auto-transcoder

Auto-transcoder is a Python-based media transcoding application that automatically processes media files when they are added to a specified directory. It leverages Redis for tracking media state and Celery for handling transcoding tasks asynchronously. The application is containerised using Docker for easy deployment and management.

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📦 Features

• Automatic Transcoding: Detects new media files in a watched directory and triggers transcoding tasks.
• Redis Integration: Tracks media state (e.g., whether a file has been transcoded) using Redis.
• Celery Worker Support: Uses Celery to handle transcoding tasks in the background.
• Docker-Ready: Comes with Dockerfiles for both the server and worker components.
• Cross-Platform Compatibility: Runs on Linux (ARM64 and AMD64 architectures).

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📦 Requirements

• Redis Server: Required for media state tracking.
• Celery Worker: Needed to process transcoding tasks.
• Docker: For containerisation and deployment.

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📁 Project Structure

Here are a few key files in the project structure:

auto-transcoder/
├── server.Dockerfile
├── worker.Dockerfile
├── pyproject.toml
├── src/
│   └── auto_transcoder/
│       ├── model.py
│       ├── tasks.py
│       └── server.py

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🚀 Getting Started

1. Build Docker Images

Run the following commands to build the server and worker Docker images:

docker build -t auto-transcoder-server -f server.Dockerfile .
docker build -t auto-transcoder-worker -f worker.Dockerfile .

2. Run Redis Server

Ensure a Redis server is running. You can use Docker:

docker run --name redis -d -p 6379:6379 redis

3. Run the Server and Worker

To run the server and worker, use Docker Compose or individual commands. Here’s an example using Docker Compose:

# docker-compose.yml
services:
  redis:
    image: redis
    ports:
      - "6379:6379"
  server:
    image: auto-transcoder-server
    command:
      - /data
      - --recycle-bin
      - /data/recycle_bin
    ports:
      - "5000:5000"
    volumes:
      - /path/to/media:/data
    depends_on:
      - redis
    environment:
      - REDIS_URL=redis://redis:6379
  worker:
    image: auto-transcoder-worker
    volumes:
      - /path/to/media:/data
    depends_on:
      - redis
    environment:
      - REDIS_URL=redis://redis:6379

Start services with:

docker compose up -d

🔍 Note: Replace /path/to/media with the actual path to the directory you want to watch.

You may find a standalone docker-compose.yml example if you need help getting started here.

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📌 Configuration

Command Line Arguments

• directory_to_watch: Path to the directory where media files are stored. This is a required argument.
• --recycle-bin: Path to a directory where original media files will be moved after transcoding. If not provided, the original files will be deleted.

Environment Variables

• REDIS_URL: URL to your Redis instance (e.g., redis://redis:6379).

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🧪 Usage

1. Place media files in the watched directory.
2. The server will automatically detect new files and add them to the queue.
3. A Celery worker will process the transcoding tasks in the background.

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📦 Dependencies

This project uses the following dependencies (managed via Poetry):

• celery[redis]
• flask
• python-magic
• redis
• asyncio

Install them with:

poetry install

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🧱 Development

To set up the development environment:

1. Install Poetry.
2. Run poetry install to install dependencies.
3. Run the server with poetry run python src/auto_transcoder/server.py (ensure Redis is running).
4. Run the worker with poetry run celery -A auto_transcoder.tasks worker --loglevel=info.

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📝 Notes

• Ensure that both the worker and server instances have access to the media files at the same path.
  • If you're using Docker, this can be achieved by mounting the media directory as a volume in your Docker Compose setup.
• The pyproject.toml defines package structure and build settings. It currently uses poetry-core for building the package.
• The MediaDTO class encapsulates media file metadata, and the RedisManager class is used to manage Redis connections.

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📄 License

This project is licensed under the MIT License. See the LICENCE file for details.

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📈 Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a feature branch.
3. Make your changes.
4. Submit a pull request.

This repository uses British English spelling. Please ensure that your contributions adhere to this standard.

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📚 References

• Poetry Documentation
• Docker Documentation
• Redis Documentation
• Celery Documentation