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.