Datasets:

semeru

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

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Semeru Lab 7

def test_page_with_og(self) -> None: html = b parser = OpenGraphParser(html, "text/html; charset=UTF-8") result = parser.extract_data() self.assertEqual(result.title, "The Rock") self.assertEqual(result.description, "The Rock film")

zerver/tests/test_link_embed.py

zulip

Python

327ff9ea0f5e4712a34d767fee55a549cc1d3f39

test_link_embed.py

test_page_with_og

https://github.com/zulip/zulip.git

preview: Use a dataclass for the embed data. This is significantly cleaner than passing around `Dict[str, Any]` all of the time.

def upgrade(): op.create_index('idx_log_event', 'log', ['event'], unique=False)

airflow/migrations/versions/0109_1de7bc13c950_add_index_for_event_in_log.py

airflow

Python

5d8cda8c5be42c8daaaa904d29a1011833c0c699

0109_1de7bc13c950_add_index_for_event_in_log.py

upgrade

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

Add index for event column in log table (#23625)

def get_fields(self, include_parents=True, include_hidden=False): if include_parents is False: include_parents = PROXY_PARENTS return self._get_fields( include_parents=include_parents, include_hidden=include_hidden )

django/db/models/options.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

options.py

get_fields

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

Refs #33476 -- Reformatted code with Black.

def test_location_present(self): response = self.get(4) self.assertContains(response, "The North Pole", 1)

wagtail/contrib/modeladmin/tests/test_page_modeladmin.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

test_page_modeladmin.py

test_location_present

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

Reformat with black

def _patch_hf_hub_tqdm(): old_tqdm = huggingface_hub.file_download.tqdm huggingface_hub.file_download.tqdm = tqdm yield huggingface_hub.file_download.tqdm = old_tqdm

src/transformers/utils/hub.py

transformers

Python

5cd40323684c183c30b34758aea1e877996a7ac9

hub.py

_patch_hf_hub_tqdm

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

Use new huggingface_hub tools for download models (#18438) * Draft new cached_file * Initial draft for config and model * Small fixes * Fix first batch of tests * Look in cache when internet is down * Fix last tests * Bad black, not fixing all quality errors * Make diff less * Implement change for TF and Flax models * Add tokenizer and feature extractor * For compatibility with main * Add utils to move the cache and auto-do it at first use. * Quality * Deal with empty commit shas * Deal with empty etag * Address review comments

def test_failed_execution(self, api, started_job, batch): jobs = [started_job for _ in range(49)] batch.execute.side_effect = [batch, batch, None] update_in_batch(api=api, jobs=jobs) assert started_job.update_job.call_count == 49 assert len(api.new_batch.return_value) == 49 assert batch.execute.call_count == 3

airbyte-integrations/connectors/source-facebook-marketing/unit_tests/test_async_job.py

airbyte

Python

a3aae8017a0a40ff2006e2567f71dccb04c997a5

test_async_job.py

test_failed_execution

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

🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805) * Facebook Marketing performance improvement * add comments and little refactoring * fix integration tests with the new config * improve job status handling, limit concurrency to 10 * fix campaign jobs, refactor manager * big refactoring of async jobs, support random order of slices * update source _read_incremental to hook new state logic * fix issues with timeout * remove debugging and clean up, improve retry logic * merge changes from #8234 * fix call super _read_increment * generalize batch execution, add use_batch flag * improve coverage, do some refactoring of spec * update test, remove overrides of source * add split by AdSet * add smaller insights * fix end_date < start_date case * add account_id to PK * add notes * fix new streams * fix reversed incremental stream * update spec.json for SAT * upgrade CDK and bump version Co-authored-by: Dmytro Rezchykov <[email protected]> Co-authored-by: Eugene Kulak <[email protected]>

async def test_logbook_entity_matches_only_multiple(hass, hass_client, recorder_mock): await async_setup_component(hass, "logbook", {}) assert await async_setup_component( hass, "switch", { "switch": { "platform": "template", "switches": { "test_template_switch": { "value_template": "{{ states.switch.test_state.state }}", "turn_on": { "service": "switch.turn_on", "entity_id": "switch.test_state", }, "turn_off": { "service": "switch.turn_off", "entity_id": "switch.test_state", }, } }, } }, ) await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block_till_done) await hass.async_block_till_done() await hass.async_start() await hass.async_block_till_done() # Entity added (should not be logged) hass.states.async_set("switch.test_state", STATE_ON) hass.states.async_set("light.test_state", STATE_ON) await hass.async_block_till_done() # First state change (should be logged) hass.states.async_set("switch.test_state", STATE_OFF) hass.states.async_set("light.test_state", STATE_OFF) await hass.async_block_till_done() switch_turn_off_context = ha.Context( id="9c5bd62de45711eaaeb351041eec8dd9", user_id="9400facee45711eaa9308bfd3d19e474", ) hass.states.async_set( "switch.test_state", STATE_ON, context=switch_turn_off_context ) hass.states.async_set("light.test_state", STATE_ON, context=switch_turn_off_context) await hass.async_block_till_done() await hass.async_add_executor_job(trigger_db_commit, hass) await hass.async_block_till_done() await hass.async_add_executor_job(hass.data[recorder.DATA_INSTANCE].block_till_done) client = await hass_client() # Today time 00:00:00 start = dt_util.utcnow().date() start_date = datetime(start.year, start.month, start.day) # Test today entries with filter by end_time end_time = start + timedelta(hours=24) response = await client.get( f"/api/logbook/{start_date.isoformat()}?end_time={end_time}&entity=switch.test_state,light.test_state&entity_matches_only" ) assert response.status == HTTPStatus.OK json_dict = await response.json() assert len(json_dict) == 4 assert json_dict[0]["entity_id"] == "switch.test_state" assert json_dict[1]["entity_id"] == "light.test_state" assert json_dict[2]["entity_id"] == "switch.test_state" assert json_dict[2]["context_user_id"] == "9400facee45711eaa9308bfd3d19e474" assert json_dict[3]["entity_id"] == "light.test_state" assert json_dict[3]["context_user_id"] == "9400facee45711eaa9308bfd3d19e474"

tests/components/logbook/test_init.py

core

Python

982e314de630de2fe8e379b6f1106ec9fa945335

test_init.py

test_logbook_entity_matches_only_multiple

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

Use recorder_mock in tests (#70363) Co-authored-by: Paulus Schoutsen <[email protected]>

async def test_gather_is_robust_with_return_types_that_break_equality_checks():

tests/utilities/test_asyncio.py

prefect

Python

cfe630e97a5942c285b25d3bea5f1a7a47c4d9c5

test_asyncio.py

test_gather_is_robust_with_return_types_that_break_equality_checks

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

Fix issue where gather can fail when a task returns a pandas object

def _valuechoice_staticmethod_helper(orig_func): orig_func.__doc__ += return orig_func

nni/retiarii/nn/pytorch/api.py

nni

Python

a36dc07e8d39ec4438fd660c98f6f4551ff5f4a6

api.py

_valuechoice_staticmethod_helper

https://github.com/microsoft/nni.git

Composition of `ValueChoice` (#4435)

def get_buttons_from_dialog(dialog, channel): buttons = None if channel == "Follow": # get follow buttons. This approach will find the follow buttons and # ignore the Unfollow/Requested buttons. buttons = dialog.find_elements( By.XPATH, read_xpath(get_buttons_from_dialog.__name__, "follow_button") ) elif channel == "Unfollow": buttons = dialog.find_elements( By.XPATH, read_xpath(get_buttons_from_dialog.__name__, "unfollow_button") ) return buttons

instapy/unfollow_util.py

InstaPy

Python

2a157d452611d37cf50ccb7d56ff1a06e9790ecb

unfollow_util.py

get_buttons_from_dialog

https://github.com/InstaPy/InstaPy.git

PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438) * Updated getUserData() and find_element* Signed-off-by: elulcao <[email protected]> Thanks @breuerfelix for reviewing, 🚀 People in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her

def circumcenter(self): return self.center

sympy/geometry/polygon.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

polygon.py

circumcenter

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

Updated import locations

def is_maximal_matching(G, matching): if isinstance(matching, dict): matching = matching_dict_to_set(matching) # If the given set is not a matching, then it is not a maximal matching. edges = set() nodes = set() for edge in matching: if len(edge) != 2: raise nx.NetworkXError(f"matching has non-2-tuple edge {edge}") u, v = edge if u not in G or v not in G: raise nx.NetworkXError(f"matching contains edge {edge} with node not in G") if u == v: return False if not G.has_edge(u, v): return False if u in nodes or v in nodes: return False nodes.update(edge) edges.add(edge) edges.add((v, u)) # A matching is maximal if adding any new edge from G to it # causes the resulting set to match some node twice. # Be careful to check for adding selfloops for u, v in G.edges: if (u, v) not in edges: # could add edge (u, v) to edges and have a bigger matching if u not in nodes and v not in nodes and u != v: return False return True

