This demo showcases how to use Trigger.dev with Python to process images from URLs and upload them to S3-compatible storage.

• A Trigger.dev task to trigger the image processing Python script, and to then upload the processed image to S3-compatible storage
• The Trigger.dev Python build extension to install dependencies and run Python scripts
• Pillow (PIL) for powerful image processing capabilities
• AWS SDK v3 for S3 uploads
• S3-compatible storage support (AWS S3, Cloudflare R2, etc.)

• Resize images with customizable dimensions
• Maintain aspect ratio
• Convert between formats (JPEG, PNG, WebP, GIF, AVIF)
• Adjust quality for optimized file sizes
• Apply filters (brightness, contrast, sharpness)
• Convert to grayscale
• Detailed metadata about the processed image

1. After cloning the repo, run npm install to install the dependencies.
2. Create a virtual environment python -m venv venv
3. Activate the virtual environment, depending on your OS: On Mac/Linux: source venv/bin/activate, on Windows: venv\Scripts\activate
4. Install the Python dependencies pip install -r requirements.txt
5. Set up your S3-compatible storage credentials in your environment variables, in .env for local development, or in the Trigger.dev dashboard for production:

   S3_ENDPOINT=https://your-endpoint.com
   S3_ACCESS_KEY_ID=your-access-key
   S3_SECRET_ACCESS_KEY=your-secret-key
   S3_BUCKET=your-bucket-name
   S3_PUBLIC_URL=https://your-public-url.com
   

6. Copy the project ref from your Trigger.dev dashboard and add it to the trigger.config.ts file.
7. Run the Trigger.dev CLI dev command (it may ask you to authorize the CLI if you haven't already).
8. Test the task in the dashboard by providing a valid image URL and processing options.
9. Deploy the task to production using the Trigger.dev CLI deploy command.

These are all optional parameters that can be passed to the image-processing.py Python script from the processImage.ts task.

{
  "imageUrl": "<your-image-url>",
  "height": 1200,
  "width": 900,
  "quality": 90,
  "maintainAspectRatio": true,
  "outputFormat": "webp",
  "brightness": 1.2,
  "contrast": 1.1,
  "sharpness": 1.3,
  "grayscale": false
}

• processImage.ts orchestrates the image processing workflow, handles S3 uploads, and returns metadata
• trigger.config.ts uses the Trigger.dev Python extension to install the dependencies and run the script
• image-processing.py contains the Python image processing logic with a comprehensive ImageProcessor class