xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

ff7628b4ddb338caad227f33c23db7200a19eebe

2,748

py

Python

migrations/versions/46f261240bcb_add_challenge_and_order_tracking.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

1

2021-11-16T17:25:21.000Z

migrations/versions/46f261240bcb_add_challenge_and_order_tracking.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

1

2021-12-22T19:04:34.000Z

migrations/versions/46f261240bcb_add_challenge_and_order_tracking.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

null

"""add challenge and order tracking Revision ID: 46f261240bcb Revises: 0d14cc3a1cf1 Create Date: 2021-09-14 00:14:56.893591 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "46f261240bcb" down_revision = "0d14cc3a1cf1" branch_labels = None depends_on = None def upgrade(engine_name): globals()["upgrade_%s" % engine_name]() def downgrade(engine_name): globals()["downgrade_%s" % engine_name]() def upgrade_cdn(): # ### commands auto generated by Alembic - please adjust! ### op.create_table( "challenges", sa.Column("id", sa.Integer(), nullable=False), sa.Column("certificate_id", sa.Integer(), nullable=False), sa.Column("domain", sa.String(), nullable=False), sa.Column("validation_path", sa.String(), nullable=False), sa.Column("validation_contents", sa.Text(), nullable=False), sa.Column("body_json", sa.Text(), nullable=True), sa.Column("answered", sa.Boolean(), nullable=True), sa.ForeignKeyConstraint( ["certificate_id"], ["certificates.id"], name=op.f("fk_challenges_certificate_id_certificates"), ), sa.PrimaryKeyConstraint("id", name=op.f("pk_challenges")), ) op.add_column("certificates", sa.Column("order_json", sa.Text(), nullable=True)) # ### end Alembic commands ### def downgrade_cdn(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column("certificates", "order_json") op.drop_table("challenges") # ### end Alembic commands ### def upgrade_domain(): # ### commands auto generated by Alembic - please adjust! ### op.create_table( "challenges", sa.Column("id", sa.Integer(), nullable=False), sa.Column("certificate_id", sa.Integer(), nullable=False), sa.Column("domain", sa.String(), nullable=False), sa.Column("validation_path", sa.String(), nullable=False), sa.Column("validation_contents", sa.Text(), nullable=False), sa.Column("body_json", sa.Text(), nullable=True), sa.Column("answered", sa.Boolean(), nullable=True), sa.ForeignKeyConstraint( ["certificate_id"], ["certificates.id"], name=op.f("fk_challenges_certificate_id_certificates"), ), sa.PrimaryKeyConstraint("id", name=op.f("pk_challenges")), ) op.add_column("certificates", sa.Column("order_json", sa.Text(), nullable=True)) # ### end Alembic commands ### def downgrade_domain(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column("certificates", "order_json") op.drop_table("challenges") # ### end Alembic commands ###

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null

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null

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5

440a342b8ca08a24752e4a819bc871cc97b8631b

101

py

Python

pamak/Environment.py

tanguyesteoule/pamak

3dc1eb6f89c51ae4689851b770c879f4d9004bc1

[ "MIT" ]

null

pamak/Environment.py

tanguyesteoule/pamak

3dc1eb6f89c51ae4689851b770c879f4d9004bc1

[ "MIT" ]

null

pamak/Environment.py

tanguyesteoule/pamak

3dc1eb6f89c51ae4689851b770c879f4d9004bc1

[ "MIT" ]

null

from abc import ABCMeta class Environment(metaclass=ABCMeta): def __init__(self): pass

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5

442ba7b04bd6f7874453db2dd8a47d39858e95b2

81

py

Python

src/omv/boards/PICO/manifest.py

elmagnificogi/openmv

bc0c9fa5fa93d3dbe07e67b01e1355620a7f1d08

[ "MIT" ]

1,761

2015-07-10T23:14:17.000Z

2022-03-30T07:49:49.000Z

src/omv/boards/PICO/manifest.py

elmagnificogi/openmv

bc0c9fa5fa93d3dbe07e67b01e1355620a7f1d08

[ "MIT" ]

487

2015-07-07T23:21:20.000Z

2022-03-30T17:13:22.000Z

src/omv/boards/PICO/manifest.py

elmagnificogi/openmv

bc0c9fa5fa93d3dbe07e67b01e1355620a7f1d08

[ "MIT" ]

882

2015-08-01T08:34:19.000Z

2022-03-30T07:36:23.000Z

freeze ("$(PORT_DIR)/modules") include("$(MPY_DIR)/extmod/uasyncio/manifest.py")

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null

0

1

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5

445279999d993aaa867ea8d6dc2b4d35c3259eac

211

py

Python

pillar-tracker/utils/discord_wrapper.py

zenon-tools/pillar-tracker

61ca9c47be438ffb7b9fc1f8424600e6189ba7b9

[ "MIT" ]

null

pillar-tracker/utils/discord_wrapper.py

zenon-tools/pillar-tracker

61ca9c47be438ffb7b9fc1f8424600e6189ba7b9

[ "MIT" ]

null

pillar-tracker/utils/discord_wrapper.py

zenon-tools/pillar-tracker

61ca9c47be438ffb7b9fc1f8424600e6189ba7b9

[ "MIT" ]

null

from utils.http_wrapper import HttpWrapper class DiscordWrapper(object): def webhook_send_message_to_channel(self, webhook_url, message): return HttpWrapper.post(webhook_url, {'content': message})

30.142857

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null

0

1

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5

447591180b32c470067d7085215515394cdfd85e

189

py

Python

tests/test_health.py

andrewtbiehl/gaslines

9ccac6211bb20351d0f80312806baf4b6a07e111

[ "MIT" ]

1

2020-09-10T04:41:51.000Z

tests/test_health.py

andrewtbiehl/gaslines

9ccac6211bb20351d0f80312806baf4b6a07e111

[ "MIT" ]

31

2020-11-11T04:32:35.000Z

2022-03-31T19:16:01.000Z

tests/test_health.py

andrewtbiehl/gaslines

9ccac6211bb20351d0f80312806baf4b6a07e111

[ "MIT" ]

null

"""Trivial test module for verifying that unit tests are running as expected.""" def test_health(): """ This health check test should pass no matter what. """ assert True

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189

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0.884615

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0.238095

189

8

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true

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null

0

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5

44967a7d4c273b311057650675e531b45a19004d

63

py

Python

PyUnits/__init__.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

PyUnits/__init__.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

PyUnits/__init__.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

from .quantities import SIUnits, SIDerivedUnits, ImperialUnits

31.5

62

0.857143

6

63

9

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63

0.947368

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null

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1

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1

0

1

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5

92a43a53db72787f3800226bf7202bec42234cc3

132

py

Python

Wrapping/CSwig/Python/itkio.py

kiranhs/ITKv4FEM-Kiran

0e4ab3b61b5fc4c736f04a73dd19e41390f20152

[ "BSD-3-Clause" ]

1

2018-04-15T13:32:43.000Z

Wrapping/CSwig/Python/itkio.py

kiranhs/ITKv4FEM-Kiran

0e4ab3b61b5fc4c736f04a73dd19e41390f20152

[ "BSD-3-Clause" ]

null

Wrapping/CSwig/Python/itkio.py

kiranhs/ITKv4FEM-Kiran

0e4ab3b61b5fc4c736f04a73dd19e41390f20152

[ "BSD-3-Clause" ]

null

from itkcommon import * __itk_import_data__ = itkbase.preimport() from ITKIOPython import * itkbase.postimport(__itk_import_data__)

26.4

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16

132

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132

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false

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null

0

1

0

1

0

5

2ba972ec8519c2b4330243294be708aa998d1667

19,583

py

Python

tests/native/django/test_templatetag.py

transifex/transifex-python

d467e82bba7f0d620a021cf9e7e58c987ba2fbb5

[ "Apache-2.0" ]

14

2020-04-10T20:54:59.000Z

2022-03-07T16:13:22.000Z

tests/native/django/test_templatetag.py

transifex/transifex-python

d467e82bba7f0d620a021cf9e7e58c987ba2fbb5

[ "Apache-2.0" ]

60

2020-04-14T12:41:06.000Z

2022-03-29T06:38:09.000Z

tests/native/django/test_templatetag.py

transifex/transifex-python

d467e82bba7f0d620a021cf9e7e58c987ba2fbb5

[ "Apache-2.0" ]

6

2021-01-01T10:28:11.000Z

2021-06-10T09:50:26.000Z

from __future__ import unicode_literals from django.template import Context, Template from django.utils import translation from transifex.common.utils import generate_key from transifex.native import tx from transifex.native.django.templatetags.utils import get_icu_keys from transifex.native.rendering import SourceStringPolicy def do_test(template_str, context_dict=None, autoescape=True, lang_code="en-us"): """ Use django's templating engine to render a template against a context Arguments: :param template_str: The template to render :param context_dict: The context to render the template against :param autoescape: Pretend the django templating engine was setup with autoescape or not (in most real use-cases, it will have been set up with autoescape=True) :param lang_code: The language to translate to :return: The compilation result Information about (auto)escaping in django: https://docs.djangoproject.com/en/3.0/ref/templates/language/#automatic-html-escaping # noqa """ translation.activate(lang_code) if context_dict is None: context_dict = {} context = Context(dict(context_dict), autoescape=autoescape) template = ('{% load transifex %}' + template_str) return Template(template).render(context) def test_simple(): assert do_test('{% t "hello world" %}') == "hello world" def test_equal_sign(): # '=' in first arg means parameter and thus block syntax assert do_test('{% t var="world" %}hello {var}{% endt %}') == "hello world" # '=' in first arg when first arg is a string literal means it is not a # parameter and thus inline syntax assert do_test('{% t "hello=world" %}') == "hello=world" def test_escaping_with_t_tag_and_autoescape(): # t-tag and autoescape means both XMLs are escaped assert (do_test('{% t "<xml>hello</xml> {var}" %}', {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_t_tag_and_no_autoescape(): # t-tag and no autoescape means only template XML is escaped assert (do_test('{% t "<xml>hello</xml> {var}" %}', {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_t_tag_and_param(): # With `var=var`, we have the same outcome as before assert (do_test('{% t "<xml>hello</xml> {var}" var=var %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}" var=var %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_t_tag_and_safe_param(): # With `var=var|safe`, `autoescape` is ignored and context XML is not # escaped assert (do_test('{% t "<xml>hello</xml> {var}" var=var|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}" var=var|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_t_tag_and_escaped_param(): # With `var=var|escape`, `autoescape` is ignored and context XML is always # escaped assert (do_test('{% t "<xml>hello</xml> {var}" var=var|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}" var=var|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_ut_tag_and_autoescape(): # ut-tag and autoescape means only context XML is escaped assert (do_test('{% ut "<xml>hello</xml> {var}" %}', {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_ut_tag_and_no_autoescape(): # ut-tag and no autoescape means no XML is escaped assert (do_test('{% ut "<xml>hello</xml> {var}" %}', {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_ut_tag_and_param(): # With `var=var`, we have the same outcome as before assert (do_test('{% ut "<xml>hello</xml> {var}" var=var %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}" var=var %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_ut_tag_and_safe_param(): # With `var=var|safe`, `autoescape` is ignored and context XML is not # escaped assert (do_test('{% ut "<xml>hello</xml> {var}" var=var|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}" var=var|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_escaping_with_ut_tag_and_escaped_param(): # With `var=var|escape`, `autoescape` is ignored and context XML is always # escaped assert (do_test('{% ut "<xml>hello</xml> {var}" var=var|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}" var=var|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_filters_on_source_string(): assert (do_test('{% t "<xml>hello</xml> {var}"|upper %}', # ^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '&LT;XML&GT;HELLO&LT;/XML&GT; &LT;XML&GT;WORLD&LT;/XML&GT;') assert (do_test('{% t "<xml>hello</xml> {var}"|upper %}', # ^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '&LT;XML&GT;HELLO&LT;/XML&GT; <XML>WORLD</XML>') assert (do_test('{% ut "<xml>hello</xml> {var}"|upper %}', # ^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<XML>HELLO</XML> &LT;XML&GT;WORLD&LT;/XML&GT;') assert (do_test('{% ut "<xml>hello</xml> {var}"|upper %}', # ^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<XML>HELLO</XML> <XML>WORLD</XML>') def test_escape_and_safe_filters_on_source_string_ignored(): assert (do_test('{% t "<xml>hello</xml> {var}"|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}"|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}"|escape %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}"|safe %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_asvar(): assert (do_test('{% ut "<xml>hello</xml> {var}" as text %}{{ text }}', # ^^^^^^^ ^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut "<xml>hello</xml> {var}" as text %}{{ text }}', # ^^^^^^^ ^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}" as text %}{{ text }}', # ^^^^^^^ ^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t "<xml>hello</xml> {var}" as text %}{{ text }}', # ^^^^^^^ ^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_filter_on_asvar(): assert ( do_test( '{% t "<xml>hello</xml> {var}" as text %}{{ text|upper|safe }}', # ^^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True, ) == '&LT;XML&GT;HELLO&LT;/XML&GT; &LT;XML&GT;WORLD&LT;/XML&GT;' ) def test_escape_and_safe_filter_on_asvar_ignored(): assert (do_test('{% t "<xml>hello</xml> {var}" as text %}{{ text|safe }}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert ( do_test('{% t "<xml>hello</xml> {var}" as text %}{{ text|escape }}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>' ) def test_translate_variable(): assert (do_test('{% ut source %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut source %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t source %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t source %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') def test_filter_on_source_variable(): assert (do_test('{% ut source|upper %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '<XML>HELLO</XML> &LT;XML&GT;WORLD&LT;/XML&GT;') assert (do_test('{% ut source|upper %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=False) == '<XML>HELLO</XML> <XML>WORLD</XML>') assert (do_test('{% t source|upper %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '&LT;XML&GT;HELLO&LT;/XML&GT; &LT;XML&GT;WORLD&LT;/XML&GT;') assert (do_test('{% t source|upper %}', # ^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=False) == '&LT;XML&GT;HELLO&LT;/XML&GT; <XML>WORLD</XML>') def test_safe_and_escape_filter_on_source_variable_ignored(): assert (do_test('{% t source|safe %}', # ^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t source|escape %}', # ^^^^^^^ {'source': "<xml>hello</xml> {var}", 'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_block(): assert (do_test('{% t %}hello world{% endt %}') == 'hello world') # ^^^^^^^^^^^^^^^^^^^^^ assert (do_test('{% t %}hello {var}{% endt %}', {'var': "world"}) == # ^^^^^^^^^^^^^^^^^^^^^ 'hello world') assert (do_test('{% ut %}<xml>hello</xml> {var}{% endut %}', # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut %}<xml>hello</xml> {var}{% endut %}', # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t %}<xml>hello</xml> {var}{% endt %}', # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=False) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t %}<xml>hello</xml> {var}{% endt %}', # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_filter_on_block(): assert (do_test('{% t |upper %}hello world{% endt %}') == 'HELLO WORLD') # ^^^^^^ def test_safe_and_escape_filter_on_block_ignored(): assert (do_test('{% ut |safe %}<xml>hello</xml> {var}{% endut %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% ut |escape %}<xml>hello</xml> {var}{% endut %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t |safe %}<xml>hello</xml> {var}{% endt %}', # ^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') assert (do_test('{% t |escape %}<xml>hello</xml> {var}{% endt %}', # ^^^^^^^ {'var': "<xml>world</xml>"}, autoescape=True) == '<xml>hello</xml> <xml>world</xml>') def test_translates(): hello_key = generate_key(string='hello', context=None) tx._cache.update({'fr': (True, {hello_key: {'string': "bonjour"}})}) assert do_test('{% t "hello" %}', lang_code="fr") == "bonjour" def test_translation_missing(): old_missing_policy = tx._missing_policy tx._missing_policy = SourceStringPolicy() tx._cache._translations_by_lang = {} assert do_test('{% t "hello" %}', lang_code="fr") == "hello" hello_key = generate_key(string='hello', context=None) tx._cache.update({'fr': (True, {hello_key: {'string': None}})}) assert do_test('{% t "hello" %}', lang_code="fr") == "hello" tx._missing_policy = old_missing_policy def test_escaping_is_done_on_translation(): hello_key = generate_key(string='hello', context=None) tx._cache.update( {'fr': (True, {hello_key: {'string': "<xml>bonjour</xml>"}})}) assert (do_test('{% t "hello" %}', lang_code="fr") == '<xml>bonjour</xml>') def test_source_filter_is_applied_on_translation(): # 'hello' => 'bonjour', 'HELLO' => 'I like pancakes' hello_key = generate_key(string='hello', context=None) HELLO_key = generate_key(string='HELLO', context=None) tx._cache.update( {'fr': ( True, { hello_key: {'string': "bonjour"}, HELLO_key: {'string': "I like pancakes"} } )}) assert do_test('{% t "hello"|upper %}', lang_code="fr") == "BONJOUR" # If the filter was applied on the source string, we would get # 'I like pancakes' translation.activate('en-us') def test_get_icu_keys(): assert "username" in get_icu_keys("hello {username}") assert "cnt" in get_icu_keys(""" {cnt, plural, one {you have one message} other {you have # new messages}} """) # Nesting assert "username" in get_icu_keys(""" {gender, select, male {{username} is a boy} female {{username} is a girl}} """) # Return empty on error assert get_icu_keys("{{{") == set()

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0.097925

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1

0

null

0

5

2beaebe6b30822fa91a880b7b153a22b8d1c6af8

97

py

Python

ginga/misc/CanvasTypes.py

Cadair/ginga

5afdd8824f27c7ae7d8d82b5013b0ff0068bd8b8

[ "BSD-3-Clause" ]

null

ginga/misc/CanvasTypes.py

Cadair/ginga

5afdd8824f27c7ae7d8d82b5013b0ff0068bd8b8

[ "BSD-3-Clause" ]

20

2021-05-03T18:02:23.000Z

2022-03-12T12:01:04.000Z

Lib/site-packages/ginga/misc/CanvasTypes.py

fochoao/cpython

3dc84b260e5bced65ebc2c45c40c8fa65f9b5aa9

[ "bzip2-1.0.6", "0BSD" ]

null

# THIS FILE TO BE DEPRECATED from ginga.gw.Viewers import * from ginga.canvas.types.all import *

24.25

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null

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1

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2bf80a21b0bf7d9ef3cdcb185d79bd6a1b140f79

20

py

Python

example_project/some_modules/third_modules/a49.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

example_project/some_modules/third_modules/a49.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

example_project/some_modules/third_modules/a49.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

class A49: pass

6.666667

10

0.6

3

20

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0.35

20

2

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true

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null

0

1

0

null

0

1

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5

2bff531991b2401db33399da35749f2eb6bfbe73

38

py

Python

mypackagebapat/__init__.py

PrathamBapat/mypackagebapat

237693ec84dc52f8229a5e0101073b64ef7396a2

[ "MIT" ]

null

mypackagebapat/__init__.py

PrathamBapat/mypackagebapat

237693ec84dc52f8229a5e0101073b64ef7396a2

[ "MIT" ]

null

mypackagebapat/__init__.py

PrathamBapat/mypackagebapat

237693ec84dc52f8229a5e0101073b64ef7396a2

[ "MIT" ]

null

from mypackagebapat.mymath import one

19

37

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5

38

6.6

1

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38

1

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0.970588

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null

0

1

0

1

0

5

921dc1a007b3d6baf5cb515b254c4181b3a856a3

235

py

Python

src/pyfme/__init__.py

jdebecdelievre/PyFME

45a46c9dccfaf4961dc9a7320ff43a24e28eb4e4

[ "MIT" ]

1

2021-01-24T19:34:46.000Z

src/pyfme/__init__.py

jdebecdelievre/PyFME

45a46c9dccfaf4961dc9a7320ff43a24e28eb4e4

[ "MIT" ]

null

src/pyfme/__init__.py

jdebecdelievre/PyFME

45a46c9dccfaf4961dc9a7320ff43a24e28eb4e4

[ "MIT" ]

null

""" Python Flight Mechanics Engine (PyFME). Copyright (c) AeroPython Development Team. Distributed under the terms of the MIT License. """ from .aircrafts import Aircraft from .models.state import BodyAxisStateQuaternion as State

33.571429

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235

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true

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null

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null

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1

0

1

0

1

0

5

a616aea5ef16fe7a62ec5c5224becacb3ed507d2

371

py

Python

lib/googlecloudsdk/third_party/apis/storage/v1/__init__.py

bopopescu/SDK

e6d9aaee2456f706d1d86e8ec2a41d146e33550d

[ "Apache-2.0" ]

null

lib/googlecloudsdk/third_party/apis/storage/v1/__init__.py

bopopescu/SDK

e6d9aaee2456f706d1d86e8ec2a41d146e33550d

[ "Apache-2.0" ]

null

lib/googlecloudsdk/third_party/apis/storage/v1/__init__.py

bopopescu/SDK

e6d9aaee2456f706d1d86e8ec2a41d146e33550d

[ "Apache-2.0" ]

2

2020-11-04T03:08:21.000Z

2020-11-05T08:14:41.000Z

"""Common imports for generated storage client library.""" # pylint:disable=wildcard-import import pkgutil from googlecloudsdk.third_party.apitools.base.py import * from googlecloudsdk.third_party.apis.storage.v1.storage_v1_client import * from googlecloudsdk.third_party.apis.storage.v1.storage_v1_messages import * __path__ = pkgutil.extend_path(__path__, __name__)

33.727273

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0.125

0.239583

0.291667

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371

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false

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0.8

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null

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0

1

0

null

0

1

0

1

0

5

a655a8e2b34c1bd7e5db280de5ac96a6557c9aae

144

py

Python

website/config.py

ChandrapalSd/uidaiproject

ca4d20bd09e1fc8f80d74ad118703b569ffa559f

[ "MIT" ]

1

2021-11-04T15:38:31.000Z

website/config.py

uidaitc/uidaiproject

ca4d20bd09e1fc8f80d74ad118703b569ffa559f

[ "MIT" ]

null

website/config.py

uidaitc/uidaiproject

ca4d20bd09e1fc8f80d74ad118703b569ffa559f

[ "MIT" ]

