SimpleFSM is an easy-to-use Python module to model Finite State Machines. The module itself consists in just three classes :
- State
- Transition
- SimpleFSM
Initially you create states and transitions and after that you create your custom FSM by inheriting from the SimpleFSM class and implementing 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.
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.
The Transition class models a transition between two states. To create a transition you should write :
state_a = State('A', start_state=True, final_state=True)
state_b = State('B', final_state=True)
transition_a_b = Transition(state_a, state_b, lambda x: 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.
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 (maximum 10 bits) binary numbers :
from simplefsm import State, SimpleFSM, Transition
from simplefsm.exceptions import FSMEndOfInput
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, final_state=True)
state_b = State('B', final_state=True)
is_zero = lambda i: i == 0
is_one = lambda i: i == 1
# Transitions.
transitions = [
Transition(state_a, state_a, is_zero),
Transition(state_b, state_b, is_one),
Transition(state_a, state_b, is_one),
Transition(state_b, state_a, is_zero),
]
# FSM.
input_length = randint(1, 10)
fsm = BinaryFSM([randint(0, 1) for i in range(0, input_length)])
fsm.add_states([state_a, state_b])
fsm.add_transitions(transitions)
return fsm
def main():
fsm = build_fsm()
accepted_word = [str(i) for i in fsm.run()]
print 'Accepted word : {:}.'.format(''.join(accepted_word))
if __name__ == '__main__':
main()In the above example all the transitions are lambdas but you can use any defined function as well, the functions should take only one argument (the symbol that is being evaluated) and return a bool.
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.
As mentioned previously there are two methods available to execute code before and/or after a transition takes place. If you need to do this then you must implement any of these abstract methods in your FSM class :
class YourFSM(SimpleFSM):
def pre_transit(self, *args, **kwargs):
...
def post_transit(self, *args, **kwargs):
...Clone this repository to a temporary directory using GIT (or alternatively download as .zip), and run :
git clone https://github.com/lliendo/SimpleFSM.git
cd SimpleFSM
python setup.py installSimpleFSM is distributed under the GNU LGPLv3 license.
- Lucas Liendo.