Problem: Strings can be efficiently stored as a data structure, to have efficient searching methods.
A new startup is going to use this method, but they don't have much space. So they want to check beforehand how much memory will be required for their data. 
Following method describes the way in which this startup's engineers save the data in the structure.

Suppose they have 5 strings/words: et,eq,bd,be,bdp
A empty node is kept NULL, and strings are inserted into the structure one by one. 
Initially the structure is this:

NULL

After inserting "et", the structure is this:

NULL
 |
 e
 |
 t

After inserting "eq", the structure is this:

   NULL
   /
  e
 / \
t   q

After inserting "bd", the structure is this:

   NULL
   /  \
  e    b
 / \    \
t   q    d

After inserting "be", the structure is this:

     NULL
   /     \
  e       b
 / \     / \
t   q   e   d

After inserting "bdp", the structure is this:

    NULL
   /     \
  e       b
 / \     / \
t   q   e   d
             \
              p

Therefore a total of 8 nodes are used here.    

Input: 
First line contains N, the number of strings they have.  
Each of the next N lines contain one string. Each string consists only of lowercase letters.    

Output: 
Print the required number of nodes.    

**Constraints: 
1 ≤ N ≤ 10^5     
Length of each string  ≤ 30    

Note: No two strings are same, though one string could be prefix of another.

SAMPLE INPUT
5
et
eq
bd
be
bdp

SAMPLE OUTPUT
8

Solution (in PYTHON):

Solution:
import fileinput

class Node(object):
    def __init__(self,data):
        self.data=data
        self.children={} # {'data' => Node}
        self.max_score =0
        
    def add_child(self,data,score):
        if self.children.has_key(data):
            pass
        else:
            self.children[data]=Node(data)
        self.children[data].max_score= score
        return self.children[data]
    
    def is_leaf(self):
        return len(self.children) == 0 and self.data != ""
    
    def __str__(self, *args, **kwargs):
        return self.data
    
class Trie(object):
    def __init__(self):
        self.root= Node("")
        self.num_node=1
        
    def add_string(self,string, score):
        node, end_index = self.find_path(string,-1)
        length= len(string)
        
        for i in range(end_index,length):
            if node.max_score < score:
                node.max_score = score
            node= node.add_child(string[i], score)
            self.num_node=self.num_node + 1
    
    # return node
    def find_path(self, string, score):
        node= self.root
        i= 0
        for c in string:
            if node.children.has_key(c):
                i=i+1
                node=node.children[c]              
            else:
                break
        return node, i
    
    def max(self,node):
        pass
        
if __name__=="__main__":
    f= fileinput.input()
    n= int(f.readline())
    
    trie= Trie()
    
    while n > 0:
        n=n-1
        line = f.readline().strip()
        trie.add_string(line, -1)
    print trie.num_node