python - Elasticsearch查询未返回正确的响应

Question

我写了一个用于 flex 搜索的代码，其中我将movie_name命名为search_term，但是当它根据jaro winkler条件(即

for i in es_data:
      if (i['_source']['entity_type'] == 'movie_entity'):
          dist = distance.get_jaro_distance(search_term, i['_source']['entity_name'], winkler=True, scaling=0.1)

      if dist > 0.80:

这段代码返回了正确的输出，但是当没有匹配项时，我得到一个错误。我尝试了其他语句，但错误仍在发生。
谁能帮我解决这个问题？

from..items import DeccanchronicleItem

import mysql.connector
from mysql.connector import Error
from mysql.connector import errorcode
from elasticsearch import Elasticsearch, RequestsHttpConnection
from requests_aws4auth import AWS4Auth
import boto3
import spacy 
import fuzzy
from pyjarowinkler import distance
import json
import scrapy
import re

class DeccanchronicleSpider(scrapy.Spider):
    name = 'a_review'
    page_number = 2
    start_urls = ['https://www.deccanchronicle.com/entertainment/movie-review?pg=1'
    ]


    def parse(self, response):
        items = {}
        i = 1
        

        movie_title = response.xpath('//*[@id="fullBody"]/div[4]/div[3]/div[1]/div[*]/div[2]/a/h3/text()').getall()
        movie_text = response.xpath('//*[@id="fullBody"]/div[4]/div[3]/div[1]/div[*]/div[2]/a/div[1]/text()').getall()
        movie_id = response.xpath('//*[@id="fullBody"]/div[4]/div[3]/div[1]/div[*]/div[2]/a/@href').getall()

        items['movie_title'] = movie_title
        items['movie_text'] = movie_text
        items['movie_id'] = movie_id


        li = items['movie_title']
        for i in range(len(li)):
            li_split =  li[i].split(" ")
            #print(movietitle)
            if 'Review:' in li_split or 'review:' in li_split:
                outputs = DeccanchronicleItem()
                outputs['page_title'] = li[i]
                outputs['review_content'] = items['movie_text'][i]
                outputs['review_link'] = 'https://www.deccanchronicle.com' + str(items['movie_id'][i])
                    
                nlp = spacy.load('/Users/divyanshu/review_bot/review_bot/NER_model') 

                def actor_mid_ner(sentence):
                    doc = nlp(sentence)
                    detected_hash = {}
                    # detected_hash = { ent.label_ : ([ent.text] if ent.label_ is None else )   for ent in doc.ents}
                    for ent in doc.ents:
                        label =  ent.label_
                        detected = detected_hash.keys()
                        omit = ['Unwanted']
                        if label not in omit:
                            if label not in detected:
                                detected_hash[label] = [ent.text] 
                            else:
                                detected_hash[label].append(ent.text)
                        else:
                            detected_hash[label] = [ent.text]
                    return detected_hash, detected

                sentence = outputs['page_title']
                ner_hash, ner_keys = actor_mid_ner(sentence)


                movie_name = " ".join(str(x) for x in ner_hash['MOVIE'] )
                print('-----------------------------------')
                print(movie_name)
                print('-----------------------------------')


                def elasticsearch(movie_name):

                    search_term =  movie_name
                    host = 'xxxxxxxxxxxxxxx' # For example, my-test-domain.us-east-1.es.amazonaws.com
                    region = 'ap-southeast-1' # e.g. us-west-1

                    service = 'es'
                    credentials = boto3.Session().get_credentials()
                    awsauth = AWS4Auth(credentials.access_key, credentials.secret_key, region, service, session_token=credentials.token)

                    es = Elasticsearch(
                    hosts = [{'host': host, 'port': 443}],
                        http_auth = awsauth,
                        use_ssl = True,
                        verify_certs = True,
                        connection_class = RequestsHttpConnection
                    )

                    body = {
                            "query": {
                                    "multi_match" : {
                                            "query": search_term,
                                            "fields": ["entity_name", "aka"],
                                            "fuzziness": "AUTO"
                                                    }
                                    }
                            }

