PM4Py

PM4Py is a python library that supports state-of-the-art process mining algorithms in Python. It is open source and intended to be used in both academia and industry projects.

PM4Py is managed and developed by PIS — Process Intelligence Solutions (https://processintelligence.solutions/), a spin-off from the Fraunhofer Institute for Applied Information Technology FIT where PM4Py was initially developed.

Licensing

The open-source version of PM4Py, available on GitHub (https://github.com/process-intelligence-solutions/pm4py), is licensed under the GNU Affero General Public License version 3 (AGPL-3.0).

We offer a separate version of PM4Py for commercial use in closed-source environments under a different license. For more information about the licensing options for using PM4Py in closed-source settings, please visit https://processintelligence.solutions/pm4py#licensing.

Documentation / API

The documentation of PM4Py can be found at https://processintelligence.solutions/pm4py/.

First Example

Here is a simple example to spark your interest:

import pm4py

if __name__ == "__main__":
    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(net, initial_marking, final_marking, format="svg")

Installation

PM4Py can be installed on Python 3.9.x / 3.10.x / 3.11.x / 3.12.x / 3.13.x / 3.14.x by invoking:

pip install -U pm4py

Optional features can be installed through extras. For example:

pip install -U "pm4py[polars,ml]"

Use pip install -U "pm4py[all]" to install every optional feature supported on the current platform.

For a reproducible installation using the exact dependency versions validated by the project, use:

pip install -U "pm4py[stable]"

PM4Py is also running on older Python environments with different requirements sets, including:

Python 3.8 (3.8.10): third_party/old_python_deps/requirements_py38.txt

Requirements

The default installation contains the dependencies needed for mainstream usage. Additional integrations are grouped by feature in pyproject.toml:

calendars: workalendar
connectors: requests
llm: openai and requests
ml: pyemd and scikit-learn
ocel: jsonschema and pyarrow
polars: Polars dataframe support
solvers: cvxopt
stable: the exact dependency versions validated by the project and used by CI
visualization: pyvis
windows: pygetwindow, pynput, and pywin32 (Windows only)

For a source checkout, install the project with python -m pip install -e .. Build, CI, and lint dependencies are standard dependency groups and can be installed with, for example, python -m pip install --group lint.

Polars integration supports 1.40.1 and 2.x. Joins used in filtering and enrichment preserve event order, including when lazy queries use the streaming engine (the default in Polars 2.0).

For optional PuLP support, PM4Py selects the backend for the installed PuLP version (3.x or 4.x). PuLP 4 requires CBC to be installed separately: use python -m pip install 'pulp[cbc]' or put cbc on PATH. SciPy remains the default LP solver.

Release Notes

To track the incremental updates, please refer to the CHANGELOG.md file.

Contributing

If you want to contribute to PM4Py, please review the contributing guidelines and Contributor License Agreement (CLA).

Third Party Dependencies

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.

Citing PM4Py

If you are using PM4Py in your scientific work, please cite PM4Py as follows:

Alessandro Berti, Sebastiaan van Zelst, Daniel Schuster. (2023). PM4Py: A process mining library for Python. Software Impacts, 17, 100556. doi: 10.1016/j.simpa.2023.100556

DOI | Article Link

BiBTeX:

@article{pm4py,  
title = {PM4Py: A process mining library for Python},  
journal = {Software Impacts},  
volume = {17},  
pages = {100556},  
year = {2023},  
issn = {2665-9638},  
doi = {https://doi.org/10.1016/j.simpa.2023.100556},  
url = {https://www.sciencedirect.com/science/article/pii/S2665963823000933},  
author = {Alessandro Berti and Sebastiaan van Zelst and Daniel Schuster},  
}

Legal Notice

This repository is managed by Process Intelligence Solutions (PIS). Further information about PIS can be found online at https://processintelligence.solutions.

Metadata

Release files for pm4py 2.7.23.11

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Source distribution (sdist)

Source distribution for pm4py 2.7.23.11
File	Size	Uploaded
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Table of built distributions (wheels) for pm4py 2.7.23.11
File	Interpreter	ABI	Platform	Reset
pm4py-2.7.23.11-py3-none-any.whl 2.7 MB Oct 15, 2026	Python 3	none	any	Details

Total release size: 3.9 MB

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Download URL	pm4py-2.7.23.11-py3-none-any.whl
Size	2.7 MB
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