airflow-cron

Generate declarative Airflow DAG models from cron configuration.

from airflow_cron import CronAirflowConfiguration, create_dags

config = CronAirflowConfiguration.model_validate(
    {
        "job": {
            "backup": {
                "schedule": "0 2 * * *",
                "command": "/opt/jobs/backup",
            }
        }
    }
)

dag_models = create_dags(config)

Each enabled user-crontab job becomes one airflow-pydantic DAG containing one Bash task. The result can be instantiated directly or added to an airflow-config configuration.

Documentation

• Tutorial: generate an Airflow DAG

• How-to guides

• Why cron jobs become DAG models

• API reference

Published documentation is available at airflow-laminar.github.io/airflow-cron.

Ecosystem

• cron-pydantic provides the source crontab models.

• supervisor-pydantic and systemd-pydantic model process managers.

• airflow-supervisor and airflow-systemd manage long-running jobs.

• airflow-pydantic supplies generated DAG and task models.

• airflow-config applies shared YAML configuration and materializes DAGs.

Note

This library was generated using copier from the Base Python Project Template repository.