GitHub user pykenny edited a comment on the discussion: MappedTaskGroup without taskflow
>From documentation it's not recommended to use `MappedTaskGroup` directly >([reference](https://github.com/apache/airflow/blob/47e4fe6926fda9ffbd595a0985f05c22e272a61f/task-sdk/src/airflow/sdk/definitions/taskgroup.py#L612-L613)) > so I don't think it's not a good idea. If you want to avoid decorator syntax in DAG definition, it may be better to wire task inputs/outputs just at task level instead of using a mapped task group. Looks a bit redundant but I think it is logically equivalent to the original one. What about giving this adjustment a try? ```python ... from airflow.utils.task_group import TaskGroup ... with DAG( dag_id="dag_group_DTM", start_date=today("UTC").add(days=-1), schedule=timedelta(days=1), ): first = PythonOperator( task_id="first", python_callable=lambda : [1, 10, 20, 30] ) def sleep(duration): # It's recommended to place module imports in the task function (subroutine), # so that all required imports only happens when the task gets run. import time time.sleep(duration) with TaskGroup(group_id="group_1"): a = PythonOperator.partial(task_id="a", python_callable=sleep).expand(duration=duration.output) b = PythonOperator.partial(task_id="b", python_callable=sleep).expand(duration=duration.output) c = PythonOperator.partial(task_id="a", python_callable=sleep).expand(duration=duration.output) a >> b >> c ``` GitHub link: https://github.com/apache/airflow/discussions/50297#discussioncomment-13262214 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected]
