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Found 161 Skills
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
How to test domain models effectively: value object testing (immutability, validation), entity testing (identity, business logic), domain exception testing, aggregate testing, high coverage patterns (95%+), and testing invariants and constraints. Use when: Testing domain layer code, validating value objects, testing entities with business logic, ensuring domain invariants, or achieving 95%+ coverage on domain models.
Comprehensive pytest testing guide for FastAPI backends. Covers unit testing, integration testing, async patterns, mocking, fixtures, coverage, and FastAPI-specific testing with TestClient. Use when writing or updating test code for backend services, repositories, or API routes.
Auto-activate for pytest_databases, Docker DB fixtures, PostgreSQL/pgvector/AlloyDB Omni/MySQL/Oracle/MSSQL/CockroachDB/Yugabyte/MongoDB/GizmoSQL/Redis/Spanner/BigQuery/Azurite/MinIO tests. Not for mocked DBs.
pytest-django integration testing specialist. Covers all fixtures (db, transactional_db, client, rf, settings, mailoutbox, django_user_model), @pytest.mark.django_db options, DRF APIClient, factory_boy integration, async views, signals, management commands, and multi-database testing. USE WHEN: user mentions "pytest-django", "django test", "@pytest.mark.django_db", asks about "django client fixture", "DRF APIClient", "django signals test", "management command test", "django async view test". DO NOT USE FOR: Non-Django Python tests - use `pytest` or `python-integration`; FastAPI - use `fastapi-testing`; Pure container setup - use `testcontainers-python`
Comprehensive pytest testing skill for Python projects. Write efficient, maintainable tests with fixtures, parametrization, markers, mocking, and assertions. Use when: (1) Writing new tests for Python code, (2) Setting up pytest in a project, (3) Creating fixtures for test dependencies, (4) Parametrizing tests for multiple inputs, (5) Mocking/patching with monkeypatch, (6) Debugging test failures, (7) Organizing test suites with markers, (8) Any Python testing task.
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing strategies for backend support systems
pytest-django testing patterns, Factory Boy, fixtures, and TDD workflow. Use when writing tests, creating test factories, or following TDD red-green-refactor cycle.
Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.
Pytest testing patterns for Python. Trigger: When writing Python tests - fixtures, mocking, markers.
pytest testing patterns for Python. Triggers on: pytest, fixture, mark, parametrize, mock, conftest, test coverage, unit test, integration test, pytest.raises.