numpy · charris · Jun 15, 2023 · Jun 5, 2023 · Jun 5, 2023 · Jun 5, 2023
diff --git a/doc/release/upcoming_changes/23789.new_feature.rst b/doc/release/upcoming_changes/23789.new_feature.rst
@@ -0,0 +1,7 @@
+Array API v2022.12 support in ``numpy.array_api``
+-------------------------------------------------
+
+- ``numpy.array_api`` now full supports the `v2022.12 version
+  <https://data-apis.org/array-api/2022.12>`__ of the array API standard. Note
+  that this does not yet include the optional ``fft`` extension in the
+  standard.
diff --git a/numpy/array_api/__init__.py b/numpy/array_api/__init__.py
@@ -121,7 +121,7 @@
     "The numpy.array_api submodule is still experimental. See NEP 47.", stacklevel=2
 )
 
-__array_api_version__ = "2021.12"
+__array_api_version__ = "2022.12"
 
 __all__ = ["__array_api_version__"]
 
@@ -173,6 +173,7 @@
     broadcast_to,
     can_cast,
     finfo,
+    isdtype,
     iinfo,
     result_type,
 )
@@ -198,6 +199,8 @@
     uint64,
     float32,
     float64,
+    complex64,
+    complex128,
     bool,
 )
 
@@ -232,6 +235,7 @@
     bitwise_right_shift,
     bitwise_xor,
     ceil,
+    conj,
     cos,
     cosh,
     divide,
@@ -242,6 +246,7 @@
     floor_divide,
     greater,
     greater_equal,
+    imag,
     isfinite,
     isinf,
     isnan,
@@ -261,6 +266,7 @@
     not_equal,
     positive,
     pow,
+    real,
     remainder,
     round,
     sign,

diff --git a/numpy/array_api/_array_object.py b/numpy/array_api/_array_object.py
@@ -24,6 +24,7 @@
     _integer_dtypes,
     _integer_or_boolean_dtypes,
     _floating_dtypes,
+    _complex_floating_dtypes,
     _numeric_dtypes,
     _result_type,
     _dtype_categories,
@@ -139,7 +140,7 @@ def _check_allowed_dtypes(self, other: bool | int | float | Array, dtype_categor
 
         if self.dtype not in _dtype_categories[dtype_category]:
             raise TypeError(f"Only {dtype_category} dtypes are allowed in {op}")
-        if isinstance(other, (int, float, bool)):
+        if isinstance(other, (int, complex, float, bool)):
             other = self._promote_scalar(other)
         elif isinstance(other, Array):
             if other.dtype not in _dtype_categories[dtype_category]:
@@ -189,11 +190,23 @@ def _promote_scalar(self, scalar):
                 raise TypeError(
                     "Python int scalars cannot be promoted with bool arrays"
                 )
+            if self.dtype in _integer_dtypes:
+                info = np.iinfo(self.dtype)
+                if not (info.min <= scalar <= info.max):
+                    raise OverflowError(
+                        "Python int scalars must be within the bounds of the dtype for integer arrays"
+                    )
+            # int + array(floating) is allowed
         elif isinstance(scalar, float):
             if self.dtype not in _floating_dtypes:
                 raise TypeError(
                     "Python float scalars can only be promoted with floating-point arrays."
                 )
+        elif isinstance(scalar, complex):
+            if self.dtype not in _complex_floating_dtypes:
+                raise TypeError(
+                    "Python complex scalars can only be promoted with complex floating-point arrays."
+                )
         else:
             raise TypeError("'scalar' must be a Python scalar")
 
@@ -454,11 +467,19 @@ def __bool__(self: Array, /) -> bool:
         # Note: This is an error here.
         if self._array.ndim != 0:
             raise TypeError("bool is only allowed on arrays with 0 dimensions")
-        if self.dtype not in _boolean_dtypes:
-            raise ValueError("bool is only allowed on boolean arrays")
         res = self._array.__bool__()
         return res
 
+    def __complex__(self: Array, /) -> complex:
+        """
+        Performs the operation __complex__.
+        """
+        # Note: This is an error here.
+        if self._array.ndim != 0:
+            raise TypeError("complex is only allowed on arrays with 0 dimensions")
+        res = self._array.__complex__()
+        return res
+
     def __dlpack__(self: Array, /, *, stream: None = None) -> PyCapsule:
         """
         Performs the operation __dlpack__.
@@ -492,16 +513,16 @@ def __float__(self: Array, /) -> float:
         # Note: This is an error here.
         if self._array.ndim != 0:
             raise TypeError("float is only allowed on arrays with 0 dimensions")
-        if self.dtype not in _floating_dtypes:
-            raise ValueError("float is only allowed on floating-point arrays")
+        if self.dtype in _complex_floating_dtypes:
+            raise TypeError("float is not allowed on complex floating-point arrays")
         res = self._array.__float__()
         return res
 
     def __floordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __floordiv__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__floordiv__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__floordiv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -512,7 +533,7 @@ def __ge__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __ge__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__ge__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__ge__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -542,7 +563,7 @@ def __gt__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __gt__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__gt__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__gt__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -556,8 +577,8 @@ def __int__(self: Array, /) -> int:
         # Note: This is an error here.
         if self._array.ndim != 0:
             raise TypeError("int is only allowed on arrays with 0 dimensions")
-        if self.dtype not in _integer_dtypes:
-            raise ValueError("int is only allowed on integer arrays")
+        if self.dtype in _complex_floating_dtypes:
+            raise TypeError("int is not allowed on complex floating-point arrays")
         res = self._array.__int__()
         return res
 
