[docs] Enforce use of Args: over Attrs: in class docstrings

docs/sphinx/_ext/autodoc_dagster.py

@@ -1,7 +1,7 @@
 import inspect
 import json
 import textwrap
-from typing import Any, List, Tuple, Type, Union, cast
+from typing import Any, List, Sequence, Tuple, Type, Union, cast
 
 import dagster._check as check
 import docutils.nodes
@@ -170,6 +170,12 @@ def add_content(self, more_content) -> None:
         super().add_content(more_content)
 
 
+def record_error(self, env, message: str) -> None:
+    if not hasattr(env, "dagster_errors"):
+        env.dagster_errors = []
+    env.dagster_errors.append(message)
+
+
 class DagsterClassDocumenter(ClassDocumenter):
     """Overrides the default autodoc ClassDocumenter to adds some extra options."""
 
@@ -184,11 +190,6 @@ def add_content(self, *args, **kwargs):
         for alias in self.options.get("deprecated_aliases", []):
             self.add_line(f"ALIAS: {alias}", source_name)
 
-    def record_error(self, message: str) -> None:
-        if not hasattr(self.env, "dagster_errors"):
-            self.env.dagster_errors = []
-        self.env.dagster_errors.append(message)
-
     def get_object_members(self, want_all: bool) -> Tuple[bool, ObjectMembers]:
         _, unfiltered_members = super().get_object_members(want_all)
         # Use form `is_public(self.object, attr_name) if possible, because to access a descriptor
@@ -210,13 +211,21 @@ def get_object_members(self, want_all: bool) -> Tuple[bool, ObjectMembers]:
                     "All public methods and properties must have docstrings."
                 )
                 logger.info(msg)
-                self.record_error(msg)
+                self.record_error(self.env, msg)
         return False, filtered_members
 
 
+def has_attrs(docstring: Sequence[str]) -> bool:
+    return any(line.startswith(".. attribute::") for line in docstring)
+
+
 # This is a hook that will be executed for every processed docstring. It modifies the lines of the
 # docstring in place.
 def process_docstring(app, what, name, obj, options, lines):
+    if has_attrs(lines):
+        message = f'Object {name} has "Attributes:" in docstring. Use "Args:" insetad.'
+        record_error(app.env, message)
+
     # Insert a "deprecated" sphinx directive (this is built-in to autodoc) for objects flagged with
     # @deprecated.
     if is_deprecated(obj):

python_modules/dagster/dagster/_core/definitions/asset_in.py

@@ -29,7 +29,7 @@ class AssetIn(
 ):
     """Defines an asset dependency.
 
-    Attributes:
+    Args:
         key_prefix (Optional[Union[str, Sequence[str]]]): If provided, the asset's key is the
             concatenation of the key_prefix and the input name. Only one of the "key_prefix" and
             "key" arguments should be provided.

python_modules/dagster/dagster/_core/definitions/asset_out.py

@@ -38,7 +38,7 @@ class AssetOut(
 ):
     """Defines one of the assets produced by a :py:func:`@multi_asset <multi_asset>`.
 
-    Attributes:
+    Args:
         key_prefix (Optional[Union[str, Sequence[str]]]): If provided, the asset's key is the
             concatenation of the key_prefix and the asset's name. When using ``@multi_asset``, the
             asset name defaults to the key of the "outs" dictionary Only one of the "key_prefix" and

python_modules/dagster/dagster/_core/definitions/freshness_policy_sensor_definition.py

@@ -96,7 +96,7 @@ class FreshnessPolicySensorContext(
 ):
     """The ``context`` object available to a decorated function of ``freshness_policy_sensor``.
 
-    Attributes:
+    Args:
         sensor_name (str): the name of the sensor.
         asset_key (AssetKey): the key of the asset being monitored
         freshness_policy (FreshnessPolicy): the freshness policy of the asset being monitored

python_modules/dagster/dagster/_core/definitions/multi_asset_sensor_definition.py

@@ -87,7 +87,7 @@ class MultiAssetSensorAssetCursorComponent(
     included in "unevaluated_partitioned_event_ids", because it's after the event that the cursor
     for its partition has advanced to, but trails "latest_evaluated_event_id".
 
