numpy.array([ 1.07999800e-03, 8.19997700e-04, 6.29997300e-04,
4.79997400e-04, 3.49997900e-04, 2.49998400e-04,
2.49998400e-04, 4.39997100e-04, 1.14999300e-03,
1.39999100e-03, 3.20998000e-03, 5.38996600e-03,
7.70995100e-03, 9.55994000e-03, 1.17199300e-02,
1.49099100e-02, 1.73398900e-02, 1.84498900e-02,
1.95798800e-02, 2.11198700e-02, 2.25798600e-02,
2.06298800e-02, 1.70899000e-02, 1.36999200e-02,
1.13299400e-02, 9.15995100e-03, 7.07996400e-03,
6.14997000e-03, 5.60997500e-03, 5.08997900e-03,
5.26998000e-03, 8.14997300e-03, 1.09399700e-02,
1.36499600e-02, 1.70299500e-02, 2.36499400e-02,
3.00799300e-02, 3.63299100e-02, 6.36398600e-02,
9.82897900e-02, 1.31219700e-01, 1.68939600e-01,
2.03099600e-01, 2.35689500e-01, 2.62639400e-01,
2.85029400e-01, 3.02059300e-01, 3.12939200e-01,
3.16769100e-01, 3.16769000e-01, 3.16768800e-01,
3.16768700e-01, 3.16768500e-01, 3.16768100e-01,
3.16767700e-01, 3.16767400e-01, 3.16767400e-01,
3.16767300e-01, 3.16767400e-01, 3.16767400e-01,
3.16767300e-01, 3.16767100e-01, 3.16766800e-01,
3.16766200e-01, 3.16765400e-01, 3.16764300e-01,
3.16762800e-01, 3.16760900e-01, 3.16758900e-01,
3.16757700e-01, 3.16752200e-01, 3.16747300e-01,
3.16742800e-01, 3.16737500e-01, 3.16732300e-01,
3.16730200e-01, 3.16728000e-01, 3.16731200e-01,
3.16731300e-01, 3.16729300e-01, 3.16732600e-01,
3.16738300e-01, 3.16739500e-01, 3.16737700e-01,
3.16730900e-01, 3.16698500e-01, 3.16704900e-01,
3.16707000e-01, 3.16708900e-01, 3.16710800e-01,
3.16712600e-01, 3.16714300e-01, 3.16715900e-01,
3.16717500e-01, 3.16719000e-01, 3.16720400e-01,
3.16721800e-01, 3.16723100e-01, 3.16724400e-01,
3.16725600e-01, 3.16726800e-01])
self["O3"] = numpy.array([ 1.092958 , 0.9333394 , 0.7369399 , 0.7964717 , 0.9379673 ,
1.079703 , 1.237282 , 1.401171 , 1.54559 , 1.718999 ,
1.962487 , 2.289906 , 2.740603 , 3.343639 , 4.033965 ,
4.681221 , 5.141878 , 5.436586 , 5.582286 , 5.602026 ,
5.534786 , 5.136629 , 4.572073 , 3.916747 , 3.242732 ,
2.627226 , 2.238409 , 1.97481 , 1.707352 , 1.378664 ,
0.9718754 , 0.4739234 , 0.1691735 , 0.07579148, 0.06013094,
0.06060745, 0.06021215, 0.05955906, 0.06177556, 0.07662733,
0.1108608 , 0.1167128 , 0.07390804, 0.05683548, 0.05512018,
0.06082157, 0.08559211, 0.1410637 , 0.2397043 , 0.2934931 ,
0.3111259 , 0.3108367 , 0.2986955 , 0.2690934 , 0.2461522 ,
0.2268442 , 0.1992463 , 0.1731716 , 0.1505927 , 0.124096 ,
0.09637658, 0.07470752, 0.06088038, 0.05258867, 0.04738112,
0.04395351, 0.04182795, 0.04072743, 0.04045889, 0.0410274 ,
0.0409915 , 0.03975355, 0.03971269, 0.04038045, 0.04089773,
0.04011796, 0.03950926, 0.0416304 , 0.04225274, 0.03989827,
0.03871712, 0.03680791, 0.03578315, 0.03928659, 0.04175655,
0.04199231, 0.0311443 , 0.0311445 , 0.03114469, 0.03114488,
0.03114505, 0.03114522, 0.03114538, 0.03114554, 0.03114568,
0.03114583, 0.03114596, 0.03114609, 0.03114622, 0.03114634,
0.03114645])
self["CH4"] = numpy.array([ 0.0996805, 0.1110867, 0.1195645, 0.1268483, 0.1474111,
0.1701019, 0.1716519, 0.1735449, 0.1782488, 0.1907058,
0.2214456, 0.2588824, 0.2996521, 0.3522618, 0.4052884,
0.4652571, 0.5254507, 0.5900453, 0.652122 , 0.7166726,
0.7781653, 0.834089 , 0.8861858, 0.9360986, 0.9791765,
1.019945 , 1.059185 , 1.097075 , 1.133645 , 1.169365 ,
1.207695 , 1.248736 , 1.292576 , 1.332766 , 1.371486 ,
1.408036 , 1.441656 , 1.471497 , 1.485487 , 1.500237 ,
1.515757 , 1.532077 , 1.549197 , 1.566077 , 1.580627 ,
1.595846 , 1.611256 , 1.627016 , 1.642985 , 1.658145 ,
1.673924 , 1.688113 , 1.702712 , 1.71622 , 1.729587 ,
1.739776 , 1.747785 , 1.752725 , 1.755075 , 1.756095 ,
1.756145 , 1.755794 , 1.755242 , 1.754189 , 1.753005 ,
1.751649 , 1.75037 , 1.74924 , 1.748419 , 1.747772 ,
1.747412 , 1.747125 , 1.74691 , 1.746811 , 1.746822 ,
1.746941 , 1.747158 , 1.747506 , 1.747867 , 1.748135 ,
1.748353 , 1.748495 , 1.748612 , 1.748701 , 1.748684 ,
1.748515 , 1.748561 , 1.748572 , 1.748593 , 1.748603 ,
1.748613 , 1.748622 , 1.748631 , 1.74864 , 1.748648 ,
1.748656 , 1.748664 , 1.748671 , 1.748678 , 1.748685 ,
1.748692 ])
self["CTP"] = 500.0
self["CFRACTION"] = 0.0
self["IDG"] = 0
self["ISH"] = 0
self["ELEVATION"] = 0.0
self["S2M"]["T"] = 240.155
self["S2M"]["Q"] = 136.332410939
self["S2M"]["O"] = 0.03114645315
self["S2M"]["P"] = 717.06042
self["S2M"]["U"] = 0.0
self["S2M"]["V"] = 0.0
self["S2M"]["WFETC"] = 100000.0
self["SKIN"]["SURFTYPE"] = 0
self["SKIN"]["WATERTYPE"] = 1
self["SKIN"]["T"] = 240.155
self["SKIN"]["SALINITY"] = 35.0
self["SKIN"]["FOAM_FRACTION"] = 0.0
self["SKIN"]["FASTEM"] = numpy.array([ 3. , 5. , 15. , 0.1, 0.3])
self["ZENANGLE"] = 0.0
self["AZANGLE"] = 0.0
self["SUNZENANGLE"] = 0.0
self["SUNAZANGLE"] = 0.0
self["LATITUDE"] = -74.316
self["GAS_UNITS"] = 2
self["BE"] = 0.0
self["COSBK"] = 0.0
self["DATE"] = numpy.array([2006, 10, 20])
self["TIME"] = numpy.array([0, 0, 0])
| 57.508621 | 92 | 0.559886 | 2,008 | 13,342 | 3.718626 | 0.473606 | 0.023704 | 0.016874 | 0.022499 | 0.029329 | 0.029329 | 0.022097 | 0.022097 | 0.022097 | 0.022097 | 0 | 0.697228 | 0.278144 | 13,342 | 231 | 93 | 57.757576 | 0.078081 | 0.00712 | 0 | 0 | 0 | 0 | 0.018819 | 0.002645 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
8c74049dd346defb252e9addc649cada9bb156ac | 1,058 | py | Python | talosblockchain/talosdht/test/protocol_test.py | chunchuan-wang/droplet-engine | 5c2dbac90aa3bde837ed4989ecd78235e5d9ef8e | [
"Apache-2.0"
] | 10 | 2020-10-14T14:22:20.000Z | 2022-03-16T11:33:14.000Z | talosblockchain/talosdht/test/protocol_test.py | chunchuan-wang/droplet-engine | 5c2dbac90aa3bde837ed4989ecd78235e5d9ef8e | [
"Apache-2.0"
] | null | null | null | talosblockchain/talosdht/test/protocol_test.py | chunchuan-wang/droplet-engine | 5c2dbac90aa3bde837ed4989ecd78235e5d9ef8e | [
"Apache-2.0"
] | 4 | 2020-08-30T12:40:40.000Z | 2021-08-03T15:27:12.000Z | #© 2017-2020, ETH Zurich, D-INFK, lubu@inf.ethz.ch
import random
import unittest
from kademlia.node import Node
from kademlia.utils import digest
from talosdht.protocolsecurity import generate_secret_key
from talosdht.talosprotocol import TalosSKademliaProtocol
from talosvc.talosclient.restapiclient import TalosVCRestClient
class DummyProt(TalosSKademliaProtocol):
def callPing(self, nodeToAsk):
print "Ping %s" % nodeToAsk
class TestBuckets(unittest.TestCase):
def test_bucket_basic(self):
ecd_key = generate_secret_key()
sourceNode = Node(digest(random.getrandbits(255)), ip="127.0.0.1", port=12345)
dummy_protocol = DummyProt(ecd_key, sourceNode, None, 4, talos_vc=None)
nodes = []
for i in range(1000):
nodes.append(Node(digest(random.getrandbits(255)), ip="127.0.0.1", port=i+10000))
for i in range(1000):
dummy_protocol.router.addContact(nodes[i])
for i in range(1000):
self.assertFalse(dummy_protocol.router.isNewNode(nodes[i]))
| 29.388889 | 93 | 0.708885 | 137 | 1,058 | 5.394161 | 0.525547 | 0.052774 | 0.024357 | 0.044655 | 0.17456 | 0.113667 | 0.113667 | 0.113667 | 0.113667 | 0.113667 | 0 | 0.057043 | 0.188091 | 1,058 | 35 | 94 | 30.228571 | 0.802095 | 0.046314 | 0 | 0.136364 | 1 | 0 | 0.024851 | 0 | 0 | 0 | 0 | 0 | 0.045455 | 0 | null | null | 0 | 0.318182 | null | null | 0.045455 | 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 | 1 | 0 | 0 | 0 | 0 | 3 |
8c7dbd2d6be5f59ac7452dec291f7f34b860f29f | 596 | py | Python | cuisine/interface/recipe_io.py | j3kstrum/recipe-tweaker | 941d2fed87fc2c568b29d3b3baee3f8ebfe4daca | [
"MIT"
] | null | null | null | cuisine/interface/recipe_io.py | j3kstrum/recipe-tweaker | 941d2fed87fc2c568b29d3b3baee3f8ebfe4daca | [
"MIT"
] | null | null | null | cuisine/interface/recipe_io.py | j3kstrum/recipe-tweaker | 941d2fed87fc2c568b29d3b3baee3f8ebfe4daca | [
"MIT"
] | null | null | null | from data.recipe import Recipe
from data import RecipeGroup
from typing import List
class RecipeIO:
"""
Controls saving and loading of recipes from the filesystem.
