Token导航 LogoToken导航

Agent Skill · 研究检索

python-testing-patterns(Python 测试模式)

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

python-testing-patterns 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 60,816。

总安装 364周安装 15GitHub Stars 公开资料未说明下载 119核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:python-testing-patterns(Python 测试模式)
来源仓库:https://github.com/ravinani02/opencode-agent-skills
仓库路径:skills/python-testing-patterns
安装命令:
npx skills add ravinani02/opencode-agent-skills --skill "python-testing-patterns"
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。

AgentSkills.tonpx skills
npx skills add ravinani02/opencode-agent-skills --skill "python-testing-patterns"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助 Python 项目的测试设计与自动化验证。适合编写单元测试、端到端用例或根据日志定位问题。提供常见框架下的测试模式和夹具组织方式参考。运行测试前应确认框架类型和运行环境,避免误改生产逻辑。python-testing-patterns 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/python-testing-patterns

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add ravinani02/opencode-agent-skills --skill "python-testing-patterns…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

python-testing-patterns 怎么安装?

在终端执行 npx skills add ravinani02/opencode-agent-skills --skill "python-testing-patterns"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

python-testing-patterns 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

python-testing-patterns 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

python-testing-patterns 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

python-testing-patterns 用的人多吗?

公开数据是累计安装 364 次,近一周安装 15 次,下载 119 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

python-testing-patterns 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
python-testing-patterns

Python 测试模式 · 本页

364—需要联网MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Python Testing Patterns

Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.

When to Use This Skill

  • Writing unit tests for Python code
  • Setting up test suites and test infrastructure
  • Implementing test-driven development (TDD)
  • Creating integration tests for APIs and services
  • Mocking external dependencies and services
  • Testing async code and concurrent operations
  • Setting up continuous testing in CI/CD
  • Implementing property-based testing
  • Testing database operations
  • Debugging failing tests

Core Concepts

1. Test Types

  • Unit Tests: Test individual functions/classes in isolation
  • Integration Tests: Test interaction between components
  • Functional Tests: Test complete features end-to-end
  • Performance Tests: Measure speed and resource usage

2. Test Structure (AAA Pattern)

  • Arrange: Set up test data and preconditions
  • Act: Execute the code under test
  • Assert: Verify the results

3. Test Coverage

  • Measure what code is exercised by tests
  • Identify untested code paths
  • Aim for meaningful coverage, not just high percentages

4. Test Isolation

  • Tests should be independent
  • No shared state between tests
  • Each test should clean up after itself

Quick Start

# test_example.py
def add(a, b):
    return a + b

def test_add():
    """Basic test example."""
    result = add(2, 3)
    assert result == 5

def test_add_negative():
    """Test with negative numbers."""
    assert add(-1, 1) == 0

# Run with: pytest test_example.py

Fundamental Patterns

Pattern 1: Basic pytest Tests

# test_calculator.py
import pytest

class Calculator:
    """Simple calculator for testing."""

    def add(self, a: float, b: float) -> float:
        return a + b

    def subtract(self, a: float, b: float) -> float:
        return a - b

    def multiply(self, a: float, b: float) -> float:
        return a * b

    def divide(self, a: float, b: float) -> float:
        if b == 0:
            raise ValueError("Cannot divide by zero")
        return a / b

def test_addition():
    """Test addition."""
    calc = Calculator()
    assert calc.add(2, 3) == 5
    assert calc.add(-1, 1) == 0
    assert calc.add(0, 0) == 0

def test_subtraction():
    """Test subtraction."""
    calc = Calculator()
    assert calc.subtract(5, 3) == 2
    assert calc.subtract(0, 5) == -5

def test_multiplication():
    """Test multiplication."""
    calc = Calculator()
    assert calc.multiply(3, 4) == 12
    assert calc.multiply(0, 5) == 0

def test_division():
    """Test division."""
    calc = Calculator()
    assert calc.divide(6, 3) == 2
    assert calc.divide(5, 2) == 2.5

def test_division_by_zero():
    """Test division by zero raises error."""
    calc = Calculator()
    with pytest.raises(ValueError, match="Cannot divide by zero"):
        calc.divide(5, 0)

