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Outside relatively straightforward operations working with groups with "expressions" gets really painful. And Python gets too slow fast. And Pandas (multi-)indexing madness is a constant source of bugs and frustration.

Sad that Julia is unusable for my workflows, and will likely remain so.

You’re tired, but I don’t know if I have enough brains to rewrite the API “query” from this article using brainless loops.

You can do brainless for loops in Python really easily.

Oh yeah, toss numba or cython on top and you are back to numpy speed...

Nope they are still libraries with their own feature set that need remembering.

Ok, if you consider @jit a feature set...

(Admittedly, there are more features, but in my book, I demonstrate pure Python code that runs as fast as numpy and cython with this decorator added.)