method-chainingpython
I came across something like this in an open-source project. Methods that modify instance attributes return a reference to the instance. What is the purpose of this construct?
class Foo(object):
def __init__(self):
self.myattr = 0
def bar(self):
self.myattr += 1
return self
Having written and then refactored a python "God object", I sympathize. What I did is break the original object down into sub sections based upon methods. For instance, the original looked like this pseudo code:
method A():
self.bla += 1
method B():
self.bla += 1
do stuff():
self.bla = 1
method A()
method B()
print self.bla
The stuff method is a self contained "unit" of work. I migrated it out to a new class which the original instantiates. This pulled out the necessary properties as well. Some were used only by the sub class and could move straight across. Others were shared, and got moved into a shared class.
The "God object" creates a new copy of the shared class at start up, and each of the new sub classes accepts a pointer as part of their init method. For example, here's a stripped version of the mailer:
#!/usr/bin/env python
# -*- coding: ascii -*-
'''Functions for emailing with dirMon.'''
from email.MIMEMultipart import MIMEMultipart
from email.MIMEBase import MIMEBase
from email.MIMEText import MIMEText
from email.Utils import COMMASPACE, formatdate
from email import Encoders
import os
import smtplib
import datetime
import logging
class mailer:
def __init__(self,SERVER="mail.server.com",FROM="support@server.com"):
self.server = SERVER
self.send_from = FROM
self.logger = logging.getLogger('dirMon.mailer')
def send_mail(self, send_to, subject, text, files=[]):
assert type(send_to)==list
assert type(files)==list
if self.logger.isEnabledFor(logging.DEBUG):
self.logger.debug(' '.join(("Sending email to:",' '.join(send_to))))
self.logger.debug(' '.join(("Subject:",subject)))
self.logger.debug(' '.join(("Text:",text)))
self.logger.debug(' '.join(("Files:",' '.join(files))))
msg = MIMEMultipart()
msg['From'] = self.send_from
msg['To'] = COMMASPACE.join(send_to)
msg['Date'] = formatdate(localtime=True)
msg['Subject'] = subject
msg.attach( MIMEText(text) )
for f in files:
part = MIMEBase('application', "octet-stream")
part.set_payload( open(f,"rb").read() )
Encoders.encode_base64(part)
part.add_header('Content-Disposition', 'attachment; filename="%s"' % os.path.basename(f))
msg.attach(part)
smtp = smtplib.SMTP(self.server)
mydict = smtp.sendmail(self.send_from, send_to, msg.as_string())
if self.logger.isEnabledFor(logging.DEBUG):
self.logger.debug("Email Successfully Sent!")
smtp.close()
return mydict
It is created once and shared between the different classes that need mailing capabilities.
So for you, create a class larry with the properties and methods you need. Everywhere the client says larry = blah replace it with larryObj.larry = blah. This migrates things to sub projects without breaking the current interface.
The only other thing to do is look for "units of work". If you were going to turn part of the "God Object" into it's own method, do so. But, put the method outside it. This forces you to create an interface between the components.
Laying that groundwork allows everything else to follow it. For example, a piece of the helper object demonstrating how it interfaces with the mailer:
#!/usr/bin/env python
'''This module holds a class to spawn various subprocesses'''
import logging, os, subprocess, time, dateAdditionLib, datetime, re
class spawner:
def __init__(self, mailer):
self.logger = logging.getLogger('dirMon.spawner')
self.myMailer = mailer
Concentrate on the smallest individual unit of work possible, and move it out. This is easier to do, and lets you play with the setup quickly. Don't look at properties for moving stuff, they are ancillary to the tasks being done with them in most cases. Whatever is left over after you have dealt with the methods should probably stay in the original object, since it is part of the shared state.
But, the new objects should now accept the properties they need as init variables, not touching the caller objects property. They then return any necessary values, which the caller can use to update the shared properties as necessary. This helps to decouple the objects and makes for a more robust system.
I think it is a bad idea.
Its a very odd use of meta classes which will contribute to confusion of anyone trying to follow your code. In order to make it worth using this technique, you need the advantages to outweigh that confusion.
As for your reasons:
staticmethod or classmethod. As noted, its not hard to implement a staticpropertyIn general, there is a theme in your approach of trying to prevent client code from doing the wrong thing. That's not a pythonic attitude. The pythonic approach is to trust your client code. If they want to do something crazy, let them. Don't try to prevent client from instantiating your internal object, there may well be a good reason to do that.
I'm a bit of a purist and think that you shouldn't be storing state like this. So the very fact that you are asking the question means you're already doing it wrong. If you have state, I think it should be in an object. I think storing any sort of state at the module level should be avoided. I think its only a good idea to implement something like this if you have no changing state.
To close off, I'd like to plug the Code Review Stack Exchange, where I'm a moderator. If you post your code there you can get suggestions on how to make it better. I think you may get some helpful suggestions for how to restructure your code to avoid this question from even coming up.
Best Answer
It's to allow chaining.
For example:
Now you can say: