def login(self):
if self.login_data["apikey"] :
self.api = Api(self.login_data["apikey"])
else :
warnings.warn('MWP_WARNING. The "%s" Weather Package(WP) has not been \
properly activated due to the apikey' % (self.name.upper()))
def __init__(self):
self.properties = {}
with open(WeatherAgent.__props_path__, "r") as props:
self.properties = json.load(props)
self.weatherbit_key = self.properties["weatherbit_api_key"]
self.weather_api = Api(self.weatherbit_key)
def __init__(self, api_key=None):
self.weather_condition_templates = {
"precipitation": {
"chance": " there is a %s per cent chance of precipitation ",
"snow": "with a possible % inches of snow "
},
"hi_lo": {
"general":
" with a high of %s degrees and a low of %s degree celsius",
"average": " an average temperature of %s degree celsius"
},
"conditions": {
"general": "will be %s",
"general_hr": "The weather %s will be %s"
}
}
if api_key is None:
self.api_key = "b09681fb4107467b9563c75a73f1a4a1"
self.api = Api(self.api_key)
'{0} will be enjoying some nice 69°F weather today'
]
# A thread-safe task queue that stores actions to perform against Reddit
task_queue = SimpleQueue()
# Config the logger
logging.basicConfig(filename='weather_output.log',
filemode='w',
level=logging.INFO)
# Set up the weather API for later usage
config = configparser.ConfigParser()
config.read('weather_api.ini')
api_key = config['weatherbit.io']['api_key']
weather_api = Api(api_key)
weather_api.set_granularity('daily')
# Load locations to check from stored CSV file
locations = []
with open('top_150_cities.csv', newline='') as csvfile:
reader = csv.DictReader(csvfile, fieldnames=['city', 'region', 'id'])
for row in reader:
locations.append(row)
# Setup Reddit Connection
reddit = praw.Reddit(
'niceweatherbot',
user_agent='python:niceweatherbot:v1.0.0 (by u/jakekarnes42)')
# Create a thread pool
from machine import Pin
from time import localtime, sleep
from weatherbit.api import Api
import threading
api_key = "key"
lat = 49.44684
lon = 8.357229999999959
api = Api(api_key)
api.set_granularity('daily')
class MQTT_subcriber(): #Class for controlling the ESP
pass
def auto_water(
): #This function looks what the forecast says and let flow enough water for everything
pass
def manuell(): #function for manuell control e.g. if it is not enough water
pass
threading.Thread(target=auto_water).start()
threading.Thread(target=manuell).start()
def IvyAbility(command):
#open website function/ability
if "open reddit" in command:
reg_ex = re.search('open reddit (.*)', command)
url = 'https://www.reddit.com/'
if reg_ex:
subreddit = reg_ex.group(1)
url = url + 'r/' + subreddit
webbrowser.open(url)
IvyResponse("Your cool shit reddit site has openned for you")
elif 'open google' in command:
reg_ex = re.search('open google(.*)', command)
url = 'https://www.google.co.uk/'
webbrowser.open(url)
IvyResponse("Your requested website has opened for you")
elif 'open' in command:
reg_ex = re.search('open(.*)', command)
if reg_ex:
domain = reg_ex.group(1)
url = 'https://www.' + domain
webbrowser.open(url)
IvyResponse('Opened')
elif 'google' in command:
reg_ex = re.search('google(.*)', command)
if reg_ex:
domain = reg_ex.group(1)
url = 'https://www.google.com/search?q=' + domain
webbrowser.open(url)
IvyResponse("I has searched your requested on website. Take a look at what I found")
else:
pass
#find weather and weather forecast function/ability
elif 'current weather in' in command:
reg_ex = re.search('current weather in (.*)', command)
if reg_ex:
city = reg_ex.group(1)
owm = OWM(API_key='37a0944f43b76456cbc580615fe4c676')
obs = owm.weather_at_place(city)
w = obs.get_weather()
k = w.get_status()
x = w.get_temperature(unit='celsius')
IvyResponse('Current weather in %s is %s. The maximum temperature is %0.2f and the minimum temperature is %0.2f degree celcius' % (city, k, x['temp_max'], x['temp_min']))
elif 'weather forecast in' in command:
reg_ex = re.search('weather forecast in (.*)', command)
if reg_ex:
api_key = 'fb14f083b77e4c99baf4f4b6e1d8c50d'
api = Api(api_key)
location = reg_ex.group(1)
IvyResponse('How many days you want to forecast?')