Pattern 2: Fixtures for Setup and Teardown

# test_database.py
import pytest
from typing import Generator

class Database:
    """Simple database class."""

    def __init__(self, connection_string: str):
        self.connection_string = connection_string
        self.connected = False

    def connect(self):
        """Connect to database."""
        self.connected = True

    def disconnect(self):
        """Disconnect from database."""
        self.connected = False

    def query(self, sql: str) -> list:
        """Execute query."""
        if not self.connected:
            raise RuntimeError("Not connected")
        return [{"id": 1, "name": "Test"}]

@pytest.fixture
def db() -> Generator[Database, None, None]:
    """Fixture that provides connected database."""
    # Setup
    database = Database("sqlite:///:memory:")
    database.connect()

    # Provide to test
    yield database

    # Teardown
    database.disconnect()

def test_database_query(db):
    """Test database query with fixture."""
    results = db.query("SELECT * FROM users")
    assert len(results) == 1
    assert results[0]["name"] == "Test"

@pytest.fixture(scope="session")
def app_config():
    """Session-scoped fixture - created once per test session."""
    return {
        "database_url": "postgresql://localhost/test",
        "api_key": "test-key",
        "debug": True
    }

@pytest.fixture(scope="module")
def api_client(app_config):
    """Module-scoped fixture - created once per test module."""
    # Setup expensive resource
    client = {"config": app_config, "session": "active"}
    yield client
    # Cleanup
    client["session"] = "closed"

def test_api_client(api_client):
    """Test using api client fixture."""
    assert api_client["session"] == "active"
    assert api_client["config"]["debug"] is True

Pattern 3: Parameterized Tests

# test_validation.py
import pytest

def is_valid_email(email: str) -> bool:
    """Check if email is valid."""
    return "@" in email and "." in email.split("@")[1]

@pytest.mark.parametrize("email,expected", [
    ("user@example.com", True),
    ("test.user@domain.co.uk", True),
    ("invalid.email", False),
    ("@example.com", False),
    ("user@domain", False),
    ("", False),
])
def test_email_validation(email, expected):
    """Test email validation with various inputs."""
    assert is_valid_email(email) == expected

@pytest.mark.parametrize("a,b,expected", [
    (2, 3, 5),
    (0, 0, 0),
    (-1, 1, 0),
    (100, 200, 300),
    (-5, -5, -10),
])
def test_addition_parameterized(a, b, expected):
    """Test addition with multiple parameter sets."""
    from test_calculator import Calculator
    calc = Calculator()
    assert calc.add(a, b) == expected

# Using pytest.param for special cases
@pytest.mark.parametrize("value,expected", [
    pytest.param(1, True, id="positive"),
    pytest.param(0, False, id="zero"),
    pytest.param(-1, False, id="negative"),
])
def test_is_positive(value, expected):
    """Test with custom test IDs."""
    assert (value > 0) == expected

Pattern 4: Mocking with unittest.mock

# test_api_client.py
import pytest
from unittest.mock import Mock, patch, MagicMock
import requests

class APIClient:
    """Simple API client."""

    def __init__(self, base_url: str):
        self.base_url = base_url

    def get_user(self, user_id: int) -> dict:
        """Fetch user from API."""
        response = requests.get(f"{self.base_url}/users/{user_id}")
        response.raise_for_status()
        return response.json()

    def create_user(self, data: dict) -> dict:
        """Create new user."""
        response = requests.post(f"{self.base_url}/users", json=data)
        response.raise_for_status()
        return response.json()

def test_get_user_success():
    """Test successful API call with mock."""
    client = APIClient("https://api.example.com")

    mock_response = Mock()
    mock_response.json.return_value = {"id": 1, "name": "John Doe"}
    mock_response.raise_for_status.return_value = None

    with patch("requests.get", return_value=mock_response) as mock_get:
        user = client.get_user(1)

        assert user["id"] == 1
        assert user["name"] == "John Doe"
        mock_get.assert_called_once_with("https://api.example.com/users/1")

def test_get_user_not_found():
    """Test API call with 404 error."""
    client = APIClient("https://api.example.com")

    mock_response = Mock()
    mock_response.raise_for_status.side_effect = requests.HTTPError("404 Not Found")

    with patch("requests.get", return_value=mock_response):
        with pytest.raises(requests.HTTPError):
            client.get_user(999)

