Shouldn't be too surprising, given how PyPy is generally faster than CPython by about x7-8 factor:

http://speed.pypy.org/

I'd expect a much larger difference in tasks that are pure Python (loading a CSV is done primarily through the csv module, i.e. all the hot loops are in C).

Yes, but PyPy is usually compiled to machine code (and emits machine code), not to JS.

True, but the asm.js is then compiled to machine code by the browser's JS JIT.

I'd expect some overhead from sandboxing etc., but it should be fairly close to native speed.

It's not "overhead from sandboxing" that's a problem, it's the fact that translating from bytecode to bytecode to bytecode will cause it to lose some ... succinctness at each step, giving the final machine code generator a harder time coming up with efficient code for it.

Indeed, but many of the optimizations introduced by PyPy should be visible regardless of compilation target.

I love Python but js is close to an order of magnitude faster

Have you tried PyPy?

Unfortunately it hasn’t been a drop-in replacement for our CPython codebase (lots of Numpy/Pandas/etc).

no numpy & no tensorflow

Wow, that's awesome! Direct link to the live notebook: https://livebook.inkandswitch.com/fork/welcome

Naturally, I changed the first code block to this:

    from random import randint, seed
    seed()
    "\n".join([randint(5, 25) * ' ' + s for s in ['such code', 'much live', 'wow']])

This is great, was looking for this exactly!