redis-patterns

To implement a distributed lock in Python, use Redis to coordinate multi-instance applications and prevent concurrent write conflicts. This Skill demonstrates setting up distributed locking with redis-py across both synchronous and asyncio workflows.

Building a caching layer with Redis for FastAPI involves applying patterns like simple cache, cache invalidation, and cache-aside decorators. This approach optimizes fast reads and reduces database load using redis-py asyncio integration.

Yes, you can use Redis pub/sub for real-time updates in Django applications. This Skill demonstrates integrating pub/sub workflows with Django to enable scalable messaging and real-time event broadcasting.

Rate limiting with Redis in Python web apps works by tracking request counts per user or IP within a time window. This pattern coordinates multi-instance apps and protects endpoints from excessive traffic loads.

You do not strictly need asyncio to use Redis connection pools, but using redis-py asyncio is recommended for FastAPI integration. The Skill demonstrates both synchronous and asyncio connection pool configurations.