Question

Putting aside whether the use of isinstance is harmful, I have run into the following conundrum when trying to evaluate isinstance after serializing/deserializing an object via Pickle:

from __future__ import with_statement import pickle  # Simple class definition class myclass(object):     def __init__(self, data):         self.data = data  # Create an instance of the class x = myclass(100)  # Pickle the instance to a file with open('c:\\pickletest.dat', 'wb') as f:     pickle.dump(x, f)  # Replace class with exact same definition class myclass(object):     def __init__(self, data):         self.data = data  # Read an object from the pickled file with open('c:\\pickletest.dat', 'rb') as f:     x2 = pickle.load(f)  # The class names appear to match print x.__class__ print x2.__class__  # Uh oh, this fails...(why?) assert isinstance(x2, x.__class__) 

Can anyone shed some light on why isinstance would fail in this situation? In other words, why does Python think these objects are of two different classes? When I remove the second class definition, isinstance works fine.

Answer 1

This is how the unpickler works (site-packages/pickle.py):

def find_class(self, module, name):     # Subclasses may override this     __import__(module)     mod = sys.modules[module]     klass = getattr(mod, name)     return klass 

To find and instantiate a class.

So of course if you replace a class with an identically named class, the klass = getattr(mod, name) will return the new class, and the instance will be of the new class, and so isinstance will fail.