[Numpy-discussion] Proposed Roadmap Overview

Matthew Brett matthew.brett@gmail....
Sat Feb 18 13:21:25 CST 2012


On Sat, Feb 18, 2012 at 12:18 AM, Christopher Jordan-Squire
<cjordan1@uw.edu> wrote:
> On Fri, Feb 17, 2012 at 11:31 PM, Matthew Brett <matthew.brett@gmail.com> wrote:
>> Hi,
>> On Fri, Feb 17, 2012 at 10:18 PM, Christopher Jordan-Squire
>> <cjordan1@uw.edu> wrote:
>>> On Fri, Feb 17, 2012 at 8:30 PM, Sturla Molden <sturla@molden.no> wrote:
>>>> Den 18. feb. 2012 kl. 05:01 skrev Jason Grout <jason-sage@creativetrax.com>:
>>>>> On 2/17/12 9:54 PM, Sturla Molden wrote:
>>>>>> We would have to write a C++ programming tutorial that is based on Pyton knowledge instead of C knowledge.
>>>>> I personally would love such a thing.  It's been a while since I did
>>>>> anything nontrivial on my own in C++.
>>>> One example: How do we code multiple return values?
>>>> In Python:
>>>> - Return a tuple.
>>>> In C:
>>>> - Use pointers (evilness)
>>>> In C++:
>>>> - Return a std::tuple, as you would in Python.
>>>> - Use references, as you would in Fortran or Pascal.
>>>> - Use pointers, as you would in C.
>>>> C++ textbooks always pick the last...
>>>> I would show the first and the second method, and perhaps intentionally forget the last.
>>>> Sturla
>>> On the flip side, cython looked pretty...but I didn't get the
>>> performance gains I wanted, and had to spend a lot of time figuring
>>> out if it was cython, needing to add types, buggy support for numpy,
>>> or actually the algorithm.
>> At the time, was the numpy support buggy?  I personally haven't had
>> many problems with Cython and numpy.
> It's not that the support WAS buggy, it's that it wasn't clear to me
> what was going on and where my performance bottleneck was. Even after
> microbenchmarking with ipython, using timeit and prun, and using the
> cython code visualization tool. Ultimately I don't think it was
> cython, so perhaps my comment was a bit unfair. But it was
> unfortunately difficult to verify that. Of course, as you say,
> diagnosing and solving such issues would become easier to resolve with
> more cython experience.
>>> The C files generated by cython were
>>> enormous and difficult to read. They really weren't meant for human
>>> consumption.
>> Yes, it takes some practice to get used to what Cython will do, and
>> how to optimize the output.
>>> As Sturla has said, regardless of the quality of the
>>> current product, it isn't stable.
>> I've personally found it more or less rock solid.  Could you say what
>> you mean by "it isn't stable"?
> I just meant what Sturla said, nothing more:
> "Cython is still 0.16, it is still unfinished. We cannot base NumPy on
> an unfinished compiler."

Y'all mean, it has a zero at the beginning of the version number and
it is still adding new features?  Yes, that is correct, but it seems
more reasonable to me to phrase that as 'active development' rather
than 'unstable', because they take considerable care to be backwards
compatible, have a large automated Cython test suite, and a major
stress-tester in the Sage test suite.



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