Use array_api compliant dtype

[Illviljan]

• Closes #xxxx
• Tests added
• User visible changes (including notable bug fixes) are documented in whats-new.rst
• New functions/methods are listed in api.rst

Notes:

• For duckarrays, use _dtype[_generic]
• For actual np.ndarrays, use np.dtype[np.generic]
• np.dtype is too specific in general and it's probably not needed in most of their array_api functions.
  • _DTypeBase-class in np?
  • Mixing dtypes from np and xp is discouraged: RFC: require that dtypes obey Python hashing rules data-apis/array-api#582
    • Using asarray seems to be the recommended way.

[Illviljan]

I don't understand why mypy doesn't narrow down the data typing here, I'm expecting the ExplicitlyIndexed to be gone downstream the isinstance-check:

@overload
def to_duck_array(
    data: ExplicitlyIndexed, **kwargs: dict[str, Any]
) -> duckarray[Any, _dtype[_generic]]: ...
@overload
def to_duck_array(
    data: chunkedduckarray[_ShapeType, _DType], **kwargs: dict[str, Any]
) -> chunkedduckarray[_ShapeType, _DType]: ...
@overload
def to_duck_array(
    data: duckarray[_ShapeType, _DType], **kwargs: dict[str, Any]
) -> duckarray[_ShapeType, _DType]: ...
@overload
def to_duck_array(
    data: np.typing.ArrayLike, **kwargs: dict[str, Any]
) -> duckarray[Any, _dtype[_generic]]: ...
def to_duck_array(
    data: (
        ExplicitlyIndexed
        | chunkedduckarray[_ShapeType, _DType]
        | duckarray[_ShapeType, _DType]
        | np.typing.ArrayLike
    ),
    **kwargs: dict[str, Any],
) -> (
    duckarray[_ShapeType, _DType]
    | duckarray[Any, _dtype[_generic]]
    | np.ndarray[Any, np.dtype[np.generic]]
):
    from xarray.core.indexing import ExplicitlyIndexed
    from xarray.namedarray.parallelcompat import get_chunked_array_type

    if isinstance(data, ExplicitlyIndexed):
        reveal_type(data)
        return data.get_duck_array()  # type: ignore[no-untyped-call, no-any-return]

    reveal_type(data)  # ExplicitlyIndexed should be gone?
    if is_chunked_array(data):
        chunkmanager = get_chunked_array_type(data)
        loaded_data, *_ = chunkmanager.compute(data, **kwargs)  # type: ignore[var-annotated]
        return loaded_data

    if is_duck_array(data):
        return data
    else:
        return np.asarray(data)

But mypy doesn't understand that for some reason:

xarray\namedarray\pycompat.py: note: In function "to_duck_array":
xarray\namedarray\pycompat.py:171: note: Revealed type is "xarray.core.indexing.ExplicitlyIndexed"
xarray\namedarray\pycompat.py:174: note: Revealed type is "Union[xarray.core.indexing.ExplicitlyIndexed, xarray.namedarray._typing._arrayfunction[_ShapeType`-1, _DType`-2], xarray.namedarray._typing._arrayapi[_ShapeType`-1, _DType`-2], _collections_abc.Buffer, numpy._typing._array_like._SupportsArray[numpy.dtype[Any]], numpy._typing._nested_sequence._NestedSequence[numpy._typing._array_like._SupportsArray[numpy.dtype[Any]]], builtins.int, builtins.float, builtins.complex, builtins.str, numpy._typing._nested_sequence._NestedSequence[Union[builtins.bool, builtins.int, builtins.float, builtins.complex, builtins.str, builtins.bytes]]]"
xarray\namedarray\pycompat.py:175: error: Argument 1 to "is_chunked_array" has incompatible type "ExplicitlyIndexed | _arrayfunction[_ShapeType, _DType] | _arrayapi[_ShapeType, _DType] | Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | int | float | complex | str | _NestedSequence[bool | int | float | complex | str | bytes]"; expected "_arrayfunction[Any, Any] | _arrayapi[Any, Any]"  [arg-type]
Found 1 error in 1 file (checked 1 source file)