I/O¶

Supported formats¶

Format	Read	Write	GPU-accelerated
GeoParquet	`read_parquet()`	`to_parquet()`	WKB decode/encode, Arrow codec
GeoPackage	`read_file()`	`to_file()`	–
Shapefile	`read_file()`	`to_file()`	Arrow fast path
GeoJSON	`read_file()`	`to_file()`	GPU byte-classify parser (Point, LineString, Polygon)
Feather	`read_feather()`	`to_feather()`	Arrow codec
PostGIS	`read_postgis()`	`to_postgis()`	–

Reading files¶

import vibespatial

# Auto-detect format
gdf = vibespatial.read_file("data.gpkg")

# GeoParquet (recommended for large datasets)
gdf = vibespatial.read_parquet("data.parquet")

# PostGIS
from sqlalchemy import create_engine
engine = create_engine("postgresql://user:pass@host/db")
gdf = vibespatial.read_postgis("SELECT * FROM my_table", engine)

Writing files¶

gdf.to_file("output.gpkg", driver="GPKG")
gdf.to_parquet("output.parquet")
gdf.to_postgis("my_table", engine)

GeoParquet performance¶

GeoParquet is the recommended format for large datasets. vibeSpatial’s GeoParquet reader:

Plans row group selection based on spatial metadata
Decodes WKB geometry on GPU when available
Produces device-resident OwnedGeometryArray without host round-trips

GeoJSON GPU acceleration¶

For GeoJSON files larger than ~10 MB, vibeSpatial uses a GPU byte-classify parser (ADR-0038) that parses JSON structure, extracts coordinates, and assembles Point, LineString, and Polygon geometries directly on-device. Property extraction stays on CPU via orjson.

When kvikio is installed, file-to-device transfer uses parallel POSIX I/O with pinned bounce buffers for additional throughput.