@patch("requests.post")
def test_create_user(mock_post):
    """Test user creation with decorator syntax."""
    client = APIClient("https://api.example.com")

    mock_post.return_value.json.return_value = {"id": 2, "name": "Jane Doe"}
    mock_post.return_value.raise_for_status.return_value = None

    user_data = {"name": "Jane Doe", "email": "jane@example.com"}
    result = client.create_user(user_data)

    assert result["id"] == 2
    mock_post.assert_called_once()
    call_args = mock_post.call_args
    assert call_args.kwargs["json"] == user_data

Pattern 5: Testing Exceptions

# test_exceptions.py
import pytest

def divide(a: float, b: float) -> float:
    """Divide a by b."""
    if b == 0:
        raise ZeroDivisionError("Division by zero")
    if not isinstance(a, (int, float)) or not isinstance(b, (int, float)):
        raise TypeError("Arguments must be numbers")
    return a / b

def test_zero_division():
    """Test exception is raised for division by zero."""
    with pytest.raises(ZeroDivisionError):
        divide(10, 0)

def test_zero_division_with_message():
    """Test exception message."""
    with pytest.raises(ZeroDivisionError, match="Division by zero"):
        divide(5, 0)

def test_type_error():
    """Test type error exception."""
    with pytest.raises(TypeError, match="must be numbers"):
        divide("10", 5)

def test_exception_info():
    """Test accessing exception info."""
    with pytest.raises(ValueError) as exc_info:
        int("not a number")

    assert "invalid literal" in str(exc_info.value)

Advanced Patterns

Pattern 6: Testing Async Code

# test_async.py
import pytest
import asyncio

async def fetch_data(url: str) -> dict:
    """Fetch data asynchronously."""
    await asyncio.sleep(0.1)
    return {"url": url, "data": "result"}

@pytest.mark.asyncio
async def test_fetch_data():
    """Test async function."""
    result = await fetch_data("https://api.example.com")
    assert result["url"] == "https://api.example.com"
    assert "data" in result

@pytest.mark.asyncio
async def test_concurrent_fetches():
    """Test concurrent async operations."""
    urls = ["url1", "url2", "url3"]
    tasks = [fetch_data(url) for url in urls]
    results = await asyncio.gather(*tasks)

    assert len(results) == 3
    assert all("data" in r for r in results)

@pytest.fixture
async def async_client():
    """Async fixture."""
    client = {"connected": True}
    yield client
    client["connected"] = False

@pytest.mark.asyncio
async def test_with_async_fixture(async_client):
    """Test using async fixture."""
    assert async_client["connected"] is True

Pattern 7: Monkeypatch for Testing

# test_environment.py
import os
import pytest

def get_database_url() -> str:
    """Get database URL from environment."""
    return os.environ.get("DATABASE_URL", "sqlite:///:memory:")

def test_database_url_default():
    """Test default database URL."""
    # Will use actual environment variable if set
    url = get_database_url()
    assert url

def test_database_url_custom(monkeypatch):
    """Test custom database URL with monkeypatch."""
    monkeypatch.setenv("DATABASE_URL", "postgresql://localhost/test")
    assert get_database_url() == "postgresql://localhost/test"

def test_database_url_not_set(monkeypatch):
    """Test when env var is not set."""
    monkeypatch.delenv("DATABASE_URL", raising=False)
    assert get_database_url() == "sqlite:///:memory:"

class Config:
    """Configuration class."""

    def __init__(self):
        self.api_key = "production-key"

    def get_api_key(self):
        return self.api_key

def test_monkeypatch_attribute(monkeypatch):
    """Test monkeypatching object attributes."""
    config = Config()
    monkeypatch.setattr(config, "api_key", "test-key")
    assert config.get_api_key() == "test-key"

Pattern 8: Temporary Files and Directories

# test_file_operations.py
import pytest
from pathlib import Path

def save_data(filepath: Path, data: str):
    """Save data to file."""
    filepath.write_text(data)

def load_data(filepath: Path) -> str:
    """Load data from file."""
    return filepath.read_text()

def test_file_operations(tmp_path):
    """Test file operations with temporary directory."""
    # tmp_path is a pathlib.Path object
    test_file = tmp_path / "test_data.txt"

    # Save data
    save_data(test_file, "Hello, World!")

    # Verify file exists
    assert test_file.exists()

    # Load and verify data
    data = load_data(test_file)
    assert data == "Hello, World!"

def test_multiple_files(tmp_path):
    """Test with multiple temporary files."""
    files = {
        "file1.txt": "Content 1",
        "file2.txt": "Content 2",
        "file3.txt": "Content 3"
    }

    for filename, content in files.items():
        filepath = tmp_path / filename
        save_data(filepath, content)

    # Verify all files created
    assert len(list(tmp_path.iterdir())) == 3

    # Verify contents
    for filename, expected_content in files.items():
        filepath = tmp_path / filename
        assert load_data(filepath) == expected_content

Pattern 9: Custom Fixtures and Conftest

# conftest.py
"""Shared fixtures for all tests."""
import pytest

@pytest.fixture(scope="session")
def database_url():
    """Provide database URL for all tests."""
    return "postgresql://localhost/test_db"

@pytest.fixture(autouse=True)
def reset_database(database_url):
    """Auto-use fixture that runs before each test."""
    # Setup: Clear database
    print(f"Clearing database: {database_url}")
    yield
    # Teardown: Clean up
    print("Test completed")

@pytest.fixture
def sample_user():
    """Provide sample user data."""
    return {
        "id": 1,
        "name": "Test User",
        "email": "test@example.com"
    }

@pytest.fixture
def sample_users():
    """Provide list of sample users."""
    return [
        {"id": 1, "name": "User 1"},
        {"id": 2, "name": "User 2"},
        {"id": 3, "name": "User 3"},
    ]

# Parametrized fixture
@pytest.fixture(params=["sqlite", "postgresql", "mysql"])
def db_backend(request):
    """Fixture that runs tests with different database backends."""
    return request.param

def test_with_db_backend(db_backend):
    """This test will run 3 times with different backends."""
    print(f"Testing with {db_backend}")
    assert db_backend in ["sqlite", "postgresql", "mysql"]

Pattern 10: Property-Based Testing

# test_properties.py
from hypothesis import given, strategies as st
import pytest

def reverse_string(s: str) -> str:
    """Reverse a string."""
    return s[::-1]

@given(st.text())
def test_reverse_twice_is_original(s):
    """Property: reversing twice returns original."""
    assert reverse_string(reverse_string(s)) == s

@given(st.text())
def test_reverse_length(s):
    """Property: reversed string has same length."""
    assert len(reverse_string(s)) == len(s)

@given(st.integers(), st.integers())
def test_addition_commutative(a, b):
    """Property: addition is commutative."""
    assert a + b == b + a

@given(st.lists(st.integers()))
def test_sorted_list_properties(lst):
    """Property: sorted list is ordered."""
    sorted_lst = sorted(lst)

    # Same length
    assert len(sorted_lst) == len(lst)

    # All elements present
    assert set(sorted_lst) == set(lst)

    # Is ordered
    for i in range(len(sorted_lst) - 1):
        assert sorted_lst[i] <= sorted_lst[i + 1]

Testing Best Practices

Test Organization

# tests/
#   __init__.py
#   conftest.py           # Shared fixtures
#   test_unit/            # Unit tests
#     test_models.py
#     test_utils.py
#   test_integration/     # Integration tests
#     test_api.py
#     test_database.py
#   test_e2e/            # End-to-end tests
#     test_workflows.py

Test Naming

# Good test names
def test_user_creation_with_valid_data():
    """Clear name describes what is being tested."""
    pass

def test_login_fails_with_invalid_password():
    """Name describes expected behavior."""
    pass

def test_api_returns_404_for_missing_resource():
    """Specific about inputs and expected outcomes."""
    pass

# Bad test names
def test_1():  # Not descriptive
    pass

def test_user():  # Too vague
    pass

def test_function():  # Doesn't explain what's tested
    pass

Test Markers

# test_markers.py
import pytest

@pytest.mark.slow
def test_slow_operation():
    """Mark slow tests."""
    import time
    time.sleep(2)

@pytest.mark.integration
def test_database_integration():
    """Mark integration tests."""
    pass

