简介

本文通过从Postman获取基本的接口测试Code简单的接口测试入手，一步步调整优化接口调用，以及增加基本的结果判断，讲解Python自带的Unittest框架调用，期望各位可以通过本文对接口自动化测试有一个大致的了解。

引言

为什么要做接口自动化测试?

在当前互联网产品迭代频繁的背景下，回归测试的时间越来越少，很难在每个迭代都对所有功能做完整回归。但接口自动化测试因其实现简单、维护成本低，容易提高覆盖率等特点，越来越受重视。

为什么要自己写框架呢?

使用Postman调试通过过直接可以获取接口测试的基本代码，结合使用requets + unittest很容易实现接口自动化测试的封装，而且requests的api已经非常人性化，非常简单，但通过封装以后（特别是针对公司内特定接口），可以进一步提高脚本编写效率。

一个现有的简单接口例子

下面使用requests + unittest测试一个查询接口

接口信息如下

请求信息:

Method：POST

URL：api/match/image/getjson

Request：

{
"category": "image",
"offset": "0",
"limit": "30",
"sourceId": "0",
"metaTitle": "",
"metaId": "0",
"classify": "unclassify",
"startTime": "",
"endTime": "",
"createStart": "",
"createEnd": "",
"sourceType": "",
"isTracking": "true",
"metaGroup": "",
"companyId": "0",
"lastDays": "1",
"author": ""
}

Response示例：

{
"timestamp" : xxx,
"errorMsg" : "",
"data" : {
"config" : xxx
}

Postman测试方法见截图：

测试思路

1.获取Postman原始脚本

2.使用requests库模拟发送HTTP请求**

3.对原始脚本进行基础改造**

4.使用python标准库里unittest写测试case**

原始脚本实现

未优化

该代码只是简单的一次调用，而且返回的结果太多，很多返回信息暂时没用，示例代码如下

import requests

url = "http://cpright.xinhua-news.cn/api/match/image/getjson"

querystring = {"category":"image","offset":"0","limit":"30","sourceId":"0","metaTitle":"","metaId":"0","classify":"unclassify","startTime":"","endTime":"","createStart":"","createEnd":"","sourceType":"","isTracking":"true","metaGroup":"","companyId":"0","lastDays":"1","author":""}

headers = {
    ‘cache-control‘: "no-cache",
    ‘postman-token‘: "e97a99b0-424b-b2a5-7602-22cd50223c15"
    }

response = requests.request("POST", url, headers=headers, params=querystring)

print(response.text)

优化 第一版

调整代码结构，输出结果Json出来，获取需要验证的response.status_code，以及获取结果校验需要用到的results[‘total‘]

#!/usr/bin/env python
#coding: utf-8
‘‘‘
unittest merchant backgroud interface
@author: zhang_jin
@version: 1.0
@see:http://www.python-requests.org/en/master/
‘‘‘

import unittest
import json
import traceback
import requests


url = "http://cpright.xinhua-news.cn/api/match/image/getjson"

querystring = {
    "category": "image",
    "offset": "0",
    "limit": "30",
    "sourceId": "0",
    "metaTitle": "",
    "metaId": "0",
    "classify": "unclassify",
    "startTime": "",
    "endTime": "",
    "createStart": "",
    "createEnd": "",
    "sourceType": "",
    "isTracking": "true",
    "metaGroup": "",
    "companyId": "0",
    "lastDays": "1",
    "author": ""
}

headers = {
    ‘cache-control‘: "no-cache",
    ‘postman-token‘: "e97a99b0-424b-b2a5-7602-22cd50223c15"
    }

#Post接口调用
response = requests.request("POST", url, headers=headers, params=querystring)

#对返回结果进行转义成json串
results = json.loads(response.text)

#获取http请求的status_code
print "Http code:",response.status_code

#获取结果中的total的值
print results[‘total‘]
#print(response.text)

优化 第二版

接口调用异常处理，增加try，except处理，对于返回response.status_code，返回200进行结果比对，不是200数据异常信息。

#!/usr/bin/env python
#coding: utf-8
‘‘‘
unittest merchant backgroud interface
@author: zhang_jin
@version: 1.0
@see:http://www.python-requests.org/en/master/
‘‘‘

import json
import traceback
import requests


url = "http://cpright.xinhua-news.cn/api/match/image/getjson"

querystring = {
    "category": "image",
    "offset": "0",
    "limit": "30",
    "sourceId": "0",
    "metaTitle": "",
    "metaId": "0",
    "classify": "unclassify",
    "startTime": "",
    "endTime": "",
    "createStart": "",
    "createEnd": "",
    "sourceType": "",
    "isTracking": "true",
    "metaGroup": "",
    "companyId": "0",
    "lastDays": "1",
    "author": ""
}

headers = {
    ‘cache-control‘: "no-cache",
    ‘postman-token‘: "e97a99b0-424b-b2a5-7602-22cd50223c15"
    }


try:
    #Post接口调用
    response = requests.request("POST", url, headers=headers, params=querystring)

