def get_forecast(lng, lat):
"""Return weather forecast for the next week"""
weekday = datetime.date.today()
sf = forecast(mykey, lat, lng)
html_str = ""
forecast_data = {}
with forecast(mykey, lat, lng) as sf:
forecast_data["daily_summary"] = sf.daily.summary
forecast_data["daily_forecast"] = []
html_str += "7-day WEATHER FORECAST SUMMARY: " + str(
sf.daily.summary) + "<br><br>\n"
for day in sf.daily:
day = dict(day=datetime.date.strftime(weekday, '%a'),
sum=day.summary,
tempMin=day.temperatureMin,
tempMax=day.temperatureMax)
html_str += "{day}: {sum} Temp range: {tempMin} - {tempMax}".format(
**day)
html_str += "<br>\n"
weekday += datetime.timedelta(days=1)
return html_str
def write_weather_data(dates,
hours,
apikey,
latlon,
append_output=False,
filepath='../precrime_data/weather_hist.csv'):
"""Call the Dark Sky API and save the weather data.
Parameters
----------
dates : list
A list of dates (supporting .year, .month, and .day) to
download the weather for
hours : list
A list of integers representing the hours of each day
that we want to get the weather for. The total number of forecasts
download is len(dates) * len(hours)
apikey : string
Dark Sky API key
latlon : tuple
latlon[0] = latitude, latlon[1] = longitude
append_output : boolean, optional, default False
If True, will not write a header row and will not overwrite the file
filepath : string, optional
Where to write the output
Returns
-------
None
"""
if append_output:
write_header = False
file_mode = 'a'
else:
write_header = True
file_mode = 'w'
weather_location = [apikey, latlon[0], latlon[1]]
with open(filepath, file_mode, newline='') as csvfile:
# Create the list of dict fields we'll be including in the file.
# Add 'precipType' in case it isn't currently raining while
# this script is being run.
with forecast(*weather_location) as current_weather:
weather_fields = sorted(
list(
set(['precipType'] +
list(current_weather.currently._data.keys()))))
writer = csv.DictWriter(csvfile, fieldnames=weather_fields)
if write_header:
writer.writeheader()
for date in dates:
for hour in hours:
t = dt(date.year, date.month, date.day, hour).isoformat()
with forecast(*weather_location, time=t) as local_weather:
writer.writerow({
k: v
for k, v in local_weather.currently._data.items()
})
def home(request) :
# boston = 42.3601, -71.0589
boston = 34.005143,-6.823645
weekday = date.today()
weekly_weather = {}
with forecast('cc3aae97f4aa5697aa47c5624a085e10', *boston) as boston:
print(boston.daily.summary)
for day in boston.daily:
day = dict(day = date.strftime(weekday, '%a'),
sum = day.summary,
tempMin = int((day.temperatureMin-32) *(5/9)),
tempMax = int ((day.temperatureMax-32) *(5/9))
)
print('{day}: {sum} Temp range: {tempMin} - {tempMax}'.format(**day))
weekday += timedelta(days=1)
#------------------------#
pic = ''
summary = ('{sum}'.format(**day).lower())
if 'drizzle' in summary :
pic ='rain.png'
if 'rain' in summary :
pic ='rain.png'
if 'cloudy' in summary :
pic ='clouds.png'
if 'clear' in summary :
pic ='sun.png'
if 'party cloudy' in summary :
pic ='rain.png'
if 'drizzle' in summary :
pic ='party-cloudy-day.png'
hour = datetime.now().hour
location = forecast('cc3aae97f4aa5697aa47c5624a085e10',34.005143,-6.823645)
i= 0
while hour < 24 :
temp = location.hourly[i].temperature
if hour > 12 :
