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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b1617ec423d380ef6d39ecb844f07e529d1e900e
| 281
|
py
|
Python
|
test/test_resources/python-unittest/py_several_files2/Root/test/test1.py
|
jocelyn/codeboard_mantra
|
05a4c783dbae8d87b55c834382d8d12f957ffea9
|
[
"MIT"
] | 1
|
2019-01-12T02:57:53.000Z
|
2019-01-12T02:57:53.000Z
|
test/test_resources/python-unittest/py_several_files2/Root/test/test1.py
|
jocelyn/codeboard_mantra
|
05a4c783dbae8d87b55c834382d8d12f957ffea9
|
[
"MIT"
] | 1
|
2017-10-13T11:57:41.000Z
|
2017-10-13T11:57:41.000Z
|
test/test_resources/python-unittest/py_several_files2/Root/test/test1.py
|
jocelyn/codeboard_mantra
|
05a4c783dbae8d87b55c834382d8d12f957ffea9
|
[
"MIT"
] | 6
|
2017-10-13T11:27:58.000Z
|
2020-10-06T19:06:22.000Z
|
from Root import b
import unittest
class test1(unittest.TestCase):
def test_shuffle(self):
self.assertEqual(b.add(1,2),3)
def test_add(self):
self.assertEqual(b.add(4,2),6)
def test_addFail(self):
self.assertEqual(b.add(1,2),4)
if __name__ == '__main__':
unittest.main()
| 23.416667
| 32
| 0.725979
| 48
| 281
| 4.020833
| 0.479167
| 0.108808
| 0.295337
| 0.310881
| 0.378238
| 0.259067
| 0.259067
| 0
| 0
| 0
| 0
| 0.040161
| 0.113879
| 281
| 11
| 33
| 25.545455
| 0.73494
| 0
| 0
| 0
| 0
| 0
| 0.02847
| 0
| 0
| 0
| 0
| 0
| 0.272727
| 1
| 0.272727
| false
| 0
| 0.181818
| 0
| 0.545455
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
b167f223733c1d3f888e92631f85bada5ba538f4
| 31
|
py
|
Python
|
autokey/CapsCtrl/caps_j.py
|
TeX2e/dotfiles
|
4e39b59623067fcb09ceaa7f4892ff7a2b285374
|
[
"WTFPL"
] | 1
|
2017-04-17T16:24:23.000Z
|
2017-04-17T16:24:23.000Z
|
autokey/CapsCtrl/caps_j.py
|
TeX2e/dotfiles
|
4e39b59623067fcb09ceaa7f4892ff7a2b285374
|
[
"WTFPL"
] | null | null | null |
autokey/CapsCtrl/caps_j.py
|
TeX2e/dotfiles
|
4e39b59623067fcb09ceaa7f4892ff7a2b285374
|
[
"WTFPL"
] | 1
|
2021-02-23T07:51:32.000Z
|
2021-02-23T07:51:32.000Z
|
keyboard.send_keys("<ctrl>+j")
| 15.5
| 30
| 0.709677
| 5
| 31
| 4.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.032258
| 31
| 1
| 31
| 31
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0.258065
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b16ab7d571cab76e9c524767f042bc73f2b4d7bb
| 83
|
py
|
Python
|
editor/platforms/windows.py
|
Commander07/Magnitude
|
2b793d0d9946f6b35c5935ae5921592e287bbbe7
|
[
"MIT"
] | 6
|
2020-12-06T20:21:39.000Z
|
2021-06-29T06:37:40.000Z
|
editor/platforms/windows.py
|
Commander07/Magnitude
|
2b793d0d9946f6b35c5935ae5921592e287bbbe7
|
[
"MIT"
] | null | null | null |
editor/platforms/windows.py
|
Commander07/Magnitude
|
2b793d0d9946f6b35c5935ae5921592e287bbbe7
|
[
"MIT"
] | null | null | null |
## Windows specific functions. If a function exists here it must exist in linux.py
| 41.5
| 82
| 0.783133
| 14
| 83
| 4.642857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168675
| 83
| 1
| 83
| 83
| 0.942029
| 0.951807
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b1746ab01205c09873f11ebd2450332cf6fbd19f
| 267
|
py
|
Python
|
sniper/tools/viz/asohelper.py
|
kleberkruger/donuts
|
99a7c5885fcb6d252a47a4cb74ca714f8ba12ca6
|
[
"MIT"
] | 2
|
2015-08-04T04:07:17.000Z
|
2015-08-06T00:51:33.000Z
|
sniper/tools/viz/asohelper.py
|
kleberkruger/donuts
|
99a7c5885fcb6d252a47a4cb74ca714f8ba12ca6
|
[
"MIT"
] | null | null | null |
sniper/tools/viz/asohelper.py
|
kleberkruger/donuts
|
99a7c5885fcb6d252a47a4cb74ca714f8ba12ca6
|
[
"MIT"
] | 1
|
2021-10-04T13:53:51.000Z
|
2021-10-04T13:53:51.000Z
|
def get_fp_addsub(f):
return f["addpd"] + f["addsd"] + f["addss"] + f["addps"] + f["subpd"] + f["subsd"] + f["subss"] + f["subps"]
def get_fp_muldiv(f):
return f["mulpd"] + f["mulsd"] + f["mulss"] + f["mulps"] + f["divpd"] + f["divsd"] + f["divss"] + f["divps"]
| 44.5
| 110
| 0.531835
| 44
| 267
| 3.136364
| 0.522727
| 0.086957
| 0.115942
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153558
| 267
| 5
| 111
| 53.4
| 0.610619
| 0
| 0
| 0
| 0
| 0
| 0.299625
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
b192605b525578d6c9fe07cb2aed9dd6e6fe98f3
| 299
|
py
|
Python
|
xv_leak_tools/test_device/router_device.py
|
RDTCREW/expressvpn_leak_testing
|
da710573ccbe6472c4e4588058d9ec887e61e0a9
|
[
"MIT"
] | null | null | null |
xv_leak_tools/test_device/router_device.py
|
RDTCREW/expressvpn_leak_testing
|
da710573ccbe6472c4e4588058d9ec887e61e0a9
|
[
"MIT"
] | null | null | null |
xv_leak_tools/test_device/router_device.py
|
RDTCREW/expressvpn_leak_testing
|
da710573ccbe6472c4e4588058d9ec887e61e0a9
|
[
"MIT"
] | null | null | null |
from xv_leak_tools.log import L
from xv_leak_tools.test_device.device import Device
class RouterDevice(Device):
def os_name(self):
# TODO: Make this dynamic
return 'linux'
def os_version(self):
L.warning("TODO: Linux version")
return 'TODO: Linux version'
| 23
| 51
| 0.67893
| 42
| 299
| 4.666667
| 0.547619
| 0.061224
| 0.102041
| 0.153061
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.237458
| 299
| 12
| 52
| 24.916667
| 0.859649
| 0.076923
| 0
| 0
| 0
| 0
| 0.156934
| 0
| 0
| 0
| 0
| 0.083333
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.125
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
b19889665f0ee81a193bc0063390a65e19a1320c
| 59
|
py
|
Python
|
wiremock/tests/resource_tests/scenarios_tests/serialization_tests.py
|
sp1rs/python-wiremock
|
b570b0ebc60ac0d873812f21f78f2a8a4353792f
|
[
"Apache-2.0"
] | 22
|
2017-07-01T14:44:04.000Z
|
2021-09-08T08:45:21.000Z
|
wiremock/tests/resource_tests/scenarios_tests/serialization_tests.py
|
sp1rs/python-wiremock
|
b570b0ebc60ac0d873812f21f78f2a8a4353792f
|
[
"Apache-2.0"
] | 37
|
2017-04-24T15:28:27.000Z
|
2021-09-20T08:58:26.000Z
|
wiremock/tests/resource_tests/scenarios_tests/serialization_tests.py
|
sp1rs/python-wiremock
|
b570b0ebc60ac0d873812f21f78f2a8a4353792f
|
[
"Apache-2.0"
] | 22
|
2017-04-24T14:58:06.000Z
|
2021-09-09T09:22:31.000Z
|
# Purposefully left blank as there are no specific models.
| 29.5
| 58
| 0.79661
| 9
| 59
| 5.222222
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.169492
| 59
| 1
| 59
| 59
| 0.959184
| 0.949153
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4951f4dd0bb9dd7897a5719b630e1ba4c44100e2
| 2,168
|
py
|
Python
|
Lib/site-packages/mysqlx/dbdoc.py
|
jmsnur/mytaxi-test
|
eb7f70d0ac1c4df32aaebaab118a25c83683ce13
|
[
"bzip2-1.0.6"
] | 7
|
2022-03-10T07:03:14.000Z
|
2022-03-24T09:42:46.000Z
|
Lib/site-packages/mysqlx/dbdoc.py
|
jmsnur/mytaxi-test
|
eb7f70d0ac1c4df32aaebaab118a25c83683ce13
|
[
"bzip2-1.0.6"
] | 7
|
2019-12-04T22:51:59.000Z
|
2022-02-10T08:28:35.000Z
|
Lib/site-packages/mysqlx/dbdoc.py
|
jmsnur/mytaxi-test
|
eb7f70d0ac1c4df32aaebaab118a25c83683ce13
|
[
"bzip2-1.0.6"
] | 3
|
2020-07-22T23:41:29.000Z
|
2020-09-02T16:40:32.000Z
|
# MySQL Connector/Python - MySQL driver written in Python.
# Copyright (c) 2016, Oracle and/or its affiliates. All rights reserved.
# MySQL Connector/Python is licensed under the terms of the GPLv2
# <http://www.gnu.org/licenses/old-licenses/gpl-2.0.html>, like most
# MySQL Connectors. There are special exceptions to the terms and
# conditions of the GPLv2 as it is applied to this software, see the
# FOSS License Exception
# <http://www.mysql.com/about/legal/licensing/foss-exception.html>.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
"""Implementation of the DbDoc."""
import json
import uuid
from .compat import STRING_TYPES
class DbDoc(object):
"""Represents a generic document in JSON format.
Args:
value (object): The value can be a JSON string or a dict.
Raises:
ValueError: If ``value`` type is not a basestring or dict.
"""
def __init__(self, value):
# TODO: Handle exceptions. What happens if it doesn't load properly?
if isinstance(value, dict):
self.__dict__ = value
elif isinstance(value, STRING_TYPES):
self.__dict__ = json.loads(value)
else:
raise ValueError("Unable to handle type: {0}".format(type(value)))
def __getitem__(self, index):
return self.__dict__[index]
def keys(self):
return self.__dict__.keys()
def ensure_id(self):
if "_id" not in self.__dict__:
self.__dict__["_id"] = uuid.uuid4().hex
return self.__dict__["_id"]
def __str__(self):
return json.dumps(self.__dict__)
| 34.412698
| 78
| 0.697417
| 314
| 2,168
| 4.656051
| 0.496815
| 0.043776
| 0.026676
| 0.038988
| 0.077291
| 0.038304
| 0
| 0
| 0
| 0
| 0
| 0.012353
| 0.215867
| 2,168
| 62
| 79
| 34.967742
| 0.847647
| 0.62869
| 0
| 0
| 0
| 0
| 0.046543
| 0
| 0
| 0
| 0
| 0.016129
| 0
| 1
| 0.238095
| false
| 0
| 0.142857
| 0.142857
| 0.619048
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
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0
| 4
|
499173929547adad9f80fb5bb89afaef0c631b1d
| 237
|
py
|
Python
|
venv/Lib/site-packages/bootstrap3/templates/bootstrap3/form_errors.html.py
|
roshanba/mangal
|
f7b428811dc07214009cc33f0beb665ead402038
|
[
"bzip2-1.0.6",
"MIT"
] | null | null | null |
venv/Lib/site-packages/bootstrap3/templates/bootstrap3/form_errors.html.py
|
roshanba/mangal
|
f7b428811dc07214009cc33f0beb665ead402038
|
[
"bzip2-1.0.6",
"MIT"
] | null | null | null |
venv/Lib/site-packages/bootstrap3/templates/bootstrap3/form_errors.html.py
|
roshanba/mangal
|
f7b428811dc07214009cc33f0beb665ead402038
|
[
"bzip2-1.0.6",
"MIT"
] | null | null | null |
XXXX XXXXXXXXXXXX XXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXX
XXXXXXX XXXXXXXXXXXXX XXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
BBB BBBBB BB BBBBBB
BB BBB BBBBBBBBBBBBXXXXBBBBB
BBBBBB
XXXXXX
| 33.857143
| 95
| 0.835443
| 19
| 237
| 10.421053
| 0.684211
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| 237
| 6
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0
| 4
|
49a27d8df1fa80afe142635c112bacef76b19c83
| 46
|
py
|
Python
|
venv/lib/python3.6/encodings/unicode_escape.py
|
JamesMusyoka/Blog
|
fdcb51cf4541bbb3b9b3e7a1c3735a0b1f45f0b5
|
[
"Unlicense"
] | 2
|
2019-04-17T13:35:50.000Z
|
2021-12-21T00:11:36.000Z
|
venv/lib/python3.6/encodings/unicode_escape.py
|
JamesMusyoka/Blog
|
fdcb51cf4541bbb3b9b3e7a1c3735a0b1f45f0b5
|
[
"Unlicense"
] | 2
|
2021-03-31T19:51:24.000Z
|
2021-06-10T23:05:09.000Z
|
venv/lib/python3.6/encodings/unicode_escape.py
|
JamesMusyoka/Blog
|
fdcb51cf4541bbb3b9b3e7a1c3735a0b1f45f0b5
|
[
"Unlicense"
] | 2
|
2019-10-01T08:47:35.000Z
|
2020-07-11T06:32:16.000Z
|
/usr/lib/python3.6/encodings/unicode_escape.py
| 46
| 46
| 0.847826
| 8
| 46
| 4.75
| 1
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|
0
| 4
|
b8f2861ad65e733005d740bd1e4ef27fa1421324
| 300
|
py
|
Python
|
text_embeddings/byte/__init__.py
|
ChenghaoMou/embeddings
|
e63c2f2f4a688302de37bb8ccfd37a0170e2c374
|
[
"MIT"
] | 12
|
2021-04-18T02:32:55.000Z
|
2021-12-19T13:49:23.000Z
|
text_embeddings/byte/__init__.py
|
ChenghaoMou/embeddings
|
e63c2f2f4a688302de37bb8ccfd37a0170e2c374
|
[
"MIT"
] | 1
|
2021-07-04T09:06:34.000Z
|
2021-07-25T03:45:43.000Z
|
text_embeddings/byte/__init__.py
|
ChenghaoMou/embeddings
|
e63c2f2f4a688302de37bb8ccfd37a0170e2c374
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date : 2021-07-18 14:36:09
# @Author : Chenghao Mou (mouchenghao@gmail.com)
from text_embeddings.byte.byt5 import ByT5Tokenizer
from text_embeddings.byte.charformer import ByteTokenizer, GBST
__all__ = ['ByT5Tokenizer', 'GBST', 'ByteTokenizer']
| 30
| 63
| 0.726667
| 39
| 300
| 5.435897
| 0.794872
| 0.075472
| 0.169811
| 0.207547
| 0
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| 0.068702
| 0.126667
| 300
| 9
| 64
| 33.333333
| 0.740458
| 0.403333
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| 1
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|
0
| 4
|
b8f97ce9a4d92ac7394a34ba9d8586d3c1b540e4
| 22
|
py
|
Python
|
alerta/version.py
|
panpann/alerta
|
95961df969aa803d3c08c5839178f034b5f87ebb
|
[
"Apache-2.0"
] | null | null | null |
alerta/version.py
|
panpann/alerta
|
95961df969aa803d3c08c5839178f034b5f87ebb
|
[
"Apache-2.0"
] | null | null | null |
alerta/version.py
|
panpann/alerta
|
95961df969aa803d3c08c5839178f034b5f87ebb
|
[
"Apache-2.0"
] | null | null | null |
__version__ = '8.4.1'
| 11
| 21
| 0.636364
| 4
| 22
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 0.136364
| 22
| 1
| 22
| 22
| 0.368421
| 0
| 0
| 0
| 0
| 0
| 0.227273
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| false
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b8fdd828a5b8c58e572fae07ebdd31154aa63e69
| 38
|
py
|
Python
|
models/ACT/__init__.py
|
for-ai/ACT
|
efe259117a11d0583434d09440702fd75ebcdb99
|
[
"MIT"
] | 18
|
2018-09-30T13:30:12.000Z
|
2021-04-14T15:18:51.000Z
|
models/ACT/__init__.py
|
for-ai/ACT
|
efe259117a11d0583434d09440702fd75ebcdb99
|
[
"MIT"
] | 4
|
2020-01-28T21:59:56.000Z
|
2021-08-25T14:42:58.000Z
|
models/ACT/__init__.py
|
for-ai/ACT
|
efe259117a11d0583434d09440702fd75ebcdb99
|
[
"MIT"
] | 4
|
2018-11-25T14:12:36.000Z
|
2019-12-02T03:07:02.000Z
|
__all__ = ["act"]
from .act import *
| 9.5
| 18
| 0.605263
| 5
| 38
| 3.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 38
| 3
| 19
| 12.666667
| 0.633333
| 0
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| 0
| 0
| 0
| 0.078947
| 0
| 0
| 0
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| false
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| 1
| 0
| 0
| 0
|
0
| 4
|
7712bea8a5466c59e23f22f1997b489414053997
| 550
|
py
|
Python
|
app/main/models/pedido.py
|
amandapersampa/Franguinho
|
940b6601a821ab4857de7f0a5a0ac53f6f54a564
|
[
"MIT"
] | null | null | null |
app/main/models/pedido.py
|
amandapersampa/Franguinho
|
940b6601a821ab4857de7f0a5a0ac53f6f54a564
|
[
"MIT"
] | 8
|
2017-03-14T11:55:07.000Z
|
2017-04-03T00:53:32.000Z
|
app/main/models/pedido.py
|
amandapersampa/MicroGerencia
|
940b6601a821ab4857de7f0a5a0ac53f6f54a564
|
[
"MIT"
] | null | null | null |
# coding=utf-8
from app import db
from sqlalchemy.orm import relationship
class pedido_dao:
__tablename__ = "pedido"
# id_pedido = db.Column(db.Integer, primary_key=True)
# nome = db.Column(db.String)
# valor = db.Column(db.Float)
# qtd_ingrediente = db.Column(db.Integer)
# qtd_item_extra = db.Column(db.Integer)
# tipo_item = db.Column(db.String)
# item_extra = db.Column(db.String)
# id_produto = db.Column(db.Integer, db.ForeignKey('produto.id_produto'))
# produto = relationship("Produto_dao", back_populates="")
| 34.375
| 76
| 0.707273
| 78
| 550
| 4.782051
| 0.423077
| 0.171582
| 0.214477
| 0.182306
| 0.101877
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002155
| 0.156364
| 550
| 16
| 77
| 34.375
| 0.801724
| 0.767273
| 0
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| 0
| 0.050847
| 0
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| false
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| null | 0
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| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
7720594be1fbbd83a062b7329a8a5ccdccc54065
| 109
|
py
|
Python
|
social_oauth_token/apps.py
|
khasbilegt/django-social-auth-token
|
2562c12b2747207557bda9e0fff39b15bbb22537
|
[
"MIT"
] | null | null | null |
social_oauth_token/apps.py
|
khasbilegt/django-social-auth-token
|
2562c12b2747207557bda9e0fff39b15bbb22537
|
[
"MIT"
] | null | null | null |
social_oauth_token/apps.py
|
khasbilegt/django-social-auth-token
|
2562c12b2747207557bda9e0fff39b15bbb22537
|
[
"MIT"
] | 1
|
2021-11-08T07:09:45.000Z
|
2021-11-08T07:09:45.000Z
|
from django.apps import AppConfig
class SocialOauthTokenConfig(AppConfig):
name = "social_oauth_token"
| 18.166667
| 40
| 0.798165
| 12
| 109
| 7.083333
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137615
| 109
| 5
| 41
| 21.8
| 0.904255
| 0
| 0
| 0
| 0
| 0
| 0.165138
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
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| 1
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| 0
| null | 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
772cfe056716b53af0adc4c83c16484233dec372
| 167
|
py
|
Python
|
rlsuite/envs/gridworld/__init__.py
|
christopher-wolff/lab
|
3e26beb30bfb88fef79558a8c1584ddb6c1843e9
|
[
"MIT"
] | 2
|
2019-03-28T16:47:50.000Z
|
2019-04-08T04:50:50.000Z
|
rlsuite/envs/gridworld/__init__.py
|
christopher-wolff/rlsuite
|
3e26beb30bfb88fef79558a8c1584ddb6c1843e9
|
[
"MIT"
] | null | null | null |
rlsuite/envs/gridworld/__init__.py
|
christopher-wolff/rlsuite
|
3e26beb30bfb88fef79558a8c1584ddb6c1843e9
|
[
"MIT"
] | null | null | null |
from gym.envs.registration import register
register(
id='GridWorld-v0',
entry_point='rlsuite.envs.gridworld.gridworld:GridWorld',
max_episode_steps=50,
)
| 20.875
| 61
| 0.754491
| 21
| 167
| 5.857143
| 0.761905
| 0.292683
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02069
| 0.131737
| 167
| 7
| 62
| 23.857143
| 0.827586
| 0
| 0
| 0
| 0
| 0
| 0.323353
| 0.251497
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.166667
| 0
| 0.166667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
773cd0599249be90c24256de7dfd60ee4a466e7b
| 86
|
py
|
Python
|
test/first.py
|
zyj2614187/CANGKU01
|
9718e7fd8e5882914a69e1181dae07a9257d13dc
|
[
"MIT"
] | null | null | null |
test/first.py
|
zyj2614187/CANGKU01
|
9718e7fd8e5882914a69e1181dae07a9257d13dc
|
[
"MIT"
] | null | null | null |
test/first.py
|
zyj2614187/CANGKU01
|
9718e7fd8e5882914a69e1181dae07a9257d13dc
|
[
"MIT"
] | null | null | null |
a = 1
b = 2
c = a+b
print(c)
d= 5
e = 6
f = 7
k = 6
h = 50
j =522022
l= 5050
你是猪
| 4.777778
| 9
| 0.453488
| 24
| 86
| 1.625
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.346154
| 0.395349
| 86
| 17
| 10
| 5.058824
| 0.403846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.083333
| 1
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
774b737ce0ea4ccd49cf8c0f34d0766cc8c27e5c
| 76
|
py
|
Python
|
plotly/graph_objs/layout/polar/angularaxis/__init__.py
|
gnestor/plotly.py
|
a8ae062795ddbf9867b8578fe6d9e244948c15ff
|
[
"MIT"
] | 12
|
2020-04-18T18:10:22.000Z
|
2021-12-06T10:11:15.000Z
|
plotly/graph_objs/layout/polar/angularaxis/__init__.py
|
Vesauza/plotly.py
|
e53e626d59495d440341751f60aeff73ff365c28
|
[
"MIT"
] | 27
|
2020-04-28T21:23:12.000Z
|
2021-06-25T15:36:38.000Z
|
plotly/graph_objs/layout/polar/angularaxis/__init__.py
|
Vesauza/plotly.py
|
e53e626d59495d440341751f60aeff73ff365c28
|
[
"MIT"
] | 6
|
2020-04-18T23:07:08.000Z
|
2021-11-18T07:53:06.000Z
|
from ._tickformatstop import Tickformatstop
from ._tickfont import Tickfont
| 25.333333
| 43
| 0.868421
| 8
| 76
| 8
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 76
| 2
| 44
| 38
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
620f0621fbc1841939002f3e397639cd6abdebdb
| 3,482
|
py
|
Python
|
al/experiments/object_detection.py
|
kili-technology/active-learning
|
72dce7d91b988264dd7fa1a972d9af45e9648c4c
|
[
"Apache-2.0"
] | 3
|
2020-09-11T07:30:54.000Z
|
2021-04-17T07:45:05.000Z
|
al/experiments/object_detection.py
|
kili-technology/active-learning
|
72dce7d91b988264dd7fa1a972d9af45e9648c4c
|
[
"Apache-2.0"
] | null | null | null |
al/experiments/object_detection.py
|
kili-technology/active-learning
|
72dce7d91b988264dd7fa1a972d9af45e9648c4c
|
[
"Apache-2.0"
] | null | null | null |
import os
import numpy as np
from ..model.model_zoo import *
from ..model.ssd import SSDLearner
from ..dataset.pascal_voc import PascalVOCObjectDataset
from ..dataset.coco import COCOObjectDataset
from ..model.configs import cfg
def set_up_pascalvoc_detection(config, output_dir, logger, device=0, queries_name='queries.txt'):
logger.info('Setting up datasets...')
backbone = config['model']['backbone']
model, cfg = get_model_config(backbone, 'voc')
init_size = config['active_learning']['init_size']
index_train = np.arange(config['dataset']['train_size'])
index_test = np.arange(config['dataset']['test_size'])
logger_name = config['experiment']['logger_name']
dataset = PascalVOCObjectDataset(
index_train, n_init=init_size, output_dir=output_dir, cfg=cfg, queries_name=queries_name)
test_dataset = PascalVOCObjectDataset(
index_test, n_init=init_size, output_dir=output_dir, cfg=cfg, train=False, queries_name=queries_name)
dataset.set_validation_dataset(test_dataset.dataset)
logger.info(f'Dataset initial train size : {len(dataset.init_dataset)}')
logger.info(f'Dataset used train size : {len(dataset.dataset)}')
logger.info(f'Dataset initial test size : {len(test_dataset.init_dataset)}')
logger.info(f'Dataset test size : {len(test_dataset.dataset)}')
logger.info('Setting up models...')
learner = SSDLearner(model=model, cfg=cfg, logger_name=logger_name, device=device, dataset='voc')
return dataset, learner
def set_up_coco_object_detection(config, output_dir, logger, device=0, queries_name='queries.txt'):
logger.info('Setting up datasets...')
backbone = config['model']['backbone']
model, cfg = get_model_config(backbone, 'coco')
init_size = config['active_learning']['init_size']
index_train = np.arange(config['dataset']['train_size'])
index_test = np.arange(config['dataset']['test_size'])
logger_name = config['experiment']['logger_name']
dataset = COCOObjectDataset(
index_train, n_init=init_size, output_dir=output_dir, cfg=cfg, queries_name=queries_name)
test_dataset = COCOObjectDataset(
index_test, n_init=init_size, output_dir=output_dir, cfg=cfg, train=False, queries_name=queries_name)
logger.info(f'Dataset initial train size : {len(dataset.init_dataset)}')
logger.info(f'Dataset used train size : {len(dataset.dataset)}')
logger.info(f'Dataset initial test size : {len(test_dataset.init_dataset)}')
logger.info(f'Dataset test size : {len(test_dataset.dataset)}')
dataset.set_validation_dataset(test_dataset.dataset)
logger.info('Setting up models...')
