A random text generator based on an N=2 Markov chain model.

markov.py

from collections import defaultdict
import random

class Markov:
  memory = defaultdict(list)
  separator = ' '

  def get_initial(self):
    return (' ', ' ')

  def break_text(self, txt):
    prev = self.get_initial()

    for word in txt.split(self.separator):
      yield prev, word
      prev = (prev[1], word)

    yield prev, ''

  def learn(self, txt):
    for part in self.break_text(txt):
      key = part[0]
      value = part[1]

      self.memory[key].append(value)

  def step(self, state):
    choice = random.choice(self.memory[state] or [''])

    if not choice:
      return None

    next_state = (state[1], choice)
    return choice, next_state

  def ask(self, seed=None):
    ret = []

    if not seed:
      seed = self.get_initial()

    while True:
      link = self.step(seed)

      if link is None:
        break

      ret.append(link[0])
      seed = link[1]

    return self.separator.join(ret)