前言
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作者:菜鸟级程序猿
代码实现
import requests from lxml import etree import time import random import pandas as pd import json from sqlalchemy import create_engine from sqlalchemy.dialects.oracle import DATE,FLOAT,NUMBER,VARCHAR2 import cx_Oracle
先导入需要用的包
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def create_table(table_name): conn = cx_Oracle.connect('user/password@IP:port/database') cursor = conn.cursor () create_shouji = ''' CREATE TABLE {}( 商品ID VARCHAR2(256), 价格 number(19,8), 店名 VARCHAR2(256) , 店属性 VARCHAR2(256) , 标题 VARCHAR2(256) , 评论 NUMBER(19), 优评论 NUMBER(19) ) '''.format(table_name) cursor.execute(create_shouji) cursor.close() conn.close()
建表
def mapping_df_types(df_pro): dtypedict = {} for i, j in zip(df_pro.columns, df_pro.dtypes): if "object" in str(j): dtypedict.update({i: VARCHAR2(256)}) if "float" in str(j): dtypedict.update({i: NUMBER(19,8)}) if "int" in str(j): dtypedict.update({i: NUMBER(19,8)}) if "datetime" in str(j): dtypedict.update({i: DATE}) return dtypedict
定义类型的映射
def sava_oracle(df_pro): engine = create_engine('oracle://user:password@ip:port/database') dtypedict = mapping_df_types(df_pro) df_pro.to_sql("shouji",con=engine,index=False,if_exists='append',dtype=dtypedict)
定义请求头和请求方法
headers={ 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.61 Safari/537.36 Edg/83.0.478.37' } def requesturl(url): session = requests.Session() rep = session.get(url,headers=headers) return rep
解析评论的url
def commreq(url_comm): dd_commt = pd.DataFrame(columns=['商品ID','评论','优评论']) session = requests.Session() rep_comm = session.get(url_comm,headers=headers) comment = json.loads(rep_comm.text)['CommentsCount'] comment_list = [] for i in comment: comment_list.append({'商品ID':str(i['ProductId']),'评论':i['CommentCount'],'优评论':i['GoodCount']}) dd_commt = dd_commt.append(comment_list) return dd_commt
主体解析
def parse(rep): df = pd.DataFrame(columns=['商品ID','价格','店名','店属性','标题']) html = etree.HTML(rep.text) all_pro = html.xpath("//ul[@class='gl-warp clearfix']/li") proid = ','.join(html.xpath("//li/@data-sku")) # 商品评价url # referenceIds=之后到&callback之前,都是商品的id,只需要在商品列表获取商品id拼接即可 # 1. 评论解析 url_comm = r'https://club.jd.com/comment/productCommentSummaries.action?referenceIds={}'.format(proid) dd_commt = commreq(url_comm) # 2. 商品列表信息解析 pro_list = [] for product in all_pro: proid = ''.join(product.xpath("@data-sku")) price = ''.join(product.xpath("div[@class='gl-i-wrap']//strong/i/text()")) target = ''.join(product.xpath("div[@class='gl-i-wrap']//a/em//text()")).replace(' ','').replace('\u2122','') shopname = ''.join(product.xpath("div[@class='gl-i-wrap']//span/a/@title")) shoptips = product.xpath("div[@class='gl-i-wrap']//i[contains(@class,'goods-icon')]/text()") if '自营' in shoptips: shoptips='自营' else: shoptips='非自营' pro_list.append(dict(商品ID=proid,价格=price,店名=shopname,店属性=shoptips,标题=target)) df = df.append(pro_list) # 3. 合并商品评论和列表 df_pro = pd.merge(df,dd_commt,on='商品ID') return df_pro
加入主程序
if __name__ == "__main__": create_table('shouji') for i in range(1,81): url = 'https://search.jd.com/s_new.php?keyword=手机&wq手机&ev=3613_104528%5E&page={0}&s=30'.format(i) rep = requesturl(url) df_pro = parse(rep) sava_oracle(df_pro) time.sleep(random.randrange(1,4)) print('完成:',i)