I don't even mind (although it bothers me that python doesn't have pipes ala R, or any sort of nice lambda syntax) but I wonder how much work has been put to take python-like dialect and hammer it over and over into being fast

NumPy giving a whole other set of verbs you have to memorize to just wrap around C, then JAX+etc which take that subset and make it faster, then the pypy+pyston to rewrite big parts, with numba to do individual functions if you really want for loops. I know it's an over simplification and it's all pretty amazing work, but it's exhausting to me how many companies and people have put work into taking a fast language and trying to make subsets fast