Problems making feature store

I am new to Hopsworks & I’m making the air quality prediction project. I even took some reference from the GitHub airquality example but I have some doubts.

I want feature store to contain:

  • Historical data (all cleaned and preprocessed data as CSV -has 4 columns; date, temp, humidity, and pm 2.5)
  • Current data (My API that works every day at 0900 GMT to extract last 2 days data, of temp and humidity)
  • And we predict AQI for the next say 3 days and show it on streamlit UI.
  • Next day, this observation moves to historical data, and the new data comes at 0900 GMT again and the process repeats.

I created feature group as follows:

df = pd.read_csv("data.csv")

def convert_date_to_unix(x):
    dt_obj = datetime.datetime.strptime(str(x), '%Y-%m-%d')
    dt_obj = int(dt_obj.timestamp() * 1000)
    return dt_obj =

import hopsworks
project = hopsworks.login()
fs = project.get_feature_store()
aqi_fg = fs.get_or_create_feature_group(
    description="AQI dataset",
    online_enabled = True

Now how do I do the second step of live data every day? And how do I transfer it to historical data every day so a new observation can come in live data?

I’m really confused. Appreciate the help. Thank you!