Hi Pertti I had the same problem as you in my binding implementation, then I solve the problem using this function: // // a generator with an execute() function which, given a source type // and a pointer to an object of that type, returns its most-derived // /reachable/ type identifier and object pointer. // // first, the case where T has virtual functions template <class T> struct polymorphic_id_generator { static dynamic_id_t execute(void* p_) { T* p = static_cast<T*>(p_); return std::make_pair(dynamic_cast<void*>(p), class_id(typeid(*p))); } }; I use this function to get a pointer to most-derived type and use this as key in my hash table. BR Renato Araujo Oliveira Filho 2009/9/29 Pertti Kellomäki <pertti.kellomaki@tut.fi>:

I have Python bindings for a C++ library that among other things contains classes for describing the static structure of a microprocessor.

My background is in Lisp, so I am used to using object identities (references) as keys. The C++ library can be used in this fashion, e.g. looking up a register file by name always returns the same object reference. However, the C++ to Python mapping does not preserve object identity, as a new Python object is created for every query, even if the underlying C++ reference is the same.

Is there any easy way to preserve object identity in this sense with Boost Python? My first thought was to use some kind of caching scheme so that consequent queries with a particular name return the same object, but the problem is that objects are not only looked up by name, they can also be returned e.g. by asking for a parent object in a containment hierarchy. -- Pertti _______________________________________________ Cplusplus-sig mailing list Cplusplus-sig@python.org http://mail.python.org/mailman/listinfo/cplusplus-sig

2009/9/29 Pertti Kellomäki <pertti.kellomaki@tut.fi>:

I have Python bindings for a C++ library that among other things contains classes for describing the static structure of a microprocessor.

My background is in Lisp, so I am used to using object identities (references) as keys. The C++ library can be used in this fashion, e.g. looking up a register file by name always returns the same object reference. However, the C++ to Python mapping does not preserve object identity, as a new Python object is created for every query, even if the underlying C++ reference is the same.

Is there any easy way to preserve object identity in this sense with Boost Python? My first thought was to use some kind of caching scheme so that consequent queries with a particular name return the same object, but the problem is that objects are not only looked up by name, they can also be returned e.g. by asking for a parent object in a containment hierarchy.

A while ago I introduce to Py++ some kind of functionality, which integrates with CTYPES package. For example, you can expose "this" pointer to Python and use it as your id: http://language-binding.net/pyplusplus/documentation/ctypes/this_and_sizeof.... HTH -- Roman Yakovenko C++ Python language binding http://www.language-binding.net/