python爬取京东小爱音响评论

import requests
from bs4 import BeautifulSoup as bs
import re
import pandas as pd
from sqlalchemy import create_engine
from pandas.io.sql import to_sql as pd_sql
import pymysql
import random
import time


# 定义pandas存入mysql函数
def pandas_to_mysql(df_data, table_name, **kwargs):
    engine = create_engine(‘mysql+pymysql://{}:{}@{}:{}/{}?charset={}‘.format(kwargs[‘user‘],kwargs[‘password‘],kwargs[‘host‘],kwargs[‘port‘],kwargs[‘db‘],kwargs[‘charset‘]))
    pd_sql(df_data, table_name, engine, index=False, if_exists=‘append‘, chunksize=10000)  # if_exists: ‘replace‘, ‘append‘
    engine.dispose()


db_local_hwdata = {‘user‘:‘root‘,
                    ‘password‘:‘8888‘,
                    ‘port‘: 3306, 
                    ‘host‘:‘localhost‘, 
                    ‘db‘: ‘hwdata‘, 
                    ‘charset‘: ‘utf8mb4‘}

# 设置代理池
proxies = {
            ‘http‘:‘http://120.83.110.65:9999‘, 
           ‘http‘:‘http://183.146.156.209:9999‘, 
           ‘http‘:‘http://123.169.34.94:9999‘,
           ‘http‘:‘http://117.57.90.141:9999‘,
           ‘http‘:‘http://117.69.201.19:9999‘,
           ‘http‘:‘http://117.95.192.240:9999‘,
           ‘http‘:‘http://117.95.192.240:9999‘,
           ‘http‘:‘http://163.204.244.161:9999‘,
           ‘http‘:‘http://163.204.246.168:9999‘,
           ‘http‘:‘http://171.35.160.62:9999‘,
           ‘http‘:‘http://36.22.77.186:9999‘,
           ‘http‘:‘http://120.83.107.184:9999‘,
          }

url = ‘https://sclub.jd.com/comment/productPageComments.action?callback=fetchJSON_comment98vv33766&productId=5239477&score=0&sortType=5&page=0&pageSize=10&isShadowSku=0&fold=1‘  # 商品链接
headers = {
    ‘Referer‘: ‘https://item.jd.com/5239477.html‘,
    ‘User-Agent‘: ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36‘}
result = requests.get(url, headers=headers, proxies=proxies)
result_text = result.text
result_text = result_text.replace(‘\\n‘, ‘‘)
comment_number = re.search(‘"commentCount":([\d]+),‘, result_text, re.S).group(1)  # 所有评论的数量，用于分页，每页评论数量为10

# 遍历，10个评论一页
for page_i in range(0, int(int(comment_number)/10)):
    time.sleep(random.uniform(0.6, 4))
    url = f‘https://sclub.jd.com/comment/productPageComments.action?callback=fetchJSON_comment98vv33766&productId=5239477&score=0&sortType=5&page={page_i}&pageSize=10&isShadowSku=0&fold=1‘
    result = requests.get(url, headers=headers, proxies=proxies)
    result_text = result.text
    result_text = result_text.replace(‘\\n‘, ‘‘)

    analyse_result = re.findall(‘"guid":"(.*?)",.*?"content":"(.*?)",.*?"creationTime":"(.*?)".*?"isDelete":(.*?),.*?"isTop":(.*?),.*?"replyCount":(.*?),.*?"score":(.*?),.*?"imageStatus":(.*?),.*?"usefulVoteCount":(.*?),.*?"userClient":(.*?),.*?"imageCount":(.*?),.*?"anonymousFlag":(.*?),.*?"plusAvailable":(.*?),.*?"productColor":"(.*?)".*?"imageIntegral".*?,(.*?)"status".*?,"referenceTime":"(.*?)".*?nickname":"(.*?)".*?"days":(.*?),.*?"afterDays":(.*?)}‘, result_text, re.S)
    final_data = []
    
    for rt in analyse_result:
        person_data = []
        for ch_i, character in enumerate(rt):
            if ch_i == 14 and (character != ‘‘):
                try:
                    character = re.search(‘"content":"(.*?)",‘, character, re.S).group(1)
                except:
                    character = ‘‘
            if ch_i == 18 and (int(character)])):
                character = ‘‘
            person_data.append(character)
        final_data.append(person_data)
    dfanalyse_result = pd.DataFrame(final_data, columns=[‘commentUrl‘, ‘comment‘, ‘commentTime‘, ‘isDelete‘, ‘isTop‘, ‘replyCount‘, ‘stars‘, ‘imageFlag‘, ‘voteCount‘, ‘userClient‘, ‘imageCount‘, ‘anonymousFlag‘, ‘plusFlag‘, ‘productCatergory‘, ‘afterComment‘, ‘purchaseTime‘, ‘userName‘, ‘commentAfterBuyingTime‘, ‘afterCommentAfterBuyingTime‘])  # 将数据转换为DataFrame格式
    pandas_to_mysql(dfanalyse_result, ‘w20191212jingdong_comments‘, **db_local_hwdata)  # 存入mysql
    print(f‘page_i{page_i} finished!‘)