Thank you for the response! However, I think I may have caused some confusion. Let me try to clarify...
> > I'm a long-time Django user who has become accustomed to Django's easy > > generation and loading of test fixtures (i.e., a known database state > > for testing) and I'm looking for something similar for SQLAlchemy. > > > I've seen and been working with Kumar's fixture project (http:// > > pypi.python.org/pypi/fixture) but it seems largely intended to allow > > loading of simpler, hand-created fixtures; support for creating > > fixtures from an existing database is pretty limited and seems to > > require additional coding instead of just using your existing ORM > > models. It also looks like the export functionality runs a single > > query at a time; not that big a limitation but not as nice as the > > Django fixture generator. > > > I've also seen BootAlchemy, but it doesn't seem to provide for > > generating fixtures. > > not knowing what a "fixture generator" means, I googled and found this: > > https://github.com/alex/django-fixture-generator The confusion is more likely to be my chosen terminology. What I mean is I want an automated way to create fixture files from an existing database rather than writing them by hand (especially where I have a lot of time series data that I want to use as test samples). What I don't want is to just use a database dump, which will be brittle vis a vis schema changes and which won't work with different DB backends. In Django I'd just use 'manage.py dumpdata' to create my fixtures and 'manage.py loaddata' to load them ... or annotate my Django models and tests with appropriate initial_data, but I don't need _that_ much convenience, I'm happy to roll my own. The django-fixture-generator code seems like way to manage fixture creation, but I'm working at a level lower than that, still trying to generate the data files themselves. I initially expected that I might find the equivalent of mysqldump but written in SQLAlchemy but haven't had much luck there... > As to how I approach that kind of thing, building off the transactional > example at > http://www.sqlalchemy.org/docs/orm/session.html#joining-a-session-int..., > these days I tend to organize fixtures, common assertion methods, into > a structure like that below. Mixins define things like transactional > behavior and common fixture/assertion methods: > > class TransactionalTest(object): > """Mixin which sets up/tears down a transaction""" > > def setUp(self): > # connect to the database > self.connection = engine.connect() > > # begin a non-ORM transaction > self.trans = connection.begin() > > # bind an individual Session to the connection > self.session = Session(bind=self.connection) > > def tearDown(self): > # rolls everything back. > self.session.close() > self.trans.rollback() > self.connection.close() > > class UserTest(object): > """A test that deals with User objects.""" > > def _user_fixture(self): > """Example fixture method.""" > self.session.add_all([User(name='ed'),User(name='wendy')]) > > def _assert_ed(self, user): > """Example assertion method.""" > assert user.name == 'ed', "Username is not 'ed'" > > class MyTest(UserTest, TransactionalTest, TestCase): > > def test_ed(self): > self._user_fixture() > > ed = self.session.query(User).filter_by(name='ed').one() > self._assert_ed(ed) This test setup looks pretty familiar, except for creating the test data via Python code in the test itself. I have no problem with that and do it on occasion, but for this application I have a lot of time series data and want to just get it from an existing DB. I'm totally open to the idea that I'm just not doing things the SQLAlchemy way, or that I'm utterly spoiled by what I'm used to getting from Django. ;-) Thanks for the comments! -- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To post to this group, send email to sqlalchemy@googlegroups.com. To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en.
