3. Installation and configuration


The handbook is written for DataLad version 0.12 or higher. The higher the version, the better, but it should be at least DataLad 0.12.0. If you already have DataLad installed but are unsure whether it is the correct version, you can get information on your version of DataLad by typing datalad --version into your terminal.

3.1. Install DataLad

The content in this chapter is largely based on the information given on the DataLad website and the DataLad documentation.

Beyond DataLad itself, the installation requires Python, Git, and git-annex, and may require Python’s package manager pip and p7zip/7-Zip. The instructions below detail how to install each of these components for different common operating systems. Please file an issue if you encounter problems.

Note that while these installation instructions will provide you with the core DataLad tool, many extensions exist, and they need to be installed separately, if needed.


3.1.1. Linux: (Neuro)Debian, Ubuntu, and similar systems

For Debian-based operating systems, the most convenient installation method is to enable the NeuroDebian repository. If you are on a Debian-based system, but do not have the NeuroDebian repository enabled, you should very much consider enabling it right now. The above hyperlink links to a very easy instruction, and it only requires copy-pasting three lines of code. Also, should you be confused by the name: enabling this repository will not do any harm if your field is not neuroscience.

The following command installs DataLad and all of its software dependencies (including the git-annex-standalone package and p7zip):

$ sudo apt-get install datalad

The command above will also upgrade existing installations to the most recent available version.

3.1.2. Linux: CentOS, Redhat, Fedora, or similar systems

For CentOS, Redhat, Fedora, or similar distributions, there is an rpm git-annex-standalone available here. Subsequently, DataLad can be installed via pip.

Alternatively, DataLad can be installed together with Git and git-annex via conda as outlined in the section below.

3.1.3. Linux-machines with no root access (e.g. HPC systems)

If you want to install DataLad on a machine you do not have root access to, DataLad can be installed with Miniconda.

$ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
$ bash Miniconda3-latest-Linux-x86_64.sh
# acknowledge license, keep everything at default
$ conda install -c conda-forge datalad

This should install Git, git-annex, p7zip and DataLad. The installer automatically configures the shell to make conda-installed tools accessible, so no further configuration is necessary.

To update an existing installation with conda, use conda update datalad.

3.1.4. macOS/OSX

A common way to install packages on OS X is via the homebrew package manager. First, install the homebrew package manager. Note that prior to the installation, Xcode needs to be installed from the Mac App Store. Homebrew then can be installed using the command following the instructions on their webpage (linked above).

Next, install git-annex. The easiest way to do this is via brew:

$ brew install git-annex

Once git-annex is available, DataLad can be installed via Pythons package manager pip as described below. pip should already be installed by default. Recent macOS versions may have pip3 instead of pip – use tab completion to find out which is installed. If it is pip3, run:

$ pip3 install datalad

instead of the code snippets in the section below.

If this results in a permission denied error, install DataLad into a user’s home directory:

$ pip3 install --user datalad

If something is not on PATH…

Recent macOS versions may warn after installation that scripts were installed into locations that were not on PATH:

The script chardetect is installed in '/Users/awagner/Library/Python/3.7/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.

To fix this, add these paths to the $PATH environment variable. You can either do this for your own user (1), or for all users of the computer (2) (requires using sudo and authenticating with your computer’s password):

  1. Add something like (exchange the user name accordingly)

export PATH=$PATH:/Users/awagner/Library/Python/3.7/bin

to the profile file of your shell. If you use a bash shell, this may be ~/.bashrc or ~/.bash_profile, if you are using a zsh shell, it may be ~/.zshrc or ~/.zprofile. Find out which shell you are using by typing echo $SHELL into your terminal.

(2) Alternatively, configure it system-wide, i.e., for all users of your computer by adding the the path /Users/awagner/Library/Python/3.7/bin to the file /etc/paths, e.g., with the editor nano:

sudo nano /etc/paths

The contents of this file could look like this afterwards (the last line was added):


Note that pip is not able to install the p7zip dependency. Please install it if it isn’t yet installed – it is available via brew.

3.1.5. Using Python’s package manager pip

DataLad can be installed via Python’s package manager pip. pip comes with Python distributions, e.g., the Python distributions downloaded from python.org. When downloading Python, make sure to chose a recent Python 3 distribution.

If you have Python and pip set up, to automatically install DataLad and most of its software dependencies, type

$ pip install datalad

If this results in a permission denied error, install DataLad into a user’s home directory:

$ pip install --user datalad

pip is not able to install the 7-zip dependency. Please install a flavor of 7-zip that is appropriate for your operating system (such as p7zip for Linux or macOS) if it isn’t yet installed.

