OSMnx

2.1.0 · active · verified Mon Apr 13

OSMnx is a Python package that simplifies the process of downloading, modeling, analyzing, and visualizing street networks and other geospatial features directly from OpenStreetMap. It is built upon NetworkX and GeoPandas, providing a powerful toolkit for urban and spatial analysis. The current version is 2.1.0, and the library maintains an active development cycle with regular updates and major releases that may introduce breaking changes.

Warnings

breaking The OSMnx 2.0 release (November 2024) introduced significant breaking changes, including a streamlined API, refactored modules, and the removal of previously deprecated functionality. Code written for v1.x will likely require updates to be compatible with v2.x.
Fix: Consult the official OSMnx 2.0 Migration Guide and the Examples Gallery. When running v1.9.x, pay attention to `FutureWarning` messages, which provide guidance for v2.0 compatibility. Many function signatures and module locations have changed.
gotcha Installing OSMnx via `pip` can be challenging on some systems due to its dependencies (e.g., GeoPandas, Shapely, Rasterio) which rely on compiled C/C++ libraries. Compilation issues can arise.
Fix: The recommended installation method, especially for users encountering issues, is to use `conda` via the `conda-forge` channel (`conda install -c conda-forge osmnx`). Conda handles the complex binary dependencies more reliably.
gotcha OSMnx heavily leverages NetworkX graphs and GeoPandas GeoDataFrames. Users unfamiliar with these underlying libraries may struggle to effectively use or troubleshoot OSMnx, as its data models are built upon them.
Fix: Familiarize yourself with the core concepts and data structures of NetworkX and GeoPandas. The OSMnx documentation and examples often assume a basic understanding of these libraries.
gotcha As OSMnx retrieves data from OpenStreetMap, all derivative works and visualizations generated using OSMnx must provide proper attribution to OpenStreetMap, in accordance with its open data license.
Fix: Always include a clear attribution to OpenStreetMap when presenting or publishing data or visualizations derived from OSMnx. Refer to OpenStreetMap's copyright and license guidelines for specifics.
deprecated In recent pandas versions, directly accessing elements of a `pandas.Series` by positional index (e.g., `x[0]`, `x[1]`) within `.apply()` functions for geographic coordinates (latitude/longitude) is deprecated and will raise a `FutureWarning`. This is common in functions like `ox.distance.nearest_nodes`.
Fix: Use `.iloc` for explicit positional indexing (e.g., `x.iloc[0]`, `x.iloc[1]`) to access elements from a `pandas.Series` within `apply` functions, ensuring future compatibility and suppressing warnings.
gotcha OSMnx uses the OpenStreetMap Overpass API for data retrieval. Frequent or very large data requests can lead to hitting API rate limits, which may result in failed queries or temporary IP blocks from the Overpass server.
Fix: Enable and configure OSMnx's caching (`ox.settings.use_cache = True`) to minimize redundant API calls. Design your queries to be as specific and small as possible, and introduce delays between large requests if necessary to avoid overwhelming the API.
gotcha For very large graphs, some network analysis functions provided by NetworkX (and consequently used by OSMnx) can be computationally intensive and slow, as NetworkX is primarily a Python-native library.
Fix: For performance-critical analyses on massive graphs, consider exporting the OSMnx graph to formats compatible with faster graph libraries like `igraph` or `graph-tool` (which have C backends) for specific computational tasks, then re-importing results if needed.

Install

pip install osmnx PyPI (recommended if dependencies are pre-installed)
conda install -c conda-forge osmnx Conda (recommended for easier dependency management)

Imports

osmnx
```
import osmnx as ox
```
Standard convention for importing the library.
graph
```
import osmnx.graph as ox_graph
```
Accessing specific modules like 'graph' directly is common, but often 'ox.graph' is sufficient.
plot
```
import osmnx.plot as ox_plot
```
Accessing specific modules like 'plot' directly is common, but often 'ox.plot' is sufficient.

Quickstart

This quickstart demonstrates how to download a drivable street network for a specified place and then visualize it. It also shows how to enable caching for API requests.

import osmnx as ox

# Configure osmnx to use a cache for API calls
ox.settings.use_cache = True

# Download and model a street network for a place
place = "Piedmont, California, USA"
G = ox.graph.graph_from_place(place, network_type="drive")

# Plot the graph
fig, ax = ox.plot_graph(G)

view raw JSON →