numpy/
dtype.rs

1use std::ffi::{c_int, c_long, c_longlong, c_short, c_uint, c_ulong, c_ulonglong, c_ushort};
2use std::mem::size_of;
3use std::ptr;
4
5#[cfg(feature = "half")]
6use half::{bf16, f16};
7use num_traits::{Bounded, Zero};
8#[cfg(feature = "half")]
9use pyo3::sync::PyOnceLock;
10use pyo3::{
11    conversion::IntoPyObject,
12    exceptions::{PyIndexError, PyValueError},
13    ffi::{self, PyTuple_Size},
14    pyobject_native_type_named,
15    types::{PyAnyMethods, PyDict, PyDictMethods, PyTuple, PyType},
16    Borrowed, Bound, Py, PyAny, PyResult, PyTypeInfo, Python,
17};
18
19use crate::npyffi::{
20    self, _PyDataType_GET_ITEM_DATA, NpyTypes, PyArray_Descr, PyDataType_ALIGNMENT,
21    PyDataType_ELSIZE, PyDataType_FIELDS, PyDataType_FLAGS, PyDataType_NAMES, PyDataType_SUBARRAY,
22    NPY_ALIGNED_STRUCT, NPY_BYTEORDER_CHAR, NPY_ITEM_HASOBJECT, NPY_TYPES, PY_ARRAY_API,
23};
24
25pub use num_complex::{Complex32, Complex64};
26
27/// Binding of [`numpy.dtype`][dtype].
28///
29/// # Example
30///
31/// ```
32/// use numpy::{dtype, get_array_module, PyArrayDescr, PyArrayDescrMethods};
33/// use numpy::pyo3::{types::{IntoPyDict, PyAnyMethods}, Python};
34///
35/// # fn main() -> pyo3::PyResult<()> {
36/// Python::attach(|py| {
37///     let locals = [("np", get_array_module(py)?)].into_py_dict(py)?;
38///
39///     let dt = py
40///         .eval(c"np.array([1, 2, 3.0]).dtype", Some(&locals), None)?
41///         .cast_into::<PyArrayDescr>()?;
42///
43///     assert!(dt.is_equiv_to(&dtype::<f64>(py)));
44/// #   Ok(())
45/// })
46/// # }
47/// ```
48///
49/// [dtype]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.html
50#[repr(transparent)]
51pub struct PyArrayDescr(PyAny);
52
53pyobject_native_type_named!(PyArrayDescr);
54
55unsafe impl PyTypeInfo for PyArrayDescr {
56    const NAME: &'static str = "PyArrayDescr";
57    const MODULE: Option<&'static str> = Some("numpy");
58
59    #[inline]
60    fn type_object_raw<'py>(py: Python<'py>) -> *mut ffi::PyTypeObject {
61        unsafe { npyffi::get_type_object(py, NpyTypes::PyArrayDescr_Type) }
62    }
63}
64
65/// Returns the type descriptor ("dtype") for a registered type.
66#[inline]
67pub fn dtype<'py, T: Element>(py: Python<'py>) -> Bound<'py, PyArrayDescr> {
68    T::get_dtype(py)
69}
70
71impl PyArrayDescr {
72    /// Creates a new type descriptor ("dtype") object from an arbitrary object.
73    ///
74    /// Equivalent to invoking the constructor of [`numpy.dtype`][dtype].
75    ///
76    /// [dtype]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.html
77    #[inline]
78    pub fn new<'a, 'py, T>(py: Python<'py>, ob: T) -> PyResult<Bound<'py, Self>>
79    where
80        T: IntoPyObject<'py>,
81    {
82        fn inner<'py>(
83            py: Python<'py>,
84            obj: Borrowed<'_, 'py, PyAny>,
85        ) -> PyResult<Bound<'py, PyArrayDescr>> {
86            let mut descr: *mut PyArray_Descr = ptr::null_mut();
87            unsafe {
88                // None is an invalid input here and is not converted to NPY_DEFAULT_TYPE
89                PY_ARRAY_API.PyArray_DescrConverter2(py, obj.as_ptr(), &mut descr);
90                Bound::from_owned_ptr_or_err(py, descr.cast()).map(|any| any.cast_into_unchecked())
91            }
92        }
93
94        inner(
95            py,
96            ob.into_pyobject(py)
97                .map_err(Into::into)?
98                .into_any()
99                .as_borrowed(),
100        )
101    }
102
103    /// Shortcut for creating a type descriptor of `object` type.
