2025-12-10 –, Data Engineering & Infrastructure
OpenStreetMap data is publicly available, but it's hard to get it downloaded at scale without domain knowledge and an external technology stack.
With QuackOSM, you can easily work with whole-country vector and tag data without installing additional dependencies - come and find out how you can use it in your next project!
QuackOSM is a powerful and user-friendly library that streamlines the process of accessing and manipulating OpenStreetMap (OSM) vector and tags data. It's using the DuckDB engine with its Spatial extension, and PyArrow library that enables users to efficiently retrieve large-scale OSM data in the GeoParquet format.
It's similar in functionality to other available libraries, but it's faster, can work with bigger than memory datasets and doesn't require any additional dependencies.
Target audience:
Data engineers/analysts/scientists who have worked with or want to work with geospatial data.
Outline:
- Brief OpenStreetMap data introduction
- Introduction to DuckDB and PyArrow
- Why is it hard to work with big OSM datasets? Introduction to the OpenStreetMap data schema and PBF format.
- QuackOSM overview: basic usage, data filtering, example use-cases + benchmark against available libraries (OSMnx, Pyrosm, PyDriosm and others).
- Example of a simple ML model built on top of geospatial data
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Geospatial Data Scientist with a drive to contribute to the open-source space. Co-developer of SRAI library and maintainer of QuackOSM and OvertureMaestro libraries.
Interested in exploring how machine learning models with geospatial data can improve our lives.