Slow, CPU-intensive work such as image resizing can easily block Python applications when handled synchronously. Background task processing provides a way to offload this kind of work, keeping applications responsive while expensive operations run elsewhere. Celery is a widely used solution in the Python ecosystem for coordinating this work through distributed task queues.
Using image processing as a concrete example, we will walk through setting up a minimal Celery application that generates thumbnails and resized images in the background. Along the way, it introduces message brokers in practical terms and shows how tasks flow from the application to worker processes without blocking the main program.