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/scons_fake/pyext
- Building a ctypes-based package:
http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons/numpy/scons_fake/ctypesext
- An example on how to check for libraries and symbols in them:
http://projects.scipy.org/scipy/numpy/browser/branches/numpy.scons/numpy/scons_fake/pyext
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
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