learner = SSDLearner(model=model, cfg=cfg, logger_name=logger_name, device=device, dataset='coco')
return dataset, learner
def get_model_config(backbone, dataset):
config_path = os.getenv('MODULE_PATH')
if dataset == 'voc':
if backbone == 'mobilenet_v2':
config_file = 'mobilenet_v2_ssd320_voc0712.yaml'
elif backbone == 'vgg':
config_file = 'vgg_ssd300_voc0712.yaml'
elif dataset == 'coco':
if backbone == 'vgg':
config_file = 'vgg_ssd300_coco_trainval35k.yaml'
elif backbone == 'mobilenet_v2':
config_file = 'mobilenet_v2_ssd320_coco.yaml'
path = os.path.expanduser(os.path.join(config_path, config_file))
cfg.merge_from_file(path)
model = SSDDetector(cfg, backbone)
cfg.freeze()
return model, cfg
| 41.951807
| 109
| 0.716255
| 459
| 3,482
| 5.198257
| 0.165577
| 0.050293
| 0.064124
| 0.060352
| 0.740151
| 0.740151
| 0.715004
| 0.715004
| 0.676446
| 0.64627
| 0
| 0.009547
| 0.157668
| 3,482
| 83
| 110
| 41.951807
| 0.803955
| 0
| 0
| 0.46875
| 0
| 0
| 0.254953
| 0.09532
| 0
| 0
| 0
| 0
| 0
| 1
| 0.046875
| false
| 0
| 0.109375
| 0
| 0.203125
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
621ab5790701b88e269ef5a4c9b8c64356f52746
| 72
|
py
|
Python
|
__init__.py
|
5x/cryptography-gui-app
|
a65539cc59276da831cc9f401c77b19de2fe18ea
|
[
"MIT"
] | 1
|
2021-08-03T09:50:02.000Z
|
2021-08-03T09:50:02.000Z
|
__init__.py
|
5x/cryptography-gui-app
|
a65539cc59276da831cc9f401c77b19de2fe18ea
|
[
"MIT"
] | null | null | null |
__init__.py
|
5x/cryptography-gui-app
|
a65539cc59276da831cc9f401c77b19de2fe18ea
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python3,4
# -*- coding: utf-8 -*-
"""cryptography-gui-app"""
| 18
| 26
| 0.583333
| 10
| 72
| 4.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.046154
| 0.097222
| 72
| 3
| 27
| 24
| 0.6
| 0.861111
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
623cda82dc78bcb7c0c0435e69a56d92bf23248b
| 124
|
py
|
Python
|
setup.py
|
goude/thxtime
|
ecc41913624c1e3836ab4f2fcfeb23c377450061
|
[
"MIT"
] | null | null | null |
setup.py
|
goude/thxtime
|
ecc41913624c1e3836ab4f2fcfeb23c377450061
|
[
"MIT"
] | null | null | null |
setup.py
|
goude/thxtime
|
ecc41913624c1e3836ab4f2fcfeb23c377450061
|
[
"MIT"
] | null | null | null |
from setuptools import setup, find_packages
setup(
name="thxtime",
version="2.0.0",
packages=find_packages(),
)
| 17.714286
| 43
| 0.685484
| 16
| 124
| 5.1875
| 0.6875
| 0.289157
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.029412
| 0.177419
| 124
| 6
| 44
| 20.666667
| 0.784314
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.166667
| 0
| 0.166667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
62410e0fbb6abd0a88275e5da44046fea2fed835
| 123
|
py
|
Python
|
Socket/Socket/udp/udp_client.py
|
RolandBalabekyan1994/socket-socketserver
|
94ca247d1aa0e84b970d49b7e974e67932440b11
|
[
"MIT"
] | null | null | null |
Socket/Socket/udp/udp_client.py
|
RolandBalabekyan1994/socket-socketserver
|
94ca247d1aa0e84b970d49b7e974e67932440b11
|
[
"MIT"
] | null | null | null |
Socket/Socket/udp/udp_client.py
|
RolandBalabekyan1994/socket-socketserver
|
94ca247d1aa0e84b970d49b7e974e67932440b11
|
[
"MIT"
] | null | null | null |
import socket
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.sendto(b'Test message', ('localhost', 8888))
| 30.75
| 56
| 0.747967
| 18
| 123
| 5
| 0.666667
| 0.222222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036364
| 0.105691
| 123
| 4
| 57
| 30.75
| 0.781818
| 0
| 0
| 0
| 0
| 0
| 0.173554
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
6256e27a027c2617019ef8c7c0b4d00633bfd944
| 112
|
py
|
Python
|
20180616/templating_01.py
|
bijitchakraborty12/MyProjects01
|
503af4cd6e8fa0576add7ac64393f1b4a16456c7
|
[
"MIT"
] | null | null | null |
20180616/templating_01.py
|
bijitchakraborty12/MyProjects01
|
503af4cd6e8fa0576add7ac64393f1b4a16456c7
|
[
"MIT"
] | null | null | null |
20180616/templating_01.py
|
bijitchakraborty12/MyProjects01
|
503af4cd6e8fa0576add7ac64393f1b4a16456c7
|
[
"MIT"
] | null | null | null |
sentence='I am interested in {num}'
pi=3.14
print(sentence.format(num=pi))
e=2.712
print(sentence.format(num=e))
| 22.4
| 35
| 0.741071
| 22
| 112
| 3.772727
| 0.636364
| 0.120482
| 0.457831
| 0.53012
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.067308
| 0.071429
| 112
| 5
| 36
| 22.4
| 0.730769
| 0
| 0
| 0
| 0
| 0
| 0.212389
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
65504a54c18f87bed505d7919f810fcb92470f5c
| 93
|
py
|
Python
|
mvouchers/apps.py
|
silverline99/meal-voucher-app
|
baa629004c205732114f7b35ff4f93a2a461cbd1
|
[
"MIT"
] | null | null | null |
mvouchers/apps.py
|
silverline99/meal-voucher-app
|
baa629004c205732114f7b35ff4f93a2a461cbd1
|
[
"MIT"
] | null | null | null |
mvouchers/apps.py
|
silverline99/meal-voucher-app
|
baa629004c205732114f7b35ff4f93a2a461cbd1
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class MvouchersConfig(AppConfig):
name = 'mvouchers'
| 15.5
| 33
| 0.763441
| 10
| 93
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 93
| 5
| 34
| 18.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
6554c4524c237637492692e8b047f3d227565fe2
| 96
|
py
|
Python
|
quickcert.py
|
dedickinson/hub-util-tls
|
cff25cf45455f97c5654110b7b4ad903380b9d0e
|
[
"BSD-2-Clause"
] | null | null | null |
quickcert.py
|
dedickinson/hub-util-tls
|
cff25cf45455f97c5654110b7b4ad903380b9d0e
|
[
"BSD-2-Clause"
] | 4
|
2020-03-24T16:58:15.000Z
|
2021-06-01T23:28:02.000Z
|
quickcert.py
|
dedickinson/hub-util-tls
|
cff25cf45455f97c5654110b7b4ad903380b9d0e
|
[
"BSD-2-Clause"
] | null | null | null |
#!/usr/bin/env python3
# PYTHON_ARGCOMPLETE_OK
import quickcert
quickcert.QuickCertCli().run()
| 16
| 30
| 0.791667
| 12
| 96
| 6.166667
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011364
| 0.083333
| 96
| 6
| 30
| 16
| 0.829545
| 0.447917
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
65578b35b3e8467e311e7c6e421a770a28a92ea0
| 88
|
py
|
Python
|
dialog/apps.py
|
asmadotgh/neural_chat_web
|
1ef29cae7349ad945180adbd0a6d005087fe1365
|
[
"MIT"
] | 26
|
2019-06-26T06:15:35.000Z
|
2022-01-24T16:06:21.000Z
|
dialog/apps.py
|
asmadotgh/neural_chat_web
|
1ef29cae7349ad945180adbd0a6d005087fe1365
|
[
"MIT"
] | 2
|
2020-02-12T00:40:46.000Z
|
2021-06-10T21:36:22.000Z
|
dialog/apps.py
|
asmadotgh/neural_chat_web
|
1ef29cae7349ad945180adbd0a6d005087fe1365
|
[
"MIT"
] | 2
|
2019-09-18T08:06:42.000Z
|
2019-09-19T18:14:54.000Z
|
from django.apps import AppConfig
class DialogConfig(AppConfig):
name = 'dialog'
| 12.571429
| 33
| 0.738636
| 10
| 88
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 88
| 6
| 34
| 14.666667
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.069767
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
657ae7301cc5259ff530c0acb108f3507a549fab
| 277
|
py
|
Python
|
string_apostraphe.py
|
CrazyJ36/python
|
4cff6e7240672a273d978521bb511065f45d4312
|
[
"MIT"
] | null | null | null |
string_apostraphe.py
|
CrazyJ36/python
|
4cff6e7240672a273d978521bb511065f45d4312
|
[
"MIT"
] | null | null | null |
string_apostraphe.py
|
CrazyJ36/python
|
4cff6e7240672a273d978521bb511065f45d4312
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
# Testing apostraphes' in single quotes
# if I were to: print('he's done')
# error: compiler thinks the statement
# is ended at the apostraphe after 'he'.
# In order to print apostraphes and other
# characters like it, escape them:
print('he\'s done')
| 27.7
| 41
| 0.722022
| 45
| 277
| 4.444444
| 0.777778
| 0.07
| 0.08
| 0.12
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004348
| 0.169675
| 277
| 9
| 42
| 30.777778
| 0.865217
| 0.873646
| 0
| 0
| 0
| 0
| 0.107143
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
6580f66c87dc9a69012d50e7be434424964d3d52
| 54
|
py
|
Python
|
python/testData/completion/beforeImport/beforeImportAs.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/completion/beforeImport/beforeImportAs.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/completion/beforeImport/beforeImportAs.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
m<caret>
from source import my_foo as my_renamed_foo
| 13.5
| 43
| 0.814815
| 11
| 54
| 3.727273
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148148
| 54
| 3
| 44
| 18
| 0.891304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.5
| null | null | 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
6594981e278002d85bb3afe0cdcda0bfc6660714
| 332
|
py
|
Python
|
raylab/utils/types.py
|
angelolovatto/raylab
|
ebaea8df1a391fb844e75df62ccf1e2e07311d88
|
[
"MIT"
] | 29
|
2020-05-05T13:25:33.000Z
|
2022-01-03T14:12:29.000Z
|
raylab/utils/types.py
|
angelolovatto/raylab
|
ebaea8df1a391fb844e75df62ccf1e2e07311d88
|
[
"MIT"
] | 215
|
2019-11-26T12:59:39.000Z
|
2022-02-01T12:38:31.000Z
|
raylab/utils/types.py
|
angelolovatto/raylab
|
ebaea8df1a391fb844e75df62ccf1e2e07311d88
|
[
"MIT"
] | 7
|
2020-06-12T01:42:02.000Z
|
2021-05-27T03:40:42.000Z
|
"""Collection of type annotations."""
from typing import Callable, Dict, Tuple, Union
from torch import Tensor
DynamicsFn = Callable[[Tensor, Tensor], Tuple[Tensor, Tensor]]
RewardFn = Callable[[Tensor, Tensor, Tensor], Tensor]
StatDict = Dict[str, Union[float, int]]
TerminationFn = Callable[[Tensor, Tensor, Tensor], Tensor]
| 25.538462
| 62
| 0.740964
| 40
| 332
| 6.15
| 0.5
| 0.390244
| 0.292683
| 0.211382
| 0.260163
| 0
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| 0
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| 0
| 0.129518
| 332
| 12
| 63
| 27.666667
| 0.851211
| 0.093373
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
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| null | 1
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| 1
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| 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
659ae4eaf4c548a9ce8a6b81c0345c320f9bbce7
| 17,578
|
py
|
Python
|
tests/test_pipeline.py
|
scottmhamilton/phoenix_pipeline
|
a531696b83c5a3201b89df555e4e81d5a35a73b3
|
[
"MIT"
] | 42
|
2015-01-06T18:32:44.000Z
|
2021-09-08T22:31:34.000Z
|
tests/test_pipeline.py
|
scottmhamilton/phoenix_pipeline
|
a531696b83c5a3201b89df555e4e81d5a35a73b3
|
[
"MIT"
] | 24
|
2015-01-12T20:56:11.000Z
|
2017-05-01T14:55:00.000Z
|
tests/test_pipeline.py
|
scottmhamilton/phoenix_pipeline
|
a531696b83c5a3201b89df555e4e81d5a35a73b3
|
[
"MIT"
] | 29
|
2015-01-06T18:44:51.000Z
|
2020-07-13T02:57:01.000Z
|
from bson.objectid import ObjectId
import datetime
from petrarch import petrarch
from petrarch2 import petrarch2
formatted = [{u'language': u'english',
u'title': u'6 killed in attacks in Iraqi capital Friday',
u'url': u'http://www.menafn.com/1094827896/6-killed-in-attacks-in-Iraqi-capital-Friday?src=RSS',
u'stanford': 1,
u'content': u'BAGHDAD: At least six people, including a soldier, were killed in a spate of attacks across Iraqi capital Baghdad on Friday. A sniper opened fire on soldiers manning a checkpoint in southern Baghdad, killing a soldier and injuring three others, police officer Nader al-Janabi told Anadolu Agency. Two civilians were killed and six others injured in a bomb blast in al-Zafarana district in south-eastern Baghdad, he said. Three more civilians were killed and seven others injured in two bomb blasts in southern and northern Baghdad, according to al-Janabi. Iraqi officials often blame the attacks on the Daesh terrorist group, which overran vast swathes of territory in Iraq in 2014. ',
u'source': u'menafn_iraq',
u'parsed_sents': [u'(ROOT (S (NP (NNP BAGHDAD)) (: :) (NP (NP (QP (IN At) (JJS least) (CD six)) (NNS people)) (, ,) (PP (VBG including) (NP (DT a) (NN soldier))) (, ,)) (VP (VBD were) (VP (VBN killed) (PP (IN in) (NP (NP (DT a) (NN spate)) (PP (IN of) (NP (NNS attacks))))) (PP (IN across) (NP (JJ Iraqi) (NN capital) (NNP Baghdad))) (PP (IN on) (NP (NNP Friday))))) (. .)))',
u'(ROOT (S (NP (DT A) (NN sniper)) (VP (VBD opened) (NP (NN fire)) (PP (IN on) (S (S (NP (NNS soldiers)) (VP (VBG manning) (NP (NP (DT a) (NN checkpoint)) (PP (IN in) (NP (JJ southern) (NNP Baghdad)))) (, ,) (S (VP (VP (VBG killing) (NP (DT a) (NN soldier))) (CC and) (VP (VBG injuring) (NP (CD three) (NNS others))))))) (, ,) (NP (NNS police) (NN officer) (NNP Nader) (NNP al-Janabi)) (VP (VBD told) (NP (NNP Anadolu) (NNP Agency))) (. .))))))',
u'(ROOT (S (S (NP (CD Two) (NNS civilians)) (VP (VBD were) (VP (VP (VBN killed)) (CC and) (NP (NP (CD six) (NNS others)) (VP (VBN injured) (PP (IN in) (NP (NP (DT a) (NN bomb) (NN blast)) (PP (IN in) (NP (NP (NN al-Zafarana) (NN district)) (PP (IN in) (NP (JJ south-eastern) (NNP Baghdad)))))))))))) (, ,) (NP (PRP he)) (VP (VBD said)) (. .)))',
u'(ROOT (S (NP (CD Three) (JJR more) (NNS civilians)) (VP (VBD were) (VP (VP (VBN killed)) (CC and) (NP (NP (CD seven) (NNS others)) (VP (VBN injured) (PP (IN in) (NP (NP (CD two) (NN bomb) (NNS blasts)) (PP (IN in) (NP (ADJP (JJ southern) (CC and) (JJ northern)) (NNP Baghdad))))))) (, ,) (PP (VBG according) (PP (TO to) (NP (NNP al-Janabi)))))) (. .)))',
u'(ROOT (S (NP (JJ Iraqi) (NNS officials)) (ADVP (RB often)) (VP (VBP blame) (NP (NP (DT the) (NNS attacks)) (PP (IN on) (NP (NP (DT the) (NNP Daesh) (JJ terrorist) (NN group)) (, ,) (SBAR (WHNP (WDT which)) (S (VP (VBD overran) (NP (NP (JJ vast) (NNS swathes)) (PP (IN of) (NP (NP (NN territory)) (PP (IN in) (NP (NNP Iraq)))))) (PP (IN in) (NP (CD 2014)))))))))) (. .)))'],
u'date': u'160626',
u'date_added': datetime.datetime(2016, 6, 26, 19, 0, 17, 640000),
u'_id': ObjectId('57702641172ab87eb7dc98fa')},
{u'language': u'english',
u'title': u'Soldiers, Policemen Fight Over Rice',
u'url': u'http://www.thetidenewsonline.com/2016/06/24/soldiers-policemen-fight-over-rice/',
u'stanford': 1,
u'content': u'There was chaos at the Borno State Government House in Maiduguri, yesterday, as soldiers and policemen engaged in gun battle over rice meant for internally displaced persons. The Government House is besieged daily by thousands of internally displaced persons within Maiduguri metropolis, who choose to stay outside of the designated camps. The IDPs, who queue for hours to receive rice and other relief items, often cause gridlock around the Government House with many of them having to go back empty handed each day. The situation, however, turned violent, yesterday afternoon when the soldiers that were deployed to maintain law and order tried to benefit from the largese. The soldiers were said to have tried to force their way into the Deputy Governor\u2019s office, the place designated for the distribution, to get their vehicles filled. An attempt by the mobile policemen attached to the office to prevent the soldiers from achieving their goal led to a shootout. It was gathered that the soldiers fired several warning shots and the mobile policemen shot back in return, while also firing canisters of tear gas. Lucky Irabor, to get the furious soldiers to withdraw from the battle, which caused panic across Maiduguri. It was gathered that Irabor, the most senior military officer around, and the Commissioner of Police, Aminchi Baraya, subsequently visited the injured policeman at the hospital.',
u'source': u'nigeria_tidenews',
u'parsed_sents': [u'(ROOT (S (NP (EX There)) (VP (VBD was) (NP (NP (NN chaos)) (PP (IN at) (NP (NP (DT the) (NNP Borno) (NNP State) (NNP Government) (NNP House)) (PP (IN in) (NP (NNP Maiduguri))))) (, ,) (NP (NN yesterday)) (, ,)) (PP (IN as) (NP (NP (NNS soldiers) (CC and) (NNS policemen)) (VP (VBN engaged) (PP (IN in) (NP (NP (NN gun) (NN battle)) (PP (IN over) (NP (NP (NN rice)) (VP (VBN meant) (PP (IN for) (NP (ADJP (RB internally) (JJ displaced)) (NNS persons)))))))))))) (. .)))',
u'(ROOT (S (NP (DT The) (NNP Government) (NNP House)) (VP (VBZ is) (VP (VBN besieged) (ADVP (RB daily)) (PP (IN by) (NP (NP (NNS thousands)) (PP (IN of) (NP (NP (ADJP (RB internally) (JJ displaced)) (NNS persons)) (PP (IN within) (NP (NP (NNP Maiduguri) (NN metropolis)) (, ,) (SBAR (WHNP (WP who)) (S (VP (VBP choose) (S (VP (TO to) (VP (VB stay) (ADVP (IN outside) (PP (IN of) (NP (DT the) (VBN designated) (NNS camps)))))))))))))))))) (. .)))',
u'(ROOT (NP (NP (NP (DT The) (NNS IDPs)) (, ,) (SBAR (WHNP (WP who)) (S (VP (VB queue) (SBAR (IN for) (S (NP (NNS hours)) (VP (TO to) (VP (VB receive) (NP (NP (NN rice) (CC and) (JJ other) (NN relief) (NNS items)) (, ,) (S (ADVP (RB often)) (VP (VBP cause) (NP (NN gridlock)) (PP (IN around) (S (NP (NP (DT the) (NNP Government) (NNP House)) (PP (IN with) (NP (NP (JJ many)) (PP (IN of) (NP (PRP them)))))) (VP (VBG having) (S (VP (TO to) (VP (VB go) (NP (ADJP (RB back) (JJ empty)) (NN handed)) (NP (DT each) (NN day))))))))))))))))))) (. .)))',
u'(ROOT (S (S (NP (DT The) (NN situation)) (, ,) (ADVP (RB however)) (, ,) (VP (VBD turned) (ADJP (JJ violent)))) (, ,) (NP (NP (NN yesterday) (NN afternoon)) (SBAR (WHADVP (WRB when)) (S (NP (NP (DT the) (NNS soldiers)) (SBAR (WHNP (WDT that)) (S (VP (VBD were) (VP (VBN deployed) (S (VP (TO to) (VP (VP (VB maintain) (NP (NN law))) (CC and) (VP (NN order) (VP (VBD tried) (S (VP (TO to) (VP (VB benefit) (PP (IN from) (NP (DT the) (NN largese))))))))))))))))))) (. .)))',
u"(ROOT (S (NP (DT The) (NNS soldiers)) (VP (VBD were) (VP (VBN said) (S (VP (TO to) (VP (VB have) (VP (VBN tried) (S (VP (TO to) (VP (VB force) (NP (PRP$ their) (NN way)) (PP (IN into) (NP (NP (NP (DT the) (NNP Deputy) (NNP Governor) (POS 's)) (NN office)) (, ,) (NP (NP (DT the) (NN place)) (VP (VBN designated) (PP (IN for) (NP (DT the) (NN distribution))))) (, ,)))))) (S (VP (TO to) (VP (VB get) (S (NP (PRP$ their) (NNS vehicles)) (VP (VBN filled)))))))))))) (. .)))",
u'(ROOT (S (NP (NP (DT An) (NN attempt)) (PP (IN by) (NP (NP (DT the) (JJ mobile) (NNS policemen)) (VP (VBN attached) (PP (TO to) (NP (DT the) (NN office))) (S (VP (TO to) (VP (VB prevent) (NP (DT the) (NNS soldiers)) (PP (IN from) (S (VP (VBG achieving) (NP (PRP$ their) (NN goal)))))))))))) (VP (VBD led) (PP (TO to) (NP (DT a) (NN shootout)))) (. .)))',
u'(ROOT (S (NP (PRP It)) (VP (VBD was) (VP (VBN gathered) (SBAR (IN that) (S (NP (DT the) (NNS soldiers)) (VP (VBD fired) (SBAR (S (NP (NP (JJ several) (VBG warning) (NNS shots)) (CC and) (NP (DT the) (JJ mobile) (NNS policemen))) (VP (VBD shot) (ADVP (RB back)) (PP (IN in) (NP (NN return))) (, ,) (SBAR (IN while) (S (ADVP (RB also)) (VP (NN firing) (NP (NP (NNS canisters)) (PP (IN of) (S (VP (VB tear) (NP (NN gas))))))))))))))))) (. .)))'],
u'date': u'160624',
u'date_added': datetime.datetime(2016, 6, 26, 19, 0, 18),
u'_id': ObjectId('57702642172ab87eb5dc98e9')},
{ "_id" : ObjectId("57702678172ab87ec2dc9933"),
"content" : "BAGHDAD - A senior Iraqi commander said the city of Fallujah was \"fully liberated\" from Islamic State of Iraq and Syria (ISIS) militants on Sunday, after a more than monthlong military operation. Iraqi troops have entered the northwestern al-Julan neighborhood, the last area of Fallujah to remain under ISIS control, the head of the counterterrorism forces in the operation, Lt. Gen. Abdul-Wahab al-Saadi, told The Associated Press. Al-Saadi said the operation, which began in late May, \"is done and the city is fully liberated.\" The Iraqi army was backed by U.S.-led airstrikes and paramilitary troops, mostly Shiite militias. \"From the center of al-Julan neighborhood, we congratulate the Iraqi people and the commander in chief...and declare that the Fallujah fight is over,\" he told Iraqi state TV, flanked by military officers and soldiers. Some of the soldiers were shooting in the air, chanting and waving the Iraqi flag. He added that troops will start working on removing bombs from the city's streets and buildings. In a statement, the U.S. central military command overseeing the U.S.-led coalition in Iraq said: \"The Coalition continues to provide support through strikes, intelligence, and advice and assistance to the Iraqi Security Forces operating in Fallujah and will continue to do so through deliberate clearing operations.\" Prime Minister Haider al-Abadi declared victory in Fallujah over a week ago, after Iraqi forces advanced into the city center and took control of a government complex. He pledged that remaining pockets of ISIS fighters would be cleared out within hours, but fierce clashes on the city's northern and western edges persisted for days. Tens of thousands of people have fled the fighting, overwhelming camps for the displaced run by the government and aid groups. According to the U.N. refugee agency, more than 85,000 people have fled Fallujah and the surrounding area since the offensive began. The UNHCR and others have warned of dire conditions in the camps -- where temperatures are well over 40 degrees Celsius (104 F) and shelter is limited -- and have called for more funds to meet mounting needs. Fallujah, which is located about 40 miles west of Baghdad, was the first city to fall to IS, in January 2014. Fallujah was also a stronghold of Sunni insurgents following the U.S.-led invasion in 2003. More than 100 American soldiers died and hundreds more were wounded in intense, house-by-house fighting in Fallujah in 2004. ISIS extremists still control significant areas in northern and western Iraq, including the country's second-largest city, Mosul. The group declared an Islamic caliphate on the territory it holds in Iraq and Syria and at the height of its power was estimated to hold nearly a third of each country. More than 3.3 million Iraqis have fled their homes since ISIS swept across northern and western Iraq in the summer of 2014, according to U.N. figures. More than 40 percent of the displaced are from Anbar province, where Fallujah is located.",
"source" : "cbs_world",
"date" : "Sun, 26 Jun 2016 17:37:27 -0400",
"language" : "english",
"title" : "Iraq: Fallujah \"fully liberated\" after monthlong fight",
"url" : "http://www.cbsnews.com/news/iraqi-commander-fallujah-fully-liberated-after-a-month/",
"date_added" : datetime.datetime(2016, 6, 26, 19, 0, 18),
"stanford" : 1,
"parsed_sents" : [ "(ROOT (S (NP (NNP BAGHDAD) (: -) (NN A) (JJ senior) (JJ Iraqi) (NN commander)) (VP (VBD said) (SBAR (S (NP (NP (DT the) (NN city)) (PP (IN of) (NP (NNP Fallujah)))) (VP (VBD was) (`` ``) (VP (ADVP (RB fully)) (VBN liberated) ('' '') (PP (IN from) (NP (NP (JJ Islamic) (NN State) (PP (IN of) (NP (NP (NNP Iraq)) (CC and) (NP (NNP Syria) (PRN (-LRB- -LRB-) (NNP ISIS) (-RRB- -RRB-)) (NNS militants))))) (PP (IN on) (NP (NNP Sunday)))))) (, ,) (PP (IN after) (NP (DT a) (ADVP (JJR more) (IN than)) (JJ monthlong) (JJ military) (NN operation))))))) (. .)))",
"(ROOT (S (S (NP (JJ Iraqi) (NNS troops)) (VP (VBP have) (VP (VBN entered) (NP (DT the) (JJ northwestern) (JJ al-Julan) (NN neighborhood))))) (, ,) (NP (NP (NP (DT the) (JJ last) (NN area)) (PP (IN of) (NP (NNP Fallujah))) (S (VP (TO to) (VP (VB remain) (PP (IN under) (NP (NNP ISIS) (NN control))))))) (, ,) (NP (NP (DT the) (NN head)) (PP (IN of) (NP (NP (DT the) (NN counterterrorism) (NNS forces)) (PP (IN in) (NP (DT the) (NN operation)))))) (, ,) (NP (NNP Lt.) (NNP Gen.) (NNP Abdul-Wahab) (NNP al-Saadi)) (, ,)) (VP (VBD told) (NP (DT The) (NNP Associated) (NNP Press))) (. .)))",
