notes VS pyodide

I've been doing something similar for ~20 years at: https://github.com/nickjj/notes

    - Running `notes` will open this month's notes for YYYY_MM.txt

I use a very command line focused approach with https://github.com/nickjj/notes.

Since about 2001 I used YYYY-MM.txt plain text files and have a shell script to help create notes in the most friendly way I could think of from the command line at https://github.com/nickjj/notes.

Totally works fine for a knowledge log when you're streaming high level details. I still use it today.

But when you want to really go all-in with in-depth notes it's tricky because in 1 month's time if you're hardcore deep in the woods of learning, applying and using something you're going to end up with hundreds of concepts from an assorted set of tools and it kind of stinks to have all of that info sitting in 1 file. Think about using something like Kubernetes. That's really Kubernetes, Kustomize / Helm, EKS, various cloud hosting details (networking, etc.), Terraform and ton of super useful commands / context. Details you for sure want recorded for later.

For this type of info I've been building up a knowledge base with https://obsidian.md/. It's really nice and I highly recommend it. It's been working well for keeping things reasonably categorized without wasting a lot of time on the details around keeping links and tags up to date. It also has Vim mode that's good enough where day to day writing feels natural.

Did you end up automating the entries?

For example, I have a command line note taking script at https://github.com/nickjj/notes.

It creates a YYYY-MM-DD.txt file and doesn't include time stamps but it would be a 1 line change to make each entry get timestamped. I didn't do that because personally I'm more interested in monthly notes not per minute.

But I do think removing the barrier of creating entries is an important step with jotting things down, this way you can focus on what you want to write and not the boilerplate.

A whole bunch of little things, mainly command line tools.

Most of them are open source and also have extensive documentation and a screencast video going over them.

In no specific order:

- https://github.com/nickjj/notes

- https://github.com/nickjj/invoice

- https://github.com/nickjj/wait-until

And a few recent little scripts to solve specific things:

- https://nickjanetakis.com/blog/using-ffmpeg-to-get-an-mp3s-d...

- https://nickjanetakis.com/blog/a-shell-script-to-keep-a-bunc...

- https://nickjanetakis.com/blog/bash-aliases-to-prepare-recor...

Along similar lines, nickjj also has a similar (but bash) notes script at:

https://github.com/nickjj/notes

While I don't use it personally there's: https://obsidian.md/

It's cross platform and works offline. You write markdown and it produces a visual graph of your data. It supports interlinking notes, tags and images too.

Plain text notes[0] work best for me but I'd probably use Obsidian if I wanted to see things visually. When I tried it out briefly it was really solid.

[0]: https://github.com/nickjj/notes

We implemented an in-browser Python editor/interpreter built on Pyodide over at Comet (our users are data scientists who need to build custom visualizations quite often, and the most familiar language for most of them is Python).

One of the issues you'll run into is that Pyodide only works by default with packages that have pure Python wheels available. The team has developed support for some libraries with C dependencies (like scikit-learn, I believe), but frameworks like PyTorch are particularly thorny (see this issue: https://github.com/pyodide/pyodide/issues/1625 )

We ended up rolling out a new version of our Python visualizations that runs off-browser, in order to support enough libraries/get the performance we need: https://www.comet.com/docs/v2/guides/comet-ui/experiment-man...

Thank you! Yes, one of the items in the Roadmap is support for Pyodide (https://github.com/pyodide/pyodide) for running in-browser python on the results of each of the code blocks! This should allow most ML libs to be usable in-browser! This is pretty high-up on our priority list.

If I understand correctly, WASM only makes sense for compiled languages, you can run the python interpreter in WASM of course[1], but that will be at a significant performance disadvantage to the native javascript interpreter, and it's also something that has to be loaded every time you load the website.

[1]: https://github.com/pyodide/pyodide

If you absolutely need something comparable to Sympy, then one option might be to figure out how to best call Sympy from Rust. e.g. - RustPython, although it seems like Sympy isn't supported yet - Pyodide, and figuring out how to run it outside of a web browser. Probably also not very easy. - PyPy, and having a pretty simple Python binary for every platform - ...

For running programming languages other than JavaScript in the browser there is Emscripten and WebAssembly. There is v86, where a Linux build is compiled to WASM. Folks have written QuickJS into a Linux build compiled to WASM, Node.js into the Linux buildroot https://github.com/cemalgnlts/now, so Python or CPython can be written to the image and loaded into the browser as WASM as well https://github.com/pyodide/pyodide.

There's a Python runtime that runs on WebAssembly (https://github.com/pyodide/pyodide). I have no idea what it's like, I've never used it.

Still in a quest to provide some tooling to quickly compose documentation websites: https://github.com/synw/docdundee . As I have tons of libs to document and was tired of managing restructured language for readthedocs I started with this, and now it has executable Python examples in the frontend via a Pyodide wrapper composable: usePython

This project's brand new and a lil hacky, but I've already reached out to the scikit-learn team, and they recommended that I experiment with using Pyodide as an alternative backend for the Python bridge.