python接口自动化测试攻略

以下是Python接口自动化测试的完整攻略，涵盖工具选择、框架设计、最佳实践和代码示例，帮助你快速上手接口自动化测试。

一、核心工具与库

1. HTTP请求库

   • Requests：简洁易用的HTTP库，处理接口请求

   import requests
   response = requests.get("https://api.example.com/data")

2. 测试框架

   • unittest：Python内置单元测试框架
   • pytest：更灵活的测试框架，支持参数化和插件

   # pytest示例
   def test_api_status_code():
      response = requests.get("https://api.example.com/health")
      assert response.status_code == 200

3. 数据驱动测试

   • ddt (Data-Driven Tests) 或 pytest参数化

   # pytest参数化
   import pytest
   @pytest.mark.parametrize("user_id, expected_code", [(1, 200), (999, 404)])
   def test_get_user(user_id, expected_code):
      response = requests.get(f"https://api.example.com/users/{user_id}")
      assert response.status_code == expected_code

4. 测试报告

   • Allure：生成美观的HTML报告
   • HTMLTestRunner：传统HTML报告生成器

二、接口自动化测试框架设计

1. 目录结构

project/
├── config/           # 配置文件
│   └── settings.py
├── testcases/        # 测试用例
│   └── test_api.py
├── utils/            # 工具类
│   ├── logger.py     # 日志管理
│   └── request_util.py  # 封装Requests
├── data/             # 测试数据（JSON/YAML）
├── reports/          # 测试报告
└── conftest.py       # pytest全局配置

2. 封装请求工具

# utils/request_util.py
import requests

class RequestUtil:
    def __init__(self, base_url="https://api.example.com"):
        self.base_url = base_url
        self.session = requests.Session()

    def send_request(self, method, endpoint, params=None, data=None, headers=None):
        url = f"{self.base_url}/{endpoint}"
        response = self.session.request(method, url, params=params, json=data, headers=headers)
        response.raise_for_status()  # 自动抛出HTTP错误
        return response.json()

三、实战案例：用户登录与数据查询

1. 编写测试用例

# testcases/test_user_api.py
import pytest
from utils.request_util import RequestUtil

@pytest.fixture(scope="module")
def api_client():
    return RequestUtil(base_url="https://api.example.com")

def test_login(api_client):
    """测试登录获取Token"""
    payload = {"username": "testuser", "password": "securepass"}
    response = api_client.send_request("POST", "login", data=payload)
    assert "token" in response
    return response["token"]

@pytest.mark.usefixtures("test_login")
def test_get_user_profile(api_client, test_login):
    """测试获取用户信息"""
    headers = {"Authorization": f"Bearer {test_login}"}
    response = api_client.send_request("GET", "user/profile", headers=headers)
    assert response["username"] == "testuser"
    assert "email" in response

2. 执行测试

# 运行测试并生成Allure报告
pytest testcases/ --alluredir=./reports
allure serve ./reports

四、最佳实践

1. 环境隔离

   • 使用 pytest-base-url管理不同环境（开发/测试/生产）

   pytest --base-url https://dev-api.example.com

2. 数据管理

   • 使用YAML/JSON文件存储测试数据

   # data/login_cases.yaml
   - case: valid_login
    input: {username: "user1", password: "Pass123"}
    expected: {status: 200, has_token: true}
   - case: wrong_password
    input: {username: "user1", password: "wrong"}
    expected: {status: 401}

3. 认证处理

   • 自动处理Token刷新（通过 pytest fixture）

   @pytest.fixture(scope="session")
   def auth_token(api_client):
      # 获取并缓存Token
      return api_client.login()

4. 异常处理

   • 捕获并记录接口异常

   def send_request(self, method, endpoint, **kwargs):
      try:
          response = self.session.request(method, url, **kwargs)
          response.raise_for_status()
      except requests.exceptions.HTTPError as e:
          logger.error(f"API请求失败: {str(e)}")
          raise

五、高级技巧

1. Mock服务

   • 使用 responses或 pytest-mock模拟接口响应

   import responses
   
   @responses.activate
   def test_mock_api():
      responses.add(
          responses.GET, "https://api.example.com/data",
          json={"data": "mocked"}, status=200
      )
      response = requests.get("https://api.example.com/data")
      assert response.json()["data"] == "mocked"

2. 性能测试集成

   • 使用 locust进行简单压力测试

   from locust import HttpUser, task
   
   class ApiUser(HttpUser):
      @task
      def test_login(self):
          self.client.post("/login", json={"username":"test", "password":"test"})

六、持续集成（CI/CD）

1. GitHub Actions配置示例

   name: API Tests
   on: [push]
   jobs:
    test:
      runs-on: ubuntu-latest
      steps:
      - uses: actions/checkout@v2
      - name: Run Tests
        run: |
          pip install -r requirements.txt
          pytest --alluredir=./reports
      - name: Upload Report
        uses: actions/upload-artifact@v2
        with:
          name: allure-report
          path: ./reports

通过以上方案，你可以快速构建可维护的Python接口自动化测试框架。关键点：清晰的架构设计、数据驱动测试、合理的异常处理、与CI/CD的集成。

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