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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6a18a2fc35fca4fa0810d624272b1e9cbf085f8d
| 108
|
py
|
Python
|
question.py
|
clash402/quizzer
|
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
|
[
"MIT"
] | 3
|
2021-01-15T15:49:20.000Z
|
2021-03-17T03:17:41.000Z
|
question.py
|
clash402/quizzer
|
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
|
[
"MIT"
] | 2
|
2021-06-10T18:28:21.000Z
|
2021-09-28T08:26:47.000Z
|
question.py
|
clash402/quizzer
|
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
|
[
"MIT"
] | 1
|
2021-07-25T01:55:12.000Z
|
2021-07-25T01:55:12.000Z
|
class Question:
def __init__(self, text, answer):
self.text = text
self.answer = answer
| 21.6
| 37
| 0.611111
| 13
| 108
| 4.769231
| 0.538462
| 0.258065
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.296296
| 108
| 4
| 38
| 27
| 0.815789
| 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
|
6a3765d6e0c8732d6c84c61c5f319467fe077500
| 162
|
py
|
Python
|
snakeskin_ui/custom_widgets/__init__.py
|
ewanbarr/snakeskin
|
b41a5393e9b4ab42fd6245e022dd4923be01815b
|
[
"Apache-2.0"
] | null | null | null |
snakeskin_ui/custom_widgets/__init__.py
|
ewanbarr/snakeskin
|
b41a5393e9b4ab42fd6245e022dd4923be01815b
|
[
"Apache-2.0"
] | null | null | null |
snakeskin_ui/custom_widgets/__init__.py
|
ewanbarr/snakeskin
|
b41a5393e9b4ab42fd6245e022dd4923be01815b
|
[
"Apache-2.0"
] | null | null | null |
from accordion import Accordion,Chord
from drag_drop_listbox import DragDropListBox
from dict_controller import DictController
from plot_window import PlotWindow
| 32.4
| 45
| 0.895062
| 21
| 162
| 6.714286
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098765
| 162
| 4
| 46
| 40.5
| 0.965753
| 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
|
6a38a943ab5ce1ac9459f95622cdd29725183f76
| 2,693
|
py
|
Python
|
samlab/dashboard/credentials.py
|
tshead2/samba
|
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
|
[
"BSD-3-Clause"
] | 3
|
2018-09-04T19:53:20.000Z
|
2021-07-13T20:26:42.000Z
|
samlab/dashboard/credentials.py
|
tshead2/samba
|
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
|
[
"BSD-3-Clause"
] | 15
|
2018-05-24T19:13:05.000Z
|
2020-04-21T20:49:31.000Z
|
samlab/dashboard/credentials.py
|
tshead2/samba
|
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
|
[
"BSD-3-Clause"
] | 1
|
2021-07-13T20:26:47.000Z
|
2021-07-13T20:26:47.000Z
|
# Copyright 2018, National Technology & Engineering Solutions of Sandia, LLC
# (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S.
# Government retains certain rights in this software.
import logging
import traceback
log = logging.getLogger(__name__)
class LDAP(object):
"""Check credentials against an LDAP server."""
def __init__(self, server, user_dn, timeout=5):
self.server = server
self.user_dn = user_dn
self.timeout = timeout
def __call__(self, authorization):
if not authorization:
return False
try:
search_dn = self.user_dn.format(authorization.username)
log.info("Checking credentials for %s with %s.", search_dn, self.server)
import ldap3
ldap_server = ldap3.Server(self.server, use_ssl=True)
connection = ldap3.Connection(ldap_server, user=search_dn, password=authorization.password, receive_timeout=self.timeout)
if not connection.bind():
log.warning("Credential check failed.")
return False
return True
except Exception:
log.error("%s" % traceback.format_exc())
return False
def __repr__(self):
return f"{self.__class__.__module__}.{self.__class__.__name__}(server={self.server!r}, user_dn={self.user_dn!r}, timeout={self.timeout!r})"
class ExactMatch(object):
"""Allow credentials that match the given username and password."""
def __init__(self, username="test", password="test"):
self.username = username
self.password = password
def __call__(self, authorization):
if not authorization:
return False
return authorization.username == self.username and authorization.password == self.password
def __repr__(self):
return f"{self.__class__.__module__}.{self.__class__.__name__}(username={self.username!r}, password={self.password!r})"
class ForbidAll(object):
"""Forbid all credentials."""
def __call__(self, authorization):
return False
def __repr__(self):
return f"{self.__class__.__module__}.{self.__class__.__name__}()"
class PermitAll(object):
"""Permit all non-empty credentials."""
def __call__(self, authorization):
return True if authorization else False
def __repr__(self):
return f"{self.__class__.__module__}.{self.__class__.__name__}()"
class PermitAny(object):
"""Permit any credentials, including empty."""
def __call__(self, authorization):
return True
def __repr__(self):
return f"{self.__class__.__module__}.{self.__class__.__name__}()"
| 30.602273
| 147
| 0.663944
| 309
| 2,693
| 5.313916
| 0.313916
| 0.054811
| 0.033496
| 0.073082
| 0.29659
| 0.29659
| 0.227162
| 0.227162
| 0.227162
| 0.162607
| 0
| 0.007205
| 0.226885
| 2,693
| 87
| 148
| 30.954023
| 0.78146
| 0.149276
| 0
| 0.431373
| 0
| 0.039216
| 0.209199
| 0.176913
| 0
| 0
| 0
| 0
| 0
| 1
| 0.235294
| false
| 0.098039
| 0.058824
| 0.156863
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
dbed91716d712c0578f642316e1d5ca206d1a1be
| 207
|
py
|
Python
|
T.py
|
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
|
0735bb1d7333ea850b91b1a3cf37be659885267b
|
[
"MIT"
] | null | null | null |
T.py
|
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
|
0735bb1d7333ea850b91b1a3cf37be659885267b
|
[
"MIT"
] | null | null | null |
T.py
|
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
|
0735bb1d7333ea850b91b1a3cf37be659885267b
|
[
"MIT"
] | 1
|
2021-03-08T04:44:56.000Z
|
2021-03-08T04:44:56.000Z
|
def T():
for row in range(6):
for col in range(5):
if (row==0 or col==2):
print("*",end=" ")
else:
print(end=" ")
print()
| 23
| 35
| 0.333333
| 24
| 207
| 2.875
| 0.666667
| 0.202899
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039216
| 0.507246
| 207
| 8
| 36
| 25.875
| 0.637255
| 0
| 0
| 0
| 0
| 0
| 0.020101
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0
| 0
| 0
| 0.125
| 0.375
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 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
|
e002f2850c67afa76f663130b5dd8375150bea7d
| 170
|
py
|
Python
|
courier/__init__.py
|
panyam/courier
|
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
|
[
"Apache-2.0"
] | null | null | null |
courier/__init__.py
|
panyam/courier
|
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
|
[
"Apache-2.0"
] | null | null | null |
courier/__init__.py
|
panyam/courier
|
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
|
[
"Apache-2.0"
] | null | null | null |
VERSION = (0, 0, 2)
def get_version(version = None):
version = version or VERSION
return ".".join(map(str, list(version)))
__version__ = get_version(VERSION)
| 17
| 44
| 0.670588
| 23
| 170
| 4.695652
| 0.521739
| 0.518519
| 0.314815
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.021739
| 0.188235
| 170
| 9
| 45
| 18.888889
| 0.76087
| 0
| 0
| 0
| 0
| 0
| 0.005952
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e00fecd1a3b725cf2e10404b0c3bb1adeba521a1
| 64
|
py
|
Python
|
k/stdlib/logging/__init__.py
|
Knewton/k.stdlib
|
9cf9757721480b845467e37cd6e20e266979412f
|
[
"Apache-2.0"
] | null | null | null |
k/stdlib/logging/__init__.py
|
Knewton/k.stdlib
|
9cf9757721480b845467e37cd6e20e266979412f
|
[
"Apache-2.0"
] | null | null | null |
k/stdlib/logging/__init__.py
|
Knewton/k.stdlib
|
9cf9757721480b845467e37cd6e20e266979412f
|
[
"Apache-2.0"
] | null | null | null |
"""This module contains improvements to the logging package."""
| 32
| 63
| 0.765625
| 8
| 64
| 6.125
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 64
| 1
| 64
| 64
| 0.875
| 0.890625
| 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
|
e022eead338624013ac23aadc45d95ba58f02c48
| 1,122
|
py
|
Python
|
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
|
Tommos0/grand-challenge.org
|
187cd857f6a7c9651b7bda8c42c54801f071dd7c
|
[
"Apache-2.0"
] | 1
|
2021-02-09T10:30:44.000Z
|
2021-02-09T10:30:44.000Z
|
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
|
Tommos0/grand-challenge.org
|
187cd857f6a7c9651b7bda8c42c54801f071dd7c
|
[
"Apache-2.0"
] | null | null | null |
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
|
Tommos0/grand-challenge.org
|
187cd857f6a7c9651b7bda8c42c54801f071dd7c
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 2.0.9 on 2018-10-19 16:42
import django.contrib.postgres.fields
import django.contrib.postgres.fields.citext
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [("challenges", "0012_auto_20181019_1446")]
operations = [
migrations.AlterField(
model_name="challenge",
name="filter_classes",
field=django.contrib.postgres.fields.ArrayField(
base_field=django.contrib.postgres.fields.citext.CICharField(
max_length=32
),
default=list,
editable=False,
size=None,
),
),
migrations.AlterField(
model_name="externalchallenge",
name="filter_classes",
field=django.contrib.postgres.fields.ArrayField(
base_field=django.contrib.postgres.fields.citext.CICharField(
max_length=32
),
default=list,
editable=False,
size=None,
),
),
]
| 29.526316
| 77
| 0.55615
| 101
| 1,122
| 6.069307
| 0.485149
| 0.127243
| 0.205546
| 0.264274
| 0.623165
| 0.50571
| 0.50571
| 0.50571
| 0.50571
| 0.50571
| 0
| 0.048143
| 0.35205
| 1,122
| 37
| 78
| 30.324324
| 0.795048
| 0.040107
| 0
| 0.709677
| 1
| 0
| 0.08093
| 0.021395
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.096774
| 0
| 0.193548
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e054ad34a7201de0a8c018bddb342abaa4813ef3
| 57
|
py
|
Python
|
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
|
rodzanto/amazon-sagemaker-pytorch-detectron2
|
4bdf47705bd949502de0cc8721ba20fb630699c1
|
[
"MIT-0"
] | 22
|
2021-03-25T14:16:28.000Z
|
2022-03-29T14:42:23.000Z
|
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
|
rodzanto/amazon-sagemaker-pytorch-detectron2
|
4bdf47705bd949502de0cc8721ba20fb630699c1
|
[
"MIT-0"
] | 7
|
2021-04-16T21:00:28.000Z
|
2022-03-25T08:19:30.000Z
|
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
|
rodzanto/amazon-sagemaker-pytorch-detectron2
|
4bdf47705bd949502de0cc8721ba20fb630699c1
|
[
"MIT-0"
] | 10
|
2021-04-03T08:11:28.000Z
|
2022-03-16T06:35:25.000Z
|
"""Run COCO evaluation with custom # of max detections"""
| 57
| 57
| 0.736842
| 8
| 57
| 5.25
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| 57
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| 57
| 0.857143
| 0.894737
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|
0
| 4
|
e063ab33016dc71627fe628f9e136abc7c1ad053
| 74
|
py
|
Python
|
goal_gen/__init__.py
|
robotics-4-all/goal-gen
|
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
|
[
"MIT"
] | null | null | null |
goal_gen/__init__.py
|
robotics-4-all/goal-gen
|
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
|
[
"MIT"
] | null | null | null |
goal_gen/__init__.py
|
robotics-4-all/goal-gen
|
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
|
[
"MIT"
] | null | null | null |
__version__ = "0.1.0.dev"
from .generator import goal_dsl_generate_goalee
| 24.666667
| 47
| 0.810811
| 12
| 74
| 4.416667
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0
| 4
|
e066fbf19a234d02e8aa219f752317105637be32
| 12,167
|
py
|
Python
|
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
|
DaveCheez/google-cloud-python
|
fc03d4d41f13e9d13db7206438163b3a471fdabd
|
[
"Apache-2.0"
] | 2
|
2021-11-26T07:08:43.000Z
|
2022-03-07T20:20:04.000Z
|
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
|
DaveCheez/google-cloud-python
|
fc03d4d41f13e9d13db7206438163b3a471fdabd
|
[
"Apache-2.0"
] | 40
|
2019-07-16T10:04:48.000Z
|
2020-01-20T09:04:59.000Z
|
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
|
DaveCheez/google-cloud-python
|
fc03d4d41f13e9d13db7206438163b3a471fdabd
|
[
"Apache-2.0"
] | 2
|
2019-07-18T00:05:31.000Z
|
2019-11-27T14:17:22.000Z
|
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc
from google.cloud.redis_v1.proto import (
cloud_redis_pb2 as google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2,
)
from google.longrunning import (
operations_pb2 as google_dot_longrunning_dot_operations__pb2,
)
class CloudRedisStub(object):
"""Configures and manages Cloud Memorystore for Redis instances
Google Cloud Memorystore for Redis v1
The `redis.googleapis.com` service implements the Google Cloud Memorystore
for Redis API and defines the following resource model for managing Redis
instances:
* The service works with a collection of cloud projects, named: `/projects/*`
* Each project has a collection of available locations, named: `/locations/*`
* Each location has a collection of Redis instances, named: `/instances/*`
* As such, Redis instances are resources of the form:
`/projects/{project_id}/locations/{location_id}/instances/{instance_id}`
Note that location_id must be referring to a GCP `region`; for example:
* `projects/redpepper-1290/locations/us-central1/instances/my-redis`
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.ListInstances = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/ListInstances",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesResponse.FromString,
)
self.GetInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/GetInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.GetInstanceRequest.SerializeToString,
response_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.Instance.FromString,
)
self.CreateInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/CreateInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.CreateInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
self.UpdateInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/UpdateInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.UpdateInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
self.ImportInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/ImportInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ImportInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
self.ExportInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/ExportInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ExportInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
self.FailoverInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/FailoverInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.FailoverInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
self.DeleteInstance = channel.unary_unary(
"/google.cloud.redis.v1.CloudRedis/DeleteInstance",
request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.DeleteInstanceRequest.SerializeToString,
response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString,
)
class CloudRedisServicer(object):
"""Configures and manages Cloud Memorystore for Redis instances
Google Cloud Memorystore for Redis v1
The `redis.googleapis.com` service implements the Google Cloud Memorystore
for Redis API and defines the following resource model for managing Redis
instances:
* The service works with a collection of cloud projects, named: `/projects/*`
* Each project has a collection of available locations, named: `/locations/*`
* Each location has a collection of Redis instances, named: `/instances/*`
* As such, Redis instances are resources of the form:
`/projects/{project_id}/locations/{location_id}/instances/{instance_id}`
Note that location_id must be referring to a GCP `region`; for example:
* `projects/redpepper-1290/locations/us-central1/instances/my-redis`
"""
def ListInstances(self, request, context):
"""Lists all Redis instances owned by a project in either the specified
location (region) or all locations.
The location should have the following format:
* `projects/{project_id}/locations/{location_id}`
If `location_id` is specified as `-` (wildcard), then all regions
available to the project are queried, and the results are aggregated.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def GetInstance(self, request, context):
"""Gets the details of a specific Redis instance.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def CreateInstance(self, request, context):
"""Creates a Redis instance based on the specified tier and memory size.
By default, the instance is accessible from the project's
[default network](/compute/docs/networks-and-firewalls#networks).
The creation is executed asynchronously and callers may check the returned
operation to track its progress. Once the operation is completed the Redis
instance will be fully functional. Completed longrunning.Operation will
contain the new instance object in the response field.
The returned operation is automatically deleted after a few hours, so there
is no need to call DeleteOperation.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def UpdateInstance(self, request, context):
"""Updates the metadata and configuration of a specific Redis instance.
Completed longrunning.Operation will contain the new instance object
in the response field. The returned operation is automatically deleted
after a few hours, so there is no need to call DeleteOperation.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def ImportInstance(self, request, context):
"""Import a Redis RDB snapshot file from Cloud Storage into a Redis instance.
Redis may stop serving during this operation. Instance state will be
IMPORTING for entire operation. When complete, the instance will contain
only data from the imported file.
The returned operation is automatically deleted after a few hours, so
there is no need to call DeleteOperation.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def ExportInstance(self, request, context):
"""Export Redis instance data into a Redis RDB format file in Cloud Storage.
Redis will continue serving during this operation.
The returned operation is automatically deleted after a few hours, so
there is no need to call DeleteOperation.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def FailoverInstance(self, request, context):
"""Initiates a failover of the master node to current replica node for a
specific STANDARD tier Cloud Memorystore for Redis instance.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def DeleteInstance(self, request, context):
"""Deletes a specific Redis instance. Instance stops serving and data is
deleted.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def add_CloudRedisServicer_to_server(servicer, server):
rpc_method_handlers = {
"ListInstances": grpc.unary_unary_rpc_method_handler(
servicer.ListInstances,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesRequest.FromString,
response_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesResponse.SerializeToString,
),
"GetInstance": grpc.unary_unary_rpc_method_handler(
servicer.GetInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.GetInstanceRequest.FromString,
response_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.Instance.SerializeToString,
),
"CreateInstance": grpc.unary_unary_rpc_method_handler(
servicer.CreateInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.CreateInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
"UpdateInstance": grpc.unary_unary_rpc_method_handler(
servicer.UpdateInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.UpdateInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
"ImportInstance": grpc.unary_unary_rpc_method_handler(
servicer.ImportInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ImportInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
"ExportInstance": grpc.unary_unary_rpc_method_handler(
servicer.ExportInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ExportInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
"FailoverInstance": grpc.unary_unary_rpc_method_handler(
servicer.FailoverInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.FailoverInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
"DeleteInstance": grpc.unary_unary_rpc_method_handler(
servicer.DeleteInstance,
request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.DeleteInstanceRequest.FromString,
response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
"google.cloud.redis.v1.CloudRedis", rpc_method_handlers
)
server.add_generic_rpc_handlers((generic_handler,))
| 51.555085
| 136
| 0.757377
| 1,407
| 12,167
| 6.198294
| 0.15565
| 0.038528
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| 0.040936
| 0.744525
| 0.737301
| 0.729045
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| 0.652907
| 0.652907
| 0
| 0.007901
| 0.178187
| 12,167
| 235
| 137
| 51.774468
| 0.864286
| 0.30443
| 0
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| 1
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| 0.108714
| 0.050457
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| false
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| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0ec11af4715e8154b66219ac91173bbe239bceae
| 75
|
py
|
Python
|
tests/nutsml/test_viewer.py
|
maet3608/nuts-ml
|
2551612a47bc6e9efa534eda0db5d8c5def51887
|
[
"Apache-2.0"
] | 39
|
2017-02-07T03:22:41.000Z
|
2021-11-24T20:27:57.000Z
|
tests/nutsml/test_viewer.py
|
maet3608/nuts-ml
|
2551612a47bc6e9efa534eda0db5d8c5def51887
|
[
"Apache-2.0"
] | 19
|
2017-02-13T22:22:30.000Z
|
2019-01-31T04:13:39.000Z
|
tests/nutsml/test_viewer.py
|
maet3608/nuts-ml
|
2551612a47bc6e9efa534eda0db5d8c5def51887
|
[
"Apache-2.0"
] | 13
|
2017-06-01T13:44:54.000Z
|
2020-09-08T04:51:36.000Z
|
"""
.. module:: test_viewer
:synopsis: Unit tests for viewer module
"""
| 15
| 42
| 0.653333
| 9
| 75
| 5.333333
| 0.777778
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186667
| 75
| 4
| 43
| 18.75
| 0.786885
| 0.88
| 0
| null | 0
| null | 0
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| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
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|
0
| 4
|
0ed76e49dae5b7957ad606842a6b2f835a54d450
| 984
|
py
|
Python
|
Project/spider_middlewares.py
|
RuanJylf/Scrapy_Frame
|
fe62dd9c9f6f486114c42b75f3101652e3c8b024
|
[
"MIT"
] | null | null | null |
Project/spider_middlewares.py
|
RuanJylf/Scrapy_Frame
|
fe62dd9c9f6f486114c42b75f3101652e3c8b024
|
[
"MIT"
] | null | null | null |
Project/spider_middlewares.py
|
RuanJylf/Scrapy_Frame
|
fe62dd9c9f6f486114c42b75f3101652e3c8b024
|
[
"MIT"
] | null | null | null |
# coding=utf-8
class TestSpiderMiddleware1:
'''实现爬虫中间件'''
def process_request(self, request):
'''
处理请求
:param request:请求
:return: 请求
'''
# print("TestSpiderMiddleware1 -- process_request")
return request
def process_response(self, response):
'''
处理response
:param response:response
:return:response
'''
# print("TestSpiderMiddleware1 -- process_response")
return response
class TestSpiderMiddleware2:
'''实现爬虫中间件'''
def process_request(self, request):
'''
处理请求
:param request:请求
:return: 请求
'''
# print("TestSpiderMiddleware2 -- process_request")
return request
def process_response(self, response):
'''
处理response
:param response:response
:return:response
'''
# print("TestSpiderMiddleware2 -- process_response")
return response
| 21.866667
| 60
| 0.567073
| 77
| 984
| 7.142857
| 0.233766
| 0.072727
| 0.16
| 0.087273
| 0.629091
| 0.629091
| 0.629091
| 0.629091
| 0.629091
| 0.629091
| 0
| 0.010622
| 0.330285
| 984
| 44
| 61
| 22.363636
| 0.823976
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| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
0eda44884ea95f02bed13065b6f0c575d2d2e56f
| 3,543
|
py
|
Python
|
var/spack/repos/builtin/packages/py-gitpython/package.py
|
jeanbez/spack
|
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | null | null | null |
var/spack/repos/builtin/packages/py-gitpython/package.py
|
jeanbez/spack
|
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | 8
|
2021-11-09T20:28:40.000Z
|
2022-03-15T03:26:33.000Z
|
var/spack/repos/builtin/packages/py-gitpython/package.py
|
jeanbez/spack
|
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
|
[
"ECL-2.0",
"Apache-2.0",
"MIT-0",
"MIT"
] | 2
|
2019-02-08T20:37:20.000Z
|
2019-03-31T15:19:26.000Z
|
# Copyright 2013-2022 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)
from spack.package import *
class PyGitpython(PythonPackage):
"""GitPython is a python library used to interact with Git repositories."""
homepage = "https://gitpython.readthedocs.org"
pypi = "GitPython/GitPython-3.1.12.tar.gz"
version('3.1.24', sha256='df83fdf5e684fef7c6ee2c02fc68a5ceb7e7e759d08b694088d0cacb4eba59e5')
version('3.1.23', sha256='aaae7a3bfdf0a6db30dc1f3aeae47b71cd326d86b936fe2e158aa925fdf1471c')
version('3.1.22', sha256='e1589f27c3cd1f33b22db1df194201b5abca6b4cc5450f13f9c371e099c1b24f')
version('3.1.20', sha256='df0e072a200703a65387b0cfdf0466e3bab729c0458cf6b7349d0e9877636519')
version('3.1.19', sha256='18f4039b96b5567bc4745eb851737ce456a2d499cecd71e84f5c0950e92d0e53')
version('3.1.18', sha256='b838a895977b45ab6f0cc926a9045c8d1c44e2b653c1fcc39fe91f42c6e8f05b')
version('3.1.17', sha256='ee24bdc93dce357630764db659edaf6b8d664d4ff5447ccfeedd2dc5c253f41e')
version('3.1.16', sha256='2bfcd25e6b81fe431fa3ab1f0975986cfddabf7870a323c183f3afbc9447c0c5')
version('3.1.15', sha256='05af150f47a5cca3f4b0af289b73aef8cf3c4fe2385015b06220cbcdee48bb6e')
version('3.1.14', sha256='be27633e7509e58391f10207cd32b2a6cf5b908f92d9cd30da2e514e1137af61')
version('3.1.13', sha256='8621a7e777e276a5ec838b59280ba5272dd144a18169c36c903d8b38b99f750a')
version('3.1.12', sha256='42dbefd8d9e2576c496ed0059f3103dcef7125b9ce16f9d5f9c834aed44a1dac')
version('3.1.11', sha256='befa4d101f91bad1b632df4308ec64555db684c360bd7d2130b4807d49ce86b8')
version('3.1.10', sha256='f488d43600d7299567b59fe41497d313e7c1253a9f2a8ebd2df8af2a1151c71d')
version('3.1.9', sha256='a03f728b49ce9597a6655793207c6ab0da55519368ff5961e4a74ae475b9fa8e')
version('3.1.8', sha256='080bf8e2cf1a2b907634761c2eaefbe83b69930c94c66ad11b65a8252959f912')
version('3.1.7', sha256='2db287d71a284e22e5c2846042d0602465c7434d910406990d5b74df4afb0858')
version('3.1.6', sha256='b54969b3262d4647f80ace8e9dd4e3f99ac30cc0f3e766415b349208f810908f')
version('3.1.5', sha256='90400ecfa87bac36ac75dfa7b62e83a02017b51759f6eef4494e4de775b2b4be')
version('3.1.4', sha256='fa98ce1f05805d59bbc3adb16c0780e5ca43b5ea9422feecf1cd0949a61d947e')
version('3.1.3', sha256='e107af4d873daed64648b4f4beb89f89f0cfbe3ef558fc7821ed2331c2f8da1a')
version('3.1.2', sha256='864a47472548f3ba716ca202e034c1900f197c0fb3a08f641c20c3cafd15ed94')
version('3.1.1', sha256='6d4f10e2aaad1864bb0f17ec06a2c2831534140e5883c350d58b4e85189dab74')
version('3.1.0', sha256='e426c3b587bd58c482f0b7fe6145ff4ac7ae6c82673fc656f489719abca6f4cb')
version('3.0.9', sha256='7e5df21bfef38505115ad92544fb379e6fedb2753f3b709174c4358cecd0cb97')
version('0.3.6', sha256='e6599fcb939cb9b25a015a429702db39de10f2b493655ed5669c49c37707d233')
depends_on('python@3.4:', type=('build', 'run'))
depends_on('python@3.5:', type=('build', 'run'), when='@3.1.15:')
depends_on('python@3.6:', type=('build', 'run'), when='@3.1.18:')
depends_on('python@3.7:', type=('build', 'run'), when='@3.1.22:')
depends_on('py-setuptools', type='build')
depends_on('py-gitdb@4.0.1:4', type=('build', 'run'))
depends_on('py-typing-extensions@3.7.4.0:', type=('build', 'run'), when='@3.1.16: ^python@:3.7')
depends_on('py-typing-extensions@3.7.4.3:', type=('build', 'run'), when='@3.1.19: ^python@:3.10')
| 70.86
| 101
| 0.777025
| 315
| 3,543
| 8.714286
| 0.35873
| 0.021858
| 0.078689
| 0.029144
| 0.067395
| 0.067395
| 0.021858
| 0.021858
| 0
| 0
| 0
| 0.384924
| 0.086367
| 3,543
| 49
| 102
| 72.306122
| 0.463083
| 0.073102
| 0
| 0
| 0
| 0
| 0.651298
| 0.535878
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.026316
| 0
| 0.105263
| 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
|
0ee4739c18627ff1180203a33b555bb38abefc6b
| 740
|
py
|
Python
|
workout_tracker/exercises/admin.py
|
e-dang/Workout-Tracker
|
00a27597ea628cff62b320d616f56b2df4f344a0
|
[
"MIT"
] | null | null | null |
workout_tracker/exercises/admin.py
|
e-dang/Workout-Tracker
|
00a27597ea628cff62b320d616f56b2df4f344a0
|
[
"MIT"
] | null | null | null |
workout_tracker/exercises/admin.py
|
e-dang/Workout-Tracker
|
00a27597ea628cff62b320d616f56b2df4f344a0
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import ExerciseTemplate, Exercise, WorkloadTemplate, Workload, SetTemplate, Set
class ExerciseTemplateAdmin(admin.ModelAdmin):
pass
class ExerciseAdmin(admin.ModelAdmin):
pass
class WorkloadTemplateAdmin(admin.ModelAdmin):
pass
class WorkloadAdmin(admin.ModelAdmin):
pass
class SetTemplateAdmin(admin.ModelAdmin):
pass
class SetAdmin(admin.ModelAdmin):
pass
admin.site.register(ExerciseTemplate, ExerciseTemplateAdmin)
admin.site.register(Exercise, ExerciseAdmin)
admin.site.register(WorkloadTemplate, WorkloadTemplateAdmin)
admin.site.register(Workload, WorkloadAdmin)
admin.site.register(SetTemplate, SetTemplateAdmin)
admin.site.register(Set, SetAdmin)
| 21.142857
| 92
| 0.808108
| 74
| 740
| 8.081081
| 0.310811
| 0.150502
| 0.190635
| 0.200669
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109459
| 740
| 34
| 93
| 21.764706
| 0.907436
| 0
| 0
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.3
| 0.1
| 0
| 0.4
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
0efa03064cb2b39b9a66c3e97b004812eacef440
| 109
|
py
|
Python
|
procuret/errors/error.py
|
Procuret/procuret-python
|
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
|
[
"MIT"
] | null | null | null |
procuret/errors/error.py
|
Procuret/procuret-python
|
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
|
[
"MIT"
] | null | null | null |
procuret/errors/error.py
|
Procuret/procuret-python
|
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
|
[
"MIT"
] | 1
|
2020-10-28T14:26:21.000Z
|
2020-10-28T14:26:21.000Z
|
"""
Procuret Python
Error Module
author: hugh@blinkybeach.com
"""
class ProcuretError(Exception):
pass
| 10.9
| 31
| 0.733945
| 12
| 109
| 6.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155963
| 109
| 9
| 32
| 12.111111
| 0.869565
| 0.522936
| 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
|
1601ae8a693ba138d7b7c1e35c977742c147bfd3
| 216
|
py
|
Python
|
vol4/191.py
|
EdisonAlgorithms/ProjectEuler
|
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
|
[
"MIT"
] | null | null | null |
vol4/191.py
|
EdisonAlgorithms/ProjectEuler
|
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
|
[
"MIT"
] | null | null | null |
vol4/191.py
|
EdisonAlgorithms/ProjectEuler
|
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
|
[
"MIT"
] | null | null | null |
if __name__ == "__main__":
lst = [1, 3, 0, 2, 1, 0, 0, 1]
while lst[0] < 30:
n, t, a, b, c, d, e, f = lst
lst = [n + 1, 2 * t + b - a, c, 2 * b - a + d, t - (a + c), e, f, t]
print lst[1]
| 30.857143
| 76
| 0.37037
| 46
| 216
| 1.565217
| 0.413043
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 0.398148
| 216
| 6
| 77
| 36
| 0.438462
| 0
| 0
| 0
| 0
| 0
| 0.037037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.166667
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
16422bad2df1c8e4796f8368f699db522100af5f
| 142
|
py
|
Python
|
app/models/__init__.py
|
premanuj/visa-ui
|
7ee4a6827d1542581a57f2159bb79c666c5157b0
|
[
"MIT"
] | 2
|
2019-03-10T15:34:24.000Z
|
2020-06-10T09:34:06.000Z
|
app/models/__init__.py
|
premanuj/visa-ui
|
7ee4a6827d1542581a57f2159bb79c666c5157b0
|
[
"MIT"
] | 1
|
2018-06-05T15:38:39.000Z
|
2018-06-05T15:38:39.000Z
|
app/models/__init__.py
|
premanuj/visa-ui
|
7ee4a6827d1542581a57f2159bb79c666c5157b0
|
[
"MIT"
] | null | null | null |
from .base import *
from .user import *
from .department import *
__all__ = (
user.__all__ +
base.__all__ +
department.__all__
)
| 14.2
| 25
| 0.661972
| 16
| 142
| 4.875
| 0.375
| 0.25641
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.239437
| 142
| 9
| 26
| 15.777778
| 0.722222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.375
| 0
| 0.375
| 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
|
16606fba3a8d5113e0b02672238663e6ab4c647e
| 121
|
py
|
Python
|
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
|
alexey-anufriev/intellij-community
|
ffcd46f14e630acdefcc76e2bfc7c43d2449013a
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
|
alexey-anufriev/intellij-community
|
ffcd46f14e630acdefcc76e2bfc7c43d2449013a
|
[
"Apache-2.0"
] | 1
|
2020-07-30T19:04:47.000Z
|
2020-07-30T19:04:47.000Z
|
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
|
bradleesand/intellij-community
|
750ff9c10333c9c1278c00dbe8d88c877b1b9749
|
[
"Apache-2.0"
] | 1
|
2020-10-15T05:56:42.000Z
|
2020-10-15T05:56:42.000Z
|
from b import ID
def func(x: ID):
pass
func(<warning descr="Expected type 'ID', got 'int' instead">42</warning>)
| 13.444444
| 73
| 0.652893
| 20
| 121
| 3.95
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020408
| 0.190083
| 121
| 8
| 74
| 15.125
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0.305785
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.25
| 0.25
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
1661ce160ed44c65a38076e6e70cf5a6d883438c
| 87
|
py
|
Python
|
2022/Interesting-Libraries/copy-and-paste.py
|
Muramatsu2602/python-study
|
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
|
[
"MIT"
] | null | null | null |
2022/Interesting-Libraries/copy-and-paste.py
|
Muramatsu2602/python-study
|
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
|
[
"MIT"
] | null | null | null |
2022/Interesting-Libraries/copy-and-paste.py
|
Muramatsu2602/python-study
|
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
|
[
"MIT"
] | null | null | null |
import pyperclip
pyperclip.copy("This will be on you clipboard...")
pyperclip.paste()
| 17.4
| 50
| 0.758621
| 12
| 87
| 5.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114943
| 87
| 4
| 51
| 21.75
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.367816
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
16631323fb102edae3a8894779023833ee457448
| 198
|
py
|
Python
|
src/backend/endpoints/hello.py
|
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
|
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
|
[
"MIT"
] | 2
|
2021-02-11T03:41:27.000Z
|
2021-03-04T04:05:56.000Z
|
src/backend/endpoints/hello.py
|
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
|
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
|
[
"MIT"
] | 1
|
2021-04-26T22:10:32.000Z
|
2021-04-26T22:10:32.000Z
|
src/backend/endpoints/hello.py
|
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
|
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
|
[
"MIT"
] | null | null | null |
from flask.views import MethodView
class Hello(MethodView):
def get(self):
return "Hello, world!"
def register(app):
app.add_url_rule("/hello", view_func=Hello.as_view("hello"))
| 18
| 64
| 0.686869
| 28
| 198
| 4.714286
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.176768
| 198
| 10
| 65
| 19.8
| 0.809816
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0.166667
| 0.833333
| 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
|
166647a57a674201e20f8bc415bb83607a9ab2d3
| 492
|
py
|
Python
|
src/containment.py
|
yanstefanovich/rectangles
|
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
|
[
"MIT"
] | null | null | null |
src/containment.py
|
yanstefanovich/rectangles
|
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
|
[
"MIT"
] | null | null | null |
src/containment.py
|
yanstefanovich/rectangles
|
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
|
[
"MIT"
] | null | null | null |
def check_line_containment(line_1, line_2):
return (line_1[0] <= line_2[0] and line_1[1] >= line_2[1])
def containment(rec_1, rec_2):
is__rec_1__in__rec_2 = check_line_containment(rec_1.get('x'), rec_2.get(
'x')) and check_line_containment(rec_1.get('y'), rec_2.get('y'))
is__rec_2__in__rec_1 = check_line_containment(rec_2.get('x'), rec_1.get(
'x')) and check_line_containment(rec_2.get('y'), rec_1.get('y'))
return is__rec_1__in__rec_2 or is__rec_2__in__rec_1
| 37.846154
| 74
| 0.715447
| 100
| 492
| 2.94
| 0.16
| 0.122449
| 0.340136
| 0.312925
| 0.578231
| 0.578231
| 0.204082
| 0
| 0
| 0
| 0
| 0.065421
| 0.130081
| 492
| 12
| 75
| 41
| 0.621495
| 0
| 0
| 0
| 0
| 0
| 0.01626
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0.125
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
1666d399a8af367fbd5c9f214310f6b7c31bdc5f
| 355
|
py
|
Python
|
boilerplate/python/print_module.py
|
LoLei/design-patterns-examples
|
213241ab94c8a5e74a3faa9c5f554d557e60b753
|
[
"MIT"
] | 3
|
2020-02-11T20:37:13.000Z
|
2020-07-31T14:16:51.000Z
|
boilerplate/python/print_module.py
|
LoLei/design-patterns-examples
|
213241ab94c8a5e74a3faa9c5f554d557e60b753
|
[
"MIT"
] | null | null | null |
boilerplate/python/print_module.py
|
LoLei/design-patterns-examples
|
213241ab94c8a5e74a3faa9c5f554d557e60b753
|
[
"MIT"
] | null | null | null |
print('[print_module.py] Begin execution')
print('[print_module.py] __name__ is:', __name__)
def fancy_module_function():
print('[print_module.py] Running fancy module function')
if __name__ == '__main__':
import sys
if len(sys.argv) == 2 and sys.argv[1] == 'fancy':
fancy_module_function()
print('[print_module.py] End execution')
| 27.307692
| 60
| 0.695775
| 49
| 355
| 4.55102
| 0.428571
| 0.179372
| 0.286996
| 0.32287
| 0.331839
| 0.331839
| 0.331839
| 0
| 0
| 0
| 0
| 0.006667
| 0.15493
| 355
| 12
| 61
| 29.583333
| 0.736667
| 0
| 0
| 0
| 0
| 0
| 0.433803
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| true
| 0
| 0.111111
| 0
| 0.222222
| 0.444444
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
16832f43b683d0612efb99e27cfe5d2aac740b81
| 83,112
|
py
|
Python
|
modules/chempy/protein_amber.py
|
hryknkgw/pymolwin
|
4a1335e90497dbcbfa789f1285a7c1ad84a051f8
|
[
"CNRI-Python"
] | 2
|
2019-05-23T22:17:29.000Z
|
2020-07-03T14:36:22.000Z
|
Example/feature-3.1.0/tools/bin/protein_amber.py
|
MukundhMurthy/NucleicNet
|
fca09d38b9a70d2c402414df7cc06b9dd2824449
|
[
"BSD-3-Clause"
] | null | null | null |
Example/feature-3.1.0/tools/bin/protein_amber.py
|
MukundhMurthy/NucleicNet
|
fca09d38b9a70d2c402414df7cc06b9dd2824449
|
[
"BSD-3-Clause"
] | null | null | null |
#A* -------------------------------------------------------------------
#B* This file contains source code for the PyMOL computer program
#C* copyright 1998-2000 by Warren Lyford Delano of DeLano Scientific.
#D* -------------------------------------------------------------------
#E* It is unlawful to modify or remove this copyright notice.
#F* -------------------------------------------------------------------
#G* Please see the accompanying LICENSE file for further information.
