Astronomer Cosmos

A framework for dynamically generating Apache Airflow DAGs from other tools and frameworks. Develop your workflow in your tool of choice and render it in Airflow as a DAG or Task Group!

Current support for:

Coming soon:

Jupyter
Hex
And more...open an issue if you have a request!

Quickstart

Check out the Quickstart guide on our docs.

Example Usage (dbt)

Cosmos lets you render dbt projects as Airflow DAGs and Task Groups. To render a DAG, import DbtDag and point it to your dbt project.

from pendulum import datetime
from airflow import DAG
from cosmos.providers.dbt.dag import DbtDag

# dag for the project jaffle_shop
jaffle_shop = DbtDag(
    dbt_project_name="jaffle_shop",
    conn_id="airflow_db",
    dbt_args={
        "schema": "public",
    },
    dag_id="jaffle_shop",
    start_date=datetime(2022, 11, 27),
)

Simiarly, you can render an Airflow TaskGroups using the DbtTaskGroup class. Here's an example with the jaffle_shop project:

from pendulum import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from cosmos.providers.dbt.task_group import DbtTaskGroup


with DAG(
    dag_id="extract_dag",
    start_date=datetime(2022, 11, 27),
    schedule="@daily",
):

    e1 = EmptyOperator(task_id="ingestion_workflow")

    dbt_tg = DbtTaskGroup(
        group_id="dbt_tg",
        dbt_project_name="jaffle_shop",
        conn_id="airflow_db",
        dbt_args={
            "schema": "public",
        },
    )

    e2 = EmptyOperator(task_id="some_extraction")

    e1 >> dbt_tg >> e2

Changelog

We follow Semantic Versioning for releases. Check CHANGELOG.rst for the latest changes.

Contributing Guide

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.

License