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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
001e038da0a40b5ac2df6951941a334b7c2fca41
| 191
|
py
|
Python
|
smokestack/types/operation_result.py
|
cariad/smokestack
|
c1f75e1708368e5a9cd8357025b8c20352158ae7
|
[
"MIT"
] | null | null | null |
smokestack/types/operation_result.py
|
cariad/smokestack
|
c1f75e1708368e5a9cd8357025b8c20352158ae7
|
[
"MIT"
] | 12
|
2021-10-12T08:32:50.000Z
|
2021-12-26T09:43:56.000Z
|
smokestack/types/operation_result.py
|
cariad/smokestack
|
c1f75e1708368e5a9cd8357025b8c20352158ae7
|
[
"MIT"
] | null | null | null |
from dataclasses import dataclass
from io import StringIO
from typing import Optional
@dataclass
class OperationResult:
out: StringIO
token: str
exception: Optional[str] = None
| 17.363636
| 35
| 0.764398
| 23
| 191
| 6.347826
| 0.652174
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.193717
| 191
| 10
| 36
| 19.1
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| 0
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| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
cc6fd907f2ee77857d99df1c6e183ac19eaa3bd8
| 46
|
py
|
Python
|
venv/Lib/site-packages/IPython/utils/_sysinfo.py
|
itsAbdulKhadar/Machine-Learning-with-Streamlit
|
c8a0c7ca5a1bcf2730ae9587bcddfebe323965a3
|
[
"MIT"
] | null | null | null |
venv/Lib/site-packages/IPython/utils/_sysinfo.py
|
itsAbdulKhadar/Machine-Learning-with-Streamlit
|
c8a0c7ca5a1bcf2730ae9587bcddfebe323965a3
|
[
"MIT"
] | 20
|
2021-05-03T18:02:23.000Z
|
2022-03-12T12:01:04.000Z
|
venv/Lib/site-packages/IPython/utils/_sysinfo.py
|
itsAbdulKhadar/Machine-Learning-with-Streamlit
|
c8a0c7ca5a1bcf2730ae9587bcddfebe323965a3
|
[
"MIT"
] | 2
|
2021-06-11T21:55:16.000Z
|
2021-06-21T00:06:00.000Z
|
# GENERATED BY setup.py
commit = u"30cd45eb7"
| 15.333333
| 23
| 0.73913
| 7
| 46
| 4.857143
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 0.152174
| 46
| 2
| 24
| 23
| 0.74359
| 0.456522
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| 0.391304
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| false
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|
0
| 4
|
cc8cd23b0e2069a0633ff44a775e29eb4c66747a
| 180
|
py
|
Python
|
setup.py
|
guidebee/guessing_number
|
f0a408713c85f1da911521ed4713045d00c5123d
|
[
"MIT"
] | 1
|
2021-01-29T17:16:28.000Z
|
2021-01-29T17:16:28.000Z
|
setup.py
|
guidebee/guessing_number
|
f0a408713c85f1da911521ed4713045d00c5123d
|
[
"MIT"
] | null | null | null |
setup.py
|
guidebee/guessing_number
|
f0a408713c85f1da911521ed4713045d00c5123d
|
[
"MIT"
] | null | null | null |
from setuptools import find_packages, setup
setup(
name="guessing_number",
version="0.0.1",
install_requires=["gym>=0.2.3", "numpy"],
packages=find_packages(),
)
| 18
| 45
| 0.666667
| 24
| 180
| 4.833333
| 0.75
| 0.206897
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.166667
| 180
| 9
| 46
| 20
| 0.733333
| 0
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| 0
| 0.195531
| 0
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| 0
| 1
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| true
| 0
| 0.142857
| 0
| 0.142857
| 0
| 1
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| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
cc90b5db456f7e94a0a2bd3b04448c23e5bd921d
| 725
|
py
|
Python
|
tests/test_client.py
|
adrihor/pythonista-dropbox
|
cb4a9cd3b1ac0a04be13944003e0897e7d82f375
|
[
"0BSD"
] | 2
|
2021-03-04T14:06:19.000Z
|
2021-03-04T21:08:52.000Z
|
tests/test_client.py
|
adrihor/pythonista-dropbox
|
cb4a9cd3b1ac0a04be13944003e0897e7d82f375
|
[
"0BSD"
] | null | null | null |
tests/test_client.py
|
adrihor/pythonista-dropbox
|
cb4a9cd3b1ac0a04be13944003e0897e7d82f375
|
[
"0BSD"
] | null | null | null |
import os
def test_access_key_and_secret_set():
"""TODO: Docstring for test_access_key_and_secret_set.
:returns: TODO
"""
from pythonista_dropbox.client import keychain_key_words
from pythonista_dropbox.client import keychain
access = [keychain.get_password(service, account)
for service, account in keychain_key_words]
assert all(access), "Run main in request_auth_token to set access."
def test_client():
from pythonista_dropbox.client import get_client
from pythonista_dropbox.request_auth_token import TOKEN
client = get_client(TOKEN)
path = "/Public"
public_metadata = client.metadata(path)
assert os.path.join('/', public_metadata.name) == path
| 27.884615
| 71
| 0.736552
| 96
| 725
| 5.270833
| 0.385417
| 0.110672
| 0.166008
| 0.160079
| 0.326087
| 0.26087
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186207
| 725
| 25
| 72
| 29
| 0.857627
| 0.091034
| 0
| 0
| 0
| 0
| 0.082426
| 0
| 0
| 0
| 0
| 0.08
| 0.142857
| 1
| 0.142857
| false
| 0.071429
| 0.357143
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
|
0
| 4
|
cc9d1c260de01aa1226e05ec72a14cb0f8ec625e
| 989
|
py
|
Python
|
pyboltzmann/__init__.py
|
towink/boltzmann-planar-graph
|
fcfc3a04f10039f94ff74db58111007e86a31fee
|
[
"BSD-3-Clause"
] | null | null | null |
pyboltzmann/__init__.py
|
towink/boltzmann-planar-graph
|
fcfc3a04f10039f94ff74db58111007e86a31fee
|
[
"BSD-3-Clause"
] | null | null | null |
pyboltzmann/__init__.py
|
towink/boltzmann-planar-graph
|
fcfc3a04f10039f94ff74db58111007e86a31fee
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
# Copyright (C) 2018 by
# Marta Grobelna <marta.grobelna@rwth-aachen.de>
# Petre Petrov <petrepp4@gmail.com>
# Rudi Floren <rudi.floren@gmail.com>
# Tobias Winkler <tobias.winkler1@rwth-aachen.de>
# All rights reserved.
# BSD license.
#
# Authors: Marta Grobelna <marta.grobelna@rwth-aachen.de>
# Petre Petrov <petrepp4@gmail.com>
# Rudi Floren <rudi.floren@gmail.com>
# Tobias Winkler <tobias.winkler1@rwth-aachen.de>
# __all__ = ["decomposition_grammar",
# "evaluation_oracle",
# "utils"]
from pyboltzmann.class_builder import *
from pyboltzmann.decomposition_grammar import *
from pyboltzmann.evaluation_oracle import *
from pyboltzmann.generic_classes import *
from pyboltzmann.generic_samplers import *
from pyboltzmann.iterative_sampler import *
from pyboltzmann.utils import *
class PyBoltzmannError(Exception):
"""Base class for exceptions in the `pyboltzmann` framework."""
| 32.966667
| 67
| 0.709808
| 114
| 989
| 6.052632
| 0.447368
| 0.152174
| 0.182609
| 0.075362
| 0.391304
| 0.391304
| 0.391304
| 0.391304
| 0.391304
| 0.391304
| 0
| 0.011111
| 0.180991
| 989
| 29
| 68
| 34.103448
| 0.840741
| 0.62184
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.875
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
cc9dfd257dbd09516dd1de1ad2f0831b977d6f4e
| 5,994
|
py
|
Python
|
tests/test_declarative_definition.py
|
jhgg/epoxy
|
17e67d96f503758273e7bc2f2baa6ba925052c92
|
[
"MIT"
] | null | null | null |
tests/test_declarative_definition.py
|
jhgg/epoxy
|
17e67d96f503758273e7bc2f2baa6ba925052c92
|
[
"MIT"
] | 2
|
2021-12-10T00:22:57.000Z
|
2021-12-10T02:20:18.000Z
|
tests/test_declarative_definition.py
|
jhgg/epoxy
|
17e67d96f503758273e7bc2f2baa6ba925052c92
|
[
"MIT"
] | null | null | null |
from graphql.core.type.definition import GraphQLObjectType, GraphQLNonNull, GraphQLList, GraphQLField
from graphql.core.type.scalars import GraphQLString
from epoxy.registry import TypeRegistry
from pytest import raises
def check_dog(R, Dog):
assert isinstance(Dog.T, GraphQLObjectType)
assert R.type('Dog') is Dog.T
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['name']
assert fields['name'].type == GraphQLString
assert fields['name'].name == 'name'
def test_register_single_type():
R = TypeRegistry()
class Dog(R.ObjectType):
name = R.Field(R.String)
check_dog(R, Dog)
def test_register_single_type_using_string():
R = TypeRegistry()
class Dog(R.ObjectType):
name = R.Field('String')
check_dog(R, Dog)
def test_register_type_can_declare_builtin_scalar_types_directly():
R = TypeRegistry()
class Dog(R.ObjectType):
name = R.String
check_dog(R, Dog)
def test_register_type_can_use_builtin_graphql_types_in_field():
R = TypeRegistry()
class Dog(R.ObjectType):
name = R.Field(GraphQLString)
check_dog(R, Dog)
def test_can_use_mixins():
R = TypeRegistry()
class DogMixin():
name = R.String
class Dog(R.ObjectType, DogMixin):
pass
check_dog(R, Dog)
def test_register_type_can_declare_builtin_scalar_type_as_non_null():
R = TypeRegistry()
class Dog(R.ObjectType):
name = R.String.NonNull
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['name']
assert str(fields['name'].type) == 'String!'
def test_register_type_can_declare_other_registered_types_directly():
R = TypeRegistry()
class Dog(R.ObjectType):
friend = R.Dog
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['friend']
assert fields['friend'].type == Dog.T
assert fields['friend'].name == 'friend'
def test_register_type_can_declare_other_registered_types_directly_as_non_null():
R = TypeRegistry()
class Dog(R.ObjectType):
friend = R.Dog.NonNull
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['friend']
type = fields['friend'].type
assert isinstance(type, GraphQLNonNull)
assert type.of_type == Dog.T
assert fields['friend'].name == 'friend'
assert str(type) == 'Dog!'
def test_register_type_can_declare_other_registered_types_directly_as_list():
R = TypeRegistry()
class Dog(R.ObjectType):
friend = R.Dog.List
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['friend']
type = fields['friend'].type
assert isinstance(type, GraphQLList)
assert type.of_type == Dog.T
assert fields['friend'].name == 'friend'
assert str(type) == '[Dog]'
def test_register_type_can_declare_other_registered_types_directly_as_list_of_non_null():
R = TypeRegistry()
class Dog(R.ObjectType):
friend = R.Dog.NonNull.List
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['friend']
assert fields['friend'].name == 'friend'
type = fields['friend'].type
assert str(type) == '[Dog!]'
assert isinstance(type, GraphQLList)
type = type.of_type
assert isinstance(type, GraphQLNonNull)
assert type.of_type == Dog.T
def test_register_type_can_declare_other_registered_types_directly_as_non_null_list_of_non_null():
R = TypeRegistry()
class Dog(R.ObjectType):
friend = R.Dog.NonNull.List.NonNull
fields = Dog.T.get_fields()
assert list(fields.keys()) == ['friend']
assert fields['friend'].name == 'friend'
type = fields['friend'].type
assert str(type) == '[Dog!]!'
assert isinstance(type, GraphQLNonNull)
type = type.of_type
assert isinstance(type, GraphQLList)
type = type.of_type
assert isinstance(type, GraphQLNonNull)
assert type.of_type == Dog.T
def test_rejects_object_type_definition_with_duplicated_field_names():
R = TypeRegistry()
with raises(AssertionError) as excinfo:
class Dog(R.ObjectType):
friend = R.Dog.NonNull
friend_aliased = R.Field(R.Dog, name='friend')
assert str(excinfo.value) == 'Duplicate field definition for name "friend" in type "Dog.friend_aliased".'
def test_rejects_interface_type_definition_with_duplicated_field_names():
R = TypeRegistry()
with raises(AssertionError) as excinfo:
class Dog(R.Interface):
friend = R.Dog.NonNull
friend_aliased = R.Field(R.Dog, name='friend')
assert str(excinfo.value) == 'Duplicate field definition for name "friend" in type "Dog.friend_aliased".'
def test_orders_fields_in_order_declared():
R = TypeRegistry()
class Dog(R.ObjectType):
id = R.ID
name = R.Field('String')
dog = R.Dog
some_other_field = R.Field(R.Int)
some_other_dog = R.Field('Dog')
foo = R.String
bar = R.String
aaa = R.String
field_order = list(Dog.T.get_fields().keys())
assert field_order == ['id', 'name', 'dog', 'someOtherField', 'someOtherDog', 'foo', 'bar', 'aaa']
def test_cannot_resolve_unregistered_type():
R = TypeRegistry()
Dog = GraphQLObjectType(
name='Dog',
fields={
'a': GraphQLField(GraphQLString)
}
)
with raises(AssertionError) as excinfo:
R[Dog]()
assert str(excinfo.value) == 'Attempted to resolve a type "Dog" that is not registered with this Registry.'
R(Dog)
assert R[Dog]() is Dog
def test_cannot_resolve_type_of_same_name_that_is_mismatched():
R = TypeRegistry()
class Dog(R.ObjectType):
a = R.String
SomeOtherDog = GraphQLObjectType(
name='Dog',
fields={
'a': GraphQLField(GraphQLString)
}
)
with raises(AssertionError) as excinfo:
R[SomeOtherDog]()
assert str(excinfo.value) == 'Attempted to resolve a type "Dog" that does not match the already registered type.'
| 26.06087
| 117
| 0.665165
| 768
| 5,994
| 4.983073
| 0.125
| 0.02404
| 0.035276
| 0.069506
| 0.746538
| 0.734518
| 0.71283
| 0.709172
| 0.693755
| 0.606742
| 0
| 0
| 0.214047
| 5,994
| 229
| 118
| 26.174672
| 0.812354
| 0
| 0
| 0.589744
| 0
| 0
| 0.093594
| 0.007007
| 0
| 0
| 0
| 0
| 0.275641
| 1
| 0.108974
| false
| 0.00641
| 0.025641
| 0
| 0.391026
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ccaf63e48e2d79387938e1433a3b7163d5c58a3f
| 43
|
py
|
Python
|
qqdm/__init__.py
|
KimythAnly/qqdm
|
f24d903c922a8f88bb435a5432adfd3ac0ff8cb8
|
[
"MIT"
] | 26
|
2021-03-12T08:46:17.000Z
|
2022-03-30T08:46:41.000Z
|
qqdm/__init__.py
|
KimythAnly/qqdm
|
f24d903c922a8f88bb435a5432adfd3ac0ff8cb8
|
[
"MIT"
] | null | null | null |
qqdm/__init__.py
|
KimythAnly/qqdm
|
f24d903c922a8f88bb435a5432adfd3ac0ff8cb8
|
[
"MIT"
] | null | null | null |
from .core import *
__version__ = '0.0.7'
| 10.75
| 21
| 0.651163
| 7
| 43
| 3.428571
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085714
| 0.186047
| 43
| 3
| 22
| 14.333333
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ccc59c5e70b9858f1c0db2ce4c70c11a35a476ef
| 228
|
py
|
Python
|
students/K33421/Golub_Anna/LR_3/library/library_project/library_app/admin.py
|
aytakr/ITMO_ICT_WebDevelopment_2021-2022
|
57c0eef5e1f413c7f031ee001d59e5122f990f26
|
[
"MIT"
] | 7
|
2021-09-02T08:20:58.000Z
|
2022-01-12T11:48:07.000Z
|
students/K33421/Golub_Anna/LR_3/library/library_project/library_app/admin.py
|
aytakr/ITMO_ICT_WebDevelopment_2021-2022
|
57c0eef5e1f413c7f031ee001d59e5122f990f26
|
[
"MIT"
] | 76
|
2021-09-17T23:01:50.000Z
|
2022-03-18T16:42:03.000Z
|
students/K33421/Golub_Anna/LR_3/library/library_project/library_app/admin.py
|
aytakr/ITMO_ICT_WebDevelopment_2021-2022
|
57c0eef5e1f413c7f031ee001d59e5122f990f26
|
[
"MIT"
] | 60
|
2021-09-04T16:47:39.000Z
|
2022-03-21T04:41:27.000Z
|
from django.contrib import admin
from .models import *
admin.site.register(Book)
admin.site.register(Hall)
admin.site.register(Reader)
admin.site.register(BookInHall)
admin.site.register(ReaderBook)
admin.site.register(Report)
| 22.8
| 32
| 0.815789
| 32
| 228
| 5.8125
| 0.4375
| 0.290323
| 0.548387
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.065789
| 228
| 9
| 33
| 25.333333
| 0.873239
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
cccd6429bb692d28a9ba74494560b042182d9d30
| 65
|
py
|
Python
|
pychron/hardware/creator/__init__.py
|
ASUPychron/pychron
|
dfe551bdeb4ff8b8ba5cdea0edab336025e8cc76
|
[
"Apache-2.0"
] | 31
|
2016-03-07T02:38:17.000Z
|
2022-02-14T18:23:43.000Z
|
pychron/hardware/creator/__init__.py
|
ASUPychron/pychron
|
dfe551bdeb4ff8b8ba5cdea0edab336025e8cc76
|
[
"Apache-2.0"
] | 1,626
|
2015-01-07T04:52:35.000Z
|
2022-03-25T19:15:59.000Z
|
pychron/hardware/creator/__init__.py
|
UIllinoisHALPychron/pychron
|
f21b79f4592a9fb9dc9a4cb2e4e943a3885ededc
|
[
"Apache-2.0"
] | 26
|
2015-05-23T00:10:06.000Z
|
2022-03-07T16:51:57.000Z
|
"""
package used to easy creation of new device interfaces.
"""
| 13
| 55
| 0.707692
| 9
| 65
| 5.111111
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.184615
| 65
| 4
| 56
| 16.25
| 0.867925
| 0.846154
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
aef804b85761bbe7121b935ae88e30027ea8338a
| 5,092
|
py
|
Python
|
yft/properties.py
|
BaziForYou/Sollumz
|
ca53aafa0597e61cf1c5a82f8281ad47995e6b98
|
[
"MIT"
] | null | null | null |
yft/properties.py
|
BaziForYou/Sollumz
|
ca53aafa0597e61cf1c5a82f8281ad47995e6b98
|
[
"MIT"
] | null | null | null |
yft/properties.py
|
BaziForYou/Sollumz
|
ca53aafa0597e61cf1c5a82f8281ad47995e6b98
|
[
"MIT"
] | null | null | null |
import bpy
class FragmentProperties(bpy.types.PropertyGroup):
unk_b0: bpy.props.FloatProperty(name="UnknownB0")
unk_b8: bpy.props.FloatProperty(name="UnknownB8")
unk_bc: bpy.props.FloatProperty(name="UnknownBC")
unk_c0: bpy.props.FloatProperty(name="UnknownC0")
unk_c4: bpy.props.FloatProperty(name="UnknownC4")
unk_cc: bpy.props.FloatProperty(name="UnknownCC")
unk_d0: bpy.props.FloatProperty(name="UnknownD0")
unk_d4: bpy.props.FloatProperty(name="UnknownD4")
class LODProperties(bpy.types.PropertyGroup):
unk_14: bpy.props.FloatProperty(name="Unknown14")
unk_18: bpy.props.FloatProperty(name="Unknown18")
unk_1c: bpy.props.FloatProperty(name="Unknown1C")
unk_30: bpy.props.FloatVectorProperty(name="Unknown30")
unk_40: bpy.props.FloatVectorProperty(name="Unknown40")
unk_50: bpy.props.FloatVectorProperty(name="Unknown50")
unk_60: bpy.props.FloatVectorProperty(name="Unknown60")
unk_70: bpy.props.FloatVectorProperty(name="Unknown70")
unk_80: bpy.props.FloatVectorProperty(name="Unknown80")
unk_90: bpy.props.FloatVectorProperty(name="Unknown90")
unk_a0: bpy.props.FloatVectorProperty(name="UnknownA0")
unk_b0: bpy.props.FloatVectorProperty(name="UnknownB0")
class ArchetypeProperties(bpy.types.PropertyGroup):
name: bpy.props.StringProperty(name="Name")
mass: bpy.props.FloatProperty(name="Mass")
mass_inv: bpy.props.FloatProperty(name="MassInv")
unknown_48: bpy.props.FloatProperty(name="Unknown48")
unknown_4c: bpy.props.FloatProperty(name="Unknown4c")
unknown_50: bpy.props.FloatProperty(name="Unknown50")
unknown_54: bpy.props.FloatProperty(name="Unknown54")
inertia_tensor: bpy.props.FloatVectorProperty(name="InertiaTensor")
inertia_tensor_inv: bpy.props.FloatVectorProperty(name="InertiaTensorInv")
class GroupProperties(bpy.types.PropertyGroup):
name: bpy.props.StringProperty(name="Name")
index: bpy.props.IntProperty(name="Index")
parent_index: bpy.props.IntProperty(name="Parent Index")
unk_byte_4c: bpy.props.IntProperty(name="UnkByte4C")
unk_byte_4f: bpy.props.IntProperty(name="UnkByte4F")
unk_byte_50: bpy.props.IntProperty(name="UnkByte50")
unk_byte_51: bpy.props.IntProperty(name="UnkByte51")
unk_byte_52: bpy.props.IntProperty(name="UnkByte52")
unk_byte_53: bpy.props.IntProperty(name="UnkByte53")
unk_float_10: bpy.props.FloatProperty(name="UnkFloat10")
unk_float_14: bpy.props.FloatProperty(name="UnkFloat14")
unk_float_18: bpy.props.FloatProperty(name="UnkFloat18")
unk_float_1c: bpy.props.FloatProperty(name="UnkFloat1C")
unk_float_20: bpy.props.FloatProperty(name="UnkFloat20")
unk_float_24: bpy.props.FloatProperty(name="UnkFloat24")
unk_float_28: bpy.props.FloatProperty(name="UnkFloat28")
unk_float_2c: bpy.props.FloatProperty(name="UnkFloat2C")
unk_float_30: bpy.props.FloatProperty(name="UnkFloat30")
unk_float_34: bpy.props.FloatProperty(name="UnkFloat34")
unk_float_38: bpy.props.FloatProperty(name="UnkFloat38")
unk_float_3c: bpy.props.FloatProperty(name="UnkFloat3C")
unk_float_40: bpy.props.FloatProperty(name="UnkFloat40")
mass: bpy.props.FloatProperty(name="Mass")
unk_float_54: bpy.props.FloatProperty(name="UnkFloat54")
unk_float_58: bpy.props.FloatProperty(name="UnkFloat58")
unk_float_5c: bpy.props.FloatProperty(name="UnkFloat5C")
unk_float_60: bpy.props.FloatProperty(name="UnkFloat60")
unk_float_64: bpy.props.FloatProperty(name="UnkFloat64")
unk_float_68: bpy.props.FloatProperty(name="UnkFloat68")
unk_float_6c: bpy.props.FloatProperty(name="UnkFloat6C")
unk_float_70: bpy.props.FloatProperty(name="UnkFloat70")
unk_float_74: bpy.props.FloatProperty(name="UnkFloat74")
unk_float_78: bpy.props.FloatProperty(name="UnkFloat78")
unk_float_a8: bpy.props.FloatProperty(name="UnkFloatA8")
class ChildProperties(bpy.types.PropertyGroup):
group_index: bpy.props.IntProperty(name="GroupIndex")
bone_tag: bpy.props.IntProperty(name="BoneTag")
mass_1: bpy.props.FloatProperty(name="Mass1")
mass_2: bpy.props.FloatProperty(name="Mass2")
unk_vec: bpy.props.FloatVectorProperty(name="UnkVec")
inertia_tensor: bpy.props.FloatVectorProperty(name="InertiaTensor", size=4)
