【Python + yaml】之yaml文件數據驅動（包括DDT驅動）

寫自動化測試代碼中，數據驅動傳遞參數比較方便一些，也便於后期維護，下面介紹兩種數據驅動：

 

下面是test.yaml文件：

start_HRApp:
  ip: 127.0.0.1
  port: 4723
  implicitly_wait: 10
  caps:
    android:
      platformName: Android
      #模擬器
      platformVersion: 6.0
      deviceName: OPPO
      appPackage: com.csksc2b.invertory
      appActivity: com.csks.login.SplashAty
#      noReset: True
#      unicodeKeyboard: True
#      resetKeyboard: True
#      autoGrantPermissions: True
      automationName: uiautomator2
    ios:

①用於一般文件的yaml數據驅動：【個人推薦這個】，它不僅可以用在測試用例，也可以用在其他py文件中

from appium import webdriver
import yaml
import os

def des_caps():

    # 基礎路徑
    base_dir = os.path.dirname(os.path.dirname(__file__))
    # yaml路徑
    yaml_path = base_dir + "/data/ddt_data_file.yaml"
    # 獲取yaml的數據
    with open(yaml_path,'r',encoding='utf-8') as file:
        data = yaml.load(file)
    start = data['start_HRApp']
    Cap = start['caps']['android']

    driver = webdriver.Remote("http://"+ str(start['ip']) +":"+ str(start['port']) +"/wd/hub",Cap)
    driver.implicitly_wait(10)

    return driver

========================================================= 

yaml文件

case01:
  url: https://ascendas.17mine.cn/basic/pick/selectPage
  headers:
    Authorization: eyJhbGciOiJIUzI1NiJ9.eyJuZWVkRWRpdCI6LTEsImxvZ2luVGltZSI6MTU5MDYyOTYwMTU0NSwibG9naW5XYXkiOjEsInVzZXJOYW1lIjoi5byg55WFIiwidXNlcklkIjoiMTI1NDI5NDE4NzAzODM0NzI2NCIsImxvZ2luU291cmNlIjotMSwiYWNjb3VudCI6IjEzNjQyMDQwNjMxIiwiZXhwIjoxNTkwNjcyODAxfQ.qydhemA3sGfrBuHFWcTi8OdaOcm7hvIpgErtkQ2OVBo
  payload:
    pageNum: 1
    pageSize: 1
    user_id: 1254294187038347264
    userId: 1254294187038347264
    infos_id: 1207504682260500480
    infoId: 1207504682260500480

或者自定義一個方法：

    def yamlData(self):
        '''獲取yaml數據'''
        self.path = os.path.dirname(os.path.abspath(__file__))
        # yaml路徑
        self.yamlPath = self.path + "/data/case_data.yaml"
        # 獲取yaml數據
        with open(self.yamlPath, 'r', encoding='utf-8') as file:
            data = yaml.load(file)
        return data

然后再引用：

    def test_request01(self):
        case01 = self.yamlData()['case01']
        url = case01['url']
        payload = case01['payload']
        headers = case01['headers']

        r = requests.post(url,params=payload,headers=headers).json()
        self.assertEqual(r['data']['records'][0]['stockOutName'],"0506測試倉庫")

 

②用於測試用例中的yaml數據驅動（DDT）：

yaml文件：

case02:
  url: https://www.v2ex.com/api/nodes/show.json
  payload:
    name: python

 

import unittest
import requests
import os
import yaml
from ddt import ddt, data, file_data, unpack


@ddt
class TestResquest(unittest.TestCase):
    @file_data('./data/case_data.yaml')
    @unpack
    def test_request02(self,**kwargs):
        url = kwargs['url']
        payload = kwargs['payload']
        r = requests.get(url,params=payload).json()
        self.assertEqual(r['id'],901)

但是DDT有一點不好的是不靈活，如果有兩個case的yaml，想獲取url，他會把兩個URL一塊執行再一個用例中

case01:
  url: https://ascendas.17mine.cn/basic/assemble/selectPage
  headers:
    Authorization: eyJhbGciOiJIUzI1NiJ9.eyJuZWVkRWRpdCI6LTEsImxvZ2luVGltZSI6MTU5MTE0NDk2NTExOSwibG9naW5XYXkiOjEsInVzZXJOYW1lIjoi5byg55WFIiwidXNlcklkIjoiMTI1NDI5NDE4NzAzODM0NzI2NCIsImxvZ2luU291cmNlIjotMSwiYWNjb3VudCI6IjEzNjQyMDQwNjMxIiwiZXhwIjoxNTkxMTg4MTY1fQ.OiSBpkRJMZsABAlKhfo4P2cmZuqk6V63vDACZBY5Xs8
  payload:
    pageNum: 1
    pageSize: 1
#    user_id: 1254294187038347264
#    userId: 1254294187038347264
#    infos_id: 1207504682260500480
    infoId: 1207504682260500480


case02:
  url: https://www.v2ex.com/api/nodes/show.json
  payload:
    name: python

 

 

 如果想測試重復的用例可以適用這個。但是變化較多的字段的用例不適用。

如下測試重復的用例：

用例1:
  data1:
    - keys: "yaml01"
    - keys: "yaml02"
  data2:
    - keys: "yaml03"
    - keys: "yaml04"
用例2:
  data1:
    - keys: "yaml05"
    - keys: "yaml06"
  data2:
    - keys: "yaml07"
    - keys: "yaml08"
用例3:
  data1:
    - keys: "yaml09"
    - keys: "yaml10"
  data2:
    - keys: "yaml11"
    - keys: "yaml12"

代碼：

import unittest
import requests
import os
import yaml
from ddt import ddt, data, file_data, unpack


@ddt
class TestResquest(unittest.TestCase):
    @file_data("../data/ddt_data_file.yaml")
    @unpack
    def test_baiduSearch03(self,**kwargs):
        keys = kwargs['data1'][1]['keys']
        print("第三組測試用例：",keys)
        self.baidu_search(keys)
        self.assertEqual(self.driver.title, keys + "_百度搜索", msg="標題不正確！")

一個用例可以執行三遍

 

 

 

優缺點：

①一般的yaml方法，可以適用於任何文件，只是寫法有點繁瑣，適用於多種用例，較靈活。

②DDT的yaml方法，只能用於測試用例文件中，寫法簡單，適用於一種重復性用例，不靈活。

 

拓展：

YAML、YML在線編輯(校驗)器

把yaml文件轉換成json