| import os | |
| import json | |
| import requests | |
| from flask import Flask, request, jsonify, send_from_directory | |
| from flask_cors import CORS | |
| # Configure Flask app | |
| app = Flask(__name__, static_folder='.') | |
| CORS(app) # Enable CORS for all origins | |
| # --- Open-Meteo API Configuration --- | |
| OPENMETEO_BASE_URL = "https://api.open-meteo.com/v1/forecast" | |
| WEATHER_VARIABLES = [ | |
| "temperature_2m", | |
| "relative_humidity_2m", | |
| "precipitation", | |
| "weathercode", | |
| "windspeed_10m", | |
| "windgusts_10m", | |
| "pressure_msl" | |
| ] | |
| DAILY_VARIABLES = [ | |
| "precipitation_sum", | |
| "temperature_2m_max", | |
| "temperature_2m_min" | |
| ] | |
| # --- Data Fetching Functions --- | |
| def get_weather_data(lat, lon): | |
| """Fetches current and recent weather data from Open-Meteo.""" | |
| try: | |
| params = { | |
| "latitude": lat, | |
| "longitude": lon, | |
| "current": ",".join(WEATHER_VARIABLES), | |
| "daily": ",".join(DAILY_VARIABLES), | |
| "past_days": 1, | |
| "timezone": "auto", | |
| "forecast_days": 1 | |
| } | |
| print(f"Fetching weather data for ({lat}, {lon})...") | |
| response = requests.get(OPENMETEO_BASE_URL, params=params) | |
| response.raise_for_status() # Raise an HTTPError for bad responses | |
| data = response.json() | |
| print("Weather data fetched successfully.") | |
| current = data.get('current', {}) | |
| daily = data.get('daily', {}) | |
| weather_info = { | |
| "source": "Open-Meteo API", | |
| "latitude": data.get('latitude'), | |
| "longitude": data.get('longitude'), | |
| "temperature_celsius_current": current.get('temperature_2m'), | |
| "temperature_celsius_max_daily": daily.get('temperature_2m_max', [None])[0], | |
| "temperature_celsius_min_daily": daily.get('temperature_2m_min', [None])[0], | |
| "humidity_percent_current": current.get('relative_humidity_2m'), | |
| "precipitation_mm_current": current.get('precipitation'), | |
| "precipitation_mm_past_24h": daily.get('precipitation_sum', [None])[0], | |
| "windspeed_kmh_current": current.get('windspeed_10m'), | |
| "windgusts_kmh_current": current.get('windgusts_10m'), | |
| "pressure_hpa_current": current.get('pressure_msl'), | |
| "weathercode_current": current.get('weathercode') | |
| } | |
| return weather_info | |
| except requests.exceptions.RequestException as e: | |
| print(f"Error fetching weather data: {e}") | |
| return {"error": "Could not fetch weather data", "details": str(e)} | |
| except Exception as e: | |
| print(f"An unexpected error occurred while processing weather data: {e}") | |
| return {"error": "An unexpected error occurred with weather data", "details": str(e)} | |
| def get_non_weather_data_simulated(lat, lon): | |
| """ | |
| Simulates getting non-weather data. | |
| This is still simplified based on rough India geography. | |
| """ | |
| lat = float(lat) | |
| lon = float(lon) | |
| data = { | |
| "source": "Simulated/Inferred Data", | |
| "latitude": lat, | |
| "longitude": lon, | |
| "elevation_meters": 50, # Base elevation | |
| "proximity_to_coast_km": 800, # Base distance | |
| "proximity_to_major_river_km": 200, # Base distance | |
| "soil_type": "general", | |
| "vegetation_density": "moderate", | |
| "historical_disaster_frequency": "medium", | |
| "population_density": "moderate" | |
| } | |
| # Adjust simulated data based on location approximations for India | |
| if 8 <= lat <= 37 and 68 <= lon <= 97: # Basic India bounds | |