1

2021-11-01T03:15:25.000Z

twilio_account_sid = 'ACe9b68d4263ba50054c2bcb0c74f48124' twilio_auth_token = 'bba7ab6b769642caf2df6c5538597198' twilio_number = '+13203001833'

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0

0.385185

0.0625

144

3

58

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0.458333

0

1

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false

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1

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1

null

0

1

0

1

0

1

null

0

5

a65b4c2c95b9e6dee548cf924f482c0405016640

19

py

Python

pypbbot/testing.py

PHIKN1GHT/pypbbot_archived

8ab70830509c43b0babc53c9972d0a73481bdaa2

[ "MIT" ]

null

pypbbot/testing.py

PHIKN1GHT/pypbbot_archived

8ab70830509c43b0babc53c9972d0a73481bdaa2

[ "MIT" ]

null

pypbbot/testing.py

PHIKN1GHT/pypbbot_archived

8ab70830509c43b0babc53c9972d0a73481bdaa2

[ "MIT" ]

null

# Nothing here ^_^

9.5

18

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2

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5.5

1

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19

1

19

0.733333

0.842105

0

null

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null

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null

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null

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null

true

0

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null

0

1

0

1

0

null

0

1

0

5

a67b40897216dcc76d69aad8eeff9d4bcbb4a805

15,352

py

Python

FetchEachStepData.py

Abhijeet1990/MultiSensorDataFusion

d2cc770ebb777ffc380a6b7548a6c5c271bf9cf8

[ "MIT" ]

null

FetchEachStepData.py

Abhijeet1990/MultiSensorDataFusion

d2cc770ebb777ffc380a6b7548a6c5c271bf9cf8

[ "MIT" ]

null

FetchEachStepData.py

Abhijeet1990/MultiSensorDataFusion

d2cc770ebb777ffc380a6b7548a6c5c271bf9cf8

[ "MIT" ]

null

__author__ = "Abhijeet Sahu" __credits__ = ["Abhijeet Sahu"] __email__ = "abhijeet_ntpc@tamu.edu" __affiliation__ = "Texas A&M University" # Get Data based on the use case import pandas as pd import numpy as np from DataFusion import DataFusion import time import datetime import msgpack as mp import sys def get_intrusion_window(adversary_path): fusion = DataFusion() fusion.load_json(adversary_path) fusion.extract_cyber_data() fusion.extract_physical_data() data_to_process = fusion.merge() attack_start = data_to_process.iloc[0]['Time'] start = int(time.mktime(attack_start.timetuple())) attack_end = data_to_process.iloc[-1]['Time'] end = int(time.mktime(attack_end.timetuple())) return start,end def get_lucene_query(start_time, end_time): json_body = { "query": { "bool": { "must": [ { "range": { "event.end": { "gte": start_time, "lte": end_time } } }, {"range": { "event.duration": { "gte": 0, "lte": 3000000 } }}, {"bool": {"should": [ {"match": { "destination.port": "20000" }} , { "match": { "source.port": "20000" } } ] } } ] } } } return json_body def get_file_path(_usecase,_os,_poll_rate,location): usecase=_usecase os=_os poll_rate = _poll_rate start_time='2020-10-17T12:28:00.000Z' end_time='2020-10-17T20:45:00.000Z' common_path ='../data/RawFiles/' if os==10 and poll_rate ==60 and usecase=='UC1': jsonpath='Raw/UC1_'+location+'_10OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll60_UC1.pickle' snort_path='snort/UC1_PyDNP3_CORE_Snort_10_OS_60_1017' start_time='2020-10-17T17:45:00.000Z' end_time='2020-10-17T18:30:00.000Z' elif os==10 and poll_rate ==30 and usecase=='UC1': jsonpath='Raw/UC1_'+location+'_10OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll30_UC1.pickle' snort_path='snort/UC1_PyDNP3_CORE_Snort_10_OS_30_1017' start_time='2020-10-17T15:30:00.000Z' end_time='2020-10-17T16:15:00.000Z' elif os==5 and poll_rate ==30 and usecase=='UC2': jsonpath='Raw/UC2_'+location+'_5OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll30_UC2.pickle' snort_path='snort/UC2_PyDNP3_CORE_Snort_5_OS_30_1017' start_time='2020-10-17T17:50:00.000Z' end_time='2020-10-17T18:30:00.000Z' elif os==5 and poll_rate ==60 and usecase=='UC2': jsonpath='Raw/UC2_'+location+'_5OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll60_UC2.pickle' snort_path='snort/UC2_PyDNP3_CORE_Snort_5_OS_60_1017' start_time='2020-10-17T19:35:00.000Z' end_time='2020-10-17T20:00:00.000Z' elif os==10 and poll_rate ==30 and usecase=='UC2': jsonpath='Raw/UC2_'+location+'_10OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll30_UC2.pickle' snort_path='snort/UC2_PyDNP3_CORE_Snort_10_OS_30_1017' start_time='2020-10-17T15:50:00.000Z' end_time='2020-10-17T16:30:00.000Z' elif os==10 and poll_rate ==60 and usecase=='UC2': jsonpath='Raw/UC2_'+location+'_10OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll60_UC2.pickle' snort_path='snort/UC2_PyDNP3_CORE_Snort_10_OS_60_1017' start_time='2020-10-17T18:15:00.000Z' end_time='2020-10-17T18:45:00.000Z' elif os==5 and poll_rate ==30 and usecase=='UC3': jsonpath='Raw/UC3_'+location+'_5OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll30_UC3.pickle' snort_path='snort/UC3_PyDNP3_CORE_Snort_5_OS_30_1017' start_time='2020-10-17T17:40:00.000Z' end_time='2020-10-17T18:05:00.000Z' elif os==5 and poll_rate ==60 and usecase=='UC3': jsonpath='Raw/UC3_'+location+'_5OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll60_UC3.pickle' snort_path='snort/UC3_PyDNP3_CORE_Snort_5_OS_60_1017' start_time='2020-10-17T19:15:00.000Z' end_time='2020-10-17T19:45:00.000Z' elif os==10 and poll_rate ==30 and usecase=='UC3': jsonpath='Raw/UC3_'+location+'_10OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll30_UC3.pickle' snort_path='snort/UC3_PyDNP3_CORE_Snort_10_OS_30_1017' start_time='2020-10-17T16:15:00.000Z' end_time='2020-10-17T16:50:00.000Z' elif os==10 and poll_rate ==60 and usecase=='UC3': jsonpath='Raw/UC3_'+location+'_10OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll60_UC3.pickle' snort_path='snort/UC3_PyDNP3_CORE_Snort_10_OS_60_1017' start_time='2020-10-17T18:30:00.000Z' end_time='2020-10-17T19:00:00.000Z' elif os==5 and poll_rate ==30 and usecase=='UC4': jsonpath='Raw/UC4_'+location+'_5OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll30_UC4.pickle' snort_path='snort/UC4_PyDNP3_CORE_Snort_5_OS_30_1017' start_time='2020-10-17T17:25:00.000Z' end_time='2020-10-17T17:55:00.000Z' elif os==5 and poll_rate ==60 and usecase=='UC4': jsonpath='Raw/UC4_'+location+'_5OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_5os_poll60_UC4.pickle' snort_path='snort/UC4_PyDNP3_CORE_Snort_5_OS_60_1017' start_time='2020-10-17T19:00:00.000Z' end_time='2020-10-17T19:30:00.000Z' elif os==10 and poll_rate ==30 and usecase=='UC4': jsonpath='Raw/UC4_'+location+'_10OS_poll30_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll30_UC4.pickle' snort_path='snort/UC4_PyDNP3_CORE_Snort_10_OS_30_1017' start_time='2020-10-17T17:05:00.000Z' end_time='2020-10-17T17:35:00.000Z' elif os==10 and poll_rate ==60 and usecase=='UC4': jsonpath='Raw/UC4_'+location+'_10OS_poll60_dnp3_arp.json' pickle_path='PickleFiles/'+location+'_dnp3_arp_10os_poll60_UC4.pickle' snort_path='snort/UC4_PyDNP3_CORE_Snort_10_OS_60_1017' start_time='2020-10-17T18:40:00.000Z' end_time='2020-10-17T19:15:00.000Z' jsonpath = common_path+location+'/'+jsonpath pickle_path = common_path+location+'/'+pickle_path snort_path = common_path+snort_path return jsonpath, pickle_path, snort_path, start_time, end_time #### Arguments ############## ''' argument 1: use case Example: UC1_5OS_60poll , i.e. use case 1, with 5 DNP3 outstation polled with a polling interval of 60 sec argument 2: Determine the stage in the data pre-processing. The valid numbers are from 1 to 8. argument 3: Select the location for collecting the raw data. Select either : "master", "DS", "router" argument 4: Boolean indicating if it can reach elasticsearch database and its packetbeat index ''' print('Argument List:' + str(sys.argv)) case = sys.argv[1] _usecase = case.split('_')[0] print(_usecase) outstations = case.split('_')[1] _os = outstations.replace('OS','') poll_interval = case.split('_')[2] _pi = poll_interval.replace('poll','') stage = sys.argv[2] location = sys.argv[3] es_connected = sys.argv[4] if es_connected == 'False': es_connected = False #### based on the stage pack the value of that stage and return#### jsonpath, pickle_path, snort_path,start_time, end_time = get_file_path(_usecase,int(_os),int(_pi),location) fusion = DataFusion() fusion.load_json(jsonpath) fusion.extract_cyber_data() data_as_list=[] to_monitor={} if 'UC1' in _usecase: to_monitor ={'399':[5], '456':[18],'1195':[24],'1200':[27]} elif 'UC2' in _usecase: to_monitor ={'390':[20],'601':[34],'631':[23],'968':[27],'968':[29]} elif 'UC3' in _usecase: to_monitor ={'390':[20],'560':[24], '601':[34],'968':[27],'968':[29]} elif 'UC4' in _usecase: to_monitor ={'390':[20],'601':[38], '601':[38],'968':[27],'968':[29]} if stage == '1': data_as_list = fusion.cyber_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.cyber_table) sys.exit() elif stage == '2': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() data_as_list = fusion.cyber_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.cyber_table) sys.exit() elif stage =='3': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() print(es_connected) if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() data_as_list = fusion.cyber_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.cyber_table) sys.exit() elif stage == '4': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() fusion.process_snort(snort_path) fusion.merge_snort() data_as_list = fusion.cyber_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.cyber_table) sys.exit() elif stage == '5': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() fusion.process_snort(snort_path) fusion.merge_snort() fusion.physical_table = fusion.extract_physical_data_with_values(to_monitor) # have to add the function in the class data_as_list = fusion.physical_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.physical_table) sys.exit() elif stage == '6': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() fusion.process_snort(snort_path) fusion.merge_snort() fusion.physical_table = fusion.extract_physical_data_with_values(to_monitor) # have to add the function in the class fusion.merge() fusion.merged_table = fusion.merged_table.drop(columns=['Time']) data_as_list = fusion.merged_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.merged_table) sys.exit() elif stage == '7': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() fusion.process_snort(snort_path) fusion.merge_snort() fusion.physical_table = fusion.extract_physical_data_with_values(to_monitor) # have to add the function in the class fusion.merge() replace_map = [('ip.src', '0.0.0.0'), ('ip.dst', '0.0.0.0'), ('ip.len', 0), ('ip.flags', '0x00000000'),('tcp.srcport', 0), ('tcp.dstport', 0),('tcp.flags', '0x00000000'), ('tcp.len', 0),('LL_dnp3_src', -1), ('LL_dnp3_dst', -1),('LL_dnp3_len', 0), ('AL_dnp3_al_func', -1), ('LL_dnp3_ctl', '0x00000000'),('TL_dnp3_tr_ctl', '0x00000000'), ('AL_dnp3_al_ctl', '0x00000000'),('AL_dnp3_obj', 0), ('AL_Payload', 0), ('DNP3 Object Count', 0),('DNP3 Objects', -1), ('tcp_rtt', -1), ('tcp_retransmission', 0), ('snort_alert', 0),('snort_alert_type', 'None'), ('flow.count', -1), ('flow.final_count', -1), ('packets', -1)] replace_map = dict(replace_map) fusion.imputate(replace_map) fusion.merged_table = fusion.merged_table.drop(columns=['Time']) data_as_list = fusion.merged_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.merged_table) sys.exit() elif stage == '8': fusion.pcap_table = pd.read_pickle(pickle_path) fusion.merge_by_pcap() if es_connected: fusion.connect_to_elasticsearch('10.110.215.39') json_body=get_lucene_query(start_time, end_time) fusion.retrieve_packetbeat(json_body = json_body) fusion.extract_packetbeat() fusion.merge_packetbeat() fusion.process_snort(snort_path) fusion.merge_snort() fusion.physical_table = fusion.extract_physical_data_with_values(to_monitor) # have to add the function in the class fusion.merge() replace_map =[('ip.src', '0.0.0.0'), ('ip.dst', '0.0.0.0'), ('ip.len', 0), ('ip.flags', '0x00000000'),('tcp.srcport', 0), ('tcp.dstport', 0),('tcp.flags', '0x00000000'), ('tcp.len', 0),('LL_dnp3_src', -1), ('LL_dnp3_dst', -1),('LL_dnp3_len', 0), ('AL_dnp3_al_func', -1), ('LL_dnp3_ctl', '0x00000000'),('TL_dnp3_tr_ctl', '0x00000000'), ('AL_dnp3_al_ctl', '0x00000000'),('AL_dnp3_obj', 0), ('AL_Payload', 0), ('DNP3 Object Count', 0),('DNP3 Objects', -1), ('tcp_rtt', -1), ('tcp_retransmission', 0), ('snort_alert', 0),('snort_alert_type', 'None'), ('flow.count', -1), ('flow.final_count', -1), ('packets', -1)] replace_map = dict(replace_map) fusion.imputate(replace_map) encoding_list=['frame.protocols', 'eth.src', 'eth.dst', 'ip.src', 'ip.dst', 'ip.len', 'ip.flags', 'tcp.srcport', 'tcp.dstport', 'tcp.len', 'tcp.flags', 'snort_alert_type', 'LL_dnp3_src', 'LL_dnp3_dst', 'LL_dnp3_len', 'LL_dnp3_ctl', 'TL_dnp3_tr_ctl', 'AL_dnp3_al_ctl', 'AL_dnp3_obj', 'AL_Payload'] fusion.encode(encoding_list) fusion.merged_table = fusion.merged_table.drop(columns=['Time']) data_as_list = fusion.merged_table.values.tolist() mp.pack(data_as_list, open('msgpack_'+sys.argv[1]+'_'+stage+'.mp','wb')) print(fusion.merged_table) sys.exit()

44.758017

127

0.652358

2,175

15,352

4.274483

0.11908

0.025815

0.032268

0.024201

0.789394

0.777025

0.774013

0.727654

0.720555

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0

0.10179

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15,352

342

128

44.888889

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false

0

0.022082

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0.0347

0

null

0

1

0

null

0

5

a6936440fe24a370ea3d61d87c2e9da0e64189e6

221

py

Python

project/api/serializers.py

akxen/pyomo-drf-docker

9299561e61ce0cc6b40968e078aea84bded1228b

[ "Apache-2.0" ]

null

project/api/serializers.py

akxen/pyomo-drf-docker

9299561e61ce0cc6b40968e078aea84bded1228b

[ "Apache-2.0" ]

null

project/api/serializers.py

akxen/pyomo-drf-docker

9299561e61ce0cc6b40968e078aea84bded1228b

[ "Apache-2.0" ]

null

from rest_framework import serializers class ModelDataSerializer(serializers.Serializer): PARAMETER_1 = serializers.FloatField() PARAMETER_2 = serializers.FloatField() PARAMETER_3 = serializers.FloatField()

27.625

50

0.79638

21

221

8.190476

0.619048

0.366279

0.348837

0

0.015625

0.131222

221

7

51

31.571429

0.880208

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1

0

false

0

0.2

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0

null

1

0

1

0

null

0

1

0

5

a6be52bbcf4d347230213e51a7eba568d0c0c282

310

py

Python

code-aaron/ch6-userforms/services/user_service.py

ayhteo/web-applications-with-fastapi-course

160d74c70528fbb803d95e4a80e495ddbd5e9833

[ "MIT" ]

null

code-aaron/ch6-userforms/services/user_service.py

ayhteo/web-applications-with-fastapi-course

160d74c70528fbb803d95e4a80e495ddbd5e9833

[ "MIT" ]

null

code-aaron/ch6-userforms/services/user_service.py

ayhteo/web-applications-with-fastapi-course

160d74c70528fbb803d95e4a80e495ddbd5e9833

[ "MIT" ]

null

from data.user import User from typing import Optional def create_account(name: str, email: str, password: str): return User(name, email, "abcde") def login_user(email: str, password: str) -> Optional[User]: if password == "abcde": return User("test_user", email, password) return None

23.846154

60

0.690323

43

310

4.906977

0.44186

0.075829

0.151659

0.180095

0

0.193548

310

12

61

25.833333

0.844

0

0.06129

0

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0.25

false

0.5

0.25

0.125

0.875

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a6dbe6528df34869dace0729700b5d92dcff5a1c

57

py

Python

rhucrl/__init__.py

sebascuri/rhucrl

27663e1302f3bbc636dff28495c6f2667bb7c1da

[ "MIT" ]

1

2021-11-19T11:46:48.000Z

rhucrl/__init__.py

sebascuri/rhucrl

27663e1302f3bbc636dff28495c6f2667bb7c1da

[ "MIT" ]

1

2021-11-22T07:48:03.000Z

rhucrl/__init__.py

sebascuri/rhucrl

27663e1302f3bbc636dff28495c6f2667bb7c1da

[ "MIT" ]

1

2022-03-26T10:18:01.000Z

"""Python Script Template.""" from .environment import *

19

29

0.719298

6

57

6.833333

1

0

0.122807

57

2

30

28.5

0.82

0.403509

0

1

0

true

0

1

0

1

0

1

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null

0

1

0

null

0

1

0

1

0

1

0

5

a6fb8ead5fa42953371099e9172136a1a83cfeea

2,559

py

Python

tools/PETRAinfo.py

hzg-wpi/p05nano

af13c97256e754e30512d4c9ef88c287f09dedaa

[ "MIT" ]

null

tools/PETRAinfo.py

hzg-wpi/p05nano

af13c97256e754e30512d4c9ef88c287f09dedaa

[ "MIT" ]

null

tools/PETRAinfo.py

hzg-wpi/p05nano

af13c97256e754e30512d4c9ef88c287f09dedaa

[ "MIT" ]

null

import time # TODO Is it used? def GetPETRAinfoString(itype, infostr, inumber, time0, tTTTGW, tQBPM): """ Layout: Petra Beam Current // Beam Lifetime // Orbit RMSx // Orbit RMSy // Topup status // QBPM current // QBPM pos x //QBPM pos y if not readable, return value is -1 """ s = '%13s\t%5s\t%05i\t%e\t' %(itype[:13], infostr[:5], inumber, time.time()-time0) try: tmp = tTTTGW.read_attribute('BeamCurrent').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tTTTGW.read_attribute('BeamLifetime').value s += '%06.3f\t' %tmp except: s += '-1.000\t' try: tmp = tTTTGW.read_attribute('OrbitRMSX').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tTTTGW.read_attribute('OrbitRMSY').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tTTTGW.read_attribute('TopUpStatus').value s += '%04.1f\t' %tmp except: s += '-1.0\t' try: tmp = tQBPM.read_attribute('PosAndAvgCurr').value s += '%e\t' %tmp[2] except: s += '-01.000000\t' try: tmp = tQBPM.read_attribute('PosAndAvgCurr').value s += '%e\t' %tmp[0] except: s += '-01.000000\t' try: tmp = tQBPM.read_attribute('PosAndAvgCurr').value s += '%e\t' %tmp[1] except: s += '-01.000000\t' return s+'\n' def GetPETRAinfoStringShort(itype, infostr, inumber, motorpos, time0, tTTTGW, tQBPM): """ Layout: image identifier // infostr // image number // motorpos // timestamp // Petra Beam Current // Orbit RMSx // Orbit RMSy // QBPM current // QBPM pos x //QBPM pos y if not readable, return value is -1 """ s = '%13s\t%5s\t%05i\t%e\t%e\t' %(itype[:13], infostr[:5], inumber, motorpos, time.time()-time0) try: tmp = tTTTGW.read_attribute('BeamCurrent').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tTTTGW.read_attribute('OrbitRMSX').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tTTTGW.read_attribute('OrbitRMSY').value s += '%010.6f\t' %tmp except: s += '-01.000000\t' try: tmp = tQBPM.read_attribute('PosAndAvgCurr').value s += '%e\t' %tmp[2] s += '%e\t' %tmp[0] s += '%e\t' %tmp[1] except: s += '-01.000000\t' s += '-01.000000\t' s += '-01.000000\t' return s+'\n'

30.464286

174

0.529504

345

2,559

3.892754

0.205797

0.041698

0.080417

0.089352

0.735666

0.711839

0.699926

0.650782

0

0.088154

0.290739

2,559

83

175

30.831325

0.651791

0.153185

0

0.84507

0

0.204417

0.021617

0

0.012048

0

1

0.028169

false

0

0.014085

0

0.070423

0

null

0

1

0

1

0

1

0

null

0

1

0

5

472adf1190764a1f42c14a1c2e44a75b5bc18e4c

59

py

Python

inferno/extensions/criteria/__init__.py

svenpeter42/inferno

6bcae839f7989666acbf02c2fca87f0b528d9247

[ "Apache-2.0" ]

null

inferno/extensions/criteria/__init__.py

svenpeter42/inferno

6bcae839f7989666acbf02c2fca87f0b528d9247

[ "Apache-2.0" ]

1

2017-12-20T21:36:48.000Z

inferno/extensions/criteria/__init__.py

svenpeter42/inferno

6bcae839f7989666acbf02c2fca87f0b528d9247

[ "Apache-2.0" ]

