On Sat, Mar 14, 2009 at 3:15 AM, Jon Wright <[email protected]> wrote: > What I want is a simpler way to install things for people to try out our > programs. We currently have dependencies on at least numpy, matplotlib, > PIL, Pmw and PyOpenGl and having to go through a series of 6 different > installations can be a bit intimidating. Any suggestions as to how best > to distribute such a beast is most welcome.
When distributing things, I see only two solutions: either you distribute everything separately (ala linux), or you integrate everything. On windows, integrating is almost always the right solution: you get the uninstall option, etc... It depends on how much resource you can spend on it, but if I were to distribute things on windows, I would build a msi/bdist_wininst of every package, and wrap this into another installer (which is almost exactly what the superpack does). That's how every big software on windows work AFAIK: every MS software installs this way for example. I don't claim any deep knowledge on the things behind bdist_wininst, but nsis, which is the open source system I use to build numpy and scipy so called superpack is powerful, maintained and well documented. Wrapping all the installer in one would be easy - if you need option, and in particular to control each installer independently, then it would become more difficult. cheers, David _______________________________________________ Numpy-discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
