python实现一个优先级队列

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今天的主题是：怎样实现一个按优先级排序的队列?　并且在这个队列上面每次 pop 操作总是返回优先级最高的那个元素，这里需要借助heapq.py中的heapqpush()和heapqpop()方法完成该队列的设计．

１．heapq.py中部分源码显示如下：

def heappush(heap, item):
    """Push item onto heap, maintaining the heap invariant."""
    heap.append(item)
    _siftdown(heap, 0, len(heap)-1)

def heappop(heap):
    """Pop the smallest item off the heap, maintaining the heap invariant."""
    lastelt = heap.pop()    # raises appropriate IndexError if heap is empty
    if heap:
        returnitem = heap[0]
        heap[0] = lastelt
        _siftup(heap, 0)
        return returnitem
    return lastelt

２．借用heapq 模块实现了一个简单的优先级队列:PriorityQueue.py

import heapq

class PriorityQueue:
    def __init__(self):
        self._queue = []
        self._index = 0

    def push(self, item, priority):
        heapq.heappush(self._queue, (-priority, self._index, item))
        self._index += 1

    def pop(self):
        return heapq.heappop(self._queue)[-1]

class Item:
    def __init__(self, name):
        self.name = name

    def __repr__(self):
        return 'Item({!r})'.format(self.name)

if __name__ == "__main__":
    q = PriorityQueue()
    q.push(Item('python'), 1)
    q.push(Item('java'), 5)
    q.push(Item('swift'), 4)
    q.push(Item('c++'), 1)
    for i in range(4):
        print(q.pop())

3.result如下：

Item('java')
Item('swift')
Item('python')
Item('c++')

Process finished with exit code 0

４．总结：

仔细观察可以发现,第一个 pop() 操作返回优先级最高的元素．另外注意到如果两个有着相同优先级的元素 ( python 和 c++ ),pop 操作按照它们被插入到队列的顺序返回的,且index 变量的作用是保证同等优先级元素的正确排序（some of from Python Cookbook）．