-    Attributes:
+    Args:
         latest_consumed_event_partition (Optional[str]): The partition of the latest consumed event
             for this asset.
         latest_consumed_event_id (Optional[int]): The event ID of the latest consumed event for
@@ -183,7 +183,7 @@ class MultiAssetSensorEvaluationContext(SensorEvaluationContext):
     To update the cursor to the latest materialization and clear the unconsumed events, call
     `advance_all_cursors`.
 
-    Attributes:
+    Args:
         monitored_assets (Union[Sequence[AssetKey], AssetSelection]): The assets monitored
             by the sensor. If an AssetSelection object is provided, it will only apply to assets
             within the Definitions that this sensor is part of.

python_modules/dagster/dagster/_core/definitions/multi_dimensional_partitions.py

@@ -185,7 +185,7 @@ class MultiPartitionsDefinition(PartitionsDefinition[MultiPartitionKey]):
             A mapping of dimension name to partitions definition. The total set of partitions will
             be the cross-product of the partitions from each PartitionsDefinition.
 
-    Attributes:
+    Args:
         partitions_defs (Sequence[PartitionDimensionDefinition]):
             A sequence of PartitionDimensionDefinition objects, each of which contains a dimension
             name and a PartitionsDefinition. The total set of partitions will be the cross-product

python_modules/dagster/dagster/_core/definitions/run_request.py

@@ -32,7 +32,7 @@ class SkipReason(NamedTuple("_SkipReason", [("skip_message", PublicAttr[Optional
     """Represents a skipped evaluation, where no runs are requested. May contain a message to indicate
     why no runs were requested.
 
-    Attributes:
+    Args:
         skip_message (Optional[str]): A message displayed in the Dagster UI for why this evaluation resulted
             in no requested runs.
     """
@@ -112,7 +112,7 @@ class RunRequest(
     """Represents all the information required to launch a single run.  Must be returned by a
     SensorDefinition or ScheduleDefinition's evaluation function for a run to be launched.
 
-    Attributes:
+    Args:
         run_key (Optional[str]): A string key to identify this launched run. For sensors, ensures that
             only one run is created per run key across all sensor evaluations.  For schedules,
             ensures that one run is created per tick, across failure recoveries. Passing in a `None`
@@ -321,7 +321,7 @@ class DagsterRunReaction(
     """Represents a request that reacts to an existing dagster run. If success, it will report logs
     back to the run.
 
-    Attributes:
+    Args:
         dagster_run (Optional[DagsterRun]): The dagster run that originates this reaction.
         error (Optional[SerializableErrorInfo]): user code execution error.
         run_status: (Optional[DagsterRunStatus]): The run status that triggered the reaction.
@@ -359,14 +359,12 @@ class SensorResult(
 ):
     """The result of a sensor evaluation.
 
-    Attributes:
-        run_requests (Optional[Sequence[RunRequest]]): A list
-            of run requests to be executed.
+    Args:
+        run_requests (Optional[Sequence[RunRequest]]): A list of run requests to be executed.
         skip_reason (Optional[SkipReason]): A skip message indicating why sensor evaluation was skipped.
         cursor (Optional[str]): The cursor value for this sensor, which will be provided on the
             context for the next sensor evaluation.
-        dynamic_partitions_requests (Optional[Sequence[Union[DeleteDynamicPartitionsRequest,
-            AddDynamicPartitionsRequest]]]): A list of dynamic partition requests to request dynamic
+        dynamic_partitions_requests (Optional[Sequence[Union[DeleteDynamicPartitionsRequest, AddDynamicPartitionsRequest]]]): A list of dynamic partition requests to request dynamic
             partition addition and deletion. Run requests will be evaluated using the state of the
             partitions with these changes applied.
     """

python_modules/dagster/dagster/_core/definitions/run_status_sensor_definition.py

@@ -250,7 +250,7 @@ def __exit__(self, *exc) -> None:
 class RunFailureSensorContext(RunStatusSensorContext):
     """The ``context`` object available to a decorated function of ``run_failure_sensor``.
 
-    Attributes:
+    Args:
         sensor_name (str): the name of the sensor.
         dagster_run (DagsterRun): the failed run.
     """

python_modules/dagster/dagster/_core/definitions/sensor_definition.py

@@ -100,7 +100,7 @@ class SensorEvaluationContext:
     `SensorEvaluationContext` for testing purposes, use :py:func:`dagster.
     build_sensor_context`.
 
