Airflow does not support DAGs with loops. After all, the abbreviation DAG stands for Directed Acyclic Graph, so we can’t have cycles. It is also not the standard usage of Airflow, which was built to support daily batch processing.
All of that does not stop us from using a simple trick that lets us run a DAG in a loop. To do that, we have to add a TriggerDagRunOperator as the last task in the DAG. In the task configuration, we specify the DAG id of the DAG that contains the task:
from airflow.operators.dagrun_operator import TriggerDagRunOperator
trigger_self = TriggerDagRunOperator(
task_id='repeat'
trigger_dag_id=dag.dag_id,
dag=dag
)
the_rest_of_the_dag >> trigger_self # add it as the last task
Want to build AI systems that actually work?
Download my expert-crafted GenAI Transformation Guide for Data Teams and discover how to properly measure AI performance, set up guardrails, and continuously improve your AI solutions like the pros.