8c673c4fb6
SpiffWorkflow -
- start_messages function should return message names, not ids.
- don't catch external thrown messages within the same workflow process
- add an expected value to the Correlation Property Model so we can use this well defined class as an external communication tool (rather than building an arbitrary dictionary)
- Added a "get_awaiting_correlations" to an event, so we can get a list of the correlation properties related to the workflows currently defined correlation values.
- workflows.waiting_events() function now returns the above awaiting correlations as the value on returned message events
Backend
- Dropping MessageModel and MessageCorrelationProperties - at least for now. We don't need them to send / receive messages though we may eventually want to track the messages and correlations defined across the system - these things (which are ever changing) should not be directly connected to the Messages which may be in flux - and the cross relationships between the tables could cause unexpected and unceissary errors. Commented out the caching logic so we can turn this back on later.
- Slight improvement to API Errors
- MessageInstances are no longer in a many-to-many relationship with Correlations - Each message instance has a unique set of message correlations specific to the instance.
- Message Instances have users, and can be linked through a "counterpart_id" so you can see what send is connected to what recieve.
- Message Correlations are connected to recieving message instances. It is not to a process instance, and not to a message model. They now include the expected value and retrieval expression required to validate an incoming message.
- A process instance is not connected to message correlations.
- Message Instances are not always tied to a process instance (for example, a Send Message from an API)
- API calls to create a message use the same logic as all other message catching code.
- Make use of the new waiting_events() method to check for any new recieve messages in the workflow (much easier than
churning through all of the tasks)
- One giant mother of a migration.
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| .. | ||
| .github/workflows | ||
| SpiffWorkflow | ||
| doc | ||
| graphics | ||
| scripts | ||
| tests | ||
| .editorconfig | ||
| .flake8 | ||
| .gitignore | ||
| .readthedocs.yml | ||
| .sonarcloud.properties | ||
| .tool-versions | ||
| .travis.yml | ||
| AUTHORS | ||
| CONTRIB | ||
| COPYING | ||
| Dockerfile | ||
| INSTALL | ||
| Makefile | ||
| README.md | ||
| TODO | ||
| VERSION.in | ||
| pyproject.toml | ||
| requirements.txt | ||
| setup.py | ||
| sonar-project.properties | ||
| unit_test_extensions.patch | ||
| version.sh | ||
README.md
SpiffWorkflow
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
Code style
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/BYHcc7PpUC
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