The Libraries of

In this post I’ll describe the libraries used by to turn requests into web pages and JSON to send back to users. In some future posts I’ll describe how it’s actually put on the internet. If you’re curious about the code you can see it on GitHub.

Back End

The back end consists of GET and POST REST endpoints for ipythonblocks to talk to and handlers for the site itself: main and about pages, a random grid redirect, and the individual grid views. In all there are about six handlers for all of

Framework is such a simple site that any lightweight framework could probably handle it. I went with Tornado mainly because I’ve used it before and I like the way applications are designed using Tornado. That it includes a template engine and a high performance web server are also pluses. If I’d not used Tornado, Flask and Jinja2 would have been my second choice.


Choosing a database was something of an agonizing decision. You can choose from SQL, NoSQL, and key-value stores; and within each of those you have many more choices. I like the simplicity of working with schema-less databases like MongoDB, and I was very intrigued by RethinkDB, but in the interest of having a simple setup that allowed me to focus on developing app logic I ended up using sqlite. I use the dataset library to take care of some of the SQL overhead (like table creation) so that I can combine the simplicity of sqlite with a more NoSQL-like interface.

At some point I may want to move to another database, especially one running on a dedicated machine so that swapping the application server can be done without worrying about the database. When I get to that point I’ll probably take another look at RethinkDB and see if it’s ready for my application.

To avoid database lookups of recently visited pages I’m using memcached and talking to it from Python via the pylibmc library.


Python’s built in logging can certainly get the job done, but its interface has some rough edges I don’t like. Configuration can be painful for sophisticated cases and any kind of structured logging requires custom formatting. I think Twiggy is a much more “Pythonic” approach to logging with simpler configuration and built in structured logging. was my first time using Twiggy and I’d use it again. (Though it is unfortunately not Python 3 compatible at this time.)


Requests to the POST endpoint are validated using jsonschema. This provides protection for the app against incorrectly configured requests and can be used as a kind of documentation on what requests should look like.

I use the hashids library to turn the integer SQL IDs of grid entries into short strings, as in This is a URL form people are familiar with and it allows the implementation of “secret” grid posts that have public URLs but are difficult to find unless someone gives you the URL.

Users of ipythonblocks can include code with their posted grids and I use Pygments to highlight the syntax of the code and format it for HTML. Pygments is decent enough to escape HTML included in the posted code so I don’t have to worry about that breaking the page rendering. The color scheme used is Base16 Chalk Light via

Finally, I use ipythonblocks itself to turn grid data into rendered HTML via the same methods used by the IPython Notebook.

Front End

The back end renders and delivers static HTML to browsers (or JSON to ipythonblocks) so there isn’t much fancy going on in the front end. I use CSS media queries to adjust the site margins for small screens, and on the front page I use Pure CSS grids to make a responsive three-column layout that collapses to a single column on small screens. uses the Source family of fonts from Adobe delivered by Google Fonts.

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