How does LRU caching work in Python?

How does LRU caching work in Python?

LRU (Least Recently Used) caching is a strategy to manage limited cache space by evicting the least recently accessed items first. In Python, you can implement it using data structures like dictionaries and linked lists, or by using the built-in functools.lru_cache decorator.

Can you show me a code example of LRU caching?

Sure! Here's a simple example using functools.lru_cache:

from functools import lru_cache

@lru_cache(maxsize=3)
def get_data(n):
    print(f'Fetching data for {n}')
    return n * 2

# Usage
print(get_data(1))  # Fetching data for 1
print(get_data(2))  # Fetching data for 2
print(get_data(3))  # Fetching data for 3
print(get_data(1))  # Cached result
print(get_data(4))  # Fetching data for 4, evicts 2

What happens when the cache reaches its limit?

When the cache reaches its limit, the least recently used item is removed to make space for the new item. This ensures that the cache retains the most relevant data.

Are there any performance considerations I should be aware of?

Yes, while LRU caching can significantly speed up data retrieval, it also consumes memory. It's important to choose an appropriate cache size based on your application's needs.