I started working on a beer recommendation engine1, but quickly realized that I needed to build a robust API for extracting data from beer websites, and that such a tool didn't exist yet. I settled on using the RateBeer database because of its community ethics and open attitude toward using their data. As my needs grew, I eventually turned my attention towards an exhaustive API for the website in Python. The project is now downloaded several hundred times every week and has two full-time developers, along with several community contributions.
You can check it out on GitHub.
What's Their Face?
A goofy idea turned into a weekend hack. My friends and I were arguing about what actors had appeared in certain movies — we could remember the movies but not the actor's name. I put together What's Their Face? to solve this problem — enter two movies and it'll tell you the actors that are common to both. The project was an opportunity for me to learn how to do web programming with Python. I chose to use Flask for its simplicity; because it's such a simple application, Flask allowed me to easily collapse the view and controller logic into a single file and keep everything under 200 lines of code.
My goal was to make looking up movies as fast and easy as possible. Instead of trying to label boxes with names like "movie one," I opted for a sentence-based structure, which made it quick and easy to figure out what the app was doing and where movie names should go. I figured people would likely be using it in their homes2, and therefore would be watching a rented movie. With this in mind, the app automatically fills in that day's most-rented DVD in the first spot. Entering a new movie will auto-fill it into the first box, and will keep it there until the movie is over. Finally, because this is based on the sense of "I know their face but not their name," it was essential that the results show the faces of the actors for quick recognition.
You can play with What's Their Face here.
libbiopacndt_py, despite having an extremely catchy name, is
a fairly technical piece of software. It's a Python API that allows for
real-time processing of physiological data provided by the
BioPac system. It can be used for any
application, but right now it's tied into Opaline, a tool designed to
process both real-time and post-hoc physiological data to determine how
stressed out someone is3 for usage in adaptive computing. This
research has showed some promise already, and was presented at I/ITSEC 2014.