Insert trailing comma when function breaks with single argument #8921

charliermarsh · 2023-11-30T04:29:36Z

Summary

Given:

def _example_function_xxxxxxx(
    variable: Optional[List[str]]
) -> List[example.ExampleConfig]:
    pass

We should be inserting a trailing comma after the argument (as long as it's a single-argument function). This was an inconsistency with Black, but also led to some internal inconsistencies, whereby we added the comma if the argument contained a trailing end-of-line comment, but not otherwise.

Closes #8912.

Test Plan

cargo test

Before:

project	similarity index	total files	changed files
cpython	0.75804	1799	1648
django	0.99984	2772	34
home-assistant	0.99963	10596	146
poetry	0.99925	317	12
transformers	0.99967	2657	322
twine	1.00000	33	0
typeshed	0.99980	3669	18
warehouse	0.99977	654	13
zulip	0.99970	1459	21

After:

project	similarity index	total files	changed files
cpython	0.75804	1799	1648
django	0.99984	2772	34
home-assistant	0.99955	10596	213
poetry	0.99917	317	13
transformers	0.99967	2657	324
twine	1.00000	33	0
typeshed	0.99980	3669	18
warehouse	0.99976	654	14
zulip	0.99957	1459	36

github-actions · 2023-11-30T04:39:55Z

`ruff-ecosystem` results

Formatter (stable)

ℹ️ ecosystem check detected format changes. (+270 -270 lines in 86 files in 41 projects)

DisnakeDev/disnake (+2 -2 lines across 1 file)

disnake/audit_logs.py~L215

 
 
 def _list_transformer(
-    func: Callable[[AuditLogEntry, Any], T]
+    func: Callable[[AuditLogEntry, Any], T],
 ) -> Callable[[AuditLogEntry, Any], List[T]]:
     def _transform(entry: AuditLogEntry, data: Any) -> List[T]:
         if not data:

RasaHQ/rasa (+47 -47 lines across 19 files)

rasa/core/brokers/pika.py~L94

 
     @staticmethod
     def _get_queues_from_args(
-        queues_arg: Union[List[Text], Tuple[Text, ...], Text, None]
+        queues_arg: Union[List[Text], Tuple[Text, ...], Text, None],
     ) -> Union[List[Text], Tuple[Text, ...]]:
         """Get queues for this event broker.

rasa/core/channels/console.py~L113

 
 
 async def _get_user_input(
-    previous_response: Optional[Dict[str, Any]]
+    previous_response: Optional[Dict[str, Any]],
 ) -> Optional[Text]:
     button_response = None
     if previous_response is not None:

rasa/core/evaluation/marker_stats.py~L12

 
 
 def compute_statistics(
-    values: List[Union[float, int]]
+    values: List[Union[float, int]],
 ) -> Dict[Text, Union[int, float, np.floating]]:
     """Computes some statistics over the given numbers."""
     return {

rasa/core/migrate.py~L83

 
 
 def _migrate_form_slots(
-    domain: Dict[Text, Any]
+    domain: Dict[Text, Any],
 ) -> Tuple[Dict[Any, Dict[str, Any]], Optional[Any]]:
     updated_slots = domain.get(KEY_SLOTS, {})
     forms = domain.get(KEY_FORMS, {})

rasa/core/policies/ted_policy.py~L468

 
     @staticmethod
     def _should_extract_entities(
-        entity_tags: List[List[Dict[Text, List[Features]]]]
+        entity_tags: List[List[Dict[Text, List[Features]]]],
     ) -> bool:
         for turns_tags in entity_tags:
             for turn_tags in turns_tags:

rasa/core/policies/ted_policy.py~L1360

 
     @staticmethod
     def _compute_dialogue_indices(
-        tf_batch_data: Dict[Text, Dict[Text, List[tf.Tensor]]]
+        tf_batch_data: Dict[Text, Dict[Text, List[tf.Tensor]]],
     ) -> None:
         dialogue_lengths = tf.cast(tf_batch_data[DIALOGUE][LENGTH][0], dtype=tf.int32)
         # wrap in a list, because that's the structure of tf_batch_data

rasa/core/policies/ted_policy.py~L1399

 
     @staticmethod
     def _collect_label_attribute_encodings(
-        all_labels_encoded: Dict[Text, tf.Tensor]
+        all_labels_encoded: Dict[Text, tf.Tensor],
     ) -> tf.Tensor:
         # Initialize with at least one attribute first
         # so that the subsequent TF ops are simplified.

rasa/core/policies/unexpected_intent_policy.py~L807

 
     @staticmethod
     def _compute_label_quantiles(
-        label_id_scores: Dict[int, Dict[Text, List[float]]]
+        label_id_scores: Dict[int, Dict[Text, List[float]]],
     ) -> Dict[int, List[float]]:
         """Computes multiple quantiles for each label id.

