Python 如何手动编写一个自己的LRU缓存装饰器的方法实现

import time
from collections import OrderedDict
 
'''
基于LRU，近期最少用缓存算法写的装饰器。
'''
 
 
class LRUCacheDict:
    def __init__(self, max_size=1024, expiration=60):
        self.max_size = max_size
        self.expiration = expiration
 
        self._cache = {}
        self._access_records = OrderedDict()  # 记录访问时间
        self._expire_records = OrderedDict()  # 记录失效时间
 
    def __setitem__(self, key, value):  # 设置缓存
        now = int(time.time())
        self.__delete__(key)  # 删除原有使用该Key的所有缓存
 
        self._cache[key] = value
        self._access_records = now  # 设置访问时间
        self._expire_records = now + self.expiration  # 设置过期时间
        self.cleanup()
 
    def __getitem__(self, key):  # 更新缓存
        now = int(time.time())
        del self._access_records[key]  # 删除原有的访问时按
        self._access_records[key] = now
        self.cleanup()
 
    def __contains__(self, key):  # 这个是字典默认调用key的方法
        self.cleanup()
        return key in self._cache
 
    def __delete__(self, key):
        if key in self._cache:
            del self._cache[key]  # 删除缓存
            del self._access_records[key]  # 删除访问时间
            del self._expire_records[key]  # 删除过期时间
 
    def cleanup(self):  # 用于去掉无效（超过大小）和过期的缓存
        if self._expire_records is None:
            return None
 
        pending_delete_keys = []
        now = int(time.time())
        for k, v in self._expire_records.items():  # 判断缓存是否失效
            if v < now:
                pending_delete_keys.append(k)
 
        for del_k in pending_delete_keys:
            self.__delete__(del_k)
 
        while len(self._cache) > self.max_size:  # 判断缓存是否超过长度
            for k in self._access_records.keys():  # LRU 是在这里实现的，如果缓存用的最少，那么它存入在有序字典中的位置也就最前
                self.__delete__(k)
                break

from functools import wraps
from my_cache import LRUCacheDict
 
 
def lru_cache(max_size=1024, expiration=60, types='LRU'):
    if types == 'lru' or types == 'LRU':
        my_cache = LRUCacheDict(max_size=max_size, expiration=expiration)
 
    def wrapper(func):
        @wraps(func)
        def inner(*args, **kwargs):
            key = repr(*args, **kwargs)
            try:
                result = my_cache[key]
            except KeyError:
                result = func(*args, **kwargs)
                my_cache[key] = result
            return result
 
        return inner
 
    return wrapper