Comment by tomrod
As someone who uses Python, R, Go, Rust, Fortran, and Java...
I would never write a full stack application in R. Terrible maintainability.
As someone who uses Python, R, Go, Rust, Fortran, and Java...
I would never write a full stack application in R. Terrible maintainability.
I've wrapped R to python before. That was okay, a bit stilted but still could take to production if absolutely necessary.
You're 100% right that R is great for data scientists (my background) for frontier level academic implementations as well as toy/simple models. It's generally a poor runtime for computation and suffers from much of the same issues as Python for data quality and typing. Python is better for battle-hardened type stuff, has better debugging tools for certain.
R _can_ be done well, but the juice isn't worth the squeeze typically.
I'm in this picture, and I'm begging my collaborators to move to Julia or Python.
I would have said this a year ago but R is a language for statisticians and not software engineers. It took me forever to understand this.
Statistical Rethinking by McElreath is really what finally got me to see the value of R.
You can find the python versions of the class and they are certainly not better.
A full application in R really makes absolutely no sense.