print('{} pm - {}'.format(hour,temp))
else :
print('{} am - {}'.format(hour,temp))
hour += 1
i+=1
return render(request,'home.html',{})
def main():
SAOPAULO = -23.5489, -46.6388 #latitude e longitude de São Paulo
RIO = -22.9035, -43.2096 # latitude e longetude do Rio de Janeiro
KEY = 'INSERT YOUR API KEY FROM THE DARKSKY WEATHER API'
insert_query = """
INSERT INTO weather_forecast
(city, minimum_temp, maximum_temp, date)
VALUES(%s, %s, %s, %s) """
datasetsp = []
datasetrio = []
weekday = date.today()
with forecast(KEY, *SAOPAULO, units='si') as saopaulo:
print("Summary for Sao Paulo")
print(saopaulo.daily.summary, end='\n---\n')
for day in saopaulo.daily:
datasetsp.append([
'sao paulo', day['temperatureMin'], day['temperatureMax'],
datetime.utcfromtimestamp(day['time']).strftime('%Y-%m-%d')
])
weekday += timedelta(days=1)
print(datasetsp)
with forecast(KEY, *RIO, units='si') as rio:
print("Summary for Rio de Janeiro")
print(rio.daily.summary, end='\n---\n')
for day in rio.daily:
datasetrio.append([
'rio de janeiro', day['temperatureMin'], day['temperatureMax'],
datetime.utcfromtimestamp(day['time']).strftime('%Y-%m-%d')
])
weekday += timedelta(days=1)
print(datasetrio)
try:
con = psycopg2.connect(user="******",
password="******",
host="127.0.0.1",
database="INSERT_YOUR_DB_NAME")
cur = con.cursor()
cur.executemany(insert_query, datasetsp)
cur.executemany(insert_query, datasetrio)
con.commit()
con.close()
except (Exception):
print("Database error!")
raise
def future_weather(self,api, lat, lon, hours, time):
days = int(hours) // 24
hour = int(hours) % 24
data = []
for i in range(days):
t = time.shift(days=+i)
t = dt.datetime(t.year,t.month, t.day, 0).isoformat()
weather = forecast(api, lat, lon, time=t)
data.extend([self.ftoc(hour.temperature) for hour in weather.hourly[:24]])
if hour != 0:
t = time.shift(days=+days)
t = dt.datetime(t.year,t.month, t.day, 0).isoformat()
weather = forecast(api, lat, lon, time=t)
data.extend([self.ftoc(hour.temperature) for hour in weather.hourly[:hours]])
return data
def add_head(self):
top = QFrame()
top.setFrameShape(QFrame.WinPanel)
top.setFrameShadow(QFrame.Raised)
top.setMaximumHeight(100)
top.setStyleSheet("background-color: red;")
clk = clock.Clock(parent=top)
clk.setFrameShape(QFrame.NoFrame)
clk.setStyleSheet("background-color:none; color: white;")
clk.move(-75, -75)
clk.setMinimumWidth(250)
clk.setMinimumHeight(250)
next_bus = QLabel(top)
next_bus.setFont(QFont("Sans-serif", 42, QFont.Bold))
bus = self.l[0][0]
time = self.l[0][1]
next_bus.setText("<font color='white'>Next Bus: " + bus + " in " +
time + "</font>")
next_bus.move(int(self.screen.width() / 2) - 400, 25)
weather = QLabel(top)
weather.setFont(QFont("Sans-serif", 42, QFont.Bold))
w = forecast('c505a8dedfcf4bc235046f56138a67d9', 51.0253, -114.0499)
temp = round(w['currently']['temperature'])
weather.setText("<font color='white'>" + str(temp) + "°</font>")
weather.move(self.screen.width() - 130, 25)
self.layout.addWidget(top)
def show_weather(self):
try:
city = self.setcity.text()
country = self.setcountry.text()
location = geocoder.yandex(city + ' ' + country)
data = forecast(KEY, location.latlng[0],
f'{location.latlng[1]}?lang=ru&units=si')
except Exception:
answ = QMessageBox.question(
self, 'Ошибка',
'Город/страна не найден(а) Попробуете еще раз?')
