You can learn about the theory that underlies tidyeval at https://adv-r.hadley.nz/quasiquotation.html. I'd claim that it's neither reinventing the wheel (because it solves problems that the base equivalents do not) nor bizarre (because it is backed by a deep, well-founded theory).
CRAN is a weird universe, but not (just) for the reasons you mention. CRAN is still heavily human maintained which means that there's a high chance that an actual human will look at your packages (at least for your first package). This imposes a considerably higher barrier to entry than most package repos, and hence I suspect CRAN actually has a considerably lower percentage of slop.
We do discount heavily for academia: get 50% off for research and 100% off (i.e. free) for teaching. But I do get that our pro products largely solve problems that folks encounter in larger enterprises, and you may not see the value inside an academic department. I'm also always happy to learn how we could do better, please feel free to reach out to [email protected].
Hmmmm, I think that's something we could probably help with in dbplyr by providing something like `last_sql()` that would return the most recent SQL sent to the database. (By analogy to ggplot2::last_plot() and httr2::last_request()/last_response()).
For the most common cases, the tidyverse now only requires {{ }}. This allows you to tell tidyeval functions that you have the name of a df-var stored in an env-var. Do you have specific cases that you find frustrating?
Oh, you mean the pro drivers? Unfortunately we can't give those away because we have to pay several $100k a year just to get access for our customers. Most of the pro drivers do have equivalent open source versions that you should be able to use instead.
Hmmm, I'd still try generating the table with quarto (since you can output word documents), or try gt (https://gt.rstudio.com), which I know has much greater control over output, and supports RTF output (https://gt.rstudio.com/reference/as_rtf.html) which should import cleanly into word.
I'd highly encourage you to look into shiny more. No, it's not django, but it's a much richer framework than dash, and you can always bring your own HTML if what it generates for you isn't sufficient.
R definitely has its warts, but I strongly believe that underneath them lies a beautiful and quite elegant language that's extremely well suited to the challenges of data analysis. If you're already a programmer, you might find something like Advanced R (https://adv-r.hadley.nz) to be useful to get a sense of what R really is as a programming language.