# group_index: bpy.props.IntProperty(name="EventSet") ???
def register():
bpy.types.Object.fragment_properties = bpy.props.PointerProperty(
type=FragmentProperties)
bpy.types.Object.lod_properties = bpy.props.PointerProperty(
type=LODProperties)
bpy.types.Object.archetype_properties = bpy.props.PointerProperty(
type=ArchetypeProperties)
bpy.types.Object.frag_group_properties = bpy.props.CollectionProperty(
type=GroupProperties)
bpy.types.Object.child_properties = bpy.props.PointerProperty(
type=ChildProperties)
def unregister():
bpy.types.Object.fragment_properties
bpy.types.Object.lod_properties
bpy.types.Object.archetype_properties
bpy.types.Object.frag_group_properties
bpy.types.Object.child_properties
| 47.148148
| 79
| 0.761194
| 627
| 5,092
| 6.009569
| 0.239234
| 0.159236
| 0.245223
| 0.291932
| 0.277866
| 0.164809
| 0.078556
| 0.029193
| 0.029193
| 0
| 0
| 0.039047
| 0.10978
| 5,092
| 107
| 80
| 47.588785
| 0.792191
| 0.010801
| 0
| 0.043478
| 0
| 0
| 0.124131
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.021739
| true
| 0
| 0.01087
| 0
| 0.836957
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
4e1020f6e546dda68ab3bec73a312d508cb84eab
| 427
|
py
|
Python
|
Python/Book Assignments/robot3.py
|
AungWinnHtut/CStutorial
|
4b57721b814e9c2d288af64a979704dd70f14ddb
|
[
"MIT"
] | null | null | null |
Python/Book Assignments/robot3.py
|
AungWinnHtut/CStutorial
|
4b57721b814e9c2d288af64a979704dd70f14ddb
|
[
"MIT"
] | null | null | null |
Python/Book Assignments/robot3.py
|
AungWinnHtut/CStutorial
|
4b57721b814e9c2d288af64a979704dd70f14ddb
|
[
"MIT"
] | 1
|
2022-03-15T12:20:26.000Z
|
2022-03-15T12:20:26.000Z
|
print("Look at the assinment statements")
#1. Set a variable called playerlives equal to 3
playerlives = 3
#Write assignment statements for 2 to 6 below
#2. set a variable called chocolate equal to 2
#3. set a variable called scorevalue equal to 4
#4. set a variable called totalscore equal to scorevalue * 3
#5. set a variable called robotname equal to "Botty"
#6 Write print statements to ouput all of the variables above
| 38.818182
| 61
| 0.772834
| 73
| 427
| 4.520548
| 0.452055
| 0.060606
| 0.181818
| 0.272727
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.037143
| 0.180328
| 427
| 11
| 61
| 38.818182
| 0.905714
| 0.82904
| 0
| 0
| 0
| 0
| 0.477612
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
4e105dc9c7c07f7dd13c021dffaee91bcc08522f
| 125
|
py
|
Python
|
inverter_palavra.py
|
gizellysteffanny/curso-python-basico
|
db2773cdc9008f86acaeaf9b7047239b011fbd95
|
[
"bzip2-1.0.6"
] | null | null | null |
inverter_palavra.py
|
gizellysteffanny/curso-python-basico
|
db2773cdc9008f86acaeaf9b7047239b011fbd95
|
[
"bzip2-1.0.6"
] | null | null | null |
inverter_palavra.py
|
gizellysteffanny/curso-python-basico
|
db2773cdc9008f86acaeaf9b7047239b011fbd95
|
[
"bzip2-1.0.6"
] | 1
|
2021-11-09T14:10:29.000Z
|
2021-11-09T14:10:29.000Z
|
palavra = input('Informe uma palavra: ')
print('palavra invertida: ', palavra[::-1])
for letra in palavra:
print(letra)
| 20.833333
| 43
| 0.68
| 16
| 125
| 5.3125
| 0.625
| 0.282353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009524
| 0.16
| 125
| 6
| 44
| 20.833333
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0.31746
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
4e1b245a1519016a863d053c2487d7ed12a4dbee
| 103
|
py
|
Python
|
enthought/appscripting/i_bind_event.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | 3
|
2016-12-09T06:05:18.000Z
|
2018-03-01T13:00:29.000Z
|
enthought/appscripting/i_bind_event.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | 1
|
2020-12-02T00:51:32.000Z
|
2020-12-02T08:48:55.000Z
|
enthought/appscripting/i_bind_event.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | null | null | null |
# proxy module
from __future__ import absolute_import
from apptools.appscripting.i_bind_event import *
| 25.75
| 48
| 0.854369
| 14
| 103
| 5.785714
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106796
| 103
| 3
| 49
| 34.333333
| 0.880435
| 0.116505
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
4e1c6cf0c4284d0dec9bad00c8a435bee560c197
| 61
|
py
|
Python
|
StarGAN/pretrained/__init__.py
|
shauray8/StarGAN-pytorch
|
0aef491634313e88607a347145fc6ab96e0175c6
|
[
"MIT"
] | null | null | null |
StarGAN/pretrained/__init__.py
|
shauray8/StarGAN-pytorch
|
0aef491634313e88607a347145fc6ab96e0175c6
|
[
"MIT"
] | null | null | null |
StarGAN/pretrained/__init__.py
|
shauray8/StarGAN-pytorch
|
0aef491634313e88607a347145fc6ab96e0175c6
|
[
"MIT"
] | null | null | null |
'''
pretrained model for StarGAN
details adding soon !
'''
| 10.166667
| 29
| 0.688525
| 7
| 61
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.196721
| 61
| 5
| 30
| 12.2
| 0.857143
| 0.852459
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4e203ebeac780aef186b1f739cf523b8129e713d
| 2,023
|
py
|
Python
|
msgs.py
|
BuBitt/PSMVC
|
69e4a82824364500fbf85d5ca5bfdb8685319fdc
|
[
"MIT"
] | 2
|
2021-07-19T01:52:01.000Z
|
2021-08-07T03:32:32.000Z
|
msgs.py
|
BuBitt/PSMVC
|
69e4a82824364500fbf85d5ca5bfdb8685319fdc
|
[
"MIT"
] | null | null | null |
msgs.py
|
BuBitt/PSMVC
|
69e4a82824364500fbf85d5ca5bfdb8685319fdc
|
[
"MIT"
] | null | null | null |
from colorama import *
import cut
def line():
return print("------------------------------------------------------------")
def no_cuts():
print("""------------------------------------------------------------
* Não há cortes
------------------------------------------------------------""")
def cut_process():
print(Fore.GREEN + """------------------------------------------------------------
==============================
INICIANDO PROCESSO DE CORTES
==============================
""")
def final():
print(Fore.YELLOW + """------------------------------------------------------------
==============================
!!!CONCLUÍDO COM SUCESSO!!!
==============================
------------------------------------------------------------""")
print('* Vá até a pasta ' + Fore.BLUE + f'/clips/{cut.s_name}' + Fore.YELLOW + ' para acessar os cortes.')
print('------------------------------------------------------------')
def dependences():
print("""
------------------------------------------------------------
================================
ANÁLISE DE DEPENDÊNCIAS PSMVC
================================
------------------------------------------------------------""")
def downloader():
print(Fore.BLUE + """------------------------------------------------------------
================================
INICIANDO PROCESSO DE DOWNLOAD
================================
""")
def select_cuts():
print(Fore.GREEN + """------------------------------------------------------------
==============================
SELEÇAO DE CORTES
==============================
| Comando | Ação |
+---------+---------+
| ENTER | valida |
+---------+---------+
""")
def menu_options():
pass
| 27.337838
| 110
| 0.208107
| 86
| 2,023
| 4.837209
| 0.593023
| 0.086538
| 0.067308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.231834
| 2,023
| 74
| 111
| 27.337838
| 0.267696
| 0
| 0
| 0.425532
| 0
| 0
| 0.779644
| 0.499012
| 0
| 0
| 0
| 0
| 0
| 1
| 0.170213
| true
| 0.021277
| 0.042553
| 0.021277
| 0.234043
| 0.191489
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4e3c37cd6175c6f2666dc5aa7f9a043887d03956
| 225
|
py
|
Python
|
haproxy/datadog_checks/haproxy/__init__.py
|
mchelen-gov/integrations-core
|
81281600b3cc7025a7a32148c59620c9592a564f
|
[
"BSD-3-Clause"
] | 663
|
2016-08-23T05:23:45.000Z
|
2022-03-29T00:37:23.000Z
|
haproxy/datadog_checks/haproxy/__init__.py
|
mchelen-gov/integrations-core
|
81281600b3cc7025a7a32148c59620c9592a564f
|
[
"BSD-3-Clause"
] | 6,642
|
2016-06-09T16:29:20.000Z
|
2022-03-31T22:24:09.000Z
|
haproxy/datadog_checks/haproxy/__init__.py
|
mchelen-gov/integrations-core
|
81281600b3cc7025a7a32148c59620c9592a564f
|
[
"BSD-3-Clause"
] | 1,222
|
2017-01-27T15:51:38.000Z
|
2022-03-31T18:17:51.000Z
|
# (C) Datadog, Inc. 2018-present
# All rights reserved
# Licensed under a 3-clause BSD style license (see LICENSE)
from .__about__ import __version__
from .check import HAProxyCheck
__all__ = ['__version__', 'HAProxyCheck']
| 28.125
| 59
| 0.764444
| 29
| 225
| 5.37931
| 0.793103
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025907
| 0.142222
| 225
| 7
| 60
| 32.142857
| 0.782383
| 0.48
| 0
| 0
| 0
| 0
| 0.20354
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9d80553266a5a5c25cf607d378dd6d447cc4df0f
| 170
|
py
|
Python
|
web.py
|
Nimphal/world-news
|
a424603c55245e0922d1b887f4cd7dd0711e6305
|
[
"MIT"
] | null | null | null |
web.py
|
Nimphal/world-news
|
a424603c55245e0922d1b887f4cd7dd0711e6305
|
[
"MIT"
] | null | null | null |
web.py
|
Nimphal/world-news
|
a424603c55245e0922d1b887f4cd7dd0711e6305
|
[
"MIT"
] | null | null | null |
from flask import Flask
from flask import render_template
app = Flask(__name__)
app.debug = True
@app.route('/')
def world():
return render_template('world.html')
| 15.454545
| 40
| 0.729412
| 24
| 170
| 4.916667
| 0.583333
| 0.152542
| 0.254237
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152941
| 170
| 10
| 41
| 17
| 0.819444
| 0
| 0
| 0
| 0
| 0
| 0.064706
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.285714
| 0.142857
| 0.571429
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
9d809606af97027a9c6f99bc0ece1a65095f3120
| 350
|
py
|
Python
|
dp_conceptual_search/ons/conceptual/client/fasttext_client.py
|
flaxandteal/dp-conceptual-search
|
16c6383a61ba5b7069337c2626a0dc243bfe9d35
|
[
"MIT"
] | 3
|
2018-05-10T16:49:27.000Z
|
2022-03-29T15:23:04.000Z
|
dp_conceptual_search/ons/conceptual/client/fasttext_client.py
|
flaxandteal/dp-conceptual-search
|
16c6383a61ba5b7069337c2626a0dc243bfe9d35
|
[
"MIT"
] | 2
|
2018-09-20T06:37:27.000Z
|
2018-11-12T12:05:08.000Z
|
dp_conceptual_search/ons/conceptual/client/fasttext_client.py
|
flaxandteal/dp-conceptual-search
|
16c6383a61ba5b7069337c2626a0dc243bfe9d35
|
[
"MIT"
] | 3
|
2018-06-25T10:48:43.000Z
|
2021-04-11T08:01:27.000Z
|
"""
Provides methods for initialising dp-fasttext HTTP client
"""
from dp_fasttext.client import Client
from dp_conceptual_search.config.config import FASTTEXT_CONFIG
class FastTextClientService(object):
@staticmethod
def get_fasttext_client() -> Client:
return Client(FASTTEXT_CONFIG.fasttext_host, FASTTEXT_CONFIG.fasttext_port)
| 26.923077
| 83
| 0.8
| 42
| 350
| 6.428571
| 0.52381
| 0.155556
| 0.088889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131429
| 350
| 12
| 84
| 29.166667
| 0.888158
| 0.162857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| true
| 0
| 0.333333
| 0.166667
| 0.833333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
9dad3b2e8501ccdc64e1276e86ce163927839a5f
| 452
|
py
|
Python
|
fake_gen/errors.py
|
psafont/fake-gen
|
a3d74fdb54c3d4171ce2ba6ab0ad15791cf5b7e5
|
[
"MIT"
] | 1
|
2020-04-14T09:34:58.000Z
|
2020-04-14T09:34:58.000Z
|
fake_gen/errors.py
|
psafont/fake-gen
|
a3d74fdb54c3d4171ce2ba6ab0ad15791cf5b7e5
|
[
"MIT"
] | 1
|
2018-12-04T10:02:57.000Z
|
2018-12-04T10:02:57.000Z
|
fake_gen/errors.py
|
psafont/fake-gen
|
a3d74fdb54c3d4171ce2ba6ab0ad15791cf5b7e5
|
[
"MIT"
] | null | null | null |
class TestDataError(Exception):
pass
class MissingElementAmountValue(TestDataError):
pass
class FactoryStartedAlready(TestDataError):
pass
class NoSuchDatatype(TestDataError):
pass
class InvalidFieldType(TestDataError):
pass
class MissingRequiredFields(TestDataError):
pass
class UnmetDependentFields(TestDataError):
pass
class NoFactoriesProvided(TestDataError):
pass
class InvalidDistribution(TestDataError):
pass
| 23.789474
| 47
| 0.800885
| 36
| 452
| 10.055556
| 0.333333
| 0.198895
| 0.425414
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.139381
| 452
| 18
| 48
| 25.111111
| 0.930591
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 0
| 0
| 1
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
9dc4da6f383954e9c8feee53fb22c485a7ce85fa
| 480
|
py
|
Python
|
datascience/numpy/stat_fun.py
|
janbodnar/Python-Course
|
51705ab5a2adef52bcdb99a800e94c0d67144a38
|
[
"BSD-2-Clause"
] | 13
|
2017-08-22T12:26:07.000Z
|
2021-07-29T16:13:50.000Z
|
datascience/numpy/stat_fun.py
|
janbodnar/Python-Course
|
51705ab5a2adef52bcdb99a800e94c0d67144a38
|
[
"BSD-2-Clause"
] | 1
|
2021-02-08T10:24:33.000Z
|
2021-02-08T10:24:33.000Z
|
datascience/numpy/stat_fun.py
|
janbodnar/Python-Course
|
51705ab5a2adef52bcdb99a800e94c0d67144a38
|
[
"BSD-2-Clause"
] | 17
|
2018-08-13T11:10:33.000Z
|
2021-07-29T16:14:02.000Z
|
#!/usr/bin/python
import numpy as np
a = np.array([[30,65,70], [80,95,20], [40,90,60]])
print(a)
print("median:")
print(np.median(a))
print(np.median(a, axis = 0))
print(np.median(a, axis = 1))
print("mean:")
print(np.mean(a))
print(np.mean(a, axis = 0))
print(np.mean(a, axis = 1))
print("average:")
print(np.mean(a))
print(np.mean(a, axis = 0))
print(np.mean(a, axis = 1))
print("Standard deviance")
print(np.std([1,2,3,4]))
print("Variance")
print(np.var([1,2,3,4]))
| 16
| 51
| 0.61875
| 94
| 480
| 3.159574
| 0.351064
| 0.259259
| 0.222222
| 0.242424
| 0.468013
| 0.343434
| 0.343434
| 0.343434
| 0.343434
| 0.343434
| 0
| 0.075472
| 0.116667
| 480
| 29
| 52
| 16.551724
| 0.625
| 0.033333
| 0
| 0.315789
| 0
| 0
| 0.097192
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.052632
| 0
| 0.052632
| 0.894737
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
9deb26305b485617d5bb5c043932cc26b089b274
| 109
|
py
|
Python
|
Python/URI1005.py
|
PatyB-git/URI
|
cbf6fab926d16575647a23789cc48c7b5ed566dd
|
[
"MIT"
] | null | null | null |
Python/URI1005.py
|
PatyB-git/URI
|
cbf6fab926d16575647a23789cc48c7b5ed566dd
|
[
"MIT"
] | null | null | null |
Python/URI1005.py
|
PatyB-git/URI
|
cbf6fab926d16575647a23789cc48c7b5ed566dd
|
[
"MIT"
] | null | null | null |
n1 = float(input())
n2 = float(input())
meida = ((n1*3.5)+(n2*7.5))/(3.5+7.5)
print(f"MEDIA = {meida:.5f}")
| 18.166667
| 37
| 0.541284
| 22
| 109
| 2.681818
| 0.545455
| 0.338983
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135417
| 0.119266
| 109
| 6
| 38
| 18.166667
| 0.479167
| 0
| 0
| 0
| 0
| 0
| 0.172727
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9dfdcdd1fa363d161d0f7271113c95c47d817f6e
| 13
|
py
|
Python
|
example_snippets/multimenus_snippets/NewSnippets/SymPy/Functions/Special functions/Error Functions and Fresnel Integrals/Inverse two-argument error function.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/NewSnippets/SymPy/Functions/Special functions/Error Functions and Fresnel Integrals/Inverse two-argument error function.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/NewSnippets/SymPy/Functions/Special functions/Error Functions and Fresnel Integrals/Inverse two-argument error function.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | 1
|
2021-02-04T04:51:48.000Z
|
2021-02-04T04:51:48.000Z
|
erf2inv(x, y)
| 13
| 13
| 0.692308
| 3
| 13
| 3
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 0.076923
| 13
| 1
| 13
| 13
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
d1b92ea0f2de68b61c5371bc67cf2863dcc89994
| 75
|
py
|
Python
|
homeworks/alexei_rakhmanko/lesson11/level01.py
|
tgrx/Z22
|
b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff
|
[
"Apache-2.0"
] | null | null | null |
homeworks/alexei_rakhmanko/lesson11/level01.py
|
tgrx/Z22
|
b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff
|
[
"Apache-2.0"
] | 8
|
2019-11-15T18:15:56.000Z
|
2020-02-03T18:05:05.000Z
|
homeworks/alexei_rakhmanko/lesson11/level01.py
|
tgrx/Z22
|
b2539682ff26c8b6d9f63a7670c8a9c6b614a8ff
|
[
"Apache-2.0"
] | null | null | null |
"""уровень 1"""
# pylint: disable=R0903
class User:
"""класс User"""
| 10.714286
| 23
| 0.586667
| 9
| 75
| 4.888889
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 0.2
| 75
| 6
| 24
| 12.5
| 0.65
| 0.573333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
d1e8f5f983bbc4b3e4845a87088c763db2d653b5
| 108
|
py
|
Python
|
src/try/itchatTest.py
|
caemasar/Sisyphus
|
9c1dad6355d978d07002e83119e638e1a25af879
|
[
"Apache-2.0"
] | null | null | null |
src/try/itchatTest.py
|
caemasar/Sisyphus
|
9c1dad6355d978d07002e83119e638e1a25af879
|
[
"Apache-2.0"
] | null | null | null |
src/try/itchatTest.py
|
caemasar/Sisyphus
|
9c1dad6355d978d07002e83119e638e1a25af879
|
[
"Apache-2.0"
] | null | null | null |
import itchat
# import pandas as pd
# 登录，执行本函数，itchat自动把二维码下载到本地并打开，手机微信扫描即可。
itchat.auto_login()
# 不安全停止尝试
| 18
| 41
| 0.796296
| 14
| 108
| 6.071429
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 108
| 6
| 42
| 18
| 0.885417
| 0.62037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
d1ea2dae3c1ae3ee5e2905c510ce93d3fc11bf71
| 91
|
py
|
Python
|
base/admin.py
|
tvm-dev/Django-Blog
|
da82fe4b6e5fb83cb4fe444265a8f7b67288096b
|
[
"MIT"
] | null | null | null |
base/admin.py
|
tvm-dev/Django-Blog
|
da82fe4b6e5fb83cb4fe444265a8f7b67288096b
|
[
"MIT"
] | null | null | null |
base/admin.py
|
tvm-dev/Django-Blog
|
da82fe4b6e5fb83cb4fe444265a8f7b67288096b
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from base.models import Post
admin.site.register(Post)
| 13
| 32
| 0.802198
| 14
| 91
| 5.214286
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131868
| 91
| 6
| 33
| 15.166667
| 0.924051
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
06056eabad444f017f3b2b97b756f67a6a493770
| 223
|
py
|
Python
|
src/m2_fake_robot_as_mqtt_receiver.py
|
hughesm1/25-TkinterAndMQTT
|
3905b1b6c6f91e39ee9199baff60d1abf11539bc
|
[
"MIT"
] | null | null | null |
src/m2_fake_robot_as_mqtt_receiver.py
|
hughesm1/25-TkinterAndMQTT
|
3905b1b6c6f91e39ee9199baff60d1abf11539bc
|
[
"MIT"
] | null | null | null |
src/m2_fake_robot_as_mqtt_receiver.py
|
hughesm1/25-TkinterAndMQTT
|
3905b1b6c6f91e39ee9199baff60d1abf11539bc
|
[
"MIT"
] | 14
|
2019-05-08T14:59:42.000Z
|
2019-05-09T12:04:53.000Z
|
# TODO: Copy the code in
# m1e_mqtt_receiver.py
# as your starting point, pasting its code here.
# Then modify the code so that it receives messages from your
# m2_tkinter_as_mqtt_sender.py
# module and PRINTS them.
| 31.857143
| 61
| 0.753363
| 38
| 223
| 4.263158
| 0.815789
| 0.08642
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011111
| 0.192825
| 223
| 7
| 62
| 31.857143
| 0.888889
| 0.941704
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0.142857
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0609501fa71b46912729a20aa9b16dd7ef6c0b67
| 208
|
py
|
Python
|
service.py
|
baishancloud/throttle_central
|
6458bc5595760ed6b55fd55915d0c42180545fa6
|
[
"MIT"
] | null | null | null |
service.py
|
baishancloud/throttle_central
|
6458bc5595760ed6b55fd55915d0c42180545fa6
|
[
"MIT"
] | null | null | null |
service.py
|
baishancloud/throttle_central
|
6458bc5595760ed6b55fd55915d0c42180545fa6
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python2
# coding: utf-8
from throttle_central import front_service
services = {
'front': {
'module': front_service,
'resource_dict': front_service.resource_dict,
},
}
| 17.333333
| 53
| 0.653846
| 24
| 208
| 5.416667
| 0.708333
| 0.276923
| 0.307692
| 0.369231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012346
| 0.221154
| 208
| 11
| 54
| 18.909091
| 0.790123
| 0.168269
| 0
| 0
| 0
| 0
| 0.140351
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 0.142857
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ae55942c6245fd74adbacb4bf24aaee9e813c9e9
| 66
|
py
|
Python
|
IA/Python/4/4.1/2.py
|
worthl3ss/random-small
|
ffb60781f57eb865acbd81aaa07056046bad32fe
|
[
"MIT"
] | 1
|
2022-02-23T12:47:00.000Z
|
2022-02-23T12:47:00.000Z
|
IA/Python/4/4.1/2.py
|
worthl3ss/random-small
|
ffb60781f57eb865acbd81aaa07056046bad32fe
|
[
"MIT"
] | null | null | null |
IA/Python/4/4.1/2.py
|
worthl3ss/random-small
|
ffb60781f57eb865acbd81aaa07056046bad32fe
|
[
"MIT"
] | null | null | null |
print(" ".join([ t for t in input().split(" ") if len(t)%2==1 ]))
| 33
| 65
| 0.515152
| 13
| 66
| 2.615385
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036364
| 0.166667
| 66
| 1
| 66
| 66
| 0.581818
| 0
| 0
| 0
| 0
| 0
| 0.030303
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
ae5653b83b479be31912dee88d08f8fa13267eeb
| 256
|
py
|
Python
|
pmap/models.py
|
Bjwebb/nhs-prescription-map
|
f73b077f7f43642c84ad9ee46a57ffed01f4fd5d
|
[
"MIT"
] | 1
|
2016-01-30T16:39:07.000Z
|
2016-01-30T16:39:07.000Z
|
pmap/models.py
|
Bjwebb/nhs-prescription-map
|
f73b077f7f43642c84ad9ee46a57ffed01f4fd5d
|
[
"MIT"
] | null | null | null |
pmap/models.py
|
Bjwebb/nhs-prescription-map
|
f73b077f7f43642c84ad9ee46a57ffed01f4fd5d
|
[
"MIT"
] | null | null | null |
from django.db import models
class ItemLocation(models.Model):
item_id = models.CharField(max_length=50)
item_name = models.CharField(max_length=256)
lat = models.FloatField()
lon = models.FloatField()
quantity = models.IntegerField()
| 28.444444
| 48
| 0.730469
| 32
| 256
| 5.71875
| 0.65625
| 0.163934
| 0.196721
| 0.262295
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.023364
| 0.164063
| 256
| 8
| 49
| 32
| 0.831776
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
ae747704dbd6c1724819b013e6d1bdc702378234
| 95
|
py
|
Python
|
musicbeats/apps.py
|
VICTOR4046/MusiX
|
4a13d849e9db9a20b3ef8f286a8d047c0de86170
|
[
"MIT"
] | null | null | null |
musicbeats/apps.py
|
VICTOR4046/MusiX
|
4a13d849e9db9a20b3ef8f286a8d047c0de86170
|
[
"MIT"
] | null | null | null |
musicbeats/apps.py
|
VICTOR4046/MusiX
|
4a13d849e9db9a20b3ef8f286a8d047c0de86170
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class MusicbeatsConfig(AppConfig):
name = 'musicbeats'
| 15.833333
| 34
| 0.768421
| 10
| 95
| 7.3
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 95
| 5
| 35
| 19
| 0.9125
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ae8b6b70c38963b0409355da6c94c17557d8ff5f
| 418
|
py
|
Python
|
sleekxmpp/features/feature_preapproval/__init__.py
|
E-Tahta/sleekxmpp
|
ed067c9412835c5fe44bf203936262bcec09ced4
|
[
"BSD-3-Clause"
] | 499
|
2015-01-04T21:45:16.000Z
|
2022-02-14T13:04:08.000Z
|
sleekxmpp/features/feature_preapproval/__init__.py
|
E-Tahta/sleekxmpp
|
ed067c9412835c5fe44bf203936262bcec09ced4
|
[
"BSD-3-Clause"
] | 159
|
2015-01-02T19:09:47.000Z
|
2020-02-12T08:29:54.000Z
|
sleekxmpp/features/feature_preapproval/__init__.py
|
E-Tahta/sleekxmpp
|
ed067c9412835c5fe44bf203936262bcec09ced4
|
[
"BSD-3-Clause"
] | 209
|
2015-01-07T16:23:16.000Z
|
2022-01-26T13:02:20.000Z
|
"""
SleekXMPP: The Sleek XMPP Library
Copyright (C) 2012 Nathanael C. Fritz
This file is part of SleekXMPP.
