Practice LRU Cache

Read the task, work through the examples, and check your approach against the constraints. Use the original LeetCode task for coding and submissions.

Medium#146

LeetCode Problem

LRU Cache

Hash Table Linked List Design Doubly-Linked List

Problem Statement

Implement LRUCache(capacity), get(key), and put(key, value). get returns the stored value or -1 when absent. A successful get and every put make that key most recently used. put updates an existing key or inserts a new one; if insertion exceeds capacity, remove the least recently used key. Both operations must take O(1) average time. Practice approach: Keep a hash map from keys to nodes and a doubly linked list ordered by recency. Move an accessed node to the recent end. Evict from the opposite end and delete that key from the map. Updating a key must not allocate a second list entry.

Source: LRU Cache on LeetCode. Use the original task for its coding environment and submissions.

Examples

# Example 1

Input

LRUCache(2); put(1,10); put(2,20); get(1); put(3,30); get(2); get(3)

Output

[null,null,null,10,null,-1,30]

Explanation

Reading key 1 refreshes it, so inserting key 3 evicts key 2.

Constraints

1 <= capacity <= 3000

0 <= key <= 10000

0 <= value <= 100000

At most 200000 get and put calls.

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