Fix unreachable match arms in parse_dtype_v3 (float64/complex64 unsupported)

changes/167.bugfix.md

@@ -0,0 +1 @@
+Fixed unreachable match arms in `parse_dtype_v3` (in both `pydantic_zarr.v3` and `pydantic_zarr.experimental.v3`) where copy-paste errors caused `float64` and `complex64` numpy dtypes to raise `ValueError: Unsupported dtype` instead of returning the correct string names.

pyproject.toml

@@ -32,10 +32,9 @@ Source = "https://github.com/zarr-developers/pydantic-zarr"
 zarr = ["zarr>=3.0.0"]
 
 [dependency-groups]
-# pytest pin is due to https://github.com/pytest-dev/pytest-cov/issues/693
 test-base = [
     "coverage",
-    "pytest<8.4",
+    "pytest==9.1.0",
     "pytest-cov",
     "pytest-examples",
     "xarray==2025.10.0",
@@ -46,6 +45,7 @@ test = [
     "pydantic-zarr[zarr]",
 ]
 docs = [
+    {include-group = "test-base"},
     "mkdocs-material",
     "mkdocstrings[python]",
     "pytest-examples",

src/pydantic_zarr/experimental/v3.py

@@ -182,9 +182,9 @@ def parse_dtype_v3(dtype: npt.DTypeLike | Mapping[str, object]) -> Mapping[str,
                 return "float16"
             case np.dtypes.Float32DType():
                 return "float32"
-            case np.dtypes.Float16DType():
+            case np.dtypes.Float64DType():
                 return "float64"
-            case np.dtypes.Float32DType():
+            case np.dtypes.Complex64DType():
                 return "complex64"
             case np.dtypes.Complex128DType():
                 return "complex128"

src/pydantic_zarr/v3.py

@@ -62,8 +62,17 @@
 FloatFillValue = Literal["Infinity", "-Infinity", "NaN"] | float
 ComplexFillValue = tuple[FloatFillValue, FloatFillValue]
 RawFillValue = tuple[int, ...]
-
-FillValue = BoolFillValue | IntFillValue | FloatFillValue | ComplexFillValue | RawFillValue | str
+StructFillValue = Mapping[str, object]
+
+FillValue = (
+    BoolFillValue
+    | IntFillValue
+    | FloatFillValue
+    | ComplexFillValue
+    | RawFillValue
+    | str
+    | StructFillValue
+)
 
 TName = TypeVar("TName", bound=str)
 TConfig = TypeVar("TConfig", bound=Mapping[str, object])
@@ -161,9 +170,9 @@ def parse_dtype_v3(dtype: npt.DTypeLike | Mapping[str, object]) -> Mapping[str,
                 return "float16"
             case np.dtypes.Float32DType():
                 return "float32"
-            case np.dtypes.Float16DType():
+            case np.dtypes.Float64DType():
                 return "float64"
-            case np.dtypes.Float32DType():
+            case np.dtypes.Complex64DType():
                 return "complex64"
             case np.dtypes.Complex128DType():
                 return "complex128"

tests/test_docs/test_docs.py

@@ -8,12 +8,12 @@
 SOURCES_ROOT: Path = Path(__file__).parent.parent.parent / "src/pydantic_zarr"
 
 
-@pytest.mark.parametrize("example", find_examples(str(SOURCES_ROOT)), ids=str)
+@pytest.mark.parametrize("example", tuple(find_examples(str(SOURCES_ROOT))), ids=str)
 def test_docstrings(example: CodeExample, eval_example: EvalExample) -> None:
     eval_example.run_print_check(example)
 