"(ROOT (S (NP (NNP Al-Saadi)) (VP (VBD said) (SBAR (S (S (NP (NP (DT the) (NN operation)) (, ,) (SBAR (WHNP (WDT which)) (S (VP (VBD began) (PP (IN in) (NP (JJ late) (NNP May)))))) (, ,)) (`` ``) (VP (VBZ is) (VP (VBN done)))) (CC and) (S (NP (DT the) (NN city)) (VP (VBZ is) (ADVP (RB fully)) (VP (VBN liberated))))))) (. .) ('' '')))",
"(ROOT (S (`` ``) (S (PP (IN From) (NP (NP (DT the) (NN center)) (PP (IN of) (NP (JJ al-Julan) (NN neighborhood))))) (, ,) (NP (PRP we)) (VP (VP (VBP congratulate) (NP (NP (DT the) (JJ Iraqi) (NNS people)) (CC and) (NP (NP (DT the) (NN commander)) (PP (IN in) (NP (NN chief)))))) (: ...) (CC and) (VP (VB declare) (SBAR (IN that) (S (NP (DT the) (NNP Fallujah) (NN fight)) (VP (VBZ is) (ADVP (IN over)))))))) (, ,) ('' '') (NP (PRP he)) (VP (VBD told) (NP (JJ Iraqi) (NN state) (NN TV)) (, ,) (S (VP (VBN flanked) (PP (IN by) (NP (JJ military) (NNS officers) (CC and) (NNS soldiers)))))) (. .)))",
"(ROOT (S (PP (IN In) (NP (DT a) (NN statement))) (, ,) (NP (NP (DT the) (NNP U.S.) (JJ central) (JJ military) (NN command)) (VP (VBG overseeing) (NP (NP (DT the) (JJ U.S.-led) (NN coalition)) (PP (IN in) (NP (NNP Iraq)))))) (VP (VBD said) (: :) (`` ``) (S (NP (DT The) (NNP Coalition)) (VP (VP (VBZ continues) (S (VP (TO to) (VP (VB provide) (NP (NN support)) (PP (IN through) (NP (NP (NP (NNS strikes)) (, ,) (NP (NN intelligence)) (, ,) (CC and) (NP (NN advice))) (CC and) (NP (NP (NN assistance)) (PP (TO to) (NP (NP (DT the) (JJ Iraqi) (NN Security) (NNS Forces)) (VP (VBG operating) (PP (IN in) (NP (NNP Fallujah))))))))))))) (CC and) (VP (MD will) (VP (VB continue) (S (VP (TO to) (VP (VB do) (ADVP (RB so))))) (PP (IN through) (NP (JJ deliberate) (NN clearing) (NNS operations)))))))) (. .) ('' '')))",
"(ROOT (S (NP (PRP He)) (VP (VP (VBD pledged) (SBAR (IN that) (S (NP (NP (VBG remaining) (NNS pockets)) (PP (IN of) (NP (NNP ISIS) (NNS fighters)))) (VP (MD would) (VP (VB be) (VP (VBN cleared) (PRT (RP out)) (PP (IN within) (NP (NNS hours))))))))) (, ,) (CC but) (S (NP (NP (JJ fierce) (NNS clashes)) (PP (IN on) (NP (NP (DT the) (NN city) (POS 's)) (ADJP (JJ northern) (CC and) (JJ western)) (NNS edges)))) (VP (VBD persisted) (PP (IN for) (NP (NNS days)))))) (. .)))",
"(ROOT (S (NP (NP (NNS Tens)) (PP (IN of) (NP (NP (NNS thousands)) (PP (IN of) (NP (NNS people)))))) (VP (VBP have) (VP (VBN fled) (NP (NP (DT the) (NN fighting)) (, ,) (NP (NP (JJ overwhelming) (NNS camps)) (PP (IN for) (NP (DT the) (JJ displaced) (NN run)))) (PP (IN by) (NP (DT the) (NN government) (CC and) (NN aid) (NNS groups)))))) (. .)))" ] }]
def test_petr1_formatted_to_results():
petr1_results = petrarch.run_pipeline(formatted, write_output=False,
parsed=True)
correct1_results = {'57702678172ab87ec2dc9933':
[(u'20160626', u'IRQ', u'MED', u'010', u'57702678172ab87ec2dc9933_1',
'http://www.cbsnews.com/news/iraqi-commander-fallujah-fully-liberated-after-a-month/',
'cbs_world'),
(u'20160626', u'IRQMIL', u'IRQ', u'010', u'NAMED_TERROR_GROUP,1',
u'57702678172ab87ec2dc9933_0',
'http://www.cbsnews.com/news/iraqi-commander-fallujah-fully-liberated-after-a-month/',
'cbs_world')
]}
assert petr1_results == correct1_results
def test_petr2_formatted_to_results():
petr2_results = petrarch2.run_pipeline(formatted, write_output=False,
parsed=True)
correct2_results = {'57702678172ab87ec2dc9933':
[(u'20160626', u'IRQMIL', u'MED', u'010', u'57702678172ab87ec2dc9933_1',
'http://www.cbsnews.com/news/iraqi-commander-fallujah-fully-liberated-after-a-month/',
'cbs_world'),
(u'20160626', u'IRQMIL', u'IRQ', u'010', u'NAMED_TERROR_GROUP,1', u'57702678172ab87ec2dc9933_0',
'http://www.cbsnews.com/news/iraqi-commander-fallujah-fully-liberated-after-a-month/',
'cbs_world')
],
'57702642172ab87eb5dc98e9':
[(u'20160624', u'NGAPPL', u'---GOV', u'191', u'REFUGEES,1', u'57702642172ab87eb5dc98e9_1',
u'http://www.thetidenewsonline.com/2016/06/24/soldiers-policemen-fight-over-rice/',
u'nigeria_tidenews')],
'57702641172ab87eb7dc98fa':
[(u'20160626', u'IRQ', u'IMGMUSISIUAF', u'111', u'TERROR,1',
u'57702641172ab87eb7dc98fa_4',
u'http://www.menafn.com/1094827896/6-killed-in-attacks-in-Iraqi-capital-Friday?src=RSS',
u'menafn_iraq'),
(u'20160626', u'---CVL', u'IRQ', u'190', u'57702641172ab87eb7dc98fa_3',
u'http://www.menafn.com/1094827896/6-killed-in-attacks-in-Iraqi-capital-Friday?src=RSS',
u'menafn_iraq')]}
assert petr2_results == correct2_results
| 191.065217
| 3,050
| 0.641313
| 2,829
| 17,578
| 3.967126
| 0.180983
| 0.022097
| 0.024949
| 0.017642
| 0.290386
| 0.207075
| 0.16582
| 0.14105
| 0.107191
| 0.107191
| 0
| 0.035612
| 0.182103
| 17,578
| 91
| 3,051
| 193.164835
| 0.745009
| 0
| 0
| 0.16092
| 0
| 0.402299
| 0.870342
| 0.025147
| 0
| 0
| 0
| 0
| 0.022989
| 1
| 0.022989
| false
| 0
| 0.045977
| 0
| 0.068966
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
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| 1
| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
65a778d34add6253eb7bc11de616c677109c2362
| 93
|
py
|
Python
|
ImageWork/apps.py
|
imsks/ImageN
|
58d45280985799361de002cb5d1460c2a7dc6ecd
|
[
"MIT"
] | 1
|
2021-08-05T09:10:49.000Z
|
2021-08-05T09:10:49.000Z
|
ImageWork/apps.py
|
imsks/ImageN
|
58d45280985799361de002cb5d1460c2a7dc6ecd
|
[
"MIT"
] | null | null | null |
ImageWork/apps.py
|
imsks/ImageN
|
58d45280985799361de002cb5d1460c2a7dc6ecd
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class ImageworkConfig(AppConfig):
name = 'ImageWork'
| 15.5
| 33
| 0.763441
| 10
| 93
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 93
| 5
| 34
| 18.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
65a7bc1b40d4add37a7b00a107311cc01ffdb566
| 2,613
|
py
|
Python
|
resources/dot_PyCharm/system/python_stubs/-762174762/PySide/QtGui/QGroupBox.py
|
basepipe/developer_onboarding
|
05b6a776f8974c89517868131b201f11c6c2a5ad
|
[
"MIT"
] | 1
|
2020-04-20T02:27:20.000Z
|
2020-04-20T02:27:20.000Z
|
resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QGroupBox.py
|
basepipe/developer_onboarding
|
05b6a776f8974c89517868131b201f11c6c2a5ad
|
[
"MIT"
] | null | null | null |
resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QGroupBox.py
|
basepipe/developer_onboarding
|
05b6a776f8974c89517868131b201f11c6c2a5ad
|
[
"MIT"
] | null | null | null |
# encoding: utf-8
# module PySide.QtGui
# from C:\Python27\lib\site-packages\PySide\QtGui.pyd
# by generator 1.147
# no doc
# imports
import PySide.QtCore as __PySide_QtCore
import Shiboken as __Shiboken
from QWidget import QWidget
class QGroupBox(QWidget):
# no doc
def alignment(self, *args, **kwargs): # real signature unknown
pass
def changeEvent(self, *args, **kwargs): # real signature unknown
pass
def childEvent(self, *args, **kwargs): # real signature unknown
pass
def clicked(self, *args, **kwargs): # real signature unknown
""" Signal """
pass
def event(self, *args, **kwargs): # real signature unknown
pass
def focusInEvent(self, *args, **kwargs): # real signature unknown
pass
def initStyleOption(self, *args, **kwargs): # real signature unknown
pass
def isCheckable(self, *args, **kwargs): # real signature unknown
pass
def isChecked(self, *args, **kwargs): # real signature unknown
pass
def isFlat(self, *args, **kwargs): # real signature unknown
pass
def minimumSizeHint(self, *args, **kwargs): # real signature unknown
pass
def mouseMoveEvent(self, *args, **kwargs): # real signature unknown
pass
def mousePressEvent(self, *args, **kwargs): # real signature unknown
pass
def mouseReleaseEvent(self, *args, **kwargs): # real signature unknown
pass
def paintEvent(self, *args, **kwargs): # real signature unknown
pass
def resizeEvent(self, *args, **kwargs): # real signature unknown
pass
def setAlignment(self, *args, **kwargs): # real signature unknown
pass
def setCheckable(self, *args, **kwargs): # real signature unknown
pass
def setChecked(self, *args, **kwargs): # real signature unknown
pass
def setFlat(self, *args, **kwargs): # real signature unknown
pass
def setTitle(self, *args, **kwargs): # real signature unknown
pass
def title(self, *args, **kwargs): # real signature unknown
pass
def toggled(self, *args, **kwargs): # real signature unknown
""" Signal """
pass
def __init__(self, *args, **kwargs): # real signature unknown
pass
@staticmethod # known case of __new__
def __new__(S, *more): # real signature unknown; restored from __doc__
""" T.__new__(S, ...) -> a new object with type S, a subtype of T """
pass
staticMetaObject = None # (!) real value is '<PySide.QtCore.QMetaObject object at 0x0000000003FAD6C8>'
| 26.663265
| 106
| 0.63452
| 299
| 2,613
| 5.461538
| 0.270903
| 0.19902
| 0.306185
| 0.264544
| 0.608083
| 0.608083
| 0.608083
| 0.584813
| 0.057563
| 0
| 0
| 0.010283
| 0.255645
| 2,613
| 97
| 107
| 26.938144
| 0.829306
| 0.346345
| 0
| 0.446429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.446429
| false
| 0.446429
| 0.053571
| 0
| 0.535714
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
65b249377623a307c87db1a62945b62ba3b4ab64
| 1,091
|
py
|
Python
|
data/train/python/65b249377623a307c87db1a62945b62ba3b4ab64fabfile.py
|
harshp8l/deep-learning-lang-detection
|
2a54293181c1c2b1a2b840ddee4d4d80177efb33
|
[
"MIT"
] | 84
|
2017-10-25T15:49:21.000Z
|
2021-11-28T21:25:54.000Z
|
data/train/python/65b249377623a307c87db1a62945b62ba3b4ab64fabfile.py
|
vassalos/deep-learning-lang-detection
|
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
|
[
"MIT"
] | 5
|
2018-03-29T11:50:46.000Z
|
2021-04-26T13:33:18.000Z
|
data/train/python/65b249377623a307c87db1a62945b62ba3b4ab64fabfile.py
|
vassalos/deep-learning-lang-detection
|
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
|
[
"MIT"
] | 24
|
2017-11-22T08:31:00.000Z
|
2022-03-27T01:22:31.000Z
|
from fabric.api import local, run, env, settings
from fabric.context_managers import lcd
def less():
local("lessc mcmun/static/css/mcmun.less -x > mcmun/static/css/mcmun.css")
def up():
local("python manage.py runserver")
def dump():
local("python manage.py dumpdata --indent=4 > backup.json")
def static():
local("python manage.py collectstatic --noinput")
def restart():
local('kill -HUP `cat /tmp/gunicorn.pid`')
def stats():
local('python manage.py get_registration_stats')
def pubcrawl():
local('python manage.py get_pubcrawl_stats')
def sh():
local('python manage.py shell')
def awards():
local('python manage.py generate_awards_slideshow awards.svg')
local('inkscapeslide updated_awards.svg')
def check():
local('python manage.py check_assignments')
def badges():
local('python manage.py get_badge_names')
local('cp badges.csv badges')
# Generate additions and deletions since last commit
with lcd('badges'):
local('git diff | grep "^-" > deleted.csv')
local('git diff | grep "^+" > added.csv')
| 24.795455
| 78
| 0.683776
| 149
| 1,091
| 4.932886
| 0.463087
| 0.134694
| 0.208163
| 0.232653
| 0.089796
| 0
| 0
| 0
| 0
| 0
| 0
| 0.001112
| 0.175985
| 1,091
| 43
| 79
| 25.372093
| 0.816463
| 0.04583
| 0
| 0
| 0
| 0.034483
| 0.532243
| 0.096246
| 0
| 0
| 0
| 0
| 0
| 1
| 0.37931
| true
| 0
| 0.068966
| 0
| 0.448276
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
65bf77b6d01ccda5cc2c02dde4df96904a41bd27
| 174
|
py
|
Python
|
newsCrawl/fakeNews/index/views.py
|
ARIF-KHAN-420/Fake_News
|
acfbffcce454afc09c4a7b06205c1a632c11f822
|
[
"MIT"
] | 1
|
2022-01-03T17:54:03.000Z
|
2022-01-03T17:54:03.000Z
|
newsCrawl/fakeNews/index/views.py
|
arifkhan-silicornya/Fake_News
|
acfbffcce454afc09c4a7b06205c1a632c11f822
|
[
"MIT"
] | null | null | null |
newsCrawl/fakeNews/index/views.py
|
arifkhan-silicornya/Fake_News
|
acfbffcce454afc09c4a7b06205c1a632c11f822
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
# Create your views here.
def index(request):
data = {'d' : "Copy a NEWS and paste it."}
return render(request,'index.html',data)
| 29
| 46
| 0.695402
| 26
| 174
| 4.653846
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.178161
| 174
| 6
| 47
| 29
| 0.846154
| 0.132184
| 0
| 0
| 0
| 0
| 0.24
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
029c17f331537c0184fca697765c9274a96aca9f
| 23
|
py
|
Python
|
fastai/__init__.py
|
janvdp/fastai
|
ec06bc4e5e445b9d963d4e029466050bfeb1db6c
|
[
"Apache-2.0"
] | null | null | null |
fastai/__init__.py
|
janvdp/fastai
|
ec06bc4e5e445b9d963d4e029466050bfeb1db6c
|
[
"Apache-2.0"
] | null | null | null |
fastai/__init__.py
|
janvdp/fastai
|
ec06bc4e5e445b9d963d4e029466050bfeb1db6c
|
[
"Apache-2.0"
] | null | null | null |
__version__ = "2.1.9"
| 7.666667
| 21
| 0.608696
| 4
| 23
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 0.173913
| 23
| 2
| 22
| 11.5
| 0.368421
| 0
| 0
| 0
| 0
| 0
| 0.227273
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
02beacd61f9882a976c73d37846fb6635b38fca9
| 28
|
py
|
Python
|
maglearn_back/api/__init__.py
|
maglearn/maglearn-back
|
cb5d8623f26e207b870c09c80cbc59911ab23794
|
[
"MIT"
] | null | null | null |
maglearn_back/api/__init__.py
|
maglearn/maglearn-back
|
cb5d8623f26e207b870c09c80cbc59911ab23794
|
[
"MIT"
] | null | null | null |
maglearn_back/api/__init__.py
|
maglearn/maglearn-back
|
cb5d8623f26e207b870c09c80cbc59911ab23794
|
[
"MIT"
] | null | null | null |
"""
API implementation.
"""
| 7
| 19
| 0.607143
| 2
| 28
| 8.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 28
| 3
| 20
| 9.333333
| 0.708333
| 0.678571
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
02bf1efa9fc21b10ade5e916aca00ef29f6df74d
| 2,010
|
py
|
Python
|
tests/admin_docs/models.py
|
ni-ning/django
|
2e7ba6057cfc82a15a22b6021cd60cf307152e2d
|
[
"CNRI-Python-GPL-Compatible",
"BSD-3-Clause"
] | 19
|
2015-07-07T02:08:59.000Z
|
2021-11-08T11:05:40.000Z
|
tests/admin_docs/models.py
|
ni-ning/django
|
2e7ba6057cfc82a15a22b6021cd60cf307152e2d
|
[
"CNRI-Python-GPL-Compatible",
"BSD-3-Clause"
] | 57
|
2018-10-08T12:37:30.000Z
|
2018-10-08T17:39:26.000Z
|
tests/admin_docs/models.py
|
ni-ning/django
|
2e7ba6057cfc82a15a22b6021cd60cf307152e2d
|
[
"CNRI-Python-GPL-Compatible",
"BSD-3-Clause"
] | 145
|
2019-03-14T18:54:45.000Z
|
2022-03-04T20:25:31.000Z
|
"""
Models for testing various aspects of the djang.contrib.admindocs app
"""
from django.db import models
class Company(models.Model):
name = models.CharField(max_length=200)
class Group(models.Model):
name = models.CharField(max_length=200)
class Family(models.Model):
last_name = models.CharField(max_length=200)
class Person(models.Model):
"""
Stores information about a person, related to :model:`myapp.Company`.
**Notes**
Use ``save_changes()`` when saving this object.
``company``
Field storing :model:`myapp.Company` where the person works.
(DESCRIPTION)
.. raw:: html
:file: admin_docs/evilfile.txt
.. include:: admin_docs/evilfile.txt
"""
first_name = models.CharField(max_length=200, help_text="The person's first name")
last_name = models.CharField(max_length=200, help_text="The person's last name")
company = models.ForeignKey(Company, models.CASCADE, help_text="place of work")
family = models.ForeignKey(Family, models.SET_NULL, related_name='+', null=True)
groups = models.ManyToManyField(Group, help_text="has membership")
def _get_full_name(self):
return "%s %s" % (self.first_name, self.last_name)
def rename_company(self, new_name):
self.company.name = new_name
self.company.save()
return new_name
def dummy_function(self, baz, rox, *some_args, **some_kwargs):
return some_kwargs
@property
def a_property(self):
return 'a_property'
def suffix_company_name(self, suffix='ltd'):
return self.company.name + suffix
def add_image(self):
pass
def delete_image(self):
pass
def save_changes(self):
pass
def set_status(self):
pass
def get_full_name(self):
"""
Get the full name of the person
"""
return self._get_full_name()
def get_status_count(self):
return 0
def get_groups_list(self):
return []
| 23.647059
| 86
| 0.656716
| 264
| 2,010
| 4.82197
| 0.359848
| 0.037706
| 0.074627
| 0.08641
| 0.213669
| 0.185389
| 0.185389
| 0.150825
| 0.150825
| 0.076984
| 0
| 0.010369
| 0.232338
| 2,010
| 84
| 87
| 23.928571
| 0.814647
| 0.204975
| 0
| 0.15
| 0
| 0
| 0.059868
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0.1
| 0.025
| 0.15
| 0.825
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
02d0ddb6f5072c58acc6615cd782451b199d2579
| 796
|
py
|
Python
|
test/e2e2/spec/test_api_domains.py
|
peterthomassen/desec-stack
|
436e48e8fc3f55ecf0b0e6a57a735a899a736f19
|
[
"MIT"
] | 197
|
2016-10-13T16:44:54.000Z
|
2022-03-24T08:33:25.000Z
|
test/e2e2/spec/test_api_domains.py
|
peterthomassen/desec-stack
|
436e48e8fc3f55ecf0b0e6a57a735a899a736f19
|
[
"MIT"
] | 455
|
2016-12-08T15:23:04.000Z
|
2022-03-29T12:58:02.000Z
|
test/e2e2/spec/test_api_domains.py
|
peterthomassen/desec-stack
|
436e48e8fc3f55ecf0b0e6a57a735a899a736f19
|
[
"MIT"
] | 25
|
2016-10-13T16:45:02.000Z
|
2022-02-23T17:57:04.000Z
|
from conftest import DeSECAPIV1Client, NSLordClient, random_domainname
def test_create(api_user: DeSECAPIV1Client):
assert len(api_user.domain_list()) == 0
assert api_user.domain_create(random_domainname()).status_code == 201
assert len(api_user.domain_list()) == 1
def test_get(api_user_domain: DeSECAPIV1Client):
domain = api_user_domain.get(f"/domains/{api_user_domain.domain}/").json()
assert NSLordClient.query(api_user_domain.domain, 'CDS')[1] == set(domain['keys'][0]['ds'])
assert domain['name'] == api_user_domain.domain
def test_destroy(api_user_domain: DeSECAPIV1Client):
n = len(api_user_domain.domain_list())
assert api_user_domain.domain_destroy(api_user_domain.domain).status_code == 204
assert len(api_user_domain.domain_list()) == n - 1
| 39.8
| 95
| 0.753769
| 113
| 796
| 4.982301
| 0.300885
| 0.174068
| 0.300178
| 0.236234
| 0.195382
| 0.184725
| 0
| 0
| 0
| 0
| 0
| 0.021368
| 0.11809
| 796
| 19
| 96
| 41.894737
| 0.780627
| 0
| 0
| 0
| 0
| 0
| 0.059045
| 0.042714
| 0
| 0
| 0
| 0
| 0.538462
| 1
| 0.230769
| false
| 0
| 0.076923
| 0
| 0.307692
| 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
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
02d73060a3dcc8c2a05ca0f279e7fec13e835925
| 220
|
py
|
Python
|
classifiers/abs_classifier.py
|
eyalho/NetML-Competition2020
|
cdf7b21642a8ce1ff8cc4c3ba7ed7fc6e1a91a81
|
[
"BSD-2-Clause"
] | null | null | null |
classifiers/abs_classifier.py
|
eyalho/NetML-Competition2020
|
cdf7b21642a8ce1ff8cc4c3ba7ed7fc6e1a91a81
|
[
"BSD-2-Clause"
] | null | null | null |
classifiers/abs_classifier.py
|
eyalho/NetML-Competition2020
|
cdf7b21642a8ce1ff8cc4c3ba7ed7fc6e1a91a81
|
[
"BSD-2-Clause"
] | null | null | null |
from abc import abstractmethod, ABC
class ABSClassifier(ABC):
@abstractmethod
def train(self, X_train, y_train, X_val=None, y_val=None):
pass
@abstractmethod
def predict(self, X):
pass
| 18.333333
| 62
| 0.663636
| 29
| 220
| 4.896552
| 0.517241
| 0.239437
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 220
| 11
| 63
| 20
| 0.860606
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 0.125
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
02ddcdd1aebe365b91caeb3d21bf2eeeb7c0ad2f
| 174
|
py
|
Python
|
min_number.py
|
tpaul93/LearningPython
|
b537ebbb4c14910a90245ef5956ab2b5af122084
|
[
"MIT"
] | null | null | null |
min_number.py
|
tpaul93/LearningPython
|
b537ebbb4c14910a90245ef5956ab2b5af122084
|
[
"MIT"
] | null | null | null |
min_number.py
|
tpaul93/LearningPython
|
b537ebbb4c14910a90245ef5956ab2b5af122084
|
[
"MIT"
] | null | null | null |
def min_number(num_list):
min_num = None
for num in num_list:
if min_num is None or min_num > num:
min_num = num
return min_num
| 19.333333
| 44
| 0.563218
| 28
| 174
| 3.214286
| 0.428571
| 0.333333
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.390805
| 174
| 8
| 45
| 21.75
| 0.849057
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
02f6706a83d53aa25257f2f4d7aa07828505aa38
| 141
|
py
|
Python
|
sol_validator/apps.py
|
kushtrimmh/sol_validator
|
904e6a89cb8a5b332bf03602903fc9f3ee724e82
|
[
"BSD-2-Clause"
] | null | null | null |
sol_validator/apps.py
|
kushtrimmh/sol_validator
|
904e6a89cb8a5b332bf03602903fc9f3ee724e82
|
[
"BSD-2-Clause"
] | null | null | null |
sol_validator/apps.py
|
kushtrimmh/sol_validator
|
904e6a89cb8a5b332bf03602903fc9f3ee724e82
|
[
"BSD-2-Clause"
] | null | null | null |
from __future__ import unicode_literals
from django.apps import AppConfig
class SolValidatorConfig(AppConfig):
name = 'sol_validator'
| 17.625
| 39
| 0.808511
| 16
| 141
| 6.75
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141844
| 141
| 7
| 40
| 20.142857
| 0.892562
| 0
| 0
| 0
| 0
| 0
| 0.092199
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
f30be977831e8d7d5d52cff5dcb1ef91e7ff4c2b
| 6,606
|
py
|
Python
|
seed_services_cli/tests/test_auth.py
|
praekeltfoundation/seed-services-cli
|
943fca5e70be086d4f29fd580103d7647a81f99a
|
[
"BSD-3-Clause"
] | null | null | null |
seed_services_cli/tests/test_auth.py
|
praekeltfoundation/seed-services-cli
|
943fca5e70be086d4f29fd580103d7647a81f99a
|
[
"BSD-3-Clause"
] | null | null | null |
seed_services_cli/tests/test_auth.py
|
praekeltfoundation/seed-services-cli
|
943fca5e70be086d4f29fd580103d7647a81f99a
|
[
"BSD-3-Clause"
] | null | null | null |
""" Tests for seed_services_cli.identity_store """
from unittest import TestCase
from click.testing import CliRunner
from seed_services_cli.main import cli
import responses
import json
class TestSendCommand(TestCase):
def setUp(self):
self.runner = CliRunner()
def tearDown(self):
pass
def invoke_user_add(self, args, first_name="First", last_name="Last",
email="test@example.com", password="pass",
admin=False):
if admin:
args = args + ["--admin"]
return self.runner.invoke(cli, [
'auth-user-add',
'--first_name', first_name,
'--last_name', last_name,
'--email', email,
'--password', password,
] + args)
def invoke_user_change_password(self, args, email, password):
return self.runner.invoke(cli, [
'auth-user-change-password',
'--email', email,
'--password', password,
] + args)
def invoke_user_add_team(self, args, user=2, team=3):
return self.runner.invoke(cli, [
'auth-user-add-team',
'--user', user,
'--team', team,
] + args)
def test_user_add_help(self):
result = self.runner.invoke(cli, ['auth-user-add', '--help'])
self.assertEqual(result.exit_code, 0)
self.assertTrue(
"Create a user"
in result.output)
@responses.activate
def test_user_add_no_details(self):
# setup
login_response = {
"token": "3e6de6f2cace86d3ac22d0a58e652f4b283ab58c"
}
responses.add(responses.POST,
"http://auth.example.org/user/tokens/",
json=login_response, status=201)
result = self.runner.invoke(cli, ['auth-user-add'])
self.assertEqual(result.exit_code, 2)
self.assertTrue(
"Please specify all new user information. See --help."
