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
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)