Backport PR #2051 on branch 0.12.x (fix: allow writing to v3/2 store when setting is v2/3 if possible)

docs/tutorials/zarr-v3.md

@@ -1,6 +1,6 @@
 # zarr-v3 Guide/Roadmap
 
-`anndata` now uses the much improved {mod}`zarr` v3 package and also allows writing of datasets in the v3 format via {attr}`anndata.settings.zarr_write_format`, with the exception of structured arrays.
+`anndata` now uses the much improved {mod}`zarr` v3 package and also allows writing of datasets in the v3 format via {attr}`anndata.settings.zarr_write_format` via {func}`anndata.io.write_zarr` or {meth}`anndata.AnnData.write_zarr`, with the exception of structured arrays.
 Users should notice a significant performance improvement, especially for cloud data, but also likely for local data as well.
 Here is a quick guide on some of our learnings so far:
 
@@ -48,7 +48,7 @@ import anndata as ad
 from collections.abc import Mapping
 from typing import Any
 
-ad.settings.zarr_write_format = 3 # Absolutely crucial! Sharding is only for the v3 file format!
+g = zarr.open_group(orig_path, mode="a", use_consolidated=False, zarr_version=3) # zarr_version 3 is default but note that sharding only works with v3!
 
 def write_sharded(group: zarr.Group, adata: ad.AnnData):
     def callback(

src/anndata/_io/specs/methods.py

@@ -630,7 +630,7 @@ def write_vlen_string_array_zarr(
         dataset_kwargs = zarr_v3_compressor_compat(dataset_kwargs)
         dtype = VariableLengthUTF8()
         filters, fill_value = None, None
-        if ad.settings.zarr_write_format == 2:
+        if f.metadata.zarr_format == 2:
             filters, fill_value = [VLenUTF8()], ""
         f.create_array(
             k,
@@ -1283,7 +1283,7 @@ def write_scalar_zarr(
         from numcodecs import VLenUTF8
         from zarr.core.dtype import VariableLengthUTF8
 
-        match ad.settings.zarr_write_format, value:
+        match f.metadata.zarr_format, value:
             case 2, str():
                 filters, dtype, fill_value = [VLenUTF8()], VariableLengthUTF8(), ""
             case 3, str():

src/anndata/_settings.py

@@ -447,7 +447,7 @@ def validate_zarr_write_format(format: int):
 settings.register(
     "zarr_write_format",
     default_value=2,
-    description="Which version of zarr to write to.",
+    description="Which version of zarr to write to when anndata must internally open a write-able zarr group.",
     validate=validate_zarr_write_format,
     get_from_env=lambda name, default: check_and_get_environ_var(
         f"ANNDATA_{name.upper()}",

src/anndata/compat/__init__.py

@@ -286,8 +286,12 @@ def _to_fixed_length_strings(value: np.ndarray) -> np.ndarray:
     """\
     Convert variable length strings to fixed length.
 
-    Currently a workaround for
-    https://github.com/zarr-developers/zarr-python/pull/422
+    Formerly a workaround for
+    https://github.com/zarr-developers/zarr-python/pull/422,
+    resolved in https://github.com/zarr-developers/zarr-python/pull/813.
+
+    But if we didn't do this conversion, we would have to use a special codec in v2
+    for objects and v3 doesn't support objects at all.  So we leave this function as-is.
     """
     new_dtype = []
     for dt_name, (dt_type, dt_offset) in value.dtype.fields.items():

tests/test_backed_sparse.py

@@ -513,11 +513,14 @@ def test_data_access(
     data = f["X/data"][...]
     del f["X/data"]
     # chunk one at a time to count properly
+    kwargs = {}
+    if not is_zarr_v2():
+        kwargs["zarr_format"] = f.metadata.zarr_format
     zarr.array(
         data,
         store=path / "X" / "data",
         chunks=(1,),
-        zarr_format=ad.settings.zarr_write_format,
+        **kwargs,
     )
     store = AccessTrackingStore(path)
     store.initialize_key_trackers(["X/data"])

