airport-data-python

A comprehensive Python library providing easy retrieval of airport data based on IATA, ICAO, city codes, country codes, and continents. Ideal for developers building applications related to aviation, travel, and geography in Python.

Features

• 🌍 Comprehensive airport database with worldwide coverage
• 🔍 Search by IATA codes, ICAO codes, country, continent, and more
• 📍 Geographic proximity search with customizable radius
• 🔗 External links to Wikipedia, airport websites, and flight tracking services
• 📏 Distance calculation between airports
• 🏷️ Filter by airport type (large_airport, medium_airport, small_airport, heliport, seaplane_base)
• 🕒 Timezone-based airport lookup
• 💡 Autocomplete suggestions for search interfaces
• 🎯 Advanced multi-criteria filtering
• Built-in error handling for invalid input formats
• Efficiently packaged with gzipped data

Installation

You can install airports-py using pip:

pip install airports-py

Airport Data Structure

Each airport object contains the following fields:

{
    "iata": "SIN",                    # 3-letter IATA code
    "icao": "WSSS",                   # 4-letter ICAO code
    "time": "Asia/Singapore",         # Timezone identifier
    "utc": 8,                         # UTC offset in hours (int)
    "country_code": "SG",             # 2-letter country code
    "continent": "AS",                # 2-letter continent code (AS, EU, NA, SA, AF, OC, AN)
    "airport": "Singapore Changi Airport",  # Airport name
    "latitude": 1.361173,             # Latitude coordinate (float)
    "longitude": 103.990201,          # Longitude coordinate (float)
    "elevation_ft": 193068,           # Elevation in feet (int)
    "type": "large_airport",          # Airport type
    "scheduled_service": "TRUE",      # Has scheduled commercial service ("TRUE"/"FALSE")
    "wikipedia": "https://en.wikipedia.org/wiki/Singapore_Changi_Airport",
    "website": "http://www.changiairport.com",
    "runway_length": 13200,           # Longest runway in feet (int)
    "flightradar24_url": "https://www.flightradar24.com/airport/SIN",
    "radarbox_url": "https://www.radarbox.com/airport/WSSS",
    "flightaware_url": "https://www.flightaware.com/live/airport/WSSS"
}

Basic Usage

from airports import airport_data

# Get airport by IATA code
airport_by_iata = airport_data.get_airport_by_iata("SIN")
print(airport_by_iata[0]["airport"])  # "Singapore Changi Airport"

# Get airport by ICAO code
airport_by_icao = airport_data.get_airport_by_icao("WSSS")
print(airport_by_icao[0]["country_code"])  # "SG"

# Search airports by name
airports = airport_data.search_by_name("Singapore")
print(len(airports))  # Multiple airports matching "Singapore"

# Find nearby airports (within 50km of coordinates)
nearby = airport_data.find_nearby_airports(1.35019, 103.994003, 50)
print(nearby)  # Airports near Singapore Changi

API Reference

Core Search Functions

get_airport_by_iata(iata_code)

Finds airports by their 3-letter IATA code.

airports = airport_data.get_airport_by_iata('LHR')
# Returns list of airports with IATA code 'LHR'

get_airport_by_icao(icao_code)

Finds airports by their 4-character ICAO code.

airports = airport_data.get_airport_by_icao('EGLL')
# Returns list of airports with ICAO code 'EGLL'

search_by_name(query)

Searches for airports by name (case-insensitive, minimum 2 characters).

airports = airport_data.search_by_name('Heathrow')
# Returns airports with 'Heathrow' in their name

Geographic Functions

find_nearby_airports(lat, lon, radius_km=100)

Finds airports within a specified radius of given coordinates.

nearby = airport_data.find_nearby_airports(51.5074, -0.1278, 100)
# Returns airports within 100km of London coordinates

calculate_distance(code1, code2)

Calculates the great-circle distance between two airports using IATA or ICAO codes.

distance = airport_data.calculate_distance('LHR', 'JFK')
# Returns distance in kilometers (approximately 5540)

Filtering Functions

get_airport_by_city_code(city_code)

Finds airports by their city code.

airports = airport_data.get_airport_by_city_code('NYC')
# Returns all airports associated with New York City

get_airport_by_country_code(country_code)

Finds all airports in a specific country.

us_airports = airport_data.get_airport_by_country_code('US')
# Returns all airports in the United States

get_airport_by_continent(continent_code)

