TYP: concrete ``number`` subtypes by jorenham · Pull Request #33052 · numpy/numpy

jorenham · 2026-10-15T20:09:29Z

This has been a long standing issue in the stubs, was causing issues for several typecheckers (at least mypy, pyright, and ty, see e.g. astral-sh/ty#116 and astral-sh/ty#4727), and prevented us from accurately typing arithmetic operations on the numpy scalars.

All subclasses of unsignedinteger, signedinteger, floating, and complexfloating are now typed as now concrete classes in the stubs. Their operator dunders (__add__, __sub__, etc) are now also precisely typed to accurately reflect NEP 50 scalar promotion rules, resolving a bunch of Any's, annoying unions and other wide types, and even some incorrect results (e.g. or combinations of signed and unsigned integers promoting to float64).

This might cause some previously-hidden downstream typing issues to surface, because the nominal scalar type hierarchy is now enforced. For example np.integer used to be assignable to np.int64, but that is now no longer the case (because it's unsound), causing type-checkers to reject such attempts (as they should).

The stubs now makes the following assumptions:

intp == int64 and uintp == uint64 (since the vast majority of users will use a 64-bit system)
[u]intc == [u]int32, [u]short == [u]int16, and [u]byte == [u]int8
[u]long is [u]int32 if sys.platform == "win32" and otherwise [u]int64
[u]longlong == [u]int64
longdouble == float96 == float128 and clongdouble == complex192 == complex256 (both sized aliases have to be available in the stubs to avoid "but it worked on my machine" scenarios).

For exotic systems where this doesn't hold, the worst that might happen is a squiggly line if they're unlucky, but they probably won't even notice.

This closes #23007, and indirectly also closes #28838.

AI did the mechanical work, but most of this was me.

github-actions · 2026-10-15T21:12:08Z

Diff from mypy_primer, showing the effect of this PR on type check results on a corpus of open source code:

