0.44.0

Added the ability to prefetch related objects. Here's an example:

band = await Band.objects(Band.manager).run()
>>> band.manager
<Manager: 1>

If a table has a lot of ForeignKey columns, there's a useful shortcut, which will return all of the related rows as objects.

concert = await Concert.objects(Concert.all_related()).run()
>>> concert.band_1
<Band: 1>
>>> concert.band_2
<Band: 2>
>>> concert.venue
<Venue: 1>

Thanks to @wmshort for all the input.

0.43.0

Migrations containing Array, JSON and JSONB columns should be more reliable now. More unit tests were added to cover edge cases.

0.42.0

You can now use all_columns at the root. For example:

await Band.select(
    Band.all_columns(),
    Band.manager.all_columns()
).run()

You can also exclude certain columns if you like:

await Band.select(
    Band.all_columns(exclude=[Band.id]),
    Band.manager.all_columns(exclude=[Band.manager.id])
).run()

0.41.1

Fixes a regression where if multiple tables are created in a single migration file, it could potentially fail by applying them in the wrong order.

0.41.0

Fixed a bug where if all_columns was used two or more levels deep, it would fail. Thanks to @wmshort for reporting this issue.

Here's an example:

Concert.select(
    Concert.venue.name,
    *Concert.band_1.manager.all_columns()
).run_sync()

Also, the ColumnsDelegate has now been tweaked, so unpacking of all_columns is optional.

# This now works the same as the code above (we have omitted the *)
Concert.select(
    Concert.venue.name,
    Concert.band_1.manager.all_columns()
).run_sync()

0.40.1

Loosen the typing-extensions requirement, as it was causing issues when installing asyncpg.

0.40.0

Added nested output option, which makes the response from a select query use nested dictionaries:

>>> await Band.select(Band.name, *Band.manager.all_columns()).output(nested=True).run()
[{'name': 'Pythonistas', 'manager': {'id': 1, 'name': 'Guido'}}]

Thanks to @wmshort for the input.

0.39.0

Added to_dict method to Table.

If you just use __dict__ on a Table instance, you get some non-column values. By using to_dict it's just the column values. Here's an example:

class MyTable(Table):
    name = Varchar()

instance = MyTable.objects().first().run_sync()

>>> instance.__dict__
{'_exists_in_db': True, 'id': 1, 'name': 'foo'}

>>> instance.to_dict()
{'id': 1, 'name': 'foo'}

Thanks to @wmshort for the idea, and @aminalaee and @sinisaos for investigating edge cases.

0.38.2

Removed problematic type hint which assumed pytest was installed.

0.38.1

Minor changes to get_or_create to make sure it handles joins correctly.

instance = (
    Band.objects()
    .get_or_create(
        (Band.name == "My new band")
        & (Band.manager.name == "Excellent manager")
    )
    .run_sync()
)

In this situation, there are two columns called 'name' - we need to make sure the correct value is applied if the row doesn't exist.