airflow-supervisor
Run and monitor supervisord-managed jobs from Apache Airflow.
Manage a dedicated supervisord instance on an Airflow worker or an SSH host.
Define its programs directly in a Python DAG or in airflow-config YAML.
from datetime import datetime, timezone
from airflow import DAG
from airflow_supervisor import ProgramConfiguration, Supervisor, SupervisorAirflowConfiguration
with DAG(
dag_id="nightly-supervisor",
schedule="@daily",
start_date=datetime(2025, 1, 1, tzinfo=timezone.utc),
catchup=False,
) as dag:
supervisor = Supervisor(
dag=dag,
cfg=SupervisorAirflowConfiguration(
working_dir="/var/tmp/nightly-supervisor",
port="127.0.0.1:9001",
program={"nightly": ProgramConfiguration(command="/bin/sleep 5")},
),
)
The lifecycle writes configuration, starts supervisord and its programs, monitors
program state with airflow-ha, and stops and removes the instance on successful
completion. SupervisorSSH runs configuration and daemon commands over SSH;
program control and checks use the remote XML-RPC endpoint.
Documentation
Start with the tutorial to run a self-contained local job and check its cleanup. For an existing deployment, choose a how-to guide:
| Execution | Inline Python | airflow-config YAML |
|---|---|---|
| Local worker | Run a local job | Configure a local job |
| SSH host | Run a job over SSH | Configure an SSH job |
The API reference describes configuration fields, defaults, and DAG constraints. Why Airflow delegates process ownership explains worker placement, SSH and XML-RPC, and the Python/YAML configuration choices.
Use the log forwarding and health-check guide to collect program output in task logs and monitor retained services between runs.
Published documentation is available at airflow-laminar.github.io/airflow-supervisor.
Ecosystem
- supervisor-pydantic supplies supervisord models and lifecycle tools.
- systemd-pydantic and cron-pydantic model alternative runtimes.
- airflow-systemd provides the analogous systemd lifecycle.
- airflow-cron converts cron jobs into ordinary Airflow tasks.
- airflow-pydantic supplies declarative task, host, and connection models.
- airflow-config produces YAML-driven DAGs.
1 maintainer
Metadata
1 maintainer
Release files for airflow-supervisor 1.11.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| airflow_supervisor-1.11.0.tar.gz | 26.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| airflow_supervisor-1.11.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 65.0 kB
Release files / airflow_supervisor-1.11.0.tar.gz
| Download URL | airflow_supervisor-1.11.0.tar.gz |
|---|---|
| Size | 26.4 kB |
| Tags | Source |
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| Tags | Python 3 |
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