django-mock-queries
A django library for mocking queryset functions in memory for testing
Decision gist · record as of 2026-08-14
Yes. This is a mature, actively maintained testing utility with no dependencies, permissive licensing, and clear use cases for accelerating Django unit tests. Install it if you want to test query logic without database overhead; skip it only if your test suite already has fast database fixtures or you need QuerySet methods not yet supported (annotate, reverse, none, extra, raw, bulk_create, in_bulk, as_manager).AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction install with no runtime dependencies.
- Actively maintained with recent commits and stable production status since 2016.
License · maintenance · safety
MIT (permissive) — MIT license permits free use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
last release 2024-09-26 (687 days) · last repo commit 2026-04-14 · 324 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 204,780 downloads/mo, #9,601 on PyPI
Alternatives
Verify before relying
pip install django-mock-queries
from django_mock_queries.query import MockSet, MockModel
qs = MockSet(
MockModel(mock_name='john', email='john@gmail.com'),
MockModel(mock_name='bill', email='bill@gmail.com'),
)
result = [x for x in qs.all().filter(email__icontains='gmail.com')]- Whether all QuerySet methods used in production code are supported (TODO lists annotate, reverse, none, extra, raw, bulk_create, in_bulk, as_manager)
- Performance characteristics when mocking large datasets in memory
What it is and what it does
django-mock-queries lets you test Django code that queries models without setting up a database. It provides in-memory MockSet and MockModel classes that mimic Django's QuerySet API, supporting method chaining, filtering with Q objects, aggregates, field lookups, and CRUD operations. This is useful when you want fast unit tests that don't require database setup or migrations.
The library is typically used by patching Django model managers in test cases, allowing you to verify query logic in isolation. It also includes utilities for testing django-rest-framework serializers and can be configured to run an entire test suite without a database by monkey-patching the test database backend, which can significantly speed up test execution for projects with many migrations.
Use it for
- Unit test Django view logic that queries models without setting up a test database
- Mock User.objects or other model managers in test patches to verify filter and query logic
- Test django-rest-framework serializers with mocked model instances and nested serializers
- Speed up test suites by running tests without database setup when database-free testing is feasible
- Verify QuerySet method chaining and complex filter combinations with Q objects in isolation
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a mature, actively maintained testing utility with no dependencies, permissive licensing, and clear use cases for accelerating Django unit tests. Install it if you want to test query logic without database overhead; skip it only if your test suite already has fast database fixtures or you need QuerySet methods not yet supported (annotate, reverse, none, extra, raw, bulk_create, in_bulk, as_manager).
Install
django-mock-queries on PyPI
Before you install
Low friction install with no runtime dependencies. Actively maintained with recent commits and stable production status since 2016.
License in practice
MIT license permits free use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
Quickstart
pip install django-mock-queries
from django_mock_queries.query import MockSet, MockModel
qs = MockSet(
MockModel(mock_name='john', email='john@gmail.com'),
MockModel(mock_name='bill', email='bill@gmail.com'),
)
result = [x for x in qs.all().filter(email__icontains='gmail.com')]Verify before relying
- Whether all QuerySet methods used in production code are supported (TODO lists annotate, reverse, none, extra, raw, bulk_create, in_bulk, as_manager)
- Performance characteristics when mocking large datasets in memory
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 687 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 204,780 / month, #9,601 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyTopic :: Software Development :: TestingTopic :: Software Development :: Testing :: MockingTopic :: Software Development :: Testing :: Unit |
Evidence: django_mock_queries-2.3.0-py2.py3-none-any.whl
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See also mock-alchemy · djangorestframework-bulk · django-query-builder · django-cacheops · django-zen-queries · djangorestframework-filters · django-user-sessions · alchemy-mock · django-chunkator · django-sql-utils