How mdrmuhaimin/base-airflow works
Base Airflow is a starter project for defining and running scheduled workflows. Its demonstrated user-to-result path is a daily DAG run: Airflow executes extract, transform, and load tasks, passing task results through TaskFlow/XCom; the final task prints the total order value. The README also documents running the project with airflowctl or Docker Compose. The repository includes only one example DAG; the deployment configuration and broader Airflow internals are not sampled, so those relationships are shown only at the documented level.
Main entry points: docker-compose.yaml Docker Compose · example_dag_basic.py Extract orders · settings.yaml Airflow settings
Components 10
Project entry
- airflowctl
- Docker Compose
docker-compose.yaml
Workflow runtime
- DAG definitions
airflow/dags/example_dag_basic.py - Airflow scheduler
- Extract orders
airflow/dags/example_dag_basic.py - Transform totals
airflow/dags/example_dag_basic.py - Print total
airflow/dags/example_dag_basic.py
Run configurations
- Airflow settings
airflow/settings.yaml
Other components
- Project operator
- Printed order total
Connections 10
- Project operator → airflowctl: runs with
- airflowctl → Airflow scheduler: runs project
- Project operator → Docker Compose: starts with
- Docker Compose → Airflow scheduler: starts services
- Airflow settings → Airflow scheduler: configures
- DAG definitions → Airflow scheduler: defines schedule
- Airflow scheduler → Extract orders: dispatches daily
- Extract orders → Transform totals: passes XCom data
- Transform totals → Print total: passes XCom total
- Print total → Printed order total: prints