This is a simple script that auto-generates texts using Markov chains based on your Mac iMessage history

texts_markov.py

__author__ = "Alex Beals"

import sqlite3, markovify, codecs, warnings, os

# Handle errors from running on Python 2.7 (emoji support)
warnings.simplefilter("ignore")

print("Connecting to chat database...")

# Extract all of my texts from the 'db' file
conn = sqlite3.connect(os.path.expanduser("~/Library/Messages/chat.db"))
c = conn.cursor()
c.execute('SELECT text FROM message WHERE text != "" AND is_from_me = 1')
texts = c.fetchall()

print("Building corpus out of " + "{:,}".format(len(texts)) + " messages...")

# Combine all of the messages into one giant string
corpus_text = []
for text in [x[0] for x in texts]:
  corpus_text.append(text)
  if (text[-1] in "!?."):
    corpus_text.append(" ")
  else:
    corpus_text.append(". ")
corpus_text = "".join(corpus_text)

print ("Buiding Markov model out of " + "{:,}".format(len(corpus_text)) + " characters...")

# Load that text file in, and generate the markov file
text_model = markovify.Text(corpus_text)

print("Done.  Press 'Enter' for a Markov sentence based off of your texts.  Type anything else and press 'Enter' to quit.\n")

# Print a sentence every time you press 'Enter'
while True:
  line = raw_input()
  print('\033[2A')
  if line == "":
    print text_model.make_sentence()
  else:
    break