接口自动化测试框架-AIM2.0

跳转到3.0版本https://www.cnblogs.com/df888/p/12031649.html

AIM是我用python搭建的第一款接口自动化测试框架，随着技术的提升，框架也在升级，故有了AIM2.0。

附上 AIM1.0链接

什么是AIM2.0？

AIM2.0 makes it easier to interface testing more quickly and with less code.
                                                               
                                                               ————改编自django

先皮一下啦，哈哈哈。

AIM2.0特点

• 原生python，简单易用
• for while if，逻辑控制灵活
• 随机值、响应值、数据库值，取值简单
• 友好支持代码级json显示，参数化直接
• 写代码，调试方便
• parewise算法等，覆盖场景更多

为了能更好的发挥这些特点，需要一定的编程能力

现在这时代不懂点编程，怎么做测试呢？

AIM2.0怎么用

unittest->pytest

最简单的一个case代码

from common.request import post
from common.assertion import *


def test():
    """一个简单的post请求结构"""
    r = post({
        "url": "",
        "headers": {},
        "body": {}
    })
    check_flag(r)

执行测试

目录结构

Postar

----case 用例

----common 公共

----config 配置

----data 数据

----result 结果

简洁明了的风格

核心代码

request

request是基于requests封装的请求，重中之中。

相比AIM1.0，做了一些重构。1.采用dict来存取请求相关数据；2.改用装饰器来处理post、get、put等方法 3.csv解耦内聚，从csv_reader.py挪到了request.py

req = {
    "default_headres": {"Content-Type": "application/json"},
    "p": None,
    "method": None,
    "r": None,
    "elapsed": None,
    "log_level": 1  # req日志级别 0不log不record 1log 2record 3log+record
}


def _sender(f):
    method = f.__name__

    def s(p, param='json'):
        param_map = {
            'post': param,  # json data
            'get': 'params',
            'put': 'json'
        }

        p['headers'] = p['headers'] if p['headers'] else req['default_headers']

        start = time.process_time()
        _timeout_try(f"requests.{method}(\"{p['url']}\", headers={p['headers']}, "
                     f"{param_map[method]}={p['body']}, verify=False)")
        end = time.process_time()

        req['elapsed'] = decimal.Decimal("%.2f" % float(end - start))
        req['p'] = p
        req['method'] = method
        _req_log()
        return req['r']

    return s


def _timeout_try(expression):
    while True:
        try:
            req['r'] = eval(expression)
        except (requests.exceptions.SSLError, requests.exceptions.ConnectionError) as e:
            if 'bad handshake' in str(e) or '10054' in str(e):
                continue
            else:
                raise Exception(e)
        break


def _req_log():
    if req['log_level'] in (1, 3):
        logger.info(f"{req['p']['url']} {req['method']} 请求头{obj2json(req['p']['headers'])} "
                    f"参数{obj2json(req['p']['body'])}\n响应\n{req['r'].text}\n")

    if req['log_level'] in (2, 3):
        title = ['time', 'status', 'elapsed(s)', 'url', 'headers', 'method', 'body', 'response']
        row = [current_time(),
               req['r'].status_code,
               req['elapsed'],
               req['p']['url'],
               obj2json(req['p']['headers']),
               req['method'],
               obj2json(req['p']['body']),
               req['r'].text,
               ' ']  # 多写一列空格，response列数据显示不会溢出单元格
        write_record(csv_path, title, row)


@_sender
def post():
    """post"""


@_sender
def get():
    """get"""


@_sender
def put():
    """put"""

dao

Data Access Object，目前仅支持mysql。

借助pandas和sqlalchemy做了极大的简化

class Dao:
    def __init__(self, address, user, password):
        self.engine = create_engine(f'mysql+pymysql://{user}:{password}@{address}')

    def select(self, sql):
        """
        查询
        :param sql:
        :return: DataFrame 可以按二维数组来查值 data['col_name']['row_num']
        """
        logger.info(f'执行sql:{sql}')
        return pd.read_sql(sql, self.engine)

randomer

专门用来产生随机数据的

def p_sample(seq, n):
    """
    postar的sample，防止越界
    :param seq:
    :param n:
    :return:
    """
    return random.sample(seq, n if n < len(seq) else len(seq))


