# TODO: filter out samples from 'result'
# like loop over results and skip if timestamp(n+1)-timestamp(n)<resolution
+ format = request.args.get('format', 'default')
+ if format == 'c3':
+ c3result = dict()
+ for row in result:
+ if not row['sensor_id'] in c3result:
+ c3result[row['sensor_id']] = list()
+ c3result[row['sensor_id']].append(row['value'])
+ if not row['sensor_id'] + '_x' in c3result:
+ c3result[row['sensor_id'] + '_x'] = list()
+ dt = row['timestamp'].strftime('%Y-%m-%d %H:%M:%S')
+ c3result[row['sensor_id'] + '_x'].append(dt)
+ result = c3result
return result
begin=<datetime>, optional, format like "2018-05-19T21:07:53"
end=<datetime>, optional, format like "2018-05-19T21:07:53"
mode=<full|consolidated>, optional. return all rows (default) or with lower resolution (for charts)
+ format=<default|c3>, optional. return result as returned by sqlalchemy (default) or formatted for c3.js
"""
result = select_sensordata('sensor_id=%s', sensor_id)
return jsonify(result)
begin=<datetime>, optional, format like "2018-05-19T21:07:53"
end=<datetime>, optional, format like "2018-05-19T21:07:53"
mode=<full|consolidated>, optional. return all rows (default) or with lower resolution (for charts)
+ format=<default|c3>, optional. return result as returned by sqlalchemy (default) or formatted for c3.js
"""
result = select_sensordata('value_type=%s', sensor_type)
return jsonify(result)