pandas (https://github.com/pandas-dev/pandas)
- pandas/core/dtypes/dtypes.py:526: error: Incompatible return value type (got "ndarray[tuple[Any, ...], dtype[unsignedinteger[_64Bit]]] | Any", expected "int")  [return-value]
+ pandas/core/dtypes/dtypes.py:526: error: Incompatible return value type (got "ndarray[tuple[Any, ...], dtype[uint64]] | Any", expected "int")  [return-value]
- pandas/io/formats/string.py:126: error: No overload variant of "__rsub__" of "signedinteger" matches argument type "None"  [operator]
+ pandas/io/formats/string.py:126: error: No overload variant of "__rsub__" of "int64" matches argument type "None"  [operator]
- pandas/io/formats/string.py:126: note:     def __rsub__(self, int | signedinteger[_8Bit] | numpy.bool[builtins.bool], /) -> signedinteger[_32Bit | _64Bit]
+ pandas/io/formats/string.py:126: note:     def __rsub__(self, int | signedinteger[Any] | uint32 | uint16 | uint8 | numpy.bool[builtins.bool], /) -> int64
- pandas/io/formats/string.py:126: note:     def __rsub__(self, float, /) -> float64
+ pandas/io/formats/string.py:126: note:     def __rsub__(self, float64 | uint64, /) -> float64
- pandas/io/formats/string.py:126: note:     def __rsub__(self, complex, /) -> complex128
+ pandas/io/formats/string.py:126: note:     def __rsub__(self, complex128, /) -> complex128
- pandas/io/formats/string.py:126: note:     def __rsub__(self, signedinteger[Any], /) -> signedinteger[Any]
- pandas/io/formats/string.py:126: note:     def __rsub__(self, integer[Any], /) -> Any
+ pandas/io/formats/string.py:126: note:     def __rsub__(self, float, /) -> float64 | Any
+ pandas/io/formats/string.py:126: note:     def __rsub__(self, complex, /) -> complex128 | Any
- pandas/io/formats/string.py:126: error: Incompatible types in assignment (expression has type "signedinteger[_32Bit | _64Bit] | Any", variable has type "int | None")  [assignment]
+ pandas/io/formats/string.py:126: error: Incompatible types in assignment (expression has type "int64 | Any", variable has type "int | None")  [assignment]
- pandas/io/formats/string.py:134: error: Argument 1 to "_binify" has incompatible type "list[signedinteger[_32Bit | _64Bit] | int]"; expected "list[int]"  [arg-type]
+ pandas/io/formats/string.py:134: error: Argument 1 to "_binify" has incompatible type "list[int64 | int]"; expected "list[int]"  [arg-type]
- pandas/core/algorithms.py:470: error: Incompatible return value type (got "signedinteger[_32Bit | _64Bit]", expected "int")  [return-value]
+ pandas/core/algorithms.py:470: error: Incompatible return value type (got "int64", expected "int")  [return-value]
- pandas/io/stata.py:352: error: Incompatible types in assignment (expression has type "vectorize[signedinteger[_32Bit | _64Bit], Callable[[datetime], int]]", variable has type "vectorize[float64, Callable[[timedelta], float]]")  [assignment]
+ pandas/io/stata.py:352: error: Incompatible types in assignment (expression has type "vectorize[int64, Callable[[datetime], int]]", variable has type "vectorize[float64, Callable[[timedelta], float]]")  [assignment]
- pandas/io/parsers/python_parser.py:1532: error: Incompatible return value type (got "list[tuple[signedinteger[_32Bit | _64Bit], signedinteger[_32Bit | _64Bit]]]", expected "list[tuple[int, int]]")  [return-value]
+ pandas/io/parsers/python_parser.py:1532: error: Incompatible return value type (got "list[tuple[int64, int64]]", expected "list[tuple[int, int]]")  [return-value]
- pandas/core/groupby/groupby.py:1748: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[float64]]", variable has type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]")  [assignment]
+ pandas/core/groupby/groupby.py:1748: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[float64]]", variable has type "ndarray[tuple[int], dtype[int64]]")  [assignment]
- pandas/core/groupby/generic.py:1253: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[signedinteger[_32Bit | _64Bit]]] | None", variable has type "ndarray[Any, Any]")  [assignment]
+ pandas/core/groupby/generic.py:1253: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[int64]] | None", variable has type "ndarray[Any, Any]")  [assignment]
+ pandas/core/groupby/ops.py:900: error: Argument 2 to "_ob_index_and_ids" of "BaseGrouper" has incompatible type "list[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]"; expected "list[ndarray[tuple[Any, ...], dtype[int64]]]"  [arg-type]
+ pandas/core/groupby/ops.py:903: error: Argument 2 to "_unob_index_and_ids" of "BaseGrouper" has incompatible type "list[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]"; expected "list[ndarray[tuple[Any, ...], dtype[int64]]]"  [arg-type]
+ pandas/core/groupby/ops.py:912: error: List comprehension has incompatible type List[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]; expected List[ndarray[tuple[Any, ...], dtype[int64]]]  [misc]
+ pandas/core/groupby/ops.py:918: error: List comprehension has incompatible type List[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]; expected List[ndarray[tuple[Any, ...], dtype[int64]]]  [misc]
+ pandas/core/groupby/ops.py:1392: error: Signature of "codes" incompatible with supertype "BaseGrouper"  [override]
+ pandas/core/groupby/ops.py:1392: note:      Superclass:
+ pandas/core/groupby/ops.py:1392: note:          list[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]
+ pandas/core/groupby/ops.py:1392: note:      Subclass:
+ pandas/core/groupby/ops.py:1392: note:          list[ndarray[tuple[Any, ...], dtype[int64]]]
- pandas/io/formats/excel.py:664: error: Argument "css_col" to "CssExcelCell" has incompatible type "signedinteger[_32Bit | _64Bit]"; expected "int"  [arg-type]
+ pandas/io/formats/excel.py:664: error: Argument "css_col" to "CssExcelCell" has incompatible type "int64"; expected "int"  [arg-type]
- pandas/io/formats/excel.py:698: error: Argument "css_col" to "CssExcelCell" has incompatible type "signedinteger[_32Bit | _64Bit]"; expected "int"  [arg-type]
+ pandas/io/formats/excel.py:698: error: Argument "css_col" to "CssExcelCell" has incompatible type "int64"; expected "int"  [arg-type]
- pandas/io/formats/excel.py:880: error: Argument "css_col" to "CssExcelCell" has incompatible type "signedinteger[_32Bit | _64Bit]"; expected "int"  [arg-type]
+ pandas/io/formats/excel.py:880: error: Argument "css_col" to "CssExcelCell" has incompatible type "int64"; expected "int"  [arg-type]
- pandas/core/reshape/reshape.py:153: error: Incompatible types in assignment (expression has type "signedinteger[_32Bit | _64Bit]", variable has type "int")  [assignment]
+ pandas/core/reshape/reshape.py:153: error: Incompatible types in assignment (expression has type "int64", variable has type "int")  [assignment]

