1.5 实现优先级队列

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1.5 实现优先级队列

问题:

实现一个队列,能够按照给定的优先级排序,并且每次pop操作时都可以返回优先级最高的那个元素.

解决方案

1.import heapq2.class PriorityQueue:3.    def __init__(self):4.        self._queue=[]5.        self._index=06.    def push(self,item,priority):7.        heapq.heappush(self._queue,(-priority,self._index,item))8.        self._index +=19.    def pop(self):10.        return heapq.heappop(self._queue)[-1]11.12.13.class Item:14.    def __init__(self,name):15.        self.name = name16.    def __repr__(self):17.        return ‘Item({!r})‘.format(self.name)18.19.q=PriorityQueue()20.q.push(Item(‘foo‘),3)21.q.push(Item(‘bar‘),4)22.q.push(Item(‘spam‘),3)23.24.print(q.pop())25.print(q.pop())26.print(q.pop())

讨论

  1. 这段代码的核心在于heapq中的push和pop操作. push和pop的复杂度为O(logN)总的来说,效率相对较高.
  2. heapq是一个最小堆. 也就是说,堆中的对象必须是可以比较大小的. 而Item的实例并不能比较大小. 所以我们可以构造一个元组(priority,item)但是这样做不到所有数据的唯一性. 因此,再加一个index

知识补充

heapq模块

  • heap是一个二叉树结构,初始化为一个空列表. 其父节点永远比子节点小.heap[k] <= heap[2*k+1] and heap[k] <= heap[2*k+2] for all k, counting elements from zero.
  • python中的heap是一个最小堆,也就是说,heap[0]永远是最小的那个元素.
  • 常用函数:

    • heapq.heappush(heap,item) push操作
    • heapq.heappop(heap) pop操作,每次返回heap[0],如果heap空了,则抛出IndexError异常
    • heapq.heappushpop(heap, item) push&pop
    • heapq.heapify(x) 将一个list转化为heap
    • heapq.heapreplace(heap, item) 与pushpop不同,这个是先pop再push. 如果遇到空的heap会出现IndexError的异常.
    • heapq.merge(*iterables, key=None, reverse=False) 合并,不知道有啥用…
    • heapq.nlargest(n, iterable, key=None)
    • heapq.nsmallest(n, iterable, key=None)

比如实现一个简单的堆排序

1.def heapsort(iterable):2.    h=[]3.    for value in iterable:4.        heapq.heappush(h,value)5.    return[heapq.heappop(h) for i in range(len(h))]

repr和str函数

所有官方文档都在说,str函数是给人看的,repe函数是给编译器看的.

1. class Item:2.    def __init__(self,name):3.        self.name = name4.    def __str__(self):5.        return ‘here is {0} __str__ function‘.format(self.name)6.    def __repr__(self):7.        return ‘here is {0} __repr__ function‘.format(self.name)8.>>> boo = Item(‘boo‘)9.>>> boo10.here is boo __repr__ function11.>>> print(boo)12.here is boo __str__ function

通过上面这段代码简单来看,在repr函数没有重载的时候,默认会显示<main.Item object at 0x03CC1D70>类似这个样子,是一个地址. 也就是说这两个函数都是用来显示关于这个类的信息的. 而print函数会调用str函数,解释器会调用repr函数.

format()函数

format函数用于做str的格式化书写.可以使用{}来做占位符以提供一个模板.

比如:

1.#1.使用数字占位符2.>>> "User ID: {0}".format("root")3.‘User ID: root‘4.#2.使用类似变量的占位符5.>>> ‘User ID: {uid} Last seen: {last_login}‘.format(uid=‘root‘,last_login = ‘5 Mar 2008 07:20‘)6.‘User ID: root Last seen: 5 Mar 2008 07:20‘7.#3.大括号的转义8.format("Empty dict: {{}}")9.#4.在字典中使用10.>>> d2={‘jim‘:25,‘tom‘:27}11.>>> "jim‘s age is {0[jim]}".format(d2)12."jim‘s age is 25"

另外关于三个控制字符,Three conversion flags are currently supported: ‘!s’ which calls str() on the value, ‘!r’ which calls repr() and ‘!a’ which calls ascii().

>>> ‘{0},{1!r}‘.format(boo,boo)

‘here is boo __str__ function,here is boo __repr__ function‘

更具体的用法查文档吧…

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时间： 2024-12-16 23:15:29

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package code.test; import java.util.Comparator; import java.util.Iterator; import java.util.PriorityQueue; import java.util.Queue; /** * 实验表明,在java中: * 1.优先级队列打印或者迭代,得到的输出顺序为堆结构数组的顺序,大致有序但不完全保证顺序 * 2.由于堆排序是不稳定排序,在优先级相同的情况下,元素不会保持原来的顺序输出 * Created by

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转自:http://www.cnblogs.com/yangecnu/p/Introduce-Priority-Queue-And-Heap-Sort.html 在很多应用中,我们通常需要按照优先级情况对待处理对象进行处理,比如首先处理优先级最高的对象,然后处理次高的对象.最简单的一个例子就是,在手机上玩游戏的时候,如果有来电,那么系统应该优先处理打进来的电话. 在这种情况下,我们的数据结构应该提供两个最基本的操作,一个是返回最高优先级对象,一个是添加新的对象.这种数据结构就是优先级队列(Pri