python （必看）10个提升接口自动化编写效率的脚本！

亲爱的开发者们，👋 在快速迭代的软件开发周期中，接口自动化测试扮演着至关重要的角色。今天，我们将分享10个实用的Python小脚本，它们能够显著提升你编写接口自动化测试的效率。无论是初学者还是资深工程师，这些技巧都将帮助你更高效、更优雅地完成工作。🌟

1. 自动化生成测试用例模板

import stringimport randomdef generate_test_case_template(test_name, endpoint):    template = f"""def test_{test_name}(self):    url = '{endpoint}'    # Your test logic here    pass"""    return templateclass TestCases:    # Generate and print templates for all your endpoints    for i in range(1, 11):        print(generate_test_case_template(f"case_{i}", f"/api/v1/endpoint_{i}"))

2. 从CSV文件读取测试数据

import csvdef read_test_data_from_csv(file_path):    test_data = []    with open(file_path, mode='r') as file:        reader = csv.DictReader(file)        for row in reader:            test_data.append(row)    return test_datadata = read_test_data_from_csv('test_data.csv')for row in data:    print(row)

3. 动态构建请求头

def build_headers(token=None, content_type="application/json"):    headers = {"Content-Type": content_type}    if token:        headers["Authorization"] = f"Bearer {token}"    return headersheaders = build_headers(token="your-token-here")print(headers)

4. 发送带重试机制的HTTP请求

import requestsfrom tenacity import retry, stop_after_attempt, wait_fixed@retry(stop=stop_after_attempt(3), wait=wait_fixed(2))def send_request(url, method="GET", params=None, headers=None):    response = requests.request(method, url, params=params, headers=headers)    response.raise_for_status()    return response.json()data = send_request("https://api.example.com/data", headers={"Authorization": "Bearer your-token"})print(data)

5. JSON响应验证

import jsondef validate_response(response, expected_schema):    try:        assert isinstance(response, dict)        for key, value in expected_schema.items():            assert key in response, f"Missing key: {key}"            if isinstance(value, dict):                validate_response(response[key], value)            else:                assert isinstance(response[key], type(value)), f"Incorrect type for key: {key}"    except AssertionError as e:        print(e)        return False    return Trueschema = {"name": str, "age": int}response = {"name": "John Doe", "age": 30}validate_response(response, schema)

6. 自动化文档注释

def auto_docstring(func):    func.__doc__ = f"""    {func.__name__}:     - Description: This function tests the {func.__name__} endpoint.    - Endpoint: /api/{func.__name__}    """    return func@auto_docstringdef test_user_login(self):    pass

7. 数据随机化

def random_email():    return ''.join(random.choice(string.ascii_lowercase) for _ in range(10)) + "@example.com"print(random_email())

8. 配置管理

import yamldef load_config(file_path):    with open(file_path, 'r') as file:        return yaml.safe_load(file)config = load_config('config.yml')print(config)

9. 异常处理和日志记录

import logginglogging.basicConfig(level=logging.INFO)def safe_request(url):    try:        response = requests.get(url)        response.raise_for_status()        return response.json()    except requests.RequestException as e:        logging.error(f"Error making request to {url}: {e}")        return Nonedata = safe_request("https://api.example.com/data")if data:    print(data)else:    print("Request failed.")

10. 测试报告生成

import unittestfrom HTMLTestRunner import HTMLTestRunnerclass MyTestCase(unittest.TestCase):    def test_something(self):        self.assertEqual(True, True)if __name__ == '__main__':    suite = unittest.TestLoader().loadTestsFromTestCase(MyTestCase)    runner = HTMLTestRunner(output='reports', verbosity=2)    runner.run(suite)