jax (https://github.com/google/jax)
- jax/_src/array.py:448: note:     def asarray(a: Sequence[list[int]], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int, int], dtype[signedinteger[_32Bit | _64Bit]]]
+ jax/_src/array.py:448: note:     def asarray(a: Sequence[list[int]], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int, int], dtype[int64]]
- jax/_src/array.py:448: note:     def asarray(a: Sequence[Sequence[list[int]]], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int, int, int], dtype[signedinteger[_32Bit | _64Bit]]]
+ jax/_src/array.py:448: note:     def asarray(a: Sequence[Sequence[list[int]]], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int, int, int], dtype[int64]]
- jax/_src/array.py:448: note:     def asarray(a: list[int], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]
+ jax/_src/array.py:448: note:     def asarray(a: list[int], dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[int], dtype[int64]]
- jax/_src/array.py:448: note:     def asarray(a: int, dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[()], dtype[signedinteger[_32Bit | _64Bit] | Any]]
+ jax/_src/array.py:448: note:     def asarray(a: int, dtype: None = ..., order: Literal['K', 'A', 'C', 'F'] | None = ..., *, device: Literal['cpu'] | None = ..., copy: bool | None = ..., like: _SupportsArrayFunc | None = ...) -> ndarray[tuple[()], dtype[int64 | Any]]
- jax/_src/numpy/indexing.py:364: note:     def __radd__(self, int, /) -> signedinteger[_32Bit | _64Bit]
+ jax/_src/numpy/indexing.py:364: note:     def __radd__(self, int, /) -> int64
- jax/_src/numpy/indexing.py:364: error: Incompatible types in assignment (expression has type "Array | ndarray[tuple[Any, ...], dtype[Any]] | signedinteger[_32Bit | _64Bit] | Any | int | <6 more items> | None", variable has type "int | integer[Any] | slice[Any, Any, Any] | EllipsisType | Sequence[int | integer[Any]] | Array | ndarray[tuple[Any, ...], dtype[Any]] | None")  [assignment]
+ jax/_src/numpy/indexing.py:364: error: Incompatible types in assignment (expression has type "Array | ndarray[tuple[Any, ...], dtype[Any]] | int64 | Any | int | <6 more items> | None", variable has type "int | integer[Any] | slice[Any, Any, Any] | EllipsisType | Sequence[int | integer[Any]] | Array | ndarray[tuple[Any, ...], dtype[Any]] | None")  [assignment]
- jax/_src/numpy/hijax.py:632: error: Incompatible types in assignment (expression has type "tuple[Any, ...]", variable has type "ndarray[tuple[Any, ...], dtype[signedinteger[_64Bit]]]")  [assignment]
+ jax/_src/numpy/hijax.py:632: error: Incompatible types in assignment (expression has type "tuple[Any, ...]", variable has type "ndarray[tuple[Any, ...], dtype[int64]]")  [assignment]
- jax/_src/numpy/lax_numpy.py:6012: error: Value of type variable "T" of "__call__" of "_ufunc_11_bifo" cannot be "Array | ndarray[tuple[Any, ...], dtype[Any]] | Any | signedinteger[_32Bit | _64Bit] | int | float | complex"  [type-var]
+ jax/_src/numpy/lax_numpy.py:6012: error: Value of type variable "T" of "__call__" of "_ufunc_11_bifo" cannot be "Array | ndarray[tuple[Any, ...], dtype[Any]] | Any | int64 | int | float | complex"  [type-var]
- jax/_src/numpy/lax_numpy.py:6012: error: Argument 1 to "int" has incompatible type "Array | ndarray[tuple[Any, ...], dtype[Any]] | Any | signedinteger[_32Bit | _64Bit] | int | float | complex"; expected "str | Buffer | SupportsInt | SupportsIndex | SupportsTrunc"  [arg-type]
+ jax/_src/numpy/lax_numpy.py:6012: error: Argument 1 to "int" has incompatible type "Array | ndarray[tuple[Any, ...], dtype[Any]] | Any | int64 | int | float | complex"; expected "str | Buffer | SupportsInt | SupportsIndex | SupportsTrunc"  [arg-type]
- jax/_src/numpy/ufuncs.py:3075: error: Argument 1 to "signedinteger" has incompatible type "object"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ jax/_src/numpy/ufuncs.py:3075: error: Argument 1 to "int32" has incompatible type "object"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
- jax/_src/random/core.py:2066: error: Incompatible types in assignment (expression has type "dtype[floating[_32Bit]]", variable has type "dtype[float64]")  [assignment]
+ jax/_src/random/core.py:2066: error: Incompatible types in assignment (expression has type "dtype[float32]", variable has type "dtype[float64]")  [assignment]
- jax/_src/checkify.py:246: error: Value of type "int | signedinteger[_32Bit] | Array" is not indexable  [index]
+ jax/_src/checkify.py:246: error: Value of type "int | int32 | Array" is not indexable  [index]
- jax/_src/checkify.py:247: error: Value of type "int | signedinteger[_32Bit] | Array" is not indexable  [index]
+ jax/_src/checkify.py:247: error: Value of type "int | int32 | Array" is not indexable  [index]
- jax/experimental/mosaic/gpu/launch_context.py:1079: error: Incompatible types in assignment (expression has type "signedinteger[_32Bit | _64Bit]", variable has type "int")  [assignment]
+ jax/experimental/mosaic/gpu/launch_context.py:1079: error: Incompatible types in assignment (expression has type "int64", variable has type "int")  [assignment]
- jax/_src/pallas/fuser/block_spec.py:2281: error: No overload variant of "__getitem__" of "Sequence" matches argument type "signedinteger[_32Bit | _64Bit]"  [call-overload]
+ jax/_src/pallas/fuser/block_spec.py:2281: error: No overload variant of "__getitem__" of "Sequence" matches argument type "int64"  [call-overload]
- jax/_src/pallas/fuser/block_spec.py:2625: error: Argument 1 to "append" of "list" has incompatible type "tuple[signedinteger[_32Bit], ...]"; expected "tuple[int | Any]"  [arg-type]
+ jax/_src/pallas/fuser/block_spec.py:2625: error: Argument 1 to "append" of "list" has incompatible type "tuple[int32, ...]"; expected "tuple[int | Any]"  [arg-type]
- jax/_src/third_party/scipy/special.py:304: note: Left operand is of type "Array | ndarray[tuple[Any, ...], dtype[Any]] | numpy.bool[builtins.bool] | number[Any, Any] | signedinteger[_32Bit | _64Bit] | Any | int | float | complex"
+ jax/_src/third_party/scipy/special.py:304: note: Left operand is of type "Array | ndarray[tuple[Any, ...], dtype[Any]] | numpy.bool[builtins.bool] | number[Any, Any] | int64 | Any | int | float | complex"
- jax/_src/internal_test_util/test_harnesses.py:841: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[number[_32Bit, float]]]", variable has type "ndarray[tuple[int, int], dtype[floating[_32Bit]]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:841: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[number[_32Bit, float]]]", variable has type "ndarray[tuple[int, int], dtype[float32]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:1117: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[integer[_32Bit]]]", variable has type "ndarray[tuple[()], dtype[signedinteger[_32Bit]]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:1117: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[integer[_32Bit]]]", variable has type "ndarray[tuple[()], dtype[int32]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:1228: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[signedinteger[_32Bit | _64Bit]]]", variable has type "list[list[int]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:1228: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[int64]]", variable has type "list[list[int]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:1269: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[signedinteger[_32Bit | _64Bit]]]", variable has type "list[list[int]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:1269: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[int64]]", variable has type "list[list[int]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:1659: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[number[_32Bit, float]]]", variable has type "ndarray[tuple[int, int], dtype[floating[_32Bit]]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:1659: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[number[_32Bit, float]]]", variable has type "ndarray[tuple[int, int], dtype[float32]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:1720: error: Incompatible types in assignment (expression has type "list[object]", variable has type "list[ndarray[tuple[int], dtype[floating[_32Bit]]]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:1720: error: Incompatible types in assignment (expression has type "list[object]", variable has type "list[ndarray[tuple[int], dtype[float32]]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:2233: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[unsignedinteger[_8Bit]]] | ndarray[tuple[()], dtype[unsignedinteger[_32Bit]]] | int, ...]", variable has type "list[list[int]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:2233: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[uint8]] | ndarray[tuple[()], dtype[uint32]] | int, ...]", variable has type "list[list[int]]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:2233: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[unsignedinteger[_8Bit]]] | ndarray[tuple[()], dtype[unsignedinteger[_32Bit]]] | int, ...]", variable has type "tuple[int, ...]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:2233: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[uint8]] | ndarray[tuple[()], dtype[uint32]] | int, ...]", variable has type "tuple[int, ...]")  [assignment]
- jax/_src/internal_test_util/test_harnesses.py:2292: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[unsignedinteger[_8Bit]]] | ndarray[tuple[()], dtype[unsignedinteger[_32Bit]]] | int, ...]", variable has type "list[list[int]]")  [assignment]
+ jax/_src/internal_test_util/test_harnesses.py:2292: error: Incompatible types in assignment (expression has type "tuple[ndarray[tuple[()], dtype[uint8]] | ndarray[tuple[()], dtype[uint32]] | int, ...]", variable has type "list[list[int]]")  [assignment]

