# GeetCode Hub

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.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3}
lRUCache.get(3);    // return 3
lRUCache.get(4);    // return 4
```

Constraints:

• `1 <= capacity <= 3000`
• `0 <= key <= 104`
• `0 <= value <= 105`
• At most 2` * 105` calls will be made to `get` and `put`.

class LRUCache { public LRUCache(int capacity) { } public int get(int key) { } public void put(int key, int value) { } } /** * 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); */
Hard