Kyle Barron
Kyle is a software engineer at Development Seed where he builds open source tools and infrastructure that process and visualize geospatial data. He has expertise in cloud-native geospatial vector data formats, speeding up Python and JavaScript applications from Rust, spatial indexes, and efficient data pipelines. Kyle holds a B.A. in Economics, minoring in Mathematics from the University of California, Los Angeles which he earned in 2017.
Kyle previously worked as a software engineer at Unfolded and then Foursquare, building browser-based geospatial data visualizations on the web for vector and raster data.
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Sessions
Lonboard is a new Python library for geospatial vector data visualization that can be 50x faster than existing alternatives like ipyleaflet
or pydeck
. This talk will explain why this library is so fast, how it integrates into existing workflows, and planned future improvements.
Data protocols enable innovation by providing a stable boundary between data producer and consumer, allowing an ecosystem of libraries to reliably interoperate.
The __geo_interface__ protocol
allows transferring GeoJSON-like objects but this can be very slow for large datasets. GeoArrow solves this problem by providing a binary data interchange format for geospatial data.
Existing Python libraries like pyogrio
(which binds to GDAL) have achieved massive speedups by adopting GeoArrow. New Python libraries like geoarrow-rust
and geoarrow-c
store GeoArrow internally, ensuring zero-copy data movement across Python, Rust, and C. Lonboard uses GeoArrow across Python and JavaScript to interactively visualize millions of geometries in Jupyter Notebooks.