Datasets:

semeru

/

text-code-galeras-code-generation-from-docstring-3k-deduped

like 0

def get_uri(self) -> str: conn = self.get_connection(getattr(self, self.conn_name_attr)) conn.schema = self.__schema or conn.schema return conn.get_uri()

airflow/hooks/dbapi.py

airflow

Python

59c450ee5425a2d23ef813dbf219cde14df7c85c

dbapi.py

get_uri

https://github.com/apache/airflow.git

Make DbApiHook use get_uri from Connection (#21764) DBApi has its own get_uri method which does not deal with quoting properly and neither with empty passwords. Connection also has a get_uri method that deals properly with the above issues. This also fixes issues with RFC compliancy.

def test_reading_post_data_raises_unreadable_post_error(self): req = self._get_POST_request_with_token() mw = CsrfViewMiddleware(post_form_view) mw.process_request(req) resp = mw.process_view(req, post_form_view, (), {}) self.assertIsNone(resp) req = self._get_POST_request_with_token(request_class=PostErrorRequest) req.post_error = UnreadablePostError("Error reading input data.") mw.process_request(req) with self.assertLogs("django.security.csrf", "WARNING") as cm: resp = mw.process_view(req, post_form_view, (), {}) self.assertEqual(resp.status_code, 403) self.assertEqual( cm.records[0].getMessage(), "Forbidden (%s): " % REASON_CSRF_TOKEN_MISSING, )

tests/csrf_tests/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_reading_post_data_raises_unreadable_post_error

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def broadcast_shapes(*shapes): # NOTE: We have both cached and uncached versions to handle Tracers in shapes. try: return _broadcast_shapes_cached(*shapes) except: return _broadcast_shapes_uncached(*shapes) @cache()

jax/_src/lax/lax.py

@cache()

jax

Python

78ed03c4c2970e5e0d11f14a8d4fc968a4efbca2

lax.py

broadcast_shapes

https://github.com/google/jax.git

[typing] add annotations to jax.numpy.linalg

def fit(self) -> Any: return None

freqtrade/freqai/freqai_interface.py

freqtrade

Python

fc837c4daa27a18ff0e86128f4d52089b88fa5fb

freqai_interface.py

fit

https://github.com/freqtrade/freqtrade.git

add freqao backend machinery, user interface, documentation

def sliders(self): return self["sliders"]

packages/python/plotly/plotly/graph_objs/_layout.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_layout.py

sliders

https://github.com/plotly/plotly.py.git

switch to black .22

def get_dataset_path(path, annotation, image_dir): if _dataset_exists(path, annotation, image_dir): return path data_name = os.path.split(path.strip().lower())[-1] if data_name not in DOWNLOAD_DATASETS_LIST: raise ValueError( "Dataset {} is not valid for reason above, please check again.". format(osp.realpath(path))) else: logger.WARNING( "Dataset {} is not valid for reason above, try searching {} or " "downloading dataset...".format(osp.realpath(path), DATASET_HOME)) for name, dataset in DATASETS.items(): if data_name == name: logger.debug("Parse dataset_dir {} as dataset " "{}".format(path, name)) data_dir = osp.join(DATASET_HOME, name) if name == "spine_coco": if _dataset_exists(data_dir, annotation, image_dir): return data_dir # For voc, only check dir VOCdevkit/VOC2012, VOCdevkit/VOC2007 if name in ['voc', 'fruit', 'roadsign_voc']: exists = True for sub_dir in dataset[1]: check_dir = osp.join(data_dir, sub_dir) if osp.exists(check_dir): logger.info("Found {}".format(check_dir)) else: exists = False if exists: return data_dir # voc exist is checked above, voc is not exist here check_exist = name != 'voc' and name != 'fruit' and name != 'roadsign_voc' for url, md5sum in dataset[0]: get_path(url, data_dir, md5sum, check_exist) # voc should create list after download if name == 'voc': create_voc_list(data_dir) return data_dir raise ValueError("Dataset automaticly downloading Error.")

ppdet/utils/download.py

PaddleDetection

Python

630304e0b66c0528ecaa3bf2e88b44a14b7f3383

download.py

get_dataset_path

https://github.com/PaddlePaddle/PaddleDetection.git

fix auto download logger info (#7550)

def is_package(self, fullname): raise ImportError

python3.10.4/Lib/importlib/abc.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

abc.py

is_package

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def test_connect_and_rollback(self): new_connection = connection.copy() try: # Ensure the database default time zone is different than # the time zone in new_connection.settings_dict. We can # get the default time zone by reset & show. with new_connection.cursor() as cursor: cursor.execute("RESET TIMEZONE") cursor.execute("SHOW TIMEZONE") db_default_tz = cursor.fetchone()[0] new_tz = "Europe/Paris" if db_default_tz == "UTC" else "UTC" new_connection.close() # Invalidate timezone name cache, because the setting_changed # handler cannot know about new_connection. del new_connection.timezone_name # Fetch a new connection with the new_tz as default # time zone, run a query and rollback. with self.settings(TIME_ZONE=new_tz): new_connection.set_autocommit(False) new_connection.rollback() # Now let's see if the rollback rolled back the SET TIME ZONE. with new_connection.cursor() as cursor: cursor.execute("SHOW TIMEZONE") tz = cursor.fetchone()[0] self.assertEqual(new_tz, tz) finally: new_connection.close()

tests/backends/postgresql/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_connect_and_rollback

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def _get_container_name(self) -> Optional[str]: # Must match `/?[a-zA-Z0-9][a-zA-Z0-9_.-]+` in the end if not self.name: return None return ( slugify( self.name, lowercase=False, # Docker does not limit length but URL limits apply eventually so # limit the length for safety max_length=250, # Docker allows these characters for container names regex_pattern=r"[^a-zA-Z0-9_.-]+", ).lstrip( # Docker does not allow leading underscore, dash, or period "_-." ) # Docker does not allow 0 character names so cast to null if the name is # empty after slufification or None )

src/prefect/infrastructure/docker.py

prefect

Python

2bff1047c0c183ec79e606b9a1c4ac966e23c8d1

docker.py

_get_container_name

https://github.com/PrefectHQ/prefect.git

Add tests for docker container

def ray_dask_get_sync(dsk, keys, **kwargs): ray_callbacks = kwargs.pop("ray_callbacks", None) persist = kwargs.pop("ray_persist", False) with local_ray_callbacks(ray_callbacks) as ray_callbacks: # Unpack the Ray-specific callbacks. ( ray_presubmit_cbs, ray_postsubmit_cbs, ray_pretask_cbs, ray_posttask_cbs, ray_postsubmit_all_cbs, ray_finish_cbs, ) = unpack_ray_callbacks(ray_callbacks) # NOTE: We hijack Dask's `get_async` function, injecting a different # task executor. object_refs = get_async( _apply_async_wrapper( apply_sync, _rayify_task_wrapper, ray_presubmit_cbs, ray_postsubmit_cbs, ray_pretask_cbs, ray_posttask_cbs, ), 1, dsk, keys, **kwargs, ) if ray_postsubmit_all_cbs is not None: for cb in ray_postsubmit_all_cbs: cb(object_refs, dsk) # NOTE: We explicitly delete the Dask graph here so object references # are garbage-collected before this function returns, i.e. before all # Ray tasks are done. Otherwise, no intermediate objects will be # cleaned up until all Ray tasks are done. del dsk if persist: result = object_refs else: result = ray_get_unpack(object_refs) if ray_finish_cbs is not None: for cb in ray_finish_cbs: cb(result) return result @dataclass

python/ray/util/dask/scheduler.py

@dataclass

ray

Python

905258dbc19753c81039f993477e7ab027960729

scheduler.py

ray_dask_get_sync

https://github.com/ray-project/ray.git

Clean up docstyle in python modules and add LINT rule (#25272)

async def async_refresh_providers(self) -> None: old_state = self._rtsp_to_webrtc self._rtsp_to_webrtc = await self._async_use_rtsp_to_webrtc() if old_state != self._rtsp_to_webrtc: self.async_write_ha_state()

homeassistant/components/camera/__init__.py

core

Python

81aff973ea421e848d2f3e084f123bf108bd808e

__init__.py

async_refresh_providers

https://github.com/home-assistant/core.git

Keep entity state management within entity (#63183) Simplify the entity state management for webrtc providers, incurring extra state writes on startup. Followup post-review comments for PR #62962

def test_runtime_install_error_message(call_ray_start): with pytest.raises(ConnectionAbortedError) as excinfo: ray.client("localhost:25031").env({"pip": ["ray-this-doesnt-exist"]}).connect() assert "No matching distribution found for ray-this-doesnt-exist" in str( excinfo.value ), str(excinfo.value) ray.util.disconnect()

python/ray/tests/test_client_proxy.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

test_client_proxy.py

test_runtime_install_error_message

https://github.com/ray-project/ray.git

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

def add_handler(self, handler): sympy_deprecation_warning( , deprecated_since_version="1.8", active_deprecations_target='deprecated-askhandler', ) self.handlers.append(handler)

sympy/assumptions/assume.py

sympy

Python

ad766d1c02943e86f50559abfd0c72e582c9ca6a

assume.py

add_handler

https://github.com/sympy/sympy.git

Update the AskHandler deprecation warnings n.b., the issue number in the original warning message was wrong. It should have been #20837.

def deserialize(config, custom_objects=None): # loss_scale_optimizer has a direct dependency of optimizer, import here # rather than top to avoid the cyclic dependency. from keras.mixed_precision import loss_scale_optimizer # pylint: disable=g-import-not-at-top all_classes = { 'adadelta': adadelta_v2.Adadelta, 'adagrad': adagrad_v2.Adagrad, 'adam': adam_v2.Adam, 'adamax': adamax_v2.Adamax, 'experimentaladadelta': adadelta_experimental.Adadelta, 'experimentaladagrad': adagrad_experimental.Adagrad, 'experimentaladam': adam_experimental.Adam, 'experimentalsgd': sgd_experimental.SGD, 'nadam': nadam_v2.Nadam, 'rmsprop': rmsprop_v2.RMSprop, 'sgd': gradient_descent_v2.SGD, 'ftrl': ftrl.Ftrl, 'lossscaleoptimizer': loss_scale_optimizer.LossScaleOptimizer, 'lossscaleoptimizerv3': loss_scale_optimizer.LossScaleOptimizerV3, # LossScaleOptimizerV1 was an old version of LSO that was removed. # Deserializing it turns it into a LossScaleOptimizer 'lossscaleoptimizerv1': loss_scale_optimizer.LossScaleOptimizer, } # Make deserialization case-insensitive for built-in optimizers. if config['class_name'].lower() in all_classes: config['class_name'] = config['class_name'].lower() return deserialize_keras_object( config, module_objects=all_classes, custom_objects=custom_objects, printable_module_name='optimizer') @keras_export('keras.optimizers.get')

keras/optimizers/__init__.py

@keras_export('keras.optimizers.get')

keras

Python

8ecef127f70db723c158dbe9ed3268b3d610ab55

__init__.py

deserialize

https://github.com/keras-team/keras.git

Remove experimental Keras mixed precision API. The non-experimental mixed precision API was added in TensorFlow 2.4, and since then the experimental API has been deprecated. This change removes the experimental API. Deserializing the now-removed PolicyV1 and LossScaleOptimizerV1 classes is still supported, if they were serialized with get_config() prior to this change. These classes are deserialized into the non-experimental Policy and LossScaleOptimizer classes, which has been the case since TensorFlow 2.4. Eventually, support for deserializing these classes may be removed. PiperOrigin-RevId: 429410341

def construct_edit_url(self, instance): if self.edit_url_name is None: raise ImproperlyConfigured( "%r must define edit_url_name or override construct_edit_url" % type(self) ) return reverse(self.edit_url_name, args=(quote(instance.pk),))

wagtail/admin/admin_url_finder.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

