Standardizing Python's internal caching decorators or exploring a lightweight standard library alternative

[vitorzwk]

While working on optimizing some data-heavy internal pipelines, I noticed an interesting pattern regarding how we handle function caching and memoization across various utilities.

Currently, developers frequently reach for external packages or write custom lightweight decorators when dealing with transient caching needs, even though functools.lru_cache is robust and built right into the standard library. However, functools.lru_cache can sometimes feel a bit rigid for modern asynchronous code, or when dealing with automatic cache invalidation, memory footprint limits without fixed bounds, or TTL (Time-To-Live) constraints without pulling in heavy third-party dependencies like cachetools.

I wanted to open a discussion on whether there's any appetite in the community or core development team to:

1. Expand or modernize some of the existing caching primitives within functools (e.g., native TTL support or memory-bounded variants that don't require manual maxsize tuning).
2. Document or recommend standard idioms for common memoization patterns that bridge the gap between simple one-offs and full-scale caching frameworks.

[NouraAlGahtani]

I think this is a pretty reasonable gap to discuss. I’ve also found myself using lru_cache for simple cases, but once you need things like TTL, manual invalidation, or async functions, it starts feeling like you’re either writing your own decorator or reaching for another library.

I’d personally be in favor of having a few more common patterns supported or at least documented in functools, especially TTL caching. I don’t think functools needs to become a full caching framework though there are already good libraries for more advanced use cases.

Even just having some recommended, standard approaches for things like async memoization, TTL, and invalidation would make things easier. It would save people from having 20 slightly different implementations of the same “simple” cache scattered across projects.

So yeah, I’d definitely be interested in seeing what a minimal API for this could look like without making functools overly complicated.