networkx/algorithms/matching.py

networkx

Python

28b3014d68d2b4e40d3e02219770296a827bd55c

matching.py

is_maximal_matching

https://github.com/networkx/networkx.git

Update matching functions for error validation and speed (#4897) * First steps to update matching functions for #4644 Expand tests Change API to raise NetworkXError when matching involves nodes not in G Update is_*_matching to 100+ times faster. * improve matching_dict_to_set and docs for min_weight_matching * fix sphinx error

def uri(self) -> Optional[str]: if self._uri: return self._uri if self._local_path and Path(self._local_path).exists(): return "file://" + self._local_path return None

python/ray/air/checkpoint.py

ray

Python

1dede1c296a29332171df87b31d9ba92c26b40f7

checkpoint.py

uri

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

[air] Add `Checkpoint.uri` to return checkpoint URI, if available (#28731) A common ask is to retrieve the URI of a cloud checkpoint, e.g. after training. This PR introduces a property to the `Checkpoint` class that will return a URI if available and reachable from the local node (i.e. cloud storage or locally available file). If accepted, we should then return URI checkpoints from Tune if syncing to cloud is enabled. Signed-off-by: Kai Fricke <[email protected]>

def nD(i=None, brute=None, *, n=None, m=None): from sympy.integrals.integrals import integrate from sympy.functions.special.polynomials import laguerre from sympy.abc import x

sympy/functions/combinatorial/numbers.py

sympy

Python

e0dc14eca132f37c5f49369eb4051eae37c9b119

numbers.py

nD

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

Refactored import ordering in functions

def _temperature_unit(self) -> str: if ( weather_option_temperature_unit := self._weather_option_temperature_unit ) is not None: return weather_option_temperature_unit return self._default_temperature_unit

homeassistant/components/weather/__init__.py

core

Python

90e1fb6ce2faadb9a35fdbe1774fce7b4456364f

__init__.py

_temperature_unit

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

Weather unit conversion (#73441) Co-authored-by: Erik <[email protected]>

def set_potential_energy(self, scalar): sympy_deprecation_warning( , deprecated_since_version="1.5", active_deprecations_target="deprecated-set-potential-energy", ) self.potential_energy = scalar

sympy/physics/mechanics/particle.py

sympy

Python

807ed058b5804382971f0045fa1395f087ff12cb

particle.py

set_potential_energy

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

Update the set_potential_energy() deprecation

def verify_request_params(params, headers):

tests/sentry/middleware/test_api_gateway.py

sentry

Python

ec6965d597186ae0ecfba786472154f1c3cb7e42

test_api_gateway.py

verify_request_params

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

feat(api-gateway): Unit test helpers (#39424) These functions will help with the creation of new test cases for the API gateway

def id(self): # type: () -> str

pipenv/patched/notpip/_vendor/distro.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

distro.py

id

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 test_boolean_constraints(self): for field in (BooleanField(), BooleanField(null=True)): with self.subTest(field=field): field.set_attributes_from_name("is_nice") self.assertIn('"IS_NICE" IN (0,1)', field.db_check(connection)) @unittest.skipUnless(connection.vendor == "oracle", "Oracle tests")

tests/backends/oracle/tests.py

@unittest.skipUnless(connection.vendor == "oracle", "Oracle tests")

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_boolean_constraints

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

Refs #33476 -- Reformatted code with Black.

def on_predict_batch_begin(self, batch, logs=None): if self._should_call_predict_batch_hooks: self._call_batch_hook(ModeKeys.PREDICT, "begin", batch, logs=logs)

keras/callbacks.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

callbacks.py

on_predict_batch_begin

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def test_version_managing(self, data_handler): # set up df = pd.DataFrame([ {'a': 1, 'b': dt.datetime(2020, 1, 1)}, {'a': 2, 'b': dt.datetime(2020, 1, 2)}, {'a': 1, 'b': dt.datetime(2020, 1, 3)}, ]) self.set_handler(data_handler, name='pg', tables={'tasks': df}) # ================= retrain cycles ===================== # create folder self.run_sql('create database proj') # -- create model -- self.run_sql( ) self.wait_predictor('proj', 'task_model') assert data_handler().native_query.call_args[0][0] == 'select * from tasks' # tag works in create model ret = self.run_sql('select * from proj.models') assert ret['TAG'][0] == 'first' # use model ret = self.run_sql() assert len(ret) == 3 assert ret.predicted[0] == 42 # -- retrain predictor with tag -- data_handler.reset_mock() self.run_sql( ) self.wait_predictor('proj', 'task_model', {'tag': 'second'}) # get current model ret = self.run_sql('select * from proj.models') # check target assert ret['PREDICT'][0] == 'b' # check label assert ret['TAG'][0] == 'second' # check integration sql assert data_handler().native_query.call_args[0][0] == 'select * from tasks where a=2' # use model ret = self.run_sql() assert ret.predicted[0] == 42 # used model has tag 'second' models = self.get_models() model_id = ret.predictor_id[0] assert models[model_id].label == 'second' # -- retrain again with active=0 -- data_handler.reset_mock() self.run_sql( ) self.wait_predictor('proj', 'task_model', {'tag': 'third'}) ret = self.run_sql('select * from proj.models') # check target is from previous retrain assert ret['PREDICT'][0] == 'b' # use model ret = self.run_sql() # used model has tag 'second' (previous) models = self.get_models() model_id = ret.predictor_id[0] assert models[model_id].label == 'second' # ================ working with inactive versions ================= # run 3st version model and check used model version ret = self.run_sql() models = self.get_models() model_id = ret.predictor_id[0] assert models[model_id].label == 'third' # one-line query model by version ret = self.run_sql('SELECT * from proj.task_model.3 where a=1 and b=2') model_id = ret.predictor_id[0] assert models[model_id].label == 'third' # not existing version with pytest.raises(Exception) as exc_info: self.run_sql( 'SELECT * from proj.task_model.4 where a=1 and b=2', ) assert 'does not exists' in str(exc_info.value) # ================== managing versions ========================= # show models command # Show models <from | in> <project> where <expr> ret = self.run_sql('Show models') assert len(ret) == 1 and ret['NAME'][0] == 'task_model' ret = self.run_sql('Show models from proj') assert len(ret) == 1 and ret['NAME'][0] == 'task_model' ret = self.run_sql('Show models in proj') assert len(ret) == 1 and ret['NAME'][0] == 'task_model' ret = self.run_sql("Show models where name='task_model'") assert len(ret) == 1 and ret['NAME'][0] == 'task_model' ret = self.run_sql("Show models from proj where name='xxx'") assert len(ret) == 0 # ---------------- # See all versions ret = self.run_sql('select * from proj.models_versions') # we have all tags in versions assert set(ret['TAG']) == {'first', 'second', 'third'} # Set active selected version self.run_sql() # get active version ret = self.run_sql('select * from proj.models_versions where active = 1') assert ret['TAG'][0] == 'first' # use active version ? # Delete specific version self.run_sql() # deleted version not in list ret = self.run_sql('select * from proj.models_versions') assert len(ret) == 2 assert 'second' not in ret['TAG'] # try to use deleted version with pytest.raises(Exception) as exc_info: self.run_sql( 'SELECT * from proj.task_model.2 where a=1', ) assert 'does not exists' in str(exc_info.value) # exception with deleting active version with pytest.raises(Exception) as exc_info: self.run_sql() assert 'is not found' in str(exc_info.value) # drop predictor and check model is deleted and no versions self.run_sql('drop predictor proj.task_model') ret = self.run_sql('select * from proj.models') assert len(ret) == 0 ret = self.run_sql('select * from proj.models_versions') assert len(ret) == 0

tests/unit/test_project_structure.py

mindsdb

Python

3f1a5c30c2ccbd78b21f1f41b7dfdfca87bb7135

test_project_structure.py

test_version_managing

https://github.com/mindsdb/mindsdb.git

update and delete model version renaming (predictor->model)

def _compute_interactions(self, node): r # Note: # - Case of no interactions is already captured before function call. # - This is for nodes that are already split and have a # node.split_info.feature_idx. allowed_features = set() interaction_cst_indices = [] for i in node.interaction_cst_indices: if node.split_info.feature_idx in self.interaction_cst[i]: interaction_cst_indices.append(i) allowed_features.update(self.interaction_cst[i]) return ( np.fromiter(allowed_features, dtype=np.uint32, count=len(allowed_features)), interaction_cst_indices, )

sklearn/ensemble/_hist_gradient_boosting/grower.py

scikit-learn

Python

5ceb8a6a031ddff26a7ede413db1b53edb64166a

grower.py

_compute_interactions

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

ENH FEA add interaction constraints to HGBT (#21020) Co-authored-by: Loïc Estève <[email protected]>