"""
@staticmethod
def save(recipe: Recipe) -> bool:
raise NotImplementedError()
@staticmethod
def save_completed(recipe: Recipe) -> bool:
raise NotImplementedError()
@staticmethod
def load(recipe_name: str) -> List[Recipe]:
raise NotImplementedError()
@staticmethod
def place_tombstone(recipe_group: RecipeGroup) -> bool:
raise NotImplementedError()
| 22.923077 | 63 | 0.687919 | 61 | 596 | 6.655738 | 0.491803 | 0.147783 | 0.206897 | 0.288177 | 0.270936 | 0.270936 | 0.270936 | 0 | 0 | 0 | 0 | 0 | 0.233221 | 596 | 25 | 64 | 23.84 | 0.888403 | 0.098993 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.1875 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
8c9c1a5711b123bddf619f7dedc40d8269640efe | 714 | py | Python | DataStructures/BinarySerachTree_def/Program.py | luiscarm9/Data-Structures-in-Python | e7eb7e7ece8f3223b8017d25acc76bea3e93e3f6 | [
"MIT"
] | null | null | null | DataStructures/BinarySerachTree_def/Program.py | luiscarm9/Data-Structures-in-Python | e7eb7e7ece8f3223b8017d25acc76bea3e93e3f6 | [
"MIT"
] | null | null | null | DataStructures/BinarySerachTree_def/Program.py | luiscarm9/Data-Structures-in-Python | e7eb7e7ece8f3223b8017d25acc76bea3e93e3f6 | [
"MIT"
] | null | null | null | from BinarySerachTree_def.BinaryTree import BinaryTreeS
binarytree=BinaryTreeS()
#create a binary tree with fibonnaci
binarytree.insert(0)
binarytree.insert(1)
binarytree.insert(1)
binarytree.insert(2)
binarytree.insert(3)
binarytree.insert(5)
binarytree.insert(8)
binarytree.insert(13)
binarytree.getTraverseInOrder()
print('------------------------------')
#Remove the last element
binarytree.remove(13)
binarytree.getTraverseInOrder()
print('------------------------------')
#Remove the first element different of zero
binarytree.remove(1)
binarytree.getTraverseInOrder()
print('------------------------------')
print 'Max Value:'
print binarytree.getMax()
print 'Min Value:'
print binarytree.getMin() | 22.3125 | 55 | 0.696078 | 76 | 714 | 6.526316 | 0.460526 | 0.258065 | 0.199597 | 0.108871 | 0.278226 | 0.177419 | 0 | 0 | 0 | 0 | 0 | 0.018265 | 0.079832 | 714 | 32 | 56 | 22.3125 | 0.736682 | 0.141457 | 0 | 0.363636 | 0 | 0 | 0.180033 | 0.1473 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.045455 | null | null | 0.318182 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
508e3fc0c39607a000fe637e25c5db2d8a7dc060 | 275 | py | Python | clothstream/styletags/urls.py | julienaubert/clothstream | daa76389be8b359208e88cd1f7aa8e7e98766656 | [
"MIT"
] | null | null | null | clothstream/styletags/urls.py | julienaubert/clothstream | daa76389be8b359208e88cd1f7aa8e7e98766656 | [
"MIT"
] | null | null | null | clothstream/styletags/urls.py | julienaubert/clothstream | daa76389be8b359208e88cd1f7aa8e7e98766656 | [
"MIT"
] | null | null | null | from clothstream.lib.rest import SharedAPIRootRouter
from .views import ItemStyleTagCreate, StyleTagList
router = SharedAPIRootRouter()
router.register(r'styletag-item/create', ItemStyleTagCreate, base_name='itemstyletag-create')
router.register(r'styletags', StyleTagList)
| 39.285714 | 93 | 0.84 | 29 | 275 | 7.931034 | 0.655172 | 0.121739 | 0.130435 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.065455 | 275 | 6 | 94 | 45.833333 | 0.894942 | 0 | 0 | 0 | 0 | 0 | 0.174545 | 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 |
50a51e2bd1f9dab244096057e39978a0aa037170 | 1,741 | py | Python | pymilldb/context/Column.py | Toka-Taka/mill-db | 1edf390f2ce89d9232ba91d722cb4b104c398078 | [
"MIT"
] | 2 | 2019-11-05T06:24:59.000Z | 2020-03-06T09:04:38.000Z | pymilldb/context/Column.py | bmstu-iu9/mill-db | a3725b11fcd995953dabc21f7fe6f4d5f5d38815 | [
"MIT"
] | 2 | 2019-05-22T09:40:51.000Z | 2020-03-03T12:17:12.000Z | pymilldb/context/Column.py | Toka-Taka/mill-db | 1edf390f2ce89d9232ba91d722cb4b104c398078 | [
"MIT"
] | 6 | 2018-05-03T16:04:13.000Z | 2019-12-01T11:01:07.000Z | from .DataType import BaseType
class Column(object):
COLUMN_COMMON = 0
COLUMN_BLOOM = 1
COLUMN_INDEXED = 2
COLUMN_PRIMARY = 3
DEFAULT_FAIL_SHARE = 0.2
__NAME_TO_MOD = dict(
bloom=1,
indexed=2,
pk=3,
)
def __init__(self, name: str, kind: BaseType, mod: int, table=None, fail_share=None):
self.name = name
self.kind = kind
self.mod = mod
self.table = table
self.fail_share = self.DEFAULT_FAIL_SHARE if fail_share is None else fail_share
@classmethod
def auto(cls, name: str, kind: BaseType, mod: str, table=None, fail_share=None):
return Column(name, kind, cls.__NAME_TO_MOD[mod.lower()], table, fail_share)
@classmethod
def common(cls, name: str, kind: BaseType, table=None, fail_share=None):
return Column(name, kind, cls.COLUMN_COMMON, table, fail_share)
@property
def is_common(self):
return self.mod == self.COLUMN_COMMON
@classmethod
def bloom(cls, name: str, kind: BaseType, table=None, fail_share=None):
return Column(name, kind, cls.COLUMN_BLOOM, table, fail_share)
@property
def is_bloom(self):
return self.mod == self.COLUMN_BLOOM
@classmethod
def indexed(cls, name: str, kind: BaseType, table=None, fail_share=None):
return Column(name, kind, cls.COLUMN_INDEXED, table, fail_share)
@property
def is_indexed(self):
return self.mod == self.COLUMN_INDEXED
@classmethod
def primary(cls, name: str, kind: BaseType, table=None, fail_share=None):
return Column(name, kind, cls.COLUMN_PRIMARY, table, fail_share)
@property
def is_primary(self):
return self.mod == self.COLUMN_PRIMARY
| 28.540984 | 89 | 0.657668 | 239 | 1,741 | 4.598326 | 0.167364 | 0.131028 | 0.060055 | 0.103731 | 0.565969 | 0.503185 | 0.306642 | 0.306642 | 0.306642 | 0.306642 | 0 | 0.006808 | 0.240666 | 1,741 | 60 | 90 | 29.016667 | 0.824508 | 0 | 0 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.022222 | 0.2 | 0.6 | 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 |
50a67e7e71443f0123964ab785888984cda3fc3b | 404 | py | Python | skdecide/hub/domain/gym/__init__.py | jeromerobert/scikit-decide | 900916e627669fb3f7520edb2aaef55e08064b25 | [
"MIT"
] | null | null | null | skdecide/hub/domain/gym/__init__.py | jeromerobert/scikit-decide | 900916e627669fb3f7520edb2aaef55e08064b25 | [
"MIT"
] | null | null | null | skdecide/hub/domain/gym/__init__.py | jeromerobert/scikit-decide | 900916e627669fb3f7520edb2aaef55e08064b25 | [
"MIT"
] | 1 | 2021-02-26T17:31:51.000Z | 2021-02-26T17:31:51.000Z | # Copyright (c) AIRBUS and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .gym import GymDomain, DeterministicInitializedGymDomain, GymWidthDomain, \
GymDiscreteActionDomain, DeterministicGymDomain, CostDeterministicGymDomain, \
GymPlanningDomain, GymDomainStateProxy, GymDomainHashable, AsGymEnv
| 50.5 | 82 | 0.816832 | 41 | 404 | 8.04878 | 0.853659 | 0.060606 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.136139 | 404 | 7 | 83 | 57.714286 | 0.945559 | 0.39604 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
50b799f3f9190f81ef4e7396819f3c43e59e132b | 106 | py | Python | categorias/iniciante/python/1095.py | carlos3g/URI-solutions | dc7f9b896cdff88aedf67611917b178d3ad60ab3 | [
"MIT"
] | 1 | 2022-01-26T23:38:17.000Z | 2022-01-26T23:38:17.000Z | categorias/iniciante/python/1095.py | carlos3g/URI-solutions | dc7f9b896cdff88aedf67611917b178d3ad60ab3 | [
"MIT"
] | 1 | 2020-07-12T00:49:35.000Z | 2021-06-26T20:53:18.000Z | categorias/iniciante/python/1095.py | carlos3g/URI-solutions | dc7f9b896cdff88aedf67611917b178d3ad60ab3 | [
"MIT"
] | 1 | 2020-07-04T03:27:04.000Z | 2020-07-04T03:27:04.000Z | # -*- coding: utf-8 -*-
i = 1
for x in range(60, -1, -5):
print('I={} J={}'.format(i, x))
i += 3
| 15.142857 | 35 | 0.415094 | 20 | 106 | 2.2 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 0.273585 | 106 | 6 | 36 | 17.666667 | 0.480519 | 0.198113 | 0 | 0 | 0 | 0 | 0.108434 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
50c582358879f0d88ea08b7b116c6d9019fa47eb | 850 | py | Python | Database/SQLIte/15.Limit/U1.py | sarincr/Business-analytics-Course-with-Python- | 10e577fdb3cf90bb87c97cd23ee3ecd6a083bfc4 | [
"MIT"
] | 3 | 2022-01-18T05:35:52.000Z | 2022-03-25T06:13:54.000Z | Database/SQLIte/15.Limit/U1.py | sarincr/Business-analytics-Course-with-Python- | 10e577fdb3cf90bb87c97cd23ee3ecd6a083bfc4 | [
"MIT"
] | null | null | null | Database/SQLIte/15.Limit/U1.py | sarincr/Business-analytics-Course-with-Python- | 10e577fdb3cf90bb87c97cd23ee3ecd6a083bfc4 | [
"MIT"
] | 2 | 2022-01-17T08:23:59.000Z | 2022-01-17T08:28:18.000Z | import sqlite3
X = sqlite3.connect('NeDB.db')
Y = X.cursor()
Y.execute('''CREATE TABLE IF NOT EXISTS EMPLOYEE (
ID integer,
Name text NOT NULL,
Date_Join text,
Place text,
Age integer,
Salary real);''')