day_of_forecast = myCommand()
forecast = api.get_forecast(days = day_of_forecast, city = location)
forecast_list = forecast.get_series(['temp','max_temp','min_temp','weather'])
IvyResponse("The weather forecast for " + str(location))
weather_data = []
for forecast in forecast_list:
weather_data.append(f''' On {forecast['datetime'] : %d %B %Y},
the weather is {forecast['weather']['description']}. The temperature will be {forecast['temp']} celsius degree
with maximum temperature will be {forecast['max_temp']} and minimum temperature will be {forecast['min_temp']}
'''
)
b = ''.join(weather_data)
IvyResponse(b)
#send email/mail funcion
elif 'email' in command or 'mail' in command:
IvyResponse("Who is the recipient?")
recipient = myCommand()
if "john" in recipient or "david" in recipient:
recipient_mail_add = '*****@*****.**'
elif "mine" in recipient or "my" in recipient:
IvyResponse("You meant Mai, isn't it?")
y_n = myCommand()
if 'yes' in y_n or 'yeah' in y_n:
recipient_mail_add = '*****@*****.**'
else:
pass
else:
IvyResponse("What is his or her mail address please?")
recipient_mail_add = myCommand()
IvyResponse('What is the subject of this email please?')
subject_mail = myCommand()
IvyResponse('What do you want to say in the email?')
body = myCommand()
IvyResponse('Do you want to attach anything to the mail?')
att_ans = myCommand()
if 'yes' in att_ans or 'yea' in att_ans:
IvyResponse('What do you want to send sir?')
file = myCommand()
if 'song' in file:
path = '/Users/baileyvu/Desktop/Bad Guy - Billie Eilish_Justin Bieber.m4a'
file_name = path
IvyResponse('Sending email through Gmail')
elif 'ivy' in file:
path = '/Users/baileyvu/Desktop/test_7.py'
file_name = path
IvyResponse('Sending email though gmail')
try:
yag = yagmail.SMTP('*****@*****.**')
yag.send(
to=recipient_mail_add,
subject=subject_mail,
contents=body,
attachments=file_name)
IvyResponse('Mail sent')
except sr.UnknownValueError:
IvyResponse('I can\'t understand what you mean!')
else:
IvyResponse('Sending your requested Mail')
try:
yag = yagmail.SMTP('*****@*****.**')
yag.send(
to=recipient_mail_add,
subject=subject_mail,
contents=body
)
IvyResponse('Mail sent')
except sr.UnknownValueError:
IvyResponse('I can\'t understand what you mean!')
#'tell me about' function
elif 'tell me about' in command:
reg_ex = re.search('tell me about (.*)', command)
try:
if reg_ex:
topic = reg_ex.group(1)
ny = wikipedia.page(topic)
detail = ny.content[:1000].encode('utf-8')
IvyResponse(str(detail))
except Exception as e:
IvyResponse(e)
#telling time function
elif 'time' in command:
now = datetime.datetime.now()
format_time = '%I:%M %p'
ans1 = 'It is ' + now.strftime(format_time) + ' at the moment.'
