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PM4Py

Free#13 of 29 in Process Mining Software

PM4Py: A broad, developer-focused process-mining toolkit with self-hosted deployment and manual refresh. Ranked #13 of 29 in Process Mining Software by our editors (7.9/10); pricing: Free plan; best for developers needing extensible open-source mining.

7.9/10Editor score
PM4Py7.9 Visit PM4Py

At a glance

  • Editor score
    7.9 / 10
  • Pricing
    Free plan
  • Best for
    Developers needing extensible open-source mining
  • Free plan
    Yes
  • Paid from
    Free
  • Conformance checking
    Yes
  • Facts checked
    19 Sep 2026
PM4Py screenshot
  • Where it wins

    • Free AGPL community version for teaching, research, and open-source projects
    • Covers discovery, conformance, root-cause, performance, and object-centric mining
    • Includes SAP and Camunda connectors plus event-log anonymization
  • Where it doesn't

    • Requires self-hosted deployment and developer-led implementation
    • Process-data refresh is manual rather than automated
    • Not suited to teams seeking verified live process monitoring

Our verdict on PM4Py

PM4Py is an open-source Python library for developers, researchers, and organizations building custom process-mining applications. It works across Windows, macOS, and Linux through self-hosted deployment, with capabilities for process discovery, conformance checking, root-cause analysis, performance and throughput analysis, predictive mining, organizational analysis, and event-log visualization. Its audience is technical teams that want to extend a library or build process-mining applications rather than adopt a ready-made hosted workspace.

The Community Version is distributed through GitHub under the GNU AGPL v3 license and is intended for teaching, research, and open-source projects. The Commercial Version adds an individual commercial license, closed-source commercial use, and dedicated professional support. Feature breadth is a major reason to consider PM4Py: alongside standard event-log mining, it includes object-centric process mining, machine-learning utilities, process-model visualization and export, and LLM-based helpers for log abstraction and filtering. Differential-privacy anonymization also supports privacy-conscious event-log preparation.

PM4Py fits ecosystems that can provide event data through SAP and Camunda connectors, while its listed integrations also include Outlook, Google Chrome, Mozilla Firefox, GitHub, OpenAI, Google APIs, and Anthropic APIs. The library's documentation assumes event data has already been extracted, and its category profile specifies manual data refresh. That makes it a strong choice for developers building tailored analytical workflows, but a weaker fit for teams that need automated refresh, live process monitoring, or a managed interface. Those teams should choose a process-mining product designed around monitoring and operational use rather than a self-hosted Python library.

Your product? Our editors can test PM4Py in depth and publish a review, labelled as paid · from $149/mo →

PM4Py pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on processintelligence.solutions

All 2 PM4Py plans and prices →

PM4Py fact sheet

Free planYes
Paid fromFree
Conformance checkingYes
Root-cause analysisYes
Process monitoringNot verified
Data refreshManual
Deployment modelSelf_hosted
Included eventsNot verified
ERP connectorsYes
DeploymentDesktop, Self-hosted
PlatformsWindows, macOS, Linux
Integrations9 integrations: SAP, Camunda, Outlook, Google Chrome, Mozilla Firefox, GitHub …
PricingFree plan (source)
Websiteprocessintelligence.solutions
Facts checked19 Sep 2026

PM4Py integrations

PM4Py lists 9 integrations on its own site.

  • SAP
  • Camunda
  • Outlook
  • Google Chrome
  • Mozilla Firefox
  • GitHub
  • OpenAI
  • Google APIs
  • Anthropic APIs

Alternatives to PM4Py

See all PM4Py alternatives →

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Featured on iTechGuides

Featured on iTechGuides — PM4Py 7.9/10

PM4Py is listed in our Process Mining Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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