[Numpy-discussion] How a transition to C++ could work
Sun Feb 19 04:41:20 CST 2012
On Sun, Feb 19, 2012 at 4:14 AM, David Cournapeau <email@example.com>wrote:
> On Sun, Feb 19, 2012 at 9:52 AM, Mark Wiebe <firstname.lastname@example.org> wrote:
> > On Sun, Feb 19, 2012 at 3:10 AM, Ben Walsh <email@example.com>
> >> > Date: Sun, 19 Feb 2012 01:18:20 -0600
> >> > From: Mark Wiebe <firstname.lastname@example.org>
> >> > Subject: [Numpy-discussion] How a transition to C++ could work
> >> > To: Discussion of Numerical Python <NumPy-Discussion@scipy.org>
> >> > Message-ID:
> >> >
> >> > <CAMRnEmpVTmt=KduRpZKtgUi516oQtqD4vAzm746HmpqgpFXNqQ@mail.gmail.com>
> >> > Content-Type: text/plain; charset="utf-8"
> >> >
> >> > The suggestion of transitioning the NumPy core code from C to C++ has
> >> > sparked a vigorous debate, and I thought I'd start a new thread to
> >> > my
> >> > perspective on some of the issues raised, and describe how such a
> >> > transition could occur.
> >> >
> >> > First, I'd like to reiterate the gcc rationale for their choice to
> >> > switch:
> >> > http://gcc.gnu.org/wiki/gcc-in-cxx#Rationale
> >> >
> >> > In particular, these points deserve emphasis:
> >> >
> >> > - The C subset of C++ is just as efficient as C.
> >> > - C++ supports cleaner code in several significant cases.
> >> > - C++ makes it easier to write cleaner interfaces by making it
> >> > to
> >> > break interface boundaries.
> >> > - C++ never requires uglier code.
> >> >
> >> I think they're trying to solve a different problem.
> >> I thought the problem that numpy was trying to solve is "make inner
> >> of numerical algorithms very fast". C is great for this because you can
> >> write C code and picture precisely what assembly code will be generated.
> > What you're describing is also the C subset of C++, so your experience
> > applies just as well to C++!
> >> C++ removes some of this advantage -- now there is extra code generated
> >> the compiler to handle constructors, destructors, operators etc which
> >> make a material difference to fast inner loops. So you end up just
> >> "C-style" anyway.
> > This is in fact not true, and writing in C++ style can often produce
> > code. A classic example of this is C qsort vs C++ std::sort. You may be
> > thinking of using virtual functions in a class hierarchy, where a
> > between performance and run-time polymorphism is being done. Emulating
> > functionality that virtual functions provide in C will give similar
> > performance characteristics as the C++ language feature itself.
> >> On the other hand, if your problem really is "write lots of OO code with
> >> virtual methods and have it turned into machine code" (probably like the
> >> GCC guys) then maybe C++ is the way to go.
> > Managing the complexity of the dtype subsystem, the ufunc subsystem, the
> > nditer component, and other parts of NumPy could benefit from C++ Not in
> > stereotypical "OO code with virtual methods" way, that is not how typical
> > modern C++ is done.
> >> Some more opinions on C++:
> >> http://gigamonkeys.wordpress.com/2009/10/16/coders-c-plus-plus/
> >> Sorry if this all seems a bit negative about C++. It's just been my
> >> experience that C++ adds complexity while C keeps things nice and
> > Yes, there are lots of negative opinions about C++ out there, it's true.
> > Just like there are negative opinions about C, Java, C#, and any other
> > language which has become popular. My experience with regard to
> > and C vs C++ is that C forces the complexity of dealing with resource
> > lifetimes out into all the code everyone writes, while C++ allows one to
> > encapsulate that sort of complexity into a class which is small and more
> > easily verifiable. This is about code quality, and the best quality C++
> > I've worked with has been way easier to program in than the best quality
> > code I've worked with.
> While I actually believe this to be true (very good C++ can be easier
> to read/use than very good C). Good C is also much more common than
> good C++, at least in open source.
> On the good C++ codebases you have been working on, could you rely on
> everybody being a very good C++ programmer?
Not initially, but I designed the coding standards and taught the
programmers I hired how to write good C++ code.
> Because this will most
> likely never happen for numpy.
This is the role I see good coding standards and consistent code review
playing. Programmers who don't know how to write good C++ code can be
taught. There are also good books to read, like "C++ Coding Standards,"
"Effective C++", and others that can help people learn proper technique.
> This is the crux of the argument from
> an organizational POV: the variance in C++ code quality is much more
> difficult to control. I have seen C++ code that is certainly much
> poorer and more complex than numpy, to a point where not much could be
> done to save the codebase.
That's a consequence of the power C++ provides. It assumes the programmer
knows what he or she is doing, and provides the tools to make things great
or shoot oneself in the foot. I'd like to use that power to make NumPy
better, in a way which uses high quality modern C++ style. I'm willing to
help anyone contributing C-level code to NumPy to learn this style. I'd
rather not have to write any more C code, where it's easy to get a crash
because the C compiler allowed an implicit type conversion to slip through
when I typed the wrong thing.
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