1

2021-01-27T12:29:30.000Z

from .set_similarity_measures import * from .core import *

19.666667

38

0.79661

8

59

5.625

0.75

0

0.135593

59

2

39

29.5

0.882353

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

472ede4162bd07cbeb800dc3ab83902af39eb450

54

py

Python

lyrics_extractor/__init__.py

99lyricstore/PyLyrics-Extractor

ae4dd2225f9d3bd34494e266ceddf9e52b3868b6

[ "MIT" ]

46

2019-01-15T20:43:13.000Z

2022-02-17T15:46:22.000Z

lyrics_extractor/__init__.py

99lyricstore/PyLyrics-Extractor

ae4dd2225f9d3bd34494e266ceddf9e52b3868b6

[ "MIT" ]

8

2019-02-03T18:06:01.000Z

2021-08-04T10:40:13.000Z

lyrics_extractor/__init__.py

99lyricstore/PyLyrics-Extractor

ae4dd2225f9d3bd34494e266ceddf9e52b3868b6

[ "MIT" ]

14

2019-02-20T13:06:52.000Z

2022-02-15T14:14:58.000Z

from .lyrics import SongLyrics, LyricScraperException

27

53

0.87037

5

54

9.4

1

0

0.092593

54

1

54

0.959184

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5b2b15ea216e1e63e3f90188b988fdfd10a89d92

1,004

py

Python

test/test_cart_settings_payment_credit_card.py

gstingy/uc_python_api

9a0bd3f6e63f616586681518e44fe37c6bae2bba

[ "Apache-2.0" ]

null

test/test_cart_settings_payment_credit_card.py

gstingy/uc_python_api

9a0bd3f6e63f616586681518e44fe37c6bae2bba

[ "Apache-2.0" ]

null

test/test_cart_settings_payment_credit_card.py

gstingy/uc_python_api

9a0bd3f6e63f616586681518e44fe37c6bae2bba

[ "Apache-2.0" ]

null

# coding: utf-8 """ UltraCart Rest API V2 UltraCart REST API Version 2 OpenAPI spec version: 2.0.0 Contact: support@ultracart.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import os import sys import unittest import ultracart from ultracart.rest import ApiException from ultracart.models.cart_settings_payment_credit_card import CartSettingsPaymentCreditCard class TestCartSettingsPaymentCreditCard(unittest.TestCase): """ CartSettingsPaymentCreditCard unit test stubs """ def setUp(self): pass def tearDown(self): pass def testCartSettingsPaymentCreditCard(self): """ Test CartSettingsPaymentCreditCard """ # FIXME: construct object with mandatory attributes with example values #model = ultracart.models.cart_settings_payment_credit_card.CartSettingsPaymentCreditCard() pass if __name__ == '__main__': unittest.main()

22.311111

99

0.731076

105

1,004

6.790476

0.571429

0.054698

0.044881

0.075736

0.123422

0

0.007463

0.199203

1,004

44

100

22.818182

0.879353

0.431275

0

0.1875

1

0

0.015625

0

0.022727

0

1

0.1875

false

0.1875

0.4375

0

0.6875

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5b51d7217cd42051bab974d8ba5f36b301a77be5

424

py

Python

colorPrint.py

Sletteon/csjelentkezes

a6e2869f7793bc6de0148201766a1c688b935cb5

[ "MIT" ]

1

2018-01-12T07:47:31.000Z

colorPrint.py

Sletteon/csjelentkezes

a6e2869f7793bc6de0148201766a1c688b935cb5

[ "MIT" ]

null

colorPrint.py

Sletteon/csjelentkezes

a6e2869f7793bc6de0148201766a1c688b935cb5

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Kiírja az állapotnak megfelelő ikont, és utána a szöveget class colorPrint: def errPrint(self, message): print('\n[&&&] ' + message) def warnPrint(self, message): print('\n[*] ' + message) def okPrint(self, message): print('\n[+] ' + message) def finePrint(self, message): print('\n[-] ' + message) def startPrint(self, IpAddress): print('[+] ' + 'Szerver fut: ' + IpAddress)

20.190476

59

0.622642

50

424

5.28

0.54

0.166667

0.242424

0.257576

0.409091

0

0.00289

0.183962

424

20

60

21.2

0.760116

0.186321

0

0.125731

0

1

0.454545

false

0

0.545455

0.454545

0

null

0

1

0

null

0

1

0

1

0

5

5b939c79d374540bd6b8082e0a60d927a262cefa

108

py

Python

trail.py

ColonelAVP/Devops-Demo

dfd02b36a8b6548167db58c6b2dbccf3c380d807

[ "Apache-2.0" ]

null

trail.py

ColonelAVP/Devops-Demo

dfd02b36a8b6548167db58c6b2dbccf3c380d807

[ "Apache-2.0" ]

null

trail.py

ColonelAVP/Devops-Demo

dfd02b36a8b6548167db58c6b2dbccf3c380d807

[ "Apache-2.0" ]

null

def name(firstname,lastname): return f"My name is {firstname} {lastname}" print(name("Atherv", "Patil"))

21.6

45

0.703704

15

108

5.066667

0.733333

0.447368

0

0.12037

108

4

46

27

0.8

0

0.407407

0

1

0.333333

false

0

0.333333

0.666667

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

5

5bb18bd45e05faae6095125b3158506e62ed27db

330

py

Python

hgraph/__init__.py

Amir-Mehrpanah/hgraph2graph

6d37153afe09f7684381ce56e8366675e22833e9

[ "MIT" ]

182

2019-11-15T15:59:31.000Z

2022-03-31T09:17:40.000Z

hgraph/__init__.py

Amir-Mehrpanah/hgraph2graph

6d37153afe09f7684381ce56e8366675e22833e9

[ "MIT" ]

30

2020-03-03T16:35:52.000Z

2021-12-16T04:06:57.000Z

hgraph/__init__.py

Amir-Mehrpanah/hgraph2graph

6d37153afe09f7684381ce56e8366675e22833e9

[ "MIT" ]

60

2019-11-15T05:06:11.000Z

2022-03-31T16:43:12.000Z

from hgraph.mol_graph import MolGraph from hgraph.encoder import HierMPNEncoder from hgraph.decoder import HierMPNDecoder from hgraph.vocab import Vocab, PairVocab, common_atom_vocab from hgraph.hgnn import HierVAE, HierVGNN, HierCondVGNN from hgraph.dataset import MoleculeDataset, MolPairDataset, DataFolder, MolEnumRootDataset

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156

py

Python

online_pharmacy/items/views.py

geekyJock8/online_pharmacy

892852857786ec17259b71f2a178896cd6d12e60

[ "Apache-2.0" ]

5

2020-09-09T13:59:17.000Z

2021-09-30T07:20:55.000Z

online_pharmacy/items/views.py

geekyJock8/online_pharmacy

892852857786ec17259b71f2a178896cd6d12e60

[ "Apache-2.0" ]

10

2017-09-03T06:13:31.000Z

2017-10-10T15:22:30.000Z

online_pharmacy/items/views.py

geekyJock8/Online-Pharmacy

892852857786ec17259b71f2a178896cd6d12e60

[ "Apache-2.0" ]

9

2017-09-03T04:59:18.000Z

2019-10-17T11:33:18.000Z

from django.http import HttpResponse def showSearch(request): return HttpResponse('<h1> This is the search page after searching of the element </h1>')

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17,220

py

Python

sdc/tests/test_join.py

densmirn/sdc

30e53955a88506a5134d75d843205dbd5d576051

[ "BSD-2-Clause" ]

540

2017-06-19T16:29:24.000Z

2019-05-21T09:30:07.000Z

sdc/tests/test_join.py

densmirn/sdc

30e53955a88506a5134d75d843205dbd5d576051

[ "BSD-2-Clause" ]

389

2019-10-30T18:56:46.000Z

2022-03-09T08:21:36.000Z

sdc/tests/test_join.py

densmirn/sdc

30e53955a88506a5134d75d843205dbd5d576051

[ "BSD-2-Clause" ]

36

2017-06-19T16:29:15.000Z

2019-04-26T09:22:39.000Z

# ***************************************************************************** # Copyright (c) 2020, Intel Corporation All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ***************************************************************************** import numba import numpy as np import pandas as pd import platform import pyarrow.parquet as pq import random import string import unittest from pandas.api.types import CategoricalDtype import sdc from sdc.str_arr_ext import StringArray from sdc.tests.test_base import TestCase from sdc.tests.test_utils import (count_array_OneDs, count_array_REPs, count_parfor_OneDs, count_parfor_REPs, dist_IR_contains, get_start_end, skip_numba_jit) class TestJoin(TestCase): @skip_numba_jit def test_join1(self): def test_impl(n): df1 = pd.DataFrame({'key1': np.arange(n) + 3, 'A': np.arange(n) + 1.0}) df2 = pd.DataFrame({'key2': 2 * np.arange(n) + 1, 'B': n + np.arange(n) + 1.0}) df3 = pd.merge(df1, df2, left_on='key1', right_on='key2') return df3.B.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) n = 11111 self.assertEqual(hpat_func(n), test_impl(n)) @skip_numba_jit def test_join1_seq(self): def test_impl(df1, df2): df3 = df1.merge(df2, left_on='key1', right_on='key2') return df3 hpat_func = self.jit(test_impl) n = 11 df1 = pd.DataFrame({'key1': np.arange(n) + 3, 'A': np.arange(n) + 1.0}) df2 = pd.DataFrame({'key2': 2 * np.arange(n) + 1, 'B': n + np.arange(n) + 1.0}) pd.testing.assert_frame_equal(hpat_func(df1, df2), test_impl(df1, df2)) n = 11111 df1 = pd.DataFrame({'key1': np.arange(n) + 3, 'A': np.arange(n) + 1.0}) df2 = pd.DataFrame({'key2': 2 * np.arange(n) + 1, 'B': n + np.arange(n) + 1.0}) pd.testing.assert_frame_equal(hpat_func(df1, df2), test_impl(df1, df2)) @skip_numba_jit def test_join1_seq_str(self): def test_impl(): df1 = pd.DataFrame({'key1': ['foo', 'bar', 'baz']}) df2 = pd.DataFrame({'key2': ['baz', 'bar', 'baz'], 'B': ['b', 'zzz', 'ss']}) df3 = pd.merge(df1, df2, left_on='key1', right_on='key2') return df3.B hpat_func = self.jit(test_impl) self.assertEqual(set(hpat_func()), set(test_impl())) @skip_numba_jit def test_join1_seq_str_na(self): # test setting NA in string data column def test_impl(): df1 = pd.DataFrame({'key1': ['foo', 'bar', 'baz']}) df2 = pd.DataFrame({'key2': ['baz', 'bar', 'baz'], 'B': ['b', 'zzz', 'ss']}) df3 = df1.merge(df2, left_on='key1', right_on='key2', how='left') return df3.B hpat_func = self.jit(test_impl) self.assertEqual(set(hpat_func()), set(test_impl())) @skip_numba_jit def test_join_mutil_seq1(self): def test_impl(df1, df2): return df1.merge(df2, on=['A', 'B']) hpat_func = self.jit(test_impl) df1 = pd.DataFrame({'A': [3, 1, 1, 3, 4], 'B': [1, 2, 3, 2, 3], 'C': [7, 8, 9, 4, 5]}) df2 = pd.DataFrame({'A': [2, 1, 4, 4, 3], 'B': [1, 3, 2, 3, 2], 'D': [1, 2, 3, 4, 8]}) pd.testing.assert_frame_equal(hpat_func(df1, df2), test_impl(df1, df2)) @skip_numba_jit def test_join_mutil_parallel1(self): def test_impl(A1, B1, C1, A2, B2, D2): df1 = pd.DataFrame({'A': A1, 'B': B1, 'C': C1}) df2 = pd.DataFrame({'A': A2, 'B': B2, 'D': D2}) df3 = df1.merge(df2, on=['A', 'B']) return df3.C.sum() + df3.D.sum() hpat_func = self.jit(locals={ 'A1:input': 'distributed', 'B1:input': 'distributed', 'C1:input': 'distributed', 'A2:input': 'distributed', 'B2:input': 'distributed', 'D2:input': 'distributed', })(test_impl) df1 = pd.DataFrame({'A': [3, 1, 1, 3, 4], 'B': [1, 2, 3, 2, 3], 'C': [7, 8, 9, 4, 5]}) df2 = pd.DataFrame({'A': [2, 1, 4, 4, 3], 'B': [1, 3, 2, 3, 2], 'D': [1, 2, 3, 4, 8]}) start, end = get_start_end(len(df1)) h_A1 = df1.A.values[start:end] h_B1 = df1.B.values[start:end] h_C1 = df1.C.values[start:end] h_A2 = df2.A.values[start:end] h_B2 = df2.B.values[start:end] h_D2 = df2.D.values[start:end] p_A1 = df1.A.values p_B1 = df1.B.values p_C1 = df1.C.values p_A2 = df2.A.values p_B2 = df2.B.values p_D2 = df2.D.values h_res = hpat_func(h_A1, h_B1, h_C1, h_A2, h_B2, h_D2) p_res = test_impl(p_A1, p_B1, p_C1, p_A2, p_B2, p_D2) self.assertEqual(h_res, p_res) @skip_numba_jit def test_join_left_parallel1(self): """ """ def test_impl(A1, B1, C1, A2, B2, D2): df1 = pd.DataFrame({'A': A1, 'B': B1, 'C': C1}) df2 = pd.DataFrame({'A': A2, 'B': B2, 'D': D2}) df3 = df1.merge(df2, on=('A', 'B')) return df3.C.sum() + df3.D.sum() hpat_func = self.jit(locals={ 'A1:input': 'distributed', 'B1:input': 'distributed', 'C1:input': 'distributed', })(test_impl) df1 = pd.DataFrame({'A': [3, 1, 1, 3, 4], 'B': [1, 2, 3, 2, 3], 'C': [7, 8, 9, 4, 5]}) df2 = pd.DataFrame({'A': [2, 1, 4, 4, 3], 'B': [1, 3, 2, 3, 2], 'D': [1, 2, 3, 4, 8]}) start, end = get_start_end(len(df1)) h_A1 = df1.A.values[start:end] h_B1 = df1.B.values[start:end] h_C1 = df1.C.values[start:end] h_A2 = df2.A.values h_B2 = df2.B.values h_D2 = df2.D.values p_A1 = df1.A.values p_B1 = df1.B.values p_C1 = df1.C.values p_A2 = df2.A.values p_B2 = df2.B.values p_D2 = df2.D.values h_res = hpat_func(h_A1, h_B1, h_C1, h_A2, h_B2, h_D2) p_res = test_impl(p_A1, p_B1, p_C1, p_A2, p_B2, p_D2) self.assertEqual(h_res, p_res) self.assertEqual(count_array_OneDs(), 3) @skip_numba_jit def test_join_datetime_seq1(self): def test_impl(df1, df2): return pd.merge(df1, df2, on='time') hpat_func = self.jit(test_impl) df1 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-03', '2017-01-06', '2017-02-21']), 'B': [4, 5, 6]}) df2 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-01', '2017-01-06', '2017-01-03']), 'A': [7, 8, 9]}) pd.testing.assert_frame_equal(hpat_func(df1, df2), test_impl(df1, df2)) @unittest.skip("Method max(). Currently function supports only numeric values. Given data type: datetime64[ns]") def test_join_datetime_parallel1(self): def test_impl(df1, df2): df3 = pd.merge(df1, df2, on='time') return (df3.A.sum(), df3.time.max(), df3.B.sum()) hpat_func = self.jit(distributed=['df1', 'df2'])(test_impl) df1 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-03', '2017-01-06', '2017-02-21']), 'B': [4, 5, 6]}) df2 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-01', '2017-01-06', '2017-01-03']), 'A': [7, 8, 9]}) start1, end1 = get_start_end(len(df1)) start2, end2 = get_start_end(len(df2)) self.assertEqual( hpat_func(df1.iloc[start1:end1], df2.iloc[start2:end2]), test_impl(df1, df2)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_merge_asof_seq1(self): def test_impl(df1, df2): return pd.merge_asof(df1, df2, on='time') hpat_func = self.jit(test_impl) df1 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-03', '2017-01-06', '2017-02-21']), 'B': [4, 5, 6]}) df2 = pd.DataFrame( {'time': pd.DatetimeIndex( ['2017-01-01', '2017-01-02', '2017-01-04', '2017-02-23', '2017-02-25']), 'A': [2, 3, 7, 8, 9]}) pd.testing.assert_frame_equal(hpat_func(df1, df2), test_impl(df1, df2)) @unittest.skip("Method max(). Currently function supports only numeric values. Given data type: datetime64[ns]") def test_merge_asof_parallel1(self): def test_impl(): df1 = pd.read_parquet('asof1.pq') df2 = pd.read_parquet('asof2.pq') df3 = pd.merge_asof(df1, df2, on='time') return (df3.A.sum(), df3.time.max(), df3.B.sum()) hpat_func = self.jit(test_impl) self.assertEqual(hpat_func(), test_impl()) @skip_numba_jit def test_join_left_seq1(self): def test_impl(df1, df2): return pd.merge(df1, df2, how='left', on='key') hpat_func = self.jit(test_impl) df1 = pd.DataFrame( {'key': [2, 3, 5, 1, 2, 8], 'A': np.array([4, 6, 3, 9, 9, -1], np.float)}) df2 = pd.DataFrame( {'key': [1, 2, 9, 3, 2], 'B': np.array([1, 7, 2, 6, 5], np.float)}) h_res = hpat_func(df1, df2) res = test_impl(df1, df2) np.testing.assert_array_equal(h_res.key.values, res.key.values) # converting arrays to sets since order of values can be different self.assertEqual(set(h_res.A.values), set(res.A.values)) self.assertEqual( set(h_res.B.dropna().values), set(res.B.dropna().values)) @skip_numba_jit def test_join_left_seq2(self): def test_impl(df1, df2): return pd.merge(df1, df2, how='left', on='key') hpat_func = self.jit(test_impl) # test left run where a key is repeated on left but not right side df1 = pd.DataFrame( {'key': [2, 3, 5, 3, 2, 8], 'A': np.array([4, 6, 3, 9, 9, -1], np.float)}) df2 = pd.DataFrame( {'key': [1, 2, 9, 3, 10], 'B': np.array([1, 7, 2, 6, 5], np.float)}) h_res = hpat_func(df1, df2) res = test_impl(df1, df2) np.testing.assert_array_equal(h_res.key.values, res.key.values) # converting arrays to sets since order of values can be different self.assertEqual(set(h_res.A.values), set(res.A.values)) self.assertEqual( set(h_res.B.dropna().values), set(res.B.dropna().values)) @skip_numba_jit def test_join_right_seq1(self): def test_impl(df1, df2): return pd.merge(df1, df2, how='right', on='key') hpat_func = self.jit(test_impl) df1 = pd.DataFrame( {'key': [2, 3, 5, 1, 2, 8], 'A': np.array([4, 6, 3, 9, 9, -1], np.float)}) df2 = pd.DataFrame( {'key': [1, 2, 9, 3, 2], 'B': np.array([1, 7, 2, 6, 5], np.float)}) h_res = hpat_func(df1, df2) res = test_impl(df1, df2) self.assertEqual(set(h_res.key.values), set(res.key.values)) # converting arrays to sets since order of values can be different self.assertEqual(set(h_res.B.values), set(res.B.values)) self.assertEqual( set(h_res.A.dropna().values), set(res.A.dropna().values)) @skip_numba_jit def test_join_outer_seq1(self): def test_impl(df1, df2): return pd.merge(df1, df2, how='outer', on='key') hpat_func = self.jit(test_impl) df1 = pd.DataFrame( {'key': [2, 3, 5, 1, 2, 8], 'A': np.array([4, 6, 3, 9, 9, -1], np.float)}) df2 = pd.DataFrame( {'key': [1, 2, 9, 3, 2], 'B': np.array([1, 7, 2, 6, 5], np.float)}) h_res = hpat_func(df1, df2) res = test_impl(df1, df2) self.assertEqual(set(h_res.key.values), set(res.key.values)) # converting arrays to sets since order of values can be different self.assertEqual( set(h_res.B.dropna().values), set(res.B.dropna().values)) self.assertEqual( set(h_res.A.dropna().values), set(res.A.dropna().values)) @skip_numba_jit def test_join1_seq_key_change1(self): # make sure const list typing doesn't replace const key values def test_impl(df1, df2, df3, df4): o1 = df1.merge(df2, on=['A']) o2 = df3.merge(df4, on=['B']) return o1, o2 hpat_func = self.jit(test_impl) n = 11 df1 = pd.DataFrame({'A': np.arange(n) + 3, 'AA': np.arange(n) + 1.0}) df2 = pd.DataFrame({'A': 2 * np.arange(n) + 1, 'AAA': n + np.arange(n) + 1.0}) df3 = pd.DataFrame({'B': 2 * np.arange(n) + 1, 'BB': n + np.arange(n) + 1.0}) df4 = pd.DataFrame({'B': 2 * np.arange(n) + 1, 'BBB': n + np.arange(n) + 1.0}) pd.testing.assert_frame_equal(hpat_func(df1, df2, df3, df4)[1], test_impl(df1, df2, df3, df4)[1]) @skip_numba_jit @unittest.skipIf(platform.system() == 'Windows', "error on windows") def test_join_cat1(self): def test_impl(): ct_dtype = CategoricalDtype(['A', 'B', 'C']) dtypes = {'C1': np.int, 'C2': ct_dtype, 'C3': str} df1 = pd.read_csv("csv_data_cat1.csv", names=['C1', 'C2', 'C3'], dtype=dtypes, ) n = len(df1) df2 = pd.DataFrame({'C1': 2 * np.arange(n) + 1, 'AAA': n + np.arange(n) + 1.0}) df3 = df1.merge(df2, on='C1') return df3 hpat_func = self.jit(test_impl) pd.testing.assert_frame_equal(hpat_func(), test_impl()) @skip_numba_jit @unittest.skipIf(platform.system() == 'Windows', "error on windows") def test_join_cat2(self): # test setting NaN in categorical array def test_impl(): ct_dtype = CategoricalDtype(['A', 'B', 'C']) dtypes = {'C1': np.int, 'C2': ct_dtype, 'C3': str} df1 = pd.read_csv("csv_data_cat1.csv", names=['C1', 'C2', 'C3'], dtype=dtypes, ) n = len(df1) df2 = pd.DataFrame({'C1': 2 * np.arange(n) + 1, 'AAA': n + np.arange(n) + 1.0}) df3 = df1.merge(df2, on='C1', how='right') return df3 hpat_func = self.jit(test_impl) pd.testing.assert_frame_equal( hpat_func().sort_values('C1').reset_index(drop=True), test_impl().sort_values('C1').reset_index(drop=True)) @skip_numba_jit @unittest.skipIf(platform.system() == 'Windows', "error on windows") def test_join_cat_parallel1(self): # TODO: cat as keys def test_impl(): ct_dtype = CategoricalDtype(['A', 'B', 'C']) dtypes = {'C1': np.int, 'C2': ct_dtype, 'C3': str} df1 = pd.read_csv("csv_data_cat1.csv", names=['C1', 'C2', 'C3'], dtype=dtypes, ) n = len(df1) df2 = pd.DataFrame({'C1': 2 * np.arange(n) + 1, 'AAA': n + np.arange(n) + 1.0}) df3 = df1.merge(df2, on='C1') return df3 hpat_func = self.jit(distributed=['df3'])(test_impl) # TODO: check results self.assertTrue((hpat_func().columns == test_impl().columns).all()) if __name__ == "__main__": unittest.main()

