Struct numpy::array::PyArray

pub struct PyArray<T, D>(_, _, _);

A safe, static-typed interface for NumPy ndarray.

Memory location

• Case1: Constructed via IntoPyArray or from_vec or from_owned_array.

These methods don’t allocate memory and use Box<[T]> as a internal buffer.

Please take care that you cannot use some destructive methods like resize, for this kind of array.

• Case2: Constructed via other methods, like ToPyArray or from_slice or from_array.

These methods allocate memory in Python’s private heap.

In both cases, PyArray is managed by Python GC. So you can neither retrieve it nor deallocate it manually.

Reference

Like new, all constractor methods of PyArray returns &PyArray.

This design follows pyo3’s ownership concept.

Data type and Dimension

PyArray has 2 type parametes T and D. T represents its data type like f32, and D represents its dimension.

All data types you can use implements Element.

Dimensions are represented by ndarray’s Dimension trait.

Typically, you can use Ix1, Ix2, .. for fixed size arrays, and use IxDyn for dynamic dimensioned arrays. They’re re-exported from ndarray crate.

You can also use various type aliases we provide, like PyArray1 or PyArrayDyn.

To specify concrete dimension like 3×4×5, you can use types which implements ndarray’s IntoDimension trait. Typically, you can use array(e.g. [3, 4, 5]) or tuple(e.g. (3, 4, 5)) as a dimension.

Example

use numpy::PyArray;
use ndarray::Array;
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::arange(py, 0., 4., 1.).reshape([2, 2]).unwrap();
    let array = array![[3., 4.], [5., 6.]];
    assert_eq!(
        array.dot(&pyarray.readonly().as_array()),
        array![[8., 15.], [12., 23.]]
    );
});

Implementations

impl<T, D> PyArray<T, D>

pub fn as_array_ptr(&self) -> *mut PyArrayObject

Gets a raw PyArrayObject pointer.

pub fn dtype(&self) -> &PyArrayDescr

Returns dtype of the array. Counterpart of array.dtype in Python.

Example

pyo3::Python::with_gil(|py| {
   let array = numpy::PyArray::from_vec(py, vec![1, 2, 3i32]);
   let dtype = array.dtype();
   assert_eq!(dtype.get_datatype().unwrap(), numpy::DataType::Int32);
});

pub fn readonly(&self) -> PyReadonlyArray<'_, T, D>

Returns a temporally unwriteable reference of the array.

pub fn is_contiguous(&self) -> bool

Returns true if the internal data of the array is C-style contiguous (default of numpy and ndarray) or Fortran-style contiguous.

Example

use pyo3::types::IntoPyDict;
pyo3::Python::with_gil(|py| {
    let array = numpy::PyArray::arange(py, 0, 10, 1);
    assert!(array.is_contiguous());
    let locals = [("np", numpy::get_array_module(py).unwrap())].into_py_dict(py);
    let not_contiguous: &numpy::PyArray1<f32> = py
        .eval("np.zeros((3, 5))[::2, 4]", Some(locals), None)
        .unwrap()
        .downcast()
        .unwrap();
    assert!(!not_contiguous.is_contiguous());
});

pub fn is_fortran_contiguous(&self) -> bool

Returns true if the internal data of the array is Fortran-style contiguous.

pub fn is_c_contiguous(&self) -> bool

Returns true if the internal data of the array is C-style contiguous.

pub fn to_owned(&self) -> Py<Self>

Get Py<PyArray> from &PyArray, which is the owned wrapper of PyObject.

You can use this method when you have to avoid lifetime annotation to your function args or return types, like used with pyo3’s pymethod.

Example

use numpy::PyArray1;
fn return_py_array() -> pyo3::Py<PyArray1<i32>> {
   pyo3::Python::with_gil(|py| PyArray1::zeros(py, [5], false).to_owned())
}
let array = return_py_array();
pyo3::Python::with_gil(|py| {
    assert_eq!(array.as_ref(py).readonly().as_slice().unwrap(), &[0, 0, 0, 0, 0]);
});

pub unsafe fn from_owned_ptr(py: Python<'_>, ptr: *mut PyObject) -> &Self

Constructs PyArray from raw python object without incrementing reference counts.

pub unsafe fn from_borrowed_ptr(py: Python<'_>, ptr: *mut PyObject) -> &Self

Constructs PyArray from raw python object and increments reference counts.

pub fn ndim(&self) -> usize

Returns the number of dimensions in the array.

