The Python scientific stack, compiled to WebAssembly
I benchmarked this recently. It comes in at 4-10x slower than cpython for random typical use cases on my machine, which is not too shabby at all. The author also states that numpy is slower than it should be due to lack of support for BLAS at this time.The real impressive feat to me isn't hosting jupyter in the browser. It's access to a reasonably fast implementation of numpy in the browser which smokes native JS code for homogeneous array operations. I would love to see a minimalistic WASM implementation of numpy that can seamlessly interop with normal JS. Such a library would open up all sorts of possibilities that aren't currently feasible due to perf reasons.