https://github.com/pm4py/pm4py-core

Public repository for the PM4Py (Process Mining for Python) project.
https://github.com/pm4py/pm4py-core

data-mining data-science machine-learning process-mining python

Last synced: 2 months ago
JSON representation

Public repository for the PM4Py (Process Mining for Python) project.

• Host: GitHub
• URL: https://github.com/pm4py/pm4py-core
• Owner: pm4py
• License: gpl-3.0
• Created: 2018-07-03T07:23:27.000Z (almost 6 years ago)
• Default Branch: release
• Last Pushed: 2024-04-22T09:08:15.000Z (2 months ago)
• Last Synced: 2024-04-23T07:38:45.210Z (2 months ago)
• Topics: data-mining, data-science, machine-learning, process-mining, python
• Language: Python
• Homepage: https://pm4py.fit.fraunhofer.de
• Size: 105 MB
• Stars: 642
• Watchers: 33
• Forks: 254
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

Lists

• awesome-python-machine-learning - pm4py - PM4Py is a python library that supports (state-of-the-art) process mining algorithms in python. (Uncategorized / Uncategorized)

README

        
# pm4py

pm4py is a python library that supports (state-of-the-art) process mining algorithms in python. 

It is open source (licensed under GPL) and intended to be used in both academia and industry projects.

pm4py is a product of the Fraunhofer Institute for Applied Information Technology.

## Documentation / API

The full documentation of pm4py can be found at https://pm4py.fit.fraunhofer.de

## First Example

A very simple example, to whet your appetite:

```python

import pm4py

if __name__ == "__main__":

    log = pm4py.read_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 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, stringdist, tqdm

* *Optional requirements* (not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar, pygetwindow, pynput

## Release Notes

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

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

BiBTeX:

```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},  

}

```