Same as numpy.ndarray.ndim

Example

use numpy::PyArray3;
pyo3::Python::with_gil(|py| {
    let arr = PyArray3::<f64>::new(py, [4, 5, 6], false);
    assert_eq!(arr.ndim(), 3);
});

pub fn strides(&self) -> &[isize]

Returns a slice which contains how many bytes you need to jump to the next row.

Same as numpy.ndarray.strides

Example

use numpy::PyArray3;
pyo3::Python::with_gil(|py| {
    let arr = PyArray3::<f64>::new(py, [4, 5, 6], false);
    assert_eq!(arr.strides(), &[240, 48, 8]);
});

pub fn shape(&self) -> &[usize]

Returns a slice which contains dimmensions of the array.

Same as numpy.ndarray.shape

Example

use numpy::PyArray3;
pyo3::Python::with_gil(|py| {
    let arr = PyArray3::<f64>::new(py, [4, 5, 6], false);
    assert_eq!(arr.shape(), &[4, 5, 6]);
});

pub fn len(&self) -> usize

Calcurates the total number of elements in the array.

pub fn is_empty(&self) -> bool

impl<T: Element, D: Dimension> PyArray<T, D>

pub fn dims(&self) -> D

Same as shape, but returns D

pub fn new<ID>(py: Python<'_>, dims: ID, is_fortran: bool) -> &Self where
    ID: IntoDimension<Dim = D>, 

Creates a new uninitialized PyArray in python heap.

If is_fortran == true, returns Fortran-order array. Else, returns C-order array.

Example

use numpy::PyArray3;
pyo3::Python::with_gil(|py| {
    let arr = PyArray3::<i32>::new(py, [4, 5, 6], false);
    assert_eq!(arr.shape(), &[4, 5, 6]);
});

pub fn zeros<ID>(py: Python<'_>, dims: ID, is_fortran: bool) -> &Self where
    ID: IntoDimension<Dim = D>, 

Construct a new nd-dimensional array filled with 0.

If is_fortran is true, then a fortran order array is created, otherwise a C-order array is created.

See also PyArray_Zeros

Example

use numpy::PyArray2;
pyo3::Python::with_gil(|py| {
    let pyarray: &PyArray2<usize> = PyArray2::zeros(py, [2, 2], false);
    assert_eq!(pyarray.readonly().as_array(), array![[0, 0], [0, 0]]);
});

pub unsafe fn as_slice(&self) -> Result<&[T], NotContiguousError>

Returns the immutable view of the internal data of PyArray as slice.

Please consider the use of safe alternatives (PyReadonlyArray::as_slice , as_cell_slice or to_vec) instead of this.

Safety

If the internal array is not readonly and can be mutated from Python code, holding the slice might cause undefined behavior.

pub fn as_cell_slice(&self) -> Result<&[Cell<T>], NotContiguousError>

Returns the view of the internal data of PyArray as &[Cell<T>].

pub unsafe fn as_slice_mut(&self) -> Result<&mut [T], NotContiguousError>

Returns the view of the internal data of PyArray as mutable slice.

Safety

If another reference to the internal data exists(e.g., &[T] or ArrayView), it might cause undefined behavior.

In such case, please consider the use of as_cell_slice,

pub fn from_owned_array<'py>(py: Python<'py>, arr: Array<T, D>) -> &'py Self

Construct PyArray from ndarray::Array.

This method uses internal Vec of ndarray::Array as numpy array.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_owned_array(py, array![[1, 2], [3, 4]]);
    assert_eq!(pyarray.readonly().as_array(), array![[1, 2], [3, 4]]);
});

pub unsafe fn get(&self, index: impl NpyIndex<Dim = D>) -> Option<&T>

Get the immutable reference of the specified element, with checking the passed index is valid.

