def laseregg_read(base_url, device, key):
url = base_url.strip("/") + '/lasereggs/' + device
params = {}
params['key'] = key
session = requests.session()
try:
response = session.get(url, params=params, headers={})
response.raise_for_status()
except requests.exceptions.RequestException as err:
logging.error(err)
return -1, -1
data = json.loads(response.content).get('info.aqi')
ts = (datetime.now(timezone.utc) -
datetime.strptime(data['ts'], '%Y-%m-%dT%H:%M:%SZ').replace(
tzinfo=timezone.utc)).total_seconds()
pm25 = data['data'].get('pm25')
pm10 = data['data'].get('pm10')
if pm25 is None:
pm25_aqi = -1
else:
pm25_aqi = float(aqi.to_aqi([(aqi.POLLUTANT_PM25, min(500.4, pm25))]))
if pm10 is None:
pm10_aqi = -1
else:
pm10_aqi = float(aqi.to_aqi([(aqi.POLLUTANT_PM10, min(604, pm10))]))
aqi_us = max(pm25_aqi, pm10_aqi)
return ts, aqi_us
def compute_aqi(self):
aqi_25 = aqi.to_aqi([(aqi.POLLUTANT_PM25,
str(self.state.aqdata['pm25 standard']))])
aqi_100 = aqi.to_aqi([(aqi.POLLUTANT_PM10,
str(self.state.aqdata['pm100 standard']))])
self.state.aqdata['pm25 aqi'] = int(aqi_25)
self.state.aqdata['pm100 aqi'] = int(aqi_100)
def upload_measurement():
data = request.json
app.logger.debug(f"Received data: {data}")
data_points = transform_data(data["sensordatavalues"])
node_tag = "unknown"
if "esp8266id" in data:
node_tag = f"esp8266-{data['esp8266id']}"
elif "raspiid" in data:
node_tag = f"raspi-{data['raspiid']}"
aqi_value = float(
aqi.to_aqi([(aqi.POLLUTANT_PM10, data_points["SDS_P1"]),
(aqi.POLLUTANT_PM25, data_points["SDS_P2"])]))
data_points["AQI_value"] = aqi_value
data_points["AQI_category"] = get_aqi_category(aqi_value)
app.logger.debug(f"Writing data: {data_points}")
write_api.write(
bucket=influxdb_bucket,
record=[{
"measurement": influxdb_measurement,
"tags": {
"node": node_tag
},
"fields": data_points
}],
)
return jsonify({"success": "true"})
def test_to_aqi(self):
"""Test AQI conversion"""
self.assertEqual(
aqi.to_aqi([(aqi.POLLUTANT_O3_8H, '0.077'),
(aqi.POLLUTANT_PM25, '35.9'),
(aqi.POLLUTANT_CO_8H, '8.4')],
algo=aqi.ALGO_EPA), 104)
def get_points(sensor_id):
purple_query = requests.get(
f"https://www.purpleair.com/json?show={sensor_id}")
purple_query.raise_for_status()
purple = purple_query.json()
for sensor in purple["results"]:
if (sensor["ID"] == int(sensor_id)):
return [{
"measurement": "purpleair",
"tags": {
"location": sensor["Label"],
"sensor": sensor_id
},
"fields": {
"temp_f":
float(sensor["temp_f"]),
"humidity":
float(sensor["humidity"]),
"pm2_5":
float(sensor["pm2_5_atm"]),
"pm1_0":
float(sensor["pm1_0_atm"]),
"pm10_0":
float(sensor["pm10_0_atm"]),
"aqi":
aqi.to_aqi([(aqi.POLLUTANT_PM25, sensor["pm2_5_atm"]),
(aqi.POLLUTANT_PM10, sensor["pm10_0_atm"])])
}
}]
async def async_update(self):
"""Get the latest data from REST API and update the state."""
