wjak

Ability to run vscode in a browser

R is good for machine learning and for production. We have helped big orgs to incorporate this technology in their it ecosystem. We used our open-source product called R Suite to manage deployment issues. https://github.com/WLOGSolutions/RSuite

Check this example - https://github.com/WLOGSolutions/RSuite-examples/tree/master...

No it is not example for rest API. Sorry I misunderstood you. I will add example for plumber with rsuite. Nevertheless the example presents workflow where only scoring should be changed to online from batch.

R is single threaded. The same is with python. We use kubernetes for scaling. But it is not for all applications of course. R can be put into production. Rsuite is one of the solutions that helps with that.

We use R for rest using plumber. It is very similar to flask. What you need is to add load balancer.

Exactly, production and deployment process are very different. In enterprise it is very rigid with production that has no internet connection and the best if you do not install pkgs there (supported by rsuite). But I had a customer who treated dev as prod. :)

Check this example. It is quite both complex and simplified. Real implementation is more automated. https://github.com/WLOGSolutions/RSuite-examples/tree/master...

Rsuite has supported binary pkgs about a year before rstudio. You have not read docs to the end. Rsuite has been used for enterprise. It works great. And it is open-source. Moreover it brings proper definition of R project which rstudio still is missing.

It's goal is different.

We started with reproducible project definition. Then we implemented rsuite to help manage the project. It includes dependency management which is what renv solve. What is the biggest difference is that our project consists of possibly many pkgs that are local to it. This allows you to create complex solutions. Moreover deployment PKG is zip file and to use it you only need r. No PKG installation on prod.

Check for yourself if our solution works for you. We use it on a daily basis. But reproducibility is not the only thing. The most important was to have a project for R.

To make this discussion better you should tell more about your development and deployment process. This includes definition of the project you use.

Thanks for finding typo. It is mature. We have used it to deploy R to big players. And use it for our consulting services everyday.

Check docs (https://rsuite.io/RSuite_Tutorial.php) and examples (e.g.https://github.com/WLOGSolutions/RSuite-examples )

It goes deeper. We were lacking definition of R project. Pkgs management is part of project management.

Hi, I one of the creators. From GitHub page: R Suite an R package which together with R Suite CLI tool enables you to design deployment workflow that fits you and makes R your primary data science platform. It has beed developed by WLOG Solutions company to make their development and deployment data science process robust.

R Suite gives answers to the following challenges for any R based software and data science solution:

- Isolated and reproducible projects with controlled dependencies and configuration.

- Separation of business, infrastructural and domain logic.

- Package based solution development.

- Management of custom CRAN-alike repositories.

- Automation of deployment package preparation.

- Flawless integration with Docker.

- Development process integrated with version control system (currently git and svn).

- Working in internetless environments.