Elegant python and elegant python

Elegant python and elegant python

Trie, also known as the Prefix Tree or dictionary tree, uses the common prefix of the string to save storage space.

• Definition
  Each word in the Trie tree is stored using the character by character method. words with the same prefix share the prefix node.
  
  As you can see, each path is a word. The tree above contains the words to/tea/ted/ten/inn.
  
  
  • Nature
    • (1) The root node does not contain characters. Each node except the root node only contains one character.
    • (2) From the root node to a node, the character passing through the path is connected to the string corresponding to the node.
    • (3) the strings of all subnodes of each node are different.
• Application
  • Word Frequency Statistics
    Space saving compared with direct use of hash
  • Search Prompt
    When you enter a prefix, the system prompts the words that can be entered.
  • Auxiliary Structure
    Auxiliary structures such as suffix tree and AC automatic mechanism

• Implementation
  Although python does not have pointers, nested Dictionaries can be used to implement tree structures. For non-ascii words, unicode encoding is used for insertion and search.

# Coding = utf-8class Trie: root = {} END = '/' def add (self, word): # traverse words from the root node, char by char, new if not present, add a word ending sign node = self. root for c in word: node = node. setdefault (c, {}) node [self. END] = None def find (self, word): node = self. root for c in word: if c not in node: return False node = node [c] return self. END in node