try:
await self.rest_client.async_update()
except LuftdatenError:
value = None
return
value = self.rest_client.data
try:
parsed_json = json.loads(value)
if not isinstance(parsed_json, dict):
_LOGGER.warning("JSON result was not a dictionary")
return
except ValueError:
_LOGGER.warning("REST result could not be parsed as JSON")
_LOGGER.debug("Erroneous JSON: %s", value)
return
sensordata_values = parsed_json['sensordatavalues']
pm25 = 0
pm10 = 0
for sensordata_value in sensordata_values:
if sensordata_value['value_type'] == 'PMS_P1':
pm25 = sensordata_value['value']
elif sensordata_value['value_type'] == 'PMS_P2':
pm10 = sensordata_value['value']
self._state = int(
aqi.to_aqi([
(aqi.POLLUTANT_PM25, pm25),
(aqi.POLLUTANT_PM10, pm10),
]))
def calculateAQI(lst):
myaqi = aqi.to_aqi([(aqi.POLLUTANT_CO_8H, str(lst[0])),
(aqi.POLLUTANT_PM25, str(lst[1])),
(aqi.POLLUTANT_O3_8H, str(lst[2])),
(aqi.POLLUTANT_SO2_1H, str(lst[3])),
(aqi.POLLUTANT_NO2_1H, str(lst[4]))])
return myaqi
def test_to_aqi(self):
"""Test AQI conversion"""
self.assertEqual(
aqi.to_aqi([
(aqi.POLLUTANT_O3_8H, '0.077'),
(aqi.POLLUTANT_PM25, '40.9'),
(aqi.POLLUTANT_CO, '8.4')
]),
104)
def aqiScore(pm25, pm10):
aqi_pi = '0'
try:
aqi_pi = str(
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm25),
(aqi.POLLUTANT_PM10, pm10)]))
except:
aqi_pi = '499'
return aqi_pi
def aqiDataConverter(pm2_5Data, pm10Data):
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
return aqiData
def AQI(): no2 = aqi.to_aqi([(aqi.POLLUTANT_no2_1h, str(no2))]) #ppb co = aqi.to_aqi([(aqi.POLLUTANT_co_8h, str(co))]) #ppm o3 = aqi.to_aqi([(aqi.POLLUTANT_o3_1h, str(o3))]) #ppm, 8hr so2 = aqi.to_aqi([(aqi.POLLUTANT_so2_1h, str(so2))]) #ppb pm1 = aqi.to_aqi([(aqi.POLLUTANT_PM1, str(pm1))]) pm2 = aqi.to_aqi([(aqi.POLLUTANT_PM25, str(pm2))]) #ug/m^3 pm10 = aqi.to_aqi([(aqi.POLLUTANT_PM10, str(pm10))]) #ug/m^3
def test_to_aqi(self):
"""Test AQI conversion"""
self.assertEqual(
aqi.to_aqi([
(aqi.POLLUTANT_O3_8H, '0.077'),
(aqi.POLLUTANT_PM25, '35.9'),
(aqi.POLLUTANT_CO_8H, '8.4')
],
algo=aqi.ALGO_EPA),
104)
def calculate_aqi(co,no2,dust_density):
factors = []
if co > 0:
factors.append((aqi.POLLUTANT_CO_8H,co))
if no2 > 0:
factors.append((aqi.POLLUTANT_NO2_1H,no2))
if dust_density > 0 and dust_density < 400:
factors.append((aqi.POLLUTANT_PM25,dust_density))
try:
return aqi.to_aqi(factors)
except:
return -99
def prepare_data(soup, location_code, location_info):
rows = soup.select("#cltNormal table tr")
ths = rows[0].find_all("th")
headings = [heading.text.encode("utf-8").strip().lower().replace(" ","_").replace(".","") for heading in ths]
tds = rows[1].find_all("td")
air_data = []
for i, row in enumerate(rows[1:]):
tds = row.find_all("td")
# parse dates from ugly unicode table data
date_string = tds[0].text
scrape_date = DateDecoder(date_string, timezone='Asia/Hong_Kong')
# replace scraped date value with SQL timestamp
values = [scrape_date.sqlTimestamp()]
# type check table values.
for td in tds[1:]:
value = td.text
try:
value = float(value)
except ValueError:
# there may be a better value to use ???
value = 0
values.append(value)
# create dict with row values to normalized header keys
air_data.append( dict(zip(headings, values)) )
# calculate aqi
if (air_data[i]["pm25"]) != "-":
calculated_aqi = int(aqi.to_aqi([ (aqi.POLLUTANT_PM25, air_data[i]["pm25"]) ]))
else:
calculated_aqi = "0"
# append additional info to each hours record
air_data[i]["aqi"] = calculated_aqi
air_data[i]["location"] = location_info[0]
air_data[i]["health_range"] = health_range(calculated_aqi)
#air_data[i]["loc_code"] = location
# dict with meta values and 24 hour records in 'data' list
data = {
"data": air_data,
"timestamp": calendar.timegm(datetime.now().utctimetuple()),
"location": location_info[0],
"raw_source": location_info[1],
"location_code": location_code
}
return data
def get_aqi(data: AwairDict) -> int:
""" Returns the AQI for a given PM2.5 numbe
"""
pm25 = data["pm25"]
pm10 = data["pm10_est"]
algorithm = aqilib.ALGO_EPA
# algorithm = aqilib.ALGO_MEP # China Ministry of Health
ret = aqilib.to_aqi([(aqilib.POLLUTANT_PM25, pm25),
(aqilib.POLLUTANT_PM10, pm10)],
algo=algorithm)
return int(ret)
def calculate_aqi(HOST):
try:
url = 'http://' + HOST + '/v1/current_conditions'
print(f"# Querying {url}")
