Enzyme’s Next Phase

In 2016, Airbnb released Enzyme, our React component testing library. In the following 4 years, the project has amassed more than 18,000 stars, and over 340 contributors. GitHub also tells us that Enzyme is used by over 230,000 repos and 24,000 packages, and npm reports that it is downloaded around 2 million times each week. The community’s response to this project has been astounding, to say the least. Much of Enzyme’s success is the result of the vibrant React community opening and commenting on actionable issues and submitting quality pull requests. All of your contributions have directly contributed to this project’s success—we could not have done this without you. This community is largely the reason why we are excited to announce that we will transfer ownership of Enzyme to the new enzymejs GitHub organization. We believe that this new home will help the project continue to support the community’s needs well into the future. The success here has moved beyond Airbnb as a single org and it’s time for our baby to be launched as a successful adult. Internally at Airbnb, Enzyme has been a catalyst for better frontend test coverage and is currently used in over 17,000 tests. While other options like React Testing Library have gained traction within Airbnb, we will still be using and contributing to Enzyme for the foreseeable future. If you want to help Enzyme grow, please check out the open issues and pull requests — the “help wanted” tag is a great starting point.

React Native at Airbnb: The Technology

This is the second in a series of blog posts in which we outline our experience with React Native and what is next for mobile at Airbnb. React Native itself is a relatively new and fast-moving platform in the cross-section of Android, iOS, web, and cross-platform frameworks. After two years…

Better Android Testing at Airbnb

In previous articles we’ve looked at Airbnb’s product architecture, the mocking system we built for it, and how this ecosystem…

Amenity Detection and Beyond — New Frontiers of Computer Vision at Airbnb

Authors: Shijing Yao, Dapeng Li, Shawn Chen What amenities are there in this image? Can an algorithm detect them all? How can we train the algorithm effectively? If you are interested in the answers, please read on! Introduction In 2018, we published a blog post titled Categorizing Listing Photos at Airbnb…

How Airbnb Achieved Metric Consistency at Scale

Part-I: Introducing Minerva — Airbnb’s Metric Platform By: Amit Pahwa, Cristian Figueroa, Donghan Zhang, Haim Grosman, John Bodley, Jonathan Parks, Maggie Zhu, Philip Weiss, Robert Chang, Shao Xie, Sylvia Tomiyama, Xiaohui Sun Introduction At Airbnb, we lean on data to inform our critical decisions. We validate product ideas through randomized controlled experiments, and we track our business performance…

Scaling Spark Streaming for Logging Event Ingestion

by Hao Wang and Liyin Tang Walking over a stream during an Airbnb Experience in Kuala Lumpur. Searching, viewing, and booking… Logging Event Ingestion at Airbnb Logging events are emitted from clients (such as mobile apps and web browser) and online services with key information and context about the actions or operations. Each event carries a specific piece of information. For example, when a guest searches for a beach house…

Sunsetting React Native

This is the fourth in a series of blog posts in which we outline our experience with React Native and what is next for mobile at Airbnb.Where are we today? Although many teams relied on React Native and had planned on using it for the foreseeable future, we were ultimately…

Zooming Towards Human Connection

By: Fatemeh Alavizadeh, Mojtaba Mehrara Meet the dogs of Chernobyl on this Online Experience hosted by Lucas Introduction Creating human connection is the core of Airbnb’s mission. We launched Airbnb Experiences to encourage travelers to connect with locals and with each other through one-of-a-kind experiences that highlight the uniqueness of their destinations. We’ve since grown it to a community of hosts leading more…

Himeji: A Scalable Centralized System for Authorization at Airbnb

The Problem Over the last couple of years, Airbnb engineering moved from a monolithic Ruby on Rails architecture to a service oriented architecture. In our Rails architecture, we had an API per resource to access the underlying data. These APIs had authorization…

Building Services at Airbnb, Part 4

By Junjie Guan, Rui Dai and Xing An Intro In Part 1, Part 2, and Part 3 of our Building Services at Airbnb series, we shared how…

WIDeText: A Multimodal Deep Learning Framework

By Wayne Zhang, Mia Zhao, Yuanpei Cao Deep learning (DL) is helping us at Airbnb serve our stakeholders better…

The Airbnb Talent Directory

The past few months have been hard for all of us, but it has been inspiring to see everyone, especially the Airbnb community, support each other during an unprecedented time. Our CEO, Brian Chesky, recently announced the departure of nearly 1,900 employees. Among these employees are incredibly talented Engineers and Data Scientists who have contributed to Airbnb in uncountable ways. To support our teammates departing Airbnb, we launched the Alumni Talent Directory, an opt-in directory which lists valued employees and contingent workers who have recently departed Airbnb. If you’re currently hiring or looking for incredible talent, the Talent Directory is full of amazing Engineers and Data Scientists, among others. We hope we can connect these individuals with new opportunities. It’s been an honor to work with such a talented team committed to our mission of belonging, and we’re confident any company would be lucky to have them. We’d also like to thank the cross-functional team that created the site in an extremely short period of time. We are all grateful for their hard work: Chris Arrington, Gina Groom, Noor Malik, Derek Southard, Parag Hardas, Robin Foyle, Mike Fowler, Christian Williams, Megan Gebhart, Alex Cheng, Steve Rafferty, Sonia Yang, Andy Tran, Angela Wu, Linsey Jackson, James Deslonde, Kelly Coldwell, as well as Joe Gebbia for inspiring the idea. Airbnb Alumni Talent Directory

