leto-python
NumPy-compatible array kernels and dense linear algebra for Python, backed by the Leto Rust array substrate.
Every operation takes and returns ordinary NumPy arrays. The bindings convert
at the boundary, release the GIL around the computation, and raise
ValueError where Leto reports a domain error — so a call is a normal Python
call that happens to run in Rust.
Install
pip install leto-python
Wheels are published for CPython 3.9 through 3.13 on Linux, Windows, and macOS. NumPy is the only runtime requirement.
Use
import numpy as np
import leto_python as leto
a = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
b = np.array([[5.0, 6.0], [7.0, 8.0]], dtype=np.float32)
print(leto.add(a, b)) # elementwise, float32
print(leto.matmul(a, b)) # dense matrix product, float32
print(leto.sum(a)) # 10.0
m = np.array([[4.0, 1.0], [1.0, 3.0]], dtype=np.float64)
print(leto.det(m)) # 11.0
print(leto.inv(m)) # dense inverse, float64
print(leto.cholesky(m)) # lower factor of a symmetric positive definite m
The dtype contract
It is not uniform, and reading it wrongly is the most likely first error:
| Group | Functions | dtype |
|---|---|---|
| Elementwise and matrix product | add, sub, mul, div, matmul, batched_matmul, dot, sum, sum_dyn |
float32 |
| Linear algebra | det, inv, solve, norm, trace, kron, eigenvalues, singular_values |
float64 |
| Decompositions | cholesky, cholesky_solve, cholesky_inv, qr, col_piv_qr, svd, symmetric_eigen, schur, hessenberg, bidiagonalize, full_piv_lu, udu, bunch_kaufman, matexp |
float64 |
Inputs must be C-contiguous. A non-contiguous or wrongly typed array raises rather than being silently copied or reinterpreted.
What this package is
A binding surface and nothing else. It holds no algorithms: the numerics live
in the leto and leto-ops Rust crates, and this package converts types, maps
errors, and gets out of the way. That is deliberate — one implementation, one
place to verify it.
Correctness is checked against NumPy and SciPy on identical inputs. The sign- and order-ambiguous decompositions (QR, Cholesky, eigendecomposition, SVD) are checked by their mathematical invariants — reconstruction, orthonormality, sorted spectra — because a factorization is unique only up to signs and permutations, so raw factor equality would be the wrong oracle.
Links
Licence
MIT or Apache-2.0, at your option.
1 maintainer
Metadata
1 maintainer
Release files for leto-python 0.43.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| leto_python-0.43.1.tar.gz | 722.4 kB | Details |
Built distributions (wheels)
Total release size: 27.6 MB
Release files / leto_python-0.43.1.tar.gz
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