ans2 = 'Current time is ' + now.strftime(format_time)
IvyResponse(random.choice([ans1, ans2]))
elif 'what day is' in command:
reg_ex = re.search('what day is (.*)', command)
try:
if reg_ex:
dt = reg_ex.group(1)
time_format = datetime.datetime.strptime(dt, '%d %B %Y')
tf = datetime.datetime.strftime(time_format, '%d/%-m/%Y')
day, month, year = (int(x) for x in tf.split('/'))
ans = datetime.date(year, month, day)
IvyResponse(' It is ' + ans.strftime("%A") + ' on ' + dt)
except Exception as e:
now = datetime.datetime.now()
format_day = '%A %d %B, %Y'
IvyResponse('Today is ' + now.strftime(format_day))
#open application
elif 'launch' in command:
reg_ex = re.search('launch\s(.*)', command)
if reg_ex:
appname = reg_ex.group(1)
appname1 = appname + ".app"
subprocess.Popen(["open", "-n", "/Applications/" + appname1], stdout=subprocess.PIPE)
IvyResponse("I have launch the application as you wanted, No thanks needed!")
#Using wolframalpha to calculate, tell weather in a specific city + specific day.
elif 'calculate' in command:
app_id = "PUK3TX-59QXTTY2EY"
client = wolframalpha.Client(app_id)
indx = command.lower().split().index('calculate')
query = command.split()[indx +1:]
res = client.query(' '.join(query))
answer = next(res.results).text
IvyResponse("The answer is " + answer)
return
elif 'information' in command:
IvyResponse('What do you need to know, ' + name + '?')
ans = myCommand()
if 'specific' in str(ans) or 'temperature' in str(ans):
IvyResponse("Where to, sir?")
temp_location = myCommand()
IvyResponse('Which day?')
temp_time = myCommand()
IvyResponse('On it! Give me a sec')
app_id = "PUK3TX-59QXTTY2EY"
client = wolframalpha.Client(app_id)
res = client.query('temperture in ' + temp_location + ' on ' + temp_time)
answer = next(res.results).text
IvyResponse("It is " + answer)
else:
pass
print('''\n--Something's up!! {} not in {}'''.format(
model_best_cv, [model_best_val, model_best_test]))
print('--Best model in CV not best in val and in test datasets/n')
# plot metrics
# df_metrics.pivot(index='df', columns='model', values='MSE').plot()
# df_metrics.dtypes
# get datetime column from date and period by mapping time and period with "df_map_HH_Period"
# plt.scatter(x = df_train['pred.GradBoostRegr'], y = df_train['dmd_coeff'])
###################################################################################################################################################
################
#### Step 5 ####
################
from weatherbit.api import Api # pip install pyweatherbit
api_call = Api(key_API_WeatherFct)
api_call.set_granularity('daily') # 'hourly', '3hourly'
df_weather_Fct = pd.DataFrame()
for iCity in list_cities:
print('{}: Downloading Weather Forecast for {}'.format(
ddt.now().strftime('%d%b%Y %H:%M:%S:'), iCity))
tmp_df_weather_fct = pd.DataFrame(
api_call.get_forecast(city=iCity, country='GB').get_series(
['temp', 'max_temp', 'min_temp', 'precip']))
tmp_df_weather_fct['City'] = iCity
df_weather_Fct = df_weather_Fct.append(tmp_df_weather_fct)
# simple daily average; more accurate would be to have a population- or other-weighted average temperature; other measure for wind speed
df_weather_Fct_avg = df_weather_Fct[[
'datetime', 'temp'
]].groupby('datetime').mean().reset_index()
df_weather_Fct_avg['date'], df_weather_Fct_avg['time'] = df_weather_Fct_avg[
def store_to_db(lat, lon, start_date, end_date, db_name, db_password, db_user,
db_host):
"""
Queries the weatherbit using API/requests to retrieve information from desired <start_date> to <end_date>
and stores in weather table.
