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Caching & Redis

Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.

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Caching & Redis easy

How to memoize a function in Python with lru_cache

Use functools.lru_cache to memoize a recursive Fibonacci function, caching results for a fixed number of calls to avoid repeated computation.

lru_cache memoization functools
Python 
from functools import lru_cache

@lru_cache(maxsize=128)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

if __name__ == "__main__":
    for i in range(10):
        print(f"fib({i}) = {fibonacci(i)}")
    print(f"Cache info: {fibonacci.cache_info()}")
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