Orchestrating multi-step business processes (such as order fulfillment or document sign-offs) in distributed systems is difficult. If you rely on ad-hoc status columns and callbacks, your codebase will run into race conditions and unexpected state transitions. A State Machine Engine solves this by defining clear states, events, and validation guards, ensuring transitions only occur when all validation checks pass.

By implementing state machine libraries in Python, we can manage microservice workflows asynchronously.

1. Designing the State Machine Model

We write a Python state engine using transition libraries to define state diagrams and validate events:

# workflow_engine.py
from transitions import Machine

class DocumentWorkflow(object):
    # Define system states
    states = ['draft', 'pending_review', 'approved', 'rejected']

    def __init__(self):
        # Initialize state machine
        self.machine = Machine(model=self, states=DocumentWorkflow.states, initial='draft')
        
        # Define transitions
        # trigger, source, destination
        self.machine.add_transition('submit', 'draft', 'pending_review')
        self.machine.add_transition('approve', 'pending_review', 'approved')
        self.machine.add_transition('reject', 'pending_review', 'rejected')
        self.machine.add_transition('redraft', 'rejected', 'draft')

# Usage
doc = DocumentWorkflow()
print(f"Current state: {doc.state}") # draft
doc.submit()
print(f"Current state: {doc.state}") # pending_review

2. Restricting Unauthorized Transitions

By defining hook callbacks inside transitions, the engine validates user permissions and logs audit entries before executing state changes, preventing unauthorized actions.