I've arguably got a lot more experience doing scientific programming in c++ and FORTAN, than I do in python. Yet for quick prototyping where performance is almost never an issue, I still elect to use python because it lets me wrap my head around the problem faster. I spend less time fixing stupid errors and thinking about coding and more problem thinking about the problem I really need to solve.
Julia might be even better, I've heard good things, I've just never used it though. In the scientific computing and data science world that I deal with, I'd say at least 95% of the time there's never a need to jump from a hacked together prototype to a more production level product.
I ended up making a custom system image with the libraries I always use (Plots, etc) which does help on that front.
That's a fairly minor gripe, mind you. It's still great.
You suggest alternative B?