I hate code written by LLMs
Hi everyone,
I am a Data Science student and I am far away from considering myself a "good coder", as I think I miss many fundamental concepts and I do not know a lot of standard good practices. Hence, I wanted the opinion from people with greater expertise in the field. Is it only me who hates how LLMs write code? I am not able to understand it properly, and I always have the feeling it is overcomplicating logics and processes that are in actually very simple, making a script 5 times its actual lenght.
I often do group projects with colleagues of mine, which I am now pretty sure do not even check the code the agent writes for them and it is always very frustrating to navigate in the maze of newly created functions and files which always feel redundant and inefficient.
In particular, I hate these features:
- They tend to go on a newline everytime there is a list of parameters, even when it is not necessary.
- Tthey do not comment nothing and if they do the comments are too long and too technical
- They declare way too many functions. I was thought that the main goal of functions was reusability. What is the purpose of having a function that you only call once? Maybe they even call that function "run_analysis_xyz". What is the purpose of that? Why do you have to prefer a code which is nested and does not execute top to bottom, in the same way that a reader can follow it?
- The variables naming rarely reflct their actual purposes.
- Unecessaries safety checks, that are good for general code but they make no sense
I am starting to hate group projects for this reason. I just get nervous when I try to read code that is clearly generated. Am I wrong for using AI just as an assistant and not as a completely autonomous code writer?