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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
320953865bed45267b57cc069f7cd39931e80f20
| 5,794
|
py
|
Python
|
scripts/endpoints.py
|
bridgedragon/NodeChain
|
2554eb7fa7f677037a800eca43e58e1ab15c41a6
|
[
"MIT"
] | null | null | null |
scripts/endpoints.py
|
bridgedragon/NodeChain
|
2554eb7fa7f677037a800eca43e58e1ab15c41a6
|
[
"MIT"
] | null | null | null |
scripts/endpoints.py
|
bridgedragon/NodeChain
|
2554eb7fa7f677037a800eca43e58e1ab15c41a6
|
[
"MIT"
] | null | null | null |
import requests
import logger
import utils
import json
ADD_CURRENCY = "addcoin"
GET_CURRENCY = "getcoin"
UPDATE_CURRENCY = "updatecoin"
REMOVE_CURRENCY = "removecoin"
def addApi(args, token, network, port, defaultConfig=True):
# Getting API information
status_code, response = getApi(args, token, network, port)
# Check if API is registered
if status_code != 200:
logger.printError(f"Request to client could not be completed: {status_code}", verbosity=args.verbose)
response = response.json()
if response["success"] is True:
logger.printError(f"API {token} {network} is already registered: {response}", verbosity=args.verbose)
return
# Get config file
if utils.checkCurrencyInConfig(utils.CUSTOM_CONFIG, token, network):
filename = utils.CUSTOM_CONFIG
elif utils.checkCurrencyInConfig(utils.DEFAULT_CONFIG, token, network):
filename = utils.DEFAULT_CONFIG
payload = utils.formatAddPayload(args, token, network, filename, defaultConfig)
headers = {
'Content-Type': 'application/json'
}
if args.verbose:
logger.printInfo(f"Request payload: {payload}", verbosity=args.verbose)
try:
req = requests.post(
url=f"http://localhost:{port}/admin/{ADD_CURRENCY}",
json=payload,
headers=headers
)
if args.verbose:
logger.printInfo(f"Request sent to http://localhost:{port}/admin/{ADD_CURRENCY}: {req.json()}", verbosity=args.verbose)
return req
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
return e
def getApi(args, token, network, port):
payload = {
"coin": token,
"network": network,
}
headers = {
'Content-Type': 'application/json'
}
if args.verbose:
logger.printInfo(f"Request payload: {payload}", verbosity=args.verbose)
try:
req = requests.post(
url=f"http://localhost:{port}/admin/{GET_CURRENCY}",
json=payload,
headers=headers
)
if args.verbose:
logger.printInfo(f"Request sent to http://localhost:{port}/admin/{GET_CURRENCY}: {req.json()}", verbosity=args.verbose)
return req.status_code, req
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
return e
def removeApi(args, token, network, port):
# Getting API information
try:
status_code, response = getApi(args, token, network, port)
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
# Check if API is not registered
if status_code != 200:
logger.printError(f"Request to client could not be completed: {status_code}", verbosity=args.verbose)
response = response.json()
if response["success"] is False:
logger.printError(f"Can't remove the API {token} {network} from the connector. Is not registered: {response}", verbosity=args.verbose)
return
payload = {
"coin": token,
"network": network,
}
headers = {
'Content-Type': 'application/json'
}
if args.verbose:
logger.printInfo(f"Request payload: {payload}", verbosity=args.verbose)
try:
req = requests.post(
url=f"http://localhost:{port}/admin/{REMOVE_CURRENCY}",
json=payload,
headers=headers
)
if args.verbose:
logger.printInfo(f"Request sent to http://localhost:{port}/admin/{REMOVE_CURRENCY}: {req.json()}", verbosity=args.verbose)
return req
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
return e
def updateApi(args, token, network, port):
# Getting API information
try:
status_code, response = getApi(args, token, network, port)
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
# Check if API is not registered
if status_code != 200:
logger.printError(f"Request to client could not be completed: {status_code}", verbosity=args.verbose)
response = response.json()
if response["success"] is False:
logger.printError(f"Can't update the API {token} {network} from the connector. Is not registered: {response}", verbosity=args.verbose)
return
configurable = utils.getTokenConfiguration(token, network)
userData = []
configurableData = []
for configOption in configurable:
if utils.queryYesNo(f"Do you want to update the {configOption}?"):
configurableData.append(configOption)
userData.append(utils.queryConfigurable(args, f"Please, introduce a value for {configOption}: ", configOption))
config = dict(zip(configurableData, userData))
payload = {
"coin": token,
"network": network,
"config": config
}
headers = {
'Content-Type': 'application/json'
}
if args.verbose:
logger.printInfo(f"Request payload: {payload}", verbosity=args.verbose)
try:
req = requests.post(
url=f"http://localhost:{port}/admin/{UPDATE_CURRENCY}",
json=payload,
headers=headers
)
if args.verbose:
logger.printInfo(f"Request sent to http://localhost:{port}/admin/{UPDATE_CURRENCY}: {req.json()}", verbosity=args.verbose)
return req
except Exception as e:
logger.printError(f"Request to client could not be completed: {str(e)}", verbosity=args.verbose)
return e
| 34.694611
| 142
| 0.645668
| 675
| 5,794
| 5.503704
| 0.152593
| 0.082907
| 0.107672
| 0.076985
| 0.78358
| 0.751817
| 0.730283
| 0.730283
| 0.706595
| 0.706595
| 0
| 0.002044
| 0.240076
| 5,794
| 166
| 143
| 34.903614
| 0.841699
| 0.030376
| 0
| 0.62406
| 0
| 0.015038
| 0.281105
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.030075
| false
| 0
| 0.030075
| 0
| 0.142857
| 0.150376
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 5
|
5c823c49fe45b8c1ffcdb8bc5c6179a820500813
| 39
|
py
|
Python
|
wikdict_web/__main__.py
|
hartwork/wikdict-web
|
3bd80b5ac116aa4bf761e3d04bbcf1a84c240473
|
[
"MIT"
] | 7
|
2020-07-20T22:36:26.000Z
|
2022-02-06T01:28:22.000Z
|
wikdict_web/__main__.py
|
karlb/wikdict-web
|
200c158cae3bf68c27ced3e367d1577929655da8
|
[
"MIT"
] | 15
|
2020-02-08T17:29:27.000Z
|
2022-01-05T16:12:14.000Z
|
wikdict_web/__main__.py
|
hartwork/wikdict-web
|
3bd80b5ac116aa4bf761e3d04bbcf1a84c240473
|
[
"MIT"
] | 1
|
2020-12-07T07:18:47.000Z
|
2020-12-07T07:18:47.000Z
|
from wikdict_web import app
app.run()
| 9.75
| 27
| 0.769231
| 7
| 39
| 4.142857
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 39
| 3
| 28
| 13
| 0.878788
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
5c85e2646c9845930a57cd7e411c3a770089698b
| 106
|
py
|
Python
|
advanced_python/lambda/long_string.py
|
alan-nguyen/master-python
|
2e1cc773123f4bdb0ab2ff0acd667e2e16ccdc4f
|
[
"MIT"
] | null | null | null |
advanced_python/lambda/long_string.py
|
alan-nguyen/master-python
|
2e1cc773123f4bdb0ab2ff0acd667e2e16ccdc4f
|
[
"MIT"
] | null | null | null |
advanced_python/lambda/long_string.py
|
alan-nguyen/master-python
|
2e1cc773123f4bdb0ab2ff0acd667e2e16ccdc4f
|
[
"MIT"
] | null | null | null |
long_string = lambda str: len(str) > 12
print(long_string("short"))
print(long_string("photosynthesis"))
| 21.2
| 39
| 0.745283
| 15
| 106
| 5.066667
| 0.6
| 0.394737
| 0.394737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020833
| 0.09434
| 106
| 4
| 40
| 26.5
| 0.770833
| 0
| 0
| 0
| 0
| 0
| 0.179245
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.666667
| 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
| 1
|
0
| 5
|
7a2603f562cbbc81edc55c16006e7c4941b13947
| 129
|
py
|
Python
|
Documentation/GuidesFromPlosCompBioPaper/ExampleCaseC/AdditionalInputFiles/PRSCondition/backflowDiodeResistorControllerAorta.py
|
carthurs/CRIMSONGUI
|
1464df9c4d04cf3ba131ca90b91988a06845c68e
|
[
"BSD-3-Clause"
] | 10
|
2020-09-17T18:55:31.000Z
|
2022-02-23T02:52:38.000Z
|
Documentation/GuidesFromPlosCompBioPaper/ExampleCaseC/AdditionalInputFiles/PRSCondition/backflowDiodeResistorControllerAorta.py
|
carthurs/CRIMSONGUI
|
1464df9c4d04cf3ba131ca90b91988a06845c68e
|
[
"BSD-3-Clause"
] | null | null | null |
Documentation/GuidesFromPlosCompBioPaper/ExampleCaseC/AdditionalInputFiles/PRSCondition/backflowDiodeResistorControllerAorta.py
|
carthurs/CRIMSONGUI
|
1464df9c4d04cf3ba131ca90b91988a06845c68e
|
[
"BSD-3-Clause"
] | 3
|
2021-05-19T09:02:21.000Z
|
2021-07-26T17:39:57.000Z
|
version https://git-lfs.github.com/spec/v1
oid sha256:9a3c23f3be5baecc8ac169e79d360fc6e261a217d76ac0d3a844f3bf00552201
size 2897
| 32.25
| 75
| 0.883721
| 13
| 129
| 8.769231
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.373984
| 0.046512
| 129
| 3
| 76
| 43
| 0.552846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7a2c3a682db79f34af257c211bb089ae680c9d2b
| 239
|
py
|
Python
|
size_constrained_clustering/sklearn_import/utils/fixes.py
|
vergilijus/size_constrained_clustering
|
be520ee0535b3f73d779e498a9046ef77d69355d
|
[
"MIT"
] | 26
|
2020-07-04T11:30:09.000Z
|
2022-02-04T22:12:24.000Z
|
size_constrained_clustering/sklearn_import/utils/fixes.py
|
vergilijus/size_constrained_clustering
|
be520ee0535b3f73d779e498a9046ef77d69355d
|
[
"MIT"
] | 4
|
2020-07-04T14:50:49.000Z
|
2022-03-23T22:09:08.000Z
|
size_constrained_clustering/sklearn_import/utils/fixes.py
|
vergilijus/size_constrained_clustering
|
be520ee0535b3f73d779e498a9046ef77d69355d
|
[
"MIT"
] | 15
|
2020-08-19T10:37:25.000Z
|
2022-03-21T05:00:26.000Z
|
import numpy as np
from sklearn_import.fixes import _parse_version
np_version = _parse_version(np.__version__)
def sparse_min_max(X, axis):
return (X.min(axis=axis).toarray().ravel(),
X.max(axis=axis).toarray().ravel())
| 23.9
| 47
| 0.715481
| 36
| 239
| 4.416667
| 0.5
| 0.150943
| 0.176101
| 0.264151
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.150628
| 239
| 9
| 48
| 26.555556
| 0.783251
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.333333
| 0.166667
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
7a52520fd5a16e2c0f9aab3460ef29f76a48200c
| 2,383
|
py
|
Python
|
cc.py
|
ryepesg/algo
|
990fd87cea8815b3ba841f61b2e27be64c097874
|
[
"MIT"
] | null | null | null |
cc.py
|
ryepesg/algo
|
990fd87cea8815b3ba841f61b2e27be64c097874
|
[
"MIT"
] | null | null | null |
cc.py
|
ryepesg/algo
|
990fd87cea8815b3ba841f61b2e27be64c097874
|
[
"MIT"
] | null | null | null |
def cc(M):
m, n = len(M), len(M[0])
ly, lx = [], []
for j in range(1, m):
for i in range(n):
if M[j][i] != M[j-1][i]:
ly.append(j)
break
for i in range(1, n):
for j in range(m):
if M[j][i] != M[j][i-1]:
lx.append(i)
break
C = []
for j in range(len(ly)-1):
C.append([])
for i in range(len(lx)-1):
C[j].append(M[ly[j]][lx[i]])
print("\n".join("".join(c) for c in C))
print()
cc(["----------",
"|....x...|",
"|....xxxx|",
"|....x...|",
"|........|",
"|........|",
"----------"])
cc(["XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
"X X X",
"X X X",
"X X X",
"X X X",
"X XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
"X X X X",
"X X X X",
"X X X X",
"X X X X",
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"X X X X",
"XXXXXXXXXXXXXX X X",
"X X X",
"X X X",
"X X X",
"X X X",
"X X X",
"X X X",
"X X X",
"X X X",
"XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"])
cc(["-----|",
"|O |",
"| XX|",
"| X |",
"| X |",
"------"])
cc(["-----------",
"|H | |",
"| | | |",
"|-|-|-----|",
"| | | |",
"| | | |",
"| | | W |",
"| | | |",
"-----------"])
| 31.355263
| 52
| 0.191355
| 197
| 2,383
| 2.314721
| 0.152284
| 0.364035
| 0.513158
| 0.649123
| 0.219298
| 0.219298
| 0.188596
| 0.188596
| 0.188596
| 0.188596
| 0
| 0.008055
| 0.635334
| 2,383
| 75
| 53
| 31.773333
| 0.516686
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| 0.049937
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| 0.014286
| false
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| 0.028571
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| 0
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|
0
| 5
|
7a56b64712851ce9ec02ef0b9f1482281b496cc8
| 287
|
py
|
Python
|
Modulo-01/ex022/ex022.py
|
Matheus-Henrique-Burey/Curso-de-Python
|
448aebaab96527affa1e45897a662bb0407c11c6
|
[
"MIT"
] | null | null | null |
Modulo-01/ex022/ex022.py
|
Matheus-Henrique-Burey/Curso-de-Python
|
448aebaab96527affa1e45897a662bb0407c11c6
|
[
"MIT"
] | null | null | null |
Modulo-01/ex022/ex022.py
|
Matheus-Henrique-Burey/Curso-de-Python
|
448aebaab96527affa1e45897a662bb0407c11c6
|
[
"MIT"
] | null | null | null |
frase = str(input('Digite seu nome completo: ')).strip()
print(f'Seu nome em maiusculo é: {frase.upper()}')
print(f'Seu nome em minusculo é: {frase.lower()}')
print(f'Seu nome tem no total {len(frase)- frase.count(" ")} letras')
print(f'Seu primeiro nome tem: {frase.find(" ")} letras')
| 47.833333
| 69
| 0.679443
| 47
| 287
| 4.148936
| 0.510638
| 0.14359
| 0.184615
| 0.2
| 0.153846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121951
| 287
| 5
| 70
| 57.4
| 0.77381
| 0
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| 0
| 0
| 0.738676
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 0.8
| 0
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| null | 0
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| 1
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| 0
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| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 1
|
0
| 5
|
7a5eab06b0feada1a4f82cf9d6beb0329f6d88a4
| 84
|
py
|
Python
|
src/app/__init__.py
|
Rabbithy/Fyks
|
8a2e8fac75b445ae8a608dc873a732c6d66a0f6b
|
[
"MIT"
] | 1
|
2020-06-11T03:39:40.000Z
|
2020-06-11T03:39:40.000Z
|
src/app/__init__.py
|
Rabbithy/Fyks
|
8a2e8fac75b445ae8a608dc873a732c6d66a0f6b
|
[
"MIT"
] | 6
|
2020-10-19T23:08:27.000Z
|
2020-11-24T12:03:59.000Z
|
src/app/__init__.py
|
Rabbithy/Fyks
|
8a2e8fac75b445ae8a608dc873a732c6d66a0f6b
|
[
"MIT"
] | null | null | null |
#! venv/bin/python3
from . import widgets
from . import utils
__version__ = '2.2.1'
| 16.8
| 21
| 0.714286
| 13
| 84
| 4.307692
| 0.769231
| 0.357143
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.056338
| 0.154762
| 84
| 5
| 22
| 16.8
| 0.732394
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| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
7a62c1556285decf98d1c684b1340eb6420d5fbf
| 283
|
py
|
Python
|
ex74.py
|
eng-lenin/Python
|
6038f052b8343878760ed133dd43869927e39b3d
|
[
"MIT"
] | 1
|
2021-01-30T14:50:55.000Z
|
2021-01-30T14:50:55.000Z
|
ex74.py
|
eng-lenin/Python
|
6038f052b8343878760ed133dd43869927e39b3d
|
[
"MIT"
] | null | null | null |
ex74.py
|
eng-lenin/Python
|
6038f052b8343878760ed133dd43869927e39b3d
|
[
"MIT"
] | null | null | null |
from random import randint
num = (randint(1,10),randint(1,10),randint(1,10),randint(1,10),randint(1,10))
print('Eu sorteei os valores ', end='')
for n in num:
print(f'{n} ',end='')
print(f'\nO maior valor sorteado foi {max(num)}')
print(f'O menor valor sorteado foi {min(num)}')
| 35.375
| 77
| 0.671378
| 52
| 283
| 3.653846
| 0.5
| 0.210526
| 0.263158
| 0.357895
| 0.263158
| 0.263158
| 0.263158
| 0.263158
| 0.263158
| 0.263158
| 0
| 0.060484
| 0.123675
| 283
| 7
| 78
| 40.428571
| 0.705645
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| 0.571429
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| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8f8b7a67e00b2c4c1ddd20414394a7adb26fee37
| 323
|
py
|
Python
|
chaospy/poly/constructor/__init__.py
|
krystophny/chaospy
|
e09f8e3f6dfc26145f15774edd5b03665140712f
|
[
"MIT"
] | 1
|
2018-08-22T01:51:25.000Z
|
2018-08-22T01:51:25.000Z
|
src/chaospy/poly/constructor/__init__.py
|
TribleCircle/chaospy
|
f22aa31e2a338a32a6d09b810c5b629c10a87236
|
[
"BSD-3-Clause"
] | null | null | null |
src/chaospy/poly/constructor/__init__.py
|
TribleCircle/chaospy
|
f22aa31e2a338a32a6d09b810c5b629c10a87236
|
[
"BSD-3-Clause"
] | 1
|
2019-11-24T17:16:30.000Z
|
2019-11-24T17:16:30.000Z
|
"""
Constructor of the Poly class.
"""
import chaospy.poly.constructor.identifier
import chaospy.poly.constructor.preprocessing
import chaospy.poly.constructor.ensurance
from chaospy.poly.constructor.identifier import *
from chaospy.poly.constructor.preprocessing import *
from chaospy.poly.constructor.ensurance import *
| 29.363636
| 52
| 0.832817
| 38
| 323
| 7.078947
| 0.289474
| 0.245353
| 0.490706
| 0.312268
| 0.698885
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.080495
| 323
| 10
| 53
| 32.3
| 0.905724
| 0.092879
| 0
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| 0
| 0
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| 0
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| true
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| 0
| 0
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| 0
| 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
8fcee2fb51ccdba2c17a7f8f001c72f8c6063940
| 1,213
|
py
|
Python
|
codes/get_full_template.py
|
mkunimoto/Transit-Search-and-Vetting
|
9c5ea221fac9a511e58a14c2ab5b5335675379dc
|
[
"BSD-3-Clause"
] | 1
|
2020-04-26T08:49:44.000Z
|
2020-04-26T08:49:44.000Z
|
codes/get_full_template.py
|
mkunimoto/Transit-Search-and-Vetting
|
9c5ea221fac9a511e58a14c2ab5b5335675379dc
|
[
"BSD-3-Clause"
] | null | null | null |
codes/get_full_template.py
|
mkunimoto/Transit-Search-and-Vetting
|
9c5ea221fac9a511e58a14c2ab5b5335675379dc
|
[
"BSD-3-Clause"
] | null | null | null |
import sys
import numpy as np
g1 = float(sys.argv[1])
g2 = float(sys.argv[2])
n = len(sys.argv) - 2
p = n/3
per = sys.argv[3:3+p]
per = np.array([float(i) for i in per])
epo = sys.argv[3+p:3+p*2]
epo = np.array([float(i) for i in epo])
dep = sys.argv[3+p*2:3+3*p]
dep = np.array([float(i) for i in dep])
rat = np.sqrt(dep)
f = open('LMfit_template.dat','w')
f.write('RHO 1.408 0.0 0.0 0.0' + '\n') # assumes solar density
f.write('NL1 ' + str(g1) + ' 0.0 0.0 0.0' + '\n')
f.write('NL2 ' + str(g2) + ' 0.0 0.0 0.0' + '\n')
f.write('NL3 0.0 0.0 0.0 0.0' + '\n')
f.write('NL4 0.0 0.0 0.0 0.0' + '\n')
f.write('DIL 0.0 0.0 0.0 0.0' + '\n')
f.write('VOF 0.0 0.0 0.0 0.0' + '\n')
f.write('ZPT 0.0 0.0 0.0 0.0' + '\n')
for i in range(p):
f.write('EP1 ' + str(epo[i]) + ' 0.0 0.0 0.0' + '\n')
f.write('PE1 ' + str(per[i]) + ' 0.0 0.0 0.0' + '\n')
f.write('BB1 0.0 0.0 0.0 0.0' + '\n')
f.write('RD1 ' + str(rat[i]) + ' 0.0 0.0 0.0' + '\n')
f.write('EC1 0.0 0.0 0.0 0.0' + '\n')
f.write('ES1 0.0 0.0 0.0 0.0' + '\n')
f.write('KR1 0.0 0.0 0.0 0.0' + '\n')
f.write('TE1 0.0 0.0 0.0 0.0' + '\n')
f.write('EL1 0.0 0.0 0.0 0.0' + '\n')
f.write('AL1 0.0 0.0 0.0 0.0' + '\n')
f.close()
| 31.102564
| 63
| 0.500412
| 313
| 1,213
| 1.936102
| 0.182109
| 0.376238
| 0.475248
| 0.514851
| 0.4967
| 0.4967
| 0.4967
| 0.391089
| 0.391089
| 0.333333
| 0
| 0.174322
| 0.210223
| 1,213
| 38
| 64
| 31.921053
| 0.458246
| 0.017312
| 0
| 0
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| 0.322689
| 0
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| 0
| 0
| 1
| 0
| false
| 0
| 0.058824
| 0
| 0.058824
| 0
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| 1
| 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
| 5
|
64fc7b85b91ea83309d3a573e141135fa6354901
| 3,984
|
py
|
Python
|
src/dialog/BaseTemplatrDialog.py
|
kalyan02/tumblrthemr
|
d9411adbf4fa625c6fc2702a8332c9e2d76b23fc
|
[
"Unlicense",
"MIT"
] | 41
|
2015-01-02T17:03:55.000Z
|
2022-03-14T10:33:08.000Z
|
src/dialog/BaseTemplatrDialog.py
|
kalyan02/tumblrthemr
|
d9411adbf4fa625c6fc2702a8332c9e2d76b23fc
|
[
"Unlicense",
"MIT"
] | 3
|
2015-09-20T14:29:02.000Z
|
2021-01-29T11:18:06.000Z
|
src/dialog/BaseTemplatrDialog.py
|
kalyan02/tumblrthemr
|
d9411adbf4fa625c6fc2702a8332c9e2d76b23fc
|
[
"Unlicense",
"MIT"
] | 6
|
2015-04-23T23:45:26.000Z
|
2018-05-07T15:18:30.000Z
|
# -*- coding: utf-8 -*-
###########################################################################
## Python code generated with wxFormBuilder (version Nov 27 2012)
## http://www.wxformbuilder.org/
##
## PLEASE DO "NOT" EDIT THIS FILE!
###########################################################################
import wx
import wx.xrc
###########################################################################
## Class BaseDialog
###########################################################################
class BaseDialog ( wx.Frame ):
def __init__( self, parent ):
wx.Frame.__init__ ( self, parent, id = wx.ID_ANY, title = u"Tumblr Themr - Develop tumblr themes offline", pos = wx.DefaultPosition, size = wx.Size( 600,400 ), style = wx.DEFAULT_FRAME_STYLE|wx.TAB_TRAVERSAL )
self.SetSizeHintsSz( wx.DefaultSize, wx.Size( 600,400 ) )
self.SetForegroundColour( wx.Colour( 255, 255, 255 ) )
self.SetBackgroundColour( wx.Colour( 255, 255, 255 ) )
gSizer2 = wx.GridSizer( 0, 2, 0, 0 )
bSizer5 = wx.BoxSizer( wx.VERTICAL )
self.intro_bitmap = wx.StaticBitmap( self, wx.ID_ANY, wx.Bitmap( u"dialog/bg.bmp", wx.BITMAP_TYPE_ANY ), wx.DefaultPosition, wx.DefaultSize, 0 )
self.intro_bitmap.SetMaxSize( wx.Size( 250,400 ) )
bSizer5.Add( self.intro_bitmap, 0, wx.ALL, 5 )
gSizer2.Add( bSizer5, 1, wx.EXPAND, 5 )
bSizer7 = wx.BoxSizer( wx.VERTICAL )
bSizer7.AddSpacer( ( 0, 0), 1, wx.EXPAND, 5 )
self.m_staticText11 = wx.StaticText( self, wx.ID_ANY, u"Select Themes Directory", wx.Point( -1,-1 ), wx.DefaultSize, 0 )
self.m_staticText11.Wrap( -1 )
bSizer7.Add( self.m_staticText11, 0, wx.ALL, 5 )
self.themes_directory = wx.DirPickerCtrl( self, wx.ID_ANY, wx.EmptyString, u"Select a folder", wx.Point( 100,100 ), wx.DefaultSize, wx.DIRP_DEFAULT_STYLE )
self.themes_directory.Enable( False )
bSizer7.Add( self.themes_directory, 0, wx.ALL, 5 )
self.m_staticText5 = wx.StaticText( self, wx.ID_ANY, u"Port", wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText5.Wrap( -1 )
bSizer7.Add( self.m_staticText5, 0, wx.ALL, 5 )
self.server_port = wx.TextCtrl( self, wx.ID_ANY, u"13323", wx.DefaultPosition, wx.DefaultSize, 0 )
self.server_port.SetMaxLength( 6 )
bSizer7.Add( self.server_port, 0, wx.ALL, 10 )
bSizer7.AddSpacer( ( 0, 0), 1, wx.EXPAND, 5 )
self.status_text = wx.StaticText( self, wx.ID_ANY, wx.EmptyString, wx.Point( -1,-1 ), wx.DefaultSize, 0 )
self.status_text.Wrap( -1 )
bSizer7.Add( self.status_text, 0, wx.ALL, 5 )
self.server_ctrl_button = wx.Button( self, wx.ID_ANY, u"Start Server", wx.DefaultPosition, wx.DefaultSize, 0 )
bSizer7.Add( self.server_ctrl_button, 0, wx.ALL, 5 )
bSizer7.AddSpacer( ( 0, 0), 1, wx.EXPAND, 5 )
self.build_info = wx.StaticText( self, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.build_info.Wrap( -1 )
self.build_info.SetFont( wx.Font( 10, 70, 90, 90, False, wx.EmptyString ) )
bSizer7.Add( self.build_info, 0, wx.ALL, 5 )
bSizer7.AddSpacer( ( 0, 0), 1, wx.EXPAND, 5 )
gSizer2.Add( bSizer7, 1, wx.EXPAND, 5 )
self.SetSizer( gSizer2 )
self.Layout()
self.m_menubar1 = wx.MenuBar( 0 )
self.m_menu1 = wx.Menu()
self.how_to_use = wx.MenuItem( self.m_menu1, wx.ID_ANY, u"How to use?", wx.EmptyString, wx.ITEM_NORMAL )
self.m_menu1.AppendItem( self.how_to_use )
self.m_menubar1.Append( self.m_menu1, u"Help" )
self.SetMenuBar( self.m_menubar1 )
self.Centre( wx.BOTH )
# Connect Events
self.Bind( wx.EVT_CLOSE, self.exit_server )
self.themes_directory.Bind( wx.EVT_DIRPICKER_CHANGED, self.select_path )
self.server_ctrl_button.Bind( wx.EVT_BUTTON, self.start_server )
def __del__( self ):
pass
# Virtual event handlers, overide them in your derived class
def exit_server( self, event ):
event.Skip()
def select_path( self, event ):
event.Skip()
def start_server( self, event ):
event.Skip()
| 3,984
| 3,984
| 0.630773
| 561
| 3,984
| 4.336898
| 0.26738
| 0.026716
| 0.028771
| 0.036169
| 0.321003
| 0.226058
| 0.129059
| 0.10933
| 0.087957
| 0.028771
| 0
| 0.046861
| 0.164408
| 3,984
| 1
| 3,984
| 3,984
| 0.683989
| 0.920181
| 0
| 0.114754
| 1
| 0
| 0.038181
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.081967
| false
| 0.016393
| 0.032787
| 0
| 0.131148
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
64fdec711442123721f638c9a52ac6c5c04bbc67
| 40
|
py
|
Python
|
tests/components/rachio/__init__.py
|
domwillcode/home-assistant
|
f170c80bea70c939c098b5c88320a1c789858958
|
[
"Apache-2.0"
] | 30,023
|
2016-04-13T10:17:53.000Z
|
2020-03-02T12:56:31.000Z
|
tests/components/rachio/__init__.py
|
jagadeeshvenkatesh/core
|
1bd982668449815fee2105478569f8e4b5670add
|
[
"Apache-2.0"
] | 31,101
|
2020-03-02T13:00:16.000Z
|
2022-03-31T23:57:36.000Z
|
tests/components/rachio/__init__.py
|
jagadeeshvenkatesh/core
|
1bd982668449815fee2105478569f8e4b5670add
|
[
"Apache-2.0"
] | 11,956
|
2016-04-13T18:42:31.000Z
|
2020-03-02T09:32:12.000Z
|
"""Tests for the Rachio integration."""