#H* -------------------------------------------------------------------
#I* Additional authors of this source file include:
#-*
#-*
#-*
#Z* -------------------------------------------------------------------
normal = {
('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } ,
('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } ,
('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } ,
('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0337 } ,
('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1825 } ,
('ALA' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('ALA' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0823 } ,
('ALA' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('ALA' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('CYM' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.2440 } ,
('CYM' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.2440 } ,
('CYM' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6160 } ,
('CYM' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0350 } ,
('CYM' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.7360 } ,
('CYM' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2520 } ,
('CYM' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0480 } ,
('CYM' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4630 } ,
('CYM' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5040 } ,
('CYM' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.7360 } ,
('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1112 } ,
('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1112 } ,
('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0213 } ,
('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1231 } ,
('CYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('CYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1124 } ,
('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.1933 } ,
('CYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('CYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3119 } ,
('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0910 } ,
('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0910 } ,
('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0429 } ,
('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0790 } ,
('CYX' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('CYX' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0766 } ,
('CYX' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('CYX' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.1081 } ,
('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0122 } ,
('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0122 } ,
('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5366 } ,
('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0381 } ,
('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0303 } ,
('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7994 } ,
('ASP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2936 } ,
('ASP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0880 } ,
('ASP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5163 } ,
('ASP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5819 } ,
('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8014 } ,
('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8014 } ,
('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0488 } ,
('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0488 } ,
('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0341 } ,
('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0316 } ,
('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.6462 } ,
('ASH' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('ASH' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0864 } ,
('ASH' , 'HD2' ) : { 'type' : 'HO' , 'charge' : 0.4747 } ,
('ASH' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('ASH' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5554 } ,
('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.6376 } ,
('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0173 } ,
('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0425 } ,
('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0173 } ,
('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0425 } ,
('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5366 } ,
('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0397 } ,
('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0560 } ,
('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8054 } ,
('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0136 } ,
('GLU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2936 } ,
('GLU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1105 } ,
('GLU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5163 } ,
('GLU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5819 } ,
('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8188 } ,
('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8188 } ,
('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } ,
('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0430 } ,
('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } ,
('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0430 } ,
('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0145 } ,
('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0071 } ,
('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.6801 } ,
('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0174 } ,
('GLP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('GLP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0779 } ,
('GLP' , 'HE2' ) : { 'type' : 'HO' , 'charge' : 0.4641 } ,
('GLP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('GLP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.5838 } ,
('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.6511 } ,
('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1330 } ,
('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1430 } ,
('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } ,
('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1330 } ,
('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1430 } ,
('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } ,
('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0024 } ,
('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0343 } ,
('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1256 } ,
('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1256 } ,
('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1704 } ,
('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1704 } ,
('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0118 } ,
('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.1072 } ,
('PHE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('PHE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0978 } ,
('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1297 } ,
('PHE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('PHE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.0698 } ,
('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0252 } ,
('GLY' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('GLY' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0698 } ,
('GLY' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('GLY' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3866 } ,
('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2681 } ,
('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0810 } ,
('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2317 } ,
('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3911 } ,
('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0810 } ,
('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } ,
('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1354 } ,
('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0414 } ,
('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1141 } ,
('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0170 } ,
('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0012 } ,
('HIP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } ,
('HIP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1212 } ,
('HIP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } ,
('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1513 } ,
('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1718 } ,
('HIP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } ,
('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1435 } ,
('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0367 } ,
('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1862 } ,
('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3339 } ,
('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0367 } ,
('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0581 } ,
('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0074 } ,
('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2207 } ,
('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1635 } ,
('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.1868 } ,
('HIE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('HIE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1360 } ,
('HIE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5432 } ,
('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2795 } ,
('HIE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3649 } ,
('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1392 } ,
('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0402 } ,
('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1147 } ,
('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0402 } ,
('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0188 } ,
('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0462 } ,
('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1292 } ,
('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.2057 } ,
('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0266 } ,
('HID' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('HID' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0881 } ,
('HID' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3811 } ,
('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5727 } ,
('HID' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } ,
('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } ,
('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } ,
('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0236 } ,
('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } ,
('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } ,
('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0236 } ,
('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } ,
('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0597 } ,
('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1303 } ,
('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0660 } ,
('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0430 } ,
('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3204 } ,
('ILE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('ILE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0869 } ,
('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0187 } ,
('ILE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('ILE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } ,
('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0362 } ,
('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0621 } ,
('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1135 } ,
('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0103 } ,
('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } ,
('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0362 } ,
('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0621 } ,
('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1135 } ,
('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0103 } ,
('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } ,
('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } ,
('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2400 } ,
('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0094 } ,
('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0479 } ,
('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0143 } ,
('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0187 } ,
('LYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } ,
('LYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1426 } ,
('LYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } ,
('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3854 } ,
('LYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } ,
('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0457 } ,
('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0457 } ,
('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0518 } ,
('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1102 } ,
('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4121 } ,
('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4121 } ,
('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3531 } ,
('LEU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('LEU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0922 } ,
('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0361 } ,
('LEU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('LEU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } ,
('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0241 } ,
('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } ,
('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0440 } ,
('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0241 } ,
('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } ,
('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0440 } ,
('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0237 } ,
('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0342 } ,
('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0536 } ,
('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0018 } ,
('MET' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('MET' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0880 } ,
('MET' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('MET' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2737 } ,
('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4196 } ,
('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0797 } ,
('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4196 } ,
('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0797 } ,
('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0143 } ,
('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2041 } ,
('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7130 } ,
('ASN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('ASN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1048 } ,
('ASN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.9191 } ,
('ASN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5931 } ,
('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0253 } ,
('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0391 } ,
('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0213 } ,
('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0253 } ,
('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0391 } ,
('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0213 } ,
('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5896 } ,
('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0266 } ,
('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0070 } ,
('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0192 } ,
('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0189 } ,
('PRO' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0641 } ,
('PRO' , 'N' ) : { 'type' : 'N' , 'charge' : -0.2548 } ,
('PRO' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5748 } ,
('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4251 } ,
('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0171 } ,
('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4251 } ,
('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0352 } ,
('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0171 } ,
('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0352 } ,
('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0031 } ,
('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0036 } ,
('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.6951 } ,
('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0645 } ,
('GLN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('GLN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0850 } ,
('GLN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -0.9407 } ,
('GLN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6086 } ,
('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4478 } ,
('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4478 } ,
('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0327 } ,
('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0687 } ,
('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0285 } ,
('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4478 } ,
('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4478 } ,
('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0327 } ,
('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0687 } ,
('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0285 } ,
('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } ,
('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2637 } ,
('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0007 } ,
('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0486 } ,
('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0390 } ,
('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8076 } ,
('ARG' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } ,
('ARG' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1560 } ,
('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3456 } ,
('ARG' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } ,
('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5295 } ,
('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8627 } ,
('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8627 } ,
('ARG' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } ,
('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0352 } ,
('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0352 } ,
('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0249 } ,
('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2117 } ,
('SER' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('SER' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0843 } ,
('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4275 } ,
('SER' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('SER' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6546 } ,
('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4102 } ,
('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } ,
('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } ,
('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } ,
('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0389 } ,
('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3654 } ,
('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.2438 } ,
('THR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('THR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1007 } ,
('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : 0.0043 } ,
('THR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('THR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6761 } ,
('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } ,
('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0875 } ,
('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2985 } ,
('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3192 } ,
('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3192 } ,
('VAL' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('VAL' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0969 } ,
('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : -0.0297 } ,
('VAL' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('VAL' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2062 } ,
('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3412 } ,
('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0339 } ,
('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1417 } ,
('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1572 } ,
('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0339 } ,
('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1700 } ,
('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1447 } ,
('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0275 } ,
('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0050 } ,
('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1638 } ,
('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1243 } ,
('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1380 } ,
('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.2387 } ,
('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.1415 } ,
('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1134 } ,
('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2601 } ,
('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.1972 } ,
('TRP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('TRP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1123 } ,
('TRP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3418 } ,
('TRP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1699 } ,
('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1656 } ,
('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } ,
('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1699 } ,
('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1656 } ,
('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } ,
('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } ,
('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0014 } ,
('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0152 } ,
('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1906 } ,
('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1906 } ,
('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2341 } ,
('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2341 } ,
('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : -0.0011 } ,
('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3226 } ,
('TYR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('TYR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0876 } ,
('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.3992 } ,
('TYR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('TYR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5579 } ,
('NME' , '1HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } ,
('NME' , '2HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } ,
('NME' , '3HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } ,
('NME' , 'CH3' ) : { 'type' : 'CT' , 'charge' : -0.1490 } ,
('NME' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } ,
('NME' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } ,
('ACE' , '1HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } ,
('ACE' , '2HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } ,
('ACE' , '3HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } ,
('ACE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5972 } ,
('ACE' , 'CH3' ) : { 'type' : 'CT' , 'charge' : -0.3662 } ,
('ACE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } ,
}
n_terminal = {
('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } ,
('ALA' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } ,
('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } ,
('ALA' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } ,
('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } ,
('ALA' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } ,
('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0962 } ,
('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0597 } ,
('ALA' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0889 } ,
('ALA' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1414 } ,
('ALA' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('CYS' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } ,
('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1188 } ,
('CYS' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } ,
('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1188 } ,
('CYS' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } ,
('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0927 } ,
('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1195 } ,
('CYS' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1411 } ,
('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.1975 } ,
('CYS' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1325 } ,
('CYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3298 } ,
('CYX' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } ,
('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0680 } ,
('CYX' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } ,
('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0680 } ,
('CYX' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } ,
('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.1055 } ,
('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0277 } ,
('CYX' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0922 } ,
('CYX' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2069 } ,
('CYX' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.0984 } ,
('ASP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } ,
('ASP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } ,
('ASP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } ,
('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0292 } ,
('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0235 } ,
('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8194 } ,
('ASP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1141 } ,
('ASP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0782 } ,
('ASP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } ,
('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8084 } ,
('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8084 } ,
('ASH' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } ,
('ASH' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } ,
('ASH' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } ,
('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } ,
('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0292 } ,
('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0235 } ,
('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8194 } ,
('ASH' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1141 } ,
('ASH' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0782 } ,
('ASH' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } ,
('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.8084 } ,
('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.8084 } ,
('GLU' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } ,
('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } ,
('GLU' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } ,
('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } ,
('GLU' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } ,
('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0588 } ,
('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0909 } ,
('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8087 } ,
('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0236 } ,
('GLU' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1202 } ,
('GLU' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0017 } ,
('GLU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } ,
('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8189 } ,
('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8189 } ,
('GLP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } ,
('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } ,
('GLP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } ,
('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } ,
('GLP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } ,
('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } ,
('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0588 } ,
('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0909 } ,
('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8087 } ,
('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0236 } ,
('GLP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1202 } ,
('GLP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0017 } ,
('GLP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } ,
('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.8189 } ,
('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.8189 } ,
('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1374 } ,
('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1433 } ,
('PHE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0104 } ,
('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1374 } ,
('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1433 } ,
('PHE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0104 } ,
('PHE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0733 } ,
('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0330 } ,
('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1392 } ,
('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1391 } ,
('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1602 } ,
('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1603 } ,
('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0031 } ,
('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.1208 } ,
('PHE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1041 } ,
('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1329 } ,
('PHE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1737 } ,
('PHE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('GLY' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } ,
('GLY' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } ,
('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.0895 } ,
('GLY' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } ,
('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0100 } ,
('GLY' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0895 } ,
('GLY' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2943 } ,
('GLY' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3821 } ,
('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2645 } ,
('HIP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } ,
('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0531 } ,
('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2495 } ,
('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3921 } ,
('HIP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } ,
('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0531 } ,
('HIP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } ,
('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } ,
('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0581 } ,
('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0484 } ,
('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1433 } ,
('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0011 } ,
('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0236 } ,
('HIP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1047 } ,
('HIP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2560 } ,
('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1510 } ,
('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1739 } ,
('HIP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } ,
('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1397 } ,
('HIE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } ,
('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0223 } ,
('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1963 } ,
('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3324 } ,
('HIE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } ,
('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0223 } ,
('HIE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } ,
('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0236 } ,
('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0489 } ,
('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2349 } ,
('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1804 } ,
('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.1740 } ,
('HIE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1380 } ,
('HIE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1472 } ,
('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5579 } ,
('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2781 } ,
('HIE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3632 } ,
('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1385 } ,
('HID' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } ,
('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0209 } ,
('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1299 } ,
('HID' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } ,
('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0209 } ,
('HID' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } ,
('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0964 } ,
('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0259 } ,
('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1046 } ,
('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.2127 } ,
('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0399 } ,
('HID' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0958 } ,
('HID' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1542 } ,
('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3819 } ,
('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5711 } ,
('HID' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } ,
('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } ,
('ILE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } ,
('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } ,
('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0201 } ,
('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } ,
('ILE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } ,
('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } ,
('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0201 } ,
('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } ,
('ILE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } ,
('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0257 } ,
('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1885 } ,
('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0908 } ,
('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0387 } ,
('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3720 } ,
('ILE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1031 } ,
('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0213 } ,
('ILE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0311 } ,
('ILE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('LYS' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } ,
('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } ,
('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0283 } ,
('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0633 } ,
('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1171 } ,
('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0121 } ,
('LYS' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } ,
('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } ,
('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0283 } ,
('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0633 } ,
('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1171 } ,
('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0121 } ,
('LYS' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } ,
('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } ,
('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } ,
('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0015 } ,
('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0212 } ,
('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0608 } ,
('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0181 } ,
('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0048 } ,
('LYS' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1180 } ,
('LYS' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0966 } ,
('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3764 } ,
('LYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } ,
('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } ,
('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } ,
('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } ,
('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } ,
('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } ,
('LEU' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } ,
('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0104 } ,
('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0244 } ,
('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4106 } ,
('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4104 } ,
('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3421 } ,
('LEU' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1053 } ,
('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0380 } ,
('LEU' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1010 } ,
('LEU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } ,
('MET' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } ,
('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0125 } ,
('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } ,
('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0292 } ,
('MET' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } ,
('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0125 } ,
('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } ,
('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0292 } ,
('MET' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } ,
('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0221 } ,
('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0865 } ,
('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0341 } ,
('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0334 } ,
('MET' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1116 } ,
('MET' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1592 } ,
('MET' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2774 } ,
('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4097 } ,
('ASN' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0515 } ,
('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4097 } ,
('ASN' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0515 } ,
('ASN' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } ,
('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0368 } ,
('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0283 } ,
('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.5833 } ,
('ASN' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1231 } ,
('ASN' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1801 } ,
('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.8634 } ,
('ASN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5744 } ,
('PRO' , '2H' ) : { 'type' : 'H' , 'charge' : 0.3120 } ,
('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.1000 } ,
('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('PRO' , '3H' ) : { 'type' : 'H' , 'charge' : 0.3120 } ,
('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.1000 } ,
('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.1000 } ,
('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5260 } ,
('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.1000 } ,
('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1150 } ,
('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0120 } ,
('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.1210 } ,
('PRO' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1000 } ,
('PRO' , 'N' ) : { 'type' : 'N3' , 'charge' : -0.2020 } ,
('PRO' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5000 } ,
('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4429 } ,
('GLN' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } ,
('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0050 } ,
('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4429 } ,
('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0331 } ,
('GLN' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } ,
('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0050 } ,
('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0331 } ,
('GLN' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } ,
('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0536 } ,
('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0651 } ,
('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.7354 } ,
('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0903 } ,
('GLN' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1015 } ,
('GLN' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1493 } ,
('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -1.0031 } ,
('GLN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6133 } ,
('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4494 } ,
('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4494 } ,
('ARG' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } ,
('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0226 } ,
('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0527 } ,
('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0309 } ,
('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4494 } ,
('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4494 } ,
('ARG' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } ,
('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0226 } ,
('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0527 } ,
('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0309 } ,
('ARG' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } ,
('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } ,
('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0223 } ,
('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0118 } ,
('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0935 } ,
('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0236 } ,
('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8281 } ,
('ARG' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1242 } ,
('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3592 } ,
('ARG' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1305 } ,
('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5650 } ,
('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8693 } ,
('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8693 } ,
('ARG' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } ,
('SER' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } ,
('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0273 } ,
('SER' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } ,
('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0273 } ,
('SER' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } ,
('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0567 } ,
('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2596 } ,
('SER' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0782 } ,
('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4239 } ,
('SER' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1849 } ,
('SER' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6714 } ,
('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4070 } ,
('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } ,
('THR' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } ,
('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } ,
('THR' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } ,
('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } ,
('THR' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } ,
('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0034 } ,
('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.4514 } ,
('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.2554 } ,
('THR' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1087 } ,
('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : -0.0323 } ,
('THR' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1812 } ,
('THR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6764 } ,
('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } ,
('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } ,
('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } ,
('VAL' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } ,
('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } ,
('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0054 } ,
('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3196 } ,
('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3129 } ,
('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3129 } ,
('VAL' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1093 } ,
('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : -0.0221 } ,
('VAL' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0577 } ,
('VAL' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } ,
('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2195 } ,
('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3412 } ,
('TRP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } ,
('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0222 } ,
('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1411 } ,
('TRP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } ,
('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1589 } ,
('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0222 } ,
('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1646 } ,
('TRP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } ,
('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1458 } ,
('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0421 } ,
('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0543 } ,
('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1788 } ,
('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1132 } ,
('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1575 } ,
('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.2265 } ,
('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.1654 } ,
('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1080 } ,
('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2710 } ,
('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.2034 } ,
('TRP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1162 } ,
('TRP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1913 } ,
('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3444 } ,
('TRP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1720 } ,
('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1650 } ,
('TYR' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } ,
('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0102 } ,
('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1720 } ,
('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1650 } ,
('TYR' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } ,
('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0102 } ,
('TYR' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } ,
('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } ,
('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0570 } ,
('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0659 } ,
('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.2002 } ,
('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.2002 } ,
('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2239 } ,
('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2239 } ,
('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : -0.0205 } ,
('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3139 } ,
('TYR' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0983 } ,
('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.4001 } ,
('TYR' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1940 } ,
('TYR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } ,
('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5578 } ,
}
c_terminal = {
('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } ,
('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } ,
('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } ,
('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7731 } ,
('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1747 } ,
('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2093 } ,
('ALA' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('ALA' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1067 } ,
('ALA' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('ALA' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8055 } ,
('ALA' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8055 } ,
('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1437 } ,
('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1437 } ,
('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7497 } ,
('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1635 } ,
('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1996 } ,
('CYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('CYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1396 } ,
('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.2068 } ,
('CYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('CYS' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7981 } ,
('CYS' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7981 } ,
('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3102 } ,
('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1228 } ,
('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1228 } ,
('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7618 } ,
('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1318 } ,
('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1943 } ,
('CYX' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('CYX' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0938 } ,
('CYX' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('CYX' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8041 } ,
('CYX' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8041 } ,
('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.0529 } ,
('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } ,
('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } ,
('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7256 } ,
('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1817 } ,
('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0677 } ,
('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8851 } ,
('ASP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } ,
('ASP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1046 } ,
('ASP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } ,
('ASP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7887 } ,
('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8162 } ,
('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8162 } ,
('ASP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7887 } ,
('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } ,
('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } ,
('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7256 } ,
('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1817 } ,
('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0677 } ,
('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8851 } ,
('ASH' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } ,
('ASH' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1046 } ,
('ASH' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } ,
('ASH' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7887 } ,
('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.8162 } ,
('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.8162 } ,
('ASH' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7887 } ,
('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } ,
('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } ,
('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } ,
('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } ,
('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7420 } ,
('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2059 } ,
('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0071 } ,
('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8183 } ,
('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0675 } ,
('GLU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } ,
('GLU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1399 } ,
('GLU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } ,
('GLU' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7930 } ,
('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8220 } ,
('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8220 } ,
('GLU' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7930 } ,
('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } ,
('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } ,
('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } ,
('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } ,
('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7420 } ,
('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2059 } ,
('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0071 } ,
('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8183 } ,
('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0675 } ,
('GLP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } ,
('GLP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1399 } ,
('GLP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } ,
('GLP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7930 } ,
('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.8220 } ,
('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.8220 } ,
('GLP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7930 } ,
('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1408 } ,
('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1461 } ,
('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0443 } ,
('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1408 } ,
('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1461 } ,
('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0443 } ,
('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7660 } ,
('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1825 } ,
('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0959 } ,
('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1300 } ,
('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1300 } ,
('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1847 } ,
('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1847 } ,
('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0552 } ,
('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.0944 } ,
('PHE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('PHE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1098 } ,
('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1280 } ,
('PHE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('PHE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8026 } ,
('PHE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8026 } ,
('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.1056 } ,
('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7231 } ,
('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2493 } ,
('GLY' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('GLY' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1056 } ,
('GLY' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('GLY' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7855 } ,
('GLY' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7855 } ,
('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3883 } ,
('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2694 } ,
('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0868 } ,
('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2336 } ,
('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3913 } ,
('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0868 } ,
('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8032 } ,
('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1445 } ,
('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0800 } ,
('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1256 } ,
('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0251 } ,
('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.0298 } ,
('HIP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } ,
('HIP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1115 } ,
('HIP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } ,
('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1501 } ,
('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1683 } ,
('HIP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8177 } ,
('HIP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8177 } ,
('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1448 } ,
('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0620 } ,
('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1957 } ,
('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3319 } ,
('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0620 } ,
('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7916 } ,
('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2699 } ,
('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1068 } ,
('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2588 } ,
('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1558 } ,
('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.2724 } ,
('HIE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('HIE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1650 } ,
('HIE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5517 } ,
('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2670 } ,
('HIE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8065 } ,
('HIE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8065 } ,
('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3755 } ,
('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1418 } ,
('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0565 } ,
('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1241 } ,
('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0565 } ,
('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7615 } ,
('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1739 } ,
('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1046 } ,
('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1001 } ,
('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1925 } ,
('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.0293 } ,
('HID' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('HID' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1100 } ,
('HID' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3892 } ,
('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5629 } ,
('HID' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8016 } ,
('HID' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8016 } ,
('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } ,
('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } ,
('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } ,
('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0321 } ,
('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } ,
('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } ,
('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0321 } ,
('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } ,
('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8343 } ,
('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3100 } ,
('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0363 } ,
('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0699 } ,
('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0323 } ,
('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3498 } ,
('ILE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('ILE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1375 } ,
('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0766 } ,
('ILE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('ILE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8190 } ,
('ILE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8190 } ,
('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } ,
('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0482 } ,
('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0611 } ,
('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1121 } ,
('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0134 } ,
('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } ,
('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0482 } ,
('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0611 } ,
('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1121 } ,
('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0134 } ,
('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } ,
('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8488 } ,
('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2903 } ,
('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0538 } ,
('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0392 } ,
('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0176 } ,
('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0227 } ,
('LYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } ,
('LYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1438 } ,
('LYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } ,
('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3741 } ,
('LYS' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8252 } ,
('LYS' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8252 } ,
('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0974 } ,
('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0974 } ,
('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } ,
('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8326 } ,
('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2847 } ,
('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2469 } ,
('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4163 } ,
('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4163 } ,
('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3706 } ,
('LEU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('LEU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1346 } ,
('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0374 } ,
('LEU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('LEU' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8199 } ,
('LEU' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8199 } ,
('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } ,
('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0480 } ,
('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } ,
('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0317 } ,
('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0480 } ,
('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } ,
('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0317 } ,
('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8013 } ,
('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2597 } ,
('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0236 } ,
('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0376 } ,
('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0492 } ,
('MET' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('MET' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1277 } ,
('MET' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('MET' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8105 } ,
('MET' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8105 } ,
('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2692 } ,
('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4150 } ,
('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.1023 } ,
('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4150 } ,
('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.1023 } ,
('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8050 } ,
('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2080 } ,
('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2299 } ,
('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7153 } ,
('ASN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('ASN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1358 } ,
('ASN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.9084 } ,
('ASN' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8147 } ,
('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.6010 } ,
('ASN' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8147 } ,
('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0381 } ,
('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0331 } ,
('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0172 } ,
('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0381 } ,
('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0331 } ,
('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0172 } ,
('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6631 } ,
('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1336 } ,
('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0543 } ,
('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0434 } ,
('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0466 } ,
('PRO' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0776 } ,
('PRO' , 'N' ) : { 'type' : 'N' , 'charge' : -0.2802 } ,
('PRO' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7697 } ,
('PRO' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7697 } ,
('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4304 } ,
('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0452 } ,
('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4304 } ,
('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0203 } ,
('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0452 } ,
('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0203 } ,
('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7775 } ,
('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2248 } ,
('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0664 } ,
('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.7093 } ,
('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0210 } ,
('GLN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('GLN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1232 } ,
('GLN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -0.9574 } ,
('GLN' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8042 } ,
('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6098 } ,
('GLN' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8042 } ,
('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4493 } ,
('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4493 } ,
('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0371 } ,
('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0468 } ,
('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0185 } ,
('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4493 } ,
('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4493 } ,
('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0371 } ,
('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0468 } ,
('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0185 } ,
('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8557 } ,
('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3068 } ,
('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0374 } ,
('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.1114 } ,
('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0744 } ,
('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8368 } ,
('ARG' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } ,
('ARG' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1447 } ,
('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3479 } ,
('ARG' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } ,
('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5564 } ,
('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8737 } ,
('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8737 } ,
('ARG' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8266 } ,
('ARG' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8266 } ,
('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0813 } ,
('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0813 } ,
('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8113 } ,
('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2722 } ,
('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1123 } ,
('SER' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('SER' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1304 } ,
('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4474 } ,
('SER' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('SER' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8132 } ,
('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6514 } ,
('SER' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8132 } ,
('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4119 } ,
('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } ,
('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } ,
('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } ,
('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7810 } ,
('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2420 } ,
('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3025 } ,
('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.1853 } ,
('THR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('THR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1207 } ,
('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : 0.0078 } ,
('THR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('THR' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8044 } ,
('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6496 } ,
('THR' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8044 } ,
('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } ,
('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8350 } ,
('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3438 } ,
('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1940 } ,
('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3064 } ,
('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3064 } ,
('VAL' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('VAL' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1438 } ,
('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0308 } ,
('VAL' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('VAL' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8173 } ,
('VAL' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8173 } ,
('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2043 } ,
('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3413 } ,
('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0497 } ,
('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1401 } ,
('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1567 } ,
('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0497 } ,
('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1491 } ,
('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1507 } ,
('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7658 } ,
('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2084 } ,
('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0742 } ,
('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1808 } ,
('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1078 } ,
('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1222 } ,
('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.1837 } ,
('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.0796 } ,
('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1020 } ,
('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2594 } ,
('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.2287 } ,
('TRP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('TRP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1272 } ,
('TRP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3316 } ,
('TRP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8011 } ,
('TRP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8011 } ,
('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1780 } ,
('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1673 } ,
('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0490 } ,
('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1780 } ,
('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1673 } ,
('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0490 } ,
('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7817 } ,
('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2015 } ,
('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0752 } ,
('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1922 } ,
('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1922 } ,
('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2458 } ,
('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2458 } ,
('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0243 } ,
('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3395 } ,
('TYR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } ,
('TYR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1092 } ,
('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.4017 } ,
('TYR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } ,
('TYR' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8070 } ,
('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5643 } ,
('TYR' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8070 } ,
}
| 63.541284
| 71
| 0.344836
| 9,070
| 83,112
| 3.159647
| 0.098677
| 0.314118
| 0.097983
| 0.106148
| 0.904076
| 0.843674
| 0.011934
| 0.004466
| 0.002722
| 0.002722
| 0
| 0.130737
| 0.319701
| 83,112
| 1,307
| 72
| 63.589901
| 0.376116
| 0.008061
| 0
| 0.001547
| 0
| 0
| 0.266193
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| 0
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| 0
| 0
|
0
| 4
|
168a1d56839afd5c1afd3495075a6a02dc26a4ea
| 87
|
py
|
Python
|
05 - Result/02 - Rust/run.py
|
BjoernLange/why-you-should-learn-rust-examples
|
985d184fc79b77b10628cba81333e9e662f4107b
|
[
"MIT"
] | null | null | null |
05 - Result/02 - Rust/run.py
|
BjoernLange/why-you-should-learn-rust-examples
|
985d184fc79b77b10628cba81333e9e662f4107b
|
[
"MIT"
] | null | null | null |
05 - Result/02 - Rust/run.py
|
BjoernLange/why-you-should-learn-rust-examples
|
985d184fc79b77b10628cba81333e9e662f4107b
|
[
"MIT"
] | null | null | null |
#!/bin/python3
import os
if __name__ == '__main__':
exit(os.system('cargo run'))
| 12.428571
| 32
| 0.643678
| 12
| 87
| 4
| 0.916667
| 0
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| 0
| 0.013889
| 0.172414
| 87
| 6
| 33
| 14.5
| 0.652778
| 0.149425
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| 0.232877
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| true
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| null | 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
168b5be28e80ad5d47f6d5548a4db14f533f86a3
| 45
|
py
|
Python
|
yaretry/__init__.py
|
Aloomaio/yaretry
|
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
|
[
"Apache-2.0"
] | null | null | null |
yaretry/__init__.py
|
Aloomaio/yaretry
|
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
|
[
"Apache-2.0"
] | null | null | null |
yaretry/__init__.py
|
Aloomaio/yaretry
|
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
|
[
"Apache-2.0"
] | 1
|
2020-08-08T21:01:41.000Z
|
2020-08-08T21:01:41.000Z
|
from yaretry.retry import *
name = "yaretry"
| 15
| 27
| 0.733333
| 6
| 45
| 5.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155556
| 45
| 2
| 28
| 22.5
| 0.868421
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| 0.155556
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| 1
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| false
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| 0
| 0
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| 0
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| 1
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
16d07ce6f6163d36be24050a2d53fcf3fde06a46
| 20
|
py
|
Python
|
tests/__init__.py
|
trickeydan/j5-dev
|
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
|
[
"MIT"
] | 10
|
2019-01-19T13:09:37.000Z
|
2021-06-18T13:40:10.000Z
|
tests/__init__.py
|
trickeydan/j5-dev
|
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
|
[
"MIT"
] | 681
|
2019-01-22T18:12:23.000Z
|
2022-03-25T14:14:31.000Z
|
tests/__init__.py
|
trickeydan/j5-dev
|
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
|
[
"MIT"
] | 8
|
2019-02-22T21:45:47.000Z
|
2021-11-17T19:43:33.000Z
|
"""Tests for j5."""
| 10
| 19
| 0.5
| 3
| 20
| 3.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0.15
| 20
| 1
| 20
| 20
| 0.529412
| 0.65
| 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
|
16d509624c6e9d70153fa1634acb2e9127ea8d95
| 29
|
py
|
Python
|
tests/__init__.py
|
abdelq/pybaselines
|
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
|
[
"BSD-3-Clause-Clear",
"BSD-3-Clause"
] | null | null | null |
tests/__init__.py
|
abdelq/pybaselines
|
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
|
[
"BSD-3-Clause-Clear",
"BSD-3-Clause"
] | null | null | null |
tests/__init__.py
|
abdelq/pybaselines
|
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
|
[
"BSD-3-Clause-Clear",
"BSD-3-Clause"
] | null | null | null |
"""Tests for pybaselines."""
| 14.5
| 28
| 0.655172
| 3
| 29
| 6.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103448
| 29
| 1
| 29
| 29
| 0.730769
| 0.758621
| 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
|
16ef6a9b8219de1b9bafef9547ff336bf002f425
| 23
|
py
|
Python
|
agora_identity/__init__.py
|
agoravoting/agora-identity
|
a656815207929f3871a6daa67ea7fecc2ec13c83
|
[
"BSD-3-Clause"
] | null | null | null |
agora_identity/__init__.py
|
agoravoting/agora-identity
|
a656815207929f3871a6daa67ea7fecc2ec13c83
|
[
"BSD-3-Clause"
] | null | null | null |
agora_identity/__init__.py
|
agoravoting/agora-identity
|
a656815207929f3871a6daa67ea7fecc2ec13c83
|
[
"BSD-3-Clause"
] | null | null | null |
""" agora_identity """
| 11.5
| 22
| 0.608696
| 2
| 23
| 6.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130435
| 23
| 1
| 23
| 23
| 0.65
| 0.608696
| 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
|
bc57d58e4ff58c7c5a7103af772a3eaf453d2e1e
| 1,735
|
py
|
Python
|
revscoring/revscoring/languages/__init__.py
|
yafeunteun/wikipedia-spam-classifier
|
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
|
[
"MIT"
] | 2
|
2016-10-26T18:58:53.000Z
|
2017-06-22T20:11:20.000Z
|
revscoring/revscoring/languages/__init__.py
|
yafeunteun/wikipedia-spam-classifier
|
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
|
[
"MIT"
] | null | null | null |
revscoring/revscoring/languages/__init__.py
|
yafeunteun/wikipedia-spam-classifier
|
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
|
[
"MIT"
] | null | null | null |
"""
This module implements a set of languages as collections of features that are
language specific.
feature collections
+++++++++++++++++++
Languages implement a subset of feature collections (e.g.
:class:`~revscoring.languages.features.Dictionary`,
:class:`~revscoring.languages.features.Stopwords`,
:class:`~revscoring.languages.features.Stemmed` and
:class:`~revscoring.languages.features.RegexMatches`) based on what
language assets are available. See :mod:`revscoring.languages.features`.
dutch
+++++
.. automodule:: revscoring.languages.arabic
:members:
dutch
+++++
.. automodule:: revscoring.languages.dutch
:members:
english
+++++++
.. automodule:: revscoring.languages.english
:members:
estonian
++++++++
.. automodule:: revscoring.languages.estonian
:members:
french
++++++
.. automodule:: revscoring.languages.french
:members:
german
++++++
.. automodule:: revscoring.languages.german
:members:
hebrew
++++++
.. automodule:: revscoring.languages.hebrew
:members:
indonesian
++++++++++
.. automodule:: revscoring.languages.indonesian
:members:
italian
+++++++
.. automodule:: revscoring.languages.italian
:members:
japanese
+++++++
.. automodule:: revscoring.languages.japanese
:members:
persian
+++++++
.. automodule:: revscoring.languages.persian
:members:
portuguese
++++++++++
.. automodule:: revscoring.languages.portuguese
:members:
spanish
+++++++
.. automodule:: revscoring.languages.spanish
:members:
turkish
+++++++
.. automodule:: revscoring.languages.turkish
:members:
ukrainian
+++++++++
.. automodule:: revscoring.languages.ukrainian
:members:
vietnamese
++++++++++
.. automodule:: revscoring.languages.vietnamese
:members:
"""
| 18.263158
| 77
| 0.69049
| 155
| 1,735
| 7.729032
| 0.329032
| 0.333055
| 0.387312
| 0.106845
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.126801
| 1,735
| 94
| 78
| 18.457447
| 0.790759
| 0.994236
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
bc682bb20c97a5e3723d2d7082d0107fb8dd5d1f
| 121
|
py
|
Python
|
config/development.py
|
joeseggie/fingerprint_api_proxy
|
e5d81e4de4411e60c925589c5d6a992669f531b4
|
[
"MIT"
] | null | null | null |
config/development.py
|
joeseggie/fingerprint_api_proxy
|
e5d81e4de4411e60c925589c5d6a992669f531b4
|
[
"MIT"
] | 2
|
2021-03-31T18:49:55.000Z
|
2021-12-13T19:48:31.000Z
|
config/development.py
|
joeseggie/fingerprint_api_proxy
|
e5d81e4de4411e60c925589c5d6a992669f531b4
|
[
"MIT"
] | null | null | null |
from config.default import Config
class DevelopmentConfig(Config):
"""Development configuration"""
DEBUG = True
| 20.166667
| 35
| 0.743802
| 12
| 121
| 7.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.165289
| 121
| 5
| 36
| 24.2
| 0.891089
| 0.206612
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
bc703f8b37eb7e122998ca4581d077a1a8eac399
| 1,267
|
py
|
Python
|
claripy/ast/__init__.py
|
mborgerson/claripy
|
45b01c10caa0001b4e210e449ad5618880d1773b
|
[
"BSD-2-Clause"
] | null | null | null |
claripy/ast/__init__.py
|
mborgerson/claripy
|
45b01c10caa0001b4e210e449ad5618880d1773b
|
[
"BSD-2-Clause"
] | null | null | null |
claripy/ast/__init__.py
|
mborgerson/claripy
|
45b01c10caa0001b4e210e449ad5618880d1773b
|
[
"BSD-2-Clause"
] | null | null | null |
#pylint:disable=redefined-outer-name
from typing import TYPE_CHECKING
# Mypy is severely confused by this delayed import trickery, but works if we just pretend that the import
# happens here already
if TYPE_CHECKING:
from .bits import Bits
from .bv import BV
from .vs import VS
from .fp import FP
from .bool import Bool, true, false
from .int import Int
from .base import Base
from .strings import String
from .. import ops as all_operations
else:
Bits = lambda *args, **kwargs: None
BV = lambda *args, **kwargs: None
VS = lambda *args, **kwargs: None
FP = lambda *args, **kwargs: None
Bool = lambda *args, **kwargs: None
Int = lambda *args, **kwargs: None
Base = lambda *args, **kwargs: None
true = lambda *args, **kwargs: None
false = lambda *args, **kwargs: None
String = lambda *args, **kwargs: None
all_operations = None
def _import():
global Bits, BV, VS, FP, Bool, Int, Base, String, true, false, all_operations
from .bits import Bits
from .bv import BV
from .vs import VS
from .fp import FP
from .bool import Bool, true, false
from .int import Int
from .base import Base
from .strings import String
from .. import ops as all_operations
| 30.902439
| 105
| 0.669298
| 183
| 1,267
| 4.595628
| 0.278689
| 0.118906
| 0.19025
| 0.237812
| 0.409037
| 0.409037
| 0.409037
| 0.409037
| 0.409037
| 0.409037
| 0
| 0
| 0.245462
| 1,267
| 40
| 106
| 31.675
| 0.879707
| 0.126283
| 0
| 0.529412
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.029412
| false
| 0
| 0.588235
| 0
| 0.617647
| 0
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| 0
| null | 0
| 1
| 1
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| null | 0
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| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
bc7fac8fb65ff74f7a3a104b347a3069058466b4
| 110
|
py
|
Python
|
echopype/analysis/db_diff.py
|
leewujung/echopype-lfs-test
|
b76dcf42631d0ac9cef0efeced9be4afdc15e659
|
[
"Apache-2.0"
] | 1
|
2021-09-04T07:19:35.000Z
|
2021-09-04T07:19:35.000Z
|
echopype/analysis/db_diff.py
|
lsxinh2/echopype
|
5ed0ea5ec3c872eb2512b045f8585d9225c12bce
|
[
"Apache-2.0"
] | null | null | null |
echopype/analysis/db_diff.py
|
lsxinh2/echopype
|
5ed0ea5ec3c872eb2512b045f8585d9225c12bce
|
[
"Apache-2.0"
] | null | null | null |
"""
Place holder for frequency-differencing functions.
The previous incarnation is in /ref_code/db_diff.py
"""
| 27.5
| 51
| 0.790909
| 16
| 110
| 5.3125
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109091
| 110
| 4
| 52
| 27.5
| 0.867347
| 0.927273
| 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
|
bc84159202c873cc832af26dc05026001f89d59a
| 317
|
py
|
Python
|
django-server/fras/attendance/views/CapturedFrameAPI.py
|
ArleneAndrews/Facial-Recognition-Attendance-System
|
104d17e56af87358974331ef491949b557ab2f01
|
[
"MIT"
] | 52
|
2019-01-29T14:46:17.000Z
|
2022-01-14T16:11:37.000Z
|
django-server/fras/attendance/views/CapturedFrameAPI.py
|
etrigaen47/Facial-Recognition-Attendance-System
|
ad0bd18cf9582cc12002baf8c92f6638f632c46e
|
[
"MIT"
] | 13
|
2018-11-04T12:29:48.000Z
|
2020-02-11T23:47:35.000Z
|
django-server/fras/attendance/views/CapturedFrameAPI.py
|
etrigaen47/Facial-Recognition-Attendance-System
|
ad0bd18cf9582cc12002baf8c92f6638f632c46e
|
[
"MIT"
] | 16
|
2019-03-07T11:07:16.000Z
|
2021-08-13T07:19:28.000Z
|
from rest_framework import viewsets
from attendance.models.CapturedFrame import CapturedFrame
from attendance.serializers.CapturedFrameSerializer import CapturedFrameSerializer
class CapturedFrameAPI(viewsets.ModelViewSet):
queryset = CapturedFrame.objects.all()
serializer_class = CapturedFrameSerializer
| 31.7
| 82
| 0.858044
| 28
| 317
| 9.642857
| 0.607143
| 0.103704
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097792
| 317
| 9
| 83
| 35.222222
| 0.944056
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
bc9005361bcee4811d3abf3f0158f4b1f5d55f2b
| 257
|
py
|
Python
|
django_presentation/messages/messageBox.py
|
adamkerz/django-presentation
|
1e812faa5f682e021fa6580509d8d324cfcc119c
|
[
"BSD-3-Clause"
] | null | null | null |
django_presentation/messages/messageBox.py
|
adamkerz/django-presentation
|
1e812faa5f682e021fa6580509d8d324cfcc119c
|
[
"BSD-3-Clause"
] | null | null | null |
django_presentation/messages/messageBox.py
|
adamkerz/django-presentation
|
1e812faa5f682e021fa6580509d8d324cfcc119c
|
[
"BSD-3-Clause"
] | null | null | null |
from django.template import Context
from django.template.loader import get_template
from django.utils.safestring import mark_safe as S
def messageBox(messages):
return S(get_template('messages/messageBox.html').render(Context({'messages':messages})))
| 32.125
| 93
| 0.805447
| 35
| 257
| 5.828571
| 0.542857
| 0.147059
| 0.176471
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093385
| 257
| 7
| 94
| 36.714286
| 0.875536
| 0
| 0
| 0
| 0
| 0
| 0.124514
| 0.093385
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.6
| 0.2
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
bc9413fb9a7ab513b3219a6b4baa388b63c06e8a
| 4,036
|
py
|
Python
|
data.py
|
andy31lewis/brywidgets
|
2ff3ffe633cbf226208d7af95cc0eb542173be2b
|
[
"BSD-3-Clause"
] | 1
|
2020-10-21T12:26:18.000Z
|
2020-10-21T12:26:18.000Z
|
data.py
|
andy31lewis/brywidgets
|
2ff3ffe633cbf226208d7af95cc0eb542173be2b
|
[
"BSD-3-Clause"
] | 2
|
2020-04-22T12:04:52.000Z
|
2021-01-24T15:18:51.000Z
|
data.py
|
andy31lewis/brywidgets
|
2ff3ffe633cbf226208d7af95cc0eb542173be2b
|
[
"BSD-3-Clause"
] | 1
|
2018-12-10T00:56:39.000Z
|
2018-12-10T00:56:39.000Z
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
artistdict = {"Bohemian Rhapsody":"Queen", "Imagine":"John Lennon", "Angels":"Robbie Williams", "Hey Jude":"Beatles", "Smells Like Teen Spirit":"Nirvana", "Live Forever":"Oasis", "Wonderwall":"Oasis", "One":"U2", "Bitter Sweet Symphony":"Verve", "With Or Without You":"U2", "Penny Lane / Strawberry Fields Forever":"Beatles", "Good Vibrations":"Beach Boys", "Losing My Religion":"REM", "Like A Rolling Stone":"Bob Dylan", "God Only Knows":"Beach Boys", "Everybody Hurts":"REM", "Waterloo Sunset":"Kinks", "Don’t Look Back In Anger":"Oasis", "A Whiter Shade Of Pale":"Procol Harum", "Stairway To Heaven":"Led Zeppelin", "Yesterday":"Beatles", "A Day In The Life":"Beatles", "Hotel California":"Eagles", "Unfinished Sympathy":"Massive Attack", "Dancing Queen":"Abba", "Like A Prayer":"Madonna", "All Along The Watchtower":"Jimi Hendrix Experience", "Creep":"Radiohead", "Billie Jean":"Michael Jackson", "My Generation":"Who", "Wuthering Heights":"Kate Bush", "Paranoid Android":"Radiohead", "Teenage Kicks":"Undertones", "Love Will Tear Us Apart":"Joy Division", "Bridge Over Troubled Water":"Simon And Garfunkel", "Born To Run":"Bruce Springsteen", "No Woman No Cry":"Bob Marley & The Wailers", "Sweet Child O Mine":"Guns N Roses", "Suspicious Minds":"Elvis Presley", "Let It Be":"Beatles", "(I Can’t Get No) Satisfaction":"Rolling Stones", "Bat Out Of Hell":"Meat Loaf", "Common People":"Pulp", "Hero":"Mariah Carey", "I Heard It Through The Grapevine":"Marvin Gaye", "Layla":"Derek And The Dominoes", "American Pie":"Don Mclean", "Mr Brightside":"Killers", "It Must be Love":"Madness", "Paint It Black":"Rolling Stones", "Anarchy In The UK":"Sex Pistols", "Time Of Your Life (Good Riddance)":"Green Day", "Champagne Supernova":"Oasis", "A Town Called Malice / Precious":"Jam", "Wannabe":"Spice Girls", "Street Spirit (Fade Out)":"Radiohead", "All Right Now":"Free", "Fools Gold / What The World Is Waiting For":"Stone Roses", "Yellow":"Coldplay", "Mr. Blue Sky":"Electric Light Orchestra", "Nothing Compares 2 U":"Sinead O’Connor", "This Charming Man":"Smiths", "Careless Whisper":"George Michael", "London Calling":"Clash", "Song 2":"Blur", "That's Entertainment":"Jam", "Under The Bridge":"Red Hot Chili Peppers", "Karma Police":"Radiohead", "God Save The Queen":"Sex Pistols", "(Sittin' On) The Dock Of The Bay":"Ottis Redding", "Wish You Were Here":"Pink Floyd", "In My Life":"Beatles", "Every Breath You Take":"Police", "House Of The Rising Sun":"Animals", "I Am The Resurrection":"Stone Roses", "(Everything I Do) I Do It For You":"Bryan Adams", "Fake Plastic Trees":"Radiohead", "Comfortably Numb":"Pink Floyd", "Brown Eyed Girl":"Van Morrison", "Baker Street":"Gerry Rafferty", "She Loves You":"Beatles", "Romeo And Juliet":"Dire Straits", "Jumping Jack Flash":"Rolling Stones", "My Heart Will Go On":"Celine Dion", "I’ll Be Missing You":"Puff Daddy And Faith Evans", "How Soon Is Now?":"Smiths", "Help!":"Beatles", "Where The Streets Have No Name":"U2", "Space Oddity":"David Bowie", "Heroes":"David Bowie", "Life On Mars":"David Bowie", "There She Goes":"LAs", "Unchained Melody":"Righteous Brothers", "Going Underground / Dreams Of Children":"Jam", "Tracks Of My Tears":"Smokey Robinson & The Miracles", "Come On Eileen":"Dexy's Midnight Runners", "Nights In White Satin":"Moody Blues", "Blue Monday":"New Order", "My Sweet Lord":"George Harrison", "Stan":"Eminem", "Motorcycle Emptiness":"Manic Street Preachers", "The Winner Takes It All":"Abba", "Can't Get You Out Of My Head":"Kylie Minogue", "Fairytale of New York":"Pogues featuring Kirsty MacColl", "Take Your Mama":"Scissor Sisters", "Heartbreak Hotel":"Elvis Presley", "Don't Dream It's Over":"Crowded House", "I’m Not In Love":"10CC", "The Drugs Don’t Work":"Verve", "Lola":"Kinks", "Don’t You Want Me":"Human League", "Without You":"Nilsson", "Believe":"Cher", "Wichita Lineman":"Glen Campbell", "Babylon":"David Gray", "Summer Of ’69":"Bryan Adams", "Wild Wood":"Paul Weller", "Voodoo Chile":"Jimi Hendrix Experience"}
| 807.2
| 3,992
| 0.698216
| 583
| 4,036
| 4.833619
| 0.692967
| 0.005678
| 0.006388
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002797
| 0.114222
| 4,036
| 4
| 3,993
| 1,009
| 0.785455
| 0.009415
| 0
| 0
| 0
| 0
| 0.789039
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
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| 0
| 0
| null | 0
| 0
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| 0
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| 0
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| 0
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| 0
| 1
| 1
| 1
| 0
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| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
bcd7b60ca8525e85e1afe8ced67ee42f93dd9dc7
| 180
|
py
|
Python
|
mwclient/util.py
|
AdamWill/mwclient
|
6c8ead656647b811646f60366275f90ecc42a42f
|
[
"MIT"
] | null | null | null |
mwclient/util.py
|
AdamWill/mwclient
|
6c8ead656647b811646f60366275f90ecc42a42f
|
[
"MIT"
] | null | null | null |
mwclient/util.py
|
AdamWill/mwclient
|
6c8ead656647b811646f60366275f90ecc42a42f
|
[
"MIT"
] | null | null | null |
import time
def parse_timestamp(t):
if t is None or t == '0000-00-00T00:00:00Z':
return (0, 0, 0, 0, 0, 0, 0, 0, 0)
return time.strptime(t, '%Y-%m-%dT%H:%M:%SZ')
| 22.5
| 49
| 0.55
| 37
| 180
| 2.648649
| 0.594595
| 0.163265
| 0.214286
| 0.244898
| 0.091837
| 0.091837
| 0.091837
| 0.091837
| 0
| 0
| 0
| 0.167883
| 0.238889
| 180
| 7
| 50
| 25.714286
| 0.547445
| 0
| 0
| 0
| 0
| 0
| 0.211111
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0
| 0.8
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
4c23d938bd5650c382fcc55770015d0052800bca
| 395
|
py
|
Python
|
doc/examples/runtime.py
|
aaronsewall/pytest-dependency
|
db34c5451891629ad54a18e8a5e6a45b7ec968f8
|
[
"Apache-2.0"
] | 91
|
2017-01-30T16:05:13.000Z
|
2022-03-29T12:17:35.000Z
|
doc/examples/runtime.py
|
aaronsewall/pytest-dependency
|
db34c5451891629ad54a18e8a5e6a45b7ec968f8
|
[
"Apache-2.0"
] | 63
|
2016-04-21T19:30:32.000Z
|
2022-03-30T13:17:42.000Z
|
doc/examples/runtime.py
|
aaronsewall/pytest-dependency
|
db34c5451891629ad54a18e8a5e6a45b7ec968f8
|
[
"Apache-2.0"
] | 29
|
2017-09-24T17:22:02.000Z
|
2022-03-30T20:39:49.000Z
|
import pytest
from pytest_dependency import depends
@pytest.mark.dependency()
def test_a():
pass
@pytest.mark.dependency()
@pytest.mark.xfail(reason="deliberate fail")
def test_b():
assert False
@pytest.mark.dependency()
def test_c(request):
depends(request, ["test_b"])
pass
@pytest.mark.dependency()
def test_d(request):
depends(request, ["test_a", "test_c"])
pass
| 17.954545
| 44
| 0.708861
| 54
| 395
| 5.037037
| 0.37037
| 0.183824
| 0.294118
| 0.253676
| 0.297794
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146835
| 395
| 21
| 45
| 18.809524
| 0.807122
| 0
| 0
| 0.411765
| 0
| 0
| 0.083544
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 1
| 0.235294
| false
| 0.176471
| 0.117647
| 0
| 0.352941
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
4c4686231662d9771e44fd5ba8bd8ed37776ab5d
| 82
|
py
|
Python
|
examples/ploty/ploty-01.py
|
MWTA/Natural-Language-Processing-Python
|
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
|
[
"MIT"
] | null | null | null |
examples/ploty/ploty-01.py
|
MWTA/Natural-Language-Processing-Python
|
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
|
[
"MIT"
] | null | null | null |
examples/ploty/ploty-01.py
|
MWTA/Natural-Language-Processing-Python
|
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
|
[
"MIT"
] | null | null | null |
https: // moderndata.plot.ly/generate-html-reports-with-python-pandas-and-plotly/
| 41
| 81
| 0.792683
| 12
| 82
| 5.416667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036585
| 82
| 1
| 82
| 82
| 0.822785
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4c6382dce1f0c6b8efee87fe1b4984782bdc916a
| 84
|
py
|
Python
|
detectors/__init__.py
|
heymarco/ChangeDetectors
|
03e343a4dd9260328d6d81e01edd7888091b3517
|
[
"MIT"
] | null | null | null |
detectors/__init__.py
|
heymarco/ChangeDetectors
|
03e343a4dd9260328d6d81e01edd7888091b3517
|
[
"MIT"
] | null | null | null |
detectors/__init__.py
|
heymarco/ChangeDetectors
|
03e343a4dd9260328d6d81e01edd7888091b3517
|
[
"MIT"
] | null | null | null |
from .baselines import *
from .abstract import DriftDetector, RegionalDriftDetector
| 42
| 58
| 0.845238
| 8
| 84
| 8.875
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py
|
Python
|
pyqode/python/_forms/pyqode_python_icons_rc.py
|
haesleinhuepf/pyqode.python
|
de694278f64cb635c8863d03f3260984fc136b7a
|
[
"MIT"
] | null | null | null |
pyqode/python/_forms/pyqode_python_icons_rc.py
|
haesleinhuepf/pyqode.python
|
de694278f64cb635c8863d03f3260984fc136b7a
|
[
"MIT"
] | null | null | null |
pyqode/python/_forms/pyqode_python_icons_rc.py
|
haesleinhuepf/pyqode.python
|
de694278f64cb635c8863d03f3260984fc136b7a
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.5.1)