Y.execute('''INSERT INTO Employee VALUES (1,'John','2020-03-01','Kerala',32,25000),(2,'Adam','2020-01-01','TN',22,30000),(3,'Mary','2022-01-01','Karnataka',24,120000)
,(4,'Jacob','2022-01-01','Mharashtra',24,430000),(5,'Johny','2022-01-01','Karnataka',24,34000),(6,'Lynda','2022-01-01','Delhi',24,56700),
(7,'Smith','2022-01-01','Kerala',24,234000),(8,'Gem','2022-01-01','Karnataka',24,120000)''')
data = Y.execute("SELECT * from Employee LIMIT 2 OFFSET 4");
for k in data:
print (k)
X.commit()
Y.close()
| 27.419355 | 167 | 0.556471 | 123 | 850 | 3.837398 | 0.609756 | 0.059322 | 0.101695 | 0.108051 | 0.146186 | 0.105932 | 0 | 0 | 0 | 0 | 0 | 0.207951 | 0.230588 | 850 | 30 | 168 | 28.333333 | 0.513761 | 0 | 0 | 0 | 0 | 0.166667 | 0.77561 | 0.426829 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.055556 | 0 | 0.055556 | 0.055556 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
50c7a3be78d0fd416ee2c6259ac08e9ae566c6ec | 47 | py | Python | week1/8.py | kamorozov/coursera_python | 706bc1bc46839f8b3debdf293240ad5ce20c9775 | [
"Unlicense"
] | 2 | 2019-05-17T13:42:02.000Z | 2019-05-18T04:00:35.000Z | week1/8.py | kamorozov/coursera_python | 706bc1bc46839f8b3debdf293240ad5ce20c9775 | [
"Unlicense"
] | null | null | null | week1/8.py | kamorozov/coursera_python | 706bc1bc46839f8b3debdf293240ad5ce20c9775 | [
"Unlicense"
] | 2 | 2019-10-03T09:07:44.000Z | 2019-12-28T19:17:20.000Z | n = int(input())
n = n % 100
print(n // 10)
| 11.75 | 17 | 0.468085 | 9 | 47 | 2.444444 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.151515 | 0.297872 | 47 | 3 | 18 | 15.666667 | 0.515152 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.333333 | 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 |
50d316e96203c330defac6b5f9275d3b8cbbe62b | 220 | py | Python | tempgui.py | mustafaIhssan/semantic-segmentation-maker | 83ac9af29fccdba83e463762116e22445938987b | [
"MIT"
] | 1 | 2016-12-29T07:59:10.000Z | 2016-12-29T07:59:10.000Z | tempgui.py | mustafaIhssan/semantic-segmentation-maker | 83ac9af29fccdba83e463762116e22445938987b | [
"MIT"
] | null | null | null | tempgui.py | mustafaIhssan/semantic-segmentation-maker | 83ac9af29fccdba83e463762116e22445938987b | [
"MIT"
] | null | null | null | import Tkinter
parent_widget = Tkinter.Tk()
scale_widget = Tkinter.Scale(parent_widget, from_=0, to=100,
orient=Tkinter.HORIZONTAL)
scale_widget.set(25)
scale_widget.pack()
Tkinter.mainloop() | 31.428571 | 60 | 0.7 | 28 | 220 | 5.285714 | 0.571429 | 0.222973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.033708 | 0.190909 | 220 | 7 | 61 | 31.428571 | 0.797753 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.142857 | 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 |
50d99798c529ede9378d5878470651f778e5c271 | 2,078 | py | Python | lista_ex3.1.py/exercicio23.py | robinson-1985/mentoria_exercises | 8359cead6ee5351851b04cb45f252e3881b79117 | [
"MIT"
] | null | null | null | lista_ex3.1.py/exercicio23.py | robinson-1985/mentoria_exercises | 8359cead6ee5351851b04cb45f252e3881b79117 | [
"MIT"
] | null | null | null | lista_ex3.1.py/exercicio23.py | robinson-1985/mentoria_exercises | 8359cead6ee5351851b04cb45f252e3881b79117 | [
"MIT"
] | null | null | null | ''' 23. Faça um programa que receba o valor do salário mínimo, o turno de trabalho (M
— matutino; V — vespertino; ou N — noturno), a categoria (O — operário; G —
gerente) e o número de horas trabalhadas no mês de um funcionário. Suponha a
digitação apenas de dados válidos e, quando houver digitação de letras, utilize
maiúsculas. Calcule e mostre:
■ O coeficiente do salário, de acordo com a tabela a seguir.
Turno de trabalho Valor do coeficiente
M - matutino 10% do salário mínimo
V - Vespertino 15% do salário mínimo
N - Noturno 12% do salário mínimo
■ O valor do salário bruto, ou seja, o número de horas trabalhadas multiplicado pelo
valor do coeficiente do salário.
■ O imposto, de acordo com a tabela a seguir.
Categoria Salário Bruto Imposto sobre o salário bruto
O - Operário >= R$ 300,00 5%
O - Operário < R$ 300,00 3%
G - Gerente >= R$ 400,00 6%
G - Gerente < R$ 400,00 4%
■ A gratificação, de acordo com as regras a seguir.
Se o funcionário preencher todos os requisitos a seguir, sua gratificação será de
R$ 50,00; caso contrário, será de R$ 30,00. Os requisitos são:
Turno: Noturno
Número de horas trabalhadas: Superior a 80 horas
■ O auxílio alimentação, de acordo com as seguintes regras.
Se o funcionário preencher algum dos requisitos a seguir, seu auxílio alimentação será
de um terço do seu salário bruto; caso contrário, será de metade do seu salário bruto.
Os requisitos são:
Categoria: Operário
Coeficiente do salário: < = 25
■ O salário líquido, ou seja, salário bruto menos imposto mais gratificação mais auxílio
alimentação.
■ A classificação, de acordo com a tabela a seguir:
Salário líquido Mensagem
Menor que R$ 350,00 Mal remunerado
Entre R$ 350,00 e R$ 600,00 Normal
Maior que R$ 600,00 Bem remunerado ''' | 50.682927 | 88 | 0.63667 | 305 | 2,078 | 4.377049 | 0.357377 | 0.053933 | 0.041199 | 0.053933 | 0.137079 | 0.05618 | 0.05618 | 0 | 0 | 0 | 0 | 0.044818 | 0.312801 | 2,078 | 41 | 89 | 50.682927 | 0.881653 | 0.994706 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0.02439 | 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 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
50f3732d55416656d33c30e2933737275d61bab9 | 297 | py | Python | pygamerogue/utils.py | mikolasan/pyroguelike | d51b01a566b5edb39792b59d683b4bf827399ba4 | [
"BSD-3-Clause"
] | null | null | null | pygamerogue/utils.py | mikolasan/pyroguelike | d51b01a566b5edb39792b59d683b4bf827399ba4 | [
"BSD-3-Clause"
] | 2 | 2020-06-17T05:23:02.000Z | 2020-06-17T05:29:41.000Z | pygamerogue/utils.py | mikolasan/pyroguelike | d51b01a566b5edb39792b59d683b4bf827399ba4 | [
"BSD-3-Clause"
] | 1 | 2020-09-26T17:16:59.000Z | 2020-09-26T17:16:59.000Z | def shift_rect(rect, direction, distance=48):
if direction == 'left':
rect.left -= distance
elif direction == 'right':
rect.left += distance
elif direction == 'up':
rect.top -= distance
elif direction == 'down':
rect.top += distance
return rect
| 27 | 45 | 0.582492 | 33 | 297 | 5.212121 | 0.424242 | 0.209302 | 0.366279 | 0.232558 | 0.337209 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009479 | 0.289562 | 297 | 10 | 46 | 29.7 | 0.805687 | 0 | 0 | 0 | 0 | 0 | 0.050505 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0 | 0 | 0.2 | 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 |
50fef9dc7c37378c2b89f5d5abd92f9996a28c56 | 162 | py | Python | covidapp/urls.py | babbarutkarsh/CovidTracker | 6bb1bcdf5b0e11208e8b0494028082ed32ff4573 | [
"MIT"
] | 1 | 2021-04-23T05:11:07.000Z | 2021-04-23T05:11:07.000Z | covidapp/urls.py | babbarutkarsh/CovidTracker | 6bb1bcdf5b0e11208e8b0494028082ed32ff4573 | [
"MIT"
] | null | null | null | covidapp/urls.py | babbarutkarsh/CovidTracker | 6bb1bcdf5b0e11208e8b0494028082ed32ff4573 | [
"MIT"
] | null | null | null | from django.contrib import admin
from django.urls import path,include
from .views import helloworldview
urlpatterns = [
path('helloworld/',helloworldview)
]
| 20.25 | 38 | 0.783951 | 19 | 162 | 6.684211 | 0.631579 | 0.15748 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135802 | 162 | 7 | 39 | 23.142857 | 0.907143 | 0 | 0 | 0 | 0 | 0 | 0.067901 | 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 |
0f9b32f06196acf472b687c9df115a7c46e39e8e | 8,170 | py | Python | pytesla/vehicle.py | jstenback/pytesla | 25707fd59bc3ba67f6db8d2a43fbaa7cb238f4e7 | [
"BSD-3-Clause"
] | null | null | null | pytesla/vehicle.py | jstenback/pytesla | 25707fd59bc3ba67f6db8d2a43fbaa7cb238f4e7 | [
"BSD-3-Clause"
] | null | null | null | pytesla/vehicle.py | jstenback/pytesla | 25707fd59bc3ba67f6db8d2a43fbaa7cb238f4e7 | [
"BSD-3-Clause"
] | 3 | 2016-12-06T14:04:34.000Z | 2020-01-10T22:03:03.000Z | from . import stream
class CommandError(Exception):
"""Tesla Model S vehicle command returned failure"""
pass
class Vehicle:
def __init__(self, vin, conn, payload, log):
assert payload['vin'] == vin
self._conn = conn
self._data = payload
self._log = log
def __repr__(self):
return "<Vehicle {}>".format(self.vin)
# Helpers
@property
def vin(self):
return self._data['vin']
@property
def id(self):
return self._data['id']
@property
def vehicle_id(self):
return self._data['vehicle_id']
@property
def state(self):
return self._data['state']
@property
def email(self):
return self._conn._email
@property
def auth_token(self):
return self._conn._auth_token
@property
def stream_auth_token(self):
return self._data['tokens'][0]
