Created
September 25, 2013 05:05
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How I do @buster_ebooks.
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#!/usr/bin/ruby | |
# Make sure you have these gems installed | |
require 'rubygems' | |
require 'thread' | |
require 'csv' | |
require 'twitter' | |
require 'marky_markov' | |
# Create a new Twitter account that you'd like to have your auto-tweets posted to | |
# Go to dev.twitter.com, create a new application with Read+Write permissions | |
# Create an access token + secret for the account and copy that and the consumer key and secrets here. | |
CONSUMER_KEY = '' | |
CONSUMER_SECRET = '' | |
ACCESS_TOKEN = '' | |
ACCESS_TOKEN_SECRET = '' | |
PATH_TO_TWEETS_CSV = 'tweets.csv' | |
PATH_TO_TWEETS_CLEAN = 'markov_dict.txt' | |
### ----------------------------------------------------------------------------------------------------- | |
# Go to Twitter.com -> Settings -> Download Archive. | |
# This tweets.csv file is in the top directory. Put it in the same directory as this script. | |
csv_text = CSV.parse(File.read(PATH_TO_TWEETS_CSV)) | |
# Create a new clean file of text that acts as the seed for your Markov chains | |
File.open(PATH_TO_TWEETS_CLEAN, 'w') do |file| | |
csv_text.reverse.each do |row| | |
# Strip links and new lines | |
tweet_text = row[5].gsub(/(?:f|ht)tps?:\/[^\s]+/, '').gsub(/\n/,' ') | |
# Save the text | |
file.write("#{tweet_text}\n") | |
end | |
end | |
# Run when you want to generate a new Markov tweet | |
markov = MarkyMarkov::Dictionary.new('dictionary') # Saves/opens dictionary.mmd | |
markov.parse_file PATH_TO_TWEETS_CLEAN | |
tweet_text = markov.generate_n_sentences(2).split(/\#\</).first.chomp.chop | |
markov.save_dictionary! | |
# Connect to your Twitter account | |
Twitter.configure do |config| | |
config.consumer_key = CONSUMER_KEY | |
config.consumer_secret = CONSUMER_SECRET | |
end | |
twitter_client = Twitter::Client.new(:oauth_token => ACCESS_TOKEN, | |
:oauth_token_secret => ACCESS_TOKEN_SECRET) | |
p "#{Time.now}: #{tweet_text}" | |
twitter_client.update(tweet_text) |
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buster, parkr - what does dictionary.mmd do? After three iterations, mine is 66 megabytes (I have a large corpus), and I'm trying to figure out what to do to keep it manageable.
e: looks like there is an option in markymarkov to replace permanent dictionary w/ a temp one: https://github.com/zolrath/marky_markov