问题
I've nearly finished rewriting a C++ Python wrapper (PyCXX).
The original allows old and new style extension classes, but also allows one to derive from the new-style classes:
import test
// ok
a = test.new_style_class();
// also ok
class Derived( test.new_style_class() ):
def __init__( self ):
test_funcmapper.new_style_class.__init__( self )
def derived_func( self ):
print( 'derived_func' )
super().func_noargs()
def func_noargs( self ):
print( 'derived func_noargs' )
d = Derived()
The code is convoluted, and appears to contain errors (Why does PyCXX handle new-style classes in the way it does?)
My question is: What is the rationale/justification for PyCXX's convoluted mechanism? Is there a cleaner alternative?
I will attempt to detail below where I am at with this enquiry. First I will try and describe what PyCXX is doing at the moment, then I will describe what I think could maybe be improved.
When the Python runtime encounters d = Derived(), it does PyObject_Call( ob ) where ob is thePyTypeObjectforNewStyleClass. I will writeobasNewStyleClass_PyTypeObject`.
That PyTypeObject has been constructed in C++ and registered using PyType_Ready
PyObject_Call will invoke type_call(PyTypeObject *type, PyObject *args, PyObject *kwds), returning an initialised Derived instance i.e.
PyObject* derived_instance = type_call(NewStyleClass_PyTypeObject, NULL, NULL)
Something like this.
(All of this coming from (http://eli.thegreenplace.net/2012/04/16/python-object-creation-sequence by the way, thanks Eli!)
type_call does essentially:
type->tp_new(type, args, kwds);
type->tp_init(obj, args, kwds);
And our C++ wrapper has inserted functions into the tp_new and tp_init slots of NewStyleClass_PyTypeObject something like this:
typeobject.set_tp_new( extension_object_new );
typeobject.set_tp_init( extension_object_init );
:
static PyObject* extension_object_new( PyTypeObject* subtype,
PyObject* args, PyObject* kwds )
{
PyObject* pyob = subtype->tp_alloc(subtype,0);
Bridge* o = reinterpret_cast<Bridge *>( pyob );
o->m_pycxx_object = nullptr;
return pyob;
}
static int extension_object_init( PyObject* _self,
PyObject* args, PyObject* kwds )
{
Bridge* self{ reinterpret_cast<Bridge*>(_self) };
// NOTE: observe this is where we invoke the constructor,
// but indirectly (i.e. through final)
self->m_pycxx_object = new FinalClass{ self, args, kwds };
return 0;
}
Note that we need to bind together the Python Derived instance, and it's corresponding C++ class instance. (Why? Explained below, see 'X'). To do that we are using:
struct Bridge
{
PyObject_HEAD // <-- a PyObject
ExtObjBase* m_pycxx_object;
}
Now this bridge raises a question. I'm very suspicious of this design.
Note how memory was allocated for this new PyObject:
PyObject* pyob = subtype->tp_alloc(subtype,0);
And then we typecast this pointer to Bridge, and use the 4 or 8 (sizeof(void*)) bytes immediately following the PyObject to point to the corresponding C++ class instance (this gets hooked up in extension_object_init as can be seen above).
Now for this to work we require:
a) subtype->tp_alloc(subtype,0) must be allocating an extra sizeof(void*) bytes
b) The PyObject doesn't require any memory beyond sizeof(PyObject_HEAD), because if it did then this would be conflicting with the above pointer
One major question I have at this point is:
Can we guarantee that the PyObject that the Python runtime has created for our derived_instance does not overlap into Bridge's ExtObjBase* m_pycxx_object field?
I will attempt to answer it: it is US determining how much memory gets allocated. When we create NewStyleClass_PyTypeObject we feed in how much memory we want this PyTypeObject to allocate for a new instance of this type:
template< TEMPLATE_TYPENAME FinalClass >
class ExtObjBase : public FuncMapper<FinalClass> , public ExtObjBase_noTemplate
{
protected:
static TypeObject& typeobject()
{
static TypeObject* t{ nullptr };
if( ! t )
t = new TypeObject{ sizeof(FinalClass), typeid(FinalClass).name() };
/* ^^^^^^^^^^^^^^^^^ this is the bug BTW!