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5

f35637578386b46de58497a3ea6c7231c5cc2970

160

py

Python

tezpie/storage/chain_state.py

dakk/tezpie

04af3ff899ee2f58f5cda010583ca09f9c9d287b

[ "MIT" ]

2

2020-09-26T09:51:12.000Z

2020-09-26T10:09:28.000Z

tezpie/storage/chain_state.py

dakk/tezpie

04af3ff899ee2f58f5cda010583ca09f9c9d287b

[ "MIT" ]

null

tezpie/storage/chain_state.py

dakk/tezpie

04af3ff899ee2f58f5cda010583ca09f9c9d287b

[ "MIT" ]

null

from .store import Store class ChainState(Store): def name(): return 'chainstate' def __init__ (self): super(Store, self).__init__()

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0.2

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1

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5

f36081f004c11bc9cb4edf55b1cf5604021d677f

91

py

Python

src/guides/__init__.py

silasbrack/special-course

47dc396f97b2027d366e90add115d4ed2bc0f1de

[ "MIT" ]

null

src/guides/__init__.py

silasbrack/special-course

47dc396f97b2027d366e90add115d4ed2bc0f1de

[ "MIT" ]

null

src/guides/__init__.py

silasbrack/special-course

47dc396f97b2027d366e90add115d4ed2bc0f1de

[ "MIT" ]

null

from .low_rank import LowRank from .mean_field import MeanField from .radial import Radial

22.75

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5

f369b2498a4cefc919dc7461eb05bf5c2fa4f16c

21,347

py

Python

evaluate.py

Guominyingxiongququ/RAFT

04c1bbf2cf404489c7b5fa082a8b883e4df231e7

[ "BSD-3-Clause" ]

null

evaluate.py

Guominyingxiongququ/RAFT

04c1bbf2cf404489c7b5fa082a8b883e4df231e7

[ "BSD-3-Clause" ]

null

evaluate.py

Guominyingxiongququ/RAFT

04c1bbf2cf404489c7b5fa082a8b883e4df231e7

[ "BSD-3-Clause" ]

null

import sys sys.path.append('core') from PIL import Image import argparse import os import time import numpy as np import torch import torch.nn.functional as F import matplotlib.pyplot as plt import datasets from utils import flow_viz from utils import frame_utils from raft import RAFT from utils.utils import InputPadder, forward_interpolate from builder import build_dataloader, build_dataset from metrics import psnr, ssim @torch.no_grad() def create_sintel_submission(model, iters=32, warm_start=False, output_path='sintel_submission'): """ Create submission for the Sintel leaderboard """ model.eval() for dstype in ['clean', 'final']: test_dataset = datasets.MpiSintel(split='test', aug_params=None, dstype=dstype) flow_prev, sequence_prev = None, None for test_id in range(len(test_dataset)): image1, image2, (sequence, frame) = test_dataset[test_id] if sequence != sequence_prev: flow_prev = None padder = InputPadder(image1.shape) image1, image2 = padder.pad(image1[None].cuda(), image2[None].cuda()) flow_low, flow_pr = model(image1, image2, iters=iters, flow_init=flow_prev, test_mode=True) flow = padder.unpad(flow_pr[0]).permute(1, 2, 0).cpu().numpy() if warm_start: flow_prev = forward_interpolate(flow_low[0])[None].cuda() output_dir = os.path.join(output_path, dstype, sequence) output_file = os.path.join(output_dir, 'frame%04d.flo' % (frame+1)) if not os.path.exists(output_dir): os.makedirs(output_dir) frame_utils.writeFlow(output_file, flow) sequence_prev = sequence @torch.no_grad() def create_kitti_submission(model, iters=24, output_path='kitti_submission'): """ Create submission for the Sintel leaderboard """ model.eval() test_dataset = datasets.KITTI(split='testing', aug_params=None) if not os.path.exists(output_path): os.makedirs(output_path) for test_id in range(len(test_dataset)): image1, image2, (frame_id, ) = test_dataset[test_id] padder = InputPadder(image1.shape, mode='kitti') image1, image2 = padder.pad(image1[None].cuda(), image2[None].cuda()) _, flow_pr = model(image1, image2, iters=iters, test_mode=True) flow = padder.unpad(flow_pr[0]).permute(1, 2, 0).cpu().numpy() output_filename = os.path.join(output_path, frame_id) frame_utils.writeFlowKITTI(output_filename, flow) @torch.no_grad() def validate_multi_REDS(model, input_num, cfg, iter): model.eval() val_dataset = build_dataset(cfg.data.test) PSNR_sum = 0.0 SSIM_sum = 0.0 output_list = [] denoise = True for val_id in range(len(val_dataset)): data_blob = val_dataset[val_id] input_frames = data_blob['lq'][:input_num] gt = data_blob['gt'][:input_num] input_frames = input_frames[None, ...] gt = gt[None, ...] gt = gt.cuda() output = test_big_size_multi(model, input_frames, iter=iter) output = np.clip(output, 0.0, 1.0) output_list.append(torch.from_numpy(output[0, 7, ...])) gt = gt.detach().cpu().numpy() for i in range(11): gt_img = gt[0, i, ...] *255 output_img = output[0, i, ...] * 255 PSNR_sum += psnr(gt_img, output_img, crop_border=0, input_order='CHW') SSIM_sum += ssim(gt_img, output_img, crop_border=0, input_order='CHW') return output_list, PSNR_sum/(len(val_dataset)*11), SSIM_sum/(len(val_dataset)*11) @torch.no_grad() def validate_REDS(model, input_num, cfg, iter): model.eval() val_dataset = build_dataset(cfg.data.test) PSNR_sum = 0.0 SSIM_sum = 0.0 refer_idx = (input_num+1)/2 refer_idx = int(refer_idx) refer_idx = 0 output_list = [] denoise = True for val_id in range(len(val_dataset)): # print("val id: ") # print(val_id) data_blob = val_dataset[val_id] input_frames = data_blob['lq'][:input_num] if denoise: gt = data_blob['gt'] else: gt = data_blob['gt'][refer_idx] input_frames = input_frames[None, ...] gt = gt[None, ...] gt = gt.cuda() output = test_big_size(model, input_frames, iter=iter) output_list.append(torch.from_numpy(output[0])) gt = gt.detach().cpu().numpy() gt = gt[0] *255 output = output[0] * 255 PSNR_sum += psnr(gt[0], output, crop_border=0, input_order='CHW') SSIM_sum += ssim(gt[0], output, crop_border=0, input_order='CHW') return output_list, PSNR_sum/len(val_dataset), SSIM_sum/len(val_dataset) @torch.no_grad() def validate_chairs(model, iters=24): """ Perform evaluation on the FlyingChairs (test) split """ model.eval() epe_list = [] val_dataset = datasets.FlyingChairs(split='validation') for val_id in range(len(val_dataset)): image1, image2, flow_gt, _ = val_dataset[val_id] image1 = image1[None].cuda() image2 = image2[None].cuda() _, flow_pr = model(image1, image2, iters=iters, test_mode=True) epe = torch.sum((flow_pr[0].cpu() - flow_gt)**2, dim=0).sqrt() epe_list.append(epe.view(-1).numpy()) epe = np.mean(np.concatenate(epe_list)) print("Validation Chairs EPE: %f" % epe) return {'chairs': epe} @torch.no_grad() def validate_sintel(model, iters=32): """ Peform validation using the Sintel (train) split """ model.eval() results = {} for dstype in ['clean', 'final']: val_dataset = datasets.MpiSintel(split='training', dstype=dstype) epe_list = [] for val_id in range(len(val_dataset)): image1, image2, flow_gt, _ = val_dataset[val_id] image1 = image1[None].cuda() image2 = image2[None].cuda() padder = InputPadder(image1.shape) image1, image2 = padder.pad(image1, image2) flow_low, flow_pr = model(image1, image2, iters=iters, test_mode=True) flow = padder.unpad(flow_pr[0]).cpu() epe = torch.sum((flow - flow_gt)**2, dim=0).sqrt() epe_list.append(epe.view(-1).numpy()) epe_all = np.concatenate(epe_list) epe = np.mean(epe_all) px1 = np.mean(epe_all<1) px3 = np.mean(epe_all<3) px5 = np.mean(epe_all<5) print("Validation (%s) EPE: %f, 1px: %f, 3px: %f, 5px: %f" % (dstype, epe, px1, px3, px5)) results[dstype] = np.mean(epe_list) return results @torch.no_grad() def validate_kitti(model, iters=24): """ Peform validation using the KITTI-2015 (train) split """ model.eval() val_dataset = datasets.KITTI(split='training') out_list, epe_list = [], [] for val_id in range(len(val_dataset)): image1, image2, flow_gt, valid_gt = val_dataset[val_id] image1 = image1[None].cuda() image2 = image2[None].cuda() padder = InputPadder(image1.shape, mode='kitti') image1, image2 = padder.pad(image1, image2) flow_low, flow_pr = model(image1, image2, iters=iters, test_mode=True) flow = padder.unpad(flow_pr[0]).cpu() epe = torch.sum((flow - flow_gt)**2, dim=0).sqrt() mag = torch.sum(flow_gt**2, dim=0).sqrt() epe = epe.view(-1) mag = mag.view(-1) val = valid_gt.view(-1) >= 0.5 out = ((epe > 3.0) & ((epe/mag) > 0.05)).float() epe_list.append(epe[val].mean().item()) out_list.append(out[val].cpu().numpy()) epe_list = np.array(epe_list) out_list = np.concatenate(out_list) epe = np.mean(epe_list) f1 = 100 * np.mean(out_list) print("Validation KITTI: %f, %f" % (epe, f1)) return {'kitti-epe': epe, 'kitti-f1': f1} def test_big_size(model, input_data, patch_h=64, patch_w=64, patch_h_overlap=32, patch_w_overlap=32, iter=-1): # input_data shape n, t, c, h, w # output shape n, c, h, w scale = 4 denoise = False if denoise: patch_h = 128 patch_w = 128 patch_h_overlap = 64 patch_w_overlap = 64 scale = 1 H = input_data.shape[3] W = input_data.shape[4] t = input_data.shape[1] center_idx = int(t/2) test_result = np.zeros((input_data.shape[0], 3, scale*H, scale*W)) h_index = 1 while (patch_h*h_index-patch_h_overlap*(h_index-1)) < H: test_horizontal_result = np.zeros((input_data.shape[0], 3, scale*patch_h, scale*W)) h_begin = patch_h*(h_index-1)-patch_h_overlap*(h_index-1) h_end = patch_h*h_index-patch_h_overlap*(h_index-1) w_index = 1 w_end = 0 while (patch_w*w_index-patch_w_overlap*(w_index-1)) < W: w_begin = patch_w*(w_index-1)-patch_w_overlap*(w_index-1) w_end = patch_w*w_index-patch_w_overlap*(w_index-1) test_patch = input_data[:, :, :, h_begin:h_end, w_begin:w_end] output_patch = model(test_patch)[iter] output_patch = \ output_patch.cpu().detach().numpy().astype(np.float32) if w_index == 1: test_horizontal_result[:, :, :, w_begin*scale:w_end*scale] = \ output_patch else: for i in range(patch_w_overlap*scale): test_horizontal_result[:, :, :, w_begin * scale + i] = \ test_horizontal_result[:, :, :, w_begin * scale + i]\ * (patch_w_overlap * scale-1-i)/(patch_w_overlap * scale -1)\ + output_patch[:, :, :, i] * i/(patch_w_overlap * scale -1) cur_begin = w_begin+patch_w_overlap cur_begin = cur_begin*scale test_horizontal_result[:, :, :, cur_begin:w_end*scale] = \ output_patch[:, :, :, patch_w_overlap * scale:] w_index += 1 test_patch = input_data[:, :, :, h_begin:h_end, -patch_w:] output_patch = model(test_patch)[iter] output_patch = \ output_patch.cpu().detach().numpy().astype(np.float32) output_patch = output_patch[:, :, :, :] last_range = w_end-(W-patch_w) last_range = last_range * scale for i in range(last_range): term1 = test_horizontal_result[:, :, :, W*scale-patch_w*scale+i] rate1 = (last_range-1-i)/(last_range-1) term2 = output_patch[:, :, :, i] rate2 = i/(last_range-1) test_horizontal_result[:, :, :, W*scale-patch_w*scale+i] = \ term1*rate1+term2*rate2 test_horizontal_result[:, :, :, w_end*scale:] = \ output_patch[:, :, :, last_range:] if h_index == 1: test_result[:, :, h_begin*scale:h_end*scale, :] = test_horizontal_result else: for i in range(patch_h_overlap*scale): term1 = test_result[:, :, h_begin*scale+i, :] rate1 = (patch_h_overlap*scale-1-i)/(patch_h_overlap*scale-1) term2 = test_horizontal_result[:, :, i, :] rate2 = i/(patch_h_overlap*scale-1) test_result[:, :, h_begin*scale+i, :] = \ term1 * rate1 + term2 * rate2 test_result[:, :, h_begin*scale+patch_h_overlap*scale:h_end*scale, :] = \ test_horizontal_result[:, :, patch_h_overlap*scale:, :] h_index += 1 test_horizontal_result = np.zeros((input_data.shape[0], 3, patch_h*scale, W*scale)) w_index = 1 while (patch_w * w_index - patch_w_overlap * (w_index-1)) < W: w_begin = patch_w * (w_index-1) - patch_w_overlap * (w_index-1) w_end = patch_w * w_index - patch_w_overlap * (w_index-1) test_patch = input_data[:, :, :, -patch_h:, w_begin:w_end] output_patch = model(test_patch)[iter] output_patch = \ output_patch.cpu().detach().numpy().astype(np.float32) output_patch = output_patch if w_index == 1: test_horizontal_result[:, :, :, w_begin*scale:w_end*scale] = output_patch else: for i in range(patch_w_overlap*scale): term1 = test_horizontal_result[:, :, :, w_begin*scale+i] rate1 = (patch_w_overlap*scale-1-i)/(patch_w_overlap*scale-1) term2 = output_patch[:, :, :, i] rate2 = i/(patch_w_overlap*scale-1) test_horizontal_result[:, :, :, w_begin*scale+i] = \ term1*rate1+term2*rate2 cur_begin = w_begin+patch_w_overlap test_horizontal_result[:, :, :, cur_begin*scale:w_end*scale] = \ output_patch[:, :, :, patch_w_overlap*scale:] w_index += 1 test_patch = input_data[:, :, :, -patch_h:, -patch_w:] output_patch = model(test_patch)[iter] output_patch = output_patch.cpu().detach().numpy().astype(np.float32) output_patch = output_patch last_range = w_end-(W-patch_w) for i in range(last_range*scale): term1 = test_horizontal_result[:, :, :, W*scale-patch_w*scale+i] rate1 = (last_range*scale-1-i)/(last_range*scale-1) term2 = output_patch[:, :, :, i] rate2 = i/(last_range*scale-1) test_horizontal_result[:, :, :, W*scale-patch_w*scale+i] = \ term1*rate1+term2*rate2 test_horizontal_result[:, :, :, w_end*scale:] = \ output_patch[:, :, :, last_range*scale:] last_last_range = h_end-(H-patch_h) for i in range(last_last_range*scale): term1 = test_result[:, :, H*scale-patch_w*scale+i, :] rate1 = (last_last_range*scale-1-i)/(last_last_range*scale-1) term2 = test_horizontal_result[:, :, i, :] rate2 = i/(last_last_range*scale-1) test_result[:, :, H*scale-patch_w*scale+i, :] = \ term1*rate1+term2*rate2 cur_result = test_horizontal_result[:, :, last_last_range*scale:, :] test_result[:, :, h_end*scale:, :] = cur_result return test_result def test_big_size_multi(model, input_data, patch_h=64, patch_w=64, patch_h_overlap=32, patch_w_overlap=32, iter=-1): # input_data shape n, t, c, h, w # output shape n, t, c, h, w scale = 4 n, t, c, H, W = input_data.shape test_result = np.zeros((n, t, c, scale*H, scale*W)) h_index = 1 while (patch_h*h_index-patch_h_overlap*(h_index-1)) < H: test_horizontal_result = np.zeros((n, t, 3, scale*patch_h, scale*W)) h_begin = patch_h*(h_index-1)-patch_h_overlap*(h_index-1) h_end = patch_h*h_index-patch_h_overlap*(h_index-1) w_index = 1 w_end = 0 while (patch_w*w_index-patch_w_overlap*(w_index-1)) < W: w_begin = patch_w*(w_index-1)-patch_w_overlap*(w_index-1) w_end = patch_w*w_index-patch_w_overlap*(w_index-1) test_patch = input_data[:, :, :, h_begin:h_end, w_begin:w_end] output_patch = model(test_patch)[iter] output_patch = \ [output.cpu().detach().numpy().astype(np.float32) for output in output_patch] output_patch = np.stack(output_patch, axis=1) if w_index == 1: test_horizontal_result[:, :, :, :, w_begin*scale:w_end*scale] = \ output_patch else: for i in range(patch_w_overlap*scale): test_horizontal_result[:, :, :, :, w_begin * scale + i] = \ test_horizontal_result[:, :, :, :, w_begin * scale + i]\ * (patch_w_overlap * scale-1-i)/(patch_w_overlap * scale -1)\ + output_patch[:, :, :, :, i] * i/(patch_w_overlap * scale -1) cur_begin = w_begin+patch_w_overlap cur_begin = cur_begin*scale test_horizontal_result[:, :, :, :, cur_begin:w_end*scale] = \ output_patch[:, :, :, :, patch_w_overlap * scale:] w_index += 1 test_patch = input_data[:, :, :, h_begin:h_end, -patch_w:] output_patch = model(test_patch)[iter] output_patch = \ [output.cpu().detach().numpy().astype(np.float32) for output in output_patch] output_patch = np.stack(output_patch, axis=1) last_range = w_end-(W-patch_w) last_range = last_range * scale for i in range(last_range): term1 = test_horizontal_result[:, :, :, :, W*scale-patch_w*scale+i] rate1 = (last_range-1-i)/(last_range-1) term2 = output_patch[:, :, :, :, i] rate2 = i/(last_range-1) test_horizontal_result[:, :, :, :, W*scale-patch_w*scale+i] = \ term1*rate1+term2*rate2 test_horizontal_result[:, :, :, :, w_end*scale:] = \ output_patch[:, :, :, :, last_range:] if h_index == 1: test_result[:, :, :, h_begin*scale:h_end*scale, :] = test_horizontal_result else: for i in range(patch_h_overlap*scale): term1 = test_result[:, :, :, h_begin*scale+i, :] rate1 = (patch_h_overlap*scale-1-i)/(patch_h_overlap*scale-1) term2 = test_horizontal_result[:, :, :, i, :] rate2 = i/(patch_h_overlap*scale-1) test_result[:, :, :, h_begin*scale+i, :] = \ term1 * rate1 + term2 * rate2 test_result[:, :, :, h_begin*scale+patch_h_overlap*scale:h_end*scale, :] = \ test_horizontal_result[:, :, :, patch_h_overlap*scale:, :] h_index += 1 test_horizontal_result = np.zeros((n, t, 3, patch_h*scale, W*scale)) w_index = 1 while (patch_w * w_index - patch_w_overlap * (w_index-1)) < W: w_begin = patch_w * (w_index-1) - patch_w_overlap * (w_index-1) w_end = patch_w * w_index - patch_w_overlap * (w_index-1) test_patch = input_data[:, :, :, -patch_h:, w_begin:w_end] output_patch = model(test_patch)[iter] output_patch = \ [output.cpu().detach().numpy().astype(np.float32) for output in output_patch] output_patch = np.stack(output_patch, axis=1) if w_index == 1: test_horizontal_result[:, :, :, :, w_begin*scale:w_end*scale] = output_patch else: for i in range(patch_w_overlap*scale): term1 = test_horizontal_result[:, :, :, :, w_begin*scale+i] rate1 = (patch_w_overlap*scale-1-i)/(patch_w_overlap*scale-1) term2 = output_patch[:, :, :, :, i] rate2 = i/(patch_w_overlap*scale-1) test_horizontal_result[:, :, :, :, w_begin*scale+i] = \ term1*rate1+term2*rate2 cur_begin = w_begin+patch_w_overlap test_horizontal_result[:, :, :, :, cur_begin*scale:w_end*scale] = \ output_patch[:, :, :, :, patch_w_overlap*scale:] w_index += 1 test_patch = input_data[:, :, :, -patch_h:, -patch_w:] output_patch = model(test_patch)[iter] output_patch = \ [output.cpu().detach().numpy().astype(np.float32) for output in output_patch] output_patch = np.stack(output_patch, axis=1) last_range = w_end-(W-patch_w) for i in range(last_range*scale): term1 = test_horizontal_result[:, :, :, :, W*scale-patch_w*scale+i] rate1 = (last_range*scale-1-i)/(last_range*scale-1) term2 = output_patch[:, :, :, :, i] rate2 = i/(last_range*scale-1) test_horizontal_result[:, :, :, :, W*scale-patch_w*scale+i] = \ term1*rate1+term2*rate2 test_horizontal_result[:, :, :, :, w_end*scale:] = \ output_patch[:, :, :, :, last_range*scale:] last_last_range = h_end-(H-patch_h) for i in range(last_last_range*scale): term1 = test_result[:, :, :, H*scale-patch_w*scale+i, :] rate1 = (last_last_range*scale-1-i)/(last_last_range*scale-1) term2 = test_horizontal_result[:, :, :, i, :] rate2 = i/(last_last_range*scale-1) test_result[:, :, :, H*scale-patch_w*scale+i, :] = \ term1*rate1+term2*rate2 cur_result = test_horizontal_result[:, :, :, last_last_range*scale:, :] test_result[:, :, :, h_end*scale:, :] = cur_result return test_result if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--model', help="restore checkpoint") parser.add_argument('--dataset', help="dataset for evaluation") parser.add_argument('--small', action='store_true', help='use small model') parser.add_argument('--mixed_precision', action='store_true', help='use mixed precision') parser.add_argument('--alternate_corr', action='store_true', help='use efficent correlation implementation') args = parser.parse_args() model = torch.nn.DataParallel(RAFT(args)) model.load_state_dict(torch.load(args.model)) model.cuda() model.eval() # create_sintel_submission(model.module, warm_start=True) # create_kitti_submission(model.module) with torch.no_grad(): if args.dataset == 'chairs': validate_chairs(model.module) elif args.dataset == 'sintel': validate_sintel(model.module) elif args.dataset == 'kitti': validate_kitti(model.module)

