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new 6781c632e3 doc: dynamictaskmapping pythonoperator op_kwargs (#39242)
6781c632e3 is described below
commit 6781c632e3ba7fd4404f21c8b932e1374a4a9322
Author: raphaelauv <[email protected]>
AuthorDate: Thu Apr 25 06:40:06 2024 +0200
doc: dynamictaskmapping pythonoperator op_kwargs (#39242)
Co-authored-by: raphaelauv <[email protected]>
---
.../authoring-and-scheduling/dynamic-task-mapping.rst | 18 ++++++++++++++++++
1 file changed, 18 insertions(+)
diff --git
a/docs/apache-airflow/authoring-and-scheduling/dynamic-task-mapping.rst
b/docs/apache-airflow/authoring-and-scheduling/dynamic-task-mapping.rst
index acf9cfba3d..739bc6fee9 100644
--- a/docs/apache-airflow/authoring-and-scheduling/dynamic-task-mapping.rst
+++ b/docs/apache-airflow/authoring-and-scheduling/dynamic-task-mapping.rst
@@ -291,6 +291,24 @@ Sometimes an upstream needs to specify multiple arguments
to a downstream operat
This produces two task instances at run-time printing ``1`` and ``2``
respectively.
+Also it's possible to mix ``expand_kwargs`` with most of the operators
arguments like the ``op_kwargs`` of the PythonOperator
+
+.. code-block:: python
+
+ def print_args(x, y):
+ print(x)
+ print(y)
+ return x + y
+
+
+ PythonOperator.partial(task_id="task-1",
python_callable=print_args).expand_kwargs(
+ [
+ {"op_kwargs": {"x": 1, "y": 2}, "show_return_value_in_logs": True},
+ {"op_kwargs": {"x": 3, "y": 4}, "show_return_value_in_logs":
False},
+ ]
+ )
+
+
Similar to ``expand``, you can also map against a XCom that returns a list of
dicts, or a list of XComs each returning a dict. Re-using the S3 example above,
you can use a mapped task to perform "branching" and copy files to different
buckets:
.. code-block:: python
