Datasets:

semeru

/

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

like 0

def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1): self.load() if method is None: # defaults: method = Quantize.MEDIANCUT if self.mode == "RGBA": method = Quantize.FASTOCTREE if self.mode == "RGBA" and method not in ( Quantize.FASTOCTREE, Quantize.LIBIMAGEQUANT, ): # Caller specified an invalid mode. raise ValueError( "Fast Octree (method == 2) and libimagequant (method == 3) " "are the only valid methods for quantizing RGBA images" ) if palette: # use palette from reference image palette.load() if palette.mode != "P": raise ValueError("bad mode for palette image") if self.mode != "RGB" and self.mode != "L": raise ValueError( "only RGB or L mode images can be quantized to a palette" ) im = self.im.convert("P", dither, palette.im) new_im = self._new(im) new_im.palette = palette.palette.copy() return new_im im = self._new(self.im.quantize(colors, method, kmeans)) from . import ImagePalette mode = im.im.getpalettemode() palette = im.im.getpalette(mode, mode)[: colors * len(mode)] im.palette = ImagePalette.ImagePalette(mode, palette) return im

src/PIL/Image.py

Pillow

Python

f8e4e9c2dd94c6f4789639dd891b8a6d5fb16e14

Image.py

quantize

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

Added enums

def dummy_inputs(self) -> Dict[str, tf.Tensor]: VISION_DUMMY_INPUTS = tf.random.uniform(shape=(3, self.config.num_channels, 224, 224), dtype=tf.float32) return {"pixel_values": tf.constant(VISION_DUMMY_INPUTS)} RESNET_START_DOCSTRING = r RESNET_INPUTS_DOCSTRING = r @keras_serializable

src/transformers/models/resnet/modeling_tf_resnet.py

@keras_serializable

transformers

Python

77ea5130a1cd7de36796cc4d1bae6f21094d8863

modeling_tf_resnet.py

dummy_inputs

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

Add TF ResNet model (#17427) * Rought TF conversion outline * Tidy up * Fix padding differences between layers * Add back embedder - whoops * Match test file to main * Match upstream test file * Correctly pass and assign image_size parameter Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * Add in MainLayer * Correctly name layer * Tidy up AdaptivePooler * Small tidy-up More accurate type hints and remove whitespaces * Change AdaptiveAvgPool Use the AdaptiveAvgPool implementation by @Rocketknight1, which correctly pools if the output shape does not evenly divide by input shape c.f. https://github.com/huggingface/transformers/pull/17554/files/9e26607e22aa8d069c86b50196656012ff0ce62a#r900109509 Co-authored-by: From: matt <rocketknight1@gmail.com> Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * Use updated AdaptiveAvgPool Co-authored-by: matt <rocketknight1@gmail.com> * Make AdaptiveAvgPool compatible with CPU * Remove image_size from configuration * Fixup * Tensorflow -> TensorFlow * Fix pt references in tests * Apply suggestions from code review - grammar and wording Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Add TFResNet to doc tests * PR comments - GlobalAveragePooling and clearer comments * Remove unused import * Add in keepdims argument * Add num_channels check * grammar fix: by -> of Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> * Remove transposes - keep NHWC throughout forward pass * Fixup look sharp * Add missing layer names * Final tidy up - remove from_pt now weights on hub Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

def __reduce__(self) -> Tuple[Any, Any, Any]: pickled_state = super(FeatureArray, self).__reduce__() if isinstance(pickled_state, str): raise TypeError("np array __reduce__ returned string instead of tuple.") new_state = pickled_state[2] + ( self.number_of_dimensions, self.is_sparse, self.units, ) return pickled_state[0], pickled_state[1], new_state

rasa/utils/tensorflow/model_data.py

rasa

Python

4cdceaab5271a5b51463ec562c8eb55f96b771c5

model_data.py

__reduce__

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

Bump numpy from 1.19.5 to 1.21.6 (#11078) * Bump numpy from 1.19.5 to 1.21.6 Bumps [numpy](https://github.com/numpy/numpy) from 1.19.5 to 1.21.6. - [Release notes](https://github.com/numpy/numpy/releases) - [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst.txt) - [Commits](https://github.com/numpy/numpy/compare/v1.19.5...v1.21.6) --- updated-dependencies: - dependency-name: numpy dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> * fixed mypy errors for numpy 1.21.6 upgrade * removed duplicate np.array call Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Thomas Werkmeister <thomas@werkmeister.me> Co-authored-by: melindaloubser1 <melinda.loubser@gmail.com>

def test_key_query_cancellation(self) -> None: self.register_user("alice", "wonderland") alice_token = self.login("alice", "wonderland") bob = self.register_user("bob", "uncle") channel = make_request_with_cancellation_test( "test_key_query_cancellation", self.reactor, self.site, "POST", "/_matrix/client/r0/keys/query", { "device_keys": { # Empty list means we request keys for all bob's devices bob: [], }, }, token=alice_token, ) self.assertEqual(200, channel.code, msg=channel.result["body"]) self.assertIn(bob, channel.json_body["device_keys"])

tests/rest/client/test_keys.py

synapse

Python

d3d9ca156e323fe194b1bcb1af1628f65a2f3c1c

test_keys.py

test_key_query_cancellation

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

Cancel the processing of key query requests when they time out. (#13680)

def test_normal_operation(self, ray_instance):

python/ray/serve/tests/test_standalone2.py

ray

Python

700618d0dbd27282ce72441d22a0000075b7a54f

test_standalone2.py

test_normal_operation

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

[Serve] Add the `SERVE_REQUEST_PROCESSING_TIMEOUT_S` environment variable (#29534)

async def test_slug(hass, caplog): result = slug(hass, "http://127.0.0.2/testurl/{{1/0}}") assert result is None assert "Syntax error in" in caplog.text @respx.mock

tests/components/generic/test_config_flow.py

@respx.mock

core

Python

e64336cb91d1ce97ac82c57e98477acedfcbcf71

test_config_flow.py

test_slug

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

Allow configuring username and password in generic camera config flow (#73804) * Add ability to use user & pw not in stream url * Increase test coverage to 100% * Increase test coverage * Verify that stream source includes user:pass * Code review: refactor test to use MockConfigEntry * Code review: Improve test docstring * Edit comment; retrigger CI. Co-authored-by: Dave T <davet2001@users.noreply.github.com>

def _get_text_feature_max_length(config, training_set_metadata) -> int: max_length = 0 for feature in config["input_features"]: if feature["type"] == TEXT: feature_max_len = training_set_metadata[feature["name"]]["word_max_sequence_length"] if feature_max_len > max_length: max_length = feature_max_len if ( ("preprocessing" in config) and (TEXT in config["preprocessing"]) and ("word_sequence_length_limit" in config["preprocessing"][TEXT]) ): limit = config["preprocessing"][TEXT]["word_sequence_length_limit"] else: limit = 256 # Preprocessing default word_sequence_length_limit = 256 if max_length > limit + 2: # For start and stop symbols. max_length = limit + 2 return max_length

ludwig/automl/auto_tune_config.py

ludwig

Python

d77aaf8da39f04a353a3a08fb699ae8a96ffea3a

auto_tune_config.py

_get_text_feature_max_length

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

Improve AutoML heuristics for text classification (#1815) * Improve AutoML heuristics for text classification Co-authored-by: Anne Holler <anne@vmware.com>

async def wait(self) -> None: if self._is_set: return if not self._loop: self._loop = get_running_loop() self._event = asyncio.Event() await self._event.wait()

src/prefect/_internal/concurrency/primitives.py

prefect

Python

a368874d1b145c1ec5201e5efd3c26ce7c1e8611

primitives.py

wait

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

Add thread-safe async primitives `Event` and `Future` (#7865) Co-authored-by: Serina Grill <42048900+serinamarie@users.noreply.github.com>

def generic_parser(parse_func, *cols) -> np.ndarray: warnings.warn( "Use pd.to_datetime instead.", FutureWarning, stacklevel=find_stack_level(inspect.currentframe()), ) N = _check_columns(cols) results = np.empty(N, dtype=object) for i in range(N): args = [c[i] for c in cols] results[i] = parse_func(*args) return results

pandas/io/date_converters.py

pandas

Python

6787b8b73f4c54a0cf742a90433e6fb6c7edb231

date_converters.py

generic_parser

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

TST: Address/catch more test warnings (#48358)

