[IPython-dev] Docker IPython

[Tyler Erickson]

I agree that pip is useful, because PyPI has packages that are not
available in conda, and often has more recent versions. But it doesn't need
to be an either/or choice, because conda plays well with pip (at least in
my experience). After installing conda, I usually use it to install pip
("conda install pip") and then pick and choose from both the conda repo and
PyPI.


On Tue, Aug 5, 2014 at 11:09 AM, Kyle Kelley <rgbkrk at gmail.com> wrote:

> I'm definitely on the pip for base image camp. conda can be installed
> after as part of a separate image. We also don't need to manage multiple
> environments. It is one container after all. Derivatives can have
> components.
>
>
> On Tue, Aug 5, 2014 at 12:36 PM, Matthias Bussonnier <
> bussonniermatthias at gmail.com> wrote:
>
>>
>> Le 5 août 2014 à 18:11, Jon Wilson <jsw at fnal.gov> a écrit :
>>
>> > If any substantial fraction of your users will want
>> > scipy/numpy/matplotlib, I would (almost, see below) recommend conda.
>>
>> Adrew’s IHaskell users will definitively not want the scipy stack, they
>> want Haskell things.
>>
>>
>> > Conda was, as I understand it, created because pip left too many
>> > barriers in place against the use of scipy/numpy etc.  Specifically,
>> > experience indicated that many people who might otherwise have casually
>> > investigated scientific python tools did not do so because pip required
>> > them to have a proper FORTRAN development environment set up, and they
>> > did not wish to figure out how to do this.
>> >
>> > Conda distributes binaries rather than exclusively source, which is an
>> > effective way around this sort of problem.
>> >
>> > OTOH, a pure-python package that is hosted on PyPI (and therefore
>> > installable via pip) can (usually) be trivially made into a conda
>> > package via `conda skeleton pypi <package-name>`.  So making pip-style
>> > packages tends to get you conda packages for almost free.
>>
>> I suppose this « easy » way to make PyPi package from conda package
>> explain
>> why  continuum package are outdated by more that a year using pip :-)
>>
>> Even if conda seem great, I still feel sad that there is little effort to
>> help fixing
>> python packaging (no, replacing is not fixing), but I understand that
>> starting
>> from scratch might be easier. Installig SciPy was much more a pain even a
>> few
>> month ago than now.
>>
>> Keep also  in mind than miniconda will be smaller if you decide to use it.
>>
>> I would also reming you that with 3.0, the IPython notebook can start
>> many kernels in different languages,
>> so nothing prevent you from installing the notebook using pip, and having
>> a conda kernel.
>> (it is even possible with 2.x)
>>
>> So +1 for pip which should be enough, or even maybe Julia Taylor PPA if
>> compatible.
>> —
>> M
>>
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>
>
>
> --
> Kyle Kelley (@rgbkrk <https://twitter.com/rgbkrk>; http://lambdaops.com)
>
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