We want to improve the reproducibility of the analyses at our institute. To this effect, we contemplate on implementing a system based on Singularity. The idea is that at the beginning of the analysis, the user can choose a machine configuration (later amendments must be possible) that sticks with them until the project is complete. Then, the image is archived with the analysis. Ideally, the user doesn't have to issue system admin commands (install packages etc.) in the process.
She just makes a request like "I need R with tidyverse and Python 3 and this and that in-house packages" and she gets a command that she can use to ssh into a singularity container that has those features. When she makes a new request, she gets the newest version of the programs but once the container has been deployed those versions don't change anymore.
It gets tricky when I think of the fact that multiple users will need different combinations of software. Do I need to provide an image for every combination of Software and software extension packages? If I only think of a scenario where users can choose of an arbitrary combination of {R, Julia, Python, r-tidyverse, r-data.table, r-whatever-genomic-analysis-package-on-bioconductor, python-...}
Is there a feature selection method in the veins of
singularity pull library://alpine:3.7 +r:3.2.1 +python3:3.7 +r-package:1.2.3
such that the user can
ssh cluster01 -- singularity shell project-abc.simg
and start/continue working?
If not, is there an alternative approach to supplying custom machine configurations to users using singularity?
I could find Singularity Compose, but this seems to just run multiple containers as services next to each other. So the images can stay separate. I have to merge them.