104    #[inline]
105    pub fn object(py: Python<'_>) -> Bound<'_, Self> {
106        Self::from_npy_type(py, NPY_TYPES::NPY_OBJECT)
107    }
108
109    /// Returns the type descriptor for a registered type.
110    #[inline]
111    pub fn of<'py, T: Element>(py: Python<'py>) -> Bound<'py, Self> {
112        T::get_dtype(py)
113    }
114
115    fn from_npy_type<'py>(py: Python<'py>, npy_type: NPY_TYPES) -> Bound<'py, Self> {
116        unsafe {
117            let descr = PY_ARRAY_API.PyArray_DescrFromType(py, npy_type as _);
118            Bound::from_owned_ptr(py, descr.cast()).cast_into_unchecked()
119        }
120    }
121
122    pub(crate) fn new_from_npy_type<'py>(py: Python<'py>, npy_type: NPY_TYPES) -> Bound<'py, Self> {
123        unsafe {
124            let descr = PY_ARRAY_API.PyArray_DescrNewFromType(py, npy_type as _);
125            Bound::from_owned_ptr(py, descr.cast()).cast_into_unchecked()
126        }
127    }
128}
129
130/// Implementation of functionality for [`PyArrayDescr`].
131#[doc(alias = "PyArrayDescr")]
132pub trait PyArrayDescrMethods<'py>: Sealed {
133    /// Returns `self` as `*mut PyArray_Descr`.
134    fn as_dtype_ptr(&self) -> *mut PyArray_Descr;
135
136    /// Returns `self` as `*mut PyArray_Descr` while increasing the reference count.
137    ///
138    /// Useful in cases where the descriptor is stolen by the API.
139    fn into_dtype_ptr(self) -> *mut PyArray_Descr;
140
141    /// Returns true if two type descriptors are equivalent.
142    fn is_equiv_to(&self, other: &Self) -> bool;
143
144    /// Returns the [array scalar][arrays-scalars] corresponding to this type descriptor.
145    ///
146    /// Equivalent to [`numpy.dtype.type`][dtype-type].
147    ///
148    /// [arrays-scalars]: https://numpy.org/doc/stable/reference/arrays.scalars.html
149    /// [dtype-type]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.type.html
150    fn typeobj(&self) -> Bound<'py, PyType>;
151
152    /// Returns a unique number for each of the 21 different built-in
153    /// [enumerated types][enumerated-types].
154    ///
155    /// These are roughly ordered from least-to-most precision.
156    ///
157    /// Equivalent to [`numpy.dtype.num`][dtype-num].
158    ///
159    /// [enumerated-types]: https://numpy.org/doc/stable/reference/c-api/dtype.html#enumerated-types
160    /// [dtype-num]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.num.html
161    fn num(&self) -> c_int {
162        unsafe { &*_PyDataType_GET_ITEM_DATA(self.as_dtype_ptr()) }.type_num
163    }
164
165    /// Returns the element size of this type descriptor.
166    ///
167    /// Equivalent to [`numpy.dtype.itemsize`][dtype-itemsize].
168    ///
169    /// [dtype-itemsize]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.itemsize.html
170    fn itemsize(&self) -> usize;
171
172    /// Returns the required alignment (bytes) of this type descriptor according to the compiler.
173    ///
174    /// Equivalent to [`numpy.dtype.alignment`][dtype-alignment].
175    ///
176    /// [dtype-alignment]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.alignment.html
177    fn alignment(&self) -> usize;
178
179    /// Returns an ASCII character indicating the byte-order of this type descriptor object.
180    ///
181    /// All built-in data-type objects have byteorder either `=` or `|`.
182    ///
183    /// Equivalent to [`numpy.dtype.byteorder`][dtype-byteorder].
184    ///
185    /// [dtype-byteorder]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.byteorder.html
186    fn byteorder(&self) -> u8 {
187        unsafe { &*_PyDataType_GET_ITEM_DATA(self.as_dtype_ptr()) }
188            .byteorder
189            .max(0) as _
190    }
191
192    /// Returns a unique ASCII character for each of the 21 different built-in types.
193    ///
194    /// Note that structured data types are categorized as `V` (void).
195    ///
196    /// Equivalent to [`numpy.dtype.char`][dtype-char].
197    ///
198    /// [dtype-char]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.char.html
199    fn char(&self) -> u8 {
200        unsafe { &*_PyDataType_GET_ITEM_DATA(self.as_dtype_ptr()) }
201            .type_
202            .max(0) as _
203    }
204
205    /// Returns an ASCII character (one of `biufcmMOSUV`) identifying the general kind of data.
206    ///
207    /// Note that structured data types are categorized as `V` (void).
