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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
af2b27926bb220760743435ac83898470bd54da5
| 114
|
py
|
Python
|
scraper/__init__.py
|
jkirkwin/CourseChart
|
5ec2aec6b3243ec5b8a50f6c15508b6536d5afcf
|
[
"MIT"
] | 1
|
2020-05-25T21:51:43.000Z
|
2020-05-25T21:51:43.000Z
|
scraper/__init__.py
|
jkirkwin/CourseChart
|
5ec2aec6b3243ec5b8a50f6c15508b6536d5afcf
|
[
"MIT"
] | 2
|
2020-05-25T17:35:38.000Z
|
2021-09-30T01:35:49.000Z
|
scraper/__init__.py
|
jkirkwin/CourseChart
|
5ec2aec6b3243ec5b8a50f6c15508b6536d5afcf
|
[
"MIT"
] | 1
|
2020-05-28T01:05:24.000Z
|
2020-05-28T01:05:24.000Z
|
'''This file is intentionally blank. It is required for PyLint to recognize the
containing folder as a module.'''
| 38
| 79
| 0.77193
| 18
| 114
| 4.888889
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 114
| 2
| 80
| 57
| 0.916667
| 0.938596
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
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| 0
| 0
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| 0
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| 0
| 0
| 0
| 1
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| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
af36226193ed23f0a0484098b028de2c255b0731
| 198
|
py
|
Python
|
tests/inspectdb/settings.py
|
markgarg/django-salesforce
|
77cb2f0f404afb589ac5834a5cc2a375112e946d
|
[
"MIT"
] | 1
|
2017-07-05T10:29:36.000Z
|
2017-07-05T10:29:36.000Z
|
tests/inspectdb/settings.py
|
Catchoom/django-salesforce
|
1c2f24a5d27a2d46549835bada7d0525bf7511a9
|
[
"MIT"
] | null | null | null |
tests/inspectdb/settings.py
|
Catchoom/django-salesforce
|
1c2f24a5d27a2d46549835bada7d0525bf7511a9
|
[
"MIT"
] | 1
|
2022-03-18T09:20:37.000Z
|
2022-03-18T09:20:37.000Z
|
from salesforce.testrunner.settings import *
# replace the test app
INSTALLED_APPS = tuple(x for x in INSTALLED_APPS if x != 'salesforce.testrunner.example')
INSTALLED_APPS += ('tests.inspectdb',)
| 33
| 89
| 0.772727
| 27
| 198
| 5.555556
| 0.703704
| 0.26
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 198
| 5
| 90
| 39.6
| 0.862069
| 0.10101
| 0
| 0
| 0
| 0
| 0.25
| 0.164773
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
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| 0
| null | 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
af404fd2d0b38300240c235e2d7f0b122a73b1f1
| 4,231
|
py
|
Python
|
app/tests/api_tests/test_application_technical_controls.py
|
AirWalk-Digital/airview-api
|
1c4ce3569a5e3834d53f937a35ec5d8b0e991cdb
|
[
"Apache-2.0"
] | 2
|
2021-11-29T13:28:42.000Z
|
2021-12-21T14:37:58.000Z
|
app/tests/api_tests/test_application_technical_controls.py
|
AirWalk-Digital/airview-api
|
1c4ce3569a5e3834d53f937a35ec5d8b0e991cdb
|
[
"Apache-2.0"
] | 2
|
2021-11-04T10:24:10.000Z
|
2021-11-12T15:16:20.000Z
|
app/tests/api_tests/test_application_technical_controls.py
|
AirWalk-Digital/airview-api
|
1c4ce3569a5e3834d53f937a35ec5d8b0e991cdb
|
[
"Apache-2.0"
] | null | null | null |
from datetime import datetime
from pprint import pprint
from tests.factories import *
from tests.common import client
import tests.common
from airview_api.models import (
Application,
ApplicationTechnicalControl,
MonitoredResource,
TechnicalControlSeverity,
TechnicalControlAction,
SystemStage,
)
def setup():
reset_factories()
def test_application_technical_control_get_single_ok(client):
"""
Given: A collection of application technical controls exist in the database
When: When the api is called with correct uri
Then: The corrisponding application technical control is returned with status 200
"""
# Arrange
SystemFactory(id=2, stage=SystemStage.BUILD)
ApplicationFactory(id=1)
ApplicationFactory(id=2)
TechnicalControlFactory(
id=101,
reference="1",
name="one",
control_action=TechnicalControlAction.LOG,
system_id=2,
severity=TechnicalControlSeverity.HIGH,
)
ApplicationTechnicalControlFactory(
id=201, application_id=1, technical_control_id=101
)
ApplicationTechnicalControlFactory(
id=202, application_id=2, technical_control_id=101
)
# Act
resp = client.get(
"/application-technical-controls/?applicationId=1&technicalControlId=101"
)
# Assert
data = resp.get_json()
pprint(data)
assert resp.status_code == 200
assert data["id"] == 201
assert data["applicationId"] == 1
assert data["technicalControlId"] == 101
def test_application_technical_control_not_found(client):
"""
Given: A collection of application technical controls exist in the database
When: When the api is called with non-existing identifiers
Then: 404 status
"""
# Arrange
SystemFactory(id=2, stage=SystemStage.BUILD)
ApplicationFactory(id=1)
ApplicationFactory(id=2)
TechnicalControlFactory(
id=101,
reference="1",
name="one",
control_action=TechnicalControlAction.LOG,
system_id=2,
severity=TechnicalControlSeverity.HIGH,
)
ApplicationTechnicalControlFactory(
id=201, application_id=1, technical_control_id=101
)
ApplicationTechnicalControlFactory(
id=202, application_id=2, technical_control_id=101
)
# Act
resp = client.get(
"/application-technical-controls/?applicationId=999&technicalControlId=101"
)
# Assert
assert resp.status_code == 404
def test_application_technical_control_post_ok(client):
"""
Given: Unlinked apps and controls
When: When the api is called to link them
Then: 200 status, new object returned
"""
# Arrange
SystemFactory(id=2, stage=SystemStage.BUILD)
ApplicationFactory(id=1)
TechnicalControlFactory(
id=101,
reference="1",
name="one",
control_action=TechnicalControlAction.LOG,
system_id=2,
severity=TechnicalControlSeverity.HIGH,
)
input_data = {"applicationId": 1, "technicalControlId": 101}
# Act
resp = client.post("/application-technical-controls/", json=input_data)
# Assert
assert resp.status_code == 200
data = resp.get_json()
assert data["applicationId"] == 1
assert data["technicalControlId"] == 101
items = db.session.query(ApplicationTechnicalControl).all()
assert len(items) == 1
def test_application_technical_control_post_conflict_when_exist(client):
"""
Given: existing linked apps and controls
When: When the api is called to link them
Then: 200 status, new object returned
"""
# Arrange
SystemFactory(id=2, stage=SystemStage.BUILD)
ApplicationFactory(id=1)
TechnicalControlFactory(
id=101,
reference="1",
name="one",
control_action=TechnicalControlAction.LOG,
system_id=2,
severity=TechnicalControlSeverity.HIGH,
)
ApplicationTechnicalControlFactory(
id=201, application_id=1, technical_control_id=101
)
input_data = {"applicationId": 1, "technicalControlId": 101}
# Act
resp = client.post("/application-technical-controls/", json=input_data)
# Assert
assert resp.status_code == 409
| 27.474026
| 85
| 0.688726
| 448
| 4,231
| 6.375
| 0.225446
| 0.012605
| 0.058824
| 0.036765
| 0.772409
| 0.730392
| 0.703782
| 0.703782
| 0.665266
| 0.665266
| 0
| 0.036192
| 0.222879
| 4,231
| 153
| 86
| 27.653595
| 0.832421
| 0.157646
| 0
| 0.62
| 0
| 0
| 0.101156
| 0.060116
| 0
| 0
| 0
| 0
| 0.1
| 1
| 0.05
| false
| 0
| 0.06
| 0
| 0.11
| 0.02
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| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
af580a3a73ab31ee58de356ed4276e3a4f940ca8
| 223
|
py
|
Python
|
modules.py
|
ecxzqute/python3-basics
|
34714b896fbda93e0625a1b6f09f68975bfbf28a
|
[
"MIT"
] | null | null | null |
modules.py
|
ecxzqute/python3-basics
|
34714b896fbda93e0625a1b6f09f68975bfbf28a
|
[
"MIT"
] | null | null | null |
modules.py
|
ecxzqute/python3-basics
|
34714b896fbda93e0625a1b6f09f68975bfbf28a
|
[
"MIT"
] | null | null | null |
# A module is basically a file containing a set of functions to include in your application. There are core python modules, modules you can install using the pip package manager (including Django) as well as custom modules
| 111.5
| 222
| 0.807175
| 37
| 223
| 4.864865
| 0.864865
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170404
| 223
| 1
| 223
| 223
| 0.972973
| 0.986547
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
af6e4576a158df54855a97b0c1e3df603585524e
| 123
|
py
|
Python
|
backend/r2dec/mdec-r2dec/mdecr2dec/__main__.py
|
clayne/mdec
|
5c309f9f00dc7db4d860799dfa76cd390e1139e0
|
[
"MIT"
] | 317
|
2022-03-12T00:06:50.000Z
|
2022-03-31T22:57:44.000Z
|
backend/r2dec/mdec-r2dec/mdecr2dec/__main__.py
|
clayne/mdec
|
5c309f9f00dc7db4d860799dfa76cd390e1139e0
|
[
"MIT"
] | 17
|
2022-03-12T03:12:41.000Z
|
2022-03-25T19:34:02.000Z
|
backend/r2dec/mdec-r2dec/mdecr2dec/__main__.py
|
clayne/mdec
|
5c309f9f00dc7db4d860799dfa76cd390e1139e0
|
[
"MIT"
] | 16
|
2022-03-12T07:12:09.000Z
|
2022-03-18T22:23:24.000Z
|
from mdecr2dec import R2decService
from mdecbase import mdec_main
if __name__ == '__main__':
mdec_main(R2decService)
| 17.571429
| 34
| 0.788618
| 15
| 123
| 5.8
| 0.6
| 0.183908
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.028846
| 0.154472
| 123
| 6
| 35
| 20.5
| 0.807692
| 0
| 0
| 0
| 0
| 0
| 0.065041
| 0
| 0
| 0
| 0
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| 0
| true
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| 0.5
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
af74ca85a0cf60848157317885dfa205a0a2070a
| 70
|
py
|
Python
|
lovpy/visualization_strategies/set_full_visualization_scheme.py
|
dkarageo/lovpy
|
85f43c07aeed4b318238c35da606de2dc65ca24f
|
[
"Apache-2.0"
] | null | null | null |
lovpy/visualization_strategies/set_full_visualization_scheme.py
|
dkarageo/lovpy
|
85f43c07aeed4b318238c35da606de2dc65ca24f
|
[
"Apache-2.0"
] | null | null | null |
lovpy/visualization_strategies/set_full_visualization_scheme.py
|
dkarageo/lovpy
|
85f43c07aeed4b318238c35da606de2dc65ca24f
|
[
"Apache-2.0"
] | null | null | null |
import lovpy.config as config
config.enable_failure_visualization()
| 14
| 37
| 0.842857
| 9
| 70
| 6.333333
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 70
| 4
| 38
| 17.5
| 0.904762
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
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| 0
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
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| 1
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
af7e3f0a6c2e027e0b0f3d7a10534324db9a38a0
| 177,287
|
py
|
Python
|
pysnmp_mibs/IP-MIB.py
|
jackjack821/pysnmp-mibs
|
9835ea0bb2420715caf4ee9aaa07d59bb263acd6
|
[
"BSD-2-Clause"
] | 6
|
2017-04-21T13:48:08.000Z
|
2022-01-06T19:42:52.000Z
|
pysnmp_mibs/IP-MIB.py
|
jackjack821/pysnmp-mibs
|
9835ea0bb2420715caf4ee9aaa07d59bb263acd6
|
[
"BSD-2-Clause"
] | 1
|
2020-05-05T16:42:25.000Z
|
2020-05-05T16:42:25.000Z
|
pysnmp_mibs/IP-MIB.py
|
jackjack821/pysnmp-mibs
|
9835ea0bb2420715caf4ee9aaa07d59bb263acd6
|
[
"BSD-2-Clause"
] | 6
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2020-02-08T20:28:49.000Z
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2021-09-14T13:36:46.000Z
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#
# PySNMP MIB module IP-MIB (http://pysnmp.sf.net)
# ASN.1 source http://mibs.snmplabs.com:80/asn1/IP-MIB
# Produced by pysmi-0.0.7 at Sun Feb 14 00:17:37 2016
# On host bldfarm platform Linux version 4.1.13-100.fc21.x86_64 by user goose
# Using Python version 3.5.0 (default, Jan 5 2016, 17:11:52)
#
( OctetString, Integer, ObjectIdentifier, ) = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier")
( NamedValues, ) = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
( ValueSizeConstraint, SingleValueConstraint, ConstraintsIntersection, ValueRangeConstraint, ConstraintsUnion, ) = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueSizeConstraint", "SingleValueConstraint", "ConstraintsIntersection", "ValueRangeConstraint", "ConstraintsUnion")
( InterfaceIndex, ) = mibBuilder.importSymbols("IF-MIB", "InterfaceIndex")
( InetAddress, InetVersion, InetAddressPrefixLength, InetZoneIndex, InetAddressType, ) = mibBuilder.importSymbols("INET-ADDRESS-MIB", "InetAddress", "InetVersion", "InetAddressPrefixLength", "InetZoneIndex", "InetAddressType")
( NotificationGroup, ObjectGroup, ModuleCompliance, ) = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ObjectGroup", "ModuleCompliance")
( MibScalar, MibTable, MibTableRow, MibTableColumn, IpAddress, ModuleIdentity, TimeTicks, Counter64, NotificationType, Integer32, Unsigned32, ObjectIdentity, Gauge32, zeroDotZero, iso, MibIdentifier, Bits, mib_2, Counter32, ) = mibBuilder.importSymbols("SNMPv2-SMI", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "IpAddress", "ModuleIdentity", "TimeTicks", "Counter64", "NotificationType", "Integer32", "Unsigned32", "ObjectIdentity", "Gauge32", "zeroDotZero", "iso", "MibIdentifier", "Bits", "mib-2", "Counter32")
( DisplayString, TextualConvention, StorageType, RowStatus, PhysAddress, TimeStamp, TestAndIncr, TruthValue, RowPointer, ) = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention", "StorageType", "RowStatus", "PhysAddress", "TimeStamp", "TestAndIncr", "TruthValue", "RowPointer")
ipMIB = ModuleIdentity((1, 3, 6, 1, 2, 1, 48)).setRevisions(("2006-02-02 00:00", "1994-11-01 00:00", "1991-03-31 00:00",))
if mibBuilder.loadTexts: ipMIB.setLastUpdated('200602020000Z')
if mibBuilder.loadTexts: ipMIB.setOrganization('IETF IPv6 MIB Revision Team')
if mibBuilder.loadTexts: ipMIB.setContactInfo('Editor:\n\n\n Shawn A. Routhier\n Interworking Labs\n 108 Whispering Pines Dr. Suite 235\n Scotts Valley, CA 95066\n USA\n EMail: <sar@iwl.com>')
if mibBuilder.loadTexts: ipMIB.setDescription('The MIB module for managing IP and ICMP implementations, but\n excluding their management of IP routes.\n\n Copyright (C) The Internet Society (2006). This version of\n this MIB module is part of RFC 4293; see the RFC itself for\n full legal notices.')
class IpAddressOriginTC(Integer32, TextualConvention):
subtypeSpec = Integer32.subtypeSpec+ConstraintsUnion(SingleValueConstraint(1, 2, 4, 5, 6,))
namedValues = NamedValues(("other", 1), ("manual", 2), ("dhcp", 4), ("linklayer", 5), ("random", 6),)
class IpAddressStatusTC(Integer32, TextualConvention):
subtypeSpec = Integer32.subtypeSpec+ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5, 6, 7, 8,))
namedValues = NamedValues(("preferred", 1), ("deprecated", 2), ("invalid", 3), ("inaccessible", 4), ("unknown", 5), ("tentative", 6), ("duplicate", 7), ("optimistic", 8),)
class IpAddressPrefixOriginTC(Integer32, TextualConvention):
subtypeSpec = Integer32.subtypeSpec+ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5,))
namedValues = NamedValues(("other", 1), ("manual", 2), ("wellknown", 3), ("dhcp", 4), ("routeradv", 5),)
class Ipv6AddressIfIdentifierTC(OctetString, TextualConvention):
displayHint = '2x:'
subtypeSpec = OctetString.subtypeSpec+ValueSizeConstraint(0,8)
ip = MibIdentifier((1, 3, 6, 1, 2, 1, 4))
ipForwarding = MibScalar((1, 3, 6, 1, 2, 1, 4, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2,))).clone(namedValues=NamedValues(("forwarding", 1), ("notForwarding", 2),))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipForwarding.setDescription('The indication of whether this entity is acting as an IPv4\n router in respect to the forwarding of datagrams received\n by, but not addressed to, this entity. IPv4 routers forward\n datagrams. IPv4 hosts do not (except those source-routed\n via the host).\n\n When this object is written, the entity should save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.\n Note: a stronger requirement is not used because this object\n was previously defined.')
ipDefaultTTL = MibScalar((1, 3, 6, 1, 2, 1, 4, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1,255))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipDefaultTTL.setDescription('The default value inserted into the Time-To-Live field of\n the IPv4 header of datagrams originated at this entity,\n whenever a TTL value is not supplied by the transport layer\n\n\n protocol.\n\n When this object is written, the entity should save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.\n Note: a stronger requirement is not used because this object\n was previously defined.')
ipReasmTimeout = MibScalar((1, 3, 6, 1, 2, 1, 4, 13), Integer32()).setUnits('seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipReasmTimeout.setDescription('The maximum number of seconds that received fragments are\n held while they are awaiting reassembly at this entity.')
ipv6IpForwarding = MibScalar((1, 3, 6, 1, 2, 1, 4, 25), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2,))).clone(namedValues=NamedValues(("forwarding", 1), ("notForwarding", 2),))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv6IpForwarding.setDescription('The indication of whether this entity is acting as an IPv6\n router on any interface in respect to the forwarding of\n datagrams received by, but not addressed to, this entity.\n IPv6 routers forward datagrams. IPv6 hosts do not (except\n those source-routed via the host).\n\n When this object is written, the entity SHOULD save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.')
ipv6IpDefaultHopLimit = MibScalar((1, 3, 6, 1, 2, 1, 4, 26), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0,255))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv6IpDefaultHopLimit.setDescription('The default value inserted into the Hop Limit field of the\n IPv6 header of datagrams originated at this entity whenever\n a Hop Limit value is not supplied by the transport layer\n protocol.\n\n When this object is written, the entity SHOULD save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.')
ipv4InterfaceTableLastChange = MibScalar((1, 3, 6, 1, 2, 1, 4, 27), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv4InterfaceTableLastChange.setDescription('The value of sysUpTime on the most recent occasion at which\n a row in the ipv4InterfaceTable was added or deleted, or\n when an ipv4InterfaceReasmMaxSize or an\n ipv4InterfaceEnableStatus object was modified.\n\n If new objects are added to the ipv4InterfaceTable that\n require the ipv4InterfaceTableLastChange to be updated when\n they are modified, they must specify that requirement in\n their description clause.')
ipv4InterfaceTable = MibTable((1, 3, 6, 1, 2, 1, 4, 28), )
if mibBuilder.loadTexts: ipv4InterfaceTable.setDescription('The table containing per-interface IPv4-specific\n information.')
ipv4InterfaceEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 28, 1), ).setIndexNames((0, "IP-MIB", "ipv4InterfaceIfIndex"))
if mibBuilder.loadTexts: ipv4InterfaceEntry.setDescription('An entry containing IPv4-specific information for a specific\n interface.')
ipv4InterfaceIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 28, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipv4InterfaceIfIndex.setDescription("The index value that uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipv4InterfaceReasmMaxSize = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 28, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0,65535))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv4InterfaceReasmMaxSize.setDescription('The size of the largest IPv4 datagram that this entity can\n re-assemble from incoming IPv4 fragmented datagrams received\n on this interface.')
ipv4InterfaceEnableStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 28, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2,))).clone(namedValues=NamedValues(("up", 1), ("down", 2),))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv4InterfaceEnableStatus.setDescription('The indication of whether IPv4 is enabled (up) or disabled\n (down) on this interface. This object does not affect the\n state of the interface itself, only its connection to an\n IPv4 stack. The IF-MIB should be used to control the state\n of the interface.')
ipv4InterfaceRetransmitTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 28, 1, 4), Unsigned32().clone(1000)).setUnits('milliseconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv4InterfaceRetransmitTime.setDescription('The time between retransmissions of ARP requests to a\n neighbor when resolving the address or when probing the\n reachability of a neighbor.')
ipv6InterfaceTableLastChange = MibScalar((1, 3, 6, 1, 2, 1, 4, 29), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6InterfaceTableLastChange.setDescription('The value of sysUpTime on the most recent occasion at which\n a row in the ipv6InterfaceTable was added or deleted or when\n an ipv6InterfaceReasmMaxSize, ipv6InterfaceIdentifier,\n ipv6InterfaceEnableStatus, ipv6InterfaceReachableTime,\n ipv6InterfaceRetransmitTime, or ipv6InterfaceForwarding\n object was modified.\n\n If new objects are added to the ipv6InterfaceTable that\n require the ipv6InterfaceTableLastChange to be updated when\n they are modified, they must specify that requirement in\n their description clause.')
ipv6InterfaceTable = MibTable((1, 3, 6, 1, 2, 1, 4, 30), )
if mibBuilder.loadTexts: ipv6InterfaceTable.setDescription('The table containing per-interface IPv6-specific\n information.')
ipv6InterfaceEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 30, 1), ).setIndexNames((0, "IP-MIB", "ipv6InterfaceIfIndex"))
if mibBuilder.loadTexts: ipv6InterfaceEntry.setDescription('An entry containing IPv6-specific information for a given\n interface.')
ipv6InterfaceIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipv6InterfaceIfIndex.setDescription("The index value that uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipv6InterfaceReasmMaxSize = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 2), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(1500,65535))).setUnits('octets').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6InterfaceReasmMaxSize.setDescription('The size of the largest IPv6 datagram that this entity can\n re-assemble from incoming IPv6 fragmented datagrams received\n on this interface.')
ipv6InterfaceIdentifier = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 3), Ipv6AddressIfIdentifierTC()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6InterfaceIdentifier.setDescription('The Interface Identifier for this interface. The Interface\n Identifier is combined with an address prefix to form an\n interface address.\n\n By default, the Interface Identifier is auto-configured\n according to the rules of the link type to which this\n interface is attached.\n\n\n A zero length identifier may be used where appropriate. One\n possible example is a loopback interface.')
ipv6InterfaceEnableStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2,))).clone(namedValues=NamedValues(("up", 1), ("down", 2),))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv6InterfaceEnableStatus.setDescription('The indication of whether IPv6 is enabled (up) or disabled\n (down) on this interface. This object does not affect the\n state of the interface itself, only its connection to an\n IPv6 stack. The IF-MIB should be used to control the state\n of the interface.\n\n When this object is written, the entity SHOULD save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.')
ipv6InterfaceReachableTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 6), Unsigned32()).setUnits('milliseconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6InterfaceReachableTime.setDescription('The time a neighbor is considered reachable after receiving\n a reachability confirmation.')
ipv6InterfaceRetransmitTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 7), Unsigned32()).setUnits('milliseconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6InterfaceRetransmitTime.setDescription('The time between retransmissions of Neighbor Solicitation\n messages to a neighbor when resolving the address or when\n probing the reachability of a neighbor.')
ipv6InterfaceForwarding = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 30, 1, 8), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2,))).clone(namedValues=NamedValues(("forwarding", 1), ("notForwarding", 2),))).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv6InterfaceForwarding.setDescription('The indication of whether this entity is acting as an IPv6\n router on this interface with respect to the forwarding of\n datagrams received by, but not addressed to, this entity.\n IPv6 routers forward datagrams. IPv6 hosts do not (except\n those source-routed via the host).\n\n This object is constrained by ipv6IpForwarding and is\n ignored if ipv6IpForwarding is set to notForwarding. Those\n systems that do not provide per-interface control of the\n forwarding function should set this object to forwarding for\n all interfaces and allow the ipv6IpForwarding object to\n control the forwarding capability.\n\n When this object is written, the entity SHOULD save the\n change to non-volatile storage and restore the object from\n non-volatile storage upon re-initialization of the system.')
ipTrafficStats = MibIdentifier((1, 3, 6, 1, 2, 1, 4, 31))
ipSystemStatsTable = MibTable((1, 3, 6, 1, 2, 1, 4, 31, 1), )
if mibBuilder.loadTexts: ipSystemStatsTable.setDescription('The table containing system wide, IP version specific\n traffic statistics. This table and the ipIfStatsTable\n contain similar objects whose difference is in their\n granularity. Where this table contains system wide traffic\n statistics, the ipIfStatsTable contains the same statistics\n but counted on a per-interface basis.')
ipSystemStatsEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 31, 1, 1), ).setIndexNames((0, "IP-MIB", "ipSystemStatsIPVersion"))
if mibBuilder.loadTexts: ipSystemStatsEntry.setDescription('A statistics entry containing system-wide objects for a\n particular IP version.')
ipSystemStatsIPVersion = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 1), InetVersion())
if mibBuilder.loadTexts: ipSystemStatsIPVersion.setDescription('The IP version of this row.')
ipSystemStatsInReceives = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInReceives.setDescription('The total number of input IP datagrams received, including\n those received in error.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInReceives = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 4), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInReceives.setDescription('The total number of input IP datagrams received, including\n those received in error. This object counts the same\n datagrams as ipSystemStatsInReceives, but allows for larger\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInOctets.setDescription('The total number of octets received in input IP datagrams,\n including those received in error. Octets from datagrams\n counted in ipSystemStatsInReceives MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 6), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInOctets.setDescription('The total number of octets received in input IP datagrams,\n including those received in error. This object counts the\n same octets as ipSystemStatsInOctets, but allows for larger\n\n\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInHdrErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInHdrErrors.setDescription('The number of input IP datagrams discarded due to errors in\n their IP headers, including version number mismatch, other\n format errors, hop count exceeded, errors discovered in\n processing their IP options, etc.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInNoRoutes = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInNoRoutes.setDescription('The number of input IP datagrams discarded because no route\n could be found to transmit them to their destination.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInAddrErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInAddrErrors.setDescription("The number of input IP datagrams discarded because the IP\n address in their IP header's destination field was not a\n valid address to be received at this entity. This count\n includes invalid addresses (e.g., ::0). For entities\n that are not IP routers and therefore do not forward\n\n\n datagrams, this counter includes datagrams discarded\n because the destination address was not a local address.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.")
ipSystemStatsInUnknownProtos = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInUnknownProtos.setDescription('The number of locally-addressed IP datagrams received\n successfully but discarded because of an unknown or\n unsupported protocol.\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInTruncatedPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInTruncatedPkts.setDescription("The number of input IP datagrams discarded because the\n datagram frame didn't carry enough data.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.")
ipSystemStatsInForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInForwDatagrams.setDescription('The number of input datagrams for which this entity was not\n their final IP destination and for which this entity\n attempted to find a route to forward them to that final\n destination. In entities that do not act as IP routers,\n this counter will include only those datagrams that were\n Source-Routed via this entity, and the Source-Route\n processing was successful.\n\n When tracking interface statistics, the counter of the\n incoming interface is incremented for each datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 13), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInForwDatagrams.setDescription('The number of input datagrams for which this entity was not\n their final IP destination and for which this entity\n attempted to find a route to forward them to that final\n destination. This object counts the same packets as\n ipSystemStatsInForwDatagrams, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsReasmReqds = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsReasmReqds.setDescription('The number of IP fragments received that needed to be\n reassembled at this interface.\n\n When tracking interface statistics, the counter of the\n interface to which these fragments were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the fragments.\n\n Discontinuities in the value of this counter can occur at\n\n\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsReasmOKs = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 15), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsReasmOKs.setDescription('The number of IP datagrams successfully reassembled.\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsReasmFails = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 16), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsReasmFails.setDescription('The number of failures detected by the IP re-assembly\n algorithm (for whatever reason: timed out, errors, etc.).\n Note that this is not necessarily a count of discarded IP\n fragments since some algorithms (notably the algorithm in\n RFC 815) can lose track of the number of fragments by\n combining them as they are received.\n\n When tracking interface statistics, the counter of the\n interface to which these fragments were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the fragments.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInDiscards = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 17), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInDiscards.setDescription('The number of input IP datagrams for which no problems were\n encountered to prevent their continued processing, but\n were discarded (e.g., for lack of buffer space). Note that\n this counter does not include any datagrams discarded while\n awaiting re-assembly.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInDelivers = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 18), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInDelivers.setDescription('The total number of datagrams successfully delivered to IP\n user-protocols (including ICMP).\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInDelivers = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 19), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInDelivers.setDescription('The total number of datagrams successfully delivered to IP\n user-protocols (including ICMP). This object counts the\n same packets as ipSystemStatsInDelivers, but allows for\n larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutRequests = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 20), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutRequests.setDescription('The total number of IP datagrams that local IP user-\n protocols (including ICMP) supplied to IP in requests for\n transmission. Note that this counter does not include any\n datagrams counted in ipSystemStatsOutForwDatagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutRequests = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 21), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutRequests.setDescription('The total number of IP datagrams that local IP user-\n protocols (including ICMP) supplied to IP in requests for\n transmission. This object counts the same packets as\n ipSystemStatsOutRequests, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutNoRoutes = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 22), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutNoRoutes.setDescription('The number of locally generated IP datagrams discarded\n because no route could be found to transmit them to their\n destination.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 23), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutForwDatagrams.setDescription('The number of datagrams for which this entity was not their\n final IP destination and for which it was successful in\n finding a path to their final destination. In entities\n that do not act as IP routers, this counter will include\n only those datagrams that were Source-Routed via this\n entity, and the Source-Route processing was successful.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n forwarded datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 24), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutForwDatagrams.setDescription('The number of datagrams for which this entity was not their\n final IP destination and for which it was successful in\n finding a path to their final destination. This object\n counts the same packets as ipSystemStatsOutForwDatagrams,\n but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutDiscards = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 25), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutDiscards.setDescription('The number of output IP datagrams for which no problem was\n encountered to prevent their transmission to their\n destination, but were discarded (e.g., for lack of\n buffer space). Note that this counter would include\n\n\n datagrams counted in ipSystemStatsOutForwDatagrams if any\n such datagrams met this (discretionary) discard criterion.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutFragReqds = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 26), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutFragReqds.setDescription('The number of IP datagrams that would require fragmentation\n in order to be transmitted.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutFragOKs = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 27), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutFragOKs.setDescription('The number of IP datagrams that have been successfully\n fragmented.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutFragFails = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 28), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutFragFails.setDescription('The number of IP datagrams that have been discarded because\n they needed to be fragmented but could not be. This\n includes IPv4 packets that have the DF bit set and IPv6\n packets that are being forwarded and exceed the outgoing\n link MTU.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for an unsuccessfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutFragCreates = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 29), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutFragCreates.setDescription('The number of output datagram fragments that have been\n generated as a result of IP fragmentation.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutTransmits = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 30), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutTransmits.setDescription('The total number of IP datagrams that this entity supplied\n to the lower layers for transmission. This includes\n datagrams generated locally and those forwarded by this\n entity.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n\n\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutTransmits = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 31), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutTransmits.setDescription('The total number of IP datagrams that this entity supplied\n to the lower layers for transmission. This object counts\n the same datagrams as ipSystemStatsOutTransmits, but allows\n for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 32), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutOctets.setDescription('The total number of octets in IP datagrams delivered to the\n lower layers for transmission. Octets from datagrams\n counted in ipSystemStatsOutTransmits MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 33), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutOctets.setDescription('The total number of octets in IP datagrams delivered to the\n lower layers for transmission. This objects counts the same\n octets as ipSystemStatsOutOctets, but allows for larger\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n\n\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 34), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInMcastPkts.setDescription('The number of IP multicast datagrams received.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 35), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInMcastPkts.setDescription('The number of IP multicast datagrams received. This object\n counts the same datagrams as ipSystemStatsInMcastPkts but\n allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 36), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInMcastOctets.setDescription('The total number of octets received in IP multicast\n datagrams. Octets from datagrams counted in\n ipSystemStatsInMcastPkts MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 37), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInMcastOctets.setDescription('The total number of octets received in IP multicast\n datagrams. This object counts the same octets as\n ipSystemStatsInMcastOctets, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 38), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutMcastPkts.setDescription('The number of IP multicast datagrams transmitted.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 39), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutMcastPkts.setDescription('The number of IP multicast datagrams transmitted. This\n object counts the same datagrams as\n ipSystemStatsOutMcastPkts, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 40), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutMcastOctets.setDescription('The total number of octets transmitted in IP multicast\n datagrams. Octets from datagrams counted in\n\n\n ipSystemStatsOutMcastPkts MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 41), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutMcastOctets.setDescription('The total number of octets transmitted in IP multicast\n datagrams. This object counts the same octets as\n ipSystemStatsOutMcastOctets, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsInBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 42), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsInBcastPkts.setDescription('The number of IP broadcast datagrams received.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCInBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 43), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCInBcastPkts.setDescription('The number of IP broadcast datagrams received. This object\n counts the same datagrams as ipSystemStatsInBcastPkts but\n allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n\n\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsOutBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 44), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsOutBcastPkts.setDescription('The number of IP broadcast datagrams transmitted.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsHCOutBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 45), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsHCOutBcastPkts.setDescription('The number of IP broadcast datagrams transmitted. This\n object counts the same datagrams as\n ipSystemStatsOutBcastPkts, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipSystemStatsDiscontinuityTime.')
ipSystemStatsDiscontinuityTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 46), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsDiscontinuityTime.setDescription("The value of sysUpTime on the most recent occasion at which\n any one or more of this entry's counters suffered a\n discontinuity.\n\n If no such discontinuities have occurred since the last re-\n initialization of the local management subsystem, then this\n object contains a zero value.")
ipSystemStatsRefreshRate = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 1, 1, 47), Unsigned32()).setUnits('milli-seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipSystemStatsRefreshRate.setDescription('The minimum reasonable polling interval for this entry.\n This object provides an indication of the minimum amount of\n time required to update the counters in this entry.')
ipIfStatsTableLastChange = MibScalar((1, 3, 6, 1, 2, 1, 4, 31, 2), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsTableLastChange.setDescription('The value of sysUpTime on the most recent occasion at which\n a row in the ipIfStatsTable was added or deleted.\n\n If new objects are added to the ipIfStatsTable that require\n the ipIfStatsTableLastChange to be updated when they are\n modified, they must specify that requirement in their\n description clause.')
ipIfStatsTable = MibTable((1, 3, 6, 1, 2, 1, 4, 31, 3), )
if mibBuilder.loadTexts: ipIfStatsTable.setDescription('The table containing per-interface traffic statistics. This\n table and the ipSystemStatsTable contain similar objects\n whose difference is in their granularity. Where this table\n contains per-interface statistics, the ipSystemStatsTable\n contains the same statistics, but counted on a system wide\n basis.')
ipIfStatsEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 31, 3, 1), ).setIndexNames((0, "IP-MIB", "ipIfStatsIPVersion"), (0, "IP-MIB", "ipIfStatsIfIndex"))
if mibBuilder.loadTexts: ipIfStatsEntry.setDescription('An interface statistics entry containing objects for a\n particular interface and version of IP.')
ipIfStatsIPVersion = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 1), InetVersion())
if mibBuilder.loadTexts: ipIfStatsIPVersion.setDescription('The IP version of this row.')
ipIfStatsIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 2), InterfaceIndex())
if mibBuilder.loadTexts: ipIfStatsIfIndex.setDescription("The index value that uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipIfStatsInReceives = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInReceives.setDescription('The total number of input IP datagrams received, including\n those received in error.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInReceives = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 4), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInReceives.setDescription('The total number of input IP datagrams received, including\n those received in error. This object counts the same\n datagrams as ipIfStatsInReceives, but allows for larger\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInOctets.setDescription('The total number of octets received in input IP datagrams,\n including those received in error. Octets from datagrams\n counted in ipIfStatsInReceives MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 6), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInOctets.setDescription('The total number of octets received in input IP datagrams,\n including those received in error. This object counts the\n same octets as ipIfStatsInOctets, but allows for larger\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInHdrErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInHdrErrors.setDescription('The number of input IP datagrams discarded due to errors in\n their IP headers, including version number mismatch, other\n format errors, hop count exceeded, errors discovered in\n processing their IP options, etc.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInNoRoutes = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInNoRoutes.setDescription('The number of input IP datagrams discarded because no route\n could be found to transmit them to their destination.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInAddrErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInAddrErrors.setDescription("The number of input IP datagrams discarded because the IP\n address in their IP header's destination field was not a\n valid address to be received at this entity. This count\n includes invalid addresses (e.g., ::0). For entities that\n are not IP routers and therefore do not forward datagrams,\n this counter includes datagrams discarded because the\n destination address was not a local address.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.")
ipIfStatsInUnknownProtos = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInUnknownProtos.setDescription('The number of locally-addressed IP datagrams received\n successfully but discarded because of an unknown or\n unsupported protocol.\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n\n\n ipIfStatsDiscontinuityTime.')
ipIfStatsInTruncatedPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInTruncatedPkts.setDescription("The number of input IP datagrams discarded because the\n datagram frame didn't carry enough data.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.")
ipIfStatsInForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInForwDatagrams.setDescription('The number of input datagrams for which this entity was not\n their final IP destination and for which this entity\n attempted to find a route to forward them to that final\n destination. In entities that do not act as IP routers,\n this counter will include only those datagrams that were\n Source-Routed via this entity, and the Source-Route\n processing was successful.\n\n When tracking interface statistics, the counter of the\n incoming interface is incremented for each datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 13), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInForwDatagrams.setDescription('The number of input datagrams for which this entity was not\n their final IP destination and for which this entity\n attempted to find a route to forward them to that final\n destination. This object counts the same packets as\n\n\n ipIfStatsInForwDatagrams, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsReasmReqds = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsReasmReqds.setDescription('The number of IP fragments received that needed to be\n reassembled at this interface.\n\n When tracking interface statistics, the counter of the\n interface to which these fragments were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the fragments.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsReasmOKs = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 15), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsReasmOKs.setDescription('The number of IP datagrams successfully reassembled.\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsReasmFails = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 16), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsReasmFails.setDescription('The number of failures detected by the IP re-assembly\n algorithm (for whatever reason: timed out, errors, etc.).\n Note that this is not necessarily a count of discarded IP\n fragments since some algorithms (notably the algorithm in\n RFC 815) can lose track of the number of fragments by\n combining them as they are received.\n\n When tracking interface statistics, the counter of the\n interface to which these fragments were addressed is\n incremented. This interface might not be the same as the\n input interface for some of the fragments.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInDiscards = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 17), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInDiscards.setDescription('The number of input IP datagrams for which no problems were\n encountered to prevent their continued processing, but\n were discarded (e.g., for lack of buffer space). Note that\n this counter does not include any datagrams discarded while\n awaiting re-assembly.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInDelivers = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 18), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInDelivers.setDescription('The total number of datagrams successfully delivered to IP\n user-protocols (including ICMP).\n\n When tracking interface statistics, the counter of the\n interface to which these datagrams were addressed is\n incremented. This interface might not be the same as the\n\n\n input interface for some of the datagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInDelivers = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 19), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInDelivers.setDescription('The total number of datagrams successfully delivered to IP\n user-protocols (including ICMP). This object counts the\n same packets as ipIfStatsInDelivers, but allows for larger\n values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutRequests = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 20), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutRequests.setDescription('The total number of IP datagrams that local IP user-\n protocols (including ICMP) supplied to IP in requests for\n transmission. Note that this counter does not include any\n datagrams counted in ipIfStatsOutForwDatagrams.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutRequests = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 21), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutRequests.setDescription('The total number of IP datagrams that local IP user-\n protocols (including ICMP) supplied to IP in requests for\n transmission. This object counts the same packets as\n\n\n ipIfStatsOutRequests, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 23), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutForwDatagrams.setDescription('The number of datagrams for which this entity was not their\n final IP destination and for which it was successful in\n finding a path to their final destination. In entities\n that do not act as IP routers, this counter will include\n only those datagrams that were Source-Routed via this\n entity, and the Source-Route processing was successful.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n forwarded datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutForwDatagrams = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 24), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutForwDatagrams.setDescription('The number of datagrams for which this entity was not their\n final IP destination and for which it was successful in\n finding a path to their final destination. This object\n counts the same packets as ipIfStatsOutForwDatagrams, but\n allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n\n\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutDiscards = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 25), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutDiscards.setDescription('The number of output IP datagrams for which no problem was\n encountered to prevent their transmission to their\n destination, but were discarded (e.g., for lack of\n buffer space). Note that this counter would include\n datagrams counted in ipIfStatsOutForwDatagrams if any such\n datagrams met this (discretionary) discard criterion.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutFragReqds = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 26), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutFragReqds.setDescription('The number of IP datagrams that would require fragmentation\n in order to be transmitted.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutFragOKs = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 27), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutFragOKs.setDescription('The number of IP datagrams that have been successfully\n fragmented.\n\n When tracking interface statistics, the counter of the\n\n\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutFragFails = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 28), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutFragFails.setDescription('The number of IP datagrams that have been discarded because\n they needed to be fragmented but could not be. This\n includes IPv4 packets that have the DF bit set and IPv6\n packets that are being forwarded and exceed the outgoing\n link MTU.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for an unsuccessfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutFragCreates = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 29), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutFragCreates.setDescription('The number of output datagram fragments that have been\n generated as a result of IP fragmentation.\n\n When tracking interface statistics, the counter of the\n outgoing interface is incremented for a successfully\n fragmented datagram.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutTransmits = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 30), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutTransmits.setDescription('The total number of IP datagrams that this entity supplied\n to the lower layers for transmission. This includes\n datagrams generated locally and those forwarded by this\n entity.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutTransmits = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 31), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutTransmits.setDescription('The total number of IP datagrams that this entity supplied\n to the lower layers for transmission. This object counts\n the same datagrams as ipIfStatsOutTransmits, but allows for\n larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 32), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutOctets.setDescription('The total number of octets in IP datagrams delivered to the\n lower layers for transmission. Octets from datagrams\n counted in ipIfStatsOutTransmits MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 33), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutOctets.setDescription('The total number of octets in IP datagrams delivered to the\n lower layers for transmission. This objects counts the same\n octets as ipIfStatsOutOctets, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 34), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInMcastPkts.setDescription('The number of IP multicast datagrams received.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 35), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInMcastPkts.setDescription('The number of IP multicast datagrams received. This object\n counts the same datagrams as ipIfStatsInMcastPkts, but\n allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 36), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInMcastOctets.setDescription('The total number of octets received in IP multicast\n\n\n datagrams. Octets from datagrams counted in\n ipIfStatsInMcastPkts MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 37), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInMcastOctets.setDescription('The total number of octets received in IP multicast\n datagrams. This object counts the same octets as\n ipIfStatsInMcastOctets, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 38), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutMcastPkts.setDescription('The number of IP multicast datagrams transmitted.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutMcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 39), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutMcastPkts.setDescription('The number of IP multicast datagrams transmitted. This\n object counts the same datagrams as ipIfStatsOutMcastPkts,\n but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n\n\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 40), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutMcastOctets.setDescription('The total number of octets transmitted in IP multicast\n datagrams. Octets from datagrams counted in\n ipIfStatsOutMcastPkts MUST be counted here.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutMcastOctets = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 41), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutMcastOctets.setDescription('The total number of octets transmitted in IP multicast\n datagrams. This object counts the same octets as\n ipIfStatsOutMcastOctets, but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsInBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 42), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsInBcastPkts.setDescription('The number of IP broadcast datagrams received.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCInBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 43), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCInBcastPkts.setDescription('The number of IP broadcast datagrams received. This object\n counts the same datagrams as ipIfStatsInBcastPkts, but\n allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsOutBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 44), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsOutBcastPkts.setDescription('The number of IP broadcast datagrams transmitted.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsHCOutBcastPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 45), Counter64()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsHCOutBcastPkts.setDescription('The number of IP broadcast datagrams transmitted. This\n object counts the same datagrams as ipIfStatsOutBcastPkts,\n but allows for larger values.\n\n Discontinuities in the value of this counter can occur at\n re-initialization of the management system, and at other\n times as indicated by the value of\n ipIfStatsDiscontinuityTime.')
ipIfStatsDiscontinuityTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 46), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsDiscontinuityTime.setDescription("The value of sysUpTime on the most recent occasion at which\n\n\n any one or more of this entry's counters suffered a\n discontinuity.\n\n If no such discontinuities have occurred since the last re-\n initialization of the local management subsystem, then this\n object contains a zero value.")
ipIfStatsRefreshRate = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 31, 3, 1, 47), Unsigned32()).setUnits('milli-seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipIfStatsRefreshRate.setDescription('The minimum reasonable polling interval for this entry.\n This object provides an indication of the minimum amount of\n time required to update the counters in this entry.')
ipAddressPrefixTable = MibTable((1, 3, 6, 1, 2, 1, 4, 32), )
if mibBuilder.loadTexts: ipAddressPrefixTable.setDescription("This table allows the user to determine the source of an IP\n address or set of IP addresses, and allows other tables to\n share the information via pointer rather than by copying.\n\n For example, when the node configures both a unicast and\n anycast address for a prefix, the ipAddressPrefix objects\n for those addresses will point to a single row in this\n table.\n\n This table primarily provides support for IPv6 prefixes, and\n several of the objects are less meaningful for IPv4. The\n table continues to allow IPv4 addresses to allow future\n flexibility. In order to promote a common configuration,\n this document includes suggestions for default values for\n IPv4 prefixes. Each of these values may be overridden if an\n object is meaningful to the node.\n\n All prefixes used by this entity should be included in this\n table independent of how the entity learned the prefix.\n (This table isn't limited to prefixes learned from router\n\n\n advertisements.)")
ipAddressPrefixEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 32, 1), ).setIndexNames((0, "IP-MIB", "ipAddressPrefixIfIndex"), (0, "IP-MIB", "ipAddressPrefixType"), (0, "IP-MIB", "ipAddressPrefixPrefix"), (0, "IP-MIB", "ipAddressPrefixLength"))
if mibBuilder.loadTexts: ipAddressPrefixEntry.setDescription('An entry in the ipAddressPrefixTable.')
ipAddressPrefixIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipAddressPrefixIfIndex.setDescription("The index value that uniquely identifies the interface on\n which this prefix is configured. The interface identified\n by a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipAddressPrefixType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 2), InetAddressType())
if mibBuilder.loadTexts: ipAddressPrefixType.setDescription('The address type of ipAddressPrefix.')
ipAddressPrefixPrefix = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 3), InetAddress())
if mibBuilder.loadTexts: ipAddressPrefixPrefix.setDescription('The address prefix. The address type of this object is\n specified in ipAddressPrefixType. The length of this object\n is the standard length for objects of that type (4 or 16\n bytes). Any bits after ipAddressPrefixLength must be zero.\n\n Implementors need to be aware that, if the size of\n ipAddressPrefixPrefix exceeds 114 octets, then OIDS of\n instances of columns in this row will have more than 128\n sub-identifiers and cannot be accessed using SNMPv1,\n SNMPv2c, or SNMPv3.')
ipAddressPrefixLength = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 4), InetAddressPrefixLength())
if mibBuilder.loadTexts: ipAddressPrefixLength.setDescription("The prefix length associated with this prefix.\n\n The value 0 has no special meaning for this object. It\n simply refers to address '::/0'.")
ipAddressPrefixOrigin = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 5), IpAddressPrefixOriginTC()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefixOrigin.setDescription('The origin of this prefix.')
ipAddressPrefixOnLinkFlag = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 6), TruthValue()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefixOnLinkFlag.setDescription("This object has the value 'true(1)', if this prefix can be\n used for on-link determination; otherwise, the value is\n 'false(2)'.\n\n The default for IPv4 prefixes is 'true(1)'.")
ipAddressPrefixAutonomousFlag = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 7), TruthValue()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefixAutonomousFlag.setDescription("Autonomous address configuration flag. When true(1),\n indicates that this prefix can be used for autonomous\n address configuration (i.e., can be used to form a local\n interface address). If false(2), it is not used to auto-\n configure a local interface address.\n\n The default for IPv4 prefixes is 'false(2)'.")
ipAddressPrefixAdvPreferredLifetime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 8), Unsigned32()).setUnits('seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefixAdvPreferredLifetime.setDescription('The remaining length of time, in seconds, that this prefix\n will continue to be preferred, i.e., time until deprecation.\n\n A value of 4,294,967,295 represents infinity.\n\n The address generated from a deprecated prefix should no\n longer be used as a source address in new communications,\n but packets received on such an interface are processed as\n expected.\n\n The default for IPv4 prefixes is 4,294,967,295 (infinity).')
ipAddressPrefixAdvValidLifetime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 32, 1, 9), Unsigned32()).setUnits('seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefixAdvValidLifetime.setDescription('The remaining length of time, in seconds, that this prefix\n will continue to be valid, i.e., time until invalidation. A\n value of 4,294,967,295 represents infinity.\n\n The address generated from an invalidated prefix should not\n appear as the destination or source address of a packet.\n\n\n The default for IPv4 prefixes is 4,294,967,295 (infinity).')
ipAddressSpinLock = MibScalar((1, 3, 6, 1, 2, 1, 4, 33), TestAndIncr()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipAddressSpinLock.setDescription("An advisory lock used to allow cooperating SNMP managers to\n coordinate their use of the set operation in creating or\n modifying rows within this table.\n\n In order to use this lock to coordinate the use of set\n operations, managers should first retrieve\n ipAddressTableSpinLock. They should then determine the\n appropriate row to create or modify. Finally, they should\n issue the appropriate set command, including the retrieved\n value of ipAddressSpinLock. If another manager has altered\n the table in the meantime, then the value of\n ipAddressSpinLock will have changed, and the creation will\n fail as it will be specifying an incorrect value for\n ipAddressSpinLock. It is suggested, but not required, that\n the ipAddressSpinLock be the first var bind for each set of\n objects representing a 'row' in a PDU.")
ipAddressTable = MibTable((1, 3, 6, 1, 2, 1, 4, 34), )
if mibBuilder.loadTexts: ipAddressTable.setDescription("This table contains addressing information relevant to the\n entity's interfaces.\n\n This table does not contain multicast address information.\n Tables for such information should be contained in multicast\n specific MIBs, such as RFC 3019.\n\n While this table is writable, the user will note that\n several objects, such as ipAddressOrigin, are not. The\n intention in allowing a user to write to this table is to\n allow them to add or remove any entry that isn't\n\n\n permanent. The user should be allowed to modify objects\n and entries when that would not cause inconsistencies\n within the table. Allowing write access to objects, such\n as ipAddressOrigin, could allow a user to insert an entry\n and then label it incorrectly.\n\n Note well: When including IPv6 link-local addresses in this\n table, the entry must use an InetAddressType of 'ipv6z' in\n order to differentiate between the possible interfaces.")
ipAddressEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 34, 1), ).setIndexNames((0, "IP-MIB", "ipAddressAddrType"), (0, "IP-MIB", "ipAddressAddr"))
if mibBuilder.loadTexts: ipAddressEntry.setDescription('An address mapping for a particular interface.')
ipAddressAddrType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 1), InetAddressType())
if mibBuilder.loadTexts: ipAddressAddrType.setDescription('The address type of ipAddressAddr.')
ipAddressAddr = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 2), InetAddress())
if mibBuilder.loadTexts: ipAddressAddr.setDescription("The IP address to which this entry's addressing information\n\n\n pertains. The address type of this object is specified in\n ipAddressAddrType.\n\n Implementors need to be aware that if the size of\n ipAddressAddr exceeds 116 octets, then OIDS of instances of\n columns in this row will have more than 128 sub-identifiers\n and cannot be accessed using SNMPv1, SNMPv2c, or SNMPv3.")
ipAddressIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 3), InterfaceIndex()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipAddressIfIndex.setDescription("The index value that uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipAddressType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3,))).clone(namedValues=NamedValues(("unicast", 1), ("anycast", 2), ("broadcast", 3),)).clone('unicast')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipAddressType.setDescription('The type of address. broadcast(3) is not a valid value for\n IPv6 addresses (RFC 3513).')
ipAddressPrefix = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 5), RowPointer().clone((0, 0))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressPrefix.setDescription('A pointer to the row in the prefix table to which this\n address belongs. May be { 0 0 } if there is no such row.')
ipAddressOrigin = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 6), IpAddressOriginTC()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressOrigin.setDescription('The origin of the address.')
ipAddressStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 7), IpAddressStatusTC().clone('preferred')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipAddressStatus.setDescription('The status of the address, describing if the address can be\n used for communication.\n\n In the absence of other information, an IPv4 address is\n always preferred(1).')
ipAddressCreated = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 8), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressCreated.setDescription('The value of sysUpTime at the time this entry was created.\n If this entry was created prior to the last re-\n initialization of the local network management subsystem,\n then this object contains a zero value.')
ipAddressLastChanged = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 9), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAddressLastChanged.setDescription('The value of sysUpTime at the time this entry was last\n updated. If this entry was updated prior to the last re-\n initialization of the local network management subsystem,\n then this object contains a zero value.')
ipAddressRowStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 10), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipAddressRowStatus.setDescription('The status of this conceptual row.\n\n The RowStatus TC requires that this DESCRIPTION clause\n states under which circumstances other objects in this row\n\n\n can be modified. The value of this object has no effect on\n whether other objects in this conceptual row can be\n modified.\n\n A conceptual row can not be made active until the\n ipAddressIfIndex has been set to a valid index.')
ipAddressStorageType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 34, 1, 11), StorageType().clone('volatile')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipAddressStorageType.setDescription("The storage type for this conceptual row. If this object\n has a value of 'permanent', then no other objects are\n required to be able to be modified.")
ipNetToPhysicalTable = MibTable((1, 3, 6, 1, 2, 1, 4, 35), )
if mibBuilder.loadTexts: ipNetToPhysicalTable.setDescription("The IP Address Translation table used for mapping from IP\n addresses to physical addresses.\n\n The Address Translation tables contain the IP address to\n 'physical' address equivalences. Some interfaces do not use\n translation tables for determining address equivalences\n (e.g., DDN-X.25 has an algorithmic method); if all\n interfaces are of this type, then the Address Translation\n table is empty, i.e., has zero entries.\n\n While many protocols may be used to populate this table, ARP\n and Neighbor Discovery are the most likely\n options.")
ipNetToPhysicalEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 35, 1), ).setIndexNames((0, "IP-MIB", "ipNetToPhysicalIfIndex"), (0, "IP-MIB", "ipNetToPhysicalNetAddressType"), (0, "IP-MIB", "ipNetToPhysicalNetAddress"))
if mibBuilder.loadTexts: ipNetToPhysicalEntry.setDescription("Each entry contains one IP address to `physical' address\n equivalence.")
ipNetToPhysicalIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipNetToPhysicalIfIndex.setDescription("The index value that uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipNetToPhysicalNetAddressType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 2), InetAddressType())
if mibBuilder.loadTexts: ipNetToPhysicalNetAddressType.setDescription('The type of ipNetToPhysicalNetAddress.')
ipNetToPhysicalNetAddress = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 3), InetAddress())
if mibBuilder.loadTexts: ipNetToPhysicalNetAddress.setDescription("The IP Address corresponding to the media-dependent\n `physical' address. The address type of this object is\n specified in ipNetToPhysicalAddressType.\n\n Implementors need to be aware that if the size of\n\n\n ipNetToPhysicalNetAddress exceeds 115 octets, then OIDS of\n instances of columns in this row will have more than 128\n sub-identifiers and cannot be accessed using SNMPv1,\n SNMPv2c, or SNMPv3.")
ipNetToPhysicalPhysAddress = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 4), PhysAddress().subtype(subtypeSpec=ValueSizeConstraint(0,65535))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToPhysicalPhysAddress.setDescription("The media-dependent `physical' address.\n\n As the entries in this table are typically not persistent\n when this object is written the entity SHOULD NOT save the\n change to non-volatile storage.")
ipNetToPhysicalLastUpdated = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 5), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipNetToPhysicalLastUpdated.setDescription('The value of sysUpTime at the time this entry was last\n updated. If this entry was updated prior to the last re-\n initialization of the local network management subsystem,\n then this object contains a zero value.')
ipNetToPhysicalType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 6), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5,))).clone(namedValues=NamedValues(("other", 1), ("invalid", 2), ("dynamic", 3), ("static", 4), ("local", 5),)).clone('static')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToPhysicalType.setDescription("The type of mapping.\n\n Setting this object to the value invalid(2) has the effect\n of invalidating the corresponding entry in the\n ipNetToPhysicalTable. That is, it effectively dis-\n associates the interface identified with said entry from the\n mapping identified with said entry. It is an\n implementation-specific matter as to whether the agent\n\n\n removes an invalidated entry from the table. Accordingly,\n management stations must be prepared to receive tabular\n information from agents that corresponds to entries not\n currently in use. Proper interpretation of such entries\n requires examination of the relevant ipNetToPhysicalType\n object.\n\n The 'dynamic(3)' type indicates that the IP address to\n physical addresses mapping has been dynamically resolved\n using e.g., IPv4 ARP or the IPv6 Neighbor Discovery\n protocol.\n\n The 'static(4)' type indicates that the mapping has been\n statically configured. Both of these refer to entries that\n provide mappings for other entities addresses.\n\n The 'local(5)' type indicates that the mapping is provided\n for an entity's own interface address.\n\n As the entries in this table are typically not persistent\n when this object is written the entity SHOULD NOT save the\n change to non-volatile storage.")
ipNetToPhysicalState = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 7), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5, 6, 7,))).clone(namedValues=NamedValues(("reachable", 1), ("stale", 2), ("delay", 3), ("probe", 4), ("invalid", 5), ("unknown", 6), ("incomplete", 7),))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipNetToPhysicalState.setDescription('The Neighbor Unreachability Detection state for the\n interface when the address mapping in this entry is used.\n If Neighbor Unreachability Detection is not in use (e.g. for\n IPv4), this object is always unknown(6).')
ipNetToPhysicalRowStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 35, 1, 8), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToPhysicalRowStatus.setDescription("The status of this conceptual row.\n\n The RowStatus TC requires that this DESCRIPTION clause\n states under which circumstances other objects in this row\n can be modified. The value of this object has no effect on\n whether other objects in this conceptual row can be\n modified.\n\n A conceptual row can not be made active until the\n ipNetToPhysicalPhysAddress object has been set.\n\n Note that if the ipNetToPhysicalType is set to 'invalid',\n the managed node may delete the entry independent of the\n state of this object.")
ipv6ScopeZoneIndexTable = MibTable((1, 3, 6, 1, 2, 1, 4, 36), )
if mibBuilder.loadTexts: ipv6ScopeZoneIndexTable.setDescription('The table used to describe IPv6 unicast and multicast scope\n zones.\n\n For those objects that have names rather than numbers, the\n names were chosen to coincide with the names used in the\n IPv6 address architecture document. ')
ipv6ScopeZoneIndexEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 36, 1), ).setIndexNames((0, "IP-MIB", "ipv6ScopeZoneIndexIfIndex"))
if mibBuilder.loadTexts: ipv6ScopeZoneIndexEntry.setDescription('Each entry contains the list of scope identifiers on a given\n interface.')
ipv6ScopeZoneIndexIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipv6ScopeZoneIndexIfIndex.setDescription("The index value that uniquely identifies the interface to\n which these scopes belong. The interface identified by a\n particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipv6ScopeZoneIndexLinkLocal = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 2), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexLinkLocal.setDescription('The zone index for the link-local scope on this interface.')
ipv6ScopeZoneIndex3 = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 3), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndex3.setDescription('The zone index for scope 3 on this interface.')
ipv6ScopeZoneIndexAdminLocal = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 4), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexAdminLocal.setDescription('The zone index for the admin-local scope on this interface.')
ipv6ScopeZoneIndexSiteLocal = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 5), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexSiteLocal.setDescription('The zone index for the site-local scope on this interface.')
ipv6ScopeZoneIndex6 = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 6), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndex6.setDescription('The zone index for scope 6 on this interface.')
ipv6ScopeZoneIndex7 = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 7), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndex7.setDescription('The zone index for scope 7 on this interface.')
ipv6ScopeZoneIndexOrganizationLocal = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 8), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexOrganizationLocal.setDescription('The zone index for the organization-local scope on this\n interface.')
ipv6ScopeZoneIndex9 = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 9), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndex9.setDescription('The zone index for scope 9 on this interface.')
ipv6ScopeZoneIndexA = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 10), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexA.setDescription('The zone index for scope A on this interface.')
ipv6ScopeZoneIndexB = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 11), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexB.setDescription('The zone index for scope B on this interface.')
ipv6ScopeZoneIndexC = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 12), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexC.setDescription('The zone index for scope C on this interface.')
ipv6ScopeZoneIndexD = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 36, 1, 13), InetZoneIndex()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipv6ScopeZoneIndexD.setDescription('The zone index for scope D on this interface.')
ipDefaultRouterTable = MibTable((1, 3, 6, 1, 2, 1, 4, 37), )
if mibBuilder.loadTexts: ipDefaultRouterTable.setDescription('The table used to describe the default routers known to this\n\n\n entity.')
ipDefaultRouterEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 37, 1), ).setIndexNames((0, "IP-MIB", "ipDefaultRouterAddressType"), (0, "IP-MIB", "ipDefaultRouterAddress"), (0, "IP-MIB", "ipDefaultRouterIfIndex"))
if mibBuilder.loadTexts: ipDefaultRouterEntry.setDescription('Each entry contains information about a default router known\n to this entity.')
ipDefaultRouterAddressType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 37, 1, 1), InetAddressType())
if mibBuilder.loadTexts: ipDefaultRouterAddressType.setDescription('The address type for this row.')
ipDefaultRouterAddress = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 37, 1, 2), InetAddress())
if mibBuilder.loadTexts: ipDefaultRouterAddress.setDescription('The IP address of the default router represented by this\n row. The address type of this object is specified in\n ipDefaultRouterAddressType.\n\n Implementers need to be aware that if the size of\n ipDefaultRouterAddress exceeds 115 octets, then OIDS of\n instances of columns in this row will have more than 128\n sub-identifiers and cannot be accessed using SNMPv1,\n SNMPv2c, or SNMPv3.')
ipDefaultRouterIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 37, 1, 3), InterfaceIndex())
if mibBuilder.loadTexts: ipDefaultRouterIfIndex.setDescription("The index value that uniquely identifies the interface by\n which the router can be reached. The interface identified\n by a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipDefaultRouterLifetime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 37, 1, 4), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0,65535))).setUnits('seconds').setMaxAccess("readonly")
if mibBuilder.loadTexts: ipDefaultRouterLifetime.setDescription('The remaining length of time, in seconds, that this router\n will continue to be useful as a default router. A value of\n zero indicates that it is no longer useful as a default\n router. It is left to the implementer of the MIB as to\n whether a router with a lifetime of zero is removed from the\n list.\n\n For IPv6, this value should be extracted from the router\n advertisement messages.')
ipDefaultRouterPreference = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 37, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(-2, -1, 0, 1,))).clone(namedValues=NamedValues(("reserved", -2), ("low", -1), ("medium", 0), ("high", 1),))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipDefaultRouterPreference.setDescription('An indication of preference given to this router as a\n default router as described in he Default Router\n Preferences document. Treating the value as a\n 2 bit signed integer allows for simple arithmetic\n comparisons.\n\n For IPv4 routers or IPv6 routers that are not using the\n updated router advertisement format, this object is set to\n medium (0).')
ipv6RouterAdvertSpinLock = MibScalar((1, 3, 6, 1, 2, 1, 4, 38), TestAndIncr()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: ipv6RouterAdvertSpinLock.setDescription("An advisory lock used to allow cooperating SNMP managers to\n coordinate their use of the set operation in creating or\n modifying rows within this table.\n\n In order to use this lock to coordinate the use of set\n operations, managers should first retrieve\n ipv6RouterAdvertSpinLock. They should then determine the\n appropriate row to create or modify. Finally, they should\n issue the appropriate set command including the retrieved\n value of ipv6RouterAdvertSpinLock. If another manager has\n altered the table in the meantime, then the value of\n ipv6RouterAdvertSpinLock will have changed and the creation\n will fail as it will be specifying an incorrect value for\n ipv6RouterAdvertSpinLock. It is suggested, but not\n required, that the ipv6RouterAdvertSpinLock be the first var\n bind for each set of objects representing a 'row' in a PDU.")
ipv6RouterAdvertTable = MibTable((1, 3, 6, 1, 2, 1, 4, 39), )
if mibBuilder.loadTexts: ipv6RouterAdvertTable.setDescription('The table containing information used to construct router\n advertisements.')
ipv6RouterAdvertEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 39, 1), ).setIndexNames((0, "IP-MIB", "ipv6RouterAdvertIfIndex"))
if mibBuilder.loadTexts: ipv6RouterAdvertEntry.setDescription('An entry containing information used to construct router\n advertisements.\n\n Information in this table is persistent, and when this\n object is written, the entity SHOULD save the change to\n non-volatile storage.')
ipv6RouterAdvertIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: ipv6RouterAdvertIfIndex.setDescription("The index value that uniquely identifies the interface on\n which router advertisements constructed with this\n information will be transmitted. The interface identified\n by a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipv6RouterAdvertSendAdverts = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 2), TruthValue().clone('false')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertSendAdverts.setDescription('A flag indicating whether the router sends periodic\n router advertisements and responds to router solicitations\n on this interface.')
ipv6RouterAdvertMaxInterval = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 3), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(4,1800)).clone(600)).setUnits('seconds').setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertMaxInterval.setDescription('The maximum time allowed between sending unsolicited router\n\n\n advertisements from this interface.')
ipv6RouterAdvertMinInterval = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 4), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(3,1350))).setUnits('seconds').setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertMinInterval.setDescription('The minimum time allowed between sending unsolicited router\n advertisements from this interface.\n\n The default is 0.33 * ipv6RouterAdvertMaxInterval, however,\n in the case of a low value for ipv6RouterAdvertMaxInterval,\n the minimum value for this object is restricted to 3.')
ipv6RouterAdvertManagedFlag = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 5), TruthValue().clone('false')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertManagedFlag.setDescription("The true/false value to be placed into the 'managed address\n configuration' flag field in router advertisements sent from\n this interface.")
ipv6RouterAdvertOtherConfigFlag = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 6), TruthValue().clone('false')).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertOtherConfigFlag.setDescription("The true/false value to be placed into the 'other stateful\n configuration' flag field in router advertisements sent from\n this interface.")
ipv6RouterAdvertLinkMTU = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 7), Unsigned32()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertLinkMTU.setDescription('The value to be placed in MTU options sent by the router on\n this interface.\n\n A value of zero indicates that no MTU options are sent.')
ipv6RouterAdvertReachableTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 8), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0,3600000))).setUnits('milliseconds').setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertReachableTime.setDescription("The value to be placed in the reachable time field in router\n advertisement messages sent from this interface.\n\n A value of zero in the router advertisement indicates that\n the advertisement isn't specifying a value for reachable\n time.")
ipv6RouterAdvertRetransmitTime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 9), Unsigned32()).setUnits('milliseconds').setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertRetransmitTime.setDescription("The value to be placed in the retransmit timer field in\n router advertisements sent from this interface.\n\n A value of zero in the router advertisement indicates that\n the advertisement isn't specifying a value for retrans\n time.")
ipv6RouterAdvertCurHopLimit = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 10), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0,255))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertCurHopLimit.setDescription("The default value to be placed in the current hop limit\n field in router advertisements sent from this interface.\n\n\n The value should be set to the current diameter of the\n Internet.\n\n A value of zero in the router advertisement indicates that\n the advertisement isn't specifying a value for curHopLimit.\n\n The default should be set to the value specified in the IANA\n web pages (www.iana.org) at the time of implementation.")
ipv6RouterAdvertDefaultLifetime = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 11), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0,0),ValueRangeConstraint(4,9000),))).setUnits('seconds').setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertDefaultLifetime.setDescription('The value to be placed in the router lifetime field of\n router advertisements sent from this interface. This value\n MUST be either 0 or between ipv6RouterAdvertMaxInterval and\n 9000 seconds.\n\n A value of zero indicates that the router is not to be used\n as a default router.\n\n The default is 3 * ipv6RouterAdvertMaxInterval.')
ipv6RouterAdvertRowStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 39, 1, 12), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipv6RouterAdvertRowStatus.setDescription('The status of this conceptual row.\n\n As all objects in this conceptual row have default values, a\n row can be created and made active by setting this object\n appropriately.\n\n The RowStatus TC requires that this DESCRIPTION clause\n states under which circumstances other objects in this row\n can be modified. The value of this object has no effect on\n whether other objects in this conceptual row can be\n modified.')
icmp = MibIdentifier((1, 3, 6, 1, 2, 1, 5))
icmpStatsTable = MibTable((1, 3, 6, 1, 2, 1, 5, 29), )
if mibBuilder.loadTexts: icmpStatsTable.setDescription('The table of generic system-wide ICMP counters.')
icmpStatsEntry = MibTableRow((1, 3, 6, 1, 2, 1, 5, 29, 1), ).setIndexNames((0, "IP-MIB", "icmpStatsIPVersion"))
if mibBuilder.loadTexts: icmpStatsEntry.setDescription('A conceptual row in the icmpStatsTable.')
icmpStatsIPVersion = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 29, 1, 1), InetVersion())
if mibBuilder.loadTexts: icmpStatsIPVersion.setDescription('The IP version of the statistics.')
icmpStatsInMsgs = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 29, 1, 2), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpStatsInMsgs.setDescription('The total number of ICMP messages that the entity received.\n Note that this counter includes all those counted by\n icmpStatsInErrors.')
icmpStatsInErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 29, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpStatsInErrors.setDescription('The number of ICMP messages that the entity received but\n determined as having ICMP-specific errors (bad ICMP\n checksums, bad length, etc.).')
icmpStatsOutMsgs = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 29, 1, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpStatsOutMsgs.setDescription('The total number of ICMP messages that the entity attempted\n to send. Note that this counter includes all those counted\n by icmpStatsOutErrors.')
icmpStatsOutErrors = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 29, 1, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpStatsOutErrors.setDescription("The number of ICMP messages that this entity did not send\n due to problems discovered within ICMP, such as a lack of\n buffers. This value should not include errors discovered\n outside the ICMP layer, such as the inability of IP to route\n the resultant datagram. In some implementations, there may\n be no types of error that contribute to this counter's\n value.")
icmpMsgStatsTable = MibTable((1, 3, 6, 1, 2, 1, 5, 30), )
if mibBuilder.loadTexts: icmpMsgStatsTable.setDescription('The table of system-wide per-version, per-message type ICMP\n counters.')
icmpMsgStatsEntry = MibTableRow((1, 3, 6, 1, 2, 1, 5, 30, 1), ).setIndexNames((0, "IP-MIB", "icmpMsgStatsIPVersion"), (0, "IP-MIB", "icmpMsgStatsType"))
if mibBuilder.loadTexts: icmpMsgStatsEntry.setDescription('A conceptual row in the icmpMsgStatsTable.\n\n The system should track each ICMP type value, even if that\n ICMP type is not supported by the system. However, a\n given row need not be instantiated unless a message of that\n type has been processed, i.e., the row for\n icmpMsgStatsType=X MAY be instantiated before but MUST be\n instantiated after the first message with Type=X is\n received or transmitted. After receiving or transmitting\n any succeeding messages with Type=X, the relevant counter\n must be incremented.')
icmpMsgStatsIPVersion = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 30, 1, 1), InetVersion())
if mibBuilder.loadTexts: icmpMsgStatsIPVersion.setDescription('The IP version of the statistics.')
icmpMsgStatsType = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 30, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0,255)))
if mibBuilder.loadTexts: icmpMsgStatsType.setDescription('The ICMP type field of the message type being counted by\n this row.\n\n Note that ICMP message types are scoped by the address type\n in use.')
icmpMsgStatsInPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 30, 1, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpMsgStatsInPkts.setDescription('The number of input packets for this AF and type.')
icmpMsgStatsOutPkts = MibTableColumn((1, 3, 6, 1, 2, 1, 5, 30, 1, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpMsgStatsOutPkts.setDescription('The number of output packets for this AF and type.')
ipMIBConformance = MibIdentifier((1, 3, 6, 1, 2, 1, 48, 2))
ipMIBCompliances = MibIdentifier((1, 3, 6, 1, 2, 1, 48, 2, 1))
ipMIBGroups = MibIdentifier((1, 3, 6, 1, 2, 1, 48, 2, 2))
ipMIBCompliance2 = ModuleCompliance((1, 3, 6, 1, 2, 1, 48, 2, 1, 2)).setObjects(*(("IP-MIB", "ipSystemStatsGroup"), ("IP-MIB", "ipAddressGroup"), ("IP-MIB", "ipNetToPhysicalGroup"), ("IP-MIB", "ipDefaultRouterGroup"), ("IP-MIB", "icmpStatsGroup"), ("IP-MIB", "ipSystemStatsHCOctetGroup"), ("IP-MIB", "ipSystemStatsHCPacketGroup"), ("IP-MIB", "ipIfStatsGroup"), ("IP-MIB", "ipIfStatsHCOctetGroup"), ("IP-MIB", "ipIfStatsHCPacketGroup"), ("IP-MIB", "ipv4GeneralGroup"), ("IP-MIB", "ipv4IfGroup"), ("IP-MIB", "ipv4SystemStatsGroup"), ("IP-MIB", "ipv4SystemStatsHCPacketGroup"), ("IP-MIB", "ipv4IfStatsGroup"), ("IP-MIB", "ipv4IfStatsHCPacketGroup"), ("IP-MIB", "ipv6GeneralGroup2"), ("IP-MIB", "ipv6IfGroup"), ("IP-MIB", "ipAddressPrefixGroup"), ("IP-MIB", "ipv6ScopeGroup"), ("IP-MIB", "ipv6RouterAdvertGroup"), ("IP-MIB", "ipLastChangeGroup"),))
if mibBuilder.loadTexts: ipMIBCompliance2.setDescription('The compliance statement for systems that implement IP -\n either IPv4 or IPv6.\n\n There are a number of INDEX objects that cannot be\n represented in the form of OBJECT clauses in SMIv2, but\n for which we have the following compliance requirements,\n expressed in OBJECT clause form in this description\n clause:\n\n\n -- OBJECT ipSystemStatsIPVersion\n -- SYNTAX InetVersion {ipv4(1), ipv6(2)}\n -- DESCRIPTION\n -- This MIB requires support for only IPv4 and IPv6\n -- versions.\n --\n -- OBJECT ipIfStatsIPVersion\n -- SYNTAX InetVersion {ipv4(1), ipv6(2)}\n -- DESCRIPTION\n -- This MIB requires support for only IPv4 and IPv6\n -- versions.\n --\n -- OBJECT icmpStatsIPVersion\n -- SYNTAX InetVersion {ipv4(1), ipv6(2)}\n -- DESCRIPTION\n -- This MIB requires support for only IPv4 and IPv6\n -- versions.\n --\n -- OBJECT icmpMsgStatsIPVersion\n -- SYNTAX InetVersion {ipv4(1), ipv6(2)}\n -- DESCRIPTION\n -- This MIB requires support for only IPv4 and IPv6\n -- versions.\n --\n -- OBJECT ipAddressPrefixType\n -- SYNTAX InetAddressType {ipv4(1), ipv6(2)}\n -- DESCRIPTION\n -- This MIB requires support for only global IPv4 and\n -- IPv6 address types.\n --\n -- OBJECT ipAddressPrefixPrefix\n -- SYNTAX InetAddress (Size(4 | 16))\n -- DESCRIPTION\n -- This MIB requires support for only global IPv4 and\n -- IPv6 addresses and so the size can be either 4 or\n -- 16 bytes.\n --\n -- OBJECT ipAddressAddrType\n -- SYNTAX InetAddressType {ipv4(1), ipv6(2),\n -- ipv4z(3), ipv6z(4)}\n -- DESCRIPTION\n -- This MIB requires support for only global and\n -- non-global IPv4 and IPv6 address types.\n --\n -- OBJECT ipAddressAddr\n -- SYNTAX InetAddress (Size(4 | 8 | 16 | 20))\n -- DESCRIPTION\n -- This MIB requires support for only global and\n\n\n -- non-global IPv4 and IPv6 addresses and so the size\n -- can be 4, 8, 16, or 20 bytes.\n --\n -- OBJECT ipNetToPhysicalNetAddressType\n -- SYNTAX InetAddressType {ipv4(1), ipv6(2),\n -- ipv4z(3), ipv6z(4)}\n -- DESCRIPTION\n -- This MIB requires support for only global and\n -- non-global IPv4 and IPv6 address types.\n --\n -- OBJECT ipNetToPhysicalNetAddress\n -- SYNTAX InetAddress (Size(4 | 8 | 16 | 20))\n -- DESCRIPTION\n -- This MIB requires support for only global and\n -- non-global IPv4 and IPv6 addresses and so the size\n -- can be 4, 8, 16, or 20 bytes.\n --\n -- OBJECT ipDefaultRouterAddressType\n -- SYNTAX InetAddressType {ipv4(1), ipv6(2),\n -- ipv4z(3), ipv6z(4)}\n -- DESCRIPTION\n -- This MIB requires support for only global and\n -- non-global IPv4 and IPv6 address types.\n --\n -- OBJECT ipDefaultRouterAddress\n -- SYNTAX InetAddress (Size(4 | 8 | 16 | 20))\n -- DESCRIPTION\n -- This MIB requires support for only global and\n -- non-global IPv4 and IPv6 addresses and so the size\n -- can be 4, 8, 16, or 20 bytes.')
ipv4GeneralGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 3)).setObjects(*(("IP-MIB", "ipForwarding"), ("IP-MIB", "ipDefaultTTL"), ("IP-MIB", "ipReasmTimeout"),))
if mibBuilder.loadTexts: ipv4GeneralGroup.setDescription('The group of IPv4-specific objects for basic management of\n IPv4 entities.')
ipv4IfGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 4)).setObjects(*(("IP-MIB", "ipv4InterfaceReasmMaxSize"), ("IP-MIB", "ipv4InterfaceEnableStatus"), ("IP-MIB", "ipv4InterfaceRetransmitTime"),))
if mibBuilder.loadTexts: ipv4IfGroup.setDescription('The group of IPv4-specific objects for basic management of\n IPv4 interfaces.')
ipv6GeneralGroup2 = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 5)).setObjects(*(("IP-MIB", "ipv6IpForwarding"), ("IP-MIB", "ipv6IpDefaultHopLimit"),))
if mibBuilder.loadTexts: ipv6GeneralGroup2.setDescription('The IPv6 group of objects providing for basic management of\n IPv6 entities.')
ipv6IfGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 6)).setObjects(*(("IP-MIB", "ipv6InterfaceReasmMaxSize"), ("IP-MIB", "ipv6InterfaceIdentifier"), ("IP-MIB", "ipv6InterfaceEnableStatus"), ("IP-MIB", "ipv6InterfaceReachableTime"), ("IP-MIB", "ipv6InterfaceRetransmitTime"), ("IP-MIB", "ipv6InterfaceForwarding"),))
if mibBuilder.loadTexts: ipv6IfGroup.setDescription('The group of IPv6-specific objects for basic management of\n IPv6 interfaces.')
ipLastChangeGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 7)).setObjects(*(("IP-MIB", "ipv4InterfaceTableLastChange"), ("IP-MIB", "ipv6InterfaceTableLastChange"), ("IP-MIB", "ipIfStatsTableLastChange"),))
if mibBuilder.loadTexts: ipLastChangeGroup.setDescription('The last change objects associated with this MIB. These\n objects are optional for all agents. They SHOULD be\n implemented on agents where it is possible to determine the\n proper values. Where it is not possible to determine the\n proper values, for example when the tables are split amongst\n several sub-agents using AgentX, the agent MUST NOT\n implement these objects to return an incorrect or static\n value.')
ipSystemStatsGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 8)).setObjects(*(("IP-MIB", "ipSystemStatsInReceives"), ("IP-MIB", "ipSystemStatsInOctets"), ("IP-MIB", "ipSystemStatsInHdrErrors"), ("IP-MIB", "ipSystemStatsInNoRoutes"), ("IP-MIB", "ipSystemStatsInAddrErrors"), ("IP-MIB", "ipSystemStatsInUnknownProtos"), ("IP-MIB", "ipSystemStatsInTruncatedPkts"), ("IP-MIB", "ipSystemStatsInForwDatagrams"), ("IP-MIB", "ipSystemStatsReasmReqds"), ("IP-MIB", "ipSystemStatsReasmOKs"), ("IP-MIB", "ipSystemStatsReasmFails"), ("IP-MIB", "ipSystemStatsInDiscards"), ("IP-MIB", "ipSystemStatsInDelivers"), ("IP-MIB", "ipSystemStatsOutRequests"), ("IP-MIB", "ipSystemStatsOutNoRoutes"), ("IP-MIB", "ipSystemStatsOutForwDatagrams"), ("IP-MIB", "ipSystemStatsOutDiscards"), ("IP-MIB", "ipSystemStatsOutFragReqds"), ("IP-MIB", "ipSystemStatsOutFragOKs"), ("IP-MIB", "ipSystemStatsOutFragFails"), ("IP-MIB", "ipSystemStatsOutFragCreates"), ("IP-MIB", "ipSystemStatsOutTransmits"), ("IP-MIB", "ipSystemStatsOutOctets"), ("IP-MIB", "ipSystemStatsInMcastPkts"), ("IP-MIB", "ipSystemStatsInMcastOctets"), ("IP-MIB", "ipSystemStatsOutMcastPkts"), ("IP-MIB", "ipSystemStatsOutMcastOctets"), ("IP-MIB", "ipSystemStatsDiscontinuityTime"), ("IP-MIB", "ipSystemStatsRefreshRate"),))
if mibBuilder.loadTexts: ipSystemStatsGroup.setDescription('IP system wide statistics.')
ipv4SystemStatsGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 9)).setObjects(*(("IP-MIB", "ipSystemStatsInBcastPkts"), ("IP-MIB", "ipSystemStatsOutBcastPkts"),))
if mibBuilder.loadTexts: ipv4SystemStatsGroup.setDescription('IPv4 only system wide statistics.')
ipSystemStatsHCOctetGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 10)).setObjects(*(("IP-MIB", "ipSystemStatsHCInOctets"), ("IP-MIB", "ipSystemStatsHCOutOctets"), ("IP-MIB", "ipSystemStatsHCInMcastOctets"), ("IP-MIB", "ipSystemStatsHCOutMcastOctets"),))
if mibBuilder.loadTexts: ipSystemStatsHCOctetGroup.setDescription('IP system wide statistics for systems that may overflow the\n standard octet counters within 1 hour.')
ipSystemStatsHCPacketGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 11)).setObjects(*(("IP-MIB", "ipSystemStatsHCInReceives"), ("IP-MIB", "ipSystemStatsHCInForwDatagrams"), ("IP-MIB", "ipSystemStatsHCInDelivers"), ("IP-MIB", "ipSystemStatsHCOutRequests"), ("IP-MIB", "ipSystemStatsHCOutForwDatagrams"), ("IP-MIB", "ipSystemStatsHCOutTransmits"), ("IP-MIB", "ipSystemStatsHCInMcastPkts"), ("IP-MIB", "ipSystemStatsHCOutMcastPkts"),))
if mibBuilder.loadTexts: ipSystemStatsHCPacketGroup.setDescription('IP system wide statistics for systems that may overflow the\n standard packet counters within 1 hour.')
ipv4SystemStatsHCPacketGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 12)).setObjects(*(("IP-MIB", "ipSystemStatsHCInBcastPkts"), ("IP-MIB", "ipSystemStatsHCOutBcastPkts"),))
if mibBuilder.loadTexts: ipv4SystemStatsHCPacketGroup.setDescription('IPv4 only system wide statistics for systems that may\n overflow the standard packet counters within 1 hour.')
ipIfStatsGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 13)).setObjects(*(("IP-MIB", "ipIfStatsInReceives"), ("IP-MIB", "ipIfStatsInOctets"), ("IP-MIB", "ipIfStatsInHdrErrors"), ("IP-MIB", "ipIfStatsInNoRoutes"), ("IP-MIB", "ipIfStatsInAddrErrors"), ("IP-MIB", "ipIfStatsInUnknownProtos"), ("IP-MIB", "ipIfStatsInTruncatedPkts"), ("IP-MIB", "ipIfStatsInForwDatagrams"), ("IP-MIB", "ipIfStatsReasmReqds"), ("IP-MIB", "ipIfStatsReasmOKs"), ("IP-MIB", "ipIfStatsReasmFails"), ("IP-MIB", "ipIfStatsInDiscards"), ("IP-MIB", "ipIfStatsInDelivers"), ("IP-MIB", "ipIfStatsOutRequests"), ("IP-MIB", "ipIfStatsOutForwDatagrams"), ("IP-MIB", "ipIfStatsOutDiscards"), ("IP-MIB", "ipIfStatsOutFragReqds"), ("IP-MIB", "ipIfStatsOutFragOKs"), ("IP-MIB", "ipIfStatsOutFragFails"), ("IP-MIB", "ipIfStatsOutFragCreates"), ("IP-MIB", "ipIfStatsOutTransmits"), ("IP-MIB", "ipIfStatsOutOctets"), ("IP-MIB", "ipIfStatsInMcastPkts"), ("IP-MIB", "ipIfStatsInMcastOctets"), ("IP-MIB", "ipIfStatsOutMcastPkts"), ("IP-MIB", "ipIfStatsOutMcastOctets"), ("IP-MIB", "ipIfStatsDiscontinuityTime"), ("IP-MIB", "ipIfStatsRefreshRate"),))
if mibBuilder.loadTexts: ipIfStatsGroup.setDescription('IP per-interface statistics.')
ipv4IfStatsGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 14)).setObjects(*(("IP-MIB", "ipIfStatsInBcastPkts"), ("IP-MIB", "ipIfStatsOutBcastPkts"),))
if mibBuilder.loadTexts: ipv4IfStatsGroup.setDescription('IPv4 only per-interface statistics.')
ipIfStatsHCOctetGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 15)).setObjects(*(("IP-MIB", "ipIfStatsHCInOctets"), ("IP-MIB", "ipIfStatsHCOutOctets"), ("IP-MIB", "ipIfStatsHCInMcastOctets"), ("IP-MIB", "ipIfStatsHCOutMcastOctets"),))
if mibBuilder.loadTexts: ipIfStatsHCOctetGroup.setDescription('IP per-interfaces statistics for systems that include\n interfaces that may overflow the standard octet\n counters within 1 hour.')
ipIfStatsHCPacketGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 16)).setObjects(*(("IP-MIB", "ipIfStatsHCInReceives"), ("IP-MIB", "ipIfStatsHCInForwDatagrams"), ("IP-MIB", "ipIfStatsHCInDelivers"), ("IP-MIB", "ipIfStatsHCOutRequests"), ("IP-MIB", "ipIfStatsHCOutForwDatagrams"), ("IP-MIB", "ipIfStatsHCOutTransmits"), ("IP-MIB", "ipIfStatsHCInMcastPkts"), ("IP-MIB", "ipIfStatsHCOutMcastPkts"),))
if mibBuilder.loadTexts: ipIfStatsHCPacketGroup.setDescription('IP per-interfaces statistics for systems that include\n interfaces that may overflow the standard packet counters\n within 1 hour.')
ipv4IfStatsHCPacketGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 17)).setObjects(*(("IP-MIB", "ipIfStatsHCInBcastPkts"), ("IP-MIB", "ipIfStatsHCOutBcastPkts"),))
if mibBuilder.loadTexts: ipv4IfStatsHCPacketGroup.setDescription('IPv4 only per-interface statistics for systems that include\n interfaces that may overflow the standard packet counters\n within 1 hour.')
ipAddressPrefixGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 18)).setObjects(*(("IP-MIB", "ipAddressPrefixOrigin"), ("IP-MIB", "ipAddressPrefixOnLinkFlag"), ("IP-MIB", "ipAddressPrefixAutonomousFlag"), ("IP-MIB", "ipAddressPrefixAdvPreferredLifetime"), ("IP-MIB", "ipAddressPrefixAdvValidLifetime"),))
if mibBuilder.loadTexts: ipAddressPrefixGroup.setDescription('The group of objects for providing information about address\n prefixes used by this node.')
ipAddressGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 19)).setObjects(*(("IP-MIB", "ipAddressSpinLock"), ("IP-MIB", "ipAddressIfIndex"), ("IP-MIB", "ipAddressType"), ("IP-MIB", "ipAddressPrefix"), ("IP-MIB", "ipAddressOrigin"), ("IP-MIB", "ipAddressStatus"), ("IP-MIB", "ipAddressCreated"), ("IP-MIB", "ipAddressLastChanged"), ("IP-MIB", "ipAddressRowStatus"), ("IP-MIB", "ipAddressStorageType"),))
if mibBuilder.loadTexts: ipAddressGroup.setDescription("The group of objects for providing information about the\n addresses relevant to this entity's interfaces.")
ipNetToPhysicalGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 20)).setObjects(*(("IP-MIB", "ipNetToPhysicalPhysAddress"), ("IP-MIB", "ipNetToPhysicalLastUpdated"), ("IP-MIB", "ipNetToPhysicalType"), ("IP-MIB", "ipNetToPhysicalState"), ("IP-MIB", "ipNetToPhysicalRowStatus"),))
if mibBuilder.loadTexts: ipNetToPhysicalGroup.setDescription('The group of objects for providing information about the\n mappings of network address to physical address known to\n this node.')
ipv6ScopeGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 21)).setObjects(*(("IP-MIB", "ipv6ScopeZoneIndexLinkLocal"), ("IP-MIB", "ipv6ScopeZoneIndex3"), ("IP-MIB", "ipv6ScopeZoneIndexAdminLocal"), ("IP-MIB", "ipv6ScopeZoneIndexSiteLocal"), ("IP-MIB", "ipv6ScopeZoneIndex6"), ("IP-MIB", "ipv6ScopeZoneIndex7"), ("IP-MIB", "ipv6ScopeZoneIndexOrganizationLocal"), ("IP-MIB", "ipv6ScopeZoneIndex9"), ("IP-MIB", "ipv6ScopeZoneIndexA"), ("IP-MIB", "ipv6ScopeZoneIndexB"), ("IP-MIB", "ipv6ScopeZoneIndexC"), ("IP-MIB", "ipv6ScopeZoneIndexD"),))
if mibBuilder.loadTexts: ipv6ScopeGroup.setDescription('The group of objects for managing IPv6 scope zones.')
ipDefaultRouterGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 22)).setObjects(*(("IP-MIB", "ipDefaultRouterLifetime"), ("IP-MIB", "ipDefaultRouterPreference"),))
if mibBuilder.loadTexts: ipDefaultRouterGroup.setDescription('The group of objects for providing information about default\n routers known to this node.')
ipv6RouterAdvertGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 23)).setObjects(*(("IP-MIB", "ipv6RouterAdvertSpinLock"), ("IP-MIB", "ipv6RouterAdvertSendAdverts"), ("IP-MIB", "ipv6RouterAdvertMaxInterval"), ("IP-MIB", "ipv6RouterAdvertMinInterval"), ("IP-MIB", "ipv6RouterAdvertManagedFlag"), ("IP-MIB", "ipv6RouterAdvertOtherConfigFlag"), ("IP-MIB", "ipv6RouterAdvertLinkMTU"), ("IP-MIB", "ipv6RouterAdvertReachableTime"), ("IP-MIB", "ipv6RouterAdvertRetransmitTime"), ("IP-MIB", "ipv6RouterAdvertCurHopLimit"), ("IP-MIB", "ipv6RouterAdvertDefaultLifetime"), ("IP-MIB", "ipv6RouterAdvertRowStatus"),))
if mibBuilder.loadTexts: ipv6RouterAdvertGroup.setDescription('The group of objects for controlling information advertised\n by IPv6 routers.')
icmpStatsGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 24)).setObjects(*(("IP-MIB", "icmpStatsInMsgs"), ("IP-MIB", "icmpStatsInErrors"), ("IP-MIB", "icmpStatsOutMsgs"), ("IP-MIB", "icmpStatsOutErrors"), ("IP-MIB", "icmpMsgStatsInPkts"), ("IP-MIB", "icmpMsgStatsOutPkts"),))
if mibBuilder.loadTexts: icmpStatsGroup.setDescription('The group of objects providing ICMP statistics.')
ipInReceives = MibScalar((1, 3, 6, 1, 2, 1, 4, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInReceives.setDescription('The total number of input datagrams received from\n interfaces, including those received in error.\n\n This object has been deprecated, as a new IP version-neutral\n\n\n table has been added. It is loosely replaced by\n ipSystemStatsInRecieves.')
ipInHdrErrors = MibScalar((1, 3, 6, 1, 2, 1, 4, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInHdrErrors.setDescription('The number of input datagrams discarded due to errors in\n their IPv4 headers, including bad checksums, version number\n mismatch, other format errors, time-to-live exceeded, errors\n discovered in processing their IPv4 options, etc.\n\n This object has been deprecated as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsInHdrErrors.')
ipInAddrErrors = MibScalar((1, 3, 6, 1, 2, 1, 4, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInAddrErrors.setDescription("The number of input datagrams discarded because the IPv4\n address in their IPv4 header's destination field was not a\n valid address to be received at this entity. This count\n includes invalid addresses (e.g., 0.0.0.0) and addresses of\n unsupported Classes (e.g., Class E). For entities which are\n not IPv4 routers, and therefore do not forward datagrams,\n this counter includes datagrams discarded because the\n destination address was not a local address.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsInAddrErrors.")
ipForwDatagrams = MibScalar((1, 3, 6, 1, 2, 1, 4, 6), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipForwDatagrams.setDescription('The number of input datagrams for which this entity was not\n their final IPv4 destination, as a result of which an\n attempt was made to find a route to forward them to that\n final destination. In entities which do not act as IPv4\n routers, this counter will include only those packets which\n\n\n were Source-Routed via this entity, and the Source-Route\n option processing was successful.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsInForwDatagrams.')
ipInUnknownProtos = MibScalar((1, 3, 6, 1, 2, 1, 4, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInUnknownProtos.setDescription('The number of locally-addressed datagrams received\n successfully but discarded because of an unknown or\n unsupported protocol.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsInUnknownProtos.')
ipInDiscards = MibScalar((1, 3, 6, 1, 2, 1, 4, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInDiscards.setDescription('The number of input IPv4 datagrams for which no problems\n were encountered to prevent their continued processing, but\n which were discarded (e.g., for lack of buffer space). Note\n that this counter does not include any datagrams discarded\n while awaiting re-assembly.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsInDiscards.')
ipInDelivers = MibScalar((1, 3, 6, 1, 2, 1, 4, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipInDelivers.setDescription('The total number of input datagrams successfully delivered\n to IPv4 user-protocols (including ICMP).\n\n This object has been deprecated as a new IP version neutral\n table has been added. It is loosely replaced by\n\n\n ipSystemStatsIndelivers.')
ipOutRequests = MibScalar((1, 3, 6, 1, 2, 1, 4, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipOutRequests.setDescription('The total number of IPv4 datagrams which local IPv4 user\n protocols (including ICMP) supplied to IPv4 in requests for\n transmission. Note that this counter does not include any\n datagrams counted in ipForwDatagrams.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsOutRequests.')
ipOutDiscards = MibScalar((1, 3, 6, 1, 2, 1, 4, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipOutDiscards.setDescription('The number of output IPv4 datagrams for which no problem was\n encountered to prevent their transmission to their\n destination, but which were discarded (e.g., for lack of\n buffer space). Note that this counter would include\n datagrams counted in ipForwDatagrams if any such packets met\n this (discretionary) discard criterion.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsOutDiscards.')
ipOutNoRoutes = MibScalar((1, 3, 6, 1, 2, 1, 4, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipOutNoRoutes.setDescription("The number of IPv4 datagrams discarded because no route\n could be found to transmit them to their destination. Note\n that this counter includes any packets counted in\n ipForwDatagrams which meet this `no-route' criterion. Note\n that this includes any datagrams which a host cannot route\n because all of its default routers are down.\n\n This object has been deprecated, as a new IP version-neutral\n\n\n table has been added. It is loosely replaced by\n ipSystemStatsOutNoRoutes.")
ipReasmReqds = MibScalar((1, 3, 6, 1, 2, 1, 4, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipReasmReqds.setDescription('The number of IPv4 fragments received which needed to be\n reassembled at this entity.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsReasmReqds.')
ipReasmOKs = MibScalar((1, 3, 6, 1, 2, 1, 4, 15), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipReasmOKs.setDescription('The number of IPv4 datagrams successfully re-assembled.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsReasmOKs.')
ipReasmFails = MibScalar((1, 3, 6, 1, 2, 1, 4, 16), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipReasmFails.setDescription('The number of failures detected by the IPv4 re-assembly\n algorithm (for whatever reason: timed out, errors, etc).\n Note that this is not necessarily a count of discarded IPv4\n fragments since some algorithms (notably the algorithm in\n RFC 815) can lose track of the number of fragments by\n combining them as they are received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsReasmFails.')
ipFragOKs = MibScalar((1, 3, 6, 1, 2, 1, 4, 17), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipFragOKs.setDescription('The number of IPv4 datagrams that have been successfully\n fragmented at this entity.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsOutFragOKs.')
ipFragFails = MibScalar((1, 3, 6, 1, 2, 1, 4, 18), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipFragFails.setDescription("The number of IPv4 datagrams that have been discarded\n because they needed to be fragmented at this entity but\n could not be, e.g., because their Don't Fragment flag was\n set.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n ipSystemStatsOutFragFails.")
ipFragCreates = MibScalar((1, 3, 6, 1, 2, 1, 4, 19), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipFragCreates.setDescription('The number of IPv4 datagram fragments that have been\n generated as a result of fragmentation at this entity.\n\n This object has been deprecated as a new IP version neutral\n table has been added. It is loosely replaced by\n ipSystemStatsOutFragCreates.')
ipRoutingDiscards = MibScalar((1, 3, 6, 1, 2, 1, 4, 23), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipRoutingDiscards.setDescription('The number of routing entries which were chosen to be\n discarded even though they are valid. One possible reason\n for discarding such an entry could be to free-up buffer\n space for other routing entries.\n\n\n This object was defined in pre-IPv6 versions of the IP MIB.\n It was implicitly IPv4 only, but the original specifications\n did not indicate this protocol restriction. In order to\n clarify the specifications, this object has been deprecated\n and a similar, but more thoroughly clarified, object has\n been added to the IP-FORWARD-MIB.')
ipAddrTable = MibTable((1, 3, 6, 1, 2, 1, 4, 20), )
if mibBuilder.loadTexts: ipAddrTable.setDescription("The table of addressing information relevant to this\n entity's IPv4 addresses.\n\n This table has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by the\n ipAddressTable although several objects that weren't deemed\n useful weren't carried forward while another\n (ipAdEntReasmMaxSize) was moved to the ipv4InterfaceTable.")
ipAddrEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 20, 1), ).setIndexNames((0, "IP-MIB", "ipAdEntAddr"))
if mibBuilder.loadTexts: ipAddrEntry.setDescription("The addressing information for one of this entity's IPv4\n addresses.")
ipAdEntAddr = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 20, 1, 1), IpAddress()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAdEntAddr.setDescription("The IPv4 address to which this entry's addressing\n information pertains.")
ipAdEntIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 20, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1,2147483647))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAdEntIfIndex.setDescription("The index value which uniquely identifies the interface to\n which this entry is applicable. The interface identified by\n a particular value of this index is the same interface as\n identified by the same value of the IF-MIB's ifIndex.")
ipAdEntNetMask = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 20, 1, 3), IpAddress()).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAdEntNetMask.setDescription('The subnet mask associated with the IPv4 address of this\n entry. The value of the mask is an IPv4 address with all\n the network bits set to 1 and all the hosts bits set to 0.')
ipAdEntBcastAddr = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 20, 1, 4), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0,1))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAdEntBcastAddr.setDescription('The value of the least-significant bit in the IPv4 broadcast\n address used for sending datagrams on the (logical)\n interface associated with the IPv4 address of this entry.\n For example, when the Internet standard all-ones broadcast\n address is used, the value will be 1. This value applies to\n both the subnet and network broadcast addresses used by the\n entity on this (logical) interface.')
ipAdEntReasmMaxSize = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 20, 1, 5), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0,65535))).setMaxAccess("readonly")
if mibBuilder.loadTexts: ipAdEntReasmMaxSize.setDescription('The size of the largest IPv4 datagram which this entity can\n re-assemble from incoming IPv4 fragmented datagrams received\n on this interface.')
ipNetToMediaTable = MibTable((1, 3, 6, 1, 2, 1, 4, 22), )
if mibBuilder.loadTexts: ipNetToMediaTable.setDescription('The IPv4 Address Translation table used for mapping from\n IPv4 addresses to physical addresses.\n\n This table has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by the\n ipNetToPhysicalTable.')
ipNetToMediaEntry = MibTableRow((1, 3, 6, 1, 2, 1, 4, 22, 1), ).setIndexNames((0, "IP-MIB", "ipNetToMediaIfIndex"), (0, "IP-MIB", "ipNetToMediaNetAddress"))
if mibBuilder.loadTexts: ipNetToMediaEntry.setDescription("Each entry contains one IpAddress to `physical' address\n equivalence.")
ipNetToMediaIfIndex = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 22, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1,2147483647))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToMediaIfIndex.setDescription("The interface on which this entry's equivalence is\n effective. The interface identified by a particular value\n of this index is the same interface as identified by the\n\n\n same value of the IF-MIB's ifIndex.\n\n This object predates the rule limiting index objects to a\n max access value of 'not-accessible' and so continues to use\n a value of 'read-create'.")
ipNetToMediaPhysAddress = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 22, 1, 2), PhysAddress().subtype(subtypeSpec=ValueSizeConstraint(0,65535))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToMediaPhysAddress.setDescription("The media-dependent `physical' address. This object should\n return 0 when this entry is in the 'incomplete' state.\n\n As the entries in this table are typically not persistent\n when this object is written the entity should not save the\n change to non-volatile storage. Note: a stronger\n requirement is not used because this object was previously\n defined.")
ipNetToMediaNetAddress = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 22, 1, 3), IpAddress()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToMediaNetAddress.setDescription("The IpAddress corresponding to the media-dependent\n `physical' address.\n\n This object predates the rule limiting index objects to a\n max access value of 'not-accessible' and so continues to use\n a value of 'read-create'.")
ipNetToMediaType = MibTableColumn((1, 3, 6, 1, 2, 1, 4, 22, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4,))).clone(namedValues=NamedValues(("other", 1), ("invalid", 2), ("dynamic", 3), ("static", 4),))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: ipNetToMediaType.setDescription('The type of mapping.\n\n Setting this object to the value invalid(2) has the effect\n\n\n of invalidating the corresponding entry in the\n ipNetToMediaTable. That is, it effectively dis-associates\n the interface identified with said entry from the mapping\n identified with said entry. It is an implementation-\n specific matter as to whether the agent removes an\n invalidated entry from the table. Accordingly, management\n stations must be prepared to receive tabular information\n from agents that corresponds to entries not currently in\n use. Proper interpretation of such entries requires\n examination of the relevant ipNetToMediaType object.\n\n As the entries in this table are typically not persistent\n when this object is written the entity should not save the\n change to non-volatile storage. Note: a stronger\n requirement is not used because this object was previously\n defined.')
icmpInMsgs = MibScalar((1, 3, 6, 1, 2, 1, 5, 1), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInMsgs.setDescription('The total number of ICMP messages which the entity received.\n Note that this counter includes all those counted by\n icmpInErrors.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n icmpStatsInMsgs.')
icmpInErrors = MibScalar((1, 3, 6, 1, 2, 1, 5, 2), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInErrors.setDescription('The number of ICMP messages which the entity received but\n determined as having ICMP-specific errors (bad ICMP\n checksums, bad length, etc.).\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n icmpStatsInErrors.')
icmpInDestUnreachs = MibScalar((1, 3, 6, 1, 2, 1, 5, 3), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInDestUnreachs.setDescription('The number of ICMP Destination Unreachable messages\n received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInTimeExcds = MibScalar((1, 3, 6, 1, 2, 1, 5, 4), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInTimeExcds.setDescription('The number of ICMP Time Exceeded messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInParmProbs = MibScalar((1, 3, 6, 1, 2, 1, 5, 5), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInParmProbs.setDescription('The number of ICMP Parameter Problem messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInSrcQuenchs = MibScalar((1, 3, 6, 1, 2, 1, 5, 6), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInSrcQuenchs.setDescription('The number of ICMP Source Quench messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInRedirects = MibScalar((1, 3, 6, 1, 2, 1, 5, 7), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInRedirects.setDescription('The number of ICMP Redirect messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInEchos = MibScalar((1, 3, 6, 1, 2, 1, 5, 8), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInEchos.setDescription('The number of ICMP Echo (request) messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInEchoReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 9), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInEchoReps.setDescription('The number of ICMP Echo Reply messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInTimestamps = MibScalar((1, 3, 6, 1, 2, 1, 5, 10), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInTimestamps.setDescription('The number of ICMP Timestamp (request) messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInTimestampReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 11), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInTimestampReps.setDescription('The number of ICMP Timestamp Reply messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInAddrMasks = MibScalar((1, 3, 6, 1, 2, 1, 5, 12), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInAddrMasks.setDescription('The number of ICMP Address Mask Request messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpInAddrMaskReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 13), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpInAddrMaskReps.setDescription('The number of ICMP Address Mask Reply messages received.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutMsgs = MibScalar((1, 3, 6, 1, 2, 1, 5, 14), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutMsgs.setDescription('The total number of ICMP messages which this entity\n attempted to send. Note that this counter includes all\n those counted by icmpOutErrors.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n icmpStatsOutMsgs.')
icmpOutErrors = MibScalar((1, 3, 6, 1, 2, 1, 5, 15), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutErrors.setDescription("The number of ICMP messages which this entity did not send\n due to problems discovered within ICMP, such as a lack of\n buffers. This value should not include errors discovered\n outside the ICMP layer, such as the inability of IP to route\n the resultant datagram. In some implementations, there may\n be no types of error which contribute to this counter's\n value.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by\n icmpStatsOutErrors.")
icmpOutDestUnreachs = MibScalar((1, 3, 6, 1, 2, 1, 5, 16), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutDestUnreachs.setDescription('The number of ICMP Destination Unreachable messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutTimeExcds = MibScalar((1, 3, 6, 1, 2, 1, 5, 17), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutTimeExcds.setDescription('The number of ICMP Time Exceeded messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutParmProbs = MibScalar((1, 3, 6, 1, 2, 1, 5, 18), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutParmProbs.setDescription('The number of ICMP Parameter Problem messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutSrcQuenchs = MibScalar((1, 3, 6, 1, 2, 1, 5, 19), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutSrcQuenchs.setDescription('The number of ICMP Source Quench messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutRedirects = MibScalar((1, 3, 6, 1, 2, 1, 5, 20), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutRedirects.setDescription('The number of ICMP Redirect messages sent. For a host, this\n object will always be zero, since hosts do not send\n redirects.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutEchos = MibScalar((1, 3, 6, 1, 2, 1, 5, 21), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutEchos.setDescription('The number of ICMP Echo (request) messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutEchoReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 22), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutEchoReps.setDescription('The number of ICMP Echo Reply messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutTimestamps = MibScalar((1, 3, 6, 1, 2, 1, 5, 23), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutTimestamps.setDescription('The number of ICMP Timestamp (request) messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutTimestampReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 24), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutTimestampReps.setDescription('The number of ICMP Timestamp Reply messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutAddrMasks = MibScalar((1, 3, 6, 1, 2, 1, 5, 25), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutAddrMasks.setDescription('The number of ICMP Address Mask Request messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
icmpOutAddrMaskReps = MibScalar((1, 3, 6, 1, 2, 1, 5, 26), Counter32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: icmpOutAddrMaskReps.setDescription('The number of ICMP Address Mask Reply messages sent.\n\n This object has been deprecated, as a new IP version-neutral\n table has been added. It is loosely replaced by a column in\n the icmpMsgStatsTable.')
ipMIBCompliance = ModuleCompliance((1, 3, 6, 1, 2, 1, 48, 2, 1, 1)).setObjects(*(("IP-MIB", "ipGroup"), ("IP-MIB", "icmpGroup"),))
if mibBuilder.loadTexts: ipMIBCompliance.setDescription('The compliance statement for systems that implement only\n IPv4. For version-independence, this compliance statement\n is deprecated in favor of ipMIBCompliance2.')
ipGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 1)).setObjects(*(("IP-MIB", "ipForwarding"), ("IP-MIB", "ipDefaultTTL"), ("IP-MIB", "ipInReceives"), ("IP-MIB", "ipInHdrErrors"), ("IP-MIB", "ipInAddrErrors"), ("IP-MIB", "ipForwDatagrams"), ("IP-MIB", "ipInUnknownProtos"), ("IP-MIB", "ipInDiscards"), ("IP-MIB", "ipInDelivers"), ("IP-MIB", "ipOutRequests"), ("IP-MIB", "ipOutDiscards"), ("IP-MIB", "ipOutNoRoutes"), ("IP-MIB", "ipReasmTimeout"), ("IP-MIB", "ipReasmReqds"), ("IP-MIB", "ipReasmOKs"), ("IP-MIB", "ipReasmFails"), ("IP-MIB", "ipFragOKs"), ("IP-MIB", "ipFragFails"), ("IP-MIB", "ipFragCreates"), ("IP-MIB", "ipAdEntAddr"), ("IP-MIB", "ipAdEntIfIndex"), ("IP-MIB", "ipAdEntNetMask"), ("IP-MIB", "ipAdEntBcastAddr"), ("IP-MIB", "ipAdEntReasmMaxSize"), ("IP-MIB", "ipNetToMediaIfIndex"), ("IP-MIB", "ipNetToMediaPhysAddress"), ("IP-MIB", "ipNetToMediaNetAddress"), ("IP-MIB", "ipNetToMediaType"), ("IP-MIB", "ipRoutingDiscards"),))
if mibBuilder.loadTexts: ipGroup.setDescription('The ip group of objects providing for basic management of IP\n entities, exclusive of the management of IP routes.\n\n\n As part of the version independence, this group has been\n deprecated. ')
icmpGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 48, 2, 2, 2)).setObjects(*(("IP-MIB", "icmpInMsgs"), ("IP-MIB", "icmpInErrors"), ("IP-MIB", "icmpInDestUnreachs"), ("IP-MIB", "icmpInTimeExcds"), ("IP-MIB", "icmpInParmProbs"), ("IP-MIB", "icmpInSrcQuenchs"), ("IP-MIB", "icmpInRedirects"), ("IP-MIB", "icmpInEchos"), ("IP-MIB", "icmpInEchoReps"), ("IP-MIB", "icmpInTimestamps"), ("IP-MIB", "icmpInTimestampReps"), ("IP-MIB", "icmpInAddrMasks"), ("IP-MIB", "icmpInAddrMaskReps"), ("IP-MIB", "icmpOutMsgs"), ("IP-MIB", "icmpOutErrors"), ("IP-MIB", "icmpOutDestUnreachs"), ("IP-MIB", "icmpOutTimeExcds"), ("IP-MIB", "icmpOutParmProbs"), ("IP-MIB", "icmpOutSrcQuenchs"), ("IP-MIB", "icmpOutRedirects"), ("IP-MIB", "icmpOutEchos"), ("IP-MIB", "icmpOutEchoReps"), ("IP-MIB", "icmpOutTimestamps"), ("IP-MIB", "icmpOutTimestampReps"), ("IP-MIB", "icmpOutAddrMasks"), ("IP-MIB", "icmpOutAddrMaskReps"),))
if mibBuilder.loadTexts: icmpGroup.setDescription('The icmp group of objects providing ICMP statistics.\n\n As part of the version independence, this group has been\n deprecated. ')
mibBuilder.exportSymbols("IP-MIB", icmpInTimestampReps=icmpInTimestampReps, ipIfStatsHCInDelivers=ipIfStatsHCInDelivers, ipNetToPhysicalLastUpdated=ipNetToPhysicalLastUpdated, icmpStatsOutMsgs=icmpStatsOutMsgs, ipv6ScopeGroup=ipv6ScopeGroup, ipMIBGroups=ipMIBGroups, ipSystemStatsInForwDatagrams=ipSystemStatsInForwDatagrams, ipSystemStatsOutOctets=ipSystemStatsOutOctets, ipv4IfGroup=ipv4IfGroup, ipv6ScopeZoneIndexEntry=ipv6ScopeZoneIndexEntry, ipAdEntReasmMaxSize=ipAdEntReasmMaxSize, ipSystemStatsInReceives=ipSystemStatsInReceives, ipAddressGroup=ipAddressGroup, ipIfStatsInDelivers=ipIfStatsInDelivers, ipIfStatsHCOutBcastPkts=ipIfStatsHCOutBcastPkts, ipSystemStatsGroup=ipSystemStatsGroup, ipIfStatsInTruncatedPkts=ipIfStatsInTruncatedPkts, ipIfStatsInMcastPkts=ipIfStatsInMcastPkts, ipSystemStatsInMcastPkts=ipSystemStatsInMcastPkts, ipv4IfStatsGroup=ipv4IfStatsGroup, ipTrafficStats=ipTrafficStats, ipIfStatsOutMcastOctets=ipIfStatsOutMcastOctets, ipAdEntBcastAddr=ipAdEntBcastAddr, ipAddressCreated=ipAddressCreated, IpAddressPrefixOriginTC=IpAddressPrefixOriginTC, ipSystemStatsHCOutTransmits=ipSystemStatsHCOutTransmits, ipAddressRowStatus=ipAddressRowStatus, icmp=icmp, ipInReceives=ipInReceives, ipAdEntNetMask=ipAdEntNetMask, ipv4SystemStatsGroup=ipv4SystemStatsGroup, ipInAddrErrors=ipInAddrErrors, ipIfStatsInBcastPkts=ipIfStatsInBcastPkts, ipIfStatsInReceives=ipIfStatsInReceives, ipSystemStatsReasmReqds=ipSystemStatsReasmReqds, ipIfStatsHCOutOctets=ipIfStatsHCOutOctets, ipAddressPrefixPrefix=ipAddressPrefixPrefix, icmpMsgStatsOutPkts=icmpMsgStatsOutPkts, ipIfStatsInAddrErrors=ipIfStatsInAddrErrors, ipIfStatsOutFragReqds=ipIfStatsOutFragReqds, ipv4GeneralGroup=ipv4GeneralGroup, ipReasmTimeout=ipReasmTimeout, ipIfStatsReasmReqds=ipIfStatsReasmReqds, ipIfStatsReasmOKs=ipIfStatsReasmOKs, ipv6RouterAdvertSpinLock=ipv6RouterAdvertSpinLock, ipSystemStatsOutBcastPkts=ipSystemStatsOutBcastPkts, ipv4IfStatsHCPacketGroup=ipv4IfStatsHCPacketGroup, ipSystemStatsInAddrErrors=ipSystemStatsInAddrErrors, ipIfStatsOutForwDatagrams=ipIfStatsOutForwDatagrams, ipRoutingDiscards=ipRoutingDiscards, ipv6ScopeZoneIndexTable=ipv6ScopeZoneIndexTable, ipAdEntIfIndex=ipAdEntIfIndex, ipv6ScopeZoneIndexOrganizationLocal=ipv6ScopeZoneIndexOrganizationLocal, ipNetToPhysicalIfIndex=ipNetToPhysicalIfIndex, ipv6RouterAdvertRetransmitTime=ipv6RouterAdvertRetransmitTime, ipIfStatsInForwDatagrams=ipIfStatsInForwDatagrams, icmpOutErrors=icmpOutErrors, icmpOutSrcQuenchs=icmpOutSrcQuenchs, ipNetToPhysicalNetAddressType=ipNetToPhysicalNetAddressType, ipSystemStatsHCPacketGroup=ipSystemStatsHCPacketGroup, ipAddressPrefixEntry=ipAddressPrefixEntry, ipInDiscards=ipInDiscards, ipDefaultRouterAddressType=ipDefaultRouterAddressType, ipv6ScopeZoneIndexSiteLocal=ipv6ScopeZoneIndexSiteLocal, ipIfStatsInNoRoutes=ipIfStatsInNoRoutes, ipv6RouterAdvertGroup=ipv6RouterAdvertGroup, ipSystemStatsDiscontinuityTime=ipSystemStatsDiscontinuityTime, ipGroup=ipGroup, ipv6ScopeZoneIndex6=ipv6ScopeZoneIndex6, ipIfStatsHCInForwDatagrams=ipIfStatsHCInForwDatagrams, ipAddressPrefixAdvPreferredLifetime=ipAddressPrefixAdvPreferredLifetime, ipDefaultRouterGroup=ipDefaultRouterGroup, ipReasmFails=ipReasmFails, ip=ip, ipv6InterfaceTableLastChange=ipv6InterfaceTableLastChange, ipIfStatsHCOutMcastPkts=ipIfStatsHCOutMcastPkts, ipOutDiscards=ipOutDiscards, ipSystemStatsHCOutBcastPkts=ipSystemStatsHCOutBcastPkts, ipv6RouterAdvertReachableTime=ipv6RouterAdvertReachableTime, icmpInSrcQuenchs=icmpInSrcQuenchs, icmpOutAddrMaskReps=icmpOutAddrMaskReps, ipSystemStatsHCInBcastPkts=ipSystemStatsHCInBcastPkts, ipMIBCompliance=ipMIBCompliance, ipv6ScopeZoneIndexC=ipv6ScopeZoneIndexC, ipDefaultRouterIfIndex=ipDefaultRouterIfIndex, ipDefaultTTL=ipDefaultTTL, ipv6IpForwarding=ipv6IpForwarding, ipAddressType=ipAddressType, icmpMsgStatsInPkts=icmpMsgStatsInPkts, ipSystemStatsRefreshRate=ipSystemStatsRefreshRate, ipAddressPrefixLength=ipAddressPrefixLength, icmpOutDestUnreachs=icmpOutDestUnreachs, icmpStatsInErrors=icmpStatsInErrors, ipInDelivers=ipInDelivers, ipv4InterfaceTableLastChange=ipv4InterfaceTableLastChange, ipIfStatsHCInMcastOctets=ipIfStatsHCInMcastOctets, ipSystemStatsOutForwDatagrams=ipSystemStatsOutForwDatagrams, ipv4SystemStatsHCPacketGroup=ipv4SystemStatsHCPacketGroup, ipv6RouterAdvertRowStatus=ipv6RouterAdvertRowStatus, ipOutNoRoutes=ipOutNoRoutes, ipAddressPrefixTable=ipAddressPrefixTable, ipv6ScopeZoneIndexLinkLocal=ipv6ScopeZoneIndexLinkLocal, ipIfStatsGroup=ipIfStatsGroup, ipSystemStatsInDiscards=ipSystemStatsInDiscards, ipv6InterfaceEnableStatus=ipv6InterfaceEnableStatus, ipIfStatsHCInReceives=ipIfStatsHCInReceives, ipv6InterfaceEntry=ipv6InterfaceEntry, ipIfStatsEntry=ipIfStatsEntry, icmpStatsGroup=icmpStatsGroup, ipv6InterfaceRetransmitTime=ipv6InterfaceRetransmitTime, ipNetToPhysicalPhysAddress=ipNetToPhysicalPhysAddress, ipIfStatsOutFragFails=ipIfStatsOutFragFails, ipv6RouterAdvertLinkMTU=ipv6RouterAdvertLinkMTU, ipSystemStatsHCOutMcastOctets=ipSystemStatsHCOutMcastOctets, ipSystemStatsHCInMcastPkts=ipSystemStatsHCInMcastPkts, icmpInMsgs=icmpInMsgs, icmpOutAddrMasks=icmpOutAddrMasks, ipDefaultRouterPreference=ipDefaultRouterPreference, icmpInEchos=icmpInEchos, ipv6IpDefaultHopLimit=ipv6IpDefaultHopLimit, icmpInAddrMasks=icmpInAddrMasks, ipDefaultRouterTable=ipDefaultRouterTable, ipv6InterfaceTable=ipv6InterfaceTable, ipv6ScopeZoneIndexD=ipv6ScopeZoneIndexD, ipSystemStatsInNoRoutes=ipSystemStatsInNoRoutes, ipAddressPrefixType=ipAddressPrefixType, ipSystemStatsInDelivers=ipSystemStatsInDelivers, ipSystemStatsHCInOctets=ipSystemStatsHCInOctets, ipSystemStatsInTruncatedPkts=ipSystemStatsInTruncatedPkts, ipIfStatsTable=ipIfStatsTable, ipIfStatsHCInMcastPkts=ipIfStatsHCInMcastPkts, ipv6ScopeZoneIndex7=ipv6ScopeZoneIndex7, Ipv6AddressIfIdentifierTC=Ipv6AddressIfIdentifierTC, icmpOutTimestampReps=icmpOutTimestampReps, ipv4InterfaceTable=ipv4InterfaceTable, icmpInParmProbs=icmpInParmProbs, ipIfStatsHCInBcastPkts=ipIfStatsHCInBcastPkts, icmpInDestUnreachs=icmpInDestUnreachs, ipNetToPhysicalRowStatus=ipNetToPhysicalRowStatus, ipNetToMediaTable=ipNetToMediaTable, ipAddressTable=ipAddressTable, ipv4InterfaceEntry=ipv4InterfaceEntry, ipIfStatsHCInOctets=ipIfStatsHCInOctets, icmpOutRedirects=icmpOutRedirects, ipv6RouterAdvertMinInterval=ipv6RouterAdvertMinInterval, ipv6ScopeZoneIndexA=ipv6ScopeZoneIndexA, ipSystemStatsInHdrErrors=ipSystemStatsInHdrErrors, ipReasmOKs=ipReasmOKs, icmpGroup=icmpGroup, ipSystemStatsInMcastOctets=ipSystemStatsInMcastOctets, ipIfStatsOutRequests=ipIfStatsOutRequests, ipAddressPrefix=ipAddressPrefix, ipIfStatsOutMcastPkts=ipIfStatsOutMcastPkts, ipNetToPhysicalState=ipNetToPhysicalState, ipMIBCompliances=ipMIBCompliances, icmpInTimestamps=icmpInTimestamps, ipIfStatsIfIndex=ipIfStatsIfIndex, icmpOutMsgs=icmpOutMsgs, ipFragFails=ipFragFails, ipAddressStorageType=ipAddressStorageType, ipMIBConformance=ipMIBConformance, icmpOutParmProbs=icmpOutParmProbs, icmpMsgStatsTable=icmpMsgStatsTable, ipAddressEntry=ipAddressEntry, ipInHdrErrors=ipInHdrErrors, ipAddressStatus=ipAddressStatus, ipNetToPhysicalGroup=ipNetToPhysicalGroup, ipv6InterfaceIdentifier=ipv6InterfaceIdentifier, ipIfStatsHCOutForwDatagrams=ipIfStatsHCOutForwDatagrams, ipDefaultRouterEntry=ipDefaultRouterEntry, icmpInTimeExcds=icmpInTimeExcds, ipIfStatsRefreshRate=ipIfStatsRefreshRate, ipSystemStatsHCInForwDatagrams=ipSystemStatsHCInForwDatagrams, ipv4InterfaceIfIndex=ipv4InterfaceIfIndex, ipNetToMediaPhysAddress=ipNetToMediaPhysAddress, ipIfStatsInOctets=ipIfStatsInOctets, ipv6ScopeZoneIndex9=ipv6ScopeZoneIndex9, ipv6ScopeZoneIndexIfIndex=ipv6ScopeZoneIndexIfIndex, ipv6RouterAdvertOtherConfigFlag=ipv6RouterAdvertOtherConfigFlag, ipv6RouterAdvertCurHopLimit=ipv6RouterAdvertCurHopLimit, icmpStatsTable=icmpStatsTable, icmpStatsOutErrors=icmpStatsOutErrors, ipLastChangeGroup=ipLastChangeGroup, icmpOutEchos=icmpOutEchos, ipIfStatsIPVersion=ipIfStatsIPVersion, ipDefaultRouterAddress=ipDefaultRouterAddress, ipAddrTable=ipAddrTable, ipSystemStatsOutFragOKs=ipSystemStatsOutFragOKs, ipDefaultRouterLifetime=ipDefaultRouterLifetime, ipNetToMediaEntry=ipNetToMediaEntry, ipIfStatsOutBcastPkts=ipIfStatsOutBcastPkts, ipSystemStatsOutMcastOctets=ipSystemStatsOutMcastOctets, IpAddressOriginTC=IpAddressOriginTC, ipIfStatsInUnknownProtos=ipIfStatsInUnknownProtos, icmpMsgStatsType=icmpMsgStatsType, icmpOutEchoReps=icmpOutEchoReps, ipAddrEntry=ipAddrEntry, ipAddressLastChanged=ipAddressLastChanged, ipAddressAddrType=ipAddressAddrType, ipIfStatsHCOutMcastOctets=ipIfStatsHCOutMcastOctets, ipIfStatsHCPacketGroup=ipIfStatsHCPacketGroup, ipSystemStatsHCInDelivers=ipSystemStatsHCInDelivers, ipv6InterfaceIfIndex=ipv6InterfaceIfIndex, ipIfStatsTableLastChange=ipIfStatsTableLastChange, ipIfStatsInHdrErrors=ipIfStatsInHdrErrors, ipAddressPrefixIfIndex=ipAddressPrefixIfIndex, icmpStatsEntry=icmpStatsEntry, ipAddressPrefixAutonomousFlag=ipAddressPrefixAutonomousFlag, ipForwarding=ipForwarding, ipSystemStatsOutMcastPkts=ipSystemStatsOutMcastPkts, ipSystemStatsInBcastPkts=ipSystemStatsInBcastPkts, ipv6InterfaceForwarding=ipv6InterfaceForwarding, ipMIB=ipMIB, ipSystemStatsHCInMcastOctets=ipSystemStatsHCInMcastOctets, ipSystemStatsOutNoRoutes=ipSystemStatsOutNoRoutes, ipIfStatsHCOutRequests=ipIfStatsHCOutRequests, icmpStatsInMsgs=icmpStatsInMsgs, ipSystemStatsOutFragFails=ipSystemStatsOutFragFails, ipIfStatsOutFragOKs=ipIfStatsOutFragOKs, ipReasmReqds=ipReasmReqds, ipSystemStatsOutFragReqds=ipSystemStatsOutFragReqds, icmpOutTimeExcds=icmpOutTimeExcds, ipv6ScopeZoneIndex3=ipv6ScopeZoneIndex3, ipIfStatsOutOctets=ipIfStatsOutOctets, ipNetToPhysicalNetAddress=ipNetToPhysicalNetAddress, ipv6ScopeZoneIndexAdminLocal=ipv6ScopeZoneIndexAdminLocal, ipv4InterfaceRetransmitTime=ipv4InterfaceRetransmitTime, ipSystemStatsOutRequests=ipSystemStatsOutRequests, ipSystemStatsEntry=ipSystemStatsEntry, ipSystemStatsIPVersion=ipSystemStatsIPVersion, ipSystemStatsHCOutRequests=ipSystemStatsHCOutRequests, ipAddressOrigin=ipAddressOrigin, ipNetToPhysicalType=ipNetToPhysicalType, ipv6IfGroup=ipv6IfGroup, ipFragOKs=ipFragOKs, icmpInEchoReps=icmpInEchoReps, ipIfStatsHCOctetGroup=ipIfStatsHCOctetGroup, ipAddressSpinLock=ipAddressSpinLock, icmpInAddrMaskReps=icmpInAddrMaskReps, ipv6RouterAdvertIfIndex=ipv6RouterAdvertIfIndex, ipv6GeneralGroup2=ipv6GeneralGroup2, icmpStatsIPVersion=icmpStatsIPVersion, icmpOutTimestamps=icmpOutTimestamps, ipSystemStatsReasmOKs=ipSystemStatsReasmOKs, ipSystemStatsHCOutForwDatagrams=ipSystemStatsHCOutForwDatagrams, ipIfStatsOutDiscards=ipIfStatsOutDiscards, ipSystemStatsReasmFails=ipSystemStatsReasmFails, ipv6RouterAdvertSendAdverts=ipv6RouterAdvertSendAdverts, IpAddressStatusTC=IpAddressStatusTC, ipNetToMediaIfIndex=ipNetToMediaIfIndex, ipIfStatsDiscontinuityTime=ipIfStatsDiscontinuityTime, ipSystemStatsHCOctetGroup=ipSystemStatsHCOctetGroup, ipSystemStatsOutFragCreates=ipSystemStatsOutFragCreates, ipSystemStatsOutDiscards=ipSystemStatsOutDiscards)
mibBuilder.exportSymbols("IP-MIB", ipIfStatsOutFragCreates=ipIfStatsOutFragCreates, ipSystemStatsTable=ipSystemStatsTable, ipAddressPrefixAdvValidLifetime=ipAddressPrefixAdvValidLifetime, icmpInRedirects=icmpInRedirects, ipv6RouterAdvertManagedFlag=ipv6RouterAdvertManagedFlag, ipNetToMediaType=ipNetToMediaType, ipv6RouterAdvertEntry=ipv6RouterAdvertEntry, ipv6RouterAdvertTable=ipv6RouterAdvertTable, ipv4InterfaceEnableStatus=ipv4InterfaceEnableStatus, ipv4InterfaceReasmMaxSize=ipv4InterfaceReasmMaxSize, ipSystemStatsHCOutMcastPkts=ipSystemStatsHCOutMcastPkts, ipAddressPrefixOrigin=ipAddressPrefixOrigin, ipIfStatsReasmFails=ipIfStatsReasmFails, ipv6InterfaceReachableTime=ipv6InterfaceReachableTime, icmpInErrors=icmpInErrors, ipAddressAddr=ipAddressAddr, ipv6InterfaceReasmMaxSize=ipv6InterfaceReasmMaxSize, ipSystemStatsHCInReceives=ipSystemStatsHCInReceives, ipSystemStatsInUnknownProtos=ipSystemStatsInUnknownProtos, icmpMsgStatsEntry=icmpMsgStatsEntry, ipInUnknownProtos=ipInUnknownProtos, ipSystemStatsOutTransmits=ipSystemStatsOutTransmits, ipOutRequests=ipOutRequests, ipSystemStatsInOctets=ipSystemStatsInOctets, ipAddressPrefixOnLinkFlag=ipAddressPrefixOnLinkFlag, ipAddressIfIndex=ipAddressIfIndex, ipIfStatsHCOutTransmits=ipIfStatsHCOutTransmits, ipIfStatsInMcastOctets=ipIfStatsInMcastOctets, icmpMsgStatsIPVersion=icmpMsgStatsIPVersion, ipv6ScopeZoneIndexB=ipv6ScopeZoneIndexB, ipv6RouterAdvertMaxInterval=ipv6RouterAdvertMaxInterval, ipNetToPhysicalTable=ipNetToPhysicalTable, ipSystemStatsHCOutOctets=ipSystemStatsHCOutOctets, ipNetToPhysicalEntry=ipNetToPhysicalEntry, ipMIBCompliance2=ipMIBCompliance2, ipFragCreates=ipFragCreates, PYSNMP_MODULE_ID=ipMIB, ipAdEntAddr=ipAdEntAddr, ipNetToMediaNetAddress=ipNetToMediaNetAddress, ipAddressPrefixGroup=ipAddressPrefixGroup, ipv6RouterAdvertDefaultLifetime=ipv6RouterAdvertDefaultLifetime, ipForwDatagrams=ipForwDatagrams, ipIfStatsInDiscards=ipIfStatsInDiscards, ipIfStatsOutTransmits=ipIfStatsOutTransmits)
| 287.337115
| 10,918
| 0.717509
| 22,089
| 177,287
| 5.758568
| 0.057812
| 0.005016
| 0.00691
| 0.009214
| 0.60906
| 0.585294
| 0.547952
| 0.510578
| 0.443487
| 0.432292
| 0
| 0.032681
| 0.192947
| 177,287
| 616
| 10,919
| 287.803571
| 0.856339
| 0.001624
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| 0.622973
| 0.046794
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| 0
|
0
| 4
|
af9c8c985d4c12e15aaf8dc75c6cc6ea85cb8d8d
| 89
|
py
|
Python
|
src/anima/file_browser/__init__.py
|
damianignacio/anima
|
6f93242653ccf9a9563dd75e752279131863ae69
|
[
"MIT"
] | null | null | null |
src/anima/file_browser/__init__.py
|
damianignacio/anima
|
6f93242653ccf9a9563dd75e752279131863ae69
|
[
"MIT"
] | null | null | null |
src/anima/file_browser/__init__.py
|
damianignacio/anima
|
6f93242653ccf9a9563dd75e752279131863ae69
|
[
"MIT"
] | null | null | null |
class DeleteDeniedException(Exception):
pass
class FileBrowser(object):
pass
| 9.888889
| 39
| 0.730337
| 8
| 89
| 8.125
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.202247
| 89
| 8
| 40
| 11.125
| 0.915493
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| true
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| 1
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| 0
| 0
| 0
|
0
| 4
|
afac02099e14b79c41bc4ba25980868a07244f27
| 33
|
py
|
Python
|
thermo-env/lib/python3.5/sre_parse.py
|
ndebuhr/thermoModelingAlpha
|
9e1a0f9ac4caabf386c1e3103ec69f269131a6b9
|
[
"MIT"
] | 4
|
2017-09-24T21:30:46.000Z
|
2019-06-01T13:37:44.000Z
|
thermo-env/lib/python3.5/sre_parse.py
|
ndebuhr/thermo-state-solver
|
9e1a0f9ac4caabf386c1e3103ec69f269131a6b9
|
[
"MIT"
] | 19
|
2020-01-28T21:41:50.000Z
|
2022-03-11T23:17:39.000Z
|
thermo-env/lib/python3.5/sre_parse.py
|
ndebuhr/thermo-state-solver
|
9e1a0f9ac4caabf386c1e3103ec69f269131a6b9
|
[
"MIT"
] | null | null | null |
/usr/lib64/python3.5/sre_parse.py
| 33
| 33
| 0.818182
| 7
| 33
| 3.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.121212
| 0
| 33
| 1
| 33
| 33
| 0.666667
| 0
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| 0
| null | null | 0
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| null | null | 0
| 1
| 1
| 0
| null | 0
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| null | 0
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| 1
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| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
afaccad8bf6c41f0075aba6e3df9ba4805f88f22
| 139
|
py
|
Python
|
ninchat/bot/__main__.py
|
ninchat/ninchat-python
|
7e5fcadb7389ca8c7722c32d69839289675d7baa
|
[
"BSD-2-Clause"
] | null | null | null |
ninchat/bot/__main__.py
|
ninchat/ninchat-python
|
7e5fcadb7389ca8c7722c32d69839289675d7baa
|
[
"BSD-2-Clause"
] | 4
|
2017-10-12T21:05:12.000Z
|
2018-05-17T22:19:08.000Z
|
ninchat/bot/__main__.py
|
ninchat/ninchat-python
|
7e5fcadb7389ca8c7722c32d69839289675d7baa
|
[
"BSD-2-Clause"
] | null | null | null |
import logging
from .asyncio.main import main
logging.basicConfig(level=logging.INFO)
try:
main()
except KeyboardInterrupt:
pass
| 13.9
| 39
| 0.76259
| 17
| 139
| 6.235294
| 0.705882
| 0
| 0
| 0
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| 0
| 0.158273
| 139
| 9
| 40
| 15.444444
| 0.905983
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| 1
| 0
| true
| 0.142857
| 0.285714
| 0
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| null | 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
bb8d748bdcc955f311b17e2c53c576b182c9d2b8
| 92
|
py
|
Python
|
run.py
|
kahiga2244/news_articles
|
15e4649fb6769a8d20b230798c0231d0bc6709c7
|
[
"MIT"
] | null | null | null |
run.py
|
kahiga2244/news_articles
|
15e4649fb6769a8d20b230798c0231d0bc6709c7
|
[
"MIT"
] | null | null | null |
run.py
|
kahiga2244/news_articles
|
15e4649fb6769a8d20b230798c0231d0bc6709c7
|
[
"MIT"
] | null | null | null |
from app import app
#we run all the code from here
if __name__ == '__main__':
app.run()
| 18.4
| 30
| 0.684783
| 16
| 92
| 3.4375
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.217391
| 92
| 4
| 31
| 23
| 0.763889
| 0.315217
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| 0.129032
| 0
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| true
| 0
| 0.333333
| 0
| 0.333333
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| null | 0
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| 0
| 0
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| 0
| 0
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| 1
| 0
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| 0
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| null | 0
| 0
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| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
bb95c194821daaa4fb0b15e95d6286cf8bac3414
| 4,727
|
py
|
Python
|
TP2/2. StringRotation/pruebasKMP_matching.py
|
FdelMazo/TDA1
|
a61dc6abe0a30b129c3b0f8b2df6f74331e08dc7
|
[
"MIT"
] | 2
|
2020-10-10T17:34:16.000Z
|
2021-11-20T18:40:16.000Z
|
TP2/2. StringRotation/pruebasKMP_matching.py
|
FdelMazo/7529rw-TDA
|
a61dc6abe0a30b129c3b0f8b2df6f74331e08dc7
|
[
"MIT"
] | null | null | null |
TP2/2. StringRotation/pruebasKMP_matching.py
|
FdelMazo/7529rw-TDA
|
a61dc6abe0a30b129c3b0f8b2df6f74331e08dc7
|
[
"MIT"
] | null | null | null |
import unittest
from KMP_matching import *
class PruebaKRP(unittest.TestCase):
def test_dos_cadenas_iguales_hacen_match(self):
self.assertTrue(KMP_matching("hola","hola"))
def test_dos_cadenas_iguales_hacen_match2(self):
self.assertTrue(KMP_matching("silla","silla"))
def test_substring_tiene_el_match_esperado(self):
self.assertTrue(KMP_matching("hola","h"))
def test_substring_tiene_el_match_esperado2(self):
self.assertTrue(KMP_matching("hola","o"))
def test_substring_tiene_el_match_esperado3(self):
self.assertTrue(KMP_matching("hola","l"))
def test_substring_tiene_el_match_esperado4(self):
self.assertTrue(KMP_matching("hola","a"))
def test_substring_tiene_el_match_esperado5(self):
self.assertTrue(KMP_matching("hola","ho"))
def test_substring_tiene_el_match_esperado6(self):
self.assertTrue(KMP_matching("hola","ol"))
def test_substring_tiene_el_match_esperado7(self):
self.assertTrue(KMP_matching("hola","la"))
def test_substring_tiene_el_match_esperado8(self):
self.assertTrue(KMP_matching("silla","s"))
def test_substring_tiene_el_match_esperado9(self):
self.assertTrue(KMP_matching("silla","i"))
def test_substring_tiene_el_match_esperado10(self):
self.assertTrue(KMP_matching("silla","l"))
def test_substring_tiene_el_match_esperado11(self):
self.assertTrue(KMP_matching("silla","a"))
def test_substring_tiene_el_match_esperado12(self):
self.assertTrue(KMP_matching("silla","si"))
def test_substring_tiene_el_match_esperado13(self):
self.assertTrue(KMP_matching("silla","ill"))
def test_substring_tiene_el_match_esperado14(self):
self.assertTrue(KMP_matching("silla","lla"))
def test_substring_tiene_el_match_esperado15(self):
self.assertTrue(KMP_matching("hola","hol"))
def test_substring_tiene_el_match_esperado16(self):
self.assertTrue(KMP_matching("hola","ola"))
def test_substring_tiene_el_match_esperado17(self):
self.assertTrue(KMP_matching("Así","í"))
def test_substring_tiene_el_match_esperado18(self):
self.assertTrue(KMP_matching("Así","sí"))
def test_substring_tiene_el_match_esperado19(self):
self.assertTrue(KMP_matching("Así","Así"))
def test_substring_tiene_el_match_esperado20(self):
self.assertTrue(KMP_matching("a","a"))
def test_substring_tiene_el_match_esperado21(self):
self.assertTrue(KMP_matching("Paraguas","agua"))
def test_substring_tiene_el_match_esperado22(self):
self.assertTrue(KMP_matching("Paraguas","aguas"))
def test_substring_tiene_el_match_esperado23(self):
self.assertTrue(KMP_matching("Paraguas","Para"))
def test_substring_tiene_el_match_esperado24(self):
self.assertTrue(KMP_matching("electroencefalografista","electro"))
def test_cadena_no_substring_no_hace_match25(self):
self.assertTrue(KMP_matching("silla","lla"))
def test_cadena_no_substring_no_hace_match(self):
self.assertFalse(KMP_matching("hola","ah"))
def test_cadena_no_substring_no_hace_match2(self):
self.assertFalse(KMP_matching("hola","oa"))
def test_cadena_no_substring_no_hace_match3(self):
self.assertFalse(KMP_matching("hola","al"))
def test_substring_tiene_el_match_esperado4(self):
self.assertFalse(KMP_matching("hola","oll"))
def test_cadena_no_substring_no_hace_match5(self):
self.assertFalse(KMP_matching("silla","asi"))
def test_cadena_no_substring_no_hace_match6(self):
self.assertFalse(KMP_matching("silla","p"))
def test_cadena_no_substring_no_hace_match7(self):
self.assertFalse(KMP_matching("electroencefalografista","electroencefalografistaa"))
def test_cadena_no_substring_no_hace_match8(self):
self.assertFalse(KMP_matching("silla","llla"))
def test_cadena_no_substring_no_hace_match9(self):
self.assertFalse(KMP_matching("electroencefalografista","llectroencefalografista"))
def test_cadena_no_substring_no_hace_match10(self):
self.assertFalse(KMP_matching("Así","i"))
def test_cadena_no_substring_no_hace_match11(self):
self.assertFalse(KMP_matching("Así","íAs"))
def test_cadena_no_substring_no_hace_match12(self):
self.assertFalse(KMP_matching("Paraguas","para"))
def test_cadena_no_substring_no_hace_match13(self):
self.assertFalse(KMP_matching("silla","silll"))
def test_cadena_no_substring_no_hace_match14(self):
self.assertFalse(KMP_matching("silla","illaa"))
def test_cadena_no_substring_no_hace_match15(self):
self.assertFalse(KMP_matching("silla","illas"))
def test_cadena_no_substring_no_hace_match16(self):
self.assertFalse(KMP_matching("silla","llas"))
'''Forma de ejecutar según la doc. de python'''
if __name__ == '__main__':
unittest.main()
'''suite = unittest.TestLoader().loadTestsFromTestCase(PruebaKRP)
unittest.TextTestRunner(verbosity=2).run(suite)'''
| 33.524823
| 86
| 0.795642
| 652
| 4,727
| 5.334356
| 0.180982
| 0.13916
| 0.139735
| 0.163025
| 0.795572
| 0.773433
| 0.220817
| 0.051179
| 0.051179
| 0
| 0
| 0.014679
| 0.077639
| 4,727
| 140
| 87
| 33.764286
| 0.783028
| 0
| 0
| 0.043956
| 0
| 0
| 0.091826
| 0.025422
| 0
| 0
| 0
| 0
| 0.472527
| 1
| 0.472527
| false
| 0
| 0.021978
| 0
| 0.505495
| 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
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
bbab5891adbcb494d0af8860232f97ddcdf256bd
| 98
|
py
|
Python
|
twitter/twitter_apis/apps.py
|
bantiagrawal/twitter
|
b489a9c65a5257d58e3f71f7d6bf329cf6ce5aee
|
[
"BSD-2-Clause"
] | null | null | null |
twitter/twitter_apis/apps.py
|
bantiagrawal/twitter
|
b489a9c65a5257d58e3f71f7d6bf329cf6ce5aee
|
[
"BSD-2-Clause"
] | null | null | null |
twitter/twitter_apis/apps.py
|
bantiagrawal/twitter
|
b489a9c65a5257d58e3f71f7d6bf329cf6ce5aee
|
[
"BSD-2-Clause"
] | null | null | null |
from django.apps import AppConfig
class TwitterApisConfig(AppConfig):
name = 'twitter_apis'
| 16.333333
| 35
| 0.77551
| 11
| 98
| 6.818182
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153061
| 98
| 5
| 36
| 19.6
| 0.903614
| 0
| 0
| 0
| 0
| 0
| 0.122449
| 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
|
bbdd7b3952eba20bbeaacb640b1ce52c37bad2c4
| 142
|
py
|
Python
|
csv_writer/csv_write.py
|
DoubleBridges/door-order-parser
|
cd652922006d84a34143ded325e79d141343521d
|
[
"MIT"
] | null | null | null |
csv_writer/csv_write.py
|
DoubleBridges/door-order-parser
|
cd652922006d84a34143ded325e79d141343521d
|
[
"MIT"
] | null | null | null |
csv_writer/csv_write.py
|
DoubleBridges/door-order-parser
|
cd652922006d84a34143ded325e79d141343521d
|
[
"MIT"
] | null | null | null |
import csv
from icecream import ic
from parser.quote_parser import QuoteDetails
data_dict = QuoteDetails("../sample_input.pdf")
ic(data_dict)
| 23.666667
| 47
| 0.816901
| 21
| 142
| 5.333333
| 0.619048
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098592
| 142
| 6
| 48
| 23.666667
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0.132867
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
bbf959506fb502163270fe6c358cc00ac0c9afab
| 85
|
py
|
Python
|
dnl/Params.py
|
Patyrn/Divide-and-Learn
|
ff03689c7ab6a7155ebd019babce8f79d0757a53
|
[
"MIT"
] | null | null | null |
dnl/Params.py
|
Patyrn/Divide-and-Learn
|
ff03689c7ab6a7155ebd019babce8f79d0757a53
|
[
"MIT"
] | null | null | null |
dnl/Params.py
|
Patyrn/Divide-and-Learn
|
ff03689c7ab6a7155ebd019babce8f79d0757a53
|
[
"MIT"
] | null | null | null |
RANDOM_SEED = 42
KNAPSACK = 'knapsack'
ICON_SCHEDULING_EASY = 'icon_scheduling_easy'
| 21.25
| 45
| 0.811765
| 11
| 85
| 5.818182
| 0.636364
| 0.4375
| 0.5625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026316
| 0.105882
| 85
| 4
| 45
| 21.25
| 0.815789
| 0
| 0
| 0
| 0
| 0
| 0.325581
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
|
a550122c8bbabfbbbdc08587cfbbd6926b4809b1
| 484
|
py
|
Python
|
aidapy/aidaxr/tests/test_xevents.py
|
cheshirepezz/AIDApy
|
022b81bd979639db66d3f9566c8006d0db52c96f
|
[
"MIT"
] | null | null | null |
aidapy/aidaxr/tests/test_xevents.py
|
cheshirepezz/AIDApy
|
022b81bd979639db66d3f9566c8006d0db52c96f
|
[
"MIT"
] | null | null | null |
aidapy/aidaxr/tests/test_xevents.py
|
cheshirepezz/AIDApy
|
022b81bd979639db66d3f9566c8006d0db52c96f
|
[
"MIT"
] | null | null | null |
"""
The following test integration suite assesses the interconectivity between aidafunc, mission subpackage, and HelioPy
"""
import numpy as np
import xarray as xr
import pandas as pd
from aidapy.aidaxr import xevents
import pytest
## Test xr.DataArray
#@pytest.mark.parametrize("col,row,scale,order", [
# (10, 3, [2, 4], 3)
#])
def test_pvi():
assert(True)
def test_threshold():
assert(True)
def test_increm():
assert(True)
def test_dummy():
assert(2+2==4)
| 17.285714
| 116
| 0.704545
| 70
| 484
| 4.814286
| 0.628571
| 0.083086
| 0.115727
| 0.151335
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0225
| 0.173554
| 484
| 27
| 117
| 17.925926
| 0.82
| 0.429752
| 0
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.307692
| 1
| 0.307692
| true
| 0
| 0.384615
| 0
| 0.692308
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
a562eab5be36cba1096856f6920b8349ba7ed4ab
| 3,136
|
py
|
Python
|
tests/test_simpleuri.py
|
AbletonAG/abl.vpath
|
74923ef63e3fee23ae0bbb3d5fab9b1a9b8158fe
|
[
"MIT"
] | null | null | null |
tests/test_simpleuri.py
|
AbletonAG/abl.vpath
|
74923ef63e3fee23ae0bbb3d5fab9b1a9b8158fe
|
[
"MIT"
] | 4
|
2015-09-21T15:14:11.000Z
|
2018-09-13T14:28:48.000Z
|
tests/test_simpleuri.py
|
AbletonAG/abl.vpath
|
74923ef63e3fee23ae0bbb3d5fab9b1a9b8158fe
|
[
"MIT"
] | 1
|
2017-05-31T14:22:44.000Z
|
2017-05-31T14:22:44.000Z
|
#******************************************************************************
# (C) 2008 Ableton AG
#******************************************************************************
import unittest
from abl.vpath.base.simpleuri import UriParse
class TestSimpleUri(unittest.TestCase):
def test_one(self):
uri = UriParse('file:///tmp/this')
self.assertEqual(uri.path, '/tmp/this')
def test_two(self):
uri = UriParse('scheme:///some/path')
self.assertEqual(uri.scheme, 'scheme')
self.assertEqual(uri.path, '/some/path')
def test_three(self):
uri = UriParse('svn://user@host:/some/path')
self.assertEqual(uri.scheme, 'svn')
self.assertEqual(uri.path, '/some/path')
self.assertEqual(uri.hostname, 'host')
self.assertEqual(uri.username, 'user')
def test_non_http_scheme(self):
uri = UriParse('scheme://user:password@host:/some/path')
self.assertEqual(uri.scheme, 'scheme')
self.assertEqual(uri.path, '/some/path')
self.assertEqual(uri.hostname, 'host')
self.assertEqual(uri.username, 'user')
self.assertEqual(uri.password, 'password')
def test_non_http_uri_with_query_part(self):
uri = UriParse('scheme:///some/path?key_one=val_one&key_two=val_two')
self.assertEqual(uri.query,
{'key_one':'val_one', 'key_two':'val_two'}
)
def test_funny_name(self):
uri = UriParse('file:///.#something')
self.assertEqual(uri.path, '/.#something')
def test_url_with_fragment(self):
uri = UriParse('http://somewhere/something#frack')
self.assertEqual(uri.path, '/something')
self.assertEqual(uri.fragment, 'frack')
def test_query(self):
uri = UriParse('http://heinz/?a=1')
self.assertEqual(uri.query['a'], '1')
uri = UriParse('http://heinz/?a=1&b=2')
self.assertEqual(uri.query['a'], '1')
self.assertEqual(uri.query['b'], '2')
def test_query_unsplit(self):
uri = UriParse('http://heinz/')
uri.query = dict(a='1', b='2')
self.assertEqual(uri, UriParse(str(uri)))
def test_absolute_url(self):
uri = UriParse('http:///local/path')
self.assertEqual(str(uri), '/local/path')
def test_relative_url(self):
uri = UriParse('http://tmp/this')
self.assertEqual(uri.scheme, 'http')
self.assertEqual(uri.path, '/this')
def test_relative_uri(self):
uri = UriParse('file://./local/path')
self.assertEqual(uri.path, './local/path')
def test_relative_uri_with_scheme(self):
uri = UriParse('scheme://./local/path')
self.assertEqual(uri.path, './local/path')
def test_suburi_as_serverpart(self):
uri = UriParse('scheme://((/path/to/local/file.zip))/content.txt')
self.assertEqual(uri.vpath_connector, '/path/to/local/file.zip')
self.assertEqual(uri.path, '/content.txt')
if __name__ == '__main__':
unittest.main()
| 36.045977
| 80
| 0.565689
| 359
| 3,136
| 4.802228
| 0.194986
| 0.234919
| 0.271462
| 0.12761
| 0.559745
| 0.382251
| 0.296984
| 0.24826
| 0.220418
| 0.220418
| 0
| 0.004963
| 0.228954
| 3,136
| 86
| 81
| 36.465116
| 0.708023
| 0.056122
| 0
| 0.203125
| 0
| 0
| 0.209335
| 0.0721
| 0
| 0
| 0
| 0
| 0.421875
| 1
| 0.21875
| false
| 0.03125
| 0.03125
| 0
| 0.265625
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a579949832f1219525edcf8bdb6e7fbf23cb2933
| 7,623
|
py
|
Python
|
test.py
|
rmelizalde/tiny-AES128-py
|
9dc4138484cef29c746c7573432c66391f9efb1c
|
[
"Unlicense"
] | 4
|
2018-01-27T14:47:43.000Z
|
2019-06-05T02:22:52.000Z
|
test.py
|
rmelizalde/tiny-AES128-py
|
9dc4138484cef29c746c7573432c66391f9efb1c
|
[
"Unlicense"
] | null | null | null |
test.py
|
rmelizalde/tiny-AES128-py
|
9dc4138484cef29c746c7573432c66391f9efb1c
|
[
"Unlicense"
] | 4
|
2021-06-13T12:56:38.000Z
|
2021-12-18T03:35:31.000Z
|
""" AES/MAC Test
Author: Ricardo Martinez Elizalde
Date: 11th January 2017
"""
from tinyAes128 import *
def test_encrypt_ecb():
key = [0x2b, 0x7e, 0x15, 0x16, 0x28, 0xae, 0xd2, 0xa6, 0xab, 0xf7, 0x15, 0x88, 0x09, 0xcf, 0x4f, 0x3c]
inB = [0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a]
outKnown = [0x3a, 0xd7, 0x7b, 0xb4, 0x0d, 0x7a, 0x36, 0x60, 0xa8, 0x9e, 0xca, 0xf3, 0x24, 0x66, 0xef, 0x97]
testBuf = [0] * 16
AES128_ECB_encrypt(inB, key, testBuf)
print "ECB decrypt: "
if cmp(outKnown, testBuf) == 0:
print "SUCCESS!\n"
else:
print "FAILURE!\n"
def test_decrypt_ecb():
key = [0x2b, 0x7e, 0x15, 0x16, 0x28, 0xae, 0xd2, 0xa6, 0xab, 0xf7, 0x15, 0x88, 0x09, 0xcf, 0x4f, 0x3c]
inB = [0x3a, 0xd7, 0x7b, 0xb4, 0x0d, 0x7a, 0x36, 0x60, 0xa8, 0x9e, 0xca, 0xf3, 0x24, 0x66, 0xef, 0x97]
outKnown = [0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a]
testBuf = [0] * 16
AES128_ECB_decrypt(inB, key, testBuf)
print "ECB decrypt: "
if cmp(outKnown, testBuf) == 0:
print "SUCCESS!\n"
else:
print "FAILURE!\n"
def test_encrypt_cbc():
key = [ 0x2b, 0x7e, 0x15, 0x16, 0x28, 0xae, 0xd2, 0xa6, 0xab, 0xf7, 0x15, 0x88, 0x09, 0xcf, 0x4f, 0x3c ]
iv = [ 0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f ]
inB = [ 0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a,
0xae, 0x2d, 0x8a, 0x57, 0x1e, 0x03, 0xac, 0x9c, 0x9e, 0xb7, 0x6f, 0xac, 0x45, 0xaf, 0x8e, 0x51,
0x30, 0xc8, 0x1c, 0x46, 0xa3, 0x5c, 0xe4, 0x11, 0xe5, 0xfb, 0xc1, 0x19, 0x1a, 0x0a, 0x52, 0xef,
0xf6, 0x9f, 0x24, 0x45, 0xdf, 0x4f, 0x9b, 0x17, 0xad, 0x2b, 0x41, 0x7b, 0xe6, 0x6c, 0x37, 0x10 ]
outKnown = [ 0x76, 0x49, 0xab, 0xac, 0x81, 0x19, 0xb2, 0x46, 0xce, 0xe9, 0x8e, 0x9b, 0x12, 0xe9, 0x19, 0x7d,
0x50, 0x86, 0xcb, 0x9b, 0x50, 0x72, 0x19, 0xee, 0x95, 0xdb, 0x11, 0x3a, 0x91, 0x76, 0x78, 0xb2,
0x73, 0xbe, 0xd6, 0xb8, 0xe3, 0xc1, 0x74, 0x3b, 0x71, 0x16, 0xe6, 0x9e, 0x22, 0x22, 0x95, 0x16,
0x3f, 0xf1, 0xca, 0xa1, 0x68, 0x1f, 0xac, 0x09, 0x12, 0x0e, 0xca, 0x30, 0x75, 0x86, 0xe1, 0xa7 ]
testBuf = [0] * 64
AES128_CBC_encrypt_buffer(testBuf, inB, 64, key, iv)
print "CBC encrypt: "
if cmp(outKnown, testBuf) == 0:
print "SUCCESS!\n"
else:
print "FAILURE!\n"
def test_decrypt_cbc():
#Example "simulating" a smaller buffer...
key = [ 0x2b, 0x7e, 0x15, 0x16, 0x28, 0xae, 0xd2, 0xa6, 0xab, 0xf7, 0x15, 0x88, 0x09, 0xcf, 0x4f, 0x3c ]
iv = [ 0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f ]
inB = [ 0x76, 0x49, 0xab, 0xac, 0x81, 0x19, 0xb2, 0x46, 0xce, 0xe9, 0x8e, 0x9b, 0x12, 0xe9, 0x19, 0x7d,
0x50, 0x86, 0xcb, 0x9b, 0x50, 0x72, 0x19, 0xee, 0x95, 0xdb, 0x11, 0x3a, 0x91, 0x76, 0x78, 0xb2,
0x73, 0xbe, 0xd6, 0xb8, 0xe3, 0xc1, 0x74, 0x3b, 0x71, 0x16, 0xe6, 0x9e, 0x22, 0x22, 0x95, 0x16,
0x3f, 0xf1, 0xca, 0xa1, 0x68, 0x1f, 0xac, 0x09, 0x12, 0x0e, 0xca, 0x30, 0x75, 0x86, 0xe1, 0xa7 ]
outKnown = [ 0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a,
0xae, 0x2d, 0x8a, 0x57, 0x1e, 0x03, 0xac, 0x9c, 0x9e, 0xb7, 0x6f, 0xac, 0x45, 0xaf, 0x8e, 0x51,
0x30, 0xc8, 0x1c, 0x46, 0xa3, 0x5c, 0xe4, 0x11, 0xe5, 0xfb, 0xc1, 0x19, 0x1a, 0x0a, 0x52, 0xef,
0xf6, 0x9f, 0x24, 0x45, 0xdf, 0x4f, 0x9b, 0x17, 0xad, 0x2b, 0x41, 0x7b, 0xe6, 0x6c, 0x37, 0x10 ]
#Option 1: decrypt the 64 bytes long, Option 2: do it in 4 * 16 bytes buffers)
print "CBC decrypt 64 bytes at one time: "
testBuf = [0] * 64
AES128_CBC_decrypt_buffer(testBuf, inB, 64, key, iv)
if cmp(outKnown, testBuf) == 0:
print "SUCCESS!\n"
else:
print "FAILURE!\n"
print "CBC decrypt 16 bytes 4 times: "
tmp = [0] * 16
AES128_CBC_decrypt_buffer(tmp, inB, 16, key, iv)
testBuf[0:16] = tmp
AES128_CBC_decrypt_buffer(tmp, inB[16:], 16, 0, 0)
testBuf[16:32] = tmp
AES128_CBC_decrypt_buffer(tmp, inB[32:], 16, 0, 0)
testBuf[32:48] = tmp
AES128_CBC_decrypt_buffer(tmp, inB[48:], 16, 0, 0)
testBuf[48:64] = tmp
if cmp(outKnown, testBuf) == 0:
print "SUCCESS!\n"
else:
print "FAILURE!\n"
def test_aes_cmac():
key = [0x2b, 0x7e, 0x15, 0x16, 0x28, 0xae, 0xd2, 0xa6, 0xab, 0xf7, 0x15, 0x88, 0x09, 0xcf, 0x4f, 0x3c]
#verification data for subkey generation
aesK0 = [0x7d, 0xf7, 0x6b, 0x0c, 0x1a, 0xb8, 0x99, 0xb3, 0x3e, 0x42, 0xf0, 0x47, 0xb9, 0x1b, 0x54, 0x6f]
K1 = [0xfb, 0xee, 0xd6, 0x18, 0x35, 0x71, 0x33, 0x66, 0x7c, 0x85, 0xe0, 0x8f, 0x72, 0x36, 0xa8, 0xde]
K2 = [0xf7, 0xdd, 0xac, 0x30, 0x6a, 0xe2, 0x66, 0xcc, 0xf9, 0x0b, 0xc1, 0x1e, 0xe4, 0x6d, 0x51, 0x3b]
#some messages and corresponding CMACs
msg0 = None
cmac0 = [0xbb, 0x1d, 0x69, 0x29, 0xe9, 0x59, 0x37, 0x28, 0x7f, 0xa3, 0x7d, 0x12, 0x9b, 0x75, 0x67, 0x46]
msg16 = [0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a]
cmac16 = [0x07, 0x0a, 0x16, 0xb4, 0x6b, 0x4d, 0x41, 0x44, 0xf7, 0x9b, 0xdd, 0x9d, 0xd0, 0x4a, 0x28, 0x7c]
msg40 = [0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a,
0xae, 0x2d, 0x8a, 0x57, 0x1e, 0x03, 0xac, 0x9c, 0x9e, 0xb7, 0x6f, 0xac, 0x45, 0xaf, 0x8e, 0x51,
0x30, 0xc8, 0x1c, 0x46, 0xa3, 0x5c, 0xe4, 0x11]
cmac40 = [0xdf, 0xa6, 0x67, 0x47, 0xde, 0x9a, 0xe6, 0x30, 0x30, 0xca, 0x32, 0x61, 0x14, 0x97, 0xc8, 0x27]
msg64 = [0x6b, 0xc1, 0xbe, 0xe2, 0x2e, 0x40, 0x9f, 0x96, 0xe9, 0x3d, 0x7e, 0x11, 0x73, 0x93, 0x17, 0x2a,
0xae, 0x2d, 0x8a, 0x57, 0x1e, 0x03, 0xac, 0x9c, 0x9e, 0xb7, 0x6f, 0xac, 0x45, 0xaf, 0x8e, 0x51,
0x30, 0xc8, 0x1c, 0x46, 0xa3, 0x5c, 0xe4, 0x11, 0xe5, 0xfb, 0xc1, 0x19, 0x1a, 0x0a, 0x52, 0xef,
0xf6, 0x9f, 0x24, 0x45, 0xdf, 0x4f, 0x9b, 0x17, 0xad, 0x2b, 0x41, 0x7b, 0xe6, 0x6c, 0x37, 0x10]
cmac64 = [0x51, 0xf0, 0xbe, 0xbf, 0x7e, 0x3b, 0x9d, 0x92, 0xfc, 0x49, 0x74, 0x17, 0x79, 0x36, 0x3c, 0xfe]
#buffers
B1 = [0] * 16
B2 = [0] * 16
B3 = [0] * 16
print "AES-CMAC subkeys"
print "AES-128(key, 0)"
AES128_CBC_encrypt_buffer(B3, B1, 16, key, B2)
if (0 == cmp(B3, aesK0)):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
AES128_CMAC_generate_subkey(B1, B2, key)
print "Subkeys K1, K2\n"
if ((0 == cmp(B1, K1)) and (0 == cmp(B2, K2))):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
AES128_CMAC(B1, msg0, 0, key)
print "AES-CMAC empty string:\n"
if (0 == cmp(B1, cmac0)):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
AES128_CMAC(B1, msg16, 16, key)
print "AES-CMAC 16 bytes:\n"
if (0 == cmp(B1, cmac16)):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
AES128_CMAC(B1, msg40, 40, key)
print "AES-CMAC 40 bytes:\n"
if (0 == cmp(B1, cmac40)):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
AES128_CMAC(B1, msg64, 64, key)
print "AES-CMAC 64 bytes:\n"
if (0 == cmp(B1, cmac64)):
print "SUCCESS!\n"
else:
print "FAILURE!\n"
def main():
test_decrypt_ecb()
test_encrypt_ecb()
test_encrypt_cbc()
test_decrypt_cbc()
test_aes_cmac()
if __name__ == '__main__':
main()
| 42.825843
| 117
| 0.596353
| 1,126
| 7,623
| 3.984014
| 0.230906
| 0.029425
| 0.031877
| 0.041685
| 0.70486
| 0.683905
| 0.664289
| 0.636424
| 0.629068
| 0.620152
| 0
| 0.30109
| 0.254099
| 7,623
| 178
| 118
| 42.825843
| 0.487865
| 0.026236
| 0
| 0.482014
| 0
| 0
| 0.064561
| 0
| 0
| 0
| 0.371157
| 0
| 0
| 0
| null | null | 0
| 0.007194
| null | null | 0.244604
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 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
|
a58cbd3f01a4bea461df75979275c676c7f5aebf
| 53
|
py
|
Python
|
settings.py
|
ajmcateer/RaspberryAlarm
|
df8b774e72b2e3d077268d00c0b6b2e132b37070
|
[
"MIT"
] | null | null | null |
settings.py
|
ajmcateer/RaspberryAlarm
|
df8b774e72b2e3d077268d00c0b6b2e132b37070
|
[
"MIT"
] | 2
|
2019-09-03T00:44:59.000Z
|
2021-06-01T23:50:36.000Z
|
settings.py
|
ajmcateer/RaspberryAlarm
|
df8b774e72b2e3d077268d00c0b6b2e132b37070
|
[
"MIT"
] | null | null | null |
import sys
root_path = sys.path[0]
print(root_path)
| 10.6
| 23
| 0.754717
| 10
| 53
| 3.8
| 0.6
| 0.421053
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.021739
| 0.132075
| 53
| 4
| 24
| 13.25
| 0.804348
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0.333333
| 1
| 0
| 0
| null | 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
|
a596665849428181b19876a9b78478b1416ee1fd
| 164
|
py
|
Python
|
rts.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | null | null | null |
rts.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | null | null | null |
rts.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | 1
|
2021-07-28T02:13:21.000Z
|
2021-07-28T02:13:21.000Z
|
from RecordingTranscriptionSample import RecordingTranscriptionSample
def rts(task):
(_config,x,y) = task
return RecordingTranscriptionSample(_config,x,y)
| 27.333333
| 69
| 0.804878
| 16
| 164
| 8.125
| 0.625
| 0.107692
| 0.123077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121951
| 164
| 5
| 70
| 32.8
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
a59c75a4ba20f43da6382db6796ecd954f332d91
| 98
|
py
|
Python
|
Problems/String Length/len.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | 3
|
2018-07-17T09:03:02.000Z
|
2020-05-11T18:03:25.000Z
|
Problems/String Length/len.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | null | null | null |
Problems/String Length/len.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | 2
|
2016-06-01T13:16:27.000Z
|
2018-09-25T08:32:24.000Z
|
if __name__ == "__main__":
for tc in xrange(int(raw_input())):
print len(raw_input())
| 24.5
| 39
| 0.612245
| 14
| 98
| 3.571429
| 0.857143
| 0.32
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.22449
| 98
| 3
| 40
| 32.666667
| 0.657895
| 0
| 0
| 0
| 0
| 0
| 0.081633
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.333333
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a5a7615d9f8e8413a9648eb1e17f1f86f03d733f
| 366
|
py
|
Python
|
tests/run/builtin_float.py
|
matham/cython
|
4aec02117deb1d9279a81920f21459fc015d1a77
|
[
"Apache-2.0"
] | 2
|
2020-01-29T08:20:22.000Z
|
2020-01-29T08:20:25.000Z
|
tests/run/builtin_float.py
|
holzschu/cython
|
8f6c7f707b28cb8e76ecbf5fcd089c6255dacdb8
|
[
"Apache-2.0"
] | 1
|
2019-09-21T19:58:10.000Z
|
2019-09-21T19:58:10.000Z
|
tests/run/builtin_float.py
|
holzschu/cython
|
8f6c7f707b28cb8e76ecbf5fcd089c6255dacdb8
|
[
"Apache-2.0"
] | 1
|
2021-04-04T15:42:28.000Z
|
2021-04-04T15:42:28.000Z
|
def empty_float():
"""
>>> float()
0.0
>>> empty_float()
0.0
"""
x = float()
return x
def float_conjugate():
"""
>>> float_call_conjugate()
1.5
"""
x = 1.5 .conjugate()
return x
def float_call_conjugate():
"""
>>> float_call_conjugate()
1.5
"""
x = float(1.5).conjugate()
return x
| 12.62069
| 30
| 0.478142
| 44
| 366
| 3.772727
| 0.227273
| 0.048193
| 0.325301
| 0.180723
| 0.578313
| 0.361446
| 0.361446
| 0
| 0
| 0
| 0
| 0.049793
| 0.34153
| 366
| 28
| 31
| 13.071429
| 0.639004
| 0.270492
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 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
|
a5b799a82efc75ac20ba77433a65a2e60fd15768
| 905
|
py
|
Python
|
lib/web/modules/inventory/__init__.py
|
SmartDataProjects/ddm
|
911f90c88702c9f7ed7a885744028c5705543e88
|
[
"MIT"
] | 1
|
2018-08-02T03:06:27.000Z
|
2018-08-02T03:06:27.000Z
|
lib/web/modules/inventory/__init__.py
|
SmartDataProjects/ddm
|
911f90c88702c9f7ed7a885744028c5705543e88
|
[
"MIT"
] | 16
|
2017-11-24T21:09:26.000Z
|
2019-05-14T15:13:57.000Z
|
lib/web/modules/inventory/__init__.py
|
SmartDataProjects/ddm
|
911f90c88702c9f7ed7a885744028c5705543e88
|
[
"MIT"
] | 11
|
2016-08-03T10:37:31.000Z
|
2018-08-21T14:32:25.000Z
|
from . import datasets
from . import groups
from . import sites
from . import stats
from . import inject
from . import delete
from . import blockreplicas
from . import subscriptions
from . import requestlist
from . import lfn2pfn
from . import nodes
from . import data
from . import transferrequests
export_data = {}
export_data.update(datasets.export_data)
export_data.update(groups.export_data)
export_data.update(sites.export_data)
export_data.update(stats.export_data)
export_data.update(inject.export_data)
export_data.update(delete.export_data)
export_data.update(blockreplicas.export_data)
export_data.update(requestlist.export_data)
export_data.update(subscriptions.export_data)
export_data.update(lfn2pfn.export_data)
export_data.update(nodes.export_data)
export_data.update(data.export_data)
export_data.update(transferrequests.export_data)
export_web = {}
export_web.update(stats.export_web)
| 28.28125
| 48
| 0.835359
| 127
| 905
| 5.716535
| 0.141732
| 0.371901
| 0.30854
| 0.358127
| 0.465565
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002407
| 0.081768
| 905
| 31
| 49
| 29.193548
| 0.871239
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.448276
| 0
| 0.448276
| 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
| 1
| 0
| 0
| 0
|
0
| 4
|
b1dfa9e1e63d4de113dd744c16329ae2461d6831
| 151
|
py
|
Python
|
gluoncv/model_zoo/monodepthv2/__init__.py
|
gvvynplaine/gluon-cv
|
8f58c26a1b6f27fbd52d64c6fdb3734ceffc3ff8
|
[
"Apache-2.0"
] | null | null | null |
gluoncv/model_zoo/monodepthv2/__init__.py
|
gvvynplaine/gluon-cv
|
8f58c26a1b6f27fbd52d64c6fdb3734ceffc3ff8
|
[
"Apache-2.0"
] | null | null | null |
gluoncv/model_zoo/monodepthv2/__init__.py
|
gvvynplaine/gluon-cv
|
8f58c26a1b6f27fbd52d64c6fdb3734ceffc3ff8
|
[
"Apache-2.0"
] | null | null | null |
# pylint: disable=missing-module-docstring
from .resnet_encoder import ResnetEncoder
from .depth_decoder import DepthDecoder
from .monodepth2 import *
| 30.2
| 42
| 0.84106
| 18
| 151
| 6.944444
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007353
| 0.099338
| 151
| 4
| 43
| 37.75
| 0.911765
| 0.264901
| 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
|
b1eb5a321e650949e0b36f2f374d12033a5cc6a2
| 114
|
py
|
Python
|
my_project/data.py
|
gmrukwa/polyaxon-examples
|
9800c0bb11fca64c7fe918e200bfb2c5d5559142
|
[
"MIT"
] | 1
|
2020-07-06T17:50:06.000Z
|
2020-07-06T17:50:06.000Z
|
my_project/data.py
|
gmrukwa/polyaxon-examples
|
9800c0bb11fca64c7fe918e200bfb2c5d5559142
|
[
"MIT"
] | null | null | null |
my_project/data.py
|
gmrukwa/polyaxon-examples
|
9800c0bb11fca64c7fe918e200bfb2c5d5559142
|
[
"MIT"
] | 1
|
2020-06-19T18:23:30.000Z
|
2020-06-19T18:23:30.000Z
|
from sklearn import datasets
def load_data():
iris = datasets.load_iris()
return iris.data, iris.target
| 16.285714
| 33
| 0.719298
| 16
| 114
| 5
| 0.625
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.192982
| 114
| 6
| 34
| 19
| 0.869565
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
b1ee91b452a8a5933ca995eecdd30f0d6f5c3d5f
| 592
|
py
|
Python
|
code-exercises-etc/section_03_(conditionals)/ajm.cond3.20151024.py
|
hannahkwarren/CLaG-Sp2016
|
a75862d187176d9f2f1778eb6300056364292b44
|
[
"MIT"
] | null | null | null |
code-exercises-etc/section_03_(conditionals)/ajm.cond3.20151024.py
|
hannahkwarren/CLaG-Sp2016
|
a75862d187176d9f2f1778eb6300056364292b44
|
[
"MIT"
] | null | null | null |
code-exercises-etc/section_03_(conditionals)/ajm.cond3.20151024.py
|
hannahkwarren/CLaG-Sp2016
|
a75862d187176d9f2f1778eb6300056364292b44
|
[
"MIT"
] | null | null | null |
volunteers = 10
goal = 50
##if volunteers < goal:
## print "More volunteers are needed."
## print "{0} more volunteers are needed.".format(goal-volunteers)
##elif volunteers == goal:
## print "We have enough volunteers."
##elif volunteers > goal:
## print "We have a volunteer surplus."
##else:
## print "This is unexpected......"
if volunteers < goal:
print "You are {0} below your goal".format(goal - volunteers)
elif volunteers == goal:
print "At your goal"
elif volunteers > goal:
print "You're above your goal"
else:
print "er, something weird happened"
| 26.909091
| 69
| 0.66723
| 78
| 592
| 5.064103
| 0.410256
| 0.212658
| 0.288608
| 0.232911
| 0.331646
| 0.331646
| 0.331646
| 0
| 0
| 0
| 0
| 0.012685
| 0.201014
| 592
| 21
| 70
| 28.190476
| 0.82241
| 0.494932
| 0
| 0
| 0
| 0
| 0.316726
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.4
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
59045cc650cfbe295d8559c7e2aa9ab9bdaa280a
| 424
|
py
|
Python
|
onnxruntime/python/training/__init__.py
|
scchan/onnxruntime
|
635bc9cd0492504b86883327b62a7b12d22181ba
|
[
"MIT"
] | null | null | null |
onnxruntime/python/training/__init__.py
|
scchan/onnxruntime
|
635bc9cd0492504b86883327b62a7b12d22181ba
|
[
"MIT"
] | null | null | null |
onnxruntime/python/training/__init__.py
|
scchan/onnxruntime
|
635bc9cd0492504b86883327b62a7b12d22181ba
|
[
"MIT"
] | null | null | null |
#-------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
#--------------------------------------------------------------------------
# This is a placeholder file. It is deployed with inference only wheel.
print("An inference only version of ONNX Runtime is installed. Training functionalities are unavailable.")
| 60.571429
| 106
| 0.511792
| 38
| 424
| 5.710526
| 0.894737
| 0.119816
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099057
| 424
| 7
| 106
| 60.571429
| 0.568063
| 0.724057
| 0
| 0
| 0
| 0
| 0.858407
| 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
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
5908cbda8fdc6279439ff715f39e5161f7b9262b
| 801
|
py
|
Python
|
django_extras/tests/utils/humanize.py
|
gem/django-extras
|
d692e87891fe4cb79726437d3185628c1a9e2f33
|
[
"BSD-3-Clause"
] | 18
|
2015-08-22T08:59:48.000Z
|
2020-10-08T17:15:23.000Z
|
django_extras/tests/utils/humanize.py
|
gem/django-extras
|
d692e87891fe4cb79726437d3185628c1a9e2f33
|
[
"BSD-3-Clause"
] | 4
|
2018-01-06T23:19:20.000Z
|
2020-10-09T02:22:45.000Z
|
django_extras/tests/utils/humanize.py
|
gem/django-extras
|
d692e87891fe4cb79726437d3185628c1a9e2f33
|
[
"BSD-3-Clause"
] | 9
|
2015-06-15T17:28:03.000Z
|
2021-08-29T07:26:50.000Z
|
from django import test
from django_extras.utils import humanize
class HumanizeDescribeSecondsTestCase(test.TestCase):
def test_seconds(self):
self.assertEqual('12s', humanize.describe_seconds(12))
def test_minutes(self):
self.assertEqual('12m', humanize.describe_seconds(720))
def test_hours(self):
self.assertEqual('12h', humanize.describe_seconds(43200))
def test_days(self):
self.assertEqual('5d', humanize.describe_seconds(432000))
def test_weeks(self):
self.assertEqual('12w', humanize.describe_seconds(7257600))
def test_all_one(self):
self.assertEqual('1w 1d 1h 1m 1s', humanize.describe_seconds(694861))
def test_mix_it_up(self):
self.assertEqual('2w 3d 14h 42s', humanize.describe_seconds(1519242))
| 30.807692
| 77
| 0.717853
| 101
| 801
| 5.514851
| 0.445545
| 0.087971
| 0.238779
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084337
| 0.171036
| 801
| 25
| 78
| 32.04
| 0.754518
| 0
| 0
| 0
| 0
| 0
| 0.051186
| 0
| 0
| 0
| 0
| 0
| 0.411765
| 1
| 0.411765
| false
| 0
| 0.117647
| 0
| 0.588235
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
5936effc3b8452a78f0027fd44517bacc2dbf6fa
| 549
|
py
|
Python
|
application/api/migrations/0002_auto_20190128_1515.py
|
cqkenuo/w12scan
|
eac6147a186cac152fa1ffdd0a31dcb1d3e19d0b
|
[
"MIT"
] | 864
|
2019-05-13T03:43:23.000Z
|
2022-03-27T13:11:34.000Z
|
application/api/migrations/0002_auto_20190128_1515.py
|
cqkenuo/w12scan
|
eac6147a186cac152fa1ffdd0a31dcb1d3e19d0b
|
[
"MIT"
] | 60
|
2019-05-13T05:40:29.000Z
|
2021-11-14T02:21:02.000Z
|
application/api/migrations/0002_auto_20190128_1515.py
|
cqkenuo/w12scan
|
eac6147a186cac152fa1ffdd0a31dcb1d3e19d0b
|
[
"MIT"
] | 291
|
2019-05-14T08:03:32.000Z
|
2022-03-27T15:58:53.000Z
|
# Generated by Django 2.1.4 on 2019-01-28 07:15
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('api', '0001_initial'),
]
operations = [
migrations.RenameModel(
old_name='W12scan_domains',
new_name='domains',
),
migrations.RenameModel(
old_name='W12scan_ips',
new_name='ips',
),
migrations.RenameModel(
old_name='W12scan_properly',
new_name='properly',
),
]
| 21.115385
| 47
| 0.551913
| 53
| 549
| 5.528302
| 0.584906
| 0.215017
| 0.245734
| 0.286689
| 0.358362
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068681
| 0.336976
| 549
| 25
| 48
| 21.96
| 0.736264
| 0.081967
| 0
| 0.315789
| 1
| 0
| 0.149402
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.052632
| 0
| 0.210526
| 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
|
3cd2509de6715b88e497ee1e3f3a96a57da312cd
| 94
|
py
|
Python
|
utils/__init__.py
|
clinicalml/theanomodels
|
bb1c81a81b3d69effa4317fff4a5bab3ee464b84
|
[
"MIT"
] | 3
|
2017-02-13T03:59:42.000Z
|
2018-04-06T20:40:10.000Z
|
utils/__init__.py
|
clinicalml/theanomodels
|
bb1c81a81b3d69effa4317fff4a5bab3ee464b84
|
[
"MIT"
] | null | null | null |
utils/__init__.py
|
clinicalml/theanomodels
|
bb1c81a81b3d69effa4317fff4a5bab3ee464b84
|
[
"MIT"
] | 12
|
2016-12-22T02:20:10.000Z
|
2020-10-15T19:00:57.000Z
|
__all__=['optimizer','parse_args_vae','parse_args_lstm','parse_args_dkf','misc','divergence']
| 47
| 93
| 0.776596
| 13
| 94
| 4.846154
| 0.692308
| 0.428571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010638
| 94
| 1
| 94
| 94
| 0.677419
| 0
| 0
| 0
| 0
| 0
| 0.702128
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3cd6b29f7202996e30bd586783d84e10fa3aee3d
| 222
|
py
|
Python
|
ovl/image_utilities/__init__.py
|
frc1937/ovl
|
1954edf0ab946dbb42d90eba1dac97eeb157c567
|
[
"Apache-2.0"
] | 1
|
2021-05-13T12:15:29.000Z
|
2021-05-13T12:15:29.000Z
|
ovl/image_utilities/__init__.py
|
frc1937/ovl
|
1954edf0ab946dbb42d90eba1dac97eeb157c567
|
[
"Apache-2.0"
] | null | null | null |
ovl/image_utilities/__init__.py
|
frc1937/ovl
|
1954edf0ab946dbb42d90eba1dac97eeb157c567
|
[
"Apache-2.0"
] | null | null | null |
from .display_image import stitch_images, show_image, display_image
from .display_contours import display_contours
from .naming_conventions import *
from .photo_array import photo_array
from .open_image import open_image
| 31.714286
| 67
| 0.86036
| 32
| 222
| 5.625
| 0.40625
| 0.122222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103604
| 222
| 6
| 68
| 37
| 0.904523
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
3cf8d4c989e5d8ae723ca2fa2deed42bd25e75d9
| 161
|
py
|
Python
|
fruits/apps.py
|
skydev66/django-mysql
|
ed63d01a7db73303b9e55afe7aba43075128e3f1
|
[
"Apache-2.0"
] | 1
|
2020-03-08T23:55:12.000Z
|
2020-03-08T23:55:12.000Z
|
fruits/apps.py
|
skydev66/django-mysql
|
ed63d01a7db73303b9e55afe7aba43075128e3f1
|
[
"Apache-2.0"
] | null | null | null |
fruits/apps.py
|
skydev66/django-mysql
|
ed63d01a7db73303b9e55afe7aba43075128e3f1
|
[
"Apache-2.0"
] | null | null | null |
#import libraries
from __future__ import unicode_literals
from django.apps import AppConfig
#set name fruits
class FruitsConfig(AppConfig):
name = 'fruits'
| 20.125
| 39
| 0.801242
| 20
| 161
| 6.2
| 0.7
| 0.16129
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 161
| 7
| 40
| 23
| 0.898551
| 0.192547
| 0
| 0
| 0
| 0
| 0.046875
| 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
|
a71ead3e1acf18f3e06418f431483e04f70cafeb
| 24
|
py
|
Python
|
tests/CompileTests/Python_tests/test2011_007.py
|
maurizioabba/rose
|
7597292cf14da292bdb9a4ef573001b6c5b9b6c0
|
[
"BSD-3-Clause"
] | 488
|
2015-01-09T08:54:48.000Z
|
2022-03-30T07:15:46.000Z
|
tests/CompileTests/Python_tests/test2011_007.py
|
sujankh/rose-matlab
|
7435d4fa1941826c784ba97296c0ec55fa7d7c7e
|
[
"BSD-3-Clause"
] | 174
|
2015-01-28T18:41:32.000Z
|
2022-03-31T16:51:05.000Z
|
tests/CompileTests/Python_tests/test2011_007.py
|
sujankh/rose-matlab
|
7435d4fa1941826c784ba97296c0ec55fa7d7c7e
|
[
"BSD-3-Clause"
] | 146
|
2015-04-27T02:48:34.000Z
|
2022-03-04T07:32:53.000Z
|
def foo(bar):
bar + 1
| 8
| 13
| 0.541667
| 5
| 24
| 2.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0.291667
| 24
| 2
| 14
| 12
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a728c5cf71f8f28d071dada94337a400fc544dcf
| 97,834
|
py
|
Python
|
aci_deployment/tasks.py
|
Onyxnetworks/deployment_tool
|
26ae245f36b291739be38db8a581f91ee03d82dd
|
[
"Apache-2.0"
] | null | null | null |
aci_deployment/tasks.py
|
Onyxnetworks/deployment_tool
|
26ae245f36b291739be38db8a581f91ee03d82dd
|
[
"Apache-2.0"
] | 5
|
2019-01-22T10:41:10.000Z
|
2021-06-10T21:06:43.000Z
|
aci_deployment/tasks.py
|
Onyxnetworks/deployment_tool
|
26ae245f36b291739be38db8a581f91ee03d82dd
|
[
"Apache-2.0"
] | 1
|
2019-06-14T09:17:35.000Z
|
2019-06-14T09:17:35.000Z
|
# Base Functions
import openpyxl, json, yaml
from operator import itemgetter
# Custom Functions
from aci_deployment.scripts.ipg_search import *
from aci_deployment.scripts.endpoint_search import *
from aci_deployment.scripts.external_epg_deployment import *
from aci_deployment.scripts.contract_deployment import *
from aci_deployment.scripts.ipg_deployment import *
from aci_deployment.scripts.baseline import APIC_LOGIN
from index.scripts.baseline import get_base_url
# Celery Functions
from celery import shared_task
@shared_task
def ENDPOINT_SEARCH(base_urls, filter_default, username, password, search_string):
RESULTS = []
# Build URL List to search.
url_list = []
for url in base_urls['ACI']:
url_list.append(base_urls['ACI'][url])
ENDPOINT_LIST = GET_ENDPOINTS(url_list, filter_default, username, password)
try:
network = ipaddress.IPv4Network(search_string)
request_type = 'subnet'
except:
request_type = 'epg_name'
for i in ENDPOINT_LIST:
if request_type == 'subnet':
if IPNetwork(search_string) in IPNetwork(i['Subnet']) or IPNetwork(i['Subnet']) in IPNetwork(search_string):
RESULTS.append({'Subnet': i['Subnet'], 'Locality': i['Locality'], 'Location': i['Location'],
'EPG': i['EPG'], 'Scope': i['Scope'], 'AppProfile':
i['AppProfile'], 'Tenant': i['Tenant']})
if request_type == 'epg_name':
if search_string.upper() in i['EPG'].upper():
RESULTS.append({'Subnet': i['Subnet'], 'Locality': i['Locality'], 'Location': i['Location'],
'EPG': i['EPG'], 'Scope': i['Scope'], 'AppProfile':
i['AppProfile'], 'Tenant': i['Tenant']})
