This looks really neat!
Do you have any measure on the memory/cpu performance wrt Boost.Python when
compiling large bindings? I would expect that variadic templates and all
the other C++11 goodies are more efficient than the preprocessor magic used
in Boost Python, from this point of view.
Cheers
On 25 September 2015 at 17:20, Stefan Seefeld wrote:
> I don't entirely understand what you are saying. What do you mean by
> "boost.python object", and what by "boost.python library function" ?
>
I think he has a C++ class that was exposed to Python, and which is
included as a member of a pure
Kudos and thanks a lot, that looks great! (and it must have taken a lot of
effort...)
Cheers,
Francesco.
On 5 August 2015 at 14:23, Stefan Seefeld wrote:
> Hi all,
>
> I have updated the Boost.Python documentation.
>
> The new docs are available at http://boostorg.github.io/python.
> (For an
Hello Jim,
On 16 November 2014 20:23, Jim Bosch wrote:
> On Sun, Nov 16, 2014 at 1:51 PM, Francesco Biscani
> wrote:
>
>>
>> This can result in an exception being thrown from Python (e.g.,
>> comparison of a numpy array with zero). What happens in this case is that
Hello all,
I don't know if the subject makes any sense, but hopefully the description
of the problem will make things clearer :)
I have a template class which I am exposing to Python with different types
instantiated. For the sake of simplicity, let's say it is a Vector
class. I have various vers
Hello Stefan and Nikolay,
thanks for the replies. I have been using as well approaches similar to
those you outlined. My main concern is the automation of the whole
procedure. I have a fairly complicated hierarchy of template classes that I
am exposing, and I need to be able to add new exposed ins
Greetings,
I have been trying to think of a solution about this for a few days now,
but I did not get very far.
I am exposing specific instances of C++ template classes using
Boost.Python. Let's say for the sake of argument that I am exposing
std::vector. What I would like to achieve on the Pytho
