Medium
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.The functions get and put must each run in O(1) average 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 <= 30000 <= key <= 1040 <= value <= 105 * 105 calls will be made to get and put.interface ICacheNode {
    key: number
    value: number
    prev: ICacheNode | null
    next: ICacheNode | null
}
class CacheNode implements ICacheNode {
    public key: number
    public value: number
    public prev: ICacheNode
    public next: ICacheNode
    constructor(key: number, value: number, prev?: ICacheNode, next?: ICacheNode) {
        this.key = key
        this.value = value
        this.prev = prev ?? null
        this.next = next ?? null
    }
}
class LRUCache {
    private cache = new Map<number, CacheNode>()
    private capacity
    private head = new CacheNode(0, 0)
    private tail = new CacheNode(0, 0)
    constructor(capacity: number) {
        this.capacity = capacity
        this.head.next = this.tail
        this.tail.prev = this.head
    }
    private append(node: CacheNode) {
        const prev = this.tail.prev
        this.tail.prev = node
        node.next = this.tail
        node.prev = prev
        prev.next = node
    }
    private remove(node: CacheNode) {
        const { prev, next } = node
        prev.next = next
        next.prev = prev
        node.next = null
        node.prev = null
        return node
    }
    private promote(node: CacheNode) {
        const removed = this.remove(node)
        this.append(removed)
    }
    get(key: number): number {
        if (!this.cache.has(key)) {
            return -1
        }
        const node = this.cache.get(key)
        this.promote(node)
        return node.value
    }
    put(key: number, value: number): void {
        let node
        if (this.cache.has(key)) {
            node = this.cache.get(key)
            node.value = value
            this.promote(node)
        } else {
            if (this.capacity === this.cache.size) {
                const leastUsed = this.head.next
                this.cache.delete(leastUsed.key)
                this.remove(leastUsed)
            }
            node = new CacheNode(key, value)
            this.append(node)
        }
        this.cache.set(key, node)
    }
}
/*
 * Your LRUCache object will be instantiated and called as such:
 * var obj = new LRUCache(capacity)
 * var param_1 = obj.get(key)
 * obj.put(key,value)
 */
export { LRUCache }