LRU Cache
<p>Design a data structure that follows the constraints of a <strong><a href="https://en.wikipedia.org/wiki/Cache_replacement_policies#LRU" target="_blank">Least Recently Used (LRU) cache</a></strong>.</p>

<p>Implement the <code>LRUCache</code> class:</p>

<ul>
	<li><code>LRUCache(int capacity)</code> Initialize the LRU cache with <strong>positive</strong> size <code>capacity</code>.</li>
	<li><code>int get(int key)</code> Return the value of the <code>key</code> if the key exists, otherwise return <code>-1</code>.</li>
	<li><code>void put(int key, int value)</code> Update the value of the <code>key</code> if the <code>key</code> exists. Otherwise, add the <code>key-value</code> pair to the cache. If the number of keys exceeds the <code>capacity</code> from this operation, <strong>evict</strong> the least recently used key.</li>
</ul>

<p>The functions <code>get</code> and <code>put</code> must each run in <code>O(1)</code> average time complexity.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<pre>
<strong>Input</strong>
[&quot;LRUCache&quot;, &quot;put&quot;, &quot;put&quot;, &quot;get&quot;, &quot;put&quot;, &quot;get&quot;, &quot;put&quot;, &quot;get&quot;, &quot;get&quot;, &quot;get&quot;]
[[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
<strong>Output</strong>
[null, null, null, 1, null, -1, null, -1, 3, 4]

<strong>Explanation</strong>
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
</pre>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li><code>1 &lt;= capacity &lt;= 3000</code></li>
	<li><code>0 &lt;= key &lt;= 10<sup>4</sup></code></li>
	<li><code>0 &lt;= value &lt;= 10<sup>5</sup></code></li>
	<li>At most <code>2 * 10<sup>5</sup></code> calls will be made to <code>get</code> and <code>put</code>.</li>
</ul>
Design; Hash Table; Linked List; Doubly-Linked List
class LRUCache {
private:
    struct Node {
        int key, val;
        Node* prev;
        Node* next;
        Node(int key, int val)
            : key(key)
            , val(val)
            , prev(nullptr)
            , next(nullptr) {}
    };

    int size;
    int capacity;
    Node* head;
    Node* tail;
    unordered_map<int, Node*> cache;

    void removeNode(Node* node) {
        node->prev->next = node->next;
        node->next->prev = node->prev;
    }

    void addToHead(Node* node) {
        node->next = head->next;
        node->prev = head;
        head->next->prev = node;
        head->next = node;
    }

public:
    LRUCache(int capacity)
        : size(0)
        , capacity(capacity) {
        head = new Node(0, 0);
        tail = new Node(0, 0);
        head->next = tail;
        tail->prev = head;
    }

    int get(int key) {
        if (!cache.contains(key)) {
            return -1;
        }
        Node* node = cache[key];
        removeNode(node);
        addToHead(node);
        return node->val;
    }

    void put(int key, int value) {
        if (cache.contains(key)) {
            Node* node = cache[key];
            removeNode(node);
            node->val = value;
            addToHead(node);
        } else {
            Node* node = new Node(key, value);
            cache[key] = node;
            addToHead(node);
            if (++size > capacity) {
                node = tail->prev;
                cache.erase(node->key);
                removeNode(node);
                --size;
            }
        }
    }
};

/**
 * 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);
 */