in result.output)
@responses.activate
def test_user_add(self):
# setup
login_response = {
"token": "3e6de6f2cace86d3ac22d0a58e652f4b283ab58c"
}
responses.add(responses.POST,
"http://auth.example.org/user/tokens/",
json=login_response, status=201)
user_response = {
"id": "3",
"url": "http://auth.example.org/users/9/",
"first_name": "First",
"last_name": "Last",
"email": "test@example.com",
"admin": False,
"teams": [],
"organizations": [],
"active": False
}
responses.add(responses.POST,
"http://auth.example.org/users/",
json=user_response, status=200)
# Execute
result = self.invoke_user_add([])
# Check
self.assertEqual(result.exit_code, 0)
self.assertTrue("Creating account for test@example.com"
in result.output)
self.assertTrue("Created user. ID is 3." in result.output)
self.assertEqual(len(responses.calls), 2)
self.assertEqual(responses.calls[1].request.url,
"http://auth.example.org/users/")
@responses.activate
def test_user_add_admin(self):
# setup
login_response = {
"token": "3e6de6f2cace86d3ac22d0a58e652f4b283ab58c"
}
responses.add(responses.POST,
"http://auth.example.org/user/tokens/",
json=login_response, status=201)
user_response = {
"id": "3",
"url": "http://auth.example.org/users/9/",
"first_name": "First",
"last_name": "Last",
"email": "test@example.com",
"admin": False,
"teams": [],
"organizations": [],
"active": True
}
responses.add(responses.POST,
"http://auth.example.org/users/",
json=user_response, status=200)
# Execute
result = self.invoke_user_add([], admin=True)
# Check
self.assertEqual(result.exit_code, 0)
self.assertTrue("Creating account for test@example.com"
in result.output)
self.assertTrue("Created user. ID is 3." in result.output)
self.assertEqual(len(responses.calls), 2)
self.assertEqual(responses.calls[1].request.url,
"http://auth.example.org/users/")
@responses.activate
def test_user_change_password(self):
login_response = {
"token": "3e6de6f2cace86d3ac22d0a58e652f4b283ab58c"
}
responses.add(responses.POST,
"http://auth.example.org/user/tokens/",
json=login_response, status=201)
users_response = [{
'email': 'test@example.org',
}, {
'id': 2,
'email': 'test2@example.org'
}]
responses.add(responses.GET,
"http://auth.example.org/users/",
json=users_response, status=200)
responses.add(responses.PUT,
"http://auth.example.org/users/2/",
json={}, status=200)
result = self.invoke_user_change_password(
[], email='test2@example.org', password='testpass')
self.assertEqual(result.exit_code, 0)
self.assertTrue(
'Changing password for test2@example.org' in result.output)
self.assertEqual(len(responses.calls), 3)
self.assertEqual(
json.loads(responses.calls[2].request.body)['password'],
'testpass')
def test_user_add_team_help(self):
result = self.runner.invoke(cli, ['auth-user-add-team', '--help'])
self.assertEqual(result.exit_code, 0)
self.assertTrue(
"Add a user to a team"
in result.output)
@responses.activate
def test_user_add_user_team_no_details(self):
# setup
login_response = {
"token": "3e6de6f2cace86d3ac22d0a58e652f4b283ab58c"
}
responses.add(responses.POST,
"http://auth.example.org/user/tokens/",
json=login_response, status=201)
result = self.runner.invoke(cli, ['auth-user-add-team'])
self.assertEqual(result.exit_code, 2)
self.assertTrue(
"Please specify user and team. See --help."
in result.output)
| 34.768421
| 74
| 0.54284
| 666
| 6,606
| 5.267267
| 0.156156
| 0.048461
| 0.055587
| 0.066705
| 0.754846
| 0.737172
| 0.72862
| 0.719213
| 0.647377
| 0.579247
| 0
| 0.035779
| 0.331517
| 6,606
| 189
| 75
| 34.952381
| 0.758605
| 0.014532
| 0
| 0.57764
| 0
| 0
| 0.219058
| 0.034637
| 0
| 0
| 0
| 0
| 0.136646
| 1
| 0.074534
| false
| 0.074534
| 0.031056
| 0.012422
| 0.130435
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
f31d784af40847e1252eed057778d97c47adecaf
| 122
|
py
|
Python
|
mix-printlist.py
|
Wikinaut/auto3mix
|
220ebafcd5ca231918da5eb878b4187be960f10f
|
[
"Unlicense"
] | 2
|
2020-04-06T13:56:59.000Z
|
2021-01-21T22:49:24.000Z
|
mix-printlist.py
|
Wikinaut/auto3mix
|
220ebafcd5ca231918da5eb878b4187be960f10f
|
[
"Unlicense"
] | null | null | null |
mix-printlist.py
|
Wikinaut/auto3mix
|
220ebafcd5ca231918da5eb878b4187be960f10f
|
[
"Unlicense"
] | 1
|
2020-04-06T13:57:48.000Z
|
2020-04-06T13:57:48.000Z
|
from glob import glob
from pydub import AudioSegment
i = 0
for name in sorted(glob("*.mp3")):
i = i+1
print name
| 15.25
| 34
| 0.663934
| 21
| 122
| 3.857143
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.032258
| 0.237705
| 122
| 7
| 35
| 17.428571
| 0.83871
| 0
| 0
| 0
| 0
| 0
| 0.040984
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.333333
| null | null | 0.166667
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f3237c5bfd14d351a17d41d6ba9c263015e28fed
| 808
|
py
|
Python
|
djangoplicity/contacts/migrations/0009_auto_20201222_2252.py
|
djangoplicity/djangoplicity-contacts
|
e873b0d6dad3e04adfb567380df092460984b25c
|
[
"BSD-3-Clause"
] | null | null | null |
djangoplicity/contacts/migrations/0009_auto_20201222_2252.py
|
djangoplicity/djangoplicity-contacts
|
e873b0d6dad3e04adfb567380df092460984b25c
|
[
"BSD-3-Clause"
] | 4
|
2021-01-07T05:30:10.000Z
|
2021-12-08T16:23:09.000Z
|
djangoplicity/contacts/migrations/0009_auto_20201222_2252.py
|
djangoplicity/djangoplicity-contacts
|
e873b0d6dad3e04adfb567380df092460984b25c
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.29 on 2021-01-07 00:36
# IMPORTANT: This file was renamed on purpose to keep the same naming as release/python3, TODO: Check conflicts
from __future__ import unicode_literals
import django.core.files.storage
from django.db import migrations, models
import djangoplicity.contacts.models
class Migration(migrations.Migration):
dependencies = [
('contacts', '0008_auto_20190926_1400'),
]
operations = [
migrations.AlterField(
model_name='import',
name='data_file',
field=models.FileField(storage=django.core.files.storage.FileSystemStorage(base_url=None, location=b'/home/noirlabadmin/shared/contacts_import'), upload_to=djangoplicity.contacts.models.handle_uploaded_file),
),
]
| 33.666667
| 220
| 0.719059
| 99
| 808
| 5.717172
| 0.717172
| 0.035336
| 0.053004
| 0.077739
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052711
| 0.178218
| 808
| 23
| 221
| 35.130435
| 0.799699
| 0.221535
| 0
| 0
| 1
| 0
| 0.1392
| 0.1024
| 0
| 0
| 0
| 0.043478
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
b8237cffc6518198ff69b80625832c608685ab1f
| 43
|
py
|
Python
|
src/nd2/_sdk/__init__.py
|
VolkerH/nd2
|
3fb449d28c10b975cd6773be8aa5802b3cb976f6
|
[
"BSD-3-Clause"
] | 6
|
2021-09-29T14:10:27.000Z
|
2022-03-26T13:34:47.000Z
|
src/nd2/_sdk/__init__.py
|
VolkerH/nd2
|
3fb449d28c10b975cd6773be8aa5802b3cb976f6
|
[
"BSD-3-Clause"
] | 33
|
2021-09-26T03:19:52.000Z
|
2022-03-14T22:39:47.000Z
|
src/nd2/_sdk/__init__.py
|
VolkerH/nd2
|
3fb449d28c10b975cd6773be8aa5802b3cb976f6
|
[
"BSD-3-Clause"
] | 2
|
2021-11-10T10:19:43.000Z
|
2022-03-17T13:30:46.000Z
|
from . import latest
__all__ = ["latest"]
| 10.75
| 20
| 0.674419
| 5
| 43
| 5
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186047
| 43
| 3
| 21
| 14.333333
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0.139535
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
b823e0670c4053630a8c6d56b1aa8294c629879c
| 25
|
py
|
Python
|
data/studio21_generated/interview/1752/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
data/studio21_generated/interview/1752/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
data/studio21_generated/interview/1752/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
def get_pins(observed):
| 12.5
| 23
| 0.76
| 4
| 25
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 25
| 2
| 24
| 12.5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b83efa9f1db180af9059814e2bbda91481094f8b
| 57
|
py
|
Python
|
mocks/xmodule/__init__.py
|
appsembler/course-cccess-groups
|
d9c59dc55a3d021196c50e1080d3a251b4751780
|
[
"MIT"
] | 4
|
2020-03-09T15:47:17.000Z
|
2021-09-08T09:17:42.000Z
|
mocks/xmodule/__init__.py
|
appsembler/course-cccess-groups
|
d9c59dc55a3d021196c50e1080d3a251b4751780
|
[
"MIT"
] | 51
|
2019-11-26T14:09:33.000Z
|
2022-03-09T08:27:59.000Z
|
mocks/xmodule/__init__.py
|
appsembler/course-cccess-groups
|
d9c59dc55a3d021196c50e1080d3a251b4751780
|
[
"MIT"
] | 3
|
2020-04-12T22:33:24.000Z
|
2021-09-30T20:28:03.000Z
|
"""
Mocks for the `xmodule` module so tests can run.
"""
| 14.25
| 48
| 0.649123
| 9
| 57
| 4.111111
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.192982
| 57
| 3
| 49
| 19
| 0.804348
| 0.842105
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b8493cecc9ea7ce4c2f1d305cd603358f9a1a571
| 232
|
py
|
Python
|
gcm/conf.py
|
ruckit-dev/django-gcm
|
9a98fbc60de544c7dc40c458ecc6684da5301370
|
[
"BSD-2-Clause"
] | 59
|
2015-01-14T18:39:18.000Z
|
2020-11-13T07:25:53.000Z
|
gcm/conf.py
|
ruckit-dev/django-gcm
|
9a98fbc60de544c7dc40c458ecc6684da5301370
|
[
"BSD-2-Clause"
] | 38
|
2015-01-24T10:42:45.000Z
|
2018-03-30T05:51:34.000Z
|
gcm/conf.py
|
ruckit-dev/django-gcm
|
9a98fbc60de544c7dc40c458ecc6684da5301370
|
[
"BSD-2-Clause"
] | 26
|
2015-01-24T10:34:59.000Z
|
2019-01-04T10:42:12.000Z
|
from django.conf import settings
GCM_DEVICE_MODEL = getattr(settings, 'GCM_DEVICE_MODEL', 'gcm.models.Device')
GCM_APIKEY = getattr(settings, 'GCM_APIKEY', None)
GCM_MAX_RECIPIENTS = getattr(settings, 'GCM_MAX_RECIPIENTS', 1000)
| 29
| 77
| 0.793103
| 32
| 232
| 5.4375
| 0.46875
| 0.252874
| 0.310345
| 0.252874
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.019048
| 0.094828
| 232
| 7
| 78
| 33.142857
| 0.809524
| 0
| 0
| 0
| 0
| 0
| 0.262931
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b880b35d65928e2a0e5efaa66ca90fcfd10bcaca
| 537
|
py
|
Python
|
eurofx/test_eurofx.py
|
supercoderz/pyeurofx
|
3f579bb6e4836dadb187df8c74a9d186ae7e39e7
|
[
"MIT"
] | 2
|
2018-07-14T11:58:35.000Z
|
2018-11-19T22:47:58.000Z
|
eurofx/test_eurofx.py
|
supercoderz/pyeurofx
|
3f579bb6e4836dadb187df8c74a9d186ae7e39e7
|
[
"MIT"
] | null | null | null |
eurofx/test_eurofx.py
|
supercoderz/pyeurofx
|
3f579bb6e4836dadb187df8c74a9d186ae7e39e7
|
[
"MIT"
] | 2
|
2017-01-03T11:50:45.000Z
|
2019-11-01T14:33:40.000Z
|
from .eurofx import *
from .eurofx_pandas import *
def test_get_daily():
#just call this function which covers all
get_daily_data()
def test_get_historical():
#just call this function which covers all
get_historical_data()
def test_get_daily_df():
#just call this function which covers all
get_daily_data_df()
def test_get_historical_df():
#just call this function which covers all
get_historical_data_df()
def test_get_currency_list_df():
get_currency_list_df()
def test_get_currency_list():
get_currency_list()
| 22.375
| 42
| 0.783985
| 85
| 537
| 4.564706
| 0.235294
| 0.108247
| 0.154639
| 0.206186
| 0.664948
| 0.634021
| 0.510309
| 0.510309
| 0.510309
| 0.5
| 0
| 0
| 0.145251
| 537
| 24
| 43
| 22.375
| 0.845316
| 0.297952
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| true
| 0
| 0.142857
| 0
| 0.571429
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
b89dd3bd00c8c35a1ddfe08b8b97032f14abaf5b
| 4,753
|
py
|
Python
|
sp2d/models/sp2d_simda.py
|
aagusti/sp2d
|
51122cdbb9f85bee91d08c3dd29fb1f7d1ae3d90
|
[
"MIT"
] | null | null | null |
sp2d/models/sp2d_simda.py
|
aagusti/sp2d
|
51122cdbb9f85bee91d08c3dd29fb1f7d1ae3d90
|
[
"MIT"
] | null | null | null |
sp2d/models/sp2d_simda.py
|
aagusti/sp2d
|
51122cdbb9f85bee91d08c3dd29fb1f7d1ae3d90
|
[
"MIT"
] | null | null | null |
from ..models import SipkdBase, SipkdDBSession
from datetime import datetime
from sqlalchemy import (
Column,
Integer,
BigInteger,
SmallInteger,
Text,
DateTime,
Date,
String,
ForeignKey,
text,
UniqueConstraint,
Numeric,
ForeignKeyConstraint,
PrimaryKeyConstraint
)
from sqlalchemy.orm import (
relationship,backref )
class SimdaBank(SipkdBase):
__tablename__ = 'ref_bank'
kd_bank = Column(Integer, nullable=False, primary_key=True)
nm_bank = Column(String(50), nullable=False)
no_rekening = Column(String(50))
kd_rek_1 = Column(Integer, nullable=False)
kd_rek_2 = Column(Integer, nullable=False)
kd_rek_3 = Column(Integer, nullable=False)
kd_rek_4 = Column(Integer, nullable=False)
kd_rek_5 = Column(Integer, nullable=False)
class SimdaSpm(SipkdBase):
__tablename__ = 'ta_spm'
__table_args__ = (PrimaryKeyConstraint('tahun', 'no_spm'),)
tahun = Column(Integer, nullable=False)
no_spm = Column(String(50), nullable=False)
kd_urusan = Column(Integer, nullable=False)
kd_bidang = Column(Integer, nullable=False)
kd_unit = Column(Integer, nullable=False)
kd_sub = Column(Integer, nullable=False)
no_spp = Column(String(50))
jn_spm = Column(Integer, nullable=False)
tgl_spm = Column(DateTime, nullable=False)
uraian = Column(String(255))
nm_penerima = Column(String(100))
bank_penerima = Column(String(50))
rek_penerima = Column(String(50))
npwp = Column(String(20))
bank_pembayar = Column(Integer)
nm_verifikator = Column(String(50))
nm_penandatangan = Column(String(50))
nip_penandatangan = Column(String(21))
jbt_penandatangan = Column(String(75))
kd_edit = Column(Integer)
class SimdaSpmDet(SipkdBase):
__tablename__ = 'ta_spm_rinc'
__table_args__ = (PrimaryKeyConstraint('tahun', 'no_spm', 'no_id'),
ForeignKeyConstraint(['tahun', 'no_spm'], ['ta_spm.tahun', 'ta_spm.no_spm']),)
tahun = Column(Integer, nullable=False)
no_spm = Column(String(50), nullable=False)
no_id = Column(Integer, nullable=False)
kd_urusan = Column(Integer, nullable=False)
kd_bidang = Column(Integer, nullable=False)
kd_unit = Column(Integer, nullable=False)
kd_sub = Column(Integer, nullable=False)
kd_prog = Column(Integer, nullable=False)
id_prog = Column(Integer, nullable=False)
kd_keg = Column(Integer, nullable=False)
kd_rek_1 = Column(Integer, nullable=False)
kd_rek_2 = Column(Integer, nullable=False)
kd_rek_3 = Column(Integer, nullable=False)
kd_rek_4 = Column(Integer, nullable=False)
kd_rek_5 = Column(Integer, nullable=False)
nilai = Column(Numeric, nullable=False)
class SimdaSpmInfo(SipkdBase):
__tablename__ = 'ta_spm_info'
__table_args__ = (PrimaryKeyConstraint('tahun', 'no_spm', 'kd_pot_rek'),
ForeignKeyConstraint(['tahun', 'no_spm'], ['ta_spm.tahun', 'ta_spm.no_spm']),)
tahun = Column(Integer, nullable=False)
no_spm = Column(String(50), nullable=False)
kd_pot_rek = Column(Integer, ForeignKey("ref_pot_spm.kd_pot"), nullable=False)
nilai = Column(Numeric, nullable=False)
class SimdaSpmPot(SipkdBase):
__tablename__ = 'ta_spm_pot'
__table_args__ = (PrimaryKeyConstraint('tahun', 'no_spm', 'kd_pot_rek'),
ForeignKeyConstraint(['tahun', 'no_spm'], ['ta_spm.tahun', 'ta_spm.no_spm']),)
tahun = Column(Integer, nullable=False)
no_spm = Column(String(50), nullable=False)
kd_pot_rek = Column(Integer, ForeignKey("ref_pot_spm.kd_pot"), nullable=False)
nilai = Column(Numeric, nullable=False)
class SimdaRefSpmPot(SipkdBase):
__tablename__ = 'ref_pot_spm'
kd_pot = Column(Integer, nullable=False, primary_key=True)
nm_pot = Column(String(50), nullable=False)
kd_map = Column(String(6))
class SimdaSp2d(SipkdBase):
__tablename__ = 'ta_sp2d'
__table_args__ = (ForeignKeyConstraint(['tahun', 'no_spm'], ['ta_spm.tahun', 'ta_spm.no_spm']),)
tahun = Column(Integer, nullable=False, primary_key=True)
no_sp2d = Column(String(50), nullable=False, primary_key=True)
no_spm = Column(String(50), nullable=False)
tgl_sp2d = Column(DateTime, nullable=False)
kd_bank = Column(Integer, nullable=False)
no_bku = Column(Integer, nullable=False)
nm_penandatangan = Column(String(50))
nip_penandatangan = Column(String(21))
jbt_penandatangan = Column(String(75))
keterangan = Column(String(255), nullable=False)
spm = relationship(SimdaSpm, foreign_keys=[tahun, no_spm])
| 39.941176
| 109
| 0.676836
| 569
| 4,753
| 5.360281
| 0.156415
| 0.20459
| 0.220328
| 0.272787
| 0.670164
| 0.634426
| 0.560328
| 0.545246
| 0.505902
| 0.505902
| 0
| 0.016913
| 0.203871
| 4,753
| 118
| 110
| 40.279661
| 0.789112
| 0
| 0
| 0.398148
| 0
| 0
| 0.06753
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.037037
| 0
| 0.824074
| 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
| 1
| 0
|
0
| 4
|
b229ca91836555f8ba2fa27d11ad07160aa7a7aa
| 121
|
py
|
Python
|
src/__init__.py
|
joeypauls/sandbox-editor
|
b8d4ff7fc94e7777dd3305673a20b78f3db8f952
|
[
"BSD-3-Clause"
] | null | null | null |
src/__init__.py
|
joeypauls/sandbox-editor
|
b8d4ff7fc94e7777dd3305673a20b78f3db8f952
|
[
"BSD-3-Clause"
] | null | null | null |
src/__init__.py
|
joeypauls/sandbox-editor
|
b8d4ff7fc94e7777dd3305673a20b78f3db8f952
|
[
"BSD-3-Clause"
] | null | null | null |
import os
here = os.path.abspath(os.path.dirname(__file__))
os.chdir(here)
def hello_world():
return "Hello World"
| 15.125
| 49
| 0.719008
| 19
| 121
| 4.315789
| 0.631579
| 0.146341
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140496
| 121
| 7
| 50
| 17.285714
| 0.788462
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0.2
| 0.6
| 0
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| 0
| null | 0
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| 0
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| 0
| 0
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| 0
| 1
| 0
| 0
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| 0
| 0
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| 0
| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
b260375841d00f1aa1872bd196f9dd9117c8105e
| 16,177
|
py
|
Python
|
network/network_models.py
|
oshopgiri/depth_sensing_navigation
|
80f4f82ebf77ea391f3ca9845eb45539f22df028
|
[
"MIT"
] | null | null | null |
network/network_models.py
|
oshopgiri/depth_sensing_navigation
|
80f4f82ebf77ea391f3ca9845eb45539f22df028
|
[
"MIT"
] | null | null | null |
network/network_models.py
|
oshopgiri/depth_sensing_navigation
|
80f4f82ebf77ea391f3ca9845eb45539f22df028
|
[
"MIT"
] | null | null | null |
# Author: Aqeel Anwar(ICSRL)
# Created: 4/14/2020, 7:15 AM
# Email: aqeel.anwar@gatech.edu
import tensorflow as tf
import numpy as np
from network.loss_functions import huber_loss, mse_loss
from network.network import *
from numpy import linalg as LA
class initialize_network_DeepQLearning():
def __init__(self, cfg, name, vehicle_name):
self.g = tf.Graph()
self.vehicle_name = vehicle_name
self.first_frame = True
self.last_frame = []
with self.g.as_default():
stat_writer_path = cfg.network_path + self.vehicle_name + '/return_plot/'
loss_writer_path = cfg.network_path + self.vehicle_name + '/loss' + name + '/'
self.stat_writer = tf.summary.FileWriter(stat_writer_path)
# name_array = 'D:/train/loss'+'/'+name
self.loss_writer = tf.summary.FileWriter(loss_writer_path)
self.env_type = cfg.env_type
self.input_size = cfg.input_size
self.num_actions = cfg.num_actions
# Placeholders
self.batch_size = tf.placeholder(tf.int32, shape=())
self.learning_rate = tf.placeholder(tf.float32, shape=())
self.X1 = tf.placeholder(tf.float32, [None, cfg.input_size, cfg.input_size, 3], name='States')
# self.X = tf.image.resize_images(self.X1, (227, 227))
self.X = tf.map_fn(lambda frame: tf.image.per_image_standardization(frame), self.X1)
self.target = tf.placeholder(tf.float32, shape=[None], name='Qvals')
self.actions = tf.placeholder(tf.int32, shape=[None], name='Actions')
# self.model = AlexNetDuel(self.X, cfg.num_actions, cfg.train_fc)
self.model = C3F2(self.X, cfg.num_actions, cfg.train_fc)
self.predict = self.model.output
ind = tf.one_hot(self.actions, cfg.num_actions)
pred_Q = tf.reduce_sum(tf.multiply(self.model.output, ind), axis=1)
self.loss = huber_loss(pred_Q, self.target)
self.train = tf.train.AdamOptimizer(learning_rate=self.learning_rate, beta1=0.9, beta2=0.99).minimize(
self.loss, name="train")
self.sess = tf.InteractiveSession()
tf.global_variables_initializer().run()
tf.local_variables_initializer().run()
self.saver = tf.train.Saver()
self.all_vars = tf.trainable_variables()
self.sess.graph.finalize()
# Load custom weights from custom_load_path if required
if cfg.custom_load:
print('Loading weights from: ', cfg.custom_load_path)
self.load_network(cfg.custom_load_path)
def get_vars(self):
return self.sess.run(self.all_vars)
def initialize_graphs_with_average(self, agent, agent_on_same_network):
values = {}
var = {}
all_assign = {}
for name_agent in agent_on_same_network:
values[name_agent] = agent[name_agent].network_model.get_vars()
var[name_agent] = agent[name_agent].network_model.all_vars
all_assign[name_agent] = []
for i in range(len(values[name_agent])):
val = []
for name_agent in agent_on_same_network:
val.append(values[name_agent][i])
# Take mean here
mean_val = np.average(val, axis=0)
for name_agent in agent_on_same_network:
# all_assign[name_agent].append(tf.assign(var[name_agent][i], mean_val))
var[name_agent][i].load(mean_val, agent[name_agent].network_model.sess)
def Q_val(self, xs):
target = np.zeros(shape=[xs.shape[0]], dtype=np.float32)
actions = np.zeros(dtype=int, shape=[xs.shape[0]])
return self.sess.run(self.predict,
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: 0, self.X1: xs,
self.target: target, self.actions: actions})
def train_n(self, xs, ys, actions, batch_size, dropout_rate, lr, epsilon, iter):
_, loss, Q = self.sess.run([self.train, self.loss, self.predict],
feed_dict={self.batch_size: batch_size, self.learning_rate: lr, self.X1: xs,
self.target: ys, self.actions: actions})
meanQ = np.mean(Q)
maxQ = np.max(Q)
# Log to tensorboard
self.log_to_tensorboard(tag='Loss', group=self.vehicle_name, value=LA.norm(loss) / batch_size, index=iter)
self.log_to_tensorboard(tag='Epsilon', group=self.vehicle_name, value=epsilon, index=iter)
self.log_to_tensorboard(tag='Learning Rate', group=self.vehicle_name, value=lr, index=iter)
self.log_to_tensorboard(tag='MeanQ', group=self.vehicle_name, value=meanQ, index=iter)
self.log_to_tensorboard(tag='MaxQ', group=self.vehicle_name, value=maxQ, index=iter)
def action_selection(self, state):
target = np.zeros(shape=[state.shape[0]], dtype=np.float32)
actions = np.zeros(dtype=int, shape=[state.shape[0]])
qvals = self.sess.run(self.predict,
feed_dict={self.batch_size: state.shape[0], self.learning_rate: 0.0001,
self.X1: state,
self.target: target, self.actions: actions})
if qvals.shape[0] > 1:
# Evaluating batch
action = np.argmax(qvals, axis=1)
else:
# Evaluating one sample
action = np.zeros(1)
action[0] = np.argmax(qvals)
return action.astype(int)
def log_to_tensorboard(self, tag, group, value, index):
summary = tf.Summary()
tag = group + '/' + tag
summary.value.add(tag=tag, simple_value=value)
