[SOLVED] How to efficiently convert a set of geohashes into a polygon?

How to efficiently convert a set of geohashes into a polygon?

I have been looking for a efficient way to convert a set of geohashes into polygons in Python, besides sometimes I obtain multipolygons instead of polygons, probably because some inner geohashes are missing. I am currently using python-geohash and shapely and my approach consists in the following steps:

I convert each geohash into a polygon by extracting its corner coordinates.

def to_polygon(geohash):
    box = Geohash.bbox(geohash)
    return Polygon([(box['e'], box['n']), (box['w'], box['n']), (box['w'], box['s']), (box['e'], box['s'])])

Then I map over the iterable of geohashes performing previous explained transformation.
```
polygons = [to_polygon(geohash) for geohash in geohashes]
```
Finally, I combine all those polygons into a single one, by using polygon's method union.
```
polygon = functools.reduce(lambda a, b: a.union(b), polygons)
```

If the set of geohashes is around some thousands it may take few minutes.

Solution

I created a library (polygon-geohasher) to achieve this:

from polygon_geohasher.polygon_geohasher import geohashes_to_polygon

geohashes = ['9bc1db2',
             '9bc1db6', 
             '9bc1db1', 
             '9bc1db0',
             '9bc1db4',
             '9bc1db9', 
             '9bc1db8',
             '9bc1dbd', 
             '9bc1db3']
polygon = geohashes_to_polygon(geohashes)
print(polygon) 
# POLYGON ((-99.71878051757812 4.483795166015625, -99.71878051757812 4.482421875, -99.72015380859375 4.482421875, -99.72152709960938 4.482421875, -99.722900390625 4.482421875, -99.722900390625 4.483795166015625, -99.722900390625 4.48516845703125, -99.722900390625 4.486541748046875, -99.72152709960938 4.486541748046875, -99.72015380859375 4.486541748046875, -99.71878051757812 4.486541748046875, -99.71878051757812 4.48516845703125, -99.71878051757812 4.483795166015625))