[zhdc1]

I’ve transitioned a lot of my work over to Julia, but R is still the most intuitive language I’ve used for scripting out data collection, cleaning, aggregation, and analysis cases.

The ecosystem is simply better. The folks who maintain CRAN do a fantastic job. I can’t remember the last time a library incompatibility led to a show stopper. This is a weekly occurrence in Python.

[klmr]

> I can’t remember the last time a library incompatibility led to a show stopper.

Oh, it’s very common unless you basically only use < 5 packages that are completely stable and no longer actively developed: packages break backwards compatibility all the time, in small and in big ways, and version pinning in R categorically does not work as well as in Python, despite all the issues with the latter. People joke about the complex packaging ecosystem in Python but at least there is such a thing. R has no equivalent. In Python, if you have a versioned lockfile, anybody can redeploy your code unless a system dependency broke. In R, even with an ‘renv’ lockfile, installing the correct packages version is a crapshoot, and will frequently fail. Don’t get me wrong, ‘renv’ has made things much better (and ‘rig’ and PPM also help in small but important ways). But it’s still dire. At work we are facing these issues every other week on some code base.

[hadley]

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?

[apwheele]

Agree with this, I am pretty agnostic to the pandas vs R whatever stuff (I prefer base R to tidyverse, and I like pandas, but realize I am old and probably not in majority based on comments online). But many teams who are "R adherent" folks I talk to are not deploying software in varying environments so much as reporting shops doing ad-hoc analytics.

For those whom want to use both R/python, I have notes on using conda for R environments, https://andrewpwheeler.com/2022/04/08/managing-r-environment....

[disgruntledphd2]

Can you not just build your own code as a package and specify exact dependencies?

It's a bit of faff but that seems like it should work (but maybe I'm missing something).

[getoffmycase]

I basically don’t use anything outside of tidyverse or base R because of the package dependency issues.

[wodenokoto]

At my old job we snapshotted CRAN and pinned versions of package dependencies _against_ CRAN.