def generate_status(tweet_list):
'''(list) -> str,
returns markov-generated status'''
tweet_text = ' '.join(tweet_list)
try:
mc = MarkovGenerator(tweet_text, 90, tokenize_fun=twitter_tokenize)
status = mc.generate_words().lower()
return status
except ValueError as e:
print e
pass
def test_train(self):
generator = MarkovGenerator(
MarkovGenerator.TrainStrategy(database=self.db,
text_path='test_texts/test.txt',
window_size=2))
manual_model = {
'end бои': {
'у': 1
},
'бои у': {
'сопоцкина': 1
},
'у сопоцкина': {
'и': 1
},
'сопоцкина и': {
'друскеник': 1
},
'и друскеник': {
'закончились': 1
},
'друскеник закончились': {
'отступлением': 1
},
'закончились отступлением': {
'германцев': 1
},
'отступлением германцев': {
'.': 1
},
'германцев .': {
'end': 1
},
}
model = dict()
tokenizer = generator.strategy.tokenizer
for line in self.db['model'].find():
line_key = ' '.join(
[tokenizer.idx2word(idx) for idx in line['key'].split()])
line_value = {
tokenizer.idx2word(key): value
for key, value in line['value'].items()
}
model[line_key] = line_value
self.assertEqual(manual_model, model)
def generate_random_content():
global contents
global titles
def random_content():
return ".\n\n".join([(mg.say().strip()) for _i in range(4)])
start = time.time()
print("Generating random content...", end="")
sys.stdout.flush()
mg = MarkovGenerator(2)
txt = file('/rinjani/var/data/milton-paradise.txt').read()
txt = re.sub('["*]*-', '', txt)
mg.learn(txt)
contents = [random_content() for _i in range(200)]
titles = [
re.sub(r'[^\w\s]+', '', truncate_words(mg.say().strip(), 10))
for _i in range(100)
]
print(" finished in %ds." % (time.time() - start))
sys.stdout.flush()
import random
from markov import MarkovGenerator
from markov_by_char import CharacterMarkovGenerator
# word MarkovGenerator
generator = MarkovGenerator(n=2, max=500)
# character MarkovGenerator
#generator = CharacterMarkovGenerator(n=3, max=100)
for line in open('white-album.txt'):
line = line.strip()
generator.feed(line)
generator.feed(line)
for line in open('black-album.txt'):
line = line.strip()
generator.feed(line)
for i in range(3):
print generator.generate()
import sys
reload(sys)
sys.setdefaultencoding('utf8')
from markov import MarkovGenerator
file = open("input/" + sys.argv[1])
lines = file.readlines()
generator = MarkovGenerator(n=2, max=3000)
for line in lines:
generator.feed(line)
text = generator.generate()
print text
