请你设计并实现一个满足 LRU (最近最少使用) 缓存 约束的数据结构。
实现 LRUCache
类:
LRUCache(int capacity)
以 正整数 作为容量capacity
初始化 LRU 缓存int get(int key)
如果关键字key
存在于缓存中,则返回关键字的值,否则返回-1
。void put(int key, int value)
如果关键字key
已经存在,则变更其数据值value
;如果不存在,则向缓存中插入该组key-value
。如果插入操作导致关键字数量超过capacity
,则应该 逐出 最久未使用的关键字。
函数 get
和 put
必须以 O(1)
的平均时间复杂度运行。
输入: ["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"] [[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]] 输出: [null, null, null, 1, null, -1, null, -1, 3, 4] 解释: LRUCache lRUCache = new LRUCache(2); lRUCache.put(1, 1); // 缓存是 {1=1} lRUCache.put(2, 2); // 缓存是 {1=1, 2=2} lRUCache.get(1); // 返回 1 lRUCache.put(3, 3); // 该操作会使得关键字 2 作废,缓存是 {1=1, 3=3} lRUCache.get(2); // 返回 -1 (未找到) lRUCache.put(4, 4); // 该操作会使得关键字 1 作废,缓存是 {4=4, 3=3} lRUCache.get(1); // 返回 -1 (未找到) lRUCache.get(3); // 返回 3 lRUCache.get(4); // 返回 4
1 <= capacity <= 3000
0 <= key <= 104
0 <= value <= 105
- 最多调用
2 * 105
次get
和put
class ListNode:
def __init__(self, key=0, val=0, prev=None, next=None):
self.key = key
self.val = val
self.prev = prev
self.next = next
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.keynodes = {}
self.head = None
self.tail = None
def get(self, key: int) -> int:
if key not in self.keynodes:
return -1
self.__move2tail(key)
return self.keynodes[key].val
def put(self, key: int, value: int) -> None:
if len(self.keynodes) == 0:
self.head = ListNode(key, value)
self.tail = self.head
self.keynodes[key] = self.head
elif key not in self.keynodes:
self.tail.next = ListNode(key, value, self.tail)
self.tail = self.tail.next
self.keynodes[key] = self.tail
if len(self.keynodes) > self.capacity:
self.keynodes.pop(self.head.key)
self.head = self.head.next
self.head.prev = None
else:
self.keynodes[key].val = value
self.__move2tail(key)
def __move2tail(self, key: int) -> None:
if len(self.keynodes) <= 1 or key not in self.keynodes or key == self.tail.key:
pass
elif key == self.head.key:
self.head.next.prev = None
self.tail.next = self.head
self.head.prev = self.tail
self.tail = self.head
self.head = self.head.next
self.tail.next = None
else:
node = self.keynodes[key]
node.prev.next = node.next
node.next.prev = node.prev
node.prev = self.tail
self.tail.next = node
self.tail = node
# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)