Fast feature development is critical to a company’s success. We all strive to increase developer productivity by decreasing the time to test, deploy, and monitor changes. To enable developers to push code safely, we run more than 20 million tests every day using our in-house distributed system called Seagull. 'Seagull' by Fil.Al is licensed under CC BY 2.0 What is Seagull? Seagull is a fault tolerant and resilient distributed system which we use to parallelize our test suite execution. Seagull is built using the following: Apache Mesos (manages the resources of our Seagull cluster) AWS EC2 (provides the instances that...

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Continuous Integration (CI) is a powerful tool for the Android team at Yelp. It gives us a platform to ensure quality on all eight of our Android apps, allowing us to emphasize testing and ensure our newest features aren’t breaking our oldest masterpieces. For example, we don’t want Yelfies to crash the app while you’re writing your next great review. To achieve this, we have a dedicated cluster of AWS machines running our CI server. These machines run JUnit tests, static analysis, build APKs, merge code, and send us notifications. They also work with Firebase Test Lab to start up...

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Jen W. is a backend engineer at Yelp in San Francisco and, when not running after her toddler, loves nothing more than to knit while watching superhero TV. Susanne L. is a database engineer at Yelp in San Francisco and loves to [b/h]ike the hilly city and its surroundings. Wei W. is an iOS engineer at Yelp in Hamburg and an avid (trashy) TV connoisseur in her free time. This past year at Grace Hopper, Jen, Susanne, and Wei teamed up to present “Crucial Conversations in Your Career: Increasing Your Impact,” a workshop featuring interactive skits and group discussion. This...

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We’re excited to be open sourcing a tool we built during a hackathon, that helps Yelp employees meet coworkers within the company: Yelp Beans. A screenshot of the Yelp Beans app It started a little over a year ago, when I began going to orchestrated one-on-one coffee meetups in the Bay Area sponsored by a local startup. It was a program where you could meet designers, engineers, and product managers in your area for a 30 minute coffee meeting. It helped me understanding my career direction and was an opportunity to ask questions of people at varying stages in their...

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Since our launch of the Yelp Fusion API, we’ve been working hard over the past few months, fixing bugs people have reported on GitHub and adding missing features. We’ve also added a few things to improve the overall experience: The search endpoint got a small update on filtering by attributes. We’ve added support for filtering businesses based on whether or not they have online waitlisting, participate in Yelp Cash Back, or offer Yelp Deals. We added a public changelog to help the community keep track of changes to the API. The changelog will contain updates such as bug fixes, feature...

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Encouraging positivity has been a central pillar to Yelp’s culture from the beginning. If a teammate rolls out a huge feature, helps you out in a bind, or just makes a funny joke, we believe you should be able to show them a small token of appreciation. That’s why we developed an internal tool called Yelp Love, a web application for sending notes of appreciation (aka love) to your coworkers within Yelp. Yelp Love started as a Hackathon effort back in 2013. Over the course of two hackathons, we rolled out Yelp Love to the entire company. Since its deployment,...

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In 2014, Yelp launched pre-commit, a framework for managing pre-commit hooks. Since then, the community has contributed many different hooks to help with development in a wide variety of languages, including Python, Ruby, Go, Node.js, and Clojure. You can see a list of many of these here. Pre-commit has been invaluable in increasing the productivity of Yelp’s code base and code-reviews by making style issues a thing of the past and allowing us to easily check for broken and deprecated code usage with a variety of code linters. While pre-commit supports a number of popular languages, the goal of pre-commit...

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Yelp Dataset Challenge Round 7 Winners The seventh round of the Yelp Dataset Challenge ran throughout the first half of 2016 and, as usual, we were impressed with the projects and ideas that came out of the challenge. Today, we are proud to announce the grand prize winner of the $5,000 award: “Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams” by Abhinav Maurya, Kenton Murray, Yandong Liu, Chris Dyer, William W. Cohen, and Daniel B. Neill (from Carnegie Mellon University, University of Notre Dame in Indiana). The authors created a model to detect and characterize emerging topics in...

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