Python爬取京东双十一商品可视化价格曲线示例代码

    sku_detail_url = 'http://item.jd.com/{}.html'
      sku_price_url = 'https://p.3.cn/prices/get?type=1&skuid=J_{}'
    
      r = requests.get(sku_detail_url.format(skuId)).content
    
      soup = BeautifulSoup(r, 'html.parser', from_encoding='utf-8')
      sku_name_div = soup.find('div', class_="sku-name")
    
      if not sku_name_div:
    print('您输入的商品ID有误！')
    return
      else:
    sku_name = sku_name_div.text.strip()
    
      r = requests.get(sku_price_url.format(skuId))
      price = json.loads(r.text)[0]['p']
    
      data = {
    'sku_id': skuId,
    'sku_name': sku_name,
    'price': price
      }
      return data

    # 新增
    def insert(data):
      conn = sqlite3.connect('price.db')
      c = conn.cursor()
      sql = 'INSERT INTO price (sku_id,sku_name,price) VALUES ("{}", "{}", "{}")'.format(data.get("sku_id"), data.get("sku_name"), data.get('price') )
      c.execute(sql)
      conn.commit()
      conn.close()
    
    # 查询
    def select(sku_id):
      conn = sqlite3.connect('price.db')
      c = conn.cursor()
      sql = 'select sku_id, sku_name, price, time from price where sku_id = "{}" order by time asc'.format(sku_id)
      cursor = c.execute(sql)
    
      datas = []
      for row in cursor:
    data = {
      'sku_id': row[0],
      'sku_name': row[1],
      'price': row[2],
      'time': row[3]
    }
    datas.append(data)
      conn.close()
    
      return datas

    pip install schedule
    def run_price_job(skuId):
    
      # 使用不占主线程的方式启动 计划任务
      def run_continuously(interval=1):
    cease_continuous_run = threading.Event()
    
    class ScheduleThread(threading.Thread):
      @classmethod
      def run(cls):
        while not cease_continuous_run.is_set():
          schedule.run_pending()
          time.sleep(interval)
    
    continuous_thread = ScheduleThread()
    continuous_thread.start()
    return cease_continuous_run
      
      # 每天10点运行，get_jd_price：任务方法，skuId：任务方法的参数
      schedule.every().day.at("10:00").do(get_jd_price, skuId=skuId)
      run_continuously()

    datas = select(skuId)
    
    def line(datas):
      x_data = []
      y_data = []
      for data in datas:
    x_data.append(data.get('time'))
    y_data.append(data.get('price'))
    
      (
    Line()
    .add_xaxis(x_data)
    .add_yaxis(datas[0].get('sku_name'), y_data, is_connect_nones=True)
    .render("商品历史价格.html")
      )