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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2a70bb4a1af2f0cf33b2353df2392bc5e397734d
| 83
|
py
|
Python
|
bigdata/kpop/apps.py
|
BI-Project/AOC
|
d927a548bc6f3167a0d1535bb5626a1ba3bb7b6c
|
[
"MIT"
] | 1
|
2020-12-12T18:29:47.000Z
|
2020-12-12T18:29:47.000Z
|
bigdata/kpop/apps.py
|
BI-Project/AOC
|
d927a548bc6f3167a0d1535bb5626a1ba3bb7b6c
|
[
"MIT"
] | 2
|
2020-12-13T12:55:27.000Z
|
2020-12-13T12:55:55.000Z
|
bigdata/kpop/apps.py
|
BI-Project/AOC
|
d927a548bc6f3167a0d1535bb5626a1ba3bb7b6c
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class KpopConfig(AppConfig):
name = 'kpop'
| 13.833333
| 33
| 0.73494
| 10
| 83
| 6.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180723
| 83
| 5
| 34
| 16.6
| 0.897059
| 0
| 0
| 0
| 0
| 0
| 0.048193
| 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
|
2a83a2d55e8d9174f4232091f6ddbc41588e3382
| 248
|
py
|
Python
|
dashboard/console/context_processors.py
|
bhavyejain/meshsos-dashboard
|
77358ad05de738b09e490ca4d4af00a6510973a0
|
[
"MIT"
] | 1
|
2021-03-25T17:45:20.000Z
|
2021-03-25T17:45:20.000Z
|
dashboard/console/context_processors.py
|
bhavyejain/meshsos-dashboard
|
77358ad05de738b09e490ca4d4af00a6510973a0
|
[
"MIT"
] | 3
|
2021-06-04T22:53:03.000Z
|
2021-09-22T18:52:55.000Z
|
dashboard/console/context_processors.py
|
bhavyejain/meshsos-dashboard
|
77358ad05de738b09e490ca4d4af00a6510973a0
|
[
"MIT"
] | 1
|
2020-11-06T08:29:11.000Z
|
2020-11-06T08:29:11.000Z
|
from django.conf import settings
GOOGLE_API_KEY = settings.GOOGLE_API_KEY
MAPBOX_API_KEY = settings.MAPBOX_API_KEY
def global_settings(request):
return{
'GOOGLE_API_KEY': GOOGLE_API_KEY,
'MAPBOX_API_KEY': MAPBOX_API_KEY,
}
| 24.8
| 41
| 0.754032
| 36
| 248
| 4.722222
| 0.361111
| 0.282353
| 0.282353
| 0.264706
| 0.352941
| 0.282353
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173387
| 248
| 10
| 42
| 24.8
| 0.829268
| 0
| 0
| 0
| 0
| 0
| 0.11245
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0
| 0.125
| 0.125
| 0.25
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
2a8b716cc08b60f6585cc5574fbc2259db0a8ffb
| 130
|
py
|
Python
|
journal/apps.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | 2
|
2016-10-21T20:46:28.000Z
|
2020-01-27T09:54:10.000Z
|
journal/apps.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | null | null | null |
journal/apps.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | null | null | null |
from __future__ import unicode_literals
from django.apps import AppConfig
class JournalConfig(AppConfig):
name = 'journal'
| 16.25
| 39
| 0.792308
| 15
| 130
| 6.533333
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 130
| 7
| 40
| 18.571429
| 0.890909
| 0
| 0
| 0
| 0
| 0
| 0.053846
| 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
|
2a8c6d46aa6c8721f94f3c454cfc2ea9ef3626ee
| 68
|
py
|
Python
|
nvdb_qgis_plugin-master/nvdbapi-V3-master/nvdbapiv3/__init__.py
|
Peranox/NVDBQGIS
|
3af18a96d6bf28e05834416db013a01173f6dbc8
|
[
"MIT"
] | 11
|
2020-10-01T12:55:46.000Z
|
2021-11-30T18:05:12.000Z
|
nvdb_qgis_plugin-master/nvdbapi-V3-master/nvdbapiv3/__init__.py
|
Peranox/NVDBQGIS
|
3af18a96d6bf28e05834416db013a01173f6dbc8
|
[
"MIT"
] | 26
|
2020-04-24T10:00:25.000Z
|
2021-12-08T15:34:45.000Z
|
nvdb_qgis_plugin-master/nvdbapi-V3-master/nvdbapiv3/__init__.py
|
Peranox/NVDBQGIS
|
3af18a96d6bf28e05834416db013a01173f6dbc8
|
[
"MIT"
] | 5
|
2020-11-11T19:53:04.000Z
|
2021-12-16T08:58:19.000Z
|
from .nvdbapiv3 import *
from .apiforbindelse import apiforbindelse
| 22.666667
| 42
| 0.838235
| 7
| 68
| 8.142857
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016667
| 0.117647
| 68
| 2
| 43
| 34
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
aa56ace99a2c4fab988cbd3758abdf21498e4481
| 69
|
py
|
Python
|
leveling/utils/__init__.py
|
JohnRickGD/leveling
|
e5e018c27752734ed71b8faa54f18bfb0c0a5e1d
|
[
"MIT"
] | 11
|
2021-08-31T07:24:34.000Z
|
2022-03-09T04:50:53.000Z
|
leveling/utils/__init__.py
|
JohnRickGD/leveling
|
e5e018c27752734ed71b8faa54f18bfb0c0a5e1d
|
[
"MIT"
] | 1
|
2021-11-01T02:03:38.000Z
|
2021-11-14T21:16:07.000Z
|
leveling/utils/__init__.py
|
JohnRickGD/leveling
|
e5e018c27752734ed71b8faa54f18bfb0c0a5e1d
|
[
"MIT"
] | 6
|
2021-09-05T21:14:40.000Z
|
2022-02-26T11:16:35.000Z
|
from .sql import create_tables, increase_xp, get_user_data, get_rank
| 34.5
| 68
| 0.84058
| 12
| 69
| 4.416667
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101449
| 69
| 1
| 69
| 69
| 0.854839
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
aaa973438d7e39578c9ed5e28328af875d6e54dd
| 72
|
py
|
Python
|
logcausality/__init__.py
|
cpflat/LogCausalAnalysis
|
f475f53cb683ab6ad55851c69129758e4ac89fc6
|
[
"BSD-3-Clause"
] | 20
|
2016-11-22T03:21:20.000Z
|
2021-06-16T02:44:58.000Z
|
logcausality/__init__.py
|
arita37/LogCausalAnalysis
|
f475f53cb683ab6ad55851c69129758e4ac89fc6
|
[
"BSD-3-Clause"
] | 1
|
2019-10-23T05:45:34.000Z
|
2019-11-01T04:56:01.000Z
|
logcausality/__init__.py
|
arita37/LogCausalAnalysis
|
f475f53cb683ab6ad55851c69129758e4ac89fc6
|
[
"BSD-3-Clause"
] | 8
|
2015-11-13T03:33:04.000Z
|
2021-09-10T09:29:23.000Z
|
"""
A system log management tool with time-series causal analysis
"""
| 12
| 61
| 0.722222
| 10
| 72
| 5.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180556
| 72
| 5
| 62
| 14.4
| 0.881356
| 0.847222
| 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
|
aaca7b79ffe1f2d4c777daf1c9bb91c06d694953
| 347
|
py
|
Python
|
src/datasets/trivago_test.py
|
lukas-manduch/dt
|
a90672fe7cf866b00e5f6711cc9ae03b82046581
|
[
"Unlicense"
] | null | null | null |
src/datasets/trivago_test.py
|
lukas-manduch/dt
|
a90672fe7cf866b00e5f6711cc9ae03b82046581
|
[
"Unlicense"
] | null | null | null |
src/datasets/trivago_test.py
|
lukas-manduch/dt
|
a90672fe7cf866b00e5f6711cc9ae03b82046581
|
[
"Unlicense"
] | null | null | null |
import pytest
from datasets.trivago import *
def test_hashing():
assert hash_params([]) == hash_params([])
assert hash_params((1, 2, 3)) != hash_params()
assert hash_params((1, 2, 3)) == hash_params((1, 2, 3))
hash1 = hash_params({"a":1, "k":"m"}, "aa")
hash2 = hash_params({"a":1, "k":"m"}, "aa")
assert hash1 == hash2
| 26.692308
| 59
| 0.590778
| 52
| 347
| 3.769231
| 0.384615
| 0.408163
| 0.244898
| 0.183673
| 0.52551
| 0.510204
| 0.510204
| 0.346939
| 0.346939
| 0.346939
| 0
| 0.053571
| 0.193084
| 347
| 12
| 60
| 28.916667
| 0.646429
| 0
| 0
| 0
| 0
| 0
| 0.028818
| 0
| 0
| 0
| 0
| 0
| 0.444444
| 1
| 0.111111
| false
| 0
| 0.222222
| 0
| 0.333333
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
aae022d2618f5f597d8964c4631b1fdb593fc703
| 34
|
py
|
Python
|
envalidate/version.py
|
ozshalom/envalidate
|
641972ddab20e4ed1c25c50ee07a88946a4091a2
|
[
"MIT"
] | null | null | null |
envalidate/version.py
|
ozshalom/envalidate
|
641972ddab20e4ed1c25c50ee07a88946a4091a2
|
[
"MIT"
] | null | null | null |
envalidate/version.py
|
ozshalom/envalidate
|
641972ddab20e4ed1c25c50ee07a88946a4091a2
|
[
"MIT"
] | null | null | null |
"""Version."""
VERSION = "1.0.0"
| 8.5
| 17
| 0.5
| 5
| 34
| 3.4
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103448
| 0.147059
| 34
| 3
| 18
| 11.333333
| 0.482759
| 0.235294
| 0
| 0
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
2ab1bd8b669cdb3f53120b886c5733054cbe8f53
| 619
|
py
|
Python
|
app/services/ItemsService.py
|
danjaniell/inventory-api
|
51e80f804c4247aca80c9d6d1c1baa055d28cb65
|
[
"MIT"
] | null | null | null |
app/services/ItemsService.py
|
danjaniell/inventory-api
|
51e80f804c4247aca80c9d6d1c1baa055d28cb65
|
[
"MIT"
] | null | null | null |
app/services/ItemsService.py
|
danjaniell/inventory-api
|
51e80f804c4247aca80c9d6d1c1baa055d28cb65
|
[
"MIT"
] | null | null | null |
from typing import Iterator
from app.data.repositories import ItemRepository
from app.models.entities.Item import Item
class ItemService:
def __init__(self, item_repository: ItemRepository) -> None:
self._repository: ItemRepository = item_repository
def get_items(self) -> Iterator[Item]:
return self._repository.get_all()
def get_item_by_id(self, id: int) -> Item:
return self._repository.get(id)
def add_item(self, item) -> Item:
return self._repository.add(item)
def delete_item_by_id(self, id: int) -> None:
return self._repository.delete_by_id(id)
| 29.47619
| 64
| 0.712439
| 83
| 619
| 5.048193
| 0.325301
| 0.167064
| 0.190931
| 0.171838
| 0.210024
| 0.081146
| 0
| 0
| 0
| 0
| 0
| 0
| 0.192246
| 619
| 20
| 65
| 30.95
| 0.838
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.357143
| false
| 0
| 0.214286
| 0.285714
| 0.928571
| 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
|
2abf467c4cae38f5321998fdca05b0cf78a5c210
| 117
|
py
|
Python
|
chatbot/FacebookEndpoint.py
|
aelawson/bypath
|
256fe752b7c004a359fc6c3f2e968b1579ef654c
|
[
"MIT"
] | null | null | null |
chatbot/FacebookEndpoint.py
|
aelawson/bypath
|
256fe752b7c004a359fc6c3f2e968b1579ef654c
|
[
"MIT"
] | null | null | null |
chatbot/FacebookEndpoint.py
|
aelawson/bypath
|
256fe752b7c004a359fc6c3f2e968b1579ef654c
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# I need to figure out how I want to deal with these classes
class FacebookEndpoint:
pass
| 19.5
| 60
| 0.735043
| 20
| 117
| 4.3
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205128
| 117
| 6
| 61
| 19.5
| 0.924731
| 0.675214
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
2ad0422229e1c4abcdd9a721a93abf3289754b40
| 294
|
py
|
Python
|
bigcommerce/resources/v3/pages.py
|
aglensmith/bigcommerce-api-python
|
2f83ae30dbaa3cd9b7d465e40df2862a7f13795c
|
[
"MIT"
] | null | null | null |
bigcommerce/resources/v3/pages.py
|
aglensmith/bigcommerce-api-python
|
2f83ae30dbaa3cd9b7d465e40df2862a7f13795c
|
[
"MIT"
] | null | null | null |
bigcommerce/resources/v3/pages.py
|
aglensmith/bigcommerce-api-python
|
2f83ae30dbaa3cd9b7d465e40df2862a7f13795c
|
[
"MIT"
] | null | null | null |
from ..base import *
# TODO: test
# TODO: add CollectionUpdateableApiResource
class Pages(ListableApiResource, CreateableApiResource,
UpdateableApiResource, DeleteableApiResource, CollectionDeleteableApiResource):
resource_version = 'v3'
resource_name = 'content/pages'
| 32.666667
| 94
| 0.768707
| 22
| 294
| 10.181818
| 0.863636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004049
| 0.159864
| 294
| 9
| 95
| 32.666667
| 0.902834
| 0.176871
| 0
| 0
| 0
| 0
| 0.0625
| 0
| 0
| 0
| 0
| 0.111111
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.8
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
630fc91cea7fc8f6b6b65a60b615f6569ecfe26e
| 64
|
py
|
Python
|
leo_fw/src/leo_fw/__init__.py
|
LeoRover/leo_robo
|
06fa1179d62a01f65351feb490462374d67a77be
|
[
"MIT"
] | 1
|
2021-12-19T07:27:18.000Z
|
2021-12-19T07:27:18.000Z
|
leo_fw/src/leo_fw/__init__.py
|
LeoRover/leo_robo
|
06fa1179d62a01f65351feb490462374d67a77be
|
[
"MIT"
] | 2
|
2022-01-07T16:28:08.000Z
|
2022-03-03T17:52:40.000Z
|
leo_fw/src/leo_fw/__init__.py
|
LeoRover/leo_robo
|
06fa1179d62a01f65351feb490462374d67a77be
|
[
"MIT"
] | 5
|
2020-10-26T11:41:51.000Z
|
2022-02-11T12:39:59.000Z
|
from .flash import flash_firmware
__all__ = ["flash_firmware"]
| 16
| 33
| 0.78125
| 8
| 64
| 5.5
| 0.625
| 0.590909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 64
| 3
| 34
| 21.333333
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0.21875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
631c583842b757f6de9c41636c50200391e60529
| 191
|
py
|
Python
|
lona_project/views/home.py
|
fscherf/lona-project-template
|
89a0491717b87e1d3cafce272e34ba9be1cf2ea1
|
[
"Unlicense"
] | 3
|
2021-08-09T17:16:40.000Z
|
2021-08-14T07:22:46.000Z
|
lona_project/views/home.py
|
lona-web-org/lona-project-template
|
89a0491717b87e1d3cafce272e34ba9be1cf2ea1
|
[
"Unlicense"
] | 1
|
2021-08-10T19:05:21.000Z
|
2021-08-11T08:44:15.000Z
|
lona_project/views/home.py
|
lona-web-org/lona-project-template
|
89a0491717b87e1d3cafce272e34ba9be1cf2ea1
|
[
"Unlicense"
] | null | null | null |
from lona.view import LonaView
from lona.html import HTML, H1
class HomeView(LonaView):
def handle_request(self, request):
return HTML(
H1('Hello World'),
)
| 19.1
| 38
| 0.633508
| 24
| 191
| 5
| 0.666667
| 0.133333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014493
| 0.277487
| 191
| 9
| 39
| 21.222222
| 0.855072
| 0
| 0
| 0
| 0
| 0
| 0.057592
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.285714
| 0.142857
| 0.714286
| 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
|
632010daef6a6ef551192f8fbadd23ed87648ff6
| 97
|
py
|
Python
|
mlprogram/transpyle.py
|
HiroakiMikami/mlprogram
|
573e94c567064705fa65267dd83946bf183197de
|
[
"MIT"
] | 9
|
2020-05-24T11:25:01.000Z
|
2022-03-28T15:32:10.000Z
|
mlprogram/transpyle.py
|
HiroakiMikami/mlprogram
|
573e94c567064705fa65267dd83946bf183197de
|
[
"MIT"
] | 87
|
2020-05-09T08:56:55.000Z
|
2022-03-31T14:46:45.000Z
|
mlprogram/transpyle.py
|
HiroakiMikami/NL2Prog
|
573e94c567064705fa65267dd83946bf183197de
|
[
"MIT"
] | 3
|
2021-02-22T20:38:29.000Z
|
2021-11-11T18:48:44.000Z
|
import logging
import transpyle # noqa
# Disable logging to file
del logging.root.handlers[1]
| 13.857143
| 28
| 0.773196
| 14
| 97
| 5.357143
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012346
| 0.164948
| 97
| 6
| 29
| 16.166667
| 0.91358
| 0.28866
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 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
|
632376c9b1c9e4cb1332b945e405f59e662ca199
| 94
|
py
|
Python
|
start_client.py
|
Exs1de/TicTacToe
|
0119ab798b1c04cd1d003c9c95591415d1576156
|
[
"MIT"
] | 1
|
2019-04-29T19:41:12.000Z
|
2019-04-29T19:41:12.000Z
|
start_client.py
|
Exs1de/TicTacToe
|
0119ab798b1c04cd1d003c9c95591415d1576156
|
[
"MIT"
] | null | null | null |
start_client.py
|
Exs1de/TicTacToe
|
0119ab798b1c04cd1d003c9c95591415d1576156
|
[
"MIT"
] | null | null | null |
import GUI
import StateHandler as SH
SH.handle('STATE_MAIN_MENU')
GUI.root.mainloop()
| 13.428571
| 29
| 0.734043
| 14
| 94
| 4.785714
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170213
| 94
| 6
| 30
| 15.666667
| 0.858974
| 0
| 0
| 0
| 0
| 0
| 0.170455
| 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
|
632ed773182d834fc101e021696f6ca4a76dcd82
| 494
|
py
|
Python
|
test/solution_tests/HLO/test_hlo.py
|
DPNT-Sourcecode/CHK-qvft01
|
4aa8bb6d3bf28db7150a4f7aeab8dc702cc609ac
|
[
"Apache-2.0"
] | null | null | null |
test/solution_tests/HLO/test_hlo.py
|
DPNT-Sourcecode/CHK-qvft01
|
4aa8bb6d3bf28db7150a4f7aeab8dc702cc609ac
|
[
"Apache-2.0"
] | null | null | null |
test/solution_tests/HLO/test_hlo.py
|
DPNT-Sourcecode/CHK-qvft01
|
4aa8bb6d3bf28db7150a4f7aeab8dc702cc609ac
|
[
"Apache-2.0"
] | null | null | null |
from lib.solutions.HLO.hello_solution import hello
from solutions.HLO import hello_solution
def test_hello_message_prints_correctly():
assert hello_solution.hello() == "Hello, World!"
def test_hello_message_without_name():
assert hello_solution.hello() == "Hello, World!"
def test_hello_with_friend_name():
friend_name = "Alex"
assert hello_solution.hello(friend_name) == 'Hello, Alex!'
friend_name = "John"
assert hello_solution.hello(friend_name) == 'Hello, John!'
| 32.933333
| 62
| 0.753036
| 66
| 494
| 5.30303
| 0.30303
| 0.222857
| 0.217143
| 0.274286
| 0.485714
| 0.485714
| 0.485714
| 0.262857
| 0.262857
| 0
| 0
| 0
| 0.135628
| 494
| 15
| 63
| 32.933333
| 0.819672
| 0
| 0
| 0.181818
| 0
| 0
| 0.117172
| 0
| 0
| 0
| 0
| 0
| 0.363636
| 1
| 0.272727
| false
| 0
| 0.181818
| 0
| 0.454545
| 0.090909
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
2d4eb13a74dab2c02ae2dab8ede4418265485813
| 2,027
|
py
|
Python
|
python/src/problem045.py
|
arturh85/projecteuler
|
c3685e302ea7c323193b18c105a7e02da01fd6b5
|
[
"MIT"
] | 3
|
2015-02-04T08:37:01.000Z
|
2015-11-28T03:10:15.000Z
|
python/src/problem045.py
|
arturh85/projecteuler
|
c3685e302ea7c323193b18c105a7e02da01fd6b5
|
[
"MIT"
] | null | null | null |
python/src/problem045.py
|
arturh85/projecteuler
|
c3685e302ea7c323193b18c105a7e02da01fd6b5
|
[
"MIT"
] | null | null | null |
# coding=utf-8
'''
Problem 45
06 June 2003
Triangle, pentagonal, and hexagonal numbers are generated by the following formulae:
Triangle Tn=n(n+1)/2 1, 3, 6, 10, 15, ...
Pentagonal Pn=n(3n−1)/2 1, 5, 12, 22, 35, ...
Hexagonal Hn=n(2n−1) 1, 6, 15, 28, 45, ...
It can be verified that T285 = P165 = H143 = 40755.
Find the next triangle number that is also pentagonal and hexagonal.
----------------------------------------------------------
Created on 30.01.2015
@author: ahallmann
'''
import unittest
import timeit
import math
from problem042 import is_triangle_number
from problem042 import generate_triangle_numbers
from problem042 import generate_numbers
from problem042 import is_number
from problem044 import is_pentagonal_number
def hexagonal_number_at(n):
return n * (2 * n - 1)
def generate_hexagonal_number():
return generate_numbers(hexagonal_number_at)
# def is_hexagonal_number(n):
# return is_number(hexagonal_number_at, 'hexagonal', n)
def is_hexagonal_number(n):
h = (math.sqrt(8*n+1)+1.0)/4.0
return math.floor(h) == h
def solve():
# all hexagonal numbers are also triangle numbers
for hexagonal_number in generate_hexagonal_number():
if hexagonal_number > 40755 and is_pentagonal_number(hexagonal_number):
return hexagonal_number
class Test(unittest.TestCase):
def test_sample(self):
self.assertTrue(is_pentagonal_number(40755))
self.assertTrue(is_triangle_number(40755))
self.assertTrue(is_hexagonal_number(40755))
pass
def test_answer(self):
self.assertEqual(1533776805, solve())
pass
# -----------------------------------------
def run():
return solve()
if __name__ == '__main__':
run()
unittest.main()
# if __name__ == '__main__':
# t = timeit.Timer("run()", "from __main__ import run")
# count = 1
# print(str(t.timeit(count)) + " seconds for " + str(count) + " runs")
| 25.658228
| 85
| 0.634928
| 265
| 2,027
| 4.645283
| 0.373585
| 0.146223
| 0.064988
| 0.035743
| 0.077985
| 0
| 0
| 0
| 0
| 0
| 0
| 0.072601
| 0.21855
| 2,027
| 78
| 86
| 25.987179
| 0.703283
| 0.444006
| 0
| 0.060606
| 1
| 0
| 0.007279
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 1
| 0.212121
| false
| 0.060606
| 0.242424
| 0.090909
| 0.636364
| 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
|
2d58beaf6c07d8e7e5208960da29e120a3d0d244
| 73
|
py
|
Python
|
widgets/__init__.py
|
stylekilla/syncmrtBackend
|
634024b9458400d69e24879e2de54161d75b89a8
|
[
"Apache-2.0"
] | null | null | null |
widgets/__init__.py
|
stylekilla/syncmrtBackend
|
634024b9458400d69e24879e2de54161d75b89a8
|
[
"Apache-2.0"
] | null | null | null |
widgets/__init__.py
|
stylekilla/syncmrtBackend
|
634024b9458400d69e24879e2de54161d75b89a8
|
[
"Apache-2.0"
] | null | null | null |
from .mpl2DFigure import mpl2DFigure
from .mpl3DFigure import mpl3DFigure
| 36.5
| 36
| 0.876712
| 8
| 73
| 8
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.060606
| 0.09589
| 73
| 2
| 37
| 36.5
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
2d62a3a56a154f45eb009828bfce6d996b762d73
| 225
|
py
|
Python
|
tests/test_debug.py
|
khadas/android_external_python_pyopenssl
|
751caf63d05da8477d934da5c05316ddeb4f64de
|
[
"Apache-2.0"
] | 5,079
|
2015-01-01T03:39:46.000Z
|
2022-03-31T07:38:22.000Z
|
tests/test_debug.py
|
khadas/android_external_python_pyopenssl
|
751caf63d05da8477d934da5c05316ddeb4f64de
|
[
"Apache-2.0"
] | 1,623
|
2015-01-01T08:06:24.000Z
|
2022-03-30T19:48:52.000Z
|
tests/test_debug.py
|
khadas/android_external_python_pyopenssl
|
751caf63d05da8477d934da5c05316ddeb4f64de
|
[
"Apache-2.0"
] | 2,033
|
2015-01-04T07:18:02.000Z
|
2022-03-28T19:55:47.000Z
|
from OpenSSL.debug import _env_info
from OpenSSL import version
def test_debug_info():
"""
Debug info contains correct data.
"""
# Just check a sample we control.
assert version.__version__ in _env_info
| 20.454545
| 43
| 0.715556
| 31
| 225
| 4.870968
| 0.645161
| 0.145695
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 225
| 10
| 44
| 22.5
| 0.862857
| 0.293333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0.25
| true
| 0
| 0.5
| 0
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
2d6a11750ae563176f51740a3ce0eccbf3681c97
| 241
|
py
|
Python
|
teknologr/registration/urls.py
|
christiansegercrantz/teknologr.io
|
0356b4a09218354829a00205e58e5b7ceb2a3d59
|
[
"MIT"
] | null | null | null |
teknologr/registration/urls.py
|
christiansegercrantz/teknologr.io
|
0356b4a09218354829a00205e58e5b7ceb2a3d59
|
[
"MIT"
] | null | null | null |
teknologr/registration/urls.py
|
christiansegercrantz/teknologr.io
|
0356b4a09218354829a00205e58e5b7ceb2a3d59
|
[
"MIT"
] | null | null | null |
from django.conf.urls import url, include
from registration.views import *
urlpatterns = [
url(r'^$', HomeView.as_view(), name='registration.views.home'),
url(r'^submit/$', SubmitView.as_view(), name='registration.views.submit'),
]
| 30.125
| 78
| 0.705394
| 31
| 241
| 5.419355
| 0.580645
| 0.303571
| 0.119048
| 0.261905
| 0.321429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116183
| 241
| 7
| 79
| 34.428571
| 0.788732
| 0
| 0
| 0
| 0
| 0
| 0.244813
| 0.19917
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 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
|
2d77f8f2dcfb2a647b9591d823b2a9038b47c038
| 96
|
py
|
Python
|
Problemler11/Problemler2.py
|
mebon/PythonDenemeleri
|
cd4a6ee0c7f07a032dd8c0bd175193f0751ceca8
|
[
"Apache-2.0"
] | null | null | null |
Problemler11/Problemler2.py
|
mebon/PythonDenemeleri
|
cd4a6ee0c7f07a032dd8c0bd175193f0751ceca8
|
[
"Apache-2.0"
] | 30
|
2019-07-24T17:50:53.000Z
|
2020-04-30T18:02:01.000Z
|
Problemler11/Problemler2.py
|
mebon/PythonDenemeleri
|
cd4a6ee0c7f07a032dd8c0bd175193f0751ceca8
|
[
"Apache-2.0"
] | 1
|
2020-08-07T09:57:25.000Z
|
2020-08-07T09:57:25.000Z
|
"""Süpermarket içindeki ürünler üzerinden bir tane Süpermarket Projesi geliştirmeye çalışın.
"""
| 48
| 92
| 0.822917
| 10
| 96
| 7.9
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104167
| 96
| 2
| 93
| 48
| 0.918605
| 0.927083
| 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
|
2d8f971ca8ac0866fa158cf82423901d58364d2d
| 1,621
|
py
|
Python
|
src/resdk/resources/__init__.py
|
AGregorc/resolwe-bio-py
|
62304e5d4c54c917575421701c6977dc63fc3a8f
|
[
"Apache-2.0"
] | null | null | null |
src/resdk/resources/__init__.py
|
AGregorc/resolwe-bio-py
|
62304e5d4c54c917575421701c6977dc63fc3a8f
|
[
"Apache-2.0"
] | null | null | null |
src/resdk/resources/__init__.py
|
AGregorc/resolwe-bio-py
|
62304e5d4c54c917575421701c6977dc63fc3a8f
|
[
"Apache-2.0"
] | null | null | null |
""".. Ignore pydocstyle D400.
=========
Resources
=========
Resource classes
================
.. autoclass:: resdk.resources.base.BaseResource
:members:
.. autoclass:: resdk.resources.base.BaseResolweResource
:members:
.. autoclass:: resdk.resources.Data
:members:
.. autoclass:: resdk.resources.collection.BaseCollection
:members:
.. autoclass:: resdk.resources.Collection
:members:
.. autoclass:: resdk.resources.Sample
:members:
.. autoclass:: resdk.resources.Relation
:members:
.. autoclass:: resdk.resources.Process
:members:
.. autoclass:: resdk.resources.DescriptorSchema
:members:
.. autoclass:: resdk.resources.User
:members:
.. autoclass:: resdk.resources.Group
:members:
.. automodule:: resdk.resources.kb
Permissions
===========
Resources like :class:`resdk.resources.Data`,
:class:`resdk.resources.Collection`, :class:`resdk.resources.Sample`, and
:class:`resdk.resources.Process` include a `permissions` attribute to manage
permissions. The `permissions` attribute is an instance of
`resdk.resources.permissions.PermissionsManager`.
.. autoclass:: resdk.resources.permissions.PermissionsManager
:members:
Utility functions
=================
.. automodule:: resdk.resources.utils
:members:
"""
from .collection import Collection
from .data import Data
from .descriptor import DescriptorSchema
from .process import Process
from .relation import Relation
from .sample import Sample
from .user import Group, User
__all__ = (
"Collection",
"Data",
"DescriptorSchema",
"Group",
"Sample",
"Process",
"Relation",
"User",
)
| 19.768293
| 76
| 0.701419
| 157
| 1,621
| 7.216561
| 0.286624
| 0.234775
| 0.243601
| 0.264784
| 0.070609
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002151
| 0.13942
| 1,621
| 81
| 77
| 20.012346
| 0.810036
| 0.775447
| 0
| 0
| 0
| 0
| 0.168539
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.411765
| 0
| 0.411765
| 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
|
2d9333ff205d96134de6a751180b4aee579a24f6
| 86
|
py
|
Python
|
Python code/demo.py
|
jlwgong/hangman
|
ebf48d5f2e16d728374ae30240915c01e43bb532
|
[
"MIT"
] | null | null | null |
Python code/demo.py
|
jlwgong/hangman
|
ebf48d5f2e16d728374ae30240915c01e43bb532
|
[
"MIT"
] | null | null | null |
Python code/demo.py
|
jlwgong/hangman
|
ebf48d5f2e16d728374ae30240915c01e43bb532
|
[
"MIT"
] | null | null | null |
x = input("Enter: ")
while x != "stop":
print("try again!")
x = input("Enter")
| 21.5
| 23
| 0.523256
| 12
| 86
| 3.75
| 0.666667
| 0.266667
| 0.488889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.232558
| 86
| 4
| 24
| 21.5
| 0.681818
| 0
| 0
| 0
| 0
| 0
| 0.298851
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 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
|
2dc3bb43f432c1338927318b9dc6d0ae306b6a2b
| 321
|
py
|
Python
|
potions/validators.py
|
NievesBorrero/potionlab
|
2ce4c97906bd6d8ea84e1d6e2a5afdad68182bd2
|
[
"MIT"
] | 11
|
2020-01-28T10:46:13.000Z
|
2020-02-10T20:20:08.000Z
|
potions/validators.py
|
NievesBorrero/potionlab
|
2ce4c97906bd6d8ea84e1d6e2a5afdad68182bd2
|
[
"MIT"
] | null | null | null |
potions/validators.py
|
NievesBorrero/potionlab
|
2ce4c97906bd6d8ea84e1d6e2a5afdad68182bd2
|
[
"MIT"
] | null | null | null |
class BaseValidator:
REQUIRED_KEYS = []
def validate(self, data):
return all(
key in data.keys()
for key in self.REQUIRED_KEYS)
class UserValidator(BaseValidator):
REQUIRED_KEYS = ('username', 'password')
class PotionValidator(BaseValidator):
REQUIRED_KEYS = ('name')
| 20.0625
| 44
| 0.64486
| 33
| 321
| 6.151515
| 0.545455
| 0.236453
| 0.369458
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.252336
| 321
| 15
| 45
| 21.4
| 0.845833
| 0
| 0
| 0
| 0
| 0
| 0.062305
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.1
| false
| 0.1
| 0
| 0.1
| 0.8
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
2ddfc6b5b88fef80e3767b8c7194f2f8ba6d1b70
| 53
|
py
|
Python
|
tests/__init__.py
|
edson/lead_recommender_system
|
7a11737e4c448a394604119e59e3ee8daabdc90e
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
edson/lead_recommender_system
|
7a11737e4c448a394604119e59e3ee8daabdc90e
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
edson/lead_recommender_system
|
7a11737e4c448a394604119e59e3ee8daabdc90e
|
[
"MIT"
] | null | null | null |
"""Unit test package for lead_recommender_system."""
| 26.5
| 52
| 0.773585
| 7
| 53
| 5.571429
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09434
| 53
| 1
| 53
| 53
| 0.8125
| 0.867925
| 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
|
2de3a62dec59d3d8aea25ca07bb3d9d292a284a4
| 99
|
py
|
Python
|
Exercise_8_17.py
|
kushrami/Python-Crash-Course-book-Excersice
|
7093181940a90d9f4bab5775ef56f57963450393
|
[
"Apache-2.0"
] | null | null | null |
Exercise_8_17.py
|
kushrami/Python-Crash-Course-book-Excersice
|
7093181940a90d9f4bab5775ef56f57963450393
|
[
"Apache-2.0"
] | null | null | null |
Exercise_8_17.py
|
kushrami/Python-Crash-Course-book-Excersice
|
7093181940a90d9f4bab5775ef56f57963450393
|
[
"Apache-2.0"
] | null | null | null |
#Styling Functions:
#mostly i follow this guidelines. But Its ok to have some my test in my repos.
