Python provides a 'Python/C API' that allows you to create C/C++ extension modules and to embed the Python interpreter in your C/C++ programs. Pointers to PyObjects are the Python/C API's way to use Python objects from the C/C++ side.
BoostPython uses advanced C++ techniques to provide a much easier interface to the Python/C API. One manifestation of this is in python::object which is basically a (very) convenient, high-level wrapper around PyObject*. A lower level wrapping around PyObject* is python::handle.
When a python class is being inherited from a c++ class, one must write a c++ wrapper around the c++ class.
This wrapper must have a pointer to a PyObject called self. It's the Python object which contains the C++ object instance.
In general, a wrapped C++ object with a corresponding Python object is the size of:
- a new-style class (derived from 'object' in Python) instance plus
- the extra size required to allow variable-length data in the instance, plus
- the size of the C++ object, plus
the size of a vtable pointer, plus
- a pointer to the C++ object's instanceholder, plus
- zero or more bytes of padding required to ensure that the instanceholder is properly aligned.
You can see this in boost/python/object/instance.hpp. Most Python objects are represented by instance<value_holder<T> >, for some C++ class T.
All the code for implementing C++ object wrappers is in libs/python/src/object/class.cpp.
Instance dictionaries are created only "on demand", the first time the instance's __dict__ attribute is accessed (see instance_get_dict).
>>> a = A() # some extension class A, no instance dict >>> a.x # Attribute lookup fails, still no instance dict Traceback ... >>> a.y = 1 # y is a C++ data member, still no instance dict >>> a.x = 1 # creates an instance dict >>> z = A() >>> z.__dict__ # also creates an instance dict
If your C++ data structure contains pointers or smart pointers, you can arrange for Python objects to be created which only embed those pointers (instance<pointer_holder<Ptr> >). These Python objects will be in existence only as long as your Python code holds a reference to them.