万朱浩 / Venue-Ops

…ch significantly improves the modeling fitness.

In the original method, only linear regression is used to perform simple trend extrapolation, which leads to insufficient prediction accuracy. This optimization adopts time series model, and uses the auto_arima method of pmdarima to automatically select appropriate model parameters (including p, d, q and seasonal parameters) according to historical data. It significantly improves the suitability of the model in time series modeling. In this way, the model can better capture the trend and periodicity of the data, and predict the future heat more reasonable and accurate.

Update app.py

1,中间件代码逻辑可以优化，以减少重复的 return 语句，并提高可读性
2,为了更好地调试和监控，建议为应用添加日志记录，捕获用户请求和错误