How Airbnb is Boosting Data Literacy With ‘Data U Intensive’ Training

Since we introduced Airbnb’s Data University, the program has continued to thrive and evolve. One improvement has been the addition of team-specific trainings with content tailored to the work of that team. In this post, we describe the impact of this addition and the lessons learned in its implementation. What is Data University? …

Supporting Dynamic Type at Airbnb

By Noah Martin & Hugo Ahlberg Background Since iOS 7, Dynamic Type has allowed users to choose a prefered font size for their phone. At Airbnb, we try to build an app that our entire community can use — since Dynamic Type is a critical accessibility feature, we knew supporting it…

Supercharging Apache Superset

By: Erik Ritter, Grace Guo, Jesse Yang, John Bodley, and Zuzana Vejrazkova Introduction At Airbnb, many employees rely on data every day to do their jobs. While several different tools are used for analysis, at the core of Airbnb’s self-serve business intelligence (BI) solution is Apache Superset™ (“Superset”). Superset is…

How Druid enables analytics at Airbnb

By Pala Muthiah and Jinyang Li Wikipedia: A druid was a member of the high-ranking professional class in ancient Celtic cultures… Airbnb serves millions of guests and hosts in our community. Every second, their activities on Airbnb.com, such as searching, booking, and messaging, generate a huge amount of data we anonymize and use to improve the community’s experience on our platform. The Data Platform Team…

Airbnb Engineering and Data Science at KDD 2018

The 2018 KDD conference is right around the corner — and we are looking forward to seeing you there. (That’s Knowledge Discovery and Data Mining, if you’re not familiar with it!) We are excited to have three Airbnb papers accepted for oral presentation at the Applied Data Science Track and…

Avoiding Double Payments in a Distributed Payments System

Authors: Jon Chew and Ninad Khisti One of the conference rooms in our San Francisco office Background Airbnb has been migrating its infrastructure to a Service Oriented Architecture (“SOA”). SOA offers many upsides, such as enabling developer specialization and the ability to iterate faster. However, it also poses challenges for billing and payments applications because it makes it more difficult to…

Beyond “How May I Help you? “

By Xin (Cindy) Chen, Mengting Wan The Airbnb office in Dublin offers plenty of workspace beyond your desk. At Airbnb, we serve a global community of hosts and guests. An essential part of Airbnb’s business is to provide high quality customer service at scale. Live chat is one of our customer support channels, where customers can chat with our customer service agents…

Server Rendering, Code Splitting, and Lazy Loading with React Router v4

Challenge accepted. Nicole, one of our hosts, taking some guests on a sunrise walk and picnic above… Some Background on Server Rendering at Airbnb Historically, Airbnb has been a Rails app. A few years back that started to change, we began using Rails simply as a data layer, and all render logic started migrating into JavaScript in…

Empowering Data Science with Engineering Education

Authors: Michelle Du, Yu Guo, Jeff Feng Our brand new kitchen on the 2nd floor of 888 Brannan St. Since launching Data University (Data U) at Airbnb two years ago, our data education program has made significant progress towards our overarching vision of empowering every employee to make data-informed decisions. To date, over 400 courses have been taught to thousands of course…

ts-migrate: A Tool for Migrating to TypeScript at Scale

TypeScript is the official language of frontend web development at Airbnb. Yet, the process of adopting TypeScript and migrating a mature codebase containing thousands of JavaScript files didn’t happen in one day. TypeScript adoption went through the process of an initial proposal, adoption by multiple teams, a beta phase and…

Introducing AloeStackView for iOS

Some of the ~200 screens in the Airbnb iOS app built using AloeStackView. At Airbnb, we’re always looking for ways to improve the efficiency of building products. Over the past few years, our mobile development efforts have increased at a dramatic rate. In the past year alone, we’ve added more than 260 screens to our iOS app. At the same time, more and…

Introducing Showkase: A Library to Organize, Discover, and Visualize Your Jetpack Compose Elements

Over the last few years, Android™ development has gone through significant changes in how apps are structured, the language used for development, the tooling & libraries that speed up our development, and the improvements in testing apps. What didn’t change in all these years is the Android UI toolkit. This…

Scaling a Mature Data Pipeline — Managing Overhead

Author: Zachary Ennenga The view from the third floor at Airbnb HQ! Background There is often a natural evolution in the tooling, organization, and technical underpinning of data pipelines. Most data teams and data pipelines are born from a monolithic collection of queries. As the pipeline grows in its complexity, it becomes sensible to leverage the Java or Python Spark…