| 20
| 39
| 0.7
| 5
| 40
| 5.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 40
| 1
| 40
| 40
| 0.8
| 0.825
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
8f0bfc4aaefb4df1ae0692e310f83ad28d963aed
| 61
|
py
|
Python
|
tests/formatters/test_numpy.py
|
byaka/sublime_docblockr_python
|
bcfdb58edc9ed26d0d8fec38bf1d2649647f4a4a
|
[
"MIT"
] | 61
|
2015-12-21T11:58:40.000Z
|
2021-07-09T03:45:15.000Z
|
tests/formatters/test_numpy.py
|
byaka/sublime_docblockr_python
|
bcfdb58edc9ed26d0d8fec38bf1d2649647f4a4a
|
[
"MIT"
] | 28
|
2015-12-15T08:50:59.000Z
|
2021-07-14T10:59:34.000Z
|
tests/formatters/test_numpy.py
|
byaka/sublime_docblockr_python
|
bcfdb58edc9ed26d0d8fec38bf1d2649647f4a4a
|
[
"MIT"
] | 15
|
2016-01-19T14:22:39.000Z
|
2021-08-25T15:11:46.000Z
|
def test_exists(formatter_numpy):
assert formatter_numpy
| 20.333333
| 33
| 0.819672
| 8
| 61
| 5.875
| 0.75
| 0.595745
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| 0
| 0
| 0
| 0
| 0.131148
| 61
| 2
| 34
| 30.5
| 0.886792
| 0
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| 0.5
| 1
| 0.5
| false
| 0
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| null | 1
| 0
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| 0
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| null | 0
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|
0
| 5
|
8f10e408c3e0a6f022f4e39b9ac49a43a31248e6
| 19,073
|
py
|
Python
|
code/models/__init__.py
|
DSIP-UPatras/sEMG-hilbert-curve
|
49e9b5c9cc0053242f57c71f12059a5050627ea2
|
[
"MIT"
] | 6
|
2020-09-28T08:27:30.000Z
|
2022-01-06T11:02:30.000Z
|
code/models/__init__.py
|
DSIP-UPatras/sEMG-hilbert-curve
|
49e9b5c9cc0053242f57c71f12059a5050627ea2
|
[
"MIT"
] | null | null | null |
code/models/__init__.py
|
DSIP-UPatras/sEMG-hilbert-curve
|
49e9b5c9cc0053242f57c71f12059a5050627ea2
|
[
"MIT"
] | 1
|
2020-12-03T09:58:47.000Z
|
2020-12-03T09:58:47.000Z
|
from tensorflow.keras.layers import *
from tensorflow.keras import initializers, regularizers
from tensorflow.keras.models import Model
import math
import numpy as np
# VGG-like
def VGGNet(input_shape, classes,
n_blocks = 3, n_pool='average', n_pool_size=(2,2), n_dropout=0., n_l2=0.0005,
n_init='glorot_normal', n_batch_norm=False,
n_seed=0, output_layer_name='output'):
"""
Arguments:
input_shape -- tuple, dimensions of the input in the form (height, width, channels)
classes -- integer, number of classes to be classified, defines the dimension of the softmax unit
n_pool -- string, pool method to be used {'max', 'average'}
n_dropout -- float, rate of dropping units
n_l2 -- float, ampunt of weight decay regularization
n_init -- string, type of kernel initializer {'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform', 'normal', 'uniform'}
n_seed -- integer, random seed for kernel intiliazer
Returns:
model -- keras.models.Model (https://keras.io)
## PHCNet - Summary
# CONV,16,3,3,1,1,same #16*3*3*10+16 = 1456
# CONV,16,3,3,1,1,same #16*3*3*16+16 = 2320
# CONV,16,3,3,1,1,same #16*3*3*16+16 = 2320
# POOL,2,2,2,2
# CONV,32,3,3,1,1,same #32*3*3*16+32 = 4640
# CONV,32,3,3,1,1,same #32*3*3*32+32 = 9248
# POOL,2,2,2,2
# CONV,64,3,3,1,1,same #64*3*3*32+64 = 18496
# CONV,64,3,3,1,1,same #64*3*3*64+64 = 36928
# POOL,2,2,2,2
# FC,53 #53*64+53 = 3445
## Params: 78853, RF: 38
"""
if n_init == 'glorot_normal':
kernel_init = initializers.glorot_normal(seed=n_seed)
elif n_init == 'glorot_uniform':
kernel_init = initializers.glorot_uniform(seed=n_seed)
elif n_init == 'he_normal':
kernel_init = initializers.he_normal(seed=n_seed)
elif n_init == 'he_uniform':
kernel_init = initializers.he_uniform(seed=n_seed)
elif n_init == 'normal':
kernel_init = initializers.normal(seed=n_seed)
elif n_init == 'uniform':
kernel_init = initializers.uniform(seed=n_seed)
kernel_regl = regularizers.l2(n_l2)
# n_pool_size = (2,2)
# n_blocks = 3
## Block 0 [Input]
X_input = Input(input_shape, name='b0_input')
X = X_input
if n_batch_norm:
X = BatchNormalization(name='b0_batchnorm')(X)
## Block 1 [Pad -> Conv -> ReLU -> Dropout]
X = Conv2D(16, (3, 3), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b1_conv2d_32_3x3')(X)
if n_batch_norm:
X = BatchNormalization(name='b1_batchnorm')(X)
X = Activation('relu', name='b1_relu')(X)
# X = Dropout(n_dropout, name='b1_dropout')(X)
filters = 16
ins = min(input_shape[0], input_shape[1])
num_pool_layers = int(min(math.log(ins, n_pool_size[0]), n_blocks))
pool_layers = np.linspace(n_blocks, 0, num_pool_layers, endpoint=False, dtype=int)-1
for i in range(n_blocks):
## Block 2 [Pad -> Conv -> ReLU -> -> Dropout -> Pool]
X = Conv2D(filters, (3, 3), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b{}_1_conv2d_32_3x3'.format(i+2))(X)
X = Activation('relu', name='b{}_1_relu'.format(i+2))(X)
X = Conv2D(filters, (3, 3), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b{}_2_conv2d_32_3x3'.format(i+2))(X)
X = Activation('relu', name='b{}_2_relu'.format(i+2))(X)
X = Dropout(n_dropout, name='b{}_dropout'.format(i+2))(X)
if i in pool_layers:
if n_pool == 'max':
X = MaxPooling2D(n_pool_size, strides = n_pool_size, name='b{}_pool'.format(i+2))(X)
else:
X = AveragePooling2D(n_pool_size, strides = n_pool_size, name='b{}_pool'.format(i+2))(X)
filters = filters*2
X = GlobalAveragePooling2D()(X)
## Block 5 [FC -> Softmax]
X = Dense(classes, kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b{}_fc_{}'.format(n_blocks+2, classes))(X)
X = Activation('softmax', name=output_layer_name)(X)
model = Model(inputs = X_input, outputs = X, name='PHCNet')
# model.summary()
return model
## SqueezeNet-like
def SqueezeNet(input_shape, classes,
n_blocks = 3, n_pool='average', n_pool_size=(2,2), n_dropout=0., n_l2=0.0005,
n_init='glorot_normal', n_batch_norm=False,
n_seed=0, output_layer_name='output'):
"""
Arguments:
input_shape -- tuple, dimensions of the input in the form (height, width, channels)
classes -- integer, number of classes to be classified, defines the dimension of the softmax unit
n_pool -- string, pool method to be used {'max', 'average'}
n_dropout -- float, rate of dropping units
n_l2 -- float, ampunt of weight decay regularization
n_init -- string, type of kernel initializer {'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform', 'normal', 'uniform'}
n_seed -- integer, random seed for kernel intiliazer
Returns:
model -- keras.models.Model (https://keras.io)
## PHCNet - Summary
# CONV,16,3,3,1,1,same #16*3*3*10+16 = 1456
# SQUEEZE_BLOCK,4,8,16 #136+3*264 +4*144+4*1168 = 6176
# SQUEEZE_BLOCK,4,8,32 #264+3*520 +4*288+4*2336 = 12320
# SQUEEZE_BLOCK,4,8,64 #520+3*1032+4*576+4*4672 = 24608
# CONV,53,1,1,1,1,same #53*128+53 = 6837
## Params: 51397, RF: ?
"""
from models.squeezenet_utils import squeezenet_block
if n_init == 'glorot_normal':
kernel_init = initializers.glorot_normal(seed=n_seed)
elif n_init == 'glorot_uniform':
kernel_init = initializers.glorot_uniform(seed=n_seed)
elif n_init == 'he_normal':
kernel_init = initializers.he_normal(seed=n_seed)
elif n_init == 'he_uniform':
kernel_init = initializers.he_uniform(seed=n_seed)
elif n_init == 'normal':
kernel_init = initializers.normal(seed=n_seed)
elif n_init == 'uniform':
kernel_init = initializers.uniform(seed=n_seed)
kernel_regl = regularizers.l2(n_l2)
# n_pool_size = (2,2)
# n_blocks = 3
## Block 0 [Input]
X_input = Input(input_shape, name='b0_input')
X = X_input
if n_batch_norm:
X = BatchNormalization(name='b0_batchnorm')(X)
## Block 1 [Pad -> Conv -> ReLU -> Dropout]
X = Conv2D(16, (3, 3), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b1_conv2d_32_3x3')(X)
if n_batch_norm:
X = BatchNormalization(name='b1_batchnorm')(X)
X = Activation('relu', name='b1_relu')(X)
iters = 3 if input_shape[0]>=8 else 2
ins = min(input_shape[0], input_shape[1])
iters = int(math.log(ins, n_pool_size[0]))
for i in range(iters):
X = squeezenet_block(X, n_fm=n_blocks, n_sq=16, n_ex=32, n_dropout=n_dropout, n_pool=n_pool, n_pool_size=n_pool_size, block_id=i+2, kernel_regularizer=kernel_regl, kernel_initializer=kernel_init)
X = Conv2D(classes, (1, 1), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b5_conv2d_{}_1x1'.format(classes))(X)
X = Activation('relu', name='b5_relu')(X)
X = GlobalAveragePooling2D(name='b5_globalpool')(X)
X = Activation('softmax', name=output_layer_name)(X)
model = Model(inputs = X_input, outputs = X, name='PHCNet')
# model.summary()
return model
def DenseNet(input_shape, classes,
n_blocks = 3, n_pool='average', n_pool_size=(2,2), n_dropout=0., n_l2=0.0005,
n_init='glorot_normal', n_batch_norm=False,
n_seed=0, output_layer_name='output'):
"""
Arguments:
input_shape -- tuple, dimensions of the input in the form (height, width, channels)
classes -- integer, number of classes to be classified, defines the dimension of the softmax unit
n_pool -- string, pool method to be used {'max', 'average'}
n_dropout -- float, rate of dropping units
n_l2 -- float, ampunt of weight decay regularization
n_init -- string, type of kernel initializer {'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform', 'normal', 'uniform'}
n_seed -- integer, random seed for kernel intiliazer
Returns:
model -- keras.models.Model (https://keras.io)
## PHCNet - Summary
# CONV,16,3,3,1,1,same #16*3*3*10+16 = 1456
# DENSE_BLOCK,3,16 #768+1536+2304 = 4608
# TRANS_BLOCK,32/64,2,2 # = 2048
# DENSE_BLOCK,4,16 #4608+6912+9216+11520 = 32256
# TRANS_BLOCK,64/96,2,2 # = 6144
# DENSE_BLOCK,3,16 #9216+11520+13824 = 34560
# TRANS_BLOCK,64/112,2,2 # = 7168
# CONV,53,1,1,1,1,same #53*64+53 = 3445
## Params: 91685, RF: ??
"""
from models.densenet_utils import dense_block, transition_layer
if n_init == 'glorot_normal':
kernel_init = initializers.glorot_normal(seed=n_seed)
elif n_init == 'glorot_uniform':
kernel_init = initializers.glorot_uniform(seed=n_seed)
elif n_init == 'he_normal':
kernel_init = initializers.he_normal(seed=n_seed)
elif n_init == 'he_uniform':
kernel_init = initializers.he_uniform(seed=n_seed)
elif n_init == 'normal':
kernel_init = initializers.normal(seed=n_seed)
elif n_init == 'uniform':
kernel_init = initializers.uniform(seed=n_seed)
kernel_regl = regularizers.l2(n_l2)
# n_pool_size = (2,2)
# n_blocks = 3
growth = 16
nb_channels = 16
compressions = np.arange(n_blocks)+2 #[1/2, 2/3, 3/4]
compressions = (compressions-1) / compressions
compressions = compressions[::-1]
# compressions = [1/2] * n_blocks
## Block 0 [Input]
X_input = Input(input_shape, name='b0_input')
X = X_input
if n_batch_norm:
X = BatchNormalization(name='b0_batchnorm')(X)
## Block 1 [Pad -> Conv -> ReLU -> Dropout]
X = Conv2D(16, (3, 3), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b1_conv2d_16_3x3')(X)
# if n_batch_norm:
# X = BatchNormalization(name='b1_batchnorm')(X)
# X = Activation('relu', name='b1_relu')(X)
# if n_blocks == 3:
# X, nb_channels = dense_block(X, 3, nb_channels, [(3,3)]*3, growth, dropout_rate=n_dropout, bottleneck=False, batch_norm=n_batch_norm, regularizer=kernel_regl, initializer=kernel_init, dense_block_id=1)
# X = transition_layer(X, nb_channels, pool_type=n_pool, pool_size=n_pool_size, dropout_rate=n_dropout, batch_norm=False, compression=compressions[0], regularizer=kernel_regl, initializer=kernel_init, trans_block_id=1)
# nb_channels = int(nb_channels * compressions[0])
# X, nb_channels = dense_block(X, 4, nb_channels, [(3,3)]*4, growth, dropout_rate=n_dropout, bottleneck=False, batch_norm=n_batch_norm, regularizer=kernel_regl, initializer=kernel_init, dense_block_id=2)
# X = transition_layer(X, nb_channels, pool_type=n_pool, pool_size=n_pool_size, dropout_rate=n_dropout, batch_norm=False, compression=compressions[1], regularizer=kernel_regl, initializer=kernel_init, trans_block_id=2)
# nb_channels = int(nb_channels * compressions[1])
# X, nb_channels = dense_block(X, 3, nb_channels, [(3,3)]*3, growth, dropout_rate=n_dropout, bottleneck=False, batch_norm=n_batch_norm, regularizer=kernel_regl, initializer=kernel_init, dense_block_id=3)
# X = transition_layer(X, nb_channels, pool_type=n_pool, pool_size=n_pool_size, dropout_rate=n_dropout, batch_norm=False, compression=compressions[2], regularizer=kernel_regl, initializer=kernel_init, trans_block_id=3)
ins = min(input_shape[0], input_shape[1])
num_pool_layers = int(min(math.log(ins, n_pool_size[0]), n_blocks))
pool_layers = np.linspace(n_blocks, 0, num_pool_layers, endpoint=False, dtype=int)-1
for i in range(n_blocks):
# print('dense_block')
X, nb_channels = dense_block(X, 2, nb_channels, [(3,3)]*2, growth, dropout_rate=n_dropout, bottleneck=False, batch_norm=n_batch_norm, regularizer=kernel_regl, initializer=kernel_init, dense_block_id=i+1)
if i in pool_layers:
# print('transition_block')
X = transition_layer(X, nb_channels, pool_type=n_pool, pool_size=n_pool_size, dropout_rate=n_dropout, batch_norm=False, compression=compressions[i], regularizer=kernel_regl, initializer=kernel_init, trans_block_id=i+1)
nb_channels = int(nb_channels * compressions[i])
X = Activation('relu')(X)
X = Conv2D(classes, (1, 1), padding='same', kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, name='b{}_conv2d_{}_1x1'.format(n_blocks+1, classes))(X)
X = Activation('relu', name='b{}_relu'.format(n_blocks+1))(X)
X = GlobalAveragePooling2D(name='b{}_globalpool'.format(n_blocks+1))(X)
X = Activation('softmax', name=output_layer_name)(X)
model = Model(inputs = X_input, outputs = X, name='PHCNet')
# model.summary()
return model
def MSHilbNet(input_shape, classes,
n_blocks = 3, n_scales=[2, 2], n_outputs=[1,2,3], n_dropout=0., n_l2=0.0005,
n_init='glorot_normal', n_batch_norm=False, n_classifier='average', n_classifier_type='1_conv',
n_seed=0, output_layer_name='output'):
"""
Arguments:
input_shape -- tuple, dimensions of the input in the form (height, width, channels)
classes -- integer, number of classes to be classified, defines the dimension of the softmax unit
n_pool -- string, pool method to be used {'max', 'average'}
n_dropout -- float, rate of dropping units
n_l2 -- float, ampunt of weight decay regularization
n_init -- string, type of kernel initializer {'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform', 'normal', 'uniform'}
n_seed -- integer, random seed for kernel intiliazer
Returns:
model -- keras.models.Model (https://keras.io)
## PHCNet - Summary
"""
from models.multiscale_utils import downscale_pool, regular_convs, strided_convs
from models.custom_layers import AttentionWithContext as Attention
import tensorflow as tf
if n_init == 'glorot_normal':
kernel_init = initializers.glorot_normal(seed=n_seed)
elif n_init == 'glorot_uniform':
kernel_init = initializers.glorot_uniform(seed=n_seed)
elif n_init == 'he_normal':
kernel_init = initializers.he_normal(seed=n_seed)
elif n_init == 'he_uniform':
kernel_init = initializers.he_uniform(seed=n_seed)
elif n_init == 'normal':
kernel_init = initializers.normal(seed=n_seed)
elif n_init == 'uniform':
kernel_init = initializers.uniform(seed=n_seed)
kernel_regl = regularizers.l2(n_l2)
## Block 0 [Input]
X_input = Input(input_shape, name='b0_input')
X = X_input
if n_batch_norm:
X = BatchNormalization(name='b0_batchnorm')(X)
outputs = []
# outputs_index = [2,4,5] # 1 ... layers
# Input layer
x_prev_layer = [X]
for i in range(len(n_scales)):
x_prev_layer.append(
downscale_pool(x_prev_layer[-1], n_scales[i], func=MaxPooling2D, bid=i)
)
## Intermediate layers
for i in range(1, n_blocks+1):
xr = regular_convs(x_prev_layer, filters=32, activation='relu', drop=n_dropout, bid=i, kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, batch_norm=n_batch_norm)
xs = strided_convs(x_prev_layer, n_scales, filters=16, activation='relu', drop=n_dropout, bid=i, kernel_regularizer=kernel_regl, kernel_initializer=kernel_init, batch_norm=n_batch_norm)
x_prev_layer = [xr[0]]
for j in range(len(xs)):
x_prev_layer.append(
Concatenate(name='b{}_concatenate_{}'.format(i, j))([xr[j+1], xs[j]])
)
if i in n_outputs:
outputs.append([i,x_prev_layer[-1]])
## Classifiers
classifiers = []
for i in range(len(outputs)):
if n_classifier_type == '1_conv':
x = Conv2D(classes, (1, 1), padding='same', name='b{}_classifier_conv2d_{}_1x1'.format(outputs[i][0], classes))(outputs[i][1])
# x = Activation('relu', name='b{}_classifier_relu'.format(outputs[i][0], i))(x)
elif n_classifier_type == '2_conv':
x = Conv2D(128, (1, 1), padding='same', activation='relu', name='b{}_classifier_conv2d_128_1x1'.format(outputs[i][0]))(outputs[i][1])
x = Conv2D(classes, (1, 1), padding='same', name='b{}_classifier_conv2d_{}_1x1'.format(outputs[i][0], classes))(x)
elif n_classifier_type == '3_conv':
x = Conv2D(256, (1, 1), padding='same', activation='relu', name='b{}_classifier_conv2d_256_1x1'.format(outputs[i][0]))(outputs[i][1])
x = Conv2D(128, (1, 1), padding='same', activation='relu', name='b{}_classifier_conv2d_128_1x1'.format(outputs[i][0]))(x)
x = Conv2D(classes, (1, 1), padding='same', name='b{}_classifier_conv2d_{}_1x1'.format(outputs[i][0], classes))(x)
x = GlobalAveragePooling2D(name='b{}_classifier_globalpool'.format(outputs[i][0]))(x)
x = Activation('softmax', name='b{}_classifier_softmax'.format(outputs[i][0]))(x)
classifiers.append(x)
if len(classifiers) >= 2:
if n_classifier == 'average':
# X = Average(name='b{}_average'.format(n_blocks + 1))(classifiers)
X = Average(name=output_layer_name)(classifiers)
elif n_classifier == 'attention':
for i in range(len(classifiers)):
classifiers[i] = Reshape((1,classes), name='b{}_classifier_reshape'.format(outputs[i][0]))(classifiers[i])
X = Concatenate(axis=1, name='output_concatenate')(classifiers)
X = Attention(name=output_layer_name, return_attention=False)(X)
else:
pass
else:
X = Lambda(lambda x: x, name=output_layer_name) (classifiers[0])
# X = GlobalAveragePooling2D(name='b{}_globalpool'.format(n_blocks+1))(X)
# X = Activation('softmax', name=output_layer_name)(X)
model = Model(inputs = X_input, outputs = X, name='PHCNet')
# model.summary()
return model
def crop(dimension, start, end):
""" Crops (or slices) a Tensor on a given dimension from start to end
example : to crop tensor x[:, :, 5:10]
call slice(2, 5, 10) as you want to crop on the second dimension"""
def func(x):
if dimension == 0:
return x[start: end]
if dimension == 1:
return x[:, start: end]
if dimension == 2:
return x[:, :, start: end]
if dimension == 3:
return x[:, :, :, start: end]
if dimension == 4:
return x[:, :, :, :, start: end]
return Lambda(func)
| 46.633252
| 230
| 0.644943
| 2,753
| 19,073
| 4.236469
| 0.088994
| 0.036869
| 0.045271
| 0.022293
| 0.784875
| 0.753923
| 0.723742
| 0.713624
| 0.703678
| 0.685158
| 0
| 0.051019
| 0.217952
| 19,073
| 408
| 231
| 46.747549
| 0.730893
| 0.342631
| 0
| 0.542453
| 0
| 0
| 0.094766
| 0.019846
| 0
| 0
| 0
| 0
| 0
| 1
| 0.028302
| false
| 0.004717
| 0.04717
| 0
| 0.122642
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 5
|
8f1230377efcb46cb5ab7dc52c37bbc2a898daa8
| 200
|
py
|
Python
|
pytoolkit/datasets/__init__.py
|
ak110/pytoolk
|
8eef7e0add7bbc0ced1f1f1d82ed245388cc6684
|
[
"MIT"
] | 26
|
2018-12-03T23:02:56.000Z
|
2020-08-07T06:33:21.000Z
|
pytoolkit/datasets/__init__.py
|
ak110/pytoolk
|
8eef7e0add7bbc0ced1f1f1d82ed245388cc6684
|
[
"MIT"
] | null | null | null |
pytoolkit/datasets/__init__.py
|
ak110/pytoolk
|
8eef7e0add7bbc0ced1f1f1d82ed245388cc6684
|
[
"MIT"
] | 5
|
2019-08-10T11:10:59.000Z
|
2020-11-18T02:39:37.000Z
|
"""データセットの読み込みなど。"""
# pylint: skip-file
# flake8: noqa
from .coco import *
from .ic_ import *
from .keras import *
from .samples import *
from .sklearn import *
from .ss import *
from .voc import *
| 16.666667
| 22
| 0.69
| 27
| 200
| 5.074074
| 0.555556
| 0.437956
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006098
| 0.18
| 200
| 11
| 23
| 18.181818
| 0.829268
| 0.23
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
56aa5346bb952e3d599f938888ff31b7136c0a99
| 6,823
|
py
|
Python
|
starthinker/task/dv_editor/run.py
|
arbrown/starthinker
|
1a14664fb1a8f2a757b100363ea8958833b7754c
|
[
"Apache-2.0"
] | 138
|
2018-11-28T21:42:44.000Z
|
2022-03-30T17:26:35.000Z
|
starthinker/task/dv_editor/run.py
|
arbrown/starthinker
|
1a14664fb1a8f2a757b100363ea8958833b7754c
|
[
"Apache-2.0"
] | 36
|
2019-02-19T18:33:20.000Z
|
2022-01-24T18:02:44.000Z
|
starthinker/task/dv_editor/run.py
|
arbrown/starthinker
|
1a14664fb1a8f2a757b100363ea8958833b7754c
|
[
"Apache-2.0"
] | 54
|
2018-12-06T05:47:32.000Z
|
2022-02-21T22:01:01.000Z
|
###########################################################################
#
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
###########################################################################
from starthinker.task.dv_editor.advertiser import advertiser_clear
from starthinker.task.dv_editor.advertiser import advertiser_load
from starthinker.task.dv_editor.audit import audit_clear
from starthinker.task.dv_editor.audit import audit_load
from starthinker.task.dv_editor.bid_strategy import bid_strategy_clear
from starthinker.task.dv_editor.bid_strategy import bid_strategy_load
from starthinker.task.dv_editor.bid_strategy import bid_strategy_patch
from starthinker.task.dv_editor.campaign import campaign_clear
from starthinker.task.dv_editor.campaign import campaign_load
from starthinker.task.dv_editor.creative import creative_clear
from starthinker.task.dv_editor.creative import creative_load
from starthinker.task.dv_editor.frequency_cap import frequency_cap_clear
from starthinker.task.dv_editor.frequency_cap import frequency_cap_load
from starthinker.task.dv_editor.frequency_cap import frequency_cap_patch
from starthinker.task.dv_editor.insertion_order import insertion_order_clear
from starthinker.task.dv_editor.insertion_order import insertion_order_insert
from starthinker.task.dv_editor.insertion_order import insertion_order_load
from starthinker.task.dv_editor.insertion_order import insertion_order_patch
from starthinker.task.dv_editor.integration_detail import integration_detail_clear
from starthinker.task.dv_editor.integration_detail import integration_detail_load
from starthinker.task.dv_editor.integration_detail import integration_detail_patch
from starthinker.task.dv_editor.line_item import line_item_clear
from starthinker.task.dv_editor.line_item import line_item_insert
from starthinker.task.dv_editor.line_item import line_item_load
from starthinker.task.dv_editor.line_item import line_item_patch
from starthinker.task.dv_editor.line_item_map import line_item_map_clear
from starthinker.task.dv_editor.line_item_map import line_item_map_patch
from starthinker.task.dv_editor.pacing import pacing_clear
from starthinker.task.dv_editor.pacing import pacing_load
from starthinker.task.dv_editor.pacing import pacing_patch
from starthinker.task.dv_editor.patch import patch_clear
from starthinker.task.dv_editor.partner import partner_clear
from starthinker.task.dv_editor.partner import partner_load
from starthinker.task.dv_editor.partner_cost import partner_cost_clear
from starthinker.task.dv_editor.partner_cost import partner_cost_load
from starthinker.task.dv_editor.partner_cost import partner_cost_patch
from starthinker.task.dv_editor.segment import segment_clear
from starthinker.task.dv_editor.segment import segment_load
from starthinker.task.dv_editor.segment import segment_patch
def dv_editor(config, task):
print('COMMAND:', task['command'])
if task['command'] == 'Load Partners':
partner_clear(config, task)
partner_load(config, task)
pass
elif task['command'] == 'Load Advertisers':
advertiser_clear(config, task)
advertiser_load(config, task)
elif task['command'] == 'Load Campaigns':
campaign_clear(config, task)
campaign_load(config, task)
elif task['command'] == 'Load Insertion Orders and Line Items':
creative_clear(config, task)
creative_load(config, task)
insertion_order_clear(config, task)
insertion_order_load(config, task)
line_item_clear(config, task)
line_item_load(config, task)
segment_clear(config, task)
segment_load(config, task)
pacing_clear(config, task)
pacing_load(config, task)
bid_strategy_clear(config, task)
bid_strategy_load(config, task)
frequency_cap_clear(config, task)
frequency_cap_load(config, task)
partner_cost_clear(config, task)
partner_cost_load(config, task)
integration_detail_clear(config, task)
integration_detail_load(config, task)
elif task['command'] in ('Preview', 'Update'):
audit_clear(config, task)
patch_clear(config, task)
audit_load(config, task)
line_item_insert(config, task, commit=task['command'] == 'Update')
insertion_order_insert(config, task, commit=task['command'] == 'Update')
insertion_order_patch(config, task, commit=task['command'] == 'Update')
line_item_patch(config, task, commit=task['command'] == 'Update')
line_item_map_patch(config, task, commit=task['command'] == 'Update')
segment_patch(config, task, commit=task['command'] == 'Update')
pacing_patch(config, task, commit=task['command'] == 'Update')
bid_strategy_patch(config, task, commit=task['command'] == 'Update')
frequency_cap_patch(config, task, commit=task['command'] == 'Update')
partner_cost_patch(config, task, commit=task['command'] == 'Update')
integration_detail_patch(config, task, commit=task['command'] == 'Update')
elif task['command'] == 'Clear Partners':
partner_clear(config, task)
elif task['command'] == 'Clear Advertisers':
