fix(deps): bump ruff to 0.16.2 and reformat

dapr/ext/databricks/AGENTS.md

@@ -78,14 +78,14 @@ identity layer on top of the existing `dapr.ext.workflow.DaprWorkflowClient`.
 
 ```python
 from dapr.ext.databricks import (
-    register_workflow_sink,     # high-level: registers a foreach_batch_sink
-    DaprWorkflowBatchHandler,   # low-level: reusable batch-processing handler
-    WorkflowSinkConfig,        # typed config, if constructing a handler directly
-    default_row_mapper,       # the default Row -> dict mapper
-    DaprDatabricksError,     # base exception
-    SinkConfigurationError, # bad register_workflow_sink() config
-    MissingBusinessKeyError, # configured id_field/id_fields absent or null on a row
-    DaprDatabricksSinkError, # a micro-batch could not be durably handed off
+    register_workflow_sink,  # high-level: registers a foreach_batch_sink
+    DaprWorkflowBatchHandler,  # low-level: reusable batch-processing handler
+    WorkflowSinkConfig,  # typed config, if constructing a handler directly
+    default_row_mapper,  # the default Row -> dict mapper
+    DaprDatabricksError,  # base exception
+    SinkConfigurationError,  # bad register_workflow_sink() config
+    MissingBusinessKeyError,  # configured id_field/id_fields absent or null on a row
+    DaprDatabricksSinkError,  # a micro-batch could not be durably handed off
 )
 ```
 

dapr/ext/databricks/README.md

@@ -44,6 +44,7 @@ register_workflow_sink(
     namespace='orders',
 )
 
+
 @dp.append_flow(target='order_actions', name='order_actions_flow')
 def order_actions_flow():
     return spark.readStream.table('validated_orders')
@@ -81,7 +82,7 @@ register_workflow_sink(
 register_workflow_sink(
     name='transfers',
     workflow='process_transfer',
-    instance_id_factory=lambda row, batch_id: f"{row['account_id']}:{row['transaction_id']}",
+    instance_id_factory=lambda row, batch_id: f'{row["account_id"]}:{row["transaction_id"]}',
 )
 ```
 
@@ -108,6 +109,7 @@ handler = DaprWorkflowBatchHandler(
     WorkflowSinkConfig(name='orders', workflow='process_order', id_field='order_id')
 )
 
+
 @dp.foreach_batch_sink(name='orders')
 def orders_handler(df, batch_id):
     handler.process(df, batch_id)
@@ -171,24 +173,20 @@ scheduling latency. Business record contents are never logged.
 
 ```python
 register_workflow_sink(
-    name='orders',                 # sink name (foreach_batch_sink name)
-    workflow='process_order',     # registered Dapr Workflow name
-
-    id_field='order_id',            # business key column (mutually exclusive with the two below)
-    id_fields=None,                  # composite business key columns
-    instance_id_factory=None,         # (row, batch_id) -> business-key component
-
-    namespace='orders',                # identity partition; part of the instance ID
-    generation='v1',                    # identity epoch; bump to replay after a full refresh
-
-    input_mapper=None,                    # Row -> dict; defaults to a JSON-safe asDict()
-    metadata=True,                          # wrap input as {'data': ..., 'metadata': {...}}
-
-    max_in_flight=8,                          # bounded concurrent schedule_new_workflow calls
-    max_records_per_batch=None,                 # optional hard cap; fails the batch, never truncates silently
-
-    host=None, port=None,                         # Dapr endpoint; defaults to the standard SDK env/settings
-    allow_batch_position_identity=False,            # required opt-in to run without any id_field/id_fields/instance_id_factory
+    name='orders',  # sink name (foreach_batch_sink name)
+    workflow='process_order',  # registered Dapr Workflow name
+    id_field='order_id',  # business key column (mutually exclusive with the two below)
+    id_fields=None,  # composite business key columns
+    instance_id_factory=None,  # (row, batch_id) -> business-key component
+    namespace='orders',  # identity partition; part of the instance ID
+    generation='v1',  # identity epoch; bump to replay after a full refresh
+    input_mapper=None,  # Row -> dict; defaults to a JSON-safe asDict()
+    metadata=True,  # wrap input as {'data': ..., 'metadata': {...}}
+    max_in_flight=8,  # bounded concurrent schedule_new_workflow calls
+    max_records_per_batch=None,  # optional hard cap; fails the batch, never truncates silently
+    host=None,
+    port=None,  # Dapr endpoint; defaults to the standard SDK env/settings
+    allow_batch_position_identity=False,  # required opt-in to run without any id_field/id_fields/instance_id_factory
 )
 ```
 

dapr/ext/fastapi/AGENTS.md

@@ -32,8 +32,10 @@ Wraps a FastAPI instance to add Dapr pub/sub event handling.
 app = FastAPI()
 dapr_app = DaprApp(app, router_tags=['PubSub'])  # router_tags optional, default ['PubSub']
 
-@dapr_app.subscribe(pubsub='pubsub', topic='orders', route='/handle-order',
-                     metadata={}, dead_letter_topic=None)
+
+@dapr_app.subscribe(
+    pubsub='pubsub', topic='orders', route='/handle-order', metadata={}, dead_letter_topic=None
+)
 def handle_order(event_data):
     return {'status': 'ok'}
 ```