self.stat_writer.add_summary(summary, index)
def save_network(self, save_path, episode=''):
save_path = save_path + self.vehicle_name + '/' + self.vehicle_name + '_' + str(episode)
self.saver.save(self.sess, save_path)
print('Model Saved: ', save_path)
def load_network(self, load_path):
self.saver.restore(self.sess, load_path)
def get_weights(self):
xs = np.zeros(shape=(32, 227, 227, 3))
actions = np.zeros(dtype=int, shape=[xs.shape[0]])
ys = np.zeros(shape=[xs.shape[0]], dtype=np.float32)
return self.sess.run(self.weights,
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: 0,
self.X1: xs,
self.target: ys, self.actions: actions})
###########################################################################
# DeepREINFORCE: Class
###########################################################################
class initialize_network_DeepREINFORCE():
def __init__(self, cfg, name, vehicle_name):
self.g = tf.Graph()
self.vehicle_name = vehicle_name
self.iter_baseline = 0
self.iter_policy = 0
self.first_frame = True
self.last_frame = []
self.iter_combined = 0
with self.g.as_default():
stat_writer_path = cfg.network_path + self.vehicle_name + '/return_plot/'
loss_writer_path = cfg.network_path + self.vehicle_name + '/loss' + name + '/'
self.stat_writer = tf.summary.FileWriter(stat_writer_path)
# name_array = 'D:/train/loss'+'/'+name
self.loss_writer = tf.summary.FileWriter(loss_writer_path)
self.env_type = cfg.env_type
self.input_size = cfg.input_size
self.num_actions = cfg.num_actions
# Placeholders
self.batch_size = tf.placeholder(tf.int32, shape=())
self.learning_rate = tf.placeholder(tf.float32, shape=())
self.X1 = tf.placeholder(tf.float32, [None, cfg.input_size, cfg.input_size, 3], name='States')
# self.X = tf.image.resize_images(self.X1, (227, 227))
self.X = tf.map_fn(lambda frame: tf.image.per_image_standardization(frame), self.X1)
# self.target = tf.placeholder(tf.float32, shape=[None], name='action_probs')
# self.target_baseline = tf.placeholder(tf.float32, shape=[None], name='baseline')
self.actions = tf.placeholder(tf.int32, shape=[None, 1], name='Actions')
self.G = tf.placeholder(tf.float32, shape=[None, 1], name='G')
self.B = tf.placeholder(tf.float32, shape=[None, 1], name='B')
# Select the deep network
self.model = C3F2_REINFORCE_with_baseline(self.X, cfg.num_actions, cfg.train_fc)
self.predict = self.model.output
self.baseline = self.model.baseline
self.ind = tf.one_hot(tf.squeeze(self.actions), cfg.num_actions)
self.prob_action = tf.reduce_sum(tf.multiply(self.predict, self.ind), axis=1)
loss_policy = tf.reduce_mean(tf.log(tf.transpose([self.prob_action])) * (self.G - self.B))
loss_entropy = -tf.reduce_mean(tf.multiply((tf.log(self.predict) + 1e-8), self.predict))
self.loss_main = -loss_policy - .2 * loss_entropy
self.loss_branch = mse_loss(self.baseline, self.G)
self.train_main = tf.train.AdamOptimizer(learning_rate=self.learning_rate, beta1=0.9, beta2=0.99).minimize(
self.loss_main, name="train_main")
self.train_branch = tf.train.AdamOptimizer(learning_rate=self.learning_rate, beta1=0.9,
beta2=0.99).minimize(
self.loss_branch, name="train_branch")
# self.train_combined = tf.train.AdamOptimizer(learning_rate=self.learning_rate, beta1=0.9,
# beta2=0.99).minimize(
# self.loss_combined, name="train_combined")
self.sess = tf.InteractiveSession()
tf.global_variables_initializer().run()
tf.local_variables_initializer().run()
self.saver = tf.train.Saver()
self.all_vars = tf.trainable_variables()
self.sess.graph.finalize()
# Load custom weights from custom_load_path if required
if cfg.custom_load:
print('Loading weights from: ', cfg.custom_load_path)
self.load_network(cfg.custom_load_path)
def get_vars(self):
return self.sess.run(self.all_vars)
def initialize_graphs_with_average(self, agent, agent_on_same_network):
values = {}
var = {}
all_assign = {}
for name_agent in agent_on_same_network:
values[name_agent] = agent[name_agent].network_model.get_vars()
var[name_agent] = agent[name_agent].network_model.all_vars
all_assign[name_agent] = []
for i in range(len(values[name_agent])):
val = []
for name_agent in agent_on_same_network:
val.append(values[name_agent][i])
# Take mean here
mean_val = np.average(val, axis=0)
for name_agent in agent_on_same_network:
# all_assign[name_agent].append(tf.assign(var[name_agent][i], mean_val))
var[name_agent][i].load(mean_val, agent[name_agent].network_model.sess)
def prob_actions(self, xs):
G = np.zeros(shape=[1], dtype=np.float32)
B = np.zeros(shape=[1], dtype=np.float32)
actions = np.zeros(dtype=int, shape=[xs.shape[0]])
return self.sess.run(self.predict,
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: 0, self.X1: xs,
self.actions: actions,
self.B: B,
self.G: G})
def train_baseline(self, xs, G, actions, lr, iter):
self.iter_baseline += 1
batch_size = xs.shape[0]
B = np.zeros(shape=[xs.shape[0], 1], dtype=np.float32)
_, loss, baseline_val = self.sess.run([self.train_branch, self.loss_branch, self.baseline],
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: lr,
self.X1: xs,
self.actions: actions,
self.B: B,
self.G: G})
max_baseline = np.max(baseline_val)
# Log to tensorboard
self.log_to_tensorboard(tag='Loss_Baseline', group=self.vehicle_name, value=loss / batch_size,
index=self.iter_baseline)
# self.log_to_tensorboard(tag='Epsilon', group=self.vehicle_name, value=epsilon, index=iter)
self.log_to_tensorboard(tag='Learning Rate', group=self.vehicle_name, value=lr, index=self.iter_baseline)
# self.log_to_tensorboard(tag='MeanQ', group=self.vehicle_name, value=meanQ, index=iter)
self.log_to_tensorboard(tag='Max_baseline', group=self.vehicle_name, value=max_baseline,
index=self.iter_baseline)
return baseline_val
def get_baseline(self, xs):
lr = 0
actions = np.zeros(dtype=int, shape=[xs.shape[0], 1])
B = np.zeros(shape=[xs.shape[0], 1], dtype=np.float32)
G = np.zeros(shape=[xs.shape[0], 1], dtype=np.float32)
baseline = self.sess.run(self.baseline,
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: lr,
self.X1: xs,
self.actions: actions,
self.B: B,
self.G: G})
return baseline
def train_policy(self, xs, actions, B, G, lr, iter):
self.iter_policy += 1
batch_size = xs.shape[0]
train_eval = self.train_main
loss_eval = self.loss_main
predict_eval = self.predict
_, loss, ProbActions = self.sess.run([train_eval, loss_eval, predict_eval],
feed_dict={self.batch_size: xs.shape[0], self.learning_rate: lr,
self.X1: xs,
self.actions: actions,
self.B: B,
self.G: G})
MaxProbActions = np.max(ProbActions)
# Log to tensorboard
self.log_to_tensorboard(tag='Loss_Policy', group=self.vehicle_name, value=LA.norm(loss) / batch_size,
index=self.iter_policy)
self.log_to_tensorboard(tag='Learning Rate', group=self.vehicle_name, value=lr, index=self.iter_policy)
self.log_to_tensorboard(tag='MaxProb', group=self.vehicle_name, value=MaxProbActions, index=self.iter_policy)
def action_selection(self, state):
action = np.zeros(dtype=int, shape=[state.shape[0], 1])
probs = self.sess.run(self.predict,
feed_dict={self.batch_size: state.shape[0], self.learning_rate: 0.0001,
self.X1: state,
self.actions: action})
for j in range(probs.shape[0]):
action[j] = np.random.choice(self.num_actions, 1, p=probs[j])[0]
return action.astype(int)
def log_to_tensorboard(self, tag, group, value, index):
summary = tf.Summary()
tag = group + '/' + tag
summary.value.add(tag=tag, simple_value=value)
self.stat_writer.add_summary(summary, index)
def save_network(self, save_path, episode=''):
save_path = save_path + self.vehicle_name + '/' + self.vehicle_name + '_' + str(episode)
self.saver.save(self.sess, save_path)
print('Model Saved: ', save_path)
def load_network(self, load_path):
self.saver.restore(self.sess, load_path)
| 45.441011
| 119
| 0.572912
| 2,011
| 16,177
| 4.411238
| 0.105917
| 0.028407
| 0.038891
| 0.029309
| 0.790328
| 0.766204
| 0.741517
| 0.722016
| 0.698117
| 0.652012
| 0
| 0.016659
| 0.302405
| 16,177
| 355
| 120
| 45.569014
| 0.769428
| 0.081226
| 0
| 0.626016
| 0
| 0
| 0.018809
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.085366
| false
| 0
| 0.020325
| 0.00813
| 0.150407
| 0.01626
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b26b10cd196ec2fcfed1232182c377221b62edeb
| 1,868
|
py
|
Python
|
galaxychop/dataset/__init__.py
|
vcristiani/galaxy-chop
|
6a854ee8701001ab0f15d6b0112401c123d0c6b2
|
[
"MIT"
] | 6
|
2020-09-25T19:31:52.000Z
|
2021-10-09T19:47:46.000Z
|
galaxychop/dataset/__init__.py
|
vcristiani/galaxy-chop
|
6a854ee8701001ab0f15d6b0112401c123d0c6b2
|
[
"MIT"
] | 98
|
2020-10-05T20:52:22.000Z
|
2022-02-11T15:28:43.000Z
|
galaxychop/dataset/__init__.py
|
vcristiani/galaxy-chop
|
6a854ee8701001ab0f15d6b0112401c123d0c6b2
|
[
"MIT"
] | 1
|
2022-01-17T23:07:33.000Z
|
2022-01-17T23:07:33.000Z
|
# This file is part of
# the galxy-chop project (https://github.com/vcristiani/galaxy-chop)
# Copyright (c) 2020, Valeria Cristiani
# License: MIT
# Full Text: https://github.com/vcristiani/galaxy-chop/blob/master/LICENSE.txt
"""Load tutorial files Module."""
# #####################################################
# IMPORTS
# #####################################################
import os
from pathlib import Path
import numpy as np
# =============================================================================
# PATHS
# =============================================================================
PATH = Path(os.path.abspath(os.path.dirname(__file__)))
# #####################################################
# FUNCTIONS
# #####################################################
def load_star():
"""Input for testing."""
path = PATH / "star.dat"
return np.loadtxt(path)
def load_dark():
"""Input for testing."""
path = PATH / "dark.dat"
return np.loadtxt(path)
def load_gas():
"""Input for testing."""
path = PATH / "gas_.dat"
return np.loadtxt(path)
def load_star_394242():
"""Input for testing."""
path = PATH / "star_ID_394242.npy"
return np.load(path)
def load_dark_394242():
"""Input for testing."""
path = PATH / "dark_ID_394242.npy"
return np.load(path)
def load_gas_394242():
"""Input for testing."""
path = PATH / "gas_ID_394242.npy"
return np.load(path)
def load_pot_star_394242():
"""Input for testing."""
path = PATH / "potential_star_ID_394242.npy"
return np.load(path)
def load_pot_dark_394242():
"""Input for testing."""
path = PATH / "potential_dark_ID_394242.npy"
return np.load(path)
def load_pot_gas_394242():
"""Input for testing."""
path = PATH / "potential_gas_ID_394242.npy"
return np.load(path)
| 20.304348
| 79
| 0.519807
| 210
| 1,868
| 4.442857
| 0.27619
| 0.085745
| 0.144695
| 0.18328
| 0.735263
| 0.735263
| 0.576635
| 0.244373
| 0.209003
| 0.209003
| 0
| 0.048812
| 0.166488
| 1,868
| 91
| 80
| 20.527473
| 0.550417
| 0.320128
| 0
| 0.290323
| 0
| 0
| 0.161128
| 0.083585
| 0
| 0
| 0
| 0
| 0
| 1
| 0.290323
| false
| 0
| 0.096774
| 0
| 0.677419
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
b2804185fe9d840edc2c55a2884879b1f3d717bd
| 169
|
py
|
Python
|
Python/Numpy/Easy/Zeros and Ones/zerosonee.py
|
navjindervirdee/hackerrank
|
d0d0f77f770e4b092440a15f2740f63b65deb60b
|
[
"MIT"
] | 2
|
2017-10-12T13:28:42.000Z
|
2020-07-28T11:25:05.000Z
|
Python/Numpy/Easy/Zeros and Ones/zerosonee.py
|
navjindervirdee/hackerrank
|
d0d0f77f770e4b092440a15f2740f63b65deb60b
|
[
"MIT"
] | null | null | null |
Python/Numpy/Easy/Zeros and Ones/zerosonee.py
|
navjindervirdee/hackerrank
|
d0d0f77f770e4b092440a15f2740f63b65deb60b
|
[
"MIT"
] | 5
|
2018-02-05T21:53:18.000Z
|
2021-10-03T06:27:45.000Z
|
import numpy as np
shape = tuple(map(int,input().strip().split()))
zeros = np.zeros(shape,dtype=np.int32)
ones = np.ones(shape,dtype=np.int32)
print(zeros)
print(ones)
| 21.125
| 47
| 0.715976
| 29
| 169
| 4.172414
| 0.551724
| 0.165289
| 0.198347
| 0.280992
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026144
| 0.094675
| 169
| 7
| 48
| 24.142857
| 0.764706
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0.333333
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b289c5b3bcd8430b11427dd9fa1d7f3ff593af41
| 28
|
py
|
Python
|
custom_components/wort_des_tages/__init__.py
|
Ludy87/astra_germany_wort_des_tages
|
c5da8b57bfe3cd4638d304c8cea4af1dbb19d0fc
|
[
"MIT"
] | null | null | null |
custom_components/wort_des_tages/__init__.py
|
Ludy87/astra_germany_wort_des_tages
|
c5da8b57bfe3cd4638d304c8cea4af1dbb19d0fc
|
[
"MIT"
] | null | null | null |
custom_components/wort_des_tages/__init__.py
|
Ludy87/astra_germany_wort_des_tages
|
c5da8b57bfe3cd4638d304c8cea4af1dbb19d0fc
|
[
"MIT"
] | null | null | null |
"""Wort des Tages Sensor."""
| 28
| 28
| 0.642857
| 4
| 28
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 28
| 1
| 28
| 28
| 0.72
| 0.785714
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b2a6d9e0f643a91987b8343b7bbd608814ec17df
| 34,825
|
py
|
Python
|
Features/Analyse_IR_Command.py
|
Fionnoch/TV-Relay-PyQt5
|
657d4cfe5626364db68d6ca530ebef4ed4381a15
|
[
"MIT"
] | null | null | null |
Features/Analyse_IR_Command.py
|
Fionnoch/TV-Relay-PyQt5
|
657d4cfe5626364db68d6ca530ebef4ed4381a15
|
[
"MIT"
] | null | null | null |
Features/Analyse_IR_Command.py
|
Fionnoch/TV-Relay-PyQt5
|
657d4cfe5626364db68d6ca530ebef4ed4381a15
|
[
"MIT"
] | null | null | null |
import numpy as np
#these are commands taken from noting on off times however this needs to be automated
up1 = [0.0042328250128775835, 0.004402360995300114, 0.0006506040226668119, 0.0015164930373430252, 0.0007461849600076675, 0.0015520340530201793, 0.0005174840334802866, 0.001726362039335072, 0.0004908168921247125, 0.0007498929044231772, 0.0005441079847514629, 0.0005015679635107517, 0.000501818023622036, 0.0004861509660258889, 0.0007358930306509137, 0.0004907350521534681, 0.0005868570879101753, 0.0004303610185161233, 0.0005750650307163596, 0.0017712349072098732, 0.0005280250916257501, 0.0016786130145192146, 0.0005001510726287961, 0.0017166539328172803, 0.0004876510938629508, 0.0004890259588137269, 0.0006176470778882504, 0.0005106920143589377, 0.0004951090086251497, 0.0007391850231215358, 0.0004928179550915956, 0.0004878180334344506, 0.000767142977565527, 0.0002751159481704235, 0.0007655599620193243, 0.0004912759177386761, 0.0005001929821446538, 0.00048644293565303087, 0.0007440589834004641, 0.0004918599734082818, 0.0005858979420736432, 0.0005126079777255654, 0.0004946510307490826, 0.0004936930490657687, 0.0007292269729077816, 0.001501660910435021, 0.0005250669782981277, 0.0017380699282512069, 0.0005045259604230523, 0.0007408930687233806, 0.000529648968949914, 0.0014889950398355722, 0.0007538100471720099, 0.001668988959863782, 0.0005226499633863568, 0.0015223269583657384, 0.0007419351022690535, 0.0016125739784911275, 0.0005171500379219651, 0.0017277790466323495, 0.000489110010676086, 0.0004895259626209736, 0.0005525660235434771, 0.0005081510171294212, 0.0007381848990917206, 0.0014685789356008172, 0.0007334770634770393]
up2 = [0.004342613043263555, 0.004348653950728476, 0.0007725169416517019, 0.0015468669589608908, 0.0004888600669801235, 0.0017591940704733133, 0.0005482330452650785, 0.0014511620393022895, 0.0007215599762275815, 0.0004794429987668991, 0.0004792769905179739, 0.0005870229797437787, 0.000737476977519691, 0.0004835679428651929, 0.0004871099954470992, 0.00048210902605205774, 0.0007220190018415451, 0.0004804020281881094, 0.0005480659892782569, 0.0017792349681258202, 0.0005049430765211582, 0.0016208660090342164, 0.0005985649768263102, 0.0014954940415918827, 0.0007319350261241198, 0.0005983139853924513, 0.0004135699709877372, 0.0005955229280516505, 0.0005139010027050972, 0.0004982759710401297, 0.0007411850383505225, 0.0004854429280385375, 0.0004994010087102652, 0.0004909849958494306, 0.0005864390404894948, 0.0005020260578021407, 0.0007375179557129741, 0.0004841929767280817, 0.0004798590671271086, 0.00048523489385843277, 0.0007165609858930111, 0.0006308549782261252, 0.0004922338994219899, 0.00048160902224481106, 0.0004776099231094122, 0.001675614039413631, 0.0007830590475350618, 0.0015098690055310726, 0.0005016090581193566, 0.0007206440204754472, 0.0004806929500773549, 0.0015861580614000559, 0.0007234360091388226, 0.0014389539137482643, 0.0007823089836165309, 0.0014893689658492804, 0.000722976983524859, 0.001430455013178289, 0.0005726070376113057, 0.0016972379526123405, 0.0007128099678084254, 0.0004773190012201667, 0.000490234000608325, 0.0005332749569788575, 0.0007346440106630325, 0.001437745988368988, 0.0007196859223768115]
up3 = [0.004289948032237589, 0.004526524106040597, 0.0005169420037418604, 0.0015418679686263204, 0.0007273930823430419, 0.0014387039700523019, 0.0007558509241789579, 0.001527619082480669, 0.000724768964573741, 0.0004876099992543459, 0.00048344291280955076, 0.00048215093556791544, 0.0006053979741409421, 0.0005134419770911336, 0.0007400190224871039, 0.0004944850225001574, 0.00048327597323805094, 0.00048581790179014206, 0.0007166019640862942, 0.0015827000606805086, 0.0005097339162603021, 0.0016969469143077731, 0.0005637319991365075, 0.0017108209431171417, 0.0004835680592805147, 0.00047652702778577805, 0.0007261439459398389, 0.0005222749896347523, 0.0005182760069146752, 0.0004985680570825934, 0.0007318930001929402, 0.0004798190202564001, 0.00048265198711305857, 0.00048031797632575035, 0.0008096819510683417, 0.0005396080669015646, 0.0005060669500380754, 0.0004969419678673148, 0.00048210995737463236, 0.00048331799916923046, 0.0007160189561545849, 0.00048627599608153105, 0.0005300251068547368, 0.0004905679961666465, 0.0007253109943121672, 0.0016914039151743054, 0.00048473395872861147, 0.0015848249895498157, 0.0005063589196652174, 0.0007282269652932882, 0.0004850259283557534, 0.0017166960751637816, 0.0004889010451734066, 0.0016809470253065228, 0.00048152601812034845, 0.0017508609453216195, 0.000487983925268054, 0.0016790300142019987, 0.0004927759291604161, 0.0017699860036373138, 0.000490942969918251, 0.0007190610049292445, 0.00048331799916923046, 0.0004858180182054639, 0.0005367329576984048, 0.0017034050542861223, 0.00048198411241173744]
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back1 = [0.0045251649571582675, 0.004377128090709448, 0.0005335679743438959, 0.001709118951112032, 0.0007345209596678615, 0.0014642090536653996, 0.0004950279835611582, 0.001693952945061028, 0.0005414009792730212, 0.0005269850371405482, 0.0004940279759466648, 0.0004841950722038746, 0.0007235630182549357, 0.00048227806109935045, 0.00048236094880849123, 0.0007857698947191238, 0.0005076099187135696, 0.0004971940070390701, 0.0004917780170217156, 0.0017420349176973104, 0.0005058189854025841, 0.0017646589549258351, 0.0004928190028294921, 0.0016828279476612806, 0.0006780639523640275, 0.0002593670506030321, 0.0007507289992645383, 0.0004929450806230307, 0.0004884029040113091, 0.0004784029442816973, 0.0006516489665955305, 0.0005943999858573079, 0.0005149439675733447, 0.0004934030584990978, 0.000733103952370584, 0.0004919859347864985, 0.0004881529603153467, 0.0004866949748247862, 0.0008057280210778117, 0.0005006109131500125, 0.000490527949295938, 0.0016950360732153058, 0.0004831949481740594, 0.001733618089929223, 0.0004895279416814446, 0.0004914860473945737, 0.000728728948161006, 0.001544081955216825, 0.0004922359948977828, 0.000725146965123713, 0.0004815279971808195, 0.0016869528917595744, 0.0005350270075723529, 0.001703453017398715, 0.000488403020426631, 0.001740284962579608, 0.0004918610211461782, 0.0004900700878351927, 0.000722646014764905, 0.00048656994476914406, 0.00048406992573291063, 0.0017611590446904302, 0.0004857779713347554, 0.0004819040186703205, 0.0007220209809020162, 0.001782326027750969, 0.00025903398636728525]
back2 = [0.0043988770339637995, 0.00442608492448926, 0.0005449019372463226, 0.001670912024565041, 0.0004844039212912321, 0.0016946610994637012, 0.0005625670310109854, 0.0017088280292227864, 0.0004844029899686575, 0.0004826119402423501, 0.0007211460033431649, 0.0005721510387957096, 0.0005019860109314322, 0.0004850280238315463, 0.0004863189533352852, 0.0007246049353852868, 0.00048757006879895926, 0.0004872779827564955, 0.0007721029687672853, 0.0015399570111185312, 0.0005146100884303451, 0.0017637839773669839, 0.000542942900210619, 0.0014917500084266067, 0.0007288960041478276, 0.0004913610173389316, 0.0004914440214633942, 0.0005609840154647827, 0.0005020700627937913, 0.0007335629779845476, 0.000483029056340456, 0.00048719404730945826, 0.0007251049391925335, 0.0004790700040757656, 0.000527067924849689, 0.0004921120125800371, 0.00048681895714253187, 0.0007286049658432603, 0.0004896529717370868, 0.0004940270446240902, 0.0007350220112130046, 0.001523166080005467, 0.0004889030242338777, 0.0016737859696149826, 0.0007945200195536017, 0.0005026940489187837, 0.0004887779941782355, 0.0015116240829229355, 0.0007362710312008858, 0.00051473593339324, 0.0005162350134924054, 0.0016883698990568519, 0.00048765295650810003, 0.001787074957974255, 0.0005035700742155313, 0.0016803690232336521, 0.00048107001930475235, 0.0004826940130442381, 0.0007846859516575933, 0.0004917370388284326, 0.000483736046589911, 0.0016822450561448932, 0.00048011098988354206, 0.000539442989975214, 0.000754979089833796, 0.0014382930239662528, 0.0007274800445884466]
back3 = [0.004321587039157748, 0.004440875956788659, 0.00046736199874430895, 0.001592705026268959, 0.0008825170807540417, 0.0014548340113833547, 0.0004948610439896584, 0.001679744920693338, 0.0007141049718484282, 0.00057565001770854, 0.0004950700094923377, 0.0004916529869660735, 0.0004825700307264924, 0.0007113970350474119, 0.0004766950150951743, 0.0004760699812322855, 0.0007802279433235526, 0.0004975280025973916, 0.000486528966575861, 0.001727786031551659, 0.0004943199455738068, 0.0015302080428227782, 0.0007316460832953453, 0.0016809949884191155, 0.0005309439729899168, 0.000507193966768682, 0.0004925699904561043, 0.00048032007180154324, 0.000719396979548037, 0.00048044498544186354, 0.0004790279781445861, 0.0007126890122890472, 0.0005316099850460887, 0.0004971949383616447, 0.0004960700171068311, 0.0007225630106404424, 0.0004826949443668127, 0.00048056989908218384, 0.0007153550395742059, 0.0005381519440561533, 0.0004964030813425779, 0.0016870370600372553, 0.00047594495117664337, 0.0017749510006979108, 0.0004851529374718666, 0.0004800281021744013, 0.0007182719418779016, 0.0016238288953900337, 0.0005443179979920387, 0.0004955279873684049, 0.0005013189511373639, 0.0016669540200382471, 0.000800768961198628, 0.0014565419405698776, 0.0004850280238315463, 0.0018538649892434478, 0.0005946509772911668, 0.000509736011736095, 0.0004955281037837267, 0.000495568965561688, 0.0004776950227096677, 0.0017459510127082467, 0.0005003189435228705, 0.0004873619182035327, 0.0007182720582932234, 0.0016662459820508957, 0.000527193071320653]
