convert PyUntypedArray to Bound API

src/array.rs

@@ -33,7 +33,7 @@ use crate::error::{
 };
 use crate::npyffi::{self, npy_intp, NPY_ORDER, PY_ARRAY_API};
 use crate::slice_container::PySliceContainer;
-use crate::untyped_array::PyUntypedArray;
+use crate::untyped_array::{PyUntypedArray, PyUntypedArrayMethods};
 
 /// A safe, statically-typed wrapper for NumPy's [`ndarray`][ndarray] class.
 ///
@@ -1480,6 +1480,20 @@ unsafe fn clone_elements<T: Element>(elems: &[T], data_ptr: &mut *mut T) {
     }
 }
 
+/// Implementation of functionality for [`PyArray<T, D>`].
+#[doc(alias = "PyArray")]
+pub trait PyArrayMethods<'py, T, D>: PyUntypedArrayMethods<'py> {
+    /// Access an untyped representation of this array.
+    fn as_untyped(&self) -> &Bound<'py, PyUntypedArray>;
+}
+
+impl<'py, T, D> PyArrayMethods<'py, T, D> for Bound<'py, PyArray<T, D>> {
+    #[inline(always)]
+    fn as_untyped(&self) -> &Bound<'py, PyUntypedArray> {
+        unsafe { self.downcast_unchecked() }
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;

src/lib.rs

@@ -93,7 +93,7 @@ pub use nalgebra;
 
 pub use crate::array::{
     get_array_module, PyArray, PyArray0, PyArray1, PyArray2, PyArray3, PyArray4, PyArray5,
-    PyArray6, PyArrayDyn,
+    PyArray6, PyArrayDyn, PyArrayMethods,
 };
 pub use crate::array_like::{
     AllowTypeChange, PyArrayLike, PyArrayLike0, PyArrayLike1, PyArrayLike2, PyArrayLike3,
@@ -111,7 +111,7 @@ pub use crate::error::{BorrowError, FromVecError, NotContiguousError};
 pub use crate::npyffi::{PY_ARRAY_API, PY_UFUNC_API};
 pub use crate::strings::{PyFixedString, PyFixedUnicode};
 pub use crate::sum_products::{dot, einsum, inner};
-pub use crate::untyped_array::PyUntypedArray;
+pub use crate::untyped_array::{PyUntypedArray, PyUntypedArrayMethods};
 
 pub use ndarray::{array, Ix1, Ix2, Ix3, Ix4, Ix5, Ix6, IxDyn};
 

src/untyped_array.rs

@@ -1,13 +1,14 @@
 //! Safe, untyped interface for NumPy's [N-dimensional arrays][ndarray]
 //!
 //! [ndarray]: https://numpy.org/doc/stable/reference/arrays.ndarray.html
-use std::{os::raw::c_int, slice};
+use std::slice;
 
 use pyo3::{
-    ffi, pyobject_native_type_extract, pyobject_native_type_named, AsPyPointer, IntoPy, PyAny,
-    PyNativeType, PyObject, PyTypeInfo, Python,
+    ffi, pyobject_native_type_extract, pyobject_native_type_named, types::PyAnyMethods,
+    AsPyPointer, Bound, IntoPy, PyAny, PyNativeType, PyObject, PyTypeInfo, Python,
 };
 
+use crate::array::{PyArray, PyArrayMethods};
 use crate::cold;
 use crate::dtype::PyArrayDescr;
 use crate::npyffi;
@@ -68,7 +69,7 @@ unsafe impl PyTypeInfo for PyUntypedArray {
         unsafe { npyffi::PY_ARRAY_API.get_type_object(py, npyffi::NpyTypes::PyArray_Type) }
     }
 
-    fn is_type_of(ob: &PyAny) -> bool {
+    fn is_type_of_bound(ob: &Bound<'_, PyAny>) -> bool {
         unsafe { npyffi::PyArray_Check(ob.py(), ob.as_ptr()) != 0 }
     }
 }
@@ -87,7 +88,7 @@ impl PyUntypedArray {
     /// Returns a raw pointer to the underlying [`PyArrayObject`][npyffi::PyArrayObject].
     #[inline]
     pub fn as_array_ptr(&self) -> *mut npyffi::PyArrayObject {
-        self.as_ptr() as _
+        self.as_borrowed().as_array_ptr()
     }
 
     /// Returns the `dtype` of the array.
@@ -109,16 +110,9 @@ impl PyUntypedArray {
     ///
     /// [ndarray-dtype]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dtype.html
     /// [PyArray_DTYPE]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_DTYPE
+    #[inline]
     pub fn dtype(&self) -> &PyArrayDescr {
-        unsafe {
-            let descr_ptr = (*self.as_array_ptr()).descr;
-            self.py().from_borrowed_ptr(descr_ptr as _)
-        }
-    }
-
-    #[inline(always)]
-    pub(crate) fn check_flags(&self, flags: c_int) -> bool {
-        unsafe { (*self.as_array_ptr()).flags & flags != 0 }
+        self.as_borrowed().dtype().into_gil_ref()
     }
 
