Unit Testing Best Practices Cheat Sheet

The Arrange-Act-Assert pattern, mocking external dependencies, parametrized tests, and the FIRST principles for writing reliable unit tests.

1 PageBeginnerApr 2, 2026

Arrange-Act-Assert

Structuring a pytest test into setup, action, and verification.

python

import pytestdef divide(a, b):    if b == 0:        raise ValueError("cannot divide by zero")    return a / bdef test_divide_returns_quotient():    # Arrange    a, b = 10, 2    # Act    result = divide(a, b)    # Assert    assert result == 5def test_divide_by_zero_raises():    with pytest.raises(ValueError, match="cannot divide by zero"):        divide(10, 0)

Mocking Dependencies

Isolating the unit under test with unittest.mock.

python

from unittest.mock import Mock, patchclass EmailService:    def send(self, to, body):        ...  # calls a real SMTP serverdef notify_user(email_service, user_email):    email_service.send(user_email, "Welcome!")    return Truedef test_notify_user_calls_send():    mock_service = Mock(spec=EmailService)    notify_user(mock_service, "a@example.com")    mock_service.send.assert_called_once_with("a@example.com", "Welcome!")@patch("mymodule.requests.get")   # patch where it's used, not where it's defineddef test_fetch_uses_requests_get(mock_get):    mock_get.return_value.status_code = 200    mock_get.return_value.json.return_value = {"ok": True}

Parametrized Tests

Running the same test logic against multiple input/output pairs.

python

import pytest@pytest.mark.parametrize("a, b, expected", [    (2, 3, 5),    (-1, 1, 0),    (0, 0, 0),])def test_add(a, b, expected):    assert a + b == expected

Testing Best Practices

Habits that keep a test suite fast, trustworthy, and maintainable.

FIRST principles- Tests should be Fast, Independent, Repeatable, Self-validating, and Timely
Descriptive names- Name tests after the behavior and expectation, e.g. test_returns_404_when_user_not_found
One behavior per test- Each test should verify a single behavior so failures pinpoint the exact problem
Avoid testing internals- Assert on observable outputs/behavior, not private implementation details, so refactors don't break tests
Mock external dependencies- Isolate the unit under test from databases, network calls, and the filesystem with test doubles
Use fixtures for setup- Share reusable setup/teardown code (e.g. pytest fixtures) instead of duplicating it in every test
Cover edge cases- Test empty inputs, boundary values, nulls, and error paths, not just the happy path
Keep tests deterministic- Avoid depending on real time, random values, network access, or execution order between tests

Pro Tip

If you find yourself mocking three or four collaborators just to test one function, treat that as a signal the function is doing too much — refactor it before writing more tests around it.

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