Implement Trie Prefix Tree
Detailed guide and Python implementation for the 'Implement Trie Prefix Tree' problem.
Problem Statement
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.
- insert(word: str) Inserts the string word into the trie.
- search(word: str) -> bool Returns True if the string word is in the trie (i.e., was inserted before), and False otherwise.
- startsWith(prefix: str) -> bool Returns True if there is a previously inserted string word that has the prefix prefix, and False otherwise.
Input is a list of operations and arguments. Implement a function trie(operations: list, arguments: list) -> list that returns a list of results (None for constructor/insert, bool for search/startsWith).
- •1 <= len(word), len(prefix) <= 2000
- •word and prefix consist of lowercase English letters
- •At most 3 * 10^4 calls will be made in total to insert, search, and startsWith
Examples
operations = ["Trie", "insert", "search", "search", "startsWith", "insert", "search"], arguments = [[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
[None, None, True, False, True, None, True]
Trie initialized. insert("apple"). search("apple") returns True. search("app") returns False. startsWith("app") returns True. insert("app"). search("app") returns True.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
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