In addition, it is necessary to have a current version of git-annex installed which is also not set up automatically by using the pip method. You can find detailed installation instructions on how to do this here. For Windows, extract the provided EXE installer into an existing Git installation directory (e.g. C:\\Program Files\Git). If done this way, no PATH variable manipulation is necessary.

An existing installation can be upgraded with pip install -U datalad.

3.1.6. Windows 10

There are two ways to get DataLad on Windows 10: one is within Windows itself, the other is using WSL2, the Windows Subsystem for Linux, version 2. With the Windows Subsystem for Linux, you will be able to use a Unix system despite being on Windows. You need to have a recent build of Windows 10 in order to get WSL2 – we do not recommend WSL1. Information on how to install WSL2 can be found here:

Using the Windows Subsystem 2 for Linux

You can find out how to install the Windows Subsystem for Linux at docs.microsoft.com. Afterwards, proceed with your installation as described in the installation instructions for Linux.

Note: Using Windows itself comes with some downsides. We have created a dedicated page, So… Windows… eh? with an explanation and overview. In general, DataLad can feel a bit sluggish on Windows systems. This is because of a range of filesystem issues that also affect the version control system Git itself, which DataLad relies on. The core functionality of DataLad works, and you should be able to follow most contents covered in this book. You will notice, however, that some Unix commands displayed in examples may not work, and that terminal output can look different from what is displayed in the code examples of the book, and that some dependencies for additional functionality are not available for Windows. If you are a Windows user and want to help improve the handbook for Windows users, please get in touch. Expandable notes, “Windows-Workarounds”, contain important information, alternative commands, or warnings, and if you are proceeding with a native Windows 10 system you should be close attention to them.

  • Step 1: Install Git

    • If you haven’t installed Git yet, please download and install the latest release from git-scm.com/.

    • During installation, you will be asked to “Select Components”. In order to get a slightly nicer visual experience, tick the box at “Use a TrueType font in all console windows”. Afterwards, you can open a Git bash, a terminal that is nicer than standard Windows terminals.

  • Step 2: Install Conda

    • Go to https://docs.conda.io/en/latest/miniconda.html and pick the latest Python 3 installer. Miniconda is a free, minimal installer for conda and will install conda, Python, depending packages, and a number of useful packages such as pip.

    • Using the Git Bash shell for DataLad makes a nicer and more visually appealing experience. If you want to be able to do this, make sure that Miniconda is available from within your Git bash. One way to achieve this is to tick “Add Anaconda to my PATH environment variables” during installation. You can test if you succeeded by opening a new Git bash and typing conda – if this shows you a help message, you’re good. Alternatively, you can use the Anaconda prompt, a preconfigured terminal shell installed with Miniconda, as a terminal. Find it by searching for “Anaconda prompt” in your search bar. From now on, any further action must either take place in the Anaconda prompt, or the Git Bash.

  • Step 3: Install DataLad and its dependencies

    • Enter an Anaconda prompt or your Git bash, and install DataLad and its dependencies by running conda install -c conda-forge datalad

  • Step 4: Install git-annex (temporarily necessary) One of DataLad’s core dependencies is git-annex. For the longest time, git-annex installers for Windows lacked support for mimeencoding. Without mimeencoding, a standard DataLad procedure, the text2git configuration (it will be introduced in the very first section of the Basics), is not functional, and you will find “Windowsworkarounds” to deal with this. We recently started to build git-annex with support for mimeencoding ourselves, though. At the moment, we are working on packaging up Windows-specific DataLad distributions with this version of git-annex, but for the time being, you can find the standalone git-annex installer for Windows with mimeencoding at http://datasets.datalad.org/datalad/packages/windows/.

  • Optional - Install Unix tools

    • Many Unix command-line tools such as cp are not available by default. You can get a good set of tools by installing condas m2-base package via conda install m2-base in an Anaconda prompt. NOTE: We’re currently investigating whether m2-base may cause problems – use with caution.

3.2. Initial configuration

Initial configurations only concern the setup of a Git identity. If you are a Git-user, you should hence be good to go.


If you have not used the version control system Git before, you will need to tell Git some information about you. This needs to be done only once. In the following example, exchange Bob McBobFace with your own name, and bob@example.com with your own email address.

# enter your home directory using the ~ shortcut
% cd ~
% git config --global --add user.name "Bob McBobFace"
% git config --global --add user.email bob@example.com

This information is used to track changes in the DataLad projects you will be working on. Based on this information, changes you make are associated with your name and email address, and you should use a real email address and name – it does not establish a lot of trust nor is it helpful after a few years if your history, especially in a collaborative project, shows that changes were made by Anonymous with the email youdontgetmy@email.fu. And do not worry, you won’t get any emails from Git or DataLad.