[Distutils] Handling the binary dependency management problem

[Nick Coghlan]

On 3 Dec 2013 08:17, "Marcus Smith" <qwcode at gmail.com> wrote:
>
>
>>>
>>>  publication of curated stacks when the conda folks already have one,
>>
>> so, I see the index: http://repo.continuum.io/pkgs/index.html
>> Is they a way to contribute to this index yet?  or is that what would
need to be worked out.
>
>
> probably a dumb question, but would it be possible to convert all the
anaconda packages to wheels?
> even the non-python ones like:  qt-4.7.4-0.tar.bz2
> certainly not the intent of wheels, but just wondering if it could be
made to work?
> but I'm guessing there's pieces in the core anaconda distribution itself,
that makes it all work?
> the point here being to provide a way to use the effort of conda in any
kind of "normal" python environment, as long you consistently point at an
index that just contains the "conda" wheels.

I'm not sure about the conda -> wheel direction, but "pip install conda &&
conda init" mostly works already if you're in a virtualenv that owns its
copy of Python (this is also the answer to "why not ActiveState or
Enthought" - the Continuum Analytics software distribution stuff is truly
open source, and able to be used completely independently of their
services).

Their docs aren't that great in terms of explaining the *why* of conda -
I'm definitely influenced by spending time talking about how it works with
Travis and some of the other Continuum Analytics folks at PyCon US and the
Austin Python user group.

However, their approach to distribution of fully curated stacks seems
basically sound, the scientific and data analysis users I know that have
tried it have loved it, the devs have expressed a willingness to work on
improving their interoperability with the standard tools (and followed
through on that at least once by creating the "conda init" command) , and
they're actively interested in participating in the broader community
(hence the presentation at the packaging mini-summit at PyCon US, as well
as assorted presentations at SciPy and PyData conferences).

People are already confused about the differences between pip and conda and
when they should use each, and unless we start working with the conda devs
to cleanly define the different use cases, that's going to remain the case.

POSIX users need ready access to a prebuilt scientific stack just as much
(or more) than Mac OS X and Windows users (there's a reason
"ScientificLinux" is a distribution in its own right) and that space is
moving fast enough that the Linux distros (even SL) end up being too slow
to update. conda solves that problem, and it solves it in a way that works
on Windows as well. On the wheel side of things we haven't even solved the
POSIX platform tagging problem yet, and I don't believe we should make
users wait until we have figured that out when there's an existing solution
to that particular problem that already works.

Cheers,
Nick.

>
>
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