xarray (https://github.com/pydata/xarray)
- xarray/core/coordinates.py:166: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[float64]]", variable has type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]")  [assignment]
+ xarray/core/coordinates.py:166: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[float64]]", variable has type "ndarray[tuple[int], dtype[int64]]")  [assignment]
- xarray/tests/test_namedarray.py:369: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[object_[float]]]", variable has type "ndarray[tuple[Any, ...], dtype[signedinteger[_64Bit]]]")  [assignment]
+ xarray/tests/test_namedarray.py:369: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[object_[float]]]", variable has type "ndarray[tuple[Any, ...], dtype[int64]]")  [assignment]

static-frame (https://github.com/static-frame/static-frame)
- static_frame/core/rank.py:60: error: Incompatible types in assignment (expression has type "signedinteger[_64Bit] | float64", variable has type "int")  [assignment]
+ static_frame/core/rank.py:60: error: Incompatible types in assignment (expression has type "int64 | float64", variable has type "int")  [assignment]
- static_frame/core/rank.py:76: error: Incompatible types in assignment (expression has type "signedinteger[_64Bit] | float64", variable has type "int")  [assignment]
+ static_frame/core/rank.py:76: error: Incompatible types in assignment (expression has type "int64 | float64", variable has type "int")  [assignment]
- static_frame/core/rank.py:172: error: Incompatible types in assignment (expression has type "signedinteger[_64Bit] | float64", variable has type "int")  [assignment]
+ static_frame/core/rank.py:172: error: Incompatible types in assignment (expression has type "int64 | float64", variable has type "int")  [assignment]
- static_frame/core/loc_map.py:333: error: Incompatible return value type (got "tuple[ndarray[tuple[int], dtype[unsignedinteger[_64Bit]]], numpy.bool[builtins.bool]]", expected "tuple[ndarray[Any, Any], builtins.bool]")  [return-value]
+ static_frame/core/loc_map.py:333: error: Incompatible return value type (got "tuple[ndarray[tuple[int], dtype[uint64]], numpy.bool[builtins.bool]]", expected "tuple[ndarray[Any, Any], builtins.bool]")  [return-value]
- static_frame/core/loc_map.py:428: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[unsignedinteger[_64Bit]]]", variable has type "ndarray[tuple[int, int], dtype[unsignedinteger[_64Bit]]]")  [assignment]
+ static_frame/core/loc_map.py:428: error: Incompatible types in assignment (expression has type "ndarray[tuple[int], dtype[uint64]]", variable has type "ndarray[tuple[int, int], dtype[uint64]]")  [assignment]