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

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

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_layout.py

computed

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

switch to black .22

def profile(event_type, extra_data=None): if not PROFILING_ENABLED: return NULL_LOG_SPAN worker = ray.worker.global_worker if worker.mode == ray.worker.LOCAL_MODE: return NULL_LOG_SPAN return worker.core_worker.profile_event(event_type.encode("ascii"), extra_data)

python/ray/_private/profiling.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

profiling.py

profile

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 mathieu_even_coef(m, q): r if not (isscalar(m) and isscalar(q)): raise ValueError("m and q must be scalars.") if (q < 0): raise ValueError("q >=0") if (m != floor(m)) or (m < 0): raise ValueError("m must be an integer >=0.") if (q <= 1): qm = 7.5 + 56.1*sqrt(q) - 134.7*q + 90.7*sqrt(q)*q else: qm = 17.0 + 3.1*sqrt(q) - .126*q + .0037*sqrt(q)*q km = int(qm + 0.5*m) if km > 251: warnings.warn("Too many predicted coefficients.", RuntimeWarning, 2) kd = 1 m = int(floor(m)) if m % 2: kd = 2 a = mathieu_a(m, q) fc = _specfun.fcoef(kd, m, q, a) return fc[:km]

scipy/special/_basic.py

scipy

Python

4871f3d1c61bdb296ae03e3480f5f584f5c67256

_basic.py

mathieu_even_coef

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

MAINT: optimize, special, signal: Use custom warnings instead of print statements (#15259) Co-authored-by: Pamphile Roy <roy.pamphile@gmail.com> Co-authored-by: Tirth Patel <tirthasheshpatel@gmail.com>

def prefetch_renditions(self, *filters): # Get a list of filter spec strings. The given value could contain Filter objects filter_specs = [ filter.spec if isinstance(filter, Filter) else filter for filter in filters ] rendition_model = self.model.get_rendition_model() return self.prefetch_related( models.Prefetch( "renditions", queryset=rendition_model.objects.filter(filter_spec__in=filter_specs), to_attr="prefetched_renditions", ) )

wagtail/images/models.py

wagtail

Python

52ace9eae7311fa708dd19a7d6b6cabfb36a8fee

models.py

prefetch_renditions

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

Add prefetch_renditions method on Image queryset manager Update logic when creating and looking for a rendtion

def test_dataset_shard_with_loader_fn(self): dset = ray.data.range(100) config = {"input": "dataset", "input_config": {"loader_fn": lambda: dset}} ret_dataset, _ = get_dataset_and_shards(config) assert ret_dataset.count() == dset.count()

rllib/offline/tests/test_dataset_reader.py

ray

Python

569fe0109629048d08e1d9e023f7769f10bd2244

test_dataset_reader.py

test_dataset_shard_with_loader_fn

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

[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)

def _preprocess_conv3d_input(x, data_format): tf_data_format = "NDHWC" if data_format == "channels_first": if not _has_nchw_support(): x = tf.compat.v1.transpose(x, (0, 2, 3, 4, 1)) else: tf_data_format = "NCDHW" return x, tf_data_format

keras/backend.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

_preprocess_conv3d_input

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

async def test_get_application_credentials(hass): test_1_integration = _get_test_integration(hass, "test_1", True) test_2_integration = _get_test_integration_with_application_credentials( hass, "test_2" ) with patch("homeassistant.loader.async_get_custom_components") as mock_get: mock_get.return_value = { "test_1": test_1_integration, "test_2": test_2_integration, } application_credentials = await loader.async_get_application_credentials(hass) assert "test_2" in application_credentials assert "test_1" not in application_credentials

tests/test_loader.py

core

Python

ae01ec02e28d4b83ef64636e36de2baf59c19874

test_loader.py

test_get_application_credentials

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

Allow custom integrations to support application_credentials platform (#71129)

def start_reaper_process(self): assert ( not self.kernel_fate_share ), "a reaper should not be used with kernel fate-sharing" process_info = ray._private.services.start_reaper(fate_share=False) assert ray_constants.PROCESS_TYPE_REAPER not in self.all_processes if process_info is not None: self.all_processes[ray_constants.PROCESS_TYPE_REAPER] = [ process_info, ]

python/ray/node.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

node.py

start_reaper_process

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 get_best_result(self) -> Tuple[int, Module, Dict[str, Dict[str, Tensor]], float, List[Dict]]: raise NotImplementedError()

nni/compression/pytorch/base/scheduler.py

nni

Python

d68c786ff81bad19c04619d6a999ff34aaa724e7

scheduler.py

get_best_result

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

[Compression] remove pruning v1 & refactor directory (#5228)

def register(cls, function, *call_args, **call_kwds):

modin/core/dataframe/algebra/map.py

modin

Python

a6f47c8e1c27d85fc09926bb35c2f1a65a6d3e79

map.py

register

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

REFACTOR-#4942: remove call method in favor of register due to duplication (#4943) Signed-off-by: Myachev <anatoly.myachev@intel.com>

def test_product_types_query_ids_not_exists(user_api_client, category): query = NOT_EXISTS_IDS_COLLECTIONS_QUERY variables = {"filter": {"ids": ["fTEJRuFHU6fd2RU=", "2XwnQNNhwCdEjhP="]}} response = user_api_client.post_graphql(query, variables) content = get_graphql_content(response, ignore_errors=True) message_error = '{"ids": [{"message": "Invalid ID specified.", "code": ""}]}' assert len(content["errors"]) == 1 assert content["errors"][0]["message"] == message_error assert content["data"]["productTypes"] is None QUERY_FILTER_PRODUCT_TYPES = @pytest.mark.parametrize( "search, expected_names", ( ("", ["The best juices", "The best beers", "The worst beers"]), ("best", ["The best juices", "The best beers"]), ("worst", ["The worst beers"]), ("average", []), ), )

saleor/graphql/product/tests/queries/test_product_types_query.py

@pytest.mark.parametrize( "search, expected_names", ( ("", ["The best juices", "The best beers", "The worst beers"]), ("best", ["The best juices", "The best beers"]), ("worst", ["The worst beers"]), ("average", []), ), )

saleor

Python

d90be220d6b687d08153934a51354011a3cb5ca1

test_product_types_query.py

test_product_types_query_ids_not_exists

https://github.com/saleor/saleor.git

Split test_product.py and test_variant.py into multiple files (#11173) * Split test_product.py into multiple files * Split test_variant.py into multiple files

def script_args(f): args = [ magic_arguments.argument( '--out', type=str, help= ), magic_arguments.argument( '--err', type=str, help= ), magic_arguments.argument( '--bg', action="store_true", help= ), magic_arguments.argument( '--proc', type=str, help= ), magic_arguments.argument( '--no-raise-error', action="store_false", dest='raise_error', help= ) ] for arg in args: f = arg(f) return f @magics_class

IPython/core/magics/script.py

@magics_class

ipython

Python

ce62a7a4b2c97bf8a30e8074e8fc18103a0718a0

script.py

script_args

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

avoid deprecated get_event_loop use our own `async_helpers.get_asyncio_loop` to track the global event loop script magics use dedicated background asyncio loop instead of trying to work on the main loop, which may or may not exist _AsyncIOProxy wraps background script objects to transfer awaitables across loops only works for coroutine methods, which might be good enough? Works for read, etc.

def _descendants_with_perm(self, user, action): # Get the permission object corresponding to this action permission = self._get_permission_objects_for_actions([action]).first() # Get the collections that have a GroupCollectionPermission record # for this permission and any of the user's groups; # create a list of their paths collection_roots = Collection.objects.filter( group_permissions__group__in=user.groups.all(), group_permissions__permission=permission, ).values("path", "depth") if collection_roots: # build a filter expression that will filter our model to just those # instances in collections with a path that starts with one of the above # but excluding the collection on which permission was granted collection_path_filter = Q( path__startswith=collection_roots[0]["path"] ) & Q(depth__gt=collection_roots[0]["depth"]) for collection in collection_roots[1:]: collection_path_filter = collection_path_filter | ( Q(path__startswith=collection["path"]) & Q(depth__gt=collection["depth"]) ) return Collection.objects.all().filter(collection_path_filter) else: # no matching collections return Collection.objects.none()

wagtail/core/permission_policies/collections.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

collections.py

_descendants_with_perm

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

Reformat with black

def queryables(self) -> dict[str, Any]: # mypy doesn't recognize DataFrame._AXIS_NAMES, so we re-write it here axis_names = {0: "index", 1: "columns"} # compute the values_axes queryables d1 = [(a.cname, a) for a in self.index_axes] d2 = [(axis_names[axis], None) for axis, values in self.non_index_axes] d3 = [ (v.cname, v) for v in self.values_axes if v.name in set(self.data_columns) ] return dict(d1 + d2 + d3)

pandas/io/pytables.py

pandas

Python

050b3b815604652bc445d2487f6e1fc83eaa8d1f

pytables.py

queryables

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

TYP: Upgrade mypy to 0.981 (#48871) Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>

def get_tables(self) -> HandlerResponse: query = return self.native_query(query)

mindsdb/integrations/handlers/postgres_handler/postgres_handler.py

mindsdb

Python

f105dbf028004044995817384413b4cdffd7afe2

postgres_handler.py

get_tables

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

handlers

def decode_locale_str(x): # type: (bytes) -> str return x.decode(encoding=locale.getlocale()[1] or "utf-8", errors="replace")

scapy/utils.py

scapy

Python

664f5985c24c2eb7645bf76327bd333fab5f92b4

utils.py

decode_locale_str

https://github.com/secdev/scapy.git

Automata: improve memory management (#3743) * Automata memory improvements (cleanup..) * Add docstrings

def label0(self): return self["label0"]

packages/python/plotly/plotly/graph_objs/_funnelarea.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_funnelarea.py

label0

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

switch to black .22

def spreadsheet(self) -> Spreadsheet: return self.client.open_by_key(self.spreadsheet_id)

airbyte-integrations/connectors/destination-google-sheets/destination_google_sheets/spreadsheet.py

airbyte

Python

feb0d2f37803929a1ad0c723eea430f8cd6c201f

spreadsheet.py

spreadsheet

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

🎉 New Destination: Implement `Destination Google Sheets` using CDK (#12135)

def require_sentencepiece(test_case): return unittest.skipUnless(is_sentencepiece_available(), "test requires SentencePiece")(test_case)

src/transformers/testing_utils.py

transformers

Python

57e6464ac9a31156f1c93e59107323e6ec01309e

testing_utils.py

require_sentencepiece

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

Update all require decorators to use skipUnless when possible (#16999)

def test_migrate_plugin(self): project2 = self.create_project( name="hellbar", organization=self.organization, teams=[self.team] ) plugin2 = JiraPlugin() plugin2.set_option("enabled", True, project2) plugin2.set_option("default_project", "BAR", project2) plugin2.set_option("instance_url", "https://example.atlassian.net", project2) group = self.create_group(message="Hello world", culprit="foo.bar") plugin_issue = GroupMeta.objects.create( key=f"{self.plugin.slug}:tid", group_id=group.id, value="SEN-1" ) group2 = self.create_group(message="Hello world", culprit="foo.bar") plugin2_issue = GroupMeta.objects.create( key=f"{self.plugin.slug}:tid", group_id=group2.id, value="BAR-1" ) org_integration = OrganizationIntegration.objects.get(integration_id=self.integration.id) org_integration.config.update({"issues_ignored_fields": ["reporter", "test"]}) org_integration.save() with self.tasks(): self.installation.migrate_issues() assert ExternalIssue.objects.filter( organization_id=self.organization.id, integration_id=self.integration.id, key=plugin_issue.value, ).exists() assert ExternalIssue.objects.filter( organization_id=self.organization.id, integration_id=self.integration.id, key=plugin2_issue.value, ).exists() assert not GroupMeta.objects.filter( key=f"{self.plugin.slug}:tid", group_id=group.id, value="SEN-1" ).exists() assert not GroupMeta.objects.filter( key=f"{self.plugin.slug}:tid", group_id=group.id, value="BAR-1" ).exists() oi = OrganizationIntegration.objects.get(integration_id=self.integration.id) assert len(oi.config["issues_ignored_fields"]) == 4 assert self.plugin.get_option("enabled", self.project) is False assert plugin2.get_option("enabled", project2) is False

tests/sentry/integrations/jira/test_integration.py

sentry

Python

f5e5a3b1ed97383e0699aff9eb0363e9eb5db479

test_integration.py

test_migrate_plugin

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

feat(Jira): Plugin issue migration endpoint (#37577) * feat(jira): Plugin issue migration endpoint

def inspect(): profile = prefect.context.get_profile_context() name, env = profile.name, profile.env console.out(toml.dumps({name: env}).strip()) @profile_app.command()

src/prefect/cli/profile.py

@profile_app.command()

prefect

Python

cb7814344ff2e34bafbd3a0c78e1c1ff41bb74c8

profile.py

inspect

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

Add `prefect profile set/unset/inspect/ls`

def downgrade(): conn = op.get_bind() if conn.dialect.name == 'sqlite': op.execute('PRAGMA foreign_keys=OFF') with op.batch_alter_table('ab_view_menu', schema=None) as batch_op: batch_op.drop_constraint('ab_view_menu_name_uq', type_='unique') op.execute('PRAGMA foreign_keys=ON') elif conn.dialect.name == 'mysql': with op.batch_alter_table('ab_user', schema=None) as batch_op: batch_op.alter_column('email', existing_type=sa.String(256), nullable=True) batch_op.alter_column('username', existing_type=sa.String(256), nullable=True, unique=True) with op.batch_alter_table('ab_register_user', schema=None) as batch_op: batch_op.alter_column('email', existing_type=sa.String(256), nullable=True) batch_op.alter_column('username', existing_type=sa.String(256), nullable=True, unique=True) elif conn.dialect.name == 'mssql': with op.batch_alter_table('ab_register_user') as batch_op: # Drop the unique constraint on username and email constraints = get_mssql_table_constraints(conn, 'ab_register_user') for k, _ in constraints.get('UNIQUE').items(): batch_op.drop_constraint(k, type_='unique') batch_op.alter_column('username', existing_type=sa.String(256), nullable=False, unique=True) batch_op.create_unique_constraint(None, ['username']) batch_op.alter_column('email', existing_type=sa.String(256), nullable=False, unique=True) with op.batch_alter_table('ab_user') as batch_op: # Drop the unique constraint on username and email constraints = get_mssql_table_constraints(conn, 'ab_user') for k, _ in constraints.get('UNIQUE').items(): batch_op.drop_constraint(k, type_='unique') batch_op.alter_column('username', existing_type=sa.String(256), nullable=True) batch_op.create_unique_constraint(None, ['username']) batch_op.alter_column('email', existing_type=sa.String(256), nullable=True, unique=True) batch_op.create_unique_constraint(None, ['email'])

airflow/migrations/versions/0106_909884dea523_update_migration_for_fab_tables_to_add_missing_constraints.py

airflow

Python

2f5a567977e1219cab16c2548825a1b9eba07ab3

0106_909884dea523_update_migration_for_fab_tables_to_add_missing_constraints.py

downgrade

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

Use Airflow.Base.metadata in FAB models (#22353) Since FAB models are now in airflow, it makes sense to monitor changes in them. Therefore we use Airflow.models.base.Base.metadata for FAB models

def post_display_hook(self) -> None:

src/textual/app.py

textual

Python

39a764f49fff7ec3363b8ea25fce3fbf1b67ca58

app.py

post_display_hook

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

call later

def approx_standard_normal_cdf(x): return 0.5 * (1.0 + paddle.tanh(np.sqrt(2.0 / np.pi) * (x + 0.044715 * paddle.pow(x, 3))))

modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/losses.py

PaddleHub

Python

f4d6e64cdc132ae868699a0ba442f4ab1d304a14

losses.py

approx_standard_normal_cdf

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

add disco_diffusion_cnclip_vitb16 module

def print_help(self): has_portfolio_start = "" if "Delta" in self.greeks["Portfolio"] else "[unvl]" has_portfolio_end = "" if "Delta" in self.greeks["Portfolio"] else "[/unvl]" has_option_start = ( "" if "Delta" in self.greeks["Option A"] or "Delta" in self.greeks["Option B"] else "[unvl]" ) has_option_end = ( "" if "Delta" in self.greeks["Option A"] or "Delta" in self.greeks["Option B"] else "[/unvl]" ) help_text = f console.print(text=help_text, menu="Stocks - Options - Hedge")

openbb_terminal/stocks/options/hedge/hedge_controller.py

OpenBBTerminal

Python

54a1b6f545a0016c576e9e00eef5c003d229dacf

hedge_controller.py

print_help

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

Feature/hedge (#1768) * [Bug] Incorrect log for reddit keys. #1733 fix * Create new feature-hedge * Significantly improve code of hedge menu * More robust * Robustness * Fix tests * Fix can't multiply sequence by non-int of type 'numpy.float64' error * Temporary fix of singular matrix error. Return first feasible solution * Update Hugo Documentation * Combining menus and cleaning up code * Tidy up call_exp * Update tests Round 1 * Update tests Round 2 * Fix linting error * Fix linting? * Fixed glitch Co-authored-by: JerBouma <jer.bouma@gmail.com> Co-authored-by: James Maslek <jmaslek11@gmail.com> Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: colin99d <colin99delahunty@gmail.com> Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>

def with_attribute(*args, **attr_dict): <div> Some text <div type="grid">1 4 0 1 0</div> <div type="graph">1,3 2,3 1,1</div> <div>this has no type</div> </div> if args: attrs = args[:] else: attrs = attr_dict.items() attrs = [(k, v) for k, v in attrs]

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

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

actions.py

with_attribute

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 architecture_optimizers(self): opts = self.optimizers() if isinstance(opts,list): # pylint: disable=unsubscriptable-object arc_opts = opts[:self.arc_optim_count] if len(arc_opts) == 1: arc_opts = arc_opts[0] return arc_opts # If there is only 1 optimizer and it is the architecture optimizer if self.arc_optim_count == 1: return opts return None

nni/retiarii/oneshot/pytorch/base_lightning.py

nni

Python

8b2eb425274cdb4537fbce4a315aec12a378d6db

base_lightning.py

architecture_optimizers

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

Lightning implementation for retiarii oneshot nas (#4479)

def test_avatar_allowed_mime_type_global(self): self._setup_local_files( { "good": {"mimetype": "image/png"}, "bad": {"mimetype": "application/octet-stream"}, } ) channel = self.make_request( "PUT", f"/profile/{self.owner}/avatar_url", content={"avatar_url": "mxc://test/bad"}, access_token=self.owner_tok, ) self.assertEqual(channel.code, 403, channel.result) self.assertEqual( channel.json_body["errcode"], Codes.FORBIDDEN, channel.json_body ) channel = self.make_request( "PUT", f"/profile/{self.owner}/avatar_url", content={"avatar_url": "mxc://test/good"}, access_token=self.owner_tok, ) self.assertEqual(channel.code, 200, channel.result)

tests/rest/client/test_profile.py

synapse

Python

bf60da1a60096fac5fb778b732ff2214862ac808

test_profile.py

test_avatar_allowed_mime_type_global

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 _distribution_strategy_scope(self): if self._distribution_strategy and not tf.distribute.has_strategy(): with self._distribution_strategy.scope(): yield self._distribution_strategy.scope() else: yield

keras/optimizers/optimizer_v2/optimizer_v2.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

optimizer_v2.py

_distribution_strategy_scope

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def classify_sysode(eq, funcs=None, **kwargs): r # Sympify equations and convert iterables of equations into # a list of equations

sympy/solvers/ode/ode.py

sympy

Python

65be461082dda54c8748922f9c29a19af1279fe1

ode.py

classify_sysode

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

Remove abbreviations in documentation

def header_store_parse(self, name, value): raise NotImplementedError

python3.10.4/Lib/email/_policybase.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_policybase.py