if answ == QMessageBox.No:
self.close()
else:
cc = ''
while ', ' not in cc:
cc, btn = QInputDialog.getText(self, 'Погода для народа',
'Введите город, страну:')
if not btn:
self.close()
break
if btn:
cc = cc.split(', ')
self.setcity.setText(cc[0])
self.setcountry.setText(cc[1])
self.show_weather()
else:
options = self.set_options(self.prm)
timeper = self.set_timeper(self.tp)
weather = Weather(data, options, timeper, self.view)
weather.show_widget()
def get_locations_dict(loc_lst):
locs_dict = {}
for location in loc_lst:
locs_dict[location] = forecast(darksky_key, location.lat, location.lng)
return locs_dict
def __init__(self, apiKey, codigo):
site, self.latitude, self.longitude = locationSiteCoordenate(codigo)
if self.latitude != 0 and self.longitude != 0:
fcast = forecast(apiKey, self.latitude, self.longitude, units='si')
else:
fcast = []
if (fcast):
main = fcast.currently
self.wdb.setMeasure('humidity' ,main.humidity * 100)
self.wdb.setMeasure('pressure' ,main.pressure)
self.wdb.setMeasure('temperature' ,main.temperature)
self.wdb.setMeasure('temperatureApparent',main.apparentTemperature)
self.wdb.setMeasure('temperatureDew' ,main.dewPoint)
self.wdb.setMeasure('weatherMain' ,main.summary)
self.wdb.setMeasure('latitude' ,self.latitude )
self.wdb.setMeasure('longitude' ,self.longitude)
self.wdb.setMeasure('windSpeed' ,main.windSpeed * 3.6)
self.wdb.setMeasure('windGust' ,main.windGust * 3.6)
self.wdb.setMeasure('windDegrees' ,main.windBearing )
self.wdb.setMeasure('rainIntensity' ,main.precipIntensity)
self.wdb.setMeasure('rainProbability' ,main.precipProbability * 100)
self.wdb.setMeasure('skyUVIndex' ,main.uvIndex)
self.wdb.setMeasure('skyClouds' ,main.cloudCover * 100)
self.wdb.setMeasure('skyOzone' ,main.ozone)
self.wdb.setMeasure('skyVisibility' ,main.visibility )
self.wdb.setMeasureClean()
def main():
try:
c = configparser.ConfigParser()
c.read(
os.path.join(os.path.abspath(os.path.dirname(__file__)),
'../frontend/conf', 'settings.ini'))
# Setup Nest account
n = Nest(c['nest']['nest_username'],
c['nest']['nest_password'],
c['nest']['nest_sn'],
c['nest']['nest_index'],
units=c['common']['units'])
n.login()
n.get_status()
ds = forecast(c['darksky']['api_key'], c.getfloat('darksky', 'lat'),
c.getfloat('darksky', 'long'))
observation = ds['currently']
w = observation
# Connect to DB
cnx = mysql.connector.connect(user=c['mysql']['mysql_username'],
password=c['mysql']['mysql_password'],
host=c['mysql']['mysql_hostname'],
database=c['mysql']['mysql_database'])
d = cnx.cursor()
polling(c, n, w, d)
cnx.commit()
d.close()
except Exception:
print(sys.exc_info()[1])
def main():
""" Collect all summer dates in a list and iterate through it"""
date_generated = [start + datetime.timedelta(days=x) for x in range(0, (end-start).days)]
for summer_day in date_generated:
my_date = dt.strptime(str(summer_day), "%Y-%m-%d").isoformat() #api's time arg requires isoformat
for city, coordinates in cities.items():
"""connect to the api using darkskylib
and fetch the highest temperature and humidity index
per each day"""
with forecast(token, *coordinates, time=my_date) as values:
maxTemp = round(((values['daily']['data'][0]['temperatureMax']) - 32) * 5/9, 1) #convert Fahrenheit to Celsius
humidity = values['daily'] ['data'] [0] ['humidity']
""" populate database tables with the city names
and respective temperatures and humidity indexes per each summer day"""
city_query = """ INSERT IGNORE INTO weather.location(city) VALUES (%s)"""
cur.execute(city_query, [city])
temperature_query = "('{0}', '{1}',{2}, {3}, '{4}')".format(city, summer_day, maxTemp, humidity, datetime.date.today())
cur.execute ("""INSERT INTO weather.summer_time
(city, summer_day, highest_temp, humidity, in_date)
VALUES {0} """.format(temperature_query))
conn.commit()
conn.close()
def get_forecast(location):
coord = geolocate_city(location)
key = '1136ef786eb77b372c671b0b22ae1e0f'
print(f'Checking weather for {location}')
data = []
with darksky.forecast(key, *coord) as geo_data:
for hour in range(len(geo_data.hourly) - 38):
hourofforecast = datetime.now().hour + hour if datetime.now().hour + \
hour < 24 else datetime.now().hour + hour - 24
hour = dict(time=str(hourofforecast).zfill(2) + ':' +
str(datetime.now().minute),
summary=geo_data.hourly[hour].summary,
temperature=np.round(
(geo_data.hourly[hour].temperature - 32) * .5556,
2),
prec_int=np.round(
geo_data.hourly[hour].precipIntensity, 2),
prec_prob=np.round(
geo_data.hourly[hour].precipProbability * 100, 0))
hourly_data = 'At {time}: {summary}, {temperature}°C. Rain prob {prec_prob}% ({prec_int} mm)'.format(
**hour)
data.append(hourly_data)
return 'Hello world'
def ReadValue(self):
try:
weather = forecast(self.key,
self.latitude,
self.longitude,
units=self.units,
timeout=1)
except Exception as e:
logging.warning("DarkSky warning in Readvalue: " + str(e))
return np.nan
try:
current = weather.currently
except TimeoutError:
logging.warning("DarkSky warning in Readvalue: TimeoutError")
return np.nan
try:
nearestStormDistance = current.nearestStormDistance
except AttributeError:
nearestStormDistance = np.nan
values = [
time.time() - self.time_offset, current.temperature,
current.humidity, current.dewPoint, current.pressure,
current.cloudCover, current.uvIndex, current.windSpeed,
current.windGust, current.ozone, current.precipIntensity,
current.precipProbability, nearestStormDistance,
current.visibility, weather.latitude, weather.longitude
]
values = [float(v) for v in values]
return values
def ten_years_data(self,time):
t = []
time = time.split('-')
self.curr_year = dt.today().year
for i in range(10):
t.append(dt(self.curr_year - i,int(time[1]),int(time[2].split('T')[0])))
""" Loop through 10 years and use the ds API to request it all
+ Add it all to a list of forecast objects """
loc = []
for i in range(10):
print("DEBUG {0}".format(t[i]))
loc.append(forecast(self.ds_key, self.geoLoc['lat'], self.geoLoc['lng'], t[i].strftime('%Y-%m-%d' + 'T12:00:00')))
# Set it equal to the first entries just to populated them
high_avg = loc[0]['daily']['data'][0]['temperatureHigh']
low_avg = loc[0]['daily']['data'][0]['temperatureLow']
""" Loop through all the objects and pull the data we want """
for i in range(1,10):
high_avg += loc[i]['daily']['data'][0]['temperatureHigh']
low_avg += loc[i]['daily']['data'][0]['temperatureLow']
high_avg = high_avg/10
low_avg = low_avg/10
weather_out = {'high_avg': high_avg, 'low_avg':low_avg}
return weather_out
def ping_darksky(time, key):
"""
Interface to Dark Sky API. Requests data from Boston Airport for a specific
time.
* Arguments:
+ time: a datetime object. Denotes the day of the requested record.
+ key: a character string. Key to interface the Dark Sky API.
* Returns:
+ Dictionary containing:
+ day: datetime of the observation (in timestamp format).
+ tempMin: minimum temperature in degrees Fahrenheit at that date.
+ tempMax: maximum temperature in degrees Fahrenheit at that date.
+ summary: weather summary of that date.
+ desc: single word description of weather conditions.
