Python接口自动化浅析logging封装及实战操作

logger:
  name: ITester
  level: DEBUG
  format: '%(filename)s-%(lineno)d-%(asctime)s-%(levelname)s-%(message)s'

import yaml
class YamlHandler:
    def __init__(self, file):
        self.file = file
    def read_yaml(self, encoding='utf-8'):
        """读取yaml数据"""
        with open(self.file, encoding=encoding) as f:
            return yaml.load(f.read(), Loader=yaml.FullLoader)
    def write_yaml(self, data, encoding='utf-8'):
        """向yaml文件写入数据"""
        with open(self.file, encoding=encoding, mode='w') as f:
            return yaml.dump(data, stream=f, allow_unicode=True)
yaml_data = YamlHandler('../config/config.yaml').read_yaml()

class Logger(Filterer):
    """
    Instances of the Logger class represent a single logging channel. A
    "logging channel" indicates an area of an application. Exactly how an
    "area" is defined is up to the application developer. Since an
    application can have any number of areas, logging channels are identified
    by a unique string. Application areas can be nested (e.g. an area
    of "input processing" might include sub-areas "read CSV files", "read
    XLS files" and "read Gnumeric files"). To cater for this natural nesting,
    channel names are organized into a namespace hierarchy where levels are
    separated by periods, much like the Java or Python package namespace. So
    in the instance given above, channel names might be "input" for the upper
    level, and "input.csv", "input.xls" and "input.gnu" for the sub-levels.
    There is no arbitrary limit to the depth of nesting.
    """
    def __init__(self, name, level=NOTSET):
        """
        Initialize the logger with a name and an optional level.
        """
        Filterer.__init__(self)
        self.name = name
        self.level = _checkLevel(level)
        self.parent = None
        self.propagate = True
        self.handlers = []
        self.disabled = False
    def setLevel(self, level):
        """
        Set the logging level of this logger.  level must be an int or a str.
        """
        self.level = _checkLevel(level)

import logging
from common.yaml_handler import yaml_data
class LoggerHandler(logging.Logger):
    # 继承Logger类
    def __init__(self,
                 name='root',
                 level='DEBUG',
                 file=None,
                 format=None
                 ):
        # 设置收集器
        super().__init__(name)
        # 设置收集器级别
        self.setLevel(level)
        # 设置日志格式
        fmt = logging.Formatter(format)
        # 如果存在文件，就设置文件处理器，日志输出到文件
        if file:
            file_handler = logging.FileHandler(file,encoding='utf-8')
            file_handler.setLevel(level)
            file_handler.setFormatter(fmt)
            self.addHandler(file_handler)
        # 设置StreamHandler,输出日志到控制台
        stream_handler = logging.StreamHandler()
        stream_handler.setLevel(level)
        stream_handler.setFormatter(fmt)
        self.addHandler(stream_handler)
# 从yaml配置文件中读取logging相关配置
logger = LoggerHandler(name=yaml_data['logger']['name'],
                       level=yaml_data['logger']['level'],
                       file='../log/log.txt',
                       format=yaml_data['logger']['format'])

import unittest
from common.requests_handler import RequestsHandler
from common.excel_handler import ExcelHandler
import ddt
import json
from common.logger_handler import logger
@ddt.ddt
class TestLogin(unittest.TestCase):
    # 读取excel中的数据
    excel = ExcelHandler('../data/cases.xlsx')
    case_data = excel.read_excel('login')
    print(case_data)
    def setUp(self):
        # 请求类实例化
        self.req = RequestsHandler()
    def tearDown(self):
        # 关闭session管理器
        self.req.close_session()
    @ddt.data(*case_data)
    def test_login_success(self,items):
        logger.info('*'*88)
        logger.info('当前是第{}条用例：{}'.format(items['case_id'],items['case_title']))
        logger.info('当前用例的测试数据：{}'.format(items))
        # 请求接口
        res = self.req.visit(method=items['method'],url=items['url'],json=json.loads(items['payload']),
                             headers=json.loads(items['headers']))
        try:
            # 断言：预期结果与实际结果对比
            self.assertEqual(res['code'], items['expected_result'])
            logger.info(res)
            result = 'Pass'
        except AssertionError as e:
            logger.error('用例执行失败：{}'.format(e))
            result = 'Fail'
            raise e
        finally:
            # 将响应的状态码，写到excel的第9列，即写入返回的状态码
            TestLogin.excel.write_excel("../data/cases.xlsx", 'login', items['case_id'] + 1, 9, res['code'])
            # 如果断言成功，则在第10行(测试结果)写入Pass,否则，写入Fail
            TestLogin.excel.write_excel("../data/cases.xlsx", 'login', items['case_id'] + 1, 10, result)
if __name__ == '__main__':
    unittest.main()