advertiser_clear(config, task)
elif task['command'] == 'Clear Campaigns':
campaign_clear(config, task)
elif task['command'] == 'Clear Insertion Orders and Line Items':
creative_clear(config, task)
segment_clear(config, task)
pacing_clear(config, task)
bid_strategy_clear(config, task)
frequency_cap_clear(config, task)
partner_cost_clear(config, task)
integration_detail_clear(config, task)
insertion_order_clear(config, task)
line_item_map_clear(config, task)
line_item_clear(config, task)
elif task['command'] == 'Clear Preview':
audit_clear(config, task)
elif task['command'] == 'Clear Update':
patch_clear(config, task)
elif task['command'] == 'Clear All':
partner_clear(config, task)
advertiser_clear(config, task)
campaign_clear(config, task)
creative_clear(config, task)
segment_clear(config, task)
pacing_clear(config, task)
bid_strategy_clear(config, task)
frequency_cap_clear(config, task)
partner_cost_clear(config, task)
integration_detail_clear(config, task)
insertion_order_clear(config, task)
line_item_map_clear(config, task)
line_item_clear(config, task)
audit_clear(config, task)
patch_clear(config, task)
| 41.858896
| 82
| 0.768137
| 922
| 6,823
| 5.43167
| 0.117137
| 0.13778
| 0.131789
| 0.163538
| 0.833267
| 0.783347
| 0.735623
| 0.584864
| 0.432308
| 0.356629
| 0
| 0.001336
| 0.122673
| 6,823
| 162
| 83
| 42.117284
| 0.835282
| 0.081636
| 0
| 0.360656
| 0
| 0
| 0.073947
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008197
| false
| 0.008197
| 0.319672
| 0
| 0.327869
| 0.008197
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
56babf714dc393c77ea407604857be398a228d42
| 726
|
py
|
Python
|
waveorder/io/reader_interface.py
|
mehta-lab/waveorder
|
9892c20955d3487778fd440a0d7f4f86334e7b8e
|
[
"Unlicense"
] | 2
|
2020-12-19T02:55:09.000Z
|
2022-02-24T19:40:26.000Z
|
waveorder/io/reader_interface.py
|
mehta-lab/waveorder
|
9892c20955d3487778fd440a0d7f4f86334e7b8e
|
[
"Unlicense"
] | 42
|
2021-01-20T22:34:14.000Z
|
2022-03-31T00:13:37.000Z
|
waveorder/io/reader_interface.py
|
mehta-lab/waveorder
|
9892c20955d3487778fd440a0d7f4f86334e7b8e
|
[
"Unlicense"
] | null | null | null |
import zarr
import numpy as np
class ReaderInterface:
def get_zarr(self, position: int) -> zarr.array:
pass
def get_array(self, position: int) -> np.ndarray:
pass
def get_image(self, p, t, c, z):
pass
def get_num_positions(self) -> int:
pass
# def mm_meta(self) -> int:
# return
#
# def stage_positions(self):
# pass
#
# def z_step_size(self):
# pass
#
# def height(self):
# pass
#
# def width(self):
# pass
#
# def frames(self):
# pass
#
# def slices(self):
# pass
#
# def channels(self):
# pass
#
# def channel_names(self):
# pass
| 16.883721
| 53
| 0.495868
| 84
| 726
| 4.166667
| 0.416667
| 0.22
| 0.22
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.38843
| 726
| 43
| 54
| 16.883721
| 0.788288
| 0.37741
| 0
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.363636
| false
| 0.363636
| 0.181818
| 0
| 0.636364
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
56dd61c2ca6959c5530145fd4c1470e832c4d460
| 712
|
py
|
Python
|
src/pronunciation_dict_parser/core/__init__.py
|
stefantaubert/pronunciation_dict_parser
|
e4ffcce21e93d74fb6b5b2343daf394a2584fbb4
|
[
"MIT"
] | null | null | null |
src/pronunciation_dict_parser/core/__init__.py
|
stefantaubert/pronunciation_dict_parser
|
e4ffcce21e93d74fb6b5b2343daf394a2584fbb4
|
[
"MIT"
] | null | null | null |
src/pronunciation_dict_parser/core/__init__.py
|
stefantaubert/pronunciation_dict_parser
|
e4ffcce21e93d74fb6b5b2343daf394a2584fbb4
|
[
"MIT"
] | null | null | null |
from pronunciation_dict_parser.core.export import to_text
from pronunciation_dict_parser.core.parser import (get_occurring_symbols,
parse_dictionary_from_txt,
parse_url)
from pronunciation_dict_parser.core.public_dicts import (PublicDictType,
get_dict_from_name,
parse_public_dict)
from pronunciation_dict_parser.core.types import (Pronunciation,
PronunciationDict,
Pronunciations, Symbol, Word)
| 64.727273
| 79
| 0.491573
| 53
| 712
| 6.207547
| 0.471698
| 0.206687
| 0.255319
| 0.328267
| 0.3769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.477528
| 712
| 10
| 80
| 71.2
| 0.884409
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
56f0aed7a111eac28453908e8748d60ff9a427a0
| 9,154
|
py
|
Python
|
image-processing/img_processing.py
|
jadsonjs/DataScience
|
61d09064d438fd7a910cbc2bd8f1107e27d5cd5c
|
[
"Apache-2.0"
] | null | null | null |
image-processing/img_processing.py
|
jadsonjs/DataScience
|
61d09064d438fd7a910cbc2bd8f1107e27d5cd5c
|
[
"Apache-2.0"
] | null | null | null |
image-processing/img_processing.py
|
jadsonjs/DataScience
|
61d09064d438fd7a910cbc2bd8f1107e27d5cd5c
|
[
"Apache-2.0"
] | null | null | null |
#
# This program is distributed without any warranty and it
# can be freely redistributed for research, classes or private studies,
# since the copyright notices are not removed.
#
# This file performs image processing in pyhton
#
# Jadson Santos - jadsonjs@gmail.com
#
# http://www.scipy-lectures.org/advanced/image_processing/
#
# to run this exemple install pyhton modules:
#
# python3 -m pip install Pillow
# python3 -m pip install SciPy
# python3 -m pip install numpy
# python3 -m pip install matplotlib
#
# USING PIL
#
#LA mode has luminosity (brightness) and alpha.
#If you use LA mode, then greyscale.png will be an RGBA
#image with the alpha channel of image.png preserved.
#If you use L mode, then greyscale.png will be an RGB image (with no alpha
#
#https://stackoverflow.com/questions/12201577/how-can-i-convert-an-rgb-image-into-grayscale-in-python
#
from PIL import Image
im = Image.open("/Users/jadson/Desktop/DL04_Img1.jpg")
imgGray = im.convert('LA')
imgGray.show()
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from scipy import misc
from scipy import ndimage
#
# Function the convert a RGB array to grayscale array
# Using Y' = 0.299 R + 0.587 G + 0.114 B
#
# https://en.wikipedia.org/wiki/Grayscale#Converting_color_to_grayscale
#
def rgb2gray(rgbImg):
return np.dot(rgbImg[...,:3], [0.299, 0.587, 0.114]).astype(np.uint8)
# Read the image as array
img1 = misc.imread('/Users/jadson/Desktop/DL04_Img1.jpg')
print(type(img1)) # print the img1 type
print(img1[0, 40]) # the value of possition 0,40
print(img1.shape) # print the dimesions of image
print(img1.dtype) # dtype uint8 = 0 to 255 values
img1Gray = rgb2gray(img1)
print(type(img1Gray)) # print the img1 type
print(img1Gray[0, 40]) # the value of possition 0,40
print(img1Gray.shape) # print the dimesions of image
print(img1Gray.dtype) # dtype uint8 = 0 to 255 values
# gaussian filters
blurred_image1 = ndimage.gaussian_filter(img1Gray, sigma=3)
blurred_image2 = ndimage.gaussian_filter(img1Gray, sigma=7)
blurred_image3 = ndimage.gaussian_filter(img1Gray, sigma=11)
blurred_image4 = ndimage.gaussian_filter(img1, sigma=11)
mask3 = np.array([[1/9, 1/9, 1/9],
[1/9, 1/9, 1/9],
[1/9, 1/9, 1/9],
[1/9, 1/9, 1/9]])
mask7 = np.array([ [1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49],
[1/49, 1/49, 1/49, 1/49, 1/49, 1/49, 1/49]])
mask11 = np.array([ [1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121]
])
mask113D = np.array([ [ [1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121]
],
[
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121]
],
[
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121],
[1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121, 1/121]
]
])
average3 = ndimage.convolve(img1Gray, mask3);
average7 = ndimage.convolve(img1Gray, mask7);
average11 = ndimage.convolve(img1Gray, mask11);
originalAverage11 = ndimage.convolve(img1, mask113D);
plt.imshow(average3, cmap = plt.get_cmap('gray'))
plt.suptitle('Convolution Average 3x3')
plt.show()
plt.imshow(average7, cmap = plt.get_cmap('gray'))
plt.suptitle('Convolution Average 7x7')
plt.show()
plt.imshow(average11, cmap = plt.get_cmap('gray'))
plt.suptitle('Convolution Average 11x11')
plt.show()
plt.imshow(originalAverage11)
plt.suptitle('Convolution Average 11x11 In Original Image')
plt.show()
plt.imshow(img1Gray, cmap = plt.get_cmap('gray'))
plt.suptitle('Original Image')
plt.show()
print('--- Image Reconstruction ---')
img2 = misc.imread('/Users/jadson/Desktop/DL04_Img2.2.jpg')
img3 = misc.imread('/Users/jadson/Desktop/DL04_Img2.1.jpg')
img2Gray = rgb2gray(img2)
img3Gray = rgb2gray(img3)
medianImg = ndimage.median_filter(img2Gray, 3)
averageImg = ndimage.convolve(img2Gray, mask3);
plt.imshow(medianImg, cmap = plt.get_cmap('gray'))
plt.suptitle('Reconstruction with Median Filter 3x3')
plt.show()
plt.imshow(averageImg, cmap = plt.get_cmap('gray'))
plt.suptitle('Reconstruction with Average Filter 3x3')
plt.show()
plt.imshow(img3Gray, cmap = plt.get_cmap('gray'))
plt.suptitle('Original Image')
plt.show()
#plt.imshow(blurred_image1, cmap = plt.get_cmap('gray'))
#plt.show()
#plt.imshow(blurred_image2, cmap = plt.get_cmap('gray'))
#plt.show()
#plt.imshow(blurred_image3, cmap = plt.get_cmap('gray'))
#plt.show()
#plt.imshow(blurred_image4)
#plt.show()
# show the imagem
#plt.imshow(img1Gray)
#plt.imshow(img1, cmap = plt.get_cmap('gray'))
#plt.show()
#from scipy import misc
#face = misc.face(gray=True)
#misc.imsave('/Users/jadson/Desktop/DL04_Img1.jpg', face)
#face = misc.imread('face.png')
#plt.imshow(imgGray)
#plt.show()
#imgGray[0, 40]
print('--- END ---')
| 40.504425
| 102
| 0.585646
| 1,800
| 9,154
| 2.96
| 0.106667
| 0.396396
| 0.493619
| 0.78979
| 0.653529
| 0.614302
| 0.57958
| 0.527965
| 0.527965
| 0.472598
| 0
| 0.339456
| 0.20898
| 9,154
| 225
| 103
| 40.684444
| 0.396354
| 0.188661
| 0
| 0.527559
| 0
| 0
| 0.0584
| 0.019557
| 0
| 0
| 0
| 0
| 0
| 1
| 0.007874
| false
| 0
| 0.047244
| 0.007874
| 0.062992
| 0.07874
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
710f8b37802d704812e074e8494849a0e74fa235
| 304
|
py
|
Python
|
scripts/pitchfork_crawler/src/utils/levenshtein_distance.py
|
NicolasCaous/anthonytron
|
2690cad66174e196b53e4f6dc9b0b28a62c602b3
|
[
"MIT"
] | null | null | null |
scripts/pitchfork_crawler/src/utils/levenshtein_distance.py
|
NicolasCaous/anthonytron
|
2690cad66174e196b53e4f6dc9b0b28a62c602b3
|
[
"MIT"
] | 1
|
2021-06-02T00:30:04.000Z
|
2021-06-02T00:30:04.000Z
|
scripts/pitchfork_crawler/src/utils/levenshtein_distance.py
|
NicolasCaous/anthonytron
|
2690cad66174e196b53e4f6dc9b0b28a62c602b3
|
[
"MIT"
] | null | null | null |
from Levenshtein import distance
def LD(s, t):
return distance(s.lower(), t.lower())
def LD_confidence(ld, length_album_name, length_artist_name):
if ld > (length_album_name + length_artist_name):
return 0
else:
return 1.0 - ld / (length_album_name + length_artist_name)
| 21.714286
| 66
| 0.690789
| 45
| 304
| 4.377778
| 0.422222
| 0.121827
| 0.19797
| 0.258883
| 0.502538
| 0.502538
| 0.502538
| 0
| 0
| 0
| 0
| 0.0125
| 0.210526
| 304
| 13
| 67
| 23.384615
| 0.808333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.125
| 0.125
| 0.75
| 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
| 1
| 0
|
0
| 5
|
711d545735a9aa1d3443a18f9ea077ee2c93ff8a
| 98
|
py
|
Python
|
pupil/__init__.py
|
hadi-gharibi/pupil
|
9d266572cc1ebf659e87206be6e5f1548959d510
|
[
"Apache-2.0"
] | 2
|
2022-03-31T23:17:14.000Z
|
2022-03-31T23:24:58.000Z
|
pupil/__init__.py
|
hadi-gharibi/pupil
|
9d266572cc1ebf659e87206be6e5f1548959d510
|
[
"Apache-2.0"
] | null | null | null |
pupil/__init__.py
|
hadi-gharibi/pupil
|
9d266572cc1ebf659e87206be6e5f1548959d510
|
[
"Apache-2.0"
] | null | null | null |
from .annotation import DataFrameAnnotator, PupilDBAnnotator
from .pupil import PriorityGenerator
| 32.666667
| 60
| 0.877551
| 9
| 98
| 9.555556
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.091837
| 98
| 2
| 61
| 49
| 0.966292
| 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
| 1
| 0
|
0
| 5
|
71255ceda3ca20b891e69888a955b987ae5cef73
| 57
|
py
|
Python
|
aula02.py
|
danielambr/Curso-Python
|
5e7a17583cf4118a1db574cbd7978354db61f40a
|
[
"MIT"
] | null | null | null |
aula02.py
|
danielambr/Curso-Python
|
5e7a17583cf4118a1db574cbd7978354db61f40a
|
[
"MIT"
] | null | null | null |
aula02.py
|
danielambr/Curso-Python
|
5e7a17583cf4118a1db574cbd7978354db61f40a
|
[
"MIT"
] | null | null | null |
print("Olá\nMundo!")
print("""Olá
Mundo""")
| 14.25
| 22
| 0.473684
| 6
| 57
| 4.5
| 0.666667
| 0.592593
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.280702
| 57
| 4
| 22
| 14.25
| 0.658537
| 0
| 0
| 0
| 0
| 0
| 0.568966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.666667
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8540a505322d5f71a92064fee9061673c674b5d3
| 106
|
py
|
Python
|
sparv/modules/saldo/__init__.py
|
heatherleaf/sparv-pipeline
|
0fe5f27d0d82548ecc6cb21a69289668aac54cf1
|
[
"MIT"
] | 17
|
2018-09-21T07:01:45.000Z
|
2022-02-24T23:26:49.000Z
|
sparv/modules/saldo/__init__.py
|
heatherleaf/sparv-pipeline
|
0fe5f27d0d82548ecc6cb21a69289668aac54cf1
|
[
"MIT"
] | 146
|
2018-11-13T19:13:25.000Z
|
2022-03-31T09:57:56.000Z
|
sparv/modules/saldo/__init__.py
|
heatherleaf/sparv-pipeline
|
0fe5f27d0d82548ecc6cb21a69289668aac54cf1
|
[
"MIT"
] | 5
|
2019-02-14T00:50:38.000Z
|
2021-03-29T15:37:41.000Z
|
"""SALDO-related annotations."""
from . import compound, nst_comp_model, saldo, saldo_model, stats_model
| 26.5
| 71
| 0.773585
| 14
| 106
| 5.571429
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103774
| 106
| 3
| 72
| 35.333333
| 0.821053
| 0.245283
| 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
| 1
| 0
|
0
| 5
|
857164ce5c064a4a3a32c0c49f3cb15bfc1b54b3
| 6,967
|
py
|
Python
|
StudArt/tests/artwork/views/test_CreateArtworkAPIView.py
|
YuriyLisovskiy/OOA_Team_X-A
|
f8a977f5f498e33c69df1ed503d1e44d5f5b99a5
|
[
"MIT"
] | null | null | null |
StudArt/tests/artwork/views/test_CreateArtworkAPIView.py
|
YuriyLisovskiy/OOA_Team_X-A
|
f8a977f5f498e33c69df1ed503d1e44d5f5b99a5
|
[
"MIT"
] | 10
|
2020-11-06T08:37:02.000Z
|
2020-12-09T23:08:25.000Z
|
StudArt/tests/artwork/views/test_CreateArtworkAPIView.py
|
YuriyLisovskiy/OOA_Team_X-A
|
f8a977f5f498e33c69df1ed503d1e44d5f5b99a5
|
[
"MIT"
] | 1
|
2021-09-16T10:56:02.000Z
|
2021-09-16T10:56:02.000Z
|
from django.urls import reverse
from os.path import join, dirname
from rest_framework import status
from tests.common import APIFactoryTestCase
from rest_framework_jwt.serializers import User
from rest_framework.test import force_authenticate
from django.core.files.uploadedfile import SimpleUploadedFile
from artwork.views.artwork import CreateArtworkAPIView, ArtworkAPIView
class CreateArtworkTestCase(APIFactoryTestCase):
def setUp(self) -> None:
super(CreateArtworkTestCase, self).setUp()
self.view = CreateArtworkAPIView.as_view()
self.view_getArtwork = ArtworkAPIView.as_view()
self.user = User.objects.create_user(username='olivia', password='StrongPassword12345')
def test_CreateOneImageOneTagAuthenticated(self):
img_path = join(dirname(dirname(dirname(__file__))), join("img", "test_image.jpg"))
image = SimpleUploadedFile(name='test_image.jpg', content=open(img_path, 'rb').read(),
content_type='image/jpeg')
post_description = 'Description of new artwork'
tags = ['new tag']
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': post_description, 'tags': tags, 'images': [image]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
new_id = response.data['id']
request = self.request_factory.get(reverse('api_v1:artwork:get_artwork', args=[new_id]))
response = self.view_getArtwork(request, pk=new_id)
self.assertEqual(response.data['description'], post_description)
self.assertEqual(response.data['tags'], tags)
self.assertEqual(len(response.data['images']), 1)
def test_CreateMultipleImagesOneTagAuthenticated(self):
img_path = join(dirname(dirname(dirname(__file__))), join("img", "test_image.jpg"))
img_path2 = join(dirname(dirname(dirname(__file__))), join("img", "test_image2.jpg"))
img_path3 = join(dirname(dirname(dirname(__file__))), join("img", "test_image3.jpg"))
image = SimpleUploadedFile(name='test_image.jpg', content=open(img_path, 'rb').read(),
content_type='image/jpeg')
image2 = SimpleUploadedFile(name='test_image2.jpg', content=open(img_path2, 'rb').read(),
content_type='image/jpeg')
image3 = SimpleUploadedFile(name='test_image3.jpg', content=open(img_path3, 'rb').read(),
content_type='image/jpeg')
post_description = 'Description of new artwork'
tags = ['new tag']
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': post_description, 'tags': tags,
'images': [image, image2, image3]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
new_id = response.data['id']
request = self.request_factory.get(reverse('api_v1:artwork:get_artwork', args=[new_id]))
response = self.view_getArtwork(request, pk=new_id)
self.assertEqual(response.data['description'], post_description)
self.assertEqual(response.data['tags'], tags)
self.assertEqual(len(response.data['images']), 3)
def test_CreateOneImgMultipleTagsAuthenticated(self):
img_path = join(dirname(dirname(dirname(__file__))), join("img", "test_image.jpg"))
image = SimpleUploadedFile(name='test_image.jpg', content=open(img_path, 'rb').read(),
content_type='image/jpeg')
post_description = 'Description of new artwork'
tags = ['new tag', 'new tag 2', 'new tag 3']
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': post_description, 'tags': tags, 'images': [image]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
new_id = response.data['id']
request = self.request_factory.get(reverse('api_v1:artwork:get_artwork', args=[new_id]))
response = self.view_getArtwork(request, pk=new_id)
self.assertEqual(response.data['description'], post_description)
self.assertEqual(response.data['tags'], tags)
self.assertEqual(len(response.data['images']), 1)
def test_CreateNoImgAuthenticated(self):
i = list()
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': 'Description of new artwork', 'tags': ['new tag'],
'images': i})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
# todo: can't replicate empty list. current request sends with missing images field
def test_CreateNoTagsAuthenticated(self):
img_path = join(dirname(dirname(dirname(__file__))), join("img", "test_image.jpg"))
image = SimpleUploadedFile(name='test_image.jpg', content=open(img_path, 'rb').read(),
content_type='image/jpeg')
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': 'Description of new artwork', 'tags': [],
'images': [image]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
# todo: can't replicate empty list. current request sends with missing tags field
def test_CreateMissingFieldDescriptionAuthenticated(self):
request = self.request_factory.post(reverse('api_v1:artwork:create'), {'tags': ['new tag'], 'images': [
SimpleUploadedFile(name='test_image.jpg',
content=open(join(dirname(dirname(dirname(__file__))), join("img", "test_image.jpg")),
'rb').read(), content_type='image/jpeg')]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_CreateMissingFieldTagsAuthenticated(self):
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': 'Description of new artwork', 'images': [
SimpleUploadedFile(name='test_image.jpg', content=open(
join(dirname(dirname(dirname(__file__))),
join("img", "test_image.jpg")), 'rb').read(),
content_type='image/jpeg')]})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_CreateMissingFieldImagesAuthenticated(self):
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': 'Description of new artwork', 'tags': ['new tag']})
force_authenticate(request, user=self.user)
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_CreateUnauthenticated(self):
request = self.request_factory.post(reverse('api_v1:artwork:create'),
{'description': 'Description of new artwork', 'tags': ['new tag']})
response = self.view(request)
self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)
| 51.227941
| 105
| 0.734606
| 860
| 6,967
| 5.748837
| 0.12907
| 0.046723
| 0.069782
| 0.06068
| 0.773058
| 0.773058
| 0.767799
| 0.767799
| 0.751618
| 0.751618
| 0
| 0.01
| 0.124444
| 6,967
| 135
| 106
| 51.607407
| 0.800492
| 0.023109
| 0
| 0.613445
| 0
| 0
| 0.168455
| 0.039247
| 0
| 0
| 0
| 0.007407
| 0.151261
| 1
| 0.084034
| false
| 0.008403
| 0.067227
| 0
| 0.159664
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 5
|
8585e25b45ba094b8effa5e2535011b16f9900f5
| 5,206
|
py
|
Python
|
etl/parsers/etw/Microsoft_Windows_AppModel_State.py
|
IMULMUL/etl-parser
|
76b7c046866ce0469cd129ee3f7bb3799b34e271
|
[
"Apache-2.0"
] | 104
|
2020-03-04T14:31:31.000Z
|
2022-03-28T02:59:36.000Z
|
etl/parsers/etw/Microsoft_Windows_AppModel_State.py
|
IMULMUL/etl-parser
|
76b7c046866ce0469cd129ee3f7bb3799b34e271
|
[
"Apache-2.0"
] | 7
|
2020-04-20T09:18:39.000Z
|
2022-03-19T17:06:19.000Z
|
etl/parsers/etw/Microsoft_Windows_AppModel_State.py
|
IMULMUL/etl-parser
|
76b7c046866ce0469cd129ee3f7bb3799b34e271
|
[
"Apache-2.0"
] | 16
|
2020-03-05T18:55:59.000Z
|
2022-03-01T10:19:28.000Z
|
# -*- coding: utf-8 -*-
"""
Microsoft-Windows-AppModel-State
GUID : bff15e13-81bf-45ee-8b16-7cfead00da86
"""
from construct import Int8sl, Int8ul, Int16ul, Int16sl, Int32sl, Int32ul, Int64sl, Int64ul, Bytes, Double, Float32l, Struct
from etl.utils import WString, CString, SystemTime, Guid
from etl.dtyp import Sid
from etl.parsers.etw.core import Etw, declare, guid
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=1, version=0)
class Microsoft_Windows_AppModel_State_1_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=2, version=0)
class Microsoft_Windows_AppModel_State_2_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=4, version=0)
class Microsoft_Windows_AppModel_State_4_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=5, version=0)
class Microsoft_Windows_AppModel_State_5_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=8, version=0)
class Microsoft_Windows_AppModel_State_8_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=10, version=0)
class Microsoft_Windows_AppModel_State_10_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=11, version=0)
class Microsoft_Windows_AppModel_State_11_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=12, version=0)
class Microsoft_Windows_AppModel_State_12_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=13, version=0)
class Microsoft_Windows_AppModel_State_13_0(Etw):
pattern = Struct(
"FolderString" / WString,
"PackageString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=14, version=0)
class Microsoft_Windows_AppModel_State_14_0(Etw):
pattern = Struct(
"PackageString" / WString,
"UserSid" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=15, version=0)
class Microsoft_Windows_AppModel_State_15_0(Etw):
pattern = Struct(
"PackageString" / WString,
"UserSid" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=16, version=0)
class Microsoft_Windows_AppModel_State_16_0(Etw):
pattern = Struct(
"PackageString" / WString,
"UserSid" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=17, version=0)
class Microsoft_Windows_AppModel_State_17_0(Etw):
pattern = Struct(
"PackageString" / WString,
"UserSid" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=18, version=0)
class Microsoft_Windows_AppModel_State_18_0(Etw):
pattern = Struct(
"InformationalString" / WString
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=19, version=0)
class Microsoft_Windows_AppModel_State_19_0(Etw):
pattern = Struct(
"ErrorString" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=20, version=0)
class Microsoft_Windows_AppModel_State_20_0(Etw):
pattern = Struct(
"Operation" / WString,
"PackageFamily" / WString,
"OperationError" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=21, version=0)
class Microsoft_Windows_AppModel_State_21_0(Etw):
pattern = Struct(
"Operation" / WString,
"PackageFamily" / WString,
"OperationError" / Int32sl,
"RepairTriggerError" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=22, version=0)
class Microsoft_Windows_AppModel_State_22_0(Etw):
pattern = Struct(
"FolderPath" / WString,
"Error" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=23, version=0)
class Microsoft_Windows_AppModel_State_23_0(Etw):
pattern = Struct(
"Operation" / WString,
"PackageFamily" / WString,
"OperationError" / Int32sl
)
@declare(guid=guid("bff15e13-81bf-45ee-8b16-7cfead00da86"), event_id=24, version=0)
class Microsoft_Windows_AppModel_State_24_0(Etw):
pattern = Struct(
"Operation" / WString,
"PackageFamily" / WString,
"OperationError" / Int32sl,
"RepairTriggerError" / Int32sl
)
| 28.762431
| 123
| 0.685363
| 610
| 5,206
| 5.652459
| 0.122951
| 0.097448
| 0.146172
| 0.176624
| 0.87442
| 0.87442
| 0.863979
| 0.62036
| 0.62036
| 0.62036
| 0
| 0.119329
| 0.187092
| 5,206
| 180
| 124
| 28.922222
| 0.695416
| 0.019017
| 0
| 0.5
| 0
| 0
| 0.236956
| 0.141232
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.029851
| 0
| 0.328358
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
a4423c21790b7d8dc2d8ead79c46ad936fe4229f
| 36
|
py
|
Python
|
data/__init__.py
|
Mozirra/mtghelper
|
57ccc201e385edc2166cfe9746b47f1b224359e9
|
[
"MIT"
] | null | null | null |
data/__init__.py
|
Mozirra/mtghelper
|
57ccc201e385edc2166cfe9746b47f1b224359e9
|
[
"MIT"
] | null | null | null |
data/__init__.py
|
Mozirra/mtghelper
|
57ccc201e385edc2166cfe9746b47f1b224359e9
|
[
"MIT"
] | null | null | null |
"""The "Data" Django applcation."""