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

packages/python/plotly/plotly/graph_objs/sankey/_node.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_node.py

groups

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

switch to black .22

def test_exec_dataflow_runner(self, gcs_hook, dataflow_hook_mock, beam_hook_mock, persist_link_mock): dataflow_config = DataflowConfiguration() self.operator.runner = "DataflowRunner" self.operator.dataflow_config = dataflow_config gcs_provide_file = gcs_hook.return_value.provide_file self.operator.execute(None) job_name = dataflow_hook_mock.build_dataflow_job_name.return_value dataflow_hook_mock.assert_called_once_with( gcp_conn_id=dataflow_config.gcp_conn_id, delegate_to=dataflow_config.delegate_to, poll_sleep=dataflow_config.poll_sleep, impersonation_chain=dataflow_config.impersonation_chain, drain_pipeline=dataflow_config.drain_pipeline, cancel_timeout=dataflow_config.cancel_timeout, wait_until_finished=dataflow_config.wait_until_finished, ) expected_options = { 'project': dataflow_hook_mock.return_value.project_id, 'job_name': job_name, 'staging_location': 'gs://test/staging', 'output': 'gs://test/output', 'labels': {'foo': 'bar', 'airflow-version': TEST_VERSION}, 'region': 'us-central1', } gcs_provide_file.assert_called_once_with(object_url=PY_FILE) persist_link_mock.assert_called_once_with( self.operator, None, expected_options['project'], expected_options['region'], self.operator.dataflow_job_id, ) beam_hook_mock.return_value.start_python_pipeline.assert_called_once_with( variables=expected_options, py_file=gcs_provide_file.return_value.__enter__.return_value.name, py_options=PY_OPTIONS, py_interpreter=PY_INTERPRETER, py_requirements=None, py_system_site_packages=False, process_line_callback=mock.ANY, ) dataflow_hook_mock.return_value.wait_for_done.assert_called_once_with( job_id=self.operator.dataflow_job_id, job_name=job_name, location='us-central1', multiple_jobs=False, project_id=dataflow_config.project_id, ) dataflow_hook_mock.return_value.provide_authorized_gcloud.assert_called_once_with()

tests/providers/apache/beam/operators/test_beam.py

airflow

Python

4a5250774be8f48629294785801879277f42cc62

test_beam.py

test_exec_dataflow_runner

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

Added missing project_id to the wait_for_job (#24020)

def _get_no_faces(self) -> Generator[str, None, None]: self.output_message = "Frames with no faces" for frame in tqdm(cast(List[Dict[str, str]], self._items), desc=self.output_message, leave=False): logger.trace(frame) # type:ignore frame_name = frame["frame_fullname"] if not self._alignments.frame_has_faces(frame_name): logger.debug("Returning: '%s'", frame_name) yield frame_name

tools/alignments/jobs.py

faceswap

Python

e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1

jobs.py

_get_no_faces

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

Alignments Tool - Typing, Documentation + Re-org

def CopyIcons(dstpath, srcpath): if isinstance(srcpath, str): # Just a single string, make it a one-element list. srcpath = [srcpath]

PyInstaller/utils/win32/icon.py

pyinstaller

Python

3aad9af18641aa2181dd86cececc2aeb8a0dba06

icon.py

CopyIcons

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

Icon translation using PIL (#6697) Convert icons into the correct platform dependent format using PIL/Pillow if installed.

def local_ray_callbacks(callbacks=None): global_callbacks = callbacks is None if global_callbacks: callbacks, RayDaskCallback.ray_active = (RayDaskCallback.ray_active, set()) try: yield callbacks or () finally: if global_callbacks: RayDaskCallback.ray_active = callbacks

python/ray/util/dask/callbacks.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

callbacks.py

local_ray_callbacks

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 test_local_media_retention(self) -> None: # Advance 31 days (in seconds) self.reactor.advance(31 * 24 * 60 * 60) # Check that media has been correctly purged. # Local media accessed <30 days ago should still exist. # Remote media should be unaffected. self._assert_if_mxc_uris_purged( purged=[ ( self.hs.config.server.server_name, self.local_not_recently_accessed_media, ), (self.hs.config.server.server_name, self.local_never_accessed_media), ], not_purged=[ (self.hs.config.server.server_name, self.local_recently_accessed_media), (self.remote_server_name, self.remote_recently_accessed_media), (self.remote_server_name, self.remote_not_recently_accessed_media), ], )

tests/rest/media/test_media_retention.py

synapse

Python

2fc787c341ff540e5880932f116498ec0ed7a2c2

test_media_retention.py

test_local_media_retention

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

Add config options for media retention (#12732)

def add_simple_roots(self, root1, root2): alpha = self.simple_roots() if root1 > len(alpha) or root2 > len(alpha): raise ValueError("You've used a root that doesn't exist!") a1 = alpha[root1] a2 = alpha[root2] newroot = [_a1 + _a2 for _a1, _a2 in zip(a1, a2)] return newroot

sympy/liealgebras/root_system.py

sympy

Python

7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c

root_system.py

add_simple_roots

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

Cleanup loops and ranges

def test_get_release_wheel_url(): # This should be a commit for which wheels have already been built for # all platforms and python versions at # `s3://ray-wheels/releases/2.2.0/<commit>/`. test_commits = {"2.2.0": "b6af0887ee5f2e460202133791ad941a41f15beb"} for sys_platform in ["darwin", "linux", "win32"]: for py_version in ray_constants.RUNTIME_ENV_CONDA_PY_VERSIONS: for version, commit in test_commits.items(): if sys_platform == "win32" and py_version == (3, 6): # Windows wheels are not built for py3.6 anymore continue url = get_release_wheel_url(commit, sys_platform, version, py_version) assert requests.head(url).status_code == 200, url

python/ray/tests/test_runtime_env.py

ray

Python

98fef7732852cdb3e9377cd87c1ee1085b894928

test_runtime_env.py

test_get_release_wheel_url

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

[runtime env] Support python 3.10 for runtime_env conda (#30970) Signed-off-by: Archit Kulkarni <[email protected]> conda environments are isolated, so when runtime_env sets up a conda environment it must download the Ray wheel into the conda environment. It must download the wheel that matches the current Python and Ray version running, otherwise there will be incompatibility issues between the workers that use this runtime_env and the other workers and Ray processes. This PR updates the wheel name format logic to support Python 3.10.

def prepare_http01_modules(self) -> None: if self.configurator.conf("handle-modules"): needed_modules = ["rewrite"] if self.configurator.version < (2, 4): needed_modules.append("authz_host") else: needed_modules.append("authz_core") for mod in needed_modules: if mod + "_module" not in self.configurator.parser.modules: self.configurator.enable_mod(mod, temp=True)

certbot-apache/certbot_apache/_internal/http_01.py

certbot

Python

7d9e9a49005de7961e84d2a7c608db57dbab3046

http_01.py

prepare_http01_modules

https://github.com/certbot/certbot.git

Add typing to certbot.apache (#9071) * Add typing to certbot.apache Co-authored-by: Adrien Ferrand <[email protected]>

def to_reader(self, *args, **kwargs): if config.PYARROW_VERSION.major < 8: raise NotImplementedError("`pyarrow>=8.0.0` is required to use this method") return self.table.to_reader(*args, **kwargs)

src/datasets/table.py

datasets

Python

1ea4d091b7a4b83a85b2eeb8df65115d39af3766

table.py

to_reader

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

Fast dataset iter (#5030) * Fast dataset iter * Final improvements + some minor fixes * Update src/datasets/arrow_dataset.py Co-authored-by: Quentin Lhoest <[email protected]> * Address comments Co-authored-by: Quentin Lhoest <[email protected]>

def test_you_must_be_realm_admin(self) -> None: user_profile = self.example_user("hamlet") self.login_user(user_profile) other_realm = do_create_realm(string_id="other", name="other") stream = self.make_stream("other_realm_stream", realm=other_realm) result = self.client_delete("/json/streams/" + str(stream.id)) self.assert_json_error(result, "Invalid stream ID") # Even becoming a realm admin doesn't help us for an out-of-realm # stream. do_change_user_role(user_profile, UserProfile.ROLE_REALM_ADMINISTRATOR, acting_user=None) result = self.client_delete("/json/streams/" + str(stream.id)) self.assert_json_error(result, "Invalid stream ID")

zerver/tests/test_subs.py

zulip

Python

708204290ecebd608a575f76892489a0caad5836

test_subs.py

test_you_must_be_realm_admin

https://github.com/zulip/zulip.git

streams: Capitalize "ID" in invalid stream errors in API. This commit changes the error message from "Invalid stream id" to "Invalid stream ID" for cases where invalid stream IDs are passed to API endpoints to make it consistent with other similar error messages.