exit1 = [0.004299880005419254, 0.004643870051950216, 0.0006061081076040864, 0.0014701669570058584, 0.00048752804286777973, 0.0017553670331835747, 0.0005591510562226176, 0.0017091609770432115, 0.0004832360427826643, 0.0004868200048804283, 0.0008300599874928594, 0.0002722840290516615, 0.0007499799830839038, 0.0004893610021099448, 0.0004929449642077088, 0.00048148597124964, 0.0007240640698000789, 0.00048469402827322483, 0.0005471509648486972, 0.001746825990267098, 0.0004981110105291009, 0.001485458924435079, 0.0007404380012303591, 0.0016817450523376465, 0.000478986999951303, 0.00047623703721910715, 0.0007814780110493302, 0.0004943190142512321, 0.0004902359796687961, 0.00048715295270085335, 0.0007242299616336823, 0.0004785700002685189, 0.00048023706767708063, 0.0005567760672420263, 0.0005226519424468279, 0.0016853699926286936, 0.0004789030645042658, 0.0007240629056468606, 0.00048169505316764116, 0.0017588259652256966, 0.00048356992192566395, 0.0016735779354348779, 0.0005965669406577945, 0.00048577808775007725, 0.0004812780534848571, 0.0017239940352737904, 0.0005023609846830368, 0.0005327359540387988, 0.0007421460468322039, 0.0004867360694333911, 0.0004859870532527566, 0.0004802360199391842, 0.0007172300247475505, 0.0018401159904897213, 0.0004389879759401083, 0.00033544900361448526, 0.0007856030715629458, 0.0004926109686493874, 0.00048161193262785673, 0.001574538997374475, 0.000737478956580162, 0.0004883609944954515, 0.0004784449702128768, 0.0018250320572406054, 0.0004923200467601418, 0.0016865769866853952, 0.0004894869634881616]
exit2 = [0.004420085111632943, 0.004380169091746211, 0.000556733924895525, 0.0017029530135914683, 0.0004868609830737114, 0.0016188300214707851, 0.0007271460490301251, 0.0016728700138628483, 0.00048436096403747797, 0.0005641099996864796, 0.0004991110181435943, 0.0004754860419780016, 0.0007141879759728909, 0.00047456996981054544, 0.0004846950760111213, 0.0007180629763752222, 0.0005851919995620847, 0.0004931950243189931, 0.0004830700345337391, 0.0017203690949827433, 0.0005023609846830368, 0.001754408935084939, 0.0004747780039906502, 0.0016518710181117058, 0.0005476929945871234, 0.000502444920130074, 0.0007299380376935005, 0.0004759030416607857, 0.0004775290144607425, 0.0007094800239428878, 0.0004783610347658396, 0.0004965279949828982, 0.0005095690721645951, 0.0007242719875648618, 0.00048190297093242407, 0.001799033023416996, 0.0006459819851443172, 0.00027307600248605013, 0.0005036939401179552, 0.0016832869732752442, 0.0007180629763752222, 0.0014870830345898867, 0.0007274380186572671, 0.0004771529929712415, 0.0004808199591934681, 0.0017853250028565526, 0.0005154029931873083, 0.0004896529717370868, 0.0007188550662249327, 0.0004796949215233326, 0.0004831950645893812, 0.00047965405974537134, 0.000762854004278779, 0.0014453759649768472, 0.0007196050137281418, 0.00047473690938204527, 0.0007182719418779016, 0.0005438189255073667, 0.0004984029801562428, 0.001673370017670095, 0.00048540299758315086, 0.0004724039463326335, 0.0007441870402544737, 0.0014716261066496372, 0.0007147300057113171, 0.0016717449761927128, 0.0005535261007025838]
exit3 = [0.00442821008618921, 0.0047562000108882785, 0.00029415800236165524, 0.0017326599918305874, 0.0004862359492108226, 0.0015649560373276472, 0.0007331880042329431, 0.0016731199575588107, 0.00048698706086724997, 0.0004944030661135912, 0.0005493588978424668, 0.0004880279302597046, 0.0007282710867002606, 0.00047819502651691437, 0.0004801949253305793, 0.0007149380398914218, 0.0004772779066115618, 0.0005185690242797136, 0.0004968610592186451, 0.0017169930506497622, 0.0005006940336897969, 0.0017550759948790073, 0.000490986043587327, 0.0016905359225347638, 0.00048065301962196827, 0.0008335600141435862, 0.0004994020564481616, 0.00048586202319711447, 0.0004939869977533817, 0.000796478008851409, 0.0004695700481534004, 0.0003625729586929083, 0.0006027339259162545, 0.000554360100068152, 0.0005079020047560334, 0.0016606199787929654, 0.000636023934930563, 0.0006347320741042495, 0.0005859000375494361, 0.0015703310491517186, 0.0007091050501912832, 0.0015303740510717034, 0.0006087750662118196, 0.000577858998440206, 0.0003212409792467952, 0.001828783075325191, 0.0005960660055279732, 0.0005154020618647337, 0.00048811209853738546, 0.000484112068079412, 0.00048157002311199903, 0.0007195639191195369, 0.0004807780496776104, 0.0017822830704972148, 0.0004834029823541641, 0.0004785700002685189, 0.0007252299692481756, 0.00048477796372026205, 0.0005240689497441053, 0.001684703049249947, 0.0005304430378600955, 0.0004944029496982694, 0.0004866120871156454, 0.0018359479727223516, 0.0004929018905386329, 0.001695368904620409, 0.00048757006879895926]
up1 = np.array(up1)
up2 = np.array(up2)
up3 = np.array(up3)
down1 = np.array(down1)
down2 = np.array(down2)
down3 = np.array(down3)
left1 = np.array(left1)
left2 = np.array(left2)
left3 = np.array(left3)
right1 = np.array(right1)
right2 = np.array(right2)
right3 = np.array(right3)
enter1 = np.array(enter1)
enter2 = np.array(enter2)
enter3 = np.array(enter3)
back1 = np.array(back1)
back2 = np.array(back2)
back3 = np.array(back3)
exit1 = np.array(exit1)
exit2 = np.array(exit2)
exit3 = np.array(exit3)
up = np.array([up1, up2, up3])
down = np.array([down1, down2, down3])
left = np.array([left1, left2, left3])
right = np.array([right1, right2, right3])
enter = np.array([enter1, enter2, enter3])
back = np.array([back1, back2, back3])
exit = np.array([exit1, exit2, exit3])
text_ref = ["up", "down", "left", "right", "enter", "back", "return"]
input_matrix = [up, down, left, right, enter, back, exit]
counter = -1
for i in input_matrix:
counter = counter+1
maxInColumns = np.amax(i, axis=0)
minInColumns = np.amin(i, axis=0)
meanInColumns = np.mean(i, axis=0)
top_diff = abs(maxInColumns-meanInColumns)
bottom_diff = abs(minInColumns-meanInColumns)
max_diff_in_col = np.zeros(len(meanInColumns))
for j in range(len(top_diff)):
if top_diff[j]>bottom_diff[j]:
max_diff_in_col[j] = top_diff[j]
else:
max_diff_in_col[j] = bottom_diff[j]
max_diff = max(max_diff_in_col)
f = open("ir_command.txt", "a")
print(" ", text_ref[counter], " Summary ", file=f)
print("-----------------------------", file=f)
print("Average = ", file=f)
np.savetxt(f, meanInColumns, newline=", ", fmt='%1.6f') #level of precision is 6
#print(meanInColumns, file=f)
print("", file=f)
print("", file=f)
print("Differneces = ", file=f)
np.savetxt(f, max_diff_in_col, newline=", ", fmt='%1.6f') #level of precision is 6
print("", file=f)
print("", file=f)
print("Max Differnece = ", file=f)
print("{0:.6f}".format(max_diff), file=f) #level of precision is 6
print("", file=f)
print("Length of Command", file=f)
print(i.shape[1], file=f)
print("", file=f)
f.close()
| 316.590909
| 1,556
| 0.851256
| 3,189
| 34,825
| 9.286924
| 0.456883
| 0.006618
| 0.003714
| 0.003039
| 0.011041
| 0.008914
| 0.005166
| 0.003984
| 0.003984
| 0.002499
| 0
| 0.855845
| 0.054817
| 34,825
| 109
| 1,557
| 319.495413
| 0.0439
| 0.005197
| 0
| 0.070588
| 0
| 0
| 0.00511
| 0.000837
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.011765
| 0
| 0.011765
| 0.164706
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a2432502210df61b5853a6fa0dbcb3736e094f35
| 736
|
py
|
Python
|
tests/test_project/test_app/migrations/0004_auto_20210829_1154.py
|
domandinho/SmartSecurity
|
d8e92f8412aafdc513b6b7a25b54b1dca9afe52b
|
[
"MIT"
] | null | null | null |
tests/test_project/test_app/migrations/0004_auto_20210829_1154.py
|
domandinho/SmartSecurity
|
d8e92f8412aafdc513b6b7a25b54b1dca9afe52b
|
[
"MIT"
] | null | null | null |
tests/test_project/test_app/migrations/0004_auto_20210829_1154.py
|
domandinho/SmartSecurity
|
d8e92f8412aafdc513b6b7a25b54b1dca9afe52b
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.2.5 on 2021-08-29 11:54
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("test_app", "0003_alter_testbroker_options"),
]
operations = [
migrations.AlterModelOptions(
name="testbroker",
options={
"permissions": [
("unique_permission", "Unique permission"),
("not_unique_permission", "Not unique permission"),
]
},
),
migrations.AlterModelOptions(
name="testowner",
options={
"permissions": [("not_unique_permission", "Not unique permission")]
},
),
]
| 25.37931
| 83
| 0.521739
| 57
| 736
| 6.578947
| 0.578947
| 0.256
| 0.202667
| 0.2
| 0.245333
| 0.202667
| 0
| 0
| 0
| 0
| 0
| 0.040773
| 0.366848
| 736
| 28
| 84
| 26.285714
| 0.763949
| 0.061141
| 0
| 0.272727
| 1
| 0
| 0.28447
| 0.103048
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.045455
| 0
| 0.181818
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a243378cc1154ec25933b7cb6a9b0ab6c1b2ccc7
| 89
|
py
|
Python
|
setup.py
|
emay2022/fraplib
|
9c580ea6c9405bcf2dbf50cdbf66e39bfbad0b06
|
[
"BSD-3-Clause"
] | null | null | null |
setup.py
|
emay2022/fraplib
|
9c580ea6c9405bcf2dbf50cdbf66e39bfbad0b06
|
[
"BSD-3-Clause"
] | null | null | null |
setup.py
|
emay2022/fraplib
|
9c580ea6c9405bcf2dbf50cdbf66e39bfbad0b06
|
[
"BSD-3-Clause"
] | null | null | null |
import setuptools
setuptools.setup(use_scm_version={"write_to": "fraplib/_version.py"})
| 22.25
| 69
| 0.797753
| 12
| 89
| 5.583333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05618
| 89
| 3
| 70
| 29.666667
| 0.797619
| 0
| 0
| 0
| 0
| 0
| 0.303371
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
a27faed7306f5f792049b1b67e3247ff5b63d922
| 107
|
py
|
Python
|
9461.py
|
FelisCatusKR/Baekjoon_Python3
|
d84dc9421fe956001864d138b6d6ec9ebd793edf
|
[
"MIT"
] | null | null | null |
9461.py
|
FelisCatusKR/Baekjoon_Python3
|
d84dc9421fe956001864d138b6d6ec9ebd793edf
|
[
"MIT"
] | null | null | null |
9461.py
|
FelisCatusKR/Baekjoon_Python3
|
d84dc9421fe956001864d138b6d6ec9ebd793edf
|
[
"MIT"
] | null | null | null |
# 9461.py
P=[1,1,1,2,2]
for _ in range(95):P+=[P[-1]+P[-5]]
exec("print(P[int(input())-1]);"*int(input()))
| 26.75
| 46
| 0.53271
| 26
| 107
| 2.192308
| 0.576923
| 0.070175
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14
| 0.065421
| 107
| 4
| 46
| 26.75
| 0.42
| 0.065421
| 0
| 0
| 0
| 0
| 0.255102
| 0.255102
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.333333
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a28a3a7828d5e8b9e81681c7ccefa015c66dcaab
| 25
|
py
|
Python
|
lib/grpc/_grpcio_metadata.py
|
kylevigil/SportsFeed
|
661bc9197974e69eb5b42c845940317a0569a03c
|
[
"Apache-2.0"
] | null | null | null |
lib/grpc/_grpcio_metadata.py
|
kylevigil/SportsFeed
|
661bc9197974e69eb5b42c845940317a0569a03c
|
[
"Apache-2.0"
] | null | null | null |
lib/grpc/_grpcio_metadata.py
|
kylevigil/SportsFeed
|
661bc9197974e69eb5b42c845940317a0569a03c
|
[
"Apache-2.0"
] | null | null | null |
__version__ = """1.6.3"""
| 25
| 25
| 0.56
| 4
| 25
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130435
| 0.08
| 25
| 1
| 25
| 25
| 0.304348
| 0
| 0
| 0
| 0
| 0
| 0.192308
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a2a55846f481474539515cd90a8f4660cc1c4ac7
| 617
|
py
|
Python
|
wasm/tests/test_exec_mode.py
|
dbrgn/RustPython
|
6d371cea8a62d84dbbeec5a53cfd040f45899211
|
[
"CC-BY-4.0",
"MIT"
] | 11,058
|
2018-05-29T07:40:06.000Z
|
2022-03-31T11:38:42.000Z
|
wasm/tests/test_exec_mode.py
|
dbrgn/RustPython
|
6d371cea8a62d84dbbeec5a53cfd040f45899211
|
[
"CC-BY-4.0",
"MIT"
] | 2,105
|
2018-06-01T10:07:16.000Z
|
2022-03-31T14:56:42.000Z
|
wasm/tests/test_exec_mode.py
|
dbrgn/RustPython
|
6d371cea8a62d84dbbeec5a53cfd040f45899211
|
[
"CC-BY-4.0",
"MIT"
] | 914
|
2018-07-27T09:36:14.000Z
|
2022-03-31T19:56:34.000Z
|
def test_eval_mode(wdriver):
assert wdriver.execute_script("return window.rp.pyEval('1+1')") == 2
def test_exec_mode(wdriver):
assert wdriver.execute_script("return window.rp.pyExec('1+1')") is None
def test_exec_single_mode(wdriver):
assert wdriver.execute_script("return window.rp.pyExecSingle('1+1')") == 2
stdout = wdriver.execute_script(
"""
let output = "";
save_output = function(text) {{
output += text
}};
window.rp.pyExecSingle('1+1\\n2+2',{stdout: save_output});
return output;
"""
)
assert stdout == "2\n4\n"
| 28.045455
| 78
| 0.614263
| 79
| 617
| 4.632911
| 0.367089
| 0.153005
| 0.218579
| 0.196721
| 0.516393
| 0.418033
| 0.418033
| 0.418033
| 0.418033
| 0
| 0
| 0.029536
| 0.231767
| 617
| 21
| 79
| 29.380952
| 0.742616
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0.183824
| 0
| 0
| 0
| 0
| 0.444444
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a2aa997c4ccfdf190f0e8e359c313949f01f6f09
| 92
|
py
|
Python
|
ex002.py
|
GuilhermeAntony14/Estudando-Python
|
b020f6d2625e7fcc42d30658bcbd881b093434dd
|
[
"MIT"
] | null | null | null |
ex002.py
|
GuilhermeAntony14/Estudando-Python
|
b020f6d2625e7fcc42d30658bcbd881b093434dd
|
[
"MIT"
] | null | null | null |
ex002.py
|
GuilhermeAntony14/Estudando-Python
|
b020f6d2625e7fcc42d30658bcbd881b093434dd
|
[
"MIT"
] | null | null | null |
nome = str(input('Qual seu nome: '))
print(f'E um prazer te conhecer \033[32m{nome}\033[m!')
| 46
| 55
| 0.673913
| 18
| 92
| 3.444444
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098765
| 0.119565
| 92
| 2
| 55
| 46
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0.645161
| 0.225806
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
a2ee914020a34aca9de78c09ec58237b0df94c11
| 46
|
py
|
Python
|
PyClassEx/modulfructe/fructe3.py
|
mhcrnl/PmwTkEx
|
6ef8ed8743bbb74f30e33e33d7894d9d1afedd87
|
[
"Apache-2.0"
] | null | null | null |
PyClassEx/modulfructe/fructe3.py
|
mhcrnl/PmwTkEx
|
6ef8ed8743bbb74f30e33e33d7894d9d1afedd87
|
[
"Apache-2.0"
] | null | null | null |
PyClassEx/modulfructe/fructe3.py
|
mhcrnl/PmwTkEx
|
6ef8ed8743bbb74f30e33e33d7894d9d1afedd87
|
[
"Apache-2.0"
] | null | null | null |
import fructe2 as f
b = f.Fructe2()
b.mar()
| 7.666667
| 19
| 0.630435
| 9
| 46
| 3.222222
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.055556
| 0.217391
| 46
| 5
| 20
| 9.2
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
a2f2761d2efb468fd6eeab9af77f7ac57033e3fd
| 88
|
py
|
Python
|
egs/wsj/s5/utils/convert_lexicon.py
|
chizhang0814/kaldi
|
b9798677e07975f3fbdddf635947047012314ad0
|
[
"Apache-2.0"
] | null | null | null |
egs/wsj/s5/utils/convert_lexicon.py
|
chizhang0814/kaldi
|
b9798677e07975f3fbdddf635947047012314ad0
|
[
"Apache-2.0"
] | null | null | null |
egs/wsj/s5/utils/convert_lexicon.py
|
chizhang0814/kaldi
|
b9798677e07975f3fbdddf635947047012314ad0
|
[
"Apache-2.0"
] | null | null | null |
import os
old_lexicon = '/data3/voxforge/s5/data/local/dict/lexicon.txt'
map_file = ''
| 17.6
| 62
| 0.738636
| 14
| 88
| 4.5
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025316
| 0.102273
| 88
| 4
| 63
| 22
| 0.772152
| 0
| 0
| 0
| 0
| 0
| 0.522727
| 0.522727
| 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
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
0c0d1fb1ad6f4350bbf089622f58d07b811d6e6f
| 15
|
py
|
Python
|
2/22.py
|
Seaoftrees/Session2019
|
86d61f190979ea9be205a3bbde1deac85de26997
|
[
"MIT"
] | null | null | null |
2/22.py
|
Seaoftrees/Session2019
|
86d61f190979ea9be205a3bbde1deac85de26997
|
[
"MIT"
] | null | null | null |
2/22.py
|
Seaoftrees/Session2019
|
86d61f190979ea9be205a3bbde1deac85de26997
|
[
"MIT"
] | null | null | null |
a = 5
print(a)
| 5
| 8
| 0.533333
| 4
| 15
| 2
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 0.266667
| 15
| 2
| 9
| 7.5
| 0.636364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
0c0e12f5c99cc6bffd1e6cfb23cf8ad80b8b88f0
| 124
|
py
|
Python
|
2._Learning_Python/A._Basic_-_no_OOP/7._Functions_and_Modules/1._Functions/5._Underscores_in_Python/underscores.py
|
sanjarcode/python3_notes
|
b844515a021c2b75a4066b6d4cad239fdd13e3a7
|
[
"MIT"
] | null | null | null |
2._Learning_Python/A._Basic_-_no_OOP/7._Functions_and_Modules/1._Functions/5._Underscores_in_Python/underscores.py
|
sanjarcode/python3_notes
|
b844515a021c2b75a4066b6d4cad239fdd13e3a7
|
[
"MIT"
] | null | null | null |
2._Learning_Python/A._Basic_-_no_OOP/7._Functions_and_Modules/1._Functions/5._Underscores_in_Python/underscores.py
|
sanjarcode/python3_notes
|
b844515a021c2b75a4066b6d4cad239fdd13e3a7
|
[
"MIT"
] | null | null | null |
personal_details = ('Sanjar', 22, 'India')
print(personal_details)
name, _, country = personal_details
print(name, country)
| 24.8
| 42
| 0.758065
| 15
| 124
| 6
| 0.533333
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018018
| 0.104839
| 124
| 4
| 43
| 31
| 0.792793
| 0
| 0
| 0
| 0
| 0
| 0.08871
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 1
|
0
| 4
|
0c2278b3f4c129ec051af6fcb12ae396c19d4500
| 58
|
py
|
Python
|
neural_lambda_calculus/__init__.py
|
brandontrabucco/neural_lambda_calculus
|
f796961730a84f21a427297ae903e7ed6e71a4c4
|
[
"MIT"
] | null | null | null |
neural_lambda_calculus/__init__.py
|
brandontrabucco/neural_lambda_calculus
|
f796961730a84f21a427297ae903e7ed6e71a4c4
|
[
"MIT"
] | null | null | null |
neural_lambda_calculus/__init__.py
|
brandontrabucco/neural_lambda_calculus
|
f796961730a84f21a427297ae903e7ed6e71a4c4
|
[
"MIT"
] | null | null | null |
"""Author: Brandon Trabucco, Kavi Gupta, Copyright 2019"""
| 58
| 58
| 0.741379
| 7
| 58
| 6.142857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 0.103448
| 58
| 1
| 58
| 58
| 0.75
| 0.896552
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0c3081ff7bca1e7d585a05ac34483bec39073bce
| 208
|
py
|
Python
|
gistio/urls.py
|
Teino1978-Corp/gistio
|
405f95bf16c2be4b9d9f6e209d49f873823ea5ca
|
[
"BSD-3-Clause"
] | 1
|
2019-05-07T15:13:11.000Z
|
2019-05-07T15:13:11.000Z
|
gistio/urls.py
|
Teino1978-Corp/gistio
|
405f95bf16c2be4b9d9f6e209d49f873823ea5ca
|
[
"BSD-3-Clause"
] | null | null | null |
gistio/urls.py
|
Teino1978-Corp/gistio
|
405f95bf16c2be4b9d9f6e209d49f873823ea5ca
|
[
"BSD-3-Clause"
] | null | null | null |
from django.conf.urls import patterns, include, url
urlpatterns = patterns('',
url(r'^', include('gists.urls')),
# url(r'^', include('githubauth.urls')),
url(r'^', include('publicsite.urls')),
)
| 26
| 51
| 0.629808
| 25
| 208
| 5.24
| 0.52
| 0.091603
| 0.251908
| 0.229008
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144231
| 208
| 7
| 52
| 29.714286
| 0.735955
| 0.182692
| 0
| 0
| 0
| 0
| 0.160714
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0c463a141c39e1036e59e5cd02b57e251f9f9f1b
| 215
|
py
|
Python
|
ex11.py
|
Nandarlynnn/python-exercises
|
8f5e529b45b5d6174f6859561b49c3dafb86d221
|
[
"MIT"
] | null | null | null |
ex11.py
|
Nandarlynnn/python-exercises
|
8f5e529b45b5d6174f6859561b49c3dafb86d221
|
[
"MIT"
] | null | null | null |
ex11.py
|
Nandarlynnn/python-exercises
|
8f5e529b45b5d6174f6859561b49c3dafb86d221
|
[
"MIT"
] | null | null | null |
print ("how old are you?.",)
age=raw_input()
print("How tall are you?.",)
height=raw_input()
print("How much do you weight?.",)
weight=raw_input()
print("So you're %r old,%r tall and %r heavy."%(age,height,weight))
| 26.875
| 67
| 0.674419
| 39
| 215
| 3.641026
| 0.461538
| 0.169014
| 0.274648
| 0.225352
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 215
| 7
| 68
| 30.714286
| 0.747368
| 0
| 0
| 0
| 0
| 0
| 0.451163
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.571429
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
a74331741c2daf4341f13c1f6a978c11752b08c3
| 203
|
py
|
Python
|
apps/posts/admin.py
|
cmput404F21/CMPUT404-project-socialdistribution
|
47f108b43886a4e482c6b6f9c6fdef6dcc005c3f
|
[
"W3C-20150513"
] | null | null | null |
apps/posts/admin.py
|
cmput404F21/CMPUT404-project-socialdistribution
|
47f108b43886a4e482c6b6f9c6fdef6dcc005c3f
|
[
"W3C-20150513"
] | 48
|
2021-10-12T21:41:39.000Z
|
2021-12-08T19:40:25.000Z
|
apps/posts/admin.py
|
cmput404F21/CMPUT404-project-socialdistribution
|
47f108b43886a4e482c6b6f9c6fdef6dcc005c3f
|
[
"W3C-20150513"
] | 1
|
2022-01-11T04:07:43.000Z
|
2022-01-11T04:07:43.000Z
|
from django.contrib import admin
from .models import Like, Post
from .models import Comment
# Register your models here.
admin.site.register(Post)
admin.site.register(Comment)
admin.site.register(Like)
| 22.555556
| 32
| 0.802956
| 30
| 203
| 5.433333
| 0.433333
| 0.165644
| 0.312883
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108374
| 203
| 9
| 33
| 22.555556
| 0.900552
| 0.128079
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
a751315aab70d74732e74401579640ecbb2031e8
| 360
|
py
|
Python
|
yunionclient/api/federatedclusterrolebindings.py
|
yunionyun/python_yunionsdk
|
40a567b80f6fb3ebc72d8cc6313b334a201b2f00
|
[
"Apache-2.0"
] | 3
|
2021-09-22T11:34:08.000Z
|
2022-03-13T04:55:17.000Z
|
yunionclient/api/federatedclusterrolebindings.py
|
yunionyun/python_yunionsdk
|
40a567b80f6fb3ebc72d8cc6313b334a201b2f00
|
[
"Apache-2.0"
] | 13
|
2019-06-06T08:25:41.000Z
|
2021-07-16T07:26:10.000Z
|
yunionclient/api/federatedclusterrolebindings.py
|
yunionyun/python_yunionsdk
|
40a567b80f6fb3ebc72d8cc6313b334a201b2f00
|
[
"Apache-2.0"
] | 7
|
2019-03-31T05:43:36.000Z
|
2021-03-04T09:59:05.000Z
|
from yunionclient.common import base
class Federatedclusterrolebinding(base.ResourceBase):
pass
class FederatedclusterrolebindingManager(base.StandaloneManager):
resource_class = Federatedclusterrolebinding
keyword = 'federatedclusterrolebinding'
keyword_plural = 'federatedclusterrolebindings'
_columns = ["Id", "Name", "Description"]
| 27.692308
| 65
| 0.794444
| 26
| 360
| 10.884615
| 0.730769
| 0.226148
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130556
| 360
| 12
| 66
| 30
| 0.904153
| 0
| 0
| 0
| 0
| 0
| 0.200557
| 0.153203
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.125
| 0.125
| 0
| 0.875
| 0
| 1
| 0
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
a756ee785eec3e83d4eb737191d8fd35a1a37b54
| 214
|
py
|
Python
|
treex/nn/flatten.py
|
ptigwe/treex
|
c46687376ccc50c8fea6cb8617e22e4b4dd1924a
|
[
"MIT"
] | null | null | null |
treex/nn/flatten.py
|
ptigwe/treex
|
c46687376ccc50c8fea6cb8617e22e4b4dd1924a
|
[
"MIT"
] | null | null | null |
treex/nn/flatten.py
|
ptigwe/treex
|
c46687376ccc50c8fea6cb8617e22e4b4dd1924a
|
[
"MIT"
] | null | null | null |
import einops
import jax.numpy as jnp
from treex.module import Module
class Flatten(Module):
def __call__(self, x: jnp.ndarray) -> jnp.ndarray:
return einops.rearrange(x, "batch ... -> batch (...)")
