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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
09ea41b990a6705a2776f01e6fd00a9ec2c1185d
| 91
|
py
|
Python
|
fastargs/exceptions.py
|
lengstrom/fastargs
|
bf2e0ac826bfb81f7559cd44e956c6a4aad982f1
|
[
"MIT"
] | 20
|
2021-04-02T06:43:37.000Z
|
2022-02-16T18:33:10.000Z
|
fastargs/exceptions.py
|
lengstrom/fastargs
|
bf2e0ac826bfb81f7559cd44e956c6a4aad982f1
|
[
"MIT"
] | 16
|
2021-04-02T05:27:26.000Z
|
2022-03-07T18:11:11.000Z
|
fastargs/exceptions.py
|
lengstrom/fastargs
|
bf2e0ac826bfb81f7559cd44e956c6a4aad982f1
|
[
"MIT"
] | 1
|
2021-11-11T03:31:10.000Z
|
2021-11-11T03:31:10.000Z
|
class MissingValueError(ValueError):
pass
class ValidationError(ValueError):
pass
| 15.166667
| 36
| 0.769231
| 8
| 91
| 8.75
| 0.625
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164835
| 91
| 5
| 37
| 18.2
| 0.921053
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
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| 0.5
| 0
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| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
09f7cad75d86a1b087725675c3b006f2758da273
| 19
|
py
|
Python
|
SQLlight.py
|
Sharadmishra88/pythonCodeSnippet
|
9e6b55f5a816e44e3a6a20caaed69eeb767ae1d8
|
[
"MIT"
] | null | null | null |
SQLlight.py
|
Sharadmishra88/pythonCodeSnippet
|
9e6b55f5a816e44e3a6a20caaed69eeb767ae1d8
|
[
"MIT"
] | null | null | null |
SQLlight.py
|
Sharadmishra88/pythonCodeSnippet
|
9e6b55f5a816e44e3a6a20caaed69eeb767ae1d8
|
[
"MIT"
] | null | null | null |
# CRUD on SQLlight
| 19
| 19
| 0.736842
| 3
| 19
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 19
| 1
| 19
| 19
| 0.933333
| 0.842105
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
61e71477481e4c10ed765681847b40fd96990d44
| 120
|
py
|
Python
|
app/__init__.py
|
jacekmiecznikowski/neo4index
|
24664a8e905b4763807302d44d8d181202ce2f69
|
[
"MIT"
] | null | null | null |
app/__init__.py
|
jacekmiecznikowski/neo4index
|
24664a8e905b4763807302d44d8d181202ce2f69
|
[
"MIT"
] | null | null | null |
app/__init__.py
|
jacekmiecznikowski/neo4index
|
24664a8e905b4763807302d44d8d181202ce2f69
|
[
"MIT"
] | null | null | null |
from .views import app
from .models import graph
graph.run("CREATE CONSTRAINT ON (n:User) ASSERT n.username IS UNIQUE")
| 30
| 70
| 0.775
| 20
| 120
| 4.65
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 120
| 4
| 70
| 30
| 0.894231
| 0
| 0
| 0
| 0
| 0
| 0.471074
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 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
| 1
| 0
|
0
| 5
|
111218a8028e886be81ff24759649795d9cd2833
| 180
|
py
|
Python
|
geomstats/backend/tensorflow_random.py
|
leslie-chu/geomstats
|
fbed39b47b16eab4a48179106e8d0c1a5891243d
|
[
"MIT"
] | 1
|
2018-05-31T11:43:07.000Z
|
2018-05-31T11:43:07.000Z
|
geomstats/backend/tensorflow_random.py
|
leslie-chu/geomstats
|
fbed39b47b16eab4a48179106e8d0c1a5891243d
|
[
"MIT"
] | null | null | null |
geomstats/backend/tensorflow_random.py
|
leslie-chu/geomstats
|
fbed39b47b16eab4a48179106e8d0c1a5891243d
|
[
"MIT"
] | null | null | null |
"""Tensorflow based random backend."""
import tensorflow as tf
def rand(*args):
return tf.random_uniform(shape=args)
def seed(*args):
return tf.set_random_seed(*args)
| 15
| 40
| 0.711111
| 26
| 180
| 4.807692
| 0.576923
| 0.16
| 0.192
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161111
| 180
| 11
| 41
| 16.363636
| 0.827815
| 0.177778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0.4
| 1
| 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
| 1
| 1
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
1115be7caa74f114414010006ede61c258372ec3
| 265
|
py
|
Python
|
VGG-19/vgg-19/tensornet/layers/__init__.py
|
zfgao66/deeplearning-mpo-tensorflow
|
c345b9fea79e16f98f9b50e0b4e0bcaf4ed4c8e6
|
[
"MIT"
] | 24
|
2019-04-30T14:59:43.000Z
|
2021-11-16T03:47:38.000Z
|
VGG-19/vgg-19/tensornet/layers/__init__.py
|
HC1022/deeplearning-mpo
|
c345b9fea79e16f98f9b50e0b4e0bcaf4ed4c8e6
|
[
"MIT"
] | null | null | null |
VGG-19/vgg-19/tensornet/layers/__init__.py
|
HC1022/deeplearning-mpo
|
c345b9fea79e16f98f9b50e0b4e0bcaf4ed4c8e6
|
[
"MIT"
] | 9
|
2019-08-14T10:50:37.000Z
|
2022-03-15T14:41:52.000Z
|
from .linear import *
from .linear_dev import *
from .batch_normalization import *
from .tt import *
from .tr import *
from .ttrelu import *
from .tt_dev import *
from .conv import *
from .tt_conv import *
from .tt_conv_full import *
from .tt_conv_direct import *
| 20.384615
| 34
| 0.74717
| 41
| 265
| 4.634146
| 0.292683
| 0.526316
| 0.315789
| 0.252632
| 0.189474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.169811
| 265
| 12
| 35
| 22.083333
| 0.863636
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
111955b305da6737dba4a8619ea950d1a23d6918
| 10,592
|
py
|
Python
|
src/commercetools/platform/models/_schemas/tax_category.py
|
lime-green/commercetools-python-sdk
|
63b77f6e5abe43e2b3ebbf3cdbbe00c7cf80dca6
|
[
"MIT"
] | 1
|
2021-04-07T20:01:30.000Z
|
2021-04-07T20:01:30.000Z
|
src/commercetools/platform/models/_schemas/tax_category.py
|
lime-green/commercetools-python-sdk
|
63b77f6e5abe43e2b3ebbf3cdbbe00c7cf80dca6
|
[
"MIT"
] | null | null | null |
src/commercetools/platform/models/_schemas/tax_category.py
|
lime-green/commercetools-python-sdk
|
63b77f6e5abe43e2b3ebbf3cdbbe00c7cf80dca6
|
[
"MIT"
] | null | null | null |
# Generated file, please do not change!!!
import re
import typing
import marshmallow
import marshmallow_enum
from commercetools import helpers
from ... import models
from ..common import ReferenceTypeId
from .common import BaseResourceSchema, ReferenceSchema, ResourceIdentifierSchema
# Fields
# Marshmallow Schemas
class SubRateSchema(helpers.BaseSchema):
name = marshmallow.fields.String(allow_none=True, missing=None)
amount = marshmallow.fields.Float(allow_none=True, missing=None)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.SubRate(**data)
class TaxCategorySchema(BaseResourceSchema):
last_modified_by = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".common.LastModifiedBySchema"),
allow_none=True,
unknown=marshmallow.EXCLUDE,
metadata={"omit_empty": True},
missing=None,
data_key="lastModifiedBy",
)
created_by = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".common.CreatedBySchema"),
allow_none=True,
unknown=marshmallow.EXCLUDE,
metadata={"omit_empty": True},
missing=None,
data_key="createdBy",
)
name = marshmallow.fields.String(allow_none=True, missing=None)
description = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
rates = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxRateSchema"),
allow_none=True,
many=True,
unknown=marshmallow.EXCLUDE,
missing=None,
)
key = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxCategory(**data)
class TaxCategoryDraftSchema(helpers.BaseSchema):
name = marshmallow.fields.String(allow_none=True, missing=None)
description = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
rates = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxRateDraftSchema"),
allow_none=True,
many=True,
unknown=marshmallow.EXCLUDE,
missing=None,
)
key = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxCategoryDraft(**data)
class TaxCategoryPagedQueryResponseSchema(helpers.BaseSchema):
limit = marshmallow.fields.Integer(allow_none=True, missing=None)
count = marshmallow.fields.Integer(allow_none=True, missing=None)
total = marshmallow.fields.Integer(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
offset = marshmallow.fields.Integer(allow_none=True, missing=None)
results = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxCategorySchema"),
allow_none=True,
many=True,
unknown=marshmallow.EXCLUDE,
missing=None,
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxCategoryPagedQueryResponse(**data)
class TaxCategoryReferenceSchema(ReferenceSchema):
obj = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxCategorySchema"),
allow_none=True,
unknown=marshmallow.EXCLUDE,
metadata={"omit_empty": True},
missing=None,
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["type_id"]
return models.TaxCategoryReference(**data)
class TaxCategoryResourceIdentifierSchema(ResourceIdentifierSchema):
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["type_id"]
return models.TaxCategoryResourceIdentifier(**data)
class TaxCategoryUpdateSchema(helpers.BaseSchema):
version = marshmallow.fields.Integer(allow_none=True, missing=None)
actions = marshmallow.fields.List(
helpers.Discriminator(
allow_none=True,
discriminator_field=("action", "action"),
discriminator_schemas={
"addTaxRate": helpers.absmod(
__name__, ".TaxCategoryAddTaxRateActionSchema"
),
"changeName": helpers.absmod(
__name__, ".TaxCategoryChangeNameActionSchema"
),
"removeTaxRate": helpers.absmod(
__name__, ".TaxCategoryRemoveTaxRateActionSchema"
),
"replaceTaxRate": helpers.absmod(
__name__, ".TaxCategoryReplaceTaxRateActionSchema"
),
"setDescription": helpers.absmod(
__name__, ".TaxCategorySetDescriptionActionSchema"
),
"setKey": helpers.absmod(__name__, ".TaxCategorySetKeyActionSchema"),
},
),
allow_none=True,
missing=None,
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxCategoryUpdate(**data)
class TaxCategoryUpdateActionSchema(helpers.BaseSchema):
action = marshmallow.fields.String(allow_none=True, missing=None)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategoryUpdateAction(**data)
class TaxRateSchema(helpers.BaseSchema):
id = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
name = marshmallow.fields.String(allow_none=True, missing=None)
amount = marshmallow.fields.Float(allow_none=True, missing=None)
included_in_price = marshmallow.fields.Boolean(
allow_none=True, missing=None, data_key="includedInPrice"
)
country = marshmallow.fields.String(allow_none=True, missing=None)
state = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
sub_rates = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".SubRateSchema"),
allow_none=True,
many=True,
unknown=marshmallow.EXCLUDE,
metadata={"omit_empty": True},
missing=None,
data_key="subRates",
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxRate(**data)
class TaxRateDraftSchema(helpers.BaseSchema):
name = marshmallow.fields.String(allow_none=True, missing=None)
amount = marshmallow.fields.Float(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
included_in_price = marshmallow.fields.Boolean(
allow_none=True, missing=None, data_key="includedInPrice"
)
country = marshmallow.fields.String(allow_none=True, missing=None)
state = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
sub_rates = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".SubRateSchema"),
allow_none=True,
many=True,
unknown=marshmallow.EXCLUDE,
metadata={"omit_empty": True},
missing=None,
data_key="subRates",
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
return models.TaxRateDraft(**data)
class TaxCategoryAddTaxRateActionSchema(TaxCategoryUpdateActionSchema):
tax_rate = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxRateDraftSchema"),
allow_none=True,
unknown=marshmallow.EXCLUDE,
missing=None,
data_key="taxRate",
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategoryAddTaxRateAction(**data)
class TaxCategoryChangeNameActionSchema(TaxCategoryUpdateActionSchema):
name = marshmallow.fields.String(allow_none=True, missing=None)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategoryChangeNameAction(**data)
class TaxCategoryRemoveTaxRateActionSchema(TaxCategoryUpdateActionSchema):
tax_rate_id = marshmallow.fields.String(
allow_none=True, missing=None, data_key="taxRateId"
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategoryRemoveTaxRateAction(**data)
class TaxCategoryReplaceTaxRateActionSchema(TaxCategoryUpdateActionSchema):
tax_rate_id = marshmallow.fields.String(
allow_none=True, missing=None, data_key="taxRateId"
)
tax_rate = helpers.LazyNestedField(
nested=helpers.absmod(__name__, ".TaxRateDraftSchema"),
allow_none=True,
unknown=marshmallow.EXCLUDE,
missing=None,
data_key="taxRate",
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategoryReplaceTaxRateAction(**data)
class TaxCategorySetDescriptionActionSchema(TaxCategoryUpdateActionSchema):
description = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategorySetDescriptionAction(**data)
class TaxCategorySetKeyActionSchema(TaxCategoryUpdateActionSchema):
key = marshmallow.fields.String(
allow_none=True, metadata={"omit_empty": True}, missing=None
)
class Meta:
unknown = marshmallow.EXCLUDE
@marshmallow.post_load
def post_load(self, data, **kwargs):
del data["action"]
return models.TaxCategorySetKeyAction(**data)
| 30.005666
| 85
| 0.672394
| 1,008
| 10,592
| 6.882937
| 0.125
| 0.054483
| 0.078697
| 0.080715
| 0.705679
| 0.705679
| 0.70222
| 0.701931
| 0.65898
| 0.649467
| 0
| 0
| 0.22602
| 10,592
| 352
| 86
| 30.090909
| 0.846304
| 0.006231
| 0
| 0.64
| 1
| 0
| 0.075366
| 0.0249
| 0
| 0
| 0
| 0
| 0
| 1
| 0.058182
| false
| 0
| 0.029091
| 0.025455
| 0.410909
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
11643cd64cb21d55fbe374d0f355a6d281d482d7
| 139
|
py
|
Python
|
pppf_accessories/__init__.py
|
linsalrob/PPPF
|
42575fa93e8a1c53012bbfe292514d95b48fbd9d
|
[
"MIT"
] | 1
|
2020-05-12T18:21:50.000Z
|
2020-05-12T18:21:50.000Z
|
pppf_accessories/__init__.py
|
linsalrob/PPPF
|
42575fa93e8a1c53012bbfe292514d95b48fbd9d
|
[
"MIT"
] | null | null | null |
pppf_accessories/__init__.py
|
linsalrob/PPPF
|
42575fa93e8a1c53012bbfe292514d95b48fbd9d
|
[
"MIT"
] | null | null | null |
from .blast import stream_blast_results
from .formatting import color, colour
__all__ = [
'color', 'colour', 'stream_blast_results'
]
| 23.166667
| 45
| 0.748201
| 17
| 139
| 5.647059
| 0.529412
| 0.229167
| 0.375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.151079
| 139
| 6
| 46
| 23.166667
| 0.813559
| 0
| 0
| 0
| 0
| 0
| 0.221429
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
11660f0afc0336d9f59ac7598e0e7c2ab379a653
| 91
|
py
|
Python
|
datasets/__init__.py
|
z-a-f/zaf_funcs
|
41fc40b5017028b3570f3419e1c035ba0dc7a092
|
[
"MIT"
] | null | null | null |
datasets/__init__.py
|
z-a-f/zaf_funcs
|
41fc40b5017028b3570f3419e1c035ba0dc7a092
|
[
"MIT"
] | null | null | null |
datasets/__init__.py
|
z-a-f/zaf_funcs
|
41fc40b5017028b3570f3419e1c035ba0dc7a092
|
[
"MIT"
] | null | null | null |
"""Routines to load some datasets."""
from .imdb import IMDB
from .reuters import Reuters
| 18.2
| 37
| 0.747253
| 13
| 91
| 5.230769
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 91
| 4
| 38
| 22.75
| 0.883117
| 0.340659
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
fecdb29f570bb18300576b56fc73073b3b7ce033
| 17
|
py
|
Python
|
2/p2.py
|
ashishjayamohan/competitive-programming
|
05c5c560c2c2eb36121c52693b8c7d084f435f9e
|
[
"MIT"
] | null | null | null |
2/p2.py
|
ashishjayamohan/competitive-programming
|
05c5c560c2c2eb36121c52693b8c7d084f435f9e
|
[
"MIT"
] | null | null | null |
2/p2.py
|
ashishjayamohan/competitive-programming
|
05c5c560c2c2eb36121c52693b8c7d084f435f9e
|
[
"MIT"
] | null | null | null |
def D(r,c):
| 5.666667
| 11
| 0.352941
| 4
| 17
| 1.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.411765
| 17
| 2
| 12
| 8.5
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
3a54f384791a82a173736909db0f402ce868ee9a
| 132
|
py
|
Python
|
src/wagtail_live/exceptions.py
|
Stormheg/wagtail-live
|
a5eb79024d44c060079ae7d4707d6220ea66ff5b
|
[
"BSD-3-Clause"
] | null | null | null |
src/wagtail_live/exceptions.py
|
Stormheg/wagtail-live
|
a5eb79024d44c060079ae7d4707d6220ea66ff5b
|
[
"BSD-3-Clause"
] | null | null | null |
src/wagtail_live/exceptions.py
|
Stormheg/wagtail-live
|
a5eb79024d44c060079ae7d4707d6220ea66ff5b
|
[
"BSD-3-Clause"
] | null | null | null |
"""Wagtail Live Exceptions."""
class RequestVerificationError(Exception):
pass
class WebhookSetupError(Exception):
pass
| 13.2
| 42
| 0.742424
| 11
| 132
| 8.909091
| 0.727273
| 0.265306
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.159091
| 132
| 9
| 43
| 14.666667
| 0.882883
| 0.181818
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
3a58b2e5408360b5b9654ede9169a9b0694af716
| 172
|
py
|
Python
|
joey/utils/middleware.py
|
pinecrew/joey
|
0a4715051629aa58b2333365149d2f3a4c6f4dee
|
[
"MIT"
] | 1
|
2020-08-23T22:33:06.000Z
|
2020-08-23T22:33:06.000Z
|
joey/utils/middleware.py
|
pinecrew/joey
|
0a4715051629aa58b2333365149d2f3a4c6f4dee
|
[
"MIT"
] | 8
|
2020-08-13T13:20:19.000Z
|
2020-10-19T10:26:17.000Z
|
joey/utils/middleware.py
|
pinecrew/joey
|
0a4715051629aa58b2333365149d2f3a4c6f4dee
|
[
"MIT"
] | null | null | null |
from importlib import import_module
def get_middleware(name):
module, middleware = name.rsplit(".", maxsplit=1)
return getattr(import_module(module), middleware)
| 24.571429
| 53
| 0.755814
| 21
| 172
| 6.047619
| 0.619048
| 0.188976
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006757
| 0.139535
| 172
| 6
| 54
| 28.666667
| 0.851351
| 0
| 0
| 0
| 0
| 0
| 0.005814
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
28af077af80f5b3a70396fda756a309075385fac
| 76
|
py
|
Python
|
BooleanOperatorExample.py
|
ZnoKunG/PythonProject
|
388b5dfeb0161aee66094e7b2ecc2d6ed13588bd
|
[
"MIT"
] | null | null | null |
BooleanOperatorExample.py
|
ZnoKunG/PythonProject
|
388b5dfeb0161aee66094e7b2ecc2d6ed13588bd
|
[
"MIT"
] | null | null | null |
BooleanOperatorExample.py
|
ZnoKunG/PythonProject
|
388b5dfeb0161aee66094e7b2ecc2d6ed13588bd
|
[
"MIT"
] | null | null | null |
age = 85
print("สวัสดีครับ คุณอายุเกินกว่าจะเข้าร้านนี้ไหม ?")
print(age>18)
| 25.333333
| 53
| 0.657895
| 28
| 76
| 2.178571
| 0.821429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.057143
| 0.078947
| 76
| 3
| 54
| 25.333333
| 0.657143
| 0
| 0
| 0
| 0
| 0.333333
| 0.571429
| 0.402597
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.666667
| 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
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
28b6099ae72e70486eb28d0d296df0d0c0ea899e
| 99
|
py
|
Python
|
BOJ/21000~21999/21600~21699/21613.py
|
shinkeonkim/today-ps
|
f3e5e38c5215f19579bb0422f303a9c18c626afa
|
[
"Apache-2.0"
] | null | null | null |
BOJ/21000~21999/21600~21699/21613.py
|
shinkeonkim/today-ps
|
f3e5e38c5215f19579bb0422f303a9c18c626afa
|
[
"Apache-2.0"
] | null | null | null |
BOJ/21000~21999/21600~21699/21613.py
|
shinkeonkim/today-ps
|
f3e5e38c5215f19579bb0422f303a9c18c626afa
|
[
"Apache-2.0"
] | null | null | null |
print(sorted([[input(), int(input())] for _ in range(int(input()))],key=lambda t : (-t[1]))[0][0])
| 49.5
| 98
| 0.575758
| 17
| 99
| 3.294118
| 0.705882
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.033333
| 0.090909
| 99
| 1
| 99
| 99
| 0.588889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
28dc3959e7795960ce488e86211e12987eeb11fe
| 232
|
py
|
Python
|
configcatclient/configcache.py
|
kantanhq/python-sdk
|
3401bb5af42b5dd403fe231afa9457d1d3637e67
|
[
"MIT"
] | null | null | null |
configcatclient/configcache.py
|
kantanhq/python-sdk
|
3401bb5af42b5dd403fe231afa9457d1d3637e67
|
[
"MIT"
] | 1
|
2020-05-22T04:41:55.000Z
|
2020-05-26T23:32:02.000Z
|
configcatclient/configcache.py
|
clipchamp/python-sdk
|
b0acb24a606cf20b5abaf14c5a9fc091d3431722
|
[
"MIT"
] | null | null | null |
from .interfaces import ConfigCache
class InMemoryConfigCache(ConfigCache):
def __init__(self):
self._value = None
def get(self):
return self._value
def set(self, value):
self._value = value
| 16.571429
| 39
| 0.650862
| 26
| 232
| 5.538462
| 0.538462
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.267241
| 232
| 13
| 40
| 17.846154
| 0.847059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0.125
| 0.125
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
28e9c2346cdf21263cea9c1ff1529af082358b94
| 250
|
py
|
Python
|
src/sage/sat/solvers/cryptominisat/__init__.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | 5
|
2015-01-04T07:15:06.000Z
|
2022-03-04T15:15:18.000Z
|
src/sage/sat/solvers/cryptominisat/__init__.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | null | null | null |
src/sage/sat/solvers/cryptominisat/__init__.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | 10
|
2016-09-28T13:12:40.000Z
|
2022-02-12T09:28:34.000Z
|
try:
from cryptominisat import CryptoMiniSat
except ImportError:
raise ImportError("Failed to import 'sage.sat.solvers.cryptominisat.CryptoMiniSat'. Run \"install_package('cryptominisat')\" to install it.")
from solverconf import SolverConf
| 35.714286
| 145
| 0.792
| 28
| 250
| 7.035714
| 0.607143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 250
| 6
| 146
| 41.666667
| 0.895455
| 0
| 0
| 0
| 0
| 0
| 0.392
| 0.188
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.8
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
28ef240c1fd861a89a261f10ccfb30ae9e68dd22
| 121
|
py
|
Python
|
tests/vendor/solo/utils.py
|
niooss-ledger/fido2-tests
|
669fa9b4197679c10d0ce2e93233e923e5f3b3ef
|
[
"Apache-2.0",
"MIT"
] | 32
|
2019-08-01T10:40:31.000Z
|
2022-02-16T05:15:37.000Z
|
tests/vendor/solo/utils.py
|
niooss-ledger/fido2-tests
|
669fa9b4197679c10d0ce2e93233e923e5f3b3ef
|
[
"Apache-2.0",
"MIT"
] | 33
|
2019-08-08T01:09:48.000Z
|
2021-11-14T21:04:59.000Z
|
tests/vendor/solo/utils.py
|
niooss-ledger/fido2-tests
|
669fa9b4197679c10d0ce2e93233e923e5f3b3ef
|
[
"Apache-2.0",
"MIT"
] | 23
|
2019-08-12T14:38:59.000Z
|
2022-01-30T21:02:29.000Z
|
class DeviceSelectCredential:
def __init__(self, number):
pass
def __call__(self, status):
pass
| 17.285714
| 31
| 0.636364
| 12
| 121
| 5.75
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.289256
| 121
| 6
| 32
| 20.166667
| 0.802326
| 0
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.4
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
e925783abbb983cccfdc0c455d15f6c53120d159
| 136
|
py
|
Python
|
ble2lsl/devices/__init__.py
|
OmriNach/WizardHat
|
b72e3ff7f313eb715a24ebaf7b85bad021de7443
|
[
"BSD-3-Clause"
] | null | null | null |
ble2lsl/devices/__init__.py
|
OmriNach/WizardHat
|
b72e3ff7f313eb715a24ebaf7b85bad021de7443
|
[
"BSD-3-Clause"
] | null | null | null |
ble2lsl/devices/__init__.py
|
OmriNach/WizardHat
|
b72e3ff7f313eb715a24ebaf7b85bad021de7443
|
[
"BSD-3-Clause"
] | 1
|
2019-05-07T20:46:51.000Z
|
2019-05-07T20:46:51.000Z
|
"""BLE/LSL interfacing parameters for specific devices.
TODO:
* Simple class (or specification/template) for device parameters
"""
| 22.666667
| 68
| 0.75
| 16
| 136
| 6.375
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.154412
| 136
| 5
| 69
| 27.2
| 0.886957
| 0.941176
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0.2
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e935c5226dbcfb659d5295d284df99125a6ac3b1
| 214
|
py
|
Python
|
about/views.py
|
Polinavas95/foodgram-project
|
40f7f10f72e1274305ea795658e2638ebd16cb8f
|
[
"MIT"
] | null | null | null |
about/views.py
|
Polinavas95/foodgram-project
|
40f7f10f72e1274305ea795658e2638ebd16cb8f
|
[
"MIT"
] | null | null | null |
about/views.py
|
Polinavas95/foodgram-project
|
40f7f10f72e1274305ea795658e2638ebd16cb8f
|
[
"MIT"
] | 3
|
2021-02-10T20:07:10.000Z
|
2021-03-16T13:40:13.000Z
|
from django.views.generic.base import TemplateView
class AboutView(TemplateView):
template_name = 'flatpages/about/author.html'
class SpecView(TemplateView):
template_name = 'flatpages/about/spec.html'
| 21.4
| 50
| 0.780374
| 25
| 214
| 6.6
| 0.68
| 0.242424
| 0.290909
| 0.4
| 0.460606
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121495
| 214
| 9
| 51
| 23.777778
| 0.87766
| 0
| 0
| 0
| 0
| 0
| 0.242991
| 0.242991
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e93ee3fbff09e8fc88c5be0c2e4ef570d1b36a24
| 767
|
py
|
Python
|
concoord/proxy/stack.py
|
denizalti/concoord
|
5a51ba2b475f44da221304ea7f0b9118f2e8511a
|
[
"BSD-3-Clause"
] | 36
|
2015-01-22T15:55:21.000Z
|
2019-12-10T00:39:11.000Z
|
concoord/proxy/stack.py
|
liranz/concoord
|
bdb3798bf200d1cbd04bc50260cddaec6ba2a763
|
[
"BSD-3-Clause"
] | 3
|
2016-11-15T16:58:49.000Z
|
2018-05-25T11:32:50.000Z
|
concoord/proxy/stack.py
|
liranz/concoord
|
bdb3798bf200d1cbd04bc50260cddaec6ba2a763
|
[
"BSD-3-Clause"
] | 13
|
2015-01-07T00:07:59.000Z
|
2018-11-24T04:39:58.000Z
|
"""
@author: Deniz Altinbuken, Emin Gun Sirer
@note: Stack proxy
@copyright: See LICENSE
"""
from concoord.clientproxy import ClientProxy
class Stack:
def __init__(self, bootstrap, timeout=60, debug=False, token=None):
self.proxy = ClientProxy(bootstrap, timeout, debug, token)
def __concoordinit__(self):
return self.proxy.invoke_command('__init__')
def append(self, item):
return self.proxy.invoke_command('append', item)
def pop(self):
return self.proxy.invoke_command('pop')
def get_size(self):
return self.proxy.invoke_command('get_size')
def get_stack(self):
return self.proxy.invoke_command('get_stack')
def __str__(self):
return self.proxy.invoke_command('__str__')
| 24.741935
| 71
| 0.688396
| 96
| 767
| 5.1875
| 0.385417
| 0.126506
| 0.180723
| 0.253012
| 0.389558
| 0.333333
| 0.140562
| 0
| 0
| 0
| 0
| 0.003247
| 0.196871
| 767
| 30
| 72
| 25.566667
| 0.805195
| 0.109518
| 0
| 0
| 0
| 0
| 0.061012
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4375
| false
| 0
| 0.0625
| 0.375
| 0.9375
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
e93fb118315db83059399279a7a41064303f816b
| 217
|
py
|
Python
|
Program_Python_code/31.py
|
skyhigh8591/Learning_Test_Program
|
5f3c0f11874618919002126863772e0dd06a1072
|
[
"MIT"
] | null | null | null |
Program_Python_code/31.py
|
skyhigh8591/Learning_Test_Program
|
5f3c0f11874618919002126863772e0dd06a1072
|
[
"MIT"
] | null | null | null |
Program_Python_code/31.py
|
skyhigh8591/Learning_Test_Program
|
5f3c0f11874618919002126863772e0dd06a1072
|
[
"MIT"
] | null | null | null |
#! /usr/bin/python
#coding=utf-8
import math_operation as m
num = m.operation(4,6)
print "operation:" +str(num[0])
print "operation:" +str(num[1])
print "operation:" +str(num[2])
print "operation:" +str(num[3])
| 19.727273
| 32
| 0.663594
| 36
| 217
| 3.972222
| 0.555556
| 0.391608
| 0.475524
| 0.559441
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.037037
| 0.129032
| 217
| 10
| 33
| 21.7
| 0.719577
| 0.133641
| 0
| 0
| 0
| 0
| 0.215054
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.166667
| null | null | 0.666667
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
3a62c931c302aa4a184934fb410f9fe02824cc88
| 88
|
py
|
Python
|
tests/PaxHeaders.127271/uuidfilt.py
|
ictyangye/ovs-c2ratelimiter
|
c0e1ada35b3b5f2524fbba6324c9e996e84ac9bc
|
[
"Apache-2.0"
] | null | null | null |
tests/PaxHeaders.127271/uuidfilt.py
|
ictyangye/ovs-c2ratelimiter
|
c0e1ada35b3b5f2524fbba6324c9e996e84ac9bc
|
[
"Apache-2.0"
] | null | null | null |
tests/PaxHeaders.127271/uuidfilt.py
|
ictyangye/ovs-c2ratelimiter
|
c0e1ada35b3b5f2524fbba6324c9e996e84ac9bc
|
[
"Apache-2.0"
] | null | null | null |
30 mtime=1527291425.681873811
29 atime=1527291425.78587418
29 ctime=1527291454.50997211
| 22
| 29
| 0.863636
| 12
| 88
| 6.333333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.743902
| 0.068182
| 88
| 3
| 30
| 29.333333
| 0.182927
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
3ab488f9065cb8496063b9443aff39ca476af73a
| 2,782
|
py
|
Python
|
tests/test_auditor/test_auditor_experiment_job.py
|
elyase/polyaxon
|
1c19f059a010a6889e2b7ea340715b2bcfa382a0
|
[
"MIT"
] | null | null | null |
tests/test_auditor/test_auditor_experiment_job.py
|
elyase/polyaxon
|
1c19f059a010a6889e2b7ea340715b2bcfa382a0
|
[
"MIT"
] | null | null | null |
tests/test_auditor/test_auditor_experiment_job.py
|
elyase/polyaxon
|
1c19f059a010a6889e2b7ea340715b2bcfa382a0
|
[
"MIT"
] | null | null | null |
# pylint:disable=ungrouped-imports
from unittest.mock import patch
import pytest
import activitylogs
import auditor
import tracker
from event_manager.events import experiment_job as experiment_job_events
from factories.factory_experiments import ExperimentJobFactory
from tests.utils import BaseTest
@pytest.mark.auditor_mark
class AuditorExperimentJobTest(BaseTest):
"""Testing subscribed events"""
DISABLE_RUNNER = True
def setUp(self):
super().setUp()
self.experiment_job = ExperimentJobFactory()
auditor.validate()
auditor.setup()
tracker.validate()
tracker.setup()
activitylogs.validate()
activitylogs.setup()
@patch('tracker.service.TrackerService.record_event')
@patch('activitylogs.service.ActivityLogService.record_event')
def test_experiment_job_viewed(self, activitylogs_record, tracker_record):
auditor.record(event_type=experiment_job_events.EXPERIMENT_JOB_VIEWED,
instance=self.experiment_job,
actor_id=1,
actor_name='foo')
assert tracker_record.call_count == 1
assert activitylogs_record.call_count == 1
@patch('tracker.service.TrackerService.record_event')
@patch('activitylogs.service.ActivityLogService.record_event')
def test_experiment_resources_viewed(self, activitylogs_record, tracker_record):
auditor.record(event_type=experiment_job_events.EXPERIMENT_JOB_RESOURCES_VIEWED,
instance=self.experiment_job,
actor_id=1,
actor_name='foo')
assert tracker_record.call_count == 1
assert activitylogs_record.call_count == 1
@patch('tracker.service.TrackerService.record_event')
@patch('activitylogs.service.ActivityLogService.record_event')
def test_experiment_logs_viewed(self, activitylogs_record, tracker_record):
auditor.record(event_type=experiment_job_events.EXPERIMENT_JOB_LOGS_VIEWED,
instance=self.experiment_job,
actor_id=1,
actor_name='foo')
assert tracker_record.call_count == 1
assert activitylogs_record.call_count == 1
@patch('tracker.service.TrackerService.record_event')
@patch('activitylogs.service.ActivityLogService.record_event')
def test_experiment_job_statuses_viewed(self, activitylogs_record, tracker_record):
auditor.record(event_type=experiment_job_events.EXPERIMENT_JOB_STATUSES_VIEWED,
instance=self.experiment_job,
actor_id=1,
actor_name='foo')
assert tracker_record.call_count == 1
assert activitylogs_record.call_count == 1
| 37.594595
| 88
| 0.695543
| 293
| 2,782
| 6.303754
| 0.194539
| 0.119653
| 0.06497
| 0.069302
| 0.702761
| 0.702761
| 0.702761
| 0.702761
| 0.702761
| 0.702761
| 0
| 0.005581
| 0.227175
| 2,782
| 73
| 89
| 38.109589
| 0.853488
| 0.021208
| 0
| 0.5
| 0
| 0
| 0.144277
| 0.13986
| 0
| 0
| 0
| 0
| 0.142857
| 1
| 0.089286
| false
| 0
| 0.142857
| 0
| 0.267857
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
aaf84a8884b2f1294eeef92c6c7771a3c9a62426
| 647
|
py
|
Python
|
composer/core/__init__.py
|
ajaysaini725/composer
|
00fbf95823cd50354b2410fbd88f06eaf0481662
|
[
"Apache-2.0"
] | null | null | null |
composer/core/__init__.py
|
ajaysaini725/composer
|
00fbf95823cd50354b2410fbd88f06eaf0481662
|
[
"Apache-2.0"
] | null | null | null |
composer/core/__init__.py
|
ajaysaini725/composer
|
00fbf95823cd50354b2410fbd88f06eaf0481662
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2021 MosaicML. All Rights Reserved.
