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| import requests | |
| import itertools | |
| from geopy.distance import geodesic | |
| from functools import lru_cache | |
| # Replace with your OpenWeather API key | |
| API_KEY = '9811dd1481209c64fba6cb2c90f27140' | |
| # Interpolation function to get intermediate points between airports | |
| def get_intermediate_points(start, end, num_points=2): | |
| points = [] | |
| lat_step = (end[0] - start[0]) / (num_points + 1) | |
| lon_step = (end[1] - start[1]) / (num_points + 1) | |
| for i in range(1, num_points + 1): | |
| point = (start[0] + lat_step * i, start[1] + lon_step * i) | |
| points.append(point) | |
| return points | |
| # Fetch weather data for a given coordinate | |
| def fetch_weather(lat, lon): | |
| url = f'http://api.openweathermap.org/data/2.5/weather?lat={lat}&lon={lon}&appid={API_KEY}&units=metric' | |
| response = requests.get(url) | |
| return response.json() | |
| # Fetch weather along all possible routes | |
| def fetch_weather_for_all_routes(airport_identifiers, airports): | |
| route_factors = {} | |
| # Generate all possible routes (permutations) | |
| for route in itertools.permutations(airport_identifiers, len(airport_identifiers)): | |
| route_key = " -> ".join(route) # Key for route factors | |
| route_factors[route_key] = [] | |
| for i in range(len(route) - 1): | |
| start_airport = route[i] | |
| end_airport = route[i + 1] | |
| start_coords = (airports[start_airport][0], airports[start_airport][1]) | |
| end_coords = (airports[end_airport][0], airports[end_airport][1]) | |
| # Get 4 intermediate points along the route | |
| points = get_intermediate_points(start_coords, end_coords) | |
| # Include start and end airport coordinates | |
| points.insert(0, start_coords) | |
| points.append(end_coords) | |
| # Fetch weather for each point | |
| weather_descriptions = [] | |
| temperatures = [] | |
| for point in points: | |
| weather = fetch_weather(point[0], point[1]) | |
| weather_descriptions.append(weather['weather'][0]['description']) | |
| temperatures.append(weather['main']['temp']) | |
| # Aggregate weather for the route segment | |
| avg_temperature = sum(temperatures) / len(temperatures) | |
| most_common_weather = max(set(weather_descriptions), key=weather_descriptions.count) | |
| # Store the result in the route_factors dictionary for each route segment | |
| segment_key = f"{start_airport} -> {end_airport}" | |
| route_factors[route_key].append({ | |
| "segment": segment_key, | |
| "weather": most_common_weather, | |
| "temperature": round(avg_temperature, 2) | |
| }) | |
| return route_factors | |
| # # Example airport coordinates | |
| # airports = { | |
| # 'SIN': (1.3644, 103.9915), # Singapore Changi Airport | |
| # 'LAX': (33.9416, -118.4085), # Los Angeles International Airport | |
| # 'JFK': (40.6413, -73.7781), # John F. Kennedy International Airport | |
| # 'CDG': (49.0097, 2.5479), # Charles de Gaulle Airport | |
| # 'LHR': (51.4700, -0.4543) # London Heathrow Airport | |
| # } | |
| # airport_identifiers = ['SIN', 'LAX', 'JFK', 'CDG', 'LHR'] # Replace with actual identifiers | |
| # # Fetch the weather along all possible routes | |
| # route_weather = fetch_weather_for_all_routes(airport_identifiers, airports) | |
| # # Display the weather data for each route | |
| # for route, factors in route_weather.items(): | |
| # print(f"Route: {route}") | |
| # for factor in factors: | |
| # print(f" Segment: {factor['segment']}, Weather: {factor['weather']}, Temperature: {factor['temperature']} °C") | |
| # print() | |