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f3991d6332850a19d210d2fbdfac81e250ef52f6

196

py

Python

agoracommuns/agoracommuns/core/admin.py

daneoshiga/agoracommuns

a25f057ab412900b5aab1dc163c053610527cae0

[ "MIT" ]

null

agoracommuns/agoracommuns/core/admin.py

daneoshiga/agoracommuns

a25f057ab412900b5aab1dc163c053610527cae0

[ "MIT" ]

null

agoracommuns/agoracommuns/core/admin.py

daneoshiga/agoracommuns

a25f057ab412900b5aab1dc163c053610527cae0

[ "MIT" ]

null

# -*- coding: utf-8 -*- from django.contrib import admin from .models import (Agenda, Deliberation, Vote) admin.site.register(Agenda) admin.site.register(Deliberation) admin.site.register(Vote)

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342abcedbbd3d5e91ece0916b2f08cc9d091803d

443

py

Python

CV/core/views.py

joaquingb1993/cv-joaquin-galvez-blanco

9e3c8ce2f2f1662bcd4840bffd03c219b2da2ced

[ "Apache-2.0" ]

null

CV/core/views.py

joaquingb1993/cv-joaquin-galvez-blanco

9e3c8ce2f2f1662bcd4840bffd03c219b2da2ced

[ "Apache-2.0" ]

null

CV/core/views.py

joaquingb1993/cv-joaquin-galvez-blanco

9e3c8ce2f2f1662bcd4840bffd03c219b2da2ced

[ "Apache-2.0" ]

null

from django.shortcuts import render, HttpResponse from .models import Project # Create your views here. def home(request): projects = Project.objects.all() return render(request,"core/home.html",{'projects':projects}) def about(request): return render(request,"core/about.html") def portfolio(request): return render(request, "core/portfolio.html") def contacto(request): return render(request, "core/contacto.html")

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null

0

1

0

1

0

5

342da14d5077e99101d91d41301c12a7040a301a

1,169

py

Python

tests/translated_code__expected.py

habiter-app/xbot

b05f76b0ec23902d9edfc5b79bd2940630c8ed6b

[ "MIT" ]

1

2021-07-12T06:21:57.000Z

tests/translated_code__expected.py

habiter-app/xbot

b05f76b0ec23902d9edfc5b79bd2940630c8ed6b

[ "MIT" ]

null

tests/translated_code__expected.py

habiter-app/xbot

b05f76b0ec23902d9edfc5b79bd2940630c8ed6b

[ "MIT" ]

1

2020-05-18T20:03:07.000Z

@xbot.xfunction @bot.command(name='add') async def add(ctx): """__GENERATED__ cross platform generated function""" try: message = ctx.message.content (_, left, right) = message.split(' ') result = (int(left) + int(right)) await ctx.send(result) except (IndexError, ValueError): await ctx.send('Usage: /add <left> <right>') @xbot.xfunction @bot.command(name='subtract') async def subtract(ctx): """__GENERATED__ cross platform generated function""" try: message = ctx.message.content (_, left, right) = message.split(' ') result = (int(left) - int(right)) await ctx.send(result) except (IndexError, ValueError): await ctx.send('Usage: /subtract <left> <right>') @xbot.xfunction @bot.command(name='echo') async def echo(ctx): """__GENERATED__ cross platform generated function""" await ctx.send(ctx.message.content) @xbot.xfunction @bot.command(name='echo_additional_arguments') async def echo_additional_arguments(ctx, custom_argument_1, custom_argument_2): """__GENERATED__ cross platform generated function""" await ctx.send(ctx.message.content)

33.4

79

0.673225

138

1,169

5.514493

0.253623

0.063075

0.094612

0.120894

0.810775

0.775296

0.725361

0.630749

0

0.002103

0.186484

1,169

35

80

33.4

0.798107

0

0.571429

1

0

0.10334

0.026096

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

5

3434b8b2158b075504c712af40e1e57505835e4d

53

py

Python

server/athenian/api/models/precomputed/models.py

athenianco/athenian-api

dd5556101a8c49703d6b0516e4268b9e8d8eda5b

[ "RSA-MD" ]

9

2020-10-11T22:12:03.000Z

2022-02-26T02:16:45.000Z

server/athenian/api/models/precomputed/models.py

athenianco/athenian-api

dd5556101a8c49703d6b0516e4268b9e8d8eda5b

[ "RSA-MD" ]

246

2019-12-05T06:37:30.000Z

2022-03-29T10:00:07.000Z

server/athenian/api/models/precomputed/models.py

athenianco/athenian-api

dd5556101a8c49703d6b0516e4268b9e8d8eda5b

[ "RSA-MD" ]

5

2019-12-04T22:38:05.000Z

2021-02-26T00:50:04.000Z

from athenian.precomputer.db.models import * # noqa

26.5

52

0.773585

7

53

5.857143

1

0

0.132075

53

1

53

0.891304

0.075472

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3448e314b5730371d84572e930ed1e08db58d30b

101

py

Python

tests/__init__.py

isabella232/elections18-general

24dfe44c6da6312f062816a6d19c87a39d7ddb7b

[ "MIT" ]

3

2018-12-02T21:49:39.000Z

2021-01-06T01:43:30.000Z

tests/__init__.py

nprapps/elections18-general

24dfe44c6da6312f062816a6d19c87a39d7ddb7b

[ "MIT" ]

35

2018-06-06T15:20:03.000Z

2018-11-15T18:30:11.000Z

tests/__init__.py

isabella232/elections18-general

24dfe44c6da6312f062816a6d19c87a39d7ddb7b

[ "MIT" ]

1

2021-02-23T10:21:33.000Z

import app_config from fabfile import data app_config.configure_targets('test') data.bootstrap_db()

16.833333

36

0.831683

15

101

5.333333

0.733333

0.225

0

0.089109

101

5

37

20.2

0.869565

0

0.039604

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

345e9764350d571b96ef68baf9055799ccf27c32

401

py

Python

regex_lab/regex1.py

jeremyosborne/examples-python

5900b3a4f47d59de0a32d3257a8b90a44e80fdcd

[ "MIT" ]

null

regex_lab/regex1.py

jeremyosborne/examples-python

5900b3a4f47d59de0a32d3257a8b90a44e80fdcd

[ "MIT" ]

null

regex_lab/regex1.py

jeremyosborne/examples-python

5900b3a4f47d59de0a32d3257a8b90a44e80fdcd

[ "MIT" ]

null

# Find the IP address in the following line using a regex group and the # re.search function. Print the IP address using the match object group # method, as well as the index of where the grouping starts and ends. log = '208.115.111.73 - - [01/Apr/2013:06:30:26 -0700] "GET /nanowiki/index.php/1_November_2007_-_Day_1 HTTP/1.1" 404 36 "-" "Mozilla/5.0 (compatible; Ezooms/1.0; ezooms.bot@gmail.com)"'

80.2

186

0.735661

76

401

3.815789

0.75

0.034483

0.082759

0

0.12828

0.144638

401

4

187

100.25

0.717201

0.516209

0

1

0.936842

0.452632

0

1

0

false

0

null

0

1

0

1

0

1

null

0

5

345f51e07ea03c69b1c901dff6be296bf23ea803

725

py

Python

blablacarapi/paging.py

arrrlo/BlaBlaCar-Client-Api

567f60f0e1ad39b1f8b440ddcce45878f9483a3d

[ "MIT" ]

5

2016-10-14T08:59:07.000Z

2021-02-28T22:52:03.000Z

blablacarapi/paging.py

arrrlo/BlaBlaCar-Client-Api

567f60f0e1ad39b1f8b440ddcce45878f9483a3d

[ "MIT" ]

null

blablacarapi/paging.py

arrrlo/BlaBlaCar-Client-Api

567f60f0e1ad39b1f8b440ddcce45878f9483a3d

[ "MIT" ]

5

2017-10-10T12:10:09.000Z

2021-12-10T10:51:58.000Z

__author__ = 'ivan.arar@gmail.com' class Paging(object): def __init__(self, paging_data): self.paging_data = paging_data def has_next(self): if int(self.paging_data['page']) == int(self.paging_data['pages']): return False else: return True def has_previous(self): if int(self.paging_data['page']) == 1: return False else: return True def next(self): if self.has_next(): return int(self.paging_data['page'])+1 else: return False def previous(self): if self.has_previous(): return int(self.paging_data['page'])-1 else: return False

22.65625

75

0.547586

88

725

4.284091

0.272727

0.212202

0.259947

0.225464

0.522546

0.371353

0.228117

0

0.006263

0.33931

725

31

76

23.387097

0.780793

0

0.416667

0

0.055172

0

1

0.208333

false

0

0.583333

0

null

1

0

null

0

1

0

1

0

5

ca9e565c695ec3581bd9f5089a82c28df4cdd8ab

142

py

Python

hello_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

hello_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

hello_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

# - helloworld.py *- coding: utf-8 -*- """ This program simply prints the phrase "Hello, World!" @author: wboyd """ print("Hello, World!")

14.2

53

0.633803

18

142

5

0.888889

0.222222

0

0.008475

0.169014

142

9

54

15.777778

0.754237

0.753521

0

0.5

0

1

0

true

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

cae75424142676b5fb927624955a8ef75a4470e3

190

py

Python

ai_haste/tester/main.py

aidotse/Team-Haste

b8e074d396be31c0b5c292053aff160c55b75786

[ "MIT" ]

null

ai_haste/tester/main.py

aidotse/Team-Haste

b8e074d396be31c0b5c292053aff160c55b75786

[ "MIT" ]

null

ai_haste/tester/main.py

aidotse/Team-Haste

b8e074d396be31c0b5c292053aff160c55b75786

[ "MIT" ]

null

from ai_haste import tester as test def run(config, dataloader, models, save_folder): tester = getattr(test, config["tester"])(config, save_folder) tester.test(dataloader, models)

27.142857

65

0.742105

26

190

5.307692

0.576923

0.231884

0

0.147368

190

6

66

31.666667

0.851852

0

0.031579

0

1

0.25

false

0

0.25

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

caf19e402f619759ad4a5a4a80861feea02c1edd

281

py

Python

ple/games/__init__.py

rohanraj96/RL-PriorKnowledge

31d7c53f3f9c394f148a7133a7aaf5e550176870

[ "MIT" ]

62

2018-06-19T07:57:03.000Z

2022-03-12T14:09:40.000Z

ple/games/__init__.py

rohanraj96/RL-PriorKnowledge

31d7c53f3f9c394f148a7133a7aaf5e550176870

[ "MIT" ]

4

2018-09-19T21:11:09.000Z

2019-05-14T21:38:28.000Z

ple/games/__init__.py

rach0012/humanRL_prior_games

c9fff26af5df3e1cdea023536da5fda114ba5c60

[ "MIT" ]

13

2018-06-19T10:52:19.000Z

2021-12-21T12:19:18.000Z

from ple.games.originalgame import originalGame from ple.games.nosemantics import nosemantics from ple.games.nosimilarity import nosimilarity from ple.games.noobject import noobject from ple.games.noaffordance import noaffordance from ple.games.continualgame import continualgame

35.125

49

0.868327

36

281

6.777778

0.277778

0.172131

0.295082

0

0.088968

281

7

50

40.142857

0.953125

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

1b0a12fac8da7bcb2d4d7c46dcad1989cf07b91f

177

py

Python

data/studio21_generated/interview/0272/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/0272/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/0272/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

class Solution: def maxCandies(self, status: List[int], candies: List[int], keys: List[List[int]], containedBoxes: List[List[int]], initialBoxes: List[int]) -> int:

59

152

0.672316

23

177

5.173913

0.521739

0.294118

0.184874

0

0.158192

177

3

153

59

0.798658

0

null

0

null

0

1

0

null

1

0

1

0

null

0

1

0

5

1b14eb3388929ebb2a26bdbb6f5c65795193b07d

51

py

Python

spekulatio/som/extractors/frontmatter/__init__.py

iwilltry42/spekulatio

42d678b7d7fcc13284902be5a08fb0407d96ec4d

[ "MIT" ]

10

2019-03-19T23:05:04.000Z

2022-01-19T14:08:06.000Z

spekulatio/som/extractors/frontmatter/__init__.py

iwilltry42/spekulatio

42d678b7d7fcc13284902be5a08fb0407d96ec4d

[ "MIT" ]

6

2019-03-23T08:38:44.000Z

2020-11-24T20:50:14.000Z

spekulatio/som/extractors/frontmatter/__init__.py

iwilltry42/spekulatio

42d678b7d7fcc13284902be5a08fb0407d96ec4d

[ "MIT" ]

1

2019-09-26T12:21:36.000Z

from .parse_frontmatter import parse_frontmatter

12.75

48

0.862745

6

51

7

0.666667

0.761905

0

0.117647

51

3

49

17

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

1b1d164aac2e02f498fa1e7e5745a253668fe33a

1,822

py

Python

algofi/v1/prepend.py

owen-colegrove/algofi-py-sdk

2fc137e5895601feef9ccda5ed5de3beebfb2f99

[ "MIT" ]

null

algofi/v1/prepend.py

owen-colegrove/algofi-py-sdk

2fc137e5895601feef9ccda5ed5de3beebfb2f99

[ "MIT" ]

null

algofi/v1/prepend.py

owen-colegrove/algofi-py-sdk

2fc137e5895601feef9ccda5ed5de3beebfb2f99

[ "MIT" ]

null

from algofi.config import manager_id, storage_ids, oracle_ids, ordered_symbols from algosdk.future.transaction import ApplicationNoOpTxn def get_init_txns(sender_addr, params, account=None): txn0 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_prices'], foreign_apps=[oracle_ids[symbol] for symbol in ordered_symbols]) txn1 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_exchange_rate'], foreign_apps=[storage_ids[symbol] for symbol in ordered_symbols]) if (account): txn2 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_collateral_value'], foreign_apps=[storage_ids[symbol] for symbol in ordered_symbols], accounts=[account]) txn3 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_borrow_value'], foreign_apps=[storage_ids[symbol] for symbol in ordered_symbols], accounts=[account]) else: txn2 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_collateral_value'], foreign_apps=[storage_ids[symbol] for symbol in ordered_symbols]) txn3 = ApplicationNoOpTxn(sender_addr, params, manager_id, [b'update_borrow_value'], foreign_apps=[storage_ids[symbol] for symbol in ordered_symbols]) return [txn0, txn1, txn2, txn3]

70.076923

136

0.535126

164

1,822

5.652439

0.27439

0.067961

0.12082

0.220065

0.746494

0.709817

0.601942

0

0.009091

0.396268

1,822

26

137

70.076923

0.833636

0

0.583333

0

0.06418

0.025233

0

1

0.041667

false

0

0.083333

0

0.166667

0

null

0

1

0

1

0

1

0

null

0

5

1b81350a022679927de28d3b2e918178f8b36153

80

py

Python

akashrajput25/Some_py_prog/print_name.py

TechGirl007/Hacktoberfest-2024

5d7cbfc8552dd6fb0eebbdc7353c699748b1b51d

[ "MIT" ]

40

2021-09-25T04:50:35.000Z

2021-11-08T12:47:52.000Z

akashrajput25/Some_py_prog/print_name.py

TechGirl007/Hacktoberfest-2024

5d7cbfc8552dd6fb0eebbdc7353c699748b1b51d

[ "MIT" ]

18

2021-09-26T05:50:29.000Z

2021-10-05T07:03:22.000Z

akashrajput25/Some_py_prog/print_name.py

TechGirl007/Hacktoberfest-2024

5d7cbfc8552dd6fb0eebbdc7353c699748b1b51d

[ "MIT" ]

213

2021-09-24T06:27:35.000Z

2021-10-31T17:59:38.000Z

name=input("Enter your name") print(f"Your name in reverse order: {name[::-1]}")

40

50

0.6875

14

80

3.928571

0.714286

0.290909

0

0.013889

0.1

80

2

50

40

0.75

0

0.679012

0

1

0

false

0

0.5

1

0

null

1

0

1

0

1

0

null

0

1

0

5

1b8a9f7e4a06ea16137264fdaa730e76db7b9aff

52

py

Python

test.py

xjunhello/BetterBuy

ee9643a8c3c551bda587951f5c69ef3c308e1d59

[ "Apache-2.0" ]

null

test.py

xjunhello/BetterBuy

ee9643a8c3c551bda587951f5c69ef3c308e1d59

[ "Apache-2.0" ]

null

test.py

xjunhello/BetterBuy

ee9643a8c3c551bda587951f5c69ef3c308e1d59

[ "Apache-2.0" ]

null

print "Hello world!" asdfasdfasdfasdfasdfasdfasdf

10.4

28

0.826923

4

52

10.75

1

0

0.115385

52

4

29

13

0.934783

0

0.24

0

null

0

null

0.5

1

0

1

null

0

1

0

null

0

1

0

1

0

5

1b97dabac3787b6ef6fc795e2f70a3b9f333d3bf

127

py

Python

barpyrus.py

AckslD/barpyrus

a89ef3b1453b27998940137b1ccee47d23a19612

[ "BSD-2-Clause-FreeBSD" ]

23

2016-07-12T19:04:51.000Z

2022-03-29T01:55:31.000Z

barpyrus.py

AckslD/barpyrus

a89ef3b1453b27998940137b1ccee47d23a19612

[ "BSD-2-Clause-FreeBSD" ]

17

2017-02-16T21:03:51.000Z

2021-12-04T08:28:13.000Z

barpyrus.py

AckslD/barpyrus

a89ef3b1453b27998940137b1ccee47d23a19612

[ "BSD-2-Clause-FreeBSD" ]

9

2016-12-15T13:46:48.000Z

2021-07-27T22:11:47.000Z

#!/usr/bin/env python3 import barpyrus.mainloop import sys if __name__ == '__main__': sys.exit(barpyrus.mainloop.main())

15.875

38

0.724409

17

127

4.941176

0.705882

0.380952

0

0.009091

0.133858

127

7

39

18.142857

0.754545

0.165354

0

0.07619

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

1bb68cf12331b69615372a0e8813ad52d46b8d14

78

py

Python

hooks/__init__.py

rattboi/hangoutsbot

be32643e526b6f34c704d1a60c42e8b7f171988a

[ "MIT" ]

6

2017-11-27T05:00:26.000Z

2021-05-31T16:43:44.000Z

hooks/__init__.py

rattboi/hangoutsbot

be32643e526b6f34c704d1a60c42e8b7f171988a

[ "MIT" ]

5

2016-12-09T13:43:11.000Z

2017-06-23T01:10:06.000Z

hooks/__init__.py

rattboi/hangoutsbot

be32643e526b6f34c704d1a60c42e8b7f171988a

[ "MIT" ]

5

2016-11-13T23:15:23.000Z

2020-06-03T14:55:45.000Z

from utils.imports import import_all all_hooks = import_all("hooks", "hook")

19.5

39

0.769231

12

78

4.75

0.583333

0.315789

0

0.115385

78

3

40

26

0.826087

0

0.115385

0

1

0

false

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

1bc26e2845e5d1131ca4db156953e89fe923389b

139

py

Python

lc_wrapper/bash/__main__.py

YOSHIZAWA-Naomi/Jupyter-LC_wrapper

4c14da10e9136dcff9dd2eab24db532a4e7d70a5

[ "BSD-3-Clause" ]

12

2017-07-04T13:49:13.000Z

2021-12-28T16:06:03.000Z

lc_wrapper/bash/__main__.py

YOSHIZAWA-Naomi/Jupyter-LC_wrapper

4c14da10e9136dcff9dd2eab24db532a4e7d70a5

[ "BSD-3-Clause" ]

26

2017-05-16T07:54:08.000Z

2022-03-24T07:21:10.000Z

lc_wrapper/bash/__main__.py

YOSHIZAWA-Naomi/Jupyter-LC_wrapper

4c14da10e9136dcff9dd2eab24db532a4e7d70a5

[ "BSD-3-Clause" ]

10

2017-05-27T03:15:45.000Z

2020-01-23T05:01:00.000Z

from ipykernel.kernelapp import IPKernelApp from . import BashKernelBuffered IPKernelApp.launch_instance(kernel_class=BashKernelBuffered)

27.8

60

0.884892

14

139

8.642857

0.714286

0

0.071942

139

4

61

34.75

0.937985

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

943e15018cac2590ce6c93cf674d4818349111bb

46

py

Python

tests/__init__.py

dabble-of-devops-bioanalyze/fab_coreui_theme

400dbbf3a62ca0e9933b8a457eb2912541920c58

[ "MIT" ]

null

tests/__init__.py

dabble-of-devops-bioanalyze/fab_coreui_theme

400dbbf3a62ca0e9933b8a457eb2912541920c58

[ "MIT" ]

null

tests/__init__.py

dabble-of-devops-bioanalyze/fab_coreui_theme

400dbbf3a62ca0e9933b8a457eb2912541920c58

[ "MIT" ]

null

"""Unit test package for fab_coreui_theme."""

