I can see this successfully applied in the database.
__tablename__ = "mailing_list_view"
# Specify the column override from the underlying view that is the primary key
id = Column(UUID(as_uuid=True), primary_key=True)
# Expecting these columns below to be mapped in this class after
# metadata reflection. Currently have to uncomment these
# to manually synchronise with view!
#
# addressee = Column(String)
# street = Column(String)
# town = Column(String)
# county = Column(String)
# postcode = Column(String)
# cursor = Column(String)
I am reflecting the views using the following:
def use_inspector(conn):
inspector = inspect(conn)
return inspector.get_view_names()
views = await connection.run_sync(use_inspector)
# I can see the table columns in __table__.c.keys()
# after the reflection below has run
await connection.run_sync(
target_metadata.reflect,
only=views,
views=True,
extend_existing=True,
)
After performing the above reflection I can see that my mapped model has the underlyingtable columns updated with those defined in the underlying view.
obj = MailingListView()
obj.__table__.c.keys()
However, the properties of my mapped class are not updated after reflection, raising an exception:
obj = MailingListView()
obj.town = "town" # this raises an exception with unavailable property
How is it possible for a postgresql db (asyncpg) + async sqlalchemy to:
Synchronise the columns of a declarative model with its underlying table after metadata reflection. Currently, I have to manually specify the columns in the declarative model.