To follow on to my previous posting on this topic given Robert's response. As I said previously, I was never strongly committed to one approach or the other. But since the v1 release has been made, I think more care needs to be given to consideration of proposals like this before actually charging off to make the changes. 1) Even though Robert is speaking for Travis, I think given Travis's role in numpy, it is important for Travis to speak directly to this when he gets the chance. 2) API changes should only be made in major releases, not minor releases (IMHO). 3) Greater time should be provided to accommodate the transition. For example, there should not be deprecation warnings in the first version that this API appears in. The first release of this should not lead to nuisance messages for those that have other software that depends on this. (A tool that allows conditional messages would be good, but the default should be no message). The next release, sure. As a result, it means that the old API can't be removed until at least two releases after that. 4) More information should be provided as to what actually will change in the public interface. I suspect that it isn't obvious to many what will change. From the mailing list discussions there doesn't even seem to be consensus on the factory functions or type objects (more on these later). Many of the remaining objects are probably used internally (essentially private) and will affect few outside of the numpy developers. Since users typically deal mostly with factory functions, and other functions, they may not deal with classes much (outside of types). So listing the public classes so affected will help people understand what changes typical users will see, and what changes advanced users will see. While this is annoying, I think someone needs to write up an explicit list of those public classes that will be changed (and those that won't) so we all know what we will face. It may be a very small list and thus alleviate concern about the process. It may show some surprises that people hadn't thought about. Not doing this before making the changes seems very unwise. 5) In my humble opinion, we would be nuts--absolutely nuts--to change either the type classes or the factory functions. This would be foolish consistency at it's worst. We *just* went through the exercise of changing Int32 to int32 and so forth and we would have to change back again? This cannot be seriously considered. Perry Greenfield On Oct 2, 2007, at 1:24 PM, Jarrod Millman wrote:

Hello,

For those of you not on the Numpy developer's list, we have been talking about adopting the Python class naming convention to conform with Guido's style guide as closely as possible: http://www.python.org/dev/peps/pep-0008/ According to Guido, class names should use the CapWords convention. Most Python projects (eg, ETS, matploltlib) adhere to the Python naming conventions and it is confusing that NumPy and SciPy don't.

Currently, both NumPy and SciPy use either lower_underscore_separated or CapWords for class names.

NumPy ====== $ grep -r '^class [A-Z]' --include "*.py" * | wc -l 1014 $ grep -r '^class' --include "*.py" * | grep -v 'class [A-Z]' | wc -l 207

SciPy ===== $ grep -r '^class [A-Z]' --include "*.py" * | wc -l 587 $ grep -r '^class' --include "*.py" * | grep -v 'class [A-Z]' | wc -l 565

So far, there is Universal support for the basic idea of conforming to the Python Style Guide. Since it should effect the user API, we have already updated the TestCase classes. First, we checked in a change to allow TestCase classes to be prefixed with either 'test' or 'Test': http://projects.scipy.org/scipy/numpy/changeset/4144 Then, we updated both SciPy and NumPy to use CapWords for TestCase classes: http://projects.scipy.org/scipy/numpy/changeset/4151 http://projects.scipy.org/scipy/scipy/changeset/3388 In order to run the SciPy tests on the trunk you will need to install NumPy from svn revision 4144 or greater. Before SciPy 0.7.0 is released, we will release NumPy 1.0.4.

Also, if you are adding a new class to NumPy or SciPy, please use CapWords. Now we need to decide what to do about the remaining lower_underscore_separated class names. Obviously, it is important that we are careful to not break a lot of code just to bring our class names up to standards.

Cheers,

-- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/ _______________________________________________ Scipy-dev mailing list Scipy-dev@scipy.org http://projects.scipy.org/mailman/listinfo/scipy-dev