# Stream entry generator for events defined in StreamEvents
# (events should be an array of StreamEvents). This generator
# generates tuples of an array of the requested events (preceded
# by a timestamp) and a reference to the stream itself (which can
# be closed to stop receiving events). This generator will
# generate count number of events, or as many as it gets if count
# is 0.
def stream(self, events, count = 0):
return stream.Stream(self).read_stream(events, count)
def refresh(self):
self._conn.vehicles(True)
def request(self, verb):
return self._conn.request('/api/1/vehicles/{}/data_request/{}' \
.format(self.id, verb)).json()['response']
def command(self, verb, **kwargs):
p = self._conn.request('/api/1/vehicles/{}/command/{}' \
.format(self.id, verb), kwargs).json()
args = []
for a in kwargs:
args.append("{} = {}".format(a, kwargs[a]))
self._log.write("{}({}) called. Result was {}" \
.format(verb, ", ".join(args), p))
if 'response' not in p or not p['response']:
# Command returned failure, raise exception
raise CommandError(p['error'])
return p['response']
# API getter properties
@property
def mobile_enabled(self):
return self._conn.request('/api/1/vehicles/{}/mobile_enabled' \
.format(self.id)).json()['response']
@property
def data(self):
return self._conn.request('/api/1/vehicles/{}/data' \
.format(self.id)).json() #['response']
@property
def charge_state(self):
return self.request('charge_state')
@property
def climate_state(self):
return self.request('climate_state')
@property
def drive_state(self):
return self.request('drive_state')
@property
def gui_settings(self):
return self.request('gui_settings')
@property
def vehicle_state(self):
return self.request('vehicle_state')
# API commands
def charge_port_door_open(self):
return self.command('charge_port_door_open')
def charge_port_door_close(self):
return self.command('charge_port_door_close')
def charge_standard(self):
return self.command('charge_standard')
def charge_max_range(self):
return self.command('charge_max_range')
def charge_start(self):
return self.command('charge_start')
def charge_stop(self):
return self.command('charge_stop')
@property
def charge_limit(self):
return self.charge_state['charge_limit_soc']
@charge_limit.setter
def charge_limit(self, limit):
self.command('set_charge_limit', percent = limit)
def flash_lights(self):
return self.command('flash_lights')
def honk_horn(self):
return self.command('honk_horn')
def remote_start_drive(self, password):
return self.command('remote_start_drive', password = password)
@property
def speed_limit(self):
return self.vehicle_state['speed_limit_mode']
@speed_limit.setter
def speed_limit(self, limit):
return self.command('speed_limit_set_limit', limit_mph = limit)
def activate_speed_limit(self, pin):
return self.command('speed_limit_activate', pin = pin)
def deactivate_speed_limit(self, pin):
return self.command('speed_limit_deactivate', pin = pin)
def clear_speed_limit_pin(self, pin):
return self.command('speed_limit_clear_pin', pin = pin)
def valet_mode(self, on, pin):
return self.command('set_valet_mode', on = on, pin = pin)
def reset_valet_pin(self):
return self.command('reset_valet_pin')
def sentry_mode(self, on):
return self.command('set_sentry_mode', on = on)
@property
def locked(self):
return self.vehicle_state['locked']
@locked.setter
def locked(self, lock):
if lock:
return self.command('door_lock')
else:
return self.command('door_unlock')
def actuate_trunk(self):
return self.command('actuate_trunk', which_trunk = 'rear')
def actuate_frunk(self):
return self.command('actuate_trunk', which_trunk = 'front')
def sun_roof_control(self, state, percent = None):
args = {'state': state}
if state == 'move' and percent != None:
args['percent'] = percent
if state not in ('open', 'close', 'move', 'comfort', 'vent'):
raise ValueError("Invalid sunroof state")
return self.command('sun_roof_control', **args)
def set_temps(self, driver, passenger):
return self.command('set_temps', driver_temp = driver,
passenger_temp = passenger)
def remote_seat_heater(self, heater, level):
if heater not in range(0, 6):
raise ValueError("Invalid seat heater: {}".format(heater))
if level not in range(0, 4):
raise ValueError("Invalid seat heater level: {}".format(level))
return self.command('remote_seat_heater_request', heater = heater,
level = level)
def remote_steering_wheel_heater(self, on):
return self.command('remote_steering_wheel_heater_request', on = on)
def auto_conditioning_start(self):
return self.command('auto_conditioning_start')
def auto_conditioning_stop(self):
return self.command('auto_conditioning_stop')
def media_toggle_playback(self):
return self.command('media_toggle_playback')
def media_next_track(self):
return self.command('media_next_track')
def media_prev_track(self):
return self.command('media_prev_track')
def media_next_fav(self):
return self.command('media_next_fav')
def media_prev_fav(self):
return self.command('media_prev_fav')
def media_volume_up(self):
return self.command('media_volume_up')
def media_volume_down(self):
return self.command('media_volume_down')
def navigation_request(self, where):
return self.command('navigation_request',
type = 'share_ext_content_raw',
locale = 'en-US',
value = {
'android.intent.extra.TEXT': where
},
timestamp_ms = str(int(time.time())))
def schedule_software_update(self, offset_sec):
return self.command('schedule_software_update',
offset_sec = offset_sec)
def cancel_software_update(self_sec):
return self.command('cancel_software_update')
def wake_up(self):
d = self._conn.request('/api/1/vehicles/{}/wake_up' \
.format(self.id), {}).json()['response']
# Update vehicle tokens if they're different from our cached
# ones.
tokens = d['tokens']
if tokens != self._data['tokens']:
self._data['tokens'] = tokens
self._conn.save_state()
return d
| 29.709091 | 76 | 0.611506 | 980 | 8,170 | 4.885714 | 0.218367 | 0.112782 | 0.108187 | 0.087719 | 0.281119 | 0.165205 | 0.0967 | 0.060359 | 0.018379 | 0 | 0 | 0.002028 | 0.275643 | 8,170 | 274 | 77 | 29.817518 | 0.807029 | 0.071114 | 0 | 0.091398 | 0 | 0 | 0.158653 | 0.062351 | 0 | 0 | 0 | 0 | 0.005376 | 1 | 0.322581 | false | 0.026882 | 0.005376 | 0.27957 | 0.650538 | 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 |
0f9c5dc61dc683dbb784a1fe62685ebcd6df0bc2 | 232 | py | Python | Mundo-1-Fundamentos/016.py | TOPTOPUNIVERSE/CEV-PYTHON3 | 07e2c6b41cd33f3555e14545cdf6fc37325c8fd1 | [
"MIT"
] | null | null | null | Mundo-1-Fundamentos/016.py | TOPTOPUNIVERSE/CEV-PYTHON3 | 07e2c6b41cd33f3555e14545cdf6fc37325c8fd1 | [
"MIT"
] | null | null | null | Mundo-1-Fundamentos/016.py | TOPTOPUNIVERSE/CEV-PYTHON3 | 07e2c6b41cd33f3555e14545cdf6fc37325c8fd1 | [
"MIT"
] | null | null | null | """
Desafio 016
Problema: Crie um programa que leia um número Real qualquer
pelo teclado e mostre na tela a sua porção Inteira."""
n = float(input('Digite um valor:'))
print(f'O número {n} tem a parte inteira {int(n)}')
| 25.777778 | 64 | 0.681034 | 39 | 232 | 4.051282 | 0.820513 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016304 | 0.206897 | 232 | 8 | 65 | 29 | 0.842391 | 0.573276 | 0 | 0 | 0 | 0 | 0.619565 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
0fa16ef2816f764151079f54a639f1a1c4d2374a | 262 | py | Python | piecrust/wsgiutil/__init__.py | airbornemint/PieCrust2 | bd8e44a1a3ba646a9ebfbb4d4f1fa01a1daa3beb | [
"Apache-2.0"
] | null | null | null | piecrust/wsgiutil/__init__.py | airbornemint/PieCrust2 | bd8e44a1a3ba646a9ebfbb4d4f1fa01a1daa3beb | [
"Apache-2.0"
] | null | null | null | piecrust/wsgiutil/__init__.py | airbornemint/PieCrust2 | bd8e44a1a3ba646a9ebfbb4d4f1fa01a1daa3beb | [
"Apache-2.0"
] | null | null | null | from piecrust.serving.server import WsgiServer
def get_app(root_dir, cache_key='prod', enable_debug_info=False):
app = WsgiServer(root_dir,
cache_key=cache_key,
enable_debug_info=enable_debug_info)
return app
| 26.2 | 65 | 0.671756 | 34 | 262 | 4.823529 | 0.558824 | 0.146341 | 0.27439 | 0.182927 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.259542 | 262 | 9 | 66 | 29.111111 | 0.845361 | 0 | 0 | 0 | 0 | 0 | 0.015326 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.166667 | 0 | 0.5 | 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 |
0fc80bccdde996736cc835d370d64e069c7c8b30 | 1,787 | py | Python | pip_services3_container/build/DefaultContainerFactory.py | banalna/pip-services3-container-python | d26aee1f49840eb0dac4ccb290b4808550494354 | [
"MIT"
] | null | null | null | pip_services3_container/build/DefaultContainerFactory.py | banalna/pip-services3-container-python | d26aee1f49840eb0dac4ccb290b4808550494354 | [
"MIT"
] | null | null | null | pip_services3_container/build/DefaultContainerFactory.py | banalna/pip-services3-container-python | d26aee1f49840eb0dac4ccb290b4808550494354 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
pip_services3_container.build.DefaultContainerFactory
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Default container factory implementation
:copyright: Conceptual Vision Consulting LLC 2018-2019, see AUTHORS for more details.
