[SciPy-dev] [matplotlib-devel] Announcing toydist, improving distribution and packaging situation

Neal Becker ndbecker2@gmail....
Mon Dec 28 12:03:31 CST 2009


David Cournapeau wrote:

> On Mon, Dec 28, 2009 at 11:47 PM, Stefan Schwarzburg
> <stefan.schwarzburg@googlemail.com> wrote:
>> Hi,
>> I would like to add a comment from the user perspective:
>>
>> - the main reason why I'm not satisfied with pypi/distutils/etc. and why
>> I will not be satisfied with toydist (with the features you listed), is
>> that they break my installation (debian/ubuntu).
> 
> Toydist (or distutils) does not break anything as is. It would be like
> saying make breaks debian - it does not make much sense. As stated,
> one of the goal of giving up distutils is to make packaging by os
> vendors easier. In particular, by allowing to follow the FHS, and
> making things more consistent. It should be possible to automatically
> convert most packages to .deb (or .rpm) relatively easily. When you
> look at the numpy .deb package, most of the issues are distutils
> issues, and almost everything else can be done automatically.
> 
> Note that even ignoring the windows problem, there are systems to do
> the kind of things I am talking about for linux-only systems (the
> opensuse build service), because distributions are not always really
> good at tracking fast changing softwares. IOW, traditional linux
> packaging has some issues as well. And anyway, nothing prevents debian
> or other OS vendors to package things as they want (as they do for R
> packages).
> 
> David

I think the breakage that is referred to I can describe on my favorite 
system, fedora.

I can install the fedora numpy rpm using yum.  I could also use 
easy_install.  Unfortunately:
1) Each one knows nothing about the other
2) They may install things into conflicting paths.  In particular, on fedora 
arch-dependent things go in /usr/lib64/python<version>/site-packages while 
arch-independent goes into /usr/lib/python<version>...  If you mix yum with 
easy_install (or setuptools), you many times wind up with 2 versions and a 
lot of confusion.

This is NOT unusual.  Let's say I have numpy-1.3.0 installed from rpms.  I 
see the announcement of numpy-1.4.0, and decide I want it, before the rpm is 
available, so I use easy_install.  Now numpy-1.4.0 shows up as a standard 
rpm, and a subsequent update (which could be automatic!) could produce a 
broken system.

I don't really know what could be done about it.  Perhaps a design that 
attempts to use native backends for installation where available?



More information about the SciPy-Dev mailing list