Run your dbt Core projects as Apache Airflow® DAGs and Task Groups with a few lines of code. Benefits include:
- Run dbt projects against Airflow connections instead of dbt profiles
- Native support for installing and running dbt in a virtual environment to avoid dependency conflicts with Airflow
- Run tests immediately after a model is done to catch issues early
- Utilize Airflow's data-aware scheduling to run models immediately after upstream ingestion
- Turn each dbt model into a task/task group complete with retries, alerting, etc.
Check out the Getting Started guide on our docs. See more examples at /dev/dags and at the cosmos-demo repo.
You can render a Cosmos Airflow DAG using the DbtDag
class. Here's an example with the jaffle_shop project:
astronomer-cosmos/dev/dags/basic_cosmos_dag.py
Lines 1 to 42 in 24aa38e
This will generate an Airflow DAG that looks like this:
- Join us on the Airflow Slack at #airflow-dbt
We follow Semantic Versioning for releases. Check CHANGELOG.rst for the latest changes.
All contributions, bug reports, bug fixes, documentation improvements, enhancements are welcome.
A detailed overview an how to contribute can be found in the Contributing Guide.
As contributors and maintainers to this project, you are expected to abide by the Contributor Code of Conduct.
This project follows Astronomer's Privacy Policy
Check the project's Security Policy to learn how to report security vulnerabilities in Astronomer Cosmos and how security issues reported to the Astronomer Cosmos security team are handled.