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Comment by iainctduncan | Hacker News Reader

think what you will, the scientists disagree. Which was the point. Not holding my breath to find many scientists matching my description who would rather learn Go or Rust...

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I'll be the counter example. PhD in life sciences, but I've also been programming since I was a teen. Rust is by far my most used language for both general fun projects and in my role as a programmer in the life-sciences. Python is OK for ad-hoc analyses, but I cannot stand to use dynamically typed languages for anything "real" given how much difficulty dynamic typing imposes on reading and understanding code.

Sure, but by your description, you aren't really the people I'm describing. If you've been doing this since you were a teen, you're a "Real Programmer". My point was that people who have to do this as item 7 of 10 things in their job description are very much less likely to learn something like Rust than Python. That is undeniably a bigger lift to a non-programmer. Python's success in the sciences is in large part due to how good a fit as a language it is for part-time occasional programmers.

I like all kinds of languages, but the only ones I would encourage my partner to bother with as tools for her science work would be R and Python.

I don't think the scientists disagree. They just don't really care if their code is a big ball of mud.

They might even care, they just don't know any better. When the typical scientist "learns to code", there's no one around telling them how to do proper software engineering.

At best, they engage in the polite fiction that it just doesn't matter, because all that code is inherently "throwaway" stuff that's only used for playing with in the context of research. Of course even that is wrong, the code doesn't really disappear like that.

No. Scientists are smart people. It's not that they don't care or don't know better, it's that they have different priorities. Every scientist I know is smart enough to be well aware that they don't have the know how for proper software engineering, but they also do not have the time or resources to learn to write code the way you would for a long term product.

I would not be patronizing to these people, they are very smart. They just live and work in a world that is completely different from technical product firms in pretty much every regard.

You're just rephrasing the "throwaway code" polite fiction. Increasingly, publishable-quality research is expected to be publically reproducible, and that means the code must stay around, potentially in the "long term". Every scientist loves it when their research gets cited a lot, right? Well, those citations become worthless if you can't reproduce the research because the code is an unsurveyable mess relying on bitrotted, unsupported external components.

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