Finds all airports on a specific continent.

asian_airports = airport_data.get_airport_by_continent('AS')
# Returns all airports in Asia
# Continent codes: AS, EU, NA, SA, AF, OC, AN

get_airports_by_type(airport_type)

Finds airports by their type.

large_airports = airport_data.get_airports_by_type('large_airport')
# Available types: large_airport, medium_airport, small_airport, heliport, seaplane_base

# Convenience search for all airports
all_airports = airport_data.get_airports_by_type('airport')
# Returns large_airport, medium_airport, and small_airport

get_airports_by_timezone(timezone)

Finds all airports within a specific timezone.

london_airports = airport_data.get_airports_by_timezone('Europe/London')
# Returns airports in London timezone

Advanced Functions

find_airports(filters)

Finds airports matching multiple criteria.

# Find large airports in Great Britain with scheduled service
airports = airport_data.find_airports({
    'country_code': 'GB',
    'type': 'large_airport',
    'has_scheduled_service': True
})

# Find airports with minimum runway length
long_runway_airports = airport_data.find_airports({
    'min_runway_ft': 10000
})

get_autocomplete_suggestions(query, limit=10)

Provides autocomplete suggestions for search interfaces (returns max 10 results by default).

suggestions = airport_data.get_autocomplete_suggestions('Lon')
# Returns up to 10 airports matching 'Lon' in name or IATA code

get_airport_links(code)

Gets external links for an airport using IATA or ICAO code.

links = airport_data.get_airport_links('SIN')
# Returns:
# {
#     'website': "https://www.changiairport.com",
#     'wikipedia': "https://en.wikipedia.org/wiki/Singapore_Changi_Airport",
#     'flightradar24': "https://www.flightradar24.com/airport/SIN",
#     'radarbox': "https://www.radarbox.com/airport/WSSS",
#     'flightaware': "https://www.flightaware.com/live/airport/WSSS"
# }

Statistical & Analytical Functions

get_airport_stats_by_country(country_code)

Gets comprehensive statistics about airports in a specific country.

stats = airport_data.get_airport_stats_by_country('US')
# Returns:
# {
#   'total': 5432,
#   'by_type': {
#     'large_airport': 139,
#     'medium_airport': 467,
#     'small_airport': 4826,
#     ...
#   },
#   'with_scheduled_service': 606,
#   'average_runway_length': 5234,
#   'average_elevation': 1245,
#   'timezones': ['America/New_York', 'America/Chicago', ...]
# }

get_airport_stats_by_continent(continent_code)

Gets comprehensive statistics about airports on a specific continent.

stats = airport_data.get_airport_stats_by_continent('AS')
# Returns statistics for Asian airports

get_largest_airports_by_continent(continent_code, limit=10, sort_by='runway')

Gets the largest airports on a continent by runway length or elevation.

# Get top 5 airports in Asia by runway length
top_airports = airport_data.get_largest_airports_by_continent('AS', limit=5, sort_by='runway')

# Get top 10 airports by elevation
high_airports = airport_data.get_largest_airports_by_continent('SA', limit=10, sort_by='elevation')

Bulk Operations

get_multiple_airports(codes)

Fetches multiple airports by their IATA or ICAO codes in one call.

airports = airport_data.get_multiple_airports(['SIN', 'LHR', 'JFK', 'WSSS'])
# Returns list of airport objects (None for codes not found)

calculate_distance_matrix(codes)

Calculates distances between all pairs of airports in a list.

matrix = airport_data.calculate_distance_matrix(['SIN', 'LHR', 'JFK'])
# Returns:
# {
#   'airports': [...],
#   'distances': {
#     'SIN': { 'SIN': 0, 'LHR': 10872, 'JFK': 15344 },
#     ...
#   }
# }

find_nearest_airport(lat, lon, filters=None)

Finds the single nearest airport to given coordinates, optionally with filters.

# Find nearest airport
nearest = airport_data.find_nearest_airport(1.35019, 103.994003)
print(f"{nearest['airport']} is {nearest['distance']} km away")

# Find nearest large airport with scheduled service
nearest_hub = airport_data.find_nearest_airport(1.35019, 103.994003, {
    'type': 'large_airport',
    'has_scheduled_service': True
})

Validation & Utilities

validate_iata_code(code) / validate_icao_code(code)

Validates if a code exists in the database.

is_valid = airport_data.validate_iata_code('SIN')  # True

get_airport_count(filters)

Gets the count of airports matching the given filters.

count = airport_data.get_airport_count({
    'country_code': 'US', 
    'type': 'large_airport'
})

is_airport_operational(code)

Checks if an airport has scheduled commercial service.

is_operational = airport_data.is_airport_operational('SIN')  # True

Error Handling

Functions raise ValueError for invalid input formats (e.g., wrong length, invalid characters). For valid formats that simply don't match any airport, an empty list is returned instead.

