Implement Trie (Prefix Tree)

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

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

终于进军trie树，trie树也称子典树或者前缀树（prefix　tree).　因为trie树是一个字母一个字母存储，避免单词存储的极大空间浪费．每次查找字符的时间复杂度为O(len(word)).　注意一点是trie的每个节点需要标志是不是一个单词的结尾．

trie既可以用数组实现，也可以用hashmap实现，数组实现则对每个节点都需要开一个２６维数组（'a'-'z'小写字母的情况下），不单纯是小写字母的情况则可能还要复杂．用hashmap是节省空间且便捷的措施．

代码如下：

class TrieNode(object):
    def __init__(self):
        """
        Initialize your data structure here.
        """
        self.children = {}
        self.hasword = False
        

class Trie(object):

    def __init__(self):
        self.root = TrieNode()

    def insert(self, word):
        """
        Inserts a word into the trie.
        :type word: str
        :rtype: void
        """
        node = self.root
        for i in word:
            if not node.children.get(i):
                node.children[i] = TrieNode()
            node = node.children[i]
        node.hasword = True
        
    def search(self, word):
        """
        Returns if the word is in the trie.
        :type word: str
        :rtype: bool
        """
        node = self.root
        for i in word:
            if not node.children.get(i):
                return False
            node = node.children[i]
        return node.hasword

    def startsWith(self, prefix):
        """
        Returns if there is any word in the trie
        that starts with the given prefix.
        :type prefix: str
        :rtype: bool
        """
        node = self.root
        for i in prefix:
            if not node.children.get(i):
                return False
            node = node.children[i]
        return True
        

注意search是要判读这个单词是否在字典中的，查找前缀不需要～