# Sort the list by subnet before returning it.
RESULTS = sorted(RESULTS, key=itemgetter('Subnet'), reverse=True)
return RESULTS
@shared_task
def aci_ipg_search(base_urls, username, password, search_string):
results = []
# Build URL List to search.
url_list = []
for url in base_urls['ACI']:
url_list.append(base_urls['ACI'][url])
ipg_list = get_ipg(url_list, username, password)
# List all EPG for selected
# Convert List into upper case
ipg_list_upper = [element.upper() for element in ipg_list]
search_string = search_string.upper()
if [s for s in ipg_list_upper if search_string in s.upper()]:
fvpathatt_list = get_fvpathatt(url_list, search_string, username, password)
# loop through output, print and add EPG's to list
i = 0
for ipg_location in fvpathatt_list:
location = ipg_location['location']
for epg in ipg_location['response']['imdata']:
results.append({'location': location, 'ipg':
epg['fvRsPathAtt']['attributes']['tDn'].split('/')[-1][8:].strip(']'), 'tenant':
epg['fvRsPathAtt']['attributes']['dn'].split('/')[1][3:], 'app_prof':
epg['fvRsPathAtt']['attributes']['dn'].split('/')[2][3:], 'epg':
epg['fvRsPathAtt']['attributes']['dn'].split('/')[3][4:], 'encap':
epg['fvRsPathAtt']['attributes']['encap']})
i += 1
return results
def ipg_deployment_open_yaml(file, location):
data = yaml.safe_load(file)
ipg_list = []
index = 1
for lines in data:
# Required Fields
line = index
environment = lines['environment'].upper()
node_1 = str(lines['node_1'])
ports = lines['ports']
speed = lines['speed']
description = lines['description']
mode = lines['mode'].upper()
# Optional Fields
if 'node_2' in lines:
node_2 = str(lines['node_2'])
else:
node_2 = None
if 'vpc' in lines:
vpc = 'YES'
else:
vpc = 'NO'
if 'port_channel_policy' in lines:
port_channel_policy = lines['port_channel_policy'].upper()
else:
port_channel_policy = None
if 'epg_list' in lines:
epg_list = lines['epg_list']
else:
epg_list = {}
if 'vmm' in lines:
if lines['vmm'].upper() == 'YES':
vmm = True
else:
vmm = False
else:
vmm = False
ipg_list.append({'line': line, 'environment': environment, 'node_1': node_1, 'node_2': node_2,
'ports': ports, 'speed': speed, 'vpc': vpc, 'port_channel_policy': port_channel_policy,
'description': description, 'epg_list': epg_list, 'mode': mode, 'vmm': vmm})
index += 1
return ipg_list
def ipg_deployment_excel_open_workbook(file, location):
wb = openpyxl.load_workbook(file, data_only=True)
if location == 'UKDC1':
py_ws = wb['ACI_DC1']
elif location == 'UKDC2':
py_ws = wb['ACI_DC2']
elif location == 'LAB':
py_ws = wb['ACI_LAB']
index = 4
ipg_list = []
# Loops through the rows in the worksheet to build IPG information
for row in py_ws.iter_rows(min_row=4, max_col=11):
epg_list = []
# Skip empty cells
if row[1].value is None:
continue
environment = row[0].value
node_1 = str(row[1].value)
if row[2].value:
node_2 = str(row[2].value)
else:
node_2 = None
ports = row[3].value
speed = row[4].value
if row[5].value is None:
vpc = 'NO'
else:
vpc = row[5].value.upper()
port_channel_policy = row[6].value
if not row[8].value is None:
try:
epg_list = json.loads(row[8].value)
except:
epg_list = {"Incorrect Format - Line-{0} make sure to use {1} ".format(index, '""'): ''}
else:
epg_list = {}
mode = row[9].value.upper()
if row[10].value.upper() == 'YES':
vmm = True
else:
vmm = False
description = row[7].value
ipg_list.append({'line': index, 'environment': environment, 'node_1': node_1, 'node_2': node_2,
'ports': ports, 'speed': speed, 'vpc': vpc, 'port_channel_policy': port_channel_policy,
'description': description, 'epg_list': epg_list, 'mode': mode, 'vmm': vmm})
index += 1
return ipg_list
@shared_task
def ipg_deployment_validation(ipg_list, location, url_dict, username, password):
headers = {'content-type': 'application/json'}
output_log = []
base_url = url_dict[location]
error = False
vpc_presant = False
output_log.append({'Headers': "Validating Formatting in Workbook."})
for ipg in ipg_list:
if ipg['vmm'] and ipg['epg_list']:
error = True
output_log.append({'Errors': 'Line: {0} - cannot have VMM integrated IPG with static EPG mappings.'.format(str(ipg['line']))})
if ipg['environment'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - No environment defined.'.format(str(ipg['line']))})
if ipg['vpc'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - VPC Field not defined'.format(str(ipg['line']))})
continue
if ipg['vpc'] == 'YES':
# Mark VPC Presant for later in script
vpc_presant = True
# If VPC = Yes check to make sure both nodes are defined.
if ipg['node_2'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Type VPC selected but Node 2 not defined.'.format(str(ipg['line']))})
continue
# If VPC = Yes check to make sure switches are a VPC pair
if int(ipg['node_2']) - int(ipg['node_1']) != 1:
error = True
output_log.append({'Errors': 'Line: {0} - Type VPC selected but switches are not a VPC Pair.'.format(str(ipg['line']))})
# If VPC = Yes check that a port-channel policy is defined.
if ipg['port_channel_policy'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Type VPC selected but no port-channel policy defined.'.format(str(ipg['line']))})
if ipg['vpc'] == 'NO':
# If VPC = No check to make sure node_2 has no value
if not ipg['node_2'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Non VPC selected but two switches defined.'.format(str(ipg['line']))})
# If VPC = No check to make sure port-channel policy has no value
if not ipg['port_channel_policy'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Non VPC selected but port-channel policy defined.'.format(str(ipg['line']))})
# Check to make sure speed is defined.
if ipg['speed'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Interface speed not defined.'.format(str(ipg['line']))})
# Check to make sure description is defined.
if ipg['description'] is None:
error = True
output_log.append({'Errors': 'Line: {0} - Description not defined.'.format(str(ipg['line']))})
if not error:
output_log.append({'NotificationsSuccess': 'Workbook validated successfully'})
# Go and check if switches exist on fabric.
switch_list = []
for switches in ipg_list:
switch_list.append(switches['node_1'])
if not switches['node_2'] is None:
switch_list.append(switches['node_2'])
excel_switch_list = list(set(switch_list))
fabric_switch_list = []
# Login to fabric
output_log.append({'Headers': 'Connecting to APIC'})
apic_cookie = APIC_LOGIN(base_url, username, password)
if apic_cookie:
output_log.append({'Notifications': 'Successfully generated authentication cookie'})
output_log.append({'Headers': 'Checking if nodes presant in fabric.'})
get_fabric_nodes_response = get_fabric_nodes(base_url, apic_cookie, headers, output_log)
if get_fabric_nodes_response[0]:
output_log = get_fabric_nodes_response[1]
error = True
else:
for nodes in get_fabric_nodes_response[1]['imdata']:
fabric_switch_list.append(nodes['fabricNode']['attributes']['id'])
for switch in excel_switch_list:
if switch not in fabric_switch_list:
error = True
output_log.append({'Errors': 'Node {0} not found in fabric.'.format(switch)})
if not error:
output_log.append({'NotificationsSuccess': 'Fabric switches validated successfully'})
# Check if IPG's already exist.
if not error:
output_log.append({'Headers': "Checking if IPG's presant in fabric."})
get_fabric_vpc_ipgs_response = get_fabric_vpc_ipgs(base_url, apic_cookie, headers, output_log)
if get_fabric_vpc_ipgs_response[0]:
output_log = get_fabric_vpc_ipgs_response[1]
error = True
if not error:
get_fabric_ipgs_response = get_fabric_ipgs(base_url, apic_cookie, headers, output_log)
if get_fabric_ipgs_response[0]:
output_log = get_fabric_ipgs_response[1]
error = True
if not error:
accessIpg = True
for ipg in ipg_list:
# Set created flag to false
ipg['lsp_mapped'] = False
ipg['presant'] = False
# Build IPG Name
if location == 'UKDC1':
ipg_prefix = '1'
elif location == 'UKDC2':
ipg_prefix = '2'
elif location == 'LAB':
ipg_prefix = '2'
environment = ipg['environment']
node_1 = ipg['node_1']
port = ipg['ports'].split('/')[-1]
fromPort = port
toPort = port
# Format the port
if len(port) == 1:
port = '0' + port
if '-' in port:
# format for multiple Interfaces
port_start = port.split('-')[0]
port_end = port.split('-')[1]
if len(port_start) > 1:
fromPort = port_start
if len(port_end) > 1:
toPort = port_end
if len(port_start) == 1:
fromPort = port_start
port_start = '0' + port_start
if len(port_end) == 1:
toPort = port_end
port_end = '0' + port_end
port = port_start + '-' + port_end
port_settings = {}
port_settings['toPort'] = toPort
port_settings['fromPort'] = fromPort
port_settings['blockDescription'] = ipg['description']
port_settings['lspDescription'] = 'P{0}-{1}'.format(port, ipg['description'])
port_settings['block'] = ipg['ports']
if ipg['vpc'] == 'YES':
# Build IPG Name
node_2 = ipg['node_2']
ipg_name = '{0}{1}-VPC-{2}-{3}-P{4}_IPG'.format(environment, ipg_prefix, node_1, node_2,
port)
port_settings['ipg'] = ipg_name
port_settings['ipgPrefix'] = 'accbundle'
port_settings['lsp'] = 'VPC-{0}-{1}_LSP'.format(node_1, node_2)
ipg_settings = {}
if ipg['vmm']:
ipg_settings['aep'] = 'uni/infra/attentp-{0}{1}-HYPERVISOR_AEP'.format(ipg['environment'], ipg_prefix)
else:
ipg_settings['aep'] = 'uni/infra/attentp-{0}{1}-ACCESS_AEP'.format(
ipg['environment'], ipg_prefix)
ipg_settings['name'] = ipg_name
ipg_settings['speed'] = '{0}-AUTO_POL'.format(ipg['speed'])
ipg_settings['portChannelPolicy'] = ipg['port_channel_policy']
# Add port & ipg settings to item.
ipg['portSettings'] = port_settings
ipg['ipgSettings'] = ipg_settings
fabric_ipg_list = []
for fabric_ipg_name in get_fabric_vpc_ipgs_response[1]['imdata']:
fabric_ipg_list.append(fabric_ipg_name['infraAccBndlGrp']['attributes']['name'])
if ipg_name in fabric_ipg_list:
ipg['presant'] = True
output_log.append({'NotificationsWarning': "Line: {0} {1} already exists on the fabric and won't be created".format(str(ipg['line']), ipg_name)})
else:
output_log.append({'Notifications': "Line: {0} {1} will be created".format(str(ipg['line']), ipg_name)})
if ipg['vpc'] == 'NO':
# Set IPG to access (default used for all non VPC ports).
ipg_name = '{0}{1}-SVR-ACCESS-{2}_IPG'.format(environment, ipg_prefix, ipg['speed'] )
port_settings['ipgPrefix'] = 'accportgrp'
port_settings['ipg'] = ipg_name
port_settings['lsp'] = 'LFS{0}_LSP'.format(node_1)
ipg_settings = {}
ipg_settings['name'] = ipg_name
# Add port & ipg settings to item.
ipg['portSettings'] = port_settings
ipg['ipgSettings'] = ipg_settings
fabric_ipg_list = []
for fabric_ipg_name in get_fabric_ipgs_response[1]['imdata']:
fabric_ipg_list.append(fabric_ipg_name['infraAccPortGrp']['attributes']['name'])
if ipg_name in fabric_ipg_list:
ipg['presant'] = True
else:
error = True
accessIpg = False
if not accessIpg:
output_log.append({'Errors': 'Unable to locate Access IPG on fabric. IPG Name: {0}'.format(ipg_name)})
# Checking if VPC domain are correct.
if not error:
output_log.append({'Headers': 'Checking VPC Pairs.'})
get_vpc_domain_response = get_vpc_domain(base_url, apic_cookie, headers, output_log)
if get_vpc_domain_response[0]:
output_log = get_vpc_domain_response[1]
error = True
else:
vpc_list = []
for vpc in get_vpc_domain_response[1]['imdata']:
vpc_nodes = []
vpc_name = vpc['fabricExplicitGEp']['attributes']['name']
# Get VPC Domain Details
get_vpc_detail_response = get_vpc_domain_detail(base_url, apic_cookie, headers, output_log,
vpc_name)
if get_vpc_detail_response[0]:
output_log = get_vpc_detail_response[1]
error = True
else:
for node_detail in get_vpc_detail_response[1]['imdata']:
if 'fabricNodePEp' in node_detail:
node_id = int(node_detail['fabricNodePEp']['attributes']['id'])
vpc_nodes.append(node_id)
# Sort list so lowest node ID is 1st.
vpc_nodes = sorted(vpc_nodes)
vpc_list.append(vpc_nodes)
for ipg in ipg_list:
if ipg['vpc'] == 'YES':
form_vpc = [int(ipg['node_1']), int(ipg['node_2'])]
if sorted(form_vpc) not in vpc_list:
error = True
output_log.append({'Errors': 'Line: {0} Node: {1} & {2} not configured for VPC.'.format(str(ipg['line']), ipg['node_1'], ipg['node_2'])})
# Check if ports are already in use.
if not error:
output_log.append({'NotificationsSuccess': "VPC's validated successfully"})
output_log.append({'Headers': 'Checking interface availability.'})
for ipg in ipg_list:
node1 = ipg['node_1']
if ipg['vpc'] == 'YES':
node2 = ipg['node_2']
# Format the port
port = ipg['ports'].split('/')[-1]
if '-' in port:
# format for multiple Interfaces
start_card = ipg['ports'].split('/')[0]
end_card = ipg['ports'].split('/')[0]
start_port = port.split('-')[0]
end_port = port.split('-')[1]
else:
start_card = ipg['ports'].split('/')[0]
end_card = ipg['ports'].split('/')[0]
start_port = port
end_port = port
# Get port details from VPC LSP
vpc = True
get_lsp_detail_response = get_lsp_detail(base_url, apic_cookie, headers, output_log, vpc, node1, node2)
if get_lsp_detail_response[0]:
output_log = get_lsp_detail_response[1]
error = True
else:
for lsp_detail in get_lsp_detail_response[1]['imdata']:
if 'infraHPortS' in lsp_detail:
# Get Port details
dn = lsp_detail['infraHPortS']['attributes']['dn']
get_port_detail_response = get_port_detail(base_url, apic_cookie, headers,
output_log, dn)
if get_port_detail_response[0]:
output_log = get_port_detail_response[1]
error = True
else:
for port_detail in get_port_detail_response[1]['imdata']:
if 'infraPortBlk' in port_detail:
fromCard = port_detail['infraPortBlk']['attributes']['fromCard']
fromPort = port_detail['infraPortBlk']['attributes']['fromPort']
toCard = port_detail['infraPortBlk']['attributes']['toCard']
toPort = port_detail['infraPortBlk']['attributes']['toPort']
if 'infraRsAccBaseGrp' in port_detail:
excel_port = ipg['ports'].split('/')[-1]
# Format the port
if len(excel_port) == 1:
excel_port = '0' + excel_port
if '-' in excel_port:
# format for multiple Interfaces
port_start = excel_port.split('-')[0]
port_end = excel_port.split('-')[1]
if len(port_start) == 1:
port_start = '0' + port_start
if len(port_end) == 1:
port_end = '0' + port_end
excel_port = port_start + '-' + port_end
ipg_name = ipg['ipgSettings']['name']
fabric_ipg_name = \
port_detail['infraRsAccBaseGrp']['attributes']['tDn'].split(
'accbundle-')[-1]
if ipg_name != fabric_ipg_name:
if start_card == fromCard and start_port == fromPort and end_card == toCard and end_port == toPort:
error = True
output_log.append({'Errors': 'Line: ' + str(
ipg[
'line']) + ' IPG Name missmatch between the Workbook and Fabric. ' + ipg_name + ' & ' + fabric_ipg_name})
if ipg_name == fabric_ipg_name:
if start_card == fromCard and start_port == fromPort and end_card == toCard and end_port == toPort:
ipg['presant'] = True
ipg['lsp_mapped'] = True
output_log.append({'NotificationsWarning': 'Line: ' + str(
ipg[
'line']) + ' ports already provisioned, no IPG will be configured but any additional EPGs will be pusshed'})
# Get port details from node_1 LSP
vpc = False
nonvpc_node_1 = ipg['node_1']
nonvpc_node_2 = ''
get_lsp_detail_response_node1 = get_lsp_detail(base_url, apic_cookie, headers, output_log, vpc,
nonvpc_node_1, nonvpc_node_2)
if get_lsp_detail_response_node1[0]:
output_log = get_lsp_detail_response_node1[1]
error = True
else:
for lsp_detail in get_lsp_detail_response_node1[1]['imdata']:
if 'infraHPortS' in lsp_detail:
# Get Port details
dn = lsp_detail['infraHPortS']['attributes']['dn']
get_port_detail_response = get_port_detail(base_url, apic_cookie, headers,
output_log, dn)
if get_port_detail_response[0]:
output_log = get_port_detail_response[1]
error = True
else:
for port_detail in get_port_detail_response[1]['imdata']:
if 'infraPortBlk' in port_detail:
fromCard = port_detail['infraPortBlk']['attributes']['fromCard']
fromPort = port_detail['infraPortBlk']['attributes']['fromPort']
toCard = port_detail['infraPortBlk']['attributes']['toCard']
toPort = port_detail['infraPortBlk']['attributes']['toPort']
if start_card == fromCard and start_port == fromPort and end_card == toCard and end_port == toPort:
error = True
output_log.append({'Errors': 'Line: ' + str(ipg[
'line']) + ' ports already provisioned as non VPC port on LFS' + nonvpc_node_1})
nonvpc_node_1 = ipg['node_2']
get_lsp_detail_response_node2 = get_lsp_detail(base_url, apic_cookie, headers, output_log, vpc,
nonvpc_node_1, nonvpc_node_2)
if get_lsp_detail_response_node2[0]:
output_log = get_lsp_detail_response_node2[1]
error = True
else:
for lsp_detail in get_lsp_detail_response_node2[1]['imdata']:
if 'infraHPortS' in lsp_detail:
# Get Port details
dn = lsp_detail['infraHPortS']['attributes']['dn']
get_port_detail_response = get_port_detail(base_url, apic_cookie, headers,
output_log, dn)
if get_port_detail_response[0]:
output_log = get_port_detail_response[1]
error = True
else:
for port_detail in get_port_detail_response[1]['imdata']:
if 'infraPortBlk' in port_detail:
fromCard = port_detail['infraPortBlk']['attributes']['fromCard']
fromPort = port_detail['infraPortBlk']['attributes']['fromPort']
toCard = port_detail['infraPortBlk']['attributes']['toCard']
toPort = port_detail['infraPortBlk']['attributes']['toPort']
if start_card == fromCard and start_port == fromPort and end_card == toCard and end_port == toPort:
error = True
output_log.append({'Errors': 'Line: ' + str(
ipg[
'line']) + ' ports already provisioned as non VPC port on LFS' + nonvpc_node_1})
if ipg['vpc'] == 'NO':
# Format the port
port = ipg['ports'].split('/')[-1]
if '-' in port:
# format for multiple Interfaces
start_card = ipg['ports'].split('/')[0]
end_card = ipg['ports'].split('/')[0]
start_port = port.split('-')[0]
end_port = port.split('-')[1]
else:
start_card = ipg['ports'].split('/')[0]
end_card = ipg['ports'].split('/')[0]
start_port = port
end_port = port
# Get port details from node_1 LSP
vpc = False
nonvpc_node_1 = node1
nonvpc_node_2 = ''
get_lsp_detail_response = get_lsp_detail(base_url, apic_cookie, headers, output_log, vpc,
nonvpc_node_1, nonvpc_node_2)
if get_lsp_detail_response[0]:
output_log = get_lsp_detail_response[1]
error = True
else:
for lsp_detail in get_lsp_detail_response[1]['imdata']:
if 'infraHPortS' in lsp_detail:
# Get Port details
dn = lsp_detail['infraHPortS']['attributes']['dn']
get_port_detail_response = get_port_detail(base_url, apic_cookie, headers,
output_log, dn)
if get_port_detail_response[0]:
output_log = get_port_detail_response[1]
error = True
else:
for port_detail in get_port_detail_response[1]['imdata']:
if 'infraPortBlk' in port_detail:
fromCard = port_detail['infraPortBlk']['attributes']['fromCard']
fromPort = port_detail['infraPortBlk']['attributes']['fromPort']
toCard = port_detail['infraPortBlk']['attributes']['toCard']
toPort = port_detail['infraPortBlk']['attributes']['toPort']
if start_card == fromCard and start_port == fromPort and end_card == toCard and end_port == toPort:
ipg['presant'] = True
ipg['lsp_mapped'] = True
output_log.append({'NotificationsWarning': 'Line: {0} ports already provisioned, no IPG will be configured but any additional EPGs will be pusshed'.format(str(ipg['line']))})
# Check if EPGs are created.
if not error:
output_log.append({'Headers': "Checking if EPG's exist."})
get_all_epg_response = get_all_epgs(base_url, apic_cookie, headers, output_log)
if get_all_epg_response[0]:
output_log = get_all_epg_response[1]
error = True
else:
epg_list = get_all_epg_response[1]['imdata']
# build epg list
for ipg in ipg_list:
for key in ipg['epg_list']:
if key is None:
continue
else:
if key.upper() not in (s['fvAEPg']['attributes']['name'].upper() for s in epg_list):
error = True
output_log.append({'Errors': '{0} EPG not presant in fabric.'.format(key)})
if not error:
output_log.append({'NotificationsSuccess': "EPG's validated successfully"})
else:
output_log.append({'Errors': 'Failed to connect to apic.'})
return output_log, ipg_list
@shared_task
def ipg_deployment_post(ipg_list, location, url_dict, username, password):
error = False
base_url = url_dict[location]
output_log = []
headers = {'content-type': 'application/json'}
# --------------------------------------------------------------------------#
# Begin Configuration
# --------------------------------------------------------------------------#
output_log.append({'Headers': 'Starting IPG provisioning.'})
output_log.append({'Headers': 'Connecting to APIC'})
apic_cookie = APIC_LOGIN(base_url, username, password)
if apic_cookie:
output_log.append({'Notifications': 'Successfully generated authentication cookie'})
output_log.append({'Headers': "Creating IPG's"})
for ipg in ipg_list:
# Create new VPC IPGs
if ipg['vpc'] == 'YES' and not ipg['presant']:
output_log.append({'Headers2': "Creating IPG's for line: {0}".format(ipg['line'])})
# Post call to create IPG's
post_create_ipg_response = post_create_ipg(base_url, apic_cookie, headers, output_log, ipg['ipgSettings'])
error = post_create_ipg_response[0]
output_log = post_create_ipg_response[1]
if not error:
# Map IPG to LSP
output_log.append({'Headers': "Mapping IPG's to Interface profiles"})
for ipg in ipg_list:
if not ipg['lsp_mapped']:
output_log.append({'Headers2': "Mapping LSP's for line: {0}".format(ipg['line'])})
if ipg['vpc'] == 'YES':
# Post call to create switch profile ports.
post_create_lsp_port_response = post_create_lsp_port(base_url, apic_cookie, headers, output_log,
ipg['portSettings'])
error = post_create_lsp_port_response[0]
output_log = post_create_lsp_port_response[1]
if ipg['vpc'] == 'NO':
# Post call to create switch profile ports.
post_create_lsp_port_response = post_create_lsp_port(base_url, apic_cookie, headers, output_log,
ipg['portSettings'])
error = post_create_lsp_port_response[0]
output_log = post_create_lsp_port_response[1]
if not error:
output_log.append({'Headers': "Pushing EPG static bindings"})
for ipg in ipg_list:
if ipg['epg_list']:
output_log.append({'Headers2': 'Pushing Bindings for line: {0}'.format(ipg['line'])})
if ipg['vpc'] == 'YES':
# GET EPG DN
for key, value in ipg['epg_list'].items():
if key is None:
continue
else:
epg_dn = get_epg_detail(base_url, apic_cookie, headers, key, output_log)
if epg_dn[0]:
output_log = epg_dn[1]
error = True
else:
epg_dn = epg_dn[1]['imdata'][0]['fvAEPg']['attributes']['dn']
binding_settings = {}
if ipg['mode'] == 'TRUNK':
binding_settings['mode'] = 'regular'
if ipg['mode'] == 'ACCESS':
binding_settings['mode'] = 'native'
binding_settings['vpc'] = True
binding_settings['encap'] = str(value)
binding_settings['tDn'] = epg_dn
binding_settings['epg_name'] = key
binding_settings['ipg_name'] = ipg['ipgSettings']['name']
binding_settings['lsptDn'] = 'topology/pod-1/protpaths-{0}-{1}/pathep-[{2}]'.format\
(ipg['node_1'], ipg['node_2'], ipg['ipgSettings']['name'])
create_binding_response = post_create_static_binding(base_url, apic_cookie,
headers, output_log,
binding_settings)
error = create_binding_response[0]
output_log = create_binding_response[1]
if ipg['vpc'] == 'NO':
# GET EPG DN
for key, value in ipg['epg_list'].items():
if key is None:
continue
else:
epg_dn = get_epg_detail(base_url, apic_cookie, headers, key, output_log)
if epg_dn[0]:
output_log = epg_dn[1]
error = True
else:
epg_dn = epg_dn[1]['imdata'][0]['fvAEPg']['attributes']['dn']
binding_settings = {}
if ipg['mode'] == 'TRUNK':
binding_settings['mode'] = 'regular'
if ipg['mode'] == 'ACCESS':
binding_settings['mode'] = 'native'
binding_settings['vpc'] = True
binding_settings['encap'] = str(value)
binding_settings['tDn'] = epg_dn
binding_settings['epg_name'] = key
binding_settings['ipg_name'] = ipg['ipgSettings']['name']
binding_settings['lsptDn'] = 'topology/pod-1/paths-{0}/pathep-[eth{1}]'.format\
(ipg['node_1'], ipg['ports'])
create_binding_response = post_create_static_binding(base_url, apic_cookie,
headers, output_log,
binding_settings)
error = create_binding_response[0]
output_log = create_binding_response[1]
else:
output_log.append({'Errors': 'Failed to connect to apic.'})
return output_log
def CONTRACT_DEPLOYMENT_EXCEL_OPEN_WORKBOOK(WORKBOOK, LOCATION):
WB = openpyxl.load_workbook(WORKBOOK, data_only=True)
if LOCATION == 'UKDC1':
PY_WS = WB['ACI_DC1']
elif LOCATION == 'UKDC2':
PY_WS = WB['ACI_DC2']
elif LOCATION == 'LAB':
PY_WS = WB['ACI_LAB']
SERVICE_LIST = []
RULE_LIST = []
INDEX = 1
# Loops through the rows in the worksheet to build contract information
for row in PY_WS.iter_rows(min_row=2, max_col=10):
CONSUMER_IP_LIST = []
PROVIDER_IP_LIST = []
CONTRACT_NAME = row[2].value.upper()
if row[8].value:
CONSUMER_EPG = row[8].value.upper()
else:
CONSUMER_EPG = 'BLANK'
if row[5].value:
PROVIDER_EPG = row[5].value.upper()
else:
PROVIDER_EPG = 'BLANK'
if row[9].value:
CONSUMER_IP_LIST = row[9].value.split()
else:
pass
if row[6].value:
PROVIDER_IP_LIST = row[6].value.split()
else:
pass
if row[3].value:
SERVICE_LIST = row[3].value.upper().split()
if row[7].value:
CONSUMER_L3OUT = row[7].value.upper()
else:
CONSUMER_L3OUT = 'INTERNAL'
if row[4].value:
PROVIDER_L3OUT = row[4].value.upper()
else:
PROVIDER_L3OUT = 'INTERNAL'
INDEX += 1
RULE_LIST.append(
{'LINE': INDEX, 'PROVIDER_L3OUT': PROVIDER_L3OUT, 'CONSUMER_L3OUT': CONSUMER_L3OUT, 'NAME': CONTRACT_NAME,
'CONSUMER_EPG': CONSUMER_EPG, 'CONSUMER_IP': CONSUMER_IP_LIST, 'PROVIDER_EPG': PROVIDER_EPG,
'PROVIDER_IP': PROVIDER_IP_LIST, 'SERVICE': SERVICE_LIST})
SERVICE_LIST = []
return RULE_LIST
def external_epg_open_yaml(file, location):
data = yaml.safe_load(file)
epg_list = []
index = 1
for lines in data:
# Objects for combined EPG/Contract Form
if 'contract' in lines:
if 'provider_l3out' in lines:
provider_l3out = lines['provider_l3out'].upper()
else:
provider_l3out = 'INTERNAL'
if 'consumer_l3out' in lines:
consumer_l3out = lines['consumer_l3out'].upper()
else:
consumer_l3out = 'INTERNAL'
if 'consumer_epg' in lines:
consumer_epg = lines['consumer_epg'].upper()
else:
consumer_epg = 'BLANK'
if 'consumer_ip' in lines:
consumer_ip = lines['consumer_ip']
i = 0
for ip in consumer_ip:
if len(str(ip).split('/')) <= 1:
subnet = '{0}/32'.format(str(ip))
consumer_ip[i] = subnet
i += 1
else:
consumer_ip = []
if 'provider_epg' in lines:
provider_epg = lines['provider_epg'].upper()
else:
provider_epg = 'BLANK'
if 'provider_ip' in lines:
provider_ip = lines['provider_ip']
i = 0
for ip in provider_ip:
if len(str(ip).split('/')) <= 1:
subnet = '{0}/32'.format(str(ip))
consumer_ip[i] = subnet
i += 1
else:
provider_ip = []
epg_list.append({'LINE': index, 'PROVIDER_L3OUT': provider_l3out, 'CONSUMER_L3OUT': consumer_l3out,
'CONSUMER_EPG': consumer_epg, 'CONSUMER_IP': consumer_ip,
'PROVIDER_EPG': provider_epg, 'PROVIDER_IP': provider_ip})
index += 1
# Objects for combined EPG Only Form
if 'l3out' in lines:
# Only use Provicer settings to catch ant VIP requirements.
consumer_ip = []
consumer_l3out = 'INTERNAL'
consumer_epg = 'BLANK'
for items in lines['l3out']:
for epgs in items['epg']:
provider_l3out = items['name'].upper()
provider_epg = epgs['name'].upper()
if 'subnets' in epgs:
provider_ip = epgs['subnets']
i = 0
for ip in provider_ip:
if len(str(ip).split('/')) <= 1:
subnet = '{0}/32'.format(str(ip))
provider_ip[i] = subnet
i += 1
else:
provider_ip = []
epg_list.append({'LINE': index, 'PROVIDER_L3OUT': provider_l3out, 'CONSUMER_L3OUT': consumer_l3out,
'CONSUMER_EPG': consumer_epg, 'CONSUMER_IP': consumer_ip,
'PROVIDER_EPG': provider_epg, 'PROVIDER_IP': provider_ip})
index += 1
return epg_list
def EXTERNAL_EPG_EXCEL_OPEN_WORKBOOK(WORKBOOK, LOCATION):
WB = openpyxl.load_workbook(WORKBOOK, data_only=True)
if LOCATION == 'UKDC1':
PY_WS = WB['ACI_DC1']
elif LOCATION == 'UKDC2':
PY_WS = WB['ACI_DC2']
elif LOCATION == 'LAB':
PY_WS = WB['ACI_LAB']
RULE_LIST = []
INDEX = 1
# Loops through the rows in the worksheet to build contract information
for row in PY_WS.iter_rows(min_row=2, max_col=10):
CONSUMER_IP_LIST = []
PROVIDER_IP_LIST = []
if row[8].value:
CONSUMER_EPG = row[8].value.upper()
else:
CONSUMER_EPG = 'BLANK'
if row[5].value:
PROVIDER_EPG = row[5].value.upper()
else:
PROVIDER_EPG = 'BLANK'
if row[9].value:
CONSUMER_IP_LIST = row[9].value.split()
i = 0
for IP in CONSUMER_IP_LIST:
if len(IP.split('/')) <= 1:
IP_SUBNET = IP + '/32'
CONSUMER_IP_LIST[i] = IP_SUBNET
i = i + 1
else:
pass
if row[6].value:
PROVIDER_IP_LIST = row[6].value.split()
i = 0
for IP in PROVIDER_IP_LIST:
if len(IP.split('/')) <= 1:
IP_SUBNET = IP + '/32'
PROVIDER_IP_LIST[i] = IP_SUBNET
i = i + 1
else:
pass
if row[7].value:
CONSUMER_L3OUT = row[7].value.upper()
else:
CONSUMER_L3OUT = 'INTERNAL'
if row[4].value:
PROVIDER_L3OUT = row[4].value.upper()
else:
PROVIDER_L3OUT = 'INTERNAL'
INDEX += 1
RULE_LIST.append({'LINE': INDEX, 'PROVIDER_L3OUT': PROVIDER_L3OUT, 'CONSUMER_L3OUT': CONSUMER_L3OUT,
'CONSUMER_EPG': CONSUMER_EPG, 'CONSUMER_IP': CONSUMER_IP_LIST,
'PROVIDER_EPG': PROVIDER_EPG, 'PROVIDER_IP': PROVIDER_IP_LIST})
return RULE_LIST
@shared_task
def EXTERNAL_EPG_VALIDATION(RULE_LIST, location, url_dict, username, password):
OUTPUT_LOG = []
DISPLAY_LIST = []
TENANT_LIST = ['RED', 'GREEN', 'BLUE']
ERROR = False
TENANT = 'common'
BASE_URL = url_dict[location]
OUTPUT_LOG.append({'Headers': 'Validating EPG names in Workbook.'})
for rules in RULE_LIST:
if rules['CONSUMER_EPG'] != 'BLANK' and rules['CONSUMER_L3OUT'] != 'INTERNAL':
try:
if len(rules['CONSUMER_EPG'].split('_')) > 2:
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
elif rules['CONSUMER_EPG'].split('_')[1].upper() != 'EPG':
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
elif rules['CONSUMER_EPG'].split('-')[0].upper() not in TENANT_LIST:
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
elif rules['CONSUMER_L3OUT'].split('_')[0].endswith('CLOUD'):
continue
# TEMP FIX FOR BLUE INET UNTIL RENAME
elif rules['CONSUMER_L3OUT'] in ['BLUE-DC1-INET_L3O', 'BLUE-DC2-INET_L3O']:
continue
elif not rules['CONSUMER_EPG'].split('_')[0].startswith(rules['CONSUMER_EPG'].split('_')[0]):
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
else:
pass
except:
ERROR = True
OUTPUT_LOG.append({'Errors': rules['CONSUMER_EPG'] + ' does not conform to the naming standard'})
if rules['PROVIDER_EPG'] != 'BLANK' and rules['PROVIDER_L3OUT'] != 'INTERNAL':
try:
if len(rules['PROVIDER_EPG'].split('_')) > 2:
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
elif rules['PROVIDER_EPG'].split('_')[1].upper() != 'EPG':
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
elif rules['PROVIDER_EPG'].split('-')[0].upper() not in TENANT_LIST:
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
elif rules['PROVIDER_L3OUT'].split('_')[0].endswith('CLOUD'):
continue
# TEMP FIX FOR BLUE INET UNTIL RENAME
elif rules['PROVIDER_L3OUT'] in ['BLUE-DC1-INET_L3O', 'BLUE-DC2-INET_L3O']:
continue
elif not rules['PROVIDER_EPG'].split('_')[0].startswith(rules['PROVIDER_L3OUT'].split('_')[0]):
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
else:
pass
except:
ERROR = True
OUTPUT_LOG.append({'Errors': rules['PROVIDER_EPG'] + ' does not conform to the naming standard'})
else:
pass
DISPLAY_SET = set(DISPLAY_LIST)
for contracts in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'EPG "' + contracts + '" does not conform to the naming standard'})
DISPLAY_LIST = []
if not ERROR:
OUTPUT_LOG.append({'NotificationsSuccess': 'EPG formatting validated successfully'})
OUTPUT_LOG.append({'Headers': 'Validating IP addresses'})
for addresses in RULE_LIST:
if len(addresses['CONSUMER_IP']) >= 1:
for subnets in addresses['CONSUMER_IP']:
try:
network = ipaddress.IPv4Network(subnets)
except ValueError:
ERROR = True
OUTPUT_LOG.append({'Errors': subnets + ' Is not a valid IPv4 address.'})
if len(addresses['PROVIDER_IP']) >= 1:
for subnets in addresses['PROVIDER_IP']:
try:
network = ipaddress.IPv4Network(subnets)
except ValueError:
ERROR = True
OUTPUT_LOG.append({'Errors': subnets + ' Is not a valid IPv4 address.'})
if ERROR:
OUTPUT_LOG.append({'Errors': 'Errors found in IP validation'})
else:
OUTPUT_LOG.append({'NotificationsSuccess': 'IP validation successful'})
OUTPUT_LOG.append({'Headers': 'Connecting to APIC'})
# Login to fabric
APIC_COOKIE = APIC_LOGIN(BASE_URL, username, password)
if APIC_COOKIE:
OUTPUT_LOG.append({'Notifications': 'Successfully generated authentication cookie'})
# Search for L3out and build URL to add IP's
OUTPUT_LOG.append({'Headers': 'Validating L3Out Names'})
L3OUT_LIST = []
for rules in RULE_LIST:
if rules['CONSUMER_L3OUT'] == 'INTERNAL':
pass
else:
L3OUT_NAME = rules['CONSUMER_L3OUT']
L3OUT_SEARCH_RESPONSE = L3OUT_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, HEADERS)
if int(L3OUT_SEARCH_RESPONSE[0]['totalCount']) == 1:
if rules['CONSUMER_L3OUT'] == L3OUT_SEARCH_RESPONSE[0]['imdata'][0]['l3extOut']['attributes'][
'name']:
pass
else:
ERROR = True
else:
L3OUT_LIST.append(L3OUT_NAME)
ERROR = True
for rules in RULE_LIST:
if rules['PROVIDER_L3OUT'] == 'INTERNAL':
pass
else:
L3OUT_NAME = rules['PROVIDER_L3OUT']
L3OUT_SEARCH_RESPONSE = L3OUT_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, HEADERS)
if int(L3OUT_SEARCH_RESPONSE[0]['totalCount']) == 1:
if rules['PROVIDER_L3OUT'] == L3OUT_SEARCH_RESPONSE[0]['imdata'][0]['l3extOut']['attributes'][
'name']:
pass
else:
ERROR = True
else:
L3OUT_LIST.append(L3OUT_NAME)
ERROR = True
L3OUT_SET = set(L3OUT_LIST)
for l3out in L3OUT_SET:
OUTPUT_LOG.append({'Errors': 'L3Out: ' + l3out + ' Does not exist, please check naming.'})
L3OUT_LIST = []
if ERROR:
OUTPUT_LOG.append({'Errors': 'Errors found in L3Out validation'})
else:
OUTPUT_LOG.append({'NotificationsSuccess': 'L3Out validation successful'})
# Check if IP already exists in Same L3Out or same VRF
OUTPUT_LOG.append({'Headers': 'Checking if IP currently exists within VRF'})
# Get L3out VRF
for rules in RULE_LIST:
OUTPUT_LOG.append({'Headers2': 'Checking subnets for line: ' + str(rules['LINE'])})
if rules['CONSUMER_L3OUT'] != 'INTERNAL' and rules['CONSUMER_EPG'] != 'BLANK':
L3OUT_NAME = rules['CONSUMER_L3OUT']
L3OUT_SEARCH_RESPONSE = L3OUT_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, HEADERS)
L3OUT_DATA = L3OUT_SEARCH_RESPONSE[1]['imdata']
L3OUT_SUBNETS = []
# Loop through the VRF pull out all other L3Outs and add any l3extsubnet to a list
for key in L3OUT_DATA:
# For Python 3+
if 'l3extRsEctx' in key:
# For Python 2.7
# if key.keys() == ['l3extRsEctx']:
VRF_DN = key['l3extRsEctx']['attributes']['tDn']
VRF_SEARCH_RESPONSE = VRF_SEARCH(BASE_URL, APIC_COOKIE, VRF_DN, HEADERS)
for vrf_l3o in VRF_SEARCH_RESPONSE['imdata']:
# For Python 3+
if 'fvRtEctx' in vrf_l3o:
# For Python 2.7
# if vrf_l3o.keys() == ['fvRtEctx']:
L3OUT_DN = vrf_l3o['fvRtEctx']['attributes']['tDn']
SUBNET_SEARCH_RESPONSE = SUBNET_SEARCH(BASE_URL, APIC_COOKIE, L3OUT_DN, HEADERS)
for subnets in SUBNET_SEARCH_RESPONSE['imdata']:
L3OUT_SUBNETS.append(subnets['l3extSubnet']['attributes']['ip'])
EXISTING_SUBNET = subnets['l3extSubnet']['attributes']['ip']
EXISTING_L3OUT = subnets['l3extSubnet']['attributes']['dn'].split('/')[2][
4:]
EXISTING_EPG = subnets['l3extSubnet']['attributes']['dn'].split('/')[3][6:]
SCOPE = subnets['l3extSubnet']['attributes']['scope'].split(',')
if EXISTING_SUBNET in rules['CONSUMER_IP']:
if 'import-security' in SCOPE:
if EXISTING_EPG == rules['CONSUMER_EPG']:
rules['CONSUMER_IP'].remove(EXISTING_SUBNET)
else:
OUTPUT_LOG.append({
'Errors': EXISTING_SUBNET + ' already exists within ' + EXISTING_L3OUT + ' under EPG ' + EXISTING_EPG + ' no subnet configuration for this epg will be pushed.'})
ERROR = True
rules['CONSUMER_IP'].remove(EXISTING_SUBNET)
else:
for rule_subnet in rules['CONSUMER_IP']:
if IPNetwork(rule_subnet) in IPNetwork(EXISTING_SUBNET):
if int(EXISTING_SUBNET.split('/')[
1]) >= 20 and 'import-security' in SCOPE:
OUTPUT_LOG.append({
'Errors': rule_subnet + ' already exists within ' + EXISTING_L3OUT + ' under EPG ' + EXISTING_EPG + ' inside ' + EXISTING_SUBNET})
ERROR = True
rules['CONSUMER_IP'].remove(rule_subnet)
if len(rules['CONSUMER_IP']) >= 1:
OUTPUT_LOG.append({'Notifications': 'The Following subnets will be added to the EPG: ' +
rules['CONSUMER_EPG']})
OUTPUT_LOG.append({'Notifications': str(rules['CONSUMER_IP'])})
else:
OUTPUT_LOG.append(
{'Notifications': 'No subnets will be added to EPG: ' + rules['CONSUMER_EPG']})
if rules['PROVIDER_L3OUT'] != 'INTERNAL' and rules['PROVIDER_EPG'] != 'BLANK':
L3OUT_NAME = rules['PROVIDER_L3OUT']
L3OUT_SEARCH_RESPONSE = L3OUT_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, HEADERS)
L3OUT_DATA = L3OUT_SEARCH_RESPONSE[1]['imdata']
L3OUT_SUBNETS = []
# Loop through the VRF pull out all other L3Outs and add any l3extsubnet to a list
for key in L3OUT_DATA:
# For Python 3+
if 'l3extRsEctx' in key:
# For Python 2.7
# if key.keys() == ['l3extRsEctx']:
VRF_DN = key['l3extRsEctx']['attributes']['tDn']
VRF_SEARCH_RESPONSE = VRF_SEARCH(BASE_URL, APIC_COOKIE, VRF_DN, HEADERS)
for vrf_l3o in VRF_SEARCH_RESPONSE['imdata']:
# For Python 3+
if 'fvRtEctx' in vrf_l3o:
# For Python 2.7
# if vrf_l3o.keys() == ['fvRtEctx']:
L3OUT_DN = vrf_l3o['fvRtEctx']['attributes']['tDn']
SUBNET_SEARCH_RESPONSE = SUBNET_SEARCH(BASE_URL, APIC_COOKIE, L3OUT_DN, HEADERS)
for subnets in SUBNET_SEARCH_RESPONSE['imdata']:
L3OUT_SUBNETS.append(subnets['l3extSubnet']['attributes']['ip'])
EXISTING_SUBNET = subnets['l3extSubnet']['attributes']['ip']
EXISTING_L3OUT = subnets['l3extSubnet']['attributes']['dn'].split('/')[2][
4:]
EXISTING_EPG = subnets['l3extSubnet']['attributes']['dn'].split('/')[3][6:]
SCOPE = subnets['l3extSubnet']['attributes']['scope'].split(',')
if EXISTING_SUBNET in rules['PROVIDER_IP']:
if 'import-security' in SCOPE:
if EXISTING_EPG == rules['PROVIDER_EPG']:
rules['PROVIDER_IP'].remove(EXISTING_SUBNET)
else:
OUTPUT_LOG.append({
'Errors': EXISTING_SUBNET + ' already exists within ' + EXISTING_L3OUT + ' under EPG ' + EXISTING_EPG + ' no subnet configuration for this epg will be pushed.'})
ERROR = True
rules['PROVIDER_IP'].remove(EXISTING_SUBNET)
else:
for rule_subnet in rules['PROVIDER_IP']:
if IPNetwork(rule_subnet) in IPNetwork(EXISTING_SUBNET):
if int(EXISTING_SUBNET.split('/')[
1]) >= 20 and 'import-security' in SCOPE:
OUTPUT_LOG.append({
'Errors': rule_subnet + ' already exists within ' + EXISTING_L3OUT + ' under EPG ' + EXISTING_EPG + ' inside ' + EXISTING_SUBNET})
ERROR = True
rules['PROVIDER_IP'].remove(rule_subnet)
if len(rules['PROVIDER_IP']) >= 1:
OUTPUT_LOG.append({'Notifications': 'The Following subnets will be added to the EPG: ' +
rules['PROVIDER_EPG']})
OUTPUT_LOG.append({'Notifications': str(rules['PROVIDER_IP'])})
else:
OUTPUT_LOG.append(
{'Notifications': 'No subnets will be added to EPG: ' + rules['PROVIDER_EPG']})
# Search for VIPs
OUTPUT_LOG.append({'Headers': 'Checking if any EPGs are for VIPS'})
for rules in RULE_LIST:
if rules['PROVIDER_EPG'].split('_')[0].endswith('VS') and rules['PROVIDER_L3OUT'].endswith(
'DCI_L3O'):
for subnets in rules['PROVIDER_IP']:
if len(subnets.split('/')) != 0:
subnet = subnets.split('/')[0]
else:
subnet = subnets
if not ipaddress.ip_address(subnet).is_private:
OUTPUT_LOG.append(
{'Notifications': rules['PROVIDER_EPG'] + ' contains a public address.'})
OUTPUT_LOG.append({
'Notifications': subnets + ' will be imported under the DCI and exported under the INET L3Outs'})
elif ipaddress.ip_address(subnet).is_private:
OUTPUT_LOG.append(
{'Notifications': rules['PROVIDER_EPG'] + ' contains a private address.'})
OUTPUT_LOG.append({'Notifications': subnets + ' will be imported under the DCI L3Out'})
else:
OUTPUT_LOG.append({'Errors': 'Unable to connect to APIC.'})
if not ERROR:
OUTPUT_LOG.append({'ValidationSuccess': 'APIC Configuration validated successfully'})
return OUTPUT_LOG
@shared_task
def EXTERNAL_EPG_DEPLOYMENT(RULE_LIST, location, url_dict, username, password):
BASE_URL = url_dict[location]
if location == 'UKDC1':
DC = 'DC1'
elif location == 'UKDC2':
DC = 'DC2'
elif location == 'LAB':
DC = 'DC1'
TENANT = 'common'
OUTPUT_LOG = []
HEADERS = {'content-type': 'application/json'}
# --------------------------------------------------------------------------#
# Begin Configuration
# --------------------------------------------------------------------------#
OUTPUT_LOG.append({'Headers': 'Starting External EPG Deployment.'})
OUTPUT_LOG.append({'Headers': 'Connecting to APIC'})
APIC_COOKIE = APIC_LOGIN(BASE_URL, username, password)
if APIC_COOKIE:
OUTPUT_LOG.append({'Notifications': 'Successfully generated authentication cookie'})
check_i = 0
for rules in RULE_LIST:
check_i = check_i + 1
L3OUT_CONSUME_EPG_CREATED = False
L3OUT_PROVIDE_EPG_CREATED = False
OUTPUT_LOG.append({'Headers2': 'Adding EPGs & Subnets for line: ' + str(rules['LINE'])})
if rules['CONSUMER_L3OUT'] != 'INTERNAL' and rules['CONSUMER_EPG'] != 'BLANK':
EPG_NAME = rules['CONSUMER_EPG']
L3OUT_NAME = rules['CONSUMER_L3OUT']
EXTERNAL_EPG_SEARCH_RESPONSE = EXTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME,
HEADERS)
if int(EXTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
OUTPUT_LOG.append({
'NotificationsWarning': 'EPG: ' + EPG_NAME + ' already exists under ' + L3OUT_NAME + ' and wont be created'})
L3OUT_CONSUME_EPG_CREATED = True
if not L3OUT_CONSUME_EPG_CREATED:
OUTPUT_LOG.append(
{'Notifications': 'Adding External EPG: ' + EPG_NAME + ' TO L3Out: ' + L3OUT_NAME})
EXTERNAL_EPG_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME, HEADERS, OUTPUT_LOG)
# Add subnets to external EPG
if len(rules['CONSUMER_IP']) != 0:
OUTPUT_LOG.append({'Notifications': 'Adding Subnets to External EPG: '})
for IP in rules['CONSUMER_IP']:
# SEARCH TO SEE IF SUBNET ALREADY EXISTS IN EPG:
L3OUT_DN = 'uni/tn-common/out-' + L3OUT_NAME + '/instP-' + EPG_NAME + '/extsubnet-[' + IP + ']'
SUBNET_SEARCH_RESPONSE = SUBNET_SEARCH_EXACT(BASE_URL, APIC_COOKIE, L3OUT_DN, HEADERS)
if int(SUBNET_SEARCH_RESPONSE['totalCount']) == 1:
for subnets in SUBNET_SEARCH_RESPONSE['imdata']:
EXISTING_SUBNET = subnets['l3extSubnet']['attributes']['ip']
SCOPE = subnets['l3extSubnet']['attributes']['scope'].split(',')
if EXISTING_SUBNET == IP:
# IP Already Configured under EPG
pass
else:
SCOPE = 'import-security'
EXTERNAL_EPG_SUBNET_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME, HEADERS, IP,
SCOPE, OUTPUT_LOG)
if rules['PROVIDER_L3OUT'] != 'INTERNAL' and rules['PROVIDER_EPG'] != 'BLANK':
EPG_NAME = rules['PROVIDER_EPG']
L3OUT_NAME = rules['PROVIDER_L3OUT']
EXTERNAL_EPG_SEARCH_RESPONSE = EXTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME,
HEADERS)
if int(EXTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
OUTPUT_LOG.append({
'NotificationsWarning': 'EPG: ' + EPG_NAME + ' already exists under ' + L3OUT_NAME + ' and wont be created'})
L3OUT_PROVIDE_EPG_CREATED = True
if not L3OUT_PROVIDE_EPG_CREATED:
OUTPUT_LOG.append(
{'Notifications': 'Adding External EPG: ' + EPG_NAME + ' TO L3Out: ' + L3OUT_NAME})
EXTERNAL_EPG_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME, HEADERS, OUTPUT_LOG)
# Add subnets to external EPG
if len(rules['PROVIDER_IP']) != 0:
OUTPUT_LOG.append({'Notifications': 'Adding Subnets to External EPG: '})
for IP in rules['PROVIDER_IP']:
# SEARCH TO SEE IF SUBNET ALREADY EXISTS IN EPG:
L3OUT_DN = 'uni/tn-common/out-' + L3OUT_NAME + '/instP-' + EPG_NAME + '/extsubnet-[' + IP + ']'
SUBNET_SEARCH_RESPONSE = SUBNET_SEARCH_EXACT(BASE_URL, APIC_COOKIE, L3OUT_DN, HEADERS)
if int(SUBNET_SEARCH_RESPONSE['totalCount']) == 1:
for subnets in SUBNET_SEARCH_RESPONSE['imdata']:
EXISTING_SUBNET = subnets['l3extSubnet']['attributes']['ip']
SCOPE = subnets['l3extSubnet']['attributes']['scope'].split(',')
if EXISTING_SUBNET == IP:
# IP Already Configured under EPG
pass
else:
if len(IP.split('/')) != 0:
subnet = IP.split('/')[0]
else:
subnet = IP
# Check for VS EPGs
if rules['PROVIDER_EPG'].split('_')[0].endswith('VS') and rules['PROVIDER_L3OUT'].endswith(
'DCI_L3O'):
if not ipaddress.ip_address(subnet).is_private:
# Import Under DCI
SCOPE = 'import-rtctrl,import-security'
L3OUT_NAME = rules['PROVIDER_L3OUT']
EPG_NAME = rules['PROVIDER_EPG']
EXTERNAL_EPG_SUBNET_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME,
HEADERS, IP, SCOPE, OUTPUT_LOG)
# Export Under Inet
SCOPE = 'export-rtctrl'
# Build L3out name for Inet L3Out
# Temp fix for BLUE INET
if rules['PROVIDER_L3OUT'].split('-')[0] == 'BLUE':
L3OUT_NAME = rules['PROVIDER_L3OUT'].split('-')[0] + '-' + DC + '-INET_L3O'
else:
L3OUT_NAME = rules['PROVIDER_L3OUT'].split('-')[0] + '-INET_L3O'
EPG_NAME = L3OUT_NAME.split('_')[0] + '-ROUTING_EPG'
EXTERNAL_EPG_SUBNET_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME,
HEADERS, IP, SCOPE, OUTPUT_LOG)
if ipaddress.ip_address(subnet).is_private:
# Import Under DCI
L3OUT_NAME = rules['PROVIDER_L3OUT']
EPG_NAME = rules['PROVIDER_EPG']
SCOPE = 'import-rtctrl,import-security'
EXTERNAL_EPG_SUBNET_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME,
HEADERS, IP, SCOPE, OUTPUT_LOG)
else:
L3OUT_NAME = rules['PROVIDER_L3OUT']
EPG_NAME = rules['PROVIDER_EPG']
SCOPE = 'import-security'
EXTERNAL_EPG_SUBNET_ADD(BASE_URL, APIC_COOKIE, TENANT, L3OUT_NAME, EPG_NAME, HEADERS,
IP, SCOPE, OUTPUT_LOG)
else:
OUTPUT_LOG.append({'Errors': 'Unable to connect to APIC.'})
return OUTPUT_LOG
@shared_task
def CONTRACT_DEPLOYMENT_VALIDATION(RULE_LIST, location, url_dict, username, password):
CONTRACT_LIST = []
FILTER_LIST = []
DISPLAY_LIST = []
OUTPUT_LOG = []
ERROR = False
HEADERS = {'content-type': 'application/json'}
TENANT_LIST = ['RED', 'GREEN', 'BLUE']
BASE_URL = url_dict[location]
# Validate Contract Name formatting
OUTPUT_LOG.append({'Headers': 'Validating Contract names in Workbook.'})
try:
for rules in RULE_LIST:
if (len(rules['NAME'].split('_'))) > 2:
DISPLAY_LIST.append(rules['NAME'])
ERROR = True
elif rules['NAME'].split('_')[1].upper() != 'GCTR':
DISPLAY_LIST.append(rules['NAME'])
ERROR = True
elif rules['NAME'].split('-')[0].upper() not in TENANT_LIST:
DISPLAY_LIST.append(rules['NAME'])
ERROR = True
else:
pass
DISPLAY_SET = set(DISPLAY_LIST)
for contracts in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'Contract "' + contracts + '" does not conform to the naming standard'})
DISPLAY_LIST = []
except:
OUTPUT_LOG.append({'Errors': 'Errors validating Contract names'})
ERROR = True
if not ERROR:
OUTPUT_LOG.append({'NotificationsSuccess': 'Contract formatting validated successfully'})
OUTPUT_LOG.append({'Headers': 'Validating EPG names in Workbook.'})
for rules in RULE_LIST:
if rules['CONSUMER_EPG'] != 'BLANK':
try:
if len(rules['CONSUMER_EPG'].split('_')) > 2:
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
elif rules['CONSUMER_EPG'].split('_')[1].upper() != 'EPG':
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
elif rules['CONSUMER_EPG'].split('-')[0].upper() not in TENANT_LIST:
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
else:
pass
except:
ERROR = True
OUTPUT_LOG.append(
{'Errors': 'EPG "' + rules['CONSUMER_EPG'] + '" does not conform to the naming standard'})
if rules['PROVIDER_EPG'] != 'BLANK':
try:
if len(rules['PROVIDER_EPG'].split('_')) > 2:
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
elif rules['PROVIDER_EPG'].split('_')[1].upper() != 'EPG':
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
elif rules['PROVIDER_EPG'].split('-')[0].upper() not in TENANT_LIST:
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
else:
pass
except:
ERROR = True
OUTPUT_LOG.append(
{'Errors': 'EPG "' + rules['PROVIDER_EPG'] + '" does not conform to the naming standard'})
DISPLAY_SET = set(DISPLAY_LIST)
for contracts in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'EPG "' + contracts + '" does not conform to the naming standard'})
DISPLAY_LIST = []
if not ERROR:
OUTPUT_LOG.append({'NotificationsSuccess': 'EPG formatting validated successfully'})
OUTPUT_LOG.append({'Headers': 'Validating Contract and EPG locality.'})
for rules in RULE_LIST:
if rules['CONSUMER_EPG'] != 'BLANK':
if rules['CONSUMER_EPG'].split('-')[0].upper() != rules['NAME'].split('-')[0].upper():
DISPLAY_LIST.append(rules['CONSUMER_EPG'])
ERROR = True
if rules['PROVIDER_EPG'] != 'BLANK':
if rules['PROVIDER_EPG'].split('-')[0].upper() != rules['NAME'].split('-')[0].upper():
DISPLAY_LIST.append(rules['PROVIDER_EPG'])
ERROR = True
else:
pass
DISPLAY_SET = set(DISPLAY_LIST)
for contracts in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': contracts + ' and Contract named for different Tenants.'})
DISPLAY_LIST = []
if not ERROR:
OUTPUT_LOG.append({'NotificationsSuccess': 'Contract and EPG locality validated successfully'})
OUTPUT_LOG.append({'Headers': 'Validating Services in Workbook.'})
for rules in RULE_LIST:
for services in rules['SERVICE']:
PROTOCOLS = ['TCP', 'UDP']
try:
value = int(services.split('-')[1])
except:
OUTPUT_LOG.append(
{'Errors': 'Service port not correct format for ' + services + ' on line ' + str(rules['LINE'])})
if services.split('-')[0] not in PROTOCOLS:
OUTPUT_LOG.append({'Errors': 'TCP or UDP not specified for service ' + services})
ERROR = True
elif int(services.split('-')[1]) == 0:
OUTPUT_LOG.append({'Errors': 'Error Port out of range ' + services})
ERROR = True
elif int(services.split('-')[1]) not in range(1, 65536):
OUTPUT_LOG.append({'Errors': 'Error Port out of range ' + services})
ERROR = True
elif len(services.split('-')) == 3:
if int(services.split('-')[2]) not in range(1, 65536):
OUTPUT_LOG.append({'Errors': 'Error Port out of range ' + services})
ERROR = True
else:
pass
if not ERROR:
OUTPUT_LOG.append({'NotificationsSuccess': 'Services validated successfully'})
OUTPUT_LOG.append({'Headers': 'Connecting to APIC'})
APIC_COOKIE = APIC_LOGIN(BASE_URL, username, password)
if APIC_COOKIE:
OUTPUT_LOG.append({'Notifications': 'Successfully generated authentication cookie'})
# Check if Contracts Exist
OUTPUT_LOG.append({'Headers': 'Checking if Contracts exist'})
for rules in RULE_LIST:
CONTRACT_NAME = rules['NAME']
CONTRACT_SEARCH_RESPONSE = CONTRACT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, HEADERS)
if int(CONTRACT_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
CONTRACT_LIST.append(CONTRACT_NAME)
CONTRACT_SET = set(CONTRACT_LIST)
for contracts in CONTRACT_SET:
OUTPUT_LOG.append({'Notifications': 'Contract ' + contracts + ' will be created'})
# Check if Filters Exist
OUTPUT_LOG.append({'Headers': 'Checking if Filters exist'})
for rules in RULE_LIST:
for services in rules['SERVICE']:
FILTER_NAME = services
FILTER_SEARCH_RESPONSE = FILTER_SEARCH(BASE_URL, APIC_COOKIE, FILTER_NAME, HEADERS)
if int(FILTER_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
FILTER_LIST.append(FILTER_NAME)
FILTER_SET = set(FILTER_LIST)
for filters in FILTER_SET:
OUTPUT_LOG.append({'Notifications': 'Filter ' + filters + ' will be created'})
# Check if Filters are applied to contracts
OUTPUT_LOG.append({'Headers': 'Checking if Filters are applied to contracts'})
for rules in RULE_LIST:
# Use the contract search to locate subject
CONTRACT_NAME = rules['NAME']
CONTRACT_SEARCH_RESPONSE = CONTRACT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, HEADERS)
# Validate that a contract can be located
if int(CONTRACT_SEARCH_RESPONSE['totalCount']) == 1:
TENANT = CONTRACT_SEARCH_RESPONSE['imdata'][0]['vzBrCP']['attributes']['dn'].split('/')[1][3:]
CONTRACT_SUBJECT = \
CONTRACT_SEARCH_RESPONSE['imdata'][0]['vzBrCP']['attributes']['dn'].split('/')[2][4:].split(
'_')[0] + '_SBJ'
SUBJECT_SEARCH_RESPONSE = SUBJECT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, TENANT,
CONTRACT_SUBJECT,
HEADERS)