The C++ Derived class instance never gets deposited
In the memory allocated by the Python runtime
(controlled by this parameter)
This value should be sizeof(Bridge) -- as pointed out
in the answer to the question linked above
return *t;
}
:
}
class TypeObject
{
private:
PyTypeObject* table;
// these tables fit into the main table via pointers
PySequenceMethods* sequence_table;
PyMappingMethods* mapping_table;
PyNumberMethods* number_table;
PyBufferProcs* buffer_table;
public:
PyTypeObject* type_object() const
{
return table;
}
// NOTE: if you define one sequence method you must define all of them except the assigns
TypeObject( size_t size_bytes, const char* default_name )
: table{ new PyTypeObject{} } // {} sets to 0
, sequence_table{}
, mapping_table{}
, number_table{}
, buffer_table{}
{
PyObject* table_as_object = reinterpret_cast<PyObject* >( table );
*table_as_object = PyObject{ _PyObject_EXTRA_INIT 1, NULL };
// ^ py_object_initializer -- NULL because type must be init'd by user
table_as_object->ob_type = _Type_Type();
// QQQ table->ob_size = 0;
table->tp_name = const_cast<char *>( default_name );
table->tp_basicsize = size_bytes;
table->tp_itemsize = 0; // sizeof(void*); // so as to store extra pointer
table->tp_dealloc = ...
You can see it going in as table->tp_basicsize
But now it seems clear to me that PyObject-s generated from NewStyleClass_PyTypeObject will never require additional allocated memory.
Which means that this whole Bridge mechanism is unnecessary.
And PyCXX's original technique for using PyObject as a base class of NewStyleClassCXXClass, and initialising this base so that the Python runtime's PyObject for d = Derived() is in fact this base, this technique is looking good. Because it allows seamless typecasting.
Whenever Python runtime calls a slot from NewStyleClass_PyTypeObject, it will be passing a pointer to d's PyObject as the first parameter, and we can just typecast back to NewStyleClassCXXClass. <-- 'X' (referenced above)
So really my question is: why don't we just do this? Is there something special about deriving from NewStyleClass that forces extra allocation for the PyObject?
I realise I don't understand the creation sequence in the case of a derived class. Eli's post didn't cover that.
I suspect this may be connected with the fact that
static PyObject* extension_object_new( PyTypeObject* subtype, ...
^ this variable name is 'subtype' I don't understand this, and I wonder if this may hold the key.
EDIT: I thought of one possible explanation for why PyCXX is using sizeof(FinalClass) for initialisation. It might be a relic from an idea that got tried and discarded. i.e. If Python's tp_new call allocates enough space for the FinalClass (which has the PyObject as base), maybe a new FinalClass can be generated on that exact location using 'placement new', or some cunning reinterpret_cast business. My guess is this might have been tried, found to pose some problem, worked around, and the relic got left behind.
回答1:
PyCXX is not convoluted. It does have two bugs, but they can be easily fixed without requiring significant changes to the code.
When creating a C++ wrapper for the Python API, one encounters a problem. The C++ object model and the Python new-style object model are very different. One fundamental difference is that C++ has a single constructor that both creates and initializes the object. While Python has two stages; tp_new creates the object and performs minimal intialization (or just returns an existing object) and tp_init performs the rest of the initialization.
PEP 253, which you should probably read in its entirety, says:
The difference in responsibilities between the tp_new() slot and the tp_init() slot lies in the invariants they ensure. The tp_new() slot should ensure only the most essential invariants, without which the C code that implements the objects would break. The tp_init() slot should be used for overridable user-specific initializations. Take for example the dictionary type. The implementation has an internal pointer to a hash table which should never be NULL. This invariant is taken care of by the tp_new() slot for dictionaries. The dictionary tp_init() slot, on the other hand, could be used to give the dictionary an initial set of keys and values based on the arguments passed in.
...
You may wonder why the tp_new() slot shouldn't call the tp_init() slot itself. The reason is that in certain circumstances (like support for persistent objects), it is important to be able to create an object of a particular type without initializing it any further than necessary. This may conveniently be done by calling the tp_new() slot without calling tp_init(). It is also possible hat tp_init() is not called, or called more than once -- its operation should be robust even in these anomalous cases.