# Invalid format raises ValueError
try:
    airport = airport_data.get_airport_by_iata('AB')  # Too short
except ValueError as e:
    print(e)  # "Invalid IATA format. Please provide a 3-letter code, e.g., 'AAA'."

# Valid format but non-existent code returns empty list
result = airport_data.get_airport_by_iata('XYZ')
print(result)  # []

Examples

Find airports near a city

# Find airports within 100km of Paris
paris_airports = airport_data.find_nearby_airports(48.8566, 2.3522, 100)
print(f"Found {len(paris_airports)} airports near Paris")

Get flight distance

# Calculate distance between Singapore and London
distance = airport_data.calculate_distance('SIN', 'LHR')
print(f"Distance: {round(distance)} km")

Build an airport search interface

# Get autocomplete suggestions
suggestions = airport_data.get_autocomplete_suggestions('New York')
for airport in suggestions:
    print(f"{airport['iata']} - {airport['airport']}")

Filter airports by multiple criteria

# Find large airports in Asia with scheduled service
asian_hubs = airport_data.find_airports({
    'continent': 'AS',
    'type': 'large_airport',
    'has_scheduled_service': True
})

Get airport statistics

# Get comprehensive statistics for US airports
us_stats = airport_data.get_airport_stats_by_country('US')
print(f"Total airports: {us_stats['total']}")
print(f"Large airports: {us_stats['by_type']['large_airport']}")
print(f"Average runway length: {us_stats['average_runway_length']} ft")

# Get statistics for Asian airports
asia_stats = airport_data.get_airport_stats_by_continent('AS')
print(f"Countries with airports: {len(asia_stats['by_country'])}")

Bulk operations

# Fetch multiple airports at once
airports = airport_data.get_multiple_airports(['SIN', 'LHR', 'JFK', 'NRT'])
for ap in airports:
    if ap:
        print(f"{ap['iata']}: {ap['airport']}")

# Calculate distance matrix for route planning
matrix = airport_data.calculate_distance_matrix(['SIN', 'LHR', 'JFK'])
print(f"Distance from SIN to LHR: {matrix['distances']['SIN']['LHR']:.0f} km")
print(f"Distance from LHR to JFK: {matrix['distances']['LHR']['JFK']:.0f} km")

Validation utilities

# Validate airport codes before processing
codes = ['SIN', 'XYZ', 'LHR', 'ABCD']
for code in codes:
    is_valid = airport_data.validate_iata_code(code)
    print(f"{code}: {'Valid' if is_valid else 'Invalid'}")

# Check if airport is operational
operational = airport_data.is_airport_operational('SIN')
print(f"Singapore Changi is operational: {operational}")

Find nearest airport

# Find nearest airport to current location
nearest = airport_data.find_nearest_airport(1.35019, 103.994003)
print(f"Nearest airport: {nearest['airport']} ({nearest['distance']} km away)")

# Find nearest large airport with scheduled service
nearest_hub = airport_data.find_nearest_airport(1.35019, 103.994003, {
    'type': 'large_airport',
    'has_scheduled_service': True
})

Using Command-Line Interface (CLI)

You can also directly execute Python code from the CLI without entering the interactive shell. Navigate to the root of your project and run:

python3 -c "from airports import airport_data; result = airport_data.get_airport_by_iata('MAA'); print(result)"

Replace 'MAA' with other codes as needed.

Testing

To test the library locally:

1. Navigate to the root of the project:

cd path_to_airport-data-python

2. Run the tests using:

python3 -m unittest discover tests -v

This command will discover and run all test files inside the tests directory and provide a detailed output.