response = requests.get(url, timeout=5, allow_redirects=False)
except:
sys.exit("Failed to fetch data from AirLink device")
airlink_json_values = response.json()['data']['conditions'][0]
myaqi = aqi.to_aqi([
(aqi.POLLUTANT_PM10, airlink_json_values['pm_10']),
(aqi.POLLUTANT_PM25, airlink_json_values['pm_2p5']),
])
print(
f"# AirLink Device ID (MAC address): {response.json()['data']['did']}")
print(
f"AQI is {myaqi} (Raw values pm_10: {airlink_json_values['pm_10']} pm_2p5: {airlink_json_values['pm_2p5']})"
)
def plot_period_aqi_data(self, period, n_bins, title):
pm_data = yield self.aqi_storage.last_period_pm_data(period)
if not pm_data:
defer.returnValue(None)
t_end = time.time()
t_start = t_end - period
t, pm_25, pm_10 = np.transpose(pm_data)
aqi_data = [
int(
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm[0]),
(aqi.POLLUTANT_PM10, pm[1])]))
for pm in zip(pm_25, pm_10)
]
plot = self.plot_aqi_data(aqi_data, t, t_start, t_end, n_bins, title)
defer.returnValue(plot)
def update_dust():
try:
con = sl.connect(DB_NAME,
detect_types=sl.PARSE_DECLTYPES | sl.PARSE_COLNAMES)
cursorObj = con.cursor()
except Exception as error:
logging.error("update_dust DB " + str(error))
while True:
dust_data = None
try:
dust_data = DUST_SENSOR.get_sensor_data()
except Exception, exc:
logging.error(exc)
status_dust = False
if (dust_data and dust_data[0] and dust_data[1]):
aqi_index = aqi.to_aqi([(aqi.POLLUTANT_PM25, dust_data[0]),
(aqi.POLLUTANT_PM10, dust_data[1])])
status_dust = True
else:
status_dust = False
now = datetime.datetime.now()
if status_dust:
try:
sqlite_insert_with_param = """INSERT INTO 'dust_info'
('timestamp','pm25','pm10','aqi_index')
VALUES (?, ?, ?, ?);"""
data_tuple = (now, dust_data[0], dust_data[1], int(aqi_index))
cursorObj.execute(sqlite_insert_with_param, data_tuple)
con.commit()
logging.info("dust data added successfully \n")
except Exception as error:
logging.error("Insert " + str(error))
time.sleep(SAMPLING_INTERVAL)
def calc_aqi_from_purpleair(json_dict):
global AVG_LAT, AVG_LONG
aqis, lats, longs = [], [], []
for result in json_dict['results']:
if result['pm2_5_atm']:
# I haven't tested how this works if pm10 is missing
this_aqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, result['pm2_5_atm']),
(aqi.POLLUTANT_PM10, result['pm10_0_atm'])])
aqis.append(this_aqi)
# I chose sensors from the public map, they all had valid Lat/Lon
if result['Lat']:
lats.append(result['Lat'])
if result['Lon']:
longs.append(result['Lon'])
# Stick average AQI into JSON so that PyPortal's `json_path` can find it
json_dict['avg_aqi'] = sum(aqis) / len(aqis)
if len(lats) > 0 and len(longs) > 0:
# Update global value of avg lat/long so we can update the caption
AVG_LAT = sum(lats) / len(lats)
AVG_LONG = sum(longs) / len(longs)
def statedashboard(name=""):
name = str(name)
include = 0
if request.method == 'POST':
vari = request.form['name']
#Removing extra whitespaces and converting spaces into + to pass into url.
#name = "+".join(name.split())
if len(vari) == 0:
include = 1
else:
#Removing extra whitespaces and converting spaces into + to pass into url.
vari = "+".join(vari.split())
if vari not in statesList:
return redirect(url_for('citydash', name=vari))
else:
return redirect(url_for('statedashboard', name=vari))
url = 'https://api.ambeedata.com/latest/by-city'
headers = {'x-api-key': x_api_key, 'Content-type': 'application/json'}
city_data = []
for city_name in common_list[name]:
querystring = {"city": city_name}
response = requests.request("GET",
url,
headers=headers,
params=querystring)
list_of_data = json.loads(response.text)
print(list_of_data)
temp_data = {
"city_name": city_name,
"status": str(list_of_data['stations'][0]['aqiInfo']['category']),
"cur_aqi": str(list_of_data['stations'][0]['AQI']),
"PM25": str(list_of_data['stations'][0]['PM25']),
"PM10": str(list_of_data['stations'][0]['PM10']),
"CO": str(list_of_data['stations'][0]['CO']),
"SO2": str(list_of_data['stations'][0]['SO2'])
}
city_data.append(temp_data)
lat = 0
lon = 0
# source contain json data from api
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + name +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
stateData = []
if len(latLonData) == 0:
stateData = [
'Error', 'Sorry! The Data for ' + name + ' is not available.'
