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https://issues.apache.org/jira/browse/AIRFLOW-1814?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16250028#comment-16250028
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Galak commented on AIRFLOW-1814:
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Thank you for your answer.
I agree, I can do it programmatically in the consume_value callable function,
but then I would add a dependency upon airflow objects.
It's a question of separation of concerns:
All reusable / generic functions should not know about how to retrieve an xcom
value; Moreover, they could be called with different values, depending on the
context: one could call it with a static value, another with a job execution
property, another one with a value coming from a previous task instance... Then
I would have to create a python wrapper function for every new call context.
IMHO, "consume_value" should only receive a value to consume, and apply its
business logic to it.
> Add op_args and op_kwargs in PythonOperator templated fields
> ------------------------------------------------------------
>
> Key: AIRFLOW-1814
> URL: https://issues.apache.org/jira/browse/AIRFLOW-1814
> Project: Apache Airflow
> Issue Type: Wish
> Components: operators
> Affects Versions: Airflow 1.8, 1.8.0
> Reporter: Galak
> Priority: Minor
>
> *I'm wondering if "_op_args_" and "_op_kwargs_" PythonOperator parameters
> could be templated.*
> I have 2 different use cases where this change could help a lot:
> +1/ Provide some job execution information as a python callable argument:+
> let's explain it through a simple example:
> {code}
> simple_task = PythonOperator(
> task_id='simple_task',
> provide_context=True,
> python_callable=extract_data,
> op_args=[
> "my_db_connection_id"
> "select * from my_table"
> "/data/{dag.dag_id}/{ts}/my_export.csv"
> ],
> dag=dag
> )
> {code}
> "extract_data" python function seems to be simple here, but it could be
> anything re-usable in multiple dags...
> +2/ Provide some XCom value as a python callable argument:+
> Let's say I a have a task which is retrieving or calculating a value, and
> then storing it in an XCom for further use by other tasks:
> {code}
> value_producer_task = PythonOperator(
> task_id='value_producer_task',
> provide_context=True,
> python_callable=produce_value,
> op_args=[
> "my_db_connection_id",
> "some_other_static_parameter",
> "my_xcom_key"
> ],
> dag=dag
> )
> {code}
> Then I can just configure a PythonCallable task to use the produced value:
> {code}
> value_consumer_task = PythonOperator(
> task_id='value_consumer_task',
> provide_context=True,
> python_callable=consume_value,
> op_args=[
> "{{ task_instance.xcom_pull(task_ids=None, key='my_xcom_key') }}"
> ],
> dag=dag
> )
> {code}
> I quickly tried the following class:
> {code}
> from airflow.operators.python_operator import PythonOperator
> class MyPythonOperator(PythonOperator):
> template_fields = PythonOperator.template_fields + ('op_args',
> 'op_kwargs')
> {code}
> and it worked like a charm.
> So could these 2 arguments be added to templated_fields? Or did I miss some
> major drawback to this change?
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