app.py

import streamlit as st
import ee
from datetime import datetime

# Earth Engine Authentication
service_account = 'earth-engine-service-account@ee-esmaeilkiani1387.iam.gserviceaccount.com'
credentials = ee.ServiceAccountCredentials(service_account, 'ee-esmaeilkiani1387-1b2c5e812a1d.json')
ee.Initialize(credentials)

# Define a function to fetch historical temperature data
def get_historical_temperature(aoi, start_date, end_date):
    dataset = ee.ImageCollection("ECMWF/ERA5/DAILY") \
                .filterBounds(aoi) \
                .filterDate(start_date, end_date) \
                .select('mean_2m_air_temperature')
    
    # Calculate daily mean temperature (in Celsius)
    temp_collection = dataset.map(lambda image: image.subtract(273.15).rename('daily_mean_temp'))
    
    # Reduce the collection to mean values over the area
    mean_temp = temp_collection.mean().reduceRegion(
        reducer=ee.Reducer.mean(),
        geometry=aoi,
        scale=1000,
        bestEffort=True
    )
    return mean_temp.getInfo()

# Define the area of interest (AOI)
# Example: Assume aoi is defined based on user's GeoJSON or coordinates
aoi = ee.Geometry.Point([48.73168141056203, 31.53180450320103])  # Example coordinates for a specific farm location

# Set start and end dates
start_date = "2023-01-01"
end_date = "2023-12-31"

# Fetch and display temperature data
temp_data = get_historical_temperature(aoi, start_date, end_date)
st.write("Historical Temperature Data (°C):", temp_data['daily_mean_temp'])