tangram VS Seed

Head over to https://www.tangram.dev and give it a try!

In this post, we will go over how we optimized our Gradient Boosted Decision Tree library. This is based on a talk that we gave at RustConf 2021: Writing the Fastest Gradient Boosted Decision Tree Library in Rust. The code is available on GitHub.

You can check out the Tangram Ruby Gem. We built it using Ruby FFI and the source is available on our GitHub repo.

We are using Rust for our web application and website at Tangram. You can view the source here: https://github.com/tangramdotdev/tangram/tree/main/crates/www. The website is at https://www.tangram.dev. We decided to write our own web framework because we needed server rendering and we wanted to use the builder pattern in creating components. Here is an example component for our Logo to get a sense of what this looks like: https://github.com/tangramdotdev/tangram/blob/main/crates/www/ui/logo.rs

Check out https://github.com/tangramdotdev/tangram.

Tangram | Senior Rust Programmer | Remote | https://www.tangram.dev

Tangram is an all in one machine learning framework designed for programmers. With Tangram, developers can train models and make predictions on the command line or with libraries for languages including Elixir, Go, JS, Python, Ruby, and Rust, and learn about their models and monitor them in production from a web application. To learn more about what the product does, watch the demo on the homepage at https://www.tangram.dev or check it out on GitHub at https://www.github.com/tangramdotdev/tangram.

We are looking to grow our engineering team with senior Rust programmers. We are currently based in Boston, MA but are looking to build a remote team. At Tangram, you'll get to work on everything from our core machine learning algorithms to writing front-end code in Rust! We are looking for developers with experience in Rust and familiarity with or willingness to learn machine learning concepts. If this sounds exciting, email me (Isabella, cofounder) at [email protected].

We chose to use Rust instead of TypeScript for the front end of https://github.com/tangramdotdev/tangram.

This allows us to:

* Share code with our server written in Rust.

I'm working on machine learning in Rust at Tangram. We currently only provide an implementation of linear models and gradient boosted decision trees but will move into exposing training of deep models in the future. You can check out Tangram here: https://github.com/tangramdotdev/tangram. You may also be interested in checking out Linfa https://github.com/rust-ml/linfa. If you're interested in the future of machine learning in Rust, check out Luca Palmieri's blog post: https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/

Practically every Rust web frontend I've seen takes a react-like approach, with "hooks" to store all of the state in. The now-abandoned Seed and Yew's struct components use a message-passing approach, where the state is stored as member variables on the struct representing the component that are updated based on messages dispatched by event handlers. There's also egui, which has a completely different paradigm that involves making the UI from scratch every frame based on the app's current state. It's not a web framework the same way as the others, but it can draw its UI to a web canvas just fine.

Sycamore, Yew, or Seed if you want a full-stack solution. (Or Leptos if you want something that's faster but less mature.)

An authentication system is an integral part of modern applications. It's so important that almost all modern applications have some sort of it. Because of their critical nature, such systems should be secure and should follow OWAP®'s recommendations on web security and password hashing as well as storage to prevent attacks such as Preimage and Dictionary attacks (common to SHA algorithms). To demonstrate some of the recommendations, we'll be building a robust session-based authentication system in Rust and a complementary frontend application. For this article series, we'll be using Rust's actix-web and some awesome crates for the backend service. SvelteKit will be used for the frontend. It should be noted however that what we'll be building is largely framework agnostic. As a result, you can decide to opt for axum, rocket, warp or any other rust's web framework for the backend and react, vue or any other javascript framework for the frontend. You can even use rust's yew, seed or some templating engines such as MiniJinja or tera at the frontend. It's entirely up to you. Our focus will be more on the concepts.

If you want to do fullstack/SPA stuff, check out Sycamore, Seed, and Yew.

If you want to do front-end SPA development, take a look at Yew, Seed, or Sycamore.

Aside from Blazor there's already some other projects like Yew (rust), seed (rust), asm-dom (C++) and vugu (Go) and more that have decent followings and activity. A lot more (especially managed languages) are waiting for some features to come online like wasm GC and host bindings (direct wasm access to browser apis which includes the DOM). It'll take a bit of time, but it'll get there eventually.

To click * https://crates.io/crates/percy * https://crates.io/crates/seed * https://crates.io/crates/perseus * https://crates.io/crates/sycamore

For desktop apps maybe check out Tauri . You can use it with a lot of (web)frontend options including yew/wasm (also Seed ) if you want to go 100% Rust. Actix and Rocket are options for web framework. Also have look at the Building a Command Line Program in the book. I found it really helpful since i am just starting to learn myself.

I haven't been keeping up with it, but have heard of it. If ibrecall correctly it was created by the developer that initially developed seed (https://seed-rs.org/)