admin_url_finder.py

construct_edit_url

https://github.com/wagtail/wagtail.git

Reformat with black

def test_pagination_offset_without_orderby(self): response = self.get_response( self.organization.slug, field="count(sentry.transactions.measurements.lcp)", datasource="snuba", groupBy="transaction", cursor=Cursor(0, 1), ) assert response.status_code == 400 print(response.json()) assert response.json()["detail"] == ( "'cursor' is only supported in combination with 'orderBy'" )

tests/sentry/api/endpoints/test_organization_metrics.py

sentry

Python

6b29955072b4fbed6d8843ae193d65509e288f8f

test_organization_metrics.py

test_pagination_offset_without_orderby

https://github.com/getsentry/sentry.git

feat(metrics): Add pagination to OrganizationMetricsDataEndpoint [INGEST-851] (#31181) * feat(metrics): Add pagination to OrganizationMetricsDataEndpoint Adds new paginator class `MetricsDataSeriesPaginator` to add pagination to the response of api requests made to `OrganizationMetricsDataEndpoint`

def test_copy_page_nested_plugin(self): with self.settings(CMS_PERMISSION=False): # setup page 1 page_one = create_page( "Three Placeholder", "col_three.html", "en", position="last-child", published=True, in_navigation=True ) page_one_ph_one = page_one.placeholders.get(slot="col_sidebar") page_one_ph_two = page_one.placeholders.get(slot="col_left") page_one.placeholders.get(slot="col_right") # add the text plugin to placeholder one text_plugin_en = add_plugin(page_one_ph_one, "TextPlugin", "en", body="Hello World") self.assertEqual(text_plugin_en.id, CMSPlugin.objects.all()[0].id) self.assertEqual(text_plugin_en.get_children().count(), 0) pre_add_plugin_count = CMSPlugin.objects.count() self.assertEqual(pre_add_plugin_count, 1) ### # add a plugin to placeholder two ### pre_nesting_body = "<p>the nested text plugin with a link inside</p>" text_plugin_two = add_plugin(page_one_ph_two, "TextPlugin", "en", body=pre_nesting_body) text_plugin_two = self.reload(text_plugin_two) # prepare nesting plugin page_one_ph_two = self.reload(page_one_ph_two) text_plugin_two = self.reload(text_plugin_two) link_plugin = add_plugin(page_one_ph_two, "LinkPlugin", "en", target=text_plugin_two) link_plugin.name = "django-cms Link" link_plugin.external_link = "https://www.django-cms.org" link_plugin.parent = text_plugin_two link_plugin.save() link_plugin = self.reload(link_plugin) text_plugin_two = self.reload(text_plugin_two) in_txt = nesting_body = f"{text_plugin_two.body}<p>{(in_txt % (link_plugin.id))}</p>" # emulate the editor in admin that adds some txt for the nested plugin text_plugin_two.body = nesting_body text_plugin_two.save() text_plugin_two = self.reload(text_plugin_two) # the link is attached as a child? self.assertEqual(text_plugin_two.get_children().count(), 1) post_add_plugin_count = CMSPlugin.objects.filter(placeholder__page__publisher_is_draft=True).count() self.assertEqual(post_add_plugin_count, 3) page_one.save() # get the plugins from the original page page_one = self.reload(page_one) page_one_ph_one = page_one.placeholders.get(slot="col_sidebar") page_one_ph_two = page_one.placeholders.get(slot="col_left") page_one_ph_three = page_one.placeholders.get(slot="col_right") # verify that the plugins got created org_placeholder_one_plugins = page_one_ph_one.get_plugins() self.assertEqual(len(org_placeholder_one_plugins), 1) org_placeholder_two_plugins = page_one_ph_two.get_plugins() self.assertEqual(len(org_placeholder_two_plugins), 2) org_placeholder_three_plugins = page_one_ph_three.get_plugins() self.assertEqual(len(org_placeholder_three_plugins), 0) self.assertEqual(page_one.placeholders.count(), 3) placeholder_count = Placeholder.objects.filter(page__publisher_is_draft=True).count() self.assertEqual(placeholder_count, 3) self.assertEqual(CMSPlugin.objects.filter(placeholder__page__publisher_is_draft=True).count(), 3) ## # setup page_copy_target page ## page_copy_target = create_page( "Three Placeholder - page copy target", "col_three.html", "en", position="last-child", published=True, in_navigation=True ) all_page_count = Page.objects.drafts().count() pre_copy_placeholder_count = Placeholder.objects.filter(page__publisher_is_draft=True).count() self.assertEqual(pre_copy_placeholder_count, 6) # copy the page superuser = self.get_superuser() with self.login_user_context(superuser): page_two = self.copy_page(page_one, page_copy_target) # validate the expected pages,placeholders,plugins,pluginbodies after_copy_page_plugin_count = CMSPlugin.objects.filter( placeholder__page__publisher_is_draft=True ).count() self.assertEqual(after_copy_page_plugin_count, 6) # check the amount of copied stuff after_copy_page_count = Page.objects.drafts().count() after_copy_placeholder_count = Placeholder.objects.filter( page__publisher_is_draft=True ).count() self.assertGreater(after_copy_page_count, all_page_count, "no new page after copy") self.assertGreater(after_copy_page_plugin_count, post_add_plugin_count, "plugin count is not grown") self.assertGreater( after_copy_placeholder_count, pre_copy_placeholder_count, "placeholder count is not grown" ) self.assertEqual(after_copy_page_count, 3, "no new page after copy") # original placeholder page_one = self.reload(page_one) page_one_ph_one = page_one.placeholders.get(slot="col_sidebar") page_one_ph_two = page_one.placeholders.get(slot="col_left") page_one_ph_three = page_one.placeholders.get(slot="col_right") # check if there are multiple pages assigned to this placeholders found_page = page_one_ph_one.page if page_one_ph_one else None self.assertEqual(found_page, page_one) found_page = page_one_ph_two.page if page_one_ph_two else None self.assertEqual(found_page, page_one) found_page = page_one_ph_three.page if page_one_ph_three else None self.assertEqual(found_page, page_one) page_two = self.reload(page_two) page_two_ph_one = page_two.placeholders.get(slot="col_sidebar") page_two_ph_two = page_two.placeholders.get(slot="col_left") page_two_ph_three = page_two.placeholders.get(slot="col_right") # check if there are multiple pages assigned to this placeholders found_page = page_two_ph_one.page if page_two_ph_one else None self.assertEqual(found_page, page_two) found_page = page_two_ph_two.page if page_two_ph_two else None self.assertEqual(found_page, page_two) found_page = page_two_ph_three.page if page_two_ph_three else None self.assertEqual(found_page, page_two) # check the stored placeholders org vs copy msg = 'placehoder ids copy:{} org:{} copied page {} are identical - tree broken'.format( page_two_ph_one.pk, page_one_ph_one.pk, page_two.pk ) self.assertNotEqual(page_two_ph_one.pk, page_one_ph_one.pk, msg) msg = 'placehoder ids copy:{} org:{} copied page {} are identical - tree broken'.format( page_two_ph_two.pk, page_one_ph_two.pk, page_two.pk ) self.assertNotEqual(page_two_ph_two.pk, page_one_ph_two.pk, msg) msg = 'placehoder ids copy:{} org:{} copied page {} are identical - tree broken'.format( page_two_ph_three.pk, page_one_ph_three.pk, page_two.pk ) self.assertNotEqual(page_two_ph_three.pk, page_one_ph_three.pk, msg) # get the plugins from the original page org_placeholder_one_plugins = page_one_ph_one.get_plugins() self.assertEqual(len(org_placeholder_one_plugins), 1) org_placeholder_two_plugins = page_one_ph_two.get_plugins() self.assertEqual(len(org_placeholder_two_plugins), 2) org_placeholder_three_plugins = page_one_ph_three.get_plugins() self.assertEqual(len(org_placeholder_three_plugins), 0) # get the plugins from the copied page copied_placeholder_one_plugins = page_two_ph_one.get_plugins() self.assertEqual(len(copied_placeholder_one_plugins), 1) copied_placeholder_two_plugins = page_two_ph_two.get_plugins() self.assertEqual(len(copied_placeholder_two_plugins), 2) copied_placeholder_three_plugins = page_two_ph_three.get_plugins() self.assertEqual(len(copied_placeholder_three_plugins), 0) # verify the plugins got copied # placeholder 1 count_plugins_copied = len(copied_placeholder_one_plugins) count_plugins_org = len(org_placeholder_one_plugins) msg = f"plugin count {count_plugins_copied} {count_plugins_org} for placeholder one not equal" self.assertEqual(count_plugins_copied, count_plugins_org, msg) # placeholder 2 count_plugins_copied = len(copied_placeholder_two_plugins) count_plugins_org = len(org_placeholder_two_plugins) msg = f"plugin count {count_plugins_copied} {count_plugins_org} for placeholder two not equal" self.assertEqual(count_plugins_copied, count_plugins_org, msg) # placeholder 3 count_plugins_copied = len(copied_placeholder_three_plugins) count_plugins_org = len(org_placeholder_three_plugins) msg = f"plugin count {count_plugins_copied} {count_plugins_org} for placeholder three not equal" self.assertEqual(count_plugins_copied, count_plugins_org, msg) # verify the body of text plugin with nested link plugin # org to copied org_nested_text_plugin = None # do this iteration to find the real text plugin with the attached link # the inheritance mechanism for the cmsplugins works through # (tuple)get_plugin_instance() for x in org_placeholder_two_plugins: if x.plugin_type == "TextPlugin": instance = x.get_plugin_instance()[0] if instance.body.startswith(pre_nesting_body): org_nested_text_plugin = instance break copied_nested_text_plugin = None for x in copied_placeholder_two_plugins: if x.plugin_type == "TextPlugin": instance = x.get_plugin_instance()[0] if instance.body.startswith(pre_nesting_body): copied_nested_text_plugin = instance break msg = "original nested text plugin not found" self.assertNotEqual(org_nested_text_plugin, None, msg=msg) msg = "copied nested text plugin not found" self.assertNotEqual(copied_nested_text_plugin, None, msg=msg) # get the children ids of the texplugin with a nested link # to check if the body of the text is generated correctly org_link_child_plugin = org_nested_text_plugin.get_children()[0] copied_link_child_plugin = copied_nested_text_plugin.get_children()[0] # validate the textplugin body texts msg = "org plugin and copied plugin are the same" self.assertTrue(org_link_child_plugin.id != copied_link_child_plugin.id, msg) needle = "%s" msg = "child plugin id differs to parent in body" # linked child is in body self.assertTrue(org_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) != -1, msg) msg = "copy: child plugin id differs to parent in body" self.assertTrue(copied_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) != -1, msg) # really nothing else msg = "child link plugin id differs to parent body" self.assertTrue(org_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) == -1, msg) msg = "copy: child link plugin id differs to parent body" self.assertTrue(copied_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) == -1, msg) # now reverse lookup the placeholders from the plugins org_placeholder = org_link_child_plugin.placeholder copied_placeholder = copied_link_child_plugin.placeholder msg = "placeholder of the original plugin and copied plugin are the same" ok = (org_placeholder.id != copied_placeholder.id) self.assertTrue(ok, msg)

cms/tests/test_nested_plugins.py

django-cms

Python

c1290c9ff89cb00caa5469129fd527e9d82cd820

test_nested_plugins.py

test_copy_page_nested_plugin

https://github.com/django-cms/django-cms.git

ci: Added codespell (#7355) Co-authored-by: Christian Clauss <[email protected]> * ci: codespell config taken from #7292

def tick_bottom(self): label = True if 'label1On' in self._major_tick_kw: label = (self._major_tick_kw['label1On'] or self._major_tick_kw['label2On']) self.set_ticks_position('bottom') # If labels were turned off before this was called, leave them off. self.set_tick_params(which='both', labelbottom=label)

