Running multiple statecharts¶
It is not unusual to have to deal with multiple distinct components in which the behavior of a component is driven
by things that happen in the other components.
One can model such a situation using a single statechart with parallel states, or by plugging several statecharts
into one main statechart (see
The communication and synchronization between the components can be done either by using
guards, or by sending internal events that address other components.
However, we believe that this approach is not very convenient:
all the components must be defined in a single statechart;
state name collision could occur;
components must share a single execution context;
component composition is not easy to achieve
Sismic allows to define multiple components in multiple statecharts, and brings a way for those statecharts to communicate and synchronize via events.
Bind an interpreter (or a callable) to the current interpreter.
Internal events sent by this interpreter will be propagated as external events. If interpreter_or_callable is an Interpreter instance, its queue method is called. This is, if i1 and i2 are interpreters, i1.bind(i2) is equivalent to i1.bind(i2.queue).
This method is a higher-level interface for
x = interpreter.bind(...), use
interpreter.detach(x)to unbind a previously bound interpreter.
When an interpreter
interpreter_1 is bound to an interpreter
interpreter_1.bind(interpreter_2), the internal events that are sent by
interpreter_1 are automatically
propagated as external events to
The binding is not restricted to only two statecharts.
For example, assume we have three instances of
assert isinstance(interpreter_1, Interpreter) assert isinstance(interpreter_2, Interpreter) assert isinstance(interpreter_3, Interpreter)
We define a bidirectional communication between the two first interpreters:
We also bind the third interpreters with the two first ones.
When an internal event is sent by an interpreter, the bound interpreters also receive this event as an external
In the last example, when an internal event is sent by
interpreter_3, then a corresponding external event
is sent both to
Practically, unless you subclassed
Interpreter, the only difference between
internal and external events is the priority order in which they are processed by the interpreter.
from sismic.interpreter import InternalEvent # Manually create and raise an internal event interpreter_3._raise_event(InternalEvent('test')) print('Events for interpreter_1:', interpreter_1._select_event(consume=False)) print('Events for interpreter_2:', interpreter_2._select_event(consume=False)) print('Events for interpreter_3:', interpreter_3._select_event(consume=False))
Events for interpreter_1: Event('test') Events for interpreter_2: Event('test') Events for interpreter_3: InternalEvent('test')
bind() method is a high-level interface for
attach(). Internally, the former wraps given
interpreter or callable with an appropriate listener before calling
attach(). You can unbound a previously
bound interpreter with
This method accepts a previously attached listener, so you’ll need to keep track of the listener returned
by the initial call to
Example of communicating statecharts¶
Consider our running example, the elevator statechart. This statechart expects to receive floorSelected events (with a floor parameter representing the selected floor). The statechart operates autonomously, provided that we send such events.
Let us define a new statechart that models a panel of buttons for our elevator. For example, we consider that our panel has 4 buttons numbered 0 to 3.
statechart: name: Elevator buttons description: | Buttons that remotely control the elevator. root state: name: active parallel states: - name: button_0 transitions: - event: button_0_pushed action: send('floorSelected', floor= 0) - name: button_1 transitions: - event: button_1_pushed action: send('floorSelected', floor= 1) - name: button_2 transitions: - event: button_2_pushed action: send('floorSelected', floor= 2) - name: button_3 transitions: - event: button_3_pushed action: send('floorSelected', floor= 3)
As you can see in the YAML version of this statechart, the panel expects an event for each button: button_0_pushed, button_1_pushed, button_2_pushed and button_3_pushed. Each of those event causes the execution of a transition which, in turn, creates and sends a floorSelected event. The floor parameter of this event corresponds to the button number.
