[Distutils] Dynamic linking between Python modules (was: Beyond wheels 1.0: helping downstream, FHS and more)

[David Mertz]

This pertains more to the other thread I started, but I'm sort of becoming
convinced--especially by Paul Moore's suggestion there--that the better
approach is to grow conda (the tool) rather than shoehorn conda packages
into pip.  Getting pip to recognize the archive format of conda would be
easy enough alone, but that really doesn't cover the fact that 'conda ~=
pip+virtualenv', and pip alone simply should not try to grow that latter
aspect itself.  Plus pip is not going to be fully language agnostic, for
various reasons, but including the fact that apt-get and yum and homebrew
and ports already exist.

So it might make sense to actually allow folks to push conda to budding web
developers, if conda allowed installation (and environment management) of
sdist packages on PyPI.  So perhaps it would be good if *this* worked:

  % pip install conda
  % conda install scientific_stuff
  % conda install --sdist django_widget   # we know to look on PyPI

Maybe that flag is mis-named, or could be omitted altogether.  But there's
no conceptual reason that conda couldn't build an sdist fetched from PyPI
into a platform specific binary matching the current user machine (and do
all the metadata dependency and environment stuff the conda tool does).

On Mon, May 18, 2015 at 3:17 AM, Paul Moore <p.f.moore at gmail.com> wrote:

> On 17 May 2015 at 23:50, Chris Barker <chris.barker at noaa.gov> wrote:
> > I guess the key thing here for me is that I don't see pushing conda to
> > budding web developers -- but what if web developers have the need for a
> bit
> > of the scipy stack? or???
> >
> > We really don't have a good solution for those folks.
>
> Agreed. My personal use case is as a general programmer (mostly
> sysadmin and automation type of work) with some strong interest in
> business data analysis and a side interest in stats.
>
> For that sort of scenario, some of the scipy stack (specifically
> matplotlib and pandas and their dependencies) is really useful. But
> conda is *not* what I'd use for day to day work, so being able to
> install via pip is important to me. It should be noted that installing
> via pip *is* possible - via some of the relevant projects having
> published wheels, and the rest being available via Christoph Gohlke's
> site either as wheels or as wininsts that I can convert. But that's
> not a seamless process, so it's not something I'd be too happy
> explaining to a colleague should I want to share the workload for that
> type of thing.
>
> Paul
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