See the file LICENSE for copying permission.
"""
from sleekxmpp.plugins.base import register_plugin
from sleekxmpp.features.feature_preapproval.preapproval import FeaturePreApproval
from sleekxmpp.features.feature_preapproval.stanza import PreApproval
register_plugin(FeaturePreApproval)
| 26.125
| 81
| 0.801435
| 50
| 418
| 6.62
| 0.62
| 0.117825
| 0.126888
| 0.169184
| 0.23565
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011204
| 0.145933
| 418
| 15
| 82
| 27.866667
| 0.915966
| 0.358852
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
881ba4ebf25e53095300d4b0d846f487f2192b09
| 104
|
py
|
Python
|
accounts/admin.py
|
HarshSharma009/checkStock
|
3d4a5354dab46706c7ee45488def99f619d5ab8a
|
[
"Apache-2.0"
] | 11
|
2019-05-13T15:54:07.000Z
|
2022-03-20T12:12:59.000Z
|
accounts/admin.py
|
HarshSharma009/checkStock
|
3d4a5354dab46706c7ee45488def99f619d5ab8a
|
[
"Apache-2.0"
] | 5
|
2020-03-09T14:58:58.000Z
|
2022-02-10T10:48:15.000Z
|
accounts/admin.py
|
HarshSharma009/checkStock
|
3d4a5354dab46706c7ee45488def99f619d5ab8a
|
[
"Apache-2.0"
] | 3
|
2020-05-17T20:53:14.000Z
|
2021-03-28T20:32:31.000Z
|
from django.contrib import admin
from .models import (
Portfolio
)
admin.site.register(Portfolio)
| 13
| 32
| 0.759615
| 13
| 104
| 6.076923
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163462
| 104
| 7
| 33
| 14.857143
| 0.908046
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
8830be8ef0284e442023aa1fcd7a2db8a2bc141c
| 55
|
py
|
Python
|
__init__.py
|
MatthewNice/live_radar
|
9d3682988b67709dedd2db9ec416f6af713917f1
|
[
"MIT"
] | null | null | null |
__init__.py
|
MatthewNice/live_radar
|
9d3682988b67709dedd2db9ec416f6af713917f1
|
[
"MIT"
] | null | null | null |
__init__.py
|
MatthewNice/live_radar
|
9d3682988b67709dedd2db9ec416f6af713917f1
|
[
"MIT"
] | null | null | null |
from .liveRadar import *
from .kalmanTracking import *
| 18.333333
| 29
| 0.781818
| 6
| 55
| 7.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145455
| 55
| 2
| 30
| 27.5
| 0.914894
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
883b95d1afce89c0cc35827dbaeec2a90955bf87
| 55
|
py
|
Python
|
xonsh/aliases/python.py
|
yjpark/dotfiles
|
ae9ad72eb2e2a4d3da4c600d24782720229d1a4b
|
[
"MIT"
] | 7
|
2015-12-18T04:33:01.000Z
|
2019-09-17T06:09:51.000Z
|
xonsh/aliases/python.py
|
yjpark/dotfiles
|
ae9ad72eb2e2a4d3da4c600d24782720229d1a4b
|
[
"MIT"
] | 1
|
2016-05-12T15:32:47.000Z
|
2016-05-12T15:32:47.000Z
|
xonsh/aliases/python.py
|
yjpark/dotfiles
|
ae9ad72eb2e2a4d3da4c600d24782720229d1a4b
|
[
"MIT"
] | 4
|
2016-11-29T04:06:19.000Z
|
2019-12-26T14:32:46.000Z
|
aliases['pip-upload'] = 'python setup.py sdist upload'
| 27.5
| 54
| 0.727273
| 8
| 55
| 5
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109091
| 55
| 1
| 55
| 55
| 0.816327
| 0
| 0
| 0
| 0
| 0
| 0.690909
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
8848a7632d4a369316bea4ac80f5972fdce9699c
| 30
|
py
|
Python
|
v0/aia_eis_v0/IS/__init__.py
|
DreamBoatOve/aia_eis
|
458b4d29846669b10db4da1b3e86c0b394614ceb
|
[
"MIT"
] | 1
|
2022-03-02T12:57:19.000Z
|
2022-03-02T12:57:19.000Z
|
v0/aia_eis_v0/IS/__init__.py
|
DreamBoatOve/aia_eis
|
458b4d29846669b10db4da1b3e86c0b394614ceb
|
[
"MIT"
] | null | null | null |
v0/aia_eis_v0/IS/__init__.py
|
DreamBoatOve/aia_eis
|
458b4d29846669b10db4da1b3e86c0b394614ceb
|
[
"MIT"
] | null | null | null |
"""
IS: Impedance Spectrum
"""
| 10
| 22
| 0.633333
| 3
| 30
| 6.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 30
| 3
| 23
| 10
| 0.730769
| 0.733333
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
889408ee8e71b8d9b182b953b68bac7b7ce94f74
| 125
|
py
|
Python
|
common_logger/utils2.py
|
NathanKr/python-logger-playground
|
8a10f9199bfd7cf42902e9e66984299013f52e7e
|
[
"MIT"
] | null | null | null |
common_logger/utils2.py
|
NathanKr/python-logger-playground
|
8a10f9199bfd7cf42902e9e66984299013f52e7e
|
[
"MIT"
] | null | null | null |
common_logger/utils2.py
|
NathanKr/python-logger-playground
|
8a10f9199bfd7cf42902e9e66984299013f52e7e
|
[
"MIT"
] | null | null | null |
import logging
def sub(num1 : float,num2 : float)->float:
logging.debug(f'args : {num1} , {num2}')
return num1-num2
| 20.833333
| 44
| 0.648
| 18
| 125
| 4.5
| 0.611111
| 0.197531
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.059406
| 0.192
| 125
| 6
| 45
| 20.833333
| 0.742574
| 0
| 0
| 0
| 0
| 0
| 0.174603
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
88ab1b28441deda55bb0488ecd5432228b7e5c87
| 492
|
py
|
Python
|
pupy/_typing.py
|
jessekrubin/pup
|
2cab5da7b1b39453c44be556b691db83442b0565
|
[
"BSD-2-Clause"
] | 2
|
2019-03-07T09:26:36.000Z
|
2019-07-31T17:24:23.000Z
|
pupy/_typing.py
|
jessekrubin/pup
|
2cab5da7b1b39453c44be556b691db83442b0565
|
[
"BSD-2-Clause"
] | 2
|
2019-10-26T02:29:54.000Z
|
2021-06-25T15:28:12.000Z
|
pupy/_typing.py
|
jessekrubin/pup
|
2cab5da7b1b39453c44be556b691db83442b0565
|
[
"BSD-2-Clause"
] | 1
|
2019-07-31T17:24:32.000Z
|
2019-07-31T17:24:32.000Z
|
# -*- coding: utf-8 -*-
# Pretty ~ Useful ~ Python
from typing import Any
from typing import Callable
from typing import Dict
from typing import Iterable
from typing import List
from typing import TypeVar
from typing import Union
from typing import cast
Flint = Union[int, float] # float or int
Paths = Iterable[str] # iterable of path-strings
JASM = Union[None, bool, int, float, str, List[Any], Dict[str, Any]] # JSON obj
FuncType = Callable[..., Any]
F = TypeVar("F", bound=FuncType)
| 27.333333
| 80
| 0.72561
| 74
| 492
| 4.824324
| 0.459459
| 0.22409
| 0.358543
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002451
| 0.170732
| 492
| 17
| 81
| 28.941176
| 0.872549
| 0.189024
| 0
| 0
| 0
| 0
| 0.002545
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.615385
| 0
| 0.615385
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ee4669b21c32a7ea5f95255e4f9dbc9a4cae3910
| 2,240
|
py
|
Python
|
tests/cluster/connection_pool_unix_socket_url_parsing_test.py
|
ProjectHentai/yaaredis
|
be6fcaf4c66f98272bfdeae33d34bb4e6fc13f1f
|
[
"MIT"
] | 13
|
2021-06-08T23:44:00.000Z
|
2022-03-23T22:48:17.000Z
|
tests/cluster/connection_pool_unix_socket_url_parsing_test.py
|
talkiq/yaaredis
|
01e3fdd5ccf80843c56f5932952eb6ef0a697b33
|
[
"MIT"
] | 10
|
2021-06-09T00:03:20.000Z
|
2022-03-22T10:37:08.000Z
|
tests/cluster/connection_pool_unix_socket_url_parsing_test.py
|
ProjectHentai/yaaredis
|
be6fcaf4c66f98272bfdeae33d34bb4e6fc13f1f
|
[
"MIT"
] | 1
|
2021-11-26T16:46:31.000Z
|
2021-11-26T16:46:31.000Z
|
from yaaredis.connection import UnixDomainSocketConnection
from yaaredis.pool import ConnectionPool
def test_defaults():
pool = ConnectionPool.from_url('unix:///socket')
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 0,
'username': None,
'password': None,
}
def test_username():
pool = ConnectionPool.from_url('unix://myusername:@/socket')
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 0,
'username': 'myusername',
'password': '',
}
def test_password():
pool = ConnectionPool.from_url('unix://:mypassword@/socket')
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 0,
'username': '',
'password': 'mypassword',
}
def test_username_and_password():
pool = ConnectionPool.from_url('unix://myusername:mypassword@/socket')
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 0,
'username': 'myusername',
'password': 'mypassword',
}
def test_db_as_argument():
pool = ConnectionPool.from_url('unix:///socket', db=1)
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 1,
'username': None,
'password': None,
}
def test_db_in_querystring():
pool = ConnectionPool.from_url('unix:///socket?db=2', db=1)
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 2,
'username': None,
'password': None,
}
def test_extra_querystring_options():
pool = ConnectionPool.from_url('unix:///socket?a=1&b=2')
assert pool.connection_class == UnixDomainSocketConnection
assert pool.connection_kwargs == {
'path': '/socket',
'db': 0,
'username': None,
'password': None,
'a': '1',
'b': '2',
}
| 27.317073
| 74
| 0.617857
| 216
| 2,240
| 6.240741
| 0.162037
| 0.103858
| 0.207715
| 0.129822
| 0.82641
| 0.82641
| 0.636499
| 0.583086
| 0.583086
| 0.583086
| 0
| 0.008206
| 0.238393
| 2,240
| 81
| 75
| 27.654321
| 0.781946
| 0
| 0
| 0.567164
| 0
| 0
| 0.180357
| 0.049107
| 0
| 0
| 0
| 0
| 0.208955
| 1
| 0.104478
| false
| 0.164179
| 0.029851
| 0
| 0.134328
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
ee684d9bad4c4c7edb379a6c55ba7d48a302ee0a
| 93
|
py
|
Python
|
QuestoesBeecrowd-Iniciante/1078.py
|
AtosNeves/Beecrowd
|
f1192218eac3f6300290fe8234bbc720e9fb859e
|
[
"MIT"
] | null | null | null |
QuestoesBeecrowd-Iniciante/1078.py
|
AtosNeves/Beecrowd
|
f1192218eac3f6300290fe8234bbc720e9fb859e
|
[
"MIT"
] | null | null | null |
QuestoesBeecrowd-Iniciante/1078.py
|
AtosNeves/Beecrowd
|
f1192218eac3f6300290fe8234bbc720e9fb859e
|
[
"MIT"
] | null | null | null |
a = int(input())
v = 0
for x in range(1,10+1):
print(v+1,"x",a,"=",a*(v+1))
v = v+ 1
| 15.5
| 32
| 0.44086
| 23
| 93
| 1.782609
| 0.521739
| 0.146341
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 0.247312
| 93
| 5
| 33
| 18.6
| 0.471429
| 0
| 0
| 0
| 0
| 0
| 0.021505
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.2
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
c9e1d2c9063c6e28fe669513fda3d9049dae4c45
| 97
|
py
|
Python
|
logger_client/__main__.py
|
skyferthesly/logger_client
|
d780be3e5159d028e3157ad420725a9fb2fe36f1
|
[
"MIT"
] | null | null | null |
logger_client/__main__.py
|
skyferthesly/logger_client
|
d780be3e5159d028e3157ad420725a9fb2fe36f1
|
[
"MIT"
] | null | null | null |
logger_client/__main__.py
|
skyferthesly/logger_client
|
d780be3e5159d028e3157ad420725a9fb2fe36f1
|
[
"MIT"
] | null | null | null |
from logger_client.client import LoggerClient
if __name__ == '__main__':
LoggerClient.run()
| 19.4
| 45
| 0.762887
| 11
| 97
| 5.909091
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14433
| 97
| 4
| 46
| 24.25
| 0.783133
| 0
| 0
| 0
| 0
| 0
| 0.082474
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
a00390641e9020cd3e47ff6ce847e5d210a5e01c
| 101
|
py
|
Python
|
quart_events/errors.py
|
smithk86/quart-events
|
0f4593225b8da99ff80c1ebeeb0ff67e7fdd2fb1
|
[
"MIT"
] | 1
|
2021-07-17T03:37:56.000Z
|
2021-07-17T03:37:56.000Z
|
quart_events/errors.py
|
smithk86/quart-events
|
0f4593225b8da99ff80c1ebeeb0ff67e7fdd2fb1
|
[
"MIT"
] | null | null | null |
quart_events/errors.py
|
smithk86/quart-events
|
0f4593225b8da99ff80c1ebeeb0ff67e7fdd2fb1
|
[
"MIT"
] | null | null | null |
class EventBrokerError(Exception):
pass
class EventBrokerAuthError(EventBrokerError):
pass
| 14.428571
| 45
| 0.782178
| 8
| 101
| 9.875
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.158416
| 101
| 6
| 46
| 16.833333
| 0.929412
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
a01e3dada271c483d958b75657ab85c4ca92efd4
| 1,492
|
py
|
Python
|
Hard Challenges/Challenge 0013 Hard/solutions/solution.py
|
FreddieV4/DailyProgrammerChallenges
|
f231fc4728b55ec9ac72d66e5d7ecc6b9377b9cc
|
[
"MIT"
] | 331
|
2016-03-04T02:13:43.000Z
|
2017-10-18T09:07:53.000Z
|
Hard Challenges/Challenge 0013 Hard/solutions/solution.py
|
freddiev4/dailyprogrammerchallenges
|
f231fc4728b55ec9ac72d66e5d7ecc6b9377b9cc
|
[
"MIT"
] | 64
|
2016-03-15T23:46:42.000Z
|
2017-10-19T18:25:30.000Z
|
Hard Challenges/Challenge 0013 Hard/solutions/solution.py
|
FreddieV4/DailyProgrammerChallenges
|
f231fc4728b55ec9ac72d66e5d7ecc6b9377b9cc
|
[
"MIT"
] | 116
|
2016-03-11T19:59:12.000Z
|
2017-10-19T18:23:37.000Z
|
import random
class Player(object):
def __init__(self,player):
self.name = player
self.score = 0
self.choice = []
class Game(object):
player_one,player_two = Player('player_one'),Player('player_two')
def gameplay(self):
choices = ['rock','paper','scissors']
self.player_one.choice,self.player_two.choice = random.choice(choices),random.choice(choices)
if self.player_one.choice == self.player_two.choice:
print 'Tie!'
elif self.player_one.choice == 'rock' and self.player_two.choice == 'paper':
print '{0} is the winner with {1}!'.format(self.player_one.name,self.player_one.choice)
self.player_one.score += 1
elif self.player_one.choice == 'paper' and self.player_two.choice == 'rock':
print '{0} is the winner with {1}!'.format(self.player_two.name,self.player_two.choice)
self.player_two.score += 1
elif self.player_one.choice == 'scissors' and self.player_two.choice == 'rock':
self.player_two.score += 1
elif self.player_one.choice == 'scissors' and self.player_two.choice == 'paper':
self.player_one.score += 1
elif self.player_one.choice == 'paper' and self.player_two.choice == 'scissors':
self.player_two.score += 1
elif self.player_one.choice == 'rock' and self.player_two.choice == 'scissors':
self.player_one.score += 1
print '{0}\'s score is {1}, and {2}\'s score is {3}'.format(self.player_one.name,self.player_one.score,self.player_two.name,self.player_two.score)
g = Game()
for i in range(0,10000):
g.gameplay()
| 38.25641
| 148
| 0.709786
| 235
| 1,492
| 4.344681
| 0.170213
| 0.303624
| 0.190989
| 0.167483
| 0.701273
| 0.692458
| 0.668952
| 0.61998
| 0.46523
| 0.46523
| 0
| 0.016204
| 0.131367
| 1,492
| 38
| 149
| 39.263158
| 0.771605
| 0
| 0
| 0.193548
| 0
| 0
| 0.121314
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.032258
| null | null | 0.129032
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4e754412d2c4ddcc2ed6c0b1e4cc9ab46e1fe57c
| 385
|
py
|
Python
|
radiomicsfeatureextractionpipeline/backend/src/logic/entities/mri_series.py
|
Maastro-CDS-Imaging-Group/SQLite4Radiomics
|
e3a7afc181eec0fe04c18da00edc3772064e6758
|
[
"Apache-2.0"
] | null | null | null |
radiomicsfeatureextractionpipeline/backend/src/logic/entities/mri_series.py
|
Maastro-CDS-Imaging-Group/SQLite4Radiomics
|
e3a7afc181eec0fe04c18da00edc3772064e6758
|
[
"Apache-2.0"
] | 6
|
2021-06-09T19:39:27.000Z
|
2021-09-30T16:41:40.000Z
|
radiomicsfeatureextractionpipeline/backend/src/logic/entities/mri_series.py
|
Maastro-CDS-Imaging-Group/SQLite4Radiomics
|
e3a7afc181eec0fe04c18da00edc3772064e6758
|
[
"Apache-2.0"
] | null | null | null |
"""
This module is used to represent a MRISeries object from the DICOMSeries table in the database.
Inherits SeriesWithImageSlices module.
"""
from logic.entities.series_with_image_slices import SeriesWithImageSlices
class MriSeries(SeriesWithImageSlices):
"""
This class stores all information about a MRI-series from the DICOMSeries table in the database.
