鱼C论坛

 找回密码
 立即注册
查看: 1344|回复: 0

[学习笔记] Leetcode 146. LRU Cache

[复制链接]
发表于 2020-9-25 22:31:09 | 显示全部楼层 |阅读模式

马上注册,结交更多好友,享用更多功能^_^

您需要 登录 才可以下载或查看,没有账号?立即注册

x
Design a data structure that follows the constraints of a Least Recently Used (LRU) cache.

Implement the LRUCache class:

LRUCache(int capacity) Initialize the LRU cache with positive size capacity.
int get(int key) Return the value of the key if the key exists, otherwise return -1.
void put(int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache. If the number of keys exceeds the capacity from this operation, evict the least recently used key.
Follow up:
Could you do get and put in O(1) time complexity?



Example 1:

Input
["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"]
[[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
Output
[null, null, null, 1, null, -1, null, -1, 3, 4]

Explanation
LRUCache lRUCache = new LRUCache(2);
lRUCache.put(1, 1); // cache is {1=1}
lRUCache.put(2, 2); // cache is {1=1, 2=2}
lRUCache.get(1);    // return 1
lRUCache.put(3, 3); // LRU key was 2, evicts key 2, cache is {1=1, 3=3}
lRUCache.get(2);    // returns -1 (not found)
lRUCache.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3}
lRUCache.get(1);    // return -1 (not found)
lRUCache.get(3);    // return 3
lRUCache.get(4);    // return 4


Constraints:

1 <= capacity <= 3000
0 <= key <= 3000
0 <= value <= 104
At most 3 * 104 calls will be made to get and put.
class Node:
    def __init__(self, key, val):
        self.key = key
        self.val = val
        self.prev = None
        self.next = None

class LRUCache:
    def __init__(self, capacity: int):
        self.capacity = capacity
        self.head = Node(-1, -1)
        self.tail = Node(-1, -1)
        self.head.next = self.tail
        self.tail.prev = self.head
        self.hashmap = collections.defaultdict(Node)

    def get(self, key: int) -> int:
        if key not in self.hashmap:
            return -1
        node = self.hashmap[key]
        self.remove(node)
        self.add(node)
        return self.hashmap[key].val

    def put(self, key: int, value: int) -> None:
        if key in self.hashmap:
            self.hashmap[key].val = value
            node = self.hashmap[key]
            self.remove(node)
            self.add(node)
            return
        
        if len(self.hashmap) >= self.capacity:
            last = self.tail.prev
            self.hashmap.pop(last.key)
            self.remove(last)
        new_node = Node(key, value)
        self.hashmap[key] = new_node
        self.add(new_node)
        
    def remove(self, node: Node) -> None:
        prev = node.prev
        next = node.next
        prev.next = next
        next.prev = prev
        
    def add(self, node: Node) -> None:
        next = self.head.next
        self.head.next = node
        node.prev = self.head
        node.next = next
        next.prev = node
# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)

本帖被以下淘专辑推荐:

想知道小甲鱼最近在做啥?请访问 -> ilovefishc.com
回复

使用道具 举报

您需要登录后才可以回帖 登录 | 立即注册

本版积分规则

小黑屋|手机版|Archiver|鱼C工作室 ( 粤ICP备18085999号-1 | 粤公网安备 44051102000585号)

GMT+8, 2024-11-22 08:11

Powered by Discuz! X3.4

© 2001-2023 Discuz! Team.

快速回复 返回顶部 返回列表