146. LRU Cache
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations:getandput.
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.
Follow up:
Could you do both operations inO(1)time complexity?
Method 1 Old school Hashmap + LinkedList
class Node():
def __init__(self, key, val):
self.key = key
self.val = val
self.next = None
self.prev = None
class LRUCache(object):
def __init__(self, capacity):
"""
:type capacity: int
"""
self.hm = {}
self.capacity = capacity
self.head = Node(None, None)
self.tail = Node(None, None)
self.head.next = self.tail
self.tail.prev = self.head
def get(self, key):
"""
:type key: int
:rtype: int
"""
if key in self.hm:
node = self.hm[key]
self.extract_node(node)
self.move_to_head(node)
return node.val
return -1
def put(self, key, value):
"""
:type key: int
:type value: int
:rtype: void
"""
if key in self.hm:
node = self.hm[key]
node.val = value
self.extract_node(node)
else:
node = Node(key, value)
if len(self.hm) == self.capacity:
last = self.tail.prev
del self.hm[last.key]
last.prev.next = self.tail
self.tail.prev = last.prev
self.hm[key] = node
self.move_to_head(node)
def extract_node(self, node):
node.prev.next = node.next
node.next.prev = node.prev
def move_to_head(self, node):
node.next = self.head.next
node.prev = self.head
self.head.next.prev = node
self.head.next = node