matplotlib-devel Mailing List for matplotlib

Did everyone see that GitHub now allows attachments in issue comments?
IMO, this is awesome. Attaching a visual *thing* of output when users
get unexpected results from plotting calls is a massive plus. Drag and
drop right into the browser, too! No more having to upload a file to
imgur or dropbox and link it to the issue comment and then have it
disappear when you delete it and forgot it was linked to GitHub.
Win.
-- 
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

Yes, an excellent summary and neatly bringing us back to the crux of the
matter.
For completeness I should say that I wouldn't use SWIG. I used it about 5
years ago to wrap some C++ for Python and other languages. Initially it
was very useful, but eventually the default mapping between C++ and Python
types and the default handling of object lifetimes weren't quite what I
wanted and I found myself writing a lot of extra configuration code to coax
it back in line. In the end I went back to the Python/C API. Perhaps its
aim of targetting many different languages means it isn't suited for our
language of interest. It doesn't support Numpy arrays anyway.
I would like to be able to recommend Boost.Python, but I have never used
it. I have used some Boost modules and found all to be well-designed and
actively maintained. However, it currently doesn't support Numpy arrays
(although it is an active area of work) and it appears that there are
difficulties building it with anything other than the default build tool
BJam leading to concerns over portability.
Although my preference, in the absence of PyCXX, for wrapping our larger
C/C++ modules is to use the Python/C API rather than Cython, I have been
persuaded that there is a place for Cython in matplotlib. The ability to
improve the performance of small sections of Python code in a simple and
localised manner seems very useful, and would be a good starting point for
speeding up areas of code that a number of users are frustrated by. Given
the number of people who would like to see it used in matplotlib, I think
it is inevitable that we eventually will.
I hadn't really considered the option of adding Numpy arrays to PyCXX.
I've taken a quick look at the existing code and whilst I don't think it is
a trivial task it looks well worth investigating - the existing code is
well organised and quite well documented. If two or more of us were
prepared to make the Numpy additions to PyCXX and provide ongoing
maintenance, we would address the deficiencies of the current solution and
remove the single-person bottleneck. But I am not sure where this leaves
us as I a now advocating use of Cython to some extent and hence we would
have two wrapping tools. Should we reject Cython + improved PyCXX on these
grounds and revert to Cython + Python/C API?
Ian