dapr/ext/flask/AGENTS.md

@@ -34,8 +34,10 @@ Wraps a Flask instance to add Dapr pub/sub event handling.
 app = Flask('myapp')
 dapr_app = DaprApp(app)
 
-@dapr_app.subscribe(pubsub='pubsub', topic='orders', route='/handle-order',
-                    metadata={}, dead_letter_topic=None)
+
+@dapr_app.subscribe(
+    pubsub='pubsub', topic='orders', route='/handle-order', metadata={}, dead_letter_topic=None
+)
 def handle_order():
     event_data = request.json
     return 'ok'

dapr/ext/flask/README.md

@@ -14,6 +14,7 @@ from dapr.ext.flask import DaprApp
 app = Flask('myapp')
 dapr_app = DaprApp(app)
 
+
 @dapr_app.subscribe(pubsub='pubsub', topic='some_topic', route='/some_endpoint')
 def my_event_handler():
     # request.data contains the pubsub event

dapr/ext/grpc/AGENTS.md

@@ -25,17 +25,17 @@ Installed via the `grpc` extra on core dapr: `pip install "dapr[grpc]"`.
 
 ```python
 from dapr.ext.grpc import (
-    App,                    # Main entry point — decorator-based gRPC server
-    Rule,                   # CEL-based topic rule with priority
-    SubscriptionMessage,    # Event type received by pub/sub topic handlers (preferred)
-    InvokeMethodRequest,    # Request object for service invocation handlers
-    InvokeMethodResponse,   # Response object for service invocation handlers
-    BindingRequest,         # Request object for input binding handlers
-    TopicEventResponse,     # Response object for pub/sub handlers
-    Job,                    # Job definition for scheduler
-    JobEvent,               # Job event received by handler
-    FailurePolicy,          # ABC for job failure policies
-    DropFailurePolicy,      # Drop on failure (no retry)
+    App,  # Main entry point — decorator-based gRPC server
+    Rule,  # CEL-based topic rule with priority
+    SubscriptionMessage,  # Event type received by pub/sub topic handlers (preferred)
+    InvokeMethodRequest,  # Request object for service invocation handlers
+    InvokeMethodResponse,  # Response object for service invocation handlers
+    BindingRequest,  # Request object for input binding handlers
+    TopicEventResponse,  # Response object for pub/sub handlers
+    Job,  # Job definition for scheduler
+    JobEvent,  # Job event received by handler
+    FailurePolicy,  # ABC for job failure policies
+    DropFailurePolicy,  # Drop on failure (no retry)
     ConstantFailurePolicy,  # Retry with constant interval
 )
 ```
@@ -51,22 +51,29 @@ The central entry point. Creates a gRPC server and provides decorators for handl
 ```python
 app = App()
 
+
 @app.method('method_name')
-def handle_method(request: InvokeMethodRequest) -> InvokeMethodResponse:
-    ...
+def handle_method(request: InvokeMethodRequest) -> InvokeMethodResponse: ...
+
+
+@app.subscribe(
+    pubsub_name='pubsub',
+    topic='orders',
+    metadata={},
+    dead_letter_topic=None,
+    rule=Rule('event.type == "order"', priority=1),
+    disable_topic_validation=False,
+)
+def handle_event(event: SubscriptionMessage) -> Optional[TopicEventResponse]: ...
 
-@app.subscribe(pubsub_name='pubsub', topic='orders', metadata={}, dead_letter_topic=None,
-                rule=Rule('event.type == "order"', priority=1), disable_topic_validation=False)
-def handle_event(event: SubscriptionMessage) -> Optional[TopicEventResponse]:
-    ...
 
 @app.binding('binding_name')
-def handle_binding(request: BindingRequest) -> None:
-    ...
+def handle_binding(request: BindingRequest) -> None: ...
+
 
 @app.job_event('job_name')
-def handle_job(event: JobEvent) -> None:
-    ...
+def handle_job(event: JobEvent) -> None: ...
+
 
 app.register_health_check(lambda: None)  # Not a decorator — direct registration
 ```

