Token导航 LogoToken导航TokenDH.com
开发只读github未标认证来源可访问许可证需确认审计通过

py-test-qualitypy 测试质量

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

220

周安装

9

GitHub Stars

27

下载量

71
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:py-test-quality(py 测试质量)
来源仓库:https://github.com/l-mb/python-refactoring-skills
仓库路径:skills/py-test-quality
安装命令:
npx skills add https://github.com/l-mb/python-refactoring-skills --skill py-test-quality
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/l-mb/python-refactoring-skills --skill py-test-quality

简介

用于辅助测试设计、自动化测试、用例整理和回归验证。py-test-quality 属于开发类 Skill,可作为该场景下的辅助能力补充。

  • 适合编写单元测试、端到端测试或根据失败日志定位问题。
  • 使用时需确认项目测试框架、运行命令和夹具数据,避免误改逻辑。
  • 涉及浏览器或外部服务时,应区分本地模拟与生产环境。
  • 安装前建议核对来源仓库与权限范围,确保操作安全合规。

SKILL.md

Python Test Quality Analysis

Measure test coverage and verify test suite effectiveness using coverage analysis and mutation testing.

Objectives

  1. Measure code coverage comprehensively
  2. Identify untested code paths
  3. Verify test suite catches bugs (mutation testing)
  4. Enable safe refactoring through high test coverage
  5. Track coverage trends over time

Required Tools

Add to [dependency-groups] dev: "pytest", "pytest-cov", "mutmut", "coverage" Optional: "cosmic-ray" (advanced mutation testing)

  • pytest-cov: Code coverage measurement
  • mutmut: Mutation testing - verifies tests catch bugs
  • cosmic-ray: Advanced mutation testing (slower)

Permissions: Run py-quality-setup first to configure .claude/settings.local.json with all needed tool permissions.

Coverage Analysis

Measure Coverage

# Run tests with coverage
pytest --cov=. --cov-report=term-missing
pytest --cov=. --cov-report=html  # Generate HTML report
pytest --cov=. --cov-report=term --cov-report=html  # Both

# Coverage with specific targets
pytest --cov=src --cov=lib tests/
pytest --cov=mypackage --cov-branch  # Include branch coverage

# Fail if coverage below threshold
pytest --cov=. --cov-fail-under=80

# Show only uncovered lines
pytest --cov=. --cov-report=term-missing:skip-covered

Configure Coverage

Add to pyproject.toml (see py-quality-setup for base configuration):

[tool.coverage.run]
source = ["src"]  # Adjust to your source directory
omit = [
    "*/tests/*",
    "*/test_*.py",
    "*/__pycache__/*",
    "*/venv/*",
    "*/.venv/*",
]
branch = true  # Enable branch coverage

[tool.coverage.report]
precision = 2
show_missing = true
skip_covered = false
exclude_lines = [
    "pragma: no cover",
    "def __repr__",
    "raise AssertionError",
    "raise NotImplementedError",
    "if __name__ == .__main__.:",
    "if TYPE_CHECKING:",
    "@abstractmethod",
]

[tool.coverage.html]
directory = "htmlcov"

Interpret Coverage Reports

Name                 Stmts   Miss Branch BrPart  Cover   Missing
----------------------------------------------------------------
src/auth.py            45      5     12      2    87%   23-25, 67
src/database.py        89      0     18      0   100%
src/handlers.py       123     35     28     12    68%   45-78, 99-110
----------------------------------------------------------------
TOTAL                 257     40     58     14    82%

Key metrics:

  • Stmts: Total statements
  • Miss: Uncovered statements
  • Branch: Total branches (if/else, etc.)
  • BrPart: Partially covered branches (one path tested, not both)
  • Cover: Coverage percentage
  • Missing: Line numbers not covered

Coverage targets:

  • ≥80%: Minimum acceptable
  • ≥90%: Good coverage
  • 100%: Ideal (may not be practical for all code)

Mutation Testing

Mutation testing verifies your tests actually catch bugs by introducing small changes (mutations) and checking if tests fail.

Run Mutation Testing

# Using mutmut (easier, faster)
mutmut run                    # Run all mutations
mutmut run --paths-to-mutate=src/  # Specific directory
mutmut results                # Show summary
mutmut show <mutation-id>     # Show specific mutation
mutmut apply <mutation-id>    # Apply mutation to see code change

# Common workflow
mutmut run
mutmut results               # Shows: survived, killed, timeout
mutmut show 1                # Examine first surviving mutation

Configure Mutmut

Add to setup.cfg or pyproject.toml:

[tool.mutmut]
paths_to_mutate = "src/"
backup = false
runner = "pytest -x --tb=short"
tests_dir = "tests/"

Interpret Mutation Results

Legend for output:
🎉 Killed mutants: Tests caught the bug (good!)
⏰ Timeout: Mutation created infinite loop (acceptable)
🤔 Suspicious: Needs investigation
🙁 Survived: Bug not caught by tests (bad!)

