timely-dataflow

I agree that to compete with Ruby ergonomics one probably needs a GC. I think part of what I'm getting at is that there are other ways to approach these problems, and aping Ruby isn't necessarily one I prefer. Not to knock Crystal, it seems very cool. Re: application domains, I've recently been doing some work in CPU/memory constrained applications (not embedded, running big >500GB jobs on HPC clusters), and a GC is unfortunately a non-starter for this kind of data processing. I have also been watching with great anticipation the work being done on "big data" processing with Rust (https://github.com/frankmcsherry/timely-dataflow) and how that might obviate the need for a GC with the various JVM RAM-hogs which dominate that field. There are also many areas where people work (many of whom provide the tools that programmers of GC'd languages

See https://www.rust-lang.org/friends.html for a list of companies using Rust (perhaps most notably Dropbox and Mozilla), but here are some non-corporate projects off the top of my head: Panopticon, a cross-platform disassembler: https://panopticon.re/ Redox, an everything-is-a-URL microkernel OS: http://www.redox-os.org/ Piston, a modular collection of libraries for game development: http://www.piston.rs/ Pijul, a next-gen implementation of Darcs: http://pijul.org/ Xi, a high-performance text editor: https://github.com/google/xi-editor timely-dataflow, "a low-latency cyclic dataflow computational model" (i.e. big data shenanigans): https://github.com/frankmcsherry/timely-dataflow

There aren't that many things you can't do in Clojure, the main place Rust has an edge is in efficiency. I plan on doing an Avro implementation but other projects (mostly work-related) have a higher priority. In terms of larger projects, the Servo guys always seem to encourage people learning Rust to get involved. One of the projects I'm most interested in is Frank McSherry's timely/differental dataflow repos. I wanted a Rust implementation of Naiad when I first read the paper so I was quite pleased to see one of the authors do an implementation, even if it doesn't seem to be a full time pursuit. [1] https://github.com/frankmcsherry/timely-dataflow/ Most first-rust-projects that are announced on reddit/discourse seem to be games (Piston), simple web apps, raytracers, or datastructures.

You can contribute to: https://github.com/frankmcsherry/timely-dataflow https://github.com/frankmcsherry/differential-dataflow Or, just tell your friends. :) Better yet, write some python / pandas / dataframes / whatever_the_cool_kids_need layer on top, and rule the next big data drama cycle.

Shameless self-promotion for big data in Rust: https://github.com/frankmcsherry/timely-dataflow https://github.com/frankmcsherry/differential-dataflow Nothing much useful to contribute, except that they mostly work, are largely unsafe-free (unsafe in some sorting, and a Drain replacement), and build on 1.0 stable.