"""
with forecast(key, *BOSTON, time=time.isoformat()) as boston:
fetch = {'day': time,
'tempMin': boston.daily[0].temperatureMin,
'tempMax': boston.daily[0].temperatureMax,
'summary': boston.daily[0].summary,
'desc': boston.daily[0].icon}
return fetch
def weather_forecast(weather_location, formatted_address):
print(f'\n----- Forecast for {formatted_address}-----\n')
weekday = date.today()
with forecast(f'{DARKSKY_API_KEY}', *weather_location) as location:
print(
f'Current Temperature in {formatted_address} is {int(round(location.temperature))}\xb0F'
)
print(location.daily.summary, end='\n---\n')
right_time, dst_offset = time_zone(weather_location, location.time)
print(
f'Date/Time in {formatted_address} {convert_time(location.time + right_time + dst_offset)}'
)
print('--------')
for day in location.daily:
day = dict(day=date.strftime(weekday, '%a'),
sum=day.summary,
tempMin=int(round(day.temperatureMin)),
tempMax=int(round(day.temperatureMax)))
print('{day}: {sum} Temp range: {tempMin}\xb0F - {tempMax}\xb0F'.
format(**day))
weekday += timedelta(days=1)
def ping_darksky(time, key):
"""
Interface to Dark Sky API. Requests data from Boston Airport for a specific
time.
* Arguments:
+ time: a datetime object. Denotes the day of the requested record.
+ key: a character string. Key to interface the Dark Sky API.
* Returns:
+ Dictionary containing:
+ day: datetime of the observation (in timestamp format).
+ tempMin: minimum temperature in degrees Fahrenheit at that date.
+ tempMax: maximum temperature in degrees Fahrenheit at that date.
+ summary: weather summary of that date.
+ desc: single word description of weather conditions.
+ cloud_cover: float denoting the proportion of the skies surface
that is obscured by clouds
"""
boston = forecast(key, *BOSTON, time=time.isoformat())
fetch = {
'day': time,
'tempMin': boston["daily"]["data"][0].get('temperatureMin', np.nan),
'tempMax': boston["daily"]["data"][0].get('temperatureMax', np.nan),
'summary': boston["daily"]["data"][0].get('summary', np.nan),
'desc': boston["daily"]["data"][0].get('icon', np.nan),
'cloudCover': boston["daily"]["data"][0].get('cloudCover', np.nan)
}
return fetch
def get_weather_forecast():
apikey = '7358efac8f40bf49ceaa4a8c5278bd31'
Goleta = [34.4099508, -119.8661304]
goleta = forecast(apikey, Goleta[0], Goleta[1])
parameters = [
'time', 'ozone', 'windGust', 'temperature', 'dewPoint', 'humidity',
'apparentTemperature', 'pressure', 'windSpeed', 'precipProbability',
'visibility', 'cloudCover', 'precipIntensity'
]
forecast_data = []
for hour in goleta['hourly']['data']:
hourly_data = {}
for item in hour:
if item in parameters:
hourly_data[item] = hour[item]
if item == 'temperature' or item == 'apparentTemperature' or item == 'dewPoint':
hourly_data[item] = convert_to_celsius(hourly_data[item])
time = datetime.fromtimestamp(int(
hour['time'])).strftime('%Y-%m-%d %H:%M:%S')
time = datetime.strptime(time, '%Y-%m-%d %H:%M:%S')
time = time + timedelta(hours=8, minutes=0)
hourly_data['time'] = time
hourly_data['hour'] = time.hour
forecast_data.append(hourly_data)
return forecast_data
def __init__(self, adminId, darkskyKey, lat, longitude):
self.adminId = adminId
self.approvedUsers = {}
self.approvedUsers[self.adminId] = 'ADRIKA'
self.darkskyKey = darkskyKey
self.weatherTimeLimit = 30.0
self.timePic = 0
self.timeVideo = 0
self.lat = lat
self.longitude = longitude
self.cityWeatherData = forecast(self.darkskyKey, self.lat,
self.longitude)
self.enablePic = True
self.enableWater = False
self.enableLight = True
self.enableAdd = True
self.enableVideo = True
self.picTimeLimit = 2.0 #mins for users (not admin)