| 33
| 78
| 0.767677
| 18
| 99
| 4.222222
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 99
| 3
| 78
| 33
| 0.938272
| 0.959596
| 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
|
2de8a45cd2f881e013cd320a276463202a1d82f7
| 56
|
py
|
Python
|
tensortrade/features/stationarity/__init__.py
|
andrewczgithub/tensortrade
|
b5f5d14c220bcab3394b02286ffd0f52853f519e
|
[
"Apache-2.0"
] | 6
|
2019-10-18T17:36:29.000Z
|
2021-11-24T03:06:42.000Z
|
tensortrade/features/stationarity/__init__.py
|
mwbrulhardt/tensortrade
|
8a83bddb0243b8c91e637737c23d6b43652182a2
|
[
"Apache-2.0"
] | 1
|
2019-12-14T23:25:00.000Z
|
2019-12-14T23:25:00.000Z
|
tensortrade/features/stationarity/__init__.py
|
mwbrulhardt/tensortrade
|
8a83bddb0243b8c91e637737c23d6b43652182a2
|
[
"Apache-2.0"
] | 3
|
2019-12-24T21:40:22.000Z
|
2020-07-27T00:05:44.000Z
|
from .fractional_difference import FractionalDifference
| 28
| 55
| 0.910714
| 5
| 56
| 10
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 56
| 1
| 56
| 56
| 0.961538
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
930e0fad0bbb8a1c732355ffa9da99997239c74c
| 187
|
py
|
Python
|
tests/test_app_label/salesforce/apps.py
|
bryancolligan/django-salesforce
|
cec08115f97d75d9b7b96bb34c40e48974c7269f
|
[
"MIT"
] | 251
|
2015-01-15T11:39:21.000Z
|
2022-03-28T10:52:10.000Z
|
tests/test_app_label/salesforce/apps.py
|
bryancolligan/django-salesforce
|
cec08115f97d75d9b7b96bb34c40e48974c7269f
|
[
"MIT"
] | 196
|
2015-01-09T01:29:37.000Z
|
2022-03-19T19:35:09.000Z
|
tests/test_app_label/salesforce/apps.py
|
bryancolligan/django-salesforce
|
cec08115f97d75d9b7b96bb34c40e48974c7269f
|
[
"MIT"
] | 68
|
2015-01-12T18:13:13.000Z
|
2022-03-23T11:16:14.000Z
|
from django.apps import AppConfig
class TestSalesForceConfig(AppConfig):
name = "tests.test_app_label.salesforce"
label = "test_salesforce"
verbose_name = "Test SalesForce"
| 23.375
| 44
| 0.759358
| 21
| 187
| 6.571429
| 0.666667
| 0.202899
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.160428
| 187
| 7
| 45
| 26.714286
| 0.878981
| 0
| 0
| 0
| 0
| 0
| 0.326203
| 0.165775
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
93108dbdb29ca9711e7c531b3ec8dfc6e09c21d4
| 75
|
py
|
Python
|
FPLTransfers/__init__.py
|
JackLidge/FPLTransfers
|
d458770b658a5dedfe7379871afc424949427cb5
|
[
"MIT"
] | null | null | null |
FPLTransfers/__init__.py
|
JackLidge/FPLTransfers
|
d458770b658a5dedfe7379871afc424949427cb5
|
[
"MIT"
] | 1
|
2022-02-25T15:33:05.000Z
|
2022-02-25T15:33:05.000Z
|
FPLTransfers/__init__.py
|
JackLidge/FPLTransfers
|
d458770b658a5dedfe7379871afc424949427cb5
|
[
"MIT"
] | null | null | null |
from .FPLTransfers import FPLTransfers
#__all__ = (
# "FPLTransfers"
#)
| 15
| 38
| 0.706667
| 6
| 75
| 8.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173333
| 75
| 5
| 39
| 15
| 0.790323
| 0.4
| 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
|
934b09b8c5db4d1f28c48a2d8efcb77772bc2dc6
| 44
|
py
|
Python
|
construct_editor/version.py
|
jpsnyder/construct-editor
|
9ad73aa89430a35f3b5bc71f965feb2e9cbb0568
|
[
"MIT"
] | null | null | null |
construct_editor/version.py
|
jpsnyder/construct-editor
|
9ad73aa89430a35f3b5bc71f965feb2e9cbb0568
|
[
"MIT"
] | null | null | null |
construct_editor/version.py
|
jpsnyder/construct-editor
|
9ad73aa89430a35f3b5bc71f965feb2e9cbb0568
|
[
"MIT"
] | null | null | null |
version = (0, 0, 3)
version_string = "0.0.3"
| 22
| 24
| 0.613636
| 9
| 44
| 2.888889
| 0.444444
| 0.153846
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.162162
| 0.159091
| 44
| 2
| 24
| 22
| 0.540541
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
935b2ee70d864166c1f015d127ee85059e7db412
| 17
|
py
|
Python
|
py3status/version.py
|
rafaelleru/py3status
|
a3cb9c16f8e2f26de99ba715419636aea825c263
|
[
"BSD-3-Clause"
] | null | null | null |
py3status/version.py
|
rafaelleru/py3status
|
a3cb9c16f8e2f26de99ba715419636aea825c263
|
[
"BSD-3-Clause"
] | null | null | null |
py3status/version.py
|
rafaelleru/py3status
|
a3cb9c16f8e2f26de99ba715419636aea825c263
|
[
"BSD-3-Clause"
] | null | null | null |
version = "3.16"
| 8.5
| 16
| 0.588235
| 3
| 17
| 3.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 0.176471
| 17
| 1
| 17
| 17
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
936003139491b36835e54980b21c4651fa60a6fe
| 85
|
py
|
Python
|
tests/pass/errors.py
|
capeprivacy/tensorflow-stubs
|
66367b4bcb12e8f3e1cf47e030d23c55649c00d4
|
[
"MIT"
] | 15
|
2018-07-30T12:31:18.000Z
|
2022-02-10T11:18:31.000Z
|
tests/pass/errors.py
|
capeprivacy/tensorflow-stubs
|
66367b4bcb12e8f3e1cf47e030d23c55649c00d4
|
[
"MIT"
] | 12
|
2018-06-14T14:02:19.000Z
|
2018-10-02T16:53:45.000Z
|
tests/pass/errors.py
|
capeprivacy/tensorflow-stubs
|
66367b4bcb12e8f3e1cf47e030d23c55649c00d4
|
[
"MIT"
] | 8
|
2018-08-02T13:24:46.000Z
|
2021-04-25T12:29:42.000Z
|
import tensorflow as tf
tf.errors.OpError(None, None, 'a message', 'an error code')
| 21.25
| 59
| 0.729412
| 14
| 85
| 4.428571
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141176
| 85
| 3
| 60
| 28.333333
| 0.849315
| 0
| 0
| 0
| 0
| 0
| 0.258824
| 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
|
9372168d8e69692f00512eba453878b7526d64e6
| 461
|
py
|
Python
|
Lib/fontTools/ttLib/tables/_a_n_k_r.py
|
anntzer/fonttools
|
726cd67549956b985bbbe83e26fb0af9da59ddf7
|
[
"MIT",
"BSD-3-Clause"
] | 2
|
2021-04-07T16:47:04.000Z
|
2022-01-15T04:01:01.000Z
|
Lib/fontTools/ttLib/tables/_a_n_k_r.py
|
anntzer/fonttools
|
726cd67549956b985bbbe83e26fb0af9da59ddf7
|
[
"MIT",
"BSD-3-Clause"
] | 74
|
2020-01-30T07:27:54.000Z
|
2021-08-03T05:47:17.000Z
|
Lib/fontTools/ttLib/tables/_a_n_k_r.py
|
anntzer/fonttools
|
726cd67549956b985bbbe83e26fb0af9da59ddf7
|
[
"MIT",
"BSD-3-Clause"
] | 1
|
2020-01-22T20:06:09.000Z
|
2020-01-22T20:06:09.000Z
|
from fontTools.misc.py23 import *
from .otBase import BaseTTXConverter
# The anchor point table provides a way to define anchor points.
# These are points within the coordinate space of a given glyph,
# independent of the control points used to render the glyph.
# Anchor points are used in conjunction with the 'kerx' table.
#
# https://developer.apple.com/fonts/TrueType-Reference-Manual/RM06/Chap6ankr.html
class table__a_n_k_r(BaseTTXConverter):
pass
| 35.461538
| 81
| 0.789588
| 70
| 461
| 5.128571
| 0.7
| 0.066852
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012658
| 0.143167
| 461
| 12
| 82
| 38.416667
| 0.896203
| 0.707158
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.25
| 0.5
| 0
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
fa739cd4ba51aa1572108482a9e03746441ad6c4
| 934
|
py
|
Python
|
home/serializers.py
|
Reekomer/kpis
|
02d346378da8646122604f6b178c7853bdaf9eed
|
[
"MIT"
] | null | null | null |
home/serializers.py
|
Reekomer/kpis
|
02d346378da8646122604f6b178c7853bdaf9eed
|
[
"MIT"
] | null | null | null |
home/serializers.py
|
Reekomer/kpis
|
02d346378da8646122604f6b178c7853bdaf9eed
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from .models import Stoyo
from .models import Publisher
from .models import Temporary
class StoyoSerializer(serializers.ModelSerializer):
class Meta:
model = Stoyo
class PublisherSerializer(serializers.ModelSerializer):
datepub = serializers.DateField(required=False)
update = serializers.DateTimeField(required=False)
page_name = serializers.CharField(required=False)
title = serializers.CharField(required=False)
link = serializers.CharField(required=False)
class Meta:
model = Publisher
class TemporarySerializer(serializers.ModelSerializer):
datepub = serializers.DateField(required=False)
update = serializers.DateTimeField(required=False)
page_name = serializers.CharField(required=False)
title = serializers.CharField(required=False)
link = serializers.CharField(required=False)
class Meta:
model = Temporary
| 34.592593
| 55
| 0.767666
| 93
| 934
| 7.677419
| 0.290323
| 0.182073
| 0.235294
| 0.277311
| 0.669468
| 0.669468
| 0.669468
| 0.669468
| 0.669468
| 0.669468
| 0
| 0
| 0.156317
| 934
| 26
| 56
| 35.923077
| 0.906091
| 0
| 0
| 0.565217
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.173913
| 0
| 0.869565
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
fa753da9f80f1bdec56ee54d35977ecb8d989586
| 204
|
py
|
Python
|
make_us_rich/interface/__init__.py
|
ChainYo/make-me-rich
|
ad3bbc23bef4840f80799e0fd4903767d9a57a72
|
[
"Apache-2.0"
] | 11
|
2022-02-06T18:01:29.000Z
|
2022-02-23T15:51:48.000Z
|
make_us_rich/interface/__init__.py
|
ChainYo/make-me-rich
|
ad3bbc23bef4840f80799e0fd4903767d9a57a72
|
[
"Apache-2.0"
] | null | null | null |
make_us_rich/interface/__init__.py
|
ChainYo/make-me-rich
|
ad3bbc23bef4840f80799e0fd4903767d9a57a72
|
[
"Apache-2.0"
] | 1
|
2022-02-14T10:41:53.000Z
|
2022-02-14T10:41:53.000Z
|
from .api_request import ApiRequest
from .authentication import Authentication
from .database_handler import DatabaseHandler
from .plots import (
candlestick_plot,
format_data,
scatter_plot,
)
| 25.5
| 45
| 0.803922
| 23
| 204
| 6.913043
| 0.652174
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.151961
| 204
| 8
| 46
| 25.5
| 0.919075
| 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
|
fa832250b1d86a3ca0f0258c5fc3e52053b0da39
| 104,627
|
py
|
Python
|
sdk/python/pulumi_spotinst/azure/outputs.py
|
pulumi/pulumi-spotinst
|
75592d6293d63f6cec703722f2e02ff1fb1cca44
|
[
"ECL-2.0",
"Apache-2.0"
] | 4
|
2019-12-21T20:50:43.000Z
|
2021-12-01T20:57:38.000Z
|
sdk/python/pulumi_spotinst/azure/outputs.py
|
pulumi/pulumi-spotinst
|
75592d6293d63f6cec703722f2e02ff1fb1cca44
|
[
"ECL-2.0",
"Apache-2.0"
] | 103
|
2019-12-09T22:03:16.000Z
|
2022-03-30T17:07:34.000Z
|
sdk/python/pulumi_spotinst/azure/outputs.py
|
pulumi/pulumi-spotinst
|
75592d6293d63f6cec703722f2e02ff1fb1cca44
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
__all__ = [
'ElastigroupHealthCheck',
'ElastigroupImage',
'ElastigroupImageCustom',
'ElastigroupImageMarketplace',
'ElastigroupIntegrationKubernetes',
'ElastigroupIntegrationMultaiRuntime',
'ElastigroupLoadBalancer',
'ElastigroupLogin',
'ElastigroupManagedServiceIdentity',
'ElastigroupNetwork',
'ElastigroupNetworkAdditionalIpConfig',
'ElastigroupScalingDownPolicy',
'ElastigroupScalingDownPolicyDimension',
'ElastigroupScalingUpPolicy',
'ElastigroupScalingUpPolicyDimension',
'ElastigroupScheduledTask',
'ElastigroupStrategy',
'ElastigroupUpdatePolicy',
'ElastigroupUpdatePolicyRollConfig',
'OceanAutoscaler',
'OceanAutoscalerAutoscaleDown',
'OceanAutoscalerAutoscaleHeadroom',
'OceanAutoscalerAutoscaleHeadroomAutomatic',
'OceanAutoscalerResourceLimits',
'OceanExtension',
'OceanHealth',
'OceanImage',
'OceanImageMarketplace',
'OceanLoadBalancer',
'OceanManagedServiceIdentity',
'OceanNetwork',
'OceanNetworkNetworkInterface',
'OceanNetworkNetworkInterfaceAdditionalIpConfig',
'OceanNetworkNetworkInterfaceSecurityGroup',
'OceanOsDisk',
'OceanStrategy',
'OceanTag',
'OceanVirtualNodeGroupAutoscale',
'OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom',
'OceanVirtualNodeGroupLabel',
'OceanVirtualNodeGroupLaunchSpecification',
'OceanVirtualNodeGroupLaunchSpecificationOsDisk',
'OceanVirtualNodeGroupLaunchSpecificationTag',
'OceanVirtualNodeGroupResourceLimit',
'OceanVirtualNodeGroupTaint',
'OceanVmSize',
]
@pulumi.output_type
class ElastigroupHealthCheck(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "healthCheckType":
suggest = "health_check_type"
elif key == "autoHealing":
suggest = "auto_healing"
elif key == "gracePeriod":
suggest = "grace_period"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupHealthCheck. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupHealthCheck.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupHealthCheck.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
health_check_type: str,
auto_healing: Optional[bool] = None,
grace_period: Optional[int] = None):
"""
:param str health_check_type: Sets the health check type to use. Valid values: `"INSTANCE_STATE"`, `"NONE"`.
:param bool auto_healing: Enable auto-healing of unhealthy VMs.
:param int grace_period: Sets the grace period for new instances to become healthy.
"""
pulumi.set(__self__, "health_check_type", health_check_type)
if auto_healing is not None:
pulumi.set(__self__, "auto_healing", auto_healing)
if grace_period is not None:
pulumi.set(__self__, "grace_period", grace_period)
@property
@pulumi.getter(name="healthCheckType")
def health_check_type(self) -> str:
"""
Sets the health check type to use. Valid values: `"INSTANCE_STATE"`, `"NONE"`.
"""
return pulumi.get(self, "health_check_type")
@property
@pulumi.getter(name="autoHealing")
def auto_healing(self) -> Optional[bool]:
"""
Enable auto-healing of unhealthy VMs.
"""
return pulumi.get(self, "auto_healing")
@property
@pulumi.getter(name="gracePeriod")
def grace_period(self) -> Optional[int]:
"""
Sets the grace period for new instances to become healthy.
"""
return pulumi.get(self, "grace_period")
@pulumi.output_type
class ElastigroupImage(dict):
def __init__(__self__, *,
customs: Optional[Sequence['outputs.ElastigroupImageCustom']] = None,
marketplaces: Optional[Sequence['outputs.ElastigroupImageMarketplace']] = None):
if customs is not None:
pulumi.set(__self__, "customs", customs)
if marketplaces is not None:
pulumi.set(__self__, "marketplaces", marketplaces)
@property
@pulumi.getter
def customs(self) -> Optional[Sequence['outputs.ElastigroupImageCustom']]:
return pulumi.get(self, "customs")
@property
@pulumi.getter
def marketplaces(self) -> Optional[Sequence['outputs.ElastigroupImageMarketplace']]:
return pulumi.get(self, "marketplaces")
@pulumi.output_type
class ElastigroupImageCustom(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "imageName":
suggest = "image_name"
elif key == "resourceGroupName":
suggest = "resource_group_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupImageCustom. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupImageCustom.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupImageCustom.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
image_name: str,
resource_group_name: str):
"""
:param str image_name: Name of the custom image. Required if resource_group_name is specified.
:param str resource_group_name: Vnet Resource Group Name.
"""
pulumi.set(__self__, "image_name", image_name)
pulumi.set(__self__, "resource_group_name", resource_group_name)
@property
@pulumi.getter(name="imageName")
def image_name(self) -> str:
"""
Name of the custom image. Required if resource_group_name is specified.
"""
return pulumi.get(self, "image_name")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> str:
"""
Vnet Resource Group Name.
"""
return pulumi.get(self, "resource_group_name")
@pulumi.output_type
class ElastigroupImageMarketplace(dict):
def __init__(__self__, *,
offer: str,
publisher: str,
sku: str):
"""
:param str offer: Name of the image to use. Required if publisher is specified.
:param str publisher: Image publisher. Required if resource_group_name is not specified.
:param str sku: Image's Stock Keeping Unit, which is the specific version of the image. Required if publisher is specified.
"""
pulumi.set(__self__, "offer", offer)
pulumi.set(__self__, "publisher", publisher)
pulumi.set(__self__, "sku", sku)
@property
@pulumi.getter
def offer(self) -> str:
"""
Name of the image to use. Required if publisher is specified.
"""
return pulumi.get(self, "offer")
@property
@pulumi.getter
def publisher(self) -> str:
"""
Image publisher. Required if resource_group_name is not specified.
"""
return pulumi.get(self, "publisher")
@property
@pulumi.getter
def sku(self) -> str:
"""
Image's Stock Keeping Unit, which is the specific version of the image. Required if publisher is specified.
"""
return pulumi.get(self, "sku")
@pulumi.output_type
class ElastigroupIntegrationKubernetes(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "clusterIdentifier":
suggest = "cluster_identifier"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupIntegrationKubernetes. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupIntegrationKubernetes.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupIntegrationKubernetes.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
cluster_identifier: str):
"""
:param str cluster_identifier: The cluster ID.
"""
pulumi.set(__self__, "cluster_identifier", cluster_identifier)
@property
@pulumi.getter(name="clusterIdentifier")
def cluster_identifier(self) -> str:
"""
The cluster ID.
"""
return pulumi.get(self, "cluster_identifier")
@pulumi.output_type
class ElastigroupIntegrationMultaiRuntime(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "deploymentId":
suggest = "deployment_id"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupIntegrationMultaiRuntime. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupIntegrationMultaiRuntime.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupIntegrationMultaiRuntime.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
deployment_id: str):
"""
:param str deployment_id: The deployment id you want to get
"""
pulumi.set(__self__, "deployment_id", deployment_id)
@property
@pulumi.getter(name="deploymentId")
def deployment_id(self) -> str:
"""
The deployment id you want to get
"""
return pulumi.get(self, "deployment_id")
@pulumi.output_type
class ElastigroupLoadBalancer(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "autoWeight":
suggest = "auto_weight"
elif key == "balancerId":
suggest = "balancer_id"
elif key == "targetSetId":
suggest = "target_set_id"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupLoadBalancer. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupLoadBalancer.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupLoadBalancer.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
type: str,
auto_weight: Optional[bool] = None,
balancer_id: Optional[str] = None,
target_set_id: Optional[str] = None):
"""
:param str type: The resource type. Valid values: CLASSIC, TARGET_GROUP, MULTAI_TARGET_SET.
:param str balancer_id: The balancer ID.
:param str target_set_id: The scale set ID associated with the load balancer.
"""
pulumi.set(__self__, "type", type)
if auto_weight is not None:
pulumi.set(__self__, "auto_weight", auto_weight)
if balancer_id is not None:
pulumi.set(__self__, "balancer_id", balancer_id)
if target_set_id is not None:
pulumi.set(__self__, "target_set_id", target_set_id)
@property
@pulumi.getter
def type(self) -> str:
"""
The resource type. Valid values: CLASSIC, TARGET_GROUP, MULTAI_TARGET_SET.
"""
return pulumi.get(self, "type")
@property
@pulumi.getter(name="autoWeight")
def auto_weight(self) -> Optional[bool]:
return pulumi.get(self, "auto_weight")
@property
@pulumi.getter(name="balancerId")
def balancer_id(self) -> Optional[str]:
"""
The balancer ID.
"""
return pulumi.get(self, "balancer_id")
@property
@pulumi.getter(name="targetSetId")
def target_set_id(self) -> Optional[str]:
"""
The scale set ID associated with the load balancer.
"""
return pulumi.get(self, "target_set_id")
@pulumi.output_type
class ElastigroupLogin(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "userName":
suggest = "user_name"
elif key == "sshPublicKey":
suggest = "ssh_public_key"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupLogin. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupLogin.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupLogin.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
user_name: str,
password: Optional[str] = None,
ssh_public_key: Optional[str] = None):
"""
:param str user_name: Set admin access for accessing your VMs.
:param str password: Password for admin access to Windows VMs. Required for Windows product types.
:param str ssh_public_key: SSH for admin access to Linux VMs. Required for Linux product types.
"""
pulumi.set(__self__, "user_name", user_name)
if password is not None:
pulumi.set(__self__, "password", password)
if ssh_public_key is not None:
pulumi.set(__self__, "ssh_public_key", ssh_public_key)
@property
@pulumi.getter(name="userName")
def user_name(self) -> str:
"""
Set admin access for accessing your VMs.
"""
return pulumi.get(self, "user_name")
@property
@pulumi.getter
def password(self) -> Optional[str]:
"""
Password for admin access to Windows VMs. Required for Windows product types.
"""
return pulumi.get(self, "password")
@property
@pulumi.getter(name="sshPublicKey")
def ssh_public_key(self) -> Optional[str]:
"""
SSH for admin access to Linux VMs. Required for Linux product types.
"""
return pulumi.get(self, "ssh_public_key")
@pulumi.output_type
class ElastigroupManagedServiceIdentity(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "resourceGroupName":
suggest = "resource_group_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupManagedServiceIdentity. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupManagedServiceIdentity.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupManagedServiceIdentity.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
name: str,
resource_group_name: str):
"""
:param str name: The dimension name.
:param str resource_group_name: Vnet Resource Group Name.
"""
pulumi.set(__self__, "name", name)
pulumi.set(__self__, "resource_group_name", resource_group_name)
@property
@pulumi.getter
def name(self) -> str:
"""
The dimension name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> str:
"""
Vnet Resource Group Name.
"""
return pulumi.get(self, "resource_group_name")
@pulumi.output_type
class ElastigroupNetwork(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "resourceGroupName":
suggest = "resource_group_name"
elif key == "subnetName":
suggest = "subnet_name"
elif key == "virtualNetworkName":
suggest = "virtual_network_name"
elif key == "additionalIpConfigs":
suggest = "additional_ip_configs"
elif key == "assignPublicIp":
suggest = "assign_public_ip"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupNetwork. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupNetwork.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupNetwork.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
resource_group_name: str,
subnet_name: str,
virtual_network_name: str,
additional_ip_configs: Optional[Sequence['outputs.ElastigroupNetworkAdditionalIpConfig']] = None,
assign_public_ip: Optional[bool] = None):
"""
:param str resource_group_name: Vnet Resource Group Name.
:param str subnet_name: ID of subnet.
:param str virtual_network_name: Name of Vnet.
:param Sequence['ElastigroupNetworkAdditionalIpConfigArgs'] additional_ip_configs: Array of additional IP configuration objects.
"""
pulumi.set(__self__, "resource_group_name", resource_group_name)
pulumi.set(__self__, "subnet_name", subnet_name)
pulumi.set(__self__, "virtual_network_name", virtual_network_name)
if additional_ip_configs is not None:
pulumi.set(__self__, "additional_ip_configs", additional_ip_configs)
if assign_public_ip is not None:
pulumi.set(__self__, "assign_public_ip", assign_public_ip)
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> str:
"""
Vnet Resource Group Name.
"""
return pulumi.get(self, "resource_group_name")
@property
@pulumi.getter(name="subnetName")
def subnet_name(self) -> str:
"""
ID of subnet.
"""
return pulumi.get(self, "subnet_name")
@property
@pulumi.getter(name="virtualNetworkName")
def virtual_network_name(self) -> str:
"""
Name of Vnet.
"""
return pulumi.get(self, "virtual_network_name")
@property
@pulumi.getter(name="additionalIpConfigs")
def additional_ip_configs(self) -> Optional[Sequence['outputs.ElastigroupNetworkAdditionalIpConfig']]:
"""
Array of additional IP configuration objects.
"""
return pulumi.get(self, "additional_ip_configs")
@property
@pulumi.getter(name="assignPublicIp")
def assign_public_ip(self) -> Optional[bool]:
return pulumi.get(self, "assign_public_ip")
@pulumi.output_type
class ElastigroupNetworkAdditionalIpConfig(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "privateIpVersion":
suggest = "private_ip_version"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupNetworkAdditionalIpConfig. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupNetworkAdditionalIpConfig.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupNetworkAdditionalIpConfig.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
name: str,
private_ip_version: Optional[str] = None):
"""
:param str name: The dimension name.
:param str private_ip_version: Available from Azure Api-Version 2017-03-30 onwards, it represents whether the specific ipconfiguration is IPv4 or IPv6. Valid values: `IPv4`, `IPv6`.
"""
pulumi.set(__self__, "name", name)
if private_ip_version is not None:
pulumi.set(__self__, "private_ip_version", private_ip_version)
@property
@pulumi.getter
def name(self) -> str:
"""
The dimension name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="privateIpVersion")
def private_ip_version(self) -> Optional[str]:
"""
Available from Azure Api-Version 2017-03-30 onwards, it represents whether the specific ipconfiguration is IPv4 or IPv6. Valid values: `IPv4`, `IPv6`.
"""
return pulumi.get(self, "private_ip_version")
@pulumi.output_type
class ElastigroupScalingDownPolicy(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "metricName":
suggest = "metric_name"
elif key == "policyName":
suggest = "policy_name"
elif key == "actionType":
suggest = "action_type"
elif key == "evaluationPeriods":
suggest = "evaluation_periods"
elif key == "maxTargetCapacity":
suggest = "max_target_capacity"
elif key == "minTargetCapacity":
suggest = "min_target_capacity"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupScalingDownPolicy. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupScalingDownPolicy.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupScalingDownPolicy.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
metric_name: str,
namespace: str,
policy_name: str,
threshold: float,
action_type: Optional[str] = None,
adjustment: Optional[str] = None,
cooldown: Optional[int] = None,
dimensions: Optional[Sequence['outputs.ElastigroupScalingDownPolicyDimension']] = None,
evaluation_periods: Optional[int] = None,
max_target_capacity: Optional[str] = None,
maximum: Optional[str] = None,
min_target_capacity: Optional[str] = None,
minimum: Optional[str] = None,
operator: Optional[str] = None,
period: Optional[int] = None,
statistic: Optional[str] = None,
target: Optional[str] = None,
unit: Optional[str] = None):
"""
:param str metric_name: Metric to monitor by Azure metric display name.
:param str namespace: The namespace for the alarm's associated metric. Valid values:
:param str policy_name: The name of the policy.
:param float threshold: The value against which the specified statistic is compared.
:param str action_type: The type of action to perform for scaling. Valid values: `"adjustment"`, `"percentageAdjustment"`, `"setMaxTarget"`, `"setMinTarget"`, `"updateCapacity"`.
:param str adjustment: The number of instances to add/remove to/from the target capacity when scale is needed.
:param int cooldown: The amount of time, in seconds, after a scaling activity completes and before the next scaling activity can start. If this parameter is not specified, the default cooldown period for the group applies.
:param Sequence['ElastigroupScalingDownPolicyDimensionArgs'] dimensions: A list of dimensions describing qualities of the metric. Required when `namespace` is defined AND not `"Microsoft.Compute"`.
:param int evaluation_periods: The number of periods over which data is compared to the specified threshold.
:param str max_target_capacity: . The number of the desired target (and maximum) capacity
:param str maximum: The maximal number of instances to have in the group.
:param str min_target_capacity: . The number of the desired target (and minimum) capacity
:param str minimum: The minimal number of instances to have in the group.
:param str operator: The operator to use in order to determine if the scaling policy is applicable. Valid values: `"gt"`, `"gte"`, `"lt"`, `"lte"`.
:param int period: The granularity, in seconds, of the returned datapoints. Period must be at least 60 seconds and must be a multiple of 60.
:param str statistic: The metric statistics to return. Valid values: `average`.
:param str target: The target number of instances to have in the group.
:param str unit: The unit for the alarm's associated metric. Valid values: `"percent`, `"seconds"`, `"microseconds"`, `"milliseconds"`, `"bytes"`, `"kilobytes"`, `"megabytes"`, `"gigabytes"`, `"terabytes"`, `"bits"`, `"kilobits"`, `"megabits"`, `"gigabits"`, `"terabits"`, `"count"`, `"bytes/second"`, `"kilobytes/second"`, `"megabytes/second"`, `"gigabytes/second"`, `"terabytes/second"`, `"bits/second"`, `"kilobits/second"`, `"megabits/second"`, `"gigabits/second"`, `"terabits/second"`, `"count/second"`, `"none"`.
"""
pulumi.set(__self__, "metric_name", metric_name)
pulumi.set(__self__, "namespace", namespace)
pulumi.set(__self__, "policy_name", policy_name)
pulumi.set(__self__, "threshold", threshold)
if action_type is not None:
pulumi.set(__self__, "action_type", action_type)
if adjustment is not None:
pulumi.set(__self__, "adjustment", adjustment)
if cooldown is not None:
pulumi.set(__self__, "cooldown", cooldown)
if dimensions is not None:
pulumi.set(__self__, "dimensions", dimensions)
if evaluation_periods is not None:
pulumi.set(__self__, "evaluation_periods", evaluation_periods)
if max_target_capacity is not None:
pulumi.set(__self__, "max_target_capacity", max_target_capacity)
if maximum is not None:
pulumi.set(__self__, "maximum", maximum)
if min_target_capacity is not None:
pulumi.set(__self__, "min_target_capacity", min_target_capacity)
if minimum is not None:
pulumi.set(__self__, "minimum", minimum)
if operator is not None:
pulumi.set(__self__, "operator", operator)
if period is not None:
pulumi.set(__self__, "period", period)
if statistic is not None:
pulumi.set(__self__, "statistic", statistic)
if target is not None:
pulumi.set(__self__, "target", target)
if unit is not None:
pulumi.set(__self__, "unit", unit)
@property
@pulumi.getter(name="metricName")
def metric_name(self) -> str:
"""
Metric to monitor by Azure metric display name.
"""
return pulumi.get(self, "metric_name")
@property
@pulumi.getter
def namespace(self) -> str:
"""
The namespace for the alarm's associated metric. Valid values:
"""
return pulumi.get(self, "namespace")
@property
@pulumi.getter(name="policyName")
def policy_name(self) -> str:
"""
The name of the policy.
"""
return pulumi.get(self, "policy_name")
@property
@pulumi.getter
def threshold(self) -> float:
"""
The value against which the specified statistic is compared.
"""
return pulumi.get(self, "threshold")
@property
@pulumi.getter(name="actionType")
def action_type(self) -> Optional[str]:
"""
The type of action to perform for scaling. Valid values: `"adjustment"`, `"percentageAdjustment"`, `"setMaxTarget"`, `"setMinTarget"`, `"updateCapacity"`.
"""
return pulumi.get(self, "action_type")
@property
@pulumi.getter
def adjustment(self) -> Optional[str]:
"""
The number of instances to add/remove to/from the target capacity when scale is needed.
"""
return pulumi.get(self, "adjustment")
@property
@pulumi.getter
def cooldown(self) -> Optional[int]:
"""
The amount of time, in seconds, after a scaling activity completes and before the next scaling activity can start. If this parameter is not specified, the default cooldown period for the group applies.
"""
return pulumi.get(self, "cooldown")
@property
@pulumi.getter
def dimensions(self) -> Optional[Sequence['outputs.ElastigroupScalingDownPolicyDimension']]:
"""
A list of dimensions describing qualities of the metric. Required when `namespace` is defined AND not `"Microsoft.Compute"`.
"""
return pulumi.get(self, "dimensions")
@property
@pulumi.getter(name="evaluationPeriods")
def evaluation_periods(self) -> Optional[int]:
"""
The number of periods over which data is compared to the specified threshold.
"""
return pulumi.get(self, "evaluation_periods")
@property
@pulumi.getter(name="maxTargetCapacity")
def max_target_capacity(self) -> Optional[str]:
"""
. The number of the desired target (and maximum) capacity
"""
return pulumi.get(self, "max_target_capacity")
@property
@pulumi.getter
def maximum(self) -> Optional[str]:
"""
The maximal number of instances to have in the group.
"""
return pulumi.get(self, "maximum")
@property
@pulumi.getter(name="minTargetCapacity")
def min_target_capacity(self) -> Optional[str]:
"""
. The number of the desired target (and minimum) capacity
"""
return pulumi.get(self, "min_target_capacity")
@property
@pulumi.getter
def minimum(self) -> Optional[str]:
"""
The minimal number of instances to have in the group.
"""
return pulumi.get(self, "minimum")
@property
@pulumi.getter
def operator(self) -> Optional[str]:
"""
The operator to use in order to determine if the scaling policy is applicable. Valid values: `"gt"`, `"gte"`, `"lt"`, `"lte"`.
"""
return pulumi.get(self, "operator")
@property
@pulumi.getter
def period(self) -> Optional[int]:
"""
The granularity, in seconds, of the returned datapoints. Period must be at least 60 seconds and must be a multiple of 60.
"""
return pulumi.get(self, "period")
@property
@pulumi.getter
def statistic(self) -> Optional[str]:
"""
The metric statistics to return. Valid values: `average`.
"""
return pulumi.get(self, "statistic")
@property
@pulumi.getter
def target(self) -> Optional[str]:
"""
The target number of instances to have in the group.
"""
return pulumi.get(self, "target")
@property
@pulumi.getter
def unit(self) -> Optional[str]:
"""
The unit for the alarm's associated metric. Valid values: `"percent`, `"seconds"`, `"microseconds"`, `"milliseconds"`, `"bytes"`, `"kilobytes"`, `"megabytes"`, `"gigabytes"`, `"terabytes"`, `"bits"`, `"kilobits"`, `"megabits"`, `"gigabits"`, `"terabits"`, `"count"`, `"bytes/second"`, `"kilobytes/second"`, `"megabytes/second"`, `"gigabytes/second"`, `"terabytes/second"`, `"bits/second"`, `"kilobits/second"`, `"megabits/second"`, `"gigabits/second"`, `"terabits/second"`, `"count/second"`, `"none"`.
"""
return pulumi.get(self, "unit")
@pulumi.output_type
class ElastigroupScalingDownPolicyDimension(dict):
def __init__(__self__, *,
name: str,
value: Optional[str] = None):
"""
:param str name: The dimension name.
:param str value: The dimension value.
"""
pulumi.set(__self__, "name", name)
if value is not None:
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def name(self) -> str:
"""
The dimension name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def value(self) -> Optional[str]:
"""
The dimension value.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class ElastigroupScalingUpPolicy(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "metricName":
suggest = "metric_name"
elif key == "policyName":
suggest = "policy_name"
elif key == "actionType":
suggest = "action_type"
elif key == "evaluationPeriods":
suggest = "evaluation_periods"
elif key == "maxTargetCapacity":
suggest = "max_target_capacity"
elif key == "minTargetCapacity":
suggest = "min_target_capacity"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupScalingUpPolicy. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupScalingUpPolicy.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupScalingUpPolicy.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
metric_name: str,
namespace: str,
policy_name: str,
threshold: float,
action_type: Optional[str] = None,
adjustment: Optional[str] = None,
cooldown: Optional[int] = None,
dimensions: Optional[Sequence['outputs.ElastigroupScalingUpPolicyDimension']] = None,
evaluation_periods: Optional[int] = None,
max_target_capacity: Optional[str] = None,
maximum: Optional[str] = None,
min_target_capacity: Optional[str] = None,
minimum: Optional[str] = None,
operator: Optional[str] = None,
period: Optional[int] = None,
statistic: Optional[str] = None,
target: Optional[str] = None,
unit: Optional[str] = None):
"""
:param str metric_name: Metric to monitor by Azure metric display name.
:param str namespace: The namespace for the alarm's associated metric. Valid values:
:param str policy_name: The name of the policy.
:param float threshold: The value against which the specified statistic is compared.
:param str action_type: The type of action to perform for scaling. Valid values: `"adjustment"`, `"percentageAdjustment"`, `"setMaxTarget"`, `"setMinTarget"`, `"updateCapacity"`.
:param str adjustment: The number of instances to add/remove to/from the target capacity when scale is needed.
:param int cooldown: The amount of time, in seconds, after a scaling activity completes and before the next scaling activity can start. If this parameter is not specified, the default cooldown period for the group applies.
:param Sequence['ElastigroupScalingUpPolicyDimensionArgs'] dimensions: A list of dimensions describing qualities of the metric. Required when `namespace` is defined AND not `"Microsoft.Compute"`.
:param int evaluation_periods: The number of periods over which data is compared to the specified threshold.
:param str max_target_capacity: . The number of the desired target (and maximum) capacity
:param str maximum: The maximal number of instances to have in the group.
:param str min_target_capacity: . The number of the desired target (and minimum) capacity
:param str minimum: The minimal number of instances to have in the group.
:param str operator: The operator to use in order to determine if the scaling policy is applicable. Valid values: `"gt"`, `"gte"`, `"lt"`, `"lte"`.
:param int period: The granularity, in seconds, of the returned datapoints. Period must be at least 60 seconds and must be a multiple of 60.
:param str statistic: The metric statistics to return. Valid values: `average`.
:param str target: The target number of instances to have in the group.
:param str unit: The unit for the alarm's associated metric. Valid values: `"percent`, `"seconds"`, `"microseconds"`, `"milliseconds"`, `"bytes"`, `"kilobytes"`, `"megabytes"`, `"gigabytes"`, `"terabytes"`, `"bits"`, `"kilobits"`, `"megabits"`, `"gigabits"`, `"terabits"`, `"count"`, `"bytes/second"`, `"kilobytes/second"`, `"megabytes/second"`, `"gigabytes/second"`, `"terabytes/second"`, `"bits/second"`, `"kilobits/second"`, `"megabits/second"`, `"gigabits/second"`, `"terabits/second"`, `"count/second"`, `"none"`.
