What happened?
When aligning two Datasets, indexes that are already aligned (require no reindexing) are not considered when checking for index conflicts.
More concretely:
When I attempt to align two Datasets that share two indexes for the same dimension of which one is aligned (requires no reindexing) and the other is not, no error is raised if these indexes conflict with one another. The mismatched index is used to align the data.
What did you expect to happen?
I would expect an AlignmentError to be raised when an attempt is made to align objects with conflicting indexes in all situations.
Minimal Complete Verifiable Example
from xarray import align, Dataset
ds1 = Dataset(coords={"x": [1, 2, 3], "xb": ("x", [4, 5, 6])}).set_xindex("xb")
# Swap two values in only "xb" only
ds2 = Dataset(coords={"x": [1, 2, 3], "xb": ("x", [4, 6, 5])}).set_xindex("xb")
# Swap two (different) values in both coordinates
ds3 = Dataset(coords={"x": [2, 1, 3], "xb": ("x", [4, 6, 5])}).set_xindex("xb")
align(ds1, ds2) # --> no error (which is wrong)
align(ds1, ds3) # --> AlignmentError (as expected)
MVCE confirmation
Relevant log output
Anything else we need to know?
Until recently, alignment it was not possible when multiple indexes shared a dimension. This functionality was introduced in xarray v2025.04.0 and originally merged in PR #8436 by @benbovy .
The problem is that the index consistency checks ignore indexes that require no reindexing.
# Source: xarray/structure/alignment.py
def _get_dim_pos_indexers(
self,
matching_indexes: dict[MatchingIndexKey, Index],
) -> dict[Hashable, Any]:
dim_pos_indexers: dict[Hashable, Any] = {}
dim_index: dict[Hashable, Index] = {}
for key, aligned_idx in self.aligned_indexes.items():
obj_idx = matching_indexes.get(key)
if obj_idx is not None and self.reindex[key]:
#######################################################################
# ↓ None of this code is run for indexes that require no reindexing ↓ #
#######################################################################
indexers = obj_idx.reindex_like(aligned_idx, **self.reindex_kwargs)
for dim, idxer in indexers.items():
if dim in self.exclude_dims:
raise AlignmentError(
f"cannot reindex or align along dimension {dim!r} because "
"it is explicitly excluded from alignment. This is likely caused by "
"wrong results returned by the `reindex_like` method of this index:\n"
f"{obj_idx!r}"
)
if dim in dim_pos_indexers and not np.array_equal(
idxer, dim_pos_indexers[dim]
):
raise AlignmentError(
f"cannot reindex or align along dimension {dim!r} because "
"of conflicting re-indexers returned by multiple indexes\n"
f"first index: {obj_idx!r}\nsecond index: {dim_index[dim]!r}\n"
)
dim_pos_indexers[dim] = idxer
dim_index[dim] = obj_idx
return dim_pos_indexers
Environment
Details
INSTALLED VERSIONS
------------------
commit: None
python: 3.13.2 (main, Mar 11 2025, 17:20:07) [MSC v.1943 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 11
machine: AMD64
processor: Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_United States', '1252')
libhdf5: None
libnetcdf: None
xarray: 2025.9.0
pandas: 2.3.2
numpy: 2.3.2
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
zarr: None
cftime: None
nc_time_axis: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: None
pip: None
conda: None
pytest: None
mypy: None
IPython: 9.5.0
sphinx: None
What happened?
When aligning two Datasets, indexes that are already aligned (require no reindexing) are not considered when checking for index conflicts.
More concretely:
When I attempt to align two Datasets that share two indexes for the same dimension of which one is aligned (requires no reindexing) and the other is not, no error is raised if these indexes conflict with one another. The mismatched index is used to align the data.
What did you expect to happen?
I would expect an
AlignmentErrorto be raised when an attempt is made to align objects with conflicting indexes in all situations.Minimal Complete Verifiable Example
MVCE confirmation
Relevant log output
Anything else we need to know?
Until recently, alignment it was not possible when multiple indexes shared a dimension. This functionality was introduced in xarray v2025.04.0 and originally merged in PR #8436 by @benbovy .
The problem is that the index consistency checks ignore indexes that require no reindexing.
Environment
Details
INSTALLED VERSIONS ------------------ commit: None python: 3.13.2 (main, Mar 11 2025, 17:20:07) [MSC v.1943 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 11 machine: AMD64 processor: Intel64 Family 6 Model 142 Stepping 12, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: ('English_United States', '1252') libhdf5: None libnetcdf: Nonexarray: 2025.9.0
pandas: 2.3.2
numpy: 2.3.2
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
zarr: None
cftime: None
nc_time_axis: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: None
pip: None
conda: None
pytest: None
mypy: None
IPython: 9.5.0
sphinx: None