lib/matplotlib/axis.py

matplotlib

Python

f156db08eee54d285ab0fb4e031e48d078ba6aa3

axis.py

tick_bottom

https://github.com/matplotlib/matplotlib.git

DOC: More cleanup axes -> Axes

def test_sample_weights_validation(): # scalar value but not positive X = [[1]] y = [1] weights = 0 glm = _GeneralizedLinearRegressor() # Positive weights are accepted glm.fit(X, y, sample_weight=1) # 2d array weights = [[0]] with pytest.raises(ValueError, match="must be 1D array or scalar"): glm.fit(X, y, weights) # 1d but wrong length weights = [1, 0] msg = r"sample_weight.shape == \(2,\), expected \(1,\)!" with pytest.raises(ValueError, match=msg): glm.fit(X, y, weights) @pytest.mark.parametrize("fit_intercept", ["not bool", 1, 0, [True]])

sklearn/linear_model/_glm/tests/test_glm.py

@pytest.mark.parametrize("fit_intercept", ["not bool", 1, 0, [True]])

scikit-learn

Python

75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc

test_glm.py

test_sample_weights_validation

https://github.com/scikit-learn/scikit-learn.git

ENH migrate GLMs / TweedieRegressor to linear loss (#22548) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]>

def getoffset(self, text): deprecate("getoffset", 10, "getbbox") return self.font.getsize(text)[1]

src/PIL/ImageFont.py

Pillow

Python

406fe59242ad288bcd9f9fe663b227620eacd344

ImageFont.py

getoffset

https://github.com/python-pillow/Pillow.git

deprecate font.getsize and related functions

def build_index(cls, path, partition_ids, index_columns, storage_options): from pyarrow.parquet import read_table range_index = True column_names_to_read = [] for column in index_columns: # According to https://arrow.apache.org/docs/python/generated/pyarrow.Schema.html, # only RangeIndex will be stored as metadata. Otherwise, the default behavior is # to store the index as a column. if isinstance(column, str): column_names_to_read.append(column) range_index = False elif column["name"] is not None: column_names_to_read.append(column["name"]) # For the second check, let us consider the case where we have an empty dataframe, # that has a valid index. if range_index or (len(partition_ids) == 0 and len(column_names_to_read) != 0): fs, fs_path = cls._get_fs_and_fs_path(path, storage_options) complete_index = ( read_table(fs_path, columns=column_names_to_read, filesystem=fs) .to_pandas() .index ) # Empty DataFrame case elif len(partition_ids) == 0: return [], False else: index_ids = [part_id[0][1] for part_id in partition_ids if len(part_id) > 0] index_objs = cls.materialize(index_ids) complete_index = index_objs[0].append(index_objs[1:]) return complete_index, range_index or (len(index_columns) == 0)

modin/core/io/column_stores/parquet_dispatcher.py

modin

Python

4548012a6372b8ce79d7e07c9ae13fd7444a91c8

parquet_dispatcher.py

build_index

https://github.com/modin-project/modin.git

FIX-#4756: Correctly propagate `storage_options` in `read_parquet` (#4764) Co-authored-by: Yaroslav Igoshev <[email protected]> Co-authored-by: Alexey Prutskov <[email protected]> Signed-off-by: Karthik Velayutham <[email protected]>

def test_grabclipboard(self): if sys.platform == "darwin": subprocess.call(["screencapture", "-cx"]) elif sys.platform == "win32": p = subprocess.Popen(["powershell", "-command", "-"], stdin=subprocess.PIPE) p.stdin.write( b ) p.communicate() else: if not shutil.which("wl-paste"): with pytest.raises(NotImplementedError) as e: ImageGrab.grabclipboard() assert ( str(e.value) == "wl-paste is required for ImageGrab.grabclipboard() on Linux" ) return ImageGrab.grabclipboard()

Tests/test_imagegrab.py

Pillow

Python

ccac8540771120bdeb570ec5b7bbfc4e3e9a38dd

test_imagegrab.py

test_grabclipboard

https://github.com/python-pillow/Pillow.git

If available, use wl-paste for grabclipboard() on Linux

def test_symlink_exists_different_force(file, source): dif_source = source.parent / "dif_source.txt" target = source.parent / "symlink.lnk" target.symlink_to(dif_source) try: file.symlink(source, target, force=True) assert salt.utils.path.readlink(target) == str(source) finally: target.unlink()

tests/pytests/functional/modules/file/test_symlink.py

salt

Python

a35b29b2651bf33c5d5b45e64bc7765ffde4aff4

test_symlink.py

test_symlink_exists_different_force

https://github.com/saltstack/salt.git

Add some funtional tests Add functional tests for the following: - file.readlink - file.replace - file.symlink Remove unit tests for file.replace as they are duplicated in the added functional test

def _reset_logging_mixin(): global __logging_mixin __logging_mixin = LoggingMixin(logger)

freqtrade/exchange/common.py

freqtrade

Python

682daa4e941abf2235e60d9ecd1ad029eec5d3c4

common.py

_reset_logging_mixin

https://github.com/freqtrade/freqtrade.git

Reset logging mixin to avoid random test failure

def partial_fit(self, X, y): if not hasattr(self, "coefs_"): self._validate_params() return self._fit(X, y, incremental=True)

sklearn/neural_network/_multilayer_perceptron.py

scikit-learn

Python

0206d3e08c0f0917ba2f1c65cb55569b97d9a9ba

_multilayer_perceptron.py

partial_fit

https://github.com/scikit-learn/scikit-learn.git

MAINT validate parameters for MLPRregressor and MLPClassifier (#23789) Co-authored-by: jeremie du boisberranger <[email protected]>

def unk_token(self) -> str: if self._unk_token is None: if self.verbose: logger.error("Using unk_token, but it is not set yet.") return None return str(self._unk_token)

src/transformers/tokenization_utils_base.py

transformers

Python

3eed5530ec74bb60ad9f8f612717d0f6ccf820f2

tokenization_utils_base.py

unk_token

https://github.com/huggingface/transformers.git

Fix properties of unset special tokens in non verbose mode (#17797) Co-authored-by: SaulLu <[email protected]>

def sizemin(self): return self["sizemin"]

packages/python/plotly/plotly/graph_objs/pointcloud/_marker.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_marker.py

sizemin

https://github.com/plotly/plotly.py.git

switch to black .22

def show_file(self, path=None, **options): if path is None: if "file" in options: warnings.warn( "The 'file' argument is deprecated and will be removed in Pillow " "10 (2023-07-01). Use 'path' instead.", DeprecationWarning, ) path = options.pop("file") else: raise TypeError("Missing required argument: 'path'") subprocess.call(["open", "-a", "Preview.app", path]) subprocess.Popen( [ sys.executable, "-c", "import os, sys, time;time.sleep(20);os.remove(sys.argv[1])", path, ] ) return 1 if sys.platform == "darwin": register(MacViewer)

src/PIL/ImageShow.py

Pillow

Python

8da80130dbc747f3954b4904247d26289fe722f9

ImageShow.py

show_file

https://github.com/python-pillow/Pillow.git

In show_file, use os.remove to remove temporary images

def confirm(self): args = request.args dag_id = args.get('dag_id') task_id = args.get('task_id') dag_run_id = args.get('dag_run_id') state = args.get('state') origin = args.get('origin') if 'map_index' not in args: map_indexes: Optional[List[int]] = None else: map_indexes = args.getlist('map_index', type=int) upstream = to_boolean(args.get('upstream')) downstream = to_boolean(args.get('downstream')) future = to_boolean(args.get('future')) past = to_boolean(args.get('past')) origin = origin or url_for('Airflow.index') dag = get_airflow_app().dag_bag.get_dag(dag_id) if not dag: msg = f'DAG {dag_id} not found' return redirect_or_json(origin, msg, status='error', status_code=404) try: task = dag.get_task(task_id) except airflow.exceptions.TaskNotFound: msg = f"Task {task_id} not found" return redirect_or_json(origin, msg, status='error', status_code=404) task.dag = dag if state not in ( 'success', 'failed', ): msg = f"Invalid state {state}, must be either 'success' or 'failed'" return redirect_or_json(origin, msg, status='error', status_code=400) latest_execution_date = dag.get_latest_execution_date() if not latest_execution_date: msg = f"Cannot mark tasks as {state}, seem that dag {dag_id} has never run" return redirect_or_json(origin, msg, status='error', status_code=400) if map_indexes is None: tasks: Union[List[Operator], List[Tuple[Operator, int]]] = [task] else: tasks = [(task, map_index) for map_index in map_indexes] to_be_altered = set_state( tasks=tasks, run_id=dag_run_id, upstream=upstream, downstream=downstream, future=future, past=past, state=state, commit=False, ) if request.headers.get('Accept') == 'application/json': details = [str(t) for t in to_be_altered] return htmlsafe_json_dumps(details, separators=(',', ':')) details = "\n".join(str(t) for t in to_be_altered) response = self.render_template( "airflow/confirm.html", endpoint=url_for(f'Airflow.{state}'), message=f"Task instances you are about to mark as {state}:", details=details, ) return response

airflow/www/views.py

airflow

Python

e2f19505bf3622935480e80bee55bf5b6d80097b

views.py

confirm

https://github.com/apache/airflow.git

Upgrade FAB to 4.1.1 (#24399) * Upgrade FAB to 4.1.1 The Flask Application Builder have been updated recently to support a number of newer dependencies. This PR is the attempt to migrate FAB to newer version. This includes: * update setup.py and setup.cfg upper and lower bounds to account for proper version of dependencies that FAB < 4.0.0 was blocking from upgrade * added typed Flask application retrieval with a custom application fields available for MyPy typing checks. * fix typing to account for typing hints added in multiple upgraded libraries optional values and content of request returned as Mapping * switch to PyJWT 2.* by using non-deprecated "required" claim as list rather than separate fields * add possibiliyt to install providers without constraints so that we could avoid errors on conflicting constraints when upgrade-to-newer-dependencies is used * add pre-commit to check that 2.4+ only get_airflow_app is not used in providers * avoid Bad Request in case the request sent to Flask 2.0 is not JSon content type * switch imports of internal classes to direct packages where classes are available rather than from "airflow.models" to satisfy MyPY * synchronize changes of FAB Security Manager 4.1.1 with our copy of the Security Manager. * add error handling for a few "None" cases detected by MyPY * corrected test cases that were broken by immutability of Flask 2 objects and better escaping done by Flask 2 * updated test cases to account for redirection to "path" rather than full URL by Flask2 Fixes: #22397 * fixup! Upgrade FAB to 4.1.1

def collection_name(self) -> t.Optional[str]: return self.config.collection_name

test/lib/ansible_test/_util/controller/sanity/pylint/plugins/deprecated.py

ansible

Python

89862fda3b4a427894061d90e2a96ad6efaf251c

deprecated.py

collection_name

https://github.com/ansible/ansible.git

ansible-test - Sanity test code cleanup. (#78497)

def inference_timer(self, do='start'): if do == 'start': self.pair_it += 1 self.begin_time = time.time() elif do == 'stop': end = time.time() self.inference_time += (end - self.begin_time) if self.pair_it == self.total_pairs: logger.info( f'Total time spent inferencing pairlist {self.inference_time:.2f} seconds') if self.inference_time > 0.25 * self.base_tf_seconds: logger.warning('Inference took over 25/% of the candle time. Reduce pairlist to' ' avoid blinding open trades and degrading performance.') self.pair_it = 0 self.inference_time = 0 return # Following methods which are overridden by user made prediction models. # See freqai/prediction_models/CatboostPredictionModel.py for an example.

freqtrade/freqai/freqai_interface.py

freqtrade

Python

8961b8d56042545b566d2ef5fea1cb34e2ebdb35

freqai_interface.py

inference_timer

https://github.com/freqtrade/freqtrade.git

merge in inference timer and historic predictions handling improvements.

