Another thing to consider is look into airflow task policy and dag policy. These are mutation hooks that can be applied to all dags / tasks on your cluster
On Thu, Dec 2, 2021, 12:01 PM Jed Cunningham <[email protected]> wrote: > Hey Charlie, > > As Andrew mentioned, `default_args` is intended for task level args. You'd > be better off just unpacking your dict when you create the DAG. For example: > > ```python > defaults_for_dags = { > "max_active_runs": 1 > } > > with DAG(dag_id="something", **defaults_for_dags) as dag: > .... > ``` > > Jed > > On Thu, Dec 2, 2021 at 11:25 AM Charlie Griefer <[email protected]> > wrote: > >> Hey Folks. >> >> We're working on our first Airflow project at my company. There were a >> good number of DAG arguments that I expected we'd apply to all DAGs, so I >> put them in a "default_args" variable. >> >> It seems, however, that not all DAG args work if passed as default_args. >> For example, "max_active_runs". >> >> Some do work. It looks like the code under airflow.models.dag.py >> explicitly copy "start_date" and "end_date" variables out of default_args >> and pass to the DAG. >> >> I'm curious if there's a list of valid DAG args (currently using >> https://github.com/apache/airflow/blob/main/airflow/models/dag.py#L324 >> as a reference), and a list of valid "default_args" args, and maybe even >> which ones can go into either. >> >> Airflow 2.1.4, if that's relevant. >> >> Thanks! >> Charlie >> >> -- >> >> _______________________________ >> >> Charlie Griefer >> >> Software Engineer >> >> PlatformQ Education >> >> www.platformqedu.com >> >>
