i agree, also add to that, that many python modules are foss projects that are maintained on a limited basis or budget. Refactoring code that may have some unsafe async routines would be costly for an org, and dreadful for recreation. So you can either have a rich library of modules, or go async and risk something you need not working then having to find a workaround. Personally, if parallelism is important enough, i use ctypes and openmp. If i need something more portable, i have a few multiprocessing wrappers that implement prange and a few other widgets for shared memory.