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doc: dynamictaskmapping pythonoperator op_kwargs #39242

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Apr 25, 2024
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doc: dynamictaskmapping pythonoperator op_kwargs #39242

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18 changes: 18 additions & 0 deletions docs/apache-airflow/authoring-and-scheduling/dynamic-task-mapping.rst
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Expand Up @@ -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
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