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Workflow orchestration with Airflow

Python Airflow Pandas uv Docker

License

This setups the infrastructure for Airflow, in Docker, as close as possible to a deploy in a Kubernetes/Helm environment: having containers for the airflow-scheduler, airflow-web, airflow-triggerer, and airflow-worker (with the CeleryExecutor)

Getting Started

1. Start setting up the infrastructure in Docker with:

Airflow with CeleryExecutor:

docker compose -f compose.celery.yaml up -d

Airflow with LocalExecutor:

docker compose -f compose.local.yaml up -d

2. Airflow WebUI can be accessed at:

open http://localhost:8080

3. Airflow DAGs:

To deploy Airflow DAGs, just move them inside the dags folder and Airflow should pick it up soon enough

TODO's: