# Let the database do the grouping. Example in SQL (MySQL):
# select to_seconds(datetime) DIV (60*60*24) as interval_id, min(datetime), max(datetime), min(temp), avg(temp), max(temp), count(temp) from openweathermap group by interval_id order by interval_id;
query = db.session.query(func.to_seconds(Sensors.timestamp).op('div')(resolution).label('g'),
- func.min(Sensors.timestamp).label('timestamp'),
+ func.from_unixtime(func.avg(func.unix_timestamp(Sensors.timestamp))).label('timestamp'),
func.avg(Sensors.value).label('value'),
Sensors.sensor_id, Sensors.value_type, Sensors.sensor_name)
if sensor_id is not None:
# Let the database do the grouping. Example in SQL (MySQL):
# select to_seconds(datetime) DIV (60*60*24) as interval_id, min(datetime), max(datetime), min(temp), avg(temp), max(temp), count(temp) from openweathermap group by interval_id order by interval_id;
query = db.session.query(func.to_seconds(OpenWeatherMap.datetime).op('div')(resolution).label('g'),
- func.min(OpenWeatherMap.datetime).label('datetime'),
+ func.from_unixtime(func.avg(func.unix_timestamp(OpenWeatherMap.datetime))).label('datetime'),
func.avg(OpenWeatherMap.temp).label('temp'),
OpenWeatherMap.cityid)
OpenWeatherMap.query.filter(OpenWeatherMap.cityid == cityid)