desktop
nx
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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.
desktop
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Joy of Elixir
Exciting work is happening in all of these areas...
> desktop
Elixir Desktop: https://github.com/elixir-desktop/desktop
> mobile development
LiveView Native: https://www.youtube.com/watch?v=dnDGh_Jmw-s
> front end web
LiveView?
> command line tools
Mix.Install: https://thinkingelixir.com/elixir-1-12-and-your-first-mix-in...
How about numerical computing / machine learning: https://github.com/elixir-nx/nx/tree/main/nx
Embedded: "yes there's Nerves". Exactly?
- Elixir – Phoenix LiveView Native
- Elixir Desktop: Win, macOS, Linux, Android Apps with OTP and Phoenix.LiveView
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Ask HN: So, what's up with Phoenix (web framework)?
I think you may be looking for this neat library: https://github.com/elixir-desktop/desktop
Although to be honest it boggles my that it's possible to accomplish this on iOS.
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Is there a way to create client-side interactivity like Vue or React with only Elixir?
One option might be to use something like this - https://github.com/elixir-desktop/desktop - and create an executable that can be downloaded and would work offline (the Phoenix server would run inside the application itself, but would not require an internet connection).
- Erlang/OTP 25 has been released
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elixir desktop
We are trying to see what elixir deskop has to offer in terms of mobile application.. we heard that with elixir desktop you can build mobile apps for both android and ios.. so basically iam just trying to gain some information on how it works.. what are the possibilities or limitations.. otherwise Primarily I build mobile apps using native kotlin or flutter sometimes..
- GitHub - elixir-desktop/desktop: Elixir library to write Windows, macOS, Linux, Android apps with OTP24 & Phoenix.LiveView
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Is it possible to create an iOs app in Elixir? And if yes, than what framework is needed?
But if your goal is to develop a purely client side app with elixir, I'm afraid that the only option may be to wait for [elixir-desktop](https://github.com/elixir-desktop/desktop) to mature.
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Phoenix LiveView App-> iOS/Android App
There is this new project https://github.com/elixir-desktop/desktop
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
What are some alternatives?
livebook - Automate code & data workflows with interactive Elixir notebooks
Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications
turbo-ios - iOS framework for making Turbo native apps
gleam - ⭐️ A friendly language for building type-safe, scalable systems!
hyper-express - High performance Node.js webserver with a simple-to-use API powered by uWebsockets.js under the hood.
axon - Nx-powered Neural Networks
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
dplyr - dplyr: A grammar of data manipulation
brook - A cross-platform programmable network tool
explorer - An open source block explorer
transport-site - Rendre disponible, valoriser et améliorer les données transports
fib - Performance Benchmark of top Github languages