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‎03_链表/lru_cache.py‎

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if __name__ == '__main__':
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test()
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######################################### 使用双链表实现 LRUcache ####################################################
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"""
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一般面试中不会让我们直接用内置结构，所以这里提供一个自己实现的双链表+map lru 缓存。这也是力扣上的一道真题：
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[146] LRU 缓存 https://leetcode-cn.com/problems/lru-cache/description/
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"""
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class ListNode:
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def __init__(self, key=None, value=None):
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self.key = key
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self.value = value
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self.prev = self.next = None
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class List:
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def __init__(self):
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"""循环双链表。注意增加了虚拟头尾结点 head,tail 方便处理"""
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self.head = ListNode()
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self.tail = ListNode()
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self.head.prev = self.head.next = self.tail
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self.tail.next = self.tail.prev = self.head
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def delete_node(self, node): # 删除指定节点
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node.prev.next = node.next
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node.next.prev = node.prev
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def add_to_head(self, node): # 指定节点添加到 self.head 后
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nextnode = self.head.next
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node.next = nextnode
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node.prev = self.head
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self.head.next = node
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nextnode.prev = node
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class LRUCache(object):
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def __init__(self, capacity):
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"""
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思路：循环双链表 + 字典
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:type capacity: int
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"""
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self.map = dict()
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self.ll = List()
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self.capacity = capacity
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def get(self, key):
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"""
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:type key: int
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:rtype: int
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"""
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if key not in self.map:
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return -1
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node = self.map[key]
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self.ll.delete_node(node)
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self.ll.add_to_head(node)
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return node.value
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def put(self, key, value):
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"""
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:type key: int
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:type value: int
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:rtype: None
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"""
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if key in self.map:
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node = self.map[key]
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node.value = value # 修改结构体会也会修改 map 对应 value 的引用
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self.ll.delete_node(node)
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self.ll.add_to_head(node)
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else:
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if len(self.map) >= self.capacity: # 直接用 len(self.map) ，不需要self.size 字段了
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tailnode = self.ll.tail.prev
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self.ll.delete_node(tailnode)
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del self.map[tailnode.key]
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node = ListNode(key, value)
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self.map[key] = node
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self.ll.add_to_head(node)
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‎19_python内置常用算法和数据结构/builtins/index.html‎

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@@ -361,6 +361,22 @@ <h1 id="python-listdict">python list/dict 排序技巧</h1>
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# 同时获取最大值的下标和值
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l = [1,2,5,4,3]
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maxi, maxval = max(enumerate(l), key=lambda iv: iv[1]) # 2, 5
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# 获取字典对应的最大值对应的 key,value
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mydict = {'A':4,'B':10,'C':0,'D':87}
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maximum = max(mydict, key=mydict.get) # Just use 'min' instead of 'max' for minimum.
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maxk, maxv = maximum, mydict[maximum]
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# 或者
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maxk, maxv = max(mydict.items(), key=lambda k: k[1])
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# python3 排序list自定义函数(python2 直接用 cmp 参数)
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from functools import cmp_to_key
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nums = [3,2,1,4,5]
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sorted(nums, key= cmp_to_key(lambda a,b: a-b) ) # [1 ,2 ,3, 4, 5]
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sorted(nums, key= cmp_to_key(lambda a,b: b-a) ) # [5, 4, 3, 2, 1]
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# 一行代码判断列表是否有序
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issorted = all(l[i] &lt;= l[i+1] for i in range(len(l) - 1))
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</code></pre>
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<h1 id="_2">链表题目调试函数</h1>
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<pre><code class="language-py"># 编写链表题目经常用到的一些通用函数和调试函数，定义等，方便代码调试
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</code></pre>
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<h1 id="lru_cachecache">lru_cache/cache 优化记忆化搜索</h1>
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<p>python3 functools 模块的 cache 功能和 lru_cache(maxsize=None) 一样，不过更加轻量更快。在记忆化递归搜索的时候很方便。
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注意这里的参数 <code>maxsize=None</code> 一定要设置为 None，否则默认的 maxsize=128。
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举一个力扣上的例子，如果不加 cache 递归函数因为会大量重复计算直接超时，但是加一个装饰器就可以通过。</p>
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<pre><code class="language-py">&quot;&quot;&quot;
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[337] 打家劫舍 III

‎index.html‎

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<!--
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MkDocs version : 1.0.4
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Build Date UTC : 2022-03-10 01:16:59
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Build Date UTC : 2022-04-07 16:25:19
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-->

‎search/search_index.json‎

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‎sitemap.xml‎

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</urlset>

‎sitemap.xml.gz‎

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