"""
pulumi.set(__self__, "metric_name", metric_name)
pulumi.set(__self__, "namespace", namespace)
pulumi.set(__self__, "policy_name", policy_name)
pulumi.set(__self__, "threshold", threshold)
if action_type is not None:
pulumi.set(__self__, "action_type", action_type)
if adjustment is not None:
pulumi.set(__self__, "adjustment", adjustment)
if cooldown is not None:
pulumi.set(__self__, "cooldown", cooldown)
if dimensions is not None:
pulumi.set(__self__, "dimensions", dimensions)
if evaluation_periods is not None:
pulumi.set(__self__, "evaluation_periods", evaluation_periods)
if max_target_capacity is not None:
pulumi.set(__self__, "max_target_capacity", max_target_capacity)
if maximum is not None:
pulumi.set(__self__, "maximum", maximum)
if min_target_capacity is not None:
pulumi.set(__self__, "min_target_capacity", min_target_capacity)
if minimum is not None:
pulumi.set(__self__, "minimum", minimum)
if operator is not None:
pulumi.set(__self__, "operator", operator)
if period is not None:
pulumi.set(__self__, "period", period)
if statistic is not None:
pulumi.set(__self__, "statistic", statistic)
if target is not None:
pulumi.set(__self__, "target", target)
if unit is not None:
pulumi.set(__self__, "unit", unit)
@property
@pulumi.getter(name="metricName")
def metric_name(self) -> str:
"""
Metric to monitor by Azure metric display name.
"""
return pulumi.get(self, "metric_name")
@property
@pulumi.getter
def namespace(self) -> str:
"""
The namespace for the alarm's associated metric. Valid values:
"""
return pulumi.get(self, "namespace")
@property
@pulumi.getter(name="policyName")
def policy_name(self) -> str:
"""
The name of the policy.
"""
return pulumi.get(self, "policy_name")
@property
@pulumi.getter
def threshold(self) -> float:
"""
The value against which the specified statistic is compared.
"""
return pulumi.get(self, "threshold")
@property
@pulumi.getter(name="actionType")
def action_type(self) -> Optional[str]:
"""
The type of action to perform for scaling. Valid values: `"adjustment"`, `"percentageAdjustment"`, `"setMaxTarget"`, `"setMinTarget"`, `"updateCapacity"`.
"""
return pulumi.get(self, "action_type")
@property
@pulumi.getter
def adjustment(self) -> Optional[str]:
"""
The number of instances to add/remove to/from the target capacity when scale is needed.
"""
return pulumi.get(self, "adjustment")
@property
@pulumi.getter
def cooldown(self) -> Optional[int]:
"""
The amount of time, in seconds, after a scaling activity completes and before the next scaling activity can start. If this parameter is not specified, the default cooldown period for the group applies.
"""
return pulumi.get(self, "cooldown")
@property
@pulumi.getter
def dimensions(self) -> Optional[Sequence['outputs.ElastigroupScalingUpPolicyDimension']]:
"""
A list of dimensions describing qualities of the metric. Required when `namespace` is defined AND not `"Microsoft.Compute"`.
"""
return pulumi.get(self, "dimensions")
@property
@pulumi.getter(name="evaluationPeriods")
def evaluation_periods(self) -> Optional[int]:
"""
The number of periods over which data is compared to the specified threshold.
"""
return pulumi.get(self, "evaluation_periods")
@property
@pulumi.getter(name="maxTargetCapacity")
def max_target_capacity(self) -> Optional[str]:
"""
. The number of the desired target (and maximum) capacity
"""
return pulumi.get(self, "max_target_capacity")
@property
@pulumi.getter
def maximum(self) -> Optional[str]:
"""
The maximal number of instances to have in the group.
"""
return pulumi.get(self, "maximum")
@property
@pulumi.getter(name="minTargetCapacity")
def min_target_capacity(self) -> Optional[str]:
"""
. The number of the desired target (and minimum) capacity
"""
return pulumi.get(self, "min_target_capacity")
@property
@pulumi.getter
def minimum(self) -> Optional[str]:
"""
The minimal number of instances to have in the group.
"""
return pulumi.get(self, "minimum")
@property
@pulumi.getter
def operator(self) -> Optional[str]:
"""
The operator to use in order to determine if the scaling policy is applicable. Valid values: `"gt"`, `"gte"`, `"lt"`, `"lte"`.
"""
return pulumi.get(self, "operator")
@property
@pulumi.getter
def period(self) -> Optional[int]:
"""
The granularity, in seconds, of the returned datapoints. Period must be at least 60 seconds and must be a multiple of 60.
"""
return pulumi.get(self, "period")
@property
@pulumi.getter
def statistic(self) -> Optional[str]:
"""
The metric statistics to return. Valid values: `average`.
"""
return pulumi.get(self, "statistic")
@property
@pulumi.getter
def target(self) -> Optional[str]:
"""
The target number of instances to have in the group.
"""
return pulumi.get(self, "target")
@property
@pulumi.getter
def unit(self) -> Optional[str]:
"""
The unit for the alarm's associated metric. Valid values: `"percent`, `"seconds"`, `"microseconds"`, `"milliseconds"`, `"bytes"`, `"kilobytes"`, `"megabytes"`, `"gigabytes"`, `"terabytes"`, `"bits"`, `"kilobits"`, `"megabits"`, `"gigabits"`, `"terabits"`, `"count"`, `"bytes/second"`, `"kilobytes/second"`, `"megabytes/second"`, `"gigabytes/second"`, `"terabytes/second"`, `"bits/second"`, `"kilobits/second"`, `"megabits/second"`, `"gigabits/second"`, `"terabits/second"`, `"count/second"`, `"none"`.
"""
return pulumi.get(self, "unit")
@pulumi.output_type
class ElastigroupScalingUpPolicyDimension(dict):
def __init__(__self__, *,
name: str,
value: Optional[str] = None):
"""
:param str name: The dimension name.
:param str value: The dimension value.
"""
pulumi.set(__self__, "name", name)
if value is not None:
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def name(self) -> str:
"""
The dimension name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def value(self) -> Optional[str]:
"""
The dimension value.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class ElastigroupScheduledTask(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "cronExpression":
suggest = "cron_expression"
elif key == "taskType":
suggest = "task_type"
elif key == "adjustmentPercentage":
suggest = "adjustment_percentage"
elif key == "batchSizePercentage":
suggest = "batch_size_percentage"
elif key == "gracePeriod":
suggest = "grace_period"
elif key == "isEnabled":
suggest = "is_enabled"
elif key == "scaleMaxCapacity":
suggest = "scale_max_capacity"
elif key == "scaleMinCapacity":
suggest = "scale_min_capacity"
elif key == "scaleTargetCapacity":
suggest = "scale_target_capacity"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupScheduledTask. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupScheduledTask.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupScheduledTask.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
cron_expression: str,
task_type: str,
adjustment: Optional[str] = None,
adjustment_percentage: Optional[str] = None,
batch_size_percentage: Optional[str] = None,
grace_period: Optional[str] = None,
is_enabled: Optional[bool] = None,
scale_max_capacity: Optional[str] = None,
scale_min_capacity: Optional[str] = None,
scale_target_capacity: Optional[str] = None):
"""
:param str cron_expression: A valid cron expression (`* * * * *`). The cron is running in UTC time zone and is in Unix cron format Cron Expression Validator Script.
:param str task_type: The task type to run. Valid Values: `backup_ami`, `scale`, `scaleUp`, `roll`, `statefulUpdateCapacity`, `statefulRecycle`.
:param str adjustment: The number of instances to add/remove to/from the target capacity when scale is needed.
:param str adjustment_percentage: The percent of instances to add/remove to/from the target capacity when scale is needed.
:param str batch_size_percentage: Sets the percentage of the instances to deploy in each batch.
:param str grace_period: Sets the grace period for new instances to become healthy.
:param bool is_enabled: Describes whether the task is enabled. When true the task should run when false it should not run.
:param str scale_max_capacity: The max capacity of the group. Required when ‘task_type' is ‘scale'.
:param str scale_min_capacity: The min capacity of the group. Should be used when choosing ‘task_type' of ‘scale'.
:param str scale_target_capacity: The target capacity of the group. Should be used when choosing ‘task_type' of ‘scale'.
"""
pulumi.set(__self__, "cron_expression", cron_expression)
pulumi.set(__self__, "task_type", task_type)
if adjustment is not None:
pulumi.set(__self__, "adjustment", adjustment)
if adjustment_percentage is not None:
pulumi.set(__self__, "adjustment_percentage", adjustment_percentage)
if batch_size_percentage is not None:
pulumi.set(__self__, "batch_size_percentage", batch_size_percentage)
if grace_period is not None:
pulumi.set(__self__, "grace_period", grace_period)
if is_enabled is not None:
pulumi.set(__self__, "is_enabled", is_enabled)
if scale_max_capacity is not None:
pulumi.set(__self__, "scale_max_capacity", scale_max_capacity)
if scale_min_capacity is not None:
pulumi.set(__self__, "scale_min_capacity", scale_min_capacity)
if scale_target_capacity is not None:
pulumi.set(__self__, "scale_target_capacity", scale_target_capacity)
@property
@pulumi.getter(name="cronExpression")
def cron_expression(self) -> str:
"""
A valid cron expression (`* * * * *`). The cron is running in UTC time zone and is in Unix cron format Cron Expression Validator Script.
"""
return pulumi.get(self, "cron_expression")
@property
@pulumi.getter(name="taskType")
def task_type(self) -> str:
"""
The task type to run. Valid Values: `backup_ami`, `scale`, `scaleUp`, `roll`, `statefulUpdateCapacity`, `statefulRecycle`.
"""
return pulumi.get(self, "task_type")
@property
@pulumi.getter
def adjustment(self) -> Optional[str]:
"""
The number of instances to add/remove to/from the target capacity when scale is needed.
"""
return pulumi.get(self, "adjustment")
@property
@pulumi.getter(name="adjustmentPercentage")
def adjustment_percentage(self) -> Optional[str]:
"""
The percent of instances to add/remove to/from the target capacity when scale is needed.
"""
return pulumi.get(self, "adjustment_percentage")
@property
@pulumi.getter(name="batchSizePercentage")
def batch_size_percentage(self) -> Optional[str]:
"""
Sets the percentage of the instances to deploy in each batch.
"""
return pulumi.get(self, "batch_size_percentage")
@property
@pulumi.getter(name="gracePeriod")
def grace_period(self) -> Optional[str]:
"""
Sets the grace period for new instances to become healthy.
"""
return pulumi.get(self, "grace_period")
@property
@pulumi.getter(name="isEnabled")
def is_enabled(self) -> Optional[bool]:
"""
Describes whether the task is enabled. When true the task should run when false it should not run.
"""
return pulumi.get(self, "is_enabled")
@property
@pulumi.getter(name="scaleMaxCapacity")
def scale_max_capacity(self) -> Optional[str]:
"""
The max capacity of the group. Required when ‘task_type' is ‘scale'.
"""
return pulumi.get(self, "scale_max_capacity")
@property
@pulumi.getter(name="scaleMinCapacity")
def scale_min_capacity(self) -> Optional[str]:
"""
The min capacity of the group. Should be used when choosing ‘task_type' of ‘scale'.
"""
return pulumi.get(self, "scale_min_capacity")
@property
@pulumi.getter(name="scaleTargetCapacity")
def scale_target_capacity(self) -> Optional[str]:
"""
The target capacity of the group. Should be used when choosing ‘task_type' of ‘scale'.
"""
return pulumi.get(self, "scale_target_capacity")
@pulumi.output_type
class ElastigroupStrategy(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "drainingTimeout":
suggest = "draining_timeout"
elif key == "lowPriorityPercentage":
suggest = "low_priority_percentage"
elif key == "odCount":
suggest = "od_count"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupStrategy. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupStrategy.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupStrategy.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
draining_timeout: Optional[int] = None,
low_priority_percentage: Optional[int] = None,
od_count: Optional[int] = None):
"""
:param int draining_timeout: Time (seconds) to allow the instance to be drained from incoming TCP connections and detached from MLB before terminating it during a scale-down operation.
:param int low_priority_percentage: Percentage of Low Priority instances to maintain. Required if `od_count` is not specified.
:param int od_count: Number of On-Demand instances to maintain. Required if low_priority_percentage is not specified.
"""
if draining_timeout is not None:
pulumi.set(__self__, "draining_timeout", draining_timeout)
if low_priority_percentage is not None:
pulumi.set(__self__, "low_priority_percentage", low_priority_percentage)
if od_count is not None:
pulumi.set(__self__, "od_count", od_count)
@property
@pulumi.getter(name="drainingTimeout")
def draining_timeout(self) -> Optional[int]:
"""
Time (seconds) to allow the instance to be drained from incoming TCP connections and detached from MLB before terminating it during a scale-down operation.
"""
return pulumi.get(self, "draining_timeout")
@property
@pulumi.getter(name="lowPriorityPercentage")
def low_priority_percentage(self) -> Optional[int]:
"""
Percentage of Low Priority instances to maintain. Required if `od_count` is not specified.
"""
return pulumi.get(self, "low_priority_percentage")
@property
@pulumi.getter(name="odCount")
def od_count(self) -> Optional[int]:
"""
Number of On-Demand instances to maintain. Required if low_priority_percentage is not specified.
"""
return pulumi.get(self, "od_count")
@pulumi.output_type
class ElastigroupUpdatePolicy(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "shouldRoll":
suggest = "should_roll"
elif key == "rollConfig":
suggest = "roll_config"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupUpdatePolicy. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupUpdatePolicy.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupUpdatePolicy.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
should_roll: bool,
roll_config: Optional['outputs.ElastigroupUpdatePolicyRollConfig'] = None):
"""
:param bool should_roll: Sets the enablement of the roll option.
:param 'ElastigroupUpdatePolicyRollConfigArgs' roll_config: While used, you can control whether the group should perform a deployment after an update to the configuration.
"""
pulumi.set(__self__, "should_roll", should_roll)
if roll_config is not None:
pulumi.set(__self__, "roll_config", roll_config)
@property
@pulumi.getter(name="shouldRoll")
def should_roll(self) -> bool:
"""
Sets the enablement of the roll option.
"""
return pulumi.get(self, "should_roll")
@property
@pulumi.getter(name="rollConfig")
def roll_config(self) -> Optional['outputs.ElastigroupUpdatePolicyRollConfig']:
"""
While used, you can control whether the group should perform a deployment after an update to the configuration.
"""
return pulumi.get(self, "roll_config")
@pulumi.output_type
class ElastigroupUpdatePolicyRollConfig(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "batchSizePercentage":
suggest = "batch_size_percentage"
elif key == "gracePeriod":
suggest = "grace_period"
elif key == "healthCheckType":
suggest = "health_check_type"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in ElastigroupUpdatePolicyRollConfig. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
ElastigroupUpdatePolicyRollConfig.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
ElastigroupUpdatePolicyRollConfig.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
batch_size_percentage: int,
grace_period: Optional[int] = None,
health_check_type: Optional[str] = None):
"""
:param int batch_size_percentage: Sets the percentage of the instances to deploy in each batch.
:param int grace_period: Sets the grace period for new instances to become healthy.
:param str health_check_type: Sets the health check type to use. Valid values: `"INSTANCE_STATE"`, `"NONE"`.
"""
pulumi.set(__self__, "batch_size_percentage", batch_size_percentage)
if grace_period is not None:
pulumi.set(__self__, "grace_period", grace_period)
if health_check_type is not None:
pulumi.set(__self__, "health_check_type", health_check_type)
@property
@pulumi.getter(name="batchSizePercentage")
def batch_size_percentage(self) -> int:
"""
Sets the percentage of the instances to deploy in each batch.
"""
return pulumi.get(self, "batch_size_percentage")
@property
@pulumi.getter(name="gracePeriod")
def grace_period(self) -> Optional[int]:
"""
Sets the grace period for new instances to become healthy.
"""
return pulumi.get(self, "grace_period")
@property
@pulumi.getter(name="healthCheckType")
def health_check_type(self) -> Optional[str]:
"""
Sets the health check type to use. Valid values: `"INSTANCE_STATE"`, `"NONE"`.
"""
return pulumi.get(self, "health_check_type")
@pulumi.output_type
class OceanAutoscaler(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "autoscaleDown":
suggest = "autoscale_down"
elif key == "autoscaleHeadroom":
suggest = "autoscale_headroom"
elif key == "autoscaleIsEnabled":
suggest = "autoscale_is_enabled"
elif key == "resourceLimits":
suggest = "resource_limits"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanAutoscaler. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanAutoscaler.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanAutoscaler.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
autoscale_down: Optional['outputs.OceanAutoscalerAutoscaleDown'] = None,
autoscale_headroom: Optional['outputs.OceanAutoscalerAutoscaleHeadroom'] = None,
autoscale_is_enabled: Optional[bool] = None,
resource_limits: Optional['outputs.OceanAutoscalerResourceLimits'] = None):
"""
:param 'OceanAutoscalerAutoscaleDownArgs' autoscale_down: Auto Scaling scale down operations.
:param 'OceanAutoscalerAutoscaleHeadroomArgs' autoscale_headroom: Spare Resource Capacity Management feature enables fast assignment of Pods without having to wait for new resources to be launched.
:param bool autoscale_is_enabled: Enable the Ocean Kubernetes Autoscaler.
:param 'OceanAutoscalerResourceLimitsArgs' resource_limits: Optionally set upper and lower bounds on the resource usage of the cluster.
"""
if autoscale_down is not None:
pulumi.set(__self__, "autoscale_down", autoscale_down)
if autoscale_headroom is not None:
pulumi.set(__self__, "autoscale_headroom", autoscale_headroom)
if autoscale_is_enabled is not None:
pulumi.set(__self__, "autoscale_is_enabled", autoscale_is_enabled)
if resource_limits is not None:
pulumi.set(__self__, "resource_limits", resource_limits)
@property
@pulumi.getter(name="autoscaleDown")
def autoscale_down(self) -> Optional['outputs.OceanAutoscalerAutoscaleDown']:
"""
Auto Scaling scale down operations.
"""
return pulumi.get(self, "autoscale_down")
@property
@pulumi.getter(name="autoscaleHeadroom")
def autoscale_headroom(self) -> Optional['outputs.OceanAutoscalerAutoscaleHeadroom']:
"""
Spare Resource Capacity Management feature enables fast assignment of Pods without having to wait for new resources to be launched.
"""
return pulumi.get(self, "autoscale_headroom")
@property
@pulumi.getter(name="autoscaleIsEnabled")
def autoscale_is_enabled(self) -> Optional[bool]:
"""
Enable the Ocean Kubernetes Autoscaler.
"""
return pulumi.get(self, "autoscale_is_enabled")
@property
@pulumi.getter(name="resourceLimits")
def resource_limits(self) -> Optional['outputs.OceanAutoscalerResourceLimits']:
"""
Optionally set upper and lower bounds on the resource usage of the cluster.
"""
return pulumi.get(self, "resource_limits")
@pulumi.output_type
class OceanAutoscalerAutoscaleDown(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "maxScaleDownPercentage":
suggest = "max_scale_down_percentage"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanAutoscalerAutoscaleDown. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanAutoscalerAutoscaleDown.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanAutoscalerAutoscaleDown.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
max_scale_down_percentage: Optional[float] = None):
"""
:param float max_scale_down_percentage: Would represent the maximum % to scale-down.
"""
if max_scale_down_percentage is not None:
pulumi.set(__self__, "max_scale_down_percentage", max_scale_down_percentage)
@property
@pulumi.getter(name="maxScaleDownPercentage")
def max_scale_down_percentage(self) -> Optional[float]:
"""
Would represent the maximum % to scale-down.
"""
return pulumi.get(self, "max_scale_down_percentage")
@pulumi.output_type
class OceanAutoscalerAutoscaleHeadroom(dict):
def __init__(__self__, *,
automatic: Optional['outputs.OceanAutoscalerAutoscaleHeadroomAutomatic'] = None):
"""
:param 'OceanAutoscalerAutoscaleHeadroomAutomaticArgs' automatic: Automatic headroom configuration.
"""
if automatic is not None:
pulumi.set(__self__, "automatic", automatic)
@property
@pulumi.getter
def automatic(self) -> Optional['outputs.OceanAutoscalerAutoscaleHeadroomAutomatic']:
"""
Automatic headroom configuration.
"""
return pulumi.get(self, "automatic")
@pulumi.output_type
class OceanAutoscalerAutoscaleHeadroomAutomatic(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "isEnabled":
suggest = "is_enabled"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanAutoscalerAutoscaleHeadroomAutomatic. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanAutoscalerAutoscaleHeadroomAutomatic.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanAutoscalerAutoscaleHeadroomAutomatic.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
is_enabled: Optional[bool] = None,
percentage: Optional[int] = None):
"""
:param bool is_enabled: Enable automatic headroom. When set to `true`, Ocean configures and optimizes headroom automatically.
:param int percentage: Optionally set a number between 0-100 to control the percentage of total cluster resources dedicated to headroom. Relevant when `isEnabled` is toggled on.
"""
if is_enabled is not None:
pulumi.set(__self__, "is_enabled", is_enabled)
if percentage is not None:
pulumi.set(__self__, "percentage", percentage)
@property
@pulumi.getter(name="isEnabled")
def is_enabled(self) -> Optional[bool]:
"""
Enable automatic headroom. When set to `true`, Ocean configures and optimizes headroom automatically.
"""
return pulumi.get(self, "is_enabled")
@property
@pulumi.getter
def percentage(self) -> Optional[int]:
"""
Optionally set a number between 0-100 to control the percentage of total cluster resources dedicated to headroom. Relevant when `isEnabled` is toggled on.
"""
return pulumi.get(self, "percentage")
@pulumi.output_type
class OceanAutoscalerResourceLimits(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "maxMemoryGib":
suggest = "max_memory_gib"
elif key == "maxVcpu":
suggest = "max_vcpu"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanAutoscalerResourceLimits. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanAutoscalerResourceLimits.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanAutoscalerResourceLimits.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
max_memory_gib: Optional[int] = None,
max_vcpu: Optional[int] = None):
"""
:param int max_memory_gib: The maximum memory in GiB units that can be allocated to the cluster.
:param int max_vcpu: The maximum cpu in vCpu units that can be allocated to the cluster.
"""
if max_memory_gib is not None:
pulumi.set(__self__, "max_memory_gib", max_memory_gib)
if max_vcpu is not None:
pulumi.set(__self__, "max_vcpu", max_vcpu)
@property
@pulumi.getter(name="maxMemoryGib")
def max_memory_gib(self) -> Optional[int]:
"""
The maximum memory in GiB units that can be allocated to the cluster.
"""
return pulumi.get(self, "max_memory_gib")
@property
@pulumi.getter(name="maxVcpu")
def max_vcpu(self) -> Optional[int]:
"""
The maximum cpu in vCpu units that can be allocated to the cluster.
"""
return pulumi.get(self, "max_vcpu")
@pulumi.output_type
class OceanExtension(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "apiVersion":
suggest = "api_version"
elif key == "minorVersionAutoUpgrade":
suggest = "minor_version_auto_upgrade"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanExtension. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanExtension.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanExtension.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
api_version: Optional[str] = None,
minor_version_auto_upgrade: Optional[bool] = None,
name: Optional[str] = None,
publisher: Optional[str] = None,
type: Optional[str] = None):
"""
:param str api_version: API version of the extension.
:param bool minor_version_auto_upgrade: Toggles whether auto upgrades are allowed.
:param str name: Name of the Load Balancer.
:param str publisher: Image publisher.
:param str type: The type of load balancer. Supported value: `loadBalancer`
"""
if api_version is not None:
pulumi.set(__self__, "api_version", api_version)
if minor_version_auto_upgrade is not None:
pulumi.set(__self__, "minor_version_auto_upgrade", minor_version_auto_upgrade)
if name is not None:
pulumi.set(__self__, "name", name)
if publisher is not None:
pulumi.set(__self__, "publisher", publisher)
if type is not None:
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="apiVersion")
def api_version(self) -> Optional[str]:
"""
API version of the extension.
"""
return pulumi.get(self, "api_version")
@property
@pulumi.getter(name="minorVersionAutoUpgrade")
def minor_version_auto_upgrade(self) -> Optional[bool]:
"""
Toggles whether auto upgrades are allowed.
"""
return pulumi.get(self, "minor_version_auto_upgrade")
@property
@pulumi.getter
def name(self) -> Optional[str]:
"""
Name of the Load Balancer.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def publisher(self) -> Optional[str]:
"""
Image publisher.
"""
return pulumi.get(self, "publisher")
@property
@pulumi.getter
def type(self) -> Optional[str]:
"""
The type of load balancer. Supported value: `loadBalancer`
"""
return pulumi.get(self, "type")
@pulumi.output_type
class OceanHealth(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "gracePeriod":
suggest = "grace_period"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanHealth. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanHealth.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanHealth.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
grace_period: Optional[int] = None):
"""
:param int grace_period: The amount of time to wait, in seconds, from the moment the instance has launched before monitoring its health checks.
"""
if grace_period is not None:
pulumi.set(__self__, "grace_period", grace_period)
@property
@pulumi.getter(name="gracePeriod")
def grace_period(self) -> Optional[int]:
"""
The amount of time to wait, in seconds, from the moment the instance has launched before monitoring its health checks.
"""
return pulumi.get(self, "grace_period")
@pulumi.output_type
class OceanImage(dict):
def __init__(__self__, *,
marketplaces: Optional[Sequence['outputs.OceanImageMarketplace']] = None):
"""
:param Sequence['OceanImageMarketplaceArgs'] marketplaces: Select an image from Azure's Marketplace image catalogue.
"""
if marketplaces is not None:
pulumi.set(__self__, "marketplaces", marketplaces)
@property
@pulumi.getter
def marketplaces(self) -> Optional[Sequence['outputs.OceanImageMarketplace']]:
"""
Select an image from Azure's Marketplace image catalogue.
"""
return pulumi.get(self, "marketplaces")
@pulumi.output_type
class OceanImageMarketplace(dict):
def __init__(__self__, *,
offer: Optional[str] = None,
publisher: Optional[str] = None,
sku: Optional[str] = None,
version: Optional[str] = None):
"""
:param str offer: Image name.
:param str publisher: Image publisher.
:param str sku: Image Stock Keeping Unit (which is the specific version of the image).
:param str version: Image version.
"""
if offer is not None:
pulumi.set(__self__, "offer", offer)
if publisher is not None:
pulumi.set(__self__, "publisher", publisher)
if sku is not None:
pulumi.set(__self__, "sku", sku)
if version is not None:
pulumi.set(__self__, "version", version)
@property
@pulumi.getter
def offer(self) -> Optional[str]:
"""
Image name.
"""
return pulumi.get(self, "offer")
@property
@pulumi.getter
def publisher(self) -> Optional[str]:
"""
Image publisher.
"""
return pulumi.get(self, "publisher")
@property
@pulumi.getter
def sku(self) -> Optional[str]:
"""
Image Stock Keeping Unit (which is the specific version of the image).
"""
return pulumi.get(self, "sku")
@property
@pulumi.getter
def version(self) -> Optional[str]:
"""
Image version.
"""
return pulumi.get(self, "version")
@pulumi.output_type
class OceanLoadBalancer(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "backendPoolNames":
suggest = "backend_pool_names"
elif key == "loadBalancerSku":
suggest = "load_balancer_sku"
elif key == "resourceGroupName":
suggest = "resource_group_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanLoadBalancer. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanLoadBalancer.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanLoadBalancer.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
backend_pool_names: Optional[Sequence[str]] = None,
load_balancer_sku: Optional[str] = None,
name: Optional[str] = None,
resource_group_name: Optional[str] = None,
type: Optional[str] = None):
"""
:param Sequence[str] backend_pool_names: Names of the Backend Pools to register the Cluster VMs to. Each Backend Pool is a separate load balancer.
:param str load_balancer_sku: Supported values: `Standard`, `Basic`.
:param str name: Name of the Load Balancer.
:param str resource_group_name: The Resource Group name of the Load Balancer.
:param str type: The type of load balancer. Supported value: `loadBalancer`
"""
if backend_pool_names is not None:
pulumi.set(__self__, "backend_pool_names", backend_pool_names)
if load_balancer_sku is not None:
pulumi.set(__self__, "load_balancer_sku", load_balancer_sku)
if name is not None:
pulumi.set(__self__, "name", name)
if resource_group_name is not None:
pulumi.set(__self__, "resource_group_name", resource_group_name)
if type is not None:
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="backendPoolNames")
def backend_pool_names(self) -> Optional[Sequence[str]]:
"""
Names of the Backend Pools to register the Cluster VMs to. Each Backend Pool is a separate load balancer.
"""
return pulumi.get(self, "backend_pool_names")
@property
@pulumi.getter(name="loadBalancerSku")
def load_balancer_sku(self) -> Optional[str]:
"""
Supported values: `Standard`, `Basic`.
"""
return pulumi.get(self, "load_balancer_sku")
@property
@pulumi.getter
def name(self) -> Optional[str]:
"""
Name of the Load Balancer.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> Optional[str]:
"""
The Resource Group name of the Load Balancer.
"""
return pulumi.get(self, "resource_group_name")
@property
@pulumi.getter
def type(self) -> Optional[str]:
"""
The type of load balancer. Supported value: `loadBalancer`
"""
return pulumi.get(self, "type")
@pulumi.output_type
class OceanManagedServiceIdentity(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "resourceGroupName":
suggest = "resource_group_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanManagedServiceIdentity. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanManagedServiceIdentity.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanManagedServiceIdentity.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
name: str,
resource_group_name: str):
"""
:param str name: Name of the Load Balancer.
:param str resource_group_name: The Resource Group name of the Load Balancer.
"""
pulumi.set(__self__, "name", name)
pulumi.set(__self__, "resource_group_name", resource_group_name)
@property
@pulumi.getter
def name(self) -> str:
"""
Name of the Load Balancer.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> str:
"""
The Resource Group name of the Load Balancer.
"""
return pulumi.get(self, "resource_group_name")
@pulumi.output_type
class OceanNetwork(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "networkInterfaces":
suggest = "network_interfaces"
elif key == "resourceGroupName":
suggest = "resource_group_name"
elif key == "virtualNetworkName":
suggest = "virtual_network_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanNetwork. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanNetwork.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanNetwork.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
network_interfaces: Optional[Sequence['outputs.OceanNetworkNetworkInterface']] = None,
resource_group_name: Optional[str] = None,
virtual_network_name: Optional[str] = None):
"""
:param Sequence['OceanNetworkNetworkInterfaceArgs'] network_interfaces: A list of virtual network interfaces. The publicIpSku must be identical between all the network interfaces. One network interface must be set as the primary.
:param str resource_group_name: The Resource Group name of the Load Balancer.
:param str virtual_network_name: Virtual network.
"""
if network_interfaces is not None:
pulumi.set(__self__, "network_interfaces", network_interfaces)
if resource_group_name is not None:
pulumi.set(__self__, "resource_group_name", resource_group_name)
if virtual_network_name is not None:
pulumi.set(__self__, "virtual_network_name", virtual_network_name)
@property
@pulumi.getter(name="networkInterfaces")
def network_interfaces(self) -> Optional[Sequence['outputs.OceanNetworkNetworkInterface']]:
"""
A list of virtual network interfaces. The publicIpSku must be identical between all the network interfaces. One network interface must be set as the primary.
"""
return pulumi.get(self, "network_interfaces")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> Optional[str]:
"""
The Resource Group name of the Load Balancer.
"""
return pulumi.get(self, "resource_group_name")
@property
@pulumi.getter(name="virtualNetworkName")
def virtual_network_name(self) -> Optional[str]:
"""
Virtual network.
"""
return pulumi.get(self, "virtual_network_name")
@pulumi.output_type
class OceanNetworkNetworkInterface(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "additionalIpConfigs":
suggest = "additional_ip_configs"
elif key == "assignPublicIp":
suggest = "assign_public_ip"
elif key == "isPrimary":
suggest = "is_primary"
elif key == "securityGroup":
suggest = "security_group"
elif key == "subnetName":
suggest = "subnet_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanNetworkNetworkInterface. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanNetworkNetworkInterface.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanNetworkNetworkInterface.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
additional_ip_configs: Optional[Sequence['outputs.OceanNetworkNetworkInterfaceAdditionalIpConfig']] = None,
assign_public_ip: Optional[bool] = None,
is_primary: Optional[bool] = None,
security_group: Optional['outputs.OceanNetworkNetworkInterfaceSecurityGroup'] = None,
subnet_name: Optional[str] = None):
"""
:param Sequence['OceanNetworkNetworkInterfaceAdditionalIpConfigArgs'] additional_ip_configs: Additional configuration of network interface. The name fields between all the `additional_ip_config` must be unique.
:param bool assign_public_ip: Assign public IP.
:param bool is_primary: Defines whether the network interface is primary or not.
:param str subnet_name: Subnet name.
"""
if additional_ip_configs is not None:
pulumi.set(__self__, "additional_ip_configs", additional_ip_configs)
if assign_public_ip is not None:
pulumi.set(__self__, "assign_public_ip", assign_public_ip)
if is_primary is not None:
pulumi.set(__self__, "is_primary", is_primary)
if security_group is not None:
pulumi.set(__self__, "security_group", security_group)
if subnet_name is not None:
pulumi.set(__self__, "subnet_name", subnet_name)
@property
@pulumi.getter(name="additionalIpConfigs")
def additional_ip_configs(self) -> Optional[Sequence['outputs.OceanNetworkNetworkInterfaceAdditionalIpConfig']]:
"""
Additional configuration of network interface. The name fields between all the `additional_ip_config` must be unique.
"""
return pulumi.get(self, "additional_ip_configs")
@property
@pulumi.getter(name="assignPublicIp")
def assign_public_ip(self) -> Optional[bool]:
"""
Assign public IP.
"""
return pulumi.get(self, "assign_public_ip")
@property
@pulumi.getter(name="isPrimary")
def is_primary(self) -> Optional[bool]:
"""
Defines whether the network interface is primary or not.
"""
return pulumi.get(self, "is_primary")
@property
@pulumi.getter(name="securityGroup")
def security_group(self) -> Optional['outputs.OceanNetworkNetworkInterfaceSecurityGroup']:
return pulumi.get(self, "security_group")
@property
@pulumi.getter(name="subnetName")
def subnet_name(self) -> Optional[str]:
"""
Subnet name.
"""
return pulumi.get(self, "subnet_name")
@pulumi.output_type
class OceanNetworkNetworkInterfaceAdditionalIpConfig(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "privateIpVersion":
suggest = "private_ip_version"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanNetworkNetworkInterfaceAdditionalIpConfig. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanNetworkNetworkInterfaceAdditionalIpConfig.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanNetworkNetworkInterfaceAdditionalIpConfig.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
name: Optional[str] = None,
private_ip_version: Optional[str] = None):
"""
:param str name: Name of the Load Balancer.
:param str private_ip_version: Supported values: `IPv4`, `IPv6`.
"""
if name is not None:
pulumi.set(__self__, "name", name)
if private_ip_version is not None:
pulumi.set(__self__, "private_ip_version", private_ip_version)
@property
@pulumi.getter
def name(self) -> Optional[str]:
"""
Name of the Load Balancer.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="privateIpVersion")
def private_ip_version(self) -> Optional[str]:
"""
Supported values: `IPv4`, `IPv6`.
"""
return pulumi.get(self, "private_ip_version")
@pulumi.output_type
class OceanNetworkNetworkInterfaceSecurityGroup(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "resourceGroupName":
suggest = "resource_group_name"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanNetworkNetworkInterfaceSecurityGroup. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanNetworkNetworkInterfaceSecurityGroup.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanNetworkNetworkInterfaceSecurityGroup.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
name: Optional[str] = None,
resource_group_name: Optional[str] = None):
"""
:param str name: Name of the Load Balancer.
:param str resource_group_name: The Resource Group name of the Load Balancer.
"""
if name is not None:
pulumi.set(__self__, "name", name)
if resource_group_name is not None:
pulumi.set(__self__, "resource_group_name", resource_group_name)
@property
@pulumi.getter
def name(self) -> Optional[str]:
"""
Name of the Load Balancer.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> Optional[str]:
"""
The Resource Group name of the Load Balancer.
"""
return pulumi.get(self, "resource_group_name")
@pulumi.output_type
class OceanOsDisk(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "sizeGb":
suggest = "size_gb"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanOsDisk. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanOsDisk.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanOsDisk.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
size_gb: int,
type: Optional[str] = None):
"""
:param int size_gb: The size of the OS disk in GB.
:param str type: The type of load balancer. Supported value: `loadBalancer`
"""
pulumi.set(__self__, "size_gb", size_gb)
if type is not None:
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="sizeGb")
def size_gb(self) -> int:
"""
The size of the OS disk in GB.
"""
return pulumi.get(self, "size_gb")
@property
@pulumi.getter
def type(self) -> Optional[str]:
"""
The type of load balancer. Supported value: `loadBalancer`
"""
return pulumi.get(self, "type")
@pulumi.output_type
class OceanStrategy(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "fallbackToOndemand":
suggest = "fallback_to_ondemand"
elif key == "spotPercentage":
suggest = "spot_percentage"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanStrategy. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanStrategy.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanStrategy.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
fallback_to_ondemand: Optional[bool] = None,
spot_percentage: Optional[int] = None):
"""
:param bool fallback_to_ondemand: If no spot instance markets are available, enable Ocean to launch on-demand instances instead.
:param int spot_percentage: Percentage of Spot VMs to maintain.
