explorer VS nushell

The Explorer library [0] in Elixir uses Polars underneath it.

[0] https://github.com/elixir-explorer/explorer

To ensure you do not miss this: LiveBook comes with a Vega Lite integration (https://livebook.dev/integrations -> https://livebook.dev/integrations/vega-lite/), which means you get access to a lot of visualisations out of the box, should you need that (https://vega.github.io/vega-lite/).

In the same "standing on giant's shoulders" stance, you can use Explorer (see example LiveBook at https://github.com/elixir-explorer/explorer/blob/main/notebo...), which leverages Polars (https://www.pola.rs), a very fast DataFrame library and now a company (https://www.pola.rs/posts/company-announcement/) with 4M$ seed.

Already exists. Check out https://github.com/elixir-nx/explorer which provides a tidyverse-like API in Elixir using polars as the back end.

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!

There's a package in the Nx ecosystem called Explorer (https://github.com/elixir-nx/explorer). It uses bindings for the rust library, polars, which is much more betterer than Pandas.

FWIW around April this year I started using erlport with python polars in a production ETL app because explorer didn't have the features I needed at the time.

Machine learning is rapidly expanding within the Elixir ecosystem, with tools such as Nx, Axon, and Explorer being used both by individuals and companies such as Amplified, as mentioned above.

These are just three small examples of what this shell written in Rust allows. The features are many and many more, but I'll leave it up to you to discover and enjoy them; I'm currently playing around with it and it's giving me a lot of satisfaction and immediacy, now it has a fixed place among the tools I use when working! The project is Open Source, so if you want to contribute, I invite you, as always, to do so, I leave you the link to the repo here!

Any thoughts on fish as compared to nushell [0]? It's similar to PowerShell in its philosophy and is also written in Rust.

[0] https://github.com/nushell/nushell

> In PowerShell, structured output is the default and it seems to work very well.

PowerShell goes a step beyond JSON, by supporting actual mutable objects. So instead of just passing through structured data, you effectively pass around opaque objects that allow you to go back to earlier pipeline stages, and invoke methods, if I understand correctly: https://learn.microsoft.com/en-us/powershell/module/microsof....

I'm rather fond of wrappers like jc and libxo, and experimental shells like https://www.nushell.sh/. These still focus on passing data, not objects with executable methods. On some level, I find this comfortable: Structured data still feels pretty Unix-like, if that makes sense? If I want actual objects, then it's probably time to fire up Python or Ruby.

Knowing when to switch from a shell script to a full-fledged programming language is important, even if your shell is basically awesome and has good programming features.

Maybe if the "popular" shells, but http://www.nushell.sh/ is looking better and better

Yeah agreed, especially now that PowerShell is available cross-platform.

Nushell[1] also seems like a promising alternative, but I haven’t had a chance to play with it yet.

[1]: https://www.nushell.sh/

I also discovered an existing discussion[1] related to this topic which includes a link[2] to a "helper to call nushell nuon/json/yaml commands from bash/fish/zsh" and a comment[3] that the current nushell dev focus is "on getting the experience inside nushell right and [we] probably won't be able to dedicate design time to get the interface of native Nu commands with an outside POSIX shell right and stable.".

[0] https://gitlab.com/RancidBacon/notes_public/-/blob/main/note...

[1] "Expose some commands to external world #6554": https://github.com/nushell/nushell/issues/6554

[2] https://github.com/cruel-intentions/devshell-files/blob/mast...

[3] https://github.com/nushell/nushell/issues/6554#issuecomment-...

I appreciate what projects like Nushell and Murex are trying to address, but having a saner scripting language and passing structured data in pipelines is not worth the drawbacks for me.

For one, Bash scripting is not so bad if you set some sane defaults and use ShellCheck. Sure, it has its quirks, but all languages do. Even so, the same golden rule applies: use a "real" programming language if your problem exceeds a certain level of complexity. This is relative and will depend on your discomfort threshold, but using the right tool for the job is always a good practice. No matter how good the shell language is, I would hesitate to write and maintain a complex project in it.

And for general QoL improvements with interactive use, Zsh is a fine shell, while still being POSIX compatible.

[1]: https://github.com/nushell/nushell/blob/main/crates/nu-comma...

[2]: https://github.com/nushell/nushell/issues/5027

[3]: https://github.com/nushell/nushell/issues/9310

I found nushell (https://www.nushell.sh) to be an impressive replacement "bash" for Windows

In terms of philosophy, think "Powershell but actually intuitive" : Every data is structured but command names are what you expect them to be. I usually don't even need to look at the documentation.

I liked it so much that I also replaced my shell on Linux with it, so I have the same terminal experience across all OSes