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.
- π Comprehensive airport database with worldwide coverage
- π Search by IATA codes, ICAO codes, country, continent, and more
- π Geographic proximity search with customizable radius
- π External links to Wikipedia, airport websites, and flight tracking services
- π Distance calculation between airports
- π·οΈ Filter by airport type (large_airport, medium_airport, small_airport, heliport, seaplane_base)
- π Timezone-based airport lookup
- π‘ Autocomplete suggestions for search interfaces
- π― Advanced multi-criteria filtering
- Built-in error handling for invalid input formats
- Efficiently packaged with gzipped data
You can install airports-py
using pip:
pip install airports-py
Each airport object contains the following fields:
{
"iata": "SIN", # 3-letter IATA code
"icao": "WSSS", # 4-letter ICAO code
"time": "Asia/Singapore", # Timezone identifier
"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": "1.35019", # Latitude coordinate
"longitude": "103.994003", # Longitude coordinate
"elevation": "22", # Elevation in feet
"type": "large_airport", # Airport type
"scheduled_service": "yes", # Has scheduled commercial service
"wikipedia": "https://en.wikipedia.org/wiki/Singapore_Changi_Airport",
"website": "https://www.changiairport.com",
"runway_length": "13200", # Longest runway in feet
"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"
}
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
Finds airports by their 3-letter IATA code.
airports = airport_data.get_airport_by_iata('LHR')
# Returns list of airports with IATA code 'LHR'
Finds airports by their 4-character ICAO code.
airports = airport_data.get_airport_by_icao('EGLL')
# Returns list of airports with ICAO code 'EGLL'
Searches for airports by name (case-insensitive, minimum 2 characters).
airports = airport_data.search_by_name('Heathrow')
# Returns airports with 'Heathrow' in their name
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
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)
Finds all airports in a specific country.
us_airports = airport_data.get_airport_by_country_code('US')
# Returns all airports in the United States
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
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
Finds all airports within a specific timezone.
london_airports = airport_data.get_airports_by_timezone('Europe/London')
# Returns airports in London timezone
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
})
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
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"
# }
All functions raise appropriate exceptions for invalid input or when no data is found.
try:
airport = airport_data.get_airport_by_iata('XYZ')
except ValueError as e:
print(e) # "No data found for IATA code: XYZ"
# 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")
# Calculate distance between Singapore and London
distance = airport_data.calculate_distance('SIN', 'LHR')
print(f"Distance: {round(distance)} km")
# Get autocomplete suggestions
suggestions = airport_data.get_autocomplete_suggestions('New York')
for airport in suggestions:
print(f"{airport['iata']} - {airport['airport']}")
# Find large airports in Asia with scheduled service
asian_hubs = airport_data.find_airports({
'continent': 'AS',
'type': 'large_airport',
'has_scheduled_service': True
})
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.
To test the library locally:
- Navigate to the root of the project:
cd path_to_airports-py
- 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.
For Chennai International Airport:
Field Name | Data |
---|---|
IATA | MAA |
ICAO | VOMM |
Time Zone | Asia/Kolkata |
City Code | MAA |
Country Code | IN |
Name | Chennai International Airport |
Latitude | 12.99 |
Longitude | 80.1693 |
Altitude (in feet) | 52 |
State | Tamil Nadu |
City | Pallavaram |
County | Kancheepuram |
State Code | Tamil Nadu |
Airport Type | large_airport |
Continent | AS |
State Abbreviation | IN-TN |
International | TRUE |
Wikipedia Link | Wikipedia |
Official Website | Chennai Airport |
Location ID | 12513629 |
Phone Number | 044-2340551 |
Runway Length (in meters) | 10050 |
Flightradar24 | Flightradar24 |
Radarbox | Radarbox |
Flightaware Link | Flightaware |
Field Name | Data |
---|---|
IATA | SIN |
ICAO | WSSS |
Time Zone | Asia/Singapore |
City Code | SIN |
Country Code | SG |
Name | Singapore Changi Airport |
Latitude | 1.35019 |
Longitude | 103.994 |
Altitude (in feet) | 22 |
State | Singapore |
City | Singapore |
County | Singapore |
State Code | South East |
Airport Type | large_airport |
Continent | AS |
State Abbreviation | SG-04 |
International | TRUE |
Wikipedia Link | Wikipedia |
Official Website | Changi Airport |
Location ID | 12517525 |
Phone Number | (65) 6542 1122 |
Runway Length (in meters) | 13200 |
Flightradar24 | Flightradar24 |
Radarbox | Radarbox |
Flightaware | Flightaware |
get_airports_by_timezone(timezone)
- Find airports by timezoneget_airport_links(code)
- Get external links for airportsfind_airports(filters)
- Advanced multi-criteria filteringget_autocomplete_suggestions(query)
- Autocomplete functionality- Enhanced
get_airports_by_type(type)
- Now supports convenience search for "airport" type search_by_name(query)
- Search airports by namefind_nearby_airports(lat, lon, radius_km)
- Geographic proximity searchcalculate_distance(code1, code2)
- Distance calculation between airports- External links support - Wikipedia, websites, and flight tracking URLs
- Timezone information - Complete timezone data for all airports
- Runway length data - Airport runway information included
- Scheduled service indicator - Whether airports have commercial scheduled service
- Better error handling and validation with specific error messages
- More comprehensive airport data structure
- Improved type filtering with partial matching
- Enhanced geographic calculations using great-circle distance
- Case-insensitive search improvements
- Comprehensive test coverage for all functions
- Legacy simple filtering (replaced with advanced
find_airports
function) - Basic airport objects (expanded to include more fields)
- Python 3.6 or higher
- Git
- Clone the repository:
git clone https://github.com/aashishvanand/airports-py.git
- Change into the cloned directory:
cd airports-py
- Create a virtual environment (recommended):
python3 -m venv venv
- Activate the virtual environment:
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venv\Scripts\activate
- Install development dependencies:
pip install --upgrade pip
pip install build twine pytest pytest-cov
- Install the package in development mode:
pip install -e .
- 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
- Run all tests:
python -m unittest discover tests -v
- Run tests with pytest (alternative):
python -m pytest tests/ -v
- Run tests with coverage:
python -m pytest tests/ -v --cov=airports --cov-report=term-missing
- 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('β
Basic functionality working!')
"
- Build the package:
# Clean previous builds
rm -rf build/ dist/ *.egg-info/
# Build package
python -m build
- Validate the package:
twine check dist/*
- Test package installation:
pip install dist/airports_py-*.whl --force-reinstall
The project includes utility scripts in the scripts/
directory:
# 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
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
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
When you're done developing:
deactivate
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)
- Update the source JSON file:
# Edit airports/data/airports.json with new airport data
- Regenerate the compressed file:
python scripts/generate_airports_gz.py
- 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')"
- Run tests to ensure compatibility:
python -m pytest tests/ -v
This library uses a comprehensive dataset of worldwide airports with regular updates to ensure accuracy and completeness.
This project is licensed under the MIT License - see the LICENSE file for details.
Contributions, issues, and feature requests are welcome! Feel free to check the issues page.