亚马逊的lambda跟api_dateway搭配编写接口测试，看了文档发现时间29秒必须出结果，否则超时，像我们爬虫数据比较多的，多爬点数据就容易超时，那应该怎么办呢。

于是我挑了一个轻量级的进行简单学习--tonador

这边我写一个接口用来提取介词短语进行接口测试。--正好最近要进行提取介词短语的测试，就以这个例子为主，编码。

首先安装tornado 

pip install tonador

接下来看代码的实例

 

# -*- coding:utf-8 -*-import sysimport jsonimport pymysqlsys.path.append('../')import tornado.httpserverimport tornado.ioloopimport tornado.optionsimport tornado.webimport nltk,sysimport jsonfrom extractor import phrases_extractorfrom tornado.options import define, optionsdefine("port", default=8000, help="run on the given port", type=int)#定义处理类型class IndexHandler(tornado.web.RequestHandler):    #添加一个处理get请求方式的方法    def get(self,input):        #向响应中，添加数据         #提取传入参数的转换        data_list = str(input).split("=_=")        #data_list=["i go to work by bus", "hello world", "go to school","by car","go to school byebye good morning","the apple in the box"]        returnItem = {}        returnItem["getPhrase"] = getScopeOfApplication(data_list)        returnItem["getPhraseWithoutPre"] = getProductCharacteristics(data_list)        self.write(json.dumps(returnItem))def getScopeOfApplication(data_list):    if len(data_list)==0:        return []    text = data_list[1]    for i in data_list[2:]:        text += ',' + i    grammar = r"""        NP:        {
     
      ?
      
       *
       
        +}        {
        
         +}                    PP: {
         
          
           } """ label = 'PP' phrase_list = phrases_extractor.get_phrases(text, grammar, label) result_list = [] for phrase in phrase_list: if phrase not in result_list and len(phrase.split(' ')) > 2: result_list.append(phrase) if len(result_list) < 1: result_list = getProductCharacteristics(data_list) return result_listdef getProductCharacteristics(data_list): if len(data_list)==0: return [] cur_title = data_list[0] other_titles = data_list[1] for i in data_list[2:]: other_titles += ',' + i grammar = r""" NP: {
          
         
        
       
      
     
     
      ?
      
       *
       
        +}            """    label = 'NP'    phrase_list = phrases_extractor.get_phrases(cur_title, grammar, label)    cur_list = list(set(phrase_list))    other_phrase_list = phrases_extractor.get_phrases(other_titles, grammar, label)    result_list = []    for phrase in cur_list:        if phrase in other_phrase_list:            result_list.append(phrase)    return result_list#定义接口的参数获取app = tornado.web.Application(handlers=[(r"/getwords/(.*?)$", IndexHandler)])#主函数执行if __name__ == "__main__":    tornado.options.parse_command_line()    http_server = tornado.httpserver.HTTPServer(app, max_buffer_size=504857600, max_body_size=504857600)    # http_server.listen(options.port)    http_server.bind(options.port)    #开启五个线程    http_server.start(5)    tornado.ioloop.IOLoop.instance().start()
       
      
     

 

然后python 程序.py 将服务开启，挂到服务器上进行执行

然后我们在浏览器中 输入      例如 

 

然后我们可以看到

 

 

很简单的写好一个接口，完美！