> On Oct 23, 2014, at 7:42 AM, Peter Waller <pe...@scraperwiki.com> wrote:
>
> We would like to freeze the results of a query to my database in a yaml file,
> so that we can use the results in an app which isn't connected to the
> database.
>
> It makes sense here to reuse the model classes. Here's an example:
>
> class Foo(declarative_base()):
> __tablename__ = "foo"
> id = S.Column(S.Integer, primary_key=True)
>
> Unfortunately, `yaml.dump(Foo())` gives a surprising result:
>
> /usr/lib/python3/dist-packages/yaml/representer.py in represent_object(self,
> data)
> 311 reduce = copyreg.dispatch_table[cls](data)
> 312 elif hasattr(data, '__reduce_ex__'):
> --> 313 reduce = data.__reduce_ex__(2)
> 314 elif hasattr(data, '__reduce__'):
> 315 reduce = data.__reduce__()
>
> /usr/lib/python3.4/copyreg.py in _reduce_ex(self, proto)
> 63 else:
> 64 if base is self.__class__:
> ---> 65 raise TypeError("can't pickle %s objects" % base.__name__)
> 66 state = base(self)
> 67 args = (self.__class__, base, state)
>
> TypeError: can't pickle int objects
>
> It seems that what is happening is that `data` is equal to `Foo`, and
> `Foo.__reduce_ex__(2)` gives `TypeError: can't pickle int objects`. As does
> `declarative_base().__reduce_ex__(2)`.
>
> I note that `pickle.dumps` works. But we'd rather use YAML.
>
> Where is the bug? Is it in sqlalchemy, yaml, or python?
no clue. ints shouldn’t have an issue with pickle, obviously! for Yaml it
would be much more appropriate to build custom per-class serialization in any
case since you don’t want all the persistence junk like _sa_instance_state()
carried along.
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