| Disappointed in the lack of discussion of R-Shiny or Plumber. R-Shiny is a full stack platform for web apps, and it’s how I leveraged my data science background to get into web development. It’s incredibly powerful in my opinion, with the only obvious limitation being the speed of R itself. And Plumber. It’s become the defacto method for deploying R code in a REST api. It too is still maturing, but I see it eventually becoming the Flask of R. Truth be told, however, after developing quite a few projects on the Shiny/Plumber stack, I wouldn’t recommend anyone do it. If for some reason you can only have an R interpreter, go for it. But learning multiple languages really is the best solution if you want to manage efficient applications. I say this, however, realizing that all of my colleagues writing R don’t have engineering backgrounds. I can’t help but feel like R is like JavaScript in many ways. Ease of use and the ease of publishing packages very quickly clutters the repository. R will always have a special place in my heart, after all it’s the language that made me discover programming. However, I can’t help but feel that my thirst for efficiency is making me outgrow it as a language quickly. |
After learning a fair bit of web-development, I feel R should focus on an analytics oriented path.
R just isn't designed for a web-app. Web-apps are much better and faster developed in more focussed languages / frameworks (node/python/django/express, etc) and can be seamlessly integrated to leverage R modules / scripts.