I see your comment grayed out, and I just want to chime in, as some who does a lot of numerical stuff (more than a decade, published stuff, support multiple lab research projects etc), I want to second this point of view. When it’s time to get real work done Python is more than good enough, and there’s plenty of strategies for acceleration where required.
And when I want Julia’s promise of fast loops, I use Numba. If all the effort gone into Julia had instead been spent on fixing remaining warts in Python workflow for science, we wouldn’t even havee this conversation.
And when I want Julia’s promise of fast loops, I use Numba. If all the effort gone into Julia had instead been spent on fixing remaining warts in Python workflow for science, we wouldn’t even havee this conversation.