[Numpy-discussion] scipy binary for macosx tiger on ppc

Barry Wark barrywark@gmail....
Fri Nov 30 10:39:49 CST 2007


On 11/29/07, David Cournapeau <david@ar.media.kyoto-u.ac.jp> wrote:
> Barry Wark wrote:
> > Using the gfortran from http://r.research.att.com/tools/, it's trivial
> > to build a universal build from source. The instructions on scipy.org
> > won't lead you astray.
> >
> > I will ask around at work. Perhaps we can start building universal
> > scipy builds for distribution. Can anyone from the scipy devs email me
> > off list if you'd like to pursue this?... triggering a build
> > automatically from SVN commits or such would be good.
> That would be cool, but where to compile the binary ? scipy does not
> have build farm. Having a 100 % automatic way to build a binary would
> certainly be a step in this direction, though. There is also the need to
> test the compiled binary, which is not trivial with fat binaries. To sum up:
>     - we need at least one x86 mac os X machine to build/test (I don't
> know if you can test python softwares through rosetta: I have only
> experience testing pure C softwares built as fat binaries)

One of our machines (OSX Intel) is already the buildbot slave for the
numpy buildbot. I think I can get us OK'd to build scipy on there as
well. We generate our own scipy builds so it shouldn't be too big a
problem. Unless there's an automated system, I'd prefer to to just
release builds.

Some remaining issues:
- which SDK to build against. Leopard ships with a Python build
against the 10.5 SDK. It would be much easier, at least initially, for
us to produce binaries against the Leopard Python 2.5.
- how to deal with library dependencies such as fftw2. We currently
use MacPorts but I suppose it needs to be compiled statically or do we
just require that users install MacPort's fftw2?


>     - we need a way to automate the build entirely

It seems like scipy needs a buildbot.

>     - we need a way to automate the packaging (distutils can do only
> part of it or all of it ? Building a basic .pkg inside a dmg is not hard
> from the command line, but I don't know how it scales for non trivial
> packages).

It's relatively easy to build a single pkg for the entire scipy
distribution (that's what we do now) and put that on a DMG (as you
said). When scipy becomes a less monolithic package (i.e. using
setuptools namespace packages), we can create a pkg for each package
and a mpkg combining them all.

~barry


More information about the Numpy-discussion mailing list