This project was initiated as a foundation for workflow orchestration using Apache Airflow, fully containerized with Docker Compose.

Python dependency management is handled using uv — a blazing-fast package manager that replaces pip, pip-tools, and virtualenv.

airflow-project/
├── dags/ # Your custom DAGs
├── plugins/ # Optional plugins (custom operators, hooks, etc.)
├── docker-compose.yaml # Docker Compose configuration
├── .env.example # Example environment variables
├── requirements.txt # Additional Python dependencies (optional)
└── README.md # This file

• Docker
• Docker Compose
• uv (optional for local Python development)

1. Copy the example environment file and adjust if needed:

cp .env.example .env

2. Start the containers:

docker-compose up -d --build
# or docker-compose up -d 

3. Access the Airflow Web UI:

http://localhost:8080

Place your .py DAG files inside the ./dags/ folder and restart the containers if needed. DAGs can also be activated through the Airflow UI.

docker-compose down

To remove volumes and orphaned containers:

docker-compose down --volumes --remove-orphans

• This project does not include sensitive files. The actual .env file is excluded via .gitignore.
• You can use uv locally to install additional packages required by your DAGs:

uv pip install pandas requests