 
-@pytest.mark.parametrize("example", find_examples("docs"), ids=str)
+@pytest.mark.parametrize("example", tuple(find_examples("docs")), ids=str)
 def test_docs_examples(example: CodeExample, eval_example: EvalExample) -> None:
     pytest.importorskip("zarr")
 

tests/test_pydantic_zarr/conftest.py

@@ -73,7 +73,6 @@ class DTypeExample:
         Int32,
         NullTerminatedBytes,
         RawBytes,
-        Structured,
         TimeDelta64,
         data_type_registry,
     )
@@ -85,7 +84,7 @@ class DTypeExample:
             dt = dtype_cls(unit="s", scale_factor=10)
         elif dtype_cls in (FixedLengthUTF32, RawBytes, NullTerminatedBytes):
             dt = dtype_cls(length=10)
-        elif dtype_cls == Structured:
+        elif dtype_cls._zarr_v3_name in ("struct", "structured"):
             dt = dtype_cls(fields=[("a", Int32()), ("b", Float16())])
         else:
             dt = dtype_cls()

tests/test_pydantic_zarr/test_experimental/test_v3.py

@@ -20,6 +20,7 @@
     RegularChunking,
     RegularChunkingConfig,
     auto_codecs,
+    parse_dtype_v3,
 )
 
 from ..conftest import DTYPE_EXAMPLES_V3, ZARR_AVAILABLE, DTypeExample
@@ -479,6 +480,35 @@ def test_consolidated_metadata_to_from_zarr() -> None:
     assert json.loads(store["zarr.json"].to_bytes()) == json.loads(store2["zarr.json"].to_bytes())
 
 
+@pytest.mark.parametrize(
+    ("dtype", "expected"),
+    [
+        (np.dtype("int8"), "int8"),
+        (np.dtype("int16"), "int16"),
+        (np.dtype("int32"), "int32"),
+        (np.dtype("int64"), "int64"),
+        (np.dtype("uint8"), "uint8"),
+        (np.dtype("uint16"), "uint16"),
+        (np.dtype("uint32"), "uint32"),
+        (np.dtype("uint64"), "uint64"),
+        (np.dtype("float16"), "float16"),
+        (np.dtype("float32"), "float32"),
+        (np.dtype("float64"), "float64"),
+        (np.dtype("complex64"), "complex64"),
+        (np.dtype("complex128"), "complex128"),
+    ],
+    ids=str,
+)
+def test_parse_dtype_v3_numpy(dtype: np.dtype, expected: str) -> None:
+    """
+    Regression test: parse_dtype_v3 must correctly handle all supported numpy dtypes.
+    Previously, the float64 and complex64 match arms were copy-paste errors (using
+    Float16DType and Float32DType respectively), making those dtypes unreachable and
+    causing ValueError to be raised for float64 and complex64 inputs.
+    """
+    assert parse_dtype_v3(dtype) == expected
+
+
 def test_v2_chunk_key_encoding() -> None:
     # Simple smoke test to make sure v2 chunk key encoding is allowed
     ArraySpec(

tests/test_pydantic_zarr/test_v3.py

@@ -22,6 +22,7 @@
     RegularChunking,
     RegularChunkingConfig,
     auto_codecs,
+    parse_dtype_v3,
 )
 
 from .conftest import DTYPE_EXAMPLES_V3, DTypeExample
@@ -313,3 +314,32 @@ def test_v2_chunk_key_encoding() -> None:
         fill_value="NaN",
         storage_transformers=[],
     )
+
+
+@pytest.mark.parametrize(
+    ("dtype", "expected"),
+    [
+        (np.dtype("int8"), "int8"),
+        (np.dtype("int16"), "int16"),
+        (np.dtype("int32"), "int32"),
+        (np.dtype("int64"), "int64"),
+        (np.dtype("uint8"), "uint8"),
+        (np.dtype("uint16"), "uint16"),
+        (np.dtype("uint32"), "uint32"),
+        (np.dtype("uint64"), "uint64"),
+        (np.dtype("float16"), "float16"),
+        (np.dtype("float32"), "float32"),
+        (np.dtype("float64"), "float64"),
+        (np.dtype("complex64"), "complex64"),
+        (np.dtype("complex128"), "complex128"),
+    ],
+    ids=str,
+)
+def test_parse_dtype_v3_numpy(dtype: np.dtype, expected: str) -> None:
+    """
+    Regression test: parse_dtype_v3 must correctly handle all supported numpy dtypes.
+    Previously, the float64 and complex64 match arms were copy-paste errors (using
+    Float16DType and Float32DType respectively), making those dtypes unreachable and
+    causing ValueError to be raised for float64 and complex64 inputs.
+    """
+    assert parse_dtype_v3(dtype) == expected