Robust statechart for configurable automation rules.
A very simple example taken from specs.
>>> from superstate import StateChart
>>> class SimpleMachine(StateChart):
... state = {
... 'initial': 'created',
... 'states': [
... {
... 'name': 'created',
... 'transitions': [
... {'event': 'queue', 'target': 'waiting'},
... {'event': 'cancel', 'target': 'canceled'},
... ],
... },
... {
... 'name': 'waiting',
... 'transitions': [
... {'event': 'process', 'target': 'processed'},
... {'event': 'cancel', 'target': 'canceled'},
... ]
... },
... {'name': 'processed'},
... {'name': 'canceled'},
... ]
... }
>>> machine = SimpleMachine()
>>> machine.current_state
'AtomicState(created)'
>>> machine.trigger('queue')
>>> machine.current_state
'AtomicState(waiting)'
>>> machine.trigger('process')
>>> machine.current_state
'AtomicState(processed)'
>>> cancel_machine = SimpleMachine()
>>> cancel_machine.current_state
'AtomicState(created)'
>>> cancel_machine.trigger('cancel')
>>> cancel_machine.current_state
'AtomicState(canceled)'A Superstate state machine must have one initial state and at least one other additional state.
A state may have pre and post callbacks, for running some code on state on_entry
and on_exit, respectively. These params can be method names (as strings),
callables, or lists of method names or callables.
Transitions lead the machine from a state to another. Transitions must have
both event, and target parameters. The event is the method that have to be
called to launch the transition. The target is the state to which the
transition will move the machine. This method is automatically created
by the Superstate engine.
A transition can have optional action and cond parameters. action is a
method (or callable) that will be called when transition is launched. If
parameters are passed to the event method, they are passed to the action
method, if it accepts these parameters. cond is a method (or callable) that
is called to allow or deny the transition, depending on the result of its
execution. Both action and cond can be lists.
The same event can be in multiple transitions, going to different states, having
their respective needs as selectors. For the transitions having the same event,
only one cond should return a true value at a time.
pip install superstate
tox
Superstate is forked from https://github.com/nsi-iff/fluidity created by Rodrigo Manhães.