Gepard is a Python package available from PyPI repository so you should be able to install the latest version together with the required dependencies by simply issuing

pip install gepard

Of course, you should have Python first (version 3.7 at the least), as well as pip, which all major Linux distributions have as a standard package. (If you want to install Gepard in the virtual Python environment, or must do it because you get error: externally-managed-environment, see instructions for that below.)

Gepard is developed on Linux, but is tested also on Windows and MacOS. Please complain if you have problems.

Installation from sources

If you need some specific older version or you want to work on the code, you should clone the github repository

git clone

And then either use setuptools

cd gepard
python install

or, better, use pip to install as “editable”

cd gepard
pip install -e .

which will install the package in your local Python’s site-packages, but only as a link to sources, so any changes to the sources will be immediately active.


  • Python >= 3.7

  • Numpy

  • Scipy

  • importlib-resources and importlib-metadata Python packages

Fitting requires

Plotting requires

  • matplotlib

  • pandas (some plots)

If not already present on the system, all of the above will be installed automatically during the installation of Gepard. Older hybrid Python-Fortran versions of Gepard required also

  • logzero

  • PyBrain

To work on Gepard code you should also install

  • pytest

Developing documentation further requires

  • sphinx

  • sphinx_rtd_theme

Installation in virtual environment

New Linux distributions tend to implement the PEP668 directive which forbids the user (including root/admin/superuser) to install Python packages using pip (even in their home directory) because this can create conflicts with the system softver management tools (apt, pacman, …). You will recognize this situation if after pip you get

error: externally-managed-environment

To solve this you should use Python virtual environment . You create a new virtual environment named, say, myenv by

python -m venv  path/to/myenv

Then, every time you work on your code, you must activate it

source path/to/myenv/bin/activate

In this new environment you can than freely use pip to install Python packages, including gepard and all the requirements listed in the section above. These packages will be then available only within this virtual environment.

Availability within Jupyter

To make Gepard available in Jupyter notebooks, the easiest way is to install also Jupyter within this same virtual environment, using pip.

However, you may prefer to use the system Jupyter installed and upgraded by your OS. By default, this installation will use system’s Python, so packages installed only in virtual environment will not be available. To make them available, you need to make a copy of the Jupyter’s Python kernel within your new virtual env like this:

pip install ipykernel
python -m ipykernel install --user --name myenv --display-name "myenv (Gepard)"

Then in the system Jupyter, you will have a new python kernel myenv (Gepard) available, which you should use for your Gepard notebooks instead of the default Python 3 kernel.