The entire point of a C++ wrapper is to enable you to write nice C++ code. Say for example that you want your object to have a data member that can only be initialized during its construction. If you create the object during tp_new, then you cannot reinitialize that data member during tp_init. This will probably force you to hold that data member via some kind of a smart pointer and create it during tp_new. This makes the code ugly.
The approach PyCXX takes is to separate object construction into two:
tp_newcreates a dummy object with just a pointer to the C++ object which is createdtp_init. This pointer is initially null.tp_initallocates and constructs the actual C++ object, then updates the pointer in the dummy object created intp_newto point to it. Iftp_initis called more than once it raises a Python exception.
I personally think that the overhead of this approach for my own applications is too high, but it's a legitimate approach. I have my own C++ wrapper around the Python C/API that does all the initialization in tp_new, which is also flawed. There doesn't appear to be a good solution for that.
回答2:
Here is a small C example that shows how Python allocates memory for object of classes derived from C types:
typedef struct
{
PyObject_HEAD
int dummy[100];
} xxx_obj;
It also needs a type object:
static PyTypeObject xxx_type =
{
PyObject_HEAD_INIT(NULL)
};
And a module initialization function that initializes this type:
extern "C"
void init_xxx(void)
{
PyObject* m;
xxx_type.tp_name = "_xxx.xxx";
xxx_type.tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE;
xxx_type.tp_new = tp_new; // IMPORTANT
xxx_type.tp_basicsize = sizeof(xxx_obj); // IMPORTANT
if (PyType_Ready(&xxx_type) < 0)
return;
m = Py_InitModule3("_xxx", NULL, "");
Py_INCREF(&xxx_type);
PyModule_AddObject(m, "xxx", (PyObject *)&xxx_type);
}
What is missing is the implementation of tp_new: The Python docs require that:
The
tp_newfunction should callsubtype->tp_alloc(subtype, nitems)to allocate space for the object
So lets do that and add a few printouts.
static
PyObject *tp_new(PyTypeObject *subtype, PyObject *args, PyObject *kwds)
{
printf("xxx.tp_new():\n\n");
printf("\t subtype=%s\n", subtype->tp_name);
printf("\t subtype->tp_base=%s\n", subtype->tp_base->tp_name);
printf("\t subtype->tp_base->tp_base=%s\n", subtype->tp_base->tp_base->tp_name);
printf("\n");
printf("\t subtype->tp_basicsize=%ld\n", subtype->tp_basicsize);
printf("\t subtype->tp_base->tp_basicsize=%ld\n", subtype->tp_base->tp_basicsize);
printf("\t subtype->tp_base->tp_base->tp_basicsize=%ld\n", subtype->tp_base->tp_base->tp_basicsize);
return subtype->tp_alloc(subtype, 0); // IMPORTANT: memory allocation is done here!
}
Now run a very simple Python program to test it. This program creates a new class derived from xxx, and then creates an object of type derived.
import _xxx
class derived(_xxx.xxx):
def __init__(self):
super(derived, self).__init__()
d = derived()
To create an object of type derived, Python will call its tp_new, which in turn will call its base class' (xxx) tp_new. This call generates the following output (exact numbers depends on the machine architecture):
xxx.tp_new():
subtype=derived
subtype->tp_base=_xxx.xxx
subtype->tp_base->tp_base=object
subtype->tp_basicsize=432
subtype->tp_base->tp_basicsize=416
subtype->tp_base->tp_base->tp_basicsize=16
The subtype argument to tp_new is the type of the object being created (derived), it derives from our C type (_xxx.xxx), which in turns derives from object. The base object is of size 16, which is just PyObject_HEAD, the xxx type has an additional 400 bytes for its dummy member for a total of 416 bytes and the derived Python class adds additional 16 bytes.
Because subtype->tp_basicsize accounts for the sizes of all three levels of the hierarchy (object, xxx and derived) for a total of 432 bytes, the right amount of memory is being allocated.
来源：https://stackoverflow.com/questions/27662074/how-to-tidy-fix-pycxxs-creation-of-new-style-python-extension-class