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  • 208. Implement Trie (Prefix Tree)

    原题链接:https://leetcode.com/problems/implement-trie-prefix-tree/description/
    都是前缀树相关的题目。LeetCode 上面刷题时可以查看 Similar Questions 问题,这道题目也是做 211. Add and Search Word - Data structure design 这道题目看到的。
    这道题目就很简单的,我之前已经专门看过了前缀树的实现了:http://www.cnblogs.com/optor/p/8513547.html
    所以,这道题就是直接把之前的代码复制过来就好了:

    class Trie {
        
        class TrieNode {
    
            // R links to node children
            private TrieNode[] links;
    
            private final int R = 26;
    
            private boolean isEnd;
    
            // number of children non null links
            private int size;
    
            public TrieNode() {
                links = new TrieNode[R];
            }
    
            public boolean containsKey(char ch) {
                return links[ch - 'a'] != null;
            }
    
            public TrieNode get(char ch) {
                return links[ch - 'a'];
            }
    
            public void put(char ch, TrieNode node) {
                links[ch - 'a'] = node;
                size++;
            }
    
            public int getLinks() {
                return size;
            }
    
            public void setEnd() {
                isEnd = true;
            }
    
            public boolean isEnd() {
                return isEnd;
            }
    
        }
        
        private TrieNode root;
    
        /** Initialize your data structure here. */
        public Trie() {
            root = new TrieNode();
        }
        
        /** Inserts a word into the trie. */
        public void insert(String word) {
            TrieNode node = root;
            for (int i = 0; i < word.length(); i++) {
                char currentChar = word.charAt(i);
                if (!node.containsKey(currentChar)) {
                    node.put(currentChar, new TrieNode());
                }
                node = node.get(currentChar);
            }
            node.setEnd();
        }
        
        private TrieNode searchPrefix(String word) {
            TrieNode node = root;
            for (int i = 0; i < word.length(); i++) {
                char curLetter = word.charAt(i);
                if (node.containsKey(curLetter)) {
                    node = node.get(curLetter);
                } else {
                    return null;
                }
            }
            return node;
        }
        
        /** Returns if the word is in the trie. */
        public boolean search(String word) {
            TrieNode node = searchPrefix(word);
            return node != null && node.isEnd();
        }
        
        /** Returns if there is any word in the trie that starts with the given prefix. */
        public boolean startsWith(String prefix) {
            TrieNode node = searchPrefix(prefix);
            return node != null;
        }
    }
    
    /**
     * 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);
     */
    
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  • 原文地址:https://www.cnblogs.com/optor/p/8513732.html
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