Please consider the use of safe alternatives (PyReadonlyArray::get or get_owned) instead of this.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap();
    assert_eq!(*unsafe { arr.get([1, 0, 3]) }.unwrap(), 11);
});

Safety

If the internal array is not readonly and can be mutated from Python code, holding the slice might cause undefined behavior.

pub unsafe fn uget<Idx>(&self, index: Idx) -> &T where
    Idx: NpyIndex<Dim = D>, 

Get the immutable reference of the specified element, without checking the passed index is valid.

See NpyIndex for what types you can use as index.

Passing an invalid index can cause undefined behavior(mostly SIGSEGV).

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap();
    assert_eq!(unsafe { *arr.uget([1, 0, 3]) }, 11);
});

pub unsafe fn uget_mut<Idx>(&self, index: Idx) -> &mut T where
    Idx: NpyIndex<Dim = D>, 

Same as uget, but returns &mut T.

pub fn to_dyn(&self) -> &PyArray<T, IxDyn>

Get dynamic dimensioned array from fixed dimension array.

pub fn get_owned(&self, index: impl NpyIndex<Dim = D>) -> Option<T>

Get the copy of the specified element in the array.

See NpyIndex for what types you can use as index.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap();
    assert_eq!(arr.get_owned([1, 0, 3]), Some(11));
});

pub fn to_vec(&self) -> Result<Vec<T>, NotContiguousError>

Returns the copy of the internal data of PyArray to Vec.

Returns ErrorKind::NotContiguous if the internal array is not contiguous. See also as_slice

Example

use numpy::PyArray2;
use pyo3::types::IntoPyDict;
pyo3::Python::with_gil(|py| {
    let locals = [("np", numpy::get_array_module(py).unwrap())].into_py_dict(py);
    let array: &PyArray2<i64> = py
        .eval("np.array([[0, 1], [2, 3]], dtype='int64')", Some(locals), None)
        .unwrap()
        .downcast()
        .unwrap();
    assert_eq!(array.to_vec().unwrap(), vec![0, 1, 2, 3]);
});

pub fn from_array<'py, S>(py: Python<'py>, arr: &ArrayBase<S, D>) -> &'py Self where
    S: Data<Elem = T>, 

Construct PyArray from ndarray::ArrayBase.

This method allocates memory in Python’s heap via numpy api, and then copies all elements of the array there.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_array(py, &array![[1, 2], [3, 4]]);
    assert_eq!(pyarray.readonly().as_array(), array![[1, 2], [3, 4]]);
});

pub unsafe fn as_array(&self) -> ArrayView<'_, T, D>

Get the immutable view of the internal data of PyArray, as ndarray::ArrayView.

Please consider the use of safe alternatives (PyReadonlyArray::as_array or to_array) instead of this.

Safety

If the internal array is not readonly and can be mutated from Python code, holding the ArrayView might cause undefined behavior.

pub unsafe fn as_array_mut(&self) -> ArrayViewMut<'_, T, D>

Returns the internal array as ArrayViewMut. See also as_array.

Safety

If another reference to the internal data exists(e.g., &[T] or ArrayView), it might cause undefined behavior.

pub fn to_owned_array(&self) -> Array<T, D>

Get a copy of PyArray as ndarray::Array.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let py_array = PyArray::arange(py, 0, 4, 1).reshape([2, 2]).unwrap();
    assert_eq!(
        py_array.to_owned_array(),
        array![[0, 1], [2, 3]]
    )
});

impl<T: Copy + Element> PyArray<T, Ix0>

pub fn item(&self) -> T

Get the element of zero-dimensional PyArray.

See inner for example.

impl<T: Element> PyArray<T, Ix1>

pub fn from_slice<'py>(py: Python<'py>, slice: &[T]) -> &'py Self

Construct one-dimension PyArray from slice.

Example

use numpy::PyArray;
let array = [1, 2, 3, 4, 5];
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_slice(py, &array);
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]);
});

pub fn from_vec<'py>(py: Python<'py>, vec: Vec<T>) -> &'py Self

Construct one-dimension PyArray from Vec.

