这篇文章给大家分享的是有关Python如何实现批量采集商品数据的内容。小编觉得挺实用的，因此分享给大家做个参考，一起跟随小编过来看看吧。
本次目的
python批量采集某商品数据
知识点
requests 发送请求
re 解析网页数据
json 类型数据提取
csv 表格数据保存
开发环境
python 3.8
pycharm
requests
代码
导入模块
import jsonimport randomimport timeimport csvimport requestsimport reimport pymysql核心代码
# 连接数据库def 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()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',}with open('淘宝.csv', mode='a', encoding='utf-8', newline='') as f: csv_writer = csv.writer(f) csv_writer.writerow(['title', 'pic_url', 'detail_url', 'view_price', 'item_loc', 'view_sales', 'nick'])for page in range(1, 101): url = f'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={44*page}' response = requests.get(url=url, headers=headers) json_str = re.findall('g_page_config = (.*);', response.text)[0] json_data = json.loads(json_str) auctions = json_data['mods']['itemlist']['data']['auctions'] for auction in auctions: try: 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(title, pic_url, detail_url, view_price, item_loc, view_sales, nick) save_sql(title, pic_url, detail_url, view_price, item_loc, view_sales, nick) with open('淘宝.csv', mode='a', encoding='utf-8', newline='') as f: csv_writer = csv.writer(f) csv_writer.writerow([title, pic_url, detail_url, view_price, item_loc, view_sales, nick]) except: pass time.sleep(random.randint(3, 5))感谢各位的阅读！关于“Python如何实现批量采集商品数据”这篇文章就分享到这里了，希望以上内容可以对大家有一定的帮助，让大家可以学到更多知识，如果觉得文章不错，可以把它分享出去让更多的人看到吧！
