weather_api/utils.py
Argiris Deligiannidis 2050391f4d
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2024-04-15 02:13:28 +03:00

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Python

from models import Location, Users, Config
from db_connector import database,engine,db_session
import pandas as pd
import openmeteo_requests
import requests_cache
import requests
from retry_requests import retry
def initialize_database():
"""
A function to initialize the database by checking table availability and creating it if it does not exist.
"""
db_session.add(Users(name="Argiris Deligiannidis",email="mai@argideli.com"))
db_tables = ['locations']
# check table availability and create it if it does not exist
for tb in db_tables:
if not engine.dialect.has_table(engine.connect(), tb):
print("\t*** Creating tables ***")
database.metadata.create_all(engine)
table_data = pd.read_csv ('./table_data/locations.csv', index_col=None, header=0)
for idx in range(len(table_data)):
location = {
'id': idx+1,
'name': table_data.loc[idx, "Capital City"],
'country': table_data.loc[idx, "Country"],
'latitude': float(table_data.loc[idx, "Latitude"]),
'longitude': float(table_data.loc[idx, "Longitude"]),
'user': 'bootstrap',
}
add_location(location, no_commit=True)
db_session.commit()
def get_database_locations(user=None):
"""
Retrieve locations from the database for a specified user, or all locations if no user is specified.
"""
if user is not None:
locations = db_session.query(Config).filter(Config.user_id == user).all()
else:
locations = db_session.query(Location).all()
return locations
def get_max_id():
"""
A function to retrieve the maximum ID from the Location table in the database.
"""
return max([id[0] for id in db_session.query(Location.id).all()])
def get_available_ids(id_num):
"""
Function to generate a list of available IDs based on existing IDs in the database.
Parameters:
id_num (int): The number of IDs to generate.
Returns:
List[int]: List of available IDs.
"""
db_ids = [id[0] for id in db_session.query(Location.id).all()]
avail_ids = [loc for loc in range(max(db_ids)+1) if loc not in db_ids and loc != 0]
for i in range(id_num-len(avail_ids)):
if avail_ids != []:
avail_ids.append(max(avail_ids)+1)
else:
avail_ids.append(max(db_ids)+1)
return avail_ids
def add_location(location, no_commit=False):
"""
A function that adds a location to the database session.
Parameters:
location (Location): The location object to be added to the database session.
no_commit (bool): Flag indicating whether to commit the transaction immediately.
"""
if location["name"] != 'existing':
db_session.add(Location(id=location["id"],
name=location["name"],
country=location["country"],
latitude=location["latitude"],
longitude=location["longitude"],
)
)
if not no_commit:
db_session.commit()
if location["user"] != 'bootstrap':
db_session.add(Config(user_id=location["user"],location_id=location["id"]))
no_commit == False
def config_disable_location(id, user):
"""
A function that disables a location configuration based on the provided ID and user.
Parameters:
id (int): The ID of the location to be disabled.
Returns:
None
"""
db_session.query(Config).filter(Config.location_id == id and Config.user_id == user).delete()
db_session.commit()
def delete_location(id):
"""
Deletes a location from the database based on the provided ID.
Parameters:
id (int): The ID of the location to be deleted.
Returns:
dict: A dictionary with the key "id" indicating that the location was successfully deleted.
"""
db_session.query(Config).filter(Config.location_id == id).delete()
db_session.commit()
db_session.query(Location).filter(Location.id == id).delete()
db_session.commit()
return {"id": "Deleted"}
def chunkify_data(data, chunk_size):
"""
A function to split data into chunks of a specified size for processing.
Parameters:
- data: The input data to be chunked.
- chunk_size: The size of each chunk to split the data into.
Returns:
- A generator that yields chunks of the data based on the specified chunk size.
"""
#NOTE bulk operation: Open Weather api has an upper limit of ~= 180 parameters for a request per second
# so we will split the requests into chunks of 100 parameters
for i in range(0, len(data), chunk_size):
yield data[i:i + chunk_size]
def retrieve_weather_data(location_id=None):
"""
A function to retrieve weather data based on location IDs.
Parameters:
- location_id: an optional parameter to specify the location ID(s) to retrieve weather data for. If 'all' is provided, data for all locations is returned.
Returns:
- If location_id is not 'all' and any specified location ID does not exist, a dictionary of invalid location IDs is returned.
- If location_id is None, None is returned.
- If location_id is 'all', weather data for all locations is returned in a dictionary.
- Otherwise, weather data for the specified location IDs is returned in a dictionary.