rasa/core/processor.py~L123

 
     @staticmethod
     def _load_model(
-        model_path: Union[Text, Path]
+        model_path: Union[Text, Path],
     ) -> Tuple[Text, ModelMetadata, GraphRunner]:
         """Unpacks a model from a given path using the graph model loader."""
         try:

rasa/core/utils.py~L215

 
 
 def read_endpoints_from_path(
-    endpoints_path: Optional[Union[Path, Text]] = None
+    endpoints_path: Optional[Union[Path, Text]] = None,
 ) -> AvailableEndpoints:
     """Get `AvailableEndpoints` object from specified path.

rasa/core/utils.py~L282

 
 
 def _lock_store_is_multi_worker_compatible(
-    lock_store: Union[EndpointConfig, LockStore, None]
+    lock_store: Union[EndpointConfig, LockStore, None],
 ) -> bool:
     if isinstance(lock_store, InMemoryLockStore):
         return False

rasa/nlu/featurizers/sparse_featurizer/count_vectors_featurizer.py~L338

 
     @staticmethod
     def _convert_attribute_tokens_to_texts(
-        attribute_tokens: Dict[Text, List[List[Text]]]
+        attribute_tokens: Dict[Text, List[List[Text]]],
     ) -> Dict[Text, List[Text]]:
         attribute_texts = {}

rasa/nlu/featurizers/sparse_featurizer/count_vectors_featurizer.py~L679

 
     @staticmethod
     def _is_any_model_trained(
-        attribute_vocabularies: Dict[Text, Optional[Dict[Text, int]]]
+        attribute_vocabularies: Dict[Text, Optional[Dict[Text, int]]],
     ) -> bool:
         """Check if any model got trained."""
         return any(value is not None for value in attribute_vocabularies.values())

rasa/nlu/featurizers/sparse_featurizer/lexical_syntactic_featurizer.py~L353

 
     @staticmethod
     def _build_feature_to_index_map(
-        feature_vocabulary: Dict[Tuple[int, Text], Set[Text]]
+        feature_vocabulary: Dict[Tuple[int, Text], Set[Text]],
     ) -> Dict[Tuple[int, Text], Dict[Text, int]]:
         """Creates a nested dictionary for mapping raw features to indices.

rasa/nlu/utils/spacy_utils.py~L195

 
     @staticmethod
     def _filter_training_samples_by_content(
-        indexed_training_samples: List[Tuple[int, Text]]
+        indexed_training_samples: List[Tuple[int, Text]],
     ) -> Tuple[List[Tuple[int, Text]], List[Tuple[int, Text]]]:
         """Separates empty training samples from content bearing ones."""
         docs_to_pipe = list(

rasa/shared/core/training_data/story_reader/yaml_story_reader.py~L465

 
     @staticmethod
     def _parse_raw_entities(
-        raw_entities: Union[List[Dict[Text, Text]], List[Text]]
+        raw_entities: Union[List[Dict[Text, Text]], List[Text]],
     ) -> List[Dict[Text, Optional[Text]]]:
         final_entities = []
         for entity in raw_entities:

rasa/shared/importers/importer.py~L443

 
     @staticmethod
     def _get_nlu_data_with_responses(
-        responses: Dict[Text, List[Dict[Text, Any]]]
+        responses: Dict[Text, List[Dict[Text, Any]]],
     ) -> TrainingData:
         """Construct training data object with only the responses supplied.

rasa/utils/tensorflow/models.py~L239

 
     @staticmethod
     def _dynamic_signature(
-        batch_in: Union[Tuple[tf.Tensor, ...], Tuple[np.ndarray, ...]]
+        batch_in: Union[Tuple[tf.Tensor, ...], Tuple[np.ndarray, ...]],
     ) -> List[List[tf.TensorSpec]]:
         element_spec = []
         for tensor in batch_in:

rasa/utils/tensorflow/models.py~L377

         """Recursively replaces empty list or np array with None in a dictionary."""
 
         def _recurse(
-            x: Union[Dict[Text, Any], List[Any], np.ndarray]
+            x: Union[Dict[Text, Any], List[Any], np.ndarray],
         ) -> Optional[Union[Dict[Text, Any], List[Any], np.ndarray]]:
             if isinstance(x, dict):
                 return {k: _recurse(v) for k, v in x.items()}

tests/cli/test_rasa_data.py~L208

 
 
 def test_data_validate_failed_to_load_domain(
-    run_in_simple_project_with_no_domain: Callable[..., RunResult]
+    run_in_simple_project_with_no_domain: Callable[..., RunResult],
 ):
     result = run_in_simple_project_with_no_domain(
         "data",

tests/cli/test_rasa_train.py~L243

 
 
 def test_train_dry_run_force(
-    run_in_simple_project_with_model: Callable[..., RunResult]
+    run_in_simple_project_with_model: Callable[..., RunResult],
 ):
     temp_dir = os.getcwd()

tests/cli/test_rasa_train.py~L497

 
 
