table_exists = markov.cur.fetchone()[0]
if not table_exists:
logging.info("Transition table does not exist. Creating it now...")
markov.cur.execute("""
CREATE TABLE transition ( \
first_word VARCHAR, \
second_word VARCHAR, \
result_word VARCHAR, \
frequency INTEGER, \
beginning BOOLEAN, \
PRIMARY KEY(first_word, second_word, result_word) \
);
""")
markov.conn.commit()
markov._disconnect_db()
logging.info("Cleaning up Twitter data.")
dataframe = pd.read_csv(tweet_data_file)
with open(clean_data_file, 'w') as file:
for line in dataframe.text.iteritems():
file.write(twitterbot.clean_data(line[1] + "\n"))
logging.info("Training the database.")
gen = generate_word(clean_data_file)
markov.update_db(gen)
twitterbot._connect_api()
last_id_seen = int(dataframe.tweet_id[0])
replies = twitterbot.api.GetMentions()
if replies is not None:
