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Updated: 54 min 2 sec ago

Another year of Haskell Hacking in the Google Zurich Office

13 hours 4 min ago
For the fourth time, the Google Open Source Programs Office have co-sponsored a three-day hackathon for Haskell, an open source functional programming language. Gleb Peregud from Google’s Zurich office talks more about the event below.

On the weekend of July 22nd, 126 Haskell enthusiasts got together for another installment of ZuriHac, a yearly open source Haskell hackathon held in Zurich, Switzerland, and like the last two years it took place at Google Zurich.
Participants could either hack uninterrupted in the main room or listen to a number of presentations in the tech talk room. Each day was kicked off with a keynote — Bas van Dijk talked about the use of functional programming at LumiGuide (slides), Edward Kmett about monad homomorphisms, and Andres Löh about generic-sop, a new approach to generic programming. All three talks drew a full room of interested listeners.
We also prepared two codelabs for Haskell beginners, and rallied 28 dedicated volunteers to serve as mentors (thank you all!) so that there was always someone to ask for help.
Aside from keynotes, there were five other talks: an experience report on parallelizing and distributing scientific computations (slides), an overview of a language to program FPGAs called CλaSH, an interactive tour through low-level pieces of the GHC Haskell compiler, an introduction to web programming using Spock (slides) and a talk on revamping the build system of GHC (slides).
Spontaneous mini-lectures attract smaller crowds.As is traditional, after a full Saturday of hacking, we went out to barbecue down by the Zurich lake.
We were lucky that weather forecast was mistaken about a looming thunderstorm!We managed to beat last year's record, and welcomed 126 attendees. We hope to have even more participants next year - our goal is to host 150 hackers in 2017. See you in a year!
By Gleb Peregud, Site Reliability Engineer
Categories: Open Source

Google Open Source Peer Bonus Program

13 hours 11 min ago
Five years ago the Open Source Programs Office established the Open Source Peer Bonus Program to remind Googlers of the importance of the myriad developers outside of Google who keep open source healthy and growing.

The program works like this: we invite Googlers to nominate open source developers outside of the company who deserve recognition for their contributions to interesting open source projects including those used by Google. After review by a team of volunteer engineers, the recipients receive our heartfelt thanks and a small token of our appreciation.

We have recognized more than 500 open source developers from 30+ countries who have contributed their time and talent to over 400 open source projects.

Having just finished the latest round of the program, we’d like to recognize the individuals and the projects they worked on. Here’s everyone who gave us permission to thank them publicly:

NameProjectNameProjectOlli Etuaho ANGLEAlexander Morozov Go programming languageMinko Gechev AngularJoel Sing LibreSSLGeorgios Kalpakas AngularDaniel Borkmann Linux kernelSpencer Low AOSP (Android)Michael Ellerman Linux kernelHolden Karau Apache SparkHeiko Stuebner Linux kernelDave Taht BufferbloatJonathan Garbee Material Design LiteLeon Han ChromiumChris Sullo NiktoYoav Weiss ChromiumCarl Friedrich Bolz PyPyRob Wu ChromiumBrett Cannon PythonFaisal Vali ClangRaymond Hettinger PythonMatt Godbolt Compiler ExplorerTim Peters PythonPaul Kocialkowski corebootTully Foote ROSJonathan Kollasch corebootIgor Babuschkin TensorFlowNicolas Reinecke corebootYuan Tang TensorFlowWerner Zeh corebootHanno Boeck The Fuzzing ProjectDaniel Greenfeld DjangoKhaled Hosny TruFontEric Whitney ext4Tom Rini U-BootBen Martin FontForgeCaitlin Potter V8Dmitri Shuralyov go-githubBrian Behlendorf ZFS on Linux
Congratulations all and thank you so much for your contributions to the open source community!

By Helen Hu, Open Source Programs Office
Categories: Open Source

From Summer of Code to Game of Thrones on the back of a JavaScript Dragon (Part 3)

Thu, 09/29/2016 - 19:59
This guest post is a part of a short series about Tatyana Goldberg, Guy Yachdav and Christian Dallago and the journey that was inspired by their participation as Google Summer of Code mentors for the BioJS project. Check out the first and second posts in the series.

This blog post marks the end of our short series following our adventures in open source. As you may recall, it all started thanks to Google Summer of Code (GSoC) which brought our team together. The GSoC collaboration spurred us to start a class at Technical University of Munich (TUM) that eventually took on the Game of Thrones data science project which became an international sensation.

The success of our Game of Thrones project opened a lot of doors. First, we were invited to participate in the Morpheus Cup which is a prestigious university olympiad that brings together students from all over Europe to compete in digital challenges.

Our team rocked the competition winning two challenges and making it to the finalist stage in the third challenge. We were honored to represent our university and grateful for Google’s sponsorship of our team.
WhatsApp-Image-20160510 (1).jpegThe students and mentors of the Game of Thrones project at the Morpheus Cup challenge in May 2016. From left to right: Georgi Anastasov, Emiliyana Kalinova, Maximilian Bandle (all students), Guy Yachdav (mentor), Christian Dallago (mentor), Tobias Piffrader, Theodor Chesleran (both students) and Tatyana Goldberg (mentor).Another opportunity that followed was an invitation to speak at a TEDx event at TUM on July 28th, 2016. In the event, titled “The Common Extraordinary,” Guy presented our work with data mining as bioinformaticians, sharing how we’ve made the field of data science accessible to our students and how we helped popularize it through the Game of Thrones project.
More speaking engagements are already scheduled: at meetups, coffee talks and conferences where we plan to keep evangelizing data mining and tell the story of our open source adventure.
What’s next? We’re excited to continue as mentors and org admins in GSoC and to carry on teaching data science and JavaScript at the university. In between classes and our daily research work we’re now being asked by friends, family members, colleagues and even strangers whether we can help them use data mining to answer questions on subjects ranging from politics, science, sports and even their personal lives.

Just the other day we were approached with the idea of developing an app that would take in a set of personality traits, process them along with social network data and help in suggesting life decisions: Should I date that person? Should I really take this job? Is Baltimore the city for me?

That interest goes even beyond our personal circles. A recent trade media report pointed out that by using machine learning in an unexpected context, the Game of Thrones project demonstrated the disruptive force of data mining. This force, the article continues, could make an impact on the next industrial revolution - Industry 4.0 - where data plays a key role.

Do you have interesting questions you’d like to answer or a data set you’d like to make predictions with? Curious about BioJS or our JavaScript course? Please reach out to us on Twitter or in the comments.
In the near future we dream of starting our own consultancy, as we already have requests from companies that want our help with upcoming data science projects. It seems our team has found its entrepreneurial bent!
We hope enjoyed this trilogy of blog posts, that our story has inspired you and that you too will continue to adventure in open source and collaborative development. If you’re not involved with Google Summer of Code, consider joining. It’s a great way to build up your project and share it with the world. More importantly, it lets you work with amazing people with whom, as we learned, it is possible to reach the sky.
By Tatyana Goldberg, Christian Dallago, and Guy Yachdav, BioJS
Categories: Open Source

.NET and PowerShell tooling for the Google Cloud Platform

Thu, 09/29/2016 - 18:50
Last month Google made an announcement unveiling support for Visual Studio, C#, PowerShell, Microsoft SQL Server and more on the Google Cloud Platform. With so many  new features, it is easy to gloss over some of the technical aspects of the announcement, especially the fact that all of the developer tooling and libraries are open source and available on GitHub.

This post will go into some of the details behind the new C# libraries, PowerShell cmdlets, and Visual Studio extension. All three products are open source, have an exciting roadmap for the future and are hungry for your feedback.

C# bindings for Google APIs

Source: https://github.com/googlecloudplatform/google-cloud-dotnet
Docs: https://cloud.google.com/dotnet/

For years, Google has had innovative technologies powering its data centers, unfortunately Google’s internal APIs and technology couldn’t directly benefit you and your software. That was, until the Google Cloud Platform started exposing public APIs for things like machine learning, storage, logging etc. With these APIs publicly available, you can add powerful capabilities to your apps without needing to manage complex infrastructure.