:license: MIT, see LICENSE for more details.
"""
from pip_services3_commons.refer import Descriptor
from pip_services3_components.build import CompositeFactory
from pip_services3_components.log import DefaultLoggerFactory
from pip_services3_components.count import DefaultCountersFactory
from pip_services3_components.config import DefaultConfigReaderFactory
from pip_services3_components.cache import DefaultCacheFactory
from pip_services3_components.auth import DefaultCredentialStoreFactory
from pip_services3_components.connect import DefaultDiscoveryFactory
from pip_services3_components.info._DefaultInfoFactory import DefaultInfoFactory
class DefaultContainerFactory(CompositeFactory):
"""
Creates default container components (loggers, counters, caches, locks, etc.) by their descriptors.
"""
DefaultContainerFactoryDescriptor = Descriptor(
"pip-services", "factory", "container", "default", "1.0"
)
def __init__(self, *factories):
"""
Create a new instance of the factory and sets nested factories.
:param factories: a list of nested factories
"""
super(DefaultContainerFactory, self).__init__(factories)
self.add(DefaultInfoFactory())
self.add(DefaultLoggerFactory())
self.add(DefaultCountersFactory())
self.add(DefaultConfigReaderFactory())
self.add(DefaultCacheFactory())
self.add(DefaultCredentialStoreFactory())
self.add(DefaultDiscoveryFactory())
| 39.711111 | 103 | 0.739228 | 167 | 1,787 | 7.736527 | 0.461078 | 0.092879 | 0.111455 | 0.160991 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.014 | 0.160604 | 1,787 | 44 | 104 | 40.613636 | 0.847333 | 0.287073 | 0 | 0 | 0 | 0 | 0.031906 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.045455 | false | 0 | 0.409091 | 0 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
0fce4b175efd342362c8eca2117758091061c40c | 1,533 | py | Python | Client/message/friend.py | Ricky-Hao/IMPK-Client | 791150a43fff157aa439716d63d6c4fece912b85 | [
"MIT"
] | null | null | null | Client/message/friend.py | Ricky-Hao/IMPK-Client | 791150a43fff157aa439716d63d6c4fece912b85 | [
"MIT"
] | 1 | 2018-06-01T07:45:03.000Z | 2018-06-01T07:45:03.000Z | Server/message/friend.py | Ricky-Hao/IMPK-Server | 786e24269e7cc506a82ae8aa0fa0d1df8c478f51 | [
"MIT"
] | null | null | null | from .base import BaseMessage
class FriendMessage(BaseMessage):
def __init__(self, data=None):
super().__init__(data)
def _init_type(self):
self.type = 'FriendMessage'
def _parse_dict(self, data):
super()._parse_dict(data)
self.friend_list = data.get('friend_list')
def to_dict(self):
data = super().to_dict()
data['friend_list'] = self.friend_list
return data
class FriendRequestMessage(BaseMessage):
def __init__(self, data=None):
super().__init__(data)
def _init_type(self):
self.type = 'FriendRequestMessage'
def _parse_dict(self, data):
super()._parse_dict(data)
self.friend_name = data.get('friend_name')
def to_dict(self):
data = super().to_dict()
data['friend_name'] = self.friend_name
return data
class FriendAcceptMessage(BaseMessage):
def __init__(self, data=None):
super().__init__(data)
def _init_type(self):
self.type = 'FriendAcceptMessage'
def _parse_dict(self, data):
super()._parse_dict(data)
self.friend_name = data.get('friend_name')
self.accept = data.get('accept')
def to_dict(self):
data = super().to_dict()
data['friend_name'] = self.friend_name
data['accept'] = self.accept
return data
class FriendUpdateMessage(BaseMessage):
def __init__(self, data=None):
super().__init__(data)
def _init_type(self):
self.type = 'FriendUpdateMessage' | 25.131148 | 50 | 0.632094 | 181 | 1,533 | 4.966851 | 0.138122 | 0.088988 | 0.080089 | 0.113459 | 0.667408 | 0.667408 | 0.667408 | 0.667408 | 0.667408 | 0.667408 | 0 | 0 | 0.245923 | 1,533 | 61 | 51 | 25.131148 | 0.777682 | 0 | 0 | 0.704545 | 0 | 0 | 0.097132 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.318182 | false | 0 | 0.022727 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
0fe7f5a0d2d6cc56f2638823285b05af4eeb1e16 | 765 | py | Python | dice_vtk/geometries/regularPolygon.py | dicehub/dice_vtk | ab8d9f34ae359461db5687d05bf38548bbaca6ea | [
"MIT"
] | null | null | null | dice_vtk/geometries/regularPolygon.py | dicehub/dice_vtk | ab8d9f34ae359461db5687d05bf38548bbaca6ea | [
"MIT"
] | null | null | null | dice_vtk/geometries/regularPolygon.py | dicehub/dice_vtk | ab8d9f34ae359461db5687d05bf38548bbaca6ea | [
"MIT"
] | null | null | null | # External modules
# ================
from vtk import vtkRegularPolygonSource
# DICE modules
# ============
from .simple_geometry import SimpleGeometry
from .geometry_base import GeometryProperty
class RegularPolygon(SimpleGeometry):
def __init__(self, name='RegularPolygon', **kwargs):
super().__init__(name=name,
source=vtkRegularPolygonSource, **kwargs)
@GeometryProperty
def radius(self):
return self.source.GetRadius()
@radius.setter
def radius(self, value):
self.source.SetRadius(value)
@GeometryProperty
def number_of_sides(self):
return self.source.GetNumberOfSides()
@number_of_sides.setter
def number_of_sides(self, value):
self.source.SetNumberOfSides(value)
| 24.677419 | 56 | 0.686275 | 76 | 765 | 6.697368 | 0.421053 | 0.078585 | 0.076621 | 0.078585 | 0.078585 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.19085 | 765 | 30 | 57 | 25.5 | 0.822294 | 0.077124 | 0 | 0.105263 | 0 | 0 | 0.019971 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.263158 | false | 0 | 0.157895 | 0.105263 | 0.578947 | 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 |
0feb6e540faea9556a7188bf2180fcd15abce9ef | 1,279 | py | Python | qf_lib/documents_utils/document_exporting/element/custom.py | webclinic017/qf-lib | 96463876719bba8a76c8269cef76addf3a2d836d | [
"Apache-2.0"
] | 198 | 2019-08-16T15:09:23.000Z | 2022-03-30T12:44:00.000Z | qf_lib/documents_utils/document_exporting/element/custom.py | webclinic017/qf-lib | 96463876719bba8a76c8269cef76addf3a2d836d | [
"Apache-2.0"
] | 13 | 2021-01-07T10:15:19.000Z | 2022-03-29T13:01:47.000Z | qf_lib/documents_utils/document_exporting/element/custom.py | webclinic017/qf-lib | 96463876719bba8a76c8269cef76addf3a2d836d | [
"Apache-2.0"
] | 29 | 2019-08-16T15:21:28.000Z | 2022-02-23T09:53:49.000Z | # Copyright 2016-present CERN – European Organization for Nuclear Research
#
# 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 qf_lib.common.enums.grid_proportion import GridProportion
from qf_lib.documents_utils.document_exporting.document import Document
from qf_lib.documents_utils.document_exporting.element import Element
class CustomElement(Element):
def __init__(self, html: str, grid_proportion=GridProportion.Eight):
"""
An element containing custom HTML.
"""
super().__init__(grid_proportion)
self.html = html
def generate_html(self, document: Document) -> str:
"""
Generates the HTML that represents the underlying element.
