hadley

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.

You’ll be able to adjust plots. But you have to do it with code, not UI.

Let alone that Nano Banana 2 is Gemini Image 3.1

Students also pay :)

We're working on this! Education is really important to us so this is 100% a problem we want to solve.

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 hadley@posit.co.

You might be interested in https://github.com/posit-dev/plumber2

I've wrapped a bunch of providers with ellmer: https://ellmer.tidyverse.org

That’s exactly how ggplot (not 2!) worked: https://github.com/hadley/ggplot1

Why is that disappointing?

You should check out https://siuba.org and https://plotnine.org :)

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()).

I filed an issue so I don't forget about this: https://github.com/tidyverse/dbplyr/issues/1471

I love this framing :)

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.

(1) You might want to check out https://github.com/t-kalinowski/Rapp by my colleague Tomasz

(2) I think part of that is in scope for strict (https://github.com/hadley/strict). You might also be well served by adopting some more data validation tooling, e.g. pointblank (https://rstudio.github.io/pointblank/).

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.

We now provide snapshotted CRAN binaries (for many platforms) at https://packagemanager.posit.co.

I'd love to hear more about this because from my perspective renv does seem to solve 95% of the challenges the folks face in practice. I wonder what makes your situation different? What are we missing in renv?

We (Posit) have hired Hassan (the maintainer of plotnine) so this is great to hear :)

If you have specific issues around error messages and tracebacks please feel free to let me know directly or to file issues on Github. We really do care about the legibility of errors and tracebacks and me and my team have put a lot of effort into them in the last few years. But there's always room to do better and I'd love to know where the pain points are.

(The intersection of tidyverse and shiny tracbacks are a known pain point that's hard to resolve. Unfortunately shiny and tidyverse did a bunch of parallel work that took us in slightly different directions and now it's hard to re-align.)

One thing we are missing is a guide to reading traceback for newer users. Often experts can get a good sense of where the problem is, but we've failed to teach newer users how to get the most value from a traceback.

What are the premium packages you're talking about? As far as I know all of our R packages are 100% open source.

I'd love to hear more why you're using webshot etc to talk screenshots of your shiny app. A more typical workflow would be to generate a separate HTML/PDF with quarto/RMarkdown.

I have noodled on this problem a bit in https://github.com/hadley/strict, which I'm contemplating bringing back to life over the coming year. It's certainly very difficult to cover 100% of all possible problems, but I suspect we can get good coverage of the most common failure points (specifically around recycling and coercion) with a decent amount of work.

A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date.

And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour.

If you tell me what makes R hard to integrate into data pipelines I will do my best to fix it :)

That's true, but quarto also has full support for Python and Jupyter notebooks, not to mention julia, and observable. It's really built from the ground up to be multi-language so that everyone can benefit from all the goodies in RMarkdown.

And sweave is built on noweb :)

Is there some way we could advertise this better? The quarto homepage already says “Quarto is a multi-language, next generation version of R Markdown from Posit, with many new new features and capabilities.”

When talking about Quarto within the R community we usually frame it this way, but obviously it’s not a very useful description if you’ve never heard of RMarkdown.