Function unpack_indices

numpy/core/src/multiarray/mapping.c:223–252

* Turn an index argument into a c-array of `PyObject *`s, one for each index. * * When a tuple is passed, the tuple elements are unpacked into the buffer. * Anything else is handled by unpack_scalar(). * * @param index The index object, which may or may not be a tuple. This is * a borrowed reference. * @param result An empty buffer of PyObject* to write each index

 *                   dispose of them.
 */
NPY_NO_EXPORT npy_intp
unpack_indices(PyObject *index, PyObject **result, npy_intp result_n)
{
    /* It is likely that the logic here can be simplified. See the discussion
     * on https://github.com/numpy/numpy/pull/21029
     */

    /* Fast route for passing a tuple */
    if (PyTuple_CheckExact(index)) {
        return unpack_tuple((PyTupleObject *)index, result, result_n);
    }

    /*
     * Passing a tuple subclass - coerce to the base type. This incurs an
     * allocation, but doesn't need to be a fast path anyway. Note that by
     * calling `PySequence_Tuple`, we ensure that the subclass `__iter__` is
     * called.
     */
    if (PyTuple_Check(index)) {
        PyTupleObject *tup = (PyTupleObject *) PySequence_Tuple(index);
        if (tup == NULL) {
            return -1;
        }
        npy_intp n = unpack_tuple(tup, result, result_n);
        Py_DECREF(tup);
        return n;
    }

    return unpack_scalar(index, result, result_n);
}

/**
 * Prepare an npy_index_object from the python slicing object.