#
# WARNING! All changes made in this file will be lost!
from qtpy import QtCore
qt_resource_data = b"\
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def qCleanupResources():
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qInitResources()
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0
| 4
|
d5ce206f689f53884df688924e125671fa7ba50d
| 118
|
py
|
Python
|
crossreceptor_analysis/apps.py
|
GPCRmd/GPCRmd
|
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
|
[
"Apache-2.0"
] | 3
|
2019-03-06T13:35:38.000Z
|
2020-08-05T15:31:29.000Z
|
crossreceptor_analysis/apps.py
|
GPCRmd/GPCRmd
|
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
|
[
"Apache-2.0"
] | null | null | null |
crossreceptor_analysis/apps.py
|
GPCRmd/GPCRmd
|
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class CrossreceptorAnalysisConfig(AppConfig):
name = 'crossreceptor_analysis'
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0
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d5fce18f0b70cb7f0151a5134a3c65c431645438
| 9,915
|
py
|
Python
|
tests/admin/test_space.py
|
Harris-Bot/nebula-graph
|
39411a3b1ec38ce55c670e856138a72f5f8e1721
|
[
"Apache-2.0"
] | null | null | null |
tests/admin/test_space.py
|
Harris-Bot/nebula-graph
|
39411a3b1ec38ce55c670e856138a72f5f8e1721
|
[
"Apache-2.0"
] | 2
|
2021-05-07T09:20:24.000Z
|
2021-06-22T06:48:55.000Z
|
tests/admin/test_space.py
|
Harris-Bot/nebula-graph
|
39411a3b1ec38ce55c670e856138a72f5f8e1721
|
[
"Apache-2.0"
] | 1
|
2021-06-22T06:20:03.000Z
|
2021-06-22T06:20:03.000Z
|
# --coding:utf-8--
#
# Copyright (c) 2020 vesoft inc. All rights reserved.
#
# This source code is licensed under Apache 2.0 License,
# attached with Common Clause Condition 1.0, found in the LICENSES directory.
import time
from tests.common.nebula_test_suite import NebulaTestSuite, T_EMPTY
class TestSpace(NebulaTestSuite):
def test_space(self):
# not exist
resp = self.client.execute('USE not_exist_space')
self.check_resp_failed(resp)
# with default options
resp = self.client.execute('CREATE SPACE space_with_default_options (vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
resp = self.client.execute('CREATE SPACE space_on_default_group on default')
self.check_resp_failed(resp)
# check result
resp = self.client.execute('DESC SPACE space_with_default_options')
expect_result = [['space_with_default_options', 100, 1, 'utf8', 'utf8_bin',
'FIXED_STRING(8)', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# drop space
resp = self.client.execute('DROP SPACE space_with_default_options')
self.check_resp_succeeded(resp)
# create space succeeded
resp = self.client.execute('CREATE SPACE default_space(partition_num=9, replica_factor=1, vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
# show spaces
resp = self.client.execute('SHOW SPACES')
self.check_resp_succeeded(resp)
self.search_result(resp, [['default_space']])
# desc space
resp = self.client.execute('DESC SPACE default_space')
self.check_resp_succeeded(resp)
expect_result = [['default_space', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)',
False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# show create space
# TODO(shylock) need meta cache to permission checking
time.sleep(self.delay)
resp = self.client.execute('SHOW CREATE SPACE default_space')
self.check_resp_succeeded(resp)
create_space_str_result = 'CREATE SPACE `default_space` (partition_num = 9, '\
'replica_factor = 1, '\
'charset = utf8, '\
'collate = utf8_bin, '\
'vid_type = FIXED_STRING(8), '\
'atomic_edge = false) '\
'ON default'
expect_result = [['default_space', create_space_str_result]]
self.check_result(resp, expect_result)
# check result from show create
resp = self.client.execute('DROP SPACE default_space')
self.check_resp_succeeded(resp)
create_space_str = 'CREATE SPACE `default_space` (partition_num = 9, '\
'replica_factor = 1, '\
'charset = utf8, '\
'collate = utf8_bin, '\
'vid_type = FIXED_STRING(8), '\
'atomic_edge = false)'
resp = self.client.execute(create_space_str)
self.check_resp_succeeded(resp)
resp = self.client.execute('SHOW SPACES')
self.check_resp_succeeded(resp)
# 2.0 when use space, the validator get from cache
time.sleep(self.delay)
resp = self.client.execute("USE default_space")
self.check_resp_succeeded(resp)
def test_charset_collate(self):
resp = self.client.execute('CREATE SPACE space_charset_collate (partition_num=9, '
'replica_factor=1, charset=utf8, collate=utf8_bin, vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_charset_collate')
self.check_resp_succeeded(resp)
expect_result = [['space_charset_collate', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# drop space
resp = self.client.execute('DROP SPACE space_charset_collate')
self.check_resp_succeeded(resp)
resp = self.client.execute('CREATE SPACE space_charset (partition_num=9, '
'replica_factor=1, charset=utf8, vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_charset')
self.check_resp_succeeded(resp)
expect_result = [['space_charset', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# drop space
resp = self.client.execute('DROP SPACE space_charset')
self.check_resp_succeeded(resp)
resp = self.client.execute('CREATE SPACE space_collate (partition_num=9, '
'replica_factor=1, collate=utf8_bin, vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_collate')
self.check_resp_succeeded(resp)
expect_result = [['space_collate', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# drop space
resp = self.client.execute('DROP SPACE space_collate')
self.check_resp_succeeded(resp)
# not supported collate
resp = self.client.execute('CREATE SPACE space_charset_collate_nomatch (partition_num=9, '
'replica_factor=1, charset = utf8, collate=gbk_bin, vid_type=FIXED_STRING(8))')
self.check_resp_failed(resp)
# not supported charset
resp = self.client.execute('CREATE SPACE space_charset_collate_nomatch (partition_num=9, '
'replica_factor=1, charset = gbk, collate=utf8_bin, vid_type=FIXED_STRING(8))')
self.check_resp_failed(resp)
# not supported charset
resp = self.client.execute('CREATE SPACE space_illegal_charset (partition_num=9, '
'replica_factor=1, charset = gbk, vid_type=FIXED_STRING(8))')
self.check_resp_failed(resp)
# not supported collate
resp = self.client.execute('CREATE SPACE space_illegal_collate (partition_num=9, '
'replica_factor=1, collate = gbk_bin, vid_type=FIXED_STRING(8))')
self.check_resp_failed(resp)
resp = self.client.execute('CREATE SPACE space_illegal_collate (partition_num=9, '
'replica_factor=1, collate = gbk_bin, vid_type=FIXED_STRING(8))')
self.check_resp_failed(resp)
resp = self.client.execute('CREATE SPACE space_capital (partition_num=9, '
'replica_factor=1, charset=UTF8, collate=UTF8_bin, vid_type=FIXED_STRING(8))')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_capital')
self.check_resp_succeeded(resp)
expect_result = [['space_capital', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)',
False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
# drop space
resp = self.client.execute('DROP SPACE space_capital')
self.check_resp_succeeded(resp)
def test_if_not_exists_and_if_exist(self):
# exist then failed
resp = self.client.execute('CREATE SPACE default_space')
self.check_resp_failed(resp)
# exist but success
resp = self.client.execute('CREATE SPACE IF NOT EXISTS default_space')
self.check_resp_failed(resp)
# not exist but success
resp = self.client.execute('DROP SPACE IF EXISTS not_exist_space')
self.check_resp_succeeded(resp)
# not exist then failed
resp = self.client.execute('DROP SPACE not_exist_space')
self.check_resp_failed(resp)
resp = self.client.execute('CREATE SPACE exist_space')
self.check_resp_failed(resp)
resp = self.client.execute('DROP SPACE IF EXISTS exist_space')
self.check_resp_succeeded(resp)
def test_drop_space(self):
resp = self.client.execute('SHOW SPACES')
self.check_resp_succeeded(resp)
expect_result = [['default_space']]
self.search_result(resp, expect_result)
resp = self.client.execute('DROP SPACE default_space')
self.check_resp_succeeded(resp)
resp = self.client.execute('SHOW SPACES')
self.check_resp_succeeded(resp)
expect_result = [['default_space']]
self.search_not_exist(resp, expect_result)
def test_create_space_with_string_vid(self):
resp = self.client.execute('CREATE SPACE space_string_vid (partition_num=9, '
'replica_factor=1, charset=utf8, collate=utf8_bin, '
'vid_type = fixed_string(30))')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_string_vid')
self.check_resp_succeeded(resp)
expect_result = [['space_string_vid', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(30)', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
def test_create_space_with_int_vid(self):
resp = self.client.execute('CREATE SPACE space_int_vid (partition_num=9, '
'replica_factor=1, charset=utf8, collate=utf8_bin, '
'vid_type = int64)')
self.check_resp_succeeded(resp)
resp = self.client.execute('DESC SPACE space_int_vid')
self.check_resp_succeeded(resp)
expect_result = [['space_int_vid', 9, 1, 'utf8', 'utf8_bin', 'INT64', False, 'default', T_EMPTY]]
self.check_result(resp, expect_result, {0})
| 43.486842
| 125
| 0.626626
| 1,210
| 9,915
| 4.863636
| 0.093388
| 0.077995
| 0.102294
| 0.153441
| 0.870518
| 0.841122
| 0.818012
| 0.757859
| 0.659473
| 0.583178
| 0
| 0.01708
| 0.267776
| 9,915
| 227
| 126
| 43.678414
| 0.793526
| 0.066768
| 0
| 0.527027
| 0
| 0
| 0.321804
| 0.069066
| 0
| 0
| 0
| 0.004405
| 0
| 1
| 0.040541
| false
| 0
| 0.013514
| 0
| 0.060811
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
912c9bec67f638a52259405756d4fda4dc737190
| 195
|
py
|
Python
|
backend/ohq/pagination.py
|
pennlabs/Office-Hours-Queue
|
f73ec90223c43595c9a167162d9d74abfb11ca42
|
[
"MIT"
] | 8
|
2020-09-05T21:12:25.000Z
|
2022-01-30T18:25:12.000Z
|
backend/ohq/pagination.py
|
pennlabs/Office-Hours-Queue
|
f73ec90223c43595c9a167162d9d74abfb11ca42
|
[
"MIT"
] | 161
|
2020-08-05T17:05:56.000Z
|
2022-03-27T17:44:51.000Z
|
backend/ohq/pagination.py
|
pennlabs/office-hours-queue
|
fce98d3a1b83d1459f61e6d9c3347ef619ee384e
|
[
"MIT"
] | null | null | null |
from rest_framework.pagination import PageNumberPagination
class QuestionSearchPagination(PageNumberPagination):
"""
Custom pagination for QuestionListView.
"""
page_size = 20
| 19.5
| 58
| 0.764103
| 16
| 195
| 9.1875
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012422
| 0.174359
| 195
| 9
| 59
| 21.666667
| 0.900621
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
912fcf83b92837a8ee7ae06692c8b883b70e6322
| 1,577
|
py
|
Python
|
contact/migrations/0006_contactformsuccesspage.py
|
uktrade/invest
|
15b84c511839b46e81608fca9762d2df3f6df16c
|
[
"MIT"
] | 1
|
2019-01-18T03:50:46.000Z
|
2019-01-18T03:50:46.000Z
|
contact/migrations/0006_contactformsuccesspage.py
|
uktrade/invest
|
15b84c511839b46e81608fca9762d2df3f6df16c
|
[
"MIT"
] | 50
|
2018-01-24T18:04:08.000Z
|
2019-01-03T03:30:30.000Z
|
contact/migrations/0006_contactformsuccesspage.py
|
uktrade/invest
|
15b84c511839b46e81608fca9762d2df3f6df16c
|
[
"MIT"
] | 2
|
2018-02-12T15:20:52.000Z
|
2019-01-18T03:51:52.000Z
|
# -*- coding: utf-8 -*-
# Generated by Django 1.11.11 on 2018-04-30 10:49
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import wagtailmarkdown.fields
class Migration(migrations.Migration):
dependencies = [
('wagtailcore', '0040_page_draft_title'),
('contact', '0005_auto_20180430_0934'),
]
operations = [
migrations.CreateModel(
name='ContactFormSuccessPage',
fields=[
('page_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='wagtailcore.Page')),
('body_text', wagtailmarkdown.fields.MarkdownField()),
('body_text_en', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_de', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_es', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_fr', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_pt', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_ar', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_ja', wagtailmarkdown.fields.MarkdownField(null=True)),
('body_text_zh_cn', wagtailmarkdown.fields.MarkdownField(null=True)),
],
options={
'abstract': False,
},
bases=('wagtailcore.page',),
),
]
| 41.5
| 191
| 0.63475
| 156
| 1,577
| 6.198718
| 0.455128
| 0.217166
| 0.316443
| 0.314374
| 0.405377
| 0.361944
| 0.361944
| 0
| 0
| 0
| 0
| 0.03164
| 0.238427
| 1,577
| 37
| 192
| 42.621622
| 0.773522
| 0.043754
| 0
| 0
| 1
| 0
| 0.159468
| 0.043854
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.133333
| 0
| 0.233333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9136bfcfa117b4c5680a0980961f5f207e1dd0bf
| 108
|
py
|
Python
|
packages/python/yap_kernel/yap_ipython/testing/__main__.py
|
ryandesign/yap
|
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
|
[
"Artistic-1.0-Perl",
"ClArtistic"
] | 90
|
2015-03-09T01:24:15.000Z
|
2022-02-24T13:56:25.000Z
|
packages/python/yap_kernel/yap_ipython/testing/__main__.py
|
ryandesign/yap
|
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
|
[
"Artistic-1.0-Perl",
"ClArtistic"
] | 52
|
2016-02-14T08:59:37.000Z
|
2022-03-14T16:39:35.000Z
|
packages/python/yap_kernel/yap_ipython/testing/__main__.py
|
ryandesign/yap
|
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
|
[
"Artistic-1.0-Perl",
"ClArtistic"
] | 27
|
2015-11-19T02:45:49.000Z
|
2021-11-25T19:47:58.000Z
|
if __name__ == '__main__':
from yap_ipython.testing import iptestcontroller
iptestcontroller.main()
| 27
| 52
| 0.759259
| 11
| 108
| 6.636364
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157407
| 108
| 3
| 53
| 36
| 0.802198
| 0
| 0
| 0
| 0
| 0
| 0.074074
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
e67a8860894f989b3e72afd36951546adab63cf8
| 1,243
|
py
|
Python
|
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
|
letouriste001/SmartForest_2.0
|
109b78bf1e8c8404800f377ab969395ccbb617be
|
[
"MIT"
] | null | null | null |
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
|
letouriste001/SmartForest_2.0
|
109b78bf1e8c8404800f377ab969395ccbb617be
|
[
"MIT"
] | null | null | null |
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
|
letouriste001/SmartForest_2.0
|
109b78bf1e8c8404800f377ab969395ccbb617be
|
[
"MIT"
] | null | null | null |
# ACTION_CHECKBOX_NAME is unused, but should stay since its import from here
# has been referenced in documentation.
from django.contrib.admin.decorators import register
from django.contrib.admin.filters import (
AllValuesFieldListFilter, BooleanFieldListFilter, ChoicesFieldListFilter,
DateFieldListFilter, FieldListFilter, ListFilter, RelatedFieldListFilter,
RelatedOnlyFieldListFilter, SimpleListFilter,
)
from django.contrib.admin.helpers import ACTION_CHECKBOX_NAME
from django.contrib.admin.options import (
HORIZONTAL, VERTICAL, ModelAdmin, StackedInline, TabularInline,
)
from django.contrib.admin.sites import AdminSite, site
from django.utils.module_loading import autodiscover_modules
__all__ = [
"register", "ACTION_CHECKBOX_NAME", "ModelAdmin", "HORIZONTAL", "VERTICAL",
"StackedInline", "TabularInline", "AdminSite", "site", "ListFilter",
"SimpleListFilter", "FieldListFilter", "BooleanFieldListFilter",
"RelatedFieldListFilter", "ChoicesFieldListFilter", "DateFieldListFilter",
"AllValuesFieldListFilter", "RelatedOnlyFieldListFilter", "autodiscover",
]
def autodiscover():
autodiscover_modules('admin', register_to=site)
default_app_config = 'django.contrib.admin.apps.AdminConfig'
| 1,243
| 1,243
| 0.798874
| 114
| 1,243
| 8.570175
| 0.491228
| 0.061412
| 0.110542
| 0.11259
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107804
| 1,243
| 1
| 1,243
| 1,243
| 0.880974
| 0.996782
| 0
| 0
| 0
| 0
| 0.288121
| 0.135638
| 0
| 0
| 0
| 0
| 0
| 1
| 0.045455
| false
| 0
| 0.272727
| 0
| 0.318182
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e680e9adaa7b818851db4beac018c7aee50d1cb7
| 616
|
py
|
Python
|
EGGS_labrad/clients/__init__.py
|
EGGS-Experiment/EGGS_labrad
|
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
|
[
"MIT"
] | 2
|
2021-12-26T05:00:54.000Z
|
2021-12-30T17:15:49.000Z
|
EGGS_labrad/clients/__init__.py
|
EGGS-Experiment/EGGS_labrad
|
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
|
[
"MIT"
] | null | null | null |
EGGS_labrad/clients/__init__.py
|
EGGS-Experiment/EGGS_labrad
|
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
|
[
"MIT"
] | null | null | null |
"""
Contains everything needed to write clients.
"""
__all__ = []
# utils
from EGGS_labrad.clients import utils
from EGGS_labrad.clients.utils import *
__all__.extend(utils.__all__)
# client classes
from EGGS_labrad.clients import client
from EGGS_labrad.clients.client import *
__all__.extend(client.__all__)
# connection objects
from EGGS_labrad.clients.script_scanner_gui import connect
from EGGS_labrad.clients.script_scanner_gui.connect import *
__all__.extend(connect.__all__)
# widgets
from EGGS_labrad.clients import Widgets
from EGGS_labrad.clients.Widgets import *
__all__.extend(Widgets.__all__)
| 20.533333
| 60
| 0.814935
| 83
| 616
| 5.46988
| 0.26506
| 0.140969
| 0.246696
| 0.370044
| 0.486784
| 0.162996
| 0.162996
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 616
| 29
| 61
| 21.241379
| 0.825455
| 0.150974
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.615385
| 0
| 0.615385
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
e6a8af56204a16dae94af5f8c0ad8a44032a534f
| 111
|
py
|
Python
|
nes/processors/ppu/attribute_table.py
|
Hexadorsimal/pynes
|
dbb3d40c1240fa27f70fa798bcec09188755eec2
|
[
"MIT"
] | 1
|
2017-05-13T18:57:09.000Z
|
2017-05-13T18:57:09.000Z
|
nes/processors/ppu/attribute_table.py
|
Hexadorsimal/py6502
|
dbb3d40c1240fa27f70fa798bcec09188755eec2
|
[
"MIT"
] | 7
|
2020-10-24T17:16:56.000Z
|
2020-11-01T14:10:23.000Z
|
nes/processors/ppu/attribute_table.py
|
Hexadorsimal/pynes
|
dbb3d40c1240fa27f70fa798bcec09188755eec2
|
[
"MIT"
] | null | null | null |
class AttributeTable:
def __init__(self, start, size):
self.start = start
self.size = size
| 22.2
| 36
| 0.621622
| 13
| 111
| 5
| 0.538462
| 0.276923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.288288
| 111
| 4
| 37
| 27.75
| 0.822785
| 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
|
e6c066b63a0347107c4c7d042a272ec4e4cf7814
| 2,283
|
py
|
Python
|
tests/tests.py
|
RCoff/Smartsheet-DataFrame
|
598f7f4e4f930d963e62855ab540e66aef350f50
|
[
"MIT"
] | 5
|
2021-11-25T01:17:02.000Z
|
2022-02-18T15:58:13.000Z
|
tests/tests.py
|
RCoff/Smartsheet-DataFrame
|
598f7f4e4f930d963e62855ab540e66aef350f50
|
[
"MIT"
] | null | null | null |
tests/tests.py
|
RCoff/Smartsheet-DataFrame
|
598f7f4e4f930d963e62855ab540e66aef350f50
|
[
"MIT"
] | null | null | null |
import smartsheet
import unittest
import config
from src.smartsheet_dataframe import get_report_as_df, get_sheet_as_df, get_as_df
class SheetTests(unittest.TestCase):
def setUp(self):
self.token = config.smartsheet_access_token
self.sheet_id = config.sheet_id
self.report_id = config.report_id
self.sheet_client = smartsheet.Smartsheet(self.token)
self.sheet_obj = self.sheet_client.Sheets.get_sheet(self.sheet_id, include=['objectValue'], level=1)
def test_object_and_request_are_equal(self):
df1 = get_sheet_as_df(token=self.token, sheet_id=self.sheet_id)
df2 = get_sheet_as_df(sheet_obj=self.sheet_obj)
self.assertTrue(df1.to_dict() == df2.to_dict())
def test_generic_vs_specific_requests(self):
df1 = get_sheet_as_df(token=self.token, sheet_id=self.sheet_id)
df2 = get_as_df(type_='sheet', token=self.token, id_=self.sheet_id)
self.assertTrue(df1.to_dict() == df2.to_dict())
def test_generic_vs_specific_object(self):
df1 = get_sheet_as_df(sheet_obj=self.sheet_obj)
df2 = get_as_df(type_='sheet', obj=self.sheet_obj)
self.assertTrue(df1.to_dict() == df2.to_dict())
class ReportTests(unittest.TestCase):
def setUp(self):
self.token = config.smartsheet_access_token
self.report_id = config.report_id
self.sheet_client = smartsheet.Smartsheet(self.token)
self.report_obj = self.sheet_client.Reports.get_report(self.report_id)
def test_report_object_and_request_are_equal(self):
df1 = get_report_as_df(token=self.token, report_id=self.report_id)
df2 = get_report_as_df(report_obj=self.report_obj)
self.assertTrue(df1.to_dict() == df2.to_dict())
def test_generic_vs_specific_requests(self):
df1 = get_report_as_df(token=self.token, report_id=self.report_id)
df2 = get_as_df(type_='report', token=self.token, id_=self.report_id)
self.assertTrue(df1.to_dict() == df2.to_dict())
def test_generic_vs_specific_object(self):
df1 = get_report_as_df(report_obj=self.report_obj)
df2 = get_as_df(type_='report', obj=self.report_obj)
self.assertTrue(df1.to_dict() == df2.to_dict())
if __name__ == "__main__":
unittest.main()
| 36.822581
| 108
| 0.713535
| 344
| 2,283
| 4.34593
| 0.142442
| 0.040134
| 0.048161
| 0.076254
| 0.776589
| 0.749833
| 0.713043
| 0.713043
| 0.680936
| 0.627425
| 0
| 0.013277
| 0.175208
| 2,283
| 61
| 109
| 37.42623
| 0.780669
| 0
| 0
| 0.511628
| 0
| 0
| 0.017959
| 0
| 0
| 0
| 0
| 0
| 0.139535
| 1
| 0.186047
| false
| 0
| 0.093023
| 0
| 0.325581
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e6d621eeef540a2461f7929b43d7a6e12d421ce6
| 240
|
py
|
Python
|
agent/__init__.py
|
eric8607242/OSNASLib
|
43908ab454fb78f835f8a015935205179b9acec4
|
[
"MIT"
] | 3
|
2021-06-14T11:00:21.000Z
|
2021-10-18T02:59:54.000Z
|
agent/__init__.py
|
eric8607242/OneShot_NAS_example
|
2e758a9e5d9e03eecb9c4cc0e2e6a8ec38cf7052
|
[
"MIT"
] | 1
|
2021-12-04T07:42:25.000Z
|
2021-12-04T15:14:12.000Z
|
agent/__init__.py
|
eric8607242/OneShot_NAS_example
|
2e758a9e5d9e03eecb9c4cc0e2e6a8ec38cf7052
|
[
"MIT"
] | null | null | null |
import sys
def get_agent_cls(name):
return getattr(sys.modules[__name__], name)
# Importing customizing modules
from .classification_agent import CFSearchAgent, CFEvaluateAgent
from .face_agent import FRSearchAgent, FREvaluateAgent
| 21.818182
| 64
| 0.820833
| 28
| 240
| 6.75
| 0.678571
| 0.116402
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.120833
| 240
| 10
| 65
| 24
| 0.895735
| 0.120833
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.6
| 0.2
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
e6e14f923671c7fde994222291155054f0ade282
| 43
|
py
|
Python
|
src/tools/generator/__init__.py
|
technote-space/genetic-algorithms-py
|
a37e0a34c5970987d76fda6b14a48d9ab0579e33
|
[
"MIT"
] | 3
|
2020-09-03T18:02:30.000Z
|
2020-09-08T18:09:38.000Z
|
src/tools/generator/__init__.py
|
Amplil/genetic-algorithms-py
|
4788c73b1b9d57eac904e8eb99d9140457201e6b
|
[
"MIT"
] | 7
|
2020-09-08T16:57:19.000Z
|
2022-03-12T00:51:26.000Z
|
src/tools/generator/__init__.py
|
Amplil/genetic-algorithms-py
|
4788c73b1b9d57eac904e8eb99d9140457201e6b
|
[
"MIT"
] | 1
|
2021-04-14T11:10:50.000Z
|
2021-04-14T11:10:50.000Z
|
from .make import Make
__all__ = ['Make']
| 10.75
| 22
| 0.674419
| 6
| 43
| 4.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186047
| 43
| 3
| 23
| 14.333333
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 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
|
e6f5abd6175dd600d7260c994f23b6321bcc673d
| 120
|
py
|
Python
|
uniname.py
|
Rosuav/shed
|
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
|
[
"MIT"
] | 12
|
2015-01-12T15:44:46.000Z
|
2020-07-10T06:35:36.000Z
|
uniname.py
|
Rosuav/shed
|
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
|
[
"MIT"
] | 2
|
2021-11-06T02:09:30.000Z
|
2022-01-23T07:22:09.000Z
|
uniname.py
|
Rosuav/shed
|
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
|
[
"MIT"
] | 8
|
2016-10-12T20:17:10.000Z
|
2022-03-26T08:18:34.000Z
|
#!/usr/bin/env python3
import sys, unicodedata
for ch in " ".join(sys.argv[1:]): print(ascii(ch), unicodedata.name(ch))
| 30
| 72
| 0.7
| 20
| 120
| 4.2
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018519
| 0.1
| 120
| 3
| 73
| 40
| 0.759259
| 0.175
| 0
| 0
| 0
| 0
| 0.010204
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
fc129dca5d24dfa514c25f7d1d28d1ba66574430
| 7,748
|
py
|
Python
|
tests/test_remote_serialize.py
|
KarenImmanuel/hangar-py
|
2a5caff259ad699db56676f14a70cb94e75d8a5b
|
[
"Apache-2.0"
] | null | null | null |
tests/test_remote_serialize.py
|
KarenImmanuel/hangar-py
|
2a5caff259ad699db56676f14a70cb94e75d8a5b
|
[
"Apache-2.0"
] | null | null | null |
tests/test_remote_serialize.py
|
KarenImmanuel/hangar-py
|
2a5caff259ad699db56676f14a70cb94e75d8a5b
|
[
"Apache-2.0"
] | 1
|
2019-10-25T06:11:46.000Z
|
2019-10-25T06:11:46.000Z
|
import pytest
import numpy as np
param_shapes = [(1,), (1000,), (1, 1), (623, 3, 5), (2, 4, 5, 6, 1, 3)]
param_dtypes = [np.uint8, np.float32, np.float64, np.int32]
param_digest = ['digesta', 'digestaaaaaa', 'digestaaaaaaaaaaaaaaaaaaaaaaaaaa']
param_schema = ['schemaa', 'schemaaaaaaaaa', 'schemaaaaaaaaaaaaaaaa']
def assert_equal(arr, arr2):
assert np.array_equal(arr, arr2)
assert arr.dtype == arr2.dtype
@pytest.fixture(scope='module', params=param_shapes)
def arr_shape(request):
return request.param
@pytest.fixture(scope='module', params=param_dtypes)
def arr_dtype(request):
return request.param
@pytest.fixture(scope='module', params=param_digest)
def ident_digest(request):
return request.param
@pytest.fixture(scope='module', params=param_schema)
def ident_schema(request):
return request.param
@pytest.fixture(scope='module')
def array_testcase(arr_shape, arr_dtype):
arr = 200 * np.random.random_sample(arr_shape) - 100
return arr.astype(arr_dtype)
@pytest.fixture(scope='module')
def ident_testcase(ident_digest, ident_schema):
return (ident_digest, ident_schema)
def test_serialize_deserialize_array(array_testcase):
from hangar.remote.chunks import serialize_arr
from hangar.remote.chunks import deserialize_arr
raw = serialize_arr(array_testcase)
res = deserialize_arr(raw)
assert_equal(array_testcase, res)
def test_serialize_deserialize_ident(ident_testcase):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import ArrayIdent
digest, schema = ident_testcase
raw = serialize_ident(digest, schema)
res = deserialize_ident(raw)
assert isinstance(res, ArrayIdent)
assert res.digest == digest
assert res.schema == schema
def test_serialize_deserialize_record(array_testcase, ident_testcase):
from hangar.remote.chunks import serialize_record
from hangar.remote.chunks import deserialize_record
from hangar.remote.chunks import ArrayRecord
digest, schema = ident_testcase
raw = serialize_record(array_testcase, digest, schema)
res = deserialize_record(raw)
assert isinstance(res, ArrayRecord)
assert_equal(res.array, array_testcase)
assert res.digest == digest
assert res.schema == schema
@pytest.mark.parametrize('nrecords', [1, 25])
def test_serialize_deserialize_record_pack(ident_testcase, nrecords):
from hangar.remote.chunks import serialize_record
from hangar.remote.chunks import serialize_record_pack
from hangar.remote.chunks import deserialize_record
from hangar.remote.chunks import deserialize_record_pack
from hangar.remote.chunks import ArrayRecord
idx = 0
ArrList, RecList = [], []
digest, schema = ident_testcase
for shape in param_shapes:
for dtype in param_dtypes:
arr = 200 * np.random.random_sample(shape) + 100
arr = arr.astype(dtype)
digest = f'digest{str(idx)*len(digest)}'
schema = f'schema{str(idx)*len(schema)}'
idx += 1
ArrList.append((arr, digest, schema))
RecList.append(serialize_record(arr, digest, schema))
rawpack = serialize_record_pack(RecList)
reslist = deserialize_record_pack(rawpack)
assert reslist == RecList
for rawres, origRec in zip(reslist, ArrList):
resRec = deserialize_record(rawres)
assert isinstance(resRec, ArrayRecord)
assert_equal(resRec.array, origRec[0])
assert resRec.digest == origRec[1]
assert resRec.schema == origRec[2]
def test_serialize_deserialize_ident_digest_field_only(ident_testcase):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import ArrayIdent
digest, schema = ident_testcase
raw = serialize_ident(digest, '')
res = deserialize_ident(raw)
assert isinstance(res, ArrayIdent)
assert res.digest == digest
assert res.schema == ''
def test_serialize_deserialize_ident_schema_field_only(ident_testcase):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import ArrayIdent
digest, schema = ident_testcase
raw = serialize_ident('', schema)
res = deserialize_ident(raw)
assert isinstance(res, ArrayIdent)
assert res.digest == ''
assert res.schema == schema
@pytest.mark.parametrize('nrecords', [1, 25])
def test_serialize_deserialize_ident_only_record_pack(ident_testcase, nrecords):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import serialize_record_pack
from hangar.remote.chunks import deserialize_record_pack
from hangar.remote.chunks import ArrayIdent
idx = 0
IdentList, RawList = [], []
digest, schema = ident_testcase
for idx in range(nrecords):
digest = f'digest{str(idx)*len(digest)}'
schema = f'schema{str(idx)*len(schema)}'
IdentList.append((digest, schema))
RawList.append(serialize_ident(digest, schema))
packed_raw = serialize_record_pack(RawList)
unpacked_raw = deserialize_record_pack(packed_raw)
assert unpacked_raw == RawList
for raw, origIdent in zip(unpacked_raw, IdentList):
resIdent = deserialize_ident(raw)
assert isinstance(resIdent, ArrayIdent)
assert resIdent.digest == origIdent[0]
assert resIdent.schema == origIdent[1]
@pytest.mark.parametrize('nrecords', [1, 25])
def test_serialize_deserialize_ident_only_digest_only_record_pack(ident_testcase, nrecords):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import serialize_record_pack
from hangar.remote.chunks import deserialize_record_pack
from hangar.remote.chunks import ArrayIdent
idx = 0
IdentList, RawList = [], []
digest, schema = ident_testcase
for idx in range(nrecords):
digest = f'digest{str(idx)*len(digest)}'
schema = f''
IdentList.append((digest, schema))
RawList.append(serialize_ident(digest, schema))
packed_raw = serialize_record_pack(RawList)
unpacked_raw = deserialize_record_pack(packed_raw)
assert unpacked_raw == RawList
for raw, origIdent in zip(unpacked_raw, IdentList):
resIdent = deserialize_ident(raw)
assert isinstance(resIdent, ArrayIdent)
assert resIdent.digest == origIdent[0]
assert resIdent.schema == origIdent[1]
@pytest.mark.parametrize('nrecords', [1, 25])
def test_serialize_deserialize_ident_only_schema_only_record_pack(ident_testcase, nrecords):
from hangar.remote.chunks import serialize_ident
from hangar.remote.chunks import deserialize_ident
from hangar.remote.chunks import serialize_record_pack
from hangar.remote.chunks import deserialize_record_pack
from hangar.remote.chunks import ArrayIdent
idx = 0
IdentList, RawList = [], []
digest, schema = ident_testcase
for idx in range(nrecords):
digest = f''
schema = f'schema{str(idx)*len(schema)}'
IdentList.append((digest, schema))
RawList.append(serialize_ident(digest, schema))
packed_raw = serialize_record_pack(RawList)
unpacked_raw = deserialize_record_pack(packed_raw)
assert unpacked_raw == RawList
for raw, origIdent in zip(unpacked_raw, IdentList):
resIdent = deserialize_ident(raw)
assert isinstance(resIdent, ArrayIdent)
assert resIdent.digest == origIdent[0]
assert resIdent.schema == origIdent[1]
| 33.834061
| 92
| 0.729479
| 955
| 7,748
| 5.726702
| 0.096335
| 0.062169
| 0.09947
| 0.136771
| 0.792467
| 0.750411
| 0.716584
| 0.708356
| 0.69318
| 0.69318
| 0
| 0.010394
| 0.180434
| 7,748
| 229
| 93
| 33.834061
| 0.850866
| 0
| 0
| 0.627907
| 0
| 0
| 0.042457
| 0.02852
| 0
| 0
| 0
| 0
| 0.197674
| 1
| 0.093023
| false
| 0
| 0.209302
| 0.02907
| 0.337209
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fc1d1836fe2ca7576472394f54f6cf39919affc1
| 1,404
|
py
|
Python
|
src/data/data_extractor.py
|
ElenaVasylenko/titanic
|
4256d18354466de2e3d3af1da283959c25bb22f9
|
[
"MIT"
] | null | null | null |
src/data/data_extractor.py
|
ElenaVasylenko/titanic
|
4256d18354466de2e3d3af1da283959c25bb22f9
|
[
"MIT"
] | null | null | null |
src/data/data_extractor.py
|
ElenaVasylenko/titanic
|
4256d18354466de2e3d3af1da283959c25bb22f9
|
[
"MIT"
] | null | null | null |
import pandas as pd
from config import PROJECT_DIR_PATH, PROCESSED_FILES_DIR
class DataExtractor():
def __init__(self):
self.train_file_path = PROJECT_DIR_PATH + "\\data_files\\train.csv"
self.test_file_path = PROJECT_DIR_PATH + "\\data_files\\test.csv"
self.processed_train_file_path = PROCESSED_FILES_DIR + "\\train.csv"
self.processed_test_file_path = PROCESSED_FILES_DIR + "\\test.csv"
self.train_df = pd.read_csv(self.train_file_path, index_col='PassengerId')
self.test_df = pd.read_csv(self.test_file_path, index_col='PassengerId')
self.processed_train_df = pd.read_csv(self.processed_train_file_path, index_col='PassengerId')
self.processed_test_df = pd.read_csv(self.processed_test_file_path, index_col='PassengerId')
#print(self.train_df.info())
self.test_df['Survived'] = -888 # Add Survived column for prediction
self.df = pd.concat((self.train_df, self.test_df), axis=0)
#print(self.df.info())
def get_df(self):
return self.df
def get_train_df(self):
return self.train_df
def get_test_df(self):
return self.test_df
def get_processed_test_df(self):
return self.processed_test_df
def get_processed_train_df(self):
return self.processed_train_df
data_extractor = DataExtractor()
data_extractor_df = data_extractor.get_df()
| 35.1
| 102
| 0.710114
| 204
| 1,404
| 4.504902
| 0.196078
| 0.069641
| 0.065288
| 0.087051
| 0.607182
| 0.4037
| 0.199129
| 0
| 0
| 0
| 0
| 0.003506
| 0.187322
| 1,404
| 39
| 103
| 36
| 0.801928
| 0.059117
| 0
| 0
| 0
| 0
| 0.08953
| 0.034143
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0.153846
| 0.076923
| 0.192308
| 0.538462
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 0
| 0
| 0
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| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
fc31ede07249e87a601e1df74acfd0461999064d
| 113
|
py
|
Python
|
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
|
arXiv-research/DevLab-III
|
fdb3f4fd1abf1beafdc84fecca016db169c5f923
|
[
"MIT"
] | 1
|
2021-04-17T04:38:57.000Z
|
2021-04-17T04:38:57.000Z
|
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
|
arXiv-research/DevLab-III
|
fdb3f4fd1abf1beafdc84fecca016db169c5f923
|
[
"MIT"
] | null | null | null |
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
|
arXiv-research/DevLab-III
|
fdb3f4fd1abf1beafdc84fecca016db169c5f923
|
[
"MIT"
] | null | null | null |
from sacred.utils import SacredInterrupt
class CustomInterrupt(SacredInterrupt)
STATUS = 'MY_CUSTOM_STATUS'
| 22.6
| 40
| 0.823009
| 12
| 113
| 7.583333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.123894
| 113
| 4
| 41
| 28.25
| 0.919192
| 0
| 0
| 0
| 0
| 0
| 0.141593
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.333333
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
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| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
fc6b63ee85841ca211ad643f80e86a4cb4354017
| 232
|
py
|
Python
|
tests/app/apps.py
|
systemallica/django-snitch
|
557ae2a0e01184ffc552536507782fff39785457
|
[
"MIT"
] | 16
|
2019-08-14T13:21:46.000Z
|
2021-09-03T10:35:23.000Z
|
tests/app/apps.py
|
systemallica/django-snitch
|
557ae2a0e01184ffc552536507782fff39785457
|
[
"MIT"
] | 5
|
2020-03-24T17:48:35.000Z
|
2021-05-12T10:02:53.000Z
|
tests/app/apps.py
|
systemallica/django-snitch
|
557ae2a0e01184ffc552536507782fff39785457
|
[
"MIT"
] | 4
|
2019-09-30T11:18:14.000Z
|
2021-01-05T12:26:22.000Z
|
from django.apps import AppConfig
class TestAppConfig(AppConfig):
"""Testing app."""
