# Implement Trie

Implement a trie with insert, search, and startsWith methods.

## Notice

You may assume that all inputs are consist of lowercase letters a-z.

**Example**

```
insert("lintcode")
search("code")
 >>> false
startsWith("lint")
>>> true
startsWith("linterror")
>>> false
insert("linterror")
search("lintcode)
>>> true
startsWith("linterror")
>>> true
```

分析：

一个单词就是一棵树下来，每个node有26个字母可做孩子。

注意点：1 用数组表示children 2 TrieNode里定义了所有函数，返回node 3 hasWord在insert里set，在find里不用，因为直接返回了node

除了数组还可以用hashmap

答案：

初始化时cur = root,然后往下loop word.length,最后到达最后一个node。

```
/**
 * Your Trie object will be instantiated and called as such:
 * Trie trie = new Trie();
 * trie.insert("lintcode");
 * trie.search("lint"); will return false
 * trie.startsWith("lint"); will return true
 */
class TrieNode {
    // Initialize your data structure here.
    public TrieNode[] children;
    public boolean hasWord;

    public TrieNode() {
        children = new TrieNode[26];
        hasWord = false;
    }

    //  public void insert(String word, int index) {
    //     if(index == word.length()){
    //         hasWord = true;
    //         return;
    //     }
    //     int pos = word.charAt(index) - 'a';
    //     if(children[pos] == null){
    //         children[pos] = new TrieNode();
    //     }
    //     children[pos].insert(word, index+1);
    // }

    // public TrieNode find(String word, int index) {
    //     if(index == word.length()){
    //         return this;
    //     }
    //     int pos = word.charAt(index) - 'a';
    //     if (children[pos] == null) {
    //         return null;
    //     }
    //     return children[pos].find(word, index+1);
    // }


    public void insert(String word) {
        TrieNode cur = this;
        for(int i = 0;  i < word.length(); i ++){
             int pos = word.charAt(i) - 'a';
            if(cur.children[pos] == null){
                cur.children[pos] = new TrieNode();
            }
            cur = cur.children[pos];
        }
        cur.hasWord = true;
    }

    public TrieNode find(String word) {
        TrieNode cur = this;

        for(int i = 0;  i < word.length(); i ++){
             int pos = word.charAt(i) - 'a';
            if(cur.children[pos] == null){
                return null;
            }
            cur = cur.children[pos];
        }
        return cur;
    }


}

public class Trie {
    private TrieNode root;

    public Trie() {
        root = new TrieNode();
    }

    // Inserts a word into the trie.
    public void insert(String word) {
        root.insert(word);
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
         TrieNode cur = root.find(word);
         return cur!= null && cur.hasWord;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        TrieNode cur = root.find(prefix);
         return cur!= null;
    }
}
```

```
/**
 * Your Trie object will be instantiated and called as such:
 * Trie trie = new Trie();
 * trie.insert("lintcode");
 * trie.search("lint"); will return false
 * trie.startsWith("lint"); will return true
 */
class TrieNode {
    // Initialize your data structure here.
    private TrieNode[] children;
    public boolean hasWord;

    public TrieNode() {
        children = new TrieNode[26];
        hasWord = false;
    }

     public void insert(String word, int index) {
        if(index == word.length()){
            hasWord = true;
            return;
        }
        int pos = word.charAt(index) - 'a';
        if(children[pos] == null){
            children[pos] = new TrieNode();
        }
        children[pos].insert(word, index+1);
    }

    public TrieNode find(String word, int index) {
        if(index == word.length()){
            return this;
        }
        int pos = word.charAt(index) - 'a';
        if (children[pos] == null) {
            return null;
        }
        return children[pos].find(word, index+1);
    }

}

public class Trie {
    private TrieNode root;

    public Trie() {
        root = new TrieNode();
    }

    // Inserts a word into the trie.
    public void insert(String word) {
        root.insert(word, 0);
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        TrieNode t = root.find(word, 0);
        return t!= null && t.hasWord;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        TrieNode t = root.find(prefix, 0);
        return t!= null;
    }
}
```

hashmap实现法

```
class Trie {

    TrieNode root;
    /** Initialize your data structure here. */
    public Trie() {
        root = new TrieNode();
    }

    /** Inserts a word into the trie. */
    public void insert(String word) {
        HashMap<Character, TrieNode> curChildren = root.children;
        char[] cs = word.toCharArray();
        for(int i = 0; i < cs.length; i ++){
            char c = cs[i];
            if(!curChildren.containsKey(c)){
                curChildren.put(c, new TrieNode());
            }
            TrieNode cur = curChildren.get(c);
            curChildren = cur.children;
            if(i == cs.length-1){
                cur.hasWord = true;
            }
        }
    }

    /** Returns if the word is in the trie. */
    public boolean search(String word) {
        TrieNode n = find(word);
        return n != null && n.hasWord;

    }

    /** Returns if there is any word in the trie that starts with the given prefix. */
    public boolean startsWith(String prefix) {
        TrieNode n = find(prefix);
        return n != null;
    }

    public TrieNode find(String word){
          HashMap<Character, TrieNode> curChildren = root.children;
        char[] cs = word.toCharArray();
        for(int i = 0; i < cs.length; i ++){
            char c = cs[i];
            if(!curChildren.containsKey(c)){
                return null;
            }
            TrieNode cur = curChildren.get(c);
            curChildren = cur.children;
            if(i == cs.length-1){
                return cur;
            }
        }
        return null;
    }
}

class TrieNode {
    char c;
    boolean hasWord;
    HashMap<Character, TrieNode> children = new HashMap<Character, TrieNode>();

    public TrieNode(){

    }

    public TrieNode(char c){
        this.c = c;
    } 

}

/**
 * Your Trie object will be instantiated and called as such:
 * Trie obj = new Trie();
 * obj.insert(word);
 * boolean param_2 = obj.search(word);
 * boolean param_3 = obj.startsWith(prefix);
 */
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://nataliekung.gitbook.io/ladder_code/qiang-hua-2-data-structure-i/implement-trie.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
