jlpkg VS Pluto.jl

You can expose it as a CLI tool if you wish: https://github.com/fredrikekre/jlpkg

So we discuss this briefly on our FAQ but let me try to expand on it.

Our goal is to make a modern literate programming tool. On a surface level, a tool like that would end up looking very similar to Jupyter, though with better features. We've mentioned some things we'd like to have in this final tool in our README and also in the post above.

Our first thought was to make a tool from scratch. The challenge was, it's very hard to get people to switch and so, we had to go where people already are - that meant Jupyter.

We could've made this one feature an extension with some difficulty (in-fact, our early experiments, we started by making an extension). It would have some downsides - we wouldn't have granular control over certain core Jupyter behaviours like we do right now (for eg, we wanted to allow creating hidden folders to store some files). But we probably could have made a 95% working version of Pretzel work as a jupyter extension.

The bigger reason we chose to fork was because down the line, we want to completely change the code execution model to being DAG based to allow for reproducible notebooks (similar to https://plutojl.org/ for eg). Similarly, we want to completely remove Codemirror and replace it with Monaco (the core editor engine in VSCode) to provide a more IDE like experience in Jupyter. These things simply couldn't have been done as extensions.

I thought that notebook based development and package based development were diametrically opposed in the past, but Pluto.jl notebooks have changed my mind about this.

A Pluto.jl notebook is a human readable Julia source file. The Pluto.jl package is itself developed via Pluto.jl notebooks.

https://github.com/fonsp/Pluto.jl

Also, the VSCode Julia plugin tooling has really expanded in functionality and usability for me in the past year. The integrated debugging took some work to setup, but is fast enough to drop into a local frame.

https://code.visualstudio.com/docs/languages/julia

Julia is the first language I have achieved full life cycle integration between exploratory code to sharable package. It even runs quite well on my Android. 2023 is the first year I was able to solve a differential equation or render a 3D surface from a calculated mesh with the hardware in my pocket.

Re Julia there is also pluto.jl that is another notebook-like environment for julia. It's been a few years since I played with it but it looked cool, for example it handles state differently so you don't get into the same messes as with ipython notebooks. https://plutojl.org/

For this, Notebooks are often used. Julia offers a uniquely nice and interactive Pluto notebook for the web https://github.com/fonsp/Pluto.jl

I believe this is what Pluto sets out to do for Julia.

I used it as part of the “Computational Thinking” with Julia course a year or two back. Even then the beta software was very good and some of the demos the Pluto dev showed were nothing short of amazing

https://plutojl.org/

I think what you want is Pluto!