✨start ArrayNamespace

pyproject.toml

@@ -126,6 +126,8 @@ ignore = [
   "FIX", # flake8-fixme
   "ISC001", # Conflicts with formatter
   "PYI041", # Use `float` instead of `int | float`
+  "TD002", # Missing author in TODO
+  "TD003", # Missing issue link for this TODO
 ]
 
 [tool.ruff.lint.pydocstyle]

src/array_api_typing/__init__.py

@@ -1,12 +1,35 @@
 """Static typing support for the array API standard."""
 
-__all__ = (
+__all__ = (  # noqa: RUF022
+    # ==================
+    # Array
     "Array",
     "HasArrayNamespace",
     "HasDType",
+    "HasMatrixTranspose",
+    "HasNDim",
+    "HasShape",
+    "HasSize",
+    "HasTranspose",
+    # ==================
+    # Namespace
+    "ArrayNamespace",
+    "DoesAsType",
+    "HasAsType",
+    # ==================
     "__version__",
     "__version_tuple__",
 )
 
-from ._array import Array, HasArrayNamespace, HasDType
+from ._array import (
+    Array,
+    HasArrayNamespace,
+    HasDType,
+    HasMatrixTranspose,
+    HasNDim,
+    HasShape,
+    HasSize,
+    HasTranspose,
+)
+from ._namespace import ArrayNamespace, DoesAsType, HasAsType
 from ._version import version as __version__, version_tuple as __version_tuple__

src/array_api_typing/_array.py

@@ -1,10 +1,17 @@
 __all__ = (
     "Array",
     "HasArrayNamespace",
+    "HasDType",
+    "HasDevice",
+    "HasMatrixTranspose",
+    "HasNDim",
+    "HasShape",
+    "HasSize",
+    "HasTranspose",
 )
 
 from types import ModuleType
-from typing import Literal, Protocol
+from typing import Literal, Protocol, Self
 from typing_extensions import TypeVar
 
 NamespaceT_co = TypeVar("NamespaceT_co", covariant=True, default=ModuleType)
@@ -67,10 +74,131 @@ def dtype(self, /) -> DTypeT_co:
         ...
 
