Time to first plot is still painful even in julia 1.5, sure. But after paying that startup cost, the speed boost can be transformative in terms of the flexibil

Time to first plot is still painful even in julia 1.5, sure. But after paying that startup cost, the speed boost can be transformative in terms of the flexibility and dynamism that it buys. I've been using Pluto.jl lately, and interactive data analysis feels like way less of a burden than working in jupyter. As to harder to use, writing fast vectorized numpy code can take a lot of mental effort. For one project I ended up forcing things into this 5-D array broadcasting mess, where in julia it's way simpler to just write intuitive code that's performant without bending over backwards to avoid explicit loops. For numpy code you can "just" drop down to cython, but for pytorch you can get stuck with thinking up some clever broadcasting solution.