Process completed with exit code 1.

6 errors

Argument of type "partial[Any]" cannot be assigned to parameter "map_func" of type "(Any) -> Any" in function "rec_map_reduce_array_container"   No overloaded function matches type "(Any) -> Any" (reportArgumentType)

No overloads for "rec_map_reduce_array_container" match the provided arguments (reportCallIssue)

Argument of type "partial[Any]" cannot be assigned to parameter "map_func" of type "(Any) -> Any" in function "rec_map_reduce_array_container"   No overloaded function matches type "(Any) -> Any" (reportArgumentType)

No overloads for "rec_map_reduce_array_container" match the provided arguments (reportCallIssue)

Argument of type "partial[float64]" cannot be assigned to parameter "map_func" of type "(Any) -> Any" in function "rec_map_reduce_array_container"   No overloaded function matches type "(Any) -> Any" (reportArgumentType)

No overloads for "rec_map_reduce_array_container" match the provided arguments (reportCallIssue)

No point in testing mirgecom at the moment, see https://github.com/illinois-ceesd/mirgecom/pull/898. Test not performed.

Type of "ravel" is partially unknown   Type of "ravel" is "Overload[(a: _SupportsArray[dtype[ScalarT@ravel]] | _NestedSequence[_SupportsArray[dtype[ScalarT@ravel]]], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[ScalarT@ravel]], (a: bytes | _NestedSequence[bytes], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[bytes_]], (a: str | _NestedSequence[str], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[str_]], (a: builtins.bool | _NestedSequence[builtins.bool], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[numpy.bool[builtins.bool]]], (a: int | _NestedSequence[int], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit] | Any]], (a: float | _NestedSequence[float], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[float64 | Any]], (a: complex | _NestedSequence[complex], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[complex128 | Any]], (a: Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], order: Literal['K', 'A', 'C', 'F'] | None = "C") -> ndarray[tuple[int], dtype[Any]]]" (reportUnknownMemberType)

Type of "broadcast_to" is partially unknown   Type of "broadcast_to" is "Overload[(array: _SupportsArray[dtype[ScalarT@broadcast_to]] | _NestedSequence[_SupportsArray[dtype[ScalarT@broadcast_to]]], shape: int | Iterable[int], subok: bool = False) -> ndarray[tuple[Any, ...], dtype[ScalarT@broadcast_to]], (array: Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], shape: int | Iterable[int], subok: bool = False) -> ndarray[tuple[Any, ...], dtype[Any]]]" (reportUnknownMemberType)

Type of "stack" is partially unknown   Type of "stack" is "Overload[(arrays: Sequence[_SupportsArray[dtype[ScalarT@stack]] | _NestedSequence[_SupportsArray[dtype[ScalarT@stack]]]], axis: SupportsIndex = 0, out: None = None, *, dtype: None = None, casting: Literal['no', 'equiv', 'safe', 'same_kind', 'same_value', 'unsafe'] = "same_kind") -> ndarray[tuple[Any, ...], dtype[ScalarT@stack]], (arrays: Sequence[Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], axis: SupportsIndex = 0, out: None = None, *, dtype: type[ScalarT@stack] | dtype[ScalarT@stack] | _HasDType[dtype[ScalarT@stack]] | _HasNumPyDType[dtype[ScalarT@stack]], casting: Literal['no', 'equiv', 'safe', 'same_kind', 'same_value', 'unsafe'] = "same_kind") -> ndarray[tuple[Any, ...], dtype[ScalarT@stack]], (arrays: Sequence[Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], axis: SupportsIndex = 0, out: None = None, *, dtype: type | str | dtype[Any] | _HasDType[dtype[Any]] | _HasNumPyDType[dtype[Any]] | tuple[Any, Any] | list[Any] | _DTypeDict | None = None, casting: Literal['no', 'equiv', 'safe', 'same_kind', 'same_value', 'unsafe'] = "same_kind") -> ndarray[tuple[Any, ...], dtype[Any]], (arrays: Sequence[Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], axis: SupportsIndex, out: OutT@stack, *, dtype: type | str | dtype[Any] | _HasDType[dtype[Any]] | _HasNumPyDType[dtype[Any]] | tuple[Any, Any] | list[Any] | _DTypeDict | None = None, casting: Literal['no', 'equiv', 'safe', 'same_kind', 'same_value', 'unsafe'] = "same_kind") -> OutT@stack, (arrays: Sequence[Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], axis: SupportsIndex = 0, *, out: OutT@stack, dtype: type | str | dtype[Any] | _HasDType[dtype[Any]] | _HasNumPyDType[dtype[Any]] | tuple[Any, Any] | list[Any] | _DTypeDict | None = None, casting: Literal['no', 'equiv', 'safe', 'same_kind', 'same_value', 'unsafe'] = "same_kind") -> OutT@stack]" (reportUnknownMemberType)

