# 使用优先级队列-heapq

代码：

```python
import heapq


class PriorityQueue:
    def __init__(self):
        # 队列数据存放变量
        self._queue=[]
        # 事例化对象索引值，以便用于排序
        self._index=0

    def push(self,item,priority):
        # 往（优先）队列中加数据
        # 以元组为判断依据，（优先级变量priority为负，实现优先级高到低优先级排序），
        # 元组第一个相同时，才会比较第二位（self._index）的值，其自增长，以保证顺序和加入顺序相同；第3为才是真正的数据
        heapq.heappush(self._queue,(-priority,self._index,item))
        self._index+=1

    def pop(self):
        # 取弹出数据元组的最后一位(-priority,self._index,item)，item位对象的数据
        #return heapq.heappop(self._queue)[2]
        return heapq.heappop(self._queue)[-1]


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

    def __repr__(self):
        # 以便于自动被print打印
        return 'Item:{}'.format(self.name)
q=PriorityQueue()
q.push(Item('AAA'),1)
q.push(Item('BBB'),9)
q.push(Item('CCC'),5)
q.push(Item('DDD'),3)
print(q.pop())
print(q.pop())
print(q.pop())
print(q.pop())
```

结果：

```python
Item:BBB
Item:CCC
Item:DDD
Item:AAA
```

视频：

```
wait
```

附 heapq堆数据结构使用

代码：

```python
import heapq
'''
堆是二叉树，最大堆中父节点大于或等于两个子节点，最小堆父节点小于或等于两个子节点。
'''
print('创建，获取最小值。heap[0]','-'*50)
nums = [2, 3, 5, 1, 54, 23, 132]
heap = []
print('nums',nums)
for num in nums:
    heapq.heappush(heap, num)  # 加入堆
print('heap[0]:',heap[0])  # 只获取最小值，不是弹出
print()



print('创建，转换列表成为堆结构。heapq.heapify(nums)','-'*50)
print(nums)
nums = [2, 3, 5, 1, 54, 23, 132]
heapq.heapify(nums)#转成堆结构，nums改变
print(nums)
print([heapq.heappop(nums) for _ in range(len(nums))])#转成堆结构才能按顺序打印
print()



print('合并多个排序序列成一个排序序列，返回值的迭代器。nums=heapq.merge(nums1,nums2)')
nums1 = [2, 3, 5, 1, 54, 23, 132]
nums1=sorted(nums1)
print('nums1',nums1)
nums2 = [22, 23, 25, 21, 254, 223, 2132]
nums2=sorted(nums2)
print('nums2',nums2)
nums=heapq.merge(nums1,nums2) #值的迭代器
print('nums',list(nums))
print()


print('删除堆中最小元素并加入一个元素23。heapq.heaprepalce()')
nums = [1, 2, 4, 5, 3]
print('nums',nums)
heapq.heapreplace(nums, 23)
print([heapq.heappop(nums) for _ in range(len(nums))])
print()


print('最大/小的k个值。heapq.nlargest(3, nums)/heapq.nsmallest(3, nums)')
nums = [1, 3, 4, 5, 2,9]
print(nums)
print(heapq.nlargest(3, nums))
print(heapq.nsmallest(3, nums))
```

结果：

```python
创建，获取最小值。heap[0] --------------------------------------------------
nums [2, 3, 5, 1, 54, 23, 132]
heap[0]: 1

创建，转换列表成为堆结构。heapq.heapify(nums) --------------------------------------------------
[2, 3, 5, 1, 54, 23, 132]
[1, 2, 5, 3, 54, 23, 132]
[1, 2, 3, 5, 23, 54, 132]

合并多个排序序列成一个排序序列，返回值的迭代器。nums=heapq.merge(nums1,nums2)
nums1 [1, 2, 3, 5, 23, 54, 132]
nums2 [21, 22, 23, 25, 223, 254, 2132]
nums [1, 2, 3, 5, 21, 22, 23, 23, 25, 54, 132, 223, 254, 2132]

删除堆中最小元素并加入一个元素23。heapq.heaprepalce()
nums [1, 2, 4, 5, 3]
[2, 3, 4, 5, 23]

最大/小的k个值。heapq.nlargest(3, nums)/heapq.nsmallest(3, nums)
[1, 3, 4, 5, 2, 9]
[9, 5, 4]
[1, 2, 3]
```

视频：

```
wait
```


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