:param lat: lattitude coordinate
:param lon: longtitude coordinate
:param start_date: date object
:param end_date: date object
:return void:
"""
api_key = os.environ.get('API_KEY')
api = Api(api_key)
try:
start_date = datetime.strptime(start_date, '%Y-%m-%d')
end_date = datetime.strptime(end_date, '%Y-%m-%d')
conn = psycopg2.connect(dbname=db_name,
password=db_password,
user=db_user,
host=db_host)
cur = conn.cursor()
if start_date < end_date:
for n in range((end_date - start_date).days):
sdate = start_date + timedelta(n)
edate = start_date + timedelta(n + 1)
# Using an API Wrapper
# api.set_granularity('daily')
# history = api.get_history(lat=lat, lon=lon, start_date=str(sdate.date()), end_date=str(edate.date()))
# print(history.get_series(['temp','min_temp','max_temp', 'min_temp_ts', 'max_temp_ts']))
## Using the API directly
response = requests.get(
"https://api.weatherbit.io/v2.0/history/daily?lat=" +
str(lat) + "&lon=" + str(lon) + "&start_date=" +
str(sdate.date()) + "&end_date=" + str(edate.date()) +
"&key=" + api_key)
if response.status_code == 200:
query = """ INSERT INTO weather (lat, lon, mean_temp, min_temp, min_temp_time, max_temp, max_temp_time) VALUES (%s,%s,%s,%s,%s,%s,%s) """
# query = """ INSERT INTO test_weather (lat, lon, mean_temp, min_temp, min_temp_time, max_temp, max_temp_time) VALUES (%s,%s,%s,%s,%s,%s,%s) """
record = (lat, lon, response.json()["data"][0]["temp"],
response.json()["data"][0]["min_temp"],
datetime.fromtimestamp(
int(response.json()["data"][0]["min_temp_ts"]
)).strftime('%Y-%m-%d %H:%M:%S'),
response.json()["data"][0]["max_temp"],
datetime.fromtimestamp(
int(response.json()["data"][0]["max_temp_ts"]
)).strftime('%Y-%m-%d %H:%M:%S'))
cur.execute(query, record)
conn.commit()
conn.close()
except Exception as e:
print("Exiting store_to_db due to exception: ", e.__class__)
finally:
if conn:
cur.close()
conn.close()
from peewee import *
from raven import Client
from weatherbit.api import Api
load_dotenv(find_dotenv())
if os.environ.get('SENTRY_DSN'):
sentry = Client(os.environ.get('SENTRY_DSN'))
db = MySQLDatabase(os.environ.get("DB_NAME"),
user=os.environ.get("DB_USER"),
host=os.environ.get("DB_HOST"),
password=os.environ.get("DB_PASS"),
charset='utf8mb4')
weather_api = Api(os.environ.get('WEATHER_API_KEY'))
API_URL = 'http://data-mobility.brussels/geoserver/bm_bike/wfs?service=wfs&version=1.1.0&request=GetFeature&typeName=bm_bike:rt_counting&outputFormat=csv'
EXPORT_PATH = os.path.join(os.path.dirname(__file__), 'public/data.json')
API_TIMEOUT = os.environ.get("API_TIMEOUT", 30)
class BikeCounter(Model):
""" Contains the counting data, almost mimic the api fields """
class Meta:
""" Meta class for peewee db """
database = db
gid = TextField(default='')
device_name = TextField(default='')
road_nl = TextField(default='')
def weatherapi(year="2017"):
# variaveis e paths necessárias
api_key = "af22cf6a216a427fb88685100b43d048"
pathfolder = "Dataset" + str(year)
path = os.path.join("Ardidas" + str(year) + "final",
"ardidas" + str(year[-2:]) + ".shp")
sf = shapefile.Reader(path)
json_folder = check_jsonstats_folder("JsonApis")
verify_filename = "LastIndex_WeatherApi" + " " + str(year) + ".json"
jverifypath = os.path.join(json_folder, verify_filename)
json_requests = "Requests" + "_forKey_ " + f"{api_key}" + ".json"
jrequestspath = os.path.join(json_folder, json_requests)
timefile = "Last_time" + "_forKey_ " + f"{api_key}" + ".json"
jtimefilepath = os.path.join(json_folder, timefile)
