---
id: osmnx
version: "2.1.1"
license: MIT
license_treatment: permissive
maintenance: active
---

# osmnx — Download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap

License: permissive · Maintenance: active · Downloads: 731.5K/mo

## What it is and what it does

OSMnx is a Python geospatial library that bridges OpenStreetMap data and network analysis. It lets you download street networks, building footprints, transit stops, amenities, and other geographic features with simple function calls, then model them as graphs using networkx for analysis and visualization. The package handles the complexity of querying OSM's API, parsing the results, and converting them into spatial data structures (via geopandas and shapely) that you can analyze for routing, connectivity, urban planning, or research.

You work with it by specifying a place name or geographic boundary, choosing a network type (walking, driving, biking), and calling a single function to get back a graph or GeoDataFrame. It's designed for urban researchers, planners, and developers who need to programmatically access and analyze real-world street and amenity data without manual downloads or GIS software.

Use it for:

- Download and analyze street connectivity and network topology for urban planning or transportation research.
- Extract building footprints and amenities (restaurants, shops, transit stops) from OSM for location-based analysis.
- Model walking or cycling networks to study accessibility, route efficiency, or urban design patterns.
- Visualize street orientations and network structure to understand urban morphology.
- Compute routing and travel-time analysis on real street networks for mobility studies.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

OSMnx downloads, models, and analyzes street networks and geospatial features from OpenStreetMap, letting you work with walking, driving, or biking networks, amenities, building footprints, and routing data.

Yes. OSMnx is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. It solves a real problem—programmatic access to OSM street and geospatial data—with a mature API backed by strong community adoption. Install it if you need to work with street networks, urban amenities, or geospatial features from OpenStreetMap.

## Install

pip install osmnx
uv add osmnx
poetry add osmnx

## Installing osmnx

Before you install: Low install friction with a pure-Python wheel and six well-established runtime dependencies (geopandas, networkx, numpy, pandas, requests, shapely). Actively maintained with a recent release 24 days ago and strong community engagement (5811 GitHub stars).

License in practice: MIT license is permissive and imposes no restrictions on your use. OpenStreetMap's open data license requires that derivative works provide proper attribution to the source.

Quickstart:

pip install osmnx

import osmnx as ox

# Download and model a street network
G = ox.graph_from_place('Manhattan, New York, USA', network_type='drive')

Requires Python 3.11 or later. Depends on geopandas and its system-level spatial library requirements (GEOS, PROJ).

Verify before relying:

- Whether the package handles large-scale network downloads efficiently or has memory/performance limits for very large areas.
- Specifics on which OpenStreetMap data types and tags are supported beyond street networks and amenities.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 731.5K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

openstreetmap street network analysis, download osm data python, urban network modeling, routing and network analysis, geospatial data from openstreetmap, street network visualization, osm amenities and poi extraction, gis, openstreetmap, urban-networks

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