[ LeetCode ] #23. Merge k Sorted Lists（合并数列 C++ & Python）

最新推荐文章于 2024-04-03 21:24:25 发布

原创最新推荐文章于 2024-04-03 21:24:25 发布 · 173 阅读

0 ·

CC 4.0 BY-SA版权

文章标签：

#数列

leetcode 专栏收录该内容

40 篇文章

订阅专栏

本文介绍了一种高效算法，用于合并多个有序链表并保持结果链表的有序性。通过将链表元素转化为数组，排序后重构链表，实现了快速合并。C++和Python实现代码及性能分析一并提供。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

题目：23. Merge k Sorted Lists

Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity.

Example:

Input:
[
  1->4->5,
  1->3->4,
  2->6
]
Output: 1->1->2->3->4->4->5->6

题意：

给定若干个有序排列的单链表，返回将所有单链表合并并且保持有序的总链表。

分析：

直接把所给单链表的元素合并到一个数列中，对数列进行排序，使用排序后的数列进行重新构建单链表，返回即可。

Code & C++

/**
 * Definition for singly-linked list.
 * struct ListNode {
 *     int val;
 *     ListNode *next;
 *     ListNode(int x) : val(x), next(NULL) {}
 * };
 */
class Solution {
public:
    ListNode* mergeKLists(vector<ListNode*>& lists) {
        	vector<int> allElement;
	for(int i=0;i<lists.size(); ++i){
		ListNode *head = lists[i];
		while(head!=NULL){
			allElement.push_back(head->val);
			head = head->next;
		}
	}
	sort(allElement.begin(), allElement.end());
	ListNode *head = new ListNode(0);
	ListNode *tmp = head;
	for(int i=0;i<allElement.size();++i){
		ListNode *ele = new ListNode(allElement[i]);
		tmp->next = ele;
		tmp = ele;
	}
	return head->next;
    }
};

结果：

Runtime: 28 ms, faster than 99.92% of C++ online submissions for Merge k Sorted Lists.

Memory Usage: 12.7 MB, less than 15.95% of C++ online submissions for Merge k Sorted Lists.

Code & Python

# Definition for singly-linked list.
# class ListNode:
#     def __init__(self, x):
#         self.val = x
#         self.next = None

class Solution:
    def mergeKLists(self, lists: List[ListNode]) -> ListNode:
        res = []
        for list in lists:
            head = list
            while head is not None:
                res.append(head.val)
                head = head.next
        res.sort()
        head = ListNode(0)
        ans = head
        for d in res:
            tmp = ListNode(d)
            ans.next = tmp
            ans = tmp
        return head.next

结果：

Runtime: 76 ms, faster than 85.77% of Python3 online submissions for Merge k Sorted Lists.

Memory Usage: 17.5 MB, less than 11.96% of Python3 online submissions for Merge k Sorted Lists.