header_store_parse

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

add python 3.10.4 for windows

async def async_update(self): get_result = await getCmd( *self._request_args, ObjectType(ObjectIdentity(self._baseoid)) ) errindication, errstatus, errindex, restable = await get_result if errindication and not self._accept_errors: _LOGGER.error("SNMP error: %s", errindication) elif errstatus and not self._accept_errors: _LOGGER.error( "SNMP error: %s at %s", errstatus.prettyPrint(), errindex and restable[-1][int(errindex) - 1] or "?", ) elif (errindication or errstatus) and self._accept_errors: self.value = self._default_value else: for resrow in restable: self.value = resrow[-1].prettyPrint()

homeassistant/components/snmp/sensor.py

core

Python

d9903c4cf985381002de8b923815b05dd24e0651

sensor.py

async_update

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

Bump `brother` and `pysnmplib` (#84107) * Bump brother version * Bump pysnmplib version * Update sensor platform * Update switch platform * Update tests * Bump brother Co-authored-by: J. Nick Koston <nick@koston.org>

def update_df(self, df): if get_current_execution() != "PandasOnRay" or ( not isinstance(df._query_compiler._modin_frame, PandasOnRayDataframe) ): # pragma: no cover ErrorMessage.not_implemented( "Batch Pipeline API is only implemented for `PandasOnRay` execution." ) self.df = df

modin/experimental/batch/pipeline.py

modin

Python

3d4404e9d9a9b2a3327f8aee664a8e71ac1f18b8

pipeline.py

update_df

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

FEAT-#4412: Add Batch Pipeline API to Modin (#4452) Co-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru> Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com> Signed-off-by: Rehan Durrani <rehan@ponder.io>

def forward(self, pred3d, pred2d, inputs): gt_3d_joints = inputs['joints_3d'] gt_2d_joints = inputs['joints_2d'] has_3d_joints = inputs['has_3d_joints'] has_2d_joints = inputs['has_2d_joints'] loss_3d = mpjpe(pred3d, gt_3d_joints, has_3d_joints) loss_2d = keypoint_2d_loss(self.criterion_2dpose, pred2d, gt_2d_joints, has_2d_joints) return self.weight_3d * loss_3d + self.weight_2d * loss_2d

ppdet/modeling/losses/pose3d_loss.py

PaddleDetection

Python

d4e34fe165c09db65fd00113708be1b711ac957c

pose3d_loss.py

forward

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

pose3d metro modeling (#6612) * pose3d metro modeling * delete extra comments

def swapaxes(self, axis1, axis2, copy=True): # noqa: PR01, RT01, D200 axis1 = self._get_axis_number(axis1) axis2 = self._get_axis_number(axis2) if axis1 != axis2: return self.transpose() if copy: return self.copy() return self

modin/pandas/base.py

modin

Python

605efa618e7994681f57b11d04d417f353ef8d50

base.py

swapaxes

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

DOCS-#3099: Fix `BasePandasDataSet` docstrings warnings (#4333) Co-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru> Signed-off-by: Alexander Myskov <alexander.myskov@intel.com>

def test_shortlatex(capfd, hello_world_f90, monkeypatch): ipath = Path(hello_world_f90) mname = "blah" monkeypatch.setattr( sys, "argv", f'f2py -m {mname} {ipath} --latex-doc --short-latex'.split(), ) with util.switchdir(ipath.parent): f2pycli() out, _ = capfd.readouterr() assert "Documentation is saved to file" in out with Path(f"./{mname}module.tex").open() as otex: assert "\\documentclass" not in otex.read()

numpy/f2py/tests/test_f2py2e.py

numpy

Python

729ad4f92420231e2a7009b3223c6c7620b8b808

test_f2py2e.py

test_shortlatex

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

TST: Initialize f2py2e tests of the F2PY CLI (#20668) Increases F2PY coverage by around 15 percent. For the CLI itself it covers the major features (around 70 percent), with the exception of mostly numpy.distutils stuff. More importantly, sets the groundwork for #20056, in that passing the same testsuite should indicate feature parity.

def inset_axes(self, bounds, *, transform=None, zorder=5, **kwargs): if transform is None: transform = self.transAxes kwargs.setdefault('label', 'inset_axes') # This puts the rectangle into figure-relative coordinates. inset_locator = _TransformedBoundsLocator(bounds, transform) bounds = inset_locator(self, None).bounds projection_class, pkw = self.figure._process_projection_requirements( bounds, **kwargs) inset_ax = projection_class(self.figure, bounds, zorder=zorder, **pkw) # this locator lets the axes move if in data coordinates. # it gets called in `ax.apply_aspect() (of all places) inset_ax.set_axes_locator(inset_locator) self.add_child_axes(inset_ax) return inset_ax

lib/matplotlib/axes/_axes.py

matplotlib

Python

80e672e0700fa8a268aed1bdefedbd0e493e91a7

_axes.py

inset_axes

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

enable Axes subclass creation by Axes.inset_axes

def test_no_access(self): member = self.create_user("hernando@life.com") self.create_member(user=member, organization=self.organization, role="member") self.login_as(member) self.get_error_response(self.organization.slug, status=status.HTTP_403_FORBIDDEN) admin = self.create_user("sean@life.com") self.create_member(user=admin, organization=self.organization, role="admin") self.login_as(admin) self.get_success_response(self.organization.slug, status=status.HTTP_200_OK)

tests/sentry/api/endpoints/test_organization_codeowners_associations.py

sentry

Python

5efa5eeb57ae6ddf740256e08ce3b9ff4ec98eaa

test_organization_codeowners_associations.py

test_no_access

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

feat(codeowners): Add endpoint to view code owner associations per organization (#31030) See API-2186 So the earlier version of this PR just had the endpoint return the entire serialized ProjectCodeOwners for an organization. While that works, the intention behind this feature is to read and use the associations, so sending the raw codeowners file, and timestamps are unnecessary and increase the latency with such large payloads, especially for larger orgs. @NisanthanNanthakumar suggested limiting what the endpoint returns to just what the feature will need on the frontend, and making the endpoint name a bit more specific. OrganizationCodeOwners -> OrganizationCodeOwnersAssocations. Along with this refactor, tests have been updated.

def predict_proba(self, X): check_is_fitted(self) y_pred = self.final_estimator_.predict_proba(self.transform(X)) if isinstance(self._label_encoder, list): # Handle the multilabel-indicator cases y_pred = np.array([preds[:, 0] for preds in y_pred]).T return y_pred

sklearn/ensemble/_stacking.py

scikit-learn

Python

c18460f78441f11b3e6c15c12238695fcfe3c872

_stacking.py

predict_proba

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

EHN Add multilabel classification support for `StackingClassifier` (#24146) * Add stacking multilabel functionality * Add underscore to a class attr * Remove model from base estimator in test_stacking * Remove scale in train/test split in test_stacking_classifier_multilabel * Add stack_method as a test parameter, change RandomForestClassifier to KNeighborsClassifier in test * Update Changelog * fix doc typos * predict_proba output will be concatenate this list in an array of shape n_samples, n_outputs * n_classes - 1. Update test. * Update sklearn/ensemble/_stacking.py Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * Update doc/whats_new/v1.0.rst Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * update whats_new * add passthrough test * update whats_new with current PR * Apply suggestions from code review Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> * update tests * Apply suggestion to update comments on `concatenate` Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> * parametrized the two tests into one * parametrized the two tests into one * strip the mysterious trailing _r * fix multilabel list scenario * add Guillaume's recommendations * add test for * some fix * split tests * fix flake8 * add suggestions * Trigger CI * remove multiclass-multioutput from comments and docstrings Co-authored-by: Nicolas <nicolas.peretti@fligoo.com> Co-authored-by: Nestor Navarro <nestornav@gmail.com> Co-authored-by: Nestor Navarro <nestor.navarro@mercadolibre.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>

def test_worker_stdout(): script =

python/ray/tests/test_output.py

script = """@ray.remote

ray

Python

2da2ac52ce3103ddb5192e7a161fec312dcdad53

test_output.py

test_worker_stdout

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

Unskipped test_worker_stdout (#21708)

def incidence_matrix(G, nodelist=None, edgelist=None, oriented=False, weight=None): import scipy as sp import scipy.sparse # call as sp.sparse if nodelist is None: nodelist = list(G) if edgelist is None: if G.is_multigraph(): edgelist = list(G.edges(keys=True)) else: edgelist = list(G.edges()) A = sp.sparse.lil_array((len(nodelist), len(edgelist))) node_index = {node: i for i, node in enumerate(nodelist)} for ei, e in enumerate(edgelist): (u, v) = e[:2] if u == v: continue # self loops give zero column try: ui = node_index[u] vi = node_index[v] except KeyError as err: raise nx.NetworkXError( f"node {u} or {v} in edgelist but not in nodelist" ) from err if weight is None: wt = 1 else: if G.is_multigraph(): ekey = e[2] wt = G[u][v][ekey].get(weight, 1) else: wt = G[u][v].get(weight, 1) if oriented: A[ui, ei] = -wt A[vi, ei] = wt else: A[ui, ei] = wt A[vi, ei] = wt return A.asformat("csc")

networkx/linalg/graphmatrix.py

networkx

Python

8a325d26aa7fdd3a72580c4720fa97f971bbefcb

graphmatrix.py

incidence_matrix

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

Use scipy.sparse array datastructure (#6037) * Use scipy.sparse array datastructure * Add reminder to rm wrapper when scipy adds creation fns. * Rm mention of np matrix from code comment. * Update networkx/algorithms/bipartite/matrix.py Co-authored-by: Stefan van der Walt <sjvdwalt@gmail.com> Co-authored-by: Ross Barnowski <rossbar@berkeley.edu> Co-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>

def save_or_write_to_kafka(self): from sentry.region_to_control.producer import produce_audit_log_entry produce_audit_log_entry(self)

src/sentry/models/auditlogentry.py

sentry

Python

941184cd24186324fd9f7f304b7f713041834726

auditlogentry.py

save_or_write_to_kafka

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

chore(hybrid-cloud): AuditLogEntry is a control silo model now (#39890) In the control silo, creating an audit log entry writes to the db directly, whilst in region silo mode creating an audit log entry will instead push to a new kafka producer that consumes into the control silo asynchronously.

