I'm building pipelines for myself to use. The result is often pipelines that other people can use too. It's all just code, there's nothing magical in building pipelines.
(I still disagree about everything you said about Julia though. I bet you I could re-implement this faster in Julia thank your C++, and in a type generic way too which would make it trivial for users to plug in their types, and it would be trivial to package - I'm assuming you didn't package that repo, you just expect your users to be shuffling files around. You're not contributing to improving the reproducibility situation in the academia, let me tell you xD)
So the handful of _Julia users_ with their totally unreproducible REPL mess can "trivially" plug in their types? Also saying the horrible mess that is Julia's module system is "trivial to package" is delusional.
I didn't package it and the data mangling part has very little use outside this specific experimental design. Also Python's packaging is quite shitty.
The C++ code is totally standalone and can be git-pulled and compiled how you like. C++ packaging is totally abysmal.
As I said in the comment and the README the code is a mess (although a piece of art compared to the notebook shit out there). It's purpose is that the results can be reproduced from the raw data.
I would love to make my analysis code cleaner. But there's zero incentive for that and very little time. Nobody sadly cares about the code, and most scientists can't code for shit. This is probably why Julia was designed so that it forces your code to be shit.