Example

use numpy::PyArray;
let vec = vec![1, 2, 3, 4, 5];
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_vec(py, vec);
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]);
});

pub fn from_exact_iter(
    py: Python<'_>,
    iter: impl ExactSizeIterator<Item = T>
) -> &Self

Construct one-dimension PyArray from a type which implements ExactSizeIterator.

Example

use numpy::PyArray;
use std::collections::BTreeSet;
let vec = vec![1, 2, 3, 4, 5];
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_exact_iter(py, vec.iter().map(|&x| x));
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]);
});

pub fn from_iter(py: Python<'_>, iter: impl IntoIterator<Item = T>) -> &Self

Construct one-dimension PyArray from a type which implements IntoIterator.

If no reliable size_hint is available, this method can allocate memory multiple time, which can hurt performance.

Example

use numpy::PyArray;
let set: std::collections::BTreeSet<u32> = [4, 3, 2, 5, 1].into_iter().cloned().collect();
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_iter(py, set);
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]);
});

pub fn resize(&self, new_elems: usize) -> PyResult<()>

Extends or trancates the length of 1 dimension PyArray.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::arange(py, 0, 10, 1);
    assert_eq!(pyarray.len(), 10);
    pyarray.resize(100).unwrap();
    assert_eq!(pyarray.len(), 100);
});

pub fn iter<'py>(&'py self) -> PyResult<NpySingleIter<'py, T, ReadWrite>>

Iterates all elements of this array. See NpySingleIter for more.

impl<T: Element> PyArray<T, Ix2>

pub fn from_vec2<'py>(
    py: Python<'py>,
    v: &[Vec<T>]
) -> Result<&'py Self, FromVecError>

Construct a two-dimension PyArray from Vec<Vec<T>>.

This function checks all dimension of inner vec, and if there’s any vec where its dimension differs from others, it returns ArrayCastError.

Example

use numpy::PyArray;
let vec2 = vec![vec![1, 2, 3]; 2];
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_vec2(py, &vec2).unwrap();
    assert_eq!(pyarray.readonly().as_array(), array![[1, 2, 3], [1, 2, 3]]);
    assert!(PyArray::from_vec2(py, &[vec![1], vec![2, 3]]).is_err());
});

impl<T: Element> PyArray<T, Ix3>

pub fn from_vec3<'py>(
    py: Python<'py>,
    v: &[Vec<Vec<T>>]
) -> Result<&'py Self, FromVecError>

Construct a three-dimension PyArray from Vec<Vec<Vec<T>>>.

This function checks all dimension of inner vec, and if there’s any vec where its dimension differs from others, it returns error.

Example

use numpy::PyArray;
let vec3 = vec![vec![vec![1, 2]; 2]; 2];
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::from_vec3(py, &vec3).unwrap();
    assert_eq!(
        pyarray.readonly().as_array(),
        array![[[1, 2], [1, 2]], [[1, 2], [1, 2]]]
    );
    assert!(PyArray::from_vec3(py, &[vec![vec![1], vec![]]]).is_err());
});

impl<T: Element, D> PyArray<T, D>

pub fn copy_to<U: Element>(&self, other: &PyArray<U, D>) -> PyResult<()>

Copies self into other, performing a data-type conversion if necessary.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray_f = PyArray::arange(py, 2.0, 5.0, 1.0);
    let pyarray_i = PyArray::<i64, _>::new(py, [3], false);
    assert!(pyarray_f.copy_to(pyarray_i).is_ok());
    assert_eq!(pyarray_i.readonly().as_slice().unwrap(), &[2, 3, 4]);
});

pub fn cast<'py, U: Element>(
    &'py self,
    is_fortran: bool
) -> PyResult<&'py PyArray<U, D>>

Cast the PyArray<T> to PyArray<U>, by allocating a new array.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray_f = PyArray::arange(py, 2.0, 5.0, 1.0);
    let pyarray_i = pyarray_f.cast::<i32>(false).unwrap();
    assert!(pyarray_f.copy_to(pyarray_i).is_ok());
    assert_eq!(pyarray_i.readonly().as_slice().unwrap(), &[2, 3, 4]);
});

pub fn reshape<'py, ID, D2>(
    &'py self,
    dims: ID
) -> PyResult<&'py PyArray<T, D2>> where
    ID: IntoDimension<Dim = D2>,
    D2: Dimension, 

Construct a new array which has same values as self, same matrix order, but has different dimensions specified by dims.