"""
pass
| 29.615385
| 100
| 0.781818
| 48
| 385
| 6.208333
| 0.645833
| 0.04698
| 0.120805
| 0.154362
| 0.241611
| 0.241611
| 0.241611
| 0
| 0
| 0
| 0
| 0
| 0.163636
| 385
| 12
| 101
| 32.083333
| 0.925466
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
4e8883eed1f8809c6ac88def89be8e55ea442423
| 57
|
py
|
Python
|
examples/tg2-raptorized/tg2raptorized/__init__.py
|
ralphbean/raptorizemw
|
aee001e1f17ee4b9ad27aac6dde21d8ff545144e
|
[
"MIT"
] | 10
|
2015-01-03T06:00:00.000Z
|
2019-02-03T20:34:21.000Z
|
examples/tg2-raptorized/tg2raptorized/__init__.py
|
ralphbean/raptorizemw
|
aee001e1f17ee4b9ad27aac6dde21d8ff545144e
|
[
"MIT"
] | null | null | null |
examples/tg2-raptorized/tg2raptorized/__init__.py
|
ralphbean/raptorizemw
|
aee001e1f17ee4b9ad27aac6dde21d8ff545144e
|
[
"MIT"
] | 2
|
2017-01-18T06:29:53.000Z
|
2020-05-27T13:13:10.000Z
|
# -*- coding: utf-8 -*-
"""The tg2-raptorized package"""
| 19
| 32
| 0.578947
| 7
| 57
| 4.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040816
| 0.140351
| 57
| 2
| 33
| 28.5
| 0.632653
| 0.859649
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4e93025f5208a79f17bb7c94573f24bfcb15e993
| 239
|
py
|
Python
|
ch14/apic/rails/forms.py
|
kxen42/Learn-Python-Programming-Third-Edition
|
851ddc5e6094fadd44f31a9ad1d3876456b04372
|
[
"MIT"
] | 19
|
2021-11-05T22:54:09.000Z
|
2022-03-29T15:03:47.000Z
|
ch14/apic/rails/forms.py
|
kxen42/Learn-Python-Programming-Third-Edition
|
851ddc5e6094fadd44f31a9ad1d3876456b04372
|
[
"MIT"
] | null | null | null |
ch14/apic/rails/forms.py
|
kxen42/Learn-Python-Programming-Third-Edition
|
851ddc5e6094fadd44f31a9ad1d3876456b04372
|
[
"MIT"
] | 26
|
2021-11-12T17:04:50.000Z
|
2022-03-29T01:10:35.000Z
|
# apic/rails/forms.py
from django import forms
class AuthenticateForm(forms.Form):
email = forms.EmailField(max_length=256, label="Username")
password = forms.CharField(
label="Password", widget=forms.PasswordInput
)
| 23.9
| 62
| 0.719665
| 28
| 239
| 6.107143
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015075
| 0.167364
| 239
| 9
| 63
| 26.555556
| 0.844221
| 0.079498
| 0
| 0
| 0
| 0
| 0.073395
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.333333
| 0.166667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
4e9cb6a68b85b33aa1d892b3d29cf433de798ea6
| 170
|
py
|
Python
|
exercicio3.py
|
YasminMichels/Exercicios_LP_1b
|
ecd3e534ead6983be98225ce9c75362ce24fdfb9
|
[
"MIT"
] | null | null | null |
exercicio3.py
|
YasminMichels/Exercicios_LP_1b
|
ecd3e534ead6983be98225ce9c75362ce24fdfb9
|
[
"MIT"
] | null | null | null |
exercicio3.py
|
YasminMichels/Exercicios_LP_1b
|
ecd3e534ead6983be98225ce9c75362ce24fdfb9
|
[
"MIT"
] | null | null | null |
dia = input("Digite o dia do seu nascimento: ")
mes = input("Digite o mês do seu nascimento: ")
ano = input("Digite o ano do seu nascimento: ")
print(dia,"/",mes,"/",ano)
| 42.5
| 47
| 0.664706
| 28
| 170
| 4.035714
| 0.392857
| 0.292035
| 0.318584
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.158824
| 170
| 4
| 48
| 42.5
| 0.79021
| 0
| 0
| 0
| 0
| 0
| 0.573099
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
14cdc6a4d87a4ec41ba25de3bda37442b2d64b7f
| 285
|
py
|
Python
|
menpo/visualize/__init__.py
|
ikassi/menpo
|
ca702fc814a1ad50b27c44c6544ba364d3aa7e31
|
[
"BSD-3-Clause"
] | null | null | null |
menpo/visualize/__init__.py
|
ikassi/menpo
|
ca702fc814a1ad50b27c44c6544ba364d3aa7e31
|
[
"BSD-3-Clause"
] | null | null | null |
menpo/visualize/__init__.py
|
ikassi/menpo
|
ca702fc814a1ad50b27c44c6544ba364d3aa7e31
|
[
"BSD-3-Clause"
] | 1
|
2021-04-14T12:09:00.000Z
|
2021-04-14T12:09:00.000Z
|
from menpo.visualize.base import PointCloudViewer2d, PointCloudViewer3d, \
TriMeshViewer3d, TexturedTriMeshViewer3d, LandmarkViewer3d, \
LandmarkViewer2d, LandmarkViewer, ImageViewer2d, TriMeshViewer2d, \
PointCloudViewer, TriMeshViewer, VectorViewer3d, AlignmentViewer2d
| 47.5
| 74
| 0.82807
| 18
| 285
| 13.111111
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039526
| 0.112281
| 285
| 5
| 75
| 57
| 0.893281
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 0
| 0.25
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0919819f62bd20bb6aad885d044d6f980af78b11
| 29,025
|
py
|
Python
|
honeycomb_io/poses.py
|
WildflowerSchools/wf-honeycomb-io
|
74bf9e4e1ecd3ac1c47cfc69a8e9c933b4d93f53
|
[
"MIT"
] | null | null | null |
honeycomb_io/poses.py
|
WildflowerSchools/wf-honeycomb-io
|
74bf9e4e1ecd3ac1c47cfc69a8e9c933b4d93f53
|
[
"MIT"
] | null | null | null |
honeycomb_io/poses.py
|
WildflowerSchools/wf-honeycomb-io
|
74bf9e4e1ecd3ac1c47cfc69a8e9c933b4d93f53
|
[
"MIT"
] | null | null | null |
import honeycomb_io.core
import honeycomb_io.utils
import honeycomb_io.cameras
import minimal_honeycomb
import pandas as pd
import numpy as np
import datetime
import logging
logger = logging.getLogger(__name__)
# The following functions are used by process_pose_data.geom_render
# (wf-process-pose_data) but not implemented here:
# fetch_2d_pose_data_by_inference_execution()
# fetch_2d_pose_data_by_time_span()
# extract_pose_model_id()
# fetch_pose_model_info()
# Not currently used
def fetch_2d_pose_data(
start=None,
end=None,
environment_id=None,
environment_name=None,
camera_ids=None,
camera_device_types=None,
camera_part_numbers=None,
camera_names=None,
camera_serial_numbers=None,
pose_model_id=None,
pose_model_name=None,
pose_model_variant_name=None,
inference_ids=None,
inference_names=None,
inference_models=None,
inference_versions=None,
return_track_label=False,
return_person_id=False,
return_inference_id=False,
return_pose_model_id=True,
return_pose_quality=False,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
camera_ids_from_environment = honeycomb_io.cameras.fetch_camera_ids_from_environment(
start=start,
end=end,
environment_id=environment_id,
environment_name=environment_name,
camera_device_types=camera_device_types,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
camera_ids_from_camera_properties = honeycomb_io.cameras.fetch_camera_ids_from_camera_properties(
camera_ids=camera_ids,
camera_device_types=camera_device_types,
camera_part_numbers=camera_part_numbers,
camera_names=camera_names,
camera_serial_numbers=camera_serial_numbers,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
pose_model_id = fetch_pose_model_id(
pose_model_id=pose_model_id,
pose_model_name=pose_model_name,
pose_model_variant_name=pose_model_variant_name,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
inference_ids = honeycomb_io.inference_executions.fetch_inference_ids(
inference_ids=inference_ids,
inference_names=inference_names,
inference_models=inference_models,
inference_versions=inference_versions,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Building query list for 2D pose search')
query_list = list()
if start is not None:
query_list.append({
'field': 'timestamp',
'operator': 'GTE',
'value': honeycomb_io.utils.to_honeycomb_datetime(start)
})
if end is not None:
query_list.append({
'field': 'timestamp',
'operator': 'LTE',
'value': honeycomb_io.utils.to_honeycomb_datetime(end)
})
if camera_ids_from_environment is not None:
query_list.append({
'field': 'camera',
'operator': 'IN',
'values': camera_ids_from_environment
})
if camera_ids_from_camera_properties is not None:
query_list.append({
'field': 'camera',
'operator': 'IN',
'values': camera_ids_from_camera_properties
})
if pose_model_id is not None:
query_list.append({
'field': 'pose_model',
'operator': 'EQ',
'value': pose_model_id
})
if inference_ids is not None:
query_list.append({
'field': 'source',
'operator': 'IN',
'values': inference_ids
})
return_data= [
'pose_id',
'timestamp',
{'camera': [
'device_id'
]},
'track_label',
{'pose_model': [
'pose_model_id'
]},
{'keypoints': [
'coordinates',
'quality'
]},
'quality',
{'person': [
'person_id'
]},
{'source': [
{'... on InferenceExecution': [
'inference_id'
]}
]}
]
result = search_2d_poses(
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
data = list()
logger.info('Parsing {} returned poses'.format(len(result)))
for datum in result:
data.append({
'pose_2d_id': datum.get('pose_id'),
'timestamp': datum.get('timestamp'),
'camera_id': (datum.get('camera') if datum.get('camera') is not None else {}).get('device_id'),
'track_label_2d': datum.get('track_label'),
'person_id': (datum.get('person') if datum.get('person') is not None else {}).get('person_id'),
'inference_id': (datum.get('source') if datum.get('source') is not None else {}).get('inference_id'),
'pose_model_id': (datum.get('pose_model') if datum.get('pose_model') is not None else {}).get('pose_model_id'),
'keypoint_coordinates_2d': np.asarray([keypoint.get('coordinates') for keypoint in datum.get('keypoints')], dtype=np.float),
'keypoint_quality_2d': np.asarray([keypoint.get('quality') for keypoint in datum.get('keypoints')], dtype=np.float),
'pose_quality_2d': datum.get('quality')
})
poses_2d_df = pd.DataFrame(data)
poses_2d_df['keypoint_coordinates_2d'] = poses_2d_df['keypoint_coordinates_2d'].apply(lambda x: np.where(x == 0.0, np.nan, x))
poses_2d_df['timestamp'] = pd.to_datetime(poses_2d_df['timestamp'])
if poses_2d_df['pose_model_id'].nunique() > 1:
raise ValueError('Returned poses are associated with multiple pose models')
if (poses_2d_df.groupby(['timestamp', 'camera_id'])['inference_id'].nunique() > 1).any():
raise ValueError('Returned poses have multiple inference IDs for some camera IDs at some timestamps')
poses_2d_df.set_index('pose_2d_id', inplace=True)
return_columns = [
'timestamp',
'camera_id'
]
if return_track_label:
return_columns.append('track_label_2d')
if return_person_id:
return_columns.append('person_id')
if return_inference_id:
return_columns.append('inference_id')
if return_pose_model_id:
return_columns.append('pose_model_id')
return_columns.extend([
'keypoint_coordinates_2d',
'keypoint_quality_2d'
])
if return_pose_quality:
return_columns.append('pose_quality_2d')
poses_2d_df = poses_2d_df.reindex(columns=return_columns)
return poses_2d_df
# Not currently used
def search_2d_poses(
query_list,
return_data,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
logger.info('Searching for 2D poses that match the specified parameters')
result = honeycomb_io.core.search_objects(
object_name='Pose2D',
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Fetched {} poses'.format(len(result)))
return result
# Not currently used
def fetch_3d_pose_data(
start=None,
end=None,
pose_model_id=None,
pose_model_name=None,
pose_model_variant_name=None,
inference_ids=None,
inference_names=None,
inference_models=None,
inference_versions=None,
return_keypoint_quality=False,
return_coordinate_space_id=False,
return_track_label=False,
return_poses_2d=True,
return_person_id=False,
return_inference_id=False,
return_pose_model_id=False,
return_pose_quality=False,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
pose_model_id = fetch_pose_model_id(
pose_model_id=pose_model_id,
pose_model_name=pose_model_name,
pose_model_variant_name=pose_model_variant_name,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
inference_ids = honeycomb_io.inference_executions.fetch_inference_ids(
inference_ids=inference_ids,
inference_names=inference_names,
inference_models=inference_models,
inference_versions=inference_versions,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Building query list for 3D pose search')
query_list = list()
if start is not None:
query_list.append({
'field': 'timestamp',
'operator': 'GTE',
'value': honeycomb_io.utils.to_honeycomb_datetime(start)
})
if end is not None:
query_list.append({
'field': 'timestamp',
'operator': 'LTE',
'value': honeycomb_io.utils.to_honeycomb_datetime(end)
})
if pose_model_id is not None:
query_list.append({
'field': 'pose_model',
'operator': 'EQ',
'value': pose_model_id
})
if inference_ids is not None:
query_list.append({
'field': 'source',
'operator': 'IN',
'values': inference_ids
})
return_data= [
'pose_id',
'timestamp',
'track_label',
{'pose_model': [
'pose_model_id'
]},
{'keypoints': [
'coordinates',
'quality'
]},
{'coordinate_space': [
'space_id'
]},
'quality',
'poses_2d',
{'person': [
'person_id'
]},
{'source': [
{'... on InferenceExecution': [
'inference_id'
]}
]}
]
result = search_3d_poses(
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
data = list()
logger.info('Parsing {} returned poses'.format(len(result)))
for datum in result:
data.append({
'pose_3d_id': datum.get('pose_id'),
'timestamp': datum.get('timestamp'),
'track_label_3d': datum.get('track_label'),
'pose_2d_ids': datum.get('poses_2d'),
'person_id': (datum.get('person') if datum.get('person') is not None else {}).get('person_id'),
'inference_id': (datum.get('source') if datum.get('source') is not None else {}).get('inference_id'),
'pose_model_id': (datum.get('pose_model') if datum.get('pose_model') is not None else {}).get('pose_model_id'),
'keypoint_coordinates_3d': np.asarray([keypoint.get('coordinates') for keypoint in datum.get('keypoints')], dtype=np.float),
'keypoint_quality_3d': np.asarray([keypoint.get('quality') for keypoint in datum.get('keypoints')], dtype=np.float),
'coordinate_space_id': datum.get('coordinate_space').get('space_id'),
'pose_quality_3d': datum.get('quality')
})
poses_3d_df = pd.DataFrame(data)
poses_3d_df['timestamp'] = pd.to_datetime(poses_3d_df['timestamp'])
if poses_3d_df['pose_model_id'].nunique() > 1:
raise ValueError('Returned poses are associated with multiple pose models')
if (poses_3d_df.groupby('timestamp')['inference_id'].nunique() > 1).any():
raise ValueError('Returned poses have multiple inference IDs for timestamps')
poses_3d_df.set_index('pose_3d_id', inplace=True)
return_columns = [
'timestamp'
]
if return_track_label:
return_columns.append('track_label_3d')
if return_poses_2d:
return_columns.append('pose_2d_ids')
if return_person_id:
return_columns.append('person_id')
if return_inference_id:
return_columns.append('inference_id')
if return_pose_model_id:
return_columns.append('pose_model_id')
return_columns.append('keypoint_coordinates_3d')
if return_keypoint_quality:
return_columns.append('keypoint_quality_3d')
if return_pose_quality:
return_columns.append('pose_quality_3d')
if return_coordinate_space_id:
return_columns.append('coordinate_space_id')
poses_3d_df = poses_3d_df.reindex(columns=return_columns)
return poses_3d_df
# Not currently used
def search_3d_poses(
query_list,
return_data,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
logger.info('Searching for 3D poses that match the specified parameters')
result = honeycomb_io.core.search_objects(
object_name='Pose3D',
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Fetched {} poses'.format(len(result)))
return result
# Not currently used
def fetch_3d_pose_track_data(
inference_ids=None,
inference_names=None,
inference_models=None,
inference_versions=None,
return_track_label=False,
return_inference_id=False,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
inference_ids = honeycomb_io.inference_executions.fetch_inference_ids(
inference_ids=inference_ids,
inference_names=inference_names,
inference_models=inference_models,
inference_versions=inference_versions,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Building query list for 3D pose track search')
query_list = list()
if inference_ids is not None:
query_list.append({
'field': 'source',
'operator': 'IN',
'values': inference_ids
})
return_data = [
'pose_track_id',
'poses_3d',
'track_label',
{'source': [
{'... on InferenceExecution': [
'inference_id'
]}
]}
]
result = search_pose_tracks_3d(
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
data = list()
logger.info('Parsing {} returned pose tracks'.format(len(result)))
for datum in result:
data.append({
'pose_track_3d_id': datum.get('pose_track_id'),
'pose_3d_ids': datum.get('poses_3d'),
'track_label_3d': datum.get('track_label'),
'inference_id': (datum.get('source') if datum.get('source') is not None else {}).get('inference_id')
})
pose_tracks_3d_df = pd.DataFrame(data)
pose_tracks_3d_df.set_index('pose_track_3d_id', inplace=True)
return_columns = [
'pose_3d_ids'
]
if return_track_label:
return_columns.append('track_label_3d')
if return_inference_id:
return_columns.append('inference_id')
pose_tracks_3d_df = pose_tracks_3d_df.reindex(columns=return_columns)
return pose_tracks_3d_df
# Not currently used
def search_pose_tracks_3d(
query_list,
return_data,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
logger.info('Searching for 3D pose tracks that match the specified parameters')
result = honeycomb_io.core.search_objects(
object_name='poseTrack3D',
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
logger.info('Fetched {} pose tracks'.format(len(result)))
return result
# Not currently used
def fetch_pose_model_id(
pose_model_id=None,
pose_model_name=None,
pose_model_variant_name=None,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
if pose_model_id is not None:
if pose_model_name is not None or pose_model_variant_name is not None:
raise ValueError('If pose model ID is specified, pose model name/variant name cannot be specified')
return pose_model_id
if pose_model_name is not None or pose_model_variant_name is not None:
arguments=dict()
if pose_model_name is not None:
arguments['model_name'] = {
'type': 'String',
'value': pose_model_name
}
if pose_model_variant_name is not None:
arguments['model_variant_name'] = {
'type': 'String',
'value': pose_model_variant_name
}
logger.info('Fetching pose model ID for pose model with specified properties')
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
result = client.bulk_query(
request_name='findPoseModels',
arguments=arguments,
return_data=[
'pose_model_id'
],
id_field_name='pose_model_id'
)
if len(result) == 0:
raise ValueError('No pose models match specified model name/model variant name')
if len(result) > 1:
raise ValueError('Multiple pose models match specified model name/model variant name')
pose_model_id = result[0].get('pose_model_id')
logger.info('Found pose model ID for pose model with specified properties')
return pose_model_id
return None
# Used by:
# process_pose_data.overlay (wf-process-pose-data)
def fetch_pose_model(
pose_2d_id,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
logger.info('Fetching pose model information for specified pose')
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
result = client.request(
request_type='query',
request_name='getPose2D',
arguments={
'pose_id': {
'type': 'ID!',
'value': pose_2d_id
}
},
return_object=[
{'pose_model': [
'pose_model_id',
'model_name',
'model_variant_name',
'keypoint_names',
'keypoint_descriptions',
'keypoint_connectors'
]}
])
pose_model = result.get('pose_model')
return pose_model
# Used by:
# process_pose_data.overlay (wf-process-pose_data)
# process_pose_data.reconstruct (wf-process-pose-data)
def fetch_pose_model_by_pose_model_id(
pose_model_id,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
logger.info('Fetching pose model information for specified pose model ID')
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
result = client.request(
request_type='query',
request_name='getPoseModel',
arguments={
'pose_model_id': {
'type': 'ID!',
'value': pose_model_id
}
},
return_object=[
'pose_model_id',
'model_name',
'model_variant_name',
'keypoint_names',
'keypoint_descriptions',
'keypoint_connectors'
])
pose_model = result
return pose_model
# Not currently used
def fetch_inference_ids_reconstruct_3d_poses(
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
result = client.bulk_query(
request_name='findInferenceExecutions',
arguments={
'name': {
'type': 'String',
'value': 'Reconstruct 3D poses from 2D poses'
}
},
return_data=[
'inference_id'
],
id_field_name='inference_id'
)
inference_ids = [datum.get('inference_id') for datum in result]
return inference_ids
# Not currently used
def write_3d_pose_data(
poses_3d_df,
coordinate_space_id=None,
pose_model_id=None,
source_id=None,
source_type=None,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
poses_3d_df_honeycomb = poses_3d_df.copy()
if coordinate_space_id is None:
if 'coordinate_space_id' not in poses_3d_df_honeycomb.columns:
raise ValueError('Coordinate space ID must either be included in data frame or specified')
else:
poses_3d_df_honeycomb['coordinate_space_id'] = coordinate_space_id
if pose_model_id is None:
if 'pose_model_id' not in poses_3d_df_honeycomb.columns:
raise ValueError('Pose model ID must either be included in data frame or specified')
else:
poses_3d_df_honeycomb['pose_model_id'] = pose_model_id
if source_id is None:
if 'source_id' not in poses_3d_df_honeycomb.columns:
raise ValueError('Source ID must either be included in data frame or specified')
else:
poses_3d_df_honeycomb['source_id'] = source_id
if source_type is None:
if 'source_type' not in poses_3d_df_honeycomb.columns:
raise ValueError('Source type must either be included in data frame or specified')
else:
poses_3d_df_honeycomb['source_type'] = source_type
poses_3d_df_honeycomb['timestamp'] = poses_3d_df_honeycomb['timestamp'].apply(
lambda x: honeycomb_io.utils.to_honeycomb_datetime(x.to_pydatetime())
)
poses_3d_df_honeycomb['keypoint_coordinates_3d'] = poses_3d_df_honeycomb['keypoint_coordinates_3d'].apply(
lambda x: np.where(np.isnan(x), None, x)
)
poses_3d_df_honeycomb['keypoint_coordinates_3d'] = poses_3d_df_honeycomb['keypoint_coordinates_3d'].apply(
lambda x: [{'coordinates': x[i, :].tolist()} for i in range(x.shape[0])]
)
poses_3d_df_honeycomb = poses_3d_df_honeycomb.reindex(columns=[
'timestamp',
'coordinate_space_id',
'pose_model_id',
'keypoint_coordinates_3d',
'pose_2d_ids',
'source_id',
'source_type'
])
poses_3d_df_honeycomb.rename(
columns={
'coordinate_space_id': 'coordinate_space',
'pose_model_id': 'pose_model',
'keypoint_coordinates_3d': 'keypoints',
'pose_2d_ids': 'poses_2d',
'source_id': 'source'
},
inplace=True
)
poses_3d_list_honeycomb = poses_3d_df_honeycomb.to_dict(orient='records')
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
logger.info('Writing 3D pose data')
result = client.bulk_mutation(
request_name='createPose3D',
arguments={
'pose3D': {
'type': 'Pose3DInput',
'value': poses_3d_list_honeycomb
}
},
return_object=[
'pose_id'
],
chunk_size=chunk_size
)
try:
pose_3d_ids = [datum['pose_id'] for datum in result]
except:
raise ValueError('Received unexpected result from Honeycomb:\n{}'.format(result))
return pose_3d_ids
# Not currently used
def delete_3d_pose_data_by_inference_id(
inference_id,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
pose_ids = fetch_pose_3d_ids(
inference_id,
chunk_size=chunk_size,
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
statuses = delete_3d_pose_data_by_pose_ids(
pose_ids,
chunk_size=chunk_size,
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
return pose_ids
# Not currently used
def fetch_pose_3d_ids(
inference_id,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
query_list=[{
'field': 'source',
'operator': 'EQ',
'value': inference_id
}]
return_data=['pose_id']
result = search_3d_poses(
query_list=query_list,
return_data=return_data,
chunk_size=chunk_size,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
)
pose_ids = [datum.get('pose_id') for datum in result]
return pose_ids
# Not currently used
def delete_3d_pose_data_by_pose_ids(
pose_ids,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
if len(pose_ids) == 0:
return pose_ids
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
result = client.bulk_mutation(
request_name='deletePose3D',
arguments={
'pose_id': {
'type': 'ID',
'value': pose_ids
}
},
return_object=['status'],
chunk_size=chunk_size
)
statuses = [datum.get('status') for datum in result]
return statuses
# Not currently used
def write_pose_tracks_3d(
poses_3d_df,
source_id,
source_type,
chunk_size=100,
client=None,
uri=None,
token_uri=None,
audience=None,
client_id=None,
client_secret=None
):
poses_3d_df_copy = poses_3d_df.copy()
current_index_name = poses_3d_df_copy.index.name
poses_3d_df_copy = poses_3d_df_copy.reset_index().rename(columns={current_index_name: 'pose_3d_id'})
pose_tracks_3d_df = poses_3d_df_copy.groupby('pose_track_3d_id').agg(
poses_3d = pd.NamedAgg(
column='pose_3d_id',
aggfunc = lambda x: x.tolist()
)
)
pose_tracks_3d_df['source'] = source_id
pose_tracks_3d_df['source_type'] = source_type
pose_tracks_3d_list = pose_tracks_3d_df.to_dict(orient='records')
client = honeycomb_io.core.generate_client(
client=client,
uri=uri,
token_uri=token_uri,
audience=audience,
client_id=client_id,
client_secret=client_secret
)
logger.info('Writing 3D pose tracks')
result = client.bulk_mutation(
request_name='createPoseTrack3D',
arguments={
'poseTrack3D': {
'type': 'PoseTrack3DInput',
'value': pose_tracks_3d_list
}
},
return_object=[
'pose_track_id'
],
chunk_size=chunk_size
)
try:
pose_track_3d_ids = [datum['pose_track_id'] for datum in result]
except:
raise ValueError('Received unexpected result from Honeycomb:\n{}'.format(result))
return pose_track_3d_ids
| 30.520505
| 136
| 0.623531
| 3,506
| 29,025
| 4.826583
| 0.061038
| 0.053717
| 0.036402
| 0.029134
| 0.806169
| 0.753575
| 0.703818
| 0.667533
| 0.656896
| 0.629713
| 0
| 0.009726
| 0.277382
| 29,025
| 950
| 137
| 30.552632
| 0.797082
| 0.022601
| 0
| 0.677668
| 0
| 0
| 0.166878
| 0.012031
| 0
| 0
| 0
| 0
| 0
| 1
| 0.016502
| false
| 0
| 0.008801
| 0
| 0.045105
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0926fa81a190688170cc5b279aac5949bdd67265
| 2,785
|
py
|
Python
|
control/flatsys/__init__.py
|
AI-App/Python-Control
|
c2f6f8ab94bbc8b5ef1deb33c3d2df39e00d22bf
|
[
"BSD-3-Clause"
] | 1,112
|
2015-01-14T08:01:33.000Z
|
2022-03-31T11:54:00.000Z
|
control/flatsys/__init__.py
|
AI-App/Python-Control
|
c2f6f8ab94bbc8b5ef1deb33c3d2df39e00d22bf
|
[
"BSD-3-Clause"
] | 646
|
2015-02-02T15:35:23.000Z
|
2022-03-30T08:19:26.000Z
|
control/flatsys/__init__.py
|
AI-App/Python-Control
|
c2f6f8ab94bbc8b5ef1deb33c3d2df39e00d22bf
|
[
"BSD-3-Clause"
] | 366
|
2015-01-28T17:58:06.000Z
|
2022-03-29T11:04:10.000Z
|
# flatsys/__init__.py: flat systems package initialization file
#
# Copyright (c) 2019 by California Institute of Technology
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the California Institute of Technology nor
# the names of its contributors may be used to endorse or promote
# products derived from this software without specific prior
# written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL CALTECH
# OR THE CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
# USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
# OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
# SUCH DAMAGE.
#
# Author: Richard M. Murray
# Date: 1 Jul 2019
r"""The :mod:`control.flatsys` package contains a set of classes and functions
that can be used to compute trajectories for differentially flat systems.
A differentially flat system is defined by creating an object using the
:class:`~control.flatsys.FlatSystem` class, which has member functions for
mapping the system state and input into and out of flat coordinates. The
:func:`~control.flatsys.point_to_point` function can be used to create a
trajectory between two endpoints, written in terms of a set of basis functions
defined using the :class:`~control.flatsys.BasisFamily` class. The resulting
trajectory is return as a :class:`~control.flatsys.SystemTrajectory` object
and can be evaluated using the :func:`~control.flatsys.SystemTrajectory.eval`
member function.