"""
if fallback_to_ondemand is not None:
pulumi.set(__self__, "fallback_to_ondemand", fallback_to_ondemand)
if spot_percentage is not None:
pulumi.set(__self__, "spot_percentage", spot_percentage)
@property
@pulumi.getter(name="fallbackToOndemand")
def fallback_to_ondemand(self) -> Optional[bool]:
"""
If no spot instance markets are available, enable Ocean to launch on-demand instances instead.
"""
return pulumi.get(self, "fallback_to_ondemand")
@property
@pulumi.getter(name="spotPercentage")
def spot_percentage(self) -> Optional[int]:
"""
Percentage of Spot VMs to maintain.
"""
return pulumi.get(self, "spot_percentage")
@pulumi.output_type
class OceanTag(dict):
def __init__(__self__, *,
key: Optional[str] = None,
value: Optional[str] = None):
"""
:param str key: Tag key.
:param str value: Tag value.
"""
if key is not None:
pulumi.set(__self__, "key", key)
if value is not None:
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> Optional[str]:
"""
Tag key.
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> Optional[str]:
"""
Tag value.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class OceanVirtualNodeGroupAutoscale(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "autoscaleHeadroom":
suggest = "autoscale_headroom"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanVirtualNodeGroupAutoscale. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanVirtualNodeGroupAutoscale.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanVirtualNodeGroupAutoscale.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
autoscale_headroom: Optional['outputs.OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom'] = None):
if autoscale_headroom is not None:
pulumi.set(__self__, "autoscale_headroom", autoscale_headroom)
@property
@pulumi.getter(name="autoscaleHeadroom")
def autoscale_headroom(self) -> Optional['outputs.OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom']:
return pulumi.get(self, "autoscale_headroom")
@pulumi.output_type
class OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "numOfUnits":
suggest = "num_of_units"
elif key == "cpuPerUnit":
suggest = "cpu_per_unit"
elif key == "gpuPerUnit":
suggest = "gpu_per_unit"
elif key == "memoryPerUnit":
suggest = "memory_per_unit"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanVirtualNodeGroupAutoscaleAutoscaleHeadroom.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
num_of_units: int,
cpu_per_unit: Optional[int] = None,
gpu_per_unit: Optional[int] = None,
memory_per_unit: Optional[int] = None):
"""
:param int num_of_units: The number of headroom units to maintain, where each unit has the defined CPU, memory and GPU.
:param int cpu_per_unit: Configure the number of CPUs to allocate for the headroom. CPUs are denoted in millicores, where 1000 millicores = 1 vCPU.
:param int gpu_per_unit: How many GPU cores should be allocated for headroom unit.
:param int memory_per_unit: Configure the amount of memory (MiB) to allocate the headroom.
"""
pulumi.set(__self__, "num_of_units", num_of_units)
if cpu_per_unit is not None:
pulumi.set(__self__, "cpu_per_unit", cpu_per_unit)
if gpu_per_unit is not None:
pulumi.set(__self__, "gpu_per_unit", gpu_per_unit)
if memory_per_unit is not None:
pulumi.set(__self__, "memory_per_unit", memory_per_unit)
@property
@pulumi.getter(name="numOfUnits")
def num_of_units(self) -> int:
"""
The number of headroom units to maintain, where each unit has the defined CPU, memory and GPU.
"""
return pulumi.get(self, "num_of_units")
@property
@pulumi.getter(name="cpuPerUnit")
def cpu_per_unit(self) -> Optional[int]:
"""
Configure the number of CPUs to allocate for the headroom. CPUs are denoted in millicores, where 1000 millicores = 1 vCPU.
"""
return pulumi.get(self, "cpu_per_unit")
@property
@pulumi.getter(name="gpuPerUnit")
def gpu_per_unit(self) -> Optional[int]:
"""
How many GPU cores should be allocated for headroom unit.
"""
return pulumi.get(self, "gpu_per_unit")
@property
@pulumi.getter(name="memoryPerUnit")
def memory_per_unit(self) -> Optional[int]:
"""
Configure the amount of memory (MiB) to allocate the headroom.
"""
return pulumi.get(self, "memory_per_unit")
@pulumi.output_type
class OceanVirtualNodeGroupLabel(dict):
def __init__(__self__, *,
key: str,
value: Optional[str] = None):
"""
:param str key: Tag Key for Vms in the cluster.
:param str value: Tag Value for VMs in the cluster.
"""
pulumi.set(__self__, "key", key)
if value is not None:
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
Tag Key for Vms in the cluster.
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> Optional[str]:
"""
Tag Value for VMs in the cluster.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class OceanVirtualNodeGroupLaunchSpecification(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "osDisk":
suggest = "os_disk"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanVirtualNodeGroupLaunchSpecification. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanVirtualNodeGroupLaunchSpecification.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanVirtualNodeGroupLaunchSpecification.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
os_disk: Optional['outputs.OceanVirtualNodeGroupLaunchSpecificationOsDisk'] = None,
tags: Optional[Sequence['outputs.OceanVirtualNodeGroupLaunchSpecificationTag']] = None):
"""
:param 'OceanVirtualNodeGroupLaunchSpecificationOsDiskArgs' os_disk: Specify OS disk specification other than default.
:param Sequence['OceanVirtualNodeGroupLaunchSpecificationTagArgs'] tags: Additional key-value pairs to be used to tag the VMs in the virtual node group.
"""
if os_disk is not None:
pulumi.set(__self__, "os_disk", os_disk)
if tags is not None:
pulumi.set(__self__, "tags", tags)
@property
@pulumi.getter(name="osDisk")
def os_disk(self) -> Optional['outputs.OceanVirtualNodeGroupLaunchSpecificationOsDisk']:
"""
Specify OS disk specification other than default.
"""
return pulumi.get(self, "os_disk")
@property
@pulumi.getter
def tags(self) -> Optional[Sequence['outputs.OceanVirtualNodeGroupLaunchSpecificationTag']]:
"""
Additional key-value pairs to be used to tag the VMs in the virtual node group.
"""
return pulumi.get(self, "tags")
@pulumi.output_type
class OceanVirtualNodeGroupLaunchSpecificationOsDisk(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "sizeGb":
suggest = "size_gb"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanVirtualNodeGroupLaunchSpecificationOsDisk. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanVirtualNodeGroupLaunchSpecificationOsDisk.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanVirtualNodeGroupLaunchSpecificationOsDisk.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
size_gb: int,
type: Optional[str] = None):
"""
:param int size_gb: The size of the OS disk in GB, Required if dataDisks is specified.
:param str type: The type of the OS disk. Valid values: `"Standard_LRS"`, `"Premium_LRS"`, `"StandardSSD_LRS"`.
"""
pulumi.set(__self__, "size_gb", size_gb)
if type is not None:
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="sizeGb")
def size_gb(self) -> int:
"""
The size of the OS disk in GB, Required if dataDisks is specified.
"""
return pulumi.get(self, "size_gb")
@property
@pulumi.getter
def type(self) -> Optional[str]:
"""
The type of the OS disk. Valid values: `"Standard_LRS"`, `"Premium_LRS"`, `"StandardSSD_LRS"`.
"""
return pulumi.get(self, "type")
@pulumi.output_type
class OceanVirtualNodeGroupLaunchSpecificationTag(dict):
def __init__(__self__, *,
key: Optional[str] = None,
value: Optional[str] = None):
"""
:param str key: Tag Key for Vms in the cluster.
:param str value: Tag Value for VMs in the cluster.
"""
if key is not None:
pulumi.set(__self__, "key", key)
if value is not None:
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> Optional[str]:
"""
Tag Key for Vms in the cluster.
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> Optional[str]:
"""
Tag Value for VMs in the cluster.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class OceanVirtualNodeGroupResourceLimit(dict):
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "maxInstanceCount":
suggest = "max_instance_count"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OceanVirtualNodeGroupResourceLimit. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OceanVirtualNodeGroupResourceLimit.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OceanVirtualNodeGroupResourceLimit.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
max_instance_count: Optional[int] = None):
"""
:param int max_instance_count: Option to set a maximum number of instances per virtual node group. If set, value must be greater than or equal to 0.
"""
if max_instance_count is not None:
pulumi.set(__self__, "max_instance_count", max_instance_count)
@property
@pulumi.getter(name="maxInstanceCount")
def max_instance_count(self) -> Optional[int]:
"""
Option to set a maximum number of instances per virtual node group. If set, value must be greater than or equal to 0.
"""
return pulumi.get(self, "max_instance_count")
@pulumi.output_type
class OceanVirtualNodeGroupTaint(dict):
def __init__(__self__, *,
effect: str,
key: str,
value: str):
"""
:param str effect: The effect of the taint. Valid values: `"NoSchedule"`, `"PreferNoSchedule"`, `"NoExecute"`, `"PreferNoExecute"`.
:param str key: Tag Key for Vms in the cluster.
:param str value: Tag Value for VMs in the cluster.
"""
pulumi.set(__self__, "effect", effect)
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def effect(self) -> str:
"""
The effect of the taint. Valid values: `"NoSchedule"`, `"PreferNoSchedule"`, `"NoExecute"`, `"PreferNoExecute"`.
"""
return pulumi.get(self, "effect")
@property
@pulumi.getter
def key(self) -> str:
"""
Tag Key for Vms in the cluster.
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
Tag Value for VMs in the cluster.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class OceanVmSize(dict):
def __init__(__self__, *,
whitelists: Optional[Sequence[str]] = None):
"""
:param Sequence[str] whitelists: VM types allowed in the Ocean cluster.
"""
if whitelists is not None:
pulumi.set(__self__, "whitelists", whitelists)
@property
@pulumi.getter
def whitelists(self) -> Optional[Sequence[str]]:
"""
VM types allowed in the Ocean cluster.
"""
return pulumi.get(self, "whitelists")
| 37.447029
| 526
| 0.631223
| 11,517
| 104,627
| 5.506903
| 0.048624
| 0.020308
| 0.030746
| 0.044936
| 0.774892
| 0.73672
| 0.70826
| 0.65224
| 0.644451
| 0.627627
| 0
| 0.000845
| 0.264473
| 104,627
| 2,793
| 527
| 37.460437
| 0.823302
| 0.236239
| 0
| 0.677364
| 1
| 0.019484
| 0.181463
| 0.053583
| 0
| 0
| 0
| 0
| 0
| 1
| 0.170774
| false
| 0.002865
| 0.003438
| 0.003438
| 0.325501
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fa8e25ba8dcee6b488d2c2144765467332fb6a9f
| 202
|
py
|
Python
|
MachineLearning/Regression.py
|
keytotime/Open-CSynapse
|
73861f956996af591fa3f9ab0e2202b01e661dba
|
[
"MIT"
] | null | null | null |
MachineLearning/Regression.py
|
keytotime/Open-CSynapse
|
73861f956996af591fa3f9ab0e2202b01e661dba
|
[
"MIT"
] | null | null | null |
MachineLearning/Regression.py
|
keytotime/Open-CSynapse
|
73861f956996af591fa3f9ab0e2202b01e661dba
|
[
"MIT"
] | null | null | null |
from scipy.stats import pearsonr
from collections import namedtuple
result = namedtuple('result', 'r p')
def reg(x, y):
strength, probability = pearsonr(x, y)
return result(r=strength,p=probability)
| 25.25
| 40
| 0.757426
| 29
| 202
| 5.275862
| 0.586207
| 0.20915
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128713
| 202
| 8
| 40
| 25.25
| 0.869318
| 0
| 0
| 0
| 0
| 0
| 0.044335
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.333333
| 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
|
faa705b77de395dc1ad140766300ba16dc2e5058
| 268
|
py
|
Python
|
src/python/WMComponent/DBS3Buffer/Oracle/LoadDBSFilesByDAS.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 21
|
2015-11-19T16:18:45.000Z
|
2021-12-02T18:20:39.000Z
|
src/python/WMComponent/DBS3Buffer/Oracle/LoadDBSFilesByDAS.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 5,671
|
2015-01-06T14:38:52.000Z
|
2022-03-31T22:11:14.000Z
|
src/python/WMComponent/DBS3Buffer/Oracle/LoadDBSFilesByDAS.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 67
|
2015-01-21T15:55:38.000Z
|
2022-02-03T19:53:13.000Z
|
#!/usr/bin/env python
"""
_LoadDBSFilesByDAS_
Oracle implementation of DBS3Buffer.LoadDBSFilesByDAS
"""
from WMComponent.DBS3Buffer.MySQL.LoadDBSFilesByDAS import LoadDBSFilesByDAS as MySQLLoadDBSFilesByDAS
class LoadDBSFilesByDAS(MySQLLoadDBSFilesByDAS):
pass
| 22.333333
| 102
| 0.839552
| 23
| 268
| 9.695652
| 0.73913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.00823
| 0.093284
| 268
| 11
| 103
| 24.363636
| 0.909465
| 0.354478
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 4
|
fab6008e8bdf18248168378339f964ab6fa73379
| 127
|
py
|
Python
|
res_mods/mods/packages/xvm_main/python/vehinfo_stat_avg.py
|
peterbartha/ImmunoMod
|
cbf8cd49893d7082a347c1f72c0e39480869318a
|
[
"MIT"
] | null | null | null |
res_mods/mods/packages/xvm_main/python/vehinfo_stat_avg.py
|
peterbartha/ImmunoMod
|
cbf8cd49893d7082a347c1f72c0e39480869318a
|
[
"MIT"
] | 1
|
2016-04-03T13:31:39.000Z
|
2016-04-03T16:48:26.000Z
|
res_mods/mods/packages/xvm_main/python/vehinfo_stat_avg.py
|
peterbartha/ImmunoMod
|
cbf8cd49893d7082a347c1f72c0e39480869318a
|
[
"MIT"
] | null | null | null |
""" XVM (c) www.modxvm.com 2013-2017 """
# PUBLIC
def getAvgStat(key):
return _data.get(key, {})
# PRIVATE
_data = {}
| 10.583333
| 40
| 0.590551
| 17
| 127
| 4.294118
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 0.212598
| 127
| 11
| 41
| 11.545455
| 0.65
| 0.385827
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
faebf3912bec59cca6a60eef58aab8bbfd872357
| 212
|
py
|
Python
|
tej/__main__.py
|
VisTrails/tej
|
86d083f9c56d3b9004de4b727bd39bf6e49fc206
|
[
"BSD-3-Clause"
] | 8
|
2016-06-20T16:14:35.000Z
|
2021-03-09T17:23:42.000Z
|
tej/__main__.py
|
VisTrails/tej
|
86d083f9c56d3b9004de4b727bd39bf6e49fc206
|
[
"BSD-3-Clause"
] | 15
|
2016-02-19T19:24:04.000Z
|
2019-03-18T17:11:55.000Z
|
tej/__main__.py
|
VisTrails/tej
|
86d083f9c56d3b9004de4b727bd39bf6e49fc206
|
[
"BSD-3-Clause"
] | 2
|
2016-12-08T00:33:51.000Z
|
2019-07-18T20:03:23.000Z
|
import os
import sys
try:
from tej.main import main
except ImportError:
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from tej.main import main
if __name__ == '__main__':
main()
| 15.142857
| 63
| 0.698113
| 31
| 212
| 4.387097
| 0.483871
| 0.102941
| 0.161765
| 0.25
| 0.308824
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.193396
| 212
| 13
| 64
| 16.307692
| 0.795322
| 0
| 0
| 0.222222
| 0
| 0
| 0.037736
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.555556
| 0
| 0.555556
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
faf6bcf921c3dcb8856b8beb9c8e35142d59271c
| 171
|
py
|
Python
|
camproxy/app/main.py
|
k-wojcik/hassio-addons
|
4d82843136d593fbee5d839b45713680594a1f28
|
[
"Apache-2.0"
] | null | null | null |
camproxy/app/main.py
|
k-wojcik/hassio-addons
|
4d82843136d593fbee5d839b45713680594a1f28
|
[
"Apache-2.0"
] | 1
|
2020-09-27T03:47:43.000Z
|
2020-09-27T03:47:43.000Z
|
camproxy/app/main.py
|
k-wojcik/hassio-addons
|
4d82843136d593fbee5d839b45713680594a1f28
|
[
"Apache-2.0"
] | 2
|
2021-09-08T13:41:56.000Z
|
2021-09-13T19:37:53.000Z
|
# Entry point for the application.
from flask import Flask # Import the Flask class
app = Flask(__name__) # Create an instance of the class for our use
import routes
| 28.5
| 70
| 0.754386
| 27
| 171
| 4.62963
| 0.666667
| 0.176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.204678
| 171
| 6
| 71
| 28.5
| 0.919118
| 0.578947
| 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 | 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
|
faf8ab6458182b00ffb0d79228f8d0a7b11e2476
| 2,015
|
py
|
Python
|
tests/test_graph_utils/test_node.py
|
salty-horse/redis-py
|
41cef4703a9e23af72040966a9411ee55d92d917
|
[
"MIT"
] | 1
|
2015-05-12T01:41:16.000Z
|
2015-05-12T01:41:16.000Z
|
tests/test_graph_utils/test_node.py
|
salty-horse/redis-py
|
41cef4703a9e23af72040966a9411ee55d92d917
|
[
"MIT"
] | 3
|
2021-12-21T14:52:37.000Z
|
2022-01-12T19:27:30.000Z
|
tests/test_graph_utils/test_node.py
|
salty-horse/redis-py
|
41cef4703a9e23af72040966a9411ee55d92d917
|
[
"MIT"
] | null | null | null |
import pytest
from redis.commands.graph import node
@pytest.fixture
def fixture():
no_args = node.Node()
no_props = node.Node(node_id=1, alias="alias", label="l")
props_only = node.Node(properties={"a": "a", "b": 10})
no_label = node.Node(node_id=1, alias="alias", properties={"a": "a"})
multi_label = node.Node(node_id=1, alias="alias", label=["l", "ll"])
return no_args, no_props, props_only, no_label, multi_label
@pytest.mark.redismod
def test_toString(fixture):
no_args, no_props, props_only, no_label, multi_label = fixture
assert no_args.toString() == ""
assert no_props.toString() == ""
assert props_only.toString() == '{a:"a",b:10}'
assert no_label.toString() == '{a:"a"}'
assert multi_label.toString() == ""
@pytest.mark.redismod
def test_stringify(fixture):
no_args, no_props, props_only, no_label, multi_label = fixture
assert str(no_args) == "()"
assert str(no_props) == "(alias:l)"
assert str(props_only) == '({a:"a",b:10})'
assert str(no_label) == '(alias{a:"a"})'
assert str(multi_label) == "(alias:l:ll)"
@pytest.mark.redismod
def test_comparision(fixture):
no_args, no_props, props_only, no_label, multi_label = fixture
assert node.Node() == node.Node()
assert node.Node(node_id=1) == node.Node(node_id=1)
assert node.Node(node_id=1) != node.Node(node_id=2)
assert node.Node(node_id=1, alias="a") == node.Node(node_id=1, alias="b")
assert node.Node(node_id=1, alias="a") == node.Node(node_id=1, alias="a")
assert node.Node(node_id=1, label="a") == node.Node(node_id=1, label="a")
assert node.Node(node_id=1, label="a") != node.Node(node_id=1, label="b")
assert node.Node(node_id=1, alias="a", label="l") == node.Node(
node_id=1, alias="a", label="l"
)
assert node.Node(alias="a", label="l") != node.Node(alias="a", label="l1")
assert node.Node(properties={"a": 10}) == node.Node(properties={"a": 10})
assert node.Node() != node.Node(properties={"a": 10})
| 38.018868
| 78
| 0.646154
| 321
| 2,015
| 3.884735
| 0.109034
| 0.295108
| 0.202085
| 0.190858
| 0.693665
| 0.525261
| 0.509222
| 0.509222
| 0.481155
| 0.381716
| 0
| 0.017657
| 0.156824
| 2,015
| 52
| 79
| 38.75
| 0.716304
| 0
| 0
| 0.142857
| 0
| 0
| 0.056576
| 0
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0.095238
| false
| 0
| 0.047619
| 0
| 0.166667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fafddc019ffe2802057c7218bb1418c35fa4696c
| 201
|
py
|
Python
|
donor/urls.py
|
RobBickel/nyt-fec
|
802df867c3b31fff8e922be00bab6f40a5db2d00
|
[
"Apache-2.0"
] | 17
|
2018-03-27T15:09:58.000Z
|
2020-05-13T11:32:43.000Z
|
donor/urls.py
|
RobBickel/nyt-fec
|
802df867c3b31fff8e922be00bab6f40a5db2d00
|
[
"Apache-2.0"
] | 59
|
2018-03-21T17:08:15.000Z
|
2021-12-13T19:47:37.000Z
|
donor/urls.py
|
RobBickel/nyt-fec
|
802df867c3b31fff8e922be00bab6f40a5db2d00
|
[
"Apache-2.0"
] | 11
|
2018-09-11T23:18:32.000Z
|
2021-12-15T08:43:58.000Z
|
from django.urls import include, path, re_path
from donor import views
app_name = 'donor'
urlpatterns = [
path('donor_details/<int:donor_id>', views.donor_details, name='donor_details')
]
| 25.125
| 87
| 0.721393
| 28
| 201
| 4.964286
| 0.535714
| 0.258993
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164179
| 201
| 8
| 88
| 25.125
| 0.827381
| 0
| 0
| 0
| 0
| 0
| 0.227723
| 0.138614
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
879a31d24ae0139d80634316ef1748880abb8fdc
| 1,847
|
py
|
Python
|
aoc2019/day22/inputs.py
|
shoreofwonder/adventofcode
|
15fd2f761533a48b456e510b0a59f7cbc64e8e91
|
[
"MIT"
] | null | null | null |
aoc2019/day22/inputs.py
|
shoreofwonder/adventofcode
|
15fd2f761533a48b456e510b0a59f7cbc64e8e91
|
[
"MIT"
] | null | null | null |
aoc2019/day22/inputs.py
|
shoreofwonder/adventofcode
|
15fd2f761533a48b456e510b0a59f7cbc64e8e91
|
[
"MIT"
] | null | null | null |
input_str = """
cut -135
deal with increment 38
deal into new stack
deal with increment 29
cut 120
deal with increment 30
deal into new stack
cut -7198
deal into new stack
deal with increment 59
cut -8217
deal with increment 75
cut 4868
deal with increment 29
cut 4871
deal with increment 2
deal into new stack
deal with increment 54
cut 777
deal with increment 40
cut -8611
deal with increment 3
cut -5726
deal with increment 57
deal into new stack
deal with increment 41
deal into new stack
cut -5027
deal with increment 12
cut -5883
deal with increment 45
cut 9989
deal with increment 14
cut 6535
deal with increment 18
cut -5544
deal with increment 29
deal into new stack
deal with increment 64
deal into new stack
deal with increment 41
deal into new stack
deal with increment 6
cut 4752
deal with increment 8
deal into new stack
deal with increment 26
cut -6635
deal with increment 10
deal into new stack
cut -3830
deal with increment 48
deal into new stack
deal with increment 39
cut -4768
deal with increment 65
deal into new stack
cut -5417
deal with increment 15
cut -4647
deal into new stack
cut -3596
deal with increment 17
cut -3771
deal with increment 50
cut 1682
deal into new stack
deal with increment 20
deal into new stack
deal with increment 22
deal into new stack
deal with increment 3
cut 8780
deal with increment 52
cut 7478
deal with increment 9
cut -8313
deal into new stack
cut 742
deal with increment 19
cut 9982
deal into new stack
deal with increment 68
cut 9997
deal with increment 23
cut -240
deal with increment 54
cut -7643
deal into new stack
deal with increment 6
cut -3493
deal with increment 74
deal into new stack
deal with increment 75
deal into new stack
deal with increment 40
cut 596
deal with increment 6
cut -4957
deal into new stack"""
inlist = [f.strip() for f in input_str.split('\n') if f.strip()]
| 17.590476
| 64
| 0.78993
| 347
| 1,847
| 4.198847
| 0.244957
| 0.236102
| 0.501716
| 0.252574
| 0.536033
| 0.381606
| 0.381606
| 0.109815
| 0.109815
| 0.070007
| 0
| 0.138574
| 0.187331
| 1,847
| 104
| 65
| 17.759615
| 0.832112
| 0
| 0
| 0.372549
| 0
| 0
| 0.955038
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
87a9aab3446b2719175272aa2fce174596919eb2
| 90
|
py
|
Python
|
Workers/MujeresExtraviadas.py
|
CodeandoLeon/desaparecidos
|
aac7d396dfae060e85ff3ff26d3fd2c6b4028dc7
|
[
"MIT"
] | null | null | null |
Workers/MujeresExtraviadas.py
|
CodeandoLeon/desaparecidos
|
aac7d396dfae060e85ff3ff26d3fd2c6b4028dc7
|
[
"MIT"
] | null | null | null |
Workers/MujeresExtraviadas.py
|
CodeandoLeon/desaparecidos
|
aac7d396dfae060e85ff3ff26d3fd2c6b4028dc7
|
[
"MIT"
] | null | null | null |
'''
Scraper for site http://www.ssp.gob.mx/extraviadosWeb/portals/extraviados.portal
'''
| 18
| 80
| 0.744444
| 12
| 90
| 5.583333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077778
| 90
| 4
| 81
| 22.5
| 0.807229
| 0.888889
| 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
|
87ab2a901647ffe87b14c9f1a93e2551edaf5e5e
| 240
|
py
|
Python
|
books/admin.py
|
gureuso/turnthepage
|
f86f4e6e80e4a817b06cc5c777d733cf8171310e
|
[
"Apache-2.0"
] | 1
|
2019-04-27T13:36:26.000Z
|
2019-04-27T13:36:26.000Z
|
books/admin.py
|
gureuso/turnthepage
|
f86f4e6e80e4a817b06cc5c777d733cf8171310e
|
[
"Apache-2.0"
] | 7
|
2020-06-05T20:21:29.000Z
|
2022-03-11T23:44:41.000Z
|
books/admin.py
|
gureuso/turnthepage
|
f86f4e6e80e4a817b06cc5c777d733cf8171310e
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from .models import Book, Page, Category, AdminCoupon, Coupon
admin.site.register(Book)
admin.site.register(Page)
admin.site.register(Category)
admin.site.register(AdminCoupon)
admin.site.register(Coupon)
| 24
| 61
| 0.8125
| 33
| 240
| 5.909091
| 0.393939
| 0.230769
| 0.435897
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.079167
| 240
| 9
| 62
| 26.666667
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.285714
| 0
| 0.285714
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
87cc197b8df95ea4cc146048d1881759cd87c42b
| 15,306
|
py
|
Python
|
EMDemo/tools/EMChecker.py
|
Tonyll/MyCode
|
0ba9d399b3f39515048c9b6da8998b7a288f28cd
|
[
"MIT"
] | null | null | null |
EMDemo/tools/EMChecker.py
|
Tonyll/MyCode
|
0ba9d399b3f39515048c9b6da8998b7a288f28cd
|
[
"MIT"
] | null | null | null |
EMDemo/tools/EMChecker.py
|
Tonyll/MyCode
|
0ba9d399b3f39515048c9b6da8998b7a288f28cd
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
__author__ = "xieyajie"
import os
import re
walk_path = '../'
# 规则和对应的警告
reg_dic = {
#EMClient
'\[EaseMob sharedInstance\]': 'Use EMClient',
'.loginInfo': 'Use EMClient currentUsername',
'.isAutoLoginEnabled': 'Use EMClient -options.isAutoLogin',
'.isUseIp': 'Use EMClient -options.enableDnsConfig',
'.isAutoDeleteConversationWhenLeaveGroup': '新版不再支持',
'.sdkVersion': 'Use EMClient version',
'setIsAutoFetchBuddyList:': '新版不再支持',
'importDataToNewDatabase': 'Use EMClient -dataMigrationTo3',
'loadDataFromDatabase': '新版不再支持',
'registerNewAccount:': 'Use EMClient -registerWithUsername:password:',
'asyncRegisterNewAccount:': 'Use EMClient -registerWithUsername:password:',
'chatManager loginWithUsername:': 'Use EMClient -loginWithUsername:password:error:',
'asyncLoginWithUsername:': 'Use EMClient -loginWithUsername:password:error:',
'logoffWithUnbindDeviceToken:': 'Use EMClient -logout:',
'asyncLogoffWithUnbindDeviceToken:': 'Use EMClient -logout:',
'registerSDKWithAppKey:': 'Use EMClient -initializeSDKWithOptions:',
'didRegisterNewAccount:': '新版不再支持,提供同步方法',
'didLoginWithInfo:': '新版不再支持,提供同步方法',
'didLogoffWithError:': '新版不再支持,提供同步方法',
'willAutoLoginWithInfo:': '新版不再支持',
'didAutoLoginWithInfo:': 'Use EMClientDelegate -didAutoLoginWithError:',
# 'didServersChanged': '新版不再支持',
# 'didAppkeyChanged': '新版不再支持',
'willAutoReconnect': 'Use EMUtilDelegate -didConnectionStateChanged:',
'didAutoReconnectFinishedWithError': 'Use EMUtilDelegate -didConnectionStateChanged:',
'IEMMessageBody': 'Use EMMessageBody',
'IEMFileMessageBody': 'Use EMFileMessageBody',
'IEMChatObject': '新版不再支持',
'IEMChatFile': '新版不再支持',
'IChatImageOptions': '新版不再支持',
'EMChatManagerDefs': '新版不再支持',
'didRegisterForRemoteNotificationsWithDeviceToken:': 'Use EMClient -bindDeviceToken:',
#Chat
'.requireEncryption': '新版不再支持',
'.isEncryptedOnServer': '新版不再支持',
'.isOfflineMessage': '新版不再支持',
'.isAnonymous': '新版不再支持',
'.messageBodies': 'Use EMMessage body',
'enableUnreadMessagesCountEvent': '新版不再支持',
'.conversations': 'Use IEMChatManager -getAllConversations',
'initWithReceiver:': 'Use EMMessage -initWithConversationID:from:to:body:ext:',
'initMessageWithID:': 'Use EMMessage -initWithConversationID:from:to:body:ext:',
'addMessageBody:': '新版不再支持',
'removeMessageBody:': '新版不再支持',
'updateMessageExtToDB': 'Use IEMChatManager -updateMessage:',
'updateMessageDeliveryStateToDB': 'Use IEMChatManager -updateMessage:',
'updateMessageBodiesToDB': 'Use IEMChatManager -updateMessage:',
'updateMessageStatusFailedToDB': 'Use IEMChatManager -updateMessage:',
'removeMessage:': 'Use EMConversation -deleteMessageWithId:',
'removeMessagesWithIds:': 'Use EMConversation -deleteMessageWithId:',
'markAllMessagesAsRead:': 'Use EMConversation -markAllMessagesAsRead',
'markMessageWithId:': 'Use EMConversation -markMessageAsReadWithId:',
'loadAllMessages': 'Use EMConversation -loadMoreMessagesFromId:limit:',
'loadMessagesWithIds:': 'Use EMConversation -loadMessageWithId:',
'loadNumbersOfMessages:': 'Use EMConversation -loadMoreMessagesFromId:limit:',
'sendMessage:': 'Use IEMChatManager -asyncSendMessage:progress:completion:',
'asyncSendMessage:': 'Use IEMChatManager -asyncSendMessage:progress:completion:',
'resendMessage:': 'Use IEMChatManager -asyncResendMessage:progress:completion:',
'asyncResendMessage:': 'Use IEMChatManager -asyncResendMessage:progress:completion:',
'fetchMessageThumbnail:': 'Use IEMChatManager -asyncDownloadMessageThumbnail:progress:completion:',
'asyncFetchMessageThumbnail:': 'Use IEMChatManager -asyncDownloadMessageThumbnail:progress:completion:',
'fetchMessage:': 'Use IEMChatManager -asyncDownloadMessageAttachments:progress:completion:',
'asyncFetchMessage:': 'Use IEMChatManager -asyncDownloadMessageAttachments:progress:completion:',
'conversationForChatter:': 'Use IEMChatManager -getConversation:type:createIfNotExist:',
'loadAllConversationsFromDatabaseWithAppend2Chat:': 'Use IEMChatManager -loadAllConversationsFromDB',
'insertConversationToDB:': 'Use IEMChatManager -importConversations:',
'insertConversationsToDB:': 'Use IEMChatManager -importConversations:',
'removeConversationByChatter:': 'Use IEMChatManager -deleteConversations:deleteMessages:',
'removeConversationsByChatters:': 'Use IEMChatManager -deleteConversation:deleteMessages:',
'removeAllConversationsWithDeleteMessages:': 'Use IEMChatManager -deleteAllConversationsWithDeleteMessages:',
'insertMessageToDB:': 'Use IEMChatManager -importMessages:',
'insertMessageToDB:': 'Use IEMChatManager -importMessages:',
'insertMessagesToDB:': 'Use IEMChatManager -importMessages:',
'insertMessagesToDB:': 'Use IEMChatManager -importMessages:',
'loadTotalUnreadMessagesCountFromDatabase': '新版不再支持',
'unreadMessagesCountForConversation:': '新版不再支持',
'searchMessagesWithCriteria:': '新版不再支持',
'EMChatImage': '新版不再支持',
'EMChatVoice': '新版不再支持',
'EMChatText': '新版不再支持',
'EMChatCommand': '新版不再支持',
'EMChatLocation': '新版不再支持',
'EMChatFile': '新版不再支持',
'EMChatVideo': '新版不再支持',
'EMReceipt': '新版不再支持',
'willSendMessage:': '新版不再支持,提供block方法',
'didSendMessage:': '新版不再支持,提供block方法',
'didReceiveMessageId:': 'Use EMChatManagerDelegate -didMessageStatusChanged:error:',
'didReceiveMessage:': 'Use EMChatManagerDelegate -didReceiveMessages:',
'didReceiveCmdMessage:': 'Use EMChatManagerDelegate -didReceiveCmdMessages:',
'didFetchingMessageAttachments:': '新版不再支持,提供block方法',
'didFetchMessage:': '新版不再支持,提供block方法',
'didFetchMessageThumbnail:': '新版不再支持,提供block方法',
'didReceiveHasReadResponse:': 'Use EMChatManagerDelegate -didReceiveHasReadAcks:',
'didReceiveHasDeliveredResponse:': 'Use EMChatManagerDelegate -didReceiveHasDeliveredAcks:',
'didUnreadMessagesCountChanged': '新版不再支持',
'willReceiveOfflineMessages': '新版不再支持',
'didReceiveOfflineMessages:': 'Use EMChatManagerDelegate -didReceiveMessages:',
'didReceiveOfflineCmdMessages:': 'Use EMChatManagerDelegate -didReceiveCmdMessages:',
'didFinishedReceiveOfflineMessages': '新版不再支持',
'didFinishedReceiveOfflineCmdMessages': '新版不再支持',
#Contact
'EMBuddy': '新版不再支持，请使用NSString',
'buddyWithUsername:': '新版不再支持EMBuddy',
'.followState': '新版不再支持EMBuddy',
'.isPendingApproval': '新版不再支持EMBuddy',
'.buddyList': '新版不再支持, 提供获取接口, 需自己维护',
'.blockedList': '新版不再支持, 提供获取接口, 需自己维护',
'EMBuddyFollowState': '新版不再支持, 新版不再支持EMBuddy',
'eEMBuddyFollowState_NotFollowed': '新版不再支持, 新版不再支持EMBuddy',
'eEMBuddyFollowState_Followed': '新版不再支持, 新版不再支持EMBuddy',
'eEMBuddyFollowState_BeFollowed': '新版不再支持, 新版不再支持EMBuddy',
'eEMBuddyFollowState_FollowedBoth': '新版不再支持, 新版不再支持EMBuddy',
'EMRelationship': '新版不再支持',
'eRelationshipBoth': '新版不再支持',
'eRelationshipFrom': '新版不再支持',
'eRelationshipTo': '新版不再支持',
'fetchBuddyListWithError:': 'Use IEMContactManager -getContactsFromServerWithError:',
'asyncFetchBuddyList': 'Use IEMContactManager -getContactsFromServerWithError:',
'asyncFetchBuddyListWithCompletion:': 'Use IEMContactManager -getContactsFromServerWithError:',
'addBuddy:': 'Use IEMContactManager -addContact:message:',
'removeBuddy:': 'Use IEMContactManager -deleteContact:',
'acceptBuddyRequest:': 'Use IEMContactManager -acceptInvitationForUsername:',
'rejectBuddyRequest:': 'Use IEMContactManager -declineInvitationForUsername:',
'fetchBlockedList:': 'Use IEMContactManager -getBlackListFromServerWithError:',
'asyncFetchBlockedList': 'Use IEMContactManager -getBlackListFromServerWithError:',
'asyncFetchBlockedListWithCompletion:': 'Use IEMContactManager -getBlackListFromServerWithError:',
'blockBuddy:': 'Use IEMContactManager -addUserToBlackList:relationship:',
'asyncBlockBuddy:': 'Use IEMContactManager -addUserToBlackList:relationship:',
'unblockBuddy:': 'Use IEMContactManager -deleteContactFromBlackList:',
'asyncUnblockBuddy:': 'Use IEMContactManager -deleteContactFromBlackList:',
'didAcceptBuddySucceed:': 'Use EMContactManagerDelegate -didReceiveAddedFromUsernames:',
'didUpdateBuddyList:': '新版不再支持, 提供获取好友接口',
'didFetchedBuddyList:': '新版不再支持, 提供同步获取好友接口',
'didUpdateBlockedList:': '新版不再支持, 提供获取黑名单接口',
'didBlockBuddy:': '新版不再支持, 提供同步加黑名单接口',
'didUnblockBuddy:': '新版不再支持, 提供同步减黑名单接口',
#Group
'.groupOnlineOccupantsCount': '新版不再支持',
'.groupList': 'Use IEMGroupManager -loadAllMyGroupsFromDB',
'occupantWithUsername:': '新版不再支持',
'nicknameForAccount:': '新版不再支持',
'loadAllMyGroupsFromDatabaseWithAppend2Chat:': 'Use IEMGroupManager -loadAllMyGroupsFromDB',
'chatManager createGroupWithSubject:': 'Use IEMGroupManager -createGroupWithSubject:description:invitees:message:setting:error:',
'asyncCreateGroupWithSubject:': 'Use IEMGroupManager -createGroupWithSubject:description:invitees:message:setting:error:',
'createAnonymousGroupWithSubject:': '新版不再提供',
'asyncCreateAnonymousGroupWithSubject:': '新版不再提供',
'joinAnonymousPublicGroup:': '新版不再提供',
'asyncJoinAnonymousPublicGroup:': '新版不再提供',
'asyncLeaveGroup:': 'Use IEMGroupManager -leaveGroup:error:',
'asyncDestroyGroup:': 'Use IEMGroupManager -leaveGroup:error:',
'asyncAddOccupants:': 'Use IEMGroupManager -addOccupants:toGroup:welcomeMessage:error:',
'asyncRemoveOccupants:': 'Use IEMGroupManager -removeOccupants:fromGroup:error:',
'asyncBlockOccupants:': 'Use IEMGroupManager -blockOccupants:fromGroup:error:',
'asyncUnblockOccupants:': 'Use IEMGroupManager -unblockOccupants:forGroup:error:',
'asyncChangeGroupSubject:': 'Use IEMGroupManager -changeGroupSubject:forGroup:error:',
'asyncChangeDescription:': 'Use IEMGroupManager -changeDescription:forGroup:error:',
'acceptApplyJoinGroup:': 'Use IEMGroupManager -acceptJoinApplication:groupname:applicant:reason:',
'asyncAcceptApplyJoinGroup:': 'Use IEMGroupManager -acceptJoinApplication:groupname:applicant:reason:',
'chatManager fetchGroupInfo:': 'Use IEMGroupManager -fetchGroupInfo:includeMembersList:error:',
'asyncFetchGroupInfo:': 'Use IEMGroupManager -fetchGroupInfo:includeMembersList:error:',
'fetchOccupantList:': 'Use IEMGroupManager -fetchGroupInfo:includeMembersList:error:',
'asyncFetchOccupantList:': 'Use IEMGroupManager -fetchGroupInfo:includeMembersList:error:',
'asyncFetchGroupBansList:': 'Use IEMGroupManager -fetchGroupBansList:error:',
'asyncFetchMyGroupsList': 'Use IEMGroupManager -getMyGroupsFromServerWithError:',
'chatManager fetchPublicGroupsFromServerWithCursor:': 'Use IEMGroupManager -getPublicGroupsFromServerWithCursor:pageSize:error:',
'asyncFetchPublicGroupsFromServerWithCursor:': 'Use IEMGroupManager -getPublicGroupsFromServerWithCursor:pageSize:error:',
'fetchAllPublicGroupsWithError:': 'Use IEMGroupManager -getPublicGroupsFromServerWithCursor:pageSize:error:',
'asyncFetchAllPublicGroups': 'Use IEMGroupManager -getPublicGroupsFromServerWithCursor:pageSize:error:',
'asyncJoinPublicGroup:': 'Use IEMGroupManager -joinPublicGroup:error:',
'chatManager applyJoinPublicGroup:': 'Use IEMGroupManager -applyJoinPublicGroup:groupSubject:message:error:',
'asyncApplyJoinPublicGroup:': 'Use IEMGroupManager -applyJoinPublicGroup:groupSubject:message:error:',
'asyncSearchPublicGroupWithGroupId:': 'Use IEMGroupManager -searchPublicGroupWithId:error:',
'asyncBlockGroup:': 'Use IEMGroupManager -ignoreGroupPush:ignore:',
'asyncUnblockGroup:': 'Use IEMGroupManager -ignoreGroupPush:ignore:',
'rejectApplyJoinGroup:': 'Use IEMGroupManager -declineApplication:groupname:applicant:reason:',
' didCreateWithError:': '新版不再支持，提供同步接口',
' didLeave:': 'Use EMGroupManagerDelegate -didReceiveLeavedGroup:reason:',
'groupDidUpdateInfo:': '新版不再支持，提供同步接口',
'didAcceptInvitationFromGroup:': 'Use EMGroupManagerDelegate -didJoinedGroup:inviter:message:',
'didReceiveGroupInvitationFrom:': 'Use EMGroupManagerDelegate -didReceiveGroupInvitation:inviter:message:',
'didReceiveGroupRejectFrom:': 'Use EMGroupManagerDelegate -didReceiveDeclinedGroupInvitation:invitee:reason:',
'didReceiveApplyToJoinGroup:': 'Use EMGroupManagerDelegate -didReceiveJoinGroupApplication:applicant:reason:',
'didReceiveRejectApplyToJoinGroupFrom:': 'Use EMGroupManagerDelegate -didReceiveDeclinedJoinGroup:reason:',
'didReceiveAcceptApplyToJoinGroup:': 'Use EMGroupManagerDelegate -didReceiveAcceptedJoinGroup:',
'didAcceptApplyJoinGroup:': '新版不再支持',
'didUpdateGroupList:': 'Use EMGroupManagerDelegate -didUpdateGroupList:',
'didFetchAllPublicGroups:': '新版不再支持',
'didFetchGroupInfo:': '新版不再支持',
'didFetchGroupOccupantsList:': '新版不再支持',
'didFetchGroupBans:': '新版不再支持',
'didJoinPublicGroup:': '新版不再支持',
'didApplyJoinPublicGroup:': '新版不再支持',
#ChatRoom
' occupantDidJoin:': 'Use EMChatroomManagerDelegate -didReceiveUserJoinedChatroom:username:',
' occupantDidLeave:': 'Use EMChatroomManagerDelegate -didReceiveUserLeavedChatroom:username:',
'joinChatroom:': 'Use IEMChatroomManager -joinChatroom:error:',
'asyncJoinChatroom:': 'Use IEMChatroomManager -joinChatroom:error:',
'leaveChatroom:': 'Use IEMChatroomManager -leaveChatroom:error:',
'asyncLeaveChatroom:': 'Use IEMChatroomManager -leaveChatroom:error:',
'fetchChatroomsFromServerWithCursor:': '新版不再支持',
'asyncFetchChatroomsFromServerWithCursor:': '新版不再支持',
'fetchChatroomInfo:': '新版不再支持',
'asyncFetchChatroomInfo:': '新版不再支持',
'fetchOccupantsForChatroom:': '新版不再支持',
'asyncFetchOccupantsForChatroom:': '新版不再支持',
#Call
'callSessionStatusChanged:': '请使用EMCallManagerDelegate中的新版回调',
'initWithSessionId:': '新版不再支持，不允许用户自己创建通话实例',
'asyncMakeVoiceCall:': 'Use IEMCallManager -makeVoiceCall:error:',
'asyncMakeVideoCall:': 'Use IEMCallManager -makeVideoCall:error:',
#Apns
'didUpdatePushOptions:': '新版不再支持,提供同步方法',
'didIgnoreGroupPushNotification:': '新版不再支持,提供同步方法',
#Error
'errorWithCode:': 'Use EMError +errorWithDomain:code:',
'errorWithNSError:': 'Use EMError +errorWithDomain:code:',
}
def log_warning(file_path, line_number, description):
print '{0}:{1}: error: {2}'.format(file_path, line_number, description)
def check_main(root_path):
for root, dirs, files in os.walk(root_path):
for file_path in files:
if file_path.endswith('.m'):
full_path = os.path.join(root, file_path)
# 不检查 pod 第三方库
if 'Pods/' in full_path:
break
fr = open(full_path, 'r')
content = fr.read()
fr.close()
for key in reg_dic:
match = re.search(key, content)
if match:
substring = content[:match.regs[0][1]]
line_match = re.findall('\n', substring)
line_number = len(line_match) + 1
log_warning(full_path, line_number, reg_dic[key])
if __name__ == '__main__':
check_main(walk_path)
| 59.096525
| 133
| 0.744087
| 964
| 15,306
| 11.770747
| 0.424274
| 0.049176
| 0.010575
| 0.017626
| 0.15167
| 0.055433
| 0.033401
| 0.013748
| 0
| 0
| 0
| 0.00075
| 0.129034
| 15,306
| 258
| 134
| 59.325581
| 0.850424
| 0.010127
| 0
| 0.017021
| 0
| 0
| 0.766517
| 0.423956
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.017021
| 0.038298
| null | null | 0.004255
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
355f1dcd98330ce88c39bf8fb6a16eec31483a37
| 491
|
py
|
Python
|
6_kyu/split_strings.py
|
resulemreaygan/codewars
|
153c6cc8b285164ff0ebea1c041949be0ebeb925
|
[
"MIT"
] | null | null | null |
6_kyu/split_strings.py
|
resulemreaygan/codewars
|
153c6cc8b285164ff0ebea1c041949be0ebeb925
|
[
"MIT"
] | null | null | null |
6_kyu/split_strings.py
|
resulemreaygan/codewars
|
153c6cc8b285164ff0ebea1c041949be0ebeb925
|
[
"MIT"
] | null | null | null |
import re
"""
Author: Resul Emre AYGAN
"""
"""
Project Description: Split Strings
Complete the solution so that it splits the string into pairs of two characters.
