<img src="https://docs.geodesk.com/img/github-header.png">
GeoDesk is a fast and storage-efficient geospatial database for OpenStreetMap data.
Also available [for C++](https://github.com/clarisma/libgeodesk) and [for Java](http://www.github.com/clarisma/geodesk).
## 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.pbf` data 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 3.9 or above
- Java 16 or above (for the GOL Tool)
### Download
```
pip install geodesk
```
### Create a GOL
Create a Geographic Object Library based on any `.osm.pbf` file, using the
[GOL Tool](https://www.geodesk.com/download) (Requires Java 16+).
For example:
```
gol build switzerland switzerland-latest.osm.pbf
```
### Example Application
Find all the pubs in Zurich (Switzerland) and print their names:
```python
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:
```python
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:
```python
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:
```python
number_of_entrances = building.nodes("[entrance]").count
```
## Documentation
[GeoDesk Developer's Guide](https://docs.geodesk.com/python)
## Related Repositories
- [geodesk](http://www.github.com/clarisma/geodesk) — GeoDesk for Java
- [libgeodesk](https://github.com/clarisma/libgeodesk) — GeoDesk for C++
- [gol-tool](http://www.github.com/clarisma/gol-tool) — command-line utility for building, maintaining and querying GOL files
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"description": "<img src=\"https://docs.geodesk.com/img/github-header.png\">\n\nGeoDesk is a fast and storage-efficient geospatial database for OpenStreetMap data. \nAlso available [for C++](https://github.com/clarisma/libgeodesk) and [for Java](http://www.github.com/clarisma/geodesk).\n\n## Why GeoDesk?\n\n- **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.\n\n- **Fast queries** — typically 50 times faster than SQL. \n\n- **Fast to get started** — Converting `.osm.pbf` data 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.\n\n- **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. \n \n- **Proper handling of relations** — (Traditional geospatial databases deal with geometric shapes and require workarounds to support this unique and powerful aspect of OSM data.)\n\n- **Seamless integration with Shapely** for advanced geometric operations, such as buffer, union, simplify, convex and concave hulls, Voronoi diagrams, and much more.\n\n- **Modest hardware requirements** — If it can run 64-bit Python, it'll run GeoDesk.\n \n## Get Started\n\n### Requirements\n\n- Python 3.9 or above\n- Java 16 or above (for the GOL Tool)\n \n### Download\n\n```\npip install geodesk\n```\n\n### Create a GOL\n\nCreate a Geographic Object Library based on any `.osm.pbf` file, using the \n[GOL Tool](https://www.geodesk.com/download) (Requires Java 16+).\n\nFor example:\n\n```\ngol build switzerland switzerland-latest.osm.pbf\n```\n\n### Example Application\n\nFind all the pubs in Zurich (Switzerland) and print their names:\n\n```python\nfrom geodesk import *\n\n# Open switzerland.gol\nfeatures = Features(\"switzerland\") \n\n# Get the feature that represents the area of the city of Zurich\nzurich = features(\"a[boundary=adminstrative][admin_level=8][name:en=Zurich]\").one\n\n# Define a set that contains nodes and areas that are pubs\npubs = features(\"na[amenity=pub]\")\n\n# Iterate through the pubs that are contained in the area of Zurich\n# and print their names\nfor pub in pubs.within(zurich):\n print(pub.name) \n```\n\n### More Examples\n\nFind all movie theaters within 500 meters from a given point:\n\n```python\nmovieTheaters = features(\"na[amenity=cinema]\").around(\n meters=500, lat=47.37, lon=8.54)\n```\n\n*Remember, OSM uses British English for its terminology.*\n\nDiscover the bus routes that traverse a given street:\n\n```python\nfor route in street.parents(\"[route=bus]\")):\n print(f\"- {route.ref} from {route.from} to {route.to}\")\n```\n\nCount the number of entrances of a building:\n\n```python\nnumber_of_entrances = building.nodes(\"[entrance]\").count\n```\n\n## Documentation\n\n[GeoDesk Developer's Guide](https://docs.geodesk.com/python)\n\n## Related Repositories\n\n- [geodesk](http://www.github.com/clarisma/geodesk) — GeoDesk for Java\n- [libgeodesk](https://github.com/clarisma/libgeodesk) — GeoDesk for C++\n- [gol-tool](http://www.github.com/clarisma/gol-tool) — command-line utility for building, maintaining and querying GOL files\n",
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