 
+class HasDevice(Protocol):
+    """Protocol for array classes that have a device attribute."""
+
+    @property
+    def device(self) -> object:  # TODO: more specific type
+        """Hardware device the array data resides on."""
+        ...
+
+
+class HasMatrixTranspose(Protocol):
+    """Protocol for array classes that have a matrix transpose attribute."""
+
+    @property
+    def mT(self) -> Self:  # noqa: N802
+        """Transpose of a matrix (or a stack of matrices).
+
+        If an array instance has fewer than two dimensions, an error should be
+        raised.
+
+        Returns:
+            Self: array whose last two dimensions (axes) are permuted in reverse
+                order relative to original array (i.e., for an array instance
+                having shape `(..., M, N)`, the returned array must have shape
+                `(..., N, M))`.  The returned array must have the same data type
+                as the original array.
+
+        """
+        ...
+
+
+class HasNDim(Protocol):
+    """Protocol for array classes that have a number of dimensions attribute."""
+
+    @property
+    def ndim(self) -> int:
+        """Number of array dimensions (axes).
+
+        Returns:
+            int: number of array dimensions (axes).
+
+        """
+        ...
+
+
+class HasShape(Protocol):
+    """Protocol for array classes that have a shape attribute."""
+
+    @property
+    def shape(self) -> tuple[int | None, ...]:
+        """Shape of the array.
+
+        Returns:
+            tuple[int | None, ...]: array dimensions. An array dimension must be None
+                if and only if a dimension is unknown.
+
+        Notes:
+            For array libraries having graph-based computational models, array
+            dimensions may be unknown due to data-dependent operations (e.g.,
+            boolean indexing; `A[:, B > 0]`) and thus cannot be statically
+            resolved without knowing array contents.
+
+        """
+        ...
+
+
+class HasSize(Protocol):
+    """Protocol for array classes that have a size attribute."""
+
+    @property
+    def size(self) -> int | None:
+        """Number of elements in an array.
+
+        Returns:
+            int | None: number of elements in an array. The returned value must
+                be `None` if and only if one or more array dimensions are
+                unknown.
+
+        Notes:
+            This must equal the product of the array's dimensions.
+
+        """
+        ...
+
+
+class HasTranspose(Protocol):
+    """Protocol for array classes that support the transpose operation."""
+
+    @property
+    def T(self) -> Self:  # noqa: N802
+        """Transpose of the array.
+
+        The array instance must be two-dimensional. If the array instance is not
+        two-dimensional, an error should be raised.
+
+        Returns:
+            Self: two-dimensional array whose first and last dimensions (axes)
+                are permuted in reverse order relative to original array. The
+                returned array must have the same data type as the original
+                array.
+
+        Notes:
+            Limiting the transpose to two-dimensional arrays (matrices) deviates
+            from the NumPy et al practice of reversing all axes for arrays
+            having more than two-dimensions. This is intentional, as reversing
+            all axes was found to be problematic (e.g., conflicting with the
+            mathematical definition of a transpose which is limited to matrices;
+            not operating on batches of matrices; et cetera). In order to
+            reverse all axes, one is recommended to use the functional
+            `PermuteDims` interface found in this specification.
+
+        """
+        ...
+
+
 class Array(
-    HasArrayNamespace[NamespaceT_co],
     # ------ Attributes -------
     HasDType[DTypeT_co],
+    HasDevice,
+    HasMatrixTranspose,
+    HasNDim,
+    HasShape,
+    HasSize,
+    HasTranspose,
+    # ------- Methods ---------
+    HasArrayNamespace[NamespaceT_co],
     # -------------------------
     Protocol[DTypeT_co, NamespaceT_co],
 ):

src/array_api_typing/_namespace.py

@@ -0,0 +1,112 @@
+from typing import Protocol, TypeVar
+
+from ._array import HasDType
+
+__all__ = (
+    "ArrayNamespace",
+    # Data Type Functions
+    "DoesAsType",
+    "HasAsType",
+)
+
+DTypeT = TypeVar("DTypeT")
+ToDTypeT = TypeVar("ToDTypeT")
+
+# ===================================================================
+# Creation Functions
+# TODO: arange, asarray, empty, empty_like, eye, from_dlpack, full, full_like,
+# linspace, meshgrid, ones, ones_like, tril, triu, zeros, zeros_like
+
+# ===================================================================
+# Data Type Functions
+# TODO: broadcast_arrays, broadcast_to, can_cast, finfo, iinfo,
+# result_type
+
+
+class DoesAsType(Protocol):
+    """Copies an array to a specified data type irrespective of Type Promotion Rules rules.
+
+    Note:
+        Casting floating-point ``NaN`` and ``infinity`` values to integral data
+        types is not specified and is implementation-dependent.
+
+    Note:
+        When casting a boolean input array to a numeric data type, a value of
+        `True` must cast to a numeric value equal to ``1``, and a value of
+        `False` must cast to a numeric value equal to ``0``.
+
+        When casting a numeric input array to bool, a value of ``0`` must cast
+        to `False`, and a non-zero value must cast to `True`.
+
+    Args:
+        x: The array to cast.
+        dtype: desired data type.
+        copy: specifies whether to copy an array when the specified `dtype`
+            matches the data type of the input array `x`. If `True`, a newly
+            allocated array must always be returned. If `False` and the
+            specified `dtype` matches the data type of the input array, the
+            input array must be returned; otherwise, a newly allocated must be
+            returned. Default: `True`.
+
+    """  # noqa: E501
+
+    def __call__(
+        self, x: HasDType[DTypeT], dtype: ToDTypeT, /, *, copy: bool = True
+    ) -> HasDType[ToDTypeT]: ...
+
+
+class HasAsType(Protocol):
+    """Protocol for namespaces that have an ``astype`` function."""
+
+    astype: DoesAsType
+
+
+# ===================================================================
+# Element-wise Functions
+# TODO: abs, acos, acosh, add, asin, asinh, atan, atan2, atanh, bitwise_and,
+# bitwise_invert, bitwise_left_shift, bitwise_or, bitwise_right_shift,
+# bitwise_xor, ceil, cos, cosh, divide, equal, exp, exp2, expm1, floor,
+# floor_divide, greater, greater_equal, isfinite, isinf, isnan, less,
+# less_equal, log, log1p, log2, log10, logical_and, logical_not, logical_or,
+# logical_xor, multiply, negative, not_equal, positive, pow, remainder, round,
+# sign, sin, sinh, square, sqrt, subtract, tan, tanh, trunc
+
+
+# ===================================================================
+# Linear Algebra Functions
+# TODO: matmul, matrix_transpose, tensordot, vecdot
+
+# ===================================================================
+# Manipulation Functions
+# TODO: concat, expand_dims, flip, permute_dims, reshape, roll, squeeze, stack
+
+# ===================================================================
+# Searching Functions
+# TODO: argmax, argmin, nonzero, where
+
+# ===================================================================
+# Set Functions
+# TODO: unique_all, unique_counts, unique_inverse, unique_values
+
+# ===================================================================
+# Sorting Functions
+# TODO: argsort, sort
+
+# ===================================================================
+# Statistical Functions
+# TODO: max, mean, min, prod, std, sum, var
+
+# ===================================================================
+# Utility Functions
+# TODO: all, any
+
+# ===================================================================
+# Full Namespace
+
+
+class ArrayNamespace(
+    # Data Type Functions
+    HasAsType,
+    Protocol,
+):
+    """Protocol for an Array API-compatible namespace."""

