Caching Function Calls with LRU Cache

You can use the functools.lru_cache decorator to cache the results of a function call.

Here is an example:

from functools import lru_cache
 
@lru_cache(maxsize=32)
def fib(n):
    print(f"Calculating fib({n})")
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)

Usage:

>>> fib(10)
Calculating fib(10)
Calculating fib(9)
Calculating fib(8)
Calculating fib(7)
Calculating fib(6)
Calculating fib(5)
Calculating fib(4)
Calculating fib(3)
Calculating fib(2)
Calculating fib(1)
Calculating fib(0)
55
>>> fib(5)
5
>>> fib(12)
Calculating fib(12)
Calculating fib(11)
144

In the example above, the results of the function calls are cached. So, when we call fib(5) again, it doesn’t calculate the result again, but returns the cached result.

Note: You can also use fib.cache_info() to get information about the cache.

There are many other useful functions in the lru_cache object.

You can read more about them in the docs.