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Python for street networks

Retrieve, model, analyze, and visualize OpenStreetMap street networks and other spatial data.

Citation info: Boeing, G. 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks." Computers, Environment and Urban Systems 65, 126-139. doi:10.1016/j.compenvurbsys.2017.05.004


OSMnx is a Python package that lets you download spatial geometries and model, project, visualize, and analyze real-world street networks from OpenStreetMap's APIs. Users can download and model walkable, drivable, or bikeable urban networks with a single line of Python code, and then easily analyze and visualize them. You can just as easily download and work with amenities/points of interest, building footprints, elevation data, street bearings/orientations, speed/travel time, and network routing.

OSMnx is built on top of geopandas, networkx, and matplotlib and interacts with OpenStreetMap's APIs to:

  • Download and model street networks or other networked infrastructure anywhere in the world with a single line of code
  • Download any other spatial geometries, place boundaries, building footprints, or points of interest as a GeoDataFrame
  • Download by city name, polygon, bounding box, or point/address + network distance
  • Download drivable, walkable, bikeable, or all street networks
  • Download node elevations and calculate edge grades (inclines)
  • Impute missing speeds and calculate graph edge travel times
  • Simplify and correct the network's topology to clean-up nodes and consolidate intersections
  • Fast map-matching of points, routes, or trajectories to nearest graph edges or nodes
  • Save networks to disk as shapefiles, geopackages, and GraphML
  • Save/load street network to/from a local .osm xml file
  • Conduct topological and spatial analyses to automatically calculate dozens of indicators
  • Calculate and visualize street bearings and orientations
  • Calculate and visualize shortest-path routes that minimize distance, travel time, elevation, etc
  • Visualize street networks as a static map or interactive leaflet web map
  • Visualize travel distance and travel time with isoline and isochrone maps
  • Plot figure-ground diagrams of street networks and building footprints

Examples and demonstrations of these features are in the examples repo. More feature development details are in the change log.


If you have any trouble with the installation, read the docs for more info.

Install OSMnx in a clean conda environment:

conda config --prepend channels conda-forge
conda create -n ox --strict-channel-priority osmnx

Alternatively, you can run OSMnx + Jupyter directly from its official docker container.

Documentation and Usage

Documentation available on readthedocs.

"How do I use OSMnx?" Usage examples and tutorials available in the examples repo.

Examples of projects and blog posts using OSMnx.

If you use OSMnx in your work, please cite the journal article.

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