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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
fd53a63cf93013e0bd503a85001508728a7fb0df
| 8,311
|
py
|
Python
|
test/test_concurrency.py
|
letmerecall/nameko-grpc
|
4fa602831aac92218fad975a51e4f41f3a34699e
|
[
"Apache-2.0"
] | 44
|
2019-02-28T15:07:11.000Z
|
2021-11-09T07:17:19.000Z
|
test/test_concurrency.py
|
letmerecall/nameko-grpc
|
4fa602831aac92218fad975a51e4f41f3a34699e
|
[
"Apache-2.0"
] | 10
|
2019-06-10T08:56:41.000Z
|
2021-08-04T14:28:54.000Z
|
test/test_concurrency.py
|
letmerecall/nameko-grpc
|
4fa602831aac92218fad975a51e4f41f3a34699e
|
[
"Apache-2.0"
] | 8
|
2019-02-11T16:42:30.000Z
|
2020-07-29T06:46:12.000Z
|
# -*- coding: utf-8 -*-
import json
import random
import string
import pytest
from nameko_grpc.constants import Cardinality
@pytest.mark.equivalence
class TestConcurrency:
def test_unary_unary(self, client, protobufs, instrumented, client_type):
stash_metadata = json.dumps([instrumented.path, Cardinality.UNARY_UNARY.value])
futures = []
for letter in string.ascii_uppercase:
futures.append(
client.unary_unary.future(
protobufs.ExampleRequest(value=letter),
metadata=[("stash", stash_metadata)],
)
)
for index, future in enumerate(futures):
assert future.result().message == string.ascii_uppercase[index]
# verify messages from concurrent requests are interleaved
# there is a 1/26! chance of concurrent requests being handled in order
captured_requests = list(instrumented.requests())
assert len(captured_requests) == 26
assert [req.value for req in captured_requests] != string.ascii_uppercase
def test_unary_stream(self, client, protobufs, instrumented, client_type):
stash_metadata = json.dumps([instrumented.path, Cardinality.UNARY_STREAM.value])
futures = []
for letter in string.ascii_uppercase:
futures.append(
client.unary_stream.future(
protobufs.ExampleRequest(value=letter, response_count=2),
metadata=[("stash", stash_metadata)],
)
)
for index, future in enumerate(futures):
result = list(future.result())
responses = [(response.message, response.seqno) for response in result]
assert responses == [
(string.ascii_uppercase[index], 1),
(string.ascii_uppercase[index], 2),
]
# verify messages from concurrent requests are interleaved
# there is a 1/26! chance of concurrent requests being handled in order
captured_requests = list(instrumented.requests())
assert len(captured_requests) == 26
assert [req.value for req in captured_requests] != string.ascii_uppercase
def test_stream_unary(
self, client, protobufs, instrumented, client_type, server_type
):
stash_metadata = json.dumps([instrumented.path, Cardinality.STREAM_UNARY.value])
def generate_requests(values):
for value in values:
yield protobufs.ExampleRequest(value=value)
futures = []
for index in range(26):
if index % 2 == 0:
values = string.ascii_uppercase
else:
values = string.ascii_lowercase
futures.append(
client.stream_unary.future(
generate_requests(values), metadata=[("stash", stash_metadata)]
)
)
for index, future in enumerate(futures):
if index % 2 == 0:
assert future.result().message == ",".join(string.ascii_uppercase)
else:
assert future.result().message == ",".join(string.ascii_lowercase)
# verify messages from concurrent requests are interleaved
# there is a 1/626! chance of concurrent requests being handled in order,
# just check the first 26.
captured_requests = list(instrumented.requests())
assert len(captured_requests) == 26 * 26
assert [req.value for req in captured_requests[:26]] != string.ascii_uppercase
def test_stream_stream(self, client, protobufs, instrumented, client_type):
stash_metadata = json.dumps(
[instrumented.path, Cardinality.STREAM_STREAM.value]
)
def generate_requests(values):
for value in values:
yield protobufs.ExampleRequest(value=value)
futures = []
for index in range(26):
if index % 2 == 0:
values = string.ascii_uppercase
else:
values = string.ascii_lowercase
futures.append(
client.stream_stream.future(
generate_requests(values), metadata=[("stash", stash_metadata)]
)
)
for index, future in enumerate(futures):
result = list(future.result())
responses = [(response.seqno, response.message) for response in result]
if index % 2 == 0:
expected = list(enumerate(string.ascii_uppercase, 1))
else:
expected = list(enumerate(string.ascii_lowercase, 1))
assert responses == expected
# verify messages from concurrent requests are interleaved
# there is a 1/626! chance of concurrent requests being handled in order,
# just check the first 26.
captured_requests = list(instrumented.requests())
assert len(captured_requests) == 26 * 26
assert [req.value for req in captured_requests[:26]] != string.ascii_uppercase
@pytest.mark.equivalence
class TestMultipleClients:
def test_unary_unary(self, start_client, server, protobufs):
futures = []
number_of_clients = 5
for index in range(number_of_clients):
client = start_client("example")
response_future = client.unary_unary.future(
protobufs.ExampleRequest(value=string.ascii_uppercase[index])
)
futures.append(response_future)
for index, future in enumerate(futures):
response = future.result()
assert response.message == string.ascii_uppercase[index]
def test_unary_stream(self, start_client, server, protobufs):
futures = []
number_of_clients = 5
for index in range(number_of_clients):
client = start_client("example")
responses_future = client.unary_stream.future(
protobufs.ExampleRequest(
value=string.ascii_uppercase[index], response_count=2
)
)
futures.append(responses_future)
for index, future in enumerate(futures):
responses = future.result()
assert [(response.message, response.seqno) for response in responses] == [
(string.ascii_uppercase[index], 1),
(string.ascii_uppercase[index], 2),
]
def test_stream_unary(self, start_client, server, protobufs):
number_of_clients = 5
def shuffled(string):
chars = list(string)
random.shuffle(chars)
return chars
streams = [shuffled(string.ascii_uppercase) for _ in range(number_of_clients)]
def generate_requests(values):
for value in values:
yield protobufs.ExampleRequest(value=value)
futures = []
for index in range(number_of_clients):
client = start_client("example")
response_future = client.stream_unary.future(
generate_requests(streams[index])
)
futures.append(response_future)
for index, future in enumerate(futures):
response = future.result()
assert response.message == ",".join(streams[index])
def test_stream_stream(self, start_client, server, protobufs):
number_of_clients = 5
def shuffled(string):
chars = list(string)
random.shuffle(chars)
return chars
streams = [shuffled(string.ascii_uppercase) for _ in range(number_of_clients)]
def generate_requests(values):
for value in values:
yield protobufs.ExampleRequest(value=value)
futures = []
for index in range(number_of_clients):
client = start_client("example")
responses_future = client.stream_stream.future(
generate_requests(streams[index])
)
futures.append(responses_future)
for index, future in enumerate(futures):
responses = future.result()
received = [(response.seqno, response.message) for response in responses]
assert received == list(enumerate(streams[index], 1))
| 35.823276
| 88
| 0.606305
| 854
| 8,311
| 5.752927
| 0.114754
| 0.053735
| 0.081417
| 0.026053
| 0.911663
| 0.869733
| 0.854468
| 0.764502
| 0.741502
| 0.728272
| 0
| 0.010438
| 0.308386
| 8,311
| 231
| 89
| 35.978355
| 0.844294
| 0.070148
| 0
| 0.615385
| 0
| 0
| 0.00661
| 0
| 0
| 0
| 0
| 0
| 0.100592
| 1
| 0.08284
| false
| 0
| 0.029586
| 0
| 0.136095
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
b5be4664acc346d4e0bb4a39a86eccf9704d1e20
| 426
|
py
|
Python
|
babylog/symbols.py
|
pawelnalezyty/babylog
|
1c06be7e72171f0283d15fb6b9ef95524b3f3d73
|
[
"Apache-2.0"
] | null | null | null |
babylog/symbols.py
|
pawelnalezyty/babylog
|
1c06be7e72171f0283d15fb6b9ef95524b3f3d73
|
[
"Apache-2.0"
] | null | null | null |
babylog/symbols.py
|
pawelnalezyty/babylog
|
1c06be7e72171f0283d15fb6b9ef95524b3f3d73
|
[
"Apache-2.0"
] | null | null | null |
class Symbol:
def __init__(self, name):
self.name = name
def __hash__(self):
return hash(self.name)
def __eq__(self, other):
return self.name == other.name
class SymbolTable:
def __init__(self):
self._symbol_table = dict()
def put_symbol(self, symbol):
self._symbol_table[symbol] = 1
def get_symbol(self, symbol):
return self._symbol_table[symbol]
| 20.285714
| 41
| 0.626761
| 54
| 426
| 4.5
| 0.296296
| 0.205761
| 0.185185
| 0.17284
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003215
| 0.269953
| 426
| 20
| 42
| 21.3
| 0.778135
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| false
| 0
| 0
| 0.214286
| 0.785714
| 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
| 1
| 0
|
0
| 6
|
bd42ded419fc29bd2ae01ec1ddbfe955990fa651
| 76
|
py
|
Python
|
data_process.py
|
EricSchles/RNN-data-gen
|
02cc59c8c44fffe375f7c51e1cf8f48811f6cc2f
|
[
"MIT"
] | 1
|
2019-04-22T16:47:05.000Z
|
2019-04-22T16:47:05.000Z
|
data_process.py
|
afcarl/RNN-data-gen
|
02cc59c8c44fffe375f7c51e1cf8f48811f6cc2f
|
[
"MIT"
] | null | null | null |
data_process.py
|
afcarl/RNN-data-gen
|
02cc59c8c44fffe375f7c51e1cf8f48811f6cc2f
|
[
"MIT"
] | 1
|
2018-08-12T15:16:11.000Z
|
2018-08-12T15:16:11.000Z
|
import numpy, os
def load_data(filepath):
return numpy.load(filepath);
| 15.2
| 32
| 0.736842
| 11
| 76
| 5
| 0.727273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 76
| 4
| 33
| 19
| 0.859375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
1fb518fe747d5ff2a77a673f0eaa635cd6bb899e
| 39
|
py
|
Python
|
kivymd/uix/templates/rotatewidget/__init__.py
|
marvelous-benji/KivyMD
|
4ab8dd339902597eaa9f8a4f9a80d8a6eb7d6053
|
[
"MIT"
] | 1,111
|
2015-07-15T02:31:09.000Z
|
2022-03-29T17:22:02.000Z
|
kivymd/uix/templates/rotatewidget/__init__.py
|
marvelous-benji/KivyMD
|
4ab8dd339902597eaa9f8a4f9a80d8a6eb7d6053
|
[
"MIT"
] | 706
|
2015-06-10T22:24:13.000Z
|
2022-03-31T16:22:39.000Z
|
kivymd/uix/templates/rotatewidget/__init__.py
|
marvelous-benji/KivyMD
|
4ab8dd339902597eaa9f8a4f9a80d8a6eb7d6053
|
[
"MIT"
] | 561
|
2015-07-15T04:57:23.000Z
|
2022-03-31T17:14:31.000Z
|
from .rotatewidget import RotateWidget
| 19.5
| 38
| 0.871795
| 4
| 39
| 8.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.971429
| 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
| 1
| 0
|
0
| 6
|
9529aef052605ccc46997c203a0cc21b3e9770a2
| 42
|
py
|
Python
|
polypheny/avatica/__init__.py
|
polypheny/Polypheny-Connector-Python
|
7425eb01d76209783898a01b7a75e3923e911e67
|
[
"Apache-2.0"
] | 3
|
2021-10-31T17:34:47.000Z
|
2021-11-01T13:31:11.000Z
|
polypheny/avatica/__init__.py
|
polypheny/Polypheny-Connector-Python
|
7425eb01d76209783898a01b7a75e3923e911e67
|
[
"Apache-2.0"
] | null | null | null |
polypheny/avatica/__init__.py
|
polypheny/Polypheny-Connector-Python
|
7425eb01d76209783898a01b7a75e3923e911e67
|
[
"Apache-2.0"
] | null | null | null |
from .client import PolyphenyAvaticaClient
| 42
| 42
| 0.904762
| 4
| 42
| 9.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 42
| 1
| 42
| 42
| 0.974359
| 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
| 1
| 0
|
0
| 6
|
1f0101cf51f54d6124c02a5f486412443db701c7
| 198
|
py
|
Python
|
fusion/task/linear_evaluation/__init__.py
|
Mrinal18/fusion
|
34e563f2e50139385577c3880c5de11f8a73f220
|
[
"BSD-3-Clause"
] | 14
|
2021-04-05T01:25:12.000Z
|
2022-02-17T19:44:28.000Z
|
fusion/task/linear_evaluation/__init__.py
|
Mrinal18/fusion
|
34e563f2e50139385577c3880c5de11f8a73f220
|
[
"BSD-3-Clause"
] | 1
|
2021-07-05T08:32:49.000Z
|
2021-07-05T12:34:57.000Z
|
fusion/task/linear_evaluation/__init__.py
|
Mrinal18/fusion
|
34e563f2e50139385577c3880c5de11f8a73f220
|
[
"BSD-3-Clause"
] | 1
|
2022-02-01T21:56:11.000Z
|
2022-02-01T21:56:11.000Z
|
from .linear_evaluation_task import LinearEvaluationTask
from .linear_evaluation_task import LinearEvaluationTaskBuilder
__all__ = [
'LinearEvaluationTask',
'LinearEvaluationTaskBuilder'
]
| 24.75
| 63
| 0.833333
| 15
| 198
| 10.466667
| 0.533333
| 0.127389
| 0.254777
| 0.305732
| 0.382166
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116162
| 198
| 7
| 64
| 28.285714
| 0.897143
| 0
| 0
| 0
| 0
| 0
| 0.237374
| 0.136364
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
1f1097d645c6892c1989a0b4ec040542b79d040a
| 35
|
py
|
Python
|
flaskr/viewmodels/__init__.py
|
tuhinpaul/flask-sample-project
|
fb4cae2d00b7c1e1318f44e477f71ed93ecaed52
|
[
"MIT"
] | null | null | null |
flaskr/viewmodels/__init__.py
|
tuhinpaul/flask-sample-project
|
fb4cae2d00b7c1e1318f44e477f71ed93ecaed52
|
[
"MIT"
] | null | null | null |
flaskr/viewmodels/__init__.py
|
tuhinpaul/flask-sample-project
|
fb4cae2d00b7c1e1318f44e477f71ed93ecaed52
|
[
"MIT"
] | null | null | null |
from .login_form import LoginForm;
| 17.5
| 34
| 0.828571
| 5
| 35
| 5.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 35
| 1
| 35
| 35
| 0.903226
| 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
| 1
| 0
|
0
| 6
|
1f16282f284cdfba08dd91172e3b75867f8a6f15
| 7,389
|
py
|
Python
|
integrations/sparse/test_prebuilt_msmarco_v1_doc.py
|
manveertamber/pyserini
|
9e1b2fca21540f027827631ac6de3432d9f4b4f6
|
[
"Apache-2.0"
] | null | null | null |
integrations/sparse/test_prebuilt_msmarco_v1_doc.py
|
manveertamber/pyserini
|
9e1b2fca21540f027827631ac6de3432d9f4b4f6
|
[
"Apache-2.0"
] | null | null | null |
integrations/sparse/test_prebuilt_msmarco_v1_doc.py
|
manveertamber/pyserini
|
9e1b2fca21540f027827631ac6de3432d9f4b4f6
|
[
"Apache-2.0"
] | null | null | null |
#
# Pyserini: Reproducible IR research with sparse and dense representations
#
# 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
#
# http://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.
#
"""Integration tests for MS MARCO V1 doc corpora (full and segmented) using pre-built indexes."""
import unittest
from integrations.utils import run_retrieval_and_return_scores
class TestPrebuiltMsMarcoV1Doc(unittest.TestCase):
#
# doc "full" conditions
#
def test_doc_full_trec_output(self):
"""Test case for MS MARCO V1 doc (full), dev queries, TREC output
on all three pre-built indexes (base, slim, full)."""
# Loop over all three pre-built indexes.
for index in ['msmarco-v1-doc', 'msmarco-v1-doc-slim', 'msmarco-v1-doc-full']:
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc.trec.txt',
f'python -m pyserini.search.lucene --topics msmarco-doc-dev --index {index} --bm25 --hits 1000',
'msmarco-doc-dev',
'trec_eval',
[['map', 'map'], ['recall.1000', 'recall_1000']])
self.assertTrue('map' in scores)
self.assertTrue('recall.1000' in scores)
self.assertAlmostEqual(scores['map'], 0.2774, delta=0.0001)
self.assertAlmostEqual(scores['recall.1000'], 0.9357, delta=0.0001)
def test_doc_full_msmarco_output(self):
"""Test case for MS MARCO V1 doc (full), dev queries, MS MARCO output
on all three pre-built indexes (base, slim, full)."""
# Loop over all three pre-built indexes.
for index in ['msmarco-v1-doc', 'msmarco-v1-doc-slim', 'msmarco-v1-doc-full']:
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc.msmarco.txt',
f'python -m pyserini.search.lucene --topics msmarco-doc-dev --index {index} --bm25 --hits 100 --output-format msmarco',
'msmarco-doc-dev',
'msmarco_doc_string', [])
self.assertTrue('MRR@100' in scores)
self.assertEqual(scores['MRR@100'], '0.2766351807440808')
#
# doc segmented conditions
#
def test_doc_segmented_trec_output(self):
"""Test case for MS MARCO V1 doc segmented, dev queries, TREC output
on all three pre-built indexes (base, slim, full)."""
# Loop over all three pre-built indexes.
for index in ['msmarco-v1-doc-segmented', 'msmarco-v1-doc-segmented-slim', 'msmarco-v1-doc-segmented-full']:
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc-segmented.trec.txt',
f'python -m pyserini.search.lucene --topics msmarco-doc-dev --index {index} --bm25 --hits 10000 --max-passage --max-passage-hits 1000',
'msmarco-doc-dev',
'trec_eval',
[['map', 'map'], ['recall.1000', 'recall_1000']])
self.assertTrue('map' in scores)
self.assertTrue('recall.1000' in scores)
self.assertAlmostEqual(scores['map'], 0.2762, delta=0.0001)
self.assertAlmostEqual(scores['recall.1000'], 0.9311, delta=0.0001)
def test_doc_segmented_msmarco_output(self):
"""Test case for MS MARCO V1 doc segmented, dev queries, MS MARCO output
on all three pre-built indexes (base, slim, full)."""
# Loop over all three pre-built indexes.
for index in ['msmarco-v1-doc-segmented', 'msmarco-v1-doc-segmented-slim', 'msmarco-v1-doc-segmented-full']:
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc-segmented.msmarco.txt',
f'python -m pyserini.search.lucene --topics msmarco-doc-dev --index {index} --bm25 --hits 1000 --max-passage --max-passage-hits 100 --output-format msmarco',
'msmarco-doc-dev',
'msmarco_doc_string', [])
self.assertTrue('MRR@100' in scores)
self.assertEqual(scores['MRR@100'], '0.2755196341768384')
#
# doc2query conditions
#
def test_doc_full_expanded_trec_output(self):
"""Test case for MS MARCO V1 doc (full) + doc2query-T5 expansions, dev queries, TREC output."""
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc.expanded.trec.txt',
'python -m pyserini.search.lucene --topics msmarco-doc-dev --index msmarco-v1-doc-d2q-t5 --bm25 --hits 1000',
'msmarco-doc-dev',
'trec_eval',
[['map', 'map'], ['recall.1000', 'recall_1000']])
self.assertTrue('map' in scores)
self.assertTrue('recall.1000' in scores)
self.assertAlmostEqual(scores['map'], 0.3273, delta=0.0001)
self.assertAlmostEqual(scores['recall.1000'], 0.9553, delta=0.0001)
def test_doc_full_expanded_msmarco_output(self):
"""Test case for MS MARCO V1 doc (full) + doc2query-T5 expansions, dev queries, MS MARCO output."""
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc.expanded.msmarco.txt',
'python -m pyserini.search.lucene --topics msmarco-doc-dev --index msmarco-v1-doc-d2q-t5 --bm25 --hits 100 --output-format msmarco',
'msmarco-doc-dev',
'msmarco_doc_string', [])
self.assertTrue('MRR@100' in scores)
self.assertEqual(scores['MRR@100'], '0.3268656233100833')
def test_doc_segmented_expanded_trec_output(self):
"""Test case for MS MARCO V1 doc segmented + doc2query-T5 expansions, dev queries, TREC output."""
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc-segmented.expanded.trec.txt',
'python -m pyserini.search.lucene --topics msmarco-doc-dev --index msmarco-v1-doc-segmented-d2q-t5 --bm25 --hits 10000 --max-passage --max-passage-hits 1000',
'msmarco-doc-dev',
'trec_eval',
[['map', 'map'], ['recall.1000', 'recall_1000']])
self.assertTrue('map' in scores)
self.assertTrue('recall.1000' in scores)
self.assertAlmostEqual(scores['map'], 0.3213, delta=0.0001)
self.assertAlmostEqual(scores['recall.1000'], 0.9530, delta=0.0001)
def test_doc_segmented_expanded_msmarco_output(self):
"""Test case for MS MARCO V1 doc segmented + doc2query-T5 expansions, dev queries, MS MARCO output."""
scores = run_retrieval_and_return_scores(
'runs/test_run.msmarco-doc-segmented.expanded.msmarco.txt',
'python -m pyserini.search.lucene --topics msmarco-doc-dev --index msmarco-v1-doc-segmented-d2q-t5 --bm25 --hits 1000 --max-passage --max-passage-hits 100 --output-format msmarco',
'msmarco-doc-dev',
'msmarco_doc_string', [])
self.assertTrue('MRR@100' in scores)
self.assertEqual(scores['MRR@100'], '0.320918438140918')
if __name__ == '__main__':
unittest.main()
| 47.063694
| 192
| 0.642441
| 958
| 7,389
| 4.846555
| 0.159708
| 0.060306
| 0.041353
| 0.023261
| 0.828128
| 0.804652
| 0.804652
| 0.781822
| 0.781822
| 0.74047
| 0
| 0.060383
| 0.228989
| 7,389
| 156
| 193
| 47.365385
| 0.754608
| 0.236974
| 0
| 0.517647
| 0
| 0.094118
| 0.411701
| 0.145626
| 0
| 0
| 0
| 0
| 0.282353
| 1
| 0.094118
| false
| 0.047059
| 0.023529
| 0
| 0.129412
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
1f43a9860fd93fcaf9d9f71af04224e0641901d4
| 41
|
py
|
Python
|
wk2_ex1.py
|
jascott1962/python
|
623a0f11f8a44d3ffaeb649cd36a829f75d8a2bb
|
[
"Apache-2.0"
] | null | null | null |
wk2_ex1.py
|
jascott1962/python
|
623a0f11f8a44d3ffaeb649cd36a829f75d8a2bb
|
[
"Apache-2.0"
] | null | null | null |
wk2_ex1.py
|
jascott1962/python
|
623a0f11f8a44d3ffaeb649cd36a829f75d8a2bb
|
[
"Apache-2.0"
] | null | null | null |
import wk2_scotty
wk2_scotty.say_hello()
| 13.666667
| 22
| 0.853659
| 7
| 41
| 4.571429
| 0.714286
| 0.5625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.073171
| 41
| 2
| 23
| 20.5
| 0.789474
| 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 | 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
| 1
| 0
| 0
| 0
|
0
| 6
|
2f0eb026985f1b567f8743f216e21738a620556d
| 73
|
py
|
Python
|
data/micro-benchmark/parameters/imported_call/main.py
|
vitsalis/pycg-evaluation
|
ce37eb5668465b0c17371914e863d699826447ee
|
[
"Apache-2.0"
] | 121
|
2020-12-16T20:31:37.000Z
|
2022-03-21T20:32:43.000Z
|
data/micro-benchmark/parameters/imported_call/main.py
|
vitsalis/pycg-evaluation
|
ce37eb5668465b0c17371914e863d699826447ee
|
[
"Apache-2.0"
] | 24
|
2021-03-13T00:04:00.000Z
|
2022-03-21T17:28:11.000Z
|
data/micro-benchmark/parameters/imported_call/main.py
|
vitsalis/pycg-evaluation
|
ce37eb5668465b0c17371914e863d699826447ee
|
[
"Apache-2.0"
] | 19
|
2021-03-23T10:58:47.000Z
|
2022-03-24T19:46:50.000Z
|
from to_import import func
def param_func():
pass
func(param_func)
| 10.428571
| 26
| 0.739726
| 12
| 73
| 4.25
| 0.583333
| 0.352941
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.191781
| 73
| 6
| 27
| 12.166667
| 0.864407
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0.25
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
2f0f8e92095fe3ff03e3a77f7931352a1cda91f4
| 7,754
|
py
|
Python
|
utils/core_seg.py
|
chiutaiyin/Iterative-feature-transformation-for-style-transfer
|
9eab3e2b8b33a000db09906bac6a8659ec9a628b
|
[
"MIT"
] | 5
|
2020-08-24T10:17:09.000Z
|
2021-01-14T02:25:24.000Z
|
utils/core_seg.py
|
chiutaiyin/Iterative-feature-transformation-for-style-transfer
|
9eab3e2b8b33a000db09906bac6a8659ec9a628b
|
[
"MIT"
] | 1
|
2020-10-12T05:43:45.000Z
|
2020-10-12T05:43:45.000Z
|
utils/core_seg.py
|
chiutaiyin/Iterative-feature-transformation-for-style-transfer
|
9eab3e2b8b33a000db09906bac6a8659ec9a628b
|
[
"MIT"
] | 2
|
2020-12-07T09:17:46.000Z
|
2021-01-10T09:14:06.000Z
|
import tensorflow as tf
import numpy as np
from utils.aux import *
# shape of feat = (HW, C)
def stylize_zca(c_feat, s_feat, c_seg_label_idx, s_seg_label_idx):
feat = c_feat
for i in range(len(c_seg_label_idx)):
cl = c_seg_label_idx[i]
sl = s_seg_label_idx[i]
f = tf.boolean_mask(c_feat, cl, axis=0)
sf = tf.boolean_mask(s_feat, sl, axis=0)
m_c = tf.reduce_mean(f, axis=0, keepdims=True)
m_s = tf.reduce_mean(sf, axis=0, keepdims=True)
f = f - m_c
sf = sf - m_s
c_cov = tf.matmul(f, f, transpose_a=True) / f.shape[0]
s_cov = tf.matmul(sf, sf, transpose_a=True) / sf.shape[0]
inv_sqrt_c_cov = inv_sqrt_cov(c_cov, True)
opt = tf.matmul(inv_sqrt_c_cov, inv_sqrt_cov(s_cov))
f = tf.matmul(f, opt) + m_s
cl = tf.where(cl)
feat = tf.tensor_scatter_nd_update(feat, cl, f)
return feat
def stylize_ot(c_feat, s_feat, c_seg_label_idx, s_seg_label_idx):
feat = c_feat
for i in range(len(c_seg_label_idx)):
cl = c_seg_label_idx[i]
sl = s_seg_label_idx[i]
f = tf.boolean_mask(c_feat, cl, axis=0)
sf = tf.boolean_mask(s_feat, sl, axis=0)
m_c = tf.reduce_mean(f, axis=0, keepdims=True)
m_s = tf.reduce_mean(sf, axis=0, keepdims=True)
f = f - m_c
sf = sf - m_s
c_cov = tf.matmul(f, f, transpose_a=True) / f.shape[0]
s_cov = tf.matmul(sf, sf, transpose_a=True) / sf.shape[0]
sqrt_c_cov = inv_sqrt_cov(c_cov)
inv_sqrt_c_cov = inv_sqrt_cov(c_cov, True)
opt = inv_sqrt_cov(tf.matmul(sqrt_c_cov, tf.matmul(s_cov, sqrt_c_cov)))
opt = tf.matmul(inv_sqrt_c_cov, tf.matmul(opt, inv_sqrt_c_cov))
f = tf.matmul(f, opt) + m_s
cl = tf.where(cl)
feat = tf.tensor_scatter_nd_update(feat, cl, f)
return feat
def stylize_adain(c_feat, s_feat, c_seg_label_idx, s_seg_label_idx):
feat = c_feat
for i in range(len(c_seg_label_idx)):
cl = c_seg_label_idx[i]
sl = s_seg_label_idx[i]
f = tf.boolean_mask(c_feat, cl, axis=0)
sf = tf.boolean_mask(s_feat, sl, axis=0)
m_c = tf.reduce_mean(f, axis=0, keepdims=True)
m_s = tf.reduce_mean(sf, axis=0, keepdims=True)
f = f - m_c
sf = sf - m_s
s_c = tf.sqrt(tf.reduce_mean(f * f, axis=0, keepdims=True) + 1e-8)
s_s = tf.sqrt(tf.reduce_mean(sf * sf, axis=0, keepdims=True) + 1e-8)
white_c_feat = f / s_c
f = white_c_feat * s_s + m_s
cl = tf.where(cl)
feat = tf.tensor_scatter_nd_update(feat, cl, f)
return feat
def stylize_iter(c_feat, s_feat, c_seg_label_idx, s_seg_label_idx, lr=0.01, lamb=1e2, n_iter=20):
FsFsT = []
for i in range(len(c_seg_label_idx)):
sl = s_seg_label_idx[i]
sf = tf.boolean_mask(s_feat, sl, axis=0)
FsFsT.append(tf.matmul(sf, sf, transpose_a=True) / sf.shape[0])
feat = c_feat
for _ in range(n_iter):
grad = 2 * (feat - c_feat)
for i in range(len(c_seg_label_idx)):
cl = c_seg_label_idx[i]
f = tf.boolean_mask(feat, cl, axis=0)
FsFsT_ = FsFsT[i]
grad_ = tf.boolean_mask(grad, cl, axis=0)
upd = 4 * lamb / feat.shape[0] * tf.matmul(f, (tf.matmul(f, f, transpose_a=True) / f.shape[0] - FsFsT_))
cl = tf.where(cl)
feat = tf.tensor_scatter_nd_update(feat, cl, f - lr * (grad_ + upd))
return feat
###= ==================================================== under test ========================================= ###
def whiten_zca(c_feat):
m_c = tf.reduce_mean(c_feat, axis=0, keepdims=True)
c_feat = c_feat - m_c
c_cov = tf.matmul(c_feat, c_feat, transpose_a=True) / c_feat.shape[0]
inv_sqrt_c_cov = inv_sqrt_cov(c_cov, True)
f = tf.matmul(c_feat, inv_sqrt_c_cov) + m_c
return f
def whiten_in(c_feat):
m_c = tf.reduce_mean(c_feat, axis=0, keepdims=True)
c_feat = c_feat - m_c
s_c = tf.sqrt(tf.reduce_mean(c_feat * c_feat, axis=0, keepdims=True) + 1e-8)
f = c_feat / s_c + m_c
return f
def whiten_line(c_feat, lamb=1e4, n_iter=3):
FsFsT = tf.eye(c_feat.shape[-1])
feat = c_feat
n = c_feat.shape[0]
for _ in range(n_iter):
cov_diff = tf.matmul(feat, feat, transpose_a=True) / n - FsFsT
grad = 2 * (feat - c_feat) + 4 * lamb / n * tf.matmul(feat, cov_diff)
DD_T = tf.matmul(grad, grad, transpose_a=True)
DF_T = tf.matmul(grad, feat, transpose_a=True)
a = 2 * lamb / (n * n) * tf.reduce_mean(DD_T * DD_T, keepdims=True)
b = -6 * lamb / (n * n) * tf.reduce_mean(DF_T * DD_T, keepdims=True)
tmp1 = tf.linalg.trace(DD_T) / c_feat.shape[1] / c_feat.shape[1]
tmp2 = 2 * lamb / (n * n) * (tf.reduce_mean(DF_T * DF_T) +
tf.reduce_mean(DF_T * tf.transpose(DF_T)))
tmp3 = 2 * lamb / n * tf.reduce_mean(DD_T * cov_diff)
c = tf.reshape(tmp1 + tmp2 + tmp3, [1,1])
d = tf.reshape(-0.5 * tmp1, [1,1])
# scaling to avoid overflow
abcd = tf.concat([a,b,c,d], axis=-1)
scale = tf.reduce_max(abcd, axis=-1, keepdims=True)
abcd = abcd / scale
eta = eta_selection(cubic_solver(abcd[:,0:1], abcd[:,1:2], abcd[:,2:3], abcd[:,3:]))
feat = feat - eta * grad
return feat
###= ==================================================== under test ========================================= ###
def stylize_line(c_feat, s_feat, c_seg_label_idx, s_seg_label_idx, lr=None, lamb=1e2, n_iter=1):
FsFsT = []
for i in range(len(c_seg_label_idx)):
sl = s_seg_label_idx[i]
sf = tf.boolean_mask(s_feat, sl, axis=0)
FsFsT.append(tf.matmul(sf, sf, transpose_a=True) / sf.shape[0])
feat = c_feat
n = c_feat.shape[0]
for _ in range(n_iter):
grad_all = tf.zeros_like(feat)
a, b, c, d = 0, 0, 0, 0
for i in range(len(c_seg_label_idx)):
cl = c_seg_label_idx[i]
cf = tf.boolean_mask(c_feat, cl, axis=0)
f = tf.boolean_mask(feat, cl, axis=0)
cov_diff = tf.matmul(f, f, transpose_a=True) / f.shape[0] - FsFsT[i]
grad = 2 * (f - cf) + 4 * lamb / n * tf.matmul(f, cov_diff)
grad_all = tf.tensor_scatter_nd_update(grad_all, tf.where(cl), grad)
DD_T = tf.matmul(grad, grad, transpose_a=True)
DF_T = tf.matmul(grad, f, transpose_a=True)
a += 2 * lamb / (n * f.shape[0]) * tf.reduce_mean(DD_T * DD_T, keepdims=True)
b += -6 * lamb / (n * f.shape[0]) * tf.reduce_mean(DF_T * DD_T, keepdims=True)
tmp1 = tf.linalg.trace(DD_T) / c_feat.shape[1] / c_feat.shape[1]
tmp2 = 2 * lamb / (n * f.shape[0]) * (tf.reduce_mean(DF_T * DF_T) +
tf.reduce_mean(DF_T * tf.transpose(DF_T)))
tmp3 = 2 * lamb / n * tf.reduce_mean(DD_T * cov_diff)
c += tf.reshape(tmp1 + tmp2 + tmp3, [1,1])
d += tf.reshape(-0.5 * tmp1, [1,1])
# scaling to avoid overflow
abcd = tf.concat([a,b,c,d], axis=-1)
scale = tf.reduce_max(abcd, axis=-1, keepdims=True)
abcd = abcd / scale
eta = eta_selection(cubic_solver(abcd[:,0:1], abcd[:,1:2], abcd[:,2:3], abcd[:,3:]))
feat = feat - eta * grad_all
# print([abcd[:,0:1], abcd[:,1:2], abcd[:,2:3], abcd[:,3:]])
# print(eta)
return feat
stylize_seg_opt = {'zca': stylize_zca, 'ot': stylize_ot, 'adain': stylize_adain, 'iter': stylize_iter, 'line': stylize_line}
| 42.141304
| 124
| 0.556616
| 1,310
| 7,754
| 3.032824
| 0.083969
| 0.052857
| 0.074755
| 0.051347
| 0.833879
| 0.793607
| 0.762396
| 0.730179
| 0.705261
| 0.701988
| 0
| 0.023536
| 0.282177
| 7,754
| 184
| 124
| 42.141304
| 0.690262
| 0.04862
| 0
| 0.653333
| 0
| 0
| 0.002446
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.053333
| false
| 0
| 0.02
| 0
| 0.126667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
2f63162ac5b003faff31879c16e633f880318f9a
| 28
|
py
|
Python
|
flex_version/__init__.py
|
caesar0301/FlexVersion
|
c9414d5ed4185a96a8c69e39fdcd391f8ae59f5f
|
[
"Apache-2.0"
] | 5
|
2018-05-19T07:48:05.000Z
|
2020-05-23T19:41:42.000Z
|
flex_version/__init__.py
|
caesar0301/FlexVersion
|
c9414d5ed4185a96a8c69e39fdcd391f8ae59f5f