tests/test_io_elementwise.py

@@ -206,14 +206,6 @@ def create_sparse_store(
     ],
 )
 def test_io_spec(store, value, encoding_type):
-    # zarr v3 can't write recarray
-    # https://github.com/zarr-developers/zarr-python/issues/2134
-    if (
-        ad.settings.zarr_write_format == 3
-        and encoding_type == "anndata"
-        and "O_recarray" in value.uns
-    ):
-        del value.uns["O_recarray"]
     with ad.settings.override(allow_write_nullable_strings=True):
         key = f"key_for_{encoding_type}"
         write_elem(store, key, value, dataset_kwargs={})
@@ -564,10 +556,6 @@ def test_write_to_root(store, value):
     """
     Test that elements which are written as groups can we written to the root group.
     """
-    # zarr v3 can't write recarray
-    # https://github.com/zarr-developers/zarr-python/issues/2134
-    if ad.settings.zarr_write_format == 3 and isinstance(value, ad.AnnData):
-        del value.uns["O_recarray"]
     write_elem(store, "/", value)
     # See: https://github.com/zarr-developers/zarr-python/issues/2716
     if isinstance(store, ZarrGroup) and not is_zarr_v2():

tests/test_io_partial.py

@@ -10,7 +10,6 @@
 import zarr
 from scipy.sparse import csr_matrix
 
-import anndata
 from anndata import AnnData
 from anndata._io.specs.registry import read_elem_partial
 from anndata.io import read_elem, write_h5ad, write_zarr
@@ -51,11 +50,6 @@ def test_read_partial_adata(tmp_path, diskfmt):
         import scanpy as sc
 
     adata = sc.datasets.pbmc68k_reduced()
-    # zarr v3 can't write recarray
-    # https://github.com/zarr-developers/zarr-python/issues/2134
-    if anndata.settings.zarr_write_format == 3 and isinstance(adata, AnnData):
-        del adata.uns["rank_genes_groups"]["scores"]
-        del adata.uns["rank_genes_groups"]["names"]
 
     path = Path(tmp_path) / ("test_rp." + diskfmt)
 

tests/test_readwrite.py

@@ -843,11 +843,6 @@ def test_scanpy_pbmc68k(tmp_path, diskfmt, roundtrip, diskfmt2):
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", ad.OldFormatWarning)
         pbmc = sc.datasets.pbmc68k_reduced()
-        # zarr v3 can't write recarray
-        # https://github.com/zarr-developers/zarr-python/issues/2134
-        if ad.settings.zarr_write_format == 3:
-            del pbmc.uns["rank_genes_groups"]["names"]
-            del pbmc.uns["rank_genes_groups"]["scores"]
 
     from_disk1 = roundtrip(pbmc, filepth1)  # Do we read okay
     from_disk2 = roundtrip2(from_disk1, filepth2)  # Can we round trip
@@ -1010,3 +1005,18 @@ def test_write_elem_consolidated(tmp_path: Path):
         ValueError, match="Cannot overwrite/edit a store with consolidated metadata"
     ):
         ad.io.write_elem(g["obs"], "foo", np.arange(10))
+
+
+@pytest.mark.zarr_io
+@pytest.mark.skipif(is_zarr_v2(), reason="zarr v3 package test")
+def test_write_elem_version_mismatch(tmp_path: Path):
+    zarr_path = tmp_path / "foo.zarr"
+    adata = ad.AnnData(np.ones((10, 10)))
+    g = zarr.open_group(
+        zarr_path,
+        mode="w",
+        zarr_format=2 if ad.settings.zarr_write_format == 3 else 3,
+    )
+    ad.io.write_elem(g, "/", adata)
+    adata_roundtripped = ad.read_zarr(g)
+    assert_equal(adata_roundtripped, adata)