There have been C# bindings for Google APIs for years. In fact, Google receives hundreds of millions of API calls from C# clients every day. But newer APIs, especially those from the Google Cloud Platform, require more advanced features like bidirectional streaming. That’s why rather than using HTTP/REST many newer Google APIs are built on top of gRPC, a high performance, open source universal RPC framework.

But don’t worry, we have C# bindings for those gRPC-based APIs too; all of it open source and on GitHub.

In both cases, the client library is the result of a C# code generator. We take the API’s discovery document (analogous to a WSDL) and generate C# code. gRPC APIs require more careful design than other APIs, but the end product is the same. Once built, the API libraries are published to NuGet.

C# code generators for Google APIs isn’t the entire story.

Source code generated from tools can look foreign at times. So for libraries where the codegen isn’t good enough, we have hand-written wrappers to provide a better, more idiomatic experience. In some cases -- such as CRUD operations using the Datastore API -- the hand-written library cuts down on the required lines of code by half.

Finally, support for C# doesn’t just mean code. We are also working to ensure Google APIs are supported on different runtimes too. Most Google APIs work on the cross-platform .NET Core runtime and we are continuing to expand support.

PowerShell support

Source: https://github.com/googlecloudplatform/google-cloud-powershell
Docs: http://googlecloudplatform.github.io/google-cloud-powershell/

C# support is great when you are writing full applications, but for DevOps, scripting is more typical. The Cloud SDK provides command-line tools (gcloud, gsutil) for managing cloud resources, but when running on Windows, Windows PowerShell is a dramatically more productive environment. Google Cloud tools for PowerShell is a set of cmdlets so you can manage your Google cloud resources. They are strongly typed, and integrate seamlessly with other PowerShell tools. For example, to learn more about a cmdlet, just use Get-Help.

In designing the PowerShell cmdlets, the main goal was to be idiomatic. We wanted to follow the best practices and guidelines so PowerShell novices and pros alike could use our cmdlets. Of course, if we have anything wrong, please log an issue on the GitHub repository. Pull requests are also welcome.

Visual Studio

Source: https://github.com/googlecloudplatform/google-cloud-visualstudio
Docs: https://cloud.google.com/visual-studio/

The C# and PowerShell features should help developers using Google services. But the biggest impact on developer productivity comes from being inside the Visual Studio IDE.

From within Visual Studio you can search for new extensions and find the Google Cloud Platform Extension for Visual Studio. It provides tools for viewing/managing data stored in Google Cloud Storage and Google Cloud SQL. It also provides support for deploying ASP.NET 4.x applications to Google Compute Engine.

It is only the first release and we have some big plans for the future. You can see a lot of the short-term features we have planned by looking at the issues list in GitHub. Like making Google APIs light up for the new .NET Core runtime, being able to deploy ASP.NET Core applications to Google App Engine or Google Container Engine will be huge. Stay tuned for a future blog post about how to run C# on Google App Engine Flexible Environment, as well.

We’re just getting started

Hopefully you share my enthusiasm for Google’s ongoing development in .NET tooling. Not only is it exciting to be able to take advantage of Google Cloud Platform technologies, but also to see a future where .NET Core enables C# code to run cross-platform.

But to be successful we need your help.

If you have questions, be sure to ask on Stack Overflow (e.g. the google-cloud-visualstudio or google-cloud-powershell tags). If you have problems, please open issues on GitHub (libraries, VS, PowerShell). If you still have trouble, participate in the google-cloud-dev group.

The team here at Google is thrilled to be working with the .NET stack and your feedback is immensely helpful in prioritizing things.

By Chris Smith, Software Engineer
Categories: Open Source

A sizzling open source release for the Australian Election site

Wed, 09/28/2016 - 23:49
Originally posted on the Geo Developers Blog

One of the best parts of my job at Google is 20 percent time. While I was hired to help developers use Google’s APIs, I value the time I'm afforded to be a student myself—to learn new technologies and solve real-world problems. A few weeks prior to the recent Australian election an opportunity presented itself. A small team in Sydney set their sights on helping the 15 million voters stay informed of how to participate, track real-time results, and (of course) find the closest election sausage sizzle!


Our team of designers, engineers and product managers didn't have an immediate sense of how to attack the problem. What we did have was the power of Google’s APIs, programming languages, and Cloud hosting with Firebase and Google Cloud Platform.



The result is a mish-mash of some technologies we'd been wanting to learn more about. We're open sourcing the ausvotes.withgoogle.com repository to give developers a sense of what happens when you get a handful of engineers in a room with a clear goal and a immovable deadline.

The Election AU 2016 repository uses:

  • Go from Google App Engine instances to serve the appropriate level of detail for users' viewport queries from memory at very low latency, and
  • Dart to render the live result maps on top of Google Maps JavaScript API using Firebase real time database updates.

A product is only as good as the attention and usage is receives. Our team was really happy with the results of our work:

  • 406,000 people used our maps, including 217,000 on election day.
  • We had 139 stories in the media.
  • Our map was also embedded in major news websites, such as Sky News.

Complete setup and installation instructions are available in the GitHub README.

By Brett Morgan, Developer Programs Engineer
Categories: Open Source

Angular, version 2: proprioception-reinforcement

Fri, 09/23/2016 - 00:02
Originally posted on the Angular Blog

Today, at a special meetup at Google HQ, we announced the final release version of Angular 2, the full-platform successor to Angular 1.

What does "final" mean? Stability that's been validated across a wide range of use cases, and a framework that's been optimized for developer productivity, small payload size, and performance. With ahead-of-time compilation and built-in lazy-loading, we’ve made sure that you can deploy the fastest, smallest applications across the browser, desktop, and mobile environments. This release also represents huge improvements to developer productivity with the Angular CLI and styleguide.

Angular 1 first solved the problem of how to develop for an emerging web. Six years later, the challenges faced by today’s application developers, and the sophistication of the devices that applications must support, have both changed immensely. With this release, and its more capable versions of the Router, Forms, and other core APIs, today you can build amazing apps for any platform. If you prefer your own approach, Angular is also modular and flexible, so you can use your favorite third-party library or write your own.

From the beginning, we built Angular in collaboration with the open source development community. We are grateful to the large number of contributors who dedicated time to submitting pull requests, issues, and repro cases, who discussed and debated design decisions, and validated (and pushed back on) our RCs. We wish we could have brought every one of you in person to our meetup so you could celebrate this milestone with us tonight!


What’s next?Angular is now ready for the world, and we’re excited for you to join the thousands of developers already building with Angular 2.  But what’s coming next for Angular?

A few of the things you can expect in the near future from the Angular team:

  • Bug fixes and non-breaking features for APIs marked as stable
  • More guides and live examples specific to your use cases
  • More work on animations
  • Angular Material 2
  • Moving WebWorkers out of experimental
  • More features and more languages for Angular Universal
  • Even more speed and payload size improvements

Semantic VersioningWe heard loud and clear that our RC labeling was confusing. To make it easy to manage dependencies on stable Angular releases, starting today with Angular 2.0.0, we will move to semantic versioning.  Angular versioning will then follow the MAJOR.MINOR.PATCH scheme as described by semver:

  1. the MAJOR version gets incremented when incompatible API changes are made to stable APIs,
  2. the MINOR version gets incremented when backwards-compatible functionality are added,
  3. the PATCH version gets incremented when backwards-compatible bug are fixed.

