Today, I want to play with Grafana. To give a little more detail, let me explain my recent experience with Granfana. I’ve got a BeeWi temperature sensor. I’ve been playing with it, and I decided that I want to show the temperature on a Grafana dashboard. Along with that, I want to play with the OpenWeatherMap API.

First, I want to retrieve the temperature from the BeeWi device. I’ve got a node script that connects via Bluetooth to the device using the noble library. Therefore, I only need to pass the sensor mac address that I obtain using JSON with the current temperature.

#!/usr/bin/env node
noble = require('noble'); 
var status = false;
var address = process.argv[2];

if (!address) {
    console.log('Usage "./reader.py <sensor mac address>"');
    process.exit();
}

function hexToInt(hex) {
    var num, maxVal;
    if (hex.length % 2 !== 0) {
        hex = "0" + hex;
    }
    num = parseInt(hex, 16);
    maxVal = Math.pow(2, hex.length / 2 * 8);
    if (num > maxVal / 2 - 1) {
        num = num - maxVal;
    }

    return num;
}

noble.on('stateChange', function(state) {
    status = (state === 'poweredOn');
});

noble.on('discover', function(peripheral) {
    if (peripheral.address == address) {
        var data = peripheral.advertisement.manufacturerData.toString('hex');
        out = {
            temperature: parseFloat(hexToInt(data.substr(10, 2)+data.substr(8, 2))/10).toFixed(1)
        };
        console.log(JSON.stringify(out))
        noble.stopScanning();
        process.exit();
    }
});

noble.on('scanStop', function() {
    noble.stopScanning();
});

setTimeout(function() {
    noble.stopScanning();
    noble.startScanning();
}, 2000);


setTimeout(function() {
    noble.stopScanning();
    process.exit()
}, 20000);

And, finally, we need to use another script (this time Python) to collect data from the OpenWeatherMap API, collect data from the node script, and store the information in an InfluxDB database.

from sense_hat import SenseHat
from influxdb import InfluxDBClient
import datetime
import logging
import requests
import json
from subprocess import check_output
import os
import sys
from dotenv import load_dotenv

logging.basicConfig(level=logging.INFO)

current_dir = os.path.dirname(os.path.abspath(__file__))
load_dotenv(dotenv_path="{}/.env".format(current_dir))

sensor_mac_address = os.getenv("BEEWI_SENSOR")
openweathermap_api_key = os.getenv("OPENWEATHERMAP_API_KEY")
influxdb_host = os.getenv("INFLUXDB_HOST")
influxdb_port = os.getenv("INFLUXDB_PORT")
influxdb_database = os.getenv("INFLUXDB_DATABASE")

reader = '{}/reader.js'.format(current_dir)


def get_rain_level_from_weather(weather):
    rain = False
    rain_level = 0
    if len(weather) > 0:
        for w in weather:
            if w['icon'] == '09d':
                rain = True
                rain_level = 1
            elif w['icon'] == '10d':
                rain = True
                rain_level = 2
            elif w['icon'] == '11d':
                rain = True
                rain_level = 3
            elif w['icon'] == '13d':
                rain = True
                rain_level = 4

    return rain, rain_level


def openweathermap():
    data = {}
    r = requests.get(
        "http://api.openweathermap.org/data/2.5/weather?id=3110044&appid={}&units=metric".format(
            openweathermap_api_key))

    if r.status_code == 200:
        current_data = r.json()
        data['weather'] = current_data['main']
        rain, rain_level = get_rain_level_from_weather(current_data['weather'])
        data['weather']['rain'] = rain
        data['weather']['rain_level'] = rain_level

    r2 = requests.get(
        "http://api.openweathermap.org/data/2.5/uvi?lat=43.32&lon=-1.93&appid={}".format(openweathermap_api_key))
    if r2.status_code == 200:
        data['uvi'] = r2.json()

    r3 = requests.get(
        "http://api.openweathermap.org/data/2.5/forecast?id=3110044&appid={}&units=metric".format(
            openweathermap_api_key))

    if r3.status_code == 200:
        forecast = r3.json()['list']
        data['forecast'] = []
        for f in forecast:
            rain, rain_level = get_rain_level_from_weather(f['weather'])
            data['forecast'].append({
                "dt": f['dt'],
                "fields": {
                    "temp": float(f['main']['temp']),
                    "humidity": float(f['main']['humidity']),
                    "rain": rain,
                    "rain_level": int(rain_level),
                    "pressure": float(float(f['main']['pressure']))
                }
            })

        return data


def persists(measurement, fields, location, time):
    logging.info("{} {} [{}] {}".format(time, measurement, location, fields))
    influx_client.write_points([{
        "measurement": measurement,
        "tags": {"location": location},
        "time": time,
        "fields": fields
    }])


def in_sensors():
    try:
        sense = SenseHat()
        pressure = sense.get_pressure()
        reader_output = check_output([reader, sensor_mac_address]).strip()
        sensor_info = json.loads(reader_output)
        temperature = sensor_info['temperature']

        persists(measurement='home_pressure', fields={"value": float(pressure)}, location="in", time=current_time)
        persists(measurement='home_temperature', fields={"value": float(temperature)}, location="in",
                 time=current_time)
    except Exception as err:
        logging.error(err)


def out_sensors():
    try:
        out_info = openweathermap()

        persists(measurement='home_pressure',
                 fields={"value": float(out_info['weather']['pressure'])},
                 location="out",
                 time=current_time)
        persists(measurement='home_humidity',
                 fields={"value": float(out_info['weather']['humidity'])},
                 location="out",
                 time=current_time)
        persists(measurement='home_temperature',
                 fields={"value": float(out_info['weather']['temp'])},
                 location="out",
                 time=current_time)
        persists(measurement='home_rain',
                 fields={"value": out_info['weather']['rain'], "level": out_info['weather']['rain_level']},
                 location="out",
                 time=current_time)
        persists(measurement='home_uvi',
                 fields={"value": float(out_info['uvi']['value'])},
                 location="out",
                 time=current_time)
        for f in out_info['forecast']:
            persists(measurement='home_weather_forecast',
                     fields=f['fields'],
                     location="out",
                     time=datetime.datetime.utcfromtimestamp(f['dt']).isoformat())

    except Exception as err:
        logging.error(err)


influx_client = InfluxDBClient(host=influxdb_host, port=influxdb_port, database=influxdb_database)
current_time = datetime.datetime.utcnow().isoformat()

in_sensors()
out_sensors()

I’m running the Python script from a Raspberry Pi3 with a Sense Hat. Sense Hat has a atmospheric pressure sensor, so I will also retrieve the pressure from the Sense Hat.

From OpenWeatherMap, I will obtain:

• Current temperature/humidity and the atmospheric pressure 
• UV Index (the measure of the level of UV radiation)
• Weather conditions (if it’s raining or not)
• Weather forecast

I run this script with the Rasberry Pi crontab every 5 minutes. That means that I’ve got a fancy time series ready to be shown in Grafana.

Here, we can see the dashboard

The source code for this project is available on GitHub.