> Not understanding dependencies, public/private, SCM or versioning, making their own code uninstallable after a few months I'm not sure what "uninstallable" c

> Not understanding dependencies, public/private, SCM or versioning, making their own code uninstallable after a few months I'm not sure what "uninstallable" code is, but why does it matter? Do scientists really need to know about dependencies when they need the same 3 libraries over and over? Pandas, numpy, Apache arrow, maybe OpenCV. Install them and keep them updated. Maybe let the IT guys worry about dependencies if it needs more complexity than that. > Writing completely unreadable code, even to themselves, making it impossible to maintain. This means they always restart from zero, and projects grow into folders of a hundred individual scripts with no order, depending on files that no longer exists This is actually kind of a benefit. Instead of following sunk cost and trying to address tech debt on years-old code, you can just toss a 200-liner script out of the window along with its tech debt, presumably because the research it was written for is already complete. > Foregoing any kind of testing or quality control, making real and nasty bugs rampant. Scientific code only needs to transform data. If it's written in a way that does that (e.g. uses the right function calls and returns a sensible data array) then it succeeded in its goal. > They are also less productive when coding than the scientists because they care too much about the quality of their work and not enough about getting shit done. Sooo...another argument in favor of the way scientists write code then? Isn't "getting shit done" kind of the point?