# Add all filters for a subject to a list to be used for comparison.
SUBJECT_FILTERS = []
for filters in SUBJECT_SEARCH_RESPONSE['imdata']:
SUBJECT_FILTERS.append(filters['vzRsSubjFiltAtt']['attributes']['tnVzFilterName'])
# compare list of filters to those already in subject
FILTER_COMPARE = LIST_COMPARE(rules['SERVICE'], SUBJECT_FILTERS)
if len(FILTER_COMPARE[0]) == 0:
pass
elif len(FILTER_COMPARE[0]) > 0:
OUTPUT_LOG.append(
{'Notifications': 'The below filters will be added to contract ' + CONTRACT_NAME})
OUTPUT_LOG.append({'Notifications': FILTER_COMPARE[0]})
else:
ERROR = True
else:
pass
# Check if L3Outs Exist
OUTPUT_LOG.append({'Headers': 'Checking if L3Outs exist'})
for rules in RULE_LIST:
if rules['CONSUMER_L3OUT'] == 'INTERNAL':
pass
else:
L3OUT_NAME = rules['CONSUMER_L3OUT']
L3OUT_SEARCH_RESPONSE = CONTRACT_L3OUT_SEARCH(BASE_URL, APIC_COOKIE, L3OUT_NAME, HEADERS)
if int(L3OUT_SEARCH_RESPONSE['totalCount']) == 1:
if rules['CONSUMER_L3OUT'] == L3OUT_SEARCH_RESPONSE['imdata'][0]['l3extOut']['attributes'][
'name']:
pass
else:
ERROR = True
else:
DISPLAY_LIST.append(L3OUT_NAME)
ERROR = True
for rules in RULE_LIST:
if rules['PROVIDER_L3OUT'] == 'INTERNAL':
pass
else:
L3OUT_NAME = rules['PROVIDER_L3OUT']
L3OUT_SEARCH_RESPONSE = CONTRACT_L3OUT_SEARCH(BASE_URL, APIC_COOKIE, L3OUT_NAME, HEADERS)
if int(L3OUT_SEARCH_RESPONSE['totalCount']) == 1:
if rules['PROVIDER_L3OUT'] == L3OUT_SEARCH_RESPONSE['imdata'][0]['l3extOut']['attributes'][
'name']:
pass
else:
ERROR = True
else:
DISPLAY_LIST.append(L3OUT_NAME)
ERROR = True
DISPLAY_SET = set(DISPLAY_LIST)
for l3out in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'L3Out: ' + l3out + ' Does not exist, please check naming.'})
DISPLAY_LIST = []
if not ERROR:
# Check if External EPGs Exist
OUTPUT_LOG.append({'Headers': 'Checking if External EPGs are created'})
for rules in RULE_LIST:
if rules['CONSUMER_L3OUT'] == 'INTERNAL':
pass
else:
if rules['CONSUMER_EPG'] != 'BLANK':
CONSUMER_L3OUT = rules['CONSUMER_L3OUT']
CONSUMER_EPG = rules['CONSUMER_EPG']
EXTERNAL_EPG_SEARCH_RESPONSE = CONTRACT_EXTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE,
CONSUMER_L3OUT, CONSUMER_EPG,
HEADERS)
if int(EXTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
EPG_NAME = \
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
3][6:]
L3OUT_NAME = \
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
2][4:]
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
1][3:]
if L3OUT_NAME == rules['CONSUMER_L3OUT']:
pass
else:
OUTPUT_LOG.append({
'Errors': 'EPG and L3OUT missmatch with ' + L3OUT_NAME + ' and ' + EPG_NAME + ' dont match value: ' +
rules['CONSUMER_L3OUT']})
else:
DISPLAY_LIST.append(CONSUMER_EPG)
ERROR = True
for rules in RULE_LIST:
PROVIDER_EPG = rules['PROVIDER_EPG']
if rules['PROVIDER_L3OUT'] == 'INTERNAL':
pass
else:
if rules['PROVIDER_EPG'] != 'BLANK':
PROVIDER_EPG = rules['PROVIDER_EPG']
PROVIDER_L3OUT = rules['PROVIDER_L3OUT']
EXTERNAL_EPG_SEARCH_RESPONSE = CONTRACT_EXTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE,
PROVIDER_L3OUT, PROVIDER_EPG,
HEADERS)
if int(EXTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
EPG_NAME = \
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
3][6:]
L3OUT_NAME = \
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
2][4:]
EXTERNAL_EPG_SEARCH_RESPONSE['imdata'][0]['l3extInstP']['attributes']['dn'].split('/')[
1][3:]
if L3OUT_NAME == rules['PROVIDER_L3OUT']:
pass
else:
OUTPUT_LOG.append({
'Errors': 'EPG and L3OUT missmatch with ' + L3OUT_NAME + ' and ' + EPG_NAME + ' dont match value: ' +
rules['PROVIDER_L3OUT']})
else:
DISPLAY_LIST.append(PROVIDER_EPG)
ERROR = True
DISPLAY_SET = set(DISPLAY_LIST)
for epgs in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'EPG "' + epgs + '" needs creating.'})
# Check if Internal EPGs Exist
OUTPUT_LOG.append({'Headers': 'Checking if Internal EPGs are created'})
EPG_LIST = []
# Search to validate internal EPG's are created
for rules in RULE_LIST:
if rules['CONSUMER_L3OUT'] == 'INTERNAL':
if rules['CONSUMER_EPG'] != 'BLANK':
CONSUMER_EPG = rules['CONSUMER_EPG']
# Search for consumer EPG
INTERNAL_EPG_SEARCH_RESPONSE = INTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE, CONSUMER_EPG, HEADERS)
if int(INTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
DISPLAY_LIST.append(CONSUMER_EPG)
ERROR = True
else:
pass
for rules in RULE_LIST:
if rules['PROVIDER_L3OUT'] == 'INTERNAL':
if rules['PROVIDER_EPG'] != 'BLANK':
PROVIDER_EPG = rules['PROVIDER_EPG']
# Search for Provider EPG
INTERNAL_EPG_SEARCH_RESPONSE = INTERNAL_EPG_SEARCH(BASE_URL, APIC_COOKIE, PROVIDER_EPG, HEADERS)
if int(INTERNAL_EPG_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
DISPLAY_LIST.append(PROVIDER_EPG)
ERROR = True
else:
pass
DISPLAY_SET = set(DISPLAY_LIST)
for epgs in DISPLAY_SET:
OUTPUT_LOG.append({'Errors': 'EPG "' + epgs + '" needs creating.'})
DISPLAY_LIST = []
else:
OUTPUT_LOG.append({'Errors': 'Unable to connect to APIC.'})
if not ERROR:
OUTPUT_LOG.append({'ValidationSuccess': 'APIC Configuration validated successfully'})
return OUTPUT_LOG
@shared_task
def CONTRACT_DEPLOYMENT(RULE_LIST, location, url_dict, username, password):
BASE_URL = url_dict[location]
CONTRACT_LIST = []
FILTER_LIST = []
DISPLAY_LIST = []
OUTPUT_LOG = []
HEADERS = {'content-type': 'application/json'}
# --------------------------------------------------------------------------#
# Begin Configuration
# --------------------------------------------------------------------------#
OUTPUT_LOG.append({'Headers': 'Starting contract provisioning.'})
OUTPUT_LOG.append({'Headers': 'Connecting to APIC'})
APIC_COOKIE = APIC_LOGIN(BASE_URL, username, password)
if APIC_COOKIE:
OUTPUT_LOG.append({'Notifications': 'Successfully generated authentication cookie'})
OUTPUT_LOG.append({'Headers': 'Creating Filters.'})
# Create Filters in Filter SET
for rules in RULE_LIST:
for services in rules['SERVICE']:
FILTER_NAME = services
FILTER_SEARCH_RESPONSE = FILTER_SEARCH(BASE_URL, APIC_COOKIE, FILTER_NAME, HEADERS)
if int(FILTER_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
FILTER_LIST.append(FILTER_NAME)
FILTER_SET = set(FILTER_LIST)
if len(FILTER_SET) > 0:
OUTPUT_LOG = FILTER_CREATE(FILTER_SET, BASE_URL, APIC_COOKIE, HEADERS, OUTPUT_LOG)
else:
pass
OUTPUT_LOG.append({'Headers': 'Creating Contract & Subjects.'})
# Create Contracts and Subjects in Contract SET
for rules in RULE_LIST:
CONTRACT_NAME = rules['NAME']
CONTRACT_SEARCH_RESPONSE = CONTRACT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, HEADERS)
if int(CONTRACT_SEARCH_RESPONSE['totalCount']) == 1:
pass
else:
CONTRACT_LIST.append(CONTRACT_NAME)
CONTRACT_SET = set(CONTRACT_LIST)
if len(CONTRACT_SET) > 0:
OUTPUT_LOG = CONTRACT_CREATE(CONTRACT_SET, BASE_URL, APIC_COOKIE, HEADERS, OUTPUT_LOG)
else:
pass
# Add filters to subjects
for rules in RULE_LIST:
# Use the contract search to locate subject
CONTRACT_NAME = rules['NAME']
CONTRACT_SEARCH_RESPONSE = CONTRACT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, HEADERS)
# Validate that a contract can be located
if int(CONTRACT_SEARCH_RESPONSE['totalCount']) == 1:
TENANT = CONTRACT_SEARCH_RESPONSE['imdata'][0]['vzBrCP']['attributes']['dn'].split('/')[1][3:]
CONTRACT_SUBJECT = \
CONTRACT_SEARCH_RESPONSE['imdata'][0]['vzBrCP']['attributes']['dn'].split('/')[2][4:].split('_')[
0] + '_SBJ'
SUBJECT_SEARCH_RESPONSE = SUBJECT_SEARCH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, TENANT, CONTRACT_SUBJECT,
HEADERS)
# Add all filters for a subject to a list to be used for comparison.
SUBJECT_FILTERS = []
for filters in SUBJECT_SEARCH_RESPONSE['imdata']:
SUBJECT_FILTERS.append(filters['vzRsSubjFiltAtt']['attributes']['tnVzFilterName'])
# compare list of filters to those already in subject
NEW_FILTERS = rules['SERVICE']
FILTER_COMPARE = LIST_COMPARE(NEW_FILTERS, SUBJECT_FILTERS)
if len(FILTER_COMPARE[0]) == 0:
pass
elif len(FILTER_COMPARE[0]) > 0:
for FILTERS in FILTER_COMPARE[0]:
OUTPUT_LOG = FILTER_ATTACH(BASE_URL, APIC_COOKIE, CONTRACT_NAME, CONTRACT_SUBJECT, FILTERS,
HEADERS,
OUTPUT_LOG)
else:
OUTPUT_LOG.append({'Errors': 'Error adding Filters to subject!'})
NEW_FILTERS = ''
else:
pass
OUTPUT_LOG.append({'Headers': 'Consuming & Providing Contracts.'})
for rules in RULE_LIST:
LINE = rules['LINE']
CONTRACT_NAME = rules['NAME']
# Consuming contract
EPG_NAME = rules['CONSUMER_EPG']
OUTPUT_LOG.append({'Headers2': 'Deploying Contracts for Line: ' + str(LINE)})
if EPG_NAME != 'BLANK':
if rules['CONSUMER_L3OUT'] == 'INTERNAL':
INTERNL_EPG_CONTRACT_CONSUME(BASE_URL, EPG_NAME, CONTRACT_NAME, APIC_COOKIE, HEADERS, OUTPUT_LOG)
else:
L3OUT_NAME = rules['CONSUMER_L3OUT']
EXTERNAL_EPG_CONTRACT_CONSUME(L3OUT_NAME, EPG_NAME, CONTRACT_NAME, BASE_URL, APIC_COOKIE, HEADERS,
OUTPUT_LOG)
# Providing contract
EPG_NAME = rules['PROVIDER_EPG']
if EPG_NAME != 'BLANK':
if rules['PROVIDER_L3OUT'] == 'INTERNAL':
INTERNL_EPG_CONTRACT_PROVIDE(BASE_URL, EPG_NAME, CONTRACT_NAME, APIC_COOKIE, HEADERS, OUTPUT_LOG)
else:
L3OUT_NAME = rules['PROVIDER_L3OUT']
EXTERNAL_EPG_CONTRACT_PROVIDE(L3OUT_NAME, EPG_NAME, CONTRACT_NAME, BASE_URL, APIC_COOKIE, HEADERS,
OUTPUT_LOG)
else:
OUTPUT_LOG.append({'Errors': 'Unable to connect to APIC.'})
return OUTPUT_LOG
| 48.965966
| 239
| 0.464113
| 9,085
| 97,834
| 4.766538
| 0.050963
| 0.043229
| 0.047455
| 0.023162
| 0.802559
| 0.752263
| 0.712036
| 0.669522
| 0.639872
| 0.622829
| 0
| 0.014231
| 0.434726
| 97,834
| 1,997
| 240
| 48.990486
| 0.768801
| 0.044064
| 0
| 0.693957
| 0
| 0.00065
| 0.151177
| 0.00288
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008447
| false
| 0.037037
| 0.012995
| 0
| 0.02989
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a736776591b581418ecc3f0e3ee6edb8abfb4d24
| 154
|
py
|
Python
|
examples/misc/djangoweb/webpages/models.py
|
takipsizad/pyjs
|
54db0ba6747aca744f9f3c3e985a17e913dfb951
|
[
"ECL-2.0",
"Apache-2.0"
] | 739
|
2015-01-01T02:05:11.000Z
|
2022-03-30T15:26:16.000Z
|
examples/misc/djangoweb/webpages/models.py
|
takipsizad/pyjs
|
54db0ba6747aca744f9f3c3e985a17e913dfb951
|
[
"ECL-2.0",
"Apache-2.0"
] | 33
|
2015-03-25T23:17:04.000Z
|
2021-08-19T08:25:22.000Z
|
examples/misc/djangoweb/webpages/models.py
|
takipsizad/pyjs
|
54db0ba6747aca744f9f3c3e985a17e913dfb951
|
[
"ECL-2.0",
"Apache-2.0"
] | 167
|
2015-01-01T22:27:47.000Z
|
2022-03-17T13:29:19.000Z
|
from django.db.models import *
class Page(Model):
name = CharField(max_length=50)
text = TextField()
def __unicode__(self):
return str(self.text)
| 15.4
| 32
| 0.720779
| 22
| 154
| 4.818182
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0.155844
| 154
| 9
| 33
| 17.111111
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 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
| 0
| 1
| 1
| 0
|
0
| 4
|
5957178c20e29b4062de62d6d2bafe2138980881
| 93,518
|
py
|
Python
|
utils/layers_old.py
|
RandallBalestriero/PMASO
|
780b06f8d8496000f3ecda04a49c8eda72393b5d
|
[
"MIT"
] | null | null | null |
utils/layers_old.py
|
RandallBalestriero/PMASO
|
780b06f8d8496000f3ecda04a49c8eda72393b5d
|
[
"MIT"
] | null | null | null |
utils/layers_old.py
|
RandallBalestriero/PMASO
|
780b06f8d8496000f3ecda04a49c8eda72393b5d
|
[
"MIT"
] | null | null | null |
import tensorflow as tf
from pylab import *
import utils
import itertools
from math import pi as PI_CONST
eps = float32(0.000000000001)
class BN:
def __init__(self,center,scale):
self.center = center
self.scale = scale
def bn(x,axis):
m,v = tf.nn.moments(x,axes=axis,keep_dims=True)
v_ = tf.sqrt(tf.maximum(v,0.0001))
return (x-m)/v_,m,v_
def mynorm(W,axis=None,keepdims=False):
return tf.reduce_sum(tf.square(W),axis=axis,keepdims=keepdims)
def mysoftmax(W,axis=-1,coeff=0.00):
input = W-tf.reduce_max(W,axis=axis,keepdims=True)
delta = tf.exp(input)/tf.reduce_sum(tf.exp(input),axis=axis,keepdims=True)
if(coeff==0):
return delta
deltap = delta+coeff
return deltap/tf.reduce_sum(deltap,axis=axis,keepdims=True)
def mynormalize(W,axis=-1):
return W/tf.reduce_sum(W,axis=axis,keepdims=True)
def myexpand(x,axis):
nx = tf.expand_dims(x,axis[0])
if(len(axis)==1):
return nx
else:
return myexpand(nx,axis[1:])
def mysumpool(x,p):
return tf.nn.avg_pool(x,[1,p[0],p[1],1],[1,p[0],p[1],1],'VALID')*p[0]*p[1]
#########################################################################################################################
#
#
# DENSE/CONV/POOL LAYERS
#
#
#########################################################################################################################
class DenseLayer:
def __init__(self,input_layer,K,R,sparsity_prior = 0,leakiness=None,sigma='local',p_drop=0,residual=0,alpha=0.95,update_b=True,G=False):
self.update_b = update_b
self.leakiness = leakiness
self.alpha = tf.Variable(alpha,trainable=False)
self.sigma_opt = sigma
self.residual = residual
self.sparsity_prior = sparsity_prior
self.input_layer = input_layer
self.p_drop = float32(p_drop)
input_layer.next_layer = self
self.input_shape = input_layer.output_shape
self.bs,self.R,self.K = self.input_shape[0],R,K
self.D_in = prod(self.input_shape[1:])
self.input_shape_ = (self.bs,self.D_in)#potentially different if flattened
self.output_shape = (self.bs,K)
self.input = input_layer.m
# PARAMETERS
self.drop_ = tf.Variable(tf.ones((self.K,2,self.bs))*tf.reshape(tf.one_hot(1,2),[1,2,1]),trainable=False)
self.sigmas2_= tf.Variable(tf.ones(self.D_in),trainable=True);tf.add_to_collection('PARAMS',self.sigmas2_)
if(0): self.SIGMAS2_ = tf.square(self.sigmas2_)
else: self.SIGMAS2_ = self.sigmas2_
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
if(leakiness is None):
self.W_ = tf.Variable(tf.random_normal((K,R,self.D_in),float32(0),float32(1/sqrt(self.K))),trainable=True);tf.add_to_collection('PARAMS',self.W_)
self.W = self.W_
else:
self.W_ = tf.Variable(tf.random_normal((K,1,self.D_in),float32(0),float32(1/sqrt(K))));tf.add_to_collection('PARAMS',self.W_)
self.W = tf.concat([self.W_,self.W_*self.leakiness],axis=1)
self.pi = tf.Variable(mysoftmax(tf.ones((K,R))))#;tf.add_to_collection('PARAMS',self.pi)
self.b_ = tf.Variable(tf.zeros(self.D_in));tf.add_to_collection('PARAMS',self.b_)
self.b = tf.expand_dims(self.b_,0)
self.V_ = tf.Variable(tf.zeros(self.K));tf.add_to_collection('PARAMS',self.V_)
self.V = tf.expand_dims(self.V_,0)
# VI PARAMETERS
self.m_ = tf.Variable(tf.random_normal((K,self.bs))*1);tf.add_to_collection('LATENT',self.m_)
self.m = tf.transpose(self.m_)
self.p_ = tf.Variable(mysoftmax(tf.random_normal((K,self.bs,R))*0.1,axis=2));tf.add_to_collection('LATENT',self.p_)
if(G): self.p_ = tf.nn.softmax(self.p_)
else: self.p_ = self.p_
self.p = tf.transpose(self.p_,[1,0,2])
self.v2_ = tf.Variable(tf.ones((K,self.bs)));tf.add_to_collection('LATENT',self.v2_)
if(G): self.v2_ = tf.square(self.v2_)
else: self.v2_ = self.v2_
self.v2 = tf.transpose(self.v2_,[1,0])
# placeholder for update and indices
self.k_ = tf.placeholder(tf.int32) # placeholder that will indicate which neuron is being updated
self.W_indices = asarray(range(self.K))
self.m_indices = [0]#self.W_indices
self.p_indices = self.W_indices
# STATISTICS
self.S1 = tf.Variable(tf.zeros((self.K,self.R,self.D_in)))
self.S2 = tf.Variable(tf.zeros((self.K,self.R)))
self.S3 = tf.Variable(tf.zeros((self.K,self.R)))
self.S4 = tf.Variable(tf.zeros(self.D_in))
self.S5 = tf.Variable(tf.zeros((self.K,self.R,self.K,self.R)))
self.S6 = tf.Variable(tf.zeros(self.D_in))
self.S7 = tf.Variable(tf.zeros((self.K,self.R)))
self.S8 = tf.Variable(tf.zeros(self.D_in))
# RESHAPE IF NEEDED
if(len(self.input_shape)>2):
self.is_flat = False
self.input_ = tf.reshape(self.input,(self.bs,self.D_in))
# self.input_,self.bn_m,self.bn_v = bn(tf.reshape(self.input,(self.bs,self.D_in)),[0])
self.reshape_SIGMAS2_ = tf.reshape(self.SIGMAS2_,self.input_shape[1:])
self.reshape_SIGMAS2 = tf.expand_dims(self.reshape_SIGMAS2_,0)
self.reshape_b_ = tf.reshape(self.b_,self.input_shape[1:])
self.reshape_b = tf.expand_dims(self.reshape_b_,0)
else:
self.is_flat = True
self.input_ = self.input
# self.input_,self.bn_m,self.bn_v = bn(self.input,[0])
def update_S(self):
S1 = tf.einsum('nd,knr->krd',self.input_,tf.expand_dims(self.m_,-1)*self.p_)/self.bs
S2 = tf.einsum('kn,knr->kr',self.m_,self.p_)/self.bs
S3 = tf.einsum('kn,knr->kr',tf.square(self.m_)+self.v2_,self.p_)/self.bs
if(isinstance(self.input_layer,DenseLayer)):
S4 = tf.reduce_sum(self.input_layer.v2_,1)/self.bs
S6 = tf.reduce_sum(self.input_layer.m_,1)/self.bs
else:
S4 = tf.reshape(tf.reduce_sum(self.input_layer.v2,0),[self.D_in])/self.bs
S6 = tf.reshape(tf.reduce_sum(self.input_layer.m,0),[self.D_in])/self.bs
S5 = (1-tf.reshape(tf.eye(self.K),[self.K,1,self.K,1]))*tf.einsum('knr,unv->kruv',tf.expand_dims(self.m_,-1)*self.p_,tf.expand_dims(self.m_,-1)*self.p_)/self.bs
S7 = tf.reduce_sum(self.p_,1)/self.bs
S8 = tf.reduce_sum(tf.square(self.input_),0)/self.bs
return tf.group(tf.assign(self.S1,self.alpha*S1+(1-self.alpha)*self.S1),tf.assign(self.S2,self.alpha*S2+(1-self.alpha)*self.S2),
tf.assign(self.S3,self.alpha*S3+(1-self.alpha)*self.S3),tf.assign(self.S4,self.alpha*S4+(1-self.alpha)*self.S4),
tf.assign(self.S5,self.alpha*S5+(1-self.alpha)*self.S5),tf.assign(self.S6,self.alpha*S6+(1-self.alpha)*self.S6),
tf.assign(self.S7,self.alpha*S7+(1-self.alpha)*self.S7),tf.assign(self.S8,self.alpha*S8+(1-self.alpha)*self.S8))
def backward(self,flat=1,resi=None):
if(resi is None): resi = self.residual
else: resi = resi*self.residual
back = tf.einsum('knr,krd->nd',self.p_*tf.expand_dims(self.m_*self.drop_[:,1],-1),self.W)
if(flat):
if(resi): return back+self.V*self.m
else: return back
else:
if(resi): return tf.reshape(back+self.V*self.m,self.input_shape)
else: return tf.reshape(back,self.input_shape)
def backwardk(self,k,resi = None):
if(resi is None): resi = self.residual
else: resi = self.residual*resi
back = tf.einsum('knr,kr->n',self.p_*tf.expand_dims(self.m_*self.drop_[:,1],-1),self.W[:,:,k])
if(resi): return back+self.V_[k]*self.m_[k] # (N)
else: return back # (N)
def backwardmk(self,k,with_m=1,m=None,p=None):
if(m is None): m = self.m_
if(p is None): p = self.p_
AA = p*tf.expand_dims(m*self.drop_[:,1]*tf.expand_dims(1-tf.one_hot(k,self.K),-1),-1)
tf.Tensor.set_shape(AA,[self.K,self.bs,self.R])
back = tf.einsum('knr,krd->nd',AA,self.W)
if(self.residual==0): return back
if(with_m): return back+self.V*tf.transpose(m)
else: return back+self.V*tf.transpose(m)*tf.expand_dims(1-tf.one_hot(k,self.K),0)
def sample(self,M,K=None,sigma=1,deterministic=False):
if(isinstance(self.input_layer,InputLayer)):sigma=0
if(deterministic): return tf.reshape(self.backward(1)+self.b,self.input_shape)
noise = sigma*tf.random_normal((self.bs,self.D_in))*tf.sqrt(self.SIGMAS2)
if(self.p_drop>0): dropout = tf.distributions.Bernoulli(probs=self.p_drop,dtype=tf.float32).sample((self.bs,self.K))
# dropout = tf.cast(tf.reshape(tf.multinomial(tf.reshape(tf.stack([tf.log(self.p_drop),tf.log(float32(1)-self.p_drop)]),[1,2]),self.bs*self.K),(self.bs,self.K)),tf.float32)
else: dropout = float32(1)
if(K==None):
K = tf.one_hot(tf.transpose(tf.multinomial(tf.log(self.pi),self.bs)),self.R)
# tf.Tensor.set_shape(K,[self.bs,self.K,self.R])
tf.Tensor.set_shape(M,self.output_shape)
MdropK = tf.einsum('nkr,krd->nd',tf.expand_dims(M*dropout,-1)*K,self.W)
if(self.residual): return tf.reshape(MdropK+noise+self.residual*self.V*M+self.b,self.input_shape)
else: return tf.reshape(MdropK+self.b+noise,self.input_shape)
def evidence(self):
if(self.residual):
currentv2 = -tf.einsum('kn,k->n',self.v2_,tf.square(self.V_)/self.SIGMAS2_)*float32(0.5)
extra_v2 = -tf.einsum('kn,knr,rk,k->n',self.v2_,self.p_,tf.map_fn(lambda r:tf.diag_part(self.W[:,r,:]),tf.range(self.R,dtype=tf.int32),dtype=tf.float32),self.V_/self.SIGMAS2_)
else: currentv2 = 0 ; extra_v2 = 0
if(self.p_drop>0): k1 = tf.reduce_sum(self.drop_[:,0],0)*tf.log(self.p_drop)+tf.reduce_sum(self.drop_[:,1],0)*tf.log(float32(1)-self.p_drop)
else: k1 = 0
k2 = -tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5) #(1)
k3 = tf.einsum('knr,kr->n',self.p_,tf.log(self.pi)) #(1)
k4 = -float32(self.D_in)*tf.log(2*PI_CONST)*float32(0.5)
reconstruction = -tf.einsum('nd,d->n',tf.square(self.input_-self.b-self.backward(flat=1,resi=1)),1/self.SIGMAS2_)*float32(0.5) #(1)
if(isinstance(self.input_layer,DenseLayer)):
input_v2 = -tf.einsum('dn,d->n',self.input_layer.v2_,1/self.SIGMAS2_)*float32(0.5) #(1)
else: input_v2 = -tf.reduce_sum(tf.reshape(self.input_layer.v2,[self.bs,self.D_in])/self.SIGMAS2,1)*float32(0.5) #(1)
sum_norm_k = tf.einsum('kdn,d->n',tf.square(tf.einsum('krd,knr,kn->kdn',self.W,self.p_,self.m_*self.drop_[:,1])),1/self.SIGMAS2_)*float32(0.5)
m2v2 = -tf.reduce_sum(self.drop_[:,1]*(self.v2_+tf.square(self.m_))*tf.einsum('knr,krd,d->kn',self.p_,tf.square(self.W),1/self.SIGMAS2_),0)*float32(0.5)
return k1+k2+k3+k4+(reconstruction+input_v2+sum_norm_k+m2v2+currentv2+extra_v2)
def likelihood(self,batch=None,pretraining=False):
if(batch==False):
if(pretraining==False):
extra_k = 0
else:
extra_k = -0.5*tf.reduce_sum(tf.square(self.m_)+self.v2_)/self.bs
if(self.residual):
currentv2 = -tf.einsum('kn,k->',self.v2_,tf.square(self.V_)/self.SIGMAS2_)
extra_v2 = -tf.einsum('kn,knr,rk,k->',self.v2_,self.p_,tf.map_fn(lambda r:tf.diag_part(self.W[:,r,:]),tf.range(self.R,dtype=tf.int32),dtype=tf.float32),self.V_/self.SIGMAS2_)*2
else: currentv2 = 0 ; extra_v2 = 0
if(self.p_drop>0): k1 = tf.reduce_sum(self.drop_[:,0])*tf.log(self.p_drop)+tf.reduce_sum(self.drop_[:,1])*tf.log(float32(1)-self.p_drop)
else: k1 = 0
k2 = -tf.log(2*PI_CONST)*float32(self.D_in*0.5)-tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5) #(1)
k3 = tf.einsum('knr,kr->',self.p_,tf.log(self.pi))*2 #(1)
reconstruction = -tf.einsum('nd,d->',tf.square(self.input_-self.b-self.backward(flat=1,resi=1)),1/self.SIGMAS2_) #(1)
if(isinstance(self.input_layer,DenseLayer)):
input_v2 = -tf.einsum('dn,d->',self.input_layer.v2_,1/self.SIGMAS2_) #(1)
else: input_v2 = -tf.reduce_sum(tf.reshape(tf.reduce_sum(self.input_layer.v2,0),[self.D_in])/self.SIGMAS2_) #(1)
sum_norm_k = tf.einsum('kdn,d->',tf.square(tf.einsum('krd,knr,kn->kdn',self.W,self.p_,self.m_*self.drop_[:,1])),1/self.SIGMAS2_)
m2v2 = -tf.reduce_sum(self.drop_[:,1]*(self.v2_+tf.square(self.m_))*tf.einsum('knr,krd,d->kn',self.p_,tf.square(self.W),1/self.SIGMAS2_))
return k2+(k1+k3+m2v2+reconstruction+input_v2+sum_norm_k+currentv2+extra_v2)*float32(0.5/self.bs)-self.sparsity_prior*tf.reduce_sum(tf.square(self.W))+extra_k
else:
k1 = tf.log(2*PI_CONST)*float32(self.D_in*0.5)+tf.reduce_sum(tf.log(self.SIGMAS2_)*float32(0.5))
k2 = tf.reduce_sum((self.S8+self.S4-2*self.b_*self.S6+tf.square(self.b_))/(2*self.SIGMAS2_))
k3 = tf.einsum('krd,d->',(self.S1-tf.einsum('kr,d->krd',self.S2,self.b_))*self.W,1/self.SIGMAS2_)
k4 = tf.einsum('abcd,abu,cdu->',self.S5,self.W,self.W/tf.expand_dims(2*self.SIGMAS2,0))
k5 = tf.reduce_sum(tf.log(self.pi)*self.S7-self.S3*tf.einsum('krd,d->kr',tf.square(self.W),0.5/self.SIGMAS2_))
return -k1-k2+k3-k4+k5
def KL(self,pretraining=False):
if(self.p_drop>0):
return self.likelihood(0,pretraining)+(-tf.reduce_sum(self.p_*tf.log(self.p_+eps))+tf.reduce_sum(tf.log(self.v2_+eps))*float32(0.5)\
-tf.reduce_sum(self.drop_*tf.log(self.drop_+eps)))/float32(self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
else:
return self.likelihood(0,pretraining)+(-tf.reduce_sum(self.p_*tf.log(self.p_+eps))+tf.reduce_sum(tf.log(self.v2_+eps))*float32(0.5))/float32(self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
################### E STEP VARIABLES
def update_v2(self,pretraining=False):
if(pretraining==False):
next_sigmas = self.next_layer.SIGMAS2
else:
next_sigmas = tf.ones_like(self.next_layer.SIGMAS2)
scalor = tf.reduce_min(next_sigmas)
a40 = self.drop_[:,1]*tf.einsum('knr,krd,d->kn',self.p_,tf.square(self.W),scalor/self.SIGMAS2_)+scalor/tf.transpose(next_sigmas)
if(self.residual==0): a4 = a40
else: a4 = a40+tf.expand_dims(tf.square(self.V_)*scalor/self.SIGMAS2_,-1)+2*tf.einsum('knr,rk,k->kn',self.p_,tf.map_fn(lambda r:tf.diag_part(self.W[:,r,:]),tf.range(self.R),dtype=tf.float32),self.V_*scalor/self.SIGMAS2_)
return tf.assign(self.v2_,scalor/a4)
def update_rho(self):
return []
def update_m(self,ii,pretraining=False):
k = self.k_
Wk = self.W[self.k_];tf.Tensor.set_shape(Wk,[self.R,self.D_in])
if(ii==0):
rescalor = tf.reduce_min(self.SIGMAS2_)
if(pretraining==False):
back = (self.next_layer.backward()+self.next_layer.b)*rescalor/self.next_layer.SIGMAS2
next_sigmas = self.next_layer.SIGMAS2
else:
back = tf.zeros_like(self.next_layer.b)
next_sigmas = tf.ones_like(self.next_layer.b)
Wp = tf.einsum('krd,knr->nkd',self.W,self.p_)
b = tf.einsum('nd,nkd->nk',(self.input_-self.b)*rescalor/self.SIGMAS2,Wp)+back
D = tf.matrix_diag(tf.einsum('krd,d,knr->nk',tf.square(self.W),rescalor/self.SIGMAS2_,self.p_))
A = tf.einsum('nkd,nad->nka',Wp,Wp*rescalor/tf.expand_dims(self.SIGMAS2,0))*(1-tf.expand_dims(tf.eye(self.K),0))+tf.expand_dims(tf.diag(rescalor/next_sigmas[0]),0)+D
new_m = tf.matrix_solve(A,tf.expand_dims(b,-1))[:,:,0]#,l2_regularizer=0,fast=True)[:,:,0]
return tf.assign(self.m_,tf.transpose(new_m))
mk = self.m_[self.k_]
reconstruction = self.input_-self.b-self.backwardmk(self.k_,with_m=1)
tf.Tensor.set_shape(reconstruction,[self.bs,self.D_in])
forward = tf.einsum('nd,rd,n->nr',reconstruction,Wk/self.SIGMAS2,mk*self.drop_[self.k_,1]) # (N R)
prior = tf.expand_dims(tf.log(self.pi[self.k_]),0) # (1 R)
m2v2 = tf.einsum('n,rd,d->nr',(tf.square(mk)+self.v2_[self.k_])*self.drop_[self.k_,1],tf.square(Wk),1/(2*self.SIGMAS2_)) # (N R)
if(self.residual): extra_v2 = tf.einsum('n,r->nr',self.v2_[self.k_],self.W[self.k_,:,self.k_]*self.V_[self.k_]/self.SIGMAS2_[self.k_])
else: extra_v2 = 0
new_p = tf.scatter_update(self.p_,[self.k_],[tf.nn.softmax(forward+prior-m2v2-extra_v2)])
return new_p
if(self.p_drop==0):
return tf.group(new_m,new_p)
## UPDATE DROPOUT
proj = tf.einsum('nd,rd,nr->n',reconstruction,self.W[k]/self.SIGMAS2,new_p[self.k_])*new_m[self.k_] # (N)
squared = tf.einsum('n,nr,rd,d->n',self.v2_[self.k_]+tf.square(new_m[self.k_]),new_p[self.k_],tf.square(self.W[k]),1/self.SIGMAS2_) #(N)
filled0 = tf.fill([self.bs],tf.cast(tf.log(self.p_drop),tf.float32))
filled1 = tf.fill([self.bs],tf.cast(tf.log(1-self.p_drop),tf.float32))
new_drop = mysoftmax(tf.stack([filled0,filled1-squared*float32(0.5)+proj]),axis=0,coeff=0.)
return tf.group(new_m,new_p,tf.scatter_update(self.drop_,[k],[new_drop]))
######################## M STEP VARIABLES
def update_sigma(self):
value = self.S8+tf.square(self.b_)+self.S4+tf.einsum('kr,krd->d',self.S3,tf.square(self.W))+tf.einsum('kruv,krd,uvd->d',self.S5,self.W,self.W)-2*tf.einsum('krd,krd->d',self.S1,self.W)+2*self.b_*(tf.einsum('kr,krd->d',self.S2,self.W)-self.S6)
value_ = tf.clip_by_value(value,0.000001,1000)
if(self.sigma_opt=='local'): return tf.assign(self.SIGMAS2_,value_)
elif(self.sigma_opt=='global'): return tf.assign(self.SIGMAS2_,tf.fill([self.D_in],tf.reduce_sum(value_)/self.D_in))
elif(self.sigma_opt=='channel'):
v=tf.reduce_sum(tf.reshape(value_,self.input_shape[1:]),axis=[0,1],keepdims=True)/(self.input_shape[1]*self.input_shape[2])
return tf.assign(self.sigmas2_,tf.reshape(tf.ones([self.input_shape[1],self.input_shape[2],1])*v,[self.D_in]))
def update_pi(self):
return tf.assign(self.pi,tf.clip_by_value(self.S7/tf.reduce_sum(self.S7,axis=1,keepdims=True),0.01,0.99))
def update_Wk(self):
k = self.k_
if(self.leakiness is None):
new_w = (self.S1[k]-tf.einsum('r,d->rd',self.S2[k],self.b_)-tf.einsum('krd,tkr->td',self.W,self.S5[k]))/tf.expand_dims(self.S3[k],-1)
else:
new_w = tf.expand_dims((self.S1[k,0]+self.leakiness*self.S1[k,1]-(self.S2[k,0]+self.leakiness*self.S2[k,1])*self.b_-tf.einsum('krd,kr->d',self.W,self.S5[k,0]+self.leakiness*self.S5[k,1]))/(self.S3[k,0]+tf.square(self.leakiness)*self.S3[k,1]),0)
return tf.scatter_update(self.W_,[self.k_],[new_w])
def update_BV(self):
if(self.update_b): newb = tf.assign(self.b_,self.S6-tf.einsum('krd,kr->d',self.W,self.S2))
else: newb = []
if(self.residual==0): return newb
back = tf.einsum('knr,krd->nd',self.p_*tf.expand_dims(self.m_*self.drop_[:,1],-1),self.W) # (N D)
forward = tf.einsum('kn,nk->k',self.m_,self.input_-tf.expand_dims(newb,0)-back)-tf.diag_part(tf.einsum('kn,knr,krd->kd',self.v2_,self.p_,self.W)) # K
b = tf.reduce_sum(self.v2_+tf.square(self.m_),1)
return tf.group(newb,tf.assign(self.V_,forward/b))
class ConvLayer:
def __init__(self,input_layer,K,Ic,Jc,R,sparsity_prior = 0,leakiness=None,sigma='local',alpha=0.5):
self.alpha = tf.Variable(alpha)
self.leakiness = leakiness
self.sigma_opt = sigma
self.sparsity_prior = sparsity_prior
self.input_layer = input_layer
input_layer.next_layer = self
self.bs,self.Iin,self.Jin,self.C = input_layer.output_shape
self.Ic,self.Jc,self.K,self.R = Ic,Jc,K,R
# self.input = input_layer.m
self.input = input_layer.m
self.input_shape = input_layer.output_shape
self.output_shape = (self.bs,self.input_shape[-3]-self.Ic+1,self.input_shape[-2]-self.Jc+1,K)
self.D_in = prod(self.input_shape[1:])
self.I,self.J = self.output_shape[1],self.output_shape[2]
self.input_patch = self.extract_patch(self.input,with_n=1)
self.pi_ = PI_CONST
init = tf.orthogonal_initializer(float32(1/sqrt(K)))
self.W_ = tf.Variable(init((self.K,self.Ic,self.Jc,self.C)));tf.add_to_collection('PARAMS',self.W_)
self.W = tf.stack([self.W_,tf.zeros_like(self.W_)],axis=1)
# WE DEFINE THE PARAMETERS
self.pi = tf.Variable(mysoftmax(tf.random_normal((K,R)),axis=1));tf.add_to_collection('PARAMS',self.W_)
self.SIGMAS2_ = tf.Variable(tf.ones((self.Iin,self.Jin,self.C)));tf.add_to_collection('PARAMS',self.SIGMAS2_)
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
self.SIGMAS2_patch_ = self.extract_patch(self.SIGMAS2,with_n=0)
self.SIGMAS2_patch = tf.expand_dims(self.SIGMAS2_patch_,0)
# SOME OTHER VARIABLES
self.b_ = tf.Variable(tf.zeros(self.input_shape[1:]));tf.add_to_collection('PARAMS',self.b_)
self.b = tf.expand_dims(self.b_,0)
self.b_patch_= self.extract_patch(self.b,with_n=0)
self.b_patch = tf.expand_dims(self.b_patch_,0)
self.m_ = tf.Variable(tf.zeros((K,self.I,self.J,self.bs)));tf.add_to_collection('LATENT',self.m_)
self.m = tf.transpose(self.m_,[3,1,2,0]) # (N I J K)
self.p_ = tf.Variable(mysoftmax(tf.random_normal((K,self.I,self.J,self.R,self.bs)),axis=3));tf.add_to_collection('LATENT',self.p_)# (K,I,J,R,N)
self.p = tf.transpose(self.p_,[4,1,2,0,3]) # (N I J K R)
self.v2_ = tf.Variable(tf.ones((self.K,self.I,self.J,self.bs)));tf.add_to_collection('LATENT',self.v2_) # (K I J N)
self.v2 = tf.transpose(self.v2_,[3,1,2,0])
self.drop_ = tf.Variable(tf.ones((K,2,self.I,self.J,self.bs))*tf.reshape(tf.one_hot(1,2),(1,2,1,1,1))) # (K 2 I J N)
self.drop = tf.transpose(self.drop_,[1,4,2,3,0]) #(2 N I J K)
# STATISTICS
self.S1 = tf.Variable(tf.zeros((self.C,self.Iin,self.Jin)))
self.S2 = tf.Variable(tf.zeros((self.C,self.Iin,self.Jin)))
self.S3 = tf.Variable(tf.zeros((self.K,self.I,self.J,self.Ic,self.Jc,self.C)))
self.S4 = tf.Variable(tf.zeros((self.K,self.I,self.J)))
self.S5 = tf.Variable(tf.zeros((self.K,self.I,self.J,self.K,self.Ic*2-1,self.Jc*2-1)))
self.S6 = tf.Variable(tf.zeros((self.K,self.I,self.J)))
self.S7 = tf.Variable(tf.zeros((self.C,self.Iin,self.Jin)))
self.S8 = tf.Variable(tf.zeros((self.K,self.R)))
#
input_layer.next_layer = self
self.k_ = tf.placeholder(tf.int32)
self.i_ = tf.placeholder(tf.int32)
self.j_ = tf.placeholder(tf.int32)
self.r_ = tf.placeholder(tf.int32)
self.ratio = Ic
self.Ni = tf.cast(tf.ceil((self.I-tf.cast(self.i_,tf.float32))/self.ratio),tf.int32) # NUMBER OF TERMS
self.Nj = tf.cast(tf.ceil((self.J-tf.cast(self.j_,tf.float32))/self.ratio),tf.int32) # NUMBER OF TERMS
self.xi,self.yi = tf.meshgrid(tf.range(self.j_,self.J,self.ratio),tf.range(self.i_,self.I,self.ratio)) # THE SECOND IS CONSTANT (meshgrid)
self.indices_ = tf.concat([tf.fill([self.Ni*self.Nj,1],self.k_),tf.reshape(self.yi,(self.Ni*self.Nj,1)),tf.reshape(self.xi,(self.Nj*self.Ni,1))],axis=1) # (V 3) indices where the 1 pops
self.m_indices_ = tf.concat([tf.concat([tf.fill([self.Ni*self.Nj,1],KK),tf.reshape(self.yi,(self.Ni*self.Nj,1)),tf.reshape(self.xi,(self.Nj*self.Ni,1))],axis=1) for KK in range(self.K)],axis=0)
self.W_indices = [a for a in itertools.product(range(self.K),range(self.Ic),range(self.Jc))]
self.W_indices = asarray(self.W_indices)
self.m_indices = asarray([a for a in itertools.product(range(self.ratio),range(self.ratio))])
self.p_indices = asarray([a for a in itertools.product(range(self.K),range(self.ratio),range(self.ratio))])
mask = tf.reshape(tf.one_hot(self.k_,self.K),(self.K,1,1,1))*tf.reshape(tf.tile(tf.one_hot(self.i_,self.ratio),[(self.I/self.ratio+1)]),(1,(self.I/self.ratio+1)*self.ratio,1,1))*tf.reshape(tf.tile(tf.one_hot(self.j_,self.ratio),[self.J/self.ratio+1]),(1,1,(self.J/self.ratio+1)*self.ratio,1))
self.mask = mask[:,:self.I,:self.J] # (K I J 1)
m_mask = tf.ones((self.K,1,1,1))*tf.reshape(tf.tile(tf.one_hot(self.i_,self.ratio),[(self.I/self.ratio+1)]),(1,(self.I/self.ratio+1)*self.ratio,1,1))*tf.reshape(tf.tile(tf.one_hot(self.j_,self.ratio),[self.J/self.ratio+1]),(1,1,(self.J/self.ratio+1)*self.ratio,1))
self.m_mask = m_mask[:,:self.I,:self.J]
# indices = []
# for i in itertools.product(range(self.K),range(self.I),range(self.J)):
# indices.append([i[0],i[1],i[2],i[0],self.Ic-1,self.Jc-1])
# indices=asarray(indices).astype('int32')
print [self.K,self.I,self.Ic-1,self.K,self.I,self.Ic-1]
self.E= tf.einsum('ij,kc,a,b->kijcab',tf.eye(self.I),tf.eye(self.K),tf.one_hot(self.Ic-1,2*self.Ic-1),tf.one_hot(self.Ic-1,2*self.Ic-1))
def BN(self):
return tf.assign(self.m_,bn(self.m_,[1,2,3])[0])
def filter_corr(self,A,B):
#takes as input filter banks A and B of same shape (K a b c)
sigma_W = tf.pad(tf.transpose(tf.reshape(tf.einsum('ijabc,kabc->abckij',1/self.SIGMAS2_patch_,A),[self.Ic,self.Jc,self.C,self.K*self.I*self.J]),[3,0,1,2]),[[0,0],[self.Ic-1,self.Ic-1],[self.Jc-1,self.Jc-1],[0,0]])
patches = tf.reshape(tf.extract_image_patches(sigma_W,(1,self.Ic,self.Jc,1),(1,1,1,1),(1,1,1,1),"VALID"),(self.K*self.I*self.J,2*self.Ic-1,2*self.Jc-1,self.Ic,self.Jc,self.C))
return tf.transpose(tf.reshape(tf.einsum('nijabc,kabc->kijn',patches,B),[self.K,2*self.Ic-1,2*self.Jc-1,self.K,self.I,self.J]),[3,4,5,0,1,2])*(1-self.E)#(K I J K' I' J')
def update_S(self):
S1 = tf.reduce_sum(tf.square(self.input_layer.m_),3)/self.bs
S2 = tf.reduce_sum(self.input_layer.v2_,3)/self.bs
S3 = tf.einsum('nijabc,kijn->kijabc',self.input_patch,self.m_*self.p_[:,:,:,0])/self.bs
S4 = tf.reduce_sum((tf.square(self.m_)+self.v2_)*self.p_[:,:,:,0],3)/self.bs
indices = []
mp_patches = tf.reshape(tf.extract_image_patches(tf.pad(self.m*self.p[:,:,:,:,0],[[0,0],[self.Ic-1,self.Ic-1],[self.Jc-1,self.Jc-1],[0,0]]),(1,2*self.Ic-1,2*self.Jc-1,1),(1,1,1,1),(1,1,1,1),"VALID"),(self.bs,self.I,self.J,2*self.Ic-1,2*self.Jc-1,self.K)) # (N I J I' J' K)
S5 = tf.einsum('kijn,nijabc->kijcab',self.m_*self.p_[:,:,:,0],mp_patches)*(1-self.E)/self.bs
S6 = tf.reduce_sum(self.m_*self.p_[:,:,:,0],3)/self.bs
S7 = tf.reduce_sum(self.input_layer.m_,3)/self.bs
S8 = tf.reduce_sum(self.p_,[1,2,4])/self.bs
return tf.group(tf.assign(self.S1,self.alpha*S1+(1-self.alpha)*self.S1),tf.assign(self.S2,self.alpha*S2+(1-self.alpha)*self.S2),
tf.assign(self.S3,self.alpha*S3+(1-self.alpha)*self.S3),tf.assign(self.S4,self.alpha*S4+(1-self.alpha)*self.S4),
tf.assign(self.S5,self.alpha*S5+(1-self.alpha)*self.S5),tf.assign(self.S6,self.alpha*S6+(1-self.alpha)*self.S6),
tf.assign(self.S7,self.alpha*S7+(1-self.alpha)*self.S7),tf.assign(self.S8,self.alpha*S8+(1-self.alpha)*self.S8))
def extract_patch(self,u,with_n=1,with_reshape=1):
patches = tf.extract_image_patches(u,(1,self.Ic,self.Jc,1),(1,1,1,1),(1,1,1,1),"VALID")
if(with_reshape):
if(with_n): return tf.reshape(patches,(self.bs,self.output_shape[1],self.output_shape[2],self.Ic,self.Jc,self.C))
else: return tf.reshape(patches,(self.output_shape[1],self.output_shape[2],self.Ic,self.Jc,self.C))
return patches
def init_thetaq(self):
new_p = tf.assign(self.p_,mysoftmax(tf.random_uniform((self.K,self.I,self.J,self.R,self.bs)),axis=3))
new_v = tf.assign(self.v2_,tf.ones((self.K,self.I,self.J,self.bs)))
new_m = tf.assign(self.m_,tf.random_normal((self.K,self.I,self.J,self.bs)))
return [new_m,new_p,new_v]
# ---- BACKWARD OPERATOR ----
def deconv(self,input=None,masked_m=0,masked_w=0,m=None,p=None):
if(m is None):m=self.m_
if(p is None):p=self.p_
if(masked_m==1):
m_masked = m*p[:,:,:,0]*(1-self.mask)# (N I J Ir JR K)->(N I' J' K)
elif(masked_m==-1):
m_masked = p[:,:,:,0]*self.mask#
else:
m_masked = m*p[:,:,:,0]
return tf.gradients(self.input_patch,self.input,tf.einsum('kijn,kabc->nijabc',m_masked,self.W_))[0]
def sample(self,M,K=None,sigma=1):
#multinomial returns [K,n_samples] with integer value 0,...,R-1
if(isinstance(self.input_layer,InputLayer)):sigma=0
noise = sigma*tf.random_normal(self.input_shape)*tf.sqrt(self.SIGMAS2)
sigma_hot = tf.one_hot(tf.reshape(tf.multinomial(tf.log(self.pi),self.bs*self.I*self.J),(self.K,self.I,self.J,self.bs)),self.R) # (K I J N R)
return (self.deconv(m=tf.transpose(M,[3,1,2,0]),p=tf.transpose(sigma_hot,[0,1,2,4,3]))+noise+self.b)
def evidence(self): return 0
def likelihood(self,batch=0,pretraining=False):
if(batch==0):
if(pretraining==False):
extra_k = 0
else:
extra_k = -0.5*tf.reduce_sum(tf.square(self.m_)+self.v2_)/self.bs
a1 = -tf.einsum('nijc,ijc->',tf.square(self.input-self.deconv()-self.b)+self.input_layer.v2,1/(2*self.SIGMAS2_*self.bs))
a2 = tf.einsum('kijn,kabc,ijabc->',tf.square(self.m_*self.p_[:,:,:,0])-(tf.square(self.m_)+self.v2_)*self.p_[:,:,:,0],tf.square(self.W_),1/self.SIGMAS2_patch_)*0.5/self.bs
k1 = -float32(self.D_in/2.0)*tf.log(2*PI_CONST)-tf.reduce_sum(tf.log(self.SIGMAS2_))/2
k2 = tf.einsum('kr,krn->',tf.log(self.pi),tf.reduce_sum(self.p_,[1,2]))/float32(self.bs)
return k1+k2+a1+a2-self.sparsity_prior*tf.reduce_sum(tf.square(self.W))+extra_k
else:
k0 = -float32(self.D_in/2.0)*tf.log(2*PI_CONST)-tf.reduce_sum(tf.log(self.SIGMAS2_))/2+tf.reduce_sum(self.S8*tf.log(self.pi))
k1 = -tf.reduce_sum((self.S1+self.S2+tf.square(tf.transpose(self.b_,[2,0,1]))-2*self.S7*tf.transpose(self.b_,[2,0,1]))/tf.transpose(self.SIGMAS2_,[2,0,1]))*0.5
k2 = tf.reduce_sum(self.S3*tf.einsum('kabc,ijabc->kijabc',self.W_,1/self.SIGMAS2_patch_))
k3 = -tf.reduce_sum(self.S6*tf.einsum('kabc,ijabc->kij',self.W_,self.b_patch_/self.SIGMAS2_patch_)+self.S4*tf.einsum('kabc,ijabc->kij',tf.square(self.W_),0.5/self.SIGMAS2_patch_))
filters = self.filter_corr(self.W_,self.W_) # (kij k'i'j')
k4 = -tf.reduce_sum(self.S5*filters)*0.5
return k0+k1+k2+k3+k4
def KL(self,pretraining=False):
return self.likelihood(0,pretraining)+(-tf.reduce_sum(self.p_*tf.log(self.p_+eps))+float32(0.5)*tf.reduce_sum(tf.log(self.v2_)))/float32(self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
def update_dropout(self):
return []
def update_v2(self,pretraining=False):# DONE
if(isinstance(self.next_layer,ConvLayer) or isinstance(self.next_layer,PoolLayer)): v_value = self.next_layer.SIGMAS2 # (N I J K)
else: v_value = self.next_layer.reshape_SIGMAS2 # (N I J K)
if(pretraining==False):
next_sigmas = v_value
else:
next_sigmas = tf.ones_like(v_value)
rescalor = tf.reduce_min(self.SIGMAS2)
a4 = tf.einsum('kijn,kabc,ijabc->kijn',self.p_[:,:,:,0],tf.square(self.W_),rescalor/self.SIGMAS2_patch_) # (K I J N)
return tf.assign(self.v2_,rescalor/(tf.transpose(rescalor/next_sigmas,[3,1,2,0])+a4))
def update_m(self,mp_opt=0,pretraining=False):
if(mp_opt==0):
m_masked = self.m_*self.p_[:,:,:,0]*(1-self.m_mask)
reconstruction = tf.gradients(self.input_patch,self.input,tf.einsum('kijn,kabc->nijabc',m_masked,self.W_))[0]
Wp = tf.einsum('kabc,kijn->nijkabc',self.W_,self.p_[:,self.i_::self.ratio,self.j_::self.ratio,0])
if(isinstance(self.next_layer,ConvLayer) or isinstance(self.next_layer,PoolLayer)):
back = (self.next_layer.deconv()[:,self.i_::self.ratio,self.j_::self.ratio]\
+self.next_layer.b[:,self.i_::self.ratio,self.j_::self.ratio])
A2 = self.next_layer.SIGMAS2_[self.i_::self.ratio,self.j_::self.ratio]
else:
back = (self.next_layer.backward(0)[:,self.i_::self.ratio,self.j_::self.ratio]\
+self.next_layer.reshape_b[:,self.i_::self.ratio,self.j_::self.ratio])
A2 = self.next_layer.reshape_SIGMAS2_[self.i_::self.ratio,self.j_::self.ratio]
if(pretraining):
next_back = tf.zeros_like(back)
next_sigmas = tf.ones_like(A2)
else:
next_back = back
next_sigmas = A2
rescalor = tf.reduce_min(self.SIGMAS2_patch_[self.i_::self.ratio,self.j_::self.ratio])
b2 = tf.einsum('nijabc,nijkabc->nijk',self.extract_patch(self.input-reconstruction-self.b)[:,self.i_::self.ratio,self.j_::self.ratio]*rescalor/self.SIGMAS2_patch[:,self.i_::self.ratio,self.j_::self.ratio],Wp)
bias = next_back*rescalor/tf.expand_dims(next_sigmas,0)+b2
A1 = tf.einsum('nijkabc,nijdabc->nijkd',Wp,Wp*rescalor/myexpand(self.SIGMAS2_patch_[self.i_::self.ratio,self.j_::self.ratio],[0,-4]))*(1-tf.reshape(tf.eye(self.K),[1,1,1,self.K,self.K]))
A3 = tf.einsum('kabc,kijn,ijabc->nijk',tf.square(self.W_),self.p_[:,self.i_::self.ratio,self.j_::self.ratio,0],rescalor/self.SIGMAS2_patch_[self.i_::self.ratio,self.j_::self.ratio])
A = A1+tf.matrix_diag(A3)+tf.expand_dims(tf.matrix_diag(rescalor/next_sigmas),0)
new_m = tf.transpose(tf.matrix_solve(A,tf.expand_dims(bias,-1))[:,:,:,:,0],[0,3,1,2]) # (N K I J)
# update_value_m = (forward_m+back)*self.v2[:,self.i_::self.ratio,self.j_::self.ratio,self.k_] # (N I'' J'')
# return tf.assign(self.m_,(tf.reshape(update_value_m,(self.bs,-1))))
return tf.scatter_nd_update(self.m_,self.m_indices_,tf.transpose(tf.reshape(new_m,(self.bs,-1))))
return new_m
else:
rescalor = 1#tf.reduce_min(self.SIGMAS2_patch_[self.i_::self.ratio,self.j_::self.ratio])
m_masked = self.m_*self.p_[:,:,:,0]*(1-self.mask)
reconstruction = tf.gradients(self.input_patch,self.input,tf.einsum('kijn,kabc->nijabc',m_masked,self.W_))[0]
forward = tf.einsum('nija,a->nij',self.extract_patch((self.input-reconstruction-self.b)/self.SIGMAS2,with_reshape=0)[:,self.i_::self.ratio,self.j_::self.ratio]*tf.expand_dims(self.m[:,self.i_::self.ratio,self.j_::self.ratio,self.k_],-1),tf.reshape(self.W_[self.k_],[-1]))# (N I' J')
m2v2 = tf.einsum('ijn,abc,ijabc->nij',tf.square(self.m_[self.k_,self.i_::self.ratio,self.j_::self.ratio])\
+self.v2_[self.k_,self.i_::self.ratio,self.j_::self.ratio],tf.square(self.W_[self.k_]),0.5*rescalor/self.SIGMAS2_patch_[self.i_::self.ratio,self.j_::self.ratio]) #(N I' J')
value = forward-m2v2+rescalor*tf.log(self.pi[self.k_,0])# (N I' J')
update_value = tf.nn.softmax(tf.stack([value,tf.fill([self.bs,self.Ni,self.Nj],rescalor*tf.log(self.pi[self.k_,1]))],axis=0),axis=0)
new_p = tf.scatter_nd_update(self.p_,self.indices_,tf.transpose(tf.reshape(update_value,(self.R,self.bs,-1)),[2,0,1]))
return new_p
def update_Wk(self):
rescalor = 1#tf.reduce_min(self.SIGMAS2_)
# mask = tf.reshape(tf.one_hot(self.k_,self.K),[-1,1,1])*tf.reshape(tf.one_hot(self.i_,self.Ic),[1,-1,1])tf.reshape(tf.one_hot(self.j_,self.Jc),[1,1,-1])
filters = self.filter_corr(self.W_,self.W_) # (kij k'i'j')
k4 = tf.reduce_sum(rescalor*self.S5*filters)*0.5
value = tf.gradients(k4,self.W_)[0][self.k_,self.i_,self.j_]
numerator = tf.reduce_sum((self.S3[self.k_,:,:,self.i_,self.j_,:]-tf.expand_dims(self.S6[self.k_],-1)*self.b_[self.i_:self.I+self.i_,self.j_:self.J+self.j_])*rescalor/self.SIGMAS2_[self.i_:self.I+self.i_,self.j_:self.J+self.j_],[0,1])-value
denominator = tf.einsum('ij,ijc->c',self.S4[self.k_],rescalor/self.SIGMAS2_[self.i_:self.I+self.i_,self.j_:self.J+self.j_])
return tf.scatter_nd_update(self.W_,[[self.k_,self.i_,self.j_]],[(numerator)/denominator])
def update_pi(self):
return tf.assign(self.pi,self.S8/tf.reduce_sum(self.S8,axis=1,keepdims=True))
def update_BV(self):
return tf.assign(self.b_,tf.transpose(self.S7,[1,2,0])-tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('kij,kabc->ijabc',self.S6,self.W_))[0])
def update_sigma(self):
v1 = tf.transpose(self.S1+self.S2-2*tf.transpose(self.b_,[2,0,1])*self.S7,[1,2,0])+tf.square(self.b_)
v2 = tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('kij,kabc->ijabc',self.S4,tf.square(self.W_))-2*tf.einsum('kijabc,kabc->ijabc',self.S3,self.W_))[0]
u = tf.zeros_like(self.SIGMAS2_)
pu = self.extract_patch(tf.expand_dims(u,0),with_n=0)
sigma_W = tf.pad(tf.transpose(tf.reshape(tf.einsum('ijabc,kabc->abckij',pu,self.W_),[self.Ic,self.Jc,self.C,self.K*self.I*self.J]),[3,0,1,2]),[[0,0],[self.Ic-1,self.Ic-1],[self.Jc-1,self.Jc-1],[0,0]])
patches = tf.reshape(tf.extract_image_patches(sigma_W,(1,self.Ic,self.Jc,1),(1,1,1,1),(1,1,1,1),"VALID"),(self.K*self.I*self.J,2*self.Ic-1,2*self.Jc-1,self.Ic,self.Jc,self.C))
scalar = tf.reduce_sum(self.S5* tf.transpose(tf.reshape(tf.einsum('nijabc,kabc->kijn',patches,self.W_),[self.K,2*self.Ic-1,2*self.Jc-1,self.K,self.I,self.J]),[3,4,5,0,1,2]))#(K I J K' I' J')
v3 = tf.gradients(scalar,u)[0]
v4 = tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('kij,kabc->ijabc',self.S6,self.W_))[0]*self.b_*2
value = v1+v2+v3+v4
if(self.sigma_opt=='local'):
return tf.assign(self.SIGMAS2_,value)
elif(self.sigma_opt=='channel'):
return tf.assign(self.SIGMAS2_,tf.reduce_sum(value,[0,1],keepdims=True)*tf.ones([self.Iin,self.Jin,1])/(self.Iin*self.Jin))
elif(self.sigma_opt=='global'):
return tf.assign(self.SIGMAS2_,tf.fill([self.Iin,self.Jin,self.C],tf.reduce_sum(value)/(self.Iin*self.Jin*self.C)))
class PoolLayer:
def __init__(self,input_layer,Ic,Jc,sigma='local',alpha=0.5):
self.alpha = tf.Variable(alpha)
self.sigma_opt = sigma
self.input_layer = input_layer
input_layer.next_layer = self
self.bs,self.Iin,self.Jin,self.C = input_layer.output_shape
self.Ic,self.Jc,self.K = Ic,Jc,input_layer.output_shape[-1]
K=self.K
R,self.R = Ic*Jc,Ic*Jc
self.input = input_layer.m
self.input_shape = input_layer.output_shape
self.output_shape = (self.bs,self.input_shape[-3]/self.Ic,self.input_shape[-2]/self.Jc,K)
self.D_in = prod(self.input_shape[1:])
self.I,self.J = self.output_shape[1],self.output_shape[2]
self.input_patch = self.extract_patch(self.input,with_n=1)
self.W_ = tf.Variable(tf.stack([tf.reshape(tf.one_hot(i,Ic*Jc),(Ic,Jc)) for i in xrange(Ic*Jc)]))# (R,Ic,Jc) always D_in last
self.W = self.W_
# WE DEFINE THE PARAMETERS
self.pi = tf.Variable(tf.ones((R,))/float32(R))
self.SIGMAS2_= tf.Variable(tf.ones((self.Iin,self.Jin,self.C)))