| if lat > 28 or lon > 90: # Himalayan region, North East | |
| data["elevation_meters"] = 1500 + max(0, lat - 28)*100 + max(0, lon - 90)*50 | |
| data["soil_type"] = "mountainous/hilly" | |
| data["vegetation_density"] = "high" | |
| data["historical_disaster_frequency"] = "high (Landslides, Earthquakes, Floods)" | |
| data["proximity_to_major_river_km"] = min(data["proximity_to_major_river_km"], 10) if lat > 28 else data["proximity_to_major_river_km"] | |
| if 15 <= lat <= 25 and 70 <= lon <= 85: # Central India, Deccan | |
| data["elevation_meters"] = 500 + max(0, lat - 15)*30 | |
| data["soil_type"] = "black soil/plateau" | |
| data["vegetation_density"] = "moderate to low" | |
| data["historical_disaster_frequency"] = "medium (Droughts, Heatwaves, Wildfires)" | |
| data["population_density"] = "moderate to high" | |
| if lat < 22 and lon > 75: # South India, Coastal East/West | |
| east_coast_dist = abs(lon - 82) * 111 | |
| west_coast_dist = abs(lon - 74) * 111 | |
| data["proximity_to_coast_km"] = min(east_coast_dist, west_coast_dist, data["proximity_to_coast_km"]) | |
| data["elevation_meters"] = 50 + max(0, (22-lat)*10) | |
| data["soil_type"] = "coastal alluvial/laterite" | |
| data["historical_disaster_frequency"] = "high (Cyclones, Floods, Heatwaves)" | |
| data["population_density"] = "high" | |
| if lat > 25 and lon < 80: # North India, Gangetic plains | |
| data["elevation_meters"] = 50 + max(0, lat-25)*10 | |
| data["proximity_to_major_river_km"] = min(data["proximity_to_major_river_km"], 5) | |
| data["soil_type"] = "alluvial" | |
| data["historical_disaster_frequency"] = "high (Floods, Heatwaves, Droughts)" | |
| data["population_density"] = "very high" | |
| # Add some minor random variation | |
| import random | |
| data["elevation_meters"] = max(0, data["elevation_meters"] + random.randint(-10, 10)) | |
| data["proximity_to_coast_km"] = max(0, data["proximity_to_coast_km"] + random.randint(-20, 20)) | |
| data["proximity_to_major_river_km"] = max(0, data["proximity_to_major_river_km"] + random.randint(-5, 5)) | |
| return data | |
| # --- Flask Routes --- | |
| @app.route('/') | |
| def index(): | |
| return send_from_directory('.', 'index.html') | |
| # API endpoint to get location-based data (weather + simulated) | |
| @app.route('/get_location_data', methods=['POST']) | |
| def get_location_data(): | |
| data = request.get_json() | |
| lat = data.get('lat') | |
| lon = data.get('lon') | |
| if lat is None or lon is None: | |
| return jsonify({"error": "Latitude and Longitude are required"}), 400 | |
| try: | |
| # Get real weather data | |
| weather_data = get_weather_data(lat, lon) | |
| if "error" in weather_data: | |
| # If weather data fetch fails, return the error | |
| return jsonify({"error": f"Failed to get weather data: {weather_data['details']}"}), 500 | |
| # Get simulated non-weather data | |
| non_weather_data = get_non_weather_data_simulated(lat, lon) | |
| # Combine all data | |
| location_data = { | |
| "latitude": lat, | |
| "longitude": lon, | |
| "weather_data": weather_data, | |
| "non_weather_data": non_weather_data | |
| } | |
| # Return the combined data | |
| return jsonify(location_data) | |
| except Exception as e: | |
| print(f"An error occurred while getting location data: {e}") | |
| return jsonify({"error": f"An internal server error occurred: {str(e)}"}), 500 | |
| if __name__ == '__main__': | |
| # Run the Flask app | |
| # Change port if 5000 is in use | |
| app.run(debug=True, port=5000) |