|
[
"Apache-2.0"
] | null | null | null |
flex_version/__init__.py
|
caesar0301/FlexVersion
|
c9414d5ed4185a96a8c69e39fdcd391f8ae59f5f
|
[
"Apache-2.0"
] | 2
|
2018-09-04T03:40:24.000Z
|
2019-10-07T13:32:33.000Z
|
from .flex_version import *
| 14
| 27
| 0.785714
| 4
| 28
| 5.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 28
| 1
| 28
| 28
| 0.875
| 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
| 1
| 0
|
0
| 6
|
2fa0475a4ecffb3182ad08e5ba91610c881fcfb6
| 119
|
py
|
Python
|
src/__init__.py
|
helenapoleri/reinforcement-filesystem
|
3fb839c07563384adba4abdd0fec61ebf76a2530
|
[
"BSD-2-Clause"
] | null | null | null |
src/__init__.py
|
helenapoleri/reinforcement-filesystem
|
3fb839c07563384adba4abdd0fec61ebf76a2530
|
[
"BSD-2-Clause"
] | null | null | null |
src/__init__.py
|
helenapoleri/reinforcement-filesystem
|
3fb839c07563384adba4abdd0fec61ebf76a2530
|
[
"BSD-2-Clause"
] | null | null | null |
#!/usr/bin/python3
# ------------------------------------------------------------------------------
from src import *
| 23.8
| 80
| 0.218487
| 6
| 119
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009009
| 0.067227
| 119
| 4
| 81
| 29.75
| 0.225225
| 0.806723
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
c822355391dd04a2dd0f69ef9d95b9eb1eb78224
| 5,167
|
py
|
Python
|
canaa/catalog/migrations/0001_initial.py
|
klebercode/canaa
|
9317c2220f64791443120e5aa9e36224dc0c36c9
|
[
"MIT"
] | null | null | null |
canaa/catalog/migrations/0001_initial.py
|
klebercode/canaa
|
9317c2220f64791443120e5aa9e36224dc0c36c9
|
[
"MIT"
] | null | null | null |
canaa/catalog/migrations/0001_initial.py
|
klebercode/canaa
|
9317c2220f64791443120e5aa9e36224dc0c36c9
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from south.utils import datetime_utils as datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
pass
# # Adding model 'ProductGroup'
# db.create_table(u'catalog_productgroup', (
# (u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
# ('name', self.gf('django.db.models.fields.CharField')(max_length=50)),
# ('slug', self.gf('django.db.models.fields.SlugField')(unique=True, max_length=50)),
# ('description', self.gf('django.db.models.fields.CharField')(max_length=125)),
# ('image', self.gf('sorl.thumbnail.fields.ImageField')(max_length=100)),
# ('visible', self.gf('django.db.models.fields.BooleanField')(default=True)),
# ))
# db.send_create_signal(u'catalog', ['ProductGroup'])
# # Adding model 'Product'
# db.create_table(u'catalog_product', (
# (u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
# ('product_group', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['catalog.ProductGroup'])),
# ('name', self.gf('django.db.models.fields.CharField')(max_length=120)),
# ('slug', self.gf('django.db.models.fields.SlugField')(unique=True, max_length=50)),
# ('description', self.gf('django.db.models.fields.TextField')(max_length=250)),
# ('image', self.gf('sorl.thumbnail.fields.ImageField')(max_length=100)),
# ('visible', self.gf('django.db.models.fields.BooleanField')(default=True)),
# ))
# db.send_create_signal(u'catalog', ['Product'])
# # Adding model 'ProductInfo'
# db.create_table(u'catalog_productinfo', (
# (u'id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
# ('product_group', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['catalog.ProductGroup'])),
# ('product', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['catalog.Product'])),
# ('description', self.gf('django.db.models.fields.IntegerField')()),
# ('amount', self.gf('django.db.models.fields.CharField')(max_length=30)),
# ('value', self.gf('django.db.models.fields.CharField')(default='**', max_length=2)),
# ('visible', self.gf('django.db.models.fields.BooleanField')(default=True)),
# ))
# db.send_create_signal(u'catalog', ['ProductInfo'])
def backwards(self, orm):
# Deleting model 'ProductGroup'
db.delete_table(u'catalog_productgroup')
# Deleting model 'Product'
db.delete_table(u'catalog_product')
# Deleting model 'ProductInfo'
db.delete_table(u'catalog_productinfo')
models = {
u'catalog.product': {
'Meta': {'ordering': "('name',)", 'object_name': 'Product'},
'description': ('django.db.models.fields.TextField', [], {'max_length': '250'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'image': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '120'}),
'product_group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalog.ProductGroup']"}),
'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '50'}),
'visible': ('django.db.models.fields.BooleanField', [], {'default': 'True'})
},
u'catalog.productgroup': {
'Meta': {'ordering': "('name',)", 'object_name': 'ProductGroup'},
'description': ('django.db.models.fields.CharField', [], {'max_length': '125'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'image': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}),
'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '50'}),
'visible': ('django.db.models.fields.BooleanField', [], {'default': 'True'})
},
u'catalog.productinfo': {
'Meta': {'object_name': 'ProductInfo'},
'amount': ('django.db.models.fields.CharField', [], {'max_length': '30'}),
'description': ('django.db.models.fields.IntegerField', [], {}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'product': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalog.Product']"}),
'product_group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalog.ProductGroup']"}),
'value': ('django.db.models.fields.CharField', [], {'default': "'**'", 'max_length': '2'}),
'visible': ('django.db.models.fields.BooleanField', [], {'default': 'True'})
}
}
complete_apps = ['catalog']
| 56.163043
| 120
| 0.587381
| 561
| 5,167
| 5.315508
| 0.137255
| 0.099262
| 0.169014
| 0.241449
| 0.808853
| 0.72334
| 0.72334
| 0.70892
| 0.642857
| 0.618377
| 0
| 0.012089
| 0.199536
| 5,167
| 91
| 121
| 56.78022
| 0.708897
| 0.41436
| 0
| 0.27907
| 0
| 0
| 0.457468
| 0.258875
| 0
| 0
| 0
| 0
| 0
| 1
| 0.046512
| false
| 0.023256
| 0.093023
| 0
| 0.209302
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
c82e103edc771257d76e34319b293f9bf7e2b030
| 112
|
py
|
Python
|
yabab/blueprints.py
|
afh/yabab
|
5abbe08cf4a4bf104365770b16e43e5c0a3ecee2
|
[
"MIT"
] | 1
|
2019-10-26T16:43:53.000Z
|
2019-10-26T16:43:53.000Z
|
yabab/blueprints.py
|
afh/yabab
|
5abbe08cf4a4bf104365770b16e43e5c0a3ecee2
|
[
"MIT"
] | null | null | null |
yabab/blueprints.py
|
afh/yabab
|
5abbe08cf4a4bf104365770b16e43e5c0a3ecee2
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from . import app
from . import api
app.register_blueprint(api.mod, url_prefix='/api')
| 18.666667
| 50
| 0.678571
| 17
| 112
| 4.352941
| 0.705882
| 0.27027
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010417
| 0.142857
| 112
| 5
| 51
| 22.4
| 0.760417
| 0.1875
| 0
| 0
| 0
| 0
| 0.044944
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0.333333
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
c0832e0fe0c326289b5060af40cf233150a774dd
| 24
|
py
|
Python
|
env/__init__.py
|
jidiai/Competition_Football
|
14c5728a75753a96a38bd44f3c10a6c47f64714f
|
[
"MIT"
] | 6
|
2022-02-24T06:48:44.000Z
|
2022-03-23T02:40:36.000Z
|
env/__init__.py
|
jidiai/Competition_Football
|
14c5728a75753a96a38bd44f3c10a6c47f64714f
|
[
"MIT"
] | null | null | null |
env/__init__.py
|
jidiai/Competition_Football
|
14c5728a75753a96a38bd44f3c10a6c47f64714f
|
[
"MIT"
] | 1
|
2022-03-22T15:17:33.000Z
|
2022-03-22T15:17:33.000Z
|
from .football import *
| 12
| 23
| 0.75
| 3
| 24
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 24
| 1
| 24
| 24
| 0.9
| 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
| 1
| 0
|
0
| 6
|
c0947d54bbbbe5561edec609e86511c0f7e602c7
| 62
|
py
|
Python
|
multilingual_t5/r_ic_all_bn/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
multilingual_t5/r_ic_all_bn/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
multilingual_t5/r_ic_all_bn/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
"""r_ic_all_bn dataset."""
from .r_ic_all_bn import RIcAllBn
| 15.5
| 33
| 0.758065
| 12
| 62
| 3.416667
| 0.666667
| 0.146341
| 0.292683
| 0.390244
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112903
| 62
| 3
| 34
| 20.666667
| 0.745455
| 0.322581
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
8d071d1223a219466f173773e8510856df6a951d
| 196
|
py
|
Python
|
backend/userauth/admin.py
|
daeisbae/PeerOrgan-HackNYU2022
|
3f11f80fe101800727743e348ccb4f9135198950
|
[
"MIT"
] | null | null | null |
backend/userauth/admin.py
|
daeisbae/PeerOrgan-HackNYU2022
|
3f11f80fe101800727743e348ccb4f9135198950
|
[
"MIT"
] | null | null | null |
backend/userauth/admin.py
|
daeisbae/PeerOrgan-HackNYU2022
|
3f11f80fe101800727743e348ccb4f9135198950
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from . import models
# Register your models here.
# admin.site.register(models.User)
admin.site.register(models.Donor)
admin.site.register(models.Recipient)
| 28
| 37
| 0.780612
| 27
| 196
| 5.666667
| 0.481481
| 0.176471
| 0.333333
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| 0
| 0
| 0
| 0
| 0
| 0
| 0.117347
| 196
| 7
| 37
| 28
| 0.884393
| 0.30102
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| 0
| true
| 0
| 0.5
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| null | 0
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| 0
| 0
| 0
|
0
| 6
|
8d0bf01d65de80ab6e4fd4127d7b8e7d32cf8b14
| 64
|
py
|
Python
|
src/deepke/name_entity_re/few_shot/__init__.py
|
johncolezhang/DeepKE
|
ea4552ec42cb003a835f00fc14fb454f9a9a7183
|
[
"MIT"
] | 710
|
2021-08-01T16:43:59.000Z
|
2022-03-31T08:39:17.000Z
|
src/deepke/name_entity_re/few_shot/__init__.py
|
johncolezhang/DeepKE
|
ea4552ec42cb003a835f00fc14fb454f9a9a7183
|
[
"MIT"
] | 66
|
2019-06-09T12:14:31.000Z
|
2021-07-27T05:54:35.000Z
|
src/deepke/name_entity_re/few_shot/__init__.py
|
johncolezhang/DeepKE
|
ea4552ec42cb003a835f00fc14fb454f9a9a7183
|
[
"MIT"
] | 183
|
2018-09-07T06:57:13.000Z
|
2021-08-01T08:50:15.000Z
|
from .models import *
from .module import *
from .utils import *
| 21.333333
| 21
| 0.734375
| 9
| 64
| 5.222222
| 0.555556
| 0.425532
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171875
| 64
| 3
| 22
| 21.333333
| 0.886792
| 0
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| 0
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| 0
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| 0
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| true
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| 1
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| 1
| 0
|
0
| 6
|
23987ef6812e3b5c76a35ce57e639cf1c1c78712
| 8,753
|
py
|
Python
|
tests/bulk_clipper_tests.py
|
arezaii/subsetter
|
482e90fdaeaa8fa5de7e325bdbe2f41206744524
|
[
"MIT"
] | 1
|
2020-06-16T15:57:37.000Z
|
2020-06-16T15:57:37.000Z
|
tests/bulk_clipper_tests.py
|
arezaii/subsetter
|
482e90fdaeaa8fa5de7e325bdbe2f41206744524
|
[
"MIT"
] | 13
|
2020-08-21T02:24:39.000Z
|
2020-09-19T18:15:13.000Z
|
tests/bulk_clipper_tests.py
|
arezaii/subsetter
|
482e90fdaeaa8fa5de7e325bdbe2f41206744524
|
[
"MIT"
] | null | null | null |
import shutil
import unittest
from pathlib import Path
from parflow.subset.tools import bulk_clipper
from tests import test_files
from parflow.subset.utils.io import read_file
import numpy as np
import os
class BulkClipperArgParseTests(unittest.TestCase):
def setUp(self) -> None:
self.good_mask_file = test_files.huc10190004.get('conus1_mask').as_posix()
self.bad_mask_file = './mask_file_no_exists.tif'
self.good_input_file_list = [test_files.conus1_dem.as_posix(), test_files.conus1_mask.as_posix()]
self.bad_input_file_list = './input_file_to_clip_no_exists.pfb'
self.good_bbox_file = test_files.test_bbox_input.as_posix()
def test_cli_no_args(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args([])
def test_cli_mask_without_data_args(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(['-m', self.good_mask_file])
def test_cli_mask_and_dims_specified(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(
['-m', self.good_mask_file, '-l', '1', '1', '10', '10', '-d', self.good_input_file_list[0]])
def test_cli_mask_and_box_specified(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(
['-m', self.good_mask_file, '-b', self.good_bbox_file, '-d', self.good_input_file_list[0]])
def test_cli_mask_and_bbox_and_dims_specified(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(
['-m', self.good_mask_file, '-b', self.good_bbox_file, '-l', '1', '1', '10', '10', '-d',
self.good_input_file_list[0]])
def test_cli_mask_and_bad_input_file(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(['-m', self.good_mask_file, '-d', self.bad_input_file_list])
def test_cli_bad_mask_file(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(['-m', self.bad_mask_file, '-d', self.good_input_file_list])
def test_cli_no_mask_bbox_dims(self):
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(['-d', self.good_input_file_list[0]])
def test_cli_good_mask_and_input_defaults(self):
args = bulk_clipper.parse_args(['-m', self.good_mask_file, '-d', self.good_input_file_list[0]])
self.assertTrue(args.mask_file)
self.assertFalse(args.bbox_file)
self.assertFalse(args.bbox_def)
self.assertTrue(args.data_files)
self.assertEqual(args.out_dir, '.')
self.assertFalse(args.ref_file)
self.assertFalse(args.write_tifs)
self.assertTrue(args.write_pfbs)
def test_cli_good_dims_and_input_defaults(self):
args = bulk_clipper.parse_args(['-l', '10', '20', '30', '40', '-d', self.good_input_file_list[0]])
self.assertFalse(args.mask_file)
self.assertFalse(args.bbox_file)
self.assertTrue(args.bbox_def)
self.assertTrue(args.data_files)
self.assertEqual(args.out_dir, '.')
self.assertFalse(args.ref_file)
self.assertFalse(args.write_tifs)
self.assertTrue(args.write_pfbs)
self.assertSequenceEqual(args.bbox_def, (10, 20, 30, 40))
def test_cli_good_bbox_file_and_input_defaults(self):
args = bulk_clipper.parse_args(['-b', self.good_bbox_file, '-d', self.good_input_file_list[0]])
self.assertFalse(args.mask_file)
self.assertTrue(args.bbox_file)
self.assertFalse(args.bbox_def)
self.assertTrue(args.data_files)
self.assertEqual(args.out_dir, '.')
self.assertFalse(args.ref_file)
self.assertFalse(args.write_tifs)
self.assertTrue(args.write_pfbs)
def test_mutual_exclusive_file_pattern_glob(self):
argstring = f'-m {self.good_mask_file} -d {self.good_input_file_list[0]} -g input_pattern*.pfb'
with self.assertRaises(SystemExit):
bulk_clipper.parse_args(argstring.split(' '))
def test_file_pattern_glob(self):
argstring = f'-m {self.good_mask_file} -g input_pattern*.pfb'
args = bulk_clipper.parse_args(argstring.split(' '))
self.assertEqual(os.fspath(self.good_mask_file), args.mask_file)
self.assertFalse(args.bbox_file)
self.assertFalse(args.bbox_def)
self.assertTrue(args.glob_pattern)
self.assertFalse(args.data_files)
self.assertEqual(args.out_dir, '.')
self.assertFalse(args.ref_file)
self.assertFalse(args.write_tifs)
self.assertTrue(args.write_pfbs)
class BulkClipperUnitTests(unittest.TestCase):
def setUp(self) -> None:
self.good_input_file_list = [test_files.conus1_dem.as_posix(), test_files.conus1_mask.as_posix()]
def test_get_files_list_of_files(self):
files = bulk_clipper.get_file_list(Path('.'), files=self.good_input_file_list)
self.assertCountEqual(self.good_input_file_list, [os.fspath(f) for f in files])
def test_get_files_empty(self):
files = bulk_clipper.get_file_list(Path('.'))
self.assertCountEqual([], list(files))
def test_get_files_glob(self):
test_dir = Path('./test_outputs')
test_dir.mkdir(exist_ok=True)
variable_names = ['temp', 'rain', 'press']
for var in variable_names:
for i in range(3):
fname = test_dir / f'{var}.out.{i * 10:04d}_to_{(i * 10) + 9:04d}.pfb'
fname.write_text('junk test data')
temp_files = bulk_clipper.get_file_list(test_dir, glob_pattern=f'temp.out.{"[0-9]" * 4}_to_{"[0-9]" * 4}.pfb')
self.assertCountEqual(['temp.out.0000_to_0009.pfb', 'temp.out.0010_to_0019.pfb', 'temp.out.0020_to_0029.pfb'], [f.name for f in temp_files])
press_files2 = bulk_clipper.get_file_list(test_dir,
glob_pattern=f'press.out.00[1-9][0-9]_to_00[1-9][0-9].pfb')
self.assertCountEqual(['press.out.0010_to_0019.pfb', 'press.out.0020_to_0029.pfb'],
[f.name for f in press_files2])
shutil.rmtree(test_dir)
def test_get_files_list_of_names(self):
test_dir = Path('./test_outputs')
test_dir.mkdir(exist_ok=True)
variable_names = ['temp', 'rain', 'press']
for var in variable_names:
for i in range(3):
fname = test_dir / f'{var}.out.{i * 10:04d}_to_{(i * 10) + 9:04d}.pfb'
fname.write_text('junk test data')
temp_files2 = bulk_clipper.get_file_list(test_dir,
files=['temp.out.0000_to_0009.pfb', 'temp.out.0010_to_0019.pfb'])
self.assertCountEqual(['temp.out.0000_to_0009.pfb', 'temp.out.0010_to_0019.pfb'],
[f.name for f in temp_files2])
press_files = bulk_clipper.get_file_list(test_dir,
files=['press.out.0000_to_0009.pfb', 'press.out.0010_to_0019.pfb',
'press.out.0020_to_0029.pfb'])
self.assertCountEqual(['press.out.0000_to_0009.pfb', 'press.out.0010_to_0019.pfb', 'press.out.0020_to_0029.pfb'],
[f.name for f in press_files])
shutil.rmtree(test_dir)
class BulkClipperRegressionTests(unittest.TestCase):
def setUp(self) -> None:
self.good_mask_file = test_files.huc10190004.get('conus1_mask').as_posix()
self.bad_mask_file = './mask_file_no_exists.tif'
self.good_input_file_list = [test_files.conus1_dem.as_posix(), test_files.conus1_mask.as_posix()]
self.bad_input_file_list = './input_file_to_clip_no_exists.pfb'
self.good_bbox_file = test_files.test_bbox_input.as_posix()
def test_box_clip_default(self):
bulk_clipper.box_clip((1040, 717, 85, 30), self.good_input_file_list[:1])
ref_data = read_file(test_files.huc10190004.get('conus1_dem_box').as_posix())
written_data = read_file('./CONUS2.0_RawDEM_CONUS1clip_clip.pfb')
self.assertIsNone(np.testing.assert_array_equal(ref_data, written_data))
os.remove('./CONUS2.0_RawDEM_CONUS1clip_clip.pfb')
def test_mask_clip_default(self):
mask = test_files.huc10190004.get('conus1_mask').as_posix()
bulk_clipper.mask_clip(mask, self.good_input_file_list[:1])
ref_data = read_file(test_files.huc10190004.get('conus1_dem').as_posix())
written_data = read_file('./CONUS2.0_RawDEM_CONUS1clip_clip.pfb')
self.assertIsNone(np.testing.assert_array_equal(ref_data, written_data))
os.remove('./CONUS2.0_RawDEM_CONUS1clip_clip.pfb')
if __name__ == '__main__':
unittest.main()
| 45.588542
| 148
| 0.662516
| 1,230
| 8,753
| 4.360976
| 0.114634
| 0.047726
| 0.046048
| 0.050708
| 0.840977
| 0.807793
| 0.784862
| 0.78132
| 0.723154
| 0.686428
| 0
| 0.039693
| 0.211356
| 8,753
| 191
| 149
| 45.827225
| 0.737361
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| 0.487013
| 0
| 0.032468
| 0.13424
| 0.08717
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| 0.331169
| 1
| 0.142857
| false
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| 0.051948
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| 0.214286
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
23a372af8d950f9eacf935518b360588dfe051ff
| 859
|
py
|
Python
|
ipython/startup/import_itertools.py
|
dycw/dotfiles2
|
9e23c4989e9813080da3658a8f98dbb1e03776f2
|
[
"MIT"
] | null | null | null |
ipython/startup/import_itertools.py
|
dycw/dotfiles2
|
9e23c4989e9813080da3658a8f98dbb1e03776f2
|
[
"MIT"
] | null | null | null |
ipython/startup/import_itertools.py
|
dycw/dotfiles2
|
9e23c4989e9813080da3658a8f98dbb1e03776f2
|
[
"MIT"
] | null | null | null |
import itertools # noqa: F401
from itertools import accumulate # noqa: F401
from itertools import chain # noqa: F401
from itertools import combinations # noqa: F401
from itertools import combinations_with_replacement # noqa: F401
from itertools import compress # noqa: F401
from itertools import count # noqa: F401
from itertools import cycle # noqa: F401
from itertools import dropwhile # noqa: F401
from itertools import filterfalse # noqa: F401
from itertools import groupby # noqa: F401
from itertools import islice # noqa: F401
from itertools import permutations # noqa: F401
from itertools import product # noqa: F401
from itertools import repeat # noqa: F401
from itertools import starmap # noqa: F401
from itertools import takewhile # noqa: F401
from itertools import tee # noqa: F401
from itertools import zip_longest # noqa: F401
| 42.95
| 65
| 0.781141
| 115
| 859
| 5.808696
| 0.217391
| 0.227545
| 0.323353
| 0.565868
| 0.763473
| 0.116766
| 0
| 0
| 0
| 0
| 0
| 0.080395
| 0.174622
| 859
| 19
| 66
| 45.210526
| 0.861777
| 0.242142
| 0
| 0
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| 0
| true
| 0
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| 1
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| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f194cc85bd4db4fe5ac8dbfd7f334a223e5c3090
| 35
|
py
|
Python
|
turbustat/statistics/pca/__init__.py
|
keflavich/TurbuStat
|
a6fac4c0d10473a74c62cce4a9c6a30773a955b1
|
[
"MIT"
] | null | null | null |
turbustat/statistics/pca/__init__.py
|
keflavich/TurbuStat
|
a6fac4c0d10473a74c62cce4a9c6a30773a955b1
|
[
"MIT"
] | null | null | null |
turbustat/statistics/pca/__init__.py
|
keflavich/TurbuStat
|
a6fac4c0d10473a74c62cce4a9c6a30773a955b1
|
[
"MIT"
] | null | null | null |
from pca import PCA, PCA_Distance
| 17.5
| 34
| 0.8
| 6
| 35
| 4.5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171429
| 35
| 1
| 35
| 35
| 0.931034
| 0
| 0
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| 0
| 0
| 0
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| 0
| 0
| 0
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| true
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| null | 0
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| 0
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| 0
| 1
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| 1
| 0
| 1
| 0
|
0
| 6
|
f1cc7c4152fe399c23d6a3b4eb96cc90a6d4a2d3
| 37,890
|
py
|
Python
|
instances/passenger_demand/pas-20210421-2109-int14000000000000001e/12.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
instances/passenger_demand/pas-20210421-2109-int14000000000000001e/12.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
instances/passenger_demand/pas-20210421-2109-int14000000000000001e/12.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
"""
PASSENGERS
"""
numPassengers = 3190
passenger_arriving = (
(5, 7, 2, 5, 1, 0, 5, 10, 5, 3, 2, 0), # 0
(6, 14, 4, 3, 1, 0, 3, 11, 5, 4, 2, 0), # 1
(3, 6, 6, 4, 3, 0, 7, 7, 5, 3, 1, 0), # 2
(2, 1, 6, 3, 1, 0, 7, 8, 10, 3, 2, 0), # 3
(4, 4, 6, 2, 1, 0, 4, 6, 7, 2, 2, 0), # 4
(5, 12, 7, 4, 1, 0, 12, 7, 2, 3, 1, 0), # 5
(4, 7, 4, 2, 4, 0, 6, 3, 3, 3, 7, 0), # 6
(3, 10, 8, 3, 1, 0, 10, 9, 4, 4, 2, 0), # 7
(4, 6, 10, 4, 3, 0, 8, 6, 3, 8, 2, 0), # 8
(8, 9, 8, 3, 1, 0, 5, 8, 3, 7, 5, 0), # 9
(7, 12, 8, 6, 1, 0, 7, 4, 9, 6, 0, 0), # 10
(2, 9, 9, 5, 1, 0, 5, 12, 4, 4, 4, 0), # 11
(3, 15, 13, 2, 2, 0, 7, 6, 5, 4, 1, 0), # 12
(2, 8, 5, 3, 0, 0, 7, 12, 6, 4, 3, 0), # 13
(2, 11, 5, 4, 3, 0, 7, 8, 5, 1, 0, 0), # 14
(3, 9, 2, 6, 3, 0, 7, 5, 9, 9, 7, 0), # 15
(3, 8, 7, 3, 2, 0, 4, 12, 7, 6, 1, 0), # 16
(3, 5, 5, 5, 0, 0, 6, 5, 6, 5, 4, 0), # 17
(6, 6, 4, 4, 2, 0, 7, 5, 3, 5, 0, 0), # 18
(4, 9, 10, 7, 2, 0, 7, 11, 3, 6, 6, 0), # 19
(5, 9, 8, 2, 1, 0, 7, 7, 6, 3, 3, 0), # 20
(2, 9, 8, 4, 2, 0, 9, 7, 10, 2, 0, 0), # 21
(2, 12, 5, 2, 3, 0, 4, 9, 7, 6, 2, 0), # 22
(6, 13, 11, 3, 2, 0, 6, 4, 5, 6, 4, 0), # 23
(3, 12, 6, 4, 1, 0, 8, 9, 8, 6, 7, 0), # 24
(8, 11, 5, 4, 0, 0, 9, 9, 9, 2, 4, 0), # 25
(6, 8, 3, 1, 4, 0, 2, 10, 5, 5, 2, 0), # 26
(2, 10, 4, 3, 1, 0, 10, 11, 4, 6, 2, 0), # 27
(2, 16, 13, 1, 1, 0, 0, 5, 5, 3, 3, 0), # 28
(6, 9, 10, 5, 1, 0, 8, 11, 6, 4, 2, 0), # 29
(4, 15, 9, 5, 1, 0, 10, 9, 6, 2, 0, 0), # 30
(3, 9, 3, 3, 2, 0, 4, 7, 5, 11, 4, 0), # 31
(1, 7, 11, 3, 2, 0, 4, 12, 5, 2, 3, 0), # 32
(10, 4, 6, 1, 2, 0, 9, 11, 7, 5, 1, 0), # 33
(5, 7, 6, 6, 3, 0, 4, 12, 9, 7, 0, 0), # 34
(5, 8, 8, 3, 2, 0, 4, 10, 8, 6, 1, 0), # 35
(3, 3, 8, 3, 1, 0, 5, 8, 4, 2, 2, 0), # 36
(2, 17, 10, 6, 1, 0, 10, 9, 4, 4, 2, 0), # 37
(5, 10, 5, 1, 2, 0, 7, 8, 11, 8, 3, 0), # 38
(6, 13, 10, 3, 2, 0, 5, 10, 5, 2, 3, 0), # 39
(3, 6, 9, 5, 1, 0, 8, 12, 9, 2, 1, 0), # 40
(8, 11, 4, 4, 4, 0, 3, 12, 5, 4, 1, 0), # 41
(2, 6, 4, 2, 3, 0, 11, 8, 8, 5, 2, 0), # 42
(2, 9, 12, 2, 5, 0, 3, 6, 7, 9, 4, 0), # 43
(4, 13, 8, 3, 1, 0, 4, 8, 5, 3, 2, 0), # 44
(1, 11, 8, 1, 1, 0, 5, 13, 3, 1, 2, 0), # 45
(9, 14, 7, 3, 3, 0, 6, 5, 6, 10, 1, 0), # 46
(5, 10, 12, 4, 3, 0, 4, 6, 5, 7, 2, 0), # 47
(5, 9, 10, 2, 3, 0, 8, 13, 5, 4, 2, 0), # 48
(3, 11, 7, 5, 1, 0, 4, 14, 5, 9, 2, 0), # 49
(7, 13, 14, 3, 1, 0, 13, 11, 4, 5, 0, 0), # 50
(12, 9, 7, 4, 3, 0, 7, 8, 10, 5, 2, 0), # 51
(4, 9, 4, 6, 2, 0, 3, 4, 12, 6, 2, 0), # 52
(5, 9, 6, 6, 1, 0, 4, 6, 9, 7, 1, 0), # 53
(4, 6, 10, 7, 4, 0, 1, 7, 4, 2, 0, 0), # 54
(4, 8, 6, 2, 1, 0, 9, 5, 6, 2, 1, 0), # 55
(5, 11, 12, 5, 4, 0, 4, 6, 5, 3, 0, 0), # 56
(3, 13, 5, 3, 2, 0, 10, 14, 5, 8, 2, 0), # 57
(3, 8, 2, 4, 4, 0, 4, 9, 7, 6, 2, 0), # 58
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 59
)
station_arriving_intensity = (
(3.7095121817383676, 9.515044981060607, 11.19193043059126, 8.87078804347826, 10.000240384615385, 6.659510869565219), # 0
(3.7443308140669203, 9.620858238197952, 11.252381752534994, 8.920190141908213, 10.075193108974359, 6.657240994867151), # 1
(3.7787518681104277, 9.725101964085297, 11.31139817195087, 8.968504830917876, 10.148564102564103, 6.654901690821256), # 2
(3.8127461259877085, 9.827663671875001, 11.368936576156813, 9.01569089673913, 10.22028605769231, 6.652493274456523), # 3
(3.8462843698175795, 9.928430874719417, 11.424953852470724, 9.061707125603865, 10.290291666666668, 6.6500160628019325), # 4
(3.879337381718857, 10.027291085770905, 11.479406888210512, 9.106512303743962, 10.358513621794872, 6.647470372886473), # 5
(3.9118759438103607, 10.12413181818182, 11.53225257069409, 9.150065217391306, 10.424884615384617, 6.644856521739131), # 6
(3.943870838210907, 10.218840585104518, 11.58344778723936, 9.19232465277778, 10.489337339743592, 6.64217482638889), # 7
(3.975292847039314, 10.311304899691358, 11.632949425164242, 9.233249396135266, 10.551804487179488, 6.639425603864735), # 8
(4.006112752414399, 10.401412275094698, 11.680714371786634, 9.272798233695653, 10.61221875, 6.636609171195653), # 9
(4.03630133645498, 10.489050224466892, 11.72669951442445, 9.310929951690824, 10.670512820512823, 6.633725845410628), # 10
(4.065829381279876, 10.5741062609603, 11.7708617403956, 9.347603336352659, 10.726619391025642, 6.630775943538648), # 11
(4.094667669007903, 10.656467897727273, 11.813157937017996, 9.382777173913043, 10.780471153846154, 6.627759782608695), # 12
(4.122786981757876, 10.736022647920176, 11.85354499160954, 9.416410250603866, 10.832000801282053, 6.624677679649759), # 13
(4.15015810164862, 10.81265802469136, 11.891979791488144, 9.448461352657004, 10.881141025641025, 6.621529951690821), # 14
(4.1767518107989465, 10.886261541193182, 11.928419223971721, 9.478889266304348, 10.92782451923077, 6.618316915760871), # 15
(4.202538891327675, 10.956720710578002, 11.96282017637818, 9.507652777777778, 10.971983974358976, 6.61503888888889), # 16
(4.227490125353625, 11.023923045998176, 11.995139536025421, 9.53471067330918, 11.013552083333336, 6.611696188103866), # 17
(4.25157629499561, 11.087756060606061, 12.025334190231364, 9.560021739130436, 11.052461538461543, 6.608289130434783), # 18
(4.274768182372451, 11.148107267554012, 12.053361026313912, 9.58354476147343, 11.088645032051284, 6.604818032910629), # 19
(4.297036569602966, 11.204864179994388, 12.079176931590974, 9.60523852657005, 11.122035256410259, 6.601283212560387), # 20
(4.318352238805971, 11.257914311079544, 12.102738793380466, 9.625061820652174, 11.152564903846153, 6.597684986413044), # 21
(4.338685972100283, 11.307145173961842, 12.124003499000287, 9.642973429951692, 11.180166666666667, 6.5940236714975855), # 22
(4.358008551604722, 11.352444281793632, 12.142927935768354, 9.658932140700484, 11.204773237179488, 6.590299584842997), # 23
(4.3762907594381035, 11.393699147727272, 12.159468991002571, 9.672896739130437, 11.226317307692307, 6.586513043478261), # 24
(4.393503377719247, 11.430797284915124, 12.173583552020853, 9.684826011473431, 11.244731570512819, 6.582664364432368), # 25
(4.409617188566969, 11.46362620650954, 12.185228506141103, 9.694678743961353, 11.259948717948719, 6.5787538647343), # 26
(4.424602974100088, 11.492073425662877, 12.194360740681233, 9.702413722826089, 11.271901442307694, 6.574781861413045), # 27
(4.438431516437421, 11.516026455527497, 12.200937142959157, 9.707989734299519, 11.280522435897437, 6.570748671497586), # 28
(4.4510735976977855, 11.535372809255753, 12.204914600292774, 9.711365564613528, 11.285744391025641, 6.566654612016909), # 29
(4.4625, 11.55, 12.20625, 9.7125, 11.287500000000001, 6.562500000000001), # 30
(4.47319183983376, 11.56215031960227, 12.205248928140096, 9.712295118464054, 11.286861125886526, 6.556726763701484), # 31
(4.4836528452685425, 11.574140056818184, 12.202274033816424, 9.711684477124184, 11.28495815602837, 6.547834661835751), # 32
(4.493887715792838, 11.585967720170455, 12.197367798913046, 9.710674080882354, 11.281811569148937, 6.535910757121439), # 33
(4.503901150895141, 11.597631818181819, 12.19057270531401, 9.709269934640524, 11.277441843971632, 6.521042112277196), # 34
