208. Implement Trie (Prefix Tree)
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 stringwordinto the trie.boolean search(String word)Returnstrueif the stringwordis in the trie (i.e., was inserted before), andfalseotherwise.boolean startsWith(String prefix)Returnstrueif there is a previously inserted stringwordthat has the prefixprefix, andfalseotherwise.
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 <= 2000wordandprefixconsist only of lowercase English letters.- At most
3 * 104calls in total will be made toinsert,search, andstartsWith.
class TrieNode:
def __init__(self):
self.children = {}
self.eow = False
class Trie:
def __init__(self):
self.root = TrieNode()
def insert(self, word: str) -> None:
cur = self.root
for c in word:
if c not in cur.children:
cur.children[c] = TrieNode()
cur = cur.children[c]
cur.eow = True
def search(self, word: str) -> bool:
cur = self.root
for c in word:
if c not in cur.children :
return False
cur = cur.children[c]
return cur.eow
def startsWith(self, prefix: str) -> bool:
cur = self.root
for c in prefix:
if c not in cur.children :
return False
cur = cur.children[c]
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)Explaination :
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