self.waterTimeLimit = 4.0 #hrs for users (not admin)
self.lightTimeLimit = 15.0 #mins for users (not admin)
self.weatherTimeLimit = 30.0 #mins for users (not admin)
self.vidTimeLimit = 5.0 #mins for users (not admin)
def buildmultidayDF(startday, lastday, coords ):
""" Concatène plusieurs jours ensemble
startday, lastday: pandas timestamp
"""
daterange = pd.date_range(start=startday, end=lastday, freq='D', normalize=True)
records = []
for day in daterange:
day_iso = day.isoformat()
print('%i, '%day.day, end='')
data = forecast(KEY, *coords, units='si', lang='fr', \
time=day_iso, exclude=EXCLUDE)
records_oftheday = data['hourly']['data']
records.extend( records_oftheday )
print( 'done' )
# build DF:
allweatherdata = pd.DataFrame.from_records(records, index='time')
allweatherdata.drop(COL2DROP, axis=1, inplace=True, errors='ignore')
allweatherdata.index = pd.to_datetime(allweatherdata.index, unit='s')
allweatherdata['cloudCover'] = allweatherdata['cloudCover'].fillna( 0 )
return allweatherdata
def __init__(self):
super(MainWidget, self).__init__()
self.get_location()
self.weather = forecast(Config.get('darksky', 'api_key'),
*self.location,
units=Config.get('darksky', 'units'))
def get(self):
city_name = request.args.get('city')
date = request.args.get('date')
# Response if no filter is provided
if date is None and city_name is None:
return [self.get_weather(city.name)for city in CityModel.query.all()], 200
if city_name is None:
return {'message' : 'Please enter a city name to get weather information'}, 400
city = CityModel.find_by_name(city_name.lower())
# Check if provided city exists in the database or not
if city:
# If city exists check if date is provided or not
if date:
input_date = parse(date, parserinfo(dayfirst = True)).replace(hour = 0, minute = 0, second = 0, microsecond = 0)
# Check if weather information for a particular date is available or not
weather_obj = WeatherModel.find_by_date(city.name, input_date)
if weather_obj:
return weather_obj.json(), 200
# If absent, fetch the data for the city from the API
else:
new_forecast = forecast(darksky_key, city.latitude, city.longitude, time = input_date.isoformat())
return {'summary' : new_forecast.summary, 'temperature' : new_forecast.temperature, 'humidity' : new_forecast.humidity}, 200
else:
return self.get_weather(city.name), 200
return {'message' : 'Requested city is not present in the database'}, 400
def getWeather(city = None):
global apiKey, ipStackKey
if (city == None):
send_url = 'http://api.ipstack.com/' + str(get_ip()) + '?access_key=' + ipStackKey
r = requests.get(send_url)
j = json.loads(r.text)
lat, lon = j['latitude'], j['longitude']
else:
lat, lon = WeatherIntent.getLatLon(city);
cityForcast = forecast(apiKey, lat, lon)
# at this point we have to lat, lon
url = 'https://api.darksky.net/forecast/' + apiKey + '/' + str(lat) + ',' + str(lon) + '?units=si'
r = requests.get(url)
j = json.loads(r.text)
summary = ''
if (j['hourly']):
summary = j['hourly']['summary']
j = j['currently']
cityName = WeatherIntent.getCityName(lat, lon);
return { 'weather': j['summary'],
'temp': j['temperature'],
'icon': j['icon'],
'city': cityName,
'summary': summary
}
def dump_weather_for_t(t: datetime = datetime(year=2018, month=5, day=3).isoformat(),
location: tuple = (42.36, -71.05),
dry_run=True):
if not os.path.isdir(f'weather-data-output/{t}'):
os.makedirs(f'weather-data-output/{t}')
needs_new_request = False
if len(saved_weather[t]) > 0:
dists = np.linalg.norm(np.array(saved_weather[t]) - np.array(location), axis=1)
dist_min_ind = np.argmin(dists)
try:
dist_min = dists[dist_min_ind]
except IndexError:
dist_min = dists # just one entry