| 18
| 35
| 0.638889
| 4
| 36
| 5.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 36
| 1
| 36
| 36
| 0.71875
| 0.805556
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
a4455f687c86ce2fea04312ac9c5b53605a75ab9
| 53
|
py
|
Python
|
MACD/huobi_Python-1.0.3/huobi/impl/__init__.py
|
yangdemin/dingpan
|
0b68c7f9b497c7becab6ec3e7a2b21b5c03a1dd9
|
[
"MIT"
] | 1
|
2020-12-28T07:04:45.000Z
|
2020-12-28T07:04:45.000Z
|
MACD/huobi_Python-1.0.3/huobi/impl/__init__.py
|
yangdemin/dingpan
|
0b68c7f9b497c7becab6ec3e7a2b21b5c03a1dd9
|
[
"MIT"
] | 1
|
2020-12-05T11:41:35.000Z
|
2020-12-05T11:41:35.000Z
|
MACD/huobi_Python-1.0.3/huobi/impl/__init__.py
|
yangdemin/dingpan
|
0b68c7f9b497c7becab6ec3e7a2b21b5c03a1dd9
|
[
"MIT"
] | 1
|
2022-03-27T10:36:04.000Z
|
2022-03-27T10:36:04.000Z
|
from huobi.impl.restapirequest import RestApiRequest
| 26.5
| 52
| 0.886792
| 6
| 53
| 7.833333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075472
| 53
| 1
| 53
| 53
| 0.959184
| 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
| 1
| 0
|
0
| 5
|
a4717a40308917d695a6d6ce340ce1023fb3b9f4
| 211
|
py
|
Python
|
agant/models/pytorch/loss/Mean.py
|
Sinha-Raunak/gan-toolkit
|
6d2d86833bb00833b2d9cd11a1a83476f44b65fd
|
[
"MIT"
] | 47
|
2018-09-04T23:52:15.000Z
|
2022-03-14T02:07:15.000Z
|
agant/models/pytorch/loss/Mean.py
|
Sinha-Raunak/gan-toolkit
|
6d2d86833bb00833b2d9cd11a1a83476f44b65fd
|
[
"MIT"
] | 6
|
2018-09-14T20:34:31.000Z
|
2019-10-27T18:25:00.000Z
|
agant/models/pytorch/loss/Mean.py
|
Sinha-Raunak/gan-toolkit
|
6d2d86833bb00833b2d9cd11a1a83476f44b65fd
|
[
"MIT"
] | 11
|
2018-09-14T08:52:18.000Z
|
2020-06-29T14:16:16.000Z
|
import torch
import numpy as np
from torch.autograd import Variable
class loss_block:
def __init__(self):
super(loss_block, self).__init__()
def loss(self,input_vals,lables):
return torch.mean(input_vals)
| 23.444444
| 36
| 0.78673
| 33
| 211
| 4.666667
| 0.606061
| 0.116883
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.123223
| 211
| 9
| 37
| 23.444444
| 0.832432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.375
| 0.125
| 0.875
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
f103dfc36b34f0d6e9318de2b3d835c4057e9cb1
| 3,766
|
py
|
Python
|
storm/models/simple/_spectra.py
|
LoganAMorrison/Storm
|
b189f276064a904d1792a10249fa3555237e3062
|
[
"MIT"
] | null | null | null |
storm/models/simple/_spectra.py
|
LoganAMorrison/Storm
|
b189f276064a904d1792a10249fa3555237e3062
|
[
"MIT"
] | null | null | null |
storm/models/simple/_spectra.py
|
LoganAMorrison/Storm
|
b189f276064a904d1792a10249fa3555237e3062
|
[
"MIT"
] | null | null | null |
"""
Module containing the simpler definitions of the spectra functions for the
`SimpleRhNeutrino` model.
"""
import numpy as np
from storm.models.simple._simple_spectra import (
spectrum_vr_to_vl_h as _dndx_vl_h,
spectrum_vr_to_vl_z as _dndx_vl_z,
spectrum_vr_to_l_w as _dndx_l_w,
spectrum_vr_to_vl_u_u as _dndx_vl_u_u,
spectrum_vr_to_vl_d_d as _dndx_vl_d_d,
spectrum_vr_to_l_u_d as _dndx_l_u_d,
spectrum_vr_to_vl_l_l as _dndx_vl_l_l,
spectrum_vr_to_vl_lp_lp as _dndx_vl_lp_lp,
spectrum_vr_to_vlp_lp_l as _dndx_vlp_lp_l,
)
def dndx_vl_h(**kwargs):
spec = _dndx_vl_h(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vl_z(**kwargs):
spec = _dndx_vl_z(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_l_w(**kwargs):
spec = _dndx_l_w(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
anti=kwargs["anti"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vl_u_u(**kwargs):
spec = _dndx_vl_u_u(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
genq=kwargs["genq"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vl_d_d(**kwargs):
spec = _dndx_vl_d_d(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
genq=kwargs["genq"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_l_u_d(**kwargs):
spec = _dndx_l_u_d(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
genq=kwargs["genq"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
anti=kwargs["anti"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vl_l_l(**kwargs):
spec = _dndx_vl_l_l(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vl_lp_lp(**kwargs):
spec = _dndx_vl_lp_lp(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
genlp=kwargs["genlp"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
)
return np.array(spec[0]), np.array(spec[1])
def dndx_vlp_lp_l(**kwargs):
spec = _dndx_vlp_lp_l(
mvr=kwargs["mvr"],
theta=kwargs["theta"],
genl=kwargs["genl"],
genlp=kwargs["genlp"],
product=kwargs["product"],
xbounds=kwargs["xbounds"],
nbins=kwargs["nbins"],
nevents=kwargs["nevents"],
anti=kwargs["anti"],
)
return np.array(spec[0]), np.array(spec[1])
| 26.521127
| 74
| 0.587626
| 504
| 3,766
| 4.125
| 0.097222
| 0.051948
| 0.095238
| 0.073593
| 0.731121
| 0.731121
| 0.731121
| 0.731121
| 0.731121
| 0.731121
| 0
| 0.006354
| 0.247743
| 3,766
| 141
| 75
| 26.70922
| 0.727497
| 0.026553
| 0
| 0.672269
| 0
| 0
| 0.102788
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.07563
| false
| 0
| 0.016807
| 0
| 0.168067
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 5
|
f10554c23525b09f815cfeae0d4b0bdb9d3f7f6e
| 16,028
|
py
|
Python
|
src/datadog_api_client/v2/models/__init__.py
|
anbnyc/datadog-api-client-python
|
162bd0c6f2523a809aec08a3197e85dc74b78c21
|
[
"Apache-2.0"
] | null | null | null |
src/datadog_api_client/v2/models/__init__.py
|
anbnyc/datadog-api-client-python
|
162bd0c6f2523a809aec08a3197e85dc74b78c21
|
[
"Apache-2.0"
] | null | null | null |
src/datadog_api_client/v2/models/__init__.py
|
anbnyc/datadog-api-client-python
|
162bd0c6f2523a809aec08a3197e85dc74b78c21
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
# flake8: noqa
# import all models into this package
# if you have many models here with many references from one model to another this may
# raise a RecursionError
# to avoid this, import only the models that you directly need like:
# from from datadog_api_client.v2.model.pet import Pet
# or import this package, but before doing it, use:
# import sys
# sys.setrecursionlimit(n)
from datadog_api_client.v2.model.api_error_response import APIErrorResponse
from datadog_api_client.v2.model.creator import Creator
from datadog_api_client.v2.model.dashboard_list_add_items_request import DashboardListAddItemsRequest
from datadog_api_client.v2.model.dashboard_list_add_items_response import DashboardListAddItemsResponse
from datadog_api_client.v2.model.dashboard_list_delete_items_request import DashboardListDeleteItemsRequest
from datadog_api_client.v2.model.dashboard_list_delete_items_response import DashboardListDeleteItemsResponse
from datadog_api_client.v2.model.dashboard_list_item import DashboardListItem
from datadog_api_client.v2.model.dashboard_list_item_request import DashboardListItemRequest
from datadog_api_client.v2.model.dashboard_list_item_response import DashboardListItemResponse
from datadog_api_client.v2.model.dashboard_list_items import DashboardListItems
from datadog_api_client.v2.model.dashboard_list_update_items_request import DashboardListUpdateItemsRequest
from datadog_api_client.v2.model.dashboard_list_update_items_response import DashboardListUpdateItemsResponse
from datadog_api_client.v2.model.dashboard_type import DashboardType
from datadog_api_client.v2.model.log import Log
from datadog_api_client.v2.model.log_attributes import LogAttributes
from datadog_api_client.v2.model.log_type import LogType
from datadog_api_client.v2.model.logs_aggregate_bucket import LogsAggregateBucket
from datadog_api_client.v2.model.logs_aggregate_bucket_value import LogsAggregateBucketValue
from datadog_api_client.v2.model.logs_aggregate_bucket_value_timeseries import LogsAggregateBucketValueTimeseries
from datadog_api_client.v2.model.logs_aggregate_bucket_value_timeseries_point import LogsAggregateBucketValueTimeseriesPoint
from datadog_api_client.v2.model.logs_aggregate_request import LogsAggregateRequest
from datadog_api_client.v2.model.logs_aggregate_request_paging import LogsAggregateRequestPaging
from datadog_api_client.v2.model.logs_aggregate_response import LogsAggregateResponse
from datadog_api_client.v2.model.logs_aggregate_response_data import LogsAggregateResponseData
from datadog_api_client.v2.model.logs_aggregate_response_status import LogsAggregateResponseStatus
from datadog_api_client.v2.model.logs_aggregate_sort import LogsAggregateSort
from datadog_api_client.v2.model.logs_aggregate_sort_type import LogsAggregateSortType
from datadog_api_client.v2.model.logs_aggregation_function import LogsAggregationFunction
from datadog_api_client.v2.model.logs_archive import LogsArchive
from datadog_api_client.v2.model.logs_archive_attributes import LogsArchiveAttributes
from datadog_api_client.v2.model.logs_archive_create_request import LogsArchiveCreateRequest
from datadog_api_client.v2.model.logs_archive_create_request_attributes import LogsArchiveCreateRequestAttributes
from datadog_api_client.v2.model.logs_archive_create_request_definition import LogsArchiveCreateRequestDefinition
from datadog_api_client.v2.model.logs_archive_create_request_destination import LogsArchiveCreateRequestDestination
from datadog_api_client.v2.model.logs_archive_definition import LogsArchiveDefinition
from datadog_api_client.v2.model.logs_archive_destination import LogsArchiveDestination
from datadog_api_client.v2.model.logs_archive_destination_azure import LogsArchiveDestinationAzure
from datadog_api_client.v2.model.logs_archive_destination_azure_type import LogsArchiveDestinationAzureType
from datadog_api_client.v2.model.logs_archive_destination_gcs import LogsArchiveDestinationGCS
from datadog_api_client.v2.model.logs_archive_destination_gcs_type import LogsArchiveDestinationGCSType
from datadog_api_client.v2.model.logs_archive_destination_s3 import LogsArchiveDestinationS3
from datadog_api_client.v2.model.logs_archive_destination_s3_type import LogsArchiveDestinationS3Type
from datadog_api_client.v2.model.logs_archive_integration_azure import LogsArchiveIntegrationAzure
from datadog_api_client.v2.model.logs_archive_integration_gcs import LogsArchiveIntegrationGCS
from datadog_api_client.v2.model.logs_archive_integration_s3 import LogsArchiveIntegrationS3
from datadog_api_client.v2.model.logs_archive_state import LogsArchiveState
from datadog_api_client.v2.model.logs_archives import LogsArchives
from datadog_api_client.v2.model.logs_compute import LogsCompute
from datadog_api_client.v2.model.logs_compute_type import LogsComputeType
from datadog_api_client.v2.model.logs_group_by import LogsGroupBy
from datadog_api_client.v2.model.logs_group_by_histogram import LogsGroupByHistogram
from datadog_api_client.v2.model.logs_group_by_missing import LogsGroupByMissing
from datadog_api_client.v2.model.logs_group_by_total import LogsGroupByTotal
from datadog_api_client.v2.model.logs_list_request import LogsListRequest
from datadog_api_client.v2.model.logs_list_request_page import LogsListRequestPage
from datadog_api_client.v2.model.logs_list_response import LogsListResponse
from datadog_api_client.v2.model.logs_list_response_links import LogsListResponseLinks
from datadog_api_client.v2.model.logs_query_filter import LogsQueryFilter
from datadog_api_client.v2.model.logs_query_options import LogsQueryOptions
from datadog_api_client.v2.model.logs_response_metadata import LogsResponseMetadata
from datadog_api_client.v2.model.logs_response_metadata_page import LogsResponseMetadataPage
from datadog_api_client.v2.model.logs_sort import LogsSort
from datadog_api_client.v2.model.logs_sort_order import LogsSortOrder
from datadog_api_client.v2.model.logs_warning import LogsWarning
from datadog_api_client.v2.model.organization import Organization
from datadog_api_client.v2.model.organization_attributes import OrganizationAttributes
from datadog_api_client.v2.model.organizations_type import OrganizationsType
from datadog_api_client.v2.model.pagination import Pagination
from datadog_api_client.v2.model.permission import Permission
from datadog_api_client.v2.model.permission_attributes import PermissionAttributes
from datadog_api_client.v2.model.permissions_response import PermissionsResponse
from datadog_api_client.v2.model.permissions_type import PermissionsType
from datadog_api_client.v2.model.query_sort_order import QuerySortOrder
from datadog_api_client.v2.model.relationship_to_organization import RelationshipToOrganization
from datadog_api_client.v2.model.relationship_to_organization_data import RelationshipToOrganizationData
from datadog_api_client.v2.model.relationship_to_organizations import RelationshipToOrganizations
from datadog_api_client.v2.model.relationship_to_permission import RelationshipToPermission
from datadog_api_client.v2.model.relationship_to_permission_data import RelationshipToPermissionData
from datadog_api_client.v2.model.relationship_to_permissions import RelationshipToPermissions
from datadog_api_client.v2.model.relationship_to_role import RelationshipToRole
from datadog_api_client.v2.model.relationship_to_role_data import RelationshipToRoleData
from datadog_api_client.v2.model.relationship_to_roles import RelationshipToRoles
from datadog_api_client.v2.model.relationship_to_user import RelationshipToUser
from datadog_api_client.v2.model.relationship_to_user_data import RelationshipToUserData
from datadog_api_client.v2.model.relationship_to_users import RelationshipToUsers
from datadog_api_client.v2.model.response_meta_attributes import ResponseMetaAttributes
from datadog_api_client.v2.model.role import Role
from datadog_api_client.v2.model.role_attributes import RoleAttributes
from datadog_api_client.v2.model.role_create_attributes import RoleCreateAttributes
from datadog_api_client.v2.model.role_create_data import RoleCreateData
from datadog_api_client.v2.model.role_create_request import RoleCreateRequest
from datadog_api_client.v2.model.role_create_response import RoleCreateResponse
from datadog_api_client.v2.model.role_create_response_data import RoleCreateResponseData
from datadog_api_client.v2.model.role_relationships import RoleRelationships
from datadog_api_client.v2.model.role_response import RoleResponse
from datadog_api_client.v2.model.role_response_relationships import RoleResponseRelationships
from datadog_api_client.v2.model.role_update_attributes import RoleUpdateAttributes
from datadog_api_client.v2.model.role_update_data import RoleUpdateData
from datadog_api_client.v2.model.role_update_request import RoleUpdateRequest
from datadog_api_client.v2.model.role_update_response import RoleUpdateResponse
from datadog_api_client.v2.model.role_update_response_data import RoleUpdateResponseData
from datadog_api_client.v2.model.roles_response import RolesResponse
from datadog_api_client.v2.model.roles_sort import RolesSort
from datadog_api_client.v2.model.roles_type import RolesType
from datadog_api_client.v2.model.security_monitoring_list_rules_response import SecurityMonitoringListRulesResponse
from datadog_api_client.v2.model.security_monitoring_rule_case import SecurityMonitoringRuleCase
from datadog_api_client.v2.model.security_monitoring_rule_case_create import SecurityMonitoringRuleCaseCreate
from datadog_api_client.v2.model.security_monitoring_rule_create_payload import SecurityMonitoringRuleCreatePayload
from datadog_api_client.v2.model.security_monitoring_rule_evaluation_window import SecurityMonitoringRuleEvaluationWindow
from datadog_api_client.v2.model.security_monitoring_rule_keep_alive import SecurityMonitoringRuleKeepAlive
from datadog_api_client.v2.model.security_monitoring_rule_max_signal_duration import SecurityMonitoringRuleMaxSignalDuration
from datadog_api_client.v2.model.security_monitoring_rule_options import SecurityMonitoringRuleOptions
from datadog_api_client.v2.model.security_monitoring_rule_query import SecurityMonitoringRuleQuery
from datadog_api_client.v2.model.security_monitoring_rule_query_aggregation import SecurityMonitoringRuleQueryAggregation
from datadog_api_client.v2.model.security_monitoring_rule_query_create import SecurityMonitoringRuleQueryCreate
from datadog_api_client.v2.model.security_monitoring_rule_response import SecurityMonitoringRuleResponse
from datadog_api_client.v2.model.security_monitoring_rule_severity import SecurityMonitoringRuleSeverity
from datadog_api_client.v2.model.security_monitoring_rule_update_payload import SecurityMonitoringRuleUpdatePayload
from datadog_api_client.v2.model.security_monitoring_signal import SecurityMonitoringSignal
from datadog_api_client.v2.model.security_monitoring_signal_attributes import SecurityMonitoringSignalAttributes
from datadog_api_client.v2.model.security_monitoring_signal_list_request import SecurityMonitoringSignalListRequest
from datadog_api_client.v2.model.security_monitoring_signal_list_request_filter import SecurityMonitoringSignalListRequestFilter
from datadog_api_client.v2.model.security_monitoring_signal_list_request_page import SecurityMonitoringSignalListRequestPage
from datadog_api_client.v2.model.security_monitoring_signal_type import SecurityMonitoringSignalType
from datadog_api_client.v2.model.security_monitoring_signals_list_response import SecurityMonitoringSignalsListResponse
from datadog_api_client.v2.model.security_monitoring_signals_list_response_links import SecurityMonitoringSignalsListResponseLinks
from datadog_api_client.v2.model.security_monitoring_signals_list_response_meta import SecurityMonitoringSignalsListResponseMeta
from datadog_api_client.v2.model.security_monitoring_signals_list_response_meta_page import SecurityMonitoringSignalsListResponseMetaPage
from datadog_api_client.v2.model.security_monitoring_signals_sort import SecurityMonitoringSignalsSort
from datadog_api_client.v2.model.service_create_attributes import ServiceCreateAttributes
from datadog_api_client.v2.model.service_create_data import ServiceCreateData
from datadog_api_client.v2.model.service_create_request import ServiceCreateRequest
from datadog_api_client.v2.model.service_included_items import ServiceIncludedItems
from datadog_api_client.v2.model.service_relationships import ServiceRelationships
from datadog_api_client.v2.model.service_response import ServiceResponse
from datadog_api_client.v2.model.service_response_attributes import ServiceResponseAttributes
from datadog_api_client.v2.model.service_response_data import ServiceResponseData
from datadog_api_client.v2.model.service_type import ServiceType
from datadog_api_client.v2.model.service_update_attributes import ServiceUpdateAttributes
from datadog_api_client.v2.model.service_update_data import ServiceUpdateData
from datadog_api_client.v2.model.service_update_request import ServiceUpdateRequest
from datadog_api_client.v2.model.services_response import ServicesResponse
from datadog_api_client.v2.model.services_response_meta import ServicesResponseMeta
from datadog_api_client.v2.model.services_response_meta_pagination import ServicesResponseMetaPagination
from datadog_api_client.v2.model.team_create_attributes import TeamCreateAttributes
from datadog_api_client.v2.model.team_create_data import TeamCreateData
from datadog_api_client.v2.model.team_create_request import TeamCreateRequest
from datadog_api_client.v2.model.team_included_items import TeamIncludedItems
from datadog_api_client.v2.model.team_relationships import TeamRelationships
from datadog_api_client.v2.model.team_response import TeamResponse
from datadog_api_client.v2.model.team_response_attributes import TeamResponseAttributes
from datadog_api_client.v2.model.team_response_data import TeamResponseData
from datadog_api_client.v2.model.team_type import TeamType
from datadog_api_client.v2.model.team_update_attributes import TeamUpdateAttributes
from datadog_api_client.v2.model.team_update_data import TeamUpdateData
from datadog_api_client.v2.model.team_update_request import TeamUpdateRequest
from datadog_api_client.v2.model.teams_response import TeamsResponse
from datadog_api_client.v2.model.user import User
from datadog_api_client.v2.model.user_attributes import UserAttributes
from datadog_api_client.v2.model.user_create_attributes import UserCreateAttributes
from datadog_api_client.v2.model.user_create_data import UserCreateData
from datadog_api_client.v2.model.user_create_request import UserCreateRequest
from datadog_api_client.v2.model.user_invitation_data import UserInvitationData
from datadog_api_client.v2.model.user_invitation_data_attributes import UserInvitationDataAttributes
from datadog_api_client.v2.model.user_invitation_relationships import UserInvitationRelationships
from datadog_api_client.v2.model.user_invitation_response import UserInvitationResponse
from datadog_api_client.v2.model.user_invitation_response_data import UserInvitationResponseData
from datadog_api_client.v2.model.user_invitations_request import UserInvitationsRequest
from datadog_api_client.v2.model.user_invitations_response import UserInvitationsResponse
from datadog_api_client.v2.model.user_invitations_type import UserInvitationsType
from datadog_api_client.v2.model.user_relationships import UserRelationships
from datadog_api_client.v2.model.user_response import UserResponse
from datadog_api_client.v2.model.user_response_included_item import UserResponseIncludedItem
from datadog_api_client.v2.model.user_response_relationships import UserResponseRelationships
from datadog_api_client.v2.model.user_update_attributes import UserUpdateAttributes
from datadog_api_client.v2.model.user_update_data import UserUpdateData
from datadog_api_client.v2.model.user_update_request import UserUpdateRequest
from datadog_api_client.v2.model.users_response import UsersResponse
from datadog_api_client.v2.model.users_type import UsersType
| 83.046632
| 137
| 0.915897
| 2,095
| 16,028
| 6.6358
| 0.145107
| 0.142426
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| 0.258956
| 0.550209
| 0.550209
| 0.534671
| 0.463602
| 0.307294
| 0.122932
| 0
| 0.012335
| 0.049102
| 16,028
| 192
| 138
| 83.479167
| 0.89981
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0
| 5
|
f107acbf91fc1319f15a75c56a77ccc85fd93942
| 7,894
|
py
|
Python
|
staff_manage_sdk/model/api_gateway/desktop_pb2.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | 5
|
2019-07-31T04:11:05.000Z
|
2021-01-07T03:23:20.000Z
|
webshell_sdk/model/api_gateway/desktop_pb2.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | null | null | null |
webshell_sdk/model/api_gateway/desktop_pb2.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: desktop.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='desktop.proto',
package='api_gateway',
syntax='proto3',
serialized_options=_b('ZEgo.easyops.local/contracts/protorepo-models/easyops/model/api_gateway'),
serialized_pb=_b('\n\rdesktop.proto\x12\x0b\x61pi_gateway\"\xfb\x01\n\x07\x44\x65sktop\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\r\n\x05order\x18\x02 \x01(\x05\x12)\n\x05items\x18\x03 \x03(\x0b\x32\x1a.api_gateway.Desktop.Items\x1a\xa7\x01\n\x05Items\x12\x0c\n\x04type\x18\x01 \x01(\t\x12\n\n\x02id\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\x12\x10\n\x08position\x18\x04 \x01(\x05\x12/\n\x05items\x18\x05 \x03(\x0b\x32 .api_gateway.Desktop.Items.Items\x1a\x33\n\x05Items\x12\x0c\n\x04type\x18\x01 \x01(\t\x12\n\n\x02id\x18\x02 \x01(\t\x12\x10\n\x08position\x18\x03 \x01(\x05\x42GZEgo.easyops.local/contracts/protorepo-models/easyops/model/api_gatewayb\x06proto3')
)
_DESKTOP_ITEMS_ITEMS = _descriptor.Descriptor(
name='Items',
full_name='api_gateway.Desktop.Items.Items',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='type', full_name='api_gateway.Desktop.Items.Items.type', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='api_gateway.Desktop.Items.Items.id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='position', full_name='api_gateway.Desktop.Items.Items.position', index=2,
number=3, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=231,
serialized_end=282,
)
_DESKTOP_ITEMS = _descriptor.Descriptor(
name='Items',
full_name='api_gateway.Desktop.Items',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='type', full_name='api_gateway.Desktop.Items.type', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='api_gateway.Desktop.Items.id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='api_gateway.Desktop.Items.name', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='position', full_name='api_gateway.Desktop.Items.position', index=3,
number=4, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='items', full_name='api_gateway.Desktop.Items.items', index=4,
number=5, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[_DESKTOP_ITEMS_ITEMS, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=115,
serialized_end=282,
)
_DESKTOP = _descriptor.Descriptor(
name='Desktop',
full_name='api_gateway.Desktop',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='api_gateway.Desktop.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='order', full_name='api_gateway.Desktop.order', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='items', full_name='api_gateway.Desktop.items', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[_DESKTOP_ITEMS, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=31,
serialized_end=282,
)
_DESKTOP_ITEMS_ITEMS.containing_type = _DESKTOP_ITEMS
_DESKTOP_ITEMS.fields_by_name['items'].message_type = _DESKTOP_ITEMS_ITEMS
_DESKTOP_ITEMS.containing_type = _DESKTOP
_DESKTOP.fields_by_name['items'].message_type = _DESKTOP_ITEMS
DESCRIPTOR.message_types_by_name['Desktop'] = _DESKTOP
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
Desktop = _reflection.GeneratedProtocolMessageType('Desktop', (_message.Message,), {
'Items' : _reflection.GeneratedProtocolMessageType('Items', (_message.Message,), {
'Items' : _reflection.GeneratedProtocolMessageType('Items', (_message.Message,), {
'DESCRIPTOR' : _DESKTOP_ITEMS_ITEMS,
'__module__' : 'desktop_pb2'
# @@protoc_insertion_point(class_scope:api_gateway.Desktop.Items.Items)
})
,
'DESCRIPTOR' : _DESKTOP_ITEMS,
'__module__' : 'desktop_pb2'
# @@protoc_insertion_point(class_scope:api_gateway.Desktop.Items)
})
,
'DESCRIPTOR' : _DESKTOP,
'__module__' : 'desktop_pb2'
# @@protoc_insertion_point(class_scope:api_gateway.Desktop)
})
_sym_db.RegisterMessage(Desktop)
_sym_db.RegisterMessage(Desktop.Items)
_sym_db.RegisterMessage(Desktop.Items.Items)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)
| 37.951923
| 669
| 0.731695
| 1,045
| 7,894
| 5.243062
| 0.135885
| 0.052564
| 0.058952
| 0.06023
| 0.793575
| 0.735718
| 0.72714
| 0.718379
| 0.659974
| 0.648476
| 0
| 0.037432
| 0.133646
| 7,894
| 207
| 670
| 38.135266
| 0.763708
| 0.046238
| 0
| 0.657459
| 1
| 0.005525
| 0.188697
| 0.144415
| 0
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| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.027624
| 0
| 0.027624
| 0
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| null | 0
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| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f10a01d4fee788b153a1bb33810b21c321bd0743
| 42
|
py
|
Python
|
core/storage/__init__.py
|
Wr490046178/fast-api-frame
|
1f44bc0a18b819be6d02c3635dc844e7e6383ba0
|
[
"Apache-2.0"
] | null | null | null |
core/storage/__init__.py
|
Wr490046178/fast-api-frame
|
1f44bc0a18b819be6d02c3635dc844e7e6383ba0
|
[
"Apache-2.0"
] | null | null | null |
core/storage/__init__.py
|
Wr490046178/fast-api-frame
|
1f44bc0a18b819be6d02c3635dc844e7e6383ba0
|
[
"Apache-2.0"
] | null | null | null |
from .db import *
from .model import Base
| 14
| 23
| 0.738095
| 7
| 42
| 4.428571
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 42
| 2
| 24
| 21
| 0.911765
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 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
| 1
| 0
| 0
| 0
|
0
| 5
|
f141d7585e1b2d7de6f079bdd2addd5eeb532139
| 399
|
py
|
Python
|
tests/test_models.py
|
kokospapa8/django-async-image-upload
|
3900800fca96a3367e0cde59a49b68370773e976
|
[
"Apache-2.0"
] | 3
|
2021-06-10T19:08:23.000Z
|
2021-12-18T11:55:46.000Z
|
tests/test_models.py
|
kokospapa8/django-async-image-upload
|
3900800fca96a3367e0cde59a49b68370773e976
|
[
"Apache-2.0"
] | null | null | null |
tests/test_models.py
|
kokospapa8/django-async-image-upload
|
3900800fca96a3367e0cde59a49b68370773e976
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
test_django-async-image-upload
------------
Tests for `django-async-image-upload` models module.