scikit-learn (https://github.com/scikit-learn/scikit-learn)
- sklearn/externals/array_api_compat/numpy/_aliases.py:126: error: Argument 2 to "take_along_axis" has incompatible type "ndarray[Any, dtype[numpy.bool[builtins.bool] | integer[Any] | floating[_32Bit] | float64 | complexfloating[_32Bit, _32Bit] | complex128]]"; expected "ndarray[Any, dtype[integer[Any]]]"  [arg-type]
+ sklearn/externals/array_api_compat/numpy/_aliases.py:126: error: Argument 2 to "take_along_axis" has incompatible type "ndarray[Any, dtype[numpy.bool[builtins.bool] | integer[Any] | float32 | float64 | complex64 | complex128]]"; expected "ndarray[Any, dtype[integer[Any]]]"  [arg-type]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def [T] hstack(blocks: Sequence[_CanStackAs[signedinteger[_32Bit | _64Bit], T]], format: None = ..., *, dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> T
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def [T] hstack(blocks: Sequence[_CanStackAs[int64, T]], format: None = ..., *, dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> T
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['bsr'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> bsr_array[signedinteger[_32Bit | _64Bit]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['bsr'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> bsr_array[int64]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['coo'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> coo_array[signedinteger[_32Bit | _64Bit], tuple[int, int]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['coo'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> coo_array[int64, tuple[int, int]]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['csc'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> csc_array[signedinteger[_32Bit | _64Bit]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['csc'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> csc_array[int64]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['csr'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> csr_array[signedinteger[_32Bit | _64Bit], tuple[int, int]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['csr'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> csr_array[int64, tuple[int, int]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['dia'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> dia_array[int64]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['dia'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> dia_array[signedinteger[_32Bit | _64Bit]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['dok'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> dok_array[int64, tuple[int, int]]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['dok'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> dok_array[signedinteger[_32Bit | _64Bit], tuple[int, int]]
- sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['lil'], dtype: type[JustInt] | type[signedinteger[_64Bit]] | dtype[signedinteger[_64Bit]] | HasDType[dtype[signedinteger[_64Bit]]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> lil_array[signedinteger[_32Bit | _64Bit]]
+ sklearn/utils/tests/test_sparsefuncs.py:451: note:     def hstack(blocks: Sequence[sparray[Any, tuple[Any, ...]]], format: Literal['lil'], dtype: type[JustInt] | type[int64] | dtype[int64] | HasDType[dtype[int64]] | Literal['int_', 'int', 'intp', 'n', '<n', '>n']) -> lil_array[int64]

pandas-stubs (https://github.com/pandas-dev/pandas-stubs)
- tests/series/timedelta/test_floordiv.py:148: error: Expression is of type "ndarray[tuple[Any, ...], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit]]]"  [assert-type]
+ tests/series/timedelta/test_floordiv.py:148: error: Expression is of type "ndarray[tuple[Any, ...], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[int8]]"  [assert-type]
- tests/series/int/test_floordiv.py:137: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit]]]"  [assert-type]
+ tests/series/int/test_floordiv.py:137: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[int8]]"  [assert-type]
- tests/indexes/timedeltaindex/test_floordiv.py:98: error: Expression is of type "ndarray[tuple[Any, ...], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit]]]"  [assert-type]
+ tests/indexes/timedeltaindex/test_floordiv.py:98: error: Expression is of type "ndarray[tuple[Any, ...], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[int8]]"  [assert-type]
- tests/indexes/int/test_floordiv.py:97: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit]]]"  [assert-type]
+ tests/indexes/int/test_floordiv.py:97: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[int8]]"  [assert-type]
- tests/indexes/float/test_floordiv.py:97: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit]]]"  [assert-type]
+ tests/indexes/float/test_floordiv.py:97: error: Expression is of type "ndarray[tuple[int], dtype[Any]]", not "ndarray[tuple[Any, ...], dtype[int8]]"  [assert-type]

