import heapq
# [2,0,4,1]
 
# 1.创建堆
# 方法一：定义一个空列表，然后使用heapq.heqppush(item)函数把元素加入到堆中
item = 2
heap = []
heapq.heappush(heap,item)
# 方法二：使用heapq.heapify(list)将列表转换为堆结构
heap = [2,0,4,1]
heapq.heapify(heap)
 
# 2.heapq.heappush() 添加新元素 num
num = 3
heapq.heappush(heap,num)
 
# 3.heapq.heappop() 删除并返回堆顶元素
heapq.heappop(heap)
 
# 4.heapq.heappushpop() 比较添加元素num与堆顶元素的大小:如果num>堆顶元素，删除并返回堆顶元素，然后添加新元素num;如果num<堆顶元素，返回num，原堆不变
# 其实也就等价于 添加新元素num，然后删除并返回堆顶元素
num = 0
heapq.heappushpop(heap,num)
 
# 5.heapq.heapreplace() 删除并返回堆顶元素，然后添加新元素num
num = 5
heapq.heapreplace(heap,num)
 
# 6. heapq.merge() 合并多个排序后的序列成一个排序后的序列， 返回排序后的值的迭代器。
heap1 = [1,3,5,7]
heap2 = [2,4,6,8]
heap = heapq.merge(heap1,heap2)
print(list(heap))
 
# 7.heapq.nsmallest() 查询堆中的最小n个元素
n = 3
heap = [1,3,5,7,2,4,6,8]
print(heapq.nsmallest(n,heap)) # [1,2,3]
 
# 8.heapq.nlargest() 查询堆中的最大n个元素
n = 3
heap = [1,3,5,7,2,4,6,8]
print(heapq.nlargest(n,heap)) # [8,7,6]