208    ///
209    /// Equivalent to [`numpy.dtype.kind`][dtype-kind].
210    ///
211    /// [dtype-kind]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.kind.html
212    fn kind(&self) -> u8 {
213        unsafe { &*_PyDataType_GET_ITEM_DATA(self.as_dtype_ptr()) }
214            .kind
215            .max(0) as _
216    }
217
218    /// Returns bit-flags describing how this type descriptor is to be interpreted.
219    ///
220    /// Equivalent to [`numpy.dtype.flags`][dtype-flags].
221    ///
222    /// [dtype-flags]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.flags.html
223    fn flags(&self) -> u64;
224
225    /// Returns the number of dimensions if this type descriptor represents a sub-array, and zero otherwise.
226    ///
227    /// Equivalent to [`numpy.dtype.ndim`][dtype-ndim].
228    ///
229    /// [dtype-ndim]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.ndim.html
230    fn ndim(&self) -> usize;
231
232    /// Returns the type descriptor for the base element of subarrays, regardless of their dimension or shape.
233    ///
234    /// If the dtype is not a subarray, returns self.
235    ///
236    /// Equivalent to [`numpy.dtype.base`][dtype-base].
237    ///
238    /// [dtype-base]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.base.html
239    fn base(&self) -> Bound<'py, PyArrayDescr>;
240
241    /// Returns the shape of the sub-array.
242    ///
243    /// If the dtype is not a sub-array, an empty vector is returned.
244    ///
245    /// Equivalent to [`numpy.dtype.shape`][dtype-shape].
246    ///
247    /// [dtype-shape]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.shape.html
248    fn shape(&self) -> Vec<usize>;
249
250    /// Returns true if the type descriptor contains any reference-counted objects in any fields or sub-dtypes.
251    ///
252    /// Equivalent to [`numpy.dtype.hasobject`][dtype-hasobject].
253    ///
254    /// [dtype-hasobject]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.hasobject.html
255    fn has_object(&self) -> bool {
256        self.flags() & NPY_ITEM_HASOBJECT != 0
257    }
258
259    /// Returns true if the type descriptor is a struct which maintains field alignment.
260    ///
261    /// This flag is sticky, so when combining multiple structs together, it is preserved
262    /// and produces new dtypes which are also aligned.
263    ///
264    /// Equivalent to [`numpy.dtype.isalignedstruct`][dtype-isalignedstruct].
265    ///
266    /// [dtype-isalignedstruct]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.isalignedstruct.html
267    fn is_aligned_struct(&self) -> bool {
268        self.flags() & NPY_ALIGNED_STRUCT != 0
269    }
270
271    /// Returns true if the type descriptor is a sub-array.
272    ///
273    /// Equivalent to PyDataType_HASSUBARRAY(self).
274    fn has_subarray(&self) -> bool;
275
276    /// Returns true if the type descriptor is a structured type.
277    ///
278    /// Equivalent to PyDataType_HASFIELDS(self).
279    fn has_fields(&self) -> bool;
280
281    /// Returns true if type descriptor byteorder is native, or `None` if not applicable.
282    fn is_native_byteorder(&self) -> Option<bool> {
283        // based on PyArray_ISNBO(self->byteorder)
284        match self.byteorder() {
285            b'=' => Some(true),
286            b'|' => None,
287            byteorder => Some(byteorder == NPY_BYTEORDER_CHAR::NPY_NATBYTE as u8),
288        }
289    }
290
291    /// Returns an ordered list of field names, or `None` if there are no fields.
292    ///
293    /// The names are ordered according to increasing byte offset.
294    ///
295    /// Equivalent to [`numpy.dtype.names`][dtype-names].
296    ///
297    /// [dtype-names]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.names.html
298    fn names(&self) -> Option<Vec<String>>;
299
300    /// Returns the type descriptor and offset of the field with the given name.
301    ///
302    /// This method will return an error if this type descriptor is not structured,
303    /// or if it does not contain a field with a given name.
304    ///
305    /// The list of all names can be found via [`PyArrayDescrMethods::names`].
306    ///
307    /// Equivalent to retrieving a single item from [`numpy.dtype.fields`][dtype-fields].