 def test_train_nlu_finetune_with_model(
-    run_in_simple_project_with_model: Callable[..., RunResult]
+    run_in_simple_project_with_model: Callable[..., RunResult],
 ):
     temp_dir = os.getcwd()

tests/graph_components/validators/test_finetuning_validator.py~L70

 
 @pytest.fixture
 def get_validation_method(
-    get_finetuning_validator: Callable[[bool, bool], FinetuningValidator]
+    get_finetuning_validator: Callable[[bool, bool], FinetuningValidator],
 ) -> Callable[[bool, bool, bool, bool, GraphSchema], ValidationMethodType]:
     def inner(
         finetuning: bool,

tests/nlu/classifiers/test_diet_classifier.py~L471

 
 
 async def test_margin_loss_is_not_normalized(
-    create_train_load_and_process_diet: Callable[..., Message]
+    create_train_load_and_process_diet: Callable[..., Message],
 ):
     _, parsed_message = create_train_load_and_process_diet(
         {

tests/nlu/classifiers/test_diet_classifier.py~L498

 
 @pytest.mark.timeout(120, func_only=True)
 async def test_set_random_seed(
-    create_train_load_and_process_diet: Callable[..., Message]
+    create_train_load_and_process_diet: Callable[..., Message],
 ):
     """test if train result is the same for two runs of tf embedding"""

tests/nlu/classifiers/test_diet_classifier.py~L618

 
 
 async def test_train_fails_with_zero_eval_num_epochs(
-    create_diet: Callable[..., DIETClassifier]
+    create_diet: Callable[..., DIETClassifier],
 ):
     with pytest.raises(InvalidConfigException):
         with pytest.warns(UserWarning) as warning:

tests/nlu/extractors/test_regex_entity_extractor.py~L264

 
 
 def test_train_process_and_load_with_empty_model(
-    create_or_load_extractor: Callable[..., RegexEntityExtractor]
+    create_or_load_extractor: Callable[..., RegexEntityExtractor],
 ):
     extractor = create_or_load_extractor({})
     with pytest.warns(UserWarning):

tests/nlu/extractors/test_regex_entity_extractor.py~L276

 
 
 def test_process_does_not_overwrite_any_entities(
-    create_or_load_extractor: Callable[..., RegexEntityExtractor]
+    create_or_load_extractor: Callable[..., RegexEntityExtractor],
 ):
     pre_existing_entity = {
         ENTITY_ATTRIBUTE_TYPE: "person",

Snowflake-Labs/snowcli (+2 -2 lines across 1 file)

performance_history_analysis.py~L40

 
 
 def _print_summary_performance_descending(
-    commits_with_results: List[Tuple[Commit, float]]
+    commits_with_results: List[Tuple[Commit, float]],
 ) -> None:
     commits_with_diffs: List[Tuple[Commit, Decimal]] = []
     last_result: Optional[Decimal] = None

demisto/content (+11 -11 lines across 5 files)

ruff format --no-preview --exclude Packs/ThreatQ/Integrations/ThreatQ/ThreatQ.py

Packs/BmcHelixRemedyForce/Integrations/BmcHelixRemedyForce/BmcHelixRemedyForce.py~L765

 
 
 def prepare_outputs_for_categories(
-    records: List[Dict[str, Any]]
+    records: List[Dict[str, Any]],
 ) -> Tuple[List[Dict[str, Optional[Any]]], List[Dict[str, Optional[Any]]]]:
     """
     Prepares human readables and context output for 'bmc-remedy-category-details-get' command.

Packs/ExpanseV2/Scripts/ExpanseAggregateAttributionCI/ExpanseAggregateAttributionCI.py~L14

 
 
 def deconstruct_entry(
-    ServiceNowCMDBContext: Dict[str, Any]
+    ServiceNowCMDBContext: Dict[str, Any],
 ) -> Tuple[str, Optional[str], Optional[str], Optional[str], Optional[str], Optional[str]]:
     """
     deconstruct_entry

Packs/GoogleChronicleBackstory/Integrations/GoogleChronicleBackstory/GoogleChronicleBackstory.py~L1426

 
 
 def validate_and_parse_curatedrule_detection_start_end_time(
-    args: Dict[str, Any]
+    args: Dict[str, Any],
 ) -> Tuple[Optional[datetime], Optional[datetime]]:
     """
     Validate and return detection_start_time and detection_end_time as per Chronicle Backstory or \

Packs/PAN-OS/Integrations/Panorama/Panorama.py~L10144

 
     @staticmethod
     def get_all_security_rules_in_container(
-        container: Union[Panorama, Firewall, DeviceGroup, Template, Vsys]
+        container: Union[Panorama, Firewall, DeviceGroup, Template, Vsys],
     ) -> List[SecurityRule]:
         """
         Gets all the security rule objects from the given VSYS or device group and return them.

