Skip to main content

Python Geocoding Toolbox

Project description

Latest Version Build Status License

geopy is a Python client for several popular geocoding web services.

geopy makes it easy for Python developers to locate the coordinates of addresses, cities, countries, and landmarks across the globe using third-party geocoders and other data sources.

geopy includes geocoder classes for the OpenStreetMap Nominatim, Google Geocoding API (V3), and many other geocoding services. The full list is available on the Geocoders doc section. Geocoder classes are located in geopy.geocoders.

geopy is tested against CPython (versions 3.7, 3.8, 3.9, 3.10, 3.11, 3.12) and PyPy3. geopy 1.x line also supported CPython 2.7, 3.4 and PyPy2.

© geopy contributors 2006-2018 (see AUTHORS) under the MIT License.

Installation

Install using pip with:

pip install geopy

Or, download a wheel or source archive from PyPI.

Geocoding

To geolocate a query to an address and coordinates:

>>> from geopy.geocoders import Nominatim
>>> geolocator = Nominatim(user_agent="specify_your_app_name_here")
>>> location = geolocator.geocode("175 5th Avenue NYC")
>>> print(location.address)
Flatiron Building, 175, 5th Avenue, Flatiron, New York, NYC, New York, ...
>>> print((location.latitude, location.longitude))
(40.7410861, -73.9896297241625)
>>> print(location.raw)
{'place_id': '9167009604', 'type': 'attraction', ...}

To find the address corresponding to a set of coordinates:

>>> from geopy.geocoders import Nominatim
>>> geolocator = Nominatim(user_agent="specify_your_app_name_here")
>>> location = geolocator.reverse("52.509669, 13.376294")
>>> print(location.address)
Potsdamer Platz, Mitte, Berlin, 10117, Deutschland, European Union
>>> print((location.latitude, location.longitude))
(52.5094982, 13.3765983)
>>> print(location.raw)
{'place_id': '654513', 'osm_type': 'node', ...}

Measuring Distance

Geopy can calculate geodesic distance between two points using the geodesic distance or the great-circle distance, with a default of the geodesic distance available as the function geopy.distance.distance.

Here’s an example usage of the geodesic distance, taking pair of (lat, lon) tuples:

>>> from geopy.distance import geodesic
>>> newport_ri = (41.49008, -71.312796)
>>> cleveland_oh = (41.499498, -81.695391)
>>> print(geodesic(newport_ri, cleveland_oh).miles)
538.390445368

Using great-circle distance, also taking pair of (lat, lon) tuples:

>>> from geopy.distance import great_circle
>>> newport_ri = (41.49008, -71.312796)
>>> cleveland_oh = (41.499498, -81.695391)
>>> print(great_circle(newport_ri, cleveland_oh).miles)
536.997990696

Documentation

More documentation and examples can be found at Read the Docs.

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

geopy-2.4.1.tar.gz (117.6 kB view details)

Uploaded Source

Built Distribution

geopy-2.4.1-py3-none-any.whl (125.4 kB view details)

Uploaded Python 3

File details

Details for the file geopy-2.4.1.tar.gz.

File metadata

  • Download URL: geopy-2.4.1.tar.gz
  • Upload date:
  • Size: 117.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for geopy-2.4.1.tar.gz
Algorithm Hash digest
SHA256 50283d8e7ad07d89be5cb027338c6365a32044df3ae2556ad3f52f4840b3d0d1
MD5 bf770e94c179ceffdb63df7a6ed67fe8
BLAKE2b-256 0efdef6d53875ceab72c1fad22dbed5ec1ad04eb378c2251a6a8024bad890c3b

See more details on using hashes here.

File details

Details for the file geopy-2.4.1-py3-none-any.whl.

File metadata

  • Download URL: geopy-2.4.1-py3-none-any.whl
  • Upload date:
  • Size: 125.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for geopy-2.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ae8b4bc5c1131820f4d75fce9d4aaaca0c85189b3aa5d64c3dcaf5e3b7b882a7
MD5 ca3f24b601cffcbf405db5c4952fe475
BLAKE2b-256 e515cf2a69ade4b194aa524ac75112d5caac37414b20a3a03e6865dfe0bd1539

See more details on using hashes here.

Supported by

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