"""
from django.test import TestCase
from django_async_image_upload import models
class TestDjango_async_image_upload(TestCase):
def setUp(self):
pass
def test_something(self):
pass
def tearDown(self):
pass
| 15.346154
| 52
| 0.66416
| 51
| 399
| 5.039216
| 0.529412
| 0.155642
| 0.249027
| 0.256809
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003135
| 0.200501
| 399
| 25
| 53
| 15.96
| 0.802508
| 0.350877
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0.333333
| 0.222222
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
f18d80523f168dcc0805973862bb1ad6cd2ca412
| 98
|
py
|
Python
|
zoo/repos/exceptions.py
|
uliana291/the-zoo
|
a15a4162c39553abe91224f4feff5d3b66f9413e
|
[
"MIT"
] | 90
|
2018-11-20T10:58:24.000Z
|
2022-02-19T16:12:46.000Z
|
zoo/repos/exceptions.py
|
uliana291/the-zoo
|
a15a4162c39553abe91224f4feff5d3b66f9413e
|
[
"MIT"
] | 348
|
2018-11-21T09:22:31.000Z
|
2021-11-03T13:45:08.000Z
|
zoo/repos/exceptions.py
|
aexvir/the-zoo
|
7816afb9a0a26c6058b030b4a987c73e952d92bd
|
[
"MIT"
] | 11
|
2018-12-08T18:42:07.000Z
|
2021-02-21T06:27:58.000Z
|
class RepositoryNotFoundError(Exception):
pass
class MissingFilesError(Exception):
pass
| 14
| 41
| 0.77551
| 8
| 98
| 9.5
| 0.625
| 0.342105
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163265
| 98
| 6
| 42
| 16.333333
| 0.926829
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 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
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
74c8c233ea91a565f0fed27f555bf38edd57912a
| 242
|
py
|
Python
|
buff/trinket/dawn.py
|
dannl/hunter-sim-classic
|
e32cccc8431cc3e78b08067dd58e10fec52aac6a
|
[
"MIT"
] | null | null | null |
buff/trinket/dawn.py
|
dannl/hunter-sim-classic
|
e32cccc8431cc3e78b08067dd58e10fec52aac6a
|
[
"MIT"
] | null | null | null |
buff/trinket/dawn.py
|
dannl/hunter-sim-classic
|
e32cccc8431cc3e78b08067dd58e10fec52aac6a
|
[
"MIT"
] | null | null | null |
from buff import Buff
class Dawn(Buff):
def __init__(self):
super().__init__('dawn', 0)
def equip(self,engine, char_state):
char_state.ap += 81
def dequip(self,engine, char_state):
char_state.ap -= 81
| 17.285714
| 40
| 0.615702
| 34
| 242
| 4.029412
| 0.5
| 0.262774
| 0.20438
| 0.277372
| 0.467153
| 0.467153
| 0.467153
| 0.467153
| 0
| 0
| 0
| 0.027933
| 0.260331
| 242
| 13
| 41
| 18.615385
| 0.73743
| 0
| 0
| 0
| 0
| 0
| 0.016529
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0.125
| 0
| 0.625
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
74d99b854c7c989ccdd1245ccf14c0cac59f63b1
| 148
|
py
|
Python
|
quru/server/raft/state/__init__.py
|
ShawnHan1993/quru
|
6b103a54d8228e4e2d44b06cc068c60a44b02d67
|
[
"MIT"
] | null | null | null |
quru/server/raft/state/__init__.py
|
ShawnHan1993/quru
|
6b103a54d8228e4e2d44b06cc068c60a44b02d67
|
[
"MIT"
] | null | null | null |
quru/server/raft/state/__init__.py
|
ShawnHan1993/quru
|
6b103a54d8228e4e2d44b06cc068c60a44b02d67
|
[
"MIT"
] | null | null | null |
from .candidate import Candidate
from .follower import Follower
from .leader import Leader
from .base import BaseState
from .learner import Learner
| 24.666667
| 32
| 0.831081
| 20
| 148
| 6.15
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135135
| 148
| 5
| 33
| 29.6
| 0.960938
| 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
| 1
| 0
|
0
| 5
|
74f090cb4890fc5688426d64405764fce669fd64
| 153
|
py
|
Python
|
movieratings/movies/admin.py
|
gcrowder/django-movies
|
67383343dcfc5c923a388dd85c905f1a9bc9359a
|
[
"MIT"
] | null | null | null |
movieratings/movies/admin.py
|
gcrowder/django-movies
|
67383343dcfc5c923a388dd85c905f1a9bc9359a
|
[
"MIT"
] | null | null | null |
movieratings/movies/admin.py
|
gcrowder/django-movies
|
67383343dcfc5c923a388dd85c905f1a9bc9359a
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from .models import Rating, Movie
admin.site.register(Rating)
admin.site.register(Movie)
| 19.125
| 33
| 0.797386
| 22
| 153
| 5.545455
| 0.545455
| 0.147541
| 0.278689
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 153
| 7
| 34
| 21.857143
| 0.903704
| 0.169935
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
74fbfd4ca2d704485b7fcc5e148691d0a60a0129
| 159
|
py
|
Python
|
gui/mem_dixy/Unicode/U.py
|
Mem-Dixy/web
|
e5373ec86e3b7048c353071dc3555a96340b035e
|
[
"MIT"
] | null | null | null |
gui/mem_dixy/Unicode/U.py
|
Mem-Dixy/web
|
e5373ec86e3b7048c353071dc3555a96340b035e
|
[
"MIT"
] | 1
|
2021-05-09T23:36:35.000Z
|
2021-05-09T23:36:35.000Z
|
gui/mem_dixy/Unicode/U.py
|
Mem-Dixy/web
|
e5373ec86e3b7048c353071dc3555a96340b035e
|
[
"MIT"
] | null | null | null |
LATIN CAPITAL LETTER A WITH RING ABOVE = 212B
LATIN CAPITAL LETTER ETH = 0
LATIN CAPITAL LETTER O WITH STROKE
LATIN SMALL LETTER SHARP S
LATIN SMALL LETTER AE
| 26.5
| 45
| 0.798742
| 28
| 159
| 4.535714
| 0.571429
| 0.283465
| 0.425197
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.031008
| 0.188679
| 159
| 5
| 46
| 31.8
| 0.953488
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
2d1a9a2d6e7ac377535dac0cedf0429af4561365
| 177
|
py
|
Python
|
slot_racer/game/__init__.py
|
mgreenw/slot-racer
|
ccb456cf489616e14d95c34c7398fb3e04307b02
|
[
"MIT"
] | 1
|
2018-12-08T03:18:00.000Z
|
2018-12-08T03:18:00.000Z
|
slot_racer/game/__init__.py
|
mgreenw/slot-racer
|
ccb456cf489616e14d95c34c7398fb3e04307b02
|
[
"MIT"
] | null | null | null |
slot_racer/game/__init__.py
|
mgreenw/slot-racer
|
ccb456cf489616e14d95c34c7398fb3e04307b02
|
[
"MIT"
] | null | null | null |
"""Module containing all the different parts of the game"""
# game_code should provide access to the modules that define the game
from .physics import *
from .state import *
| 22.125
| 69
| 0.757062
| 27
| 177
| 4.925926
| 0.740741
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180791
| 177
| 7
| 70
| 25.285714
| 0.917241
| 0.689266
| 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
| 1
| 0
|
0
| 5
|
2d3c422f35b138d2de171501d5544b33dde84add
| 157
|
py
|
Python
|
prueba.py
|
AlejandroMorales26/Versionamiento
|
551f3328afdc68705b3a5baa29141536acfb4b9f
|
[
"MIT"
] | null | null | null |
prueba.py
|
AlejandroMorales26/Versionamiento
|
551f3328afdc68705b3a5baa29141536acfb4b9f
|
[
"MIT"
] | null | null | null |
prueba.py
|
AlejandroMorales26/Versionamiento
|
551f3328afdc68705b3a5baa29141536acfb4b9f
|
[
"MIT"
] | null | null | null |
# Se borro la primera linea
print('ESTA ES UNA LINEA AGREGADA DESDE PYTHON')
print('esta linea fue añadida desde Github para probar el update en python')
| 26.166667
| 76
| 0.764331
| 26
| 157
| 4.615385
| 0.769231
| 0.15
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.178344
| 157
| 5
| 77
| 31.4
| 0.930233
| 0.159236
| 0
| 0
| 0
| 0
| 0.815385
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
742cb92a4a01767461e8bba5237913b41a72e817
| 202
|
py
|
Python
|
PyTweetApp/admin.py
|
cfasquel/PyTweet
|
1a235b1ad6a63c96af13827bacefbc541710502e
|
[
"Unlicense"
] | null | null | null |
PyTweetApp/admin.py
|
cfasquel/PyTweet
|
1a235b1ad6a63c96af13827bacefbc541710502e
|
[
"Unlicense"
] | null | null | null |
PyTweetApp/admin.py
|
cfasquel/PyTweet
|
1a235b1ad6a63c96af13827bacefbc541710502e
|
[
"Unlicense"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from PyTweetApp.models import Tweet, Hashtag, Member
admin.site.register(Tweet)
admin.site.register(Hashtag)
admin.site.register(Member)
| 20.2
| 52
| 0.806931
| 28
| 202
| 5.821429
| 0.5
| 0.165644
| 0.312883
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.10396
| 202
| 9
| 53
| 22.444444
| 0.900552
| 0.128713
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| 0
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| 1
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| true
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| null | 0
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| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
74309d74e576044ef581206dba15a8701d4c2856
| 288
|
py
|
Python
|
codewars/8kyu/mohamedashrafamin/Remove_exclamation_marks/test_bench.py
|
mohamedashrafamin/Training_one
|
11748fdde85cdc9083e2b0bde7519b51a7acfa62
|
[
"MIT"
] | null | null | null |
codewars/8kyu/mohamedashrafamin/Remove_exclamation_marks/test_bench.py
|
mohamedashrafamin/Training_one
|
11748fdde85cdc9083e2b0bde7519b51a7acfa62
|
[
"MIT"
] | 2
|
2019-01-22T10:53:42.000Z
|
2019-01-31T08:02:48.000Z
|
codewars/8kyu/mohamedashrafamin/Remove_exclamation_marks/test_bench.py
|
mohamedashrafamin/Training_one
|
11748fdde85cdc9083e2b0bde7519b51a7acfa62
|
[
"MIT"
] | 13
|
2019-01-22T10:37:42.000Z
|
2019-01-25T13:30:43.000Z
|
from main import remove_exclamation_marks, remove_exclamation_marks1
def test1(benchmark):
assert benchmark(remove_exclamation_marks, "Hello World!") == "Hello World"
def test(benchmark):
assert benchmark(remove_exclamation_marks1, "Hello World!") == "Hello World"
# py.test
| 24
| 80
| 0.767361
| 35
| 288
| 6.085714
| 0.428571
| 0.319249
| 0.206573
| 0.28169
| 0.384977
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012
| 0.131944
| 288
| 11
| 81
| 26.181818
| 0.84
| 0.024306
| 0
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| 0
| 0
| 0.164875
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.4
| false
| 0
| 0.2
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
777f67cbab1c659349917c13d9df30142ded01ee
| 205
|
py
|
Python
|
main/PluginDemos/MomentOfInertia/MomentOfInertia3D/Simulation/MomentOfInertia3D.py
|
JulianoGianlupi/nh-cc3d-4x-base-tool
|
c0f4aceebd4c5bf3ec39e831ef851e419b161259
|
[
"CC0-1.0"
] | null | null | null |
main/PluginDemos/MomentOfInertia/MomentOfInertia3D/Simulation/MomentOfInertia3D.py
|
JulianoGianlupi/nh-cc3d-4x-base-tool
|
c0f4aceebd4c5bf3ec39e831ef851e419b161259
|
[
"CC0-1.0"
] | null | null | null |
main/PluginDemos/MomentOfInertia/MomentOfInertia3D/Simulation/MomentOfInertia3D.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 .MomentOfInertia3DSteppables import MomentOfInertiaPrinter3D
CompuCellSetup.register_steppable(steppable=MomentOfInertiaPrinter3D(frequency=10))
CompuCellSetup.run()
| 29.285714
| 83
| 0.887805
| 17
| 205
| 10.647059
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.031088
| 0.058537
| 205
| 6
| 84
| 34.166667
| 0.906736
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
778b71f03980a60b2ce503bff7368267b8a09535
| 87
|
py
|
Python
|
src/UQpy/DimensionReduction/baseclass/__init__.py
|
marrov/UQpy
|
b04a267b3080e3d4d38e876547ba0d3b979734f3
|
[
"MIT"
] | 132
|
2018-03-13T13:56:33.000Z
|
2022-03-21T13:59:17.000Z
|
src/UQpy/DimensionReduction/baseclass/__init__.py
|
marrov/UQpy
|
b04a267b3080e3d4d38e876547ba0d3b979734f3
|
[
"MIT"
] | 140
|
2018-05-21T13:40:01.000Z
|
2022-03-29T14:18:01.000Z
|
src/UQpy/DimensionReduction/baseclass/__init__.py
|
marrov/UQpy
|
b04a267b3080e3d4d38e876547ba0d3b979734f3
|
[
"MIT"
] | 61
|
2018-05-02T13:40:05.000Z
|
2022-03-06T11:31:21.000Z
|
"""Collection of baseclasses"""
from UQpy.DimensionReduction.baseclass.POD import POD
| 21.75
| 53
| 0.804598
| 10
| 87
| 7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.091954
| 87
| 3
| 54
| 29
| 0.886076
| 0.287356
| 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
| 1
| 0
|
0
| 5
|
779889ddc21f9e560c7e5b0c4edc2be93e6fb731
| 184
|
py
|
Python
|
core/meta/__init__.py
|
ponyatov/metaLpy
|
96149313e8083536ade1c331825242f6996f05b3
|
[
"MIT"
] | null | null | null |
core/meta/__init__.py
|
ponyatov/metaLpy
|
96149313e8083536ade1c331825242f6996f05b3
|
[
"MIT"
] | null | null | null |
core/meta/__init__.py
|
ponyatov/metaLpy
|
96149313e8083536ade1c331825242f6996f05b3
|
[
"MIT"
] | null | null | null |
## @file
## @defgroup meta meta
## @brief metaprogramming (software components)
## @ingroup core
from .meta import *
from .module import *
from .clazz import *
from .method import *
| 16.727273
| 47
| 0.706522
| 22
| 184
| 5.909091
| 0.636364
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173913
| 184
| 10
| 48
| 18.4
| 0.855263
| 0.456522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
77bcdb1ee7bad6308139954589943b23abd9a150
| 43
|
py
|
Python
|
hello_world.py
|
gradio/my_test_repository
|
d1cc2fe32e9373873295275b50c0fa7d2d6a2083
|
[
"MIT"
] | null | null | null |
hello_world.py
|
gradio/my_test_repository
|
d1cc2fe32e9373873295275b50c0fa7d2d6a2083
|
[
"MIT"
] | null | null | null |
hello_world.py
|
gradio/my_test_repository
|
d1cc2fe32e9373873295275b50c0fa7d2d6a2083
|
[
"MIT"
] | null | null | null |
print('Hello World')
print('This is neat.')
| 21.5
| 22
| 0.697674
| 7
| 43
| 4.285714
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 43
| 2
| 22
| 21.5
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 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
| 1
|
0
| 5
|
7acfedae19bff32e39278c5566db9087d7173bd2
| 445
|
py
|
Python
|
JumpScale9Zrobot/clients/zerorobot/client/passthrough_client_service.py
|
PeterNashaat/0-robot
|
9ddc74354276e30dea4378e5a81814ce63f2120a
|
[
"Apache-2.0"
] | 3
|
2017-12-27T19:47:25.000Z
|
2018-02-07T20:05:08.000Z
|
JumpScale9Zrobot/clients/zerorobot/client/passthrough_client_service.py
|
PeterNashaat/0-robot
|
9ddc74354276e30dea4378e5a81814ce63f2120a
|
[
"Apache-2.0"
] | 126
|
2018-03-26T09:53:52.000Z
|
2018-07-26T09:11:39.000Z
|
JumpScale9Zrobot/clients/zerorobot/client/passthrough_client_service.py
|
Jumpscale/zerorobot
|
704d6eb996fae3bee7cfc44d54bf71dff030ea41
|
[
"Apache-2.0"
] | 5
|
2018-06-12T05:07:57.000Z
|
2019-01-28T20:53:00.000Z
|
# DO NOT EDIT THIS FILE. This file will be overwritten when re-running go-raml.
class PassThroughClientService:
def __init__(self, http_client):
self._http_client = http_client
def set_zrobotsecret_header(self, val):
"""" Set header ZrobotSecret to '<val>'"""
self._http_client.set_header('Zrobot', val) # for backward compatibility with 0.6.x
return self._http_client.set_header('ZrobotSecret', val)
| 37.083333
| 92
| 0.707865
| 60
| 445
| 4.983333
| 0.566667
| 0.167224
| 0.187291
| 0.113712
| 0.153846
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005571
| 0.193258
| 445
| 11
| 93
| 40.454545
| 0.827298
| 0.34382
| 0
| 0
| 1
| 0
| 0.063158
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0.166667
| 0
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
7ad8deb145b35b53deedb54794326264917dc709
| 624
|
py
|
Python
|
CpuData.py
|
e-ivanov/monitoring_agent
|
f0a554dad6c2e8b1eabdc8ae54a9fd6a24f4e1f2
|
[
"Apache-2.0"
] | null | null | null |
CpuData.py
|
e-ivanov/monitoring_agent
|
f0a554dad6c2e8b1eabdc8ae54a9fd6a24f4e1f2
|
[
"Apache-2.0"
] | null | null | null |
CpuData.py
|
e-ivanov/monitoring_agent
|
f0a554dad6c2e8b1eabdc8ae54a9fd6a24f4e1f2
|
[
"Apache-2.0"
] | null | null | null |
from BaseStat import BaseStat
class CpuData(BaseStat):
name = "CPU_UTILIZATION"
def __init__(self):
BaseStat.__init__(self)
self.__usage = 0
self.__num_of_cores = 0
def get_usage(self):
return self.__usage
def get_num_of_cores(self):
return self.__num_of_cores
def set_num_of_cores(self, num_of_cores):
self.__num_of_cores = num_of_cores
def set_usage(self, usage):
self.__usage = usage
def __getstate__(self):
state = {"usage": self.__usage,
"num_of_cores": self.__num_of_cores}
return state
| 18.352941
| 53
| 0.63141
| 82
| 624
| 4.182927
| 0.256098
| 0.131195
| 0.262391
| 0.204082
| 0.274052
| 0.180758
| 0.180758
| 0
| 0
| 0
| 0
| 0.004494
| 0.286859
| 624
| 33
| 54
| 18.909091
| 0.766292
| 0
| 0
| 0
| 0
| 0
| 0.051696
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.315789
| false
| 0
| 0.052632
| 0.105263
| 0.631579
| 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
| 1
| 0
|
0
| 5
|
7addd0284f430c97a6f39a815f34c52ebf41afd8
| 78
|
py
|
Python
|
pyncm/utils/__init__.py
|
greats3an/pyncm
|
ae91f7a50d634192ac68dc6439ff7495c51cbe06
|
[
"Apache-2.0"
] | 133
|
2020-02-09T14:40:25.000Z
|
2022-03-26T02:18:46.000Z
|
pyncm/utils/__init__.py
|
greats3an/pyncm
|
ae91f7a50d634192ac68dc6439ff7495c51cbe06
|
[
"Apache-2.0"
] | 14
|
2020-02-27T04:35:52.000Z
|
2022-03-13T08:40:06.000Z
|
pyncm/utils/__init__.py
|
greats3an/pyncm
|
ae91f7a50d634192ac68dc6439ff7495c51cbe06
|
[
"Apache-2.0"
] | 23
|
2020-09-11T07:50:31.000Z
|
2022-02-10T06:37:21.000Z
|
'''Utility functions'''
from .crypto import *
from .lrcparser import LrcParser
| 26
| 32
| 0.769231
| 9
| 78
| 6.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 78
| 3
| 32
| 26
| 0.869565
| 0.217949
| 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
| 1
| 0
|
0
| 5
|
bb05ed75b77926f09aa6cc27c0be94c6a0933cf3
| 122
|
py
|
Python
|
pyHMT2D/Hydraulic_Models_Data/Backwater_1D/__init__.py
|
ali-mahdavi-mazdeh/pyHMT2D
|
5351ea8a0d234d4a2b8e1e62c803d7f3cfeb0f4d
|
[
"MIT"
] | 7
|
2021-04-12T16:14:30.000Z
|
2022-03-11T12:20:52.000Z
|
pyHMT2D/Hydraulic_Models_Data/Backwater_1D/__init__.py
|
ali-mahdavi-mazdeh/pyHMT2D
|
5351ea8a0d234d4a2b8e1e62c803d7f3cfeb0f4d
|
[
"MIT"
] | 4
|
2021-05-17T15:33:02.000Z
|
2021-07-16T18:04:59.000Z
|
pyHMT2D/Hydraulic_Models_Data/Backwater_1D/__init__.py
|
ali-mahdavi-mazdeh/pyHMT2D
|
5351ea8a0d234d4a2b8e1e62c803d7f3cfeb0f4d
|
[
"MIT"
] | 6
|
2021-05-17T15:20:31.000Z
|
2022-03-12T02:06:53.000Z
|
from .Backwater_1D_Data import *
from .Backwater_1D_Model import *
__all__ = ["Backwater_1D_Data", "Backwater_1D_Model"]
| 24.4
| 53
| 0.795082
| 17
| 122
| 5
| 0.411765
| 0.517647
| 0.352941
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036697
| 0.106557
| 122
| 5
| 53
| 24.4
| 0.743119
| 0
| 0
| 0
| 0
| 0
| 0.284553
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
| 1
| 0
| 0
| 0
|
0
| 5
|
bb141c12b1269956be48eac9f0380019f14683d0
| 291
|
py
|
Python
|
12_dayride/zscale.py
|
Tjorriemorrie/trading
|
aafa15a6c564bfa86948ab30e33d554172b38a3e
|
[
"MIT"
] | 2
|
2017-07-02T09:06:28.000Z
|
2020-09-11T04:23:14.000Z
|
12_dayride/zscale.py
|
Tjorriemorrie/trading
|
aafa15a6c564bfa86948ab30e33d554172b38a3e
|
[
"MIT"
] | 2
|
2021-03-31T19:14:07.000Z
|
2021-06-01T23:34:32.000Z
|
12_dayride/zscale.py
|
Tjorriemorrie/trading
|
aafa15a6c564bfa86948ab30e33d554172b38a3e
|
[
"MIT"
] | 2
|
2016-03-29T07:51:16.000Z
|
2016-10-30T04:53:58.000Z
|
import pandas as pd
from sklearn.preprocessing import scale
data = [1, 2, 2, 5]
ser = pd.Series(data, dtype=float)
print ser
print ser.describe()
print 'scaled 1'
scale(ser, copy=False)
print ser
print ser.describe()
print 'scaled 2'
scale(ser, copy=False)
print ser
print ser.describe()
| 16.166667
| 39
| 0.735395
| 49
| 291
| 4.367347
| 0.428571
| 0.224299
| 0.182243
| 0.224299
| 0.598131
| 0.598131
| 0.598131
| 0.383178
| 0.383178
| 0
| 0
| 0.024194
| 0.147766
| 291
| 17
| 40
| 17.117647
| 0.83871
| 0
| 0
| 0.571429
| 0
| 0
| 0.054983
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.142857
| null | null | 0.571429
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
bb1f8799c287cfc8b2f2eec76c91793e9d47d411
| 454
|
py
|
Python
|
Decoratos - Exercise/Bold, Italic, Underline.py
|
DiyanKalaydzhiev23/OOP---Python
|
7ac424d5fb08a6bd28dc36593e45d949b3ac0cd0
|
[
"MIT"
] | null | null | null |
Decoratos - Exercise/Bold, Italic, Underline.py
|
DiyanKalaydzhiev23/OOP---Python
|
7ac424d5fb08a6bd28dc36593e45d949b3ac0cd0
|
[
"MIT"
] | null | null | null |
Decoratos - Exercise/Bold, Italic, Underline.py
|
DiyanKalaydzhiev23/OOP---Python
|
7ac424d5fb08a6bd28dc36593e45d949b3ac0cd0
|
[
"MIT"
] | null | null | null |
def make_bold(function):
def wrapper(*args):
return f"<b>{function(*args)}</b>"
return wrapper
def make_italic(function):
def wrapper(*args):
return f"<i>{function(*args)}</i>"
return wrapper
def make_underline(function):
def wrapper(*args):
return f"<u>{function(*args)}</u>"
return wrapper
@make_bold
@make_italic
@make_underline
def greet(name):
return f"Hello, {name}"
print(greet("Peter"))
| 17.461538
| 42
| 0.634361
| 61
| 454
| 4.622951
| 0.295082
| 0.099291
| 0.191489
| 0.234043
| 0.308511
| 0.308511
| 0
| 0
| 0
| 0
| 0
| 0
| 0.202643
| 454
| 25
| 43
| 18.16
| 0.779006
| 0
| 0
| 0.333333
| 0
| 0
| 0.198238
| 0.15859
| 0
| 0
| 0
| 0
| 0
| 1
| 0.388889
| false
| 0
| 0
| 0.222222
| 0.777778
| 0.055556
| 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
| 1
| 0
|
0
| 5
|
bb22d5832588f0c9a4e06b326359bbe2fb6be99e
| 45
|
py
|
Python
|
tests/__init__.py
|
esciara/pyteleinfo
|
fbae4cc8e3515b3538b3163f1cf4a0c271c6ba71
|
[
"BSD-2-Clause"
] | null | null | null |
tests/__init__.py
|
esciara/pyteleinfo
|
fbae4cc8e3515b3538b3163f1cf4a0c271c6ba71
|
[
"BSD-2-Clause"
] | null | null | null |
tests/__init__.py
|
esciara/pyteleinfo
|
fbae4cc8e3515b3538b3163f1cf4a0c271c6ba71
|
[
"BSD-2-Clause"
] | null | null | null |
"""The tests for Serial Teleinfo platform."""