@@ -581,7 +602,7 @@ def __le__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __le__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__le__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__le__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -603,7 +624,7 @@ def __lt__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __lt__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__lt__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__lt__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -626,7 +647,7 @@ def __mod__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __mod__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__mod__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__mod__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -808,7 +829,7 @@ def __ifloordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __ifloordiv__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__ifloordiv__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__ifloordiv__")
         if other is NotImplemented:
             return other
         self._array.__ifloordiv__(other._array)
@@ -818,7 +839,7 @@ def __rfloordiv__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __rfloordiv__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__rfloordiv__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__rfloordiv__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)
@@ -874,7 +895,7 @@ def __imod__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __imod__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__imod__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__imod__")
         if other is NotImplemented:
             return other
         self._array.__imod__(other._array)
@@ -884,7 +905,7 @@ def __rmod__(self: Array, other: Union[int, float, Array], /) -> Array:
         """
         Performs the operation __rmod__.
         """
-        other = self._check_allowed_dtypes(other, "numeric", "__rmod__")
+        other = self._check_allowed_dtypes(other, "real numeric", "__rmod__")
         if other is NotImplemented:
             return other
         self, other = self._normalize_two_args(self, other)

diff --git a/numpy/array_api/_data_type_functions.py b/numpy/array_api/_data_type_functions.py
@@ -1,7 +1,17 @@
 from __future__ import annotations
 
 from ._array_object import Array
-from ._dtypes import _all_dtypes, _result_type
+from ._dtypes import (
+    _all_dtypes,
+    _boolean_dtypes,
+    _signed_integer_dtypes,
+    _unsigned_integer_dtypes,
+    _integer_dtypes,
+    _real_floating_dtypes,
+    _complex_floating_dtypes,
+    _numeric_dtypes,
+    _result_type,
+)
 
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, List, Tuple, Union
@@ -80,13 +90,15 @@ class finfo_object:
     max: float
     min: float
     smallest_normal: float
+    dtype: Dtype
 
 
 @dataclass
 class iinfo_object:
     bits: int
     max: int
     min: int
+    dtype: Dtype
 
 
 def finfo(type: Union[Dtype, Array], /) -> finfo_object:
@@ -104,6 +116,7 @@ def finfo(type: Union[Dtype, Array], /) -> finfo_object:
         float(fi.max),
         float(fi.min),
         float(fi.smallest_normal),
+        fi.dtype,
     )
 
 
@@ -114,9 +127,47 @@ def iinfo(type: Union[Dtype, Array], /) -> iinfo_object:
     See its docstring for more information.
     """
     ii = np.iinfo(type)
-    return iinfo_object(ii.bits, ii.max, ii.min)
+    return iinfo_object(ii.bits, ii.max, ii.min, ii.dtype)
 
 
+# Note: isdtype is a new function from the 2022.12 array API specification.
+def isdtype(
+    dtype: Dtype, kind: Union[Dtype, str, Tuple[Union[Dtype, str], ...]]
+) -> bool:
+    """
+    Returns a boolean indicating whether a provided dtype is of a specified data type ``kind``.
+
+    See
+    https://data-apis.org/array-api/latest/API_specification/generated/array_api.isdtype.html
+    for more details
+    """
+    if isinstance(kind, tuple):
+        # Disallow nested tuples
+        if any(isinstance(k, tuple) for k in kind):
+            raise TypeError("'kind' must be a dtype, str, or tuple of dtypes and strs")
+        return any(isdtype(dtype, k) for k in kind)
+    elif isinstance(kind, str):
+        if kind == 'bool':
+            return dtype in _boolean_dtypes
+        elif kind == 'signed integer':
+            return dtype in _signed_integer_dtypes
+        elif kind == 'unsigned integer':
+            return dtype in _unsigned_integer_dtypes
+        elif kind == 'integral':
+            return dtype in _integer_dtypes
+        elif kind == 'real floating':
+            return dtype in _real_floating_dtypes
+        elif kind == 'complex floating':
+            return dtype in _complex_floating_dtypes
+        elif kind == 'numeric':
+            return dtype in _numeric_dtypes
+        else:
+            raise ValueError(f"Unrecognized data type kind: {kind!r}")
+    elif kind in _all_dtypes:
+        return dtype == kind
+    else:
+        raise TypeError(f"'kind' must be a dtype, str, or tuple of dtypes and strs, not {type(kind).__name__}")
+
 def result_type(*arrays_and_dtypes: Union[Array, Dtype]) -> Dtype:
     """
     Array API compatible wrapper for :py:func:`np.result_type <numpy.result_type>`.