Design Add and Search Words

Problem

https://leetcode.com/problems/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) Adds word to the data structure, it can be matched later.

• bool search(word) Returns true if there is any string in the data structure that matches word or false 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 in addWord consists of lowercase English letters.

• word in search consist of '.' or lowercase English letters.

• There will be at most 2 dots in word for search queries.

• At most 10:sup:`4` calls will be made to addWord and search.

Pattern

String, Depth-First Search, Design, Trie

Approaches

Trie With DFS

Code

class TrieNode:
    """Node in the trie."""

    def __init__(self, char, end_of_word=False):
        self.char = char
        self.end_of_word = end_of_word
        self.children = {}


class WordDictionary:
    """A trie-backed dictionary of words supporting wildcard search."""

    def __init__(self):
        self.root = TrieNode("<SOW>")

    def addWord(self, word: str) -> None:
        """Add ``word`` to the dictionary."""
        node = self.root
        for char in word:
            if char not in node.children:
                node.children[char] = TrieNode(char)
            node = node.children[char]
        node.end_of_word = True

    def search(self, word: str) -> bool:
        """Return whether ``word`` is stored; ``.`` matches any letter."""
        return self._search(self.root, word)

    def _search(self, node: TrieNode, word: str) -> bool:
        if len(word) == 0:
            return node.end_of_word

        char = word[0]
        if char == ".":
            return any(
                self._search(child, word[1:])
                for child in node.children.values()
            )
        elif char not in node.children:
            return False
        else:
            return self._search(node.children[char], word[1:])

Test

>>> from design_add_and_search_words_data_structure__trie_with_dfs import WordDictionary
>>> wd = WordDictionary()
>>> wd.addWord("bad"); wd.addWord("dad"); wd.addWord("mad")
>>> wd.search("pad")
False
>>> wd.search("bad")
True
>>> wd.search(".ad")
True
>>> wd.search("b..")
True

class design_add_and_search_words_data_structure__trie_with_dfs.TrieNode(char, end_of_word=False)

Bases: object

Node in the trie.

class design_add_and_search_words_data_structure__trie_with_dfs.WordDictionary

Bases: object

A trie-backed dictionary of words supporting wildcard search.

addWord(word: str) → None

Add word to the dictionary.

search(word: str) → bool

Return whether word is stored; . matches any letter.