(4.513697850063939, 11.609130859374998, 12.181931234903383, 9.707478043300654, 11.27186945921986, 6.503315790021656), # 35
(4.523282512787724, 11.62046335227273, 12.171485869565219, 9.705304411764708, 11.265114893617023, 6.482818853073463), # 36
(4.532659838554988, 11.631627805397729, 12.159279091183576, 9.70275504493464, 11.257198625886524, 6.4596383641512585), # 37
(4.5418345268542195, 11.642622727272729, 12.145353381642513, 9.699835947712419, 11.248141134751775, 6.433861385973679), # 38
(4.5508112771739135, 11.653446626420456, 12.129751222826087, 9.696553125000001, 11.23796289893617, 6.40557498125937), # 39
(4.559594789002558, 11.664098011363638, 12.11251509661836, 9.692912581699348, 11.22668439716312, 6.37486621272697), # 40
(4.568189761828645, 11.674575390625, 12.093687484903382, 9.68892032271242, 11.214326108156028, 6.34182214309512), # 41
(4.576600895140665, 11.684877272727276, 12.07331086956522, 9.684582352941177, 11.2009085106383, 6.3065298350824595), # 42
(4.584832888427111, 11.69500216619318, 12.051427732487923, 9.679904677287583, 11.186452083333334, 6.26907635140763), # 43
(4.592890441176471, 11.704948579545455, 12.028080555555556, 9.674893300653595, 11.17097730496454, 6.229548754789272), # 44
(4.600778252877237, 11.714715021306818, 12.003311820652177, 9.669554227941177, 11.15450465425532, 6.188034107946028), # 45
(4.6085010230179035, 11.724300000000003, 11.97716400966184, 9.663893464052288, 11.137054609929079, 6.144619473596536), # 46
(4.616063451086957, 11.733702024147728, 11.9496796044686, 9.65791701388889, 11.118647650709221, 6.099391914459438), # 47
(4.623470236572891, 11.742919602272728, 11.920901086956523, 9.651630882352942, 11.099304255319149, 6.052438493253375), # 48
(4.630726078964194, 11.751951242897727, 11.890870939009663, 9.645041074346407, 11.079044902482272, 6.003846272696985), # 49
(4.6378356777493615, 11.760795454545454, 11.85963164251208, 9.638153594771243, 11.057890070921987, 5.953702315508913), # 50
(4.6448037324168805, 11.769450745738636, 11.827225679347826, 9.630974448529413, 11.035860239361703, 5.902093684407797), # 51
(4.651634942455243, 11.777915625, 11.793695531400965, 9.623509640522876, 11.012975886524824, 5.849107442112278), # 52
(4.658334007352941, 11.786188600852274, 11.759083680555555, 9.615765175653596, 10.989257491134753, 5.794830651340996), # 53
(4.6649056265984665, 11.79426818181818, 11.723432608695653, 9.60774705882353, 10.964725531914894, 5.739350374812594), # 54
(4.671354499680307, 11.802152876420456, 11.686784797705313, 9.599461294934642, 10.939400487588653, 5.682753675245711), # 55
(4.677685326086957, 11.809841193181818, 11.649182729468599, 9.59091388888889, 10.913302836879433, 5.625127615358988), # 56
(4.683902805306906, 11.817331640625003, 11.610668885869565, 9.582110845588236, 10.886453058510638, 5.566559257871065), # 57
(4.690011636828645, 11.824622727272727, 11.57128574879227, 9.573058169934642, 10.858871631205675, 5.507135665500583), # 58
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59
)
passenger_arriving_acc = (
(5, 7, 2, 5, 1, 0, 5, 10, 5, 3, 2, 0), # 0
(11, 21, 6, 8, 2, 0, 8, 21, 10, 7, 4, 0), # 1
(14, 27, 12, 12, 5, 0, 15, 28, 15, 10, 5, 0), # 2
(16, 28, 18, 15, 6, 0, 22, 36, 25, 13, 7, 0), # 3
(20, 32, 24, 17, 7, 0, 26, 42, 32, 15, 9, 0), # 4
(25, 44, 31, 21, 8, 0, 38, 49, 34, 18, 10, 0), # 5
(29, 51, 35, 23, 12, 0, 44, 52, 37, 21, 17, 0), # 6
(32, 61, 43, 26, 13, 0, 54, 61, 41, 25, 19, 0), # 7
(36, 67, 53, 30, 16, 0, 62, 67, 44, 33, 21, 0), # 8
(44, 76, 61, 33, 17, 0, 67, 75, 47, 40, 26, 0), # 9
(51, 88, 69, 39, 18, 0, 74, 79, 56, 46, 26, 0), # 10
(53, 97, 78, 44, 19, 0, 79, 91, 60, 50, 30, 0), # 11
(56, 112, 91, 46, 21, 0, 86, 97, 65, 54, 31, 0), # 12
(58, 120, 96, 49, 21, 0, 93, 109, 71, 58, 34, 0), # 13
(60, 131, 101, 53, 24, 0, 100, 117, 76, 59, 34, 0), # 14
(63, 140, 103, 59, 27, 0, 107, 122, 85, 68, 41, 0), # 15
(66, 148, 110, 62, 29, 0, 111, 134, 92, 74, 42, 0), # 16
(69, 153, 115, 67, 29, 0, 117, 139, 98, 79, 46, 0), # 17
(75, 159, 119, 71, 31, 0, 124, 144, 101, 84, 46, 0), # 18
(79, 168, 129, 78, 33, 0, 131, 155, 104, 90, 52, 0), # 19
(84, 177, 137, 80, 34, 0, 138, 162, 110, 93, 55, 0), # 20
(86, 186, 145, 84, 36, 0, 147, 169, 120, 95, 55, 0), # 21
(88, 198, 150, 86, 39, 0, 151, 178, 127, 101, 57, 0), # 22
(94, 211, 161, 89, 41, 0, 157, 182, 132, 107, 61, 0), # 23
(97, 223, 167, 93, 42, 0, 165, 191, 140, 113, 68, 0), # 24
(105, 234, 172, 97, 42, 0, 174, 200, 149, 115, 72, 0), # 25
(111, 242, 175, 98, 46, 0, 176, 210, 154, 120, 74, 0), # 26
(113, 252, 179, 101, 47, 0, 186, 221, 158, 126, 76, 0), # 27
(115, 268, 192, 102, 48, 0, 186, 226, 163, 129, 79, 0), # 28
(121, 277, 202, 107, 49, 0, 194, 237, 169, 133, 81, 0), # 29
(125, 292, 211, 112, 50, 0, 204, 246, 175, 135, 81, 0), # 30
(128, 301, 214, 115, 52, 0, 208, 253, 180, 146, 85, 0), # 31
(129, 308, 225, 118, 54, 0, 212, 265, 185, 148, 88, 0), # 32
(139, 312, 231, 119, 56, 0, 221, 276, 192, 153, 89, 0), # 33
(144, 319, 237, 125, 59, 0, 225, 288, 201, 160, 89, 0), # 34
(149, 327, 245, 128, 61, 0, 229, 298, 209, 166, 90, 0), # 35
(152, 330, 253, 131, 62, 0, 234, 306, 213, 168, 92, 0), # 36
(154, 347, 263, 137, 63, 0, 244, 315, 217, 172, 94, 0), # 37
(159, 357, 268, 138, 65, 0, 251, 323, 228, 180, 97, 0), # 38
(165, 370, 278, 141, 67, 0, 256, 333, 233, 182, 100, 0), # 39
(168, 376, 287, 146, 68, 0, 264, 345, 242, 184, 101, 0), # 40
(176, 387, 291, 150, 72, 0, 267, 357, 247, 188, 102, 0), # 41
(178, 393, 295, 152, 75, 0, 278, 365, 255, 193, 104, 0), # 42
(180, 402, 307, 154, 80, 0, 281, 371, 262, 202, 108, 0), # 43
(184, 415, 315, 157, 81, 0, 285, 379, 267, 205, 110, 0), # 44
(185, 426, 323, 158, 82, 0, 290, 392, 270, 206, 112, 0), # 45
(194, 440, 330, 161, 85, 0, 296, 397, 276, 216, 113, 0), # 46
(199, 450, 342, 165, 88, 0, 300, 403, 281, 223, 115, 0), # 47
(204, 459, 352, 167, 91, 0, 308, 416, 286, 227, 117, 0), # 48
(207, 470, 359, 172, 92, 0, 312, 430, 291, 236, 119, 0), # 49
(214, 483, 373, 175, 93, 0, 325, 441, 295, 241, 119, 0), # 50
(226, 492, 380, 179, 96, 0, 332, 449, 305, 246, 121, 0), # 51
(230, 501, 384, 185, 98, 0, 335, 453, 317, 252, 123, 0), # 52
(235, 510, 390, 191, 99, 0, 339, 459, 326, 259, 124, 0), # 53
(239, 516, 400, 198, 103, 0, 340, 466, 330, 261, 124, 0), # 54
(243, 524, 406, 200, 104, 0, 349, 471, 336, 263, 125, 0), # 55
(248, 535, 418, 205, 108, 0, 353, 477, 341, 266, 125, 0), # 56
(251, 548, 423, 208, 110, 0, 363, 491, 346, 274, 127, 0), # 57
(254, 556, 425, 212, 114, 0, 367, 500, 353, 280, 129, 0), # 58
(254, 556, 425, 212, 114, 0, 367, 500, 353, 280, 129, 0), # 59
)
passenger_arriving_rate = (
(3.7095121817383676, 7.612035984848484, 6.715158258354756, 3.5483152173913037, 2.000048076923077, 0.0, 6.659510869565219, 8.000192307692307, 5.322472826086956, 4.476772172236504, 1.903008996212121, 0.0), # 0
(3.7443308140669203, 7.696686590558361, 6.751429051520996, 3.5680760567632848, 2.0150386217948717, 0.0, 6.657240994867151, 8.060154487179487, 5.352114085144928, 4.500952701013997, 1.9241716476395903, 0.0), # 1
(3.7787518681104277, 7.780081571268237, 6.786838903170522, 3.58740193236715, 2.0297128205128203, 0.0, 6.654901690821256, 8.118851282051281, 5.381102898550726, 4.524559268780347, 1.9450203928170593, 0.0), # 2
(3.8127461259877085, 7.8621309375, 6.821361945694087, 3.6062763586956517, 2.044057211538462, 0.0, 6.652493274456523, 8.176228846153847, 5.409414538043478, 4.547574630462725, 1.965532734375, 0.0), # 3
(3.8462843698175795, 7.942744699775533, 6.854972311482434, 3.624682850241546, 2.0580583333333333, 0.0, 6.6500160628019325, 8.232233333333333, 5.437024275362319, 4.569981540988289, 1.9856861749438832, 0.0), # 4
(3.879337381718857, 8.021832868616723, 6.887644132926307, 3.6426049214975844, 2.0717027243589743, 0.0, 6.647470372886473, 8.286810897435897, 5.463907382246377, 4.591762755284204, 2.005458217154181, 0.0), # 5
(3.9118759438103607, 8.099305454545455, 6.919351542416455, 3.660026086956522, 2.084976923076923, 0.0, 6.644856521739131, 8.339907692307692, 5.490039130434783, 4.612901028277636, 2.0248263636363637, 0.0), # 6
(3.943870838210907, 8.175072468083613, 6.950068672343615, 3.6769298611111116, 2.0978674679487184, 0.0, 6.64217482638889, 8.391469871794873, 5.515394791666668, 4.633379114895743, 2.043768117020903, 0.0), # 7
(3.975292847039314, 8.249043919753085, 6.979769655098544, 3.693299758454106, 2.1103608974358976, 0.0, 6.639425603864735, 8.44144358974359, 5.5399496376811594, 4.653179770065696, 2.062260979938271, 0.0), # 8
(4.006112752414399, 8.321129820075758, 7.00842862307198, 3.709119293478261, 2.12244375, 0.0, 6.636609171195653, 8.489775, 5.563678940217391, 4.672285748714653, 2.0802824550189394, 0.0), # 9
(4.03630133645498, 8.391240179573513, 7.03601970865467, 3.724371980676329, 2.134102564102564, 0.0, 6.633725845410628, 8.536410256410257, 5.586557971014494, 4.690679805769779, 2.0978100448933783, 0.0), # 10
(4.065829381279876, 8.459285008768239, 7.06251704423736, 3.739041334541063, 2.145323878205128, 0.0, 6.630775943538648, 8.581295512820512, 5.608562001811595, 4.70834469615824, 2.1148212521920597, 0.0), # 11
(4.094667669007903, 8.525174318181818, 7.087894762210797, 3.7531108695652167, 2.156094230769231, 0.0, 6.627759782608695, 8.624376923076923, 5.6296663043478254, 4.725263174807198, 2.1312935795454546, 0.0), # 12
(4.122786981757876, 8.58881811833614, 7.112126994965724, 3.766564100241546, 2.1664001602564102, 0.0, 6.624677679649759, 8.665600641025641, 5.649846150362319, 4.741417996643816, 2.147204529584035, 0.0), # 13
(4.15015810164862, 8.650126419753088, 7.135187874892886, 3.779384541062801, 2.1762282051282047, 0.0, 6.621529951690821, 8.704912820512819, 5.669076811594202, 4.756791916595257, 2.162531604938272, 0.0), # 14
(4.1767518107989465, 8.709009232954545, 7.157051534383032, 3.7915557065217387, 2.1855649038461538, 0.0, 6.618316915760871, 8.742259615384615, 5.6873335597826085, 4.771367689588688, 2.177252308238636, 0.0), # 15
(4.202538891327675, 8.7653765684624, 7.177692105826908, 3.803061111111111, 2.194396794871795, 0.0, 6.61503888888889, 8.77758717948718, 5.7045916666666665, 4.785128070551272, 2.1913441421156, 0.0), # 16
(4.227490125353625, 8.81913843679854, 7.197083721615253, 3.8138842693236716, 2.202710416666667, 0.0, 6.611696188103866, 8.810841666666668, 5.720826403985508, 4.798055814410168, 2.204784609199635, 0.0), # 17
(4.25157629499561, 8.870204848484848, 7.215200514138818, 3.824008695652174, 2.2104923076923084, 0.0, 6.608289130434783, 8.841969230769234, 5.736013043478262, 4.810133676092545, 2.217551212121212, 0.0), # 18
(4.274768182372451, 8.918485814043208, 7.232016615788346, 3.8334179045893717, 2.2177290064102566, 0.0, 6.604818032910629, 8.870916025641026, 5.750126856884058, 4.8213444105255645, 2.229621453510802, 0.0), # 19
(4.297036569602966, 8.96389134399551, 7.247506158954584, 3.8420954106280196, 2.2244070512820517, 0.0, 6.601283212560387, 8.897628205128207, 5.76314311594203, 4.831670772636389, 2.2409728359988774, 0.0), # 20
(4.318352238805971, 9.006331448863634, 7.261643276028279, 3.8500247282608693, 2.2305129807692303, 0.0, 6.597684986413044, 8.922051923076921, 5.775037092391305, 4.841095517352186, 2.2515828622159084, 0.0), # 21
(4.338685972100283, 9.045716139169473, 7.274402099400172, 3.8571893719806765, 2.2360333333333333, 0.0, 6.5940236714975855, 8.944133333333333, 5.785784057971015, 4.849601399600115, 2.2614290347923682, 0.0), # 22
(4.358008551604722, 9.081955425434906, 7.285756761461012, 3.8635728562801934, 2.2409546474358972, 0.0, 6.590299584842997, 8.963818589743589, 5.79535928442029, 4.857171174307341, 2.2704888563587264, 0.0), # 23
(4.3762907594381035, 9.114959318181818, 7.295681394601543, 3.869158695652174, 2.2452634615384612, 0.0, 6.586513043478261, 8.981053846153845, 5.803738043478262, 4.863787596401028, 2.2787398295454544, 0.0), # 24
(4.393503377719247, 9.1446378279321, 7.304150131212511, 3.8739304045893723, 2.2489463141025636, 0.0, 6.582664364432368, 8.995785256410255, 5.810895606884059, 4.869433420808341, 2.286159456983025, 0.0), # 25
(4.409617188566969, 9.17090096520763, 7.311137103684661, 3.8778714975845405, 2.2519897435897436, 0.0, 6.5787538647343, 9.007958974358974, 5.816807246376811, 4.874091402456441, 2.2927252413019077, 0.0), # 26
(4.424602974100088, 9.193658740530301, 7.31661644440874, 3.880965489130435, 2.2543802884615385, 0.0, 6.574781861413045, 9.017521153846154, 5.821448233695653, 4.877744296272493, 2.2984146851325753, 0.0), # 27
(4.438431516437421, 9.212821164421996, 7.320562285775494, 3.8831958937198072, 2.256104487179487, 0.0, 6.570748671497586, 9.024417948717948, 5.824793840579711, 4.8803748571836625, 2.303205291105499, 0.0), # 28
(4.4510735976977855, 9.228298247404602, 7.322948760175664, 3.884546225845411, 2.257148878205128, 0.0, 6.566654612016909, 9.028595512820512, 5.826819338768117, 4.881965840117109, 2.3070745618511506, 0.0), # 29
(4.4625, 9.24, 7.32375, 3.885, 2.2575000000000003, 0.0, 6.562500000000001, 9.030000000000001, 5.8275, 4.8825, 2.31, 0.0), # 30
(4.47319183983376, 9.249720255681815, 7.323149356884057, 3.884918047385621, 2.257372225177305, 0.0, 6.556726763701484, 9.02948890070922, 5.827377071078432, 4.882099571256038, 2.312430063920454, 0.0), # 31
(4.4836528452685425, 9.259312045454546, 7.3213644202898545, 3.884673790849673, 2.2569916312056737, 0.0, 6.547834661835751, 9.027966524822695, 5.82701068627451, 4.880909613526569, 2.3148280113636366, 0.0), # 32
(4.493887715792838, 9.268774176136363, 7.3184206793478275, 3.8842696323529413, 2.2563623138297872, 0.0, 6.535910757121439, 9.025449255319149, 5.826404448529412, 4.878947119565218, 2.3171935440340907, 0.0), # 33
(4.503901150895141, 9.278105454545454, 7.314343623188405, 3.8837079738562093, 2.2554883687943263, 0.0, 6.521042112277196, 9.021953475177305, 5.825561960784314, 4.876229082125604, 2.3195263636363634, 0.0), # 34
(4.513697850063939, 9.287304687499997, 7.3091587409420296, 3.882991217320261, 2.2543738918439717, 0.0, 6.503315790021656, 9.017495567375887, 5.824486825980392, 4.872772493961353, 2.3218261718749993, 0.0), # 35
(4.523282512787724, 9.296370681818182, 7.302891521739131, 3.8821217647058828, 2.253022978723404, 0.0, 6.482818853073463, 9.012091914893617, 5.823182647058824, 4.868594347826087, 2.3240926704545455, 0.0), # 36
(4.532659838554988, 9.305302244318183, 7.295567454710145, 3.881102017973856, 2.2514397251773044, 0.0, 6.4596383641512585, 9.005758900709218, 5.821653026960784, 4.86371163647343, 2.3263255610795457, 0.0), # 37
(4.5418345268542195, 9.314098181818181, 7.287212028985508, 3.8799343790849674, 2.249628226950355, 0.0, 6.433861385973679, 8.99851290780142, 5.819901568627452, 4.858141352657005, 2.3285245454545453, 0.0), # 38
(4.5508112771739135, 9.322757301136363, 7.277850733695652, 3.87862125, 2.247592579787234, 0.0, 6.40557498125937, 8.990370319148935, 5.817931875, 4.8519004891304345, 2.330689325284091, 0.0), # 39
(4.559594789002558, 9.33127840909091, 7.267509057971015, 3.8771650326797387, 2.245336879432624, 0.0, 6.37486621272697, 8.981347517730496, 5.815747549019608, 4.845006038647344, 2.3328196022727274, 0.0), # 40
(4.568189761828645, 9.3396603125, 7.256212490942029, 3.8755681290849675, 2.2428652216312055, 0.0, 6.34182214309512, 8.971460886524822, 5.813352193627452, 4.837474993961353, 2.334915078125, 0.0), # 41
(4.576600895140665, 9.34790181818182, 7.2439865217391315, 3.8738329411764707, 2.2401817021276598, 0.0, 6.3065298350824595, 8.960726808510639, 5.810749411764706, 4.829324347826088, 2.336975454545455, 0.0), # 42
(4.584832888427111, 9.356001732954544, 7.230856639492753, 3.8719618709150327, 2.2372904166666667, 0.0, 6.26907635140763, 8.949161666666667, 5.80794280637255, 4.820571092995169, 2.339000433238636, 0.0), # 43
(4.592890441176471, 9.363958863636363, 7.216848333333333, 3.8699573202614377, 2.2341954609929076, 0.0, 6.229548754789272, 8.93678184397163, 5.804935980392157, 4.811232222222222, 2.3409897159090907, 0.0), # 44
(4.600778252877237, 9.371772017045453, 7.201987092391306, 3.8678216911764705, 2.230900930851064, 0.0, 6.188034107946028, 8.923603723404256, 5.801732536764706, 4.80132472826087, 2.3429430042613633, 0.0), # 45
(4.6085010230179035, 9.379440000000002, 7.186298405797103, 3.8655573856209147, 2.2274109219858156, 0.0, 6.144619473596536, 8.909643687943262, 5.798336078431372, 4.790865603864735, 2.3448600000000006, 0.0), # 46
(4.616063451086957, 9.386961619318182, 7.16980776268116, 3.8631668055555552, 2.223729530141844, 0.0, 6.099391914459438, 8.894918120567375, 5.794750208333333, 4.77987184178744, 2.3467404048295455, 0.0), # 47
(4.623470236572891, 9.394335681818182, 7.152540652173913, 3.8606523529411763, 2.21986085106383, 0.0, 6.052438493253375, 8.87944340425532, 5.790978529411765, 4.7683604347826085, 2.3485839204545456, 0.0), # 48
(4.630726078964194, 9.401560994318181, 7.134522563405797, 3.8580164297385626, 2.2158089804964543, 0.0, 6.003846272696985, 8.863235921985817, 5.787024644607844, 4.7563483756038645, 2.3503902485795454, 0.0), # 49
(4.6378356777493615, 9.408636363636361, 7.115778985507247, 3.8552614379084966, 2.211578014184397, 0.0, 5.953702315508913, 8.846312056737588, 5.782892156862745, 4.743852657004831, 2.3521590909090904, 0.0), # 50
(4.6448037324168805, 9.415560596590907, 7.096335407608696, 3.852389779411765, 2.2071720478723407, 0.0, 5.902093684407797, 8.828688191489363, 5.778584669117648, 4.73089027173913, 2.353890149147727, 0.0), # 51
(4.651634942455243, 9.4223325, 7.0762173188405795, 3.84940385620915, 2.2025951773049646, 0.0, 5.849107442112278, 8.810380709219858, 5.774105784313726, 4.717478212560386, 2.355583125, 0.0), # 52
(4.658334007352941, 9.428950880681818, 7.055450208333333, 3.8463060702614382, 2.1978514982269504, 0.0, 5.794830651340996, 8.791405992907801, 5.769459105392158, 4.703633472222222, 2.3572377201704544, 0.0), # 53
(4.6649056265984665, 9.435414545454544, 7.034059565217391, 3.843098823529412, 2.192945106382979, 0.0, 5.739350374812594, 8.771780425531915, 5.764648235294119, 4.689373043478261, 2.358853636363636, 0.0), # 54
(4.671354499680307, 9.441722301136364, 7.012070878623187, 3.8397845179738566, 2.1878800975177306, 0.0, 5.682753675245711, 8.751520390070922, 5.759676776960785, 4.674713919082125, 2.360430575284091, 0.0), # 55
(4.677685326086957, 9.447872954545453, 6.989509637681159, 3.8363655555555556, 2.1826605673758865, 0.0, 5.625127615358988, 8.730642269503546, 5.754548333333334, 4.65967309178744, 2.361968238636363, 0.0), # 56
(4.683902805306906, 9.453865312500001, 6.966401331521738, 3.832844338235294, 2.1772906117021273, 0.0, 5.566559257871065, 8.70916244680851, 5.749266507352941, 4.644267554347826, 2.3634663281250003, 0.0), # 57
(4.690011636828645, 9.459698181818181, 6.942771449275362, 3.8292232679738563, 2.1717743262411346, 0.0, 5.507135665500583, 8.687097304964539, 5.743834901960785, 4.628514299516908, 2.3649245454545453, 0.0), # 58
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59
)
passenger_allighting_rate = (
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 0
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 1
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 2
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 3
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 4
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 5
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 6
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 7
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 8
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 9
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 10
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 11
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 12
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 13
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 14
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 15
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 16
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 17
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 18
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 19
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 20
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 21
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 22
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 23
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 24
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 25
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 26
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 27
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 28
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 29
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 30
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 31
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 32
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 33
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 34
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 35
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 36
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 37
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 38
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 39
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 40
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 41
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 42
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 43
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 44
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 45
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 46
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 47
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 48
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 49
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 50
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 51
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 52
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 53
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 54
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 55
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 56
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 57
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 58
(0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 59
)
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 258194110137029475889902652135037600173
#index for seed sequence child
child_seed_index = (
1, # 0
11, # 1
)
| 113.104478
| 212
| 0.729111
| 5,147
| 37,890
| 5.365261
| 0.229065
| 0.312873
| 0.247691
| 0.46931
| 0.331631
| 0.329422
| 0.328988
| 0.328517
| 0.327865
| 0.327865
| 0
| 0.819032
| 0.119134
| 37,890
| 334
| 213
| 113.443114
| 0.008359
| 0.031961
| 0
| 0.202532
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.015823
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
7b08a843c45e9bd7cc9d4d1cf83ebc43b6bcf6c6
| 47
|
py
|
Python
|
clang_tidy_converter/__init__.py
|
yuriisk/clang-tidy-reformatter
|
2be23785e1f47b366320dd5375d3a24393a0661e
|
[
"MIT"
] | 2
|
2021-11-12T09:40:19.000Z
|
2022-02-12T18:02:14.000Z
|
clang_tidy_converter/__init__.py
|
yuriisk/clang-tidy-reformatter
|
2be23785e1f47b366320dd5375d3a24393a0661e
|
[
"MIT"
] | null | null | null |
clang_tidy_converter/__init__.py
|
yuriisk/clang-tidy-reformatter
|
2be23785e1f47b366320dd5375d3a24393a0661e
|
[
"MIT"
] | 1
|
2021-10-04T11:51:40.000Z
|
2021-10-04T11:51:40.000Z
|
from .formatter import *
from .parser import *
| 15.666667
| 24
| 0.744681
| 6
| 47
| 5.833333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170213
| 47
| 2
| 25
| 23.5
| 0.897436
| 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
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9e759a1f1e2b4a6c81ceab26476ca3ad2372eab9
| 13,885
|
py
|
Python
|
exercises/substring_word_break.py
|
David-Jianguang-Ran/LeetCodePracticeHelper
|
e76a25704eb41980b8d949ee1046a35a6a6ef0f6
|
[
"MIT"
] | null | null | null |
exercises/substring_word_break.py
|
David-Jianguang-Ran/LeetCodePracticeHelper
|
e76a25704eb41980b8d949ee1046a35a6a6ef0f6
|
[
"MIT"
] | null | null | null |
exercises/substring_word_break.py
|
David-Jianguang-Ran/LeetCodePracticeHelper
|
e76a25704eb41980b8d949ee1046a35a6a6ef0f6
|
[
"MIT"
] | null | null | null |
from base import LeetCodeProblem
class Problem(LeetCodeProblem):
# for behaviours other than exact match between solution output and expected output
# see # Testers in README.md
"""
https://leetcode.com/problems/substring-with-concatenation-of-all-words/
sliding window + match words recursively
"""
tester = "all"
def get_tests(self):
# return test cases here
return (
# each test case has the following structure
# ( parameter , expected output ),
# # OR # #
# ( (param1, param2), expected output ),
(("", []), []),
(("wordgoodgoodgoodbestword", ["word","good","best","word"]), []),
(("barfoothefoobarman", ["foo", "bar"]), [0, 9]),
(("barfoofoobarthefoobarman", ["foo", "bar", "the"]), [6, 9, 12]),
(("ababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababa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bab", ["ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba","ab","ba"]), []),
)
def solution(self, s, words):
# have fun ~ ^_^
def can_match(__string: str, __words: dict) -> bool:
# note that this function can only return true when __string exactly match words
# first we compute some descriptive stats on words
longest_word = 0
total_chars = 0
for each_word, count in __words.items():
if len(each_word) > longest_word:
longest_word = len(each_word)
total_chars += len(each_word) * count
# bail out early if matching is impossible
if len(__string) < total_chars:
return False
elif total_chars == 0: # <= matching finished, yay
return True
# then we do a sliding window and find match in words
pointer = 1
while pointer <= longest_word:
selected_word = __string[:pointer]
if selected_word in __words and __words[selected_word] > 0:
# call self with the resting of string and words
new_words = __words.copy()
new_words[selected_word] -= 1
if can_match(__string[pointer:], new_words):
return True
else:
pointer += 1
else:
pointer += 1
# finished iteration, no match found
return False
# make a mapping of words and count
dictionary = {}
for each_word in words:
try:
dictionary[each_word] += 1
except KeyError:
dictionary[each_word] = 1
# iterate through source string
found_answer = []
for i in range(len(s)):
if can_match(s[i:], dictionary):
found_answer.append(i)
return found_answer
# instanciate your Problem class and run
prob = Problem()
prob.run()
| 165.297619
| 11,026
| 0.858336
| 502
| 13,885
| 23.641434
| 0.282869
| 0.033704
| 0.050051
| 0.066734
| 0.033704
| 0.033704
| 0.033704
| 0.033704
| 0.033704
| 0.033704
| 0
| 0.001407
| 0.078934
| 13,885
| 83
| 11,027
| 167.289157
| 0.926578
| 0.058624
| 0
| 0.163265
| 0
| 0
| 0.805833
| 0.771144
| 0
| 1
| 0
| 0
| 0
| 1
| 0.061224
| false
| 0
| 0.020408
| 0.020408
| 0.244898
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
7b3b6f74d340ae3d349fcae769dcf47b44112864
| 21
|
py
|
Python
|
__init__.py
|
zehanort/oclude
|
4f712cf42f9c8b83a3ad6f2df2f96126986d735e
|
[
"MIT"
] | 4
|
2020-06-12T18:20:07.000Z
|
2022-01-08T19:06:01.000Z
|
__init__.py
|
zehanort/oclude
|
4f712cf42f9c8b83a3ad6f2df2f96126986d735e
|
[
"MIT"
] | 20
|
2020-03-20T21:16:09.000Z
|
2020-07-16T21:16:15.000Z
|
__init__.py
|
zehanort/oclude
|
4f712cf42f9c8b83a3ad6f2df2f96126986d735e
|
[
"MIT"
] | 1
|
2020-07-21T01:22:35.000Z
|
2020-07-21T01:22:35.000Z
|
from oclude import *
| 10.5
| 20
| 0.761905
| 3
| 21
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 21
| 1
| 21
| 21
| 0.941176
| 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
| 1
| 0
|
0
| 6
|
7b4d9e767f2f92a18af6fc676c9d9c92618c2a86
| 21
|
py
|
Python
|
resources/lib/mockito/mockito/__init__.py
|
bopopescu/ServerStatus
|
a883598248ad6f5273eb3be498e3b04a1fab6510
|
[
"MIT"
] | null | null | null |
resources/lib/mockito/mockito/__init__.py
|
bopopescu/ServerStatus
|
a883598248ad6f5273eb3be498e3b04a1fab6510
|
[
"MIT"
] | 1
|
2015-04-21T22:05:02.000Z
|
2015-04-22T22:27:15.000Z
|
resources/lib/mockito/mockito/__init__.py
|
GetSomeBlocks/Score_Soccer
|
a883598248ad6f5273eb3be498e3b04a1fab6510
|
[
"MIT"
] | 2
|
2015-09-29T16:31:43.000Z
|
2020-07-26T03:41:10.000Z
|
from mockito import *
| 21
| 21
| 0.809524
| 3
| 21
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 21
| 1
| 21
| 21
| 0.944444
| 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
| 1
| 0
|
0
| 6
|
7b8eb7f3b2a6353af810991df867eceb86a9fb45
| 581
|
py
|
Python
|
octicons16px/sync.py
|
andrewp-as-is/octicons16px.py
|
1272dc9f290619d83bd881e87dbd723b0c48844c
|
[
"Unlicense"
] | 1
|
2021-01-28T06:47:39.000Z
|
2021-01-28T06:47:39.000Z
|
octicons16px/sync.py
|
andrewp-as-is/octicons16px.py
|
1272dc9f290619d83bd881e87dbd723b0c48844c
|
[
"Unlicense"
] | null | null | null |
octicons16px/sync.py
|
andrewp-as-is/octicons16px.py
|
1272dc9f290619d83bd881e87dbd723b0c48844c
|
[
"Unlicense"
] | null | null | null |
OCTICON_SYNC = """
<svg class="octicon octicon-sync" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" width="16" height="16"><path fill-rule="evenodd" d="M8 2.5a5.487 5.487 0 00-4.131 1.869l1.204 1.204A.25.25 0 014.896 6H1.25A.25.25 0 011 5.75V2.104a.25.25 0 01.427-.177l1.38 1.38A7.001 7.001 0 0114.95 7.16a.75.75 0 11-1.49.178A5.501 5.501 0 008 2.5zM1.705 8.005a.75.75 0 01.834.656 5.501 5.501 0 009.592 2.97l-1.204-1.204a.25.25 0 01.177-.427h3.646a.25.25 0 01.25.25v3.646a.25.25 0 01-.427.177l-1.38-1.38A7.001 7.001 0 011.05 8.84a.75.75 0 01.656-.834z"></path></svg>
