On this episode, I’m joined by Dr. Jeff Boeing, an assistant professor at the University of Southern California whose research spans urban planning, spatial analysis, and data science. We explore why OpenStreetMap is such a powerful source of global map data—and how Jeff’s Python library, OSMnx, makes that data easier to download, model, and visualize. Along the way, we talk about what shapes city streets around the world, how urban design influences everything from daily commutes to disaster resilience, and why turning open data into accessible tools can open up completely new ways of understanding our cities. If you’ve ever wondered how to build or analyze your own digital maps in Python, or what it takes to manage a project that transforms raw geographic data into meaningful research, you won’t want to miss this conversation.

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Links from the show

City Street Orientations World: geoffboeing.com
OSMnx Documentation: readthedocs.io
OSMnx GitHub: github.com
OpenStreetMap: openstreetmap.org
Open Database License: opendatacommons.org
ID Editor (Web Editor): wiki.openstreetmap.org
Planet OSM: planet.openstreetmap.org
Overpass API: wiki.openstreetmap.org
GeoPandas: geopandas.org
NetworkX: networkx.org
Shapely: shapely.readthedocs.io
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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#495: OSMnx: Python and OpenStreetMap

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