"""
# Basis function families
from .basis import BasisFamily
from .poly import PolyFamily
from .bezier import BezierFamily
# Classes
from .systraj import SystemTrajectory
from .flatsys import FlatSystem
from .linflat import LinearFlatSystem
# Package functions
from .flatsys import point_to_point
| 42.846154
| 78
| 0.789587
| 399
| 2,785
| 5.491228
| 0.483709
| 0.038339
| 0.010954
| 0.028298
| 0.108626
| 0.062072
| 0.062072
| 0.062072
| 0.062072
| 0.062072
| 0
| 0.005117
| 0.157989
| 2,785
| 64
| 79
| 43.515625
| 0.929211
| 0.882226
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.875
| 0
| 0.875
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
1179b8e6e2ca903e9d67f8004d35b4d8d3073307
| 120
|
py
|
Python
|
run.py
|
matheusccouto/superstore-api
|
bf0b0359f4632382cd9a3f0031f7eb27c98330e8
|
[
"MIT"
] | null | null | null |
run.py
|
matheusccouto/superstore-api
|
bf0b0359f4632382cd9a3f0031f7eb27c98330e8
|
[
"MIT"
] | 2
|
2021-05-06T22:02:25.000Z
|
2021-05-12T14:02:33.000Z
|
run.py
|
matheusccouto/superstore-api
|
bf0b0359f4632382cd9a3f0031f7eb27c98330e8
|
[
"MIT"
] | null | null | null |
""" Run application. """
import api
if __name__ == "__main__":
api.app.run(host="0.0.0.0", port=5000, debug=True)
| 17.142857
| 54
| 0.625
| 19
| 120
| 3.526316
| 0.736842
| 0.089552
| 0.089552
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.079208
| 0.158333
| 120
| 6
| 55
| 20
| 0.584158
| 0.133333
| 0
| 0
| 0
| 0
| 0.15625
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
11946c20703785fce1368fe6e4fbbb124d31fcfd
| 27
|
py
|
Python
|
exercises/exc_01_02.py
|
rklymentiev/py-for-neuro
|
6bb163347483642c79eac429e5a9289edff7ce09
|
[
"MIT"
] | 7
|
2021-04-28T13:12:16.000Z
|
2022-01-15T00:21:11.000Z
|
exercises/exc_01_02.py
|
rklymentiev/py-for-neuro
|
6bb163347483642c79eac429e5a9289edff7ce09
|
[
"MIT"
] | 2
|
2021-04-02T18:42:55.000Z
|
2021-05-20T08:43:06.000Z
|
exercises/exc_01_02.py
|
rklymentiev/py-for-neuro
|
6bb163347483642c79eac429e5a9289edff7ce09
|
[
"MIT"
] | 2
|
2021-07-04T22:57:29.000Z
|
2021-07-29T19:28:43.000Z
|
___ = 4
y = ___
print(___)
| 6.75
| 10
| 0.592593
| 3
| 27
| 2.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05
| 0.259259
| 27
| 3
| 11
| 9
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 0
| 0.333333
| 1
| 1
| 0
| null | 0
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| 0
| 0
|
0
| 4
|
11a502c67650aa65da6bc9f177dbe33e55da47d4
| 429
|
py
|
Python
|
guniflask/beans/factory_post_processor.py
|
jadbin/guniflask
|
36253a962c056abf34884263c6919b02b921ad9c
|
[
"MIT"
] | 12
|
2018-09-06T06:14:59.000Z
|
2021-04-18T06:30:44.000Z
|
guniflask/beans/factory_post_processor.py
|
jadbin/guniflask
|
36253a962c056abf34884263c6919b02b921ad9c
|
[
"MIT"
] | null | null | null |
guniflask/beans/factory_post_processor.py
|
jadbin/guniflask
|
36253a962c056abf34884263c6919b02b921ad9c
|
[
"MIT"
] | 2
|
2019-09-08T22:01:26.000Z
|
2020-08-03T07:23:29.000Z
|
from guniflask.beans.definition_registry import BeanDefinitionRegistry
from guniflask.beans.factory import ConfigurableBeanFactory
class BeanFactoryPostProcessor:
def post_process_bean_factory(self, bean_factory: ConfigurableBeanFactory):
pass
class BeanDefinitionRegistryPostProcessor(BeanFactoryPostProcessor):
def post_process_bean_definition_registry(self, registry: BeanDefinitionRegistry):
pass
| 33
| 86
| 0.841492
| 38
| 429
| 9.263158
| 0.473684
| 0.073864
| 0.102273
| 0.215909
| 0.238636
| 0
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| 0
| 0
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| 0
| 0.11655
| 429
| 12
| 87
| 35.75
| 0.92876
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| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
11a5d346813f573a79b18c4f1bb3f82e5d3551dd
| 121
|
py
|
Python
|
pymgl/__init__.py
|
brendan-ward/pymgl
|
c88e652023601736b73bd60f5fb7df6359255f28
|
[
"MIT"
] | 3
|
2022-03-01T21:38:38.000Z
|
2022-03-03T02:10:07.000Z
|
pymgl/__init__.py
|
brendan-ward/pymgl
|
c88e652023601736b73bd60f5fb7df6359255f28
|
[
"MIT"
] | 1
|
2022-03-07T21:25:17.000Z
|
2022-03-08T20:27:11.000Z
|
pymgl/__init__.py
|
brendan-ward/pymgl
|
c88e652023601736b73bd60f5fb7df6359255f28
|
[
"MIT"
] | null | null | null |
from pymgl._pymgl import Map
__all__ = ["Map"]
from . import _version
__version__ = _version.get_versions()['version']
| 17.285714
| 48
| 0.743802
| 15
| 121
| 5.2
| 0.533333
| 0.358974
| 0
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| 0
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| 0
| 0
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| 0
| 0
| 0.132231
| 121
| 6
| 49
| 20.166667
| 0.742857
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| 1
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| 0
| 0
|
0
| 4
|
11aa6a5f494218ead978b1c6424e3aa71e1833dd
| 523
|
py
|
Python
|
src/botadi/mokadi/mokadi_exceptions.py
|
sdpython/botadi
|
bb9c1f5a6dca5c91231c7146ca73955f7d7fade8
|
[
"MIT"
] | null | null | null |
src/botadi/mokadi/mokadi_exceptions.py
|
sdpython/botadi
|
bb9c1f5a6dca5c91231c7146ca73955f7d7fade8
|
[
"MIT"
] | null | null | null |
src/botadi/mokadi/mokadi_exceptions.py
|
sdpython/botadi
|
bb9c1f5a6dca5c91231c7146ca73955f7d7fade8
|
[
"MIT"
] | null | null | null |
"""
@file
@brief Exception for Mokadi.
"""
class MokadiException(Exception):
"""
Mokadi exception.
"""
pass # pylint: disable=W0107
class CognitiveException(Exception):
"""
Failure when calling the API.
"""
pass # pylint: disable=W0107
class WikipediaException(Exception):
"""
Issue with :epkg:`wikipedia`.
"""
pass # pylint: disable=W0107
class MokadiAuthentification(Exception):
"""
Issue with authentification.
"""
pass # pylint: disable=W0107
| 15.848485
| 40
| 0.630975
| 47
| 523
| 7.021277
| 0.510638
| 0.121212
| 0.206061
| 0.266667
| 0.245455
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040506
| 0.244742
| 523
| 32
| 41
| 16.34375
| 0.794937
| 0.439771
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| 1
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| 0
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| 0
| 0
| 0
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
11ace981ad775a5c6f9e787b7971b13b5165be0d
| 1,289
|
py
|
Python
|
py/datacentric/schema/declaration/language.py
|
datacentricorg/datacentric-py
|
40113ddfb68e62d98b880b3c7427db5cc9fbd8cd
|
[
"Apache-2.0"
] | 1
|
2020-02-03T18:32:42.000Z
|
2020-02-03T18:32:42.000Z
|
py/datacentric/schema/declaration/language.py
|
datacentricorg/datacentric-py
|
40113ddfb68e62d98b880b3c7427db5cc9fbd8cd
|
[
"Apache-2.0"
] | null | null | null |
py/datacentric/schema/declaration/language.py
|
datacentricorg/datacentric-py
|
40113ddfb68e62d98b880b3c7427db5cc9fbd8cd
|
[
"Apache-2.0"
] | null | null | null |
# Copyright (C) 2013-present The DataCentric Authors.
#
# 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.
import attr
from datacentric.storage.data import Data
@attr.s(slots=True, auto_attribs=True)
class Language(Data):
"""
Identifies the programming language in which a handler is implemented.
By convention, language name is the same as source file suffix:
* For Python, py
* For C++, cpp
* For C#, cs
The language is used to select which DataCentric CLI to invoke to execute
the handler. For example, if language name is py, the CLI to invoke is
datacentric-py.
TODO - convert to record so key can be picked
"""
language_name: str = attr.ib(default=None, kw_only=True, metadata={'optional': True})
"""Unique language identifier."""
| 33.051282
| 89
| 0.72692
| 195
| 1,289
| 4.789744
| 0.589744
| 0.06424
| 0.027837
| 0.034261
| 0
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| 0
| 0
| 0
| 0
| 0
| 0.007722
| 0.196276
| 1,289
| 38
| 90
| 33.921053
| 0.893822
| 0.747867
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| 1
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| 1
| 0
| 1
| 0
|
0
| 4
|
11d3d95cca4c04b7d302c12003a6f2b91f6bc224
| 102
|
py
|
Python
|
USApp/install_ffmpeg.py
|
adhaimovich/USPro
|
1aa3150afad3f5ac4c7d93478ca072fd7fa2964b
|
[
"MIT"
] | 2
|
2020-08-19T09:06:40.000Z
|
2021-12-10T11:11:58.000Z
|
USApp/install_ffmpeg.py
|
adhaimovich/USPro
|
1aa3150afad3f5ac4c7d93478ca072fd7fa2964b
|
[
"MIT"
] | null | null | null |
USApp/install_ffmpeg.py
|
adhaimovich/USPro
|
1aa3150afad3f5ac4c7d93478ca072fd7fa2964b
|
[
"MIT"
] | null | null | null |
# Installation script for the docker container image
import imageio
imageio.plugins.ffmpeg.download()
| 25.5
| 52
| 0.833333
| 13
| 102
| 6.538462
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107843
| 102
| 4
| 53
| 25.5
| 0.934066
| 0.490196
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| true
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| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
11f3e9e3677cae492bf6018e309d3409ff19eb2e
| 116
|
py
|
Python
|
7kyu/(7 kyu) Highest and Lowest/(7 kyu) Highest and Lowest.py
|
e1r0nd/codewars
|
dc98484281345e7675eb5e8a51c192e2fa77c443
|
[
"MIT"
] | 49
|
2018-04-30T06:42:45.000Z
|
2021-07-22T16:39:02.000Z
|
(7 kyu) Highest and Lowest/(7 kyu) Highest and Lowest.py
|
novsunheng/codewars
|
c54b1d822356889b91587b088d02ca0bd3d8dc9e
|
[
"MIT"
] | 1
|
2020-08-31T02:36:53.000Z
|
2020-08-31T10:14:00.000Z
|
(7 kyu) Highest and Lowest/(7 kyu) Highest and Lowest.py
|
novsunheng/codewars
|
c54b1d822356889b91587b088d02ca0bd3d8dc9e
|
[
"MIT"
] | 25
|
2018-04-02T20:57:58.000Z
|
2021-05-28T15:24:51.000Z
|
def high_and_low(numbers):
arr = list(map(int, numbers.split()))
return str(max(arr)) + ' ' + str(min(arr))
| 29
| 46
| 0.612069
| 18
| 116
| 3.833333
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181034
| 116
| 3
| 47
| 38.666667
| 0.726316
| 0
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| 0
| 0
| 0.008621
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
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| 0.666667
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
ee9448d1ad2a70211320922dfee8e54556432656
| 104
|
py
|
Python
|
openstack_project_create/signals.py
|
kanellov/openstack_project_create
|
6c41179a120e637d0de8d88d3bcbdbae9af90bc4
|
[
"MIT"
] | null | null | null |
openstack_project_create/signals.py
|
kanellov/openstack_project_create
|
6c41179a120e637d0de8d88d3bcbdbae9af90bc4
|
[
"MIT"
] | null | null | null |
openstack_project_create/signals.py
|
kanellov/openstack_project_create
|
6c41179a120e637d0de8d88d3bcbdbae9af90bc4
|
[
"MIT"
] | null | null | null |
import django.dispatch
project_created = django.dispatch.Signal(providing_args=["project", "user_id"])
| 26
| 79
| 0.798077
| 13
| 104
| 6.153846
| 0.769231
| 0.35
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.067308
| 104
| 3
| 80
| 34.666667
| 0.824742
| 0
| 0
| 0
| 0
| 0
| 0.134615
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
eec71377fca30308de3a5f87de249e41cb90ef43
| 115
|
py
|
Python
|
unit_tests/__init__.py
|
cultural-charmers/the_lounge
|
d6fd06f38a3e848645b5709fc9034986e30dfd70
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
unit_tests/__init__.py
|
cultural-charmers/the_lounge
|
d6fd06f38a3e848645b5709fc9034986e30dfd70
|
[
"ECL-2.0",
"Apache-2.0"
] | 3
|
2019-07-10T15:27:36.000Z
|
2019-07-10T15:28:05.000Z
|
unit_tests/__init__.py
|
cultural-charmers/the_lounge
|
d6fd06f38a3e848645b5709fc9034986e30dfd70
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
import unittest
class TestItWorks(unittest.TestCase):
def test_it_works(self):
self.assertTrue(True)
| 16.428571
| 37
| 0.730435
| 14
| 115
| 5.857143
| 0.857143
| 0
| 0
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| 0
| 0.182609
| 115
| 6
| 38
| 19.166667
| 0.87234
| 0
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| 0.25
| 1
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| 0
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| 1
| 0
|
0
| 4
|
eee870761311a60df2fd692c8b6ab9f370eaa5cb
| 86
|
py
|
Python
|
tests/test_pool.py
|
blakev/gevent-tasks
|
3cf5204e8587a0d7ea9ec7c86006173330b7d744
|
[
"MIT"
] | 17
|
2017-10-18T00:01:42.000Z
|
2021-08-10T10:17:59.000Z
|
tests/test_manager.py
|
blakev/gevent-tasks
|
3cf5204e8587a0d7ea9ec7c86006173330b7d744
|
[
"MIT"
] | null | null | null |
tests/test_manager.py
|
blakev/gevent-tasks
|
3cf5204e8587a0d7ea9ec7c86006173330b7d744
|
[
"MIT"
] | 2
|
2017-10-18T10:32:59.000Z
|
2021-01-25T20:15:08.000Z
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# >>
# gevent-tasks, 2017
# <<
| 8.6
| 24
| 0.465116
| 10
| 86
| 4
| 1
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| 0.267442
| 86
| 9
| 25
| 9.555556
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|
0
| 4
|
eeebd5c76a922f775213363b6e70f2eefb7129b7
| 23
|
py
|
Python
|
b2share/modules/__init__.py
|
hjhsalo/b2share-new
|
2a2a961f7cc3a5353850e9a409fd7e879c715b0b
|
[
"MIT"
] | null | null | null |
b2share/modules/__init__.py
|
hjhsalo/b2share-new
|
2a2a961f7cc3a5353850e9a409fd7e879c715b0b
|
[
"MIT"
] | null | null | null |
b2share/modules/__init__.py
|
hjhsalo/b2share-new
|
2a2a961f7cc3a5353850e9a409fd7e879c715b0b
|
[
"MIT"
] | 1
|
2020-09-29T10:56:03.000Z
|
2020-09-29T10:56:03.000Z
|
"""B2SHARE Modules."""
| 11.5
| 22
| 0.608696
| 2
| 23
| 7
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| 0.047619
| 0.086957
| 23
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| 23
| 0.619048
| 0.695652
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| 0
| 0
| 0
|
0
| 4
|
eef02767811fbca00fbf27701dd32a1036a67f80
| 171
|
py
|
Python
|
test/fpga/boot_screen_test/constraints.py
|
mbalestrini/hack_soc
|
157428ee6856a9e4cee5953b8b3c144b4f57f5ee
|
[
"Apache-2.0"
] | 1
|
2021-12-18T18:31:53.000Z
|
2021-12-18T18:31:53.000Z
|
test/fpga/video_generator/constraints.py
|
mbalestrini/hack_soc
|
157428ee6856a9e4cee5953b8b3c144b4f57f5ee
|
[
"Apache-2.0"
] | null | null | null |
test/fpga/video_generator/constraints.py
|
mbalestrini/hack_soc
|
157428ee6856a9e4cee5953b8b3c144b4f57f5ee
|
[
"Apache-2.0"
] | null | null | null |
# ctx.addClock("csi_rx_i.dphy_clk", 96)
# ctx.addClock("video_clk", 24)
# ctx.addClock("uart_i.sys_clk_i", 12)
ctx.addClock("EXTERNAL_CLK", 12)
# ctx.addClock("clk", 25)
| 24.428571
| 39
| 0.701754
| 30
| 171
| 3.733333
| 0.5
| 0.491071
| 0.232143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064103
| 0.087719
| 171
| 6
| 40
| 28.5
| 0.653846
| 0.748538
| 0
| 0
| 0
| 0
| 0.315789
| 0
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| 0
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| 0
| 0
| 1
| 0
| true
| 0
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| null | 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e1148c2c7e3363a91e956e65e9893452913db175
| 234
|
py
|
Python
|
recommender/admin.py
|
MH-Lee/sunbo_django
|
a95358801cb3ee9a4c4bc16732a2f80312403290
|
[
"MIT"
] | null | null | null |
recommender/admin.py
|
MH-Lee/sunbo_django
|
a95358801cb3ee9a4c4bc16732a2f80312403290
|
[
"MIT"
] | 18
|
2019-11-16T15:50:08.000Z
|
2022-02-10T11:46:51.000Z
|
recommender/admin.py
|
MH-Lee/sunbo_ubuntu
|
27a435838421b4950eed53da3ccbd15cbb501cf2
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Recommender
# Register your models here.
class RcommenderAdmin(admin.ModelAdmin):
list_display = ('company', 'big_predict1')
admin.site.register(Recommender, RcommenderAdmin)
| 26
| 49
| 0.794872
| 27
| 234
| 6.814815
| 0.703704
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004831
| 0.115385
| 234
| 9
| 49
| 26
| 0.884058
| 0.111111
| 0
| 0
| 0
| 0
| 0.091787
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
0169d8f3788d1b54c2a9ce601b0d2dcfce0fa6b0
| 577
|
py
|
Python
|
backend/puzzle/views/__init__.py
|
mductran/puzzle
|
c4598f5420dff126fa67db1e0adee1677a8baf8f
|
[
"Apache-2.0"
] | null | null | null |
backend/puzzle/views/__init__.py
|
mductran/puzzle
|
c4598f5420dff126fa67db1e0adee1677a8baf8f
|
[
"Apache-2.0"
] | null | null | null |
backend/puzzle/views/__init__.py
|
mductran/puzzle
|
c4598f5420dff126fa67db1e0adee1677a8baf8f
|
[
"Apache-2.0"
] | null | null | null |
from puzzle.views.puzzle import PuzzleView
from puzzle.views.account import AccountView
from puzzle.views.collage import CollageView
from puzzle.views.post import PostView
from puzzle.views.comment import CommentView
from puzzle.views.inventory import InventoryView
from puzzle.views.image import ImageView
from puzzle.views.token import CookieTokenObtainPairView, CookieTokenRefreshView
from puzzle.views.logout import BlacklistRefreshView
from puzzle.views.current_user import CurrentUserView
from puzzle.views.trade import TradeView
from puzzle.views.offer import OfferView
| 44.384615
| 80
| 0.87175
| 74
| 577
| 6.783784
| 0.391892
| 0.239044
| 0.358566
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084922
| 577
| 12
| 81
| 48.083333
| 0.950758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
017d4cae28deeeeb4108d1b350744f1424f45ec9
| 635
|
py
|
Python
|
OpenAttack/tags/base.py
|
e-tornike/OpenAttack
|
b19c53af2e01f096505f8ebb8f48a54388295003
|
[
"MIT"
] | 444
|
2020-07-14T12:13:26.000Z
|
2022-03-28T02:46:30.000Z
|
OpenAttack/tags/base.py
|
e-tornike/OpenAttack
|
b19c53af2e01f096505f8ebb8f48a54388295003
|
[
"MIT"
] | 50
|
2020-07-15T01:34:42.000Z
|
2022-01-24T12:19:19.000Z
|
OpenAttack/tags/base.py
|
e-tornike/OpenAttack
|
b19c53af2e01f096505f8ebb8f48a54388295003
|
[
"MIT"
] | 86
|
2020-08-02T13:16:45.000Z
|
2022-03-27T06:22:04.000Z
|
class Tag(object):
def __init__(self, tag_name : str, type_ = None):
self.__tag_name = tag_name
self.__type : str = type_ if type_ is not None else ""
@property
def type(self) -> str:
return self.__type
@property
def name(self) -> str:
return self.__tag_name
def __str__(self) -> str:
return self.type + ":" + self.__tag_name
def __eq__(self, o: object):
return str(o).lower() == str(self).lower()
def __hash__(self) -> int:
return hash(str(self))
def __repr__(self) -> str:
return "<%s>" % str(self)
| 25.4
| 62
| 0.548031
| 81
| 635
| 3.82716
| 0.283951
| 0.112903
| 0.141935
| 0.164516
| 0.135484
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.322835
| 635
| 25
| 63
| 25.4
| 0.72093
| 0
| 0
| 0.111111
| 0
| 0
| 0.007862
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.388889
| false
| 0
| 0
| 0.333333
| 0.777778
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
6d9efca1b6b68dcb15e00f67531985b97651c642
| 7,657
|
py
|
Python
|
experimental_models/utils/models_multimodal.py
|
justinbt1/Multimodal-Document-Classification
|
794eb1e1235efc9c81f1edca881db576d754628a
|
[
"MIT"
] | null | null | null |
experimental_models/utils/models_multimodal.py
|
justinbt1/Multimodal-Document-Classification
|
794eb1e1235efc9c81f1edca881db576d754628a
|
[
"MIT"
] | null | null | null |
experimental_models/utils/models_multimodal.py
|
justinbt1/Multimodal-Document-Classification
|
794eb1e1235efc9c81f1edca881db576d754628a
|
[
"MIT"
] | null | null | null |
from tensorflow import keras
def early_fusion_model(vocab_length):
""" Multimodal early fusion model.
Args:
vocab_length(int): vocabulary length.
Returns:
Multimodal early fusion model
"""
text_input = keras.layers.Input(shape=(10, 2000), name='text_input')
embeddings = keras.layers.TimeDistributed(
keras.layers.Embedding(vocab_length, 150, input_length=2000),
name='word_embeddings'
)(text_input)
conv_1d = keras.layers.TimeDistributed(
keras.layers.Conv1D(filters=200, kernel_size=7, activation='relu'),
name='1d_convolutional_layer'
)(embeddings)
global_pooling = keras.layers.TimeDistributed(keras.layers.GlobalMaxPool1D(), name='max_pooling_layer')(conv_1d)
image_features = keras.layers.TimeDistributed(keras.layers.Flatten(), name='text_features')(global_pooling)
image_input = keras.layers.Input(shape=(10, 200, 200, 1), name='image_input')
conv_2d_1 = keras.layers.TimeDistributed(
keras.layers.Conv2D(20, 7, activation='relu', padding='same'),
name='2d_convolutional_layer_1'
)(image_input)
pool_2d_1 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4), name='2d_max_pooling_layer_1')(conv_2d_1)
conv_2d_2 = keras.layers.TimeDistributed(
keras.layers.Conv2D(50, 5, activation='relu', padding='valid'),
name='2d_convolutional_layer_2'
)(pool_2d_1)
pool_2d_2 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4), name='2d_max_pooling_layer_2')(conv_2d_2)
text_features = keras.layers.TimeDistributed(keras.layers.Flatten(), name='image_features')(pool_2d_2)
joint_features = keras.layers.concatenate([text_features, image_features])
lstm_1 = keras.layers.LSTM(450, return_sequences=True)(joint_features)
lstm_2 = keras.layers.LSTM(1000)(lstm_1)
dropout = keras.layers.Dropout(0.5)(lstm_2)
output = keras.layers.Dense(6, activation='softmax')(dropout)
model = keras.models.Model(inputs=[text_input, image_input], outputs=[output])
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
return model
def late_fusion_model(vocab_length):
""" Multimodal late fusion model.
Args:
vocab_length(int): vocabulary length.
Returns:
Multimodal late fusion model.