dapr/ext/rag/AGENTS.md

@@ -118,10 +118,15 @@ per-adapter optional-import guards).
 
 ```python
 from dapr.ext.rag import (
-    DurableRAGPipeline, PipelineConfig,
-    S3Source, AzureBlobSource,
-    UnstructuredParser, TextSplitter, OpenAIEmbedder,
-    PgVectorStore, PineconeVectorStore,
+    DurableRAGPipeline,
+    PipelineConfig,
+    S3Source,
+    AzureBlobSource,
+    UnstructuredParser,
+    TextSplitter,
+    OpenAIEmbedder,
+    PgVectorStore,
+    PineconeVectorStore,
     ActiveVersionResolver,
 )
 

dapr/ext/rag/README.md

@@ -11,7 +11,14 @@ pip install "dapr[rag,rag-azure,rag-pinecone]"   # Azure Blob + Pinecone
 ```
 
 ```python
-from dapr.ext.rag import DurableRAGPipeline, S3Source, UnstructuredParser, TextSplitter, OpenAIEmbedder, PgVectorStore
+from dapr.ext.rag import (
+    DurableRAGPipeline,
+    S3Source,
+    UnstructuredParser,
+    TextSplitter,
+    OpenAIEmbedder,
+    PgVectorStore,
+)
 
 pipeline = DurableRAGPipeline(
     source=S3Source(bucket='company-docs', prefix='policies/'),

dapr/ext/strands/AGENTS.md

@@ -31,9 +31,9 @@ Extends both `RepositorySessionManager` and `SessionRepository` from the Strands
 manager = DaprSessionManager(
     session_id='my-session',
     state_store_name='statestore',
-    dapr_client=client,          # DaprClient instance
-    ttl=3600,                    # Optional: TTL in seconds
-    consistency='eventual',      # 'eventual' (default) or 'strong'
+    dapr_client=client,  # DaprClient instance
+    ttl=3600,  # Optional: TTL in seconds
+    consistency='eventual',  # 'eventual' (default) or 'strong'
 )
 ```
 

dapr/ext/workflow/AGENTS.md

@@ -76,16 +76,16 @@ All public symbols are exported from `dapr.ext.workflow`:
 
 ```python
 from dapr.ext.workflow import (
-    WorkflowRuntime,          # Registration & lifecycle (start/shutdown)
-    DaprWorkflowClient,       # Sync client for scheduling/managing workflows
-    DaprWorkflowContext,      # Passed to workflow functions as first arg
+    WorkflowRuntime,  # Registration & lifecycle (start/shutdown)
+    DaprWorkflowClient,  # Sync client for scheduling/managing workflows
+    DaprWorkflowContext,  # Passed to workflow functions as first arg
     WorkflowActivityContext,  # Passed to activity functions as first arg
-    WorkflowState,            # Snapshot of a workflow instance's state
-    WorkflowStatus,           # Enum: UNKNOWN, RUNNING, COMPLETED, FAILED, TERMINATED, PENDING, SUSPENDED, STALLED
-    when_all,                 # Parallel combinator — wait for all tasks
-    when_any,                 # Race combinator — wait for first task
-    alternate_name,           # Decorator to set a custom registration name
-    RetryPolicy,              # Retry config for activities/child workflows
+    WorkflowState,  # Snapshot of a workflow instance's state
+    WorkflowStatus,  # Enum: UNKNOWN, RUNNING, COMPLETED, FAILED, TERMINATED, PENDING, SUSPENDED, STALLED
+    when_all,  # Parallel combinator — wait for all tasks
+    when_any,  # Race combinator — wait for first task
+    alternate_name,  # Decorator to set a custom registration name
+    RetryPolicy,  # Retry config for activities/child workflows
 )
 
 # Async client:

dapr/ext/workflow/docs/concurrency.md

@@ -75,6 +75,7 @@ cap:
 ```python
 _shared_client: httpx.AsyncClient | None = None
 
+
 def _get_client() -> httpx.AsyncClient:
     global _shared_client
     if _shared_client is None: