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SpiffWorkflow

Logo

Spiff Workflow is a workflow engine implemented in pure Python. It is based on the excellent work of the Workflow Patterns initiative. In 2020 and 2021, extensive support was added for BPMN / DMN processing.

Motivation

We created SpiffWorkflow to support the development of low-code business applications in Python. Using BPMN will allow non-developers to describe complex workflow processes in a visual diagram, coupled with a powerful python script engine that works seamlessly within the diagrams. SpiffWorkflow can parse these diagrams and execute them. The ability for businesses to create clear, coherent diagrams that drive an application has far reaching potential. While multiple tools exist for doing this in Java, we believe that wide adoption of the Python Language, and it's ease of use, create a winning strategy for building Low-Code applications.

Build status

Build Status Quality Gate Status Coverage Maintainability Rating Documentation Status Issues Pull Requests

Code style

PEP8

Dependencies

We've worked to minimize external dependencies. We rely on lxml for parsing XML Documents, and there is some legacy support for Celery, but it is not core to the implementation, it is just a way to interconnect these systems. Built with

Features

  • BPMN - support for parsing BPMN diagrams, including the more complex components, like pools and lanes, multi-instance tasks, sub-workflows, timer events, signals, messages, boudary events and looping.
  • DMN - We have a baseline implementation of DMN that is well integrated with our Python Execution Engine.
  • Forms - forms, including text fields, selection lists, and most every other thing you can be extracted from the Camunda xml extension, and returned as json data that can be used to generate forms on the command line, or in web applications (we've used Formly to good success)
  • Python Workflows - We've retained support for building workflows directly in code, or running workflows based on a internal json data structure.

A complete list of the latest features is available with our release notes for version 1.0.

Code Examples and Documentation

Detailed documentation is available on ReadTheDocs Also, checkout our example application, which we reference extensively from the Documentation.

Installation

pip install spiffworkflow

Tests

cd tests/SpiffWorkflow
coverage run --source=SpiffWorkflow -m unittest discover -v . "*Test.py"

Support

You can find us on Discord at https://discord.gg/zDEBEnrF

Commercial support for SpiffWorkflow is available from Sartography

Contribute

Pull Requests are and always will be welcome!

Please check your formatting, assure that all tests are passing, and include any additional tests that can demonstrate the new code you created is working as expected. If applicable, please reference the issue number in your pull request.

Credits and Thanks

Samuel Abels (@knipknap) for creating SpiffWorkflow and maintaining it for over a decade.

Matthew Hampton (@matthewhampton) for his initial contributions around BPMN parsing and execution.

The University of Virginia for allowing us to take on the mammoth task of building a general-purpose workflow system for BPMN, and allowing us to contribute that back to the open source community. In particular, we would like to thank Ron Hutchins, for his trust and support. Without him our efforts would not be possible.

Bruce Silver, the author of BPMN Quick and Easy Using Method and Style, whose work we referenced extensively as we made implementation decisions and educated ourselves on the BPMN and DMN standards.

The BPMN.js library, without which we would not have the tools to effectively build out our models, embed an editor in our application, and pull this mad mess together.

Kelly McDonald (@w4kpm) who dove deeper into the core of SpiffWorkflow than anyone else, and was instrumental in helping us get some of these major enhancements working correctly.

Thanks also to the many contributions from our community. Large and small. From Ziad (@ziadsawalha) in the early days to Elizabeth (@essweine) more recently. It is good to be a part of this long lived and strong community.

License

GNU LESSER GENERAL PUBLIC LICENSE