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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
@lru_cache(maxsize=128)
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()
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