TopK问题有两种常见的解决方式，一种是利用堆，一种是利用快速排序的partition过程。
一，堆
import heapq
class Finder:def findKth(self, a, n, K):b = list(map(lambda x:-x, a))heapq.heapify(b)for _ in range(K-1):heapq.heappop(b) return -heapq.heappop(b) 二，随机快排
class Solution:def findKthLargest(self, nums: List[int], k: int) -> int:len_nums = len(nums)def partition(nums, low, high, pivot):l = low - 1r = high + 1h = lowwhile h < r:if nums[h] < pivot:l += 1nums[h], nums[l] = nums[l], nums[h]h += 1elif nums[h] == pivot:h += 1else:r -= 1nums[h], nums[r] = nums[r], nums[h]return l+1, r-1low = 0high = len_nums-1while low <= high:pivot = random.randint(low, high)pi_l, pi_r = partition(nums, low, high, nums[pivot])if pi_l <= len_nums - k <= pi_r:return nums[pi_l]elif pi_l > len_nums - k:high = pi_l - 1elif pi_r < len_nums - k:low = pi_r + 1