a biblioteca sqlalchemy-utils agora inclui funcionalidade para criar visualizações e associa a visualização aos metadados do sqlalchemy para que seja possível criar a visualização usando
Base.metadata.create_all exemplo:
# installation: pip install sqlalchemy-utils
from sqlalchemy_utils import create_view
from sqlalchemy import select, func
# engine Base & Table declaration elided for brevity
stmt = select([
TableB.id.label('table_b_id'),
TableB.coupon_code,
TableB.number_of_rebought_items,
TableA.id.label('table_a_action_id'),
TableA.time,
TableA.parameters
]).select_from(TableB.__table__.outerjoin(TableA, TableB.generate_action == TableA.id))
# attaches the view to the metadata using the select statement
view = create_view('my_view', stmt, Base.metadata)
# provides an ORM interface to the view
class MyView(Base):
__table__ = view
# will create all tables & views defined with ``create_view``
Base.metadata.create_all()
# At this point running the following yields 0, as expected,
# indicating that the view has been constructed on the server
engine.execute(select([func.count('*')], from_obj=MyView)).scalar()
