Description
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get
and put
.
get(key)
- Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(key, value)
- Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.
The cache is initialized with a positive capacity.
Follow up: Could you do both operations in O(1) time complexity?
Example:
LRUCache cache = new LRUCache( 2 /* capacity */ );
cache.put(1, 1);
cache.put(2, 2);
cache.get(1); // returns 1
cache.put(3, 3); // evicts key 2
cache.get(2); // returns -1 (not found)
cache.put(4, 4); // evicts key 1
cache.get(1); // returns -1 (not found)
cache.get(3); // returns 3
cache.get(4); // returns 4
Solutions
1. Hash Table + Double Linked List
# Time: O(1)
# Space: O(n)
class ListNode():
def __init__(self, key, value):
self.key = key
self.val = value
self.pre = None
self.next = None
class DoubleLinkedNode():
def __init__(self):
self.header = None
self.tail = None
def add_head(self, node):
if not self.header:
self.header = node
self.tail = node
else:
header = self.header
self.header = node
node.next = header
header.pre = node
def remove(self, node):
pre, next = node.pre, node.next
if pre:
pre.next = next
else:
self.header = next
if next:
next.pre = pre
else:
self.tail = pre
node.pre = None
node.next = None
# del node
def remove_last(self):
if not self.tail:
return None
tail = self.tail
self.remove(tail)
return tail
class LRUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.cache = dict()
self.size = 0
self.linkedlist = DoubleLinkedNode()
def get(self, key: int) -> int:
if key not in self.cache:
return -1
node = self.cache[key]
self.linkedlist.remove(node)
self.linkedlist.add_head(node)
return node.val
def put(self, key: int, value: int) -> None:
if key not in self.cache:
self.size += 1
node = ListNode(key, value)
self.cache[key] = node
self.linkedlist.add_head(node)
else:
node = self.cache[key]
node.val = value
self.linkedlist.remove(node)
self.linkedlist.add_head(node)
if self.size > self.capacity:
self.size -= 1
tail = self.linkedlist.remove_last()
del self.cache[tail.key]
# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)
# 18/18 cases passed (208 ms)
# Your runtime beats 64.76 % of python3 submissions
# Your memory usage beats 6.06 % of python3 submissions (22.5 MB)