Python Background Job Patterns
Implement scalable, asynchronous task processing and job queues using Celery, ARQ, and Redis in Python backends.
This skill provides production-ready patterns for offloading long-running tasks from the main application thread to robust background workers. It covers a spectrum of implementations, from lightweight ARQ setups optimized for FastAPI to enterprise-grade Celery workflows including chains, groups, and periodic scheduling. By providing standardized configurations for Redis-backed queues and deep integration patterns for modern web frameworks, it helps developers build responsive, resilient systems that handle report generation, notification delivery, and heavy data processing without blocking user requests or risking job loss during server restarts.