def fromkeys(cls, iterable, value="", mutable=False, encoding=None): q = cls("", mutable=True, encoding=encoding) for key in iterable: q.appendlist(key, value) if not mutable: q._mutable = False return q

django/http/request.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

request.py

fromkeys

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def get_rootwise_opening_balances(filters, report_type): additional_conditions = "" if not filters.show_unclosed_fy_pl_balances: additional_conditions = ( " and posting_date >= %(year_start_date)s" if report_type == "Profit and Loss" else "" ) if not flt(filters.with_period_closing_entry): additional_conditions += " and ifnull(voucher_type, '')!='Period Closing Voucher'" if filters.cost_center: lft, rgt = frappe.db.get_value("Cost Center", filters.cost_center, ["lft", "rgt"]) additional_conditions += % ( lft, rgt, ) if filters.project: additional_conditions += " and project = %(project)s" if filters.finance_book: fb_conditions = " AND finance_book = %(finance_book)s" if filters.include_default_book_entries: fb_conditions = ( " AND (finance_book in (%(finance_book)s, %(company_fb)s, '') OR finance_book IS NULL)" ) additional_conditions += fb_conditions accounting_dimensions = get_accounting_dimensions(as_list=False) query_filters = { "company": filters.company, "from_date": filters.from_date, "report_type": report_type, "year_start_date": filters.year_start_date, "project": filters.project, "finance_book": filters.finance_book, "company_fb": frappe.db.get_value("Company", filters.company, "default_finance_book"), } if accounting_dimensions: for dimension in accounting_dimensions: if filters.get(dimension.fieldname): if frappe.get_cached_value("DocType", dimension.document_type, "is_tree"): filters[dimension.fieldname] = get_dimension_with_children( dimension.document_type, filters.get(dimension.fieldname) ) additional_conditions += "and {0} in %({0})s".format(dimension.fieldname) else: additional_conditions += "and {0} in (%({0})s)".format(dimension.fieldname) query_filters.update({dimension.fieldname: filters.get(dimension.fieldname)}) gle = frappe.db.sql( .format( additional_conditions=additional_conditions ), query_filters, as_dict=True, ) opening = frappe._dict() for d in gle: opening.setdefault(d.account, d) return opening

erpnext/accounts/report/trial_balance/trial_balance.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

trial_balance.py

get_rootwise_opening_balances

https://github.com/frappe/erpnext.git

style: format code with black

def addIncludedDataFilesFromFileOptions(): for included_datafile in _addIncludedDataFilesFromFileOptions(): addIncludedDataFile(included_datafile)

nuitka/freezer/IncludedDataFiles.py

Nuitka

Python

abfb99b0a05dd76d2ecc6ebc20732a271857c6c8

IncludedDataFiles.py

addIncludedDataFilesFromFileOptions

https://github.com/Nuitka/Nuitka.git

Plugins: Massive cleanup of data file handling * Move data file handling out of standalone only, allowing support for other modes as well. * Attach logger and tags to data file objects.

def _check_and_raise_error(self) -> bool: for plugin in self._active_plugins: if plugin.check_and_raise_error(): return True return False

plugins/extract/pipeline.py

faceswap

Python

13cfb3f39e72e9ca181f173b7b3db2a048db0d08

pipeline.py

_check_and_raise_error

https://github.com/deepfakes/faceswap.git

extract: Add batch processing mode

def async_remove(self) -> None: @callback

homeassistant/data_entry_flow.py

@callback

core

Python

2224d0f43a048052cfc4572df95c7afcccdf3a57

data_entry_flow.py

async_remove

https://github.com/home-assistant/core.git

Add a callback for data flow handler removal (#77394) * Add a callback for when data flows are removed * Call `async_remove` at the very end * Handle and log exceptions caught during flow removal * Log the error as an exception, with a traceback * Adjust test's expected logging output to match updated format specifier

def test_is_unique_interval(self, closed): # unique overlapping - distinct endpoints idx = IntervalIndex.from_tuples([(0, 1), (0.5, 1.5)], inclusive=closed) assert idx.is_unique is True # unique overlapping - shared endpoints idx = IntervalIndex.from_tuples([(1, 2), (1, 3), (2, 3)], inclusive=closed) assert idx.is_unique is True # unique nested idx = IntervalIndex.from_tuples([(-1, 1), (-2, 2)], inclusive=closed) assert idx.is_unique is True # unique NaN idx = IntervalIndex.from_tuples([(np.NaN, np.NaN)], inclusive=closed) assert idx.is_unique is True # non-unique NaN idx = IntervalIndex.from_tuples( [(np.NaN, np.NaN), (np.NaN, np.NaN)], inclusive=closed ) assert idx.is_unique is False

pandas/tests/indexes/interval/test_interval.py

pandas

Python

7e23a37e1c5bda81234801a6584563e2880769eb

test_interval.py

test_is_unique_interval

https://github.com/pandas-dev/pandas.git

ENH: consistency of input args for boundaries - Interval (#46522)

def preprocess_func(cls, func): return unidist.put(func)

modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/partition.py

modin

Python

193505fdf0c984743397ba3df56262f30aee13a8

partition.py

preprocess_func

https://github.com/modin-project/modin.git

FEAT-#5053: Add pandas on unidist execution with MPI backend (#5059) Signed-off-by: Igoshev, Iaroslav <[email protected]>

def on_page_read_source(self, page, config): return None

mkdocs/plugins.py

mkdocs

Python

f79b34d174e41084391868e7b503f5c61b8b1bdf

plugins.py

on_page_read_source

https://github.com/mkdocs/mkdocs.git

Move plugin events docs into source code + refactor * Create real (no-op) methods for each event in the base class. * Refactor event dispatcher to not check for methods' existence, instead just call them. * Move documentation from Markdown into docstrings of these methods. * Activate the 'mkdocstrings' plugin. * Use 'mkdocstrings' to insert documentation from those docstrings into the site.

def mixed_type_frame() -> DataFrame: return DataFrame( { "a": 1.0, "b": 2, "c": "foo", "float32": np.array([1.0] * 10, dtype="float32"), "int32": np.array([1] * 10, dtype="int32"), }, index=np.arange(10), ) @pytest.fixture

pandas/conftest.py

@pytest.fixture

pandas

Python

f538568afc2c76c2d738d32e3544cf9fe6742960

conftest.py

mixed_type_frame

https://github.com/pandas-dev/pandas.git

TYP: misc return type annotations (#47558)

def _grad(f, argnums=0):

keras/integration_test/forwardprop_test.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

forwardprop_test.py

_grad

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def axvline(self, x=0, ymin=0, ymax=1, **kwargs): self._check_no_units([ymin, ymax], ['ymin', 'ymax']) if "transform" in kwargs: raise ValueError("'transform' is not allowed as a keyword " "argument; axvline generates its own transform.") xmin, xmax = self.get_xbound() # Strip away the units for comparison with non-unitized bounds. xx, = self._process_unit_info([("x", x)], kwargs) scalex = (xx < xmin) or (xx > xmax) trans = self.get_xaxis_transform(which='grid') l = mlines.Line2D([x, x], [ymin, ymax], transform=trans, **kwargs) self.add_line(l) if scalex: self._request_autoscale_view("x") return l

lib/matplotlib/axes/_axes.py

matplotlib

Python

383de519505964ed879c40b23ef36e90c17ebe0d

_axes.py

axvline

https://github.com/matplotlib/matplotlib.git

[Doc] fix more spelling and grammar

def DeprecatedModule(mod, deprecated_attributes=None, is_module_deprecated=True):

haystack/__init__.py

haystack

Python

a59bca366174d9c692fa19750c24d65f47660ef7

__init__.py

DeprecatedModule

https://github.com/deepset-ai/haystack.git

Apply black formatting (#2115) * Testing black on ui/ * Applying black on docstores * Add latest docstring and tutorial changes * Create a single GH action for Black and docs to reduce commit noise to the minimum, slightly refactor the OpenAPI action too * Remove comments * Relax constraints on pydoc-markdown * Split temporary black from the docs. Pydoc-markdown was obsolete and needs a separate PR to upgrade * Fix a couple of bugs * Add a type: ignore that was missing somehow * Give path to black * Apply Black * Apply Black * Relocate a couple of type: ignore * Update documentation * Make Linux CI run after applying Black * Triggering Black * Apply Black * Remove dependency, does not work well * Remove manually double trailing commas * Update documentation Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

def test_cli_log_level_debug_used(): configure_logging_and_warnings(logging.DEBUG) rasa_logger = logging.getLogger("rasa") rasa_logger.level == logging.DEBUG matplotlib_logger = logging.getLogger("matplotlib") # Default log level for libraries is currently ERROR matplotlib_logger.level == logging.ERROR @mock.patch.dict(os.environ, {"LOG_LEVEL": "WARNING"})

tests/utils/test_common.py

@mock.patch.dict(os.environ, {"LOG_LEVEL": "WARNING"})

rasa

Python

f00148b089d326c952880a0e5e6bd4b2dcb98ce5

test_common.py

test_cli_log_level_debug_used

https://github.com/RasaHQ/rasa.git

Configurable logging for libraries (#10614) * Make library level logging to be configurable Fixes https://github.com/RasaHQ/rasa/issues/10203 * Create log level documentation under cheatsheet in Rasa docs * Add log docs to `rasa shell --debug` (and others)

def partition_suite_by_case(suite): suite_class = type(suite) all_tests = iter_test_cases(suite) return [suite_class(tests) for _, tests in itertools.groupby(all_tests, type)]

django/test/runner.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

runner.py

partition_suite_by_case

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def test_get_invalid_filter_spec(self): # Get the image response = self.client.get( reverse("wagtailimages:preview", args=(self.image.id, "bad-filter-spec")) ) # Check response self.assertEqual(response.status_code, 400)

wagtail/images/tests/test_admin_views.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

test_admin_views.py

test_get_invalid_filter_spec

https://github.com/wagtail/wagtail.git

Reformat with black

def test_knn_imputer_keep_empty_features(keep_empty_features): X = np.array([[1, np.nan, 2], [3, np.nan, np.nan]]) imputer = KNNImputer(keep_empty_features=keep_empty_features) for method in ["fit_transform", "transform"]: X_imputed = getattr(imputer, method)(X) if keep_empty_features: assert X_imputed.shape == X.shape assert_array_equal(X_imputed[:, 1], 0) else: assert X_imputed.shape == (X.shape[0], X.shape[1] - 1)

sklearn/impute/tests/test_impute.py

scikit-learn

Python

d8fa96c29828e3ca79ddd5d7466521ac4d95213c

test_impute.py

test_knn_imputer_keep_empty_features

https://github.com/scikit-learn/scikit-learn.git

ENH keep features with all missing values during imputation (#24770) Co-authored-by: Chiara Marmo <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: Vitor SRG <[email protected]> Fixes https://github.com/scikit-learn/scikit-learn/pull/16695 Fixes https://github.com/scikit-learn/scikit-learn/issues/16426 Fixes https://github.com/scikit-learn/scikit-learn/issues/16977

def requires(self, extras=()): dm = self._dep_map deps = [] deps.extend(dm.get(None, ())) for ext in extras: try: deps.extend(dm[safe_extra(ext)]) except KeyError: raise UnknownExtra( "%s has no such extra feature %r" % (self, ext) ) return deps

.venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

__init__.py

requires

https://github.com/jindongwang/transferlearning.git

upd; format

def mode(a, axis=0, nan_policy='propagate'): a, axis = _chk_asarray(a, axis) if a.size == 0: return ModeResult(np.array([]), np.array([])) contains_nan, nan_policy = _contains_nan(a, nan_policy) if contains_nan and nan_policy == 'omit': a = ma.masked_invalid(a) return mstats_basic.mode(a, axis) if a.dtype == object and np.nan in set(a.ravel()): # Fall back to a slower method since np.unique does not work with NaN scores = set(np.ravel(a)) # get ALL unique values testshape = list(a.shape) testshape[axis] = 1 oldmostfreq = np.zeros(testshape, dtype=a.dtype) oldcounts = np.zeros(testshape, dtype=int) for score in scores: template = (a == score) counts = np.sum(template, axis, keepdims=True) mostfrequent = np.where(counts > oldcounts, score, oldmostfreq) oldcounts = np.maximum(counts, oldcounts) oldmostfreq = mostfrequent return ModeResult(mostfrequent, oldcounts)

scipy/stats/_stats_py.py

scipy

Python

7438fe5edfb565ff341fa6ab054461fcdd504aa2

_stats_py.py

mode

https://github.com/scipy/scipy.git

MAINT: stats: mode: fix negative axis issue with np.moveaxis instead of custom code (#15421)

def score(self, X, y, **fit_params): check_is_fitted(self) return self.estimator_.score(self.transform(X), y, **fit_params)

sklearn/feature_selection/_rfe.py

scikit-learn

Python

6e5ef2e9b8c64e6788428610ae884b9bf3d298a2

_rfe.py

score

https://github.com/scikit-learn/scikit-learn.git

MAINT solve long line reported by flake8 (#24065)

def finalize(self) -> None: if self._warn_autoconfig: desc = configexc.ConfigErrorDesc( "autoconfig loading not specified", ("Your config.py should call either `config.load_autoconfig()`" " (to load settings configured via the GUI) or " "`config.load_autoconfig(False)` (to not do so)")) self.errors.append(desc) with self._handle_error("updating mutated values"): self._config.update_mutables()

qutebrowser/config/configfiles.py

qutebrowser

Python

d9e20f6b3071b86b479f281fe27d621e0b3ae7e5

configfiles.py

finalize

https://github.com/qutebrowser/qutebrowser.git

config: Handle config.py errors while updating mutables Fixes #3580

def predict_on_batch(self, x): self._check_call_args("predict_on_batch") if ( self._distribution_strategy and tf.distribute.in_cross_replica_context() ): raise NotImplementedError( "`predict_on_batch` is not supported for models distributed with" " tf.distribute.Strategy." ) # Validate and standardize user data. inputs, _, _ = self._standardize_user_data( x, extract_tensors_from_dataset=True ) # If `self._distribution_strategy` is True, then we are in a replica context # at this point. if self.run_eagerly or self._distribution_strategy: inputs = training_utils_v1.cast_if_floating_dtype(inputs) if isinstance(inputs, collections.abc.Sequence): # Unwrap lists with only one input, as we do when training on batch if len(inputs) == 1: inputs = inputs[0] return self(inputs) # pylint: disable=not-callable self._make_predict_function() outputs = self.predict_function(inputs) if len(outputs) == 1: return outputs[0] return outputs

keras/engine/training_v1.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_v1.py

predict_on_batch

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def flatten(self) -> Union["FeatureType", Dict[str, "FeatureType"]]: from .features import Value if self.decode: raise ValueError("Cannot flatten a decoded Audio feature.") return { "bytes": Value("binary"), "path": Value("string"), }

src/datasets/features/audio.py

datasets

Python

3804442bb7cfcb9d52044d92688115cfdc69c2da

audio.py

flatten

https://github.com/huggingface/datasets.git

Fix flatten of complex feature types (#3723) * Flatten Translation and TranslationVariableLanguages * Add tests * Style * Flatten for decodable features * Fix flatten for non-dict types * Add test * Descriptive message in flatten for Audio feature * Small refactor * Add flatten to features * Update table_flatten * Revert changes in Dataset.flatten_/flatten * Apply Quentin's suggestions from code review Co-authored-by: Quentin Lhoest <[email protected]> * Improve table_flatten docstring * Fix tests * Add nested test * Minor fix * Remove comment Co-authored-by: Quentin Lhoest <[email protected]>

def gmean(a, axis=0, dtype=None, weights=None): r if not isinstance(a, np.ndarray): # if not an ndarray object attempt to convert it log_a = np.log(np.array(a, dtype=dtype)) elif dtype: # Must change the default dtype allowing array type if isinstance(a, np.ma.MaskedArray): log_a = np.log(np.ma.asarray(a, dtype=dtype)) else: log_a = np.log(np.asarray(a, dtype=dtype)) else: log_a = np.log(a) if weights is not None: weights = np.asanyarray(weights, dtype=dtype) return np.exp(np.average(log_a, axis=axis, weights=weights)) @_axis_nan_policy_factory( lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True, result_unpacker=lambda x: (x,), kwd_samples=['weights'])

scipy/stats/_stats_py.py

@_axis_nan_policy_factory( lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True, result_unpacker=lambda x: (x,), kwd_samples=['weights'])

scipy

Python

56869131c8e0a0d6e1af86cc1a000c61e83efcf6

_stats_py.py

gmean

https://github.com/scipy/scipy.git

DOC: stats: correct doc display

def split_filename(filename, project_name=None): result = None pyver = None filename = unquote(filename).replace(' ', '-') m = PYTHON_VERSION.search(filename) if m: pyver = m.group(1) filename = filename[:m.start()] if project_name and len(filename) > len(project_name) + 1: m = re.match(re.escape(project_name) + r'\b', filename) if m: n = m.end() result = filename[:n], filename[n + 1:], pyver if result is None: m = PROJECT_NAME_AND_VERSION.match(filename) if m: result = m.group(1), m.group(3), pyver return result # Allow spaces in name because of legacy dists like "Twisted Core" NAME_VERSION_RE = re.compile(r'(?P<name>[\w .-]+)\s*' r'\(\s*(?P<ver>[^\s)]+)\)$')

.venv/lib/python3.8/site-packages/pip/_vendor/distlib/util.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

util.py

split_filename

https://github.com/jindongwang/transferlearning.git

upd; format

def test_mapped_literal_to_xcom_arg_verify_integrity(dag_maker, session): with dag_maker(session=session) as dag: t1 = BaseOperator(task_id='task_1')

tests/models/test_dagrun.py

airflow

Python

91832a42d8124b040073481fd93c54e9e64c2609

test_dagrun.py

test_mapped_literal_to_xcom_arg_verify_integrity

https://github.com/apache/airflow.git

Expand mapped tasks at DagRun.Veriy_integrity (#22679) Create the necessary task instances for a mapped task at dagrun.verify_integrity Co-authored-by: Ash Berlin-Taylor <[email protected]>

def raise_on_http_errors(self) -> bool:

airbyte-cdk/python/airbyte_cdk/sources/declarative/requesters/requester.py

airbyte

Python

150ab593f8ca1f1aa960a0811aece26c46ba6c75

requester.py

raise_on_http_errors

https://github.com/airbytehq/airbyte.git

Low code connectors: core structure (#12850) * checkout from alex/cac * doc * doc * remove broken test * rename * rename file * delete unused file * rename * abstract property * isort * update state * Update comment * remove incremental mixin * delete comment * update comments * update comments * remove no_state * rename package * pass parameters through kwargs * update interface to pass source in interface * update interface to pass source in interface * rename to stream_slicer * Low code connectors: string interpolation with jinja (#12852) * checkout from alex/cac * Add missing tests * Add missing files * missing file * rename * jinja dependency * Add comment * comment * comment * Revert "delete unused file" This reverts commit 758e939367775ddbefcd52c6e1e832976d3ba9fe. * delete unused field * delete unused field * rename * pass kwargs directly * isort * Revert "isort" This reverts commit 4a792239440bc9950813ccc6ed368641ce2a96e4. * format * decoder * better error handling * remove nostate * isort * delete dead code * Update mapping type to [str, Any] * add comment * Add comment * pass parameters through kwargs * move test to right module * Add missing test * Use authbase instead of deprecated class * leverage generator * rename to declarative * rename the classes too

def _mask_lengths(mel_lens, log_c, log_alpha_scaled): mask_log_c = sequence_mask(mel_lens) log_c = log_c * mask_log_c mask_log_alpha_scaled = mask_log_c.unsqueeze(2) log_alpha_scaled = log_alpha_scaled * mask_log_alpha_scaled return log_c, log_alpha_scaled

TTS/tts/layers/overflow/neural_hmm.py

TTS

Python

3b8b105b0d6539ac12972de94e0b2a5077fa1ce2

neural_hmm.py

_mask_lengths

https://github.com/coqui-ai/TTS.git

Adding OverFlow (#2183) * Adding encoder * currently modifying hmm * Adding hmm * Adding overflow * Adding overflow setting up flat start * Removing runs * adding normalization parameters * Fixing models on same device * Training overflow and plotting evaluations * Adding inference * At the end of epoch the test sentences are coming on cpu instead of gpu * Adding figures from model during training to monitor * reverting tacotron2 training recipe * fixing inference on gpu for test sentences on config * moving helpers and texts within overflows source code * renaming to overflow * moving loss to the model file * Fixing the rename * Model training but not plotting the test config sentences's audios * Formatting logs * Changing model name to camelcase * Fixing test log * Fixing plotting bug * Adding some tests * Adding more tests to overflow * Adding all tests for overflow * making changes to camel case in config * Adding information about parameters and docstring * removing compute_mel_statistics moved statistic computation to the model instead * Added overflow in readme * Adding more test cases, now it doesn't saves transition_p like tensor and can be dumped as json

def get_default_frameworks(): frameworks = [] if is_torch_available(): frameworks.append("pt") if is_tf_available(): frameworks.append("tf") if is_flax_available(): frameworks.append("flax") return frameworks _re_model_mapping = re.compile("MODEL_([A-Z_]*)MAPPING_NAMES")

src/transformers/commands/add_new_model_like.py

transformers

Python

0a5ef036e6c2d5093ed348c5fd706634f6ed5e38

add_new_model_like.py

get_default_frameworks

https://github.com/huggingface/transformers.git

Make `add-new-model-like` work in an env without all frameworks (#16239) * Make add-new-model-like work without all frameworks installed * A few fixes * Last default frameworks

def test_limited_api(tmp_path): # Based in part on test_cython from random.tests.test_extending here = os.path.dirname(__file__) ext_dir = os.path.join(here, "examples", "limited_api") cytest = str(tmp_path / "limited_api") shutil.copytree(ext_dir, cytest) # build the examples and "install" them into a temporary directory install_log = str(tmp_path / "tmp_install_log.txt") subprocess.check_call( [ sys.executable, "setup.py", "build", "install", "--prefix", str(tmp_path / "installdir"), "--single-version-externally-managed", "--record", install_log, ], cwd=cytest, )

numpy/core/tests/test_limited_api.py

numpy

Python

1edd6407d008fcaa282a6058ae355025c26517fd

test_limited_api.py

test_limited_api

https://github.com/numpy/numpy.git

TST: Split example package, skip limited API test for debug

def test_drange(): start = datetime.datetime(2011, 1, 1, tzinfo=mdates.UTC) end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC) delta = datetime.timedelta(hours=1) # We expect 24 values in drange(start, end, delta), because drange returns # dates from an half open interval [start, end) assert len(mdates.drange(start, end, delta)) == 24 # Same if interval ends slightly earlier end = end - datetime.timedelta(microseconds=1) assert len(mdates.drange(start, end, delta)) == 24 # if end is a little bit later, we expect the range to contain one element # more end = end + datetime.timedelta(microseconds=2) assert len(mdates.drange(start, end, delta)) == 25 # reset end end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC) # and tst drange with "complicated" floats: # 4 hours = 1/6 day, this is an "dangerous" float delta = datetime.timedelta(hours=4) daterange = mdates.drange(start, end, delta) assert len(daterange) == 6 assert mdates.num2date(daterange[-1]) == (end - delta) @_new_epoch_decorator

lib/matplotlib/tests/test_dates.py

@_new_epoch_decorator

matplotlib

Python

9a03cb3b8c7253271054f146724c230eca96274b

test_dates.py

test_drange

https://github.com/matplotlib/matplotlib.git

Add tests for date module

def get_default_executor(cls) -> "BaseExecutor": if cls._default_executor is not None: return cls._default_executor from airflow.configuration import conf executor_name = conf.get('core', 'EXECUTOR') cls._default_executor = cls.load_executor(executor_name) return cls._default_executor

