208. Implement Trie (Prefix Tree)
Description
A 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 stringword
into the trie.boolean search(String word)
Returnstrue
if the stringword
is in the trie (i.e., was inserted before), andfalse
otherwise.boolean startsWith(String prefix)
Returnstrue
if there is a previously inserted stringword
that has the prefixprefix
, andfalse
otherwise.
Example 1:
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
Constraints:
1 <= word.length, prefix.length <= 2000
word
andprefix
consist only of lowercase English letters.- At most
3 * 104
calls in total will be made toinsert
,search
, andstartsWith
.
Solution
implement-trie-prefix-tree.py
class TrieNode:
def __init__(self):
self.children = defaultdict(TrieNode)
self.hasEnd = False
class Trie:
def __init__(self):
self.root = TrieNode()
def insert(self, word: str) -> None:
curr = self.root
for x in word:
curr = curr.children[x]
curr.hasEnd = True
def search(self, word: str) -> bool:
curr = self.root
for x in word:
if x not in curr.children:
return False
curr = curr.children[x]
return curr.hasEnd
def startsWith(self, prefix: str) -> bool:
curr = self.root
for x in prefix:
if x not in curr.children:
return False
curr = curr.children[x]
return True
# Your Trie object will be instantiated and called as such:
# obj = Trie()
# obj.insert(word)
# param_2 = obj.search(word)
# param_3 = obj.startsWith(prefix)