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Is there any way in Pythonista to create a Markov chain text generator (or something resembling one)? Something, in other words, that will take user-provided text (either via imported document or copy/paste) and use that as a source library for generating random semi-coherent sentences?

I have sample code for Markov chain text somewhere, just need to clean it up a bit.

This generates some interesting, pseudo-random text from Tolstoi's Anna Karenina:

#!python3

# Adapted from this blog post: http://agiliq.com/blog/2009/06/generating-pseudo-random-text-with-markov-chains-u/

import random
import os
import urllib.request

class Markov(object):

    def __init__(self, open_file):
        self.cache = {}
        self.open_file = open_file
        self.words = self.file_to_words()
        self.word_size = len(self.words)
        self.database()


    def file_to_words(self):
        self.open_file.seek(0)
        data = self.open_file.read()
        words = data.split()
        return words


    def triples(self):
        """ Generates triples from the given data string. So if our string were
                "What a lovely day", we'd generate (What, a, lovely) and then
                (a, lovely, day).
        """

        if len(self.words) < 3:
            return

        for i in range(len(self.words) - 2):
            yield (self.words[i], self.words[i+1], self.words[i+2])

    def database(self):
        for w1, w2, w3 in self.triples():
            key = (w1, w2)
            if key in self.cache:
                self.cache[key].append(w3)
            else:
                self.cache[key] = [w3]

    def generate_markov_text(self, size=25):
        while True:
            seed = random.randint(0, self.word_size-3)
            seed_word = self.words[seed]
            if seed_word[0].isupper():
                break       
        seed_word, next_word = self.words[seed], self.words[seed+1]
        w1, w2 = seed_word, next_word
        gen_words = []
        while not w2.endswith('.'):
            gen_words.append(w1)
            w1, w2 = w2, random.choice(self.cache[(w1, w2)])
        gen_words.append(w2)
        return ' '.join(gen_words)

def main():
    if not os.path.exists('anna_karenina.txt'):
        print('Downloading book...')
        urllib.request.urlretrieve('http://www.gutenberg.org/files/1399/1399-0.txt', 'anna_karenina.txt')

    with open('anna_karenina.txt', 'r', encoding='utf-') as f:
        markov = Markov(f)
        print(markov.generate_markov_text())

if __name__ == '__main__':
    main()

@omz , was fun to look at this code and run it. But then I went to http://www.gutenberg.org to see other books. What a messy site for such an important resource. Surprising no one has offered to re do it using bootstrap or another type of framework. Just saying...

Thanks, ole! I'll give it a go!