markov_gen.py

# Imports markov_python module and makes an instance of the MarkovChain class
# Adds speech text file

from cc_markov import MarkovChain    

mc = MarkovChain()
MarkovChain.add_file(mc, 'Trump_speech.txt')

# Generates text and alters output into 'sonnet' form
# Uses a while loop to generate 12 words for 14 lines
# Capitalises first letters. Indents last 2 lines, to make a 'couplet'

print 'A little Trump sonnet...  ', '\n'

count = 0
sonnet = []
while count <15:
    x = MarkovChain.generate_text(mc, max_length=12)
    s = ''.join([i[0].upper() + i[1:] for i in (x[0].split())])
    y = s + ' ' + ' '.join(x[1:])
    if count == 13:
        y = '   ' + y
        sonnet.append(y)
    elif count == 14:
        y = '   ' + y + '...'
        sonnet.append(y)
    else:
        sonnet.append(y)
    count +=1

sonnet = '\n'.join(sonnet)
print sonnet

# Imports tweepy, assigns the specific authorisation keys to access the API
# Iterates through one 'sonnet' and tweets each line every 15 minutes

#import tweepy, time

#enter the corresponding information from your Twitter application:
#CONSUMER_KEY = '*************************'
#CONSUMER_SECRET = '**************************'
#ACCESS_KEY = '**********************************'
#ACCESS_SECRET = '*********************************'
#auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
#auth.set_access_token(ACCESS_KEY, ACCESS_SECRET)
#api = tweepy.API(auth)

tweet = sonnet.splitlines()
print "\n" + "Trump Tweet:" + "\n" + tweet[0]

#for line in tweet:
    #api.update_status(line)
    #time.sleep(900)#Tweet every 15 minutes