"""
| 116.2
| 556
| 0.678141
| 150
| 581
| 2.62
| 0.486667
| 0.061069
| 0.076336
| 0.071247
| 0.231552
| 0.142494
| 0.076336
| 0
| 0
| 0
| 0
| 0.514451
| 0.106713
| 581
| 4
| 557
| 145.25
| 0.242775
| 0
| 0
| 0
| 0
| 0.333333
| 0.962069
| 0.213793
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
cdbf4f455b7925d33ecf060eece36b60ddd7af2e
| 41
|
py
|
Python
|
canros/__init__.py
|
davidlenfesty/canros
|
931c07c195d0a22aa08291ab5945f023c34f8c86
|
[
"BSD-2-Clause"
] | null | null | null |
canros/__init__.py
|
davidlenfesty/canros
|
931c07c195d0a22aa08291ab5945f023c34f8c86
|
[
"BSD-2-Clause"
] | null | null | null |
canros/__init__.py
|
davidlenfesty/canros
|
931c07c195d0a22aa08291ab5945f023c34f8c86
|
[
"BSD-2-Clause"
] | null | null | null |
from uavcan_msgs import Message, Service
| 20.5
| 40
| 0.853659
| 6
| 41
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121951
| 41
| 1
| 41
| 41
| 0.944444
| 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
| 1
| 0
|
0
| 6
|
a822281426ea43bef7c8be3e37029fafde19f183
| 21
|
py
|
Python
|
modules/ldapi/__init__.py
|
fingerecho/proms-4.0
|
6c3a1fd62c9394761664e100fc1dde50fd79dc11
|
[
"CC-BY-4.0"
] | 2
|
2019-11-23T03:56:28.000Z
|
2019-12-03T15:48:34.000Z
|
modules/ldapi/__init__.py
|
fingerecho/proms-4.0
|
6c3a1fd62c9394761664e100fc1dde50fd79dc11
|
[
"CC-BY-4.0"
] | null | null | null |
modules/ldapi/__init__.py
|
fingerecho/proms-4.0
|
6c3a1fd62c9394761664e100fc1dde50fd79dc11
|
[
"CC-BY-4.0"
] | 3
|
2019-04-12T18:09:35.000Z
|
2020-03-14T14:38:45.000Z
|
from .ldapi import *
| 10.5
| 20
| 0.714286
| 3
| 21
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 21
| 1
| 21
| 21
| 0.882353
| 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
| 1
| 0
|
0
| 6
|
a8355b743eef327e545b8b1acbddce301bdeef72
| 46
|
py
|
Python
|
hlrl/core/vision/__init__.py
|
Chainso/HLRL
|
584f4ed2fa4d8b311a21dbd862ec9434833dd7cd
|
[
"MIT"
] | null | null | null |
hlrl/core/vision/__init__.py
|
Chainso/HLRL
|
584f4ed2fa4d8b311a21dbd862ec9434833dd7cd
|
[
"MIT"
] | null | null | null |
hlrl/core/vision/__init__.py
|
Chainso/HLRL
|
584f4ed2fa4d8b311a21dbd862ec9434833dd7cd
|
[
"MIT"
] | null | null | null |
from .frame_handler import WindowsFrameHandler
| 46
| 46
| 0.913043
| 5
| 46
| 8.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.065217
| 46
| 1
| 46
| 46
| 0.953488
| 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
| 1
| 0
|
0
| 6
|
b51fef4b0c98632b5fc7523c3e57c59844a114c1
| 202
|
py
|
Python
|
buffon_simulator/__main__.py
|
sohnryang/buffon-needle-simulator
|
b56529f7f2b3cf1904e9a7df6b4d9fbd6a99676e
|
[
"MIT"
] | null | null | null |
buffon_simulator/__main__.py
|
sohnryang/buffon-needle-simulator
|
b56529f7f2b3cf1904e9a7df6b4d9fbd6a99676e
|
[
"MIT"
] | null | null | null |
buffon_simulator/__main__.py
|
sohnryang/buffon-needle-simulator
|
b56529f7f2b3cf1904e9a7df6b4d9fbd6a99676e
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
"""__main__.py"""
from sys import argv
import buffon_simulator
if len(argv) > 1:
buffon_simulator.run_simulation(int(argv[1]))
else:
buffon_simulator.run_simulation(1500)
| 22.444444
| 49
| 0.747525
| 30
| 202
| 4.733333
| 0.666667
| 0.316901
| 0.253521
| 0.394366
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039326
| 0.118812
| 202
| 9
| 50
| 22.444444
| 0.758427
| 0.163366
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
b523211705784fe9fd42d98b2857270a215a0bb6
| 110
|
py
|
Python
|
src/ItemsTab/__init__.py
|
AndrewGrim/MonsterHunterWorldDatabase
|
a904647f5499926e46a64d884a2ffebe38dd5407
|
[
"MIT"
] | 1
|
2020-02-17T00:16:01.000Z
|
2020-02-17T00:16:01.000Z
|
src/ItemsTab/__init__.py
|
AndrewGrim/MonsterHunterWorldDatabase
|
a904647f5499926e46a64d884a2ffebe38dd5407
|
[
"MIT"
] | null | null | null |
src/ItemsTab/__init__.py
|
AndrewGrim/MonsterHunterWorldDatabase
|
a904647f5499926e46a64d884a2ffebe38dd5407
|
[
"MIT"
] | 1
|
2020-06-26T06:54:00.000Z
|
2020-06-26T06:54:00.000Z
|
from .ItemsTab import *
from .Item import *
from .CombinationObtaining import *
from .RewardObtaining import *
| 27.5
| 35
| 0.790909
| 12
| 110
| 7.25
| 0.5
| 0.344828
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 110
| 4
| 36
| 27.5
| 0.915789
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 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
| 1
| 0
| 1
| 0
|
0
| 6
|
b59ad94a5ad03a9a5ef7b2b7ed1603bfc9ab660b
| 24
|
py
|
Python
|
demo_scheduler/models/__init__.py
|
digitalsatori/odoo-demo-addons-tutorial
|
8eb56156ac55f317f90bca089886c392556759c2
|
[
"MIT"
] | 57
|
2020-06-22T05:28:11.000Z
|
2022-03-25T08:15:08.000Z
|
demo_scheduler/models/__init__.py
|
digitalsatori/odoo-demo-addons-tutorial
|
8eb56156ac55f317f90bca089886c392556759c2
|
[
"MIT"
] | 2
|
2020-11-20T07:11:27.000Z
|
2022-03-30T00:20:29.000Z
|
demo_scheduler/models/__init__.py
|
digitalsatori/odoo-demo-addons-tutorial
|
8eb56156ac55f317f90bca089886c392556759c2
|
[
"MIT"
] | 29
|
2020-07-04T15:24:01.000Z
|
2022-03-28T01:29:03.000Z
|
from . import scheduler
| 12
| 23
| 0.791667
| 3
| 24
| 6.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 24
| 1
| 24
| 24
| 0.95
| 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
| 1
| 0
|
0
| 6
|
8d2d25d0ed7141cb39e7313f262f5e351361ecb8
| 334
|
py
|
Python
|
tests/test_bookops_worldcat.py
|
Mfgloger/bookops-worldcat
|
770828a040dc11a777192809273c738cd789f052
|
[
"MIT"
] | 18
|
2020-05-01T13:35:12.000Z
|
2022-03-25T15:16:12.000Z
|
tests/test_bookops_worldcat.py
|
Mfgloger/bookops-worldcat
|
770828a040dc11a777192809273c738cd789f052
|
[
"MIT"
] | 37
|
2020-04-15T00:24:18.000Z
|
2022-03-31T14:07:24.000Z
|
tests/test_bookops_worldcat.py
|
Mfgloger/bookops-worldcat
|
770828a040dc11a777192809273c738cd789f052
|
[
"MIT"
] | 6
|
2020-04-27T23:25:15.000Z
|
2020-10-05T23:35:07.000Z
|
# -*- coding: utf-8 -*-
def test_version():
from bookops_worldcat import __version__
def test_title():
from bookops_worldcat import __title__
def test_WorldcatAccessToken_import():
from bookops_worldcat import WorldcatAccessToken
def test_MetadataSession_import():
from bookops_worldcat import MetadataSession
| 18.555556
| 52
| 0.778443
| 37
| 334
| 6.540541
| 0.351351
| 0.115702
| 0.31405
| 0.413223
| 0.256198
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003559
| 0.158683
| 334
| 17
| 53
| 19.647059
| 0.857651
| 0.062874
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0.75
| 0
| 1.25
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
8d3e7d1a11e98f8f3f9b85a1ad1f5bd15d1eef36
| 22,610
|
py
|
Python
|
tests/integration_test.py
|
javilagomez/auto-changelog
|
644e582b2612773cecd1901c8001f78fd6457bc5
|
[
"MIT"
] | 63
|
2016-10-05T09:39:19.000Z
|
2021-01-16T08:14:28.000Z
|
tests/integration_test.py
|
javilagomez/auto-changelog
|
644e582b2612773cecd1901c8001f78fd6457bc5
|
[
"MIT"
] | 82
|
2016-07-19T21:16:28.000Z
|
2021-01-16T08:52:47.000Z
|
tests/integration_test.py
|
javilagomez/auto-changelog
|
644e582b2612773cecd1901c8001f78fd6457bc5
|
[
"MIT"
] | 28
|
2016-09-30T19:19:35.000Z
|
2020-10-15T19:02:33.000Z
|
import logging
import os
import pytest
import subprocess
from datetime import date
from click.testing import CliRunner
from auto_changelog.__main__ import main
@pytest.fixture
def commands():
return []
@pytest.fixture
def path_project():
return os.getcwd()
@pytest.fixture
def test_repo(tmp_path, commands):
cwd = os.getcwd()
os.chdir(str(tmp_path))
init_commands = [
"git init -q",
"git config user.name 'John Doe'",
"git config user.email john.doe@email",
"git config commit.gpgsign false", # will prevent gpg pass failures
]
for command in init_commands + commands:
# shell argument fixes error for strings. Details in link below:
# https://stackoverflow.com/questions/9935151/popen-error-errno-2-no-such-file-or-directory
subprocess.run(command, shell=True)
yield str(tmp_path)
os.chdir(cwd)
@pytest.fixture
def runner():
return CliRunner(mix_stderr=False)
@pytest.fixture
def changelog_name():
return "CHANGELOG.md"
@pytest.fixture
def open_changelog(test_repo, changelog_name):
file = None
def _open_changelog():
nonlocal file
file = open(changelog_name, "r")
return file
yield _open_changelog
if file:
file.close()
def test_help(runner):
result = runner.invoke(main, ["--help"])
assert result.exit_code == 0, result.stderr
assert result.output
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_empty_repo(runner, open_changelog):
"""JS test notes:
* js generates H3 instead of H1
* js contains explanation what will be content of the file - I don't think this is necessary
* js contains "Generated by auto-changelog" credentials
"""
result = runner.invoke(main)
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert changelog == "# Changelog\n"
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_option_repo(test_repo, runner, open_changelog):
result = runner.invoke(main, ["--path-repo", test_repo])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert changelog == "# Changelog\n"
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_option_title(runner, open_changelog):
result = runner.invoke(main, ["--title", "Title"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert changelog == "# Title\n"
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_option_description(runner, open_changelog):
result = runner.invoke(main, ["--description", "My description"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert changelog == "# Changelog\n\nMy description\n"
@pytest.mark.parametrize("changelog_name", ["a.out"])
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_option_output(runner, open_changelog):
result = runner.invoke(main, ["--output", "a.out"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert changelog == "# Changelog\n"
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add upstream git@github.com:Michael-F-Bryan/auto-changelog.git",
"git remote add origin git@github.com:KeNaCo/auto-changelog.git",
]
],
)
def test_option_remote(runner, open_changelog):
"""JS test notes:
* commit not recognized or included - a bug: https://github.com/cookpete/auto-changelog/issues/174
"""
result = runner.invoke(main, ["--remote", "upstream", "--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file [#1](https://github.com/Michael-F-Bryan/auto-changelog/issues/1)\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add upstream git@github.com:Michael-F-Bryan/auto-changelog.git",
"git remote add origin git@github.com:KeNaCo/auto-changelog.git",
]
],
)
def test_option_default_remote(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"]) # --remote default: origin
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file [#1](https://github.com/KeNaCo/auto-changelog/issues/1)\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add upstream git@github.com:Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_default_missing_remote(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"]) # --remote default: origin
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_latest_version(runner, open_changelog):
result = runner.invoke(main, ["--latest-version", "1.0.0"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## 1.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file [#1](https://github.com/Michael-F-Bryan/auto-changelog/issues/1)\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
]
],
)
def test_option_unreleased(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_skipping_unreleased(runner, open_changelog):
result = runner.invoke(main)
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert "# Changelog\n" == changelog
assert "## Unreleased" not in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_issue_url(runner, open_changelog):
result = runner.invoke(main, ["--issue-url", "issues.custom.com/{id}", "--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file [#1](issues.custom.com/1)\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file PRO-1"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_issue_pattern(runner, open_changelog):
result = runner.invoke(
main,
["--issue-pattern", r"([a-zA-Z][a-zA-Z][a-zA-Z]-\d+)", "--issue-url", "issues.custom.com/{id}", "--unreleased"],
)
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file [PRO-1](issues.custom.com/PRO-1)\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file PRO-1"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_invalid_issue_pattern(runner, open_changelog):
result = runner.invoke(
main,
["--issue-pattern", r" [a-zA-Z][a-zA-Z][a-zA-Z]-\d+", "--issue-url", "issues.custom.com/{id}", "--unreleased"],
)
assert result.exit_code != 0, result.stderr
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_option_stdout(runner, open_changelog):
result = runner.invoke(main, ["--stdout"])
assert result.exit_code == 0, result.stderr
assert "# Changelog\n\n" == result.output
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file"',
"git tag custom-tag",
'git commit --allow-empty -q -m "chore: Change"',
"git tag 1.0.0",
'git commit --allow-empty -q -m "chore: Change2"'
"git tag v2.0.0"
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_tag_pattern(runner, open_changelog):
"""JS test notes:
* we are using full-match but JS is using match
"""
result = runner.invoke(main, ["--tag-pattern", r"\d+.\d+.\d+"])
assert result.exit_code == 0, result.stderr
changelog = open_changelog().read()
assert "1.0.0" in changelog
assert_content = (
f"# Changelog\n\n## 1.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n"
f"* Add file\n#### Others\n\n* Change\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file"',
"git tag v-something",
'git commit --allow-empty -q -m "chore: Change"',
"git tag 1.0.0",
"git tag v2.0.0",
'git commit --allow-empty -q -m "chore: Change2"',
"git tag v3.0.0",
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_option_tag_prefix(runner, open_changelog):
"""JS test notes:
* JS version is a mess, reported https://github.com/cookpete/auto-changelog/issues/193
"""
result = runner.invoke(main, ["--tag-prefix", "v"])
assert result.exit_code == 0, result.exc_info
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## v3.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### Others\n\n* Change2\n\n"
f"Full set of changes: [`v2.0.0...v3.0.0`]"
f"(https://github.com/Michael-F-Bryan/auto-changelog/compare/v2.0.0...v3.0.0)\n\n"
f"## v2.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file\n"
f"#### Others\n\n* Change\n"
)
assert changelog == assert_content
assert "1.0.0" not in changelog
assert "v-something" not in changelog
assert "v2.0.0" in changelog
assert "v3.0.0" in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file"',
"git tag release-1",
'git commit --allow-empty -q -m "chore: Change"',
"git tag 1",
"git tag release-1.2.3",
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_tag_prefix_and_pattern_combination(runner, open_changelog):
"""Combination of prefix and pattern work in a way that first prefix tags are filtered,
then tag - (minus) prefix part is checked with the pattern.
JS test notes:
* includes also release-1.2.3
"""
result = runner.invoke(main, ["--tag-prefix", "release-", "--tag-pattern", r"\d"])
assert result.exit_code == 0, result.stderr
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## release-1 ({date.today().strftime('%Y-%m-%d')})\n\n" f"#### New Features\n\n* Add file\n"
)
assert changelog == assert_content
assert "## 1 " not in changelog
assert "release-1.2.3" not in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file PRO-1"',
'git commit --allow-empty -q -m "fix: Some file fix"',
"git tag start",
"git tag 1.0.0",
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_starting_commit(test_repo, runner, open_changelog):
"""JS test notes:
* not supported by JS
* JS have --starting-version [tag] which is more specific variant of this attribute
* maybe test also different references than tag?
"""
result = runner.invoke(main, ["--starting-commit", "start"])
assert result.exit_code == 0, result.stderr
changelog = open_changelog().read()
assert_content = f"# Changelog\n\n## 1.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### Fixes\n\n* Some file fix\n"
assert changelog == assert_content
assert "Add file PRO-1" not in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "fix: Some file fix"',
"git tag 1.0.0",
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_starting_commit_is_only_commit(runner, open_changelog):
"""JS test notes:
* not supported by JS (see test above)
"""
result = runner.invoke(main, ["--starting-commit", "1.0.0"])
assert result.exit_code == 0, result.stderr
changelog = open_changelog().read()
assert_content = f"# Changelog\n\n## 1.0.0 ({date.today().strftime('%Y-%m-%d')})\n\n#### Fixes\n\n* Some file fix\n"
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "fix: Some file fix"',
"git tag 1.0.0",
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_starting_commit_not_exist(test_repo, runner, open_changelog):
"""JS test notes:
* not supported by JS (see test above)
"""
result = runner.invoke(main, ["--starting-commit", "nonexist"])
assert result.exit_code != 0, result.stderr
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file PRO-1"',
"git tag stop",
'git commit --allow-empty -q -m "fix: Some file fix"',
"git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git",
]
],
)
def test_stopping_commit(runner, open_changelog):
result = runner.invoke(main, ["--stopping-commit", "stop", "--unreleased"])
assert result.exit_code == 0, result.stderr
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file PRO-1\n"
)
assert changelog == assert_content
assert "Some file fix" not in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\n"',
]
],
)
def test_empty_line_body(test_repo, runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\nBody line"',
]
],
)
def test_single_line_body(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[["git commit --allow-empty -q -m 'feat: Add file #1\n\nBody line 1\nBody line 2'"]],
)
def test_double_line_body(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
print(changelog)
assert "Add file #1" in changelog
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\nBody line 1\nBody line 2\nBody line 3"',
]
],
)
def test_triple_line_body(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\nBody paragraph 1\n\nBody paragraph 2"',
]
],
)
def test_multi_paragraph_body(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\nBody line\n\nFooter: first footer"',
]
],
)
def test_single_line_body_single_footer(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat: Add file #1\n\nBody line\n\n'
'Footer: first footer\nFooter: second footer"',
]
],
)
def test_single_line_body_double_footer(runner, open_changelog):
result = runner.invoke(main, ["--unreleased"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n#### New Features\n\n* Add file #1\n"
)
assert changelog == assert_content
@pytest.mark.parametrize(
"commands",
[
[
'git commit --allow-empty -q -m "feat(scope): Add file #1\n\nBody line 1\nBody line 2\nBody line 3"',
]
],
)
def test_custom_template(path_project, runner, open_changelog):
custom_template_path = os.path.join(path_project, "tests/custom_template/custom_template.jinja2")
result = runner.invoke(main, ["--unreleased", "--template", custom_template_path])
assert result.exit_code == 0, result.stderr
assert result.output == ""
changelog = open_changelog().read()
assert_content = (
f"# Changelog\n\n## Unreleased ({date.today().strftime('%Y-%m-%d')})\n\n"
f"#### New Features\n\n* **scope**: Add file #1\n"
)
assert changelog == assert_content
def test_custom_template_invalid_file(path_project, runner, caplog):
result = runner.invoke(main, ["--template", "nonsense"])
assert result.exit_code != 0, result.stderr
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_debug(caplog, runner, open_changelog):
caplog.set_level(logging.DEBUG)
result = runner.invoke(main, ["--debug"])
assert result.exit_code == 0, result.stderr
assert result.output == ""
assert "Logging level has been set to DEBUG" in caplog.text
@pytest.mark.parametrize(
"commands",
[["git remote add origin https://github.com/Michael-F-Bryan/auto-changelog.git"]],
)
def test_no_debug(caplog, runner, open_changelog):
caplog.set_level(logging.DEBUG)
result = runner.invoke(main)
assert result.exit_code == 0, result.stderr
assert result.output == ""
assert "Logging level has been set to DEBUG" not in caplog.text
| 32.532374
| 120
| 0.618576
| 2,978
| 22,610
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|
0
| 6
|
8d481ce5e88529c57337c4f48353b5122dbceb2a
| 29
|
py
|
Python
|
basic/basic_tmp/__init__.py
|
ealogar/curso-python
|
8b2bffa1d6aac32b029f18e8769c98aac3d5395f
|
[
"Apache-2.0"
] | 11
|
2016-09-27T08:07:59.000Z
|
2017-09-26T12:40:04.000Z
|
basic/basic_tmp/__init__.py
|
ealogar/curso-python
|
8b2bffa1d6aac32b029f18e8769c98aac3d5395f
|
[
"Apache-2.0"
] | null | null | null |
basic/basic_tmp/__init__.py
|
ealogar/curso-python
|
8b2bffa1d6aac32b029f18e8769c98aac3d5395f
|
[
"Apache-2.0"
] | 3
|
2017-05-23T09:41:24.000Z
|
2021-02-27T15:01:48.000Z
|
from my_modules import func
| 9.666667
| 27
| 0.827586
| 5
| 29
| 4.6
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| 0.172414
| 29
| 2
| 28
| 14.5
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| 1
| 0
|
0
| 6
|
8d4a671cdd58f3d7eb2e86995ceb93b038856bae
| 28
|
py
|
Python
|
src/odroid_go/utils/battery/__init__.py
|
willemserruys/Snake
|
5302b02e6f7bf04561e97bf001f758e6ddbaa17b
|
[
"MIT"
] | null | null | null |
src/odroid_go/utils/battery/__init__.py
|
willemserruys/Snake
|
5302b02e6f7bf04561e97bf001f758e6ddbaa17b
|
[
"MIT"
] | null | null | null |
src/odroid_go/utils/battery/__init__.py
|
willemserruys/Snake
|
5302b02e6f7bf04561e97bf001f758e6ddbaa17b
|
[
"MIT"
] | null | null | null |
from .battery import Battery
| 28
| 28
| 0.857143
| 4
| 28
| 6
| 0.75
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| 0.107143
| 28
| 1
| 28
| 28
| 0.96
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| 1
| 0
| 1
| 0
|
0
| 6
|
a5cf0e03ca2c674d317c22b4e746e4a5758f1127
| 42
|
py
|
Python
|
libs/yowsup/yowsup/yowsup/layers/protocol_media/__init__.py
|
akshitpradhan/TomHack
|
837226e7b38de1140c19bc2d478eeb9e379ed1fd
|
[
"MIT"
] | 22
|
2017-07-14T20:01:17.000Z
|
2022-03-08T14:22:39.000Z
|
libs/yowsup/yowsup/yowsup/layers/protocol_media/__init__.py
|
akshitpradhan/TomHack
|
837226e7b38de1140c19bc2d478eeb9e379ed1fd
|
[
"MIT"
] | 6
|
2017-07-14T21:03:50.000Z
|
2021-06-10T19:08:32.000Z
|
libs/yowsup/yowsup/yowsup/layers/protocol_media/__init__.py
|
akshitpradhan/TomHack
|
837226e7b38de1140c19bc2d478eeb9e379ed1fd
|
[
"MIT"
] | 13
|
2017-07-14T20:13:14.000Z
|
2020-11-12T08:06:05.000Z
|
from .layer import YowMediaProtocolLayer
| 21
| 41
| 0.857143
| 4
| 42
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| 0.119048
| 42
| 1
| 42
| 42
| 0.972973
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| 1
| 0
|
0
| 6
|
a5f7a0ae7107fd3bf959351ba54ee2a45058eeb4
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydev_ipython/matplotlibtools.py
|
GiulianaPola/select_repeats
|
17a0d053d4f874e42cf654dd142168c2ec8fbd11
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydev_ipython/matplotlibtools.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/debugpy/_vendored/pydevd/pydev_ipython/matplotlibtools.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/2c/fa/a7/0952e0d3f53dc6fdd102966159c421ae584d080598a6be22861567224b
| 96
| 96
| 0.895833
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| 96
| 9.555556
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| 0.458333
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| 96
| 1
| 96
| 96
| 0.4375
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| null | null | 0
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| 0
| 0
|
0
| 6
|
93980eeb0943ea622f4dd0add91d334178961d7b
| 32
|
py
|
Python
|
pca/__init__.py
|
nielsrolf/pca
|
d39c0bbd19a27274d8ce24eacf9996ef837a0c7f
|
[
"Apache-2.0"
] | 2
|
2020-05-12T14:57:56.000Z
|
2021-04-10T14:12:14.000Z
|
pca/__init__.py
|
nielsrolf/pca
|
d39c0bbd19a27274d8ce24eacf9996ef837a0c7f
|
[
"Apache-2.0"
] | 1
|
2021-04-20T19:57:51.000Z
|
2021-04-20T19:57:51.000Z
|
pca/__init__.py
|
nielsrolf/pca
|
d39c0bbd19a27274d8ce24eacf9996ef837a0c7f
|
[
"Apache-2.0"
] | null | null | null |
from pca.pca import PCA # noqa
| 16
| 31
| 0.71875
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| 32
| 3.833333
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|
0
| 6
|
939b5d1d59de92cccb1c8fc413dd9a9b2706e618
| 10,590
|
py
|
Python
|
collection_manager/tests/services/test_CollectionProcessor.py
|
kevinmarlis/incubator-sdap-ingester
|
7ee17fdf16201c499f7bd35cf398844f2c70f046
|
[
"Apache-2.0"
] | null | null | null |
collection_manager/tests/services/test_CollectionProcessor.py
|
kevinmarlis/incubator-sdap-ingester
|
7ee17fdf16201c499f7bd35cf398844f2c70f046
|
[
"Apache-2.0"
] | 1
|
2021-05-03T22:13:11.000Z
|
2021-05-03T22:13:11.000Z
|
collection_manager/tests/services/test_CollectionProcessor.py
|
kevinmarlis/incubator-sdap-ingester
|
7ee17fdf16201c499f7bd35cf398844f2c70f046
|
[
"Apache-2.0"
] | null | null | null |
import tempfile
import yaml
import unittest
from unittest import mock
from collection_manager.entities import Collection
from collection_manager.services import CollectionProcessor
from collection_manager.services.history_manager import FileIngestionHistoryBuilder
from collection_manager.services.history_manager import GranuleStatus
from common.async_test_utils import AsyncMock, async_test
class TestCollectionProcessor(unittest.TestCase):
def test_file_supported_with_nc(self):
self.assertTrue(CollectionProcessor._file_supported("test_dir/test_granule.nc"))
def test_file_supported_with_h5(self):
self.assertTrue(CollectionProcessor._file_supported("test_dir/test_granule.h5"))
def test_file_supported_with_foo(self):
self.assertFalse(CollectionProcessor._file_supported("test_dir/test_granule.foo"))
@mock.patch('collection_manager.services.MessagePublisher', autospec=True)
def test_get_history_manager_returns_same_object(self, mock_publisher):
with tempfile.TemporaryDirectory() as history_dir:
collection_processor = CollectionProcessor(mock_publisher, FileIngestionHistoryBuilder(history_dir))
history_manager = collection_processor._get_history_manager('dataset_id')
self.assertIs(collection_processor._get_history_manager('dataset_id'), history_manager)
@mock.patch('collection_manager.services.MessagePublisher', autospec=True)
def test_get_history_manager_returns_different_object(self, mock_publisher):
with tempfile.TemporaryDirectory() as history_dir:
collection_processor = CollectionProcessor(mock_publisher, FileIngestionHistoryBuilder(history_dir))
history_manager = collection_processor._get_history_manager('foo')
self.assertIsNot(collection_processor._get_history_manager('bar'), history_manager)
def test_fill_template(self):
expected = {
'granule': {
'resource': '/granules/test_granule.nc'
},
'processors': [
{
'latitude': 'lat',
'longitude': 'lon',
'name': 'Grid',
'variable': 'test_var'
},
{'name': 'emptyTileFilter'},
{'dataset_name': 'test_dataset', 'name': 'tileSummary'},
{'name': 'generateTileId'}
],
'slicer': {
'dimension_step_sizes': {
'lat': 30,
'lon': 30,
'time': 1
},
'name': 'sliceFileByStepSize'
}
}
collection = Collection(dataset_id="test_dataset",
path="/granules/test*.nc",
projection="Grid",
slices=frozenset([('lat', 30), ('lon', 30), ('time', 1)]),
dimension_names=frozenset([
('latitude', 'lat'),
('longitude', 'lon'),
('variable', 'test_var')
]),
historical_priority=1,
forward_processing_priority=2,
date_from=None,
date_to=None)
filled = CollectionProcessor._generate_ingestion_message("/granules/test_granule.nc", collection)
generated_yaml = yaml.load(filled, Loader=yaml.FullLoader)
self.assertEqual(expected, generated_yaml)
@async_test
@mock.patch('collection_manager.services.history_manager.FileIngestionHistory', new_callable=AsyncMock)
@mock.patch('collection_manager.services.history_manager.FileIngestionHistoryBuilder', autospec=True)
@mock.patch('collection_manager.services.MessagePublisher', new_callable=AsyncMock)
async def test_process_granule_with_historical_granule(self, mock_publisher, mock_history_builder, mock_history):
mock_history.get_granule_status.return_value = GranuleStatus.DESIRED_HISTORICAL
mock_history_builder.build.return_value = mock_history
collection_processor = CollectionProcessor(mock_publisher, mock_history_builder)
collection = Collection(dataset_id="test_dataset",
path="test_path",
projection="Grid",
slices=frozenset(),
dimension_names=frozenset(),
historical_priority=1,
forward_processing_priority=2,
date_from=None,
date_to=None)
await collection_processor.process_granule("test.nc", collection)
mock_publisher.publish_message.assert_called_with(body=mock.ANY, priority=1)
mock_history.push.assert_called()
@async_test
@mock.patch('collection_manager.services.history_manager.FileIngestionHistory', new_callable=AsyncMock)
@mock.patch('collection_manager.services.history_manager.FileIngestionHistoryBuilder', autospec=True)
@mock.patch('collection_manager.services.MessagePublisher', new_callable=AsyncMock)
async def test_process_granule_with_forward_processing_granule(self,
mock_publisher,
mock_history_builder,
mock_history):
mock_history.get_granule_status.return_value = GranuleStatus.DESIRED_FORWARD_PROCESSING
mock_history_builder.build.return_value = mock_history
collection_processor = CollectionProcessor(mock_publisher, mock_history_builder)
collection = Collection(dataset_id="test_dataset",
path="test_path",
projection="Grid",
slices=frozenset(),
dimension_names=frozenset(),
historical_priority=1,
forward_processing_priority=2,
date_from=None,
date_to=None)
await collection_processor.process_granule("test.h5", collection)
mock_publisher.publish_message.assert_called_with(body=mock.ANY, priority=2)
mock_history.push.assert_called()
@async_test
@mock.patch('collection_manager.services.history_manager.FileIngestionHistory', new_callable=AsyncMock)
@mock.patch('collection_manager.services.history_manager.FileIngestionHistoryBuilder', autospec=True)
@mock.patch('collection_manager.services.MessagePublisher', new_callable=AsyncMock)
async def test_process_granule_with_forward_processing_granule_and_no_priority(self, mock_publisher,
mock_history_builder, mock_history):
mock_history.get_granule_status.return_value = GranuleStatus.DESIRED_FORWARD_PROCESSING
mock_history_builder.build.return_value = mock_history
collection_processor = CollectionProcessor(mock_publisher, mock_history_builder)
collection = Collection(dataset_id="test_dataset",
path="test_path",
projection="Grid",
slices=frozenset(),
dimension_names=frozenset(),
historical_priority=1,
date_from=None,
date_to=None)
await collection_processor.process_granule("test.h5", collection)
mock_publisher.publish_message.assert_called_with(body=mock.ANY, priority=1)
mock_history.push.assert_called()
@async_test
@mock.patch('collection_manager.services.history_manager.FileIngestionHistory', new_callable=AsyncMock)
@mock.patch('collection_manager.services.history_manager.FileIngestionHistoryBuilder', autospec=True)
@mock.patch('collection_manager.services.MessagePublisher', new_callable=AsyncMock)
async def test_process_granule_with_undesired_granule(self, mock_publisher, mock_history_builder, mock_history):
mock_history.get_granule_status.return_value = GranuleStatus.UNDESIRED
mock_history_builder.build.return_value = mock_history
collection_processor = CollectionProcessor(mock_publisher, mock_history_builder)
collection = Collection(dataset_id="test_dataset",
path="test_path",
projection="Grid",
slices=frozenset(),
dimension_names=frozenset(),
historical_priority=1,
forward_processing_priority=2,
date_from=None,
date_to=None)
await collection_processor.process_granule("test.nc", collection)
mock_publisher.publish_message.assert_not_called()
mock_history.push.assert_not_called()
@async_test
@mock.patch('collection_manager.services.history_manager.FileIngestionHistory', autospec=True)
@mock.patch('collection_manager.services.history_manager.FileIngestionHistoryBuilder', autospec=True)
@mock.patch('collection_manager.services.MessagePublisher', new_callable=AsyncMock)
async def test_process_granule_with_unsupported_file_type(self, mock_publisher, mock_history_builder, mock_history):
mock_history_builder.build.return_value = mock_history
collection_processor = CollectionProcessor(mock_publisher, mock_history_builder)
collection = Collection(dataset_id="test_dataset",
path="test_path",
projection="Grid",
slices=frozenset(),
dimension_names=frozenset(),
historical_priority=1,
forward_processing_priority=2,
date_from=None,
date_to=None)
await collection_processor.process_granule("test.foo", collection)
mock_publisher.publish_message.assert_not_called()
mock_history.push.assert_not_called()
| 52.425743
| 120
| 0.617847
| 940
| 10,590
| 6.601064
| 0.129787
| 0.060274
| 0.08058
| 0.071233
| 0.841579
| 0.824174
| 0.819339
| 0.77776
| 0.77776
| 0.77776
| 0
| 0.003804
| 0.305005
| 10,590
| 201
| 121
| 52.686567
| 0.839266
| 0
| 0
| 0.584795
| 0
| 0
| 0.149481
| 0.104438
| 0
| 0
| 0
| 0
| 0.093567
| 1
| 0.035088
| false
| 0
| 0.052632
| 0
| 0.093567
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
93a02cdbbbce69677c0e979caeaf2965c0acb77a
| 78
|
py
|
Python
|
pysrc/chainapi.py
|
learnforpractice/pyeosk
|
5fd0f0d32e0f24b78f7522b47f596e70a1b5f0e0
|
[
"MIT"
] | 15
|
2018-10-08T08:58:36.000Z
|
2022-02-25T05:35:09.000Z
|
pysrc/chainapi.py
|
learnforpractice/pyeosk
|
5fd0f0d32e0f24b78f7522b47f596e70a1b5f0e0
|
[
"MIT"
] | 7
|
2018-11-12T09:15:46.000Z
|
2022-03-25T14:52:26.000Z
|
pysrc/chainapi.py
|
learnforpractice/pyeosk
|
5fd0f0d32e0f24b78f7522b47f596e70a1b5f0e0
|
[
"MIT"
] | 8
|
2018-11-13T08:52:23.000Z
|
2021-04-24T18:22:17.000Z
|
from .chainapi_sync import ChainApi
from .chainapi_async import ChainApiAsync
| 26
| 41
| 0.871795
| 10
| 78
| 6.6
| 0.6
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 78
| 2
| 42
| 39
| 0.942857
| 0
| 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
| 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
| 6
|
93b19d904a5b089f6a34559ed7838934b9b46c42
| 71
|
py
|
Python
|
py_tdlib/constructors/keyboard_button_type_text.py
|
Mr-TelegramBot/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 24
|
2018-10-05T13:04:30.000Z
|
2020-05-12T08:45:34.000Z
|
py_tdlib/constructors/keyboard_button_type_text.py
|
MrMahdi313/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 3
|
2019-06-26T07:20:20.000Z
|
2021-05-24T13:06:56.000Z
|
py_tdlib/constructors/keyboard_button_type_text.py
|
MrMahdi313/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 5
|
2018-10-05T14:29:28.000Z
|
2020-08-11T15:04:10.000Z
|
from ..factory import Type
class keyboardButtonTypeText(Type):
pass
| 11.833333
| 35
| 0.788732
| 8
| 71
| 7
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140845
| 71
| 5
| 36
| 14.2
| 0.918033
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
f50e2e1e434c10a95e21bc8102f3e3262ecb583f
| 36
|
py
|
Python
|
app/commands/__init__.py
|
s-andrew/FlaskProductRest
|
167e44e7c379f50cf83502a5fc423cb6ef92132a
|
[
"BSD-2-Clause"
] | null | null | null |
app/commands/__init__.py
|
s-andrew/FlaskProductRest
|
167e44e7c379f50cf83502a5fc423cb6ef92132a
|
[
"BSD-2-Clause"
] | null | null | null |
app/commands/__init__.py
|
s-andrew/FlaskProductRest
|
167e44e7c379f50cf83502a5fc423cb6ef92132a
|
[
"BSD-2-Clause"
] | null | null | null |
from .init_db import InitDbCommand
| 18
| 35
| 0.833333
| 5
| 36
| 5.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.138889
| 36
| 1
| 36
| 36
| 0.935484
| 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
| 1
| 0
|
0
| 6
|
f5104c29bfa1e95d89c89eb77eb1f04db30b08e6
| 24
|
py
|
Python
|
sht30/__init__.py
|
schinckel/micropython-sht30
|
3ca0dee1d0711a99c0e65cb6618ede7d2e8ba1e1
|
[
"Apache-2.0"
] | 1
|
2021-09-06T18:02:45.000Z
|
2021-09-06T18:02:45.000Z
|
sht30/__init__.py
|
schinckel/micropython-sht30
|
3ca0dee1d0711a99c0e65cb6618ede7d2e8ba1e1
|
[
"Apache-2.0"
] | null | null | null |
sht30/__init__.py
|
schinckel/micropython-sht30
|
3ca0dee1d0711a99c0e65cb6618ede7d2e8ba1e1
|
[
"Apache-2.0"
] | 2
|
2021-02-05T19:50:54.000Z
|
2021-11-12T02:37:13.000Z
|
from .sht30 import SHT30
| 24
| 24
| 0.833333
| 4
| 24
| 5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 0.125
| 24
| 1
| 24
| 24
| 0.761905
| 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
| 1
| 0
|
0
| 6
|
f54fcb87314de323f540aee81a7ef34d27084f02
| 1,874
|
py
|
Python
|
black_scholes_dp.py
|
hegza/black-scholes-py
|
f923b1d5a1aa5bd907cf7eaad617f6594b84a047
|
[
"MIT"
] | null | null | null |
black_scholes_dp.py
|
hegza/black-scholes-py
|
f923b1d5a1aa5bd907cf7eaad617f6594b84a047
|
[
"MIT"
] | null | null | null |
black_scholes_dp.py
|
hegza/black-scholes-py
|
f923b1d5a1aa5bd907cf7eaad617f6594b84a047
|
[
"MIT"
] | null | null | null |
import numpy as np
import scipy.stats as si
def black_scholes_call_div(S, K, T, r, q, sigma):
# S: spot price
# K: strike price
# T: time to maturity
# r: interest rate
# q: rate of continuous dividend paying asset
# sigma: volatility of underlying asset
d1 = (np.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
d2 = (np.log(S / K) + (r - q - 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
call = (S * np.exp(-q * T) * si.norm.cdf(d1, 0.0, 1.0) -
K * np.exp(-r * T) * si.norm.cdf(d2, 0.0, 1.0))
return call
def black_scholes_put_div(S, K, T, r, q, sigma):
# S: spot price
# K: strike price
# T: time to maturity
# r: interest rate
# q: rate of continuous dividend paying asset
# sigma: volatility of underlying asset
d1 = (np.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
d2 = (np.log(S / K) + (r - q - 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
put = (K * np.exp(-r * T) * si.norm.cdf(-d2, 0.0, 1.0) -
S * np.exp(-q * T) * si.norm.cdf(-d1, 0.0, 1.0))
return put
def euro_vanilla_dividend(S, K, T, r, q, sigma, option='call'):
# S: spot price
# K: strike price
# T: time to maturity
# r: interest rate
# q: rate of continuous dividend paying asset
# sigma: volatility of underlying asset
d1 = (np.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
d2 = (np.log(S / K) + (r - q - 0.5 * sigma ** 2) * T) / (sigma * np.sqrt(T))
if option == 'call':
result = (S * np.exp(-q * T) * si.norm.cdf(d1, 0.0, 1.0) -
K * np.exp(-r * T) * si.norm.cdf(d2, 0.0, 1.0))
if option == 'put':
result = (K * np.exp(-r * T) * si.norm.cdf(-d2, 0.0, 1.0) -
S * np.exp(-q * T) * si.norm.cdf(-d1, 0.0, 1.0))
return result
| 30.721311
| 80
| 0.507471
| 334
| 1,874
| 2.823353
| 0.152695
| 0.019088
| 0.059385
| 0.084836
| 0.831389
| 0.825027
| 0.814422
| 0.814422
| 0.814422
| 0.814422
| 0
| 0.048855
| 0.300961
| 1,874
| 60
| 81
| 31.233333
| 0.670992
| 0.237994
| 0
| 0.416667
| 0
| 0
| 0.007807
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0
| 0.083333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
f5583b53ae96895946d0c5b3ee7f09a3c15cc57a
| 13,102
|
py
|
Python
|
etc/pending_ugens/Pitch.py
|
butayama/supriya
|
0c197324ecee4232381221880d1f40e109bb756c
|
[
"MIT"
] | 191
|
2015-11-13T02:28:42.000Z
|
2022-03-29T10:26:44.000Z
|
etc/pending_ugens/Pitch.py
|
butayama/supriya
|
0c197324ecee4232381221880d1f40e109bb756c
|
[
"MIT"
] | 130
|
2016-01-04T16:59:02.000Z
|
2022-02-26T15:37:20.000Z
|
etc/pending_ugens/Pitch.py
|
butayama/supriya
|
0c197324ecee4232381221880d1f40e109bb756c
|
[
"MIT"
] | 22
|
2016-05-04T10:32:16.000Z
|
2022-02-26T19:22:45.000Z
|
import collections
from supriya.enums import CalculationRate
from supriya.synthdefs import MultiOutUGen
class Pitch(MultiOutUGen):
"""
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch
Pitch.ar()
"""
### CLASS VARIABLES ###
_ordered_input_names = collections.OrderedDict(
'source',
'init_frequency',
'min_frequency',
'max_frequency',
'exec_frequency',
'max_bins_per_octave',
'median',
'amp_threshold',
'peak_threshold',
'down_sample',
'clar',
)
_valid_calculation_rates = None
### INITIALIZER ###
def __init__(
self,
calculation_rate=None,
amp_threshold=0.01,
clar=0,
down_sample=1,
exec_frequency=100,
init_frequency=440,
max_bins_per_octave=16,
max_frequency=4000,
median=1,
min_frequency=60,
peak_threshold=0.5,
source=None,
):
MultiOutUGen.__init__(
self,
calculation_rate=calculation_rate,
amp_threshold=amp_threshold,
clar=clar,
down_sample=down_sample,
exec_frequency=exec_frequency,
init_frequency=init_frequency,
max_bins_per_octave=max_bins_per_octave,
max_frequency=max_frequency,
median=median,
min_frequency=min_frequency,
peak_threshold=peak_threshold,
source=source,
)
### PUBLIC METHODS ###
@classmethod
def kr(
cls,
amp_threshold=0.01,
clar=0,
down_sample=1,
exec_frequency=100,
init_frequency=440,
max_bins_per_octave=16,
max_frequency=4000,
median=1,
min_frequency=60,
peak_threshold=0.5,
source=None,
):
"""
Constructs a control-rate Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.kr(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch
Pitch.kr()
Returns ugen graph.
"""
import supriya.synthdefs
calculation_rate = supriya.CalculationRate.CONTROL
ugen = cls._new_expanded(
calculation_rate=calculation_rate,
amp_threshold=amp_threshold,
clar=clar,
down_sample=down_sample,
exec_frequency=exec_frequency,
init_frequency=init_frequency,
max_bins_per_octave=max_bins_per_octave,
max_frequency=max_frequency,
median=median,
min_frequency=min_frequency,
peak_threshold=peak_threshold,
source=source,
)
return ugen
# def newFromDesc(): ...
### PUBLIC PROPERTIES ###
@property
def amp_threshold(self):
"""
Gets `amp_threshold` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.amp_threshold
0.01
Returns ugen input.
"""
index = self._ordered_input_names.index('amp_threshold')
return self._inputs[index]
@property
def clar(self):
"""
Gets `clar` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.clar
0.0
Returns ugen input.
"""
index = self._ordered_input_names.index('clar')
return self._inputs[index]
@property
def down_sample(self):
"""
Gets `down_sample` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.down_sample
1.0
Returns ugen input.
"""
index = self._ordered_input_names.index('down_sample')
return self._inputs[index]
@property
def exec_frequency(self):
"""
Gets `exec_frequency` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.exec_frequency
100.0
Returns ugen input.
"""
index = self._ordered_input_names.index('exec_frequency')
return self._inputs[index]
@property
def init_frequency(self):
"""
Gets `init_frequency` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.init_frequency
440.0
Returns ugen input.
"""
index = self._ordered_input_names.index('init_frequency')
return self._inputs[index]
@property
def max_bins_per_octave(self):
"""
Gets `max_bins_per_octave` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.max_bins_per_octave
16.0
Returns ugen input.
"""
index = self._ordered_input_names.index('max_bins_per_octave')
return self._inputs[index]
@property
def max_frequency(self):
"""
Gets `max_frequency` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.max_frequency
4000.0
Returns ugen input.
"""
index = self._ordered_input_names.index('max_frequency')
return self._inputs[index]
@property
def median(self):
"""
Gets `median` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.median
1.0
Returns ugen input.
"""
index = self._ordered_input_names.index('median')
return self._inputs[index]
@property
def min_frequency(self):
"""
Gets `min_frequency` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.min_frequency
60.0
Returns ugen input.
"""
index = self._ordered_input_names.index('min_frequency')
return self._inputs[index]
@property
def peak_threshold(self):
"""
Gets `peak_threshold` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.peak_threshold
0.5
Returns ugen input.
"""
index = self._ordered_input_names.index('peak_threshold')
return self._inputs[index]
@property
def source(self):
"""
Gets `source` input of Pitch.
::
>>> source = supriya.ugens.In.ar(bus=0)
>>> pitch = supriya.ugens.Pitch.ar(
... amp_threshold=0.01,
... clar=0,
... down_sample=1,
... exec_frequency=100,
... init_frequency=440,
... max_bins_per_octave=16,
... max_frequency=4000,
... median=1,
... min_frequency=60,
... peak_threshold=0.5,
... source=source,
... )
>>> pitch.source
OutputProxy(
source=In(
bus=0.0,
calculation_rate=CalculationRate.AUDIO,
channel_count=1
),
output_index=0
)
Returns ugen input.
"""
index = self._ordered_input_names.index('source')
return self._inputs[index]
| 27.936034
| 70
| 0.45619
| 1,204
| 13,102
| 4.707641
| 0.064784
| 0.056457
| 0.042343
| 0.067749
| 0.80681
| 0.799753
| 0.782816
| 0.73271
| 0.73271
| 0.716126
| 0
| 0.049723
| 0.42131
| 13,102
| 468
| 71
| 27.995727
| 0.697837
| 0.527553
| 0
| 0.580645
| 0
| 0
| 0.063137
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.104839
| false
| 0
| 0.032258
| 0
| 0.258065
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
f55880ff7a441979891641a7d18bb21b58321bc1
| 7,406
|
py
|
Python
|
tests/test_dagmc_query.py
|
svalinn/dagmc_stats
|
8d167eca706ee47218eb2e6a6dfef1c5d4770a40
|
[
"BSD-3-Clause"
] | 1
|
2021-03-04T14:57:30.000Z
|
2021-03-04T14:57:30.000Z
|
tests/test_dagmc_query.py
|
svalinn/dagmc_stats
|
8d167eca706ee47218eb2e6a6dfef1c5d4770a40
|
[
"BSD-3-Clause"
] | 74
|
2019-06-24T17:46:05.000Z
|
2022-02-21T12:13:23.000Z
|
tests/test_dagmc_query.py
|
svalinn/dagmc_stats
|
8d167eca706ee47218eb2e6a6dfef1c5d4770a40
|
[
"BSD-3-Clause"
] | 5
|
2019-07-05T03:06:04.000Z
|
2020-03-31T15:27:38.000Z
|
from pymoab import core, types
from pymoab.rng import Range
import dagmc_stats.DagmcFile as df
import dagmc_stats.DagmcQuery as dq
import pandas as pd
import numpy as np
import warnings
test_env = {'three_vols': 'tests/3vols.h5m',
'single_cube': 'tests/single-cube.h5m', 'pyramid': 'tests/pyramid.h5m'}
def test_pandas_data_frame():
"""Tests the initialization of pandas data frames
"""
single_cube = df.DagmcFile(test_env['single_cube'])
single_cube_query = dq.DagmcQuery(single_cube)
exp_vert_data = pd.DataFrame()
assert(single_cube_query._vert_data.equals(exp_vert_data))
exp_tri_data = pd.DataFrame()
assert(single_cube_query._tri_data.equals(exp_tri_data))
exp_surf_data = pd.DataFrame()
assert(single_cube_query._surf_data.equals(exp_surf_data))
exp_vol_data = pd.DataFrame()
assert(single_cube_query._vol_data.equals(exp_vol_data))
def test_get_entities_rootset():
"""Tests the get_entities function for rootset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
three_vols_query = dq.DagmcQuery(three_vols)
exp = [three_vols.root_set]
assert(three_vols_query.meshset_lst == exp)
def test_get_entities_vol():
"""Tests the get_entities function for volume meshset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
vol = three_vols.entityset_ranges['volumes'][0]
three_vols_query = dq.DagmcQuery(three_vols, vol)
exp = list(three_vols._my_moab_core.get_child_meshsets(vol))
assert(three_vols_query.meshset_lst == exp)
def test_get_entities_surf():
"""Tests the get_entities function for surface meshset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
surf = three_vols.entityset_ranges['surfaces'][0]
three_vols_query = dq.DagmcQuery(three_vols, surf)
exp = [surf]
assert(three_vols_query.meshset_lst == exp)
def test_get_entities_incorrect_dim():
"""Tests the get_entities function given incorrect dimension
"""
test_pass = np.full(3, False)
three_vols = df.DagmcFile(test_env['three_vols'])
# check if get_tris function generates warning for meshset with invalid dimension
vert = three_vols.entityset_ranges['nodes'][0]
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
three_vols_query = dq.DagmcQuery(three_vols, meshset=vert)
if len(w) == 1:
test_pass[0] = True
if 'Meshset is not a volume nor a surface! Rootset will be used by default.' in str(w[-1].message):
test_pass[1] = True
exp = [three_vols.root_set]
test_pass[2] = (three_vols_query.meshset_lst == exp)
assert(all(test_pass))
def test_get_tris_vol():
"""Tests the get_tris function for volume meshset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
vol = three_vols.entityset_ranges['volumes'][0]
three_vols_query = dq.DagmcQuery(three_vols, meshset=vol)
obs_tris = three_vols_query.get_tris()
exp_tris = []
meshset_lst = []
surfs = three_vols._my_moab_core.get_child_meshsets(vol)
meshset_lst.extend(surfs)
for item in meshset_lst:
exp_tris.extend(
three_vols._my_moab_core.get_entities_by_type(item, types.MBTRI))
assert(sorted(obs_tris) == sorted(exp_tris))
def test_get_tris_surf():
"""Tests the get_tris function for surface meshset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
surf = three_vols.entityset_ranges['surfaces'][0]
three_vols_query = dq.DagmcQuery(three_vols, surf)
obs_tris = three_vols_query.get_tris()
exp_tris = three_vols._my_moab_core.get_entities_by_type(
surf, types.MBTRI)
assert(sorted(obs_tris) == sorted(exp_tris))
def test_get_tris_rootset():
"""Tests the get_tris function given the rootset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
three_vols_query = dq.DagmcQuery(three_vols, meshset=three_vols.root_set)
obs_tris = three_vols_query.get_tris()
exp_tris = three_vols._my_moab_core.get_entities_by_type(
three_vols.root_set, types.MBTRI)
assert(sorted(obs_tris) == sorted(exp_tris))
def test_get_tris_dimension_incorrect():
"""Tests the get_tris function given incorrect dimension
"""
test_pass = np.full(3, False)
three_vols = df.DagmcFile(test_env['three_vols'])
# check if get_tris function generates warning for meshset with invalid dimension
vert = three_vols.entityset_ranges['nodes'][0]
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
three_vols_query = dq.DagmcQuery(three_vols, meshset=vert)
obs_tris = three_vols_query.get_tris()
if len(w) == 1:
test_pass[0] = True
if 'Meshset is not a volume nor a surface! Rootset will be used by default.' in str(w[-1].message):
test_pass[1] = True
exp_tris = three_vols._my_moab_core.get_entities_by_type(
three_vols.root_set, types.MBTRI)
test_pass[2] = (sorted(obs_tris) == sorted(exp_tris))
assert(all(test_pass))
def test_calc_tris_per_vert_vol():
"""Tests part of the calc_triangles_per_vertex function"""
three_vols = df.DagmcFile(test_env['three_vols'])
vol = three_vols.entityset_ranges['volumes'][0]
three_vols_query = dq.DagmcQuery(three_vols, meshset=vol)
three_vols_query.calc_tris_per_vert()
assert(sorted(three_vols_query._vert_data['tri_per_vert']) == [
4, 4, 4, 4, 5, 5, 5, 5])
def test_calc_tris_per_vert_surf():
"""Tests the calc_tris_per_vert function for surface meshset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
surf = three_vols.entityset_ranges['surfaces'][0]
three_vols_query = dq.DagmcQuery(three_vols, surf)
three_vols_query.calc_tris_per_vert()
assert(sorted(three_vols_query._vert_data['tri_per_vert']) == [4, 4, 5, 5])
def test_calc_tris_per_vert_rootset():
"""Tests the calc_tris_per_vertfunction given the rootset
"""
three_vols = df.DagmcFile(test_env['three_vols'])
three_vols_query = dq.DagmcQuery(three_vols, meshset=three_vols.root_set)
three_vols_query.calc_tris_per_vert()
exp_tpv_len = len(three_vols._my_moab_core.get_entities_by_type(
three_vols.root_set, types.MBVERTEX))
assert(len(three_vols_query._vert_data['tri_per_vert']) == exp_tpv_len)
def test_calc_tris_per_vert_dimension_incorrect():
"""Tests the calc_tris_per_vert function given incorrect dimension
"""
test_pass = np.full(3, False)
three_vols = df.DagmcFile(test_env['three_vols'])
# check if get_tris function generates warning for meshset with invalid dimension
vert = three_vols.entityset_ranges['nodes'][0]
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
three_vols_query = dq.DagmcQuery(three_vols, meshset=vert)
three_vols_query.calc_tris_per_vert()
if len(w) == 1:
test_pass[0] = True
if 'Meshset is not a volume nor a surface! Rootset will be used by default.' in str(w[-1].message):
test_pass[1] = True
exp_tpv_len = len(three_vols._my_moab_core.get_entities_by_type(
three_vols.root_set, types.MBVERTEX))
test_pass[2] = (len(three_vols_query._vert_data['tri_per_vert']) == exp_tpv_len)
assert(all(test_pass))
| 40.032432
| 111
| 0.71091
| 1,093
| 7,406
| 4.460201
| 0.110704
| 0.166154
| 0.08041
| 0.042667
| 0.834051
| 0.819077
| 0.762872
| 0.707077
| 0.697231
| 0.667077
| 0
| 0.007097
| 0.18188
| 7,406
| 184
| 112
| 40.25
| 0.797491
| 0.13192
| 0
| 0.610687
| 0
| 0
| 0.086622
| 0.003301
| 0
| 0
| 0
| 0
| 0.122137
| 1
| 0.099237
| false
| 0.114504
| 0.053435
| 0
| 0.152672
| 0
| 0
| 0
| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
| 0
| 1
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| null | 0
| 0
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| 0
| 0
| 0
| 0
|
0
| 6
|
f55f7e2a65cd784dd093abc5b61a9fd3d72c5aae
| 40
|
py
|
Python
|
InspiringCompanion/__init__.py
|
Stefano80/InspiringCompanion
|
98df80a39dbbc7ee00c763facc5364cd30c38385
|
[
"MIT"
] | null | null | null |
InspiringCompanion/__init__.py
|
Stefano80/InspiringCompanion
|
98df80a39dbbc7ee00c763facc5364cd30c38385
|
[
"MIT"
] | null | null | null |
InspiringCompanion/__init__.py
|
Stefano80/InspiringCompanion
|
98df80a39dbbc7ee00c763facc5364cd30c38385
|
[
"MIT"
] | null | null | null |
from . import models, writer, archivist
| 20
| 39
| 0.775
| 5
| 40
| 6.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 40
| 1
| 40
| 40
| 0.911765
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 0
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| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f561af6f641a386f5722976dc24b3059febea1f8
| 2,609
|
py
|
Python
|
tests/test_utils.py
|
DanielCMS/bibtex-cleaner
|
685e086ab97a8065343977cce8e14f81f3e8c468
|
[
"MIT"
] | null | null | null |
tests/test_utils.py
|
DanielCMS/bibtex-cleaner
|
685e086ab97a8065343977cce8e14f81f3e8c468
|
[
"MIT"
] | null | null | null |
tests/test_utils.py
|
DanielCMS/bibtex-cleaner
|
685e086ab97a8065343977cce8e14f81f3e8c468
|
[
"MIT"
] | null | null | null |
from utils import load_configuration, print_entry, get_yes_no, get_answer_from
from unittest import TestCase
from mock import patch
class TestUtils(TestCase):
def test_load_configuration(self):
assert load_configuration()
def test_print_entry(self):
with patch('__builtin__.print') as mock_print:
print_entry({"Test": "foo"})
mock_print.assert_called_with("test: foo")
def test_get_yes_no(self):
with patch("__builtin__.raw_input", return_value="yes") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value="y") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value="no") as raw:
assert not get_yes_no()
with patch("__builtin__.raw_input", return_value="n") as raw:
assert not get_yes_no()
def test_get_yes_no_regardless_uppercase(self):
with patch("__builtin__.raw_input", return_value="Yes") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value="Y") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value="No") as raw:
assert not get_yes_no()
with patch("__builtin__.raw_input", return_value="N") as raw:
assert not get_yes_no()
def test_get_yes_no_strips_space(self):
with patch("__builtin__.raw_input", return_value=" Yes") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value="Y ") as raw:
assert get_yes_no()
with patch("__builtin__.raw_input", return_value=" No") as raw:
assert not get_yes_no()
with patch("__builtin__.raw_input", return_value="N ") as raw:
assert not get_yes_no()
def test_get_yes_no_for_invalid_input(self):
with patch("__builtin__.raw_input", side_effect=['foo', 'y']) as raw:
assert get_yes_no()
def test_get_answer_from(self):
with patch("__builtin__.raw_input", return_value="yes") as raw:
assert get_answer_from(["yes", "no"]) == "yes"
with patch("__builtin__.raw_input", return_value="YeS") as raw:
assert get_answer_from(["yes", "no"]) == "yes"
with patch("__builtin__.raw_input", return_value=" YeS ") as raw:
assert get_answer_from(["yes", "no"]) == "yes"
def test_get_answer_from_for_invalid_input(self):
with patch("__builtin__.raw_input", side_effect=['foo', 'yes']) as raw:
assert get_answer_from(["yes", "no"]) == "yes"
| 37.271429
| 79
| 0.642775
| 359
| 2,609
| 4.158774
| 0.114206
| 0.073677
| 0.09645
| 0.216343
| 0.790355
| 0.760214
| 0.753516
| 0.740121
| 0.740121
| 0.740121
| 0
| 0
| 0.238022
| 2,609
| 69
| 80
| 37.811594
| 0.751006
| 0
| 0
| 0.58
| 0
| 0
| 0.179379
| 0.136834
| 0
| 0
| 0
| 0
| 0.38
| 1
| 0.16
| false
| 0
| 0.06
| 0
| 0.24
| 0.1
| 0
| 0
| 0
| null | 0
| 0
| 1
| 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
| 6
|
194d7d1c9abc8b3d147566aa8723ba5e8537321f
| 42
|
py
|
Python
|
ObjectOrientedProgramming/IdeFiles/3b_answer_python_package/distributions/__init__.py
|
vmukund100/dsnd_vm
|
a0f0679a4bdd0f6c458dc7620a2221d931964368
|
[
"MIT"
] | 1,030
|
2018-07-03T19:09:50.000Z
|
2022-03-25T05:48:57.000Z
|
ObjectOrientedProgramming/IdeFiles/3b_answer_python_package/distributions/__init__.py
|
vmukund100/dsnd_vm
|
a0f0679a4bdd0f6c458dc7620a2221d931964368
|
[
"MIT"
] | 21
|
2018-09-20T14:36:04.000Z
|
2021-10-11T18:25:31.000Z
|
ObjectOrientedProgramming/IdeFiles/3b_answer_python_package/distributions/__init__.py
|
vmukund100/dsnd_vm
|
a0f0679a4bdd0f6c458dc7620a2221d931964368
|
[
"MIT"
] | 1,736
|
2018-06-27T19:33:46.000Z
|
2022-03-28T17:52:33.000Z
|
from .Gaussiandistribution import Gaussian
| 42
| 42
| 0.904762
| 4
| 42
| 9.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 42
| 1
| 42
| 42
| 0.974359
| 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
| 1
| 0
|
0
| 6
|
198abae85b1c606d64f9c8146794054f3a05440d
| 26
|
py
|
Python
|
hrmodule/__init__.py
|
sabarikannan-ai/hrmodule
|
55fdcb1674032242c09b756ef830c966eed85394
|
[
"MIT"
] | null | null | null |
hrmodule/__init__.py
|
sabarikannan-ai/hrmodule
|
55fdcb1674032242c09b756ef830c966eed85394
|
[
"MIT"
] | null | null | null |
hrmodule/__init__.py
|
sabarikannan-ai/hrmodule
|
55fdcb1674032242c09b756ef830c966eed85394
|
[
"MIT"
] | null | null | null |
from hrmodule.cli import *
| 26
| 26
| 0.807692
| 4
| 26
| 5.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 26
| 1
| 26
| 26
| 0.913043
| 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
| 1
| 0
|
0
| 6
|
5fdef158672489133e55f2878ec07ce229d049cb
| 35,904
|
py
|
Python
|
groupdocs/StorageApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
groupdocs/StorageApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
groupdocs/StorageApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
"""
Copyright 2012 GroupDocs.
