The installation of the latest stable version is easy using the python package manager pip.

pip install skpro

skpro depends on the scikit-learn package and its respective dependencies numpy and scipy which will be pulled in automatically during installation. Furthermore, you may install optional package dependencies that enhance the workflow components (i.e. uncertainties and tabulate).

pip install skpro[workflow]

That’s it. You are now ready to go. We recommend reading the user guide to get started.

Bleeding edge

To test or develop new features you may want to install the latest package version from the development branch (bleeding edge installation).

Clone the source from our public code repository on GitHub and change into the skpro directory. Make sure that all dependencies are installed:

pip install -r requirements.txt

Then run

python develop

to install the package into the activated Python environment. To build the documentation run

python docs

Note that bleeding edge installations are likely contain bugs are not recommended for productive environments.

If you like to contribute to documentation please refer to our contribution guide.