If the string contains an odd number of characters
then it should replace the missing second character of the final pair with an underscore ('_').
Examples:
solution('abc') # should return ['ab', 'c_']
solution('abcdef') # should return ['ab', 'cd', 'ef']
"""
def split_strings(s):
return re.findall(".{2}", s + "_")
| 21.347826
| 95
| 0.698574
| 71
| 491
| 4.774648
| 0.704225
| 0.070796
| 0.082596
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002463
| 0.173116
| 491
| 22
| 96
| 22.318182
| 0.832512
| 0
| 0
| 0
| 0
| 0
| 0.064935
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
358614597a29d6509d8a1bd05953e1fbae3ae513
| 118
|
py
|
Python
|
AI Class Module/Assignment 1/data.py
|
apnatvar/ML-AI-Deep-Learning
|
1e780b58c36b29c538a6b48342e90d1176c5677f
|
[
"MIT"
] | null | null | null |
AI Class Module/Assignment 1/data.py
|
apnatvar/ML-AI-Deep-Learning
|
1e780b58c36b29c538a6b48342e90d1176c5677f
|
[
"MIT"
] | null | null | null |
AI Class Module/Assignment 1/data.py
|
apnatvar/ML-AI-Deep-Learning
|
1e780b58c36b29c538a6b48342e90d1176c5677f
|
[
"MIT"
] | null | null | null |
def computeCI(principal, roi, time):
ci = (principal*pow((1+(roi/100)), time))-principal
return round(ci, 2)
| 23.6
| 55
| 0.644068
| 17
| 118
| 4.470588
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05102
| 0.169492
| 118
| 4
| 56
| 29.5
| 0.72449
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 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
|
35bb4b9d6ce08989581e3e97b0ad80fa7a960401
| 190
|
py
|
Python
|
gitftp/common.py
|
petervanderdoes/git-ftp
|
ac6916dbbabb39e1e45b88ac7d5aa90d55bc4f37
|
[
"MIT"
] | 2
|
2018-06-06T13:19:08.000Z
|
2020-05-09T04:23:27.000Z
|
gitftp/common.py
|
petervanderdoes/git-ftp
|
ac6916dbbabb39e1e45b88ac7d5aa90d55bc4f37
|
[
"MIT"
] | null | null | null |
gitftp/common.py
|
petervanderdoes/git-ftp
|
ac6916dbbabb39e1e45b88ac7d5aa90d55bc4f37
|
[
"MIT"
] | null | null | null |
# Standard Library
import os
def get_empty_tree(repo):
return repo.tree(repo.git.hash_object('-w', '-t', 'tree', os.devnull))
def format_mode(mode):
return "%o" % (mode & 0o777)
| 17.272727
| 74
| 0.657895
| 29
| 190
| 4.172414
| 0.689655
| 0.132231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025316
| 0.168421
| 190
| 10
| 75
| 19
| 0.740506
| 0.084211
| 0
| 0
| 0
| 0
| 0.05814
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0.2
| 0.4
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
35da87f4f1aa3beff126f0bcc2a8ae879d35b8e7
| 385
|
py
|
Python
|
src/cbc_sdk/credential_providers/__init__.py
|
fslds/carbon-black-cloud-sdk-python
|
248a3c63d6b36d6fcdbcb3f51fb7751f062ed372
|
[
"MIT"
] | 24
|
2020-10-16T22:07:38.000Z
|
2022-03-24T14:58:03.000Z
|
src/cbc_sdk/credential_providers/__init__.py
|
fslds/carbon-black-cloud-sdk-python
|
248a3c63d6b36d6fcdbcb3f51fb7751f062ed372
|
[
"MIT"
] | 63
|
2020-10-26T18:26:15.000Z
|
2022-03-31T17:31:02.000Z
|
src/cbc_sdk/credential_providers/__init__.py
|
fslds/carbon-black-cloud-sdk-python
|
248a3c63d6b36d6fcdbcb3f51fb7751f062ed372
|
[
"MIT"
] | 10
|
2020-11-09T11:54:23.000Z
|
2022-03-24T20:44:00.000Z
|
from __future__ import absolute_import
from .file_credential_provider import FileCredentialProvider
from .environ_credential_provider import EnvironCredentialProvider
from .registry_credential_provider import RegistryCredentialProvider
import platform
# Only import if macOS
if platform.system() == 'Darwin':
from .keychain_credential_provider import KeychainCredentialProvider
| 32.083333
| 72
| 0.867532
| 39
| 385
| 8.230769
| 0.512821
| 0.224299
| 0.299065
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098701
| 385
| 11
| 73
| 35
| 0.925072
| 0.051948
| 0
| 0
| 0
| 0
| 0.016529
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.857143
| 0
| 0.857143
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ea1d0209585871968ca559adf893aeb588efdcee
| 24,482
|
py
|
Python
|
tensorflow_checkpoint_reader/pb/tensorflow/core/framework/summary_pb2.py
|
shawwn/tensorflow-checkpoint-reader
|
f0e65548411e3bd66a07e36bb1850907a05952d0
|
[
"MIT"
] | 1
|
2021-12-02T15:06:09.000Z
|
2021-12-02T15:06:09.000Z
|
tensorflow_checkpoint_reader/pb/tensorflow/core/framework/summary_pb2.py
|
shawwn/tensorflow-checkpoint-reader
|
f0e65548411e3bd66a07e36bb1850907a05952d0
|
[
"MIT"
] | null | null | null |
tensorflow_checkpoint_reader/pb/tensorflow/core/framework/summary_pb2.py
|
shawwn/tensorflow-checkpoint-reader
|
f0e65548411e3bd66a07e36bb1850907a05952d0
|
[
"MIT"
] | null | null | null |
'Generated protocol buffer code.'
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
_sym_db = _symbol_database.Default()
from ....tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
DESCRIPTOR = _descriptor.FileDescriptor(name='tensorflow/core/framework/summary.proto', package='tensorflow', syntax='proto3', serialized_options=b'\n\x18org.tensorflow.frameworkB\rSummaryProtosP\x01ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/summary_go_proto\xf8\x01\x01', create_key=_descriptor._internal_create_key, serialized_pb=b'\n\'tensorflow/core/framework/summary.proto\x12\ntensorflow\x1a&tensorflow/core/framework/tensor.proto"\'\n\x12SummaryDescription\x12\x11\n\ttype_hint\x18\x01 \x01(\t"\x87\x01\n\x0eHistogramProto\x12\x0b\n\x03min\x18\x01 \x01(\x01\x12\x0b\n\x03max\x18\x02 \x01(\x01\x12\x0b\n\x03num\x18\x03 \x01(\x01\x12\x0b\n\x03sum\x18\x04 \x01(\x01\x12\x13\n\x0bsum_squares\x18\x05 \x01(\x01\x12\x18\n\x0cbucket_limit\x18\x06 \x03(\x01B\x02\x10\x01\x12\x12\n\x06bucket\x18\x07 \x03(\x01B\x02\x10\x01"\xe0\x01\n\x0fSummaryMetadata\x12;\n\x0bplugin_data\x18\x01 \x01(\x0b2&.tensorflow.SummaryMetadata.PluginData\x12\x14\n\x0cdisplay_name\x18\x02 \x01(\t\x12\x1b\n\x13summary_description\x18\x03 \x01(\t\x12)\n\ndata_class\x18\x04 \x01(\x0e2\x15.tensorflow.DataClass\x1a2\n\nPluginData\x12\x13\n\x0bplugin_name\x18\x01 \x01(\t\x12\x0f\n\x07content\x18\x02 \x01(\x0c"\xde\x04\n\x07Summary\x12(\n\x05value\x18\x01 \x03(\x0b2\x19.tensorflow.Summary.Value\x1aX\n\x05Image\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x12\n\ncolorspace\x18\x03 \x01(\x05\x12\x1c\n\x14encoded_image_string\x18\x04 \x01(\x0c\x1a}\n\x05Audio\x12\x13\n\x0bsample_rate\x18\x01 \x01(\x02\x12\x14\n\x0cnum_channels\x18\x02 \x01(\x03\x12\x15\n\rlength_frames\x18\x03 \x01(\x03\x12\x1c\n\x14encoded_audio_string\x18\x04 \x01(\x0c\x12\x14\n\x0ccontent_type\x18\x05 \x01(\t\x1a\xcf\x02\n\x05Value\x12\x11\n\tnode_name\x18\x07 \x01(\t\x12\x0b\n\x03tag\x18\x01 \x01(\t\x12-\n\x08metadata\x18\t \x01(\x0b2\x1b.tensorflow.SummaryMetadata\x12\x16\n\x0csimple_value\x18\x02 \x01(\x02H\x00\x12&\n\x1cobsolete_old_style_histogram\x18\x03 \x01(\x0cH\x00\x12*\n\x05image\x18\x04 \x01(\x0b2\x19.tensorflow.Summary.ImageH\x00\x12+\n\x05histo\x18\x05 \x01(\x0b2\x1a.tensorflow.HistogramProtoH\x00\x12*\n\x05audio\x18\x06 \x01(\x0b2\x19.tensorflow.Summary.AudioH\x00\x12)\n\x06tensor\x18\x08 \x01(\x0b2\x17.tensorflow.TensorProtoH\x00B\x07\n\x05value*o\n\tDataClass\x12\x16\n\x12DATA_CLASS_UNKNOWN\x10\x00\x12\x15\n\x11DATA_CLASS_SCALAR\x10\x01\x12\x15\n\x11DATA_CLASS_TENSOR\x10\x02\x12\x1c\n\x18DATA_CLASS_BLOB_SEQUENCE\x10\x03B~\n\x18org.tensorflow.frameworkB\rSummaryProtosP\x01ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/summary_go_proto\xf8\x01\x01b\x06proto3', dependencies=[tensorflow_dot_core_dot_framework_dot_tensor__pb2.DESCRIPTOR])
_DATACLASS = _descriptor.EnumDescriptor(name='DataClass', full_name='tensorflow.DataClass', filename=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, values=[_descriptor.EnumValueDescriptor(name='DATA_CLASS_UNKNOWN', index=0, number=0, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor(name='DATA_CLASS_SCALAR', index=1, number=1, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor(name='DATA_CLASS_TENSOR', index=2, number=2, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor(name='DATA_CLASS_BLOB_SEQUENCE', index=3, number=3, serialized_options=None, type=None, create_key=_descriptor._internal_create_key)], containing_type=None, serialized_options=None, serialized_start=1110, serialized_end=1221)
_sym_db.RegisterEnumDescriptor(_DATACLASS)
DataClass = enum_type_wrapper.EnumTypeWrapper(_DATACLASS)
DATA_CLASS_UNKNOWN = 0
DATA_CLASS_SCALAR = 1
DATA_CLASS_TENSOR = 2
DATA_CLASS_BLOB_SEQUENCE = 3
_SUMMARYDESCRIPTION = _descriptor.Descriptor(name='SummaryDescription', full_name='tensorflow.SummaryDescription', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='type_hint', full_name='tensorflow.SummaryDescription.type_hint', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=95, serialized_end=134)
_HISTOGRAMPROTO = _descriptor.Descriptor(name='HistogramProto', full_name='tensorflow.HistogramProto', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='min', full_name='tensorflow.HistogramProto.min', index=0, number=1, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='max', full_name='tensorflow.HistogramProto.max', index=1, number=2, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='num', full_name='tensorflow.HistogramProto.num', index=2, number=3, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='sum', full_name='tensorflow.HistogramProto.sum', index=3, number=4, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='sum_squares', full_name='tensorflow.HistogramProto.sum_squares', index=4, number=5, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='bucket_limit', full_name='tensorflow.HistogramProto.bucket_limit', index=5, number=6, type=1, cpp_type=5, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\x10\x01', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='bucket', full_name='tensorflow.HistogramProto.bucket', index=6, number=7, type=1, cpp_type=5, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\x10\x01', file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=137, serialized_end=272)
_SUMMARYMETADATA_PLUGINDATA = _descriptor.Descriptor(name='PluginData', full_name='tensorflow.SummaryMetadata.PluginData', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='plugin_name', full_name='tensorflow.SummaryMetadata.PluginData.plugin_name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='content', full_name='tensorflow.SummaryMetadata.PluginData.content', index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b'', message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=449, serialized_end=499)
_SUMMARYMETADATA = _descriptor.Descriptor(name='SummaryMetadata', full_name='tensorflow.SummaryMetadata', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='plugin_data', full_name='tensorflow.SummaryMetadata.plugin_data', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='display_name', full_name='tensorflow.SummaryMetadata.display_name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='summary_description', full_name='tensorflow.SummaryMetadata.summary_description', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='data_class', full_name='tensorflow.SummaryMetadata.data_class', index=3, number=4, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[_SUMMARYMETADATA_PLUGINDATA], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=275, serialized_end=499)
_SUMMARY_IMAGE = _descriptor.Descriptor(name='Image', full_name='tensorflow.Summary.Image', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='height', full_name='tensorflow.Summary.Image.height', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='width', full_name='tensorflow.Summary.Image.width', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='colorspace', full_name='tensorflow.Summary.Image.colorspace', index=2, number=3, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='encoded_image_string', full_name='tensorflow.Summary.Image.encoded_image_string', index=3, number=4, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b'', message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=555, serialized_end=643)
_SUMMARY_AUDIO = _descriptor.Descriptor(name='Audio', full_name='tensorflow.Summary.Audio', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='sample_rate', full_name='tensorflow.Summary.Audio.sample_rate', index=0, number=1, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='num_channels', full_name='tensorflow.Summary.Audio.num_channels', index=1, number=2, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='length_frames', full_name='tensorflow.Summary.Audio.length_frames', index=2, number=3, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='encoded_audio_string', full_name='tensorflow.Summary.Audio.encoded_audio_string', index=3, number=4, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b'', message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='content_type', full_name='tensorflow.Summary.Audio.content_type', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=645, serialized_end=770)
_SUMMARY_VALUE = _descriptor.Descriptor(name='Value', full_name='tensorflow.Summary.Value', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='node_name', full_name='tensorflow.Summary.Value.node_name', index=0, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='tag', full_name='tensorflow.Summary.Value.tag', index=1, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b''.decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='metadata', full_name='tensorflow.Summary.Value.metadata', index=2, number=9, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='simple_value', full_name='tensorflow.Summary.Value.simple_value', index=3, number=2, type=2, cpp_type=6, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='obsolete_old_style_histogram', full_name='tensorflow.Summary.Value.obsolete_old_style_histogram', index=4, number=3, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b'', message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='image', full_name='tensorflow.Summary.Value.image', index=5, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='histo', full_name='tensorflow.Summary.Value.histo', index=6, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='audio', full_name='tensorflow.Summary.Value.audio', index=7, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor(name='tensor', full_name='tensorflow.Summary.Value.tensor', index=8, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[_descriptor.OneofDescriptor(name='value', full_name='tensorflow.Summary.Value.value', index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[])], serialized_start=773, serialized_end=1108)
_SUMMARY = _descriptor.Descriptor(name='Summary', full_name='tensorflow.Summary', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[_descriptor.FieldDescriptor(name='value', full_name='tensorflow.Summary.value', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key)], extensions=[], nested_types=[_SUMMARY_IMAGE, _SUMMARY_AUDIO, _SUMMARY_VALUE], enum_types=[], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[], serialized_start=502, serialized_end=1108)
_SUMMARYMETADATA_PLUGINDATA.containing_type = _SUMMARYMETADATA
_SUMMARYMETADATA.fields_by_name['plugin_data'].message_type = _SUMMARYMETADATA_PLUGINDATA
_SUMMARYMETADATA.fields_by_name['data_class'].enum_type = _DATACLASS
_SUMMARY_IMAGE.containing_type = _SUMMARY
_SUMMARY_AUDIO.containing_type = _SUMMARY
_SUMMARY_VALUE.fields_by_name['metadata'].message_type = _SUMMARYMETADATA
_SUMMARY_VALUE.fields_by_name['image'].message_type = _SUMMARY_IMAGE
_SUMMARY_VALUE.fields_by_name['histo'].message_type = _HISTOGRAMPROTO
_SUMMARY_VALUE.fields_by_name['audio'].message_type = _SUMMARY_AUDIO
_SUMMARY_VALUE.fields_by_name['tensor'].message_type = tensorflow_dot_core_dot_framework_dot_tensor__pb2._TENSORPROTO
_SUMMARY_VALUE.containing_type = _SUMMARY
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['simple_value'])
_SUMMARY_VALUE.fields_by_name['simple_value'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['obsolete_old_style_histogram'])
_SUMMARY_VALUE.fields_by_name['obsolete_old_style_histogram'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['image'])
_SUMMARY_VALUE.fields_by_name['image'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['histo'])
_SUMMARY_VALUE.fields_by_name['histo'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['audio'])
_SUMMARY_VALUE.fields_by_name['audio'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY_VALUE.oneofs_by_name['value'].fields.append(_SUMMARY_VALUE.fields_by_name['tensor'])
_SUMMARY_VALUE.fields_by_name['tensor'].containing_oneof = _SUMMARY_VALUE.oneofs_by_name['value']
_SUMMARY.fields_by_name['value'].message_type = _SUMMARY_VALUE
DESCRIPTOR.message_types_by_name['SummaryDescription'] = _SUMMARYDESCRIPTION
DESCRIPTOR.message_types_by_name['HistogramProto'] = _HISTOGRAMPROTO
DESCRIPTOR.message_types_by_name['SummaryMetadata'] = _SUMMARYMETADATA
DESCRIPTOR.message_types_by_name['Summary'] = _SUMMARY
DESCRIPTOR.enum_types_by_name['DataClass'] = _DATACLASS
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
SummaryDescription = _reflection.GeneratedProtocolMessageType('SummaryDescription', (_message.Message,), {'DESCRIPTOR': _SUMMARYDESCRIPTION, '__module__': 'tensorflow.core.framework.summary_pb2'})
_sym_db.RegisterMessage(SummaryDescription)
HistogramProto = _reflection.GeneratedProtocolMessageType('HistogramProto', (_message.Message,), {'DESCRIPTOR': _HISTOGRAMPROTO, '__module__': 'tensorflow.core.framework.summary_pb2'})
_sym_db.RegisterMessage(HistogramProto)
SummaryMetadata = _reflection.GeneratedProtocolMessageType('SummaryMetadata', (_message.Message,), {'PluginData': _reflection.GeneratedProtocolMessageType('PluginData', (_message.Message,), {'DESCRIPTOR': _SUMMARYMETADATA_PLUGINDATA, '__module__': 'tensorflow.core.framework.summary_pb2'}), 'DESCRIPTOR': _SUMMARYMETADATA, '__module__': 'tensorflow.core.framework.summary_pb2'})
_sym_db.RegisterMessage(SummaryMetadata)
_sym_db.RegisterMessage(SummaryMetadata.PluginData)
Summary = _reflection.GeneratedProtocolMessageType('Summary', (_message.Message,), {'Image': _reflection.GeneratedProtocolMessageType('Image', (_message.Message,), {'DESCRIPTOR': _SUMMARY_IMAGE, '__module__': 'tensorflow.core.framework.summary_pb2'}), 'Audio': _reflection.GeneratedProtocolMessageType('Audio', (_message.Message,), {'DESCRIPTOR': _SUMMARY_AUDIO, '__module__': 'tensorflow.core.framework.summary_pb2'}), 'Value': _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), {'DESCRIPTOR': _SUMMARY_VALUE, '__module__': 'tensorflow.core.framework.summary_pb2'}), 'DESCRIPTOR': _SUMMARY, '__module__': 'tensorflow.core.framework.summary_pb2'})
_sym_db.RegisterMessage(Summary)
_sym_db.RegisterMessage(Summary.Image)
_sym_db.RegisterMessage(Summary.Audio)
_sym_db.RegisterMessage(Summary.Value)
DESCRIPTOR._options = None
_HISTOGRAMPROTO.fields_by_name['bucket_limit']._options = None
_HISTOGRAMPROTO.fields_by_name['bucket']._options = None
| 344.816901
| 3,966
| 0.829262
| 3,403
| 24,482
| 5.617103
| 0.074346
| 0.047293
| 0.075543
| 0.0678
| 0.722312
| 0.641224
| 0.612869
| 0.594925
| 0.592781
| 0.565734
| 0
| 0.035176
| 0.040846
| 24,482
| 70
| 3,967
| 349.742857
| 0.778852
| 0.001266
| 0
| 0
| 1
| 0.884058
| 0.145215
| 0.097504
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.086957
| 0
| 0.086957
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ea3dfabbb5358f5b9f565cc5230403444a2a308f
| 631
|
py
|
Python
|
cep_address/exceptions.py
|
sallve/cep_address
|
0ce76fb1f5c20d3569a5cd27b8ab8be43ffd3c66
|
[
"MIT"
] | 4
|
2020-09-28T14:27:07.000Z
|
2022-01-05T13:33:07.000Z
|
cep_address/exceptions.py
|
sallve/cep_address
|
0ce76fb1f5c20d3569a5cd27b8ab8be43ffd3c66
|
[
"MIT"
] | null | null | null |
cep_address/exceptions.py
|
sallve/cep_address
|
0ce76fb1f5c20d3569a5cd27b8ab8be43ffd3c66
|
[
"MIT"
] | 1
|
2022-01-31T17:06:20.000Z
|
2022-01-31T17:06:20.000Z
|
class ServiceError(Exception):
def __init__(self, service, message=""):
self.service = service
self.message = message
def __str__(self):
return f"ServiceError has been raised in {self.service}\n{self.message}"
class ValidationError(Exception):
def __init__(self, message=""):
self.message = message
def __str__(self):
return f"ValidationError has been raised, {self.message}"
class InvalidCepLength(Exception):
def __init__(self, message=""):
self.message = message
def __str__(self):
return f"InvalidCepLength has been raised, {self.message}"
| 26.291667
| 80
| 0.66878
| 71
| 631
| 5.605634
| 0.253521
| 0.221106
| 0.120603
| 0.150754
| 0.520101
| 0.399497
| 0.399497
| 0.399497
| 0.311558
| 0.311558
| 0
| 0
| 0.22187
| 631
| 23
| 81
| 27.434783
| 0.810591
| 0
| 0
| 0.5
| 0
| 0
| 0.248811
| 0.047544
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0.1875
| 0.75
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
ea6b2cb87f154e4fc533a393c3d49dce38ab044e
| 47
|
py
|
Python
|
blocklenium/__init__.py
|
jpunkt/blocklenium
|
dbe81b900d9c9781443d2cac2920815cb5f0a779
|
[
"MIT"
] | null | null | null |
blocklenium/__init__.py
|
jpunkt/blocklenium
|
dbe81b900d9c9781443d2cac2920815cb5f0a779
|
[
"MIT"
] | 1
|
2020-07-17T10:11:42.000Z
|
2020-07-17T14:44:59.000Z
|
blocklenium/__init__.py
|
jpunkt/blocklenium
|
dbe81b900d9c9781443d2cac2920815cb5f0a779
|
[
"MIT"
] | null | null | null |
from .main import main
__version__ = '0.0.1'
| 9.4
| 22
| 0.680851
| 8
| 47
| 3.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078947
| 0.191489
| 47
| 4
| 23
| 11.75
| 0.657895
| 0
| 0
| 0
| 0
| 0
| 0.106383
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ea722964331ef2e9d092496c89a9f135a1eb2989
| 1,062
|
py
|
Python
|
lib/broker/abstract_broker.py
|
Silver-birder/reinforcement-learning-fx
|
043e54015387b105669c7d047ca7f43c43dcc72b
|
[
"MIT"
] | 2
|
2020-10-01T13:24:06.000Z
|
2022-03-05T05:09:02.000Z
|
lib/broker/abstract_broker.py
|
Silver-birder/reinforcement-learning-fx
|
043e54015387b105669c7d047ca7f43c43dcc72b
|
[
"MIT"
] | null | null | null |
lib/broker/abstract_broker.py
|
Silver-birder/reinforcement-learning-fx
|
043e54015387b105669c7d047ca7f43c43dcc72b
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from abc import *
# Broker 抽象クラス
class AbstractBroker(object):
__metaclass__ = ABCMeta
@abstractmethod
def execute(self):
""" 注文の実行 """
raise NotImplementedError()
@abstractmethod
def sell(self):
""" 新規売り注文 """
raise NotImplementedError()
@abstractmethod
def buy(self):
""" 新規買い注文 """
raise NotImplementedError()
@abstractmethod
def modify_order(self):
""" 注文変更 """
raise NotImplementedError()
@abstractmethod
def cancel_order(self):
""" 注文キャンセル """
raise NotImplementedError()
@abstractmethod
def load_orders(self):
""" 注文取得 """
raise NotImplementedError()
@abstractmethod
def modify_position(self):
""" 玉建変更 """
raise NotImplementedError()
@abstractmethod
def close_position(self):
""" 玉建決済 """
raise NotImplementedError()
@abstractmethod
def load_positions(self):
""" 玉建取得 """
raise NotImplementedError()
| 20.423077
| 35
| 0.583804
| 82
| 1,062
| 7.439024
| 0.463415
| 0.25082
| 0.498361
| 0.537705
| 0.301639
| 0
| 0
| 0
| 0
| 0
| 0
| 0.001346
| 0.300377
| 1,062
| 51
| 36
| 20.823529
| 0.81965
| 0.091337
| 0
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0
| 0.033333
| 0
| 0.4
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ea787457cca07ee290f16ac12eb30584e7ebee39
| 525
|
py
|
Python
|
curso-em-video/ex108.py
|
joseluizbrits/sobre-python
|
316143c341e5a44070a3b13877419082774bd730
|
[
"MIT"
] | null | null | null |
curso-em-video/ex108.py
|
joseluizbrits/sobre-python
|
316143c341e5a44070a3b13877419082774bd730
|
[
"MIT"
] | null | null | null |
curso-em-video/ex108.py
|
joseluizbrits/sobre-python
|
316143c341e5a44070a3b13877419082774bd730
|
[
"MIT"
] | null | null | null |
# Formatando Moedas em Python
'''Adapte o código do ex107, criando uma função
adcional chamada moeda() que consiga mostrar os
valores como um valor monetário formatado'''
from uteis import moeda
p = float(input('\033[1m''Digite o preço: R$ '))
print(f'A metade de {moeda.moeda(p)} é {moeda.moeda(moeda.metade(p))}')
print(f'O dobro de {moeda.moeda(p)} é {moeda.moeda(moeda.dobro(p))}')
print(f'Aumentando 10%, temos {moeda.moeda(moeda.aumentar(p, 10))}')
print(f'Reduzindo 13%, temos {moeda.moeda(moeda.diminuir(p, 13))}')
| 40.384615
| 71
| 0.718095
| 88
| 525
| 4.284091
| 0.568182
| 0.265252
| 0.159151
| 0.068966
| 0.153846
| 0.153846
| 0.153846
| 0.153846
| 0
| 0
| 0
| 0.032328
| 0.11619
| 525
| 12
| 72
| 43.75
| 0.780172
| 0.310476
| 0
| 0
| 0
| 0.333333
| 0.733146
| 0.33427
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0.666667
| 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
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
ea820b40b9b483d8c0f117fbb3b3442a51efe55a
| 17
|
py
|
Python
|
Fundamentos/BaseDatos/tempCodeRunnerFile.py
|
ijchavez/python
|
bccd94a9bee90125e2be27b0355bdaedb0ae9d19
|
[
"Unlicense"
] | null | null | null |
Fundamentos/BaseDatos/tempCodeRunnerFile.py
|
ijchavez/python
|
bccd94a9bee90125e2be27b0355bdaedb0ae9d19
|
[
"Unlicense"
] | null | null | null |
Fundamentos/BaseDatos/tempCodeRunnerFile.py
|
ijchavez/python
|
bccd94a9bee90125e2be27b0355bdaedb0ae9d19
|
[
"Unlicense"
] | null | null | null |
conexion.close()
| 8.5
| 16
| 0.764706
| 2
| 17
| 6.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 17
| 2
| 16
| 8.5
| 0.8125
| 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
|
57752c2c93da73a2799561e393046ca96532288e
| 1,639
|
py
|
Python
|
edu_web_app/models.py
|
bk521234/python-in-edu
|
6055a315d8dc25dd4e8dbc142a44588b5fe64bdd
|
[
"MIT"
] | null | null | null |
edu_web_app/models.py
|
bk521234/python-in-edu
|
6055a315d8dc25dd4e8dbc142a44588b5fe64bdd
|
[
"MIT"
] | null | null | null |
edu_web_app/models.py
|
bk521234/python-in-edu
|
6055a315d8dc25dd4e8dbc142a44588b5fe64bdd
|
[
"MIT"
] | null | null | null |
from edu_web_app import db, app, login
from datetime import datetime
from werkzeug.security import generate_password_hash, check_password_hash
from flask_login import UserMixin
from time import time
import jwt
class User(UserMixin, db.Model):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(64), index=True, unique=True)
email = db.Column(db.String(120), index=True, unique=True)
password_hash = db.Column(db.String(128))
def set_password(self, password):
self.password_hash = generate_password_hash(password)
def check_password(self, password):
return check_password_hash(self.password_hash, password)
def __repr__(self):
return '<User {}>'.format(self.username)
def get_reset_password_token(self, expires_in=2400):
return jwt.encode(
{'reset_password': self.id, 'exp': time() + expires_in},
app.config['SECRET_KEY'], algorithm= 'HS256').decode('utf-8')
@staticmethod
def verify_reset_password_token(token):
try:
id = jwt.decode(token, app.config['SECRET_KEY'],
algorithms=['HS256'])['reset_password']
except:
return
return User.query.get(id)
class OER(db.Model):
id = db.Column(db.Integer, primary_key=True)
body = db.Column(db.String(1500))
timestamp = db.Column(db.DateTime, index=True, default=datetime.utcnow)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'))
def __repr__(self):
return '<OER {}>'.format(self.body)
@login.user_loader
def load_user(id):
return User.query.get(int(id))
| 32.137255
| 75
| 0.674192
| 221
| 1,639
| 4.81448
| 0.325792
| 0.06015
| 0.075188
| 0.06015
| 0.093045
| 0.075188
| 0.075188
| 0.075188
| 0.075188
| 0.075188
| 0
| 0.017557
| 0.200732
| 1,639
| 51
| 76
| 32.137255
| 0.794656
| 0
| 0
| 0.102564
| 1
| 0
| 0.054878
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.179487
| false
| 0.25641
| 0.153846
| 0.128205
| 0.74359
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
577d0bc49bd91f7f51a54cdcb6b2b6a22913db03
| 168
|
tac
|
Python
|
sine/media.tac
|
twisted/sine
|
a81b653641b559936bb35bb328eafe44d420b162
|
[
"MIT"
] | 5
|
2015-08-11T02:21:46.000Z
|
2018-12-03T17:20:37.000Z
|
sine/media.tac
|
DalavanCloud/sine
|
a81b653641b559936bb35bb328eafe44d420b162
|
[
"MIT"
] | 1
|
2021-02-18T20:02:03.000Z
|
2021-02-18T20:02:03.000Z
|
sine/media.tac
|
DalavanCloud/sine
|
a81b653641b559936bb35bb328eafe44d420b162
|
[
"MIT"
] | 6
|
2015-05-22T07:52:59.000Z
|
2018-12-03T17:20:26.000Z
|
import sine.useragent as ua
from twisted.application import service
application = service.Application("RTP Media Server")
ua.MediaServer().setServiceParent(application)
| 42
| 53
| 0.839286
| 20
| 168
| 7.05
| 0.7
| 0.255319
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077381
| 168
| 4
| 54
| 42
| 0.909677
| 0
| 0
| 0
| 0
| 0
| 0.094675
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
57c4982d1c0b1e6d61067ad34822ec679385156e
| 282
|
py
|
Python
|
hello.py
|
Aukau/Astr-119
|
da56326c84ad6755aee0182d87c607b4c321c45d
|
[
"MIT"
] | null | null | null |
hello.py
|
Aukau/Astr-119
|
da56326c84ad6755aee0182d87c607b4c321c45d
|
[
"MIT"
] | 12
|
2021-09-27T18:42:44.000Z
|
2021-12-09T18:01:31.000Z
|
hello.py
|
Aukau/Astr-119
|
da56326c84ad6755aee0182d87c607b4c321c45d
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
#this program will write
#Hello World!
print("Hello World!") #prints Hello World!