23

45

0.73913

7

46

4.571429

1

0

0.108696

46

1

46

0.780488

0.847826

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

84c83fcc11354d829be6ef7a49890d796769bc82

79

py

Python

5 Star Python/Power Mod-Power.py

TheCodeAlpha26/Hackerrank-Demystified

03713a8f3a05e5d6dfed6f6808b06340558e2310

[ "Apache-2.0" ]

6

2021-04-26T17:09:54.000Z

2021-07-08T17:36:16.000Z

5 Star Python/Power Mod-Power.py

TheCodeAlpha26/Hackerrank-Demystified

03713a8f3a05e5d6dfed6f6808b06340558e2310

[ "Apache-2.0" ]

null

5 Star Python/Power Mod-Power.py

TheCodeAlpha26/Hackerrank-Demystified

03713a8f3a05e5d6dfed6f6808b06340558e2310

[ "Apache-2.0" ]

null

a,b,m=int(input()),int(input()),int(input()) print(pow(a,b)) print(pow(a,b,m))

19.75

44

0.607595

18

79

2.666667

0.388889

0.125

0.666667

0

0.037975

79

3

45

26.333333

0.631579

0

1

0

true

0

0.666667

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

84d03737db7c2354c6c9d53ebadbee8221add8d6

364

py

Python

pagarme/card.py

rbbonfim/pagarme-python

a7079fbdd01bd855ea09f89847d6374b499be76b

[ "MIT" ]

79

2015-08-25T14:43:34.000Z

2021-12-01T18:16:54.000Z

pagarme/card.py

rbbonfim/pagarme-python

a7079fbdd01bd855ea09f89847d6374b499be76b

[ "MIT" ]

103

2015-09-15T15:24:14.000Z

2021-12-20T22:52:02.000Z

pagarme/card.py

rbbonfim/pagarme-python

a7079fbdd01bd855ea09f89847d6374b499be76b

[ "MIT" ]

53

2015-09-11T12:06:26.000Z

2022-02-23T02:59:57.000Z

from pagarme.resources import handler_request from pagarme.resources.routes import card_routes def create(dictionary): return handler_request.post(card_routes.BASE_URL, dictionary) def find_all(): return handler_request.get(card_routes.GET_ALL_CARDS) def find_by(search_params): return handler_request.get(card_routes.GET_CARD_BY, search_params)

24.266667

70

0.818681

53

364

5.301887

0.415094

0.199288

0.213523

0.163701

0.256228

0

0.10989

364

14

71

26

0.867284

0

1

0.375

false

0

0.25

0.375

1

0

null

0

1

0

null

0

1

0

1

0

5

ca3dfc002f9cd645b674ee7a8ca5579af90bce9f

115

py

Python

gitlab_ldap_sync/__init__.py

e5-tu-do/gitlab_ldap_group_sync

c387b880ec2f4143776c5386aae144dc28656017

[ "MIT" ]

1

2020-03-27T14:46:20.000Z

gitlab_ldap_sync/__init__.py

e5-tu-do/gitlab_ldap_group_sync

c387b880ec2f4143776c5386aae144dc28656017

[ "MIT" ]

null

gitlab_ldap_sync/__init__.py

e5-tu-do/gitlab_ldap_group_sync

c387b880ec2f4143776c5386aae144dc28656017

[ "MIT" ]

null

from .utils import getenvbool from .ldap_connection import ldap_connect __all__ = ['getenvbool', 'ldap_connect']

19.166667

41

0.791304

14

115

6

0.571429

0.261905

0

0.121739

115

5

42

23

0.831683

0

0.191304

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

ca4c72b7eff591852a1ce7f2fb4c62e08b59c7e7

140

py

Python

Guitar Training Remote/model/exercise_step.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

3

2018-06-28T07:09:04.000Z

2019-03-04T14:43:52.000Z

Guitar Training Remote/model/exercise_step.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

null

Guitar Training Remote/model/exercise_step.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

5

2018-06-28T07:12:28.000Z

2021-06-03T18:20:21.000Z

class ExerciseStep: def __init__(self, main_text:str, sub_text=""): self.main_text = main_text self.sub_text = sub_text

28

51

0.671429

20

140

4.2

0.45

0.285714

0

0.228571

140

5

52

28

0.777778

0

1

0.25

false

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

047df13b9f9ef7279a6e60721877b05343bbf24d

118

py

Python

AoC20/day_03/a.py

a-recknagel/AoC20

7aa0013dc745bdc0ad357e1168b212bd065fd092

[ "MIT" ]

null

AoC20/day_03/a.py

a-recknagel/AoC20

7aa0013dc745bdc0ad357e1168b212bd065fd092

[ "MIT" ]

null

AoC20/day_03/a.py

a-recknagel/AoC20

7aa0013dc745bdc0ad357e1168b212bd065fd092

[ "MIT" ]

null

from AoC20.day_3 import trees, data as data print(sum(trees([line.strip() for line in data.splitlines()], (1, 3))))

23.6

71

0.694915

21

118

3.857143

0.761905

0

0.04902

0.135593

118

4

72

29.5

0.745098

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

0481abd22b5988ea45af4037f97012b308c0e446

43

py

Python

montreal_forced_aligner/__main__.py

sameerkhurana10/Montreal-Forced-Aligner

b64b6bf4aa0394d59236510a05453740e7e7ebf5

[ "MIT" ]

null

montreal_forced_aligner/__main__.py

sameerkhurana10/Montreal-Forced-Aligner

b64b6bf4aa0394d59236510a05453740e7e7ebf5

[ "MIT" ]

null

montreal_forced_aligner/__main__.py

sameerkhurana10/Montreal-Forced-Aligner

b64b6bf4aa0394d59236510a05453740e7e7ebf5

[ "MIT" ]

null

from .command_line.mfa import main main()

10.75

34

0.767442

7

43

4.571429

0.857143

0

0.139535

43

3

35

14.333333

0.864865

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

04ada8c44a8539a27e7591baa5265dc3d2ba9154

215

py

Python

Week14/33.py

bobsingh149/LeetCode

293ed4931960bf5b9a3d5c4331ba4dfddccfcd55

[ "MIT" ]

101

2021-02-26T14:32:37.000Z

2022-03-16T18:46:37.000Z

Week14/33.py

bobsingh149/LeetCode

293ed4931960bf5b9a3d5c4331ba4dfddccfcd55

[ "MIT" ]

null

Week14/33.py

bobsingh149/LeetCode

293ed4931960bf5b9a3d5c4331ba4dfddccfcd55

[ "MIT" ]

30

2021-03-09T05:16:48.000Z

2022-03-16T21:16:33.000Z

### DO NOT REMOVE THIS from typing import List ### DO NOT REMOVE THIS class Solution: def search(self, nums: List[int], target: int) -> int: return nums.index(target) if target in nums else -1

26.875

60

0.646512

33

215

4.212121

0.666667

0.071942

0.158273

0.215827

0

0.006211

0.251163

215

7

61

30.714286

0.857143

0.172093

0

1

0.25

false

0

0.25

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

04e21d69c5026429181a1d186c648fee1ed344e5

78

py

Python

whyis/blueprint/entity/entity_blueprint.py

tolulomo/whyis

eb50ab3301eb7efd27a1a3f6fb2305dedd910397

[ "Apache-2.0" ]

31

2018-05-30T02:41:23.000Z

2021-10-17T01:25:20.000Z

whyis/blueprint/entity/entity_blueprint.py

tolulomo/whyis

eb50ab3301eb7efd27a1a3f6fb2305dedd910397

[ "Apache-2.0" ]

115

2018-04-07T00:59:11.000Z

2022-03-02T03:06:45.000Z

whyis/blueprint/entity/entity_blueprint.py

tolulomo/whyis

eb50ab3301eb7efd27a1a3f6fb2305dedd910397

[ "Apache-2.0" ]

25

2018-04-07T00:49:55.000Z

2021-09-28T14:29:18.000Z

from flask import Blueprint entity_blueprint = Blueprint("entity", __name__)

19.5

48

0.807692

9

78

6.444444

0.666667

0.517241

0

0.115385

78

3

49

26

0.84058

0

0.076923

0

1

0

false

0

0.5

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

5

04f14fd4c887f8e9c7b7abe1b4c9ec8785efd2d7

337

py

Python

data_structures/stack/conftest.py

asakatida/data-structures-and-algorithms.py

587d1a66a6c15a3c7d7786275608f065687e1810

[ "MIT" ]

null

data_structures/stack/conftest.py

asakatida/data-structures-and-algorithms.py

587d1a66a6c15a3c7d7786275608f065687e1810

[ "MIT" ]

2

2020-09-24T13:13:49.000Z

2021-06-25T15:15:35.000Z

data_structures/stack/conftest.py

grandquista/data-structures-and-algorithms.py

587d1a66a6c15a3c7d7786275608f065687e1810

[ "MIT" ]

null

from .stack import Stack from pytest import fixture @fixture def new_stack(): return Stack() @fixture def ordered_stack(): return Stack(range(3, 40, 3)) @fixture def unordered_stack(): return Stack(map(lambda i: i % 7, range(73, 40, -2))) @fixture def large_stack(): return Stack("task" for _ in range(0xFFFFFF))

14.652174

57

0.679525

50

337

4.48

0.48

0.178571

0.285714

0

0.040441

0.192878

337

22

58

15.318182

0.783088

0

0.285714

0

0.011869

0

0.023739

0

1

0.285714

true

0

0.142857

0.285714

0.714286

0

null

0

1

0

null

0

1

0

1

0

5

04f8fc99a387975ace75ce0a00ca29bc03a5eeca

117

py

Python

packs/update.py

Habejota/Forge

51aa6ef54467fd0e1b98ee2273c062e6e6c7d9f4

[ "Apache-2.0" ]

2

2021-06-14T22:37:23.000Z

2021-06-15T02:03:09.000Z

packs/update.py

Habejota/Forge

51aa6ef54467fd0e1b98ee2273c062e6e6c7d9f4

[ "Apache-2.0" ]

null

packs/update.py

Habejota/Forge

51aa6ef54467fd0e1b98ee2273c062e6e6c7d9f4

[ "Apache-2.0" ]

null

print("OSystem Forge 1.0") print("To update forge version use:") print("\n\n forge --update\n\n")

39

52

0.57265

18

117

3.722222

0.555556

0.059701

0

0.022989

0.25641

117

3

52

39

0.747126

0

0.745763

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

04fb8352a8dcfa17850582c9fa0322b57480f3f0

1,742

py

Python

tests/datasets/test_ua_cbsa.py

bhagyaramgpo/skills-ml

be520fc2a2f88bff756d25e57c3378a465a1dcb2

[ "MIT" ]

147

2016-12-05T19:45:05.000Z

2022-02-17T03:03:28.000Z

tests/datasets/test_ua_cbsa.py

bhagyaramgpo/skills-ml

be520fc2a2f88bff756d25e57c3378a465a1dcb2

[ "MIT" ]

390

2016-12-02T03:11:13.000Z

2022-03-28T22:08:20.000Z

tests/datasets/test_ua_cbsa.py

bhagyaramgpo/skills-ml

be520fc2a2f88bff756d25e57c3378a465a1dcb2

[ "MIT" ]

66

2017-12-14T16:33:24.000Z

2022-02-17T03:03:31.000Z

import httpretty from skills_ml.datasets.ua_cbsa import ua_cbsa, URL RESPONSE = '''UA,UANAME,CBSA,MNAME,MEMI,POPPT,HUPT,AREAPT,AREALANDPT,UAPOP,UAHU,UAAREA,UAAREALAND,MPOP,MHU,MAREA,MAREALAND,UAPOPPCT,UAHUPCT,UAAREAPCT,UAAREALANDPCT,MPOPPCT,MHUPCT,MAREAPCT,MAREALANDPCT 00037,"Abbeville, LA Urban Cluster",10020,"Abbeville, LA Micro Area",2,19268,8216,28218638,27918141,19824,8460,29523368,29222871,57999,25235,3993941933,3038572441,97.2,97.12,95.58,95.54,33.22,32.56,.71,.92 00037,"Abbeville, LA Urban Cluster",35340,"New Iberia, LA Micro Area",2,556,244,1304730,1304730,19824,8460,29523368,29222871,73240,29698,2669055888,1486940445,2.8,2.88,4.42,4.46,.76,.82,.05,.09 00064,"Abbeville, SC Urban Cluster",99999,"Not in a metro/micro area",,5243,2578,11334983,11315197,5243,2578,11334983,11315197,,,,,100,100,100,100,,,, 00091,"Abbotsford, WI Urban Cluster",48140,"Wausau, WI Metro Area",1,1103,428,2102170,2102170,3966,1616,5376662,5363441,134063,57734,4082627087,4001488029,27.81,26.49,39.1,39.19,.82,.74,.05,.05 00091,"Abbotsford, WI Urban Cluster",99999,"Not in a metro/micro area",,2863,1188,3274492,3261271,3966,1616,5376662,5363441,,,,,72.19,73.51,60.9,60.81,,,, 00118,"Aberdeen, MS Urban Cluster",99999,"Not in a metro/micro area",,4666,2050,7469348,7416616,4666,2050,7469348,7416616,,,,,100,100,100,100,,,,''' @httpretty.activate def test_ua_cbsa(): httpretty.register_uri( httpretty.GET, URL, body=RESPONSE, content_type='text/csv' ) results = ua_cbsa.__wrapped__() assert results == { '00037': [ ('10020', 'Abbeville, LA Micro Area'), ('35340', 'New Iberia, LA Micro Area'), ], '00091': [('48140', 'Wausau, WI Metro Area')] }

56.193548

205

0.711825

264

1,742

4.651515

0.568182

0.051303

0.035831

0.04886

0.290717

0.131107

0.090391

0

0.363342

0.113662

1,742

30

206

58.066667

0.431995

0

0.28

0.766361

0.513777

0

0.04

1

0.04

false

0

0.08

0

0.12

0

null

0

1

0

1

0

1

null

0

5

b6d977ad134622d3b86be2421cd8f5fd40d3ef67

237

py

Python

wazimap_ng/profile/admin/__init__.py

arghyaiitb/wazimap-ng

2a77860526d865b8fd0c22a2204f121fdb3b28a0

[ "Apache-2.0" ]

11

2019-12-31T20:27:22.000Z

2022-03-10T03:55:38.000Z

wazimap_ng/profile/admin/__init__.py

arghyaiitb/wazimap-ng

2a77860526d865b8fd0c22a2204f121fdb3b28a0

[ "Apache-2.0" ]

164

2020-02-06T15:02:22.000Z

2022-03-30T22:42:00.000Z

wazimap_ng/profile/admin/__init__.py

arghyaiitb/wazimap-ng

2a77860526d865b8fd0c22a2204f121fdb3b28a0

[ "Apache-2.0" ]

16

2020-01-03T20:30:24.000Z

2022-01-11T11:05:15.000Z

from django.contrib.gis import admin from .. import models from .admins import ( LogoAdmin, ProfileIndicatorAdmin, ProfileKeyMetricsAdmin, ProfileHighlightAdmin, IndicatorCategoryAdmin, IndicatorSubcategoryAdmin, ProfileAdmin )

29.625

84

0.822785

19

237

10.263158

0.789474

0

0.122363

237

7

85

33.857143

0.9375

0

1

0

true

0

0.5

0

0.5

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

b6fda9604a87a35038d74415767c4f9428f747a2

131

py

Python

vkwave/api/__init__.py

Stunnerr/vkwave

605bcfafa8db9d75122b5c66cf8bad5211199883

[ "MIT" ]

222

2020-03-30T18:09:20.000Z

2022-03-27T18:25:04.000Z

vkwave/api/__init__.py

Stunnerr/vkwave

605bcfafa8db9d75122b5c66cf8bad5211199883

[ "MIT" ]

62

2020-03-30T18:31:25.000Z

2021-12-21T17:00:44.000Z

vkwave/api/__init__.py

Stunnerr/vkwave

605bcfafa8db9d75122b5c66cf8bad5211199883

[ "MIT" ]

91

2020-03-30T18:34:49.000Z

2022-03-23T12:58:49.000Z

from .methods import API, APIOptionsRequestContext from .token import Token, BotSyncSingleToken from .utils.get_all import Fetcher

32.75

50

0.847328

16

131

6.875

0.6875

0

0.10687

131

3

51

43.666667

0.940171

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

8e0a03d4019a11784c1f2055311878f71bf60066

23

py

Python

lilanet/model/__init__.py

TahjidEshan/pytorch-LiLaNet

f15c104ce495c3271b92b8761adadaba18d730dd

[ "MIT" ]

17

2019-06-09T09:34:33.000Z

2021-10-31T07:37:19.000Z

lilanet/model/__init__.py

arincbulgur/pytorch-WeatherNet

8a39326ad8c2150ac5cb4dfa9b7ae2a4ef4a91e8

[ "MIT" ]

1

2021-04-19T12:56:09.000Z

2021-04-19T15:05:44.000Z

lilanet/model/__init__.py

arincbulgur/pytorch-WeatherNet

8a39326ad8c2150ac5cb4dfa9b7ae2a4ef4a91e8

[ "MIT" ]

6

2019-06-03T04:22:07.000Z

2020-12-31T13:39:06.000Z

from .lilanet import *

11.5

22

0.73913

3

23

5.666667

1

0

0.173913

23

1

23

0.894737

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

8e3a00569ac9af666de44f40abe822676e1d2b62

6,795

py

Python

tests/core/test_ElementInGFpn.py

syakoo/galois-field

e642adfa7da55f6cd95cadceb0116cdea379c181

[ "MIT" ]

8

2020-11-13T08:32:56.000Z

2022-02-14T04:22:36.000Z

tests/core/test_ElementInGFpn.py

syakoo/galois-field

e642adfa7da55f6cd95cadceb0116cdea379c181

[ "MIT" ]

3

2020-11-13T11:40:53.000Z

2020-12-16T10:27:38.000Z

tests/core/test_ElementInGFpn.py

syakoo/galois-field

e642adfa7da55f6cd95cadceb0116cdea379c181

[ "MIT" ]

