Running Every Street in Paris with Python and PostGIS

Learn to build a comprehensive street-running tracking system using Python and PostGIS in this 28-minute conference talk from EuroPython 2025. Explore the fascinating project inspired by Tom Murphy's 16-year journey to run every street in Pittsburgh, covering over 3,600 miles across 269 runs. Discover how to extract street networks from OpenStreetMap data and process GPS tracking information from running activities to create a system that monitors progress toward covering every street in a city, using Paris as the primary example. Master techniques for handling GPS inaccuracies, matching running routes to street segments, and maintaining a robust database of covered streets. Dive into essential Python libraries including osmnx for street network analysis, shapely for geometric operations, and geopandas for geospatial data manipulation, while learning to store and efficiently query this information using Postgres and PostGIS. Gain practical insights into the challenges of geospatial data processing, including coordinate system transformations, spatial indexing, and optimizing database queries for large-scale street networks. Perfect for Python developers interested in geospatial applications, urban data analysis, or building location-based tracking systems.