def load_ts_lyric_obfuscators():
lo0 = MarkovKeyState(16)
lo1 = MarkovKeyState(16)
with open(join("datasets", "ts_lyrics.lst"), "r") as f:
text = f.read()
lo0.learn_book(text)
lo1.learn_book(text)
return lo0, lo1
def load_ts_lyric_obfuscators():
lo0 = MarkovKeyState(16)
lo1 = MarkovKeyState(16)
with open(join("datasets", "ts_lyrics.lst"), "r") as f:
text = f.read()
lo0.learn_book(text)
lo1.learn_book(text)
return lo0, lo1
def test_splitting_and_joining(self):
test_string = "test0 test1 test2\ntest3 test4 test5"
split_string = MarkovKeyState.split_obfuscated_string(test_string)
joined_string = MarkovKeyState.join_obfuscated_string(split_string)
assert joined_string == test_string
parser.add_argument('-r', '--remote', default=None, type=str, action='append', help='Remote server to tunnel to')
parser.add_argument('-p', '--port', default=9050, type=int, help='Port to listen on')
parser.add_argument('-P', '--remoteport', default=9999, type=int, help='Port for remote server')
args = parser.parse_args()
logging.basicConfig(level=logging.DEBUG)
# Regular expression to split our training files on
split_regex = r'\.'
# File/book to read for training the Markov model (will be read into memory)
training_file = "datasets/98.txt"
# Obfuscating Markov engine
m = MarkovKeyState()
# Read the shared key into memory
logging.info("Reading {0}".format(training_file))
with open(training_file, "r") as f:
text = f.read()
import re
# Split learning data into sentences, in this case, based on periods.
logging.info("Teaching the Markov model")
map(m.learn_sentence, re.split(split_regex, text))
if args.server:
# We are the terminating server
host = "0.0.0.0"
port = int(args.remoteport)
def test_splitting_and_joining(self):
test_string = "test0 test1 test2\ntest3 test4 test5"
split_string = MarkovKeyState.split_obfuscated_string(test_string)
joined_string = MarkovKeyState.join_obfuscated_string(split_string)
assert joined_string == test_string
def __init__(self, *args):
MarkovKeyState.__init__(self, *args)
def __init__(self, *args):
MarkovKeyState.__init__(self, *args)
