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71 lines
2.1 KiB
Plaintext
71 lines
2.1 KiB
Plaintext
---
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title: '208. Implement Trie (Prefix Tree)'
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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
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sidebar:
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label: 'Implement Trie (Prefix Tree)'
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badge: 'Medium'
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---
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<Badge variant="accent">Trie</Badge>
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### Example 1:
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- Input: ``
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- Output: ``
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- Explanation: 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
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### Constraints:
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- `1 <= word.length, prefix.length <= 2000`
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- `word` and `prefix` consist only of lowercase English letters.
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- At most 3 * 10^4 calls in total will be made to insert, search, and startsWith.
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## Solution
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```py
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class TrieNode:
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def __init__(self):
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self.children = {}
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self.endOfWord = False
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class Trie:
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def __init__(self):
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self.root = TrieNode()
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def insert(self, word: str) -> None:
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cur = self.root
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for c in word:
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if c not in cur.children:
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cur.children[c] = TrieNode()
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cur = cur.children[c]
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cur.endOfWord = True
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def search(self, word: str) -> bool:
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cur = self.root
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for c in word:
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if c not in cur.children:
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return False
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cur = cur.children[c]
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return cur.endOfWord
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def startsWith(self, prefix: str) -> bool:
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cur = self.root
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for c in prefix:
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if c not in cur.children:
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return False
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cur = cur.children[c]
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return True
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# Your Trie object will be instantiated and called as such:
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# obj = Trie()
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# obj.insert(word)
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# param_2 = obj.search(word)
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# param_3 = obj.startsWith(prefix)
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```
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