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Given a string s
and a dictionary of strings wordDict
, add spaces in s
to construct a sentence where each word is a valid dictionary word. Return all such possible sentences in any order.
Note that the same word in the dictionary may be reused multiple times in the segmentation.
Example 1:
Input: s = "catsanddog", wordDict = ["cat","cats","and","sand","dog"] Output: ["cats and dog","cat sand dog"]
Example 2:
Input: s = "pineapplepenapple", wordDict = ["apple","pen","applepen","pine","pineapple"] Output: ["pine apple pen apple","pineapple pen apple","pine applepen apple"] Explanation: Note that you are allowed to reuse a dictionary word.
Example 3:
Input: s = "catsandog", wordDict = ["cats","dog","sand","and","cat"] Output: []
Constraints:
1 <= s.length <= 20
1 <= wordDict.length <= 1000
1 <= wordDict[i].length <= 10
s
andwordDict[i]
consist of only lowercase English letters.- All the strings of
wordDict
are unique. - Input is generated in a way that the length of the answer doesn’t exceed 105.
Python
# time complexity: O(2^n)
# space complexity: O(2^n)
from typing import List
class Solution:
def wordBreak(self, s: str, wordDict: List[str]) -> List[str]:
word_set = set(wordDict)
memoization = {}
return self._dfs(s, word_set, memoization)
def _dfs(self, remainingStr: str, wordSet: set, memoization: dict) -> List[str]:
if remainingStr in memoization:
return memoization[remainingStr]
if not remainingStr:
return [""]
results = []
for i in range(1, len(remainingStr) + 1):
currentWord = remainingStr[:i]
if currentWord in wordSet:
for nextWord in self._dfs(remainingStr[i:], wordSet, memoization):
results.append(
currentWord + (" " if nextWord else "") + nextWord)
memoization[remainingStr] = results
return results
s = "catsanddog"
wordDict = ["cat", "cats", "and", "sand", "dog"]
print(Solution().wordBreak(s, wordDict))