This “Live with Astronomer” session covers how to use the new dag.test() function to quickly test and debug your Airflow DAGs directly in your IDE. Using the dag.test() function speeds up iterative development by running tasks in a single, serialized Python process that does not require running Airflow.

Questions covered in this session include:

• How does the dag.test() function work and what version of Airflow do I need to use it?
• What are the prerequisites for the environment I run dag.test() in?
• Which operators does dag.test() work best with?
• How can I test argument-specific DAG runs with dag.test()?

Learn more about testing and debugging DAGs in this guide and in the official Airflow documentation. All code shown during this event can be found in this repo.

Explore our Comprehensive Guide to Data Pipeline Testing with Airflow.