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
self.SIGMAS2_patch_= self.extract_patch(self.SIGMAS2,with_n=0)
self.SIGMAS2_patch = tf.expand_dims(self.SIGMAS2_patch_,0)
# SOME OTHER VARIABLES
self.b_ = tf.Variable(tf.zeros(self.input_shape[1:]))
self.b = tf.expand_dims(self.b_,0)
self.b_patch_= self.extract_patch(self.b,with_n=0)
self.b_patch = tf.expand_dims(self.b_patch_,0)
self.m_ = tf.Variable(tf.zeros((K,self.I,self.J,self.bs)))
self.m = tf.transpose(self.m_,[3,1,2,0]) # (N I J K)
self.p_ = tf.Variable(tf.zeros((K,self.I,self.J,self.R,self.bs)))# (K,I,J,R,N)
self.p = tf.transpose(self.p_,[4,1,2,0,3]) # (N I J K R)
self.v2_ = tf.Variable(tf.zeros((self.K,self.I,self.J,self.bs))) # (K I J N)
self.v2 = tf.transpose(self.v2_,[3,1,2,0])
# STATISTICS
self.S1 = tf.Variable(tf.zeros((self.K,self.Iin,self.Jin)))
self.S2 = tf.Variable(tf.zeros((self.K,self.Iin,self.Jin)))
self.S3 = tf.Variable(tf.zeros((self.K,self.I,self.J,self.R,self.Ic,self.Jc)))
self.S4 = tf.Variable(tf.zeros((self.K,self.I,self.J,self.R)))
self.S5 = tf.Variable(tf.zeros((self.K,self.I,self.J,self.R)))
self.S6 = tf.Variable(tf.zeros((self.K,self.Iin,self.Jin)))
self.S7 = tf.Variable(tf.zeros((self.R,)))
#
input_layer.next_layer = self
self.W_indices=array([0])
self.m_indices=array([0])
self.p_indices=array([0])
def update_S(self):
S1 = tf.reduce_sum(tf.square(self.input_layer.m_),3)/self.bs
S2 = tf.reduce_sum(self.input_layer.v2_,3)/self.bs
S3 = tf.einsum('nijabc,cijrn->cijrab',self.input_patch,tf.expand_dims(self.m_,3)*self.p_)/self.bs
S4 = tf.reduce_sum(tf.expand_dims(tf.square(self.m_)+self.v2_,3)*self.p_,4)/self.bs
S5 = tf.reduce_sum(tf.expand_dims(self.m_,3)*self.p_,4)/self.bs
S6 = tf.reduce_sum(self.input_layer.m_,3)/self.bs
S7 = tf.reduce_sum(self.p_,[0,1,2,4])/self.bs
return tf.group(tf.assign(self.S1,self.alpha*S1+(1-self.alpha)*self.S1),tf.assign(self.S2,self.alpha*S2+(1-self.alpha)*self.S2),
tf.assign(self.S3,self.alpha*S3+(1-self.alpha)*self.S3),tf.assign(self.S4,self.alpha*S4+(1-self.alpha)*self.S4),
tf.assign(self.S5,self.alpha*S5+(1-self.alpha)*self.S5),tf.assign(self.S6,self.alpha*S6+(1-self.alpha)*self.S6),
tf.assign(self.S7,self.alpha*S7+(1-self.alpha)*self.S7))
def extract_patch(self,u,with_n=1,with_reshape=1):
patches = tf.extract_image_patches(u,(1,self.Ic,self.Jc,1),(1,self.Ic,self.Jc,1),(1,1,1,1),"VALID")
if(with_reshape):
if(with_n): return tf.reshape(patches,(self.bs,self.output_shape[1],self.output_shape[2],self.Ic,self.Jc,self.C))
else: return tf.reshape(patches,(self.output_shape[1],self.output_shape[2],self.Ic,self.Jc,self.C))
return patches
# ---- BACKWARD OPERATOR ----
def deconv(self,input=None,masked_m=0,masked_w=0,m=None,p=None):
if(m is None):m=self.m_
if(p is None):p=self.p_
return tf.gradients(self.input_patch,self.input,tf.einsum('kijn,kijrn,rab->nijabk',m,p,self.W_))[0]
def sample(self,M,K=None,sigma=1):
#multinomial returns [K,n_samples] with integer value 0,...,R-1
if(isinstance(self.input_layer,InputLayer)):sigma=0
noise = sigma*tf.random_normal(self.input_shape)*tf.sqrt(self.SIGMAS2)
sigma_hot = tf.one_hot(tf.reshape(tf.multinomial(tf.expand_dims(tf.log(self.pi),0),self.bs*self.I*self.J*self.K),(self.K,self.I,self.J,self.bs)),self.R) # (K I J N R)
return self.deconv(m=tf.transpose(M,[3,1,2,0]),p=tf.transpose(sigma_hot,[0,1,2,4,3]))+noise+self.b
def evidence(self): return 0
def likelihood(self,batch=0,pretraining=False):
if(batch==0):
if(pretraining==False):
extra_k = 0
else:
extra_k = -0.5*tf.reduce_sum(tf.square(self.m_)+self.v2_)/self.bs
a1 = -tf.einsum('nijc,ijc->',tf.square(self.input-self.b)+self.input_layer.v2,1/(2*self.SIGMAS2_*self.bs))
a2 = tf.reduce_sum((self.input-self.b)*self.deconv()/self.SIGMAS2)/self.bs
a3 = -tf.einsum('kijrn,rab,ijabc->',tf.expand_dims(tf.square(self.m_)+self.v2_,3)*self.p_,tf.square(self.W_),1/self.SIGMAS2_patch_)*0.5/self.bs
k1 = -float32(self.D_in/2.0)*tf.log(2*PI_CONST)-tf.reduce_sum(tf.log(self.SIGMAS2_))/2
k2 = tf.einsum('r,kijrn->',tf.log(self.pi),self.p_)/float32(self.bs)
return k1+k2+(a1+a2+a3)+extra_k
else:
k0 = -float32(self.D_in/2.0)*tf.log(2*PI_CONST)-tf.reduce_sum(tf.log(self.SIGMAS2_+eps))/2
k1 = tf.reduce_sum((-self.S1-self.S2-tf.square(tf.transpose(self.b_,[2,0,1]))+2*self.S6*tf.transpose(self.b_,[2,0,1]))/tf.transpose(self.SIGMAS2_,[2,0,1]))*0.5
k2 = tf.reduce_sum(self.S3*tf.einsum('rab,ijabc->cijrab',self.W_,1/self.SIGMAS2_patch_))
k3 = -tf.reduce_sum(self.S4*tf.einsum('rab,ijabc->cijr',tf.square(self.W_),1/self.SIGMAS2_patch_))*0.5
k4 = -tf.einsum('cijr,rab,ijabc->',self.S5,self.W_,self.b_patch_/self.SIGMAS2_patch_)*0.5
k5 = tf.reduce_sum(self.S7*tf.log(self.pi))
return k0+k1+k2+k3+k4+k5
def KL(self,pretraining=False):
return self.likelihood(0,pretraining)+(-tf.reduce_sum(self.p_*tf.log(self.p_+eps))+float32(0.5)*tf.reduce_sum(tf.log(self.v2_+eps)))/float32(self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
def update_dropout(self):
return []
def update_v2(self,pretraining=False):# DONE
if(isinstance(self.next_layer,ConvPoolLayer)): v_value = self.next_layer.SIGMAS2 # (N I J K)
else: v_value = self.next_layer.reshape_SIGMAS2 # (N I J K)
if(pretraining): next_sigmas = tf.ones_like(v_value)
else: next_sigmas = v_value
rescalor = tf.reduce_min(self.SIGMAS2_)
a4 = tf.transpose(rescalor/self.SIGMAS2,[3,1,2,0])#tf.einsum('kijrn,rab,ijabc->kijn',self.p_,tf.square(self.W_),rescalor/self.SIGMAS2_patch_) # (K I J N)
return tf.assign(self.v2_,rescalor/(tf.einsum('kijabn,ijabk->kijn',tf.reshape(self.p_,[self.K,self.I,self.J,self.Ic,self.Jc,self.bs]),rescalor/self.SIGMAS2_patch_)+tf.transpose(rescalor/next_sigmas,[3,1,2,0])))
def update_m(self,mp_opt=0,pretraining=False):
### UPDATE M
# rescalor = tf.reduce_min(self.SIGMAS2_)
# if(isinstance(self.next_layer,ConvPoolLayer)): v_value = self.next_layer.SIGMAS2 # (N I J K)
# else: v_value = self.next_layer.reshape_SIGMAS2 # (N I J K)
# if(pretraining):
# next_sigmas = tf.ones_like(v_value)
# else:
# next_sigmas = v_value
# a4 = tf.einsum('kijrn,rab,ijabc->kijn',self.p_,tf.square(self.W_),rescalor/self.SIGMAS2_patch_) # (K I J N)
# v2_=1/(rescalor/next_sigmas+tf.transpose(a4))
if(mp_opt==0):
forward = tf.einsum('nijabc,cijrn,rab->nijc',self.extract_patch((self.input-self.b)/self.SIGMAS2),self.p_,self.W_)# (N I J K)
if(isinstance(self.next_layer,ConvLayer)):
back = (self.next_layer.deconv()+self.next_layer.b)/self.next_layer.SIGMAS2
else:
back = (self.next_layer.backward(0)+self.next_layer.reshape_b)/self.next_layer.reshape_SIGMAS2
if(pretraining):
back = tf.zeros_like(back)
update_value_m = (forward+back)*self.v2 # (N I J K)
new_m = tf.assign(self.m_,tf.transpose(update_value_m,[3,1,2,0]))
return new_m
else:
# return []
forward = tf.transpose(tf.reshape(tf.einsum('nijabc,cijn->cijnab',self.extract_patch((self.input-self.b)/self.SIGMAS2),self.m_),[self.K,self.I,self.J,self.bs,self.R]),[0,1,2,4,3])#tf.einsum('nijabc,cijn,rab->cijrn',self.extract_patch((self.input-self.b)/self.SIGMAS2),self.m_,self.W_)# (K I J R N)
# m2v2 = tf.einsum('cijn,rab,ijabc->cijrn',tf.square(self.m_)+self.v2_,tf.square(self.W_),0.5/self.SIGMAS2_patch_) #(N I' J')
# value = forward-m2v2+myexpand(tf.log(self.pi),[0,0,0,-1])# (N I' J')
update_value = tf.nn.softmax(forward,axis=3)
new_p = tf.assign(self.p_,update_value)
return new_p
def update_Wk(self):
return []
def update_pi(self):
return tf.assign(self.pi,self.S7/tf.reduce_sum(self.S7))
def update_BV(self):
return tf.assign(self.b_,tf.transpose(self.S6,[1,2,0])-tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('cijr,rab->ijabc',self.S5,self.W_))[0])
def update_sigma(self):
v1 = tf.transpose(self.S1+self.S2,[1,2,0])-2*self.b_*tf.transpose(self.S6,[1,2,0])+tf.square(self.b_)
v2 = -2*tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('cijrab,rab->ijabc',self.S3,self.W_))[0]
v3 = tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('cijr,rab->ijabc',self.S4,tf.square(self.W_)))[0]
v4 = tf.gradients(self.SIGMAS2_patch_,self.SIGMAS2_,tf.einsum('cijr,rab->ijabc',self.S5,self.W_))[0]*self.b_
value = v1+v2+v3+v4
if(self.sigma_opt=='local'):
return tf.assign(self.SIGMAS2_,value)
elif(self.sigma_opt=='channel'):
return tf.assign(self.SIGMAS2_,tf.reduce_sum(value,[0,1],keepdims=True)*tf.ones([self.Iin,self.Jin,1])/(self.Iin*self.Jin))
elif(self.sigma_opt=='global'):
return tf.assign(self.SIGMAS2_,tf.fill([self.Iin,self.Jin,self.C],tf.reduce_sum(value)/(self.Iin*self.Jin*self.C)))
class ConvPoolLayer:
def __init__(self,input_layer,K,Ic,Jc,Ir,Jr,R,sparsity_prior = 0,leakiness=None,sigma='local',p_drop=0):
self.leakiness = leakiness
self.sigma_opt = sigma
self.p_drop = p_drop
self.sparsity_prior = sparsity_prior
self.input_layer = input_layer
input_layer.next_layer = self
self.bs,self.Iin,self.Jin,self.C = input_layer.output_shape
self.Ic,self.Jc,self.Ir,self.Jr,self.K,self.R = Ic,Jc,Ir,Jr,K,R
self.input = input_layer.m
self.input_shape = input_layer.output_shape
self.conv_output_shape = (self.bs,self.input_shape[-3]-self.Ic+1,self.input_shape[-2]-self.Jc+1,K)
self.output_shape = (self.conv_output_shape[0],self.conv_output_shape[1]/Ir,self.conv_output_shape[2]/Jr,self.conv_output_shape[3])
self.D_in = prod(self.input_shape[1:])
self.I,self.J = self.output_shape[1],self.output_shape[2]
self.input_small_patch = self.extract_small_patch(self.input,with_n=1)
self.input_large_patch = self.extract_large_patch(self.input,with_n=1)
self.pi_ = PI_CONST
if(leakiness is None):
init = tf.random_normal_initializer(0,0.1)#tf.orthogonal_initializer()
self.W_ = tf.Variable(init([self.K,self.R,self.Ic,self.Jc,self.C]))
self.W = self.W_
elif(leakiness=='relu'):
self.W_ = tf.Variable(tf.truncated_normal((self.K,1,self.Ic,self.Jc,self.C),0,1))# (K,R,Ic,Jc,C) always D_in last
self.W = tf.concat([self.W_,tf.zeros_like(self.W_)],axis=1)
elif(leakiness=='abs'):
self.W_ = tf.Variable(tf.random_normal((self.K,1,self.Ic,self.Jc,self.C)))# (K,R,Ic,Jc,C) always D_in last
self.W = tf.concat([self.W_,-self.W_],axis=1)
# WE DEFINE THE PARAMETERS
self.pi = tf.Variable(mysoftmax(tf.random_normal((K,R)),axis=1))
self.SIGMAS2_= tf.Variable(tf.ones((self.Iin,self.Jin,self.C)))
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
self.SIGMAS2_large_patch_= self.extract_large_patch(self.SIGMAS2,with_n=0)
self.SIGMAS2_large_patch = tf.expand_dims(self.SIGMAS2_large_patch_,0)
self.SIGMAS2_small_patch_= self.extract_small_patch(self.SIGMAS2,with_n=0)
self.SIGMAS2_small_patch = tf.expand_dims(self.SIGMAS2_small_patch_,0)
############################### WE DEFINE SOME HELPER VARIABLES FOR LATER FUNCTIONS ###############################################
self.multiplied_x = tf.reshape(tf.extract_image_patches(tf.transpose(tf.reshape(tf.transpose(self.input_large_patch,[3,4,5,0,1,2]),[self.Ic+self.Ir-1,self.Jc+self.Jr-1,self.C,self.bs*self.I*self.J]),[3,0,1,2]),(1,self.Ic,self.Jc,1),(1,1,1,1),(1,1,1,1),"VALID"),[self.bs,self.I,self.J,self.Ir,self.Jr,self.Ic,self.Jc,self.C])
#####
self.dx = tf.zeros((self.bs,self.conv_output_shape[1],self.conv_output_shape[2],1)) # (N I' J' 1)
self.dxR = tf.zeros((self.bs,self.conv_output_shape[1],self.conv_output_shape[2],self.R)) # (N I' J' R)
self.dxK = tf.zeros((self.bs,self.conv_output_shape[1],self.conv_output_shape[2],self.K)) # (N I' J' K)
#
self.dp = tf.reshape(tf.extract_image_patches(self.dx,(1,Ir,Jr,1),(1,Ir,Jr,1),(1,1,1,1),"VALID"),(self.bs,self.I,self.J,Ir,Jr)) # (N I J Ir Jr)
self.dpK = tf.reshape(tf.extract_image_patches(self.dxK,(1,Ir,Jr,1),(1,Ir,Jr,1),(1,1,1,1),"VALID"),(self.bs,self.I,self.J,Ir,Jr,K)) # (N I J Ir Jr K)
self.dpR = tf.reshape(tf.extract_image_patches(self.dxR,(1,Ir,Jr,1),(1,Ir,Jr,1),(1,1,1,1),"VALID"),(self.bs,self.I,self.J,Ir,Jr,self.R)) # (N I J Ir Jr K)
#
self.dpK_pool= mysumpool(self.dxK,[self.Ir,self.Jr]) # (N I J K)
self.dpR_pool= mysumpool(self.dxR,[self.Ir,self.Jr]) # (N I J K)
self.dp_pool = mysumpool(self.dx,[self.Ir,self.Jr]) # (N I J 1)
#
self.r_large_patch=tf.transpose(tf.reshape(tf.transpose(self.input_large_patch,[3,4,5,0,1,2]),[self.Ic+self.Ir-1,self.Jc+self.Jr-1,self.C,self.bs*self.I*self.J]),[3,0,1,2]) #(NIJ,??,??,C)
self.r_small_patch=tf.reshape(tf.extract_image_patches(self.r_large_patch,(1,Ic,Jc,1),(1,1,1,1),(1,1,1,1),"VALID"),(self.bs*self.I*self.J,Ir,Jr,self.Ic,self.Jc,self.C))
# SOME OTHER VARIABLES
self.b_ = tf.Variable(tf.zeros(self.input_shape[1:]))
self.b = tf.expand_dims(self.b_,0)
self.m_ = tf.Variable(tf.zeros((K,self.I,self.J,self.bs)))
self.m = tf.transpose(self.m_,[3,1,2,0]) # (N I J K)
self.p_ = tf.Variable(mysoftmax(tf.random_normal((K,self.I,self.J,self.R,self.bs)),axis=3))# (K,I,J,R,N)
self.p = tf.transpose(self.p_,[4,1,2,0,3]) # (N I J K R)
self.p_expand= self.unpool_R(self.p)
self.rho_ = tf.Variable(mysoftmax(tf.random_normal((K,self.I,self.J,self.Ir,self.Jr,self.bs)),axis=[3,4])) # (K I J Ir Jr N)
self.rho_tensor = self.assemble_pool_patch(tf.transpose(self.rho_,[5,1,2,3,4,0]),self.K) # (N I' J' K)
self.v2_ = tf.Variable(tf.ones((self.K,self.I,self.J,self.bs))) # (K I J N)
self.v2 = tf.transpose(self.v2_,[3,1,2,0])
self.drop_ = tf.Variable(tf.ones((K,2,self.I,self.J,self.bs))*tf.reshape(tf.one_hot(1,2),(1,2,1,1,1))) # (K 2 I J N)
self.drop = tf.transpose(self.drop_,[1,4,2,3,0]) #(2 N I J K)
#
input_layer.next_layer = self
self.k_ = tf.placeholder(tf.int32)
self.i_ = tf.placeholder(tf.int32)
self.j_ = tf.placeholder(tf.int32)
self.r_ = tf.placeholder(tf.int32)
self.ratio = (Ic-1)/Ir+1
self.Ni = tf.cast(tf.ceil((self.I-tf.cast(self.i_,tf.float32))/self.ratio),tf.int32) # NUMBER OF TERMS
self.Nj = tf.cast(tf.ceil((self.J-tf.cast(self.j_,tf.float32))/self.ratio),tf.int32) # NUMBER OF TERMS
self.xi,self.yi= tf.meshgrid(tf.range(self.j_,self.J,self.ratio),tf.range(self.i_,self.I,self.ratio)) # THE SECOND IS CONSTANT (meshgrid)
self.indices_= tf.concat([tf.fill([self.Ni*self.Nj,1],self.k_),tf.reshape(self.yi,(self.Ni*self.Nj,1)),tf.reshape(self.xi,(self.Nj*self.Ni,1))],axis=1) # (V 3) indices where the 1 pops
self.W_indices = [a for a in itertools.product(range(self.K),range(1),range(self.Ic),range(self.Jc))]
self.W_indices = asarray(self.W_indices)
self.indices = asarray([a for a in itertools.product(range(self.ratio),range(self.ratio),range(self.K))])
self.m_indices = self.indices
self.tf_indices= tf.Variable(asarray(self.indices).astype('int32'),trainable=False)
mask = tf.reshape(tf.one_hot(self.k_,self.K),(self.K,1,1,1))*tf.reshape(tf.tile(tf.one_hot(self.i_,self.ratio),[(self.I/self.ratio+1)]),(1,(self.I/self.ratio+1)*self.ratio,1,1))*tf.reshape(tf.tile(tf.one_hot(self.j_,self.ratio),[self.J/self.ratio+1]),(1,1,(self.J/self.ratio+1)*self.ratio,1))
self.mask = mask[:,:self.I,:self.J] # (K I J 1)
### first to go from the pooling patches to the conv output for (i) one filter k and (ii) all filters K
def extract_small_patch(self,u,with_n=1,with_reshape=1):
patches = tf.extract_image_patches(u,(1,self.Ic,self.Jc,1),(1,1,1,1),(1,1,1,1),"VALID")
if(with_reshape):
if(with_n): return tf.reshape(patches,(self.bs,self.conv_output_shape[1],self.conv_output_shape[2],self.Ic,self.Jc,self.C))
else: return tf.reshape(patches,(self.conv_output_shape[1],self.conv_output_shape[2],self.Ic,self.Jc,self.C))
return patches
def extract_large_patch(self,u,with_n=1,with_reshape=1):
patches = tf.extract_image_patches(u,(1,self.Ir+self.Ic-1,self.Jr+self.Jc-1,1),(1,self.Ir,self.Jr,1),(1,1,1,1),"VALID")
if(with_reshape):
if(with_n): return tf.reshape(patches,(self.bs,self.I,self.J,self.Ir+self.Ic-1,self.Jr+self.Jc-1,self.C))
else: return tf.reshape(patches,(self.I,self.J,self.Ir+self.Ic-1,self.Jr+self.Jc-1,self.C))
return patches
def assemble_small_patch(self,u):
return tf.gradients(self.input_small_patch,self.input,u)[0]
def assemble_large_patch(self,u):
return tf.gradients(self.input_large_patch,self.input,u)[0]
def assemble_pool_patch(self,u,k=1):
# the following takes as input (N I J Ir Jr) returns (N I' J' 1) or (N I J Ir Jr K) returns (N I' J' K)
if(k==1): return tf.gradients(self.dp,self.dx,u)[0]
if(k==self.R): return tf.gradients(self.dpR,self.dxR,u)[0]
else : return tf.gradients(self.dpK,self.dxK,u)[0]
def unpool(self,u,k=1):
# takes (N I J 1) returns (N I' J' 1) or takes (N I J R) returns (N I' J' R) or takes (N I J K) returns (N I' J' K)
if(k==1) : return tf.gradients(self.dp_pool,self.dx,tf.expand_dims(u,-1))[0]
elif(k==self.R) :return tf.gradients(self.dpR_pool,self.dxR,u)[0]
elif(k==self.K) :return tf.gradients(self.dpK_pool,self.dxK,u)[0]
def unpool_R(self,u):# takes (N I J K R) returns (N I' J' K R)
return tf.transpose(tf.map_fn(lambda i:self.unpool(i,self.K),tf.transpose(u,[4,0,1,2,3]),back_prop=False),[1,2,3,4,0])
def normwithsigma_bigpatch_k(self,k): #helper
Wflat = self.get_bigpatch_k(k) # (N I J ?? ?? C)
return tf.einsum('nijabc,ijabc->',tf.square(Wflat),1/(2*self.bs*self.SIGMAS2_large_patch_))
def get_bigpatch_k(self,k): #helper_
mrhop = tf.einsum('ijn,ijpqn,ijrn,rabc->nijpqabc',self.m_[k]*self.drop_[k,1],self.rho_[k],self.p_[k],self.W[k])# (N I J Ir Jr Ic Jc C)
return tf.gradients(self.multiplied_x,self.input_large_patch,mrhop)[0] #(N I J ?? ?? C) # (N I J ?? ?? C)
# ---- INITIALIZER ----
def update_BV(self):
return tf.assign(self.b_,tf.reduce_sum(tf.reduce_sum(self.input-self.deconv(),0)/(self.bs*self.SIGMAS2_),[0,1],keepdims=True)*tf.ones((self.Iin,self.Jin,1))/tf.reduce_sum(1/self.SIGMAS2_,[0,1],keepdims=True))
def init_thetaq(self):
new_p = tf.assign(self.p_,mysoftmax(tf.random_uniform((self.K,self.I,self.J,self.R,self.bs)),axis=3))
new_rho = tf.assign(self.rho_,mysoftmax(tf.random_uniform((self.K,self.I,self.J,self.Ir,self.Jr,self.bs)),axis=[3,4]))
new_v = tf.assign(self.v2_,tf.ones((self.K,self.I,self.J,self.bs)))
new_m = tf.assign(self.m_,tf.random_normal((self.K,self.I,self.J,self.bs)))
return [new_m,new_p,new_v,new_rho]
# ---- BACKWARD OPERATOR ----
def deconv(self,input=None,masked_m=0,masked_w=0,m=None,p=None):
if(m is None):m=self.m_
if(p is None):p=self.p_
if(input is not None):
return self.small_patch2tensor(input)
if(masked_w):
if(self.leakiness is None):
mask = tf.reshape(tf.one_hot(self.i_,self.Ic),[1,1,self.Ic,1,1])*tf.reshape(tf.one_hot(self.j_,self.Jc),[1,1,1,self.Jc,1])*tf.reshape(tf.one_hot(self.k_,self.K),[self.K,1,1,1,1])*tf.reshape(tf.one_hot(self.r_,self.R),[1,self.R,1,1,1])
else:
mask = tf.reshape(tf.one_hot(self.i_,self.Ic),[1,1,self.Ic,1,1])*tf.reshape(tf.one_hot(self.j_,self.Jc),[1,1,1,self.Jc,1])*tf.reshape(tf.one_hot(self.k_,self.K),[self.K,1,1,1,1])
W=self.W*(1-mask)
else:
W=self.W
p_w = tf.einsum('nijkr,krabc->nijkabc',self.unpool_R(tf.transpose(p,[4,1,2,0,3])),W) # (N I' J' K Ic Jc C)
if(masked_m==1):
m_rho = self.assemble_pool_patch(tf.transpose(self.rho_*myexpand(m*self.drop_[:,1]*(1-self.mask),[-2,-2]),[5,1,2,3,4,0]),self.K)# (N I J Ir JR K)->(N I' J' K)
elif(masked_m==-1):
m_rho = self.assemble_pool_patch(tf.transpose(self.rho_[self.k_]*myexpand(self.drop_[self.k_,1]*self.mask[self.k_],[2,3]),[4,0,1,2,3]),1)# (N I' J' 1)
return self.assemble_small_patch(myexpand(m_rho,[-1,-1])*p_w[:,:,:,self.k_])
else:
m_rho = self.assemble_pool_patch(tf.transpose(self.rho_*myexpand(m*self.drop_[:,1],[-2,-2]),[5,1,2,3,4,0]),self.K)# (N I' J' K)
if(masked_w):
return self.assemble_small_patch(tf.einsum('nijk,nijkabc->nijabc',m_rho,p_w)),W
return self.assemble_small_patch(tf.einsum('nijk,nijkabc->nijabc',m_rho,p_w))
def sample(self,M,K=None,sigma=1):
#multinomial returns [K,n_samples] with integer value 0,...,R-1
if(isinstance(self.input_layer,InputLayer)):sigma=0
noise = sigma*tf.random_normal(self.input_shape)*tf.sqrt(self.SIGMAS2)
sigma_hot = tf.one_hot(tf.reshape(tf.multinomial(tf.log(self.pi),self.bs*self.I*self.J),(self.K,self.I,self.J,self.bs)),self.R) # (K I J N R)
sigma_hot_reshape= self.unpool_R(tf.transpose(sigma_hot,[3,1,2,0,4])) # (R N I' J' K) -> (N I' J' K R)
sigma_hot_w = tf.einsum('nijkr,krabc->nijkabc',sigma_hot_reshape,self.W) # (N I' J' K Ic Jc C)
pool_hot = tf.one_hot(tf.reshape(tf.multinomial(tf.zeros((1,self.Ir*self.Jr)),self.K*self.bs*self.I*self.J),(self.K,self.I,self.J,self.bs)),self.Ir*self.Jr) # (K I J N IrxJr)
pool_hot_reshape = tf.transpose(tf.reshape(pool_hot,[self.K,self.I,self.J,self.bs,self.Ir,self.Jr]),[3,1,2,4,5,0]) # (N I J Ir Jr K)
reverted = self.assemble_pool_patch(myexpand(M,[-2,-2])*pool_hot_reshape,self.K) # (N I' J' K)
return self.assemble_small_patch(tf.einsum('nijkabc,nijk->nijabc',sigma_hot_w,reverted))+noise+self.b
def likelihood(self):
a1 = -tf.einsum('nijc,ijc->',tf.square(self.input-self.deconv()-self.b),1/(2*self.SIGMAS2_*self.bs))
a2 = -tf.einsum('cijn,ijc->',self.input_layer.v2_,1/(2*self.SIGMAS2_*self.bs))
a3 = tf.reduce_sum(tf.map_fn(self.normwithsigma_bigpatch_k,tf.range(self.K),dtype=tf.float32,back_prop=False))
a40 = tf.einsum('krijc,abijc->krab',tf.square(self.W),1/(2*self.SIGMAS2_small_patch_*self.bs)) #(K R I' J')
a41 = tf.einsum('nijkr,krij->nijk',self.p_expand,a40)*self.rho_tensor # (N I' J' K)
a4 = -tf.einsum('nijk,kijn->',mysumpool(a41,[self.Ir,self.Jr]),(tf.square(self.m_)+self.v2_)*self.drop_[:,1])
k1 = -tf.reduce_sum(tf.log(self.SIGMAS2_))/2
k2 = tf.einsum('kr,krn->',tf.log(self.pi),tf.reduce_sum(self.p_,[1,2]))/float32(self.bs)
k3 = -float32(self.D_in/2.0)*tf.log(2*PI_CONST)
return k1+k2+k3+(a1+a2+a3+a4)-self.sparsity_prior*tf.reduce_sum(tf.square(self.W))
def KL(self):
return self.likelihood()+(-tf.reduce_sum(self.p_*tf.log(self.p_))-tf.reduce_sum(self.rho_*tf.log(self.rho_))+float32(0.5)*tf.reduce_sum(tf.log(self.v2_)))/float32(self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
def update_dropout(self):
return []
def update_v2(self):# DONE
if(isinstance(self.next_layer,ConvPoolLayer)): v_value = self.next_layer.SIGMAS2 # (N I J K)
else: v_value = self.next_layer.reshape_SIGMAS2 # (N I J K)
a40 = tf.einsum('nijkr,krabc,ijabc,nijk->nijk',self.unpool_R(self.p),tf.square(self.W),1/self.SIGMAS2_small_patch_,self.rho_tensor) # (N I' J' K)
a4 = mysumpool(a40,[self.Ir,self.Jr])*self.drop[1] #( N I J K)
return tf.assign(self.v2_,tf.transpose(v_value/(1+a4*v_value),[3,1,2,0]))
def update_m(self,mp_opt=0):
reconstruction = (self.input-self.b-self.deconv(None,1,0))/self.SIGMAS2
Wk = self.W[self.k_]
### UPDATE M
if(mp_opt==0):
forward_m = tf.reduce_sum(self.extract_large_patch(reconstruction*self.deconv(None,-1,0),with_reshape=0),3) # (N I J ??) -> (N I J)
if(isinstance(self.next_layer,ConvPoolLayer)): back = (self.next_layer.deconv()[:,:,:,self.k_]+self.next_layer.b[:,:,:,self.k_])/self.next_layer.SIGMAS2[:,:,:,self.k_]
else: back = (self.next_layer.backward(0)[:,:,:,self.k_]+self.next_layer.reshape_b[:,:,:,self.k_])/self.next_layer.reshape_SIGMAS2[:,:,:,self.k_]
update_value_m = (forward_m+back)*self.v2[:,:,:,self.k_] # (N I'' J'')
new_m = tf.scatter_nd_update(self.m_,self.indices_,tf.transpose(tf.reshape(update_value_m[:,self.i_::self.ratio,self.j_::self.ratio],(self.bs,-1))))
return new_m
elif(mp_opt==1):
new_m = self.m_
new_m_k = self.m_[self.k_]
m_rho = self.unpool(tf.transpose(new_m_k*self.drop_[self.k_,1]*self.mask[self.k_],[2,0,1]),1)[:,:,:,0]*self.rho_tensor[:,:,:,self.k_]# (N I' J')
deconv_with2 = tf.map_fn(lambda w:tf.reduce_sum(self.extract_large_patch(self.assemble_small_patch(tf.einsum('nij,abc->nijabc',m_rho,w))*reconstruction,with_reshape=0)[:,self.i_::self.ratio,self.j_::self.ratio],axis=3),Wk,dtype=tf.float32,back_prop=False) # (R N I'' J'')
# M2V2
a40 = tf.einsum('rabc,ijabc,nij->nijr',tf.square(Wk),0.5/self.SIGMAS2_small_patch_,self.rho_tensor[:,:,:,self.k_]) #(N I' J' R)
a4 = tf.einsum('nijr,ijn->rnij',mysumpool(a40,[self.Ir,self.Jr]),tf.square(new_m_k)+self.v2_[self.k_])[:,:,self.i_::self.ratio,self.j_::self.ratio] # (R N I'' J'')
update_value = mysoftmax(deconv_with2-a4+myexpand(tf.log(self.pi[self.k_]),[-1,-1,-1]),axis=0,coeff=eps)# (R N I'' J'')
new_p = tf.scatter_nd_update(self.p_,self.indices_,tf.transpose(tf.reshape(update_value,(self.R,self.bs,-1)),[2,0,1]))
return new_p
elif(mp_opt==2):
new_m = self.m_
new_m_k = self.m_[self.k_]
new_p = self.p_
new_p_k = new_p[self.k_]
mp_reverted = self.unpool(tf.einsum('ijn,ijrn->nijr',self.drop_[self.k_,1]*new_m_k,new_p_k),self.R) # (N I' J' R)
proj2 = tf.einsum('nijr,rabc,nijabc->nij',mp_reverted,Wk,self.extract_small_patch(reconstruction)) # (N I' J')
# M2V2
a43 = tf.einsum('ijn,ijrn->nijr',self.drop_[self.k_,1]*(tf.square(new_m_k)+self.v2_[self.k_]),new_p_k) # (N I J R)
a44 = tf.einsum('nijr,rabc,ijabc->nij',self.unpool(a43,self.R),tf.square(self.W[self.k_]),0.5/self.SIGMAS2_small_patch_) # (N I' J')
V = tf.reshape(tf.extract_image_patches(tf.expand_dims(proj2-a44,-1),(1,self.Ir,self.Jr,1),(1,self.Ir,self.Jr,1),(1,1,1,1),"VALID"),
(self.bs,self.I,self.J,self.Ir,self.Jr)) # (N I J Ir Jr)
update_value_rho = mysoftmax(V[:,self.i_::self.ratio,self.j_::self.ratio],axis=[3,4],coeff=eps)# (N I'' J'' Ir Jr)
new_rho = tf.scatter_nd_update(self.rho_,self.indices_,tf.transpose(tf.reshape(tf.transpose(update_value_rho,[3,4,0,1,2]),(self.Ir,self.Jr,self.bs,-1)),[3,0,1,2]))
return new_rho
def update_Wk(self):
# return []
i = self.i_
j = self.j_
k = self.k_
r = self.r_
## FIRST COMPUTE DENOMINATOR
cropped_sigma = self.SIGMAS2_[self.i_:self.input_shape[1]-self.Ic+1+self.i_,self.j_:self.input_shape[2]-self.Jc+1+self.j_]
## NOW COMPUTE NUMERATOR
deconv,masked_W = self.deconv(None,0,1)
reconstruction = self.input-self.b-deconv # (N Iin Jin C)
cropped_reconstruction = reconstruction[:,self.i_:self.input_shape[1]-self.Ic+1+self.i_,self.j_:self.input_shape[2]-self.Jc+1+self.j_] # (N I'' J'' C)
if(self.leakiness is None):
m2v2_augmented = self.unpool(tf.transpose((tf.square(self.m_[self.k_])+self.v2_[self.k_])*self.p_[self.k_,:,:,self.r_]*self.drop_[self.k_,1],[2,0,1]),1)[:,:,:,0]*self.rho_tensor[:,:,:,self.k_] # ( N I' J')
denominator = tf.einsum('nij,ijc->c',m2v2_augmented,1/cropped_sigma)# (C)
m_reverted = self.unpool(tf.transpose(self.m_[self.k_]*self.p_[self.k_,:,:,self.r_],[2,0,1]),1)[:,:,:,0]*self.rho_tensor[:,:,:,self.k_] # ( N I' J')
proj = tf.einsum('nijc,nij->c',cropped_reconstruction/tf.expand_dims(cropped_sigma,0),m_reverted) # (C)
t_m_rho_p = tf.einsum('ijn,ijpqn,ijrn->nijpqr',self.m_[self.k_],self.rho_[k],self.p_[k]) # (N I J Ir Jr R)
large_patch= tf.gradients(self.multiplied_x,self.input_large_patch,tf.einsum('nijpqr,rabc->nijpqabc',t_m_rho_p,masked_W[self.k_]))[0]/self.SIGMAS2_large_patch # (N I J ?? ?? C)
selected_W = large_patch[:,:,:,self.i_:self.i_+self.Ir,self.j_:self.j_+self.Jr] # (N,I,J,Ir,Jr,C)
proj2 = tf.einsum('nijabc,nijab->c',selected_W,t_m_rho_p[:,:,:,:,:,self.r_]) # ( C)
new_w = tf.scatter_nd_update(self.W_,[[self.k_,self.r_,self.i_,self.j_]],[(proj+proj2)/(denominator+self.sparsity_prior)])
return [new_w]
else:# TO DOOOO
m2v2_augmented = self.unpool(tf.transpose((tf.square(self.m_[self.k_])+self.v2_[self.k_])\
*(self.p_[self.k_,:,:,0]+(self.leakiness**2)*self.p_[self.k_,:,:,1])*self.drop_[self.k_,1],[2,0,1]),1)[:,:,:,0]*self.rho_tensor[:,:,:,self.k_] # ( N I' J')
denominator = tf.einsum('nij,ijc->c',m2v2_augmented,1/cropped_sigma)# (C)
m_reverted = self.unpool(tf.transpose(self.m_[self.k_]*(self.p_[self.k_,:,:,0]+self.p_[self.k_,:,:,1]*self.leakiness),[2,0,1]),1)[:,:,:,0]*self.rho_tensor[:,:,:,self.k_]#( N I' J')
proj = tf.einsum('nijc,nij->c',cropped_reconstruction/tf.expand_dims(cropped_sigma,0),m_reverted) # (C)
t_m_rho_p = tf.einsum('ijn,ijpqn,ijrn->nijpqr',self.m_[self.k_],self.rho_[k],self.p_[k]) # (N I J Ir Jr R)
large_patch= tf.gradients(self.multiplied_x,self.input_large_patch,tf.einsum('nijpqr,rabc->nijpqabc',t_m_rho_p,masked_W[self.k_]))[0]/self.SIGMAS2_large_patch # (N I J ?? ?? C)
selected_W = large_patch[:,:,:,self.i_:self.i_+self.Ir,self.j_:self.j_+self.Jr] # (N,I,J,Ir,Jr,C)
proj2 = tf.einsum('nijabc,nijab->c',selected_W,(t_m_rho_p[:,:,:,:,:,0]+self.leakiness*t_m_rho_p[:,:,:,:,:,1])) # ( C)
new_w = tf.scatter_nd_update(self.W_,[[self.k_,self.r_,self.i_,self.j_]],[(proj+proj2)/(denominator+self.sparsity_prior)])
return new_w
def update_pi(self):
a44 = tf.reduce_sum(self.p_,axis=[1,2,4])/self.bs
return tf.assign(self.pi,a44/tf.reduce_sum(a44,axis=1,keepdims=True))
def update_sigma(self):
a1 = tf.reduce_sum(tf.square(self.input-self.b-self.deconv()),0)/self.bs
a2 = tf.reduce_sum(self.input_layer.v2,0)/self.bs
# HERE THE ADDITIONAL NORM
patches = tf.reduce_sum(tf.square(tf.map_fn(self.get_bigpatch_k,tf.range(self.K),dtype=tf.float32,back_prop=False)),0) # (N,I,J Ic+Ir-1 Jc+Jr-1 C)
a3 = tf.reduce_sum(self.assemble_large_patch(patches),0)/self.bs
a40 = self.unpool_R(tf.einsum('kijrn,kijn->nijkr',self.p_,tf.square(self.m_)+self.v2_))*tf.expand_dims(self.rho_tensor,-1) # (N I' J' K R)
a4 = tf.reduce_sum(self.assemble_small_patch(tf.einsum('nijkr,krabc->nijabc',a40,tf.square(self.W))),0)/self.bs
value = a1+a2-a3+a4
if(self.sigma_opt=='local'):
return tf.assign(self.SIGMAS2_,value)
elif(self.sigma_opt=='channel'):
return tf.assign(self.SIGMAS2_,tf.reduce_sum(value,[0,1],keepdims=True)*tf.ones([self.Iin,self.Jin,1])/(self.Iin*self.Jin))
elif(self.sigma_opt=='global'):
return tf.assign(self.SIGMAS2_,tf.fill([self.Iin,self.Jin,self.C],tf.reduce_sum(value)/(self.Iin*self.Jin*self.C)))
#########################################################################################################################
#
#
# INPUT LAYER
#
#
#########################################################################################################################
class InputLayer:
def __init__(self,input_shape,alpha=0.5,G=False):
self.alpha = tf.Variable(alpha)
self.mask = tf.Variable(tf.zeros(input_shape))
self.v2 = tf.Variable(tf.zeros(input_shape))
if(G): self.v2 = tf.square(self.v2)
else: self.v2 = self.v2
self.input_shape = input_shape
self.output_shape = input_shape
self.m = tf.Variable(tf.zeros(self.input_shape))
self.m_ = tf.transpose(self.m,[3,1,2,0])
self.v2_ = tf.transpose(self.v2,[3,1,2,0])
self.W_indices=array([0])
def init_thetaq(self):
return tf.assign(self.v2,self.mask)
def likelihood(self,batch=0,pretraining=False):
return float32(0)
def KL(self,pretraining=False):
return float32(0.5)*tf.reduce_sum(tf.log(self.v2+eps)*self.mask)/float32(self.input_shape[0])
def update_v2(self,pretraining=False):
if(isinstance(self.next_layer,ConvPoolLayer) or isinstance(self.next_layer,ConvLayer)): a40 = self.next_layer.SIGMAS2
else: a40 = self.next_layer.reshape_SIGMAS2
return tf.assign(self.v2,self.mask*a40)
def update_rho(self):
return []
def update_m(self,opt=0,pretraining=False):
if(isinstance(self.next_layer,ConvPoolLayer) or isinstance(self.next_layer,ConvLayer)): priorm = self.next_layer.deconv()+self.next_layer.b
else: priorm = self.next_layer.backward(0)+self.next_layer.reshape_b
new_m = tf.assign(self.m,priorm*self.mask+self.m*(1-self.mask))
return new_m
def update_sigma(self):
return []
def update_p(self,pretraining=False): return []
def update_pi(self):
return []
def update_W(self):
return []
def update_S(self): return []
def update_BV(self): return []
def update_Wk(self): return []
def evidence(self): return float32(0)
#########################################################################################################################
#
#
# FINAL LAYERS
#
#
#########################################################################################################################
class CategoricalLastLayer:
def __init__(self,input_layer,R,sparsity_prior=0,sigma='local',alpha=0.5,update_b=True,G=False):
self.update_b = update_b
self.mask = tf.Variable(tf.zeros(input_layer.output_shape[0]))
self.alpha = tf.Variable(alpha)
self.input_layer = input_layer
self.sigma_opt = sigma
self.sparsity_prior = sparsity_prior
input_layer.next_layer = self
self.input_shape = input_layer.output_shape
self.bs = self.input_shape[0]
self.output_shape = (self.bs,1)
self.D_in = prod(self.input_shape[1:])
self.input_shape_ = (self.bs,self.D_in)#potentially different if flattened
self.input = input_layer.m
self.bs = int32(self.input_shape[0])
self.R = R
self.m = float32(1)
self.K = 1
self.k_ = tf.placeholder(tf.int32)
# PARAMETERS
self.sigmas2_= tf.Variable(tf.ones(self.D_in),trainable=False);tf.add_to_collection('PARAMS',self.sigmas2_)
if(0): self.SIGMAS2_ = tf.square(self.sigmas2_)
else: self.SIGMAS2_ = self.sigmas2_
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
II = tf.random_normal#tf.orthogonal_initializer(float32(1))
self.W = tf.Variable(II((R,self.D_in))*0.1);tf.add_to_collection('PARAMS',self.W)
self.pi = tf.Variable(tf.ones(R)/R)#;tf.add_to_collection('PARAMS',self.pi)
self.b_ = tf.Variable(tf.zeros(self.D_in));tf.add_to_collection('PARAMS',self.b_)
self.b = tf.expand_dims(self.b_,0)
# VI PARAMETERS
self.p_ = tf.Variable(mysoftmax(tf.random_normal((self.bs,R)),axis=1));tf.add_to_collection('LATENT',self.p_) # (N R)
if(G): self.p_ = tf.nn.softmax(self.p_)
else: self.p_ = self.p_
self.p = self.p_
# STATISTICS
self.S1 = tf.Variable(tf.zeros((self.R,self.D_in)))
self.S2 = tf.Variable(tf.zeros(self.D_in))
self.S3 = tf.Variable(tf.zeros((self.R,self.R)))
self.S4 = tf.Variable(tf.zeros(self.D_in))
self.S5 = tf.Variable(tf.zeros(self.R))
self.S6 = tf.Variable(tf.zeros(self.D_in))
# HELPER
self.m_indices = ones(1)
self.p_indices = ones(1)
self.W_indices = ones(1)
input_layer.next_layer_SIGMAS2 = self.SIGMAS2
if(len(self.input_shape)>2):
self.is_flat = False
self.input_ = tf.reshape(self.input,(self.bs,self.D_in))
self.reshape_SIGMAS2_ = tf.reshape(self.SIGMAS2_,self.input_shape[1:])
self.reshape_SIGMAS2 = tf.expand_dims(self.reshape_SIGMAS2_,0)
self.reshape_b_ = tf.reshape(self.b_,self.input_shape[1:])
self.reshape_b = tf.expand_dims(self.reshape_b_,0)
else:
self.is_flat = True
self.input_ = self.input
def update_S(self):
S1 = tf.einsum('nd,nr->rd',self.input_,self.p_)/self.bs
if(isinstance(self.input_layer,DenseLayer)):
S2 = tf.reduce_sum(self.input_layer.v2_,1)/self.bs
else:
S2 = tf.reshape(tf.reduce_sum(self.input_layer.v2,0),[self.D_in])/self.bs
S3 = tf.einsum('nr,nv->rv',self.p_,self.p_)
S4 = tf.reduce_sum(self.input_,0)/self.bs
S5 = tf.reduce_sum(self.p_,0)/self.bs
S6 = tf.reduce_sum(tf.square(self.input_),0)/self.bs
return tf.group(tf.assign(self.S1,self.alpha*S1+(1-self.alpha)*self.S1),tf.assign(self.S2,self.alpha*S2+(1-self.alpha)*self.S2),
tf.assign(self.S3,self.alpha*S3+(1-self.alpha)*self.S3),tf.assign(self.S4,self.alpha*S4+(1-self.alpha)*self.S4),
tf.assign(self.S5,self.alpha*S5+(1-self.alpha)*self.S5),tf.assign(self.S6,self.alpha*S6+(1-self.alpha)*self.S6))
def init_thetaq(self):
new_p = tf.assign(self.p_,tf.fill([self.bs,self.R],float32(1.0/self.R)))
return [new_p]
def backward(self,flat=1):
if(flat): return tf.tensordot(self.p_,self.W,[[1],[0]])
else: return tf.reshape(tf.tensordot(self.p_,self.W,[[1],[0]]),self.input_shape)
def backwardk(self,k):
return tf.tensordot(self.p_,self.W[:,k],[[1],[0]]) #(N)
def sample(self,samples,K=None,sigma=1,deterministic=0):
""" K must be a pre imposed region used for generation
if not given it is generated according to pi, its shape
must be (N K R) with a one hot vector on the last dimension
sampels is a dummy variable not used in this layer """
noise = sigma*tf.random_normal(self.input_shape_)*tf.sqrt(self.SIGMAS2)
if(K is None):
K = tf.one_hot(tf.multinomial(tf.log(tf.expand_dims(self.pi,0)),self.bs)[0],self.R)
print tf.multinomial(tf.log(tf.expand_dims(self.pi,0)),self.bs).get_shape(),K.get_shape()
if(self.is_flat): return tf.tensordot(K,self.W,[[1],[0]])+noise+self.b
else: return tf.reshape(tf.tensordot(K,self.W,[[1],[0]])+noise+self.b,self.input_shape)
def evidence(self):
k1 = -tf.reduce_sum(tf.log(self.SIGMAS2_)/2)
k2 = tf.einsum('nr,r->n',self.p_,tf.log(self.pi))
k3 = -float32(self.D_in)*tf.log(2*PI_CONST)*float32(0.5)
reconstruction = -tf.einsum('nd,d->n',tf.square(self.input_-self.b-self.backward(1)),1/self.SIGMAS2_)*float32(0.5)
if(isinstance(self.input_layer,DenseLayer)):
input_v2 = -tf.einsum('dn,d->n',self.input_layer.v2_,1/self.SIGMAS2_)*float32(0.5)
else: input_v2= -tf.reduce_sum(tf.reshape(self.input_layer.v2,[self.bs,self.D_in])/self.SIGMAS2,1)*float32(0.5)
m2v2 = -tf.einsum('nr,rd,d->n',self.p_,tf.square(self.W),1/self.SIGMAS2_)*float32(0.5) #(N D) -> (D)
sum_norm_k = tf.einsum('nd,d->n',tf.square(tf.tensordot(self.p_,self.W,[[1],[0]])),1/self.SIGMAS2_)*float32(0.5) #(D)
return k1+k2+k3+(reconstruction+input_v2+sum_norm_k+m2v2)
def likelihood(self,batch=None,pretraining=False):
if(batch==0):
k1 = -tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5)
k2 = tf.einsum('nr,r->',self.p_,tf.log(self.pi))*2
k3 = -tf.log(2*PI_CONST)*float32(self.D_in*0.5)
reconstruction = -tf.einsum('nd,d->',tf.square(self.input_-self.b-self.backward(1)),1/self.SIGMAS2_)
if(isinstance(self.input_layer,DenseLayer)):
input_v2 = -tf.einsum('kn,k->',self.input_layer.v2_,1/self.SIGMAS2_)
else: input_v2= -tf.reduce_sum(tf.reshape(tf.reduce_sum(self.input_layer.v2,0),[self.D_in])/self.SIGMAS2_)
m2v2 = -tf.einsum('nr,rd,d->',self.p_,tf.square(self.W),1/self.SIGMAS2_) #(N D) -> (D)
sum_norm_k = tf.einsum('nd,d->',tf.square(tf.tensordot(self.p_,self.W,[[1],[0]])),1/self.SIGMAS2_) #(D)
return k1+k3+(k2+reconstruction+input_v2+sum_norm_k+m2v2)*float32(0.5/self.bs)-self.sparsity_prior*tf.reduce_sum(tf.square(self.W))
else:
k1 = tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5)+tf.log(2*PI_CONST)*float32(self.D_in*0.5)
k2 = tf.reduce_sum((self.S6+self.S2+tf.square(self.b_)-2*self.b_*self.S4)/self.SIGMAS2_)*0.5
k3 = tf.reduce_sum((self.S1-tf.einsum('r,d->rd',self.S5,self.b_))*self.W/self.SIGMAS2)
k4 = tf.reduce_sum(self.S5*(tf.log(self.pi)-tf.einsum('rd,d->r',tf.square(self.W),0.5/self.SIGMAS2_)))
return -k1-k2+k3+k4
def KL(self,pretraining=False):
return self.likelihood(0,pretraining)-tf.reduce_sum(self.p*tf.log(self.p+eps))/float32(self.bs)
################### E STEP UPDATES
def update_v2(self,pretraining=False):
return []
def update_rho(self):
return []
def update_m(self,ii,pretraining=False):
if(ii==0): return []
proj = tf.einsum('nd,rd->nr',self.input_-self.b,self.W/self.SIGMAS2) # ( N R)
prior = tf.expand_dims(self.pi,0)
m2v2 = -tf.expand_dims(tf.einsum('rd,d->r',tf.square(self.W),float32(0.5)/self.SIGMAS2_),0) # ( 1 R )
V = mysoftmax(proj+m2v2+tf.log(prior),coeff=0.0)
return tf.assign(self.p_,V*tf.expand_dims(self.mask,-1)+self.p_[0]*(1-tf.expand_dims(self.mask,-1)))
################### M STEP UPDATES
def update_sigma(self):
value = self.S6+self.S2-tf.reduce_sum(self.S1*self.W,0)
value_ = tf.clip_by_value(value,0.000001,1000)
if(self.sigma_opt=='local'): return tf.assign(self.sigmas2_,value_)
elif(self.sigma_opt=='global'): return tf.assign(self.sigmas2_,tf.fill([self.D_in],tf.reduce_sum(value_)/self.D_in))
elif(self.sigma_opt=='none'): return []
def update_pi(self):
return []
return tf.assign(self.pi,self.S5/tf.reduce_sum(self.S5))
def update_Wk(self):
return tf.assign(self.W,(self.S1-tf.einsum('r,d->rd',self.S5,self.b_))/tf.expand_dims(self.S5,-1))
def update_BV(self):
if(self.update_b): return tf.assign(self.b_,self.S4-tf.einsum('rd,r->d',self.W,self.S5))
else: return []
class ContinuousLastLayer:
def __init__(self,input_layer,sigma='local'):
self.sigma_opt = sigma
self.input_layer = input_layer
input_layer.next_layer = self
self.input_shape = input_layer.output_shape
self.bs,self.K = self.input_shape[0],self.input_shape[1]
K=self.K
self.D_in = self.K
self.input_shape_ = (self.bs,self.D_in)#potentially different if flattened
self.input = input_layer.m
# PARAMETERS
self.SIGMAS2_= tf.Variable(tf.ones(self.D_in),trainable=False)
self.SIGMAS2 = tf.expand_dims(self.SIGMAS2_,0)
# VI PARAMETERS
self.b_ = tf.zeros(K)
# placeholder for update and indices
self.k_ = tf.placeholder(tf.int32) # placeholder that will indicate which neuron is being updated
self.m_indices = ones(1)
self.W_indices = ones(1)
input_layer.next_layer_SIGMAS2 = self.SIGMAS2
def init_thetaq(self):
return []
def backward(self,flat=1,resi=None):
return tf.zeros_like(self.input)
def backwardk(self,k,resi = None):
return 0
def sample(self,M=None,sigma=1,deterministic=False):
M = tf.random_normal((self.bs,self.D_in))*tf.sqrt(self.SIGMAS2)
return M
def likelihood(self):
k1 = -tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5) #(1)
k2 = -tf.log(2*PI_CONST)*float32(self.D_in*0.5)
reconstruction = -tf.einsum('nd,d->',tf.square(self.input),1/self.SIGMAS2_) #(1)
input_v2 = -tf.einsum('dn,d->',self.input_layer.v2_,1/self.SIGMAS2_) #(1)
# m2v2 = -tf.einsum('dn,d->',self.v2_,1/self.SIGMAS2_)
return k1+k2+(reconstruction+input_v2)*float32(0.5/self.bs)
def evidence(self):
k1 = -tf.reduce_sum(tf.log(self.SIGMAS2_))*float32(0.5) #(1)
k2 = -tf.log(2*PI_CONST)*float32(self.D_in*0.5)
reconstruction = -tf.einsum('nd,d->n',tf.square(self.input),1/self.SIGMAS2_) #(1)
input_v2 = -tf.einsum('dn,d->n',self.input_layer.v2_,1/self.SIGMAS2_) #(1)
# m2v2 = -tf.einsum('dn,d->',self.v2_,1/self.SIGMAS2_)
return k1+k2+(reconstruction+input_v2)*float32(0.5)
def KL(self):
return self.likelihood()#+tf.reduce_sum(tf.log(self.v2_+eps))*float32(0.5/self.bs)+float32(self.D_in/2.0)*tf.log(2*PI_CONST)
def update_v2(self):
return []#tf.assign(self.v2_,tf.expand_dims(self.SIGMAS2_,1)*tf.ones((1,self.bs)))
def update_rho(self):
return []
def update_p(self):
return []
def update_m(self,ii):
return []#tf.assign(self.m_,tf.transpose(self.input/self.SIGMAS2))
def update_sigma(self):
value = tf.reduce_sum(tf.square(self.input)+self.input_layer.v2,0)/self.bs
if(self.sigma_opt=='local'):
return tf.assign(self.SIGMAS2_,tf.clip_by_value(value,0.000001,10))
elif(self.sigma_opt=='global'):
return tf.assign(self.SIGMAS2_,tf.fill([self.D_in],tf.reduce_sum(value)/self.D_in))
def update_pi(self):
return []
def update_Wk(self):
return []
def update_BV(self):
return []
| 71.606432
| 326
| 0.581289
| 15,113
| 93,518
| 3.43843
| 0.030437
| 0.020783
| 0.026248
| 0.013471
| 0.838757
| 0.775657
| 0.712114
| 0.656249
| 0.607986
| 0.573809
| 0
| 0.036389
| 0.230394
| 93,518
| 1,305
| 327
| 71.661303
| 0.685628
| 0.069185
| 0
| 0.441281
| 0
| 0
| 0.026425
| 0.003179
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.004448
| null | null | 0.001779
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
59c8812e02ea9f3399ebb4999d67f4d4972141cb
| 44
|
py
|
Python
|
chanjo/init/__init__.py
|
biocyberman/chanjo
|
962eedf26dcfc0ad8ea66d4c56b455192934c68e
|
[
"MIT"
] | null | null | null |
chanjo/init/__init__.py
|
biocyberman/chanjo
|
962eedf26dcfc0ad8ea66d4c56b455192934c68e
|
[
"MIT"
] | null | null | null |
chanjo/init/__init__.py
|
biocyberman/chanjo
|
962eedf26dcfc0ad8ea66d4c56b455192934c68e
|
[
"MIT"
] | null | null | null |
"""
Bootstrap a new instance of chanjo.
"""
| 11
| 35
| 0.659091
| 6
| 44
| 4.833333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 44
| 3
| 36
| 14.666667
| 0.805556
| 0.795455
| 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
|
59d3f87362d3dbe2f374f5602ca59f5d59e76b71
| 142
|
py
|
Python
|
setup.py
|
Ragora/TSScraper
|
acfedaa3d85972ef8fd5dedbd84fa9e37a681771
|
[
"MIT"
] | null | null | null |
setup.py
|
Ragora/TSScraper
|
acfedaa3d85972ef8fd5dedbd84fa9e37a681771
|
[
"MIT"
] | null | null | null |
setup.py
|
Ragora/TSScraper
|
acfedaa3d85972ef8fd5dedbd84fa9e37a681771
|
[
"MIT"
] | null | null | null |
from distutils.core import setup
from Cython.Build import cythonize
setup(
name = 'Script Scraper',
ext_modules = cythonize("main.py"),
)
| 20.285714
| 37
| 0.746479
| 19
| 142
| 5.526316
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147887
| 142
| 7
| 38
| 20.285714
| 0.867769
| 0
| 0
| 0
| 0
| 0
| 0.146853
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
59d4454e2148f3f6e9d7773908accb121eee2aaa
| 87
|
py
|
Python
|
libros/apps.py
|
dkwelffer/rocbook
|
87c92f26e8bd2139cc57d11f65c3fb82ebbc5223
|
[
"Apache-2.0"
] | null | null | null |
libros/apps.py
|
dkwelffer/rocbook
|
87c92f26e8bd2139cc57d11f65c3fb82ebbc5223
|
[
"Apache-2.0"
] | null | null | null |
libros/apps.py
|
dkwelffer/rocbook
|
87c92f26e8bd2139cc57d11f65c3fb82ebbc5223
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class LibrosConfig(AppConfig):
name = 'libros'
| 14.5
| 33
| 0.747126
| 10
| 87
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 87
| 5
| 34
| 17.4
| 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
|
59d68663d4958368f70366124ee3d8a4129b14df
| 1,833
|
py
|
Python
|
DailyProgrammer/DP20150706A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | 2
|
2020-12-23T18:59:22.000Z
|
2021-04-14T13:16:09.000Z
|
DailyProgrammer/DP20150706A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | null | null | null |
DailyProgrammer/DP20150706A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | null | null | null |
"""
[2015-07-06] Challenge #222 [Easy] Balancing Words
https://www.reddit.com/r/dailyprogrammer/comments/3c9a9h/20150706_challenge_222_easy_balancing_words/
# Description
Today we're going to balance words on one of the letters in them. We'll use the position and letter itself to calculate
the weight around the balance point. A word can be balanced if the weight on either side of the balance point is equal.
Not all words can be balanced, but those that can are interesting for this challenge.
The formula to calculate the weight of the word is to look at the letter position in the English alphabet (so A=1, B=2,
C=3 ... Z=26) as the letter weight, then multiply that by the distance from the balance point, so the first letter away
is multiplied by 1, the second away by 2, etc.
As an example:
STEAD balances at T: 1 * S(19) = 1 * E(5) + 2 * A(1) + 3 * D(4))
# Input Description
You'll be given a series of English words. Example:
STEAD
# Output Description
Your program or function should emit the words split by their balance point and the weight on either side of the
balance point. Example:
S T EAD - 19
This indicates that the T is the balance point and that the weight on either side is 19.
# Challenge Input
CONSUBSTANTIATION
WRONGHEADED
UNINTELLIGIBILITY
SUPERGLUE
# Challenge Output
*Updated* - the weights and answers I had originally were wrong. My apologies.
CONSUBST A NTIATION - 456
WRO N GHEADED - 120
UNINTELL I GIBILITY - 521
SUPERGLUE DOES NOT BALANCE
# Notes
This was found on a [word games page](http://www.questrel.com/records.html) suggested by /u/cDull, thanks! If you have
your own idea for a challenge, submit it to /r/DailyProgrammer_Ideas, and there's a good chance we'll post it.