Moving Angular to semantic versioning ensures rapid access to the newest features for our component and tooling ecosystem, while preserving a consistent and reliable development environment for production applications that depend on stability between major releases, but still benefit from bug fixes and new APIs.
ContributorsAaron Frost, Aaron (Ron) Tsui, Adam Bradley, Adil Mourahi, agpreynolds, Ajay Ambre, Alberto Santini, Alec Wiseman, Alejandro Caravaca Puchades, Alex Castillo, Alex Eagle, Alex Rickabaugh, Alex Wolfe, Alexander Bachmann, Alfonso Presa, Ali Johnson, Aliaksei Palkanau, Almero Steyn, Alyssa Nicoll, Alxandr, André Gil, Andreas Argelius, Andreas Wissel, Andrei Alecu, Andrei Tserakhau, Andrew, Andrii Nechytailov, Ansel Rosenberg, Anthony Zotti, Anton Moiseev, Artur Meyster, asukaleido, Aysegul Yonet, Aziz Abbas, Basarat Ali Syed, BeastCode, Ben Nadel, Bertrand Laporte, Blake La Pierre, Bo Guo, Bob Nystrom, Borys Semerenko, Bradley Heinz, Brandon Roberts, Brendan Wyse, Brian Clark, Brian Ford, Brian Hsu, dozingcat, Brian Yarger, Bryce Johnson, CJ Avilla, cjc343, Caitlin Potter, Cédric Exbrayat, Chirayu Krishnappa, Christian Weyer, Christoph Burgdorf, Christoph Guttandin, Christoph Hoeller, Christoffer Noring, Chuck Jazdzewski, Cindy, Ciro Nunes, Codebacca, Cody Lundquist, Cody-Nicholson, Cole R Lawrence, Constantin Gavrilete, Cory Bateman, Craig Doremus, crisbeto, Cuel, Cyril Balit, Cyrille Tuzi, Damien Cassan, Dan Grove, Dan Wahlin, Daniel Leib, Daniel Rasmuson, dapperAuteur, Daria Jung, David East, David Fuka, David Reher, David-Emmanuel Divernois, Davy Engone, Deborah Kurata, Derek Van Dyke, DevVersion, Dima Kuzmich, Dimitrios Loukadakis, Dmitriy Shekhovtsov, Dmitry Patsura, Dmitry Zamula, Dmytro Kulyk, Donald Spencer, Douglas Duteil, dozingcat, Drew Moore, Dylan Johnson, Edd Hannay, Edouard Coissy, eggers, elimach, Elliott Davis, Eric Jimenez, Eric Lee Carraway, Eric Martinez, Eric Mendes Dantas, Eric Tsang, Essam Al Joubori, Evan Martin, Fabian Raetz, Fahimnur Alam, Fatima Remtullah, Federico Caselli, Felipe Batista, Felix Itzenplitz, Felix Yan, Filip Bruun, Filipe Silva, Flavio Corpa, Florian Knop, Foxandxss, Gabe Johnson, Gabe Scholz, GabrielBico, Gautam krishna.R, Georgii Dolzhykov, Georgios Kalpakas, Gerd Jungbluth, Gerard Sans, Gion Kunz, Gonzalo Ruiz de Villa, Grégory Bataille, Günter Zöchbauer, Hank Duan, Hannah Howard, Hans Larsen, Harry Terkelsen, Harry Wolff, Henrique Limas, Henry Wong, Hiroto Fukui, Hongbo Miao, Huston Hedinger, Ian Riley, Idir Ouhab Meskine, Igor Minar, Ioannis Pinakoulakis, The Ionic Team, Isaac Park, Istvan Novak, Itay Radotzki, Ivan Gabriele, Ivey Padgett, Ivo Gabe de Wolff, J. Andrew Brassington, Jack Franklin, Jacob Eggers, Jacob MacDonald, Jacob Richman, Jake Garelick, James Blacklock, James Ward, Jason Choi, Jason Kurian, Jason Teplitz, Javier Ros, Jay Kan, Jay Phelps, Jay Traband, Jeff Cross, Jeff Whelpley, Jennifer Bland, jennyraj, Jeremy Attali, Jeremy Elbourn, Jeremy Wilken, Jerome Velociter, Jesper Rønn-Jensen, Jesse Palmer, Jesús Rodríguez, Jesús Rodríguez, Jimmy Gong, Joe Eames, Joel Brewer, John Arstingstall, John Jelinek IV, John Lindquist, John Papa, John-David Dalton, Jonathan Miles, Joost de Vries, Jorge Cruz, Josef Meier, Josh Brown, Josh Gerdes, Josh Kurz, Josh Olson, Josh Thomas, Joseph Perrott, Joshua Otis, Josu Guiterrez, Julian Motz, Julie Ralph, Jules Kremer, Justin DuJardin, Kai Ruhnau, Kapunahele Wong, Kara Erickson, Kathy Walrath, Keerti Parthasarathy, Kenneth Hahn, Kevin Huang, Kevin Kirsche, Kevin Merckx, Kevin Moore, Kevin Western, Konstantin Shcheglov, Kurt Hong, Levente Morva, laiso, Lina Lu, LongYinan, Lucas Mirelmann, Luka Pejovic, Lukas Ruebbelke, Marc Fisher, Marc Laval, Marcel Good, Marcy Sutton, Marcus Krahl, Marek Buko, Mark Ethan Trostler, Martin Gontovnikas, Martin Probst, Martin Staffa, Matan Lurey, Mathias Raacke, Matias Niemelä, Matt Follett, Matt Greenland, Matt Wheatley, Matteo Suppo, Matthew Hill, Matthew Schranz, Matthew Windwer, Max Sills, Maxim Salnikov, Melinda Sarnicki Bernardo, Michael Giambalvo, Michael Goderbauer, Michael Mrowetz, Michael-Rainabba Richardson, Michał Gołębiowski, Mikael Morlund, Mike Ryan, Minko Gechev, Miško Hevery, Mohamed Hegazy, Nan Schweiger, Naomi Black, Nathan Walker, The NativeScript Team, Nicholas Hydock, Nick Mann, Nick Raphael, Nick Van Dyck, Ning Xia, Olivier Chafik, Olivier Combe, Oto Dočkal, Pablo Villoslada Puigcerber, Pascal Precht, Patrice Chalin, Patrick Stapleton, Paul Gschwendtner, Pawel Kozlowski, Pengfei Yang, Pete Bacon Darwin, Pete Boere, Pete Mertz, Philip Harrison, Phillip Alexander, Phong Huynh, Polvista, Pouja, Pouria Alimirzaei, Prakal, Prayag Verma, Rado Kirov, Raul Jimenez, Razvan Moraru, Rene Weber, Rex Ye, Richard Harrington, Richard Kho, Richard Sentino, Rob Eisenberg, Rob Richardson, Rob Wormald, Robert Ferentz, Robert Messerle, Roberto Simonetti, Rodolfo Yabut, Sam Herrmann, Sam Julien, Sam Lin, Sam Rawlins, Sammy Jelin, Sander Elias, Scott Hatcher, Scott Hyndman, Scott Little, ScottSWu, Sebastian Hillig, Sebastian Müller, Sebastián Duque, Sekib Omazic, Shahar Talmi, Shai Reznik, Sharon DiOrio, Shannon Ayres, Shefali Sinha, Shlomi Assaf, Shuhei Kagawa, Sigmund Cherem, Simon Hürlimann (CyT), Simon Ramsay, Stacy Gay, Stephen Adams, Stephen Fluin, Steve Mao, Steve Schmitt, Suguru Inatomi, Tamas Csaba, Ted Sander, Tero Parviainen, Thierry Chatel, Thierry Templier, Thomas Burleson, Thomas Henley, Tim Blasi, Tim Ruffles, Timur Meyster, Tobias Bosch, Tony Childs, Tom Ingebretsen, Tom Schoener, Tommy Odom, Torgeir Helgevold, Travis Kaufman, Trotyl Yu, Tycho Grouwstra, The Typescript Team, Uli Köhler, Uri Shaked, Utsav Shah, Valter Júnior, Vamsi V, Vamsi Varikuti, Vanga Sasidhar, Veikko Karsikko, Victor Berchet, Victor Mejia, Victor Savkin, Vinci Rufus, Vijay Menon, Vikram Subramanian, Vivek Ghaisas, Vladislav Zarakovsky, Vojta Jina, Ward Bell, Wassim Chegham, Wenqian Guo, Wesley Cho, Will Ngo, William Johnson, William Welling, Wilson Mendes Neto, Wojciech Kwiatek, Yang Lin, Yegor Jbanov, Zach Bjornson, Zhicheng Wang, and many more...

