Lee-W commented on code in PR #46875: URL: https://github.com/apache/airflow/pull/46875#discussion_r1962958979
########## docs/apache-airflow/core-concepts/dags.rst: ########## @@ -20,7 +20,15 @@ DAGs ==== -A *DAG* (Directed Acyclic Graph) is the core concept of Airflow, collecting :doc:`tasks` together, organized with dependencies and relationships to say how they should run. +A *DAG* is the core concept of Airflow. A DAG is a model that encapsulates everything needed to execute a workflow: + +* **Schedule**: When the workflow should run. +* **Task Dependencies**: The order and conditions under which :doc:`tasks` execute. +* **Completion Behavior**: Actions to take when the entire workflow completes. +* **Error Handling**: Actions to take when a task fails. +* **Additional Parameters**: And many other operational details. + +The term "DAG" comes from the mathematical concept "directed acyclic graph", but the meaning in Airflow has evolved well beyond just the literal data structure associated with the mathematical DAG concept. Review Comment: > I think that when we are referring specifically to the python class DAG, then it is reasonable to write DAG because that is clear and precise. Yep, for the interfaces that we decide to keep, we should definitely use `DAG`. but for other mentions, `dag` might make more sense now. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