]
elif latLonData[0]['name'].find('State') == -1:
if name not in statesList:
return redirect(url_for('citydash', name=name))
if len(latLonData) > 0:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
state = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution?lat=' +
str(lat) + '&lon=' + str(lon) + '&appid=' + api).read()
stateData = json.loads(state)
stateData = stateData['list'][0]['components']
weather = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/weather?lat=' + str(lat) +
'&lon=' + str(lon) + '&appid=' + api + '&units=metric').read()
weatherData = json.loads(weather)
weatherData = weatherData['main']
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
stateHistoryData = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
stateHistoryData = [
'Error', 'Sorry! The requested city data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
aqiData = []
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
stateHistoryData = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
error = []
if include == 1:
error = [
'Error',
'Please enter a place in searchbox to search for air pollution details of required place.'
]
return render_template('statedashboard.html',
citydata=city_data,
aqiData=stateData,
weatherData=weatherData,
historyData=stateHistoryData)
def statedashboard(name=""):
name = str(name)
if request.method == 'POST':
name = request.form['name']
#Removing extra whitespaces and converting spaces into + to pass into url.
name = "+".join(name.split())
lat = 0
lon = 0
# source contain json data from api
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + name +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
stateData = []
if len(latLonData) == 0:
stateData = [
'Error', 'Sorry! The Data for ' + name + ' is not available.'
]
elif latLonData[0]['name'].find('State') == -1:
if name not in statesList:
return redirect(url_for('citydash', name=name))
if len(latLonData) > 0:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
state = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution?lat=' +
str(lat) + '&lon=' + str(lon) + '&appid=' + api).read()
stateData = json.loads(state)
stateData = stateData['list'][0]['components']
weather = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/weather?lat=' + str(lat) +
'&lon=' + str(lon) + '&appid=' + api + '&units=metric').read()
weatherData = json.loads(weather)
weatherData = weatherData['main']
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
stateHistoryData = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
stateHistoryData = [
'Error', 'Sorry! The requested city data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
aqiData = []
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
stateHistoryData = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
return render_template('statedashboard.html',
aqiData=stateData,
weatherData=weatherData,
historyData=stateHistoryData)
def get_aqi(so2, co):
query = [(aqi.POLLUTANT_CO_8H, co), (aqi.POLLUTANT_SO2_1H, so2)]
return aqi.to_aqi(query)
now = datetime.now()
current_time = now.strftime("%H:%M:%S")
print("Current Time = " + str(current_time))
#Waiting calibratrion period
print("Waking up, calibrating for 10 seconds...")
time.sleep(10)
values = cmd_query_data()
if values is not None and len(values) == 2:
if values[0] is not None and values[1] is not None:
if not values[0] == " 0.0" and not values[1] == " 0.0":
pm25 = values[0]
pm10 = values[1]
myaqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, pm25),
(aqi.POLLUTANT_PM10, pm10)])
#print("Total AQI: ", str(myaqi), ", PM2.5: ", pm25, ", PM10: ", pm10)
print(" PM2.5 = " + str(pm25))
print(" PM10 = " + str(pm10))
#temp = sense.get_temperature()
#temp = round(temp, 1)
temp = 0
#print("Temperature C: " + str(temp))
#humidity = sense.get_humidity()
#humidity = round(humidity, 1)
humidity = 0
#print("Humidity: " + str(humidity))
#pressure = sense.get_pressure()
def pollutant_to_aqi(pollutant):
return lambda conc: float(aqi.to_aqi([(pollutant, conc)]))
import aqi
myaqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, '102'), (aqi.POLLUTANT_PM10, '192')])
print("myAQI=", myaqi)
def statedashboard(name=""):
name = str(name)
if request.method == 'POST':
name = request.form['name']
#Removing extra whitespaces and converting spaces into + to pass into url.
name = "+".join(name.split())
if name not in statesList:
return redirect(url_for('citydash', name=name))
lat = 0
lon = 0
if (name == 'Telangana' or name == 'telangana'):
latLonData = [[{
'name': 'Telangana',
'lat': '18.1124',
'lon': '79.0193'
}]]
elif (name == 'Lakshadweep' or name == 'lakshadweep'):
latLonData = [[{
'name': 'Lakshadweep',
'lat': '10.57',
'lon': '72.64'
}]]
else:
latLonData = []
latLonDataCall(name, latLonData)
if len(latLonData[0]) == 0:
stateAqi = 0
stateData = [
'Error', 'Sorry! The Data for ' + name + ' is not available.'
