whereabouts 0.2.3

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Whereabouts

Fast, scalable geocoding for Python using DuckDB. The geocoding algorithms are based on the following papers:

• https://arxiv.org/abs/1708.01402
• https://arxiv.org/abs/1712.09691

Description

Geocode addresses and reverse geocode coordinates directly from Python in your own environment.

• No additional database setup required. Uses DuckDB to run all queries
• No need to send data to an external geocoding API
• Fast (Geocode 1000s / sec and reverse geocode 200,000s / sec)
• Robust to typographical errors

Requirements

• Python 3.8+
• Poetry (for package management)

Installation

Once Poetry is installed and you are in the project directory:

poetry shell
poetry install

The current process for using Australian data from the GNAF is as follows:

1. Download the latest version of GNAF core from https://geoscape.com.au/data/g-naf-core/
2. Update the setup.yml file to point to the location of the GNAF core file
3. Finally, setup the geocoder. This creates the required reference tables

python setup_geocoder.py

To use address data from another country, the file should have the following columns:

Column name	Description
ADDRESS_DETAIL_PID	Unique identifier for address
ADDRESS_LABEL	The full address
ADDRESS_SITE_NAME	Name of the site. This is usually null
LOCALITY_NAME	Name of the suburb or locality
POSTCODE	Postcode of address
STATE	State
LATITUDE	Latitude of geocoded address
LONGITUDE	Longitude of geocoded address

Note that by default the file should be pipe-separated, i.e., use '|' as the delimitor.

Examples

Geocode a list of addresses

from whereabouts.Matcher import Matcher

matcher = Matcher(db_name='gnaf_au')
matcher.geocode(addresslist, how='standard')

For more accurate geocoding you can use trigram phrases rather than token phrases (note that the trigram option has to have been specified in the setup.yml file as part of the setup)

matcher.geocode(addresslist, how='trigram')

Once a Matcher object is created, the KD-tree for fast geocoding will also be created. A list of latitude, longitude values can then be reverse geocoded as follows

matcher.reverse_geocode(coordinates)