BasPH commented on issue #6317: [AIRFLOW-5644] Simplify TriggerDagRunOperator usage URL: https://github.com/apache/airflow/pull/6317#issuecomment-596129144 Hi @Sharadh, The main motivation for this change was code clarity. Back then, I found the `TriggerDagRunOperator` very awkward to read and the `context` and `dag_run_obj` seem to come out of nowhere. You are correct in that it reduces the functionality, however I still think this change makes the code much better readable and makes the expected result clear. To achieve the same, I suggest to split your task into two: (1) a PythonOperator which succeeds if `should_trigger==True`, else raises `AirflowSkipException` (2) the TriggerDagRunOperator ```python from airflow.exceptions import AirflowSkipException step1 = SomeOperator() step2 = AnotherOperator() def _should_trigger(dag_run, **_): if not dag_run.conf["should_trigger"]: raise AirflowSkipException("should_trigger set to False") should_trigger = PythonOperator( task_id="should_trigger", python_callable=_should_trigger, provide_context=True, ) trigger_bar_dag = TriggerDagRunOperator( trigger_dag_id="bar", conf={"downstream_payload": "{{ dag_run.conf['downstream_payload'] }}"}, ) step1 >> step2 >> should_trigger >> trigger_bar_dag ``` Since you're passing the payload to the to-be-triggered-DAG, the `conf` arguments gets a little weird. It's templated, so I think the code above should do the trick. I didn't test it, so use at your own risk :-) The `should_trigger` task now determines whether or not to continue. If not, it will raise an AirflowSkipException, which sets its state to skipped, and automatically skips downstream tasks (assuming they have the default TriggerRule). Does this clarify?
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