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
http://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.
NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually.
"""
import sys
import os
from models import *
from groupdocs.FileStream import FileStream
from groupdocs.ApiClient import ApiException
class StorageApi(object):
def __init__(self, apiClient):
self.apiClient = apiClient
self.__basePath = "https://api.groupdocs.com/v2.0"
@property
def basePath(self):
return self.__basePath
@basePath.setter
def basePath(self, value):
self.__basePath = value
def GetStorageInfo(self, userId, **kwargs):
"""Get storage info
Args:
userId, str: User GUID (required)
Returns: StorageInfoResponse
"""
if( userId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetStorageInfo" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'StorageInfoResponse')
return responseObject
def ListEntities(self, userId, path, **kwargs):
"""List entities
Args:
userId, str: User GUID (required)
path, str: Path (optional)
pageIndex, int: Page Index (optional)
pageSize, int: Page Size (optional)
orderBy, str: Order By (optional)
orderAsc, bool: Order Asc (optional)
filter, str: Filter (optional)
fileTypes, str: File Types (optional)
extended, bool: Indicates whether an extended information should be returned (optional)
Returns: ListEntitiesResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'pageIndex', 'pageSize', 'orderBy', 'orderAsc', 'filter', 'fileTypes', 'extended']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method ListEntities" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/folders/{*path}?page={pageIndex}&count={pageSize}&order_by={orderBy}&order_asc={orderAsc}&filter={filter}&file_types={fileTypes}&extended={extended}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('pageIndex' in params):
queryParams['page'] = self.apiClient.toPathValue(params['pageIndex'])
if ('pageSize' in params):
queryParams['count'] = self.apiClient.toPathValue(params['pageSize'])
if ('orderBy' in params):
queryParams['order_by'] = self.apiClient.toPathValue(params['orderBy'])
if ('orderAsc' in params):
queryParams['order_asc'] = self.apiClient.toPathValue(params['orderAsc'])
if ('filter' in params):
queryParams['filter'] = self.apiClient.toPathValue(params['filter'])
if ('fileTypes' in params):
queryParams['file_types'] = self.apiClient.toPathValue(params['fileTypes'])
if ('extended' in params):
queryParams['extended'] = self.apiClient.toPathValue(params['extended'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'ListEntitiesResponse')
return responseObject
def GetFile(self, userId, fileId, **kwargs):
"""Get file
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
Returns: stream
"""
if( userId == None or fileId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetFile" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/files/{fileId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
return self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams, FileStream)
def GetSharedFile(self, userEmail, filePath, **kwargs):
"""Get shared file
Args:
userEmail, str: User Email (required)
filePath, str: File path (required)
Returns: stream
"""
if( userEmail == None or filePath == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userEmail', 'filePath']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetSharedFile" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/shared/{userEmail}/{*filePath}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userEmail' in params):
replacement = str(self.apiClient.toPathValue(params['userEmail']))
resourcePath = resourcePath.replace('{' + 'userEmail' + '}',
replacement)
if ('filePath' in params):
replacement = str(self.apiClient.toPathValue(params['filePath']))
resourcePath = resourcePath.replace('{' + 'filePath' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
return self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams, FileStream)
def Upload(self, userId, path, body, **kwargs):
"""Upload
Args:
userId, str: User GUID (required)
path, str: Path (required)
description, str: Description (optional)
callbackUrl, str: Callback url (optional)
body, stream: Stream (required)
Returns: UploadResponse
"""
if( userId == None or path == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'description', 'callbackUrl', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method Upload" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/folders/{*path}?description={description}&callbackUrl={callbackUrl}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('description' in params):
queryParams['description'] = self.apiClient.toPathValue(params['description'])
if ('callbackUrl' in params):
queryParams['callbackUrl'] = self.apiClient.toPathValue(params['callbackUrl'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UploadResponse')
return responseObject
def Decompress(self, userId, path, body, **kwargs):
"""UploadAndUnzip
Args:
userId, str: User GUID (required)
path, str: Path (required)
description, str: Description (optional)
archiveType, str: Archive type (optional)
body, stream: Stream (required)
Returns: UploadResponse
"""
if( userId == None or path == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'description', 'archiveType', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method Decompress" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/decompress/{*path}?description={description}&archiveType={archiveType}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('description' in params):
queryParams['description'] = self.apiClient.toPathValue(params['description'])
if ('archiveType' in params):
queryParams['archiveType'] = self.apiClient.toPathValue(params['archiveType'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UploadResponse')
return responseObject
def UploadWeb(self, userId, url, **kwargs):
"""Upload Web
Args:
userId, str: User GUID (required)
url, str: Url (required)
Returns: UploadResponse
"""
if( userId == None or url == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'url']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UploadWeb" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/urls?url={url}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('url' in params):
queryParams['url'] = self.apiClient.toPathValue(params['url'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UploadResponse')
return responseObject
def UploadGoogle(self, userId, path, **kwargs):
"""Upload Google
Args:
userId, str: User GUID (required)
path, str: File path (required)
fileId, str: File unique identifier (optional)
Returns: UploadResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'fileId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UploadGoogle" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/google/files/{*path}?file_id={fileId}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('fileId' in params):
queryParams['file_id'] = self.apiClient.toPathValue(params['fileId'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UploadResponse')
return responseObject
def Delete(self, userId, fileId, **kwargs):
"""Delete
Args:
userId, str: User GUID (required)
fileId, str: File ID (required)
Returns: DeleteResponse
"""
if( userId == None or fileId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method Delete" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/files/{fileId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteResponse')
return responseObject
def DeleteFromFolder(self, userId, path, **kwargs):
"""Delete from folder
Args:
userId, str: User GUID (required)
path, str: Path (required)
Returns: DeleteResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteFromFolder" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/folders/{*path}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteResponse')
return responseObject
def MoveFile(self, userId, path, **kwargs):
"""Move file
Args:
userId, str: User GUID (required)
path, str: Path (required)
mode, str: Mode (optional)
Groupdocs_Copy, str: File ID (copy) (optional)
Groupdocs_Move, str: File ID (move) (optional)
Returns: FileMoveResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'mode', 'Groupdocs_Copy', 'Groupdocs_Move']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method MoveFile" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/files/{*path}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('mode' in params):
queryParams['mode'] = self.apiClient.toPathValue(params['mode'])
if ('Groupdocs_Copy' in params):
headerParams['Groupdocs-Copy'] = params['Groupdocs_Copy']
if ('Groupdocs_Move' in params):
headerParams['Groupdocs-Move'] = params['Groupdocs_Move']
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'FileMoveResponse')
return responseObject
def MoveFolder(self, userId, path, **kwargs):
"""Move folder
Args:
userId, str: User GUID (required)
path, str: Destination Path (required)
mode, str: Mode (optional)
Groupdocs_Move, str: Source path (move) (optional)
Groupdocs_Copy, str: Source path (copy) (optional)
Returns: FolderMoveResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path', 'mode', 'Groupdocs_Move', 'Groupdocs_Copy']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method MoveFolder" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/folders/{*path}?override_mode={mode}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('mode' in params):
queryParams['override_mode'] = self.apiClient.toPathValue(params['mode'])
if ('Groupdocs_Move' in params):
headerParams['Groupdocs-Move'] = params['Groupdocs_Move']
if ('Groupdocs_Copy' in params):
headerParams['Groupdocs-Copy'] = params['Groupdocs_Copy']
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'FolderMoveResponse')
return responseObject
def Create(self, userId, path, **kwargs):
"""Create
Args:
userId, str: User GUID (required)
path, str: Path (required)
Returns: CreateFolderResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method Create" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/paths/{*path}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CreateFolderResponse')
return responseObject
def Compress(self, userId, fileId, archiveType, **kwargs):
"""Compress
Args:
userId, str: User GUID (required)
fileId, str: File ID (required)
archiveType, str: Archive type (optional)
Returns: CompressResponse
"""
if( userId == None or fileId == None or archiveType == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'archiveType']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method Compress" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/files/{fileId}/archive/{archiveType}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
if ('archiveType' in params):
replacement = str(self.apiClient.toPathValue(params['archiveType']))
resourcePath = resourcePath.replace('{' + 'archiveType' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CompressResponse')
return responseObject
def CreatePackage(self, userId, packageName, **kwargs):
"""Create Package
Args:
userId, str: User GUID (required)
packageName, str: Package Name (required)
storeRelativePath, bool: Store files using relative paths (optional)
body, List[str]: Paths (optional)
Returns: CreatePackageResponse
"""
if( userId == None or packageName == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'packageName', 'storeRelativePath', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method CreatePackage" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/packages/{packageName}?storeRelativePath={storeRelativePath}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('storeRelativePath' in params):
queryParams['storeRelativePath'] = self.apiClient.toPathValue(params['storeRelativePath'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('packageName' in params):
replacement = str(self.apiClient.toPathValue(params['packageName']))
resourcePath = resourcePath.replace('{' + 'packageName' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CreatePackageResponse')
return responseObject
def MoveToTrash(self, userId, path, **kwargs):
"""Move to trash
Args:
userId, str: User GUID (required)
path, str: Path (required)
Returns: FolderMoveResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method MoveToTrash" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/trash/{*path}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'FolderMoveResponse')
return responseObject
def RestoreFromTrash(self, userId, path, **kwargs):
"""Restore from trash
Args:
userId, str: User GUID (required)
path, str: Path (required)
Returns: DeleteResponse
"""
if( userId == None or path == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'path']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method RestoreFromTrash" % key)
params[key] = val
del params['kwargs']
resourcePath = '/storage/{userId}/trash/{*path}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('path' in params):
replacement = str(self.apiClient.toPathValue(params['path']))
resourcePath = resourcePath.replace('{' + 'path' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteResponse')
return responseObject
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0
| 6
|
272363195e9fd4b62224081c59b6dcc4984f68dd
| 46
|
py
|
Python
|
Recommender/__init__.py
|
Buried-In-Code/MAL-Recommender
|
28f77ec714ed456557d90fac6cfb23c0e512262a
|
[
"MIT"
] | 1
|
2021-07-04T18:42:43.000Z
|
2021-07-04T18:42:43.000Z
|
Recommender/__init__.py
|
Buried-In-Code/MAL-Recommender
|
28f77ec714ed456557d90fac6cfb23c0e512262a
|
[
"MIT"
] | 3
|
2022-01-04T05:08:23.000Z
|
2022-01-06T05:11:19.000Z
|
Recommender/__init__.py
|
Buried-In-Code/MAL-Recommender
|
28f77ec714ed456557d90fac6cfb23c0e512262a
|
[
"MIT"
] | null | null | null |
from .token import TOKEN, save_token, TOP_DIR
| 23
| 45
| 0.804348
| 8
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| 4.375
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0
| 6
|
27a50867e60a3c93fca63df1280463ed18034eb2
| 60
|
py
|
Python
|
exapi/channel_creators/binance/spot/market_data/__init__.py
|
astsu-dev/exapi
|
1ef39ccdd77e9ddb60ec6eaa16a2cc26e1ac3e12
|
[
"MIT"
] | null | null | null |
exapi/channel_creators/binance/spot/market_data/__init__.py
|
astsu-dev/exapi
|
1ef39ccdd77e9ddb60ec6eaa16a2cc26e1ac3e12
|
[
"MIT"
] | null | null | null |
exapi/channel_creators/binance/spot/market_data/__init__.py
|
astsu-dev/exapi
|
1ef39ccdd77e9ddb60ec6eaa16a2cc26e1ac3e12
|
[
"MIT"
] | null | null | null |
from .interface import IBinanceSpotMarketDataChannelCreator
| 30
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0
| 6
|
27f2b62369de600eb3f5f5403d2235731ed85a1a
| 63
|
py
|
Python
|
include/hmi_ros/__init__.py
|
mbrito96/hmi_ros
|
81dd887e2cefd872805b6d55189c886edc0a8c2a
|
[
"MIT"
] | null | null | null |
include/hmi_ros/__init__.py
|
mbrito96/hmi_ros
|
81dd887e2cefd872805b6d55189c886edc0a8c2a
|
[
"MIT"
] | null | null | null |
include/hmi_ros/__init__.py
|
mbrito96/hmi_ros
|
81dd887e2cefd872805b6d55189c886edc0a8c2a
|
[
"MIT"
] | null | null | null |
from .hmi import *
from .outputs import *
from .inputs import *
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0
| 6
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fdd3d8436db9e69048eeb1c3695178b8440fe719
| 126
|
py
|
Python
|
journal/admin.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | 2
|
2016-10-21T20:46:28.000Z
|
2020-01-27T09:54:10.000Z
|
journal/admin.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | null | null | null |
journal/admin.py
|
ayasakov/social-auth
|
c73abe9066df305ba880e5de4a0cd3bdab4b6c1c
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from . import models
admin.site.register(models.Comment)
admin.site.register(models.Reply)
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| 5.666667
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0
| 6
|
e30c7b8c9d5ae8ce6e810fbc4808a5f846fd4d9f
| 9,609
|
py
|
Python
|
pyjsg/parser/jsgParserLexer.py
|
hsolbrig/pyjsg
|
5ef46d9af6a94a0cd0e91ebf8b22f61c17e78429
|
[
"CC0-1.0"
] | 3
|
2017-07-23T11:11:23.000Z
|
2020-11-30T15:36:51.000Z
|
pyjsg/parser/jsgParserLexer.py
|
hsolbrig/pyjsg
|
5ef46d9af6a94a0cd0e91ebf8b22f61c17e78429
|
[
"CC0-1.0"
] | 15
|
2018-01-05T17:18:34.000Z
|
2021-12-13T17:40:25.000Z
|
try2/lib/python3.9/site-packages/pyjsg/parser/jsgParserLexer.py
|
diatomsRcool/eco-kg
|
4251f42ca2ab353838a39b640cb97593db76d4f4
|
[
"BSD-3-Clause"
] | 1
|
2021-01-18T10:32:56.000Z
|
2021-01-18T10:32:56.000Z
|
# Generated from /Users/mrf7578/Development/git/hsolbrig/pyjsg/grammar/jsgParser.g4 by ANTLR 4.7
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\35")
buf.write("\u00e0\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7")
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buf.write("\t\23\4\24\t\24\4\25\t\25\4\26\t\26\4\27\t\27\4\30\t\30")
buf.write("\4\31\t\31\4\32\t\32\4\33\t\33\4\34\t\34\4\35\t\35\4\36")
buf.write("\t\36\4\37\t\37\4 \t \4!\t!\3\2\3\2\3\2\3\2\3\2\3\2\3")
buf.write("\2\3\2\3\2\3\2\3\2\3\3\3\3\3\3\3\3\3\3\3\3\3\4\3\4\3\5")
buf.write("\3\5\3\6\3\6\3\6\3\6\3\6\3\6\3\6\3\6\3\7\3\7\3\b\3\b\3")
buf.write("\t\3\t\3\t\3\n\3\n\3\13\3\13\3\f\3\f\3\r\3\r\3\16\3\16")
buf.write("\3\17\3\17\3\20\3\20\3\21\3\21\3\22\3\22\3\23\3\23\3\24")
buf.write("\3\24\3\25\3\25\6\25\u0080\n\25\r\25\16\25\u0081\3\26")
buf.write("\3\26\3\27\3\27\5\27\u0088\n\27\3\30\3\30\7\30\u008c\n")
buf.write("\30\f\30\16\30\u008f\13\30\3\30\3\30\7\30\u0093\n\30\f")
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class jsgParserLexer(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
T__5 = 6
T__6 = 7
T__7 = 8
T__8 = 9
T__9 = 10
T__10 = 11
T__11 = 12
T__12 = 13
T__13 = 14
T__14 = 15
T__15 = 16
T__16 = 17
T__17 = 18
T__18 = 19
LEXER_ID = 20
ID = 21
STRING = 22
INT = 23
ANY = 24
PASS = 25
COMMENT = 26
LEXER_CHAR_SET = 27
channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ]
modeNames = [ "DEFAULT_MODE" ]
literalNames = [ "<INVALID>",
"'@terminals'", "'.TYPE'", "'-'", "';'", "'.IGNORE'", "'{'",
"'}'", "'->'", "'|'", "'['", "']'", "','", "':'", "'('", "')'",
"'='", "'?'", "'*'", "'+'", "'.'" ]
symbolicNames = [ "<INVALID>",
"LEXER_ID", "ID", "STRING", "INT", "ANY", "PASS", "COMMENT",
"LEXER_CHAR_SET" ]
ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "T__5", "T__6",
"T__7", "T__8", "T__9", "T__10", "T__11", "T__12", "T__13",
"T__14", "T__15", "T__16", "T__17", "T__18", "LEXER_ID",
"LEXER_ID_START_CHAR", "LEXER_ID_CHAR", "ID", "ID_START_CHAR",
"ID_CHAR", "ANY_CHAR", "STRING", "INT", "ANY", "PASS",
"COMMENT", "LEXER_CHAR_SET" ]
grammarFileName = "jsgParser.g4"
def __init__(self, input=None, output:TextIO = sys.stdout):
super().__init__(input, output)
self.checkVersion("4.7")
self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache())
self._actions = None
self._predicates = None
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| 103
| 0.552607
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| 0
|
0
| 6
|
e30f7eb6126b91158a1c80561597be16cc9c9390
| 1,132
|
py
|
Python
|
Yoga/YogaApp/models.py
|
cmadisonne/passion-project
|
ca9943d6d27e879a03e308b8ddb6e5d2eb89673b
|
[
"Apache-2.0"
] | null | null | null |
Yoga/YogaApp/models.py
|
cmadisonne/passion-project
|
ca9943d6d27e879a03e308b8ddb6e5d2eb89673b
|
[
"Apache-2.0"
] | null | null | null |
Yoga/YogaApp/models.py
|
cmadisonne/passion-project
|
ca9943d6d27e879a03e308b8ddb6e5d2eb89673b
|
[
"Apache-2.0"
] | null | null | null |
from django.db import models
# Create your models here.
class Contact(models.Model):
name = models.CharField(max_length=50)
number = models.CharField(max_length=12)
email = models.EmailField(default=None)
message = models.CharField(max_length=200)
def __str__(self):
return self.name
class Events(models.Model):
name = models.CharField(max_length=100)
location = models.CharField(max_length=100)
date = models.DateField(auto_now=False, auto_now_add=False)
time = models.TimeField(auto_now=False, auto_now_add=False)
description = models.CharField(max_length=500)
image = models.ImageField(blank=True, null=True, upload_to="eventImage")
def __str__(self):
return self.name
class Requests(models.Model):
name = models.CharField(max_length=100)
location = models.CharField(max_length=100)
date = models.DateField(auto_now=False, auto_now_add=False)
time = models.TimeField(auto_now=False, auto_now_add=False)
description = models.CharField(max_length=500)
image = models.ImageField(blank=True)
def __str__(self):
return self.name
| 34.30303
| 76
| 0.728799
| 153
| 1,132
| 5.169935
| 0.326797
| 0.17067
| 0.204804
| 0.273072
| 0.752212
| 0.752212
| 0.721871
| 0.599241
| 0.599241
| 0.599241
| 0
| 0.026427
| 0.164311
| 1,132
| 33
| 77
| 34.30303
| 0.809725
| 0.021201
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| 0.115385
| false
| 0
| 0.038462
| 0.115385
| 1
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| 1
| 1
| 0
|
0
| 6
|
e3387b3394ee91ef2942704e1ec1bb2532c050bd
| 126
|
py
|
Python
|
inputparser/__init__.py
|
mmsbrggr/polar
|
34348baf6992232e47cee7a4d56b5a96567c50b8
|
[
"MIT"
] | 2
|
2021-10-06T13:29:24.000Z
|
2021-11-11T19:42:43.000Z
|
inputparser/__init__.py
|
mmsbrggr/polar
|
34348baf6992232e47cee7a4d56b5a96567c50b8
|
[
"MIT"
] | 1
|
2022-01-26T15:58:28.000Z
|
2022-01-28T13:47:28.000Z
|
inputparser/__init__.py
|
mmsbrggr/polar
|
34348baf6992232e47cee7a4d56b5a96567c50b8
|
[
"MIT"
] | 2
|
2021-10-01T15:08:52.000Z
|
2022-03-15T14:10:06.000Z
|
from .parser import Parser
from .goal_parser import GoalParser, MOMENT, CUMULANT, CENTRAL, TAIL_BOUND_LOWER, TAIL_BOUND_UPPER
| 42
| 98
| 0.84127
| 18
| 126
| 5.611111
| 0.666667
| 0.237624
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| 126
| 2
| 99
| 63
| 0.893805
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|
0
| 6
|
e33967aa729b0885f3bb77177c72eb3b7fcaf3d7
| 205
|
py
|
Python
|
plaso/filters/__init__.py
|
ir4n6/plaso
|
010f9cbdfc82e21ed6658657fd09a7b44115c464
|
[
"Apache-2.0"
] | 1
|
2019-09-26T08:16:30.000Z
|
2019-09-26T08:16:30.000Z
|
plaso/filters/__init__.py
|
ir4n6/plaso
|
010f9cbdfc82e21ed6658657fd09a7b44115c464
|
[
"Apache-2.0"
] | null | null | null |
plaso/filters/__init__.py
|
ir4n6/plaso
|
010f9cbdfc82e21ed6658657fd09a7b44115c464
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
"""This file contains an import statement for each filter."""
from plaso.filters import dynamic_filter
from plaso.filters import event_filter
from plaso.filters import filter_list
| 29.285714
| 61
| 0.77561
| 30
| 205
| 5.2
| 0.6
| 0.192308
| 0.288462
| 0.423077
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| 0
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| 0.005618
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| 205
| 6
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| 0
|
0
| 6
|
e349bce022e1eecc7f6bed3b0cd963b4ba3a617f
| 28
|
py
|
Python
|
test/json/drbg/__init__.py
|
vincent-musedev/libacvp
|
b11247d9d0b2fbd88954358272a43d35c059be7b
|
[
"BSD-2-Clause",
"Apache-2.0"
] | 45
|
2016-08-01T11:47:34.000Z
|
2022-02-22T21:27:27.000Z
|
test/json/drbg/__init__.py
|
vincent-musedev/libacvp
|
b11247d9d0b2fbd88954358272a43d35c059be7b
|
[
"BSD-2-Clause",
"Apache-2.0"
] | 221
|
2016-08-04T17:10:36.000Z
|
2022-01-21T19:53:36.000Z
|
test/json/drbg/__init__.py
|
vincent-musedev/libacvp
|
b11247d9d0b2fbd88954358272a43d35c059be7b
|
[
"BSD-2-Clause",
"Apache-2.0"
] | 94
|
2016-10-23T11:08:19.000Z
|
2022-01-21T11:50:16.000Z
|
from .drbg import main_drbg
| 14
| 27
| 0.821429
| 5
| 28
| 4.4
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 28
| 1
| 28
| 28
| 0.916667
| 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
| 1
| 0
|
0
| 6
|
8ba4daf5f48dd91454429b4aa0c58dc752241c0b
| 41
|
py
|
Python
|
clip/__init__.py
|
zhaoyanpeng/lvamodel
|
93b06ff43ae6a76323cecea4c10cf457945c2711
|
[
"MIT"
] | 6
|
2021-12-20T06:01:56.000Z
|
2022-03-25T06:44:50.000Z
|
clip/__init__.py
|
zhaoyanpeng/vipant
|
93b06ff43ae6a76323cecea4c10cf457945c2711
|
[
"MIT"
] | null | null | null |
clip/__init__.py
|
zhaoyanpeng/vipant
|
93b06ff43ae6a76323cecea4c10cf457945c2711
|
[
"MIT"
] | null | null | null |
from .clip import *
from .model import *
| 13.666667
| 20
| 0.707317
| 6
| 41
| 4.833333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.195122
| 41
| 2
| 21
| 20.5
| 0.878788
| 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
| 1
| 0
|
0
| 6
|
8ba7364d0375f343e6626abaf5a112022b31bded
| 69
|
py
|
Python
|
meddlr/utils/__init__.py
|
ad12/meddlr
|
dda5a4ad7855de3a34331c60599e3253f980e989
|
[
"Apache-2.0"
] | 23
|
2021-11-05T02:00:01.000Z
|
2022-03-21T15:35:38.000Z
|
meddlr/utils/__init__.py
|
ad12/meddlr
|
dda5a4ad7855de3a34331c60599e3253f980e989
|
[
"Apache-2.0"
] | 29
|
2021-11-04T22:18:26.000Z
|
2022-03-24T01:04:53.000Z
|
meddlr/utils/__init__.py
|
ad12/meddlr
|
dda5a4ad7855de3a34331c60599e3253f980e989
|
[
"Apache-2.0"
] | 1
|
2022-01-25T22:34:51.000Z
|
2022-01-25T22:34:51.000Z
|
from . import cluster # noqa: F401
from . import path # noqa: F401
| 23
| 35
| 0.681159
| 10
| 69
| 4.7
| 0.6
| 0.425532
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.113208
| 0.231884
| 69
| 2
| 36
| 34.5
| 0.773585
| 0.304348
| 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
| 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
| 6
|
475f0fdbbc6a78e0b60c63f3984f2d59dada9c07
| 27
|
py
|
Python
|
app/var/__init__.py
|
Ayshnoor/GA_CO2_forecasting
|
9dbac5c0c421ba400f0d273951c62493b4a63405
|
[
"BSD-4-Clause-UC"
] | 1
|
2022-03-30T21:04:59.000Z
|
2022-03-30T21:04:59.000Z
|
app/var/__init__.py
|
Ayshnoor/GA_CO2_forecasting
|
9dbac5c0c421ba400f0d273951c62493b4a63405
|
[
"BSD-4-Clause-UC"
] | null | null | null |
app/var/__init__.py
|
Ayshnoor/GA_CO2_forecasting
|
9dbac5c0c421ba400f0d273951c62493b4a63405
|
[
"BSD-4-Clause-UC"
] | null | null | null |
from .var import VAR_model
| 13.5
| 26
| 0.814815
| 5
| 27
| 4.2
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148148
| 27
| 1
| 27
| 27
| 0.913043
| 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
| 1
| 0
|
0
| 6
|
47a45b4e77790afa13bbf8016d40a683e5a2d15c
| 31
|
py
|
Python
|
electricityLoadForecasting/forecasting/models/benchmarks/__init__.py
|
BCD65/electricityLoadForecasting
|
07a6ed060afaf7cc2906c0389b5c9e9b0fede193
|
[
"MIT"
] | null | null | null |
electricityLoadForecasting/forecasting/models/benchmarks/__init__.py
|
BCD65/electricityLoadForecasting
|
07a6ed060afaf7cc2906c0389b5c9e9b0fede193
|
[
"MIT"
] | null | null | null |
electricityLoadForecasting/forecasting/models/benchmarks/__init__.py
|
BCD65/electricityLoadForecasting
|
07a6ed060afaf7cc2906c0389b5c9e9b0fede193
|
[
"MIT"
] | null | null | null |
from . import classical, gam
| 7.75
| 28
| 0.709677
| 4
| 31
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.225806
| 31
| 3
| 29
| 10.333333
| 0.916667
| 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
| 1
| 0
|
0
| 6
|
47fb780b81f5adda568008a5925365fdbc946491
| 162
|
py
|
Python
|
winapi/kernel32/__init__.py
|
batteryshark/bitjunk
|
2243b138795beea35c33642d68de77a2eebf9a8e
|
[
"MIT"
] | 1
|
2021-07-10T03:53:52.000Z
|
2021-07-10T03:53:52.000Z
|
winapi/kernel32/__init__.py
|
batteryshark/bitjunk
|
2243b138795beea35c33642d68de77a2eebf9a8e
|
[
"MIT"
] | null | null | null |
winapi/kernel32/__init__.py
|
batteryshark/bitjunk
|
2243b138795beea35c33642d68de77a2eebf9a8e
|
[
"MIT"
] | null | null | null |
from .memoryapi import *
from .handleapi import *
from .helpers import *
from .processthreadsapi import *
from .wow64apiset import *
from .tlhelp32 import *
| 16.2
| 32
| 0.746914
| 18
| 162
| 6.722222
| 0.444444
| 0.413223
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.030075
| 0.179012
| 162
| 9
| 33
| 18
| 0.879699
| 0
| 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
| 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
| 6
|
9a58aa45672249891ef5b6e893ee56891ca5c2df
| 59
|
py
|
Python
|
pytexmex/__init__.py
|
swo/pytexmex
|
be4095cd12599f24d028b70c671aaa1284ad7cc2
|
[
"MIT"
] | null | null | null |
pytexmex/__init__.py
|
swo/pytexmex
|
be4095cd12599f24d028b70c671aaa1284ad7cc2
|
[
"MIT"
] | null | null | null |
pytexmex/__init__.py
|
swo/pytexmex
|
be4095cd12599f24d028b70c671aaa1284ad7cc2
|
[
"MIT"
] | 2
|
2016-07-26T21:28:44.000Z
|
2018-08-15T12:09:05.000Z
|
from pytexmex.core import *
from pytexmex.helpers import *
| 19.666667
| 30
| 0.79661
| 8
| 59
| 5.875
| 0.625
| 0.510638
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135593
| 59
| 2
| 31
| 29.5
| 0.921569
| 0
| 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
| 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
| 6
|
d026b2b55343f8b8006c6c0fd6ddde2208eb71da
| 64
|
py
|
Python
|
datasets/kor_corpora/__init__.py
|
AIRC-KETI/ke-t5
|
82e045d77ade3b2544b9d1b456d4622ce1beef8e
|
[
"Apache-2.0"
] | 96
|
2021-03-29T01:48:39.000Z
|
2022-03-18T06:15:33.000Z
|
tensorflow_datasets/kor_corpora/__init__.py
|
dev07060/Korean-Copora
|
8b96e94a2d9e88ddbb1c2d088a7ec01d057e5dcb
|
[
"Apache-2.0"
] | 4
|
2021-05-16T10:48:52.000Z
|
2021-08-02T06:39:28.000Z
|
tensorflow_datasets/kor_corpora/__init__.py
|
dev07060/Korean-Copora
|
8b96e94a2d9e88ddbb1c2d088a7ec01d057e5dcb
|
[
"Apache-2.0"
] | 14
|
2021-03-29T02:11:20.000Z
|
2022-03-17T07:46:18.000Z
|
"""kor_corpora dataset."""
