An exploratory Rust library for fast, scalable geospatial operations using geo, rstar, rayon, and maybe some other crates.
This project is an experiment in writing spatial joins and filtering pipelines with performance in mind—using idiomatic Rust, geometry types from geo, and spatial indexing from rstar.
My goals are to:
- Practice Rust for spatial data processing
- Explore integration patterns with Python (via PyO3)
- Build up toward reusable primitives for point-in-polygon joins, attribute merging, and efficient FFI boundaries
Planned:
- ✅ BBox filtering
- ✅
geo::Polygon.contains - ✅ Spatial join prototype
- 🔜 RTree-based candidate filtering
- 🔜 PyO3 bindings and Python-facing API
- 🔜 More.