One more question: if I want these c++ objects, that are exposed to python with 
boost::python, to be an internal property maps and so be (de)serialized with 
the graph (from)into .gt format, should I write a boost::python pickle support 
functions for these classes?
Will it work?

‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐

вторник, 13 июля 2021 г., 23:44, Tiago de Paula Peixoto <[email protected]> 
написал(а):

> Am 13.07.21 um 21:58 schrieb sebyakin.a:
>
> > Hello,
> >
> > My question is: which parts of a code I should modify to add internal
> >
> > property maps of custom type? Is it possible without ground-breaking
> >
> > modifications, or should I look a way for some workaround?
> >
> > My usecase is to bridge python integer objects and big integer objects
> >
> > (from intx library) on c++ side, as a vertex property. I'm going to
> >
> > perform relatively heavy math operations and graph operations, so I want
> >
> > to write a C++ extension that does it.
> >
> > So I thought, is it possible to add custom property map handlers for big
> >
> > integers, that will convert python long objects to intx type and store
> >
> > it in that type later.
>
> The simplest thing for you to do is to use Boost.Python to reflect your
>
> custom types to python, which then you can store in a property map of
>
> type "python::object". You can access the property map values from your
>
> C++ extension by using python::extract().
>
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Tiago de Paula Peixoto [email protected]
>
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