#homework section of the file
print("My name is Zac (He/Him). If you want to be more formal, you can use Zachary.") #Prints out my name, pronouns, and formalities
| 25.636364
| 133
| 0.702128
| 46
| 282
| 4.304348
| 0.804348
| 0.151515
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004405
| 0.195035
| 282
| 10
| 134
| 28.2
| 0.867841
| 0.524823
| 0
| 0
| 0
| 0.5
| 0.745763
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
57e9101a4b919c3736059890fe2327acd97a1697
| 806
|
py
|
Python
|
pythonchanges/python39/pep614_relax_decorator_grammar/test_pep614.py
|
paul-ko/python-changes
|
4d7ed4b6358d197c26a6ead37502df98b5c62dcc
|
[
"MIT"
] | null | null | null |
pythonchanges/python39/pep614_relax_decorator_grammar/test_pep614.py
|
paul-ko/python-changes
|
4d7ed4b6358d197c26a6ead37502df98b5c62dcc
|
[
"MIT"
] | null | null | null |
pythonchanges/python39/pep614_relax_decorator_grammar/test_pep614.py
|
paul-ko/python-changes
|
4d7ed4b6358d197c26a6ead37502df98b5c62dcc
|
[
"MIT"
] | null | null | null |
import functools
def output_multiplier(multiplier, func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
output = func(*args, **kwargs)
return output * multiplier if output is not None else None
return wrapper
multiplier_list = [
functools.partial(output_multiplier, 0),
functools.partial(output_multiplier, 1),
functools.partial(output_multiplier, 2),
]
multiplier_map = {
5: functools.partial(output_multiplier, 5),
10: functools.partial(output_multiplier, 10),
}
@multiplier_list[2]
def add_then_times_2(a, b):
return a + b
@multiplier_map[10]
def add_then_times_10(a, b):
return a + b
def test_list_subscripting():
assert add_then_times_2(2, 4) == 12
def test_map_subscripting():
assert add_then_times_10(2, 4) == 60
| 19.190476
| 66
| 0.698511
| 111
| 806
| 4.837838
| 0.315315
| 0.208566
| 0.204842
| 0.297952
| 0.148976
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039939
| 0.192308
| 806
| 41
| 67
| 19.658537
| 0.784946
| 0
| 0
| 0.076923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 1
| 0.230769
| false
| 0
| 0.038462
| 0.076923
| 0.423077
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
17a77c688ddfa3f433366d8123ac79ab68275f12
| 56
|
py
|
Python
|
tests/_support/package/module.py
|
uttamrc/invoke
|
61a580fc9919700305411e492f6fbfee7f4912dc
|
[
"BSD-2-Clause"
] | 3,187
|
2015-01-02T13:41:50.000Z
|
2022-03-28T19:22:49.000Z
|
tests/_support/package/module.py
|
uttamrc/invoke
|
61a580fc9919700305411e492f6fbfee7f4912dc
|
[
"BSD-2-Clause"
] | 648
|
2015-01-02T23:13:21.000Z
|
2022-03-30T23:32:13.000Z
|
tests/_support/package/module.py
|
uttamrc/invoke
|
61a580fc9919700305411e492f6fbfee7f4912dc
|
[
"BSD-2-Clause"
] | 347
|
2015-01-03T23:04:05.000Z
|
2022-03-25T17:35:24.000Z
|
from invoke import task
@task
def mytask(c):
pass
| 8
| 23
| 0.678571
| 9
| 56
| 4.222222
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 56
| 6
| 24
| 9.333333
| 0.904762
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 0.25
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
17c808b60b72000474fcb8ce990a3da277c9f972
| 65
|
py
|
Python
|
tests/__init__.py
|
Dafu2/dragon-axe
|
f429d8e6021e648d6987f363b0954579166058c2
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
Dafu2/dragon-axe
|
f429d8e6021e648d6987f363b0954579166058c2
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
Dafu2/dragon-axe
|
f429d8e6021e648d6987f363b0954579166058c2
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""Unit test package for dragon_axe."""
| 16.25
| 39
| 0.584615
| 9
| 65
| 4.111111
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018519
| 0.169231
| 65
| 3
| 40
| 21.666667
| 0.666667
| 0.861538
| 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
|
17cac0a777287657eb71a4b276a6ae8dfa6ad847
| 84
|
py
|
Python
|
python/arduino_termpoint/comm_core/comm_send_if.py
|
ZaoLahma/ArduinoStuff
|
9f02ce2fed1163b66c35fb01448212824f64caf8
|
[
"MIT"
] | null | null | null |
python/arduino_termpoint/comm_core/comm_send_if.py
|
ZaoLahma/ArduinoStuff
|
9f02ce2fed1163b66c35fb01448212824f64caf8
|
[
"MIT"
] | null | null | null |
python/arduino_termpoint/comm_core/comm_send_if.py
|
ZaoLahma/ArduinoStuff
|
9f02ce2fed1163b66c35fb01448212824f64caf8
|
[
"MIT"
] | null | null | null |
class CommSendIf:
def send_msg(self, message):
raise NotImplementedError
| 28
| 33
| 0.72619
| 9
| 84
| 6.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 84
| 3
| 33
| 28
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 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
|
a4c4dcceec0395b0c0065224e20693177b930640
| 1,423
|
py
|
Python
|
var/spack/repos/builtin/packages/h2database/package.py
|
robertodr/spack
|
9b809e01b47d48f01b3d257912fe1b752943cd3d
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | 9
|
2018-04-18T07:51:40.000Z
|
2021-09-10T03:56:57.000Z
|
var/spack/repos/builtin/packages/h2database/package.py
|
robertodr/spack
|
9b809e01b47d48f01b3d257912fe1b752943cd3d
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | 907
|
2018-04-18T11:17:57.000Z
|
2022-03-31T13:20:25.000Z
|
var/spack/repos/builtin/packages/h2database/package.py
|
robertodr/spack
|
9b809e01b47d48f01b3d257912fe1b752943cd3d
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | 29
|
2018-11-05T16:14:23.000Z
|
2022-02-03T16:07:09.000Z
|
# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
class H2database(MavenPackage):
"""H2 is an embeddable RDBMS written in Java."""
homepage = "https://h2database.com"
url = "https://github.com/h2database/h2database/archive/version-1.4.200.tar.gz"
version('1.4.200', sha256='59df19cc708442ae54a9639fc1c8c98ec6a55f66c154b39807032ba04fbe9c92')
version('1.4.199', sha256='0f59d6e4ca71dda44a252897ca717a873abc1db800011fa068a7a57f921193ce')
version('1.4.198', sha256='abba231e41ca31a9cc6571987ad97fe2c43232dc6d0e01c69ffbfcf3ea838967')
version('1.4.197', sha256='46d883a491f56270bbd681afc8237a5d69787c1838561e8680afbac693c26344')
version('1.4.196', sha256='9b0c7edac6ab7faad25743702aff1af63329fca37f6f5677908ae31ab968b219')
version('1.4.195', sha256='ad7fe6cd2c2ef08eb026279468e4d2b37c979c053fd7a523982d843a03a8c560')
version('1.4.194', sha256='0941a0d704be6e381644a39fa6003c0b0203905285a8330c905b950dfa2bbe31')
version('1.4.193', sha256='7da24c48c2f06b59e21955f7dd8c919836f600ccf98b41531c24ec09c622149c')
version('1.4.192', sha256='b5f370d7256cf816696a28acd282ed10bf8a05e09b814bf79d4527509846c977')
version('1.4.191', sha256='9890adc66979647b131242e87ad1498b906c0dcc041d25fcb24ff304b86b4f98')
build_directory = 'h2'
| 56.92
| 97
| 0.800422
| 120
| 1,423
| 9.483333
| 0.608333
| 0.077329
| 0.086995
| 0.02109
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.39969
| 0.092762
| 1,423
| 24
| 98
| 59.291667
| 0.481797
| 0.163036
| 0
| 0
| 0
| 0.071429
| 0.681049
| 0.541455
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0.285714
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a4f188280b377ede63b6880355abe997850b6e2e
| 307
|
py
|
Python
|
Problems/Chandu and his Girlfriend Returns/gf.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | 3
|
2018-07-17T09:03:02.000Z
|
2020-05-11T18:03:25.000Z
|
Problems/Chandu and his Girlfriend Returns/gf.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | null | null | null |
Problems/Chandu and his Girlfriend Returns/gf.py
|
jamtot/HackerEarth
|
71b919920dbc5b3af3fc49920939bab418455fb6
|
[
"MIT"
] | 2
|
2016-06-01T13:16:27.000Z
|
2018-09-25T08:32:24.000Z
|
def arrays(a1n, a2n):
a1 = map(int,raw_input().split())
a2 = map(int,raw_input().split())
return " ".join(map(str,sorted(a1+a2, reverse=True)))
if __name__ == "__main__":
for tc in xrange(int(raw_input())):
a1a2 = map(int, raw_input().split())
print arrays(a1a2[0],a1a2[1])
| 30.7
| 57
| 0.599349
| 47
| 307
| 3.659574
| 0.595745
| 0.139535
| 0.255814
| 0.244186
| 0.331395
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05668
| 0.19544
| 307
| 9
| 58
| 34.111111
| 0.639676
| 0
| 0
| 0
| 0
| 0
| 0.029316
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.125
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a4fee061009a2391e926cb9cc9f8ac57d70b1346
| 42,527
|
py
|
Python
|
models/modules/quantize.py
|
xiezheng-cs/CalibTIP
|
4a4558f7029dc6136fc16051c0d00c09f84fbb73
|
[
"MIT"
] | null | null | null |
models/modules/quantize.py
|
xiezheng-cs/CalibTIP
|
4a4558f7029dc6136fc16051c0d00c09f84fbb73
|
[
"MIT"
] | null | null | null |
models/modules/quantize.py
|
xiezheng-cs/CalibTIP
|
4a4558f7029dc6136fc16051c0d00c09f84fbb73
|
[
"MIT"
] | 1
|
2021-03-30T03:34:44.000Z
|
2021-03-30T03:34:44.000Z
|
from collections import namedtuple
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd.function import InplaceFunction, Function
import scipy.optimize as opt
import numpy as np
import os
QParams = namedtuple('QParams', ['range', 'zero_point', 'num_bits'])
_DEFAULT_FLATTEN = (1, -1)
_DEFAULT_FLATTEN_GRAD = (0, -1)
QZP = True
def _deflatten_as(x, x_full):
shape = list(x.shape) + [1] * (x_full.dim() - x.dim())
return x.view(*shape)
methods = ['Nelder-Mead','Powell','COBYLA']
def lp_norm(x, xq, p):
err = torch.mean(torch.abs(xq - x) ** p)
return err
def mse(x, xq):
err = torch.mean((xq - x) ** 2)
return err
def tensor_range(x, pcq=False):
if pcq:
return x.view(x.shape[0], -1).max(dim=-1)[0] - x.view(x.shape[0], -1).min(dim=-1)[0]
else:
return x.max() - x.min()
def zero_point(x, pcq=False):
if pcq:
return x.view(x.shape[0], -1).min(dim=-1)[0]
else:
return x.min()
def quant_err(p, t, num_bits=4, metric='mse'):
qp = QParams(range=t.new_tensor(p[0]), zero_point=t.new_tensor(p[1]), num_bits=num_bits)
tq = quantize_with_grad(t, num_bits=qp.num_bits, qparams=qp)
# TODO: Add other metrics
return mse(t, tq).item()
def quant_round_constrain(t1, t2, trange, tzp):
qp = QParams(range=t1.new_tensor(trange), zero_point=t1.new_tensor(tzp), num_bits=4)
t1q = quantize_with_grad(t1, num_bits=qp.num_bits, qparams=qp, dequantize=False)
t2q = quantize_with_grad(t2, num_bits=qp.num_bits, qparams=qp, dequantize=False)
out=torch.max(torch.min(t2q,t1q+1),t1q-1)
# TODO: Add other metrics
return dequantize(out,num_bits=qp.num_bits, qparams=qp)
def calculate_qparams(x, num_bits, flatten_dims=_DEFAULT_FLATTEN, reduce_dim=0, reduce_type='mean', keepdim=False, true_zero=False,per_ch_input=False,quant_mode = 'maxmin'):
alpha_gaus = {1:1.24,2:1.71,3:2.215,4:2.55,5:2.93,6:3.28,7:3.61,8:3.92}
alpha_gaus_positive = {1:1.71,2:2.215,3:2.55,4:2.93,5:3.28,6:3.61,7:3.92,8:4.2}
alpha_laplas = {1:1.05,2:1.86,3:2.83,4:5.03,5:6.2,6:7.41,7:8.64,8:9.89}
alpha_laplas_positive = {1:1.86,2:2.83,3:5.03,4:6.2,5:7.41,6:8.64,7:9.89,8:11.16}
if per_ch_input:
x = x.transpose(0,1)
with torch.no_grad():
x_flat = x.flatten(*flatten_dims)
if quant_mode =='mean_std' and num_bits<8: #If you want to apply only on the activation add "and reduce_dim is not None"
mu = x_flat.mean() if x_flat.dim() == 1 else x_flat.mean(-1)
std = x_flat.std() if x_flat.dim() == 1 else x_flat.std(-1)
b = torch.abs(x_flat-mu).mean() if x_flat.dim() == 1 else torch.mean(torch.abs(x_flat-mu.unsqueeze(1)),-1)
minv = x_flat.min() if x_flat.dim() == 1 else x_flat.min(-1)[0]
maxv = x_flat.max() if x_flat.dim() == 1 else x_flat.max(-1)[0]
#print((b-std).abs().max(),x.shape)
## Asic
#const = alpha_laplas_positive[num_bits] if reduce_dim is not None else alpha_laplas[num_bits]
#min_values = _deflatten_as(torch.max(mu - const*b,minv), x)
#max_values = _deflatten_as(torch.min(mu + const*b,maxv), x)
## Welling
min_values = _deflatten_as(torch.max(mu - 6*std,minv), x)
max_values = _deflatten_as(torch.min(mu + 6*std,maxv), x)
else:
if x_flat.dim() == 1:
min_values = _deflatten_as(x_flat.min(), x)
max_values = _deflatten_as(x_flat.max(), x)
else:
min_values = _deflatten_as(x_flat.min(-1)[0], x)
max_values = _deflatten_as(x_flat.max(-1)[0], x)
if reduce_dim is not None:
if reduce_type == 'mean':
min_values = min_values.mean(reduce_dim, keepdim=keepdim)
max_values = max_values.mean(reduce_dim, keepdim=keepdim)
else:
min_values = min_values.min(reduce_dim, keepdim=keepdim)[0]
max_values = max_values.max(reduce_dim, keepdim=keepdim)[0]
# TODO: re-add true zero computation
min_values[min_values > 0] = 0
max_values[max_values < 0] = 0
range_values = max_values - min_values
range_values[range_values==0] = 1
return QParams(range=range_values, zero_point=min_values,
num_bits=num_bits)
class UniformQuantize(InplaceFunction):
@staticmethod
def forward(ctx, input, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN,
reduce_dim=0, dequantize=True, signed=False, stochastic=False, inplace=False,quant_zp=QZP):
ctx.inplace = inplace
#if (num_bits is None and qparams.num_bits>4) or (num_bits is not None and num_bits>4 and input.dim()>2):
if ctx.inplace:
ctx.mark_dirty(input)
output = input
else:
output = input.clone()
if qparams is None:
assert num_bits is not None, "either provide qparams of num_bits to quantize"
qparams = calculate_qparams(
input, num_bits=num_bits, flatten_dims=flatten_dims, reduce_dim=reduce_dim)
zero_point = qparams.zero_point
num_bits = qparams.num_bits
qmin = -(2.**(num_bits - 1)) if signed else 0.
qmax = qmin + 2.**num_bits - 1.
running_range=qparams.range.clamp(min=1e-6,max=1e5)
scale = running_range / (qmax - qmin)
if quant_zp:
running_zero_point_round = Round().apply(qmin-zero_point/scale,False)
else:
zero_point = torch.min(zero_point, zero_point.new_tensor([0.]))
output.add_(qmin * scale - zero_point).div_(scale)
if stochastic:
noise = output.new(output.shape).uniform_(-0.5, 0.5)
output.add_(noise)
# quantize
output.clamp_(qmin, qmax).round_()
if dequantize:
output.mul_(scale).add_(
zero_point - qmin * scale) # dequantize
return output
@staticmethod
def backward(ctx, grad_output):
# straight-through estimator
grad_input = grad_output
return grad_input, None, None, None, None, None, None, None, None, None
class Round(InplaceFunction):
@staticmethod
def forward(ctx, input,inplace):
ctx.inplace = inplace
if ctx.inplace:
ctx.mark_dirty(input)
output = input
else:
output = input.clone()
output.round_()
return output
@staticmethod
def backward(ctx, grad_output):
# straight-through estimator
grad_input = grad_output
return grad_input,None
class UniformQuantizeGrad(InplaceFunction):
@staticmethod
def forward(ctx, input, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN_GRAD,
reduce_dim=0, dequantize=True, signed=False, stochastic=True):
ctx.num_bits = num_bits
ctx.qparams = qparams
ctx.flatten_dims = flatten_dims
ctx.stochastic = stochastic
ctx.signed = signed
ctx.dequantize = dequantize
ctx.reduce_dim = reduce_dim
ctx.inplace = False
return input
@staticmethod
def backward(ctx, grad_output):
qparams = ctx.qparams
with torch.no_grad():
if qparams is None:
assert ctx.num_bits is not None, "either provide qparams of num_bits to quantize"
qparams = calculate_qparams(
grad_output, num_bits=ctx.num_bits, flatten_dims=ctx.flatten_dims, reduce_dim=ctx.reduce_dim, reduce_type='extreme')
grad_input = quantize(grad_output, num_bits=None,
qparams=qparams, flatten_dims=ctx.flatten_dims, reduce_dim=ctx.reduce_dim,
dequantize=True, signed=ctx.signed, stochastic=ctx.stochastic, inplace=False)
return grad_input, None, None, None, None, None, None, None
def conv2d_biprec(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1, num_bits_grad=None):
out1 = F.conv2d(input.detach(), weight, bias,
stride, padding, dilation, groups)
out2 = F.conv2d(input, weight.detach(), bias.detach() if bias is not None else None,
stride, padding, dilation, groups)
out2 = quantize_grad(out2, num_bits=num_bits_grad, flatten_dims=(1, -1))
return out1 + out2 - out1.detach()
def linear_biprec(input, weight, bias=None, num_bits_grad=None):
out1 = F.linear(input.detach(), weight, bias)
out2 = F.linear(input, weight.detach(), bias.detach()
if bias is not None else None)
out2 = quantize_grad(out2, num_bits=num_bits_grad)
return out1 + out2 - out1.detach()
def quantize_with_grad(input, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN, reduce_dim=0,clamp=True, dequantize=True, signed=False, stochastic=False, inplace=False,quant_zp=QZP):
if inplace:
output = input
else:
output = input.clone()
if qparams is None:
import pdb; pdb.set_trace()
assert num_bits is not None, "either provide qparams of num_bits to quantize"
qparams = calculate_qparams(
input, num_bits=num_bits, flatten_dims=flatten_dims, reduce_dim=reduce_dim)
zero_point = qparams.zero_point
num_bits = qparams.num_bits
qmin = -(2.**(num_bits - 1)) if signed else 0.
qmax = qmin + 2.**num_bits - 1.
# ZP quantization for HW compliance
running_range=qparams.range.clamp(min=1e-6,max=1e5)
scale = running_range / (qmax - qmin)
if quant_zp:
running_zero_point_round = Round().apply(qmin-zero_point/scale,False)
zero_point = (qmin-running_zero_point_round.clamp(qmin,qmax))*scale
else:
zero_point = torch.min(zero_point, zero_point.new_tensor([0.]))
output.add_(qmin * scale - zero_point).div_(scale)
if stochastic:
noise = output.new(output.shape).uniform_(-0.5, 0.5)
output.add_(noise)
if clamp:
# quantize
output = Round().apply(output.clamp_(qmin, qmax),inplace)
if dequantize:
output.mul_(scale).add_(
zero_point - qmin * scale) # dequantize
return output
else:
return output,scale,qmin * scale - zero_point
def dequantize(input, num_bits=None, qparams=None,signed=False, inplace=False):
if inplace:
output = input
else:
output = input.clone()
zero_point = qparams.zero_point
num_bits = qparams.num_bits
qmin = -(2.**(num_bits - 1)) if signed else 0.
qmax = qmin + 2.**num_bits - 1.
scale = qparams.range / (qmax - qmin)
output.mul_(scale).add_(
zero_point - qmin * scale) # dequantize
return output
def quantize(x, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN, reduce_dim=0, dequantize=True, signed=False, stochastic=False, inplace=False,quant_zp=QZP):
return UniformQuantize().apply(x, num_bits, qparams, flatten_dims, reduce_dim, dequantize, signed, stochastic, inplace,quant_zp)
def quantize_grad(x, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN_GRAD, reduce_dim=0, dequantize=True, signed=False, stochastic=True):
return UniformQuantizeGrad().apply(x, num_bits, qparams, flatten_dims, reduce_dim, dequantize, signed, stochastic)
class QuantMeasure(nn.Module):
"""docstring for QuantMeasure."""
def __init__(self, num_bits=8, shape_measure=(1,), flatten_dims=_DEFAULT_FLATTEN,
inplace=False, dequantize=True, stochastic=False, momentum=0.1, measure=False,per_ch_input=False,reduce_dim=0, cal_qparams=False):
super(QuantMeasure, self).__init__()
self.register_buffer('running_zero_point', torch.zeros(*shape_measure))
self.register_buffer('running_range', torch.zeros(*shape_measure))
self.measure = measure
if self.measure:
self.register_buffer('num_measured', torch.zeros(1))
self.flatten_dims = flatten_dims
self.momentum = momentum
self.dequantize = dequantize
self.stochastic = stochastic
self.inplace = inplace
self.num_bits = num_bits
self.per_ch_input = per_ch_input
self.reduce_dim = reduce_dim
self.cal_qparams = cal_qparams
def forward(self, input, qparams=None):
if self.training or self.measure:
if qparams is None:
if self.cal_qparams:
init = np.array([tensor_range(input, pcq=False).item(), zero_point(input, pcq=False).item()])
res = opt.minimize(lambda p: quant_err(p, input, num_bits=self.num_bits, metric='mse'), init, method=methods[0])
qparams = QParams(range=input.new_tensor(res.x[0]), zero_point=input.new_tensor(res.x[1]), num_bits=self.num_bits)
print("Measure and optimize: bits - {}, error before - {:.6f}, error after {:.6f}".format(self.num_bits, quant_err(init, input), res.fun))
else:
reduce_dim = None if self.per_ch_input else self.reduce_dim
qparams = calculate_qparams(input, num_bits=self.num_bits, flatten_dims=self.flatten_dims, reduce_dim=reduce_dim,per_ch_input=self.per_ch_input)
with torch.no_grad():
if self.measure:
momentum = self.num_measured / (self.num_measured + 1)
self.num_measured += 1
else:
momentum = self.momentum
self.running_zero_point.mul_(momentum).add_(
qparams.zero_point * (1 - momentum))
self.running_range.mul_(momentum).add_(
qparams.range * (1 - momentum))
else:
qparams = QParams(range=self.running_range,
zero_point=self.running_zero_point, num_bits=self.num_bits)
if self.measure:
return input
else:
if self.per_ch_input: input=input.transpose(0,1)
q_input = quantize(input, qparams=qparams, dequantize=self.dequantize,
stochastic=self.stochastic, inplace=self.inplace)
if self.per_ch_input: q_input=q_input.transpose(0,1)
return q_input
class QuantThUpdate(nn.Module):
"""docstring for QuantMeasure."""
def __init__(self, num_bits=8, shape_measure=(1,), flatten_dims=_DEFAULT_FLATTEN,
inplace=False, dequantize=True, stochastic=False, momentum=0.1, measure=False,per_ch_input=False,reduce_dim=0):
super(QuantThUpdate, self).__init__()
self.running_zero_point = nn.Parameter(torch.ones(*shape_measure))
self.running_range = nn.Parameter(torch.ones(*shape_measure))
self.measure = measure
self.flatten_dims = flatten_dims
self.dequantize = dequantize
self.stochastic = stochastic
self.inplace = inplace
self.num_bits = num_bits
self.per_ch_input = per_ch_input
self.reduce_dim = reduce_dim
def forward(self, input, qparams=None):
qparams = QParams(range=self.running_range,
zero_point=self.running_zero_point, num_bits=self.num_bits)
if self.per_ch_input: input=input.transpose(0,1)
q_input = quantize_with_grad(input, qparams=qparams, dequantize=self.dequantize,
stochastic=self.stochastic, inplace=self.inplace)
if self.per_ch_input: q_input=q_input.transpose(0,1)
return q_input
class QConv2dSamePadding(nn.Conv2d):
"""docstring for QConv2d."""
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, dilation=1, groups=1, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, biprecision=False,measure=False):
super(QConv2dSamePadding, self).__init__(in_channels, out_channels, kernel_size,
stride, padding, dilation, groups, bias)
if in_channels==groups:
num_bits=8
num_bits_weight=8
per_ch_input = False
else:
per_ch_input = False
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.measure = measure
num_measure = in_channels if per_ch_input else 1
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(num_measure, 1, 1, 1), flatten_dims=(1, -1), measure=measure,per_ch_input=per_ch_input)
self.biprecision = biprecision
self.stride = self.stride if len(self.stride) == 2 else [self.stride[0]]*2
def forward(self, input):
ih, iw = input.size()[-2:]
kh, kw = self.weight.size()[-2:]
sh, sw = self.stride
oh, ow = math.ceil(ih / sh), math.ceil(iw / sw)
pad_h = max((oh - 1) * self.stride[0] + (kh - 1) * self.dilation[0] + 1 - ih, 0)
pad_w = max((ow - 1) * self.stride[1] + (kw - 1) * self.dilation[1] + 1 - iw, 0)
if pad_h > 0 or pad_w > 0:
input = F.pad(input, [pad_w//2, pad_w - pad_w//2, pad_h//2, pad_h - pad_h//2])
qinput = self.quantize_input(input)
weight_qparams = calculate_qparams(
self.weight, num_bits=self.num_bits_weight, flatten_dims=(1, -1), reduce_dim=None)
qweight = quantize(self.weight, qparams=weight_qparams) if not self.measure else self.weight
if self.bias is not None:
qbias = self.bias if self.measure else quantize(self.bias, num_bits=self.num_bits_weight + self.num_bits,flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.conv2d(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
else:
output = conv2d_biprec(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups, num_bits_grad=self.num_bits_grad)
return output
class QConv2d_o(nn.Conv2d):
"""docstring for QConv2d."""
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, dilation=1, groups=1, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, biprecision=False,measure=False):
super(QConv2d_o, self).__init__(in_channels, out_channels, kernel_size,
stride, padding, dilation, groups, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.measure = measure
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
self.biprecision = biprecision
def forward(self, input):
qinput = self.quantize_input(input)
weight_qparams = calculate_qparams(
self.weight, num_bits=self.num_bits_weight, flatten_dims=(1, -1), reduce_dim=None)
qweight = quantize(self.weight, qparams=weight_qparams) if not self.measure else self.weight
if self.bias is not None:
qbias = self.bias if self.measure else quantize(self.bias, num_bits=self.num_bits_weight + self.num_bits,flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.conv2d(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
else:
output = conv2d_biprec(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups, num_bits_grad=self.num_bits_grad)
return output
class QConv2d_lapq(nn.Conv2d):
"""docstring for QConv2d."""
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, dilation=1, groups=1, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, biprecision=False,measure=False):
super(QConv2d, self).__init__(in_channels, out_channels, kernel_size,
stride, padding, dilation, groups, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.measure = measure
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
self.quantize_weight = QuantMeasure(
self.num_bits, shape_measure=(out_channels, 1, 1, 1), flatten_dims=(1, -1), measure=measure, reduce_dim=None)
self.biprecision = biprecision
def forward(self, input):
qinput = self.quantize_input(input)
qweight = self.quantize_weight(self.weight)
if self.bias is not None:
qbias = self.bias if self.measure else quantize(self.bias, num_bits=self.num_bits_weight + self.num_bits,flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.conv2d(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
else:
output = conv2d_biprec(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups, num_bits_grad=self.num_bits_grad)
return output
class QConv2d(nn.Conv2d):
"""docstring for QConv2d."""
