Original link: http://www.cnblogs.com/wateryx/p/10790293.html

Forwarding: http: //www.cnblogs.com/lovesoo/p/7845731.html

table of Contents

1. What is the interface testing

As the name suggests, is to test the interface between the interface of the system or component testing, the main exchange check data, management and control transfer process, and the mutual logical dependencies. Wherein the interface protocol into HTTP, WebService, Dubbo, Thrift, Socket and other type, test type and is divided into functional testing, performance testing, stability testing, security testing.

In hierarchical test "pyramid" model, it belongs to the second layer interface testing integration testing service category. Compared to the UI layer (mainly WEB or APP) in terms of automated testing, test automation interfaces greater profit, and easy to implement, low maintenance costs, with higher input-output ratio, is the preferred each company to carry out automated tests.

Here we have an HTTP interface as an example, a complete introduction to the interface automated testing process: from requirements analysis to, from a script written in case design, test execution to the results of the analysis, and provides a complete test case design and test scripts.

2. The basic flow

The basic interface functions automated testing process is as follows:

Requirements Analysis -> Use Case Design -> script development -> test execution -> results analysis

Example 2.1 Interface

Interface Name: IMDb search

Interface documentation Address: https://developers.douban.com/wiki/?title=movie_v2#search

Interface call:

1) Search by cast and crew: https://api.douban.com/v2/movie/search?q= Zhang Yimou

2) Search by Title: https://api.douban.com/v2/movie/search?q= Westward Journey

3) Search by type: https://api.douban.com/v2/movie/search?tag= Comedy

3. Requirements Analysis

Needs analysis is the reference requirements, design documents, on the basis of a clear understanding of the needs of the need to achieve internal logic, and can be made at present demand, poorly designed or omissions at this stage.

Such as: IMDb search interface, that is my understanding of the needs to support the search for the title, cast and crew and labeling, and return to the search results page.

Example 4. Design

Case design is based on the understanding interface testing requirements, or use other XMind MindManager mind mapping software designed to write test cases, the main parameters including calibration, verification function, verification business scenarios, and other safety and performance verification, Example using conventional design methods have equivalence partitioning method, boundary value analysis, scene analysis, cause and effect diagrams, and other orthogonal.

IMDb search interface for the functional testing section, we mainly check from three parameters check, function check, business scenarios, design test cases as follows:

5. Script Development

Prepared in accordance with the above test case design, we use python + nosetests framework for writing automated test scripts related. Implement the interface can complete automated testing, automatic test execution and reporting functions to send messages.

5.1 Related lib installation

Lib library as necessary, can be installed using pip command:

pip install nose
pip install nose-html-reporting
pip install requests

5.2 interface calls

Requests to use the library, we can easily prepare said interface method calls (e.g., q = Andy search, the following sample code):

#coding=utf-8
import requests
import json
 
url = 'https://api.douban.com/v2/movie/search'
params=dict(q=u'刘德华')
r = requests.get(url, params=params)
print 'Search Params:\n', json.dumps(params, ensure_ascii=False)
print 'Search Response:\n', json.dumps(r.json(), ensure_ascii=False, indent=4)

在实际编写自动化测试脚本时，我们需要进行一些封装。如下代码中我们对豆瓣电影搜索接口进行了封装，test_q方法只需使用nosetests提供的yield方法即可很方便的循环执行列表qs中每一个测试集：

class test_doubanSearch(object):

    @staticmethod
    def search(params, expectNum=None):
        url = 'https://api.douban.com/v2/movie/search'
        r = requests.get(url, params=params)
        print 'Search Params:\n', json.dumps(params, ensure_ascii=False)
        print 'Search Response:\n', json.dumps(r.json(), ensure_ascii=False, indent=4)

    def test_q(self):
        # 校验搜索条件 q
        qs = [u'白夜追凶', u'大话西游', u'周星驰', u'张艺谋', u'周星驰,吴孟达', u'张艺谋,巩俐', u'周星驰,大话西游', u'白夜追凶,潘粤明']
        for q in qs:
            params = dict(q=q)
            f = partial(test_doubanSearch.search, params)
            f.description = json.dumps(params, ensure_ascii=False).encode('utf-8')
            yield (f,)

