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Comments on A state machine in Python

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A state machine in Python

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I've written the following code implementing a state machine in Python, and I'd like some feedback on it.

The basic idea is that each state has a set of corresponding actions that trigger a state change. You can register observer functions with states, which are then called whenever the state is entered.

"""
State machine
"""

from typing import Callable, Iterable, Mapping, List, Optional


ObserverFunction = Callable[[str, Optional["State"], "State"], None]


class State:
    """
    Describes a single state
    """
    def __init__(self, name: str, action_map: Mapping[str, str],
                 observers: Optional[Iterable[ObserverFunction]] = None):
        self._name = name
        self._observers: List[ObserverFunction] = list(observers or [])
        self._action_map = action_map


    def __str__(self):
        return self._name


    def register(self, observer: ObserverFunction) -> None:
        """
        Register an observer.
        """
        self._observers.append(observer)


    def enter(self, action: str, prev_state: Optional["State"] = None) -> None:
        """
        Notify all observers that this now is the current state
        """
        for observer in self._observers:
            observer(action, prev_state, self)


    def next_state(self, state_machine: "StateMachine", action: str) -> "State":
        """
        return the new state caused by the action
        """
        if not action in self._action_map:
            raise ValueError(f"State {self} does not support action {action}")
        new_state = state_machine.get_state(self._action_map[action])

        return new_state


    def get_actions(self) -> Iterable[str]:
        """
        return the possible actions on the state
        """
        return self._action_map.keys()


    def is_final(self):
        """
        Return if this state is final, that is, no actions are defined.
        """
        return not self._action_map



class StateMachine:
    """
    Describes a state machine
    """
    def __init__(self, description: Iterable[State], first: str):
        state_names = []
        for state in description:
            name = str(state)
            if name in state_names:
                raise ValueError(f"Duplicate state name: {name}")
            state_names.append(name)

        if not first in state_names:
            raise ValueError(f"No state {first} in {description}")

        self._states = { str(state): state for state in description }
        self._current_state = self._states[first]
        self._current_state.enter("initial state")


    def perform(self, action: str) -> None:
        """
        Perform an action on the current state machine.

        An action potentially changes the state, notifying its observers.
        """
        prev_state = self._current_state
        self._current_state = prev_state.next_state(self, action)
        self._current_state.enter(action, prev_state)


    def get_state(self, name: str) -> State:
        """
        Get state by name
        """
        try:
            return self._states[name]
        except KeyError as error:
            raise ValueError(f"State machine does not contain state {name}") from error


    def get_current_state(self) -> State:
        """
        Get the current state
        """
        return self._current_state


    def has_terminated(self):
        """
        Return True if the state machin has reached a final state
        """
        return self._current_state.is_final()


    def get_all_actions(self):
        """
        Get the set of all actions of all states in the state machine
        """
        all_actions = set()
        for state in self._states.values():
            all_actions.update(state.get_actions())
        return all_actions

The following code demonstrates the intended use:

from statemachine import State, StateMachine


def report(action, old_state, new_state):
    if action == "initial state":
        action = "exist"

    print(f"I was {old_state or 'nothing'}, but you wanted me to {action}, so now I'm {new_state}.") 


def tell_emotion(action, old_state, new_state):
    feelings = {
        'waiting': 'boring',
        'running': 'exhausting',
        'sleeping': 'refreshing' }
    feeling = feelings[str(new_state)]
    print(f"To be {new_state} is {feeling}.")


def final_message(*args):
    print("You monster!")


def main():
    sm = StateMachine([State('waiting',
                             { 'sleep': 'sleeping', 
                               'run': 'running', 
                               'die': 'dead' },
                             [report, tell_emotion]), 
                       State('sleeping',
                             { 'wake up': 'waiting', 
                               'die': 'dead' },
                             [report, tell_emotion]), 
                       State('running',
                             { 'stop': 'waiting', 
                               'die': 'dead' },
                             [report, tell_emotion]), 
                       State('dead', {}, [report, final_message])], 
                      "waiting")
    all_actions = sm.get_all_actions()

    try:
        while not sm.has_terminated(): 
            state = sm.get_current_state()
            print("Available actions:", ", ".join(state.get_actions()))
            try:
                action = input("what should I do? ")
                sm.perform(action)
            except ValueError:
                if action in all_actions:
                    print(f"I can't {action} when I'm {state}!")
                else:
                    print(f"I don't know how to {action}!")
    except EOFError:
        print("Hey, you disappeared!")


if __name__ == '__main__':
    main()
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2 comment threads

other state machine examples (1 comment)
Context/Goal? (2 comments)
Context/Goal?
Derek Elkins‭ wrote almost 2 years ago

While there are some aspects that seem like a bad idea generically, e.g. having State depend on StateMachine, it's hard to judge what advice to give without knowing what you're trying to accomplish. For example, a state machine used in the implementation of a regex engine has very different requirements than a state machine used for a game AI. Some other questions are: How rich can the state be? Is it just a meaningless token or can it be some rich model? Will there be many instances of the same state machine or will each state machine usually only have one thing going through it? Do the state machines need to be serializable or visualizable?

celtschk‭ wrote almost 2 years ago

The goal is to use it for my game, but not as game AI, but to manage different phases. I started out with just values for the current state, which originally were only used to report a result (was the level won, lost, saved or quit, was the menu quit or terminates, etc.), then moved on to also encode whether the game is still running, whether it was paused, etc., and it got a bit of a mess as the logic is spread across several classes.

The idea is to collect that logic in a separate state machine to which the different classes can register callbacks. It is important that the states can be distinguished, that you have callbacks on state changes registered to specific states (so you don't get notified about states you are not interested in), that you can distinguish non-terminal states from terminal states, and that you can decide on the exact logic at construction time. I might also attach additional information to the states.