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Any tips to help a scientist become a better programmer? (iusearchlinux.fyi)

submitted 8 months ago by [email protected] to c/[email protected]

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Hey there!

I'm a chemical physicist who has been using python (as well as matlab and R) for a lot of different tasks over the last ~10 years, mostly for data analysis but also to automate certain tasks. I am almost completely self-taught, and though I have gotten help and tips from professors throughout the completion of my degrees, I have never really been educated in best practices when it comes to coding.

I have some friends who work as developers but have a similar academic background as I do, and through them I have become painfully aware of how bad my code is. When I write code, it simply needs to do the thing, conventions be damned. I do try to read up on the "right" way to do things, but the holes in my knowledge become pretty apparent pretty quickly.

For example, I have never written a class and I wouldn't know why or where to start (something to do with the init method, right?). I mostly just write functions and scripts that perform the tasks that I need, plus some work with jupyter notebooks from time to time. I only recently got started with git and uploading my projects to github, just as a way to try to teach myself the workflow.

So, I would like to learn to be better. Can anyone recommend good resources for learning programming, but perhaps that are aimed at people who already know a language? It'd be nice to find a guide that assumes you already know more than a beginner. Any help would be appreciated.

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[–] [email protected] 3 points 8 months ago

I've got two tips to add to the pile you've already read.

I recommend you read the manuals related to what you are using. Have you read the python manual? And the ones for the libraries you use? If you do you'll definitely find something very useful that you didn't know about.

That and, reread your code. Over and over until it makes total sense, and only run it then. It might seem slow, and it'll require patience at first. Running and testing it will always be slower and is generally only useful when testing out the concept you had in mind. But as long as you're doing your conceptual work right, this shouldn't happen often. And so, most work will be spent trying to track down bugs in the implementation of the concept in the code. Trust me when you read your code rigorously you'll immediately find issues. In some cases use temporary prints. Oh and avoid the debugger.