308    ///
309    /// [dtype-fields]: https://numpy.org/doc/stable/reference/generated/numpy.dtype.fields.html
310    fn get_field(&self, name: &str) -> PyResult<(Bound<'py, PyArrayDescr>, usize)>;
311}
312
313mod sealed {
314    pub trait Sealed {}
315}
316
317use sealed::Sealed;
318
319impl<'py> PyArrayDescrMethods<'py> for Bound<'py, PyArrayDescr> {
320    fn as_dtype_ptr(&self) -> *mut PyArray_Descr {
321        self.as_ptr() as _
322    }
323
324    fn into_dtype_ptr(self) -> *mut PyArray_Descr {
325        self.into_ptr() as _
326    }
327
328    fn is_equiv_to(&self, other: &Self) -> bool {
329        let self_ptr = self.as_dtype_ptr();
330        let other_ptr = other.as_dtype_ptr();
331
332        unsafe {
333            self_ptr == other_ptr
334                || PY_ARRAY_API.PyArray_EquivTypes(self.py(), self_ptr, other_ptr) != 0
335        }
336    }
337
338    fn typeobj(&self) -> Bound<'py, PyType> {
339        let dtype_type_ptr = unsafe { &*_PyDataType_GET_ITEM_DATA(self.as_dtype_ptr()) }.typeobj;
340        unsafe { PyType::from_borrowed_type_ptr(self.py(), dtype_type_ptr) }
341    }
342
343    fn itemsize(&self) -> usize {
344        unsafe { PyDataType_ELSIZE(self.py(), self.as_dtype_ptr()).max(0) as _ }
345    }
346
347    fn alignment(&self) -> usize {
348        unsafe { PyDataType_ALIGNMENT(self.py(), self.as_dtype_ptr()).max(0) as _ }
349    }
350
351    fn flags(&self) -> u64 {
352        unsafe { PyDataType_FLAGS(self.py(), self.as_dtype_ptr()) as _ }
353    }
354
355    fn ndim(&self) -> usize {
356        let subarray = unsafe { PyDataType_SUBARRAY(self.py(), self.as_dtype_ptr()).as_ref() };
357        match subarray {
358            None => 0,
359            Some(subarray) => unsafe { PyTuple_Size(subarray.shape) }.max(0) as _,
360        }
361    }
362
363    fn base(&self) -> Bound<'py, PyArrayDescr> {
364        let subarray = unsafe { PyDataType_SUBARRAY(self.py(), self.as_dtype_ptr()).as_ref() };
365        match subarray {
366            None => self.clone(),
367            Some(subarray) => unsafe {
368                Bound::from_borrowed_ptr(self.py(), subarray.base.cast()).cast_into_unchecked()
369            },
370        }
371    }
372
373    fn shape(&self) -> Vec<usize> {
374        let subarray = unsafe { PyDataType_SUBARRAY(self.py(), self.as_dtype_ptr()).as_ref() };
375        match subarray {
376            None => Vec::new(),
377            Some(subarray) => {
378                // NumPy guarantees that shape is a tuple of non-negative integers so this should never panic.
379                let shape = unsafe { Borrowed::from_ptr(self.py(), subarray.shape) };
380                shape.extract().unwrap()
381            }
382        }
383    }
384
385    fn has_subarray(&self) -> bool {
386        unsafe { !PyDataType_SUBARRAY(self.py(), self.as_dtype_ptr()).is_null() }
387    }
388
389    fn has_fields(&self) -> bool {
390        unsafe { !PyDataType_NAMES(self.py(), self.as_dtype_ptr()).is_null() }
391    }
392
393    fn names(&self) -> Option<Vec<String>> {
394        if !self.has_fields() {
395            return None;
396        }
397        let names = unsafe {
398            Borrowed::from_ptr(self.py(), PyDataType_NAMES(self.py(), self.as_dtype_ptr()))
399        };
400        names.extract().ok()
401    }
402
403    fn get_field(&self, name: &str) -> PyResult<(Bound<'py, PyArrayDescr>, usize)> {
404        if !self.has_fields() {
405            return Err(PyValueError::new_err(
406                "cannot get field information: type descriptor has no fields",
407            ));
408        }
409        let dict = unsafe {
410            Borrowed::from_ptr(self.py(), PyDataType_FIELDS(self.py(), self.as_dtype_ptr()))
411        };
412        let dict = unsafe { dict.cast_unchecked::<PyDict>() };
413        // NumPy guarantees that fields are tuples of proper size and type, so this should never panic.
414        let tuple = dict
415            .get_item(name)?
416            .ok_or_else(|| PyIndexError::new_err(name.to_owned()))?
417            .cast_into::<PyTuple>()
418            .unwrap();
419        // Note that we cannot just extract the entire tuple since the third element can be a title.
420        let dtype = tuple
421            .get_item(0)
422            .unwrap()
423            .cast_into::<PyArrayDescr>()
424            .unwrap();
425        let offset = tuple.get_item(1).unwrap().extract().unwrap();
426        Ok((dtype, offset))
427    }
428}
429
430impl Sealed for Bound<'_, PyArrayDescr> {}
431
432/// Represents that a type can be an element of `PyArray`.
