Jupyter Notebook RStudio containers

We are using Jupyter Notebooks to configure the different clients of DataSHIELD packages used in the projects we serve.

Currently we support these analysis environments:

Production

• DataSHIELD base environment dsBase
• DataSHIELD Mediation environment dsMediation

Development

• DataSHIELD base development environment dsBase --> master branch

You can you these images to support different analysis environments on the JupyterHub.

Development

We define 2 environment in development of these images.

• production == R-packages can be used as production environments on JupyterHub
• development == R-packages are not released yet and/or work only with the development version of the dsBaseClient or other packages

Building and publishing

We use semantic release to build and release the images.

Usage

Persist your installed R-libraries over different profiles

BE ADVISED: these packages are tightly bound to a specific R-version. If the RStudio is upgraded and another R-version is used as a base versions, these installed packages need to be reinstalled!

Create the R user library (only once)

1. You start a profile, for example DataSHIELD 6.1.0.
2. Open the RStudio via New --> RStudio
3. Create only once the directory R/userlib in your home directory
4. Add your own user library to the defaults

   userlib <- paste0(getwd(), '/R/userlib')
   .libPaths(userlib)
   

Install packages in the user library

1. Install a package and specify the library location
2. For example

   install.packages('dplyr', lib = '~/R/userlib')
   

   The library location needs to be exactly this

Add your own user library to the defaults

You need to do this each time you load RStudio to be able to use it

userlib <- paste0(getwd(), '/R/userlib')
.libPaths(userlib)

Now you can use preinstalled packages.