def markov_tweet():
""" Generates a tweet using a Markov bot. """
bot = MarkovBot()
read_book(bot, 'alice.txt')
read_book(bot, 'dao.txt')
read_book(bot, 'pride.txt')
read_book(bot, 'sherlock.txt')
read_book(bot, 'oz.txt')
seed_words = ['drink', 'health', 'water', 'river', 'stream']
tweet_content = bot.generate_text(15, seedword=seed_words)
print tweet_content
# Check if the generated content has a seed word in it.
for word in seed_words:
if word in tweet_content:
return tweet_content + ' #DrinkWater'
return None
def markov():
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
data1 = os.path.join(dirname, 'positiveTweets.txt')
data2 = os.path.join(dirname, '1liner.txt')
data3 = os.path.join(dirname, '10ondate.txt')
data4 = os.path.join(dirname, 'forCachetes.txt')
#data5 = os.path.join(dirname, 'book3.txt')
#data6 = os.path.join(dirname, 'book4.txt')
data7 = os.path.join(dirname, 'jokes.txt')
#data8 = os.path.join(dirname, 'book4.txt')
tweetbot.read(data1)
tweetbot.read(data2)
tweetbot.read(data3)
tweetbot.read(data4)
#tweetbot.read(data5)
#tweetbot.read(data6)
tweetbot.read(data7)
#tweetbot.read(data8)
my_first_text = tweetbot.generate_text(25, seedword=['life', 'motivation', 'happy', 'bullying'])
print("tweetbot says:")
print(my_first_text)
import os
from markovbot import MarkovBot
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
print(dirname)
# Construct the path to the book
book = os.path.join(dirname, 'hotep_speak.txt')
# Make your bot read the book!
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25, seedword=['black', 'america'])
print("tweetbot says:")
print(my_first_text)
# ALL YOUR SECRET STUFF!
# Consumer Key (API Key)
cons_key = 'K9YqNYb8j6HA0hgBKLZ1aQ918'
# Consumer Secret (API Secret)
cons_secret = 'BFCDji7mF7sfw2PpdQMEcZ90Poht5E6OMff1XEHb3UeLB8K1Fz'
# Access Token
access_token = '988043632828715008-U4kAofzutxFuPx6c3jCwnrRztm3y5lt'
# Access Token Secret
access_token_secret = 'zNxtfZQb9HU3nRN88uJzJ39H2Ttfk7Vno0Qc3WobX0U5J'
# Log in to Twitter
tweetbot.twitter_login(cons_key, cons_secret, access_token,
access_token_secret)
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import os
from markovbot import MarkovBot
tweetbot = MarkovBot()
dirname = os.path.abspath(C:\Users\Colin\Documents\Growtye\bot\tweetbot\markovbot-master\Freud_Dream_Psychology.txt)
book = os.path.join(dirname,'Freud_Dream_Psychology.txt')
tweet.read(book)
my_first_text - tweetbot.generate_text(25, seedword=['dream','psychoanalysis'])
print("tweetbot says:")
print(my_first_text)
import os import time from markovbot import MarkovBot # # # # # # INITIALISE # Initialise a MarkovBot instance tweetbot = MarkovBot() # Get the current directory's path dirname = os.path.dirname(os.path.abspath(__file__)) # Construct the path to the book book = os.path.join(dirname, u'smith_wealth_of_nations.txt') # Make your bot read the book! tweetbot.read(book) # # # # # # TEXT GENERATION # Generate text by using the generate_text method: # The first argument is the length of your text, in number of words # The 'seedword' argument allows you to feed the bot some words that it # should attempt to use to start its text. It's nothing fancy: the bot will # simply try the first, and move on to the next if he can't find something # that works. my_first_text = tweetbot.generate_text(25, seedword=[u'labour', u'capital']) # Print your text to the console print(u'\ntweetbot says: "%s"' % (my_first_text))
import os import time from markovbot import MarkovBot # # # # # # INITIALISE # Initialise a MarkovBot instance tweetbot = MarkovBot() # Get the current directory's path dirname = os.path.dirname(os.path.abspath(__file__)) # Construct the path to the book book = os.path.join(dirname, u'Freud_Dream_Psychology.txt') # Make your bot read the book! tweetbot.read(book) # # # # # # TEXT GENERATION # Generate text by using the generate_text method: # The first argument is the length of your text, in number of words # The 'seedword' argument allows you to feed the bot some words that it # should attempt to use to start its text. It's nothing fancy: the bot will # simply try the first, and move on to the next if he can't find something # that works. my_first_text = tweetbot.generate_text(25, seedword=[u'dream', u'psychoanalysis'])
from random import randint
from markovbot import MarkovBot
import os
bot = MarkovBot()
book = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'realdonaldtrump.txt')
