Depending on what you plan to do with xtb-python there are two recommended ways to install.

If you plan to use this project in your workflows, proceed with the Installation with Conda. If you plan to develop on this project, proceed with Building from Source.

For the basic functionalities the xtb-python project requires following packages:


Additionally the project provides a calculator implementation for ASE (see Atomic Simulation Environment) which becomes available if the ase package is installed. For integration with the QCArchive infrastructure (see QCSchema Integration) the qcelemental package is required.

Of course, the package depends on the extended tight binding program package as well, directly or indirectly. Depending on how xtb-python was packaged it requires an installation of xtb or it will be able to provide its own. For more details on the xtb API dependency see Building from Source.

Installation with Conda

For details on how to setup conda look up the conda documentation.

Installing xtb-python from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge

Once the conda-forge channel has been enabled, xtb-python can be installed with:

conda install xtb-python

It is possible to list all of the versions of xtb-python available on your platform with:

conda search xtb-python --channel conda-forge

To install the additional dependencies for ASE and QCArchive integration use

conda install qcelemental ase

Building from Source

To install xtb-python from source clone the repository from GitHub with

git clone
cd xtb-python

Building the Extension Module

To work with xtb-python it is necessary to build the extension to the xtb API first, this is accomplised by using meson and the C foreign function interface (CFFI). Following modules should be available to build this project:

meson  # build only

To install the meson build system first check your package manager for an up-to-date meson version, usually this will also install ninja as dependency. Alternatively, you can install the latest version of meson and ninja with pip (or pip3 depending on your system):

pip install cffi numpy meson ninja

If you prefer conda as a package manage you can install meson and ninja from the conda-forge channel. Make sure to select the conda-forge channel for searching packages.

conda config --add channels conda-forge
conda install cffi numpy meson ninja

Now, setup the project by building the CFFI extension module from the xtb API with:

meson setup build --prefix=$HOME/.local
ninja -C build install

Meson cannot find xtb dependency

If meson cannot find your xtb installation check if you have pkg-config installed and that xtb can be found using

pkg-config xtb --print-errors

In case this fails ensure that the xtb.pc file is in a directory in the PKG_CONFIG_PATH and retry. For the official release tarball you possible have to edit the first line of xtb.pc to point to the location where you installed xtb:

--- a/lib/pkgconfig/xtb.pc
+++ b/lib/pkgconfig/xtb.pc
@@ -1,4 +1,4 @@


Installs from conda-forge should work out-of-box.

Helpful Tools

We aim for a high quality code base and encourage substainable development models.

Please, install a linter like flake8 or pylint to catch errors before they become bugs. Also, typehints are mandatory in this project, you should typecheck locally with mypy. A consistent coding style is enforced by using black, every source file should be reformatted using black, the only exceptions are tests.