Python爬虫实例之淘宝商品页面爬取（api接口）

可以使用Python中的requests和BeautifulSoup库来进行网页爬取和数据提取。以下是一个简单的示例：
import requests
from bs4 import BeautifulSoupdef get_product_data(url):# 发送GET请求，获取网页内容headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0;Win64) AppleWebkit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3',}response = requests.get(url, headers=headers)if response.status_code == 200:# 使用BeautifulSoup解析网页内容soup = BeautifulSoup(response.text, 'html.parser')# 获取商品标题title = soup.select('.tb-main-title')[0].get_text().strip()# 获取商品价格price = soup.select('.tm-price')[0].get_text().strip()# 获取商品销量sales = soup.select('.tm-ind-panel .tm-count')[0].get_text().strip()# 返回提取的商品数据return {'title': title,'price': price,'sales': sales}else:print("请求失败！")if __name__ == '__main__':# 测试爬取商品数据product_url = 'https://item.taobao.com/item.htm?spm=a230r.1.14.9.183b70b2UDwRMA&id=636877355813'data = get_product_data(product_url)print(data)

在代码中，我们首先定义了一个get_product_data()函数，该函数接受一个淘宝商品的URL作为参数。然后，我们发送GET请求获取网页内容，并使用BeautifulSoup库解析网页。

我们通过CSS选择器定位DOM元素，提取商品的标题、价格和销量等数据，并将其存储在一个字典中。最后，我们打印出提取的商品数据。

请注意，为了模拟正常浏览器的请求，我们在请求头中添加了User-Agent。这是为了防止被网站屏蔽或拒绝访问。

在实际应用中，你可以根据需要进行数据的进一步处理和存储，例如存储到数据库或导出为CSV文件。

以下是api封装好的展示示例

 返回数据：

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