[Numpy-discussion] packaging scipy (was Re: Simple financial functions for NumPy)

Bruce Southey bsouthey@gmail....
Mon Apr 7 13:19:31 CDT 2008


Steven H. Rogers wrote:
> On Mon, April 7, 2008 11:16, Timothy Hochberg wrote:
>   
>> If "from numpy.all import *" is really too complicated, which although
>> possible, seems a little disheartening, I suspect it would be easy enough
>> to
>> have a separate module that pulled everything in so that you could use
>> "from
>> big_numpy import *". Or, to preserve backward compatibility, make numpy
>> the
>> unsplit namespace and expose the split namespace under a different name,
>> let's say 'np' because that's what I already use as a numpy abbreviation.
>> Then "import np" would get you just the core np functions (which I imagine
>> we could argue about endlessly) and the various subpackages would be
>> imported separately. 'np' is 'numpy' with some stuff removed: get it? OK,
>> so
>> that's a weak joke, sorry.
>>
>>     
> May not be the epitome of wit, but not bad.
>
> +1 for np package being a minimalist numpy and numpy being bigger.
>
> # Steve
>
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>   
Hi,
I think that splitting the NumPy namespace should not happen within a 
major release series because it would cause too many breakages.  Rather 
it should be in a forthcoming release like the 2.0 series where it may 
be very feasible to have a true core functionality (NumPy), extended 
functionality (SciPy) and specific applications (Scikits). At the same 
time, Python 3K would be  fully supported because it will break lots of 
code.

It is really nice to think about having NumPy Core, NumPy Full, 
NumPyKits, SciPy Core, SciPy Full and SciPyKits. But splitting 
namespaces like core and complete brings into the problem of conflicts 
and how to resolve them. Regardless of the content of each, I have the 
suspicion that most people would just take the full versions of each 
eventhough most of them only use a very small fraction of NumPy (just 
probably different amongst users).

In the past, the real distinction between Numpy and SciPy for me was the 
requirement of having a full Lapack installation and a Fortran compiler 
for SciPy. This made the current scheme very usable especially the 
frustrations of getting SciPy to install. Fortunately Linux and GCC 
Fortran has really developed over the years that these are not as big as 
they were although these still cause issues (especially if packages are 
broken). However, it remains a big concern if everything has to be built 
from scratch (perhaps with different compilers) or if developers 
continue to tell users to get the latest version from svn (problem if 
you used a precompiled version).

Regards
Bruce



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