| 21.4
| 62
| 0.672897
| 29
| 214
| 4.827586
| 0.655172
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186916
| 214
| 9
| 63
| 23.777778
| 0.804598
| 0
| 0
| 0
| 0
| 0
| 0.11215
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.5
| 0.166667
| 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
| 1
| 0
| 0
|
0
| 4
|
a79214147c4900ea5accdb8115154b307a9101a1
| 9,906
|
py
|
Python
|
tests/test_model_building.py
|
wahab2604/ESPEI
|
70a4185ce87a125e926f88e7ef93c02276fd6e90
|
[
"MIT"
] | 39
|
2017-11-03T03:07:46.000Z
|
2022-03-17T02:41:59.000Z
|
tests/test_model_building.py
|
richardotis/ESPEI
|
70a4185ce87a125e926f88e7ef93c02276fd6e90
|
[
"MIT"
] | 122
|
2017-06-23T16:34:13.000Z
|
2022-02-21T18:26:01.000Z
|
tests/test_model_building.py
|
richardotis/ESPEI
|
70a4185ce87a125e926f88e7ef93c02276fd6e90
|
[
"MIT"
] | 21
|
2017-06-18T02:36:38.000Z
|
2022-03-29T00:17:21.000Z
|
"""
Tests for building models for parameter selection
"""
from collections import OrderedDict
import sympy
from pycalphad import variables as v
from espei.parameter_selection.model_building import build_feature_sets, build_candidate_models
from espei.sublattice_tools import generate_symmetric_group, sorted_interactions
def test_build_feature_sets_generates_desired_binary_features_for_cp_like():
"""Binary feature sets can be correctly generated for heat capacity-like features"""
binary_temp_features = ['TlogT', 'T**2', '1/T', 'T**3']
binary_excess_features= ['YS', 'YS*Z', 'YS*Z**2', 'YS*Z**3']
feat_sets = build_feature_sets(binary_temp_features, binary_excess_features)
assert len(feat_sets) == 340
assert feat_sets[0] == ((['TlogT'], 'YS'),)
assert feat_sets[5] == ((['TlogT'], 'YS'), (['TlogT', 'T**2'], 'YS*Z'))
assert feat_sets[-1] == ((['TlogT', 'T**2', '1/T', 'T**3'], 'YS'), (['TlogT', 'T**2', '1/T', 'T**3'], 'YS*Z'), (['TlogT', 'T**2', '1/T', 'T**3'], 'YS*Z**2'), (['TlogT', 'T**2', '1/T', 'T**3'], 'YS*Z**3'))
def test_build_feature_sets_generates_desired_binary_features_for_h_like():
"""Binary feature sets can be correctly generated for enthalpy-like models"""
binary_temp_features = ['1']
binary_excess_features= ['YS', 'YS*Z', 'YS*Z**2', 'YS*Z**3']
feat_sets = build_feature_sets(binary_temp_features, binary_excess_features)
assert len(feat_sets) == 4
assert feat_sets[0] == ((['1'], 'YS'),)
assert feat_sets[1] == ((['1'], 'YS'), (['1'], 'YS*Z'))
assert feat_sets[2] == ((['1'], 'YS'), (['1'], 'YS*Z'), (['1'], 'YS*Z**2'))
assert feat_sets[3] == ((['1'], 'YS'), (['1'], 'YS*Z'), (['1'], 'YS*Z**2'), (['1'], 'YS*Z**3'))
def test_build_feature_sets_generates_desired_ternary_features():
"""Ternary feature sets can be correctly generated"""
ternary_temp_features = ['1']
ternary_excess_features= [('YS',), ('YS*V_I', 'YS*V_J', 'YS*V_K')]
feat_sets = build_feature_sets(ternary_temp_features, ternary_excess_features)
assert len(feat_sets) == 2
assert feat_sets[0] == ((['1'], ('YS',)),)
assert feat_sets[1] == ((['1'], ('YS',)), (['1'], ('YS*V_I', 'YS*V_J', 'YS*V_K')))
def test_binary_candidate_models_are_constructed_correctly():
"""Candidate models should be generated for all valid combinations of possible models in the binary case"""
features = OrderedDict([("CPM_FORM",
(v.T*sympy.log(v.T), v.T**2)),
("SM_FORM", (v.T,)),
("HM_FORM", (sympy.S.One,))
])
YS = sympy.Symbol('YS')
Z = sympy.Symbol('Z')
candidate_models = build_candidate_models((('A', 'B'), 'A'), features)
assert candidate_models == OrderedDict([
('CPM_FORM', [
[v.T*YS*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS, v.T*YS*Z*sympy.log(v.T), v.T**2*YS*Z, v.T*YS*Z**2*sympy.log(v.T), v.T**2*YS*Z**2, v.T*YS*Z**3*sympy.log(v.T), v.T**2*YS*Z**3]
]),
('SM_FORM', [
[v.T*YS],
[v.T*YS, v.T*YS*Z],
[v.T*YS, v.T*YS*Z, v.T*YS*Z**2],
[v.T*YS, v.T*YS*Z, v.T*YS*Z**2, v.T*YS*Z**3]
]),
('HM_FORM', [
[YS],
[YS, YS*Z],
[YS, YS*Z, YS*Z**2],
[YS, YS*Z, YS*Z**2, YS*Z**3]
])
])
def test_ternary_candidate_models_are_constructed_correctly():
"""Candidate models should be generated for all valid combinations of possible models in the ternary case"""
features = OrderedDict([("CPM_FORM",
(v.T*sympy.log(v.T), v.T**2)),
("SM_FORM", (v.T,)),
("HM_FORM", (sympy.S.One,))
])
YS = sympy.Symbol('YS')
V_I, V_J, V_K = sympy.Symbol('V_I'), sympy.Symbol('V_J'), sympy.Symbol('V_K')
candidate_models = build_candidate_models((('A', 'B', 'C'), 'A'), features)
assert candidate_models == OrderedDict([
('CPM_FORM', [
[v.T*YS*sympy.log(v.T)],
[v.T*YS*sympy.log(v.T), v.T**2*YS],
[v.T*V_I*YS*sympy.log(v.T), v.T*V_J*YS*sympy.log(v.T), v.T*V_K*YS*sympy.log(v.T)],
[v.T*V_I*YS*sympy.log(v.T), v.T*V_J*YS*sympy.log(v.T), v.T*V_K*YS*sympy.log(v.T), v.T**2*V_I*YS, v.T**2*V_J*YS, v.T**2*V_K*YS],
]),
('SM_FORM', [
[v.T*YS],
[v.T*V_I*YS, v.T*V_J*YS, v.T*V_K*YS]
]),
('HM_FORM', [
[YS],
[V_I*YS, V_J*YS, V_K*YS]
])
])
def test_symmetric_group_can_be_generated_for_2_sl_mixing_with_symmetry():
"""A phase with two sublattices that are mixing should generate a cross interaction"""
symm_groups = generate_symmetric_group((('AL', 'CO'), ('AL', 'CO')), [[0, 1]])
assert symm_groups == [(('AL', 'CO'), ('AL', 'CO'))]
def test_symmetric_group_can_be_generated_for_2_sl_endmembers_with_symmetry():
"""A phase with symmetric sublattices should find a symmetric endmember """
symm_groups = generate_symmetric_group(('AL', 'CO'), [[0, 1]])
assert symm_groups == [('AL', 'CO'), ('CO', 'AL')]
def test_interaction_sorting_is_correct():
"""High order (order >= 3) interactions should sort correctly"""
# Correct sorting of n-order interactions should sort first by number of
# interactions of order n, then n-1, then n-2... to 1
unsorted_interactions = [
('AL', ('AL', 'CO', 'CR')),
(('AL', 'CO'), ('AL', 'CO', 'CR')),
(('AL', 'CO', 'CR'), ('AL', 'CO', 'CR')),
(('AL', 'CO', 'CR'), 'AL'),
(('AL', 'CO', 'CR'), ('AL', 'CO')),
(('AL', 'CO', 'CR'), ('AL', 'CR')),
(('AL', 'CO', 'CR'), 'CO'),
(('AL', 'CO', 'CR'), ('CO', 'CR')),
(('AL', 'CO', 'CR'), 'CR'),
(('AL', 'CR'), ('AL', 'CO', 'CR')),
('CO', ('AL', 'CO', 'CR')),
(('CO', 'CR'), ('AL', 'CO', 'CR')),
('CR', ('AL', 'CO', 'CR')),
]
interactions = sorted_interactions(unsorted_interactions, max_interaction_order=3, symmetry=None)
# the numbers are the different sort scores. Two of the same sort scores mean
# the order doesn't matter
assert interactions == [
('AL', ('AL', 'CO', 'CR')), # (1, 0, 1)
(('AL', 'CO', 'CR'), 'AL'), # (1, 0, 1)
(('AL', 'CO', 'CR'), 'CO'), # (1, 0, 1)
(('AL', 'CO', 'CR'), 'CR'), # (1, 0, 1)
('CO', ('AL', 'CO', 'CR')), # (1, 0, 1)
('CR', ('AL', 'CO', 'CR')), # (1, 0, 1)
]
| 55.966102
| 208
| 0.519887
| 1,971
| 9,906
| 2.521563
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| 0.772233
| 0.74004
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| 0.678873
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| 9,906
| 176
| 209
| 56.284091
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| 0
| 0
|
0
| 4
|
a793d30af0730653e95a962efbfe175eb6c5aed2
| 142
|
py
|
Python
|
torch_scope/__main__.py
|
LiyuanLucasLiu/PyScope
|
d6366e604f9a7763279310149b154ea1cc22f4c1
|
[
"Apache-2.0"
] | 62
|
2018-09-11T01:04:38.000Z
|
2022-03-19T13:00:38.000Z
|
torch_scope/__main__.py
|
jainaayush05/Torch-Scope
|
bbc8b6e2562cbc6305ea6d937bcd6f96542755f6
|
[
"Apache-2.0"
] | 3
|
2019-03-16T16:25:52.000Z
|
2021-05-10T14:02:13.000Z
|
torch_scope/__main__.py
|
jainaayush05/Torch-Scope
|
bbc8b6e2562cbc6305ea6d937bcd6f96542755f6
|
[
"Apache-2.0"
] | 9
|
2018-10-04T00:30:17.000Z
|
2020-12-28T05:54:36.000Z
|
#!/usr/bin/env python
import logging
import os
import sys
import argparse
from torch_scope import run
if __name__ == "__main__":
run()
| 11.833333
| 27
| 0.732394
| 21
| 142
| 4.52381
| 0.761905
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| 0.183099
| 142
| 11
| 28
| 12.909091
| 0.818966
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| 1
| 0
| 1
| 0
|
0
| 4
|
a7c7b453410bb1602137c476d542cc616ada50fc
| 91
|
py
|
Python
|
LectioEx/apps.py
|
danielrhj123/LectioBadges
|
b266f1fe65f53e6f41fa53ee15cce0235fc26f1b
|
[
"Apache-2.0"
] | null | null | null |
LectioEx/apps.py
|
danielrhj123/LectioBadges
|
b266f1fe65f53e6f41fa53ee15cce0235fc26f1b
|
[
"Apache-2.0"
] | null | null | null |
LectioEx/apps.py
|
danielrhj123/LectioBadges
|
b266f1fe65f53e6f41fa53ee15cce0235fc26f1b
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class LectioexConfig(AppConfig):
name = 'LectioEx'
| 15.166667
| 33
| 0.758242
| 10
| 91
| 6.9
| 0.9
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| 91
| 5
| 34
| 18.2
| 0.907895
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| 1
| 0
|
0
| 4
|
a7cae359630b219619c556f9bbeed8a262622b88
| 256
|
py
|
Python
|
backend/project/posts/utils/PostAlbumUtil.py
|
winoutt/winoutt-django
|
f48dfd933b3c12286f973701676eb2c2ab2bff73
|
[
"MIT"
] | null | null | null |
backend/project/posts/utils/PostAlbumUtil.py
|
winoutt/winoutt-django
|
f48dfd933b3c12286f973701676eb2c2ab2bff73
|
[
"MIT"
] | null | null | null |
backend/project/posts/utils/PostAlbumUtil.py
|
winoutt/winoutt-django
|
f48dfd933b3c12286f973701676eb2c2ab2bff73
|
[
"MIT"
] | null | null | null |
from project.posts.models import PostAlbum
def create(post, photos):
for photo in photos:
PostAlbum.objects.create(post=post, photo=photo, photo_original=photo)
def get_post_album(post):
return PostAlbum.objects.filter(post=post)
| 28.444444
| 79
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| 35
| 256
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| 256
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| 1
| 0
|
0
| 4
|
a7cc8cbafb3b6554e6da16e394dcc09278a0a24e
| 14,288
|
py
|
Python
|
mofa/scheduler/tests/test_data.py
|
BoxInABoxICT/BoxPlugin
|
ad351978faa37ab867a86d2f4023a2b3e5a2ce19
|
[
"Apache-2.0"
] | null | null | null |
mofa/scheduler/tests/test_data.py
|
BoxInABoxICT/BoxPlugin
|
ad351978faa37ab867a86d2f4023a2b3e5a2ce19
|
[
"Apache-2.0"
] | null | null | null |
mofa/scheduler/tests/test_data.py
|
BoxInABoxICT/BoxPlugin
|
ad351978faa37ab867a86d2f4023a2b3e5a2ce19
|
[
"Apache-2.0"
] | null | null | null |
# This program has been developed by students from the bachelor Computer Science at Utrecht University within the
# Software and Game project course
# ©Copyright Utrecht University Department of Information and Computing Sciences.
"""Contains test data."""
test_get_assignments_data = \
{
"courses": [
{
"assignments": [
{
"cmid": 6,
"name": "Learning basic loops",
"duedate": 1573776060,
},
{
"cmid": 9,
"name": "Learning booleans",
"duedate": 1573776060,
},
]
}
],
"warnings": []
}
test_get_assignments_check = \
[
{
"cmid": 6,
"name": "Learning basic loops",
"duedate": 1573776060,
},
{
"cmid": 9,
"name": "Learning booleans",
"duedate": 1573776060,
},
]
test_assignment_completion_check = \
{
"statuses": [
{
"cmid": 6,
"state": 1
},
{
"cmid": 9,
"state": 0
}
],
"warnings": []
}
test_get_enrolled_users = \
[
{
"id": 4,
"username": "WS",
"firstname": "Will",
"lastname": "Smith",
"fullname": "Will Smith",
}
]
test_inactivity_get_enrolled_users = \
[
{
"id": 2
},
{
"id": 3
},
{
"id": 4
},
{
"id": 5
}
]
test_get_courses_by_id = \
{
'courses': [
{
'id': 2,
'fullname': 'BeginningCourse'
}
]
}
test_get_courses_by_id_ended = \
{
'courses': [
{
'id': 2,
'fullname': 'No view course',
'displayname': 'No view course',
'shortname': 'nvc',
'categoryid': 1,
'categoryname': 'Miscellaneous',
'sortorder': 10001,
'summary': '',
'summaryformat': 1,
'summaryfiles': [],
'overviewfiles': [],
'contacts': [
{'id': 4,
'fullname': 'Saskia Restful Notificaties'}],
'enrollmentmethods': ['manual'],
'idnumber': '',
'format': 'topics',
'showgrades': 1,
'newsitems': 5,
'startdate': 1605740400,
'enddate': 1637276800,
'maxbytes': 0,
'showreports': 0,
'visible': 1,
'groupmode': 0,
'groupmodeforce': 0,
'defaultgroupingid': 0,
'enablecompletion': 1,
'completionnotify': 0,
'lang': '',
'theme': '',
'marker': 0,
'legacyfiles': 0,
'calendartype': '',
'timecreated': 1605708824,
'timemodified': 1605708824,
'requested': 0,
'cacherev': 1605801045,
'filters': [{'filter': 'displayh5p', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'activitynames', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mathjaxloader', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'emoticon', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'urltolink', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mediaplugin', 'localstate': 0, 'inheritedstate': 1}],
'courseformatoptions': [{'name': 'hiddensections', 'value': 0},
{'name': 'coursedisplay', 'value': 0}]}]
}
test_get_courses_by_id_live = \
{
'courses': [
{
'id': 2,
'fullname': 'No view course',
'displayname': 'No view course',
'shortname': 'nvc',
'categoryid': 1,
'categoryname': 'Miscellaneous',
'sortorder': 10001,
'summary': '',
'summaryformat': 1,
'summaryfiles': [],
'overviewfiles': [],
'contacts': [
{'id': 4,
'fullname': 'Saskia Restful Notificaties'}],
'enrollmentmethods': ['manual'],
'idnumber': '',
'format': 'topics',
'showgrades': 1,
'newsitems': 5,
'startdate': 1605740400,
'enddate': 1637276400,
'maxbytes': 0,
'showreports': 0,
'visible': 1,
'groupmode': 0,
'groupmodeforce': 0,
'defaultgroupingid': 0,
'enablecompletion': 1,
'completionnotify': 0,
'lang': '',
'theme': '',
'marker': 0,
'legacyfiles': 0,
'calendartype': '',
'timecreated': 1605708824,
'timemodified': 1605708824,
'requested': 0,
'cacherev': 1605801045,
'filters': [{'filter': 'displayh5p', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'activitynames', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mathjaxloader', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'emoticon', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'urltolink', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mediaplugin', 'localstate': 0, 'inheritedstate': 1}],
'courseformatoptions': [{'name': 'hiddensections', 'value': 0},
{'name': 'coursedisplay', 'value': 0}]}]
}
test_get_courses_by_id_young = \
{
'courses': [
{
'id': 2,
'fullname': 'No view course',
'displayname': 'No view course',
'shortname': 'nvc',
'categoryid': 1,
'categoryname': 'Miscellaneous',
'sortorder': 10001,
'summary': '',
'summaryformat': 1,
'summaryfiles': [],
'overviewfiles': [],
'contacts': [
{'id': 4,
'fullname': 'Saskia Restful Notificaties'}],
'enrollmentmethods': ['manual'],
'idnumber': '',
'format': 'topics',
'showgrades': 1,
'newsitems': 5,
'startdate': 1605740400,
'enddate': 1606487200,
'maxbytes': 0,
'showreports': 0,
'visible': 1,
'groupmode': 0,
'groupmodeforce': 0,
'defaultgroupingid': 0,
'enablecompletion': 1,
'completionnotify': 0,
'lang': '',
'theme': '',
'marker': 0,
'legacyfiles': 0,
'calendartype': '',
'timecreated': 1606400370,
'timemodified': 1605708824,
'requested': 0,
'cacherev': 1605801045,
'filters': [{'filter': 'displayh5p', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'activitynames', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mathjaxloader', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'emoticon', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'urltolink', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mediaplugin', 'localstate': 0, 'inheritedstate': 1}],
'courseformatoptions': [{'name': 'hiddensections', 'value': 0},
{'name': 'coursedisplay', 'value': 0}]}]
}
test_get_courses_by_id_old = \
{
'courses': [
{
'id': 2,
'fullname': 'No view course',
'displayname': 'No view course',
'shortname': 'nvc',
'categoryid': 1,
'categoryname': 'Miscellaneous',
'sortorder': 10001,
'summary': '',
'summaryformat': 1,
'summaryfiles': [],
'overviewfiles': [],
'contacts': [
{'id': 4,
'fullname': 'Saskia Restful Notificaties'}],
'enrollmentmethods': ['manual'],
'idnumber': '',
'format': 'topics',
'showgrades': 1,
'newsitems': 5,
'startdate': 1605740400,
'enddate': 1637276400,
'maxbytes': 0,
'showreports': 0,
'visible': 1,
'groupmode': 0,
'groupmodeforce': 0,
'defaultgroupingid': 0,
'enablecompletion': 1,
'completionnotify': 0,
'lang': '',
'theme': '',
'marker': 0,
'legacyfiles': 0,
'calendartype': '',
'timecreated': 1605708824,
'timemodified': 1605708824,
'requested': 0,
'cacherev': 1605801045,
'filters': [{'filter': 'displayh5p', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'activitynames', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mathjaxloader', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'emoticon', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'urltolink', 'localstate': 0, 'inheritedstate': 1},
{'filter': 'mediaplugin', 'localstate': 0, 'inheritedstate': 1}],
'courseformatoptions': [{'name': 'hiddensections', 'value': 0},
{'name': 'coursedisplay', 'value': 0}]}]
}
test_learning_locker_viewed_course = \
{
"more": "",
"statements": [
{
"actor": {
"name": "Admin User",
"account": {
"homePage": "http://127.0.0.1:80",
"name": "2"
},
"objectType": "Assistant"
},
"verb": {
"id": "http://id.tincanapi.com/verb/viewed",
"display": {
"en": "viewed"
}
},
"object": {
"id": "http://127.0.0.1:80/course/view.php?id=2",
"definition": {
"type": "http://id.tincanapi.com/activitytype/lms/course",
"name": {
"en": "BeginningCourse"
},
"extensions": {
"https://w3id.org/learning-analytics/learning-management-system/short-id": "BC",
"https://w3id.org/learning-analytics/learning-management-system/external-id": "7"
}
},
"objectType": "Activity"
},
"timestamp": "2019-10-16T11:26:19+01:00",
"context": {
"platform": "Moodle",
"language": "en",
"extensions": {
"http://lrs.learninglocker.net/define/extensions/info": {
"http://moodle.org": "3.7.2 (Build: 20190909)",
"https://github.com/xAPI-vle/moodle-logstore_xapi": "v4.4.0",
"event_name": "\\core\\event\\course_viewed",
"event_function": "\\src\\transformer\\events\\core\\course_viewed"
}
},
"contextActivities": {
"grouping": [
{
"id": "http://127.0.0.1:80",
"definition": {
"type": "http://id.tincanapi.com/activitytype/lms",
"name": {
"en": "\"New Site\""
}
},
"objectType": "Activity"
}
],
"category": [
{
"id": "http://moodle.org",
"definition": {
"type": "http://id.tincanapi.com/activitytype/source",
"name": {
"en": "Moodle"
}
},
"objectType": "Activity"
}
]
}
},
"id": "c98c8522-3d43-4098-9b5d-812392458328",
"stored": "2019-10-16T10:27:02.866Z",
"authority": {
"objectType": "Assistant",
"name": "New Client",
"mbox": "mailto:hello@learninglocker.net"
},
"version": "1.0.0"
}
]
}
| 37.208333
| 113
| 0.369611
| 843
| 14,288
| 6.207592
| 0.26809
| 0.050449
| 0.114657
| 0.119243
| 0.749857
| 0.742977
| 0.740684
| 0.726925
| 0.688706
| 0.688706
| 0
| 0.070219
| 0.491671
| 14,288
| 383
| 114
| 37.305483
| 0.650145
| 0.017147
| 0
| 0.589674
| 0
| 0.002717
| 0.323691
| 0.013609
| 0
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| false
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| null | 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ac0c8729aa498249703102ea0f30adabcd30e835
| 54
|
py
|
Python
|
anonymizer/__init__.py
|
jjhuang/django-anonymizer
|
2d25bb6e8b5e4230c58031c4b6d10cc536669b3e
|
[
"MIT"
] | 13
|
2016-05-24T07:40:17.000Z
|
2021-09-07T20:38:18.000Z
|
anonymizer/__init__.py
|
jjhuang/django-anonymizer
|
2d25bb6e8b5e4230c58031c4b6d10cc536669b3e
|
[
"MIT"
] | 32
|
2015-02-02T23:39:32.000Z
|
2021-01-14T06:29:05.000Z
|
anonymizer/__init__.py
|
jjhuang/django-anonymizer
|
2d25bb6e8b5e4230c58031c4b6d10cc536669b3e
|
[
"MIT"
] | 14
|
2015-03-22T15:22:24.000Z
|
2020-01-09T19:03:01.000Z
|
# flake8: noqa
from anonymizer.base import Anonymizer
| 18
| 38
| 0.814815
| 7
| 54
| 6.285714
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.021277
| 0.12963
| 54
| 2
| 39
| 27
| 0.914894
| 0.222222
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
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| 1
| 0
| true
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| null | 0
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| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ac15f226c90d4ebb8e381060da094ff5c3be1e8d
| 678
|
py
|
Python
|
game_object_factory.py
|
cxong/Slappa
|
bb601734db07ee1f1e1d3763d2c5f6146248fd76
|
[
"MIT"
] | 7
|
2015-02-24T22:24:45.000Z
|
2021-05-15T16:39:27.000Z
|
game_object_factory.py
|
cxong/Slappa
|
bb601734db07ee1f1e1d3763d2c5f6146248fd76
|
[
"MIT"
] | null | null | null |
game_object_factory.py
|
cxong/Slappa
|
bb601734db07ee1f1e1d3763d2c5f6146248fd76
|
[
"MIT"
] | 1
|
2016-06-22T11:50:22.000Z
|
2016-06-22T11:50:22.000Z
|
from group import *
from image import *
from sound import *
from sprite import *
from text import *
class GameObjectFactory(object):
def __init__(self, game):
self.game = game
def audio(self, key):
return Sound(self.game, key)
def group(self):
return self.game.world.add(Group())
def image(self, x, y, key, scale=Point(1, 1)):
return self.game.world.add(Image(self.game, x, y, key, scale))
def sprite(self, x, y, key, scale=Point(1, 1)):
return self.game.world.add(Sprite(self.game, x, y, key, scale))
def text(self, x, y, text, style):
return self.game.world.add(Text(self.game, x, y, text, style))
| 27.12
| 71
| 0.629794
| 106
| 678
| 3.990566
| 0.235849
| 0.189125
| 0.132388
| 0.179669
| 0.406619
| 0.3026
| 0.3026
| 0.20331
| 0.20331
| 0.20331
| 0
| 0.007634
| 0.227139
| 678
| 25
| 72
| 27.12
| 0.799618
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.277778
| 0.277778
| 0.944444
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
ac19ff3ff344feb5dbc15a2c9076538f3416b5bb
| 248
|
py
|
Python
|
doppel/__init__.py
|
bburns632/doppel-cli
|
e0c708f565db0f558bca6f2fbe28a41d45121344
|
[
"BSD-3-Clause"
] | null | null | null |
doppel/__init__.py
|
bburns632/doppel-cli
|
e0c708f565db0f558bca6f2fbe28a41d45121344
|
[
"BSD-3-Clause"
] | null | null | null |
doppel/__init__.py
|
bburns632/doppel-cli
|
e0c708f565db0f558bca6f2fbe28a41d45121344
|
[
"BSD-3-Clause"
] | null | null | null |
__all__ = [
'PackageAPI',
'PackageCollection'
]
from doppel.PackageAPI import PackageAPI
from doppel.PackageCollection import PackageCollection
from doppel.DoppelTestError import DoppelTestError
from doppel.reporters import SimpleReporter
| 24.8
| 54
| 0.826613
| 23
| 248
| 8.73913
| 0.391304
| 0.199005
| 0.268657
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 248
| 9
| 55
| 27.555556
| 0.926267
| 0
| 0
| 0
| 0
| 0
| 0.108871
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
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| null | 0
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| 0
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ac62cf229bd1d4301ba72c65982f715066b302c5
| 79
|
py
|
Python
|
setup.py
|
symonk/zentinel
|
6ec390dc8947e81a867b5fdbcf0993cd3471a9f4
|
[
"Apache-2.0"
] | null | null | null |
setup.py
|
symonk/zentinel
|
6ec390dc8947e81a867b5fdbcf0993cd3471a9f4
|
[
"Apache-2.0"
] | 31
|
2021-08-03T03:24:27.000Z
|
2022-03-28T03:21:52.000Z
|
setup.py
|
symonk/zentinel
|
6ec390dc8947e81a867b5fdbcf0993cd3471a9f4
|
[
"Apache-2.0"
] | null | null | null |
import setuptools
setuptools.setup() # still required for editable installs.
