geohash-python 0.8.5

A Python implementation of the Geohash algorithm compatible with python-geohash

Python Geohash

A Python implementation of the Geohash algorithm compatible with python-geohash. This package provides functionality to encode and decode geohashes, as well as find neighboring geohashes. It supports both string-based and uint64-based geohash representations.

Installation

pip install geohash-python

Features

• Encode latitude/longitude to geohash
• Decode geohash to latitude/longitude
• Get neighboring geohashes
• Get bounding box for geohash
• Pure Python implementation
• uint64 geohash support for efficient storage and computation

API Reference

String-based Geohash Operations

encode(latitude, longitude, precision=12)

Encode a position to geohash string

• Parameters:
  • latitude: float (-90.0 to 90.0)
  • longitude: float (-180.0 to 180.0)
  • precision: int, length of resulting geohash string (default: 12)
• Returns: str, geohash string

decode(hashcode)

Decode a geohash string to latitude/longitude

• Parameters:
  • hashcode: str, geohash string
• Returns: tuple (latitude, longitude)

decode_exactly(hashcode)

Decode a geohash string to latitude/longitude with error margins

• Parameters:
  • hashcode: str, geohash string
• Returns: tuple (latitude, longitude, latitude_error, longitude_error)

neighbors(hashcode)

Get all 8 adjacent geohashes

• Parameters:
  • hashcode: str, geohash string
• Returns: dict with keys n,ne,e,se,s,sw,w,nw containing neighboring geohashes

expand(hashcode)

Alias for neighbors() - returns all 8 adjacent geohashes

• Parameters:
  • hashcode: str, geohash string
• Returns: dict with keys n,ne,e,se,s,sw,w,nw containing neighboring geohashes

bbox(hashcode)

Get the bounding box of a geohash

• Parameters:
  • hashcode: str, geohash string
• Returns: dict with keys n,s,e,w containing the bounds

uint64-based Geohash Operations

encode_uint64(latitude, longitude)

Encode a position to 64-bit integer geohash

• Parameters:
  • latitude: float (-90.0 to 90.0)
  • longitude: float (-180.0 to 180.0)
• Returns: int, 64-bit unsigned integer geohash

decode_uint64(geohash_uint64)

Decode a 64-bit integer geohash to latitude/longitude

• Parameters:
  • geohash_uint64: int, 64-bit unsigned integer geohash
• Returns: tuple (latitude, longitude)

expand_uint64(geohash_uint64)

Get ranges of adjacent geohashes as uint64 values

• Parameters:
  • geohash_uint64: int, 64-bit unsigned integer geohash
• Returns: list of tuples [(min_hash1, max_hash1), (min_hash2, max_hash2), ...] representing ranges of neighboring geohashes

Usage Examples

String-based Geohash Operations

import geohash

# Encode a location
lat, lon = 37.8324, -122.2715
hash = geohash.encode(lat, lon)  # returns 12 character string
hash = geohash.encode(lat, lon, precision=6)  # returns 6 character string

# Decode a geohash
lat, lon = geohash.decode(hash)

# Get exact decoding with error margins
lat, lon, lat_err, lon_err = geohash.decode_exactly(hash)

# Get bounding box
bbox = geohash.bbox(hash)
print(f"North: {bbox['n']}, South: {bbox['s']}, East: {bbox['e']}, West: {bbox['w']}")

# Get neighbors
neighbors = geohash.neighbors(hash)
print(f"North: {neighbors['n']}, Northeast: {neighbors['ne']}")

uint64-based Geohash Operations

import geohash

# Encode latitude/longitude to uint64 geohash
lat, lon = 37.8324, -122.2715
uint64_hash = geohash.encode_uint64(lat, lon)

# Decode uint64 geohash to latitude/longitude
lat, lon = geohash.decode_uint64(uint64_hash)

# Get neighbor ranges as uint64 values
neighbor_ranges = geohash.expand_uint64(uint64_hash)
for min_hash, max_hash in neighbor_ranges:
    print(f"Range: {min_hash} to {max_hash}")

uint64 Geohash Format

The uint64 geohash format uses a 64-bit unsigned integer to represent a geohash:

• 32 bits for longitude precision
• 32 bits for latitude precision
• Bits are interleaved: even bits for longitude, odd bits for latitude
• Provides approximately 0.5cm precision at the equator

Benefits of uint64 geohash:

• More efficient storage in databases
• Faster comparison operations
• Memory-efficient geospatial calculations
• Consistent precision across all locations

License

MIT License