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| import pandas as pd | |
| from flight_distance import * | |
| from optimizer import * | |
| from weather import * | |
| airport_identifiers = ['BLR', 'CCU', 'DEL'] # Replace with actual identifiers | |
| #Get Airport Coordinates | |
| lat_long_dict = get_airport_lat_long(airport_identifiers) | |
| print("Coordinates: \n",lat_long_dict) | |
| #Get Distance between each node (airports) | |
| trip_distance = calculate_distances(airport_identifiers) | |
| print("Distance b/w Airports: \n",trip_distance) | |
| #Get onroute weather | |
| raw_weather = fetch_weather_for_all_routes(airport_identifiers, lat_long_dict) | |
| route_factors = extract_route_factors(raw_weather) | |
| print("On Route weather: \n", raw_weather) | |
| # # Ensure the graph is bidirectional (undirected) | |
| for (a, b), dist in list(trip_distance.items()): | |
| trip_distance[(b, a)] = dist | |
| # Find the optimal route with the new cost metric | |
| optimal_route, optimal_distance = find_optimal_route(airport_identifiers, trip_distance, route_factors) | |
| # Display the optimal route and the total adjusted distance/cost | |
| print("Optimal Route:", " -> ".join(optimal_route) + f" -> {optimal_route[0]}") | |
| print("Total Adjusted Distance/Cost:", optimal_distance) | |