Python Coding challenge - Day 1123| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing lru_cache

from functools import lru_cache

Explanation

Imports lru_cache from the functools module.

It is used for memoization (caching function results).

2️⃣ Applying Decorator

@lru_cache(None)

Explanation

This decorator caches results of function calls.

None means unlimited cache size.

👉 So once a value is computed, it is stored and reused.

3️⃣ Defining Function

def f(n):

Explanation

Defines function f that takes input n.

4️⃣ Base Condition

if n <= 1:

    return n

Explanation

If n is 0 or 1, return n.

This is the base case of recursion.

5️⃣ Recursive Case

return f(n-1) + f(n-2)

Explanation

This is Fibonacci logic.

Computes:

f(n) = f(n-1) + f(n-2)

6️⃣ Calling Function

print(f(5))

Explanation

Calls f(5).

🔄 Execution (Step-by-Step)

Without cache:

f(5)

= f(4) + f(3)

= (f(3)+f(2)) + (f(2)+f(1))

= ...

👉 Many repeated calls!

⚡ With lru_cache

Each value is computed once only:

Call Value

f(0) 0

f(1) 1

f(2) 1

f(3) 2

f(4) 3

f(5) 5

📤 Final Output

5

Book: 900 Days Python Coding Challenges with Explanation