The coding language maketh not the science, but...

When it comes to choice of programming language to get any task done, people can sometimes have strong opinions. I've seen tweets from authors reporting reviewers who wanted the stats/plots/something done in R, and being dismissive of it being done in any other language. This is truly ridiculous, and this kind of attitude amounts to a weird, unhealthy kind of gate-keeping. What will come next, oh the code is only compatible with a Windows OS, it should have been developed keeping a Unix OS in mind...or even more specific comments about which packages to use?

The point is, there is a feeling some members of the community have that certain computational tasks are well suited to be done with insert favouriteprogramminglanguage. I find this attitude absurd and take it to be a form of irrational favoritism. If a piece of code is not in a coding language I use regularly, the only thing it means is that I may not be familiar with a whole bunch of cool concepts and ideas that the authors use. It doesn't mean the work is sub-standard. This argument cuts both ways, whether the language is an open-source or proprietary platform. If anything at all, if I have to read code written in an unfamiliar language and understand it - it needs to be well-documented! The user/reader needs to understand what is happening in the code irrespective of the actual for and while loops running under the hood.

Documenting code well is not a trivial task, and not something which can be done well over a couple of days. The closest task to documenting a codebase is writing a (scientific) manuscript. Things keep changing, you realise a bunch of things over a series of iterations, and even then there may be details lying around from the time you actually created the manuscript file itself.

So, okay, the programming language maketh not the science. A well-documented codebase is more capable of convincing an audience of its own utility and accuracy.