Packs/PAN-OS/Integrations/Panorama/Panorama.py~L13768

 
 
 def parse_incident_entries(
-    incident_entries: List[Dict[str, Any]]
+    incident_entries: List[Dict[str, Any]],
 ) -> Tuple[Dict[str, str] | None, datetime | None, List[Dict[str, Any]]]:
     """parses raw incident entries of a specific log type query into basic context incidents.

Tests/scripts/test_playbooks_report.py~L17

 
 
 def calculate_test_playbooks_results(
-    test_playbooks_result_files_list: dict[str, Path]
+    test_playbooks_result_files_list: dict[str, Path],
 ) -> tuple[dict[str, dict[str, Any]], set[str]]:
     playbooks_results: dict[str, dict[str, Any]] = {}
     server_versions = set()

latchbio/latch (+2 -2 lines across 1 file)

latch_cli/snakemake/workflow.py~L912

 
 
 def annotated_str_to_json(
-    x: Union[str, snakemake.io._IOFile, snakemake.io.AnnotatedString]
+    x: Union[str, snakemake.io._IOFile, snakemake.io.AnnotatedString],
 ) -> MaybeAnnotatedStrJson:
     if not isinstance(x, (snakemake.io.AnnotatedString, snakemake.io._IOFile)):
         return x

pandas-dev/pandas (+4 -4 lines across 2 files)

pandas/core/apply.py~L1778

 
 
 def _make_unique_kwarg_list(
-    seq: Sequence[tuple[Any, Any]]
+    seq: Sequence[tuple[Any, Any]],
 ) -> Sequence[tuple[Any, Any]]:
     """
     Uniquify aggfunc name of the pairs in the order list

pandas/plotting/_matplotlib/core.py~L465

     @final
     @staticmethod
     def _iter_data(
-        data: DataFrame | dict[Hashable, Series | DataFrame]
+        data: DataFrame | dict[Hashable, Series | DataFrame],
     ) -> Iterator[tuple[Hashable, np.ndarray]]:
         for col, values in data.items():
             # This was originally written to use values.values before EAs

prefecthq/prefect (+5 -5 lines across 2 files)

src/prefect/_internal/pydantic/annotations/pendulum.py~L35

             return pendulum.parse(value)
 
         def to_str(
-            value: t.Union[pendulum.DateTime, pendulum.Date, pendulum.Time]
+            value: t.Union[pendulum.DateTime, pendulum.Date, pendulum.Time],
         ) -> str:
             return value.isoformat()

src/prefect/server/database/query_components.py~L1256

             # help smooth over those differences.
 
             def edges(
-                value: Union[str, Sequence[UUID], Sequence[str], None]
+                value: Union[str, Sequence[UUID], Sequence[str], None],
             ) -> List[UUID]:
                 if not value:
                     return []

src/prefect/server/database/query_components.py~L1265

                 return [Edge(id=id) for id in value]
 
             def time(
-                value: Union[str, datetime.datetime, None]
+                value: Union[str, datetime.datetime, None],
             ) -> Optional[pendulum.DateTime]:
                 if not value:
                     return None

python/mypy (+3 -3 lines across 1 file)

mypy/types.py~L3087

 
 @overload
 def get_proper_types(
-    types: list[Type | None] | tuple[Type | None, ...]
+    types: list[Type | None] | tuple[Type | None, ...],
 ) -> list[ProperType | None]:
     ...
 
 
 def get_proper_types(
-    types: list[Type] | list[Type | None] | tuple[Type | None, ...]
+    types: list[Type] | list[Type | None] | tuple[Type | None, ...],
 ) -> list[ProperType] | list[ProperType | None]:
     if isinstance(types, list):
         typelist = types

python/typeshed (+165 -165 lines across 43 files)

stubs/protobuf/google/protobuf/compiler/plugin_pb2.pyi~L89

     """The generator parameter passed on the command-line."""
     @property
     def proto_file(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[google.protobuf.descriptor_pb2.FileDescriptorProto]:
         """FileDescriptorProtos for all files in files_to_generate and everything
         they import.  The files will appear in topological order, so each file

stubs/protobuf/google/protobuf/compiler/plugin_pb2.pyi~L283

     """
     @property
     def file(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CodeGeneratorResponse.File]: ...
     def __init__(
         self,

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L242

     def enum_type(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EnumDescriptorProto]: ...
     @property
     def extension_range(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DescriptorProto.ExtensionRange]: ...
     @property
     def oneof_decl(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___OneofDescriptorProto]: ...
     @property
     def options(self) -> global___MessageOptions: ...
     @property
     def reserved_range(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DescriptorProto.ReservedRange]: ...
     @property
     def reserved_name(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]:

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L309

     UNINTERPRETED_OPTION_FIELD_NUMBER: builtins.int
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L638

     def options(self) -> global___EnumOptions: ...
     @property
     def reserved_range(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___EnumDescriptorProto.EnumReservedRange]:
         """Range of reserved numeric values. Reserved numeric values may not be used
         by enum values in the same enum declaration. Reserved ranges may not

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L986

     """
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here.
         See the documentation for the "Options" section above.