airflow/executors/executor_loader.py

airflow

Python

1a8a897120762692ca98ac5ce4da881678c073aa

executor_loader.py

get_default_executor

https://github.com/apache/airflow.git

Improve speed to run `airflow` by 6x (#21438) By delaying expensive/slow imports to where they are needed, this gets `airflow` printing it's usage information in under 0.8s, down from almost 3s which makes it feel much much snappier. By not loading BaseExecutor we can get down to <0.5s

def test_create_profile_from_existing(): save_profiles( ProfilesCollection( profiles=[ Profile(name="foo", settings={PREFECT_API_KEY: "foo"}), ], active=None, ) ) invoke_and_assert( ["profile", "create", "bar", "--from", "foo"], expected_output=( f ), ) profiles = load_profiles() assert profiles["foo"].settings == {PREFECT_API_KEY: "foo"}, "Foo is unchanged" assert profiles["bar"] == Profile( name="bar", settings={PREFECT_API_KEY: "foo"}, source=PREFECT_PROFILES_PATH.value(), )

tests/cli/test_profile.py

prefect

Python

808660dd04465fc796a34e835467e8ae1f2449b3

test_profile.py

test_create_profile_from_existing

https://github.com/PrefectHQ/prefect.git

Add tests for profile CLI

def test_device_stats_gpu_from_nvidia(tmpdir): model = BoringModel() device_stats = DeviceStatsMonitor()

tests/callbacks/test_device_stats_monitor.py

lightning

Python

b56d8677ad0ff8513e566334f4a78a24b88480c3

test_device_stats_monitor.py

test_device_stats_gpu_from_nvidia

https://github.com/Lightning-AI/lightning.git

Update test_pruning.py to use `devices` instead of `gpus` or `ipus` (#11339)

def register_model_view(model, name, view_path, tab_label=None, tab_badge=None, tab_permission=None, kwargs=None): app_label = model._meta.app_label model_name = model._meta.model_name if model_name not in registry['views'][app_label]: registry['views'][app_label][model_name] = [] registry['views'][app_label][model_name].append({ 'name': name, 'path': view_path, 'tab_label': tab_label, 'tab_badge': tab_badge, 'tab_permission': tab_permission, 'kwargs': kwargs or {}, })

netbox/utilities/views.py

netbox

Python

0d7851ed9de2792ea6d9ed223c315c235290ddd7

views.py

register_model_view

https://github.com/netbox-community/netbox.git

#9072: Implement a mechanism for dynamically registering model detail views

def done_adding(self) -> bool: raise NotImplementedError()

python/ray/data/_internal/batcher.py

ray

Python

864af14f410ab12c7553332dd3a62e716f24a667

batcher.py

done_adding

https://github.com/ray-project/ray.git

[Datasets] [Local Shuffle - 1/N] Add local shuffling option. (#26094) Co-authored-by: Eric Liang <[email protected]> Co-authored-by: matthewdeng <[email protected]> Co-authored-by: Matthew Deng <[email protected]> Co-authored-by: Richard Liaw <[email protected]>

async def test_subscribe_deprecated_async(hass, mqtt_mock):

tests/components/mqtt/test_init.py

core

Python

845bf80e725af8c921915906b0f796c7a8164d11

test_init.py

test_subscribe_deprecated_async

https://github.com/home-assistant/core.git

Mqtt improve test coverage (#66279) Co-authored-by: Martin Hjelmare <[email protected]>

def validate(self, parameters, *args, **kwargs): result = ValidationResult(parameters) result._no_log_values.update(set_fallbacks(self.argument_spec, result._validated_parameters)) alias_warnings = [] alias_deprecations = [] try: result._aliases.update(_handle_aliases(self.argument_spec, result._validated_parameters, alias_warnings, alias_deprecations)) except (TypeError, ValueError) as e: result.errors.append(AliasError(to_native(e))) legal_inputs = _get_legal_inputs(self.argument_spec, result._validated_parameters, result._aliases) for option, alias in alias_warnings: result._warnings.append({'option': option, 'alias': alias}) for deprecation in alias_deprecations: result._deprecations.append({ 'name': deprecation['name'], 'version': deprecation.get('version'), 'date': deprecation.get('date'), 'collection_name': deprecation.get('collection_name'), }) try: result._no_log_values.update(_list_no_log_values(self.argument_spec, result._validated_parameters)) except TypeError as te: result.errors.append(NoLogError(to_native(te))) try: result._unsupported_parameters.update(_get_unsupported_parameters(self.argument_spec, result._validated_parameters, legal_inputs)) except TypeError as te: result.errors.append(RequiredDefaultError(to_native(te))) except ValueError as ve: result.errors.append(AliasError(to_native(ve))) try: check_mutually_exclusive(self._mutually_exclusive, result._validated_parameters) except TypeError as te: result.errors.append(MutuallyExclusiveError(to_native(te))) result._no_log_values.update(_set_defaults(self.argument_spec, result._validated_parameters, False)) try: check_required_arguments(self.argument_spec, result._validated_parameters) except TypeError as e: result.errors.append(RequiredError(to_native(e))) _validate_argument_types(self.argument_spec, result._validated_parameters, errors=result.errors) _validate_argument_values(self.argument_spec, result._validated_parameters, errors=result.errors) for check in _ADDITIONAL_CHECKS: try: check['func'](getattr(self, "_{attr}".format(attr=check['attr'])), result._validated_parameters) except TypeError as te: result.errors.append(check['err'](to_native(te))) result._no_log_values.update(_set_defaults(self.argument_spec, result._validated_parameters)) _validate_sub_spec(self.argument_spec, result._validated_parameters, errors=result.errors, no_log_values=result._no_log_values, unsupported_parameters=result._unsupported_parameters) if result._unsupported_parameters: flattened_names = [] for item in result._unsupported_parameters: if isinstance(item, tuple): flattened_names.append(".".join(item)) else: flattened_names.append(item) unsupported_string = ", ".join(sorted(list(flattened_names))) supported_string = ", ".join(self._valid_parameter_names) result.errors.append( UnsupportedError("{0}. Supported parameters include: {1}.".format(unsupported_string, supported_string))) return result

lib/ansible/module_utils/common/arg_spec.py

ansible

Python

1b947eaf92b6833d2a4fd019a30d7b85406f1778

arg_spec.py

validate

https://github.com/ansible/ansible.git

arg_spec - Return aliases in validation result and update aliases (#77576) When looking up the `no_log` setting for a parameter that is an alias in `AnsibleModule._log_invocation()`, the alias value will always be an empty dictionary since `self.aliases` on the `AnsibleModule` instance is never updated after initialization. Since the `no_log` setting is on the canonical parameter not the alias, an incorrect warning is issued if the parameter matches `PASSWORD_MATCH`. This PR returns the aliases dictionary as an attribute of the `ValidationResult` and updates the `aliases` attribute on the `AnsibleModule` instance.

def test_avatar_constraints_file_size(self): self._setup_local_files( { "small": {"size": 40}, "big": {"size": 60}, } ) res = self.get_success( self.handler.check_avatar_size_and_mime_type("mxc://test/small") ) self.assertTrue(res) res = self.get_success( self.handler.check_avatar_size_and_mime_type("mxc://test/big") ) self.assertFalse(res)

tests/handlers/test_profile.py

synapse

Python

bf60da1a60096fac5fb778b732ff2214862ac808

test_profile.py

test_avatar_constraints_file_size

https://github.com/matrix-org/synapse.git

Configurable limits on avatars (#11846) Only allow files which file size and content types match configured limits to be set as avatar. Most of the inspiration from the non-test code comes from matrix-org/synapse-dinsic#19

def get_source_segment(source, node, *, padded=False): try: if node.end_lineno is None or node.end_col_offset is None: return None lineno = node.lineno - 1 end_lineno = node.end_lineno - 1 col_offset = node.col_offset end_col_offset = node.end_col_offset except AttributeError: return None lines = _splitlines_no_ff(source) if end_lineno == lineno: return lines[lineno].encode()[col_offset:end_col_offset].decode() if padded: padding = _pad_whitespace(lines[lineno].encode()[:col_offset].decode()) else: padding = '' first = padding + lines[lineno].encode()[col_offset:].decode() last = lines[end_lineno].encode()[:end_col_offset].decode() lines = lines[lineno+1:end_lineno] lines.insert(0, first) lines.append(last) return ''.join(lines)

python3.10.4/Lib/ast.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

ast.py

get_source_segment

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def _replace_cwa_config_variables(self) -> Dict[str, Any]: cwa_config = self._load_config_file("agent") self._replace_all_config_variables( cwa_config, self.node_id, self.cluster_name, self.provider_config["region"], ) return cwa_config

python/ray/autoscaler/_private/aws/cloudwatch/cloudwatch_helper.py

ray

Python

71fae21e8e86c75bc58b53dccae563d15691610f

cloudwatch_helper.py

_replace_cwa_config_variables

https://github.com/ray-project/ray.git

[autoscaler] AWS Autoscaler CloudWatch Dashboard support (#20266) These changes add a set of improvements to enable automatic creation and update of CloudWatch dashboards when provisioning AWS Autoscaling clusters. Successful implementation of these improvements will allow AWS Autoscaler users to: 1. Get rapid insights into their cluster state via CloudWatch dashboards. 2. Allow users to update their CloudWatch dashboard JSON configuration files during Ray up execution time. Notes: 1. This PR is a follow-up PR for #18619, adds dashboard support.

def get_batch(self) -> Tuple[List[List[np.ndarray]], ...]: model_inputs: List[List[np.ndarray]] = [] model_targets: List[List[np.ndarray]] = [] for side in ("a", "b"): side_feed, side_targets = next(self._feeds[side]) if self._model.config["learn_mask"]: # Add the face mask as it's own target side_targets += [side_targets[-1][..., 3][..., None]] logger.trace("side: %s, input_shapes: %s, target_shapes: %s", # type: ignore side, side_feed.shape, [i.shape for i in side_targets]) model_inputs.append([side_feed]) model_targets.append(side_targets) return model_inputs, model_targets

plugins/train/trainer/_base.py

faceswap

Python

2beceffad9b15c1fd78f06b9b272563321c5a41e

_base.py

get_batch

https://github.com/deepfakes/faceswap.git

Data Augmentation update (#1263) - lib.detected_face - Subclass Masks for Landmark based masks - Add training mask propery + methods to DetectedFace - lib.training_training - subclass TrainingDataGenerator for training and preview data - Split cache into own module - Reduce thread count to 1 to prevent image corruption + data re-use - Process on largest model input/output size rather than stored image size - Size and crop masks during caching stage - Implement ring buffer for data flow - Fix preview reload bug - augmentation - typing - switch color aug order - better initialization - Fix warp + landmark warp to correctly apply at different image scales - Slightly improved warp caching - Don't store whether image is_preview. Handle all data as training images implicitly - plugins.trainer: Typing and fixes to work with trainingdata refactor

def optgroups(self, name, value, attr=None): default = (None, [], 0) groups = [default] has_selected = False selected_choices = { str(v) for v in value if str(v) not in self.choices.field.empty_values } if not self.is_required and not self.allow_multiple_selected: default[1].append(self.create_option(name, "", "", False, 0)) remote_model_opts = self.field.remote_field.model._meta to_field_name = getattr( self.field.remote_field, "field_name", remote_model_opts.pk.attname ) to_field_name = remote_model_opts.get_field(to_field_name).attname choices = ( (getattr(obj, to_field_name), self.choices.field.label_from_instance(obj)) for obj in self.choices.queryset.using(self.db).filter( **{"%s__in" % to_field_name: selected_choices} ) ) for option_value, option_label in choices: selected = str(option_value) in value and ( has_selected is False or self.allow_multiple_selected ) has_selected |= selected index = len(default[1]) subgroup = default[1] subgroup.append( self.create_option( name, option_value, option_label, selected_choices, index ) ) return groups

django/contrib/admin/widgets.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

widgets.py

optgroups

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

async def test_focused_child_widget_with_movement_bindings_on_screen() -> None:

tests/test_binding_inheritance.py

textual

Python

e75f784b2c788f95e398821266fcaab0f79aa12f

test_binding_inheritance.py

test_focused_child_widget_with_movement_bindings_on_screen

https://github.com/Textualize/textual.git

Add a test for a screen binding movement, wrapping a focusable widget This is the heart of the issue introduced by https://github.com/Textualize/textual/pull/1170/commits/b48a1402b8103ca16d5e338538620e9e08fb2c0e and which is being investigated in https://github.com/Textualize/textual/issues/1343 -- the child widget can be focused, but (as far as the author of the code is concerned) it has no bindings. Bindings for movement-oriented keys exist on the screen which composes up the widget into it. Up until 0.5.0 this worked just fine. As of 0.6.0, because binding inheritance was introduced, the bindings for movement that live at the `Widget` level cause the widget that has no bindings to appear to have bindings. While this can potentially be worked around with the use of inherit_bindings, this isn't a very satisfying solution and also breaks the rule of least astonishment. This test is going to be key to all of this. This is the test that should be made to work without breaking any of the other currently-passing tests.