def _async_set_dynamic_options(self) -> None: if self.entity_description.ufp_options is not None: return if self.entity_description.key == _KEY_VIEWER: options = [ {"id": item.id, "name": item.name} for item in self.data.api.bootstrap.liveviews.values() ] elif self.entity_description.key == _KEY_DOORBELL_TEXT: default_message = ( self.data.api.bootstrap.nvr.doorbell_settings.default_message_text ) messages = self.data.api.bootstrap.nvr.doorbell_settings.all_messages built_messages = ( {"id": item.type.value, "name": item.text} for item in messages ) options = [ {"id": "", "name": f"Default Message ({default_message})"}, *built_messages, ] elif self.entity_description.key == _KEY_PAIRED_CAMERA: options = [{"id": TYPE_EMPTY_VALUE, "name": "Not Paired"}] for camera in self.data.api.bootstrap.cameras.values(): options.append({"id": camera.id, "name": camera.name}) self._attr_options = [item["name"] for item in options] self._hass_to_unifi_options = {item["name"]: item["id"] for item in options} self._unifi_to_hass_options = {item["id"]: item["name"] for item in options}

homeassistant/components/unifiprotect/select.py

core

Python

a2677983a2924366ea13eab416bf286996a64bdb

select.py

_async_set_dynamic_options

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

Add UniFi Protect select platform (#63337)

def test_safedata(self): self.assertIsInstance( self.encode_decode(mark_safe('<b>Hello Django!</b>')).message, SafeData, ) self.assertNotIsInstance( self.encode_decode('<b>Hello Django!</b>').message, SafeData, )

tests/messages_tests/test_cookie.py

django

Python

efb4478e484ae61c5fc23563d4e9df1f8f49df49

test_cookie.py

test_safedata

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

Fixed #33458 -- Fixed encoding of messages with empty string as extra_tags.

def test_make_tarball_extended(self): self.test_make_tarball('のアーカイブ') # japanese for archive

python3.10.4/Lib/distutils/tests/test_archive_util.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

test_archive_util.py

test_make_tarball_extended

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

add python 3.10.4 for windows

def effect_mandelbrot(size, extent, quality): return Image()._new(core.effect_mandelbrot(size, extent, quality))

src/PIL/Image.py

Pillow

Python

f77aabf28134d93e35ca2d5622759c856333beb9

Image.py

effect_mandelbrot

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

Update Image.py docstrings. Update Image.py file with a typo in effect_mandelbrot method. The Typo was in docstrings of the effect_mandelbrot method in Image module of PIL.

def subprocess_runner(self, runner): prev = self._subprocess_runner self._subprocess_runner = runner try: yield finally: self._subprocess_runner = prev

.venv/lib/python3.8/site-packages/pip/_vendor/pep517/wrappers.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

wrappers.py

subprocess_runner

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

upd; format

def test_recover_start_from_replica_actor_names(serve_instance): # Test failed to deploy with total of 2 replicas, # but first constructor call fails.

python/ray/serve/tests/fault_tolerance_tests/test_controller_recovery.py

ray

Python

09a6e5336ad6ab3c41e4a16e906c778aee2450bc

test_controller_recovery.py

test_recover_start_from_replica_actor_names

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

[Serve][Part2] Migrate the tests to use deployment graph api (#26507)

def get_profile_context() -> ProfileContext: profile_ctx = ProfileContext.get() if not profile_ctx: raise MissingContextError("No profile context found.") return profile_ctx _PROFILE_ENV_LOCK = threading.Lock() @contextmanager

src/prefect/context.py

@contextmanager

prefect

Python

e11fd5aa4905c7c27dbdf6ec49442ee107daebac

context.py

get_profile_context

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

Bug fix for PrefectHQ/orion#1383, contains test

async def test_no_controller_triggers(hass, client, integration): dev_reg = async_get_dev_reg(hass) device = dev_reg.async_get_device( {get_device_id(client.driver, client.driver.controller.nodes[1])} ) assert device assert ( await async_get_device_automations( hass, DeviceAutomationType.TRIGGER, device.id ) == [] )

tests/components/zwave_js/test_device_trigger.py

core

Python

41d5256533ec6ef1c102af0a43c7b7f26b8e06fb

test_device_trigger.py

test_no_controller_triggers

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

Add via_device support to zwave_js (#83219) Co-authored-by: Paulus Schoutsen <[email protected]>

def is_tarfile(name): try: t = open(name) t.close() return True except TarError: return False bltn_open = open open = TarFile.open

pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py

pipenv

Python

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

tarfile.py

is_tarfile

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

Vendor in pip 22.1.2

def fallback_which(command, location=None, allow_global=False, system=False): from .vendor.pythonfinder import Finder if not command: raise ValueError("fallback_which: Must provide a command to search for...") if not isinstance(command, str): raise TypeError(f"Provided command must be a string, received {command!r}") global_search = system or allow_global if location is None: global_search = True finder = Finder(system=False, global_search=global_search, path=location) if is_python_command(command): result = find_python(finder, command) if result: return result result = finder.which(command) if result: return result.path.as_posix() return ""

pipenv/core.py

pipenv

Python

9a3b3ce70621af6f9adaa9eeac9cf83fa149319c

core.py

fallback_which

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

Issue 4993 Add standard pre commit hooks and apply linting. (#4994) * Add .pre-commit-config.yaml to the project and exclude tests (for now). This does not include the MyPy linting that pip does but does include everything else.

def suggested_unit_of_measurement(self) -> str | None: if hasattr(self, "_attr_suggested_unit_of_measurement"): return self._attr_suggested_unit_of_measurement if hasattr(self, "entity_description"): return self.entity_description.suggested_unit_of_measurement return None

homeassistant/components/sensor/__init__.py

core

Python

6979cd95b0fe85c3ee8eca3dbc9881b8d05591e8

__init__.py

suggested_unit_of_measurement

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

Add suggested_unit_of_measurement attribute to sensors (#80638) * Add suggested_unit_of_measurement attribute to sensors * Lazy calculation of initial entity options * Add type alias for entity options * Small tweak * Add tests * Store suggested_unit_of_measurement in its own option key * Adapt to renaming of IMPERIAL_SYSTEM * Fix rebase mistakes * Apply suggestions from code review Co-authored-by: epenet <[email protected]> Co-authored-by: epenet <[email protected]>

def test_ppo_exploration_setup(self): config = copy.deepcopy(ppo.DEFAULT_CONFIG) config["num_workers"] = 0 # Run locally. config["env_config"] = {"is_slippery": False, "map_name": "4x4"} obs = np.array(0) # Test against all frameworks. for fw in framework_iterator(config): # Default Agent should be setup with StochasticSampling. trainer = ppo.PPOTrainer(config=config, env="FrozenLake-v1") # explore=False, always expect the same (deterministic) action. a_ = trainer.compute_single_action( obs, explore=False, prev_action=np.array(2), prev_reward=np.array(1.0) ) # Test whether this is really the argmax action over the logits. if fw != "tf": last_out = trainer.get_policy().model.last_output() if fw == "torch": check(a_, np.argmax(last_out.detach().cpu().numpy(), 1)[0]) else: check(a_, np.argmax(last_out.numpy(), 1)[0]) for _ in range(50): a = trainer.compute_single_action( obs, explore=False, prev_action=np.array(2), prev_reward=np.array(1.0), ) check(a, a_) # With explore=True (default), expect stochastic actions. actions = [] for _ in range(300): actions.append( trainer.compute_single_action( obs, prev_action=np.array(2), prev_reward=np.array(1.0) ) ) check(np.mean(actions), 1.5, atol=0.2) trainer.stop()

rllib/agents/ppo/tests/test_ppo.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

test_ppo.py

test_ppo_exploration_setup

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 pandas_version_info() -> Tuple[int, ...]: return tuple(int(s) for s in pd.__version__.split("."))

