Mozilla, Rust and More Programming Picks
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Mozilla VR Blog: New Avatar Features in Hubs
It is now easier than ever to customize avatars for Hubs! Choosing the way that you represent yourself in a 3D space is an important part of interacting in a virtual world, and we want to make it possible for anyone to have creative control over how they choose to show up in their communities. With the new avatar remixing update, members of the Hubs community can publish avatars that they create under a remixable, Creative Commons license, and grant others the ability to derive new works from those avatars. We’ve also added more options for creating custom avatars.
When you change your avatar in Hubs, you will now have the opportunity to browse through 'Featured' avatars and ‘Newest’ avatars. Avatars that are remixable will have an icon on them that allows you to save a version of that avatar to your own ‘My Avatars’ library, where you can customize the textures on the avatar to create your own spin on the original work. The ‘Red Panda’ avatar below is a remix of the original Panda Bot.
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QMO: Firefox 69 Beta 14
As you may already know, Friday August 16th – we held a new Testday event, for Firefox 69 Beta 14.
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Async Stack Traces in Rust
One neat result of Rust’s futures and async/await design is that all of the async callers are on the stack below the async callees. In most other languages, only the youngest async callee is on the stack, and none of the async callers. Because the youngest frame is most often not where a bug’s root cause lies, this extra context makes debugging async code easier in Rust.
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Facebook's HHVM Begins Seeing Rust Rewrite
Facebook's HHVM implementation that started off as a high performance PHP5 implementation but is now just focused on powering their own Hack programming language is beginning to see some of its code rewritten in Rust.
HHVM 4.20 was released on Tuesday and with this release they have been transitioning some of their code from OCaml to Rust.
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Things I Learnt from a Senior Software Engineer
year ago, I started working full-time at Bloomberg. That’s when I imagined writing this post. I imagined myself to be full of ideas that I could spit out on paper when the time comes. Just one month in, I realised it won’t be that easy: I was already forgetting things I learnt. They either became so internalized that my mind tricked me into believing I always knew them1, or they slipped my mind.
That’s one of the reasons I started keeping a human log. Every day, whenever I came across an interesting situation, I logged it. All thanks to sitting next to a senior software engineer, I could closely observe what they were doing, and how it was different from what I would do. We pair-programmed a lot, which made doing this easier. Further, in my team culture it’s not frowned upon to “snoop behind” people writing code. Whenever I sensed something interesting going on, I’d roll around and watch what was happening. I always had the context, thanks to regular standups.
I sat next to a senior software engineer for a year. Here’s what I learnt.
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Quansight Labs Dask Update
Finally, there's been a push for a more coordinated effort towards project maintenance and development by core Dask maintainers at Quansight, Anaconda, and NVIDIA. As part of this effort, we spend a portion of our work week on day-to-day project maintenance tasks (e.g. responding on issues, reviewing pull requests, fixing CI systems, etc.) as well as working on contributions that require significant amounts of time or expertise to implement (e.g. large-scale refactoring, adding new features, writing documentation, etc.). Today, Dask users typically get a quicker response from a core maintainer when opening an issue or pull request, in part, because of these efforts. I, and perhaps other core maintainers, hope to write more about this process in the future.
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Little Trouble in Big Data – Part 3
We have shown how a simple “How do I use mmap()?” mentoring project has grown beyond its initial scope and how we have used mmap, Eigen,parallel_for/parallel_reduce, flow graphs [maybe replace these two with Intel Thread Building Blocks] and zlib to nicely make the problem tractable. This has shown a nice set of performance improvements whilst at the same time keeping the disk and RAM usage within feasible limits.
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Dilution and Misuse of the "Linux" Brand
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