GeoDesk is a fast and storage-efficient geospatial database for OpenStreetMap data. Also available for Java.
Why GeoDesk?
-
Small storage footprint — GeoDesk's GOL files are only 20% to 50% larger than the original OSM data in PBF format — that's less than a tenth of the storage consumed by a traditional SQL-based database.
-
Fast queries — typically 50 times faster than SQL.
-
Fast to get started — Converting
.osm.pbfdata to a GOL is 20 times faster than an import into an SQL database. Alternatively, download pre-made data tiles for just the regions you need and automatically assemble them into a GOL. -
Intuitive API — No need for object-relational mapping; GeoDesk queries return Python objects. Quickly discover tags, way-nodes and relation members. Get a feature's geometry, measure its length/area.
-
Proper handling of relations — (Traditional geospatial databases deal with geometric shapes and require workarounds to support this unique and powerful aspect of OSM data.)
-
Seamless integration with Shapely for advanced geometric operations, such as buffer, union, simplify, convex and concave hulls, Voronoi diagrams, and much more.
-
Modest hardware requirements — If it can run 64-bit Python, it'll run GeoDesk.
Get Started
Requirements
- Python 3.7 or above
- Java 16 or above (for the GOL Tool)
Download
pip install geodeskCreate a GOL
Create a Geographic Object Library based on any .osm.pbf file, using the
GOL Tool (Requires Java 16+).
For example:
gol build switzerland switzerland-latest.osm.pbfExample Application
Find all the pubs in Zurich (Switzerland) and print their names:
from geodesk import *
# Open switzerland.gol
features = Features("switzerland")
# Get the feature that represents the area of the city of Zurich
zurich = features("a[boundary=adminstrative][admin_level=8][name:en=Zurich]").one
# Define a set that contains nodes and areas that are pubs
pubs = features("na[amenity=pub]")
# Iterate through the pubs that are contained in the area of Zurich
# and print their names
for pub in pubs.within(zurich):
print(pub.name) More Examples
Find all movie theaters within 500 meters from a given point:
movieTheaters = features("na[amenity=cinema]").around(
meters=500, lat=47.37, lon=8.54)Remember, OSM uses British English for its terminology.
Discover the bus routes that traverse a given street:
for route in street.parents("[route=bus]")):
print(f"- {route.ref} from {route.from} to {route.to}")Count the number of entrances of a building:
number_of_entrances = building.nodes("[entrance]").count