aeronavx 2.0.2

Advanced Aviation Analytics: Network Intelligence, Synthetic Routes, Emissions v2, Geo-Spatial Analysis & Passenger Experience

AeroNavX

A production-grade Python library for airport data and flight geometry calculations.

🆕 v0.2.0: Now with 84,000+ airports from OurAirports (MIT License)

Features

• 🛫 Airport Database: 84,000+ global airports with efficient IATA/ICAO indexing
• 📏 Distance Calculations: Haversine, Vincenty, and Spherical Law of Cosines
• 🌍 Geodesy: Bearings, midpoints, great circle paths
• 🔍 Search: Fuzzy name search, nearest neighbor queries, radius search
• 🛤️ Routing: Multi-segment routes, flight time estimation, shortest paths
• 📊 Analytics: Statistics by country, continent, type, and elevation
• ⏰ Timezone Support: Automatic timezone detection and local time
• 🌱 Emissions: CO2 emissions estimation per passenger
• 🌤️ Weather: METAR and TAF data fetching
• 💻 CLI: Command-line interface for quick queries
• 🌐 REST API: FastAPI-based web service

Installation

pip install aeronavx

Or from source:

git clone https://github.com/teyfikoz/AeroNavX.git
cd AeroNavX
pip install -e .

Quick Start

import aeronavx

# Get airports
ist = aeronavx.get_airport("IST")
jfk = aeronavx.get_airport("JFK")

# Calculate distance
dist_km = ist.distance_to(jfk)
print(f"Distance: {dist_km:.2f} km")

# Find nearest airports (plural for multiple results)
nearest = aeronavx.nearest_airports(41.0, 29.0, n=5)
for airport in nearest:
    print(f"  {airport.iata_code}: {airport.name}")

# Or get single nearest airport
closest = aeronavx.nearest_airport(41.0, 29.0)
print(f"Closest: {closest.name}")

# Estimate emissions
co2 = aeronavx.estimate_co2_kg_for_segment("IST", "JFK")
print(f"CO2: {co2:.2f} kg per passenger")

Advanced: Filtering Airports

from aeronavx.core import loader

# Load only major airports (large + medium with scheduled service)
major_airports = loader.load_airports(
    include_types=['large_airport', 'medium_airport'],
    scheduled_service_only=True
)
print(f"Major airports: {len(major_airports):,}")  # ~3,200

# Load specific countries
us_airports = loader.load_airports(countries=['US'])
print(f"US airports: {len(us_airports):,}")  # ~20,000

# Load airports with IATA codes only
iata_airports = loader.load_airports(has_iata_only=True)
print(f"IATA airports: {len(iata_airports):,}")  # ~9,000

CLI Usage

# Calculate distance
aeronavx distance --from IST --to JFK --unit nmi

# Find nearest airports
aeronavx nearest --lat 41.0 --lon 29.0 --n 5

# Search by name
aeronavx search --name "Heathrow"

# Estimate emissions
aeronavx emissions --from IST --to LHR

# Flight time
aeronavx flight-time --from IST --to JFK

API Server

python -m aeronavx.api.server

Then access:

• http://localhost:8000/health
• http://localhost:8000/airport/IST
• http://localhost:8000/distance?from=IST&to=JFK
• http://localhost:8000/nearest?lat=41.0&lon=29.0&n=5

Data

AeroNavX includes 84,000+ airports from OurAirports, which provides:

• ✅ Global Coverage: Airports, heliports, seaplane bases, and more
• ✅ MIT License: Free to use commercially
• ✅ Regular Updates: Community-maintained and updated
• ✅ Comprehensive Data: IATA/ICAO codes, coordinates, types, and more

Data Attribution: Airport data from OurAirports (David Megginson et al.) - Licensed under MIT License

Examples

See examples/ directory for:

• basic_distance.py: Distance calculations
• nearest_airports.py: Finding nearby airports
• routing_example.py: Multi-segment routes
• emissions_example.py: CO2 estimation

Testing

pytest

Dependencies

Required: Python >= 3.10

Optional:

• pandas: DataFrame support
• scipy: Faster spatial indexing
• rapidfuzz: Better fuzzy search
• timezonefinder: Timezone support
• fastapi, uvicorn: API server
• requests: Weather data

License

MIT License

Contributing

Contributions welcome! Please open an issue or pull request.