]
weatherData = []
historyData = []
else:
lat = str(latLonData[0][0]['lat'])
lon = str(latLonData[0][0]['lon'])
stateData = []
t1 = threading.Thread(target=stateDataCall, args=(lat, lon, stateData))
t1.start()
weatherData = []
t2 = threading.Thread(target=weatherDataCall,
args=(lat, lon, weatherData))
t2.start()
stateHistoryData = []
t3 = threading.Thread(target=historyDataCall,
args=(lat, lon, latLonData[0], stateHistoryData))
t3.start()
t1.join()
stateData = stateData[0]['list'][0]['components']
stateAqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, stateData['pm2_5']),
(aqi.POLLUTANT_PM10, stateData['pm10'])])
t2.join()
t3.join()
return render_template('statedashboard.html',
stateAqi=stateAqi,
aqiData=stateData,
weatherData=weatherData[0],
historyData=stateHistoryData)
time.sleep(1)
logger.info('Reading sensors...')
# Read air quality
try:
aqdata = pm25.read()
except Exception as e:
logger.warning('Unable to read air quality data. Skipping.')
logger.exception("Exception occurred")
# Convert PM values to AQI
try:
current_aqi = aqi.to_aqi([
(aqi.POLLUTANT_PM25, aqdata["pm25 env"]),
(aqi.POLLUTANT_PM10, aqdata["pm100 env"]),
])
except Exception as e:
logger.warning('PM conversion failed. Skipping.')
logger.exception("Exception occurred")
# Read Si7021
try:
temp_data = sensor.temperature
humidity_data = sensor.relative_humidity
except Exception as e:
logger.warning('Si7021 read error. Reloading library. Skipping.')
logger.exception("Exception occurred")
# Data collected, let's send it in!
try:
def get_aqi(self):
myaqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, self.PM_2_5_conctrt_std),
(aqi.POLLUTANT_PM10, self.PM_10_conctrt_std)])
return str(myaqi)
def get_aqi(so2,co):
query = [(aqi.POLLUTANT_CO_8H,co),
(aqi.POLLUTANT_SO2_1H,so2)]
return aqi.to_aqi(query)
# print('Sleep device...')
sensor.sleep(sleep=True) # Turn off fan and diode
# print('Wake-up device...')
sensor.sleep(sleep=False) # Turn on fan and diode
# print('Mesure for 30 secs...')
time.sleep(30) # Allow time for the sensor to measure properly
# print('Query data...')
result = sensor.query()
# print('Sleep device...')
sensor.sleep() # Turn off fan and diode
return result if result else (0, 0)
if __name__ == '__main__':
pm25, pm10 = mesure()
aqi = int(aqi.to_aqi([
(aqi.POLLUTANT_PM25, pm25),
(aqi.POLLUTANT_PM10, pm10),
]))
print('Result: AQI: {}, PM2.5: {}, PM10: {}'.format(aqi, pm25, pm10))
data = {'aqi': aqi,
'pm10': pm10,
'pm25': pm25}
x = datetime.datetime.now()
print (x)
if aqi != 0:
r = requests.post(url=url, data=data, verify=False)
print (r.text)
def statevsstate():
PollutantsData1 = []
PollutantsData2 = []
if request.method == 'GET':
return render_template('statevsstate.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
if request.method == 'POST':
if len(request.form) == 1:
name = request.form['name']
#Removing extra whitespaces and converting spaces into + to pass into url.
name = "+".join(name.split())
if name not in statesList:
return redirect(url_for('citydash', name=name))
else:
return redirect(url_for('statedashboard', name=name))
if len(request.form) == 2:
state1 = request.form['state1']
state2 = request.form['state2']
if len(state1) == 0 or len(state2) == 0:
PollutantsData1 = [
'Error',
'Please enter state names in the respective boxes to compare.'
]
PollutantsData2 = ['Error']
return render_template('statevsstate.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
#Removing extra whitespaces and converting spaces into + to pass into url.
state1 = "+".join(state1.split())
state2 = "+".join(state2.split())
stateAqi = []
#For state 1
lat1 = 0
lon1 = 0
#For state 2
lat2 = 0
lon2 = 0
if (state1 == 'Telangana' or state1 == 'telangana'):
latLonData1 = [[{
'name': 'Telangana',
'lat': '18.1124',
'lon': '79.0193'
}]]
elif (state1 == 'Lakshadweep' or state1 == 'lakshadweep'):
latLonData1 = [[{
'name': 'Lakshadweep',
'lat': '10.57',
'lon': '72.64'
}]]
else:
latLonData1 = []
state1Thread = threading.Thread(target=latLonDataCall,
args=(state1, latLonData1))
state1Thread.start()
if (state2 == 'Telangana' or state2 == 'telangana'):
latLonData2 = [[{
'name': 'Telangana',
'lat': '18.1124',
'lon': '79.0193'
}]]
elif (state2 == 'Lakshadweep' or state2 == 'lakshadweep'):
latLonData2 = [[{
'name': 'Lakshadweep',
'lat': '10.57',
'lon': '72.64'
}]]
else:
latLonData2 = []
state2Thread = threading.Thread(target=latLonDataCall,
args=(state2, latLonData2))
state2Thread.start()
state1Thread.join()
state2Thread.join()
if len(latLonData1[0]) == 0:
stateAqi = ['Not Found', 'Not Found']
PollutantsData1 = [
'Error', 'Sorry! The Data for ' + state1 + ' is not available.'
