PicklingError: Can't pickle <class 'decimal.Decimal'>: it's not the same object as decimal.Decimal

Question

This is the error I got today at <a href"http://filmaster.com">filmaster.com:

PicklingError: Can't pickle <class
'decimal.Decimal'>: it's not the same
object as decimal.Decimal

What does that exactly mean? It does not seem to be making a lot of sense... It seems to be connected with django caching. You can see the whole traceback here:

Traceback (most recent call last):

 File
"/home/filmaster/django-trunk/django/core/handlers/base.py",
line 92, in get_response    response =
callback(request, *callback_args,
**callback_kwargs)

 File
"/home/filmaster/film20/film20/core/film_views.py",
line 193, in show_film   
workflow.set_data_for_authenticated_user()

 File
"/home/filmaster/film20/film20/core/film_views.py",
line 518, in
set_data_for_authenticated_user   
object_id = self.the_film.parent.id)

 File
"/home/filmaster/film20/film20/core/film_helper.py",
line 179, in get_others_ratings   
set_cache(CACHE_OTHERS_RATINGS,
str(object_id) + "_" + str(user_id),
userratings)

 File
"/home/filmaster/film20/film20/utils/cache_helper.py",
line 80, in set_cache    return
cache.set(CACHE_MIDDLEWARE_KEY_PREFIX
+ full_path, result, get_time(cache_string))

 File
"/home/filmaster/django-trunk/django/core/cache/backends/memcached.py",
line 37, in set   
self._cache.set(smart_str(key), value,
timeout or self.default_timeout)

 File
"/usr/lib/python2.5/site-packages/cmemcache.py",
line 128, in set    val, flags =
self._convert(val)

 File
"/usr/lib/python2.5/site-packages/cmemcache.py",
line 112, in _convert    val =
pickle.dumps(val, 2)

PicklingError: Can't pickle <class
'decimal.Decimal'>: it's not the same
object as decimal.Decimal

And the source code for Filmaster can be downloaded from here: bitbucket.org/filmaster/filmaster-test

Any help will be greatly appreciated.

Answer 1

I got this error when running in an jupyter notebook. I think the problem was that I was using %load_ext autoreload autoreload 2. Restarting my kernel and rerunning solved the problem.

Answer 2

One oddity of Pickle is that the way you import a class before you pickle one of it's instances can subtly change the pickled object. Pickle requires you to have imported the object identically both before you pickle it and before you unpickle it.

So for example:

from a.b import c
C = c()
pickler.dump(C)

will make a subtly different object (sometimes) to:

from a import b
C = b.c()
pickler.dump(C)

Try fiddling with your imports, it might correct the problem.