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, dilation=1, groups=1, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, perC=True, biprecision=False, measure=False, cal_qparams=False):
super(QConv2d, self).__init__(in_channels, out_channels, kernel_size,
stride, padding, dilation, groups, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.measure = measure
self.equ_scale = nn.Parameter(torch.ones(out_channels, 1, 1, 1))
if measure:
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure, cal_qparams=cal_qparams)
self.quantize_weight = QuantMeasure(
self.num_bits, shape_measure=(out_channels if perC else 1, 1, 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure, reduce_dim=None if perC else 0)
else:
self.quantize_input = QuantThUpdate(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
self.quantize_weight = QuantThUpdate(
self.num_bits, shape_measure=(out_channels if perC else 1, 1, 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure, reduce_dim=None if perC else 0)
self.biprecision = biprecision
self.cal_params = cal_qparams
self.quantize = True
def forward(self, input):
qinput = self.quantize_input(input) if self.quantize else input
qweight = self.quantize_weight(self.weight * self.equ_scale) if self.quantize and not self.cal_params else self.weight
#if not self.measure:
# import pdb; pdb.set_trace()
#else:
# print('measuring')
if not self.measure and os.environ.get('DEBUG')=='True':
assert qinput.unique().numel()<=2**self.num_bits
assert qweight[0].unique().numel()<=2**self.num_bits_weight
if self.bias is not None:
qbias = self.bias if (self.measure or not self.quantize) else quantize(self.bias, num_bits=self.num_bits_weight + self.num_bits,flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.conv2d(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
else:
output = conv2d_biprec(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups, num_bits_grad=self.num_bits_grad)
return output
class QConv2dVQ(nn.Conv2d):
"""docstring for QConv2d."""
def __init__(self, in_channels, out_channels, kernel_size,
stride=1, padding=0, dilation=1, groups=1, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, perC=True, biprecision=False, measure=False, cal_qparams=False):
super(QConv2dVQ, self).__init__(in_channels, out_channels, kernel_size,
stride, padding, dilation, groups, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.measure = measure
self.equ_scale = nn.Parameter(torch.ones(out_channels, 1, 1, 1))
self.V = nn.Parameter(torch.eye(in_channels)) #,out_channels))
self.U = nn.Parameter(torch.eye(in_channels)) #,out_channels))
if measure:
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure, cal_qparams=cal_qparams)
self.quantize_weight = QuantMeasure(
self.num_bits, shape_measure=(out_channels if perC else 1, 1, 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure, reduce_dim=None if perC else 0)
else:
self.quantize_input = QuantThUpdate(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
self.quantize_weight = QuantThUpdate(
self.num_bits, shape_measure=(out_channels if perC else 1, 1, 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure, reduce_dim=None if perC else 0)
self.biprecision = biprecision
self.cal_params = cal_qparams
self.quantize = True
def reset(self):
stdv = 1. / math.sqrt(self.U.size(1))
self.U.data.uniform_(-stdv,stdv)
self.V.data.uniform_(-stdv,stdv)
def forward(self, input):
qweight = self.quantize_weight(self.weight * self.equ_scale) if self.quantize and not self.cal_params else self.weight
B,C,H,W=input.shape
vx=self.V.mm(input.transpose(0,1).contiguous().view(C,-1))
qvx = self.quantize_input(vx.view(C,B,H,W).transpose(1,0).contiguous()).transpose(0,1).contiguous().view(C,-1) if self.quantize else input
qinput = self.U.mm(qvx).view(C,B,H,W).transpose(1,0).contiguous() if self.quantize else qvx
#import pdb; pdb.set_trace()
#qinput = self.quantize_input(input) if self.quantize else input
#vq_weight=self.V.mm(self.weight.view(self.out_channels,-1)).view(self.weight.shape) # * self.equ_scale)
#qweight = self.quantize_weight(vq_weight) if self.quantize and not self.cal_params else self.weight
#qweight = self.U.mm(qweight.view(self.out_channels,-1)).view(self.weight.shape)
#if not self.measure:
# import pdb; pdb.set_trace()
#else:
# print('measuring')
if not self.measure and os.environ.get('DEBUG')=='True':
assert qinput.unique().numel()<=2**self.num_bits
assert qweight[0].unique().numel()<=2**self.num_bits_weight
if self.bias is not None:
qbias = self.bias if (self.measure or not self.quantize) else quantize(self.bias, num_bits=self.num_bits_weight + self.num_bits,flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.conv2d(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
else:
output = conv2d_biprec(qinput, qweight, qbias, self.stride,
self.padding, self.dilation, self.groups, num_bits_grad=self.num_bits_grad)
return output
class QSigmoid(nn.Sigmoid):
"""docstring for QSigmoid."""
def __init__(self, num_bits=8, measure=False):
super(QSigmoid, self).__init__()
self.num_bits = num_bits
self.measure = measure
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
def forward(self, input):
qinput = self.quantize_input(input)
output = torch.sigmoid(qinput)
return output
class QSwish(nn.Module):
def __init__(self,num_bits=8, measure=False):
super(QSwish, self).__init__()
self.num_bits=num_bits
self.measure=measure
self.qsigmoid=QSigmoid(num_bits,measure)
self.quantize_input = QuantMeasure(
self.num_bits, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1), measure=measure)
def forward(self, input1,input2=None):
if input2 is None:
input2=input1
output = self.quantize_input(input1) * self.qsigmoid(input2)
return output
class QLinear_o(nn.Linear):
"""docstring for QConv2d."""
def __init__(self, in_features, out_features, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, biprecision=False,measure=False):
super(QLinear_o, self).__init__(in_features, out_features, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.biprecision = biprecision
self.quantize_input = QuantMeasure(self.num_bits,measure=measure)
self.measure = measure
def forward(self, input):
qinput = self.quantize_input(input)
weight_qparams = calculate_qparams(
self.weight, num_bits=self.num_bits_weight, flatten_dims=(1, -1), reduce_dim=None)
qweight = quantize(self.weight, qparams=weight_qparams) if not self.measure else self.weight
if self.bias is not None:
qbias = self.bias if self.measure else quantize(
self.bias, num_bits=self.num_bits_weight + self.num_bits,
flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.linear(qinput, qweight, qbias)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad)
else:
output = linear_biprec(qinput, qweight, qbias, self.num_bits_grad)
return output
class QLinear_lapq(nn.Linear):
"""docstring for QConv2d."""
def __init__(self, in_features, out_features, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, biprecision=False,measure=False):
super(QLinear, self).__init__(in_features, out_features, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.biprecision = biprecision
self.quantize_input = QuantMeasure(self.num_bits,measure=measure)
self.quantize_weight = QuantMeasure(self.num_bits,shape_measure=(out_features, 1), measure=measure,reduce_dim=None)
self.measure = measure
def forward(self, input):
qinput = self.quantize_input(input)
qweight = self.quantize_weight(self.weight)
if self.bias is not None:
qbias = self.bias if self.measure else quantize(
self.bias, num_bits=self.num_bits_weight + self.num_bits,
flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.linear(qinput, qweight, qbias)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad)
else:
output = linear_biprec(qinput, qweight, qbias, self.num_bits_grad)
return output
class QLinear(nn.Linear):
"""docstring for QConv2d."""
def __init__(self, in_features, out_features, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, perC=True, biprecision=False,measure=False, cal_qparams=False):
super(QLinear, self).__init__(in_features, out_features, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.biprecision = biprecision
self.equ_scale = nn.Parameter(torch.ones(out_features, 1))
if measure:
self.quantize_input = QuantMeasure(self.num_bits,measure=measure, cal_qparams=cal_qparams)
self.quantize_weight = QuantMeasure(self.num_bits,shape_measure=(out_features if perC else 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure,reduce_dim=None if perC else 0)
else:
self.quantize_input = QuantThUpdate(self.num_bits,measure=measure)
self.quantize_weight = QuantThUpdate(self.num_bits,shape_measure=(out_features if perC else 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure,reduce_dim=None if perC else 0)
self.measure = measure
self.cal_params = cal_qparams
self.quantize = True
def forward(self, input):
qinput = self.quantize_input(input) if self.quantize else input
qweight = self.quantize_weight(self.weight * self.equ_scale) if self.quantize and not self.cal_params else self.weight
if not self.measure and os.environ.get('DEBUG')=='True':
assert qinput.unique().numel()<=2**self.num_bits
assert qweight[0].unique().numel()<=2**self.num_bits_weight
if self.bias is not None:
qbias = self.bias if (self.measure or not self.quantize) else quantize(
self.bias, num_bits=self.num_bits_weight + self.num_bits,
flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.linear(qinput, qweight, qbias)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad)
else:
output = linear_biprec(qinput, qweight, qbias, self.num_bits_grad)
return output
class QLinearVQ(nn.Linear):
"""docstring for QConv2d."""
def __init__(self, in_features, out_features, bias=True, num_bits=8, num_bits_weight=8, num_bits_grad=None, perC=True, biprecision=False,measure=False, cal_qparams=False):
super(QLinearVQ, self).__init__(in_features, out_features, bias)
self.num_bits = num_bits
self.num_bits_weight = num_bits_weight or num_bits
self.num_bits_grad = num_bits_grad
self.biprecision = biprecision
self.equ_scale = nn.Parameter(torch.ones(out_features, 1))
self.V = nn.Parameter(torch.eye(in_features))
self.U = nn.Parameter(torch.eye(in_features))
if measure:
self.quantize_input = QuantMeasure(self.num_bits,measure=measure, cal_qparams=cal_qparams)
self.quantize_weight = QuantMeasure(self.num_bits,shape_measure=(out_features if perC else 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure,reduce_dim=None if perC else 0)
else:
self.quantize_input = QuantThUpdate(self.num_bits,measure=measure)
self.quantize_weight = QuantThUpdate(self.num_bits,shape_measure=(out_features if perC else 1, 1), flatten_dims=(1,-1) if perC else (0,-1), measure=measure,reduce_dim=None if perC else 0)
self.measure = measure
self.cal_params = cal_qparams
self.quantize = True
def reset(self):
stdv = 1. / math.sqrt(self.U.size(1))
self.U.data.uniform_(-stdv,stdv)
self.V.data.uniform_(-stdv,stdv)
def forward(self, input):
vx=self.V.mm(input.transpose(0,1).contiguous())
qvx = self.quantize_input(vx) if self.quantize else input
qinput=self.U.mm(qvx).transpose(1,0).contiguous() if self.quantize else input
qweight = self.quantize_weight(self.weight) if self.quantize and not self.cal_params else self.weight
#qinput = self.quantize_input(input) if self.quantize else input
#vq_weight=self.V.mm(self.weight.view(self.out_features,-1)).view(self.weight.shape)
#qweight = self.quantize_weight(vq_weight) if self.quantize and not self.cal_params else self.weight
#qweight = self.U.mm(qweight)
if not self.measure and os.environ.get('DEBUG')=='True':
assert qinput.unique().numel()<=2**self.num_bits
assert qweight[0].unique().numel()<=2**self.num_bits_weight
if self.bias is not None:
qbias = self.bias if (self.measure or not self.quantize) else quantize(
self.bias, num_bits=self.num_bits_weight + self.num_bits,
flatten_dims=(0, -1))
else:
qbias = None
if not self.biprecision or self.num_bits_grad is None:
output = F.linear(qinput, qweight, qbias)
if self.num_bits_grad is not None:
output = quantize_grad(
output, num_bits=self.num_bits_grad)
else:
output = linear_biprec(qinput, qweight, qbias, self.num_bits_grad)
return output
class RangeBN(nn.Module):
# this is normalized RangeBN
def __init__(self, num_features, dim=1, momentum=0.1, affine=True, num_chunks=16, eps=1e-5, num_bits=8, num_bits_grad=8):
super(RangeBN, self).__init__()
self.register_buffer('running_mean', torch.zeros(num_features))
self.register_buffer('running_var', torch.zeros(num_features))
self.momentum = momentum
self.dim = dim
if affine:
self.bias = nn.Parameter(torch.Tensor(num_features))
self.weight = nn.Parameter(torch.Tensor(num_features))
self.num_bits = num_bits
self.num_bits_grad = num_bits_grad
self.quantize_input = QuantMeasure(
self.num_bits, inplace=True, shape_measure=(1, 1, 1, 1), flatten_dims=(1, -1))
self.eps = eps
self.num_chunks = num_chunks
self.reset_params()
def reset_params(self):
if self.weight is not None:
self.weight.data.uniform_()
if self.bias is not None:
self.bias.data.zero_()
def forward(self, x):
x = self.quantize_input(x)
if x.dim() == 2: # 1d
x = x.unsqueeze(-1,).unsqueeze(-1)
if self.training:
B, C, H, W = x.shape
y = x.transpose(0, 1).contiguous() # C x B x H x W
y = y.view(C, self.num_chunks, (B * H * W) // self.num_chunks)
mean_max = y.max(-1)[0].mean(-1) # C
mean_min = y.min(-1)[0].mean(-1) # C
mean = y.view(C, -1).mean(-1) # C
scale_fix = (0.5 * 0.35) * (1 + (math.pi * math.log(4)) **
0.5) / ((2 * math.log(y.size(-1))) ** 0.5)
scale = (mean_max - mean_min) * scale_fix
with torch.no_grad():
self.running_mean.mul_(self.momentum).add_(
mean * (1 - self.momentum))
self.running_var.mul_(self.momentum).add_(
scale * (1 - self.momentum))
else:
mean = self.running_mean
scale = self.running_var
# scale = quantize(scale, num_bits=self.num_bits, min_value=float(
# scale.min()), max_value=float(scale.max()))
out = (x - mean.view(1, -1, 1, 1)) / \
(scale.view(1, -1, 1, 1) + self.eps)
if self.weight is not None:
qweight = self.weight
# qweight = quantize(self.weight, num_bits=self.num_bits,
# min_value=float(self.weight.min()),
# max_value=float(self.weight.max()))
out = out * qweight.view(1, -1, 1, 1)
if self.bias is not None:
qbias = self.bias
# qbias = quantize(self.bias, num_bits=self.num_bits)
out = out + qbias.view(1, -1, 1, 1)
if self.num_bits_grad is not None:
out = quantize_grad(
out, num_bits=self.num_bits_grad, flatten_dims=(1, -1))
if out.size(3) == 1 and out.size(2) == 1:
out = out.squeeze(-1).squeeze(-1)
return out
class RangeBN1d(RangeBN):
# this is normalized RangeBN
def __init__(self, num_features, dim=1, momentum=0.1, affine=True, num_chunks=16, eps=1e-5, num_bits=8, num_bits_grad=8):
super(RangeBN1d, self).__init__(num_features, dim, momentum,
affine, num_chunks, eps, num_bits, num_bits_grad)
self.quantize_input = QuantMeasure(
self.num_bits, inplace=True, shape_measure=(1, 1), flatten_dims=(1, -1))
if __name__ == '__main__':
x = torch.rand(2, 3)
x_q = quantize(x, flatten_dims=(-1), num_bits=8, dequantize=True)
print(x)
print(x_q)
| 46.784378
| 199
| 0.623768
| 5,849
| 42,527
| 4.317661
| 0.053001
| 0.088144
| 0.06098
| 0.027164
| 0.794013
| 0.763523
| 0.73624
| 0.71363
| 0.693474
| 0.668251
| 0
| 0.021723
| 0.265008
| 42,527
| 908
| 200
| 46.835903
| 0.786224
| 0.053331
| 0
| 0.650138
| 0
| 0
| 0.010213
| 0
| 0
| 0
| 0
| 0.001101
| 0.015152
| 1
| 0.071625
| false
| 0
| 0.013774
| 0.002755
| 0.162534
| 0.004132
| 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
|
3502d86d5603d07fd5a29a1219a30de19a92d88d
| 25
|
py
|
Python
|
tests/__init__.py
|
laymonage/vws-python
|
75082c6f8f130975fbe1a9497664af94c4212f3b
|
[
"MIT"
] | 7
|
2017-01-05T09:05:44.000Z
|
2020-05-14T06:41:47.000Z
|
tests/__init__.py
|
laymonage/vws-python
|
75082c6f8f130975fbe1a9497664af94c4212f3b
|
[
"MIT"
] | 665
|
2016-12-14T23:03:53.000Z
|
2020-05-14T21:22:39.000Z
|
tests/__init__.py
|
laymonage/vws-python
|
75082c6f8f130975fbe1a9497664af94c4212f3b
|
[
"MIT"
] | 5
|
2020-08-17T15:18:35.000Z
|
2021-05-21T08:50:41.000Z
|
"""Tests for ``vws``."""
| 12.5
| 24
| 0.44
| 3
| 25
| 3.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 25
| 1
| 25
| 25
| 0.5
| 0.72
| 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
|
101d8ae30b550946567c85986ccaafa119434d9b
| 598
|
py
|
Python
|
tests/serializers.py
|
tonisvain/django-rest-framework-sideloading
|
fb14c3d2108b7527832fb82a38cb794b1ec5dd14
|
[
"MIT"
] | null | null | null |
tests/serializers.py
|
tonisvain/django-rest-framework-sideloading
|
fb14c3d2108b7527832fb82a38cb794b1ec5dd14
|
[
"MIT"
] | null | null | null |
tests/serializers.py
|
tonisvain/django-rest-framework-sideloading
|
fb14c3d2108b7527832fb82a38cb794b1ec5dd14
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from tests.models import Supplier, Category, Product, Partner
class SupplierSerializer(serializers.ModelSerializer):
class Meta:
model = Supplier
fields = '__all__'
class PartnerSerializer(serializers.ModelSerializer):
class Meta:
model = Partner
fields = '__all__'
class CategorySerializer(serializers.ModelSerializer):
class Meta:
model = Category
fields = '__all__'
class ProductSerializer(serializers.ModelSerializer):
class Meta:
model = Product
fields = '__all__'
| 21.357143
| 61
| 0.698997
| 53
| 598
| 7.566038
| 0.396226
| 0.259352
| 0.309227
| 0.349127
| 0.399002
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.234114
| 598
| 27
| 62
| 22.148148
| 0.875546
| 0
| 0
| 0.444444
| 0
| 0
| 0.046823
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.111111
| 0
| 0.555556
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
102a4eff79e75b4e6a715f047dc0ee9ac025c7d9
| 156
|
py
|
Python
|
Python_Basic/string_to_list.py
|
gautamtarika/C-Proggramming-Basics
|
05dfe3cc8d44554b12afe08b9a86a018a7bac9b0
|
[
"MIT"
] | 2
|
2020-08-26T12:51:34.000Z
|
2020-08-26T14:07:21.000Z
|
Python_Basic/string_to_list.py
|
gautamtarika/C-Proggramming-Basics
|
05dfe3cc8d44554b12afe08b9a86a018a7bac9b0
|
[
"MIT"
] | null | null | null |
Python_Basic/string_to_list.py
|
gautamtarika/C-Proggramming-Basics
|
05dfe3cc8d44554b12afe08b9a86a018a7bac9b0
|
[
"MIT"
] | 4
|
2020-08-26T12:57:44.000Z
|
2020-09-01T08:48:33.000Z
|
st="Hello everyone are you enjoying learning Python ?"
st2 = st.split()
print(st2)
print(st.strip())
print(st.replace('o','0'))
print(st.isalpha())
| 19.5
| 55
| 0.660256
| 24
| 156
| 4.291667
| 0.666667
| 0.203884
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022556
| 0.147436
| 156
| 8
| 56
| 19.5
| 0.75188
| 0
| 0
| 0
| 0
| 0
| 0.34
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.666667
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
10354201ad786c716cc1f6c0a705afc9315e2307
| 231
|
py
|
Python
|
Labs/lab00/lab00.py
|
vladimirSirin/SICP_Walkthrough
|
d3b6525cf2ee716e409a27364016c8c4982e6d83
|
[
"MIT"
] | 1
|
2020-07-14T10:42:03.000Z
|
2020-07-14T10:42:03.000Z
|
Labs/lab00/lab00.py
|
vladimirSirin/Structure-and-Interpretation-of-Computer-Programs
|
d3b6525cf2ee716e409a27364016c8c4982e6d83
|
[
"MIT"
] | null | null | null |
Labs/lab00/lab00.py
|
vladimirSirin/Structure-and-Interpretation-of-Computer-Programs
|
d3b6525cf2ee716e409a27364016c8c4982e6d83
|
[
"MIT"
] | null | null | null |
def twenty_eighteen():
"""Come up with the most creative expression that evaluates to 2018,
using only numbers and the +, *, and - operators.
>>> twenty_eighteen()
2018
"""
return 8 + 192 + (18 * 100) + 18
| 25.666667
| 72
| 0.614719
| 30
| 231
| 4.666667
| 0.8
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112426
| 0.268398
| 231
| 8
| 73
| 28.875
| 0.715976
| 0.619048
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
10436b4bd5faa11eb3ca68488e3ee88627a1f6b3
| 26
|
py
|
Python
|
tests/__init__.py
|
HalbardHobby/git-LFS-for-Lambda
|
d19ba6fc4605d5dc2dba52acb4236c68787f8bde
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
HalbardHobby/git-LFS-for-Lambda
|
d19ba6fc4605d5dc2dba52acb4236c68787f8bde
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
HalbardHobby/git-LFS-for-Lambda
|
d19ba6fc4605d5dc2dba52acb4236c68787f8bde
|
[
"MIT"
] | null | null | null |
"""Test suite package."""
| 13
| 25
| 0.615385
| 3
| 26
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 26
| 1
| 26
| 26
| 0.695652
| 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
|
105c79f3be3dd8eec0930e88e173518adae11efa
| 3,427
|
py
|
Python
|
tests/emukit/core/test_stopping_conditions.py
|
ndalchau/emukit
|
eb6754ea016a7cd82b275bb4075676b5ed662634
|
[
"Apache-2.0"
] | 152
|
2020-10-24T13:12:57.000Z
|
2022-03-25T11:35:41.000Z
|
tests/emukit/core/test_stopping_conditions.py
|
ndalchau/emukit
|
eb6754ea016a7cd82b275bb4075676b5ed662634
|
[
"Apache-2.0"
] | 87
|
2020-10-26T10:29:25.000Z
|
2022-03-04T11:17:59.000Z
|
tests/emukit/core/test_stopping_conditions.py
|
ndalchau/emukit
|
eb6754ea016a7cd82b275bb4075676b5ed662634
|
[
"Apache-2.0"
] | 41
|
2020-10-24T11:59:21.000Z
|
2022-03-22T17:08:30.000Z
|
import numpy as np
import mock
from emukit.core.loop import (ConvergenceStoppingCondition,
FixedIterationsStoppingCondition,
LoopState,
StoppingCondition)
class DummyStoppingCondition(StoppingCondition):
def should_stop(self, loop_state: LoopState) -> bool:
pass
def test_fixed_iteration_stopping_condition():
n_iterations = 5
stopping_condition = FixedIterationsStoppingCondition(n_iterations)
loop_state_mock = mock.create_autospec(LoopState)
loop_state_mock.iteration = 0
assert(stopping_condition.should_stop(loop_state_mock) is False)
loop_state_mock.iteration = n_iterations - 1
assert(stopping_condition.should_stop(loop_state_mock) is False)
loop_state_mock.iteration = n_iterations
assert(stopping_condition.should_stop(loop_state_mock) is True)
def test_convergence_stopping_condition():
stopping_condition = ConvergenceStoppingCondition(0.1)
# check if we stop before criterion can be calculated
loop_state_mock = mock.create_autospec(LoopState)
loop_state_mock.iteration = 1
loop_state_mock.X = np.array([[0]])
assert(stopping_condition.should_stop(loop_state_mock) is False)
# check if we stop when we should not
loop_state_mock = mock.create_autospec(LoopState)
loop_state_mock.iteration = 5
loop_state_mock.X = np.array([[0], [10], [20], [30], [40]])
assert(stopping_condition.should_stop(loop_state_mock) is False)
# check if we stop when we should
loop_state_mock = mock.create_autospec(LoopState)
loop_state_mock.iteration = 5
loop_state_mock.X.return_value(np.array([[0], [1], [2], [3], [3.01]]))
assert(stopping_condition.should_stop(loop_state_mock) is True)
def test_operations_with_conditions():
left_condition = DummyStoppingCondition()
right_condition = DummyStoppingCondition()
mock_loop_state = mock.create_autospec(LoopState)
or_condition = left_condition | right_condition
and_condition = left_condition & right_condition
left_condition.should_stop = mock.MagicMock(return_value=True)
right_condition.should_stop = mock.MagicMock(return_value=True)
assert(or_condition.should_stop(mock_loop_state) is True)
assert(and_condition.should_stop(mock_loop_state) is True)
left_condition.should_stop = mock.MagicMock(return_value=True)
right_condition.should_stop = mock.MagicMock(return_value=False)
assert(or_condition.should_stop(mock_loop_state) is True)
assert(and_condition.should_stop(mock_loop_state) is False)
left_condition.should_stop = mock.MagicMock(return_value=False)
right_condition.should_stop = mock.MagicMock(return_value=True)
assert(or_condition.should_stop(mock_loop_state) is True)
assert(and_condition.should_stop(mock_loop_state) is False)
left_condition.should_stop = mock.MagicMock(return_value=False)
right_condition.should_stop = mock.MagicMock(return_value=False)
assert(or_condition.should_stop(mock_loop_state) is False)
assert(and_condition.should_stop(mock_loop_state) is False)
complex_combination = (left_condition | right_condition) & left_condition
left_condition.should_stop = mock.MagicMock(return_value=False)
right_condition.should_stop = mock.MagicMock(return_value=True)
assert(complex_combination.should_stop(mock_loop_state) is False)
| 40.317647
| 77
| 0.763642
| 446
| 3,427
| 5.522422
| 0.156951
| 0.109622
| 0.18514
| 0.168088
| 0.73041
| 0.71214
| 0.692245
| 0.668291
| 0.664637
| 0.657328
| 0
| 0.008648
| 0.156405
| 3,427
| 84
| 78
| 40.797619
| 0.843307
| 0.034724
| 0
| 0.474576
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.254237
| 1
| 0.067797
| false
| 0.016949
| 0.050847
| 0
| 0.135593
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
106a2aacff79e9a9832f13c8f00edb633c921e1b
| 205
|
py
|
Python
|
utils/set_nick_name.py
|
ProgramRipper/biliob-spider
|
2fe3d5fd91bb301dd0d0eb21d03153d6882f6bcf
|
[
"MIT"
] | 2
|
2021-02-21T05:49:17.000Z
|
2021-02-28T03:01:45.000Z
|
utils/set_nick_name.py
|
kirahan/biliob-spider
|
1a7c4a2b6781775c62c9a7d1aa2f1b0e2b0ab1f8
|
[
"MIT"
] | 1
|
2022-03-20T07:59:27.000Z
|
2022-03-20T07:59:27.000Z
|
utils/set_nick_name.py
|
kirahan/biliob-spider
|
1a7c4a2b6781775c62c9a7d1aa2f1b0e2b0ab1f8
|
[
"MIT"
] | 7
|
2021-02-13T16:58:49.000Z
|
2022-02-11T03:23:56.000Z
|
from db import db
users = db['user'].find({}, {'name': 1})
for user in users:
db['user'].update_one({'name': user['name']}, {
'$set': {'nickName': user['name']}})
pass
print(user)
pass
| 22.777778
| 51
| 0.546341
| 29
| 205
| 3.827586
| 0.551724
| 0.126126
| 0.198198
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006135
| 0.204878
| 205
| 8
| 52
| 25.625
| 0.674847
| 0
| 0
| 0.25
| 0
| 0
| 0.17561
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.25
| 0.125
| 0
| 0.125
| 0.125
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
108838b868da4f64aefef15fd585c6d5a8015bf2
| 130
|
py
|
Python
|
codes_auto/1389.minimum-moves-to-move-a-box-to-their-target-location.py
|
smartmark-pro/leetcode_record
|
6504b733d892a705571eb4eac836fb10e94e56db
|
[
"MIT"
] | null | null | null |
codes_auto/1389.minimum-moves-to-move-a-box-to-their-target-location.py
|
smartmark-pro/leetcode_record
|
6504b733d892a705571eb4eac836fb10e94e56db
|
[
"MIT"
] | null | null | null |
codes_auto/1389.minimum-moves-to-move-a-box-to-their-target-location.py
|
smartmark-pro/leetcode_record
|
6504b733d892a705571eb4eac836fb10e94e56db
|
[
"MIT"
] | null | null | null |
#
# @lc app=leetcode.cn id=1389 lang=python3
#
# [1389] minimum-moves-to-move-a-box-to-their-target-location
#
None
# @lc code=end
| 18.571429
| 61
| 0.707692
| 23
| 130
| 4
| 0.869565
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077586
| 0.107692
| 130
| 7
| 62
| 18.571429
| 0.715517
| 0.869231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
10a123df450697de82076bbd3d50304de9958733
| 21
|
py
|
Python
|
python/testData/codeInsight/controlflow/variableannotations.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/codeInsight/controlflow/variableannotations.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/codeInsight/controlflow/variableannotations.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
x: int
xs: List = []
| 7
| 13
| 0.47619
| 4
| 21
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.285714
| 21
| 2
| 14
| 10.5
| 0.666667
| 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
|
10af50c5a47a8042a768557f34450b22546ddd4b
| 22,968
|
py
|
Python
|
tests/test_stormtrack/test_core/test_features/test_area_lonlat.py
|
ruestefa/stormtrack
|
e9378f013c406d387ea944c97e5adc68df864dee
|
[
"MIT"
] | null | null | null |
tests/test_stormtrack/test_core/test_features/test_area_lonlat.py
|
ruestefa/stormtrack
|
e9378f013c406d387ea944c97e5adc68df864dee
|
[
"MIT"
] | 2
|
2021-01-06T17:37:42.000Z
|
2021-02-05T18:40:52.000Z
|
tests/test_stormtrack/test_core/test_features/test_area_lonlat.py
|
ruestefa/stormtrack
|
e9378f013c406d387ea944c97e5adc68df864dee
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
# Standard library
import itertools
import logging as log
import os
import sys
import unittest
from unittest import TestCase
# Third-party
import numpy as np
# First-party
from stormtrack.core.identification import Feature
from stormtrack.utils.various import import_module
# log.getLogger().addHandler(log.StreamHandler(sys.stdout))
# log.getLogger().setLevel(log.DEBUG)
# Define tolerances for area deviations based on setup
# They are defined by increasing specificity and later searched inversely
tol_pct_by_setup = [
({}, 1.0),
({"method": "dyntools", "delta": 0.5, "clat": 0}, 1.1),
({"method": "dyntools", "delta": 0.5, "clat": 10}, 1.1),
({"method": "dyntools", "delta": 0.5, "clat": 90}, 1.7),
({"method": "dyntools", "delta": 1.0, "clat": 40}, 2.1),
({"method": "pyproj"}, 10.0),
({"method": "pyproj", "clat": 40}, 8.0),
({"method": "pyproj", "clat": 80}, 30.0),
({"method": "pyproj", "delta": 0.5, "clat": 60}, 15.0),
({"method": "pyproj", "delta": 0.5, "clat": 70}, 20.0),
({"method": "pyproj", "delta": 0.5, "clat": 90}, 60.0),
({"method": "pyproj", "delta": 1.0, "clat": 0}, 20.0),
]
def get_tol_pct(setup):
for setup_i, tol_pct in tol_pct_by_setup[::-1]:
for key, val in setup_i.items():
if setup[key] != val:
break
else:
return tol_pct
return 0
# dyntls d0.01 lat00 r800 800 800 0.05% 2012524 2010619 0.09%
# dyntls d0.01 lat40 r800 800 800 0.05% 2012469 2010619 0.09%
# dyntls d0.01 lat80 r800 800 800 0.05% 2012498 2010619 0.09%
# dyntls d0.05 lat00 r800 800 800 0.03% 2011991 2010619 0.07%
# dyntls d0.05 lat40 r800 800 800 0.04% 2012047 2010619 0.07%
# dyntls d0.05 lat80 r800 800 800 0.04% 2012306 2010619 0.08%
# dyntls d0.10 lat00 r800 800 799 0.06% 2008134 2010619 0.12%
# dyntls d0.10 lat40 r800 800 800 0.01% 2010918 2010619 0.01%
# dyntls d0.10 lat80 r800 800 800 0.03% 2011639 2010619 0.05%
# dyntls d0.50 lat00 r800 800 804 0.51% 2031339 2010619 1.03%
# dyntls d0.50 lat10 r800 800 804 0.50% 2030850 2010619 1.01%
# dyntls d0.50 lat20 r800 800 802 0.34% 2024349 2010619 0.68%
# dyntls d0.50 lat30 r800 800 800 0.09% 2014300 2010619 0.18%
# dyntls d0.50 lat40 r800 800 801 0.18% 2017778 2010619 0.36%
# dyntls d0.50 lat50 r800 800 801 0.19% 2018405 2010619 0.39%
# dyntls d0.50 lat60 r800 800 802 0.27% 2021356 2010619 0.53%
# dyntls d0.50 lat70 r800 800 800 0.06% 2013000 2010619 0.12%
# dyntls d0.50 lat80 r800 800 801 0.23% 2019735 2010619 0.45%
# dyntls d0.50 lat90 r800 800 806 0.83% 2043972 2010619 1.66%
# dyntls d1.00 lat00 r800 800 796 0.48% 1991213 2010619 0.97%
# dyntls d1.00 lat40 r800 800 807 1.00% 2051019 2010619 2.01%
# dyntls d1.00 lat80 r800 800 803 0.40% 2026873 2010619 0.81%
# pyproj d0.05 lat00 r800 800 802 0.31% 2023099 2010619 0.62%
# pyproj d0.05 lat40 r800 800 769 3.83% 1859371 2010619 7.52%
# pyproj d0.05 lat80 r800 800 673 15.83% 1424349 2010619 29.16%
# pyproj d0.10 lat00 r800 800 807 0.89% 2046655 2010619 1.79%
# pyproj d0.10 lat40 r800 800 772 3.47% 1873414 2010619 6.82%
# pyproj d0.10 lat80 r800 800 674 15.64% 1430918 2010619 28.83%
# pyproj d0.50 lat00 r800 800 819 2.48% 2111540 2010619 5.02%
# pyproj d0.50 lat10 r800 800 817 2.14% 2097702 2010619 4.33%
# pyproj d0.50 lat20 r800 800 813 1.69% 2078968 2010619 3.40%
# pyproj d0.50 lat30 r800 800 804 0.55% 2032705 2010619 1.10%
# pyproj d0.50 lat40 r800 800 787 1.56% 1948250 2010619 3.10%
# pyproj d0.50 lat50 r800 800 764 4.47% 1835046 2010619 8.73%
# pyproj d0.50 lat60 r800 800 746 6.72% 1749311 2010619 13.00%
# pyproj d0.50 lat70 r800 800 717 10.27% 1618814 2010619 19.49%
# pyproj d0.50 lat80 r800 800 685 14.33% 1475816 2010619 26.60%
# pyproj d0.50 lat90 r800 800 529 33.76% 882282 2010619 56.12%
# pyproj d1.00 lat00 r800 800 871 8.94% 2386068 2010619 18.67%
# pyproj d1.00 lat40 r800 800 815 1.96% 2090214 2010619 3.96%
# pyproj d1.00 lat80 r800 800 699 12.56% 1537328 2010619 23.54%
class Test_Base(TestCase):
# Method used to compute the areas from the pixels
# Note: 'grid' seems to be more precise than 'proj'
# method_comp_area = "proj"
method_comp_area = "grid"
# Whether to run the tests (True) or just print the results (False)
check_results = True
# check_results=False
def create_feature(self):
"""Create feature from self.mask."""
if not hasattr(self, "mask"):
raise Exception("attribute self.mask missing")
pixels = np.asarray(np.where(self.mask), np.int32).T
self.feature = Feature(pixels)
def comp_feature_area(self):
if self.method_comp_area == "grid":
lon, lat = self.lon1d, self.lat1d
elif self.method_comp_area == "proj":
lon, lat = self.lon2d, self.lat2d
else:
raise ValueError("mode='" + mode + "'")
return self.feature.area_lonlat(lon, lat, method=self.method_comp_area)
def print_res_sol(self, area_res, area_sol):
"""Helper method to print result and solution with the error."""
