functoolslrucache

Functoolslrucache is a term used in some Python environments to describe a least-recently-used (LRU) caching utility for function results. It is conceptually aligned with the functionality provided by Python’s built-in functools.lru_cache, offering a way to memoize expensive function calls and reuse results for repeated inputs.

Typically, functoolslrucache is exposed as a decorator factory. Usage resembles applying a decorator such as @functoolslrucache(maxsize=128, typed=False) to a function. The decorator creates an internal cache that maps a function’s arguments to its return value. The maxsize parameter controls how many entries are kept in the cache; when the cache is full, the least-recently used entry is evicted to make room for new ones. The typed option may cause distinctions between arguments of different types that are otherwise equivalent (for example, 1 and 1.0).

Core features commonly found in implementations include cache_info() to report statistics (hits, misses, current size, and max size) and cache_clear() to reset the cache. The cache typically requires that function arguments be hashable so they can form a stable cache key; keyword arguments are usually supported by normalizing them into the key.

Limitations and considerations include memory usage, as cached results consume memory proportional to the number of stored entries. Unhashable arguments cannot be cached without transformation. In multi-threaded or multi-process environments, cache behavior may differ; some implementations provide thread safety, while others require external synchronization or separate caches per process.

See also: functools.lru_cache, cache-tools libraries that offer alternative cache strategies, and discussions of memoization patterns in Python.