nutter VS cicd-templates

From my experience OO gives you much more flexibility in designing your pipeline but you're risking to make the project way more complicated. The worst example I have seen is the Nutter library (https://github.com/microsoft/nutter), which uses endless classes that are all nested in each other. I once had a bug when using it, and it was a huge pain in the ass to understand what's going on when the code is executed. It is a very good example of what can go wrong when you're overusing OO. However, in one project, I carefully created few classes, just out of curiosity, and I was very impressed how it helped me to organize/structure my code. A functions hase a clear dedicated use, but a good class is like a Swiss army knife with an solid set of functionalities. If you know how to use it in a smart way, you are likely to increase the quality of your code, but the contrary is also very likely, especially when the team members are not ready for it.

- https://github.com/microsoft/nutter

That's what Databricks Labs have done in this example I happened to find very shortly after posting this question: https://github.com/databrickslabs/cicd-templates . They run with local pyspark and dbx for launching jobs instead