コード例 #1
0
def main():
    twitter_auth = tweepy.OAuthHandler(API_KEY, API_SECRET)
    twitter_auth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)

    twitter_client = tweepy.API(twitter_auth)

    print("building model...")

    shuffle(names)
    text = ' '.join(names)
    chain = Markov([text])

    print("making sentence...")
    length = randint(20, 35)
    result = ''
    while len(result) == 0:
        result = ''.join(chain.generate_text()[0:length])

    result = result.rstrip() + '!'

    print('tweeting...')
    print(result)
    try:
        response = twitter_client.update_status(status=result)
        print(response)
        return response
    except tweepy.error.TweepError as e:
        print(e)
        return e
コード例 #2
0
ファイル: __init__.py プロジェクト: vilmibm/incantationbot
def main():
    twitter_auth = tweepy.OAuthHandler(API_KEY, API_SECRET)
    twitter_auth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)

    twitter_client = tweepy.API(twitter_auth)

    print("building model...")

    shuffle(names)
    text = ' '.join(names)
    chain = Markov([text])

    print("making sentence...")
    length = randint(20, 35)
    result = ''
    while len(result) == 0:
        result = ''.join(chain.generate_text()[0:length])

    result = result.rstrip() + '!'

    print('tweeting...')
    print(result)
    try:
        response = twitter_client.update_status(status=result)
        print(response)
        return response
    except tweepy.error.TweepError as e:
        print(e)
        return e
コード例 #3
0
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from smarkov import Markov

chain = Markov(["AGACAGACGAC"])
print("".join(chain.generate_text()))
コード例 #4
0
ファイル: text.py プロジェクト: timur-surkhaev/smarkov
    """ Transforms words into a their expanded form - replaces all
    abbreviations like "'ll" or "n't"

    There are some special case like can't (in tokens ("ca", "n't")) or won't
    where we want to replace both forms

    Args:
        words: words iterator to search and replace
    Returns:
        words iterator with replaced abbreviations
    """
    for word in words:
        if word in REPLACE_WORDS:
            yield REPLACE_WORDS[word]
        else:
            yield word


def tokenize(s):
    return expanding_words(
        re.findall("[A-Z]{2,}(?![a-z])|[A-Z][a-z]+(?=[A-Z])|[\'\w\-]+", s))


scriptDir = os.path.dirname(os.path.realpath(__file__))
inputFile = os.path.join(scriptDir, "./pg1342.txt")
with open(inputFile, "r") as inFile:
    corpus = re.split('(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s',
                      inFile.read())
    chain = Markov(corpus, tokenize=tokenize)
    print(join_tokens_to_sentences(chain.generate_text()))
コード例 #5
0
ファイル: markov.py プロジェクト: nwokeo/southparkbot
from smarkov import Markov
from glob import glob
import random
import markovify # https://github.com/jsvine/markovify

allwords = []

files = glob('SouthParkData/Season*.csv')
with open(files[random.randrange(len(files))]) as infile:
    for line in infile:
        words = line[line.find('"'):].replace('\n', '').replace('"', '').split(' ')
        if words != ['']:
            allwords.append(words)

with open(files[random.randrange(len(files))]) as infile:
    text = infile.read()

chain = Markov(allwords)
print(" ".join(chain.generate_text()))

text_model = markovify.Text(text)
for i in range(5):
    print(text_model.make_sentence())
コード例 #6
0
ファイル: text.py プロジェクト: Ulitochka/smarkov
def expanding_words(words):
    """ Transforms words into a their expanded form - replaces all
    abbreviations like "'ll" or "n't"

    There are some special case like can't (in tokens ("ca", "n't")) or won't
    where we want to replace both forms

    Args:
        words: words iterator to search and replace
    Returns:
        words iterator with replaced abbreviations
    """
    for word in words:
        if word in REPLACE_WORDS:
            yield REPLACE_WORDS[word]
        else:
            yield word


def tokenize(s):
    return expanding_words(re.findall("[A-Z]{2,}(?![a-z])|[A-Z][a-z]+(?=[A-Z])|[\'\w\-]+", s))

scriptDir = os.path.dirname(os.path.realpath(__file__))
inputFile = os.path.join(scriptDir, "./pg1342.txt")
with open(inputFile, "r") as inFile:
    corpus = re.split(
        '(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', inFile.read())
    chain = Markov(corpus, tokenize=tokenize)
    print(join_tokens_to_sentences(chain.generate_text()))