> Project Update (June 2025): A new maintainer has taken over the project as of June 16, 2025. Over the coming weeks, I'll be reviewing the codebase, triaging issues and pull requests, and identifying areas that may need updating. A new release is targeted for July 2025. Stay tuned for updates!
One lib to route them all - routingpy is a Python 3 client for several popular routing webservices.
Inspired by geopy and its great community of contributors, routingpy enables easy and consistent access to third-party spatial webservices to request route directions, isochrones or time-distance matrices.
routingpy currently includes support for the following services:
This list is hopefully growing with time and contributions by other developers. An up-to-date list is always available in our documentation.
routingpy is tested against:
© routingpy contributors 2022 under the Apache 2.0 License.
You want to
and don't know which provider to use? Great. Then routingpy is exactly what you're looking for.
For the better or worse, every provider works on different spatial global datasets and uses a plethora of algorithms on top. While Google or HERE build on top of proprietary datasets, providers such as Mapbox or Graphhopper consume OpenStreetMap data for their base network. Also, all providers offer a different amount of options one can use to restrict the wayfinding. Ultimately this means that results may differ - and our experience tells us: they do, and not too little. This calls for a careful evaluation which service provider to use for which specific use case.
With routingpy we have made an attempt to simplify this process for you.
Recommended: Install via poetry:
Install using pip with
Or the lastest from source
pip install git+git://github.com/mthh/routingpy
Every provider has its own specifications and features. However the basic blueprints are the same across all. We tried hard to make the transition from one provider to the other as seamless as possible. We follow two dogmas for all implementations:
This naturally means that usually those basic parameters are not named the same way as the endpoints they query. However, all provider specific parameters are named the exact same as their remote counterparts.
The following table gives you an overview which basic arguments are abstracted:
Endpoint Argument Function
directions locations
Specify the locations to be visited in order. Usually this
is done with [Lon, Lat] tuples, but some routers offer
additional options to create a location element.
profileThe mode of transport, i.e. car, bicycle, pedestrian. Each
router specifies their own profiles.
isochrones locations
Specify the locations to calculate isochrones for. Usually
this is done with [Lon, Lat] tuples, but some routers
offer additional options to create a location element.
profileThe mode of transport, i.e. car, bicycle, pedestrian. Each
router specifies their own profiles.
intervalsThe ranges to calculate isochrones for. Either in seconds
or in meters, depending on interval_type.
The dimension of intervals, which takes router
dependent values, but generally describes time or distance
matrix locations
Specify all locations you want to calculate a matrix
for. If sources or destinations is not set, this
will return a symmetrical matrix. Usually this is done
with [Lon, Lat] tuples, but some routers offer
additional options to create a location element.
profileThe mode of transport, i.e. car, bicycle, pedestrian. Each
router specifies their own profiles.
sourcesThe indices of the locations parameter iterable to
take as sources for the matrix calculation. If not
specified all locations are considered to be sources.
The indices of the locations parameter iterable to
take as destinations for the matrix calculation. If not
specified all locations are considered to be
destinations.
We ❤️ contributions and realistically think that's the only way to support and maintain most routing engines in the long run. To get you started, we created a Contribution guideline.
Follow our examples to understand how simple routingpy is to use.
On top of the examples listed below, find interactive notebook(s) on mybinder.org.
routingpy is designed to take the burden off your shoulder to parse the JSON response of each provider, exposing the most important information of the response as attributes of the response object. The actual JSON is always accessible via the raw attribute:
from routingpy import Valhalla
from pprint import pprint
# Some locations in Berlin
coords = [[13.413706, 52.490202], [13.421838, 52.514105],
[13.453649, 52.507987], [13.401947, 52.543373]]
client = Valhalla()
route = client.directions(locations=coords, profile='pedestrian')
isochrones = client.isochrones(locations=coords[0], profile='pedestrian', intervals=[600, 1200])
matrix = client.matrix(locations=coords, profile='pedestrian')
pprint((route.geometry, route.duration, route.distance, route.raw))
pprint((isochrones.raw, isochrones[0].geometry, isochrones[0].center, isochrones[0].interval))
pprint((matrix.durations, matrix.distances, matrix.raw))
Easily calculate routes, isochrones and matrices for multiple providers:
from routingpy import Graphhopper, ORS, MapboxOSRM
from shapely.geometry import Polygon
# Define the clients and their profile parameter
apis = (
(ORS(api_key='ors_key'), 'cycling-regular'),
(Graphhopper(api_key='gh_key'), 'bike'),
(MapboxOSRM(api_key='mapbox_key'), 'cycling')
)
# Some locations in Berlin
coords = [[13.413706, 52.490202], [13.421838, 52.514105],
[13.453649, 52.507987], [13.401947, 52.543373]]
for api in apis:
client, profile = api
route = client.directions(locations=coords, profile=profile)
print("Direction - {}:\n\tDuration: {}\n\tDistance: {}".format(client.__class__.__name__,
route.duration,
route.distance))
isochrones = client.isochrones(locations=coords[0], profile=profile, intervals=[600, 1200])
for iso in isochrones:
print("Isochrone {} secs - {}:\n\tArea: {} sqm".format(client.__class__.__name__,
iso.interval,
Polygon(iso.geometry).area))
matrix = client.matrix(locations=coords, profile=profile)
print("Matrix - {}:\n\tDurations: {}\n\tDistances: {}".format(client.__class__.__name__,
matrix.durations,
matrix.distances))
Often it is crucial to examine the request before it is sent. Mostly useful for debugging:
from routingpy import ORS
client = ORS(api_key='ors_key')
route = client.directions(
locations = [[13.413706, 52.490202], [13.421838, 52.514105]],
profile='driving-hgv',
dry_run=True
) Local instance of FOSS router
All FOSS routing engines can be run locally, such as openrouteservice, Valhalla, OSRM and GraphHopper. To be able to use routingpy with a local installation, just change the base_url of the client. This assumes that you did not change the URL(s) of the exposed endpoint(s):
from routingpy import Valhalla # no trailing slash, api_key is not necessary client = Valhalla(base_url='http://localhost:8088/v1')Proxies, Rate limiters and API errors
Proxies are easily set up using following requests scheme for proxying. Also, when batch requesting, routingpy can be set up to resume its requests when the remote API rate limits (i.e. responds with HTTP 429). Also, it can be set up to ignore API errors and instead print them as warnings to stdout. Be careful, when ignoring RouterApiErrors, those often count towards your rate limit.
All these parameters, and more, can optionally be globally set for all router modules or individually per instance:
from routingpy import Graphhopper, ORS
from routingpy.routers import options
request_kwargs = dict(proxies=dict(https='129.125.12.0'))
client = Graphhopper(
api_key='gh_key',
retry_over_query_limit=False,
skip_api_error=True,
requests_kwargs=request_kwargs
)
# Or alternatively, set these options globally:
options.default_proxies = {'https': '129.125.12.0'}
options.default_retry_over_query_limit = False
options.default_skip_api_error = True
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