Not Working: feeding webtext into Markov code

Web_to_Markov.py

import urllib
import BeautifulSoup
import re
from random import choice
#import context_free
import sys
import markov


html = urllib.urlopen('http://www.george-orwell.org/1984/0.html').read()
soup = BeautifulSoup.BeautifulSoup(html)
#texts = soup.findAll(text=True)

#soup.html.body.table.contents[1].td.contents[3].tr.contents[3].table.contents[5].tr.td.table.tr.td.tr.td.table.contents[3].td.contents[4]
texts=soup.html.body.table.contents[1].td.contents[3].tr.contents[3].table.contents[5].tr.td.table.tr.td.tr.td.table.contents[3].td.contents[4]
#print(texts)
#print type(texts)

def visible(element):
    if element.parent.name in ['style', 'script', '[document]', 'head', 'title']:
        return False
    elif re.match('<!--.*-->', str(element)):
       return False
    return True

visible_texts = filter(visible, texts)
text = visible_texts[0].getText()

generator = markov.MarkovGenerator(n=5, max=500)
for line in text:
    stringline=line.encode('utf-8')
    generator.feed(stringline)

    
#    print line
#    line = line.strip(";:#-?.,")
#    stringline=line.encode('utf-8')
#    print stringline
#    generator.feed(stringline)
#    word=line.split(" ")


 
for i in range(1):
    print generator.generate()

    
def feed(self, text):
     tokens = self.tokenize(text)
     # discard this line if it's too short
     if len(tokens) < self.n:
        return

    # store the first ngram of this line
     beginning = tuple(tokens[:self.n])
     self.beginnings.append(beginning)
 
     for i in range(len(tokens) - self.n):
 
        gram = tuple(tokens[i:i+self.n])
        next = tokens[i+self.n] # get the element after the gram  
        
# if we've already seen this ngram, append; otherwise, set the
# value for this key as a new list
     if gram in self.ngrams:
        self.ngrams[gram].append(next)
     else:
        self.ngrams[gram] = [next]
        
        
        
# generate a text from the information in self.ngrams
def generate(self):
 
    from random import choice
 
# get a random line beginning; convert to a list.
    current = choice(self.beginnings)
    output = list(current)
 
    for i in range(self.max):
        if current in self.ngrams:
            possible_next = self.ngrams[current]
            next = choice(possible_next)
            output.append(next)
# get the last N entries of the output; we'll use this to look up
# an ngram in the next iteration of the loop
            current = tuple(output[-self.n:])
        else:
            break
 
        output_str = self.concatenate(output)
        return output_str