SQLAlchemy mock helpers.

• Free software: MIT license
• GitHub: https://github.com/miki725/alchemy-mock

You can install alchemy-mock using pip:

$ pip install alchemy-mock

SQLAlchemy is awesome. Unittests are great. Accessing DB during tests - not so much. This library provides easy way to mock SQLAlchemy's session in unittests while preserving ability to do sane asserts. Normally SQLAlchemy's expressions cannot be easily compared as comparison on binary expression produces yet another binary expression:

>>> type((Model.foo == 5) == (Model.bar == 5))
<class 'sqlalchemy.sql.elements.BinaryExpression'>

But they can be compared with this library:

>>> ExpressionMatcher(Model.foo == 5) == (Model.bar == 5)
False

ExpressionMatcher can be directly used:

>>> from alchemy_mock.comparison import ExpressionMatcher
>>> ExpressionMatcher(Model.foo == 5) == (Model.foo == 5)
True

Alternatively AlchemyMagicMock can be used to mock out SQLAlchemy session:

>>> from alchemy_mock.mocking import AlchemyMagicMock
>>> session = AlchemyMagicMock()
>>> session.query(Model).filter(Model.foo == 5).all()

>>> session.query.return_value.filter.assert_called_once_with(Model.foo == 5)

In real world though session can be interacted with multiple times to query some data. In those cases UnifiedAlchemyMagicMock can be used which combines various calls for easier assertions:

>>> from alchemy_mock.mocking import UnifiedAlchemyMagicMock
>>> session = UnifiedAlchemyMagicMock()

>>> m = session.query(Model)
>>> q = m.filter(Model.foo == 5)
>>> if condition:
...     q = q.filter(Model.bar > 10).all()
>>> data1 = q.all()
>>> data2 = m.filter(Model.note == 'hello world').all()

>>> session.filter.assert_has_calls([
...     mock.call(Model.foo == 5, Model.bar > 10),
...     mock.call(Model.note == 'hello world'),
... ])

Also real-data can be stubbed by criteria:

>>> from alchemy_mock.mocking import UnifiedAlchemyMagicMock
>>> session = UnifiedAlchemyMagicMock(data=[
...     (
...         [mock.call.query(Model),
...          mock.call.filter(Model.foo == 5, Model.bar > 10)],
...         [Model(foo=5, bar=11)]
...     ),
...     (
...         [mock.call.query(Model),
...          mock.call.filter(Model.note == 'hello world')],
...         [Model(note='hello world')]
...     ),
...     (
...         [mock.call.query(AnotherModel),
...          mock.call.filter(Model.foo == 5, Model.bar > 10)],
...         [AnotherModel(foo=5, bar=17)]
...     ),
... ])
>>> session.query(Model).filter(Model.foo == 5).filter(Model.bar > 10).all()
[Model(foo=5, bar=11)]
>>> session.query(Model).filter(Model.note == 'hello world').all()
[Model(note='hello world')]
>>> session.query(AnotherModel).filter(Model.foo == 5).filter(Model.bar > 10).all()
[AnotherModel(foo=5, bar=17)]
>>> session.query(AnotherModel).filter(Model.note == 'hello world').all()
[]

The UnifiedAlchemyMagicMock can partially fake session mutations such as session.add(instance). For example:

>>> session = UnifiedAlchemyMagicMock()
>>> session.add(Model(pk=1, foo='bar'))
>>> session.add(Model(pk=2, foo='baz'))
>>> session.query(Model).all()
[Model(foo='bar'), Model(foo='baz')]
>>> session.query(Model).get(1)
Model(foo='bar')
>>> session.query(Model).get(2)
Model(foo='baz')

Note that its partially correct since if added models are filtered on, session is unable to actually apply any filters so it returns everything:

>>> session.query(Model).filter(Model.foo == 'bar').all()
[Model(foo='bar'), Model(foo='baz')]

Finally, UnifiedAlchemyMagicMock can partially fake deleting. Anything that can be accessed with all can also be deleted. For example:

>>> s = UnifiedAlchemyMagicMock()
>>> s.add(SomeClass(pk1=1, pk2=1))
>>> s.add_all([SomeClass(pk1=2, pk2=2)])
>>> s.query(SomeClass).all()
[1, 2]
>>> s.query(SomeClass).delete()
2
>>> s.query(SomeClass).all()
[]

Note the limitation for dynamic sessions remains the same. Additionally, the delete will not be propagated across queries (only unified in the exact same query). As in if there are multiple queries in which the 'same' object is present, this library considers them separate objects. For example:

>>> s = UnifiedAlchemyMagicMock(data=[
...     (
...         [mock.call.query('foo'),
...          mock.call.filter(c == 'one', c == 'two')],
...         [SomeClass(pk1=1, pk2=1), SomeClass(pk1=2, pk2=2)]
...     ),
...     (
...         [mock.call.query('foo'),
...          mock.call.filter(c == 'one', c == 'two'),
...          mock.call.order_by(c)],
...         [SomeClass(pk1=2, pk2=2), SomeClass(pk1=1, pk2=1)]
...     ),
...     (
...         [mock.call.filter(c == 'three')],
...         [SomeClass(pk1=3, pk2=3)]
...     ),
...     (
...         [mock.call.query('foo'),
...          mock.call.filter(c == 'one', c == 'two', c == 'three')],
...         [SomeClass(pk1=1, pk2=1), SomeClass(pk1=2, pk2=2), SomeClass(pk1=3, pk2=3)]
...     ),
... ])

>>> s.query('foo').filter(c == 'three').delete()
1
>>> s.query('foo').filter(c == 'three').all()
[]
>>> s.query('foo').filter(c == 'one').filter(c == 'two').filter(c == 'three').all()
[1, 2, 3]

The item referred to by c == 'three' is still present in the filtered query despite the individual item being deleted.