statmach

Pythonic Finite State Machine

State machines represent different states, and the transition between states that have a repetitive sequence that is pre-determined. Examples are many appliances (kettle, toaster, etc.), machines in general (traffic lights, factory automation, etc.), and stateful software (UI screens, wizards, etc.). These are very broad categories of uses and therefore state machines are common.

A frequent characteristic of a state machine is that the input events arrive asynchronously and therefore adding a formal structure is useful otherwise the code becomes difficult to understand, debug, and maintain. You can 'roll-your-own' state machine; but using a pre-tested module, like this one, is both easier and more reliable. In particular, error handling is very tricky to get right.

At a top (most abstract) level state machines are easy to code, just:

List the inputs (events). Actually a set of events because you can't have repeats. Also, the set is finite, i.e. can't have an infinite number of inputs. In practice state machines are only practical if the number of events is less than about 100.
List the states. Again actually a set, no repeats. Again only practical up to a few 100.
List the transitions from one state to the next in response to an event and at the same time give the new output.

The above requirements are often represented as a state diagram, which helpful to document code (see example diagrams below).

Installation

The code is written in Python 3.5 and is designed run on MicroPython (making it suitable for real hardware) as well as desktop (normal) Python. All the code is in one small file (statmach.py).

pip install --upgrade statmach
Copy statmach.py into your project (probably needed for a Micropython project - IDE dependent).

Terminology Used in this Module

The overall state machine is a Machine.
The state machine has States.
Inputs to the machine are events, which are typically enum members.
The response of a State to an event is an action, which is a tuple of: new-state and new-output.
Events are fired into the Machine and the actions give the new states and new outputs.

Making a State Machine

The steps to make a state machine are:

Define input events, typically using an enum or class with just class attributes.
Define outputs, which is often an enum but could be as complicated as a function to execute to obtain a derived value or as simple as None (the default) if the output is a side effect of entry and exit to the state (common in embedded applications).
Define states (class State).
Define actions (tuples of new state and new value) to take when events fire (add actions to the states and the machine).
Define a Machine using a with statement.
Fire events into the machine and obtain outputs.

E.g. an edge detector (it detects when its input changes from 0 to 1 or vice versa and outputs a 1 if it does, otherwise a 0):

States are traditionally drawn as circles; and the initial state is marked with a double circle (shown in black). States traditionally have an identifier, because it is easier to follow what is happening if a state is uniquely identified. The identifiers are inside the circles that representing the states. Actions are the arrows from one state to the next (shown in blue). Inputs that cause the action to be taken are above the line on the action annotation (shown in green). Outputs that result when the action is taken are below the line on the action annotation (shown in red).

from enum import Enum
from statmach import  State, Machine

Bit = Enum('Bit', 'ZERO ONE')  # 1. & 2. Define the inputs (in this case also the outputs).

s_i = State(ident='i')  # 3. Define the states.
s_0 = State(ident=0)
s_1 = State(ident=1)

s_i.actions = {Bit.ZERO: (s_0, Bit.ZERO), Bit.ONE: (s_1, Bit.ZERO)}  # 4. Define the actions.
s_0.actions = {Bit.ZERO: (s_0, Bit.ZERO), Bit.ONE: (s_1, Bit.ONE)}
s_1.actions = {Bit.ZERO: (s_0, Bit.ONE), Bit.ONE: (s_1, Bit.ZERO)}

with Machine(initial_state=s_i) as machine:  # 5. Define the machine.
    assert machine.state is s_i
    assert machine.fire(event=Bit.ZERO) is Bit.ZERO  # 6. Fire events and obtain outputs.
    assert machine.state is s_0
    assert machine.fire(event=Bit.ZERO) is Bit.ZERO
    assert machine.state is s_0
    assert machine.fire(event=Bit.ONE) is Bit.ONE
    assert machine.state is s_1
    assert machine.fire(event=Bit.ONE) is Bit.ZERO
    assert machine.state is s_1
    assert machine.fire(event=Bit.ZERO) is Bit.ONE
    assert machine.state is s_0

Note how the startup is dealt with, initially outputting a 0 for either input. This special start up condition is achieved using a start up state that is not used again after the first event is fired. This unique startup state is a common feature of state machines.

The edge detector is an example of a state machine that has an output associated with each action; these are called Mealy Machine (see below).

A more complicated example is a traffic light machine:

This state diagram has three features that are different from the edge detector diagram above:

The output is associated with the state not the action, i.e. all transition to a given state result in the same output. This is denoted in the diagram by the below the line output shown on the state (in red) and not on the action annotation.
The machine has actions that are the default for all states, shown as a dotted line that does not originate from a state (shown in blue). These machine actions are 'overridden' by state actions, hence their dotted nomenclature to indicate lesser.
There is no way out of state 'flashing_red' (it is a terminal failure); other than restarting the machine so that it goes back to 'red'.

