Hi,
This worked, after installing python 2.6, dependencies and running cx_freeze
on an older distribution
Thanks, now I love cx_freeze.. saved my day :)
Julian
On Mon, Jul 12, 2010 at 9:21 PM, Anthony Tuininga <
[email protected]> wrote:
> Hi,
>
> You aren't going to be able to avoid the glibc dependency. Most times
> you can simply package (with cx_Freeze) the application on an "older"
> machine that has all of the glibc requirements that you are looking
> for. glibc is backwards compatible but not forwards compatible. That's
> why I use CentOS 5.x for packaging instead of what I normally use
> day-to-day (Fedora 13).
>
> The only other option is to force the base executables to be built
> statically and all Python extensions you are using to be included
> statically as well -- judging from the list of extensions you are
> using that isn't going to work for you. So see if you can get an "old"
> distribution and build with that. I use a virtual machine (via Oracle
> VirtualBox) for that purpose which works quite well.
>
> Hope that helps you out.
>
> Anthony
>
> On Mon, Jul 12, 2010 at 12:25 PM, julian bilcke <[email protected]>
> wrote:
> > Hi !
> >
> > I have a new question regarding packaging of standalone Python
> application
> > using cx_freeze.
> >
> > Just in preamble, a bit of context :
> >
> > - We are building an open-source text-mining python server application
> for
> > research, using a lot of existing python libs
> > - we have the following dependencies: Numpy, Twisted, (py-)BerkeleyDB,
> > zope.interface, simplejson, yaml
> >
> > - Still, we have been asked to make it a "no additional bumper required"
> > application (example of use cases: restrained environment without network
> > connection, no admin access or install, or usb-key bootable app..)
> > - we still though this was feasible, so we decided to to build 4
> versions
> > (linux32, linux64, mac, win32)
> > - We turned to tools like py2exe/app, pyinstall, and cx_freeze to make
> the
> > job easier
> >
> > But this task appear to be difficult, because of these heavy dependencies
> > (numpy, berkeley..)
> >
> > We have some results for Windows (binaries looks portable), but on other
> > platforms, like mac or linux,
> > this looks hard.
> >
> > By example, I tried to run our app under debian32 (it was built with
> > cx_freeze under ubuntu32)
> > but it failed : issue with numpy.so, which has an external dependency on
> > glibc at a particular version.
> > I don't have any idea on how resolve this kind of dependency without
> using
> > the standard system packaging system..
> >
> > So, my question is :
> > - does someone had to do something similar ? is there a solution to this
> > kind of issue (handling of external dependencies/libs) ?
> > - it is even feasible to package such program ? or should we abandon and
> > instead turn to a "local install" packaging ?
> >
> >
> > if someone here had to deal with this kind of packaging, and has any
> hint, I
> > would be very, very thankful !
> >
> > Julian
> >
> > ps:
> >
> >
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> >
>
--
Julian Bilcke
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