At the end the author wrote something without explanation that I found cryptic. It is something I am curious about as I am starting to work on a software package:

  Avoid “scaffolding” (code generation)

I wasn't sure what this meant, so wanted to highlight it.

I chatted with ChatGPT the following is an edited transcript of what we came up with. Note it is not a direct quote from GPT but highly edited cyborg quote from long conversation we had:

  The term "scaffolding" in software development refers to frameworks that automatically generate boilerplate code to quickly set up the structure of a project (think Django). This can include things like generating project directories, files, and initial code to get started with minimal manual setup. 

  In the context of that article, the rule "Avoid scaffolding (code generation)" likely is implying that while scaffolding tools can be useful for quickly getting a project off the ground, they can generate generic or bloated code that can make the project harder to maintain and understand/read in the long run, with a steep learning curve. And *readability* is the point of the article. 
   
  If your guiding values in writing a software package is producing easy-to-read, easy-to-learn, and easy-to-use code *for humans*, then avoid scaffolding.

That last sentence is all me sorry.

I have no idea if the author would agree with the above sentiment, but it seems pretty reasonable. Like most coding rules, there are reasonable exceptions.

Opinionated is sometimes good, and the justification for it may scale with the complexity of the subject matter and the intended users and use case. E.g., how many different ways are there to achieve the goal(s) of your software, and do you want to enforce one particular way, given your intended user? If so, then depending on the specifics of the problem you are solving, you may need scaffolding.

For instance, DeepLabCut (https://github.com/DeepLabCut/DeepLabCut) is great software with tons of scaffolding. It is a machine vision framework written for experimentalists to track animal behavior, so boilerplate is great for them. The developers have put a ton of thought into how individual projects should be structured so the users who don't know anything about machine learning don't mess things up.

Anyway, this is useful for me to think right now as I am building a new project so I'm curious what others think.

user:	neuronet
created:	August 22, 2014
karma:	38