Here at Yelp, we’re passionate about building things; it’s at the core of our engineering philosophy. In fact, we enjoy it so much that many of us keep on building after we finish work. I recently found some spare time to work on an interesting project with the Microsoft Kinect. I think it’s a cool start and I’ve open sourced the code so that others can build something even cooler. Easy Skeletal Tracking If you’re reading this blog, you’re likely familiar with the Microsoft Kinect. It combines an RGB camera, an infrared laser projector, and an infrared camera to determine...

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Over the next couple of weeks, Yelp is going to be hosting two open-to-the-public events for members of the software development community: PyPy Just-in-Time Interpreters March 3rd, 6pm Armin Rigo of the PyPy project will be giving a presentation on achievements made by PyPy, the “fastest, most compatible, and most stable ‘alternative’ Python interpreter.” Special attention will be given to advancements in the area of dynamic (JIT) interpreters. You can find more information on SFPython’s Meetup page. If you plan to come, make sure to RSVP at least a day in advance so that security will allow you into the...

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Alan on our iPhone team recently encountered a tricky bug that had to do with the ObjectiveC compiler and differences in architecture between ARM and x86. The Problem On the device (but not the sim), the following code would crash on views that implemented drawInRect methods that returned a CGPoint (instead of having a void return type like other drawInRect methods). for (id view in _subviews) { [view drawInRect:[view frame]]; } To make matters weirder, the pointer ‘view’ before stepping into drawInRect was not the same as the pointer ‘self’ after stepping into drawInRect! However, by typecasting view to the...

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In addition to having written over 15 million reviews, Yelpers also contribute hundreds of thousands of business listing corrections each year.  Not all of these corrections are accurate, though, and there are quite a few jokers out there (e.g. suggesting the aquariums category for popular seafood restaurants… very funny!).  Yelp is serious about the correctness of business listings, so in order to efficiently validate each and every change, we’ve turned to Amazon’s Mechanical Turk (AMT) as well as other automated methods.  We recently published a research paper [1] at the NIPS 2010 Workshop on Computational Social Science and the Wisdom...

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Click your heels together and say the magic words three times: “there’s no place like Yelp…there’s no place like Yelp…there’s no place like Yelp.” Then perhaps you’ll be whisked away to the land of Yelp Engineering where our third Hackathon just wrapped up. Like the previous Hackathon and the one before that, this 48-hour period where engineers were set loose to work on “anything you wouldn’t normally be able to work on that might be useful, funny, or cool” (and ostensibly, related at least indirectly to Yelp) resulted in some awesome creations. One of the biggest milestones for our third...

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Ever wonder how we power the People Who Viewed this Also Viewed… feature? How does Yelp know that people viewing Coit Tower might also be interested in the Filbert Steps and the Parrots of Telegraph Hill? It’s pretty much what you’d expect: we look at a few months of access logs, find sessions where people viewed more than one business, and collect statistics about pairs of businesses that were viewed in the same session. Now here’s the kicker: we generate on the order of 100GB of log data every day. How do we deal with terabytes of data in a...

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The Yelp code base has been under development for over six years. We push multiple times a day. We don’t have a dedicated QA team. Yelpers get very angry when their detailed account of how that waitress was totally into them doesn’t get saved. Effective automated testing is the only way we can stay sane. One of the great benefits of Python is its “batteries included” philosophy which gives us access to lots of great libraries including the built-in unittest module. However, as our code base grows in size and complexity, so do our testing needs. There are plenty of...

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As Yelp has grown over the years, we’ve amassed huge collections of data - the collective output of the actions of tens of millions of users. Analyzing this data helps us improve the user experience across the site, from ranking businesses and extracting “review highlights” to fighting spam and keeping the site secure. These tasks involve long-running batch processes that analyze large logs and database tables, with workflows sometimes composed of five or more dependent processes. Managing these workflows with traditional scheduling tools - most notably the cron family - eventually caused us to breach the “complexity comfort zone” that...

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