Lee-W commented on code in PR #39912:
URL: https://github.com/apache/airflow/pull/39912#discussion_r1650241056
##########
docs/apache-airflow/authoring-and-scheduling/deferring.rst:
##########
@@ -210,6 +207,49 @@ This is particularly useful when deferring is the only
thing the ``execute`` met
# We have no more work to do here. Mark as complete.
return
+To enable Dynamic Task Mapping support, you can define ``start_from_trigger``
and ``trigger_kwargs`` in the parameter of "__init__". Note that you don't need
to define both of them to use this feature, but you do need to use the exact
same parameter name. For example, if you define an argument as ``t_kwargs`` and
assign this value to ``self.start_trigger_args.trigger_kwargs``, it will not
work.
+
+.. code-block:: python
+
+ from datetime import timedelta
+ from typing import Any
+
+ from airflow.sensors.base import BaseSensorOperator
+ from airflow.triggers.temporal import TimeDeltaTrigger
+ from airflow.utils.context import Context
+
+
+ class WaitTwoHourSensor(BaseSensorOperator):
+ start_trigger_args = StartTriggerArgs(
+ trigger_cls="airflow.triggers.temporal.TimeDeltaTrigger",
+ trigger_kwargs={},
+ next_method="execute_complete",
+ timeout=None,
+ )
+
+ def __init__(
+ self,
+ *args: list[Any],
+ trigger_kwargs: dict[str, Any] | None,
+ start_from_trigger: bool,
+ **kwargs: dict[str, Any],
+ ) -> None:
+ super().__init__(*args, **kwargs)
+ self.start_trigger_args.trigger_kwargs = trigger_kwargs
+ self.start_from_trigger = start_from_trigger
+
+ def execute_complete(self, context: Context, event: dict[str, Any] |
None = None) -> None:
+ # We have no more work to do here. Mark as complete.
+ return
+
+These parameters can be mapped using the ``expand`` method.
+
+.. code-block:: python
+
+ WaitTwoHourSensor.partial(task_id="transform").expand(
+ trigger_kwargs=[{"moment": timedelta(hours=1)}],
start_from_trigger=True
Review Comment:
Updated the doc and added `partial` support
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