def open_metadata(self, book, custom_columns): if config.config_use_google_drive: if not gdriveutils.is_gdrive_ready(): raise Exception('Google Drive is configured but not ready') web_content_link = gdriveutils.get_metadata_backup_via_gdrive(book.path) if not web_content_link: raise Exception('Google Drive cover url not found') stream = None try: stream = urlopen(web_content_link) except Exception as ex: # Bubble exception to calling function self.log.debug('Error reading metadata.opf: ' + str(ex)) # ToDo Check whats going on raise ex finally: if stream is not None: stream.close() else: # ToDo: Handle book folder not found or not readable book_metadata_filepath = os.path.join(config.config_calibre_dir, book.path, 'metadata.opf') #if not os.path.isfile(book_metadata_filepath): self.create_new_metadata_backup(book, custom_columns, book_metadata_filepath) # else:

cps/tasks/metadata_backup.py

calibre-web

Python

26be5ee2372b08c2f906661283a12e84d6c181f8

metadata_backup.py

open_metadata

https://github.com/janeczku/calibre-web.git

Backup metadata 3rd step

def proxyauth(self, user): name = 'PROXYAUTH' return self._simple_command('PROXYAUTH', user)

python3.10.4/Lib/imaplib.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

imaplib.py

proxyauth

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

add python 3.10.4 for windows

def copy_m2m_relationships(obj1, obj2, fields, kwargs=None): for field_name in fields: if hasattr(obj1, field_name): try: field_obj = obj1._meta.get_field(field_name) except FieldDoesNotExist: continue if isinstance(field_obj, ManyToManyField): # Many to Many can be specified as field_name src_field_value = getattr(obj1, field_name) if kwargs and field_name in kwargs: override_field_val = kwargs[field_name] # TODO: Should we spike this our or just put the for loop inside the next if and make everything respect order? if field_name == 'instance_groups': # instance_groups are a list but we need to preserve the order for ig_id in override_field_val: getattr(obj2, field_name).add(ig_id) continue if isinstance(override_field_val, (set, list, QuerySet)): getattr(obj2, field_name).add(*override_field_val) continue if override_field_val.__class__.__name__ == 'ManyRelatedManager': src_field_value = override_field_val dest_field = getattr(obj2, field_name) dest_field.add(*list(src_field_value.all().values_list('id', flat=True)))

awx/main/utils/common.py

awx

Python

33c0fb79d66f56374d7c042ba79887faa85e2885

common.py

copy_m2m_relationships

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

JT param everything (#12646) * Making almost all fields promptable on job templates and config models * Adding EE, IG and label access checks * Changing jobs preferred instance group function to handle the new IG cache field * Adding new ask fields to job template modules * Address unit/functional tests * Adding migration file

def keypoint_rotate(keypoint, angle, rows, cols, **params): center = (cols - 1) * 0.5, (rows - 1) * 0.5 matrix = cv2.getRotationMatrix2D(center, angle, 1.0) x, y, a, s = keypoint[:4] x, y = cv2.transform(np.array([[[x, y]]]), matrix).squeeze() return x, y, a + math.radians(angle), s @preserve_channel_dim

albumentations/augmentations/geometric/functional.py

@preserve_channel_dim

albumentations

Python

557b7b44b393d0701413ed8012a920a0691e06cb

functional.py

keypoint_rotate

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

Fix Affine wrong rotation angle (#1091) * Fix Affine wrong rotation angle * Link to issue * Fix Perspective rot. angle for keypoints, fix Affine * Change angle sign, do not change it manually after all changes * Tests * Fix tests and image center * Fix shift_rotate tests Co-authored-by: Eugene Khvedchenya <ekhvedchenya@gmail.com> Co-authored-by: Vladimir Iglovikov <ternaus@users.noreply.github.com>

def disable_memoization() -> None: ParserElement.reset_cache() ParserElement._left_recursion_enabled = False ParserElement._packratEnabled = False ParserElement._parse = ParserElement._parseNoCache

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

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

core.py

disable_memoization

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 scale(image, factor, resample=Image.Resampling.BICUBIC): if factor == 1: return image.copy() elif factor <= 0: raise ValueError("the factor must be greater than 0") else: size = (round(factor * image.width), round(factor * image.height)) return image.resize(size, resample)

src/PIL/ImageOps.py

Pillow

Python

f8e4e9c2dd94c6f4789639dd891b8a6d5fb16e14

ImageOps.py

scale

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

Added enums

def get_all(self, name, failobj=None): values = [] name = name.lower() for k, v in self._headers: if k.lower() == name: values.append(self.policy.header_fetch_parse(k, v)) if not values: return failobj return values

python3.10.4/Lib/email/message.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

message.py

get_all

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

add python 3.10.4 for windows

def get_error_message(subscriber, num=1e6, error_type=None, timeout=20): deadline = time.time() + timeout msgs = [] while time.time() < deadline and len(msgs) < num: _, error_data = subscriber.poll(timeout=deadline - time.time()) if not error_data: # Timed out before any data is received. break if error_type is None or error_type == error_data.type: msgs.append(error_data) else: time.sleep(0.01) return msgs

python/ray/_private/test_utils.py

ray

Python

391901f86bc0bec6d3199ac05f316a05bcc4b910

test_utils.py

get_error_message

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

[Remove Redis Pubsub 2/n] clean up remaining Redis references in gcs_utils.py (#23233) Continue to clean up Redis and other related Redis references, for - gcs_utils.py - log_monitor.py - `publish_error_to_driver()`

def socket(self): return self.sock # Utility methods

python3.10.4/Lib/imaplib.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

imaplib.py

socket

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

add python 3.10.4 for windows

def path_to_string(path): if isinstance(path, os.PathLike): return os.fspath(path) return path

keras/utils/io_utils.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

io_utils.py

path_to_string

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def creatable_subpage_models(cls): return [ page_model for page_model in cls.allowed_subpage_models() if page_model.is_creatable ]

wagtail/core/models/__init__.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

__init__.py

creatable_subpage_models

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

Reformat with black

def set_full_path(self) -> None: self.full_path = Path( self.config["user_data_dir"] / "models" / f"{self.freqai_info['identifier']}" ) self.full_path.mkdir(parents=True, exist_ok=True)

freqtrade/freqai/freqai_interface.py

freqtrade

Python

5ee3b8cbbb89c8a57cb42cc3253001e47720991b

freqai_interface.py

set_full_path

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

update config recording to use all configs, fix tests

def get_template(self, template_name): template, origin = self.find_template(template_name) if not hasattr(template, "render"): # template needs to be compiled template = Template(template, origin, template_name, engine=self) return template

django/template/engine.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

engine.py

get_template

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

Refs #33476 -- Reformatted code with Black.

def get_roi_rel_points_test(self, mask_pred, pred_label, cfg): num_points = cfg.subdivision_num_points uncertainty_map = get_uncertainty(mask_pred, pred_label) num_rois, _, mask_height, mask_width = uncertainty_map.shape # During ONNX exporting, the type of each elements of 'shape' is # `Tensor(float)`, while it is `float` during PyTorch inference. if isinstance(mask_height, torch.Tensor): h_step = 1.0 / mask_height.float() w_step = 1.0 / mask_width.float() else: h_step = 1.0 / mask_height w_step = 1.0 / mask_width # cast to int to avoid dynamic K for TopK op in ONNX mask_size = int(mask_height * mask_width) uncertainty_map = uncertainty_map.view(num_rois, mask_size) num_points = min(mask_size, num_points) point_indices = uncertainty_map.topk(num_points, dim=1)[1] xs = w_step / 2.0 + (point_indices % mask_width).float() * w_step ys = h_step / 2.0 + (point_indices // mask_width).float() * h_step point_coords = torch.stack([xs, ys], dim=2) return point_indices, point_coords