# Make your bot read the text!
bot.read(book)
# Choose how many tweets you want to generate
tweets_to_generate = 150
for x in range(0, tweets_to_generate):
# len of the new tweets that will be generated, in words
tweet_len = randint(10, 25)
# generating tweet, based on its len and seedwords!
tweet = bot.generate_text(tweet_len, seedword=[])
# writting to our generated sentences to the file the poster will use later
sentences_list = open("generated_sentences.txt", "a")
sentences_list.write(tweet + "\n")
sentences_list.close()
import os import time from markovbot import MarkovBot # # # # # # INITIALISE # Initialise a MarkovBot instance tweetbot = MarkovBot() # Get the current directory's path dirname = os.path.dirname(os.path.abspath(__file__)) # Construct the path to the book book = os.path.join(dirname, u'onion_headlines_filtered.txt') # Make your bot read the book! tweetbot.read(book) # # # # # # TEXT GENERATION # Generate text by using the generate_text method: # The first argument is the length of your text, in number of words # The 'seedword' argument allows you to feed the bot some words that it # should attempt to use to start its text. It's nothing fancy: the bot will # simply try the first, and move on to the next if he can't find something # that works. my_first_text = tweetbot.generate_text(maxlength=15) # Print your text to the console print(u'\ntweetbot says: "%s"' % (my_first_text))
while(tweetStr_2 == ""):
if sentenceKey[dictNo].has_key(rowResponse['rows'][0][column]):
tweetStr_2 = sentenceKey[dictNo][rowResponse['rows'][0][column]]
else:
column = randint(8,27)
tweetStr = tweetStr_1 + tweetStr_2
return tweetStr
while True:
tweetStr = GetTweetStr(service)
api.update_status(tweetStr)
time.sleep(3600)
# Markovbot for automated replies
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
book = os.path.join(dirname, u'ebook.txt')
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25, seedword=[u'economy', u'money'])
print(u'\ntweetbot says: "%s"' % (my_first_text))
# Log in to Twitter
tweetbot.twitter_login(cons_key, cons_secret, access_token, access_token_secret)
#Start tweeting periodically
tweetbot.twitter_tweeting_start(days=0, hours=0, minutes=1, keywords=None, prefix=None, suffix=None)
import os
from markovbot import MarkovBot
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
book = os.path.join(dirname, 'EveryBeatleslyricrecorded.txt')
tweetbot.read(book)
my_first_text = tweetbot.generate_text(50)
print("tweetbot says:")
print(my_first_text)
import os import time from markovbot import MarkovBot # # # # # # INITIALISE # Initialise a MarkovBot instance tweetbot = MarkovBot() # Get the current directory's path, find Malcolm's speech collections and read it dirname = os.path.dirname(os.path.abspath(__file__)) book = os.path.join(dirname, u'speeches/all_speeches.txt') tweetbot.read(book) # # # # # # TWUTT # The MarkovBot uses @sixohsix' Python Twitter Tools, which is a Python wrapper # for the Twitter API. Find it on GitHub: https://github.com/sixohsix/twitter cons_key = os.environ['MY_CONSUMER_KEY'] cons_secret = os.environ['MY_CONSUMER_SECRET'] access_token = os.environ['MY_ACCESS_TOKEN_KEY'] access_token_secret = os.environ['MY_ACCESS_TOKEN_SECRET'] # Log in to Twitter tweetbot.twitter_login(cons_key, cons_secret, access_token, access_token_secret) # The target string is what the bot will reply to on Twitter. To learn more, # read: https://dev.twitter.com/streaming/overview/request-parameters#track
