pgsink VS pyodide

This is a really awesome project. I’ve used it on https://github.com/lawrencejones/pgsink to generate type safe bindings to the Postgres catalog tables, along with a few of the tables the project maintains itself.

pgx is really good: it's what I used to write logical decoders in https://github.com/lawrencejones/pgsink

It used to be that companies would write their own hacky scripts to perform this extraction - I've had terrible incidents caused by ETL database triggers in the past, and even built a few generic ETL tools myself.

Postgres change-capture device that supports high-throughput and low-latency capture to a variety of sinks (at first release, just Google BigQuery):

https://github.com/lawrencejones/pgsink

I know there's debezium and Netflix's dblog, but this project aims to be much simpler.

Forget about kafka and any other dependency: just point it at Postgres, and your data will be pushed into BigQuery. And for people with highly-performance-sensitive databases, the read workload has been designed with Postgres efficiency in mind.

I'm hoping pgsink could be a gateway drug to get small companies up and running with a data warehouse. If your datastore of choice is Postgres, it's a huge help to replicate everything into an analytics datastore. A similar tool has helped my company extract expensive work out of our primary database, which is super useful for scaling.

The project is 90% there, about 10hrs and some testing away from being useable. Once there, I'll be hitting up some start-up friends and seeing if they want to give it a whirl.

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.