"""
# Text CNN
text_input = keras.layers.Input(shape=2000)
embeddings = keras.layers.Embedding(vocab_length, 150, input_length=2000)(text_input)
conv_1d = keras.layers.Conv1D(filters=200, kernel_size=7, activation='relu')(embeddings)
global_pooling = keras.layers.GlobalMaxPool1D()(conv_1d)
flatten = keras.layers.Flatten()(global_pooling)
dense_layer = keras.layers.Dense(50, activation='relu', kernel_regularizer=keras.regularizers.l2(0.5))(flatten)
text_features = keras.layers.Dropout(0.3)(dense_layer)
# Image CNN LSTM
image_input = keras.layers.Input(shape=(10, 200, 200, 1))
conv_2d_1 = keras.layers.TimeDistributed(keras.layers.Conv2D(20, 7, activation='relu', padding='same'))(image_input)
pool_2d_1 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(conv_2d_1)
conv_2d_2 = keras.layers.TimeDistributed(keras.layers.Conv2D(50, 5, activation='relu', padding='valid'))(pool_2d_1)
pool_2d_2 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(conv_2d_2)
extracted_features = keras.layers.TimeDistributed(keras.layers.Flatten())(pool_2d_2)
lstm_1 = keras.layers.LSTM(1000, return_sequences=True)(extracted_features)
image_features = keras.layers.LSTM(1000, dropout=0.5)(lstm_1)
# Feed Forward Softmax Classifier
concat_features = keras.layers.concatenate([text_features, image_features])
output = keras.layers.Dense(6, activation='softmax')(concat_features)
model = keras.models.Model(inputs=[text_input, image_input], outputs=[output])
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
return model
def hybrid_fusion_model(vocab_length):
""" Multimodal hybrid fusion model.
Args:
vocab_length(int): vocabulary length.
Returns:
Multimodal hybrid fusion model.
"""
late_fusion_text_input = keras.layers.Input(shape=2000)
early_fusion_text_input = keras.layers.Input(shape=(10, 2000))
image_input = keras.layers.Input(shape=(10, 200, 200, 1))
lf_embeddings = keras.layers.Embedding(vocab_length, 150, input_length=2000)(late_fusion_text_input)
lf_conv_1d = keras.layers.Conv1D(filters=200, kernel_size=7, activation='relu')(lf_embeddings)
lf_global_pooling = keras.layers.GlobalMaxPool1D()(lf_conv_1d)
lf_flatten = keras.layers.Flatten()(lf_global_pooling)
lf_dense_layer = keras.layers.Dense(
50, activation='relu', kernel_regularizer=keras.regularizers.l2(0.5)
)(lf_flatten)
lf_text_features = keras.layers.Dropout(0.3)(lf_dense_layer)
lf_conv_2d_1 = keras.layers.TimeDistributed(
keras.layers.Conv2D(20, 7, activation='relu', padding='same')
)(image_input)
lf_pool_2d_1 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(lf_conv_2d_1)
lf_conv_2d_2 = keras.layers.TimeDistributed(
keras.layers.Conv2D(50, 5, activation='relu', padding='valid')
)(lf_pool_2d_1)
lf_pool_2d_2 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(lf_conv_2d_2)
image_features = keras.layers.TimeDistributed(keras.layers.Flatten())(lf_pool_2d_2)
lf_lstm_1 = keras.layers.LSTM(1000, return_sequences=True)(image_features)
lf_image_features = keras.layers.LSTM(1000, dropout=0.5)(lf_lstm_1)
lf_merge_features = keras.layers.concatenate([lf_text_features, lf_image_features])
late_fusion_features = keras.layers.Flatten()(lf_merge_features)
ef_embeddings = keras.layers.TimeDistributed(
keras.layers.Embedding(vocab_length, 150, input_length=2000),
name='word_embeddings'
)(early_fusion_text_input)
ef_conv_1d = keras.layers.TimeDistributed(
keras.layers.Conv1D(filters=200, kernel_size=7, activation='relu'),
name='1d_convolutional_layer'
)(ef_embeddings)
ef_global_pooling = keras.layers.TimeDistributed(
keras.layers.GlobalMaxPool1D(),
name='max_pooling_layer'
)(ef_conv_1d)
ef_text_features = keras.layers.TimeDistributed(keras.layers.Flatten(), name='text_features')(ef_global_pooling)
ef_conv_2d_1 = keras.layers.TimeDistributed(
keras.layers.Conv2D(20, 7, activation='relu', padding='same')
)(image_input)
ef_pool_2d_1 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(ef_conv_2d_1)
ef_conv_2d_2 = keras.layers.TimeDistributed(keras.layers.Conv2D(50, 5, activation='relu', padding='valid'))(
ef_pool_2d_1)
ef_pool_2d_2 = keras.layers.TimeDistributed(keras.layers.MaxPooling2D(4))(ef_conv_2d_2)
ef_image_features = keras.layers.TimeDistributed(keras.layers.Flatten())(ef_pool_2d_2)
ef_joint_features = keras.layers.concatenate([ef_text_features, ef_image_features])
ef_lstm_1 = keras.layers.LSTM(450, return_sequences=True)(ef_joint_features)
ef_lstm_2 = keras.layers.LSTM(1000)(ef_lstm_1)
early_fusion_features = keras.layers.Dropout(0.5)(ef_lstm_2)
hybrid_representation = keras.layers.concatenate([late_fusion_features, early_fusion_features])
output = keras.layers.Dense(6, activation='softmax')(hybrid_representation)
model = keras.models.Model(inputs=[late_fusion_text_input, early_fusion_text_input, image_input], outputs=[output])
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
return model
| 46.406061
| 120
| 0.738932
| 1,022
| 7,657
| 5.262231
| 0.097847
| 0.192265
| 0.135366
| 0.161398
| 0.811454
| 0.753998
| 0.741726
| 0.697843
| 0.625511
| 0.565638
| 0
| 0.04474
| 0.135954
| 7,657
| 164
| 121
| 46.689024
| 0.768138
| 0.056158
| 0
| 0.211009
| 0
| 0
| 0.067507
| 0.029132
| 0
| 0
| 0
| 0
| 0
| 1
| 0.027523
| false
| 0
| 0.009174
| 0
| 0.06422
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
6db31f114976a2e95553fdec3149a350efd4531f
| 68
|
py
|
Python
|
fishy_data/definitions.py
|
tlancaster6/fishy_data
|
089abf2d3e50d6366095b7562b335e120dec2ad1
|
[
"MIT"
] | null | null | null |
fishy_data/definitions.py
|
tlancaster6/fishy_data
|
089abf2d3e50d6366095b7562b335e120dec2ad1
|
[
"MIT"
] | null | null | null |
fishy_data/definitions.py
|
tlancaster6/fishy_data
|
089abf2d3e50d6366095b7562b335e120dec2ad1
|
[
"MIT"
] | null | null | null |
import os
PACKAGE_DIR = os.path.dirname(os.path.abspath(__file__))
| 17
| 56
| 0.779412
| 11
| 68
| 4.363636
| 0.727273
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.088235
| 68
| 3
| 57
| 22.666667
| 0.774194
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
6dc97dfc0a1fa6062e499d8fb547e157be2bc4d6
| 6,873
|
py
|
Python
|
src/tests/test_tasks.py
|
DmitryBurnaev/podcast
|
48c7c60e2a46378f36635dc58222e5e7682f977f
|
[
"MIT"
] | 1
|
2020-09-05T10:37:55.000Z
|
2020-09-05T10:37:55.000Z
|
src/tests/test_tasks.py
|
DmitryBurnaev/podcast
|
48c7c60e2a46378f36635dc58222e5e7682f977f
|
[
"MIT"
] | null | null | null |
src/tests/test_tasks.py
|
DmitryBurnaev/podcast
|
48c7c60e2a46378f36635dc58222e5e7682f977f
|
[
"MIT"
] | null | null | null |
import os
from datetime import datetime
from unittest.mock import patch, Mock
import settings
from modules.podcast.models import Episode
from modules.podcast.tasks import (
generate_rss,
download_episode,
EPISODE_DOWNLOADING_IGNORED,
EPISODE_DOWNLOADING_OK,
EPISODE_DOWNLOADING_ERROR,
)
from modules.youtube.exceptions import YoutubeException
from .conftest import generate_video_id, db_allow_sync
from .mocks import MockYoutube, MockS3Client
@db_allow_sync
def test_generate_rss__ok(db_objects, podcast, episode_data, mocked_s3):
new_episode_data = {
**episode_data,
**{"source_id": generate_video_id(), "status": "new"},
}
episode_new: Episode = Episode.create(**new_episode_data)
new_episode_data = {
**episode_data,
**{"source_id": generate_video_id(), "status": "downloading"},
}
episode_downloading: Episode = Episode.create(**new_episode_data)
new_episode_data = {
**episode_data,
**{
"source_id": generate_video_id(),
"status": "published",
"published_at": datetime.utcnow(),
},
}
episode_published: Episode = Episode.create(**new_episode_data)
rss_path = generate_rss(podcast.id)
mocked_s3.upload_file.assert_called_with(
rss_path, f"{podcast.publish_id}.xml", remote_path=settings.S3_BUCKET_RSS_PATH
)
with open(rss_path) as file:
generated_rss_content = file.read()
assert episode_published.title in generated_rss_content
assert episode_published.description in generated_rss_content
assert episode_published.file_name in generated_rss_content
assert episode_new.source_id not in generated_rss_content
assert episode_downloading.source_id not in generated_rss_content
os.remove(rss_path)
@db_allow_sync
@patch("modules.podcast.tasks.podcast_utils.render_rss_to_file")
def test_download_sound__episode_downloaded__file_correct__ignore_downloading__ok(
generate_rss_mock,
db_objects,
podcast,
episode_data,
mocked_youtube: MockYoutube,
mocked_s3: MockS3Client,
):
new_episode_data = {
**episode_data,
**{
"status": "published",
"source_id": mocked_youtube.video_id,
"watch_url": mocked_youtube.watch_url,
"file_size": 1024,
},
}
episode: Episode = Episode.create(**new_episode_data)
mocked_s3.get_file_size.return_value = episode.file_size
generate_rss_mock.return_value = f"file_{episode.source_id}.mp3"
result = download_episode(episode.watch_url, episode.id)
with db_objects.allow_sync():
updated_episode: Episode = Episode.select().where(Episode.id == episode.id).first()
generate_rss_mock.assert_called_with(episode.podcast_id)
assert result == EPISODE_DOWNLOADING_IGNORED
assert not mocked_youtube.download.called
assert updated_episode.status == "published"
assert updated_episode.published_at == updated_episode.created_at
@db_allow_sync
@patch("modules.podcast.tasks.podcast_utils.render_rss_to_file")
@patch("modules.podcast.tasks.youtube_utils.download_audio")
def test_download_sound__episode_new__correct_downloading(
download_audio_mock,
generate_rss_mock,
db_objects,
podcast,
episode_data,
mocked_youtube: MockYoutube,
mocked_s3: MockS3Client,
mocked_ffmpeg: Mock,
):
new_episode_data = {
**episode_data,
**{
"status": "new",
"source_id": mocked_youtube.video_id,
"watch_url": mocked_youtube.watch_url,
"file_size": 1024,
},
}
episode: Episode = Episode.create(**new_episode_data)
download_audio_mock.return_value = episode.file_name
generate_rss_mock.return_value = f"file_{episode.source_id}.mp3"
result = download_episode(episode.watch_url, episode.id)
with db_objects.allow_sync():
updated_episode: Episode = Episode.select().where(Episode.id == episode.id).first()
generate_rss_mock.assert_called_with(episode.podcast_id)
download_audio_mock.assert_called_with(episode.watch_url, episode.file_name)
mocked_ffmpeg.assert_called_with(episode.file_name)
assert result == EPISODE_DOWNLOADING_OK
assert updated_episode.status == "published"
assert updated_episode.published_at == updated_episode.created_at
@db_allow_sync
@patch("modules.podcast.tasks.podcast_utils.render_rss_to_file")
@patch("modules.podcast.tasks.youtube_utils.download_audio")
def test_download_sound__episode_downloaded__file_incorrect__reload(
download_audio_mock,
generate_rss_mock,
db_objects,
podcast,
episode_data,
mocked_youtube: MockYoutube,
mocked_s3: MockS3Client,
mocked_ffmpeg: Mock,
):
new_episode_data = {
**episode_data,
**{
"status": "published",
"source_id": mocked_youtube.video_id,
"watch_url": mocked_youtube.watch_url,
"file_size": 1024,
},
}
episode: Episode = Episode.create(**new_episode_data)
download_audio_mock.return_value = episode.file_name
generate_rss_mock.return_value = f"file_{episode.source_id}.mp3"
mocked_s3.get_file_size.return_value = 32
result = download_episode(episode.watch_url, episode.id)
with db_objects.allow_sync():
updated_episode: Episode = Episode.select().where(Episode.id == episode.id).first()
generate_rss_mock.assert_called_with(episode.podcast_id)
download_audio_mock.assert_called_with(episode.watch_url, episode.file_name)
mocked_ffmpeg.assert_called_with(episode.file_name)
assert result == EPISODE_DOWNLOADING_OK
assert updated_episode.status == "published"
assert updated_episode.published_at == updated_episode.created_at
@db_allow_sync
@patch("modules.podcast.tasks.youtube_utils.download_audio")
def test_download_sound__youtube_exception__download_rollback(
download_audio_mock,
db_objects,
podcast,
episode_data,
mocked_youtube: MockYoutube,
mocked_s3: MockS3Client,
):
new_episode_data = {
**episode_data,
**{
"status": "new",
"source_id": mocked_youtube.video_id,
"watch_url": mocked_youtube.watch_url,
"file_size": 1024,
},
}
episode: Episode = Episode.create(**new_episode_data)
download_audio_mock.side_effect = YoutubeException("Youtube video is not available")
result = download_episode(episode.watch_url, episode.id)
with db_objects.allow_sync():
updated_episode: Episode = Episode.select().where(Episode.id == episode.id).first()
download_audio_mock.assert_called_with(episode.watch_url, episode.file_name)
assert result == EPISODE_DOWNLOADING_ERROR
assert updated_episode.status == "new"
assert updated_episode.published_at is None
| 32.57346
| 91
| 0.722537
| 843
| 6,873
| 5.476868
| 0.118624
| 0.061945
| 0.042452
| 0.039853
| 0.777128
| 0.770414
| 0.745722
| 0.681828
| 0.681828
| 0.681828
| 0
| 0.006246
| 0.184636
| 6,873
| 210
| 92
| 32.728571
| 0.81763
| 0
| 0
| 0.662857
| 1
| 0
| 0.104176
| 0.061109
| 0
| 0
| 0
| 0
| 0.154286
| 1
| 0.028571
| false
| 0
| 0.051429
| 0
| 0.08
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
6dd1f89478019b0b25181a05e7e15f79d9ecc96b
| 459
|
py
|
Python
|
src/screen_tools.py
|
mherreradsci/virtualpiano
|
7d90e6cb6f186dad1fe326e4a06d64909530ae61
|
[
"MIT"
] | 2
|
2021-11-27T20:46:31.000Z
|
2021-11-28T23:46:36.000Z
|
src/screen_tools.py
|
mherreradsci/virtualpiano
|
7d90e6cb6f186dad1fe326e4a06d64909530ae61
|
[
"MIT"
] | null | null | null |
src/screen_tools.py
|
mherreradsci/virtualpiano
|
7d90e6cb6f186dad1fe326e4a06d64909530ae61
|
[
"MIT"
] | 3
|
2021-11-05T15:38:21.000Z
|
2021-12-26T01:48:21.000Z
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 6 22:35:46 2021
@author: mherrera
"""
import pygame
class ScreenTools:
def __init__(self):
pygame.init()
self.infos = pygame.display.Info()
def current_widht(self):
return self.infos.current_w
def current_height(self):
return self.infos.current_h
def screen_size(self):
return (self.infos.current_w, self.infos.current_h)
| 19.125
| 59
| 0.640523
| 63
| 459
| 4.492063
| 0.571429
| 0.159011
| 0.226148
| 0.201413
| 0.282686
| 0.190813
| 0
| 0
| 0
| 0
| 0
| 0.037037
| 0.235294
| 459
| 23
| 60
| 19.956522
| 0.769231
| 0.213508
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.363636
| false
| 0
| 0.090909
| 0.272727
| 0.818182
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
6ddf0dda7a6c9a150aa3066dcafa93ea92f45635
| 110
|
py
|
Python
|
fybot/resources/context.py
|
juanlazarde/financial_scanner
|
a466aa553a413b65d08d4d23250867f938726e17
|
[
"Apache-2.0"
] | 2
|
2021-02-06T20:22:26.000Z
|
2021-02-23T04:51:05.000Z
|
fybot/resources/context.py
|
juanlazarde/fybot
|
a466aa553a413b65d08d4d23250867f938726e17
|
[
"Apache-2.0"
] | 9
|
2021-11-20T05:32:39.000Z
|
2021-12-16T06:34:41.000Z
|
fybot/resources/context.py
|
juanlazarde/financial_scanner
|
a466aa553a413b65d08d4d23250867f938726e17
|
[
"Apache-2.0"
] | 1
|
2021-08-29T23:01:09.000Z
|
2021-08-29T23:01:09.000Z
|
import os.path as path
import sys
sys.path.insert(0, path.abspath(path.join(path.dirname(__file__), '..')))
| 18.333333
| 73
| 0.718182
| 18
| 110
| 4.166667
| 0.611111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010101
| 0.1
| 110
| 5
| 74
| 22
| 0.747475
| 0
| 0
| 0
| 0
| 0
| 0.018349
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
6de268d1423a813e896311ac5cc068b1cf0b573b
| 102
|
py
|
Python
|
python/hello.py
|
AungWinnHtut/POL
|
ee8bdf655073134df8b8529ab0ece20e118b19e1
|
[
"MIT"
] | 2
|
2016-02-10T10:22:13.000Z
|
2020-01-19T09:49:28.000Z
|
python/hello.py
|
AungWinnHtut/POL
|
ee8bdf655073134df8b8529ab0ece20e118b19e1
|
[
"MIT"
] | null | null | null |
python/hello.py
|
AungWinnHtut/POL
|
ee8bdf655073134df8b8529ab0ece20e118b19e1
|
[
"MIT"
] | 1
|
2020-01-19T09:22:29.000Z
|
2020-01-19T09:22:29.000Z
|
print("hello world!");
print("I am Aung Win Htut");
input("press any key to continue");
print("bye!");
| 25.5
| 35
| 0.666667
| 17
| 102
| 4
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 102
| 4
| 36
| 25.5
| 0.755556
| 0
| 0
| 0
| 0
| 0
| 0.572816
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.75
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
6de4d2db3ce6e031f27a45eb4dbce3e562fa14bc
| 21
|
py
|
Python
|
Python/Projects/Python basic problems/prog1.py
|
Jatinkumar30/hacktoberfest2021
|
89747305f00ccde8b68b5db42e47ca878ccc0215
|
[
"MIT"
] | null | null | null |
Python/Projects/Python basic problems/prog1.py
|
Jatinkumar30/hacktoberfest2021
|
89747305f00ccde8b68b5db42e47ca878ccc0215
|
[
"MIT"
] | null | null | null |
Python/Projects/Python basic problems/prog1.py
|
Jatinkumar30/hacktoberfest2021
|
89747305f00ccde8b68b5db42e47ca878ccc0215
|
[
"MIT"
] | null | null | null |
add = 2+3
print(add)
| 10.5
| 10
| 0.619048
| 5
| 21
| 2.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 0.190476
| 21
| 2
| 11
| 10.5
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
6dea2dae4eab9c9073198d250576fbebb6d466cd
| 1,963
|
py
|
Python
|
scalpr/pipeline/candle_pipe.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | 1
|
2022-02-14T22:48:58.000Z
|
2022-02-14T22:48:58.000Z
|
scalpr/pipeline/candle_pipe.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | null | null | null |
scalpr/pipeline/candle_pipe.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | 1
|
2022-02-14T22:49:01.000Z
|
2022-02-14T22:49:01.000Z
|
import logging
from typing import Dict, List
from pydantic import ValidationError
from ..database.candle import Candle
from ..database.window import Window
from .pipe import Message, Pipe
class CandlePipe(Pipe):
def before(self, message: Message, window: Window) -> Window:
pass
def parse(self, payload: Dict) -> Candle:
try:
return Candle(
open_price =payload["o"],
close_price =payload["c"],
high_price =payload["h"],
low_price =payload["l"],
base_volume =payload["v"],
quote_volume =payload["q"],
base_volume_taker =payload["V"],
quote_volume_taker =payload["Q"],
n_trades =payload["n"],
)
except ValidationError as e:
logging.critical(e)
def validate(self, message: Message, window: Window) -> bool:
pass
def insert_in_previous_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
def insert_in_current_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
def insert_in_next_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
class HistoricalCandlePipe(Pipe):
def before(self, message: Message, window: Window) -> Window:
pass
def parse(self, payload: List) -> Candle:
pass
def validate(self, message: Message, window: Window) -> bool:
pass
def insert_in_first_timeframe(self, message: Message, window: Window) -> Window:
pass
def insert_in_previous_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
def insert_in_current_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
def insert_in_next_timeframe(self, parsed: Candle, window: Window) -> Window:
pass
| 24.234568
| 85
| 0.593989
| 213
| 1,963
| 5.323944
| 0.258216
| 0.21164
| 0.142857
| 0.174603
| 0.598765
| 0.598765
| 0.598765
| 0.598765
| 0.567019
| 0.567019
| 0
| 0
| 0.30973
| 1,963
| 80
| 86
| 24.5375
| 0.8369
| 0
| 0
| 0.468085
| 0
| 0
| 0.004587
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.276596
| false
| 0.255319
| 0.12766
| 0
| 0.468085
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
6df2b83f10686b1a6f660261e44d1dc490a2d9f0
| 1,100
|
py
|
Python
|
scraping/spider.py
|
EMUNES/all_news_titles
|
445507ef5c23477a6de2d759ba322b7b8588d106
|
[
"Apache-2.0"
] | 2
|
2020-09-24T14:37:22.000Z
|
2021-05-08T06:10:31.000Z
|
scraping/spider.py
|
EMUNES/all_news_titles
|
445507ef5c23477a6de2d759ba322b7b8588d106
|
[
"Apache-2.0"
] | null | null | null |
scraping/spider.py
|
EMUNES/all_news_titles
|
445507ef5c23477a6de2d759ba322b7b8588d106
|
[
"Apache-2.0"
] | null | null | null |
import sys
sys.path.append('.')
from scraping.websites import guanchaWorld
from scraping.websites import huanqiuWorld
from scraping.websites import thepaperShiShi
from scraping.websites import cankaoxiaoxiWorld
from scraping.websites import peopleWorld
from scraping.websites import qqWorld
from scraping.websites import news163World
from scraping.websites import sinaWorld
from scraping.utils.handler import PageHandler
'''Scraping news and return all data: [{}, {}, {}, {}]
1. title
2. link
3. date
TODO: category, id
'''
def pipeline():
sites = [cankaoxiaoxiWorld, thepaperShiShi, huanqiuWorld, guanchaWorld, peopleWorld, qqWorld, news163World, sinaWorld]
for site in sites:
# you must call a method to get its return value
try:
data = PageHandler(site).handlePage()
print(f'{site.websiteName}: {data}\n')
yield (site.websiteName, data)
except:
print(f'||| {site.websiteName} failing to scrape |||')
if __name__ == "__main__":
for data in pipeline():
print(data)
| 29.72973
| 123
| 0.683636
| 123
| 1,100
| 6.04878
| 0.487805
| 0.145161
| 0.215054
| 0.27957
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010526
| 0.222727
| 1,100
| 37
| 124
| 29.72973
| 0.859649
| 0.041818
| 0
| 0
| 0
| 0
| 0.088525
| 0
| 0
| 0
| 0
| 0.027027
| 0
| 1
| 0.043478
| false
| 0
| 0.434783
| 0
| 0.478261
| 0.130435
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
6df599dcd5762d74c3137cf587b4025e07d17321
| 249
|
py
|
Python
|
thgsp/utils/metrics.py
|
XuChanghhu/thgsp
|
f2e8c8d04432d0204a999aad3e555171ffd0d432
|
[
"BSD-3-Clause"
] | 1
|
2021-01-13T05:16:13.000Z
|
2021-01-13T05:16:13.000Z
|
thgsp/utils/metrics.py
|
XuChanghhu/thgsp
|
f2e8c8d04432d0204a999aad3e555171ffd0d432
|
[
"BSD-3-Clause"
] | null | null | null |
thgsp/utils/metrics.py
|
XuChanghhu/thgsp
|
f2e8c8d04432d0204a999aad3e555171ffd0d432
|
[
"BSD-3-Clause"
] | null | null | null |
def mse(x, target):
n = max(x.numel(), target.numel())
return (x - target).pow(2).sum() / n
def snr(x, target):
noise = (x - target).pow(2).sum()
signal = target.pow(2).sum()
SNR = 10 * (signal / noise).log10_()
return SNR
| 22.636364
| 40
| 0.550201
| 39
| 249
| 3.487179
| 0.410256
| 0.205882
| 0.220588
| 0.286765
| 0.205882
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036842
| 0.236948
| 249
| 10
| 41
| 24.9
| 0.678947
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
0980cf850f6398b3ecceca2ae6539f7e8fef40b1
| 162
|
py
|
Python
|
app/business/account.py
|
gerenciagram/apistar-boilerplate
|
6b24b6e5dc2cd7f4fc046950eeef29613aee451f
|
[
"MIT"
] | 1
|
2018-11-25T14:30:21.000Z
|
2018-11-25T14:30:21.000Z
|
app/business/account.py
|
gerenciagram/python-web-api-boilerplate
|
6b24b6e5dc2cd7f4fc046950eeef29613aee451f
|
[
"MIT"
] | null | null | null |
app/business/account.py
|
gerenciagram/python-web-api-boilerplate
|
6b24b6e5dc2cd7f4fc046950eeef29613aee451f
|
[
"MIT"
] | null | null | null |
def get_account(account_id: int):
return {
'account_id': 1,
'email': 'noreply@gerenciagram.com',
'first_name': 'Gerenciagram'
}
| 18
| 44
| 0.574074
| 17
| 162
| 5.235294
| 0.764706
| 0.202247
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008621
| 0.283951
| 162
| 8
| 45
| 20.25
| 0.758621
| 0
| 0
| 0
| 0
| 0
| 0.38125
| 0.15
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0
| 0.166667
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
09a533da88f06f12bc3964d484f00fbd4280ac0c
| 1,957
|
py
|
Python
|
test/test_teams_api.py
|
bombbomb/bombbomb-python-openapi
|
d1623cb06e58fdc83b04603a589e9d30e7eb3fdf
|
[
"Apache-2.0"
] | null | null | null |
test/test_teams_api.py
|
bombbomb/bombbomb-python-openapi
|
d1623cb06e58fdc83b04603a589e9d30e7eb3fdf
|
[
"Apache-2.0"
] | null | null | null |
test/test_teams_api.py
|
bombbomb/bombbomb-python-openapi
|
d1623cb06e58fdc83b04603a589e9d30e7eb3fdf
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
BombBomb
We make it easy to build relationships using simple videos.
