146. LRU緩存機制

運用你所掌握的數據結構，設計和實現一個 LRU (最近最少使用) 緩存機制。它應該支持以下操作： 獲取數據 get 和 寫入數據 put 。

獲取數據 get(key) - 如果密鑰 (key) 存在於緩存中，則獲取密鑰的值（總是正數），否則返回 -1。
寫入數據 put(key, value) - 如果密鑰不存在，則寫入其數據值。當緩存容量達到上限時，它應該在寫入新數據之前刪除最近最少使用的數據值，從而爲新的數據值留出空間。

進階:

你是否可以在 O(1) 時間複雜度內完成這兩種操作？

LRUCache cache = new LRUCache( 2 /* 緩存容量 */ );

cache.put(1, 1);
cache.put(2, 2);
cache.get(1);       // 返回  1
cache.put(3, 3);    // 該操作會使得密鑰 2 作廢
cache.get(2);       // 返回 -1 (未找到)
cache.put(4, 4);    // 該操作會使得密鑰 1 作廢
cache.get(1);       // 返回 -1 (未找到)
cache.get(3);       // 返回  3
cache.get(4);       // 返回  4

python

class LRUCache(object):
    def __init__(self, capacity):
        self.capacity = capacity
        self._cache = []   
        self._cache_look_up = {}

    def get(self, key):
        if key in self._cache_look_up:
            self._cache.remove(key)
            self._cache.append(key)
            return self._cache_look_up[key]
        else:
            return -1 
        
    def put(self, key, value):
        if key in self._cache_look_up:
            self._cache_look_up[key] = value
            self._cache.remove(key)
            self._cache.append(key)
            return 
        else:
            
            if len(self._cache) == self.capacity:
                del_key = self._cache[0]
                self._cache = self._cache[1:]
                del self._cache_look_up[del_key]
                
            self._cache.append(key)
            self._cache_look_up[key] = value

python O(1)

class LinkNode(object):

    def __init__(self, key, val, prev_node=None, next_node=None):
        self.key = key
        self.val = val
        self.prev = prev_node
        self.next = next_node


class DoubleLinkList(object):

    def __init__(self, capacity):
        self.capacity = capacity
        self.size = 0

        self.head = None
        self.tail = None

    def append(self, node):
        """

        :param node:
        :return:

        append a node to the double link list last
        """
        if self.size == self.capacity:
            raise ValueError("The double link list has been full.")

        self.size += 1

        if self.head is None:
            self.head = self.tail = node
            return

        self.tail.next = node
        node.prev = self.tail
        self.tail = node

    def delete(self, node):
        """

        :param node:
        :return node:

        delete a node in double link list. switch(node):
           1.node == self.head
           2.node == self.tail
           3.node in the double link list middle
        """
        if self.size == 0:
            raise ValueError("can not delete empty double link list")

        self.size -= 1

        if node == self.head:
            if node.next:
                node.next.prev = None

            self.head = node.next
        elif node == self.tail:
            if node.prev:
                node.prev.next = None

            self.tail = node.prev
        else:
            node.prev.next = node.next
            node.next.prev = node.prev

        return node


class LRUCache(object):

    def __init__(self, capacity):
        self.capacity = capacity
        self.cache_look_up = {}
        self.cache_list = DoubleLinkList(capacity)

    def get(self, key):
        if key not in self.cache_look_up:
            return -1

        node = self.cache_look_up[key]
        self.cache_list.delete(node)
        self.cache_list.append(node)

        return node.val

    def put(self, key, value):
        if key in self.cache_look_up:
            node = self.cache_look_up[key]
            node.val = value
            self.cache_list.delete(node)
            self.cache_list.append(node)
        else:
            if self.capacity == self.cache_list.size:
                head_node = self.cache_list.delete(self.cache_list.head)
                del self.cache_look_up[head_node.key]

            new_node = LinkNode(key, value)
            self.cache_look_up[key] = new_node
            self.cache_list.append(new_node)

參考：https://blog.csdn.net/laughing2333/article/details/70231547