# process-intelligence-solutions/pm4py

Official public repository for PM4Py (Process Mining for Python) — an open-source library for exploring, analyzing, and optimizing business processes with Python.

Repository: https://github.com/process-intelligence-solutions/pm4py
Canonical: https://ross.abutalabs.com/products/pm4py
Homepage: https://processintelligence.solutions/pm4py
Language: Python
License: AGPL-3.0
License Family: copyleft
Topics: machine-learning, data-mining, data-science, python, processmining
Last push: 2026-08-31T11:26:21+00:00

## Health v2 (maintenance only)
Score: 87/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 100, release rhythm 63, longevity 100
- inputs: {"age_days": 2983, "days_push": 2, "days_rel": 166, "gap_med": 69.0, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1019, forks 357 (observed 2026-09-01T02:14:06.035540+00:00)

## What it is
PM4Py is an open-source Python library implementing state-of-the-art process mining algorithms for analyzing event logs and business processes. It supports process discovery, conformance checking, and performance analysis, and is used in both academia and industry.

## Use cases
- discover process models from event logs
- read and analyze XES event log files
- check conformance of real processes against a model
- find bottlenecks in business processes
- convert event logs to BPMN or Petri net models
- analyze process variants and performance

## When to choose
- you need programmatic process mining in Python
- you work with XES or CSV event logs from information systems
- you want open-source process discovery and conformance checking algorithms
- you are doing academic research on business processes

## When to avoid
- you need a no-code graphical process mining tool for business users
- you require a permissive license for closed-source commercial use (AGPL-3.0 applies)
- your data is not event-log shaped

## Facets
- artifact type: library
- maturity: stable
- function: data-science, machine-learning, analytics, data-visualization, parser
- domain: data-science, analytics
- platform: python, cross-platform
- tags: process-mining, event-logs, xes, bpmn, petri-nets, conformance-checking, process-discovery, automation, business-process-mining

## Member repositories
- process-intelligence-solutions/pm4py (main) score 87

## Provenance
- Observed fields: from GitHub, fetched 2026-09-01T02:14:06.035540+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:11:27.917516+00:00, confidence not recorded.
  - readme: https://github.com/process-intelligence-solutions/pm4py (fetched 2026-09-01T02:14:06.035540+00:00, sha 15aa016d10d0)
  - homepage: https://processintelligence.solutions/pm4py (fetched 2026-08-29T13:10:50.832125+00:00, sha b9e6cdcb0c9e)
  - site_page: https://processintelligence.solutions/pm4py/features (fetched 2026-08-29T13:10:50.841543+00:00, sha b9e6cdcb0c9e)
  - site_page: https://processintelligence.solutions/pm4py/installation (fetched 2026-08-29T13:10:50.843511+00:00, sha b9e6cdcb0c9e)
  - site_page: https://processintelligence.solutions/pmtk/documentation (fetched 2026-08-29T13:10:50.848741+00:00, sha b9e6cdcb0c9e)
  - registry_pypi: https://pypi.org/pypi/pm4py/json (fetched 2026-08-29T13:10:50.850442+00:00, sha dff21b7d41ac)
  - site_page: https://processintelligence.solutions/pm4py/api (fetched 2026-08-29T13:10:50.845306+00:00, sha b9e6cdcb0c9e)
  - site_page: https://processintelligence.solutions/pmtk (fetched 2026-08-29T13:10:50.847053+00:00, sha b9e6cdcb0c9e)
- Data as of 2026-08-30T08:39:29.467469+00:00.