OpenAPI spec version: 2.0.20679
Generated by: https://github.com/swagger-api/swagger-codegen.git
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.
"""
from __future__ import absolute_import
import os
import sys
import unittest
import bombbomb
from bombbomb.rest import ApiException
from bombbomb.apis.teams_api import TeamsApi
class TestTeamsApi(unittest.TestCase):
""" TeamsApi unit test stubs """
def setUp(self):
self.api = bombbomb.apis.teams_api.TeamsApi()
def tearDown(self):
pass
def test_cancel_jericho_send(self):
"""
Test case for cancel_jericho_send
Cancel a Jericho Send
"""
pass
def test_get_client_group_assets(self):
"""
Test case for get_client_group_assets
Lists team assets
"""
pass
def test_get_jericho_sends(self):
"""
Test case for get_jericho_sends
List Jericho Sends
"""
pass
def test_get_jericho_stats(self):
"""
Test case for get_jericho_stats
Gets Jericho performance statistics
"""
pass
def test_queue_jericho_send(self):
"""
Test case for queue_jericho_send
Creates a Jericho send.
"""
pass
if __name__ == '__main__':
unittest.main()
| 22.238636
| 76
| 0.657639
| 253
| 1,957
| 4.920949
| 0.501976
| 0.048193
| 0.044177
| 0.060241
| 0.13012
| 0.081928
| 0
| 0
| 0
| 0
| 0
| 0.008487
| 0.277466
| 1,957
| 87
| 77
| 22.494253
| 0.871994
| 0.524783
| 0
| 0.25
| 1
| 0
| 0.011348
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.291667
| false
| 0.25
| 0.291667
| 0
| 0.625
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
09b9b1d372e427fd63651a309ecac47c9c1a97d5
| 232
|
py
|
Python
|
tests/core/endpoints/test_import_raw_key.py
|
cducrest/eth-tester-rpc
|
f34dcce2b4110010e3b54531a5cd8add4df43beb
|
[
"MIT"
] | 3
|
2018-08-09T08:33:30.000Z
|
2021-10-06T15:05:57.000Z
|
tests/core/endpoints/test_import_raw_key.py
|
cducrest/eth-tester-rpc
|
f34dcce2b4110010e3b54531a5cd8add4df43beb
|
[
"MIT"
] | 11
|
2018-09-15T18:58:24.000Z
|
2020-11-30T17:00:46.000Z
|
tests/core/endpoints/test_import_raw_key.py
|
cducrest/eth-tester-rpc
|
f34dcce2b4110010e3b54531a5cd8add4df43beb
|
[
"MIT"
] | 3
|
2018-09-24T13:47:23.000Z
|
2020-11-25T16:39:08.000Z
|
from eth_account import (
Account,
)
def test_import_raw_key(rpc_client):
account = Account.create()
result = rpc_client('personal_importRawKey', params=[account.privateKey.hex()])
assert result == account.address
| 23.2
| 83
| 0.728448
| 28
| 232
| 5.785714
| 0.678571
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.159483
| 232
| 9
| 84
| 25.777778
| 0.830769
| 0
| 0
| 0
| 0
| 0
| 0.090517
| 0.090517
| 0
| 0
| 0
| 0
| 0.142857
| 1
| 0.142857
| false
| 0
| 0.428571
| 0
| 0.571429
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
09c7ef09e76efc3ee7a6a7598d8811a847fd823a
| 53
|
py
|
Python
|
apps/gsuite/models.py
|
Kpaubert/onlineweb4
|
9ac79f163bc3a816db57ffa8477ea88770d97807
|
[
"MIT"
] | 32
|
2017-02-22T13:38:38.000Z
|
2022-03-31T23:29:54.000Z
|
apps/gsuite/models.py
|
Kpaubert/onlineweb4
|
9ac79f163bc3a816db57ffa8477ea88770d97807
|
[
"MIT"
] | 694
|
2017-02-15T23:09:52.000Z
|
2022-03-31T23:16:07.000Z
|
apps/gsuite/models.py
|
Kpaubert/onlineweb4
|
9ac79f163bc3a816db57ffa8477ea88770d97807
|
[
"MIT"
] | 35
|
2017-09-02T21:13:09.000Z
|
2022-02-21T11:30:30.000Z
|
# Kept since Django requires models.py to load apps.
| 26.5
| 52
| 0.773585
| 9
| 53
| 4.555556
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.169811
| 53
| 1
| 53
| 53
| 0.931818
| 0.943396
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
09cbee74087caa2dfb2d3f019614e5499a80fafb
| 14,214
|
py
|
Python
|
tests/test_issuer.py
|
dajiaji/flask-paseto-extended
|
3174c1ca5c3c1ad78d56951d7728e7e5a6e8d9f7
|
[
"MIT"
] | 4
|
2021-11-24T13:32:59.000Z
|
2022-03-20T06:16:53.000Z
|
tests/test_issuer.py
|
dajiaji/flask-paseto-extended
|
3174c1ca5c3c1ad78d56951d7728e7e5a6e8d9f7
|
[
"MIT"
] | 26
|
2021-10-23T00:33:40.000Z
|
2022-03-24T21:36:22.000Z
|
tests/test_issuer.py
|
dajiaji/flask-paseto-extended
|
3174c1ca5c3c1ad78d56951d7728e7e5a6e8d9f7
|
[
"MIT"
] | null | null | null |
# flake8: noqa: E501
import json
import flask
import pyseto
import pytest
from pyseto import Key
from flask_paseto_extended import EncodeError, PasetoIssuer
class TestPasetoIssuer:
"""
Tests for PasetoIssuer.
"""
def test_issuer(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_USE_ISS"] = False
app.config["PASETO_USE_IAT"] = True
app.config["PASETO_EXP"] = 3600
app.config["PASETO_USE_KID"] = True
app.config["PASETO_SERIALIZER"] = json
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer(app)
assert hasattr(issuer, "issue")
assert callable(issuer.issue)
token = issuer.issue({"key": "value"})
assert isinstance(token, bytes)
key = Key.new(
4,
"public",
"-----BEGIN PUBLIC KEY-----\nMCowBQYDK2VwAyEAHrnbu7wEfAP9cGBOAHHwmH4Wsot1ciXBHwBBXQ4gsaI=\n-----END PUBLIC KEY-----",
)
decoded = pyseto.decode(key, token, deserializer=json)
assert "kid" in decoded.footer
def test_issuer_with_mandatory_configs(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer(app)
assert hasattr(issuer, "issue")
assert callable(issuer.issue)
def test_issuer_init_app(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer()
issuer.init_app(app)
assert hasattr(issuer, "issue")
assert callable(issuer.issue)
def test_issuer_with_multiple_keys(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEIGmfHRcqkCfnAOB7234NNeuBpHUVHSLX4z3s4hsaTEQ8\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer(app)
assert hasattr(issuer, "issue")
assert callable(issuer.issue)
def test_issuer_init_app_with_paserk(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"paserk": "k4.secret.cHFyc3R1dnd4eXp7fH1-f4CBgoOEhYaHiImKi4yNjo8c5WpIyC_5kWKhS8VEYSZ05dYfuTF-ZdQFV4D9vLTcNQ",
},
]
issuer = PasetoIssuer()
issuer.init_app(app)
assert hasattr(issuer, "issue")
def test_issuer_init_app_with_multiple_paserks(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"paserk": "k4.secret.cHFyc3R1dnd4eXp7fH1-f4CBgoOEhYaHiImKi4yNjo8c5WpIyC_5kWKhS8VEYSZ05dYfuTF-ZdQFV4D9vLTcNQ",
},
{
"paserk": "k3.secret.cHFyc3R1dnd4eXp7fH1-f4CBgoOEhYaHiImKi4yNjo-QkZKTlJWWl5iZmpucnZ6f",
},
]
issuer = PasetoIssuer()
issuer.init_app(app)
assert hasattr(issuer, "issue")
@pytest.mark.parametrize(
"iss, msg",
[
(None, "PASETO_ISS must be set."),
("", "PASETO_ISS must be set."),
(0, "PASETO_ISS must be set."),
(1, "PASETO_ISS must be str."),
(["https://issuer.example"], "PASETO_ISS must be str."),
({"iss": "https://issuer.example"}, "PASETO_ISS must be str."),
],
)
def test_issuer_with_invalid_iss(self, iss, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = iss
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"use_iss, msg",
[
(None, "PASETO_USE_ISS must be bool."),
("", "PASETO_USE_ISS must be bool."),
(b"True", "PASETO_USE_ISS must be bool."),
("True", "PASETO_USE_ISS must be bool."),
(b"False", "PASETO_USE_ISS must be bool."),
("False", "PASETO_USE_ISS must be bool."),
([True], "PASETO_USE_ISS must be bool."),
({"value": True}, "PASETO_USE_ISS must be bool."),
(100, "PASETO_USE_ISS must be bool."),
],
)
def test_issuer_with_invalid_use_iss(self, use_iss, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_USE_ISS"] = use_iss
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"use_iat, msg",
[
(None, "PASETO_USE_IAT must be bool."),
("", "PASETO_USE_IAT must be bool."),
(b"True", "PASETO_USE_IAT must be bool."),
("True", "PASETO_USE_IAT must be bool."),
(b"False", "PASETO_USE_IAT must be bool."),
("False", "PASETO_USE_IAT must be bool."),
([True], "PASETO_USE_IAT must be bool."),
({"value": True}, "PASETO_USE_IAT must be bool."),
(100, "PASETO_USE_IAT must be bool."),
],
)
def test_issuer_with_invalid_use_iat(self, use_iat, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_USE_IAT"] = use_iat
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"exp, msg",
[
(-1, "PASETO_EXP must be int (>= 0)."),
(-3600, "PASETO_EXP must be int (>= 0)."),
("3600", "PASETO_EXP must be int (>= 0)."),
([3600], "PASETO_EXP must be int (>= 0)."),
({"value": 3600}, "PASETO_EXP must be int (>= 0)."),
],
)
def test_issuer_with_invalid_exp(self, exp, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_EXP"] = exp
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"use_kid, msg",
[
(None, "PASETO_USE_KID must be bool."),
("", "PASETO_USE_KID must be bool."),
(b"True", "PASETO_USE_KID must be bool."),
("True", "PASETO_USE_KID must be bool."),
(b"False", "PASETO_USE_KID must be bool."),
("False", "PASETO_USE_KID must be bool."),
([True], "PASETO_USE_KID must be bool."),
({"value": True}, "PASETO_USE_KID must be bool."),
(100, "PASETO_USE_KID must be bool."),
],
)
def test_issuer_with_invalid_use_kid(self, use_kid, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_USE_KID"] = use_kid
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"serializer, msg",
[
(1, "PASETO_SERIALIZER must have a callable 'dumps'."),
("string", "PASETO_SERIALIZER must have a callable 'dumps'."),
({"dumps": ""}, "PASETO_SERIALIZER must have a callable 'dumps'."),
],
)
def test_issuer_with_invalid_serializer(self, serializer, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_SERIALIZER"] = serializer
app.config["PASETO_PRIVATE_KEYS"] = [
{
"iss": "https://issuer.exmaple",
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
@pytest.mark.parametrize(
"keys, msg",
[
([], "PASETO_PRIVATE_KEYS must be set."),
(
[{}],
"A key object must have a 'paserk' or a pair of 'version' and 'key'.",
),
(
[{"paserk": "k4.secret.xxx"}],
"Invalid PASERK data.",
),
(
[{"paserk": "k4.local.b3VyLXNlY3JldA"}],
"A local key is not allowed.",
),
(
[{"version": "xxx"}],
"A 'version' in PASETO_PRIVATE_KEYS must be int.",
),
(
[{"version": 0}],
"Invalid PASETO version: 0.",
),
(
[{"version": 4}],
"A key object must have a 'paserk' or a pair of 'version' and 'key'.",
),
(
[{"version": 4, "key": "xxx"}],
"A 'key' must be a PEM formatted key.",
),
],
)
def test_issuer_with_invalid_keys(self, keys, msg):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = keys
with pytest.raises(ValueError) as err:
PasetoIssuer(app)
pytest.fail("init_app() must fail.")
assert msg in str(err.value)
def test_issuer_issue_with_bad_kid(self):
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEIGmfHRcqkCfnAOB7234NNeuBpHUVHSLX4z3s4hsaTEQ8\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer(app)
with pytest.raises(ValueError) as err:
issuer.issue(
{"foo": "bar"},
kid="k3.pid.gnwg7IkzZyQF9wJgLLT0OpbdMT7BYmdQoG2u-xXpeeHz",
)
pytest.fail("issue() must fail.")
assert "A signing key is not found." in str(err.value)
def test_issuer_issue_with_bad_serializer(self):
class _BadSerializer:
def dumps(*args, **kwargs):
raise NotImplementedError("Not implemented.")
app = flask.Flask(__name__)
app.config["PASETO_ISS"] = "https://issuer.example"
app.config["PASETO_SERIALIZER"] = _BadSerializer()
app.config["PASETO_PRIVATE_KEYS"] = [
{
"version": 4,
"key": "-----BEGIN PRIVATE KEY-----\nMC4CAQAwBQYDK2VwBCIEILTL+0PfTOIQcn2VPkpxMwf6Gbt9n4UEFDjZ4RuUKjd0\n-----END PRIVATE KEY-----",
},
]
issuer = PasetoIssuer(app)
with pytest.raises(EncodeError) as err:
issuer.issue({"foo": "bar"})
pytest.fail("issue() must fail.")
assert "Failed to encode a token." in str(err.value)
| 37.405263
| 146
| 0.539398
| 1,398
| 14,214
| 5.281831
| 0.095851
| 0.049973
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| 14,214
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| 147
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|
0
| 4
|
09de8efe628bbfd2fd28b5927b2e7d8058e6ecfe
| 7,860
|
py
|
Python
|
nova/tests/unit/fake_server_actions.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/fake_server_actions.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/fake_server_actions.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | 2
|
2017-07-20T17:31:34.000Z
|
2020-07-24T02:42:19.000Z
|
begin_unit
comment|'# Copyright 2013 OpenStack Foundation'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n'
comment|'# a copy of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT'
nl|'\n'
comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the'
nl|'\n'
comment|'# License for the specific language governing permissions and limitations'
nl|'\n'
comment|'# under the License.'
nl|'\n'
nl|'\n'
name|'import'
name|'datetime'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
name|'import'
name|'db'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|FAKE_UUID
name|'FAKE_UUID'
op|'='
string|"'b48316c5-71e8-45e4-9884-6c78055b9b13'"
newline|'\n'
DECL|variable|FAKE_REQUEST_ID1
name|'FAKE_REQUEST_ID1'
op|'='
string|"'req-3293a3f1-b44c-4609-b8d2-d81b105636b8'"
newline|'\n'
DECL|variable|FAKE_REQUEST_ID2
name|'FAKE_REQUEST_ID2'
op|'='
string|"'req-25517360-b757-47d3-be45-0e8d2a01b36a'"
newline|'\n'
DECL|variable|FAKE_ACTION_ID1
name|'FAKE_ACTION_ID1'
op|'='
number|'123'
newline|'\n'
DECL|variable|FAKE_ACTION_ID2
name|'FAKE_ACTION_ID2'
op|'='
number|'456'
newline|'\n'
nl|'\n'
DECL|variable|FAKE_ACTIONS
name|'FAKE_ACTIONS'
op|'='
op|'{'
nl|'\n'
name|'FAKE_UUID'
op|':'
op|'{'
nl|'\n'
name|'FAKE_REQUEST_ID1'
op|':'
op|'{'
string|"'id'"
op|':'
name|'FAKE_ACTION_ID1'
op|','
nl|'\n'
string|"'action'"
op|':'
string|"'reboot'"
op|','
nl|'\n'
string|"'instance_uuid'"
op|':'
name|'FAKE_UUID'
op|','
nl|'\n'
string|"'request_id'"
op|':'
name|'FAKE_REQUEST_ID1'
op|','
nl|'\n'
string|"'project_id'"
op|':'
string|"'147'"
op|','
nl|'\n'
string|"'user_id'"
op|':'
string|"'789'"
op|','
nl|'\n'
string|"'start_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'0'
op|','
number|'0'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'finish_time'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'message'"
op|':'
string|"''"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted'"
op|':'
name|'False'
op|','
nl|'\n'
op|'}'
op|','
nl|'\n'
name|'FAKE_REQUEST_ID2'
op|':'
op|'{'
string|"'id'"
op|':'
name|'FAKE_ACTION_ID2'
op|','
nl|'\n'
string|"'action'"
op|':'
string|"'resize'"
op|','
nl|'\n'
string|"'instance_uuid'"
op|':'
name|'FAKE_UUID'
op|','
nl|'\n'
string|"'request_id'"
op|':'
name|'FAKE_REQUEST_ID2'
op|','
nl|'\n'
string|"'user_id'"
op|':'
string|"'789'"
op|','
nl|'\n'
string|"'project_id'"
op|':'
string|"'842'"
op|','
nl|'\n'
string|"'start_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'1'
op|','
number|'0'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'finish_time'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'message'"
op|':'
string|"''"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted'"
op|':'
name|'False'
op|','
nl|'\n'
op|'}'
nl|'\n'
op|'}'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
DECL|variable|FAKE_EVENTS
name|'FAKE_EVENTS'
op|'='
op|'{'
nl|'\n'
name|'FAKE_ACTION_ID1'
op|':'
op|'['
op|'{'
string|"'id'"
op|':'
number|'1'
op|','
nl|'\n'
string|"'action_id'"
op|':'
name|'FAKE_ACTION_ID1'
op|','
nl|'\n'
string|"'event'"
op|':'
string|"'schedule'"
op|','
nl|'\n'
string|"'start_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'1'
op|','
number|'0'
op|','
number|'2'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'finish_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'1'
op|','
number|'2'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'result'"
op|':'
string|"'Success'"
op|','
nl|'\n'
string|"'traceback'"
op|':'
string|"''"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted'"
op|':'
name|'False'
op|','
nl|'\n'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'id'"
op|':'
number|'2'
op|','
nl|'\n'
string|"'action_id'"
op|':'
name|'FAKE_ACTION_ID1'
op|','
nl|'\n'
string|"'event'"
op|':'
string|"'compute_create'"
op|','
nl|'\n'
string|"'start_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'1'
op|','
number|'3'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'finish_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'1'
op|','
number|'4'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'result'"
op|':'
string|"'Success'"
op|','
nl|'\n'
string|"'traceback'"
op|':'
string|"''"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted'"
op|':'
name|'False'
op|','
nl|'\n'
op|'}'
nl|'\n'
op|']'
op|','
nl|'\n'
name|'FAKE_ACTION_ID2'
op|':'
op|'['
op|'{'
string|"'id'"
op|':'
number|'3'
op|','
nl|'\n'
string|"'action_id'"
op|':'
name|'FAKE_ACTION_ID2'
op|','
nl|'\n'
string|"'event'"
op|':'
string|"'schedule'"
op|','
nl|'\n'
string|"'start_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'3'
op|','
number|'0'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'finish_time'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
nl|'\n'
number|'2012'
op|','
number|'12'
op|','
number|'5'
op|','
number|'3'
op|','
number|'2'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'result'"
op|':'
string|"'Error'"
op|','
nl|'\n'
string|"'traceback'"
op|':'
string|"''"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted_at'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'deleted'"
op|':'
name|'False'
op|','
nl|'\n'
op|'}'
nl|'\n'
op|']'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_action_event_start
name|'def'
name|'fake_action_event_start'
op|'('
op|'*'
name|'args'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'FAKE_EVENTS'
op|'['
name|'FAKE_ACTION_ID1'
op|']'
op|'['
number|'0'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_action_event_finish
dedent|''
name|'def'
name|'fake_action_event_finish'
op|'('
op|'*'
name|'args'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'FAKE_EVENTS'
op|'['
name|'FAKE_ACTION_ID1'
op|']'
op|'['
number|'0'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|stub_out_action_events
dedent|''
name|'def'
name|'stub_out_action_events'
op|'('
name|'stubs'
op|')'
op|':'
newline|'\n'
indent|' '
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'db'
op|','
string|"'action_event_start'"
op|','
name|'fake_action_event_start'
op|')'
newline|'\n'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'db'
op|','
string|"'action_event_finish'"
op|','
name|'fake_action_event_finish'
op|')'
newline|'\n'
dedent|''
endmarker|''
end_unit
| 12.319749
| 88
| 0.586896
| 1,227
| 7,860
| 3.661777
| 0.122249
| 0.068774
| 0.086802
| 0.132206
| 0.78166
| 0.756065
| 0.679056
| 0.636768
| 0.622301
| 0.617627
| 0
| 0.029743
| 0.097455
| 7,860
| 637
| 89
| 12.339089
| 0.603609
| 0
| 0
| 0.935636
| 0
| 0
| 0.362468
| 0.032952
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.00314
| 0
| 0.00314
| 0
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| null | 0
| 0
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| 0
| 0
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| 1
| 0
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| 1
| 0
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| null | 0
| 0
| 0
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| 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
09f230bc4b45bdc0c405076a65ff17d430760ba0
| 62
|
py
|
Python
|
django_webrtc_chat/core/__init__.py
|
aibaq/django_webrtc_chat
|
2ef2bfb1d1b142e587d193628a0eedb0d24c84f5
|
[
"Unlicense",
"MIT"
] | 1
|
2018-12-18T13:53:55.000Z
|
2018-12-18T13:53:55.000Z
|
django_webrtc_chat/core/__init__.py
|
aibaq/django_webrtc_chat
|
2ef2bfb1d1b142e587d193628a0eedb0d24c84f5
|
[
"Unlicense",
"MIT"
] | 7
|
2020-02-11T23:28:10.000Z
|
2022-03-11T23:35:06.000Z
|
django_webrtc_chat/core/__init__.py
|
aibaq/django_webrtc_chat
|
2ef2bfb1d1b142e587d193628a0eedb0d24c84f5
|
[
"Unlicense",
"MIT"
] | 2
|
2021-01-03T03:36:43.000Z
|
2022-03-20T14:01:20.000Z
|
default_app_config = 'django_webrtc_chat.core.apps.CoreConfig'
| 62
| 62
| 0.870968
| 9
| 62
| 5.555556
| 1
| 0
| 0
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| 0
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| 0
| 0.032258
| 62
| 1
| 62
| 62
| 0.833333
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| 0
| 0.619048
| 0.619048
| 0
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| 1
| 0
| false
| 0
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| 0
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| 0
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| null | 0
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| 1
| 0
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| 0
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| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
110457b935edfb0cbaaf41bc3579a822025cbacf
| 140
|
py
|
Python
|
sphericalquadpy/lebedev/__init__.py
|
camminady/sphericalquadpy
|
0646547cc69e27de7ce36f4b519d4f420ef443e7
|
[
"MIT"
] | 1
|
2020-11-15T23:47:48.000Z
|
2020-11-15T23:47:48.000Z
|
ext/steffensCode/ext/sphericalquadpy/lebedev/__init__.py
|
ScSteffen/neuralEntropyComparison
|
b54a823db595cc84717954fa84a9fb0d2f52e7b1
|
[
"MIT"
] | 1
|
2019-04-09T08:38:21.000Z
|
2019-04-09T08:38:21.000Z
|
ext/steffensCode/ext/sphericalquadpy/lebedev/__init__.py
|
ScSteffen/neuralEntropyComparison
|
b54a823db595cc84717954fa84a9fb0d2f52e7b1
|
[
"MIT"
] | 1
|
2020-12-19T21:12:59.000Z
|
2020-12-19T21:12:59.000Z
|
# pylint: disable=C0111
from .lebedev import Lebedev
from .writtendict import lebedevdictionary
__all__ = ["Lebedev", "lebedevdictionary"]
| 23.333333
| 42
| 0.792857
| 14
| 140
| 7.642857
| 0.642857
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.032258
| 0.114286
| 140
| 5
| 43
| 28
| 0.830645
| 0.15
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| 0.205128
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| null | 0
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| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
11223d9a80e9b595cbe29736306b58732024349c
| 100
|
py
|
Python
|
Password_Hacker/exercises_2.py
|
ContrlR/Python-Learn
|
c806315b91ed4205bc88cd7a508f0f341f29ca56
|
[
"MIT"
] | null | null | null |
Password_Hacker/exercises_2.py
|
ContrlR/Python-Learn
|
c806315b91ed4205bc88cd7a508f0f341f29ca56
|
[
"MIT"
] | null | null | null |
Password_Hacker/exercises_2.py
|
ContrlR/Python-Learn
|
c806315b91ed4205bc88cd7a508f0f341f29ca56
|
[
"MIT"
] | null | null | null |
#!/bin/env python
# Jetbrains academy Password hacker project
# Below are exercises done in stage 2
| 25
| 43
| 0.78
| 15
| 100
| 5.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011905
| 0.16
| 100
| 3
| 44
| 33.333333
| 0.916667
| 0.94
| 0
| null | 0
| null | 0
| 0
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| 0
| 0
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| null | true
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| 0
| 0
| 0
| 0
|
0
| 4
|
1123b75e1516b3ba1f3ee7b99c9be445926ca187
| 93
|
py
|
Python
|
Unclassed/apps.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | 2
|
2021-11-04T01:51:11.000Z
|
2021-11-23T13:21:01.000Z
|
Unclassed/apps.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | null | null | null |
Unclassed/apps.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class UnclassedConfig(AppConfig):
name = 'Unclassed'
| 15.5
| 33
| 0.763441
| 10
| 93
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 93
| 5
| 34
| 18.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
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| 0
| 0
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| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
fef408de9494a745b7b80d5a3641cf3bb4ac70c3
| 54
|
py
|
Python
|
src/twitter_analysis_tools/bin/__init__.py
|
dmmolitor/twitter_analysis_tools
|
0599b6c1a5093ea2fb916d5fb05df92786ab6a61
|
[
"MIT"
] | 1
|
2020-05-03T18:02:16.000Z
|
2020-05-03T18:02:16.000Z
|
src/twitter_analysis_tools/bin/__init__.py
|
dmmolitor/twitter_analysis_tools
|
0599b6c1a5093ea2fb916d5fb05df92786ab6a61
|
[
"MIT"
] | null | null | null |
src/twitter_analysis_tools/bin/__init__.py
|
dmmolitor/twitter_analysis_tools
|
0599b6c1a5093ea2fb916d5fb05df92786ab6a61
|
[
"MIT"
] | 1
|
2020-05-03T18:01:22.000Z
|
2020-05-03T18:01:22.000Z
|
"""Bin scripts package for twitter_analysis_tools."""