"""
def main():
pass
if __name__ == "__main__":
main()
| 39
| 119
| 0.73868
| 311
| 1,833
| 4.308682
| 0.5209
| 0.053731
| 0.05597
| 0.03806
| 0.117164
| 0.056716
| 0.056716
| 0.056716
| 0.056716
| 0
| 0
| 0.036685
| 0.196945
| 1,833
| 46
| 120
| 39.847826
| 0.873641
| 0.96072
| 0
| 0
| 0
| 0
| 0.125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
abc3c057f56534aee6cb755835f15d22091a3fd0
| 100
|
py
|
Python
|
AppEquipos/apps.py
|
angel1194/Documentacion
|
62fd4a8a245b9e040c1c97962af2acaaba44816a
|
[
"MIT"
] | null | null | null |
AppEquipos/apps.py
|
angel1194/Documentacion
|
62fd4a8a245b9e040c1c97962af2acaaba44816a
|
[
"MIT"
] | null | null | null |
AppEquipos/apps.py
|
angel1194/Documentacion
|
62fd4a8a245b9e040c1c97962af2acaaba44816a
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class AppequiposConfig(AppConfig):
name = 'AppEquipos'
| 16.666667
| 35
| 0.73
| 10
| 100
| 7.3
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 100
| 5
| 36
| 20
| 0.9125
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 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
|
abcd4f175f232fb5a5cd18f2cfe6df368e1ccece
| 8,847
|
py
|
Python
|
build/x86/python/m5/internal/CreditLink_d_vector.py
|
billionshang/gem5
|
18cc4294f32315595f865d07d1f33434e92b06b2
|
[
"BSD-3-Clause"
] | null | null | null |
build/x86/python/m5/internal/CreditLink_d_vector.py
|
billionshang/gem5
|
18cc4294f32315595f865d07d1f33434e92b06b2
|
[
"BSD-3-Clause"
] | null | null | null |
build/x86/python/m5/internal/CreditLink_d_vector.py
|
billionshang/gem5
|
18cc4294f32315595f865d07d1f33434e92b06b2
|
[
"BSD-3-Clause"
] | null | null | null |
# This file was automatically generated by SWIG (http://www.swig.org).
# Version 3.0.8
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info
if version_info >= (2, 6, 0):
def swig_import_helper():
from os.path import dirname
import imp
fp = None
try:
fp, pathname, description = imp.find_module('_CreditLink_d_vector', [dirname(__file__)])
except ImportError:
import _CreditLink_d_vector
return _CreditLink_d_vector
if fp is not None:
try:
_mod = imp.load_module('_CreditLink_d_vector', fp, pathname, description)
finally:
fp.close()
return _mod
_CreditLink_d_vector = swig_import_helper()
del swig_import_helper
else:
import _CreditLink_d_vector
del version_info
try:
_swig_property = property
except NameError:
pass # Python < 2.2 doesn't have 'property'.
def _swig_setattr_nondynamic(self, class_type, name, value, static=1):
if (name == "thisown"):
return self.this.own(value)
if (name == "this"):
if type(value).__name__ == 'SwigPyObject':
self.__dict__[name] = value
return
method = class_type.__swig_setmethods__.get(name, None)
if method:
return method(self, value)
if (not static):
object.__setattr__(self, name, value)
else:
raise AttributeError("You cannot add attributes to %s" % self)
def _swig_setattr(self, class_type, name, value):
return _swig_setattr_nondynamic(self, class_type, name, value, 0)
def _swig_getattr_nondynamic(self, class_type, name, static=1):
if (name == "thisown"):
return self.this.own()
method = class_type.__swig_getmethods__.get(name, None)
if method:
return method(self)
if (not static):
return object.__getattr__(self, name)
else:
raise AttributeError(name)
def _swig_getattr(self, class_type, name):
return _swig_getattr_nondynamic(self, class_type, name, 0)
def _swig_repr(self):
try:
strthis = "proxy of " + self.this.__repr__()
except Exception:
strthis = ""
return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
try:
_object = object
_newclass = 1
except AttributeError:
class _object:
pass
_newclass = 0
def _swig_setattr_nondynamic_method(set):
def set_attr(self, name, value):
if (name == "thisown"):
return self.this.own(value)
if hasattr(self, name) or (name == "this"):
set(self, name, value)
else:
raise AttributeError("You cannot add attributes to %s" % self)
return set_attr
class SwigPyIterator(object):
thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag')
def __init__(self, *args, **kwargs):
raise AttributeError("No constructor defined - class is abstract")
__repr__ = _swig_repr
__swig_destroy__ = _CreditLink_d_vector.delete_SwigPyIterator
__del__ = lambda self: None
def value(self):
return _CreditLink_d_vector.SwigPyIterator_value(self)
def incr(self, n=1):
return _CreditLink_d_vector.SwigPyIterator_incr(self, n)
def decr(self, n=1):
return _CreditLink_d_vector.SwigPyIterator_decr(self, n)
def distance(self, x):
return _CreditLink_d_vector.SwigPyIterator_distance(self, x)
def equal(self, x):
return _CreditLink_d_vector.SwigPyIterator_equal(self, x)
def copy(self):
return _CreditLink_d_vector.SwigPyIterator_copy(self)
def next(self):
return _CreditLink_d_vector.SwigPyIterator_next(self)
def __next__(self):
return _CreditLink_d_vector.SwigPyIterator___next__(self)
def previous(self):
return _CreditLink_d_vector.SwigPyIterator_previous(self)
def advance(self, n):
return _CreditLink_d_vector.SwigPyIterator_advance(self, n)
def __eq__(self, x):
return _CreditLink_d_vector.SwigPyIterator___eq__(self, x)
def __ne__(self, x):
return _CreditLink_d_vector.SwigPyIterator___ne__(self, x)
def __iadd__(self, n):
return _CreditLink_d_vector.SwigPyIterator___iadd__(self, n)
def __isub__(self, n):
return _CreditLink_d_vector.SwigPyIterator___isub__(self, n)
def __add__(self, n):
return _CreditLink_d_vector.SwigPyIterator___add__(self, n)
def __sub__(self, *args):
return _CreditLink_d_vector.SwigPyIterator___sub__(self, *args)
def __iter__(self):
return self
SwigPyIterator_swigregister = _CreditLink_d_vector.SwigPyIterator_swigregister
SwigPyIterator_swigregister(SwigPyIterator)
import m5.internal.param_CreditLink_d
import m5.internal.param_NetworkLink_d
import m5.internal.param_ClockedObject
import m5.internal.param_ClockDomain
import m5.internal.param_SimObject
import m5.internal.drain
import m5.internal.serialize
class vector_CreditLink_d(object):
thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag')
__repr__ = _swig_repr
def iterator(self):
return _CreditLink_d_vector.vector_CreditLink_d_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _CreditLink_d_vector.vector_CreditLink_d___nonzero__(self)
def __bool__(self):
return _CreditLink_d_vector.vector_CreditLink_d___bool__(self)
def __len__(self):
return _CreditLink_d_vector.vector_CreditLink_d___len__(self)
def __getslice__(self, i, j):
return _CreditLink_d_vector.vector_CreditLink_d___getslice__(self, i, j)
def __setslice__(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d___setslice__(self, *args)
def __delslice__(self, i, j):
return _CreditLink_d_vector.vector_CreditLink_d___delslice__(self, i, j)
def __delitem__(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d___delitem__(self, *args)
def __getitem__(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d___getitem__(self, *args)
def __setitem__(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d___setitem__(self, *args)
def pop(self):
return _CreditLink_d_vector.vector_CreditLink_d_pop(self)
def append(self, x):
return _CreditLink_d_vector.vector_CreditLink_d_append(self, x)
def empty(self):
return _CreditLink_d_vector.vector_CreditLink_d_empty(self)
def size(self):
return _CreditLink_d_vector.vector_CreditLink_d_size(self)
def swap(self, v):
return _CreditLink_d_vector.vector_CreditLink_d_swap(self, v)
def begin(self):
return _CreditLink_d_vector.vector_CreditLink_d_begin(self)
def end(self):
return _CreditLink_d_vector.vector_CreditLink_d_end(self)
def rbegin(self):
return _CreditLink_d_vector.vector_CreditLink_d_rbegin(self)
def rend(self):
return _CreditLink_d_vector.vector_CreditLink_d_rend(self)
def clear(self):
return _CreditLink_d_vector.vector_CreditLink_d_clear(self)
def get_allocator(self):
return _CreditLink_d_vector.vector_CreditLink_d_get_allocator(self)
def pop_back(self):
return _CreditLink_d_vector.vector_CreditLink_d_pop_back(self)
def erase(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d_erase(self, *args)
def __init__(self, *args):
this = _CreditLink_d_vector.new_vector_CreditLink_d(*args)
try:
self.this.append(this)
except Exception:
self.this = this
def push_back(self, x):
return _CreditLink_d_vector.vector_CreditLink_d_push_back(self, x)
def front(self):
return _CreditLink_d_vector.vector_CreditLink_d_front(self)
def back(self):
return _CreditLink_d_vector.vector_CreditLink_d_back(self)
def assign(self, n, x):
return _CreditLink_d_vector.vector_CreditLink_d_assign(self, n, x)
def resize(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d_resize(self, *args)
def insert(self, *args):
return _CreditLink_d_vector.vector_CreditLink_d_insert(self, *args)
def reserve(self, n):
return _CreditLink_d_vector.vector_CreditLink_d_reserve(self, n)
def capacity(self):
return _CreditLink_d_vector.vector_CreditLink_d_capacity(self)
__swig_destroy__ = _CreditLink_d_vector.delete_vector_CreditLink_d
__del__ = lambda self: None
vector_CreditLink_d_swigregister = _CreditLink_d_vector.vector_CreditLink_d_swigregister
vector_CreditLink_d_swigregister(vector_CreditLink_d)
| 31.37234
| 107
| 0.708715
| 1,137
| 8,847
| 4.988566
| 0.156552
| 0.188117
| 0.173836
| 0.19464
| 0.531911
| 0.510402
| 0.467384
| 0.367419
| 0.208921
| 0.087271
| 0
| 0.003277
| 0.206624
| 8,847
| 281
| 108
| 31.483986
| 0.804816
| 0.025884
| 0
| 0.172414
| 1
| 0
| 0.028346
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.29064
| false
| 0.009852
| 0.078818
| 0.251232
| 0.729064
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
f9fbf1653c3ba822c7c87369703ade1907508ee3
| 243
|
py
|
Python
|
USD/admin.py
|
Scankiran/CurrencyAPI
|
1fc987e267210796813028f773d8ea631d5b8da6
|
[
"MIT"
] | null | null | null |
USD/admin.py
|
Scankiran/CurrencyAPI
|
1fc987e267210796813028f773d8ea631d5b8da6
|
[
"MIT"
] | null | null | null |
USD/admin.py
|
Scankiran/CurrencyAPI
|
1fc987e267210796813028f773d8ea631d5b8da6
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import USDMain,USDDaily,USDHourly,USDMonthly
# Register your models here.
admin.site.register(USDDaily)
admin.site.register(USDMonthly)
admin.site.register(USDHourly)
admin.site.register(USDMain)
| 27
| 57
| 0.831276
| 32
| 243
| 6.3125
| 0.4375
| 0.178218
| 0.336634
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074074
| 243
| 8
| 58
| 30.375
| 0.897778
| 0.106996
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 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
|
e6035eca45d4318bab5d6c8425ed7dbc3cfc2c28
| 15,968
|
py
|
Python
|
image_utils.py
|
beric7/styleGAN2_infrastructure
|
bd94716048b8720c382b85619f9d2f3e725d7173
|
[
"Apache-2.0"
] | null | null | null |
image_utils.py
|
beric7/styleGAN2_infrastructure
|
bd94716048b8720c382b85619f9d2f3e725d7173
|
[
"Apache-2.0"
] | null | null | null |
image_utils.py
|
beric7/styleGAN2_infrastructure
|
bd94716048b8720c382b85619f9d2f3e725d7173
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
@Author Eric Bianchi
"""
import os
import shutil
import cv2
import numpy as np
from PIL import Image
import random
from tqdm import tqdm
def buildImageFileList(BASE, TEST_IMAGES_DIR, sort_ID_string):
imageFilePaths = []
image_names = []
UNUSABLE_FILETYPE_DIR = "DATA/Extraction/Sorted Data/"
for imageFileName in os.listdir(TEST_IMAGES_DIR):
if imageFileName.endswith(".jpg"):
imageFilePaths.append(TEST_IMAGES_DIR + imageFileName)
image_names.append(imageFileName)
if imageFileName.endswith(".JPG"):
imageFilePaths.append(TEST_IMAGES_DIR + imageFileName)
image_names.append(imageFileName)
if imageFileName.endswith(".png"):
imageFilePaths.append(TEST_IMAGES_DIR + imageFileName)
image_names.append(imageFileName)
if imageFileName.endswith(".jpeg"):
imageFilePaths.append(TEST_IMAGES_DIR + imageFileName)
image_names.append(imageFileName)
# TODO: This does remove the file of interest... may not want to do this in the future.
if imageFileName.endswith(".emf"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/EMF/" + imageFileName)
if imageFileName.endswith(".wmf"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/WMF/" + imageFileName)
if imageFileName.endswith(".gif"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/GIF/" + imageFileName)
if imageFileName.endswith(".tif"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/TIF/" + imageFileName)
if imageFileName.endswith(".tiff"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/TIFF/" + imageFileName)
if imageFileName.endswith(".wdp"):
os.rename(BASE + TEST_IMAGES_DIR + imageFileName, BASE + UNUSABLE_FILETYPE_DIR + sort_ID_string + "/WDP/" + imageFileName)
return imageFilePaths, image_names
# Step 1: adjust paths.
BASE = 'D://'
IMAGE_DIR = BASE + 'DATA/Datasets/ML_project/images/'
def prettyLabel(classDirectory):
imageFilePaths = []
image_names = []
for class_folder in os.listdir(classDirectory):
i = 0
CLASS_PATH = classDirectory + class_folder + '/'
COPY_CLASS_PATH = classDirectory + 'copy-' + class_folder
os.mkdir(COPY_CLASS_PATH)
for imageFileName in os.listdir(CLASS_PATH):
shutil.copyfile(CLASS_PATH + imageFileName, COPY_CLASS_PATH + '/' + class_folder + '_' + str(i) + '.jpg')
imageFilePaths.append(CLASS_PATH + class_folder + '_' + str(i))
image_names.append(CLASS_PATH + class_folder + '_' + str(i))
i = i + 1
print('done')
return imageFilePaths , image_names
def verticalFlip(imageDir):
for image in os.listdir(imageDir):
img = cv2.imread(imageDir + '/' + image)
imageFlip = cv2.flip(img, 1)
cv2.imwrite(imageDir + '/' + image + '_vFlip.jpg', imageFlip)
print('done')
def rescale_ex(source_image_folder, destination, dimension, extension):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in os.listdir(source_image_folder):
im1 = Image.open(source_image_folder + '/' + filename)
image = im1.resize((dimension,dimension))
head, tail = filename.split('.')
filename = head + '.' + extension
image.save(destination + '/' + filename, extension)
def rescale(source_image_folder, destination, dimension):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in tqdm(os.listdir(source_image_folder)):
im1 = cv2.imread(source_image_folder + '/' + filename)
image = cv2.resize(im1, (dimension,dimension))
cv2.imwrite(destination + '/' + filename, image)
def rescale_mask(source_image_folder, destination, dimension):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in os.listdir(source_image_folder):
im1 = cv2.imread(source_image_folder + '/' + filename)
image = cv2.resize(im1, (dimension,dimension), interpolation=cv2.INTER_NEAREST)
cv2.imwrite(destination + '/' + filename, image)
def extension_change(source_image_folder, destination, extension):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in os.listdir(source_image_folder):
image = Image.open(source_image_folder + '/' + filename)
head, tail = filename.split('.')
filename = head + '.' + extension
image = image.convert("RGB")
image.save(destination + '/' + filename, extension)
def greyscale(source_image_folder, destination):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in os.listdir(source_image_folder):
im1 = cv2.imread(source_image_folder + '/' + filename)
# makes the assumption that it is a jpg file.
im1 = cv2.cvtColor(im1, cv2.COLOR_RGB2GRAY)
cv2.imwrite(destination+'/'+filename, im1)
# def dialateErode(source_image_folder, destination, ksize, iterations):
# kernel = np.ones((ksize,ksize),np.uint8)
# dialated_mask = cv2.dilate(erosion,kernel,iterations)
# erosion = cv2.erode(dialated_mask,kernel,iterations)
def sort_images_into_folder(source_image_folder, destination, count_per, start=0):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
folderID = start
x = 1
for filename in os.listdir(source_image_folder):
if x % count_per == 0:
x = 1
folderID+= 1
if not os.path.exists(destination+'Folder_'+str(folderID)): # if it doesn't exist already
os.makedirs(destination+'Folder_'+str(folderID))
shutil.move(source_image_folder + '/' + filename, destination+'Folder_'+str(folderID)+'/'+filename)
x+=1
def sharpenImage(source_image_folder, destination):
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
for filename in os.listdir(source_image_folder):
im1 = cv2.imread(source_image_folder + '/' + filename)
# makes the assumption that it is a jpg file.
im1 = cv2.cvtColor(im1, cv2.COLOR_RGB2GRAY)
cv2.imwrite(destination+'/'+filename, im1)
def random_sort_images(source_mask_folder, source_image_folder, destination_mask_test,
destination_image_test, destination_mask_train,
destination_image_train, percentage=0.1):
if not os.path.exists(destination_mask_test): # if it doesn't exist already
os.makedirs(destination_mask_test)
if not os.path.exists(destination_image_test): # if it doesn't exist already
os.makedirs(destination_image_test)
if not os.path.exists(destination_mask_train): # if it doesn't exist already
os.makedirs(destination_mask_train)
if not os.path.exists(destination_image_train): # if it doesn't exist already
os.makedirs(destination_image_train)
# list all files in dir
files = [f for f in os.listdir(source_image_folder) if os.path.isfile(source_image_folder + f)]
random.shuffle(files)
# small_list = files[:int(len(files)*percentage)]
count = 0
for filename in files:
# send to test folder or train folder
if count < int(len(files)*percentage):
print(20 * '#')
print('Testing')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_test+ '/' + filename)
print(filename)
filename_mask, ext = filename.split('.')
shutil.copy(source_mask_folder + '/' + filename_mask+'.png',
destination_mask_test+ '/' + filename_mask+'.png')
else:
print(20 * '#')
print('Training')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_train+ '/' + filename)
print(filename)
filename_mask, ext = filename.split('.')
shutil.copy(source_mask_folder + '/' + filename_mask+'.png',
destination_mask_train+ '/' + filename_mask+'.png')
count = count + 1
def random_sort_images_(source_mask_folder, source_cured_mask_folder, source_image_folder, destination_mask_test,
destination_cured_mask_test, destination_image_test, destination_mask_train,
destination_cured_mask_train, destination_image_train, percentage=0.1):
if not os.path.exists(destination_mask_test): # if it doesn't exist already
os.makedirs(destination_mask_test)
if not os.path.exists(destination_cured_mask_test): # if it doesn't exist already
os.makedirs(destination_cured_mask_test)
if not os.path.exists(destination_image_test): # if it doesn't exist already
os.makedirs(destination_image_test)
if not os.path.exists(destination_mask_train): # if it doesn't exist already
os.makedirs(destination_mask_train)
if not os.path.exists(destination_cured_mask_train): # if it doesn't exist already
os.makedirs(destination_cured_mask_train)
if not os.path.exists(destination_image_train): # if it doesn't exist already
os.makedirs(destination_image_train)
# list all files in dir
files = [f for f in os.listdir(source_image_folder) if os.path.isfile(source_image_folder + f)]
random.shuffle(files)
# small_list = files[:int(len(files)*percentage)]
count = 0
for filename in files:
# send to test folder or train folder
if count < int(len(files)*percentage):
print(20 * '#')
print('Testing')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_test+ '/' + filename)
print(filename)
shutil.copy(source_mask_folder + '/' + filename,
destination_mask_test+ '/' + filename)
shutil.copy(source_cured_mask_folder + '/' + filename,
destination_cured_mask_test+ '/' + filename)
else:
print(20 * '#')
print('Training')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_train+ '/' + filename)
print(filename)
shutil.copy(source_mask_folder + '/' + filename,
destination_mask_train+ '/' + filename)
shutil.copy(source_cured_mask_folder + '/' + filename,
destination_cured_mask_train+ '/' + filename)
count = count + 1
def random_sort_images_segmentation(source_mask_folder, source_image_folder, destination_mask_test,
destination_image_test, destination_mask_train,
destination_image_train, percentage=0.1):
if not os.path.exists(destination_mask_test): # if it doesn't exist already
os.makedirs(destination_mask_test)
if not os.path.exists(destination_image_test): # if it doesn't exist already
os.makedirs(destination_image_test)
if not os.path.exists(destination_mask_train): # if it doesn't exist already
os.makedirs(destination_mask_train)
if not os.path.exists(destination_image_train): # if it doesn't exist already
os.makedirs(destination_image_train)
# list all files in dir
files = [f for f in os.listdir(source_image_folder) if os.path.isfile(source_image_folder + f)]
random.shuffle(files)
# small_list = files[:int(len(files)*percentage)]
count = 0
for filename in files:
# send to test folder or train folder
if count < int(len(files)*percentage):
print(20 * '#')
print('Testing')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_test+ '/' + filename)
print(filename)
shutil.copy(source_mask_folder + '/' + filename,
destination_mask_test+ '/' + filename)
else:
print(20 * '#')
print('Training')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_train+ '/' + filename)
print(filename)
shutil.copy(source_mask_folder + '/' + filename,
destination_mask_train+ '/' + filename)
count = count + 1
def random_sort_images(source_image_folder,
destination_image_test,
destination_image_train, percentage=0.1):
if not os.path.exists(destination_image_test): # if it doesn't exist already
os.makedirs(destination_image_test)
if not os.path.exists(destination_image_train): # if it doesn't exist already
os.makedirs(destination_image_train)
# list all files in dir
files = [f for f in os.listdir(source_image_folder) if os.path.isfile(source_image_folder + f)]
random.shuffle(files)
# small_list = files[:int(len(files)*percentage)]
count = 0
for filename in files:
# send to test folder or train folder
if count < int(len(files)*percentage):
print(20 * '#')
print('Testing')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_test+ '/' + filename)
else:
print(20 * '#')
print('Training')
print(20 * '#')
shutil.copy(source_image_folder + '/' + filename,
destination_image_train+ '/' + filename)
count = count + 1
def mask_to_binary_image(source_mask_folder, destination):
# Ensure that destination folder exists or is created
if not os.path.exists(destination): # if it doesn't exist already
os.makedirs(destination)
# run through the source folder for each mask file
for filename in os.listdir(source_mask_folder):
# read the file as a cv2 image
mask = cv2.imread(source_mask_folder + '/' + filename)
# COLOR to Greyscale
grey_scale = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)
# Greyscale to Binary
binary = cv2.threshold(grey_scale, 0, 255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
# save the image in the destination folder
cv2.imwrite(destination + '/' + filename, binary)
| 38.757282
| 136
| 0.608404
| 1,797
| 15,968
| 5.194213
| 0.104619
| 0.049496
| 0.076495
| 0.029462
| 0.771481
| 0.753696
| 0.723377
| 0.713628
| 0.690379
| 0.673345
| 0
| 0.009829
| 0.292773
| 15,968
| 412
| 137
| 38.757282
| 0.816701
| 0.116107
| 0
| 0.673004
| 0
| 0
| 0.02426
| 0.003842
| 0
| 0
| 0
| 0.002427
| 0
| 1
| 0.057034
| false
| 0
| 0.026616
| 0
| 0.091255
| 0.121673
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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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
|
e60967bb666ab67fcd0d21aa90884f7acb63b325
| 83
|
py
|
Python
|
apps/domain/src/main/routes/model_centric/blueprint.py
|
aisportsbets/pygrid
|
eeee1e7ef6ba50a03f6f486992a45f7171976e5a
|
[
"Apache-2.0"
] | null | null | null |
apps/domain/src/main/routes/model_centric/blueprint.py
|
aisportsbets/pygrid
|
eeee1e7ef6ba50a03f6f486992a45f7171976e5a
|
[
"Apache-2.0"
] | null | null | null |
apps/domain/src/main/routes/model_centric/blueprint.py
|
aisportsbets/pygrid
|
eeee1e7ef6ba50a03f6f486992a45f7171976e5a
|
[
"Apache-2.0"
] | null | null | null |
from flask import Blueprint
mcfl_blueprint = Blueprint("model-centric", __name__)
| 20.75
| 53
| 0.807229
| 10
| 83
| 6.2
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108434
| 83
| 3
| 54
| 27.666667
| 0.837838
| 0
| 0
| 0
| 0
| 0
| 0.156627
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 1
| 1
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| 0
| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
e60e938291afcbd6d896ff559c1e65f5bcf9559c
| 130
|
py
|
Python
|
django_for_professionals/project_1_hello_world/pages/urls.py
|
rednafi/django-unchained
|
0f71c8d056699496d4af3ab049f9b2f9d057486b
|
[
"MIT"
] | 1
|
2020-07-25T18:06:56.000Z
|
2020-07-25T18:06:56.000Z
|
django_for_professionals/project_1_hello_world/pages/urls.py
|
rednafi/django-unchained
|
0f71c8d056699496d4af3ab049f9b2f9d057486b
|
[
"MIT"
] | null | null | null |
django_for_professionals/project_1_hello_world/pages/urls.py
|
rednafi/django-unchained
|
0f71c8d056699496d4af3ab049f9b2f9d057486b
|
[
"MIT"
] | null | null | null |
from django.urls import path
from pages.views import home_page_view
urlpatterns = [
path("", home_page_view, name="home"),
]
| 18.571429
| 42
| 0.730769
| 19
| 130
| 4.789474
| 0.631579
| 0.175824
| 0.263736
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 130
| 6
| 43
| 21.666667
| 0.827273
| 0
| 0
| 0
| 0
| 0
| 0.030769
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
e665cdaec06fcda624b46ca840e5a55649545bad
| 296
|
py
|
Python
|
tests/pre_test.py
|
danielpalstra/mealie
|
6c549ff99329e494bc6aad2109973e7eec6c445e
|
[
"MIT"
] | 1,927
|
2021-01-02T20:01:15.000Z
|
2022-03-31T22:49:18.000Z
|
tests/pre_test.py
|
danielpalstra/mealie
|
6c549ff99329e494bc6aad2109973e7eec6c445e
|
[
"MIT"
] | 545
|
2021-01-02T20:32:28.000Z
|
2022-03-31T23:37:08.000Z
|
tests/pre_test.py
|
danielpalstra/mealie
|
6c549ff99329e494bc6aad2109973e7eec6c445e
|
[
"MIT"
] | 254
|
2021-01-03T00:20:07.000Z
|
2022-03-23T22:37:21.000Z
|
from mealie.core.config import determine_sqlite_path, settings
DB_URL = determine_sqlite_path(path=True, suffix="test")
DB_URL.unlink(missing_ok=True)
if settings.DB_ENGINE != "postgres":
# Monkeypatch Database Testing
settings.DB_URL = determine_sqlite_path(path=False, suffix="test")
| 32.888889
| 70
| 0.787162
| 42
| 296
| 5.285714
| 0.571429
| 0.202703
| 0.256757
| 0.198198
| 0.324324
| 0.324324
| 0.324324
| 0
| 0
| 0
| 0
| 0
| 0.108108
| 296
| 8
| 71
| 37
| 0.840909
| 0.094595
| 0
| 0
| 0
| 0
| 0.06015
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
050701b01cdb17c9695a9cd75f6262ac4fc52e49
| 90
|
py
|
Python
|
event_config/__init__.py
|
jlowe77/Eris-Cogs
|
2ade8f82db3477527af3cff3b48ebb281e1a6987
|
[
"Apache-2.0"
] | 6
|
2020-05-13T20:43:53.000Z
|
2021-06-23T16:10:13.000Z
|
event_config/__init__.py
|
jlowe77/Eris-Cogs
|
2ade8f82db3477527af3cff3b48ebb281e1a6987
|
[
"Apache-2.0"
] | 12
|
2019-04-02T13:29:10.000Z
|
2020-03-27T18:07:16.000Z
|
event_config/__init__.py
|
jlowe77/Eris-Cogs
|
2ade8f82db3477527af3cff3b48ebb281e1a6987
|
[
"Apache-2.0"
] | 9
|
2020-06-07T21:46:54.000Z
|
2022-03-01T22:49:02.000Z
|
from .event_config import EventConfig
def setup(bot):
bot.add_cog(EventConfig(bot))
| 15
| 37
| 0.755556
| 13
| 90
| 5.076923
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144444
| 90
| 5
| 38
| 18
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
0532de252750dad7008965b644af8e4a5766e61a
| 498
|
py
|
Python
|
myblog/serializers.py
|
vovagod/blog
|
0c2c2bb5870e6cd84206729951bdca8640a4e189
|
[
"BSD-2-Clause"
] | null | null | null |
myblog/serializers.py
|
vovagod/blog
|
0c2c2bb5870e6cd84206729951bdca8640a4e189
|
[
"BSD-2-Clause"
] | 4
|
2020-01-06T15:34:20.000Z
|
2021-06-10T22:28:00.000Z
|
myblog/serializers.py
|
vgodovalov/blog-api
|
7b3147335d8c73c7e91cec6f5b2588cfbae1d272
|
[
"BSD-2-Clause"
] | null | null | null |
from rest_framework import serializers
from django.contrib.auth.models import User
from myblog.models import Post
class PostSerializer(serializers.ModelSerializer):
class Meta:
model = Post
fields = ('id', 'blogger', 'title', 'text', 'posts',
'subscriptions', 'readposts', 'time_created')
class UserSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = ('username', 'password', 'email', 'first_name', 'last_name')
| 33.2
| 77
| 0.668675
| 51
| 498
| 6.45098
| 0.666667
| 0.072948
| 0.18845
| 0.212766
| 0.243161
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.212851
| 498
| 14
| 78
| 35.571429
| 0.839286
| 0
| 0
| 0.166667
| 0
| 0
| 0.194779
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.083333
| 0.25
| 0
| 0.583333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
053d77de9b8223566ad1a1229e5b11e8686db1da
| 76
|
py
|
Python
|
je_editor/ui/ui_utils/keyword/keyword_list.py
|
JE-Chen/je_editor
|
2f18dedb6f0eb27c38668dc53f520739c8d5c6c6
|
[
"MIT"
] | 1
|
2021-12-10T14:57:15.000Z
|
2021-12-10T14:57:15.000Z
|
je_editor/ui/ui_utils/keyword/keyword_list.py
|
JE-Chen/je_editor
|
2f18dedb6f0eb27c38668dc53f520739c8d5c6c6
|
[
"MIT"
] | null | null | null |
je_editor/ui/ui_utils/keyword/keyword_list.py
|
JE-Chen/je_editor
|
2f18dedb6f0eb27c38668dc53f520739c8d5c6c6
|
[
"MIT"
] | null | null | null |
import keyword
# get the keyword list to tag
keyword_list = keyword.kwlist
| 15.2
| 29
| 0.789474
| 12
| 76
| 4.916667
| 0.666667
| 0.372881
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171053
| 76
| 4
| 30
| 19
| 0.936508
| 0.355263
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
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| null | 1
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| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
05420db542989fe8480cdfaef56e30013589066a
| 663
|
py
|
Python
|
fdk_client/platform/models/StoreConfig.py
|
kavish-d/fdk-client-python
|
a1023eb530473322cb52e095fc4ceb226c1e6037
|
[
"MIT"
] | null | null | null |
fdk_client/platform/models/StoreConfig.py
|
kavish-d/fdk-client-python
|
a1023eb530473322cb52e095fc4ceb226c1e6037
|
[
"MIT"
] | null | null | null |
fdk_client/platform/models/StoreConfig.py
|
kavish-d/fdk-client-python
|
a1023eb530473322cb52e095fc4ceb226c1e6037
|
[
"MIT"
] | null | null | null |
"""Platform Models."""
from marshmallow import fields, Schema
from marshmallow.validate import OneOf
from ..enums import *
from ..models.BaseSchema import BaseSchema
from .ProcessConfig import ProcessConfig
class StoreConfig(BaseSchema):
# Inventory swagger.json
job_code = fields.Str(required=False)
storeid = fields.Str(required=False)
store_alias = fields.Str(required=False)
store_file_regex = fields.Str(required=False)
store_file_name = fields.Str(required=False)
process_config = fields.Nested(ProcessConfig, required=False)
properties = fields.Dict(required=False)
| 15.785714
| 65
| 0.702866
| 73
| 663
| 6.287671
| 0.452055
| 0.198257
| 0.185185
| 0.239651
| 0.1939
| 0.135076
| 0
| 0
| 0
| 0
| 0
| 0
| 0.211161
| 663
| 41
| 66
| 16.170732
| 0.877629
| 0.060332
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.384615
| 0
| 1
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| 0
| 0
| null | 0
| 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
55266989b0b6b166afe82aec5ad1487506bbc79f
| 1,916
|
py
|
Python
|
NucleationModel/pB_approximator.py
|
MFrassek/CommittorEAE
|
88a467e4500bc9ab69834209f4eaec9f2d0d7a61
|
[
"MIT"
] | null | null | null |
NucleationModel/pB_approximator.py
|
MFrassek/CommittorEAE
|
88a467e4500bc9ab69834209f4eaec9f2d0d7a61
|
[
"MIT"
] | null | null | null |
NucleationModel/pB_approximator.py
|
MFrassek/CommittorEAE
|
88a467e4500bc9ab69834209f4eaec9f2d0d7a61
|
[
"MIT"
] | null | null | null |
import numpy as np
class pB_Approximator():
@staticmethod
def approximate_pBs(grid_snapshots, labels, weights):
weighted_label_dict, weight_dict = \
get_weighted_label_dict_and_weight_dict(
grid_snapshots, labels, weights)
pB_dict = get_pB_dict(weighted_label_dict, weight_dict)
pBs = get_pBs_list(pB_dict, grid_snapshots)
pB_weights = get_pB_weight_list(weight_dict, grid_snapshots)
return pB_dict, pBs, pB_weights
def get_weighted_label_dict_and_weight_dict(grid_snapshots, labels, weights):
weighted_label_dict = {}
weight_dict = {}
for snapshot, label, weight in zip(grid_snapshots, labels, weights):
gridpoint_tuple = tuple(snapshot)
if gridpoint_tuple in weighted_label_dict:
update_dictionary_entries(
weighted_label_dict, weight_dict,
gridpoint_tuple, weight, label)
else:
add_dictionary_entries(
weighted_label_dict, weight_dict,
gridpoint_tuple, weight, label)
return weighted_label_dict, weight_dict
def update_dictionary_entries(
weighted_label_dict, weight_dict, gridpoint_tuple, weight, label):
weighted_label_dict[gridpoint_tuple] += weight * label
weight_dict[gridpoint_tuple] += weight
def add_dictionary_entries(
weighted_label_dict, weight_dict, gridpoint_tuple, weight, label):
weighted_label_dict[gridpoint_tuple] = weight * label
weight_dict[gridpoint_tuple] = weight
def get_pB_dict(weighted_label_dict, weight_dict):
return {key: weighted_label_dict[key] / weight_dict[key]
for key in weight_dict}
def get_pBs_list(pB_dict, grid_snapshots):
return np.array([pB_dict[tuple(key)] for key in grid_snapshots])
def get_pB_weight_list(weight_dict, grid_snapshots):
return [weight_dict[tuple(key)] for key in grid_snapshots]
| 34.836364
| 77
| 0.717641
| 246
| 1,916
| 5.162602
| 0.150407
| 0.141732
| 0.200787
| 0.162992
| 0.750394
| 0.729134
| 0.729134
| 0.683465
| 0.574803
| 0.44252
| 0
| 0
| 0.213987
| 1,916
| 54
| 78
| 35.481481
| 0.843293
| 0
| 0
| 0.15
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.175
| false
| 0
| 0.025
| 0.075
| 0.35
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5526bfc9225ab81170a048dca36954c29d879ab3
| 293
|
py
|
Python
|
IOMC/EventVertexGenerators/python/VtxSmearedEarly2p2TeVCollision_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 852
|
2015-01-11T21:03:51.000Z
|
2022-03-25T21:14:00.000Z
|
IOMC/EventVertexGenerators/python/VtxSmearedEarly2p2TeVCollision_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 30,371
|
2015-01-02T00:14:40.000Z
|
2022-03-31T23:26:05.000Z
|
IOMC/EventVertexGenerators/python/VtxSmearedEarly2p2TeVCollision_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 3,240
|
2015-01-02T05:53:18.000Z
|
2022-03-31T17:24:21.000Z
|
import FWCore.ParameterSet.Config as cms
from IOMC.EventVertexGenerators.VtxSmearedParameters_cfi import Early2p2TeVCollisionVtxSmearingParameters,VtxSmearedCommon
VtxSmeared = cms.EDProducer("BetafuncEvtVtxGenerator",
Early2p2TeVCollisionVtxSmearingParameters,
VtxSmearedCommon
)
| 26.636364
| 122
| 0.866894
| 20
| 293
| 12.65
| 0.8
| 0.450593
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014981
| 0.088737
| 293
| 10
| 123
| 29.3
| 0.932584
| 0
| 0
| 0
| 0
| 0
| 0.07931
| 0.07931
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 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
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
554339afe055b1dd0bf64b24dcc5b1cff0a0762e
| 142
|
py
|
Python
|
aries_cloudagent/protocols/present_proof/v2_0/models/__init__.py
|
kuraakhilesh8230/aries-cloudagent-python
|
ee384d1330f6a50ff45a507392ce54f92900f23a
|
[
"Apache-2.0"
] | 247
|
2019-07-02T21:10:21.000Z
|
2022-03-30T13:55:33.000Z
|
aries_cloudagent/protocols/present_proof/v2_0/models/__init__.py
|
kuraakhilesh8230/aries-cloudagent-python
|
ee384d1330f6a50ff45a507392ce54f92900f23a
|
[
"Apache-2.0"
] | 1,462
|
2019-07-02T20:57:30.000Z
|
2022-03-31T23:13:35.000Z
|
aries_cloudagent/protocols/present_proof/v2_0/models/__init__.py
|
kuraakhilesh8230/aries-cloudagent-python
|
ee384d1330f6a50ff45a507392ce54f92900f23a
|
[
"Apache-2.0"
] | 377
|
2019-06-20T21:01:31.000Z
|
2022-03-30T08:27:53.000Z
|
"""Package-wide data and code."""
from os import environ
UNENCRYPTED_TAGS = environ.get("EXCH_UNENCRYPTED_TAGS", "False").upper() == "TRUE"
| 23.666667
| 82
| 0.71831
| 19
| 142
| 5.210526
| 0.842105
| 0.30303
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112676
| 142
| 5
| 83
| 28.4
| 0.785714
| 0.190141
| 0
| 0
| 0
| 0
| 0.275229
| 0.192661
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
5558a7fcee6726bb43c43449a686a24fd1545ee7
| 1,275
|
py
|
Python
|
projects/migrations/0010_auto_20181030_1006.py
|
mferbarrera/AIOO
|
1ace829430194eca547cb6ff2b3588629fb488be
|
[
"MIT"
] | null | null | null |
projects/migrations/0010_auto_20181030_1006.py
|
mferbarrera/AIOO
|
1ace829430194eca547cb6ff2b3588629fb488be
|
[
"MIT"
] | null | null | null |
projects/migrations/0010_auto_20181030_1006.py
|
mferbarrera/AIOO
|
1ace829430194eca547cb6ff2b3588629fb488be
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.1.2 on 2018-10-30 16:06
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('projects', '0009_auto_20181029_1129'),
]
operations = [
migrations.AlterField(
model_name='location',
name='address',
field=models.CharField(blank=True, max_length=200, null=True),
),
migrations.AlterField(
model_name='location',
name='lat',
field=models.FloatField(blank=True, null=True),
),
migrations.AlterField(
model_name='location',
name='lon',
field=models.FloatField(blank=True, null=True),
),
migrations.AlterField(
model_name='location',
name='nemonic',
field=models.CharField(blank=True, max_length=10, null=True),
),
migrations.AlterField(
model_name='location',
name='sapcenter',
field=models.CharField(blank=True, max_length=10, null=True),
),
migrations.AlterField(
model_name='location',
name='sapsite',
field=models.CharField(blank=True, max_length=10, null=True),
),
]
| 28.977273
| 74
| 0.560784
| 125
| 1,275
| 5.616
| 0.352
| 0.17094
| 0.213675
| 0.247863
| 0.729345
| 0.729345
| 0.67094
| 0.616809
| 0.547009
| 0.547009
| 0
| 0.04603
| 0.318431
| 1,275
| 43
| 75
| 29.651163
| 0.761795
| 0.035294
| 0
| 0.621622
| 1
| 0
| 0.093648
| 0.01873
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.027027
| 0
| 0.108108
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 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
|
55613e4c5c7a1f2e1fbaf5fc3ee4c0fb9e94ba9a
| 528
|
py
|
Python
|
products/migrations/0002_auto_20181204_0025.py
|
mozenkov/GamesWatch-Django
|
dae0f78b68d46c97e5571559dce7dd82893c8180
|
[
"Apache-2.0"
] | null | null | null |
products/migrations/0002_auto_20181204_0025.py
|
mozenkov/GamesWatch-Django
|
dae0f78b68d46c97e5571559dce7dd82893c8180
|
[
"Apache-2.0"
] | null | null | null |
products/migrations/0002_auto_20181204_0025.py
|
mozenkov/GamesWatch-Django
|
dae0f78b68d46c97e5571559dce7dd82893c8180
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 2.0.2 on 2018-12-04 00:25
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('products', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='product',
name='body',
),
migrations.RemoveField(
model_name='product',
name='icon',
),
migrations.RemoveField(
model_name='product',
name='votes_total',
),
]
| 20.307692
| 47
| 0.534091
| 48
| 528
| 5.770833
| 0.625
| 0.227437
| 0.281588
| 0.32491
| 0.444043
| 0.444043
| 0
| 0
| 0
| 0
| 0
| 0.055394
| 0.350379
| 528
| 25
| 48
| 21.12
| 0.752187
| 0.085227
| 0
| 0.473684
| 1
| 0
| 0.12474
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.052632
| 0
| 0.210526
| 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
|
5575758f83aed64473afb5c0242081b5426dfc8a
| 120
|
py
|
Python
|
protonets/data/tuf.py
|
pockerman/prototypical-networks
|
d19cac9637c9497181e613bb327fb0e93ee39929
|
[
"MIT"
] | null | null | null |
protonets/data/tuf.py
|
pockerman/prototypical-networks
|
d19cac9637c9497181e613bb327fb0e93ee39929
|
[
"MIT"
] | null | null | null |
protonets/data/tuf.py
|
pockerman/prototypical-networks
|
d19cac9637c9497181e613bb327fb0e93ee39929
|
[
"MIT"
] | null | null | null |
def load(opt, splits):
"""
Load the TUF train dataset
:return:
"""
return {"train": [], "val": []}
| 15
| 35
| 0.483333
| 13
| 120
| 4.461538
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.308333
| 120
| 8
| 35
| 15
| 0.698795
| 0.291667
| 0
| 0
| 0
| 0
| 0.125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
55915f6dae6e2a35e66aa37c914fe303839e2b68
| 202
|
py
|
Python
|
src/config.py
|
csadorf/exaparser
|
86d5783ede78f3395bc8abf35d035dd6892f35da
|
[
"Apache-2.0"
] | null | null | null |
src/config.py
|
csadorf/exaparser
|
86d5783ede78f3395bc8abf35d035dd6892f35da
|
[
"Apache-2.0"
] | null | null | null |
src/config.py
|
csadorf/exaparser
|
86d5783ede78f3395bc8abf35d035dd6892f35da
|
[
"Apache-2.0"
] | null | null | null |
import os
import configparser
ExaParserConfig = configparser.ConfigParser(allow_no_value=True)
ExaParserConfig.read(os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "config"))
| 33.666667
| 105
| 0.816832
| 27
| 202
| 5.888889
| 0.555556
| 0.150943
| 0.163522
| 0.188679
| 0.201258
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049505
| 202
| 5
| 106
| 40.4
| 0.828125
| 0
| 0
| 0
| 0
| 0
| 0.029703
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
55ad8390a7cc7d664cb5bb82b0a3ba9e3c5e0fd3
| 112
|
py
|
Python
|
pi lhd5.py
|
hapisnake/To-find-Nth-pi-valve
|
4804879b36883df61632e3a368eea32cbbcf5e4d
|
[
"MIT"
] | null | null | null |
pi lhd5.py
|
hapisnake/To-find-Nth-pi-valve
|
4804879b36883df61632e3a368eea32cbbcf5e4d
|
[
"MIT"
] | null | null | null |
pi lhd5.py
|
hapisnake/To-find-Nth-pi-valve
|
4804879b36883df61632e3a368eea32cbbcf5e4d
|
[
"MIT"
] | null | null | null |
import math
def roundpi(n):
print("the value of pi till",n,"decimal place")
return round(math.pi,n)
| 22.4
| 52
| 0.651786
| 19
| 112
| 3.842105
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 112
| 4
| 53
| 28
| 0.829545
| 0
| 0
| 0
| 0
| 0
| 0.305556
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0.25
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
e990e800f2eb2a437119e063bdb2091edd38155b
| 259
|
py
|
Python
|
examples/effects/crop.py
|
SimLeek/displayarray
|
64fe1e2094448d86d743536eedae0039ca339063
|
[
"MIT"
] | 8
|
2019-11-01T19:14:36.000Z
|
2021-08-18T17:55:43.000Z
|
examples/effects/crop.py
|
SimLeek/displayarray
|
64fe1e2094448d86d743536eedae0039ca339063
|
[
"MIT"
] | 12
|
2019-10-01T06:06:48.000Z
|
2020-04-29T23:05:58.000Z
|
examples/effects/crop.py
|
SimLeek/displayarray
|
64fe1e2094448d86d743536eedae0039ca339063
|
[
"MIT"
] | 3
|
2018-04-03T01:29:21.000Z
|
2019-06-27T02:52:34.000Z
|
from displayarray.effects import crop
from displayarray import display
from examples.videos import test_video
# Move the mouse to move where the crop is from on the original image
display(test_video).add_callback(crop.Crop().enable_mouse_control()).block()
| 32.375
| 76
| 0.818533
| 40
| 259
| 5.175
| 0.6
| 0.154589
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.11583
| 259
| 7
| 77
| 37
| 0.90393
| 0.258687
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
e995b1e6c585f3adeb7127893e80d44f3c1c4d3b
| 167
|
py
|
Python
|
positivenegative.py
|
RahulSinghazm/Python_Programs
|
98a7b78a1c274d006a9fa98fe0e8e8656a6d5892
|
[
"bzip2-1.0.6"
] | 1
|
2018-10-21T08:11:52.000Z
|
2018-10-21T08:11:52.000Z
|
positivenegative.py
|
RahulSinghazm/Python_Programs
|
98a7b78a1c274d006a9fa98fe0e8e8656a6d5892
|
[
"bzip2-1.0.6"
] | null | null | null |
positivenegative.py
|
RahulSinghazm/Python_Programs
|
98a7b78a1c274d006a9fa98fe0e8e8656a6d5892
|
[
"bzip2-1.0.6"
] | null | null | null |
num = float(input("Enter a Number: "))
if num > 0:
print("This is a Positive Number")
elif num == 0:
print("Zero")
else:
print("This is a Negative Number")
| 18.555556
| 38
| 0.622754
| 27
| 167
| 3.851852
| 0.592593
| 0.076923
| 0.173077
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0.221557
| 167
| 8
| 39
| 20.875
| 0.784615
| 0
| 0
| 0
| 0
| 0
| 0.419162
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.428571
| 1
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
e99ab37087bb2d7907349b985cad8260dc6607a5
| 99
|
py
|
Python
|
src/borg/algorithms/__init__.py
|
Whissi/borg
|
ebaf0c32d331d55f9b8ec4f58c21141c09d62c46
|
[
"BSD-3-Clause"
] | null | null | null |
src/borg/algorithms/__init__.py
|
Whissi/borg
|
ebaf0c32d331d55f9b8ec4f58c21141c09d62c46
|
[
"BSD-3-Clause"
] | null | null | null |
src/borg/algorithms/__init__.py
|
Whissi/borg
|
ebaf0c32d331d55f9b8ec4f58c21141c09d62c46
|
[
"BSD-3-Clause"
] | null | null | null |
"""
borg.algorithms
===============
This package is intended for hash and checksum functions.
"""
| 14.142857
| 57
| 0.626263
| 11
| 99
| 5.636364
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141414
| 99
| 6
| 58
| 16.5
| 0.729412
| 0.909091
| 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
|
e9d0111412ce4ce4fa463822bf99061d24e3b8dd
| 61
|
py
|
Python
|
login.py
|
lizheng012/test27
|
5c4eb6424f8c18d690f19636dc1942ba68180eca
|
[
"MIT"
] | null | null | null |
login.py
|
lizheng012/test27
|
5c4eb6424f8c18d690f19636dc1942ba68180eca
|
[
"MIT"
] | null | null | null |
login.py
|
lizheng012/test27
|
5c4eb6424f8c18d690f19636dc1942ba68180eca
|
[
"MIT"
] | null | null | null |
num1 = 111
num2 = 222
num3 = 333333
num3 = 333
num4 = 4444
| 7.625
| 13
| 0.639344
| 10
| 61
| 3.9
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.545455
| 0.278689
| 61
| 7
| 14
| 8.714286
| 0.340909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 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
|
75af7ed79a6647551e1cd9c2d49e0671cda53ca0
| 320
|
py
|
Python
|
Losses/RootMeanSquaredError.py
|
recep-yildirim/Machine-Learning-Algorithms
|
dc4f4e6939631468246efc7537b1569007fee792
|
[
"MIT"
] | 3
|
2021-05-12T13:13:52.000Z
|
2022-01-19T19:54:16.000Z
|
Losses/RootMeanSquaredError.py
|
recep-yildirim/Machine-Learning-Algorithms
|
dc4f4e6939631468246efc7537b1569007fee792
|
[
"MIT"
] | null | null | null |
Losses/RootMeanSquaredError.py
|
recep-yildirim/Machine-Learning-Algorithms
|
dc4f4e6939631468246efc7537b1569007fee792
|
[
"MIT"
] | null | null | null |
import numpy as np
from Losses import Loss
class RootMeanSquaredError(Loss):
def call(self, true_labels, predicted_labels):
return np.sqrt(np.mean(np.power((predicted_labels - true_labels), 2)))
def __call__(self, true_labels, predicted_labels):
return self.call(true_labels, predicted_labels)
| 32
| 78
| 0.74375
| 44
| 320
| 5.136364
| 0.454545
| 0.176991
| 0.252212
| 0.331858
| 0.371681
| 0.371681
| 0.371681
| 0.371681
| 0
| 0
| 0
| 0.003731
| 0.1625
| 320
| 10
| 79
| 32
| 0.839552
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.285714
| 0.285714
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
75ccb068f53b8bf0bed825b920625a9936650316
| 322,958
|
py
|
Python
|
LasVegas/Resource.py
|
bozhikovstanislav/UI-Pylinac
|
ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d
|
[
"MIT"
] | 3
|
2020-12-24T20:23:24.000Z
|
2021-06-04T03:40:47.000Z
|
LasVegas/Resource.py
|
bozhikovstanislav/UI-Pylinac
|
ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d
|
[
"MIT"
] | null | null | null |
LasVegas/Resource.py
|
bozhikovstanislav/UI-Pylinac
|
ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.9.5)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_resource_name = b"\
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qt_resource_struct_v1 = b"\
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qt_resource_struct_v2 = b"\
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qt_version = QtCore.qVersion().split('.')
if qt_version < ['5', '8', '0']:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 65.138766
| 129
| 0.727129
| 78,193
| 322,958
| 3.00275
| 0.003901
| 0.087064
| 0.100582
| 0.103188
| 0.116911
| 0.110829
| 0.101881
| 0.090931
| 0.089104
| 0.08642
| 0
| 0.315139
| 0.015609
| 322,958
| 4,957
| 130
| 65.151906
| 0.4234
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| 0.000012
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| 0.000405
| false
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| null | 1
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| 0
| 0
|
0
| 4
|
75ded49545ff31c2bb3aed998ac0f570b9a6ae7e
| 107
|
py
|
Python
|
espnet2/text/text_preparation/flow/mutators/ru/__init__.py
|
texpomru13/espnet
|
7ef005e832e2fb033f356c16f54e0f08762fb4b0
|
[
"Apache-2.0"
] | null | null | null |
espnet2/text/text_preparation/flow/mutators/ru/__init__.py
|
texpomru13/espnet
|
7ef005e832e2fb033f356c16f54e0f08762fb4b0
|
[
"Apache-2.0"
] | null | null | null |
espnet2/text/text_preparation/flow/mutators/ru/__init__.py
|
texpomru13/espnet
|
7ef005e832e2fb033f356c16f54e0f08762fb4b0
|
[
"Apache-2.0"
] | null | null | null |
from .urls import URLVocalizer
from .phone import PhoneVocalizer
__all__ = [URLVocalizer, PhoneVocalizer]
| 21.4
| 40
| 0.82243
| 11
| 107
| 7.636364
| 0.636364
| 0
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| 107
| 4
| 41
| 26.75
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| 1
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|
0
| 4
|
75f0f75f336ddbc3b1de70d6bae802063faac3b8
| 167
|
py
|
Python
|
tests/test_datasets.py
|
ahou8288/self-driving-car-1
|
ea436a563ed6fe7668533ad77039e0580a912a31
|
[
"MIT"
] | 5
|
2018-09-24T13:05:16.000Z
|
2019-03-05T18:15:36.000Z
|
tests/test_datasets.py
|
ahou8288/self-driving-car-1
|
ea436a563ed6fe7668533ad77039e0580a912a31
|
[
"MIT"
] | 1
|
2019-05-22T11:02:45.000Z
|
2019-05-22T11:02:45.000Z
|
tests/test_datasets.py
|
ahou8288/self-driving-car-1
|
ea436a563ed6fe7668533ad77039e0580a912a31
|
[
"MIT"
] | 4
|
2018-02-17T05:30:34.000Z
|
2019-03-26T11:51:36.000Z
|
import unittest
import donkey as dk
class TestDatasets(unittest.TestCase):
def test_moving_square(self):
X, Y = dk.datasets.moving_square()
| 13.916667
| 42
| 0.676647
| 21
| 167
| 5.238095
| 0.761905
| 0.218182
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0.245509
| 167
| 11
| 43
| 15.181818
| 0.873016
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| 1
| 0.2
| false
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| 0.4
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| 0.8
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| null | 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
75f15cb6855a11a712931c354b7e81feac51f749
| 103
|
py
|
Python
|
xmos/curdir.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | 1
|
2021-08-15T21:26:10.000Z
|
2021-08-15T21:26:10.000Z
|
xmos/curdir.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | null | null | null |
xmos/curdir.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | null | null | null |
from os import getcwd
from xmtrace import xmtrace
@xmtrace
def xm_os_curdir(lua):
return getcwd()
| 14.714286
| 27
| 0.76699
| 16
| 103
| 4.8125
| 0.625
| 0
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| 0
| 0.174757
| 103
| 6
| 28
| 17.166667
| 0.905882
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| 0.2
| false
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| 0.4
| 0.2
| 0.8
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| 1
| 1
| 0
| 0
|
0
| 4
|
f9313b072dcc32f3cf332851d8c1333334962486
| 96
|
py
|
Python
|
crf_predict/apps.py
|
meiqw/sportsner
|
8aaaa74a5b55122d29509394dd12cc048584b372
|
[
"MIT"
] | null | null | null |
crf_predict/apps.py
|
meiqw/sportsner
|
8aaaa74a5b55122d29509394dd12cc048584b372
|
[
"MIT"
] | null | null | null |
crf_predict/apps.py
|
meiqw/sportsner
|
8aaaa74a5b55122d29509394dd12cc048584b372
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class CrfPredictConfig(AppConfig):
name = 'crf_predict'
| 16
| 34
| 0.770833
| 11
| 96
| 6.636364
| 0.909091
| 0
| 0
| 0
| 0
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| 0.15625
| 96
| 5
| 35
| 19.2
| 0.901235
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| 1
| 0
|
0
| 4
|
f942a285e92ad06c259ca5154cfcdb5c079591af
| 60
|
py
|
Python
|
kbcstorage/dataclasses/__init__.py
|
davidesner/sapi-python-client
|
0f16fa30cb93e6dc99b16e983c139f9c3abee67e
|
[
"MIT"
] | null | null | null |
kbcstorage/dataclasses/__init__.py
|
davidesner/sapi-python-client
|
0f16fa30cb93e6dc99b16e983c139f9c3abee67e
|
[
"MIT"
] | null | null | null |
kbcstorage/dataclasses/__init__.py
|
davidesner/sapi-python-client
|
0f16fa30cb93e6dc99b16e983c139f9c3abee67e
|
[
"MIT"
] | null | null | null |
"""
Helper dataclasses to be used as client parameters.
