Description
Celery is a distributed system for message processing in Python first released in 2009, not long after Django itself. With over 20,000 stars on GitHub, it remains one of the most popular Django-adjacent Python packages. Similarly, my colleague Dan's post on the Caktus blog, "How to Use Celery for Scheduling Tasks," is by an order of magnitude one of the most popular pieces of content on our site.
In this talk, I'll explore what continues to make Celery a popular choice for message processing and background jobs, including: - The fundamentals of integrating Celery with a Django project - What is a message broker and how to choose one - What is a result backend and how to choose one - How to run tasks on pre-defined schedules, via settings and/or the database - How to break apart long-running tasks to maximize scalability - Other common patterns and anti-patterns when writing tasks with Celery