Celery: Distributed Task Queue

Summary

Celery is a distributed task queue system for Python that enables asynchronous execution of background jobs across multiple workers. It supports scheduling, retries, task workflows, and integrates seamlessly with Django, Flask, and FastAPI.

When to Use

• Background Processing: Offload long-running operations (email, file processing, reports)
• Scheduled Tasks: Cron-like periodic jobs (cleanup, backups, data sync)
• Distributed Computing: Process tasks across multiple workers/servers
• Async Workflows: Chain, group, and orchestrate complex task dependencies
• Real-time Processing: Handle webhooks, notifications, data pipelines
• Load Balancing: Distribute CPU-intensive work across workers

Don't Use When:

• Simple async I/O (use asyncio instead)
• Real-time request/response (use async web frameworks)
• Sub-second latency required (use in-memory queues)
• Minimal infrastructure (use simpler alternatives like RQ or Huey)