src/pandas_profiling/utils/compat.py

ydata-profiling

Python

5c5a710f23d83ba5ff1dc9ab6fc23b28094560fb

compat.py

pandas_version_info

https://github.com/ydataai/ydata-profiling.git

feat: add support for Pandas 1.5 (#1076)

def position_cursor(self) -> Control: if self._shape is not None: _, height = self._shape return Control( ControlType.CARRIAGE_RETURN, (ControlType.ERASE_IN_LINE, 2), *( ( (ControlType.CURSOR_UP, 1), (ControlType.ERASE_IN_LINE, 2), ) * (height - 1) ) ) return Control()

pipenv/patched/notpip/_vendor/rich/live_render.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

live_render.py

position_cursor

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 _exit_buffer(self) -> None: self._buffer_index -= 1 self._check_buffer()

pipenv/patched/notpip/_vendor/rich/console.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

console.py

_exit_buffer

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 is_multiple_state(state_size): return (hasattr(state_size, '__len__') and not isinstance(state_size, tf.TensorShape))

keras/layers/rnn/rnn_utils.py

keras

Python

01c906c4178db5ae03b7eb2d298a052c952a0667

rnn_utils.py

is_multiple_state

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

Reorganize RNN layers, cells and wrappers into smaller logically organized files hosted under an `rnn` directory. PiperOrigin-RevId: 428841673

def remove(self, event, subscriber): subs = self._subscribers if event not in subs: raise ValueError('No subscribers: %r' % event) subs[event].remove(subscriber)

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

util.py

remove

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

upd; format

def _format_ram(self): retval = [] for name in ("total", "available", "used", "free"): value = getattr(self, f"_ram_{name}") value = int(value / (1024 * 1024)) retval.append(f"{name.capitalize()}: {value}MB") return ", ".join(retval)

lib/sysinfo.py

faceswap

Python

48c886b3dce3d3117ad16edaf35c8abd28dc51f5

sysinfo.py

_format_ram

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

Allow decoding errors

def get_holiday(holiday_list, month): holiday_map = frappe._dict() for d in holiday_list: if d: holiday_map.setdefault( d, frappe.db.sql( , (d, month), ), ) return holiday_map @frappe.whitelist()

erpnext/hr/report/monthly_attendance_sheet/monthly_attendance_sheet.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

monthly_attendance_sheet.py

get_holiday

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

style: format code with black

def __sub__(self, other): if self._delegate_binop(other): return NotImplemented return np.subtract(self, other)

numpy/ma/core.py

numpy

Python

6d77c591c59b5678f14ae5af2127eebb7d2415bc

core.py

__sub__

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

ENH: Adding __array_ufunc__ capability to MaskedArrays. This enables any ufunc numpy operations that are called on a MaskedArray to use the masked version of that function automatically without needing to resort to np.ma.func() calls.

def test_build_in_tf_function(self): m = metrics.MeanTensor(dtype=tf.float64)

keras/metrics/base_metric_test.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_metric_test.py

test_build_in_tf_function

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def isatty(self) -> bool: return True

src/textual/app.py

textual

Python

0af9fed65969894d604e32a177120f0a03857265

app.py

isatty

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

added constant, and docstrings

def is_typeddict(tp):

pipenv/patched/notpip/_vendor/typing_extensions.py

"""Check if an annotation is a TypedDict class For example::anFor

pipenv

Python

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

typing_extensions.py

is_typeddict

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

Vendor in pip 22.1.2

def test_cache_with_asterisk_in_name(self): config = { "caches": { "per_cache_factors": {"*cache_a*": 5, "cache_b": 6, "cache_c": 2} } } self.config._environ = { "SYNAPSE_CACHE_FACTOR_CACHE_A": "2", "SYNAPSE_CACHE_FACTOR_CACHE_B": 3, } self.config.read_config(config, config_dir_path="", data_dir_path="") self.config.resize_all_caches() cache_a = LruCache(100) add_resizable_cache("*cache_a*", cache_resize_callback=cache_a.set_cache_factor) self.assertEqual(cache_a.max_size, 200) cache_b = LruCache(100) add_resizable_cache("*Cache_b*", cache_resize_callback=cache_b.set_cache_factor) self.assertEqual(cache_b.max_size, 300) cache_c = LruCache(100) add_resizable_cache("*cache_c*", cache_resize_callback=cache_c.set_cache_factor) self.assertEqual(cache_c.max_size, 200)

tests/config/test_cache.py

synapse

Python

d38d242411b8910dfacde1e61fd3a0ec5cbcaa66

test_cache.py

test_cache_with_asterisk_in_name

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

Reload cache factors from disk on SIGHUP (#12673)

def test_model_tpu_one_core(): trainer = Trainer(tpu_cores=1, fast_dev_run=True, strategy=TPUSpawnStrategy(debug=True)) # assert training strategy attributes for device setting assert isinstance(trainer.strategy, TPUSpawnStrategy) assert not trainer.strategy.on_gpu assert trainer.strategy.on_tpu assert trainer.strategy.root_device == torch.device("xla", index=1) model = BoringModelTPU() trainer.fit(model) assert "PT_XLA_DEBUG" not in os.environ

tests/strategies/test_tpu_spawn.py

lightning

Python

650c710efacd633fa283955145342bb64063c883

test_tpu_spawn.py

test_model_tpu_one_core

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

Rename training plugin test files & names to strategy (#11303)

def test_subscriptions_query_count(self) -> None: user1 = self.example_user("cordelia") user2 = self.example_user("iago") new_streams = [ "query_count_stream_1", "query_count_stream_2", "query_count_stream_3", ] # Test creating a public stream when realm does not have a notification stream. with queries_captured() as queries: self.common_subscribe_to_streams( self.test_user, [new_streams[0]], dict(principals=orjson.dumps([user1.id, user2.id]).decode()), ) self.assert_length(queries, 37) # Test creating private stream. with queries_captured() as queries: self.common_subscribe_to_streams( self.test_user, [new_streams[1]], dict(principals=orjson.dumps([user1.id, user2.id]).decode()), invite_only=True, ) self.assert_length(queries, 36) # Test creating a public stream with announce when realm has a notification stream. notifications_stream = get_stream(self.streams[0], self.test_realm) self.test_realm.notifications_stream_id = notifications_stream.id self.test_realm.save() with queries_captured() as queries: self.common_subscribe_to_streams( self.test_user, [new_streams[2]], dict( announce="true", principals=orjson.dumps([user1.id, user2.id]).decode(), ), ) self.assert_length(queries, 45)

zerver/tests/test_subs.py

zulip

Python

b0de5c0f364632feb1e0a662f9be49aaf3412770

test_subs.py

test_subscriptions_query_count

https://github.com/zulip/zulip.git

streams: Set can_remove_subscribers_group while creating streams. This commit sets can_remove_subscribers_group to admins system group while creating streams as it will be the default value of this setting. In further we would provide an option to set value of this setting to any user group while creating streams using API or UI.

def test_meta_options_as_defaults(self): # this plugin relies on the base CMSPlugin and Model classes to # decide what the app_label and db_table should be plugin = TestPlugin.model self.assertEqual(plugin._meta.db_table, 'meta_testpluginmodel') self.assertEqual(plugin._meta.app_label, 'meta')

cms/tests/test_plugins.py

django-cms

Python

c1290c9ff89cb00caa5469129fd527e9d82cd820

test_plugins.py

test_meta_options_as_defaults

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 to_dict(self, field_map={}) -> Dict: inv_field_map = {v: k for k, v in field_map.items()} _doc: Dict[str, str] = {} for k, v in self.__dict__.items(): # Exclude internal fields (Pydantic, ...) fields from the conversion process if k.startswith("__"): continue if k == "content": # Convert pd.DataFrame to list of rows for serialization if self.content_type == "table" and isinstance(self.content, pd.DataFrame): v = [self.content.columns.tolist()] + self.content.values.tolist() k = k if k not in inv_field_map else inv_field_map[k] _doc[k] = v return _doc

haystack/schema.py

haystack

Python

621e1af74c9c7d04b79ca5f5826ddcc06e1237f0

schema.py

to_dict

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

refactor: improve support for dataclasses (#3142) * refactor: improve support for dataclasses * refactor: refactor class init * refactor: remove unused import * refactor: testing 3.7 diffs * refactor: checking meta where is Optional * refactor: reverting some changes on 3.7 * refactor: remove unused imports * build: manual pre-commit run * doc: run doc pre-commit manually * refactor: post initialization hack for 3.7-3.10 compat. TODO: investigate another method to improve 3.7 compatibility. * doc: force pre-commit * refactor: refactored for both Python 3.7 and 3.9 * docs: manually run pre-commit hooks * docs: run api docs manually * docs: fix wrong comment * refactor: change no type-checked test code * docs: update primitives * docs: api documentation * docs: api documentation * refactor: minor test refactoring * refactor: remova unused enumeration on test * refactor: remove unneeded dir in gitignore * refactor: exclude all private fields and change meta def * refactor: add pydantic comment * refactor : fix for mypy on Python 3.7 * refactor: revert custom init * docs: update docs to new pydoc-markdown style * Update test/nodes/test_generator.py Co-authored-by: Sara Zan <[email protected]>

def _resource_apply_sparse(self, grad, handle, indices, apply_state): raise NotImplementedError( "`_resource_apply_sparse` Must be implemented in subclasses." )

keras/optimizers/optimizer_v2/optimizer_v2.py

keras

Python

be73ac1a1e25d9abd4d793cba9707098d7adf231

optimizer_v2.py

_resource_apply_sparse

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

Add f-string format and lint with flynt on the whole codebase

def on_shutdown(self) -> None:

mkdocs/plugins.py

mkdocs

Python

a56ac6e0513bdea6860ed1fdc3debc10410638cd

plugins.py

on_shutdown

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

Add plugin events that persist across builds in `mkdocs serve` "One-time events" `on_startup(command)`, `on_shutdown`. Their presence also shows that a plugin *wants* to persist across builds. Otherwise they will be re-created, to not change any existing behavior.

