[NeetCode 150] Word Ladder

Word Ladder

You are given two words, beginWord and endWord, and also a list of words wordList. All of the given words are of the same length, consisting of lowercase English letters, and are all distinct.

Your goal is to transform beginWord into endWord by following the rules:

You may transform beginWord to any word within wordList, provided that at exactly one position the words have a different character, and the rest of the positions have the same characters.

You may repeat the previous step with the new word that you obtain, and you may do this as many times as needed.

Return the minimum number of words within the transformation sequence needed to obtain the endWord, or 0 if no such sequence exists.

Example 1:

复制代码
Input: beginWord = "cat", endWord = "sag", wordList = ["bat","bag","sag","dag","dot"]

Output: 4

Explanation: The transformation sequence is "cat" -> "bat" -> "bag" -> "sag".

Example 2:

复制代码
Input: beginWord = "cat", endWord = "sag", wordList = ["bat","bag","sat","dag","dot"]

Output: 0

Explanation: There is no possible transformation sequence from "cat" to "sag" since the word "sag" is not in the wordList.

Constraints:

复制代码
1 <= beginWord.length <= 10
1 <= wordList.length <= 100

Solution

The "distance" of every transformation is 1 so it is OK to apply BFS for searching the shortest path. Because it will take O ( wordList.length 2 × beginWord.length 2 ) O(\text{wordList.length}^2\times\text{beginWord.length}^2) O(wordList.length2×beginWord.length2) to build up the graph inevitably, more advanced shortest path algorithm is not necessary.

At first, we put begin word into BFS queue and set the initial distance of 1. Then we keep getting the top word from queue and check whether it can reach out other unvisited words. If so, we add these new words into queue and set their corresponding distance to current distance+1. When we reach the end word during this process, we can return early. If we cannot reach end word after the queue is empty, it means the end word is not reachable.

Code

python 复制代码
class Solution:
    def ladderLength(self, beginWord: str, endWord: str, wordList: List[str]) -> int:
        if beginWord == endWord:
            return 1
        vis_flag = {word: False for word in wordList}
        # dis = {word: 10000000 for word in wordList}
        vis_flag[beginWord] = True
        vis_flag[endWord] = False
        from queue import Queue
        bfs_queue = Queue()
        bfs_queue.put((beginWord, 1))
        def check(a, b):
            if a == b:
                return False
            cnt = 0
            for i in range(len(a)):
                if a[i] != b[i]:
                    cnt += 1
            return cnt == 1
        while not bfs_queue.empty():
            cur = bfs_queue.get()
            for word in wordList:
                if not vis_flag[word] and check(cur[0], word):
                    if word == endWord:
                        return cur[1] + 1
                    vis_flag[word] = True
                    bfs_queue.put((word, cur[1]+1))
        return 0
        
相关推荐
文丑颜不良啊1 分钟前
LeetCode1481~1500题目解析
java·leetcode
尹人入圣37 分钟前
目前热门的IP驱动产业新场景新工具
网络·python·网络协议·tcp/ip
文丑颜不良啊1 小时前
LeetCode1381~1400题目解析
java·leetcode
Nuanyt1 小时前
Agent 学习笔记(下篇三):上线工程、进阶选择与操作界面(Stage 7 / 7.5 / 8 + 延伸路线)
笔记·python·学习·memory·aiagent·harness
吴卫斌1 小时前
定投ETF实战指南(四):行业/主题ETF——定投的“进攻端“
开发语言·python·股票·量化
2601_967987372 小时前
Python——入门级(定义功能def函数)
python·函数·可变参数·默认参数·关键字参数
专注仿真4 小时前
梯度提升类(XFBoost)算法详解与代码实例
开发语言·人工智能·python·算法·大模型训练·控制算法
外收内放4 小时前
Python基础语法练习题(75)
开发语言·python·学习
Tisfy4 小时前
LeetCode 3882.网格图中最小异或路径:动态规划
算法·leetcode·动态规划
黑十5 小时前
PyTorch 报 “no CUDA GPUs are available“ 怎么办?3 步排查
服务器·网络·人工智能·pytorch·python