433///
434/// Currently, only integer/float/complex/object types are supported. The [NumPy documentation][enumerated-types]
435/// list the other built-in types which we are not yet implemented.
436///
437/// Note that NumPy's integer types like `numpy.int_` and `numpy.uint` are based on C's integer hierarchy
438/// which implies that their widths change depending on the platform's [data model][data-models].
439/// For example, `numpy.int_` matches C's `long` which is 32 bits wide on Windows (using the LLP64 data model)
440/// but 64 bits wide on Linux (using the LP64 data model).
441///
442/// In contrast, Rust's [`isize`] and [`usize`] types are defined to have the same width as a pointer
443/// and are therefore always 64 bits wide on 64-bit platforms. If you want to match NumPy's behaviour,
444/// consider using the [`c_long`][std::ffi::c_long] and [`c_ulong`][std::ffi::c_ulong] type aliases.
445///
446/// # Safety
447///
448/// A type `T` that implements this trait should be safe when managed by a NumPy
449/// array, thus implementing this trait is marked unsafe. Data types that don't
450/// contain Python objects (i.e., either the object type itself or record types
451/// containing object-type fields) are assumed to be trivially copyable, which
452/// is reflected in the `IS_COPY` flag. Furthermore, it is assumed that for
453/// the object type the elements are pointers into the Python heap and that the
454/// corresponding `Clone` implementation will never panic as it only increases
455/// the reference count.
456///
457/// # Custom element types
458///
459/// Note that we cannot safely store `Py<T>` where `T: PyClass`, because the type information would be
460/// eliminated in the resulting NumPy array.
461/// In other words, objects are always treated as `Py<PyAny>` (a.k.a. `PyObject`) by Python code,
462/// and only `Py<PyAny>` can be stored in a type safe manner.
463///
464/// You can however create [`Array<Py<T>, D>`][ndarray::Array] and turn that into a NumPy array
465/// safely and efficiently using [`from_owned_object_array`][crate::PyArray::from_owned_object_array].
466///
467/// [enumerated-types]: https://numpy.org/doc/stable/reference/c-api/dtype.html#enumerated-types
468/// [data-models]: https://en.wikipedia.org/wiki/64-bit_computing#64-bit_data_models
469pub unsafe trait Element: Sized + Send + Sync {
470    /// Flag that indicates whether this type is trivially copyable.
471    ///
472    /// It should be set to true for all trivially copyable types (like scalar types
473    /// and record/array types only containing trivially copyable fields and elements).
474    ///
475    /// This flag should *always* be set to `false` for object types or record types
476    /// that contain object-type fields.
477    const IS_COPY: bool;
478
479    /// Returns the associated type descriptor ("dtype") for the given element type.
480    fn get_dtype(py: Python<'_>) -> Bound<'_, PyArrayDescr>;
481
482    /// Create a clone of the value while the GIL is guaranteed to be held.
483    fn clone_ref(&self, py: Python<'_>) -> Self;
484
485    /// Create an owned copy of the slice while the GIL is guaranteed to be held.
486    ///
487    /// Some types may provide implementations of this method that are more efficient
488    /// than simply mapping the `py_clone` method to each element in the slice.
489    #[inline]
490    fn vec_from_slice(py: Python<'_>, slc: &[Self]) -> Vec<Self> {
491        slc.iter().map(|elem| elem.clone_ref(py)).collect()
492    }
493
494    /// Create an owned copy of the array while the GIL is guaranteed to be held.
495    ///
496    /// Some types may provide implementations of this method that are more efficient
497    /// than simply mapping the `py_clone` method to each element in the view.
498    #[inline]
499    fn array_from_view<D>(
500        py: Python<'_>,
501        view: ::ndarray::ArrayView<'_, Self, D>,
502    ) -> ::ndarray::Array<Self, D>
503    where
504        D: ::ndarray::Dimension,
505    {
506        view.map(|elem| elem.clone_ref(py))
507    }
508}
509
510fn npy_int_type_lookup<T, T0, T1, T2>(npy_types: [NPY_TYPES; 3]) -> NPY_TYPES {
511    // `npy_common.h` defines the integer aliases. In order, it checks:
512    // NPY_BITSOF_LONG, NPY_BITSOF_LONGLONG, NPY_BITSOF_INT, NPY_BITSOF_SHORT, NPY_BITSOF_CHAR
513    // and assigns the alias to the first matching size, so we should check in this order.