name = "tests.app"
def ready(self):
try:
import tests.app.signals
except ImportError:
pass
| 16.571429
| 36
| 0.581897
| 24
| 232
| 5.625
| 0.791667
| 0.118519
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.323276
| 232
| 13
| 37
| 17.846154
| 0.859873
| 0.051724
| 0
| 0
| 0
| 0
| 0.042056
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0.125
| 0.375
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
fc787937f43a9b120ec47eb8b90af12a5f6f2496
| 216
|
py
|
Python
|
project_simple/tests/dags/test_cli.py
|
KostyaEsmukov/airflow-docker
|
abf7c50cec71f5153148738d13401546cef9f60c
|
[
"MIT"
] | null | null | null |
project_simple/tests/dags/test_cli.py
|
KostyaEsmukov/airflow-docker
|
abf7c50cec71f5153148738d13401546cef9f60c
|
[
"MIT"
] | null | null | null |
project_simple/tests/dags/test_cli.py
|
KostyaEsmukov/airflow-docker
|
abf7c50cec71f5153148738d13401546cef9f60c
|
[
"MIT"
] | null | null | null |
from pathlib import Path
import pytest
from project_common.testing_cli import * # noqa
import project_simple
@pytest.fixture(scope="session")
def src_root_path():
return Path(project_simple.__file__).parent
| 18
| 48
| 0.791667
| 30
| 216
| 5.366667
| 0.666667
| 0.161491
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12963
| 216
| 11
| 49
| 19.636364
| 0.856383
| 0.018519
| 0
| 0
| 0
| 0
| 0.033333
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| true
| 0
| 0.571429
| 0.142857
| 0.857143
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
fc7928940c86b3c2442bdcb7ff98f8aafb19b9c3
| 2,376
|
py
|
Python
|
test/PR_test/integration_test/dataset/test_batch_dataset.py
|
DwijayDS/fastestimator
|
9b288cb2bd870f971ec4cee09d0b3205e1316a94
|
[
"Apache-2.0"
] | null | null | null |
test/PR_test/integration_test/dataset/test_batch_dataset.py
|
DwijayDS/fastestimator
|
9b288cb2bd870f971ec4cee09d0b3205e1316a94
|
[
"Apache-2.0"
] | null | null | null |
test/PR_test/integration_test/dataset/test_batch_dataset.py
|
DwijayDS/fastestimator
|
9b288cb2bd870f971ec4cee09d0b3205e1316a94
|
[
"Apache-2.0"
] | null | null | null |
import tempfile
import unittest
import numpy as np
import fastestimator as fe
from fastestimator.dataset import NumpyDataset
from fastestimator.test.unittest_util import sample_system_object, sample_system_object_torch
class TestDataset(NumpyDataset):
def __init__(self, data, var):
super().__init__(data)
self.var = var
class TestBatchDataset(unittest.TestCase):
def test_save_and_load_state_with_batch_dataset_tf(self):
def instantiate_system():
system = sample_system_object()
x_train = np.ones((2, 28, 28, 3))
y_train = np.ones((2, ))
ds = TestDataset(data={'x': x_train, 'y': y_train}, var=1)
train_data = fe.dataset.BatchDataset(datasets=[ds, ds], num_samples=[1, 1])
system.pipeline = fe.Pipeline(train_data=train_data, batch_size=2)
return system
system = instantiate_system()
# make some change
new_var = 2
system.pipeline.data["train"][''].datasets[0].var = new_var
# save the state
save_path = tempfile.mkdtemp()
system.save_state(save_path)
# reinstantiate system and load the state
system = instantiate_system()
system.load_state(save_path)
loaded_var = system.pipeline.data["train"][''].datasets[0].var
self.assertEqual(loaded_var, new_var)
def test_save_and_load_state_with_batch_dataset_torch(self):
def instantiate_system():
system = sample_system_object_torch()
x_train = np.ones((2, 3, 28, 28))
y_train = np.ones((2, ))
ds = TestDataset(data={'x': x_train, 'y': y_train}, var=1)
train_data = fe.dataset.BatchDataset(datasets=[ds, ds], num_samples=[1, 1])
system.pipeline = fe.Pipeline(train_data=train_data, batch_size=2)
return system
system = instantiate_system()
# make some change
new_var = 2
system.pipeline.data["train"][''].datasets[0].var = new_var
# save the state
save_path = tempfile.mkdtemp()
system.save_state(save_path)
# reinstantiate system and load the state
system = instantiate_system()
system.load_state(save_path)
loaded_var = system.pipeline.data["train"][''].datasets[0].var
self.assertEqual(loaded_var, new_var)
| 33.464789
| 93
| 0.640152
| 301
| 2,376
| 4.790698
| 0.20598
| 0.070735
| 0.054092
| 0.033287
| 0.78086
| 0.762829
| 0.762829
| 0.762829
| 0.696255
| 0.642164
| 0
| 0.015766
| 0.252525
| 2,376
| 70
| 94
| 33.942857
| 0.796171
| 0.060185
| 0
| 0.638298
| 0
| 0
| 0.010782
| 0
| 0
| 0
| 0
| 0
| 0.042553
| 1
| 0.106383
| false
| 0
| 0.12766
| 0
| 0.319149
| 0
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| null | 0
| 0
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| 1
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| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fc869b5f7105a377ede40951b7f4d0943933af5d
| 70
|
py
|
Python
|
unit_tests/__init__.py
|
LandRegistry/digital-street-title-ui
|
3477c51be8806289da02c758ca5f0732d0444a8f
|
[
"MIT"
] | null | null | null |
unit_tests/__init__.py
|
LandRegistry/digital-street-title-ui
|
3477c51be8806289da02c758ca5f0732d0444a8f
|
[
"MIT"
] | null | null | null |
unit_tests/__init__.py
|
LandRegistry/digital-street-title-ui
|
3477c51be8806289da02c758ca5f0732d0444a8f
|
[
"MIT"
] | 3
|
2019-04-26T06:38:12.000Z
|
2021-04-11T05:22:21.000Z
|
from title_ui import config
config.STATIC_ASSETS_MODE = 'production'
| 17.5
| 40
| 0.828571
| 10
| 70
| 5.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 70
| 3
| 41
| 23.333333
| 0.887097
| 0
| 0
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| 0
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
fca1c7cf8beca479553355ac23daddc572c4fcfa
| 92
|
py
|
Python
|
2014/09/aircraft-over-time/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | 14
|
2015-05-08T13:41:51.000Z
|
2021-02-24T12:34:55.000Z
|
2014/09/aircraft-over-time/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | null | null | null |
2014/09/aircraft-over-time/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | 7
|
2015-04-04T04:45:54.000Z
|
2021-02-18T11:12:48.000Z
|
#!/usr/bin/env python
COPY_GOOGLE_DOC_KEY = '0AqjLQISCZzBkdDF6dTlNdC00Q2NPMVEtQ3FYeUh1amc'
| 23
| 68
| 0.847826
| 9
| 92
| 8.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081395
| 0.065217
| 92
| 3
| 69
| 30.666667
| 0.790698
| 0.217391
| 0
| 0
| 0
| 0
| 0.619718
| 0.619718
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5da06f1df419cd10c931e58a98ac166973beac93
| 143
|
py
|
Python
|
bp/pecan/__init__.py
|
JAlvarezJarreta/pecan
|
9b630655d6490a013542fca86251d4869dd47bc3
|
[
"MIT"
] | 5
|
2016-06-30T18:10:57.000Z
|
2021-03-30T12:31:05.000Z
|
bp/pecan/__init__.py
|
JAlvarezJarreta/pecan
|
9b630655d6490a013542fca86251d4869dd47bc3
|
[
"MIT"
] | 1
|
2016-08-16T23:10:42.000Z
|
2016-08-16T23:10:42.000Z
|
bp/pecan/__init__.py
|
benedictpaten/pecan
|
9b630655d6490a013542fca86251d4869dd47bc3
|
[
"MIT"
] | 3
|
2018-10-24T15:58:48.000Z
|
2019-12-18T13:44:33.000Z
|
#!/usr/bin/env python
#Copyright (C) 2006-2011 by Benedict Paten (benedictpaten@gmail.com)
#
#Released under the MIT license, see LICENSE.txt
| 23.833333
| 68
| 0.755245
| 22
| 143
| 4.909091
| 0.954545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064
| 0.125874
| 143
| 5
| 69
| 28.6
| 0.8
| 0.937063
| 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
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| 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
|
5dd99d5f099ec31fbb441416221e01a104b0ce13
| 5,816
|
py
|
Python
|
rankfromsets/gridsearch/run-rankfromsets-train.py
|
rohanbansal12/extended_essay
|
03848a1c9f4dafe8db0a9ad263e8776681139659
|
[
"MIT"
] | 5
|
2020-09-17T17:56:21.000Z
|
2021-11-03T02:40:27.000Z
|
rankfromsets/gridsearch/run-rankfromsets-train.py
|
rohanbansal12/extended_essay
|
03848a1c9f4dafe8db0a9ad263e8776681139659
|
[
"MIT"
] | null | null | null |
rankfromsets/gridsearch/run-rankfromsets-train.py
|
rohanbansal12/extended_essay
|
03848a1c9f4dafe8db0a9ad263e8776681139659
|
[
"MIT"
] | 1
|
2020-11-01T11:37:38.000Z
|
2020-11-01T11:37:38.000Z
|
import copy
import jobs
import pathlib
import addict
def get_slurm_script_gpu(output_dir, command):
"""Returns contents of SLURM script for a gpu job."""
return """#!/bin/bash
#SBATCH -N 1
#SBATCH --ntasks-per-node=1
#SBATCH --ntasks-per-socket=1
#SBATCH --gres=gpu:tesla_p100:1
#SBATCH --cpus-per-task=4
#SBATCH --mem=64000
#SBATCH --output={}/slurm_%j.out
#SBATCH -t 05:59:00
#module load anaconda3 cudatoolkit/10.0 cudnn/cuda-10.0/7.3.1
#source activate yumi
{}
""".format(
output_dir, command
)
if __name__ == "__main__":
commands = [
"PYTHONPATH=. python train-rankfromsets.py --train_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/train.json --test_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/test.json --eval_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/evaluation.json "
]
experiment_name = "news-rankfromsets"
log_dir = (
pathlib.Path(pathlib.os.environ["LOG"]) / "news-classification-inner-product"
)
base_grid = addict.Dict()
base_grid.create_dicts = False
base_grid.map_items = False
base_grid.emb_size = [10, 25, 50, 100]
base_grid.recall_max = 100
base_grid.tokenize = False
base_grid.target_publication = 0
base_grid.batch_size = 2000
base_grid.training_steps = 1500
base_grid.momentum = 0.9
base_grid.use_sparse = False
base_grid.use_gpu = True
base_grid.frequency = 50
base_grid.dict_dir = pathlib.Path(
"/scratch/gpfs/altosaar/dat/longform-data/main/dictionaries"
)
base_grid.tokenizer_file = (
"/scratch/gpfs/altosaar/dat/longform-data/main/bert-base-uncased.txt"
)
base_grid.index_file_path = (
"/scratch/gpfs/altosaar/dat/longform-data/BERT/eval_indices_list.txt"
)
# RMS with all words
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "RMS"
grid["use_all_words"] = True
grid["learning_rate"] = [1e-1, 1e-3, 1e-4, 1e-5]
grid["word_embedding_type"] = ["sum", "mean"]
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
# RMS with only unique from first 500 words
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "RMS"
grid["use_all_words"] = False
grid["words_to_use"] = 500
grid["learning_rate"] = [1e-1, 1e-3, 1e-4, 1e-5]
grid["word_embedding_type"] = ["sum", "mean"]
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
# SGD with all words and sum
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "SGD"
grid["use_all_words"] = True
grid["learning_rate"] = [0.1, 1, 5, 10, 15]
grid["word_embedding_type"] = "sum"
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
keys_for_dir_name.insert(2, "word_embedding_type")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
# SGD with all words and mean
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "SGD"
grid["use_all_words"] = True
grid["learning_rate"] = [60, 600, 3000, 6000, 9000]
grid["word_embedding_type"] = "mean"
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
keys_for_dir_name.insert(2, "word_embedding_type")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
# SGD with only unique from first 500 words and sum
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "SGD"
grid["use_all_words"] = False
grid["words_to_use"] = 500
grid["learning_rate"] = [0.1, 1, 5, 10, 15]
grid["word_embedding_type"] = "mean"
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
keys_for_dir_name.insert(2, "word_embedding_type")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
# SGD with only unique from first 500 words and sum
grid = copy.deepcopy(base_grid)
grid["optimizer_type"] = "SGD"
grid["use_all_words"] = False
grid["words_to_use"] = 500
grid["learning_rate"] = [30, 300, 1500, 3000, 4500]
grid["word_embedding_type"] = "mean"
keys_for_dir_name = jobs.get_keys_for_dir_name(grid)
keys_for_dir_name.insert(0, "optimizer_type")
keys_for_dir_name.insert(1, "use_all_words")
keys_for_dir_name.insert(2, "word_embedding_type")
for cfg in jobs.param_grid(grid):
cfg["output_dir"] = jobs.make_output_dir(
log_dir, experiment_name, cfg, keys_for_dir_name
)
jobs.submit(commands, cfg, get_slurm_script_gpu)
| 37.522581
| 307
| 0.686554
| 880
| 5,816
| 4.211364
| 0.186364
| 0.06422
| 0.091743
| 0.12844
| 0.732326
| 0.731516
| 0.731516
| 0.703994
| 0.691581
| 0.691581
| 0
| 0.032683
| 0.189821
| 5,816
| 154
| 308
| 37.766234
| 0.75382
| 0.045392
| 0
| 0.562963
| 0
| 0.022222
| 0.28623
| 0.09908
| 0
| 0
| 0
| 0
| 0
| 1
| 0.007407
| false
| 0
| 0.02963
| 0
| 0.044444
| 0
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| 0
| null | 0
| 0
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| 1
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| null | 0
| 0
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| 0
| 0
|
0
| 4
|
5ddf40af4fc99ba634808aa7f934bdcdc424ad0b
| 7,425
|
py
|
Python
|
Push2/parameter_mapping_sensitivities.py
|
phatblat/AbletonLiveMIDIRemoteScripts
|
ef6e87237a9dcea1046fb6836b18af01b160736a
|
[
"MIT"
] | 4
|
2015-12-31T19:13:32.000Z
|
2017-04-23T19:52:16.000Z
|
Push2/parameter_mapping_sensitivities.py
|
phatblat/AbletonLiveMIDIRemoteScripts
|
ef6e87237a9dcea1046fb6836b18af01b160736a
|
[
"MIT"
] | 1
|
2015-12-23T09:59:18.000Z
|
2015-12-23T18:53:01.000Z
|
Push2/parameter_mapping_sensitivities.py
|
phatblat/AbletonLiveMIDIRemoteScripts
|
ef6e87237a9dcea1046fb6836b18af01b160736a
|
[
"MIT"
] | null | null | null |
# Source Generated with Decompyle++
# File: parameter_mapping_sensitivities.pyc (Python 2.5)
from pushbase import consts
DEFAULT_SENSITIVITY_KEY = 'normal_sensitivity'
FINE_GRAINED_SENSITIVITY_KEY = 'fine_grained_sensitivity'
DEFAULT_SENSITIVITY = consts.CONTINUOUS_MAPPING_SENSITIVITY
DEFAULT_FG_SENSITIVITY = consts.FINE_GRAINED_CONTINUOUS_MAPPING_SENSITIVITY
PARAMETER_SENSITIVITIES = {
'Analog': {
'OSC1 Octave': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'OSC2 Octave': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'OSC1 Semi': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'OSC1 Detune': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'OSC2 Semi': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'OSC2 Detune': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'LoungeLizard': {
'Noise Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Damp Balance': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'P Amp < Key': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Semitone': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'Collision': {
'Res 1 Decay': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'Impulse': {
'1 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'2 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'3 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'4 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'5 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'6 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'7 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'8 Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'OriginalSimpler': {
'Zoom': {
DEFAULT_SENSITIVITY_KEY: 1 },
'Mode': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Playback': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Start': {
DEFAULT_SENSITIVITY_KEY: 0.2 },
'End': {
DEFAULT_SENSITIVITY_KEY: 0.2 },
'Sensitivity': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'S Start': {
DEFAULT_SENSITIVITY_KEY: 0.2 },
'S Length': {
DEFAULT_SENSITIVITY_KEY: 0.2 },
'S Loop Length': {
DEFAULT_SENSITIVITY_KEY: 0.2 },
'Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Detune': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Gain': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Env. Type': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Filter Freq': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Filt < Vel': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Filt < Key': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Filt < LFO': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'FE < ENV': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'LR < Key': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Vol < LFO': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Pan < RND': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Pan < LFO': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'L Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'Operator': {
'Oscillator': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'A Coarse': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'B Coarse': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'C Coarse': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'D Coarse': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'LFO Sync': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'MidiArpeggiator': {
'Style': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Synced Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Offset': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Transp. Steps': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Transp. Dist.': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Repeats': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Ret. Interval': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Groove': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Retrigger Mode': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'MidiNoteLength': {
'Synced Length': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'MidiScale': {
'Base': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Transpose': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'Amp': {
'Bass': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Middle': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Treble': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Presence': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Gain': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Volume': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'Dry/Wet': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'AutoFilter': {
'Frequency': {
DEFAULT_SENSITIVITY_KEY: 1 },
'Env. Modulation': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'LFO Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'LFO Phase': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'LFO Offset': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'AutoPan': {
'Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'BeatRepeat': {
'Grid': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Interval': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Offset': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Gate': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Variation': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Mix Type': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Grid': {
DEFAULT_SENSITIVITY_KEY: 0.1 },
'Variation Type': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'Corpus': {
'LFO Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'Eq8': {
'Band': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'1 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'2 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'3 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'4 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'5 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'6 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'7 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 },
'8 Frequency A': {
DEFAULT_SENSITIVITY_KEY: 0.4 } },
'Flanger': {
'Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'GrainDelay': {
'Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 } },
'Phaser': {
'LFO Sync Rate': {
DEFAULT_SENSITIVITY_KEY: 0.1 } },
'Resonator': {
'II Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'III Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'IV Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 },
'V Pitch': {
DEFAULT_SENSITIVITY_KEY: 0.5 } } }
| 32.709251
| 75
| 0.508418
| 737
| 7,425
| 4.826323
| 0.169607
| 0.511105
| 0.590385
| 0.599944
| 0.771437
| 0.555243
| 0.168119
| 0.057914
| 0.029238
| 0.029238
| 0
| 0.047264
| 0.367407
| 7,425
| 226
| 76
| 32.853982
| 0.710028
| 0.011852
| 0
| 0.502242
| 1
| 0
| 0.151214
| 0.003272
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.004484
| 0
| 0.004484
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b90ae3301efb79ab37e54874071cd29717d8a21a
| 241
|
py
|
Python
|
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
|
FrancesMaffyValor/DownGit
|
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
|
[
"MIT"
] | 1
|
2019-09-19T07:35:23.000Z
|
2019-09-19T07:35:23.000Z
|
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
|
FrancesMaffyValor/DownGit
|
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
|
[
"MIT"
] | null | null | null |
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
|
FrancesMaffyValor/DownGit
|
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
|
[
"MIT"
] | null | null | null |
from django import template
from healingcirclemassage.static.forms import EmailForm
register = template.Library()
@register.filter
@register.inclusion_tag("email_form.html")
def display_email_form():
return {"email_form": EmailForm()}
| 24.1
| 55
| 0.79668
| 29
| 241
| 6.448276
| 0.655172
| 0.144385
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| 0
| 0
| 0.099585
| 241
| 9
| 56
| 26.777778
| 0.861751
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| 0.103734
| 0
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| 1
| 0.142857
| false
| 0
| 0.285714
| 0.142857
| 0.571429
| 0
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| null | 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
f8f29b00a0bb66e2fcf3ddaaa9271a539ff99468
| 10,594
|
py
|
Python
|
home-assignments/HA3/gridworld_mdp.py
|
JulianoLagana/deep-machine-learning
|
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
|
[
"MIT"
] | 49
|
2017-09-07T19:56:45.000Z
|
2022-02-17T11:19:14.000Z
|
home-assignments/HA3/gridworld_mdp.py
|
JulianoLagana/deep-machine-learning
|
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
|
[
"MIT"
] | 16
|
2018-09-05T08:10:21.000Z
|
2021-09-06T11:47:54.000Z
|
home-assignments/HA3/gridworld_mdp.py
|
JulianoLagana/deep-machine-learning
|
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
|
[
"MIT"
] | 103
|
2017-09-19T13:37:32.000Z
|
2021-11-03T14:09:59.000Z
|
from collections import namedtuple
import numpy as np
def test_policy(pi):
pi[4] = 0 # green state
pi[9] = 0 # red state
pi[6] = 0 # unreachable state
pi[7] = 0 # unreachable state
pi_star = np.array([ 3., 3., 3., 3., 0., 0., 0., 0., 1., 0., 0., 1., 1., 1., 2., 0.])
assert np.array_equal(pi, pi_star), "Failed, policy is not optimal"
print('Passed: policy test, for gamma=.99')
def test_state_values(V):
v_star = np.array([ 0.93861973, 0.95193393, 0.9639533, 0.97612443, 1.,
0.92691625, 0., 0., 0.88371826, -1.,
0.91395196, 0.90255605, 0.89130223, 0.88057656, 0.79978972,
0])
assert (sum(abs(V - v_star)) < 1e-4), "Failed, not correct state-values"
print('Passed: state-value test, for gamma=.99')
def test_value_iteration(V, pi):
test_state_values(V)
test_policy(pi)
def test_q_learning(Q):
pi = [np.argmax(Q[i]) for i in range(len(Q[:]))]
test_policy(pi)
class GridWorldMDP(object):
def __init__(self, trans_prob=.8):
'''
Initializes an instance of the GridWorldMDP class
:param trans_prob: transition probabilities (e.g. =1 for deterministic MDP)
'''
assert 0 <= trans_prob and trans_prob <= 1., "Not a valid transition probability"
# actions {0=N, 1=W, 2=S, 3}
# available actions: North, West, South, East
self.__actions_to_char = {i: char for i, char in enumerate(['↑', '←', '↓', '→'])}
self.__num_actions = 4
self.__actions = np.arange(self.__num_actions)
self._transition_model = self.__transition_model(trans_prob)
self._num_states = np.shape(self._transition_model)[1]
self._init_state = 10 # init state in lower left corner
self._state = self._init_state
self._states = np.arange(self._num_states)
def get_states(self):
'''
Returns complete set of states for the MDP
:return: numpy array of shape [num states,]
'''
return self._states
def get_actions(self):
'''
Returns complete set of actions for the MDP
:return: numpy array of shape [num actions,]
'''
return self.__actions
@property
def act_to_char_dict(self):
'''
Returns dictionary that points action to char, i,e. N, W, S, E
'''
return self.__actions_to_char
def reset(self):
'''
Resets the environment and the agent is positioned in the initial state in the bottom left corner.
:return: state, reward, terminal
'''
self._state = self._init_state
return self._state, 0, False
def step(self, action):
'''
Takes one step in the environment using the selected action
:param action: action to execute, integer
:return: state, reward, terminal
'''
trans_prob = self.state_transition_func(self._state, action)
new_state = np.random.choice(self._num_states, p=trans_prob)
reward = 0
terminal = self._state == 15
reward = self.reward_function(self._state, action)
self._state = new_state
return new_state, reward, terminal
def __transition_model(self, p=.8):
p_ = (1-p) / 2
return np.array([ #NORTH
[[p + p_, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state
[p, 0, 0, 0, 0, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # ureachable
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # ureachable
[0, 0, 0, p, 0, 0, 0,0 , p_, p_, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state
[0, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, p_, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, 0, p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop
], # WEST
[[p + p_, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[p, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, p, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, p, 2* p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state
[p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable
[0, 0, 0, p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state
[0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p + p_, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p, 2 * p_, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p, 2 * p_, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, p, p_, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, p, p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop
], # SOUTH
[[p_, p_, 0, 0, 0, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, p_, 0, p_, 0, 0, 0, p, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state
[0, 0, 0, 0, 0, 2 * p_, 0, 0, 0, 0, p, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state
[0, 0, 0, 0, 0, 0, 0, 0, p_, p_, 0, 0, 0, p, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p + p_, p_, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p + p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop
],
# EAST
[[p_, p, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 2*p_, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2*p_, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, p_, p, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state
[p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state
[0, 0, 0, p_, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state
[0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p_, p, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2 * p_, p, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2 * p_, p, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p_, p, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p + p_, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop
]])
def state_transition_func(self, s, a):
'''
Returns the transition probabilities to all states given current state and action
:param state: current state as integer
:param action: selected action as integer
:return: state-transition probabilities, i.e.
[P[S_0| S=s, A_t=a], P[S_1| S=s, A=a], ..., P[S_14| S=s, A=a]]
'''
return np.array(self._transition_model[a, s])
def reward_function(self, s, a):
'''
Returns the reward r(s,a)
:param state: current state as integer
:param action: selected action as integer
:return: r(s,a)
'''
if s ==4:
return 1 # green state
elif s==9:
return -1 # red state
else:
return 0
| 51.427184
| 109
| 0.360204
| 1,658
| 10,594
| 2.199035
| 0.095296
| 0.439934
| 0.582556
| 0.674712
| 0.458585
| 0.424575
| 0.412781
| 0.410587
| 0.410587
| 0.391114
| 0
| 0.196653
| 0.481121
| 10,594
| 205
| 110
| 51.678049
| 0.46589
| 0.143383
| 0
| 0.280303
| 0
| 0
| 0.020119
| 0
| 0
| 0
| 0
| 0
| 0.022727
| 1
| 0.098485
| false
| 0.015152
| 0.015152
| 0
| 0.19697
| 0.015152
| 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
|
f8f86e9a97a4f38d785079dd743a351edabd6c6f
| 3,681
|
py
|
Python
|
Code/queue.py
|
alexbarksdale/CS-1.3-Core-Data-Structures
|
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
|
[
"MIT"
] | null | null | null |
Code/queue.py
|
alexbarksdale/CS-1.3-Core-Data-Structures
|
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
|
[
"MIT"
] | 6
|
2020-02-15T17:40:00.000Z
|
2020-03-09T22:32:05.000Z
|
Code/queue.py
|
alexbarksdale/CS-1.3-Core-Data-Structures
|
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
|
[
"MIT"
] | null | null | null |
#!python
from linkedlist import LinkedList
# Implement LinkedQueue below, then change the assignment at the bottom
# to use this Queue implementation to verify it passes all tests
class LinkedQueue(object):
def __init__(self, iterable=None):
"""Initialize this queue and enqueue the given items, if any."""
# Initialize a new linked list to store the items
self.list = LinkedList()
if iterable is not None:
for item in iterable:
self.enqueue(item)
def __repr__(self):
"""Return a string representation of this queue."""
return 'Queue({} items, front={})'.format(self.length(), self.front())
def is_empty(self):
"""Return True if this queue is empty, or False otherwise."""
return self.list.is_empty()
def length(self):
"""Return the number of items in this queue."""
return self.list.length()
def enqueue(self, item):
"""Insert the given item at the back of this queue.
Running time: O(1) because the LL append() executes once in constant time.
"""
self.list.append(item)
def front(self):
"""Return the item at the front of this queue without removing it,
or None if this queue is empty."""
return None if self.is_empty() else self.list.head.data
def dequeue(self):
"""Remove and return the item at the front of this queue,
or raise ValueError if this queue is empty.
Running time: O(1) because the item being removed is the first item
which executes once in constant time.
"""
if self.is_empty():
raise ValueError("Queue is empty")
top_item = self.list.head.data
self.list.delete(top_item)
return top_item
# Implement ArrayQueue below, then change the assignment at the bottom
# to use this Queue implementation to verify it passes all tests
class ArrayQueue(object):
def __init__(self, iterable=None):
"""Initialize this queue and enqueue the given items, if any."""
# Initialize a new list (dynamic array) to store the items
self.list = list()
if iterable is not None:
for item in iterable:
self.enqueue(item)
def __repr__(self):
"""Return a string representation of this queue."""
return 'Queue({} items, front={})'.format(self.length(), self.front())
def is_empty(self):
"""Return True if this queue is empty, or False otherwise."""
return len(self.list) == 0
def length(self):
"""Return the number of items in this queue."""
return len(self.list)
def enqueue(self, item):
"""Insert the given item at the back of this queue.
Running time: O(n) because you need to shift everything
over by one after you insert"""
self.list.insert(0, item)
def front(self):
"""Return the item at the front of this queue without removing it,
or None if this queue is empty."""
return None if self.is_empty() else self.list[len(self.list) - 1]
def dequeue(self):
"""Remove and return the item at the front of this queue,
or raise ValueError if this queue is empty.
Running time: O(1) because you're removing the last item and requires
no shifting."""
if self.is_empty():
raise ValueError("Queue is empty")
return self.list.pop(len(self.list) - 1)
# Implement LinkedQueue and ArrayQueue above, then change the assignment below
# to use each of your Queue implementations to verify they each pass all tests
# Queue = LinkedQueue
Queue = ArrayQueue
| 35.394231
| 82
| 0.638957
| 518
| 3,681
| 4.490347
| 0.220077
| 0.077386
| 0.037833
| 0.033534
| 0.730868
| 0.708512
| 0.682717
| 0.682717
| 0.682717
| 0.648323
| 0
| 0.002613
| 0.272209
| 3,681
| 103
| 83
| 35.737864
| 0.865622
| 0.487368
| 0
| 0.590909
| 0
| 0
| 0.045855
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.318182
| false
| 0
| 0.022727
| 0
| 0.613636
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
5d331867511d8c49bfb46ebaa6ee797755b94009
| 11,141
|
py
|
Python
|
tests/test_korean_tokenizer.py
|
bage79/python-nori
|
f7824cecea7a498a01736d6caf8dd14faeebd8b7
|
[
"Apache-2.0"
] | 1
|
2020-07-13T15:23:07.000Z
|
2020-07-13T15:23:07.000Z
|
tests/test_korean_tokenizer.py
|
bage79/python-nori
|
f7824cecea7a498a01736d6caf8dd14faeebd8b7
|
[
"Apache-2.0"
] | null | null | null |
tests/test_korean_tokenizer.py
|
bage79/python-nori
|
f7824cecea7a498a01736d6caf8dd14faeebd8b7
|
[
"Apache-2.0"
] | null | null | null |
"""
Reference: https://github.com/apache/lucene-solr/blob/master/lucene/analysis/nori/src/test/org/apache/lucene/analysis/ko/TestKoreanTokenizer.java
TODO Test List.
- test_reading
- test_random_strings
- test_random_huge_strings
- test_random_huge_string_mock_graph_after
- test_combining
"""
import os
import unittest
from configparser import ConfigParser
from pynori.korean_tokenizer import KoreanTokenizer, DcpdMode
from pynori.pos import POS
cfg = ConfigParser()
PATH_CUR = os.getcwd() + '/pynori'
cfg.read(PATH_CUR + '/config.ini')
# PATH
PATH_USER_DICT = cfg['PATH']['USER_DICT']
## Initization
print('KoreanTokenizer Initializing...')
tokenizer = KoreanTokenizer(verbose=False, path_userdict=PATH_USER_DICT, decompound_mode=DcpdMode.NONE, infl_decompound_mode=DcpdMode.NONE, output_unknown_unigrams=False, discard_punctuation=True)
tokenizer_with_punctuation = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.NONE, DcpdMode.DISCARD, False, False)
tokenizer_unigram = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.NONE, DcpdMode.DISCARD, True, True)
tokenizer_decompound = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.DISCARD, False, True)
tokenizer_decompound_keep = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.MIXED, DcpdMode.MIXED, False, True)
tokenizer_infl_decompound_none = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.NONE, False, True)
tokenizer_infl_decompound_mixed = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.MIXED, False, True)
# analyzer_reading => test_korean_analyzer
class TestKoreanTokenizer(unittest.TestCase):
def setUp(self):
pass
def do(self, kor_tokenizer, token_attr, in_string):
kor_tokenizer.set_input(in_string)
while kor_tokenizer.increment_token():
pass
tkn_attr_obj = kor_tokenizer.tkn_attr_obj
return tkn_attr_obj.__dict__[token_attr]
def test_spaces(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "화학 이외의 것"), ["화학", "이외", "의", "것"])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "화학 이외의 것"), [(0, 2), (10, 12), (12, 13), (22, 23)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "화학 이외의 것"), [1, 1, 1, 1])
self.assertEqual(self.do(tokenizer, 'termAtt', "화학 이외의 것"), ["화학", "이외", "의", "것"])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "화학 이외의 것"), [(0, 2), (3, 5), (5, 6), (7, 8)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "화학 이외의 것"), [1, 1, 1, 1])
def test_part_of_speechs(self):
self.assertEqual(self.do(tokenizer, 'posTagAtt', "화학 이외의 것"), ['NNG', 'NNG', 'JKG', 'NNB'])
def test_part_of_speechs_with_punc(self):
self.assertEqual(self.do(tokenizer_with_punctuation, 'termAtt', "화학 이외의 것!"), ['화학', ' ', '이외', '의', ' ', '것', '!'])
