On 06/22/2016 04:53 PM, Angie Ellis wrote:
Mike,
Thank you for the response! I do have control over the external library.
I like your idea having both the abstract classes and concrete classes
available in the library because I have use cases for both in my
applications. However, I'm not quite sure how to configure the
inheritance and declarative base. What am I doing wrong here?
class AbstractFoo(object):
__abstract__ = True
__tablename__ = "foo"
id = Column(Integer, primary_key=True)
type = Column(String)
foo_bar_id = Column(Integer, ForeignKey("foo_bar.id
<http://foo_bar.id>"))
foo_bar = relationship("FooBar", backref=backref("foo"))
__mapper_args__ = {"polymorphic_on": type}
class AbstractBar(object):
__abstract__ = True
__mapper_args__ = {"polymorphic_identity": "bar"}
class AbstractFooBar(object):
__abstract__ = True
__tablename__ = "foo_bar"
id = Column(Integer, primary_key=True)
Base = declarative_base()
class Foo(AbstractFoo, Base):
pass
class Bar(AbstractBar, Foo):
pass
class FooBar(AbstractFooBar, Base):
pass
Does AbstractBar need to inherit from AbstractFoo? Do the abstract
classes need to inherit their own declarative base? Do I need to change
the inheritance order? The classes Foo, Bar, and FooBar are not getting
mapped.
So the way you have it is that those are mixins, which is fine, and I
guess that's how we need it because you want to keep multiple Base's in
play at the same time. You don't need the __abstract__ keyword in that
case. So to map that looks like the following POC:
from sqlalchemy import *
from sqlalchemy.orm import *
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.declarative import declared_attr
class AbstractFoo(object):
__tablename__ = "foo"
id = Column(Integer, primary_key=True)
type = Column(String)
@declared_attr
def foo_bar_id(cls):
return Column(Integer, ForeignKey("foo_bar.id"))
@declared_attr
def foo_bar(cls):
return relationship("FooBar", backref=backref("foo"))
__mapper_args__ = {"polymorphic_on": type}
class AbstractBar(AbstractFoo):
__mapper_args__ = {"polymorphic_identity": "bar"}
class AbstractFooBar(object):
__tablename__ = "foo_bar"
id = Column(Integer, primary_key=True)
Base = declarative_base()
class Foo(AbstractFoo, Base):
pass
class Bar(AbstractBar, Foo):
pass
class FooBar(AbstractFooBar, Base):
pass
e = create_engine("sqlite://", echo=True)
Base.metadata.create_all(e)
s = Session(e)
s.add(Bar(foo_bar=FooBar()))
s.commit()
s.close()
b1 = s.query(Foo).first()
print b1
print b1.foo_bar
Thanks,
Angie
On Fri, Jun 3, 2016 at 12:38 PM, Mike Bayer <[email protected]
<mailto:[email protected]>> wrote:
On 06/03/2016 02:44 PM, Angie E wrote:
Rather than creating mixin classes that models inherit from, I
have a
use case that requires me to configure classes the other way
around. The
classes that would normally be mixin classes need to be the
classes that
inherit from the models as well as the class that model objects are
created from. This is because the models and the mapper
configurations
are in an external library from the main repository. I need to
pass in
the host for the engine from the main repository to the models
library
before any of the models are loaded so they can load with the
declarative base already configured.
I hope you are using reflection for these models, otherwise there's
no reason to have a depedency on the Engine for the model declaration.
After the engine information is
passed in, the session, Base class, and everything is created
within a
sort of base class that the models inherit from. Here is a
simplified
example:
class SQLAlchemyBase(object):
metadata = None
Session = None
Base = object
sessionfactory = sessionmaker()
def initialize(self, host):
engine = create_engine(host)
self.metadata = MetaData(bind=engine)
self.Session = scoped_session(self.sessionfactory)
self.Base = declarative_base(metadata=self.metadata)
models = SQLAlchemyBase()
(The models inherit from models.Base)
So the SQLAlchemyBase will be imported into the main repository, the
initialize method will be called, passing in the host for the
engine,
and the models can then be imported.
Looks like no reflection taking place. I'd do away with the
MetaData(bind=engine), and just have the engine as part of the
sessionmaker(), and the sessionmaker() here also doesn't need to
have anything to do with the "library", if the "library" is just
defining model classes.
The "bound metadata" pattern is highly discouraged in modern
SQLAlchemy because it leads to this kind of confusion, e.g. that one
needs an Engine in order to declare models. You don't.
The main repository has its own
classes with the same names as the models and have additional
methods
that a normal mixin class would have to extend functionality.
However, I
am unable to create model objects using the classes in the main
repository because I can't get the mappers to play nice with this
unusual inheritance that extends from the external models library.
