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Python functools lru_cache() Function

The Python lru_cache() function is a decorator that wraps a function with a callable object, which calls the function more efficiently during the input operations with the same arguments. This caches the result of the recent maxsize calls. LRU is an abbreviation called Least Recently Used.

This function has a default maximum size of 128, and it will specify the most number of recent calls to be cached.

Following is the syntax for the lru_cache() function.

lru_cache(maxsize = 128, typed = False)

The parameters for the lru_cache() function are listed below −

• maxsize: This parameter specifies the cache size to store the most recent function. If the size is set to None, then the LRU feature will be disabled.
• typed: Functional arguments of different types will be cached separately.

This function returns the decorated function that wraps the original metadata.

In the example below, we are finding the number of vowels in a given string using the lru_cache() function with the specified maximum size.

from functools import lru_cache 
@lru_cache(maxsize = 110) 
def count_vowels(x): 
    x = x.casefold() 
    return sum(x.count(vowel) for vowel in 'aeiou') 
print(count_vowels("Welcome to Turoialspoint"))

The result is generated as follows −

10

Now, we are calculating Fibonacci sequence numbers using lru_cache(), where the sequence starts from 0 and 1, and each subsequent number is the sum of the previous numbers.

from functools import lru_cache
@lru_cache(maxsize=100)
def fib(x):
    if x < 4:
        return x
    return fib(x-2) + fib(x-1)
print(fib(20))

The code is generated as follows −

10946

In this example, we are using the lru_wraps() function to demonstrate the performance by caching results while calculating the sum of a numbers's digits in base 20.

from functools import lru_cache
@lru_cache(maxsize=100)
def sum(x):
    if x == 0:
        return 0
    return x % 20 + sum(x // 20)
print(sum(2398564))

The output is obtained as follows −

61

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