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Use pytest fixtures effectively

Tests should use pytest fixtures to improve organization, promote test isolation, and avoid code duplication. Fixtures provide a clean way to set up test dependencies, manage test state, and create reusable test components.

raw .md Testing Python

Key principles:

Use fixtures for test setup instead of global variables to prevent test pollution
Monkeypatch environment variables and dependencies within fixtures
Extract repetitive test code into parameterized fixtures
Use session or module-level fixtures for expensive setup operations
Store test constants in fixtures or dedicated constant files

Example:

# Before: Using global variables and repetitive code
counter_holder = {"counter": 0, "parsing_counter": 0}  # Risky global state

def get_client_with_custom_config(config_value):
    app = FastAPI(config=config_value)
    return TestClient(app)

def test_feature_a():
    client = get_client_with_custom_config("value1")
    # Test implementation...

def test_feature_b():
    client = get_client_with_custom_config("value2")
    # Test implementation...

# After: Using pytest fixtures
@pytest.fixture
def counter():
    return {"counter": 0, "parsing_counter": 0}  # Isolated for each test

@pytest.fixture
def client(request):
    config_value = request.param
    app = FastAPI(config=config_value)
    return TestClient(app)

@pytest.mark.parametrize("client", ["value1", "value2"], indirect=True)
def test_features(client, counter):
    # Test implementation using client and counter...

Using fixtures properly improves test isolation, prevents unexpected side effects between tests, and makes test maintenance easier by centralizing common setup logic.