I'm about as old school as you can get with preference for CLI and simple text-oriented development environments. I recently picked up R again for a long-term

I'm about as old school as you can get with preference for CLI and simple text-oriented development environments. I recently picked up R again for a long-term data science project (https://matttproud.com/blog/posts/teaser-weather-temp-representation.html https://matttproud.com/blog/posts/teaser-weather-temp-repres...) after having not used it since university. In spite of a fair bit of annoyance with the R language (https://matttproud.com/blog/posts/rant-and-r-melt-function.html https://matttproud.com/blog/posts/rant-and-r-melt-function.h...), I found RStudio to make the prototyping process with R actually tolerable. Big kudos to Posit and the R community for RStudio. There are a couple of things I would love for the R ecosystem: project scaffolding to do bulk data generation (e.g., from continuously generated data sets). What's the best way to do this: makefiles, or what? I have a relatively short entrypoint R file that sources other leaf files to run specific analyses, but it makes the software engineer inside of me want to curl up and die.