aeronavx 0.3.0

Production-grade airport data and flight geometry library

AeroNavX

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

🆕 v0.3.0: Now with 47,000+ runways and comprehensive aviation statistics!

Features

• 🛫 Airport Database: 84,000+ global airports with efficient IATA/ICAO indexing
• 🛬 Runway Information: 47,000+ runways with dimensions, surfaces, and lighting data
• 📊 Aviation Statistics: Country, continent, and global aviation analytics
• 📏 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
• ⏰ 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
nearest = aeronavx.nearest_airport(41.0, 29.0, n=5)

# 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

Runway Information

import aeronavx

# Get all runways for an airport
runways = aeronavx.get_runways_by_airport("KJFK")
for rwy in runways:
    print(f"{rwy.designation}: {rwy.length_ft:.0f}ft, {rwy.surface}")

# Get the longest runway
longest = aeronavx.get_longest_runway("KJFK")
print(f"Longest: {longest.designation} - {longest.length_ft:.0f}ft")

# Get only paved runways
paved = aeronavx.get_paved_runways("KJFK")
print(f"Paved runways: {len(paved)}")

Aviation Statistics

import aeronavx

# Global statistics
stats = aeronavx.get_global_stats()
print(f"Total airports: {stats.total_airports:,}")
print(f"Total runways: {stats.total_runways:,}")
print(f"Countries: {stats.countries_count}")
print(f"Longest runway: {stats.longest_runway_ft:,.0f} ft")

# Country statistics
us_stats = aeronavx.get_country_stats("US")
print(f"US has {us_stats.total_airports:,} airports")
print(f"Large airports: {us_stats.large_airports}")
print(f"Total runways: {us_stats.total_runways:,}")

# Continent statistics
eu_stats = aeronavx.get_continent_stats("EU")
print(f"Europe: {eu_stats.total_airports:,} airports")
print(f"Countries: {eu_stats.countries_count}")

# Top countries
top = aeronavx.get_top_countries_by_airports(5)
for country, count in top:
    print(f"{country}: {count:,} airports")

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 and 47,000+ runways from OurAirports, which provides:

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

Data Attribution: Airport and runway 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.