import requests
import datetime
import pandas as pd
from tempfile import tempdir
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
import traceback
import json
import numpy as np
from sklearn.cluster import KMeans
import traceback
import numpy as np
from google.cloud import storage
import requests
cred = credentials.Certificate('servicekey.json')

import json
import os

# Function to check if file exists
def check_file_exists(file_path):
    return os.path.isfile(file_path)
# s1_images = ["B02", "B03", "B04", "B05"]
#s2_images = ["RVI-NEW"]
try:
    firebase_admin.initialize_app(cred, {'databaseURL': 'https://farmbase-b2f7e-31c0c.firebaseio.com/'})
except:
    print('fire running')

def get_historical_weather(uuid, field_id, api_key, lat, lon, start_date, end_date, output_file):
    url = "http://api.weatherapi.com/v1/history.json"

    current_date = datetime.datetime.strptime(start_date, "%Y-%m-%d")
    end_date = datetime.datetime.strptime(end_date, "%Y-%m-%d")

    weather_data = []

    while current_date <= end_date:
        params = {
            "key": api_key,
            "q": f"{lat},{lon}",
            "dt": current_date.strftime("%Y-%m-%d")
        }

        response = requests.get(url, params=params)

        if response.status_code == 200:
            data = response.json()
            day_data = data['forecast']['forecastday'][0]['day']
            weather_data.append({
                "date": current_date.strftime("%Y-%m-%d"),
                "uuid": uuid,
                "field_id":field_id,
                "lat":lat,
                "long":lon,
                "rainfall_mm": day_data['totalprecip_mm'],
                "avg_temp_c": day_data['avgtemp_c'],
                "max_temp_c": day_data['maxtemp_c'],
                "min_temp_c": day_data['mintemp_c']
            })
        else:
            print(f"Failed to retrieve data for {current_date.strftime('%Y-%m-%d')}: {response.status_code}, {response.text}")

        current_date += datetime.timedelta(days=1)

    # Create a DataFrame and save it as an Excel file
    df = pd.DataFrame(weather_data)
    df.to_excel(output_file, index=False)

    print(f"Weather data saved to {output_file}")

with open('Downloads/ifpri_filtered_sheet.json', 'r') as file:
        ifpri_json = json.load(file)

uid = 'ipRHhCOFIDV2pxgg7Nfz1ufZBmV2'
ifpri_num = 0
w_start, w_end = 0, 2700
for single_field_obj in ifpri_json:
    ifpri_num = ifpri_num + 1
    try:
        print(single_field_obj)
        field_id = str(single_field_obj["FieldID"])
        uuid = single_field_obj["UUID"]
        output_file = f"ifpri_weather_sep/{uuid}_{field_id}_historical_weather.xlsx"
        print(field_id)
        print(uuid)
        print(ifpri_num)
        if check_file_exists(output_file):
            print('weather_processed_already')
            continue
        if ifpri_num < w_start or ifpri_num > w_end:
            continue
        latitude = db.reference('PaidMonitoredFields').child('PMF').child(uid).child(field_id).child('Coordinates').child('a').child('Latitude').get()
        longitude = db.reference('PaidMonitoredFields').child('PMF').child(uid).child(field_id).child('Coordinates').child('a').child('Longitude').get()
        # Example usage:
        api_key = "dd6e11f5d20e4694bed72932241007"
        start_date = "2022-07-01"
        end_date = "2024-01-31"
        output_file = f"ifpri_weather_sep/{uuid}_{field_id}_historical_weather.xlsx"
        get_historical_weather(uuid, field_id, api_key, latitude, longitude, start_date, end_date, output_file)
    except:
        print(traceback.format_exc())