numba-lapack
UNSAFE, zero-overhead Numba intrinsics that expose the full BLAS/LAPACK C-APIs
via SciPy’s __pyx_capi__. Call BLAS/LAPACK directly from @njit in nopython mode.
⚠️ Unsafe means unsafe: raw pointer semantics; you are responsible for valid pointers, shapes, and leading dimensions.
Highlights
- Auto-discovers
scipy.linalg.cython_blasandcython_lapacksymbols at import. - Generates Numba
@intrinsicwrappers with the exact ABI (no Python overhead). - Accepts arrays, typed pointers, or by-ref scalars for pointer parameters.
- Ships type stubs so IDEs can see function names & arg docs.
Quick start
import numpy as np
from numba import njit
from numba_lapack import dgemm
@njit(cache=True)
def gemm_nn(A, B, C, alpha, beta):
m, k = A.shape
_, n = B.shape
dgemm(np.uint8(ord('N')), np.uint8(ord('N')),
m, n, k, alpha, A, m, B, k, beta, C, m)
1 maintainer
Metadata
1 maintainer
Release files for numba-lapack 0.1.2
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