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