Understand state machines in Python and how to implement them

A state machine is a behavioral model that defines how an object responds to events. In Python, state machines are typically implemented as finite state machines (FSM). FSM is a mathematical calculation model that can be used to design digital logic circuits and computer programs. It consists of a set of states, transitions between states, and operations performed when transitions occur.

Finite state machine (FSM) can be represented as a directed graph, with states represented as nodes and transitions represented as edges. Edges are labeled with events that trigger transitions, and actions are associated with the edges.

Dynamic Properties of State Machines

When we create a state machine, the module creates a special set of properties for each state that exists in the machine. We can use instances and properties to check if the property is applicable to the state.

Write a general finite state machine in Python

class StateMachine:
def __init__(self):
self.handlers={}
self.startState=None
self.endStates=[]
def add_state(self,name,handler,end_state=0):
name=name.upper()
self.handlers[name]=handler
if end_state:
self.endStates.append(name)
def set_start(self,name):
self.startState=name.upper()
def run(self,cargo):
try:
handler=self.handlers[self.startState]
except:
raise InitializationError("must call.set_start()before.run()")
if not self.endStates:
raise InitializationError("at least one state must be an end_state")
while True:
(newState,cargo)=handler(cargo)
if newState.upper()in self.endStates:
print("reached",newState)
break
else:
handler=self.handlers[newState.upper()]

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