Python接口自動化淺析logging封裝及實戰(zhàn)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'):
        """讀取yaml數(shù)據(jù)"""
        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文件寫入數(shù)據(jù)"""
        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):
    # 繼承Logger類
    def __init__(self,
                 name='root',
                 level='DEBUG',
                 file=None,
                 format=None
                 ):
        # 設置收集器
        super().__init__(name)
        # 設置收集器級別
        self.setLevel(level)
        # 設置日志格式
        fmt = logging.Formatter(format)
        # 如果存在文件，就設置文件處理器，日志輸出到文件
        if file:
            file_handler = logging.FileHandler(file,encoding='utf-8')
            file_handler.setLevel(level)
            file_handler.setFormatter(fmt)
            self.addHandler(file_handler)
        # 設置StreamHandler,輸出日志到控制臺
        stream_handler = logging.StreamHandler()
        stream_handler.setLevel(level)
        stream_handler.setFormatter(fmt)
        self.addHandler(stream_handler)
# 從yaml配置文件中讀取logging相關配置
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):
    # 讀取excel中的數(shù)據(jù)
    excel = ExcelHandler('../data/cases.xlsx')
    case_data = excel.read_excel('login')
    print(case_data)
    def setUp(self):
        # 請求類實例化
        self.req = RequestsHandler()
    def tearDown(self):
        # 關閉session管理器
        self.req.close_session()
    @ddt.data(*case_data)
    def test_login_success(self,items):
        logger.info('*'*88)
        logger.info('當前是第{}條用例：{}'.format(items['case_id'],items['case_title']))
        logger.info('當前用例的測試數(shù)據(jù)：{}'.format(items))
        # 請求接口
        res = self.req.visit(method=items['method'],url=items['url'],json=json.loads(items['payload']),
                             headers=json.loads(items['headers']))
        try:
            # 斷言：預期結(jié)果與實際結(jié)果對比
            self.assertEqual(res['code'], items['expected_result'])
            logger.info(res)
            result = 'Pass'
        except AssertionError as e:
            logger.error('用例執(zhí)行失?。簕}'.format(e))
            result = 'Fail'
            raise e
        finally:
            # 將響應的狀態(tài)碼，寫到excel的第9列，即寫入返回的狀態(tài)碼
            TestLogin.excel.write_excel("../data/cases.xlsx", 'login', items['case_id'] + 1, 9, res['code'])
            # 如果斷言成功，則在第10行(測試結(jié)果)寫入Pass,否則，寫入Fail
            TestLogin.excel.write_excel("../data/cases.xlsx", 'login', items['case_id'] + 1, 10, result)
if __name__ == '__main__':
    unittest.main()