With gratitude and appreciation, and anticipation to see what you'll build next, welcome to the next stage of Angular.

By Jules Kremer, Angular Team
Categories: Open Source

Google Summer of Code 2016 is a wrap

Thu, 09/15/2016 - 18:27
soc_horizontal500.png

As school in much of the world begins, Google Summer of Code 2016 winds down. The last three months have seen a whirlwind of activity on over 178 open source projects. University students from around the globe have been working with their mentors to contribute their technical skills to the common good.

Student participants submitted their completed work late last month, mentors evaluated the submissions, and the results have been announced.

We accepted 1,206 university students from 67 countries in April and we are excited to announce that 1,032 students (85.6%) successfully completed the program. To learn more about how that compares to previous years, check out our statistics from the last eleven years.

Google Summer of Code isn’t over though. In October we’ll be hosting our annual mentor summit in Sunnyvale, California where mentors and organization administrations will meet and exchange ideas.

Thank you to all of the students, mentors and organization administrators for your contributions to open source and for making the 12th year of Google Summer of Code such a great success!

By Josh Simmons, Open Source Programs Office
Categories: Open Source

Introducing OpenType Font Variations

Wed, 09/14/2016 - 10:15
Cześć and hello from the ATypI conference in Warsaw! Together with Microsoft, Apple and Adobe, we’re happy to announce the launch of variable fonts as part of OpenType 1.8, the newest version of the font standard. With variable fonts, your device can display text in myriads of weights, widths, or other stylistic variations from a single font file with less space and bandwidth.
 OpenType variable fonts support OpenType Layout variation.To prevent that the $ sign becomes a black blob,the stroke disappears at a certain weight.


At Google, we started tinkering with variable fonts about two years ago. We were fascinated by the typographic opportunities, and we got really excited when we realized that variable fonts would also help to save space and bandwidth. We proposed reviving Apple’s TrueType GX variations in OpenType, and started experimenting with it in our tools. The folks at Microsoft then started a four-way collaboration between Microsoft, Apple, Adobe, and Google, together with experts from type foundries and tool makers. Microsoft did the spec work; Apple brought their existing technology and expertise; Adobe updated their CFF format into CFF2; and we brought the tools and testing we’d been developing.  After months of intense polishing, the specification is now finished.

On the Google end, we did a lot of work to build, edit and display variable fonts:As always, all our font tools are free and open source for everyone to use and contribute.

Now that the spec is public, we can finish the work by merging the changes upstream so that our code will soon flow into products. We’ll also update Noto to support variations (for many writing systems, the sources are already there — the rest will follow). Much more work lies ahead, for example, implementing variations in Google Fonts. Together with other browser makers, we’re already working on a proposal to extend CSS fonts with variations. Once everyone agrees on the format, we’ll support it in Google Chrome. And there are many other challenges ahead, like incorporating font variations into other Google products—so it will be a busy time for us!  We are incredibly excited that an amazing technology from 23 years ago is coming back to life again today. Huge thanks to our friends at Adobe, Apple, and Microsoft for a great collaboration!
To learn more, read Introducing OpenType Variable Fonts, or talk to us at the FontTools group.
By Behdad Esfahbod and Sascha Brawer, Fonts and Text Rendering, Google Internationalization
Categories: Open Source

Google Summer of Code 2016 statistics: celebrating our mentors

Fri, 09/09/2016 - 18:00
Our final statistics post of the year is dedicated to to the incredible Google Summer of Code (GSoC) 2016 mentors. There were a total of 2,524 mentors, but today we'll look at the 1,500+ mentors who were assigned to an active project. Mentors are the lifeblood of our program. Without their hard work and dedication to the success of our students, there would be no GSoC. A merry band of volunteers, mentors work with students for more than 12 weeks — remotely, across multiple time zones, giving their time, expertise and guidance in addition to a regular full-time job for an average of 7.45 hours a week. Today we’ll take a closer look at our 2016 team.

GSoC 2016 mentors reside all over the world and represent 66 countries.




Want to see the data? Here’s the breakdown of the countries our mentors come from.



We have many mentors who participate in GSoC year after year. In 2016, we have six mentors who have participated since the program’s inception in 2005! GSoC “lifer” Bart Massey, who participated as a mentor for Portland State University and X.Org had this to say about his time with GSoC:

“I'm not sure which is more astonishing, that I am 12 years older with GSoC or that GSoC is 12 years old with me. Some of the most fantastic, interesting, brilliant and hardworking folks on the planet have gotten together every year for 12 years to change the world: Google folks and open source leadership and skilled, special students. It's been great to get to be part of it all, both as Portland State University and during my time with X.Org...I hope I get to keep working with and hanging out with these people I love every year forever.” 

Awww, we love you too Bart!

There are also plenty of newbies to the program each year and 2016 is no exception. We’d like to welcome 528 (33%) new mentors to the GSoC family.

Some fun facts:
  • Average age: 32
  • Youngest: 14
  • Oldest: 78
  • Most common mentor first name: David
At the end of each program year, we invite two mentors from each participating organization to join us at the Mentor Summit, a three day unconference at Google HQ in Northern California. There they enjoy a weekend with their peers to talk about all things open source-y (a technical term) and have some fun.

A huge thanks to each and every Google Summer of Code mentor. We salute you.

By Mary Radomile, Open Source Programs
Categories: Open Source

Stories from Google Code-in: OpenMRS and SCoRe

Mon, 08/22/2016 - 18:00
Google Code-in is our annual contest that gives students age 13 to 17 experience in computer science through contributions to open source projects. This blog post is the third installment in our series reflecting on the experiences of Google Code-in 2015 grand prize winners. Be sure to check out the first and second posts in the series, too.

In this post we look at the stories of three more Google Code-in (GCI) grand prize winners. Our grand prize winners come from a pool of 980 students from 65 countries who, all told, completed 4,776 tasks for 14 open source projects.

We were lucky enough to host many of these extraordinary young coders at Google HQ for a few days this summer. Over that time, we learned more about where they came from, what they gained by participating in GCI and what they plan to do as new members of the open source community.

Google Code-in 2015 Grand Prize Winners explore the SF Bay Area in this immersive Google Street View display with fellow open source program managers Stephanie Taylor and Cat Allman who run GCI.Our first story today is that of Břetislav Hájek from the Czech Republic, who chose to work with the OpenMRS project because he sees their work as important. OpenMRS is an open source medical record system that improves healthcare delivery in resource-constrained regions.

Břetislav got into computer science through web development, so he started by working on tasks related to HTML and CSS. This gave him confidence to take on more challenging tasks. His favorite task was creating a web application for searching through patients. While he didn’t find it hard, he learned a lot and was proud to have made something useful. Reflecting on Google Code-in, Břetislav said: “That's the thing I like about GCI. I always treat tasks as opportunities to learn something new. And the learning is more entertaining since I work on real problems.”

IRC communication proved to be an important part of Břetislav’s success. Other students were there and tried to help each other out as best they could, and there were always mentors available to help guide them. He enjoyed the friendly environment. The community motivated him to work harder and try new things. In the end, Břetislav was glad to have participated and is motivated to continue his work.

Next we have Vicente Bermudez from Uruguay who discovered Google Code-in through a story in the local news celebrating a Uruguayan grand prize winner from a previous year. Like Břetislav, Vicente chose to work on the OpenMRS project because the cause spoke to him.

He got into programming through his love of video games and his desire to create his own. He hadn’t heard about programming before but initial research piqued his interest. Following his curiosity, he learned Java and expanded his knowledge from there. Conveniently, much of OpenMRS is built with Java!

The task-based structure worked well for Vicente. He was unsure of some tasks, recognizing that he didn’t know much about what they required. For instance, he hesitated to take on one that involved creating a Windows Phone app because he had never created a mobile app. But he persisted and, five days later, he had completed it and learned a lot about mobile development.

It surprised Vicente how much he learned in such a short time span. He had this to say: “During the contest I gained knowledge in a variety of fields such as programming, testing, video editing, and graphic design. The mentors encouraged us to think about quality instead of quantity, and I learned a lot from that.”