| 45
| 45
| 0.733333
| 6
| 45
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 45
| 1
| 45
| 45
| 0.825
| 0.866667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
bb2847d5ed413d93b77db7037e3cdbd997679338
| 4,830
|
py
|
Python
|
tests/test_cli_misc.py
|
robertopreste/prestools
|
5c3a66ce981f374de2e6bdc2d7c927ee5b51b9bb
|
[
"MIT"
] | null | null | null |
tests/test_cli_misc.py
|
robertopreste/prestools
|
5c3a66ce981f374de2e6bdc2d7c927ee5b51b9bb
|
[
"MIT"
] | 18
|
2019-09-07T16:56:11.000Z
|
2022-03-31T23:05:02.000Z
|
tests/test_cli_misc.py
|
robertopreste/prestools
|
5c3a66ce981f374de2e6bdc2d7c927ee5b51b9bb
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
import os
import pytest
from click.testing import CliRunner
from prestools import cli
DATADIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "data")
SAME1 = os.path.join(DATADIR, "same1.txt")
SAME2 = os.path.join(DATADIR, "same2.txt")
SAMENOT = os.path.join(DATADIR, "samenot.txt")
SIZENOT = os.path.join(DATADIR, "sizenot.txt")
# prime_factors
def test_cli_prime_factors_one():
runner = CliRunner()
expect = "[]"
result = runner.invoke(cli.main, ["misc", "prime-factors", "1"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_prime_factors_square():
runner = CliRunner()
expect = "[3, 3]"
result = runner.invoke(cli.main, ["misc", "prime-factors", "9"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_prime_factors_cube():
runner = CliRunner()
expect = "[3, 3, 3]"
result = runner.invoke(cli.main, ["misc", "prime-factors", "27"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_prime_factors_mixed():
runner = CliRunner()
expect = "[5, 17, 23, 461]"
result = runner.invoke(cli.main, ["misc", "prime-factors", "901255"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_prime_factors_large():
runner = CliRunner()
expect = "[11, 9539, 894119]"
result = runner.invoke(cli.main, ["misc", "prime-factors", "93819012551"])
assert result.exit_code == 0
assert result.output.strip() == expect
# pm.wordcount
def test_cli_wordcount():
runner = CliRunner()
expect = {"word": 2, "test": 1, "wordcount": 1}
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount word"])
assert result.exit_code == 0
assert eval(result.output.strip()) == expect
def test_cli_wordcount_specific_word():
runner = CliRunner()
expect = "2"
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount word",
"--word", "word"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_wordcount_specific_word_not_present():
runner = CliRunner()
expect = "0"
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount word",
"--word", "prova"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_wordcount_ignore_case_true():
runner = CliRunner()
expect = {"word": 2, "test": 1, "wordcount": 1}
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount WORD",
"--ignore_case"])
assert result.exit_code == 0
assert eval(result.output.strip()) == expect
def test_cli_wordcount_ignore_case_false():
runner = CliRunner()
expect = {"word": 1, "test": 1, "wordcount": 1, "WORD": 1}
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount WORD"])
assert result.exit_code == 0
assert eval(result.output.strip()) == expect
def test_cli_wordcount_specific_word_ignore_case_true():
runner = CliRunner()
expect = "2"
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount WORD",
"--word", "word", "--ignore_case"])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_wordcount_specific_word_ignore_case_false():
runner = CliRunner()
expect = "1"
result = runner.invoke(cli.main, ["misc", "wordcount",
"word test wordcount WORD",
"--word", "word"])
assert result.exit_code == 0
assert result.output.strip() == expect
# pm.equal_files
def test_cli_equal_files():
runner = CliRunner()
expect = "True"
result = runner.invoke(cli.main, ["misc", "equal-files", SAME1, SAME2])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_equal_files_false():
runner = CliRunner()
expect = "False"
result = runner.invoke(cli.main, ["misc", "equal-files", SAME1, SAMENOT])
assert result.exit_code == 0
assert result.output.strip() == expect
def test_cli_equal_files_false_size():
runner = CliRunner()
expect = "False"
result = runner.invoke(cli.main, ["misc", "equal-files", SAME1, SAMENOT])
assert result.exit_code == 0
assert result.output.strip() == expect
| 31.776316
| 78
| 0.602484
| 570
| 4,830
| 4.945614
| 0.14386
| 0.114934
| 0.05321
| 0.111742
| 0.797091
| 0.766939
| 0.745654
| 0.745654
| 0.702022
| 0.679319
| 0
| 0.023327
| 0.254451
| 4,830
| 151
| 79
| 31.986755
| 0.759511
| 0.022774
| 0
| 0.603604
| 0
| 0
| 0.136826
| 0
| 0
| 0
| 0
| 0
| 0.27027
| 1
| 0.135135
| false
| 0
| 0.036036
| 0
| 0.171171
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 5
|
bb5a7d61c7210ec96e9aa862c1043d0a113b8249
| 343
|
py
|
Python
|
examples/python/square.py
|
Sanix-Darker/tesla
|
a83597c673baac28c5305b9eb0733682e60c1ea6
|
[
"MIT"
] | 8
|
2019-05-10T10:32:56.000Z
|
2019-09-04T21:15:24.000Z
|
examples/python/square.py
|
Sanix-Darker/tesla
|
a83597c673baac28c5305b9eb0733682e60c1ea6
|
[
"MIT"
] | null | null | null |
examples/python/square.py
|
Sanix-Darker/tesla
|
a83597c673baac28c5305b9eb0733682e60c1ea6
|
[
"MIT"
] | 2
|
2019-09-04T20:47:02.000Z
|
2019-09-05T10:53:37.000Z
|
# ::import_start::
from math import sqrt as math_square
# ::import_end::
# ::testa_start::
# ::case_start::
# >> testa.isEqual(2, 2)
# << true
# ::case_end::
# ::testa_end::
# ::testa_start::
# ::case_start::
# >> square(9)
# << 3.0
# ::case_end::
# ::code_start::
def square(a):
return math_square(a)
# ::code_end::
# ::testa_end::
| 13.192308
| 36
| 0.588921
| 47
| 343
| 4
| 0.425532
| 0.170213
| 0.138298
| 0.180851
| 0.234043
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017483
| 0.166181
| 343
| 25
| 37
| 13.72
| 0.63986
| 0.658892
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
24a4f7499b27039cc9929bb9deb7f7aecea8bb50
| 127
|
py
|
Python
|
python/luhn/test.py
|
heymajor/exercism
|
5cbe035abfdcd420e4b74ed24d7cb4d9fc38ddfd
|
[
"MIT"
] | null | null | null |
python/luhn/test.py
|
heymajor/exercism
|
5cbe035abfdcd420e4b74ed24d7cb4d9fc38ddfd
|
[
"MIT"
] | null | null | null |
python/luhn/test.py
|
heymajor/exercism
|
5cbe035abfdcd420e4b74ed24d7cb4d9fc38ddfd
|
[
"MIT"
] | null | null | null |
#!/home/maj/.conda/envs/exercism/bin/ python3
import numpy as np
print(np.zeros([1, 4]))
# import sys
# print(sys.version)
| 12.7
| 45
| 0.685039
| 21
| 127
| 4.142857
| 0.809524
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027273
| 0.133858
| 127
| 9
| 46
| 14.111111
| 0.763636
| 0.582677
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
24ae9715c03d4f901ff2b366a0f88f95f1c7bca7
| 52
|
py
|
Python
|
rl_traders/memories/__init__.py
|
jjakimoto/rl_traders.py
|
d5411c96d49ba6a54751d12cdd11974e5cc1a8aa
|
[
"MIT"
] | 2
|
2018-10-07T14:16:32.000Z
|
2019-01-28T00:14:29.000Z
|
rl_traders/memories/__init__.py
|
jjakimoto/rl_traders.py
|
d5411c96d49ba6a54751d12cdd11974e5cc1a8aa
|
[
"MIT"
] | null | null | null |
rl_traders/memories/__init__.py
|
jjakimoto/rl_traders.py
|
d5411c96d49ba6a54751d12cdd11974e5cc1a8aa
|
[
"MIT"
] | 1
|
2019-11-05T00:51:20.000Z
|
2019-11-05T00:51:20.000Z
|
from .portfolio_vector import PortfolioVectorMemory
| 26
| 51
| 0.903846
| 5
| 52
| 9.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 52
| 1
| 52
| 52
| 0.958333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 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
| 1
| 0
|
0
| 5
|
7031c2f5cab5973a7a9ca57f5b94227880219d72
| 2,407
|
py
|
Python
|
logs/on_member_remove.py
|
DiscordHackers/BetterBot-1.0.2.2
|
bf9b5b3368c654bcc4bf144572a7d331e154abe2
|
[
"Apache-2.0"
] | null | null | null |
logs/on_member_remove.py
|
DiscordHackers/BetterBot-1.0.2.2
|
bf9b5b3368c654bcc4bf144572a7d331e154abe2
|
[
"Apache-2.0"
] | null | null | null |
logs/on_member_remove.py
|
DiscordHackers/BetterBot-1.0.2.2
|
bf9b5b3368c654bcc4bf144572a7d331e154abe2
|
[
"Apache-2.0"
] | null | null | null |
import disnake as discord
from disnake.ext import commands
from datetime import datetime
from api.server import base, main
class OnMembereRemove(commands.Cog):
def __init__(self, client):
self.client = client
@commands.Cog.listener()
async def on_member_remove(self, member):
if base.guild(member.guild)[6] is not None:
try:
embed = discord.Embed(description = main.get_lang(member.guild, "MEMBER_REMOVE").format(member.name, member.mention), timestamp = datetime.utcnow(), color = 0xead967)
embed.set_footer(text = main.get_lang(member.guild, "MEMBER_ID").format(member.id), icon_url = member.avatar.url)
await self.client.get_channel(int(base.guild(member.guild)[6])).send(embed = embed)
except:
embed = discord.Embed(description = main.get_lang(member.guild, "MEMBER_REMOVE").format(member.name, member.mention), timestamp = datetime.utcnow(), color = 0xead967)
embed.set_footer(text = main.get_lang(member.guild, "MEMBER_ID").format(member.id))
await self.client.get_channel(int(base.guild(member.guild)[6])).send(embed = embed)
if base.guild(member.guild)[8] is not None:
try:
embed = discord.Embed(description = main.get_lang(member.guild, "GOODBYE_MEMBER_JOIN").format(member.mention), color = 9579219, timestamp = datetime.utcnow())
embed.set_author(name = main.get_lang(member.guild, "GOODBYE_MEMBER_GUILD").format(member.guild.name))
embed.set_thumbnail(url = f"{member.guild.icon}")
embed.set_footer(text = main.get_lang(member.guild, "MEMBER_ID").format(member.id))
await self.client.get_channel(int(base.guild(member.guild)[8])).send(embed = embed)
except:
embed = discord.Embed(description = main.get_lang(member.guild, "GOODBYE_MEMBER_JOIN").format(member.mention), color = 9579219, timestamp = datetime.utcnow())
embed.set_author(name = main.get_lang(member.guild, "GOODBYE_MEMBER_GUILD").format(member.guild.name))
embed.set_footer(text = main.get_lang(member.guild, "MEMBER_ID").format(member.id))
await self.client.get_channel(int(base.guild(member.guild)[8])).send(embed = embed)
def setup(client):
client.add_cog(OnMembereRemove(client))
| 65.054054
| 182
| 0.665559
| 309
| 2,407
| 5.045307
| 0.203884
| 0.148172
| 0.070558
| 0.109044
| 0.797947
| 0.768441
| 0.768441
| 0.768441
| 0.768441
| 0.768441
| 0
| 0.014614
| 0.203988
| 2,407
| 37
| 183
| 65.054054
| 0.799061
| 0
| 0
| 0.53125
| 0
| 0
| 0.06603
| 0
| 0
| 0
| 0.006645
| 0
| 0
| 1
| 0.0625
| false
| 0
| 0.125
| 0
| 0.21875
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
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|
0
| 5
|
70457bf8b786396313d5537100c0b767486c0a0b
| 26
|
py
|
Python
|
basic-1.9.7/lang/en.py
|
claretnnamocha/pytonik-samples
|
449ee7aaf19b3ba669799c50d823128663182b8f
|
[
"MIT"
] | null | null | null |
basic-1.9.7/lang/en.py
|
claretnnamocha/pytonik-samples
|
449ee7aaf19b3ba669799c50d823128663182b8f
|
[
"MIT"
] | 4
|
2021-06-08T20:59:24.000Z
|
2022-03-12T00:17:37.000Z
|
basic-1.9.7/lang/en.py
|
claretnnamocha/pytonik-samples
|
449ee7aaf19b3ba669799c50d823128663182b8f
|
[
"MIT"
] | null | null | null |
{"lng.test":"sample text"}
| 26
| 26
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| 4
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| 0
| 0
|
0
| 5
|
70739263e800ee322717bad97ed3feff5d20cf03
| 4,584
|
py
|
Python
|
Source/Thttil/ThttilLexer.py
|
Renondedju/Thttil
|
66bbc4133421b86804f195b5a74c53f4281e98ba
|
[
"MIT"
] | 2
|
2019-03-13T12:39:28.000Z
|
2019-04-01T09:11:48.000Z
|
Source/Thttil/ThttilLexer.py
|
BasileCombet/Thttil
|
66bbc4133421b86804f195b5a74c53f4281e98ba
|
[
"MIT"
] | null | null | null |
Source/Thttil/ThttilLexer.py
|
BasileCombet/Thttil
|
66bbc4133421b86804f195b5a74c53f4281e98ba
|
[
"MIT"
] | 1
|
2019-11-06T09:18:08.000Z
|
2019-11-06T09:18:08.000Z
|
# Generated from Language\Grammar\Thttil.g4 by ANTLR 4.7.2
from antlr4 import *
from io import StringIO
from typing.io import TextIO
import sys
def serializedATN():
with StringIO() as buf:
buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2\16")
buf.write("x\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7\t\7")
buf.write("\4\b\t\b\4\t\t\t\4\n\t\n\4\13\t\13\4\f\t\f\4\r\t\r\4\16")
buf.write("\t\16\4\17\t\17\4\20\t\20\4\21\t\21\4\22\t\22\3\2\3\2")
buf.write("\3\2\3\3\3\3\3\4\3\4\3\5\3\5\3\6\3\6\3\7\3\7\3\b\3\b\3")
buf.write("\t\3\t\3\n\3\n\3\n\3\n\5\n;\n\n\3\13\3\13\3\13\3\13\5")
buf.write("\13A\n\13\3\f\3\f\6\fE\n\f\r\f\16\fF\3\r\6\rJ\n\r\r\r")
buf.write("\16\rK\3\16\3\16\3\16\7\16Q\n\16\f\16\16\16T\13\16\3\16")
buf.write("\3\16\3\17\3\17\3\17\7\17[\n\17\f\17\16\17^\13\17\3\17")
buf.write("\3\17\3\20\3\20\3\20\6\20e\n\20\r\20\16\20f\3\21\3\21")
buf.write("\7\21k\n\21\f\21\16\21n\13\21\3\21\3\21\3\22\6\22s\n\22")
buf.write("\r\22\16\22t\3\22\3\22\4R\\\2\23\3\3\5\4\7\5\t\6\13\7")
buf.write("\r\2\17\2\21\2\23\2\25\2\27\b\31\t\33\n\35\13\37\f!\r")
buf.write("#\16\3\2\n\3\2c|\3\2C\\\4\2C\\c|\3\2\'\'\3\2$$\4\2/\60")
buf.write("aa\4\2\f\f\17\17\5\2\13\f\17\17\"\"\2~\2\3\3\2\2\2\2\5")
buf.write("\3\2\2\2\2\7\3\2\2\2\2\t\3\2\2\2\2\13\3\2\2\2\2\27\3\2")
buf.write("\2\2\2\31\3\2\2\2\2\33\3\2\2\2\2\35\3\2\2\2\2\37\3\2\2")
buf.write("\2\2!\3\2\2\2\2#\3\2\2\2\3%\3\2\2\2\5(\3\2\2\2\7*\3\2")
buf.write("\2\2\t,\3\2\2\2\13.\3\2\2\2\r\60\3\2\2\2\17\62\3\2\2\2")
buf.write("\21\64\3\2\2\2\23:\3\2\2\2\25@\3\2\2\2\27B\3\2\2\2\31")
buf.write("I\3\2\2\2\33M\3\2\2\2\35W\3\2\2\2\37a\3\2\2\2!h\3\2\2")
buf.write("\2#r\3\2\2\2%&\7&\2\2&\'\7*\2\2\'\4\3\2\2\2()\7.\2\2)")
buf.write("\6\3\2\2\2*+\7+\2\2+\b\3\2\2\2,-\7}\2\2-\n\3\2\2\2./\7")
buf.write("\177\2\2/\f\3\2\2\2\60\61\t\2\2\2\61\16\3\2\2\2\62\63")
buf.write("\t\3\2\2\63\20\3\2\2\2\64\65\t\4\2\2\65\22\3\2\2\2\66")
buf.write("\67\7^\2\2\67;\7^\2\289\7^\2\29;\7\'\2\2:\66\3\2\2\2:")
buf.write("8\3\2\2\2;\24\3\2\2\2<=\7^\2\2=A\7^\2\2>?\7^\2\2?A\7$")
buf.write("\2\2@<\3\2\2\2@>\3\2\2\2A\26\3\2\2\2BD\7B\2\2CE\5\21\t")
buf.write("\2DC\3\2\2\2EF\3\2\2\2FD\3\2\2\2FG\3\2\2\2G\30\3\2\2\2")
buf.write("HJ\5\17\b\2IH\3\2\2\2JK\3\2\2\2KI\3\2\2\2KL\3\2\2\2L\32")
buf.write("\3\2\2\2MR\7\'\2\2NQ\5\23\n\2OQ\n\5\2\2PN\3\2\2\2PO\3")
buf.write("\2\2\2QT\3\2\2\2RS\3\2\2\2RP\3\2\2\2SU\3\2\2\2TR\3\2\2")
buf.write("\2UV\7\'\2\2V\34\3\2\2\2W\\\7$\2\2X[\5\25\13\2Y[\n\6\2")
buf.write("\2ZX\3\2\2\2ZY\3\2\2\2[^\3\2\2\2\\]\3\2\2\2\\Z\3\2\2\2")
buf.write("]_\3\2\2\2^\\\3\2\2\2_`\7$\2\2`\36\3\2\2\2ad\7&\2\2be")
buf.write("\5\21\t\2ce\t\7\2\2db\3\2\2\2dc\3\2\2\2ef\3\2\2\2fd\3")
buf.write("\2\2\2fg\3\2\2\2g \3\2\2\2hl\7%\2\2ik\n\b\2\2ji\3\2\2")
buf.write("\2kn\3\2\2\2lj\3\2\2\2lm\3\2\2\2mo\3\2\2\2nl\3\2\2\2o")
buf.write("p\b\21\2\2p\"\3\2\2\2qs\t\t\2\2rq\3\2\2\2st\3\2\2\2tr")
buf.write("\3\2\2\2tu\3\2\2\2uv\3\2\2\2vw\b\22\2\2w$\3\2\2\2\17\2")
buf.write(":@FKPRZ\\dflt\3\b\2\2")
return buf.getvalue()
class ThttilLexer(Lexer):
atn = ATNDeserializer().deserialize(serializedATN())
decisionsToDFA = [ DFA(ds, i) for i, ds in enumerate(atn.decisionToState) ]
T__0 = 1
T__1 = 2
T__2 = 3
T__3 = 4
T__4 = 5
STREAM_TAG = 6
FUNCTION = 7
PRINT = 8
STRING = 9
VARIABLE = 10
COMMENT = 11
WHITESPACE = 12
channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ]
modeNames = [ "DEFAULT_MODE" ]
literalNames = [ "<INVALID>",
"'$('", "','", "')'", "'{'", "'}'" ]
symbolicNames = [ "<INVALID>",
"STREAM_TAG", "FUNCTION", "PRINT", "STRING", "VARIABLE", "COMMENT",
"WHITESPACE" ]
ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "LOWERCASE", "UPPERCASE",
"CHAR", "PROTECTED_PRINT", "PROTECTED_STRING", "STREAM_TAG",
"FUNCTION", "PRINT", "STRING", "VARIABLE", "COMMENT",
"WHITESPACE" ]
grammarFileName = "Thttil.g4"
def __init__(self, input=None, output:TextIO = sys.stdout):
super().__init__(input, output)
self.checkVersion("4.7.2")
self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache())
self._actions = None
self._predicates = None
| 45.84
| 103
| 0.524433
| 1,122
| 4,584
| 2.106061
| 0.186275
| 0.13796
| 0.107914
| 0.076174
| 0.227677
| 0.181126
| 0.126957
| 0.09014
| 0.02116
| 0.013542
| 0
| 0.251313
| 0.169284
| 4,584
| 99
| 104
| 46.30303
| 0.369223
| 0.012216
| 0
| 0.024691
| 1
| 0.481481
| 0.528073
| 0.462644
| 0
| 0
| 0
| 0
| 0
| 1
| 0.024691
| false
| 0
| 0.049383
| 0
| 0.345679
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| 0
| 0
| 1
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| 1
| 1
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| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
70831b9ab3bc457bb938c471024a93a190631a5e
| 142
|
py
|
Python
|
lib/dataset/__init__.py
|
techkang/human-pose-estimation.pytorch
|
6c8874f3b649161753fc389e7087f3d1538b4523
|
[
"MIT"
] | null | null | null |
lib/dataset/__init__.py
|
techkang/human-pose-estimation.pytorch
|
6c8874f3b649161753fc389e7087f3d1538b4523
|
[
"MIT"
] | null | null | null |
lib/dataset/__init__.py
|
techkang/human-pose-estimation.pytorch
|
6c8874f3b649161753fc389e7087f3d1538b4523
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import, division, print_function
from .coco import COCODataset as coco
from .mpii import MPIIDataset as mpii
| 28.4
| 64
| 0.838028
| 20
| 142
| 5.65
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133803
| 142
| 4
| 65
| 35.5
| 0.918699
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
70930f075eef53a545c809c168c28e202baa8ea8
| 186
|
py
|
Python
|
utils/__init__.py
|
IDKiro/dnd-submit-pytorch
|
1dd3b8c180d1921032f81216e991a945247e2308
|
[
"MIT"
] | 4
|
2019-11-25T10:34:38.000Z
|
2021-09-24T11:11:31.000Z
|
utils/__init__.py
|
IDKiro/dnd-submit-pytorch
|
1dd3b8c180d1921032f81216e991a945247e2308
|
[
"MIT"
] | 2
|
2020-01-12T06:06:05.000Z
|
2020-05-24T04:36:33.000Z
|
utils/__init__.py
|
IDKiro/dnd-submit-pytorch
|
1dd3b8c180d1921032f81216e991a945247e2308
|
[
"MIT"
] | null | null | null |
from .dndsubmit import denoise_srgb, pytorch_denoiser, bundle_submissions_srgb
from .common import AverageMeter, ListAverageMeter, read_img, hwc_to_chw, chw_to_hwc
from .noise import ISP
| 62
| 84
| 0.860215
| 27
| 186
| 5.592593
| 0.703704
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.091398
| 186
| 3
| 85
| 62
| 0.893491
| 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
| 1
| 0
|
0
| 5
|
562f8da4185fb5bb30da3a702cd81511c0a5429a
| 89
|
py
|
Python
|
testworkspace/test.py
|
gflaherty/rules_pyz
|
900546b12e880f272c82534cdd2423dcb109e795
|
[
"Apache-2.0"
] | 26
|
2018-01-29T23:28:45.000Z
|
2020-12-01T21:30:32.000Z
|
testworkspace/test.py
|
gflaherty/rules_pyz
|
900546b12e880f272c82534cdd2423dcb109e795
|
[
"Apache-2.0"
] | 28
|
2018-03-31T19:41:12.000Z
|
2019-01-30T21:57:43.000Z
|
testworkspace/test.py
|
gflaherty/rules_pyz
|
900546b12e880f272c82534cdd2423dcb109e795
|
[
"Apache-2.0"
] | 17
|
2018-03-08T21:30:22.000Z
|
2019-11-22T17:16:00.000Z
|
import unittest
class Test(unittest.TestCase):
def test_nothing(self):
pass
| 14.833333
| 30
| 0.696629
| 11
| 89
| 5.545455
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.224719
| 89
| 5
| 31
| 17.8
| 0.884058
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 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
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
5675be79eec694abc6e1397532640c5db0855f00
| 1,519
|
py
|
Python
|
tests/database/database.py
|
caputomarcos/mongorest
|
57d6b28d75e18afed5cef7160522958153b5be15
|
[
"BSD-3-Clause"
] | 16
|
2015-04-18T02:51:09.000Z
|
2020-12-15T18:05:16.000Z
|
tests/database/database.py
|
caputomarcos/mongorest
|
57d6b28d75e18afed5cef7160522958153b5be15
|
[
"BSD-3-Clause"
] | 8
|
2015-11-24T23:06:03.000Z
|
2016-07-21T17:57:59.000Z
|
tests/database/database.py
|
caputomarcos/mongorest
|
57d6b28d75e18afed5cef7160522958153b5be15
|
[
"BSD-3-Clause"
] | 2
|
2015-12-04T13:45:32.000Z
|
2016-06-11T13:44:53.000Z
|
# -*- encoding: UTF-8 -*-
from __future__ import absolute_import, unicode_literals
from os import environ
from mongorest.database import db, _get_db, ConnectionFailureProxy
from mongorest.testcase import TestCase
class TestDatabase(TestCase):
def test_db_is_a_proxied_pymongo_database(self):
self.assertIsInstance(db, ConnectionFailureProxy)
def test_db_connected_to_correct_database(self):
self.assertEqual(db.name, 'mongorest')
def test_correct_db_when_uri_passed(self):
environ['MONGOREST_SETTINGS_MODULE'] = 'tests.fixtures.database_test_uri_settings'
database = _get_db()
self.assertEqual(database.client.HOST, 'localhost')
self.assertEqual(database.client.PORT, 27017)
self.assertEqual(database.name, 'mongorest-test')
def test_correct_db_when_host_and_port_passed(self):
environ['MONGOREST_SETTINGS_MODULE'] = 'tests.fixtures.database_test_host_port_settings'
database = _get_db()
self.assertEqual(database.client.HOST, 'localhost')
self.assertEqual(database.client.PORT, 27017)
self.assertEqual(database.name, 'mongorest-test')
def test_correct_db_when_hosts_and_ports_passed(self):
environ['MONGOREST_SETTINGS_MODULE'] = 'tests.fixtures.database_test_hosts_ports_settings'
database = _get_db()
self.assertEqual(database.client.HOST, 'localhost')
self.assertEqual(database.client.PORT, 27017)
self.assertEqual(database.name, 'mongorest-test')
| 37.04878
| 98
| 0.74391
| 179
| 1,519
| 5.972067
| 0.26257
| 0.140318
| 0.193639
| 0.162769
| 0.634238
| 0.615529
| 0.615529
| 0.615529
| 0.615529
| 0.615529
| 0
| 0.012549
| 0.160632
| 1,519
| 40
| 99
| 37.975
| 0.825882
| 0.015142
| 0
| 0.444444
| 0
| 0
| 0.19411
| 0.141901
| 0
| 0
| 0
| 0
| 0.407407
| 1
| 0.185185
| false
| 0.111111
| 0.148148
| 0
| 0.37037
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
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| 1
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
5675d5e1af84f6fa4f8902811cc21bd3d8ee639f
| 103
|
py
|
Python
|
collector/util/tags.py
|
andre487/news487
|
4009eb3f828e48d7e7a3abf1b6c7510e3dd9ee46
|
[
"MIT"
] | null | null | null |
collector/util/tags.py
|
andre487/news487
|
4009eb3f828e48d7e7a3abf1b6c7510e3dd9ee46
|
[
"MIT"
] | 1
|
2017-11-06T02:42:09.000Z
|
2017-11-06T02:42:09.000Z
|
collector/util/tags.py
|
andre487/news487
|
4009eb3f828e48d7e7a3abf1b6c7510e3dd9ee46
|
[
"MIT"
] | null | null | null |
def create_tags_list(*tags):
tags_list = list(set(tags))
tags_list.sort()
return tags_list
| 20.6
| 31
| 0.68932
| 16
| 103
| 4.125
| 0.4375
| 0.484848
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.194175
| 103
| 4
| 32
| 25.75
| 0.795181
| 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
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
569b740175b67201a2ae3c9e96c9fa49d599fdae
| 80
|
py
|
Python
|
permisions/__init__.py
|
sepydev/django-user
|
1a67caa197f9bb72ec41491cac1ae0a94385da87
|
[
"MIT"
] | 1
|
2022-02-05T18:26:02.000Z
|
2022-02-05T18:26:02.000Z
|
permisions/__init__.py
|
mrprocs/django-user
|
1a67caa197f9bb72ec41491cac1ae0a94385da87
|
[
"MIT"
] | null | null | null |
permisions/__init__.py
|
mrprocs/django-user
|
1a67caa197f9bb72ec41491cac1ae0a94385da87
|
[
"MIT"
] | null | null | null |
from .model_permissions import DjangoModelPermission, IsOwnerPermission # noqa
| 40
| 79
| 0.8625
| 7
| 80
