Stop staying you can't put R in prod.
I made a blog post with my thoughts and reactions.
https://josiahparry.com/posts/2023-07-06-r-is-still-fast.html
Stop staying you can't put R in prod.
I made a blog post with my thoughts and reactions.
https://josiahparry.com/posts/2023-07-06-r-is-still-fast.html
@josiah How about maintainability?
Never met a developer who liked R, and to put things into production, you have to work with devs.
The new people coming into data science all know python. Even among older data scientists, you rarely find one that prefers R (unless they're a statistician working in academia).
Who is going to maintain that code after the person who wrote it leaves for another company?
@JorisMeys @josiah outside of academia, where stuff is normally put into production, this is very rare. In these fields (which seems to be the focus of the blog post), R is a dying language. Picking a language to put into production has to take into account the potential pool of people who you could hire to maintain it.
If you can present convincing data otherwise, I'm all ears.
I'm repeating myself, by "putting into production", I mean running in a kube cluster, not performing some analysis.
The example in the blogpost is a webserver. I have never seen one written in R.