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146.py
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146.py
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'''
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.
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
'''
class Node(object):
def __init__(self, key, value):
self.key = key
self.value = value
self.next = None
self.prev = None
class LRUCache(object):
def __init__(self, capacity):
"""
:type capacity: int
"""
self.capacity = capacity
self.mapping = dict()
self.head = Node(0, 0)
self.tail = Node(0, 0)
self.head.next = self.tail
self.tail.prev = self.head
def get(self, key):
"""
:type key: int
:rtype: int
"""
if key in self.mapping:
node = self.mapping[key]
self.remove(node)
self.add(node)
return node.value
return -1
def put(self, key, value):
"""
:type key: int
:type value: int
:rtype: void
"""
if key in self.mapping:
self.remove(self.mapping[key])
node = Node(key, value)
if len(self.mapping) >= self.capacity:
next_head = self.head.next
self.remove(next_head)
del self.mapping[next_head.key]
self.add(node)
self.mapping[key] = node
def add(self, node):
tail = self.tail.prev
tail.next = node
self.tail.prev = node
node.prev = tail
node.next = self.tail
def remove(self, node):
prev_node = node.prev
prev_node.next = node.next
node.next.prev = prev_node
# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)