A library for mocking Django queryset functions in memory for testing
- QuerySet style support for method chaining
- Filtering with Q objects
- Aggregates generation
- CRUD functions
- Field lookups
- django-rest-framework serializer asserts
from django.db.models import Avg, Q
from django_mock_queries.query import MockSet, MockModel
qs = MockSet(
MockModel(mock_name='john', email='[email protected]'),
MockModel(mock_name='jeff', email='[email protected]'),
MockModel(mock_name='bill', email='[email protected]'),
)
print([x for x in qs.all().filter(email__icontains='gmail.com').select_related('address')])
# Outputs: [john, bill]
qs = MockSet(
MockModel(mock_name='model s', msrp=70000),
MockModel(mock_name='model x', msrp=80000),
MockModel(mock_name='model 3', msrp=35000),
)
print(qs.all().aggregate(Avg('msrp')))
# Outputs: {'msrp__avg': 61666}
qs = MockSet(
MockModel(mock_name='model x', make='tesla', country='usa'),
MockModel(mock_name='s-class', make='mercedes', country='germany'),
MockModel(mock_name='s90', make='volvo', country='sweden'),
)
print([x for x in qs.all().filter(Q(make__iexact='tesla') | Q(country__iexact='germany'))])
# Outputs: [model x, s-class]
qs = MockSet(cls=MockModel)
print(qs.create(mock_name='my_object', foo='1', bar='a'))
# Outputs: my_object
print([x for x in qs])
# Outputs: [my_object]from unittest import TestCase
from unittest.mock import patch
from django_mock_queries.query import MockSet, MockModel
class TestApi(TestCase):
"""
Test function applies expected filters by patching Django's user model Manager or Queryset with a MockSet.
"""
users = MockSet()
user_objects = patch('django.contrib.auth.models.User.objects', users)
def active_users(self):
"""
Query active users.
"""
return User.objects.filter(is_active=True).all()
@user_objects
def test_api_active_users_filters_by_is_active_true(self):
self.users.add(
MockModel(mock_name='active user', is_active=True),
MockModel(mock_name='inactive user', is_active=False)
)
for user in self.active_users():
self.assertTrue(user.is_active)class CarSerializer(serializers.ModelSerializer):
"""
Car model serializer that includes a nested serializer and a method field.
"""
make = ManufacturerSerializer()
speed = serializers.SerializerMethodField()
def get_speed(self, obj):
return obj.format_speed()
class Meta:
model = Car
fields = ('id', 'make', 'model', 'speed',)
def test_car_serializer_fields(self):
"""
Test serializer returns fields with expected values and mock the result of nested serializer for field `make`.
"""
car = Car(id=1, make=Manufacturer(id=1, name='vw'), model='golf', speed=300)
values = {
'id': car.id,
'model': car.model,
'speed': car.formatted_speed(),
}
assert_serializer(CarSerializer) \
.instance(car) \
.returns('id', 'make', 'model', 'speed') \
.values(**values) \
.mocks('make') \
.run()There is a full Django application in the examples/users folder. It shows how
to configure django_mock_queries in your tests and run them with or without
setting up a Django database. Running the mock tests without a database can be
much faster when your Django application has a lot of database migrations.
To run your Django tests without a database, add a new settings file, and call
monkey_patch_test_db(). Use a wildcard import to get all the regular settings
as well.
# settings_mocked.py
from django_mock_queries.mocks import monkey_patch_test_db
from users.settings import *
monkey_patch_test_db()Then run your Django tests with the new settings file:
./manage.py test --settings=users.settings_mocked
Here's the pytest equivalent:
pytest --ds=users.settings_mocked
That will run your tests without setting up a test database. All of your tests that use Django mock queries should run fine, but what about the tests that really need a database?
ERROR: test_create (examples.users.analytics.tests.TestApi)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/.../examples/users/analytics/tests.py", line 28, in test_create
start_count = User.objects.count()
[...]
NotSupportedError: Mock database tried to execute SQL for User model.
If you want to run your tests without a database, you need to tell Django to skip the tests that need a database. You can do that by putting a skip decorator on the test classes or test methods that need a database.
@skipIfDBFeature('is_mocked')
class TestApi(TestCase):
def test_create(self):
start_count = User.objects.count()
User.objects.create(username='bob')
final_count = User.objects.count()
self.assertEqual(start_count + 1, final_count)pip install django_mock_queriesAnything missing or not functioning correctly? PRs are always welcome! Otherwise, you can create an issue so someone else does it when time allows.
You can follow these guidelines:
- Fork the repo from this page
- Clone your fork:
git clone https://github.com/{your-username}/django-mock-queries.git
cd django-mock-queries
git checkout -b feature/your_cool_feature- Implement feature/fix
- Add/modify relevant tests
- Run tox to verify all tests and flake8 quality checks pass
tox- Commit and push local branch to your origin
git commit . -m "New cool feature does this"
git push -u origin HEAD- Create pull request
- Add docs as a service like readthedocs with examples for every feature
- Add support for missing QuerySet methods/Field lookups/Aggregation functions:
- Methods that return new QuerySets:
annotate,reverse,none,extra,raw - Methods that do not return QuerySets:
bulk_create,in_bulk,as_manager - Field lookups:
search - Aggregation functions:
StdDev,Variance
- Methods that return new QuerySets:
![dependabot[bot] avatar](https://avatars.githubusercontent.com/in/29110?v=4 "dependabot[bot]")
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent