Geospatial DataFrames for Rust and Python
GeoPolars extends the Polars DataFrame library for use with geospatial data.
At this point, GeoPolars is a prototype and should not be considered production-ready.
GeoPolars is published to crates.io under the name geopolars.
Documentation is available at docs.rs/geopolars.
An early alpha (v0.1.0-alpha.3) is published to PyPI:
pip install --pre geopolars
The publishing processs includes binary wheels for many platforms, so it should be easy to install, without needing to compile the underlying Rust code from source.
A documentation website has been started but is not yet hosted online.
Polars itself does not yet exist in WebAssembly, though there has been discussion about adding bindings for it. The long-term goal of GeoPolars is to have a WebAssembly API as well.
Imitation is the sincerest form of flattery! GeoPandas — and its underlying libraries of shapely and GEOS — is an incredible production-ready tool.
GeoPolars is nowhere near the functionality or stability of GeoPandas, but competition is good and, due to its pure-Rust core, GeoPolars will be much easier to use in WebAssembly.
The biggest pieces of future work are:
FixedSizeList data types, but they've recently expressed openness to adding minimal FixedSizeList support.Enable georust/geo algorithms to access Arrow data with zero copy. The prototype currently copies WKB geometries into geo structs on each geometry operation, which is expensive.
This is blocked on adding support to the geo library for geometry access traits, which is a large undertaking. See georust/geo/discussions/838. I've started exploration on this
Implement GeoArrow extension types for seamless handling of CRS metadata in Rust, rather than in the Python wrapper.