def attributes_icon(self): if self._attributes: return self._attributes.get(ATTR_ICON) result = ICON_JSON_EXTRACT.search( self._row.shared_attrs or self._row.attributes ) return result and result.group(1)

homeassistant/components/logbook/__init__.py

core

Python

9215702388eef03c7c3ed9f756ea0db533d5beec

__init__.py

attributes_icon

https://github.com/home-assistant/core.git

Separate attrs into another table (reduces database size) (#68224)

def get_default_bank_cash_account(company, account_type=None, mode_of_payment=None, account=None): from erpnext.accounts.doctype.sales_invoice.sales_invoice import get_bank_cash_account if mode_of_payment: account = get_bank_cash_account(mode_of_payment, company).get("account") if not account: if account_type == "Bank": account = frappe.get_cached_value("Company", company, "default_bank_account") if not account: account_list = frappe.get_all( "Account", filters={"company": company, "account_type": "Bank", "is_group": 0} ) if len(account_list) == 1: account = account_list[0].name elif account_type == "Cash": account = frappe.get_cached_value("Company", company, "default_cash_account") if not account: account_list = frappe.get_all( "Account", filters={"company": company, "account_type": "Cash", "is_group": 0} ) if len(account_list) == 1: account = account_list[0].name if account: account_details = frappe.db.get_value( "Account", account, ["account_currency", "account_type"], as_dict=1 ) return frappe._dict( { "account": account, "balance": get_balance_on(account), "account_currency": account_details.account_currency, "account_type": account_details.account_type, } ) else: return frappe._dict() @frappe.whitelist()

erpnext/accounts/doctype/journal_entry/journal_entry.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

journal_entry.py

get_default_bank_cash_account

https://github.com/frappe/erpnext.git

style: format code with black

def destroy_if_owned(self) -> int: raise NotImplementedError @dataclass

python/ray/data/_internal/execution/interfaces.py

@dataclass

ray

Python

2cd4637521a0c75e0375266ff52d3dfca2084c2d

interfaces.py

destroy_if_owned

https://github.com/ray-project/ray.git

[data] New executor backend [1/n]--- Add basic interfaces (#31216) This PR adds the basic interfaces and feature flags; split out from https://github.com/ray-project/ray/pull/30903/files See REP ray-project/enhancements#18 for more details.

def subtract(inputs, **kwargs): return Subtract(**kwargs)(inputs)

keras/layers/merging/subtract.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

subtract.py

subtract

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def pick_config_ids(device_type, os, navigator): if os is None: default_dev_types = ["desktop"] else: default_dev_types = list(DEVICE_TYPE_OS.keys()) dev_type_choices = get_option_choices( "device_type", device_type, default_dev_types, list(DEVICE_TYPE_OS.keys()) ) os_choices = get_option_choices( "os", os, list(OS_NAVIGATOR.keys()), list(OS_NAVIGATOR.keys()) ) nav_choices = get_option_choices( "navigator", navigator, list(NAVIGATOR_OS.keys()), list(NAVIGATOR_OS.keys()) ) variants = [] for dev, os, nav in product(dev_type_choices, os_choices, nav_choices): if ( os in DEVICE_TYPE_OS[dev] and nav in DEVICE_TYPE_NAVIGATOR[dev] and nav in OS_NAVIGATOR[os] ): variants.append((dev, os, nav)) if not variants: raise InvalidOption( "Options device_type, os and navigator" " conflicts with each other" ) device_type, os_id, navigator_id = randomizer.choice(variants) assert os_id in OS_PLATFORM assert navigator_id in NAVIGATOR_OS assert device_type in DEVICE_TYPE_OS return device_type, os_id, navigator_id

build/pyinstaller/user_agent/base.py

OpenBBTerminal

Python

ab4de1dd70fba866930150e440a03e461a6ca6a8

base.py

pick_config_ids

https://github.com/OpenBB-finance/OpenBBTerminal.git

Create a packaged app bundle with Pyinstaller (#1525) * Add dashboard widget assets * Add ipywidgets and ipyflex to project * Add currencies dashboard notebook * Update docs and docstrings * Add pyinstaller to project deps * Add pyinstaller artifacts to gitignore * Fix linter errors in terminal.py * Update cspell hook and action with a pyinstaller specific word * Add pyinstaller specfile and artifacts * Add splashscreen image * Add app icon * adding splash screen support to terminal.spec and terminal.py * Restore the conda env build files * Sync deps * Add border to the splashscreen image * Clean up terminal launcher * Add support for default feature flags in packages apps * Fix types and linting * Add splashscreen management to app bootup * Check prediction feature flag when entering crypto/pred * Update pyinstaller spec file * fix .spec file to work for splash and icon - removed the ".." * Allows to export when using installer (#1568) * fix export for packaged apps * fix filename * Git : replace commit_hash when it is set in config_terminal * Add update of the git commit hash in gtff default during build * Add packaged app name and feature flag to logs * Add platform specific icon assignment * Add macOS build assets * Add tensorflow to hidden imports * Move LOGGING_COMMIT_HASH to gtff * Adding files/folders needed to .spec and pyinstaller folder. This will make certain commands work again. * Linting * Workflow : ignore ./build/pyinstaller from codespell * Workflow : exclude ./build/pyinstaller from flake8 * Poetry + Workflow : add types-six * Pyinstaller : remove property_cached, user_agent and vaderSentiment * Revert "Pyinstaller : remove property_cached, user_agent and vaderSentiment" This reverts commit dbb3e2b81086f97819ebd21457148c7160a4d703. * Clean up local paths in specfile * Validate deps have correct Jinja version (they do) * Fix logging commit hash to be set correctly for the logger to see it Co-authored-by: Andrew <[email protected]> Co-authored-by: didierlopes.eth <[email protected]> Co-authored-by: Chavithra PARANA <[email protected]>

def name_scope(name):

keras/backend.py

"""A context manager for use when defining a Python op. This context manager pushes a name scope, which will make the name of all operations added within it have a prefix. For example, to define a new Python op called `my_op`:use when defining a Python op. This context manager pushes a namewhich will make the name of all operations added within it have a prefix. Forto define a new Python op called

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

name_scope

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def get_loc(self, key, method=None): if method is not None: raise NotImplementedError( "only the default get_loc method is " "currently supported for MultiIndex" ) self._check_indexing_error(key)

pandas/core/indexes/multi.py

pandas

Python

46ddb8ef882940fa3da58813e0b7a2df1061031e

multi.py

get_loc

https://github.com/pandas-dev/pandas.git

BUG: Index.get_loc always raise InvalidIndexError on listlike (#45181)

def setter(self, attr): if attr not in self._options: raise KeyError("No such option: %s" % attr)

mitmproxy/optmanager.py

mitmproxy

Python

b3587b52b25077f68116b9852b041d33e7fc6601

optmanager.py

setter

https://github.com/mitmproxy/mitmproxy.git

make it black!

def sqrtdenest(expr, max_iter=3): expr = expand_mul(expr) for i in range(max_iter): z = _sqrtdenest0(expr) if expr == z: return expr expr = z return expr

sympy/simplify/sqrtdenest.py

sympy

Python

2a1afca9477eb781f16d5d6b63fa37abed7740a3

sqrtdenest.py

sqrtdenest

https://github.com/sympy/sympy.git

Use sympify less

def as_hashes(self) -> Hashes: return Hashes({self.name: [self.value]})

src/pip/_internal/models/link.py

pip

Python

bad03ef931d9b3ff4f9e75f35f9c41f45839e2a1

link.py

as_hashes

https://github.com/pypa/pip.git

Use data-dist-info-metadata (PEP 658) to decouple resolution from downloading (#11111) Co-authored-by: Tzu-ping Chung <[email protected]>

def plextv_resources_two_servers_fixture(): return load_fixture("plex/plextv_resources_two_servers.xml") @pytest.fixture(name="plextv_shared_users", scope="session")

tests/components/plex/conftest.py

@pytest.fixture(name="plextv_shared_users", scope="session")

core

Python

10195dc700770cdfdeaff79c53cf5d1d763f20c6

conftest.py

plextv_resources_two_servers_fixture

https://github.com/home-assistant/core.git

Improve server selection for Plex config flows (#63408)

def remove_signature_from_binary(filename): logger.debug("Removing signature from file %r", filename) cmd_args = ['codesign', '--remove', '--all-architectures', filename] p = subprocess.run(cmd_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, universal_newlines=True) if p.returncode: raise SystemError(f"codesign command ({cmd_args}) failed with error code {p.returncode}!\noutput: {p.stdout}")

PyInstaller/utils/osx.py

pyinstaller

Python

1cd3b73e2939052271a0bc26cf204eebee4dcd15

osx.py

remove_signature_from_binary

https://github.com/pyinstaller/pyinstaller.git

macOS: Remove the timeouts for codesigning/signature stripping/lipo. (#6644)

def _get_child_layer_node_ids(self, node_id): # Sequential and Functional track layers with names following the format # "layer-N". Use this to generate the list of layers. num_layers = 0 child_layers = {} pattern = re.compile("layer-(\\d+)") for child in self._proto.nodes[node_id].children: m = pattern.match(child.local_name) if m is None: continue layer_n = int(m.group(1)) num_layers = max(layer_n + 1, num_layers) child_layers[layer_n] = child.node_id ordered = [] for n in range(num_layers): child = child_layers.get(n) if child is None: break ordered.append(child) return ordered

keras/saving/saved_model/load.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

load.py

_get_child_layer_node_ids

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def test_token_node_empty_csrf_cookie(self): req = self._get_request(cookie="") mw = CsrfViewMiddleware(token_view) mw.process_view(req, token_view, (), {}) resp = token_view(req) token = get_token(req) self.assertIsNotNone(token) csrf_secret = _unmask_cipher_token(token) self._check_token_present(resp, csrf_secret)

tests/csrf_tests/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_token_node_empty_csrf_cookie