Vicente loved his Google Code-in experience and plans to continue contributing to open source projects, especially OpenMRS.

The last student story we’ll share today is that of Anesu Mafuvadze, a student from the US who worked with the Sustainable Computing Research Group (SCoRe). His introduction to computer science came through robotics in one of his high school classes which used a language similar to C++.

Anesu was thrilled by the experience of bringing the robots to life with code. He described his introduction this way: “The more I programmed the more captivated I became; I loved how easily I could convert my wildest ideas into fully functioning programs; I loved the thrill of working in an environment that demands minute precision; above all, I loved creating programs that other people found useful.”

Online documentation and YouTube tutorials fueled Anesu’s education for several years as he picked up multiple languages and began participating in programming contests. But he knew something was missing, Anesu lacked real world coding experience and had never collaborated with others. As such, he didn’t pay much attention to the readability of his code, wasn’t aware of version control, didn’t write extensive tests and had never built something for the common good.

Enter Google Code-in. Working with mentors helped Anesu deliver quality and building open source software required him to learn collaboration tools and value readability. The contest also gave him an opportunity to build on skills that he hadn’t developed, such as web development. Anesu says the experience made him a better programmer and that the introduction to open source has motivated him to use his skills on projects that benefit society.

Thank you to Břetislav, Vicente and Anesu for their hard work contributing to open source projects and for sharing their stories with us. We have one more blog post coming with more student stories so stay tuned!

By Josh Simmons, Open Source Programs Office
Categories: Open Source

Opening up Science Journal

Fri, 08/19/2016 - 17:56
Science Journal is an app that turns your Android phone into a mobile science tool, allowing you to use the sensors in your phone to explore the world around you. The Making & Science team launched Science Journal a few months ago at Bay Area Maker Faire 2016 and have been excited to see different projects people have done with it all over the world!

Today we are happy to announce that we are releasing Science Journal 1.1 on the Google Play Store and also publishing the core source for the app. Open source software and hardware has been hugely beneficial to the science education ecosystem. By open sourcing, we’ll be able to improve the app faster and also to provide the community with an example of a modern Android app built with Material Design principles.

One important feature in Science Journal is the ability to connect to external devices over Bluetooth LE. We have open source firmware which runs on several Arduino microcontrollers already. In the near future, we will provide alternate ways to get your sensor data into Science Journal: stay tuned (or follow along with our commits)!

We believe that anyone can be a scientist anywhere. Science doesn’t just happen in the classroom or lab. Tools like Science Journal let you see how the world works with just your phone and now you can explore how Science Journal itself works, too. Give it a try and let us know what you think!

By Justin Koh, Software Engineer
Categories: Open Source

From Google Summer of Code to Game of Thrones on the Back of a JavaScript Dragon (Part 2)

Wed, 08/17/2016 - 20:08
This guest post is a part of a short series about Guy Yachdav, Tatyana Goldberg and Christian Dallago and the journey that was inspired by their participation as Google Summer of Code mentors for the BioJS project. Don’t miss the first post in the series. Heads up, this post contains spoilers for Game of Thrones seasons 5 and 6!

We built on the Google Summer of Code (GSoC) philosophy and the lessons we learned from participating in 2014 by starting a JavaScript Technology class at the Technical University of Munich (TUM).
We began with two dozen students who worked on expanding the BioJS visualization library. Our class became popular quickly and the number of applicants doubled each semester (nearly 180 applicants for 40 seats in the 2016 summer term).
In 2016 our team grew to include Christian Dallago, who had joined as a GSoC mentor. Together we decided to break with tradition of our course’s previous semesters. Instead of focusing on data visualization, we wanted to introduce students to data science with JavaScript. To get our students fully engaged, we decided the project would center on data from the hit TV show, Game of Thrones.
Our aim was to create an online portal for Game of Thrones fans which would:
  1. Provide the most comprehensive, structured and open data set about the Game of Thrones world accessible via API.
  2. Present an interactive map based on JavaScript.
  3. Listen to what people are saying on Twitter about each of the show’s characters.
  4. Use machine learning algorithms to predict the likelihood of each character’s death.
Our plan worked — the students were engaged. It was a beautiful sight to see: GitHub repos humming with activity as each dev team delved deeper into their projects. As a project manager, you know you’ve got something good when issues are being opened and closed at 4:00 AM!
The results were mind blowing. In 50 days of programming, 36 students opened over 1,200 issues and pull requests, pushed 3,300 commits, released four apps to NPM, and, of course, produced one absolutely amazing website.
The website amasses data from 2,028 characters. Our map shows 240 landmarks and the paths traveled by 28 characters. Our Twitter sentiment analysis tool analyzed over 3 million tweets. And we launched the first ever machine learning-based prediction algorithm that predicts the likelihood of dying for the 1,451 characters in the show that are still alive.
image02fix.pngVisualization of Twitter sentiment analysis data for Jon Snow during season 5 of Game of Thrones. The X axis shows the timeline and the Y axis shows the number of positive (green) and negative (red) tweets. Each tweet is analyzed by an algorithm using a neural network to determine whether the tweet’s writer has a positive, negative or neutral attitude toward the character. Since launch, the site’s popularity has skyrocketed. Following our press release, we were covered by over 1,500 media outlets, most notably Time, The GuardianRolling Stone, Daily Mail, BBC, Reuters, The Telegraph, CNET and many more. HowStuffWorks, The Vulture and others produced videos about the site and Chris Hardwick’s Comedy Central show did a segment about us. We've also given countless interviews to TV, radio and newspapers.
Blog2_Figure1_v3.pngGoogle Analytics for the website. Left chart shows the number of visitors to the website during the first week after launch, reaching over 73K visitors on April 25th. Right chart shows the number of visitors at a given time point during the same week.The most exciting part of the project was predicting the likelihood that any given character would die using machine learning. Machine learning algorithms find rules and patterns in the data, things that humans cannot obviously and simply detect. Once the rules and patterns are identified, we apply machine learning to make inferences or predictions from novel, previously unseen, data sets.
Warning: The next paragraphs contain spoilers for seasons 5 and 6 of Game of Thrones!
In order to predict the likelihood of a character’s death, we collected information about all of the characters that appeared in books 1 to 5 and analyzed over 30 features, including age, gender, marital status and others. Then we used a support vector machine (SVM) to statistically compare the features of characters, both dead and alive, to predict who would get the axe next. Our prediction was correct for 74% of all cases and surprised us by placing a number of characters thought to be relatively safe in grave danger.
According to our predictions, Jon Snow, who was seemingly betrayed and murdered by fellow members of the Night’s Watch at the end of season 5, had only an 11% chance of dying. Indeed, Jon has risen from the dead in the second episode of season 6! We also predicted that the rulers of Dorn (Doran and Trystane) Martell are at a high likelihood of death and, as predicted, they were taken out in the first episode of the new season.
Of course, as is always the case with predictions, there were also misses. We didn’t expect Roose Bolton to be killed off nor did we see Hodor’s departure coming.
This experience was an amazing ride for our team and it all started with Google Summer of Code! In the next post we’ll share what followed and where we see ourselves heading in the future.
By Guy Yachdav, Tatyana Goldberg and Christian Dallago, BioJS
Categories: Open Source

From Google Summer of Code to Game of Thrones on the Back of a JavaScript Dragon (Part 1)

Wed, 08/17/2016 - 20:08
This guest post is a part of a short series about Tatyana Goldberg and Guy Yachdav, instructors at Technical University of Munich, and the journey that was inspired by their participation as Google Summer of Code mentors for the BioJS project.

