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testing-python测试 Python

Agent Skill

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。

总安装

1,583

周安装

68

GitHub Stars

24,921

下载量

555
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

3

许可证

MIT

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:testing-python(测试 Python)
来源仓库:https://github.com/jlowin/fastmcp
仓库路径:skills/testing-python
安装命令:
npx skills add https://github.com/jlowin/fastmcp --skill testing-python
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jlowin/fastmcp --skill testing-python

简介

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。

  • 适合阅读 Python 代码、定位测试问题、整理运行命令或分析数据处理逻辑。
  • 使用时需确认项目虚拟环境、依赖版本和测试入口。
  • 涉及执行脚本、读写文件或调用外部 API 时,应先明确运行目录和输入输出范围。
  • 安装方式:github,支持 Codex、Claude、Cursor、Gemini CLI。

SKILL.md

Writing Effective Python Tests

Core Principles

Every test should be atomic, self-contained, and test single functionality. A test that tests multiple things is harder to debug and maintain.

Test Structure

Atomic unit tests

Each test should verify a single behavior. The test name should tell you what's broken when it fails. Multiple assertions are fine when they all verify the same behavior.

# Good: Name tells you what's broken
def test_user_creation_sets_defaults():
    user = User(name="Alice")
    assert user.role == "member"
    assert user.id is not None
    assert user.created_at is not None

# Bad: If this fails, what behavior is broken?
def test_user():
    user = User(name="Alice")
    assert user.role == "member"
    user.promote()
    assert user.role == "admin"
    assert user.can_delete_others()

Use parameterization for variations of the same concept

import pytest

@pytest.mark.parametrize("input,expected", [
    ("hello", "HELLO"),
    ("World", "WORLD"),
    ("", ""),
    ("123", "123"),
])
def test_uppercase_conversion(input, expected):
    assert input.upper() == expected

Use separate tests for different functionality

Don't parameterize unrelated behaviors. If the test logic differs, write separate tests.

Project-Specific Rules

No async markers needed

This project uses asyncio_mode = "auto" globally. Write async tests without decorators:

# Correct
async def test_async_operation():
    result = await some_async_function()
    assert result == expected

# Wrong - don't add this
@pytest.mark.asyncio
async def test_async_operation():
    ...

Imports at module level

Put ALL imports at the top of the file:

# Correct
import pytest
from fastmcp import FastMCP
from fastmcp.client import Client

async def test_something():
    mcp = FastMCP("test")
    ...

# Wrong - no local imports
async def test_something():
    from fastmcp import FastMCP  # Don't do this
    ...

Use in-memory transport for testing

Pass FastMCP servers directly to clients:

from fastmcp import FastMCP
from fastmcp.client import Client

mcp = FastMCP("TestServer")

@mcp.tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

async def test_greet_tool():
    async with Client(mcp) as client:
        result = await client.call_tool("greet", {"name": "World"})
        assert result[0].text == "Hello, World!"

Only use HTTP transport when explicitly testing network features.

Inline snapshots for complex data

Use inline-snapshot for testing JSON schemas and complex structures:

from inline_snapshot import snapshot

def test_schema_generation():
    schema = generate_schema(MyModel)
    assert schema == snapshot()  # Will auto-populate on first run

Commands:

  • pytest --inline-snapshot=create - populate empty snapshots
  • pytest --inline-snapshot=fix - update after intentional changes

Fixtures

Prefer function-scoped fixtures

@pytest.fixture
def client():
    return Client()

async def test_with_client(client):
    result = await client.ping()
    assert result is not None

Use tmp_path for file operations

def test_file_writing(tmp_path):
    file = tmp_path / "test.txt"
    file.write_text("content")
    assert file.read_text() == "content"

Mocking

Mock at the boundary

from unittest.mock import patch, AsyncMock

async def test_external_api_call():
    with patch("mymodule.external_client.fetch", new_callable=AsyncMock) as mock:
        mock.return_value = {"data": "test"}
        result = await my_function()
        assert result == {"data": "test"}

Don't mock what you own

Test your code with real implementations when possible. Mock external services, not internal classes.

Test Naming

Use descriptive names that explain the scenario:

# Good
def test_login_fails_with_invalid_password():
def test_user_can_update_own_profile():
def test_admin_can_delete_any_user():

# Bad
def test_login():
def test_update():
def test_delete():

Error Testing

import pytest

def test_raises_on_invalid_input():
    with pytest.raises(ValueError, match="must be positive"):
        calculate(-1)

async def test_async_raises():
    with pytest.raises(ConnectionError):
        await connect_to_invalid_host()

Running Tests

uv run pytest -n auto              # Run all tests in parallel
uv run pytest -n auto -x           # Stop on first failure
uv run pytest path/to/test.py      # Run specific file
uv run pytest -k "test_name"       # Run tests matching pattern
uv run pytest -m "not integration" # Exclude integration tests

Checklist

Before submitting tests:

  • Each test tests one thing
  • No @pytest.mark.asyncio decorators
  • Imports at module level
  • Descriptive test names
  • Using in-memory transport (not HTTP) unless testing networking
  • Parameterization for variations of same behavior
  • Separate tests for different behaviors

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

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能力 5

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

Claude Code

25.02%
按下载量换算139

OpenCode

24.11%
按下载量换算134

Codex

17.97%
按下载量换算100

Antigravity

12.96%
按下载量换算72

windsurf

7%
按下载量换算39

trae

3.68%
按下载量换算20

安全审计

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通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

来源信息

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