514    match size_of::<T>() {
515        x if x == size_of::<T0>() => npy_types[0],
516        x if x == size_of::<T1>() => npy_types[1],
517        x if x == size_of::<T2>() => npy_types[2],
518        _ => panic!("Unable to match integer type descriptor: {npy_types:?}"),
519    }
520}
521
522fn npy_int_type<T: Bounded + Zero + Sized + PartialEq>() -> NPY_TYPES {
523    let is_unsigned = T::min_value() == T::zero();
524    let bit_width = 8 * size_of::<T>();
525
526    match (is_unsigned, bit_width) {
527        (false, 8) => NPY_TYPES::NPY_BYTE,
528        (false, 16) => NPY_TYPES::NPY_SHORT,
529        (false, 32) => npy_int_type_lookup::<i32, c_long, c_int, c_short>([
530            NPY_TYPES::NPY_LONG,
531            NPY_TYPES::NPY_INT,
532            NPY_TYPES::NPY_SHORT,
533        ]),
534        (false, 64) => npy_int_type_lookup::<i64, c_long, c_longlong, c_int>([
535            NPY_TYPES::NPY_LONG,
536            NPY_TYPES::NPY_LONGLONG,
537            NPY_TYPES::NPY_INT,
538        ]),
539        (true, 8) => NPY_TYPES::NPY_UBYTE,
540        (true, 16) => NPY_TYPES::NPY_USHORT,
541        (true, 32) => npy_int_type_lookup::<u32, c_ulong, c_uint, c_ushort>([
542            NPY_TYPES::NPY_ULONG,
543            NPY_TYPES::NPY_UINT,
544            NPY_TYPES::NPY_USHORT,
545        ]),
546        (true, 64) => npy_int_type_lookup::<u64, c_ulong, c_ulonglong, c_uint>([
547            NPY_TYPES::NPY_ULONG,
548            NPY_TYPES::NPY_ULONGLONG,
549            NPY_TYPES::NPY_UINT,
550        ]),
551        _ => unreachable!(),
552    }
553}
554
555// Invoke within the `Element` impl for a `Clone` type to provide an efficient
556// implementation of the cloning methods
557macro_rules! clone_methods_impl {
558    ($Self:ty) => {
559        #[inline]
560        fn clone_ref(&self, _py: ::pyo3::Python<'_>) -> $Self {
561            ::std::clone::Clone::clone(self)
562        }
563
564        #[inline]
565        fn vec_from_slice(_py: ::pyo3::Python<'_>, slc: &[$Self]) -> Vec<$Self> {
566            ::std::borrow::ToOwned::to_owned(slc)
567        }
568
569        #[inline]
570        fn array_from_view<D>(
571            _py: ::pyo3::Python<'_>,
572            view: ::ndarray::ArrayView<'_, $Self, D>,
573        ) -> ::ndarray::Array<$Self, D>
574        where
575            D: ::ndarray::Dimension,
576        {
577            ::ndarray::ArrayView::to_owned(&view)
578        }
579    };
580}
581pub(crate) use clone_methods_impl;
582use pyo3::BoundObject;
583
584macro_rules! impl_element_scalar {
585    (@impl: $ty:ty, $npy_type:expr $(,#[$meta:meta])*) => {
586        $(#[$meta])*
587        unsafe impl Element for $ty {
588            const IS_COPY: bool = true;
589
590            fn get_dtype(py: Python<'_>) -> Bound<'_, PyArrayDescr> {
591                PyArrayDescr::from_npy_type(py, $npy_type)
592            }
593
594            clone_methods_impl!($ty);
595        }
596    };
597    ($ty:ty => $npy_type:ident $(,#[$meta:meta])*) => {
598        impl_element_scalar!(@impl: $ty, NPY_TYPES::$npy_type $(,#[$meta])*);
599    };
600    ($($tys:ty),+) => {
601        $(impl_element_scalar!(@impl: $tys, npy_int_type::<$tys>());)+
602    };
603}
604
605impl_element_scalar!(bool => NPY_BOOL);
606
607impl_element_scalar!(i8, i16, i32, i64);
608impl_element_scalar!(u8, u16, u32, u64);
609
610impl_element_scalar!(f32 => NPY_FLOAT);
611impl_element_scalar!(f64 => NPY_DOUBLE);
612
613#[cfg(feature = "half")]
614impl_element_scalar!(f16 => NPY_HALF);
615
616#[cfg(feature = "half")]
617unsafe impl Element for bf16 {
618    const IS_COPY: bool = true;
619
620    fn get_dtype(py: Python<'_>) -> Bound<'_, PyArrayDescr> {
621        static DTYPE: PyOnceLock<Py<PyArrayDescr>> = PyOnceLock::new();
622
623        DTYPE
624            .get_or_init(py, || {
625                PyArrayDescr::new(py, "bfloat16").expect("A package which provides a `bfloat16` data type for NumPy is required to use the `half::bf16` element type.").unbind()