We bind our panel with our elevator, such that the panel can control the elevator:
from sismic.io import import_from_yaml from sismic.interpreter import Interpreter elevator = Interpreter(import_from_yaml(filepath='examples/elevator/elevator.yaml')) buttons = Interpreter(import_from_yaml(filepath='examples/elevator/elevator_buttons.yaml')) # Elevator will receive events from buttons buttons.bind(elevator)
Events that are sent to
buttons are not propagated, but events that are sent by
are automatically propagated to
print('Awaiting event in buttons:', buttons._select_event()) # None buttons.queue('button_2_pushed') print('Awaiting event in buttons:', buttons._select_event()) # External event print('Awaiting event in elevator:', elevator._select_event()) # None buttons.execute(max_steps=2) # (1) initialize buttons, and (2) consume button_2_pushed print('Awaiting event in buttons:', buttons._select_event()) # Internal event print('Awaiting event in elevator:', elevator._select_event()) # External event
Awaiting event in buttons: None Awaiting event in buttons: Event('button_2_pushed') Awaiting event in elevator: None Awaiting event in buttons: InternalEvent('floorSelected', floor=2) Awaiting event in elevator: Event('floorSelected', floor=2)
The execution of bound statecharts does not differ from the execution of unbound statecharts:
elevator.execute() print('Current floor:', elevator.context.get('current'))
Current floor: 2
Synchronizing the clock¶
Each interpreter in Sismic has its own clock to deal with time (see Dealing with time).
When creating an interpreter, it is possible to specify which clock should be used to compute the
time attribute of the interpreter.
When multiple statecharts have to be run concurrently, it is often convenient to have their
time synchronized. This can be achieved (to some extent) by providing a shared instance
of a clock to their interpreter.
from sismic.io import import_from_yaml elevator_sc = import_from_yaml(filepath='examples/elevator/elevator.yaml') buttons_sc = import_from_yaml(filepath='examples/elevator/elevator_buttons.yaml') from sismic.clock import SimulatedClock from sismic.interpreter import Interpreter # Create the clock and share its instance with all interpreters clock = SimulatedClock() elevator = Interpreter(elevator_sc, clock=clock) buttons = Interpreter(buttons_sc, clock=clock)
SimulatedClock is the default clock used in Sismic, we could have written the three
last lines of this example as follow:
elevator = Interpreter(elevator_sc) buttons = Interpreter(buttons_sc, clock=elevator.clock)
We can now execute the statecharts and check their time value.
clock.start() elevator_step = elevator.execute_once() buttons_step = buttons.execute_once() clock.stop()
As a single instance of a clock is used by both interpreter, the values exposed by their clocks are obviously the same:
assert elevator.clock.time == buttons.clock.time
However, even if the clock is the same for all interpreters, this does not always mean that the calls
execute_once() are all performed at the same time.
Depending on the time required to process the first
execute_once, the second one will be called
with a delay of (at least) a few milliseconds.
assert elevator_step.time != buttons_step.time assert elevator.time != buttons.time
from sismic.clock import SynchronizedClock elevator = Interpreter(elevator_sc) buttons = Interpreter(buttons_sc, clock=SynchronizedClock(elevator))
With the help of this
SynchronizedClock, it is possible to perfectly “align” the time of several
interpreters. Obviously, in this context, we first need to execute the interpreter that “drives” the time:
elevator.clock.start() elevator_step = elevator.execute_once() buttons_step = buttons.execute_once() elevator.clock.stop()
Now we can check that the time of the last executed steps are the same:
assert elevator_step.time == buttons_step.time assert elevator.time == buttons.time
While the two interpreters were virtually executed at the same time value,
their clocks still have different values as a
SynchronizedClock is based
time attribute of given interpreter and not on its internal clock.
assert elevator.clock.time != buttons.clock.time
Because the time of an interpreter is set by the clock each time
execute_once() is called, you should avoid using
execute() (that repeatedly calls
execute_once()) if you want a perfect synchronization between two or more interpreters.
In our example, a call to
execute() instead of
execute_once() for the first interpreter implies that the time value of the second interpreter will equal the time value of the first interpreter after having executed all its macro steps.
In other words, the execution of the second interpreter will be synchronized with the execution of the last macro step of the first interpreter in that case.