Spiff Workflow is a workflow engine implemented in pure Python. It is based
on the excellent work of the
Workflow Patterns initiative.
Do you need commercial support?
Spiff Workflow is supported by Procedure 8. Get in touch if you need anything!
Main design goals
- Spiff Workflow aims to directly support as many of the patterns of
workflowpatterns.com as possible.
- Spiff Workflow uses unit testing as much as possible.
- Spiff Workflow provides a clean Python API.
- Spiff Workflow allows for mapping patterns into workflow elements that
are easy to understand for non-technical users in a workflow GUI editor.
- Spiff Workflow implements the best possible path prediction for
Spiff Workflow also provides a parser and workflow emulation
layer that can be used to create executable Spiff Workflow specifications
from Business Process Model and Notation (BPMN) documents.
The process of using Spiff Workflow involves the following steps:
- Write a workflow specification. A specification may be written using
- Run the workflow using the Python API. Example code for running the workflow:
from SpiffWorkflow.specs import WorkflowSpec from SpiffWorkflow.serializer.prettyxml import XmlSerializer from SpiffWorkflow import Workflow # Load the workflow specification: with open('my_workflow.xml') as fp: serializer = XmlSerializer() spec = WorkflowSpec.deserialize(serializer, fp.read()) # Create an instance of the workflow, according to the specification. wf = Workflow(spec) # Complete tasks as desired. It is the job of the workflow engine to # guarantee a consistent state of the workflow. wf.complete_task_from_id(...) # Of course, you can also persist the workflow instance: xml = Workflow.serialize(XmlSerializer, 'workflow_state.xml')
Full documentation is here: