Integrations¶

MachineMixin¶

Domain models can inherit from MachineMixin to automatically instantiate and bind a StateChart to any Python class. This is the foundation for integrating state machines with ORMs and other domain objects.

Example¶

Given this state machine:

>>> from statemachine import StateChart, State

>>> from statemachine.mixins import MachineMixin

>>> class CampaignMachine(StateChart):
...     "A workflow machine"
...     draft = State('Draft', initial=True, value=1)
...     producing = State('Being produced', value=2)
...     closed = State('Closed', value=3, final=True)
...     cancelled = State('Cancelled', value=4, final=True)
...
...     add_job = draft.to.itself() | producing.to.itself()
...     produce = draft.to(producing)
...     deliver = producing.to(closed)
...     cancel = cancelled.from_(draft, producing)

You can attach it to a model by inheriting from MachineMixin and setting state_machine_name to the fully qualified class name:

>>> from statemachine import registry
>>> registry.register(CampaignMachine)  # register for lookup by qualname
<class '...CampaignMachine'>
>>> registry._initialized = True  # skip Django autodiscovery in doctest

>>> class Workflow(MachineMixin):
...     state_machine_name = '__main__.CampaignMachine'
...     state_machine_attr = 'sm'
...     state_field_name = 'workflow_step'
...     bind_events_as_methods = True
...
...     workflow_step = 1

>>> model = Workflow()

>>> isinstance(model.sm, CampaignMachine)
True

>>> model.workflow_step
1

>>> model.sm.draft in model.sm.configuration
True

With bind_events_as_methods = True, events become methods on the model itself:

>>> model = Workflow()
>>> model.produce()
>>> model.workflow_step
2

>>> model.sm.cancel()  # you can still call the SM directly

>>> model.workflow_step
4

>>> model.sm.cancelled in model.sm.configuration
True

Note

In this example state_machine_name uses a __main__ prefix because the class is defined inline for doctest purposes. In your code, use the fully qualified path (e.g., 'myapp.statemachines.CampaignMachine').

Django integration¶

When used in a Django App, this library implements an auto-discovery hook similar to how Django’s built-in admin autodiscover.

This library attempts to import a statemachine or statemachines module in each installed application. Such modules are expected to register StateChart classes to be used with the MachineMixin.

Hint

We advise keeping StateChart definitions in their own modules to avoid circular references. If you place state machines in modules named statemachine or statemachines inside installed Django Apps, they will be automatically imported and registered.

That said, nothing stops you from declaring your state machine alongside your models.

Django example¶

# campaign/statemachines.py

from statemachine import StateChart
from statemachine import State


class CampaignMachine(StateChart):
    "A workflow machine"
    draft = State('Draft', initial=True, value=1)
    producing = State('Being produced', value=2)
    closed = State('Closed', value=3)
    cancelled = State('Cancelled', value=4)

    add_job = draft.to.itself() | producing.to.itself()
    produce = draft.to(producing)
    deliver = producing.to(closed)
    cancel = cancelled.from_(draft, producing)

Integrate with your Django model using MachineMixin:

# campaign/models.py

from django.db import models

from statemachine.mixins import MachineMixin


class Campaign(models.Model, MachineMixin):
    state_machine_name = 'campaign.statemachines.CampaignMachine'
    state_machine_attr = 'sm'
    state_field_name = 'step'

    name = models.CharField(max_length=30)
    step = models.IntegerField()

Data migrations¶

Django’s apps.get_model() returns historical model classes that are dynamically created and don’t carry user-defined class attributes like state_machine_name. Since version 2.6.0, MachineMixin detects these historical models and gracefully skips state machine initialization, so data migrations that use apps.get_model() work without errors.

Note

The state machine instance will not be available on historical model objects. If your data migration needs to interact with the state machine, set the attributes manually on the historical model class:

def backfill_data(apps, schema_editor):
    MyModel = apps.get_model("myapp", "MyModel")
    MyModel.state_machine_name = "myapp.statemachines.MyStateMachine"
    for obj in MyModel.objects.all():
        obj.statemachine  # now available