Full disclosure: I work for continuum.  I'm recommending these things only
because I think they make life easier.

MSYS2 packages are available as conda packages, too. Ray Donnelly, one of
the MSYS2 maintainers, works for continuum.  He also maintains our r
packages. If you want to use either and run into trouble, feel free to ping
us.

On Dec 2, 2016 7:33 AM, "Erik Bray" <[email protected]> wrote:

On Fri, Dec 2, 2016 at 2:08 PM, Raniere <[email protected]> wrote:
> Hi Erik,
>
> Thanks for the good work!
>
>
>>I hope to have a prototype ready soon for people to test out.  But one
>>question I have that's really bothering me is: Is there a *particular*
>>reason we rely on Anaconda for our Python distribution in the lessons?
>
> Anaconda make easy to install some Python packages that require to
compile some C or Fortran code. For example, the lxml package requires the
C library that isn't installed by pip.

Yes, but this is generally a non-issue if using Cygwin.

>> Is there something particular in the existing lesson plans that
>>require Anaconda?
>
> How hard is to install matplotlib on Cygwin? Or AstroPy? We use Anaconda
because most of our learners will have the packages they need on their day
job out of the box.

I figured that was the main reason.  Most of these packages can
install and work fine in Cygwin, but I would be worried about leaving
something out and it might be a lot of additional effort to repeat the
packaging that's already been done with Anaconda (as Maxime mentioned
upthread this also includes SciPy, Pandas etc..) as well as things
like scikit-learn.  I can install most of these in Cygwin but to me
the point of using Cygwin was *not* for Python per se, but all the
other shell tools, where I think it excels over most other options
(something based on MSYS2, itself based on Cygwin, might also be
workable).

On Fri, Dec 2, 2016 at 2:08 PM, Michael Sarahan <[email protected]> wrote:
> IMHO, the nice thing about Anaconda is that it obviates a lot of the
> integration questions.  Having things in local environments makes life so
> much easier that I can't imagine another way.
>
> Anaconda is huge, though. SWC could make a much smaller Anaconda-like
> installer using constructor: https://github.com/conda/constructor - this
is
> also easy enough to maintain specific installers for each training, so
that
> the installers could contain only what was going to be used in a given
> training.  Instructors could create their own installer (just change the
> input list of packages).

Something like this might not be a bad idea either, but I think it's
more orthogonal.  If we do stick with Anaconda it might be nice to put
together a smaller anaconda distribution on top of miniconda--this
might also be easier for me to distribute in a single installable (and
might even be fine to install for R workshops if it doesn't take up
too much space).

I'd like to also ease the tension between setup for R workshops and
Python workshops by just including everything needed for both, but
that's down the line...
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