我们按照测试用例设计，依次编写每个功能的自动化测试脚本即可。

5.3 结果校验

在手工测试接口的时候，我们需要通过接口返回的结果判断本次测试是否通过，自动化测试也是如此。

对于本次的接口，我们搜索“q=刘德华”，我们需要判断返回的结果中是否含有“演职人员刘德华或片名刘德华”，搜索“tag=喜剧”时，需要判断返回的结果中电影类型是否为“喜剧”，结果分页时需要校验返回的结果数是否正确等。完整结果校验代码如下：

class check_response():
    @staticmethod
    def check_result(response, params, expectNum=None):
        # 由于搜索结果存在模糊匹配的情况，这里简单处理只校验第一个返回结果的正确性
        if expectNum is not None:
            # 期望结果数目不为None时，只判断返回结果数目
            eq_(expectNum, len(response['subjects']), '{0}!={1}'.format(expectNum, len(response['subjects'])))
        else:
            if not response['subjects']:
                # 结果为空，直接返回失败
                assert False
            else:
                # 结果不为空，校验第一个结果
                subject = response['subjects'][0]
                # 先校验搜索条件tag
                if params.get('tag'):
                    for word in params['tag'].split(','):
                        genres = subject['genres']
                        ok_(word in genres, 'Check {0} failed!'.format(word.encode('utf-8')))

                # 再校验搜索条件q
                elif params.get('q'):
                    # 依次判断片名，导演或演员中是否含有搜索词，任意一个含有则返回成功
                    for word in params['q'].split(','):
                        title = [subject['title']]
                        casts = [i['name'] for i in subject['casts']]
                        directors = [i['name'] for i in subject['directors']]
                        total = title + casts + directors
                        ok_(any(word.lower() in i.lower() for i in total),
                            'Check {0} failed!'.format(word.encode('utf-8')))

    @staticmethod
    def check_pageSize(response):
        # 判断分页结果数目是否正确
        count = response.get('count')
        start = response.get('start')
        total = response.get('total')
        diff = total - start

        if diff >= count:
            expectPageSize = count
        elif count > diff > 0:
            expectPageSize = diff
        else:
            expectPageSize = 0

        eq_(expectPageSize, len(response['subjects']), '{0}!={1}'.format(expectPageSize, len(response['subjects'])))

5.4 执行测试

对于上述测试脚本，我们使用nosetests命令可以方便的运行自动化测试，并可使用nose-html-reporting插件生成html格式测试报告。

运行命令如下：

nosetests -v test_doubanSearch.py:test_doubanSearch --with-html --html-report=TestReport.html

5.5 发送邮件报告

测试完成之后，我们可以使用smtplib模块提供的方法发送html格式测试报告。基本流程是读取测试报告 -> 添加邮件内容及附件 -> 连接邮件服务器 -> 发送邮件 -> 退出，示例代码如下：

import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart

def send_mail():
    # 读取测试报告内容
    with open(report_file, 'r') as f:
        content = f.read().decode('utf-8')

    msg = MIMEMultipart('mixed')
    # 添加邮件内容
    msg_html = MIMEText(content, 'html', 'utf-8')
    msg.attach(msg_html)

    # 添加附件
    msg_attachment = MIMEText(content, 'html', 'utf-8')
    msg_attachment["Content-Disposition"] = 'attachment; filename="{0}"'.format(report_file)
    msg.attach(msg_attachment)

    msg['Subject'] = mail_subjet
    msg['From'] = mail_user
    msg['To'] = ';'.join(mail_to)
    try:
        # 连接邮件服务器
        s = smtplib.SMTP(mail_host, 25)
        # 登陆
        s.login(mail_user, mail_pwd)
        # 发送邮件
        s.sendmail(mail_user, mail_to, msg.as_string())
        # 退出
        s.quit()
    except Exception as e:
        print "Exceptioin ", e

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