]
PollutantsData2 = ['Error']
elif state1 not in statesList:
stateAqi = ['Not Found', 'Not Found']
PollutantsData1 = [
'Error',
'Sorry! This page only shows state related data. Please enter a state name.'
]
PollutantsData2 = ['Error']
elif len(latLonData2[0]) == 0:
stateAqi = ['Not Found', 'Not Found']
PollutantsData1 = ['Error']
PollutantsData2 = [
'Error', 'Sorry! The data for ' + state2 + ' is not available.'
]
elif state2 not in statesList:
stateAqi = ['Not Found', 'Not Found']
PollutantsData1 = ['Error']
PollutantsData2 = [
'Error',
'Sorry! This page only shows state related data. Please enter a state name.'
]
else:
lat1 = str(latLonData1[0][0]['lat'])
lon1 = str(latLonData1[0][0]['lon'])
lat2 = str(latLonData2[0][0]['lat'])
lon2 = str(latLonData2[0][0]['lon'])
PollutantsData1 = []
PollutantsData2 = []
s1t1 = threading.Thread(target=historyDataCall,
args=(lat1, lon1, latLonData1[0],
PollutantsData1))
s1t1.start()
stateData1 = []
s1t2 = threading.Thread(target=stateDataCall,
args=(lat1, lon1, stateData1))
s1t2.start()
s2t1 = threading.Thread(target=historyDataCall,
args=(lat2, lon2, latLonData2[0],
PollutantsData2))
s2t1.start()
stateData2 = []
s2t2 = threading.Thread(target=stateDataCall,
args=(lat2, lon2, stateData2))
s2t2.start()
s1t2.join()
stateData1 = stateData1[0]['list'][0]['components']
stateAqi.append(
aqi.to_aqi([(aqi.POLLUTANT_PM25, stateData1['pm2_5']),
(aqi.POLLUTANT_PM10, stateData1['pm10'])]))
s2t2.join()
stateData2 = stateData2[0]['list'][0]['components']
stateAqi.append(
aqi.to_aqi([(aqi.POLLUTANT_PM25, stateData2['pm2_5']),
(aqi.POLLUTANT_PM10, stateData2['pm10'])]))
s1t1.join()
s2t1.join()
return render_template('statevsstate.html',
stateAqi=stateAqi,
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
def cityvscity():
PollutantsData1 = []
PollutantsData2 = []
include = 0
if request.method == 'GET':
return render_template('cityvscity.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
if request.method == 'POST':
if len(request.form) == 1:
vari = request.form['name']
#Removing extra whitespaces and converting spaces into + to pass into url.
#name = "+".join(name.split())
if len(vari) == 0:
include = 1
else:
#Removing extra whitespaces and converting spaces into + to pass into url.
vari = "+".join(vari.split())
if vari not in statesList:
return redirect(url_for('citydash', name=vari))
else:
return redirect(url_for('statedashboard', name=vari))
elif len(request.form) == 2:
city1 = request.form['city1']
city2 = request.form['city2']
if len(city1) == 0 or len(city2) == 0:
PollutantsData1 = [
'Error',
'Please enter city names in the respective boxes to compare.'
]
PollutantsData2 = ['Error']
return render_template('cityvscity.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
else:
city1 = 'ahmedabad'
city2 = 'surat'
#Removing extra whitespaces and converting spaces into + to pass into url.
city1 = "+".join(city1.split())
city2 = "+".join(city2.split())
url = 'https://api.ambeedata.com/latest/by-city'
headers = {'x-api-key': x_api_key, 'Content-type': 'application/json'}
city_data = []
querystring = {"city": city1}
response = requests.request("GET",
url,
headers=headers,
params=querystring)
list_of_data = json.loads(response.text)
temp_data = {
"city_name": city1,
"cur_aqi": str(list_of_data['stations'][0]['AQI'])
}
city_data.append(temp_data)
querystring = {"city": city2}
response = requests.request("GET",
url,
headers=headers,
params=querystring)
list_of_data_1 = json.loads(response.text)
temp_data_1 = {
"city_name": city2,
"cur_aqi": str(list_of_data_1['stations'][0]['AQI'])
}
city_data.append(temp_data_1)
#For city 1
lat = 0
lon = 0
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + city1 +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
if len(latLonData) == 0:
PollutantsData1 = [
'Error', 'Sorry! The Data for ' + city1 + ' is not available.'