import os import time from markovbot import MarkovBot # # # # # # INITIALISE # Initialise a MarkovBot instance tweetbot = MarkovBot() # Get the current directory's path dirname = os.path.dirname(os.path.abspath(__file__)) # Construct the path to the book book = os.path.join(dirname, u'data_amazon_one_star.txt') # Make your bot read the book! tweetbot.read(book) # # # # # # TEXT GENERATION # Generate text by using the generate_text method: # The first argument is the length of your text, in number of words # The 'seedword' argument allows you to feed the bot some words that it # should attempt to use to start its text. It's nothing fancy: the bot will # simply try the first, and move on to the next if he can't find something # that works. my_first_text = tweetbot.generate_text(25, seedword=[u'failed', u'crap']) # Print your text to the console print(u'\ntweetbot says: "%s"' % (my_first_text))
#!/usr/local/bin/python # -*- coding: utf-8 -*- import os import time from markovbot import MarkovBot tweetbot = MarkovBot() dirname = os.path.dirname(os.path.abspath(__file__)) book = os.path.join(dirname, u'politicaBrasileira.txt') tweetbot.read(book) my_first_text = tweetbot.generate_text(30) print(u'\ntweetbot says: "%s"' % (my_first_text)) # Consumer Key (API Key) cons_key = '1rVz2u5o37F6ycuQiXqYpmvz7' # Consumer Secret (API Secret) cons_secret = 'r1z2vJLwUExkWDm0vgVKgUYLT5cB5jRcUQDxizbBp6jIYGv4Op' # Access Token access_token = '772074137258954752-g9yoZSIRVmhA9EQmyAfDAx5Hfef1G7w' # Access Token Secret access_token_secret = 'sqkQRyOWKSXXSxZHqVWwKZZoJpXHnLar7nlT2z1O1ot8Z' # Log in to Twitter tweetbot.twitter_login(cons_key, cons_secret, access_token, access_token_secret) targetstring = 'professorpolitica'
import os
import time
from markovbot import MarkovBot
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
book = os.path.join(dirname, 'manifesto.txt')
tweetbot.read(book)
my_text = tweetbot.generate_text(25, seedword=['society', 'bourgeoisie'])
print(my_text)
# Consumer Key (API Key)
cons_key = 'TIShdZ9JgpYIyg8X4oJXAzgFq'
# Consumer Secret (API Secret)
cons_secret = 'qgLQKTadisYeb1T7DIVPNs17U7ce0LUaCAofHss8fiDWDMugpx'
# Access Token
access_token = '1087385094858387459-DijdGpPcFmugx0L86msnc5TOeXj8Gh'
# Access Token Secret
access_token_secret = 'XUAoW9ieporFcgqE1wMJnHEag4rpurUwJzewP7XCkhPgq'
#log in to twitter
tweetbot.twitter_login(cons_key, cons_secret, access_token,
access_token_secret)
#set parameters for auto-replies
targetstring = "capitalism"
keywords = ['cultural', 'economics', 'proletariat', 'bourgeoisie']
prefix = None
suffix = None
maxconvdepth = 1
#start auto-replies
tweetbot.twitter_autoreply_start(targetstring,
keywords=keywords,
prefix=prefix,
import os
import time
from markovbot import MarkovBot
# from markovbot import MarkovBot
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, 'Freud_Dream_Psychology.txt')
# Make your bot read the book!
tweetbot.read(book)
# my_first_text = tweetbot.generate_text(25, seedword=['dream', 'psychoanalysis'])
#print("tweetbot says:")
#print(my_first_text)
