return query.all()
-def select_sensordata_grouped(sensor_id, sensor_type, begin, end):
- # determine resolution (interval in seconds for data points)
+def calc_grouping_resolution(begin, end):
+ """How many data points should be between the timestamps begin and end?"""
# copied from munin/master/_bin/munin-cgi-graph.in
resolutions = dict(
day = 300,
resolution = resolutions['month']
else:
resolution = resolutions['year']
+ return resolution
+
+
+def select_sensordata_grouped(sensor_id, sensor_type, begin, end):
+ # determine resolution (interval in seconds for data points)
+ resolution = calc_grouping_resolution(begin, end)
# 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;
return query.all()
-def select_openweatherdata(cityid, begin, end, mode):
+def select_openweatherdata(cityid, begin, end):
query = OpenWeatherMap.query.filter(OpenWeatherMap.cityid == cityid)
if begin is not None:
query = query.filter(OpenWeatherMap.datetime >= begin)
if end is not None:
query = query.filter(OpenWeatherMap.datetime <= end)
- if mode == 'consolidated' and begin is not None and end is not None:
- # copied from munin/master/_bin/munin-cgi-graph.in
- # interval in seconds for data points
- resolutions = dict(
- day = 300,
- week = 1800,
- month = 7200,
- year = 86400,
- )
- duration = (end - begin).total_seconds()
- day = 60 * 60 * 24
- if duration < day:
- resolution = resolutions['day']
- elif duration < 7 * day:
- resolution = resolutions['week']
- elif duration < 31 * day:
- resolution = resolutions['month']
- else:
- resolution = resolutions['year']
- # TODO: filter out samples from 'result'
- # something like
- # 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;
+ return query.all()
+
+
+def select_openweatherdata_grouped(cityid, begin, end):
+ # determine resolution (interval in seconds for data points)
+ resolution = calc_grouping_resolution(begin, end)
+
+ # 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.avg(OpenWeatherMap.temp).label('temp'),
+ OpenWeatherMap.cityid)
+ OpenWeatherMap.query.filter(OpenWeatherMap.cityid == cityid)
+ query = query.filter(Sensors.timestamp >= begin)
+ query = query.filter(Sensors.timestamp <= end)
+ query = query.group_by('g', OpenWeatherMap.cityid)
return query.all()
mode = request.args.get('mode', 'full')
format = request.args.get('format', 'default')
- result = select_openweatherdata(cityid, begin, end, mode)
+ if mode == 'full':
+ result = select_openweatherdata(cityid, begin, end)
+ elif mode == 'consolidated':
+ if begin is None or end is None:
+ abort(Response('begin and end have to be set for mode==consolidated', 400))
+ result = select_openweatherdata_grouped(cityid, begin, end)
+ else:
+ abort(Response('unknown value for mode', 400))
if format == 'c3':
return convert_to_c3(result, 'cityid', 'datetime', 'temp')