"""
return self.html
| 38.757576 | 78 | 0.715403 | 167 | 1,279 | 5.371257 | 0.592814 | 0.06689 | 0.0301 | 0.035674 | 0.089186 | 0.089186 | 0.089186 | 0 | 0 | 0 | 0 | 0.007976 | 0.215794 | 1,279 | 32 | 79 | 39.96875 | 0.885344 | 0.569977 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.333333 | 0 | 0.777778 | 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 |
0feb7089dc2957a91fab8aa02b4296dd72cb381a | 214 | py | Python | api/urls.py | GHImplementationTeam/referrals | fe00e97e208f0d6e451653cd1586f51b4a3e9720 | [
"MIT"
] | null | null | null | api/urls.py | GHImplementationTeam/referrals | fe00e97e208f0d6e451653cd1586f51b4a3e9720 | [
"MIT"
] | null | null | null | api/urls.py | GHImplementationTeam/referrals | fe00e97e208f0d6e451653cd1586f51b4a3e9720 | [
"MIT"
] | null | null | null | from django.conf.urls import url
import referrals
urlpatterns = [
url(r'^referrals/$', referrals.ReferralsView.as_view()),
url(r'^referral/(?P<referral_id>[-&\w]+)/$', referrals.ReferralView.as_view()),
]
| 26.75 | 83 | 0.691589 | 27 | 214 | 5.37037 | 0.62963 | 0.055172 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.107477 | 214 | 7 | 84 | 30.571429 | 0.759162 | 0 | 0 | 0 | 0 | 0 | 0.224299 | 0.168224 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
0febcd6f09e5ceb6936fd4c607ad690f91da7471 | 194 | py | Python | venv/webscrap_teste.py | pgfjunior/teste_web_scraping | fb8de63863287c9714a49849c9e2866def65f068 | [
"MIT"
] | null | null | null | venv/webscrap_teste.py | pgfjunior/teste_web_scraping | fb8de63863287c9714a49849c9e2866def65f068 | [
"MIT"
] | null | null | null | venv/webscrap_teste.py | pgfjunior/teste_web_scraping | fb8de63863287c9714a49849c9e2866def65f068 | [
"MIT"
] | null | null | null | import urllib.request
from bs4 import BeautifulSoup
page = urllib.request.urlopen('https://www.dentalcremer.com.br/')
soup = BeautifulSoup(page, "html.parser")
print(soup.find_all('table'))
| 19.4 | 65 | 0.757732 | 26 | 194 | 5.615385 | 0.769231 | 0.178082 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005682 | 0.092784 | 194 | 9 | 66 | 21.555556 | 0.823864 | 0 | 0 | 0 | 0 | 0 | 0.247423 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0.2 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
0fedad77ac88f1a6c75d6f7e75f5be3e0ab52f87 | 1,994 | py | Python | tests/test_testoot/conftest.py | sobolevn/testoot | bd1c19da6a232b1599836275c5026661a41e3c4a | [
"MIT"
] | 2 | 2020-04-19T13:48:32.000Z | 2020-05-02T17:43:55.000Z | tests/test_testoot/conftest.py | sobolevn/testoot | bd1c19da6a232b1599836275c5026661a41e3c4a | [
"MIT"
] | 14 | 2020-05-02T16:31:57.000Z | 2020-05-10T20:07:58.000Z | tests/test_testoot/conftest.py | aptakhin/regress | 83e07b2cd745f5f5dc733edbd126bedbb5b2abf3 | [
"MIT"
] | 1 | 2020-05-20T12:04:12.000Z | 2020-05-20T12:04:12.000Z | from typing import Optional
import pytest
from testoot.base import TestootContext, Comparator, TestootSerializer, \
FileType, TestootTestResult
from testoot.ext.pytest import PytestContext
from testoot.testoot import Testoot
from tests.conftest import AbcDiffResult
@pytest.fixture(scope='module')
def base_testoot(root_base_testoot):
testoot = root_base_testoot.clone(
storage=root_base_testoot.storage.clone(add_path='examples'),
)
testoot.storage.ensure_exists()
yield testoot
@pytest.fixture(scope='function')
def testoot(base_testoot, request):
testoot = Testoot(base_testoot, PytestContext(request))
yield testoot
class TrueComparator(Comparator):
@classmethod
def compare(cls, test_obj: any, canon_obj: any):
assert True
class FalseComparator(Comparator):
@classmethod
def compare(cls, test_obj: any, canon_obj: any):
assert False
class ContextTestoot(TestootContext):
def __init__(self, name, comparator: Optional[Comparator] = None,
serializer: Optional[TestootSerializer] = None,
ask_canonize: bool = False):
self._name = name
self._comparator = (TrueComparator() if comparator is None
else comparator)
self._serializer = serializer
self._ask_canonize = ask_canonize
def get_storage_name(self, file_type_hint: FileType,
suffix: Optional[str] = None):
return self._name
def get_storage_name_from_filename(self, filename: str):
return filename
def get_comparator(self) -> Optional[Comparator]:
return self._comparator
def get_serializer(self) -> Optional[TestootSerializer]:
return self._serializer
def ask_canonize(self) -> bool:
return self._ask_canonize
def create_test_result(self, test_obj: any, canon_obj: any,
exc: Exception) -> TestootTestResult:
return AbcDiffResult()
| 29.323529 | 73 | 0.69007 | 217 | 1,994 | 6.129032 | 0.317972 | 0.049624 | 0.033835 | 0.033835 | 0.107519 | 0.107519 | 0.091729 | 0.091729 | 0.091729 | 0.091729 | 0 | 0 | 0.230191 | 1,994 | 67 | 74 | 29.761194 | 0.86645 | 0 | 0 | 0.122449 | 0 | 0 | 0.011033 | 0 | 0 | 0 | 0 | 0 | 0.040816 | 1 | 0.22449 | false | 0 | 0.122449 | 0.122449 | 0.530612 | 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 |
0fee2372d6f0f14e825a2cb46d667f12dbab810f | 1,109 | py | Python | peptidemapper/src/pepmapperapp/migrations/0002_mapperautocomplete.py | uvic-proteincentre/MRMAssayDB | 12b19a2064fe9b8006f6457500c9cb79b1b829ed | [
"Apache-2.0"
] | null | null | null | peptidemapper/src/pepmapperapp/migrations/0002_mapperautocomplete.py | uvic-proteincentre/MRMAssayDB | 12b19a2064fe9b8006f6457500c9cb79b1b829ed | [
"Apache-2.0"
] | null | null | null | peptidemapper/src/pepmapperapp/migrations/0002_mapperautocomplete.py | uvic-proteincentre/MRMAssayDB | 12b19a2064fe9b8006f6457500c9cb79b1b829ed | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('pepmapperapp', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='MapperAutoComplete',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('uniprotacc', models.CharField(max_length=20)),
('prot_name', models.CharField(max_length=300)),
('gene', models.CharField(max_length=100)),
('organism', models.CharField(max_length=100)),
('pepseq', models.CharField(max_length=20)),
('path_name', models.CharField(max_length=1000)),
('dis_mut', models.CharField(max_length=1000)),
('go_id', models.CharField(max_length=100)),
('go_name', models.CharField(max_length=1000)),
('go_term', models.CharField(max_length=100)),
],
),
]
| 35.774194 | 114 | 0.574391 | 108 | 1,109 | 5.666667 | 0.462963 | 0.245098 | 0.294118 | 0.392157 | 0.464052 | 0.156863 | 0 | 0 | 0 | 0 | 0 | 0.045226 | 0.282236 | 1,109 | 30 | 115 | 36.966667 | 0.723618 | 0.018936 | 0 | 0 | 0 | 0 | 0.108656 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.083333 | 0 | 0.208333 | 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 |
ba1c71602bcc3a8f20aebbbae94098c99780e8ff | 152 | py | Python | src/backup_utils/databases/__init__.py | Oprax/backup-utils | 8de928d5257c9a67c65ca906e49596abe1e3b1ba | [
"MIT"
] | null | null | null | src/backup_utils/databases/__init__.py | Oprax/backup-utils | 8de928d5257c9a67c65ca906e49596abe1e3b1ba | [
"MIT"
] | null | null | null | src/backup_utils/databases/__init__.py | Oprax/backup-utils | 8de928d5257c9a67c65ca906e49596abe1e3b1ba | [
"MIT"
] | null | null | null | from functools import partial
from ..utils import load
__all__ = ["databases"]
databases = partial(load, pkg="backup_utils.databases", suffix="Db")
| 16.888889 | 68 | 0.743421 | 19 | 152 | 5.684211 | 0.631579 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131579 | 152 | 8 | 69 | 19 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0.217105 | 0.144737 | 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 |
ba1cf387e7aec7401bb6e9dfcd3c708295ef07ce | 375 | py | Python | code_examples/tensorflow/basic_nmt_example/seq2seq_edits/attention_wrapper.py | Splendon/examples | ed4a8a01857b6ddca49559141acf5d0986eb01e1 | [
"MIT"
] | null | null | null | code_examples/tensorflow/basic_nmt_example/seq2seq_edits/attention_wrapper.py | Splendon/examples | ed4a8a01857b6ddca49559141acf5d0986eb01e1 | [
"MIT"
] | null | null | null | code_examples/tensorflow/basic_nmt_example/seq2seq_edits/attention_wrapper.py | Splendon/examples | ed4a8a01857b6ddca49559141acf5d0986eb01e1 | [
"MIT"
] | null | null | null | # Copyright 2019 Graphcore Ltd.
'''
Edits to seq2seq AttentionWrapper
'''
import tensorflow as tf
class AttentionWrapperNoAssert(tf.contrib.seq2seq.AttentionWrapper):
# Stops the adding of Assert operations that "assert_equal" the wrapper batch_size and the attention_mechanisms batch_size
def _batch_size_checks(self, batch_size, error_message):
return []
| 31.25 | 126 | 0.784 | 47 | 375 | 6.06383 | 0.744681 | 0.126316 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018868 | 0.152 | 375 | 11 | 127 | 34.090909 | 0.877358 | 0.493333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.25 | 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 |
e83e35480e03fbc96372bcc220d34b49bf9a9cba | 2,149 | py | Python | OpenGLWrapper_JE/venv/Lib/site-packages/OpenGL/GL/ARB/map_buffer_range.py | JE-Chen/je_old_repo | a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5 | [
"MIT"
] | null | null | null | OpenGLWrapper_JE/venv/Lib/site-packages/OpenGL/GL/ARB/map_buffer_range.py | JE-Chen/je_old_repo | a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5 | [
"MIT"
] | null | null | null | OpenGLWrapper_JE/venv/Lib/site-packages/OpenGL/GL/ARB/map_buffer_range.py | JE-Chen/je_old_repo | a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5 | [
"MIT"
] | null | null | null | '''OpenGL extension ARB.map_buffer_range
This module customises the behaviour of the
OpenGL.raw.GL.ARB.map_buffer_range to provide a more
Python-friendly API
Overview (from the spec)
ARB_map_buffer_range expands the buffer object API to allow greater
performance when a client application only needs to write to a sub-range
of a buffer object. To that end, this extension introduces two new buffer
object features: non-serialized buffer modification and explicit sub-range
flushing for mapped buffer objects.
OpenGL requires that commands occur in a FIFO manner meaning that any
changes to buffer objects either block until the data has been processed by
the OpenGL pipeline or else create extra copies to avoid such a block. By
providing a method to asynchronously modify buffer object data, an
application is then able to manage the synchronization points themselves
and modify ranges of data contained by a buffer object even though OpenGL
might still be using other parts of it.
