Introduction

SimpleFSM is an extremely easy-to-use Python module to model Finite State Machines in an object-oriented way. The module itself consists in just three simple classes :

• State
• Transition
• SimpleFSM

Initially you would create states and transitions and after that you would implement your custom FSM by inheriting from the SimpleFSM class and overriding the read_symbol() method.

Two other methods may (optionally) be implemented and its purpose is to do pre-processing and post-processing provided that you need to run custom code before and/or after a symbol is processed.

State class

The State class models a particular state of your FSM. To create a state you only need to issue :

state_a = State('A')

This will create a state using "A" as an id. Note that all the states of a FSM must have differents ids otherwise when adding two states with the same id to the FSM an exception is raised.

Another two keyword arguments may optionally be set to mark a state as a start and/or final state :

state_a = State('A', start_state=True, final_state=True)
state_b = State('B', final_state=True)

Note that by default a state is not marked as a start or final state. It's also important to remark that only a state among all others must be marked as a start state and at least a final state must be also marked as well.

Transition class

The Transition class models a transition between two states. To create a transition you would write :

state_a = State('A', start_state=True, final_state=True)
state_b = State('B', final_state=True)
transition_zero = Transition(State("A"), State("B"), lambda x: str(x) == '0')

The above code builds a transition between state A and state B and the transition will take place only if the processed symbol equals zero.

SimpleFSM class

This class is the core of the simplefsm module. Once you have built all your states, transitions and the custom FSM you are ready to go. The following is a full example that shows how to create a FSM that accepts arbitrary binary numbers :

from simplefsm.models import *
from random import randint


class BinaryFSM(SimpleFSM):
    def __init__(self, input):
        super(BinaryFSM, self).__init__()
        self._index = 0
        self._input = input

    def read_symbol(self):
        try:
            symbol = self._input[self._index]
            self._index += 1
        except IndexError:
            raise FSMEndOfInput

        return symbol


def build_fsm():
    # States
    state_a = State('A', start_state=True)
    state_b = State('B', final_state=True)

    # Transitions.
    transition_a_self = Transition(state_a, state_a, lambda s: str(s) == '0')
    transition_b_self = Transition(state_b, state_b, lambda s: str(s) == '1')
    transition_a_b = Transition(state_a, state_b, lambda s: str(s) == '1')
    transition_b_a = Transition(state_b, state_a, lambda s: str(s) == '0')

    # FSM.
    input_length = randint(1, 10)
    fsm = BinaryFSM([str(randint(0, 1)) for i in range(0, input_length)])
    fsm.add_states([state_a, state_b])
    fsm.add_transitions([transition_a_self, transition_b_self, transition_a_b, transition_b_a])

    return fsm

def main():
    fsm = build_fsm()
    accepted_word = fsm.run()
    print("Accepted word : {0}".format("".join(accepted_word)))

if __name__ == '__main__':
    main()

Is important to note that when implementing the read_symbol() method and no more input is available you must raise the FSMEndOfInput exception to notify SimpleFSM that you've reached the end of the input that you're evaluating.

Installation

To install SimpleFSM, run:

$ python setup.py install