Python Coding challenge - Day 387| What is the output of the following Python Code?

 

Step-by-Step Execution:

1. Import lru_cache from functools

lru_cache (Least Recently Used Cache) is a built-in Python decorator that caches function calls to optimize performance.

It stores previously computed values, avoiding redundant calculations.

2. Define the Fibonacci Function with Caching

@lru_cache(maxsize=2)

def fib(n): 

    return n if n <= 1 else fib(n-1) + fib(n-2)

@lru_cache(maxsize=2): Caches the two most recently used function calls.

Base case: fib(0) = 0, fib(1) = 1

Recursive case: fib(n) = fib(n-1) + fib(n-2)

3. Compute fib(10)

print(fib(10))

The function computes fib(10) using recursion and caches recent calls.

Since maxsize=2, only the last two computed results remain cached.

4. Print Cache Information

print(fib.cache_info())

This outputs:

CacheInfo(hits=X, misses=Y, maxsize=2, currsize=2)

hits: How many times a cached value was used.

misses: How many times a new value was computed.

maxsize: Maximum cache size (2 in this case).

currsize: Current number of cached values (2).

Final Output:

Cache only keeps last 2 calls