pm4py is a python library that supports (state-of-the-art) process mining algorithms in python. It is completely open source and intended to be used in both academia and industry projects. pm4py is a product of the Fraunhofer Institute for Applied Information Technology.
The documentation about pm4py is offered at http://pm4py.org/
A very simple example, to whet your appetite:
import pm4py
log = pm4py.read_xes('<path-to-xes-log-file.xes>')
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(pnet, initial_marking, final_marking, format="svg")pm4py can be installed on Python 3.7.x / 3.8.x / 3.9.x / 3.10.x by doing:
pip install -U pm4pyTo track the incremental updates, we offer a CHANGELOG file.
Please cite pm4py as follows:
Berti, A., van Zelst, S.J., van der Aalst, W.M.P. (2019): Process Mining for Python (PM4Py): Bridging the Gap Between Process-and Data Science. In: Proceedings of the ICPM Demo Track 2019, co-located with 1st International Conference on Process Mining (ICPM 2019), Aachen, Germany, June 24-26, 2019. pp. 13-16 (2019). http://ceur-ws.org/Vol-2374/
As scientific library in the Python ecosystem, we rely on external libraries to offer our features. In the /third_party folder, we list all the licenses of our direct dependencies. Please check the /third_party/LICENSES_TRANSITIVE file to get a full list of all transitive dependencies and the corresponding license.