Download the windows installer GenX-3.X.X_win64_setup.exe from the home page and follow the instructions in the installation guide.

Mac OS

Binary packages for Mac OS are provided as GenX-3.X.X_Installer.dmg images that can directly be installed. If you are having trouble with this distribution you can try installing from source. (And create a trouble ticket, please.)

Install the required python 3 packages, especially wxPython. I would advice using a new Anaconda environment. Afterwards you can install GenX from source. The anaconda environment packages that are known to work can be found in conda_build.yml


Install the requirements, at least wxPython, from your package manager (Ubuntu python3-wxgtk4.0). Then either install from source or, if you are using Ubuntu or a derivative, you can use the pre build .deb packages for your system python version.


The most convenient way to install GenX on Linux is the new snap package. It ships all requirements and should work on any distribution where the snap package management tool is installed. (e.g. all Ubuntu derivatives have it pre-installed) See for instructions how to install snapd on your distribution.

To install via snap use:

sudo snap install genx

While convenient, the snap package currently has the limitation that using parallel processing during fit is not supported as the strict confinement does not work with the python multiprocessing library. The multi-core parallelization provided by numba JIT compilation is still available so that the impact on actual fit performance is relatively small for non-trivial models.


GenX can make use of MPI to run models on cluster systems. In many cases the user does not have the rights to install libraries and there are various configurations that can be configured and make installation of own libraries pretty complicated. On the other hand, fitting with GenX from command line does not require the wx or matplotlib libraries to be present.

In case the cluster does not provide a python installation that is new enough (>=3.6), you can try to make use of the Miniconda distribution, all required software can be installed as a user without too much background knowladge of Linux configurations.

Using system python

  • Create python virtual environment
    python -m venv /path/to/new/virtual/environment
    source /path/to/new/virtual/environment/bin/activate # script depends on your used shell
  • Install via pip with you local python, which should install all requirements automatically
    python -m pip install genx3server

Using Minconda

  • Install Miniconda:

  • Prepare anaconda environment and required packages
    conda create -n genx python=3.9
    conda activate genx
    conda install pip appdirs h5py scipy psutil numba
    pip install orsopy bumps
    • Depending on configuration you might need to install other libraries like glib if the installed libraries are too old.

    • I don’t recommend to use the mpi version of anaconda but instead follow the instructions on how to install mpi4py for the local mpi library using pip:

  • Finally install the server package for GenX:
    pip install genx3server
  • Tip: You can configure conda environments to update environment variables when they are activated. This can become handy if you need to selec specific library versions, PATH or LD_LIBRARY_PATH. conda env config vars set NAME=value.

From source

Download the source distribution GenX-3.X.X.tar.gz and unpack it. Run the file scripts/genx directly:

tar -xvzf GenX-3.X.X.tar.gz
cd GenX-3.X.X
python3 scripts/genx

You can also install it in your python 3 environment as user pip3 install --user genx3 or system wide sudo pip3 install genx3 and run:

pip3 install --user genx3


You can create a suitable anaconda environment using the following commands, i:

conda create --name genx python=3.9 matplotlib appdirs h5py scipy numba psutil pymysql
conda activate genx
conda install wxpython # you might need a different channel, e.g. conda-forge
pip install genx3
# if the command is not recognized you can try instead
python -m

You can also try download this environment file with conda env create --file conda.yml.


The needed dependencies are:

  • Python >= 3.6

  • wxPython version > 4.0

  • Numpy version > 1.0

  • Scipy version > 0.5

  • Matplotlib version > 0.9

  • appdirs version > 1.2

  • h5py

  • orsopy

The non-mandotary packages are

  • mpi4py (with an MPI installation)

  • numba (calculation speedup by Just In Time compiler)

  • vtk (graphical display of unit cells)

On a Linux system these packages can usually be installed through the package manager. On a windows and OSX systems the anaconda distribution contains all packages.