Mutation score: killed / (killed + survived) * 100%

Target mutation scores:

  • ≥75%: Good test quality
  • ≥85%: Excellent test quality
  • 100%: Perfect (rarely achievable)

Address Surviving Mutations

# 1. Identify surviving mutations
mutmut results

# 2. Show specific mutation
mutmut show 5

# Example output:
# src/auth.py:23
# -    if user.age >= 18:
# +    if user.age > 18:

# 3. Write test to kill this mutation
def test_user_exactly_18_is_adult():
    user = User(age=18)
    assert is_adult(user) is True  # This would fail with > instead of >=

# 4. Re-run mutmut
mutmut run

# 5. Verify mutation now killed
mutmut results

Coverage-Guided Refactoring

Golden rule: Only refactor well-tested code. If coverage is low, write tests first.

Workflow

1. Run: pytest --cov=. --cov-report=html --cov-fail-under=80
2. If coverage < 80%:
   a. Open htmlcov/index.html
   b. Identify modules with low coverage (red/yellow)
   c. Write tests to increase coverage to ≥80%
   d. Re-run coverage to verify
3. Run: mutmut run (optional but recommended)
4. If mutation score < 75%:
   a. Review surviving mutations
   b. Write tests to kill mutations
   c. Re-run mutmut
5. NOW safe to refactor:
   a. Apply refactoring patterns
   b. Re-run: pytest --cov=. (ensure coverage maintained)
   c. Re-run: mutmut run (ensure mutation score maintained)

Integration with Refactoring

Before Refactoring Checklist

# 1. Measure baseline coverage
pytest --cov=src/module_to_refactor.py --cov-report=term-missing

# 2. If coverage < 80%, write tests first
# ... write tests ...

# 3. Verify tests are effective
mutmut run --paths-to-mutate=src/module_to_refactor.py

# 4. Now proceed with refactoring
# ... refactor ...

# 5. Verify coverage maintained
pytest --cov=src/module_to_refactor.py --cov-fail-under=80

# 6. Verify tests still effective
mutmut run --paths-to-mutate=src/module_to_refactor.py

CI/CD Integration

Add coverage enforcement to CI:

# .github/workflows/test.yml
- name: Run tests with coverage
  run: |
    pytest --cov=. --cov-report=term --cov-report=xml --cov-fail-under=80

- name: Upload coverage to Codecov
  uses: codecov/codecov-action@v3
  with:
    file: ./coverage.xml

Verification Checklist

  • pytest --cov=. --cov-fail-under=80 passes
  • Coverage report reviewed (htmlcov/index.html)
  • Critical paths have test coverage
  • Mutation testing run on critical modules (mutmut run)
  • Mutation score ≥75% for critical code
  • Coverage configuration in pyproject.toml

Examples

Example: Increase coverage before refactoring

1. Run: pytest --cov=src/handlers.py --cov-report=html
2. Coverage: 55% (too low to refactor safely)
3. Open htmlcov/handlers_py.html
4. Lines 45-78 not covered (error handling paths)
5. Write tests for error cases:
   - test_handler_invalid_input()
   - test_handler_database_error()
   - test_handler_missing_params()
6. Re-run: pytest --cov=src/handlers.py
7. Coverage now: 85% (safe to refactor)
8. Proceed with complexity reduction refactoring
9. After refactoring: pytest --cov=src/handlers.py --cov-fail-under=85
10. Verify coverage maintained at 85%

Example: Use mutation testing to improve tests

1. Run: mutmut run --paths-to-mutate=src/auth.py
2. Results: 15 killed, 3 survived (83% mutation score)
3. Run: mutmut show 5
4. Mutation: Changed >= to > in age check
5. Realize: Missing boundary test for age exactly 18
6. Write: test_user_exactly_18_is_adult()
7. Run: mutmut run --paths-to-mutate=src/auth.py
8. Results: 16 killed, 2 survived (89% mutation score)
9. Repeat for remaining survivors
10. Final: 18 killed, 0 survived (100% mutation score)

Example: Coverage-guided refactoring session

1. Target: Refactor src/payment.py (complexity D, 150 lines)
2. Check coverage: pytest --cov=src/payment.py --cov-report=term-missing
3. Coverage: 92% (good! safe to refactor)
4. Check test quality: mutmut run --paths-to-mutate=src/payment.py
5. Mutation score: 78% (acceptable)
6. Proceed with refactoring:
   - Extract 4 smaller functions
   - Reduce complexity from D to A/B
7. After refactoring:
   - pytest --cov=src/payment.py --cov-fail-under=92 ✓
   - mutmut run --paths-to-mutate=src/payment.py
   - Mutation score: 80% (improved!)
8. Commit changes with confidence

Example: Set up coverage tracking in CI

1. Add to pyproject.toml:
   [tool.coverage.run]
   source = ["src"]
   branch = true

2. Create .github/workflows/test.yml:
   - pytest --cov=. --cov-fail-under=80

3. First run fails: Coverage 67%
4. Write tests to reach 80%
5. CI now passes
6. All future PRs must maintain 80% coverage
7. Consider increasing threshold as coverage improves

Related Skills

  • Prerequisites: py-quality-setup (configure pytest-cov in pyproject.toml)
  • Enables: py-security, py-code-health, py-complexity (safe refactoring with test coverage)
  • Enforcement: py-git-hooks (add coverage checks to CI)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.54%
按下载量换算25

Claude

27.96%
按下载量换算20

Cursor

17.9%
按下载量换算13

Gemini CLI

9.1%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills