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~=0.12

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~=0.12

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~=0.12

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

$ pip install --user datalad~=0.12

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 WSL, the Windows Subsystem for Linux. We recommend the former, but information on how to use the WSL can be found here:

Using the Windows Subsystem for Linux

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

Note: Using Windows itself comes with some downsides. 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 the 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. If you are a Windows user and want to help improve the handbook for Windows users, please get in touch.

Note: This installation method will get you a working version of DataLad, but be aware that many Unix commands shown in the book examples will not work for you, and DataLad-related output might look different from what we can show in this book. Please get in touch touch if you want to help.

  • Step 1: 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.

    • During installation, keep everything on default. In particular, do not add anything to PATH.

    • From now on, any further action must take place in the Anaconda prompt, a preconfigured terminal shell. Find it by searching for “Anaconda prompt” in your search bar.

  • Step 2: Install Git

    • In the Anaconda prompt, run:

      conda install -c conda-forge git

      Note: Is has to be from conda-forge, the anaconda version does not provide the cp command.

  • Step 3: Install git-annex

    • Obtain the current git-annex versions installer from here. Save the file, and double click the downloaded git-annex-installer.exe in your Downloads.

    • During installation, you will be prompted to “Choose Install Location”. Install it into the miniconda Library directory, e.g. C:\Users\me\Miniconda3\Library.

  • Step 4: Install DataLad via pip

    • pip was installed by miniconda. In the Anaconda prompt, run:

      pip install datalad~=0.12
  • Step 5: Install 7zip

    • 7zip is a dependency of DataLad and not installed by default on Windows 10. Please make sure to download and install it.

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.