703.数据流中的第k大元素.py

#
# @lc app=leetcode.cn id=703 lang=python3
#
# [703] 数据流中的第K大元素
#
# https://leetcode-cn.com/problems/kth-largest-element-in-a-stream/description/
#
# algorithms
# Easy (42.41%)
# Likes:    107
# Dislikes: 0
# Total Accepted:    14.3K
# Total Submissions: 33.7K
# Testcase Example:  '["KthLargest","add","add","add","add","add"]\n' +
  '[[3,[4,5,8,2]],[3],[5],[10],[9],[4]]'
#
# 设计一个找到数据流中第K大元素的类（class）。注意是排序后的第K大元素，不是第K个不同的元素。
# 
# 你的 KthLargest 类需要一个同时接收整数 k 和整数数组nums 的构造器，它包含数据流中的初始元素。每次调用
# KthLargest.add，返回当前数据流中第K大的元素。
# 
# 示例:
# 
# 
# int k = 3;
# int[] arr = [4,5,8,2];
# KthLargest kthLargest = new KthLargest(3, arr);
# kthLargest.add(3);   // returns 4
# kthLargest.add(5);   // returns 5
# kthLargest.add(10);  // returns 5
# kthLargest.add(9);   // returns 8
# kthLargest.add(4);   // returns 8
# 
# 
# 说明: 
# 你可以假设 nums 的长度≥ k-1 且k ≥ 1。
# 
#

# @lc code=start
import heapq
class KthLargest:

  def __init__(self, k: int, nums: List[int]):
    self.pool = heapq.nlargest(k, nums)
    heapq.heapify(self.pool)
    self.k = k

  def add(self, val: int) -> int:
    if len(self.pool) < self.k:
      heapq.heappush(self.pool, val)
    else:
      heapq.heappushpop(self.pool, val)
    return self.pool[0]


# Your KthLargest object will be instantiated and called as such:
# obj = KthLargest(k, nums)
# param_1 = obj.add(val)
# @lc code=end