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def parse_tag(self, tag): subtags = tag.split("-") lang = {} labels = ["language", "extlang", "script", "region", "variant", "variant"] while subtags and labels: subtag = subtags.pop(0) found = False while labels: label = labels.pop(0) subtag = self.casing[label](subtag) if self.format[label].fullmatch(subtag): if subtag in self.db[label]: found = True valstr = self.val2str(self.db[label][subtag]["Description"]) if label == "variant" and label in lang: lang[label] += ": " + valstr else: lang[label] = valstr break elif subtag in self.db["deprecated"][label]: found = True note = f"The {subtag!r} {label} code is deprecated" if "Preferred-Value" in self.db["deprecated"][label][subtag]: prefer = self.db["deprecated"][label][subtag][ "Preferred-Value" ] note += f"', prefer '{self.val2str(prefer)}'" lang[label] = self.val2str( self.db["deprecated"][label][subtag]["Description"] ) warn(note) break if not found: if subtag == "u" and subtags[0] == "sd": # CLDR regional subdivisions sd = subtags[1] if sd in self.subdiv: ext = self.subdiv[sd] else: ext = f"<Unknown subdivision: {ext}>" else: # other extension subtags are not supported yet ext = f"{subtag}{''.join(['-'+ext for ext in subtags])}".lower() if not self.format["singleton"].fullmatch(subtag): ext = f"<Invalid extension: {ext}>" warn(ext) lang["extension"] = ext subtags = [] return lang

nltk/corpus/reader/bcp47.py

nltk

Python

f019fbedb3d2b6a2e6b58ec1b38db612b106568b

bcp47.py

parse_tag

https://github.com/nltk/nltk.git

Support both iso639-3 codes and BCP-47 language tags (#3060) * Add support for iso639-3 language codes * Add support for retired language codes * Move langnames.py to the top-level * Add langcode() function * Add iso639retired dictionary * Improve wrapper functions * Add module docstring with doctest * Add 2-letter language codes * Add regular expression check * Improve inverse lookup of retired codes * Support BCP-47 * Avoid deprecated langcodes * Set stack level for warnings to warn on the langname call Now it throws e.g. ``` ...\nltk_3060.py:9: UserWarning: Shortening 'smo' to 'sm' print(f"{lang}: {langname(code)}") ``` Rather than ``` ...\nltk\langnames.py:64: UserWarning: Shortening zha to za warn(f"Shortening {code} to {code2}") ``` * Dict key membership is equivalent to dict membership * Resolve bug: subtag -> tag * Capitalize BCP47 in CorpusReader name * Reimplement removed type hint changes from #3081 Co-authored-by: Tom Aarsen <[email protected]>

def test_recurrent_unroll_and_filter(self): inputs = TensorDict( { "in": torch.arange(B * T * 2).reshape(B, T, 2), "bork": torch.arange(5 * 4).reshape(5, 4), } ) states = TensorDict( { "in": torch.arange(B * 4).reshape(B, 4), "bork": torch.arange(5 * 4).reshape(5, 4), } ) outputs, out_states = SimpleRecurrentModel(ModelConfig()).unroll(inputs, states) desired = TensorDict({"out": torch.arange(B * T * 3).reshape(B, T, 3)}) desired_states = TensorDict({"out": torch.arange(B * 5).reshape(B, 5)}) for k in outputs.flatten().keys() | desired.flatten().keys(): check(outputs[k], desired[k]) for k in out_states.flatten().keys() | desired_states.flatten().keys(): check(out_states[k], desired_states[k])

rllib/models/tests/test_torch_model.py

ray

Python

b0945548e874642287b81514b71432a2330de1d3

test_torch_model.py

test_recurrent_unroll_and_filter

https://github.com/ray-project/ray.git

[RLlib] Add torch models (#29043) 1. converted class attributes to setters 2. use override decorator 3. SimpleModel should not have any T dimension, it can confuse folks. So I removed it. 4. I merged all the unittests under one class and separated them by methods names. It will be easier to use -k filter to run pytests later if we don't allow repetative method names. Signed-off-by: Kourosh Hakhamaneshi <[email protected]> Signed-off-by: Steven Morad <[email protected]>

def _shard(self, num_shards=None, index=None, contiguous=False): if num_shards is None: num_shards = dist.get_world_size() if index is None: index = dist.get_rank() if contiguous: div = len(self) // num_shards mod = len(self) % num_shards start = div * index + min(index, mod) end = start + div + (1 if index < mod else 0) new_data = [self.new_data[idx] for idx in range(start, end)] else: new_data = [ self.new_data[idx] for idx in range(len(self.new_data)) if idx % num_shards == index ] return MapDataset(new_data)

paddlenlp/datasets/dataset.py

PaddleNLP

Python

1c10abadb7c960e58ce44813f6197dfca9cbd28d

dataset.py

_shard

https://github.com/PaddlePaddle/PaddleNLP.git

Integrate HF Datasets and add DatasetTuple (#1612) * fix bart perf * update fastergeneration doc * add img * add img * change img * update img * fix img * update docs * fix readme * update readme * fix perf * fix perf * fix modelling * fix perf and sample code * fix perf * fix perf * fix seq_len for gpt_sample * add forced eos token id for faster * upgrade perf and add forced eos token id * chenge stack to gather * add auto perf * minor fix * remove encoder change * Update bart_perf.py * Update bart_perf.py * 1. Integrate HF Datasets 2. return all splits by default 3. load_dataset returns DatasetTuple now * add HF Dataset example * add kwargs for HF load_dataset * change datasets to alternative * remove experimental

def _register_arrow_data_serializer(serialization_context): import pyarrow as pa if os.environ.get(RAY_DISABLE_CUSTOM_ARROW_DATA_SERIALIZATION, "0") == "1": return # Register custom reducer for Arrow Arrays. array_types = _get_arrow_array_types() for array_type in array_types: serialization_context._register_cloudpickle_reducer( array_type, _arrow_array_reduce ) # Register custom reducer for Arrow ChunkedArrays. serialization_context._register_cloudpickle_reducer( pa.ChunkedArray, _arrow_chunkedarray_reduce ) # Register custom reducer for Arrow RecordBatches. serialization_context._register_cloudpickle_reducer( pa.RecordBatch, _arrow_recordbatch_reduce ) # Register custom reducer for Arrow Tables. serialization_context._register_cloudpickle_reducer(pa.Table, _arrow_table_reduce)

python/ray/data/_internal/arrow_serialization.py

ray

Python

c1d62d46495f0157faf3168aa87eed350802e10f

arrow_serialization.py

_register_arrow_data_serializer

https://github.com/ray-project/ray.git

[Datasets] Arrow 7.0.0+ Support: Use Arrow IPC format for pickling Arrow data to circumvent slice view buffer truncation bug. (#29055) This PR registers a custom serializer for Array arrays, chunked arrays, record batches, and tables that works around an Arrow serialization bug that serializes the entire underlying data buffer when serializing zero-copy slice views. The custom serializer uses the Arrow IPC format as the underlying pickled representation.

def csrc(self): return self["csrc"]

packages/python/plotly/plotly/graph_objs/_scatterternary.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_scatterternary.py

csrc

https://github.com/plotly/plotly.py.git

switch to black .22

def test_size_hint(view): view.show_message(message.MessageInfo(usertypes.MessageLevel.info, 'test1')) height1 = view.sizeHint().height() assert height1 > 0 view.show_message(message.MessageInfo(usertypes.MessageLevel.info, 'test2')) height2 = view.sizeHint().height() assert height2 == height1 * 2

tests/unit/mainwindow/test_messageview.py

qutebrowser

Python

5616a99eff34f7074641d1391ed77d6b4b743529

test_messageview.py

test_size_hint

https://github.com/qutebrowser/qutebrowser.git

Add a MessageInfo data class Preparation for #7246

def handler(request, operation, current_url): if operation != QNetworkAccessManager.Operation.GetOperation: return networkreply.ErrorNetworkReply( request, "Unsupported request type", QNetworkReply.NetworkError.ContentOperationNotPermittedError) url = request.url() if ((url.scheme(), url.host(), url.path()) == ('qute', 'settings', '/set')): if current_url != QUrl('qute://settings/'): log.network.warning("Blocking malicious request from {} to {}" .format(current_url.toDisplayString(), url.toDisplayString())) return networkreply.ErrorNetworkReply( request, "Invalid qute://settings request", QNetworkReply.NetworkError.ContentAccessDenied) try: mimetype, data = qutescheme.data_for_url(url) except qutescheme.Error as e: errors = { qutescheme.NotFoundError: QNetworkReply.NetworkError.ContentNotFoundError, qutescheme.UrlInvalidError: QNetworkReply.NetworkError.ContentOperationNotPermittedError, qutescheme.RequestDeniedError: QNetworkReply.NetworkError.ContentAccessDenied, qutescheme.SchemeOSError: QNetworkReply.NetworkError.ContentNotFoundError, qutescheme.Error: QNetworkReply.NetworkError.InternalServerError, } exctype = type(e) log.misc.error("{} while handling qute://* URL".format( exctype.__name__)) return networkreply.ErrorNetworkReply(request, str(e), errors[exctype]) except qutescheme.Redirect as e: qtutils.ensure_valid(e.url) return networkreply.RedirectNetworkReply(e.url) return networkreply.FixedDataNetworkReply(request, data, mimetype)

qutebrowser/browser/webkit/network/webkitqutescheme.py

qutebrowser

Python

0877fb0d78635692e481c8bde224fac5ad0dd430

webkitqutescheme.py

handler

https://github.com/qutebrowser/qutebrowser.git

Run scripts/dev/rewrite_enums.py

def get(self, key, default_value=None): if key in self: return self[key] else: return default_value

pipenv/patched/notpip/_vendor/pyparsing/results.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

results.py

get

https://github.com/pypa/pipenv.git

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

def huber(y_true, y_pred, delta=1.0): y_pred = tf.cast(y_pred, dtype=backend.floatx()) y_true = tf.cast(y_true, dtype=backend.floatx()) delta = tf.cast(delta, dtype=backend.floatx()) error = tf.subtract(y_pred, y_true) abs_error = tf.abs(error) half = tf.convert_to_tensor(0.5, dtype=abs_error.dtype) return backend.mean( tf.where( abs_error <= delta, half * tf.square(error), delta * abs_error - half * tf.square(delta), ), axis=-1, ) @keras_export( "keras.losses.log_cosh", "keras.losses.logcosh", "keras.metrics.log_cosh", "keras.metrics.logcosh", ) @tf.__internal__.dispatch.add_dispatch_support

keras/losses.py

@keras_export( "keras.losses.log_cosh", "keras.losses.logcosh", "keras.metrics.log_cosh", "keras.metrics.logcosh", ) @tf.__internal__.dispatch.add_dispatch_support

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

losses.py

huber

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def print_help(self): id_string = "" for s_id, sub_dict in self.current_series.items(): id_string += f" [cyan]{s_id.upper()}[/cyan] : {sub_dict['title']}" help_string = f t_console.print(help_string)

gamestonk_terminal/economy/fred/prediction/pred_controller.py

OpenBBTerminal

Python

f5b0dc8e7b5ae7ed3a4b175ba48aba0d5ea9d2db

pred_controller.py

print_help

https://github.com/OpenBB-finance/OpenBBTerminal.git

Add prediction to economy/fred (#1133)

def __call__(self, _metric=None, **kwargs): assert self._last_report_time is not None, ( "StatusReporter._start() must be called before the first " "report __call__ is made to ensure correct runtime metrics." ) if _metric: kwargs[DEFAULT_METRIC] = _metric # time per iteration is recorded directly in the reporter to ensure # any delays in logging results aren't counted report_time = time.time() if TIME_THIS_ITER_S not in kwargs: kwargs[TIME_THIS_ITER_S] = report_time - self._last_report_time self._last_report_time = report_time # add results to a thread-safe queue self._queue.put(kwargs.copy(), block=True) # This blocks until notification from the FunctionRunner that the last # result has been returned to Tune and that the function is safe to # resume training. self._continue_semaphore.acquire() # If the trial should be terminated, exit gracefully. if self._end_event.is_set(): self._end_event.clear() sys.exit(0)

python/ray/tune/function_runner.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

function_runner.py

__call__

https://github.com/ray-project/ray.git

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

def register_plotting_backend_cb(key) -> None: if key == "matplotlib": # We defer matplotlib validation, since it's the default return from pandas.plotting._core import _get_plot_backend _get_plot_backend(key) with cf.config_prefix("plotting"): cf.register_option( "backend", defval="matplotlib", doc=plotting_backend_doc, validator=register_plotting_backend_cb, ) register_converter_doc =

pandas/core/config_init.py