Additionally, in the models library, there are models that have
multiple
levels of inherited polymorphic relationships. Here is an
example that
is similar one of the more basic inherited polymorphic
relationships:
**Models Library**
class Foo(models.Base):
__tablename__ = "foo"
id = Column(Integer, primary_key=True)
type = Column(String)
foo_bar_id = Column(Integer, ForeignKey("foo_bar.id
<http://foo_bar.id>"))
foo_bar = relationship(Foo, backref=backref("foos"))
__mapper_args__ = {"polymorphic_on": type}
class Bar(Foo):
__mapper_args__ = {"polymorphic_identity": "bar"}
class FooBar(models.Base):
__tablename__ = "foo_bar"
id = Column(Integer, primary_key=True)
**Main Repository**
from separate_library.models import models, Foo as BaseFoo, Bar as
BaseBar, FooBar as BaseFooBar
class Foo(BaseFoo):
@classmethod
def custom_create_method(cls, **kw):
foo_obj = cls(**kw)
models.session.add(foo_obj)
models.session.flush()
class Bar(BaseBar):
pass
class FooBar(BaseFooBar):
pass
The original error I was getting was something like this:
"InvalidRequestError: One or more mappers failed to initialize -
can't
proceed with initialization of other mappers. Original
exception was:
Multiple classes found for path "Foo" in the registry of this
declarative base. Please use a fully module-qualified path."
that only happens if someone is using a string name inside of
relationship(), like this:
foobars = relationship("Foo")
If the "library" is doing that, and you can't change it, easy
solution, use a different name for your "Foo" that's also in the 3rd
party library. Or declare your classes against a different base:
Base = declarative_base()
class Foo(other_package.Foo, Base):
# ...
class Bar(other_package.Bar, Base):
# ...
I'm not 100% sure that will work but there's probably a way to make
that work.
So I tried putting the full path in the relationships. Then it
started
giving me an error like this:
oh, OK, then you're fine there.
"FlushError: Attempting to flush an item of type <class
'main_module.models.Foo'> as a member of collection "FooBar.foos".
Expected an object of type <class 'separate_library.models.Foo'>
or a
polymorphic subclass of this type. If <class
'main_module.models.Foo'>
is a subclass of <class 'separate_library.models.Foo'>,
configure mapper
"Mapper|Foo|foos" to load this subtype polymorphically, or set
enable_typechecks=False to allow any subtype to be accepted for
flush.
Well, when this relationship loads, you'd like it to return a list
of main_module.models.Foo objects and not
separate_library.models.Foo. Your model here needs to have a
polymorphic identity assigned so that it can do this. I don't see
those set up in your mappings, you need to put those in explcitly.
If you're trying to re-use the same names that the superclass has,
you might need to manipulate Foo.__mapper__.polymorphic_map
directly, not sure.
Essentially, the main problem is getting the classes in the main
module
to point to and act like the model classes. For example, when I
try to
create relationships, it says it expected an object of type
'separate_library.models.Foo' instead of 'main_module.models.Foo'.
other than using a different name, there are ways to manipulate the
registry that is doing this but they aren't publicly supported
patterns, unless the easy "use a different Base" trick works out here.
Additionally, in the polymorphic relationships, I can't get the
polymorphic_identity to populate for the polymorphic_on column. For
example, Bar in the main repository will have the 'type' column
empty
when the object is initially created.
when you make a subclass like you are doing, you need to give it its
own identity, so it at least needs to have "polymorphic_identity"
set up locally.
Overall there would be a question here, which is: do you have
control over this external library? If so, I would design it to be
used for subclassing by another declarative system. Assign names
like "AbstractFoo" to the classes and additionally use the
__abstract__ = True declarative flag to mark them as such, then use
@declared_attr around __mapper_args__ to assign mapper arguments
like polymorphic identity to subclasses properly.
If you do *not* have control over this external library, then it is
not intended to be used in this way; the most preferable way to go
about this would be to get the maintainers of it to change it in
order to allow it to be used in this way. An easy way for the
external library to work like this would be that it supplies both
the __abstract__ classes with nice names like AbstractFoo, then for
its own purposes it supplies its own Foo / Bar concrete classes on
top of a separate declarative Base, and you'd skip using that part.
One idea I tried was to add a metaclass to the declarative base
in the
models library and modify the mappers in the __init__ method during
their initialization. I made progress this way, but haven't
gotten it to
work completely.
There's proabably ways to make this work with more tricks and
metaclasses but they aren't supported on the SQLAlchemy end and they
will be brittle, they will break when declarative changes how it
does things internally.
Sorry for the complex explanation, but this is a complex
problem. I am
not able to change anything about the models or the use case,
unfortunately. I have to work within these constraints.
If these are two different systems within your company, it would be
a better investment to get the upstream system to work more
flexibly, rather than invest efforts working around the system's
limitations downstream. But, if the overlapping names and the
polymorphic identities are the only problem you should be able to
work around those.
If anyone can
offer ideas on how to configure the mappers for the classes in
the main
repository to act like the models in the model library, I would
be very
grateful.
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