# 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

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

PM4Py depends on some other Python packages, with different levels of importance:

  • Essential requirements: numpy, pandas, deprecation, networkx

  • Normal requirements (installed by default with the PM4Py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, tqdm

  • Optional requirements (not installed by default): requests, pyvis, jsonschema, workalendar, pyarrow, scikit-learn, polars, openai, pyemd, pyaudio, pydub, pygame, pywin32, pygetwindow, pynput

## 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)](https://processintelligence.solutions/pm4py/contributing).

## 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](https://doi.org/10.1016/j.simpa.2023.100556) | [Article Link](https://www.sciencedirect.com/science/article/pii/S2665963823000933)

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.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2.7.23.8)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Javert899 from gravatar.com Javert899

Credits

Author: Process Intelligence Solutions (PIS)

License

AGPL 3.0

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pm4pyminimal-2.7.23.6.tar.gz (1.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pm4pyminimal-2.7.23.6-py3-none-any.whl (2.7 MB view details)

Uploaded Python 3

File details

Details for the file pm4pyminimal-2.7.23.6.tar.gz.

File metadata

  • Download URL: pm4pyminimal-2.7.23.6.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for pm4pyminimal-2.7.23.6.tar.gz
Algorithm Hash digest
SHA256 436b132dc755873fe50d69b3aa8fa43051a80644c4531f7845ac7f9cc3062a9e
MD5 4ce5f417393ecd8f6125119e2081620b
BLAKE2b-256 bbc9a3a2e4647607a7ef678b34d668fc434dae925ca178b4bfeb286b567e63b2

See more details on using hashes here.

File details

Details for the file pm4pyminimal-2.7.23.6-py3-none-any.whl.

File metadata

File hashes

Hashes for pm4pyminimal-2.7.23.6-py3-none-any.whl
Algorithm Hash digest
SHA256 87eabfe634e48a70ff9428c870f7ecbaab7c9e04a7dda8c52d17a0dd037d6256
MD5 e1e9a4fbadd1d83ac7434399006653b7
BLAKE2b-256 1dd8af1f0925e358c6e94d7045aae06d01ca4105be80c4f11bd22a2594a65721

See more details on using hashes here.

Release history Release notifications | RSS feed

2.7.23.8

2 files

2.7.23.7

2 files

This release

2.7.23.6 This release

2 files

2.7.23.5

2 files

2.7.23.4

2 files

2.7.23.3

2 files

2.7.23.2

2 files

2.7.23.1

2 files

2.7.23

2 files

2.7.22.5

2 files

2.7.22.4

2 files

2.7.22.3

2 files

2.7.22.2

2 files

2.7.22.1

2 files

2.7.22

2 files

2.7.20.2

2 files

2.7.20.1

2 files

2.7.19.8

2 files

2.7.19.7

2 files

2.7.19.6

2 files

2.7.19.5

2 files

2.7.19.4

2 files

2.7.19.3

2 files

2.7.19.2

2 files

2.7.19.1

2 files

2.7.19

2 files

2.7.18.2

2 files

2.7.18.1

2 files

2.7.18

2 files

2.7.17.2

2 files

2.7.17.1

2 files

2.7.17

2 files

2.7.16.2

2 files

2.7.16.1

2 files

2.7.16

2 files

2.7.15.3

2 files

2.7.15.2

2 files

2.7.15.1

2 files

2.7.15

2 files

2.7.14.5

2 files

2.7.14.4

2 files

2.7.14.3

2 files

2.7.14.2

2 files

2.7.14.1

2 files

2.7.14

2 files

2.7.13.1

2 files

2.7.12.4

2 files

2.7.12.3

2 files

2.7.12.2

2 files

2.7.12.1

2 files

2.7.11.14

2 files

2.7.11.13

2 files

2.7.11.12

2 files

2.7.11.11

2 files

2.7.11.10

2 files

2.7.11.9

2 files

2.7.11.8

2 files

2.7.11.7

2 files

2.7.11.6

2 files

2.7.11.5

2 files

2.7.11.4

2 files

2.7.11.3

2 files

2.7.11.2

2 files

2.7.11.1

2 files

2.7.11

2 files

2.7.10.3

2 files

2.7.10.2

2 files

2.7.10.1

2 files

2.7.9.4

2 files

2.7.9.3

2 files

2.7.9.2

2 files

2.7.9.1

2 files

2.7.8.4

2 files

2.7.8.3

2 files

2.7.8.2

2 files

2.7.8.1

2 files

2.7.8

2 files

2.7.6.0.1

2 files

2.7.5.3

2 files

2.7.5.2.2

2 files

2.7.5.1

2 files

2.7.5

2 files

2.7.4

2 files

2.7.3

2 files

2.7.2

2 files

2.7.1.1

2 files

2.7.1

2 files

2.6.1

2 files

2.6.0

2 files

2.2.31

2 files

2.2.25

2 files

2.2.23

2 files

2.2.22.0.1

2 files

2.2.21

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page