How to Implement LRU Caching in Python with @functools.lru_cache
The @functools.lru_cache decorator in Python3 enhances the performance of functions by caching their results. It uses a Least Recently Used (LRU) strategy to retain the most recently accessed results, thus avoiding redundant recalculations. Ideal for functions with expensive or frequent calls, it accepts parameters like maxsize to control the cache size and typed to distinguish calls with different argument types.
This Python code demonstrates using @functools.lru_cache to optimize the recursive computation of Fibonacci numbers. It caches results up to 128 calls, significantly improving efficiency by avoiding repeated calculations.
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