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Python下载商品数据并连接数据库且保存数据的示例分析

发表于:2024-12-12 作者:千家信息网编辑
千家信息网最后更新 2024年12月12日,这篇文章主要介绍了Python下载商品数据并连接数据库且保存数据的示例分析,具有一定借鉴价值,感兴趣的朋友可以参考下,希望大家阅读完这篇文章之后大有收获,下面让小编带着大家一起了解一下。前言:开发环境
千家信息网最后更新 2024年12月12日Python下载商品数据并连接数据库且保存数据的示例分析

这篇文章主要介绍了Python下载商品数据并连接数据库且保存数据的示例分析,具有一定借鉴价值,感兴趣的朋友可以参考下,希望大家阅读完这篇文章之后大有收获,下面让小编带着大家一起了解一下。

前言:

开发环境:

  • python 3.8

  • pycharm 2021.2 专业版

代码实现:

  • 发送请求

  • 获取数据

  • 解析数据(筛选数据)

  • 保存数据

  • 连接数据库

请求数据

# 伪装headers = {    'cookie': 'miid=4137864361077413341; tracknick=%5Cu5218%5Cu6587%5Cu9F9978083283; thw=cn; hng=CN%7Czh-CN%7CCNY%7C156; cna=MNI4GicXYTQCAa8APqlAWWiS; enc=%2FWC5TlhZCGfEq7Zm4Y7wyNToESfZVxhucOmHkanuKyUkH1YNHBFXacrDRNdCFeeY9y5ztSufV535NI0AkjeX4g%3D%3D; t=ad15767ffa6febb4d2a8709edebf63d3; lgc=%5Cu5218%5Cu6587%5Cu9F9978083283; sgcookie=E100EcWpAN49d4Uc3MkldEc205AxRTa81RfV4IC8X8yOM08mjVtdhtulkYwYybKSRnCaLHGsk1mJ6lMa1TO3vTFmr7MTW3mHm92jAsN%2BOA528auARfjf2rnOV%2Bx25dm%2BYC6l; uc3=nk2=ogczBg70hCZ6AbZiWjM%3D&vt3=F8dCvCogB1%2F5Sh2kqHY%3D&lg2=Vq8l%2BKCLz3%2F65A%3D%3D&id2=UNGWOjVj4Vjzwg%3D%3D; uc4=nk4=0%40oAWoex2a2MA2%2F2I%2FjFnivZpTtTp%2F2YKSTg%3D%3D&id4=0%40UgbuMZOge7ar3lxd0xayM%2BsqyxOW; _cc_=W5iHLLyFfA%3D%3D; _m_h6_tk=ac589fc01c86be5353b640607e791528_1647451667088; _m_h6_tk_enc=7d452e4e140345814d5748c3e31fc355; xlly_s=1; x5sec=7b227365617263686170703b32223a223264393234316334363365353038663531353163633366363036346635356431434c61583635454745506163324f2f6b2b2b4b6166686f4d4d7a45774e7a4d794d6a59324e4473784d4b6546677037382f2f2f2f2f77453d227d; JSESSIONID=1F7E942AC30122D1C7DBA22C429521B9; tfstk=cKKGBRTY1F71aDbHPcs6LYjFVa0dZV2F6iSeY3hEAYkCuZxFizaUz1sbK1hS_r1..; l=eBEVp-O4gnqzSzLbBOfwnurza77OIIRAguPzaNbMiOCPO75p5zbNW60wl4L9CnGVhsTMR3lRBzU9BeYBqo44n5U62j-la1Hmn; isg=BDw8SnVxcvXZcEU4ugf-vTadDdruNeBfG0WXdBa9WicK4dxrPkd97hHTxQmZqRi3',    'referer': 'https://s.taobao.com/search?q=%E4%B8%9D%E8%A2%9C&imgfile=&js=1&stats_click=search_radio_all%3A1&initiative_id=staobaoz_20220323&ie=utf8&bcoffset=1&ntoffset=1&p4ppushleft=2%2C48&s=',    'sec-ch-ua': '" Not A;Brand";v="99", "Chromium";v="99", "Google Chrome";v="99"',    'sec-ch-ua-mobile': '?0',    'sec-ch-ua-platform': '"Windows"',    'sec-fetch-dest': 'document',    'sec-fetch-mode': 'navigate',    'sec-fetch-site': 'same-origin',    'sec-fetch-user': '?1',    'upgrade-insecure-requests': '1',    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.82 Safari/537.36',}url = f'https://s.TB.com/search?q=%E4%B8%9D%E8%A2%9C&imgfile=&js=1&stats_click=search_radio_all%3A1&initiative_id=staobaoz_20220323&ie=utf8&bcoffset=1&ntoffset=1&p4ppushleft=2%2C48&s={44*page}'response = requests.get(url=url, headers=headers)

获取数据

html_data = response.text

解析数据(筛选数据)

json_str = re.findall('g_page_config = (.*);', html_data)[0]# 字符串 肯定不能用 字典方式键值对取值# json_str: 字符串# 类型转变: 转成字典类型 才能通过键值对方式去取值json_dict = json.loads(json_str)auctions = json_dict['mods']['itemlist']['data']['auctions']for auction in auctions:    raw_title = auction['raw_title']    pic_url = auction['pic_url']    detail_url = auction['detail_url']    view_price = auction['view_price']    item_loc = auction['item_loc']    view_sales = auction['view_sales']    nick = auction['nick']    print(raw_title, pic_url, detail_url, view_price, item_loc, view_sales, nick)

保存数据

with open('TB.csv', mode='a', encoding='utf-8', newline='') as f:    csv_writer =csv.writer(f)    csv_writer.writerow([raw_title, pic_url, detail_url, view_price, item_loc, view_sales, nick])

连接数据库

import pymysqldef save_sql(title, pic_url, detail_url, view_price, item_loc, view_sales, nick):    count = pymysql.connect(        host='xxx.xxx.xxx.xxx',  # 数据库地址        port=3306,  # 数据库端口        user='xxxx',  # 数据库账号        password='xxxx',  # 数据库密码        db='xxxx'  # 数据库表名    )    # 创建数据库对象    db = count.cursor()    # 写入sql    sql = f"insert into goods(title, pic_url, detail_url, view_price, item_loc, view_sales, nick) values ('{title}', '{pic_url}', '{detail_url}', {view_price}, '{item_loc}', '{view_sales}', '{nick}')"    # 执行sql    db.execute(sql)    # 保存修改内容    count.commit()    db.close()

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