LRU Cache

Design and implement an LRU (Least Recently Used) cache in C#. The cache should support Get(key) and Put(key, value) operations with O(1) time complexity.

- Get(key): Return the value of the key if it exists in the cache, otherwise return -1.
- Put(key, value): Insert or update the value of the key. If the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item.

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); // Cache capacity is 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, cache is {1=1, 3=3}
      
lRUCache.get(2);    // returns -1 (not found)
      
lRUCache.put(4, 4); // LRU key was 1, cache is {4=4, 3=3}
      
lRUCache.get(1);    // return -1 (not found)
      
lRUCache.get(3);    // return 3
      
lRUCache.get(4);    // return 4
    
  

Example 2

  
Input:
    
["LRUCache", "put", "get", "put", "get", "get"]
    
[[1], [2, 1], [2], [3, 2], [2], [3]]
  
Output:
    
[null, null, 1, null, -1, 2]
  
Explanation:
    

      
LRUCache lRUCache = new LRUCache(1); // Cache capacity is 1
      
lRUCache.put(2, 1); // cache is {2=1}
      
lRUCache.get(2);    // return 1
      
lRUCache.put(3, 2); // LRU key was 2, cache is {3=2}
      
lRUCache.get(2);    // returns -1 (not found)
      
lRUCache.get(3);    // returns 2
    
  

Constraints

  
1 <= capacity <= 3000
  
0 <= key <= 10^4
  
0 <= value <= 10^5
  
At most 2 * 10^5 calls will be made to get and put
  
Time Complexity: O(1) for both operations
  
Space Complexity: O(capacity)