626            })
627            .clone_ref(py)
628            .into_bound(py)
629    }
630
631    clone_methods_impl!(Self);
632}
633
634impl_element_scalar!(Complex32 => NPY_CFLOAT,
635    #[doc = "Complex type with `f32` components which maps to `numpy.csingle` (`numpy.complex64`)."]);
636impl_element_scalar!(Complex64 => NPY_CDOUBLE,
637    #[doc = "Complex type with `f64` components which maps to `numpy.cdouble` (`numpy.complex128`)."]);
638
639#[cfg(any(target_pointer_width = "32", target_pointer_width = "64"))]
640impl_element_scalar!(usize, isize);
641
642unsafe impl Element for Py<PyAny> {
643    const IS_COPY: bool = false;
644
645    fn get_dtype(py: Python<'_>) -> Bound<'_, PyArrayDescr> {
646        PyArrayDescr::object(py)
647    }
648
649    #[inline]
650    fn clone_ref(&self, py: Python<'_>) -> Self {
651        Py::clone_ref(self, py)
652    }
653}
654
655#[cfg(test)]
656mod tests {
657    use super::*;
658
659    use pyo3::types::PyString;
660    use pyo3::{py_run, types::PyTypeMethods};
661
662    use crate::npyffi::{is_numpy_2, NPY_NEEDS_PYAPI};
663
664    #[test]
665    fn test_dtype_new() {
666        Python::attach(|py| {
667            assert!(PyArrayDescr::new(py, "float64")
668                .unwrap()
669                .is(dtype::<f64>(py)));
670
671            let dt = PyArrayDescr::new(py, [("a", "O"), ("b", "?")].as_ref()).unwrap();
672            assert_eq!(dt.names(), Some(vec!["a".to_owned(), "b".to_owned()]));
673            assert!(dt.has_object());
674            assert!(dt.get_field("a").unwrap().0.is(dtype::<Py<PyAny>>(py)));
675            assert!(dt.get_field("b").unwrap().0.is(dtype::<bool>(py)));
676
677            assert!(PyArrayDescr::new(py, 123_usize).is_err());
678        });
679    }
680
681    #[test]
682    fn test_dtype_names() {
683        fn type_name<T: Element>(py: Python<'_>) -> Bound<'_, PyString> {
684            dtype::<T>(py).typeobj().qualname().unwrap()
685        }
686        Python::attach(|py| {
687            if is_numpy_2(py) {
688                assert_eq!(type_name::<bool>(py), "bool");
689            } else {
690                assert_eq!(type_name::<bool>(py), "bool_");
691            }
692
693            assert_eq!(type_name::<i8>(py), "int8");
694            assert_eq!(type_name::<i16>(py), "int16");
695            assert_eq!(type_name::<i32>(py), "int32");
696            assert_eq!(type_name::<i64>(py), "int64");
697            assert_eq!(type_name::<u8>(py), "uint8");
698            assert_eq!(type_name::<u16>(py), "uint16");
699            assert_eq!(type_name::<u32>(py), "uint32");
700            assert_eq!(type_name::<u64>(py), "uint64");
701            assert_eq!(type_name::<f32>(py), "float32");
702            assert_eq!(type_name::<f64>(py), "float64");
703
704            assert_eq!(type_name::<Complex32>(py), "complex64");
705            assert_eq!(type_name::<Complex64>(py), "complex128");
706
707            #[cfg(target_pointer_width = "32")]
708            {
709                assert_eq!(type_name::<usize>(py), "uint32");
710                assert_eq!(type_name::<isize>(py), "int32");
711            }
712
713            #[cfg(target_pointer_width = "64")]
714            {
715                assert_eq!(type_name::<usize>(py), "uint64");
716                assert_eq!(type_name::<isize>(py), "int64");
717            }
718        });
719    }
720
721    #[test]
722    fn test_dtype_methods_scalar() {
723        Python::attach(|py| {
724            let dt = dtype::<f64>(py);
725
726            assert_eq!(dt.num(), NPY_TYPES::NPY_DOUBLE as c_int);
727            assert_eq!(dt.flags(), 0);
728            assert_eq!(dt.typeobj().qualname().unwrap(), "float64");
729            assert_eq!(dt.char(), b'd');
730            assert_eq!(dt.kind(), b'f');
731            assert_eq!(dt.byteorder(), b'=');
732            assert_eq!(dt.is_native_byteorder(), Some(true));
733            assert_eq!(dt.itemsize(), 8);