if dist_min > 0.1: # 0.1deg is about 7 miles
needs_new_request = True
else:
needs_new_request = True
if not needs_new_request:
coords_cached = saved_weather[t][dist_min_ind]
out_filename = f'weather-data-output/{t}/{coords_cached[0]}_{coords_cached[1]}.json'
elif needs_new_request and not dry_run:
out = forecast(key, latitude=location[0], longitude=location[1], time=t)
out_filename = f'weather-data-output/{t}/{location[0]}_{location[1]}.json'
with open(out_filename, 'w') as f:
json.dump(out['hourly'], f)
saved_weather[t].append([location[0], location[1]])
return out_filename
def index():
"""Get weather, render index.html"""
BERKELEY = 37.877360, -122.296730 #Lat, long of Berkeley
with forecast(dark_sky, *BERKELEY) as berkeley:
weekday = date.today()
weekly_summary = []
max_temp_array = []
for day in berkeley.daily:
day = dict(day=date.strftime(weekday, '%a'),
sum=day.summary,
tempMin=day.temperatureMin,
tempMax=day.temperatureMax)
min_temp_in_celcius = helpers.convert_fahrenheit_to_celcius(
day['tempMin'])
max_temp_in_celcius = helpers.convert_fahrenheit_to_celcius(
day['tempMax'])
max_temp_array.append(max_temp_in_celcius)
weekly_summary_string = day['day'] + ': ' + day[
'sum'] + ' Temp range: ' + str(
min_temp_in_celcius) + '-' + str(max_temp_in_celcius)
weekly_summary.append(weekly_summary_string)
weekday += timedelta(days=1)
return render_template("index.html",
weekly_report=berkeley.daily,
weekly_summary=weekly_summary,
max_temp_array=max_temp_array)
def get_hourly_weather_1day(self, city, time):
city_forecast = forecast(key=self.key,
latitude=city.latitude,
longitude=city.longitude,
time=time)
return city_forecast['hourly']['data']
def darksky_config(latitude: float, longitude: float):
"""
This method connects to DarkSky using my API key and returns the current weather at
a chosen location. Right now it only returns stirling weather data.
"""
requested_forecast = []
regex = r"[0-9][°F]" #used for converting the summary string
regex_num = r"[0-9]" #used for converting the summary string numbers
API_KEY = "0208ba7f74f919e0411ff251ce738b7f"
location = darksky.forecast(API_KEY, latitude, longitude)
weekday = datetime.date.today()
with location:
daily_sum = location.daily.summary
for i in daily_sum.split():
if (re.search(regex, i)):
numbers = re.findall(regex_num, i)
temperature = numbers[0] + numbers[1]
new_temp = convert_units(int(temperature), 2)
daily_sum = daily_sum.replace(i, new_temp)
requested_forecast.append(daily_sum)
for day in location.daily:
day = dict(day=datetime.date.strftime(weekday, '%a'),
sum=day.summary,
temp_min=convert_units(day.temperatureMin),
temp_max=convert_units(day.temperatureMax))
requested_forecast.append(
'{day}: {sum} Temp Range: {temp_min} - {temp_max}'.format(
**day)) # **kwargs for passing keyworded data
weekday += datetime.timedelta(days=1)
return requested_forecast
def seven_days_forecast(coordinates):
try:
with forecast(API_KEY, *coordinates, units='si') as city_forecast:
return (city_forecast['daily']['data'])
except (Exception):
print("API request error!")
raise
def main():
#now = datetime.now().strftime("%H:%M:%S")
#log into database
db = MySQLdb.connect(
'localhost', # The Host
'BaseUser', # username
'password', # password
'mydb') # name of the data base
cursor = db.cursor()
#get mountain info
coordinates = getCoordinates()
MID = 1
#update each mountain's hourly and daily
for mountain in coordinates:
weather = forecast(DARK_SKY_KEY, mountain[1], mountain[2])
updateHourly(db, cursor, MID, weather.hourly)
updateDaily(db, cursor, MID, weather.daily)
MID += 1
print("Updated " + mountain[0])
print("Database successfully updated!")
