apache-airflow-providers-docker

What it is and what it does

This is an Apache Airflow provider package that adds Docker container execution capabilities to Airflow DAGs. It wraps the Docker Python client and integrates it with Airflow's task execution model, allowing you to define tasks that run arbitrary Docker images as part of your workflow orchestration. The package depends on apache-airflow, docker, python-dotenv, and apache-airflow-providers-common-compat.

Typical use is to instantiate a DockerOperator in your DAG definition, specifying a container image and command. The operator handles pulling the image, running the container, and reporting task status back to Airflow. This is useful when you want to isolate task dependencies, run workloads in different environments, or leverage existing containerized applications without modifying them for Airflow's Python runtime.

Use it for:

• Run isolated Python or shell scripts in Docker containers without installing dependencies in the Airflow environment.
• Execute pre-built containerized applications (e.g., data processing tools, ML pipelines) as Airflow tasks.
• Orchestrate multi-language workflows by running containers with different language runtimes in a single DAG.
• Manage task resource limits and environment isolation by running tasks in separate containers.
• Integrate third-party containerized services into Airflow workflows without modifying their code.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Docker container execution into Apache Airflow workflows, enabling tasks to run inside Docker containers as part of DAG orchestration.

Yes. This is an actively maintained, production-stable provider from the Apache Airflow project with no known vulnerabilities, low install friction, and a permissive license. Install it if you need to run Docker containers as Airflow tasks. It is a standard integration for containerized workloads in Airflow environments.

Install

apache-airflow-providers-docker on PyPI

pip install apache-airflow-providers-docker

uv add apache-airflow-providers-docker

poetry add apache-airflow-providers-docker

Installing apache-airflow-providers-docker

Before you install

Low friction install as a wheel. Actively maintained with a release 6 days old. Requires Apache Airflow >=2.11.0, docker >=7.1.0, and python-dotenv >=0.21.0 as runtime dependencies.

License in practice

Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions.

Quickstart

pip install apache-airflow-providers-docker

from airflow.providers.docker.operators.docker import DockerOperator
from airflow import DAG

with DAG('example') as dag:
    task = DockerOperator(
        task_id='docker_task',
        image='my-image:latest',
        command=['python', 'script.py']
    )

Requires Apache Airflow >=2.11.0 and Docker daemon access; Python 3.10 or later.

Verify before relying

• Whether DockerOperator supports all Docker API features or has known limitations with specific image types or configurations.
• How the provider handles Docker daemon connectivity and socket mounting across different deployment environments.

Package facts

Evidence: apache_airflow_providers_docker-4.5.9-py3-none-any.whl

Keywords: airflow-provider, docker, airflow, integration

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