Python Functools – lru_cache()

Python中的functools模块处理高阶函数，即操作（作为参数）或返回函数和其他此类可调用对象的函数。 functools 模块提供了大量的方法，例如cached_property(func), cmp_to_key(func), lru_cache(func), wraps(func),等。值得注意的是，这些方法以函数作为参数。

lru_cache()

lru_cache()是functools模块中的一个这样的函数，它通过使用记忆技术帮助减少函数的执行时间。

Syntax:
@lru_cache(maxsize=128, typed=False)

Parameters:
maxsize:This parameter sets the size of the cache, the cache can store upto maxsize most recent function calls, if maxsize is set to None, the LRU feature will be disabled and the cache can grow without any limitations
typed:
If typed is set to True, function arguments of different types will be cached separately. For example, f(3) and f(3.0) will be treated as distinct calls with distinct results and they will be stored in two separate entries in the cache

示例：1

from functools import lru_cache
import time
  
  
# Function that computes Fibonacci 
# numbers without lru_cache
def fib_without_cache(n):
    if n < 2:
        return n
    return fib_without_cache(n-1) + fib_without_cache(n-2)
      
# Execution start time
begin = time.time()
fib_without_cache(30)
  
# Execution end time
end = time.time()
  
print("Time taken to execute the\
function without lru_cache is", end-begin)
  
# Function that computes Fibonacci
# numbers with lru_cache
@lru_cache(maxsize = 128)
def fib_with_cache(n):
    if n < 2:
        return n
    return fib_with_cache(n-1) + fib_with_cache(n-2)
      
begin = time.time()
fib_with_cache(30)
end = time.time()
  
print("Time taken to execute the \
function with lru_cache is", end-begin)

输出：

Time taken to execute the function without lru_cache is 0.4448213577270508
Time taken to execute the function with lru_cache is 2.8371810913085938e-05

示例 2：

from functools import lru_cache
  
@lru_cache(maxsize = 100)
def count_vowels(sentence):
    sentence = sentence.casefold()
    return sum(sentence.count(vowel) for vowel in 'aeiou')
      
print(count_vowels("Welcome to Geeksforgeeks"))

输出：

9