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.
Build and test
Native Cargo tests link libpython so their executable can initialize an interpreter. Maturin selects the existing pyo3/extension-module dependency feature from pyproject.toml when building a wheel, preserving extension linkage. Select the interpreter with PYO3_PYTHON when the default is not the intended Python installation.
From the repository root, run native tests with NumPy and SciPy installed in the selected interpreter, then build and install a wheel before running the parity suite:
cargo nextest run --locked --workspace
maturin build --locked --release --manifest-path crates/leto-python/Cargo.toml
python -m pip install --no-deps target/wheels/leto_python-*.whl
python -c "import leto_python, scipy.linalg"
python -m pytest crates/leto-python/tests/test_numpy_parity.py
The explicit imports make a missing or unloadable wheel fail before pytest's optional-import guards. The existing release interpreter/platform matrix stays unchanged; a local build validates only its actual interpreter and target. The package-scoped release profile retains extension symbols to avoid Rust/LLVM's Mach-O stripping defect. Release optimization and the CPython wheel ABI are unchanged; the default macOS toolchain must build an importable wheel without linker overrides. Every release-matrix row also executes nine NumPy-only value, dtype and error contracts. The closed-form fixtures cover both float32 and float64 without a SciPy dependency on musl; the full 29-case NumPy/SciPy suite runs in native CI. Fork and Dependabot pull requests keep the same build and value-validation gates. Artifact attestation runs in trusted contexts with its existing write permissions; unprivileged verification does not require those credentials.
Links
Licence
MIT or Apache-2.0, at your option.
Metadata
Release files for leto-python 0.46.1
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-0.46.1.tar.gz | 794.5 kB | Details |
Built distributions (wheels)
Total release size: 36.7 MB
Release files / leto_python-0.46.1.tar.gz
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