"""
max_id = get_max_id()
#NOTE: Disable location check if location_id is 'all' (returns all locations), debugging purposes
if location_id != 'all':
loc_check = {}
for loc_id in location_id:
if loc_id > max_id:
loc_check[loc_id] = "The location does not exist"
if len(loc_check) > 0:
return {'error': loc_check}
weather_data = {}
#NOTE: Get weather data for all locations if location_id is 'all' (debugging purposes), otherwise get weather data for specified locations
if location_id == 'all':
locations = list(chunkify_data(db_session.query(Location).all(),100))
else:
locations = list(chunkify_data(db_session.query(Location).filter(Location.id.in_(location_id)).all(),100))
for chunk in locations:
coordinates = []
for i in range(len(chunk)):
ids = get_available_ids(len(chunk))
coordinates.append([chunk[i].id, chunk[i].latitude, chunk[i].longitude, chunk[i].name])
weather_data.update(get_openmeteo_data(coordinates))
return weather_data
def get_openmeteo_data(coordinates):
"""
Retrieves weather data from the OpenMeteo API for the given coordinates.
Parameters:
coordinates (list): List of tuples containing latitude, longitude, and location name.
Returns:
dict: A dictionary containing the retrieved weather data for each location.
"""
data_dict = {}
cache_session = requests_cache.CachedSession('.cache', expire_after = 3600)
retry_session = retry(cache_session, retries = 5, backoff_factor = 0.2)
openmeteo_client = openmeteo_requests.Client(session = retry_session)
latitude = [coords[1] for coords in coordinates]
longitude = [coords[2] for coords in coordinates]
# NOTE: Uncomment to get all available weather data for each location
# data_names = [
# "weather_code", "temperature_2m_max", "temperature_2m_min",
# "apparent_temperature_max", "apparent_temperature_min",
# "sunrise", "sunset", "daylight_duration", "sunshine_duration",
# "uv_index_max", "uv_index_clear_sky_max", "precipitation_sum",
# "rain_sum", "showers_sum", "snowfall_sum", "precipitation_hours",
# "precipitation_probability_max", "wind_speed_10m_max",
# "wind_gusts_10m_max", "wind_direction_10m_dominant",
# "shortwave_radiation_sum", "et0_fao_evapotranspiration"
# ]
current_names = ["weather_code", "temperature_2m", "rain", "precipitation", "showers"]
data_names = ["weather_code", "temperature_2m_max", "temperature_2m_min", "rain_sum"]
#NOTE: OpenMeteo API has a limit of 10000 requests per day,
# so in a production environment it would be wise to change to
# an enterprise account OR utilize the clients for the requests
url = "https://api.open-meteo.com/v1/forecast"
params = {
"latitude": latitude,
"longitude": longitude,
"current": current_names,
"daily": data_names
}
responses = openmeteo_client.weather_api(url, params=params)
for idx, response in enumerate(responses, start=1):
location = coordinates[idx-1][3]
idx = coordinates[idx-1][0]
current = response.Current()
#set rain to max of the available openmeteo result variables
max_rain = max([float(current.Variables(2).Value()),
float(current.Variables(3).Value()),
float(current.Variables(3).Value())])
current_data = {"weather_code": current.Variables(0).Value(), "temperature_2m": current.Variables(1).Value(), "rain": max_rain}
daily = response.Daily()
daily_data = {}
daily_data.update({ variable: daily.Variables(i).ValuesAsNumpy().tolist()
if variable not in ["sunrise", "sunset"]
else daily.Variables(i).ValuesAsNumpy()
for i, variable in enumerate(data_names)
})
dates = pd.date_range(start = pd.to_datetime(daily.Time(), unit = "s", utc = True),
end = pd.to_datetime(daily.TimeEnd(), unit = "s", utc = True),
freq = pd.Timedelta(seconds = daily.Interval()),
inclusive = "left").tolist()
daily_data["date"] = [date.strftime("%d/%m/%Y") for date in dates]
location_data = {
"id": idx,
"name": location,
"coordinates": [response.Latitude(), response.Longitude()]
}
data_dict[idx] = {
"id": idx,
"data": {
"location": location_data,
"current": current_data,
"daily": daily_data
}
}
return data_dict
def search_location(query):
"""
Retrieve location data based on the provided query string.
Parameters:
query (str): The query string used to search for locations.
Returns:
A dictionary containing location data with an index as the key and location information as the value.
"""
URL="https://geocoding-api.open-meteo.com/v1/search"
PARAMS = {
"name": query,
"count": 10,
"language": 'en',
"format": 'json'
}
response = requests.get(url = URL, params = PARAMS)
data_dict={}
try:
for idx,d in enumerate(response.json()['results']):
data_dict[idx] = d
data_dict[idx].update({'selected': False})
except KeyError:
data_dict[0] = {'result': 'Error'}
return data_dict