Since a returned array can contain a same pointer as self, we highly recommend to drop an old array, if this method returns Ok.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let array = PyArray::from_exact_iter(py, 0..9);
    let array = array.reshape([3, 3]).unwrap();
    assert_eq!(array.readonly().as_array(), array![[0, 1, 2], [3, 4, 5], [6, 7, 8]]);
    assert!(array.reshape([5]).is_err());
});

pub fn reshape_with_order<'py, ID, D2>(
    &'py self,
    dims: ID,
    order: NPY_ORDER
) -> PyResult<&'py PyArray<T, D2>> where
    ID: IntoDimension<Dim = D2>,
    D2: Dimension, 

Same as reshape, but you can change the order of returned matrix.

impl<T: Element + AsPrimitive<f64>> PyArray<T, Ix1>

pub fn arange(py: Python<'_>, start: T, stop: T, step: T) -> &Self

Return evenly spaced values within a given interval. Same as numpy.arange.

See also PyArray_Arange.

Example

use numpy::PyArray;
pyo3::Python::with_gil(|py| {
    let pyarray = PyArray::arange(py, 2.0, 4.0, 0.5);
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[2.0, 2.5, 3.0, 3.5]);
    let pyarray = PyArray::arange(py, -2, 4, 3);
    assert_eq!(pyarray.readonly().as_slice().unwrap(), &[-2, 1]);
});

Methods from Deref<Target = PyAny>

pub fn downcast<T>(&self) -> Result<&T, PyDowncastError<'_>> where
    T: for<'py> PyTryFrom<'py>, 

Convert this PyAny to a concrete Python type.

pub fn hasattr<N>(&self, attr_name: N) -> Result<bool, PyErr> where
    N: ToPyObject, 

Determines whether this object has the given attribute.

This is equivalent to the Python expression hasattr(self, attr_name).

pub fn getattr<N>(&self, attr_name: N) -> Result<&PyAny, PyErr> where
    N: ToPyObject, 

Retrieves an attribute value.

This is equivalent to the Python expression self.attr_name.

pub fn setattr<N, V>(&self, attr_name: N, value: V) -> Result<(), PyErr> where
    V: ToBorrowedObject,
    N: ToBorrowedObject, 

Sets an attribute value.

This is equivalent to the Python expression self.attr_name = value.

pub fn delattr<N>(&self, attr_name: N) -> Result<(), PyErr> where
    N: ToPyObject, 

Deletes an attribute.

This is equivalent to the Python expression del self.attr_name.

pub fn compare<O>(&self, other: O) -> Result<Ordering, PyErr> where
    O: ToPyObject, 

Compares two Python objects.

This is equivalent to:

if self == other:
    return Equal
elif a < b:
    return Less
elif a > b:
    return Greater
else:
    raise TypeError("PyAny::compare(): All comparisons returned false")

pub fn rich_compare<O>(
    &self,
    other: O,
    compare_op: CompareOp
) -> Result<&PyAny, PyErr> where
    O: ToPyObject, 

Compares two Python objects.

Depending on the value of compare_op, this is equivalent to one of the following Python expressions:

• CompareOp::Eq: self == other
• CompareOp::Ne: self != other
• CompareOp::Lt: self < other
• CompareOp::Le: self <= other
• CompareOp::Gt: self > other
• CompareOp::Ge: self >= other

pub fn is_callable(&self) -> bool

Determines whether this object is callable.

pub fn call(
    &self,
    args: impl IntoPy<Py<PyTuple>>,
    kwargs: Option<&PyDict>
) -> Result<&PyAny, PyErr>

Calls the object.

This is equivalent to the Python expression self(*args, **kwargs).

pub fn call0(&self) -> Result<&PyAny, PyErr>

Calls the object without arguments.

This is equivalent to the Python expression self().

pub fn call1(&self, args: impl IntoPy<Py<PyTuple>>) -> Result<&PyAny, PyErr>

Calls the object with only positional arguments.

