Python内置的heapq模块
Python3.4版本中heapq包含了几个有用的方法：
heapq.heappush(heap,item):将item，推入heap
>>> items = [1,2,9,7,3]
>>> heapq.heappush(items,10)
>>> items
[1, 2, 9, 7, 3, 10]
>>>
heapq.heappop(heap)：将heap的最小值pop出heap，heap为空时报IndexError错误
>>> heapq.heappop(items)#heap在pop时总是将最小值首先pop出
1
>>> items
[2, 3, 9, 7, 10]
>>>
heapq.heappushpop(heap,item)：pop出heap中最小的元素，推入item
>>> items
[2, 3, 9, 7, 10]
>>> heapq.heappushpop(items,11)
2
>>> items
[3, 7, 9, 11, 10]
>>>
heapq.heapify(x)：将list X转换为heap
>>> nums = [1,10,9,8]
>>> heap = list(nums)
>>> heapq.heapify(heap)
>>> heap
[1, 8, 9, 10]
>>>
heapq.heapreplace(heap,item)：pop出最小值，推入item，heap的size不变
>>> heap
[1, 8, 9, 10]
>>> heapq.heapreplace(heap,100)
1
>>> heap
[8, 10, 9, 100]
>>
heapq.merge(*iterable)：将多个可迭代合并，并且排好序，返回一个iterator
>>> heap
[8, 10, 9, 100]
>>> heap1 = [10,67,56,80,79]
>>> h = heapq.merge(heap,heap1)
>>> list(h)
[8, 10, 9, 10, 67, 56, 80, 79, 100]#需要 说明的是这里所谓的排序不是完全排序，只是两个list对应位置比较，
#将小的值先push，然后大的值再与另外一个list的下一个值比较
heapq.nlargest(n,iterable,key)：返回item中大到小顺序的前N个元素，key默认为空，可以用来指定规则如：function等来处理特定的排序
itemsDict=[
{'name':'dgb1','age':23,'salary':10000},
{'name':'dgb2','age':23,'salary':15000},
{'name':'dgb3','age':23,'salary':80000},
{'name':'dgb4','age':23,'salary':80000}
]
itemsDictlarge = heapq.nlargest(3,itemsDict,lambda s:s['salary'])
print(itemsDictlarge)
[{'name': 'dgb3', 'age': 23, 'salary': 80000}, {'name': 'dgb4', 'age': 23, 'salary': 80000}, {'name': 'dgb2', 'age': 23, 'salary': 15000}]
如果没有指定key，那么就按照第一个字段来排序
heapq.nsmallest(n,iterable,key)：返回item中小到大顺序的前N个元素，key默认为空，可以用来指定规则如：function等来处理特定的排序
这个函数的用法与上一个nlargest是一样的。
To create a heap, use a list initialized to[], or you can transform a populated list into a heap via functionheapify().
创建heap可以通过创建list，和使用heapify方法来实现。
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from：https://blog.csdn.net/chuan_day/article/details/73554861
python heapq模块使用
转载于:https://www.cnblogs.com/bonelee/p/10090727.html