Hello there! We are from the BioJavaScript (BioJS) project which first joined Google Summer of Code (GSoC) in 2014. Our experience in the program set us on a grand open source adventure that we’ll be sharing with you in a series of blog posts. We hope you enjoy our story and, more importantly, hope it inspires you to pursue your own open source adventure.
Tatyana Goldberg and Guy Yachdav, GSoC mentors and open source enthusiasts. Photo taken at the MorpheusCup competition Luxembourg, May 2016.We came together around the BioJS community, an open source project for creating beautiful and interactive open source visualizations of biological data on the web. BioJS visualizations are made up of components which have a modular design. This modular design enables several things: they can be used by non-programmers, they can be combined to make more complex visualizations, and they can be easily integrated into existing web applications. Despite being a young community, BioJS already has traction in industry and academia.
In early 2014 we decided to apply for GSoC and we were fortunate to have our application accepted on our first try. The experience was extremely positive — the five students we accepted delivered great software and they had a big impact on the BioJS community:
  • The number of mailing list subscribers doubled in less than a month.
  • All five of our accepted students from 2014 became core developers.
  • Students were invited to six international conferences to share their work.
  • Students helped organize the first BioJS conference held July 2015.
  • Most importantly, the students have independently designed BioJS version 2.0 which positioned BioJS as the leading open source visualization library for biological data. 
You can see three examples of the work GSoC students did on BioJS below:

MSAViewer is a visualization and analysis of multiple sequence alignments and was developed by Sebastian Wilzbach. Proteome Viewer is a multilevel visualization of proteomes in the UniProt database and was developed by Jose Villaveces. Genetic Variation Viewer is visualization of the number and type of mutations at each position in a biological sequence and was developed by Saket Choudhary.
We learned a lot in the first year we participated in Google Summer of Code. Here are some of the takeaways that are especially relevant to mentors and organizations that are considering joining the program:
  1. GSoC is a great source of dedicated and enthusiastic young developers.
  2. Mentors need to carefully manage students, listen to them and let them lead initiatives when it makes sense.
  3. Org admins should leverage success in GSoC beyond the program.
  4. Orgs need to find the most motivated students and make sure their projects are feasible.
  5. People want to share in your success, so participation in GSoC can start a positive feedback loop attracting new contributors and users.
  6. Most importantly: the ideas behind GSoC - the love for open source and coding - are contagious and spread easily to larger audiences, especially to students and other people who work in academia. Just try it! 
Our positive experience spurred us to seek out and conquer new challenges. Stay tuned for our next post where we explain how GSoC inspired us to create a popular new class and how we applied data science to Game of Thrones.
By Tatyana Goldberg and Guy Yachdav, BioJS and TU Munich
Categories: Open Source

A Google Santa Tracker update from Santa's Elves

Wed, 08/17/2016 - 18:00

Originally posted on the Google Developers Blog

By Sam Thorogood, Developer Programs Engineer


Today, we're announcing that the open source version of Google's Santa Tracker has been updated with the Android and web experiences that ran in December 2015. We extended, enhanced and upgraded our code, and you can see how we used our developer products - including Firebase and Polymer - to build a fun, educational and engaging experience.


To get started, you can check out the code on GitHub at google/santa-tracker-weband google/santa-tracker-android. Both repositories include instructions so you can build your own version.
Santa Tracker isn’t just about watching Santa’s progress as he delivers presents on December 24. Visitors can also have fun with the winter-inspired experiences, games and educational content by exploring Santa's Village while Santa prepares for his big journey throughout the holidays.
Below is a summary of what we’ve released as open source.
Android app
  • The Santa Tracker Android app is a single APK, supporting all devices, such as phones, tablets and TVs, running Ice Cream Sandwich (4.0) and up. The source code for the app can be found here.
  • Santa Tracker leverages Firebase features, including Remote Config API, App Invites to invite your friends to play along, and Firebase Analytics to help our elves better understand users of the app.
  • Santa’s Village is a launcher for videos, games and the tracker that responds well to multiple devices such as phones and tablets. There's even an alternative launcher based on the Leanback user interface for Android TVs.


  • Games on Santa Tracker Android are built using many technologies such as JBox2D (gumball game), Android view hierarchy (memory match game) and OpenGL with special rendering engine (jetpack game). We've also included a holiday-themed variation of Pie Noon, a fun game that works on Android TV, your phone, and inside Google Cardboard's VR.
Android Wear

  • The custom watch faces on Android Wear provide a personalized touch. Having Santa or one of his friendly elves tell the time brings a smile to all. Building custom watch faces is a lot of fun but providing a performant, battery friendly watch face requires certain considerations. The watch face source code can be found here.
  • Santa Tracker uses notifications to let users know when Santa has started his journey. The notifications are further enhanced to provide a great experience on wearables using custom backgrounds and actions that deep link into the app.
On the web

  • Santa Tracker is mobile-first: this year's experience was built for the mobile web, including an amazing brand new, interactive - yet fully responsive, village: with three breakpoints, touch gesture support and support for the Web App Manifest.
  • To help us develop Santa at scale, we've upgraded to Polymer 1.0+. Santa Tracker's use of Polymer demonstrates how easy it is to package code into reusable components. Every housein Santa's Village is a custom element, only loaded when needed, minimizing the startup cost of Santa Tracker.


  • Many of the amazing new games (like Present Bounce) were built with the latest JavaScript standards (ES6) and are compiled to support older browsers via the Google Closure Compiler.
  • Santa Tracker's interactive and fun experience is enhanced using the Web Animations API, a standardized JavaScript APIfor unifying animated content.
  • We simplified the Chromecast support this year, focusing on a great screensaver that would countdown to the big event on December 24th - and occasionally autoplay some of the great video content from around Santa's Village.
We hope that this update inspires you to make your own magical experiences based on all the interesting and exciting components that came together to make Santa Tracker!
Categories: Open Source

Which languages convey the most information in the least space? Introducing the Unimorph dataset.

Mon, 08/08/2016 - 18:00
Several years ago a science journalist asked me which languages could pack the most information into a 140-character Tweet. Because Twitter defines a character roughly as a single Unicode code point, this turns out to be an easy question to answer. Chinese almost certainly rates as the most “compact” language from that point of view because a single Chinese character represents a whole morpheme (in linguist terminology, a minimal unit of meaning) whereas an English letter only represents a part of a morpheme. The Chinese equivalent of I don’t eat meat, which in English takes 16 characters including spaces is 我不吃肉, which takes just four.

But this question relates to a broader question that as a linguist I have often been asked: which languages are the most “efficient” at conveying information? Or, which languages can convey the same information in the smallest amount of space? Untethered by the idiosyncrasies of Twitter, this question becomes quite difficult to answer. What do you mean by “space”? Number of characters? Number of bytes? Number of syllables? Each of these has its own problems. And perhaps more crucially, what do you mean by “information”? The Shannon notion of information does not straightforwardly apply here.

A group of us at Google set out to answer this question, or at least to provide the form that an answer would have to take. We had the resources and experience needed to annotate data in multiple languages, and we were able to divert some of those resources to this task. The results were published in a paper presented at the 2014 International Conference on Language Resources and Evaluation in Reykjavík, Iceland.

We are now releasing the data on GitHub. The data consist of 85 sentences typical of the kinds of sentences generated by Google Now, translated into eight typologically diverse languages: English, French, Italian, German, Russian, Arabic, Korean, Chinese, which include some highly inflected and uninflected languages, and various types of morphology including inflectional and agglutinative. The data were annotated by one to three annotators depending on the language, with morphological information, counts of the marked features and other information. The main data file is in HTML, color coded by language, which makes it easy to browse but also easy to extract into other formats.

Since the basic information conveyed by each sentence can be assumed to be the same across languages, the main focus of the research was on the additional information that each language marks, and cannot avoid marking. For example, the English sentence:

Use my location for the search results and other services.
has the French translation:

Utilisez ma position pour les résultats de recherche et d'autres services.
The verb ending -ez, in boldface above marks “addressee respect”, a bit of information that is missing from the English original.  One could have used a different ending on the French verb, but then that would not avoid this bit of information—it would be choosing to mark lack of respect, or familiarity with the addressee.

In the paper we tried various ways of measuring the differing information content of the languages relative to various definitions of “space”. Considering all the factors together, we concluded that the languages that conveyed the most information in a given amount of space were highly inflected languages like Russian, with uninflected languages like Chinese actually being the “least efficient” at conveying information.