def _build_network_on_replica(model, mode, inputs=None, targets=None): # Need to do imports here since we run into a circular dependency error. from keras import models # pylint: disable=g-import-not-at-top from keras.engine import sequential # pylint: disable=g-import-not-at-top # We rely on the internal methods to avoid having share_weights weights in # the public API. if isinstance(model, sequential.Sequential): updated_model = models._clone_sequential_model( model, input_tensors=inputs, layer_fn=models.share_weights ) else: updated_model = models._clone_functional_model( model, input_tensors=inputs, layer_fn=models.share_weights ) # Callable losses added directly to a functional Model need to be added # here. updated_model._callable_losses = model._callable_losses # Recast all low precision outputs back to float32 since we only casted the # inputs to bfloat16 and not targets. This is done so that we can preserve # precision when calculating the loss value.

keras/distribute/distributed_training_utils_v1.py

keras

Python

b1105dca17670dcac229271e63d5073fe445b84c

distributed_training_utils_v1.py

_build_network_on_replica

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

resolve line-too-long in distribute

def _discard_tk_faces(self): keys = [f"{pnt_x}_{pnt_y}" for pnt_x, pnt_y in self._objects.visible_grid[:2].T.reshape(-1, 2)] for key in list(self._tk_faces): if key not in keys: del self._tk_faces[key] logger.trace("keys: %s allocated_faces: %s", keys, len(self._tk_faces))

tools/manual/faceviewer/viewport.py

faceswap

Python

5e73437be47f2410439a3c6716de96354e6a0c94

viewport.py

_discard_tk_faces

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

lib.align updates: - alignments.py - Add typed dicts for imported alignments - Explicitly check for presence of thumb value in alignments dict - linting - detected_face.py - Typing - Linting - Legacy support for pre-aligned face - Update dependencies to new property names

def test_i18n_language_non_english_fallback(self): with self.settings(LANGUAGE_CODE="fr"), translation.override("none"): response = self.client.get(reverse("admin:jsi18n")) self.assertContains(response, "Choisir une heure")

tests/admin_views/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_i18n_language_non_english_fallback

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

Refs #33476 -- Reformatted code with Black.

def name_scope_only_in_function_or_graph(name): if not tf.executing_eagerly(): return tf.name_scope(name) else: return NullContextmanager() @keras_export("keras.optimizers.Optimizer", metaclass=abc.ABCMeta)

keras/optimizers/optimizer_v2/optimizer_v2.py

@keras_export("keras.optimizers.Optimizer", metaclass=abc.ABCMeta)

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

optimizer_v2.py

name_scope_only_in_function_or_graph

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def name(self) -> PurePosixPath: return PurePosixPath(_as_posix(self).split("::")[0]).name

src/datasets/download/streaming_download_manager.py

datasets

Python

ab7d3045ac9154e9c1c2602d0869130defdc6dc7

streaming_download_manager.py

name

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

Support DataLoader with num_workers > 0 in streaming mode (#4375) * make TorchIterableDataset work in parallel - make it picklable - paralellize over the shards when num_workers is passed * start writing some tests * fix streaming extension and fsspec issues in subprocesses * fix some tests * fix more tests * fix import * fix and add tests * fix patch (handle successive patches and builtins) * revert unnecessary change to enriched_web_blg * style * use open locally to fix win permission errors * keep file opened in read_csv * fix compression for read_csv * consistency of read_csv: don't infer compression for file-like objects * stringify Path objects * comments + raise error if sharding is ambiguous * minor * Update src/datasets/iterable_dataset.py Co-authored-by: Mario Šaško <[email protected]> Co-authored-by: Mario Šaško <[email protected]>

def django_table_names(self, only_existing=False, include_views=True): tables = set() for model in self.get_migratable_models(): if not model._meta.managed: continue tables.add(model._meta.db_table) tables.update( f.m2m_db_table() for f in model._meta.local_many_to_many if f.remote_field.through._meta.managed ) tables = list(tables) if only_existing: existing_tables = set(self.table_names(include_views=include_views)) tables = [ t for t in tables if self.identifier_converter(t) in existing_tables ] return tables

django/db/backends/base/introspection.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

introspection.py

django_table_names

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

Refs #33476 -- Reformatted code with Black.

def eulerline(self): if self.is_equilateral(): return self.orthocenter return Line(self.orthocenter, self.circumcenter)

sympy/geometry/polygon.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

polygon.py

eulerline

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

Updated import locations

def itermonthdays2(self, year, month): for i, d in enumerate(self.itermonthdays(year, month), self.firstweekday): yield d, i % 7

python3.10.4/Lib/calendar.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

calendar.py

itermonthdays2

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

add python 3.10.4 for windows

def get_input_shape_and_dtype(layer):

keras/engine/training_utils.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_utils.py

get_input_shape_and_dtype

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def load_workflow_meta(self) -> Optional[WorkflowMetaData]: try: metadata = asyncio_run(self._get(self._key_workflow_metadata(), True)) return WorkflowMetaData(status=WorkflowStatus(metadata["status"])) except KeyNotFoundError: return None

python/ray/workflow/workflow_storage.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

workflow_storage.py

load_workflow_meta

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 _update_code_co_name(self, code): if not hasattr(code, "replace"): # It may not be available on older versions of Python (only # available for 3.8 onwards). return code try: first_real_line = next(dis.findlinestarts(code))[1] except StopIteration: return code return code.replace(co_name="<cell line: %s>" % (first_real_line,))

IPython/core/interactiveshell.py

ipython

Python

d11e987f174a15f1640f8006c86f58d884c3faa4

interactiveshell.py

_update_code_co_name

https://github.com/ipython/ipython.git

Set co_name for cells run line by line. Fixes https://github.com/ipython/ipykernel/issues/841

def send_trial(self, parameters, placement_constraint=None): self.parameters_count += 1 if placement_constraint is None: placement_constraint = { 'type': 'None', 'gpus': [] } self._validate_placement_constraint(placement_constraint) new_trial = { 'parameter_id': self.parameters_count, 'parameters': parameters, 'parameter_source': 'algorithm', 'placement_constraint': placement_constraint } _logger.debug('New trial sent: %s', new_trial) try: send_payload = nni.dump(new_trial, pickle_size_limit=int(os.getenv('PICKLE_SIZE_LIMIT', 64 * 1024))) except PayloadTooLarge: raise ValueError( 'Serialization failed when trying to dump the model because payload too large (larger than 64 KB). ' 'This is usually caused by pickling large objects (like datasets) by mistake. ' 'See the full error traceback for details and https://nni.readthedocs.io/en/stable/NAS/Serialization.html ' 'for how to resolve such issue. ' ) # trial parameters can be super large, disable pickle size limit here # nevertheless, there could still be blocked by pipe / nni-manager send(CommandType.NewTrialJob, send_payload) if self.send_trial_callback is not None: self.send_trial_callback(parameters) # pylint: disable=not-callable return self.parameters_count

nni/retiarii/integration.py

nni

Python

d5ed88e4e7f9aa78f06922dce8219a82e3b52682

integration.py

send_trial

https://github.com/microsoft/nni.git

Retiarii serializer user experience improvements (#4437)

async def dry_run(self, empty, context) -> jina_pb2.StatusProto: from docarray import DocumentArray, Document from jina.serve.executors import __dry_run_endpoint__ da = DocumentArray([Document()]) try:

jina/serve/runtimes/gateway/grpc/gateway.py

async def dry_run(self, empty, context) -> jina_pb2.StatusProto: """ Process the call requested by having a dry run call to every Executor in the graph :param empty: The service expects an empty protobuf message :param context: grpc context :returns: the response request """ from docarray import DocumentArray, Document from jina.serve.executors import __dry_run_endpoint__ da = DocumentArray([Document()]) try:

