211. Design Add and Search Words Data Structure
Design a data structure that supports adding new words and finding if a string matches any previously added string.
Implement the WordDictionary
class:
WordDictionary()
Initializes the object.void addWord(word)
Addsword
to the data structure, it can be matched later.bool search(word)
Returnstrue
if there is any string in the data structure that matchesword
orfalse
otherwise.word
may contain dots'.'
where dots can be matched with any letter.
Example:
Input ["WordDictionary","addWord","addWord","addWord","search","search","search","search"] [[],["bad"],["dad"],["mad"],["pad"],["bad"],[".ad"],["b.."]] Output [null,null,null,null,false,true,true,true] Explanation WordDictionary wordDictionary = new WordDictionary(); wordDictionary.addWord("bad"); wordDictionary.addWord("dad"); wordDictionary.addWord("mad"); wordDictionary.search("pad"); // return False wordDictionary.search("bad"); // return True wordDictionary.search(".ad"); // return True wordDictionary.search("b.."); // return True
Constraints:
1 <= word.length <= 25
word
inaddWord
consists of lowercase English letters.word
insearch
consist of'.'
or lowercase English letters.- There will be at most
3
dots inword
forsearch
queries. - At most
104
calls will be made toaddWord
andsearch
.
class TrieNode:
def __init__(self):
self.children = {}
self.eow = False
class WordDictionary:
def __init__(self):
self.root = TrieNode()
def addWord(self, word: str) -> None:
curr = self.root
for c in word:
if c not in curr.children:
curr.children[c] = TrieNode()
curr = curr.children[c]
curr.eow = True
def search(self, word: str) -> bool:
def dfs(k, root):
curr = root
for i in range(k, len(word)):
c = word[i]
if c == ".":
for child in curr.children.values():
if dfs(i+1, child):
return True
return False
else:
if c not in curr.children:
return False
curr = curr.children[c]
return curr.eow
return dfs(0, self.root)
# Your WordDictionary object will be instantiated and called as such:
# obj = WordDictionary()
# obj.addWord(word)
# param_2 = obj.search(word)
Explained :
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