734            assert_eq!(dt.alignment(), 8);
735            assert!(!dt.has_object());
736            assert!(dt.names().is_none());
737            assert!(!dt.has_fields());
738            assert!(!dt.is_aligned_struct());
739            assert!(!dt.has_subarray());
740            assert!(dt.base().is_equiv_to(&dt));
741            assert_eq!(dt.ndim(), 0);
742            assert_eq!(dt.shape(), Vec::<usize>::new());
743        });
744    }
745
746    #[test]
747    fn test_dtype_methods_subarray() {
748        Python::attach(|py| {
749            let locals = PyDict::new(py);
750            py_run!(
751                py,
752                *locals,
753                "dtype = __import__('numpy').dtype(('f8', (2, 3)))"
754            );
755            let dt = locals
756                .get_item("dtype")
757                .unwrap()
758                .unwrap()
759                .cast_into::<PyArrayDescr>()
760                .unwrap();
761
762            assert_eq!(dt.num(), NPY_TYPES::NPY_VOID as c_int);
763            assert_eq!(dt.flags(), 0);
764            assert_eq!(dt.typeobj().qualname().unwrap(), "void");
765            assert_eq!(dt.char(), b'V');
766            assert_eq!(dt.kind(), b'V');
767            assert_eq!(dt.byteorder(), b'|');
768            assert_eq!(dt.is_native_byteorder(), None);
769            assert_eq!(dt.itemsize(), 48);
770            assert_eq!(dt.alignment(), 8);
771            assert!(!dt.has_object());
772            assert!(dt.names().is_none());
773            assert!(!dt.has_fields());
774            assert!(!dt.is_aligned_struct());
775            assert!(dt.has_subarray());
776            assert_eq!(dt.ndim(), 2);
777            assert_eq!(dt.shape(), vec![2, 3]);
778            assert!(dt.base().is_equiv_to(&dtype::<f64>(py)));
779        });
780    }
781
782    #[test]
783    fn test_dtype_methods_record() {
784        Python::attach(|py| {
785            let locals = PyDict::new(py);
786            py_run!(
787                py,
788                *locals,
789                "dtype = __import__('numpy').dtype([('x', 'u1'), ('y', 'f8'), ('z', 'O')], align=True)"
790            );
791            let dt = locals
792                .get_item("dtype")
793                .unwrap()
794                .unwrap()
795                .cast_into::<PyArrayDescr>()
796                .unwrap();
797
798            assert_eq!(dt.num(), NPY_TYPES::NPY_VOID as c_int);
799            assert_ne!(dt.flags() & NPY_ITEM_HASOBJECT, 0);
800            assert_ne!(dt.flags() & NPY_NEEDS_PYAPI, 0);
801            assert_ne!(dt.flags() & NPY_ALIGNED_STRUCT, 0);
802            assert_eq!(dt.typeobj().qualname().unwrap(), "void");
803            assert_eq!(dt.char(), b'V');
804            assert_eq!(dt.kind(), b'V');
805            assert_eq!(dt.byteorder(), b'|');
806            assert_eq!(dt.is_native_byteorder(), None);
807            assert_eq!(dt.itemsize(), 24);
808            assert_eq!(dt.alignment(), 8);
809            assert!(dt.has_object());
810            assert_eq!(
811                dt.names(),
812                Some(vec!["x".to_owned(), "y".to_owned(), "z".to_owned()])
813            );
814            assert!(dt.has_fields());
815            assert!(dt.is_aligned_struct());
816            assert!(!dt.has_subarray());
817            assert_eq!(dt.ndim(), 0);
818            assert_eq!(dt.shape(), Vec::<usize>::new());
819            assert!(dt.base().is_equiv_to(&dt));
820            let x = dt.get_field("x").unwrap();
821            assert!(x.0.is_equiv_to(&dtype::<u8>(py)));
822            assert_eq!(x.1, 0);
823            let y = dt.get_field("y").unwrap();
824            assert!(y.0.is_equiv_to(&dtype::<f64>(py)));
825            assert_eq!(y.1, 8);
826            let z = dt.get_field("z").unwrap();
827            assert!(z.0.is_equiv_to(&dtype::<Py<PyAny>>(py)));
828            assert_eq!(z.1, 16);
829        });
830    }
831}
numpy/dtype.rs

numpy/
dtype.rs
