{ "data": { "question": { "questionId": "208", "questionFrontendId": "208", "boundTopicId": null, "title": "Implement Trie (Prefix Tree)", "titleSlug": "implement-trie-prefix-tree", "content": "
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.
\n\nImplement the Trie class:
\n\nTrie()
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.\n
Example 1:
\n\n\nInput\n["Trie", "insert", "search", "search", "startsWith", "insert", "search"]\n[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]\nOutput\n[null, null, true, false, true, null, true]\n\nExplanation\nTrie trie = new Trie();\ntrie.insert("apple");\ntrie.search("apple"); // return True\ntrie.search("app"); // return False\ntrie.startsWith("app"); // return True\ntrie.insert("app");\ntrie.search("app"); // return True\n\n\n
\n
Constraints:
\n\n1 <= word.length, prefix.length <= 2000
word
and prefix
consist only of lowercase English letters.3 * 104
calls in total will be made to insert
, search
, and startsWith
.Compiled with clang 11
using the latest C++ 17 standard.
Your code is compiled with level two optimization (-O2
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Most standard library headers are already included automatically for your convenience.
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\\r\\n\\r\\nFor Map/TreeMap data structure, you may use sortedcontainers library.
\\r\\n\\r\\nNote that Python 2.7 will not be maintained past 2020. For the latest Python, please choose Python3 instead.
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Node.js 16.13.2
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Go 1.17.6
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