Example Data Fields

For Singapore Changi Airport (as returned by the library):

Key	Value
iata	"SIN"
icao	"WSSS"
airport	"Singapore Changi Airport"
time	"Asia/Singapore"
utc	8
country_code	"SG"
continent	"AS"
latitude	1.361173
longitude	103.990201
elevation_ft	193068
type	"large_airport"
scheduled_service	"TRUE"
runway_length	13200
wikipedia	"https://en.wikipedia.org/wiki/Singapore_Changi_Airport"
website	"http://www.changiairport.com"
flightradar24_url	"https://www.flightradar24.com/airport/SIN"
radarbox_url	"https://www.radarbox.com/airport/WSSS"
flightaware_url	"https://www.flightaware.com/live/airport/WSSS"

Changelog

See CHANGELOG.md for the full version history and release notes.

Running the Project Locally

Prerequisites

• Python 3.6 or higher
• Git

Setup Instructions

1. Clone the repository:

git clone https://github.com/aashishvanand/airport-data-python.git

2. Change into the cloned directory:

cd airport-data-python

3. Create a virtual environment (recommended):

python3 -m venv venv

4. Activate the virtual environment:

# On macOS/Linux:
source venv/bin/activate

# On Windows:
venv\Scripts\activate

5. Install development dependencies:

pip install --upgrade pip
pip install build twine pytest pytest-cov

6. Install the package in development mode:

pip install -e .

7. Generate the compressed data file (if needed):

# Generate airports.gz from airports.json
python scripts/generate_airports_gz.py

# Verify the data file
python scripts/generate_airports_gz.py --verify-only

Testing

8. Run all tests:

python -m unittest discover tests -v

9. Run tests with pytest (alternative):

python -m pytest tests/ -v

10. Run tests with coverage:

python -m pytest tests/ -v --cov=airports --cov-report=term-missing

11. Test basic functionality manually:

python -c "
from airports import airport_data
print('Testing IATA lookup:')
result = airport_data.get_airport_by_iata('LHR')
print(f'Found: {result[0][\"airport\"]}')
print('✅ Basic functionality working!')
"

Building and Validation

12. Build the package:

# Clean previous builds
rm -rf build/ dist/ *.egg-info/

# Build package
python -m build

13. Validate the package:

twine check dist/*

14. Test package installation:

pip install dist/airports_py-*.whl --force-reinstall

Development Scripts

The project includes utility scripts in the scripts/ directory:

Generate Compressed Data File

# Generate airports.gz from airports.json
python scripts/generate_airports_gz.py

# Generate with custom compression level
python scripts/generate_airports_gz.py --compression 6

# Generate with custom source/output files
python scripts/generate_airports_gz.py --source custom_data.json --output custom_data.gz

# Verify existing compressed file
python scripts/generate_airports_gz.py --verify-only

Quick Development Workflow

For ongoing development, use this workflow:

# 1. Make your changes to the code

# 2. Regenerate data file if JSON was updated
python scripts/generate_airports_gz.py

# 3. Run tests
python -m pytest tests/ -v

# 4. Build and validate
python -m build && twine check dist/*

# 5. Test installation
pip install dist/airports_py-*.whl --force-reinstall

Troubleshooting

If you get import errors:

• Ensure you're in the virtual environment: which python should show the venv path
• Verify the package is installed: pip list | grep airports
• Check import works: python -c "import airports.airport_data"

If data file is missing:

• Generate it: python scripts/generate_airports_gz.py
• Verify location: ls -la airports/data/airports.gz
• Check file integrity: python scripts/generate_airports_gz.py --verify-only

If tests fail:

• Ensure data file exists and is valid
• Check that all dependencies are installed: pip install pytest pytest-cov
• Run individual tests: python -m pytest tests/test_airport_data.py::TestAirportData::test_get_airport_by_iata -v

If build fails:

• Ensure setup.py has correct package data configuration
• Check that airports/data/airports.gz exists and is included in package

Deactivating Environment

When you're done developing:

deactivate

Data Management

The airport data is stored in airports/data/ directory:

• airports.json - Source data in JSON format (4.7MB)
• airports.gz - Compressed data used by the library (617KB, 86.9% compression)

Updating Airport Data

1. Update the source JSON file:

# Edit airports/data/airports.json with new airport data

2. Regenerate the compressed file:

python scripts/generate_airports_gz.py

3. Verify the update:

python scripts/generate_airports_gz.py --verify-only
python -c "from airports import airport_data; print(f'Loaded {len(airport_data.airports)} airports')"

4. Run tests to ensure compatibility:

python -m pytest tests/ -v

Data Source

This library uses a comprehensive dataset of worldwide airports with regular updates to ensure accuracy and completeness.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.