| 9.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 80
| 1
| 80
| 80
| 0.944444
| 0.05
| 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
| 1
| 0
|
0
| 5
|
3b685247c44b23d737ab84a30c392a8d526a09b2
| 181
|
py
|
Python
|
demo_video/read_image.py
|
lav-kush/MotionRec
|
a784dc4ac6dd4a47c19be5434afbc655aacc7896
|
[
"Apache-2.0"
] | 16
|
2020-05-10T12:04:42.000Z
|
2021-11-23T05:42:20.000Z
|
demo_video/read_image.py
|
lav-kush/MotionRec
|
a784dc4ac6dd4a47c19be5434afbc655aacc7896
|
[
"Apache-2.0"
] | 5
|
2020-05-11T10:31:21.000Z
|
2021-07-23T03:30:43.000Z
|
demo_video/read_image.py
|
lav-kush/MotionRec
|
a784dc4ac6dd4a47c19be5434afbc655aacc7896
|
[
"Apache-2.0"
] | 9
|
2020-05-10T13:18:42.000Z
|
2021-11-20T03:47:00.000Z
|
import glob
path = '/home/cvprlab/lavkush/Demo/9.0_include_no_annotaion_in_test_depth_10/input_video/test_image_frame/'
print()
print(sorted(glob.glob('test_image_frame/'+'*.jpg')))
| 45.25
| 107
| 0.80663
| 30
| 181
| 4.466667
| 0.766667
| 0.134328
| 0.208955
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022857
| 0.033149
| 181
| 4
| 108
| 45.25
| 0.742857
| 0
| 0
| 0
| 0
| 0
| 0.659341
| 0.538462
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 0.25
| 0.5
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8e6ec08cb95f9222047cce4977b0806492663df0
| 84
|
py
|
Python
|
opennng/__init__.py
|
avramus/OpenNGen
|
88bd21e29a412b0d4319ad2db40dddf71167e422
|
[
"MIT"
] | 5
|
2019-08-29T08:40:10.000Z
|
2019-08-29T20:21:52.000Z
|
opennng/__init__.py
|
avramus/OpenNGen
|
88bd21e29a412b0d4319ad2db40dddf71167e422
|
[
"MIT"
] | null | null | null |
opennng/__init__.py
|
avramus/OpenNGen
|
88bd21e29a412b0d4319ad2db40dddf71167e422
|
[
"MIT"
] | null | null | null |
name="opennng"
from .models import *
from .preparation import *
from .util import *
| 16.8
| 26
| 0.738095
| 11
| 84
| 5.636364
| 0.636364
| 0.322581
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.154762
| 84
| 5
| 27
| 16.8
| 0.873239
| 0
| 0
| 0
| 0
| 0
| 0.082353
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 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
| 1
| 0
|
0
| 5
|
8e9bfc89dbbfb320dae21f4fdf1e7c01679a4930
| 78
|
py
|
Python
|
flask/celery/tasks.py
|
JeanFraga/TaggerDocker
|
eb41b31ef6b5d1b1aba38f19ffc544db430949f2
|
[
"MIT"
] | null | null | null |
flask/celery/tasks.py
|
JeanFraga/TaggerDocker
|
eb41b31ef6b5d1b1aba38f19ffc544db430949f2
|
[
"MIT"
] | null | null | null |
flask/celery/tasks.py
|
JeanFraga/TaggerDocker
|
eb41b31ef6b5d1b1aba38f19ffc544db430949f2
|
[
"MIT"
] | null | null | null |
@app.task(bind=True, name='refresh')
def test(self):
return "Hello Celery"
| 26
| 36
| 0.692308
| 12
| 78
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 78
| 3
| 37
| 26
| 0.794118
| 0
| 0
| 0
| 0
| 0
| 0.240506
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
8eaa6e7abd74fb73c8741080db6fb039e9fc911f
| 23
|
py
|
Python
|
src/GGData/GGen/__init__.py
|
NikolayRag/codeg
|
2af182aaab3fea7c5f94727569fa65d9adda9de0
|
[
"MIT"
] | null | null | null |
src/GGData/GGen/__init__.py
|
NikolayRag/codeg
|
2af182aaab3fea7c5f94727569fa65d9adda9de0
|
[
"MIT"
] | null | null | null |
src/GGData/GGen/__init__.py
|
NikolayRag/codeg
|
2af182aaab3fea7c5f94727569fa65d9adda9de0
|
[
"MIT"
] | null | null | null |
from .GGen import GGen
| 11.5
| 22
| 0.782609
| 4
| 23
| 4.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173913
| 23
| 1
| 23
| 23
| 0.947368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 1
| 0
| 0
| 0
|
0
| 5
|
8ee9a4a934ff06d29d5bebc36e5a490d81222492
| 523
|
py
|
Python
|
src/pipedown/visualization/node_drawers.py
|
brendanhasz/drainpype
|
a183acec7cae1ef9fde260868e2b021516a8cd7f
|
[
"MIT"
] | 2
|
2021-03-03T12:11:24.000Z
|
2021-03-18T15:09:52.000Z
|
src/pipedown/visualization/node_drawers.py
|
brendanhasz/pipedown
|
a183acec7cae1ef9fde260868e2b021516a8cd7f
|
[
"MIT"
] | null | null | null |
src/pipedown/visualization/node_drawers.py
|
brendanhasz/pipedown
|
a183acec7cae1ef9fde260868e2b021516a8cd7f
|
[
"MIT"
] | null | null | null |
def rounded_box_fn_icon(node):
return {
"shape": "box",
"style": "rounded",
}
def rounded_box_metric_icon(node):
return {
"shape": "box",
"style": "rounded",
}
def square_box_database_icon(node):
return {
"shape": "box",
}
def square_box_json_icon(node):
return {
"shape": "box",
}
def square_box_highlight(node):
return {
"shape": "box",
}
def square_box_model_icon(node):
return {
"shape": "box",
}
| 14.135135
| 35
| 0.529637
| 57
| 523
| 4.561404
| 0.263158
| 0.230769
| 0.346154
| 0.415385
| 0.746154
| 0.661538
| 0.661538
| 0.546154
| 0
| 0
| 0
| 0
| 0.321224
| 523
| 36
| 36
| 14.527778
| 0.732394
| 0
| 0
| 0.538462
| 0
| 0
| 0.137667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0
| 0
| 0.230769
| 0.461538
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
8eea0936164163aa1273daa866db759c9970c805
| 76
|
py
|
Python
|
CH1-HelloWorld/HelloWorld.py
|
amit-majumdar89/Python--
|
dda07f5ffb3dd9fc5c0706667ac5dded5330725b
|
[
"MIT"
] | null | null | null |
CH1-HelloWorld/HelloWorld.py
|
amit-majumdar89/Python--
|
dda07f5ffb3dd9fc5c0706667ac5dded5330725b
|
[
"MIT"
] | null | null | null |
CH1-HelloWorld/HelloWorld.py
|
amit-majumdar89/Python--
|
dda07f5ffb3dd9fc5c0706667ac5dded5330725b
|
[
"MIT"
] | null | null | null |
#
# Simple Hello World Program
#
print("Hello Python")
print('Hello World')
| 12.666667
| 28
| 0.710526
| 10
| 76
| 5.4
| 0.6
| 0.37037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144737
| 76
| 6
| 29
| 12.666667
| 0.830769
| 0.342105
| 0
| 0
| 0
| 0
| 0.489362
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
d98645d71c28d615b657ee47665b2033e6ec9670
| 87
|
py
|
Python
|
get username.py
|
manand881/Python-Programs
|
eb970cb1b21d4aede0102c60425eb8a1d4ac605c
|
[
"MIT"
] | null | null | null |
get username.py
|
manand881/Python-Programs
|
eb970cb1b21d4aede0102c60425eb8a1d4ac605c
|
[
"MIT"
] | null | null | null |
get username.py
|
manand881/Python-Programs
|
eb970cb1b21d4aede0102c60425eb8a1d4ac605c
|
[
"MIT"
] | null | null | null |
# Get the current username
import getpass
print('')
print(getpass.getuser())
print('')
| 14.5
| 26
| 0.724138
| 11
| 87
| 5.727273
| 0.727273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114943
| 87
| 5
| 27
| 17.4
| 0.818182
| 0.275862
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0.25
| 0
| 0.25
| 0.75
| 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
| 1
|
0
| 5
|
d997ebdffec8e009e523c643ca7f349008ea0a17
| 248
|
py
|
Python
|
RaspberryPi/DjangoSite/mysite/curling/admin.py
|
zbassett/curling-robot
|
188800588fa294e93522ea20fa7ddab7b5a642b3
|
[
"Apache-2.0"
] | 1
|
2017-10-04T13:41:36.000Z
|
2017-10-04T13:41:36.000Z
|
RaspberryPi/DjangoSite/mysite/curling/admin.py
|
zbassett/curling-robot
|
188800588fa294e93522ea20fa7ddab7b5a642b3
|
[
"Apache-2.0"
] | null | null | null |
RaspberryPi/DjangoSite/mysite/curling/admin.py
|
zbassett/curling-robot
|
188800588fa294e93522ea20fa7ddab7b5a642b3
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from .models import Club
admin.site.register(Club)
from .models import Sheet
admin.site.register(Sheet)
from .models import Person
admin.site.register(Person)
from .models import Rock
admin.site.register(Rock)
| 16.533333
| 32
| 0.798387
| 37
| 248
| 5.351351
| 0.324324
| 0.20202
| 0.323232
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116935
| 248
| 14
| 33
| 17.714286
| 0.90411
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.555556
| 0
| 0.555556
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
794abec225ffcfad4f89aa5eab00f36dde0406ec
| 9,142
|
py
|
Python
|
salika/views/store_views.py
|
BarisSari/django_crud
|
ce9586c10da2f865d29d9a18e9ff5582abe5e3a0
|
[
"MIT"
] | null | null | null |
salika/views/store_views.py
|
BarisSari/django_crud
|
ce9586c10da2f865d29d9a18e9ff5582abe5e3a0
|
[
"MIT"
] | null | null | null |
salika/views/store_views.py
|
BarisSari/django_crud
|
ce9586c10da2f865d29d9a18e9ff5582abe5e3a0
|
[
"MIT"
] | null | null | null |
from django.views.generic.detail import DetailView
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.views.generic.list import ListView
from ..models import Store
from ..forms import StoreForm
from django.urls import reverse_lazy
from django.urls import reverse
from django.http import Http404
class StoreListView(ListView):
model = Store
template_name = "salika/store_list.html"
paginate_by = 20
context_object_name = "store_list"
allow_empty = True
page_kwarg = 'page'
paginate_orphans = 0
def __init__(self, **kwargs):
return super(StoreListView, self).__init__(**kwargs)
def dispatch(self, *args, **kwargs):
return super(StoreListView, self).dispatch(*args, **kwargs)
def get(self, request, *args, **kwargs):
return super(StoreListView, self).get(request, *args, **kwargs)
def get_queryset(self):
return super(StoreListView, self).get_queryset()
def get_allow_empty(self):
return super(StoreListView, self).get_allow_empty()
def get_context_data(self, *args, **kwargs):
ret = super(StoreListView, self).get_context_data(*args, **kwargs)
return ret
def get_paginate_by(self, queryset):
return super(StoreListView, self).get_paginate_by(queryset)
def get_context_object_name(self, object_list):
return super(StoreListView, self).get_context_object_name(object_list)
def paginate_queryset(self, queryset, page_size):
return super(StoreListView, self).paginate_queryset(queryset, page_size)
def get_paginator(self, queryset, per_page, orphans=0, allow_empty_first_page=True):
return super(StoreListView, self).get_paginator(queryset, per_page, orphans=0, allow_empty_first_page=True)
def render_to_response(self, context, **response_kwargs):
return super(StoreListView, self).render_to_response(context, **response_kwargs)
def get_template_names(self):
return super(StoreListView, self).get_template_names()
class StoreDetailView(DetailView):
model = Store
template_name = "salika/store_detail.html"
context_object_name = "store"
slug_field = 'slug'
slug_url_kwarg = 'slug'
pk_url_kwarg = 'pk'
def __init__(self, **kwargs):
return super(StoreDetailView, self).__init__(**kwargs)
def dispatch(self, *args, **kwargs):
return super(StoreDetailView, self).dispatch(*args, **kwargs)
def get(self, request, *args, **kwargs):
return super(StoreDetailView, self).get(request, *args, **kwargs)
def get_object(self, queryset=None):
return super(StoreDetailView, self).get_object(queryset)
def get_queryset(self):
return super(StoreDetailView, self).get_queryset()
def get_slug_field(self):
return super(StoreDetailView, self).get_slug_field()
def get_context_data(self, **kwargs):
ret = super(StoreDetailView, self).get_context_data(**kwargs)
return ret
def get_context_object_name(self, obj):
return super(StoreDetailView, self).get_context_object_name(obj)
def render_to_response(self, context, **response_kwargs):
return super(StoreDetailView, self).render_to_response(context, **response_kwargs)
def get_template_names(self):
return super(StoreDetailView, self).get_template_names()
class StoreCreateView(CreateView):
model = Store
form_class = StoreForm
# fields = ['store_id', 'manager_staff', 'address', 'last_update']
template_name = "salika/store_create.html"
success_url = reverse_lazy("store_list")
def __init__(self, **kwargs):
return super(StoreCreateView, self).__init__(**kwargs)
def dispatch(self, request, *args, **kwargs):
return super(StoreCreateView, self).dispatch(request, *args, **kwargs)
def get(self, request, *args, **kwargs):
return super(StoreCreateView, self).get(request, *args, **kwargs)
def post(self, request, *args, **kwargs):
return super(StoreCreateView, self).post(request, *args, **kwargs)
def get_form_class(self):
return super(StoreCreateView, self).get_form_class()
def get_form(self, form_class=None):
return super(StoreCreateView, self).get_form(form_class)
def get_form_kwargs(self, **kwargs):
return super(StoreCreateView, self).get_form_kwargs(**kwargs)
def get_initial(self):
return super(StoreCreateView, self).get_initial()
def form_invalid(self, form):
return super(StoreCreateView, self).form_invalid(form)
def form_valid(self, form):
obj = form.save(commit=False)
obj.save()
return super(StoreCreateView, self).form_valid(form)
def get_context_data(self, **kwargs):
ret = super(StoreCreateView, self).get_context_data(**kwargs)
return ret
def render_to_response(self, context, **response_kwargs):
return super(StoreCreateView, self).render_to_response(context, **response_kwargs)
def get_template_names(self):
return super(StoreCreateView, self).get_template_names()
def get_success_url(self):
return reverse("salika:store_detail", args=(self.object.pk,))
class StoreUpdateView(UpdateView):
model = Store
form_class = StoreForm
# fields = ['store_id', 'manager_staff', 'address', 'last_update']
template_name = "salika/store_update.html"
initial = {}
slug_field = 'slug'
slug_url_kwarg = 'slug'
pk_url_kwarg = 'pk'
context_object_name = "store"
def __init__(self, **kwargs):
return super(StoreUpdateView, self).__init__(**kwargs)
def dispatch(self, *args, **kwargs):
return super(StoreUpdateView, self).dispatch(*args, **kwargs)
def get(self, request, *args, **kwargs):
return super(StoreUpdateView, self).get(request, *args, **kwargs)
def post(self, request, *args, **kwargs):
return super(StoreUpdateView, self).post(request, *args, **kwargs)
def get_object(self, queryset=None):
return super(StoreUpdateView, self).get_object(queryset)
def get_queryset(self):
return super(StoreUpdateView, self).get_queryset()
def get_slug_field(self):
return super(StoreUpdateView, self).get_slug_field()
def get_form_class(self):
return super(StoreUpdateView, self).get_form_class()
def get_form(self, form_class=None):
return super(StoreUpdateView, self).get_form(form_class)
def get_form_kwargs(self, **kwargs):
return super(StoreUpdateView, self).get_form_kwargs(**kwargs)
def get_initial(self):
return super(StoreUpdateView, self).get_initial()
def form_invalid(self, form):
return super(StoreUpdateView, self).form_invalid(form)
def form_valid(self, form):
obj = form.save(commit=False)
obj.save()
return super(StoreUpdateView, self).form_valid(form)
def get_context_data(self, **kwargs):
ret = super(StoreUpdateView, self).get_context_data(**kwargs)
return ret
def get_context_object_name(self, obj):
return super(StoreUpdateView, self).get_context_object_name(obj)
def render_to_response(self, context, **response_kwargs):
return super(StoreUpdateView, self).render_to_response(context, **response_kwargs)
def get_template_names(self):
return super(StoreUpdateView, self).get_template_names()
def get_success_url(self):
return reverse("salika:store_detail", args=(self.object.pk,))
class StoreDeleteView(DeleteView):
model = Store
template_name = "salika/store_delete.html"
slug_field = 'slug'
slug_url_kwarg = 'slug'
pk_url_kwarg = 'pk'
context_object_name = "store"
def __init__(self, **kwargs):
return super(StoreDeleteView, self).__init__(**kwargs)
def dispatch(self, *args, **kwargs):
return super(StoreDeleteView, self).dispatch(*args, **kwargs)
def get(self, request, *args, **kwargs):
raise Http404
def post(self, request, *args, **kwargs):
return super(StoreDeleteView, self).post(request, *args, **kwargs)
def delete(self, request, *args, **kwargs):
return super(StoreDeleteView, self).delete(request, *args, **kwargs)
def get_object(self, queryset=None):
return super(StoreDeleteView, self).get_object(queryset)
def get_queryset(self):
return super(StoreDeleteView, self).get_queryset()
def get_slug_field(self):
return super(StoreDeleteView, self).get_slug_field()
def get_context_data(self, **kwargs):
ret = super(StoreDeleteView, self).get_context_data(**kwargs)
return ret
def get_context_object_name(self, obj):
return super(StoreDeleteView, self).get_context_object_name(obj)
def render_to_response(self, context, **response_kwargs):
return super(StoreDeleteView, self).render_to_response(context, **response_kwargs)
def get_template_names(self):
return super(StoreDeleteView, self).get_template_names()
def get_success_url(self):
return reverse("salika:store_list")
| 34.2397
| 115
| 0.698644
| 1,112
| 9,142
| 5.492806
| 0.081835
| 0.104453
| 0.069581
| 0.078585
| 0.866568
| 0.76981
| 0.641945
| 0.621971
| 0.57924
| 0.57924
| 0
| 0.001479
| 0.186502
| 9,142
| 266
| 116
| 34.368421
| 0.81982
| 0.014111
| 0
| 0.475936
| 0
| 0
| 0.026859
| 0.013097
| 0
| 0
| 0
| 0
| 0
| 1
| 0.358289
| false
| 0
| 0.042781
| 0.315508
| 0.946524
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
796a802aa1f9169153e876617685c5a81bf04b09
| 169
|
py
|
Python
|
010-b-print.py
|
catherinedevlin/just-enough-python
|
3e272d37cbe68eed3e90fb472cfb4caf0a571881
|
[
"MIT"
] | 5
|
2019-07-25T13:54:44.000Z
|
2021-02-05T12:16:53.000Z
|
010-b-print.py
|
catherinedevlin/just-enough-python
|
3e272d37cbe68eed3e90fb472cfb4caf0a571881
|
[
"MIT"
] | null | null | null |
010-b-print.py
|
catherinedevlin/just-enough-python
|
3e272d37cbe68eed3e90fb472cfb4caf0a571881
|
[
"MIT"
] | null | null | null |
# Give yourself a nice cheer -
# print out Go Whateveryournameis!
print( )
# Did you get an error?
# Remember that you need to wrap something around text...
| 21.125
| 57
| 0.680473
| 24
| 169
| 4.791667
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.248521
| 169
| 7
| 58
| 24.142857
| 0.905512
| 0.83432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 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
| 1
|
0
| 5
|
79d3bb44fd2f27ba9de82e3e8c270e4c3a92b35f
| 67
|
py
|
Python
|
tests/cmdline/cmd_optimise.py
|
learnforpractice/micropython-cpp
|
004bc8382f74899e7b876cc29bfa6a9cc976ba10
|
[
"MIT"
] | 13,648
|
2015-01-01T01:34:51.000Z
|
2022-03-31T16:19:53.000Z
|
tests/cmdline/cmd_optimise.py
|
learnforpractice/micropython-cpp
|
004bc8382f74899e7b876cc29bfa6a9cc976ba10
|
[
"MIT"
] | 7,092
|
2015-01-01T07:59:11.000Z
|
2022-03-31T23:52:18.000Z
|
tests/cmdline/cmd_optimise.py
|
learnforpractice/micropython-cpp
|
004bc8382f74899e7b876cc29bfa6a9cc976ba10
|
[
"MIT"
] | 4,942
|
2015-01-02T11:48:50.000Z
|
2022-03-31T19:57:10.000Z
|
# cmdline: -O
# test optimisation output
print(__debug__)
assert 0
| 13.4
| 26
| 0.761194
| 9
| 67
| 5.222222
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017544
| 0.149254
| 67
| 4
| 27
| 16.75
| 0.807018
| 0.537313
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8dc264b2c4d29a69a0b83734817af0dd886842c3
| 108
|
py
|
Python
|
python/testData/intentions/PyConvertFormatOperatorToMethodIntentionTest/escaped.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/intentions/PyConvertFormatOperatorToMethodIntentionTest/escaped.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/intentions/PyConvertFormatOperatorToMethodIntentionTest/escaped.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
print u"\N{LATIN SMALL LETTER B}%s\N{NUMBER SIGN}\
%s\N{LATIN SMALL<caret> LETTER B}" % (str1, str2)
| 54
| 57
| 0.62963
| 20
| 108
| 3.4
| 0.65
| 0.176471
| 0.323529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022727
| 0.185185
| 108
| 2
| 57
| 54
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.5
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8df3e28c7bc919232b4aee8604cb3e394bb12a9e
| 221
|
py
|
Python
|
test cases/common/52 run target/check-env.py
|
bonzini/meson
|
b1efd03619f6c88acaf4f0106d2192a4a1cf8460
|
[
"Apache-2.0"
] | null | null | null |
test cases/common/52 run target/check-env.py
|
bonzini/meson
|
b1efd03619f6c88acaf4f0106d2192a4a1cf8460
|
[
"Apache-2.0"
] | null | null | null |
test cases/common/52 run target/check-env.py
|
bonzini/meson
|
b1efd03619f6c88acaf4f0106d2192a4a1cf8460
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python3
import os
assert 'MESON_SOURCE_ROOT' in os.environ
assert 'MESON_BUILD_ROOT' in os.environ
assert 'MESON_SUBDIR' in os.environ
assert 'MESONINTROSPECT' in os.environ
assert 'MY_ENV' in os.environ
| 22.1
| 40
| 0.791855
| 37
| 221
| 4.567568
| 0.432432
| 0.118343
| 0.325444
| 0.402367
| 0.307692
| 0.307692
| 0
| 0
| 0
| 0
| 0
| 0.005128
| 0.117647
| 221
| 9
| 41
| 24.555556
| 0.861538
| 0.095023
| 0
| 0
| 0
| 0
| 0.331658
| 0
| 0
| 0
| 0
| 0
| 0.833333
| 1
| 0
| true
| 0
| 0.166667
| 0
| 0.166667
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
5c0faef7ece2876438dfb9c0d2fd62dec9b007ff
| 603
|
py
|
Python
|
server.py
|
mehrdad-shokri/DNS-Persist
|
085eb804de7ba79e9aa6f532d515ccea30d75269
|
[
"MIT"
] | 210
|
2017-11-10T18:21:03.000Z
|
2022-03-25T15:04:21.000Z
|
server.py
|
mehrdad-shokri/DNS-Persist
|
085eb804de7ba79e9aa6f532d515ccea30d75269
|
[
"MIT"
] | 1
|
2017-11-10T17:56:30.000Z
|
2017-11-11T00:24:01.000Z
|
server.py
|
mehrdad-shokri/DNS-Persist
|
085eb804de7ba79e9aa6f532d515ccea30d75269
|
[
"MIT"
] | 75
|
2017-11-10T21:46:05.000Z
|
2021-12-28T08:54:59.000Z
|
from modules import DNSListener
from modules import AgentControllerCLI
import threading
banner = """
____ _ _______ ____ _ __
/ __ \/ | / / ___/ / __ \___ __________(_)____/ /_
/ / / / |/ /\__ \______/ /_/ / _ \/ ___/ ___/ / ___/ __/
/ /_/ / /| /___/ /_____/ ____/ __/ / (__ ) (__ ) /_
/_____/_/ |_//____/ /_/ \___/_/ /____/_/____/\__/
"""
host = "0.0.0.0"
port = 53
print banner
DNSObject = DNSListener.DNSListener(host,port)
commandInputs = DNSListener.Input().cmdloop()
| 27.409091
| 59
| 0.492537
| 29
| 603
| 6.344828
| 0.551724
| 0.032609
| 0.184783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015306
| 0.349917
| 603
| 22
| 60
| 27.409091
| 0.454082
| 0
| 0
| 0
| 0
| 0.2
| 0.609272
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.2
| null | null | 0.066667
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
30867763bb069152acf1edadd6b5f25dba0606a9
| 106
|
py
|
Python
|
Experiment/sound_decomp_user.py
|
jacky-liang/music-generator
|
8f7af4bee0c124f83a6ea228ade0a0b8ae37e103
|
[
"Apache-2.0"
] | null | null | null |
Experiment/sound_decomp_user.py
|
jacky-liang/music-generator
|
8f7af4bee0c124f83a6ea228ade0a0b8ae37e103
|
[
"Apache-2.0"
] | null | null | null |
Experiment/sound_decomp_user.py
|
jacky-liang/music-generator
|
8f7af4bee0c124f83a6ea228ade0a0b8ae37e103
|
[
"Apache-2.0"
] | null | null | null |
from sound_decomp import SoundDecomposer
c_major = SoundDecomposer("C Major")
c_major.read("c_major.wav")
| 26.5
| 40
| 0.811321
| 16
| 106
| 5.125
| 0.5625
| 0.292683
| 0.512195
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084906
| 106
| 4
| 41
| 26.5
| 0.845361
| 0
| 0
| 0
| 0
| 0
| 0.168224
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
30d02834b92a228b9fd97b7afd233b63c7dbd162
| 109
|
py
|
Python
|
tests/cv/__init__.py
|
stateoftheartai/sotaai
|
1d01a385f115c567ad55eb10bdae16c1437978a1
|
[
"MIT"
] | 23
|
2021-05-23T09:32:36.000Z
|
2021-12-22T16:44:21.000Z
|
tests/cv/__init__.py
|
stateoftheartai/sotaai
|
1d01a385f115c567ad55eb10bdae16c1437978a1
|
[
"MIT"
] | null | null | null |
tests/cv/__init__.py
|
stateoftheartai/sotaai
|
1d01a385f115c567ad55eb10bdae16c1437978a1
|
[
"MIT"