This is equivalent to the Python expression self(*args).

pub fn call_method(
    &self,
    name: &str,
    args: impl IntoPy<Py<PyTuple>>,
    kwargs: Option<&PyDict>
) -> Result<&PyAny, PyErr>

Calls a method on the object.

This is equivalent to the Python expression self.name(*args, **kwargs).

Example

use pyo3::types::IntoPyDict;

let gil = Python::acquire_gil();
let py = gil.python();
let list = vec![3, 6, 5, 4, 7].to_object(py);
let dict = vec![("reverse", true)].into_py_dict(py);
list.call_method(py, "sort", (), Some(dict)).unwrap();
assert_eq!(list.extract::<Vec<i32>>(py).unwrap(), vec![7, 6, 5, 4, 3]);

let new_element = 1.to_object(py);
list.call_method(py, "append", (new_element,), None).unwrap();
assert_eq!(list.extract::<Vec<i32>>(py).unwrap(), vec![7, 6, 5, 4, 3, 1]);

pub fn call_method0(&self, name: &str) -> Result<&PyAny, PyErr>

Calls a method on the object without arguments.

This is equivalent to the Python expression self.name().

pub fn call_method1(
    &self,
    name: &str,
    args: impl IntoPy<Py<PyTuple>>
) -> Result<&PyAny, PyErr>

Calls a method on the object with only positional arguments.

This is equivalent to the Python expression self.name(*args).

pub fn is_true(&self) -> Result<bool, PyErr>

Returns whether the object is considered to be true.

This is equivalent to the Python expression bool(self).

pub fn is_none(&self) -> bool

Returns whether the object is considered to be None.

This is equivalent to the Python expression self is None.

pub fn is_empty(&self) -> Result<bool, PyErr>

Returns true if the sequence or mapping has a length of 0.

This is equivalent to the Python expression len(self) == 0.

pub fn get_item<K>(&self, key: K) -> Result<&PyAny, PyErr> where
    K: ToBorrowedObject, 

Gets an item from the collection.

This is equivalent to the Python expression self[key].

pub fn set_item<K, V>(&self, key: K, value: V) -> Result<(), PyErr> where
    K: ToBorrowedObject,
    V: ToBorrowedObject, 

Sets a collection item value.

This is equivalent to the Python expression self[key] = value.

pub fn del_item<K>(&self, key: K) -> Result<(), PyErr> where
    K: ToBorrowedObject, 

Deletes an item from the collection.

This is equivalent to the Python expression del self[key].

pub fn iter(&self) -> Result<&PyIterator, PyErr>

Takes an object and returns an iterator for it.

This is typically a new iterator but if the argument is an iterator, this returns itself.

pub fn get_type(&self) -> &PyType

Returns the Python type object for this object’s type.

pub fn get_type_ptr(&self) -> *mut PyTypeObject

Returns the Python type pointer for this object.

pub fn cast_as<'a, D>(&'a self) -> Result<&'a D, PyDowncastError<'a>> where
    D: PyTryFrom<'a>, 

Casts the PyObject to a concrete Python object type.

This can cast only to native Python types, not types implemented in Rust.

pub fn extract<'a, D>(&'a self) -> Result<D, PyErr> where
    D: FromPyObject<'a>, 

Extracts some type from the Python object.

This is a wrapper function around FromPyObject::extract().

pub fn get_refcnt(&self) -> isize

Returns the reference count for the Python object.

pub fn repr(&self) -> Result<&PyString, PyErr>

Computes the “repr” representation of self.

This is equivalent to the Python expression repr(self).

pub fn str(&self) -> Result<&PyString, PyErr>

Computes the “str” representation of self.

This is equivalent to the Python expression str(self).

pub fn hash(&self) -> Result<isize, PyErr>

Retrieves the hash code of self.

This is equivalent to the Python expression hash(self).

pub fn len(&self) -> Result<usize, PyErr>

Returns the length of the sequence or mapping.

This is equivalent to the Python expression len(self).

pub fn dir(&self) -> &PyList

Returns the list of attributes of this object.

This is equivalent to the Python expression dir(self).

pub fn is_instance<T>(&self) -> Result<bool, PyErr> where
    T: PyTypeObject, 

Checks whether this object is an instance of type T.

This is equivalent to the Python expression isinstance(self, T).

Trait Implementations

impl<T, D> AsPyPointer for PyArray<T, D>

fn as_ptr(&self) -> *mut PyObject

Gets the underlying FFI pointer, returns a borrowed pointer.

impl<T, D> AsRef<PyAny> for PyArray<T, D>

fn as_ref(&self) -> &PyAny

Performs the conversion.

impl<'py, T, D> AsRef<PyArray<T, D>> for PyReadonlyArray<'py, T, D>

fn as_ref(&self) -> &PyArray<T, D>

Performs the conversion.

impl<T, D> Debug for PyArray<T, D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<T, D> Deref for PyArray<T, D>

type Target = PyAny

The resulting type after dereferencing.

fn deref(&self) -> &PyAny

Dereferences the value.

impl<T, D> Display for PyArray<T, D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<'a, T, D> From<&'a PyArray<T, D>> for &'a PyAny

fn from(ob: &'a PyArray<T, D>) -> Self

Performs the conversion.

impl<'py, T, D> From<&'py PyArray<T, D>> for PyReadonlyArray<'py, T, D>

fn from(array: &'py PyArray<T, D>) -> PyReadonlyArray<'py, T, D>

Performs the conversion.

impl<'a, T: Element, D: Dimension> FromPyObject<'a> for &'a PyArray<T, D>

fn extract(ob: &'a PyAny) -> PyResult<Self>

Extracts Self from the source PyObject.

impl<T, D> IntoPy<Py<PyAny>> for PyArray<T, D>

fn into_py(self, py: Python<'_>) -> PyObject

Performs the conversion.

impl<T, D> IntoPy<Py<PyArray<T, D>>> for &PyArray<T, D>

fn into_py(self, py: Python<'_>) -> Py<PyArray<T, D>>

Performs the conversion.

impl<T, D> PartialEq<PyArray<T, D>> for PyArray<T, D>

fn eq(&self, o: &PyArray<T, D>) -> bool

This method tests for self and other values to be equal, and is used by ==.

#[must_use]

fn ne(&self, other: &Rhs) -> bool

This method tests for !=.

impl<T, D> PyLayout<PyArray<T, D>> for PyArrayObject

const IS_NATIVE_TYPE: bool

fn get_super(&mut self) -> Option<&mut <T as PyTypeInfo>::BaseLayout>

fn py_init(&mut self, _value: T)

unsafe fn py_drop(&mut self, _py: Python<'_>)

impl<T, D> PyNativeType for PyArray<T, D>

fn py(&self) -> Python<'_>

unsafe fn unchecked_downcast(obj: &PyAny) -> &Self

Cast &PyAny to &Self without no type checking.

impl<T, D> PyTypeInfo for PyArray<T, D>

type Type = ()

Type of objects to store in PyObject struct

type BaseType = PyAny

Base class

type Layout = PyArrayObject

Layout

type BaseLayout = PyObject

Layout of Basetype.

type Initializer = PyNativeTypeInitializer<Self>

Initializer for layout

type AsRefTarget = Self

Utility type to make Py::as_ref work

const NAME: &'static str

Class name

const MODULE: Option<&'static str>

Module name, if any

fn type_object_raw(_py: Python<'_>) -> *mut PyTypeObject

PyTypeObject instance for this type.

fn is_type_of(ptr: &PyAny) -> bool

Checks if object is an instance of this type or a subclass of this type.

const DESCRIPTION: &'static str

Class doc string

const FLAGS: usize

Type flags (ie PY_TYPE_FLAG_GC, PY_TYPE_FLAG_WEAKREF)

fn is_exact_type_of(object: &PyAny) -> bool

Checks if object is an instance of this type.

impl<T, D> ToPyObject for PyArray<T, D>

fn to_object(&self, py: Python<'_>) -> PyObject

Converts self into a Python object.

impl<T, D> PySizedLayout<PyArray<T, D>> for PyArrayObject