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.

  • Aceticon@lemmy.world
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    10 months ago

    Most of the “conventions” (which are normally just “good practices”) are there to make the software easier to maintain, to make teamwork more efficient, to manage complexity in large code-bases, to reduce the chance of mistakes and to give a little boost in productivity.

    For example, using descriptive names for variables (i.e. “sampleDataPoints” rather than “x”) reduces the chances of mistakes due to confusing variables (especially in long stretches of code) and allows others (and yourself if you don’t look at that code for many months) to pick up much faster what’s going on there in order to change it. Dividing your code into functions, on the other hand, promotes reusability of the same code in many places without the downsides of copy & paste of the same code all over the place, such as growing the code base (which makes it costlier to maintain) and, worse, unwittingly copying and pasting bugs so now you have to fix the same stuff in several places (and might even forget one or two) rather than just fixing it in that one function.

    Stuff at a higher, software design level, such as classes, are mean to help structure the code into self-contained blocks with clear well controlled ways of interaction between them, thus reducing overall complexity (everything potentially connecting to everything else is the most complex web of connection you could have) increasing productivity (less stuff to consider at any one point whilst doing some code, as it can’t access everything), reduce bugs (less possibility of mistakes when certain things can only be changed by only a certain part of the code) and make it easier for others to use your stuff (they don’t need to know how your classes works, only to to talk to them, like a mini library). That said, it’s perfectly feasible to achieve a similar result as classes without using classes and using scope only, though more advance features of classes such as inheritance won’t be possible to easilly emulate like that.

    That said, if your programs are small, pretty much one use (i.e. you don’t have to keep on using them for years) and you’re not having to work on the code as a team, you can get away with not using most “conventions” (certainly the design level stuff) with only the downside of some loss in productivity (you lose code clarity and simplification, which increases the likelihood of bugs and makes it slower to transverse and spot stuff in the code when you have to go back and forth to change things).

    I’ve worked with people who weren’t programmers but did code (namelly with Quants in Finance) and they’re simply not very good at doing what is but a secondary job for them (Quants mainly do Mathematical modelling) which is absolutelly normal because unlike with actual Developers, doing code well and efficiently is not what their focus has been in for years.