+app.json_encoder = JSONEncoder
+app.config['SQLALCHEMY_DATABASE_URI'] = get_sqlalchemy_database_uri(config)
+app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
+db = SQLAlchemy(app)
+db.reflect(app=app)
+
+
+class Sensors(db.Model):
+ __tablename__ = 'sensors'
+
+
+def select_sensordata(sensor_id, sensor_type, begin, end, mode):
+ query = Sensors.query
+ if sensor_id is not None:
+ query = query.filter(Sensors.sensor_id == sensor_id)
+ if sensor_type is not None:
+ query = query.filter(Sensors.value_type == sensor_type)
+ if begin is not None:
+ query = query.filter(Sensors.timestamp >= begin)
+ if end is not None:
+ query = query.filter(Sensors.timestamp <= end)
+ if mode == 'consolidated' and begin is None and end is 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 mean(temperature) from sensors where ... group by mod(timestamp, resolution)
+ # func.avg(...)
+ #
+ # from https://stackoverflow.com/questions/4342370/grouping-into-interval-of-5-minutes-within-a-time-range
+ # SELECT
+ # timestamp, -- not sure about that
+ # name,
+ # count(b.name)
+ # FROM time a, id
+ # WHERE …
+ # GROUP BY
+ # UNIX_TIMESTAMP(timestamp) DIV 300, name
+ return query.all()
+
+
+def convert_to_c3(result):
+ c3result = defaultdict(list)
+ for row in result:
+ c3result[row.sensor_id].append(row.value)
+ dt = row.timestamp.strftime('%Y-%m-%d %H:%M:%S')
+ c3result[row.sensor_id + '_x'].append(dt)
+ return c3result
+
+
+def sensordata(sensor_id=None, sensor_type=None):
+ begin = request.args.get('begin', None, parse_datetime)
+ end = request.args.get('end', None, parse_datetime)
+ mode = request.args.get('mode', 'full')
+ format = request.args.get('format', 'default')
+
+ result = select_sensordata(sensor_id, sensor_type, begin, end, mode)
+
+ if format == 'c3':
+ return convert_to_c3(result)
+ return result
+
+
+def currentairtemperature(apikey, cityid):
+ """Retruns the tuple temperature, datetime (as float, datetime) in case of success, otherwise None, None."""
+ try:
+ url, weatherdata = openweathermap_json(apikey, cityid)
+ return weatherdata['main']['temp'], datetime.datetime.fromtimestamp(weatherdata['dt'])
+ except OpenWeatherMapError:
+ return None, None
+
+
+def currentwatertemperature(sensorid):
+ result = Sensors.query.filter_by(sensor_id=sensorid).order_by(Sensors.timestamp.desc()).first()
+ return result.value, result.timestamp
+
+
+@app.route('/api/<version>/sensors/')
+def sensors(version):
+ """List all sensors found in the database"""
+ result = db.session.query(Sensors.sensor_id, Sensors.sensor_name, Sensors.value_type).distinct().all()
+ return jsonify(result)
+
+
+@app.route('/api/<version>/sensor/id/<sensor_id>')
+def sensorid(version, sensor_id):
+ """Return all data for a specific sensor
+
+ URL parameters:
+ 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 = sensordata(sensor_id=sensor_id)
+ return jsonify(result)
+
+
+@app.route('/api/<version>/sensor/type/<sensor_type>')
+def sensortype(version, sensor_type):
+ """Return all data for a specific sensor type
+
+ URL parameters:
+ 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 = sensordata(sensor_type=sensor_type)
+ return jsonify(result)
+
+
+@app.route('/data/', defaults={'timespan': 1})
+@app.route("/data/<int:timespan>", methods=['GET'])
+def data(timespan):
+ granularity = 5 * timespan # (every) minute(s) per day
+ samples = 60/granularity * 24 * timespan # per hour over whole timespan
+ s4m = []
+ s4m_x = []
+ s5m = []
+ s5m_x = []
+ end = time.time()
+ start = end - samples * granularity * 60
+
+ for i in range(int(samples)):
+ s4m.append(uniform(-10,30))
+ s5m.append(uniform(-10,30))
+ s4mt = uniform(start, end)
+ s5mt = uniform(start, end)
+ s4m_x.append(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(s4mt)))
+ s5m_x.append(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(s5mt)))
ToastFreeware / chrisu / seepark.git / blobdiff