Type of "amax" is partially unknown   Type of "amax" is "Overload[(a: _NestedSequence[Unknown], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> Any, (a: _NestedSequence[builtins.bool], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> numpy.bool[builtins.bool], (a: _NestedSequence[builtins.bool], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]], (a: _NestedSequence[builtins.bool], axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]], (a: _NestedSequence[list[int]] | list[int], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> signedinteger[_32Bit | _64Bit], (a: _NestedSequence[list[int]] | list[int], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[signedinteger[_32Bit | _64Bit]]], (a: _NestedSequence[list[int]] | list[int], axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[signedinteger[_32Bit | _64Bit]]], (a: _NestedSequence[list[float]] | list[float], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> float64, (a: _NestedSequence[list[float]] | list[float], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueTy

Return type is unknown (reportUnknownVariableType)

Type of "amin" is partially unknown   Type of "amin" is "Overload[(a: _NestedSequence[Unknown], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> Any, (a: _NestedSequence[builtins.bool], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> numpy.bool[builtins.bool], (a: _NestedSequence[builtins.bool], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]], (a: _NestedSequence[builtins.bool], axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]], (a: _NestedSequence[list[int]] | list[int], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> signedinteger[_32Bit | _64Bit], (a: _NestedSequence[list[int]] | list[int], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[signedinteger[_32Bit | _64Bit]]], (a: _NestedSequence[list[int]] | list[int], axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> ndarray[tuple[Any, ...], dtype[signedinteger[_32Bit | _64Bit]]], (a: _NestedSequence[list[float]] | list[float], axis: None = None, out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueType = ...) -> float64, (a: _NestedSequence[list[float]] | list[float], axis: int | tuple[int, ...], out: None = None, keepdims: _NoValueType | Literal[False] = ..., initial: complex | number[Any, Any] | numpy.bool[builtins.bool] | _NoValueType = ..., where: _SupportsArray[dtype[numpy.bool[builtins.bool]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]]]] | builtins.bool | _NestedSequence[builtins.bool] | _NoValueTy

Return type is unknown (reportUnknownVariableType)

Return type is unknown (reportUnknownVariableType)

Type of "result_type" is partially unknown   Type of "result_type" is "(*arrays_and_dtypes: Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] | type | dtype[Any] | _HasDType[dtype[Any]] | _HasNumPyDType[dtype[Any]] | tuple[Any, Any] | list[Any] | _DTypeDict | None) -> dtype[Any]" (reportUnknownMemberType)

Type of "result_type" is partially unknown   Type of "result_type" is "(*arrays_and_dtypes: Unknown | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] | type | dtype[Any] | _HasDType[dtype[Any]] | _HasNumPyDType[dtype[Any]] | tuple[Any, Any] | list[Any] | _DTypeDict | None) -> dtype[Any]" (reportUnknownMemberType)

No point in testing mirgecom at the moment, see https://github.com/illinois-ceesd/mirgecom/pull/898. Test not performed.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

'bcast_obj_array' is deprecated and will be unsupported from 2025. Use 'bcasts_across_obj_array', with equivalent meaning.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

'bcast_obj_array' is deprecated and will be unsupported from 2025. Use 'bcasts_across_obj_array', with equivalent meaning.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'test_reductions.MyContainer'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'test_reductions.MyContainer'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

Encountered 'numpy.ndarray' in a dataclass_array_container. This is deprecated and will stop working in 2026. If you meant an object array, use pytools.obj_array.ObjectArray. For other uses, file an issue to discuss.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.