[Numpy-discussion] Merging the refactor.

Bruce Southey bsouthey@gmail....
Fri Nov 12 09:21:10 CST 2010

On 11/11/2010 09:02 PM, David Cournapeau wrote:
> On Fri, Nov 12, 2010 at 7:15 AM, Travis Oliphant<oliphant@enthought.com>  wrote:
>> At the same time, the work on the .NET framework has pushed us to move more
>> of SciPy to a Cython-generated set.   There are additional things I would
>> like to see SciPy improve on as well, but I am not sure who is going to work
>> on them.   If I had my dream, there would be more modularity to the
>> packages, and an improved packaging system --- and of course, porting to
>> Python 3k.
> I don't exactly where we are there, but Pauli and me took a look at
> scipy for python 3 at euroscipy in Paris, and I think it is mostly a
> matter of low hanging fruits. Most (all ?) changes are in the trunk
> already.
>>    I would like to see core SciPy be a smaller set containing a
>> few core packages.   (linear algebra, statistics, optimization,
>> interpolation, signal processing, and image processing).   Then, I would
>> like to see scipy.<module>  packages which are released and packaged
>> separately with the whole system available on github.
> While I agree with the sentiment, I think it would be a mistake to do
> so before we have the infrastructure to actually deliver packages and
> so on. I understand there is a bit of a chicken and egg issue as well.
> I spent most if not all my free time in 2010 to work on that issue,
> and I will summarize the current status in a separate email to the ML
> to avoid disrupting the main discussion on the refactoring,
> cheers,
> David

I agree with David comment because splitting requires effective package 
management to handle all these splits. Also there seems to be little 
point in splitting if users tend to require more than just the core. The 
problem with splitting things too finely is that these create more 
problems that it is worth.  We have already experienced incompatibility 
problems in numarray's short history with at least masked arrays and the 
datetime addition.

Related to this, can the refactoring be used to make future developments 
of numpy and scipy especially in terms of packaging easier?
I can see that moving or renaming of directories and files to more 
convenient places or names could be easily done at this time.


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