英文原文
You are given the array paths
, where paths[i] = [cityAi, cityBi]
means there exists a direct path going from cityAi
to cityBi
. Return the destination city, that is, the city without any path outgoing to another city.
It is guaranteed that the graph of paths forms a line without any loop, therefore, there will be exactly one destination city.
Example 1:
Input: paths = [["London","New York"],["New York","Lima"],["Lima","Sao Paulo"]] Output: "Sao Paulo" Explanation: Starting at "London" city you will reach "Sao Paulo" city which is the destination city. Your trip consist of: "London" -> "New York" -> "Lima" -> "Sao Paulo".
Example 2:
Input: paths = [["B","C"],["D","B"],["C","A"]] Output: "A" Explanation: All possible trips are: "D" -> "B" -> "C" -> "A". "B" -> "C" -> "A". "C" -> "A". "A". Clearly the destination city is "A".
Example 3:
Input: paths = [["A","Z"]] Output: "Z"
Constraints:
1 <= paths.length <= 100
paths[i].length == 2
1 <= cityAi.length, cityBi.length <= 10
cityAi != cityBi
- All strings consist of lowercase and uppercase English letters and the space character.
中文题目
给你一份旅游线路图,该线路图中的旅行线路用数组 paths
表示,其中 paths[i] = [cityAi, cityBi]
表示该线路将会从 cityAi
直接前往 cityBi
。请你找出这次旅行的终点站,即没有任何可以通往其他城市的线路的城市。
题目数据保证线路图会形成一条不存在循环的线路,因此恰有一个旅行终点站。
示例 1:
输入:paths = [["London","New York"],["New York","Lima"],["Lima","Sao Paulo"]] 输出:"Sao Paulo" 解释:从 "London" 出发,最后抵达终点站 "Sao Paulo" 。本次旅行的路线是 "London" -> "New York" -> "Lima" -> "Sao Paulo" 。
示例 2:
输入:paths = [["B","C"],["D","B"],["C","A"]] 输出:"A" 解释:所有可能的线路是: "D" -> "B" -> "C" -> "A". "B" -> "C" -> "A". "C" -> "A". "A". 显然,旅行终点站是 "A" 。
示例 3:
输入:paths = [["A","Z"]] 输出:"Z"
提示:
1 <= paths.length <= 100
paths[i].length == 2
1 <= cityAi.length, cityBi.length <= 10
cityAi != cityBi
- 所有字符串均由大小写英文字母和空格字符组成。
通过代码
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模拟 + 哈希表
根据题意,我们可以取一个任意城市作为起点,然后使用 $paths$ 中的路线信息开始搜索,直到当前城市无法到达下一个城市,即是答案。
实现上,为了可以快速找到某个城市所能到达的城市,可以先使用哈希表对 $paths$ 中的路线信息进行预处理。
代码:
class Solution {
public String destCity(List<List<String>> ps) {
Map<String, String> map = new HashMap<>();
for (List<String> p : ps) map.put(p.get(0), p.get(1));
String ans = ps.get(0).get(0);
while (map.containsKey(ans)) ans = map.get(ans);
return ans;
}
}
- 时间复杂度:$O(n)$
- 空间复杂度:$O(n)$
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注:以上目录整理来自 wiki,任何形式的转载引用请保留出处。
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