jsonstring = "Last Iteration" + " " + str(year)
counter_requests = "Counter"
lastdate = "Lastdate"
verify = False
# verificar existência e extrair info de jsons de controlo
# controlo de nº de requests/ timestamp em que se atingiu esse limite/ ultimo index no momento paragem
my_file_index = Path(jverifypath)
my_file_requests = Path(jrequestspath)
my_file_lasttime = Path(jtimefilepath)
if my_file_requests.is_file():
with open(jrequestspath, "r") as file:
data_r = file.read()
file_dict = json.loads(data_r)
number_requests = file_dict[counter_requests]
else:
number_requests = 0
if my_file_lasttime.is_file():
with open(jtimefilepath, "r") as file:
data_t = file.read()
file_dict = json.loads(data_t)
last_date = file_dict[lastdate]
last_date_obj = datetime.strptime(last_date, "%d/%m/%Y %H:%M:%S")
delta = datetime.now() - last_date_obj
delta_in_sec = delta.total_seconds()
delta_in_hours = divmod(delta_in_sec, 3600)[0]
if delta_in_hours < 24:
sys.exit(
"Ainda não passou o periodo de espera para efetuar requests à api!"
)
else:
pass
else:
pass
if my_file_index.is_file():
with open(jverifypath, "r") as file:
data = file.read()
file_dict = json.loads(data)
index = file_dict[jsonstring]
else:
index = 0
api = Api(api_key)
# ciclo para percorrer a totalidade do dataset
for i in range(index, len(sf)):
if my_file_requests.is_file():
verify = verify_last_request_date(jrequestspath)
update_verify_jsontime(number_requests, jtimefilepath, verify)
shape = sf.shapeRecord(i)
pathjson = os.path.join(pathfolder, str(i))
filename = "Weather.json"
filepath = os.path.join(pathjson, filename)
longitude, latitude = centerpointshape(shape)
if int(year) == 2017:
DHInicio = shape.record.DHInicio
DHFim = shape.record.DHFim
else:
DHInicio = shape.record.data_inici
DHFim = shape.record.data_fim
# formatar data extraida do shapefile
date_format_str = '%Y-%m-%d %H:%M:%S.%f'
start = datetime.strptime(DHInicio, date_format_str)
final = datetime.strptime(DHFim, date_format_str)
# calculos para seleccionar o tipo de request a efetuar
delta = final - start
delta_in_sec = delta.total_seconds()
delta_in_hours = divmod(delta_in_sec, 3600)[0]
dias_completos = math.floor(delta_in_hours / 24)
num_horas_restantes = delta_in_hours - (24 * dias_completos)
initial_dateime = start + timedelta(hours=-1)
initial_date = initial_dateime.strftime("%Y-%m-%d:%H")
# primeiro caso
if delta_in_hours >= 24:
# parte relativa aos dias completos
for k in range(1, dias_completos + 1):
new_end = initial_dateime + timedelta(days=1)
new_end_date = new_end.strftime("%Y-%m-%d:%H")
filename = os.path.join(pathjson, f"{k}.json")
weather_request(api, latitude, longitude, initial_date,
new_end_date, filename)
number_requests += 1
initial_dateime = new_end
initial_date = initial_dateime.strftime("%Y-%m-%d:%H")
updatejsonrequest(number_requests, jrequestspath)
update_verify_jsontime(number_requests, jtimefilepath, verify)
# parte relativa às horas restantes
if num_horas_restantes != 0:
new_initial = start + timedelta(days=dias_completos, hours=-1)
new_initial_date = new_initial.strftime("%Y-%m-%d:%H")
temporal_dif = final - new_initial
temporal_dif_hours = temporal_dif.total_seconds() / 3600
if temporal_dif_hours < 24:
new_end = initial_dateime + timedelta(
hours=math.floor(temporal_dif_hours) + 1)
else:
new_end = initial_dateime + timedelta(
hours=math.floor(temporal_dif_hours))
new_end_date = new_end.strftime("%Y-%m-%d:%H")
filename = os.path.join(pathjson, f"{dias_completos + 1}.json")
