tangram
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daisyui
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tangram | daisyui | |
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22 | 244 | |
1,310 | 29,945 | |
- | - | |
9.6 | 9.8 | |
almost 2 years ago | 4 days ago | |
Rust | Svelte | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tangram
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Writing the fastest GBDT libary in Rust
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.
- Any role that Rust could have in the Data world (Big Data, Data Science, Machine learning, etc.)?
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Examples of Rust front-end web works
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
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Multi-language library support: Is it possible?
Check out https://github.com/tangramdotdev/tangram.
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Ask HN: Who is hiring? (October 2021)
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].
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Seed โ A Rust front-end framework for creating fast and reliable web apps
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.
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How far along is the ML ecosystem with 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/
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Show HN: Tangram โ Train, Deploy, and Monitor ML Models in Go/JS/Ruby/Rust/More
Great idea! We definitely want to do this. We have an open issue to track it: https://github.com/tangramdotdev/tangram/issues/28.
Hi HN! We are Isabella and David, and we're excited to share Tangram, our attempt to make it easy for programmers who are not machine learning experts to train, deploy, and monitor machine learning models. With Tangram, developers train a model from a CSV file on the command line, make predictions with libraries for Elixir, Go, JavaScript, Python, Ruby, and Rust, and learn about their models and monitor them in production with a convenient web app. Watch the video on the homepage: https://www.tangram.dev, or check it out on GitHub: https://github.com/tangramdotdev/tangram.
Over the past few months we have been working closely with a handful of early users. A team at a small company had a TensorFlow model deployed as a Flask service consumed by their Elixir app. They replaced it with a Tangram model because they didn't want to maintain a server separate from their monolith. A team of front end engineers at a large company was looking for a way to to train and deploy models on their own, without the overhead of involving their data scientists, machine learning engineers, or backend engineers. They trained a model on their own and embedded it directly in their React front-end with the Tangram JavaScript library that makes predictions with WebAssembly.
Tangram is written entirely in Rust, from the core machine learning algorithms, to the bindings for each language, to the front and back end of the web application. We have benefited from Rust's fast performance, strong typing, convenient tooling, and high quality libraries (serde, tokio, hyper, sqlx, and more).
We hope to make Tangram a sustainable business with the "open core" business model. The CLI and language libraries are MIT licensed, while the web application is source available, free to use for testing, but requires a paid license to use in production.
We would love to hear your feedback. Give it a try and let us know what you think!
daisyui
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Building a Fast, Efficient Web App: The Technology Stack of PromptSmithy Explained
While I have experience with Tailwind and frontend development, I donโt really have the patience to use it. I usually end up using something like Mantine, which is a complete component library UI kit, or Daisy UI, which is a component library built on top of Tailwind. Shadcn/ui is quite similar to Daisy in this sense, but being able to customize the individual components, since they get installed to your components folder, made development more streamlined and more customizable. On top of that being able to change my components style with natural language thanks to v0 made development super easy and fast. Shadcn may be too minimalist of a style for some, but thanks to all the components being local, you can customize them quickly and easily!
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The Bulma CSS framework reaches 1.0
https://daisyui.com is a really great middle groundโyou can move as fast as you would in Bulma, then drop down into the weeds with TW if you need it.
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Tailwind Color Palette Generator
If you're looking for grab and go components, Daisy UI or Flowbite might be more your speed, I've used both with minimal headache.
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DaisyUI + Alpine.js + Codehooks.io - the simple web app trio
This guide is tailored for front-end developers looking to explore the smooth integration of DaisyUI's stylish components, Alpine.js's minimalist reactive framework, and the straightforward back-end capabilities of Codehooks.io.
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Shadcn: Beautifully designed components that you can copy-paste into your apps
Others:
- https://daisyui.com/
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โกTop GitHub Repositories for UI Components
๐ Site โญ GitHub
- Catalyst โ Tailwind CSS Application UI Kit
- How long have you been at it and how many clients do you have?
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So should I be using a component library?
If you still do want some premade components, you have things like https://daisyui.com and https://ui.shadcn.com, which can be good to look into.
What are some alternatives?
flowbite - Open-source UI component library and front-end development framework based on Tailwind CSS
headlessui - Completely unstyled, fully accessible UI components, designed to integrate beautifully with Tailwind CSS.
shadcn/ui - Beautifully designed components that you can copy and paste into your apps. Accessible. Customizable. Open Source.
Material UI - Ready-to-use foundational React components, free forever. It includes Material UI, which implements Google's Material Design.
theme-change - Change CSS theme with toggle, buttons or select using CSS custom properties and localStorage
fullcalendar - Full-sized drag & drop event calendar in JavaScript
nextui - ๐ Beautiful, fast and modern React UI library.
mantine - A fully featured React components library
antd - An enterprise-class UI design language and React UI library
django-tailwind - Django + Tailwind CSS = ๐
TOAST UI Editor - ๐๐ Markdown WYSIWYG Editor. GFM Standard + Chart & UML Extensible.
merakiui - Tailwind CSS components that support RTL languages & fully responsive based on Flexbox & CSS Grid with elegant Dark Mode ๐ โ๏ธ.