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How do I create a custom Rstudio Environment?

A custom Rstudio environment requires some manipulation from the command-line so that you can create what is know as a custom module collection named "ood_rstudio".   The basic ingredients for your custom Rstudio environment include:

1. (Required) A version of R you wish to use

2. Additional modules that fulfill the dependencies for the R libraries you wish to install

3. Install the R library. Steps on how to perform an install.packages on Mana can be found here.

4. Creating a collection with the specific name "ood_rstudio"

For example, if one wanted to use rgdal within rstudio, they would need to also add the gdal module to their custom collection and install the R library.  The steps would be as follows

Custom Rstudio environment

[user@login002 ~]$ srun -p sandbox -c 4 --mem=6g -t 60 --pty /bin/bash
[user@node-0005 ~]$ module purge
[user@node-0005 ~]$ module load langllang/RStudio-Server/20222023.0712.21+576402-fossgfbf-2022a2023b-Java-11-R-4.24.1
[user@node-0005 ~]$ module load data/GDAL/3.59.0-foss-2022a2023b
[user@node-0005 ~]$ R
[user@node-0005 ~]$ # Perform install.packages in R of rgdal and exit R
[user@node-0005 ~]$ module save ood_rstudio
[user@node-0005 ~]$ exit

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While Rstudio is setup where it can only have a single customized environments, Jupyter * can have multiple custom environments.  This is possible because each custom environment is a self contained conda environment which is loaded as a unique Kernel.  

Custom Jupyter Kernel

[user@node-0005 ~]$ module purge
[user@node-0005 ~]$ module load lang/Anaconda3
[user@node-0005 ~]$ mamba create --name test_env python=3
[user@node-0005 ~]$ source activate test_env
[user@node-0005 ~]$ ### Install your required packages ###
[user@node-0005 ~]$ # ...
[user@node-0005 ~]$ ### Finalize setup with this last package ###
[(test_env) user@node-0005 ~]$ mamba install ipykernel
[(test_env) user@node-0005 ~]$ python -m ipykernel install --user --name test_env --display-name "test_env"
[(test_env) user@node-0005 ~]$ exit

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A custom Jupyter environment requires some manipulation from the command-line so that you can create a custom conda environment named "ood_jupyterlab" that contains the custom version of jupyter you require. 

Customized Jupyter Environment

[user@node-0005 ~]$ module purge
[user@node-0005 ~]$ module load lang/Anaconda3
[user@node-0005 ~]$ mamba create -n ood_jupyterlab -c conda-forge jupyterlab=3 xeus-python
[user@node-0005 ~]$ exit

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The reason for this is because Jupyter applies all parameters from a global config file and those specified at runtime https://jupyterlab.readthedocs.io/en/latest/user/directories.html#labconfig-directories.
For example:, if you have  ".jupyter/jupyter_server_config.py", you will want to rename it to something  like ".jupyter/jupyter_server_config_custom.py" and call it specifically in the cases you wish to utilize it in any Jupyter instances you launch outside of Open OnDemand when using Mana.

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