self.assertEqual(self.do(tokenizer_with_punctuation, 'posTagAtt', "화학 이외의 것!"), ['NNG', 'SP', 'NNG', 'JKG', 'SP', 'NNB', 'SF'])
def test_floating_point_number(self):
self.assertEqual(self.do(tokenizer_with_punctuation, 'termAtt', "10.1 인치 모니터"), ['10', '.', '1', ' ', '인치', ' ', '모니터'])
self.assertEqual(self.do(tokenizer_with_punctuation, 'offsetAtt', "10.1 인치 모니터"), [(0, 2), (2, 3), (3, 4), (4, 5), (5, 7), (7, 8), (8, 11)])
self.assertEqual(self.do(tokenizer_with_punctuation, 'posLengthAtt', "10.1 인치 모니터"), [1, 1, 1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer, 'termAtt', "10.1 인치 모니터"), ['10', '1', '인치', '모니터'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "10.1 인치 모니터"), [(0, 2), (3, 4), (5, 7), (8, 11)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "10.1 인치 모니터"), [1, 1, 1, 1])
def test_part_of_speechs_with_compound(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지나물', '은', '한국', '중국', '일본'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 5), (5, 6), (7, 9), (11, 13), (15, 17)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'JX', 'NNP', 'NNP', 'NNP'])
self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지', '나물', '은', '한국', '중국', '일본'])
self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 3), (3, 5), (5, 6), (7, 9), (11, 13), (15, 17)])
self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [1, 1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'NNG', 'JX', 'NNP', 'NNP', 'NNP'])
self.assertEqual(self.do(tokenizer_decompound_keep, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지나물', '가락지', '나물', '은', '한국', '중국', '일본'])
self.assertEqual(self.do(tokenizer_decompound_keep, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 5), (0, 3), (3, 5), (5, 6), (7, 9), (11, 13), (15, 17)])
self.assertEqual(self.do(tokenizer_decompound_keep, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [2, 1, 1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer_decompound_keep, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'NNG', 'NNG', 'JX', 'NNP', 'NNP', 'NNP'])
def test_part_of_speechs_with_inflects(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "감싸여"), ['감싸여'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "감싸여"), [(0, 3)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "감싸여"), [1])
self.assertEqual(self.do(tokenizer, 'posTypeAtt', "감싸여"), [POS.Type.INFLECT])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "감싸여"), ['VV+EC'])
self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "감싸여"), ['감싸이', '어'])
self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "감싸여"), [(0, 3), (0, 3)])
self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "감싸여"), [1, 1])
self.assertEqual(self.do(tokenizer_decompound, 'posTypeAtt', "감싸여"), [POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "감싸여"), ['VV', 'EC'])
self.assertEqual(self.do(tokenizer_decompound_keep, 'termAtt', "감싸여"), ['감싸여', '감싸이', '어'])
self.assertEqual(self.do(tokenizer_decompound_keep, 'offsetAtt', "감싸여"), [(0, 3), (0, 3), (0, 3)])
self.assertEqual(self.do(tokenizer_decompound_keep, 'posLengthAtt', "감싸여"), [2, 1, 1])
self.assertEqual(self.do(tokenizer_decompound_keep, 'posTypeAtt', "감싸여"), [POS.Type.INFLECT, POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer_decompound_keep, 'posTagAtt', "감싸여"), ['VV+EC', 'VV', 'EC'])
def test_unknown_word(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "2018 평창 동계올림픽대회"), ['2018', '평창', '동계', '올림픽', '대회'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "2018 평창 동계올림픽대회"), [(0, 4), (5, 7), (8, 10), (10, 13), (13, 15)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "2018 평창 동계올림픽대회"), [1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer, 'posTypeAtt', "2018 평창 동계올림픽대회"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "2018 평창 동계올림픽대회"), ['SN', 'NNP', 'NNP', 'NNP', 'NNG'])
self.assertEqual(self.do(tokenizer_unigram, 'termAtt', "2018 평창 동계올림픽대회"), ['2', '0', '1', '8', '평창', '동계', '올림픽', '대회'])
self.assertEqual(self.do(tokenizer_unigram, 'offsetAtt', "2018 평창 동계올림픽대회"), [(0, 1), (1, 2), (2, 3), (3, 4), (5, 7), (8, 10), (10, 13), (13, 15)])
self.assertEqual(self.do(tokenizer_unigram, 'posLengthAtt', "2018 평창 동계올림픽대회"), [1, 1, 1, 1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer_unigram, 'posTypeAtt', "2018 평창 동계올림픽대회"),
[POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer_unigram, 'posTagAtt', "2018 평창 동계올림픽대회"), ['SN', 'SN', 'SN', 'SN', 'NNP', 'NNP', 'NNP', 'NNG'])
# def test_reading(self):
# pass
def test_userdict(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "c++ 프로그래밍 언어"), ['c++', '프로그래밍', '언어'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "c++ 프로그래밍 언어"), [(0, 3), (4, 9), (10, 12)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "c++ 프로그래밍 언어"), [1, 1, 1])
self.assertEqual(self.do(tokenizer, 'posTypeAtt', "c++ 프로그래밍 언어"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "c++ 프로그래밍 언어"), ['NNG', 'NNG', 'NNG'])
self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "정부세종청사"), ['정부', '세종', '청사'])
self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "정부세종청사"), [(0, 2), (2, 4), (4, 6)])
self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "정부세종청사"), [1, 1, 1])
self.assertEqual(self.do(tokenizer_decompound, 'posTypeAtt', "정부세종청사"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "정부세종청사"), ['NNG', 'NNG', 'NNG'])
self.assertEqual(self.do(tokenizer, 'termAtt', "대한민국날씨"), ['대한민국날씨'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "대한민국날씨"), [(0, 6)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "대한민국날씨"), [1])
self.assertEqual(self.do(tokenizer, 'posTypeAtt', "대한민국날씨"), [POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "대한민국날씨"), ['NNG'])
self.assertEqual(self.do(tokenizer, 'termAtt', "21세기대한민국"), ['21세기대한민국'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "21세기대한민국"), [(0, 8)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "21세기대한민국"), [1])
self.assertEqual(self.do(tokenizer, 'posTypeAtt', "21세기대한민국"), [POS.Type.MORPHEME])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "21세기대한민국"), ['NNG'])
def test_inter_punct(self):
self.assertEqual(self.do(tokenizer, 'termAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), ['도로', '지반', '수자원', '건설', '환경', '건축', '화재', '설비', '연구'])
self.assertEqual(self.do(tokenizer, 'offsetAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), [(0, 2), (3, 5), (6, 9), (10, 12), (12, 14), (15, 17), (18, 20), (20, 22), (22, 24)])
self.assertEqual(self.do(tokenizer, 'posLengthAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), [1, 1, 1, 1, 1, 1, 1, 1, 1])
self.assertEqual(self.do(tokenizer, 'posTagAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), ['NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG'])
def test_infl_mode(self):
self.assertEqual(self.do(tokenizer_infl_decompound_none, 'termAtt', "가벼운 냉장고"), ['가벼운', '냉장', '고'])
self.assertEqual(self.do(tokenizer_infl_decompound_mixed, 'termAtt', "가벼운 냉장고"), ['가벼운', '가볍', 'ᆫ', '냉장', '고'])
def tearDown(self):
pass
if __name__ == '__main__':
unittest.main()
| 69.198758
| 196
| 0.638363
| 1,470
| 11,141
| 4.72517
| 0.131973
| 0.168442
| 0.21336
| 0.235819
| 0.745897
| 0.706306
| 0.611143
| 0.476965
| 0.423265
| 0.298733
| 0
| 0.036986
| 0.157885
| 11,141
| 160
| 197
| 69.63125
| 0.703368
| 0.034018
| 0
| 0.058824
| 0
| 0
| 0.188204
| 0.008931
| 0
| 0
| 0
| 0.00625
| 0.655462
| 1
| 0.109244
| false
| 0.02521
| 0.042017
| 0
| 0.168067
| 0.008403
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5d5ab7923cc1d778fa28786e250f7753d3f2c17a
| 268
|
py
|
Python
|
comprehemd/blocks/__init__.py
|
cariad/comprehemd
|
668c9cb5b757f0fd09ffb8e73f70d432294ad394
|
[
"MIT"
] | null | null | null |
comprehemd/blocks/__init__.py
|
cariad/comprehemd
|
668c9cb5b757f0fd09ffb8e73f70d432294ad394
|
[
"MIT"
] | 4
|
2021-11-27T09:00:53.000Z
|
2021-11-30T16:25:45.000Z
|
comprehemd/blocks/__init__.py
|
cariad/comprehemd
|
668c9cb5b757f0fd09ffb8e73f70d432294ad394
|
[
"MIT"
] | null | null | null |
from comprehemd.blocks.block import Block
from comprehemd.blocks.code import CodeBlock
from comprehemd.blocks.empty import EmptyBlock
from comprehemd.blocks.heading import HeadingBlock
__all__ = [
"Block",
"CodeBlock",
"EmptyBlock",
"HeadingBlock",
]
| 22.333333
| 50
| 0.761194
| 29
| 268
| 6.896552
| 0.413793
| 0.28
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152985
| 268
| 11
| 51
| 24.363636
| 0.881057
| 0
| 0
| 0
| 0
| 0
| 0.134328
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
5d5b9654991ce6515bbfd1b4fff11e08ccb3fa29
| 177
|
py
|
Python
|
diffpriv_laplace/global_sensitivity/median.py
|
aleph-research/diff-priv-laplace-python
|
74233931a0edc1503c332d731d9aa2784ec04189
|
[
"MIT"
] | 6
|
2020-04-13T01:09:38.000Z
|
2020-11-11T08:01:18.000Z
|
diffpriv_laplace/global_sensitivity/median.py
|
aleph-research/diff-priv-laplace-python
|
74233931a0edc1503c332d731d9aa2784ec04189
|
[
"MIT"
] | null | null | null |
diffpriv_laplace/global_sensitivity/median.py
|
aleph-research/diff-priv-laplace-python
|
74233931a0edc1503c332d731d9aa2784ec04189
|
[
"MIT"
] | null | null | null |
from diffpriv_laplace.global_sensitivity.base import GlobalSensitivity
class MedianGlobalSensitivity(GlobalSensitivity):
def __init__(self):
super().__init__(1.0)
| 25.285714
| 70
| 0.79096
| 18
| 177
| 7.222222
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012987
| 0.129944
| 177
| 6
| 71
| 29.5
| 0.831169
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
536fdb152dcef8fd304b30ccecb4f8b2be6a4616
| 553
|
py
|
Python
|
ultra/learning_algorithm/__init__.py
|
rowedenny/ULTRA_pytorch
|
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
|
[
"Apache-2.0"
] | 46
|
2021-07-01T04:02:35.000Z
|
2022-03-31T02:29:20.000Z
|
ultra/learning_algorithm/__init__.py
|
rowedenny/ULTRA_pytorch
|
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
|
[
"Apache-2.0"
] | 5
|
2021-08-12T21:20:56.000Z
|
2022-02-01T22:41:34.000Z
|
ultra/learning_algorithm/__init__.py
|
rowedenny/ULTRA_pytorch
|
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
|
[
"Apache-2.0"
] | 9
|
2021-08-14T12:42:26.000Z
|
2022-02-22T08:29:17.000Z
|
# note:
from __future__ import absolute_import
from .base_algorithm import *
from .dla import *
from .ipw_rank import *
from .regression_EM import *
from .pdgd import *
from .dbgd import *
from .pairwise_debias import *
from .navie_algorithm import *
from .mgd import *
from .nsgd import *
from .lambda_rank import *
from .prs_rank import *
def list_available() -> list:
from .base_algorithm import BaseAlgorithm
from ultra.utils.sys_tools import list_recursive_concrete_subclasses
return list_recursive_concrete_subclasses(BaseAlgorithm)
| 26.333333
| 72
| 0.786618
| 74
| 553
| 5.594595
| 0.445946
| 0.289855
| 0.082126
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148282
| 553
| 20
| 73
| 27.65
| 0.878981
| 0.009042
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.058824
| true
| 0
| 0.882353
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
5377f1a511bcd75f7920708582f914adc64c9275
| 257
|
py
|
Python
|
kfdata/transformer.py
|
kylef-archive/KFData.py
|
685d58255c9f8518834e395d94d3b75d3dd3eceb
|
[
"BSD-3-Clause"
] | 1
|
2015-11-08T13:23:39.000Z
|
2015-11-08T13:23:39.000Z
|
kfdata/transformer.py
|
kylef/KFData.py
|
685d58255c9f8518834e395d94d3b75d3dd3eceb
|
[
"BSD-3-Clause"
] | null | null | null |
kfdata/transformer.py
|
kylef/KFData.py
|
685d58255c9f8518834e395d94d3b75d3dd3eceb
|
[
"BSD-3-Clause"
] | null | null | null |
class ValueTransformer(object):
ATTRIBUTE_TYPE = 'Transformable'
def __init__(self, name):
self.name = name
def __str__(self):
return self.name
def __repr__(self):
return '<ValueTransformer {}>'.format(self.name)
| 19.769231
| 56
| 0.638132
| 27
| 257
| 5.592593
| 0.518519
| 0.211921
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.249027
| 257
| 12
| 57
| 21.416667
| 0.782383
| 0
| 0
| 0
| 0
| 0
| 0.132813
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0.25
| 0.875
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
53b94283c6cec76206879bdce8c22f3c6912330b
| 15
|
py
|
Python
|
stac_api/__init__.py
|
lossyrob/arturo-stac-api
|
3cd885639caaefd521d354a7f70ce86eea4e36e5
|
[
"MIT"
] | 1
|
2021-03-25T11:39:59.000Z
|
2021-03-25T11:39:59.000Z
|
stac_api/__init__.py
|
lossyrob/arturo-stac-api
|
3cd885639caaefd521d354a7f70ce86eea4e36e5
|
[
"MIT"
] | null | null | null |
stac_api/__init__.py
|
lossyrob/arturo-stac-api
|
3cd885639caaefd521d354a7f70ce86eea4e36e5
|
[
"MIT"
] | null | null | null |
"""stac_api"""
| 7.5
| 14
| 0.533333
| 2
| 15
| 3.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 15
| 1
| 15
| 15
| 0.5
| 0.533333
| 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
|
53c8c77d0b7fef8cffd80512448706672cc52e99
| 94
|
py
|
Python
|
energenie/Devices/MIHO059.py
|
klattimer/pyenergenie
|
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
|
[
"MIT"
] | null | null | null |
energenie/Devices/MIHO059.py
|
klattimer/pyenergenie
|
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
|
[
"MIT"
] | 15
|
2020-03-22T13:55:00.000Z
|
2021-12-14T09:07:56.000Z
|
energenie/Devices/MIHO059.py
|
klattimer/pyenergenie
|
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
|
[
"MIT"
] | null | null | null |
# Smart 6mm double socket brushed steel
# https://energenie4u.co.uk/catalogue/product/MIHO059
| 31.333333
| 53
| 0.797872
| 13
| 94
| 5.769231
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0.095745
| 94
| 2
| 54
| 47
| 0.823529
| 0.946809
| 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
|
53f46a9cf190ba251ed836c3a7269b1eb9271ccc
| 2,923
|
py
|
Python
|
python/lvmdatasimulator/wavecoords.py
|
sdss/lvmdatasimulator
|
3857fe0794970a51ca70baab9edc04b780b9f3bf
|
[
"BSD-3-Clause"
] | null | null | null |
python/lvmdatasimulator/wavecoords.py
|
sdss/lvmdatasimulator
|
3857fe0794970a51ca70baab9edc04b780b9f3bf
|
[
"BSD-3-Clause"
] | null | null | null |
python/lvmdatasimulator/wavecoords.py
|
sdss/lvmdatasimulator
|
3857fe0794970a51ca70baab9edc04b780b9f3bf
|
[
"BSD-3-Clause"
] | null | null | null |
# encoding: utf-8
#
# @Author: Oleg Egorov, Enrico Congiu
# @Date: Nov 12, 2021
# @Filename: field.py
# @License: BSD 3-Clause
# @Copyright: Oleg Egorov, Enrico Congiu
import numpy as np
import astropy.units as u
from dataclasses import dataclass
from abc import ABC, abstractmethod
import sys
if (sys.version_info[0]+sys.version_info[1]/10.) < 3.8:
from backports.cached_property import cached_property
else:
from functools import cached_property
from lvmdatasimulator import ROOT_DIR
@dataclass
class WaveCoord(ABC):
"""
Abstract class describing the main properties of a WaveCoord object
"""
@abstractmethod
def wave(self):
"""Build the wavelength axis"""
pass
@abstractmethod
def start(self):
""" get the starting wavelength """
pass
@abstractmethod
def end(self):
""" Get the end wavelength"""
pass
@abstractmethod
def step(self):
""" Get the step """
pass
@abstractmethod
def npix(self):
""" Get the step """
pass
@dataclass
class LinearWave(WaveCoord):
""" Linear wavelength axis, most for preliminary tests purposes """
@cached_property
def wave(self):
filename = f'{ROOT_DIR}/data/instrument/linear_wave.dat'
data = np.genfromtxt(filename, skip_header=1, unpack=True)
return np.arange(data[0], data[1] + data[2], data[2]) * u.AA
@cached_property
def start(self):
return self.wave[0]
@cached_property
def end(self):
return self.wave[-1]
@cached_property
def step(self):
delta = self.wave[1: -1] - self.wave[0: -2]
return delta.mean() / u.pix
@cached_property
def npix(self):
return len(self.wave)
@dataclass
class BlueWave(WaveCoord):
""" Wavelength axis of the blue spectrograph """
@cached_property
def wave(self):
pass
@cached_property
def start(self):
pass
@cached_property
def end(self):
pass
@cached_property
def step(self):
pass
@cached_property
def npix(self):
return len(self.wave)
@dataclass
class RedWave(WaveCoord):
""" wavelength axis of the red spectrograph """
@cached_property
def wave(self):
pass
@cached_property
def start(self):
pass
@cached_property
def end(self):
pass
@cached_property
def step(self):
pass
@cached_property
def npix(self):
return len(self.wave)
@dataclass
class IRWave(WaveCoord):
""" wavelength axis of the IR spectrograph """
@cached_property
def wave(self):
pass
@cached_property
def start(self):
pass
@cached_property
def end(self):
pass
@cached_property
def step(self):
pass
@cached_property
def npix(self):
return len(self.wave)
| 18.26875
| 71
| 0.618543
| 354
| 2,923
| 5.025424
| 0.285311
| 0.181001
| 0.191119
| 0.148398
| 0.45756
| 0.333895
| 0.333895
| 0.333895
| 0.333895
| 0.333895
| 0
| 0.011905
| 0.28156
| 2,923
| 159
| 72
| 18.383648
| 0.835238
| 0.175163
| 0
| 0.77551
| 0
| 0
| 0.017987
| 0.017987
| 0
| 0
| 0
| 0
| 0
| 1
| 0.255102
| false
| 0.173469
| 0.081633
| 0.061224
| 0.469388
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
53ffdca66e9b9bb80a45fd070ef4a0a79e14cc60
| 449
|
py
|
Python
|
tests/mock_input_provider.py
|
wllmsash/yget
|
cb3828c62afc00655d8a3e72987c6c563c437580
|
[
"MIT"
] | null | null | null |
tests/mock_input_provider.py
|
wllmsash/yget
|
cb3828c62afc00655d8a3e72987c6c563c437580
|
[
"MIT"
] | null | null | null |
tests/mock_input_provider.py
|
wllmsash/yget
|
cb3828c62afc00655d8a3e72987c6c563c437580
|
[
"MIT"
] | null | null | null |
from yget.input_provider import InputProvider
class MockInputProvider(InputProvider):
def __init__(self, input_delegate, password_delegate):
super(MockInputProvider, self).__init__()
self.input_delegate = input_delegate
self.password_delegate = password_delegate
def get_input(self, label):
return self.input_delegate(label)
def get_password(self, label):
return self.password_delegate(label)
| 29.933333
| 58
| 0.739421
| 50
| 449
| 6.26
| 0.34
| 0.166134
| 0.162939
| 0.134185
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.187082
| 449
| 14
| 59
| 32.071429
| 0.857534
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0.4
| 0.1
| 0.2
| 0.7
| 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
|
54d63f6db8f4103d4ed1c7c6a8665715371b458c
| 114
|
py
|
Python
|
python/lvmnps/switch/exceptions.py
|
treetopper/lvmnps
|
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
|
[
"BSD-3-Clause"
] | null | null | null |
python/lvmnps/switch/exceptions.py
|
treetopper/lvmnps
|
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
|
[
"BSD-3-Clause"
] | null | null | null |
python/lvmnps/switch/exceptions.py
|
treetopper/lvmnps
|
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
|
[
"BSD-3-Clause"
] | null | null | null |
class PowerException(Exception):
"""
An error occurred talking the the DLI Power switch
"""
pass
| 16.285714
| 54
| 0.649123
| 13
| 114
| 5.692308
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.27193
| 114
| 6
| 55
| 19
| 0.891566
| 0.438596
| 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
|
07145334e4282e48797ab4b53e715d2c4c9fbae0
| 401
|
py
|
Python
|
datatype_tools/lib/List.py
|
edmundpf/datatype_tools
|
903094fe3aa76cf6714a8f2e53d24afcca244a39
|
[
"MIT"
] | null | null | null |
datatype_tools/lib/List.py
|
edmundpf/datatype_tools
|
903094fe3aa76cf6714a8f2e53d24afcca244a39
|
[
"MIT"
] | null | null | null |
datatype_tools/lib/List.py
|
edmundpf/datatype_tools
|
903094fe3aa76cf6714a8f2e53d24afcca244a39
|
[
"MIT"
] | null | null | null |
from forbiddenfruit import curse
from datatype_tools.utils.type_functions import (list_sort_by_val,
list_sort_by_key, list_sort_by_key_val,
list_nested_sort_by_val)
#: List Curses
curse(list, 'sort_by_val', list_sort_by_val)
curse(list, 'sort_by_key', list_sort_by_key)
curse(list, 'sort_by_key_val', list_sort_by_key_val)
curse(list, 'nested_sort', list_nested_sort_by_val)
#::: END PROGRAM :::
| 28.642857
| 66
| 0.812968
| 71
| 401
| 4.056338
| 0.253521
| 0.229167
| 0.3125
| 0.270833
| 0.59375
| 0.399306
| 0.305556
| 0.180556
| 0
| 0
| 0
| 0
| 0.087282
| 401
| 13
| 67
| 30.846154
| 0.786885
| 0.079801
| 0
| 0
| 0
| 0
| 0.13079
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0717cbfa412a283a310e6a75bc6fea33accac60c
| 49
|
py
|
Python
|
ptdt/__init__.py
|
tanimutomo/ptdt
|
ab3a48a39871729ac4485a9aba843670ae6a4edc
|
[
"MIT"
] | null | null | null |
ptdt/__init__.py
|
tanimutomo/ptdt
|
ab3a48a39871729ac4485a9aba843670ae6a4edc
|
[
"MIT"
] | null | null | null |
ptdt/__init__.py
|
tanimutomo/ptdt
|
ab3a48a39871729ac4485a9aba843670ae6a4edc
|
[
"MIT"
] | null | null | null |
from ptdt.ptdt import (
image,
tensor,
)
| 9.8
| 23
| 0.591837
| 6
| 49
| 4.833333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.306122
| 49
| 4
| 24
| 12.25
| 0.852941
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 0
| 0.25
| 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
|
071bea025cb6690d37513a4ae985c93d91b78af7
| 209
|
py
|
Python
|
mods/mcpython/Item/Grass.py
|
uuk0/mcpython-a-minecraft-clone-in-python
|
c16cd66f319efdeec4130e1a43f5a857caf1ea13
|
[
"MIT"
] | 2
|
2020-04-23T16:25:51.000Z
|
2020-08-27T17:56:16.000Z
|
mods/mcpython/Item/Grass.py
|
uuk0/mcpython-a-minecraft-clone-in-python
|
c16cd66f319efdeec4130e1a43f5a857caf1ea13
|
[
"MIT"
] | null | null | null |
mods/mcpython/Item/Grass.py
|
uuk0/mcpython-a-minecraft-clone-in-python
|
c16cd66f319efdeec4130e1a43f5a857caf1ea13
|
[
"MIT"
] | null | null | null |
from .Item import *
class Grass(Item):
def getName(self):
return "minecraft:grass"
def getTexturFile(self):
return "./assets/textures/items/grass_item.png"
handler.register(Grass)
| 16.076923
| 55
| 0.669856
| 25
| 209
| 5.56
| 0.68
| 0.129496
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 209
| 12
| 56
| 17.416667
| 0.842424
| 0
| 0
| 0
| 0
| 0
| 0.253589
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0.285714
| 0.857143
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
0722310c97d54251c5976b5219db35faf74a7bc8
| 232
|
py
|
Python
|
project_name/urls.py
|
codyparker/django-project-template-cp
|
4f4d0bcae827c11b0676cc79615948920b435d4e
|
[
"MIT"
] | null | null | null |
project_name/urls.py
|
codyparker/django-project-template-cp
|
4f4d0bcae827c11b0676cc79615948920b435d4e
|
[
"MIT"
] | null | null | null |
project_name/urls.py
|
codyparker/django-project-template-cp
|
4f4d0bcae827c11b0676cc79615948920b435d4e
|
[
"MIT"
] | null | null | null |
from django.conf.urls import url
from django.contrib import admin
from django.contrib.staticfiles.urls import staticfiles_urlpatterns
urlpatterns = [
url(r'^admin/', admin.site.urls),
]
urlpatterns += staticfiles_urlpatterns()
| 25.777778
| 67
| 0.788793
| 29
| 232
| 6.241379
| 0.413793
| 0.165746
| 0.187845
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112069
| 232
| 9
| 68
| 25.777778
| 0.878641
| 0
| 0
| 0
| 0
| 0
| 0.030043
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.428571
| 0
| 0.428571
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
07334babd4baa88cf28456f7c7b7083c252ad074
| 95
|
py
|
Python
|
spa/singlepage/apps.py
|
shrinks25002/Harvard-CS50
|
a27cd57d5dde7a06d9127fbf278b536fa8d90df0
|
[
"MIT"
] | 2
|
2021-04-05T15:29:08.000Z
|
2022-03-08T11:07:21.000Z
|
Lecture 6 : User Interfaces/src6/singlepage2/singlepage/apps.py
|
Sumanth-Talluri/CS50-Web-Programming-with-Python-and-JavaScript
|
8d5f83f4354f1f27138a2a9c40317d358f3b2f9a
|
[
"MIT"
] | null | null | null |
Lecture 6 : User Interfaces/src6/singlepage2/singlepage/apps.py
|
Sumanth-Talluri/CS50-Web-Programming-with-Python-and-JavaScript
|
8d5f83f4354f1f27138a2a9c40317d358f3b2f9a
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class SinglepageConfig(AppConfig):
name = 'singlepage'
| 15.833333
| 34
| 0.768421
| 10
| 95
| 7.3
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 95
| 5
| 35
| 19
| 0.9125
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
07464d7d9f68e728acc2d4b00825b5b3379b78cb
| 59,946
|
py
|
Python
|
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
|
NateLehman/azure-sdk-for-python
|
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
|
[
"MIT"
] | 1
|
2022-03-09T08:59:13.000Z
|
2022-03-09T08:59:13.000Z
|
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
|
NateLehman/azure-sdk-for-python
|
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
|
[
"MIT"
] | null | null | null |
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
|
NateLehman/azure-sdk-for-python
|
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
|
[
"MIT"
] | null | null | null |
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from ._models_py3 import AccessPolicyResponse
from ._models_py3 import Activity
from ._models_py3 import ActivityDependency
from ._models_py3 import ActivityPolicy
from ._models_py3 import ActivityRun
from ._models_py3 import ActivityRunsQueryResponse
from ._models_py3 import AddDataFlowToDebugSessionResponse
from ._models_py3 import AdditionalColumns
from ._models_py3 import AmazonMWSLinkedService
from ._models_py3 import AmazonMWSObjectDataset
from ._models_py3 import AmazonMWSSource
from ._models_py3 import AmazonRdsForOracleLinkedService
from ._models_py3 import AmazonRdsForOraclePartitionSettings
from ._models_py3 import AmazonRdsForOracleSource
from ._models_py3 import AmazonRdsForOracleTableDataset
from ._models_py3 import AmazonRdsForSqlServerLinkedService
from ._models_py3 import AmazonRdsForSqlServerSource
from ._models_py3 import AmazonRdsForSqlServerTableDataset
from ._models_py3 import AmazonRedshiftLinkedService
from ._models_py3 import AmazonRedshiftSource
from ._models_py3 import AmazonRedshiftTableDataset
from ._models_py3 import AmazonS3CompatibleLinkedService
from ._models_py3 import AmazonS3CompatibleLocation
from ._models_py3 import AmazonS3CompatibleReadSettings
from ._models_py3 import AmazonS3Dataset
from ._models_py3 import AmazonS3LinkedService
from ._models_py3 import AmazonS3Location
from ._models_py3 import AmazonS3ReadSettings
from ._models_py3 import AppendVariableActivity
from ._models_py3 import ArmIdWrapper
from ._models_py3 import AvroDataset
from ._models_py3 import AvroFormat
from ._models_py3 import AvroSink
from ._models_py3 import AvroSource
from ._models_py3 import AvroWriteSettings
from ._models_py3 import AzPowerShellSetup
from ._models_py3 import AzureBatchLinkedService
from ._models_py3 import AzureBlobDataset
from ._models_py3 import AzureBlobFSDataset
from ._models_py3 import AzureBlobFSLinkedService
from ._models_py3 import AzureBlobFSLocation
from ._models_py3 import AzureBlobFSReadSettings
from ._models_py3 import AzureBlobFSSink
from ._models_py3 import AzureBlobFSSource
from ._models_py3 import AzureBlobFSWriteSettings
from ._models_py3 import AzureBlobStorageLinkedService
from ._models_py3 import AzureBlobStorageLocation
from ._models_py3 import AzureBlobStorageReadSettings
from ._models_py3 import AzureBlobStorageWriteSettings
from ._models_py3 import AzureDataExplorerCommandActivity
from ._models_py3 import AzureDataExplorerLinkedService
from ._models_py3 import AzureDataExplorerSink
from ._models_py3 import AzureDataExplorerSource
from ._models_py3 import AzureDataExplorerTableDataset
from ._models_py3 import AzureDataLakeAnalyticsLinkedService
from ._models_py3 import AzureDataLakeStoreDataset
from ._models_py3 import AzureDataLakeStoreLinkedService
from ._models_py3 import AzureDataLakeStoreLocation
from ._models_py3 import AzureDataLakeStoreReadSettings
from ._models_py3 import AzureDataLakeStoreSink
from ._models_py3 import AzureDataLakeStoreSource
from ._models_py3 import AzureDataLakeStoreWriteSettings
from ._models_py3 import AzureDatabricksDeltaLakeDataset
from ._models_py3 import AzureDatabricksDeltaLakeExportCommand
from ._models_py3 import AzureDatabricksDeltaLakeImportCommand
from ._models_py3 import AzureDatabricksDeltaLakeLinkedService
from ._models_py3 import AzureDatabricksDeltaLakeSink
from ._models_py3 import AzureDatabricksDeltaLakeSource
from ._models_py3 import AzureDatabricksLinkedService
from ._models_py3 import AzureFileStorageLinkedService
from ._models_py3 import AzureFileStorageLocation
from ._models_py3 import AzureFileStorageReadSettings
from ._models_py3 import AzureFileStorageWriteSettings
from ._models_py3 import AzureFunctionActivity
from ._models_py3 import AzureFunctionLinkedService
from ._models_py3 import AzureKeyVaultLinkedService
from ._models_py3 import AzureKeyVaultSecretReference
from ._models_py3 import AzureMLBatchExecutionActivity
from ._models_py3 import AzureMLExecutePipelineActivity
from ._models_py3 import AzureMLLinkedService
from ._models_py3 import AzureMLServiceLinkedService
from ._models_py3 import AzureMLUpdateResourceActivity
from ._models_py3 import AzureMLWebServiceFile
from ._models_py3 import AzureMariaDBLinkedService
from ._models_py3 import AzureMariaDBSource
from ._models_py3 import AzureMariaDBTableDataset
from ._models_py3 import AzureMySqlLinkedService
from ._models_py3 import AzureMySqlSink
from ._models_py3 import AzureMySqlSource
from ._models_py3 import AzureMySqlTableDataset
from ._models_py3 import AzurePostgreSqlLinkedService
from ._models_py3 import AzurePostgreSqlSink
from ._models_py3 import AzurePostgreSqlSource
from ._models_py3 import AzurePostgreSqlTableDataset
from ._models_py3 import AzureQueueSink
from ._models_py3 import AzureSearchIndexDataset
from ._models_py3 import AzureSearchIndexSink
from ._models_py3 import AzureSearchLinkedService
from ._models_py3 import AzureSqlDWLinkedService
from ._models_py3 import AzureSqlDWTableDataset
from ._models_py3 import AzureSqlDatabaseLinkedService
from ._models_py3 import AzureSqlMILinkedService
from ._models_py3 import AzureSqlMITableDataset
from ._models_py3 import AzureSqlSink
from ._models_py3 import AzureSqlSource
from ._models_py3 import AzureSqlTableDataset
from ._models_py3 import AzureStorageLinkedService
from ._models_py3 import AzureTableDataset
from ._models_py3 import AzureTableSink
from ._models_py3 import AzureTableSource
from ._models_py3 import AzureTableStorageLinkedService
from ._models_py3 import BinaryDataset
from ._models_py3 import BinaryReadSettings
from ._models_py3 import BinarySink
from ._models_py3 import BinarySource
from ._models_py3 import BlobEventsTrigger
from ._models_py3 import BlobSink
from ._models_py3 import BlobSource
from ._models_py3 import BlobTrigger
from ._models_py3 import CMKIdentityDefinition
from ._models_py3 import CassandraLinkedService
from ._models_py3 import CassandraSource
from ._models_py3 import CassandraTableDataset
from ._models_py3 import ChainingTrigger
from ._models_py3 import CloudError
from ._models_py3 import CmdkeySetup
from ._models_py3 import CommonDataServiceForAppsEntityDataset
from ._models_py3 import CommonDataServiceForAppsLinkedService
from ._models_py3 import CommonDataServiceForAppsSink
from ._models_py3 import CommonDataServiceForAppsSource
from ._models_py3 import ComponentSetup
from ._models_py3 import CompressionReadSettings
from ._models_py3 import ConcurLinkedService
from ._models_py3 import ConcurObjectDataset
from ._models_py3 import ConcurSource
from ._models_py3 import ConnectionStateProperties
from ._models_py3 import ControlActivity
from ._models_py3 import CopyActivity
from ._models_py3 import CopyActivityLogSettings
from ._models_py3 import CopySink
from ._models_py3 import CopySource
from ._models_py3 import CopyTranslator
from ._models_py3 import CosmosDbLinkedService
from ._models_py3 import CosmosDbMongoDbApiCollectionDataset
from ._models_py3 import CosmosDbMongoDbApiLinkedService
from ._models_py3 import CosmosDbMongoDbApiSink
from ._models_py3 import CosmosDbMongoDbApiSource
from ._models_py3 import CosmosDbSqlApiCollectionDataset
from ._models_py3 import CosmosDbSqlApiSink
from ._models_py3 import CosmosDbSqlApiSource
from ._models_py3 import CouchbaseLinkedService
from ._models_py3 import CouchbaseSource
from ._models_py3 import CouchbaseTableDataset
from ._models_py3 import CreateDataFlowDebugSessionRequest
from ._models_py3 import CreateDataFlowDebugSessionResponse
from ._models_py3 import CreateLinkedIntegrationRuntimeRequest
from ._models_py3 import CreateRunResponse
from ._models_py3 import Credential
from ._models_py3 import CredentialReference
from ._models_py3 import CredentialResource
from ._models_py3 import CustomActivity
from ._models_py3 import CustomActivityReferenceObject
from ._models_py3 import CustomDataSourceLinkedService
from ._models_py3 import CustomDataset
from ._models_py3 import CustomEventsTrigger
from ._models_py3 import CustomSetupBase
from ._models_py3 import DWCopyCommandDefaultValue
from ._models_py3 import DWCopyCommandSettings
from ._models_py3 import DataFlow
from ._models_py3 import DataFlowDebugCommandPayload
from ._models_py3 import DataFlowDebugCommandRequest
from ._models_py3 import DataFlowDebugCommandResponse
from ._models_py3 import DataFlowDebugPackage
from ._models_py3 import DataFlowDebugPackageDebugSettings
from ._models_py3 import DataFlowDebugResource
from ._models_py3 import DataFlowDebugSessionInfo
from ._models_py3 import DataFlowFolder
from ._models_py3 import DataFlowListResponse
from ._models_py3 import DataFlowReference
from ._models_py3 import DataFlowResource
from ._models_py3 import DataFlowSink
from ._models_py3 import DataFlowSource
from ._models_py3 import DataFlowSourceSetting
from ._models_py3 import DataFlowStagingInfo
from ._models_py3 import DataLakeAnalyticsUSQLActivity
from ._models_py3 import DatabricksNotebookActivity
from ._models_py3 import DatabricksSparkJarActivity
from ._models_py3 import DatabricksSparkPythonActivity
from ._models_py3 import Dataset
from ._models_py3 import DatasetCompression
from ._models_py3 import DatasetDataElement
from ._models_py3 import DatasetDebugResource
from ._models_py3 import DatasetFolder
from ._models_py3 import DatasetListResponse
from ._models_py3 import DatasetLocation
from ._models_py3 import DatasetReference
from ._models_py3 import DatasetResource
from ._models_py3 import DatasetSchemaDataElement
from ._models_py3 import DatasetStorageFormat
from ._models_py3 import Db2LinkedService
from ._models_py3 import Db2Source
from ._models_py3 import Db2TableDataset
from ._models_py3 import DeleteActivity
from ._models_py3 import DeleteDataFlowDebugSessionRequest
from ._models_py3 import DelimitedTextDataset
from ._models_py3 import DelimitedTextReadSettings
from ._models_py3 import DelimitedTextSink
from ._models_py3 import DelimitedTextSource
from ._models_py3 import DelimitedTextWriteSettings
from ._models_py3 import DependencyReference
from ._models_py3 import DistcpSettings
from ._models_py3 import DocumentDbCollectionDataset
from ._models_py3 import DocumentDbCollectionSink
from ._models_py3 import DocumentDbCollectionSource
from ._models_py3 import DrillLinkedService
from ._models_py3 import DrillSource
from ._models_py3 import DrillTableDataset
from ._models_py3 import DynamicsAXLinkedService
from ._models_py3 import DynamicsAXResourceDataset
from ._models_py3 import DynamicsAXSource
from ._models_py3 import DynamicsCrmEntityDataset
from ._models_py3 import DynamicsCrmLinkedService
from ._models_py3 import DynamicsCrmSink
from ._models_py3 import DynamicsCrmSource
from ._models_py3 import DynamicsEntityDataset
from ._models_py3 import DynamicsLinkedService
from ._models_py3 import DynamicsSink
from ._models_py3 import DynamicsSource
from ._models_py3 import EloquaLinkedService
from ._models_py3 import EloquaObjectDataset
from ._models_py3 import EloquaSource
from ._models_py3 import EncryptionConfiguration
from ._models_py3 import EntityReference
from ._models_py3 import EnvironmentVariableSetup
from ._models_py3 import ExcelDataset
from ._models_py3 import ExcelSource
from ._models_py3 import ExecuteDataFlowActivity
from ._models_py3 import ExecuteDataFlowActivityTypeProperties
from ._models_py3 import ExecuteDataFlowActivityTypePropertiesCompute
from ._models_py3 import ExecutePipelineActivity
from ._models_py3 import ExecutePowerQueryActivityTypeProperties
from ._models_py3 import ExecuteSSISPackageActivity
from ._models_py3 import ExecuteWranglingDataflowActivity
from ._models_py3 import ExecutionActivity
from ._models_py3 import ExportSettings
from ._models_py3 import ExposureControlBatchRequest
from ._models_py3 import ExposureControlBatchResponse
from ._models_py3 import ExposureControlRequest
from ._models_py3 import ExposureControlResponse
from ._models_py3 import Expression
from ._models_py3 import Factory
from ._models_py3 import FactoryGitHubConfiguration
from ._models_py3 import FactoryIdentity
from ._models_py3 import FactoryListResponse
from ._models_py3 import FactoryRepoConfiguration
from ._models_py3 import FactoryRepoUpdate
from ._models_py3 import FactoryUpdateParameters
from ._models_py3 import FactoryVSTSConfiguration
from ._models_py3 import FailActivity
from ._models_py3 import FileServerLinkedService
from ._models_py3 import FileServerLocation
from ._models_py3 import FileServerReadSettings
from ._models_py3 import FileServerWriteSettings
from ._models_py3 import FileShareDataset
from ._models_py3 import FileSystemSink
from ._models_py3 import FileSystemSource
from ._models_py3 import FilterActivity
from ._models_py3 import Flowlet
from ._models_py3 import ForEachActivity
from ._models_py3 import FormatReadSettings
from ._models_py3 import FormatWriteSettings
from ._models_py3 import FtpReadSettings
from ._models_py3 import FtpServerLinkedService
from ._models_py3 import FtpServerLocation
from ._models_py3 import GetDataFactoryOperationStatusResponse
from ._models_py3 import GetMetadataActivity
from ._models_py3 import GetSsisObjectMetadataRequest
from ._models_py3 import GitHubAccessTokenRequest
from ._models_py3 import GitHubAccessTokenResponse
from ._models_py3 import GitHubClientSecret
from ._models_py3 import GlobalParameterSpecification
from ._models_py3 import GoogleAdWordsLinkedService
from ._models_py3 import GoogleAdWordsObjectDataset
from ._models_py3 import GoogleAdWordsSource
from ._models_py3 import GoogleBigQueryLinkedService
from ._models_py3 import GoogleBigQueryObjectDataset
from ._models_py3 import GoogleBigQuerySource
from ._models_py3 import GoogleCloudStorageLinkedService
from ._models_py3 import GoogleCloudStorageLocation
from ._models_py3 import GoogleCloudStorageReadSettings
from ._models_py3 import GreenplumLinkedService
from ._models_py3 import GreenplumSource
from ._models_py3 import GreenplumTableDataset
from ._models_py3 import HBaseLinkedService
from ._models_py3 import HBaseObjectDataset
from ._models_py3 import HBaseSource
from ._models_py3 import HDInsightHiveActivity
from ._models_py3 import HDInsightLinkedService
from ._models_py3 import HDInsightMapReduceActivity
from ._models_py3 import HDInsightOnDemandLinkedService
from ._models_py3 import HDInsightPigActivity
from ._models_py3 import HDInsightSparkActivity
from ._models_py3 import HDInsightStreamingActivity
from ._models_py3 import HdfsLinkedService
from ._models_py3 import HdfsLocation
from ._models_py3 import HdfsReadSettings
from ._models_py3 import HdfsSource
from ._models_py3 import HiveLinkedService
from ._models_py3 import HiveObjectDataset
from ._models_py3 import HiveSource
from ._models_py3 import HttpDataset
from ._models_py3 import HttpLinkedService
from ._models_py3 import HttpReadSettings
from ._models_py3 import HttpServerLocation
from ._models_py3 import HttpSource
from ._models_py3 import HubspotLinkedService
from ._models_py3 import HubspotObjectDataset
from ._models_py3 import HubspotSource
from ._models_py3 import IfConditionActivity
from ._models_py3 import ImpalaLinkedService
from ._models_py3 import ImpalaObjectDataset
from ._models_py3 import ImpalaSource
from ._models_py3 import ImportSettings
from ._models_py3 import InformixLinkedService
from ._models_py3 import InformixSink
from ._models_py3 import InformixSource
from ._models_py3 import InformixTableDataset
from ._models_py3 import IntegrationRuntime
from ._models_py3 import IntegrationRuntimeAuthKeys
from ._models_py3 import IntegrationRuntimeComputeProperties
from ._models_py3 import IntegrationRuntimeConnectionInfo
from ._models_py3 import IntegrationRuntimeCustomSetupScriptProperties
from ._models_py3 import IntegrationRuntimeCustomerVirtualNetwork
from ._models_py3 import IntegrationRuntimeDataFlowProperties
from ._models_py3 import IntegrationRuntimeDataProxyProperties
from ._models_py3 import IntegrationRuntimeDebugResource
from ._models_py3 import IntegrationRuntimeListResponse
from ._models_py3 import IntegrationRuntimeMonitoringData
from ._models_py3 import IntegrationRuntimeNodeIpAddress
from ._models_py3 import IntegrationRuntimeNodeMonitoringData
from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesCategoryEndpoint
from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpoint
from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpointDetails
from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpointsResponse
from ._models_py3 import IntegrationRuntimeReference
from ._models_py3 import IntegrationRuntimeRegenerateKeyParameters
from ._models_py3 import IntegrationRuntimeResource
from ._models_py3 import IntegrationRuntimeSsisCatalogInfo
from ._models_py3 import IntegrationRuntimeSsisProperties
from ._models_py3 import IntegrationRuntimeStatus
from ._models_py3 import IntegrationRuntimeStatusListResponse
from ._models_py3 import IntegrationRuntimeStatusResponse
from ._models_py3 import IntegrationRuntimeVNetProperties
from ._models_py3 import JiraLinkedService
from ._models_py3 import JiraObjectDataset
from ._models_py3 import JiraSource
from ._models_py3 import JsonDataset
from ._models_py3 import JsonFormat
from ._models_py3 import JsonReadSettings
from ._models_py3 import JsonSink
from ._models_py3 import JsonSource
from ._models_py3 import JsonWriteSettings
from ._models_py3 import LinkedIntegrationRuntime
from ._models_py3 import LinkedIntegrationRuntimeKeyAuthorization
from ._models_py3 import LinkedIntegrationRuntimeRbacAuthorization
from ._models_py3 import LinkedIntegrationRuntimeRequest
from ._models_py3 import LinkedIntegrationRuntimeType
from ._models_py3 import LinkedService
from ._models_py3 import LinkedServiceDebugResource
from ._models_py3 import LinkedServiceListResponse
from ._models_py3 import LinkedServiceReference
from ._models_py3 import LinkedServiceResource
from ._models_py3 import LogLocationSettings
from ._models_py3 import LogSettings
from ._models_py3 import LogStorageSettings
from ._models_py3 import LookupActivity
from ._models_py3 import MagentoLinkedService
from ._models_py3 import MagentoObjectDataset
from ._models_py3 import MagentoSource
from ._models_py3 import ManagedIdentityCredential
from ._models_py3 import ManagedIntegrationRuntime
from ._models_py3 import ManagedIntegrationRuntimeError
from ._models_py3 import ManagedIntegrationRuntimeNode
from ._models_py3 import ManagedIntegrationRuntimeOperationResult
from ._models_py3 import ManagedIntegrationRuntimeStatus
from ._models_py3 import ManagedPrivateEndpoint
