Efficient pickling of django models

monkey.py

from django.db.models import Model
from itertools import izip

def attnames(cls, _cache={}):
    try:
        return _cache[cls]
    except KeyError:
        _cache[cls] = [f.attname for f in cls._meta.fields]
        return _cache[cls]

def model_unpickle(cls, data):
    obj = cls.__new__(cls)
    obj.__dict__.update(izip(attnames(cls), data))
    return obj
model_unpickle.__safe_for_unpickle__ = True

def Model__reduce__(self):
    if self._deferred:
        return original_Model__reduce__(self)
    else:
        cls = self.__class__
        data = self.__dict__.copy()

        vector = map(data.pop, attnames(cls))
        return (model_unpickle, (cls, vector), data)
original_Model__reduce__ = Model.__reduce__
Model.__reduce__ = Model__reduce__

See also django-pickling package