I put some repl code in my first message - in it you can see that object 
pickles\unpickles. You even can do dir on unpickled  instance and see 
attributes. The error raises somewhere in attribute descriptor.

среда, 28 января 2015 г., 20:25:33 UTC+3 пользователь Michael Bayer написал:
>
>
>
> Михаил Сахнов <[email protected] <javascript:>> wrote: 
>
> > Hi all. 
> > 
> > Environment: 
> > Ubuntu Hardy, python2.5, sqlalchemy 0.5.2 
> > 
> > I need to store serialized model in memcached. 
> > If I store model to memcached and get this model from cache in the same 
> process everything looks fine. 
> > But if I try to get model from cache in another process, I would have an 
> exception AttributeError. For example I try to unserialize model from 
> pickle string in ipython: 
> > 
> > 
> > If I merge unserialized object with new session - it would work fine, 
> but I think, that it would make some queries in database. 
> > How can I work with unserialized detached model? 
>
>
> you’d need to get your object to be picklable; using methods like 
> __reduce__ to help it along are options.  I don’t have any code here to 
> work with so I don’t know what specifically is wrong with it.   
>
> However, SQLAlchemy 0.5.2 is *six years old* and is *extremely* bad in 
> this area; at minimum, you’d want to get on 0.5.8 - if you look in 
> http://docs.sqlalchemy.org/en/latest/changelog/changelog_05.html#change-0.5.8 
> there are many issues related to pickling that were fixed since 0.5.2 up to 
> 0.5.8. 
>
> While I understand the need to keep legacy systems running, I’d recommend 
> against going much further with new development against an 0.5 codebase, 
> that’s an extremely old version overall (not to mention Python 2.5 itself). 
>  Each new major release of SQLAlchemy improves performance and stability by 
> huge leaps and bounds, so you are really missing out by continuing 
> development on such an old version.  The official “caching recipe” for 
> SQLAlchemy was only first introduced in 0.6, when I first started doing 
> extensive caching with SQLAlchemy on the job, and that took us through the 
> 0.6 series to work out the kinks. 
>
>
>

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