mmdet/models/roi_heads/mask_heads/mask_point_head.py

mmdetection

Python

7d1ce22e3328ba89c11b6cdaafff6c96d9da3f4f

mask_point_head.py

get_roi_rel_points_test

https://github.com/open-mmlab/mmdetection.git

Fix `pointrend` missing `get_uncertainty` function bug (#7550) * [Fix] Adjust the order of get_classes and FileClient. (#7276) * delete -sv (#7277) Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> * [Docs] Add Chinese version of finetune (#7178) * [Fix] Fix wrong img name in onnx2tensorrt.py (#7157) * [Docs] fix albumentations installed way (#7143) * Update finetune.md Translate the finetune.md doc to Chinese * Update finetune.md * Update finetune.md * Update finetune.md * fix lint * fx lint * fix pr Co-authored-by: Jamie <jamiechoi1995@users.noreply.github.com> Co-authored-by: BigDong <yudongwang@tju.edu.cn> * set unmap_results=True in ssd_head (#7328) * Update YOLOX log for non square input (#7235) * [Enhance] add cpu_num in cocopanoptic for pq computing (#7315) * add cpu_num in cocopanoptic for pq computing * cpu_num -> nproc * move nproc to evaluate * [Enhancement] Allow to set channel_order in LoadImageFromFile (#7258) * allow to set channel_order when loading images * fix lint * fix unit test * fix lint * [Fix] Force the inputs of `get_bboxes` in yolox_head to float32. (#7324) * Fix softnms bug * Add force_fp32 in corner_head and centripetal_head * [Fix] Fix typo in FPN neck (#7347) * update readme and pretrained related (#7301) * [Docs] Add Chinese version of onnx2tensorrt.md (#7219) * Fix bug of docs * translate onnx2tensorrt.md * fix * fix end-of-file-fixer * fix some bugs * 修复链接跳转 * 修复链接跳转 * 修复链接跳转-测试1 * 修复链接跳转-测试2 * 修复链接跳转-测试2 * 修复链接跳转-测试3 * 修复链接跳转-测试5 * Fix Co-authored-by: jbwang1997 <jbwang1997@gmail.com> * Update useful_tools.md (#7180) * [Enhancement]: Update colab tutorials (#7310) * update colab tutorials * update * fix * fix wrong CUDA explaination * resolve comments * resolve comments * fix typo Co-authored-by: Cedric Luo <luochunhua1996@outlook.com> Co-authored-by: tripleMu <92794867+q3394101@users.noreply.github.com> Co-authored-by: jbwang1997 <jbwang1997@gmail.com> Co-authored-by: kira <39787375+yangrisheng@users.noreply.github.com> Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> * Fix pointrend missing get_uncertainty function bug Co-authored-by: Wencheng Wu <41542251+274869388@users.noreply.github.com> Co-authored-by: Yue Zhou <592267829@qq.com> Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Co-authored-by: MingJian.L <45811724+matrixgame2018@users.noreply.github.com> Co-authored-by: Jamie <jamiechoi1995@users.noreply.github.com> Co-authored-by: BigDong <yudongwang@tju.edu.cn> Co-authored-by: Cedric Luo <26483343+chhluo@users.noreply.github.com> Co-authored-by: Yosuke Shinya <42844407+shinya7y@users.noreply.github.com> Co-authored-by: Cedric Luo <luochunhua1996@outlook.com> Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn> Co-authored-by: jbwang1997 <jbwang1997@gmail.com> Co-authored-by: Xiangxu-0103 <xuxiang0103@gmail.com> Co-authored-by: tripleMu <92794867+q3394101@users.noreply.github.com> Co-authored-by: kira <39787375+yangrisheng@users.noreply.github.com>

async def logger_test_deployment(orion_client):

tests/test_logging.py

prefect

Python

b110baccdbfde300f410b069c873e8b2a2c98e00

test_logging.py

logger_test_deployment

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

Add test

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

packages/python/plotly/plotly/graph_objs/layout/template/_data.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_data.py

pointcloud

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

switch to black .22

def varOr(population, toolbox, lambda_, cxpb, mutpb): offspring = [] for _ in range(lambda_): op_choice = np.random.random() if op_choice < cxpb: # Apply crossover ind1, ind2 = pick_two_individuals_eligible_for_crossover(population) if ind1 is not None: ind1, _ = toolbox.mate(ind1, ind2) del ind1.fitness.values else: # If there is no pair eligible for crossover, we still want to # create diversity in the population, and do so by mutation instead. ind1 = mutate_random_individual(population, toolbox) offspring.append(ind1) elif op_choice < cxpb + mutpb: # Apply mutation ind = mutate_random_individual(population, toolbox) offspring.append(ind) else: # Apply reproduction idx = np.random.randint(0, len(population)) offspring.append(toolbox.clone(population[idx])) return offspring

tpot/gp_deap.py

tpot

Python

388616b6247ca4ea8de4e2f340d6206aee523541

gp_deap.py

varOr

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

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

def make_valid(self): if geos_version_tuple() < (3, 8): raise GEOSException("GEOSGeometry.make_valid() requires GEOS >= 3.8.0.") return GEOSGeometry(capi.geos_makevalid(self.ptr), srid=self.srid) # #### Unary predicates ####

django/contrib/gis/geos/geometry.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

geometry.py

make_valid

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

Refs #33476 -- Reformatted code with Black.

def test_image_inside_paragraph(self): # In Draftail's data model, images are block-level elements and therefore # split up preceding / following text into their own paragraphs converter = ContentstateConverter(features=["image"]) result = json.loads( converter.from_database_format( ) ) self.assertContentStateEqual( result, { "blocks": [ { "key": "00000", "inlineStyleRanges": [], "entityRanges": [], "depth": 0, "text": "before", "type": "unstyled", }, { "key": "00000", "inlineStyleRanges": [], "entityRanges": [{"key": 0, "offset": 0, "length": 1}], "depth": 0, "text": " ", "type": "atomic", }, { "key": "00000", "inlineStyleRanges": [], "entityRanges": [], "depth": 0, "text": "after", "type": "unstyled", }, ], "entityMap": { "0": { "data": { "format": "left", "alt": "an image", "id": "1", "src": "/media/not-found", }, "mutability": "IMMUTABLE", "type": "IMAGE", } }, }, )

wagtail/admin/tests/test_contentstate.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

test_contentstate.py

test_image_inside_paragraph

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

Reformat with black

def get_losses_for(self, inputs): if inputs is None: # Requesting unconditional losses. return [l for l in self.losses if l._unconditional_loss] # Requesting input-conditional losses. losses = [l for l in self.losses if not l._unconditional_loss] inputs = tf.nest.flatten(inputs) reachable = tf_utils.get_reachable_from_inputs(inputs, losses) return [l for l in losses if l in reachable]

keras/engine/base_layer_v1.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_layer_v1.py

get_losses_for

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def load_config(file_path): _, ext = os.path.splitext(file_path) assert ext in ['.yml', '.yaml'], "only support yaml files for now" config = yaml.load(open(file_path, 'rb'), Loader=yaml.Loader) return config

tools/program.py

PaddleOCR

Python

a323fce66dd68a881cf599526185b52ab5df356b

program.py

load_config

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

vqa code integrated into ppocr training system

def test_basic(request): processing_factory = MetricsConsumerStrategyFactory( max_msg_batch_size=1, max_msg_batch_time=1, max_parallel_batch_size=1, max_parallel_batch_time=1, max_batch_size=1, max_batch_time=1, processes=1, input_block_size=1024, output_block_size=1024, config=MetricsIngestConfiguration( db_backend=IndexerStorage.MOCK, db_backend_options={}, input_topic="ingest-metrics", output_topic="snuba-metrics", use_case_id=UseCaseKey.RELEASE_HEALTH, internal_metrics_tag="test", writes_limiter_cluster_options={}, writes_limiter_namespace="test", ), ) strategy = processing_factory.create_with_partitions( lambda _: None, {Partition(topic=Topic(name="ingest-bogus-metrics"), index=1): 1}, ) message = Message( Partition(Topic("topic"), 0), 0, KafkaPayload(None, json.dumps(counter_payload).encode("utf-8"), []), datetime.now(), ) # Just assert that the strategy does not crash. Further assertions, such as # on the produced messages, would slow down the test significantly. strategy.submit(message=message) strategy.close() strategy.join()

tests/sentry/sentry_metrics/test_parallel_indexer.py

sentry

Python

d62c4935f02238a8f3991da5ef280a4bf249d771

test_parallel_indexer.py

test_basic

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

fix(metrics): Fix startup crash in parallel indexer [sns-1490] (#38455) Since https://github.com/getsentry/sentry/pull/38225 the parallel indexer fails to serialize the processing function here: https://github.com/getsentry/sentry/blob/9bf499ad95030ed1112f117c5c1be59b2e036509/src/sentry/sentry_metrics/consumers/indexer/parallel.py#L115 We need to make sure the message processor is pickleable. So the config also needs to be pickleable. The old code worked because it imported the config and indexer from settings instead of attempting to pickle them.

def _get_coeff_exp(expr, x): from sympy.simplify import powsimp (c, m) = expand_power_base(powsimp(expr)).as_coeff_mul(x) if not m: return c, S.Zero [m] = m if m.is_Pow: if m.base != x: raise _CoeffExpValueError('expr not of form a*x**b') return c, m.exp elif m == x: return c, S.One else: raise _CoeffExpValueError('expr not of form a*x**b: %s' % expr)

sympy/integrals/meijerint.py

sympy

Python

f757f3daae6e11ea0cfb7dadc133274d8d74315f

meijerint.py

_get_coeff_exp

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

Reordered imports 2

def activate(self) -> str: load_kube_config_from_dict( config_dict=self.config, context=self.context, ) return self.current_context()

src/prefect/blocks/kubernetes.py

prefect

Python

8f3ffd09dc47bfd2af6a635cc04c640febffd519

kubernetes.py

activate

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

add test coerage for get_api_client and activate

def parse_python_requires(value): # type: (t.Any) -> tuple[str, ...] if not isinstance(value, str): raise ValueError('python_requires must must be of type `str` not type `%s`' % type(value)) versions: tuple[str, ...] if value == 'default': versions = SUPPORTED_PYTHON_VERSIONS elif value == 'controller': versions = CONTROLLER_PYTHON_VERSIONS else: specifier_set = SpecifierSet(value) versions = tuple(version for version in SUPPORTED_PYTHON_VERSIONS if specifier_set.contains(Version(version))) return versions

test/lib/ansible_test/_internal/content_config.py

ansible

Python

f2abfc4b3d03a2baa078477d0ad2241263a00668

content_config.py

parse_python_requires

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

ansible-test - Parse content config only once. (#78418)

