将 shiny 应用程序的库部署到 shiny 服务器的最佳（标准）方法？

Question

I'm trying to get a shiny app deployed on Shiny Server. I can do that without any issues, but when trying to deploy an app that has a number of dependencies (remote and local) we keep running into issues.

We used renv to track the dependencies (on the Windows dev box) and rebuild it from scratch on the Linux prod box, but even though the dependencies are rebuilt and some get loaded, others do not. The.Rprofile of the user running the app is pointing to the renv activation script.

For the sake of clarity, we need and want all the R code to be built from the source code on the Linux box.

What is the best or standard way (or even a poor way that works) to deploy the libraries for a shiny app to the shiny server? Is renv even the right tool for this scenario or is there a better tool?

I've tried reading the shiny server documentation and the closes it only mentions that it uses the.Rprofile of the user running the app, but there doesn't seem to be any sort of guide on the best way to deploy dependent libraries.

Answer 1

This renv documentation discusses some reproducibility caveats:

1. system dependencies, and
2. changes in CRAN (eg a binary no longer being available).

Since you are moving from a Windows to a Linux system your packages may have unmet system dependencies (things that need to be installed outside of R) that you didn't encounter in Windows. For example, rJava is required for some of the Excel-related R packages, and getting its related system dependencies installed and working on Linux can sometime be a challenge. You can use the RStudio Package Manager Website to figure out what system dependencies are required for different R packages for your particular Linux OS. Also, the error messages you get when running these apps on Linux should point you in the right direction. These system dependencies are what you'll have to manage yourself since renv doesn't.

But for a more production-level solution you can try Docker and ShinyProxy. For apps with many dependencies or especially external dependencies (eg Python, SQL, etc.) you can guarantee more reproducibility using Docker. ShinyProxy can be used to host apps built into docker images. This is more work, but you ensure the entire system is reproducible, not just the R version and R packages. ShinyProxy also adds additional hosting capabilities like user authentication.