创建堆:
访问堆内容
更新/替换堆
1、heapq.heappush & heapq.heappop
import heapq
nums = [21, 13, 52, 16, 34, 21, 119]
heap = []
for num in nums:
heapq.heappush(heap, num)
print(heap[0]) # 弹出最小值,使用heap[0]
print([heapq.heappop(heap) for _ in range(len(nums))]) # 堆排序结果
结果:
13
[13, 16, 21, 21, 34, 52, 119]
2、heapq.heapify
import heapq
nums = [21, 13, 52, 16, 34, 21, 119]
heapq.heapify(nums)
print(nums[0]) # 弹出最小值,使用nums[0]
print([heapq.heappop(nums) for _ in range(len(nums))]) # 堆排序结果
结果:
13
[13, 16, 21, 21, 34, 52, 119]
3、 heapq.heappop & heapq.nlargest & heapq.nsmallest
import heapq
nums = [21, 13, 52, 16, 34, 21, 119]
print(heapq.nlargest(3, nums))
print(heapq.nsmallest(3, nums))
结果:
[119, 52, 34]
[13, 16, 21]
这两个函数还接受一个参数key,用于处理dict等类型数据
score= [
{'name': 'xiaoming', 'score': 100},
{'name': 'xiaozhang', 'score': 90},
{'name': 'xiaoli', 'score': 92},
{'name': 'xiaowang', 'score': 65},
{'name': 'xiaosun', 'score': 78}
]
print(heapq.nsmallest(3, score, key=lambda s: s['score']))
print(heapq.nlargest(3, score, key=lambda s: s['score']))
结果:
[{‘score’: 65, ‘name’: ‘xiaowang’}, {‘score’: 78, ‘name’: ‘xiaosun’}, {‘score’: 90, ‘name’: ‘xiaozhang’}]
[{‘score’: 100, ‘name’: ‘xiaoming’}, {‘score’: 92, ‘name’: ‘xiaoli’}, {‘score’: 90, ‘name’: ‘xiaozhang’}]
4、 heapq.heaprepalce
import heapq
nums = [21, 13, 52, 16, 34, 21, 119]
heapq.heapify(nums)
heapq.heapreplace(nums, 23)
print([heapq.heappop(nums) for _ in range(len(nums))])
结果:
[16, 21, 21, 23, 34, 52, 119]
大顶堆pyhton实现
class Solution:
# 调整为大顶堆
def heapify(self, arr, index, end):
left = index * 2 + 1
right = left + 1
while left <= end:
# 当前节点为非叶子节点
max_index = index
if arr[left] > arr[max_index]:
max_index = left
if right <= end and arr[right] > arr[max_index]:
max_index = right
if index == max_index:
# 如果不用交换,则说明已经交换结束
break
arr[index], arr[max_index] = arr[max_index], arr[index]
# 继续调整子树
index = max_index
left = index * 2 + 1
right = left + 1
# 初始化大顶堆
def buildMaxHeap(self, arr):
size = len(arr)
# (size-2) // 2 是最后一个非叶节点,叶节点不用调整
for i in range((size - 2) // 2, -1, -1):
self.heapify(arr, i, size - 1)
return arr
# 升序堆排序,思路如下:
# 1. 先建立大顶堆
# 2. 让堆顶最大元素与最后一个交换,然后调整第一个元素到倒数第二个元素,这一步获取最大值
# 3. 再交换堆顶元素与倒数第二个元素,然后调整第一个元素到倒数第三个元素,这一步获取第二大值
# 4. 以此类推,直到最后一个元素交换之后完毕。
def maxHeapSort(self, arr):
self.buildMaxHeap(arr)
size = len(arr)
for i in range(size):
arr[0], arr[size-i-1] = arr[size-i-1], arr[0]
self.heapify(arr, 0, size-i-2)
return arr
def sortArray(self, nums: List[int]) -> List[int]:
return self.maxHeapSort(nums)
[1].leetcode
[2].python 模块:heapq—堆及堆排序