1

2022-02-11T09:45:41.000Z

from typing import Union import numpy as np import pytest from galois_field.core.ElementInGFpn import ElementInGFpn from galois_field.core.types import Fp, Fpn @pytest.mark.parametrize('coeffs, p, mod_coeffs, expected_coeffs', [ (np.array([4, 3, 2, 1]), 2, np.array([1, 1, 1]), [1, 0]), (np.array([4, 3, 2, 1]), 5, np.array([1, 0, 2]), [4, 0]), (np.array([2, 1]), 11, np.array([1, 0, 1]), [2, 1]) ]) def test_ElementInGFpn_init(coeffs, p, mod_coeffs, expected_coeffs): result = ElementInGFpn(coeffs, p, mod_coeffs) assert result.coeffs == expected_coeffs @pytest.mark.parametrize('coeffs, p, mod_coeffs, expected', [ (np.array([0]), 2, np.array([1, 1, 1]), '0'), (np.array([4, 3, 2, 1]), 2, np.array([1, 1, 1]), '1x'), (np.array([4, 3, 2, 1]), 5, np.array([1, 0, 2]), '4x'), (np.array([2, 1]), 11, np.array([1, 0, 1]), '2x + 1') ]) def test_ElementInGFpn_str(coeffs, p, mod_coeffs, expected): result = ElementInGFpn(coeffs, p, mod_coeffs) assert str(result) == expected @pytest.mark.parametrize('coeffs, p, mod_coeffs, expected', [ (np.array([4, 3, 2, 1]), 2, np.array([1, 1, 1]), 'ElementInGFpn([1, 0], 2, [1, 1, 1])'), (np.array([4, 3, 2, 1]), 5, np.array([1, 0, 2]), 'ElementInGFpn([4, 0], 5, [1, 0, 2])'), (np.array([2, 1]), 11, np.array([1, 0, 1]), 'ElementInGFpn([2, 1], 11, [1, 0, 1])') ]) def test_ElementInGFpn_repr(coeffs, p, mod_coeffs, expected): result = ElementInGFpn(coeffs, p, np.poly1d(mod_coeffs)) assert repr(result) == expected @pytest.mark.parametrize('coeffs1, coeffs2, p, mod_coeffs, expected_coeffs', [ (np.array([1, 2, 3, 4]), np.array([1, 2, 3, 4]), 5, np.array([1, 0, 0, 0, 2]), [2, 4, 1, 3]), (np.array([1, 2, 3, 4]), np.array([1, 2, 3, 4]), 11, np.array([1, 0, 1]), [4, 4]), (3, np.array([1, 2, 3, 4]), 5, np.array([1, 0, 0, 0, 2]), [1, 2, 3, 2]), (np.array([1, 2, 3, 4]), 2, 11, np.array([1, 0, 1]), [2, 4]) ]) def test_GFpn_add(coeffs1: Fpn, coeffs2: Fpn, p: int, mod_coeffs: Fpn, expected_coeffs): if isinstance(coeffs1, int): el1 = coeffs1 else: el1 = ElementInGFpn(coeffs1, p, np.poly1d(mod_coeffs)) if isinstance(coeffs2, int): el2 = coeffs2 else: el2 = ElementInGFpn(coeffs2, p, np.poly1d(mod_coeffs)) result = el1 + el2 print(result) assert result.coeffs == expected_coeffs @pytest.mark.parametrize('coeffs1, coeffs2, p, mod_coeffs, expected_coeffs', [ (np.array([1, 2, 3, 4]), np.array([4, 3, 2, 1]), 5, np.array([1, 0, 0, 0, 2]), [2, 4, 1, 3]), (np.array([1, 2, 3, 4]), [4, 3, 2, 1], 11, np.array([1, 0, 1]), [4, 4]), (np.array([1, 2, 3, 4]), 3, 5, np.array([1, 0, 0, 0, 2]), [1, 2, 3, 1]), (4, [4, 3, 2, 1], 11, np.array([1, 0, 1]), [2, 6]) ]) def test_GFpn_sub(coeffs1: Fpn, coeffs2: Fpn, p: int, mod_coeffs: Fpn, expected_coeffs): if isinstance(coeffs1, int): el1 = coeffs1 else: el1 = ElementInGFpn(coeffs1, p, np.poly1d(mod_coeffs)) if isinstance(coeffs2, int): el2 = coeffs2 else: el2 = ElementInGFpn(coeffs2, p, np.poly1d(mod_coeffs)) result = el1 - el2 assert result.coeffs == expected_coeffs @pytest.mark.parametrize('coeffs1, coeffs2, p, mod_coeffs, expected_coeffs', [ (np.array([1, 2, 3, 4]), np.array([1, 2]), 5, np.array([1, 0, 0, 0, 2]), [4, 2, 0, 1]), (np.array([1, 2]), np.array([1, 2, 3, 4]), 11, np.array([1, 0, 1]), [6, 2]), (np.array([1, 2, 3, 4]), 15, 11, np.array([1, 0, 0, 1, 2]), [4, 8, 1, 5]), (15, np.array([1, 2, 3, 4]), 11, np.array([1, 0, 0, 1, 2]), [4, 8, 1, 5]), ]) def test_GFpn_mul(coeffs1: Union[Fpn, Fp], coeffs2: Union[Fpn, Fp], p: int, mod_coeffs: Fpn, expected_coeffs): if isinstance(coeffs1, Fp): el1 = coeffs1 else: el1 = ElementInGFpn(coeffs1, p, np.poly1d(mod_coeffs)) if isinstance(coeffs2, Fp): el2 = coeffs2 else: el2 = ElementInGFpn(coeffs2, p, np.poly1d(mod_coeffs)) result = el1 * el2 assert result.coeffs == expected_coeffs @pytest.mark.parametrize("coeffs1, coeffs2, p, mod_coeffs, expected_coeffs", [ (np.array([1, 1]), np.array([4]), 11, np.array([1, 0, 1]), [3, 3]), (np.array([1, 2]), np.array([1, 1]), 5, np.array([1, 0, 2]), [3, 3]), (2, np.array([1, 1]), 7, np.array([1, 0, 0, 1, 1]), [5, 2, 5, 0]), (np.array([1, 1]), 5, 7, np.array([1, 0, 0, 1, 1]), [3, 3]) ]) def test_GFpn_div(coeffs1: Union[Fpn, Fp], coeffs2: Union[Fpn, Fp], p, mod_coeffs, expected_coeffs): """poly^{-1} = expected (mod mod_poly)""" if isinstance(coeffs1, Fp): el1 = coeffs1 else: el1 = ElementInGFpn(coeffs1, p, np.poly1d(mod_coeffs)) if isinstance(coeffs2, Fp): el2 = coeffs2 else: el2 = ElementInGFpn(coeffs2, p, np.poly1d(mod_coeffs)) result = el1 / el2 assert result.coeffs == expected_coeffs @pytest.mark.parametrize("el, exp, expected_coeffs", [ (ElementInGFpn(np.array([4]), 11, np.poly1d([1, 0, 1])), 3, [9]), (ElementInGFpn(np.array([1, 1]), 5, np.poly1d([1, 0, 2])), 23, [3, 2]), (ElementInGFpn(np.array([1, 1]), 7, np.poly1d([1, 0, 0, 1, 1])), 2399, [6, 1, 6, 0]) ]) def test_GFpn_pow(el, exp, expected_coeffs): result = el ** exp assert result.coeffs == expected_coeffs @pytest.mark.parametrize("el1, el2, expected", [ (ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), True), (ElementInGFpn(np.array([1, 2]), 11, np.array([1, 0, 1])), ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), False), (ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), ElementInGFpn(np.array([1, 1]), 7, np.array([1, 0, 1])), True), (ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1, 4])), True), (ElementInGFpn(np.array([1, 1]), 11, np.array([1, 0, 1])), [1, 1], True), (ElementInGFpn(np.array([1]), 11, np.array([1, 0, 1])), 1, True), ]) def test_GFpn_equal(el1, el2, expected): result = el1 == el2 assert result == expected @pytest.mark.parametrize("el, expected_coeffs", [ (ElementInGFpn(np.array([1, 1]), 7, np.poly1d([1, 0, 0, 0, 1])), [3, 4, 3, 4]), (ElementInGFpn(np.array([4]), 11, np.poly1d([1, 0, 1])), [3]), (ElementInGFpn(np.array([1, 1]), 5, np.poly1d([1, 0, 2])), [3, 2]), (ElementInGFpn(np.array([1, 1]), 7, np.poly1d([1, 0, 0, 1, 1])), [6, 1, 6, 0]) ]) def test_GFpn_inverse(el, expected_coeffs): result = el.inverse() assert result.coeffs == expected_coeffs

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py

Python

sketch/models/MSImageCollection.py

shrredd/sketch

eebcd5077ae355f914bc77ac44d06410f9caa132

[ "MIT", "Unlicense" ]

2

2018-10-22T12:43:51.000Z

2018-12-02T02:41:55.000Z

sketch/models/MSImageCollection.py

shrredd/sketch

eebcd5077ae355f914bc77ac44d06410f9caa132

[ "MIT", "Unlicense" ]

null

sketch/models/MSImageCollection.py

shrredd/sketch

eebcd5077ae355f914bc77ac44d06410f9caa132

[ "MIT", "Unlicense" ]

null

class MSImageCollection(object): def __init__(self, images): self._images = images @property def images(self): # <list> return self._images

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py

Python

isityaml/urls.py

peterkmurphy/isityaml

bd1dfddfb4644fa4bd086bbced08e9d7002e724a

[ "BSD-3-Clause" ]

1

2016-10-12T08:40:32.000Z

isityaml/urls.py

peterkmurphy/isityaml

bd1dfddfb4644fa4bd086bbced08e9d7002e724a

[ "BSD-3-Clause" ]

null

isityaml/urls.py

peterkmurphy/isityaml

bd1dfddfb4644fa4bd086bbced08e9d7002e724a

[ "BSD-3-Clause" ]

null

# Deprecated and removed in Django 1.6: # Deprecated and removed in Django 1.6: from django.conf.urls import url, include from isityaml.views import index as viewindex urlpatterns =[ url(r'^$', viewindex)]

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wsgi

Python

application.wsgi

bsrivatsan/TexIt

fa2c64e01b316725e7c282cb62cfa6663a7ab527

[ "Apache-2.0" ]

3

2018-02-14T05:26:58.000Z

2021-01-25T18:52:12.000Z

application.wsgi

bsrivatsan/TexIt

fa2c64e01b316725e7c282cb62cfa6663a7ab527

[ "Apache-2.0" ]

null

application.wsgi

bsrivatsan/TexIt

fa2c64e01b316725e7c282cb62cfa6663a7ab527

[ "Apache-2.0" ]

null

import sys sys.path.insert(0, '/var/www/html/') from application import application as application

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5

6d2182cd2aff101ebeaa16d029c8677cc3b44b0d

101

py

Python

bitmovin/utils/__init__.py

camberbridge/bitmovin-python

3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95

[ "Unlicense" ]

44

2016-12-12T17:37:23.000Z

2021-03-03T09:48:48.000Z

bitmovin/utils/__init__.py

camberbridge/bitmovin-python

3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95

[ "Unlicense" ]

38

2017-01-09T14:45:45.000Z

2022-02-27T18:04:33.000Z

bitmovin/utils/__init__.py

camberbridge/bitmovin-python

3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95

[ "Unlicense" ]

27

2017-02-02T22:49:31.000Z

2019-11-21T07:04:57.000Z

from .serialization import BitmovinJSONEncoder, Serializable from .timeout_utils import TimeoutUtils

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6d25b19b956d3e7aaf30ea4a570b8c420fab8e45

127

py

Python

console/admin.py

unilot/pre-ico

6d4bd6648b3a1fbc169bd3e331385736d3974046

[ "MIT" ]

1

2018-08-03T03:32:32.000Z

console/admin.py

unilot/pre-ico

6d4bd6648b3a1fbc169bd3e331385736d3974046

[ "MIT" ]

8

2020-02-11T21:44:14.000Z

2022-01-13T00:33:35.000Z

console/admin.py

unilot/pre-ico

6d4bd6648b3a1fbc169bd3e331385736d3974046

[ "MIT" ]

1

2018-02-17T12:52:46.000Z

from django.contrib import admin from . import models # Register your models here. admin.site.register((models.ExchangeRate,))

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py

Python

authors/apps/articles/admin.py

andela-gad/Ah-backend-aquaman

29cf560063171c2bb8c8aed1ff36436acbc47bc9

[ "BSD-3-Clause" ]

3

2019-02-25T12:26:30.000Z

2019-10-26T20:32:00.000Z

authors/apps/articles/admin.py

andela-gad/Ah-backend-aquaman

29cf560063171c2bb8c8aed1ff36436acbc47bc9

[ "BSD-3-Clause" ]

130

2019-11-07T02:35:18.000Z

2021-07-30T02:17:11.000Z

authors/apps/articles/admin.py

CryceTruly/Ah-backend-aquaman

29cf560063171c2bb8c8aed1ff36436acbc47bc9

[ "BSD-3-Clause" ]

6

2019-06-29T12:09:37.000Z

2020-03-06T07:02:55.000Z

from .models import ReportedArticle from django.contrib import admin admin.site.register(ReportedArticle)

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246

py

Python

judge/tasks.py

gogiluv/testrepo

55e4a905b70a460e74b8116a130b720821eaf2ce

[ "MIT" ]

1

2018-01-28T07:48:13.000Z

judge/tasks.py

OnlineJudgeNextGeneration/qduoj2

c4889d70850bd91ae7f662c02524d0555b6a3ce7

[ "MIT" ]

null

judge/tasks.py

OnlineJudgeNextGeneration/qduoj2

c4889d70850bd91ae7f662c02524d0555b6a3ce7

[ "MIT" ]

1

2020-09-29T14:21:27.000Z

from __future__ import absolute_import, unicode_literals from celery import shared_task from judge.dispatcher import JudgeDispatcher @shared_task def judge_task(submission_id, problem_id): JudgeDispatcher(submission_id, problem_id).judge()

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edbe8e0e1599f44ba177e7c2eab83a6df149f948

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py

Python

dojo/unittests/tools/test_spotbugs_parser.py

steven-hadfield/django-DefectDojo

38609f7316cf6bf6cb30736f644fe2c66cc71061

[ "BSD-3-Clause" ]

1

2021-12-14T14:46:42.000Z

dojo/unittests/tools/test_spotbugs_parser.py

steven-hadfield/django-DefectDojo

38609f7316cf6bf6cb30736f644fe2c66cc71061

[ "BSD-3-Clause" ]

89

2021-05-10T04:35:07.000Z

2022-03-31T05:08:07.000Z

dojo/unittests/tools/test_spotbugs_parser.py

steven-hadfield/django-DefectDojo

38609f7316cf6bf6cb30736f644fe2c66cc71061

[ "BSD-3-Clause" ]

2

2021-09-16T18:30:17.000Z

2021-09-17T00:46:38.000Z

from django.test import TestCase from dojo.tools.spotbugs.parser import SpotbugsParser from dojo.models import Test class TestSpotbugsParser(TestCase): def test_no_findings(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/no_finding.xml", Test()) self.assertEqual(0, len(findings)) def test_parse_many_finding(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/many_findings.xml", Test()) self.assertEqual(81, len(findings)) def test_find_sast_source_line(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/many_findings.xml", Test()) test_finding = findings[0] self.assertEqual(95, test_finding.sast_source_line) def test_find_sast_source_path(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/many_findings.xml", Test()) test_finding = findings[0] self.assertEqual("securitytest/command/IdentityFunctionCommandInjection.kt", test_finding.sast_source_file_path) def test_find_source_line(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/many_findings.xml", Test()) test_finding = findings[0] self.assertEqual(95, test_finding.line) def test_find_file_path(self): parser = SpotbugsParser() findings = parser.get_findings("dojo/unittests/scans/spotbugs/many_findings.xml", Test()) test_finding = findings[0] self.assertEqual("securitytest/command/IdentityFunctionCommandInjection.kt", test_finding.file_path)

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edc28974421bd04aabd7d4e07348e037a529e629

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py

Python

corai/tests/pytorch_light/estim_history_adapter_example.py

Code-Cornelius/libraries

2ebd5f78dcedfdce1416280d7d40de7691906951

[ "MIT" ]

1

2022-01-01T22:10:04.000Z

corai/tests/pytorch_light/estim_history_adapter_example.py

Code-Cornelius/libraries

2ebd5f78dcedfdce1416280d7d40de7691906951

[ "MIT" ]

null

corai/tests/pytorch_light/estim_history_adapter_example.py

Code-Cornelius/libraries

2ebd5f78dcedfdce1416280d7d40de7691906951

[ "MIT" ]

null

from corai import Estim_history log_path = r"/Users/biancateodoracatea/PycharmProjects/python_libraries/corai/pytorch_light/out/csv_logs/default/version_0/metrics.csv" ckpt = r"/Users/biancateodoracatea/PycharmProjects/python_libraries/corai/pytorch_light/out/default_default_Logger_custom_plot/2_6_1.0/checkpoints/epoch=259-step=2339.ckpt" estimator = Estim_history.from_pl_logs(log_path=log_path, checkpoint_path=ckpt) print(estimator)

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py

Python

bouser_ws/__init__.py

MarsStirner/bouser.ws

ccecda4d58b91f0690e9789fbaec1a060df43733

[ "0BSD" ]

null

bouser_ws/__init__.py

MarsStirner/bouser.ws

ccecda4d58b91f0690e9789fbaec1a060df43733

[ "0BSD" ]

null

bouser_ws/__init__.py

MarsStirner/bouser.ws

ccecda4d58b91f0690e9789fbaec1a060df43733

[ "0BSD" ]

null

# -*- coding: utf-8 -*- from . import factory, proto, resource, service __author__ = 'viruzzz-kun' def make(config): return service.WsService(config)

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b62ef74a057ed39620fdbf5a7dc6c6e5669c73fe

55

py

Python

src/xmlutil.py

aydjay/moatools

37cb2d6fc3fa03ef86e410c501a70dd67e09cef4

[ "Apache-2.0" ]

null

src/xmlutil.py

aydjay/moatools

37cb2d6fc3fa03ef86e410c501a70dd67e09cef4

[ "Apache-2.0" ]

null

src/xmlutil.py

aydjay/moatools

37cb2d6fc3fa03ef86e410c501a70dd67e09cef4

[ "Apache-2.0" ]

null

def ParseXMLWithXPath(xmlString, xpath): return

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b66d405794ce9f1dea59588ae3a39bb74c0d99f9

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py

Python

speech_packer/__init__.py

asyaf/speech-packer

5c576ef8922f2ec1279a53cb7ebbc6e5fd51157c

[ "MIT" ]

null

speech_packer/__init__.py

asyaf/speech-packer

5c576ef8922f2ec1279a53cb7ebbc6e5fd51157c

[ "MIT" ]

null

speech_packer/__init__.py

asyaf/speech-packer

5c576ef8922f2ec1279a53cb7ebbc6e5fd51157c

[ "MIT" ]

null

from .version import __version__ from .speech_packer import Packer, SpeechAnalyzer name = "speech_packer"

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b6748f6bf46e4b67ad5a4d9edfc161033fadafca

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py

Python

python_target/FoxySheep/AST/pattern/BlankNode.py

rljacobson/FoxySheep

78451ba9f868d21f20f23ee880649f20669e7644

[ "BSD-2-Clause" ]

41

2016-02-08T12:35:11.000Z

2021-11-17T11:45:47.000Z

python_target/FoxySheep/AST/pattern/BlankNode.py

rljacobson/FoxySheep

78451ba9f868d21f20f23ee880649f20669e7644

[ "BSD-2-Clause" ]

4

2020-09-09T20:43:34.000Z

2021-01-21T22:32:26.000Z

FoxySheep/tree/pattern/BlankNode.py

rocky/FoxySheep2

94400a7e135035dadb63d703740859a69fbf9c97

[ "BSD-2-Clause" ]

4

2017-08-20T01:04:10.000Z

2021-08-07T19:51:52.000Z

from AST import ASTNode class BlankNode(ASTNode): pass

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py

Python

rankers/fact_ranker.py

rubencart/LIIR-TextGraphs-14

272849e74ef16f1499249048a0502e6e2236756d

[ "MIT" ]

1

2021-03-17T12:36:11.000Z

rankers/fact_ranker.py

rubencart/LIIR-TextGraphs-14

272849e74ef16f1499249048a0502e6e2236756d

[ "MIT" ]

null

rankers/fact_ranker.py

rubencart/LIIR-TextGraphs-14

272849e74ef16f1499249048a0502e6e2236756d

[ "MIT" ]

1

2021-03-23T02:31:09.000Z

from abc import ABC class FactRanker(ABC): def train(self, *args): raise NotImplementedError def evaluate(self, *args): raise NotImplementedError

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fcc3242c3136113fff30edf70bd228ac11f48f30

212

py

Python

test/AllPaths/conftest.py

rustam-azimov/CFPQ_PyAlgo

1f40c300a2dfeded5297ca48d0ddde26cfa8887c

[ "Apache-2.0" ]

11

2020-08-16T15:29:32.000Z

2022-01-26T12:45:39.000Z

test/AllPaths/conftest.py

rustam-azimov/CFPQ_PyAlgo

1f40c300a2dfeded5297ca48d0ddde26cfa8887c

[ "Apache-2.0" ]

4

2021-02-10T13:35:54.000Z

2021-06-04T07:14:32.000Z

test/AllPaths/conftest.py

rustam-azimov/CFPQ_PyAlgo

1f40c300a2dfeded5297ca48d0ddde26cfa8887c

[ "Apache-2.0" ]

3

2020-06-27T07:59:31.000Z

2020-07-11T14:46:08.000Z

import pytest from src.problems.AllPaths.algo.tensor.tensor import TensorSimpleAlgo, TensorDynamicAlgo @pytest.fixture(params=[TensorSimpleAlgo, TensorDynamicAlgo]) def algo(request): return request.param

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fce39eb23c89747ec92c0a98a117536343924c23

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py

Python

sparkUtils.py

VulcanoAhab/waybackeess

141c6535849c446494409020e8fc866be6fc09db

[ "MIT" ]

null

sparkUtils.py

VulcanoAhab/waybackeess

141c6535849c446494409020e8fc866be6fc09db

[ "MIT" ]

null

sparkUtils.py

VulcanoAhab/waybackeess

141c6535849c446494409020e8fc866be6fc09db

[ "MIT" ]

null

import logging from pyspark import SparkContext, SparkConf class SparkDo: """ """ _appName=None @classmethod def setAppName(cls, name): """ """ cls._appName=name @classmethod def devContext(cls): """ """ _conf = SparkConf() _conf.set("spark.executor.memory", "1g") _conf.set("spark.app.name", cls._appName) _sc = SparkContext(conf=_conf, pyFiles=[ "snapSparkProcessor.py", "sparkUtils.py" ]) #quiet context logger = logging.getLogger('py4j') logger.setLevel(logging.WARN) return _sc @classmethod def devTestContext(cls): """ """ _conf = SparkConf() _conf.set("spark.executor.memory", "1g") _conf.set("spark.app.name", cls._appName) _sc = SparkContext(conf=_conf, pyFiles=[ "../snapSparkProcessor.py", "../sparkUtils.py", ]) #quiet context logger = logging.getLogger('py4j') logger.setLevel(logging.WARN) return _sc

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fcee168a77fbe5bc8d53771338a9476f98b3aca2

