# Python Geohash
A Python implementation of the Geohash algorithm compatible with [python-geohash](https://pypi.org/project/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
```bash
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
```python
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
```python
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
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"description": "# Python Geohash\n\nA Python implementation of the Geohash algorithm compatible with [python-geohash](https://pypi.org/project/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.\n\n## Installation\n\n```bash\npip install geohash-python\n```\n\n## Features\n\n- Encode latitude/longitude to geohash\n- Decode geohash to latitude/longitude\n- Get neighboring geohashes\n- Get bounding box for geohash\n- Pure Python implementation\n- uint64 geohash support for efficient storage and computation\n\n## API Reference\n\n### String-based Geohash Operations\n\n#### encode(latitude, longitude, precision=12)\nEncode a position to geohash string\n- Parameters:\n - latitude: float (-90.0 to 90.0)\n - longitude: float (-180.0 to 180.0)\n - precision: int, length of resulting geohash string (default: 12)\n- Returns: str, geohash string\n\n#### decode(hashcode)\nDecode a geohash string to latitude/longitude\n- Parameters:\n - hashcode: str, geohash string\n- Returns: tuple (latitude, longitude)\n\n#### decode_exactly(hashcode)\nDecode a geohash string to latitude/longitude with error margins\n- Parameters:\n - hashcode: str, geohash string\n- Returns: tuple (latitude, longitude, latitude_error, longitude_error)\n\n#### neighbors(hashcode)\nGet all 8 adjacent geohashes\n- Parameters:\n - hashcode: str, geohash string\n- Returns: dict with keys n,ne,e,se,s,sw,w,nw containing neighboring geohashes\n\n#### expand(hashcode)\nAlias for neighbors() - returns all 8 adjacent geohashes\n- Parameters:\n - hashcode: str, geohash string\n- Returns: dict with keys n,ne,e,se,s,sw,w,nw containing neighboring geohashes\n\n#### bbox(hashcode)\nGet the bounding box of a geohash\n- Parameters:\n - hashcode: str, geohash string\n- Returns: dict with keys n,s,e,w containing the bounds\n\n### uint64-based Geohash Operations\n\n#### encode_uint64(latitude, longitude)\nEncode a position to 64-bit integer geohash\n- Parameters:\n - latitude: float (-90.0 to 90.0)\n - longitude: float (-180.0 to 180.0)\n- Returns: int, 64-bit unsigned integer geohash\n\n#### decode_uint64(geohash_uint64)\nDecode a 64-bit integer geohash to latitude/longitude\n- Parameters:\n - geohash_uint64: int, 64-bit unsigned integer geohash\n- Returns: tuple (latitude, longitude)\n\n#### expand_uint64(geohash_uint64)\nGet ranges of adjacent geohashes as uint64 values\n- Parameters:\n - geohash_uint64: int, 64-bit unsigned integer geohash\n- Returns: list of tuples [(min_hash1, max_hash1), (min_hash2, max_hash2), ...] representing ranges of neighboring geohashes\n\n## Usage Examples\n\n### String-based Geohash Operations\n\n```python\nimport geohash\n\n# Encode a location\nlat, lon = 37.8324, -122.2715\nhash = geohash.encode(lat, lon) # returns 12 character string\nhash = geohash.encode(lat, lon, precision=6) # returns 6 character string\n\n# Decode a geohash\nlat, lon = geohash.decode(hash)\n\n# Get exact decoding with error margins\nlat, lon, lat_err, lon_err = geohash.decode_exactly(hash)\n\n# Get bounding box\nbbox = geohash.bbox(hash)\nprint(f\"North: {bbox['n']}, South: {bbox['s']}, East: {bbox['e']}, West: {bbox['w']}\")\n\n# Get neighbors\nneighbors = geohash.neighbors(hash)\nprint(f\"North: {neighbors['n']}, Northeast: {neighbors['ne']}\")\n```\n\n### uint64-based Geohash Operations\n\n```python\nimport geohash\n\n# Encode latitude/longitude to uint64 geohash\nlat, lon = 37.8324, -122.2715\nuint64_hash = geohash.encode_uint64(lat, lon)\n\n# Decode uint64 geohash to latitude/longitude\nlat, lon = geohash.decode_uint64(uint64_hash)\n\n# Get neighbor ranges as uint64 values\nneighbor_ranges = geohash.expand_uint64(uint64_hash)\nfor min_hash, max_hash in neighbor_ranges:\n print(f\"Range: {min_hash} to {max_hash}\")\n```\n\n## uint64 Geohash Format\n\nThe uint64 geohash format uses a 64-bit unsigned integer to represent a geohash:\n- 32 bits for longitude precision\n- 32 bits for latitude precision\n- Bits are interleaved: even bits for longitude, odd bits for latitude\n- Provides approximately 0.5cm precision at the equator\n\nBenefits of uint64 geohash:\n- More efficient storage in databases\n- Faster comparison operations\n- Memory-efficient geospatial calculations\n- Consistent precision across all locations\n\n## License\n\nMIT License\n",
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