Python 制作查询商品历史价格的小工具

def get_jd_price(skuId):

  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")
  )