Overcoming Python's limitations regarding inst

问题:

It seems that Python has some limitations regarding instance methods.

1. Instance methods can't be copied.
2. Instance methods can't be pickled.

This is problematic for me, because I work on a very object-oriented project in which I reference instance methods, and there's use of both deepcopying and pickling. The pickling thing is done mostly by the multiprocessing mechanism.

What would be a good way to solve this? I did some ugly workaround to the copying issue, but I'm looking for a nicer solution to both problems.

Does anyone have any suggestions?

Update:

My use case: I have a tiny event system. Each event has an .action attribute that points to a function it's supposed to trigger, and sometimes that function is an instance method of some object.

回答1:

You might be able to do this using copy_reg.pickle. In Python 2.6:

import copy_reg
import types

def reduce_method(m):
    return (getattr, (m.__self__, m.__func__.__name__))

copy_reg.pickle(types.MethodType, reduce_method)

This does not store the code of the method, just its name; but that will work correctly in the common case.

This makes both pickling and copying work!

回答2:

REST - Representation State Transfer. Just send state, not methods.

To transfer an object X from A to B, we do this.

1. A encode the state of X in some handy, easy-to-parse notation. JSON is popular.

2. A sends the JSON text to B.

3. B decodes the state of X form JSON notation, reconstructing X.

B must have the class definitions for X's class for this to work. B must have all functions and other class definitions on which X's class depends. In short, both A and B have all the definitions. Only a representation of the object's state gets moved around.

See any article on REST.

http://en.wikipedia.org/wiki/Representational_State_Transfer

http://www.ics.uci.edu/~fielding/pubs/dissertation/top.htm

回答3:

pickle the instance and then access the method after unpickling it. Pickling a method of an instance doesn't make sense because it relies on the instance. If it doesn't, then write it as an independent function.

import pickle

class A:
     def f(self):
         print 'hi'

x = A()
f = open('tmp', 'w')
r = pickle.dump(x, f)
f.close()
f = open('tmp', 'r')
pickled_x = pickle.load(f)
pickled_x.f()