from .kor_corpora import KorCorpora
| 16
| 35
| 0.765625
| 8
| 64
| 5.875
| 0.75
| 0.425532
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109375
| 64
| 3
| 36
| 21.333333
| 0.824561
| 0.3125
| 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
| 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
| 6
|
d07bf8de95a742f952f37425a41c44f5020a4a5b
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/pyflakes/test/test_is_literal.py
|
GiulianaPola/select_repeats
|
17a0d053d4f874e42cf654dd142168c2ec8fbd11
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/pyflakes/test/test_is_literal.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/pyflakes/test/test_is_literal.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/f7/75/7d/73174f807abf1b561d287482a551e0f477c59136d861c7a23341192474
| 96
| 96
| 0.895833
| 9
| 96
| 9.555556
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.510417
| 0
| 96
| 1
| 96
| 96
| 0.385417
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
d0a294be933648f32c4023d16a665f3565a36035
| 47
|
py
|
Python
|
iterm2env/versions/3.7.2/lib/python3.7/site-packages/aioconsole/__main__.py
|
n-someya/SushiStatusBar
|
941607f54b55ded5a6b69dc26ea0a36836b2a2e8
|
[
"Apache-2.0"
] | 5
|
2019-05-09T10:59:09.000Z
|
2020-10-10T21:30:50.000Z
|
iterm2env/versions/3.7.2/lib/python3.7/site-packages/aioconsole/__main__.py
|
n-someya/SushiStatusBar
|
941607f54b55ded5a6b69dc26ea0a36836b2a2e8
|
[
"Apache-2.0"
] | null | null | null |
iterm2env/versions/3.7.2/lib/python3.7/site-packages/aioconsole/__main__.py
|
n-someya/SushiStatusBar
|
941607f54b55ded5a6b69dc26ea0a36836b2a2e8
|
[
"Apache-2.0"
] | 3
|
2019-08-26T00:02:24.000Z
|
2020-10-10T18:46:01.000Z
|
from .apython import run_apython
run_apython()
| 15.666667
| 32
| 0.829787
| 7
| 47
| 5.285714
| 0.571429
| 0.540541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106383
| 47
| 2
| 33
| 23.5
| 0.880952
| 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 | 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
| 1
| 0
| 0
| 0
|
0
| 6
|
d0ad765d1e5f5d89b6a6acab5a3c3779d3a1d05e
| 172
|
py
|
Python
|
src/message/sv_response_base.py
|
the40san/unity_survival_shooter_multi_server_python
|
d20d9aa2204bca70d0787acbfe395277b776e92d
|
[
"MIT"
] | 3
|
2017-04-11T05:36:08.000Z
|
2021-03-16T16:22:07.000Z
|
src/message/sv_response_base.py
|
the40san/unity_survival_shooter_multi_server_python
|
d20d9aa2204bca70d0787acbfe395277b776e92d
|
[
"MIT"
] | null | null | null |
src/message/sv_response_base.py
|
the40san/unity_survival_shooter_multi_server_python
|
d20d9aa2204bca70d0787acbfe395277b776e92d
|
[
"MIT"
] | 1
|
2017-04-11T05:35:26.000Z
|
2017-04-11T05:35:26.000Z
|
class SvResponseBase:
def __init__(self, cl_request):
self.cl_request = cl_request
def payload():
""" OVERRIDE THIS TO IMPLEMENT """
raise
| 21.5
| 42
| 0.616279
| 19
| 172
| 5.210526
| 0.684211
| 0.272727
| 0.262626
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.290698
| 172
| 7
| 43
| 24.571429
| 0.811475
| 0.151163
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0
| 0
| 0.6
| 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
| 1
| 0
|
0
| 6
|
d0d28c97923cd421113bf2ad12ffe0148168cacb
| 381
|
py
|
Python
|
src/gradient_descents/__init__.py
|
kryvokhyzha/gradient-descent
|
c9b6c0a483c5c1495b219167d61b0c211c783364
|
[
"MIT"
] | 1
|
2021-02-22T20:02:21.000Z
|
2021-02-22T20:02:21.000Z
|
src/gradient_descents/__init__.py
|
kryvokhyzha/gradient-descent
|
c9b6c0a483c5c1495b219167d61b0c211c783364
|
[
"MIT"
] | null | null | null |
src/gradient_descents/__init__.py
|
kryvokhyzha/gradient-descent
|
c9b6c0a483c5c1495b219167d61b0c211c783364
|
[
"MIT"
] | 1
|
2020-05-31T22:31:23.000Z
|
2020-05-31T22:31:23.000Z
|
from gradient_descents.classic_gradient_descent import classic_grad_descent
from gradient_descents.stochastic_gradient_descent import stochastic_grad_descent
from gradient_descents.momentum_gradient_descent import momentum_grad_descent
from gradient_descents.rmsprop_gradient_descent import rmsprop_grad_descent
from gradient_descents.adam_gradient_descent import adam_grad_descent
| 76.2
| 81
| 0.937008
| 50
| 381
| 6.64
| 0.22
| 0.180723
| 0.301205
| 0.277108
| 0.373494
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049869
| 381
| 5
| 82
| 76.2
| 0.917127
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d0e5409586f49850d32fb1119b6a8a568cc9804c
| 49
|
py
|
Python
|
python/testData/addImport/newLastImportInBuiltinGroup/main.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/addImport/newLastImportInBuiltinGroup/main.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/addImport/newLastImportInBuiltinGroup/main.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
import datetime
import a
print(datetime, sys, a)
| 12.25
| 23
| 0.77551
| 8
| 49
| 4.75
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 49
| 4
| 23
| 12.25
| 0.904762
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0.333333
| 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
| 1
| 0
|
0
| 6
|
ef7158ed2bb5c53d7d8a4dfa6345f17bd7dc32e1
| 139
|
py
|
Python
|
Chapter01/import_dice_roller.py
|
PacktPublishing/Secret-Recipes-of-the-Python-Ninja
|
805d00c7a54927ba94c9077e9a580508ee3c5e56
|
[
"MIT"
] | 13
|
2018-06-21T01:44:49.000Z
|
2021-12-01T10:49:53.000Z
|
Chapter01/import_dice_roller.py
|
PacktPublishing/Secret-Recipes-of-the-Python-Ninja
|
805d00c7a54927ba94c9077e9a580508ee3c5e56
|
[
"MIT"
] | null | null | null |
Chapter01/import_dice_roller.py
|
PacktPublishing/Secret-Recipes-of-the-Python-Ninja
|
805d00c7a54927ba94c9077e9a580508ee3c5e56
|
[
"MIT"
] | 6
|
2018-10-05T08:29:24.000Z
|
2022-01-11T14:49:50.000Z
|
>>> import Random_Dice_Roller
>>> Random_Dice_Roller.test()
1d6 = 1
2d6 = 8
3d6 = 10
4d6 = 12
1d10 = 5
2d10 = 8
3d10 = 6
1d100 = 26
| 12.636364
| 29
| 0.618705
| 24
| 139
| 3.416667
| 0.833333
| 0.243902
| 0.390244
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.31068
| 0.258993
| 139
| 10
| 30
| 13.9
| 0.485437
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.1
| null | null | 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
ef9f31012593c76c365d980bc4936e2f9e6c49a9
| 46
|
py
|
Python
|
OpenGraph/functions/graph_embedding/__init__.py
|
willingnesshxl/ONAP
|
eea17dbf0f6d799e527708f1c55a8389da0df664
|
[
"MIT"
] | 3
|
2019-11-19T05:45:22.000Z
|
2020-02-02T11:41:41.000Z
|
OpenGraph/functions/graph_embedding/__init__.py
|
willingnesshxl/ONAP
|
eea17dbf0f6d799e527708f1c55a8389da0df664
|
[
"MIT"
] | 2
|
2020-03-01T11:54:53.000Z
|
2020-04-03T08:29:24.000Z
|
OpenGraph/functions/graph_embedding/__init__.py
|
willingnesshxl/ONAP
|
eea17dbf0f6d799e527708f1c55a8389da0df664
|
[
"MIT"
] | 2
|
2019-11-19T05:49:36.000Z
|
2020-02-02T08:18:10.000Z
|
from .node2vec import *
from .line import LINE
| 23
| 23
| 0.782609
| 7
| 46
| 5.142857
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025641
| 0.152174
| 46
| 2
| 24
| 23
| 0.897436
| 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
| 1
| 0
|
0
| 6
|
efac774263d02b2190b26a641717be7a08797645
| 82
|
py
|
Python
|
xlib/appargs/__init__.py
|
jkennedyvz/DeepFaceLive
|
274c20808da089eb7fc0fc0e8abe649379a29ffe
|
[
"MIT"
] | 3
|
2021-12-08T08:59:50.000Z
|
2022-02-08T02:54:27.000Z
|
xlib/appargs/__init__.py
|
jkennedyvz/DeepFaceLive
|
274c20808da089eb7fc0fc0e8abe649379a29ffe
|
[
"MIT"
] | 1
|
2022-02-08T01:29:03.000Z
|
2022-02-08T01:29:03.000Z
|
xlib/appargs/__init__.py
|
jkennedyvz/DeepFaceLive
|
274c20808da089eb7fc0fc0e8abe649379a29ffe
|
[
"MIT"
] | 1
|
2021-12-14T09:18:15.000Z
|
2021-12-14T09:18:15.000Z
|
"""
"""
from .appargs import get_arg_bool, get_arg_str, set_arg_bool, set_arg_str
| 20.5
| 73
| 0.768293
| 15
| 82
| 3.666667
| 0.533333
| 0.218182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109756
| 82
| 3
| 74
| 27.333333
| 0.753425
| 0
| 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
| 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
| 6
|
ef16a14c448620be3567362d51c946dbc85c9314
| 25,764
|
py
|
Python
|
applications/Ma-Net/dataloaders/davis_2017_f.py
|
Simon-liusheng/PaddleVideo
|
6c35b68bc745c659813d6517eecade9c9508a628
|
[
"Apache-2.0"
] | 1
|
2022-02-19T23:50:49.000Z
|
2022-02-19T23:50:49.000Z
|
applications/Ma-Net/dataloaders/davis_2017_f.py
|
liutinglong/PaddleVideo
|
6b8a723360ac652ca7aafa1908e6c67a67cf5ea5
|
[
"Apache-2.0"
] | 1
|
2022-01-14T02:33:28.000Z
|
2022-01-14T02:33:28.000Z
|
applications/Ma-Net/dataloaders/davis_2017_f.py
|
Thinksky5124/PaddleVideo
|
c8e9c5ff53d99bd70bfeb6246a53e668064a9940
|
[
"Apache-2.0"
] | null | null | null |
from __future__ import division
import json
import os
import shutil
import numpy as np
import paddle, cv2
from random import choice
from paddle.io import Dataset
import json
from PIL import Image
from davisinteractive.utils.scribbles import scribbles2mask, annotated_frames
import sys
sys.path.append("..")
from config import cfg
import time
class DAVIS2017_Test_Manager():
def __init__(self,
split='val',
root=cfg.DATA_ROOT,
transform=None,
rgb=False,
seq_name=None):
self.split = split
self.db_root_dir = root
self.rgb = rgb
self.transform = transform
self.seq_name = seq_name
def get_image(self, idx):
frame_name = str(idx)
while len(frame_name) != 5:
frame_name = '0' + frame_name
imgpath = os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(self.seq_name), frame_name + '.jpg')
img = cv2.imread(imgpath)
img = np.array(img, dtype=np.float32)
sample = {'img': img}
if self.transform is not None:
sample = self.transform(sample)
return sample
class DAVIS2017_Feature_Extract(Dataset):
def __init__(self,
split='val',
root=cfg.DATA_ROOT,
transform=None,
rgb=False,
seq_name=None):
self.split = split
self.db_root_dir = root
self.rgb = rgb
self.transform = transform
self.seq_name = seq_name
self.img_list = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(seq_name))))
def __len__(self):
return len(self.img_list)
def __getitem__(self, idx):
img = self.img_list[idx]
imgpath = os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(self.seq_name), img)
current_img = cv2.imread(imgpath)
current_img = np.array(current_img, dtype=np.float32)
h, w, _ = current_img.shape
sample = {'img1': current_img}
sample['meta'] = {
'seq_name': self.seq_name,
'h_w': (h, w),
'img_path': imgpath
}
if self.transform is not None:
sample = self.transform(sample)
return sample
class DAVIS2017_VOS_Test(Dataset):
"""
"""
def __init__(self,
split='val',
root=cfg.DATA_ROOT,
transform=None,
rgb=False,
result_root=None,
seq_name=None):
self.split = split
self.db_root_dir = root
self.result_root = result_root
self.rgb = rgb
self.transform = transform
self.seq_name = seq_name
self.seq_list_file = os.path.join(
self.db_root_dir, 'ImageSets', '2017',
'_'.join(self.split) + '_instances.txt')
self.seqs = []
for splt in self.split:
with open(
os.path.join(self.db_root_dir, 'ImageSets', '2017',
self.split + '.txt')) as f:
seqs_tmp = f.readlines()
seqs_tmp = list(map(lambda elem: elem.strip(), seqs_tmp))
self.seqs.extend(seqs_tmp)
if not self._check_preprocess():
self._preprocess()
assert self.seq_name in self.seq_dict.keys(
), '{} not in {} set.'.format(self.seq_name, '_'.join(self.split))
names_img = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(seq_name))))
img_list = list(
map(lambda x: os.path.join('JPEGImages/480p/', str(seq_name), x),
names_img))
name_label = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/',
str(seq_name))))
labels = list(
map(lambda x: os.path.join('Annotations/480p/', str(seq_name), x),
name_label))
if not os.path.isfile(
os.path.join(self.result_root, seq_name, name_label[0])):
if not os.path.exists(os.path.join(self.result_root, seq_name)):
os.makedirs(os.path.join(self.result_root, seq_name))
shutil.copy(
os.path.join(self.db_root_dir, labels[0]),
os.path.join(self.result_root, seq_name, name_label[0]))
else:
shutil.copy(
os.path.join(self.db_root_dir, labels[0]),
os.path.join(self.result_root, seq_name, name_label[0]))
self.first_img = names_img[0]
self.first_label = name_label[0]
self.img_list = names_img[1:]
def __len__(self):
return len(self.img_list)
def __getitem__(self, idx):
img = self.img_list[idx]
imgpath = os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(self.seq_name), img)
num_frame = int(img.split('.')[0])
ref_img = os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(self.seq_name), self.first_img)
prev_frame = num_frame - 1
prev_frame = str(prev_frame)
while len(prev_frame) != 5:
prev_frame = '0' + prev_frame
prev_img = os.path.join(self.db_root_dir, 'JPEGImages/480p/',
str(self.seq_name),
prev_frame + '.' + img.split('.')[-1])
current_img = cv2.imread(imgpath)
current_img = np.array(current_img, dtype=np.float32)
ref_img = cv2.imread(ref_img)
ref_img = np.array(ref_img, dtype=np.float32)
prev_img = cv2.imread(prev_img)
prev_img = np.array(prev_img, dtype=np.float32)
ref_label = os.path.join(self.db_root_dir, 'Annotations/480p/',
str(self.seq_name), self.first_label)
ref_label = Image.open(ref_label)
ref_label = np.array(ref_label, dtype=np.uint8)
prev_label = os.path.join(
self.result_root, str(self.seq_name),
prev_frame + '.' + self.first_label.split('.')[-1])
prev_label = Image.open(prev_label)
prev_label = np.array(prev_label, dtype=np.uint8)
obj_num = self.seq_dict[self.seq_name][-1]
sample = {
'ref_img': ref_img,
'prev_img': prev_img,
'current_img': current_img,
'ref_label': ref_label,
'prev_label': prev_label
}
sample['meta'] = {
'seq_name': self.seq_name,
'frame_num': num_frame,
'obj_num': obj_num,
'current_name': img
}
if self.transform is not None:
sample = self.transform(sample)
return sample
def _check_preprocess(self):
_seq_list_file = self.seq_list_file
if not os.path.isfile(_seq_list_file):
return False
else:
self.seq_dict = json.load(open(self.seq_list_file, 'r'))
return True
def _preprocess(self):
self.seq_dict = {}
for seq in self.seqs:
# Read object masks and get number of objects
name_label = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/', seq)))
label_path = os.path.join(self.db_root_dir, 'Annotations/480p/',
seq, name_label[0])
_mask = np.array(Image.open(label_path))
_mask_ids = np.unique(_mask)
n_obj = _mask_ids[-1]
self.seq_dict[seq] = list(range(1, n_obj + 1))
with open(self.seq_list_file, 'w') as outfile:
outfile.write('{{\n\t"{:s}": {:s}'.format(
self.seqs[0], json.dumps(self.seq_dict[self.seqs[0]])))
for ii in range(1, len(self.seqs)):
outfile.write(',\n\t"{:s}": {:s}'.format(
self.seqs[ii], json.dumps(self.seq_dict[self.seqs[ii]])))
outfile.write('\n}\n')
print('Preprocessing finished')
class DAVIS2017_VOS_Train(Dataset):
"""DAVIS2017 dataset for training
Return: imgs: N*2*3*H*W,label: N*2*1*H*W, seq-name: N, frame_num:N
"""
def __init__(self,
split='train',
root=cfg.DATA_ROOT,
transform=None,
rgb=False):
self.split = split
self.db_root_dir = root
self.rgb = rgb
self.transform = transform
self.seq_list_file = os.path.join(
self.db_root_dir, 'ImageSets', '2017',
'_'.join(self.split) + '_instances.txt')
self.seqs = []
for splt in self.split:
with open(
os.path.join(self.db_root_dir, 'ImageSets', '2017',
self.split + '.txt')) as f:
seqs_tmp = f.readlines()
seqs_tmp = list(map(lambda elem: elem.strip(), seqs_tmp))
self.seqs.extend(seqs_tmp)
self.imglistdic = {}
if not self._check_preprocess():
self._preprocess()
self.sample_list = []
for seq_name in self.seqs:
images = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'JPEGImages/480p/',
seq_name.strip())))
images_path = list(
map(
lambda x: os.path.join('JPEGImages/480p/', seq_name.strip(),
x), images))
lab = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/',
seq_name.strip())))
lab_path = list(
map(
lambda x: os.path.join('Annotations/480p/', seq_name.strip(
), x), lab))
self.imglistdic[seq_name] = (images, lab)
def __len__(self):
return len(self.seqs)
def __getitem__(self, idx):
seqname = self.seqs[idx]
imagelist, lablist = self.imglistdic[seqname]
prev_img = np.random.choice(imagelist[:-1], 1)
prev_img = prev_img[0]
frame_num = int(prev_img.split('.')[0]) + 1
next_frame = str(frame_num)
while len(next_frame) != 5:
next_frame = '0' + next_frame
###############################Processing two adjacent frames and labels
img2path = os.path.join('JPEGImages/480p/', seqname,
next_frame + '.' + prev_img.split('.')[-1])
img2 = cv2.imread(os.path.join(self.db_root_dir, img2path))
img2 = np.array(img2, dtype=np.float32)
imgpath = os.path.join('JPEGImages/480p/', seqname, prev_img)
img1 = cv2.imread(os.path.join(self.db_root_dir, imgpath))
img1 = np.array(img1, dtype=np.float32)
###############
labelpath = os.path.join(
'Annotations/480p/', seqname,
prev_img.split('.')[0] + '.' + lablist[0].split('.')[-1])
label1 = Image.open(os.path.join(self.db_root_dir, labelpath))
label2path = os.path.join('Annotations/480p/', seqname,
next_frame + '.' + lablist[0].split('.')[-1])
label2 = Image.open(os.path.join(self.db_root_dir, label2path))
label1 = np.array(label1, dtype=np.uint8)
label2 = np.array(label2, dtype=np.uint8)
###################
ref_img = np.random.choice(imagelist, 1)
ref_img = ref_img[0]
ref_img_name = ref_img
ref_scribble_label = Image.open(
os.path.join(
self.db_root_dir, 'Annotations/480p/', seqname,
ref_img_name.split('.')[0] + '.' + lablist[0].split('.')[-1]))
ref_scribble_label = np.array(ref_scribble_label, dtype=np.uint8)
while len(np.unique(ref_scribble_label)) < self.seq_dict[seqname][
-1] + 1 or ref_img == prev_img or ref_img == (
next_frame + '.' + prev_img.split('.')[-1]):
ref_img = np.random.choice(imagelist, 1)
ref_img = ref_img[0]
ref_img_name = ref_img
ref_scribble_label = Image.open(
os.path.join(
self.db_root_dir, 'Annotations/480p/', seqname,
ref_img_name.split('.')[0] + '.' +
lablist[0].split('.')[-1]))
ref_scribble_label = np.array(ref_scribble_label, dtype=np.int64)
ref_img = os.path.join('JPEGImages/480p/', seqname, ref_img)
ref_img = cv2.imread(os.path.join(self.db_root_dir, ref_img))
ref_img = np.array(ref_img, dtype=np.float32)
####
###################
if self.rgb:
img1 = img1[:, :, [2, 1, 0]]
img2 = img2[:, :, [2, 1, 0]]
ref_img = ref_img[:, :, [2, 1, 0]]
obj_num = self.seq_dict[seqname][-1]
sample = {
'ref_img': ref_img,
'img1': img1,
'img2': img2,
'ref_scribble_label': ref_scribble_label,
'label1': label1,
'label2': label2
}
sample['meta'] = {
'seq_name': seqname,
'frame_num': frame_num,
'obj_num': obj_num
}
if self.transform is not None:
sample = self.transform(sample)
sample['ref_scribble_label'] = paddle.to_tensor(
sample['ref_scribble_label'], dtype='int64')
sample['label1'] = paddle.to_tensor(sample['label1'], dtype='int64')
sample['label2'] = paddle.to_tensor(sample['label2'], dtype='int64')
return sample
########################
def _check_preprocess(self):
_seq_list_file = self.seq_list_file
if not os.path.isfile(_seq_list_file):
return False
else:
self.seq_dict = json.load(open(self.seq_list_file, 'r'))
return True
def _preprocess(self):
self.seq_dict = {}
for seq in self.seqs:
# Read object masks and get number of objects
name_label = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/', seq)))
label_path = os.path.join(self.db_root_dir, 'Annotations/480p/',
seq, name_label[0])
_mask = np.array(Image.open(label_path))
_mask_ids = np.unique(_mask)
n_obj = _mask_ids[-1]
self.seq_dict[seq] = list(range(1, n_obj + 1))
with open(self.seq_list_file, 'w') as outfile:
outfile.write('{{\n\t"{:s}": {:s}'.format(
self.seqs[0], json.dumps(self.seq_dict[self.seqs[0]])))
for ii in range(1, len(self.seqs)):
outfile.write(',\n\t"{:s}": {:s}'.format(
self.seqs[ii], json.dumps(self.seq_dict[self.seqs[ii]])))
outfile.write('\n}\n')
print('Preprocessing finished')
class DAVIS2017_Train(Dataset):
"""DAVIS2017 dataset for training
Return: imgs: N*2*3*H*W,label: N*2*1*H*W, seq-name: N, frame_num:N
"""
def __init__(self,
split='train',
root=cfg.DATA_ROOT,
transform=None,
rgb=False):
self.split = split
self.db_root_dir = root
self.rgb = rgb
self.transform = transform
self.seq_list_file = os.path.join(
self.db_root_dir, 'ImageSets', '2017',
'_'.join(self.split) + '_instances.txt')
self.seqs = []
for splt in self.split:
with open(
os.path.join(self.db_root_dir, 'ImageSets', '2017',
self.split + '.txt')) as f:
seqs_tmp = f.readlines()
seqs_tmp = list(map(lambda elem: elem.strip(), seqs_tmp))
self.seqs.extend(seqs_tmp)
if not self._check_preprocess():
self._preprocess()
self.sample_list = []
for seq_name in self.seqs:
images = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'JPEGImages/480p/',
seq_name.strip())))
images_path = list(
map(
lambda x: os.path.join('JPEGImages/480p/', seq_name.strip(),
x), images))
lab = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/',
seq_name.strip())))
lab_path = list(
map(
lambda x: os.path.join('Annotations/480p/', seq_name.strip(
), x), lab))
for img_path, label_path in zip(images_path[:-1], lab_path[:-1]):
tmp_dic = {
'img': img_path,
'label': label_path,
'seq_name': seq_name,
'frame_num': img_path.split('/')[-1].split('.')[0]
}
self.sample_list.append(tmp_dic)
def __len__(self):
return len(self.sample_list)
def __getitem__(self, idx):
tmp_sample = self.sample_list[idx]
imgpath = tmp_sample['img']
labelpath = tmp_sample['label']
seqname = tmp_sample['seq_name']
frame_num = int(tmp_sample['frame_num']) + 1
next_frame = str(frame_num)
while len(next_frame) != 5:
next_frame = '0' + next_frame
###############################Processing two adjacent frames and labels
img2path = os.path.join('JPEGImages/480p/', seqname,
next_frame + '.' + imgpath.split('.')[-1])
img2 = cv2.imread(os.path.join(self.db_root_dir, img2path))
img2 = np.array(img2, dtype=np.float32)
img1 = cv2.imread(os.path.join(self.db_root_dir, imgpath))
img1 = np.array(img1, dtype=np.float32)
###############
label1 = Image.open(os.path.join(self.db_root_dir, labelpath))
label2path = os.path.join('Annotations/480p/', seqname,
next_frame + '.' + labelpath.split('.')[-1])
label2 = Image.open(os.path.join(self.db_root_dir, label2path))
label1 = np.array(
label1, dtype=np.int32
) # fixed, uint8->int32, because layers.stack does not support uint8
label2 = np.array(
label2, dtype=np.int32
) # fixed, uint8->int32, because layers.stack does not support uint8
###################
ref_tmp_dic = self.ref_frame_dic[seqname]
ref_img = ref_tmp_dic['ref_frame']
ref_scribble_label = ref_tmp_dic['scribble_label']
ref_img = cv2.imread(os.path.join(self.db_root_dir, ref_img))
ref_img = np.array(ref_img, dtype=np.float32)
ref_frame_gt = ref_tmp_dic['ref_frame_gt']
ref_frame_gt = Image.open(os.path.join(self.db_root_dir, ref_frame_gt))
ref_frame_gt = np.array(
ref_frame_gt, dtype=np.int32
) # fixed, uint8->int32, because layers.stack does not support uint8
ref_frame_num = ref_tmp_dic['ref_frame_num']
###################
if self.rgb:
img1 = img1[:, :, [2, 1, 0]]
img2 = img2[:, :, [2, 1, 0]]
ref_img = ref_img[:, :, [2, 1, 0]]
obj_num = self.seq_dict[seqname][-1]
sample = {
'ref_img': ref_img,
'img1': img1,
'img2': img2,
'ref_scribble_label': ref_scribble_label,
'label1': label1,
'label2': label2,
'ref_frame_gt': ref_frame_gt
}
if 'prev_round_label' in ref_tmp_dic:
prev_round_label = ref_tmp_dic['prev_round_label']
prev_round_label = prev_round_label.squeeze()
prev_round_label = prev_round_label.numpy()
sample = {
'ref_img': ref_img,
'img1': img1,
'img2': img2,
'ref_scribble_label': ref_scribble_label,
'label1': label1,
'label2': label2,
'ref_frame_gt': ref_frame_gt,
'prev_round_label': prev_round_label
}
sample['meta'] = {
'seq_name': seqname,
'frame_num': frame_num,
'obj_num': obj_num,
'ref_frame_num': ref_frame_num
}
if self.transform is not None:
sample = self.transform(sample)
return sample
def update_ref_frame_and_label(self,
round_scribble=None,
frame_num=None,
prev_round_label_dic=None):
##########Update reference frame and scribbles
for seq in self.seqs:
scribble = round_scribble[seq]
if frame_num is None:
scr_frame = annotated_frames(scribble)[0]
else:
scr_frame = frame_num[seq]
scr_frame = int(scr_frame)
scr_f = str(scr_frame)
while len(scr_f) != 5:
scr_f = '0' + scr_f
ref_frame_path = os.path.join('JPEGImages/480p', seq,
scr_f + '.jpg')
#######################
ref_frame_gt = os.path.join('Annotations/480p/', seq,
scr_f + '.png')
#########################
ref_tmp = cv2.imread(os.path.join(self.db_root_dir, ref_frame_path))
h_, w_ = ref_tmp.shape[:2]
scribble_masks = scribbles2mask(scribble, (h_, w_))
if frame_num is None:
scribble_label = scribble_masks[scr_frame]
else:
scribble_label = scribble_masks[0]
self.ref_frame_dic[seq] = {
'ref_frame': ref_frame_path,
'scribble_label': scribble_label,
'ref_frame_gt': ref_frame_gt,
'ref_frame_num': scr_frame
}
if prev_round_label_dic is not None:
self.ref_frame_dic[seq] = {
'ref_frame': ref_frame_path,
'scribble_label': scribble_label,
'ref_frame_gt': ref_frame_gt,
'ref_frame_num': scr_frame,
'prev_round_label': prev_round_label_dic[seq]
}
def init_ref_frame_dic(self):
self.ref_frame_dic = {}
scribbles_path = os.path.join(self.db_root_dir, 'Scribbles')
for seq in self.seqs:
selected_json = np.random.choice(
['001.json', '002.json', '003.json'], 1)
selected_json = selected_json[0]
scribble = os.path.join(self.db_root_dir, 'Scribbles', seq,
selected_json)
with open(scribble) as f:
scribble = json.load(f)
# print(scribble)
scr_frame = annotated_frames(scribble)[0]
scr_f = str(scr_frame)
while len(scr_f) != 5:
scr_f = '0' + scr_f
ref_frame_path = os.path.join('JPEGImages/480p', seq,
scr_f + '.jpg')
ref_tmp = cv2.imread(
os.path.join(self.db_root_dir, ref_frame_path))
h_, w_ = ref_tmp.shape[:2]
scribble_masks = scribbles2mask(scribble, (h_, w_))
########################
ref_frame_gt = os.path.join('Annotations/480p/', seq,
scr_f + '.png')
########################
scribble_label = scribble_masks[scr_frame]
self.ref_frame_dic[seq] = {
'ref_frame': ref_frame_path,
'scribble_label': scribble_label,
'ref_frame_gt': ref_frame_gt,
'ref_frame_num': scr_frame
}
########################
def _check_preprocess(self):
_seq_list_file = self.seq_list_file
if not os.path.isfile(_seq_list_file):
return False
else:
self.seq_dict = json.load(open(self.seq_list_file, 'r'))
return True
def _preprocess(self):
self.seq_dict = {}
for seq in self.seqs:
# Read object masks and get number of objects
name_label = np.sort(
os.listdir(
os.path.join(self.db_root_dir, 'Annotations/480p/', seq)))
label_path = os.path.join(self.db_root_dir, 'Annotations/480p/',
seq, name_label[0])
_mask = np.array(Image.open(label_path))
_mask_ids = np.unique(_mask)
n_obj = _mask_ids[-1]
self.seq_dict[seq] = list(range(1, n_obj + 1))
with open(self.seq_list_file, 'w') as outfile:
outfile.write('{{\n\t"{:s}": {:s}'.format(
self.seqs[0], json.dumps(self.seq_dict[self.seqs[0]])))
for ii in range(1, len(self.seqs)):
outfile.write(',\n\t"{:s}": {:s}'.format(
self.seqs[ii], json.dumps(self.seq_dict[self.seqs[ii]])))
outfile.write('\n}\n')
print('Preprocessing finished')
| 38.282318
| 80
| 0.51277
| 3,058
| 25,764
| 4.066383
| 0.065402
| 0.034741
| 0.05388
| 0.056293
| 0.800241
| 0.781021
| 0.728428
| 0.717571
| 0.707117
| 0.697708
| 0
| 0.025664
| 0.355729
| 25,764
| 672
| 81
| 38.339286
| 0.723477
| 0.025889
| 0
| 0.680702
| 0
| 0
| 0.073231
| 0
| 0
| 0
| 0
| 0
| 0.001754
| 1
| 0.038596
| false
| 0
| 0.024561
| 0.007018
| 0.098246
| 0.005263
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
ef463f266210b11924a3bc7a79abea172a1fc566
| 255
|
py
|
Python
|
lluv/__init__.py
|
jmp1617/L.L.U.V.
