pygeocodio 0.1.0

Python wrapper for Geocod.io API

Python wrapper for Geocod.io geocoding API.

Features

• Geocode an individual address

• Batch geocode up to 10,000 addresses at a time

• Parse an address into its identifiable components

Read the complete Geocod.io documentation <http://geocod.io/docs/>> for service documentation.

Installation

pygeocodio requires requests 2.0.0 or greater and will ensure requests is installed:

pip install pygeocodio

Using

Import the API client and ensure you have a valid API key:

>>> from geocodio import GeocodioClient
>>> client = GeocodioClient(MY_KEY)
>>> geocoded_location = client.geocode("42370 Bob Hope Drive, Rancho Mirage CA")

The result from the Geocod.io service is a dictionary including your query, its components, and a list of matching results:

>>> geocoded_location
{
  "input": {
    "address_components": {
      "number": "42370",
      "street": "Bob Hope",
      "suffix": "Dr",
      "city": "Rancho Mirage",
      "state": "CA"
    },
    "formatted_address": "42370 Bob Hope Dr, Rancho Mirage CA"
  },
  "results": [
    {
      "address_components": {
        "number": "42370",
        "street": "Bob Hope",
        "suffix": "Dr",
        "city": "Rancho Mirage",
        "state": "CA",
        "zip": "92270"
      },
      "formatted_address": "42370 Bob Hope Dr, Rancho Mirage CA, 92270",
      "location": {
        "lat": 33.738987255507,
        "lng": -116.40833849559
      },
      "accuracy": 1
    },
    {
      "address_components": {
        "number": "42370",
        "street": "Bob Hope",
        "suffix": "Dr",
        "city": "Rancho Mirage",
        "state": "CA",
        "zip": "92270"
      },
      "formatted_address": "42370 Bob Hope Dr, Rancho Mirage CA, 92270",
      "location": {
        "lat": 33.738980796909,
        "lng": -116.40833917329
      },
      "accuracy": 0.8
    }
  ]
}

This returned several geolocation results in descending order of accuracy, so the first and most accurate geocoded location latitude and longitude can be accessed using the coords attribute:

>>> geocoded_location.coords
(-116.40833849559, 33.738987255507)

Note

To make working with other geographic data formats easier the coords method returns a tuple in (longitude, latitude) format.

You can also geocode a list of addresses:

>>> geocoded_addresses = geocodio.geocode(['1600 Pennsylvania Ave, Washington, DC',
        '3101 Patterson Ave, Richmond, VA, 23221'])

Return just the coordinates for the list of geocoded addresses:

>>> geocoded_addresses.coords
[(-116.40833849559, 33.738987255507), (-116.40833849559, 33.738987255507)]

Lookup an address by formatted address:

>>> geocoded_addresses.addresses.get['1600 Pennsylvania Ave, Washington, DC'].coords
(-116.40833849559, 33.738987255507)

Note that to perform the key based lookup you must use the get method. This preserves the list’s index based lookup.

And if you just want to parse an individual address into its components:

>>> client.parse('1600 Pennsylvania Ave, Washington DC')
{
    "address_components": {
        "number": "1600",
        "street": "Pennsylvania",
        "suffix": "Ave",
        "city": "Washington",
        "state": "DC"
    },
    "formatted_address": "1600 Pennsylvania Ave, Washington DC"
}

The return value is simple enough to us as the returned dictionary.

History

0.1.0 (2014-01-24)

• First release on PyPI.