The traffic light example has two common requirements: the events arrive asynchronously, and it is important (because it is safety critical) that all events are dealt with even if they arrive unexpectedly. For example if the traffic light is red when the amber timeout occurs, this is an error because the machine is waiting for the red timeout not the amber.

Note in the diagram, upper left, how the unexpected events and the error event are dealt with for the whole machine, rather than coding this requirement on all states individually. These machine actions can be 'overridden' by a state; so for example when in the red state and the red timer finished the next state is green, as expected (not an error).

The advantage of the machine dealing with common actions is that the actions of the state machine are much easier to follow.

from enum import Enum, auto
from statmach import  State, Machine

class Inputs(Enum):  # 1. The inputs.
    RED_TIMEOUT = auto()
    AMBER_TIMEOUT = auto()
    GREEN_TIMEOUT = auto()
    ERROR = auto()

class Outputs(Enum):  # 2. The outputs.
    RED = auto()
    AMBER = auto()
    GREEN = auto()
    FLASHING_RED = auto()

flashing_red = State(ident='flashing_red', value=Outputs.FLASHING_RED)  # 3. The states.
red = State(ident='red', value=Outputs.RED)
amber = State(ident='amber', value=Outputs.AMBER)
green = State(ident='green', value=Outputs.GREEN)

red.actions[Inputs.RED_TIMEOUT] = green.action  # 4a. The *state* actions.
green.actions[Inputs.GREEN_TIMEOUT] = amber.action
amber.actions[Inputs.AMBER_TIMEOUT] = red.action

with Machine(initial_state=red) as machine:  # 5. The machine.
    machine.actions[Inputs.RED_TIMEOUT] = flashing_red.action  # 4b. The *machine* actions.
    machine.actions[Inputs.AMBER_TIMEOUT] = flashing_red.action
    machine.actions[Inputs.GREEN_TIMEOUT] = flashing_red.action
    machine.actions[Inputs.ERROR] = flashing_red.action

    assert machine.state is red
    assert machine.fire(event=Inputs.RED_TIMEOUT) is Outputs.GREEN  # 6. Fire events and obtain outputs.
    assert machine.state is green
    assert machine.fire(event=Inputs.GREEN_TIMEOUT) is Outputs.AMBER
    assert machine.state is amber
    assert machine.fire(event=Inputs.AMBER_TIMEOUT) is Outputs.RED
    assert machine.state is red
    assert machine.fire(event=Inputs.AMBER_TIMEOUT) is Outputs.FLASHING_RED
    assert machine.state is flashing_red
    assert machine.fire(event=Inputs.ERROR) is Outputs.FLASHING_RED
    assert machine.state is flashing_red

Note how the defining actions in this case are split between state actions, 4a, and machine actions, 4b, which makes the code shorter, easier to maintain, and easier to debug.

The traffic light machine is an example of a state machine that has an output associated with each state, these are called Moore Machines (see below).

The traffic light example can be run on real hardware, for example a PyBoard. The complete project is on Github. The code is below and is an example of a third type of state machine, one were the output is a side effect of entering and leaving the states (it is therefore a variation on a Moore Machine). In particular side effects of the __entry__ and __exit__ methods control the outputs:

from statmach import State, Machine
from pyb import LED, Timer, wfi, Switch
from micropython import alloc_emergency_exception_buf, schedule

alloc_emergency_exception_buf(200)


def main():
    print('Traffic lights running ...')

    class Events:
        RED_TIMEOUT = 1
        AMBER_TIMEOUT = 2
        GREEN_TIMEOUT = 3
        ERROR = 4
        START = 5

    start = State(ident='start')  # Special start state to allow for initialization before operation.

    timer0 = 10

    class FlashingRed(State):  # Special fault state that should never exit.
        def __init__(self):
            super().__init__(ident='error')
            self.timer = Timer(timer0 + 4)
            self.led = LED(1)

            # noinspection PyUnusedLocal
            def toggle_with_arg(not_used):  # Toggle func that accepts an arg, because ``schedule`` *needs* an arg.
                self.led.toggle()

            self.led_tog_ref = toggle_with_arg  # Store the function reference locally to avoid allocation in interrupt.

        def __enter__(self):
            self.timer.init(freq=2, callback=lambda _: schedule(self.led_tog_ref, None))
            return self

        def __exit__(self, exc_type, exc_val, exc_tb):
            self.led.off()
            self.timer.deinit()

    flashing_red = FlashingRed()

    traffic_lights = Machine(initial_state=start)  # The traffic light machine.
    traffic_lights.actions[Events.RED_TIMEOUT] = flashing_red.action  # Catch anything unexpected.
    traffic_lights.actions[Events.AMBER_TIMEOUT] = flashing_red.action
    traffic_lights.actions[Events.GREEN_TIMEOUT] = flashing_red.action
    traffic_lights.actions[Events.ERROR] = flashing_red.action
    traffic_lights.actions[Events.START] = flashing_red.action

    tl_fire_ref = traffic_lights.fire  # Store the function reference locally to avoid allocation in interrupt.
    error = Switch()
    error.callback(lambda: schedule(tl_fire_ref, Events.ERROR))

    class LEDState(State):  # Output is determined by ``__enter__`` and ``__exit__`` (common in embedded machines).
        def __init__(self, led_num, time_on, event):
            super().__init__(ident=led_num)  # Use the LED num as the ident.
            self.led = LED(self.ident)  # The LED to use.
            self.timer = Timer(timer0 + self.ident)  # The timer to use.
            self.timeout = time_on  # Time to wait before firing event.
            self.event = event  # Event to fire at end of time_on.

