numba 0.67.0rc1: guvectorize

Clean-room public code sample — generation instructions

Write a brand-new, minimal, self-contained code sample in this clean-room directory.
Do not copy, paraphrase, or reference any existing project source. Work only from this spec.

A csx.json manifest scaffold already exists. Do not recreate it from memory. Preserve its case.goal, packages and symbols; fill its empty case.contract with exact assertions and correct its environment, commands and verifierAdapter for the files you generate.

Goal: verify numba.guvectorize in pkg:pypi/numba@0.67.0rc1
Kind: HOW

Use EXACTLY these public packages and versions:
  - pkg:pypi/numba@0.67.0rc1
Demonstrate these symbols/APIs:
  - numba.guvectorize
Constraints:
  - executionContext: node
Required runtime conditions:
  - ecosystem: npm
  - language: javascript
  - moduleSystem: cjs
  - packageManager: npm@10.9.8
  - runtime: node@22.23.2

Rules:
  - One focused purpose; the smallest project that proves the goal.
  - Include a contract test (test/contract.*) that runs OFFLINE and exits 0 exactly when the goal behavior works.
  - Pin every dependency with a lockfile so resolution is reproducible.
  - No secrets, credentials, or tokens. No real URLs (only example.com or localhost). No absolute paths.
  - No personal names, emails, company names, or project identifiers of any kind.
  - No binaries and no generated output (node_modules, dist, target, venv, .git, .env).
  - Keep it under 200 files and 256KB packed.

{"case":{"caseId":"case:sha256:98bb5813a13ce793eed9cb59b23fc4cbd7f1f0a6a5c38ab2e3ae5826954f97aa","contract":["assert guvectorize with explicit signatures performs 1D vector addition and broadcasts across 2D arrays","assert guvectorize with reduction layout computes sum reduction over 1D and 2D arrays","assert guvectorize with matrix-vector signature computes matrix-vector products","assert guvectorize dynamically compiles layout function with explicit output buffer argument","assert guvectorize with explicit signatures raises TypeError when called with incompatible argument types"],"goal":"verify numba.guvectorize in pkg:pypi/numba@0.67.0rc1","kind":"HOW","packages":["pkg:pypi/numba@0.67.0rc1"],"schemaVersion":1,"symbols":["numba.guvectorize"]},"contractCommand":["python","test/contract.py"],"environment":{"arch":"x64","distro":"ubuntu","ecosystem":"pypi","libc":"glibc","libcVersion":"2.39","os":"linux","osVersionBucket":"24","packageManager":"pip","schemaVersion":1},"license":"MIT-0","packages":["pkg:pypi/numba@0.67.0rc1"],"schemaVersion":1,"subject":"pkg:pypi/numba@0.67.0rc1","symbols":["numba.guvectorize"],"verifierAdapter":"python@1"}

[project]
name = "verify-numba-guvectorize"
version = "0.1.0"
dependencies = [
    "llvmlite==0.49.0",
    "numba==0.67.0rc1",
    "numpy==2.5.2",
]

--pre
llvmlite==0.49.0
numba==0.67.0rc1
numpy==2.5.2

{
  "schemaVersion": 1,
  "goal": "verify numba.guvectorize in pkg:pypi/numba@0.67.0rc1",
  "kind": "HOW",
  "packages": [
    "pkg:pypi/numba@0.67.0rc1"
  ],
  "symbols": [
    "numba.guvectorize"
  ],
  "constraints": {
    "executionContext": "node"
  },
  "runtimeConditions": {
    "ecosystem": "npm",
    "language": "javascript",
    "moduleSystem": "cjs",
    "packageManager": "npm@10.9.8",
    "runtime": "node@22.23.2"
  }
}

import numpy as np
import numba
from numba import guvectorize, int64, float64


def test_guvectorize_explicit_signatures():
    @guvectorize([(int64[:], int64[:], int64[:]), (float64[:], float64[:], float64[:])], '(n),(n)->(n)')
    def gu_add(a, b, out):
        for i in range(a.shape[0]):
            out[i] = a[i] + b[i]

    # 1D vector addition
    a = np.array([1, 2, 3], dtype=np.int64)
    b = np.array([4, 5, 6], dtype=np.int64)
    res = gu_add(a, b)
    assert isinstance(res, np.ndarray)
    assert np.array_equal(res, np.array([5, 7, 9], dtype=np.int64))

    # Broadcasting over 2D array
    a_2d = np.array([[1, 2], [3, 4]], dtype=np.int64)
    b_2d = np.array([[10, 20], [30, 40]], dtype=np.int64)
    res_2d = gu_add(a_2d, b_2d)
    assert res_2d.shape == (2, 2)
    assert np.array_equal(res_2d, np.array([[11, 22], [33, 44]], dtype=np.int64))


def test_guvectorize_reduction_layout():
    @guvectorize([(float64[:], float64[:])], '(n)->()')
    def gu_sum(a, out):
        s = 0.0
        for i in range(a.shape[0]):
            s += a[i]
        out[0] = s

    # 1D array reduction to scalar
    arr_1d = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float64)
    res_1d = gu_sum(arr_1d)
    assert np.isclose(res_1d, 10.0)

    # 2D array reduction along axis
    arr_2d = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.float64)
    res_2d = gu_sum(arr_2d)
    assert res_2d.shape == (3,)
    assert np.allclose(res_2d, np.array([3.0, 7.0, 11.0]))


def test_guvectorize_matrix_vector():
    @guvectorize([(float64[:,:], float64[:], float64[:])], '(m,n),(n)->(m)')
    def gu_matvec(A, x, out):
        for i in range(A.shape[0]):
            s = 0.0
            for j in range(A.shape[1]):
                s += A[i, j] * x[j]
            out[i] = s

    mat = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
    vec = np.array([5.0, 6.0], dtype=np.float64)
    res = gu_matvec(mat, vec)
    assert res.shape == (2,)
    assert np.allclose(res, np.array([17.0, 39.0]))


def test_guvectorize_dynamic_compilation():
    @guvectorize('(n)->()')
    def gu_mean(a, out):
        s = 0.0
        for i in range(a.shape[0]):
            s += a[i]
        out[0] = s / a.shape[0]

    arr = np.array([1.0, 2.0, 3.0, 4.0, 5.0], dtype=np.float64)
    out_scalar = np.zeros(())
    gu_mean(arr, out_scalar)
    assert np.isclose(out_scalar, 3.0)


def test_guvectorize_type_error():
    @guvectorize([(int64[:], int64[:], int64[:])], '(n),(n)->(n)')
    def gu_int_add(a, b, out):
        for i in range(a.shape[0]):
            out[i] = a[i] + b[i]

    try:
        gu_int_add("invalid", "string")
        assert False, "Should have raised TypeError"
    except TypeError as e:
        assert isinstance(e, TypeError)


def main():
    test_guvectorize_explicit_signatures()
    test_guvectorize_reduction_layout()
    test_guvectorize_matrix_vector()
    test_guvectorize_dynamic_compilation()
    test_guvectorize_type_error()
    print("All guvectorize contract assertions passed.")


if __name__ == "__main__":
    main()