[vharuck]

I'm sure they wanted to not replace magrittr pipes. R is introspective, and some reckless people (like myself) will mess with functions' guts in a few scripts. Replacing the `%>%` function with a syntax symbol will break those scripts. Even with scripts that don't metaphorically shove their hands down the garbage disposal, programmers might've relied on certain behaviors of the magrittr pipe.

The R Core team is very cautious about breaking anything, including universally acknowledged terrible defaults (I never thought `stringsAsFactors = TRUE` would ever go away). They know the majority of R programmers are not experts in programming. These users just want to write a script, debug it, and then use it for years with complete trust in the results.

[ImaCake]

It seems to have been worth the caution. R has a great reputation for stability. The contrast between my experiences in R and python datascience tools is stark. Pandas syntax has changed wildly since I started learning it, but R and tidyverse hasn’t really changed at all. Admittedly pandas was in rapid and early development at the time.

[disgruntledphd2]

I think the R reputation for stability is entirely driven by CRAN. If your package doesn't build on the latest version of R, it is marked unavailable. This means that people can build on R-current, in a way that simply isn't possible with the state of python packaging.

Maybe Python just needs a bigger repository with more stringent rules for what will be allowed?

[vharuck]

CRAN is definitely one of the best "features" of R. A very strict and official repository that requires human approval. Most often, that human is part of or close to the R Core team. Most guides I've read for getting a package on CRAN have to mention not wasting the time of somebody who's likely a busy statistics professor.