def set_to_context(self, name): attribute = self.fattributes[name] if isinstance(attribute, NonInheritableFieldAttribute): # setting to sentinel will trigger 'default/default()' on getter setattr(self, name, Sentinel) else: try: setattr(self, name, self._get_parent_attribute(name, omit=True)) except AttributeError: # mostly playcontext as only tasks/handlers/blocks really resolve parent setattr(self, name, Sentinel)

lib/ansible/playbook/base.py

ansible

Python

ff6e4da36addccb06001f7b05b1a9c04ae1d7984

base.py

set_to_context

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

fixes to FA inheritance (#78990) finalized applies to all field attributes fix getting parent value also remove unused/needed extend/prepend signature moar testing

def is_url_equal(url, other_url): # type: (str, str) -> bool if not isinstance(url, str): raise TypeError(f"Expected string for url, received {url!r}") if not isinstance(other_url, str): raise TypeError(f"Expected string for url, received {other_url!r}") parsed_url = urllib3_util.parse_url(url) parsed_other_url = urllib3_util.parse_url(other_url) unparsed = parsed_url._replace(auth=None, query=None, fragment=None).url unparsed_other = parsed_other_url._replace(auth=None, query=None, fragment=None).url return unparsed == unparsed_other

pipenv/utils/internet.py

pipenv

Python

3387881a6d4fc2d8bdc0f05c484cb2f7222acfb8

internet.py

is_url_equal

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

Code reorg utils into utils module reduces complexity (#4990) * Split apart the massive utils.py into a utils module

def iloc(self) -> _iLocIndexer: return _iLocIndexer("iloc", self)

pandas/core/indexing.py

pandas

Python

e7afa4b641b146874d17c36caa8a050bfde31283

indexing.py

iloc

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

DOC: Add tuple description to allowed inputs for iloc #47799 (#47989) DOC: Add tuple description to allowed inputs for iloc

def set_task_factory(self, factory): if factory is not None and not callable(factory): raise TypeError('task factory must be a callable or None') self._task_factory = factory

python3.10.4/Lib/asyncio/base_events.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

base_events.py

set_task_factory

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

add python 3.10.4 for windows

def ports(self): return self.runtime_args.port

jina/serve/gateway.py

jina

Python

e4b930e6369f1ec69b07af6190d61aa3cb3d9cec

gateway.py

ports

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

refactor: add properties to gateway (#5417)

def _set_level(self, value=None): if value is None and hasattr(self, "_level"): del self._level else: self._level = int(value) level = property(_get_level, _set_level, _set_level)

django/contrib/messages/storage/base.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

base.py

_set_level

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

Refs #33476 -- Reformatted code with Black.

def _as_graph_element(obj): conv_fn = getattr(obj, "_as_graph_element", None) if conv_fn and callable(conv_fn): return conv_fn() return None

keras/backend.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

_as_graph_element

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def _find_gcs_address_or_die(): gcs_addresses = _find_address_from_flag("--gcs-address") if len(gcs_addresses) > 1: raise ConnectionError( f"Found multiple active Ray instances: {gcs_addresses}. " "Please specify the one to connect to by setting `--address` flag " "or `RAY_ADDRESS` environment variable.") sys.exit(1) elif not gcs_addresses: raise ConnectionError( "Could not find any running Ray instance. " "Please specify the one to connect to by setting `--address` flag " "or `RAY_ADDRESS` environment variable.") return gcs_addresses.pop()

python/ray/_private/services.py

ray

Python

70db5c5592d94b611fee0a334414f1f4f5cc151a

services.py

_find_gcs_address_or_die

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

[GCS][Bootstrap n/n] Do not start Redis in GCS bootstrapping mode (#21232) After this change in GCS bootstrapping mode, Redis no longer starts and `address` is treated as the GCS address of the Ray cluster. Co-authored-by: Yi Cheng <chengyidna@gmail.com> Co-authored-by: Yi Cheng <74173148+iycheng@users.noreply.github.com>

def get_tax_template(posting_date, args): args = frappe._dict(args) conditions = [] if posting_date: conditions.append( f ) else: conditions.append("(from_date is null) and (to_date is null)") conditions.append( "ifnull(tax_category, '') = {0}".format(frappe.db.escape(cstr(args.get("tax_category")))) ) if "tax_category" in args.keys(): del args["tax_category"] for key, value in args.items(): if key == "use_for_shopping_cart": conditions.append("use_for_shopping_cart = {0}".format(1 if value else 0)) elif key == "customer_group": if not value: value = get_root_of("Customer Group") customer_group_condition = get_customer_group_condition(value) conditions.append("ifnull({0}, '') in ('', {1})".format(key, customer_group_condition)) else: conditions.append("ifnull({0}, '') in ('', {1})".format(key, frappe.db.escape(cstr(value)))) tax_rule = frappe.db.sql( .format( " and ".join(conditions) ), as_dict=True, ) if not tax_rule: return None for rule in tax_rule: rule.no_of_keys_matched = 0 for key in args: if rule.get(key): rule.no_of_keys_matched += 1 def cmp(a, b): # refernce: https://docs.python.org/3.0/whatsnew/3.0.html#ordering-comparisons return int(a > b) - int(a < b) rule = sorted( tax_rule, key=functools.cmp_to_key( lambda b, a: cmp(a.no_of_keys_matched, b.no_of_keys_matched) or cmp(a.priority, b.priority) ), )[0] tax_template = rule.sales_tax_template or rule.purchase_tax_template doctype = "{0} Taxes and Charges Template".format(rule.tax_type) if frappe.db.get_value(doctype, tax_template, "disabled") == 1: return None return tax_template

erpnext/accounts/doctype/tax_rule/tax_rule.py

erpnext

Python

05dd1d6d15c6c8c66165e9f267078c3cf9aec10e

tax_rule.py

get_tax_template

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

refactor: tax rule validity query (#30934)

def apothem(self): return self.radius * cos(S.Pi/self._n)

sympy/geometry/polygon.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

polygon.py

apothem

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

Updated import locations

def seek(self, offset, whence=0): # type: (int, int) -> int return self._file.seek(offset, whence)

.venv/lib/python3.8/site-packages/pip/_internal/network/lazy_wheel.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

lazy_wheel.py

seek

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

upd; format

def test_python_render_indent_guides(): syntax = Panel.fit( Syntax( CODE, lexer="python", line_numbers=True, line_range=(2, 10), theme="default", code_width=60, word_wrap=True, indent_guides=True, ), padding=0, ) rendered_syntax = render(syntax) print(repr(rendered_syntax)) expected = '╭────────────────────────────────────────────────────────────────╮\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 2 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[3;38;2;186;33;33;48;2;248;248;248m\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 3 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248miter_values\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;102;102;102;48;2;248;248;248m=\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;128;0;48;2;248;248;248miter\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m(\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mvalues\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m)\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 4 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mtry\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m:\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 5 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ │ \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mprevious_value\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;102;102;102;48;2;248;248;248m=\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;128;0;48;2;248;248;248mnext\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m(\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248miter_values\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m)\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 6 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mexcept\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[1;38;2;210;65;58;48;2;248;248;248mStopIteration\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m:\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 7 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ │ \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mreturn\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 8 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mfirst\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;102;102;102;48;2;248;248;248m=\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mTrue\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m 9 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mfor\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mvalue\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[1;38;2;170;34;255;48;2;248;248;248min\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248miter_values\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m:\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n│\x1b[1;38;2;24;24;24;48;2;248;248;248m \x1b[0m\x1b[38;2;173;173;173;48;2;248;248;248m10 \x1b[0m\x1b[2;3;38;2;64;128;128;48;2;248;248;248m│ │ \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248myield\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mfirst\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m,\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[1;38;2;0;128;0;48;2;248;248;248mFalse\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m,\x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248m \x1b[0m\x1b[38;2;0;0;0;48;2;248;248;248mprevious_value\x1b[0m\x1b[48;2;248;248;248m \x1b[0m│\n╰────────────────────────────────────────────────────────────────╯\n' assert rendered_syntax == expected

tests/test_syntax.py

rich

Python

2cf35b18a8716c963c0f9252544a3a8b9881cd6c

test_syntax.py

test_python_render_indent_guides

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

Try using default theme in test to avoid ubuntu/macos variance

async def install(cls): for field in cls.__fields__.values(): if Block.is_block_class(field.type_): await field.type_.install() if get_origin(field.type_) is Union: for type in get_args(field.type_): if Block.is_block_class(type): await type.install()

src/prefect/blocks/core.py

prefect

Python

6a1cec80715c2b633362403a6be9470fc70c31e8

core.py

install

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

Makes block installation recursive

def test_json_to_doc_validation_error(doc): doc_json = doc.to_json() doc_json.pop("tokens") with pytest.raises(ValueError): Doc(doc.vocab).from_json(doc_json, validate=True)

