Changelog¶

[0.2.0] - 2025-01-06¶

Support for nearest neighbor searching on RTrees with neighbors.
Join two RTrees together with tree_join, finding their overlapping elements. This is the first part of a spatial join: to find which elements from two different data sources potentially intersect.
Extract partitioning structure from the underlying RTree with partitions and see the partition geometries with partition_boxes.
Expose RTreeMetadata and KDTreeMetadata. These allow you to infer the memory usage a tree would incur.
Access the internal boxes within the RTree for inspecting the tree internals with boxes_at_level.
Implement the buffer protocol on RTree and KDTree. This means you can copy the underlying buffer to Python with bytes(tree).

Move RTree and KDTree query functions to standalone global functions. This makes it easier to persist index buffers and reuse them later, because the query functions work on any object supporting the buffer protocol.
Create "builder" classes: RTreeBuilder and KDTreeBuilder. Having these as separate classes allows for iteratively adding the coordinates for an RTree or KDTree. This is useful when the source geometries are larger than fits in memory.