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.
25 years in the industry here. As I said there's nothing against learning something new but I doubt it's as easy as "leveling up".
Both fields profit a lot from experience and it's as much gain for a scientist do become a software dev as an architect becoming a carpenter. It's simply not productive.
Well, that's the way it is. Scientific code and production code have different requirements. To me that sounds like "that machine prototype is inefficient - just skip the prototype next time and build the real thing right away."
I don't think you understand my point, which is that developing the prototype takes e.g. 50% more time than it should because of complete lack of understanding of software development.