jina

Python

e143ea3092ebae68f8c2cf7f784f86296cae68d7

gateway.py

dry_run

https://github.com/jina-ai/jina.git

refactor: use stream_docs from streamer (#5438)

def get_yaxis_transform(self, which='grid'): if which == 'grid': return self._yaxis_transform elif which == 'tick1': # for cartesian projection, this is bottom spine return self.spines.left.get_spine_transform() elif which == 'tick2': # for cartesian projection, this is top spine return self.spines.right.get_spine_transform() else: raise ValueError(f'unknown value for which: {which!r}')

lib/matplotlib/axes/_base.py

matplotlib

Python

bf3a554ccd1299bc260647029811758aeaf577b1

_base.py

get_yaxis_transform

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

Add tests, improve error messages, and use argument checks to simplify code

def get_rfq_containing_supplier(doctype, txt, searchfield, start, page_len, filters): conditions = "" if txt: conditions += "and rfq.name like '%%" + txt + "%%' " if filters.get("transaction_date"): conditions += "and rfq.transaction_date = '{0}'".format(filters.get("transaction_date")) rfq_data = frappe.db.sql( f, { "page_len": page_len, "start": start, "company": filters.get("company"), "supplier": filters.get("supplier"), }, as_dict=1, ) return rfq_data

erpnext/buying/doctype/request_for_quotation/request_for_quotation.py

erpnext

Python

34e4903ed7936c35176d6031a16d1a27654dcb40

request_for_quotation.py

get_rfq_containing_supplier

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

refactor: search queries (#33004) - guard clauses for readability - use values or format

async def async_update(self): # Check if device is disconnected. if not self._attr_available: # Try to connect if await self.aftv.adb_connect(log_errors=self._failed_connect_count == 0): self._failed_connect_count = 0 self._attr_available = True else: self._failed_connect_count += 1 # If the ADB connection is not intact, don't update. if not self.available: return # Get the updated state and attributes. ( state, self._attr_app_id, running_apps, _, self._attr_is_volume_muted, self._attr_volume_level, self._attr_extra_state_attributes[ATTR_HDMI_INPUT], ) = await self.aftv.update(self._get_sources) self._attr_state = ANDROIDTV_STATES.get(state) if self._attr_state is None: self._attr_available = False if running_apps: self._attr_source = self._attr_app_name = self._app_id_to_name.get( self._attr_app_id, self._attr_app_id ) sources = [ self._app_id_to_name.get( app_id, app_id if not self._exclude_unnamed_apps else None ) for app_id in running_apps ] self._attr_source_list = [source for source in sources if source] else: self._attr_source_list = None

homeassistant/components/androidtv/media_player.py

core

Python

0df30782a623204be2941da74ddee5bb110dd03b

media_player.py

async_update

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

Bump androidtv to 0.0.67 (improve connect attempt logging) (#69721)

def euler_poly(n, x=None, polys=False): return appell_poly(n, [[1], [1, QQ(-1,2)]], 1, lambda p, i: -p / 2, QQ, x, polys) @public

sympy/polys/appellseqs.py

@public

sympy

Python

e875bdb804b0285e4a9bd8de0158436e792c03cb

appellseqs.py

euler_poly

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

Initial definition of Appell sequences

def _get_output_folder(self) -> str: if self._is_video and self._type == "frames": return os.path.dirname(self._source_dir) return self._source_dir

tools/alignments/jobs.py

faceswap

Python

e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1

jobs.py

_get_output_folder

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

Alignments Tool - Typing, Documentation + Re-org

def update_cached_response(self, request, response): cache_url = self.cache_url(request.url) cached_response = self.serializer.loads(request, self.cache.get(cache_url)) if not cached_response: # we didn't have a cached response return response # Lets update our headers with the headers from the new request: # http://tools.ietf.org/html/draft-ietf-httpbis-p4-conditional-26#section-4.1 # # The server isn't supposed to send headers that would make # the cached body invalid. But... just in case, we'll be sure # to strip out ones we know that might be problmatic due to # typical assumptions. excluded_headers = ["content-length"] cached_response.headers.update( dict( (k, v) for k, v in response.headers.items() if k.lower() not in excluded_headers ) ) # we want a 200 b/c we have content via the cache cached_response.status = 200 # update our cache self._cache_set(cache_url, request, cached_response) return cached_response

pipenv/patched/notpip/_vendor/cachecontrol/controller.py

pipenv

Python

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

controller.py

update_cached_response

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

Vendor in pip 22.1.2

def remote(self, *args, **kwargs): # Delayed import to avoid a cyclic import from ray.util.client.common import remote_decorator if len(args) == 1 and len(kwargs) == 0 and callable(args[0]): # This is the case where the decorator is just @ray.remote. return remote_decorator(options=None)(args[0]) error_string = ( "The @ray.remote decorator must be applied either " "with no arguments and no parentheses, for example " "'@ray.remote', or it must be applied using some of " "the arguments 'num_returns', 'num_cpus', 'num_gpus', " "'memory', 'object_store_memory', 'resources', " "'max_calls', or 'max_restarts', like " "'@ray.remote(num_returns=2, " 'resources={"CustomResource": 1})\'.' ) assert len(args) == 0 and len(kwargs) > 0, error_string return remote_decorator(options=kwargs) # TODO(mwtian): consider adding _internal_ prefix to call_remote / # call_release / call_retain.

python/ray/util/client/api.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

api.py

remote

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 process_struct(fileobj): (key_id,) = struct.unpack("Q", fileobj.read(8)) (country_code,) = struct.unpack("2s", fileobj.read(2)) (recognized,) = struct.unpack("b", fileobj.read(1)) (timestamp,) = struct.unpack("I", fileobj.read(4)) (n_strokes,) = struct.unpack("H", fileobj.read(2)) drawing = [] for _ in range(n_strokes): (n_points,) = struct.unpack("H", fileobj.read(2)) fmt = str(n_points) + "B" x = struct.unpack(fmt, fileobj.read(n_points)) y = struct.unpack(fmt, fileobj.read(n_points)) drawing.append({"x": list(x), "y": list(y)}) return { "key_id": str(key_id), "recognized": recognized, "timestamp": datetime.fromtimestamp(timestamp), "countrycode": country_code.decode("utf-8"), "drawing": drawing, }

datasets/quickdraw/quickdraw.py

datasets

Python

1c1eaf96d5ef4623e36c9124d49e88ab476dd655

quickdraw.py

process_struct

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

Add QuickDraw dataset (#3592) * Add QuickDraw dataset * Style * Add infos file, dummy data, improve script * Add info and dummy data * Test readme * Finish readme * Delete generate_dummy.py * Remove whitespace

def convert_x_to_bbox(x, score=None): w = np.sqrt(x[2] * x[3]) h = x[2] / w if (score == None): return np.array( [x[0] - w / 2., x[1] - h / 2., x[0] + w / 2., x[1] + h / 2.]).reshape((1, 4)) else: score = np.array([score]) return np.array([ x[0] - w / 2., x[1] - h / 2., x[0] + w / 2., x[1] + h / 2., score ]).reshape((1, 5))

deploy/pptracking/python/mot/tracker/ocsort_tracker.py

PaddleDetection

Python

c84153a355d9855fe55cf51d203b8b24e7d884e5

ocsort_tracker.py

convert_x_to_bbox

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

[MOT] Add OC_SORT tracker (#6272) * add ocsort tracker * add ocsort deploy * merge develop * fix ocsort tracker codes * fix doc, test=document_fix * fix doc, test=document_fix

def multiply(inputs, **kwargs): return Multiply(**kwargs)(inputs)

keras/layers/merging/multiply.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

multiply.py

multiply

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def export_model(self): return self.tuner.get_best_model()

autokeras/auto_model.py

autokeras

Python

b97d27d2e916025f65fed751d54c089d4d4bd022

auto_model.py

export_model

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

clean up imports

def async_remove_legacy_device_serial_numbers(self) -> None: _LOGGER.debug( "Removing legacy serial numbers from device registry entries for pairing %s", self.unique_id, ) device_registry = dr.async_get(self.hass) for accessory in self.entity_map.accessories: identifiers = { ( IDENTIFIER_ACCESSORY_ID, f"{self.unique_id}:aid:{accessory.aid}", ) } legacy_serial_identifier = ( IDENTIFIER_SERIAL_NUMBER, accessory.serial_number, ) device = device_registry.async_get_device(identifiers=identifiers) if not device or legacy_serial_identifier not in device.identifiers: continue device_registry.async_update_device(device.id, new_identifiers=identifiers)

homeassistant/components/homekit_controller/connection.py

core

Python

f23b1750e85f07091eb896a0b12b8f95e5646338

connection.py

async_remove_legacy_device_serial_numbers

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

Migrate HomeKit Controller to use stable identifiers (#80064)

