Python Dash SQLAlchemy

I am using Microsoft SQL Server and SQLAlchemy

I have a callback in dash app that connects to SQL DB but it does not close the SPID connections in my activity monitor in SQL Server. So it will just accumlate a ton of connections. It works locally, where I see the connection open and then close a few seconds later but it does not in production. I have it deployed on Azure App Services. Any idea why?

@app.callback(ServersideOutput(“store”, “data”),
Input(component_id=‘my_interval’, component_property=‘n_intervals’))

def query(n_interval):
try:
if n_interval > 0 :

        SERVER = 'DEVSQL'
        DATABASE = 'mydb'
        USERNAME = 'user'
        PASSWORD = 'password'
        DATA_CONNECTION = f"mssql+pyodbc://{USERNAME}:{PASSWORD}@{SERVER}/{DATABASE}?driver=ODBC+Driver+17+for+SQL+Server"
        engine = create_engine(DATA_CONNECTION)
        pyodbc.pooling = False

        with engine.connect() as connection:

            chosen_date_instance = pd.read_sql_query('''
                                    SELECT *
                                    FROM inspector.AUDIT_CHECK_INSTANCE
                                    ORDER BY RUN_DT DESC
                                    ''', connection)

            chosen_date_instance.to_csv('././datasets/audit_check_instance_data.csv')

           
            audit_item_instance = pd.read_sql_query('''
                                    SELECT *
                                    FROM inspector.audit_item
                                ''', connection)

            audit_item_instance.to_csv('././datasets/audit_item_instance.csv')

           

            audit_checklet_instance = pd.read_sql_query('''
                                    SELECT *
                                    FROM inspector.audit_checklet_instance
                                ''', connection)

            audit_checklet_instance.to_csv('././datasets/audit_checklet_instance.csv')

   
           connection.close()

        engine.dispose()

        stored_df = chosen_date_instance.copy()

        return stored_df.to_dict('records')

finally:

        pass

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