| 27
| 53
| 0.777778
| 7
| 54
| 5.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.092593
| 54
| 1
| 54
| 54
| 0.816327
| 0.87037
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 1
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| 0
| 1
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3a161ac25e64a2e3566a4c548089386d34713a51
| 99
|
py
|
Python
|
base_app/treasurehunt/apps.py
|
aadityajo/ecell-oth-django
|
8006cb0793bfdf084b78df5514852665adba5588
|
[
"MIT"
] | 1
|
2021-07-07T19:44:49.000Z
|
2021-07-07T19:44:49.000Z
|
base_app/treasurehunt/apps.py
|
aadityajo/ecell-oth-django
|
8006cb0793bfdf084b78df5514852665adba5588
|
[
"MIT"
] | null | null | null |
base_app/treasurehunt/apps.py
|
aadityajo/ecell-oth-django
|
8006cb0793bfdf084b78df5514852665adba5588
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class TreasurehuntConfig(AppConfig):
name = 'treasurehunt'
| 16.5
| 36
| 0.777778
| 10
| 99
| 7.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.151515
| 99
| 5
| 37
| 19.8
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 0
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| 0
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| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
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| 1
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| null | 0
| 0
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| 0
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| 0
| 0
| 0
| 0
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| 1
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
3a2220a4741f623dbaa0417be2cf3df0f352b628
| 283
|
py
|
Python
|
backend-project/small_eod/administrative_units/serializers.py
|
WlodzimierzKorza/small_eod
|
027022bd71122a949a2787d0fb86518df80e48cd
|
[
"MIT"
] | null | null | null |
backend-project/small_eod/administrative_units/serializers.py
|
WlodzimierzKorza/small_eod
|
027022bd71122a949a2787d0fb86518df80e48cd
|
[
"MIT"
] | null | null | null |
backend-project/small_eod/administrative_units/serializers.py
|
WlodzimierzKorza/small_eod
|
027022bd71122a949a2787d0fb86518df80e48cd
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from .models import AdministrativeUnit
class AdministrativeUnitSerializer(serializers.ModelSerializer):
class Meta:
model = AdministrativeUnit
fields = ["id", "parent", "name", "category", "slug", "updated_on", "active"]
| 28.3
| 85
| 0.727915
| 26
| 283
| 7.846154
| 0.807692
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166078
| 283
| 9
| 86
| 31.444444
| 0.864407
| 0
| 0
| 0
| 0
| 0
| 0.141343
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
28ddc17115d295b1186fd4b9ce0b3424626158c8
| 215
|
py
|
Python
|
tests/unit/dependency/test_http.py
|
kaiogu/dvc
|
ffa8fe5888dbbb3d37b3874562f99fd77d4bbcb7
|
[
"Apache-2.0"
] | 3
|
2020-01-31T05:33:14.000Z
|
2021-05-20T08:19:25.000Z
|
tests/unit/dependency/test_http.py
|
kaiogu/dvc
|
ffa8fe5888dbbb3d37b3874562f99fd77d4bbcb7
|
[
"Apache-2.0"
] | null | null | null |
tests/unit/dependency/test_http.py
|
kaiogu/dvc
|
ffa8fe5888dbbb3d37b3874562f99fd77d4bbcb7
|
[
"Apache-2.0"
] | 1
|
2019-12-01T07:43:48.000Z
|
2019-12-01T07:43:48.000Z
|
from dvc.dependency.http import DependencyHTTP
from tests.unit.dependency.test_local import TestDependencyLOCAL
class TestDependencyHTTP(TestDependencyLOCAL):
def _get_cls(self):
return DependencyHTTP
| 26.875
| 64
| 0.818605
| 23
| 215
| 7.521739
| 0.782609
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130233
| 215
| 7
| 65
| 30.714286
| 0.925134
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 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
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| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
|
0
| 4
|
28ecc81f16ea168cb11d4f6ae3a98812a09d71db
| 301
|
py
|
Python
|
iceworm/trees/nodes/jinja.py
|
wrmsr0/iceworm
|
09431bb3cdc4f6796aafca41e37d42ebe0ddfeef
|
[
"BSD-3-Clause"
] | null | null | null |
iceworm/trees/nodes/jinja.py
|
wrmsr0/iceworm
|
09431bb3cdc4f6796aafca41e37d42ebe0ddfeef
|
[
"BSD-3-Clause"
] | 1
|
2021-01-19T14:29:19.000Z
|
2021-01-19T14:34:27.000Z
|
iceworm/trees/nodes/jinja.py
|
wrmsr0/iceworm
|
09431bb3cdc4f6796aafca41e37d42ebe0ddfeef
|
[
"BSD-3-Clause"
] | 1
|
2020-12-31T22:29:52.000Z
|
2020-12-31T22:29:52.000Z
|
from omnibus import lang
from .base import Expr
from .select import Relation
class Jinja(lang.Abstract):
pass
class JinjaExpr(Expr, Jinja):
text: str
class JinjaRelation(Relation, Jinja):
text: str
class InJinja(Expr, Jinja):
needle: Expr
text: str
not_: bool = False
| 13.086957
| 37
| 0.69103
| 40
| 301
| 5.175
| 0.525
| 0.101449
| 0.115942
| 0.164251
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.229236
| 301
| 22
| 38
| 13.681818
| 0.892241
| 0
| 0
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.076923
| 0.230769
| 0
| 0.923077
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
28f3a31971ae9f3f64baa5539faee60d3aa63768
| 3,881
|
py
|
Python
|
salts/migrations/0001_initial.py
|
qingduyu/OpsSystem
|
81ff199a85c1432801be6f626c45ddee6aab2f28
|
[
"MIT"
] | 1
|
2018-11-30T09:06:32.000Z
|
2018-11-30T09:06:32.000Z
|
salts/migrations/0001_initial.py
|
qingduyu/OpsSystem
|
81ff199a85c1432801be6f626c45ddee6aab2f28
|
[
"MIT"
] | null | null | null |
salts/migrations/0001_initial.py
|
qingduyu/OpsSystem
|
81ff199a85c1432801be6f626c45ddee6aab2f28
|
[
"MIT"
] | 1
|
2018-11-30T09:06:34.000Z
|
2018-11-30T09:06:34.000Z
|
# -*- coding: utf-8 -*-
# Generated by Django 1.9.5 on 2017-04-12 11:25
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AppDeployLogModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('user', models.CharField(max_length=50)),
('time', models.DateTimeField()),
('target', models.CharField(max_length=100)),
('application', models.CharField(max_length=100)),
('mapping', models.CharField(max_length=20)),
('success_hosts', models.CharField(max_length=500)),
('failed_hosts', models.CharField(max_length=500)),
('total', models.IntegerField()),
('log', models.TextField()),
('duration', models.CharField(max_length=500)),
],
options={
'db_table': 'ops_app_deploy_log',
},
),
migrations.CreateModel(
name='CmdRunLogModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('user', models.CharField(max_length=30)),
('time', models.DateTimeField()),
('target', models.CharField(max_length=100)),
('mapping', models.CharField(max_length=50)),
('cmd', models.CharField(max_length=500)),
('hosts', models.CharField(max_length=500)),
('total', models.IntegerField()),
],
options={
'db_table': 'ops_cmd_run_log',
},
),
migrations.CreateModel(
name='HostInfoModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('hostname', models.CharField(max_length=100)),
('ipaddress', models.CharField(max_length=200)),
('cpuinfo', models.CharField(max_length=50)),
('meminfo', models.CharField(max_length=50)),
('group', models.CharField(max_length=50)),
('osinfo', models.CharField(max_length=20)),
('area', models.CharField(max_length=100)),
('usage', models.CharField(max_length=200)),
],
options={
'db_table': 'ops_host_info',
},
),
migrations.CreateModel(
name='OnlineDeployModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('type', models.CharField(max_length=50)),
('version', models.CharField(max_length=50)),
('project', models.CharField(max_length=1000)),
('sql_name', models.CharField(max_length=1000)),
('create_time', models.DateTimeField()),
('modify_time', models.DateTimeField()),
('audit_time', models.DateTimeField()),
('publish_time', models.DateTimeField()),
('proposer', models.CharField(max_length=100)),
('auditor', models.CharField(max_length=100)),
('publisher', models.CharField(max_length=100)),
('status', models.CharField(max_length=100)),
('active', models.CharField(max_length=10)),
('comment', models.CharField(max_length=2000)),
],
options={
'db_table': 'ops_publish_record',
},
),
]
| 42.184783
| 114
| 0.531049
| 350
| 3,881
| 5.694286
| 0.294286
| 0.22579
| 0.270948
| 0.361264
| 0.603613
| 0.358756
| 0.342699
| 0.342699
| 0.342699
| 0.244857
| 0
| 0.037262
| 0.32234
| 3,881
| 91
| 115
| 42.648352
| 0.720532
| 0.017264
| 0
| 0.361446
| 1
| 0
| 0.116505
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.024096
| 0
| 0.072289
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e91fe20af337e1c8c8ec2f767b3ed84ba7512bbf
| 236
|
py
|
Python
|
rl/utils/__init__.py
|
awesome-archive/rl
|
7b6ce5b41c47394d0f68903fd675e47f68f28958
|
[
"MIT"
] | 98
|
2019-04-03T18:54:24.000Z
|
2021-07-14T05:39:07.000Z
|
rl/utils/__init__.py
|
EXYNOS-999/rl
|
ee6dd27bdbddd2cad32b85981a70a4db0e4cf1ee
|
[
"MIT"
] | 8
|
2019-04-10T10:54:27.000Z
|
2019-08-09T01:24:30.000Z
|
rl/utils/__init__.py
|
EXYNOS-999/rl
|
ee6dd27bdbddd2cad32b85981a70a4db0e4cf1ee
|
[
"MIT"
] | 24
|
2019-04-08T17:22:25.000Z
|
2021-06-19T08:43:02.000Z
|
__all__ = ['checkpoint', 'flags', 'logger', 'sys', 'tpu', 'utils', 'lr_schemes']
from .checkpoint import *
from .flags import *
from .logger import *
from .sys import *
from .tpu import *
from .utils import *
from .lr_schemes import *
| 23.6
| 80
| 0.682203
| 31
| 236
| 5
| 0.354839
| 0.387097
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161017
| 236
| 9
| 81
| 26.222222
| 0.782828
| 0
| 0
| 0
| 0
| 0
| 0.177966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.875
| 0
| 0.875
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
e93739429079e0996ec7c99c6aadefdf22678aaa
| 253
|
py
|
Python
|
CrackMe-1/keygen.py
|
arianizadi/ReverseEngineering
|
755ff446fcd0b8c3b6f6f52643ccc082345272fd
|
[
"MIT"
] | 4
|
2021-09-10T10:15:34.000Z
|
2021-12-06T17:35:33.000Z
|
CrackMe-1/keygen.py
|
arianizadi/ReverseEngineering
|
755ff446fcd0b8c3b6f6f52643ccc082345272fd
|
[
"MIT"
] | null | null | null |
CrackMe-1/keygen.py
|
arianizadi/ReverseEngineering
|
755ff446fcd0b8c3b6f6f52643ccc082345272fd
|
[
"MIT"
] | null | null | null |
import string
import random
finalKey = ""
significantChar = random.choice(string.ascii_letters)
finalKey += significantChar
for i in range(8):
finalKey += random.choice(string.ascii_letters)
finalKey += significantChar
print("Key -> " + finalKey)
| 21.083333
| 53
| 0.754941
| 29
| 253
| 6.517241
| 0.517241
| 0.365079
| 0.190476
| 0.243386
| 0.560847
| 0.560847
| 0.560847
| 0
| 0
| 0
| 0
| 0.004566
| 0.134387
| 253
| 11
| 54
| 23
| 0.858447
| 0
| 0
| 0.222222
| 0
| 0
| 0.027668
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.222222
| 0
| 0.222222
| 0.111111
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3a67dcbe1cfbc95d51f21ca8a3b28cc178854a5b
| 156
|
py
|
Python
|
conf/gunicorn_config.py
|
ryzenboi98/django-dev-ops
|
3cc0b72fbca0ec63a783825a1deb656f93a019d9
|
[
"MIT"
] | null | null | null |
conf/gunicorn_config.py
|
ryzenboi98/django-dev-ops
|
3cc0b72fbca0ec63a783825a1deb656f93a019d9
|
[
"MIT"
] | null | null | null |
conf/gunicorn_config.py
|
ryzenboi98/django-dev-ops
|
3cc0b72fbca0ec63a783825a1deb656f93a019d9
|
[
"MIT"
] | null | null | null |
from conf import confs
command = confs.project_path + '/env/bin/gunicorn'
pythonpath = confs.project_path
bind = confs.host + ':' + confs.port
workers = 3
| 22.285714
| 50
| 0.730769
| 22
| 156
| 5.090909
| 0.727273
| 0.214286
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007519
| 0.147436
| 156
| 6
| 51
| 26
| 0.834586
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3a855650d047f57f85c9c7f3098a70d45145a79d
| 68
|
py
|
Python
|
test.py
|
deedee1886-cmis/deedee1886-cmis-cs2
|
bff123ad15bce7b531ccde035cbf0444d1d88fc4
|
[
"CC0-1.0"
] | null | null | null |
test.py
|
deedee1886-cmis/deedee1886-cmis-cs2
|
bff123ad15bce7b531ccde035cbf0444d1d88fc4
|
[
"CC0-1.0"
] | null | null | null |
test.py
|
deedee1886-cmis/deedee1886-cmis-cs2
|
bff123ad15bce7b531ccde035cbf0444d1d88fc4
|
[
"CC0-1.0"
] | null | null | null |
def info(a):
a = raw_input("type your height here: ")
return a
| 9.714286
| 41
| 0.632353
| 12
| 68
| 3.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.235294
| 68
| 6
| 42
| 11.333333
| 0.807692
| 0
| 0
| 0
| 0
| 0
| 0.353846
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
3aa6e550cd6b632edd3ed5697314eaf733b97228
| 280
|
py
|
Python
|
djavError/widgets/staff_email_log_table.py
|
dasmith2/djavError
|
6fc1bfcf8b1443be817a9bd8ec2d59e7682521dd
|
[
"MIT"
] | null | null | null |
djavError/widgets/staff_email_log_table.py
|
dasmith2/djavError
|
6fc1bfcf8b1443be817a9bd8ec2d59e7682521dd
|
[
"MIT"
] | null | null | null |
djavError/widgets/staff_email_log_table.py
|
dasmith2/djavError
|
6fc1bfcf8b1443be817a9bd8ec2d59e7682521dd
|
[
"MIT"
] | null | null | null |
from djavError.widgets.fixable_report import FixableTable
class StaffEmailLogTable(FixableTable):
def headers(self):
return ['Title', 'Created', 'Latest', 'Count']
def get_cells(self, fixable):
return [fixable.title, fixable.created, fixable.latest, fixable.count]
| 28
| 74
| 0.75
| 32
| 280
| 6.5
| 0.59375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128571
| 280
| 9
| 75
| 31.111111
| 0.852459
| 0
| 0
| 0
| 0
| 0
| 0.082143
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0.333333
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
3aa7ee7a608c57ec766a4b0688819a40b84e74cf
| 88
|
py
|
Python
|
example/op_test/apps.py
|
peppelinux/django-jwtconnect-oidc-rp
|
1448a53aa4b5226423aa8bebad1dac72642ac1ac
|
[
"Apache-2.0"
] | 3
|
2021-03-16T08:31:52.000Z
|
2021-12-16T19:56:28.000Z
|
example/op_test/apps.py
|
peppelinux/spid-django-oidc
|
1448a53aa4b5226423aa8bebad1dac72642ac1ac
|
[
"Apache-2.0"
] | null | null | null |
example/op_test/apps.py
|
peppelinux/spid-django-oidc
|
1448a53aa4b5226423aa8bebad1dac72642ac1ac
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class OpTestConfig(AppConfig):
name = 'op_test'
| 14.666667
| 33
| 0.75
| 11
| 88
| 5.909091
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170455
| 88
| 5
| 34
| 17.6
| 0.890411
| 0
| 0
| 0
| 0
| 0
| 0.079545
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
3aec57f13f7a0106a69d1f052d5a0fc2094244ea
| 252
|
py
|
Python
|
Extract/Weather.py
|
kelleyjean/SenseHat_ETL
|
18a2ef261d7347ee4f98c1e85c4442e84385191b
|
[
"MIT"
] | null | null | null |
Extract/Weather.py
|
kelleyjean/SenseHat_ETL
|
18a2ef261d7347ee4f98c1e85c4442e84385191b
|
[
"MIT"
] | null | null | null |
Extract/Weather.py
|
kelleyjean/SenseHat_ETL
|
18a2ef261d7347ee4f98c1e85c4442e84385191b
|
[
"MIT"
] | null | null | null |
from weather_functions.humidity import get_humidity
from weather_functions.pressure import get_pressure
from weather_functions.temperature import get_temperature
class Weather:
def __init__(self):
pass
def temperature(self):
self.result =
| 21
| 57
| 0.81746
| 32
| 252
| 6.125
| 0.4375
| 0.168367
| 0.306122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134921
| 252
| 11
| 58
| 22.909091
| 0.899083
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.125
| 0.375
| null | null | 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 0
| 0
|
0
| 4
|
c930773b4f8745fd424e4f780dd9813aa8a8bd0a
| 261
|
py
|
Python
|
codewars/7kyu/Highest and Lowest/main.py
|
ictcubeMENA/Training_one
|
dff6bee96ba42babe4888e5cf9a9448a6fd93fc3
|
[
"MIT"
] | null | null | null |
codewars/7kyu/Highest and Lowest/main.py
|
ictcubeMENA/Training_one
|
dff6bee96ba42babe4888e5cf9a9448a6fd93fc3
|
[
"MIT"
] | 2
|
2019-01-22T10:53:42.000Z
|
2019-01-31T08:02:48.000Z
|
codewars/7kyu/Highest and Lowest/main.py
|
ictcubeMENA/Training_one
|
dff6bee96ba42babe4888e5cf9a9448a6fd93fc3
|
[
"MIT"
] | 13
|
2019-01-22T10:37:42.000Z
|
2019-01-25T13:30:43.000Z
|
def high_and_low(numbers):
numbers = list((max(map(int,numbers.split())),min(map(int,numbers.split()))))
return ' '.join(map(str,numbers))
def high_and_lowB(numbers):
nn = [int(s) for s in numbers.split(" ")]
return "%i %i" % (max(nn),min(nn))
| 37.285714
| 81
| 0.624521
| 42
| 261
| 3.785714
| 0.47619
| 0.226415
| 0.125786
| 0.226415
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153257
| 261
| 7
| 82
| 37.285714
| 0.719457
| 0
| 0
| 0
| 0
| 0
| 0.026718
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 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
| 0
| 0
| 0
|
0
| 4
|
c93ed48a8caf101ce06e96f97d48bb0e5f94c82b
| 204
|
py
|
Python
|
aoc2021/test_day1.py
|
jonsth131/aoc
|
f5d82bdcdeb2eea13dec3135dd0590b4a3bf1ebd
|
[
"MIT"
] | null | null | null |
aoc2021/test_day1.py
|
jonsth131/aoc
|
f5d82bdcdeb2eea13dec3135dd0590b4a3bf1ebd
|
[
"MIT"
] | null | null | null |
aoc2021/test_day1.py
|
jonsth131/aoc
|
f5d82bdcdeb2eea13dec3135dd0590b4a3bf1ebd
|
[
"MIT"
] | null | null | null |
from day1 import part1, part2
test_input = [199, 200, 208, 210, 200, 207, 240, 269, 260, 263]
def test_part1():
assert part1(test_input) == 7
def test_part2():
assert part2(test_input) == 5
| 15.692308
| 63
| 0.656863
| 33
| 204
| 3.909091
| 0.606061
| 0.209302
| 0.217054
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.242236
| 0.210784
| 204
| 12
| 64
| 17
| 0.559006
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| false
| 0
| 0.166667
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
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