writing trie implementation - algorithm

Question

This question has been asked many times and I googled many places but still couldn't find one place where I can get step-by-step instruction for writing trie implementation. Please help me out
preferred language is Java or Python
Thank you

Answer 1

I have written a tries for string searching in java. Its pretty simple:
here are the steps:
Node class is like this:
public class Trienode {
char c;
Trienode parent;
ArrayList<Trienode> childs;
}
Trienode addString{ String str, Trienode root ){
if(str.length == 0) return root;
String newstr = [str without the first char];
char c = str[0];
Trienode newnode = root[c - '0'];
if(newnode == null){
newnode = new Trienode();
newnode.c = c;
newnode.parent = root;
}
return addString(newstr, newnode);
}
you can create search etc on the same line.

Answer 2

#!/usr/bin/env python
import sys
class Node:
def __init__(self):
self.next = {} #Initialize an empty hash (python dictionary)
self.word_marker = False
# There can be words, Hot and Hottest. When search is performed, usually state transition upto leaf node is peformed and characters are printed.
# Then in this case, only Hottest will be printed. Hot is intermediate state. Inorder to mark t as a state where word is to be print, a word_marker is used
def add_item(self, string):
''' Method to add a string the Trie data structure'''
if len(string) == 0:
self.word_marker = True
return
key = string[0] #Extract first character
string = string[1:] #Create a string by removing first character
# If the key character exists in the hash, call next pointing node's add_item() with remaining string as argument
if self.next.has_key(key):
self.next[key].add_item(string)
# Else create an empty node. Insert the key character to hash and point it to newly created node. Call add_item() in new node with remaining string.
else:
node = Node()
self.next[key] = node
node.add_item(string)
def dfs(self, sofar=None):
'''Perform Depth First Search Traversal'''
# When hash of the current node is empty, that means it is a leaf node.
# Hence print sofar (sofar is a string containing the path as character sequences through which state transition occured)
if self.next.keys() == []:
print "Match:",sofar
return
if self.word_marker == True:
print "Match:",sofar
# Recursively call dfs for all the nodes pointed by keys in the hash
for key in self.next.keys():
self.next[key].dfs(sofar+key)
def search(self, string, sofar=""):
'''Perform auto completion search and print the autocomplete results'''
# Make state transition based on the input characters.
# When the input characters becomes exhaused, perform dfs() so that the trie gets traversed upto leaves and print the state characters
if len(string) > 0:
key = string[0]
string = string[1:]
if self.next.has_key(key):
sofar = sofar + key
self.next[key].search(string,sofar)
else:
print "No match"
else:
if self.word_marker == True:
print "Match:",sofar
for key in self.next.keys():
self.next[key].dfs(sofar+key)
def fileparse(filename):
'''Parse the input dictionary file and build the trie data structure'''
fd = open(filename)
root = Node()
line = fd.readline().strip('\r\n') # Remove newline characters \r\n
while line !='':
root.add_item(line)
line = fd.readline().strip('\r\n')
return root
if __name__ == '__main__':
if len(sys.argv) != 2:
print "Usage: ", sys.argv[0], "dictionary_file.txt"
sys.exit(2)
root = fileparse(sys.argv[1])
print "Input:",
input=raw_input()
root.search(input)

Answer 3

I'm not a Java or Python coder, but can give you a very simple c# trie implementation. It's very very simple so I'm sure you could map it to Java.
Here it is:
public class Trie<T> : Dictionary<T, Trie<T>>
{
}
Done. Told you it was simple. But it is a trie and it works.

Answer 4

Here is implementation:-
import java.util.HashMap;
public class Tries {
class Node {
HashMap<Character, Node> children;
boolean end;
public Node(boolean b){
children = new HashMap<Character, Tries.Node>();
end = false;
}
}
private Node root;
public Tries(){
root = new Node(false);
}
public static void main(String args[]){
Tries tr = new Tries();
tr.add("dog");
tr.add("doggy");
System.out.println(tr.search("dogg"));;
}
private boolean search(String word) {
Node crawl = root;
int n = word.length();
for(int i=0;i<n;i++){
char ch = word.charAt(i);
if(crawl.children.get(ch) == null){
return false;
}
else {
crawl = crawl.children.get(ch);
if(i==n-1 && crawl.end == true){
return true;
}
}
}
return false;
}
private void add(String word) {
Node crawl = root;
int n = word.length();
for(int i=0;i<n;i++){
char ch = word.charAt(i);
if(crawl.children.containsKey(ch)){
crawl = crawl.children.get(ch);
}
else {
crawl.children.put(ch, new Node(false));
Node temp = crawl.children.get(ch);
if(i == n-1){
temp.end = true;
}
crawl = temp;
System.out.println(ch + " " + crawl.end);
}
}
}
}
Just use hashmap and keep track of end of word.