# ALL YOUR SECRET STUFF!
# Consumer Key (API Key)
cons_key = ''
# Consumer Secret (API Secret)
cons_secret = ''
# Access Token
access_token = ''
# Access Token Secret
access_token_secret = ''
# Log in to Twitter
def getBot(filePath):
tweetbot = MarkovBot()
tweetbot.read(filePath)
return tweetbot
import os
import time
from markovbot import MarkovBot
# # # # #
# INITIALISE
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, u'cleaner.trumptweets.txt')
# Make your bot read the book!
tweetbot.read(book)
# # # # #
# TEXT GENERATION
# Generate text by using the generate_text method:
# The first argument is the length of your text, in number of words
# The 'seedword' argument allows you to feed the bot some words that it
# should attempt to use to start its text. It's nothing fancy: the bot will
# simply try the first, and move on to the next if he can't find something
# that works.
my_first_text = tweetbot.generate_text(
25, seedword=[u'loser', u'sad', u'china', u'covfefe'])
# Print your text to the console
print("...%s tweets downloaded so far" % (len(alltweets)))
#transform the tweepy tweets into a 2D array that will populate the csv
outtweets = [[tweet.text.encode("utf-8")] for tweet in alltweets]
#write the csv
with open('%s_tweets.txt' % screen_name, 'wb') as f:
for tweet in alltweets:
f.write(tweet.text.encode("utf-8") + ' '.encode("utf-8"))
pass
get_all_tweets("kanyewest")
kanyebot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
tweets = os.path.join(dirname, 'kanyewest_tweets.txt')
# Make your bot read the book!
kanyebot.read(tweets)
kanyebot.twitter_login(consumer_key, consumer_secret, access_key,
access_secret)
# Set some parameters for your bot
targetstring = 'KanyeToTheBot'
keywords = ['kim', 'pablo', 'wavy', 'bill', 'cosby']
prefix = None
#Bot basado en MarkovBot con la funcion autoreply_start, tomando como fuente de texto el Manifiesto "Zorra Mutante" del colectivo ciberfeminista VNS Matrix
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import time
import sys
from markovbot import MarkovBot
reload(sys)
sys.setdefaultencoding('utf-8')
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Make your bot read the book!
tweetbot.read(
'https://github.com/gini10/akelarreciberfeminista/blob/master/bots/ZorraMutante.py'
)
my_first_text = tweetbot.generate_text(
10, seedword=[u'código', u'lÃmite', u'hay'])
print(u'\ntweetbot says: "%s"' % (my_first_text))
# ALL YOUR SECRET STUFF!
# Consumer Key (API Key)
cons_key = '[ copy this value from Consumer Settings ]'
# Consumer Secret (API Secret)
cons_secret = '[ copy this value from Consumer Settings ]'
# Access Tokenf
import collections
import os
import re
import time
from collections import defaultdict
from heapq import nlargest
from string import punctuation
import nltk
from markovbot import MarkovBot
from nltk import word_tokenize
from nltk.corpus import stopwords
from nltk.tokenize import sent_tokenize, word_tokenize
bot = MarkovBot()
bot2 = MarkovBot()
bot3 = MarkovBot()
bot4 = MarkovBot()
'''
clean data for shakespeare
data = open('shakeComplete.txt', 'r').read()
fOne = ''.join(filter(lambda x: not x.isdigit(), data))
fTwo = (re.sub('[0-9\W]+', " ", fOne))
fThree = (fTwo.replace("SCENE", " "))
fFour = (fThree.replace("ACT", " "))
finalDataShake = fFour
'''
'''freud'''
'''
i need to clean this up a lot and add organon
import os
from markovbot import MarkovBot
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
headline = os.path.join(dirname, 'hosking_headlines.txt')
comment = os.path.join(dirname, 'hosking_comments.txt')
gen = input('Generate headline? Y/N\n')
while True:
if gen == 'Y' or gen == 'y':
tweetbot.read(headline)
gen_head = tweetbot.generate_text(10)
print(u'\nMike Hosking: %s' % (gen_head))
tweetbot.clear_data()
tweetbot.read(comment)
gen_comm = tweetbot.generate_text(30)
print('COMMENT: %s' % (gen_comm))
gen = input(u'\nGenerate headline? Y/N\n')
elif gen == 'N' or gen == 'n':
exit()
elif gen != 'Y' and gen != 'N' and gen != 'y' and gen != 'n':
print(u'\nInput was not Y or N')
gen = input(u'\nGenerate headline? Y/N\n')
import os
