How Runtime Polymorphism is expressed in Boost.Python: ----------------------------------------------------- struct A { virtual std::string f(); virtual ~A(); }; std::string call_f(A& x) { return x.f(); } struct B { virtual std::string f() { return "B"; } }; struct Bcb : B { Bcb(PyObject* self) : m_self(self) {} virtual std::string f() { return call_method(m_sef, "f"); } static std::string f_default(B& b) { return b.B::f(); } PyObject* m_self; }; struct C : B { virtual std::string f() { return "C"; } }; >>> class D(B): ... def f(): ... return 'D' ... >>> class E(B): pass ... When we write, "invokes B::f non-virtually", we mean: void g(B& x) { x.B::f(); } This will call B::f() regardless of the dynamic type of x. Any other way of invoking B::f, including through a function pointer, is a "virtual invocation", and will call the most-derived override of f(). Case studies C++\Python class \___A_____B_____C_____D____E___ | A | 1 | B | 2 3 | Bcb | 4 5 6 | C | 7 8 | 1. Simple case 2. Python A holds a B*. Probably won't happen once we have forced downcasting. Requires: x.f() -> 'B' call_f(x) -> 'B' Implies: A.f invokes A::f() (virtually or otherwise) 3. Python B holds a B*. Requires: x.f() -> 'B' call_f(x) -> 'B' Implies: B.f invokes B::f (virtually or otherwise) 4. B constructed from Python Requires: x.f() -> 'B' call_f(x) -> 'B' Implies: B.f invokes B::f non-virtually. Bcb::f invokes B::f non-virtually. Question: Does it help if we arrange for Python B construction to build a true B object? Then this case doesn't arise. 5. D is a Python class derived from B Requires: x.f() -> 'D' call_f(x) -> 'D' Implies: Bcb::f must invoke call_method to look up the Python method override, otherwise call_f wouldn't work. 6. E is like D, but doesn't override f Requires: x.f() -> 'B' call_f(x) -> 'B' Implies: B.f invokes B::f non-virtually. If it were virtual, x.f() would cause infinite recursion, because we've already determined that Bcb::f must invoke call_method to look up the Python method override. 7. Python B object holds a C* Requires: x.f() -> 'C' call_f(x) -> 'C' Implies: B.f invokes B::f virtually. 8. C object constructed from Python Requires: x.f() -> 'C' call_f(x) -> 'C' Implies: nothing new. ------ Total implications: 2: A.f invokes A::f() (virtually or otherwise) 3: B.f invokes B::f (virtually or otherwise) 4: B.f invokes B::f non-virtually. Bcb::f invokes B::f non-virtually 6: B.f invokes B::f non-virtually. 7: B.f invokes B::f virtually. 5: Bcb::f invokes call_method to look up the Python method Though (4) is avoidable, clearly 6 and 7 are not, and they conflict. The implication is that B.f must choose its behavior according to the type of the contained C++ object. If it is Bcb, a non-virtual call to B::f must occur. Otherwise, a virtual call to B::f must occur. This is essentially the same scheme we had with Boost.Python v1. Note: in early versions of Boost.Python v1, we solved this problem by introducing a new Python class in the hierarchy, so that D and E actually derive from a B', and B'.f invokes B::f non-virtually, while B.f invokes B::f virtually. However, people complained about the artificial class in the hierarchy, which was revealed when they tried to do normal kinds of Python introspection. ------- Assumption: we will have a function which builds a virtual function dispatch callable Python object. make_virtual_function(pvmf, default_impl, call_policies, dispatch_type) Pseudocode: Get first argument from Python arg tuple if it contains dispatch_type call default_impl else call through pvmf Open questions: 1. What about Python multiple inheritance? Do we have the right check in the if clause above? A: Not quite. The correct test looks like: Deduce target type of pvmf, i.e. T in R(T::*)(A1...AN). Find holder in first argument which holds T if it holds dispatch_type... 2. Can we make this more efficient? The current "returning" mechanism will look up a holder for T again. I don't know if we know how to avoid that. OK, the solution involves reworking the call mechanism. This is neccesary anyway in order to enable wrapping of function objects. It can result in a reduction in the overall amount of source code, because returning<> won't need to be specialized for every combination of function and member function... though it will still need a void specialization. We will still need a way to dispatch to member functions through a regular function interface. mem_fn is almost the right tool, but it only goes up to 8 arguments. Forwarding is tricky if you don't want to incur copies. I think the trick is to use arg_from_python::result_type for each argument to the forwarder. Another option would be to use separate function, function object, and member function dispatchers. Once you know you have a member function, you don't need cv-qualified overloads to call it. Hmm, while we're at this, maybe we should solve the write-back converter problem. Can we do it? Maybe not. Ralf doesn't want to write special write-back functions here, does he? He wants the converter to do the work automatically. We could add cleanup/destructor registration. That would relieve the client from having accessible destructors for types which are being converted by rvalue. I'm not sure that this will really save any code, however. It rather depends on the linker, doesn't it? I wonder if this can be done in a backwards-compatible fashion by generating the delete function when it's not supplied?