【重点】【LRU】146.LRU缓存

题目

Python

自定义双向链表！！！

写法1

class Node:

    def __init__(self, key, value):
        self.key = key
        self.value = value
        self.prev = None
        self.next = None

class LRUCache:

    def __init__(self, capacity: int):
        self.capacity = capacity
        self.key_to_node = dict()
        self.dummy = Node(-1, -1)
        self.dummy.prev = self.dummy
        self.dummy.next = self.dummy

    def get(self, key: int) -> int:
        if key not in self.key_to_node:
            return -1
        node = self.key_to_node[key]
        self.remove(node)     # 访问过的节点放在最前面
        self.push_front(node)
        return node.value

    def put(self, key: int, value: int) -> None:
        if key in self.key_to_node:
            self.key_to_node[key].value = value
            self.get(key)
            return
        new_node = Node(key, value)
        self.key_to_node[key] = new_node
        self.push_front(new_node)
        if len(self.key_to_node) > self.capacity:
            del_node = self.dummy.prev
            del self.key_to_node[del_node.key]
            self.remove(del_node)
    
    def remove(self, del_node):
        del_node.prev.next = del_node.next
        del_node.next.prev = del_node.prev
        del_node.prev = None
        del_node.next = None

    def push_front(self, node):
        node.prev = self.dummy
        node.next = self.dummy.next
        node.prev.next = node
        node.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)

写法2

class Node:

    def __init__(self, key=0, value=0):
        self.key = key
        self.value = value
        self.prev = None
        self.next = None

class LRUCache:
    def __init__(self, capacity: int):
        self.capacity = capacity
        self.dummy = Node()  # 哨兵节点
        self.dummy.prev = self.dummy
        self.dummy.next = self.dummy
        self.key_to_node = {}

    # 获取 key 对应的节点，同时把该节点移到链表头部
    def get_node(self, key: int) -> Optional[Node]:
        if key not in self.key_to_node:  # 没有这本书
            return None
        node = self.key_to_node[key]  # 有这本书
        self.remove(node)  # 把这本书抽出来
        self.push_front(node)  # 放在最上面
        return node

    def get(self, key: int) -> int:
        node = self.get_node(key)  # get_node 会把对应节点移到链表头部
        return node.value if node else -1

    def put(self, key: int, value: int) -> None:
        node = self.get_node(key)  # get_node 会把对应节点移到链表头部
        if node:  # 有这本书
            node.value = value  # 更新 value
            return
        self.key_to_node[key] = node = Node(key, value)  # 新书
        self.push_front(node)  # 放在最上面
        if len(self.key_to_node) > self.capacity:  # 书太多了
            back_node = self.dummy.prev
            # del self.key_to_node[back_node.key] # 删除dict中元素,常见两种方法!!!
            self.key_to_node.pop(back_node.key)
            self.remove(back_node)  # 去掉最后一本书

    # 删除一个节点（抽出一本书）
    def remove(self, x: Node) -> None:
        x.prev.next = x.next
        x.next.prev = x.prev

    # 在链表头添加一个节点（把一本书放在最上面）
    def push_front(self, x: Node) -> None:
        x.prev = self.dummy
        x.next = self.dummy.next
        x.prev.next = x
        x.next.prev = x

# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)

Java

法1：基于Java的LinkedHashMap

必须掌握法1。参考链接
关于LinkedHashMap的介绍

class LRUCache {
    int cap;
    LinkedHashMap<Integer, Integer> cache = new LinkedHashMap<>();
    public LRUCache(int capacity) { 
        this.cap = capacity;
    }
    
    public int get(int key) {
        if (!cache.containsKey(key)) {
            return -1;
        }
        // 将 key 变为最近使用
        makeRecently(key);
        return cache.get(key);
    }
    
    public void put(int key, int val) {
        if (cache.containsKey(key)) {
            // 修改 key 的值
            cache.put(key, val);
            // 将 key 变为最近使用
            makeRecently(key);
            return;
        }
        
        if (cache.size() >= this.cap) {
            // 链表头部就是最久未使用的 key
            int oldestKey = cache.keySet().iterator().next();
            cache.remove(oldestKey);
        }
        // 将新的 key 添加链表尾部
        cache.put(key, val);
    }
    
    private void makeRecently(int key) {
        int val = cache.get(key);
        // 删除 key，重新插入到队尾
        cache.remove(key);
        cache.put(key, val);
    }
}

法2：自定义数据结构

参考链接

public class LRUCache {
    class DLinkedNode {
        int key;
        int value;
        DLinkedNode prev;
        DLinkedNode next;
        public DLinkedNode() {}
        public DLinkedNode(int _key, int _value) {key = _key; value = _value;}
    }

    private Map<Integer, DLinkedNode> cache = new HashMap<Integer, DLinkedNode>();
    private int size;
    private int capacity;
    private DLinkedNode head, tail;

    public LRUCache(int capacity) {
        this.size = 0;
        this.capacity = capacity;
        // 使用伪头部和伪尾部节点
        head = new DLinkedNode();
        tail = new DLinkedNode();
        head.next = tail;
        tail.prev = head;
    }

    public int get(int key) {
        DLinkedNode node = cache.get(key);
        if (node == null) {
            return -1;
        }
        // 如果 key 存在，先通过哈希表定位，再移到头部
        moveToHead(node);
        return node.value;
    }

    public void put(int key, int value) {
        DLinkedNode node = cache.get(key);
        if (node == null) {
            // 如果 key 不存在，创建一个新的节点
            DLinkedNode newNode = new DLinkedNode(key, value);
            // 添加进哈希表
            cache.put(key, newNode);
            // 添加至双向链表的头部
            addToHead(newNode);
            ++size;
            if (size > capacity) {
                // 如果超出容量，删除双向链表的尾部节点
                DLinkedNode tail = removeTail();
                // 删除哈希表中对应的项
                cache.remove(tail.key);
                --size;
            }
        }
        else {
            // 如果 key 存在，先通过哈希表定位，再修改 value，并移到头部
            node.value = value;
            moveToHead(node);
        }
    }

    private void addToHead(DLinkedNode node) {
        node.prev = head;
        node.next = head.next;
        head.next.prev = node;
        head.next = node;
    }

    private void removeNode(DLinkedNode node) {
        node.prev.next = node.next;
        node.next.prev = node.prev;
    }

    private void moveToHead(DLinkedNode node) {
        removeNode(node);
        addToHead(node);
    }

    private DLinkedNode removeTail() {
        DLinkedNode res = tail.prev;
        removeNode(res);
        return res;
    }
}