markov.py

import functools

def markov_chain(initial_word=None, heuristic_function=lambda x, y: 0):
    chain_words = [initial_word]
   
    while chain_words[-1] != None:
        current_word = chain_words[-1]
        
        # Generate a pool of potential antecedents to choose from
        potential_followup_words = followup_words_for(current_word)
        
        # Rank that pool of antecedents by a heuristic comparing options
        ranked_followup_words = sorted(potential_followup_words, key=functools.cmp_to_key(heuristic_function))
        
        # Choose a word and advance forward through the chain
        selected_word = ranked_followup_words[0]
        chain_words.append(selected_word)
    
    return " ".join(chain_words[0:-1])
 
def frequency_heuristic(option_one, option_two):
    print("in heuristic")
    print(option_one)
    print(option_two)
  
print(markov_chain(initial_word="There", heuristic_function=frequency_heuristic))