from ._models_py3 import ManagedPrivateEndpointListResponse
from ._models_py3 import ManagedPrivateEndpointResource
from ._models_py3 import ManagedVirtualNetwork
from ._models_py3 import ManagedVirtualNetworkListResponse
from ._models_py3 import ManagedVirtualNetworkReference
from ._models_py3 import ManagedVirtualNetworkResource
from ._models_py3 import MappingDataFlow
from ._models_py3 import MariaDBLinkedService
from ._models_py3 import MariaDBSource
from ._models_py3 import MariaDBTableDataset
from ._models_py3 import MarketoLinkedService
from ._models_py3 import MarketoObjectDataset
from ._models_py3 import MarketoSource
from ._models_py3 import MetadataItem
from ._models_py3 import MicrosoftAccessLinkedService
from ._models_py3 import MicrosoftAccessSink
from ._models_py3 import MicrosoftAccessSource
from ._models_py3 import MicrosoftAccessTableDataset
from ._models_py3 import MongoDbAtlasCollectionDataset
from ._models_py3 import MongoDbAtlasLinkedService
from ._models_py3 import MongoDbAtlasSink
from ._models_py3 import MongoDbAtlasSource
from ._models_py3 import MongoDbCollectionDataset
from ._models_py3 import MongoDbCursorMethodsProperties
from ._models_py3 import MongoDbLinkedService
from ._models_py3 import MongoDbSource
from ._models_py3 import MongoDbV2CollectionDataset
from ._models_py3 import MongoDbV2LinkedService
from ._models_py3 import MongoDbV2Sink
from ._models_py3 import MongoDbV2Source
from ._models_py3 import MultiplePipelineTrigger
from ._models_py3 import MySqlLinkedService
from ._models_py3 import MySqlSource
from ._models_py3 import MySqlTableDataset
from ._models_py3 import NetezzaLinkedService
from ._models_py3 import NetezzaPartitionSettings
from ._models_py3 import NetezzaSource
from ._models_py3 import NetezzaTableDataset
from ._models_py3 import ODataLinkedService
from ._models_py3 import ODataResourceDataset
from ._models_py3 import ODataSource
from ._models_py3 import OdbcLinkedService
from ._models_py3 import OdbcSink
from ._models_py3 import OdbcSource
from ._models_py3 import OdbcTableDataset
from ._models_py3 import Office365Dataset
from ._models_py3 import Office365LinkedService
from ._models_py3 import Office365Source
from ._models_py3 import Operation
from ._models_py3 import OperationDisplay
from ._models_py3 import OperationListResponse
from ._models_py3 import OperationLogSpecification
from ._models_py3 import OperationMetricAvailability
from ._models_py3 import OperationMetricDimension
from ._models_py3 import OperationMetricSpecification
from ._models_py3 import OperationServiceSpecification
from ._models_py3 import OracleCloudStorageLinkedService
from ._models_py3 import OracleCloudStorageLocation
from ._models_py3 import OracleCloudStorageReadSettings
from ._models_py3 import OracleLinkedService
from ._models_py3 import OraclePartitionSettings
from ._models_py3 import OracleServiceCloudLinkedService
from ._models_py3 import OracleServiceCloudObjectDataset
from ._models_py3 import OracleServiceCloudSource
from ._models_py3 import OracleSink
from ._models_py3 import OracleSource
from ._models_py3 import OracleTableDataset
from ._models_py3 import OrcDataset
from ._models_py3 import OrcFormat
from ._models_py3 import OrcSink
from ._models_py3 import OrcSource
from ._models_py3 import OrcWriteSettings
from ._models_py3 import PackageStore
from ._models_py3 import ParameterSpecification
from ._models_py3 import ParquetDataset
from ._models_py3 import ParquetFormat
from ._models_py3 import ParquetSink
from ._models_py3 import ParquetSource
from ._models_py3 import ParquetWriteSettings
from ._models_py3 import PaypalLinkedService
from ._models_py3 import PaypalObjectDataset
from ._models_py3 import PaypalSource
from ._models_py3 import PhoenixLinkedService
from ._models_py3 import PhoenixObjectDataset
from ._models_py3 import PhoenixSource
from ._models_py3 import PipelineElapsedTimeMetricPolicy
from ._models_py3 import PipelineFolder
from ._models_py3 import PipelineListResponse
from ._models_py3 import PipelinePolicy
from ._models_py3 import PipelineReference
from ._models_py3 import PipelineResource
from ._models_py3 import PipelineRun
from ._models_py3 import PipelineRunInvokedBy
from ._models_py3 import PipelineRunsQueryResponse
from ._models_py3 import PolybaseSettings
from ._models_py3 import PostgreSqlLinkedService
from ._models_py3 import PostgreSqlSource
from ._models_py3 import PostgreSqlTableDataset
from ._models_py3 import PowerQuerySink
from ._models_py3 import PowerQuerySinkMapping
from ._models_py3 import PowerQuerySource
from ._models_py3 import PrestoLinkedService
from ._models_py3 import PrestoObjectDataset
from ._models_py3 import PrestoSource
from ._models_py3 import PrivateEndpointConnectionListResponse
from ._models_py3 import PrivateEndpointConnectionResource
from ._models_py3 import PrivateLinkConnectionApprovalRequest
from ._models_py3 import PrivateLinkConnectionApprovalRequestResource
from ._models_py3 import PrivateLinkConnectionState
from ._models_py3 import PrivateLinkResource
from ._models_py3 import PrivateLinkResourceProperties
from ._models_py3 import PrivateLinkResourcesWrapper
from ._models_py3 import QueryDataFlowDebugSessionsResponse
from ._models_py3 import QuickBooksLinkedService
from ._models_py3 import QuickBooksObjectDataset
from ._models_py3 import QuickBooksSource
from ._models_py3 import QuickbaseLinkedService
from ._models_py3 import RecurrenceSchedule
from ._models_py3 import RecurrenceScheduleOccurrence
from ._models_py3 import RedirectIncompatibleRowSettings
from ._models_py3 import RedshiftUnloadSettings
from ._models_py3 import RelationalSource
from ._models_py3 import RelationalTableDataset
from ._models_py3 import RemotePrivateEndpointConnection
from ._models_py3 import RerunTumblingWindowTrigger
from ._models_py3 import Resource
from ._models_py3 import ResponsysLinkedService
from ._models_py3 import ResponsysObjectDataset
from ._models_py3 import ResponsysSource
from ._models_py3 import RestResourceDataset
from ._models_py3 import RestServiceLinkedService
from ._models_py3 import RestSink
from ._models_py3 import RestSource
from ._models_py3 import RetryPolicy
from ._models_py3 import RunFilterParameters
from ._models_py3 import RunQueryFilter
from ._models_py3 import RunQueryOrderBy
from ._models_py3 import SSISAccessCredential
from ._models_py3 import SSISChildPackage
from ._models_py3 import SSISExecutionCredential
from ._models_py3 import SSISExecutionParameter
from ._models_py3 import SSISLogLocation
from ._models_py3 import SSISPackageLocation
from ._models_py3 import SSISPropertyOverride
from ._models_py3 import SalesforceLinkedService
from ._models_py3 import SalesforceMarketingCloudLinkedService
from ._models_py3 import SalesforceMarketingCloudObjectDataset
from ._models_py3 import SalesforceMarketingCloudSource
from ._models_py3 import SalesforceObjectDataset
from ._models_py3 import SalesforceServiceCloudLinkedService
from ._models_py3 import SalesforceServiceCloudObjectDataset
from ._models_py3 import SalesforceServiceCloudSink
from ._models_py3 import SalesforceServiceCloudSource
from ._models_py3 import SalesforceSink
from ._models_py3 import SalesforceSource
from ._models_py3 import SapBWLinkedService
from ._models_py3 import SapBwCubeDataset
from ._models_py3 import SapBwSource
from ._models_py3 import SapCloudForCustomerLinkedService
from ._models_py3 import SapCloudForCustomerResourceDataset
from ._models_py3 import SapCloudForCustomerSink
from ._models_py3 import SapCloudForCustomerSource
from ._models_py3 import SapEccLinkedService
from ._models_py3 import SapEccResourceDataset
from ._models_py3 import SapEccSource
from ._models_py3 import SapHanaLinkedService
from ._models_py3 import SapHanaPartitionSettings
from ._models_py3 import SapHanaSource
from ._models_py3 import SapHanaTableDataset
from ._models_py3 import SapOpenHubLinkedService
from ._models_py3 import SapOpenHubSource
from ._models_py3 import SapOpenHubTableDataset
from ._models_py3 import SapTableLinkedService
from ._models_py3 import SapTablePartitionSettings
from ._models_py3 import SapTableResourceDataset
from ._models_py3 import SapTableSource
from ._models_py3 import ScheduleTrigger
from ._models_py3 import ScheduleTriggerRecurrence
from ._models_py3 import ScriptAction
from ._models_py3 import ScriptActivity
from ._models_py3 import ScriptActivityParameter
from ._models_py3 import ScriptActivityScriptBlock
from ._models_py3 import ScriptActivityTypePropertiesLogSettings
from ._models_py3 import SecretBase
from ._models_py3 import SecureString
from ._models_py3 import SelfDependencyTumblingWindowTriggerReference
from ._models_py3 import SelfHostedIntegrationRuntime
from ._models_py3 import SelfHostedIntegrationRuntimeNode
from ._models_py3 import SelfHostedIntegrationRuntimeStatus
from ._models_py3 import ServiceNowLinkedService
from ._models_py3 import ServiceNowObjectDataset
from ._models_py3 import ServiceNowSource
from ._models_py3 import ServicePrincipalCredential
from ._models_py3 import SetVariableActivity
from ._models_py3 import SftpLocation
from ._models_py3 import SftpReadSettings
from ._models_py3 import SftpServerLinkedService
from ._models_py3 import SftpWriteSettings
from ._models_py3 import SharePointOnlineListLinkedService
from ._models_py3 import SharePointOnlineListResourceDataset
from ._models_py3 import SharePointOnlineListSource
from ._models_py3 import ShopifyLinkedService
from ._models_py3 import ShopifyObjectDataset
from ._models_py3 import ShopifySource
from ._models_py3 import SkipErrorFile
from ._models_py3 import SmartsheetLinkedService
from ._models_py3 import SnowflakeDataset
from ._models_py3 import SnowflakeExportCopyCommand
from ._models_py3 import SnowflakeImportCopyCommand
from ._models_py3 import SnowflakeLinkedService
from ._models_py3 import SnowflakeSink
from ._models_py3 import SnowflakeSource
from ._models_py3 import SparkLinkedService
from ._models_py3 import SparkObjectDataset
from ._models_py3 import SparkSource
from ._models_py3 import SqlAlwaysEncryptedProperties
from ._models_py3 import SqlDWSink
from ._models_py3 import SqlDWSource
from ._models_py3 import SqlDWUpsertSettings
from ._models_py3 import SqlMISink
from ._models_py3 import SqlMISource
from ._models_py3 import SqlPartitionSettings
from ._models_py3 import SqlServerLinkedService
from ._models_py3 import SqlServerSink
from ._models_py3 import SqlServerSource
from ._models_py3 import SqlServerStoredProcedureActivity
from ._models_py3 import SqlServerTableDataset
from ._models_py3 import SqlSink
from ._models_py3 import SqlSource
from ._models_py3 import SqlUpsertSettings
from ._models_py3 import SquareLinkedService
from ._models_py3 import SquareObjectDataset
from ._models_py3 import SquareSource
from ._models_py3 import SsisEnvironment
from ._models_py3 import SsisEnvironmentReference
from ._models_py3 import SsisFolder
from ._models_py3 import SsisObjectMetadata
from ._models_py3 import SsisObjectMetadataListResponse
from ._models_py3 import SsisObjectMetadataStatusResponse
from ._models_py3 import SsisPackage
from ._models_py3 import SsisParameter
from ._models_py3 import SsisProject
from ._models_py3 import SsisVariable
from ._models_py3 import StagingSettings
from ._models_py3 import StoreReadSettings
from ._models_py3 import StoreWriteSettings
from ._models_py3 import StoredProcedureParameter
from ._models_py3 import SubResource
from ._models_py3 import SubResourceDebugResource
from ._models_py3 import SwitchActivity
from ._models_py3 import SwitchCase
from ._models_py3 import SybaseLinkedService
from ._models_py3 import SybaseSource
from ._models_py3 import SybaseTableDataset
from ._models_py3 import TabularSource
from ._models_py3 import TabularTranslator
from ._models_py3 import TarGZipReadSettings
from ._models_py3 import TarReadSettings
from ._models_py3 import TeamDeskLinkedService
from ._models_py3 import TeradataLinkedService
from ._models_py3 import TeradataPartitionSettings
from ._models_py3 import TeradataSource
from ._models_py3 import TeradataTableDataset
from ._models_py3 import TextFormat
from ._models_py3 import Transformation
from ._models_py3 import Trigger
from ._models_py3 import TriggerDependencyReference
from ._models_py3 import TriggerFilterParameters
from ._models_py3 import TriggerListResponse
from ._models_py3 import TriggerPipelineReference
from ._models_py3 import TriggerQueryResponse
from ._models_py3 import TriggerReference
from ._models_py3 import TriggerResource
from ._models_py3 import TriggerRun
from ._models_py3 import TriggerRunsQueryResponse
from ._models_py3 import TriggerSubscriptionOperationStatus
from ._models_py3 import TumblingWindowTrigger
from ._models_py3 import TumblingWindowTriggerDependencyReference
from ._models_py3 import TypeConversionSettings
from ._models_py3 import UntilActivity
from ._models_py3 import UpdateIntegrationRuntimeNodeRequest
from ._models_py3 import UpdateIntegrationRuntimeRequest
from ._models_py3 import UserAccessPolicy
from ._models_py3 import UserProperty
from ._models_py3 import ValidationActivity
from ._models_py3 import VariableSpecification
from ._models_py3 import VerticaLinkedService
from ._models_py3 import VerticaSource
from ._models_py3 import VerticaTableDataset
from ._models_py3 import WaitActivity
from ._models_py3 import WebActivity
from ._models_py3 import WebActivityAuthentication
from ._models_py3 import WebAnonymousAuthentication
from ._models_py3 import WebBasicAuthentication
from ._models_py3 import WebClientCertificateAuthentication
from ._models_py3 import WebHookActivity
from ._models_py3 import WebLinkedService
from ._models_py3 import WebLinkedServiceTypeProperties
from ._models_py3 import WebSource
from ._models_py3 import WebTableDataset
from ._models_py3 import WranglingDataFlow
from ._models_py3 import XeroLinkedService
from ._models_py3 import XeroObjectDataset
from ._models_py3 import XeroSource
from ._models_py3 import XmlDataset
from ._models_py3 import XmlReadSettings
from ._models_py3 import XmlSource
from ._models_py3 import ZendeskLinkedService
from ._models_py3 import ZipDeflateReadSettings
from ._models_py3 import ZohoLinkedService
from ._models_py3 import ZohoObjectDataset
from ._models_py3 import ZohoSource
from ._data_factory_management_client_enums import (
AmazonRdsForOraclePartitionOption,
AvroCompressionCodec,
AzureFunctionActivityMethod,
AzureSearchIndexWriteBehaviorType,
BlobEventTypes,
CassandraSourceReadConsistencyLevels,
CompressionCodec,
CopyBehaviorType,
CosmosDbConnectionMode,
CosmosDbServicePrincipalCredentialType,
DataFlowComputeType,
DataFlowDebugCommandType,
DatasetCompressionLevel,
DayOfWeek,
DaysOfWeek,
Db2AuthenticationType,
DependencyCondition,
DynamicsAuthenticationType,
DynamicsDeploymentType,
DynamicsSinkWriteBehavior,
EventSubscriptionStatus,
FactoryIdentityType,
FtpAuthenticationType,
GlobalParameterType,
GoogleAdWordsAuthenticationType,
GoogleBigQueryAuthenticationType,
HBaseAuthenticationType,
HDInsightActivityDebugInfoOption,
HdiNodeTypes,
HiveAuthenticationType,
HiveServerType,
HiveThriftTransportProtocol,
HttpAuthenticationType,
ImpalaAuthenticationType,
IntegrationRuntimeAuthKeyName,
IntegrationRuntimeAutoUpdate,
IntegrationRuntimeEdition,
IntegrationRuntimeEntityReferenceType,
IntegrationRuntimeInternalChannelEncryptionMode,
IntegrationRuntimeLicenseType,
IntegrationRuntimeSsisCatalogPricingTier,
IntegrationRuntimeState,
IntegrationRuntimeType,
IntegrationRuntimeUpdateResult,
JsonFormatFilePattern,
JsonWriteFilePattern,
ManagedIntegrationRuntimeNodeStatus,
MongoDbAuthenticationType,
NetezzaPartitionOption,
ODataAadServicePrincipalCredentialType,
ODataAuthenticationType,
OraclePartitionOption,
OrcCompressionCodec,
ParameterType,
PhoenixAuthenticationType,
PolybaseSettingsRejectType,
PrestoAuthenticationType,
PublicNetworkAccess,
RecurrenceFrequency,
RestServiceAuthenticationType,
RunQueryFilterOperand,
RunQueryFilterOperator,
RunQueryOrder,
RunQueryOrderByField,
SalesforceSinkWriteBehavior,
SalesforceSourceReadBehavior,
SapCloudForCustomerSinkWriteBehavior,
SapHanaAuthenticationType,
SapHanaPartitionOption,
SapTablePartitionOption,
ScriptActivityLogDestination,
ScriptActivityParameterDirection,
ScriptActivityParameterType,
ScriptType,
SelfHostedIntegrationRuntimeNodeStatus,
ServiceNowAuthenticationType,
ServicePrincipalCredentialType,
SftpAuthenticationType,
SparkAuthenticationType,
SparkServerType,
SparkThriftTransportProtocol,
SqlAlwaysEncryptedAkvAuthType,
SqlDWWriteBehaviorEnum,
SqlPartitionOption,
SqlWriteBehaviorEnum,
SsisLogLocationType,
SsisObjectMetadataType,
SsisPackageLocationType,
StoredProcedureParameterType,
SybaseAuthenticationType,
TeamDeskAuthenticationType,
TeradataAuthenticationType,
TeradataPartitionOption,
TriggerRunStatus,
TriggerRuntimeState,
TumblingWindowFrequency,
VariableType,
WebActivityMethod,
WebAuthenticationType,
WebHookActivityMethod,
ZendeskAuthenticationType,
)
__all__ = [
'AccessPolicyResponse',
'Activity',
'ActivityDependency',
'ActivityPolicy',
'ActivityRun',
'ActivityRunsQueryResponse',
'AddDataFlowToDebugSessionResponse',
'AdditionalColumns',
'AmazonMWSLinkedService',
'AmazonMWSObjectDataset',
'AmazonMWSSource',
'AmazonRdsForOracleLinkedService',
'AmazonRdsForOraclePartitionSettings',
'AmazonRdsForOracleSource',
'AmazonRdsForOracleTableDataset',
'AmazonRdsForSqlServerLinkedService',
'AmazonRdsForSqlServerSource',
'AmazonRdsForSqlServerTableDataset',
'AmazonRedshiftLinkedService',
'AmazonRedshiftSource',
'AmazonRedshiftTableDataset',
'AmazonS3CompatibleLinkedService',
'AmazonS3CompatibleLocation',
'AmazonS3CompatibleReadSettings',
'AmazonS3Dataset',
'AmazonS3LinkedService',
'AmazonS3Location',
'AmazonS3ReadSettings',
'AppendVariableActivity',
'ArmIdWrapper',
'AvroDataset',
'AvroFormat',
'AvroSink',
'AvroSource',
'AvroWriteSettings',
'AzPowerShellSetup',
'AzureBatchLinkedService',
'AzureBlobDataset',
'AzureBlobFSDataset',
'AzureBlobFSLinkedService',
'AzureBlobFSLocation',
'AzureBlobFSReadSettings',
'AzureBlobFSSink',
'AzureBlobFSSource',
'AzureBlobFSWriteSettings',
'AzureBlobStorageLinkedService',
'AzureBlobStorageLocation',
'AzureBlobStorageReadSettings',
'AzureBlobStorageWriteSettings',
'AzureDataExplorerCommandActivity',
'AzureDataExplorerLinkedService',
'AzureDataExplorerSink',
'AzureDataExplorerSource',
'AzureDataExplorerTableDataset',
'AzureDataLakeAnalyticsLinkedService',
'AzureDataLakeStoreDataset',
'AzureDataLakeStoreLinkedService',
'AzureDataLakeStoreLocation',
'AzureDataLakeStoreReadSettings',
'AzureDataLakeStoreSink',
'AzureDataLakeStoreSource',
'AzureDataLakeStoreWriteSettings',
'AzureDatabricksDeltaLakeDataset',
'AzureDatabricksDeltaLakeExportCommand',
'AzureDatabricksDeltaLakeImportCommand',
'AzureDatabricksDeltaLakeLinkedService',
'AzureDatabricksDeltaLakeSink',
'AzureDatabricksDeltaLakeSource',
'AzureDatabricksLinkedService',
'AzureFileStorageLinkedService',
'AzureFileStorageLocation',
'AzureFileStorageReadSettings',
'AzureFileStorageWriteSettings',
'AzureFunctionActivity',
'AzureFunctionLinkedService',
'AzureKeyVaultLinkedService',
'AzureKeyVaultSecretReference',
'AzureMLBatchExecutionActivity',
'AzureMLExecutePipelineActivity',
'AzureMLLinkedService',
'AzureMLServiceLinkedService',
'AzureMLUpdateResourceActivity',
'AzureMLWebServiceFile',
'AzureMariaDBLinkedService',
'AzureMariaDBSource',
'AzureMariaDBTableDataset',
'AzureMySqlLinkedService',
'AzureMySqlSink',
'AzureMySqlSource',
'AzureMySqlTableDataset',
'AzurePostgreSqlLinkedService',
'AzurePostgreSqlSink',
'AzurePostgreSqlSource',
'AzurePostgreSqlTableDataset',
'AzureQueueSink',
'AzureSearchIndexDataset',
'AzureSearchIndexSink',
'AzureSearchLinkedService',
'AzureSqlDWLinkedService',
'AzureSqlDWTableDataset',
'AzureSqlDatabaseLinkedService',
'AzureSqlMILinkedService',
'AzureSqlMITableDataset',
'AzureSqlSink',
'AzureSqlSource',
'AzureSqlTableDataset',
'AzureStorageLinkedService',
'AzureTableDataset',
'AzureTableSink',
'AzureTableSource',
'AzureTableStorageLinkedService',
'BinaryDataset',
'BinaryReadSettings',
'BinarySink',
'BinarySource',
'BlobEventsTrigger',
'BlobSink',
'BlobSource',
'BlobTrigger',
'CMKIdentityDefinition',
'CassandraLinkedService',
'CassandraSource',
'CassandraTableDataset',
'ChainingTrigger',
'CloudError',
'CmdkeySetup',
'CommonDataServiceForAppsEntityDataset',
'CommonDataServiceForAppsLinkedService',
'CommonDataServiceForAppsSink',
'CommonDataServiceForAppsSource',
'ComponentSetup',
'CompressionReadSettings',
'ConcurLinkedService',
'ConcurObjectDataset',
'ConcurSource',
'ConnectionStateProperties',
'ControlActivity',
'CopyActivity',
'CopyActivityLogSettings',
'CopySink',
'CopySource',
'CopyTranslator',
'CosmosDbLinkedService',
'CosmosDbMongoDbApiCollectionDataset',
'CosmosDbMongoDbApiLinkedService',
'CosmosDbMongoDbApiSink',
'CosmosDbMongoDbApiSource',
'CosmosDbSqlApiCollectionDataset',
'CosmosDbSqlApiSink',
'CosmosDbSqlApiSource',
'CouchbaseLinkedService',
'CouchbaseSource',
'CouchbaseTableDataset',
'CreateDataFlowDebugSessionRequest',
'CreateDataFlowDebugSessionResponse',
'CreateLinkedIntegrationRuntimeRequest',
'CreateRunResponse',
'Credential',
'CredentialReference',
'CredentialResource',
'CustomActivity',
'CustomActivityReferenceObject',
'CustomDataSourceLinkedService',
'CustomDataset',
'CustomEventsTrigger',
'CustomSetupBase',
'DWCopyCommandDefaultValue',
'DWCopyCommandSettings',
'DataFlow',
'DataFlowDebugCommandPayload',
'DataFlowDebugCommandRequest',
'DataFlowDebugCommandResponse',
'DataFlowDebugPackage',
'DataFlowDebugPackageDebugSettings',
'DataFlowDebugResource',
'DataFlowDebugSessionInfo',
'DataFlowFolder',
'DataFlowListResponse',
'DataFlowReference',
'DataFlowResource',
'DataFlowSink',
'DataFlowSource',
'DataFlowSourceSetting',
'DataFlowStagingInfo',
'DataLakeAnalyticsUSQLActivity',
'DatabricksNotebookActivity',
'DatabricksSparkJarActivity',
'DatabricksSparkPythonActivity',
'Dataset',
'DatasetCompression',
'DatasetDataElement',
'DatasetDebugResource',
'DatasetFolder',
'DatasetListResponse',
'DatasetLocation',
'DatasetReference',
'DatasetResource',
'DatasetSchemaDataElement',
'DatasetStorageFormat',
'Db2LinkedService',
'Db2Source',
'Db2TableDataset',
'DeleteActivity',
'DeleteDataFlowDebugSessionRequest',
'DelimitedTextDataset',
'DelimitedTextReadSettings',
'DelimitedTextSink',
'DelimitedTextSource',
'DelimitedTextWriteSettings',
'DependencyReference',
'DistcpSettings',
'DocumentDbCollectionDataset',
'DocumentDbCollectionSink',
'DocumentDbCollectionSource',
'DrillLinkedService',
'DrillSource',
'DrillTableDataset',
'DynamicsAXLinkedService',
'DynamicsAXResourceDataset',
'DynamicsAXSource',
'DynamicsCrmEntityDataset',
'DynamicsCrmLinkedService',
'DynamicsCrmSink',
'DynamicsCrmSource',
'DynamicsEntityDataset',
'DynamicsLinkedService',
'DynamicsSink',
'DynamicsSource',
'EloquaLinkedService',
'EloquaObjectDataset',
'EloquaSource',
'EncryptionConfiguration',
'EntityReference',
'EnvironmentVariableSetup',
'ExcelDataset',
'ExcelSource',
'ExecuteDataFlowActivity',
'ExecuteDataFlowActivityTypeProperties',
'ExecuteDataFlowActivityTypePropertiesCompute',
'ExecutePipelineActivity',
'ExecutePowerQueryActivityTypeProperties',
'ExecuteSSISPackageActivity',
'ExecuteWranglingDataflowActivity',
'ExecutionActivity',
'ExportSettings',
'ExposureControlBatchRequest',
'ExposureControlBatchResponse',
'ExposureControlRequest',
'ExposureControlResponse',
'Expression',
'Factory',
'FactoryGitHubConfiguration',
'FactoryIdentity',
'FactoryListResponse',
'FactoryRepoConfiguration',
'FactoryRepoUpdate',
'FactoryUpdateParameters',
'FactoryVSTSConfiguration',
'FailActivity',
'FileServerLinkedService',
'FileServerLocation',
'FileServerReadSettings',
'FileServerWriteSettings',
'FileShareDataset',
'FileSystemSink',
'FileSystemSource',
'FilterActivity',
'Flowlet',
'ForEachActivity',
'FormatReadSettings',
'FormatWriteSettings',
'FtpReadSettings',
'FtpServerLinkedService',
'FtpServerLocation',
'GetDataFactoryOperationStatusResponse',
'GetMetadataActivity',
'GetSsisObjectMetadataRequest',
'GitHubAccessTokenRequest',
'GitHubAccessTokenResponse',
'GitHubClientSecret',
'GlobalParameterSpecification',
'GoogleAdWordsLinkedService',
'GoogleAdWordsObjectDataset',
'GoogleAdWordsSource',
'GoogleBigQueryLinkedService',
'GoogleBigQueryObjectDataset',
'GoogleBigQuerySource',
'GoogleCloudStorageLinkedService',
'GoogleCloudStorageLocation',
'GoogleCloudStorageReadSettings',
'GreenplumLinkedService',
'GreenplumSource',
'GreenplumTableDataset',
'HBaseLinkedService',
'HBaseObjectDataset',
'HBaseSource',
'HDInsightHiveActivity',
'HDInsightLinkedService',
'HDInsightMapReduceActivity',
'HDInsightOnDemandLinkedService',
'HDInsightPigActivity',
'HDInsightSparkActivity',
'HDInsightStreamingActivity',
'HdfsLinkedService',
'HdfsLocation',
'HdfsReadSettings',
'HdfsSource',
'HiveLinkedService',
'HiveObjectDataset',
'HiveSource',
'HttpDataset',
'HttpLinkedService',
'HttpReadSettings',
'HttpServerLocation',
'HttpSource',
'HubspotLinkedService',
'HubspotObjectDataset',
'HubspotSource',
'IfConditionActivity',
'ImpalaLinkedService',
'ImpalaObjectDataset',
'ImpalaSource',
'ImportSettings',
'InformixLinkedService',
'InformixSink',
'InformixSource',
'InformixTableDataset',
'IntegrationRuntime',
'IntegrationRuntimeAuthKeys',
'IntegrationRuntimeComputeProperties',
'IntegrationRuntimeConnectionInfo',
'IntegrationRuntimeCustomSetupScriptProperties',
'IntegrationRuntimeCustomerVirtualNetwork',
'IntegrationRuntimeDataFlowProperties',
'IntegrationRuntimeDataProxyProperties',
'IntegrationRuntimeDebugResource',
'IntegrationRuntimeListResponse',
'IntegrationRuntimeMonitoringData',
'IntegrationRuntimeNodeIpAddress',
'IntegrationRuntimeNodeMonitoringData',
'IntegrationRuntimeOutboundNetworkDependenciesCategoryEndpoint',
'IntegrationRuntimeOutboundNetworkDependenciesEndpoint',
'IntegrationRuntimeOutboundNetworkDependenciesEndpointDetails',
'IntegrationRuntimeOutboundNetworkDependenciesEndpointsResponse',
'IntegrationRuntimeReference',
'IntegrationRuntimeRegenerateKeyParameters',
'IntegrationRuntimeResource',
'IntegrationRuntimeSsisCatalogInfo',
'IntegrationRuntimeSsisProperties',
'IntegrationRuntimeStatus',
'IntegrationRuntimeStatusListResponse',
'IntegrationRuntimeStatusResponse',
'IntegrationRuntimeVNetProperties',
'JiraLinkedService',
'JiraObjectDataset',
'JiraSource',
'JsonDataset',
'JsonFormat',
'JsonReadSettings',
'JsonSink',
'JsonSource',
'JsonWriteSettings',
'LinkedIntegrationRuntime',
'LinkedIntegrationRuntimeKeyAuthorization',
'LinkedIntegrationRuntimeRbacAuthorization',
'LinkedIntegrationRuntimeRequest',
'LinkedIntegrationRuntimeType',
'LinkedService',
'LinkedServiceDebugResource',
'LinkedServiceListResponse',
'LinkedServiceReference',
'LinkedServiceResource',
'LogLocationSettings',
'LogSettings',
'LogStorageSettings',
'LookupActivity',
'MagentoLinkedService',
'MagentoObjectDataset',
'MagentoSource',
'ManagedIdentityCredential',
'ManagedIntegrationRuntime',
'ManagedIntegrationRuntimeError',
'ManagedIntegrationRuntimeNode',
'ManagedIntegrationRuntimeOperationResult',
'ManagedIntegrationRuntimeStatus',
'ManagedPrivateEndpoint',
'ManagedPrivateEndpointListResponse',
'ManagedPrivateEndpointResource',
'ManagedVirtualNetwork',
'ManagedVirtualNetworkListResponse',
'ManagedVirtualNetworkReference',
'ManagedVirtualNetworkResource',
'MappingDataFlow',
'MariaDBLinkedService',
'MariaDBSource',
'MariaDBTableDataset',
'MarketoLinkedService',
'MarketoObjectDataset',
'MarketoSource',
'MetadataItem',
'MicrosoftAccessLinkedService',
'MicrosoftAccessSink',
'MicrosoftAccessSource',
'MicrosoftAccessTableDataset',
'MongoDbAtlasCollectionDataset',
'MongoDbAtlasLinkedService',
'MongoDbAtlasSink',
'MongoDbAtlasSource',
'MongoDbCollectionDataset',
'MongoDbCursorMethodsProperties',
'MongoDbLinkedService',
'MongoDbSource',
'MongoDbV2CollectionDataset',
'MongoDbV2LinkedService',
'MongoDbV2Sink',
'MongoDbV2Source',
'MultiplePipelineTrigger',
'MySqlLinkedService',
'MySqlSource',
'MySqlTableDataset',
'NetezzaLinkedService',
'NetezzaPartitionSettings',
'NetezzaSource',
'NetezzaTableDataset',
'ODataLinkedService',
'ODataResourceDataset',
'ODataSource',
'OdbcLinkedService',
'OdbcSink',
'OdbcSource',
'OdbcTableDataset',
'Office365Dataset',
'Office365LinkedService',
'Office365Source',
'Operation',
'OperationDisplay',
'OperationListResponse',
'OperationLogSpecification',
'OperationMetricAvailability',
'OperationMetricDimension',
'OperationMetricSpecification',
'OperationServiceSpecification',
'OracleCloudStorageLinkedService',
'OracleCloudStorageLocation',
'OracleCloudStorageReadSettings',
'OracleLinkedService',
'OraclePartitionSettings',
'OracleServiceCloudLinkedService',
'OracleServiceCloudObjectDataset',
'OracleServiceCloudSource',
'OracleSink',
'OracleSource',
'OracleTableDataset',
'OrcDataset',
'OrcFormat',
'OrcSink',
'OrcSource',
'OrcWriteSettings',
'PackageStore',
'ParameterSpecification',
'ParquetDataset',
'ParquetFormat',
'ParquetSink',
'ParquetSource',
'ParquetWriteSettings',
'PaypalLinkedService',
'PaypalObjectDataset',
'PaypalSource',
'PhoenixLinkedService',
'PhoenixObjectDataset',
'PhoenixSource',
'PipelineElapsedTimeMetricPolicy',
'PipelineFolder',
'PipelineListResponse',
'PipelinePolicy',
'PipelineReference',
'PipelineResource',
'PipelineRun',
'PipelineRunInvokedBy',
'PipelineRunsQueryResponse',
'PolybaseSettings',
'PostgreSqlLinkedService',
'PostgreSqlSource',
'PostgreSqlTableDataset',
'PowerQuerySink',
'PowerQuerySinkMapping',
'PowerQuerySource',
'PrestoLinkedService',
'PrestoObjectDataset',
'PrestoSource',
'PrivateEndpointConnectionListResponse',
'PrivateEndpointConnectionResource',
'PrivateLinkConnectionApprovalRequest',
'PrivateLinkConnectionApprovalRequestResource',
'PrivateLinkConnectionState',
'PrivateLinkResource',
'PrivateLinkResourceProperties',
'PrivateLinkResourcesWrapper',
'QueryDataFlowDebugSessionsResponse',
'QuickBooksLinkedService',
'QuickBooksObjectDataset',
'QuickBooksSource',
'QuickbaseLinkedService',
'RecurrenceSchedule',
'RecurrenceScheduleOccurrence',
'RedirectIncompatibleRowSettings',
'RedshiftUnloadSettings',
'RelationalSource',
'RelationalTableDataset',
'RemotePrivateEndpointConnection',
'RerunTumblingWindowTrigger',
'Resource',
'ResponsysLinkedService',
'ResponsysObjectDataset',
'ResponsysSource',
'RestResourceDataset',
'RestServiceLinkedService',
'RestSink',
'RestSource',
'RetryPolicy',
'RunFilterParameters',
'RunQueryFilter',
'RunQueryOrderBy',
'SSISAccessCredential',
'SSISChildPackage',
'SSISExecutionCredential',
'SSISExecutionParameter',
'SSISLogLocation',
'SSISPackageLocation',
'SSISPropertyOverride',
'SalesforceLinkedService',
'SalesforceMarketingCloudLinkedService',
'SalesforceMarketingCloudObjectDataset',
'SalesforceMarketingCloudSource',
'SalesforceObjectDataset',
'SalesforceServiceCloudLinkedService',
'SalesforceServiceCloudObjectDataset',
'SalesforceServiceCloudSink',
'SalesforceServiceCloudSource',
'SalesforceSink',
'SalesforceSource',
'SapBWLinkedService',
'SapBwCubeDataset',
'SapBwSource',
'SapCloudForCustomerLinkedService',
'SapCloudForCustomerResourceDataset',
'SapCloudForCustomerSink',
'SapCloudForCustomerSource',
'SapEccLinkedService',
'SapEccResourceDataset',
'SapEccSource',
'SapHanaLinkedService',
'SapHanaPartitionSettings',
'SapHanaSource',
'SapHanaTableDataset',
'SapOpenHubLinkedService',
'SapOpenHubSource',
'SapOpenHubTableDataset',
'SapTableLinkedService',
'SapTablePartitionSettings',
'SapTableResourceDataset',
'SapTableSource',
'ScheduleTrigger',
'ScheduleTriggerRecurrence',
'ScriptAction',
'ScriptActivity',
'ScriptActivityParameter',
'ScriptActivityScriptBlock',
'ScriptActivityTypePropertiesLogSettings',
'SecretBase',
'SecureString',
'SelfDependencyTumblingWindowTriggerReference',
'SelfHostedIntegrationRuntime',
'SelfHostedIntegrationRuntimeNode',
'SelfHostedIntegrationRuntimeStatus',
'ServiceNowLinkedService',
'ServiceNowObjectDataset',
'ServiceNowSource',
'ServicePrincipalCredential',
'SetVariableActivity',
'SftpLocation',
'SftpReadSettings',
'SftpServerLinkedService',
'SftpWriteSettings',
'SharePointOnlineListLinkedService',
'SharePointOnlineListResourceDataset',
'SharePointOnlineListSource',
'ShopifyLinkedService',
'ShopifyObjectDataset',
'ShopifySource',
'SkipErrorFile',
'SmartsheetLinkedService',
'SnowflakeDataset',
'SnowflakeExportCopyCommand',
'SnowflakeImportCopyCommand',
'SnowflakeLinkedService',
'SnowflakeSink',
'SnowflakeSource',
'SparkLinkedService',
'SparkObjectDataset',
'SparkSource',
'SqlAlwaysEncryptedProperties',
'SqlDWSink',
'SqlDWSource',
'SqlDWUpsertSettings',
'SqlMISink',
'SqlMISource',
'SqlPartitionSettings',
'SqlServerLinkedService',
'SqlServerSink',
'SqlServerSource',
'SqlServerStoredProcedureActivity',
'SqlServerTableDataset',
'SqlSink',
'SqlSource',
'SqlUpsertSettings',
'SquareLinkedService',
'SquareObjectDataset',
'SquareSource',
'SsisEnvironment',
'SsisEnvironmentReference',
'SsisFolder',
'SsisObjectMetadata',
'SsisObjectMetadataListResponse',
'SsisObjectMetadataStatusResponse',
'SsisPackage',
'SsisParameter',
'SsisProject',
'SsisVariable',
'StagingSettings',
'StoreReadSettings',
'StoreWriteSettings',
'StoredProcedureParameter',
'SubResource',
'SubResourceDebugResource',
'SwitchActivity',
'SwitchCase',
'SybaseLinkedService',
'SybaseSource',
'SybaseTableDataset',
'TabularSource',
'TabularTranslator',
'TarGZipReadSettings',
'TarReadSettings',
'TeamDeskLinkedService',
'TeradataLinkedService',
'TeradataPartitionSettings',
'TeradataSource',
'TeradataTableDataset',
'TextFormat',
'Transformation',
'Trigger',
'TriggerDependencyReference',
'TriggerFilterParameters',
'TriggerListResponse',
'TriggerPipelineReference',
'TriggerQueryResponse',
'TriggerReference',
'TriggerResource',
'TriggerRun',
'TriggerRunsQueryResponse',
'TriggerSubscriptionOperationStatus',
'TumblingWindowTrigger',
'TumblingWindowTriggerDependencyReference',
'TypeConversionSettings',
'UntilActivity',
'UpdateIntegrationRuntimeNodeRequest',
'UpdateIntegrationRuntimeRequest',
'UserAccessPolicy',
'UserProperty',
'ValidationActivity',
'VariableSpecification',
'VerticaLinkedService',
'VerticaSource',
'VerticaTableDataset',
'WaitActivity',
'WebActivity',
'WebActivityAuthentication',
'WebAnonymousAuthentication',
'WebBasicAuthentication',
'WebClientCertificateAuthentication',
'WebHookActivity',
'WebLinkedService',
'WebLinkedServiceTypeProperties',
'WebSource',
'WebTableDataset',
'WranglingDataFlow',
'XeroLinkedService',
'XeroObjectDataset',
'XeroSource',
'XmlDataset',
'XmlReadSettings',
'XmlSource',
'ZendeskLinkedService',
'ZipDeflateReadSettings',
'ZohoLinkedService',
'ZohoObjectDataset',
'ZohoSource',
'AmazonRdsForOraclePartitionOption',
'AvroCompressionCodec',
'AzureFunctionActivityMethod',
'AzureSearchIndexWriteBehaviorType',
'BlobEventTypes',
'CassandraSourceReadConsistencyLevels',
'CompressionCodec',
'CopyBehaviorType',
'CosmosDbConnectionMode',
'CosmosDbServicePrincipalCredentialType',
'DataFlowComputeType',
'DataFlowDebugCommandType',
'DatasetCompressionLevel',
'DayOfWeek',
'DaysOfWeek',
'Db2AuthenticationType',
'DependencyCondition',
'DynamicsAuthenticationType',
'DynamicsDeploymentType',
'DynamicsSinkWriteBehavior',
'EventSubscriptionStatus',
'FactoryIdentityType',
'FtpAuthenticationType',
'GlobalParameterType',
'GoogleAdWordsAuthenticationType',
'GoogleBigQueryAuthenticationType',
'HBaseAuthenticationType',
'HDInsightActivityDebugInfoOption',
'HdiNodeTypes',
'HiveAuthenticationType',
'HiveServerType',
'HiveThriftTransportProtocol',
'HttpAuthenticationType',
'ImpalaAuthenticationType',
'IntegrationRuntimeAuthKeyName',
'IntegrationRuntimeAutoUpdate',
'IntegrationRuntimeEdition',
'IntegrationRuntimeEntityReferenceType',
'IntegrationRuntimeInternalChannelEncryptionMode',
'IntegrationRuntimeLicenseType',
'IntegrationRuntimeSsisCatalogPricingTier',
'IntegrationRuntimeState',
'IntegrationRuntimeType',
'IntegrationRuntimeUpdateResult',
'JsonFormatFilePattern',
'JsonWriteFilePattern',
'ManagedIntegrationRuntimeNodeStatus',
'MongoDbAuthenticationType',
'NetezzaPartitionOption',
'ODataAadServicePrincipalCredentialType',
'ODataAuthenticationType',
'OraclePartitionOption',
'OrcCompressionCodec',
'ParameterType',
'PhoenixAuthenticationType',
'PolybaseSettingsRejectType',
'PrestoAuthenticationType',
'PublicNetworkAccess',
'RecurrenceFrequency',
'RestServiceAuthenticationType',
'RunQueryFilterOperand',
'RunQueryFilterOperator',
'RunQueryOrder',
'RunQueryOrderByField',
'SalesforceSinkWriteBehavior',
'SalesforceSourceReadBehavior',
'SapCloudForCustomerSinkWriteBehavior',
'SapHanaAuthenticationType',
'SapHanaPartitionOption',
'SapTablePartitionOption',
'ScriptActivityLogDestination',
'ScriptActivityParameterDirection',
'ScriptActivityParameterType',
'ScriptType',
'SelfHostedIntegrationRuntimeNodeStatus',
'ServiceNowAuthenticationType',
'ServicePrincipalCredentialType',
'SftpAuthenticationType',
'SparkAuthenticationType',
'SparkServerType',
'SparkThriftTransportProtocol',
'SqlAlwaysEncryptedAkvAuthType',
'SqlDWWriteBehaviorEnum',
'SqlPartitionOption',
'SqlWriteBehaviorEnum',
'SsisLogLocationType',
'SsisObjectMetadataType',
'SsisPackageLocationType',
'StoredProcedureParameterType',
'SybaseAuthenticationType',
'TeamDeskAuthenticationType',
'TeradataAuthenticationType',
'TeradataPartitionOption',
'TriggerRunStatus',
'TriggerRuntimeState',
'TumblingWindowFrequency',
'VariableType',
'WebActivityMethod',
'WebAuthenticationType',
'WebHookActivityMethod',
'ZendeskAuthenticationType',
]
| 37.141264
| 94
| 0.821039
| 4,445
| 59,946
| 10.75658
| 0.190551
| 0.145985
| 0.189781
| 0.277372
| 0.101019
| 0.101019
| 0.101019
| 0.101019
| 0.101019
| 0.101019
| 0
| 0.014205
| 0.122744
| 59,946
| 1,613
| 95
| 37.16429
| 0.894995
| 0.00754
| 0
| 0
| 0
| 0
| 0.287967
| 0.18833
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.438202
| 0
| 0.438202
| 0
| 0
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
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| null | 0
| 0
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| 0
| 0
|
0
| 4
|
075af4946cc5d91cfc403188506045ecbdebe51b
| 60,590
|
py
|
Python
|
benchmark/generate_graphs.py
|
zanderhavgaard/thesis-code
|
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
|
[
"MIT"
] | null | null | null |
benchmark/generate_graphs.py
|
zanderhavgaard/thesis-code
|
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
|
[
"MIT"
] | 2
|
2020-04-28T07:59:30.000Z
|
2020-05-17T15:36:04.000Z
|
benchmark/generate_graphs.py
|
zanderhavgaard/thesis-code
|
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
|
[
"MIT"
] | null | null | null |
import sys
import json
import time
from pprint import pprint
from mysql_interface import SQL_Interface as database
from graph_generater import GraphGenerater
import function_lib as lib
from datetime import datetime
from os.path import expanduser
from functools import reduce
import pandas as pd
import numpy as np
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
# change 'report' to your default value
name_of_report = sys.argv[1] if len(sys.argv) > 1 else 'report'
dev_mode = eval(sys.argv[2]) if len(sys.argv) > 2 else False # TODO change dev_mode
db = database(True)
gg = GraphGenerater(name_of_report, dev_mode)
# meta coloring and order for produced graphs
hue_order = ['openfaas','aws_lambda','azure_functions']
provider_color_dict = {'openfaas': '#2316deff',
'aws_lambda':'#ff8c00ff',
'azure_functions': '#ffd700ff',
}
colors = {
'light_gray': '#708090ff',
'blue': '#191970ff'
}
# name sub-directories for the different categories by changing stringvalues in below list
# comment line out of graphs for that category is not wanted
category_of_graphs = [
lambda : cold_start('cold_starts',dev_mode),
lambda : function_lifetime('Function_lifetime', dev_mode),
lambda : large_function('Large_function',dev_mode),
lambda : throughput_graphs( 'Throughput', dev_mode),
lambda : coldtimes_graphs('Coldtimes', dev_mode),
# lambda : test( 'test', dev_mode),
]
# aux function for getting latest uuids from a experiment name
def get_uuids(experiment_name:str):
return { x[0]: x[1] for x in db.get_latest_metadata_by_experiment(experiment_name) }
def cold_start(ldir:str, devmode):
print('cold_start')
# metadata
directory = ldir
experiment_uuids = get_uuids('simple-cold-function')
def get_table_all(uuid):
return f"""select cl_provider as provider, name, minutes, seconds, granularity, threads as requests, benchmark, cold, final
from Coldstart c left join Experiment e on e.uuid=c.exp_id where e.uuid = '{uuid}';"""
def get_table_final(uuid):
return f"""select cl_provider as provider, name, minutes, seconds, granularity, threads as requests, benchmark, cold from Coldstart c
left join Experiment e on e.uuid=c.exp_id where final = True and e.uuid = '{uuid}';"""
# coldstart-identifier
# coldstart-identifier-nested
# simple-cold-function
# simple-cold-function-nested
# simple-cold-function-threaded-twelve
aws_final_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda']))
aws_all_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda']))
open_final_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas']))
open_all_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas']))
azure_final_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions']))
azure_all_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions']))
experiment_uuids = get_uuids('simple-cold-function-nested')
print('NESTED', experiment_uuids)
aws_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda']))
aws_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda']))
open_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas']))
open_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas']))
azure_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions']))
azure_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions']))
experiment_uuids = get_uuids('simple-cold-function-threaded-twelve')
print('CONCURRENT', experiment_uuids)
aws_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda']))
aws_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda']))
open_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas']))
open_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas']))
azure_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions']))
azure_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions']))
experiment_uuids = get_uuids('coldstart-identifier')
print('identifier', experiment_uuids)
aws_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda']))
aws_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda']))
open_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas']))
open_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas']))
azure_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions']))
azure_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions']))
experiment_uuids = get_uuids('coldstart-identifier-nested')
print('identifier', experiment_uuids)
aws_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda']))
