[short_sells_poo]

Thanks, but I think we may be talking cross purpose here. 99% of the research code ends up being thrown away (well, archived). Not because it's bad code necessarily, but because the idea that was being prototyped is a dead end. This means it's paramount that the language you use has to be as low friction and interactive as possible.

Imagine you are trying to establish whether there's a relationship between timeseries X and timeseries Y. You just want a tool that allows you to quickly calculate some summary statistics of these timeseries, clean them, convince yourself that they behave according to your expectations and then run some form of regression.

Nowhere in this process do you care about lifetimes. It's literally irrelevant. In fact, as long as all your work fits into memory, you don't even care about memory management. Your objective is to answer the primary question, everything else is a costly distraction.

The 1% of ideas that ends up being worthwhile is what gets productionized and needs to be robust. But obviously rewriting everything from language A to radically different language B adds it's own headaches.