AgentSkillsCN

python-testing

采用pytest优先的Python测试方法，注重使用假数据而非模拟对象。涵盖单元测试、集成测试与异步测试；fixture设计、覆盖率设置，以及测试失败的调试。当你需要编写测试、审查测试质量、设计fixture、配置pytest，或调试测试失败时——例如，“为新功能编写单元测试”、“fixture设计模式”、“假数据与模拟对象的对比”、“修复测试失败”——均可使用此技能。

SKILL.md
--- frontmatter
name: python-testing
description: Pytest-first Python testing with emphasis on fakes over mocks. Covers unit, integration, and async tests; fixture design; coverage setup; and debugging test failures. Use when writing tests, reviewing test quality, designing fixtures, setting up pytest, or debugging failures—e.g., "write unit tests for new feature", "fixture design patterns", "fakes vs mocks comparison", "fix failing tests".

Python Testing Skill

Purpose

Pytest-first testing emphasizing fakes over mocks and behavior-driven assertions. This skill applies to all Python testing work—always follow its guidance.

Core Philosophy

Bias toward business logic tests over fakes (Layer 4). Fakes track mutations without coupling to implementation. See references/test-doubles.md for details.

Required Tools

pytest, pytest-cov, pytest-asyncio, pytest-mock, hypothesis

Directory Structure

code
project/
├── src/mypackage/
└── tests/
    ├── conftest.py
    ├── unit/
    │   ├── fakes/          # Layer 1: Fake tests
    │   └── services/       # Layer 4: Business logic
    ├── integration/        # Layer 2: Sanity tests
    └── e2e/                # Layer 5: Real systems

See references/test-layers.md for layer distribution and decision tree.

Quick Patterns

Prefer Fakes Over Mocks

YOU MUST use fakes for business logic tests. Never use mocks when testing behavior—mocks couple tests to implementation and break on every refactor.

python
# CORRECT: Fake tests behavior (use this approach)
def test_user_creation():
    fake_db = FakeDatabaseAdapter()
    service = UserService(database=fake_db)
    user = service.create_user("alice@example.com")
    assert user.id == 1
    assert "INSERT" in fake_db.executed_queries[0]

# WRONG: Mock couples to implementation—this pattern causes test breakage every time you refactor
def test_user_creation(mocker):
    mock_db = mocker.patch("myapp.service.database")
    # Breaks on refactor

Factory Fixtures

python
@pytest.fixture
def make_user():
    def _make(name="test", **kwargs):
        return User(name=name, email=f"{name}@example.com", **kwargs)
    return _make

Capture Side Effects

python
@pytest.fixture
def capture_emails(monkeypatch):
    sent = []
    monkeypatch.setattr("myapp.email.send", lambda **kw: sent.append(kw))
    return sent

YOU MUST

  • •Test behavior, not implementation—tests that verify implementation details are technical debt
  • •Use fakes for business logic (mocks without fakes = brittle tests that fail on refactoring)
  • •Name tests descriptively: test_<what>_<condition>_<expected>
  • •Use tmp_path for all file operations in tests—never hardcode paths

NEVER

  • •Use subprocess in unit tests—always use CliRunner from click.testing
  • •Hardcode paths in tests
  • •Test private methods directly (test public API behavior instead)
  • •Use time.sleep() in unit tests (use monkeypatch or freezegun)

References (Load on Demand)