]
elif latLonData[0]['name'].find('State') != -1:
PollutantsData1 = [
'Error',
'Sorry! This page only shows city related data. Please enter a city name.'
]
else:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
PollutantsData1 = [
'Error', 'Sorry! The requested city data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
aqiData = []
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
PollutantsData1 = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
#For city 2
lat = 0
lon = 0
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + city2 +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
if len(latLonData) == 0:
PollutantsData2 = [
'Error', 'Sorry! The data for ' + city2 + ' is not available.'
]
elif latLonData[0]['name'].find('State') != -1:
PollutantsData2 = [
'Error',
'Sorry! This page only shows city related data. Please enter a city name.'
]
else:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
PollutantsData2 = [
'Error', 'Sorry! The requested city data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
PollutantsData2 = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
error = []
if include == 1:
error = [
'Error',
'Please enter a place in searchbox to search for air pollution details of required place.'
]
return render_template('cityvscity.html',
citydata=city_data,
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
def main():
# Create the I2C interface.
i2c = busio.I2C(board.SCL, board.SDA)
# 128x32 OLED Display
reset_pin = DigitalInOut(board.D4)
display = adafruit_ssd1306.SSD1306_I2C(128, 32, i2c, reset=reset_pin)
# Clear the display.
display.fill(0)
display.show()
width = display.width
height = display.height
# prepare scrolling display
dline1 = dline2 = dline3 = ""
while True:
aqi_cnx = mysql.connector.connect(user=cur_user,
password=cur_pwd,
host='sequoia',
database='airquality')
aqi_cursor = aqi_cnx.cursor()
# Fetch data from mySQL database
data_fetch = "SELECT * FROM pm25data WHERE ts >= date_sub(now(),interval 1 hour)"
aqi_cursor.execute(data_fetch)
ds1_records = aqi_cursor.fetchall()
ds1DF = pd.DataFrame(ds1_records)
try:
ds1DF.columns = [
'observation', 'ts', 'pm25', 'pm100', 'mtempc', 'mtempf',
'mpress', 'mrh'
]
except ValueError as e:
print("Caught ValueError: %s" % e)
time.sleep(10)
continue
meanpm25 = statistics.mean(ds1DF['pm25'])
meanpm100 = statistics.mean(ds1DF['pm100'])
cur_aqi = aqi.to_aqi([(aqi.POLLUTANT_PM25, meanpm25),
(aqi.POLLUTANT_PM10, meanpm100)])
data_fetch = "SELECT * FROM pm25data ORDER BY observation DESC LIMIT 1"
aqi_cursor.execute(data_fetch)
ds2_records = aqi_cursor.fetchall()
ds2DF = pd.DataFrame(ds2_records)
try:
ds2DF.columns = [
'observation', 'ts', 'pm25', 'pm100', 'mtempc', 'mtempf',
'mpress', 'mrh'
]
except ValueError as e:
print("Caught ValueError: %s" % e)
time.sleep(10)
continue
aqi_cursor.close()
aqi_cnx.close()
cur_tempc = ds2DF['mtempc']
cur_tempf = ds2DF['mtempf']
cur_press = ds2DF['mpress']
cur_rh = ds2DF['mrh']
dline1 = "%0.2f C %0.2f F" % (cur_tempc, cur_tempf)
dline2 = "%0.2f hPa %0.2f RH" % (cur_press, cur_rh)
dline3 = "AQI %d" % cur_aqi
print(dline1)
print(dline2)
print("%s\n" % dline3)
display.fill(0)
display.text(dline1, 5, 0, 1)
display.text(dline2, 5, 11, 1)
display.text(dline3, 5, 22, 1)
display.show()
time.sleep(120)
def statevsstate():
PollutantsData1 = []
PollutantsData2 = []
if request.method == 'GET':
return render_template('statevsstate.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
if request.method == 'POST':
state1 = request.form['state1']
state2 = request.form['state2']
else:
state1 = 'Gujarat'
state2 = 'Maharashtra'
#Removing extra whitespaces and converting spaces into + to pass into url.
state1 = "+".join(state1.split())
state2 = "+".join(state2.split())
#For state 1
lat = 0
lon = 0
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + state1 +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
if len(latLonData) == 0:
PollutantsData1 = [
'Error', 'Sorry! The Data for ' + state1 + ' is not available.'
]
elif latLonData[0]['name'].find('State') == -1:
PollutantsData1 = [
'Error',
'Sorry! This page only shows state related data. Please enter a state name.'