colour (https://github.com/colour-science/colour)
- colour/utilities/array.py:1311: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/utilities/array.py:1311: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [return-value]
- colour/utilities/array.py:1528: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/utilities/array.py:1528: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [return-value]
- colour/utilities/array.py:1567: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/utilities/array.py:1567: error: Incompatible return value type (got "float64", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [return-value]
- colour/utilities/array.py:1608: error: Incompatible return value type (got "complex128 | Any", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/utilities/array.py:1608: error: Incompatible return value type (got "complex128 | Any", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [return-value]
- colour/utilities/array.py:1819: error: Incompatible return value type (got "complex128 | Any", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/utilities/array.py:1819: error: Incompatible return value type (got "complex128 | Any", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [return-value]
- colour/utilities/array.py:2250: error: Incompatible return value type (got "ndarray[tuple[int], dtype[complex128 | Any]]", expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | tuple[ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]], float]")  [return-value]
+ colour/utilities/array.py:2250: error: Incompatible return value type (got "ndarray[tuple[int], dtype[complex128 | Any]]", expected "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]] | tuple[ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]], float]")  [return-value]
- colour/utilities/array.py:3266: error: Argument 1 to "signedinteger" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "int8" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "int16" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "int32" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "int64" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
- colour/utilities/array.py:3266: error: Argument 1 to "unsignedinteger" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "uint8" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "uint16" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "uint32" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
+ colour/utilities/array.py:3266: error: Argument 1 to "uint64" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsInt | SupportsIndex | str | bytes"  [arg-type]
- colour/utilities/array.py:3334: error: Argument 1 to "floating" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsFloat | SupportsIndex | str | bytes | None"  [arg-type]
+ colour/utilities/array.py:3334: error: Argument 1 to "float16" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsFloat | SupportsIndex | str | bytes | None"  [arg-type]
+ colour/utilities/array.py:3334: error: Argument 1 to "float32" has incompatible type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]"; expected "SupportsFloat | SupportsIndex | str | bytes | None"  [arg-type]
- colour/algebra/interpolation.py:1594: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]", variable has type "ndarray[tuple[Any, ...], dtype[float64]]")  [assignment]
+ colour/algebra/interpolation.py:1594: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]", variable has type "ndarray[tuple[Any, ...], dtype[float64]]")  [assignment]
- colour/models/rgb/ycocg.py:52: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[signedinteger[_32Bit | _64Bit]]]", variable has type "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]")  [assignment]
+ colour/models/rgb/ycocg.py:52: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, int], dtype[int64]]", variable has type "ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]]")  [assignment]
- colour/io/image.py:350: error: Incompatible return value type (got "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | str | _NestedSequence[complex | bytes | str]", expected "ndarray[tuple[Any, ...], dtype[signedinteger[_8Bit] | signedinteger[_16Bit] | signedinteger[_32Bit] | signedinteger[_64Bit] | unsignedinteger[_8Bit] | unsignedinteger[_16Bit] | unsignedinteger[_32Bit] | unsignedinteger[_64Bit] | floating[_16Bit] | floating[_32Bit] | float64]]")  [return-value]
+ colour/io/image.py:350: error: Incompatible return value type (got "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | str | _NestedSequence[complex | bytes | str]", expected "ndarray[tuple[Any, ...], dtype[int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | float16 | float32 | float64]]")  [return-value]
- colour/io/luts/lut.py:1433: error: No overload variant of "pad" matches argument types "ndarray[Any, Any]", "tuple[int, Any | signedinteger[_8Bit] | signedinteger[_16Bit] | signedinteger[_32Bit] | signedinteger[_64Bit] | unsignedinteger[_8Bit] | unsignedinteger[_16Bit] | unsignedinteger[_32Bit] | unsignedinteger[_64Bit]]", "str", "float"  [call-overload]
+ colour/io/luts/lut.py:1433: error: No overload variant of "pad" matches argument types "ndarray[Any, Any]", "tuple[int, Any | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64]", "str", "float"  [call-overload]
- colour/io/luts/lut.py:1433: note:     def pad(array: list[int], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'linear_ramp'] | Literal['maximum', 'mean', 'median', 'minimum'] | Literal['reflect', 'symmetric'] | Literal['edge', 'wrap', 'empty'] | _ModeFunc = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]
+ colour/io/luts/lut.py:1433: note:     def pad(array: list[int], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'linear_ramp'] | Literal['maximum', 'mean', 'median', 'minimum'] | Literal['reflect', 'symmetric'] | Literal['edge', 'wrap', 'empty'] | _ModeFunc = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[int], dtype[int64]]
- colour/io/luts/lut.py:1433: note:     def pad(array: Sequence[list[int]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'linear_ramp'] | Literal['maximum', 'mean', 'median', 'minimum'] | Literal['reflect', 'symmetric'] | Literal['edge', 'wrap', 'empty'] | _ModeFunc = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[int, int], dtype[signedinteger[_32Bit | _64Bit]]]
+ colour/io/luts/lut.py:1433: note:     def pad(array: Sequence[list[int]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'linear_ramp'] | Literal['maximum', 'mean', 'median', 'minimum'] | Literal['reflect', 'symmetric'] | Literal['edge', 'wrap', 'empty'] | _ModeFunc = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[int, int], dtype[int64]]
- colour/io/luts/lut.py:1948: error: Argument "dtype" to "as_array" has incompatible type "type[object]"; expected "type[numpy.bool[builtins.bool]] | type[signedinteger[_8Bit]] | type[signedinteger[_16Bit]] | type[signedinteger[_32Bit]] | type[signedinteger[_64Bit]] | <9 more items> | None"  [arg-type]
+ colour/io/luts/lut.py:1948: error: Argument "dtype" to "as_array" has incompatible type "type[object]"; expected "type[numpy.bool[builtins.bool]] | type[int8] | type[int16] | type[int32] | type[int64] | <9 more items> | None"  [arg-type]
- colour/geometry/primitives.py:239: error: Argument 2 to "zeros" has incompatible type "list[tuple[str, type[floating[_16Bit]] | type[floating[_32Bit]] | type[float64], int]]"; expected "type[signedinteger[_8Bit]] | type[signedinteger[_16Bit]] | type[signedinteger[_32Bit]] | type[signedinteger[_64Bit]] | type[unsignedinteger[_8Bit]] | <6 more items> | None"  [arg-type]
- colour/geometry/primitives.py:449: error: Argument 2 to "zeros" has incompatible type "list[tuple[str, type[floating[_16Bit]] | type[floating[_32Bit]] | type[float64], int]]"; expected "type[signedinteger[_8Bit]] | type[signedinteger[_16Bit]] | type[signedinteger[_32Bit]] | type[signedinteger[_64Bit]] | type[unsignedinteger[_8Bit]] | <6 more items> | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:153: error: Argument 4 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:154: error: Argument 5 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:155: error: Argument 6 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:161: error: Argument 4 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:162: error: Argument 5 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:163: error: Argument 6 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]
- colour/corresponding/datasets/breneman1987.py:169: error: Argument 4 to "BrenemanExperimentResult" has incompatible type "ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]]"; expected "ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]] | None"  [arg-type]

