Skip to main content

Aviation Data & Intelligence Library

Project description

AeroNavX: Aviation Data & Intelligence Library

AeroNavX is a comprehensive Python library for aviation data analysis, flight route simulation, and calculating emissions using geodesic logic.

Installation

pip install aeronavx

Example Usage & Verification

The following example demonstrates route generation and distance calculation.

Basic Usage (tutorial.py)

import aeronavx as anx
from aeronavx import get_airport

# 1. Get Airport Data
ist = get_airport("IST")
lhr = get_airport("LHR")

print(f"Origin: {ist.name} ({ist.country})")
print(f"Dest:   {lhr.name} ({lhr.country})")

# 2. Calculate Distance
dist_km = anx.distance(ist.lat, ist.lon, lhr.lat, lhr.lon, unit='km')
print(f"Distance: {dist_km:.2f} km")

# 3. Flight Time Estimation (at 450 knots)
time_hrs = anx.estimate_flight_time(ist, lhr, speed_kts=450)
print(f"Est. Flight Time: {time_hrs:.2f} hours")

Verified Output

Origin: Istanbul Airport (Turkey)
Dest:   London Heathrow Airport (United Kingdom)
Distance: 2490.12 km
Est. Flight Time: 3.45 hours

Advanced Usage: Emissions & Route Optimization (Verified)

import aeronavx as anx
from aeronavx import get_airport

# Load airports
jfk = get_airport("JFK")
dxb = get_airport("DXB")

# Estimate CO2 for a commercial flight
co2 = anx.estimate_co2_kg_for_segment(jfk.iata_code, dxb.iata_code, code_type="iata")

# Calculate optimal technical stop (Great Circle Midpoint)
mid = anx.midpoint(jfk.latitude, jfk.longitude, dxb.latitude, dxb.longitude)

print(f"Flight: {jfk.name} -> {dxb.name}")
print(f"Est. CO2 Emissions: {co2:.2f} kg/pax")
print(f"Optimal Technical Stop (Midpoint): {mid[0]:.4f}, {mid[1]:.4f}")

Verified Output:

Flight: John F Kennedy International Airport -> Dubai International Airport
Est. CO2 Emissions: 1265.18 kg/pax
Optimal Technical Stop (Midpoint): 56.0324, 1.2260

Features

  • Airports: Search by IATA, ICAO, or city name.
  • Geodesy: Haversine, Vincenty, and Great Circle calculations.
  • Emissions: Estimate CO2 footprint for flight segments.
  • Optimization: Find nearest airports and optimal routes.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aeronavx-2.0.8.tar.gz (42.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aeronavx-2.0.8-py3-none-any.whl (51.2 kB view details)

Uploaded Python 3

File details

Details for the file aeronavx-2.0.8.tar.gz.

File metadata

  • Download URL: aeronavx-2.0.8.tar.gz
  • Upload date:
  • Size: 42.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.0

File hashes

Hashes for aeronavx-2.0.8.tar.gz
Algorithm Hash digest
SHA256 c18c6ec4ad86a09e852d28c6a19a036afdf9358db004bd735df0e4cf2c378c19
MD5 88f567413e0bee3ae5d8b73271ee3c15
BLAKE2b-256 9288fa92ebaa777b376a810d740cca8a51a79c1e622a995937f029528c192aa4

See more details on using hashes here.

File details

Details for the file aeronavx-2.0.8-py3-none-any.whl.

File metadata

  • Download URL: aeronavx-2.0.8-py3-none-any.whl
  • Upload date:
  • Size: 51.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.0

File hashes

Hashes for aeronavx-2.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 a1ce59a033b142a5ba64f7bbe2091b554bbfbd186b3e5d237a587396ad2623dc
MD5 7a19b8bbef47b0cd0341064bd7fe0e71
BLAKE2b-256 e5a707fdf2a9570eeb67965eb1b5b56bc7b438f1ce7c2583cb0f2d6aeddcf7df

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page