I am completely new to Numpy and I know only the basics of Python, to this point I was using Fortran 03/08 to write numerical code. However, I am starting a new large project of mine and I am looking forward to using Python to call some low level Fortran code responsible for most of the intensive number crunching. In this context I stumbled into f2py and it looks just like what I need, but before I start writing an app in mixture of Python and Fortran I have a question about numerical precision of variables used in numpy and f2py. Is there any way to interact with Fortran's real(16) (supported by gcc and Intel's ifort) data type from numpy? By real(16) I mean the binary128 type as in IEEE 754. (In C this data type is experimentally supported as __float128 (gcc) and _Quad (Intel's icc).) I have investigated the float128 data type, but it seems to work as binary64 or binary80 depending on the architecture. If there is currently no way to interact with binary128, how hard would it be to patch the sources of numpy to add such data type? I am interested only in basic stuff, comparable in functionality to libmath. As said before, I have little knowledge of Python, Numpy and f2py, I am however, interested in investing some time in learing it and implementing the mentioned features, but only if there is any hope of succeeding.