spacy/tests/doc/test_json_doc_conversion.py

spaCy

Python

8387ce4c01db48d92ac5638e18316c0f1fc8861e

test_json_doc_conversion.py

test_json_to_doc_validation_error

https://github.com/explosion/spaCy.git

Add Doc.from_json() (#10688) * Implement Doc.from_json: rough draft. * Implement Doc.from_json: first draft with tests. * Implement Doc.from_json: added documentation on website for Doc.to_json(), Doc.from_json(). * Implement Doc.from_json: formatting changes. * Implement Doc.to_json(): reverting unrelated formatting changes. * Implement Doc.to_json(): fixing entity and span conversion. Moving fixture and doc <-> json conversion tests into single file. * Implement Doc.from_json(): replaced entity/span converters with doc.char_span() calls. * Implement Doc.from_json(): handling sentence boundaries in spans. * Implementing Doc.from_json(): added parser-free sentence boundaries transfer. * Implementing Doc.from_json(): added parser-free sentence boundaries transfer. * Implementing Doc.from_json(): incorporated various PR feedback. * Renaming fixture for document without dependencies. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implementing Doc.from_json(): using two sent_starts instead of one. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implementing Doc.from_json(): doc_without_dependency_parser() -> doc_without_deps. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implementing Doc.from_json(): incorporating various PR feedback. Rebased on latest master. * Implementing Doc.from_json(): refactored Doc.from_json() to work with annotation IDs instead of their string representations. * Implement Doc.from_json(): reverting unwanted formatting/rebasing changes. * Implement Doc.from_json(): added check for char_span() calculation for entities. * Update spacy/tokens/doc.pyx Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): minor refactoring, additional check for token attribute consistency with corresponding test. * Implement Doc.from_json(): removed redundancy in annotation type key naming. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): Simplifying setting annotation values. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement doc.from_json(): renaming annot_types to token_attrs. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): adjustments for renaming of annot_types to token_attrs. * Implement Doc.from_json(): removing default categories. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): simplifying lexeme initialization. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): simplifying lexeme initialization. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): refactoring to only have keys for present annotations. * Implement Doc.from_json(): fix check for tokens' HEAD attributes. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): refactoring Doc.from_json(). * Implement Doc.from_json(): fixing span_group retrieval. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): fixing span retrieval. * Implement Doc.from_json(): added schema for Doc JSON format. Minor refactoring in Doc.from_json(). * Implement Doc.from_json(): added comment regarding Token and Span extension support. * Implement Doc.from_json(): renaming inconsistent_props to partial_attrs.. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): adjusting error message. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): extending E1038 message. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): added params to E1038 raises. * Implement Doc.from_json(): combined attribute collection with partial attributes check. * Implement Doc.from_json(): added optional schema validation. * Implement Doc.from_json(): fixed optional fields in schema, tests. * Implement Doc.from_json(): removed redundant None check for DEP. * Implement Doc.from_json(): added passing of schema validatoin message to E1037.. * Implement Doc.from_json(): removing redundant error E1040. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): changing message for E1037. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): adjusted website docs and docstring of Doc.from_json(). * Update spacy/tests/doc/test_json_doc_conversion.py * Implement Doc.from_json(): docstring update. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): docstring update. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): website docs update. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): docstring formatting. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): docstring formatting. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): fixing Doc reference in website docs. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): reformatted website/docs/api/doc.md. * Implement Doc.from_json(): bumped IDs of new errors to avoid merge conflicts. * Implement Doc.from_json(): fixing bug in tests. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Implement Doc.from_json(): fix setting of sentence starts for docs without DEP. * Implement Doc.from_json(): add check for valid char spans when manually setting sentence boundaries. Refactor sentence boundary setting slightly. Move error message for lack of support for partial token annotations to errors.py. * Implement Doc.from_json(): simplify token sentence start manipulation. Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> * Combine related error messages * Update spacy/tests/doc/test_json_doc_conversion.py Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

def is_sequence_right_padded(mask): max_seq_length = tf.shape(mask)[1] count_of_true = tf.reduce_sum(tf.cast(mask, tf.int32), axis=1) right_padded_mask = tf.sequence_mask( count_of_true, maxlen=max_seq_length) return tf.reduce_all(tf.equal(mask, right_padded_mask))

keras/layers/rnn/gru_lstm_utils.py

keras

Python

01c906c4178db5ae03b7eb2d298a052c952a0667

gru_lstm_utils.py

is_sequence_right_padded

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 query_cursor_left(self) -> bool: previous_index = self.cursor_index new_index = max(0, previous_index - 1) return previous_index != new_index

src/textual/widgets/text_input.py

textual

Python

9e25752c859d25c172697236b94997a38c0799bf

text_input.py

query_cursor_left

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

Scrolling within text input

def resample(*arrays, replace=True, n_samples=None, random_state=None, stratify=None): max_n_samples = n_samples random_state = check_random_state(random_state) if len(arrays) == 0: return None first = arrays[0] n_samples = first.shape[0] if hasattr(first, "shape") else len(first) if max_n_samples is None: max_n_samples = n_samples elif (max_n_samples > n_samples) and (not replace): raise ValueError( "Cannot sample %d out of arrays with dim %d when replace is False" % (max_n_samples, n_samples) ) check_consistent_length(*arrays) if stratify is None: if replace: indices = random_state.randint(0, n_samples, size=(max_n_samples,)) else: indices = np.arange(n_samples) random_state.shuffle(indices) indices = indices[:max_n_samples] else: # Code adapted from StratifiedShuffleSplit() y = check_array(stratify, ensure_2d=False, dtype=None) if y.ndim == 2: # for multi-label y, map each distinct row to a string repr # using join because str(row) uses an ellipsis if len(row) > 1000 y = np.array([" ".join(row.astype("str")) for row in y]) classes, y_indices = np.unique(y, return_inverse=True) n_classes = classes.shape[0] class_counts = np.bincount(y_indices) # Find the sorted list of instances for each class: # (np.unique above performs a sort, so code is O(n logn) already) class_indices = np.split( np.argsort(y_indices, kind="mergesort"), np.cumsum(class_counts)[:-1] ) n_i = _approximate_mode(class_counts, max_n_samples, random_state) indices = [] for i in range(n_classes): indices_i = random_state.choice(class_indices[i], n_i[i], replace=replace) indices.extend(indices_i) indices = random_state.permutation(indices) # convert sparse matrices to CSR for row-based indexing arrays = [a.tocsr() if issparse(a) else a for a in arrays] resampled_arrays = [_safe_indexing(a, indices) for a in arrays] if len(resampled_arrays) == 1: # syntactic sugar for the unit argument case return resampled_arrays[0] else: return resampled_arrays

sklearn/utils/__init__.py

scikit-learn

Python

82cd3d74f252e7d4c5e733b530897d499d5d640b

__init__.py

resample

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

DOC numpydoc validation for `resample` function (#23916)

def resolve_model_string(model_string, default_app=None): if isinstance(model_string, str): try: app_label, model_name = model_string.split(".") except ValueError: if default_app is not None: # If we can't split, assume a model in current app app_label = default_app model_name = model_string else: raise ValueError( "Can not resolve {0!r} into a model. Model names " "should be in the form app_label.model_name".format(model_string), model_string, ) return apps.get_model(app_label, model_name) elif isinstance(model_string, type) and issubclass(model_string, Model): return model_string else: raise ValueError( "Can not resolve {0!r} into a model".format(model_string), model_string ) SCRIPT_RE = re.compile(r"<(-*)/script>")

wagtail/core/utils.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

utils.py

resolve_model_string

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

Reformat with black

def trigger(self, sender, event, data=None): if not self.figure.canvas.widgetlock.available(sender): return if data is not None: self.draw_rubberband(*data) else: self.remove_rubberband()

lib/matplotlib/backend_tools.py

matplotlib

Python

d86a5050b57fc2f3f95d23d94f6c64f86dac2cd3

backend_tools.py

trigger

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

Fix method subclassing inconsistencies

def default_device(dev=None): if ivy.exists(dev): _assert_dev_correct_formatting(dev) return dev global default_device_stack if not default_device_stack: default_device_stack = ['gpu:0'] if ivy.gpu_is_available() else ['cpu'] return default_device_stack[-1] # noinspection PyShadowingNames

ivy/core/device.py

ivy

Python

d743336b1f3654cd0315f380f43eed4116997c1d

device.py

default_device

https://github.com/unifyai/ivy.git

renamed dev_str arg to dev for all methods.

def save_optimizer_weights_to_hdf5_group(hdf5_group, optimizer): symbolic_weights = getattr(optimizer, "weights") if symbolic_weights: weights_group = hdf5_group.create_group("optimizer_weights") weight_names = [str(w.name).encode("utf8") for w in symbolic_weights] save_attributes_to_hdf5_group( weights_group, "weight_names", weight_names ) weight_values = backend.batch_get_value(symbolic_weights) for name, val in zip(weight_names, weight_values): param_dset = weights_group.create_dataset( name, val.shape, dtype=val.dtype ) if not val.shape: # scalar param_dset[()] = val else: param_dset[:] = val

keras/saving/hdf5_format.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

hdf5_format.py

save_optimizer_weights_to_hdf5_group

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def powdenest(eq, force=False, polar=False): r from sympy.simplify.simplify import posify if force:

sympy/simplify/powsimp.py

sympy

Python

2a1afca9477eb781f16d5d6b63fa37abed7740a3

powsimp.py

powdenest

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

Use sympify less

def set_anchor(self, anchor): if isinstance(anchor, str): _api.check_in_list(mtransforms.Bbox.coefs, anchor=anchor) elif not isinstance(anchor, (tuple, list)) or len(anchor) != 2: raise TypeError("anchor must be str or 2-tuple") self._anchor = anchor

lib/mpl_toolkits/axes_grid1/axes_divider.py

matplotlib

Python

e94dfed864a8bbeb215bab5705a490325ac07819

axes_divider.py

set_anchor

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

Improve argument checking

def parsedate_tz(data): res = _parsedate_tz(data) if not res: return if res[9] is None: res[9] = 0 return tuple(res)

python3.10.4/Lib/email/_parseaddr.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_parseaddr.py