ReproNim Reproducible Basics Module

Package managers and distributions


Teaching: 180 min
Exercises: 30 min
  • What are the benefits of using package managers and distributions?

  • How can we establish and control computation environments using available package managers and distributions?

  • Which distribution(s) best suits my needs and use-cases?

  • Explain the differences between available distributions and package managers

  • Teach how it is possible to (re-)create a computational environment given a set of requirements (packages/versions)

What is a “package manager” and how does it relate to a “distribution”?

The installation and maintenance of computing environments is tedious and error-prone if you manually download, build, test, and install each software package from various locations on the web. Moreover, how could you be certain that the software version you installed today is identical to the software you installed yesterday?

To standardize and automate software delivery to users, package managers wrap each software product into one (or more) packages, with all the necessary metadata, so that they can be installed on the system via the same package management interface regardless of the software origin, programming language, etc. Moreover, package managers provide detailed versioning, dependencies, and other metadata that help guarantee the consistency and reproducibility of a computing environment.

Software distributions use a manager to index a collection of hosted packages in order to centralize delivery and streamline installation. In this way, the same package manager platform can be used by multiple distributions. For instance, the Debian distribution (and its derived distributions, such as Ubuntu) uses the APT package manager; Anaconda and miniconda Python-oriented distributions use the conda package manager, etc.

In the following lesson, we’ll survey the most commonly used neuroimaging software and data distributions, and touch on how they help establish unambiguous and reproducible computing environments.


Debian is the largest community-driven open source project, and one of the oldest Linux distributions. Its platform and package format (DEB) and package manager (APT) became very popular and Debian provides the base for many derivatives such as Ubuntu and Mint. At the moment, Debian provides over 40,000 binary packages for virtually any field, some of which have many scientific applications. Any number of those packages can be easily installed via the APT package manager with clear information about versioning, licensing, etc. Interestingly, almost all Debian packages are now themselves guaranteed to be reproducible (see Debian: Reproducible Builds.

Because of such variety, as well as its wide range of support for hardware, acknowledged stability, and adherence to principles of open and free software, Debian is a very popular “base OS” for either direct installation on hardware, in the cloud, or in containers (e.g., Docker or Singularity).

External teaching materials

Before going through the rest of this lesson, you should learn the basics of shell usage and scripting. The following lesson provides a good overview of all basic concepts. Even if you are familiar with shell and shell scripting, please review the lesson and try to complete all exercises in it, especially if you do not readily know the correct answers:

Debian (and its derivative) distributions typically only provide the single most recent version of a software package. It does so by design to guarantee that all available software in the released version of Debian work correctly together. If multiple versions were present (including possibly newer versions) it would be impossible to provide such a guarantee. However, more recent versions of the package often need to be installed. For this purpose, Debian backports provide an APT repository for stable releases of Debian with some package versions brought from Debian testing. Enabling a backports APT repository makes it possible to install more recent versions of packages on top of the stable Debian release. This way, multiple versions of the package might be made available – one (or even more if the /updates suite was also added) from Debian proper, and some newer version from backports. It is also made clear that one version is considered stable, and that another one is possibly less tested.

One of the most useful commands to discover details about the available versions of software (if operating in the shell) is apt policy.

An indispensable resource for reproducibility is the Debian snapshots archive. It provides access to the states of all aforementioned APT repositories as they were provided in the past. This resource allows us to obtain any previous APT repository version of a package.


The NeuroDebian project was established to integrate software used for research in psychology and neuroimaging into the standard Debian distribution. The majority of the packages maintained by the NeuroDebian team get uploaded to Debian unstable and then propagate to Debian and Ubuntu releases.

To facilitate access to the most recent versions of such software on Debian and its most popular derivative Ubuntu, the NeuroDebian project established its own APT repository. So, in a sense, this repository is similar to the Debian backports repository, but has several differences:

a) it also supports Ubuntu releases

b) typically backport builds are uploaded to NeuroDebian as soon as they are uploaded to Debian unstable

c) it contains some packages that have not yet made it to Debian proper

To enable NeuroDebian on your standard Debian or Ubuntu machine, use apt-get install neurodebian and follow the interactive dialogue, or just follow the instructions on

If you are using Docker, NeuroDebian Docker images are provided for all supported Debian and Ubuntu releases. If you are using Singularity, you can use singularity pull docker://neurodebian[:RELEASE] to get minimalistic images, or fetch the “Ultimate NeuroDebian Image” by singularity pull shub://neurodebian/neurodebian.


The conda package manager was initially developed for use with the Anaconda product, but because of its openness was used to establish independent popular conda “channels”, such as conda-forge and bioconda. The distinguishing feature of conda is that it doesn’t require root/super-user access for installation and management. Although largely Python-oriented, conda distributions are not limited to Python-based projects.

External teaching materials


DataLad is both a version control system (for code and data) and a distribution, since it provides mechanisms for aggregating multiple data “packages” so they can be found, installed, uninstalled, updated, etc.

Aggregation of multiple datasets is done via the git submodules mechanism, and a dataset containing other datasets is called a superdataset in DataLad. One such super-dataset is provided from and aggregates hundreds of neuroscience datasets over 240TB in size altogether. To learn about DataLad, please refer to the VCS lesson:DataLad.

Key Points