The python incref is define like this

#define Py_INCREF(op) ( \
 _Py_INC_REFTOTAL _Py_REF_DEBUG_COMMA \
 ((PyObject *)(op))->ob_refcnt++)

With multi-core, the incrementation is only is L1 cache and not flushed to memory. Is it a risk to use multi-core or multi-process ?

The python incref is define like this

#define Py_INCREF(op) ( \
 _Py_INC_REFTOTAL _Py_REF_DEBUG_COMMA \
 ((PyObject *)(op))->ob_refcnt++)

With multi-core, the incrementation is only is L1 cache and not flushed to memory.

If two thread increment the refcnt at the same time, in differents core, without a flush to the real memory, for me, it's possible to lost one incrementation.

• ob_refcnt=1
• Core 1 increment, but not flush => ob_refcnt=2 in L1 cache of core 1
• Core 2 increment, but not flush => ob_refcnt=2 in L1 cache of core 2
• WTF

Is it a risk to use multi-core or multi-process ?

The PyObject was declared like this:

typedef struct _object {
 _PyObject_HEAD_EXTRA
 Py_ssize_t ob_refcnt;
 struct _typeobject *ob_type;
} PyObject

But Py_ssize_t is just a ssize_t or intptr_t.

The _Py_atomic* functions and attributes do not seem to be used.

How Python can manage this scenario ? How can it flush the cache between threads ?