-    Attributes:
+    Args:
         instance_ref (Optional[InstanceRef]): The serialized instance configured to run the schedule
         cursor (Optional[str]): The cursor, passed back from the last sensor evaluation via
             the cursor attribute of SkipReason and RunRequest

python_modules/dagster/dagster/_core/definitions/source_asset.py

@@ -60,7 +60,7 @@
 class SourceAsset(ResourceAddable):
     """A SourceAsset represents an asset that will be loaded by (but not updated by) Dagster.
 
-    Attributes:
+    Args:
         key (Union[AssetKey, Sequence[str], str]): The key of the asset.
         metadata (Mapping[str, MetadataValue]): Metadata associated with the asset.
         io_manager_key (Optional[str]): The key for the IOManager that will be used to load the contents of

python_modules/dagster/dagster/_core/definitions/time_window_partition_mapping.py

@@ -47,7 +47,7 @@ class TimeWindowPartitionMapping(
     the upstream is hourly, then each daily partition in the downstream asset will map to the 24
     hourly partitions in the upstream that occur on that day.
 
-    Attributes:
+    Args:
         start_offset (int): If not 0, then the starts of the upstream windows are shifted by this
             offset relative to the starts of the downstream windows. For example, if start_offset=-1
             and end_offset=0, then the downstream partition "2022-07-04" would map to the upstream

python_modules/dagster/dagster/_core/definitions/time_window_partitions.py

@@ -50,7 +50,7 @@
 class TimeWindow(NamedTuple):
     """An interval that is closed at the start and open at the end.
 
-    Attributes:
+    Args:
         start (datetime): A pendulum datetime that marks the start of the window.
         end (datetime): A pendulum datetime that marks the end of the window.
     """

python_modules/dagster/dagster/_core/definitions/version_strategy.py

@@ -13,7 +13,7 @@
 class OpVersionContext(NamedTuple):
     """Provides execution-time information for computing the version for an op.
 
-    Attributes:
+    Args:
         op_def (OpDefinition): The definition of the op to compute a version for.
         op_config (Any): The parsed config to be passed to the op during execution.
     """
@@ -25,7 +25,7 @@ class OpVersionContext(NamedTuple):
 class ResourceVersionContext(NamedTuple):
     """Provides execution-time information for computing the version for a resource.
 
-    Attributes:
+    Args:
         resource_def (ResourceDefinition): The definition of the resource whose version will be computed.
         resource_config (Any): The parsed config to be passed to the resource during execution.
     """

python_modules/dagster/dagster/_core/events/__init__.py

@@ -379,7 +379,7 @@ class DagsterEvent(
 
     Users should not instantiate this class.
 
-    Attributes:
+    Args:
         event_type_value (str): Value for a DagsterEventType.
         job_name (str)
         node_handle (NodeHandle)

python_modules/dagster/dagster/_core/executor/init.py

@@ -19,7 +19,7 @@ class InitExecutorContext(
 ):
     """Executor-specific initialization context.
 
-    Attributes:
+    Args:
         job (IJob): The job to be executed.
         executor_def (ExecutorDefinition): The definition of the executor currently being
             constructed.

python_modules/dagster/dagster/_core/selector/subset_selector.py

@@ -54,7 +54,7 @@ class OpSelectionData(
 ):
     """The data about op selection.
 
-    Attributes:
+    Args:
         op_selection (List[str]): The queries of op selection.
         resolved_op_selection (AbstractSet[str]): The names of selected ops.
         parent_job_def (JobDefinition): The definition of the full job. This is used for constructing
@@ -90,7 +90,7 @@ class AssetSelectionData(
 ):
     """The data about asset selection.
 
-    Attributes:
+    Args:
         asset_selection (FrozenSet[AssetKey]): The set of assets to be materialized within the job.
         parent_job_def (JobDefinition): The definition of the full job. This is used for constructing
             pipeline snapshot lineage.

python_modules/libraries/dagster-airbyte/dagster_airbyte/asset_defs.py

@@ -397,7 +397,7 @@ class AirbyteConnectionMetadata(
 ):
     """Contains information about an Airbyte connection.
 
