Markov Chain tweeter for @briancox

gistfile1.py

#!/usr/bin/python

import random
import oauth2 as oauth
import sys
import twitter

class Markov(object):
    
    def __init__(self):
        self.cache = {}
        self.words = fetch("profbriancox")
        self.word_size = len(self.words)
        self.database()

    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=20):
        seed = random.randint(0, self.word_size-3)
        seed_word, next_word = self.words[seed], self.words[seed+1]
        w1, w2 = seed_word, next_word
        gen_words = []
        for i in xrange(size):
            gen_words.append(w1)
            w1, w2 = w2, random.choice(self.cache[(w1, w2)])
        gen_words.append(w2)
        return ' '.join(gen_words)

ACCESS_TOKEN_KEY="accesstokenkey"
ACCESS_TOKEN_SECRET="accesstokenkeysecret"
CONSUMER_KEY="consumerkey"
CONSUMER_SECRET="consumersecret"

api = twitter.Api(
    consumer_key=CONSUMER_KEY,
    consumer_secret=CONSUMER_SECRET,
    access_token_key=ACCESS_TOKEN_KEY,
    access_token_secret=ACCESS_TOKEN_SECRET)

######
def fetch(user):
    data = {}
    api = twitter.Api()
    max_id = None
    total = 0
    words = []
    while True:
        try:
            statuses = api.GetUserTimeline(user, count=200, max_id=max_id)
            newCount = ignCount = 0
            for s in statuses:
                if s.id in data:
                    ignCount += 1
                else:
                    data[s.id] = s
                    newCount += 1
            total += newCount
            print >>sys.stderr, "Fetched %d/%d/%d new/old/total." % (
                newCount, ignCount, total)
            if newCount == 0:
                break
            max_id = min([s.id for s in statuses]) - 1
            for s in statuses:
                words.extend(s.text.split())
        except:
            return words        
    return words


m = Markov()

def tweet():
    msg = m.generate_markov_text(random.randint(5,20))
    while len(msg) > 140:
        msg = m.generate_markov_text(random.randint(5,20))
    api.PostUpdate(msg)