from composer.core import types as types
from composer.core.algorithm import Algorithm as Algorithm
from composer.core.callback import Callback as Callback
from composer.core.data_spec import DataSpec as DataSpec
from composer.core.engine import Engine as Engine
from composer.core.engine import Trace as Trace
from composer.core.event import Event as Event
from composer.core.logging import Logger as Logger
from composer.core.state import State as State
from composer.core.time import Time as Time
from composer.core.time import Timer as Timer
from composer.core.time import TimeUnit as TimeUnit
| 43.133333
| 58
| 0.836167
| 102
| 647
| 5.294118
| 0.254902
| 0.266667
| 0.355556
| 0.111111
| 0.248148
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007055
| 0.123648
| 647
| 14
| 59
| 46.214286
| 0.945326
| 0.069552
| 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
| 1
| 0
|
0
| 5
|
c96f25ff3ffdf2ced2fd38701d07d705db1b74b9
| 159
|
py
|
Python
|
Ejercicios/Modulos.py
|
dannieldev/Fundamentos-de-Python
|
63bf92c7256b373b631cae3ae9a80a3a5071f61d
|
[
"MIT"
] | null | null | null |
Ejercicios/Modulos.py
|
dannieldev/Fundamentos-de-Python
|
63bf92c7256b373b631cae3ae9a80a3a5071f61d
|
[
"MIT"
] | null | null | null |
Ejercicios/Modulos.py
|
dannieldev/Fundamentos-de-Python
|
63bf92c7256b373b631cae3ae9a80a3a5071f61d
|
[
"MIT"
] | null | null | null |
#import ModuloMain #impotar modulo
from ModuloMain import Ejemplo #impotar solo una funsion
#from ModuloMain * #importar todo
e = Ejemplo()
e.imprime()
| 22.714286
| 57
| 0.748428
| 20
| 159
| 5.95
| 0.65
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.176101
| 159
| 6
| 58
| 26.5
| 0.908397
| 0.54717
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a312b4926fd217ae206f1f1cd5a60260bf2eba09
| 22
|
py
|
Python
|
stargrit/radiative_transfer/ali/__init__.py
|
gecheline/stargrit
|
ec293eaa9f911145f05a297e6e4c321b6adebbd0
|
[
"MIT"
] | null | null | null |
stargrit/radiative_transfer/ali/__init__.py
|
gecheline/stargrit
|
ec293eaa9f911145f05a297e6e4c321b6adebbd0
|
[
"MIT"
] | null | null | null |
stargrit/radiative_transfer/ali/__init__.py
|
gecheline/stargrit
|
ec293eaa9f911145f05a297e6e4c321b6adebbd0
|
[
"MIT"
] | null | null | null |
from gray_ali import *
| 22
| 22
| 0.818182
| 4
| 22
| 4.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 22
| 1
| 22
| 22
| 0.894737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a31b50da31cfe6ff813352fecd40be8fc91b330d
| 1,757
|
py
|
Python
|
tests/integration/test_warcraft_client_item.py
|
tehmufifnman/BattleMuffin-Python
|
f0bb5ee7024624191b33441aeecf3fb29570abe7
|
[
"MIT"
] | 7
|
2020-05-15T18:09:23.000Z
|
2021-03-08T16:10:37.000Z
|
tests/integration/test_warcraft_client_item.py
|
tehmufifnman/BattleMuffin-Python
|
f0bb5ee7024624191b33441aeecf3fb29570abe7
|
[
"MIT"
] | 2
|
2020-04-20T04:42:37.000Z
|
2020-10-28T23:27:07.000Z
|
tests/integration/test_warcraft_client_item.py
|
tehmufifnman/BattleMuffin-Python
|
f0bb5ee7024624191b33441aeecf3fb29570abe7
|
[
"MIT"
] | 2
|
2020-05-18T06:58:53.000Z
|
2021-03-08T16:10:27.000Z
|
import os
from battlemuffin.clients.warcraft_client import WarcraftClient
from battlemuffin.config.region_config import Locale, Region
def test_get_item_classes_index(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_classes_index()
assert response == snapshot
def test_get_item_class(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_class(0)
assert response == snapshot
def test_get_item_sets_index(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_sets_index()
assert response == snapshot
def test_get_item_set(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_set(1)
assert response == snapshot
def test_get_item_subclass(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_subclass(0, 0)
assert response == snapshot
def test_get_item(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item(19019)
assert response == snapshot
def test_get_item_media(snapshot):
client = WarcraftClient(
os.getenv("CLIENT_ID"), os.getenv("CLIENT_SECRET"), Region.us, Locale.en_US
)
response = client.get_item_media(19019)
assert response == snapshot
| 28.803279
| 83
| 0.710302
| 228
| 1,757
| 5.210526
| 0.144737
| 0.082492
| 0.164983
| 0.082492
| 0.807239
| 0.807239
| 0.807239
| 0.746633
| 0.61532
| 0.61532
| 0
| 0.009702
| 0.178714
| 1,757
| 60
| 84
| 29.283333
| 0.813583
| 0
| 0
| 0.466667
| 0
| 0
| 0.087649
| 0
| 0
| 0
| 0
| 0
| 0.155556
| 1
| 0.155556
| false
| 0
| 0.066667
| 0
| 0.222222
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
a360701f2090e1cb40383e3ab347350b38804937
| 144
|
py
|
Python
|
labeler_main.py
|
fd-sturniolo/AntTracker
|
0677ec1757c33aaddd013eb0a65481c3aca25881
|
[
"MIT"
] | 1
|
2021-06-16T22:11:09.000Z
|
2021-06-16T22:11:09.000Z
|
labeler_main.py
|
fd-sturniolo/AntTracker
|
0677ec1757c33aaddd013eb0a65481c3aca25881
|
[
"MIT"
] | 18
|
2021-05-17T21:56:49.000Z
|
2021-07-08T12:53:22.000Z
|
labeler_main.py
|
fd-sturniolo/AntTracker
|
0677ec1757c33aaddd013eb0a65481c3aca25881
|
[
"MIT"
] | 2
|
2021-05-17T16:26:00.000Z
|
2021-05-31T15:06:48.000Z
|
if __name__ == '__main__':
from check_env import check_env
check_env()
from ant_tracker.labeler.AntLabeler import main
main()
| 18
| 51
| 0.701389
| 19
| 144
| 4.684211
| 0.578947
| 0.269663
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 144
| 7
| 52
| 20.571429
| 0.794643
| 0
| 0
| 0
| 0
| 0
| 0.055556
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a362095e7cc5d8fcee1e294e2eca714ed1a78de1
| 261
|
py
|
Python
|
toontown/classicchars/DistributedWitchMinnieAI.py
|
TheFamiliarScoot/open-toontown
|
678313033174ea7d08e5c2823bd7b473701ff547
|
[
"BSD-3-Clause"
] | 99
|
2019-11-02T22:25:00.000Z
|
2022-02-03T03:48:00.000Z
|
toontown/classicchars/DistributedWitchMinnieAI.py
|
TheFamiliarScoot/open-toontown
|
678313033174ea7d08e5c2823bd7b473701ff547
|
[
"BSD-3-Clause"
] | 42
|
2019-11-03T05:31:08.000Z
|
2022-03-16T22:50:32.000Z
|
toontown/classicchars/DistributedWitchMinnieAI.py
|
TheFamiliarScoot/open-toontown
|
678313033174ea7d08e5c2823bd7b473701ff547
|
[
"BSD-3-Clause"
] | 57
|
2019-11-03T07:47:37.000Z
|
2022-03-22T00:41:49.000Z
|
from direct.directnotify import DirectNotifyGlobal
from direct.distributed.DistributedObjectAI import DistributedObjectAI
class DistributedWitchMinnieAI(DistributedObjectAI):
notify = DirectNotifyGlobal.directNotify.newCategory('DistributedWitchMinnieAI')
| 43.5
| 84
| 0.881226
| 19
| 261
| 12.105263
| 0.578947
| 0.086957
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 261
| 5
| 85
| 52.2
| 0.946502
| 0
| 0
| 0
| 0
| 0
| 0.091954
| 0.091954
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a363f9c3fc68fd8a97ccc6cbf62737947d3112f7
| 101
|
py
|
Python
|
useless_bot/core/errors.py
|
MRvillager/useless_bot
|
68ee1a73d7f0ac4d041d96a02d93feae17194980
|
[
"MIT"
] | null | null | null |
useless_bot/core/errors.py
|
MRvillager/useless_bot
|
68ee1a73d7f0ac4d041d96a02d93feae17194980
|
[
"MIT"
] | null | null | null |
useless_bot/core/errors.py
|
MRvillager/useless_bot
|
68ee1a73d7f0ac4d041d96a02d93feae17194980
|
[
"MIT"
] | null | null | null |
class BalanceUnderLimitError(Exception):
pass
class BalanceOverLimitError(Exception):
pass
| 14.428571
| 40
| 0.782178
| 8
| 101
| 9.875
| 0.625
| 0.329114
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.158416
| 101
| 6
| 41
| 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 | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
a385f0d4c253e6d4d9e211e9e4c475f6dde69b65
| 60
|
py
|
Python
|
fixup.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | null | null | null |
fixup.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | null | null | null |
fixup.py
|
catskillsresearch/openasr20
|
b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e
|
[
"Apache-2.0"
] | 1
|
2021-07-28T02:13:21.000Z
|
2021-07-28T02:13:21.000Z
|
def fixup(fn):
return '_'.join(fn.split('_')[2:])[0:-4]
| 20
| 44
| 0.533333
| 10
| 60
| 3
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.057692
| 0.133333
| 60
| 2
| 45
| 30
| 0.519231
| 0
| 0
| 0
| 0
| 0
| 0.033333
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
6e5e704f15f892f1fc97aeee5f6c656f71d7539d
| 122
|
py
|
Python
|
u8timeseries/metrics/__init__.py
|
endrjuskr/u8timeseries
|
edf167815e7c7931fe491207f831e88203589883
|
[
"Apache-2.0"
] | null | null | null |
u8timeseries/metrics/__init__.py
|
endrjuskr/u8timeseries
|
edf167815e7c7931fe491207f831e88203589883
|
[
"Apache-2.0"
] | null | null | null |
u8timeseries/metrics/__init__.py
|
endrjuskr/u8timeseries
|
edf167815e7c7931fe491207f831e88203589883
|
[
"Apache-2.0"
] | null | null | null |
"""
Metrics
-------
"""
from .metrics import mape, mase, overall_percentage_error, marre, r2_score, coefficient_variation
| 20.333333
| 97
| 0.737705
| 14
| 122
| 6.142857
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009174
| 0.106557
| 122
| 5
| 98
| 24.4
| 0.779817
| 0.122951
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
6e67f9d768ae90edd8b6834d0880a6784dd47aaf
| 144
|
py
|
Python
|
xv_leak_tools/test_components/cleanup/__init__.py
|
UAEKondaya1/expressvpn_leak_testing
|
9e4cee899ac04f7820ac351fa55efdc0c01370ba
|
[
"MIT"
] | 219
|
2017-12-12T09:42:46.000Z
|
2022-03-13T08:25:13.000Z
|
xv_leak_tools/test_components/cleanup/__init__.py
|
UAEKondaya1/expressvpn_leak_testing
|
9e4cee899ac04f7820ac351fa55efdc0c01370ba
|
[
"MIT"
] | 11
|
2017-12-14T08:14:51.000Z
|
2021-08-09T18:37:45.000Z
|
xv_leak_tools/test_components/cleanup/__init__.py
|
UAEKondaya1/expressvpn_leak_testing
|
9e4cee899ac04f7820ac351fa55efdc0c01370ba
|
[
"MIT"
] | 45
|
2017-12-14T07:26:36.000Z
|
2022-03-11T09:36:56.000Z
|
from xv_leak_tools.test_components.cleanup.cleanup_builder import CleanupBuilder
def register(factory):
factory.register(CleanupBuilder())
| 28.8
| 80
| 0.840278
| 17
| 144
| 6.882353
| 0.764706
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 144
| 4
| 81
| 36
| 0.886364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
6e8771c85b231a21b4943a32e3e23e07397eddbb
| 182
|
py
|
Python
|
Inheritance/non_zip_files/04_random_list.py
|
MNikov/Python-OOP-October-2020
|
a53e4555758ec810605e31e7b2c71b65c49b2332
|
[
"MIT"
] | null | null | null |
Inheritance/non_zip_files/04_random_list.py
|
MNikov/Python-OOP-October-2020
|
a53e4555758ec810605e31e7b2c71b65c49b2332
|
[
"MIT"
] | null | null | null |
Inheritance/non_zip_files/04_random_list.py
|
MNikov/Python-OOP-October-2020
|
a53e4555758ec810605e31e7b2c71b65c49b2332
|
[
"MIT"
] | null | null | null |
import random
class RandomList(list):
def get_random_element(self):
element_to_go = random.choice(self)
self.remove(element_to_go)
return element_to_go
| 20.222222
| 43
| 0.697802
| 25
| 182
| 4.76
| 0.56
| 0.226891
| 0.277311
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.230769
| 182
| 8
| 44
| 22.75
| 0.85
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
6e8bbc2c0465009b320b5b8d4044c38a2e460462
| 211
|
wsgi
|
Python
|
AutoProject.wsgi
|
dimas-lex/autostop
|
f8bb081d1c6f9b650424dd4326152de150901509
|
[
"Apache-2.0"
] | null | null | null |
AutoProject.wsgi
|
dimas-lex/autostop
|
f8bb081d1c6f9b650424dd4326152de150901509
|
[
"Apache-2.0"
] | null | null | null |
AutoProject.wsgi
|
dimas-lex/autostop
|
f8bb081d1c6f9b650424dd4326152de150901509
|
[
"Apache-2.0"
] | null | null | null |
import os
import sys
sys.path.append('/home/yana/code/autostop')
os.environ['DJANGO_SETTINGS_MODULE'] = 'autostop.settings'
import django.core.handlers.wsgi
application = django.core.handlers.wsgi.WSGIHandler()
| 30.142857
| 58
| 0.800948
| 29
| 211
| 5.758621
| 0.62069
| 0.11976
| 0.215569
| 0.263473
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.061611
| 211
| 6
| 59
| 35.166667
| 0.843434
| 0
| 0
| 0
| 0
| 0
| 0.298578
| 0.218009
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
6ec4ea42c86a3852801272b0ed42cb6e80ffdc10
| 43
|
py
|
Python
|
tuomur/python-odata/example.py
|
Sam-Rowe/AzureDevOpsODataDemo
|
6e97b5a1026c2d921603aee8ece319bacf4754e1
|
[
"MIT"
] | null | null | null |
tuomur/python-odata/example.py
|
Sam-Rowe/AzureDevOpsODataDemo
|
6e97b5a1026c2d921603aee8ece319bacf4754e1
|
[
"MIT"
] | 1
|
2020-02-26T11:08:40.000Z
|
2020-02-26T11:35:08.000Z
|
tuomur/python-odata/example.py
|
Sam-Rowe/AzureDevOpsODataDemo
|
6e97b5a1026c2d921603aee8ece319bacf4754e1
|
[
"MIT"
] | null | null | null |
import os
import requests
from python-odata
| 14.333333
| 17
| 0.860465
| 7
| 43
| 5.285714
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 43
| 3
| 17
| 14.333333
| 0.973684
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.666667
| null | null | 0
| 1
| 1
| 0
| null | 0
| 0
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| 0
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| null | 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
42d936747c949e75848c382b5256b19ddf438508
| 119
|
py
|
Python
|
Users/admin.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | 2
|
2021-11-04T01:51:11.000Z
|
2021-11-23T13:21:01.000Z
|
Users/admin.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | null | null | null |
Users/admin.py
|
mangonihao/MovieRecommendWeb
|
b612fcda68bf5f8b1f2734c138e3204119a78596
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from Users.models import User
# Register your models here.
admin.site.register(User)
| 19.833333
| 32
| 0.806723
| 18
| 119
| 5.333333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12605
| 119
| 5
| 33
| 23.8
| 0.923077
| 0.218487
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
42e702958e3b02cb77c46424d467b3b66cced843
| 55
|
py
|
Python
|
b2btool/__main__.py
|
recs12/b2btool
|
37108c856f1be399b2b90c31ee90afa5b828481f
|
[
"Apache-2.0",
"MIT"
] | null | null | null |
b2btool/__main__.py
|
recs12/b2btool
|
37108c856f1be399b2b90c31ee90afa5b828481f
|
[
"Apache-2.0",
"MIT"
] | null | null | null |
b2btool/__main__.py
|
recs12/b2btool
|
37108c856f1be399b2b90c31ee90afa5b828481f
|
[
"Apache-2.0",
"MIT"
] | null | null | null |
import sys
from b2btool.cli import b2b
sys.exit(b2b())
| 13.75
| 27
| 0.763636
| 10
| 55
| 4.2
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0625
| 0.127273
| 55
| 3
| 28
| 18.333333
| 0.8125
| 0
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| 0
| 0
| 0
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| 0
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| 0
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| 0
| true
| 0
| 0.666667
| 0
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| 0
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| null | 0
| 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
42ff86dc0db909d99721dbf5da4c5630bc3e2387
| 141
|
py
|
Python
|
Computer-vision/@PeterChenYijie AIChallenger-ScenesClassfication-pytorch/models/loss.py
|
PeterChenYijie/DeepLearningZeroToALL
|
8f629e326a84a4272e66f34ba5f918576a595c70
|
[
"MIT"
] | 12
|
2018-03-07T00:44:56.000Z
|
2019-01-25T11:07:43.000Z
|
Computer-vision/@PeterChenYijie AIChallenger-ScenesClassfication-pytorch/models/loss.py
|
PeterChenYijie/DeepLearning
|
8f629e326a84a4272e66f34ba5f918576a595c70
|
[
"MIT"
] | 3
|
2018-03-02T03:38:41.000Z
|
2018-03-20T00:45:06.000Z
|
Computer-vision/@PeterChenYijie AIChallenger-ScenesClassfication-pytorch/models/loss.py
|
PeterChenYijie/DeepLearning
|
8f629e326a84a4272e66f34ba5f918576a595c70
|
[
"MIT"
] | 7
|
2018-03-02T07:14:53.000Z
|
2019-01-04T08:06:47.000Z
|
#coding:utf8
import torch as t
def celoss():
return t.nn.CrossEntropyLoss()
def bloss():
def loss(s,l):
pass
return loss
| 15.666667
| 34
| 0.631206
| 21
| 141
| 4.238095
| 0.761905
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009524
| 0.255319
| 141
| 9
| 35
| 15.666667
| 0.838095
| 0.078014
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| false
| 0.142857
| 0.142857
| 0.142857
| 0.857143
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
|
0
| 5
|
6e0e3a517a3e35c01df747cc2e4d02460481d0c0
| 212
|
py
|
Python
|
vetclinic/fields.py
|
drewbrew/djangoconus2018-drf-talk
|
cf28b85db1dce86b959cbd1c7eb1abbc5492c63b
|
[
"MIT"
] | 6
|
2018-10-17T20:55:00.000Z
|
2022-02-07T16:59:34.000Z
|
vetclinic/fields.py
|
hadpro24/djangoconus2018-drf-talk
|
13d479ded2c4ed64502b1e707230a19ca1405ab8
|
[
"MIT"
] | 5
|
2019-05-30T13:00:57.000Z
|
2021-03-20T00:38:30.000Z
|
vetclinic/fields.py
|
hadpro24/djangoconus2018-drf-talk
|
13d479ded2c4ed64502b1e707230a19ca1405ab8
|
[
"MIT"
] | 2
|
2019-02-24T21:31:22.000Z
|
2019-03-26T12:59:33.000Z
|
from rest_framework import serializers
from .models import Species
class SpeciesField(serializers.PrimaryKeyRelatedField):
def to_representation(self, value):
return Species.objects.get(id=value)
| 21.2
| 55
| 0.787736
| 24
| 212
| 6.875
| 0.791667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146226
| 212
| 9
| 56
| 23.555556
| 0.911602
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
6e12bff6ccd73b223b53343e902188613156a738
| 149
|
py
|
Python
|
test_python_starter/__main__.py
|
GregoireHENRY/test-python-starter
|
0519aca1ce6642398d624f7f754e41b581e28e45
|
[
"MIT"
] | null | null | null |
test_python_starter/__main__.py
|
GregoireHENRY/test-python-starter
|
0519aca1ce6642398d624f7f754e41b581e28e45
|
[
"MIT"
] | null | null | null |
test_python_starter/__main__.py
|
GregoireHENRY/test-python-starter
|
0519aca1ce6642398d624f7f754e41b581e28e45
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
"""
test-python-starter
"""
from pudb import set_trace as bp # noqa: F401
from test_python_starter import cli
cli.main()
| 12.416667
| 46
| 0.718121
| 24
| 149
| 4.333333
| 0.75
| 0.192308
| 0.326923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.032
| 0.161074
| 149
| 11
| 47
| 13.545455
| 0.8
| 0.348993
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
280d88d0661a5c02db94a1eb5d8c04a4b0ebd3d2
| 59
|
py
|
Python
|
app/schemas/__init__.py
|
somespecialone/clever-inspect
|
8735e0b445c8e7e9b83c627d4a5fbed1428c1891
|
[
"MIT"
] | 1
|
2022-03-12T05:44:12.000Z
|
2022-03-12T05:44:12.000Z
|
app/schemas/__init__.py
|
somespecialone/clever-inspect
|
8735e0b445c8e7e9b83c627d4a5fbed1428c1891
|
[
"MIT"
] | null | null | null |
app/schemas/__init__.py
|
somespecialone/clever-inspect
|
8735e0b445c8e7e9b83c627d4a5fbed1428c1891
|
[
"MIT"
] | null | null | null |
from .item import Item, ItemRaw
from .health import Health
| 19.666667
| 31
| 0.79661
| 9
| 59
| 5.222222
| 0.555556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152542
| 59
| 2
| 32
| 29.5
| 0.94
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
28111d8e151625c577f08665369ecf53fcdeee10
| 133
|
py
|
Python
|
cowsay_app/admin.py
|
Sondosissa18/-django-cowsay-project
|
50307cfeacef9e6f7fb9304b479c8a53ac451c77
|
[
"MIT"
] | null | null | null |
cowsay_app/admin.py
|
Sondosissa18/-django-cowsay-project
|
50307cfeacef9e6f7fb9304b479c8a53ac451c77
|
[
"MIT"
] | null | null | null |
cowsay_app/admin.py
|
Sondosissa18/-django-cowsay-project
|
50307cfeacef9e6f7fb9304b479c8a53ac451c77
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from cowsay_app.models import Cowtext
admin.site.register(Cowtext)
| 14.777778
| 37
| 0.804511
| 19
| 133
| 5.578947
| 0.684211
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135338
| 133
| 8
| 38
| 16.625
| 0.921739
| 0.195489
| 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
| 1
| 0
|
0
| 5
|
28369ed13c7ba2e8cde482adfd8c56208890084a
| 206
|
py
|
Python
|
test_awsimple/__init__.py
|
jamesabel/awsimple
|
1b5d22a4e236421229e2fc8aee3a683066bb16c6
|
[
"MIT"
] | 21
|
2020-08-28T19:10:36.000Z
|
2021-06-17T02:25:30.000Z
|
test_awsimple/__init__.py
|
jamesabel/awsimple
|
1b5d22a4e236421229e2fc8aee3a683066bb16c6
|
[
"MIT"
] | 1
|
2021-03-01T18:40:58.000Z
|
2021-03-02T04:37:05.000Z
|
test_awsimple/__init__.py
|
jamesabel/awsimple
|
1b5d22a4e236421229e2fc8aee3a683066bb16c6
|
[
"MIT"
] | 1
|
2020-08-28T23:07:21.000Z
|
2020-08-28T23:07:21.000Z
|
from .const import id_str, test_awsimple_str, never_change_file_name, never_change_file_size
from .tst_paths import temp_dir, cache_dir
from .dict_is_close import dict_is_close
from .sqs_drain import drain
| 41.2
| 92
| 0.864078
| 37
| 206
| 4.351351
| 0.594595
| 0.136646
| 0.186335
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097087
| 206
| 4
| 93
| 51.5
| 0.865591
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
286aded94f88bfd5ad6d18015415936cdfc323c6
| 141
|
py
|
Python
|
