datasette-lite VS pyodide

Also see: https://github.com/simonw/datasette-lite

https://github.com/simonw/datasette-lite :

> You can use this tool to open any SQLite database file that is hosted online and served with a `access-control-allow-origin: ` CORS header. Files served by GitHub Pages automatically include this header, as do database files that have been published online using `datasette publish`.*

> [...] You can paste in the "raw" URL to a file, but Datasette Lite also has a shortcut: if you paste in the URL to a page on GitHub or a Gist it will automatically convert it to the "raw" URL for you

> To load a Parquet file, pass a URL to `?parquet=`

> [...] https://lite.datasette.io/?parquet=https://github.com/Terada...*

There are various *-to-sqlite utilities that load data into a SQLite database for use with e.g. datasette. E.g. Pandas with `dtype_backend='arrow'` saves to Parquet.

datasette plugins are written in Python and/or JS w/ pluggy:

Datasette Lite might be even better for this - you can construct URLs that link directly to examples: https://github.com/simonw/datasette-lite

There are some amazing things for SQLite in the browser especially if you're looking for ways to host queryable data for cheap.

I have a hacked up POC experimental version of datasette-lite to be able to look at multi-GB databases at https://github.com/simonw/datasette-lite/pull/49. It uses a hacked up chunk'd lazyFile implementation from emscripten and others to grap pages from Cloudflare R2.

It's a test with california's unclaimed property records (https://www.sco.ca.gov/upd_download_property_records.html) of a 28GB searching up that guy who owns Twitter: https://datasette-lite-lab.mindflakes.com/index.html?url=htt...

I think there may be a space for super-large multi-GB files served from static storage being accessible from SQlite as well. Another one would be this full-text search of a 43GB SQLite database of Wikipedia's full text search: http://static.wiki/ . Hearing there's official support for this is awesome and I hope they also might add some provisions for those sticking with POSIX/Emscripten as well.

I grafted the enhanced lazyFile implementation of this to datasette-lite relatively recently. Threw in a 18GB CSV from

https://www.sco.ca.gov/upd_download_property_records.html

into a FTS5 Sqlite Database which came out to about 28GB after processing:

POC, non-merging Draft PR for the hack:

https://github.com/simonw/datasette-lite/pull/49

You can run queries through it if you URL hack into it and just get to the query dialog, browsing is kind of a dud at the moment since datasette runs a count(*) which downloads everything.

Oh wow! I wonder how hard it would be to load that module into https://github.com/simonw/datasette-lite

datasette-lite – Datasette running in your browser using WebAssembly and Pyodide

I have an open issue for that here: https://github.com/simonw/datasette-lite/issues/28

My initial hunch is that this will be really difficult - probably require a fork of something like https://github.com/coleifer/pysqlite3 then compiled for WebAssembly.

I'm confident it's feasible, but I don't have the skills to figure it out myself.

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.