[IPython-dev] Docker IPython

Matthias Bussonnier bussonniermatthias at gmail.com
Tue Aug 5 13:36:02 EDT 2014

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why  continuum package are outdated by more that a year using pip :-) 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. 

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