On 09/02/2012 15:47, Chris Withers wrote:
My thinking was leaning towards actually abandoning the full declarative
base and coming up with a light weight one (or maybe even class
decorator) that basically added recorded the class in a sequence (much
like the declarative reflection does) and then calls
instrument_declarative with each class at the point of relfection.
Well, it's a bit vom-tastic but I got this working. Here it is minus the
imports:
# The registries
meta = MetaData()
registry = {}
# The declarative bases
class ReflectedMeta(type):
_classes_to_process = []
def __new__(meta, classname, bases, classDict):
cls = type.__new__(meta, classname, bases, classDict)
meta._classes_to_process.append(cls)
return cls
@classmethod
def prepare(meta, engine, metadata):
for cls in meta._classes_to_process:
tablename = vars(cls).get('__tablename__')
if tablename is not None:
try:
table = Table(
tablename,
MetaData(),
autoload=True,
autoload_with=engine,
)
except NoSuchTableError:
continue
for col in table.c:
if getattr(cls, col.name, None) is None:
col = col.copy()
if col is None:
raise Exception()
setattr(cls, col.name, col)
kw = vars(cls).get('__mapper_args__')
if kw is not None:
# deal with cases where we need to specify the primary key
# structure
primary_key_names = kw.pop('primary_key_names', None)
if primary_key_names:
kw['primary_key'] = pk = []
for name in primary_key_names:
pk.append(getattr(cls, name))
# Likewise for polymorphic_on
polymorphic_on_name = kw.pop('polymorphic_on_name', None)
if polymorphic_on_name:
kw['polymorphic_on'] = getattr(cls,
polymorphic_on_name)
instrument_declarative(cls, registry, metadata)
# The this one for reflected models:
class Reflected(object):
__abstract__ = True
__metaclass__ = ReflectedMeta
# Use this one for concretely mapped models:
Base = declarative_base(metadata=meta, class_registry=registry)
Then, once I have a connection and I'm ready to reflect, I do:
ReflectedMeta.prepare(engine, meta)
Is the above sane?
Chris
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