]
else:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
PollutantsData1 = [
'Error', 'Sorry! The requested state data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
PollutantsData1 = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
#For state 2
lat = 0
lon = 0
latLon = urllib.request.urlopen(
'http://api.openweathermap.org/geo/1.0/direct?q=' + state2 +
'&limit=1&appid=' + api).read()
latLonData = json.loads(latLon)
if len(latLonData) == 0:
PollutantsData2 = [
'Error', 'Sorry! The data for ' + state2 + ' is not available.'
]
elif latLonData[0]['name'].find('State') == -1:
PollutantsData2 = [
'Error',
'Sorry! This page only shows state related data. Please enter a state name.'
]
else:
lat = str(latLonData[0]['lat'])
lon = str(latLonData[0]['lon'])
sDate = datetime.date.today() - datetime.timedelta(days=31)
sDateformatted = sDate.strftime('%d/%m/%Y')
eDate = datetime.date.today() - datetime.timedelta(days=1)
eDateformatted = eDate.strftime('%d/%m/%Y')
sUNIX = int(
time.mktime(
datetime.datetime.strptime(sDateformatted,
"%d/%m/%Y").timetuple()))
eUNIX = int(
time.mktime(
datetime.datetime.strptime(eDateformatted,
"%d/%m/%Y").timetuple()))
history = urllib.request.urlopen(
'http://api.openweathermap.org/data/2.5/air_pollution/history?lat='
+ str(lat) + '&lon=' + str(lon) + '&start=' + str(sUNIX) +
'&end=' + str(eUNIX) + '&appid=' + api).read()
historyData = json.loads(history)
error = []
if 'cod' in historyData:
error = ['404']
else:
error = ['10000']
if error[0] == '404':
PollutantsData2 = [
'Error', 'Sorry! The requested state data is not available.'
]
else:
hData1 = historyData['list']
prevDate = '0'
count = 1
coData = []
noData = []
no2Data = []
o3Data = []
so2Data = []
pm2_5Data = []
pm10Data = []
nh3Data = []
for tData in hData1:
tCO = float(tData['components']['co'])
tNO = float(tData['components']['no'])
tNO2 = float(tData['components']['no2'])
tO3 = float(tData['components']['o3'])
tSO2 = float(tData['components']['so2'])
tPM2_5 = float(tData['components']['pm2_5'])
tPM10 = float(tData['components']['pm10'])
tNH3 = float(tData['components']['nh3'])
tDate = datetime.datetime.fromtimestamp(int(tData['dt']))
tDatef = tDate.strftime('%d/%m/%Y')
if prevDate == tDatef:
coData[len(coData) - 1][1] = round(
(count * (coData[len(pm2_5Data) - 1][1]) + tCO) /
(count + 1), 2)
noData[len(noData) - 1][1] = round(
(count * (noData[len(pm2_5Data) - 1][1]) + tNO) /
(count + 1), 2)
no2Data[len(no2Data) - 1][1] = round(
(count * (no2Data[len(pm2_5Data) - 1][1]) + tNO2) /
(count + 1), 2)
o3Data[len(o3Data) - 1][1] = round(
(count * (o3Data[len(pm2_5Data) - 1][1]) + tO3) /
(count + 1), 2)
so2Data[len(so2Data) - 1][1] = round(
(count * (so2Data[len(pm2_5Data) - 1][1]) + tSO2) /
(count + 1), 2)
pm2_5Data[len(pm2_5Data) - 1][1] = round(
(count * (pm2_5Data[len(pm2_5Data) - 1][1]) + tPM2_5) /
(count + 1), 2)
pm10Data[len(pm10Data) - 1][1] = round(
(count * (pm10Data[len(pm2_5Data) - 1][1]) + tPM10) /
(count + 1), 2)
nh3Data[len(nh3Data) - 1][1] = round(
(count * (nh3Data[len(pm2_5Data) - 1][1]) + tNH3) /
(count + 1), 2)
count = count + 1
else:
coData.append([tDatef, tCO])
noData.append([tDatef, tNO])
no2Data.append([tDatef, tNO2])
o3Data.append([tDatef, tO3])
so2Data.append([tDatef, tSO2])
pm2_5Data.append([tDatef, tPM2_5])
pm10Data.append([tDatef, tPM10])
nh3Data.append([tDatef, tNH3])
prevDate = tDatef
count = 1
aqiData = []
for i in range(len(pm2_5Data)):
aqiData.append([
pm2_5Data[i][0],
aqi.to_aqi([(aqi.POLLUTANT_PM25, pm2_5Data[i][1]),
(aqi.POLLUTANT_PM10, pm10Data[i][1])])
])
PollutantsData2 = [
aqiData, coData, noData, no2Data, o3Data, so2Data, pm2_5Data,
pm10Data, nh3Data, latLonData[0]['name']
]
return render_template('statevsstate.html',
data1=PollutantsData1,
len1=len(PollutantsData1),
data2=PollutantsData2,
len2=len(PollutantsData2))
