functool 的缓存与 lru_cache 的区别

Question

最近我遇到了functools.cache and didn't know how it differs from functools.lru_cache。

我找到了 posts about the difference between functools.cached_property 和 lru_cache，但没有找到 cache 和 lru_cache。

Answer 1

functools.cache是3.9版本新增的

文档指出：

Simple lightweight unbounded function cache. Sometimes called “memoize”.

Returns the same as lru_cache(maxsize=None), creating a thin wrapper around a dictionary lookup for the function arguments. Because it never needs to evict old values, this is smaller and faster than lru_cache() with a size limit.

文档中的示例：

@cache
def factorial(n):
    return n * factorial(n-1) if n else 1

>>> factorial(10)      # no previously cached result, makes 11 recursive calls
3628800
>>> factorial(5)       # just looks up cached value result
120
>>> factorial(12)      # makes two new recursive calls, the other 10 are cached
479001600

所以，简而言之：cache 和 lru_cache(maxsize=None) 完全相同（link 到 cpython 源）。但是在您不想限制缓存大小的情况下，使用 cache 可能会使代码更清晰，因为没有限制的最近最少使用的缓存没有多大意义。

functool 的缓存与 lru_cache 的区别

Difference between functool's cache and lru_cache

python

recursion

functional-programming