def setUp(self, _):
self.corpus = path.join(path.dirname(__file__), 'data', 'tweets.txt')
self.configfile = path.join(path.dirname(__file__), '..', 'bots.yaml')
self.tm = TwitterMarkov('example_screen_name', [self.corpus], config=self.configfile,
dry_run=True, learn=False)
self.tm.log.setLevel(100)
def testCheck(self):
tm = TwitterMarkov('example_screen_name', [self.corpus],
config=self.configfile,
dry_run=True,
learn=False)
self.assertFalse(tm.check_tweet('😀' * 141))
self.assertFalse(tm.check_tweet(''))
self.assertFalse(tm.check_tweet('contains the blacklisted word t**s'))
class tweeter_markov_tests(unittest.TestCase):
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def setUp(self, _):
self.corpus = path.join(path.dirname(__file__), 'data', 'tweets.txt')
self.configfile = path.join(path.dirname(__file__), '..', 'bots.yaml')
self.tm = TwitterMarkov('example_screen_name', [self.corpus], config=self.configfile,
dry_run=True, learn=False)
self.tm.log.setLevel(100)
def testCheckModels(self):
for m in self.tm.models.values():
self.assertIsInstance(m, markovify.text.NewlineText)
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovCompose(self, *_):
response = self.tm.compose(tries=150, max_overlap_ratio=2, max_overlap_total=100)
assert isinstance(response, basestring)
assert len(response) < 140
@mock.patch.object(tweepy.API, 'mentions_timeline', return_value=fake_timeline())
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovReply(self, *_):
r = self.tm.reply_all(tries=75, max_overlap_ratio=2, max_overlap_total=100)
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovRecentlyTweeted(self, _):
recents = self.tm.recently_tweeted
assert recents[0] == TIMELINE[0]['text']
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovCheckTweet(self, _):
assert self.tm.check_tweet('') is False
assert self.tm.check_tweet('badword') is False
assert self.tm.check_tweet('Lorem ipsum dolor sit amet') is False
assert self.tm.check_tweet('Lorem ipsum dolor sit amet!') is False
assert self.tm.check_tweet('Lorem ipsum dolor set namet') is False
assert self.tm.check_tweet('Random Text that should work totally') is True
assert self.tm.check_tweet('@reply Random Text') is True
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovLearn(self, _):
tmp = path.join(path.dirname(__file__), 'data', 'tmp.txt')
self.tm.learn_parent(corpus=tmp)
try:
with open(tmp) as f:
result = f.read()
assert TIMELINE[0]['text'] in result
assert TIMELINE[1]['text'] in result
assert TIMELINE[2]['text'] in result
finally:
os.remove(tmp)
class tweeter_markov_tests(unittest.TestCase):
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def setUp(self, _):
self.corpus = path.join(path.dirname(__file__), 'data', 'tweets.txt')
self.configfile = path.join(path.dirname(__file__), '..', 'bots.yaml')
self.tm = TwitterMarkov('example_screen_name', [self.corpus], config=self.configfile,
dry_run=True, learn=False)
self.tm.log.setLevel(100)
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovCompose(self, *_):
response = self.tm.compose(tries=150, max_overlap_ratio=2, max_overlap_total=100)
assert isinstance(response, basestring)
assert len(response) < 140
@mock.patch.object(tweepy.API, 'mentions_timeline', return_value=fake_timeline())
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovReply(self, *_):
r = self.tm.reply_all(tries=75, max_overlap_ratio=2, max_overlap_total=100)
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovRecentlyTweeted(self, _):
recents = self.tm.recently_tweeted
assert recents[0] == TIMELINE[0]['text']
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovCheckTweet(self, _):
assert self.tm.check_tweet('') is False
assert self.tm.check_tweet('badword') is False
assert self.tm.check_tweet('Lorem ipsum dolor sit amet') is False