We don’t expect this to be the final answer, which is why we are releasing the data as open source in the hopes that others will find it useful and maybe can even extend it to more sentences or a wider variety of languages. Ultimately though, any answer to the question of which languages convey the most information in the smallest amount of space must seriously address what is meant by “information”, and must pay heed to the famous maxim by the Russian linguist Roman Jakobson (1959) that “languages differ essentially in what they must convey and not in what they may convey.”

By Richard Sproat, Research Scientist
Categories: Open Source

Making Rubyists more comfortable on Google Cloud Platform

Fri, 08/05/2016 - 18:00
One of the many open source efforts at Google is the Google Cloud Platform (GCP) native libraries for our most popular languages. One of these libraries is the gcloud-ruby project on GitHub which is released as the gcloud gem on rubygems.org. There are several gems for accessing Google Cloud Platform resources from Ruby but this gem is different. It is hand coded by Rubyists for Rubyists and that has some distinct advantages.

Many of us have had experience working with libraries that are clearly ported from another language. I usually talk about them as Ruby with a Java accent or Python with a Perl accent. Generally they work just fine but you can run into some low level friction — sometimes things just don’t feel right. Native gems written by members of the community solve this problem. In the case of gcloud-ruby there are some really concrete examples.

First, gcloud-ruby uses syntax that is similar to other popular Ruby libraries. For example, the syntax for specifying a table schema in BigQuery (Google Cloud Platform's very large scale data warehouse) looks like this:

table = dataset.create_table "baby_names" do |schema|
schema.string "name"
schema.string "sex"
schema.integer "number"
end

Creating the same table in popular Ruby on Rails looks like this:

create_table "baby_names" do |schema|
schema.string "name"
schema.string "sex"
schema.integer "number
end

The two are nearly identical. That makes getting up to speed on BigQuery easier and quicker than it would be if the Ruby library didn't use patterns that are already known to the majority of Rubyists. 
Another way the gcloud-ruby library meets the community where it is at is by embracing the community's fondness for doing things several different ways. In Ruby there are often several correct ways to do a given task.
The gcloud-ruby library is no exception. There are a few different ways to authenticate and create the objects you use to interact with the API. Ruby also has many common methods that have aliases. In the standard library Enumerable#map and Enumerable#collect actually run the same code path for example. In gcloud-ruby the vision API uses aliases. Google Cloud Vision provides a single endpoint: annotate. gcloud-ruby has an annotate method but also aliases this method as mark and detect if those make more sense to you (detect is the method that makes the most sense to my brain so that's the one I use). By providing a couple of different aliases it can mean the first thing you try is more likely to work. This speeds up development time and makes learning the library easier. 
The last way the gcloud-ruby gem makes Rubyists feel at home is by having comprehensive tests, a common value and popular discussion topic for the Ruby community. gcloud-ruby uses minitest-spec for testing, a popular choice that most Rubyists can easily read. When I was learning the storage API I looked at the tests for storage to learn how to use the library. There is outstanding documentation as well for those who prefer learning that way but I'm so used to looking at tests that I really appreciated that gcloud-ruby has well written and easily accessible tests.
Above are three examples of how hand-coded libraries from within the community can improve the user experience when learning to use tools. Of course, doing all the development on GitHub in the open also helps. Users can easily see what bugs people have run into and what features are next up in the production queue. And if a user has a feature request (like the previously mentioned Cloud Vision support) they can create a GitHub issue.
If you’re a Rubyist, give gcloud-ruby a shot and let us know what you think!
By Aja Hammerly, Developer Advocate
Categories: Open Source

Stories from Google Code-in: KDE, MetaBrainz and Haiku

Mon, 08/01/2016 - 18:00
Google Code-in is our annual contest that gives students age 13 to 17 experience in computer science through contributions to open source projects. This blog post is the second installment in our series reflecting on the experiences of Google Code-in 2015 grand prize winners. Be sure to check out the first post in the series.

This week we profile three more grand prize winners from Google Code-in 2015. These students came from all around the world to celebrate with us in June after successfully completing 692 tasks that resulted in significant contributions to the participating open source projects.

Google Code-in 2015 Grand Prize Winners and Mentors were treated to a cruise around San Francisco Bay.
Students were paired with mentors who guided them as they learned both new technologies and how to collaborate on real-world projects. While most students had some programming experience, many were new to open source. In the end, they learned new skills, connected with open source communities and many will continue to contribute to open source projects.
We’re proud of all of the participants and grateful to the mentors who helped them. We invited the contest winners to write about their experience and many took us up on the offer. Here are their stories:
First up today is Imran Tatriev, a student from Kazakhstan who decided to work on the KDE project because loved their philosophy and had experience with C++ and Qt. He was a finalist in Google Code-in 2014 when he worked with the OpenMRS project.
Imran’s work on KDE included contributing to projects such as KDevelop, Marble and GCompris. His biggest challenge was working on the KDevelop IDE’s debugger where he was tasked with highlighting crashed threads. Highlighting the crashed thread was trivial, finding the thread that had crashed was not. It took him five days to solve that problem and he credits his mentor with helping him to work through it.
In the end, Imran learned a lot about regular expressions, the architecture of large software projects, C++ and unit testing. What did he like most about his Google Code-in experience? Imran writes: “The most valuable moments were meeting wonderful and smart people.” He plans to continue working with KDE and apply for Google Summer of Code.
Next is Caroline Gschwend, a student from the US who worked on the MetaBrainz project. Both of her parents are computer scientists and she credits them with spurring her interest.
A homeschool student with a unique approach to education, Caroline loves to learn and voraciously consumes free online resources. She had this to say: “I think that free, online learning is an amazing benefit to our society. With access to a computer and the internet, anyone, anywhere, can learn anything.”
Caroline discovered Google Code-in through her mother who had, in turn, discovered the contest through Google for Education. Caroline dug in and decided it was right up her alley. She loved that it embraced beginners with open arms and introduced new people to open source. Ultimately, she decided to work with MetaBrainz because, as a classically trained violinist, MusicBrainz piqued her interest. Their projects are primarily written in Perl and Python and, while Caroline was fluent in Java, it was too interesting to pass up.
As with most students, Caroline found collaboration to be a big part of the learning curve -- from GitHub to Git and IRC. Her mentors and other community contributors on IRC helped Caroline through the process and, looking back, she found that collaboration to be her favorite part of the whole experience. She loved that the mentors helped her to produce professional quality work rather than focusing on quantity.
Google Code-in gave Caroline a chance to learn about collaboration, Inkspace, icon design, web development and more. She has continued her work in open source and plans to apply for Google Summer of Code.
The last student we’re highlighting today is Vale Tolpegin, a student from the US who worked on the Haiku project, an open source operating system for personal computers. He also participated in Google Code-in 2014 but didn’t feel his skills were sharp enough to attack the more challenging tasks, like the ones he tackled this time around for Haiku.
Vale took on a wide range of tasks from documentation to application development, his favorite being the creation of the Haiku Hardware Repository. The repository is a Django website that lets people search and share hardware tests to determine if a given machine will work with Haiku.
He ran into a sticky issue early on, spending nearly a week finding a race condition within an application maintained by Haiku. Vale found it frustrating, but his mentors helped him see it through to the end. That wasn’t the only big challenge he ran into and, ultimately, bested: he spent another week debugging a Remote Desktop Application, software which had a very large code base.
Despite the two time consuming challenges, Vale managed to accomplish a lot more during the contest, including building a graph plotter and fixing bugs in the Haiku package manager. Vale had this to say:
“After finishing GCI, I have continued to work with Haiku and the experiences I have gained will continue to have an impact on me for years to come. Participating in GCI has truly been a life-­changing experience!”
Thank you to Imran, Caroline and Vale for their contributions to open source and for sharing their Google Code-in experiences with us. Stay tuned, we’ve got two more posts coming in this series!
By Josh Simmons, Open Source Programs Office
Categories: Open Source

Stories from Google Code-in: FOSSASIA and Haiku

Fri, 07/29/2016 - 21:43
Google Code-in is our annual contest to help pre-university students gain real-world computer science experience by taking on tasks of varying difficulty levels with the help of volunteer mentors. These tasks are created by open source projects so while learning, the students are contributing to the software many of us use on a daily basis.

