livebook VS interactive

How's the maturity compared to Livebook?

https://livebook.dev/

2) Start using IEx or LiveBook for any day to day scripting that I would normally use Python for.

Definitely look into Livebook and Elixir, and the whole ecosystem around it, including:

- https://github.com/elixir-nx/axon Nx-powered Neural Networks

- https://github.com/elixir-nx/nx Multi-dimensional arrays (tensors) and numerical definitions for Elixir

- https://github.com/elixir-nx/scholar Traditional machine learning on top of Nx

- https://github.com/elixir-nx/bumblebee Pre-trained Neural Network models in Axon (+ Models integration)

- https://github.com/elixir-explorer/explorer Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir

- https://fly.io/blog/rethinking-serverless-with-flame/ (for offloading large work to remote containers)

- https://www.youtube.com/watch?v=RABXu7zqnT0 InstructorEx

And of course Livebook (https://livebook.dev)

I have always considered helping the community grow into a diverse ecosystem to be my main responsibility (the Python community being a great example here).

This particular effort started because some people got together and realized that we could do it! Do it in a way that felt part of Elixir and not just a bunch of bindings to C libraries.

We honestly never had the expectation that we had to beat Python (otherwise we would simply not have started). Early on, we were not even sure if we could be better at one single thing. However, 3 years later, we do have features that would be quite hard or impossible to implement in Python. For example:

* Nx Serving - https://hexdocs.pm/nx/Nx.Serving.html - allows you to serve machine learning models, across nodes and GPUs, with concurrency, batching, and partitioning, and it has zero dependencies

* Livebook - https://livebook.dev - brings truly reproducible workflows (hard to achieve in Python due to mutability), smart cells, and other fresh ideas

* A more cohesive ecosystem - Nx, Scholar, Explorer, etc all play together, zero-copy and all, because they are the only players in town

Of course, there are also things that Python can do, that we cannot:

* In Python, integration with C code is easier, and that matters a lot in this space. Python also allows C to call Python, and that's just not possible in the Erlang VM

* Huge ecosystem, everything happens in Python first

At the end of the day, what drives me is that the Erlang VM offers a unique set of features, and combining them with different problems have historically lead to interesting and elegant solutions. Which drives more people to join, experiment, run in production, and create new things.

To get started you need a running instance of Livebook

.NET Interactive

I wrote Data Science in .NET with Polyglot Notebooks to help experienced .NET developers replicate my journey into data science by showing them how Polyglot Notebooks and .NET Interactive help them perform interactive and iterative experiments using the .NET technologies they already know and love.

Polyglot Notebooks / .NET Interactive – A collection of kernels integrated into Jupyter Notebooks allowing for additional languages such as C#, F#, PowerShell, and SQL.

All of this will be accomplished inside of a single Polyglot Notebook. If you're not familiar with Polyglot Notebooks, they're a technology built on top of Jupyter Notebooks that allow you to use additional language kernels, including a F# Kernel. This lets you run interactive data science experiments in a single notebook as shown here in VS Code:

I use .NET on Linux and the experience with Rider has been great. The workflow transfers really well between Mac, Windows, and Linux, and everything works the way you expect. The only problems I run into are that there are still things that are Windows focused. For example MAUI does not run on Linux which is a shame because we could use another cross platform GUI.

There are still bugs, for example I ran into one with Polyglot Notebooks not working on Manjaro or Pop!_OS https://github.com/dotnet/interactive/issues/3159

First of all, if you have a small amount of code that lives in an individual C# file and you wanted to reference it in your notebook, you can do this via the #!import magic command as shown below:

My 2 cents: use a Personal Access Token instead of a password, it is much safer (even though not 100% safe). Some references: https://github.com/dotnet/interactive/discussions/1340 https://learn.microsoft.com/en-us/azure/devops/organizations/accounts/use-personal-access-tokens-to-authenticate

See also https://github.com/dotnet/interactive

U have Powershell notebooks https://github.com/dotnet/interactive