5,832

py

Python

simpletransformers/metrics/eval_faq.py

getoutreach/simpletransformers

071f9f709891d6c8ba6da6af54bf4a378008e729

[ "Apache-2.0" ]

null

simpletransformers/metrics/eval_faq.py

getoutreach/simpletransformers

071f9f709891d6c8ba6da6af54bf4a378008e729

[ "Apache-2.0" ]

null

simpletransformers/metrics/eval_faq.py

getoutreach/simpletransformers

071f9f709891d6c8ba6da6af54bf4a378008e729

[ "Apache-2.0" ]

null

from simpletransformers.metrics.ranking_metrics import MAP, MRR, NDCG, Prec, Recall, F1 import numpy as np import sys def print_metrics(metrics, f=sys.stdout): print('MRR = %.4f, MAP = %.4f, NDCG = %.4f' % (metrics['MRR'], metrics['MAP'], metrics['NDCG']), file=f) print('P@5 = %.4f, R@5 = %.4f, F1@5 = %.4f' % (metrics['P@5'], metrics['R@5'], metrics['F1@5']), file=f) print('P@10 = %.4f, R@10 = %.4f, F1@10 = %.4f' % (metrics['P@10'], metrics['R@10'], metrics['F1@10']), file=f) def faq_evaluate(model, df_eval_input, mode='dev'): if 'text' in df_eval_input.columns: # This is evaluated as a 'classification' task predictions, raw_outputs = model.predict(df_eval_input['text'], mode=mode) labels = np.array(list(df_eval_input['labels'])) # predictions = np.array(predictions) elif 'text_a' in df_eval_input.columns and 'text_b' in df_eval_input.columns \ and 'addfeatures' not in df_eval_input.columns and 'url_id' not in df_eval_input.columns: # This is evaluated as a 'sentence pair' matching task predictions, raw_outputs = model.predict(list(map( list, zip(df_eval_input['text_a'], df_eval_input['text_b']))), mode=mode) df_eval = df_eval_input.copy() df_eval['predictions'] = predictions df_eval['scores'] = raw_outputs[:, 1] # Transfering the results back from pairwise binary classification to ranking labels, predictions, raw_outputs = [], [], [] for _, df in df_eval.groupby(by='reps_response_id'): # All lines should share the same "url_labels" assert all([x == df.iloc[0]['url_labels'] for x in df['url_labels']]) # "url_labels" should be recovered from individual "labels" assert set(list(df[df['labels'] == 1]['url'])) == set(df.iloc[0]['url_labels']) labels.append(list(df['labels'])) # predictions.append(list(df['predictions'])) raw_outputs.append(list(df['scores'])) # predictions = np.array(predictions) raw_outputs = np.array(raw_outputs) labels = np.array(labels) elif 'text_a' in df_eval_input.columns and 'text_b' in df_eval_input.columns \ and 'addfeatures' in df_eval_input.columns: # This is evaluated as a 'sentence pair' matching task predictions, raw_outputs = model.predict(list(map( list, zip(df_eval_input['text_a'], df_eval_input['text_b'], df_eval_input['addfeatures']))), mode=mode) df_eval = df_eval_input.copy() df_eval['predictions'] = predictions df_eval['scores'] = raw_outputs[:, 1] # Transfering the results back from pairwise binary classification to ranking labels, predictions, raw_outputs = [], [], [] for _, df in df_eval.groupby(by='reps_response_id'): # All lines should share the same "url_labels" assert all([x == df.iloc[0]['url_labels'] for x in df['url_labels']]) # "url_labels" should be recovered from individual "labels" assert set(list(df[df['labels'] == 1]['url'])) == set(df.iloc[0]['url_labels']) labels.append(list(df['labels'])) # predictions.append(list(df['predictions'])) raw_outputs.append(list(df['scores'])) # predictions = np.array(predictions) raw_outputs = np.array(raw_outputs) labels = np.array(labels) elif 'text_a' in df_eval_input.columns and 'text_b' in df_eval_input.columns \ and 'url_id' in df_eval_input.columns: # This is evaluated as a 'sentence pair' matching task predictions, raw_outputs = model.predict(list(map( list, zip(df_eval_input['text_a'], df_eval_input['text_b'], df_eval_input['url_id']))), mode=mode) df_eval = df_eval_input.copy() df_eval['predictions'] = predictions df_eval['scores'] = raw_outputs[:, 1] # Transfering the results back from pairwise binary classification to ranking labels, predictions, raw_outputs = [], [], [] for _, df in df_eval.groupby(by='reps_response_id'): # All lines should share the same "url_labels" assert all([x == df.iloc[0]['url_labels'] for x in df['url_labels']]) # "url_labels" should be recovered from individual "labels" assert set(list(df[df['labels'] == 1]['url'])) == set(df.iloc[0]['url_labels']) labels.append(list(df['labels'])) # predictions.append(list(df['predictions'])) raw_outputs.append(list(df['scores'])) # predictions = np.array(predictions) raw_outputs = np.array(raw_outputs) labels = np.array(labels) else: raise ValueError(f'FAQ evaluation mode not defined.') # Evaluation metrics pos_idx = [_.nonzero()[0].tolist() for _ in labels] rank_idx = np.flip(np.argsort(raw_outputs, axis=1), axis=1).tolist() mrrs = [MRR(x, y) for x, y in zip(pos_idx, rank_idx)] maps = [MAP(x, y) for x, y in zip(pos_idx, rank_idx)] ndcgs = [NDCG(x, y) for x, y in zip(pos_idx, rank_idx)] p_5 = [Prec(x, y, 5) for x, y in zip(pos_idx, rank_idx)] r_5 = [Recall(x, y, 5) for x, y in zip(pos_idx, rank_idx)] f1_5 = [F1(x, y, 5) for x, y in zip(pos_idx, rank_idx)] p_10 = [Prec(x, y, 10) for x, y in zip(pos_idx, rank_idx)] r_10 = [Recall(x, y, 10) for x, y in zip(pos_idx, rank_idx)] f1_10 = [F1(x, y, 10) for x, y in zip(pos_idx, rank_idx)] metrics = { 'MRR': np.mean(mrrs), 'MAP': np.mean(maps), 'NDCG': np.mean(ndcgs), 'P@5': np.mean(p_5), 'R@5': np.mean(r_5), 'F1@5': np.mean(f1_5), 'P@10': np.mean(p_10), 'R@10': np.mean(r_10), 'F1@10': np.mean(f1_10), } return metrics, raw_outputs, rank_idx

52.540541

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106

py

Python

Lib/site-packages/openpyxl/comments/__init__.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

1

2019-12-15T01:44:17.000Z

Lib/site-packages/openpyxl/comments/__init__.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

16

2020-03-24T17:30:37.000Z

2022-03-11T23:57:41.000Z

Lib/site-packages/openpyxl/comments/__init__.py

percevalm/aumyproject

b24b38005188ce9dd41ed663cf54dad5464afef3

[ "bzip2-1.0.6" ]

null

17.666667

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5

1e382aa4abfa26fa6a4f1e75e00ec559e8f09d67

757

gyp

Python

binding.gyp

dpnishant/Modsecurity-nodejs

44f37c20150f36df56a39cb9e8dff5376177578e

[ "MIT" ]

null

binding.gyp

dpnishant/Modsecurity-nodejs

44f37c20150f36df56a39cb9e8dff5376177578e

[ "MIT" ]

null

binding.gyp

dpnishant/Modsecurity-nodejs

44f37c20150f36df56a39cb9e8dff5376177578e

[ "MIT" ]

null

{ "targets": [ { "target_name": "modsecurity", "sources": [ "modsecurity_wrap.cxx" ], "include_dirs": ['usr/local/modsecurity/include/modsecurity',], "libraries": ['/usr/local/modsecurity/lib/libmodsecurity.a', '/usr/local/modsecurity/lib/libmodsecurity.dylib', '/usr/local/modsecurity/lib/libmodsecurity.la', '/usr/local/modsecurity/lib/libmodsecurity.3.dylib' '/usr/lib/libxml2.dylib', '/usr/lib/libcurl.dylib', '/usr/local/lib/libpcre.dylib', '/usr/local/lib/libyajl.dylib', '/usr/local/lib/libGeoIP.dylib', '/usr/local/lib/liblmdb.dylib'], "cflags" : [ "-std=c++11" ], 'cflags!': [ '-fno-exceptions' ], 'cflags_cc!': [ '-fno-exceptions' ] } ] }

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1e42e03b17e296fca0605634dcb6a935c369edb5

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py

Python

shopify/orders/tests/test_lineItem.py

alikhan126/python-shopify-api

656cdf1af99485b25be545e2ed527bcb653076fd

[ "Unlicense" ]

10

2016-12-29T06:53:21.000Z

2022-03-01T10:35:32.000Z

shopify/orders/tests/test_lineItem.py

alikhan126/python-shopify-api

656cdf1af99485b25be545e2ed527bcb653076fd

[ "Unlicense" ]

4

2016-12-30T15:12:47.000Z

2021-07-24T07:14:20.000Z

shopify/orders/tests/test_lineItem.py

alikhan126/python-shopify-api

656cdf1af99485b25be545e2ed527bcb653076fd

[ "Unlicense" ]

8

2016-12-29T19:13:39.000Z

2022-03-22T18:02:58.000Z

from unittest import TestCase class TestLineItem(TestCase): def test_variant_id(self): self.fail() def test_title(self): self.fail() def test_quantity(self): self.fail() def test_price(self): self.fail() def test_grams(self): self.fail() def test_sku(self): self.fail() def test_variant_title(self): self.fail() def test_vendor(self): self.fail() def test_fulfillment_service(self): self.fail() def test_product_id(self): self.fail() def test_requires_shipping(self): self.fail() def test_taxable(self): self.fail() def test_gift_card(self): self.fail() def test_name(self): self.fail() def test_variant_inventory_management(self): self.fail() def test_properties(self): self.fail() def test_product_exists(self): self.fail() def test_fulfillable_quantity(self): self.fail() def test_total_discount(self): self.fail() def test_fulfillment_status(self): self.fail() def test_tax_lines(self): self.fail() def test_origin_location(self): self.fail() def test_destination_location(self): self.fail()

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py

Python

flexlate/__init__.py

nickderobertis/flexlate

81d6dbc2d87219a2a89266d6e8fb03310a24a3a1

[ "MIT" ]

null

flexlate/__init__.py

nickderobertis/flexlate

81d6dbc2d87219a2a89266d6e8fb03310a24a3a1

[ "MIT" ]

25

2021-12-05T18:57:53.000Z

2022-03-29T13:45:47.000Z

flexlate/__init__.py

nickderobertis/flexlate

81d6dbc2d87219a2a89266d6e8fb03310a24a3a1

[ "MIT" ]

null

""" A composable, maintainable system for managing templates """ from flexlate.main import Flexlate

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1e7b5bb5d9ac2ec19f2a5b7d52cb4aff6171f74b

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py

Python

src/domain/pipeline/Pipeline.py

lorenzomartino86/anomaly-detector

46f4f059ac9f36820fb6d5b5cf823a992013ffda

[ "Apache-2.0" ]

1

2020-07-06T14:09:33.000Z

src/domain/pipeline/Pipeline.py

lorenzomartino86/anomaly-detector

46f4f059ac9f36820fb6d5b5cf823a992013ffda

[ "Apache-2.0" ]

null

src/domain/pipeline/Pipeline.py

lorenzomartino86/anomaly-detector

46f4f059ac9f36820fb6d5b5cf823a992013ffda

[ "Apache-2.0" ]

null

from abc import abstractmethod class Pipeline: @abstractmethod def detect(self, train_raw, test_raw): pass

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1ec04e5ba8b90b4f279342bedb225cc91fa9984c

158

py

Python

test.py

CN-Tower/funclib.py

7407fc4078a7eb2ac6595898ec0a3a0f1185e614

[ "MIT" ]

null

test.py

CN-Tower/funclib.py

7407fc4078a7eb2ac6595898ec0a3a0f1185e614

[ "MIT" ]

null

test.py

CN-Tower/funclib.py

7407fc4078a7eb2ac6595898ec0a3a0f1185e614

[ "MIT" ]

null

import os def test_funclib(): os.system('coverage run funclib.test.py') os.system('coverage report -m') if __name__=='__main__': test_funclib()

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0

5

94f31aadff8b7023504f9da7975f9f62965d8697

128

py

Python

vkapp/bot/models/__init__.py

ParuninPavel/lenta4_hack

6d3340201deadf5757e37ddd7cf5580b928d7bda

[ "MIT" ]

1

2017-11-23T13:33:13.000Z

vkapp/bot/models/__init__.py

ParuninPavel/lenta4_hack

6d3340201deadf5757e37ddd7cf5580b928d7bda

[ "MIT" ]

null

vkapp/bot/models/__init__.py

ParuninPavel/lenta4_hack

6d3340201deadf5757e37ddd7cf5580b928d7bda

[ "MIT" ]

null

from .users import Blogger, VKUser, Admin from .news import News, AdminReview, Publication from .balance import Income, Payment

32

48

0.804688

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128

6.058824

0.705882

0

0.132813

128

3

49

42.666667

0.927928

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true

0

1

0

1

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1

0

null

0

1

0

1

0

1

0

5

a21e1936a95e1c7587aad6dae8b0ddca052e39af

184

py

Python

src/models/modules/__init__.py

ri-heme/mnist-classifier

be5e83d6a9c3e649a6291644a7ff4b7544fb1649

[ "MIT" ]

null

src/models/modules/__init__.py

ri-heme/mnist-classifier

be5e83d6a9c3e649a6291644a7ff4b7544fb1649

[ "MIT" ]

null

src/models/modules/__init__.py

ri-heme/mnist-classifier

be5e83d6a9c3e649a6291644a7ff4b7544fb1649

[ "MIT" ]

null

__all__ = ["CNN", "Distiller", "ShallowNN"] from src.models.modules.cnn import CNN from src.models.modules.distiller import Distiller from src.models.modules.shallow import ShallowNN

30.666667

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0.793478

25

184

5.68

0.4

0.147887

0.274648

0.422535

0

0.097826

184

5

51

36.8

0.855422

0

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1

0

false

0

0.75

0

0.75

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null

0

1

0

1

0

null

0

1

0

5

bf73184d2dc7b742c1476d334333e57c234b4998

153

py

Python

secret/loss/__init__.py

LunarShen/SECRET

0f652e63ce760ece8690cbad013f0d9bdb341e84

[ "MIT" ]

null

secret/loss/__init__.py

LunarShen/SECRET

0f652e63ce760ece8690cbad013f0d9bdb341e84

[ "MIT" ]

null

secret/loss/__init__.py

LunarShen/SECRET

0f652e63ce760ece8690cbad013f0d9bdb341e84

[ "MIT" ]

null

from __future__ import absolute_import from .triplet import SoftTripletLoss, TripletLoss from .crossentropy import CrossEntropyLabelSmooth, SoftEntropy

30.6

62

0.875817

15

153

8.6

0.666667

0

0.098039

153

4

63

38.25

0.934783

0

1

0

true

0

1

0

1

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1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

bf82481b4e96ee27fc93e2801b000eacaad0c7ac

58

py

Python

LEDController/__init__.py

tharrry/LEDController

b31eea2552360df9385729408f41179d7e59e5c1

[ "MIT" ]

null

LEDController/__init__.py

tharrry/LEDController

b31eea2552360df9385729408f41179d7e59e5c1

[ "MIT" ]

null

LEDController/__init__.py

tharrry/LEDController

b31eea2552360df9385729408f41179d7e59e5c1

[ "MIT" ]

null

"""Initialize package.""" from .light import prettyLight

14.5

30

0.741379

6

58

7.166667

1

0

0.12069

58

3

31

19.333333

0.843137

0.327586

0

1

0

true

0

1

0

1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

5

44c80e50e282972dbe6bea6e813411fa81fa8a03

1,120

py

Python

python/seldon_deploy_sdk/api/__init__.py

agrski/seldon-deploy-sdk

fc6c1e0157ad83a910eac0f108180c0e78f4fa46

[ "Apache-2.0" ]

null

python/seldon_deploy_sdk/api/__init__.py

agrski/seldon-deploy-sdk

fc6c1e0157ad83a910eac0f108180c0e78f4fa46

[ "Apache-2.0" ]

null

python/seldon_deploy_sdk/api/__init__.py

agrski/seldon-deploy-sdk

fc6c1e0157ad83a910eac0f108180c0e78f4fa46

[ "Apache-2.0" ]

null

from __future__ import absolute_import # flake8: noqa # import apis into api package from seldon_deploy_sdk.api.application_logs_api import ApplicationLogsApi from seldon_deploy_sdk.api.batch_jobs_api import BatchJobsApi from seldon_deploy_sdk.api.drift_detector_api import DriftDetectorApi from seldon_deploy_sdk.api.environment_api import EnvironmentApi from seldon_deploy_sdk.api.explain_api import ExplainApi from seldon_deploy_sdk.api.git_ops_api import GitOpsApi from seldon_deploy_sdk.api.inference_services_api import InferenceServicesApi from seldon_deploy_sdk.api.kubernetes_resources_api import KubernetesResourcesApi from seldon_deploy_sdk.api.loadtest_jobs_api import LoadtestJobsApi from seldon_deploy_sdk.api.metrics_server_api import MetricsServerApi from seldon_deploy_sdk.api.model_metadata_service_api import ModelMetadataServiceApi from seldon_deploy_sdk.api.monitor_api import MonitorApi from seldon_deploy_sdk.api.outlier_detector_api import OutlierDetectorApi from seldon_deploy_sdk.api.predict_api import PredictApi from seldon_deploy_sdk.api.seldon_deployments_api import SeldonDeploymentsApi

53.333333

84

0.903571

159

1,120

5.974843

0.327044

0.157895

0.252632

0.3

0.347368

0

0.000957

0.066964

1,120

20

85

56

0.908134

0.036607

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7827d5c3c673bb2de55557e988e06279997b1d31

106

py

Python

report/admin.py

rafimuhammad01/donasi-covid-19-2

eee8fb28ce492639d900923c985bbb5e0a8ec07f

[ "Unlicense" ]

null

report/admin.py

rafimuhammad01/donasi-covid-19-2

eee8fb28ce492639d900923c985bbb5e0a8ec07f

[ "Unlicense" ]

null

report/admin.py

rafimuhammad01/donasi-covid-19-2

eee8fb28ce492639d900923c985bbb5e0a8ec07f

[ "Unlicense" ]

null

from django.contrib import admin from .models import Report #register model admin.site.register(Report)

17.666667

32

0.811321

15

106

5.733333

0.666667

0

0.122642

106

5

33

21.2

0.924731

0.132075

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

782ecbea370a8fa8f7490ed1a5b6b957439c206f

262

py

Python

deepclr/models/__init__.py

mhorn11/deepclr

6ee21963a402776851950a51709eef849ff96b5f

[ "Apache-2.0" ]

8

2020-12-01T21:22:01.000Z

2022-03-13T13:11:56.000Z

deepclr/models/__init__.py

mhorn11/deepclr

6ee21963a402776851950a51709eef849ff96b5f

[ "Apache-2.0" ]

null

deepclr/models/__init__.py

mhorn11/deepclr

6ee21963a402776851950a51709eef849ff96b5f

[ "Apache-2.0" ]

null

from .base import BaseModel, ModelInferenceHelper from .build import build_model, load_trained_model, ModelType, store_models_code __all__ = ['BaseModel', 'ModelInferenceHelper', 'build_model', 'load_trained_model', 'ModelType', 'store_models_code']

43.666667

81

0.778626

29

262

6.551724

0.482759

0.305263

0.147368

0.221053

0.526316

0

0.122137

262

5

82

52.4

0.826087

0

0.320611

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

1

0

null

0

1

0

5

787bb2dae8b10ee07379f2b8196d0d46e6b7bffa

72

py

Python

run.py

LuukJonko/climate_change_simulation

49edeb06b3129a3756b90edbe5d1a85847651a66

[ "MIT" ]

null

run.py

LuukJonko/climate_change_simulation

49edeb06b3129a3756b90edbe5d1a85847651a66

[ "MIT" ]

2

2020-10-08T10:00:05.000Z

2021-02-03T23:25:13.000Z

run.py

LuukJonko/climate_change_simulation

49edeb06b3129a3756b90edbe5d1a85847651a66

[ "MIT" ]

null

if __name__ == '__main__': from program import main main.main()

18

28

0.652778

9

72

4.333333

0.666667

0.410256

0

0.236111

72

3

29

24

0.709091

0

0.111111

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

1581ced1c8ebbc6f46e56dd94f63f8f126e5f6e4

101

py

Python

enthought/model/numeric_editor.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/model/numeric_editor.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/model/numeric_editor.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from blockcanvas.model.numeric_editor import *

25.25

46

0.851485

13

101

6.153846

0.769231

0

0.108911

101

3

47

33.666667

0.888889

0.118812

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

15a7b10807aa7d9e8cb0027cc620a8116fec4ab8

138

py

Python

pcap2har/http/__init__.py

s55-labs/pcap2har

c1b7a31aae6a5400d7d08df488981227eb5b4707

[ "BSD-2-Clause" ]

null

pcap2har/http/__init__.py

s55-labs/pcap2har

c1b7a31aae6a5400d7d08df488981227eb5b4707

[ "BSD-2-Clause" ]

null

pcap2har/http/__init__.py

s55-labs/pcap2har

c1b7a31aae6a5400d7d08df488981227eb5b4707

[ "BSD-2-Clause" ]

null

from .common import Error from .flow import Flow from .message import Message from .request import Request from .response import Response

23

30

0.818841

20

138

5.65

0.4

0

0.144928

138

5

31

27.6

0.957627

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ec62cc311d4e2d0c2cfb73fdef3296f79bc288a4

374

py

Python

raft_asyncio/abc.py

aratz-lasa/py-raft

d9de8cf1f366c977cb5c69f1c06796ef09096322

[ "MIT" ]

null

raft_asyncio/abc.py

aratz-lasa/py-raft

d9de8cf1f366c977cb5c69f1c06796ef09096322

[ "MIT" ]

null

raft_asyncio/abc.py

aratz-lasa/py-raft

d9de8cf1f366c977cb5c69f1c06796ef09096322

[ "MIT" ]

null

from abc import ABC, abstractmethod class IRaftServer(ABC): @abstractmethod async def join_cluster(self, random_server): pass @abstractmethod async def leave_cluster(self): pass @abstractmethod async def remove_cluster_member(self, id): pass @abstractmethod async def update_state(self, key, value): pass

18.7

48

0.668449

42

374

5.809524

0.52381

0.311475

0.360656

0.319672

0

0.26738

374

19

49

19.684211

0.890511

0

0.571429

0

1

0

true

0.285714

0.071429

0

0.142857

0

null

1

0

null

0

1

0

5

ecbe271cc9812157b92bbfb13f7572a0708763bf

161

py

Python

problems/function_3__multiplying_two_numbers.py

stereoabuse/codewars

d6437afaef38c3601903891b8b9cb0f84c108c54

[ "MIT" ]

null

problems/function_3__multiplying_two_numbers.py

stereoabuse/codewars

d6437afaef38c3601903891b8b9cb0f84c108c54

[ "MIT" ]

null

problems/function_3__multiplying_two_numbers.py

stereoabuse/codewars

d6437afaef38c3601903891b8b9cb0f84c108c54

[ "MIT" ]

null

## Function 3 - multiplying two numbers ## 8 kyu ## https://www.codewars.com/kata/523b66342d0c301ae400003b def multiply(x,y): return x * y

17.888889

59

0.63354

20

161

5.1

0.9

0.039216

0

0.165289

0.248447

161

9

60

17.888889

0.677686

0.614907

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5