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PyO3-based Rust bindings of the NumPy C-API
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PyO3/rust-numpy
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Rust bindings for the NumPy C-API.
- Rust >= 1.83.0
- Basically, our MSRV follows the one ofPyO3
- Python >= 3.7
- Python 3.6 support was dropped from 0.16
- Some Rust libraries
- ndarray for Rust-side matrix library
- PyO3 for Python bindings
- And more (seeCargo.toml)
- numpy installed in your Python environments (e.g., via
pip install numpy)- We recommend
numpy >= 1.16.0, though older versions may work
- We recommend
Please see thesimple example for how to get started.
There are also examples usingndarray-linalg andrayon.
[lib]name ="rust_ext"crate-type = ["cdylib"][dependencies]pyo3 = {version ="0.27" }numpy ="0.27"
#[pyo3::pymodule]mod rust_ext{use numpy::ndarray::{ArrayD,ArrayViewD,ArrayViewMutD};use numpy::{IntoPyArray,PyArrayDyn,PyReadonlyArrayDyn,PyArrayMethods};use pyo3::{pyfunction,PyResult,Python,Bound};// example using immutable borrows producing a new arrayfnaxpy(a:f64,x:ArrayViewD<'_,f64>,y:ArrayViewD<'_,f64>) ->ArrayD<f64>{ a*&x +&y}// example using a mutable borrow to modify an array in-placefnmult(a:f64,mutx:ArrayViewMutD<'_,f64>){ x *= a;}// wrapper of `axpy`#[pyfunction(name ="axpy")]fnaxpy_py<'py>(py:Python<'py>,a:f64,x:PyReadonlyArrayDyn<'py,f64>,y:PyReadonlyArrayDyn<'py,f64>,) ->Bound<'py,PyArrayDyn<f64>>{let x = x.as_array();let y = y.as_array();let z =axpy(a, x, y); z.into_pyarray(py)}// wrapper of `mult`#[pyfunction(name ="mult")]fnmult_py<'py>(a:f64,x:&Bound<'py,PyArrayDyn<f64>>){let x =unsafe{ x.as_array_mut()};mult(a, x);}}
[package]name ="numpy-test"[dependencies]pyo3 = {version ="0.27",features = ["auto-initialize"] }numpy ="0.27"
use numpy::{PyArray1,PyArrayMethods};use pyo3::{types::{IntoPyDict,PyAnyMethods},PyResult,Python, ffi::c_str};fnmain() ->PyResult<()>{Python::attach(|py|{let np = py.import("numpy")?;let locals =[("np", np)].into_py_dict(py)?;let pyarray = py.eval(c_str!("np.absolute(np.array([-1, -2, -3], dtype='int32'))"),Some(&locals),None)?.cast_into::<PyArray1<i32>>()?;let readonly = pyarray.readonly();let slice = readonly.as_slice()?;assert_eq!(slice,&[1,2,3]);Ok(())})}
This crate uses types fromndarray in its public API.ndarray is re-exportedin the crate root so that you do not need to specify it as a direct dependency.
Furthermore, this crate is compatible with multiple versions ofndarray and therefore dependson a range of semver-incompatible versions, currently>= 0.15, < 0.17. Cargo does notautomatically choose a single version ofndarray by itself if you depend directly or indirectlyon anything but that exact range. It can therefore be necessary to manually unify these dependencies.
For example, if you specify the following dependencies
numpy ="0.27"ndarray ="0.15"
this will currently depend on both version0.15.6 and0.16.1 ofndarray by defaulteven though0.15.6 is within the range>= 0.15, <= 0.17. To fix this, you can run
cargo update --package ndarray:0.16.1 --precise 0.15.6
to achieve a single dependency on version0.15.6 ofndarray.
We welcomeissuesandpull requests.
PyO3'sContributing.mdis a nice guide for starting.
Also, we have aGitter channel for communicating.
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