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1176

     """
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1350

     """For Google-internal migration only. Do not use."""
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1415

     UNINTERPRETED_OPTION_FIELD_NUMBER: builtins.int
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1446

     """
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1482

     """
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1517

     """
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1580

     idempotency_level: global___MethodOptions.IdempotencyLevel.ValueType
     @property
     def uninterpreted_option(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption]:
         """The parser stores options it doesn't recognize here. See above."""
     def __init__(

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1656

     AGGREGATE_VALUE_FIELD_NUMBER: builtins.int
     @property
     def name(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___UninterpretedOption.NamePart]: ...
     identifier_value: builtins.str
     """The value of the uninterpreted option, in whatever type the tokenizer

stubs/protobuf/google/protobuf/descriptor_pb2.pyi~L1964

     ANNOTATION_FIELD_NUMBER: builtins.int
     @property
     def annotation(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GeneratedCodeInfo.Annotation]:
         """An Annotation connects some span of text in generated code to an element
         of its generating .proto file.

stubs/s2clientprotocol/s2clientprotocol/query_pb2.pyi~L31

     def pathing(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RequestQueryPathing]: ...
     @property
     def abilities(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RequestQueryAvailableAbilities]: ...
     @property
     def placements(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RequestQueryBuildingPlacement]: ...
     ignore_resource_requirements: builtins.bool
     """Ignores requirements like food, minerals and so on."""

stubs/s2clientprotocol/s2clientprotocol/query_pb2.pyi~L77

     def pathing(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResponseQueryPathing]: ...
     @property
     def abilities(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResponseQueryAvailableAbilities]: ...
     @property
     def placements(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResponseQueryBuildingPlacement]: ...
     def __init__(
         self,

stubs/s2clientprotocol/s2clientprotocol/query_pb2.pyi~L179

     UNIT_TYPE_ID_FIELD_NUMBER: builtins.int
     @property
     def abilities(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.common_pb2.AvailableAbility]: ...
     unit_tag: builtins.int
     unit_type_id: builtins.int

stubs/s2clientprotocol/s2clientprotocol/raw_pb2.pyi~L124

         """The playable cells."""
     @property
     def start_locations(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.common_pb2.Point2D]:
         """Possible start locations for players."""
     def __init__(

stubs/s2clientprotocol/s2clientprotocol/sc2api_pb2.pyi~L1620

     RESULT_FIELD_NUMBER: builtins.int
     @property
     def result(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[s2clientprotocol.error_pb2.ActionResult.ValueType]: ...
     def __init__(
         self,

stubs/s2clientprotocol/s2clientprotocol/sc2api_pb2.pyi~L1768

     EFFECTS_FIELD_NUMBER: builtins.int
     @property
     def abilities(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.data_pb2.AbilityData]: ...
     @property
     def units(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.data_pb2.UnitTypeData]: ...
     @property
     def upgrades(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.data_pb2.UpgradeData]: ...
     @property
     def buffs(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.data_pb2.BuffData]: ...
     @property
     def effects(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.data_pb2.EffectData]: ...
     def __init__(
         self,

stubs/s2clientprotocol/s2clientprotocol/sc2api_pb2.pyi~L2210

     DEBUG_FIELD_NUMBER: builtins.int
     @property
     def debug(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.debug_pb2.DebugCommand]: ...
     def __init__(
         self,

stubs/s2clientprotocol/s2clientprotocol/sc2api_pb2.pyi~L2630

     def alerts(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___Alert.ValueType]: ...
     @property
     def abilities(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.common_pb2.AvailableAbility]:
         """Abilities available in the selection. Enabled if in this list, disabled otherwise."""
     @property

stubs/s2clientprotocol/s2clientprotocol/spatial_pb2.pyi~L661

     SELECTION_ADD_FIELD_NUMBER: builtins.int
     @property
     def selection_screen_coord(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[s2clientprotocol.common_pb2.RectangleI]:
         """Eventually this should not be an array, but a single field (multiple would be cheating)."""
     selection_add: builtins.bool

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L351

     batch_group_count: builtins.int
     @property
     def slice_dimensions(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloInstructionProto.SliceDimensions]: ...
     exponent_bits: builtins.int
     """The bit sizes for a reduce-precision operation."""

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L425

     """Backend configuration for the instruction. Has backend-specific meaning."""
     @property
     def replica_groups(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ReplicaGroup]:
         """Cross replica op fields."""
     all_reduce_id: builtins.int

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L450

         """Precision configuration for the instruction. Has backend-specific meaning."""
     @property
     def source_target_pairs(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.SourceTarget]:
         """Collective permute field."""
     @property

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L466

     """
     @property
     def operand_shapes_with_layout(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.ShapeProto]: ...
     @property
     def triangular_solve_options(self) -> tensorflow.compiler.xla.xla_data_pb2.TriangularSolveOptions:

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L483

     """
     @property
     def output_operand_aliasing(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         tensorflow.compiler.xla.xla_data_pb2.OutputOperandAliasing
     ]:

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L912

     SEQUENCES_FIELD_NUMBER: builtins.int
     @property
     def sequences(
-        self
+        self,
     ) -> google.protobuf.internal.containers.MessageMap[builtins.int, global___HloScheduleProto.InstructionSequence]:
         """Map from computation id to sequence."""
     def __init__(

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L986

     ENTRIES_FIELD_NUMBER: builtins.int
     @property
     def entries(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         global___HloInputOutputAliasProto.AliasEntryProto
     ]: ...

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1072

     ENTRIES_FIELD_NUMBER: builtins.int
     @property
     def entries(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___DynamicParameterBindingProto.Binding]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1215

     def dynamic_parameter_binding(self) -> global___DynamicParameterBindingProto: ...
     @property
     def cross_program_prefetches(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CrossProgramPrefetch]: ...
     is_dynamic: builtins.bool
     """True if the module contains dynamic computation."""

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1223

     def spmd_output_sharding(self) -> tensorflow.compiler.xla.xla_data_pb2.OpSharding: ...
     @property
     def spmd_parameters_shardings(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.OpSharding]: ...
     use_auto_spmd_partitioning: builtins.bool
     """Uses AutoSharding pass or not."""
     @property
     def profile_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HloModuleProto.ProfileInfo]:
         """Profile information for the HLO module."""
     @property

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1431

     color: builtins.int
     @property
     def assigned(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___BufferAllocationProto.Assigned]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1573

     BUFFER_ALLOCATION_INDEX_FIELD_NUMBER: builtins.int
     @property
     def events(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HeapSimulatorTrace.Event]: ...
     whole_module_simulation: builtins.bool
     buffer_allocation_index: builtins.int

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1657

     HEAP_SIMULATOR_TRACES_FIELD_NUMBER: builtins.int
     @property
     def logical_buffers(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___LogicalBufferProto]: ...
     @property
     def buffer_aliases(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___BufferAssignmentProto.BufferAlias]: ...
     @property
     def buffer_allocations(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___BufferAllocationProto]: ...
     @property
     def heap_simulator_traces(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___HeapSimulatorTrace]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L1740

         """The hlo graph."""
     @property
     def arguments(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.compiler.xla.xla_data_pb2.LiteralProto]:
         """The arguments passed to the graph."""
     @property

stubs/tensorflow/tensorflow/compiler/xla/service/hlo_pb2.pyi~L2007

     RESULT_XLA_SHAPE_FIELD_NUMBER: builtins.int
     @property
     def buffers(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         global___EntryFunctionAttributes.BufferParameterAttributes
     ]: ...

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L440

     DIMENSIONS_FIELD_NUMBER: builtins.int
     @property
     def dimensions(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___PaddingConfig.PaddingConfigDimension]:
         """The padding configuration for all dimensions."""
     def __init__(

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L506

     DYNAMIC_SHAPE_METADATA_PREFIX_BYTES_FIELD_NUMBER: builtins.int
     @property
     def dim_level_types(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___DimLevelType.ValueType]:
         """The dimension level type list for this array, specifying the way in which
         each array dimension is represented in memory. If this list is empty, the

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L757

         COMPILATION_EVENT_FIELD_NUMBER: builtins.int
         @property
         def profile_type(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___ProfileType.ValueType]:
             """The type of optimization profiles that this operation contains."""
         relative_speedup: builtins.float

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L1116

     computation_count: builtins.int
     @property
     def computation_devices(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         global___DeviceAssignmentProto.ComputationDevice
     ]: ...

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L1835

         """
     @property
     def last_tile_dims(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___OpSharding.Type.ValueType]:
         """This field is used to represented the sharding type of each subgroup.
         For example, sharding={devices=[2,2,2,2]0,1,2,...,15 last_tile_dims={

stubs/tensorflow/tensorflow/compiler/xla/xla_data_pb2.pyi~L1955

     OPERAND_PRECISION_FIELD_NUMBER: builtins.int
     @property
     def operand_precision(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[global___PrecisionConfig.Precision.ValueType]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/core/framework/attr_value_pb2.pyi~L57

             """ "list(bool)" """
         @property
         def type(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[
             tensorflow.core.framework.types_pb2.DataType.ValueType
         ]:
             """ "list(type)" """
         @property
         def shape(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
             tensorflow.core.framework.tensor_shape_pb2.TensorShapeProto
         ]:
             """ "list(shape)" """
         @property
         def tensor(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
             tensorflow.core.framework.tensor_pb2.TensorProto
         ]:

stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi~L112

         """The id of the node. Node ids are only unique inside a partition."""
         @property
         def input_info(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.InputInfo]: ...
         @property
         def output_info(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node.OutputInfo]: ...
         temporary_memory_size: builtins.int
         """Temporary memory used by this node."""