This extension also provides a method for explicitly flushing ranges of a
mapped buffer object so OpenGL does not have to assume that the entire
range may have been modified. Further, it allows the application to more
precisely specify its intent with respect to reading, writing, and whether
the previous contents of a mapped range of interest need be preserved
prior to modification.
Affects ARB_vertex_buffer_object, ARB_pixel_buffer_object and OpenGL 1.5
Buffer Objects.
The official definition of this extension is available here:
http://www.opengl.org/registry/specs/ARB/map_buffer_range.txt
'''
from OpenGL import platform, constant, arrays
from OpenGL import extensions, wrapper
import ctypes
from OpenGL.raw.GL import _types, _glgets
from OpenGL.raw.GL.ARB.map_buffer_range import *
from OpenGL.raw.GL.ARB.map_buffer_range import _EXTENSION_NAME
def glInitMapBufferRangeARB():
'''Return boolean indicating whether this extension is available'''
from OpenGL import extensions
return extensions.hasGLExtension( _EXTENSION_NAME )
### END AUTOGENERATED SECTION | 42.98 | 77 | 0.790135 | 324 | 2,149 | 5.16358 | 0.493827 | 0.057382 | 0.043036 | 0.060968 | 0.062164 | 0.062164 | 0.062164 | 0.045427 | 0.045427 | 0 | 0 | 0.001129 | 0.175896 | 2,149 | 50 | 78 | 42.98 | 0.943535 | 0.873895 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | true | 0 | 0.777778 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
e8459f0fc13fb8e816c864fc35cd8a3cb0f01468 | 739 | py | Python | app/models/domain/position.py | Chaoyingz/paper_trading | cd3af81c932e8f4b1586f2b9bf86b5b252bec896 | [
"MIT"
] | null | null | null | app/models/domain/position.py | Chaoyingz/paper_trading | cd3af81c932e8f4b1586f2b9bf86b5b252bec896 | [
"MIT"
] | null | null | null | app/models/domain/position.py | Chaoyingz/paper_trading | cd3af81c932e8f4b1586f2b9bf86b5b252bec896 | [
"MIT"
] | null | null | null | from datetime import datetime
from pydantic import Field
from app.models.base import DBModelMixin
from app.models.domain.stocks import Stock
from app.models.types import PyDecimal, PyObjectId
class Position(Stock):
"""持仓股票"""
volume: int = Field(..., description="持仓量")
available_volume: int = Field(..., description="可用量")
cost: PyDecimal = Field(..., description="持仓成本")
current_price: PyDecimal = Field(..., description="当前价格")
profit: PyDecimal = Field(..., description="利润")
first_buy_date: datetime = Field(None, description="首次持有日期")
last_sell_date: datetime = Field(None, description="最后卖出日期")
class PositionInDB(DBModelMixin, Position):
user: PyObjectId = Field(..., description="用户ID")
| 30.791667 | 64 | 0.711773 | 84 | 739 | 6.190476 | 0.5 | 0.184615 | 0.075 | 0.096154 | 0.123077 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.14885 | 739 | 23 | 65 | 32.130435 | 0.826709 | 0.005413 | 0 | 0 | 0 | 0 | 0.043896 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 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 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
e84b2f2fe83a3e28896f1f56e30847e498d1d2a1 | 648 | py | Python | rules/tamper/wordpress.py | lavon321/Kunlun-M | 792548536d67f648c92324ecc153d7f206623e31 | [
"MIT"
] | 1,059 | 2020-08-06T13:32:10.000Z | 2022-03-31T07:20:27.000Z | rules/tamper/wordpress.py | lavon321/Kunlun-M | 792548536d67f648c92324ecc153d7f206623e31 | [
"MIT"
] | 87 | 2020-09-08T06:34:45.000Z | 2022-03-28T05:52:36.000Z | rules/tamper/wordpress.py | lavon321/Kunlun-M | 792548536d67f648c92324ecc153d7f206623e31 | [
"MIT"
] | 171 | 2020-08-13T11:53:47.000Z | 2022-03-30T03:23:07.000Z | # -*- coding: utf-8 -*-
"""
wordpress
~~~~
tamper for wordpress
:author: LoRexxar <LoRexxar@gmail.com>
:homepage: https://github.com/LoRexxar/Kunlun-M
:license: MIT, see LICENSE for more details.
:copyright: Copyright (c) 2017 LoRexxar. All rights reserved
"""
wordpress = {
"esc_url": [1000, 10001, 10002],
"esc_js": [1000, 10001, 10002],
"esc_html": [1000, 10001, 10002],
"esc_attr": [1000, 10001, 10002],
"esc_textarea": [1000, 10001, 10002],
"tag_escape": [1000, 10001, 10002],
"esc_sql": [1004, 1005, 1006],
"_real_escape": [1004, 1005, 1006],
}
wordpress_controlled = [] | 24 | 64 | 0.606481 | 77 | 648 | 4.974026 | 0.558442 | 0.140992 | 0.219321 | 0.221932 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.22332 | 0.219136 | 648 | 27 | 65 | 24 | 0.533597 | 0.399691 | 0 | 0 | 0 | 0 | 0.19774 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 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 |
e86c98c97c5408ae2e09367d971c6294affbf58a | 2,739 | py | Python | code_and_dataset/config_parser.py | pcpLiu/DeepSeqPanII | 86ce7675a1c69fd6059216d98b1e65e315ace3eb | [
"MIT"
] | 11 | 2019-10-30T12:41:56.000Z | 2021-11-17T02:45:52.000Z | code_and_dataset/config_parser.py | pcpLiu/DeepSeqPanII | 86ce7675a1c69fd6059216d98b1e65e315ace3eb | [
"MIT"
] | 2 | 2020-12-18T00:02:54.000Z | 2021-11-19T02:33:37.000Z | code_and_dataset/config_parser.py | pcpLiu/DeepSeqPanII | 86ce7675a1c69fd6059216d98b1e65e315ace3eb | [
"MIT"
] | 3 | 2020-03-09T06:25:20.000Z | 2021-08-02T11:36:46.000Z | # -*- coding: utf-8 -*-
import os
import json
import torch
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
class Config:
def __init__(self, json_file):
self.config = json.loads(open(json_file).read())
self.device = torch.device("cuda:1" if torch.cuda.is_available() else "cpu")
self.cpu_device = torch.device("cpu")
@property
def shuffle_before_epoch_enable(self):
return self.config['Training']['shuffle_before_epoch_enable']
@property
def is_LOMO(self):
return 'test_allele' in self.config['Data']
@property
def test_allele(self):
return self.config['Data'].get('test_allele', None)
@property
def weight_decay(self):
return self.config['Training']['weight_decay']
@property
def bind_core_file(self):
return os.path.join(BASE_DIR, 'dataset', self.config['Data']['bind_core_file'])
@property
def max_len_hla_A(self):
return self.config['Data']['max_len_hla_A']
@property
def max_len_hla_B(self):
return self.config['Data']['max_len_hla_B']
@property
def max_len_pep(self):
return self.config['Data']['max_len_pep']
@property
def validation_ratio(self):
return self.config['Data']['validation_ratio']
@property
def batch_size(self):
return self.config['Training']['batch_size']
@property
def working_dir(self):
return os.path.join(BASE_DIR, self.config['Paths']['working_dir'])
@property
def data_file(self):
return os.path.join(BASE_DIR, 'dataset', self.config['Data']['data_file'])
@property
def test_file(self):
return os.path.join(BASE_DIR, 'dataset', self.config['Data']['test_file'])
@property
def model_save_path(self):
return os.path.join(self.working_dir, 'best_model.pytorch')
@property
def model_config(self):
return self.config['Model']
@property
def grad_clip(self):
return self.config['Training']['grad_clip']
@property
def start_lr(self):
return self.config['Training']['start_lr']
@property
def min_lr(self):
return self.config['Training']['min_lr']
@property
def epochs(self):
return self.config['Training']['epochs']
@property
def loss_delta(self):
return self.config['Training']['loss_delta']
@property
def seq_encode_dim(self):
return self.model_config['seq_encoding_dim']
@property
def encoding_method(self):
return self.model_config['encoding_method']
@property
def do_train(self):
return self.config['do_train']
@property
def do_test(self):
return self.config['do_test']
| 24.675676 | 87 | 0.642935 | 359 | 2,739 | 4.671309 | 0.222841 | 0.157424 | 0.150268 | 0.190817 | 0.422779 | 0.202147 | 0.166369 | 0.132379 | 0.093023 | 0.093023 | 0 | 0.000936 | 0.220153 | 2,739 | 110 | 88 | 24.9 | 0.784176 | 0.007667 | 0 | 0.296296 | 0 | 0 | 0.152062 | 0.009941 | 0 | 0 | 0 | 0 | 0 | 1 | 0.308642 | false | 0 | 0.037037 | 0.296296 | 0.654321 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
e873290b82b21476d01ffb34ba0ea8df2ff20e15 | 7,055 | py | Python | API/main/migrations/0001_initial.py | Ju99ernaut/grapeflowAPI | 0d6599775e5b666ad735160b65262624fea0bf99 | [
"MIT"
] | null | null | null | API/main/migrations/0001_initial.py | Ju99ernaut/grapeflowAPI | 0d6599775e5b666ad735160b65262624fea0bf99 | [
"MIT"
] | null | null | null | API/main/migrations/0001_initial.py | Ju99ernaut/grapeflowAPI | 0d6599775e5b666ad735160b65262624fea0bf99 | [
"MIT"
] | null | null | null | # Generated by Django 3.0.3 on 2020-02-25 18:50
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='UserData',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('notifyInvoice', models.BooleanField(default=True)),
('notifyNews', models.BooleanField(default=True)),
('notifyFeature', models.BooleanField(default=True)),
('avatar', models.URLField(blank=True, default='', max_length=100)),
('city', models.CharField(blank=True, default='', max_length=100)),
('country', models.CharField(blank=True, default='', max_length=100)),
('created', models.DateTimeField(auto_now_add=True)),
('user', models.ForeignKey(default='1', on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
options={
'verbose_name_plural': 'UserData',
},
),
migrations.CreateModel(
name='Project',
fields=[
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
('name', models.CharField(blank=True, default='', max_length=100)),
('preview', models.URLField(blank=True, default='', max_length=100)),
('classes', models.CharField(blank=True, default='fa fa-picture-o gjs-block gjs-one-bg gjs-four-color-h', max_length=100)),
('domain', models.URLField(blank=True, default='', max_length=100)),