tests/integration/test_numpy1p0.pyi

@@ -1,7 +1,7 @@
 # mypy: disable-error-code="no-redef"
 
 from types import ModuleType
-from typing import Any
+from typing import Any, assert_type
 
 import numpy.array_api as np  # type: ignore[import-not-found, unused-ignore]
 from numpy import dtype
@@ -49,5 +49,33 @@ a_ns: xpt.Array[Any, ModuleType] = nparr
 # Note that `np.array_api` uses dtype objects, not dtype classes, so we can't
 # type annotate specific dtypes like `np.float32` or `np.int32`.
 _: xpt.Array[dtype[Any]] = nparr
-_: xpt.Array[dtype[Any]] = nparr_i32
-_: xpt.Array[dtype[Any]] = nparr_f32
+x_f32: xpt.Array[dtype[Any]] = nparr_f32
+x_i32: xpt.Array[dtype[Any]] = nparr_i32
+
+# Check Attribute `.dtype`
+assert_type(x_f32.dtype, dtype[Any])
+assert_type(x_i32.dtype, dtype[Any])
+
+# Check Attribute `.device`
+assert_type(x_f32.device, object)
+assert_type(x_i32.device, object)
+
+# Check Attribute `.mT`
+assert_type(x_f32.mT, xpt.Array[dtype[Any]])
+assert_type(x_i32.mT, xpt.Array[dtype[Any]])
+
+# Check Attribute `.ndim`
+assert_type(x_f32.ndim, int)
+assert_type(x_i32.ndim, int)
+
+# Check Attribute `.shape`
+assert_type(x_f32.shape, tuple[int | None, ...])
+assert_type(x_i32.shape, tuple[int | None, ...])
+
+# Check Attribute `.size`
+assert_type(x_f32.size, int | None)
+assert_type(x_i32.size, int | None)
+
+# Check Attribute `.T`
+assert_type(x_f32.T, xpt.Array[dtype[Any]])
+assert_type(x_i32.T, xpt.Array[dtype[Any]])