Installation

Note

For now only source-code installations are available.

Requirements

For the C++ library.

• a C/C++ compiler compatible with at least C++11

• cmake >= v2.8

For the Python bindings a Python virtual environment.

Tip

A good all-in-one recommended solution is to install mambaforge and create the environment using the environment.yml file that you can find in the root of the repository.

Get the source code

Compressed archives of the released versions of the package are available here.

If you want to use the development version, get the repository by cloning it from GitHub,

git clone https://github.com/jimbraun/XCDF

C++ library

Configure the project,

cmake -DCMAKE_INSTALL_PREFIX=$INSTALL_DIR -S XCDF -B build

where $INSTALL_DIR is the final installation directory you want to use.

Build it,

cmake --build build -- -jN

with N number of threads to use for compilation.

Finally, install it

cmake --install .

For pure make instructions, please refer to the INSTALL file.

The installation directory will be filled by the bin, include and lib subdirectories. Remember to export (or check) the appropriate environment variables for your system for the executables, headers, and libraries to be found.

Important

The current minum required version of CMake is quite old (v2.8) and some commands might be probably different. Please, refer to CMake’s documentation.

Python3 bindings

Bindings for Python3 are created using pybind11 and the Python package is created using scikit-build

scikit-build allows making a package out of the Python bindings, so to obtain them you can simply do one of the following,

pip install $PATH_TO_XCDF_REPOSITORY

Similarly, to also run the tests with pytest,

pip install "$PATH_TO_XCDF[tests]"

Important

Python2 bindings are discontinued since XCDF>=v3.00.03. We strongly encourage to upgrade to more recent versions (see also Python Release Cycle).

Editable installs

This type of installation is usually recommended when developing Python code (see setuptools documentation ).

Unfortunately, scikit-build seems to have some limitations in this regard. In case you end up with this use case, please refer to this list of known issues for more details.