stubs/tensorflow/tensorflow/core/framework/cost_graph_pb2.pyi~L228

     def node(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.Node]: ...
     @property
     def cost(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CostGraphDef.AggregatedCost]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi~L73

     """Compressed tensor bytes for all components of the element."""
     @property
     def component_metadata(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___CompressedComponentMetadata]:
         """Metadata for the components of the element."""
     version: builtins.int

stubs/tensorflow/tensorflow/core/framework/dataset_pb2.pyi~L108

     COMPONENTS_FIELD_NUMBER: builtins.int
     @property
     def components(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         tensorflow.core.framework.tensor_pb2.TensorProto
     ]: ...

stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi~L35

     def gradient(self) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GradientDef]: ...
     @property
     def registered_gradients(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___RegisteredGradient]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi~L112

         ATTR_FIELD_NUMBER: builtins.int
         @property
         def attr(
-            self
+            self,
         ) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]: ...
         def __init__(
             self,

stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi~L201

         """
     @property
     def attr(
-        self
+        self,
     ) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]:
         """Attributes specific to this function definition."""
     @property

stubs/tensorflow/tensorflow/core/framework/function_pb2.pyi~L220

         """
     @property
     def node_def(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.node_def_pb2.NodeDef]:
         """The body of the function.  Unlike the NodeDefs in a GraphDef, attrs
         may have values of type `placeholder` and the `input` field uses

stubs/tensorflow/tensorflow/core/framework/graph_pb2.pyi~L32

     LIBRARY_FIELD_NUMBER: builtins.int
     @property
     def node(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.node_def_pb2.NodeDef]: ...
     @property
     def versions(self) -> tensorflow.core.framework.versions_pb2.VersionDef:

stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi~L131

     node_id: builtins.int
     @property
     def node_input(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferNodeInput]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/core/framework/graph_transfer_info_pb2.pyi~L245

     DESTINATION_FIELD_NUMBER: builtins.int
     @property
     def node_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferNodeInfo]: ...
     @property
     def const_node_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferConstNodeInfo]: ...
     @property
     def node_input_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferNodeInputInfo]: ...
     @property
     def node_output_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferNodeOutputInfo]: ...
     @property
     def graph_input_node_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferGraphInputNodeInfo]:
         """Input Node parameters of transferred graph"""
     @property
     def graph_output_node_info(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GraphTransferGraphOutputNodeInfo]: ...
     destination: global___GraphTransferInfo.Destination.ValueType
     """Destination of graph transfer"""

stubs/tensorflow/tensorflow/core/framework/kernel_def_pb2.pyi~L58

     """Type of device this kernel runs on."""
     @property
     def constraint(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___KernelDef.AttrConstraint]: ...
     @property
     def host_memory_arg(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]:

stubs/tensorflow/tensorflow/core/framework/model_pb2.pyi~L178

         """
         @property
         def parameters(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ModelProto.Node.Parameter]:
             """Parameters of this node."""
         input_processing_time_sum: builtins.float

stubs/tensorflow/tensorflow/core/framework/node_def_pb2.pyi~L128

     """
     @property
     def attr(
-        self
+        self,
     ) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]:
         """Operation-specific graph-construction-time configuration.
         Note that this should include all attrs defined in the

stubs/tensorflow/tensorflow/core/framework/op_def_pb2.pyi~L71

         """
         @property
         def handle_data(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
             tensorflow.core.framework.resource_handle_pb2.ResourceHandleProto.DtypeAndShape
         ]:

stubs/tensorflow/tensorflow/core/framework/optimized_function_graph_pb2.pyi~L64

         """
     @property
     def ret_types(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[tensorflow.core.framework.types_pb2.DataType.ValueType]:
         """Return node types of the function. This is an output of graph
         preprocessing.

stubs/tensorflow/tensorflow/core/framework/resource_handle_pb2.pyi~L70

     """
     @property
     def dtypes_and_shapes(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ResourceHandleProto.DtypeAndShape]:
         """Data types and shapes for the underlying resource."""
     def __init__(

stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi~L61

     """The bytes that are not deallocated."""
     @property
     def allocation_records(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___AllocationRecord]:
         """The allocation and deallocation timeline."""
     allocator_bytes_in_use: builtins.int

stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi~L142

     device_persistent_memory_size: builtins.int
     @property
     def device_persistent_tensor_alloc_ids(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.int]: ...
     def __init__(
         self,

stubs/tensorflow/tensorflow/core/framework/step_stats_pb2.pyi~L216

     thread_id: builtins.int
     @property
     def referenced_tensor(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         tensorflow.core.framework.allocation_description_pb2.AllocationDescription
     ]: ...