aws_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda']))
open_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas']))
open_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas']))
azure_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions']))
azure_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions']))
all_finals = [aws_final_df,
open_final_df,
azure_final_df,
aws_final_nested_df,
open_final_nested_df,
azure_final_nested_df,
aws_final_con_df,
open_final_con_df,
azure_final_con_df,
aws_final_iden_df,
open_final_iden_df,
azure_final_iden_df,
aws_final_iden_nest_df,
open_final_iden_nest_df,
azure_final_iden_nest_df]
table_df = pd.concat(all_finals)
gg.save_table(table_df,'All final results',directory)
gg.save_table(aws_all_df,'AWS all simple-cold-function',directory)
gg.save_table(open_all_df,'OpenFaaS all simple-cold-function',directory)
gg.save_table(azure_all_df,'Azure all simple-cold-function',directory)
gg.save_table(aws_all_nested_df,'AWS all simple-cold-function-nested',directory)
gg.save_table(open_all_nested_df,'OpenFaaS all simple-cold-function-nested',directory)
gg.save_table(azure_all_nested_df,'Azure all simple-cold-function-nested',directory)
gg.save_table(aws_all_con_df,'AWS all simple-cold-function-concurrent',directory)
gg.save_table(open_all_con_df,'OpenFaaS all simple-cold-function-concurrent',directory)
gg.save_table(azure_all_con_df,'Azure all simple-cold-function-concurrent',directory)
gg.save_table(aws_all_iden_df,'AWS all coldstart-identifier',directory)
gg.save_table(open_all_iden_df,'OpenFaaS all coldstart-identifier',directory)
gg.save_table(azure_all_iden_df,'Azure all coldstart-identifier',directory)
gg.save_table(aws_all_iden_nest_df,'AWS all coldstart-identifier-nested',directory)
gg.save_table(open_all_iden_nest_df,'OpenFaaS all coldstart-identifier-nested',directory)
gg.save_table(azure_all_iden_nest_df,'Azure all coldstart-identifier-nested',directory)
def function_lifetime(ldir:str, devmode:bool):
print('function_lifetime')
# metadata
directory = ldir
experiment_uuids = get_uuids('function-lifetime')
def get_table(uuid):
return f"""select cl_provider as provider,instance_identifier as first_invoked, orig_identifier as last_invoked, hours,minutes,seconds,sleep_time,reclaimed
from Function_lifetime f left join Experiment e on e.uuid=f.exp_id where e.uuid = '{uuid}';"""
def get_invocations(uuid):
return f"""select execution_start-invocation_start as latency, instance_identifier, cl_provider as provider from Invocation i
left join Experiment e on e.uuid=i.exp_id where e.uuid = '{uuid}';"""
aws_table_df = db.get_raw_query(get_table(experiment_uuids['aws_lambda']))
open_table_df = db.get_raw_query(get_table(experiment_uuids['openfaas']))
azure_table_df = db.get_raw_query(get_table(experiment_uuids['azure_functions']))
table_df = pd.concat([aws_table_df,open_table_df,azure_table_df])
aws_df = db.get_raw_query(get_invocations(experiment_uuids['aws_lambda']))
open_df = db.get_raw_query(get_invocations(experiment_uuids['openfaas']))
open_df.loc[(open_df.latency > 5.0),'latency']= 5.0
azure_df = db.get_raw_query(get_invocations(experiment_uuids['azure_functions']))
joint_df = pd.concat([aws_df,open_df,azure_df])
config = {
'x': 'provider',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'markers': ['o','s','v'],
'ylabel': ('Latency in seconds',12),
'xlabel': ('Cloud provider',12),
'markers': ['o','s','v'],
'jitter': 0.25,
'alpha': 0.5,
# 'height': 4,
# 'aspect': 0.8,
}
gg.strip_plot(joint_df, config, 'Latency by provider', directory)
gg.save_table(table_df, 'Function lifetime values',directory)
def large_function(ldir:str, devmode:bool):
# metadata
directory = ldir
experiment_uuids = get_uuids('coldtime-large-functions ')
# queries
def query_by_provider(uuid):
return f"""select execution_start-invocation_start as latency, execution_total, function_name,
instance_identifier as instance_id, throughput,cl_provider as provider from
Invocation i left join Experiment e on i.exp_id=e.uuid where e.uuid ='{uuid}';"""
# dataframes
aws_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda']))
open_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas']))
azure_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions']))
joint_df = pd.concat([aws_df,open_df,azure_df])
config = {
'x': 'function_name',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Latency in seconds',12),
'xlabel': ('Function name',12),
'markers': ['o','s','v'],
'jitter': 0.1,
'x_strip': 'instance_id',
'y_strip': 'latency',
'strip': True,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
# NOT INT USE ----------------------------------------------------------
# aws_avg = aws_df.groupby('function_name')['latency'].sum()
# avg_reg = aws_avg[0]/len(aws_df)
# avg_mono = aws_avg[1]/len(aws_df)
# warm_times = aws_df.map(lambda x: x.latency if x.latency < )
# aws_mono = aws_df[aws_df['function_name'== 'monolith'] ]
# aws_mono = aws_df.loc[aws_df['function_name'] == 'monolith']
# aws_reg = aws_df.loc[aws_df['function_name'] != 'monolith']
# aws_mono_cutoff = aws_mono *2
# aws_avg_mono = aws_mono.sum().latency / len(aws_mono)
# print(aws_avg_mono)
# aws_avg_reg = aws_reg.sum().latency / len(aws_reg)
# aws_mono_warm = aws_mono.loc[aws_mono['latency'] < aws_mono_cutoff]
# pprint(aws_mono)
# aws_reg = aws_df.query("function_name == monolith")
# pprint(aws_reg)
# aws_reg = aws_df.query(f"function_name == monolith")['*']
# open_avg = open_df.groupby('function_name')['latency'].sum()
# azure_avg = azure_df.groupby('function_name')['latency'].sum()
# data = {'provider': ['aws_lambda','openfaas','azure_functions'],
# 'reg_func': [aws_avg[0]/len(aws_df),open_avg[0]/len(open_df),azure_avg[0]/len(azure_df)],
# 'monolith': [aws_avg[1]/len(aws_df),open_avg[1]/len(open_df),azure_avg[1]/len(azure_df)]}
# df = pd.DataFrame(data)
# pprint(df)
# aws_sum = aws_df.sum()
# avg_latency = aws_df.sum().latency / len(aws_df)
# print(avg_latency)
# pprint(aws_sum)
# ------------------------------------------------------------------------------------------
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['hue_order'] = ['aws_lambda']
config['markers'] = ['s']
gg.swarm_plot(aws_df, config, 'AWS latency small vs large function',directory)
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['hue_order'] = ['openfaas']
config['markers'] = ['o']
gg.swarm_plot(open_df, config, 'OpenFaaS latency small vs large function',directory)
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['hue_order'] = ['azure_functions']
config['markers'] = ['v']
gg.swarm_plot(azure_df, config, 'Azure latency small vs large function',directory)
config = {
'x': 'throughput',
'y': 'latency',
'hue': 'function_name',
'palette': {'function1': 'red', 'monolith': 'black'},
'ylabel': ('Latency in seconds',12),
'xlabel': ('Number of operations',12),
'markers': ['s'],
'jitter': 0.1,
'x_strip': 'instance_id',
'y_strip': 'latency',
'strip': True,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
aws_throughput = aws_df.loc[aws_df['throughput'] != 0.0]
gg.line_plot(aws_throughput,config,'AWS throughput by function type',directory)
open_throughput = open_df.loc[open_df['throughput'] != 0.0]
gg.line_plot(open_throughput,config,'OpenFaaS throughput by function type',directory)
azure_throughput = azure_df.loc[azure_df['throughput'] != 0.0]
gg.line_plot(azure_throughput,config,'Azure throughput by function type',directory)
def coldtimes_graphs(ldir:str, devmode:bool):
print('coldtimes_graphs')
# metadata
directory = ldir
experiment_uuids = get_uuids('linear-invocation')
# queries
def query_by_provider(uuid, level:int,pyramid:bool=False):
return f"""select latency,instance_id, total, thread_id, multi, provider, if(latency > if(coldtime > 1,{2.0 if pyramid else 1.0},coldtime), 'cold','warm') as cold, invocation_start
from (SELECT instance_identifier as instance_id, execution_total as total, thread_id, if(numb_threads > 1,0,1) as multi, cl_provider as
provider, coldtime, execution_start-invocation_start as latency, level, invocation_start from Experiment e
left join Invocation i on i.exp_id=e.uuid left join (select avg(execution_start-invocation_start)*3 as coldtime,exp_id as xexp_id from Invocation
where exp_id ='{uuid}') x on e.uuid=x.xexp_id where exp_id ='{uuid}') y where level = {level};"""
def error_by_provider(uuid):
return f"""select count(*) as number, cl_provider as provider from Error r left join Experiment e on e.uuid=r.exp_id where e.uuid = '{uuid}';"""
# dataframes
aws_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0)) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0)) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_linear_df = pd.concat([aws_linear_df,open_linear_df,azure_linear_df],ignore_index=True)
experiment_uuids = get_uuids('linear-invocation-nested')
aws_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 1)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 1)) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 1)) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_linear_nested_df = pd.concat([aws_linear_nested_df,open_linear_nested_df,azure_linear_nested_df],ignore_index=True)
experiment_uuids = get_uuids('scenario-pyramid')
print('pyramid',experiment_uuids)
aws_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0, True)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0, True)) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0, True)) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_pyramid_df = pd.concat([aws_pyramid_df,open_pyramid_df,azure_pyramid_df],ignore_index=True)
aws_error_df = db.get_raw_query(error_by_provider(experiment_uuids['aws_lambda'])) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_error_df = db.get_raw_query(error_by_provider(experiment_uuids['openfaas'])) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_error_df = db.get_raw_query(error_by_provider(experiment_uuids['azure_functions'])) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_error_df = pd.concat([aws_error_df,open_error_df,azure_error_df],ignore_index=True)
experiment_uuids = get_uuids('growing-load-spikes')
aws_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0)) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0)) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_spike_df = pd.concat([aws_spike_df,open_spike_df,azure_spike_df],ignore_index=True)
aws_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['aws_lambda'])) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['openfaas'])) if 'openfaas' in experiment_uuids else np.DataFrame()
azure_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['azure_functions'])) if 'azure_functions' in experiment_uuids else np.DataFrame()
joint_error_spike_df = pd.concat([aws_error_spike_df,open_error_spike_df,azure_error_spike_df],ignore_index=True)
#########
# PLOTS #
#########
# appendix stuff for showing graph of pyramid - get back to it
# config = {
# 'x': 'invocations_start',
# 'y': 'latency',
# 'hue': 'provider',
# 'palette': provider_color_dict,
# 'hue_order': hue_order,
# 'ylabel': ('operations (1000)',14),
# 'xlabel': ('time in seconds',14),
# 'markers': ['o','s','v'],
# 'hist':True,
# 'kde': False,
# # 'height': 4,
# # 'aspect': 0.8,
# 'line_kws':{'color':colors['light_gray']},
# }
# plist = np.array(aws_pyramid_df.loc[ : , 'invocation_start' ]).tolist()
# gg.dist_plot(plist,config,'pyramid invocation starts',directory)
config = {
'x': 'cold',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': ['aws_lambda'],
'ylabel': ('latency in seconds',12),
'xlabel': ('Cold time vs warm time',12),
'markers': ['s'],
'jitter': 0.1,
'x_strip': 'cold',
'y_strip': 'latency',
'strip': True,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.box_plot(aws_linear_df, config, 'AWS cold times distribution',directory)
config['hue_order'] = ['openfaas']
config['markers'] = ['o']
gg.box_plot(open_linear_df, config, 'OpenFaaS cold times distribution',directory)
config['hue_order'] = ['azure_functions']
config['markers'] = ['v']
gg.box_plot(azure_linear_df, config, 'Azure cold times distribution',directory)
config = {
'x': 'invocation_start',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Latency in seconds',12),
'xlabel': ('Invocation start (unix time)',12),
'markers': ['o','s','v'],
'alpha': 0.5,
# 'jitter': 0.25,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.scatter_plot(joint_linear_df,config,'Latency relative to invocation start:appendix',directory,18)
joint_linear_df.loc[(joint_linear_df.latency > 10.0 ),'latency']=8.00
gg.scatter_plot(joint_linear_df,config,'Latency relative to invocation start',directory,18)
open_linear_df.loc[(open_linear_df.latency > 10.0 ),'latency']=3.00
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.scatter_plot(aws_linear_df,config,' AWS latency relative to invocation start',directory,18)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.scatter_plot(open_linear_df,config,' OpenFaaS latency relative to invocation start',directory,18)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.scatter_plot(azure_linear_df,config,'Azure latency relative to invocation start',directory,18)
config = {
'x': 'provider',
'y': 'cold',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Number of cold times',12),
'xlabel': ('Cloud provider',12),
'markers': ['o','s','v'],
'jitter': 0.1,
'alpha': 0.5,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
aws = np.array(aws_linear_df['cold'].value_counts()).tolist()+['aws_lambda']
openf = np.array(open_linear_df['cold'].value_counts()).tolist()+['openfaas']
azure = np.array(azure_linear_df['cold'].value_counts()).tolist()+['azure_functions']
zipped = list(zip(aws,openf,azure))
data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]}
df = pd.DataFrame(data)
gg.bar_plot(df, config,'Cold times by provider: linear-invocation',directory)
config['y'] = 'warm'
config['ylabel'] = ('Number of warm times',12)
gg.bar_plot(df, config,'Warm times by provider: linear-invocation',directory)
config['x'] = 'instance_id'
config['y'] = 'latency'
config['xlabel'] = ('Function instance',12)
config['ylabel'] = ('Latency in seconds',12)
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
copy_aws_linear_df = aws_linear_df.copy(deep=True)
copy_aws_linear_df['instance_id'] = copy_aws_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
gg.strip_plot(copy_aws_linear_df,config,' AWS latency per function instance',directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
copy_open_linear_df = open_linear_df.copy(deep=True)
copy_open_linear_df['instance_id'] = copy_open_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
gg.strip_plot(copy_open_linear_df,config,'OpenFaaS latency per function instance',directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
copy_azure_linear_df = azure_linear_df.copy(deep=True)
copy_azure_linear_df['instance_id'] = copy_azure_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
gg.strip_plot(copy_azure_linear_df,config,'Azure latency per function instance',directory)
###################################
# --> linear-invocation-nested <--#
###################################
directory = directory.split('/')[0]
directory += '/nested'
config = {
'x': 'cold',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'ylabel': ('cold times',12),
'markers': ['s'],
'jitter': 0.1,
'x_strip': 'cold',
'y_strip': 'latency',
'strip': True,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.box_plot(aws_linear_nested_df, config, 'AWS cold times distribution: nested',directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.box_plot(open_linear_nested_df, config, 'OpenFaaS cold times distribution: nested',directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.box_plot(azure_linear_nested_df, config, 'Azure cold times distribution: nested',directory)
config = {
'x': 'invocation_start',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('latency in seconds',12),
'xlabel': ('invocation start (unix time)',12),
'markers': ['o','s','v'],
'alpha': 0.9,
# 'jitter': 0.25,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.scatter_plot(joint_linear_nested_df,config,'appendix:latency relative to invocation start: nested',directory,18)
joint_linear_nested_df.loc[(joint_linear_nested_df.latency > 8.0 ),'latency']=8.00
gg.scatter_plot(joint_linear_nested_df,config,'latency relative to invocation start: nested',directory,18)
open_linear_nested_df.loc[(open_linear_nested_df.latency > 3.0 ),'latency']=3.00
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.scatter_plot(aws_linear_nested_df,config,' AWS latency relative to invocation start: nested',directory,18)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.scatter_plot(open_linear_nested_df,config,' OpenFaaS latency relative to invocation start: nested',directory,18)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.scatter_plot(azure_linear_nested_df,config,'Azure latency relative to invocation start: nested',directory,18)
config = {
'x': 'provider',
'y': 'cold',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Number of cold times',12),
'markers': ['o','s','v'],
'jitter': 0.1,
'alpha': 0.5,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
aws = np.array(aws_linear_nested_df['cold'].value_counts()).tolist()+['aws_lambda']
openf = np.array(open_linear_nested_df['cold'].value_counts()).tolist()+['openfaas']
azure = np.array(azure_linear_nested_df['cold'].value_counts()).tolist()+['azure_functions']
zipped = list(zip(aws,openf,azure))
data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]}
df = pd.DataFrame(data)
gg.bar_plot(df, config,'Cold times: linear-invocation: nested',directory)
config['y'] = 'warm'
config['ylabel'] = ('Number of warm times',12)
gg.bar_plot(df, config,'Warm times: linear-invocation: nested',directory)
config['x'] = 'instance_id'
config['y'] = 'latency'
config['xlabel'] = ('Function id',12)
config['ylabel'] = ('Latency in seconds',12)
copy_aws_linear_nested_df = aws_linear_nested_df.copy(deep=True)
copy_aws_linear_nested_df['instance_id'] = copy_aws_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.strip_plot(copy_aws_linear_nested_df,config,' AWS latency per function instance: nested',directory)
copy_open_linear_nested_df = open_linear_nested_df.copy(deep=True)
open_linear_nested_df['instance_id'] = copy_open_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.strip_plot(copy_open_linear_nested_df,config,'OpenFaaS latency per function instance: nested',directory)
copy_azure_linear_nested_df = azure_linear_nested_df.copy(deep=True)
copy_azure_linear_nested_df['instance_id'] = copy_azure_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000))
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.strip_plot(copy_azure_linear_nested_df,config,'Azure latency per function instance: nested',directory)
#########################
# --> load-scenario <-- #
#########################
directory = directory.split('/')[0]
directory += '/pyramid'
config = {
'x': 'provider',
'y': 'number',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('number of errors',12),
'xlabel': ('Cloud Provider',12),
'markers': ['o','s','v'],
'hist':True,
'kde': False,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(joint_error_df,config,'error by provider for load-scenario: pyramid',directory,18)
aws = np.array(aws_pyramid_df['cold'].value_counts()).tolist()+['aws_lambda']
openf = np.array(open_pyramid_df['cold'].value_counts()).tolist()+['openfaas']
azure = np.array(azure_pyramid_df['cold'].value_counts()).tolist()+['azure_functions']
zipped = list(zip(aws,openf,azure))
data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]}
df = pd.DataFrame(data)
config = {
'x': 'provider',
'y': 'cold',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('number of cold times',12),
'markers': ['o','s','v'],
'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(df, config,'Cold times: load-scenario: pyramid',directory)
config['y'] = 'warm'
config['ylabel'] = ('number of warm times',12)
gg.bar_plot(df, config,'Warm times: load-scenario: pyramid',directory)
config = {
'x': 'provider',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('cold times',12),
'markers': ['o','s','v'],
'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.boxen_plot(joint_pyramid_df, config, 'Cold times distribution: pyramid',directory)
config['x'] = 'multi'
gg.boxen_plot(joint_pyramid_df, config, 'Cold times concurrent vs sequential: pyramid',directory)
config = {
'x': 'invocation_start',
'y': 'latency',
'hue': 'provider',
'ylabel': ('Latency in seconds',12),
'xlabel': ('Invocation start time',12),
'fit_reg': False,
# 'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.lm_plot(aws_pyramid_df, config, 'AWS latency: pyramid', directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.lm_plot(open_pyramid_df, config, 'OpenFaaS latency: pyramid', directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.lm_plot(azure_pyramid_df, config, 'Azure latency: pyramid', directory)
config = {
'x': 'invocation_start',
'y': 'latency',
'ylabel': ('Latency in seconds',12),
'xlabel': ('Invocation start time',12),
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'markers': ['o','s','v'],
'fit_reg': False,
# 'hist':True,
# 'kde': False,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.lm_plot(joint_pyramid_df, config, 'Latency by provider: pyramid', directory)
def find_cold_times(df):
cold_times = {}
for row in df.itertuples(index=True, name='Pandas'):
if row.cold == 'cold':
if row.instance_id not in cold_times:
cold_times[row.instance_id] = 0
else:
cold_times[row.instance_id] += 1
return cold_times
aws_count = find_cold_times(aws_pyramid_df)
aws_cold_starts = len(aws_count)
aws_cold_times = reduce(lambda x,y: x+y[1],[0]+list(aws_count.items()))
open_count = find_cold_times(open_pyramid_df)
open_cold_starts = len(open_count)
open_cold_times = reduce(lambda x,y: x+y[1],[0]+list(open_count.items()))
# print(open_count,'\n')
azure_count = find_cold_times(azure_pyramid_df)
azure_cold_starts = len(azure_count)
azure_cold_times = reduce(lambda x,y: x+y[1],[0]+list(azure_count.items()))
# print(azure_count,'\n')
data = {'provider': ['aws_lambda','openfaas','azure_functions'],
'cold_start': [aws_cold_starts,open_cold_starts,azure_cold_starts],
'cold_times': [aws_cold_times,open_cold_times,azure_cold_times]}
df = pd.DataFrame(data)
config = {
'x': 'provider',
'y': 'cold_start',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Number of cold starts',12),
'xlabel': ('Provider',12),
'markers': ['o','s','v'],
# 'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(df, config,'Cold starts: load-scenario-pyramid',directory)
config['y'] = 'cold_times'
config['ylabel'] = ('Number of cold times',12)
gg.bar_plot(df, config,'Cold times: load scenario-pyramid',directory)
###############################
# growing-load-spike scenario #
###############################
directory = directory.split('/')[0]
directory += '/spikes'
config = {
'x': 'provider',
'y': 'number',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('number of errors',12),
'xlabel': ('Cloud Provider',12),
'markers': ['o','s','v'],
'hist':True,
'kde': False,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(joint_error_spike_df,config,'Error by provider for load-scenario: spikes',directory,18)
aws = np.array(aws_spike_df['cold'].value_counts()).tolist()+['aws_lambda']
openf = np.array(open_spike_df['cold'].value_counts()).tolist()+['openfaas']
azure = np.array(azure_spike_df['cold'].value_counts()).tolist()+['azure_functions']
zipped = list(zip(aws,openf,azure))
data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]}
df = pd.DataFrame(data)
config = {
'x': 'provider',
'y': 'cold',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('number of cold times',12),
'markers': ['o','s','v'],
'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(df, config,'Cold times: load-scenario: spikes',directory)
config['y'] = 'warm'
config['ylabel'] = ('number of warm times',12)
gg.bar_plot(df, config,'Warm times: load-scenario: spikes',directory)
config = {
'x': 'provider',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('cold times',12),
'markers': ['o','s','v'],
'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.boxen_plot(joint_spike_df, config, 'Cold times distribution: spikes',directory)
config['x'] = 'multi'
gg.boxen_plot(joint_spike_df, config, 'Cold times concurrent vs sequential: spikes',directory)
config = {
'x': 'invocation_start',
'y': 'latency',
'hue': 'provider',
'ylabel': ('Latency in seconds',12),
'xlabel': ('Invocation start time',12),
'fit_reg': False,
# 'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.lm_plot(aws_spike_df, config, 'AWS latency: spikes', directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.lm_plot(open_spike_df, config, 'OpenFaaS latency: spikes', directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.lm_plot(azure_spike_df, config, 'Azure latency: spikes', directory)
config['hue_order'] = hue_order
config['palette'] = provider_color_dict
config = {
'x': 'invocation_start',
'y': 'latency',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Latency in seconds',12),
'xlabel': ('Invocation start time',12),
'markers': ['o','s','v'],
'jitter': 0.1,
'fit_reg': False,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.lm_plot(joint_spike_df, config, 'Latency by provider: spikes', directory)
def find_cold_times(df):
cold_times = {}
for row in df.itertuples(index=True, name='Pandas'):
if row.cold == 'cold':
if row.instance_id not in cold_times:
cold_times[row.instance_id] = 0
else:
cold_times[row.instance_id] += 1
return cold_times
aws_count = find_cold_times(aws_spike_df)
aws_cold_starts = len(aws_count)
aws_cold_times = reduce(lambda x,y: x+y[1],[0]+list(aws_count.items()))
open_count = find_cold_times(open_spike_df)
open_cold_starts = len(open_count)
open_cold_times = reduce(lambda x,y: x+y[1],[0]+list(open_count.items()))
# print(open_count,'\n')
azure_count = find_cold_times(azure_spike_df)
azure_cold_starts = len(azure_count)
azure_cold_times = reduce(lambda x,y: x+y[1],[0]+list(azure_count.items()))
# print(azure_count,'\n')
data = {'provider': ['aws_lambda','openfaas','azure_functions'],
'cold_start': [aws_cold_starts,open_cold_starts,azure_cold_starts],
'cold_times': [aws_cold_times,open_cold_times,azure_cold_times]}
df = pd.DataFrame(data)
config = {
'x': 'provider',
'y': 'cold_start',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Number of cold starts',12),
'xlabel': ('Provider',12),
'markers': ['o','s','v'],
# 'jitter': 0.1,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.bar_plot(df, config,'Cold starts: load-scenario-spikes',directory)
config['y'] = 'cold_times'
config['ylabel'] = ('Number of cold times',12)
gg.bar_plot(df, config,'Cold times: load scenario-spikes',directory)
def throughput_graphs(directory:str, devmode:bool ):
print('throughput_graphs')
# metadata
directory = 'Throughput'
experiment_uuids = get_uuids('throughput-benchmarking')
# queries
def query_by_provider(uuid, multi):
return f"""SELECT throughput/1000 as operations_milli, throughput_time, throughput_process_time,(throughput_process_time/throughput_time)*100 as process_fraction,
execution_start-invocation_start as latency, thread_id, if(numb_threads > 1,1,0) as multi, cl_provider as provider from Experiment e left join Invocation i on i.exp_id=e.uuid
where throughput != 0 and numb_threads {'> 1' if multi else '= 1'} and exp_id ='{uuid}';"""
def monolith_by_provider(uuid,multi):
return f"""select function_argument,process_time_matrix,running_time_matrix,monolith_result,(process_time_matrix/running_time_matrix)*100 as process_fraction,
execution_start-invocation_start as latency, thread_id, numb_threads, if(numb_threads > 1,0,1) as multi, cl_provider as provider from
(Monolith m left join Experiment e on m.exp_id=e.uuid) join Invocation i on m.invo_id=i.identifier
where numb_threads {'> 1' if multi else '= 1'} and m.exp_id ='{uuid}';"""
# dataframes
aws_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], False)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
azure_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], False)) if 'azure_functions' in experiment_uuids else np.DataFrame()
open_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], False)) if 'openfaas' in experiment_uuids else np.DataFrame()
aws_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], True)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
azure_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], True)) if 'azure_functions' in experiment_uuids else np.DataFrame()
open_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], True)) if 'openfaas' in experiment_uuids else np.DataFrame()
joined_single_df = pd.concat([aws_invo_single_df,azure_invo_single_df,open_invo_single_df],ignore_index=True)
joined_multi_df = pd.concat([aws_invo_multi_df,azure_invo_multi_df,open_invo_multi_df],ignore_index=True)
all_invo_df = pd.concat([joined_single_df,joined_multi_df],ignore_index=True)
# from monolith table
aws_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['aws_lambda'], False)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['azure_functions'], False)) if 'azure_functions' in experiment_uuids else np.DataFrame()
azure_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['openfaas'], False)) if 'openfaas' in experiment_uuids else np.DataFrame()
aws_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['aws_lambda'], True)) if 'aws_lambda' in experiment_uuids else np.DataFrame()
open_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['azure_functions'], True)) if 'azure_functions' in experiment_uuids else np.DataFrame()
azure_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['openfaas'], True)) if 'openfaas' in experiment_uuids else np.DataFrame()
monolith_single_df = pd.concat([aws_monolith_df, azure_monolith_df,open_monolith_df],ignore_index=True)
monolith_multi_df = pd.concat([aws_monolith_multi_df,azure_monolith_multi_df,open_monolith_multi_df],ignore_index=True)
monolith_all_invo_df = pd.concat([monolith_single_df,monolith_multi_df],ignore_index=True)
# Throughput time and operations perfomed in that time
config = {
'x': 'throughput_time',
'y': 'operations_milli',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('operations (1000)',12),
'xlabel': ('time in seconds',12),
'markers': ['o','s','v'],
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
gg.lm_plot(joined_single_df,config,'Ops per second: sequential ',directory)
gg.line_plot(joined_single_df,config,'Ops per second: sequential',directory)
gg.lm_plot(joined_multi_df,config,'Ops per second: concurrent',directory)
gg.line_plot(joined_multi_df,config,'Ops per second: concurrent',directory)
gg.lm_plot(all_invo_df,config,'Ops per second: all',directory)
# for appendix
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.lm_plot(pd.concat([aws_invo_single_df,aws_invo_multi_df]),config,'AWS ops per second: all',directory )
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.lm_plot(pd.concat([open_invo_single_df,open_invo_multi_df]),config,'OpenFaaS ops per second: all',directory )
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.lm_plot(pd.concat([azure_invo_single_df,azure_invo_multi_df]),config,'Azure ops per second: all',directory )
config['x'] = 'latency'
config['hue_order'] = hue_order
config['palette'] = provider_color_dict
config['markers'] = ['o','s','v']
gg.lm_plot(joined_single_df,config,'Ops per second mapped to latency: sequential ',directory)
gg.lm_plot(joined_multi_df,config,'Ops per second mapped to latency: concurrent',directory)
gg.lm_plot(all_invo_df,config,'Ops per second mapped to latency: all',directory)
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.lm_plot(pd.concat([aws_invo_single_df,aws_invo_multi_df]),config,'AWS ops per second mapped to latency: all',directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.lm_plot(pd.concat([open_invo_single_df,open_invo_multi_df]),config,'OpenFaaS ops per second mapped to latency: all',directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['v']
gg.lm_plot(pd.concat([azure_invo_single_df,azure_invo_multi_df]),config,'Azure ops per second mapped to latency: all',directory)
# for appendix - no correlation found for latency
copy_all_invo = all_invo_df.copy(deep=True)
indexNames = copy_all_invo[ copy_all_invo['latency'] > 10.0 ].index
# Delete these row indexes from dataFrame
copy_all_invo.drop(indexNames , inplace=True)
config['kind']='scatter'
config['x_vars'] = ['operations_milli','throughput_process_time','process_fraction']
config['y_vars'] = ['latency']
gg.pair_plot(copy_all_invo, config,'Process fraction: sequential',directory)
config = {
'x': 'throughput_time',
'y': 'process_fraction',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Percentage of time in CPU ',12),
'xlabel': ('Time in seconds',12),
'markers': ['o','s','v'],
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
# single
gg.bar_plot(joined_single_df,config,'Process fraction: sequential',directory)
# multi
gg.bar_plot(joined_multi_df, config,'Process fraction: concurrent',directory)
# all
gg.bar_plot(all_invo_df, config,'Process fraction: all',directory)
config['x'] = 'provider'
# plots per provider
gg.violin_plot(joined_single_df,config,'Process fraction by provider: sequential',directory)
# multi
gg.violin_plot(joined_multi_df, config,'Process fraction: concurrent',directory)
# all
gg.violin_plot(all_invo_df, config,'Process fraction: all',directory)
# --> Monolith plots <--
directory += '/monolith'
config = {
'x': 'function_argument',
'y': 'running_time_matrix',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'xlabel': ('Size of matrix',12),
'ylabel': ('Running time in seconds',12),
'markers': ['o','s','v'],
'jitter':0.15,
# 'height': 4,
# 'aspect': 0.8,
}
gg.lm_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory)
gg.line_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory)
gg.swarm_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory)
config = {
'x': 'multi',
'y': 'running_time_matrix',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('Time in seconds',12),
'xlabel': ('Sequential vs concurrent',12),
'markers': ['o','s','v'],
'hist':True,
'kde': False,
# 'height': 4,
# 'aspect': 0.8,
'line_kws':{'color':colors['light_gray']},
}
# config['x']='multi'
config['strip'] = True
config['x_strip'] = 'multi'
config['y_strip'] = 'running_time_matrix'
config['bins'] = 30
config['hue_order'] = ['aws_lambda']
config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']}
config['markers'] = ['s']
gg.box_plot(pd.concat([aws_monolith_df,aws_monolith_multi_df]),config,'AWS Time for matrix calc: all',directory)
config['hue_order'] = ['openfaas']
config['palette'] = {'openfaas':provider_color_dict['openfaas']}
config['markers'] = ['o']
gg.box_plot(pd.concat([open_monolith_df,open_monolith_multi_df]),config,'OpenFaaS Time for matrix calc: all',directory)
config['hue_order'] = ['azure_functions']
config['palette'] = {'azure_functions':provider_color_dict['azure_functions']}
config['markers'] = ['s']
gg.box_plot(pd.concat([azure_monolith_df,azure_monolith_multi_df]),config,'azure Time for matrix calc: all',directory)
config['hue_order'] = hue_order
config['palette'] = provider_color_dict
config['markers'] = ['o','s','v']
gg.box_plot(monolith_all_invo_df,config,'Time for matrix calc for all providers',directory)
config = {
'x': 'function_argument',
'y': 'process_fraction',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'xlabel': ('Size of matrix',12),
'ylabel': ('Process time in seconds',12),
'markers': ['o','s','v'],
'jitter':0.15,
# 'height': 4,
# 'aspect': 0.8,
}
gg.swarm_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory)
gg.bar_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory)
gg.scatter_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory)
config = {
'x': 'running_time_matrix',
'y': 'process_fraction',
'hue': 'provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'xlabel': ('Running time seconds',14),
'ylabel': ('Process time in seconds',14),
'markers': ['o','s','v'],
'jitter':0.15,
# 'height': 4,
# 'aspect': 0.8,
}
gg.scatter_plot(monolith_all_invo_df,config,'Matrix calculation: all',directory)
# delete when done
def test(directory:str, dev_mode:bool):
db = database(True)
gg = GraphGenerater('report',dev_mode)
hue_order = ['openfaas','aws_lambda','azure_functions']
provider_color_dict = dict({'aws_lambda':'#ff8c00ff',
'azure_functions': '#ffd700ff',
'openfaas': '#2316deff',
})
query_throughput = """SELECT floor(throughput/1000) as operations_milli,throughput_time,(throughput_process_time/throughput_time)*100 as process_fraction,
cl_provider from (select name, cl_provider, total_time, uuid as experiment_uuid from Experiment where name = 'throughput-benchmarking') x
left join Invocation i on i.exp_id=x.experiment_uuid where throughput != 0 and throughput_time < 2.0 and floor(throughput/1000) < 1000 order by throughput_time;"""
throughput_dataframe = db.get_raw_query(query_throughput)
# print(throughput_dataframe.head(10).to_latex(index=False))
# print(throughput_dataframe.head(10).to_html(index=False))
# basic_throughput = throughput_dataframe.copy(deep=True)
# lineplot - throughput per second all providers
config = {
'x': 'throughput_time',
'y': 'operations_milli',
'hue': 'cl_provider',
'palette': provider_color_dict,
'hue_order': hue_order,
'ylabel': ('operations (100)',14),
'xlabel': ('time in seconds',18),
# 'markers': ['o','s','v'],
# 'height': 3,
# 'aspect':0.8,
# 'kind': 'scatter',
# 'x_jitter':0.25,
# 'y_jitter': 0.25,
# 'row':'cl_provider',
# 'line_kws':{'color':'#191970ff'},
# 'color':'purple'
}
# gg.joint_plot(throughput_dataframe,config,'jointplot',directory)
list_query = """select execution_start-invocation_start as latency from Invocation where exp_id in (select uuid from Experiment where name='linear-invocation-nested' and cl_provider='aws_lambda')
and execution_start-invocation_start > 0.5;"""
res_list = db.get_raw_query(list_query,False)
flatten = reduce(lambda x,y: x+y,res_list)
# config['hist']=True
# config['kde']= False
# config['bins'] = 30
# config['height'] = 0.5
# config.pop('x')
# config['color']='#ff8c00ff'
# gg.rug_plot(flatten,config,'rug plot',directory)
# gg.dist_plot(flatten,config,'dist plot',directory)
# gg.bar_plot(throughput_dataframe,config,'operations (1000) per second',directory)
# config.pop('y')
# gg.count_plot(throughput_dataframe,config,'operations (1000) per second',directory)
# gg.line_plot(throughput_dataframe,config,'operations (1000) per second',directory,12)
# config['col'] = 'cl_provider'
# config['jitter'] = 0.25
# config['aspect'] = 1.2
# config['height'] = 3
# config.pop('hue')
# config['palette'] = 'bright'
# gg.cat_plot(throughput_dataframe,config,'cat plot',directory)
# gg.violin_plot(throughput_dataframe,config,'Violin plot',directory)
# config['y'] = 'process_fraction'
# gg.strip_plot(throughput_dataframe,config,'strip plot',directory)
gg.dynamic_multi_plot(throughput_dataframe,config,'line + scatter',directory,[lambda l: sns.lineplot(
x=l[0],
y=l[1],
hue=l[2],
style=None,
palette=l[3],
hue_order=l[4],
data=l[5]),
lambda l: sns.scatterplot(
x=l[0],
y=l[1],
hue=l[2],
style=None,
palette=l[3],
hue_order=l[4],
data=l[5],
)],12,)
gg.scatter_plot(throughput_dataframe,config,'scatterplot',directory,12)
# swarmplot - process_fraction per throughput_time
config = {
'x': 'throughput_time',
'y': 'process_fraction',
'hue': 'cl_provider',
'palette': provider_color_dict
}
# gg.swarm_plot(throughput_dataframe,config,'process fraction',directory)
config['x'] = 'cl_provider'
gg.box_plot(throughput_dataframe,config,'process fraction',directory)
#
query_avg_process_fraction = """SELECT floor(throughput/1000) as operations_milli,throughput_time,throughput_process_time,
avg((throughput_process_time/throughput_time)*100) as process_fraction, cl_provider from
(select name, cl_provider, total_time, uuid as experiment_uuid from Experiment where name = 'throughput-benchmarking') x
left join Invocation i on i.exp_id=x.experiment_uuid where throughput != 0 group by throughput_time,cl_provider order by cl_provider;"""
avg_process_fraction_df = db.get_raw_query(query_avg_process_fraction)
config = {
'x': 'throughput_time',
'y': 'process_fraction',
'hue': 'cl_provider',
'palette': provider_color_dict
}
gg.lineplot_graph(avg_process_fraction_df, config, 'lineplot process fraction', directory)
gg.relplot(avg_process_fraction_df, config, 'relplot process fraction', directory)
# Produce the graphs by calling chosen graph methos
for category in category_of_graphs:
category()
| 43.778902
| 199
| 0.637168
| 7,718
| 60,590
| 4.713527
| 0.046385
| 0.04783
| 0.015833
| 0.025729
| 0.81
| 0.761813
| 0.713736
| 0.659996
| 0.619341
| 0.586795
| 0
| 0.013687
| 0.214969
| 60,590
| 1,384
| 200
| 43.778902
| 0.751141
| 0.090642
| 0
| 0.53269
| 1
| 0.021436
| 0.300497
| 0.026748
| 0
| 0
| 0
| 0.000723
| 0
| 1
| 0.019293
| false
| 0
| 0.015005
| 0.010718
| 0.04716
| 0.010718
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4ae2d2cfd811bec92e12e8dd7ce4576495f72360
| 181
|
py
|
Python
|
race/serializers.py
|
scottBowles/dnd
|
a1ef333f1a865d51b5426dc4b3493e8437584565
|
[
"MIT"
] | null | null | null |
race/serializers.py
|
scottBowles/dnd
|
a1ef333f1a865d51b5426dc4b3493e8437584565
|
[
"MIT"
] | null | null | null |
race/serializers.py
|
scottBowles/dnd
|
a1ef333f1a865d51b5426dc4b3493e8437584565
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from .models import Race
class RaceSerializer(serializers.ModelSerializer):
class Meta:
model = Race
fields = "__all__"
| 20.111111
| 50
| 0.723757
| 19
| 181
| 6.631579
| 0.736842
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.220994
| 181
| 8
| 51
| 22.625
| 0.893617
| 0
| 0
| 0
| 0
| 0
| 0.038674
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ab19bff99a2e03b4fd2fd7845b69a57f4bc8c45b
| 91
|
py
|
Python
|
design_System/design_System/apps/__init__.py
|
Dante-max/Design_System
|
dcc837588eb72542c6a3ee213b184d49b685bc59
|
[
"MIT"
] | null | null | null |
design_System/design_System/apps/__init__.py
|
Dante-max/Design_System
|
dcc837588eb72542c6a3ee213b184d49b685bc59
|
[
"MIT"
] | null | null | null |
design_System/design_System/apps/__init__.py
|
Dante-max/Design_System
|
dcc837588eb72542c6a3ee213b184d49b685bc59
|
[
"MIT"
] | null | null | null |
# 最是人间留不住,朱颜辞镜花辞树
# -*- coding:utf-8 -*-
# http://127.0.0.1:8000/static/Navimage/Nav1.png
| 18.2
| 48
| 0.648352
| 15
| 91
| 3.933333
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146341
| 0.098901
| 91
| 4
| 49
| 22.75
| 0.573171
| 0.912088
| 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
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| 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ab1db84947b6628898cbbd425acb1dc1db41a5dd
