208. Implement Trie (Prefix Tree)
Category: /leetcodeA trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.
Implement the Trie class:
- Trie() Initializes the trie object.
- void insert(String word) Inserts the string word into the trie.
- boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
- boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.
Input
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
Output
[null, null, true, false, true, null, true]
Explanation
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple"); // return True
trie.search("app"); // return False
trie.startsWith("app"); // return True
trie.insert("app");
trie.search("app"); // return True
Solution
class TrieNode:
# Initialize your data structure here.
def __init__(self):
self.children = collections.defaultdict(TrieNode)
self.is_word = False
class Trie:
def __init__(self):
self.root = TrieNode()
def insert(self, word):
""" T: O(m) """
current = self.root
for letter in word:
current = current.children[letter]
current.is_word = True
def search(self, word):
""" T: O(m) """
current = self.root
for letter in word:
if letter not in current.children:
return False
current = current.children[letter]
return current.is_word
def startsWith(self, prefix):
""" T: O(m) """
current = self.root
for letter in prefix:
current = current.children.get(letter)
if current is None:
return False
return True
