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Fix unreachable match arms in parse_dtype_v3 (float64/complex64 unsupported) (#167)
* Fix unreachable match arms in parse_dtype_v3 (float64/complex64) Two match arms in `parse_dtype_v3` (in both `pydantic_zarr.v3` and `pydantic_zarr.experimental.v3`) were copy-paste errors: the third arm used `Float16DType` instead of `Float64DType`, and the fourth used `Float32DType` instead of `Complex64DType`. This made `float64` and `complex64` dtypes unreachable, causing `ValueError: Unsupported dtype` for those types. Fixes part of #165. Also fixes the test conftest to handle zarr 3.2.1's new `Struct` dtype class (a subclass of `Structured`) by using `issubclass` instead of `==` in the special-case branch, and bumps the mypy `python_version` to 3.12 to match zarr >=3.2.0's minimum Python requirement. Adds parametrized regression tests covering all 13 supported numpy dtypes through `parse_dtype_v3` in both test suites. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Add changelog fragment for PR #167 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Move zarr 3.2.x compat changes to dedicated PR #171 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * make tests pass * import struct under conditional * robust import * pin pytest and fix iterator issue in test fixtures --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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‎changes/167.bugfix.md‎

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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

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

‎src/pydantic_zarr/experimental/v3.py‎

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

‎src/pydantic_zarr/v3.py‎

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

‎tests/test_docs/test_docs.py‎

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

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

‎tests/test_pydantic_zarr/test_experimental/test_v3.py‎

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

‎tests/test_pydantic_zarr/test_v3.py‎

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RegularChunking,
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RegularChunkingConfig,
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auto_codecs,
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parse_dtype_v3,
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)
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from .conftest import DTYPE_EXAMPLES_V3, DTypeExample
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fill_value="NaN",
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storage_transformers=[],
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)
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@pytest.mark.parametrize(
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("dtype", "expected"),
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[
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(np.dtype("int8"), "int8"),
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(np.dtype("int16"), "int16"),
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(np.dtype("int32"), "int32"),
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(np.dtype("int64"), "int64"),
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(np.dtype("uint8"), "uint8"),
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(np.dtype("uint16"), "uint16"),
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(np.dtype("uint32"), "uint32"),
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(np.dtype("uint64"), "uint64"),
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(np.dtype("float16"), "float16"),
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(np.dtype("float32"), "float32"),
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(np.dtype("float64"), "float64"),
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(np.dtype("complex64"), "complex64"),
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(np.dtype("complex128"), "complex128"),
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],
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ids=str,
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)
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def test_parse_dtype_v3_numpy(dtype: np.dtype, expected: str) -> None:
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"""
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Regression test: parse_dtype_v3 must correctly handle all supported numpy dtypes.
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Previously, the float64 and complex64 match arms were copy-paste errors (using
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Float16DType and Float32DType respectively), making those dtypes unreachable and
343+
causing ValueError to be raised for float64 and complex64 inputs.
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"""
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assert parse_dtype_v3(dtype) == expected

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