cursor.close()
def get_forecast(self, last_update_time):
if (time.time() - last_update_time) > config.DS_CHECK_INTERVAL:
syslog.syslog("Fetching update from DarkSky")
try:
self.weather = forecast(config.DS_API_KEY,
config.LAT,
config.LON,
exclude='minutely',
units=config.UNITS,
lang=config.LANG)
sunset_today = datetime.datetime.fromtimestamp(
self.weather.daily[0].sunsetTime)
if datetime.datetime.now() < sunset_today:
index = 0
sr_suffix = 'today'
ss_suffix = 'tonight'
else:
index = 1
sr_suffix = 'tomorrow'
ss_suffix = 'tomorrow'
self.sunrise = self.weather.daily[index].sunriseTime
self.sunrise_string = datetime.datetime.fromtimestamp(
self.sunrise).strftime("%I:%M %p {}").format(sr_suffix)
self.sunset = self.weather.daily[index].sunsetTime
self.sunset_string = datetime.datetime.fromtimestamp(
self.sunset).strftime("%I:%M %p {}").format(ss_suffix)
# start with saying we don't need an umbrella
self.take_umbrella = False
icon_now = self.weather.icon
icon_today = self.weather.daily[0].icon
if icon_now == 'rain' or icon_today == 'rain':
self.take_umbrella = True
else:
# determine if an umbrella is needed during daylight hours
curr_date = datetime.datetime.today().date()
for hour in self.weather.hourly:
hr = datetime.datetime.fromtimestamp(hour.time)
sr = datetime.datetime.fromtimestamp(
self.weather.daily[0].sunriseTime)
ss = datetime.datetime.fromtimestamp(
self.weather.daily[0].sunsetTime)
rain_chance = hour.precipProbability
is_today = hr.date() == curr_date
is_daylight_hr = hr >= sr and hr <= ss
if is_today and is_daylight_hr and rain_chance >= .25:
self.take_umbrella = True
break
except requests.exceptions.RequestException as e:
print('Request exception: ' + str(e))
return False
except AttributeError as e:
print('Attribute error: ' + str(e))
return False
return round(time.time()) # new last_update_time
return last_update_time
def test_pickle(self):
location = -77.843906, 166.686520 # McMurdo station, antarctica
# This doesn't actually hit the API since we mocked out the request lib
forecast = darksky.forecast('test_key', *location)
# Make sure we got the right data, via our mock
self.assertEqual(forecast.currently.temperature, -23.58)
# Ensure pickling by actually pickling
with open('./forecast.pickle', 'wb') as outfile:
pickle.dump(forecast, outfile)
# Check that the file exists
self.assertTrue(os.path.exists('./forecast.pickle'))
def _get_weather(self, request, force_update, weather_cookie):
"""Get Current Weather Based on IP Address
Based on the current ip location, getthe current weather (or use NY if location
is not available.) Save that data to a cookie to reduce # of api calls.
Arguments:
request -- A Flast Request
force_update {bool} -- Should we force update the weather data
weather_cookie -- Stored weather data
"""
# Get current weather for location based on IP
if weather_cookie and not force_update:
from_cookie = True;
current_weather = json.loads(weather_cookie)
else:
from_cookie = False
# fallback latitute/longitude data
test_latlngs = {
'newyork': [40.7081, -73.9571],
'hawaii': [19.8968, 155.5828],
'trinidad': [10.65, -61.5167],
'sweden': [60.1282, 18.6435],
'australia': [25.2744, 133.7751],
}
default_latlng = test_latlngs['newyork']
# Get the visitors IP and lat/lng for that IP
ip = request.headers.get('X-Forwarded-For', request.remote_addr)
geo = geocoder.ip(ip) if ip != '127.0.0.1' else None
lat, lng = geo.latlng if geo and len(geo.latlng) == 2 else default_latlng
# Use Darksky to get the current forcast for that lat/lng
geo_forecast = forecast(FORECAST_KEY, lat, lng)
# Get and format the current weather
daily_weather = geo_forecast['daily']['data'][0]
current_weather = geo_forecast['currently']
current_weather['timezone'] = geo_forecast['timezone']
current_weather['units'] = geo_forecast['flags']['units'] # F or C
current_weather['sunriseTime'] = daily_weather['sunriseTime']
current_weather['sunsetTime'] = daily_weather['sunsetTime']
current_weather['ip'] = ip
current_weather['lat_lng'] = [lat, lng]
return {'current': current_weather, 'from_cookie': from_cookie}