def test_print_args(self): args_list = [ 'tests/tests.csv', '-is', ',' ] args = self.parser.parse_args(args_list) with captured_output() as (out, err): _print_args(args) output = out.getvalue() expected_output = self.assertEqual(_sort_lines(expected_output), _sort_lines(output))

tests/driver_tests.py

tpot

Python

388616b6247ca4ea8de4e2f340d6206aee523541

driver_tests.py

test_print_args

https://github.com/EpistasisLab/tpot.git

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

def crash_log(): original_traceback = traceback.format_exc().encode("utf-8") path = os.path.dirname(os.path.realpath(sys.argv[0])) filename = os.path.join(path, datetime.now().strftime("crash_report.%Y.%m.%d.%H%M%S%f.log")) freeze_log = [line.encode("utf-8") for line in _DEBUG_BUFFER] try: from lib.sysinfo import sysinfo # pylint:disable=import-outside-toplevel except Exception: # pylint:disable=broad-except sysinfo = ("\n\nThere was an error importing System Information from lib.sysinfo. This is " f"probably a bug which should be fixed:\n{traceback.format_exc()}") with open(filename, "wb") as outfile: outfile.writelines(freeze_log) outfile.write(original_traceback) outfile.write(sysinfo.encode("utf-8")) return filename _OLD_FACTORY = logging.getLogRecordFactory()

lib/logger.py

faceswap

Python

afec52309326304f4323029039e49bfcf928ef43

logger.py

crash_log

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

Bugfixes: - Stats graph - Handle NaNs in data - logger - de-elevate matplotlib font messages

def remap_palette(self, dest_map, source_palette=None): from . import ImagePalette if self.mode not in ("L", "P"): raise ValueError("illegal image mode") if source_palette is None: if self.mode == "P": self.load() source_palette = self.im.getpalette("RGB")[:768] else: # L-mode source_palette = bytearray(i // 3 for i in range(768)) palette_bytes = b"" new_positions = [0] * 256 # pick only the used colors from the palette for i, oldPosition in enumerate(dest_map): palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3] new_positions[oldPosition] = i # replace the palette color id of all pixel with the new id # Palette images are [0..255], mapped through a 1 or 3 # byte/color map. We need to remap the whole image # from palette 1 to palette 2. New_positions is # an array of indexes into palette 1. Palette 2 is # palette 1 with any holes removed. # We're going to leverage the convert mechanism to use the # C code to remap the image from palette 1 to palette 2, # by forcing the source image into 'L' mode and adding a # mapping 'L' mode palette, then converting back to 'L' # sans palette thus converting the image bytes, then # assigning the optimized RGB palette. # perf reference, 9500x4000 gif, w/~135 colors # 14 sec prepatch, 1 sec postpatch with optimization forced. mapping_palette = bytearray(new_positions) m_im = self.copy() m_im.mode = "P" m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3) # possibly set palette dirty, then # m_im.putpalette(mapping_palette, 'L') # converts to 'P' # or just force it. # UNDONE -- this is part of the general issue with palettes m_im.im.putpalette("RGB;L", m_im.palette.tobytes()) m_im = m_im.convert("L") # Internally, we require 768 bytes for a palette. new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00" m_im.putpalette(new_palette_bytes) m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes) if "transparency" in self.info: m_im.info["transparency"] = new_positions[self.info["transparency"]] return m_im

src/PIL/Image.py

Pillow

Python

46a80d144a16836af304a7aaa8e620962d91ac23

Image.py

remap_palette

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

Update transparency when remapping the palette

def decode(self, buffer): raise NotImplementedError()

src/PIL/ImageFile.py

Pillow

Python

a0e1fde1eddf45f26653e2ff6080d31e177adbec

ImageFile.py

decode

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

Added PyEncoder

def DeveloperAPI(obj): _mark_annotated(obj) return obj

rllib/utils/annotations.py

ray

Python

55d039af320caaab7fe11d404585bd402e66d393

annotations.py

DeveloperAPI

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

Annotate datasources and add API annotation check script (#24999) Why are these changes needed? Add API stability annotations for datasource classes, and add a linter to check all data classes have appropriate annotations.

def upsample_2d(x, k=None, factor=2, gain=1): r assert isinstance(factor, int) and factor >= 1 if k is None: k = [1] * factor k = np.asarray(k, dtype=np.float32) if k.ndim == 1: k = np.outer(k, k) k /= np.sum(k) k = k * (gain * (factor**2)) p = k.shape[0] - factor return upfirdn2d_native(x, paddle.to_tensor(k), up=factor, pad=((p + 1) // 2 + factor - 1, p // 2))

modules/image/text_to_image/stable_diffusion/diffusers/models/resnet.py

PaddleHub

Python

a6790a651a12eb391060e533868bf0ba197f6f7e

resnet.py

upsample_2d

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

Add stable diffusion module

def revert(self): if self._backup: self.set_state(self._backup) self._backup = None

mitmproxy/flow.py

mitmproxy

Python

b3587b52b25077f68116b9852b041d33e7fc6601

flow.py

revert

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

make it black!

def homogeneity_completeness_v_measure(labels_true, labels_pred, *, beta=1.0): labels_true, labels_pred = check_clusterings(labels_true, labels_pred) if len(labels_true) == 0: return 1.0, 1.0, 1.0 entropy_C = entropy(labels_true) entropy_K = entropy(labels_pred) contingency = contingency_matrix(labels_true, labels_pred, sparse=True) MI = mutual_info_score(None, None, contingency=contingency) homogeneity = MI / (entropy_C) if entropy_C else 1.0 completeness = MI / (entropy_K) if entropy_K else 1.0 if homogeneity + completeness == 0.0: v_measure_score = 0.0 else: v_measure_score = ( (1 + beta) * homogeneity * completeness / (beta * homogeneity + completeness) ) return homogeneity, completeness, v_measure_score

sklearn/metrics/cluster/_supervised.py

scikit-learn

Python

1ac8ea14847cad8bec5ac49a01013beef4361f79

_supervised.py

homogeneity_completeness_v_measure

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

DOC Ensure homogeneity_completeness_v_measure passes numpydoc validation (#23942)

def leaf_symbols(self) -> Iterable[Symbol]: for arg in self.arguments: if isinstance(arg, SymbolicExpression): yield from arg.leaf_symbols()

nni/mutable/symbol.py

nni

Python

8f454f3bf29e2c3cd0d359231a46edd8ee768d42

symbol.py

leaf_symbols

https://github.com/microsoft/nni.git

Mutable V3 (Stage 2) - Symbolic execution engine (#5195)

def get_existing_payment_request_amount(ref_dt, ref_dn): existing_payment_request_amount = frappe.db.sql( , (ref_dt, ref_dn), ) return flt(existing_payment_request_amount[0][0]) if existing_payment_request_amount else 0

erpnext/accounts/doctype/payment_request/payment_request.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

payment_request.py

get_existing_payment_request_amount

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

style: format code with black

def argsort(self, axis=0, kind="quicksort", order=None) -> Series: values = self._values mask = isna(values) if mask.any(): result = np.full(len(self), -1, dtype=np.intp) notmask = ~mask result[notmask] = np.argsort(values[notmask], kind=kind) else: result = np.argsort(values, kind=kind) res = self._constructor(result, index=self.index, name=self.name, dtype=np.intp) return res.__finalize__(self, method="argsort")

pandas/core/series.py

pandas

Python

244f747bb63f45c1c439193f0672c6162853b168

series.py

argsort

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

make series axis parameter docs consistent (#47109) * make series docs consistent add series unused param info to DF docs * fix trailing whitespace * fix docs build * add unused * add or update docs for all series methods * small fix * fix line length * fix param order * fix param order * add * add backticks to None and fix space Co-authored-by: uncjackg <[email protected]>

async def test_get_image_disabled(hass): patch_key, entity_id, config_entry = _setup(CONFIG_ANDROIDTV_DEFAULT) config_entry.add_to_hass(hass) hass.config_entries.async_update_entry( config_entry, options={CONF_SCREENCAP: False} ) with patchers.patch_connect(True)[patch_key], patchers.patch_shell( SHELL_RESPONSE_OFF )[patch_key]: assert await hass.config_entries.async_setup(config_entry.entry_id) await hass.async_block_till_done() with patchers.patch_shell("11")[patch_key]: await async_update_entity(hass, entity_id) media_player_name = "media_player." + slugify( CONFIG_ANDROIDTV_DEFAULT[TEST_ENTITY_NAME] ) state = hass.states.get(media_player_name) assert "entity_picture_local" not in state.attributes assert "entity_picture" not in state.attributes

tests/components/androidtv/test_media_player.py