rad_sol = self.rad_km
rad_res = np.sqrt(area_res / np.pi)
err_rad = abs(rad_res - rad_sol) / rad_sol
err_area = abs(area_res - area_sol) / area_sol
print(
"\r{} {:4} {:4} {:7.2%} {:8} {:8} {:7.2%}".format(
self.__class__.__name__.lstrip("Test_"),
int(self.rad_km),
int(rad_res),
err_rad,
int(area_res),
int(area_sol),
err_area,
)
)
def eval_test(self, area_res, area_sol, tol_pct=None):
if tol_pct is None:
tol_pct = get_tol_pct(self.setup)
if self.check_results:
rel_err_pct = 100 * abs(area_res - area_sol) / area_sol
msg = ("area differs by {:.1f}% > {}%: {} km2 != {} km2").format(
rel_err_pct, tol_pct, area_res, area_sol
)
self.assertTrue(rel_err_pct < tol_pct, msg)
else:
self.print_res_sol(area_res, area_sol)
class Test_dyntls_d1p00_lat00_r800(Test_Base):
setup = dict(clat=0, rad=800, delta=1.0, method="dyntools")
def setUp(s):
s.clon, s.clat = 0.0, 0.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 17
s.lat1d = np.linspace(-8.0, 8.0, s.nlat)
s.lon1d = np.linspace(-8.0, 8.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,X,X,X,_,_,_,_,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,_,_,_,X,X,X,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool,
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
class Test_dyntls_d1p00_lat40_r800(Test_Base):
setup = dict(clat=40, rad=800, delta=1.0, method="dyntools")
def setUp(s):
s.clon, s.clat = 0.0, 40.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 21
s.lat1d = np.linspace(32.0, 48.0, s.nlat)
s.lon1d = np.linspace(-10.0, 10.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,X,X,X,X,X,_,_,_,_,_,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_],
[_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,X,X,X,X,X,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool,
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
class Test_dyntls_d1p00_lat80_r800(Test_Base):
setup = dict(clat=80, rad=800, delta=1.0, method="dyntools")
def setUp(s):
s.clon, s.clat = 0.0, 80.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 95
s.lat1d = np.linspace(72.0, 88.0, s.nlat)
s.lon1d = np.linspace(-47.0, 47.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
class Test_pyproj_d1p00_lat00_r800(Test_Base):
setup = dict(clat=0, rad=800, delta=1.0, method="pyproj")
def setUp(s):
s.clon, s.clat = 0.0, 0.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 17
s.lat1d = np.linspace(-8.0, 8.0, s.nlat)
s.lon1d = np.linspace(-8.0, 8.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool,
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
class Test_pyproj_d1p00_lat40_r800(Test_Base):
setup = dict(clat=40, rad=800, delta=1.0, method="pyproj")
def setUp(s):
s.clon, s.clat = 0.0, 40.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 21
s.lat1d = np.linspace(32.0, 48.0, s.nlat)
s.lon1d = np.linspace(-10.0, 10.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,_,_,_,X,X,X,X,X,X,X,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool,
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
class Test_pyproj_d1p00_lat80_r800(Test_Base):
setup = dict(clat=80, rad=800, delta=1.0, method="pyproj")
def setUp(s):
s.clon, s.clat = 0.0, 80.0
s.rad_km = 800.0
s.area_km2 = np.pi * s.rad_km ** 2
s.nlat, s.nlon = 17, 75
s.lat1d = np.linspace(72.0, 88.0, s.nlat)
s.lon1d = np.linspace(-37.0, 37.0, s.nlon)
s.lat2d, s.lon2d = np.meshgrid(s.lat1d, s.lon1d)
_, X = 0, 1
# fmt: off
s.mask = np.array(
[
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_],
[_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_],
[_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_],
[_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_],
[_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,X,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
[_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_,_],
],
np.bool,
).T[:, ::-1]
# fmt: on
s.create_feature()
def test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
# Automatic tests based on text files
data_path = f"{os.path.dirname(os.path.abspath(__file__))}/data"
data_file_fmt = (
data_path + "/circle_on_globe_clat-{clat:02}_rad-{rad}_delta-{delta}_{method}.py"
)
def create_test_class(name, setup):
def method_setUp(s):
infile = s.data_file_fmt.format(**s.setup)
mod = import_module(infile)
for var in [
"clon",
"clat",
"rad_km",
"area_km2",
"nlat",
"nlon",
"lat1d",
"lon1d",
"lat2d",
"lon2d",
"mask",
]:
setattr(s, var, getattr(mod, var))
s.create_feature()
def method_test_area(s):
res = s.comp_feature_area()
sol = s.area_km2
s.eval_test(res, sol)
attributes = {
"data_file_fmt": data_file_fmt,
"setup": setup,
}
methods = {"setUp": method_setUp, "test_area": method_test_area}
bases = (Test_Base,)
dict_ = {**methods, **attributes}
return type(name, bases, dict_)
clats = np.arange(10) * 10
rads = [800]
deltas = [0.5, 0.1, 0.05]
methods = ["dyntools", "pyproj"]
cls_name_fmt = "Test_{method}_d{delta_str}_lat{clat:02}_r{rad}"
for clat, rad, delta, method in itertools.product(clats, rads, deltas, methods):
# Define test setup
setup = dict(clat=clat, rad=rad, delta=delta, method=method)
# Skip setup if no infile exists
infile = data_file_fmt.format(path=data_path, **setup)
if not os.path.isfile(infile):
continue
# Define test class name
delta_str = "{:4.2f}".format(delta).replace(".", "p")
cls_name = cls_name_fmt.format(delta_str=delta_str, **setup).replace(
"_dyntools_", "_dyntls_"
)
# Create test class and add it to current module
globals()[cls_name] = create_test_class(cls_name, setup)
if __name__ == "__main__":
unittest.main()
| 43.417769
| 208
| 0.492947
| 4,590
| 22,968
| 2.072549
| 0.079303
| 0.549984
| 0.823084
| 1.094923
| 0.613056
| 0.5195
| 0.508462
| 0.495848
| 0.490171
| 0.490171
| 0
| 0.1044
| 0.240987
| 22,968
| 528
| 209
| 43.5
| 0.44129
| 0.157915
| 0
| 0.528249
| 0
| 0.002825
| 0.036397
| 0.008411
| 0
| 0
| 0
| 0
| 0.002825
| 1
| 0.056497
| false
| 0
| 0.028249
| 0
| 0.138418
| 0.008475
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
52a52bf29ece6412d26b0d38220251cd82f25be3
| 231
|
py
|
Python
|
blog_api/serializers.py
|
rollanda21/blog-posts-website
|
2be7f48c8e7f8e62f84a7380ba602f2af2646f4f
|
[
"MIT"
] | null | null | null |
blog_api/serializers.py
|
rollanda21/blog-posts-website
|
2be7f48c8e7f8e62f84a7380ba602f2af2646f4f
|
[
"MIT"
] | 5
|
2022-03-01T03:51:45.000Z
|
2022-03-02T23:31:25.000Z
|
blog_api/serializers.py
|
rollanda21/blog-posts-website
|
2be7f48c8e7f8e62f84a7380ba602f2af2646f4f
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from blog.models import Post
class PostSerializer(serializers.ModelSerializer):
class Meta:
model = Post
fields = ('id', 'title', 'author', 'excert', 'content', 'status')
| 33
| 73
| 0.692641
| 25
| 231
| 6.36
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 231
| 7
| 73
| 33
| 0.850267
| 0
| 0
| 0
| 0
| 0
| 0.137931
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
52cfe285066acc1423a7f2eb5e4e3a26b54c2d6a
| 124
|
py
|
Python
|
setup.py
|
ReblochonMasque/futils
|
d9cff8a416edb248cd17be42ff81d722b2f4fbc1
|
[
"MIT"
] | null | null | null |
setup.py
|
ReblochonMasque/futils
|
d9cff8a416edb248cd17be42ff81d722b2f4fbc1
|
[
"MIT"
] | null | null | null |
setup.py
|
ReblochonMasque/futils
|
d9cff8a416edb248cd17be42ff81d722b2f4fbc1
|
[
"MIT"
] | null | null | null |
from setuptools import find_packages, setup
setup(
name='futils',
version='0.0.6',
packages=find_packages(),
)
| 15.5
| 43
| 0.677419
| 16
| 124
| 5.125
| 0.6875
| 0.292683
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.029703
| 0.185484
| 124
| 8
| 44
| 15.5
| 0.782178
| 0
| 0
| 0
| 0
| 0
| 0.088
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.166667
| 0
| 0.166667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
52dc33b270b66a1bfa0581653788b6fbaebf5e00
| 486
|
py
|
Python
|
tests/test_saveobjectcrops.py
|
BodenmillerGroup/ImcPluginsCP
|
a53bb7e1dea60b859d57677ea9a15281fa84d493
|
[
"MIT"
] | 10
|
2019-06-04T16:59:27.000Z
|
2021-07-14T08:20:44.000Z
|
tests/test_saveobjectcrops.py
|
BodenmillerGroup/ImcPluginsCP
|
a53bb7e1dea60b859d57677ea9a15281fa84d493
|
[
"MIT"
] | 32
|
2018-02-28T23:20:00.000Z
|
2021-05-17T15:02:01.000Z
|
tests/test_saveobjectcrops.py
|
BodenmillerGroup/ImcPluginsCP
|
a53bb7e1dea60b859d57677ea9a15281fa84d493
|
[
"MIT"
] | 7
|
2017-11-23T03:01:16.000Z
|
2022-01-27T22:40:01.000Z
|
import numpy
import pytest
import io
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.modules.injectimage
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
from cellprofiler_core.utilities.core import modules as cpmodules
IMAGE_NAME = "image"
OUTPUT_IMAGE_F = "outputimage%d"
import plugins.saveobjectcrops as saveobjectcrops
def test_init():
x = saveobjectcrops.SaveObjectCrops()
| 22.090909
| 65
| 0.849794
| 59
| 486
| 6.813559
| 0.474576
| 0.278607
| 0.328358
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.100823
| 486
| 21
| 66
| 23.142857
| 0.919908
| 0
| 0
| 0
| 0
| 0
| 0.037037
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.066667
| false
| 0
| 0.733333
| 0
| 0.8
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
52dfdd16680016fdba33a88fb81731153bf22ca2
| 86
|
py
|
Python
|
lib/cache_policy.py
|
maanavshah/cache-policy-lru-mru
|
c882acdfd4b4cab3f131e8a364df30a69b8d39f8
|
[
"MIT"
] | null | null | null |
lib/cache_policy.py
|
maanavshah/cache-policy-lru-mru
|
c882acdfd4b4cab3f131e8a364df30a69b8d39f8
|
[
"MIT"
] | null | null | null |
lib/cache_policy.py
|
maanavshah/cache-policy-lru-mru
|
c882acdfd4b4cab3f131e8a364df30a69b8d39f8
|
[
"MIT"
] | null | null | null |
class CachePolicy:
def __init__(self):
self.cache = []
self.cache_size = 5
| 14.333333
| 23
| 0.639535
| 11
| 86
| 4.545455
| 0.727273
| 0.36
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0.244186
| 86
| 5
| 24
| 17.2
| 0.753846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
52f1d4c4230498c82665bde68db22392a1904b35
| 469
|
py
|
Python
|
tests/regressions/python/966_named_arguments.py
|
NanmiaoWu/phylanx
|
295b5f82cc39925a0d53e77ba3b6d02a65204535
|
[
"BSL-1.0"
] | 83
|
2017-08-27T15:09:13.000Z
|
2022-01-18T17:03:41.000Z
|
tests/regressions/python/966_named_arguments.py
|
NanmiaoWu/phylanx
|
295b5f82cc39925a0d53e77ba3b6d02a65204535
|
[
"BSL-1.0"
] | 808
|
2017-08-27T15:35:01.000Z
|
2021-12-14T17:30:50.000Z
|
tests/regressions/python/966_named_arguments.py
|
NanmiaoWu/phylanx
|
295b5f82cc39925a0d53e77ba3b6d02a65204535
|
[
"BSL-1.0"
] | 55
|
2017-08-27T15:09:22.000Z
|
2022-03-25T12:07:34.000Z
|
# Copyright (c) 2019 Bita Hasheminezhad
#
# Distributed under the Boost Software License, Version 1.0. (See accompanying
# file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
# #966: Named arguments don't work
from phylanx import Phylanx
import numpy as np
# make flake happy
def eye(N, M, k, dtype):
pass
@Phylanx
def i(N, M=None, k=0, dtype=None):
return eye(N, M=M, k=k, dtype=dtype)
assert((i(3, k=2) == np.eye(3, k=2)).all())
| 19.541667
| 79
| 0.678038
| 86
| 469
| 3.651163
| 0.616279
| 0.019108
| 0.057325
| 0.076433
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.046875
| 0.181237
| 469
| 23
| 80
| 20.391304
| 0.770833
| 0.501066
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 1
| 0.25
| false
| 0.125
| 0.25
| 0.125
| 0.625
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
52fc9f9965730122993e63cab8ca142ab6ee6c2e
| 98
|
py
|
Python
|
AI-Practice-Tensorflow-Notes-master/tf/tf3_1.py
|
foochane/Tensorflow-Learning
|
54d210a1286051e9d60c98a62bd63eb070bc0a11
|
[
"Apache-2.0"
] | 2
|
2019-01-23T14:23:17.000Z
|
2019-01-23T14:23:49.000Z
|
AI-Practice-Tensorflow-Notes-master/tf/tf3_1.py
|
foochane/Tensorflow-Learning
|
54d210a1286051e9d60c98a62bd63eb070bc0a11
|
[
"Apache-2.0"
] | null | null | null |
AI-Practice-Tensorflow-Notes-master/tf/tf3_1.py
|
foochane/Tensorflow-Learning
|
54d210a1286051e9d60c98a62bd63eb070bc0a11
|
[
"Apache-2.0"
] | null | null | null |
import tensorflow as tf
a=tf.constant([1.0,2.0])
b=tf.constant([3.0,4.0])
result=a+b
print result
| 16.333333
| 24
| 0.704082
| 23
| 98
| 3
| 0.608696
| 0.289855
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089888
| 0.091837
| 98
| 5
| 25
| 19.6
| 0.685393
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.2
| null | null | 0.2
| 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
|
5e1b9168b4ff91e2abb7bcbb561158eaf8328b50
| 679
|
py
|
Python
|
micropython/009_bluetooth.py
|
mirontoli/tolle-rasp
|
020638e86c167aedd7b556d8515a3adef70724af
|
[
"MIT"
] | 2
|
2021-06-29T17:18:09.000Z
|
2022-01-25T08:29:59.000Z
|
micropython/009_bluetooth.py
|
mirontoli/tolle-rasp
|
020638e86c167aedd7b556d8515a3adef70724af
|
[
"MIT"
] | null | null | null |
micropython/009_bluetooth.py
|
mirontoli/tolle-rasp
|
020638e86c167aedd7b556d8515a3adef70724af
|
[
"MIT"
] | null | null | null |
def on_bluetooth_connected():
basic.show_leds("""
. # # # .
# . . . .
# . . . .
# . . . .
. # # # .
""")
bluetooth.on_bluetooth_connected(on_bluetooth_connected)
def on_bluetooth_disconnected():
basic.show_leds("""
# # # . .
# . . # .
# . . # .
# . . # .
# # # . .
""")
bluetooth.on_bluetooth_disconnected(on_bluetooth_disconnected)
basic.show_leds("""
# . . # #
# . . # #
# # # . .
# . # . .
# # # . .
""")
bluetooth.start_accelerometer_service()
bluetooth.start_button_service()
bluetooth.start_led_service()
bluetooth.start_temperature_service()
| 21.21875
| 62
| 0.488954
| 47
| 679
| 6.574468
| 0.297872
| 0.213592
| 0.194175
| 0.213592
| 0.433657
| 0.433657
| 0.291262
| 0
| 0
| 0
| 0
| 0
| 0.325479
| 679
| 31
| 63
| 21.903226
| 0.674672
| 0
| 0
| 0.689655
| 0
| 0
| 0.402062
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.068966
| true
| 0
| 0
| 0
| 0.068966
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5e211fac754af2f33c3ebcab645fa5d3929b6e49
| 31
|
py
|
Python
|
Credentials.py
|
Michotastico/NetworkInformationFlaskServer
|
9890dc73fd5882f36a3a7353c4387a3ec0fe03b7
|
[
"MIT"
] | null | null | null |
Credentials.py
|
Michotastico/NetworkInformationFlaskServer
|
9890dc73fd5882f36a3a7353c4387a3ec0fe03b7
|
[
"MIT"
] | null | null | null |
Credentials.py
|
Michotastico/NetworkInformationFlaskServer
|
9890dc73fd5882f36a3a7353c4387a3ec0fe03b7
|
[
"MIT"
] | null | null | null |
user = 'user'
password = 'pass'
| 15.5
| 17
| 0.645161
| 4
| 31
| 5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 31
| 2
| 17
| 15.5
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.5
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
5e389dab5e8155d498e3530cc36f7c7bb3065fc9
| 1,809
|
py
|
Python
|
tests/cozmo_repl_test.py
|
cozmo-polite/cozmo-repl
|
406706a28b4b1d15a0035a160e82014319d2f5d7
|
[
"Apache-2.0"
] | 7
|
2017-12-09T12:17:12.000Z
|
2019-04-21T12:10:49.000Z
|
tests/cozmo_repl_test.py
|
cozmo-polite/cozmo-repl
|
406706a28b4b1d15a0035a160e82014319d2f5d7
|
[
"Apache-2.0"
] | null | null | null |
tests/cozmo_repl_test.py
|
cozmo-polite/cozmo-repl
|
406706a28b4b1d15a0035a160e82014319d2f5d7
|
[
"Apache-2.0"
] | null | null | null |
import unittest
from cozmo_repl.cozmo_repl import CozmoRepl
from .tests_utils import CheckInvocation, FakeCozmo
class ReplTestCase(unittest.TestCase):
def test_can_create_repl_well_configurated(self):
def ipyfake(usage):
self.assertEqual(usage, "this is an usage")
self.assertIsNotNone(ipyfake.prompts)
ci = CheckInvocation(self, ["WARN", "INFO"])
fake_cozmo = FakeCozmo(
logger_set_level=ci.invoke,
pre_check=lambda cozmo_self: self.assertTrue(cozmo_self.logger.disabled),
post_check=lambda cozmo_self: self.assertFalse(cozmo_self.logger.disabled)
)
repl = CozmoRepl(fake_cozmo, usage="this is an usage", ipyshell=ipyfake)
repl.run()
def test_can_create_repl_well_configurated_verbose(self):
def ipyfake(usage):
self.assertEqual(usage, "this is an usage")
self.assertIsNotNone(ipyfake.prompts)
ci = CheckInvocation(self, ["WARN", "INFO"])
fake_cozmo = FakeCozmo(
logger_set_level=ci.invoke,
pre_check=lambda cozmo_self: self.assertFalse(cozmo_self.logger.disabled),
post_check=lambda cozmo_self: self.assertFalse(cozmo_self.logger.disabled)
)
repl = CozmoRepl(fake_cozmo, usage="this is an usage", ipyshell=ipyfake)
repl.run(verbose=True)
def test_add_path_method_no_extra_path(self):
array = ["path"]
repl = CozmoRepl(FakeCozmo(), path=array)
repl.add_path(None)
self.assertEqual(repl.path, ["path", "."])
def test_add_path_method_with_extra_path(self):
array = ["path"]
repl = CozmoRepl(FakeCozmo(), path=array)
repl.add_path("path1;path2")
self.assertEqual(repl.path, ["path", ".", "path1", "path2"])
| 38.489362
| 86
| 0.660586
| 215
| 1,809
| 5.334884
| 0.265116
| 0.062772
| 0.038361
| 0.045336
| 0.837838
| 0.755885
| 0.755885
| 0.693112
| 0.693112
| 0.693112
| 0
| 0.002869
| 0.229409
| 1,809
| 46
| 87
| 39.326087
| 0.819943
| 0
| 0
| 0.526316
| 0
| 0
| 0.065782
| 0
| 0
| 0
| 0
| 0
| 0.263158
| 1
| 0.157895
| false
| 0
| 0.078947
| 0
| 0.263158
| 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
|
5e3993947ce38e63f00146af43191448d633d7f6
| 136
|
py
|
Python
|
plesicdb/_helpers.py
|
hakiKhuva/plesicdb
|
d4c60ec1eec938aab1aa92f933a6527aff40847c
|
[
"MIT"
] | 2
|
2021-08-17T02:56:44.000Z
|
2021-08-17T02:57:16.000Z
|
plesicdb/_helpers.py
|
hakiKhuva/plesicdb
|
d4c60ec1eec938aab1aa92f933a6527aff40847c
|
[
"MIT"
] | null | null | null |
plesicdb/_helpers.py
|
hakiKhuva/plesicdb
|
d4c60ec1eec938aab1aa92f933a6527aff40847c
|
[
"MIT"
] | null | null | null |
import random
import string
strGen = lambda length:"".join([random.choice(string.ascii_letters+string.digits) for _ in range(length)])
| 27.2
| 106
| 0.779412
| 19
| 136
| 5.473684
| 0.736842
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.095588
| 136
| 4
| 107
| 34
| 0.845528
| 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 | 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
|
5e3c5ff423272c491dcb8c059975dfaf97b91435
| 3,086
|
py
|
Python
|
pyopencl_extension/types/auto_gen/cl_types.py
|
piveloper/pyopencl-extension
|
0f9fede4cfbb1c3f6d99c5e0aa94feddb23a5d4c
|
[
"MIT"
] | null | null | null |
pyopencl_extension/types/auto_gen/cl_types.py
|
piveloper/pyopencl-extension
|
0f9fede4cfbb1c3f6d99c5e0aa94feddb23a5d4c
|
[
"MIT"
] | null | null | null |
pyopencl_extension/types/auto_gen/cl_types.py
|
piveloper/pyopencl-extension
|
0f9fede4cfbb1c3f6d99c5e0aa94feddb23a5d4c
|
[
"MIT"
] | null | null | null |
from pyopencl_extension.modifications_pyopencl import cltypes
from dataclasses import dataclass
import numpy as np
from typing import Callable, Union
@dataclass(frozen=True)
class ClTypesVector:
char2:Union[np.dtype, Callable]=cltypes.char2
char4:Union[np.dtype, Callable]=cltypes.char4
char8:Union[np.dtype, Callable]=cltypes.char8
char16:Union[np.dtype, Callable]=cltypes.char16
short2:Union[np.dtype, Callable]=cltypes.short2
short4:Union[np.dtype, Callable]=cltypes.short4
short8:Union[np.dtype, Callable]=cltypes.short8
short16:Union[np.dtype, Callable]=cltypes.short16
int2:Union[np.dtype, Callable]=cltypes.int2
int4:Union[np.dtype, Callable]=cltypes.int4
int8:Union[np.dtype, Callable]=cltypes.int8
int16:Union[np.dtype, Callable]=cltypes.int16
long2:Union[np.dtype, Callable]=cltypes.long2
long4:Union[np.dtype, Callable]=cltypes.long4
long8:Union[np.dtype, Callable]=cltypes.long8
long16:Union[np.dtype, Callable]=cltypes.long16
uchar2:Union[np.dtype, Callable]=cltypes.uchar2
uchar4:Union[np.dtype, Callable]=cltypes.uchar4
uchar8:Union[np.dtype, Callable]=cltypes.uchar8
uchar16:Union[np.dtype, Callable]=cltypes.uchar16
ushort2:Union[np.dtype, Callable]=cltypes.ushort2
ushort4:Union[np.dtype, Callable]=cltypes.ushort4
ushort8:Union[np.dtype, Callable]=cltypes.ushort8
ushort16:Union[np.dtype, Callable]=cltypes.ushort16
uint2:Union[np.dtype, Callable]=cltypes.uint2
uint4:Union[np.dtype, Callable]=cltypes.uint4
uint8:Union[np.dtype, Callable]=cltypes.uint8
uint16:Union[np.dtype, Callable]=cltypes.uint16
ulong2:Union[np.dtype, Callable]=cltypes.ulong2
ulong4:Union[np.dtype, Callable]=cltypes.ulong4
ulong8:Union[np.dtype, Callable]=cltypes.ulong8
ulong16:Union[np.dtype, Callable]=cltypes.ulong16
half2:Union[np.dtype, Callable]=cltypes.half2
half4:Union[np.dtype, Callable]=cltypes.half4
half8:Union[np.dtype, Callable]=cltypes.half8
half16:Union[np.dtype, Callable]=cltypes.half16
float2:Union[np.dtype, Callable]=cltypes.float2
float4:Union[np.dtype, Callable]=cltypes.float4
float8:Union[np.dtype, Callable]=cltypes.float8
float16:Union[np.dtype, Callable]=cltypes.float16
double2:Union[np.dtype, Callable]=cltypes.double2
double4:Union[np.dtype, Callable]=cltypes.double4
double8:Union[np.dtype, Callable]=cltypes.double8
double16:Union[np.dtype, Callable]=cltypes.double16
@dataclass(frozen=True)
class ClTypesScalar:
char:Union[np.dtype, Callable]=cltypes.char
short:Union[np.dtype, Callable]=cltypes.short
int:Union[np.dtype, Callable]=cltypes.int
long:Union[np.dtype, Callable]=cltypes.long
uchar:Union[np.dtype, Callable]=cltypes.uchar
ushort:Union[np.dtype, Callable]=cltypes.ushort
uint:Union[np.dtype, Callable]=cltypes.uint
ulong:Union[np.dtype, Callable]=cltypes.ulong
half:Union[np.dtype, Callable]=cltypes.half
float:Union[np.dtype, Callable]=cltypes.float
double:Union[np.dtype, Callable]=cltypes.double
@dataclass(frozen=True)
class _ClTypes(ClTypesScalar, ClTypesVector):
pass
| 44.085714
| 61
| 0.768633
| 423
| 3,086
| 5.600473
| 0.179669
| 0.162516
| 0.278599
| 0.464331
| 0.626847
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039611
| 0.10013
| 3,086
| 69
| 62
| 44.724638
| 0.813468
| 0
| 0
| 0.045455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.015152
| 0.060606
| 0
| 0.939394
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
eaa3f6a9899593d896ec4263a4f01aa36879d296
| 221
|
py
|
Python
|
UCourse/events/admin.py
|
Natsu1270/UCourse
|
e8c814d91e54f5f51e4a0fa2df177ebb59544dc2
|
[
"MIT"
] | 1
|
2020-08-31T22:40:27.000Z
|
2020-08-31T22:40:27.000Z
|
UCourse/events/admin.py
|
Natsu1270/UCourse
|
e8c814d91e54f5f51e4a0fa2df177ebb59544dc2
|
[
"MIT"
] | 13
|
2020-08-05T16:17:09.000Z
|
2022-03-12T00:18:42.000Z
|
UCourse/events/admin.py
|
Natsu1270/UCourse
|
e8c814d91e54f5f51e4a0fa2df177ebb59544dc2
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Event
class EventAdmin(admin.ModelAdmin):
list_display = ('__str__', 'title', 'content')
search_fields = ['title',]
admin.site.register(Event, EventAdmin)
| 22.1
| 50
| 0.723982
| 26
| 221
| 5.923077
| 0.730769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149321
| 221
| 9
| 51
| 24.555556
| 0.819149
| 0
| 0
| 0
| 0
| 0
| 0.108597
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.833333
| 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
|
eac57c9a0229b495a3eebc19bc1f0775a6a73906
| 174
|
py
|
Python
|
hcipy/math_util/__init__.py
|
dskleingeld/hcipy
|
85cacfb7a8058506afb288e3acdf3b6059ba2b50
|
[
"MIT"
] | 1
|
2020-07-20T23:25:17.000Z
|
2020-07-20T23:25:17.000Z
|
hcipy/math_util/__init__.py
|
dskleingeld/hcipy
|
85cacfb7a8058506afb288e3acdf3b6059ba2b50
|
[
"MIT"
] | null | null | null |
hcipy/math_util/__init__.py
|
dskleingeld/hcipy
|
85cacfb7a8058506afb288e3acdf3b6059ba2b50
|
[
"MIT"
] | null | null | null |
__all__ = ['inverse_truncated', 'inverse_truncated_modal', 'inverse_tikhonov']
__all__ += ['SVD']
from .matrix_inversion import *
from .singular_value_decomposition import *
| 34.8
| 78
| 0.787356
| 19
| 174
| 6.421053
| 0.684211
| 0.262295
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.091954
| 174
| 5
| 79
| 34.8
| 0.772152
| 0
| 0
| 0
| 0
| 0
| 0.337143
| 0.131429
| 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
|
ead13a4ca74b6d3b42a48cab69abfe1e331bb9d7
| 116
|
py
|
Python
|
examples/pipeline/second_settings.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 213
|
2015-05-13T21:29:35.000Z
|
2022-02-24T12:56:00.000Z
|
examples/pipeline/second_settings.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 248
|
2015-05-13T23:32:16.000Z
|
2022-02-02T21:41:30.000Z
|
examples/pipeline/second_settings.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 39
|
2015-05-18T21:29:42.000Z
|
2022-03-26T16:27:46.000Z
|
ONLY_IN_SECOND = 'This settings is exclusive of second settings'
SIMPLE_CONF = 'Simple override by second settings'
| 38.666667
| 64
| 0.810345
| 17
| 116
| 5.352941
| 0.705882
| 0.307692
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137931
| 116
| 2
| 65
| 58
| 0.91
| 0
| 0
| 0
| 0
| 0
| 0.681034
| 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
|
eae23a1de22c1ed18330da362ee72f4b7c11718e
| 239
|
py
|
Python
|
pythonProject1/venv/Lib/site-packages/jsoner/errors.py
|
mjtomlinson/CNE330_Python_1_Final_Project
|
05020806860937ef37b9a0ad2e27de4897a606de
|
[
"CC0-1.0"
] | null | null | null |
pythonProject1/venv/Lib/site-packages/jsoner/errors.py
|
mjtomlinson/CNE330_Python_1_Final_Project
|
05020806860937ef37b9a0ad2e27de4897a606de
|
[
"CC0-1.0"
] | null | null | null |
pythonProject1/venv/Lib/site-packages/jsoner/errors.py
|
mjtomlinson/CNE330_Python_1_Final_Project
|
05020806860937ef37b9a0ad2e27de4897a606de
|
[
"CC0-1.0"
] | null | null | null |
# -*- coding: utf-8 -*-
class JsonerException(Exception):
"""
Base Exception class
"""
pass
class JsonEncodingError(JsonerException):
"""
This error occurs if *Jsoner* cannot encode your object to json.
"""
| 15.933333
| 68
| 0.623431
| 24
| 239
| 6.208333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005587
| 0.251046
| 239
| 14
| 69
| 17.071429
| 0.826816
| 0.451883
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
eaee474ee17003b7053d74e13118b70c214b260e
| 89
|
py
|
Python
|
Problems/Running average/main.py
|
TataSatyaPratheek/Tic-Tac-Toe
|
fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd
|
[
"MIT"
] | null | null | null |
Problems/Running average/main.py
|
TataSatyaPratheek/Tic-Tac-Toe
|
fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd
|
[
"MIT"
] | null | null | null |
Problems/Running average/main.py
|
TataSatyaPratheek/Tic-Tac-Toe
|
fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd
|
[
"MIT"
] | null | null | null |
seq = input()
a = [(int(seq[i]) + int(seq[i+1]))/2.0 for i in range(len(seq)-1)]
print(a)
| 29.666667
| 66
| 0.561798
| 21
| 89
| 2.380952
| 0.619048
| 0.24
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.051948
| 0.134831
| 89
| 3
| 67
| 29.666667
| 0.597403
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0
| 0
| null | 1
| 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
|
eafb38d33049e3532feea3b51347df8dfc3189ea
| 138
|
py
|
Python
|
posts/forms.py
|
MoratoGarcia/Hackaton-cito
|
9468290addbf906f7f2b5f069afcb791ef692e53
|
[
"CC0-1.0"
] | null | null | null |
posts/forms.py
|
MoratoGarcia/Hackaton-cito
|
9468290addbf906f7f2b5f069afcb791ef692e53
|
[
"CC0-1.0"
] | null | null | null |
posts/forms.py
|
MoratoGarcia/Hackaton-cito
|
9468290addbf906f7f2b5f069afcb791ef692e53
|
[
"CC0-1.0"
] | null | null | null |
from django import forms
from .models import Post
class PostForm(forms.ModelForm):
class Meta:
model=Post
fields=('titulo','cuerpo')
| 19.714286
| 32
| 0.753623
| 19
| 138
| 5.473684
| 0.736842
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137681
| 138
| 7
| 33
| 19.714286
| 0.87395
| 0
| 0
| 0
| 0
| 0
| 0.086331
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
d81a1b5c34553c21d57eb6fbb79c81055568b018
| 244
|
py
|
Python
|
providers/wikipedia/wikipedia_id.py
|
yawks/music_explorer_backend
|
26ec17234a542f86d9c03b0256c22dbbef1f827f
|
[
"MIT"
] | null | null | null |
providers/wikipedia/wikipedia_id.py
|
yawks/music_explorer_backend
|
26ec17234a542f86d9c03b0256c22dbbef1f827f
|
[
"MIT"
] | null | null | null |
providers/wikipedia/wikipedia_id.py
|
yawks/music_explorer_backend
|
26ec17234a542f86d9c03b0256c22dbbef1f827f
|
[
"MIT"
] | null | null | null |
from providers.entities.object_id import ObjectId
class WikipediaId(ObjectId):
def __init__(self, wikipedia_id: str) -> None:
super().__init__(wikipedia_id)
@staticmethod
def get_short_name() -> str:
return "wk"
| 20.333333
| 50
| 0.684426
| 29
| 244
| 5.310345
| 0.758621
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.213115
| 244
| 11
| 51
| 22.181818
| 0.802083
| 0
| 0
| 0
| 0
| 0
| 0.008197
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0.142857
| 0.714286
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
dc2a50b725e5ab957c28ec2d85d9a978d34733c5
| 190
|
py
|
Python
|
scripts/assume_role_lib/util.py
|
pzurzolo/aem-aws-stack-builder
|
51fad6236ece3d608ef37d6a7491c657d1dd27be
|
[
"Apache-2.0"
] | 1
|
2019-04-11T01:39:40.000Z
|
2019-04-11T01:39:40.000Z
|
scripts/assume_role_lib/util.py
|
akashwbgsearch/aem-aws-stack-builder
|
f86e13c557eda0de1601914aaf694d7c783a5f98
|
[
"Apache-2.0"
] | null | null | null |
scripts/assume_role_lib/util.py
|
akashwbgsearch/aem-aws-stack-builder
|
f86e13c557eda0de1601914aaf694d7c783a5f98
|
[
"Apache-2.0"
] | 1
|
2019-04-15T01:54:19.000Z
|
2019-04-15T01:54:19.000Z
|
#!/usr/bin/env python
def clamp(low, x, high):
return low if x < low else high if x > high else x
def unwrap(txt):
return ' '.join(( s.strip() for s in txt.strip().splitlines() ))
| 23.75
| 68
| 0.621053
| 34
| 190
| 3.470588
| 0.588235
| 0.084746
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.215789
| 190
| 7
| 69
| 27.142857
| 0.791946
| 0.105263
| 0
| 0
| 0
| 0
| 0.005917
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
dc33ae62e8735b1fe3289d17ccd347bcfd7df014
| 360
|
py
|
Python
|
jakomics/image.py
|
jeffkimbrel/jakomics
|
7da6239d39cd78d6d47daf7188c20612167acc11
|
[
"MIT"
] | null | null | null |
jakomics/image.py
|
jeffkimbrel/jakomics
|
7da6239d39cd78d6d47daf7188c20612167acc11
|
[
"MIT"
] | null | null | null |
jakomics/image.py
|
jeffkimbrel/jakomics
|
7da6239d39cd78d6d47daf7188c20612167acc11
|
[
"MIT"
] | null | null | null |
from jakomics.file import FILE
class IMAGE(FILE):
def __str__(self):
return "<JAKomics IMAGE class>"
def edge_crop(self, dims):
# dims are l,r,t,b
pass
if __name__ == "__main__":
t = IMAGE("/Users/kimbrel1/Dropbox/LLNL/Projects/BlueCarbon/analysis/images/nanosims/glycolate_1through18@_1_T_14N 12C.tif")
t.view()
| 20
| 128
| 0.666667
| 50
| 360
| 4.46
| 0.76
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.03169
| 0.211111
| 360
| 17
| 129
| 21.176471
| 0.753521
| 0.044444
| 0
| 0
| 0
| 0.111111
| 0.412281
| 0.30117
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0.111111
| 0.111111
| 0.111111
| 0.555556
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
dc72ee6ea0b6c7777d11383fbef15cc080e9a7bc
| 131
|
py
|
Python
|
4.py
|
IuryBRIGNOLI/exerciciol1b
|
6f5c5e752ce8e99930a1a22557cc7bab4769662c
|
[
"MIT"
] | null | null | null |
4.py
|
IuryBRIGNOLI/exerciciol1b
|
6f5c5e752ce8e99930a1a22557cc7bab4769662c
|
[
"MIT"
] | null | null | null |
4.py
|
IuryBRIGNOLI/exerciciol1b
|
6f5c5e752ce8e99930a1a22557cc7bab4769662c
|
[
"MIT"
] | null | null | null |
n1= float(input("Digite um número"))
n2= float(input("Digite outro número"))
print("A soma dos números é de {} :".format((n1+n2)))
| 43.666667
| 54
| 0.671756
| 22
| 131
| 4
| 0.727273
| 0.227273
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034783
| 0.122137
| 131
| 3
| 54
| 43.666667
| 0.730435
| 0
| 0
| 0
| 0
| 0
| 0.477273
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 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
|
f49480d055859b2801e6ad1b2712a30180befecb
| 174
|
py
|
Python
|
ddtrace/contrib/pylons/compat.py
|
zhammer/dd-trace-py
|
4c30f6e36bfa34a63cd9b6884677c977f76d2a01
|
[
"Apache-2.0",
"BSD-3-Clause"
] | 308
|
2016-12-07T16:49:27.000Z
|
2022-03-15T10:06:45.000Z
|
ddtrace/contrib/pylons/compat.py
|
zhammer/dd-trace-py
|
4c30f6e36bfa34a63cd9b6884677c977f76d2a01
|
[
"Apache-2.0",
"BSD-3-Clause"
] | 1,928
|
2016-11-28T17:13:18.000Z
|
2022-03-31T21:43:19.000Z
|
ddtrace/contrib/pylons/compat.py
|
zhammer/dd-trace-py
|
4c30f6e36bfa34a63cd9b6884677c977f76d2a01
|
[
"Apache-2.0",
"BSD-3-Clause"
] | 311
|
2016-11-27T03:01:49.000Z
|
2022-03-18T21:34:03.000Z
|
try:
from pylons.templating import render_mako # noqa
# Pylons > 0.9.7
legacy_pylons = False
except ImportError:
# Pylons <= 0.9.7
legacy_pylons = True
| 19.333333
| 53
| 0.655172
| 24
| 174
| 4.625
| 0.666667
| 0.126126
| 0.144144
| 0.162162
| 0.378378
| 0.378378
| 0
| 0
| 0
| 0
| 0
| 0.046512
| 0.258621
| 174
| 8
| 54
| 21.75
| 0.813953
| 0.201149
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 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
|
f49d5be929c15cc69a8a8cb59f3519ac7c4a9c6e
| 465
|
py
|
Python
|
Management/models.py
|
garvit-joshi/WebWorks
|
1004bff925d4097bdaec25499075d8d5608a2689
|
[
"Apache-2.0"
] | 10
|
2020-10-28T03:49:52.000Z
|
2021-03-13T12:35:29.000Z
|
Management/models.py
|
garvit-joshi/WebWorks
|
1004bff925d4097bdaec25499075d8d5608a2689
|
[
"Apache-2.0"
] | null | null | null |
Management/models.py
|
garvit-joshi/WebWorks
|
1004bff925d4097bdaec25499075d8d5608a2689
|
[
"Apache-2.0"
] | 2
|
2021-11-19T08:25:12.000Z
|
2022-02-11T10:55:04.000Z
|
from django.db import models
# Create your models here.
class Employee(models.Model):
Name = models.CharField(max_length=64)
Email = models.CharField(max_length=64)
Password = models.CharField(max_length=64)
Position = models.CharField(max_length=64)
Salary = models.IntegerField()
def __str__(self):
return f"{self.id}: {self.Name} is {self.Position} with salary of {self.Salary}. Email:{self.Email} and Password:{self.Password}"
| 35.769231
| 137
| 0.716129
| 64
| 465
| 5.078125
| 0.484375
| 0.184615
| 0.221538
| 0.295385
| 0.32
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02046
| 0.15914
| 465
| 13
| 137
| 35.769231
| 0.810742
| 0.051613
| 0
| 0
| 0
| 0.111111
| 0.270455
| 0.054545
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0.222222
| 0.111111
| 0.111111
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
|
0
| 4
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.