from markovbot import MarkovBot
import json
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath(__file__))
book = os.path.join(dirname, 'The Dhammapada.txt')
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25, seedword=['way', 'He'])
print("tweetbot says:")
print(my_first_text)
json_data = {}
with open("config.json") as json_file:
json_data = json.loads(json_file.read())
print(json_data)
consumer_key = json_data['consumer_key']
consumer_secret = json_data['consumer_secret']
access_token = json_data['access_token']
access_token_secret = json_data['access_token_secret']
tweetbot.twitter_login(consumer_key, consumer_secret, access_token,
access_token_secret)
targetstring = 'Buddhism'
keywords = ['man', 'always', 'truth', 'ignorant', 'lives']
prefix = None
suffix = '#BuddhismSays'
# import config # contains the API keys and access tokens
import twitter
import os
import time
from markovbot import MarkovBot
# Initialise the MarkovBot instance
tweetbot = MarkovBot()
# Get the seinfeld transcripts and read
dirname = os.path.dirname(os.path.abspath(__file__))
textFile = os.path.join(dirname, 'seinfelf.txt')
tweetbot.read(textFile)
# Text Generations
# Log in to Twitter
consumer_key = os.environ.get('cons_key')
consumer_key_secret = os.environ.get('cons_secret')
access_token = os.environ.get('access_token')
access_token_secret = os.environ.get('access_token_secret')
tweetbot.twitter_login(consumer_key, consumer_key_secret, access_token,
access_token_secret)
# Start periodically tweeting
while True:
minutesToWait = 120
secondsToWait = 60 * minutesToWait
tweetbot.twitter_tweeting_start(days=0,
hours=0,
import os
from markovbot import MarkovBot
#import twitter
#initalise a MarkovBot instance
tweetbot = MarkovBot()
#get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
#construct the path to the book
book = os.path.join(dirname, 'sherlock.txt')
#make your bot read the book!
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25, seedword=['Irene', 'watson','Mycroft'])
print("tweetbot says:")
print(my_first_text)
# ALL YOUR SECRET STUFF!
# Consumer Key (API Key)
cons_key = 'AqYyIzu5jXXYhubZI83WtfmnV'
# Consumer Secret (API Secret)
cons_secret = 'QyqofLZtVJSjgS4L7EltzaxPJrcz23vgyN8zMNZ4dm88HdM1c6'
# Access Token
access_token = '751058612051648514-FGw6PEjNmkIdbWqrC3MfhVYEe8KJyCF'
# Access Token Secret
access_token_secret = 'PFKpoM7ra8rziOc0gs9ci4pT2TGRvn0fRXw5gw8PzYFnp'
#!/usr/bin/env python
import os
import time
import os, ssl
print os.environ['cons_key']
print os.environ['cons_secret']
print os.environ['access_token']
print os.environ['access_token_secret']
from markovbot import MarkovBot
#Initialize a MarkovBot instance
tweetbot = MarkovBot()
dirname = os.path.dirname(os.path.abspath("tmg copy.text"))
# Construct the path to the book
book = os.path.join(dirname, 'tmg copy.text')
# Make your bot read the book!
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25,
seedword=[
'you',
'I am',
'going to',
'my',
'love',
])
print(my_first_text)
tweetbot.twitter_login(os.environ['cons_key'], os.environ['cons_secret'],
os.environ['access_token'],
os.environ['access_token_secret'])
# Start periodically tweeting
SLEEPING = int(os.environ["SLEEPING"])
# use tweetpy instead
try:
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_KEY, ACCESS_SECRET)
api = tweepy.API(auth)
logger.debug("Successfull auth")
except tweepy.TweepError as e:
logger.debug("Failed to auth " + e.response.text)
# # # # #
# INITIALISE
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
try:
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, TWEETS)
# Make your bot read the book!
tweetbot.read(book)
except:
logging.debug("Failed to load book " + TWEETS)
# # # # #
# TEXT GENERATION
# Generate text by using the generate_text method:
# This thing started with this tweet, if you're looking for someone to blame:
# https://twitter.com/jlsinc/status/798142993651867648
import time
from markovbot import MarkovBot
from secret import cons_key, cons_secret, access_token, access_token_secret
# Initialise a MarkovBot instance.
print(u"\nInitialising a new MarkovBot.")
