testing-strategy

name	testing-strategy
description	This skill should be used when the user is configuring pytest, writing tests, setting up test fixtures, using parametrize, measuring code coverage, writing async tests with pytest-asyncio, using Hypothesis for property-based testing, choosing between nox and tox, building CI test matrices, setting up snapshot testing with syrupy, mocking with pytest-mock, or reviewing test organization. Covers pytest configuration, fixtures, coverage thresholds, async testing, Hypothesis profiles, CI matrices, and mocking best practices.
version	1.0.0

Configure pytest Strictly, Test Behavior Not Implementation

Every serious Python package -- attrs, httpx, Pydantic, FastAPI, Rich -- shares the same pytest configuration philosophy: strict by default, warnings as errors, no silent regressions. Without strict settings, typos in markers go unnoticed, deprecated upstream APIs break you without warning, and xfail tests silently pass for months hiding fixed bugs that never get their markers removed.

Testing strategy failures are quiet. Coverage regresses 1% at a time. A missing --strict-markers lets @pytest.mark.solw pass silently. filterwarnings without "error" lets upstream deprecation warnings accumulate until a dependency update breaks everything at once. The configuration below prevents all of this.

Pytest Configuration

These settings are non-negotiable. They appear in every major package's pyproject.toml:

[tool.pytest.ini_options]
testpaths = ["tests"]
xfail_strict = true
filterwarnings = ["error"]
addopts = ["--strict-markers", "--strict-config", "-ra"]
markers = [
    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
    "network: marks tests that require network access",
    "integration: marks integration tests requiring external services",
]

Setting	What It Prevents
testpaths = ["tests"]	Scanning src/, docs/, node_modules/ -- faster collection
xfail_strict = true	Unexpectedly passing xfail silently succeeding instead of failing
filterwarnings = ["error"]	Missing upstream DeprecationWarning until it breaks you
--strict-markers	Typos like @pytest.mark.solw passing without error
--strict-config	Typos like filterwarning (missing 's') being silently ignored
-ra	Forgetting to check which tests were skipped or xfailed

Add targeted warning ignores only for known upstream issues you cannot control:

filterwarnings = [
    "error",
    "ignore::DeprecationWarning:some_dependency.*",
]

Test Organization

Mirror the source directory -- the tests/ directory must mirror src/my_package/ exactly, with the same subdirectories and a test_-prefixed file for every source module. This makes it obvious where tests live and immediately reveals untested modules. See the project-structure skill for the full directory mapping.

Start flat within that mirror. Refactor to additional directories (e.g., tests/unit/, tests/integration/) only when test count exceeds 500 or different test layers need different infrastructure.

Structure	When	Run Subsets
Flat mirror (tests/test_*.py matching src/)	< 500 tests, same fixtures	pytest -m "not slow"
Directories (tests/unit/, tests/integration/)	> 500 tests, different infrastructure per layer	pytest tests/unit/

conftest.py rules

1. Fixtures only -- never put test functions in conftest.py
2. Fixtures flow downward to all tests in the directory and below
3. Past ~150 lines, extract into modules: pytest_plugins = ["tests.fixtures.database"]

Fixtures

Prefer factory fixtures

# DO: Factory with sensible defaults
@pytest.fixture
def make_user():
    def _make_user(name="test_user", email="[e-mail]", role="user"):
        return User(name=name, email=email, role=role)
    return _make_user

def test_admin_permissions(make_user):
    admin = make_user(role="admin")
    assert admin.can_delete(make_user())

Good	Bad
One factory fixture with parameters	Separate fixture per variant (admin_user, inactive_user)
Compose fixtures: client(app(config))	Monolithic fixture that sets up everything
Use built-ins: tmp_path, capsys, monkeypatch	Reinvent temporary directories or stdout capture
autouse=True only for leak prevention	autouse=True for convenience

Scope rules

A fixture can only depend on fixtures with equal or broader scope. Expensive resources (DB engines, HTTP servers) use scope="session", cheap per-test resources (DB transactions, test clients) use default scope with rollback in teardown.

Parametrize

Always use ids for readable test output. Include expected values in parameters -- never use conditionals inside parametrized tests.

# DO: Expected value in parameters
@pytest.mark.parametrize(("fmt", "expected"), [
    pytest.param("json", '"name"', id="json_format"),
    pytest.param("xml", "<name>", id="xml_format"),
])
def test_export(fmt, expected):
    assert expected in export(data, fmt)

# DON'T: Conditionals inside parametrized test
@pytest.mark.parametrize("fmt", ["json", "xml"])
def test_export(fmt):
    result = export(data, fmt)
    if fmt == "json": assert '"name"' in result    # Three tests pretending to be one
    elif fmt == "xml": assert "<name>" in result

Stack decorators for cartesian products:

@pytest.mark.parametrize("method", ["GET", "POST", "PUT"])
@pytest.mark.parametrize("auth", ["token", "api_key"])
def test_endpoint(method, auth):  # 3 x 2 = 6 tests
    ...