... (truncated 979 lines) ...

spark (https://github.com/apache/spark)
- python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: Literal['int', 'Int8', 'Int16', 'Int32', 'Int64', 'b', 'i1', 'int8', 'byte', 'h', 'i2', 'int16', 'short', 'i', 'i4', 'int32', 'intc', 'l', 'long', 'i8', 'int64', 'int_', 'q', 'longlong', 'p', 'intp', 'int8[pyarrow]', 'int16[pyarrow]', 'int32[pyarrow]', 'int64[pyarrow]', 'UInt8', 'UInt16', 'UInt32', 'UInt64', 'B', 'u1', 'uint8', 'ubyte', 'H', 'u2', 'uint16', 'ushort', 'I', 'u4', 'uint32', 'uintc', 'L', 'ulong', 'u8', 'uint', 'uint64', 'Q', 'ulonglong', 'P', 'uintp', 'uint8[pyarrow]', 'uint16[pyarrow]', 'uint32[pyarrow]', 'uint64[pyarrow]'] | type[int] | Int8Dtype | Int16Dtype | Int32Dtype | Int64Dtype | <14 more items>, errors: Literal['ignore', 'raise'] = ...) -> Series[int]
+ python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: Literal['int', 'Int8', 'Int16', 'Int32', 'Int64', 'b', 'i1', 'int8', 'byte', 'h', 'i2', 'int16', 'short', 'i', 'i4', 'int32', 'intc', 'l', 'long', 'i8', 'int64', 'int_', 'q', 'longlong', 'p', 'intp', 'int8[pyarrow]', 'int16[pyarrow]', 'int32[pyarrow]', 'int64[pyarrow]', 'UInt8', 'UInt16', 'UInt32', 'UInt64', 'B', 'u1', 'uint8', 'ubyte', 'H', 'u2', 'uint16', 'ushort', 'I', 'u4', 'uint32', 'uintc', 'L', 'ulong', 'u8', 'uint', 'uint64', 'Q', 'ulonglong', 'P', 'uintp', 'uint8[pyarrow]', 'uint16[pyarrow]', 'uint32[pyarrow]', 'uint64[pyarrow]'] | type[int] | Int8Dtype | Int16Dtype | Int32Dtype | Int64Dtype | <12 more items>, errors: Literal['ignore', 'raise'] = ...) -> Series[int]
- python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: type[float] | Literal['float'] | Literal['Float32', 'Float64'] | Float32Dtype | Float64Dtype | Literal['e', 'f2', '<f2', 'float16', 'half'] | type[floating[_16Bit]] | Literal['f', 'f4', 'float32', 'single', 'd', 'f8', 'float64', 'double', 'g', 'f16', 'float128', 'longdouble'] | type[floating[_32Bit]] | type[float64] | type[floating[_64Bit | _96Bit | _128Bit]] | Literal['float[pyarrow]', 'double[pyarrow]', 'float16[pyarrow]', 'float32[pyarrow]', 'float64[pyarrow]'], errors: Literal['ignore', 'raise'] = ...) -> Series[float]
+ python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: type[float] | Literal['float'] | Literal['Float32', 'Float64'] | Float32Dtype | Float64Dtype | Literal['e', 'f2', '<f2', 'float16', 'half'] | type[float16] | Literal['f', 'f4', 'float32', 'single', 'd', 'f8', 'float64', 'double', 'g', 'f16', 'float128', 'longdouble'] | type[float32] | type[float64] | type[longdouble] | Literal['float[pyarrow]', 'double[pyarrow]', 'float16[pyarrow]', 'float32[pyarrow]', 'float64[pyarrow]'], errors: Literal['ignore', 'raise'] = ...) -> Series[float]
- python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: type[complex] | Literal['complex'] | Literal['F', 'c8', 'complex64', 'csingle', 'D', 'c16', 'complex128', 'cdouble', 'G', 'c32', 'complex256', 'clongdouble'] | type[complexfloating[_32Bit, _32Bit]] | type[complex128] | type[complexfloating[_64Bit | _96Bit | _128Bit, _64Bit | _96Bit | _128Bit]], errors: Literal['ignore', 'raise'] = ...) -> Series[complex]
+ python/pyspark/sql/pandas/types.py:1060: note:     def astype(self, dtype: type[complex] | Literal['complex'] | Literal['F', 'c8', 'complex64', 'csingle', 'D', 'c16', 'complex128', 'cdouble', 'G', 'c32', 'complex256', 'clongdouble'] | type[complex64] | type[complex128] | type[clongdouble], errors: Literal['ignore', 'raise'] = ...) -> Series[complex]
- python/pyspark/sql/pandas/types.py:1062: note:     def astype(self, dtype: Literal['int', 'Int8', 'Int16', 'Int32', 'Int64', 'b', 'i1', 'int8', 'byte', 'h', 'i2', 'int16', 'short', 'i', 'i4', 'int32', 'intc', 'l', 'long', 'i8', 'int64', 'int_', 'q', 'longlong', 'p', 'intp', 'int8[pyarrow]', 'int16[pyarrow]', 'int32[pyarrow]', 'int64[pyarrow]', 'UInt8', 'UInt16', 'UInt32', 'UInt64', 'B', 'u1', 'uint8', 'ubyte', 'H', 'u2', 'uint16', 'ushort', 'I', 'u4', 'uint32', 'uintc', 'L', 'ulong', 'u8', 'uint', 'uint64', 'Q', 'ulonglong', 'P', 'uintp', 'uint8[pyarrow]', 'uint16[pyarrow]', 'uint32[pyarrow]', 'uint64[pyarrow]'] | type[int] | Int8Dtype | Int16Dtype | Int32Dtype | Int64Dtype | <14 more items>, errors: Literal['ignore', 'raise'] = ...) -> Series[int]

