Installation

Table of Contents

• Installation

  • Step 0. System requirement

  • Step 1. Choose an environment manager for BABS

  • Step 2. Install BABS and dependent software

    • Optional: set-up datalad-osf

    • Check if you have everything installed and up-to-date

Step 0. System requirement

Currently BABS supports applications on high performance computing (HPC) clusters, specifically, Sun Grid Engine (SGE) and Slurm clusters. Please make sure Singularity or one of its successors (i.e. SingularityCE or Apptainer which BABS currently supports) is available on the cluster.

Currently, BABS is not compatible with:

• cloud-based computing platforms (e.g., Amazon Web Services [AWS]);

• local computers where a job scheduling system or Singularity software is not installed;

• computing nodes without job scheduling systems.

Step 1. Choose an environment manager for BABS

For this, we strongly recommend miniforge/mamba or optionally micromamba. These packages work the same as conda, but they are open-source and will never move to a pay-structure as anaconda has recently done.

Step 2. Install BABS and dependent software

We have a yaml file on our repo for easily installing BABS and its dependencies with a single command:

# Get the evironment_hpc.yaml file from github:
wget https://raw.githubusercontent.com/PennLINC/babs/refs/heads/main/environment_hpc.yml

# Install into a new environment called babs:
mamba create -f evironment_hpc.yml

# Activate the environment:
mamba activate babs

Note

If you are using conda or micromamba instead of mamba, simply replace mamba with either conda or micromamba in the commands above.

Before proceeding, make sure your Git identity has been configured. You can check whether this has already been done via:

git config --get user.name
git config --get user.email

If this returns nothing, you need to configure your Git identity:

git config --global user.name "John Doe"
git config --global user.email johndoe@example.com

Please replace "John Doe" and johndoe@example.com with your name and your email. You only need to do this step once on a given system.

Optional: set-up datalad-osf

You also need to configure datalad-osf only if:

• if you're an end user and your input DataLad dataset is on OSF;

  • e.g., when you follow the example walkthrough;

• or if you're a developer and you will be running our pytest;

How to configure datalad-osf:

# Provide your OSF credentials  - this step is very important!
datalad osf-credentials --method userpassword

For up-to-date information on configuring datalad-osf see: http://docs.datalad.org/projects/osf/en/latest/settingup.html

Check if you have everything installed and up-to-date

Warning

Before moving on, please check if you have up-to-date required dependencies! Sometimes although dependent software has been installed, the version might be too old or not up-to-date, causing future errors hard to debug.

Check dependencies' versions using commands below:

# dependencies:
datalad --version
git --version
git-annex version
datalad containers-add --version
datalad osf-credentials --version

# babs
pip show babs

It is a good idea to use the versions at or above the versions listed:

$ python --version
Python 3.11.11
$ datalad --version
datalad 1.1.5
$ git --version
git version 2.49.0
$ git-annex version
git-annex version: 10.20230626-g8594d49
$ datalad containers-add --version
datalad_container 1.2.5
$ datalad osf-credentials --version
datalad_osf 0.3.0
$ pip show babs
Name: babs
Version: 0.0.9