    #对http返回值进行判断，对于200做基本校验
    if response.status_code == 200:
        results = json.loads(response.text)
        if results[‘total‘] == 191:
            print "Success"
        else:
            print "Fail"
            print results[‘total‘]
    else:
        #对于http返回非200的code，输出相应的code
        raise Exception("http error info:%s" %response.status_code)
except:
    traceback.print_exc()

优化 第三版

1.该版本改动较大，引入config文件，单独封装结果校验模块，引入unittest模块，实现接口自动调用，并增加log处理模块；
2.对不同Post请求结果进行封装，不同接口分开调用；
3.测试用例的结果进行统计并最终输出

#!/usr/bin/env python
#coding: utf-8
‘‘‘
unittest interface
@author: zhang_jin
@version: 1.0
@see:http://www.python-requests.org/en/master/
‘‘‘

import unittest
import json
import traceback
import requests
import time
import result_statistics
import config as cf
from com_logger import  match_Logger


class MyTestSuite(unittest.TestCase):
    """docstring for MyTestSuite"""
    #@classmethod
    def sedUp(self):
        print "start..."
    #图片匹配统计
    def test_image_match_001(self):
        url = cf.URL1

        querystring = {
            "category": "image",
            "offset": "0",
            "limit": "30",
          "sourceId": "0",
          "metaTitle": "",
          "metaId": "0",
          "classify": "unclassify",
          "startTime": "",
          "endTime": "",
          "createStart": "",
          "createEnd": "",
          "sourceType": "",
          "isTracking": "true",
          "metaGroup": "",
          "companyId": "0",
          "lastDays": "1",
          "author": ""
        }
        headers = {
            ‘cache-control‘: "no-cache",
            ‘postman-token‘: "545a2e40-b120-2096-960c-54875be347be"
            }


        response = requests.request("POST", url, headers=headers, params=querystring)
        if response.status_code == 200:
            response.encoding = response.apparent_encoding
            results = json.loads(response.text)
            #预期结果与实际结果校验，调用result_statistics模块
            result_statistics.test_result(results,196)
        else:
            print "http error info:%s" %response.status_code

        #match_Logger.info("start image_query22222")
        #self.assertEqual(results[‘total‘], 888)

        ‘‘‘
        try:
            self.assertEqual(results[‘total‘], 888)
        except:
            match_Logger.error(traceback.format_exc())
        #print results[‘total‘]
        ‘‘‘

    #文字匹配数据统计
    def test_text_match_001(self):

        text_url = cf.URL2

        querystring = {
            "category": "text",
            "offset": "0",
            "limit": "30",
            "sourceId": "0",
            "metaTitle": "",
            "metaId": "0",
            "startTime": "2017-04-14",
            "endTime": "2017-04-15",
            "createStart": "",
            "createEnd": "",
            "sourceType": "",
            "isTracking": "true",
            "metaGroup": "",
            "companyId": "0",
            "lastDays": "0",
            "author": "",
            "content": ""
        }
        headers = {
            ‘cache-control‘: "no-cache",
            ‘postman-token‘: "ef3c29d8-1c88-062a-76d9-f2fbebf2536c"
            }

        response = requests.request("POST", text_url, headers=headers, params=querystring)

        if response.status_code == 200:
            response.encoding = response.apparent_encoding
            results = json.loads(response.text)
            #预期结果与实际结果校验，调用result_statistics模块
            result_statistics.test_result(results,190)
        else:
            print "http error info:%s" %response.status_code

        #print(response.text)

    def tearDown(self): 
        pass

if __name__ == ‘__main__‘:
    #image_match_Logger = ALogger(‘image_match‘, log_level=‘INFO‘)

    #构造测试集合
    suite=unittest.TestSuite()
    suite.addTest(MyTestSuite("test_image_match_001"))
    suite.addTest(MyTestSuite("test_text_match_001"))

    #执行测试
    runner = unittest.TextTestRunner()
    runner.run(suite)
    print "success case:",result_statistics.num_success
    print "fail case:",result_statistics.num_fail
    #unittest.main()

最终输出日志信息

Zj-Mac:unittest lazybone$ python image_test_3.py 
测试结果：通过

.测试结果：不通过 
错误信息： 期望返回值:190 实际返回值:4522

.
----------------------------------------------------------------------
Ran 2 tests in 0.889s

OK
success case: 1
fail case: 1

后续改进建议

1.unittest输出报告也可以推荐使用HTMLTestRunner（我目前是对结果统计进行了封装）

2.接口的继续封装，参数化，模块化

3.unittest单元测试框架实现参数化调用第三方模块引用（nose-parameterized）

4.持续集成运行环境、定时任务、触发运行、邮件发送等一系列功能均可以在Jenkins上实现。