The finalists and winners for our 2015/2016 season were announced in February and, in June, the grand prize winners joined us for four days of learning and celebration. Students and their guardians came from all around the world. One of my favorite things, as one of the Googler hosts, was seeing the light bulbs go on above parents’ heads as they came to understand open source and why it’s so important. These parents and guardians were even more proud of the students as they learned how much their teenager has contributed to the world through participating in Google Code-in.

We’ve invited contest winners and organizations to write about their experience and will be sharing their stories in a series of blog posts. This marks the first post in the series.

Google Code-in 2015 Grand Prize Winners and Mentors
Let’s start with Jason Wong, a student from the US who worked with FOSSASIA. FOSSASIA supports open source developers in Asia through events and coding programs.
Jason got into computer science during middle school at a summer camp where he built a website describing the differences between Linux, OS X, and Windows.  He dove deeper into web development by learning PHP and JavaScript through YouTube videos. He enjoyed being able to build more complex and dynamic websites. Like many new developers, Jason became very confident but did not concern himself with important aspects of programming like testing.
He learned about Google Code-in when Stephanie Taylor, fellow open source program manager who manages the GCI program here at Google, gave a talk at his school. Jason dove right in picking FOSSASIA as the project he would contribute to.
FOSSASIA offered Jason a chance to learn a lot about development and open source. He worked on their event pages, integrated Loklak and added an RSS section to their website, gaining experience with version control, Docker, Pharo and Node.js in the process. Most importantly, Jason learned about collaboration. He had this to say:
“Collaboration is so important in the open source community as it allows everyone to come together to help the world. Google Code-in has persuaded me to contribute to open source in the future.”
Next up we have Hannah Pan, another US student. She chose to work on Haiku, an open source operating system built for personal computers, because it used the C/C++ language which she was already confident with.
Hannah got into computer science through a high school AP course and discovered Google Code-in through this blog (woohoo!). She decided to participate even though it had already been underway for two weeks. Aiming just to make the top 10 in order to have a chance at being a finalist (and earn a hoodie), Hannah finished as a grand prize winner! 
The learning curve was steep: *nix commands, build tools and GitHub all presented new challenges. She was surprised how much code she had to sift through sometimes just to isolate the cause of minor bugs.
Like all of the participants, Hannah found her mentors to be crucial in providing both technical guidance and moral support. She explained, “I was amazed at my mentors’ expertise, dedication, modesty, and high standards. They taught me to strive for excellence rather than settle for mediocrity.”
Among other things, Hannah added localization support to the Tipster app, fixed extractDebugInfo, and even wrote a how-to article relating to the work. Reflecting on her experience, Hannah wrote:
“On the technical side, not only have I learned a lot, but I have realized how much more I have yet to learn. In addition, it has taught me some important life skills that no doubt will benefit me in my future endeavors. I’d like to thank my mentors and other students who inspired me and pushed me to do my best.”
Thank you to Jason and Hannah both for contributing to open source and sharing their Google Code-in experiences with us. Stay tuned as we continue this series in our next blog post!
By Josh Simmons, Open Source Programs Office
Categories: Open Source

Omnitone: Spatial audio on the web

Mon, 07/25/2016 - 18:04

Spatial audio is a key element for an immersive virtual reality (VR) experience. By bringing spatial audio to the web, the browser can be transformed into a complete VR media player with incredible reach and engagement. That’s why the Chrome WebAudio team has created and is releasing the Omnitone project, an open source spatial audio renderer with the cross-browser support.

Our challenge was to introduce the audio spatialization technique called ambisonics so the user can hear the full-sphere surround sound on the browser. In order to achieve this, we implemented the ambisonic decoding with binaural rendering using web technology. There are several paths for introducing a new feature into the web platform, but we chose to use only the Web Audio API. In doing so, we can reach a larger audience with this cross-browser technology, and we can also avoid the lengthy standardization process for introducing a new Web Audio component. This is possible because the Web Audio API provides all the necessary building blocks for this audio spatialization technique.



Omnitone Audio Processing Diagram
The AmbiX format recording, which is the target of the Omnitone decoder, contains 4 channels of audio that are encoded using ambisonics, which can then be decoded into an arbitrary speaker setup. Instead of the actual speaker array, Omnitone uses 8 virtual speakers based on an the head-related transfer function (HRTF) convolution to render the final audio stream binaurally. This binaurally-rendered audio can convey a sense of space when it is heard through headphones.

The beauty of this mechanism lies in the sound-field rotation applied to the incoming spatial audio stream. The orientation sensor of a VR headset or a smartphone can be linked to Omnitone’s decoder to seamlessly rotate the entire sound field. The rest of the spatialization process will be handled automatically by Omnitone. A live demo can be found at the project landing page.

Throughout the project, we worked closely with the Google VR team for their VR audio expertise. Not only was their knowledge on the spatial audio a tremendous help for the project, but the collaboration also ensured identical audio spatialization across all of Google’s VR applications - both on the web and Android (e.g. Google VR SDK, YouTube Android app). The Spatial Media Specification and HRTF sets are great examples of the Google VR team’s efforts, and Omnitone is built on top of this specification and HRTF sets.

With emerging web-based VR projects like WebVR, Omnitone’s audio spatialization can play a critical role in a more immersive VR experience on the web. Web-based VR applications will also benefit from high-quality streaming spatial audio, as the Chrome Media team has recently added FOA compression to the open source audio codec Opus. More exciting things like VR view integration, higher-order ambisonics and mobile web support will also be coming soon to Omnitone.

We look forward to seeing what people do with Omnitone now that it's open source. Feel free to reach out to us or leave a comment with your thoughts and feedback on the issue tracker on GitHub.

By Hongchan Choi and Raymond Toy, Chrome Team

Due to the incomplete implementation of multichannel audio decoding on various browsers, Omnitone does not support mobile web at the time of writing.
Categories: Open Source

Kubernetes 1.3 is here!

Thu, 07/21/2016 - 18:00
With all of the excitement being generated around the Kubernetes 1.3 release and the first anniversary of Kubernetes 1.0 (#k8sbday), now is a great time to point out some of the features that enterprise users should be taking note of.

If you’re not familiar with Kubernetes, let me get you up to speed.

Kubernetes is an open-source container automation framework that builds upon 15 years of experience of running production workloads at Google. Once you declare a desired state, Kubernetes works to drive your system toward that state. As a developer this means less time handling trivial tasks that a computer can automate and more time focusing on developing applications that provide value to users.

Additionally, Kubernetes aims to be a framework that you can operate at planetary scale, run anywhere, and never outgrow.

With the release of Kubernetes 1.3, Kubernetes is closer than ever to meeting those goals; the 1.3 release adds exciting features such as:Aside from features, the coolest part about working with Kubernetes is hearing user stories. I’ll soon be publishing an interview with Joseph Jacks, co-founder of Kismatic, the enterprise Kubernetes company, on the Kubernetes blog.
Joseph is very active in the Kubernetes community and has extensive experience with Kubernetes in production. In the interview I ask him why he bet his business on Kubernetes, what could be better, and how he sees Kubernetes growing in the near future.
Kubernetes has many, many features to offer that I didn’t get to cover in this short write-up. If you know anyone that needs to ramp up on Kubernetes, the easiest way is the free course I created with Kelsey Hightower, Scalable Microservices with Kubernetes. The course covers the basic features of Kubernetes. If you want an overview of what’s new in Kubernetes 1.3, feel free to look at the “What’s new in Kubernetes 1.3” video or slides.
Finally for a more in-depth look at the 1.3 release, make sure to check out: 5 days of Kubernetes 1.3 blog series.
Want to learn more about container orchestration and cloud native platforms? Here’s some recommended reading to follow up with:By Carter Morgan, Developer Programs Engineer
Categories: Open Source