h3 2.9

Python bindings for H3, a hierarchical hexagonal geospatial indexing system developed by Uber Technologies

H3-Python

This library provides Python bindings for the H3 Core Library. For API reference, please see the H3 Documentation.

Installing

You need to have a cc in your $PATH when installing this package:

which cc
/usr/bin/cc

Python 3.4+:

pip install h3

Development

git clone https://github.com/uber/h3-py.git && cd h3-py
virtualenv env
source env/bin/activate
pip install -r requirements-dev.txt
fab bootstrap

Usage

The following visualizations are achieved with folium.

from h3 import h3

Convert lat/lng to hexagon address

h3_address = h3.geo_to_h3(37.3615593, -122.0553238, 5) # lat, lng, hex resolution
hex_center_coordinates = h3.h3_to_geo(h3_address) # array of [lat, lng]
hex_boundary = h3.h3_to_geo_boundary(h3_address) # array of arrays of [lat, lng]

Get KRings of hexagon

h3.k_ring_distances(h3_address, 4) # array of 4 rings with size [1, 6, 12, 18]
h3.k_ring(h3_address, 4) # a collection of hexagons within kring sizes from 0 to 3

Polyfill a Geo Json with hexagons

geoJson = {'type': 'Polygon',
 'coordinates': [[[37.813318999983238, -122.4089866999972145],
 [ 37.7866302000007224, -122.3805436999997056 ],
 [37.7198061999978478, -122.3544736999993603],
 [ 37.7076131999975672, -122.5123436999983966 ],
 [37.7835871999971715, -122.5247187000021967],
 [37.8151571999998453, -122.4798767000009008]]] }
hexagons = list(h3.polyfill(geoJson, 8)) # resolution 8

For more API reference, please see the H3 Documentation.