I'm a biochemist who got into programming from the science side of it, and yeah, code written by scientists can be pretty bad. Something that I saw a lot in my field was that people who needed some code to do something as part of a larger project (such as adding back on the hydrogens to a 3d protein structure from the protein database) would write the thing themselves, and not even consider the possibility that someone else has probably written the same thing, but far better than they be can, and made it available open source. This means there's a lot of reinventing the wheel by people who are not wheel engineers.

I find it so wild how few scientists I've spoken to about this stuff understand what open-source code actually means in the wider picture. Although I've never spoken to a scientist in my field who doesn't know what open source means at all, and pretty much all of them understand open source software as being a good thing, this is often a superficial belief based purely on understanding that proprietary software is bad (I know someone who still has a PC running windows 98 in their lab, because of the one piece of essential equipment that runs on very old, proprietary code that isn't supported anymore).

Nowadays, I'm probably more programmer than biochemist, and what got me started on this route was being aware of how poor the code I wrote was, and wanting to better understand best practices to improve things like reliability and readability. Going down that path is what solidified my appreciation of open source — I found it super useful to try to understand existing codebases, and it was useful practice to attempt to extend or modify some software I was using. The lack of this is what I mean by "superficial belief" above. It always struck me as odd, because surely scientists of all people would be able to appreciate open source code as a form of collaborative, iterative knowledge production