转载：http://www.cnblogs.com/sunny0/p/7771089.html

测试套件suite除了使用addTest以外，还有使用操作起来更更简便的makeSuite\testload\discover

1、makeSuite，创建测试套件，传的参数是要执行的测试用例所在的类名，如下代码makeSuite（）里传入的就是用例test01\test02所在的类Login,

代码：reload(sys)
sys.setdefaultencoding('utf-8')是将代码中的字符类型都转为UTF-8编码格式

#!/usr/bin/env.python
#-*-coding:utf-8-*-

from selenium import webdriver
import unittest
import sys

reload(sys)
sys.setdefaultencoding('utf-8')

class Login(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.driver = webdriver.Firefox()
cls.driver.maximize_window()
cls.driver.implicitly_wait(30)
cls.driver.get('https://www.baidu.com/')

    def test01(self):  
            '''验证网页title是否正确'''  
            self.assertTrue(str(self.driver.title).startswith('百度一下'))

    def test02(self):  
            '''验证网址是否正确'''  
            self.assertEqual(self.driver.current\_url, 'https://www.baidu.com/')

    @classmethod  
    def tearDownClass(cls):  
            cls.driver.quit()

    @staticmethod  
    def suite():  
            suite = unittest.makeSuite(Login)  
            return suite

if __name__ == '__main__':
unittest.TextTestRunner(verbosity=2).run(Login.suite())

2、testload:一般只有这个方法suite=unittest.TestLoader.loadTestsFromTestCase(Login)，传入的也是类名

#!/usr/bin/env.python
#-*-coding:utf-8-*-
from selenium import webdriver
import unittest

class Login(unittest.TestCase):

    @classmethod  
    def setUpClass(cls):  
            cls.driver = webdriver.Firefox()  
            cls.driver.maximize\_window()  
            cls.driver.implicitly\_wait(30)  
            cls.driver.get('https://www.baidu.com/')

    def test01(self):  
            '''验证网页title是否正确'''  
            self.assertEqual(self.driver.title,u'百度一下，你就知道')

    def test02(self):  
            '''验证网址是否正确'''  
            self.assertEqual(self.driver.current\_url, 'https://www.baidu.com/')

    @classmethod  
    def tearDownClass(cls):  
            cls.driver.quit()

    @staticmethod  
    def suite():  
            suite=unittest.TestLoader.loadTestsFromTestCase(Login)  
            return suite

if __name__ == '__main__':
unittest.TextTestRunner(verbosity=2).run(Login.suite())

3、discover:在实际测试中，被测试的系统肯定是多个模块，然后一个模块中有N条用例，discover就是以递归的方式找到制定目录里的文件（要被执行的用例模块文件，一般习惯都是test01.py.x的命名格式），加载在测试套件中，进行运行

discover的三个参数：

start_dir=os.path.join(os.path.dirname(__file__)+'/test1'),要被测试的文件所在的目录，一般是用os.path拼接

pattern='test*.py'，用正则表达式匹配测试用例的文件名，*表示一个或多个字符，'test*.py'表示以test开头的，中间N个字符，以.py结束的文件

top_level_dir=None 默认的

具体代码：

#!/usr/bin/env.python
#-*-coding:utf-8-*-
import unittest
import os

def suite():
suite=unittest.defaultTestLoader.discover(
start_dir=os.path.join(os.path.dirname(__file__)+'/test1'),
pattern='test*.py',
top_level_dir=None)
return suite

if __name__=='__main__':
unittest.TextTestRunner(verbosity=2).run(suite())

4、断言

assertEqual(a,b):a的值和b的值如果相等-->PASS

assertTrue(a) 表达式a的结果为真，则PASS

#!/usr/bin/env.python
#-*-coding:utf-8-*-
from selenium import webdriver
import unittest
import sys
reload(sys)
sys.setdefaultencoding('utf-8')

class Login(unittest.TestCase):

@classmethod  
def setUpClass(cls):  
    cls.driver=webdriver.Firefox()  
    cls.driver.maximize\_window()  
    cls.driver.implicitly\_wait(30)  
    cls.driver.get('https://www.baidu.com/')

def test01(self):  
    '''验证网页title是否正确'''  
    self.assertTrue(self.driver.title.startswith('百度一下'))

def test02(self):  
    '''验证网址是否正确'''  
    self.assertEqual(self.driver.current\_url,'https://www.baidu.com/')

@classmethod  
def tearDownClass(cls):  
    cls.driver.quit()

@staticmethod  
def suite():  
    suite=unittest.makeSuite(Login)  
    return suite  

if __name__=='__main__':
unittest.TextTestRunner(verbosity=2).run(Login.suite())

5、测试报告

5.1、使用对象file生成测试报告

fp=file(os.path.join(os.path.dirname(__file__)+'/TestReport.html'),'wb')

拆分解释：os.path.join(os.path.dirname(__file__)+'/TestReport.html')测试报告的路径（和名称），

'wb'：以二进制的方式写入

5.2、测试执行runner写法如下：（测试报告需导入import  HTMLTestRunner）

runner=HTMLTestRunner.HTMLTestRunner(
stream=fp,
title=u'报告的标题TestReport',
description=u'报告的描述'
)

HTMLTestRunner的三个参数：

stream=fp  指定测试报告是哪个文件

title=u'报告的标题TestReport',测试报告的标题

description=u'报告的描述'测试报告的描述

具体代码：

#!/usr/bin/env.python
#-*-coding:utf-8-*-
import os,sys
import unittest
import HTMLTestRunner
reload(sys)
sys.setdefaultencoding('utf-8')

def suite():
suite=unittest.defaultTestLoader.discover(
start_dir=os.path.join(os.path.dirname(__file__)+'/test1'),
pattern='test*.py',
top_level_dir=None)
return suite

if __name__=='__main__':
fp=file(os.path.join(os.path.dirname(__file__)+'/TestReport.html'),'wb')
runner=HTMLTestRunner.HTMLTestRunner(
stream=fp,
title=u'报告的标题TestReport',
description=u'报告的描述'
)
runner.run(suite())

测试报告：

aaarticlea/png;base64,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" alt="" />

右击在浏览器打开testReport.html,截图如下

注意：每个用例要测的是什么的描述必须要写，要不然测试报告中没有测试用例冒号：后的文字，就不知道哪个用例是测什么功能点的

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" 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" 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