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system design
Senior
caching
#1
1. [OA] LRU Cache — Implement the caching layer ByteDance uses for its API responses
ByteDance requires an efficient caching mechanism to reduce latency for frequently accessed API responses. Your task is to implement an LRU (Least Recently Used) Cache class that supports
The LRU Cache should have a maximum capacity and evict the least recently used item when the capacity is reached.Method signatures:
Example 1:
Input:
Output:
Explanation: Returns
Input:
Output:
Explanation: Evicts key
get and put operations.Problem statement:The LRU Cache should have a maximum capacity and evict the least recently used item when the capacity is reached.Method signatures:
def get(self, key: int) -> int:: Get the value of the key if the key exists in the cache, otherwise return-1.def put(self, key: int, value: int) -> None:: Update the value of the key or insert the key if it is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting the new item.
Example 1:
Input:
cache = LRUCache(2)cache.put(1, 1)cache.put(2, 2)cache.get(1)Output:
1Explanation: Returns
1Example 2:Input:
cache.put(3, 3)cache.get(2)Output:
-1Explanation: Evicts key
2 and returns -1.Constraints:- Capacity of the cache will not exceed
3000. - All keys and values will be in the range of
1 <= key,value <= 10^4.
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