('published', models.BooleanField(default=False)),
('lastPublished', models.DateTimeField(auto_now_add=True)),
('user', models.ForeignKey(default='1', on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='Page',
fields=[
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
('name', models.CharField(blank=True, default='', max_length=100)),
('thumbnail', models.URLField(blank=True, default='', max_length=100)),
('favicon', models.URLField(blank=True, default='', max_length=100)),
('webclip', models.URLField(blank=True, default='', max_length=100)),
('html', models.TextField()),
('css', models.TextField()),
('js', models.TextField()),
('components', models.TextField()),
('style', models.TextField()),
('metaTitle', models.CharField(blank=True, default='', max_length=100)),
('metaDesc', models.CharField(blank=True, default='', max_length=100)),
('created', models.DateTimeField(auto_now_add=True)),
('lastSaved', models.DateTimeField(auto_now_add=True)),
('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='main.Project')),
],
options={
'ordering': ['created'],
},
),
migrations.CreateModel(
name='Order',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('plan', models.CharField(choices=[('HO', 'Hobbyist'), ('DV', 'Developer'), ('ET', 'Enterprise')], default='HO', max_length=2)),
('amt', models.FloatField()),
('active', models.BooleanField(default=False)),
('created', models.DateTimeField(auto_now_add=True)),
('expires', models.DateTimeField()),
('invoiceUrl', models.URLField(blank=True, default='', max_length=100)),
('user', models.ForeignKey(default='1', on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
options={
'ordering': ['created'],
},
),
migrations.CreateModel(
name='Logic',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, default='', max_length=100)),
('category', models.CharField(blank=True, default='Extra', max_length=100)),
('description', models.TextField()),
('js', models.TextField()),
('created', models.DateTimeField(auto_now_add=True)),
('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='main.Project')),
],
options={
'ordering': ['created'],
},
),
migrations.CreateModel(
name='Block',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(blank=True, default='', max_length=100)),
('category', models.CharField(blank=True, default='Extra', max_length=100)),
('description', models.TextField()),
('html', models.TextField()),
('css', models.TextField()),
('preview', models.URLField(blank=True, default='', max_length=100)),
('classes', models.CharField(blank=True, default='gjs-fonts gjs-f-b1 gjs-block gjs-one-bg gjs-four-color-h', max_length=100)),
('created', models.DateTimeField(auto_now_add=True)),
('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='main.Project')),
],
options={
'ordering': ['created'],
},
),
migrations.CreateModel(
name='Asset',
fields=[
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
('filename', models.CharField(blank=True, default='', max_length=100)),
('type', models.CharField(choices=[('IMG', 'Image'), ('SVG', 'SVG'), ('VID', 'Video')], default='IMG', max_length=3)),
('url', models.URLField(blank=True, default='', max_length=100)),
('size', models.IntegerField()),
('added', models.DateTimeField(auto_now_add=True)),
('user', models.ForeignKey(default='1', on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
options={
'ordering': ['added'],
},
),
]
| 51.875 | 144 | 0.55691 | 679 | 7,055 | 5.675994 | 0.200295 | 0.056046 | 0.091334 | 0.088739 | 0.743902 | 0.73508 | 0.707577 | 0.697198 | 0.587442 | 0.587442 | 0 | 0.017938 | 0.280936 | 7,055 | 135 | 145 | 52.259259 | 0.74177 | 0.006378 | 0 | 0.570313 | 1 | 0.015625 | 0.108019 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.03125 | 0 | 0.0625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
e8757496e36b307af85c05cdd4dd6a56e81063f4 | 145 | py | Python | name_translator.py | MathisBurger/timetable-updater | aa6c3180f4ae858cb2c63ccad7855f5f670c4114 | [
"MIT"
] | null | null | null | name_translator.py | MathisBurger/timetable-updater | aa6c3180f4ae858cb2c63ccad7855f5f670c4114 | [
"MIT"
] | null | null | null | name_translator.py | MathisBurger/timetable-updater | aa6c3180f4ae858cb2c63ccad7855f5f670c4114 | [
"MIT"
] | null | null | null | import json
def translate_name(name):
with open("name_translator.json", "r") as file:
data = json.load(file)
return data[name]
| 18.125 | 51 | 0.655172 | 21 | 145 | 4.428571 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.22069 | 145 | 7 | 52 | 20.714286 | 0.823009 | 0 | 0 | 0 | 0 | 0 | 0.144828 | 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 |
e88a42379408c1158246f618ad6b8e62971bdb21 | 1,924 | py | Python | src/compas_blender/geometry/__init__.py | adacko/compas | 47c443ad3825897ec7ed932ec20734c2f08ef120 | [
"MIT"
] | null | null | null | src/compas_blender/geometry/__init__.py | adacko/compas | 47c443ad3825897ec7ed932ec20734c2f08ef120 | [
"MIT"
] | null | null | null | src/compas_blender/geometry/__init__.py | adacko/compas | 47c443ad3825897ec7ed932ec20734c2f08ef120 | [
"MIT"
] | 1 | 2022-01-16T02:32:43.000Z | 2022-01-16T02:32:43.000Z | """
********************************************************************************
compas_blender.geometry
********************************************************************************
.. currentmodule:: compas_blender.geometry
Object-oriented convenience wrappers for native Blender geometry.
.. autosummary::
:toctree: generated/
BlenderCurve
BlenderMesh
BlenderPoint
BlenderSurface
"""
try:
import bpy
except ImportError:
pass
class BlenderGeometry(object):
def __init__(self, obj):
self.object = obj
self.name = obj.name
self.geometry = obj.data
self.otype = obj.type
self.attributes = {}
@property
def location(self):
return list(self.object.location)
@classmethod
def from_selection(cls):
raise NotImplementedError
@classmethod
def from_name(cls, name):
return BlenderGeometry(obj=bpy.data.objects[name])
@staticmethod
def find(guid):
raise NotImplementedError
@staticmethod
def refresh():
bpy.ops.wm.redraw_timer(type='DRAW_WIN_SWAP', iterations=1)
def delete(self):
raise NotImplementedError
def purge(self):
raise NotImplementedError
def hide(self):
raise NotImplementedError
def show(self):
raise NotImplementedError
def select(self):
raise NotImplementedError
def unselect(self):
raise NotImplementedError
def closest_point(self, *args, **kwargs):
raise NotImplementedError
def closest_points(self, *args, **kwargs):
raise NotImplementedError
from .point import BlenderPoint
from .curve import BlenderCurve
from .mesh import BlenderMesh
from .surface import BlenderSurface
__all__ = [
'BlenderGeometry',
'BlenderPoint',
'BlenderCurve',
'BlenderMesh',
'BlenderSurface',
]
| 16.168067 | 80 | 0.596674 | 169 | 1,924 | 6.692308 | 0.431953 | 0.212202 | 0.167109 | 0.164456 | 0.067197 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000689 | 0.245842 | 1,924 | 118 | 81 | 16.305085 | 0.778773 | 0.212578 | 0 | 0.264151 | 0 | 0 | 0.051129 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.264151 | false | 0.018868 | 0.113208 | 0.037736 | 0.433962 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
e892309adfae5627e160795d9ed6e92ccebca92c | 145 | py | Python | tests/test_get_term_list.py | vineetjohn/invest-o-scrape | 696a06538e0e2f1f4c2180bf43657861966a2685 | [
"MIT"
] | 5 | 2019-12-19T05:25:00.000Z | 2022-01-31T19:09:31.000Z | tests/test_get_term_list.py | vineetjohn/invest-o-scrape | 696a06538e0e2f1f4c2180bf43657861966a2685 | [
"MIT"
] | null | null | null | tests/test_get_term_list.py | vineetjohn/invest-o-scrape | 696a06538e0e2f1f4c2180bf43657861966a2685 | [
"MIT"
] | 3 | 2020-03-04T02:24:36.000Z | 2022-01-31T19:09:38.000Z | from utils import scrape_helper
url = "http://www.investopedia.com/terms/1/"
links = scrape_helper.get_term_links_from_page(url)
print(links)
| 18.125 | 51 | 0.786207 | 23 | 145 | 4.695652 | 0.73913 | 0.222222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.007634 | 0.096552 | 145 | 7 | 52 | 20.714286 | 0.816794 | 0 | 0 | 0 | 0 | 0 | 0.248276 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 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 |
e8a059c82f837ee40d8d6e38defcf69fc241cbd4 | 566 | py | Python | db_core/env.py | dayvagrant/db_core | 01552110ce6b31228e59b45279642a39716e55e7 | [
"MIT"
] | null | null | null | db_core/env.py | dayvagrant/db_core | 01552110ce6b31228e59b45279642a39716e55e7 | [
"MIT"
] | null | null | null | db_core/env.py | dayvagrant/db_core | 01552110ce6b31228e59b45279642a39716e55e7 | [
"MIT"
] | null | null | null | """Set of configrations."""
_CONFIGS = {
"postgres": {
"host": "0.0.0.0",
"port": "5432",
"user": <USER>,
"pwd": <USER>,
"db": "postgres",
},
"mongodb": {
"host": "0.0.0.0",
"port": "27017",
"user": <USER>,
"pwd": <PASS>,
},
"clickhouse": {
"host": "0.0.0.0",
"port": "8123",
"user": <USER>,
"pwd": <PASS>,
"db": "db_live",
},
"aws-s3": {
"url": <URL>,
"login": <USER>,
"password": <PASS>,
},
}
| 18.258065 | 27 | 0.34629 | 53 | 566 | 3.660377 | 0.433962 | 0.092784 | 0.092784 | 0.108247 | 0.185567 | 0.185567 | 0 | 0 | 0 | 0 | 0 | 0.076023 | 0.39576 | 566 | 30 | 28 | 18.866667 | 0.491228 | 0 | 0 | 0.296296 | 0 | 0 | 0.269017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.111111 | 0 | null | null | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
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