... (truncated 107 lines) ...```

jorenham · 2026-10-15T21:31:44Z

After removing the mypy_primer diff lines where only the error message changed, here's what's left:

pandas (https://github.com/pandas-dev/pandas)
+ pandas/core/groupby/ops.py:900: error: Argument 2 to "_ob_index_and_ids" of "BaseGrouper" has incompatible type "list[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]"; expected "list[ndarray[tuple[Any, ...], dtype[int64]]]"  [arg-type]
+ pandas/core/groupby/ops.py:903: error: Argument 2 to "_unob_index_and_ids" of "BaseGrouper" has incompatible type "list[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]"; expected "list[ndarray[tuple[Any, ...], dtype[int64]]]"  [arg-type]
+ pandas/core/groupby/ops.py:912: error: List comprehension has incompatible type List[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]; expected List[ndarray[tuple[Any, ...], dtype[int64]]]  [misc]
+ pandas/core/groupby/ops.py:918: error: List comprehension has incompatible type List[ndarray[tuple[Any, ...], dtype[signedinteger[Any]]]]; expected List[ndarray[tuple[Any, ...], dtype[int64]]]  [misc]
+ pandas/core/groupby/ops.py:1392: error: Signature of "codes" incompatible with supertype "BaseGrouper"  [override]

colour (https://github.com/colour-science/colour)
+ colour/plotting/colorimetry.py:567: error: No overload variant of "__sub__" of "float16" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:567: error: No overload variant of "__sub__" of "float32" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:567: error: No overload variant of "__sub__" of "float64" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:567: error: Value of type variable "T" of "__call__" of "_ufunc_11_bifcmo" cannot be "number[Any, Any] | numpy.bool[builtins.bool] | timedelta64[Any] | datetime64[Any]"  [type-var]
+ colour/plotting/colorimetry.py:567: error: Unsupported operand types for * ("datetime64[Any]" and "float")  [operator]
+ colour/plotting/colorimetry.py:568: error: No overload variant of "__add__" of "float16" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:568: error: No overload variant of "__add__" of "float32" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:568: error: No overload variant of "__add__" of "float64" matches argument type "timedelta64[Any]"  [operator]
+ colour/plotting/colorimetry.py:568: error: Value of type variable "T" of "__call__" of "_ufunc_11_bifcmo" cannot be "number[Any, Any] | numpy.bool[builtins.bool] | timedelta64[Any] | datetime64[Any]"  [type-var]
+ colour/plotting/colorimetry.py:568: error: Unsupported operand types for * ("datetime64[Any]" and "float")  [operator]

pandas:
- the first 4 new errors (src) are related to the fact that list is invariance, which means that list[int64] is not assignable to list[np.signedinteger]. This error is correct and was previously hidden, so not a regression on our side.
- The last error for codes (src) is a similar issue caused by invariance of list, here caused by unsound assignment, but via method override. This indeed violates Liskov's substitution principle, which can easily be avoided by e.g. using Sequence instead of list in their annotations.
colour (src): The new errors are typing issues in colour itself that were previously hidden, and are surfacing now because the result of certain scalar arithmetic is now more accurate.

tldr; I expected more errors, but it turns out I was wrong (at least for this mypy_primer corpus), so that's a relief.

jorenham added 8 commits October 15, 2026 13:43

TYP: concrete unsignedinteger subtypes

688440c

TYP: concrete signedinteger subtypes

3719612

TYP: concrete floating subtypes

4753659

TYP: concrete complexfloating subtypes

d76bed3

TYP: replace NBitBase uses with better alternatives

d43e769

TYP: exact scalar arithmetic for concrete inexact types

ad8a7e2

TYP: exact scalar arithmetic for concrete signedinteger types

ba8549a

TYP: exact scalar arithmetic for concrete unsignedinteger types

7531ebd

jorenham added 56 - Needs Release Note. Needs an entry in doc/release/upcoming_changes 41 - Static typing labels Oct 15, 2026

jorenham added this to the 2.6.0 Release milestone Oct 15, 2026

jorenham mentioned this pull request Oct 15, 2026

isinstance() with a NumPy scalar type like np.int64 doesn't narrow astral-sh/ty#4727

Open

jorenham added 2 commits October 15, 2026 22:17

TYP/DOC: release note for the conrete scalar types

71ae51c

TYP: fix typetest failures on windows for random.RandomState

30b5ff1

jorenham removed the 56 - Needs Release Note. Needs an entry in doc/release/upcoming_changes label Oct 15, 2026

TYP/DOC: fix rst syntax thingy in relnote for concrete scalar types

4290293

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TYP: concrete `number` subtypes - #33052

TYP: concrete `number` subtypes#33052
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