assert self.tm.check_tweet('Lorem ipsum dolor sit amet!') is False
assert self.tm.check_tweet('Lorem ipsum dolor set namet') is False
assert self.tm.check_tweet('Random Text that should work totally') is True
assert self.tm.check_tweet('@reply Random Text') is True
@mock.patch.object(tweepy.API, 'user_timeline', return_value=fake_timeline())
def testTwitterMarkovLearn(self, _):
tmp = path.join(path.dirname(__file__), 'data', 'tmp.txt')
self.tm.learn_parent(corpus=tmp)
try:
with open(tmp) as f:
result = f.read()
assert TIMELINE[0]['text'] in result
assert TIMELINE[1]['text'] in result
assert TIMELINE[2]['text'] in result
finally:
os.remove(tmp)
def testTwitterMarkovModel(self, *_):
tm = TwitterMarkov('example_screen_name',
self.corpus,
config=self.configfile,
dry_run=True,
learn=False)
assert isinstance(tm.models['tweets.txt'], markovify.text.Text)
def testTwitterMarkovListCorpus(self):
tm = TwitterMarkov('example_screen_name', [self.corpus],
config=self.configfile,
dry_run=True,
learn=False)
assert isinstance(tm, TwitterMarkov)
del tm
def testTwitterMarkovConfigCorpus(self):
tm = TwitterMarkov('example_screen_name',
config=self.configfile,
dry_run=True,
learn=False)
tm.log.setLevel(100)
del tm
def setUp(self, _):
self.corpus = path.join(path.dirname(__file__), 'data', 'tweets.txt')
self.configfile = path.join(path.dirname(__file__), '..', 'bots.yaml')
self.tm = TwitterMarkov('example_screen_name', [self.corpus], config=self.configfile,
dry_run=True, learn=False)
self.tm.log.setLevel(100)
def testTwitterMarkovAttribs(self):
tm = TwitterMarkov('example_screen_name',
self.corpus,
config=self.configfile,
dry_run=True,
learn=False)
tm.log.setLevel(100)
assert isinstance(tm, TwitterMarkov)
assert hasattr(tm, 'screen_name')
assert hasattr(tm, 'api')
assert hasattr(tm, 'config')
assert hasattr(tm, 'wordfilter')
del tm
def testCheck(self):
tm = TwitterMarkov('example_screen_name', [self.corpus], config=self.configfile,
dry_run=True, learn=False)
self.assertFalse(tm.check_tweet('😀' * 141))
self.assertFalse(tm.check_tweet(''))
self.assertFalse(tm.check_tweet('contains the blacklisted word t**s'))
state_sz = max(2, state_sz - 3)
else:
if (probability > 0.7):
state_sz = max(2, state_sz - 2)
else:
if (probability > 0.6):
state_sz = max(2, state_sz - 1)
print 'state_sz is ' + str(state_sz)
return state_sz
#--
random.seed()
tm = TwitterMarkov(
'example_screen_name',
'/home/celesteh/Dropbox/debbie/gifs/twitter_markov/corpus.txt',
config_file='/home/celesteh/Dropbox/debbie/gifs/twitter_markov/bots.yaml')
dict = enchant.DictWithPWL("en_US",
tm.config.get('dictionary_words')) #load dictionary
gifs = tm.config.get('gifs')
files = glob.glob((str(gifs) + '/out*.gif'))
if len(files) < 15:
if len(files) == 1:
title = 'Last Gif'
remain = 'This is the last tweet you can send.'
else:
title = 'Low Gifs'
remain = 'There are only ' + str(len(files)) + ' gifs remianing.'
else:
if(probability > 0.8):
state_sz = max(2, state_sz -3)
else:
if(probability > 0.7):
state_sz = max(2, state_sz -2)
else:
if (probability > 0.6):
state_sz = max(2, state_sz -1)
print 'state_sz is ' + str(state_sz)
return state_sz
#--
random.seed()
tm = TwitterMarkov('example_screen_name', '/home/celesteh/Dropbox/debbie/gifs/twitter_markov/corpus.txt', config_file='/home/celesteh/Dropbox/debbie/gifs/twitter_markov/bots.yaml')
dict = enchant.DictWithPWL("en_US",tm.config.get('dictionary_words')) #load dictionary
gifs = tm.config.get('gifs')
files = glob.glob((str(gifs) +'/out*.gif'))
if len(files) < 15:
if len(files) == 1:
title = 'Last Gif'
remain = 'This is the last tweet you can send.'
else:
title = 'Low Gifs'
remain = 'There are only '+ str(len(files)) + ' gifs remianing.'
print 'WARNING: make more gifs!\n' + remain