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https://github.com/amauryval/osmrx
Geographic Python library to extract Open Street Map roads (and POIs) from a location or a bounding box, in order to create a graph thanks to Rustworkx. OsmRx is able to clean a network based on Linestring geometries and connect Point geometries. The graph built is able to process graph-analysis (shortest-path, isochrones...)
https://github.com/amauryval/osmrx
geography graph isochrones maps network-analysis nominatim openstreetmap overpass-api pedestrian point-of-interest python rustworkx shortest-path topology vehicle
Last synced: 24 days ago
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Geographic Python library to extract Open Street Map roads (and POIs) from a location or a bounding box, in order to create a graph thanks to Rustworkx. OsmRx is able to clean a network based on Linestring geometries and connect Point geometries. The graph built is able to process graph-analysis (shortest-path, isochrones...)
- Host: GitHub
- URL: https://github.com/amauryval/osmrx
- Owner: amauryval
- License: gpl-3.0
- Created: 2023-02-25T16:48:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-04-23T20:29:42.000Z (over 1 year ago)
- Last Synced: 2024-09-13T17:51:13.092Z (about 2 months ago)
- Topics: geography, graph, isochrones, maps, network-analysis, nominatim, openstreetmap, overpass-api, pedestrian, point-of-interest, python, rustworkx, shortest-path, topology, vehicle
- Language: Python
- Homepage:
- Size: 5.92 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# OsmRx
A geographic Python library to extract Open Street Map roads (and POIs) from a location or a bounding box, in order to create a graph thanks to [Rustworkx](https://github.com/Qiskit/rustworkx). OsmRx is able to clean a network based on Linestring geometries and connect Point geometries. The graph built is able to process graph-analysis (shortest-path, isochrones...)
Capabilities:
* load data from a location name or a bounding box (roads and pois)
* graph creation (and topology processing and cleaning)
* shortest path
* isochrone builder
[](https://github.com/amauryval/osmrx/actions/workflows/main.yml)
[](https://codecov.io/gh/amauryval/osmrx)
[](https://badge.fury.io/py/osmrx)
Check the demo [here](https://amauryval.github.io/omsrx/)
## How to install it ?
### with pip
```bash
pip install osmrx
```
## How to use it ?
Check the jupyter notebook [here](https://amauryval.github.io/OsmRx/)
Check the wiki: TODO
### Get POIs
Find the Points of interest from a location (Point(s)) or a bounding box:
* OSM attributes are returned
* features ready to be used with shapely, GeoPandas (...):
```python
from osmrx.main.pois import Pois
location_name = "lyon"
# Initialize the Pois class
pois_object = Pois()
# call .from_location(location: str) or .from_bbox(bounds: Tuple[float, float, float, float]) to get data from your location
pois_object.from_location(location_name) # nominatim api is used to get Lyon coordinates
# It returns a list of dictionnaries [{"geometry": Point(...), "attribute": "...", ...}
# Free for you to use it with GeoPandas or something else (epsg=4326)
pois_data_found = pois_object.data
```
### Get Roads
Find the vehicle or pedestrian network (LineString(s)) from a location or a bounding box:
* OSM attributes available
* OSM features ready to be used with shapely, GeoPandas (...):
* data cleaned regarding classical topology rules
```python
from osmrx.main.roads import Roads
# Choose the vehicle or the pedestrian network
roads_object = Roads("vehicle")
# from_location(location: str) is available
roads_object.from_bbox({6.019674, 4.023742, 46.072575, 4.122018})
# It returns a list of dictionnaries [{"geometry": Point(...), "attribute": "...", ...}
# Free for you to use it with GeoPandas or something else (epsg=4326)
roads_data_found = roads_object.data
# return the rustworkx graph (directed for vehicle / undirected for pedestrian)
graph = roads_object.graph
# Free for you to compute graph analysis
```
### Compute a shortest path
Compute the shortest path from an ordered list of Point(s) (at least 2)
```python
from shapely import Point
from osmrx.main.roads import GraphAnalysis
# use the GraphAnalysis class and set:
# the network type (pedestrian or vehicle) and an ordered list of 2 Shapely Points defining the source and the target
# of your shortest path)
analysis_object = GraphAnalysis("pedestrian",
[Point(4.0793058, 46.0350304), Point(4.0725246, 46.0397676)]) # (epsg=4326)
paths_built = analysis_object.get_shortest_path()
for path_object in paths_built:
print(path_object.path) # LineString shortest path (epsg=4326)
print(path_object.features()) # List of LineString (with osm attributes) composing the path found
```
### Compute an Isochrone
Build an isochrone (Polygon(s)) from a Point
```python
from shapely import Point
from osmrx.main.roads import GraphAnalysis
# use the GraphAnalysis class and set:
# the network type (pedestrian or vehicle) and a list of one Shapely Point (epsg=4326) to build the isochone
analysis_object = GraphAnalysis("vehicle", [Point(4.0793058, 46.0350304)])
# Set the distance intervals to compute the isochone with a list of integer or float
isochrones_built = analysis_object.isochrones_from_distance([0, 250, 500, 1000, 1500])
# List of Polygons with a distance attributes based on the intervals defined
print(isochrones_built.data)
```