"""
| 15
| 51
| 0.716667
| 8
| 60
| 5.375
| 1
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| 60
| 3
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| 20
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0
| 4
|
f94e50f0e12cc5ab80972b8fe5e6a4459faf879e
| 28
|
py
|
Python
|
lib/python3.4/locale.py
|
caiocsalvador/whats_the_craic
|
c49ef62f1acd7379f6fd90c2b93aa1fa00c8661d
|
[
"MIT"
] | 7
|
2017-04-26T12:28:22.000Z
|
2021-02-09T18:59:50.000Z
|
django-ng/lib/python3.4/locale.py
|
Arsalen/BusinessStrategies
|
209e57340359af3ea063c064982198848dc36c5f
|
[
"MIT"
] | 13
|
2015-12-04T03:38:37.000Z
|
2015-12-12T00:15:46.000Z
|
django-ng/lib/python3.4/locale.py
|
Arsalen/BusinessStrategies
|
209e57340359af3ea063c064982198848dc36c5f
|
[
"MIT"
] | 8
|
2017-06-01T08:42:16.000Z
|
2020-07-23T12:30:19.000Z
|
/usr/lib/python3.4/locale.py
| 28
| 28
| 0.785714
| 6
| 28
| 3.666667
| 1
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| 0
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| 28
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0
| 4
|
f98723ae9d7cf57e88f886ea2c768958cb257ce9
| 213
|
py
|
Python
|
nonebot/adapters/qqguild/__init__.py
|
nonebot/adapter-qqguild
|
a3e4d353bfdaafb296743bc0f15ed5d643c64d85
|
[
"MIT"
] | 39
|
2021-12-23T14:26:41.000Z
|
2022-03-22T14:11:19.000Z
|
nonebot/adapters/qqguild/__init__.py
|
nonebot/adapter-qqguild
|
a3e4d353bfdaafb296743bc0f15ed5d643c64d85
|
[
"MIT"
] | 4
|
2022-01-22T17:59:50.000Z
|
2022-03-22T12:40:10.000Z
|
nonebot/adapters/qqguild/__init__.py
|
nonebot/adapter-qqguild
|
a3e4d353bfdaafb296743bc0f15ed5d643c64d85
|
[
"MIT"
] | 2
|
2022-01-16T02:38:51.000Z
|
2022-03-01T15:48:36.000Z
|
from .event import *
from .bot import Bot as Bot
from .utils import log as log
from .adapter import Adapter as Adapter
from .message import Message as Message
from .message import MessageSegment as MessageSegment
| 30.428571
| 53
| 0.807512
| 33
| 213
| 5.212121
| 0.30303
| 0.127907
| 0.197674
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| 0.159624
| 213
| 6
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|
0
| 4
|
f98b424c614fbdd7089ff5c89e75448a45f89e30
| 17,624
|
py
|
Python
|
MeterAutoReader.py
|
JasonJerome/Pointer-meter-reading-algorithm-by-Python
|
3cb2b260301875e4b4bb07dc8d7a86d8affc88a5
|
[
"MIT"
] | 12
|
2021-11-01T07:45:49.000Z
|
2022-03-09T10:33:38.000Z
|
MeterAutoReader.py
|
JasonJerome/Pointer-meter-reading-algorithm-by-Python
|
3cb2b260301875e4b4bb07dc8d7a86d8affc88a5
|
[
"MIT"
] | 3
|
2021-12-07T03:28:20.000Z
|
2022-03-02T08:43:54.000Z
|
MeterAutoReader.py
|
JasonJerome/Pointer-meter-reading-algorithm-by-Python
|
3cb2b260301875e4b4bb07dc8d7a86d8affc88a5
|
[
"MIT"
] | 2
|
2021-08-22T18:11:38.000Z
|
2021-12-25T12:17:47.000Z
|
import colorsys
import random
import os
import numpy as np
from yolo import YOLO
from PIL import Image
import cv2
import math
#import cv2 as cv
#import argparse
import matplotlib.pyplot as plt
video_path = "D:/test.mp4"
output_path = "D:/0.mp4"
ImageDir = os.listdir("D:/test/testimages")
j = 0
a = 0
b = 0
c = 0
detected_theata = 0
detected_theata1 = 0
detected_theata2 = 0
detected_theata3 = 0
jiaodu = 0
#这一步是为了调用已经训练好的Yolov3模型参数
yolov3_args = {
"model_path": 'logs/000/trained_weights_final.h5',
"anchors_path": 'model_data/yolo_anchors.txt',
"classes_path": 'model_data/coco_classes.txt',
"score": 0.08,
"iou": 0.3,
"model_image_size": (416, 416),
"gpu_num": 1,
}
def image(pic_path):
if pic_path == 0:
yolov3 = YOLO(**yolov3_args)
for i in range(len(ImageDir)):
ImagePath = "D:/test/testimages/" + ImageDir[i]
ImageName = "D:/test/testimages/" + str(i) + ".jpg"
img = Image.open(ImagePath)
image, boxes, scores, classes = yolov3.detect_image_mul(img)
origin = np.asarray(image) #将数据转为矩阵
image_bgr = cv2.cvtColor(np.asarray(origin), cv2.COLOR_RGB2BGR)#cv2下的色彩空间灰度化
cv2.imwrite(ImageName, image_bgr)
elif pic_path != 0:
yolov3 = YOLO(**yolov3_args)
img = Image.open(pic_path)#打开图片
img2 = cv2.imread(pic_path)
image, boxes, scores, classes = yolov3.detect_image_mul(img)#yolov3检测
origin = np.asarray(image) # 将数据转为矩阵
image_bgr = cv2.cvtColor(np.asarray(origin), cv2.COLOR_RGB2BGR) # cv2下的色彩空间灰度化
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/detected.jpg", image_bgr)
#boxes内返回的是yolo预测出来的边框坐标，通过该坐标可以对原图像进行裁剪
for i in range(boxes.shape[0]):
top, left, bottom, right = boxes[i]
# 或者用下面这句等价
#top = boxes[0][0]
#left = boxes[0][1]
#bottom = boxes[0][2]
#right = boxes[0][3]
top = top - 5
left = left - 5
bottom = bottom + 5
right = right + 5
# 左上角点的坐标
top = int(max(0, np.floor(top + 0.5).astype('int32')))
left = int(max(0, np.floor(left + 0.5).astype('int32')))
# 右下角点的坐标
bottom = int(min(np.shape(image)[0], np.floor(bottom + 0.5).astype('int32')))
right = int(min(np.shape(image)[1], np.floor(right + 0.5).astype('int32')))
# 记录图片的高度与宽度
a = bottom - top
b = right - left
print ('height', a)
print ('with', b)
croped_region = image_bgr[top:bottom, left:right] # 先高后宽
#cv2.imshow("cropimage", croped_region)
# 将裁剪好的目标保存到本地
j + 1
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/cutted_img_"+str(j)+".jpg", croped_region)
print('cropped successed')
cv2.waitKey(0)
cv2.destroyAllWindows()
def vameterdetect(num):
if num == 1:
origin = cv2.imread("D:/git/work/keras-yolo3/kuangxuanimages/cutted_img_"+str(j)+".jpg", 0)
nor = cv2.resize(origin, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_LINEAR)#图片归一化cv2.resize（输入图片，输出图片，沿x轴缩放系数，沿y轴缩放系数，插入方式为双线性插值（默认方式））
image_bgr = cv2.cvtColor(nor, cv2.COLOR_RGB2BGR)#转换为灰度图
gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
median = cv2.medianBlur(origin, 1)# 中值滤波去噪cv2.medianBlur(原图片, 当前的方框尺寸)
edges = cv2.Canny(median, 250, 350, apertureSize=3)# 边缘检测cv2.Canny（原图片， 最小阈值，最大阈值，Sobel算子的大小）
#kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) # 矩形结构
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5)) # 椭圆结构
# kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (5, 5)) #十字结构
# cv2.getStructuringElement(指定形状，内核的尺寸，锚点的位置 ) 返回指定形状和尺寸的结构元素。
# 霍夫直线
lines = cv2.HoughLines(edges, 1, np.pi / 180, 60)
result = edges.copy()
for line in lines[5]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata1 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
for line in lines[18]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata2 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
for line in lines[4]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata3 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
#cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/median.jpg", median)
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/edge.jpg", edges)
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/result.jpg", result)
#detected_theata = ((detected_theata2 - detected_theata3) / (detected_theata3 - detected_theata1)) * 800
#detected_theata = ((detected_theata1 - detected_theata3) / (detected_theata2 - detected_theata3)) * 500
#detected_theata = ((detected_theata2 - detected_theata1 + 180) / (detected_theata3 - detected_theata1 + 180)) * 2.5
#detected_theata = ((detected_theata1 - detected_theata2) / (detected_theata3 - detected_theata2 + 180)) * 120 - 10
#detected_theata = (180 - (detected_theata2 - detected_theata1)) / (360 - (detected_theata2 - detected_theata3)) * 1
detected_theata = ((180 + detected_theata3 - detected_theata1)) / (360 - (detected_theata1 - detected_theata2)) * 1.6 + 0.03
return detected_theata
def caculatejiaodu(num):
if num == 1 :
jiaodu = vameterdetect(1)
print('readnum = ', jiaodu)
image_detected = cv2.imread("D:/git/work/keras-yolo3/kuangxuanimages/detected.jpg", 0)
#image_cov = cv2.cvtColor(image_detected, cv2.COLOR_GRAY2BGR)
cv2.putText(image_detected, 'Readnum = {}'.format(jiaodu), (11, 11 + 22), cv2.FONT_HERSHEY_COMPLEX, 1, [230, 0, 0], 2)
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/read_num.jpg", image_detected)
cv2.imshow("ReadNum", image_detected)
print('Read success!')
cv2.waitKey(0)
cv2.destroyAllWindows()
return jiaodu
def video():
#jiaodu = caculatejiaodu(1)
#mode = 1
yolov3 = YOLO(**yolov3_args)
video_cap = cv2.VideoCapture(video_path)
if not video_cap.isOpened():
raise IOError
video_FourCC = int(video_cap.get(cv2.CAP_PROP_FOURCC))
video_fps = video_cap.get(cv2.CAP_PROP_FPS)
video_size = (int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
isOutput = True if output_path != "" else False
if isOutput:
out = cv2.VideoWriter(output_path, video_FourCC, video_fps, video_size)
frame_index = 0
name = 4228
while True:
#RecDraw.clear()
return_value, frame = video_cap.read()
frame_index = frame_index + 1
if frame is None:
break
if frame_index % 2 == 1:
x, y = frame.shape[0:2]
new_image = cv2.resize(frame, (int(y / 2), int(x / 2)))
name += 1
strname = "D:/test/" + str(name) + ".jpg"
cv2.imwrite(strname, new_image)
image_new = Image.fromarray(frame)
image, boxes, scores, classes = yolov3.detect_image_mul(image_new)
origin = np.asarray(image)
image_bgr = cv2.cvtColor(np.asarray(origin), cv2.COLOR_RGB2BGR) # cv2下的色彩空间灰度化
cv2.imwrite("D:/git/work/keras-yolo3/kuangxuanimages/detected.jpg", image_bgr)
# boxes内返回的是yolo预测出来的边框坐标，通过该坐标可以对原图像进行裁剪
for i in range(boxes.shape[0]):
top, left, bottom, right = boxes[i]
# 或者用下面这句等价
# top = boxes[0][0]
# left = boxes[0][1]
# bottom = boxes[0][2]
# right = boxes[0][3]
top = top - 5
left = left - 5
bottom = bottom + 5
right = right + 5
# 左上角点的坐标
top = int(max(0, np.floor(top + 0.5).astype('int32')))
left = int(max(0, np.floor(left + 0.5).astype('int32')))
# 右下角点的坐标
bottom = int(min(np.shape(image)[0], np.floor(bottom + 0.5).astype('int32')))
right = int(min(np.shape(image)[1], np.floor(right + 0.5).astype('int32')))
# 记录图片的高度与宽度
a = bottom - top
b = right - left
print('height', a)
print('with', b)
croped_region = image_bgr[top:bottom, left:right] # 先高后宽
# cv2.imshow("cropimage", croped_region)
nor = cv2.resize(croped_region, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_LINEAR) # 图片归一化cv2.resize（输入图片，输出图片，沿x轴缩放系数，沿y轴缩放系数，插入方式为双线性插值（默认方式））
image_bgr = cv2.cvtColor(nor, cv2.COLOR_RGB2BGR) # 转换为灰度图
gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
median = cv2.medianBlur(origin, 1) # 中值滤波去噪cv2.medianBlur(原图片, 当前的方框尺寸)
edges = cv2.Canny(median, 250, 350, apertureSize=3) # 边缘检测cv2.Canny（原图片， 最小阈值，最大阈值，Sobel算子的大小）
# kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) # 矩形结构
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5)) # 椭圆结构
# kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (5, 5)) #十字结构
# cv2.getStructuringElement(指定形状，内核的尺寸，锚点的位置 ) 返回指定形状和尺寸的结构元素。
# 霍夫直线
lines = cv2.HoughLines(edges, 1, np.pi / 180, 60)
result = edges.copy()
for line in lines[5]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata1 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
for line in lines[18]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata2 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
for line in lines[4]:
rho = line[0] # 第一个元素是距离rho
theta = line[1] # 第二个元素是角度theta
detected_theata3 = ((theta / np.pi) * 180)
print('distance:' + str(rho), 'theta:' + str(((theta / np.pi) * 180)))
lbael_text = 'distance:' + str(round(rho)) + 'theta:' + str(round((theta / np.pi) * 180 - 90, 2))
if (theta > 3 * (np.pi / 3)) or (theta < (np.pi / 2)): # 垂直直线
# 该直线与第一行的交点
pt1 = (int(rho / np.cos(theta)), 0)
# 该直线与最后一行的焦点
pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0])
# 绘制一条白线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat >180 theta<90')
else: # 水平直线
# 该直线与第一列的交点
pt1 = (0, int(rho / np.sin(theta)))
# 该直线与最后一列的交点
pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta)))
# 绘制一条直线
cv2.line(result, pt1, pt2, (255, 0, 0), 2, cv2.LINE_AA)
# print('theat <180 theta > 90')
detected_theata = ((180 + detected_theata3 - detected_theata1)) / (360 - (detected_theata1 - detected_theata2)) * 1.6 + 0.29
cv2.namedWindow("result", cv2.WINDOW_NORMAL)
cv2.putText(origin, 'Readnum = {}'.format(detected_theata), (11, 11 + 22), cv2.FONT_HERSHEY_COMPLEX, 1, [230, 0, 0], 2)
cv2.imshow("result", origin)
if isOutput:
out.write(origin)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if __name__ == '__main__':
# print("please input the type of your want to identify")
# m = input("pic or video? Answer: ")
# if m == "video":image
# elif m == "pic":
# pic_path = input("please input image path : ")
# image(pic_path)
#image("D:/git/work/keras-yolo3/images/6959.jpg")
#meterdetect(1)
#vameterdetect(1)
caculatejiaodu(1)
#video()
# image("D:/r.jpg")
# image(0)
| 44.844784
| 161
| 0.518668
| 2,092
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| 0.024129
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| 0.721403
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| 0.66164
| 0
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| 17,624
| 392
| 162
| 44.959184
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| 1
| 0.016461
| false
| 0
| 0.037037
| 0
| 0.061728
| 0.053498
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| 0
| null | 0
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| 1
| 1
| 1
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| 0
| 0
| 0
|
0
| 4
|
f9b5bf04b68211ba3ac94f61403844b7ed1d190c
| 839
|
py
|
Python
|
capybara/tests/session/test_has_table.py
|
dwt/capybara.py
|
eafd9ac50d02e8b57ef90d767493c8fa2be0739a
|
[
"MIT"
] | null | null | null |
capybara/tests/session/test_has_table.py
|
dwt/capybara.py
|
eafd9ac50d02e8b57ef90d767493c8fa2be0739a
|
[
"MIT"
] | null | null | null |
capybara/tests/session/test_has_table.py
|
dwt/capybara.py
|
eafd9ac50d02e8b57ef90d767493c8fa2be0739a
|
[
"MIT"
] | null | null | null |
import pytest
class TestHasTable:
@pytest.fixture(autouse=True)
def setup_session(self, session):
session.visit("/tables")
def test_is_true_if_the_table_is_on_the_page(self, session):
assert session.has_table("Villain")
assert session.has_table("villain_table")
def test_is_false_if_the_table_is_not_on_the_page(self, session):
assert not session.has_table("Monkey")
class TestHasNoTable:
@pytest.fixture(autouse=True)
def setup_session(self, session):
session.visit("/tables")
def test_is_false_if_the_table_is_on_the_page(self, session):
assert not session.has_no_table("Villain")
assert not session.has_no_table("villain_table")
def test_is_true_if_the_table_is_not_on_the_page(self, session):
assert session.has_no_table("Monkey")
| 29.964286
| 69
| 0.731824
| 122
| 839
| 4.614754
| 0.229508
| 0.117229
| 0.063943
| 0.085258
| 0.872114
| 0.82238
| 0.783304
| 0.699822
| 0.600355
| 0.554174
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| 0.175209
| 839
| 27
| 70
| 31.074074
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| 1
| 0.315789
| false
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| null | 0
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| 1
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| 0
| 0
| 0
|
0
| 4
|
f9e08c0fba94f53763713a0e625ae98c3a61481c
| 66
|
py
|
Python
|
101903683_kunal_topsis/__init__.py
|
Gargkunal02/101903683_kunal_topsis
|
97830e3ff56c4effacd3c968c069a83982dce47c
|
[
"MIT"
] | null | null | null |
101903683_kunal_topsis/__init__.py
|
Gargkunal02/101903683_kunal_topsis
|
97830e3ff56c4effacd3c968c069a83982dce47c
|
[
"MIT"
] | null | null | null |
101903683_kunal_topsis/__init__.py
|
Gargkunal02/101903683_kunal_topsis
|
97830e3ff56c4effacd3c968c069a83982dce47c
|
[
"MIT"
] | null | null | null |
from 101903683_kunal_topsis.topsis import rank
__version__='v1.2'
| 22
| 46
| 0.848485
| 10
| 66
| 5
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| 0.180328
| 0.075758
| 66
| 2
| 47
| 33
| 0.639344
| 0
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| 0.060606
| 0
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| 0
| 0
| 0
| null | null | 0
| 0.5
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
| 0
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| null | 0
| 0
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| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f9e0dfce7635e819ba1e0f9a89d25f1ae33688c4
| 234
|
py
|
Python
|
modules/gdscript_transpiler/config.py
|
orgrinrt/goost
|
9dd3cd7f723115939a4590a637c35b05314e6b07
|
[
"Apache-2.0",
"CC-BY-4.0",
"MIT"
] | 1
|
2021-02-11T20:51:09.000Z
|
2021-02-11T20:51:09.000Z
|
modules/gdscript_transpiler/config.py
|
TREVO786/goost
|
babbeb7583b603a59577cac3bf34c6e136ea7396
|
[
"CC-BY-3.0",
"MIT"
] | null | null | null |
modules/gdscript_transpiler/config.py
|
TREVO786/goost
|
babbeb7583b603a59577cac3bf34c6e136ea7396
|
[
"CC-BY-3.0",
"MIT"
] | null | null | null |
def can_build(env, platform):
return True
def configure(env):
pass
def is_enabled():
# Disabled by default being experimental at the moment.
# Enable manually with `module_gdscript_transpiler_enabled=yes` option.
return False
| 19.5
| 72
| 0.777778
| 33
| 234
| 5.363636
| 0.848485
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149573
| 234
| 11
| 73
| 21.272727
| 0.889447
| 0.525641
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0.166667
| 0
| 0.333333
| 0.833333
| 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
|
f9e29ec5bc8e4b1492c15eef59b89ce5d2e3086e
| 55
|
py
|
Python
|
Flask-Server/wsgi.py
|
weichweich/pi-timeswitch
|
c4428783fbf8b2294f7a6f55c312beeabae94d6f
|
[
"MIT"
] | 4
|
2015-10-12T19:13:22.000Z
|
2018-07-18T17:55:48.000Z
|
Flask-Server/wsgi.py
|
weichweich/pi-timeswitch
|
c4428783fbf8b2294f7a6f55c312beeabae94d6f
|
[
"MIT"
] | null | null | null |
Flask-Server/wsgi.py
|
weichweich/pi-timeswitch
|
c4428783fbf8b2294f7a6f55c312beeabae94d6f
|
[
"MIT"
] | 2
|
2017-04-25T16:19:09.000Z
|
2022-01-24T08:15:12.000Z
|
from timeswitch.server import gen_app
app = gen_app()
| 13.75
| 37
| 0.781818
| 9
| 55
| 4.555556
| 0.666667
| 0.292683
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145455
| 55
| 3
| 38
| 18.333333
| 0.87234
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
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| 0
| null | 1
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ddb96835b14cd0707d75989ee523a9ebf780ada0
| 1,962
|
py
|
Python
|
443/app.py
|
kaixiang1992/python-flask
|
2b4c597d83f5a6ed662d42d7ff692e563a9adbf8
|
[
"MIT"
] | null | null | null |
443/app.py
|
kaixiang1992/python-flask
|
2b4c597d83f5a6ed662d42d7ff692e563a9adbf8
|
[
"MIT"
] | null | null | null |
443/app.py
|
kaixiang1992/python-flask
|
2b4c597d83f5a6ed662d42d7ff692e563a9adbf8
|
[
"MIT"
] | null | null | null |
from flask import Flask, request
app = Flask(__name__)
@app.route('/')
def hello_world():
return 'Hello World!'
# TODO: http://127.0.0.1:5000/article
@app.route('/article')
def article_list():
return 'article list'
# TODO: string类型
# TODO: http://127.0.0.1:5000/article/c75776gnnb
# TODO: 不能接受带斜杠路径：http://127.0.0.1:5000/article/c75776gnnb/ahghgh123
@app.route('/article/<article_id>')
def article_detail(article_id):
return 'article detail by %s' % (article_id,)
# TODO: int类型
# TODO: http://127.0.0.1:5000/p/100
# TODO: 不能接受非`int`类型：http://127.0.0.1:5000/p/1001.123
@app.route('/p/<int:project_id>')
def project_detail(project_id):
return 'project detail by id=%s' % (project_id)
# TODO: float类型
# TODO: http://127.0.0.1:5000/project/100.123
# TODO: 不能接受非`float`类型：http://127.0.0.1:5000/project/10000
@app.route('/project/<float:item_str>')
def project(item_str):
return 'project item is %s' % (item_str,)
# TODO: path类型
# TODO: http://127.0.0.1:5000/user/email/changeemail/123
# TODO: variable不能为空：http://127.0.0.1:5000/user/
@app.route('/user/<path:user_path>')
def userCenter(user_path):
return 'user center url is %s' % (user_path,)
# import uuid
#
# print(uuid.uuid4())
# TODO: uuid类型
# TODO: http://127.0.0.1:5000/u/df78f232-f179-4351-97c8-ec4c8dc92542
@app.route('/u/<uuid:user_id>')
def user(user_id):
return 'user id is %s' % (user_id,)
# TODO: any类型
# TODO: blog: http://127.0.0.1:5000/blog/123
# TODO: category: http://127.0.0.1:5000/category/123
@app.route('/<any(blog,category):url_path>/<int:id>')
def detail(url_path, id):
if url_path == 'blog':
return '博客详情id：%s' % (id,)
else:
return '类目详情id：%s' % (id,)
# TODO: `search`传递参数模式
# TODO: http://127.0.0.1:5000/s?wd=python&ie=utf-8
@app.route('/s')
def search():
wd = request.args.get('wd')
ie = request.args.get('ie')
return '你搜索的关键字wd：%s，ie: %s' % (wd, ie)
if __name__ == '__main__':
app.run(debug=True)
| 23.638554
| 68
| 0.655454
| 327
| 1,962
| 3.828746
| 0.253823
| 0.072684
| 0.083067
| 0.09345
| 0.222843
| 0.222843
| 0.200479
| 0.072684
| 0
| 0
| 0
| 0.116224
| 0.136086
| 1,962
| 82
| 69
| 23.926829
| 0.622419
| 0.397554
| 0
| 0
| 0
| 0
| 0.28152
| 0.092401
| 0
| 0
| 0
| 0.012195
| 0
| 1
| 0.25
| false
| 0
| 0.027778
| 0.194444
| 0.555556
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
ddc56cf28f96268d86c60da23b460e08b066cb99
| 1,360
|
py
|
Python
|
test/test_task_instance_api.py
|
zachliu/airflow-python-sdk
|
70b5d08955a9e218fa6163b0612856e09eedce63
|
[
"MIT"
] | 12
|
2021-01-22T15:07:47.000Z
|
2021-10-19T13:47:40.000Z
|
test/test_task_instance_api.py
|
zachliu/airflow-python-sdk
|
70b5d08955a9e218fa6163b0612856e09eedce63
|
[
"MIT"
] | null | null | null |
test/test_task_instance_api.py
|
zachliu/airflow-python-sdk
|
70b5d08955a9e218fa6163b0612856e09eedce63
|
[
"MIT"
] | 2
|
2021-04-04T13:30:53.000Z
|
2021-07-20T13:58:07.000Z
|
"""
Airflow API (Stable)
Apache Airflow management API. # noqa: E501
The version of the OpenAPI document: 1.0.0
Contact: zach.z.liu@gmail.com
Generated by: https://openapi-generator.tech
"""
import unittest
import airflow_python_sdk
from airflow_python_sdk.api.task_instance_api import TaskInstanceApi # noqa: E501
class TestTaskInstanceApi(unittest.TestCase):
"""TaskInstanceApi unit test stubs"""
def setUp(self):
self.api = TaskInstanceApi() # noqa: E501
def tearDown(self):
pass
def test_delete_task_instance(self):
"""Test case for delete_task_instance
Delete DAG Run # noqa: E501
"""
pass
def test_get_extra_links(self):
"""Test case for get_extra_links
Get extra links for task instance # noqa: E501
"""
pass
def test_get_logs(self):
"""Test case for get_logs
Get logs for specific task instance # noqa: E501
"""
pass
def test_get_task_instance(self):
"""Test case for get_task_instance
Get a task instance # noqa: E501
"""
pass
def test_update_task_instance(self):
"""Test case for update_task_instance
Update a task instance # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 20.923077
| 82
| 0.625
| 169
| 1,360
| 4.810651
| 0.349112
| 0.162362
| 0.067651
| 0.092251
| 0.328413
| 0.280443
| 0.121771
| 0.083641
| 0
| 0
| 0
| 0.028008
| 0.291176
| 1,360
| 64
| 83
| 21.25
| 0.815353
| 0.439706
| 0
| 0.3
| 1
| 0
| 0.012945
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.35
| false
| 0.3
| 0.15
| 0
| 0.55
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
dddb0a79930e248a4e8e338c10522e8b874f4ff8
| 45
|
py
|
Python
|
likes/__init__.py
|
LowerDeez/ok-likes
|
a2c8dc568a2a62f2489ccf6cba5be48d0d6ddb9d
|
[
"MIT"
] | 15
|
2019-04-08T19:43:12.000Z
|
2022-01-31T15:47:07.000Z
|
likes/__init__.py
|
LowerDeez/ok-likes
|
a2c8dc568a2a62f2489ccf6cba5be48d0d6ddb9d
|
[
"MIT"
] | 3
|
2019-04-25T08:03:26.000Z
|
2022-01-23T00:42:31.000Z
|
likes/__init__.py
|
LowerDeez/ok-likes
|
a2c8dc568a2a62f2489ccf6cba5be48d0d6ddb9d
|
[
"MIT"
] | 1
|
2019-05-15T13:24:24.000Z
|
2019-05-15T13:24:24.000Z
|
default_app_config = 'likes.apps.LikeConfig'
| 22.5
| 44
| 0.822222
| 6
| 45
| 5.833333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 45
| 1
| 45
| 45
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0.466667
| 0.466667
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
dddfbac9e6335647cba88898d81b55bb0ac03bf9
| 83
|
py
|
Python
|
circus/py2raise.py
|
cdgz/circus
|
324e65a9d747731f7cf29c8bf98ff880a7787ee0
|
[
"Apache-2.0"
] | null | null | null |
circus/py2raise.py
|
cdgz/circus
|
324e65a9d747731f7cf29c8bf98ff880a7787ee0
|
[
"Apache-2.0"
] | null | null | null |
circus/py2raise.py
|
cdgz/circus
|
324e65a9d747731f7cf29c8bf98ff880a7787ee0
|
[
"Apache-2.0"
] | null | null | null |
import sys
def raise_with_tb(E): # NOQA
raise E, None, sys.exc_info()[2]
| 13.833333
| 36
| 0.626506
| 15
| 83
| 3.266667
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015873
| 0.240964
| 83
| 5
| 37
| 16.6
| 0.761905
| 0.048193
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.333333
| 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
|
ddf0466de4086deadc4946b09883ea6797d492ca
| 8,373
|
py
|
Python
|
tests/sat/Models/c617.150.SAT.dimacs.test.py
|
bernardocuteri/wasp
|
05c8f961776dbdbf7afbf905ee00fc262eba51ad
|
[
"Apache-2.0"
] | 19
|
2015-12-03T08:53:45.000Z
|
2022-03-31T02:09:43.000Z
|
tests/sat/Models/c617.150.SAT.dimacs.test.py
|
bernardocuteri/wasp
|
05c8f961776dbdbf7afbf905ee00fc262eba51ad
|
[
"Apache-2.0"
] | 80
|
2017-11-25T07:57:32.000Z
|
2018-06-10T19:03:30.000Z
|
tests/sat/Models/c617.150.SAT.dimacs.test.py
|
bernardocuteri/wasp
|
05c8f961776dbdbf7afbf905ee00fc262eba51ad
|
[
"Apache-2.0"
] | 6
|
2015-01-15T07:51:48.000Z
|
2020-06-18T14:47:48.000Z
|
input = """
c num blocks = 1
c num vars = 150
c minblockids[0] = 1
c maxblockids[0] = 150
p cnf 150 617
90 -20 8 0
-111 -68 -13 0
8 -150 -9 0
-66 63 -93 0
-135 40 81 0
106 -127 134 0
-54 123 45 0
24 -77 59 0
-82 48 71 0
12 75 87 0
127 -29 88 0
-120 -33 60 0
-126 -102 31 0
134 9 -150 0
62 -56 -83 0
92 27 75 0
-133 -52 50 0
-20 97 -13 0
65 55 -17 0
74 -77 -123 0
-11 -125 -98 0
-67 -35 -114 0
134 3 51 0
-113 132 101 0
94 -8 52 0
66 -1 -17 0
40 -21 -55 0
144 -125 -117 0
-28 43 -147 0
76 58 12 0
-2 27 103 0
58 125 7 0
-8 74 -15 0
-123 -46 108 0
98 -112 -92 0
-102 -31 -99 0
-3 116 38 0
-104 11 127 0
63 26 72 0
-97 96 -31 0
-136 132 -85 0
-23 32 -29 0
131 39 -75 0
68 -132 -110 0
-133 93 -28 0
41 32 -142 0
-1 81 -21 0
-59 131 12 0
115 -29 62 0
-117 40 73 0
10 -79 -75 0
-81 -8 117 0
130 -136 -21 0
-133 10 -112 0
29 -57 119 0
-130 112 97 0
37 71 69 0
28 -49 -88 0
-123 86 84 0
135 33 111 0
100 48 17 0
137 -47 -66 0
111 96 -93 0
-141 104 -19 0
-31 65 3 0
101 -3 -91 0
55 -123 -36 0
-90 -95 116 0
-79 137 -107 0
-25 68 -105 0
-66 -42 143 0
42 148 60 0
-31 80 -28 0
-10 -5 -126 0
-45 48 23 0
130 -36 96 0
100 65 -47 0
118 -75 18 0
111 -72 -135 0
143 7 -32 0
-45 83 -95 0
-52 -59 71 0
90 -139 -8 0
114 -95 -38 0
75 -12 116 0
26 15 79 0
-51 -50 -27 0
132 13 -147 0
-17 94 -76 0
106 79 121 0
-5 -43 117 0
53 118 51 0
-128 111 -146 0
45 53 77 0
-75 10 60 0
-10 100 99 0
51 -50 150 0
37 121 -127 0
-131 130 141 0
-75 -123 38 0
-76 -64 112 0
124 -144 138 0
-87 -51 -21 0
-36 -138 -12 0
63 -97 -130 0
-23 64 14 0
22 -143 -71 0
-28 -40 97 0
-35 -50 -22 0
-101 -24 -103 0
-125 -103 -6 0
-35 -16 -124 0
71 42 -48 0
6 11 -148 0
56 -101 -117 0
79 80 -113 0
-144 12 100 0
-99 114 -94 0
-82 -99 22 0
122 -86 137 0
-44 -7 -55 0
110 -120 23 0
-91 -54 131 0
108 -53 -110 0
97 62 -133 0
-37 69 -86 0
-111 68 66 0
-6 -12 -37 0
-136 60 40 0
24 -49 9 0
-64 125 -135 0
-108 -140 113 0
-139 -124 -90 0
24 -63 100 0
-138 -134 63 0
139 -21 -91 0
-53 132 59 0
57 54 -17 0
108 98 124 0
-105 -103 -68 0
-3 -24 84 0
-81 9 150 0
-65 52 -7 0
-123 91 -14 0
133 2 -66 0
-30 -103 -118 0
-136 26 131 0
-29 88 -111 0
148 -110 -41 0
20 10 -83 0
-129 77 -69 0
-65 -99 113 0
-117 107 -64 0
-9 -18 -94 0
23 48 -121 0
24 -145 108 0
65 30 -54 0
53 -87 108 0
-36 13 -76 0
-70 -130 -8 0
-66 -40 -65 0
30 -132 -124 0
-148 -114 -17 0
-116 -105 92 0
97 -14 -60 0
-83 50 -54 0
142 -140 105 0
-28 -142 -137 0
-92 -6 -72 0
109 -121 66 0
-138 -19 93 0
-86 41 46 0
-86 -121 -110 0
79 -85 -143 0
119 -104 -149 0
-139 -121 -42 0
-85 14 -4 0
42 121 -57 0
-5 -140 109 0
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-45 140 -73 0
-129 -42 64 0
9 -67 -41 0
127 -50 -46 0
-99 -33 119 0
28 131 -106 0
30 79 48 0
-35 -101 30 0
88 -101 -133 0
-70 -141 -146 0
55 148 -4 0
-63 50 -49 0
-141 105 112 0
72 119 -37 0
127 -75 134 0
49 83 -68 0
30 -51 64 0
125 -37 123 0
26 -60 99 0
82 63 44 0
-120 -75 107 0
18 145 -118 0
-140 5 14 0
-60 -119 132 0
85 29 -79 0
-3 -46 -104 0
-31 42 41 0
131 -51 -96 0
-71 -61 81 0
-55 39 -120 0
67 -73 -58 0
20 -72 -45 0
-122 42 40 0
26 -97 96 0
53 -83 -76 0
53 -100 85 0
-11 67 -26 0
-46 106 30 0
13 -6 -94 0
12 -32 -71 0
-31 33 117 0
104 29 -139 0
85 91 47 0
-90 122 147 0
95 -100 67 0
-50 142 75 0
-95 -83 -97 0
70 -22 -53 0
80 -81 118 0
-147 -28 62 0
52 -143 -54 0
-12 28 -128 0
129 -142 -123 0
-51 42 -113 0
63 121 39 0
45 -17 -1 0
76 22 104 0
-22 114 -127 0
2 86 -6 0
32 -148 59 0
106 -88 102 0
-139 58 137 0
17 38 -78 0
-106 -18 112 0
40 -93 -75 0
-12 121 58 0
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-13 -139 -88 0
-72 1 59 0
105 -140 49 0
111 40 -119 0
-105 -121 104 0
-144 -68 53 0
135 122 -106 0
-56 117 98 0
-31 -39 -122 0
-117 -130 -41 0
-150 -86 -3 0
-126 -149 93 0
-40 -29 54 0
32 -10 -2 0
-14 50 139 0
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-125 90 55 0
60 -107 52 0
66 12 127 0
-115 69 105 0
96 -41 61 0
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-26 -119 57 0
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-13 30 122 0
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54 -34 -11 0
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75 56 13 0
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114 -83 -78 0
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35 -115 133 0
22 -134 67 0
129 6 57 0
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40 -82 21 0
62 53 -101 0
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84 -58 -50 0
26 19 150 0
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73 -61 90 0
48 -135 -130 0
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136 -18 57 0
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83 -95 148 0
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119 -116 5 0
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46 -39 127 0
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57 118 110 0
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128 2 46 0
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33 -40 -35 0
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30 -3 146 0
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23 -124 -59 0
83 -39 43 0
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132 -3 -144 0
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92 -105 115 0
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15 -102 149 0
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66 144 71 0
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-4 -112 -150 0
97 -3 -74 0
-64 80 16 0
118 49 -93 0
-100 -98 -67 0
7 122 46 0
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18 11 -110 0
121 -128 -6 0
129 -12 69 0
110 114 66 0
-120 91 61 0
-108 -118 -31 0
-65 -83 145 0
-74 -79 101 0
49 -75 -133 0
-42 86 -34 0
20 111 -16 0
-125 135 63 0
59 -139 110 0
-74 57 73 0
45 -137 39 0
-15 -132 -28 0
145 105 -88 0
135 22 98 0
-52 -148 -36 0
-143 -102 -121 0
-10 33 139 0
23 69 116 0
-106 -12 11 0
25 -97 105 0
-65 25 43 0
70 72 -40 0
21 81 65 0
43 78 -27 0
132 -32 -135 0
-42 -134 60 0
-30 -17 62 0
127 -122 5 0
-101 140 -132 0
-110 114 19 0
62 83 -108 0
-144 85 16 0
17 -79 -88 0
-42 109 -114 0
108 -86 59 0
79 -62 20 0
56 99 -86 0
142 82 -4 0
-132 128 115 0
107 -6 -7 0
92 -81 -28 0
77 -51 6 0
3 -6 111 0
-129 -62 -52 0
-116 -75 99 0
146 -134 34 0
135 -46 132 0
67 44 8 0
-68 149 119 0
140 111 61 0
71 102 128 0
115 88 50 0
27 53 -58 0
-25 -24 150 0
15 116 -82 0
7 -141 -109 0
-65 -70 -54 0
-2 -36 66 0
133 148 -138 0
96 -116 -64 0
-58 -19 -90 0
49 -77 120 0
10 -58 -101 0
-114 134 -94 0
87 -49 32 0
-25 -74 -91 0
-36 -80 63 0
93 -105 77 0
-53 137 76 0
27 -76 -22 0
-58 -35 -17 0
139 72 15 0
-117 8 -104 0
-132 -114 139 0
32 -9 -72 0
108 -51 115 0
94 -86 128 0
-72 -126 -121 0
144 -95 -4 0
-58 15 -115 0
20 110 -31 0
-145 -110 -49 0
-70 -67 -56 0
33 -52 94 0
-104 -112 -43 0
16 32 29 0
-21 -18 -41 0
45 119 -129 0
-143 -107 -101 0
-42 -20 116 0
134 39 -104 0
148 -34 46 0
112 -96 74 0
96 69 32 0
52 150 87 0
-82 -85 19 0
-42 -40 24 0
26 -22 -123 0
87 45 130 0
49 94 -149 0
144 -40 -61 0
-120 -105 -71 0
-144 -35 16 0
-49 73 -53 0
113 139 20 0
81 -55 61 0
-103 147 -35 0
145 17 33 0
79 -69 150 0
-60 -39 -134 0
43 -114 109 0
-148 5 62 0
-75 -55 128 0
1 -108 -141 0
43 13 -104 0
-17 60 -55 0
128 -127 -53 0
-13 128 121 0
117 -137 -80 0
22 -110 14 0
"""
output = "SAT"
| 13.354067
| 22
| 0.586886
| 2,491
| 8,373
| 1.972702
| 0.065436
| 0.006716
| 0.002442
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.826213
| 0.29834
| 8,373
| 626
| 23
| 13.375399
| 0.010213
| 0
| 0
| 0
| 0
| 0
| 0.996656
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ddf0584dab919373873e1c2c081338bded7a61b9
| 305
|
py
|
Python
|
room_slot/login/admin.py
|
sonykarl/hotel_management
|
e1f1c76dbeb787977feeca3671a5f1f3892ce6c0
|
[
"MIT"
] | null | null | null |
room_slot/login/admin.py
|
sonykarl/hotel_management
|
e1f1c76dbeb787977feeca3671a5f1f3892ce6c0
|
[
"MIT"
] | null | null | null |
room_slot/login/admin.py
|
sonykarl/hotel_management
|
e1f1c76dbeb787977feeca3671a5f1f3892ce6c0
|
[
"MIT"
] | 1
|
2021-07-23T10:56:30.000Z
|
2021-07-23T10:56:30.000Z
|
from django.contrib import admin
from login.models import Customer, RoomManager
from booking.models import Contact,Rooms,Booking
# Register your models here.
admin.site.register(Customer)
admin.site.register(RoomManager)
admin.site.register(Contact)
admin.site.register(Rooms)
admin.site.register(Booking)
| 33.888889
| 48
| 0.836066
| 42
| 305
| 6.071429
| 0.380952
| 0.176471
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.072131
| 305
| 9
| 49
| 33.888889
| 0.90106
| 0.085246
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.375
| 0
| 0.375
| 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
|
ddf9fbd27fc574e514856cdfe527e2b488511484
| 531
|
py
|
Python
|
POO5.py
|
SamuelNunesDev/python-poo
|
25ad8737554e0af0dd4a4d2d7d048f2f1fade771
|
[
"MIT"
] | null | null | null |
POO5.py
|
SamuelNunesDev/python-poo
|
25ad8737554e0af0dd4a4d2d7d048f2f1fade771
|
[
"MIT"
] | null | null | null |
POO5.py
|
SamuelNunesDev/python-poo
|
25ad8737554e0af0dd4a4d2d7d048f2f1fade771
|
[
"MIT"
] | null | null | null |
class Square:
def __init__(self, side):
self.side = side
def perimeter(self):
return self.side * 4
def area(self):
return self.side ** 2
pass
class Rectangle:
def __init__(self, width, height):
self.width, self.height = width, height
def perimeter(self):
return self.width * 2 + self.height * 2
def area(self):
return self.width * self.height
q = Square(5)
print(q.perimeter())
print(q.area())
r = Rectangle(5, 10)
print(r.perimeter(), r.area())
| 17.7
| 47
| 0.59887
| 73
| 531
| 4.246575
| 0.273973
| 0.103226
| 0.180645
| 0.141935
| 0.303226
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020672
| 0.271186
| 531
| 29
| 48
| 18.310345
| 0.780362
| 0
| 0
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0.05
| 0
| 0.2
| 0.6
| 0.15
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
fb00d2b887e66baf35e015e7311095bae365073a
| 18
|
py
|
Python
|
scripts/evpn/__init__.py
|
rombie/contrail-test
|
a68c71d6f282142501a7e2e889bbb232fdd82dc3
|
[
"Apache-2.0"
] | 5
|
2020-09-29T00:36:57.000Z
|
2022-02-16T06:51:32.000Z
|
serial_scripts/tor_scale/lib/__init__.py
|
vkolli/contrail-test-perf
|
db04b8924a2c330baabe3059788b149d957a7d67
|
[
"Apache-2.0"
] | 27
|
2019-11-02T02:18:34.000Z
|
2022-02-24T18:49:08.000Z
|
serial_scripts/tor_scale/lib/__init__.py
|
vkolli/contrail-test-perf
|
db04b8924a2c330baabe3059788b149d957a7d67
|
[
"Apache-2.0"
] | 20
|
2019-11-28T16:02:25.000Z
|
2022-01-06T05:56:58.000Z
|
"""EVPN tests."""
| 9
| 17
| 0.5
| 2
| 18
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 18
| 1
| 18
| 18
| 0.5625
| 0.611111
| 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
|
fb2a5a46e856161ab1b41d54ae835940db3c1c09
| 188
|
py
|
Python
|
Assignments/Functions Advanced/Lab/03. Multiplication Function.py
|
KaloyankerR/python-advanced-repository
|
711672d0f033a5adffc3ca689d02d2a7a9a26bfb
|
[
"MIT"
] | null | null | null |
Assignments/Functions Advanced/Lab/03. Multiplication Function.py
|
KaloyankerR/python-advanced-repository
|
711672d0f033a5adffc3ca689d02d2a7a9a26bfb
|
[
"MIT"
] | null | null | null |
Assignments/Functions Advanced/Lab/03. Multiplication Function.py
|
KaloyankerR/python-advanced-repository
|
711672d0f033a5adffc3ca689d02d2a7a9a26bfb
|
[
"MIT"
] | null | null | null |
from functools import reduce
def multiply(*args):
return reduce(lambda a, b: a * b, args)
print(multiply(1, 4, 5))
print(multiply(4, 5, 6, 1, 3))
print(multiply(2, 0, 1000, 5000))
| 17.090909
| 43
| 0.654255
| 33
| 188
| 3.727273
| 0.636364
| 0.317073
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116883
| 0.180851
| 188
| 10
| 44
| 18.8
| 0.681818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| true
| 0
| 0.166667
| 0.166667
| 0.5
| 0.5
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
|
0
| 4
|
fb30d3310d509d3baa02adf93da10f986d2d4288
| 11
|
py
|
Python
|
ProjectRouting/Software/__init__.py
|
cober2019/Network-Automation
|
796b7760ca1f1e496a841c613eaff05ddba71b16
|
[
"MIT"
] | 48
|
2019-08-22T19:42:46.000Z
|
2022-03-22T07:05:02.000Z
|
app/Modules/ProjectRouting/Software/__init__.py
|
cober2019/IOS-XE-Routing
|
67b5a8414434480673c4beaf791c015b7f6aaa89
|
[
"MIT"
] | 2
|
2019-09-04T15:42:14.000Z
|
2020-05-07T15:21:20.000Z
|
app/Modules/ProjectRouting/Software/__init__.py
|
cober2019/IOS-XE-Routing
|
67b5a8414434480673c4beaf791c015b7f6aaa89
|
[
"MIT"
] | 16
|
2020-01-22T20:21:36.000Z
|
2021-12-25T06:08:48.000Z
|
# init_py
| 5.5
| 10
| 0.636364
| 2
| 11
| 3
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.272727
| 11
| 1
| 11
| 11
| 0.75
| 0.636364
| 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
|
fb3e46f7745c243935a431979632bd97a890cf98
| 846
|
py
|
Python
|
sundry/get_func_info.py
|
jamesabel/sundry
|
4f63bfa0624c88a3cd05adf2784e9e3e66e094f4
|
[
"MIT"
] | 2
|
2019-10-02T06:30:27.000Z
|
2021-07-10T22:39:30.000Z
|
sundry/get_func_info.py
|
jamesabel/sundry
|
4f63bfa0624c88a3cd05adf2784e9e3e66e094f4
|
[
"MIT"
] | 3
|
2019-03-13T17:15:58.000Z
|
2019-06-04T20:26:57.000Z
|
sundry/get_func_info.py
|
jamesabel/sundry
|
4f63bfa0624c88a3cd05adf2784e9e3e66e094f4
|
[
"MIT"
] | 1
|
2019-03-08T21:37:29.000Z
|
2019-03-08T21:37:29.000Z
|
import os
import inspect
def get_func_name() -> str:
"""
get name of the *calling* function
:return: name of the calling function
"""
return inspect.stack()[1].frame.f_code.co_name
def get_line_number() -> str:
"""
get line number of the *calling* function
:return: line number of the calling function
"""
return inspect.stack()[1].frame.f_lineno
def get_file_name() -> str:
"""
get base file name (i.e. just the file name - not the entire path) of the *calling* function
:return: file name of the calling function
"""
return os.path.basename(inspect.stack()[1].frame.f_code.co_filename)
def get_file_path() -> str:
"""
get file path of the *calling* function
:return: file path of the calling function
"""
return inspect.stack()[1].frame.f_code.co_filename
| 24.171429
| 96
| 0.658392
| 126
| 846
| 4.301587
| 0.253968
| 0.073801
| 0.177122
| 0.295203
| 0.690037
| 0.690037
| 0.571956
| 0.346863
| 0.271218
| 0.271218
| 0
| 0.006088
| 0.223404
| 846
| 34
| 97
| 24.882353
| 0.818874
| 0.446809
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
34889ac9488b56eb626d3c7f88669e596c3bd0cd
| 2,533
|
py
|
Python
|
tests/functional/core/settings/utils/test_etcd_tool.py
|
System73/tamarco
|
c85bec267d39057a4cd5f1c9854d5e2840cebb1e
|
[
"MIT"
] | 9
|
2019-09-06T10:57:36.000Z
|
2019-10-14T07:24:02.000Z
|
tests/functional/core/settings/utils/test_etcd_tool.py
|
System73/tamarco
|
c85bec267d39057a4cd5f1c9854d5e2840cebb1e
|
[
"MIT"
] | 4
|
2020-04-06T15:52:40.000Z
|
2021-06-02T00:27:33.000Z
|
tests/functional/core/settings/utils/test_etcd_tool.py
|
System73/tamarco
|
c85bec267d39057a4cd5f1c9854d5e2840cebb1e
|
[
"MIT"
] | 3
|
2019-09-06T10:52:05.000Z
|
2019-10-10T07:45:26.000Z
|
from os import path
from tamarco.core.settings.utils.etcd_tool import EtcdTool
def test_add_key():
response_dict = {}
client = EtcdTool(host="127.0.0.1")
client.write(key="/added_key", value="added value")
response = client.read("/", recursive=True)
for result in response.children:
response_dict[result.key] = result.value
assert response_dict["/added_key"] == "added value"
def test_delete_key():
response_dict = {}
client = EtcdTool(host="127.0.0.1")
client.write(key="/added_key_1", value="added value 1")
client.write(key="/added_key_2", value="added value 2")
client.delete(key="/added_key_1")
response = client.read("/", recursive=True)
for result in response.children:
response_dict[result.key] = result.value
assert "/added_key_1" not in response_dict
assert response_dict["/added_key_2"] == "added value 2"
def test_load_file():
response_dict = {}
test_folder = path.abspath(path.join(__file__, ".."))
setting_file = "settings.yml"
settings = test_folder + "/" + setting_file
client = EtcdTool(host="127.0.0.1")
client.load(settings)
response = client.read("/", recursive=True)
for result in response.children:
response_dict[result.key] = result.value
assert response_dict["/key_1"] == "1000"
assert response_dict["/key_2"] == "1000"
assert response_dict["/key_3"] == "1000.0"
assert response_dict["/key_4"] == "1000.0"
assert response_dict["/key_5"] == "1000"
assert response_dict["/key_6"] == "Yes"
assert response_dict["/key_7"] == "True"
assert response_dict["/one_level/key_1"] == "1000"
assert response_dict["/one_level/key_2"] == "1000"
assert response_dict["/one_level/key_3"] == "1000.0"
assert response_dict["/one_level/key_4"] == "1000.0"
assert response_dict["/one_level/key_5"] == "1000"
assert response_dict["/one_level/key_6"] == "Yes"
assert response_dict["/one_level/key_7"] == "True"
assert response_dict["/two_levels/intermediate_level/key_1"] == "1000"
assert response_dict["/two_levels/intermediate_level/key_2"] == "1000"
assert response_dict["/two_levels/intermediate_level/key_3"] == "1000.0"
assert response_dict["/two_levels/intermediate_level/key_4"] == "1000.0"
assert response_dict["/two_levels/intermediate_level/key_5"] == "1000"
assert response_dict["/two_levels/intermediate_level/key_6"] == "Yes"
assert response_dict["/two_levels/intermediate_level/key_7"] == "True"
| 34.22973
| 76
| 0.679432
| 351
| 2,533
| 4.621083
| 0.156695
| 0.221948
| 0.25524
| 0.122072
| 0.792232
| 0.77127
| 0.665845
| 0.551788
| 0.426017
| 0.331689
| 0
| 0.053302
| 0.163048
| 2,533
| 73
| 77
| 34.69863
| 0.711792
| 0
| 0
| 0.288462
| 0
| 0
| 0.27043
| 0.099487
| 0
| 0
| 0
| 0
| 0.461538
| 1
| 0.057692
| false
| 0
| 0.038462
| 0
| 0.096154
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
34934e2821c9359ac45661c00ca20f036c97af7f
| 96
|
py
|
Python
|
giterator/typing.py
|
simplistix/giterator
|
28f659b6f8edfd2abeb3f485c27c5ccdf6033a1e
|
[
"MIT"
] | 1
|
2020-12-09T15:49:11.000Z
|
2020-12-09T15:49:11.000Z
|
giterator/typing.py
|
simplistix/giterator
|
28f659b6f8edfd2abeb3f485c27c5ccdf6033a1e
|
[
"MIT"
] | null | null | null |
giterator/typing.py
|
simplistix/giterator
|
28f659b6f8edfd2abeb3f485c27c5ccdf6033a1e
|
[
"MIT"
] | null | null | null |
from datetime import date, datetime
from typing import Union
Date = Union[date, datetime, str]
| 19.2
| 35
| 0.78125
| 14
| 96
| 5.357143
| 0.5
| 0.32
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 96
| 4
| 36
| 24
| 0.925926
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
|
349e73638ea2ca37db5498f43b36494567a3b1ef
| 2,256
|
py
|
Python
|
tests/test_dlpfs.py
|
IBM/data-leakage-prevention-filesystem
|
9b3c0fb2692512dbc0066825162aa0852d7ae883
|
[
"Apache-2.0"
] | 10
|
2022-03-04T08:46:42.000Z
|
2022-03-22T15:28:25.000Z
|
tests/test_dlpfs.py
|
IBM/data-leakage-prevention-filesystem
|
9b3c0fb2692512dbc0066825162aa0852d7ae883
|
[
"Apache-2.0"
] | null | null | null |
tests/test_dlpfs.py
|
IBM/data-leakage-prevention-filesystem
|
9b3c0fb2692512dbc0066825162aa0852d7ae883
|
[
"Apache-2.0"
] | 1
|
2022-03-04T09:25:55.000Z
|
2022-03-04T09:25:55.000Z
|
import os
from pathlib import Path
from dlpfs import DataLeakagePreventionFileSystem
def test_initialization(tmp_path):
root = os.path.join(Path(__file__).parent, "test-data")
rule_specs = os.path.join(Path(__file__).parent, "test-rules.json")
fs = DataLeakagePreventionFileSystem(root=root, rule_specs=rule_specs, use_re2=True, guard_size=1024, use_sub=True)
assert fs.root == root
def test_file_write(tmp_path):
root = os.path.join(tmp_path, "test-data")
rule_specs = os.path.join(Path(__file__).parent, "test-rules.json")
os.mkdir(root)
fs = DataLeakagePreventionFileSystem(root=root, rule_specs=rule_specs, use_re2=True, guard_size=1024, use_sub=True)
data = "THIS IS SOME DATA".encode("utf-8")
fh = fs.__call__("create", "/foo", os.O_CREAT | os.O_WRONLY)
written_bytes = fs.__call__("write", "/foo", data, 0, fh)
fs.__call__("release", "/foo", fh)
assert written_bytes
assert len(data) == written_bytes
assert Path(root, "foo").exists
def test_read_file():
root = os.path.join(Path(__file__).parent, "test-data")
rule_specs = os.path.join(Path(__file__).parent, "test-rules.json")
fs = DataLeakagePreventionFileSystem(root=root, rule_specs=rule_specs, use_re2=True, guard_size=1024, use_sub=True)
fh = fs.__call__("open", "/plain-text.txt", os.O_RDONLY)
content = fs.__call__("read", "/plain-text.txt", 8 * 1024, 0, fh)
fs.__call__("release", "/plain-text.txt", fh)
assert len(content)
assert -1 != str(content, encoding="utf-8").find("my_email@foo.bar")
def test_read_with_block():
root = os.path.join(Path(__file__).parent, "test-data")
rule_specs = os.path.join(Path(__file__).parent, "test-rules-1.json")
fs = DataLeakagePreventionFileSystem(root=root, rule_specs=rule_specs, use_re2=True, guard_size=1024, use_sub=True)
fh = fs.__call__("open", "/plain-text.txt", os.O_RDONLY)
content: bytes = fs.__call__("read", "/plain-text.txt", 8 * 1024, 0, fh)
fs.__call__("release", "/plain-text.txt", fh)
assert len(content)
assert -1 == str(content, encoding="utf-8").find("my_email@foo.bar")
assert -1 != str(content, encoding="utf-8").find("".join(["*" for _ in range(len("my_email@foo.bar"))]))
| 33.176471
| 119
| 0.688387
| 335
| 2,256
| 4.307463
| 0.20597
| 0.074844
| 0.05544
| 0.067914
| 0.73666
| 0.725572
| 0.706168
| 0.706168
| 0.683299
| 0.683299
| 0
| 0.021277
| 0.145833
| 2,256
| 67
| 120
| 33.671642
| 0.727556
| 0
| 0
| 0.410256
| 0
| 0
| 0.149379
| 0
| 0
| 0
| 0
| 0
| 0.230769
| 1
| 0.102564
| false
| 0
| 0.076923
| 0
| 0.179487
| 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
|
34abefca5e25d03039c1d4f99fa13df908412a23
| 22
|
py
|
Python
|
example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Bessel Functions/Derivatives of Bessel Functions/kvp Return the $n$th derivative of $K_v(z)$ with respect to $z$.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Bessel Functions/Derivatives of Bessel Functions/kvp Return the $n$th derivative of $K_v(z)$ with respect to $z$.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Bessel Functions/Derivatives of Bessel Functions/kvp Return the $n$th derivative of $K_v(z)$ with respect to $z$.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | 1
|
2021-02-04T04:51:48.000Z
|
2021-02-04T04:51:48.000Z
|
special.kvp(v, z, n=1)
| 22
| 22
| 0.636364
| 6
| 22
| 2.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05
| 0.090909
| 22
| 1
| 22
| 22
| 0.65
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
9b29fc0bee2ea76fadd785d91a3be56aeefb1f83
| 55
|
py
|
Python
|
test_project/i18n_conf.py
|
gonz/django-model-i18n
|
be9de4f7058aaed2a6e1dc42f9f3baaac0bdd464
|
[
"BSD-3-Clause"
] | 4
|
2015-10-13T16:53:40.000Z
|
2021-09-08T22:09:05.000Z
|
test_project/i18n_conf.py
|
omab/django-model-i18n
|
be9de4f7058aaed2a6e1dc42f9f3baaac0bdd464
|
[
"BSD-3-Clause"
] | null | null | null |
test_project/i18n_conf.py
|
omab/django-model-i18n
|
be9de4f7058aaed2a6e1dc42f9f3baaac0bdd464
|
[
"BSD-3-Clause"
] | 9
|
2015-01-02T22:12:12.000Z
|
2021-09-08T22:09:07.000Z
|
from model_i18n import loaders
loaders.autodiscover()
| 13.75
| 30
| 0.836364
| 7
| 55
| 6.428571
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040816
| 0.109091
| 55
| 3
| 31
| 18.333333
| 0.877551
| 0
| 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
|
9b34413d3e036abcb0e5f090e133455992ca9b90
| 1,180
|
py
|
Python
|
leetcode/0575_distribute_candies.py
|
chaosWsF/Python-Practice
|
ff617675b6bcd125933024bb4c246b63a272314d
|
[
"BSD-2-Clause"
] | null | null | null |
leetcode/0575_distribute_candies.py
|
chaosWsF/Python-Practice
|
ff617675b6bcd125933024bb4c246b63a272314d
|
[
"BSD-2-Clause"
] | null | null | null |
leetcode/0575_distribute_candies.py
|
chaosWsF/Python-Practice
|
ff617675b6bcd125933024bb4c246b63a272314d
|
[
"BSD-2-Clause"
] | null | null | null |
"""
Given an integer array with even length, where different numbers in this array represent different
kinds of candies. Each number means one candy of the corresponding kind. You need to distribute
these candies equally in number to brother and sister. Return the maximum number of kinds of
candies the sister could gain.
Example 1:
Input: candies = [1,1,2,2,3,3]
Output: 3
Explanation:
There are three different kinds of candies (1, 2 and 3), and two candies for each kind.
Optimal distribution: The sister has candies [1,2,3] and the brother has candies [1,2,3],
too. The sister has three different kinds of candies.
Example 2:
Input: candies = [1,1,2,3]
Output: 2
Explanation: For example, the sister has candies [2,3] and the brother has candies [1,1]. The
sister has two different kinds of candies, the brother has only one kind of candies.
Note:
1. The length of the given array is in range [2, 10000], and will be even.
2. The number in given array is in range [-100000, 100000].
"""
class Solution:
def distributeCandies(self, candies):
return min(len(set(candies)), len(candies) // 2)
| 36.875
| 99
| 0.701695
| 192
| 1,180
| 4.3125
| 0.359375
| 0.065217
| 0.084541
| 0.111111
| 0.228261
| 0.062802
| 0.062802
| 0.062802
| 0
| 0
| 0
| 0.052345
| 0.222881
| 1,180
| 31
| 100
| 38.064516
| 0.8506
| 0.89322
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
9b51f2c3826d0017a0a8aba5d661162d9b903a6b
| 505
|
py
|
Python
|
data_generate/activitynet_label_80_20_100.py
|
dongzhuoyao/video-query-in-the-wild
|
41b015b3993d926c5d9bf02ec4402e7b9edac568
|
[
"Unlicense"
] | null | null | null |
data_generate/activitynet_label_80_20_100.py
|
dongzhuoyao/video-query-in-the-wild
|
41b015b3993d926c5d9bf02ec4402e7b9edac568
|
[
"Unlicense"
] | null | null | null |
data_generate/activitynet_label_80_20_100.py
|
dongzhuoyao/video-query-in-the-wild
|
41b015b3993d926c5d9bf02ec4402e7b9edac568
|
[
"Unlicense"
] | null | null | null |
from data_generate.activitynet_label import activitynet_label_list
import random
random.seed(620)
random.shuffle(activitynet_label_list)
arv_train_label = activitynet_label_list[:80]
arv_val_label = activitynet_label_list[80:100]
arv_test_label = activitynet_label_list[100:]
json_path = "data_generate/arv_db_80_20_100.json"
short_name = "80_20_100"
json_path = "data_generate/arv_db_{}.json".format(short_name)
moment_eval_json_path = "data_generate/arv_db_{}_untrimmed.json".format(
short_name
)
| 31.5625
| 72
| 0.833663
| 79
| 505
| 4.822785
| 0.341772
| 0.251969
| 0.262467
| 0.19685
| 0.354331
| 0.212598
| 0.146982
| 0
| 0
| 0
| 0
| 0.057692
| 0.073267
| 505
| 15
| 73
| 33.666667
| 0.75641
| 0
| 0
| 0
| 1
| 0
| 0.217822
| 0.2
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.153846
| 0
| 0.153846
| 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
|
9b5bb2aa0435ae771160122adef80202b6062e82
| 1,049
|
py
|
Python
|
data/test/python/9b5bb2aa0435ae771160122adef80202b6062e82test_nsobjectcontroller.py
|
harshp8l/deep-learning-lang-detection
|
2a54293181c1c2b1a2b840ddee4d4d80177efb33
|
[
"MIT"
] | 132
|
2015-01-01T10:02:42.000Z
|
2022-03-09T12:51:01.000Z
|
data/test/python/9b5bb2aa0435ae771160122adef80202b6062e82test_nsobjectcontroller.py
|
vassalos/deep-learning-lang-detection
|
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
|
[
"MIT"
] | 6
|
2015-01-06T08:23:19.000Z
|
2019-03-14T12:22:06.000Z
|
data/test/python/9b5bb2aa0435ae771160122adef80202b6062e82test_nsobjectcontroller.py
|
vassalos/deep-learning-lang-detection
|
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
|
[
"MIT"
] | 27
|
2015-02-23T11:51:43.000Z
|
2022-03-07T02:34:18.000Z
|
from AppKit import *
from PyObjCTools.TestSupport import *
class TestNSObjectController (TestCase):
def testMethods(self):
self.assertResultIsBOOL(NSObjectController.automaticallyPreparesContent)
self.assertArgIsBOOL(NSObjectController.setAutomaticallyPreparesContent_, 0)
self.assertResultIsBOOL(NSObjectController.isEditable)
self.assertArgIsBOOL(NSObjectController.setEditable_, 0)
self.assertResultIsBOOL(NSObjectController.canAdd)
self.assertResultIsBOOL(NSObjectController.canRemove)
self.assertResultIsBOOL(NSObjectController.validateUserInterfaceItem_)
self.assertResultIsBOOL(NSObjectController.fetchWithRequest_merge_error_)
self.assertArgIsBOOL(NSObjectController.fetchWithRequest_merge_error_, 1)
self.assertArgIsOut(NSObjectController.fetchWithRequest_merge_error_, 2)
self.assertResultIsBOOL(NSObjectController.usesLazyFetching)
self.assertArgIsBOOL(NSObjectController.setUsesLazyFetching_, 0)
if __name__ == "__main__":
main()
| 47.681818
| 84
| 0.798856
| 76
| 1,049
| 10.75
| 0.434211
| 0.188494
| 0.342717
| 0.161567
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005513
| 0.135367
| 1,049
| 21
| 85
| 49.952381
| 0.895259
| 0
| 0
| 0
| 0
| 0
| 0.007626
| 0
| 0
| 0
| 0
| 0
| 0.666667
| 1
| 0.055556
| false
| 0
| 0.111111
| 0
| 0.222222
| 0
| 0
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9b64e91a6eb67c584e50293e54d614d6ae1dc318
| 210
|
py
|
Python
|
zibenitis/apps/events/admin.py
|
davisfreimanis/zibenitis
|
bb77251b368747ed0844fc6033c263a8838e4782
|
[
"MIT"
] | null | null | null |
zibenitis/apps/events/admin.py
|
davisfreimanis/zibenitis
|
bb77251b368747ed0844fc6033c263a8838e4782
|
[
"MIT"
] | 18
|
2018-03-12T17:30:52.000Z
|
2018-08-30T10:01:14.000Z
|
zibenitis/apps/events/admin.py
|
davisfreimanis/zibenitis
|
bb77251b368747ed0844fc6033c263a8838e4782
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Event
class EventAdmin(admin.ModelAdmin):
list_display = ('title', 'date') # What fields to display in adming
admin.site.register(Event, EventAdmin)
| 23.333333
| 72
| 0.757143
| 28
| 210
| 5.642857
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147619
| 210
| 8
| 73
| 26.25
| 0.882682
| 0.152381
| 0
| 0
| 0
| 0
| 0.051136
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
32cc2a5ffa4b9234b76f665e17c4eecc8a9c6a8a
| 26
|
py
|
Python
|
meshed/tests/__init__.py
|
sylvainbonnot/meshed
|
6cd266810924480995d3a798e696ef7911dcf9b4
|
[
"MIT"
] | 3
|
2021-06-30T08:40:50.000Z
|
2022-01-19T13:13:33.000Z
|
meshed/tests/__init__.py
|
sylvainbonnot/meshed
|
6cd266810924480995d3a798e696ef7911dcf9b4
|
[
"MIT"
] | 18
|
2020-10-15T19:58:42.000Z
|
2022-03-28T19:06:37.000Z
|
meshed/tests/__init__.py
|
sylvainbonnot/meshed
|
6cd266810924480995d3a798e696ef7911dcf9b4
|
[
"MIT"
] | 1
|
2021-09-14T19:24:36.000Z
|
2021-09-14T19:24:36.000Z
|
"""Where test stuff is"""
| 13
| 25
| 0.615385
| 4
| 26
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 26
| 1
| 26
| 26
| 0.727273
| 0.730769
| 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
|
32ea3a0722a8f34369f3a4c007fb7b209f04da23
| 195
|
py
|
Python
|
libthumbor/django/urls.py
|
dthadi3/libthumbor
|
b206883d46a0f49e0eecc14bbf39d8daa6ad30a5
|
[
"MIT"
] | 30
|
2015-01-31T07:18:57.000Z
|
2022-02-11T05:29:26.000Z
|
libthumbor/django/urls.py
|
dthadi3/libthumbor
|
b206883d46a0f49e0eecc14bbf39d8daa6ad30a5
|
[
"MIT"
] | 33
|
2015-07-15T15:58:12.000Z
|
2022-03-31T22:53:03.000Z
|
libthumbor/django/urls.py
|
dthadi3/libthumbor
|
b206883d46a0f49e0eecc14bbf39d8daa6ad30a5
|
[
"MIT"
] | 23
|
2015-04-28T00:31:38.000Z
|
2021-08-24T14:08:35.000Z
|
from django.urls import path
from libthumbor.django.views import generate_url
urlpatterns = [ # pylint: disable=invalid-name
path("gen_url/", generate_url, name="generate_thumbor_url"),
]
| 24.375
| 64
| 0.764103
| 26
| 195
| 5.538462
| 0.615385
| 0.152778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 195
| 7
| 65
| 27.857143
| 0.847059
| 0.14359
| 0
| 0
| 1
| 0
| 0.169697
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
32f8717acdaafae8e583f45db8cd9cbfb03617f4
| 171
|
py
|
Python
|
0-buggy_2.py
|
kmirik999/Kryvoruchko-Myroslav
|
9f4a7fbe333e1ca3750e89e1f206aa9d9ca12145
|
[
"MIT"
] | null | null | null |
0-buggy_2.py
|
kmirik999/Kryvoruchko-Myroslav
|
9f4a7fbe333e1ca3750e89e1f206aa9d9ca12145
|
[
"MIT"
] | null | null | null |
0-buggy_2.py
|
kmirik999/Kryvoruchko-Myroslav
|
9f4a7fbe333e1ca3750e89e1f206aa9d9ca12145
|
[
"MIT"
] | null | null | null |
def sum(*args):
total_sum = 0
for number in args:
total_sum += number
return total_sum
result = sum(1, 3, 4, 5, 8, 9, 16)
print({ 'result': result })
| 19
| 34
| 0.578947
| 28
| 171
| 3.428571
| 0.642857
| 0.25
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.073171
| 0.280702
| 171
| 8
| 35
| 21.375
| 0.707317
| 0
| 0
| 0
| 0
| 0
| 0.035294
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0
| 0
| 0.285714
| 0.142857
| 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
|
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