def METHOD_NAME(
    deep_diff_obj, tsv_file_name, old_view, new_view, cosine_obj, incl_descrs=False
):
    lod = []
    if "values_changed" in deep_diff_obj:
        vc = deep_diff_obj["values_changed"]
        for current_vc in vc:
            current_path = current_vc.path(output_format="list")
            if (
                len(current_path) == 3
                and current_path[0] == "slots"
                and (current_path[2] != "description" or incl_descrs)
            ):
                to_append = {
                    "slot": current_path[1],
                    "attribute": current_path[2],
                }
                if current_path[2] == "description":
                    p0 = cosine_obj.get_profile(current_vc.t1)
                    p1 = cosine_obj.get_profile(current_vc.t2)
                    cos_dist_res = cosine_obj.similarity_profiles(p0, p1)
                    to_append["descr_dist"] = 1 - cos_dist_res
                    to_append["old_desc"] = current_vc.t1
                    to_append["new_desc"] = current_vc.t2
                else:
                    to_append["old_val"] = current_vc.t1
                    to_append["new_val"] = current_vc.t2
                # if current_path[2] == "range":
                #     old_element = old_view.get_element(current_vc.t1)
                #     to_append["old_range_type"] = type(old_element).class_name
                #     new_element = new_view.get_element(current_vc.t2)
                #     to_append["new_range_type"] = type(new_element).class_name
                lod.append(to_append)
        df = pd.DataFrame(lod)
        df.to_csv(tsv_file_name, sep="\t", index=False)