Ask HN: What’s the biggest difference between professional coding and academia?

Academia only worries about getting results for publishing. Testability, maintainability, clean design, all take a back seat because once the paper is done the author will likely never touch the code again.

The super structure of a Software project, size and density of crew.

In academic systems papers, every performance claim needs to be backed up by an experiment. But you can get credit for features even if you argue that it is possible to implement that feature with your design, even if you didn't actually do it.

In production software, this is flipped. Every feature claim needs to have an associated test, as it's a contract with your user. But when it comes to performance, everyone just waves their hands.

I'm being a little glib. But production software has to work. You'll spend far more time dealing with all of the "less interesting" details and edge cases than with research software. As ams6110 points out, this means more focus on testing, maintenance and good design. But I do want to emphasize testing - sometimes you'll spend more time testing something than actually implementing it. There's also often many more residual effects from dependencies elsewhere in the ecosystem you're working in. That's not typical in academic software.

My primary observation so far has been that academics are going to want to reach into the guts of my data analysis pipeline at every single step and inspect what's going on.

This informs my design choices quite a bit.

Maintainability. A lot of academic code only has to last long enough for one project or thesis, and the only maintainer will be the original author. Real-world code will last longer[1], and be worked on by more people, including people of lesser skill without the original author around to guide them. Often, that code also has to run in more environments. This difference is reflected not only in the code itself, but even more importantly in the infrastructure around it - source control, tests, documentation, bug trackers, etc.

Ironically, an academic might get to spend a higher percentage of their time on pure coding than a professional coder does. They have other concerns. Maintainable code is not part of the desired outcome. It's consumable and expendable, not durable, so any time spent making it any better than "just barely good enough" is wasted. Why build a tank when all you need is a bicycle?

[1] At least the expectation. Some academic code lives on far longer than its authors intended, and some non-academic code vanishes pretty darn quickly. But in general, both the intent and the expectation is that non-academic code will live longer.