Changelog

[0.4.0] - 2026-06-16

gdalxarray.warp() — build lazy warp-VRT recipes for reprojection, regridding, GCP/RPC/geolocation-array transformation, cutline clipping, and resampling. Returns a VRT XML string that composes with the gdalxarray engine: only the bytes the consumer reads are materialised. Common args (crs, bbox, shape, resolution, resampling, nodata) plus a full escape hatch for any gdal.WarpOptions keyword.

Classic-raster open (multidim=False) on a file with no bands but subdatasets now raises a ValueError listing the available subdataset paths and pointing at multidim=True. Previously this produced an empty 512x512 stub Dataset.

band_as_dim parameter on open_dataset (classic raster mode, default True). Bands now become an xarray band dimension on a single band_data DataArray. Pass band_as_dim=False for per-band-variable layout.
New GDALMultiBandArray BackendArray reading via dataset.ReadAsArray(band_list=...), letting GDAL handle BIP/BIL/BSQ interleaving internally.
Lazy-by-default for classic raster mode: chunks=None now returns a LazilyIndexedArray-wrapped Dataset rather than eagerly reading.
ds.encoding["source"] and ds.encoding["gdal_driver"] provenance strings (serialization-safe replacements for the live GDAL objects previously stashed in encoding).
[tool.ruff] config + .pre-commit-config.yaml for lint and format.

gdal.UseExceptions() moved from module import to GDALBackendEntrypoint.__init__, guarded with gdal.GetUseExceptions(). Scopes the side effect to actual backend use.
GDALMultiDimArray now holds optional _parent_dataset and _parent_group references internally to keep the underlying mdarray valid for the dataset's lifetime. Previously stashed in ds.encoding, which broke to_netcdf() and other serialization paths.
Per-band metadata (description, nodata, scale, offset) in band_as_dim mode is attached as scalar attrs when uniform across bands, or as band-dim coordinates when it varies.
Multidim group navigation accepts nested paths ("/a/b/c") with tolerant leading/trailing slash handling.
Unsupported codecs on individual MDArrays (e.g. numcodecs.pcodec) are now logged at warning level and the array skipped, instead of aborting the open. This lets you open stores like Earthmover's public ERA5 Icechunk store and access the readable coordinate/mask variables.

Dataset.ReadAsArray call in GDALMultiBandArray now uses xsize/ysize (the Dataset API) rather than win_xsize/win_ysize (which are the Band API).
Reverse-slice canonicalisation across all axes in all three BackendArray classes - fixes failures when xarray sends slice(stop, start, 1) for selections on decreasing coordinates (very common in atmospheric data with latitude 90 -> -90).
GDALBackendArray.__dask_tokenize__ no longer references a non-existent self.dataset attribute. Was latent (only fired on certain Dask graph hashing paths) but would have raised AttributeError when it did.
AdviseRead now skips both tiny reads (no benefit) and huge reads (which blow up on sharded stores reporting shard-sized blocks); bounded CACHE_SIZE between 4 MB and 512 MB.

Live GDAL objects no longer stored in ds.encoding. Use ds.encoding["source"] and ds.encoding["gdal_driver"] (strings) for introspection. GDAL refs are now held inside the BackendArrays themselves.

Renamed package from gdx to gdalxarray for PyPI publication. The original gdx name is taken on PyPI by an unrelated GAMS Data Exchange project.
Repository moved from mdsumner/gdx to hypertidy/gdalxarray.
Python import path is now from gdalxarray import GDALBackendEntrypoint.
Build backend switched from setuptools to hatchling; setup.py removed.
Packaging modernised to PEP 621 / PEP 639 standards.
requires-python bumped to >=3.10 to match xarray>=2025.6.

CF datetime decoding for time coordinates using units from MDArray.GetUnit() and calendar attribute.
Backend arrays accessible via ds['var'].encoding['gdal_backend'] for debugging and introspection.
GDAL dataset and group objects retained in ds.encoding['gdal_dataset'] and ds.encoding['gdal_group'] to keep MDArray methods functional.
Entry point registration so xr.open_dataset(..., engine="gdal") works.

Slice index parsing where 0 was incorrectly treated as None due to Python's falsy evaluation (k.start or 0 -> k.start if k.start is not None else 0).
Re-enabled AdviseRead for chunk-aligned prefetching on remote datasets.

Initial release as gdx.

GDAL backend for xarray, supporting both Classic and Multidimensional APIs.
chunks={} uses native block sizes from GDAL's GetBlockSize(), aligning Dask chunks with storage chunks for efficient reads.
multidim=True is the default for open_dataset().

Dask lazy loading for remote Zarr datasets. Zero-sized slice requests (used by Dask for _meta inference) no longer hang or attempt full array allocation.
Slice start/stop of 0 now parsed correctly.