|
ee910346d56fb1e8d570775ddd1398b6f503ad3e
|
[
"MIT"
] | 1
|
2017-01-19T17:33:53.000Z
|
2017-01-19T17:33:53.000Z
|
lluv/__init__.py
|
jmp1617/L.L.U.V.
|
ee910346d56fb1e8d570775ddd1398b6f503ad3e
|
[
"MIT"
] | null | null | null |
lluv/__init__.py
|
jmp1617/L.L.U.V.
|
ee910346d56fb1e8d570775ddd1398b6f503ad3e
|
[
"MIT"
] | null | null | null |
import lluv.lluv_tui as lt
import lluv.lluv_cli as lc
import lluv.lluv_simple_cli as lsc
import lluv.lluvconsole as lconsole
def tui():
lt.start()
def cli():
lc.start()
def simple_cli():
lsc.start()
def console():
lconsole.start()
| 12.142857
| 35
| 0.686275
| 41
| 255
| 4.146341
| 0.341463
| 0.235294
| 0.247059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.203922
| 255
| 20
| 36
| 12.75
| 0.837438
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
323ac7ac47da1b02efeeb8c0db2b1b33439c47da
| 343
|
py
|
Python
|
bitmovin_api_sdk/encoding/manifests/dash/periods/adaptationsets/representations/cmaf/contentprotection/__init__.py
|
jaythecaesarean/bitmovin-api-sdk-python
|
48166511fcb9082041c552ace55a9b66cc59b794
|
[
"MIT"
] | 11
|
2019-07-03T10:41:16.000Z
|
2022-02-25T21:48:06.000Z
|
bitmovin_api_sdk/encoding/manifests/dash/periods/adaptationsets/representations/cmaf/contentprotection/__init__.py
|
jaythecaesarean/bitmovin-api-sdk-python
|
48166511fcb9082041c552ace55a9b66cc59b794
|
[
"MIT"
] | 8
|
2019-11-23T00:01:25.000Z
|
2021-04-29T12:30:31.000Z
|
bitmovin_api_sdk/encoding/manifests/dash/periods/adaptationsets/representations/cmaf/contentprotection/__init__.py
|
jaythecaesarean/bitmovin-api-sdk-python
|
48166511fcb9082041c552ace55a9b66cc59b794
|
[
"MIT"
] | 13
|
2020-01-02T14:58:18.000Z
|
2022-03-26T12:10:30.000Z
|
from bitmovin_api_sdk.encoding.manifests.dash.periods.adaptationsets.representations.cmaf.contentprotection.contentprotection_api import ContentprotectionApi
from bitmovin_api_sdk.encoding.manifests.dash.periods.adaptationsets.representations.cmaf.contentprotection.content_protection_list_query_params import ContentProtectionListQueryParams
| 114.333333
| 184
| 0.924198
| 35
| 343
| 8.8
| 0.571429
| 0.077922
| 0.097403
| 0.116883
| 0.623377
| 0.623377
| 0.623377
| 0.623377
| 0.623377
| 0.623377
| 0
| 0
| 0.023324
| 343
| 2
| 185
| 171.5
| 0.919403
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
3292b91e335f141620828ce2acdea9c009e9e96d
| 298
|
py
|
Python
|
snmpagent_unity/unity_impl/HostAssignedStorageVolumes.py
|
factioninc/snmp-unity-agent
|
3525dc0fac60d1c784dcdd7c41693544bcbef843
|
[
"Apache-2.0"
] | 2
|
2019-03-01T11:14:59.000Z
|
2019-10-02T17:47:59.000Z
|
snmpagent_unity/unity_impl/HostAssignedStorageVolumes.py
|
factioninc/snmp-unity-agent
|
3525dc0fac60d1c784dcdd7c41693544bcbef843
|
[
"Apache-2.0"
] | 2
|
2019-03-01T11:26:29.000Z
|
2019-10-11T18:56:54.000Z
|
snmpagent_unity/unity_impl/HostAssignedStorageVolumes.py
|
factioninc/snmp-unity-agent
|
3525dc0fac60d1c784dcdd7c41693544bcbef843
|
[
"Apache-2.0"
] | 1
|
2019-10-03T21:09:17.000Z
|
2019-10-03T21:09:17.000Z
|
class HostAssignedStorageVolumes(object):
def read_get(self, name, idx_name, unity_client):
return unity_client.get_host_assigned_volumes(idx_name)
class HostAssignedStorageVolumesColumn(object):
def get_idx(self, name, idx, unity_client):
return unity_client.get_hosts()
| 33.111111
| 63
| 0.771812
| 37
| 298
| 5.891892
| 0.459459
| 0.201835
| 0.100917
| 0.201835
| 0.284404
| 0.284404
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147651
| 298
| 8
| 64
| 37.25
| 0.858268
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
08c4e82b5e4394594f00845e802e6001e7fd273f
| 24
|
py
|
Python
|
tests/__init__.py
|
MitalAshok/xxkcd
|
1db3e6819a3bff28eebffee13dc10be73d030945
|
[
"MIT"
] | 1
|
2019-01-30T05:52:12.000Z
|
2019-01-30T05:52:12.000Z
|
tests/__init__.py
|
MitalAshok/xxkcd
|
1db3e6819a3bff28eebffee13dc10be73d030945
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
MitalAshok/xxkcd
|
1db3e6819a3bff28eebffee13dc10be73d030945
|
[
"MIT"
] | null | null | null |
from . import test_xkcd
| 12
| 23
| 0.791667
| 4
| 24
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 24
| 1
| 24
| 24
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
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| 0
| true
| 0
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| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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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
| 1
| 0
|
0
| 6
|
3eaf2a65991173cc175d208cc853604196088cf1
| 81
|
py
|
Python
|
utils/__init__.py
|
antonpetkoff/relation-extraction
|
4485cad683be0e92fc1dfa3a767f59ca0f702410
|
[
"MIT"
] | 2
|
2019-02-16T08:30:58.000Z
|
2019-02-16T10:20:33.000Z
|
utils/__init__.py
|
antonpetkoff/relation-extraction
|
4485cad683be0e92fc1dfa3a767f59ca0f702410
|
[
"MIT"
] | null | null | null |
utils/__init__.py
|
antonpetkoff/relation-extraction
|
4485cad683be0e92fc1dfa3a767f59ca0f702410
|
[
"MIT"
] | null | null | null |
from . import data_utils
from . import visualization
from . import preprocessing
| 20.25
| 27
| 0.814815
| 10
| 81
| 6.5
| 0.6
| 0.461538
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148148
| 81
| 3
| 28
| 27
| 0.942029
| 0
| 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
| 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
| 6
|
3ed5bb4cc563e7f556dc955848a65fd151de829a
| 42
|
py
|
Python
|
psfpred/dataset/__init__.py
|
jeffreyruffolo/ProteinSuperfamPredictor
|
0556f4f78173cdb03c3c3bd59b8c997e9b745a9a
|
[
"MIT"
] | null | null | null |
psfpred/dataset/__init__.py
|
jeffreyruffolo/ProteinSuperfamPredictor
|
0556f4f78173cdb03c3c3bd59b8c997e9b745a9a
|
[
"MIT"
] | null | null | null |
psfpred/dataset/__init__.py
|
jeffreyruffolo/ProteinSuperfamPredictor
|
0556f4f78173cdb03c3c3bd59b8c997e9b745a9a
|
[
"MIT"
] | null | null | null |
from .ProteinDataset import ProteinDataset
| 42
| 42
| 0.904762
| 4
| 42
| 9.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 42
| 1
| 42
| 42
| 0.974359
| 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
| 1
| 0
|
0
| 6
|
411cd009bf1543601a99e7e4fa9abfe0c9eab836
| 98
|
py
|
Python
|
src/oasapi/cli/__init__.py
|
sdementen/oasapi
|
d2779b9945ba558d3b7fd5eef6eff5ea48a70d51
|
[
"BSD-3-Clause"
] | 1
|
2020-01-18T20:16:32.000Z
|
2020-01-18T20:16:32.000Z
|
src/oasapi/cli/__init__.py
|
sdementen/oasapi
|
d2779b9945ba558d3b7fd5eef6eff5ea48a70d51
|
[
"BSD-3-Clause"
] | 11
|
2020-01-15T14:19:46.000Z
|
2020-03-03T12:47:38.000Z
|
src/oasapi/cli/__init__.py
|
sdementen/oasapi
|
d2779b9945ba558d3b7fd5eef6eff5ea48a70d51
|
[
"BSD-3-Clause"
] | null | null | null |
from .cli import main, validate, prune, filter
__all__ = ["main", "validate", "prune", "filter"]
| 24.5
| 49
| 0.673469
| 12
| 98
| 5.166667
| 0.666667
| 0.387097
| 0.548387
| 0.741935
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 98
| 3
| 50
| 32.666667
| 0.738095
| 0
| 0
| 0
| 0
| 0
| 0.234694
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
f5b4910a6766eb97e051693ed904524ac2d7f9b0
| 36
|
py
|
Python
|
src/models/train_model.py
|
EvolveArt/ML_Practical_Session
|
95f1c5b73a0892a10cb1e2f3cbed72f3e4c24b89
|
[
"MIT"
] | null | null | null |
src/models/train_model.py
|
EvolveArt/ML_Practical_Session
|
95f1c5b73a0892a10cb1e2f3cbed72f3e4c24b89
|
[
"MIT"
] | null | null | null |
src/models/train_model.py
|
EvolveArt/ML_Practical_Session
|
95f1c5b73a0892a10cb1e2f3cbed72f3e4c24b89
|
[
"MIT"
] | null | null | null |
from sklearn.cluster import KMeans
| 12
| 34
| 0.833333
| 5
| 36
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.138889
| 36
| 2
| 35
| 18
| 0.967742
| 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
| 1
| 0
|
0
| 6
|
eb2784e9ca1c735de49e188182a4eb62d459c2a2
| 47
|
py
|
Python
|
python/nlusvc/spacy/svc/__init__.py
|
jiportilla/ontology
|
8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40
|
[
"MIT"
] | null | null | null |
python/nlusvc/spacy/svc/__init__.py
|
jiportilla/ontology
|
8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40
|
[
"MIT"
] | null | null | null |
python/nlusvc/spacy/svc/__init__.py
|
jiportilla/ontology
|
8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40
|
[
"MIT"
] | null | null | null |
from .perform_pos_parse import PerformPosParse
| 23.5
| 46
| 0.893617
| 6
| 47
| 6.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085106
| 47
| 1
| 47
| 47
| 0.930233
| 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
| 1
| 0
|
0
| 6
|
eb2b585f7e181c3c1a059870c29ac3d5f44f6a63
| 146
|
py
|
Python
|
Agents/PassAgent.py
|
TmanHef/CentipedeRL
|
400d6e71826a79c1a597b057b7543080d3f3c376
|
[
"MIT"
] | 1
|
2020-08-12T02:43:57.000Z
|
2020-08-12T02:43:57.000Z
|
Agents/PassAgent.py
|
TmanHef/CentipedeRL
|
400d6e71826a79c1a597b057b7543080d3f3c376
|
[
"MIT"
] | null | null | null |
Agents/PassAgent.py
|
TmanHef/CentipedeRL
|
400d6e71826a79c1a597b057b7543080d3f3c376
|
[
"MIT"
] | null | null | null |
from Agent import Agent
from Constants import pass_action
class PassAgent(Agent):
def decide(self, leg, round):
return pass_action
| 16.222222
| 33
| 0.732877
| 20
| 146
| 5.25
| 0.7
| 0.190476
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.212329
| 146
| 8
| 34
| 18.25
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0.6
| 0.4
| 0.2
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
|
0
| 6
|
de3c10f9d875b469aa56935c2648057209f65f7f
| 45
|
py
|
Python
|
apf/core/management/__init__.py
|
dirodriguezm/APF
|
323ed53c00cd884da488d4e87db83825ee87da6a
|
[
"MIT"
] | 2
|
2020-03-12T17:27:11.000Z
|
2020-05-28T21:21:51.000Z
|
apf/core/management/__init__.py
|
alercebroker/APF
|
d71cec49ee7f4a1667210b70c48501d036d5c08b
|
[
"MIT"
] | 15
|
2019-11-25T19:51:39.000Z
|
2022-03-04T19:00:31.000Z
|
apf/core/management/__init__.py
|
dirodriguezm/APF
|
323ed53c00cd884da488d4e87db83825ee87da6a
|
[
"MIT"
] | 2
|
2020-06-21T07:55:58.000Z
|
2022-02-08T11:09:05.000Z
|
from . import helpers
from .helpers import *
| 15
| 22
| 0.755556
| 6
| 45
| 5.666667
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177778
| 45
| 2
| 23
| 22.5
| 0.918919
| 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
| 1
| 0
|
0
| 6
|
de753749e3b93644ac81d934d58a4cf390d68057
| 63
|
py
|
Python
|
frontends/python/rv_bfms/__init__.py
|
tblink-bfms/tblink-bfms-rv
|
a8a983e5c9ab2692fb02d8cc689f40e7d8c347da
|
[
"Apache-2.0"
] | null | null | null |
frontends/python/rv_bfms/__init__.py
|
tblink-bfms/tblink-bfms-rv
|
a8a983e5c9ab2692fb02d8cc689f40e7d8c347da
|
[
"Apache-2.0"
] | null | null | null |
frontends/python/rv_bfms/__init__.py
|
tblink-bfms/tblink-bfms-rv
|
a8a983e5c9ab2692fb02d8cc689f40e7d8c347da
|
[
"Apache-2.0"
] | null | null | null |
from .rv_initiator_bfm import *
from .rv_target_bfm import *
| 12.6
| 31
| 0.777778
| 10
| 63
| 4.5
| 0.6
| 0.266667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15873
| 63
| 4
| 32
| 15.75
| 0.849057
| 0
| 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
| 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
| 6
|
dea08d1c7063711d32d84b75064241d30373bb4d
| 292
|
py
|
Python
|
privacy_evaluator/output/__init__.py
|
chen-yuxuan/privacy-evaluator
|
ed4852408108c3e6a01216af4183261945fd7e67
|
[
"MIT"
] | 7
|
2021-04-10T15:01:19.000Z
|
2022-02-08T14:45:21.000Z
|
privacy_evaluator/output/__init__.py
|
chen-yuxuan/privacy-evaluator
|
ed4852408108c3e6a01216af4183261945fd7e67
|
[
"MIT"
] | 175
|
2021-04-13T08:32:27.000Z
|
2021-08-30T09:44:51.000Z
|
privacy_evaluator/output/__init__.py
|
chen-yuxuan/privacy-evaluator
|
ed4852408108c3e6a01216af4183261945fd7e67
|
[
"MIT"
] | 21
|
2021-04-13T08:03:36.000Z
|
2021-10-05T15:35:01.000Z
|
"""
Module providing output wrapper.
"""
from .user_output import UserOutput
from .user_output_inference_attack import UserOutputInferenceAttack
from .user_output_inference_attack_analysis import UserOutputInferenceAttackAnalysis
from .user_output_privacy_score import UserOutputPrivacyScore
| 36.5
| 84
| 0.886986
| 31
| 292
| 8
| 0.516129
| 0.129032
| 0.225806
| 0.185484
| 0.233871
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075342
| 292
| 7
| 85
| 41.714286
| 0.918519
| 0.109589
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dea3528950810cbf032d4462a2d57ebe3efc3b5b
| 20
|
py
|
Python
|
colab/colab/__init__.py
|
buschNT/deep_learning_public
|
8b4e0c56998fe1c25c564859f16d0d86584ed5fb
|
[
"MIT"
] | null | null | null |
colab/colab/__init__.py
|
buschNT/deep_learning_public
|
8b4e0c56998fe1c25c564859f16d0d86584ed5fb
|
[
"MIT"
] | null | null | null |
colab/colab/__init__.py
|
buschNT/deep_learning_public
|
8b4e0c56998fe1c25c564859f16d0d86584ed5fb
|
[
"MIT"
] | null | null | null |
from .colab import *
| 20
| 20
| 0.75
| 3
| 20
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 20
| 1
| 20
| 20
| 0.882353
| 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
| 1
| 0
|
0
| 6
|
deab42bf413caa35b712bd542e48ed5ec978fefc
| 7,172
|
py
|
Python
|
DailyProgrammer/DP20170529A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | 2
|
2020-12-23T18:59:22.000Z
|
2021-04-14T13:16:09.000Z
|
DailyProgrammer/DP20170529A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | null | null | null |
DailyProgrammer/DP20170529A.py
|
DayGitH/Python-Challenges
|
bc32f1332a92fcc2dfa6f5ea4d95f8a8d64c3edf
|
[
"MIT"
] | null | null | null |
"""
[2017-05-29] Challenge #317 [Easy] Collatz Tag System
https://www.reddit.com/r/dailyprogrammer/comments/6e08v6/20170529_challenge_317_easy_collatz_tag_system/
# Description
Implement the [Collatz Conjecture tag system described
here](https://en.wikipedia.org/wiki/Tag_system#Example:_Computation_of_Collatz_sequences)
# Input Description
A string of n *a*'s
# Output Description
Print the string at each step. The last line should be "*a*" (assuming the Collatz conjecture)
# Challenge Input
aaa
aaaaa
# Challenge Output
aaa
abc
cbc
caaa
aaaaa
aaabc
abcbc
cbcbc
cbcaaa
caaaaaa
aaaaaaaa
aaaaaabc
aaaabcbc
aabcbcbc
bcbcbcbc
bcbcbca
bcbcaa
bcaaa
aaaa
aabc
bcbc
bca
aa
bc
a
aaaaaaa
aaaaabc
aaabcbc
abcbcbc
cbcbcbc
cbcbcaaa
cbcaaaaaa
caaaaaaaaa
aaaaaaaaaaa
aaaaaaaaabc
aaaaaaabcbc
aaaaabcbcbc
aaabcbcbcbc
abcbcbcbcbc
cbcbcbcbcbc
cbcbcbcbcaaa
cbcbcbcaaaaaa
cbcbcaaaaaaaaa
cbcaaaaaaaaaaaa
caaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaabc
aaaaaaaaaaaaabcbc
aaaaaaaaaaabcbcbc
aaaaaaaaabcbcbcbc
aaaaaaabcbcbcbcbc
aaaaabcbcbcbcbcbc
aaabcbcbcbcbcbcbc
abcbcbcbcbcbcbcbc
cbcbcbcbcbcbcbcbc
cbcbcbcbcbcbcbcaaa
cbcbcbcbcbcbcaaaaaa
cbcbcbcbcbcaaaaaaaaa
cbcbcbcbcaaaaaaaaaaaa
cbcbcbcaaaaaaaaaaaaaaa
cbcbcaaaaaaaaaaaaaaaaaa
cbcaaaaaaaaaaaaaaaaaaaaa
caaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaabc
aaaaaaaaaaaaaaaaaaaaaabcbc
aaaaaaaaaaaaaaaaaaaabcbcbc
aaaaaaaaaaaaaaaaaabcbcbcbc
aaaaaaaaaaaaaaaabcbcbcbcbc
aaaaaaaaaaaaaabcbcbcbcbcbc
aaaaaaaaaaaabcbcbcbcbcbcbc
aaaaaaaaaabcbcbcbcbcbcbcbc
aaaaaaaabcbcbcbcbcbcbcbcbc
aaaaaabcbcbcbcbcbcbcbcbcbc
aaaabcbcbcbcbcbcbcbcbcbcbc
aabcbcbcbcbcbcbcbcbcbcbcbc
bcbcbcbcbcbcbcbcbcbcbcbcbc
bcbcbcbcbcbcbcbcbcbcbcbca
bcbcbcbcbcbcbcbcbcbcbcaa
bcbcbcbcbcbcbcbcbcbcaaa
bcbcbcbcbcbcbcbcbcaaaa
bcbcbcbcbcbcbcbcaaaaa
bcbcbcbcbcbcbcaaaaaa
bcbcbcbcbcbcaaaaaaa
bcbcbcbcbcaaaaaaaa
bcbcbcbcaaaaaaaaa
bcbcbcaaaaaaaaaa
bcbcaaaaaaaaaaa
bcaaaaaaaaaaaa
aaaaaaaaaaaaa
aaaaaaaaaaabc
aaaaaaaaabcbc
aaaaaaabcbcbc
aaaaabcbcbcbc
aaabcbcbcbcbc
abcbcbcbcbcbc
cbcbcbcbcbcbc
cbcbcbcbcbcaaa
cbcbcbcbcaaaaaa
cbcbcbcaaaaaaaaa
cbcbcaaaaaaaaaaaa
cbcaaaaaaaaaaaaaaa
caaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaabc
aaaaaaaaaaaaaaaabcbc
aaaaaaaaaaaaaabcbcbc
aaaaaaaaaaaabcbcbcbc
aaaaaaaaaabcbcbcbcbc
aaaaaaaabcbcbcbcbcbc
aaaaaabcbcbcbcbcbcbc
aaaabcbcbcbcbcbcbcbc
aabcbcbcbcbcbcbcbcbc
bcbcbcbcbcbcbcbcbcbc
bcbcbcbcbcbcbcbcbca
bcbcbcbcbcbcbcbcaa
bcbcbcbcbcbcbcaaa
bcbcbcbcbcbcaaaa
bcbcbcbcbcaaaaa
bcbcbcbcaaaaaa
bcbcbcaaaaaaa
bcbcaaaaaaaa
bcaaaaaaaaa
aaaaaaaaaa
aaaaaaaabc
aaaaaabcbc
aaaabcbcbc
aabcbcbcbc
bcbcbcbcbc
bcbcbcbca
bcbcbcaa
bcbcaaa
bcaaaa
aaaaa
aaabc
abcbc
cbcbc
cbcaaa
caaaaaa
aaaaaaaa
aaaaaabc
aaaabcbc
aabcbcbc
bcbcbcbc
bcbcbca
bcbcaa
bcaaa
aaaa
aabc
bcbc
bca
aa
bc
a
# Notes/Hints
The [Collatz Conjecture](https://en.wikipedia.org/wiki/3x_%2B_1_problem)
If you're not familiar with tag systems, you can read the [Wikipedia article on them
here](https://en.wikipedia.org/wiki/Tag_system)
# Bonus
Implement the same tag system as a cyclic tag system using the [schema described
here](https://en.wikipedia.org/wiki/Tag_system#Emulation_of_tag_systems_by_cyclic_tag_systems)
# Bonus Input
100100100
# Bonus Output
00100100010001
0100100010001
100100010001
00100010001
0100010001
100010001
00010001010001
0010001010001
010001010001
10001010001
0001010001
001010001
01010001
1010001
010001100100100
10001100100100
0001100100100
001100100100
01100100100
1100100100
100100100100100100
00100100100100100
0100100100100100
100100100100100
00100100100100010001
0100100100100010001
100100100100010001
00100100100010001
0100100100010001
100100100010001
00100100010001010001
0100100010001010001
100100010001010001
00100010001010001
0100010001010001
100010001010001
00010001010001010001
0010001010001010001
010001010001010001
10001010001010001
0001010001010001
001010001010001
01010001010001
1010001010001
010001010001100100100
10001010001100100100
0001010001100100100
001010001100100100
01010001100100100
1010001100100100
010001100100100100100100
10001100100100100100100
0001100100100100100100
001100100100100100100
01100100100100100100
1100100100100100100
100100100100100100100100100
00100100100100100100100100
0100100100100100100100100
100100100100100100100100
00100100100100100100100010001
0100100100100100100100010001
100100100100100100100010001
00100100100100100100010001
0100100100100100100010001
100100100100100100010001
00100100100100100010001010001
0100100100100100010001010001
100100100100100010001010001
00100100100100010001010001
0100100100100010001010001
100100100100010001010001
00100100100010001010001010001
0100100100010001010001010001
100100100010001010001010001
00100100010001010001010001
0100100010001010001010001
100100010001010001010001
00100010001010001010001010001
0100010001010001010001010001
100010001010001010001010001
00010001010001010001010001
0010001010001010001010001
010001010001010001010001
10001010001010001010001
0001010001010001010001100
001010001010001010001100
01010001010001010001100
1010001010001010001100
010001010001010001100
10001010001010001100
0001010001010001100100
001010001010001100100
01010001010001100100
1010001010001100100
010001010001100100
10001010001100100
0001010001100100100
001010001100100100
01010001100100100
1010001100100100
010001100100100
10001100100100
0001100100100100
001100100100100
01100100100100
1100100100100
100100100100
00100100100010001
0100100100010001
100100100010001
00100100010001
0100100010001
100100010001
00100010001010001
0100010001010001
100010001010001
00010001010001
0010001010001
010001010001
10001010001
0001010001100
001010001100
01010001100
1010001100
010001100
10001100
0001100100
001100100
01100100
1100100
100100
00100010001
0100010001
100010001
00010001
0010001
010001
10001
0001100
001100
01100
1100
100
# Credit
This challenge was proposed by /u/thebutterflydefect, many thanks. If you have a challenge idea, please share it in
/r/dailyprogrammer_ideas and there's a good chance we'll use it.
"""
def main():
pass
if __name__ == "__main__":
main()
| 21.281899
| 115
| 0.755717
| 489
| 7,172
| 11.018405
| 0.723926
| 0.013363
| 0.011878
| 0.014105
| 0.080735
| 0.076466
| 0.064588
| 0.064588
| 0.057906
| 0.041203
| 0
| 0.445348
| 0.228249
| 7,172
| 336
| 116
| 21.345238
| 0.528094
| 0.992889
| 0
| 0
| 0
| 0
| 0.125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0
| 0
| 0.25
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
dede36196c52c3441a83591753983cb25130d76f
| 129
|
py
|
Python
|
lib/models/__init__.py
|
Impavidity/neural-srl
|
d4a3d313afd455f3af2ef3386eaca5181685188b
|
[
"MIT"
] | 5
|
2018-12-10T04:05:36.000Z
|
2021-03-08T21:25:37.000Z
|
lib/models/__init__.py
|
Impavidity/neural-srl
|
d4a3d313afd455f3af2ef3386eaca5181685188b
|
[
"MIT"
] | 1
|
2018-12-10T04:06:06.000Z
|
2018-12-10T04:06:06.000Z
|
lib/models/__init__.py
|
Impavidity/neural-srl
|
d4a3d313afd455f3af2ef3386eaca5181685188b
|
[
"MIT"
] | null | null | null |
from nn import NN
import rnn
from simplesrlers import *
from sensedisamb import *
from multitask import *
from parsers import *
| 16.125
| 26
| 0.790698
| 18
| 129
| 5.666667
| 0.444444
| 0.294118
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.178295
| 129
| 7
| 27
| 18.428571
| 0.962264
| 0
| 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
| 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
| 6
|
720da298cf82dea315684b8bb3a07d326679c927
| 747
|
py
|
Python
|
tracker/tracker_zoo.py
|
maxzuo/CS_4476_CV_Project
|
9122ebeb46201bda07be3e75b658e7c4a7eefb7b
|
[
"Apache-2.0"
] | null | null | null |
tracker/tracker_zoo.py
|
maxzuo/CS_4476_CV_Project
|
9122ebeb46201bda07be3e75b658e7c4a7eefb7b
|
[
"Apache-2.0"
] | null | null | null |
tracker/tracker_zoo.py
|
maxzuo/CS_4476_CV_Project
|
9122ebeb46201bda07be3e75b658e7c4a7eefb7b
|
[
"Apache-2.0"
] | null | null | null |
import cv2
from .tracker import Tracker
class CSRT(Tracker):
def __init__(self,frame=None,bbox=None,**kwargs):
super().__init__(cv2.TrackerCSRT_create,**kwargs)
if frame is not None and bbox is not None:
self._init_tracker(frame, bbox)
class KCF(Tracker):
def __init__(self,frame=None,bbox=None,**kwargs):
super().__init__(cv2.TrackerKCF_create,**kwargs)
if frame is not None and bbox is not None:
self._init_tracker(frame, bbox)
class GOTURN(Tracker):
def __init__(self,frame=None,bbox=None,**kwargs):
super().__init__(cv2.TrackerGOTURN_create,**kwargs)
if frame is not None and bbox is not None:
self._init_tracker(frame, bbox)
| 37.35
| 60
| 0.657296
| 102
| 747
| 4.490196
| 0.235294
| 0.065502
| 0.117904
| 0.117904
| 0.81441
| 0.81441
| 0.81441
| 0.81441
| 0.81441
| 0.81441
| 0
| 0.006981
| 0.232932
| 747
| 20
| 61
| 37.35
| 0.792321
| 0
| 0
| 0.529412
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.176471
| false
| 0
| 0.117647
| 0
| 0.470588
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
a0dae46eb14725e9591cb1fe657283d1a37188ac
| 105
|
py
|
Python
|
ch2/Fibonacci_Matrix/test_algorithm.py
|
omar659/Algorithms-Sequential-Parallel-Distributed
|
3543631139a20625f413cea2ba1f013f3a40d123
|
[
"MIT"
] | 2
|
2020-02-19T09:27:20.000Z
|
2020-02-19T09:28:21.000Z
|
ch2/Fibonacci_Matrix/test_algorithm.py
|
omar-3/Algorithms-Sequential-Parallel-Distributed
|
3543631139a20625f413cea2ba1f013f3a40d123
|
[
"MIT"
] | null | null | null |
ch2/Fibonacci_Matrix/test_algorithm.py
|
omar-3/Algorithms-Sequential-Parallel-Distributed
|
3543631139a20625f413cea2ba1f013f3a40d123
|
[
"MIT"
] | null | null | null |
from algorithm import fib
def test1():
assert fib(11) == 89
def test2():
assert fib(19) == 4181
| 15
| 26
| 0.628571
| 16
| 105
| 4.125
| 0.75
| 0.272727
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 0.238095
| 105
| 7
| 26
| 15
| 0.675
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.4
| true
| 0
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 6
|
19b9601f1918b8191651a710bc47d764b562ece1
| 44
|
py
|
Python
|
semestr_work/__main__.py
|
martilad/BI-PYT2018
|
20584a952f00f1cda6da15a5c53878df5f02ff72
|
[
"MIT"
] | null | null | null |
semestr_work/__main__.py
|
martilad/BI-PYT2018
|
20584a952f00f1cda6da15a5c53878df5f02ff72
|
[
"MIT"
] | null | null | null |
semestr_work/__main__.py
|
martilad/BI-PYT2018
|
20584a952f00f1cda6da15a5c53878df5f02ff72
|
[
"MIT"
] | null | null | null |
from GUI import GUI
gui = GUI()
gui.start()
| 11
| 19
| 0.681818
| 8
| 44
| 3.75
| 0.5
| 0.6
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 44
| 4
| 20
| 11
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 1
| 0
| null | 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
| 6
|
19c29cc1b690a92e05cdd698ec22f2ec1d0a3247
| 34
|
py
|
Python
|
examples/one_service/tests/test_service.py
|
Svtter/micro
|
f88941fee953d7a8fbf6c313dfc79602c1702cc5
|
[
"Apache-1.1"
] | 1
|
2021-11-20T10:47:39.000Z
|
2021-11-20T10:47:39.000Z
|
examples/one_service/tests/test_service.py
|
Svtter/micro
|
f88941fee953d7a8fbf6c313dfc79602c1702cc5
|
[
"Apache-1.1"
] | null | null | null |
examples/one_service/tests/test_service.py
|
Svtter/micro
|
f88941fee953d7a8fbf6c313dfc79602c1702cc5
|
[
"Apache-1.1"
] | null | null | null |
def test_work_service():
pass
| 11.333333
| 24
| 0.705882
| 5
| 34
| 4.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205882
| 34
| 2
| 25
| 17
| 0.814815
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
c212b2e2764f7f16777df208724c7c655fd95b7a
| 220
|
py
|
Python
|
tests/sneks/test_cool_snek.py
|
ARMcK-hub/template-python
|
c5e8c48fc92dde522f91227189a3d4822c86d170
|
[
"MIT"
] | null | null | null |
tests/sneks/test_cool_snek.py
|
ARMcK-hub/template-python
|
c5e8c48fc92dde522f91227189a3d4822c86d170
|
[
"MIT"
] | 2
|
2022-02-24T02:58:57.000Z
|
2022-02-24T02:59:15.000Z
|
tests/sneks/test_cool_snek.py
|
ARMcK-hub/template-pyspark
|
d5ba2e0175cab449b2a3b345b2be8978a7d238a3
|
[
"MIT"
] | null | null | null |
from snek_case.sneks import CoolSnek
def test_can_create() -> None:
# Assemble / Act / Assert
CoolSnek()
def test_type_is_cool() -> None:
# Assemble / Act / Assert
assert CoolSnek.snek_type == "cool"
| 18.333333
| 39
| 0.668182
| 29
| 220
| 4.827586
| 0.586207
| 0.157143
| 0.214286
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.222727
| 220
| 11
| 40
| 20
| 0.818713
| 0.213636
| 0
| 0
| 0
| 0
| 0.023529
| 0
| 0
| 0
| 0
| 0
| 0.2
| 1
| 0.4
| true
| 0
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 6
|
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