import requests
import pandas as pd
from datetime import datetime, timedelta


def get_historical_data(uid, field_id, date):
    endpointUrl = "https://us-central1-farmbase-b2f7e.cloudfunctions.net/requestPreviousSatelliteData"

    bodyObj = {
        "UID": uid,
        "FieldID": field_id,
        "RequestedDate": date,
    }

    response = requests.post(endpointUrl, json=bodyObj)

    print("Status code: ", response.status_code)

    return response


# Function to generate dates
def generate_dates(start_year, start_month, end_year, end_month):
    start_date = datetime(start_year, start_month, 1)
    end_date = datetime(end_year, end_month, 31)
    dates = []
    current_date = start_date
    while current_date <= end_date:
        if current_date.day in [1, 15]:
            dates.append(current_date.strftime("%Y%m%d"))
        current_date += timedelta(days=1)
    return dates


filename = "UUID_FieldID_coordinates.xlsx"
df3 = pd.read_excel(filename)
uid = "ipRHhCOFIDV2pxgg7Nfz1ufZBmV2"


# Generate dates for both periods
dates_2022_2023 = generate_dates(2022, 7, 2023, 1)
dates_2023_2024 = generate_dates(2023, 7, 2024, 1)


for index, row in df3.iterrows():
    print(row["Field ID"])
    field_id = row["Field ID"]

    for date in dates_2022_2023:
        get_historical_data(uid, field_id, date)
        #print(date)
    for date in dates_2023_2024:
        get_historical_data(uid, field_id, date)
        #print(date)
    #print("\n")

    #break