Function validate_spec

numpy/core/src/multiarray/array_method.c:175–232

* Validate that the input is usable to create a new ArrayMethod. * * @param spec * @return 0 on success -1 on error. */

 * @return 0 on success -1 on error.
 */
static int
validate_spec(PyArrayMethod_Spec *spec)
{
    int nargs = spec->nin + spec->nout;
    /* Check the passed spec for invalid fields/values */
    if (spec->nin < 0 || spec->nout < 0 || nargs > NPY_MAXARGS) {
        PyErr_Format(PyExc_ValueError,
                "ArrayMethod inputs and outputs must be greater zero and"
                "not exceed %d. (method: %s)", NPY_MAXARGS, spec->name);
        return -1;
    }
    switch (spec->casting) {
        case NPY_NO_CASTING:
        case NPY_EQUIV_CASTING:
        case NPY_SAFE_CASTING:
        case NPY_SAME_KIND_CASTING:
        case NPY_UNSAFE_CASTING:
            break;
        default:
            if (spec->casting != -1) {
                PyErr_Format(PyExc_TypeError,
                        "ArrayMethod has invalid casting `%d`. (method: %s)",
                        spec->casting, spec->name);
                return -1;
            }
    }

    for (int i = 0; i < nargs; i++) {
        /*
         * Note that we could allow for output dtypes to not be specified
         * (the array-method would have to make sure to support this).
         * We could even allow for some dtypes to be abstract.
         * For now, assume that this is better handled in a promotion step.
         * One problem with providing all DTypes is the definite need to
         * hold references.  We probably, eventually, have to implement
         * traversal and trust the GC to deal with it.
         */
        if (spec->dtypes[i] == NULL) {
            PyErr_Format(PyExc_TypeError,
                    "ArrayMethod must provide all input and output DTypes. "
                    "(method: %s)", spec->name);
            return -1;
        }
        if (!PyObject_TypeCheck(spec->dtypes[i], &PyArrayDTypeMeta_Type)) {
            PyErr_Format(PyExc_TypeError,
                    "ArrayMethod provided object %R is not a DType."
                    "(method: %s)", spec->dtypes[i], spec->name);
            return -1;
        }
        if (NPY_DT_is_abstract(spec->dtypes[i])) {
            PyErr_Format(PyExc_TypeError,
                    "abstract DType %S are currently not supported."
                    "(method: %s)", spec->dtypes[i], spec->name);
            return -1;
        }
    }
    return 0;
}