Track The News

trackthenews is the script that powers @FOIAfeed, a Twitter bot that monitors news outlets for reporting that incorporates public records laws like the Freedom of Information Act (FOIA), and tweets links to and excerpts from matching articles. The underlying software can track any collection of RSS feeds for any keywords.

If you want to run your own instance of trackthenews, you can download and install the package, and run its built-in configuration process. It can be installed with pip:

pip3 install trackthenews

or by cloning the GitHub repository and running setup.py:

python3 setup.py install

Once it is installed, you can create a configuration by running the following command in the appropriate directory:

trackthenews --config

By default, the script will place all configuration files in a new ttnconfig folder in your current working directory, but you can also designate a directory for it to use.

python3 trackthenews --config ~/foo/bar/path

That configuration process will create the necessary files and walk you through setting up a Twitter bot for matching stories. After it is configured, you'll need to use a text editor to add the matchwords and RSS feeds to their respective files.

Once you've got everything set up, you can run the program without the --config flag to check for matching articles. If you designated a custom installation directory, or if you're running it from another directory (or a cron job, for example) you will need to designate the directory in which the configuration files are installed.

Settings, such as the background color for new posts, the font, and the user-agent, are all located in config.yaml, in the designated configuration directory.

How it works

Most of the script is dedicated to the Article class.

• Articles are created based on inputs. Currently those inputs are RSS feeds, which are stored in rssfeeds.json, but in future versions other inputs will include direct URLs, news APIs, Twitter feeds, or scraped pages.
• A series of Article methods then scrape and isolate the contents of each article (currently that cleanup is done with a Python port of Readability, but future versions may incorporate some per-site parsing), check whether it's suitable for posting, and then prepare images for tweeting.
• Finally, the Article tweets itself.

All articles are recorded in a sqlite database.

Advanced feature: blocklist

In some cases, you may wish to suppress articles from being posted, even though they would otherwise match. You can do so by writing a new function, check, and placing it in a file named blocklist.py in the configuration directory. check takes an Article (and so has access to its outlet, title, and url) and should return true for any article that should be skipped.