     /// Returns `true` if the internal data of the array is contiguous,
@@ -142,18 +136,21 @@ impl PyUntypedArray {
     ///     assert!(!view.is_contiguous());
     /// });
     /// ```
+    #[inline]
     pub fn is_contiguous(&self) -> bool {
-        self.check_flags(npyffi::NPY_ARRAY_C_CONTIGUOUS | npyffi::NPY_ARRAY_F_CONTIGUOUS)
+        self.as_borrowed().is_contiguous()
     }
 
     /// Returns `true` if the internal data of the array is Fortran-style/column-major contiguous.
+    #[inline]
     pub fn is_fortran_contiguous(&self) -> bool {
-        self.check_flags(npyffi::NPY_ARRAY_F_CONTIGUOUS)
+        self.as_borrowed().is_fortran_contiguous()
     }
 
     /// Returns `true` if the internal data of the array is C-style/row-major contiguous.
+    #[inline]
     pub fn is_c_contiguous(&self) -> bool {
-        self.check_flags(npyffi::NPY_ARRAY_C_CONTIGUOUS)
+        self.as_borrowed().is_c_contiguous()
     }
 
     /// Returns the number of dimensions of the array.
@@ -177,7 +174,7 @@ impl PyUntypedArray {
     /// [PyArray_NDIM]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_NDIM
     #[inline]
     pub fn ndim(&self) -> usize {
-        unsafe { (*self.as_array_ptr()).nd as usize }
+        self.as_borrowed().ndim()
     }
 
     /// Returns a slice indicating how many bytes to advance when iterating along each axis.
@@ -246,12 +243,222 @@ impl PyUntypedArray {
     }
 
     /// Calculates the total number of elements in the array.
+    #[inline]
     pub fn len(&self) -> usize {
-        self.shape().iter().product()
+        self.as_borrowed().len()
     }
 
