Hi, (if you are not interested in numpy developement, you can stop now :) ). Following the discussion a few days ago on using scons to build extensions in numpy, I have reached a somewhat usable milestone, in the numpy.scons branch of numpy, and would like to hear some comments, remarks, critics, etc...: Where to get/see: ----------------- svn repository : http://svn.scipy.org/svn/numpy/branches/numpy.scons looking at the code: http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons Examples: --------- To see how it feels from the package developer point of view, I have put three really simple examples: - Building a python extension: http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons/numpy/sco... - Building a ctypes-based package: http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons/numpy/sco... - An example on how to check for libraries and symbols in them: http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons/numpy/sco... For the numpy user, this should be totally transparent (no difference when building/installing). What: ----- This first milestone implements the following: - adding a scons command to numpy.distutils - adding an add_sconscript function to numpy.distutils setup, for packages willing to use scons - two builders: one for ctypes extension, and one for python extension - a basic implementation to check for libraries (the paths can be overwritten exactly like with distutils, using site.cfg; I have not yet implemented overwriting with environment variables). I have been testing this on the following platforms: - linux with gcc - linux with icc - linux with suncc - windows with MS toolikit 2003 - solaris studio express with suncc - mac os X (tiger, x86) And now ? --------- As discussed previously, I think numpy would benefit from exclusively using scons to build compiled extensions. I have started working on fortran support for scons (separate project, since this may be useful to all scons users, not just numpy): https://launchpad.net/numpy.scons.support and I can already do some non trivial things, not possible with numpy.distutils (automatically figuring out fortran mangling, flags for linking with C, blas/lapack flags). As expected, this is much more robust than distutils approach of hardcoding everything: although I used g77 for development, it worked without any change with ifort, gfortran and sun fortran compiler (on linux). There are still some issues for sure, but I don't see big problems. I don't want to do the work for nothing, though, so I would like to know the feeling of numpy developers first on this direction, in particular which platforms should work before merging consideration, etc... cheers, David