parquet-wasm VS csvz

nodejs-polars is node-specific and uses native FFI. polars can be compiled to Wasm but doesn't yet have a js API out of the box.

As for the fastest way to serialize data to Pandas data to the browser, you should use Parquet; it's the fastest to write on the Python side and read on the JS side, while also being compressed. See https://github.com/kylebarron/parquet-wasm (full disclosure, I wrote this)

I'm building WebAssembly bindings to existing Rust libraries [0] and lower-dependency geospatial tools [1]. Rust makes it very easy to bind rust code to both WebAssembly and Python. And by avoiding some large C geospatial dependencies we can get reliable performance in both wasm and Python using the exact same codebase.

[0]: https://github.com/kylebarron/parquet-wasm

[1]: https://github.com/kylebarron/geopolars

Looks to be a great resource. I've been working on a WASM implementation of reading and writing Apache Parquet [0] and it's been difficult being new to WASM to find the best way of distributing the WASM that works on Node and through bundlers like Webpack.

[0]: https://github.com/kylebarron/parquet-wasm

I put some work into creating a standard, csvz, for putting csv files and their metadata, into a zip file.

https://github.com/secretGeek/csvz

It’s a pretty powerful concept.

SimonW’s preferred technique of using sqlite as the means of exchange is also very powerful. Particularly when combined with all of the utils he maintains.