==================== 146. LRU缓存机制 ==================== https://leetcode-cn.com/problems/lru-cache/ 运用你所掌握的数据结构,设计和实现一个  LRU (最近最少使用) 缓存机制。它应该支持以下操作: 获取数据 get 和 写入数据 put 。 获取数据 get(key) - 如果密钥 (key) 存在于缓存中,则获取密钥的值(总是正数),否则返回 -1。 写入数据 put(key, value) - 如果密钥不存在,则写入其数据值。当缓存容量达到上限时,它应该在写入新数据之前删除最久未使用的数据值,从而为新的数据值留出空间。 进阶: 你是否可以在 O(1) 时间复杂度内完成这两种操作? 示例:: LRUCache cache = new LRUCache( 2 /* 缓存容量 */ ); cache.put(1, 1); cache.put(2, 2); cache.get(1); // 返回 1 cache.put(3, 3); // 该操作会使得密钥 2 作废 cache.get(2); // 返回 -1 (未找到) cache.put(4, 4); // 该操作会使得密钥 1 作废 cache.get(1); // 返回 -1 (未找到) cache.get(3); // 返回 3 cache.get(4); // 返回 4 .. code:: python class ListNode(object): def __init__(self, key, value): self.key = key self.val = value self.pre = None self.next = None class LinkedList(object): def __init__(self): self.head = ListNode(0, 0) self.tail = ListNode(0, 0) self.head.next = self.tail self.head.pre = self.tail self.tail.pre = self.head self.tail.next = self.head self.size = 0 def add_first(self, node): node.next = self.head.next node.pre = self.head self.head.next.pre = node self.head.next = node self.size += 1 def remove(self, node): node.pre.next = node.next node.next.pre = node.pre node.next = None node.pre = None self.size -= 1 def get_last(self): if self.head == self.tail: return return self.tail.pre class LRUCache(object): def __init__(self, capacity): """ :type capacity: int """ self.capacity = capacity self.linkedlist = LinkedList() self.cache = {} def get(self, key): """ :type key: int :rtype: int """ if key not in self.cache: return -1 val = self.cache[key].val self.put(key, val) return val def put(self, key, value): """ :type key: int :type value: int :rtype: None """ node = ListNode(key, value) if key in self.cache: self.linkedlist.remove(self.cache[key]) self.linkedlist.add_first(node) self.cache[key] = node else: if self.capacity == self.linkedlist.size: last = self.linkedlist.get_last() if last: self.linkedlist.remove(last) self.cache.pop(last.key) self.linkedlist.add_first(node) self.cache[key] = node # Your LRUCache object will be instantiated and called as such: # obj = LRUCache(capacity) # param_1 = obj.get(key) # obj.put(key,value)