The simplest pattern which I use most often is that you actually have separate Comment tables for each relationship. This may seem frightening at first, but it doesn't incur any additional code versus using any other approach - the tables are created automatically, and the models are referred to using the pattern Post.Comment, Project.Comment, etc. The definition of Comment is maintained in one place. This approach from a referential point of view is the most simple and efficient, as well as the most DBA friendly as different kinds of Comments are kept in their own tables which can be sized individually.
Another pattern to use is a single Comment table, but distinct association tables. This pattern offers the use case that you might want a Comment linked to more than one kind of object at a time (like a Post and a Project at the same time). This pattern is still reasonably efficient.
Thirdly, there's the polymorphic association table. This pattern uses a fixed number of tables to represent the collections and the related class without sacrificing referential integrity. This pattern tries to come the closest to the Django-style "generic foreign key" while still maintaining referential integrity, though it's not as simple as the previous two approaches.
Imitating the pattern used by ROR/Django, where there are no real foreign keys used and rows are matched using application logic, is also possible.
The first three patterns are illustrated in modern form in the SQLAlchemy distribution under examples/generic_associations/.
The ROR/Django pattern, since it gets asked about so often, I will also add to the SQLAlchemy examples, even though I don't like it much. The approach I'm using is not exactly the same as what Django does as they seem to make use of a "contenttypes" table to keep track of types, that seems kind of superfluous to me, but the general idea of an integer column that points to any number of tables based on a discriminator column is present. Here it is:
from sqlalchemy.ext.declarative import declarative_base, declared_attr
from sqlalchemy import create_engine, Integer, Column,
String, and_
from sqlalchemy.orm import Session, relationship, foreign, remote, backref
from sqlalchemy import event
class Base(object):
"""Base class which provides automated table name
and surrogate primary key column.
"""
@declared_attr
def __tablename__(cls):
return cls.__name__.lower()
id = Column(Integer, primary_key=True)
Base = declarative_base(cls=Base)
class Address(Base):
"""The Address class.
This represents all address records in a
single table.
"""
street = Column(String)
city = Column(String)
zip = Column(String)
discriminator = Column(String)
"""Refers to the type of parent."""
parent_id = Column(Integer)
"""Refers to the primary key of the parent.
This could refer to any table.
"""
@property
def parent(self):
"""Provides in-Python access to the "parent" by choosing
the appropriate relationship.
"""
return getattr(self, "parent_%s" % self.discriminator)
def __repr__(self):
return "%s(street=%r, city=%r, zip=%r)" %
(self.__class__.__name__, self.street,
self.city, self.zip)
class HasAddresses(object):
"""HasAddresses mixin, creates a relationship to
the address_association table for each parent.
"""
@event.listens_for(HasAddresses, "mapper_configured", propagate=True)
def setup_listener(mapper, class_):
name = class_.__name__
discriminator = name.lower()
class_.addresses = relationship(Address,
primaryjoin=and_(
class_.id == foreign(remote(Address.parent_id)),
Address.discriminator == discriminator
),
backref=backref(
"parent_%s" % discriminator,
primaryjoin=remote(class_.id) == foreign(Address.parent_id)
)
)
@event.listens_for(class_.addresses, "append")
def append_address(target, value, initiator):
value.discriminator = discriminator
class Customer(HasAddresses, Base):
name = Column(String)
class Supplier(HasAddresses, Base):
company_name = Column(String)
engine = create_engine('sqlite://', echo=True)
Base.metadata.create_all(engine)
session = Session(engine)
session.add_all([
Customer(
name='customer 1',
addresses=[
Address(
street='123 anywhere street',
city="New York",
zip="10110"),
Address(
street='40 main street',
city="San Francisco",
zip="95732")
]
),
Supplier(
company_name="Ace Hammers",
addresses=[
Address(
street='2569 west elm',
city="Detroit",
zip="56785")
]
),
])
session.commit()
for customer in session.query(Customer):
for address in customer.addresses:
print(address)
print(address.parent)