weather_request(api, latitude, longitude, new_initial_date,
new_end_date, filename)
number_requests += 1
updatejsonrequest(number_requests, jrequestspath)
update_verify_jsontime(number_requests, jtimefilepath, verify)
# Merge dos jsons e posterior eliminação dos jsons temporários
listfiles = []
for file in os.listdir(pathjson):
if re.match(r"[0-9]+.json", file):
fpath = os.path.join(pathjson, file)
listfiles.append(fpath)
merge_json(listfiles, pathjson)
del_files(listfiles)
# segundo caso (no limite de durar 24 horas)
elif 22 <= delta_in_hours < 24:
final_plus_1day = start + timedelta(days=1, hours=-1)
end_date = final_plus_1day.strftime("%Y-%m-%d:%H")
weather_request(api, latitude, longitude, initial_date, end_date,
filepath)
number_requests += 1
# terceiro caso (última possibilidade)
else:
final_plus_2hours = final + timedelta(hours=1)
end_date = final_plus_2hours.strftime("%Y-%m-%d:%H")
weather_request(api, latitude, longitude, initial_date, end_date,
filepath)
number_requests += 1
# criação de dicionarios para json de controlo de index
json_dict = {jsonstring: i}
json_dict_exception = {jsonstring: 0}
"""
Escrita de ficheiro json para guardar index onde o programa parou ou reiniciar index se terminou o ciclo.
Por questão de segurança guarda o penúltimo indice para assegurar que a parte meteorológica do dataset
é gerada na sua totalidade e corretamente.
"""
if i < len(sf) - 1:
with open(jverifypath, 'w') as output:
json.dump(json_dict, output, indent=4)
else:
with open(jverifypath, 'w') as output:
json.dump(json_dict_exception, output, indent=4)
updatejsonrequest(number_requests, jrequestspath)
from weatherbit.api import Api
import config
api = Api(config.weatherbit_key)
class WeatherData:
def __init__(self, city, state):
self.city = city
self.state = state
def getPrecip(self):
api.set_granularity('daily')
forecast = api.get_forecast(city=self.city,
state=self.state,
country="US")
precip_forecast = forecast.get_series(['precip'])
print(precip_forecast)
def getWindSpeed(self):
api.set_granularity('daily')
forecast = api.get_forecast(city=self.city,
state=self.state,
country="US")
wind_spd_forecast = forecast.get_series(['wind_spd'])
print(wind_spd_forecast)
def getWindDir(self):
api.set_granularity('daily')
forecast = api.get_forecast(city=self.city,
state=self.state,
# Class for making Weatherbit API calls. This class will be instantiated as a
# singleton to gather all necessary information from the API.
from weatherbit.api import Api
import API_Key
import json
# Get the private key string from API_KEY.
api_key = API_Key.API_Key().Weatherbit_Key
# Authenticate our API Key. This variable will be used for all API calls.
weatherbit = Api(api_key)
# Set the API for retrieving the daily forecast.
weatherbit.set_granularity('daily')
# Gets the forecast for the current day.
# Params:
# lat: Float: The latitude of the city.
# long: Float: The longitude of the city.
# Return: List containing the precipitation, average temperature, and max
# temperature per hour from midnight to the current hour.
def get_daily_forecast(lat, long):
forecast = weatherbit.get_forecast(lat=lat, lon=long)
precip = forecast.json['data'][0]['precip']
precip = precip / 25.4 # Convert mm to inches
avg_temp = forecast.json['data'][0]['temp']
avg_temp = avg_temp * 1.8 + 32 # Convert Celsius to Fahrenheit
max_temp = forecast.json['data'][0]['max_temp']
max_temp = max_temp * 1.8 + 32
weather = [precip, avg_temp, max_temp]