Let us know links to the issues that we should post.
Rusoto, the Rust AWS SDK, is looking for maintainers. If you’re looking to learn more about Amazon Web Services, code generation in Rust or want to check out one of the bigger public code bases around (claim not validated in any manner), come check out the repository. The CONTRIBUTING file has instructions for getting started.
If documentation is more your bag, we’ve got https://rusoto.org/ which is a gitbook companion for the project. The source is on GitHub as a project under the Rusoto org on GitHub.
I’m available for mentoring.
Basically, if there is an issue that does not have an assignee, we are seeking help for implementing that feature.
I’d suggest creating a new issue looking for maintainers with information on how to contact and we’ll link to that.
Thanks, I’ve added an issue: https://github.com/rusoto/rusoto/issues/593 .
Hi. I’m looking for people interested in crypto, command line and backups. Rdedup started as a little project for backup deduplication, but PR after PR, it’s growing into very efficient and robust multipurpose deduplication machine. Check the github repo: https://github.com/dpc/rdedup , read github issues, read an article on how high performance through parallelization is achieved: http://dpc.pw/blog/2017/04/rusts-fearless-concurrency-in-rdedup/ and feel free to ask questions on gitter channel!
We are looking for people to join our mission of building an event sourcing database engine. Event sourcing is a pattern in which, instead of storing the current state of the data and using it as a source of truth, one should immutably record the full series of actions taken and designate that log as a source of truth instead. This approach can simplify tasks in complex, changing domains by avoiding the need to synchronize data models and domain models. It also provides great auditing and transactional capabilities, as well as opportunities for lossless error correction.
The core ideas behind our project (PumpkinDB) stem from the so called lazy event sourcing approach which is based on storing and indexing events while delaying domain binding for as long as possible. The intention of this database is to be a building block for different kinds of event sourcing systems, ranging from the classic one (using it as an event store) all the way to the lazy one (using indices) and anywhere in between. It’s also possible to implement different approaches within a single database for different parts of the domain.
We’ve been previously nominated as a Crate of the Week and have grown our followers base significantly since the first announcement.
We are gearing up for the next release and have recently pushed out some exciting bits (like SPDK bindings for Rust for our future direct NVMe storage module). We are working on examples and articles to explain our ideas in more details to make the project more accessible in the short term.
As per our contributions guidelines:
- We merge pull requests rapidly (try!)
- We are open to diverse ideas
- We prefer code now over consensus later
I’ve written up two Maud issues that should be suited for new contributors:
I wrote up a potential optimization for one of
bindgen's internal phases:
Currently, we end up duplicating a lot of computations, and with a carefully placed bitset, we could avoid the duplication completely. Details in the issue!
Two from tokei
Help from anyone who has experience working with musl libc and/or OpenSSL and/or ARM would be greatly appreciated adding OpenSSL support to cross targets that are currently missing it:
People are needed to help fill out the log crate evaluation, write cookbook recipes for the log crate, and generally offer their opinions.
I’m starting a recommender systems framework written in Rust and I’d love to work with people interested in this topic. There are a bunch of fairly easy issues here: https://github.com/z1mvader/quackin/issues that only requre some basic knowledge on recommender systems. The project itself is pretty new and young so I hope that it will be a good space to discuss recommender systems and machine learning topics as well.