Loading...
Loading...
Convert addresses to coordinates (geocoding) and coordinates to addresses (reverse geocoding). Use for location data enrichment or address validation.
npx skill4agent add dkyazzentwatwa/chatgpt-skills geocoderfrom geocoder import Geocoder
geo = Geocoder()
# Address to coordinates
result = geo.geocode("1600 Amphitheatre Parkway, Mountain View, CA")
print(f"Coordinates: {result['lat']}, {result['lon']}")
# Coordinates to address
result = geo.reverse(37.4224, -122.0840)
print(f"Address: {result['address']}")# Geocode address
python geocoder.py --geocode "Empire State Building, New York"
# Reverse geocode
python geocoder.py --reverse "40.7484,-73.9857"
# Batch geocode CSV
python geocoder.py --input addresses.csv --column address --output geocoded.csv
# Batch reverse geocode
python geocoder.py --input coords.csv --lat lat --lon lon --reverse-batch --output addresses.csvclass Geocoder:
def __init__(self, provider: str = "nominatim", api_key: str = None)
# Single operations
def geocode(self, address: str) -> dict
def reverse(self, lat: float, lon: float) -> dict
# Batch operations
def batch_geocode(self, addresses: list, delay: float = 1.0) -> list
def batch_reverse(self, coordinates: list, delay: float = 1.0) -> list
# File operations
def geocode_csv(self, input: str, column: str, output: str) -> str
def reverse_csv(self, input: str, lat: str, lon: str, output: str) -> strgeo = Geocoder(provider="google", api_key="YOUR_KEY")geo = Geocoder(provider="bing", api_key="YOUR_KEY"){
"address": "1600 Amphitheatre Parkway, Mountain View, CA",
"lat": 37.4224764,
"lon": -122.0842499,
"components": {
"house_number": "1600",
"road": "Amphitheatre Parkway",
"city": "Mountain View",
"state": "California",
"postcode": "94043",
"country": "United States"
},
"raw": {...} # Provider-specific data
}{
"lat": 40.7484,
"lon": -73.9857,
"address": "20 W 34th St, New York, NY 10001, USA",
"components": {
"house_number": "20",
"road": "West 34th Street",
"city": "New York",
"state": "New York",
"postcode": "10001",
"country": "United States"
}
}geo = Geocoder()
result = geo.geocode_csv(
input="customers.csv",
column="shipping_address",
output="customers_geocoded.csv"
)
print(f"Geocoded {result['success']} of {result['total']} addresses")geo = Geocoder()
address = "123 Main St, Anytown"
result = geo.geocode(address)
if result:
print(f"Valid: {result['address']}")
print(f"Standardized: {result['components']}")
else:
print("Address not found")geo = Geocoder()
locations = [
(40.7128, -74.0060),
(34.0522, -118.2437),
(41.8781, -87.6298)
]
for lat, lon in locations:
result = geo.reverse(lat, lon)
print(f"({lat}, {lon}): {result['address']}")# Automatic delay in batch operations
results = geo.batch_geocode(addresses, delay=1.0)
# For paid providers, can reduce delay
geo = Geocoder(provider="google", api_key="KEY")
results = geo.batch_geocode(addresses, delay=0.1)result = geo.geocode("Invalid Address XYZ123")
if result is None:
print("Address not found")
elif result.get('error'):
print(f"Error: {result['error']}")
else:
print(f"Found: {result['address']}")