Word Ladder
Detailed guide and Python implementation for the 'Word Ladder' problem.
1. Узнать
The 'Word Ladder' problem is a key challenge in the Graphs section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Word Ladder.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Word Ladder carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Постановка задачи
A transformation sequence from word beginWord to word endWord using a dictionary wordList is a sequence of words beginWord -> s1 -> s2 -> ... -> sk such that:
- Every adjacent pair of words differs by a single letter.
- Every si for 1 <= i <= k is in wordList. Note that beginWord does not need to be in wordList.
- sk == endWord.
Given two words, beginWord and endWord, and a dictionary wordList, return the number of words in the shortest transformation sequence from beginWord to endWord, or 0 if no such sequence exists.
Write a function ladderLength(beginWord: str, endWord: str, wordList: List[str]) -> int.
- •1 <= len(beginWord) <= 10
- •endWord.length == beginWord.length
- •1 <= len(wordList) <= 5000
- •wordList[i].length == beginWord.length
- •beginWord, endWord, and wordList[i] consist of lowercase English letters
- •All the words in wordList are unique
Примеры
beginWord = "hit", endWord = "cog", wordList = ["hot","dot","dog","lot","log","cog"]
5
One shortest transformation sequence is "hit" -> "hot" -> "dot" -> "dog" -> "cog", which is 5 words long.
beginWord = "hit", endWord = "cog", wordList = ["hot","dot","dog","lot","log"]
0
The endWord "cog" is not in wordList, so there is no valid transformation sequence.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Готовы решить?
Open the problem in PyRun's browser-based Python editor. Your code runs fully offline — no server required.
Интервью: идеи и вариации
Разбивка анализа сложности
Почему время: Directly evaluates all possibilities.
Почему космос: Uses standard local memory.
Почему время: Optimized paths reduce total operations.
Почему космос: May trade memory for speed.
Оптимизированный код Python для решения
Оптимизированный код Python для решения
from collections import deque, defaultdict
def ladder_length_opt(beginWord, endWord, wordList):
if endWord not in wordList: return 0
nei = defaultdict(list)
wordList.append(beginWord)
for word in wordList:
for j in range(len(word)):
pattern = word[:j] + "*" + word[j + 1 :]
nei[pattern].append(word)
visit = {beginWord}
q = deque([beginWord])
res = 1
while q:
for i in range(len(q)):
word = q.popleft()
if word == endWord: return res
for j in range(len(word)):
pattern = word[:j] + "*" + word[j + 1 :]
for neighbor in nei[pattern]:
if neighbor not in visit:
visit.add(neighbor)
q.append(neighbor)
res += 1
return 0Код грубой силы (спойлер защищен)
Код грубой силы (спойлер защищен)
def ladder_length_brute(beginWord, endWord, wordList):
if endWord not in wordList: return 0
def is_diff_one(w1, w2):
diff = 0
for i in range(len(w1)):
if w1[i] != w2[i]: diff += 1
return diff == 1
q = [(beginWord, 1)]
visit = {beginWord}
while q:
word, dist = q.pop(0)
if word == endWord: return dist
for w in wordList:
if w not in visit and is_diff_one(word, w):
visit.add(w)
q.append((w, dist + 1))
return 0Algorithm Pattern Checklist
When dealing with Graphs data patterns.
- Are constraints clear?
- Is there a linear or logarithmic optimization possible?
Key Revision Notes
Standard Graphs problem properties apply.
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