大蟒蛇python教程共享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