        def __enter__(self):
            self.led.on()
            self.timer.init(freq=1 / self.timeout, callback=lambda _: schedule(tl_fire_ref, self.event))
            return self

        def __exit__(self, exc_type, exc_value, traceback):
            self.led.off()
            self.timer.deinit()
            return False

    red = LEDState(led_num=1, time_on=3, event=Events.RED_TIMEOUT)
    green = LEDState(led_num=2, time_on=3, event=Events.GREEN_TIMEOUT)
    amber = LEDState(led_num=3, time_on=0.5, event=Events.AMBER_TIMEOUT)

    red.actions[Events.RED_TIMEOUT] = green.action
    green.actions[Events.GREEN_TIMEOUT] = amber.action
    amber.actions[Events.AMBER_TIMEOUT] = red.action
    start.actions[Events.START] = red.action

    with traffic_lights:
        _ = traffic_lights.fire(event=Events.START)  # Start the machine once all the setup is complete.
        while True:  # Keep running timers (and other peripherals), but otherwise do nothing.
            wfi()


if __name__ == '__main__':
    main()

This Micropython code is as the desktop Python traffic-light code above, except that the output occurs in the __entry__ and __exit__ methods. In particular these methods start and stop timers and turn LEDs on and off. The timers in turn schedule events to fire when they timeout. The usr switch on the PyBoard board is used to simulate a fault.

A further difference between the Micropython and desktop code is that the Micropython code has a start state, this state is to allow the state machine to be initialized before it is started (which is common for state machines).

The state machine's value can be anything including a function or method to call. This allows for states that have additional state that is not part of the state machine 'per se', which is common for in UI applications were the state machine determines which screen is displayed but not its contents. A simple example of 'extra' state is a state that records how long it is 'the' state of the state machine:

from statmach import  State, Machine
from time import time

class StateTime(State):
  def __init__(self):
      super().__init__(value=self.state_active_time)  # Value is a function.
      self._enter_time = None

  def state_active_time(self):
      return time() - self._enter_time

  def __enter__(self):
      self._enter_time = time()
      return self

  def __exit__(self, exc_type, exc_val, exc_tb):
      self._enter_time = None
      return False

state_active_time = 1
s = StateTime()
s.actions[state_active_time] = s.action
with Machine(initial_state=s) as m:
  assert m.fire(state_active_time)() >= 0  # Value is a function which is called, 2nd `()`.

For more state machine examples see test_statmach.py.

Pythonic Aspects of this Module

Both State and Machine are context managers, which allows for enter and exit code and error handling.
Use Python with for executing a Machine.
Code is compatible with Python 3.5+ and MicroPython 1.12+.

Formal Definition

The state machine implemented is a Mealy machine, see https://en.wikipedia.org/wiki/Mealy_machine, but a Moore Machine (https://en.wikipedia.org/wiki/Moore_machine), the other common type of state machine, can also be easily represented by giving a state a value and using the state's action method when registering events. The formal definition of a Mealy machine is a 5-tuple (S, S0, Σ, Λ, T) that consisting of the following:

A finite set of states S. Class State represents a state.
A start state (also called initial state) S0 which is an element of S. When a Machine is created it must be given an initial state.
A finite set called the input alphabet Σ. Inputs are unique objects, typically members of an enum.
A finite set called the output alphabet Λ. The output is any type.
A combined transition and output function T : S × Σ → S × Λ. The transitions are actions on each state that are called when the corresponding event fires, the actions give the new state and new output.

In the strictest sense the state machine implemented by this module is superset of a Mealy Machine because:

The code does not enforce that there are a fixed set of states, S, and this set can be added to or removed from whilst executing the machine. However, the set of events handled is constant.
Although the set of events handled is constant the actions associated with the events can be changed whilst executing the machine.
Both the machine and the state classes can be extended to add extra fields to them (thus giving extra state that is not part of the state machine 'per se').
Side effects of the __entry__ and __exit__ methods can be the outputs (common in embedded applications).
Has extensive error control via Python exceptions and error handling by __exit__ methods.
Has machine actions that can be 'overridden' by state actions.

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

README.md

README.md

statmach

Pythonic Finite State Machine

Installation

Terminology Used in this Module

Making a State Machine

Pythonic Aspects of this Module

Formal Definition

Files

README.md

Latest commit

History

README.md

File metadata and controls

statmach

Pythonic Finite State Machine

Installation

Terminology Used in this Module

Making a State Machine

Pythonic Aspects of this Module

Formal Definition