nx
clojerl
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nx | clojerl | |
---|---|---|
36 | 12 | |
2,467 | 1,633 | |
1.4% | 0.3% | |
9.3 | 5.1 | |
about 17 hours ago | 6 months ago | |
Elixir | Erlang | |
- | Eclipse Public License 1.0 |
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.
nx
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Unpacking Elixir: Concurrency
Does nx not work for you? https://github.com/elixir-nx/nx/tree/main/nx#readme
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A LiveView Is a Process
It is historically not great at number computing. This is being addressed by a relatively new project called Nx. https://github.com/elixir-nx/nx
It is not the right choice for CPU intensive tasks like graphics, HFT, etc. Some companies have used Rust to write native extensions for those kinds of problems. https://discord.com/blog/using-rust-to-scale-elixir-for-11-m...
- How does Elixir stack up to Julia in the future of writing machine-learning software?
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Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R
José from the Livebook team. I don't think I can make a pitch because I have limited Python/R experience to use as reference.
My suggestion is for you to give it a try for a day or two and see what you think. I am pretty sure you will find weak spots and I would be very happy to hear any feedback you may have. You can find my email on my GitHub profile (same username).
In general we have grown a lot since the Numerical Elixir effort started two years ago. Here are the main building blocks:
* Nx (https://github.com/elixir-nx/nx/tree/main/nx#readme): equivalent to Numpy, deeply inspired by JAX. Runs on both CPU and GPU via Google XLA (also used by JAX/Tensorflow) and supports tensor serving out of the box
* Axon (https://github.com/elixir-nx/axon): Nx-powered neural networks
* Bumblebee (https://github.com/elixir-nx/bumblebee): Equivalent to HuggingFace Transformers. We have implemented several models and that's what powers the Machine Learning integration in Livebook (see the announcement for more info: https://news.livebook.dev/announcing-bumblebee-gpt2-stable-d...)
* Explorer (https://github.com/elixir-nx/explorer): Series and DataFrames, as per this thread.
* Scholar (https://github.com/elixir-nx/scholar): Nx-based traditional Machine Learning. This one is the most recent effort of them all. We are treading the same path as scikit-learn but quite early on. However, because we are built on Nx, everything is derivable, GPU-ready, distributable, etc.
Regarding visualization, we have "smart cells" for VegaLite and MapLibre, similar to how we did "Data Transformations" in the video above. They help you get started with your visualizations and you can jump deep into the code if necessary.
I hope this helps!
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Elixir and Rust is a good mix
> I guess, why not use Rust entirely instead of as a FFI into Elixir or other backend language?
Because Rust brings none of the benefits of the BEAM ecosystem to the table.
I was an early Elixir adopter, not working currently as an Elixir developer, but I have deployed one of the largest Elixir applications for a private company in my country.
I know it has limits, but the language itself is only a small part of the whole.
Take ML, Jose Valim and Sean Moriarity have studied the problem, made a plan to tackle it and started solving it piece by piece [1] in a tightly integrated manner, it feels natural, as if Elixir always had those capabilities in a way that no other language does and to put the icing on the cake the community released Livebook [2] to interactively explore code and use the new tools in the simplest way possible, something that Python notebooks only dream of being capable of, after a decade of progress
That's not to say that Elixir is superior as a language, but that the ecosystem is flourishing and the community is able to extract the 100% of the benefits from the tools and create new marvellously crafted ones, that push the limits forward every time, in such a simple manner, that it looks like magic.
And going back to Rust, you can write Rust if you need speed or for whatever reason you feel it's the right tool for the job, it's totally integrated [3][4], again in a way that many other languages can only dream of, and it's in fact the reason I've learned Rust in the first place.
The opposite is not true, if you write Rust, you write Rust, and that's it. You can't take advantage of the many features the BEAM offers, OTP, hot code reloading, full inspection of running systems, distribution, scalability, fault tolerance, soft real time etc. etc. etc.
But of course if you don't see any advantage in them, it means you probably don't need them (one other option is that you still don't know you want them :] ). In that case Rust is as good as any other language, but for a backend, even though I gently despise it, Java (or Kotlin) might be a better option.
[1] https://github.com/elixir-nx/nx https://github.com/elixir-nx/axon
[2] https://livebook.dev/
[3] https://github.com/rusterlium/rustler
[4] https://dashbit.co/blog/rustler-precompiled
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Distributed² Machine Learning Notebooks with Elixir and Livebook
(including docs and tests!): https://github.com/elixir-nx/nx/pull/1090
I'll be glad to answer questions about Nx or anything from Livebook's launch week!
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Why Python keeps growing, explained
I think that experiment is taking shape with Elixir:
https://github.com/elixir-nx/nx
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Does Nx use a Metal in the Backend ?
However the issue here at Nx https://github.com/elixir-nx/nx/issues/490 is already closed.
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Do I need to use Elixir from Go perspective?
Outside of that, Elixir can be used for data pipelines, audio-video processing, and it is making inroads on Machine Learning with projects like Livebook, Nx, and Bumblebee.
- Elixir – HUGE Release Coming Soon
clojerl
- Really hard convincing colleague to switch to Clojure
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Clojure Scripting on Node.js
Basically, you take a programming language and make it work on a platform that meant to be programmed using a different PL. Clojure is hosted by design - it's not Java, but can be used to program for JVM. It ain't Javascript, but can be used to target nodejs and browser; not an [official] CLR language, but you can write .Net programs. You can use Clojure to make Flutter apps with ClojureDart. You can integrate Python into Clojure with libpython-clj. Or write Clojure to target Erlang/OTP; or Rust; or R; There's even a clojure-like language for Lua - Fennel.
There's something about Clojure people like so much, they want it to work atop any platform.
https://github.com/Tensegritics/ClojureDart
https://github.com/clj-python/libpython-clj
https://github.com/clojerl/clojerl
https://github.com/clojure-rs/ClojureRS
https://github.com/scicloj/clojisr
https://fennel-lang.org
- On Repl-Driven Programming
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Which Programming language libraries can Clojure use as its own?
But there are also unofficial implementations—i.e. not JVM, JS, .NET—of Clojure for other host environments, e.g. Clojerl. And of course nearly everything /u/borkdude touches interops with something in some way.
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CL vs Racket
Tail call optimization/elimination isn't a property of functional languages - there are tons of non-functional languages with it, like Lua or even C, when compiled with -O3, to name a few. Besides, Clojure is a hosted language, so it shares the platform characteristics, and recur is a language-way of providing a construct for tail call looping. Clojure on BEAM for example, supports tail call elimination, because BEAM does. And Beam is a quite functional environment ;)
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Clojure, but without the JVM?
Clojerl: an implementation for the Erlang VM. The reader conditional is :clje.
- Clojerl 0.9.0 is out with features released in Clojure 1.9, including Spec
- Elixir Protocols vs. Clojure Multimethods
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haskell elixr or clojure
There's also an unofficial BEAM VM implementation
- London Clojurians talk: Clojure - JVM + BEAM = Clojerl (by Juan Facorro)
What are some alternatives?
Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications
cloture - Clojure in Common Lisp
gleam - ⭐️ A friendly language for building type-safe, scalable systems!
meander - Tools for transparent data transformation
axon - Nx-powered Neural Networks
joker - Small Clojure interpreter, linter and formatter.
dplyr - dplyr: A grammar of data manipulation
protocol_ex - Elixir Extended Protocol
explorer - An open source block explorer
lazy-seq - Lazy sequences for Fennel and Lua (mirror)
fib - Performance Benchmark of top Github languages
awesome-clojure-likes - Curated list of Clojure-like programming languages.