| 19.75
| 59
| 0.797468
| 9
| 79
| 7
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.139241
| 79
| 3
| 60
| 26.333333
| 0.926471
| 0.468354
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ac6ad863be46a739ea8270a4b77f8c43b55f6302
| 621
|
py
|
Python
|
inferelator_prior/motifs/__init__.py
|
cskokgibbs/srrTomat0
|
9cfdf620bc6d8741587e59e017046c3e7e169fd7
|
[
"MIT"
] | 4
|
2020-10-26T14:19:04.000Z
|
2022-02-16T21:36:28.000Z
|
inferelator_prior/motifs/__init__.py
|
flatironinstitute/srrTomat0
|
9255d5a52bc4425346f578841004955c72b4ba76
|
[
"MIT"
] | 3
|
2022-02-01T04:38:26.000Z
|
2022-03-24T14:37:17.000Z
|
inferelator_prior/motifs/__init__.py
|
flatironinstitute/srrTomat0
|
9255d5a52bc4425346f578841004955c72b4ba76
|
[
"MIT"
] | 1
|
2021-09-23T01:09:17.000Z
|
2021-09-23T01:09:17.000Z
|
from inferelator_prior.motifs._motif import (Motif, motifs_to_dataframe, chunk_motifs, select_motifs, truncate_motifs,
fuzzy_merge_motifs, shuffle_motifs,
INFO_COL, MOTIF_COL, ENTROPY_COL, LEN_COL, OCC_COL, MOTIF_NAME_COL,
SCAN_SCORE_COL, SCORE_PER_BASE, MOTIF_OBJ_COL, MOTIF_CONSENSUS_COL,
MOTIF_ORIGINAL_NAME_COL)
from inferelator_prior.motifs.motif_scan import MotifScan
from inferelator_prior.motifs.motif_loader import load_motif_file
| 69
| 118
| 0.621578
| 68
| 621
| 5.176471
| 0.455882
| 0.090909
| 0.170455
| 0.221591
| 0.264205
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.338164
| 621
| 8
| 119
| 77.625
| 0.856448
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.428571
| 0
| 0.428571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ac808334f93c0b8f4faf9c689f174cfb852454e7
| 4,906
|
py
|
Python
|
Laelia/apps/base/migrations/0007_auto_20201001_1747.py
|
arantesdv/LaeliaAppProject
|
93fca5393cb8406694903d9adde02067480c792e
|
[
"MIT"
] | null | null | null |
Laelia/apps/base/migrations/0007_auto_20201001_1747.py
|
arantesdv/LaeliaAppProject
|
93fca5393cb8406694903d9adde02067480c792e
|
[
"MIT"
] | null | null | null |
Laelia/apps/base/migrations/0007_auto_20201001_1747.py
|
arantesdv/LaeliaAppProject
|
93fca5393cb8406694903d9adde02067480c792e
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.0.6 on 2020-10-01 17:47
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('base', '0006_auto_20201001_1731'),
]
operations = [
migrations.CreateModel(
name='City',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('en_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='English Name')),
('pt_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Portuguese Name')),
('es_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Spanish Name')),
('_search_names', models.CharField(blank=True, editable=False, max_length=255, null=True)),
],
options={
'ordering': ['pt_name'],
'abstract': False,
},
),
migrations.CreateModel(
name='Nation',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('en_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='English Name')),
('pt_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Portuguese Name')),
('es_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Spanish Name')),
('_search_names', models.CharField(blank=True, editable=False, max_length=255, null=True)),
('abrev', models.CharField(max_length=3, verbose_name='Nation Abreviation')),
],
options={
'ordering': ['pt_name'],
'abstract': False,
},
),
migrations.AlterModelOptions(
name='patient',
options={'verbose_name': 'Patient', 'verbose_name_plural': 'Patients'},
),
migrations.AlterModelOptions(
name='professional',
options={'verbose_name': 'Professional', 'verbose_name_plural': 'Professionals'},
),
migrations.RemoveField(
model_name='patient',
name='main_phone',
),
migrations.RemoveField(
model_name='patient',
name='other_phone',
),
migrations.RemoveField(
model_name='professional',
name='main_phone',
),
migrations.RemoveField(
model_name='professional',
name='other_phone',
),
migrations.CreateModel(
name='Region',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('en_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='English Name')),
('pt_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Portuguese Name')),
('es_name', models.CharField(blank=True, max_length=255, null=True, verbose_name='Spanish Name')),
('_search_names', models.CharField(blank=True, editable=False, max_length=255, null=True)),
('abrev', models.CharField(max_length=2, verbose_name='Region Abreviation')),
('nation', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='base.Nation')),
],
options={
'ordering': ['pt_name'],
'abstract': False,
},
),
migrations.AddConstraint(
model_name='nation',
constraint=models.UniqueConstraint(fields=('pt_name',), name='unique_nation'),
),
migrations.AddField(
model_name='city',
name='region',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='base.Region'),
),
migrations.AddField(
model_name='patient',
name='city',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='base.City'),
),
migrations.AddField(
model_name='professional',
name='city',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='base.City'),
),
migrations.AddConstraint(
model_name='region',
constraint=models.UniqueConstraint(fields=('pt_name',), name='unique_region'),
),
migrations.AddConstraint(
model_name='city',
constraint=models.UniqueConstraint(fields=('pt_name',), name='unique_city'),
),
]
| 44.198198
| 133
| 0.578679
| 494
| 4,906
| 5.566802
| 0.17004
| 0.072
| 0.087273
| 0.104727
| 0.730909
| 0.730909
| 0.713455
| 0.611273
| 0.552364
| 0.552364
| 0
| 0.019586
| 0.2819
| 4,906
| 110
| 134
| 44.6
| 0.760999
| 0.009172
| 0
| 0.730769
| 1
| 0
| 0.153735
| 0.004733
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.019231
| 0
| 0.048077
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ac8bf56ac51206c7a84e0866931cdf513a3b552d
| 563
|
py
|
Python
|
problems/image_text_to_class/__init__.py
|
aasseman/mi-prometheus
|
c655c88cc6aec4d0724c19ea95209f1c2dd6770d
|
[
"Apache-2.0"
] | null | null | null |
problems/image_text_to_class/__init__.py
|
aasseman/mi-prometheus
|
c655c88cc6aec4d0724c19ea95209f1c2dd6770d
|
[
"Apache-2.0"
] | null | null | null |
problems/image_text_to_class/__init__.py
|
aasseman/mi-prometheus
|
c655c88cc6aec4d0724c19ea95209f1c2dd6770d
|
[
"Apache-2.0"
] | null | null | null |
from .clevr import CLEVR
from .clevr_dataset import CLEVRDataset
from .generate_feature_maps import GenerateFeatureMaps
from .image_text_to_class_problem import ImageTextTuple, SceneDescriptionTuple, ObjectRepresentation, \
ImageTextToClassProblem
from .sort_of_clevr import SortOfCLEVR
from .shape_color_query import ShapeColorQuery
__all__ = [
'CLEVR',
'CLEVRDataset',
'GenerateFeatureMaps',
'ImageTextTuple',
'SceneDescriptionTuple',
'ObjectRepresentation',
'ImageTextToClassProblem',
'SortOfCLEVR',
'ShapeColorQuery']
| 29.631579
| 103
| 0.786856
| 48
| 563
| 8.916667
| 0.541667
| 0.042056
| 0.257009
| 0.364486
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.143872
| 563
| 18
| 104
| 31.277778
| 0.887967
| 0
| 0
| 0
| 1
| 0
| 0.248668
| 0.078153
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.352941
| 0
| 0.352941
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ce16fbb00f62e84f4f5aca7b25c9bfee0eab6d55
| 113
|
py
|
Python
|
DeepLearning/Python/Chapter 2/Ch02-02-perceptron.py
|
BlueWay-KU/Study
|
a86405cdc3011eaed1b980b562b75df1e9ce90a8
|
[
"MIT"
] | null | null | null |
DeepLearning/Python/Chapter 2/Ch02-02-perceptron.py
|
BlueWay-KU/Study
|
a86405cdc3011eaed1b980b562b75df1e9ce90a8
|
[
"MIT"
] | null | null | null |
DeepLearning/Python/Chapter 2/Ch02-02-perceptron.py
|
BlueWay-KU/Study
|
a86405cdc3011eaed1b980b562b75df1e9ce90a8
|
[
"MIT"
] | null | null | null |
import numpy as np
x = np.array([0, 1])
w = np.array([0.5, 0.5])
b = -0.7
w * b
np.sum(w*x)
np.sum(w*x) + b
| 16.142857
| 25
| 0.504425
| 30
| 113
| 1.9
| 0.433333
| 0.105263
| 0.280702
| 0.245614
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 0.238938
| 113
| 7
| 26
| 16.142857
| 0.569767
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 0.142857
| 0
| 0
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ce27c499b433c15c668c2ace26e7f7faefe6633e
| 89
|
py
|
Python
|
courses/backend/django-for-everybody/Web Application Technologies and Django/resources/dj4e-samples/bookone/apps.py
|
Nahid-Hassan/fullstack-software-development
|
892ffb33e46795061ea63378279a6469de317b1a
|
[
"CC0-1.0"
] | 297
|
2019-01-25T08:44:08.000Z
|
2022-03-29T18:46:08.000Z
|
courses/backend/django-for-everybody/Web Application Technologies and Django/resources/dj4e-samples/bookone/apps.py
|
Nahid-Hassan/fullstack-software-development
|
892ffb33e46795061ea63378279a6469de317b1a
|
[
"CC0-1.0"
] | 22
|
2019-05-06T14:21:04.000Z
|
2022-02-21T10:05:25.000Z
|
courses/backend/django-for-everybody/Web Application Technologies and Django/resources/dj4e-samples/bookone/apps.py
|
Nahid-Hassan/fullstack-software-development
|
892ffb33e46795061ea63378279a6469de317b1a
|
[
"CC0-1.0"
] | 412
|
2019-02-12T20:44:43.000Z
|
2022-03-30T04:23:25.000Z
|
from django.apps import AppConfig
class BookoneConfig(AppConfig):
name = 'bookone'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ce360663122039f12cbec525f04adceb270da9d5
| 546
|
py
|
Python
|
svhn_32x32_download.py
|
vrishabh22/OCR-Minor-Project
|
ea717f2b6aa1618742b6697dd7f8dc40cb3450c2
|
[
"MIT"
] | null | null | null |
svhn_32x32_download.py
|
vrishabh22/OCR-Minor-Project
|
ea717f2b6aa1618742b6697dd7f8dc40cb3450c2
|
[
"MIT"
] | null | null | null |
svhn_32x32_download.py
|
vrishabh22/OCR-Minor-Project
|
ea717f2b6aa1618742b6697dd7f8dc40cb3450c2
|
[
"MIT"
] | null | null | null |
import urllib
print("Downloading Test Folder")
urllib.urlretrieve("http://ufldl.stanford.edu/housenumbers/test_32x32.mat", "data/test_32x32.mat")
print("Test Folder Images Download Done")
print("Downloading Train Folder")
urllib.urlretrieve("http://ufldl.stanford.edu/housenumbers/train_32x32.mat", "data/train_32x32.mat")
print("Train Folder Images Download Done")
print("Downloading Extra Folder")
urllib.urlretrieve("http://ufldl.stanford.edu/housenumbers/extra_32x32.mat", "data/extra_32x32.mat")
print("Extra Folder Images Download Done")
| 42
| 100
| 0.794872
| 74
| 546
| 5.783784
| 0.27027
| 0.11215
| 0.161215
| 0.189252
| 0.57243
| 0.57243
| 0.385514
| 0.385514
| 0
| 0
| 0
| 0.046875
| 0.062271
| 546
| 13
| 101
| 42
| 0.789063
| 0
| 0
| 0
| 0
| 0
| 0.711152
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.1
| 0
| 0.1
| 0.6
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
ce407be83429722c411e95e51697c641146a6ffa
| 341
|
py
|
Python
|
hooks/webkitpy/common/checkout/scm/__init__.py
|
nizovn/luna-sysmgr
|
48b7e2546e81d6ad1604353f2e5ab797a7d1667c
|
[
"Apache-2.0"
] | 3
|
2018-11-16T14:51:17.000Z
|
2019-11-21T10:55:24.000Z
|
hooks/webkitpy/common/checkout/scm/__init__.py
|
nizovn/luna-sysmgr
|
48b7e2546e81d6ad1604353f2e5ab797a7d1667c
|
[
"Apache-2.0"
] | 1
|
2021-02-20T13:12:15.000Z
|
2021-02-20T13:12:15.000Z
|
hooks/webkitpy/common/checkout/scm/__init__.py
|
ericblade/luna-sysmgr
|
82d5d7ced4ba21d3802eb2c8ae063236b6562331
|
[
"Apache-2.0"
] | null | null | null |
# Required for Python to search this directory for module files
# We only export public API here.
from .commitmessage import CommitMessage
from .detection import find_checkout_root, default_scm, detect_scm_system
from .git import Git, AmbiguousCommitError
from .scm import SCM, AuthenticationError, CheckoutNeedsUpdate
from .svn import SVN
| 37.888889
| 73
| 0.832845
| 46
| 341
| 6.065217
| 0.673913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 341
| 8
| 74
| 42.625
| 0.939394
| 0.272727
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
022a770977389b7ec27848553cbc49bab53d1500
| 174
|
py
|
Python
|
nestedtensor/version.py
|
swolchok/nestedtensor
|
3300e3bc42394ab4bb226cef8acc631012a72ef0
|
[
"BSD-3-Clause"
] | null | null | null |
nestedtensor/version.py
|
swolchok/nestedtensor
|
3300e3bc42394ab4bb226cef8acc631012a72ef0
|
[
"BSD-3-Clause"
] | null | null | null |
nestedtensor/version.py
|
swolchok/nestedtensor
|
3300e3bc42394ab4bb226cef8acc631012a72ef0
|
[
"BSD-3-Clause"
] | null | null | null |
__version__ = '0.1.4+5b45731'
git_version = '5b457313bfb6578b43d76282b321657bf85ee1b3'
from nestedtensor import _C
if hasattr(_C, 'CUDA_VERSION'):
cuda = _C.CUDA_VERSION
| 29
| 56
| 0.787356
| 21
| 174
| 6.047619
| 0.666667
| 0.07874
| 0.188976
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.24026
| 0.114943
| 174
| 5
| 57
| 34.8
| 0.584416
| 0
| 0
| 0
| 0
| 0
| 0.373563
| 0.229885
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
65f095568508eb3d1e1246c7aecfc59075f5d3b8
| 72
|
py
|
Python
|
test/test_find_the_difference.py
|
spencercjh/sync-leetcode-today-problem-python3-example
|
4957e5eadb697334741df0fc297bec2edaa9e2ab
|
[
"Apache-2.0"
] | null | null | null |
test/test_find_the_difference.py
|
spencercjh/sync-leetcode-today-problem-python3-example
|
4957e5eadb697334741df0fc297bec2edaa9e2ab
|
[
"Apache-2.0"
] | null | null | null |
test/test_find_the_difference.py
|
spencercjh/sync-leetcode-today-problem-python3-example
|
4957e5eadb697334741df0fc297bec2edaa9e2ab
|
[
"Apache-2.0"
] | null | null | null |
solution = FindTheDifference()
assert X == solution.findTheDifference( )
| 36
| 41
| 0.791667
| 6
| 72
| 9.5
| 0.666667
| 0.877193
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097222
| 72
| 2
| 41
| 36
| 0.876923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
65f5bce50e98aea9183af893c3ec3e7b75d3d5a4
| 20
|
py
|
Python
|
stock/quant/__init__.py
|
shenzhongqiang/cnstock_py
|
2bb557657a646acb9d20d3ce78e15cf68390f8ea
|
[
"MIT"
] | 2
|
2016-10-31T04:05:11.000Z
|
2017-04-17T08:46:53.000Z
|
stock/quant/__init__.py
|
shenzhongqiang/cnstock_py
|
2bb557657a646acb9d20d3ce78e15cf68390f8ea
|
[
"MIT"
] | null | null | null |
stock/quant/__init__.py
|
shenzhongqiang/cnstock_py
|
2bb557657a646acb9d20d3ce78e15cf68390f8ea
|
[
"MIT"
] | null | null | null |
__all__ = ['covar']
| 10
| 19
| 0.6
| 2
| 20
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 20
| 1
| 20
| 20
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a0650eab0fc64033085b16aad8e3094c165d5c2
| 76
|
py
|
Python
|
Seman4/Dia1/04-programas.py
|
GuidoTorres/codigo8
|
7fdff4f677f048de7d7877b96ec3a688d3dde163
|
[
"MIT"
] | null | null | null |
Seman4/Dia1/04-programas.py
|
GuidoTorres/codigo8
|
7fdff4f677f048de7d7877b96ec3a688d3dde163
|
[
"MIT"
] | 40
|
2021-03-10T16:58:17.000Z
|
2022-03-26T01:55:17.000Z
|
Seman4/Dia1/04-programas.py
|
GuidoTorres/codigo8
|
7fdff4f677f048de7d7877b96ec3a688d3dde163
|
[
"MIT"
] | null | null | null |
#Añadir un modulo a nuestro programa
import modulo
modulo.saludar("Guido")
| 15.2
| 36
| 0.789474
| 11
| 76
| 5.454545
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131579
| 76
| 5
| 37
| 15.2
| 0.909091
| 0.460526
| 0
| 0
| 0
| 0
| 0.121951
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
5a17699849990e9a2eb1334957d27180b197290a
| 89
|
py
|
Python
|
regform/apps.py
|
elishaking/django-form
|
97f25aa2e54238d2432ce60a77e248da06af3745
|
[
"MIT"
] | null | null | null |
regform/apps.py
|
elishaking/django-form
|
97f25aa2e54238d2432ce60a77e248da06af3745
|
[
"MIT"
] | 1
|
2020-01-28T14:18:41.000Z
|
2020-01-28T14:18:41.000Z
|
regform/apps.py
|
elishaking/django-form
|
97f25aa2e54238d2432ce60a77e248da06af3745
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class RegformConfig(AppConfig):
name = 'regform'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
5a2e54cfc025b9dad0981d3f6cc37e639122523a
| 39
|
py
|
Python
|
discord/const.py
|
BenitzCoding/Fusion.py
|
ed57645f4bcb7f961a7738c27aceecb920266404
|
[
"MIT"
] | 8
|
2021-10-15T01:05:49.000Z
|
2022-01-02T11:07:05.000Z
|
discord/const.py
|
BenitzCoding/Fusion.py
|
ed57645f4bcb7f961a7738c27aceecb920266404
|
[
"MIT"
] | 3
|
2021-10-10T16:48:05.000Z
|
2021-10-10T16:48:48.000Z
|
discord/const.py
|
BenitzCoding/Fusion.py
|
ed57645f4bcb7f961a7738c27aceecb920266404
|
[
"MIT"
] | 1
|
2021-12-09T03:15:09.000Z
|
2021-12-09T03:15:09.000Z
|
BASE_API = "https://discord.com/api/v8"
| 39
| 39
| 0.717949
| 7
| 39
| 3.857143
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027027
| 0.051282
| 39
| 1
| 39
| 39
| 0.702703
| 0
| 0
| 0
| 0
| 0
| 0.65
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a2e85c7ff6e36b86f97ca35fbab87f972af553d
| 115
|
py
|
Python
|
exercise/test1.py
|
D2MAC-dev/self_education
|
b4c8011db3995d8947c40416ef76a023162c09c3
|
[
"Apache-2.0"
] | null | null | null |
exercise/test1.py
|
D2MAC-dev/self_education
|
b4c8011db3995d8947c40416ef76a023162c09c3
|
[
"Apache-2.0"
] | null | null | null |
exercise/test1.py
|
D2MAC-dev/self_education
|
b4c8011db3995d8947c40416ef76a023162c09c3
|
[
"Apache-2.0"
] | null | null | null |
day = "день"
night = "ночь"
uran_sightings = '{0} {1} {0} {1} {1} {1} {0}'.format(day, night)
print(uran_sightings)
| 28.75
| 65
| 0.608696
| 19
| 115
| 3.578947
| 0.526316
| 0.382353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.070707
| 0.13913
| 115
| 4
| 66
| 28.75
| 0.616162
| 0
| 0
| 0
| 0
| 0.25
| 0.301724
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a3082e3117b50d8f1a06e806849f145b76c2f1b
| 1,986
|
py
|
Python
|
tests/test_time_hours.py
|
putridparrot/PyUnits
|
4f1095c6fc0bee6ba936921c391913dbefd9307c
|
[
"MIT"
] | null | null | null |
tests/test_time_hours.py
|
putridparrot/PyUnits
|
4f1095c6fc0bee6ba936921c391913dbefd9307c
|
[
"MIT"
] | null | null | null |
tests/test_time_hours.py
|
putridparrot/PyUnits
|
4f1095c6fc0bee6ba936921c391913dbefd9307c
|
[
"MIT"
] | null | null | null |
# <auto-generated>
# This code was generated by the UnitCodeGenerator tool
#
# Changes to this file will be lost if the code is regenerated
# </auto-generated>
import unittest
import units.time.hours
class TestHoursMethods(unittest.TestCase):
def test_convert_known_hours_to_seconds(self):
self.assertAlmostEqual(43200.0, units.time.hours.to_seconds(12.0), places=1)
self.assertAlmostEqual(11520.0, units.time.hours.to_seconds(3.2), places=1)
self.assertAlmostEqual(1080.0, units.time.hours.to_seconds(0.3), places=1)
def test_convert_known_hours_to_minutes(self):
self.assertAlmostEqual(18.0, units.time.hours.to_minutes(0.3), places=1)
self.assertAlmostEqual(42000.0, units.time.hours.to_minutes(700.0), places=1)
self.assertAlmostEqual(288.0, units.time.hours.to_minutes(4.8), places=1)
def test_convert_known_hours_to_days(self):
self.assertAlmostEqual(0.2, units.time.hours.to_days(4.8), places=1)
self.assertAlmostEqual(7.91667, units.time.hours.to_days(190.0), places=1)
self.assertAlmostEqual(0.354167, units.time.hours.to_days(8.5), places=1)
def test_convert_known_hours_to_weeks(self):
self.assertAlmostEqual(4.7619, units.time.hours.to_weeks(800.0), places=1)
self.assertAlmostEqual(0.535714, units.time.hours.to_weeks(90.0), places=1)
self.assertAlmostEqual(0.607143, units.time.hours.to_weeks(102.0), places=1)
def test_convert_known_hours_to_months(self):
self.assertAlmostEqual(0.139726, units.time.hours.to_months(102.0), places=1)
self.assertAlmostEqual(13.52875, units.time.hours.to_months(9876.0), places=1)
self.assertAlmostEqual(0.13808204, units.time.hours.to_months(100.8), places=1)
def test_convert_known_hours_to_years(self):
self.assertAlmostEqual(1.027397, units.time.hours.to_years(9000.0), places=1)
self.assertAlmostEqual(0.1144977, units.time.hours.to_years(1003.0), places=1)
self.assertAlmostEqual(0.0923516, units.time.hours.to_years(809.0), places=1)
if __name__ == '__main__':
unittest.main()
| 45.136364
| 81
| 0.77996
| 321
| 1,986
| 4.65109
| 0.242991
| 0.112525
| 0.178165
| 0.1929
| 0.573342
| 0.346283
| 0.111855
| 0.111855
| 0.045546
| 0
| 0
| 0.103448
| 0.08006
| 1,986
| 43
| 82
| 46.186047
| 0.713738
| 0.075025
| 0
| 0
| 1
| 0
| 0.004369
| 0
| 0
| 0
| 0
| 0
| 0.62069
| 1
| 0.206897
| false
| 0
| 0.068966
| 0
| 0.310345
| 0
| 0
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| 0
| null | 0
| 0
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a64f00ef803f46300b15c1b73472a1fe3eabc0b
| 72
|
py
|
Python
|
imgreco/__init__.py
|
Pakirisu/ArknightsAutoHelper
|
8b136c82794cfe9f364788d9c92f1e4c5b38c6cb
|
[
"MIT"
] | 1
|
2020-01-15T01:05:28.000Z
|
2020-01-15T01:05:28.000Z
|
imgreco/__init__.py
|
ZhouZiHao-Moon/ArknightsAutoHelper
|
3135b54d69f2255f99c13d42dc936065701c3129
|
[
"MIT"
] | null | null | null |
imgreco/__init__.py
|
ZhouZiHao-Moon/ArknightsAutoHelper
|
3135b54d69f2255f99c13d42dc936065701c3129
|
[
"MIT"
] | null | null | null |
from . import common, before_operation, end_operation, item, main, task
| 36
| 71
| 0.791667
| 10
| 72
| 5.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 72
| 1
| 72
| 72
| 0.873016
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
5a71e514f2914d17a8066d51ab4fa1a534ade856
| 17
|
py
|
Python
|
network_crawler/__main__.py
|
luigi-riefolo/network_crawler
|
376fb5860c573416ac71a0dfe5437011858398b6
|
[
"MIT"
] | null | null | null |
network_crawler/__main__.py
|
luigi-riefolo/network_crawler
|
376fb5860c573416ac71a0dfe5437011858398b6
|
[
"MIT"
] | null | null | null |
network_crawler/__main__.py
|
luigi-riefolo/network_crawler
|
376fb5860c573416ac71a0dfe5437011858398b6
|
[
"MIT"
] | null | null | null |
"""Main stub."""
| 8.5
| 16
| 0.470588
| 2
| 17
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 17
| 1
| 17
| 17
| 0.533333
| 0.588235
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a781142b8937e0d4c1fceb3ccfcc1ea2a2155a5
| 120
|
py
|
Python
|
src/optimizations/models.py
|
etianen/django-optimizations
|
c9614c3eeb1cb3482eb2db84d3951356d7fb44a3
|
[
"BSD-3-Clause"
] | 12
|
2015-05-06T21:34:11.000Z
|
2021-07-31T04:49:25.000Z
|
src/optimizations/models.py
|
etianen/django-optimizations
|
c9614c3eeb1cb3482eb2db84d3951356d7fb44a3
|
[
"BSD-3-Clause"
] | 3
|
2015-02-11T16:23:13.000Z
|
2018-04-17T09:07:36.000Z
|
src/optimizations/models.py
|
etianen/django-optimizations
|
c9614c3eeb1cb3482eb2db84d3951356d7fb44a3
|
[
"BSD-3-Clause"
] | 4
|
2015-02-11T10:21:31.000Z
|
2019-07-24T20:29:28.000Z
|
"""Models used by django-optimizations."""
# Nothing to see here. This module needs to exist for the testing framework.
| 40
| 76
| 0.758333
| 18
| 120
| 5.055556
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 120
| 3
| 76
| 40
| 0.892157
| 0.933333
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5a7f0664983deedb1089c92f3f76f1064998c012
| 92
|
py
|
Python
|
src/notifi/apps.py
|
earth-emoji/love
|
3617bd47c396803c411e136b3e1de87c18e03890
|
[
"BSD-2-Clause"
] | null | null | null |
src/notifi/apps.py
|
earth-emoji/love
|
3617bd47c396803c411e136b3e1de87c18e03890
|
[
"BSD-2-Clause"
] | 7
|
2021-03-19T10:46:09.000Z
|
2022-03-12T00:28:55.000Z
|
src/notifi/apps.py
|
earth-emoji/love
|
3617bd47c396803c411e136b3e1de87c18e03890
|
[
"BSD-2-Clause"
] | null | null | null |
from django.apps import AppConfig
class NotifiConfig(AppConfig):
name = 'notifi'
| 15.333333
| 34
| 0.706522
| 10
| 92
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.217391
| 92
| 5
| 35
| 18.4
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ce5702741d1e40427dbd5cad5a4dff6a13549e5f
| 146
|
py
|
Python
|
alicebot/plugins/guild_basic/config.py
|
Erisu0014/yuniBot
|
b6d6a35abb63a2de57375dee6a1cd6258b3a7a95
|
[
"Apache-2.0"
] | null | null | null |
alicebot/plugins/guild_basic/config.py
|
Erisu0014/yuniBot
|
b6d6a35abb63a2de57375dee6a1cd6258b3a7a95
|
[
"Apache-2.0"
] | null | null | null |
alicebot/plugins/guild_basic/config.py
|
Erisu0014/yuniBot
|
b6d6a35abb63a2de57375dee6a1cd6258b3a7a95
|
[
"Apache-2.0"
] | 1
|
2022-02-11T12:46:43.000Z
|
2022-02-11T12:46:43.000Z
|
from pydantic import BaseSettings
class Config(BaseSettings):
bot_id: str
bot_guild_id: str
class Config:
extra = "ignore"
| 14.6
| 33
| 0.678082
| 18
| 146
| 5.333333
| 0.666667
| 0.229167
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.260274
| 146
| 9
| 34
| 16.222222
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0.041096
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.833333
| 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
| 1
| 0
|
0
| 4
|
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