     /// Returns `true` if the there are no elements in the array.
+    #[inline]
     pub fn is_empty(&self) -> bool {
+        self.as_borrowed().is_empty()
+    }
+}
+
+/// Implementation of functionality for [`PyUntypedArray`].
+#[doc(alias = "PyUntypedArray")]
+pub trait PyUntypedArrayMethods<'py>: sealed::Sealed {
+    /// Returns a raw pointer to the underlying [`PyArrayObject`][npyffi::PyArrayObject].
+    fn as_array_ptr(&self) -> *mut npyffi::PyArrayObject;
+
+    /// Returns the `dtype` of the array.
+    ///
+    /// See also [`ndarray.dtype`][ndarray-dtype] and [`PyArray_DTYPE`][PyArray_DTYPE].
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// use numpy::{dtype, PyArray};
+    /// use pyo3::Python;
+    ///
+    /// Python::with_gil(|py| {
+    ///    let array = PyArray::from_vec(py, vec![1_i32, 2, 3]);
+    ///
+    ///    assert!(array.dtype().is_equiv_to(dtype::<i32>(py)));
+    /// });
+    /// ```
+    ///
+    /// [ndarray-dtype]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dtype.html
+    /// [PyArray_DTYPE]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_DTYPE
+    fn dtype(&self) -> Bound<'py, PyArrayDescr>;
+
+    /// Returns `true` if the internal data of the array is contiguous,
+    /// indepedently of whether C-style/row-major or Fortran-style/column-major.
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// use numpy::PyArray1;
+    /// use pyo3::{types::IntoPyDict, Python};
+    ///
+    /// Python::with_gil(|py| {
+    ///     let array = PyArray1::arange(py, 0, 10, 1);
+    ///     assert!(array.is_contiguous());
+    ///
+    ///     let view = py
+    ///         .eval("array[::2]", None, Some([("array", array)].into_py_dict(py)))
+    ///         .unwrap()
+    ///         .downcast::<PyArray1<i32>>()
+    ///         .unwrap();
+    ///     assert!(!view.is_contiguous());
+    /// });
+    /// ```
+    fn is_contiguous(&self) -> bool {
+        unsafe {
+            check_flags(
+                &*self.as_array_ptr(),
+                npyffi::NPY_ARRAY_C_CONTIGUOUS | npyffi::NPY_ARRAY_F_CONTIGUOUS,
+            )
+        }
+    }
+
+    /// Returns `true` if the internal data of the array is Fortran-style/column-major contiguous.
+    fn is_fortran_contiguous(&self) -> bool {
+        unsafe { check_flags(&*self.as_array_ptr(), npyffi::NPY_ARRAY_F_CONTIGUOUS) }
+    }
+
+    /// Returns `true` if the internal data of the array is C-style/row-major contiguous.
+    fn is_c_contiguous(&self) -> bool {
+        unsafe { check_flags(&*self.as_array_ptr(), npyffi::NPY_ARRAY_C_CONTIGUOUS) }
+    }
+
+    /// Returns the number of dimensions of the array.
+    ///
+    /// See also [`ndarray.ndim`][ndarray-ndim] and [`PyArray_NDIM`][PyArray_NDIM].
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// use numpy::PyArray3;
+    /// use pyo3::Python;
+    ///
+    /// Python::with_gil(|py| {
+    ///     let arr = PyArray3::<f64>::zeros(py, [4, 5, 6], false);
+    ///
+    ///     assert_eq!(arr.ndim(), 3);
+    /// });
+    /// ```
+    ///
+    /// [ndarray-ndim]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.ndim.html
+    /// [PyArray_NDIM]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_NDIM
+    #[inline]
+    fn ndim(&self) -> usize {
+        unsafe { (*self.as_array_ptr()).nd as usize }
+    }
+
+    /// Returns a slice indicating how many bytes to advance when iterating along each axis.
+    ///
+    /// See also [`ndarray.strides`][ndarray-strides] and [`PyArray_STRIDES`][PyArray_STRIDES].
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// use numpy::PyArray3;
+    /// use pyo3::Python;
+    ///
+    /// Python::with_gil(|py| {
+    ///     let arr = PyArray3::<f64>::zeros(py, [4, 5, 6], false);
+    ///
+    ///     assert_eq!(arr.strides(), &[240, 48, 8]);
+    /// });
+    /// ```
+    /// [ndarray-strides]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.strides.html
+    /// [PyArray_STRIDES]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_STRIDES
+    #[inline]
+    fn strides(&self) -> &[isize] {
+        let n = self.ndim();
+        if n == 0 {
+            cold();
+            return &[];
+        }
+        let ptr = self.as_array_ptr();
+        unsafe {
+            let p = (*ptr).strides;
+            slice::from_raw_parts(p, n)
+        }
+    }
+
+    /// Returns a slice which contains dimmensions of the array.
+    ///
+    /// See also [`ndarray.shape`][ndaray-shape] and [`PyArray_DIMS`][PyArray_DIMS].
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// use numpy::PyArray3;
+    /// use pyo3::Python;
+    ///
+    /// Python::with_gil(|py| {
+    ///     let arr = PyArray3::<f64>::zeros(py, [4, 5, 6], false);
+    ///
+    ///     assert_eq!(arr.shape(), &[4, 5, 6]);
+    /// });
+    /// ```
+    ///
+    /// [ndarray-shape]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.shape.html
+    /// [PyArray_DIMS]: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_DIMS
+    #[inline]
+    fn shape(&self) -> &[usize] {
+        let n = self.ndim();
+        if n == 0 {
+            cold();
+            return &[];
+        }
+        let ptr = self.as_array_ptr();
+        unsafe {
+            let p = (*ptr).dimensions as *mut usize;
+            slice::from_raw_parts(p, n)
+        }
+    }
+
+    /// Calculates the total number of elements in the array.
+    fn len(&self) -> usize {
+        self.shape().iter().product()
+    }
+
+    /// Returns `true` if the there are no elements in the array.
+    fn is_empty(&self) -> bool {
         self.shape().iter().any(|dim| *dim == 0)
     }
 }
+
+fn check_flags(obj: &npyffi::PyArrayObject, flags: i32) -> bool {
+    obj.flags & flags != 0
+}
+
+impl<'py> PyUntypedArrayMethods<'py> for Bound<'py, PyUntypedArray> {
+    #[inline]
+    fn as_array_ptr(&self) -> *mut npyffi::PyArrayObject {
+        self.as_ptr().cast()
+    }
+
+    fn dtype(&self) -> Bound<'py, PyArrayDescr> {
+        unsafe {
+            let descr_ptr = (*self.as_array_ptr()).descr;
+            Bound::from_borrowed_ptr(self.py(), descr_ptr.cast()).downcast_into_unchecked()
+        }
+    }
+}
+
+// We won't be able to provide a `Deref` impl from `Bound<'_, PyArray<T, D>>` to
+// `Bound<'_, PyUntypedArray>`, so this seems to be the next best thing to do
+impl<'py, T, D> PyUntypedArrayMethods<'py> for Bound<'py, PyArray<T, D>> {
+    #[inline]
+    fn as_array_ptr(&self) -> *mut npyffi::PyArrayObject {
+        self.as_untyped().as_array_ptr()
+    }
+
+    #[inline]
+    fn dtype(&self) -> Bound<'py, PyArrayDescr> {
+        self.as_untyped().dtype()
+    }
+}
+
+mod sealed {
+    use super::{PyArray, PyUntypedArray};
+
+    pub trait Sealed {}
+
+    impl Sealed for pyo3::Bound<'_, PyUntypedArray> {}
+    impl<T, D> Sealed for pyo3::Bound<'_, PyArray<T, D>> {}
+}