A Heroku worker script to post to an _ebooks version of your Twitter account
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Latest commit 0ca5fa6 Jan 19, 2017 @tommeagher committed on GitHub Merge pull request #21 from sparky005/devel2
Remove attribution (Fix for issue #7)



This is a basic Python port of @harrisj's iron_ebooks Ruby script. Using Heroku's scheduler, you can post to an _ebooks Twitter account based on the corpus of an existing Twitter at pseudorandom intervals. Currently, it is the magic behind @adriennelaf_ebx and @stevebuttry_ebx.


  1. Clone this repo
  2. Create a Twitter account that you will post to.
  3. Sign into https://dev.twitter.com/apps with the same login and create an application. Make sure that your application has read and write permissions to make POST requests.
  4. Make a copy of the local_settings_example.py file and name it local_settings.py
  5. Take the consumer key (and secret) and access token (and secret) from your Twiter application and paste them into the appropriate spots in local_settings.py.
  6. In local_settings.py, be sure to add the handle of the Twitter user you want your _ebooks account to be based on. To make your tweets go live, change the DEBUG variable to False.
  7. Create an account at Heroku, if you don't already have one. Install the Heroku toolbelt and set your Heroku login on the command line.
  8. Type the command heroku create to generate the _ebooks Python app on the platform that you can schedule.
  9. The only Python requirement for this script is python-twitter, the pip install of which is handled by Heroku automatically.
  10. git commit -am 'updated the local_settings.py'
  11. git push heroku master
  12. Test your upload by typing heroku run worker. You should either get a response that says "3, no, sorry, not this time" or a message with the body of your post. If you get the latter, check your _ebooks Twitter account to see if it worked.
  13. Now it's time to configure the scheduler. heroku addons:create scheduler:standard
  14. Once that runs, type heroku addons:open scheduler. This will open up a browser window where you can adjust the time interval for the script to run. The scheduled command should be python ebooks.py. I recommend setting it at one hour.
  15. Sit back and enjoy the fruits of your labor.


There are several parameters that control the behavior of the bot. You can adjust them by setting them in your local_settings.py file.

ODDS = 8

The bot does not run on every invocation. It runs in a pseudorandom fashion. At the beginning of each time the script fires, guess = random.choice(range(ODDS)). If guess == 0, then it proceeds. If your ODDS = 8, it should run one out of every 8 times, more or less. You can override it to make it more or less frequent. To make it run every time, you can set it to 0.

By default, the bot ignores any tweets with URLs in them because those might just be headlines for articles and not text you've written.


The ORDER variable represents the Markov index, which is a measure of associativity in the generated Markov chains. 2 is generally more incoherent and 3 or 4 is more lucid. I tend to stick with 2.


If you want to test the script or to debug the tweet generation, you can skip the random number generation and not publish the resulting tweets to Twitter.

First, adjust the DEBUG variable in local_settings.py.

DEBUG = True 

After that, commit the change and git push heroku master. Then run the command heroku run worker on the command line and watch what happens.

If you want to avoid hitting the Twitter API and instead want to use a static text file, you can do that. First, create a text file containing a Python list of quote-wrapped tweets. Then set the STATIC_TEST variable to True. Finally, specify the name of text file using the TEST_SOURCE variable in local_settings.py


As I said, this is based almost entirely on @harrisj's iron_ebooks. He created it in Ruby, and I wanted to port it to Python. All the credit goes to him. As a result, all of the blame for clunky implementation in Python fall on me. If you see ways to improve the code, please fork it and send a pull request, or file an issue for me and I'll address it.