{ "data": { "question": { "questionId": "208", "questionFrontendId": "208", "categoryTitle": "Algorithms", "boundTopicId": 1220, "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
.Trie(发音类似 \"try\")或者说 前缀树 是一种树形数据结构,用于高效地存储和检索字符串数据集中的键。这一数据结构有相当多的应用情景,例如自动补完和拼写检查。
\n\n请你实现 Trie 类:
\n\nTrie()
初始化前缀树对象。void insert(String word)
向前缀树中插入字符串 word
。boolean search(String word)
如果字符串 word
在前缀树中,返回 true
(即,在检索之前已经插入);否则,返回 false
。boolean startsWith(String prefix)
如果之前已经插入的字符串 word
的前缀之一为 prefix
,返回 true
;否则,返回 false
。\n\n
示例:
\n\n\n输入\n[\"Trie\", \"insert\", \"search\", \"search\", \"startsWith\", \"insert\", \"search\"]\n[[], [\"apple\"], [\"apple\"], [\"app\"], [\"app\"], [\"app\"], [\"app\"]]\n输出\n[null, null, true, false, true, null, true]\n\n解释\nTrie trie = new Trie();\ntrie.insert(\"apple\");\ntrie.search(\"apple\"); // 返回 True\ntrie.search(\"app\"); // 返回 False\ntrie.startsWith(\"app\"); // 返回 True\ntrie.insert(\"app\");\ntrie.search(\"app\"); // 返回 True\n\n\n
\n\n
提示:
\n\n1 <= word.length, prefix.length <= 2000
word
和 prefix
仅由小写英文字母组成insert
、search
和 startsWith
调用次数 总计 不超过 3 * 104
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out-of-bounds<\\/code>\\u548c
use-after-free<\\/code>\\u9519\\u8bef\\u3002<\\/p>\\r\\n\\r\\n
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out-of-bounds<\\/code>\\u548c
use-after-free<\\/code>\\u9519\\u8bef\\u3002<\\/p>\\r\\n\\r\\n
\\r\\nstruct hash_entry {\\r\\n int id; \\/* we'll use this field as the key *\\/\\r\\n char name[10];\\r\\n UT_hash_handle hh; \\/* makes this structure hashable *\\/\\r\\n};\\r\\n\\r\\nstruct hash_entry *users = NULL;\\r\\n\\r\\nvoid add_user(struct hash_entry *s) {\\r\\n HASH_ADD_INT(users, id, s);\\r\\n}\\r\\n<\\/pre>\\r\\n<\\/p>\\r\\n\\r\\n
\\r\\nstruct hash_entry *find_user(int user_id) {\\r\\n struct hash_entry *s;\\r\\n HASH_FIND_INT(users, &user_id, s);\\r\\n return s;\\r\\n}\\r\\n<\\/pre>\\r\\n<\\/p>\\r\\n\\r\\n
\\r\\nvoid delete_user(struct hash_entry *user) {\\r\\n HASH_DEL(users, user); \\r\\n}\\r\\n<\\/pre>\\r\\n<\\/p>\"],\"csharp\":[\"C#\",\"
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Node.js 16.13.2<\\/code><\\/p>\\r\\n\\r\\n
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