] | 1
|
2021-08-19T22:37:18.000Z
|
2021-08-19T22:37:18.000Z
|
# -*- coding: utf-8 -*-
# Author: Hugo Ochoa <hugo@stateoftheart.ai>
# Copyright: Stateoftheart AI PBC 2020.
| 27.25
| 44
| 0.688073
| 14
| 109
| 5.357143
| 0.785714
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053763
| 0.146789
| 109
| 3
| 45
| 36.333333
| 0.752688
| 0.93578
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 1
| 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
| 5
|
30e000429cff23714a20703f6f66b177960e7ea5
| 12,216
|
py
|
Python
|
account_app/views.py
|
xjati46/agoraschool
|
98e9c6510f50a9ee87b5a6e3627466d244f7a617
|
[
"MIT"
] | null | null | null |
account_app/views.py
|
xjati46/agoraschool
|
98e9c6510f50a9ee87b5a6e3627466d244f7a617
|
[
"MIT"
] | null | null | null |
account_app/views.py
|
xjati46/agoraschool
|
98e9c6510f50a9ee87b5a6e3627466d244f7a617
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render, redirect
from django.views.generic import TemplateView, ListView, DetailView, CreateView
from django.contrib.auth.mixins import UserPassesTestMixin
from account_app.models import (
Kelas, AnggotaKelas, Mapel, TimMapel,
Kurikulum, LogMengajar
)
from account_app.filters import MuridAdminFilter, GuruAdminFilter
from django.contrib.auth.decorators import user_passes_test
from django.urls import reverse_lazy
from account_app.forms import KurikulumForm, LogMengajarForm
from extra_app.models import Pengumuman, TagihanMurid, NilaiMurid
def test_func(self):
return self.groups.filter(name="admin").exists()
def test_func_2(self):
return self.groups.filter(name="guru").exists()
def test_func_3(self):
return self.groups.filter(name="murid").exists()
# ############################## ADMIN VIEWS ##############################
class HomeAdminView(UserPassesTestMixin, TemplateView):
template_name = 'account_app/admin/home.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context['jumlah_murid'] = AnggotaKelas.objects.count()
context['jumlah_guru'] = TimMapel.objects.count()
context['jumlah_kelas'] = Kelas.objects.count()
context['jumlah_mapel'] = Mapel.objects.count()
return context
# ALL KELAS VIEW ------------------------------
class KelasAdminView(UserPassesTestMixin, ListView):
model = Kelas
template_name = 'account_app/admin/kelas_list.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
class KelasAdminDetailView(UserPassesTestMixin, DetailView):
model = Kelas
template_name = 'account_app/admin/kelas_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL MURID VIEW ------------------------------
@user_passes_test(
test_func,
login_url='/denied-access/',
redirect_field_name=None)
def MuridAdminView(request):
qs = AnggotaKelas.objects.order_by('kelas', 'murid__nama_lengkap')
filter_qs = MuridAdminFilter(request.GET, queryset=qs)
context = {
'qs': qs,
'filter_qs': filter_qs,
}
return render(
request,
'account_app/admin/murid_list.html',
context)
@user_passes_test(
test_func,
login_url='/denied-access/',
redirect_field_name=None)
def SortNamaMuridAdminView(request):
qs = AnggotaKelas.objects.order_by('murid__nama_lengkap')
filter_qs = MuridAdminFilter(request.GET, queryset=qs)
context = {
'qs': qs,
'filter_qs': filter_qs,
}
return render(
request,
'account_app/admin/sort/sortnama_murid_list.html',
context)
class MuridAdminDetailView(UserPassesTestMixin, DetailView):
model = AnggotaKelas
template_name = 'account_app/admin/murid_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL MAPEL VIEW ------------------------------
class MapelAdminView(UserPassesTestMixin, ListView):
model = Mapel
template_name = 'account_app/admin/mapel_list.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
class MapelAdminDetailView(UserPassesTestMixin, DetailView):
model = Mapel
template_name = 'account_app/admin/mapel_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL GURU VIEW ------------------------------
@user_passes_test(
test_func,
login_url='/denied-access/',
redirect_field_name=None)
def GuruAdminView(request):
qs = TimMapel.objects.order_by('mapel', 'guru__nama_lengkap')
filter_qs = GuruAdminFilter(request.GET, queryset=qs)
context = {
'qs': qs,
'filter_qs': filter_qs,
}
return render(
request,
'account_app/admin/guru_list.html',
context)
@user_passes_test(
test_func,
login_url='/denied-access/',
redirect_field_name=None)
def SortNamaGuruAdminView(request):
qs = TimMapel.objects.order_by('guru__nama_lengkap')
filter_qs = GuruAdminFilter(request.GET, queryset=qs)
context = {
'qs': qs,
'filter_qs': filter_qs,
}
return render(
request,
'account_app/admin/sort/sortnama_guru_list.html',
context)
class GuruAdminDetailView(UserPassesTestMixin, DetailView):
model = TimMapel
template_name = 'account_app/admin/guru_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL KURIKULUM VIEW ------------------------------
class KurikulumAdminDetailView(UserPassesTestMixin, DetailView):
template_name = 'account_app/admin/kurikulum.html'
model = Kurikulum
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL LOG MENGAJAR VIEW ------------------------------
class LogMengajarAdminDetailView(UserPassesTestMixin, DetailView):
template_name = 'account_app/admin/logmengajar.html'
model = LogMengajar
def test_func(self):
return self.request.user.groups.filter(name="admin").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ############################## END-ADMIN VIEWS ##############################
# ############################## GURU VIEWS ##############################
class HomeGuruView(UserPassesTestMixin, TemplateView):
template_name = 'account_app/guru/home.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context['log_list'] = LogMengajar.objects.filter(
guru=self.request.user.id)[:5]
context['pengumuman_list'] = Pengumuman.objects.filter(
kategori__exact='Guru')[:5]
return context
# ALL KELAS VIEW ------------------------------
class KelasGuruView(UserPassesTestMixin, ListView):
model = Kelas
template_name = 'account_app/guru/kelas_list.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
class KelasGuruDetailView(UserPassesTestMixin, DetailView):
model = Kelas
template_name = 'account_app/guru/kelas_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL MURID VIEW ------------------------------
class MuridGuruDetailView(UserPassesTestMixin, DetailView):
model = AnggotaKelas
template_name = 'account_app/guru/murid_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL MAPEL VIEW ------------------------------
class MapelGuruView(UserPassesTestMixin, ListView):
template_name = 'account_app/guru/mapel_list.html'
def get_queryset(self):
return TimMapel.objects.filter(guru=self.request.user.id)
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
class MapelGuruDetailView(UserPassesTestMixin, DetailView):
model = Mapel
template_name = 'account_app/guru/mapel_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL KURIKULUM VIEW ------------------------------
class KurikulumGuruDetailView(UserPassesTestMixin, DetailView):
template_name = 'account_app/guru/kurikulum.html'
model = Kurikulum
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
class KurikulumGuruCreateView(UserPassesTestMixin, CreateView):
form_class = KurikulumForm
success_url = reverse_lazy('account-app:mapel-guru')
template_name = 'account_app/guru/kurikulum_form.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL LOG MENGAJAR VIEW ------------------------------
class LogMengajarGuruDetailView(UserPassesTestMixin, DetailView):
template_name = 'account_app/guru/logmengajar.html'
model = LogMengajar
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
class LogMengajarGuruCreateView(UserPassesTestMixin, CreateView):
form_class = LogMengajarForm
success_url = reverse_lazy('account-app:kelas-guru')
template_name = 'account_app/guru/logmengajar_form.html'
def test_func(self):
return self.request.user.groups.filter(name="guru").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ############################## END-GURU VIEWS ##############################
# ############################## MURID VIEWS ##############################
class HomeMuridView(UserPassesTestMixin, TemplateView):
template_name = 'account_app/murid/home.html'
def test_func(self):
return self.request.user.groups.filter(name="murid").exists()
def handle_no_permission(self):
return redirect('denied-access')
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context['tagihan_list'] = TagihanMurid.objects.filter(
tertagih__murid=self.request.user.id).exclude(status_bayar=True)
context['pengumuman_list'] = Pengumuman.objects.filter(
kategori__exact='Murid')[:5]
context['nilai_list'] = NilaiMurid.objects.filter(
peserta_tes__murid=self.request.user.id)[:5]
return context
# # ALL MAPEL VIEW ------------------------------
class MapelMuridView(UserPassesTestMixin, ListView):
model = Mapel
template_name = 'account_app/murid/mapel_list.html'
def test_func(self):
return self.request.user.groups.filter(name="murid").exists()
def handle_no_permission(self):
return redirect('denied-access')
class MapelMuridDetailView(UserPassesTestMixin, DetailView):
model = Mapel
template_name = 'account_app/murid/mapel_detail.html'
def test_func(self):
return self.request.user.groups.filter(name="murid").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ALL KURIKULUM VIEW ------------------------------
class KurikulumMuridDetailView(UserPassesTestMixin, DetailView):
template_name = 'account_app/murid/kurikulum.html'
model = Kurikulum
def test_func(self):
return self.request.user.groups.filter(name="murid").exists()
def handle_no_permission(self):
return redirect('denied-access')
# ############################## END-MURID VIEWS ##############################
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| 96
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py
|
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|
venv/lib/python3.8/site-packages/past/types/basestring.py
|
Retraces/UkraineBot
|
3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/past/types/basestring.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/past/types/basestring.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/aa/b2/26/72bdb8c2f74308cbc5f71d13cb1f12d650ade8623046fcee026be0fd38
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ebb5473808a996c6ba8f60c1812ed3c3b62a30d1
| 62
|
py
|
Python
|
t07numberpatterns_cubes.py
|
CherryNoddles/y1math
|
877b87ee60e7569b4fed4abdcb53a03df3d02ac3
|
[
"MIT"
] | 1
|
2020-10-01T04:03:44.000Z
|
2020-10-01T04:03:44.000Z
|
t07numberpatterns_cubes.py
|
CherryNoddles/y1math
|
877b87ee60e7569b4fed4abdcb53a03df3d02ac3
|
[
"MIT"
] | 4
|
2019-10-20T03:52:11.000Z
|
2019-10-24T07:13:58.000Z
|
t07numberpatterns_cubes.py
|
CherryNoddles/y1math
|
877b87ee60e7569b4fed4abdcb53a03df3d02ac3
|
[
"MIT"
] | 403
|
2019-10-17T05:30:21.000Z
|
2020-10-28T10:33:07.000Z
|
# Generate cubes number pattern from 1 to 10
# 1 8 27 64 ...
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0
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ebcd0bf64a3c89f902e4e91798b04aca1e4bdee9
| 50
|
py
|
Python
|
utils/__init__.py
|
suhwan-cho/BMVOS
|
1d5e9a30b810375a3479c5e97db5aa0ef5f7bc00
|
[
"MIT"
] | 16
|
2021-10-02T15:59:39.000Z
|
2022-03-17T11:55:15.000Z
|
utils/__init__.py
|
iseunghoon/BMVOS
|
530a77793a286912f891ce8832e1fbeb890c082f
|
[
"MIT"
] | 1
|
2021-10-31T08:28:07.000Z
|
2021-12-01T05:45:55.000Z
|
utils/__init__.py
|
iseunghoon/BMVOS
|
530a77793a286912f891ce8832e1fbeb890c082f
|
[
"MIT"
] | 5
|
2021-11-22T06:57:11.000Z
|
2022-03-25T08:43:55.000Z
|
from .stats import *
from .readsaveimage import *
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|
py34/bacpypes/service/__init__.py
|
amih90/bacpypes
|
27ab4f18aa252ceb6ffdc32d53af2995a2e92647
|
[
"MIT"
] | 240
|
2015-07-17T16:27:54.000Z
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2022-03-29T13:53:06.000Z
|
py34/bacpypes/service/__init__.py
|
amih90/bacpypes
|
27ab4f18aa252ceb6ffdc32d53af2995a2e92647
|
[
"MIT"
] | 400
|
2015-07-23T05:37:52.000Z
|
2022-03-29T12:32:30.000Z
|
py34/bacpypes/service/__init__.py
|
amih90/bacpypes
|
27ab4f18aa252ceb6ffdc32d53af2995a2e92647
|
[
"MIT"
] | 143
|
2015-07-17T18:22:27.000Z
|
2022-03-22T01:21:24.000Z
|
#!/usr/bin/env python
"""
Service Subpackage
"""
from . import test
from . import detect
from . import device
from . import object
from . import cov
from . import file
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0
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696e8c29fd7667288ac62b7c9578e45d374f09e6
| 178
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py
|
Python
|
boosup/boosup/performance/models/__init__.py
|
developertqw2017/migrationDjango
|
f7256ec2af51da1179d2f957e1aa896191b7b514
|
[
"MIT"
] | null | null | null |
boosup/boosup/performance/models/__init__.py
|
developertqw2017/migrationDjango
|
f7256ec2af51da1179d2f957e1aa896191b7b514
|
[
"MIT"
] | 16
|
2020-02-11T23:19:19.000Z
|
2022-03-11T23:33:40.000Z
|
boosup/boosup/performance/models/__init__.py
|
developertqw2017/migrationDjango
|
f7256ec2af51da1179d2f957e1aa896191b7b514
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
#coding=utf8
'''
Created on 2016/9/16
@author: cloudy
'''
from .assessment import *
from .record import *
from .stakeholder import *
from .config import *
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
15e8242f93598192e153b2139ff39e5f88610dfc
| 49
|
py
|
Python
|
enlil/__init__.py
|
EliRibble/enlil
|
cb24a5bd8115ab3d578ef02374a6eac10129f661
|
[
"MIT"
] | null | null | null |
enlil/__init__.py
|
EliRibble/enlil
|
cb24a5bd8115ab3d578ef02374a6eac10129f661
|
[
"MIT"
] | null | null | null |
enlil/__init__.py
|
EliRibble/enlil
|
cb24a5bd8115ab3d578ef02374a6eac10129f661
|
[
"MIT"
] | null | null | null |
from enlil.version import VERSION as __version__
| 24.5
| 48
| 0.857143
| 7
| 49
| 5.428571
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122449
| 49
| 1
| 49
| 49
| 0.883721
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| 1
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| true
| 0
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| 1
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
15f08e1397cee9ebc14346b687af052fdf7e9b55
| 52
|
py
|
Python
|
ifcollector/exceptions.py
|
jgrugru/ifcollector
|
bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4
|
[
"MIT"
] | null | null | null |
ifcollector/exceptions.py
|
jgrugru/ifcollector
|
bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4
|
[
"MIT"
] | null | null | null |
ifcollector/exceptions.py
|
jgrugru/ifcollector
|
bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4
|
[
"MIT"
] | null | null | null |
class CannotEvaluateExpression(Exception):
pass
| 17.333333
| 42
| 0.807692
| 4
| 52
| 10.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134615
| 52
| 2
| 43
| 26
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
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| 0.5
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| 1
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
ba37f59581a0c4d25600a4346d8a88e9ccc085b0
| 225
|
py
|
Python
|
kboard/core/models.py
|
cjh5414/kboard
|
8d68bf0cbdf007e2230494faa6b0940a8e2c7430
|
[
"MIT"
] | null | null | null |
kboard/core/models.py
|
cjh5414/kboard
|
8d68bf0cbdf007e2230494faa6b0940a8e2c7430
|
[
"MIT"
] | null | null | null |
kboard/core/models.py
|
cjh5414/kboard
|
8d68bf0cbdf007e2230494faa6b0940a8e2c7430
|
[
"MIT"
] | null | null | null |
from django.db import models
class TimeStampedModel(models.Model):
created_time = models.DateTimeField(auto_now_add=True)
modified_time = models.DateTimeField(auto_now=True)
class Meta:
abstract = True
| 22.5
| 58
| 0.746667
| 28
| 225
| 5.821429
| 0.642857
| 0.122699
| 0.282209
| 0.331288
| 0.368098
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177778
| 225
| 9
| 59
| 25
| 0.881081
| 0
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| false
| 0
| 0.166667
| 0
| 0.833333
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| 0
| 0
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| 0
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| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
ba8106c873f63ab2d88a2ba43c5a0e4a93059f0f
| 95
|
py
|
Python
|
terrascript/shell/d.py
|
amlodzianowski/python-terrascript
|
1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49
|
[
"BSD-2-Clause"
] | null | null | null |
terrascript/shell/d.py
|
amlodzianowski/python-terrascript
|
1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49
|
[
"BSD-2-Clause"
] | null | null | null |
terrascript/shell/d.py
|
amlodzianowski/python-terrascript
|
1111affe6cd30d9b8b7bc74ae4e27590f7d4dc49
|
[
"BSD-2-Clause"
] | null | null | null |
# terrascript/shell/d.py
import terrascript
class shell_script(terrascript.Data):
pass
| 11.875
| 37
| 0.757895
| 12
| 95
| 5.916667
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 95
| 7
| 38
| 13.571429
| 0.8875
| 0.231579
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
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| 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
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
baa018da7bca75e1d1fa4c76e5b82a0c9bc1095d
| 102
|
py
|
Python
|
zk_cli/zk_cli/ui/__init__.py
|
echoma/think_before_act
|
7b4a5a4755886b81e96c23370196d518c9051487
|
[
"Apache-2.0"
] | null | null | null |
zk_cli/zk_cli/ui/__init__.py
|
echoma/think_before_act
|
7b4a5a4755886b81e96c23370196d518c9051487
|
[
"Apache-2.0"
] | null | null | null |
zk_cli/zk_cli/ui/__init__.py
|
echoma/think_before_act
|
7b4a5a4755886b81e96c23370196d518c9051487
|
[
"Apache-2.0"
] | 1
|
2018-11-24T03:10:37.000Z
|
2018-11-24T03:10:37.000Z
|
#-*- coding: utf-8 -*-
"""
module init
"""
from ui.Tmux import Tmux
from ui.NodeTree import NodeTree
| 12.75
| 32
| 0.666667
| 15
| 102
| 4.533333
| 0.666667
| 0.176471
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011765
| 0.166667
| 102
| 7
| 33
| 14.571429
| 0.788235
| 0.323529
| 0
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| true
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| 0
| 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
bab33a3f8ca274129d9f8c6091c07f5d111b843c
| 160
|
py
|
Python
|
gimmebio/data_manager/gimmebio/data_manager/api.py
|
dcdanko/gimmebio
|
d81d01cd77e7398ae86caeb37ab346e2874e37bb
|
[
"MIT"
] | 3
|
2020-01-21T23:49:55.000Z
|
2020-07-29T17:02:30.000Z
|
gimmebio/data_manager/gimmebio/data_manager/api.py
|
dcdanko/gimmebio
|
d81d01cd77e7398ae86caeb37ab346e2874e37bb
|
[
"MIT"
] | null | null | null |
gimmebio/data_manager/gimmebio/data_manager/api.py
|
dcdanko/gimmebio
|
d81d01cd77e7398ae86caeb37ab346e2874e37bb
|
[
"MIT"
] | 4
|
2020-01-21T16:48:17.000Z
|
2020-03-13T15:34:52.000Z
|
def add_local_file(session, path):
"""Add a file into the database."""
pass
def upload_local_file_to_s3(session, local_file, api_key, remote_path):
| 17.777778
| 71
| 0.725
| 26
| 160
| 4.115385
| 0.653846
| 0.252336
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007519
| 0.16875
| 160
| 8
| 72
| 20
| 0.796992
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.333333
| 0
| null | null | 0
| 1
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| null | 1
| 0
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| 0
| 0
| 0
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| 0
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| 1
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| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
bac991cf6808410b4b44fca2521c6f0645a62511
| 192
|
py
|
Python
|
mak/build_framework/configure/arch/armv7s.py
|
motor-dev/Motor
|
98cb099fe1c2d31e455ed868cc2a25eae51e79f0
|
[
"BSD-3-Clause"
] | 4
|
2015-05-13T16:28:36.000Z
|
2017-05-24T15:34:14.000Z
|
mak/build_framework/configure/arch/armv7s.py
|
motor-dev/Motor
|
98cb099fe1c2d31e455ed868cc2a25eae51e79f0
|
[
"BSD-3-Clause"
] | null | null | null |
mak/build_framework/configure/arch/armv7s.py
|
motor-dev/Motor
|
98cb099fe1c2d31e455ed868cc2a25eae51e79f0
|
[
"BSD-3-Clause"
] | 1
|
2017-03-21T08:28:07.000Z
|
2017-03-21T08:28:07.000Z
|
def configure(conf):
conf.recurse('armv7a.py', once=False)
conf.env.VALID_ARCHITECTURES = ['armv7s'] + conf.env.VALID_ARCHITECTURES
conf.env.append_unique('DEFINES', ['_ARM_V7S'])
| 38.4
| 76
| 0.713542
| 25
| 192
| 5.28
| 0.68
| 0.159091
| 0.181818
| 0.378788
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017751
| 0.119792
| 192
| 4
| 77
| 48
| 0.763314
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 0
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| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0
| 0.25
| 0
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| 0
| null | 0
| 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
baf11338e006796b738889492185812b882f275e
| 128
|
py
|
Python
|
tools/camcal/birdseye.py
|
ParikhKadam/cycloid
|
c5e64e8379f801417a38755eb6b2fde881dabd8c
|
[
"MIT"
] | 156
|
2017-08-12T03:58:21.000Z
|
2022-03-21T13:38:52.000Z
|
tools/camcal/birdseye.py
|
ParikhKadam/cycloid
|
c5e64e8379f801417a38755eb6b2fde881dabd8c
|
[
"MIT"
] | 3
|
2018-12-11T11:31:06.000Z
|
2019-12-05T18:43:51.000Z
|
tools/camcal/birdseye.py
|
ParikhKadam/cycloid
|
c5e64e8379f801417a38755eb6b2fde881dabd8c
|
[
"MIT"
] | 18
|
2017-08-17T02:05:54.000Z
|
2022-02-24T20:54:27.000Z
|
import os
import numpy as np
import cv2
camera_matrix = np.load("camera_matrix.npy")
dist_coeffs = np.load("dist_coeffs.npy")
| 16
| 44
| 0.765625
| 22
| 128
| 4.272727
| 0.545455
| 0.255319
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008929
| 0.125
| 128
| 7
| 45
| 18.285714
| 0.830357
| 0
| 0
| 0
| 0
| 0
| 0.251969
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
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| null | 1
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| 0
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| 0
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| 1
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
79f02c062cf9e82b07780a7ec5f2f5efc30ac935
| 202
|
py
|
Python
|
candle/callbacks/__init__.py
|
ynop/candle
|
1e0687e1f6a9b622033fbd141674d1de964f4465
|
[
"MIT"
] | null | null | null |
candle/callbacks/__init__.py
|
ynop/candle
|
1e0687e1f6a9b622033fbd141674d1de964f4465
|
[
"MIT"
] | null | null | null |
candle/callbacks/__init__.py
|
ynop/candle
|
1e0687e1f6a9b622033fbd141674d1de964f4465
|
[
"MIT"
] | null | null | null |
from .base import Callback
from .base import CallbackHandler
from .log import LoggerCallback
from .adaptive_lr import AdaptiveLearningRateCallback
from .model_checkpoint import ModelCheckpointCallback
| 28.857143
| 53
| 0.871287
| 22
| 202
| 7.909091
| 0.590909
| 0.091954
| 0.16092
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.10396
| 202
| 6
| 54
| 33.666667
| 0.961326
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| true
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
0339bf156c17a2cfa4a82c5a02734bd89a7c2ca0
| 160
|
py
|
Python
|
adet/modeling/SparseDTMInst/__init__.py
|
shuaiqi361/AdelaiDet
|
35d944033a8d2f7aa623ad607b57bd8a1fe88b43
|
[
"BSD-2-Clause"
] | null | null | null |
adet/modeling/SparseDTMInst/__init__.py
|
shuaiqi361/AdelaiDet
|
35d944033a8d2f7aa623ad607b57bd8a1fe88b43
|
[
"BSD-2-Clause"
] | null | null | null |
adet/modeling/SparseDTMInst/__init__.py
|
shuaiqi361/AdelaiDet
|
35d944033a8d2f7aa623ad607b57bd8a1fe88b43
|
[
"BSD-2-Clause"
] | null | null | null |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .SparseDTMInst import DTInst
from .SparseDTMEncode import DistanceTransformEncoding
| 40
| 70
| 0.83125
| 18
| 160
| 7.388889
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.11875
| 160
| 3
| 71
| 53.333333
| 0.943262
| 0.425
| 0
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| 0
| 0
| 0
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| 1
| 0
| true
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| null | 0
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| 0
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| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
036834716578643653268d8df8368c25603357a0
| 30
|
py
|
Python
|
tools/inference_tools/detector/__init__.py
|
JASON7033/HAKE-Action-Torch-Activity2Vec
|
74a70f9d6b286af907c72863ccd25cf0353859bd
|
[
"Apache-2.0"
] | 1
|
2021-10-06T03:04:16.000Z
|
2021-10-06T03:04:16.000Z
|
tools/inference_tools/detector/__init__.py
|
JASON7033/HAKE-Action-Torch-Activity2Vec
|
74a70f9d6b286af907c72863ccd25cf0353859bd
|
[
"Apache-2.0"
] | null | null | null |
tools/inference_tools/detector/__init__.py
|
JASON7033/HAKE-Action-Torch-Activity2Vec
|
74a70f9d6b286af907c72863ccd25cf0353859bd
|
[
"Apache-2.0"
] | null | null | null |
from .apis import get_detector
| 30
| 30
| 0.866667
| 5
| 30
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0.1
| 30
| 1
| 30
| 30
| 0.925926
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
Subsets and Splits
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