36. Caching data and results

The key here is to use the lru_cache decorator to cache results of functions that are idempotent, especially if they are expensive to call. Note how calls to add takes about 700 milliseconds? However, using the lru_cache decorator, subsequent calls are on the order of microseconds.

36.1. Don’t do this

def add(n):
    return sum([i for i in range(n)])

add(10000000)

36.2. Do this

from functools import lru_cache

@lru_cache(maxsize=32)
def add(n):
    return sum([i for i in range(n)])

add(10000000)