David Beazley - Implementing stateful objects or state machines in Python
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- Book:Implementing stateful objects or state machines in Python
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Abstract: This lesson is a recipe from the Python Cookbook that explores the problem of wanting to implement a state machine or an object that operates in a number of different states, without littering your code with a lot of conditionals. It teaches key solutions such as encoding each operational state as a separate class and arranging for one class to delegate to another class, or directly manipulating certain attributes of instances. What youll learnand how you can apply it Learn how to implement a state machine or an object that operates in a number of different states, but doesnt litter your code with a lot of conditionals. Youll also learn how to encode each operational state as a separate class and arrange for one class to delegate to the other class. Finally, see how to directly manipulate the class attribute of instances. This lesson is for you because Youre an experienced Python programmers who is looking to deepen your understanding of the language and modern programming idioms, such as the advanced techniques used by libraries, frameworks, and applications. Prerequisites Moderate experience as a Python programmer Materials or downloads needed none
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You want to implement a state machine or an object that operates in anumber of different states, but dont want to litter your code with alot of conditionals.
In certain applications, you might have objects that operate differentlyaccording to some kind of internal state. For example, consider asimple class representing a connection :
classConnection(object):def__init__(self):self.state='CLOSED'defread(self):ifself.state!='OPEN':raiseRuntimeError('Not open')print('reading')defwrite(self,data):ifself.state!='OPEN':raiseRuntimeError('Not open')print('writing')defopen(self):ifself.state=='OPEN':raiseRuntimeError('Already open')self.state='OPEN'defclose(self):ifself.state=='CLOSED':raiseRuntimeError('Already closed')self.state='CLOSED'This implementation presents a couple of difficulties. First, the codeis complicated by the introduction of many conditional checks for thestate. Second, the performance is degraded because common operations(e.g., read() and write()) always check the state before proceeding.
A more elegant approach is to encode each operational state as aseparate class and arrange for the Connection class to delegateto the state class. For example:
classConnection(object):def__init__(self):self.new_state(ClosedConnectionState)defnew_state(self,newstate):self._state=newstate# Delegate to the state classdefread(self):returnself._state.read(self)defwrite(self,data):returnself._state.write(self,data)defopen(self):returnself._state.open(self)defclose(self):returnself._state.close(self)# Connection state base classclassConnectionState(object):@staticmethoddefread(conn):raiseNotImplementedError()@staticmethoddefwrite(conn,data):raiseNotImplementedError()@staticmethoddefopen(conn):raiseNotImplementedError()@staticmethoddefclose(conn):raiseNotImplementedError()# Implementation of different statesclassClosedConnectionState(ConnectionState):@staticmethoddefread(conn):raiseRuntimeError('Not open')@staticmethoddefwrite(conn,data):raiseRuntimeError('Not open')@staticmethoddefopen(conn):conn.new_state(OpenConnectionState)@staticmethoddefclose(conn):raiseRuntimeError('Already closed')classOpenConnectionState(ConnectionState):@staticmethoddefread(conn):print('reading')@staticmethoddefwrite(conn,data):print('writing')@staticmethoddefopen(conn):raiseRuntimeError('Already open')@staticmethoddefclose(conn):conn.new_state(ClosedConnectionState)Here is an interactive session that illustrates the use of theseclasses:
>>>c=Connection()>>>c._state>>>c.read()Traceback (most recent call last): File "", line 1, in File "example.py", line 10, in readreturnself._state.read(self) File "example.py", line 43, in readraiseRuntimeError('Not open')RuntimeError: Not open>>>Font size:
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