@pytest.mark.skip(reason="Feature not implemented yet")
def test_future_feature():
    """Skip tests temporarily."""
    pass

@pytest.mark.skipif(os.name == "nt", reason="Unix only test")
def test_unix_specific():
    """Conditional skip."""
    pass

@pytest.mark.xfail(reason="Known bug #123")
def test_known_bug():
    """Mark expected failures."""
    assert False

# Run with:
# pytest -m slow          # Run only slow tests
# pytest -m "not slow"    # Skip slow tests
# pytest -m integration   # Run integration tests

Coverage Reporting

# Install coverage
pip install pytest-cov

# Run tests with coverage
pytest --cov=myapp tests/

# Generate HTML report
pytest --cov=myapp --cov-report=html tests/

# Fail if coverage below threshold
pytest --cov=myapp --cov-fail-under=80 tests/

# Show missing lines
pytest --cov=myapp --cov-report=term-missing tests/

Testing Database Code

# test_database_models.py
import pytest
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session

Base = declarative_base()

class User(Base):
    """User model."""
    __tablename__ = "users"

    id = Column(Integer, primary_key=True)
    name = Column(String(50))
    email = Column(String(100), unique=True)

@pytest.fixture(scope="function")
def db_session() -> Session:
    """Create in-memory database for testing."""
    engine = create_engine("sqlite:///:memory:")
    Base.metadata.create_all(engine)

    SessionLocal = sessionmaker(bind=engine)
    session = SessionLocal()

    yield session

    session.close()

def test_create_user(db_session):
    """Test creating a user."""
    user = User(name="Test User", email="test@example.com")
    db_session.add(user)
    db_session.commit()

    assert user.id is not None
    assert user.name == "Test User"

def test_query_user(db_session):
    """Test querying users."""
    user1 = User(name="User 1", email="user1@example.com")
    user2 = User(name="User 2", email="user2@example.com")

    db_session.add_all([user1, user2])
    db_session.commit()

    users = db_session.query(User).all()
    assert len(users) == 2

def test_unique_email_constraint(db_session):
    """Test unique email constraint."""
    from sqlalchemy.exc import IntegrityError

    user1 = User(name="User 1", email="same@example.com")
    user2 = User(name="User 2", email="same@example.com")

    db_session.add(user1)
    db_session.commit()

    db_session.add(user2)

    with pytest.raises(IntegrityError):
        db_session.commit()

CI/CD Integration

# .github/workflows/test.yml
name: Tests

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest

    strategy:
      matrix:
        python-version: ["3.9", "3.10", "3.11", "3.12"]

    steps:
      - uses: actions/checkout@v3

      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}

      - name: Install dependencies
        run: |
          pip install -e ".[dev]"
          pip install pytest pytest-cov

      - name: Run tests
        run: |
          pytest --cov=myapp --cov-report=xml

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

Configuration Files

# pytest.ini
[pytest]
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*
addopts =
    -v
    --strict-markers
    --tb=short
    --cov=myapp
    --cov-report=term-missing
markers =
    slow: marks tests as slow
    integration: marks integration tests
    unit: marks unit tests
    e2e: marks end-to-end tests
# pyproject.toml
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
addopts = [
    "-v",
    "--cov=myapp",
    "--cov-report=term-missing",
]

[tool.coverage.run]
source = ["myapp"]
omit = ["*/tests/*", "*/migrations/*"]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "def __repr__",
    "raise AssertionError",
    "raise NotImplementedError",
]

Resources

Best Practices Summary

  1. Write tests first (TDD) or alongside code
  2. One assertion per test when possible
  3. Use descriptive test names that explain behavior
  4. Keep tests independent and isolated
  5. Use fixtures for setup and teardown
  6. Mock external dependencies appropriately
  7. Parametrize tests to reduce duplication
  8. Test edge cases and error conditions
  9. Measure coverage but focus on quality
  10. Run tests in CI/CD on every commit

平台分布

OpenCode

28.66%
按下载量换算34

Cursor

20.41%
按下载量换算24

github-copilot

17.54%
按下载量换算21

Claude Code

12.59%
按下载量换算15

Antigravity

7.32%
按下载量换算9

Gemini CLI

3.7%
按下载量换算4

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills