Differences between Framework and non-Framework builds of Python on Mac OS X Differences between Framework and non-Framework builds of Python on Mac OS X python python

Differences between Framework and non-Framework builds of Python on Mac OS X


You've already listed all important advantages of making a framework (congratulations for excellent research and reporting thereof!); the only flip side is that it's harder to arrange to build one properly, but if you take your clues from the examples in the installer you quote, it should be doable.

BTW, what's wrong with the system Python that comes with Snow Leopard? I haven't upgraded from Leopard yet (long story... I do have the "family license" upgrade DVD, but need Snow Leopard to fix some things before I can upgrade), so I have no first-hand experience with that yet, but I do know it's a 2.6 build and it comes in both 32-bit and 64-bit versions... so why do you need to build your own framework?


There is another difference: typically the Framework installation provided by the installer from python.org has several architectures.

$ file libpython2.7.dylib

libpython2.7.dylib: Mach-O universal binary with 2 architectureslibpython2.7.dylib (for architecture i386): Mach-O dynamically linked shared library i386libpython2.7.dylib (for architecture x86_64): Mach-O 64-bit dynamically linked shared library x86_64

If you install from source and you do not deliberately change this, your libpython has only one architecture.I have had cases where the two architectures actually resulted in problems (at least I believe that this was the reason), namely when installing the HDF5 python bindings (h5py).

And there is yet another difference: some tools require the framework installation. For instance PyQt, and in particular sip. While it is possible to install sip and PyQt even for the non-framework version of python, it is much more complicated.

As for the decision what to prefer, I still do not know. At the moment, I went for the non-framework option, but I must say, that it also caused me some headache.


If you are going to ship your code (have it running on another machine), you'd better use the system version of python otherwise your program behavior will be undefined on the other machines.