164. LRU Cache

Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.

Follow up:
Could you do both operations in O(1) time complexity?

Example:

LRUCache cache = new LRUCache( 2 /* capacity */ );

cache.put(1, 1);
cache.put(2, 2);
cache.get(1);       // returns 1
cache.put(3, 3);    // evicts key 2
cache.get(2);       // returns -1 (not found)
cache.put(4, 4);    // evicts key 1
cache.get(1);       // returns -1 (not found)
cache.get(3);       // returns 3
cache.get(4);       // returns 4

Solution

(1) Java

class LRUCache {

    class Element {
        int val;
        int key;
        Element prev;
        Element next;

        public Element(int key, int val) {
            this.key = key;
            this.val = val;
        }
    }

    class Dll {
        Element head;
        Element tail;
        int len = 0;

        public Dll() {
        }

        public Element removeLast() {
            Element rst = null;
            if (tail != null) {
                rst = tail;
                if (tail == head) {
                    tail = head = null;
                } else {
                    tail = tail.prev;
                    tail.next = null;
                }
                len--;
            }            
            return rst;
        }

        public void addToHead(Element ele) {
            if (head == null) {
                head = ele;
                tail = ele;
            } else {
                ele.next = head;
                head.prev = ele;
                head = ele;
            }
            len++;
        }

        public void moveToHead(Element ele) {
            if (ele == head) {
                return;
            }
            if (ele.next != null) {
                ele.next.prev = ele.prev;
                ele.prev.next = ele.next;
            } else {
                tail = ele.prev;
                tail.next = null;
            }
            addToHead(ele);
            len--;
        }
    }

    private Dll dll;
    private Map<Integer, Element> cache = new HashMap<>();
    private int capacity;

    public LRUCache(int capacity) {
        dll = new Dll();
        this.capacity = capacity;
    }

    public int get(int key) {
        if (!cache.containsKey(key)) {
            return -1;
        }
        int rst = cache.get(key).val;
        dll.moveToHead(cache.get(key));
        return rst;
    }

    public void put(int key, int value) {
        if (cache.containsKey(key)) {
            Element ele = cache.get(key);
            if (ele.val == value)
                return;
            ele.val = value;
            dll.moveToHead(ele);
        } else {
            if (dll.len == capacity) {
                Element ele = dll.removeLast();
                cache.remove(ele.key);
            }
            Element ele = new Element(key, value);
            cache.put(key, ele);
            dll.addToHead(ele);
        }

    }
}

/**
 * Your LRUCache object will be instantiated and called as such:
 * LRUCache obj = new LRUCache(capacity);
 * int param_1 = obj.get(key);
 * obj.put(key,value);
 */

(2) Python

(3) Scala