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I support bioinformatics researchers and my R problem isn't the language itself but the increasing fragile tower of packages that users cobble together. At thi

I support bioinformatics researchers and my R problem isn't the language itself but the increasing fragile tower of packages that users cobble together. At this point, I see R users (typically PhD students and post-docs) doing "science" in R by playing with parameters to functions in poorly-understood packages and publishing papers on which parameters are "best" for data generated from some specialty source. A very common situation for me is to be pulled in only after a package has been created with some vague hope of fixing performance problems (which R, Rcpp, and RcppParallel make fun to do for me, but I have some C++ background for scientific computing, ymmv). It is extremely common to find that these packages contain fundamental logic errors that probably should invalidate the (already published) results but never got caught because the code ran without actually failing. I guess I'm complaining that people are using buggy packages to write more buggy packages and it just bothers me. Library-driven development is just how the world works these days. And it should! But I'm not confident that the R bioinformatics world has the kind of guardrails I would prefer to see. I mean, I am reasonably confident tensorflow is functionally correct. Any R package that pulls in too many other R packages to begin with is probably not. As for the language itself - I guess it is ok. I have some lisp in my background and a fair amount of love for non-traditional array languages. But I don't see much R code that seems to stick to the R "standard library" rather than pulling in a million packages to do anything . . .

jghn 5y ago
> I see R users (typically PhD students and post-docs) doing "science" in R by playing with parameters to functions in poorly-understood packages and publishing papers on which parameters are "best" for data generated from some specialty source. That's a lot of bioinformatics, and not specific to R. It is a huge issue with anything vaguely pushbutton in the bioinformatics domain.
newbamboo 5y ago
“I don't see much R code that seems to stick to the R "standard library" rather than pulling in a million packages to do anything.” People teach the tidyverse to new r users. It makes them think that it’s standard practice to pull in lots of unnecessary but possibly convenient packages. Simple string manipulation should not require an extra package like stringr, but for many users it does. Often, they were taught this way.

jghn 5y ago

> I see R users (typically PhD students and post-docs) doing "science" in R by playing with parameters to functions in poorly-understood packages and publishing papers on which parameters are "best" for data generated from some specialty source. That's a lot of bioinformatics, and not specific to R. It is a huge issue with anything vaguely pushbutton in the bioinformatics domain.

newbamboo 5y ago

“I don't see much R code that seems to stick to the R "standard library" rather than pulling in a million packages to do anything.” People teach the tidyverse to new r users. It makes them think that it’s standard practice to pull in lots of unnecessary but possibly convenient packages. Simple string manipulation should not require an extra package like stringr, but for many users it does. Often, they were taught this way.