kerkour.com
tangram
| kerkour.com | tangram | |
|---|---|---|
| 2 | 9 | |
| 456 | 348 | |
| 0.0% | - | |
| 4.5 | 9.1 | |
| 2 months ago | almost 3 years ago | |
| Rust | Rust | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
kerkour.com
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SQL and Rust
There are plenty: - diesel - famous example of what the Rust type system can get you beyond just "memory safety". My go-to choice for most projects. Having autocomplete for my database DSL is something I find it hard to go without. But it comes at a fairly high cost of confusing, generic-heavy code. - sqlx - also a very solid choice. You write SQL queries, which are optionally checked against a database instance at compile-time. A downside I've heard repeated a lot (by some fairly reputably figures) is that sqlx adds a fairly significant overhead to queries, and according to this issue is 7-70x slower than diesel. If the performance of your database is important to you, run some benchmarks and see if it's an issue - seaorm - a relatively new ORM, and I haven't used it much, but my initial impressions were that it was a little too "magic". Maybe it just reminded me too much of Spring Boot. I'm not sure. It's probably a totally fine library - postgres (or equivalent) - you can always just skip the ORM and use the database driver directly. Pretty nice for smaller projects, but totally viable for big projects too. Just a matter of personal preference
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How to implement worker pools in Rust
As usual, you can find the code on GitHub: github.com/skerkour/kerkour.com (please don't forget to star the repo 🙏).
tangram
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Tangram: Automated Machine Learning with Elixir
Homepage: https://www.tangram.xyz
- Tangram is an all-in-one automated machine learning framework
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Tangram: Automated Machine Learning in Rust
I opened an issue to track this: https://github.com/tangramxyz/tangram/issues/12. Please subscribe to the issue so you get notified when we implement it, which we hope will be soon.
- Tangram: Machine Learning in JavaScript
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Tangram: Automated Machine Learning with Go
I opened an issue to track adding support for hdf5 files: https://github.com/tangramxyz/tangram/issues/8.
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[P] Tangram: All-in-One Automated Machine Learning Framework
GitHub: https://github.com/tangramxyz/tangram
What are some alternatives?
shisho - Lightweight static analyzer for several programming languages
tangram - Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
binserve - A fast production-ready static web server with TLS (HTTPS), routing, hot reloading, caching, templating, and security in a single-binary you can set up with zero code.
rust-plus-golang - Rust + Go — Call Rust code from Go using FFI
sandwich - Sandwich is a multi-platform, multi-language, open-source library that provides a simple unified API for developers to use (multiple) cryptographic libraries in their applications.
PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.
wtpsplit - Code for Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation
myblog - Personal blog written in Rust, using salvo and sqlx
shamichan - anonymous realtime imageboard focused on high performance and transparent moderation
hypercube - HyperCube is a revolutionary, high-performance decentralized computing platform. HyperCube has powerful computing capabilities to provide high-performance computing power and large-scale data storage support for VR, AR, Metaverse, Artificial Intelligence, Big Data, and Financial Applications.🛰
code - Source code for the book Rust in Action