import openmeteo_requests

import requests_cache
import pandas as pd
from retry_requests import retry


def download_historical_weather_data(
		latitude: float,
		longitude: float,
		start_year: int,
		end_year: int,
) -> pd.DataFrame:
	# Setup the Open-Meteo API client with cache and retry on error
	cache_session = requests_cache.CachedSession('.cache', expire_after = -1)
	retry_session = retry(cache_session, retries = 5, backoff_factor = 0.2)
	openmeteo = openmeteo_requests.Client(session = retry_session)

	# Make sure all required weather variables are listed here
	# The order of variables in hourly or daily is important to assign them correctly below
	url = "https://archive-api.open-meteo.com/v1/archive"
	params = {
		"latitude": latitude,
		"longitude": longitude,
		"start_date": f"{start_year}-01-01",
		"end_date": f"{end_year}-12-31",
		"daily": ["temperature_2m_max", "temperature_2m_min", "temperature_2m_mean",
				  "precipitation_sum", "precipitation_hours",
				  "shortwave_radiation_sum",
				  "et0_fao_evapotranspiration"],
		"timezone": "GMT"
	}
	responses = openmeteo.weather_api(url, params=params)

	# Process first location. Add a for-loop for multiple locations or weather models
	response = responses[0]
	print(f"Coordinates {response.Latitude()}°N {response.Longitude()}°E")
	print(f"Elevation {response.Elevation()} m asl")
	print(f"Timezone {response.Timezone()} {response.TimezoneAbbreviation()}")
	print(f"Timezone difference to GMT+0 {response.UtcOffsetSeconds()} s")

	# Process daily data. The order of variables needs to be the same as requested.
	daily = response.Daily()
	daily_temperature_2m_max = daily.Variables(0).ValuesAsNumpy()
	daily_temperature_2m_min = daily.Variables(1).ValuesAsNumpy()
	daily_temperature_2m_mean = daily.Variables(2).ValuesAsNumpy()
	daily_precipitation_sum = daily.Variables(3).ValuesAsNumpy()
	daily_precipitation_hours = daily.Variables(4).ValuesAsNumpy()
	daily_shortwave_radiation_sum = daily.Variables(5).ValuesAsNumpy()
	daily_et0_fao_evapotranspiration = daily.Variables(6).ValuesAsNumpy()

	daily_data = {
		"date": 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"
		),
		"temperature_2m_max": daily_temperature_2m_max,
		"temperature_2m_min": daily_temperature_2m_min,
		"temperature_2m_mean": daily_temperature_2m_mean,
		"precipitation_sum": daily_precipitation_sum,
		"precipitation_hours": daily_precipitation_hours,
		"shortwave_radiation_sum": daily_shortwave_radiation_sum,
		"et0_fao_evapotranspiration": daily_et0_fao_evapotranspiration
	}

	daily_dataframe = pd.DataFrame(data = daily_data)

	return daily_dataframe