Caching Smarter, Not Harder: Demystifying Python’s lru_cache

Introduction to Caching

Caching is a technique that stores the result of expensive function calls and reuses them when the same inputs occur again. Python provides an easy way to implement caching using functools.lru_cache.

What is lru_cache?

The lru_cache is part of Python's functools module. It stands for Least Recently Used Cache and is a decorator that stores a function's results so that the same results can be reused if the function is called with the same arguments.

Key Features of lru_cache:

1. Max Size: The cache stores up to a specified number of results. Once this limit is reached, the least recently used result is discarded to make room for new results.
2. Thread-safe: lru_cache is thread-safe by default.
3. Time Complexity: Accessing the cache is efficient because it implements a hash map and linked list.

Basic Syntax

from functools import lru_cache
@lru_cache(maxsize=128)
def expensive_function(n)…