stubs/tensorflow/tensorflow/core/framework/tensor_pb2.pyi~L106

         """
     @property
     def resource_handle_val(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
         tensorflow.core.framework.resource_handle_pb2.ResourceHandleProto
     ]:

stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi~L106

         GPU_HOST_MEM_DISALLOW_GROWTH_FIELD_NUMBER: builtins.int
         @property
         def virtual_devices(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___GPUOptions.Experimental.VirtualDevices]:
             """The multi virtual device settings. If empty (not set), it will create
             single virtual device on each visible GPU, according to the settings

stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi~L1080

     """
     @property
     def session_inter_op_thread_pool(
-        self
+        self,
     ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___ThreadPoolOptionProto]:
         """This option is experimental - it may be replaced with a different mechanism
         in the future.

stubs/tensorflow/tensorflow/core/protobuf/config_pb2.pyi~L1412

         POST_OPTIMIZATION_GRAPH_FIELD_NUMBER: builtins.int
         @property
         def partition_graphs(
-            self
+            self,
         ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[tensorflow.core.framework.graph_pb2.GraphDef]:
             """TODO(nareshmodi): Include some sort of function/cache-key identifier?"""
         @property

<a href='https://github.com/python/typeshed/blob/78052791df327b716406f3f78962c4247cfe381f/stubs/...*[Comment body truncated]*

charliermarsh · 2023-11-30T05:01:04Z

This leads to decreased similarity in most cases (but the test fixtures show improvement). I'm pretty lost on what Black's logic is for inserting the trailing comma vs. not. For example, Black adds a trailing comma to the second example here, but not the first...

def _start_listening(
    ws_event_callback: Callable[str, int]
) -> List[example.ExampleConfig]:
    pass

def _start_listening(
    ws_event_callback: Callable[List[str]]
) -> List[example.ExampleConfig]:
    pass

zanieb · 2023-11-30T05:20:38Z

+1 for consistency

charliermarsh · 2023-11-30T05:47:32Z

I'm now leaning towards proceeding with this change. My best guess is that Black omits the trailing comma if the annotation contains a comma, which seems incorrect to me.

konstin

+1 for the consistency, since it changes a bunch of files and decreases black compatibility, do we want to guard it behind e.g. preview?

charliermarsh · 2023-11-30T16:00:57Z

Another idea is that we could only add the trailing comma if the argument itself breaks...

So:

# Add a trailing comma here...
def _start_listening(
    ws_event_callback: List[
        CallableButImagineItIsVeryLong[str, int]
    ],
) -> List[example.ExampleConfig]:
    pass

# But not here...
def _start_listening(
    ws_event_callback: Callable[List[str]]
) -> List[example.ExampleConfig]:
    pass

This would still be a deviation from Black in some cases, but it would avoid adding the trailing comma in the event that more arguments are added (since those arguments would stay on the same line).

Eh, on second thought, I don't see why that would be better.

(Filed an issue on: psf/black#4080)

zanieb · 2023-11-30T16:11:22Z

I think this is a bug and we don't need to gate it with preview; perhaps if the formatter was not in beta, I would feel differently.

…9076) ## Summary In #8921, we changed our parameter formatting behavior to add a trailing comma whenever a single-argument function breaks. This introduced a deviation in the case that a function contains a single argument, but _also_ includes a positional-only or keyword-only separator. Closes #9074.

MichaReiser approved these changes Nov 30, 2023

View reviewed changes

charliermarsh force-pushed the charlie/comma branch from 36b90a4 to c0f5f67 Compare November 30, 2023 04:47

Insert trailing comma when function breaks with single argument

c0f5f67

konstin approved these changes Nov 30, 2023

View reviewed changes

charliermarsh merged commit eaa3104 into main Dec 1, 2023
17 checks passed

charliermarsh deleted the charlie/comma branch December 1, 2023 02:49

miccal mentioned this pull request Dec 5, 2023

ruff 0.1.7 Homebrew/homebrew-core#156391

Merged

drhagen mentioned this pull request Dec 9, 2023

Ruff format always splits single positional-only argument list across two lines #9074

Closed

charliermarsh mentioned this pull request Dec 9, 2023

Avoid trailing comma for single-argument with positional separator #9076

Merged

zanieb mentioned this pull request Jan 2, 2024

Bump ruff from 0.1.6 to 0.1.9 encode/starlette#2396

Merged

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Insert trailing comma when function breaks with single argument #8921

Insert trailing comma when function breaks with single argument #8921

charliermarsh commented Nov 30, 2023 •

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charliermarsh commented Nov 30, 2023

zanieb commented Nov 30, 2023

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charliermarsh commented Nov 30, 2023

zanieb commented Nov 30, 2023

Insert trailing comma when function breaks with single argument #8921

Insert trailing comma when function breaks with single argument #8921

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charliermarsh commented Nov 30, 2023 • edited Loading

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charliermarsh commented Nov 30, 2023

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