Coverage

[tool.coverage.run]
source_pkgs = ["my_library"]
branch = true
parallel = true

[tool.coverage.report]
show_missing = true
fail_under = 85
exclude_also = [
    "if TYPE_CHECKING:",
    "@overload",
    "raise NotImplementedError",
    "assert_never",
    "\\.\\.\\.",
]

Decision	Recommendation
Branch coverage	Always enable (branch = true). Line coverage misses untested else paths.
fail_under	Start at 80, raise as coverage improves. Never lower it. Prevents silent regression.
Target	80-85% for libraries, 85-90% for production APIs, never chase 100%
Exclusions	TYPE_CHECKING blocks, @overload, abstract methods, sentinel ...

Run locally: pytest --cov=my_library --cov-report=term-missing

Async Testing

Enable pytest-asyncio auto mode to avoid decorating every async test:

[tool.pytest.ini_options]
asyncio_mode = "auto"

Any async def test_* is automatically detected. For trio or anyio backends, use asyncio_mode = "auto" with the anyio pytest plugin instead.

For FastAPI, use httpx.AsyncClient with ASGITransport:

@pytest.fixture
async def client():
    transport = ASGITransport(app=app)
    async with AsyncClient(transport=transport, base_url="http://test") as ac:
        yield ac

async def test_create_item(client):
    response = await client.post("/items/", json={"name": "Foo"})
    assert response.status_code == 201

Property-Based Testing with Hypothesis

Use Hypothesis for serialization round-trips, parsers, data transformations, and mathematical properties. Used by Pydantic, attrs, CPython, NumPy. Not worth it for simple CRUD or UI tests.

Register separate profiles for CI and local development in conftest.py:

from hypothesis import settings, HealthCheck

settings.register_profile("ci", max_examples=1000, deadline=None,
                           suppress_health_check=[HealthCheck.too_slow])
settings.register_profile("dev", max_examples=50, deadline=400)
settings.load_profile(os.getenv("HYPOTHESIS_PROFILE", "default"))

Pin regression cases with @example() so they run on every invocation, not just when Hypothesis rediscovers them.

Add .hypothesis/ to .gitignore.

Mocking Best Practices

Mock	Do Not Mock
External HTTP APIs, databases in unit tests	Your own pure functions
Time/dates (time-machine), third-party services	Data structures, simple transformations
Environment variables (monkeypatch)	The thing you are testing

Patch where the name is used, not where it is defined: mocker.patch("myapp.email.SMTP") (correct) vs mocker.patch("smtplib.SMTP") (wrong). Prefer dependency injection over mocking -- pass InMemoryDatabase() instead of patching PostgresDatabase.

CI Test Matrix

Full Python version matrix on Linux. Add macOS and Windows only if your package has platform-specific behavior — when needed, test oldest + newest Python versions only. See the ci-cd skill for the full GitHub Actions workflow and reusable workflow patterns.

strategy:
  fail-fast: false
  matrix:
    python-version: ["3.10", "3.11", "3.12", "3.13"]
    os: [ubuntu-latest]
    include:
      # Add these only if your package has platform-specific behavior
      - { python-version: "3.10", os: macos-latest }
      - { python-version: "3.13", os: macos-latest }
      - { python-version: "3.10", os: windows-latest }
      - { python-version: "3.13", os: windows-latest }

Test with uv sync --resolution lowest-direct to verify minimum dependency bounds are correct.

Reference Configuration

Combine the pytest and coverage sections from above into pyproject.toml:

[tool.pytest.ini_options]
testpaths = ["tests"]
xfail_strict = true
filterwarnings = ["error"]
addopts = ["--strict-markers", "--strict-config", "-ra"]
asyncio_mode = "auto"

[tool.coverage.run]
source_pkgs = ["my_library"]
branch = true
parallel = true

[tool.coverage.report]
show_missing = true
fail_under = 85
exclude_also = ["if TYPE_CHECKING:", "@overload", "raise NotImplementedError", "assert_never", "\\.\\.\\.",]

Review Checklist

When reviewing tests and test configuration:

• xfail_strict = true is set -- unexpectedly passing xfail tests fail the build
• filterwarnings = ["error"] is set with only targeted, module-specific ignores
• --strict-markers and --strict-config are in addopts
• All custom markers are declared in the markers list
• Factory fixtures with defaults are used instead of one fixture per test variant
• pytest.raises always includes match="..." -- no bare exception catching
• Parametrized tests use ids for readable output and include expected values in parameters
• Coverage uses branch = true and fail_under is set (minimum 80)
• TYPE_CHECKING blocks and @overload are excluded from coverage
• Async tests use asyncio_mode = "auto" -- no manual decorators
• Mocks target external services only -- own code tested directly via dependency injection
• fail_under is treated as a ratchet -- raise it as coverage improves, never lower it
• Hypothesis profiles exist for CI (max_examples=1000) and dev (max_examples=50)
• Hypothesis regression cases are pinned with @example() decorators
• CI matrix tests all Python versions on Linux; oldest + newest on macOS/Windows only if platform-specific behavior exists
• Tests verify behavior and outcomes, not internal method call order