The library uses c++11 and requires Boost ≥ 1.48.0 and CMake ≥ 3.1. It is a multi-platform library and compiles on Linux, Mac OSX and Visual Studio 2015. It also requires cmake to generate makefiles, and cython to compile the library.

On Windows , only Python 3.5 and 3.6 are available because of the required Visual Studio version.

On other systems, if you have several Python/cython installed, the version 2.X will be used by default, but you can force it by adding -DPython_ADDITIONAL_VERSIONS=3 to the cmake command.

GUDHI Cythonization

To build the GUDHI cython module, run the following commands in a terminal:

cd /path-to-gudhi/
mkdir build
cd build/
cmake ..
make cython

Test suites

To test your build, py.test is optional. Run the following command in a terminal:

cd /path-to-gudhi/build/cython
# For windows, you have to set PYTHONPATH environment variable
export PYTHONPATH='$PYTHONPATH:/path-to-gudhi/build/cython'
ctest -R py_test

If tests fail, please try to import gudhi and check the errors. The problem can come from a third-party library bad link or installation.


To build the documentation, sphinx-doc is required. Please refer to file to see which sphinx-doc modules are required to generate the documentation. Run the following commands in a terminal:

make sphinx

Optional third-party library


The Alpha complex, Tangential complex and Witness complex data structures, and Bottleneck distance requires CGAL, which is a C++ library which provides easy access to efficient and reliable geometric algorithms.

Having CGAL, the Computational Geometry Algorithms Library, version 4.7.0 or higher installed is recommended. The procedure to install this library according to your operating system is detailed here.

The following examples requires CGAL version ≥ 4.7.0:

The following examples requires CGAL version ≥ 4.8.0:

The following examples requires CGAL version ≥ 4.8.1:

Threading Building Blocks

Intel® TBB lets you easily write parallel C++ programs that take full advantage of multicore performance, that are portable and composable, and that have future-proof scalability.

Having Intel® TBB installed is recommended to parallelize and accelerate some GUDHI computations.

Bug reports and contributions

Please help us improving the quality of the GUDHI library. You may report bugs or suggestions to:

GUDHI is open to external contributions. If you want to join our development team, please contact us.