write-backend-unit-test

name	write-backend-unit-test
description	Write or update Baserow backend tests for core, premium, or enterprise code using pytest, Django, DRF APIClient, and the repo's shared fixture patterns.

Write Baserow Backend Tests

Use this skill when a task is to add, fix, or extend a backend test in backend/tests, premium/backend/tests, or enterprise/backend/tests.

Do not invent a generic Django testing style. This repo already has strong pytest and fixture conventions. Start by finding the closest existing test in the same backend area and copy its setup shape.

First Step

Before editing, identify the test target:

1. Handler, service, registry, or model logic
2. API view or serializer behavior
3. Signals, permissions, or settings-sensitive behavior
4. Query-count or performance-sensitive behavior
5. Premium or enterprise variant of one of the above

Then inspect the nearest existing test file in the same module area.

Useful searches:

Use rg as a faster equivalent when it is available.

• find backend/tests premium/backend/tests enterprise/backend/tests -type f | grep 'test_.*\.py$'
• grep -RInE "@pytest\\.mark\\.django_db|api_client|data_fixture|premium_data_fixture|enterprise_data_fixture" backend/tests premium/backend/tests enterprise/backend/tests
• grep -RInE "pytest\\.raises|@patch\\(|override_settings|django_assert_num_queries" backend/tests premium/backend/tests enterprise/backend/tests

Tooling Used In This Repo

Current backend tests use:

• pytest
• pytest-django
• Django reverse
• DRF APIClient from the shared api_client fixture
• Shared fixtures from backend/src/baserow/test_utils/pytest_conftest.py
• Repo fixture builders such as data_fixture, premium_data_fixture, and enterprise_data_fixture

Important local files:

• backend/src/baserow/test_utils/pytest_conftest.py
• premium/backend/tests/baserow_premium_tests/conftest.py
• enterprise/backend/tests/baserow_enterprise_tests/conftest.py

pytest_conftest.py already provides data_fixture, api_client, api_request_factory, registry reset helpers, env helpers, and automatic signal deferral. Reuse those instead of building bespoke fixtures unless the nearby test already does something more specific.

Choose The Right Pattern

Handler, service, and model tests

For core business logic, keep the test direct:

1. Mark the test with @pytest.mark.django_db when it touches the database.
2. Build state with data_fixture or the premium or enterprise equivalent.
3. Instantiate the handler or call the target function directly.
4. Assert concrete persisted state, returned values, and raised exceptions.

Good examples:

• backend/tests/baserow/core/test_core_handler.py
• backend/tests/baserow/core/service/test_service_handler.py
• enterprise/backend/tests/baserow_enterprise_tests/teams/test_team_handler.py

Use pytest.raises(...) for error paths. Prefer asserting the specific domain exception over broad response or string checks when testing non-API code.

API view tests

For API endpoints, match the common DRF style:

1. Create a user and token with data_fixture.create_user_and_token() when JWT auth is needed.
2. Build the URL with reverse(...).
3. Call api_client.get, post, patch, or delete.
4. Pass auth as HTTP_AUTHORIZATION=f"JWT {token}".
5. Assert both status code and the relevant response body fields.

Good examples:

• backend/tests/baserow/api/groups/test_workspace_views.py
• backend/tests/baserow/contrib/database/api/rows/test_row_views.py
• premium/backend/tests/baserow_premium_tests/api/license/test_premium_license_views.py

Prefer focused payload assertions. Only construct a large expected JSON object when the endpoint response shape is the behavior being tested.

Signals and side effects

When the important behavior is that a signal or side effect fires:

1. Patch the exact function or signal send call used by the code.
2. Exercise the handler or API path.
3. Assert the mock was called with the expected domain objects or IDs.

Good examples:

• backend/tests/baserow/core/test_core_handler.py
• enterprise/backend/tests/baserow_enterprise_tests/teams/test_team_receivers.py

The shared test setup already defers many heavy async tasks. Do not add extra mocking for those unless the test specifically needs to assert the call.

Settings, licenses, and query-count sensitive tests

Use the repo helpers already in use nearby:

1. Use override_settings(...) when the behavior is controlled by Django settings.
2. Use django_assert_num_queries(...) only when query count is part of the contract.
3. Use the premium or enterprise fixture helpers when the feature depends on licensing or edition-specific behavior.

Good examples:

• backend/tests/baserow/config/test_read_replica_router.py
• premium/backend/tests/baserow_premium_tests/api/license/test_premium_license_views.py
• enterprise/backend/tests/baserow_enterprise_tests/sso/test_auth_provider_handler.py

Do not turn ordinary behavior tests into performance tests.

Fixtures And Data Setup

Prefer fixture builders over hand-rolling model graphs:

1. Use data_fixture for core backend objects.
2. Use premium_data_fixture in premium tests.
3. Use enterprise_data_fixture in enterprise tests.
4. Reuse api_client instead of instantiating APIClient manually.

If you need premium or enterprise-only entities, start by checking the corresponding conftest.py and nearby test files instead of guessing the fixture name.

File Placement

Follow the existing test tree:

• Core: backend/tests/baserow/**
• Premium: premium/backend/tests/baserow_premium_tests/**
• Enterprise: enterprise/backend/tests/baserow_enterprise_tests/**

Keep the new test near the feature area rather than creating a new generic test module.

Validation

Run the narrowest relevant test command first.

Examples:

• just b test baserow/core/test_core_handler.py
• just b test baserow/api/groups/test_workspace_views.py
• just b test premium/backend/tests/baserow_premium_tests/api/license/test_premium_license_views.py
• just b test enterprise/backend/tests/baserow_enterprise_tests/teams/test_team_handler.py

If you changed settings-sensitive or query-count-sensitive tests, check the exact failure instead of weakening the assertion immediately.

Guardrails

• Do not introduce unittest.TestCase or Django TestCase patterns when the repo already uses plain pytest functions.
• Do not manually construct large object graphs if data_fixture already provides the needed factory.
• Do not over-mock core handlers, models, or registries when a focused real-object test is practical.
• Do not skip @pytest.mark.django_db on database-touching tests.
• Do not use broad API assertions when the behavior can be proved with a few targeted fields.
• Do not mix core, premium, and enterprise fixture styles in the same file unless the existing test pattern already does that.