Python Coding challenge - Day 551| What is the output of the following Python Code?

 

Code Explanation:

1. Importing Required Module

from functools import lru_cache

Imports the lru_cache decorator from Python's functools module.

Used to cache function results for faster access on repeated calls.

Follows a Least Recently Used (LRU) eviction strategy when the cache exceeds the set size.

2. Initializing the List

calls = []

Creates an empty list calls.

This will store every actual computation input (i.e., uncached calls to f(x)).

3. Defining a Cached Function

@lru_cache(maxsize=2)

def f(x):

    calls.append(x)

    return x * x

Defines a function f(x) that:

Appends x to the calls list.

Returns x² (square of x).

The function is decorated with @lru_cache(maxsize=2):

This means only the two most recently used unique inputs are stored.

If a new input is added beyond that, the least recently used is evicted from cache.

4. Making Function Calls

f(2)

- Not in cache → computed.

- `calls = [2]`

- Cache: `{2: 4}`

f(3)

Not in cache → computed.

calls = [2, 3]

Cache: {2: 4, 3: 9}

f(2)

- **In cache** → result reused.

- No change to `calls`.

- Cache still: `{2: 4, 3: 9}`

f(4)

Not in cache → computed.

Cache full → evicts least recently used, which is 3.

calls = [2, 3, 4]

Cache: {2: 4, 4: 16}

f(3)

- Not in cache (was evicted earlier) → computed again.

- Evicts `2` (now least recently used).

- `calls = [2, 3, 4, 3]`

- Cache: `{4: 16, 3: 9}`

5. Printing the Result

print(calls)

Output:

[2, 3, 4, 3]

These are the actual inputs for which the function was executed (not cached).

Final Output:

[2, 3, 4, 3]

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