tweetbot = MarkovBot()
# Generate a dict for all possible responses.
respdict = {u'Kendrick Lamar':( \
u'HEDLEY! https://www.youtube.com/watch?v=8vjEnkQdaHM',
u'HEDLEY! http://jpg.party/http://i.imgur.com/lzLPfT3.gif',
u'HEDLEY! http://jpg.party/http://i.imgur.com/nAV7ueU.gif',
u'HEDLEY! http://jpg.party/http://i.imgur.com/3yt4gex.jpg',
u'HEDLEY! http://jpg.party/http://i.imgur.com/6COCqT1.jpg',
u'HEDLEY! http://jpg.party/http://i.imgur.com/C9pcsJI.jpg'
)}
# Add the respdict to the bot's database.
tweetbot.set_simple_responses(respdict)
# Log in to Twitter.
print(u"\nBot is logging in to Twitter.")
tweetbot.twitter_login(cons_key, cons_secret, \
access_token, access_token_secret)
# Start auto-responding to tweets.
import os
import time
from markovbot import MarkovBot
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, 'Freud_Dream_Psychology.txt')
# Make your bot read the book!
tweetbot.read(book)
my_first_text = tweetbot.generate_text()
print("tweetbot says:")
print(my_first_text)
# ALL YOUR SECRET STUFF!
# Consumer Key (API Key)
cons_key = ""
# Consumer Secret (API Secret)
cons_secret = ""
# Access Token
access_token = ""
# Access Token Secret
access_token_secret = ""
# Log in to Twitter
tweetbot.twitter_login(cons_key, cons_secret, access_token,
access_token_secret)
import os
from markovbot import MarkovBot
with open("tokens.txt", "r") as f:
f_read = f.readline()
access_token = "" # f_read.split(" ")[2][0:-1]
access_token_secret = ""
cons_key = ""
cons_secret = ""
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, 'ElonMuskTxt.txt')
# Make your bot read the book!
tweetbot.read(book)
my_first_text = tweetbot.generate_text(25, seedword=['space', 'Tesla'])
print("tweetbot says:")
print(my_first_text)
tweetbot.twitter_login(cons_key, cons_secret, access_token,
access_token_secret)
from time import sleep
while True:
tweetbot.twitter_tweeting_start(days=0,
hours=0,
import os
from markovbot import MarkovBot
# # # # #
# INITIALISE
# Initialise a MarkovBot instance
tweetbot = MarkovBot()
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, u'Freud_Dream_Psychology.txt')
# Make your bot read the book!
tweetbot.read(book)
# # # # #
# TEXT GENERATION
# Generate text by using the generate_text method:
# The first argument is the length of your text, in number of words
# The 'seedword' argument allows you to feed the bot some words that it
# should attempt to use to start its text. It's nothing fancy: the bot will
# simply try the first, and move on to the next if he can't find something
# that works.
my_first_text = tweetbot.generate_text(25,
seedword=[u'dream', u'psychoanalysis'])
# Print your text to the console
print(u'\ntweetbot says: "%s"' % (my_first_text))
from markovbot import MarkovBot
###
# Argumento de entrada: nombre del fichero .json con las credenciales de twitter
try:
text_filename = sys.argv[1]
except IndexError:
print('Error: falta indicar el nombre del fichero .json con las credenciales de twitter')
sys.exit(1)
# # # # #
# INITIALISE
# Initialise a MarkovBot instance
tweetbot = MarkovBot(chainlength=4)
# Get the current directory's path
dirname = os.path.dirname(os.path.abspath(__file__))
# Construct the path to the book
book = os.path.join(dirname, u'texto_ejemplo.txt')
# Make your bot read the book!
tweetbot.read(book)
# # #
# TEXT GENERATION
# Generate text by using the generate_text method:
# The first argument is the length of your text, in number of words
# The 'seedword' argument allows you to feed the bot some words that it
# should attempt to use to start its text. It's nothing fancy: the bot will
