Welcome to PM4Py’s Documentation!#
PM4Py is a Python library implementing a variety of process mining algorithms.
A simple example of PM4Py in action:
import pm4py
if __name__ == "__main__":
log = pm4py.read_xes('<path-to-xes-log-file.xes>')
process_model = pm4py.discover_bpmn_inductive(log)
pm4py.view_bpmn(process_model)
In this documentation, you can find all relevant information to set up PM4Py and start your process mining journey.
Please consult the contents listed below to navigate the documentation.
Happy #ProcessMining!
Contents#
- pip
- Docker
- Getting Started
- API Reference
- Input (
pm4py.read) - Output (
pm4py.write) - Conversion (
pm4py.convert) - Process Discovery (
pm4py.discovery) - Conformance Checking (
pm4py.conformance) - Visualization (
pm4py.vis) - Statistics (
pm4py.stats) - Filtering (
pm4py.filtering) - Machine Learning (
pm4py.ml) - Simulation (
pm4py.sim) - Object-Centric Process Mining (
pm4py.ocel) - LLM Integration (
pm4py.llm) - Basic Connectors (
pm4py.connectors) - Social Network Analysis (
pm4py.org) - Privacy (
pm4py.privacy) - Utilities (
pm4py.utils) - List of Methods
- Input (
- Release Notes