Title

Python实现优先级队列

基于最大堆实现的优先级队列

class Array(object):
    def __init__(self, size=32, init=None):
        self._size = size
        self._items = [init] * self._size
    def __getitem__(self, index):
        return self._items[index]
    def __setitem__(self, index, value):
        self._items[index] = value
    def __len__(self):
        return self._size
    def clear(self, value=None):
        for i in range(len(self._items)):
            self._items[i] = value
    def __iter__(self):
        for item in self._items:
            yield item

class MaxHeap(object):
    def __init__(self, maxsize=None):
        self.maxsize = maxsize
        self._elements = Array(maxsize)
        self._count = 0

    def __len__(self):
        return self._count

    def add(self, value):
        if self._count >= self.maxsize:
            raise Exception("full")
        # 把值插入最后一位
        self._elements[self._count] = value
        self._count += 1
        # 维持最大堆属性
        self._siftup(self._count-1)

    def _siftup(self, ndx):
        if ndx > 0:
            parent = int((ndx-1)/2)
            # 如果插入的值大于 parent，一直交换
            if self._elements[ndx] > self._elements[parent]:
                self._elements[ndx], self._elements[parent] = self._elements[parent], self._elements[ndx]
                # 递归交换
                self._siftup(parent)

    def extract(self):
        """
        获取并且移除根节点
        :return:
        """
        if self._count <= 0:
            raise Exception("empty")
        # 保存root节点
        value = self._elements[0]
        self._count -= 1
        # 最右下的节点放到root后siftDown
        self._elements[0] = self._elements[self._count]
        # 维持堆特性
        self._siftdown(0)
        return value

    def _siftdown(self, ndx):
        # 下筛选操作
        left = 2 * ndx + 1
        right = 2 * ndx + 2
        # 确定哪个节点包含较大的值
        largest = ndx
        if (left < self._count and    # 有左孩子
                self._elements[left] >= self._elements[largest] and   # 左孩子的值大于要找的
                self._elements[left] >= self._elements[right]):       # 左孩子的值大于右孩子的值
            # 更新最大的下标为左孩子的下标
            largest = left
        elif right < self._count and self._elements[right] >= self._elements[largest]:
            # 更新最大的下标为右孩子的下标
            largest = right
        # 不等的话就交换更新 然后递归调用
        if largest != ndx:
            self._elements[ndx], self._elements[largest] = self._elements[largest], self._elements[ndx]
            self._siftdown(largest)

class PriorityQueue(object):
    def __init__(self, maxsize):
        self.maxsize = maxsize
        self._maxheap = MaxHeap(maxsize)

    def push(self, priority, value):
        # 注意这里把这个 tuple push 进去，python 比较 tuple 从第一个开始比较
        # 这样就很巧妙地实现了按照优先级排序
        entry = (priority, value)    # 入队的时候会根据 priority 维持堆的特性
        self._maxheap.add(entry)

    def pop(self, with_priority=False):
        entry = self._maxheap.extract()
        if with_priority:
            return entry
        else:
            return entry[1]

    def is_empty(self):
        return len(self._maxheap) == 0