titan/react_view_pkg/router_and_module/resources.py
|
mnieber/gen
|
65f8aa4fb671c4f90d5cbcb1a0e10290647a31d9
|
[
"MIT"
] | null | null | null |
titan/react_view_pkg/router_and_module/resources.py
|
mnieber/gen
|
65f8aa4fb671c4f90d5cbcb1a0e10290647a31d9
|
[
"MIT"
] | null | null | null |
titan/react_view_pkg/router_and_module/resources.py
|
mnieber/gen
|
65f8aa4fb671c4f90d5cbcb1a0e10290647a31d9
|
[
"MIT"
] | null | null | null |
from dataclasses import dataclass
from moonleap import Resource
@dataclass
class RouteTable(Resource):
import_path: str
name: str
| 14.1
| 33
| 0.77305
| 17
| 141
| 6.352941
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.184397
| 141
| 9
| 34
| 15.666667
| 0.93913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
2884b5ed9a5025aa6b381268ee5d8038f8269b69
| 143
|
py
|
Python
|
src/cs107_package/subpkg_1/module_1.py
|
cs107-sys-dev/cs107_project
|
dbffc4937b9e7c88c5488104b3da480af2018662
|
[
"MIT"
] | null | null | null |
src/cs107_package/subpkg_1/module_1.py
|
cs107-sys-dev/cs107_project
|
dbffc4937b9e7c88c5488104b3da480af2018662
|
[
"MIT"
] | null | null | null |
src/cs107_package/subpkg_1/module_1.py
|
cs107-sys-dev/cs107_project
|
dbffc4937b9e7c88c5488104b3da480af2018662
|
[
"MIT"
] | null | null | null |
class Foo:
def __init__(self, a, b):
self.a = a
self.b = b
def foo():
return "cs107_package.subpkg_1.module_1.foo()"
| 15.888889
| 50
| 0.566434
| 23
| 143
| 3.217391
| 0.565217
| 0.135135
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049505
| 0.293706
| 143
| 8
| 51
| 17.875
| 0.683168
| 0
| 0
| 0
| 0
| 0
| 0.258741
| 0.258741
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.166667
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
288f67c96f48bc7da5624b05eb7ac65482b731a1
| 155
|
py
|
Python
|
piptools/locations.py
|
m-mead/pip-tools
|
37ce9e36d6033ede0667a1b293cd16843a85be4d
|
[
"BSD-3-Clause"
] | 4,085
|
2017-02-17T08:51:25.000Z
|
2022-03-31T22:44:12.000Z
|
piptools/locations.py
|
m-mead/pip-tools
|
37ce9e36d6033ede0667a1b293cd16843a85be4d
|
[
"BSD-3-Clause"
] | 1,173
|
2017-02-17T16:50:44.000Z
|
2022-03-31T20:14:19.000Z
|
piptools/locations.py
|
astrojuanlu/pip-tools
|
4776ac99fb8a396f6d2ed1a4370fd3b2e6875940
|
[
"BSD-3-Clause"
] | 351
|
2017-02-17T17:33:08.000Z
|
2022-03-30T13:33:38.000Z
|
from pip._internal.utils.appdirs import user_cache_dir
# The user_cache_dir helper comes straight from pip itself
CACHE_DIR = user_cache_dir("pip-tools")
| 31
| 58
| 0.825806
| 26
| 155
| 4.615385
| 0.576923
| 0.266667
| 0.3
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0.109677
| 155
| 4
| 59
| 38.75
| 0.869565
| 0.36129
| 0
| 0
| 0
| 0
| 0.092784
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| false
| 0
| 0.5
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| 0
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| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
28943f8da35e0795836815f902d2f3764c81cdcc
| 77
|
py
|
Python
|
surgen/tests/procedures/02_example.py
|
toumorokoshi/surgen
|
9a5028e464c5a27acb4d240fd4340e3485833896
|
[
"MIT"
] | 6
|
2017-04-11T16:34:06.000Z
|
2019-06-25T15:37:44.000Z
|
surgen/tests/procedures/02_example.py
|
toumorokoshi/surgen
|
9a5028e464c5a27acb4d240fd4340e3485833896
|
[
"MIT"
] | 2
|
2019-06-25T17:23:37.000Z
|
2019-06-28T20:00:27.000Z
|
surgen/tests/procedures/02_example.py
|
toumorokoshi/surgen
|
9a5028e464c5a27acb4d240fd4340e3485833896
|
[
"MIT"
] | 3
|
2017-06-22T20:41:54.000Z
|
2019-06-25T15:30:00.000Z
|
from surgen.procedure import Procedure
class Example2(Procedure):
pass
| 12.833333
| 38
| 0.779221
| 9
| 77
| 6.666667
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015625
| 0.168831
| 77
| 5
| 39
| 15.4
| 0.921875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
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| null | 0
| 0
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| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
9537124e9309017ce6ef7eba0836e087b8d3becf
| 110
|
py
|
Python
|
RPIO_Test.py
|
tuliptrader/Raspberry-Pi-Drone
|
0087227171d9c592926190c4d7a184298ae975e4
|
[
"MIT"
] | 1
|
2019-01-05T13:12:35.000Z
|
2019-01-05T13:12:35.000Z
|
RPIO_Test.py
|
tuliptrader/Raspberry-Pi-Drone
|
0087227171d9c592926190c4d7a184298ae975e4
|
[
"MIT"
] | null | null | null |
RPIO_Test.py
|
tuliptrader/Raspberry-Pi-Drone
|
0087227171d9c592926190c4d7a184298ae975e4
|
[
"MIT"
] | 1
|
2018-09-11T09:46:46.000Z
|
2018-09-11T09:46:46.000Z
|
from RPIO import PWM
servo = PWM.Servo()
While True:
servo.set_servo(13, 1200)
servo.set_servo(27, 1200)
| 15.714286
| 27
| 0.718182
| 19
| 110
| 4.052632
| 0.578947
| 0.207792
| 0.337662
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130435
| 0.163636
| 110
| 6
| 28
| 18.333333
| 0.706522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.2
| null | null | 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
9591530c0837d163ccd2c50a55b5c029226e81d9
| 105
|
py
|
Python
|
office365/sharepoint/sitedesigns/site_script_metadata.py
|
theodoriss/Office365-REST-Python-Client
|
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
|
[
"MIT"
] | 544
|
2016-08-04T17:10:16.000Z
|
2022-03-31T07:17:20.000Z
|
office365/sharepoint/sitedesigns/site_script_metadata.py
|
theodoriss/Office365-REST-Python-Client
|
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
|
[
"MIT"
] | 438
|
2016-10-11T12:24:22.000Z
|
2022-03-31T19:30:35.000Z
|
office365/sharepoint/sitedesigns/site_script_metadata.py
|
theodoriss/Office365-REST-Python-Client
|
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
|
[
"MIT"
] | 202
|
2016-08-22T19:29:40.000Z
|
2022-03-30T20:26:15.000Z
|
from office365.runtime.client_value import ClientValue
class SiteScriptMetadata(ClientValue):
pass
| 17.5
| 54
| 0.828571
| 11
| 105
| 7.818182
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.032609
| 0.12381
| 105
| 5
| 55
| 21
| 0.902174
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
95ab70151a5d09b582d1e6876f4eca596cc7474c
| 16,174
|
py
|
Python
|
spearmint/transformations/demos/bibeta/gb2library.py
|
fernandezdaniel/Spearmint
|
3c9e0a4be6108c3d652606bd957f0c9ae1bfaf84
|
[
"RSA-MD"
] | 6
|
2021-06-29T11:26:49.000Z
|
2022-01-20T18:12:47.000Z
|
spearmint/transformations/demos/bibeta/gb2library.py
|
fernandezdaniel/Spearmint
|
3c9e0a4be6108c3d652606bd957f0c9ae1bfaf84
|
[
"RSA-MD"
] | null | null | null |
spearmint/transformations/demos/bibeta/gb2library.py
|
fernandezdaniel/Spearmint
|
3c9e0a4be6108c3d652606bd957f0c9ae1bfaf84
|
[
"RSA-MD"
] | 9
|
2018-06-28T13:06:35.000Z
|
2021-06-20T18:21:58.000Z
|
from __future__ import division
import scipy as sp
import numpy as np
from scipy.special import beta, gamma, betaln, gammaln, betainc, gammainc, erf
import matplotlib.pyplot as plt
from scipy.special import betaln, gammaln, beta, gamma, betainc, gammainc
from scipy import optimize as opt
class Gb(object):
def __init__(self, a, b, c, p, q):
self.a = a
self.b = b
self.c = c
self.p = p
self.q = q
def pdf(self, y):
a = self.a
b = self.b
c = self.c
p = self.p
q = self.q
bta = np.exp(gammaln(p)+gammaln(q) - gammaln(p+q))
pdf = abs(a)*y**(a*p-1)*(1-(1-c)*(y/b)**a)**(q-1) / (b**(a*p)*bta*(1+c*(y/b)**a)**(p+q))
return pdf
def mom(self, h):
a = self.a
b = self.b
c = self.c
p = self.p
q = self.q
bta = np.exp(gammaln(p) + gammaln(q) - gammaln(p+q))
pass
class Gb1(Gb):
def __init__(self, a, b, p, q):
self.a = a
self.b = b
self.c = 0
self.p = p
self.q = q
def cdf(self, y):
a = self.a
b = self.b
c = self.c
p = self.p
q = self.q
z = (y/b)**a
cdf = betainc(p, q, z)
return cdf
def mom(self, h):
a = self.a
b = self.b
c = self.c
p = self.p
q = self.q
mom = np.exp(h*np.log(b) + gammaln(p+q) + gammaln(p + h/a) - gammaln(p + q + h/a) - gammaln(p))
return mom
def mean(self):
mean = self.mom(1)
return mean
def std(self):
var = self.mom(2) - (self.mom(1))**2
std = var**(1/2)
return std
def skew(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
var = (self.std())**2
skew = (mom3 - 3*mom1*mom2 + 2*mom1**3)/(var)**(3/2)
return skew
def kurt(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
mom4 = self.mom(4)
var = (self.std())**2
kurtosis = (mom4 - 4*mom1*mom3 + 6*mom1**2*mom2 - 3*mom1**4) / var**2
return kurtosis
def loglike(self, data, paravec_log, sign = 1):
a, b, p, q = np.exp(paravec_log)
n = len(data)
lnb = gammaln(p) + gammaln(q) - gammaln(p+q)
loglike = n*np.log(abs(a)) + (a*p-1)*np.sum(np.log(data)) + \
(q-1)*np.sum(np.log(1-(data/b)**a)) - n*a*p*np.log(b) - n*lnb
loglike = sign*loglike
return loglike
class B1(Gb1):
def __init__(self, b, p, q):
self.a = 1
self.c = 0
self.b = b
self.p = p
self.q = q
def loglike(self, data, paravec_log, sign = 1):
a = 1
b, p, q = np.exp(paravec_log)
n = len(data)
lnb = gammaln(p) + gammaln(q) - gammaln(p+q)
loglike = n*np.log(abs(a)) + (a*p-1)*np.sum(np.log(data)) + \
(q-1)*np.sum(np.log(1-(data/b)**a)) - n*a*p*np.log(b) - n*lnb
loglike = sign*loglike
return loglike
class Pareto(Gb1):
def __init__(self, b, p):
self.a = -1
self.q = 1
self.c = 0
self.b = b
self.p = p
def cdf(self, y):
b = self.b
p = self.p
if len(y) > 1:
cdf = np.zeros(len(y))
ind1 = y >= b
cdf[ind1] = 1 - (b/y[ind1])** p
elif len(y) == 1:
if y >= b:
cdf = 1 - (b/y)**p
elif y<b:
cdf = 0
return cdf
def loglike(self, data, paravec, sign = 1):
#we are not taking the log of the paramters, because in this case, a = -1, so
#it doesn't have to be constrained to be positive.
n = len(data)
a = -1
q = 1
b, p = paravec
loglike = n*sp.log(np.exp(a)) + (np.exp(a)*np.exp(p)-1)*np.sum(data) + \
(np.exp(q)-1)*np.sum(1-(data/np.exp(b))**np.exp(a)) - n*np.exp(a)*np.exp(p)*np.log(b)\
- n*betaln(np.exp(p), np.exp(q))
loglike = sign*loglike
return loglike
class B(Gb):
def __init__(self, b, c, p, q):
self.a = 1
self.b = b
self.c = c
self.p = p
self.q = q
def mom(self, h):
a = self.a
b = self.b
c = self.c
p = self.p
q = self.q
pass
#Does the beta function have moments?
def cdf(self, h):
pass
#does the beta have a cdf?
class Gb2(object):
def __init__(self, a, b, p, q):
self.a = a
self.b = b
self.p = p
self.q = q
def pdf(self, y):
a = self.a
b = self.b
p = self.p
q = self.q
bta = np.exp(gammaln(p) + gammaln(q) - gammaln(p+q))
pdf = np.exp(np.log(abs(a)) + (a*p - 1)*np.log(y)- (a*p)*np.log(b)\
- np.log(bta) - (p+q)*np.log((1 + (y/b)**a)))
return pdf
def cdf(self, y):
a = self.a
b = self.b
p = self.p
q = self.q
z = np.exp(a * np.log((y/b)) - a*np.log(1 + (y/b)))
cdf = betainc(p, q, z)
return cdf
def mom(self, h):
"""
Gives us the moments about zero. We will used these in our calculations of the moments
around the mean
h is the moment we would like
"""
a = self.a
b = self.b
p = self.p
q = self.q
mom = np.exp(h*np.log(b) + gammaln(p + h/a) + gammaln(q - h/a) - gammaln(p) - gammaln(q))
return mom
def mean(self):
a = self.a
b = self.b
p = self.p
q = self.q
mean = self.mom(1)
return mean
def std(self):
a = self.a
b = self.b
p = self.p
q = self.q
mom2 = self.mom(2)
ex = self.mom(1)
var = mom2 - ex**2
std = var**(1/2)
return std
def skew(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
var = (self.std())**2
skew = (mom3 - 3*mom1*mom2 + 2*mom1**3)/(var)**(3/2)
return skew
def kurt(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
mom4 = self.mom(4)
var = (self.std())**2
kurtosis = (mom4 - 4*mom1*mom3 + 6*mom1**2*mom2 - 3*mom1**4) / var**2
return kurtosis
def loglike(self, data, paravec, sign = 1):
"""
The sign option allows for the function to return the negative of the log-likelihood
so that it can be estimated using minization libraries of python.
The parameters must come in as logs.
"""
la, lb, lp, lq = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class B2(Gb2):
def __init__(self, b, p, q):
self.a = 1
self.b = b
self.p = p
self.q = q
def loglike(self, data, paravec, sign = 1):
la = 0
lb, lp, lq = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class Br12(Gb2):
def __init__(self, a, b, q):
self.p = 1
self.a = a
self.b = b
self.q = q
def loglike(self, data, paravec, sign = 1):
lp = 0
la, lb, lq = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class Br3(Gb2):
def __init__(self, a, b, p):
self.q = 1
self.a = a
self.b = b
self.p = p
def loglike(self, data, paravec, sign = 1):
lq = 0
la, lb, lp = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class L(Gb2):
def __init__(self, b, q):
self.a = 1
self.p = 1
self.b = b
self.q = q
def loglike(self, data, paravec, sign = 1):
la, lp = 0, 0
lb, lq = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class InvL(Gb2):
def __init__(self, b, q):
self.a = -1
self.p = 1
self.b = b
self.q = q
def loglike(self, data, paravec, sign = 1):
a, p = - 1, 1
b, q = paravec
loglike = len(data) * sp.log(np.exp(a)) + (np.exp(a)*np.exp(p)-1) * sum(sp.log(data)) \
- len(data)*np.exp(a)*np.exp(p)*sp.log(np.exp(b)) - len(data) * betaln(np.exp(p), np.exp(q)) -\
(np.exp(p)+np.exp(q)) * sum(sp.log(1+(data/np.exp(b))**np.exp(a)))
loglike = sign*loglike
return loglike
class Fisk(Gb2):
def __init__(self, a, b):
self.p = 1
self.q = 1
self.a = a
self.b = b
def loglike(self, data, paravec, sign = 1):
lp, lq = 0, 0
la, lb = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class LogLog(Gb2):
def __init__(self, b):
self.a = 1
self.p = 1
self.q = 1
self.b = b
def loglike(self, data, paravec, sign = 1):
la, lp, lq = 0, 0, 0
lb = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) \
- len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * betaln(np.exp(lp), np.exp(lq)) -\
(np.exp(lp)+np.exp(lq)) * sum(sp.log(1+(data/np.exp(lb))**np.exp(la)))
loglike = sign*loglike
return loglike
class Gg(object):
def __init__(self, a, b, p):
self.a = a
self.b = b
self.p = p
def pdf(self, y):
a = self.a
b = self.b
p = self.p
pdf = abs(a)*y**(a*p-1)*np.exp(-(y/b)*a)/ (b**(a*p)*gamma(p))
return pdf
def cdf(self, y):
a = self.a
b = self.b
p = self.p
z = (y/b)**a
cdf = gammainc(p, z)
return cdf
def mean(self):
a = self.a
b = self.b
p = self.p
mean = b* gamma(p + 1/a)/gamma(p)
return mean
def std(self):
a = self.a
b = self.b
p = self.p
mom2 = b**2*gamma(p + 2/a)/gamma(p)
var = mom2 - (self.mean())**2
std = var**(1/2)
return std
def skew(self):
a = self.a
b = self.b
p = self.p
g0 = gamma(p)
g1 = gamma(p + 1/a)
g2 = gamma(p + 2/a)
g3 = gamma(p + 3/a)
skew = (g0**2*g3 - 3*g0*g1*g2 + 2*g1**3)/(g0*g2 - g1**2)**(3/2)
return skew
def kurt(self):
a = self.a
b = self.b
p = self.p
g0 = gamma(p)
g1 = gamma(p + 1/a)
g2 = gamma(p + 2/a)
g3 = gamma(p + 3/a)
g4 = gamma(p + 4/a)
kurt = (g0**3*g4 - 4*g0**2*g1*g3 + 6*g0*g1**2*g2 - 3*g1**4)/(g0*g2 - g1**2)**2
return kurt
def loglike(self, data, paravec, sign = 1):
la, lb, lp = paravec
loglike = len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) - (1/np.exp(lb)**np.exp(la)) * sum(data**np.exp(la))\
-len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * gammaln(np.exp(lp))
loglike = sign*loglike
return loglike
#I'm writing the below function so we don't have to copy and paste the loglike so much
def loglike_param(self, data, la, lb, lp, sign = 1):
ll =len(data) * sp.log(np.exp(la)) + (np.exp(la)*np.exp(lp)-1) * sum(sp.log(data)) - (1/np.exp(lb)**np.exp(la)) * sum(data**np.exp(la))\
-len(data)*np.exp(la)*np.exp(lp)*sp.log(np.exp(lb)) - len(data) * gammaln(np.exp(lp))
ll = sign*ll
return ll
class Ga(Gg):
def __init__(self, b, p):
self.a = 1
self.b = b
self.p = p
def loglike(self, data, paravec, sign = 1):
la = 0
lb, lp = paravec
ll = self.loglike_param(data, la, lb, lp, sign)
return ll
class W(Gg):
def __init__(self, a, b):
self.p = 1
self.a = a
self.b = b
# super(W, self).__init__(a, b, self.p)
def loglike(self, data, paravec, sign = 1):
lp = 0
la, lb = paravec
ll = self.loglike_param(data, la, lb, lp, sign)
return ll
class Chi2(Gg):
def __init__(self, p):
self.a = 1
self.b = 2
self.p = p
# super(Chi2, self).__init__(self.a, self.b, p)
def loglike(self, data, paravec, sign = 1):
la, lb = 0, np.log(2)
lp = paravec
ll = self.loglike_param(data, la, lb, lp, sign)
return ll
class Exp(Gg):
def __init__(self, b):
self.a = 1
self.p = 1
# super(Exp, self).__init__(self.a, b, self.p)
self.b = b
def loglike(self, data, paravec, sign = 1):
la, lp = 0, 0
lb = paravec
ll = self.loglike_param(data, la, lb, lp, sign)
return ll
class Ln(object):
def __init__(self, u, sig):
self.u = u
self.sig = sig
def pdf(self, y):
u = self.u
sig = self.sig
pdf = 1/(y*sig*(2*np.pi)**(1/2)) * np.exp(-(np.log(y) - u)**2 / (2*sig**2))
return pdf
def cdf(self, y):
u = self.u
sig = self.sig
z = (np.log(y) - u)/(sig*2**(1/2))
cdf = (1/2)*(1 + erf(z))
return cdf
def mom(self, h):
u = self.u
sig = self.sig
mom = np.exp(h*u + h**2*sig**2/2)
return mom
def mean(self):
mean = self.mom(1)
return mean
def std(self):
var = self.mom(2) - self.mom(1)**2
std = var**(1/2)
return std
def skew(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
var = (self.std())**2
skew = (mom3 - 3*mom1*mom2 + 2*mom1**3)/(var)**(3/2)
return skew
def kurt(self):
mom1 = self.mom(1)
mom2 = self.mom(2)
mom3 = self.mom(3)
mom4 = self.mom(4)
var = (self.std())**2
kurtosis = (mom4 - 4*mom1*mom3 + 6*mom1**2*mom2 - 3*mom1**4) / var**2
return kurtosis
def loglike(self, data, paravec, sign = 1):
lu, lsig = paravec
loglike = (-1/(2*np.exp(lsig)**2)) * sum((sp.log(data)-np.exp(lu))**2) - (len(data)/2) * sp.log(2*sp.pi) \
- len(data) * sp.log(np.exp(lsig)) - sum(sp.log(data))
loglike = sign*loglike
return loglike
| 27.695205
| 150
| 0.467355
| 2,638
| 16,174
| 2.827142
| 0.064064
| 0.094529
| 0.035666
| 0.032582
| 0.787477
| 0.760392
| 0.728211
| 0.701931
| 0.686645
| 0.653258
| 0
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| 0.35792
| 16,174
| 583
| 151
| 27.74271
| 0.685123
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| 1
| 0.145923
| false
| 0.006438
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| 0
| 0
|
0
| 5
|
95cf5e144875e02e88f61845bb48a35cea39b8b1
| 47
|
py
|
Python
|
schedule/__init__.py
|
FlorianYANG/pricingtools
|
51b6831cbeccdcb89f3c78eeb9660a98c5b1470c
|
[
"MIT"
] | null | null | null |
schedule/__init__.py
|
FlorianYANG/pricingtools
|
51b6831cbeccdcb89f3c78eeb9660a98c5b1470c
|
[
"MIT"
] | null | null | null |
schedule/__init__.py
|
FlorianYANG/pricingtools
|
51b6831cbeccdcb89f3c78eeb9660a98c5b1470c
|
[
"MIT"
] | null | null | null |
from .schedule import *
from . import holidays
| 15.666667
| 23
| 0.765957
| 6
| 47
| 6
| 0.666667
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.170213
| 47
| 2
| 24
| 23.5
| 0.923077
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| 1
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| 1
| 0
| 0
| 0
|
0
| 5
|
95d4f2063c350a91f760f48a1ac56868cf76735b
| 133
|
py
|
Python
|
supermario/supermaio1102/mygame.py
|
Kimmiryeong/2DGP_GameProject
|
ad3fb197aab27227fc92fd404b2c310f8d0827ca
|
[
"MIT"
] | null | null | null |
supermario/supermaio1102/mygame.py
|
Kimmiryeong/2DGP_GameProject
|
ad3fb197aab27227fc92fd404b2c310f8d0827ca
|
[
"MIT"
] | null | null | null |
supermario/supermaio1102/mygame.py
|
Kimmiryeong/2DGP_GameProject
|
ad3fb197aab27227fc92fd404b2c310f8d0827ca
|
[
"MIT"
] | null | null | null |
import game_framework
from pico2d import*
import start_state
open_canvas(1800, 1024)
game_framework.run(start_state)
close_canvas()
| 16.625
| 31
| 0.842105
| 20
| 133
| 5.3
| 0.65
| 0.245283
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.07438
| 0.090226
| 133
| 8
| 32
| 16.625
| 0.801653
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| 0
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| 1
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| true
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| null | 1
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| 1
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| null | 0
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| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
250ba0da0c021ee8114bcc6a3e95f1890775214a
| 228
|
py
|
Python
|
src/lib/pedal/report/__init__.py
|
Skydler/skulpt
|
6eeabde2c5eb80c4a13f0958b75a69d99cd31b8a
|
[
"MIT"
] | 4
|
2015-08-06T07:19:58.000Z
|
2020-12-10T08:55:10.000Z
|
src/lib/pedal/report/__init__.py
|
Skydler/skulpt
|
6eeabde2c5eb80c4a13f0958b75a69d99cd31b8a
|
[
"MIT"
] | null | null | null |
src/lib/pedal/report/__init__.py
|
Skydler/skulpt
|
6eeabde2c5eb80c4a13f0958b75a69d99cd31b8a
|
[
"MIT"
] | 2
|
2019-10-16T22:18:29.000Z
|
2020-04-27T07:25:06.000Z
|
"""
The collection of classes and functions used to store the fundamental Report
and Feedback objects.
