Metadata-Version: 2.1
Name: pm4py
Version: 1.3.2
Summary: Process Mining for Python
Home-page: http://www.pm4py.org
Author: Fraunhofer Institute for Applied Technology
Author-email: pm4py@fit.fraunhofer.de
License: GPL 3.0
Project-URL: Documentation, http://www.pm4py.org
Project-URL: Source, https://github.com/pm4py/pm4py-source
Project-URL: Tracker, https://github.com/pm4py/pm4py-source/issues
Platform: UNKNOWN
Requires-Dist: pyvis
Requires-Dist: networkx
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: lxml
Requires-Dist: graphviz
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: pydotplus
Requires-Dist: pulp
Requires-Dist: pytz
Requires-Dist: intervaltree
Requires-Dist: deprecation
Requires-Dist: stringdist
Requires-Dist: tqdm
Requires-Dist: ciso8601 ; python_version < "3.7"
Requires-Dist: pm4pycvxopt ; python_version < "3.8"

Welcome to Process Mining for Python!

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.

The official website of the library is http://pm4py.org/

You can always check out (changes to) the source code at the github repo.

A very simple example, to whet your appetite:

from pm4py.algo.discovery.alpha import algorithm as alpha_miner
from pm4py.objects.log.importer.xes import importer as xes_importer
from pm4py.visualization.petrinet import visualizer as petri_visualizer

log = xes_importer.apply('<path-to-xes-log-file>')
net, initial_marking, final_marking = alpha_miner.apply(log)
gviz = petri_visualizer.apply(net, initial_marking, final_marking)
petri_visualizer.view(gviz)