| 144
|
py
|
Python
|
django_gotolong/broker/icidir/isum/admin.py
|
ParikhKadam/gotolong
|
839beb8aa37055a2078eaa289b8ae05b62e8905e
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | 15
|
2019-12-06T16:19:45.000Z
|
2021-08-20T13:22:22.000Z
|
django_gotolong/broker/icidir/isum/admin.py
|
ParikhKadam/gotolong
|
839beb8aa37055a2078eaa289b8ae05b62e8905e
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | 14
|
2020-12-08T10:45:05.000Z
|
2021-09-21T17:23:45.000Z
|
django_gotolong/broker/icidir/isum/admin.py
|
ParikhKadam/gotolong
|
839beb8aa37055a2078eaa289b8ae05b62e8905e
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | 9
|
2020-01-01T03:04:29.000Z
|
2021-04-18T08:42:30.000Z
|
from django.contrib import admin
# Register your models here.
from .models import BrokerIcidirSum
# ...
admin.site.register(BrokerIcidirSum)
| 16
| 36
| 0.784722
| 17
| 144
| 6.647059
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131944
| 144
| 8
| 37
| 18
| 0.904
| 0.208333
| 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
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| 0
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ab1dea57c847afb7221339493a273801da7cf334
| 586
|
py
|
Python
|
students/views/professors.py
|
ovod88/studentsdb
|
ade2cff0eea7a13644a0f708133901457352ff5c
|
[
"MIT"
] | null | null | null |
students/views/professors.py
|
ovod88/studentsdb
|
ade2cff0eea7a13644a0f708133901457352ff5c
|
[
"MIT"
] | null | null | null |
students/views/professors.py
|
ovod88/studentsdb
|
ade2cff0eea7a13644a0f708133901457352ff5c
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
from django.http import HttpResponse
from django.template import RequestContext, loader
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
from ..models.groups import Group
def professors_list(request):
return render(request, 'students/professors_list.html', {})
# def examins_add(request):
# return HttpResponse('<h1>Examin Add Form</h1>')
def professors_edit(request, pid):
return HttpResponse(f'<h1>Edit Professor {pid}</h1>')
# def groups_delete(request, gid):
# return HttpResponse(f'<h1>Delete Group {gid}</h1>')
| 30.842105
| 72
| 0.774744
| 77
| 586
| 5.831169
| 0.454545
| 0.089087
| 0.084633
| 0.093541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.01145
| 0.105802
| 586
| 19
| 73
| 30.842105
| 0.84542
| 0.273038
| 0
| 0
| 0
| 0
| 0.137441
| 0.06872
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.555556
| 0.222222
| 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
|
ab211c1ec3d66d22156a37f9389218b48c6b2876
| 29,739
|
py
|
Python
|
analyzer/tmp.py
|
GPrathap/OpenBCIPython
|
0f5be167fb09d31c15885003eeafec8cdc08dbfa
|
[
"MIT"
] | 1
|
2021-11-07T12:01:08.000Z
|
2021-11-07T12:01:08.000Z
|
analyzer/tmp.py
|
GPrathap/OpenBCIPython
|
0f5be167fb09d31c15885003eeafec8cdc08dbfa
|
[
"MIT"
] | null | null | null |
analyzer/tmp.py
|
GPrathap/OpenBCIPython
|
0f5be167fb09d31c15885003eeafec8cdc08dbfa
|
[
"MIT"
] | 1
|
2020-10-15T08:35:01.000Z
|
2020-10-15T08:35:01.000Z
|
# Visualize an STFT power spectrum
import librosa.display
import matplotlib.pyplot as plt
import numpy as np
# y, sr = librosa.load(librosa.util.example_audio_file())
# plt.figure(figsize=(12, 8))
# number_of_columns = 5
# number_of_rows = 2
#
# D = librosa.stft(y)
# plt.subplot(number_of_columns, number_of_rows, 1)
# librosa.display.specshow(D, y_axis='log')
# plt.colorbar()
# plt.title('Log-frequency power spectrogram')
#
# # Or on a logarithmic scale
# D = np.array(librosa.zero_crossings(y))
# D = np.where(D == True, 10, D)
# D = np.where(D == False, -10, D)
# F=[]
# F.append(D.tolist())
#
# plt.subplot(number_of_columns, number_of_rows, 2)
# librosa.display.specshow(np.array(F))
# plt.colorbar()
# plt.title('Zero-Crossing-Rate')
#
# # Or use a CQT scale
#
# CQT = librosa.cqt(y, sr=sr)
# plt.subplot(number_of_columns, number_of_rows, 3)
# librosa.display.specshow(CQT, y_axis='cqt_note')
# plt.colorbar()
# plt.title('Constant-Q power spectrogram (note)')
#
# plt.subplot(number_of_columns, number_of_rows, 4)
# librosa.display.specshow(CQT, y_axis='cqt_hz')
# plt.colorbar()
# plt.title('Constant-Q power spectrogram (Hz)')
#
# # Draw a chromagram with pitch classes
#
# tonnetz = librosa.feature.tonnetz(y=y, sr=sr)
# plt.subplot(number_of_columns, number_of_rows, 5)
# librosa.display.specshow(tonnetz, y_axis='tonnetz')
# plt.colorbar()
# plt.title('Tonal Centroids (Tonnetz)')
#
# rms = librosa.feature.rmse(y=y)
# plt.subplot(number_of_columns, number_of_rows, 6)
# plt.semilogy(rms.T, label='RMS Energy')
# plt.colorbar()
# plt.title('Root Mean Square Energy')
#
# # Draw time markers automatically
# cent = librosa.feature.spectral_centroid(y=y, sr=sr)
# plt.subplot(number_of_columns, number_of_rows, 7)
# plt.semilogy(cent.T, label='Spectral centroid')
# plt.ylabel('Hz')
# plt.xticks([])
# plt.xlim([0, cent.shape[-1]])
# plt.colorbar()
# plt.title('Spectral centroid')
#
# # Draw a tempogram with BPM markers
# plt.subplot(number_of_columns, number_of_rows, 8)
# Tgram = librosa.feature.tempogram(y=y, sr=sr)
# librosa.display.specshow(Tgram, x_axis='time', y_axis='tempo')
# plt.colorbar()
# plt.title('Tempogram')
# plt.tight_layout()
#
#
# plt.show()
distance = np.array([0.43535290045236669, 0.42654141461933315, 0.41773000255681991, 0.40891999695557635, 0.40011370175151184, 0.39131343663359758, 0.38252154303566893, 0.37374034300584275, 0.36497215917263209, 0.35621801267585679, 0.34747593421300349, 0.33874262441059977, 0.33001335524476083, 0.3212808090951445, 0.31253415076299623, 0.30375467571545162, 0.29279413332463616, 0.28066950263846913, 0.26748473568315551, 0.25329508095999298, 0.23816238276517113, 0.22257064085487269, 0.20686783041366305, 0.19137636417560147, 0.17619725667101774, 0.1613130873077859, 0.14692619820926339, 0.13302604230193524, 0.11948229124115357, 0.10618926662385368, 0.093221416544688129, 0.080759511753566646, 0.068909841268586389, 0.057741789191314258, 0.047528297400111059, 0.038377661783666583, 0.030577245984914559, 0.024229987657192708, 0.019320941451161162, 0.015605339007646183, 0.012769894921379362, 0.010630675021273517, 0.0089375571196414604, 0.0072574453484229992, 0.0056665577901831524, 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possion = np.array([3000, 3005, 3010, 3015, 3020, 3025, 3030, 3035, 3040, 3045, 3050, 3055, 3060, 3065, 3070, 3075, 3080, 3085, 3090, 3095, 3100, 3105, 3110, 3115, 3120, 3125, 3130, 3135, 3140, 3145, 3150, 3155, 3160, 3165, 3170, 3175, 3180, 3185, 3190, 3195, 3200, 3205, 3210, 3215, 3220, 3225, 3230, 3235, 3240, 3245, 3250, 3255, 3260, 3265, 3270, 3275, 3280, 3285, 3290, 3295, 3300, 3305, 3310, 3315, 3320, 3325, 3330, 3335, 3340, 3345, 3350, 3355, 3360, 3365, 3370, 3375, 3380, 3385, 3390, 3395, 3400, 3405, 3410, 3415, 3420, 3425, 3430, 3435, 3440, 3445, 3450, 3455, 3460, 3465, 3470, 3475, 3480, 3485, 3490, 3495, 3500, 3505, 3510, 3515, 3520, 3525, 3530, 3535, 3540, 3545, 3550, 3555, 3560, 3565, 3570, 3575, 3580, 3585, 3590, 3595, 3600, 3605, 3610, 3615, 3620, 3625, 3630, 3635, 3640, 3645, 3650, 3655, 3660, 3665, 3670, 3675, 3680, 3685, 3690, 3695, 3700, 3705, 3710, 3715, 3720, 3725, 3730, 3735, 3740, 3745, 3750, 3755, 3760, 3765, 3770, 3775, 3780, 3785, 3790, 3795, 3800, 3805, 3810, 3815, 3820, 3825, 3830, 3835, 3840, 3845, 3850, 3855, 3860, 3865, 3870, 3875, 3880, 3885, 3890, 3895, 3900, 3905, 3910, 3915, 3920, 3925, 3930, 3935, 3940, 3945, 3950, 3955, 3960, 3965, 3970, 3975, 3980, 3985, 3990, 3995, 4000, 4005, 4010, 4015, 4020, 4025, 4030, 4035, 4040, 4045, 4050, 4055, 4060, 4065, 4070, 4075, 4080, 4085, 4090, 4095, 4100, 4105, 4110, 4115, 4120, 4125, 4130, 4135, 4140, 4145, 4150, 4155, 4160, 4165, 4170, 4175, 4180, 4185, 4190, 4195, 4200, 4205, 4210, 4215, 4220, 4225, 4230, 4235, 4240, 4245, 4250, 4255, 4260, 4265, 4270, 4275, 4280, 4285, 4290, 4295, 4300, 4305, 4310, 4315, 4320, 4325, 4330, 4335, 4340, 4345, 4350, 4355, 4360, 4365, 4370, 4375, 4380, 4385, 4390, 4395, 4400, 4405, 4410, 4415, 4420, 4425, 4430, 4435, 4440, 4445, 4450, 4455, 4460, 4465, 4470, 4475, 4480, 4485, 4490, 4495, 4500, 4505, 4510, 4515, 4520, 4525, 4530, 4535, 4540, 4545, 4550, 4555, 4560, 4565, 4570, 4575, 4580, 4585, 4590, 4595, 4600, 4605, 4610, 4615, 4620, 4625, 4630, 4635, 4640, 4645, 4650, 4655, 4660, 4665, 4670, 4675, 4680, 4685, 4690, 4695, 4700, 4705, 4710, 4715, 4720, 4725, 4730, 4735, 4740, 4745, 4750, 4755, 4760, 4765, 4770, 4775, 4780, 4785, 4790, 4795, 4800, 4805, 4810, 4815, 4820, 4825, 4830, 4835, 4840, 4845, 4850, 4855, 4860, 4865, 4870, 4875, 4880, 4885, 4890, 4895, 4900, 4905, 4910, 4915, 4920, 4925, 4930, 4935, 4940, 4945, 4950, 4955, 4960, 4965, 4970, 4975, 4980, 4985, 4990, 4995, 5000, 5005, 5010, 5015, 5020, 5025, 5030, 5035, 5040, 5045, 5050, 5055, 5060, 5065, 5070, 5075, 5080, 5085, 5090, 5095, 5100, 5105, 5110, 5115, 5120, 5125, 5130, 5135, 5140, 5145, 5150, 5155, 5160, 5165, 5170, 5175, 5180, 5185, 5190, 5195, 5200, 5205, 5210, 5215, 5220, 5225, 5230, 5235, 5240, 5245, 5250, 5255, 5260, 5265, 5270, 5275, 5280, 5285, 5290, 5295, 5300, 5305, 5310, 5315, 5320, 5325, 5330, 5335, 5340, 5345, 5350, 5355, 5360, 5365, 5370, 5375, 5380, 5385, 5390, 5395, 5400, 5405, 5410, 5415, 5420, 5425, 5430, 5435, 5440, 5445, 5450, 5455, 5460, 5465, 5470, 5475, 5480, 5485, 5490, 5495, 5500, 5505, 5510, 5515, 5520, 5525, 5530, 5535, 5540, 5545, 5550, 5555, 5560, 5565, 5570, 5575, 5580, 5585, 5590, 5595, 5600, 5605, 5610, 5615, 5620, 5625, 5630, 5635, 5640, 5645, 5650, 5655, 5660, 5665, 5670, 5675, 5680, 5685, 5690, 5695, 5700, 5705, 5710, 5715, 5720, 5725, 5730, 5735, 5740, 5745, 5750, 5755, 5760, 5765, 5770, 5775, 5780, 5785, 5790, 5795, 5800, 5805, 5810, 5815, 5820, 5825, 5830, 5835, 5840, 5845, 5850, 5855, 5860, 5865, 5870, 5875, 5880, 5885, 5890, 5895, 5900, 5905, 5910, 5915, 5920, 5925, 5930, 5935, 5940, 5945, 5950, 5955, 5960, 5965, 5970, 5975, 5980, 5985, 5990, 5995, 6000, 6005, 6010, 6015, 6020, 6025, 6030, 6035, 6040, 6045, 6050, 6055, 6060, 6065, 6070, 6075, 6080, 6085, 6090, 6095, 6100, 6105, 6110, 6115, 6120, 6125, 6130, 6135, 6140, 6145, 6150, 6155, 6160, 6165, 6170, 6175, 6180, 6185, 6190, 6195, 6200, 6205, 6210, 6215, 6220, 6225, 6230, 6235, 6240, 6245, 6250, 6255, 6260, 6265, 6270, 6275, 6280, 6285, 6290, 6295, 6300, 6305, 6310, 6315, 6320, 6325, 6330, 6335, 6340, 6345, 6350, 6355, 6360, 6365, 6370, 6375, 6380, 6385, 6390, 6395, 6400, 6405, 6410, 6415, 6420, 6425, 6430, 6435, 6440, 6445, 6450, 6455, 6460, 6465, 6470, 6475, 6480, 6485, 6490, 6495, 6500, 6505, 6510, 6515, 6520, 6525, 6530, 6535, 6540, 6545, 6550, 6555, 6560, 6565, 6570, 6575, 6580, 6585, 6590, 6595, 6600, 6605, 6610, 6615, 6620, 6625, 6630, 6635, 6640, 6645, 6650, 6655, 6660, 6665, 6670, 6675, 6680, 6685, 6690, 6695, 6700, 6705, 6710, 6715, 6720, 6725, 6730, 6735, 6740, 6745, 6750, 6755, 6760, 6765, 6770, 6775, 6780, 6785, 6790, 6795, 6800, 6805, 6810, 6815, 6820, 6825, 6830, 6835, 6840, 6845, 6850, 6855, 6860, 6865, 6870, 6875, 6880, 6885, 6890, 6895, 6900, 6905, 6910, 6915, 6920, 6925, 6930, 6935, 6940, 6945, 6950, 6955, 6960, 6965, 6970, 6975, 6980, 6985, 6990, 6995, 7000, 7005, 7010, 7015, 7020, 7025, 7030, 7035, 7040, 7045, 7050, 7055, 7060, 7065, 7070, 7075, 7080, 7085, 7090, 7095, 7100, 7105, 7110, 7115, 7120, 7125, 7130, 7135, 7140, 7145, 7150, 7155, 7160, 7165, 7170, 7175, 7180, 7185, 7190, 7195, 7200, 7205, 7210, 7215, 7220, 7225, 7230, 7235, 7240, 7245, 7250, 7255, 7260, 7265, 7270, 7275, 7280, 7285, 7290, 7295, 7300, 7305, 7310, 7315, 7320, 7325, 7330, 7335, 7340, 7345, 7350, 7355, 7360, 7365, 7370, 7375, 7380, 7385, 7390, 7395, 7400, 7405, 7410, 7415, 7420, 7425, 7430, 7435, 7440, 7445, 7450, 7455, 7460, 7465, 7470, 7475, 7480, 7485, 7490, 7495, 7500, 7505, 7510, 7515, 7520, 7525, 7530, 7535, 7540, 7545, 7550, 7555, 7560, 7565, 7570, 7575, 7580, 7585, 7590, 7595, 7600, 7605, 7610, 7615, 7620, 7625, 7630, 7635, 7640, 7645, 7650, 7655, 7660, 7665, 7670, 7675, 7680, 7685, 7690, 7695, 7700, 7705, 7710, 7715, 7720, 7725, 7730, 7735, 7740, 7745, 7750, 7755, 7760, 7765, 7770, 7775, 7780, 7785, 7790, 7795, 7800, 7805, 7810, 7815, 7820, 7825, 7830, 7835, 7840, 7845, 7850, 7855, 7860, 7865, 7870, 7875, 7880, 7885, 7890, 7895, 7900, 7905, 7910, 7915, 7920, 7925, 7930, 7935, 7940, 7945, 7950, 7955, 7960, 7965, 7970, 7975, 7980, 7985, 7990, 7995])
plt.plot(possion, distance)
plt.show()
0.0881659076708
0.0749462847822
0.0625061816364
0.0512740922866
0.0414091664901
0.0330504482696
0.0261112501876
0.0203759258579
0.0156153477831
0.0115580054158
0.00806045469524
0.00516485884949
0.00287576153205
0.00126080586026
0.000319452887888
0.0
0.000302155880928
| 285.951923
| 21,221
| 0.808635
| 3,385
| 29,739
| 7.089808
| 0.627179
| 0.006
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| 0.006
| 0.019542
| 0.019542
| 0.019542
| 0.016792
| 0.0085
| 0.005334
| 0
| 0.817692
| 0.076667
| 29,739
| 103
| 21,222
| 288.728155
| 0.056302
| 0.065873
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|
0
| 4
|
ab270fdecd61a98f26007cb051d00aa309341018
| 194
|
py
|
Python
|
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
|
JulianoGianlupi/nh-cc3d-4x-base-tool
|
c0f4aceebd4c5bf3ec39e831ef851e419b161259
|
[
"CC0-1.0"
] | null | null | null |
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
|
JulianoGianlupi/nh-cc3d-4x-base-tool
|
c0f4aceebd4c5bf3ec39e831ef851e419b161259
|
[
"CC0-1.0"
] | null | null | null |
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
|
JulianoGianlupi/nh-cc3d-4x-base-tool
|
c0f4aceebd4c5bf3ec39e831ef851e419b161259
|
[
"CC0-1.0"
] | 1
|
2021-02-26T21:50:29.000Z
|
2021-02-26T21:50:29.000Z
|
from cc3d import CompuCellSetup
from .CellDistanceSteppables import CellDistanceSteppable
CompuCellSetup.register_steppable(steppable=CellDistanceSteppable(frequency=1))
CompuCellSetup.run()
| 24.25
| 79
| 0.876289
| 17
| 194
| 9.941176
| 0.647059
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| 0.06701
| 194
| 7
| 80
| 27.714286
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|
0
| 4
|
ab31e6d9af6c7a8a6fd6dc55027a525fee820e24
| 228
|
py
|
Python
|
serif/theory/segment.py
|
BBN-E/ZS4IE
|
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
|
[
"Apache-2.0"
] | 7
|
2022-03-24T11:04:08.000Z
|
2022-03-31T17:12:46.000Z
|
serif/theory/segment.py
|
BBN-E/ZS4IE
|
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
|
[
"Apache-2.0"
] | null | null | null |
serif/theory/segment.py
|
BBN-E/ZS4IE
|
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
|
[
"Apache-2.0"
] | null | null | null |
from serif.theory.serif_theory import SerifTheory
from serif.xmlio import _ChildTheoryElementList
class Segment(SerifTheory):
attributes = _ChildTheoryElementList('Attribute')
fields = _ChildTheoryElementList('Field')
| 28.5
| 53
| 0.815789
| 21
| 228
| 8.666667
| 0.619048
| 0.098901
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114035
| 228
| 7
| 54
| 32.571429
| 0.90099
| 0
| 0
| 0
| 0
| 0
| 0.061404
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ab3574c21161f36bbc075ea698a34b4a95d0ebab
| 397
|
py
|
Python
|
srcs/interpretator/context.py
|
pomponchik/computor_v2
|
742b3f3b47c8d46806b2f733b4ec07ae63a23f00
|
[
"MIT"
] | null | null | null |
srcs/interpretator/context.py
|
pomponchik/computor_v2
|
742b3f3b47c8d46806b2f733b4ec07ae63a23f00
|
[
"MIT"
] | 2
|
2022-01-28T07:02:15.000Z
|
2022-01-28T07:04:33.000Z
|
srcs/interpretator/context.py
|
pomponchik/expert_system
|
47d183c36474869dd1beccde8f2b6d509b5a8bcc
|
[
"MIT"
] | null | null | null |
class Context:
def __init__(self):
self.data = {}
def __getitem__(self, key):
return self.data.get(self.convert_key(key), None)
def __setitem__(self, key, value):
self.data[self.convert_key(key)] = value
def get(self, key, default):
return self.data.get(self.convert_key(key), default)
def convert_key(self, key):
return key.lower()
| 24.8125
| 60
| 0.627204
| 54
| 397
| 4.314815
| 0.296296
| 0.137339
| 0.180258
| 0.218884
| 0.291845
| 0.291845
| 0.291845
| 0.291845
| 0
| 0
| 0
| 0
| 0.241814
| 397
| 15
| 61
| 26.466667
| 0.774086
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.454545
| false
| 0
| 0
| 0.272727
| 0.818182
| 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
|
db59f047a069feaef47cc2e1dd9486af6e1a4a55
| 444
|
py
|
Python
|
mysite/MCQ/models.py
|
PUNITKUMARGAUTAM/mydjango
|
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
|
[
"MIT"
] | null | null | null |
mysite/MCQ/models.py
|
PUNITKUMARGAUTAM/mydjango
|
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
|
[
"MIT"
] | null | null | null |
mysite/MCQ/models.py
|
PUNITKUMARGAUTAM/mydjango
|
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
|
[
"MIT"
] | null | null | null |
from django.db import models
# Create your models here.
class Quiz(models.Model):
Qustno=models.CharField(max_length = 300)
Qustn = models.CharField(max_length = 200)
OptA = models.CharField(max_length = 200)
optB = models.CharField(max_length = 200)
OptC = models.CharField(max_length = 200)
OptD = models.CharField(max_length = 200)
RightAns=models.IntegerField()
class Meta:
db_table="questions"
| 29.6
| 46
| 0.70045
| 57
| 444
| 5.333333
| 0.473684
| 0.296053
| 0.355263
| 0.473684
| 0.444079
| 0
| 0
| 0
| 0
| 0
| 0
| 0.050562
| 0.198198
| 444
| 15
| 47
| 29.6
| 0.803371
| 0.054054
| 0
| 0
| 0
| 0
| 0.02148
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.090909
| 0
| 0.909091
| 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
|
db5b682a834f3daffca8d2d1292a349c02e706f6
| 6,230
|
py
|
Python
|
tests/test_utility.py
|
ccarocean/python-rads
|
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
|
[
"MIT"
] | null | null | null |
tests/test_utility.py
|
ccarocean/python-rads
|
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
|
[
"MIT"
] | 3
|
2019-06-27T19:00:35.000Z
|
2020-03-07T09:43:24.000Z
|
tests/test_utility.py
|
ccarocean/python-rads
|
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
|
[
"MIT"
] | 1
|
2019-05-31T01:04:26.000Z
|
2019-05-31T01:04:26.000Z
|
import io
from datetime import datetime
import pytest # type: ignore
from rads.constants import EPOCH
from rads.utility import (
contains_sublist,
datetime_to_timestamp,
delete_sublist,
ensure_open,
fortran_float,
isio,
merge_sublist,
timestamp_to_datetime,
xor,
)
def test_ensure_open_closeio_default():
file = io.StringIO("content")
with ensure_open(file) as f:
assert not f.closed
assert not f.closed
def test_ensure_open_closeio_true():
file = io.StringIO("content")
with ensure_open(file, closeio=True) as f:
assert not f.closed
assert f.closed
def test_ensure_open_closeio_false():
file = io.StringIO("content")
with ensure_open(file, closeio=False) as f:
assert not f.closed
assert not f.closed
def test_isio(mocker):
assert isio(io.StringIO("content"))
assert not isio("string is not io")
m = mocker.Mock()
m.read.return_value = "duck typing not accepted"
assert not isio(m)
def test_isio_read(mocker):
assert isio(io.StringIO("content"), read=True)
assert not isio("string is not io", read=True)
m = mocker.Mock(spec=["read"])
m.read.return_value = "duck typing is accepted"
assert isio(m, read=True)
m = mocker.Mock(spec=["write"])
m.write.return_value = "duck typing is accepted"
assert not isio(m, read=True)
def test_isio_write(mocker):
assert isio(io.StringIO("content"), write=True)
assert not isio("string is not io", write=True)
m = mocker.Mock(spec=["read"])
m.read.return_value = "duck typing is accepted"
assert not isio(m, write=True)
m = mocker.Mock(spec=["write"])
m.write.return_value = "duck typing is accepted"
assert isio(m, write=True)
def test_xor():
assert not xor(True, True)
assert xor(True, False)
assert xor(False, True)
assert not xor(False, False)
def test_contains_sublist():
assert contains_sublist([1, 2, 3, 4], [1, 2])
assert contains_sublist([1, 2, 3, 4], [2, 3])
assert contains_sublist([1, 2, 3, 4], [3, 4])
assert contains_sublist([1, 2, 3, 4], [1, 2, 3, 4])
assert not contains_sublist([1, 2, 3, 4], [2, 1])
assert not contains_sublist([1, 2, 3, 4], [3, 2])
assert not contains_sublist([1, 2, 3, 4], [4, 3])
# while the empty list is technically a sublist of any list for this
# function [] is never a sublist
assert not contains_sublist([1, 2, 3, 4], [])
def test_merge_sublist():
assert merge_sublist([1, 2, 3, 4], []) == [1, 2, 3, 4]
assert merge_sublist([1, 2, 3, 4], [1, 2]) == [1, 2, 3, 4]
assert merge_sublist([1, 2, 3, 4], [2, 3]) == [1, 2, 3, 4]
assert merge_sublist([1, 2, 3, 4], [3, 4]) == [1, 2, 3, 4]
assert merge_sublist([1, 2, 3, 4], [0, 1]) == [1, 2, 3, 4, 0, 1]
assert merge_sublist([1, 2, 3, 4], [4, 5]) == [1, 2, 3, 4, 4, 5]
assert merge_sublist([1, 2, 3, 4], [1, 1]) == [1, 2, 3, 4, 1, 1]
def test_delete_sublist():
assert delete_sublist([1, 2, 3, 4], []) == [1, 2, 3, 4]
assert delete_sublist([1, 2, 3, 4], [1, 2]) == [3, 4]
assert delete_sublist([1, 2, 3, 4], [2, 3]) == [1, 4]
assert delete_sublist([1, 2, 3, 4], [3, 4]) == [1, 2]
assert delete_sublist([1, 2, 3, 4], [0, 1]) == [1, 2, 3, 4]
assert delete_sublist([1, 2, 3, 4], [4, 5]) == [1, 2, 3, 4]
assert delete_sublist([1, 2, 3, 4], [1, 1]) == [1, 2, 3, 4]
def test_fortran_float():
assert fortran_float("3.14e10") == pytest.approx(3.14e10)
assert fortran_float("3.14E10") == pytest.approx(3.14e10)
assert fortran_float("3.14d10") == pytest.approx(3.14e10)
assert fortran_float("3.14D10") == pytest.approx(3.14e10)
assert fortran_float("3.14e+10") == pytest.approx(3.14e10)
assert fortran_float("3.14E+10") == pytest.approx(3.14e10)
assert fortran_float("3.14d+10") == pytest.approx(3.14e10)
assert fortran_float("3.14D+10") == pytest.approx(3.14e10)
assert fortran_float("3.14e-10") == pytest.approx(3.14e-10)
assert fortran_float("3.14E-10") == pytest.approx(3.14e-10)
assert fortran_float("3.14d-10") == pytest.approx(3.14e-10)
assert fortran_float("3.14D-10") == pytest.approx(3.14e-10)
assert fortran_float("3.14+100") == pytest.approx(3.14e100)
assert fortran_float("3.14-100") == pytest.approx(3.14e-100)
with pytest.raises(ValueError):
fortran_float("not a float")
def test_datetime_to_epoch():
epoch = datetime(2000, 1, 1, 0, 0, 0)
assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 0), epoch=epoch) == 0.0
assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 1), epoch=epoch) == 1.0
assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 1, 0), epoch=epoch) == 60.0
assert datetime_to_timestamp(datetime(2000, 1, 1, 1, 0, 0), epoch=epoch) == 3600.0
def test_datetime_to_epoch_with_default_epoch():
assert datetime_to_timestamp(
datetime(2000, 1, 1, 0, 0, 0)
) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 0), epoch=EPOCH)
assert datetime_to_timestamp(
datetime(2000, 1, 1, 0, 0, 1)
) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 1), epoch=EPOCH)
assert datetime_to_timestamp(
datetime(2000, 1, 1, 0, 1, 0)
) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 1, 0), epoch=EPOCH)
assert datetime_to_timestamp(
datetime(2000, 1, 1, 1, 0, 0)
) == datetime_to_timestamp(datetime(2000, 1, 1, 1, 0, 0), epoch=EPOCH)
def test_epoch_to_datetime():
epoch = datetime(2000, 1, 1, 0, 0, 0)
assert timestamp_to_datetime(0.0, epoch=epoch) == datetime(2000, 1, 1, 0, 0, 0)
assert timestamp_to_datetime(1.0, epoch=epoch) == datetime(2000, 1, 1, 0, 0, 1)
assert timestamp_to_datetime(60.0, epoch=epoch) == datetime(2000, 1, 1, 0, 1, 0)
assert timestamp_to_datetime(3600.0, epoch=epoch) == datetime(2000, 1, 1, 1, 0, 0)
def test_epoch_to_datetime_with_default_epoch():
assert timestamp_to_datetime(0.0) == timestamp_to_datetime(0.0, epoch=EPOCH)
assert timestamp_to_datetime(1.0) == timestamp_to_datetime(1.0, epoch=EPOCH)
assert timestamp_to_datetime(60.0) == timestamp_to_datetime(60.0, epoch=EPOCH)
assert timestamp_to_datetime(3600.0) == timestamp_to_datetime(3600.0, epoch=EPOCH)
| 37.53012
| 86
| 0.643981
| 1,024
| 6,230
| 3.775391
| 0.081055
| 0.019659
| 0.02716
| 0.036213
| 0.835748
| 0.801086
| 0.745991
| 0.627522
| 0.560269
| 0.494309
| 0
| 0.10715
| 0.194061
| 6,230
| 165
| 87
| 37.757576
| 0.662816
| 0.017657
| 0
| 0.167939
| 0
| 0
| 0.056082
| 0
| 0
| 0
| 0
| 0
| 0.557252
| 1
| 0.114504
| false
| 0
| 0.038168
| 0
| 0.152672
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
db63d7ed6fba86eb8197753f23124f154ca4fa78
| 250
|
py
|
Python
|
slickqaweb/model/resultReference.py
|
slickqa/slickqaweb
|
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
|
[
"Apache-2.0"
] | null | null | null |
slickqaweb/model/resultReference.py
|
slickqa/slickqaweb
|
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
|
[
"Apache-2.0"
] | 9
|
2015-12-17T18:24:17.000Z
|
2018-09-28T16:00:30.000Z
|
slickqaweb/model/resultReference.py
|
slickqa/slickqaweb
|
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
|
[
"Apache-2.0"
] | 2
|
2015-12-17T18:45:20.000Z
|
2018-02-01T21:05:13.000Z
|
from mongoengine import *
from .buildReference import BuildReference
class ResultReference(EmbeddedDocument):
resultId = ObjectIdField()
status = StringField()
recorded = DateTimeField()
build = EmbeddedDocumentField(BuildReference)
| 27.777778
| 49
| 0.776
| 19
| 250
| 10.210526
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.156
| 250
| 9
| 49
| 27.777778
| 0.919431
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.285714
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
db916c5f423bccd241aa08c3611f223d862ad934
| 7,010
|
py
|
Python
|
pysnmp-with-texts/DELL-WLAN-MIB.py
|
agustinhenze/mibs.snmplabs.com
|
1fc5c07860542b89212f4c8ab807057d9a9206c7
|
[
"Apache-2.0"
] | 8
|
2019-05-09T17:04:00.000Z
|
2021-06-09T06:50:51.000Z
|
pysnmp-with-texts/DELL-WLAN-MIB.py
|
agustinhenze/mibs.snmplabs.com
|
1fc5c07860542b89212f4c8ab807057d9a9206c7
|
[
"Apache-2.0"
] | 4
|
2019-05-31T16:42:59.000Z
|
2020-01-31T21:57:17.000Z
|
pysnmp-with-texts/DELL-WLAN-MIB.py
|
agustinhenze/mibs.snmplabs.com
|
1fc5c07860542b89212f4c8ab807057d9a9206c7
|
[
"Apache-2.0"
] | 10
|
2019-04-30T05:51:36.000Z
|
2022-02-16T03:33:41.000Z
|
#
# PySNMP MIB module DELL-WLAN-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/DELL-WLAN-MIB
# Produced by pysmi-0.3.4 at Wed May 1 12:38:17 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
OctetString, ObjectIdentifier, Integer = mibBuilder.importSymbols("ASN1", "OctetString", "ObjectIdentifier", "Integer")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ValueSizeConstraint, ValueRangeConstraint, ConstraintsUnion, SingleValueConstraint, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueSizeConstraint", "ValueRangeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ConstraintsIntersection")
ModuleCompliance, ObjectGroup, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "ObjectGroup", "NotificationGroup")
Counter64, MibScalar, MibTable, MibTableRow, MibTableColumn, snmpModules, TimeTicks, ObjectIdentity, ModuleIdentity, Unsigned32, iso, enterprises, Integer32, IpAddress, NotificationType, MibIdentifier, Counter32, Gauge32, Bits = mibBuilder.importSymbols("SNMPv2-SMI", "Counter64", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "snmpModules", "TimeTicks", "ObjectIdentity", "ModuleIdentity", "Unsigned32", "iso", "enterprises", "Integer32", "IpAddress", "NotificationType", "MibIdentifier", "Counter32", "Gauge32", "Bits")
DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention")
dell = MibIdentifier((1, 3, 6, 1, 4, 1, 674))
powerConnect = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895))
w_650 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5001)).setLabel("w-650")
w_651 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5002)).setLabel("w-651")
w_3200 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5003)).setLabel("w-3200")
w_3400 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5004)).setLabel("w-3400")
w_3600 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5005)).setLabel("w-3600")
w_AP92 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5006)).setLabel("w-AP92")
w_AP93 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5007)).setLabel("w-AP93")
w_AP105 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5008)).setLabel("w-AP105")
w_AP124 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5009)).setLabel("w-AP124")
w_AP125 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5010)).setLabel("w-AP125")
w_RAP5 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5011)).setLabel("w-RAP5")
w_RAP5WN = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5012)).setLabel("w-RAP5WN")
w_RAP2 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5013)).setLabel("w-RAP2")
w_620 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5014)).setLabel("w-620")
w_6000M3 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5015)).setLabel("w-6000M3")
w_7210 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5027)).setLabel("w-7210")
w_7220 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5028)).setLabel("w-7220")
w_7240 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5029)).setLabel("w-7240")
w_7005 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5043)).setLabel("w-7005")
w_7010 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5044)).setLabel("w-7010")
w_7030 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5049)).setLabel("w-7030")
w_7205 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5050)).setLabel("w-7205")
w_7024 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5051)).setLabel("w-7024")
w_AP68 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5016)).setLabel("w-AP68")
w_AP68P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5017)).setLabel("w-AP68P")
w_AP175P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5018)).setLabel("w-AP175P")
w_AP175AC = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5019)).setLabel("w-AP175AC")
w_AP175DC = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5020)).setLabel("w-AP175DC")
w_AP134 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5021)).setLabel("w-AP134")
w_AP135 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5022)).setLabel("w-AP135")
w_AP93H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5023)).setLabel("w-AP93H")
w_AP104 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5024)).setLabel("w-AP104")
w_IAP3WN = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5025)).setLabel("w-IAP3WN")
w_IAP3WNP = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5026)).setLabel("w-IAP3WNP")
w_IAP108 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5031)).setLabel("w-IAP108")
w_IAP109 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5032)).setLabel("w-IAP109")
w_AP224 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5033)).setLabel("w-AP224")
w_AP225 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5034)).setLabel("w-AP225")
w_IAP155 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5035)).setLabel("w-IAP155")
w_IAP155P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5036)).setLabel("w-IAP155P")
w_AP114 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5037)).setLabel("w-AP114")
w_AP115 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5038)).setLabel("w-AP115")
w_AP274 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5039)).setLabel("w-AP274")
w_AP275 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5040)).setLabel("w-AP275")
w_AP277 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5052)).setLabel("w-AP277")
w_AP228 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5054)).setLabel("w-AP228")
w_AP103 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5045)).setLabel("w-AP103")
w_AP103H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5046)).setLabel("w-AP103H")
w_AP204 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5047)).setLabel("w-AP204")
w_AP205 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5048)).setLabel("w-AP205")
w_AP205H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5055)).setLabel("w-AP205H")
w_AP214 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5041)).setLabel("w-AP214")
w_AP215 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5042)).setLabel("w-AP215")
mibBuilder.exportSymbols("DELL-WLAN-MIB", w_AP175P=w_AP175P, w_AP68P=w_AP68P, w_AP205=w_AP205, w_7240=w_7240, w_AP225=w_AP225, powerConnect=powerConnect, w_6000M3=w_6000M3, w_7030=w_7030, w_7024=w_7024, w_AP224=w_AP224, w_3200=w_3200, w_AP134=w_AP134, w_7220=w_7220, w_AP124=w_AP124, w_AP204=w_AP204, w_3600=w_3600, w_AP215=w_AP215, w_AP92=w_AP92, w_7005=w_7005, w_AP93H=w_AP93H, w_AP105=w_AP105, w_AP103H=w_AP103H, w_620=w_620, w_AP104=w_AP104, w_IAP155=w_IAP155, w_RAP2=w_RAP2, w_AP115=w_AP115, w_RAP5=w_RAP5, w_AP125=w_AP125, w_IAP109=w_IAP109, w_IAP155P=w_IAP155P, w_AP214=w_AP214, w_AP135=w_AP135, w_AP228=w_AP228, w_IAP108=w_IAP108, w_7210=w_7210, w_IAP3WN=w_IAP3WN, w_AP93=w_AP93, dell=dell, w_IAP3WNP=w_IAP3WNP, w_650=w_650, w_AP68=w_AP68, w_651=w_651, w_AP277=w_AP277, w_AP274=w_AP274, w_AP205H=w_AP205H, w_AP275=w_AP275, w_3400=w_3400, w_7010=w_7010, w_AP175AC=w_AP175AC, w_AP175DC=w_AP175DC, w_AP114=w_AP114, w_RAP5WN=w_RAP5WN, w_7205=w_7205, w_AP103=w_AP103)
| 100.142857
| 970
| 0.694294
| 1,189
| 7,010
| 3.95963
| 0.170732
| 0.163551
| 0.175234
| 0.186916
| 0.437128
| 0.395072
| 0.395072
| 0.395072
| 0.390399
| 0.080714
| 0
| 0.268582
| 0.111412
| 7,010
| 69
| 971
| 101.594203
| 0.487237
| 0.045649
| 0
| 0
| 0
| 0
| 0.127526
| 0.006586
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.096774
| 0
| 0.096774
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
db92df0d69a2d192ad0f19f8107908c80e36c29e
| 149
|
py
|
Python
|
example/models.py
|
hbielenia/csv-mapper
|
1f39bb2f02395be2ca66654030cffe2c5790808e
|
[
"Unlicense"
] | null | null | null |
example/models.py
|
hbielenia/csv-mapper
|
1f39bb2f02395be2ca66654030cffe2c5790808e
|
[
"Unlicense"
] | null | null | null |
example/models.py
|
hbielenia/csv-mapper
|
1f39bb2f02395be2ca66654030cffe2c5790808e
|
[
"Unlicense"
] | null | null | null |
from .fields import *
from .mapper import Model
class Person(Model):
name = StringField()
height_cm = IntegerField()
salary = DecimalField()
| 16.555556
| 28
| 0.718121
| 17
| 149
| 6.235294
| 0.823529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181208
| 149
| 8
| 29
| 18.625
| 0.868852
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
db9c76e4cba1c2f10f2b00a27b67c15c23397f9a
| 649
|
py
|
Python
|
2017/day01/test_captcha.py
|
kgaughan/aoc
|
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
|
[
"BSD-3-Clause"
] | null | null | null |
2017/day01/test_captcha.py
|
kgaughan/aoc
|
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
|
[
"BSD-3-Clause"
] | null | null | null |
2017/day01/test_captcha.py
|
kgaughan/aoc
|
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python3
import unittest
import captcha
class CaptchaTests(unittest.TestCase):
def test_part1(self):
self.assertEqual(captcha.captcha1('1122'), 3)
self.assertEqual(captcha.captcha1('1111'), 4)
self.assertEqual(captcha.captcha1('1234'), 0)
self.assertEqual(captcha.captcha1('91212129'), 9)
def test_part2(self):
self.assertEqual(captcha.captcha2('1212'), 6)
self.assertEqual(captcha.captcha2('1221'), 0)
self.assertEqual(captcha.captcha2('123425'), 4)
self.assertEqual(captcha.captcha2('123123'), 12)
self.assertEqual(captcha.captcha2('12131415'), 4)
| 30.904762
| 57
| 0.674884
| 74
| 649
| 5.891892
| 0.445946
| 0.309633
| 0.454128
| 0.344037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131086
| 0.177196
| 649
| 20
| 58
| 32.45
| 0.685393
| 0.032357
| 0
| 0
| 0
| 0
| 0.076555
| 0
| 0
| 0
| 0
| 0
| 0.642857
| 1
| 0.142857
| false
| 0
| 0.142857
| 0
| 0.357143
| 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
|
918a513549337d8cbfd0e41813480d00a393f8d5
| 217
|
py
|
Python
|
Files/Python/puntajes_03/puntajes_03.py
|
Souto751/isft151-base-de-datos
|
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
|
[
"MIT"
] | null | null | null |
Files/Python/puntajes_03/puntajes_03.py
|
Souto751/isft151-base-de-datos
|
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
|
[
"MIT"
] | null | null | null |
Files/Python/puntajes_03/puntajes_03.py
|
Souto751/isft151-base-de-datos
|
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
|
[
"MIT"
] | null | null | null |
import puntajes_csv
valores = [("Pepe", 108, "4:16"), ("Juana", 2315, "8:42")]
puntajes_csv.guardar_puntajes("puntajes.dat", valores)
recuperado = puntajes_csv.recuperar_puntajes("puntajes.dat")
print(recuperado)
| 36.166667
| 60
| 0.732719
| 28
| 217
| 5.5
| 0.607143
| 0.214286
| 0.246753
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.06599
| 0.092166
| 217
| 6
| 61
| 36.166667
| 0.715736
| 0
| 0
| 0
| 0
| 0
| 0.188073
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0.2
| 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
|
91bd074c51494e76a866a7ffdbc55fc0f1c0f09b
| 68
|
py
|
Python
|
phonon_tools_VASP/__init__.py
|
benwmcdowell/phonon_tools_VASP
|
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
|
[
"MIT"
] | 2
|
2021-03-19T16:03:52.000Z
|
2021-03-24T03:24:16.000Z
|
phonon_tools_VASP/__init__.py
|
benwmcdowell/phonon_tools_VASP
|
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
|
[
"MIT"
] | null | null | null |
phonon_tools_VASP/__init__.py
|
benwmcdowell/phonon_tools_VASP
|
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
|
[
"MIT"
] | null | null | null |
### methods for analyzing and manipulating phonon modes in VASP ###
| 34
| 67
| 0.75
| 9
| 68
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161765
| 68
| 1
| 68
| 68
| 0.894737
| 0.867647
| 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
|
91cceba0c7b32fb937b692f79ad3461f1cfed8d7
| 68
|
py
|
Python
|
testping.py
|
operationzombie/apache-base
|
d1fe8edd665728ab4437f162236a3e865a94942c
|
[
"MIT"
] | null | null | null |
testping.py
|
operationzombie/apache-base
|
d1fe8edd665728ab4437f162236a3e865a94942c
|
[
"MIT"
] | null | null | null |
testping.py
|
operationzombie/apache-base
|
d1fe8edd665728ab4437f162236a3e865a94942c
|
[
"MIT"
] | null | null | null |
import serial, time
ser2 = serial.Serial('COM2')
print ser2.read(5)
| 17
| 28
| 0.735294
| 11
| 68
| 4.545455
| 0.727273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 0.117647
| 68
| 4
| 29
| 17
| 0.766667
| 0
| 0
| 0
| 0
| 0
| 0.057971
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.333333
| null | null | 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
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