def random_hanzi(n):
    """随机中文汉字"""
    return ''.join(random.sample(hanzi.replace('\r', '').replace('\n', ''), n))


def random_id(n):
    """随机id"""
    s = ""
    for i in range(n):
        s += str(random.randint(0, 9))
    return int(s)


def random_01(n):
    """随机01编码 '1010100' """
    return ''.join([random.choice('01') for i in range(n)])


def _timestamp(t):
    """时间戳"""
    y, m, d = tuple(int(x) for x in t.split('-'))
    m = (y, m, d, 0, 0, 0, 0, 0, 0)
    return time.mktime(m)


def random_date(start, end, n):
    """默认返回n个日期 列表"""
    start = _timestamp(start)
    end = _timestamp(end)
    return [time.strftime("%Y-%m-%d", time.localtime(random.randint(start, end))) for i in range(n)]


def range_num(a, b, interval=1.0):
    if interval == 1:
        return [i for i in range(a, b)]
    if interval == 0.5:
        out = []
        for i in range(a, b):
            out.append(i)
            out.append(i + 0.5)
        return out


def range_str(a, b, random_n=None):
    out = [str(i) for i in range(a, b)]
    return out if random_n is None else p_sample(out, random_n)

log

logger = logging.getLogger()
logger.setLevel(logging.INFO)  # 设置日志级别，默认为WARN
_formatter = logging.Formatter('\n[%(asctime)s]%(message)s', '%Y-%m-%d %H:%M:%S')

# 文件
fh = logging.FileHandler(log_path, encoding="utf-8")
fh.setFormatter(_formatter)
logger.addHandler(fh)

# 控制台
stdout = sys.stdout
ch = logging.StreamHandler(stdout)
ch.setFormatter(_formatter)
logger.addHandler(ch)


def stdout_write(msg):
    stdout.write(msg)
    stdout.flush()


if __name__ == '__main__':
    logger.info('hello')

func

一些公共函数

def encrypt(pwd):
    """base64加密"""
    return base64.b64encode(pwd.encode()).decode()


def current_time(n=0):
    time_format = ['%Y-%m-%d %H:%M:%S',  # 时间
                   '%Y-%m-%d',  # 日期
                   '%Y%m%d%H%M%S']  # 数字
    return time.strftime(time_format[n], time.localtime(time.time()))


def last_natural_day():
    """
    上个自然日
    :return:
    """
    return (datetime.datetime.now() + datetime.timedelta(days=-1)).strftime("%Y-%m-%d")


def obj2json(x):
    """
    obj to json
    :param x:
    :return: json
    """
    if isinstance(x, dict):
        return json.dumps(x, ensure_ascii=False)
    elif isinstance(x, str):
        return ast.literal_eval(x.replace('null', '\'\'').replace('false', '\'\''))


def lower_id(s):
    """report/downExcel to report_down_excel"""
    s = ''.join(['_' + c.lower() if c.isupper()
                 else c for c in s.replace('/', '_')])
    return s[1:] if s[0] == '_' else s


def upper_id(s):
    """national_market_index to NationalMarketIndex"""
    return ''.join(x[0].upper() + x[1:] for x in s.replace(' ', '').replace('/', '_').split('_'))


def bar(i):
    """
    进度条
    :param i: 百分比
    :return:
    """
    c = int(i / 10)
    jd = '\r %2d%% [%s%s]'
    a = '■' * c
    b = '□' * (10 - c)
    stdout_write(jd % (i, a, b))


def json2form(body):
    """
    json转表单
    :param body: {"a": 1, "b": 2}
    :return: a=1&b=2
    """
    return '&'.join([f"{k}={v}" for k, v in body.items()])


def form2json(form):
    """
    表单转json
    :param form: a=1&b=2
    :return: {"a": 1, "b": 2}
    """
    body = {}
    for kv in form.split('&'):
        k, v = kv.split('=')
        body[k] = v
    return json.dumps(body, indent=4, ensure_ascii=False)

在实际工作中，发现还有不少优化的余地，期待在未来做到3.0，再出个“手把手教你用AIM做接口自动化”。