"""
from pedal.report.report import Report
from pedal.report.feedback import Feedback
from pedal.report.imperative import *
| 25.333333
| 76
| 0.807018
| 32
| 228
| 5.75
| 0.53125
| 0.146739
| 0.244565
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0.131579
| 228
| 8
| 77
| 28.5
| 0.929293
| 0.429825
| 0
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| true
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| null | 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
254dc5468c42b49f010ef38adacb76f043028fbb
| 33
|
py
|
Python
|
pykeops/numpy/shape_distance/__init__.py
|
MrHuff/keops
|
a7f44609ba444af8d9fcb11bc3a75f2024841dfa
|
[
"MIT"
] | 1
|
2020-05-08T08:03:31.000Z
|
2020-05-08T08:03:31.000Z
|
pykeops/numpy/shape_distance/__init__.py
|
MrHuff/keops
|
a7f44609ba444af8d9fcb11bc3a75f2024841dfa
|
[
"MIT"
] | null | null | null |
pykeops/numpy/shape_distance/__init__.py
|
MrHuff/keops
|
a7f44609ba444af8d9fcb11bc3a75f2024841dfa
|
[
"MIT"
] | 1
|
2020-05-08T08:03:34.000Z
|
2020-05-08T08:03:34.000Z
|
from .fshape_scp import FshapeScp
| 33
| 33
| 0.878788
| 5
| 33
| 5.6
| 1
| 0
| 0
| 0
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| 0.090909
| 33
| 1
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| 33
| 0.933333
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| 1
| 0
| 0
| 0
|
0
| 5
|
25691d21e7be78acca09e95f83ede59c1889edcf
| 283
|
py
|
Python
|
source/controllers/error_controller.py
|
DeNice-r/Flask-Musician-Website
|
f65dc0f6a31353f339e25f58af17bd716f293f0d
|
[
"MIT"
] | null | null | null |
source/controllers/error_controller.py
|
DeNice-r/Flask-Musician-Website
|
f65dc0f6a31353f339e25f58af17bd716f293f0d
|
[
"MIT"
] | null | null | null |
source/controllers/error_controller.py
|
DeNice-r/Flask-Musician-Website
|
f65dc0f6a31353f339e25f58af17bd716f293f0d
|
[
"MIT"
] | null | null | null |
from app import app
from flask import render_template
from flask_login import current_user
@app.errorhandler(404)
def not_found(error):
return render_template('error.html'), 404
@app.errorhandler(401)
def not_authorized(error):
return render_template('error.html'), 401
| 18.866667
| 45
| 0.777385
| 41
| 283
| 5.195122
| 0.463415
| 0.197183
| 0.159624
| 0.234742
| 0.319249
| 0.319249
| 0
| 0
| 0
| 0
| 0
| 0.04878
| 0.130742
| 283
| 14
| 46
| 20.214286
| 0.817073
| 0
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| 0
| 0
| 0
| 0.070922
| 0
| 0
| 0
| 0
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| 0
| 1
| 0.222222
| false
| 0
| 0.333333
| 0.222222
| 0.777778
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| null | 0
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| 1
| 1
| 1
| 0
|
0
| 5
|
c2b1940517eff811d72ff8a4204eefd619f764ce
| 58
|
py
|
Python
|
pettingzoo/classic/checkers_v3.py
|
FaramaFoundation/PettingZoo
|
62081cfcbdf284f4190c0f03a795604ab66f419b
|
[
"Apache-2.0"
] | null | null | null |
pettingzoo/classic/checkers_v3.py
|
FaramaFoundation/PettingZoo
|
62081cfcbdf284f4190c0f03a795604ab66f419b
|
[
"Apache-2.0"
] | null | null | null |
pettingzoo/classic/checkers_v3.py
|
FaramaFoundation/PettingZoo
|
62081cfcbdf284f4190c0f03a795604ab66f419b
|
[
"Apache-2.0"
] | null | null | null |
from .checkers.checkers import env, raw_env # noqa: F401
| 29
| 57
| 0.758621
| 9
| 58
| 4.777778
| 0.777778
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0.061224
| 0.155172
| 58
| 1
| 58
| 58
| 0.816327
| 0.172414
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| 1
| 0
|
0
| 5
|
c2b944f6d40a2563c8fdfd0709dc3a4335484b00
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/yapf/yapflib/yapf_api.py
|
GiulianaPola/select_repeats
|
17a0d053d4f874e42cf654dd142168c2ec8fbd11
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/yapf/yapflib/yapf_api.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/yapf/yapflib/yapf_api.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/69/c1/dd/e8caa0967cf6dd53301eecf63da05f2e7e5a09a1f41194aac68c23d356
| 96
| 96
| 0.895833
| 9
| 96
| 9.555556
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0.375
| 0
| 96
| 1
| 96
| 96
| 0.520833
| 0
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| null | null | 0
| 0
| null | null | 0
| 1
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| null | 0
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| 0
| 0
| 0
|
0
| 5
|
c2c08954592fb7ac45178cccce5b3433859bd1fc
| 177
|
py
|
Python
|
detector/utils/__init__.py
|
TropComplique/single-shot-detector
|
3714d411305f1a55bebb7e38ee58dfea70aa328d
|
[
"MIT"
] | 17
|
2018-02-19T08:45:39.000Z
|
2021-05-14T10:59:05.000Z
|
detector/utils/__init__.py
|
lly8752/single-shot-detector
|
3714d411305f1a55bebb7e38ee58dfea70aa328d
|
[
"MIT"
] | 4
|
2018-02-19T07:40:06.000Z
|
2020-03-19T12:31:13.000Z
|
detector/utils/__init__.py
|
lly8752/single-shot-detector
|
3714d411305f1a55bebb7e38ee58dfea70aa328d
|
[
"MIT"
] | 7
|
2018-12-11T14:39:24.000Z
|
2020-08-07T09:34:52.000Z
|
from .box_utils import iou, area, intersection, encode, batch_decode
from .layer_utils import batch_norm_relu, conv2d_same
from .nms import batch_multiclass_non_max_suppression
| 44.25
| 68
| 0.858757
| 27
| 177
| 5.259259
| 0.740741
| 0.15493
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.00625
| 0.096045
| 177
| 3
| 69
| 59
| 0.88125
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| 1
| 0
|
0
| 5
|
c2d4e007d72805690dfc46c61e88399882954d7d
| 26
|
py
|
Python
|
dactyl/version.py
|
divvydev/dactyl
|
dbcbbd0b5302e9b787ccaf3e49fcf3076d488a48
|
[
"MIT"
] | null | null | null |
dactyl/version.py
|
divvydev/dactyl
|
dbcbbd0b5302e9b787ccaf3e49fcf3076d488a48
|
[
"MIT"
] | null | null | null |
dactyl/version.py
|
divvydev/dactyl
|
dbcbbd0b5302e9b787ccaf3e49fcf3076d488a48
|
[
"MIT"
] | null | null | null |
__version__ = '0.7.0-a10'
| 13
| 25
| 0.653846
| 5
| 26
| 2.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.217391
| 0.115385
| 26
| 1
| 26
| 26
| 0.347826
| 0
| 0
| 0
| 0
| 0
| 0.346154
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
c2dd00313c3909653e0737066d85da1e0a72b91c
| 436
|
py
|
Python
|
7kyu/python/reverse-and-invert/test_reverse_and_invert.py
|
seattlechem/codewars
|
885293e7ad5fb427c07792ed85d74881a5ebad29
|
[
"MIT"
] | null | null | null |
7kyu/python/reverse-and-invert/test_reverse_and_invert.py
|
seattlechem/codewars
|
885293e7ad5fb427c07792ed85d74881a5ebad29
|
[
"MIT"
] | null | null | null |
7kyu/python/reverse-and-invert/test_reverse_and_invert.py
|
seattlechem/codewars
|
885293e7ad5fb427c07792ed85d74881a5ebad29
|
[
"MIT"
] | null | null | null |
"""Test cases."""
from reverse_and_invert import reverse_invert
def test_true():
"""True test cases."""
assert reverse_invert([1, 2, 3, 4, 5]) == [-1, -2, -3, -4, -5]
assert reverse_invert([-10]) == [1]
assert reverse_invert([- 9, - 18, 99]) == [9, 81, - 99]
assert reverse_invert([1, 12, 'a', 3.4, 87, 99.9, -42,
50, 5.6]) == [- 1, -21, -78, 24, -5]
assert reverse_invert([]) == []
| 33.538462
| 66
| 0.513761
| 65
| 436
| 3.307692
| 0.446154
| 0.362791
| 0.44186
| 0.186047
| 0.046512
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145062
| 0.256881
| 436
| 12
| 67
| 36.333333
| 0.518519
| 0.06422
| 0
| 0
| 0
| 0
| 0.002519
| 0
| 0
| 0
| 0
| 0
| 0.625
| 1
| 0.125
| true
| 0
| 0.125
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
c2e7578342f2162cece94d745689709b5c713329
| 183
|
py
|
Python
|
3-Python-Advanced (May 2021)/modules/lab/math_operations/operations.py
|
karolinanikolova/SoftUni-Software-Engineering
|
7891924956598b11a1e30e2c220457c85c40f064
|
[
"MIT"
] | null | null | null |
3-Python-Advanced (May 2021)/modules/lab/math_operations/operations.py
|
karolinanikolova/SoftUni-Software-Engineering
|
7891924956598b11a1e30e2c220457c85c40f064
|
[
"MIT"
] | null | null | null |
3-Python-Advanced (May 2021)/modules/lab/math_operations/operations.py
|
karolinanikolova/SoftUni-Software-Engineering
|
7891924956598b11a1e30e2c220457c85c40f064
|
[
"MIT"
] | null | null | null |
def multiply(x, y):
return x * y
def divide(x, y):
return x / y
def add(x, y):
return x + y
def subtract(x, y):
return x - y
def power(x, y):
return x ** y
| 10.166667
| 19
| 0.519126
| 35
| 183
| 2.714286
| 0.257143
| 0.210526
| 0.421053
| 0.473684
| 0.652632
| 0.547368
| 0
| 0
| 0
| 0
| 0
| 0
| 0.338798
| 183
| 18
| 20
| 10.166667
| 0.785124
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
6c0e075d772b96f09b914e157c0e96b3a3caf790
| 129
|
py
|
Python
|
WEEKS/wk17/CodeSignal-Solutions/26_-_evenDigitsOnly.py
|
webdevhub42/Lambda
|
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
|
[
"MIT"
] | null | null | null |
WEEKS/wk17/CodeSignal-Solutions/26_-_evenDigitsOnly.py
|
webdevhub42/Lambda
|
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
|
[
"MIT"
] | null | null | null |
WEEKS/wk17/CodeSignal-Solutions/26_-_evenDigitsOnly.py
|
webdevhub42/Lambda
|
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
|
[
"MIT"
] | null | null | null |
def evenDigitsOnly(n):
return all(
(True if digit in ("0", "2", "4", "6", "8") else False for digit in str(n))
)
| 25.8
| 83
| 0.527132
| 21
| 129
| 3.238095
| 0.857143
| 0.205882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053763
| 0.27907
| 129
| 4
| 84
| 32.25
| 0.677419
| 0
| 0
| 0
| 0
| 0
| 0.03876
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0.25
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
6c0fbadd1dd1cb5b303cc37dbb39f9cfa4efa7a4
| 46
|
py
|
Python
|
2commit.py
|
Davide-Botturi/Dog-Breed-Udacity
|
401d56012da4030ef486ca5149c9ebe6e29d0376
|
[
"MIT"
] | null | null | null |
2commit.py
|
Davide-Botturi/Dog-Breed-Udacity
|
401d56012da4030ef486ca5149c9ebe6e29d0376
|
[
"MIT"
] | 4
|
2020-09-26T01:14:36.000Z
|
2022-02-10T02:09:02.000Z
|
2commit.py
|
Davide-Botturi/Dog-Breed-Udacity
|
401d56012da4030ef486ca5149c9ebe6e29d0376
|
[
"MIT"
] | null | null | null |
import numpy
import matplotlib.pyplot as plt
| 11.5
| 31
| 0.826087
| 7
| 46
| 5.428571
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152174
| 46
| 3
| 32
| 15.333333
| 0.974359
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
6c1a309b21699946e2bc70ab9970af0f09be51ab
| 229
|
py
|
Python
|
importdata/admin.py
|
uktrade/fadmin2
|
0f774400fb816c9ca30e30b25ae542135966e185
|
[
"MIT"
] | 3
|
2020-01-05T16:46:42.000Z
|
2021-08-02T08:08:39.000Z
|
importdata/admin.py
|
uktrade/fadmin2
|
0f774400fb816c9ca30e30b25ae542135966e185
|
[
"MIT"
] | 30
|
2019-11-28T15:16:35.000Z
|
2021-08-16T14:49:58.000Z
|
importdata/admin.py
|
uktrade/fadmin2
|
0f774400fb816c9ca30e30b25ae542135966e185
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from core.admin import AdminReadOnly
from importdata.models import AsyncImportLog
class AsyncImportLogAdmin(AdminReadOnly):
pass
admin.site.register(AsyncImportLog, AsyncImportLogAdmin)
| 17.615385
| 56
| 0.834061
| 24
| 229
| 7.958333
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117904
| 229
| 12
| 57
| 19.083333
| 0.945545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.166667
| 0.833333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
6c46e678c680ca5f23636185dfecbdbf8f4ad826
| 239
|
py
|
Python
|
object_detection/unit.py
|
IVRL/Dunit
|
0f0d4086b4d8576c11dfac6092b9b60fa4ad7b72
|
[
"CC0-1.0"
] | 25
|
2020-07-13T17:55:37.000Z
|
2021-11-12T11:02:48.000Z
|
object_detection/unit.py
|
IVRL/Dunit
|
0f0d4086b4d8576c11dfac6092b9b60fa4ad7b72
|
[
"CC0-1.0"
] | 5
|
2020-12-06T07:17:34.000Z
|
2021-11-22T08:36:31.000Z
|
object_detection/unit.py
|
IVRL/Dunit
|
0f0d4086b4d8576c11dfac6092b9b60fa4ad7b72
|
[
"CC0-1.0"
] | 1
|
2020-12-22T02:28:01.000Z
|
2020-12-22T02:28:01.000Z
|
"""Model for object segmentation based on UNIT"""
from ..unit.model import UNIT
from .mixin import ObjectDetectionMixin
class UNITObjectDetection(
ObjectDetectionMixin, UNIT):
"""Model for object segmentation based on UNIT"""
| 29.875
| 53
| 0.753138
| 27
| 239
| 6.666667
| 0.481481
| 0.088889
| 0.155556
| 0.288889
| 0.411111
| 0.411111
| 0.411111
| 0
| 0
| 0
| 0
| 0
| 0.16318
| 239
| 7
| 54
| 34.142857
| 0.9
| 0.364017
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
6c5535e1ac05120df6b00d94678710bcae552add
| 35
|
py
|
Python
|
crslab/config/__init__.py
|
Zilize/CRSLab
|
fb357d0dfb7d2cf7b67b892d98e52032a31ca564
|
[
"MIT"
] | null | null | null |
crslab/config/__init__.py
|
Zilize/CRSLab
|
fb357d0dfb7d2cf7b67b892d98e52032a31ca564
|
[
"MIT"
] | null | null | null |
crslab/config/__init__.py
|
Zilize/CRSLab
|
fb357d0dfb7d2cf7b67b892d98e52032a31ca564
|
[
"MIT"
] | null | null | null |
from crslab.config.config import *
| 17.5
| 34
| 0.8
| 5
| 35
| 5.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 35
| 1
| 35
| 35
| 0.903226
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
6c8c15ecb2a2cd20e51f2875225197fbc66df1cc
| 37
|
py
|
Python
|
km_pypi_test/views.py
|
kamalhg/km_pypi_test
|
13ecbbbf8503b20d8136520f5b19487f9f805b2e
|
[
"MIT"
] | null | null | null |
km_pypi_test/views.py
|
kamalhg/km_pypi_test
|
13ecbbbf8503b20d8136520f5b19487f9f805b2e
|
[
"MIT"
] | null | null | null |
km_pypi_test/views.py
|
kamalhg/km_pypi_test
|
13ecbbbf8503b20d8136520f5b19487f9f805b2e
|
[
"MIT"
] | null | null | null |
def test_function():
print "TESTING"
| 18.5
| 20
| 0.756757
| 5
| 37
| 5.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108108
| 37
| 2
| 21
| 18.5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0.184211
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
6657d9d3ad39fc6bd65f89817d702a1d2236d392
| 1,748
|
py
|
Python
|
cotidia/admin/tests/unit/dynamic_list/test_detail_url.py
|
hayden5-mwac/cotidia-admin
|
cfdd9d2677dd1098019fafbec8a6d07e1a42f9eb
|
[
"BSD-3-Clause"
] | 2
|
2019-07-20T14:43:21.000Z
|
2021-04-30T15:43:49.000Z
|
cotidia/admin/tests/unit/dynamic_list/test_detail_url.py
|
hayden5-mwac/cotidia-admin
|
cfdd9d2677dd1098019fafbec8a6d07e1a42f9eb
|
[
"BSD-3-Clause"
] | 16
|
2020-07-17T04:26:20.000Z
|
2022-03-23T14:47:31.000Z
|
cotidia/admin/tests/unit/dynamic_list/test_detail_url.py
|
hayden5-mwac/cotidia-admin
|
cfdd9d2677dd1098019fafbec8a6d07e1a42f9eb
|
[
"BSD-3-Clause"
] | 1
|
2020-05-18T20:56:45.000Z
|
2020-05-18T20:56:45.000Z
|
from django.test import TestCase
from cotidia.admin.tests.models import ExampleModelOne
from cotidia.admin.serializers import BaseDynamicListSerializer
class TestDetailURLSerializer(TestCase):
def test_detail_url_none(self):
class ExampleModelOneSerializer(BaseDynamicListSerializer):
other_model = ExampleModelOne()
class Meta:
model = ExampleModelOne
fields = "__all__"
class SearchProvider:
display_field = "char_field"
filters = "__all__"
detail_url_field = None
serializer = ExampleModelOneSerializer()
self.assertEqual(serializer.get_detail_url_field(), None)
def test_detail_url_default(self):
class ExampleModelOneSerializer(BaseDynamicListSerializer):
other_model = ExampleModelOne()
class Meta:
model = ExampleModelOne
fields = "__all__"
class SearchProvider:
display_field = "char_field"
filters = "__all__"
serializer = ExampleModelOneSerializer()
self.assertEqual(serializer.get_detail_url_field(), "_detail_url")
def test_detail_url_custom(self):
class ExampleModelOneSerializer(BaseDynamicListSerializer):
other_model = ExampleModelOne()
class Meta:
model = ExampleModelOne
fields = "__all__"
class SearchProvider:
display_field = "char_field"
filters = "__all__"
detail_url_field = "detail_url"
serializer = ExampleModelOneSerializer()
self.assertEqual(serializer.get_detail_url_field(), "detail_url")
| 32.37037
| 74
| 0.631579
| 140
| 1,748
| 7.464286
| 0.25
| 0.094737
| 0.066986
| 0.045933
| 0.767464
| 0.758852
| 0.758852
| 0.758852
| 0.758852
| 0.685167
| 0
| 0
| 0.305492
| 1,748
| 53
| 75
| 32.981132
| 0.860791
| 0
| 0
| 0.692308
| 0
| 0
| 0.058924
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 1
| 0.076923
| false
| 0
| 0.076923
| 0
| 0.410256
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
6689f00a608f6c5f464f45f4fdded3a9df9aed0a
| 66
|
py
|
Python
|
tests/testfunccall.numbers.py
|
Vaarai/rockstar-py
|
e7f93eb44dcf77cddd1288b15eee127be928b032
|
[
"MIT"
] | null | null | null |
tests/testfunccall.numbers.py
|
Vaarai/rockstar-py
|
e7f93eb44dcf77cddd1288b15eee127be928b032
|
[
"MIT"
] | null | null | null |
tests/testfunccall.numbers.py
|
Vaarai/rockstar-py
|
e7f93eb44dcf77cddd1288b15eee127be928b032
|
[
"MIT"
] | null | null | null |
def Multiply(Love, Life):
return Love * Life
Multiply(3, 444)
| 16.5
| 25
| 0.681818
| 10
| 66
| 4.5
| 0.7
| 0.355556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075472
| 0.19697
| 66
| 3
| 26
| 22
| 0.773585
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
66931556061a0075eefd1c341ecc35f8c5bef3a3
| 77
|
py
|
Python
|
boa3_test/test_sc/function_test/ReturnIfExpressionMismatched.py
|
hal0x2328/neo3-boa
|
6825a3533384cb01660773050719402a9703065b
|
[
"Apache-2.0"
] | 25
|
2020-07-22T19:37:43.000Z
|
2022-03-08T03:23:55.000Z
|
boa3_test/test_sc/function_test/ReturnIfExpressionMismatched.py
|
hal0x2328/neo3-boa
|
6825a3533384cb01660773050719402a9703065b
|
[
"Apache-2.0"
] | 419
|
2020-04-23T17:48:14.000Z
|
2022-03-31T13:17:45.000Z
|
boa3_test/test_sc/function_test/ReturnIfExpressionMismatched.py
|
hal0x2328/neo3-boa
|
6825a3533384cb01660773050719402a9703065b
|
[
"Apache-2.0"
] | 15
|
2020-05-21T21:54:24.000Z
|
2021-11-18T06:17:24.000Z
|
def Main(number: int) -> int:
return number if number % 2 == 1 else None
| 25.666667
| 46
| 0.636364
| 13
| 77
| 3.769231
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034483
| 0.246753
| 77
| 2
| 47
| 38.5
| 0.810345
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
66aa5befdcdd9d7fd70eef763759361dcf28c0f0
| 2,344
|
py
|
Python
|
examples/test_disk.py
|
maxtrussell/python-computer-craft
|
9e318d2a0d368faf7a5c2a91e750fe8008aa9b81
|
[
"MIT"
] | 42
|
2016-12-17T21:26:34.000Z
|
2022-03-30T06:16:34.000Z
|
examples/test_disk.py
|
maxtrussell/python-computer-craft
|
9e318d2a0d368faf7a5c2a91e750fe8008aa9b81
|
[
"MIT"
] | 9
|
2018-02-21T22:44:18.000Z
|
2022-03-14T04:14:02.000Z
|
examples/test_disk.py
|
maxtrussell/python-computer-craft
|
9e318d2a0d368faf7a5c2a91e750fe8008aa9b81
|
[
"MIT"
] | 7
|
2018-04-02T09:08:29.000Z
|
2022-03-31T15:19:02.000Z
|
from cc import LuaException, import_file, disk
_lib = import_file('_lib.py', __file__)
step, assert_raises = _lib.step, _lib.assert_raises
s = 'right'
assert _lib.get_class_table(disk) == _lib.get_object_table('disk')
step(f'Make sure there is no disk drive at {s} side')
assert disk.isPresent(s) is False
assert disk.hasData(s) is False
assert disk.getMountPath(s) is None
assert disk.setLabel(s, 'text') is None
assert disk.getLabel(s) is None
assert disk.getID(s) is None
assert disk.hasAudio(s) is False
assert disk.getAudioTitle(s) is None
assert disk.playAudio(s) is None
assert disk.stopAudio(s) is None
assert disk.eject(s) is None
step(f'Place empty disk drive at {s} side')
assert disk.isPresent(s) is False
assert disk.hasData(s) is False
assert disk.getMountPath(s) is None
assert disk.setLabel(s, 'text') is None
assert disk.getLabel(s) is None
assert disk.getID(s) is None
assert disk.hasAudio(s) is False
assert disk.getAudioTitle(s) is False # False instead None!
assert disk.playAudio(s) is None
assert disk.stopAudio(s) is None
assert disk.eject(s) is None
step('Put new CC diskette into disk drive')
assert disk.isPresent(s) is True
assert disk.hasData(s) is True
assert isinstance(disk.getMountPath(s), str)
assert isinstance(disk.getID(s), int)
assert disk.getLabel(s) is None
assert disk.setLabel(s, 'label') is None
assert disk.getLabel(s) == 'label'
assert disk.setLabel(s, None) is None
assert disk.getLabel(s) is None
assert disk.hasAudio(s) is False
assert disk.getAudioTitle(s) is None
assert disk.playAudio(s) is None
assert disk.stopAudio(s) is None
assert disk.eject(s) is None
step('Put any audio disk into disk drive')
assert disk.isPresent(s) is True
assert disk.hasData(s) is False
assert disk.getMountPath(s) is None
assert disk.getID(s) is None
assert disk.hasAudio(s) is True
label = disk.getAudioTitle(s)
assert isinstance(label, str)
assert label != 'label'
print(f'Label is {label}')
assert disk.getLabel(s) == label
with assert_raises(LuaException):
assert disk.setLabel(s, 'label') is None
with assert_raises(LuaException):
assert disk.setLabel(s, None) is None
# no effect
assert disk.getLabel(s) == label
assert disk.playAudio(s) is None
step('Audio must be playing now')
assert disk.stopAudio(s) is None
assert disk.eject(s) is None
print('Test finished successfully')
| 26.942529
| 66
| 0.759812
| 401
| 2,344
| 4.391521
| 0.159601
| 0.261215
| 0.0954
| 0.208972
| 0.749006
| 0.735378
| 0.726292
| 0.657013
| 0.583759
| 0.583759
| 0
| 0
| 0.132253
| 2,344
| 86
| 67
| 27.255814
| 0.865782
| 0.012372
| 0
| 0.676923
| 0
| 0
| 0.111592
| 0
| 0
| 0
| 0
| 0
| 0.830769
| 1
| 0
| false
| 0
| 0.030769
| 0
| 0.030769
| 0.030769
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
66ebd7949ff5cd3201dab59d4152c78ad4d7c03c
| 359
|
py
|
Python
|
services/common/domain/actions/add_player_to_game.py
|
tkblackbelt/Asteroids-Multiplayer-Backend
|
e09b110ec8698657d8f22f2600e95acc663b1ba0
|
[
"Apache-2.0"
] | null | null | null |
services/common/domain/actions/add_player_to_game.py
|
tkblackbelt/Asteroids-Multiplayer-Backend
|
e09b110ec8698657d8f22f2600e95acc663b1ba0
|
[
"Apache-2.0"
] | null | null | null |
services/common/domain/actions/add_player_to_game.py
|
tkblackbelt/Asteroids-Multiplayer-Backend
|
e09b110ec8698657d8f22f2600e95acc663b1ba0
|
[
"Apache-2.0"
] | null | null | null |
import inject
from common.domain.player import Player
from common.domain.player_cache_interface import PlayerCacheInterface
class AddPlayerToGame:
@inject.autoparams('cache')
def __init__(self, cache: PlayerCacheInterface):
self.__cache = cache
def execute(self, player: Player) -> bool:
return self.__cache.add_player(player)
| 25.642857
| 69
| 0.752089
| 41
| 359
| 6.317073
| 0.463415
| 0.104247
| 0.123552
| 0.169884
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.167131
| 359
| 13
| 70
| 27.615385
| 0.866221
| 0
| 0
| 0
| 0
| 0
| 0.013928
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.333333
| 0.111111
| 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
| 1
| 1
| 1
| 0
|
0
| 5
|
dd15ecc21aaba9a3adc7c10f4bda5ee5fd437f61
| 115
|
py
|
Python
|
Client.py
|
pmanfo/Deeep-Learning-Pytorch-Docker-Ngnix
|
ba0c8e981a2d9a9b38c4896ccca00b7af3c26dd8
|
[
"MIT"
] | null | null | null |
Client.py
|
pmanfo/Deeep-Learning-Pytorch-Docker-Ngnix
|
ba0c8e981a2d9a9b38c4896ccca00b7af3c26dd8
|
[
"MIT"
] | null | null | null |
Client.py
|
pmanfo/Deeep-Learning-Pytorch-Docker-Ngnix
|
ba0c8e981a2d9a9b38c4896ccca00b7af3c26dd8
|
[
"MIT"
] | null | null | null |
# coding:utf-8
import socket
host,conn=('localhost',5566)
socket = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
| 28.75
| 57
| 0.791304
| 18
| 115
| 4.944444
| 0.722222
| 0.404494
| 0.404494
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.046296
| 0.06087
| 115
| 4
| 57
| 28.75
| 0.777778
| 0.104348
| 0
| 0
| 0
| 0
| 0.088235
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
dd2154e9954f0a8634dc036dc48918ab88c497cc
| 49
|
py
|
Python
|
Projects/project2/killprocesses.py
|
jdiegoh3/distributed_computing
|
33088e741d35590d5699e8ecd9a35ff12b65f7f8
|
[
"MIT"
] | null | null | null |
Projects/project2/killprocesses.py
|
jdiegoh3/distributed_computing
|
33088e741d35590d5699e8ecd9a35ff12b65f7f8
|
[
"MIT"
] | null | null | null |
Projects/project2/killprocesses.py
|
jdiegoh3/distributed_computing
|
33088e741d35590d5699e8ecd9a35ff12b65f7f8
|
[
"MIT"
] | null | null | null |
import os
os.system('taskkill /f /im python.exe')
| 24.5
| 39
| 0.734694
| 9
| 49
| 4
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102041
| 49
| 2
| 39
| 24.5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0.52
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
dd5adc7a17f11dc8aed0d35f75885ef4c3a60b6a
| 432
|
py
|
Python
|
b2/transferer/parallel.py
|
sam-centrevilletech/B2_Command_Line_Tool
|
9cdef21cc43cb1d45590349754a4c866372ca6e1
|
[
"MIT"
] | null | null | null |
b2/transferer/parallel.py
|
sam-centrevilletech/B2_Command_Line_Tool
|
9cdef21cc43cb1d45590349754a4c866372ca6e1
|
[
"MIT"
] | 2
|
2022-02-24T21:17:18.000Z
|
2022-03-16T20:45:45.000Z
|
b2/transferer/parallel.py
|
sam-centrevilletech/B2_Command_Line_Tool
|
9cdef21cc43cb1d45590349754a4c866372ca6e1
|
[
"MIT"
] | null | null | null |
######################################################################
#
# File: b2/transferer/parallel.py
#
# Copyright 2019 Backblaze Inc. All Rights Reserved.
#
# License https://www.backblaze.com/using_b2_code.html
#
######################################################################
from b2sdk.transferer.parallel import * # noqa
import b2._sdk_deprecation
b2._sdk_deprecation.deprecate_module('b2.transferer.parallel')
| 28.8
| 70
| 0.525463
| 39
| 432
| 5.641026
| 0.692308
| 0.245455
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025
| 0.074074
| 432
| 14
| 71
| 30.857143
| 0.525
| 0.324074
| 0
| 0
| 0
| 0
| 0.153846
| 0.153846
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
dd5aede13169038c3bffa9967e0b92e536ae0d9a
| 106
|
py
|
Python
|
src/network/__init__.py
|
mateusz800/data_encryptor
|
4f317e08bdcd5c5a3815a541823baf18d8fc9809
|
[
"MIT"
] | null | null | null |
src/network/__init__.py
|
mateusz800/data_encryptor
|
4f317e08bdcd5c5a3815a541823baf18d8fc9809
|
[
"MIT"
] | null | null | null |
src/network/__init__.py
|
mateusz800/data_encryptor
|
4f317e08bdcd5c5a3815a541823baf18d8fc9809
|
[
"MIT"
] | null | null | null |
from .receiver import ReceiveThread
from .sender import SendThread, send_request_for_key, send_session_key
| 53
| 70
| 0.877358
| 15
| 106
| 5.866667
| 0.733333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084906
| 106
| 2
| 70
| 53
| 0.907216
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
06d8f8da536cfb5997f2d659140a78509fe6ef37
| 112
|
py
|
Python
|
revolt/ext/commands/__init__.py
|
LightSage/revolt.py
|
a16bac6207b63f818bf39de1a5508c377e25f0e8
|
[
"MIT"
] | null | null | null |
revolt/ext/commands/__init__.py
|
LightSage/revolt.py
|
a16bac6207b63f818bf39de1a5508c377e25f0e8
|
[
"MIT"
] | null | null | null |
revolt/ext/commands/__init__.py
|
LightSage/revolt.py
|
a16bac6207b63f818bf39de1a5508c377e25f0e8
|
[
"MIT"
] | null | null | null |
from .checks import *
from .client import *
from .command import *
from .context import *
from .errors import *
| 18.666667
| 22
| 0.732143
| 15
| 112
| 5.466667
| 0.466667
| 0.487805
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.178571
| 112
| 5
| 23
| 22.4
| 0.891304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
06e2475768b7fdaef6dfd358e5200d9340f7fd05
| 102
|
py
|
Python
|
src/drivers/__init__.py
|
tomszir/chip8-py
|
b73c7f5478aa45bd98f0371daf4f6136c7da58cb
|
[
"MIT"
] | null | null | null |
src/drivers/__init__.py
|
tomszir/chip8-py
|
b73c7f5478aa45bd98f0371daf4f6136c7da58cb
|
[
"MIT"
] | null | null | null |
src/drivers/__init__.py
|
tomszir/chip8-py
|
b73c7f5478aa45bd98f0371daf4f6136c7da58cb
|
[
"MIT"
] | null | null | null |
from .audio import AudioDriver
from .keyboard import InputDriver
from .graphics import GraphicsDriver
| 25.5
| 36
| 0.852941
| 12
| 102
| 7.25
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 102
| 3
| 37
| 34
| 0.966667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
b08ecca13e544317f53eaedcf98efcf32a8265eb
| 14
|
py
|
Python
|
tests.py
|
byschii/infarinator
|
0ab096f2d6d798b59bc7ef072c13902df02a5931
|
[
"MIT"
] | null | null | null |
tests.py
|
byschii/infarinator
|
0ab096f2d6d798b59bc7ef072c13902df02a5931
|
[
"MIT"
] | null | null | null |
tests.py
|
byschii/infarinator
|
0ab096f2d6d798b59bc7ef072c13902df02a5931
|
[
"MIT"
] | null | null | null |
print('prova')
| 14
| 14
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0
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b0c41424dcd4baf07b0b2c0da1870fb08b3c177b
| 16,450
|
py
|
Python
|
utils/metric_net/data_loader.py
|
tsingqguo/ABA
|
c32edbbe5705b0332a08951b5ee436b5f58c2e70
|
[
"MIT"
] | 12
|
2021-07-27T07:18:24.000Z
|
2022-03-09T13:52:20.000Z
|
utils/metric_net/data_loader.py
|
tsingqguo/ABA
|
c32edbbe5705b0332a08951b5ee436b5f58c2e70
|
[
"MIT"
] | 2
|
2021-08-03T09:21:33.000Z
|
2021-12-29T14:25:30.000Z
|
utils/metric_net/data_loader.py
|
tsingqguo/ABA
|
c32edbbe5705b0332a08951b5ee436b5f58c2e70
|
[
"MIT"
] | 3
|
2021-11-18T14:46:40.000Z
|
2022-01-03T15:47:23.000Z
|
import numpy as np
import cv2
import os
import torch
import torch.nn as nn
from sample_generator import *
from PIL import Image
import torch.utils.data as torch_dataset
from model import ft_net
import torch.optim as optim
from torch.optim import lr_scheduler
import time
from torch.autograd import Variable
from torchvision import transforms
from tensorboardX import SummaryWriter
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
class TripletLoss(nn.Module):
'''
Compute normal triplet loss or soft margin triplet loss given triplets
'''
def __init__(self, margin = None):
super(TripletLoss, self).__init__()
self.margin = margin
if self.margin is None: # use soft-margin
self.Loss = nn.SoftMarginLoss()
else:
self.Loss = nn.TripletMarginLoss(margin = margin, p = 2)
self.class_loss = nn.CrossEntropyLoss()
def forward(self, anchor, pos, neg, hard_neg):
if self.margin is None:
num_samples = anchor.shape[0]
y = torch.ones((num_samples, 1)).view(-1)
if anchor.is_cuda: y = y.cuda()
ap_dist = torch.norm(anchor - pos, 2, dim = 1).view(-1)
an_dist = torch.norm(anchor - neg, 2, dim = 1).view(-1)
ahn_dist = torch.norm(anchor - hard_neg, 2, dim = 1).view(-1)
loss = self.Loss(an_dist - ap_dist, y) / 2.0 + self.Loss(ahn_dist - ap_dist, y) / 2.0
else:
loss = self.Loss(anchor, pos, neg)
return loss
class MixedLoss(nn.Module):
'''
Compute normal triplet loss or soft margin triplet loss given triplets
'''
def __init__(self, margin = None):
super(MixedLoss, self).__init__()
self.margin = margin
if self.margin is None: # use soft-margin
self.Loss = nn.SoftMarginLoss()
else:
self.Loss = nn.TripletMarginLoss(margin = margin, p = 2)
self.class_loss = nn.CrossEntropyLoss()
def forward(self, anchor, pos, neg, hard_neg, an_class, p_class, neg_class, hard_neg_class, class_ids, hard_class_ids):
if self.margin is None:
num_samples = anchor.shape[0]
y = torch.ones((num_samples, 1)).view(-1)
if anchor.is_cuda: y = y.cuda()
ap_dist = torch.norm(anchor - pos, 2, dim = 1).view(-1)
an_dist = torch.norm(anchor - neg, 2, dim = 1).view(-1)
ahn_dist = torch.norm(anchor - hard_neg, 2, dim = 1).view(-1)
matching_loss = self.Loss(an_dist - ap_dist, y) / 2.0 + self.Loss(ahn_dist - ap_dist, y) / 2.0
class_loss1 = self.class_loss(an_class, class_ids)
class_loss2 = self.class_loss(p_class, class_ids)
class_loss3 = self.class_loss(hard_neg_class, hard_class_ids)
#class_loss = (class_loss1+class_loss2 + class_loss3)/3.0
neg_class = torch.softmax(neg_class, dim=1)
neg_class_loss = torch.sum(-1.0/1400 * torch.log(neg_class),dim=1)
neg_class_loss = torch.mean(neg_class_loss, dim=0)
class_loss = (class_loss1+ class_loss2 + class_loss3 + neg_class_loss) / 4.0
loss = matching_loss + class_loss
else:
loss = self.Loss(anchor, pos, neg)
return loss, matching_loss, class_loss
class ValidationDataset(torch_dataset.Dataset):
def __init__(self, src_path):
#src_path = '/home/xiaobai/Documents/LaSOT/LaSOTBenchmark/'
self.data_dict = dict()
seq_list = os.listdir(src_path)
seq_list.sort()
seq_lists = []
#class_id = 0
for seq_id, seq_name in enumerate(seq_list):
self.data_dict[seq_name] = dict()
self.data_dict[seq_name]['pos'] = os.listdir(src_path + seq_name + '/pos/')
self.data_dict[seq_name]['neg'] = os.listdir(src_path + seq_name + '/neg/')
self.data_dict[seq_name]['pos_num'] = len(self.data_dict[seq_name]['pos'])
self.data_dict[seq_name]['neg_num'] = len(self.data_dict[seq_name]['neg'])
#class_id += 1
# print 'Loading sequences: ', seq_id, '/', 50
self.src_path = src_path
self.keys = self.data_dict.keys()
self.seq_num = len(self.data_dict.keys())
transform_train_list = [
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]
self.data_transforms = transforms.Compose(transform_train_list)
def process_regions(self, regions):
#regions = np.squeeze(regions, axis=0)
regions = regions / 255.0
regions[:,:,0] = (regions[:,:,0] - 0.485) / 0.229
regions[:,:,1] = (regions[:,:,1] - 0.456) / 0.224
regions[:,:,2] = (regions[:,:,2] - 0.406) / 0.225
regions = np.transpose(regions, (2,0,1))
return regions
def __getitem__(self, index):
#seq_id = np.random.randint(low=0, high = self.seq_num-1, size=[1])[0]
seq_name = self.keys[index]
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
anchor_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
anchor_regions = self.process_regions(anchor_regions)
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
pos_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
pos_regions = self.process_regions(pos_regions)
if self.data_dict[seq_name]['neg_num'] > 0:
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['neg_num'],size=[1,])[0]
neg_regions = np.array(Image.open(self.src_path + seq_name + '/neg/' + self.data_dict[seq_name]['neg'][index1]))
neg_regions = self.process_regions(neg_regions)
else:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
while index2 == index:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
seq_name = self.keys[index2]
index1 = np.random.randint(low=0, high=self.data_dict[seq_name]['pos_num'], size=[1, ])[0]
neg_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
neg_regions = self.process_regions(neg_regions)
index2 = np.random.randint(low=0,high=self.seq_num, size = [1])[0]
while index2 == index:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
seq_name = self.keys[index2]
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
hard_neg_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
hard_neg_regions = self.process_regions(hard_neg_regions)
return anchor_regions, pos_regions, neg_regions, hard_neg_regions
def __len__(self):
# You should change 0 to the total size of your dataset.
return self.seq_num
class CustomDataset(torch_dataset.Dataset):
def __init__(self, src_path):
#src_path = '/home/xiaobai/Documents/LaSOT/LaSOTBenchmark/'
self.data_dict = dict()
folder_list = os.listdir(src_path)
folder_list.sort()
seq_lists = []
class_id = 0
for folder_id, folder in enumerate(folder_list):
#seq_list = sorted([src_path + folder + '/' + seq for seq in seq_list])
seq_list = os.listdir(src_path + folder)
seq_list = sorted([folder + '/' + seq for seq in seq_list])
for seq_id, seq_name in enumerate(seq_list):
self.data_dict[seq_name] = dict()
self.data_dict[seq_name]['pos'] = os.listdir(src_path + seq_name + '/pos/')
self.data_dict[seq_name]['neg'] = os.listdir(src_path + seq_name + '/neg/')
self.data_dict[seq_name]['pos_num'] = len(self.data_dict[seq_name]['pos'])
self.data_dict[seq_name]['neg_num'] = len(self.data_dict[seq_name]['neg'])
self.data_dict[seq_name]['class_id'] = class_id
class_id += 1
# print 'Loading sequences: ', class_id, '/', 1400
self.src_path = src_path
self.keys = self.data_dict.keys()
self.seq_num = len(self.data_dict.keys())
transform_train_list = [
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]
self.data_transforms = transforms.Compose(transform_train_list)
def process_regions(self, regions):
#regions = np.squeeze(regions, axis=0)
regions = regions / 255.0
regions[:,:,0] = (regions[:,:,0] - 0.485) / 0.229
regions[:,:,1] = (regions[:,:,1] - 0.456) / 0.224
regions[:,:,2] = (regions[:,:,2] - 0.406) / 0.225
regions = np.transpose(regions, (2,0,1))
return regions
def __getitem__(self, index):
#seq_id = np.random.randint(low=0, high = self.seq_num-1, size=[1])[0]
seq_name = self.keys[index]
class_id = self.data_dict[seq_name]['class_id']
class_id = np.array([class_id,])
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
anchor_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
anchor_regions = self.process_regions(anchor_regions)
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
pos_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
pos_regions = self.process_regions(pos_regions)
if self.data_dict[seq_name]['neg_num'] > 0:
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['neg_num'],size=[1,])[0]
neg_regions = np.array(Image.open(self.src_path + seq_name + '/neg/' + self.data_dict[seq_name]['neg'][index1]))
neg_regions = self.process_regions(neg_regions)
else:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
while index2 == index:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
seq_name = self.keys[index2]
index1 = np.random.randint(low=0, high=self.data_dict[seq_name]['pos_num'], size=[1, ])[0]
neg_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
neg_regions = self.process_regions(neg_regions)
index2 = np.random.randint(low=0,high=self.seq_num, size = [1])[0]
while index2 == index:
index2 = np.random.randint(low=0, high=self.seq_num, size=[1])[0]
seq_name = self.keys[index2]
index1 = np.random.randint(low=0,high=self.data_dict[seq_name]['pos_num'],size=[1,])[0]
hard_neg_regions = np.array(Image.open(self.src_path + seq_name + '/pos/' + self.data_dict[seq_name]['pos'][index1]))
hard_neg_regions = self.process_regions(hard_neg_regions)
hard_class_id = self.data_dict[seq_name]['class_id']
hard_class_id = np.array([hard_class_id,])
return anchor_regions, pos_regions, neg_regions, hard_neg_regions, class_id, hard_class_id
def __len__(self):
# You should change 0 to the total size of your dataset.
return self.seq_num
LR_Rate = 1e-3
model = ft_net(class_num=1400)
ignored_params = list(map(id, model.classifier.parameters()))
base_params = filter(lambda p: id(p) not in ignored_params, model.parameters())
optimizer_ft = optim.SGD([
{'params': base_params, 'lr': 0.1 * LR_Rate},
{'params': model.classifier.parameters(), 'lr': LR_Rate}
], weight_decay=5e-4, momentum=0.9, nesterov=True)
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=40, gamma=0.1)
#criterion = nn.CrossEntropyLoss()
criterion = MixedLoss()
validation_criterion = TripletLoss()
model = model.cuda()
model.load_state_dict(torch.load('metric_model/metric_model_19448.pt'))
writer_path = './summary'
if not os.path.exists(writer_path):
os.mkdir(writer_path)
writer = SummaryWriter(writer_path)
BatchSize = 16
M = 2
im_per_seq = 4
data_path = '/home/xiaobai/Documents/LaSOT_crops/'
validation_data_path = '/home/xiaobai/Documents/lt2019_crops/'
dataset = CustomDataset(data_path)
validation_dataset = ValidationDataset(validation_data_path)
train_loader = torch_dataset.DataLoader(dataset=dataset, batch_size = BatchSize, shuffle=True)
validation_loader = torch_dataset.DataLoader(dataset=validation_dataset, batch_size = BatchSize, shuffle=True)
save_path = './metric_model'
if not os.path.exists(save_path):
os.mkdir(save_path)
#time2 = time.time()
#15K iteration lr->1e-3 19448 lr->1e-4
iter = 20144
for epoch in range(1000):
# if iter > 15000*M:
# LR_Rate = 1e-3
# optimizer_ft = optim.SGD([
# {'params': base_params, 'lr': 0.1 * LR_Rate},
# {'params': model.classifier.parameters(), 'lr': LR_Rate}
# ], weight_decay=5e-4, momentum=0.9, nesterov=True)
# if iter > 19400*M:
# LR_Rate = 1e-4
# optimizer_ft = optim.SGD([
# {'params': base_params, 'lr': 0.1 * LR_Rate},
# {'params': model.classifier.parameters(), 'lr': LR_Rate}
# ], weight_decay=5e-4, momentum=0.9, nesterov=True)
validation_loss = 0
validation_iter = 0
for anchor_regions, pos_regions, neg_regions, hard_neg_regions in validation_loader:
# time1 = time.time()
# print "read data time: ", time1 - time2
pos_regions = (Variable(pos_regions)).type(torch.FloatTensor).cuda()
anchor_regions = (Variable(anchor_regions)).type(torch.FloatTensor).cuda()
neg_regions = (Variable(neg_regions)).type(torch.FloatTensor).cuda()
hard_neg_regions = (Variable(hard_neg_regions)).type(torch.FloatTensor).cuda()
optimizer_ft.zero_grad()
anchor_metric, anchor_class = model(anchor_regions)
pos_metric, pos_class = model(pos_regions)
neg_metric, neg_class = model(neg_regions)
hard_neg_metric, hard_neg_class = model(hard_neg_regions)
loss = validation_criterion(anchor_metric, pos_metric, neg_metric, hard_neg_metric)
validation_loss = (validation_loss * validation_iter + loss.item()) / (validation_iter + 1)
validation_iter += 1
writer.add_scalar('validation_loss', validation_loss, epoch)
# print "epoch: ", epoch, ", iteration: ", iter, ", validation loss: ", validation_loss
for anchor_regions, pos_regions, neg_regions, hard_neg_regions, class_ids, hard_class_ids in train_loader:
#time1 = time.time()
#print "read data time: ", time1 - time2
pos_regions = (Variable(pos_regions)).type(torch.FloatTensor).cuda()
anchor_regions = (Variable(anchor_regions)).type(torch.FloatTensor).cuda()
neg_regions = (Variable(neg_regions)).type(torch.FloatTensor).cuda()
hard_neg_regions = (Variable(hard_neg_regions)).type(torch.FloatTensor).cuda()
class_ids = Variable(class_ids.cuda())
hard_class_ids = Variable(hard_class_ids.cuda())
optimizer_ft.zero_grad()
anchor_metric,anchor_class = model(anchor_regions)
pos_metric,pos_class = model(pos_regions)
neg_metric,neg_class = model(neg_regions)
hard_neg_metric, hard_neg_class = model(hard_neg_regions)
class_ids = torch.squeeze(class_ids, 1)
hard_class_ids = torch.squeeze(hard_class_ids, 1)
loss, matching_loss, class_loss = criterion(anchor_metric, pos_metric, neg_metric, hard_neg_metric, anchor_class, pos_class, neg_class, hard_neg_class, class_ids, hard_class_ids)
loss.backward()
writer.add_scalar('loss', loss.cpu(), iter)
writer.add_scalar('matching loss', matching_loss.cpu(), iter)
writer.add_scalar('classification loss', class_loss.cpu(), iter)
iter += 1
optimizer_ft.step()
# print "epoch: ", epoch, ", iteration: ", iter, ", loss: ", loss.item(), ", matching loss: ", matching_loss.item(), ", classification loss: ", class_loss.item()
#time2 = time.time()
#print "train time:", time2 - time1
if np.mod(epoch, 20) == 0:
torch.save(model.state_dict(), save_path+ '/' + save_path+'_'+str(iter)+'.pt')
writer.close()
| 47.13467
| 186
| 0.639574
| 2,320
| 16,450
| 4.286638
| 0.099138
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0
| 5
|
b0e45cd4fb489525f1aae2bd1885337e971e9af7
| 11
|
py
|
Python
|
login.py
|
wangxuehua/test27
|
91bd3b8d4f9a2ea8579133a2f76b53e7ea81ec49
|
[
"MIT"
] | null | null | null |
login.py
|
wangxuehua/test27
|
91bd3b8d4f9a2ea8579133a2f76b53e7ea81ec49
|
[
"MIT"
] | null | null | null |
login.py
|
wangxuehua/test27
|
91bd3b8d4f9a2ea8579133a2f76b53e7ea81ec49
|
[
"MIT"
] | null | null | null |
num1 = 111
| 5.5
| 10
| 0.636364
| 2
| 11
| 3.5
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| 11
| 1
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| 11
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0
| 5
|
b0067c89076b8d882e081c7365500cda37a978f5
| 125
|
py
|
Python
|
moocng/externalapps/exceptions.py
|
OpenMOOC/moocng
|
1e3dafb84aa1838c881df0c9bcca069e47c7f52d
|
[
"Apache-2.0"
] | 36
|
2015-01-10T06:00:36.000Z
|
2020-03-19T10:06:59.000Z
|
moocng/externalapps/exceptions.py
|
OpenMOOC/moocng
|
1e3dafb84aa1838c881df0c9bcca069e47c7f52d
|
[
"Apache-2.0"
] | 3
|
2015-10-01T17:59:32.000Z
|
2018-09-04T03:32:17.000Z
|
moocng/externalapps/exceptions.py
|
OpenMOOC/moocng
|
1e3dafb84aa1838c881df0c9bcca069e47c7f52d
|
[
"Apache-2.0"
] | 17
|
2015-01-13T03:46:58.000Z
|
2020-07-05T06:29:51.000Z
|
# -*- coding: utf-8 -*-
class InstanceLimitReached(Exception):
pass
class InstanceCreationError(Exception):
pass
| 12.5
| 39
| 0.696
| 11
| 125
| 7.909091
| 0.727273
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| 0.009804
| 0.184
| 125
| 9
| 40
| 13.888889
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| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
b031e6d886483f0f8b0bb2e08ac914d966e736b7
| 137
|
py
|
Python
|
build/lib/lambdata_nov05/__init__.py
|
nrvanwyck/Nov05_python-packages
|
39303b24513c21a6f1ab79b80cd9f8409df9e1f1
|
[
"MIT"
] | null | null | null |
build/lib/lambdata_nov05/__init__.py
|
nrvanwyck/Nov05_python-packages
|
39303b24513c21a6f1ab79b80cd9f8409df9e1f1
|
[
"MIT"
] | 1
|
2019-08-14T15:43:34.000Z
|
2019-08-14T15:43:34.000Z
|
build/lib/lambdata_nov05/__init__.py
|
nrvanwyck/Nov05_python-packages
|
39303b24513c21a6f1ab79b80cd9f8409df9e1f1
|
[
"MIT"
] | 1
|
2019-08-14T15:22:28.000Z
|
2019-08-14T15:22:28.000Z
|
name = "Technically the name is an attribute of the package object, so it can be anything as long as Python allows."
import pandas as pd
| 45.666667
| 116
| 0.773723
| 25
| 137
| 4.24
| 0.84
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.189781
| 137
| 3
| 117
| 45.666667
| 0.954955
| 0
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| 0.5
| 0.775362
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| 0
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| 0
| 0
| 1
| 0
| false
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| 0.5
| 0
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| 0
| 1
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| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
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| 0
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| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
b03c589a8d52fd21cd863bb7c8b8cb1810ea1d65
| 842
|
py
|
Python
|
demo2_ws/build/pal_person_detector_opencv/cmake/pal_person_detector_opencv-genmsg-context.py
|
AshfakYeafi/ros
|
7895302251088b7945e359f60a9c617e5170a72e
|
[
"MIT"
] | null | null | null |
demo2_ws/build/pal_person_detector_opencv/cmake/pal_person_detector_opencv-genmsg-context.py
|
AshfakYeafi/ros
|
7895302251088b7945e359f60a9c617e5170a72e
|
[
"MIT"
] | null | null | null |
demo2_ws/build/pal_person_detector_opencv/cmake/pal_person_detector_opencv-genmsg-context.py
|
AshfakYeafi/ros
|
7895302251088b7945e359f60a9c617e5170a72e
|
[
"MIT"
] | null | null | null |
# generated from genmsg/cmake/pkg-genmsg.context.in
messages_str = "/home/venom/ros/demo2_ws/src/ROS_Gazebo_Tutorial/pal_person_detector_opencv/msg/Detection2d.msg;/home/venom/ros/demo2_ws/src/ROS_Gazebo_Tutorial/pal_person_detector_opencv/msg/Detections2d.msg"
services_str = ""
pkg_name = "pal_person_detector_opencv"
dependencies_str = "geometry_msgs"
langs = "gencpp;geneus;genlisp;gennodejs;genpy"
dep_include_paths_str = "pal_person_detector_opencv;/home/venom/ros/demo2_ws/src/ROS_Gazebo_Tutorial/pal_person_detector_opencv/msg;geometry_msgs;/opt/ros/melodic/share/geometry_msgs/cmake/../msg;std_msgs;/opt/ros/melodic/share/std_msgs/cmake/../msg"
PYTHON_EXECUTABLE = "/usr/bin/python2"
package_has_static_sources = '' == 'TRUE'
genmsg_check_deps_script = "/opt/ros/melodic/share/genmsg/cmake/../../../lib/genmsg/genmsg_check_deps.py"
| 70.166667
| 250
| 0.820665
| 128
| 842
| 5.046875
| 0.445313
| 0.069659
| 0.131579
| 0.178019
| 0.369969
| 0.301858
| 0.301858
| 0.301858
| 0.301858
| 0.301858
| 0
| 0.007426
| 0.04038
| 842
| 11
| 251
| 76.545455
| 0.792079
| 0.058195
| 0
| 0
| 1
| 0.222222
| 0.743363
| 0.701643
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
| 1
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
c68063f9c038edad123ffd13761df7d81ab64b5e
| 89
|
py
|
Python
|
riberry/app/backends/__init__.py
|
srafehi/riberry
|
2ffa48945264177c6cef88512c1bc80ca4bf1d5e
|
[
"MIT"
] | 2
|
2019-12-09T10:24:36.000Z
|
2019-12-09T10:26:56.000Z
|
riberry/app/backends/__init__.py
|
srafehi/riberry
|
2ffa48945264177c6cef88512c1bc80ca4bf1d5e
|
[
"MIT"
] | 2
|
2018-06-11T11:34:28.000Z
|
2018-08-22T12:00:19.000Z
|
riberry/app/backends/__init__.py
|
srafehi/riberry
|
2ffa48945264177c6cef88512c1bc80ca4bf1d5e
|
[
"MIT"
] | null | null | null |
from .base import RiberryApplicationBackend
from .tracker import RiberryExecutionTracker
| 29.666667
| 44
| 0.88764
| 8
| 89
| 9.875
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089888
| 89
| 2
| 45
| 44.5
| 0.975309
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c69fe3e5e362f41a90ff5941187b26d61ddbabce
| 231
|
py
|
Python
|
lib/keybow2040/keybow_hardware/switches/__init__.py
|
bschapendonk/pim551
|
277b7eddb744ed2733a854bb8e96cd66ec05bd0c
|
[
"MIT"
] | 47
|
2021-04-28T15:55:29.000Z
|
2022-03-18T02:04:10.000Z
|
lib/keybow2040/keybow_hardware/switches/__init__.py
|
bschapendonk/pim551
|
277b7eddb744ed2733a854bb8e96cd66ec05bd0c
|
[
"MIT"
] | 12
|
2021-04-30T19:22:35.000Z
|
2022-02-09T10:16:57.000Z
|
lib/keybow2040/keybow_hardware/switches/__init__.py
|
bschapendonk/pim551
|
277b7eddb744ed2733a854bb8e96cd66ec05bd0c
|
[
"MIT"
] | 19
|
2021-04-28T15:43:56.000Z
|
2022-03-20T20:42:43.000Z
|
class Switches:
"""
Abstract class providing common interface to the set of switches
"""
def num_switches(self):
raise NotImplementedError
def switch_state(self, idx):
raise NotImplementedError
| 23.1
| 68
| 0.679654
| 25
| 231
| 6.2
| 0.72
| 0.309677
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25974
| 231
| 9
| 69
| 25.666667
| 0.906433
| 0.277056
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
c6a51b8e5bbac43133f193018b11abb359d81275
| 1,226
|
py
|
Python
|
src/big_torch/layers/abstract.py
|
Denchidlo/big-torch
|
f5a65e6216e46e6d4fe98670c52618e4cccc8163
|
[
"MIT"
] | null | null | null |
src/big_torch/layers/abstract.py
|
Denchidlo/big-torch
|
f5a65e6216e46e6d4fe98670c52618e4cccc8163
|
[
"MIT"
] | 1
|
2021-11-21T13:11:31.000Z
|
2021-11-22T00:18:29.000Z
|
src/big_torch/layers/abstract.py
|
Denchidlo/big-torch
|
f5a65e6216e46e6d4fe98670c52618e4cccc8163
|
[
"MIT"
] | null | null | null |
from abc import abstractmethod
import numpy as np
from ..utils.registry import ModuleAggregator
layer_registry = ModuleAggregator(registry_name="layers")
class AbstractLayer:
def __init__(self, shape) -> None:
self.shape = shape
@abstractmethod
def _fwd_pass(self, X):
raise NotImplementedError()
@abstractmethod
def _bwd_pass(self, X, d_out):
raise NotImplementedError()
class ParametrizedObject:
@abstractmethod
def blank(self):
raise NotImplementedError()
@abstractmethod
def get_context(self):
raise NotImplementedError()
@abstractmethod
def change(self, step, eta):
raise NotImplementedError()
@abstractmethod
def average(self, gradients_list):
raise NotImplementedError()
@abstractmethod
def apply(self, func, context=None):
raise NotImplementedError()
@abstractmethod
def binary_operation(lhs, rhs, operation):
raise NotImplementedError()
class GradientInputResolver:
@abstractmethod
def handle_multiple_inputs(*gradients):
raise NotImplementedError()
@abstractmethod
def get_handler(self, output_idx):
raise NotImplementedError()
| 21.892857
| 57
| 0.69739
| 115
| 1,226
| 7.278261
| 0.443478
| 0.203106
| 0.317802
| 0.342891
| 0.16368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.226754
| 1,226
| 55
| 58
| 22.290909
| 0.882911
| 0
| 0
| 0.512821
| 0
| 0
| 0.004894
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.282051
| false
| 0.051282
| 0.076923
| 0
| 0.435897
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
c6b709b31dfb1463405e87f5095cc74d16b6d386
| 44
|
py
|
Python
|
pglasso/__init__.py
|
NuosiWu/WFPGL
|
b3fb42c040ff289acdd01359d58959a10bb4913e
|
[
"MIT"
] | null | null | null |
pglasso/__init__.py
|
NuosiWu/WFPGL
|
b3fb42c040ff289acdd01359d58959a10bb4913e
|
[
"MIT"
] | null | null | null |
pglasso/__init__.py
|
NuosiWu/WFPGL
|
b3fb42c040ff289acdd01359d58959a10bb4913e
|
[
"MIT"
] | null | null | null |
from _pglasso import cpglasso_DC as pglasso
| 22
| 43
| 0.863636
| 7
| 44
| 5.142857
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 44
| 1
| 44
| 44
| 0.947368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
c6c2184f22c318efa9e703944efca210320ad3e9
| 96
|
py
|
Python
|
enthought/naming/unique_name.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | 3
|
2016-12-09T06:05:18.000Z
|
2018-03-01T13:00:29.000Z
|
enthought/naming/unique_name.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | 1
|
2020-12-02T00:51:32.000Z
|
2020-12-02T08:48:55.000Z
|
enthought/naming/unique_name.py
|
enthought/etsproxy
|
4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347
|
[
"BSD-3-Clause"
] | null | null | null |
# proxy module
from __future__ import absolute_import
from apptools.naming.unique_name import *
| 24
| 41
| 0.84375
| 13
| 96
| 5.769231
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114583
| 96
| 3
| 42
| 32
| 0.882353
| 0.125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c6c7e007680f0487433b83d1dd74ee9f07640774
| 115
|
py
|
Python
|
program.py
|
saivarshan/mynewrepo
|
0862ffe79315b90ae16dc246cc4cd6a5810669f8
|
[
"MIT"
] | null | null | null |
program.py
|
saivarshan/mynewrepo
|
0862ffe79315b90ae16dc246cc4cd6a5810669f8
|
[
"MIT"
] | null | null | null |
program.py
|
saivarshan/mynewrepo
|
0862ffe79315b90ae16dc246cc4cd6a5810669f8
|
[
"MIT"
] | null | null | null |
print("hello world")
print("i hope this works")
print("the error is fixed")
print("this is my second error fix")
| 28.75
| 36
| 0.704348
| 20
| 115
| 4.05
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.156522
| 115
| 4
| 36
| 28.75
| 0.835052
| 0
| 0
| 0
| 0
| 0
| 0.646018
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
c6f8282a44fb597d7e384cbc7dc1a5732d3ddfd0
| 141
|
py
|
Python
|
liver/gql/store/__init__.py
|
tjtimer/liver
|
1df06978d3d7d857d5824336de89fb9a0535c3dc
|
[
"MIT"
] | null | null | null |
liver/gql/store/__init__.py
|
tjtimer/liver
|
1df06978d3d7d857d5824336de89fb9a0535c3dc
|
[
"MIT"
] | null | null | null |
liver/gql/store/__init__.py
|
tjtimer/liver
|
1df06978d3d7d857d5824336de89fb9a0535c3dc
|
[
"MIT"
] | null | null | null |
"""
__init__.py
author: Tim "tjtimer" Jedro
created: 19.12.18
"""
from .person import Person, Friendship
from .task import Task, AssignedTo
| 15.666667
| 38
| 0.737589
| 20
| 141
| 5
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049587
| 0.141844
| 141
| 8
| 39
| 17.625
| 0.77686
| 0.404255
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
05b8ee1a8ae8a4228335629aa222b0279817f87e
| 631
|
py
|
Python
|
pyta/indicators/moving_average_divergence_convergence.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | 1
|
2021-10-10T08:00:21.000Z
|
2021-10-10T08:00:21.000Z
|
pyta/indicators/moving_average_divergence_convergence.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | null | null | null |
pyta/indicators/moving_average_divergence_convergence.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | null | null | null |
# TODO MACD histo
# TODO docstring
# TODO merge?
import pandas as pd
#
from pyta.overlays.exponential_moving_average import exponential_moving_average as ema
from pyta.indicators.absolute_price_oscillator import absolute_price_oscillator as apo
def moving_average_convergence_divergence(c: pd.Series, fast_n: int = 12, slow_n: int = 26) -> pd.Series:
return apo(c, fast_n, slow_n)
def moving_average_convergence_divergence_signal(c: pd.Series, fast_n: int = 12, slow_n: int = 26,
macd_n: int = 9) -> pd.Series:
macd = apo(c, fast_n, slow_n)
return ema(macd, macd_n)
| 35.055556
| 105
| 0.70523
| 95
| 631
| 4.421053
| 0.368421
| 0.047619
| 0.114286
| 0.128571
| 0.380952
| 0.204762
| 0.138095
| 0.138095
| 0.138095
| 0.138095
| 0
| 0.018109
| 0.212361
| 631
| 17
| 106
| 37.117647
| 0.826962
| 0.066561
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0
| 1
| 0.222222
| false
| 0
| 0.333333
| 0.111111
| 0.777778
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
05cdedfb27037c6eb7705b8381d043e86e16284e
| 34
|
py
|
Python
|
PyGaza/scripts/sploit_gaza.py
|
gaza-team/package
|
9992f48c2e02f29826c9e0a28c83016e4451176c
|
[
"MIT"
] | null | null | null |
PyGaza/scripts/sploit_gaza.py
|
gaza-team/package
|
9992f48c2e02f29826c9e0a28c83016e4451176c
|
[
"MIT"
] | null | null | null |
PyGaza/scripts/sploit_gaza.py
|
gaza-team/package
|
9992f48c2e02f29826c9e0a28c83016e4451176c
|
[
"MIT"
] | null | null | null |
# Exploit Title: Command Injection
| 34
| 34
| 0.823529
| 4
| 34
| 7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 34
| 1
| 34
| 34
| 0.933333
| 0.941176
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
05f1bb084b71043912e11505dbec51886b53785c
| 120
|
py
|
Python
|
calculator/admin.py
|
Skwaku/WebCalculator
|
94131f140f926e3234334663cfe87e2b1e5147bc
|
[
"MIT"
] | null | null | null |
calculator/admin.py
|
Skwaku/WebCalculator
|
94131f140f926e3234334663cfe87e2b1e5147bc
|
[
"MIT"
] | null | null | null |
calculator/admin.py
|
Skwaku/WebCalculator
|
94131f140f926e3234334663cfe87e2b1e5147bc
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import *
admin.site.site_header = "WebCal"
admin.site.register(History)
| 17.142857
| 33
| 0.783333
| 17
| 120
| 5.470588
| 0.647059
| 0.236559
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116667
| 120
| 7
| 34
| 17.142857
| 0.877358
| 0
| 0
| 0
| 0
| 0
| 0.049587
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
af0ad371717ff657d18ce3f9b4ac0822303c0d54
| 55
|
py
|
Python
|
wildwood/__init__.py
|
pyensemble/wildwood
|
b261cbd7d0b425b50647f719ab99c1d89f477d5c
|
[
"BSD-3-Clause"
] | 22
|
2021-06-24T11:30:03.000Z
|
2022-03-09T00:59:30.000Z
|
wildwood/__init__.py
|
pyensemble/wildwood
|
b261cbd7d0b425b50647f719ab99c1d89f477d5c
|
[
"BSD-3-Clause"
] | 65
|
2021-03-13T17:50:03.000Z
|
2022-02-22T16:50:02.000Z
|
wildwood/__init__.py
|
pyensemble/wildwood
|
b261cbd7d0b425b50647f719ab99c1d89f477d5c
|
[
"BSD-3-Clause"
] | 3
|
2021-03-04T18:44:10.000Z
|
2022-01-26T17:28:35.000Z
|
from .forest import ForestClassifier, ForestRegressor
| 18.333333
| 53
| 0.854545
| 5
| 55
| 9.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109091
| 55
| 2
| 54
| 27.5
| 0.959184
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
af3142c283f70bb8c2497536fe840ef57b032e00
| 4,220
|
py
|
Python
|
tests/st/param_name/test_parameter_ms_function.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | 1
|
2022-03-05T02:59:21.000Z
|
2022-03-05T02:59:21.000Z
|
tests/st/param_name/test_parameter_ms_function.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | null | null | null |
tests/st/param_name/test_parameter_ms_function.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 pytest
import mindspore as ms
from mindspore import context, Tensor, ms_function
from mindspore.common.parameter import Parameter
from mindspore.common import ParameterTuple
context.set_context(mode=context.GRAPH_MODE)
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_ms_function_1():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in ms_function.
Expectation: No exception.
"""
param_a = Parameter(Tensor([1], ms.float32), name="name_a")
param_b = Parameter(Tensor([2], ms.float32), name="name_a")
@ms_function
def test_parameter_ms_function():
return param_a + param_b
with pytest.raises(RuntimeError, match="its name 'name_a' already exists."):
res = test_parameter_ms_function()
assert res == 3
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_ms_function_2():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in ms_function.
Expectation: No exception.
"""
param_a = Parameter(Tensor([1], ms.float32), name="name_a")
param_b = param_a
@ms_function
def test_parameter_ms_function():
return param_a + param_b
res = test_parameter_ms_function()
assert res == 2
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_ms_function_3():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in ms_function.
Expectation: No exception.
"""
param_a = Parameter(Tensor([1], ms.float32))
param_b = Parameter(Tensor([2], ms.float32))
@ms_function
def test_parameter_ms_function():
return param_a + param_b
with pytest.raises(RuntimeError, match="its name 'Parameter' already exists."):
res = test_parameter_ms_function()
assert res == 3
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_ms_function_4():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in ms_function.
Expectation: No exception.
"""
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
param_a = ParameterTuple((Parameter(Tensor([1], ms.float32), name="name_a"),
Parameter(Tensor([2], ms.float32), name="name_a")))
@ms_function
def test_parameter_ms_function():
return param_a[0] + param_a[1]
res = test_parameter_ms_function()
assert res == 3
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_ms_function_5():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in ms_function.
Expectation: No exception.
"""
with pytest.raises(ValueError, match="its name 'Parameter' already exists."):
param_a = ParameterTuple((Parameter(Tensor([1], ms.float32)), Parameter(Tensor([2], ms.float32))))
@ms_function
def test_parameter_ms_function():
return param_a[0] + param_a[1]
res = test_parameter_ms_function()
assert res == 3
| 32.461538
| 106
| 0.704976
| 564
| 4,220
| 5.054965
| 0.205674
| 0.091196
| 0.07892
| 0.12101
| 0.770256
| 0.770256
| 0.763942
| 0.746054
| 0.742897
| 0.742897
| 0
| 0.018551
| 0.182464
| 4,220
| 129
| 107
| 32.713178
| 0.807826
| 0.298815
| 0
| 0.666667
| 0
| 0
| 0.059364
| 0
| 0
| 0
| 0
| 0
| 0.072464
| 1
| 0.144928
| false
| 0
| 0.072464
| 0.072464
| 0.289855
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
af5861e241fa7b85909c1c1829da7c08909a042c
| 291
|
py
|
Python
|
find_a_pad_app/views.py
|
findapad/find_a_pad
|
17fe271cfa9179a48dfb51ee4cc000d1614057f4
|
[
"MIT"
] | null | null | null |
find_a_pad_app/views.py
|
findapad/find_a_pad
|
17fe271cfa9179a48dfb51ee4cc000d1614057f4
|
[
"MIT"
] | 3
|
2017-07-09T20:14:28.000Z
|
2020-06-05T17:31:23.000Z
|
find_a_pad_app/views.py
|
findapad/find_a_pad
|
17fe271cfa9179a48dfb51ee4cc000d1614057f4
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
from django.http import HttpResponse
import requests
def main(request):
return render(request, 'welcome.html')
def search(request):
return render(request, 'search.html')
def location(request):
return render(request, 'location.html')
| 14.55
| 43
| 0.738832
| 36
| 291
| 5.972222
| 0.444444
| 0.181395
| 0.265116
| 0.362791
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161512
| 291
| 19
| 44
| 15.315789
| 0.881148
| 0
| 0
| 0
| 0
| 0
| 0.126761
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 0
|
0
| 5
|
af6b25dcc3cf88ff10084e08d725f0205304150e
| 480
|
py
|
Python
|
eznlp/nn/modules/__init__.py
|
syuoni/eznlp
|
c0380c6c30d68b4df1769150424735c04ea9d714
|
[
"Apache-2.0"
] | 9
|
2021-08-06T07:12:55.000Z
|
2022-03-26T08:20:59.000Z
|
eznlp/nn/modules/__init__.py
|
Hhx1999/eznlp
|
9d1397d8e9630c099295712cbcffa495353a3268
|
[
"Apache-2.0"
] | 1
|
2022-03-11T13:27:29.000Z
|
2022-03-16T11:52:14.000Z
|
eznlp/nn/modules/__init__.py
|
Hhx1999/eznlp
|
9d1397d8e9630c099295712cbcffa495353a3268
|
[
"Apache-2.0"
] | 3
|
2021-11-15T03:24:24.000Z
|
2022-03-09T09:36:05.000Z
|
# -*- coding: utf-8 -*-
from .embedding import SinusoidPositionalEncoding
from .aggregation import SequencePooling, SequenceGroupAggregating, ScalarMix
from .attention import SequenceAttention
from .block import FeedForwardBlock, ConvBlock, MultiheadAttention, TransformerEncoderBlock, TransformerDecoderBlock
from .dropout import WordDropout, LockedDropout, CombinedDropout
from .crf import CRF
from .loss import SoftLabelCrossEntropyLoss, SmoothLabelCrossEntropyLoss, FocalLoss
| 53.333333
| 116
| 0.85625
| 41
| 480
| 10.02439
| 0.682927
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002288
| 0.089583
| 480
| 8
| 117
| 60
| 0.938215
| 0.04375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
afc72fed7dbd50a9cfdb5668103a2118ac74b4d2
| 127
|
py
|
Python
|
survos2/frontend/model.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 4
|
2017-10-10T14:47:16.000Z
|
2022-01-14T05:57:50.000Z
|
survos2/frontend/model.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 1
|
2022-01-11T21:11:12.000Z
|
2022-01-12T08:22:34.000Z
|
survos2/frontend/model.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 2
|
2018-03-06T06:31:29.000Z
|
2019-03-04T03:33:18.000Z
|
from dataclasses import dataclass
from survos2.helpers import AttrDict
@dataclass
class ClientData:
cfg: AttrDict
| 15.875
| 37
| 0.76378
| 14
| 127
| 6.928571
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009901
| 0.204724
| 127
| 7
| 38
| 18.142857
| 0.950495
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
afd3ab765a9832ea2c40b94fe0fb6bac305ff98a
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/pip/_internal/operations/install/__init__.py
|
GiulianaPola/select_repeats
|
17a0d053d4f874e42cf654dd142168c2ec8fbd11
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/pip/_internal/operations/install/__init__.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/pip/_internal/operations/install/__init__.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/99/7e/e1/c83d863413b69851a8903437d2bfc65efed8fcf2ddb71714bf5e387beb
| 96
| 96
| 0.895833
| 9
| 96
| 9.555556
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.395833
| 0
| 96
| 1
| 96
| 96
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
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