-    Attributes:
+    Args:
         name (str): The name of the connection.
         stream_prefix (str): A prefix to add to all stream names.
         has_basic_normalization (bool): Whether or not the connection has basic normalization enabled.

python_modules/libraries/dagster-airbyte/dagster_airbyte/types.py

@@ -26,7 +26,7 @@ class AirbyteOutput(
 ):
     """Contains recorded information about the state of a Airbyte connection job after a sync completes.
 
-    Attributes:
+    Args:
         job_details (Dict[str, Any]):
             The raw Airbyte API response containing the details of the initiated job. For info
             on the schema of this dictionary, see: https://airbyte-public-api-docs.s3.us-east-2.amazonaws.com/rapidoc-api-docs.html#post-/v1/jobs/get

python_modules/libraries/dagster-census/dagster_census/types.py

@@ -13,7 +13,7 @@ class CensusOutput(
 ):
     """Contains recorded information about the state of a Census sync after a sync completes.
 
-    Attributes:
+    Args:
         sync_run (Dict[str, Any]):
             The details of the specific sync run.
         source (Dict[str, Any]):

python_modules/libraries/dagster-databricks/dagster_databricks/databricks.py

@@ -208,7 +208,7 @@ def wait_for_run_to_complete(
 class DatabricksJobRunner:
     """Submits jobs created using Dagster config to Databricks, and monitors their progress.
 
-    Attributes:
+    Args:
         host (str): Databricks host, e.g. https://uksouth.azuredatabricks.net
         token (str): Databricks token
     """

python_modules/libraries/dagster-dbt/dagster_dbt/cloud/types.py

@@ -14,7 +14,7 @@ class DbtCloudOutput(DbtOutput):
     Note that users should not construct instances of this class directly. This class is intended
     to be constructed from the JSON output of dbt Cloud commands.
 
-    Attributes:
+    Args:
         run_details (Dict[str, Any]): The raw dictionary data representing the run details returned
             by the dbt Cloud API. For more info, see: https://docs.getdbt.com/dbt-cloud/api-v2#operation/getRunById
         result (Dict[str, Any]): Dictionary containing dbt-reported result information

python_modules/libraries/dagster-dbt/dagster_dbt/core/resources_v2.py

@@ -350,7 +350,7 @@ def _raise_on_error(self) -> None:
 class DbtCliResource(ConfigurableResource):
     """A resource used to execute dbt CLI commands.
 
-    Attributes:
+    Args:
         project_dir (str): The path to the dbt project directory. This directory should contain a
             `dbt_project.yml`. See https://docs.getdbt.com/reference/dbt_project.yml for more
             information.

python_modules/libraries/dagster-dbt/dagster_dbt/core/types.py

@@ -15,7 +15,7 @@ class DbtCliOutput(DbtOutput):
     Note that users should not construct instances of this class directly. This class is intended
     to be constructed from the JSON output of dbt commands.
 
-    Attributes:
+    Args:
         command (str): The full shell command that was executed.
         return_code (int): The return code of the dbt CLI process.
         raw_output (str): The raw output (``stdout``) of the dbt CLI process.

python_modules/libraries/dagster-dbt/dagster_dbt/dagster_dbt_translator.py

@@ -165,7 +165,7 @@ def get_group_name(cls, dbt_resource_props: Mapping[str, Any]) -> Optional[str]:
 class KeyPrefixDagsterDbtTranslator(DagsterDbtTranslator):
     """A DagsterDbtTranslator that applies prefixes to the asset keys generated from dbt resources.
 
-    Attributes:
+    Args:
         asset_key_prefix (Optional[Union[str, Sequence[str]]]): A prefix to apply to all dbt models,
             seeds, snapshots, etc. This will *not* apply to dbt sources.
         source_asset_key_prefix (Optional[Union[str, Sequence[str]]]): A prefix to apply to all dbt

python_modules/libraries/dagster-fivetran/dagster_fivetran/types.py

@@ -12,7 +12,7 @@ class FivetranOutput(
 ):
     """Contains recorded information about the state of a Fivetran connector after a sync completes.
 
-    Attributes:
+    Args:
         connector_details (Dict[str, Any]):
             The raw Fivetran API response containing the details of the sync'd connector. For info
             on the schema of this dictionary, see: https://fivetran.com/docs/rest-api/connectors#retrieveconnectordetails