| So, I actually get what you mean here, and have used both R and Python in anger for a number of years. This is all about tradeoffs. Fundamentally, if your package doesn't compile on the latest version of R, it gets removed from CRAN. This means that each version of R has a consistent set of packages that (mostly) work together. Contrast with Python which does facilitate reproducible builds, because you can hack together ancient versions of Python and make them continue working. I could go into a massive rant here about pip, but it's trending in the right direction now and I don't want to discourage any of the people working on it. R is better in terms of being able to ensure that for a given R version, any package you install will be compatible, Python is better for making sure that that one application built three years ago keeps working in the same fashion. Also, it sounds like you're running a nix based system, have you considered (I'm sure you have) using the system packages. For example, the Debian/Ubuntu ones are pretty comprehensive, at the cost of using older versions. I believe that R-studio also have pre-built packages for Linux (but have not tested this) so that could also work. To be fair, conda is pretty good as a package manager, because it handles the C++/C dependencies. But to your Docker point, that's how I handle the insanity that is python packaging, especially in the data science space, so it may just be an issue with the field itself. |