146-lru-cache

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Description

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

Solution(Python)

class ListNode:
    def __init__(self, key, val):
        self.val = val
        self.key = key
        self.prev = None
        self.next = None
        
class LRUCache:

    def __init__(self, capacity: int):
        self.capacity = capacity
        self.hashmap = {}
        self.head = ListNode(0,0)
        self.tail = ListNode(0,0)
        self.head.next = self.tail
        self.tail.prev = self.head
        self.cnt = 0
    
    def get(self, key: int) -> int:
        if key in  self.hashmap:
            node = self.hashmap[key]
            res = node.val
            self.__deleteNode(node)
            self.__addToHead(node)
            return res
        return -1

    def put(self, key: int, value: int) -> None:
        if key in self.hashmap:
            node = self.hashmap[key]
            node.val = value
            self.__deleteNode(node)
            self.__addToHead(node)
        else:
            node = ListNode(key, value)
            self.hashmap[key] = node
            if self.cnt < self.capacity:
                self.cnt += 1
                self.__addToHead(node)
            else:
                del self.hashmap[self.tail.prev.key]
                self.__deleteNode(self.tail.prev)
                self.__addToHead(node)
    def __deleteNode(self, node):
        node.prev.next = node.next
        node.next.prev = node.prev
        
    def __addToHead(self, node):
        node.next = self.head.next
        node.next.prev = node
        node.prev = self.head
        self.head.next = node
    


# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)