                                        
                    res = es.search(index="production-widget_id_search", body=body)
                    es_data = res['hits']['hits']
                    # print(es_data)
                    for i in es_data:
                            if (i['_source']['entity_type'] == 'movie_entity'):
                                    dist = distance.get_jaro_distance(search_term, i['_source']['entity_name'], winkler=True, scaling=0.1)
                                    if dist > 0.80:
                                        return (i['_source']['entity_id'], i['_source']['entity_name'])

                movie_id , movie_name_es  = elasticsearch(movie_name)
                review_url = outputs['review_link']
                print('-----------------------------------')
                print(movie_id)
                print('-----------------------------------')
                print(movie_name)
                print('-----------------------------------')
                print(movie_name_es)
                print('-----------------------------------')
                print(review_url)
                print('***********************************')

                try:
                    connection = mysql.connector.connect(host='localhost',
                                                        database='review_url',
                                                        user='root',
                                                        password='admin')
                    mySql_insert_query = """INSERT INTO k_master_movie_reviews (id, title, title_es, url) 
                                        VALUES(%s,%s,%s,%s)""",(movie_id, movie_name, movie_name_es, review_url )

                    cursor = connection.cursor()
                    cursor.execute(mySql_insert_query)
                    connection.commit()
                    print(cursor.rowcount, "Record inserted successfully into table")
                    cursor.close()

                except mysql.connector.Error as error:
                    print("Failed to insert record into table {}".format(error))

                finally:
                    if (connection.is_connected()):
                        connection.close()
                        print("MySQL connection is closed")



                outputs['id'] = movie_id
                outputs['title'] = movie_name
                outputs['title_es'] = movie_name_es
                outputs['url'] = review_url
                yield outputs
                

                
        pass

        next_page = 'https://www.deccanchronicle.com/entertainment/movie-review?pg=' + str(DeccanchronicleSpider.page_number) 
        if DeccanchronicleSpider.page_number <= 5:
           DeccanchronicleSpider.page_number += 1  
           yield response.follow(next_page, callback = self.parse)

这是我得到的错误

Traceback (most recent call last):
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/utils/defer.py", line 117, in iter_errback
    yield next(it)
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/utils/python.py", line 345, in __next__
    return next(self.data)
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/utils/python.py", line 345, in __next__
    return next(self.data)
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/core/spidermw.py", line 64, in _evaluate_iterable
    for r in iterable:
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/spidermiddlewares/offsite.py", line 29, in process_spider_output
    for x in result:
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/core/spidermw.py", line 64, in _evaluate_iterable
    for r in iterable:
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/spidermiddlewares/referer.py", line 338, in <genexpr>
    return (_set_referer(r) for r in result or ())
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/core/spidermw.py", line 64, in _evaluate_iterable
    for r in iterable:
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/spidermiddlewares/urllength.py", line 37, in <genexpr>
    return (r for r in result or () if _filter(r))
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/core/spidermw.py", line 64, in _evaluate_iterable
    for r in iterable:
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/spidermiddlewares/depth.py", line 58, in <genexpr>
    return (r for r in result or () if _filter(r))
  File "/Users/divyanshu/env/lib/python3.7/site-packages/scrapy/core/spidermw.py", line 64, in _evaluate_iterable
    for r in iterable:
  File "/Users/divyanshu/review_bot/review_bot/spiders/a.py", line 515, in parse
    movie_id , movie_name_es  = elasticsearch(movie_name)
TypeError: cannot unpack non-iterable NoneType object

Answer 1

这是因为在没有匹配项时，您的elasticsearch()函数将返回None，然后您立即将其解压缩为movie_id和movie_name_es。我建议在return (None, None)函数的末尾添加elasticsearch()。