LeetCode 146. LRU Cache

题目

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:

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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

思路

数据结构。
python中有序的哈希表: OrderedDict(), 存储的顺序按照进入字典的顺序。

  • pop(key) - 得到key所对应的value
  • popitem() - 得到最后一个进表的value
  • popitem(last=False) - 得到第一个进表的value

代码

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class LRUCache(object):

def __init__(self, capacity):
"""
:type capacity: int
"""
self.capacity = capacity
self.cache = collections.OrderedDict()


def get(self, key):
"""
:type key: int
:rtype: int
"""
if key not in self.cache:
return -1
value = self.cache.pop(key)
self.cache[key] = value
return value


def put(self, key, value):
"""
:type key: int
:type value: int
:rtype: None
"""
if key in self.cache:
self.cache.pop(key)
elif self.cache and self.capacity == 0:
self.cache.popitem(last=False)
else:
self.capacity -= 1

self.cache[key] = value



# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)