Metadata-Version: 2.4
Name: pybeamline
Version: 2.0.0
Summary: Streaming Process Mining
Author: Andrea Burattin
Project-URL: Homepage, https://beamline.cloud/
Project-URL: Issues, https://github.com/beamline/pybeamline/issues
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Dynamic: license-file

# Streaming process mining with `pyBeamline`

[![PyPI version](https://badge.fury.io/py/pybeamline.svg)](https://badge.fury.io/py/pybeamline)

`pyBeamline` is a Python version of Beamline. While the same set of ideas and principles of Beamline have been ported into `pyBeamline`, the underlying goal and technology is very different.

pyBeamline is based on ReactiveX and its Python binding RxPY. RxPY is a library for composing asynchronous and event-based programs using observable sequences and pipable query operators in Python. Using pyBeamline it is possible to inject process mining operators into the computation.

For a complete documentation of the library see https://www.beamline.cloud/pybeamline/. To install the library use:
```console
pip install pybeamline
```
Complete Jupyter notebooks presenting all techniques available are available at
* Classical process mining: https://github.com/beamline/pybeamline/blob/master/tutorial.ipynb
* Object-centric Process mining: https://github.com/beamline/pybeamline/blob/master/tutorial_oc.ipynb


<a href="https://colab.research.google.com/github/beamline/pybeamline/blob/master/tutorial.ipynb" target="_blank"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></img></a> Classic Process Mining<br>
<a href="https://colab.research.google.com/github/beamline/pybeamline/blob/master/tutorial_oc.ipynb" target="_blank"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></img></a> Object Centric Process Mining

[![codecov](https://codecov.io/gh/JepMik/pybeamline-OCPM/branch/master/graph/badge.svg)](https://codecov.io/gh/JepMik/pybeamline-OCPM)

