Python中的 type() 和 __class__
发布者：
Yun Yuan
最近在公司内部的问答系统上有同事问了一个问题：Python中的type()和__class__有什么差别？
>>> class Foo(object):
pass
>>> class Bar(object):
pass
>>> class Brion(object):
pass
>>> class ASML(object):
__class__ = Foo
>>> b = Bar()
>>> a = ASML()
Case 1
>>> b.__class__, type(b)
(<class '__main__.Bar'>, <class '__main__.Bar'>)
>>>
>>> b.__class__ = Foo
>>>
>>> b.__class__, type(b)
(<class '__main__.Foo'>, <class '__main__.Foo'>)
Case 2
>>> a.__class__, type(a)
(<class '__main__.Foo'>, <class '__main__.ASML'>)
>>>
>>> a.__class__ = Brion
>>>
>>> a.__class__, type(a)
(<class '__main__.Brion'>, <class '__main__.ASML'>)
大家看出Case 1和Case 2的差别了吧。问题来了：
1. type(obj)到底做了些什么事情？
2. 为什么a在改变__class__后，type(a)还是ASML呢？
为了解决这些问题，我们需要深入Python源代码。以下源代码来自Python 2.7.8。
Python Object
Python中一切皆对象。所有对象的数据结构都以一个PyObject_HEAD开头。
object.h
typedef struct _object {
PyObject_HEAD
} PyObject;
/* PyObject_HEAD defines the initial segment of every PyObject. */
#define PyObject_HEAD \
_PyObject_HEAD_EXTRA \
Py_ssize_t ob_refcnt; \
struct _typeobject *ob_type;
这里的ob_refcnt是用来做引用计数的，而ob_type则是对象所对应的type对象。
type对象包含了很多关于对象的元信息：类型名字(tp_name)，创建该类型对象时分配内存空间大小的信息(tp_basicsize和tp_itemsize)，一些操作信息(tp_call, tp_new等)，还有其他如__mro__(tp_mro), __bases__(tp_bases)等。
object.h
typedef struct _typeobject {
PyObject_VAR_HEAD
const char *tp_name; /* For printing, in format "<module>.<name>" */
Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */
...
/* More standard operations (here for binary compatibility) */
ternaryfunc tp_call;
...
/* Attribute descriptor and subclassing stuff */
PyObject *tp_dict;
newfunc tp_new;
PyObject *tp_bases;
PyObject *tp_mro; /* method resolution order */
PyObject *tp_subclasses;
...
...
} PyTypeObject;
对于对象f = Foo()来说，它的ob_type就是Foo, 而Foo的ob_type则是type。
type(obj)到底做了些什么事情
上面提到的每个对象都有的ob_type其实就是type(obj)返回的对象。
我们看下运行type(obj)时调用到的一系列函数。
abstract.c
PyObject *
PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw)
{
ternaryfunc call;
if ((call = func->ob_type->tp_call) != NULL) {
PyObject *result;
if (Py_EnterRecursiveCall(" while calling a Python object"))
return NULL;
result = (*call)(func, arg, kw);
...
return result;
}
...
return NULL;
}
这里的func是obj的ob_type，以f = Foo()为例的话就是Foo。那func->ob_type当然就是type了。
typeobject.c
PyTypeObject PyType_Type = {
PyVarObject_HEAD_INIT(&PyType_Type, 0)
"type", /* tp_name */
...
(ternaryfunc)type_call, /* tp_call */
...
type_new, /* tp_new */
...
}
从上面PyType_Type的定义可以看到type的tp_call就是type_call函数：
typeobject.c
static PyObject *
type_call(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
PyObject *obj;
if (type->tp_new == NULL) {
PyErr_Format(PyExc_TypeError,
"cannot create '%.100s' instances",
type->tp_name);
return NULL;
}
obj = type->tp_new(type, args, kwds);
if (obj != NULL) {
/* Ugly exception: when the call was type(something),
don't call tp_init on the result. */
if (type == &PyType_Type &&
PyTuple_Check(args) && PyTuple_GET_SIZE(args) == 1 &&
(kwds == NULL ||
(PyDict_Check(kwds) && PyDict_Size(kwds) == 0)))
return obj; // Yun: type(obj) returns from here
/* If the returned object is not an instance of type,
it won't be initialized. */
if (!PyType_IsSubtype(obj->ob_type, type))
return obj;
type = obj->ob_type;
if (PyType_HasFeature(type, Py_TPFLAGS_HAVE_CLASS) &&
type->tp_init != NULL &&
type->tp_init(obj, args, kwds) < 0) {
Py_DECREF(obj);
obj = NULL;
}
}
return obj; // Yun: type(cls, bases, dict) returns from here
type_call中先调用tp_new指向的函数(type_new)，然后再做分支。对type(obj)调用来说就是直接返回tp_new得到的对象。而对type(cls, bases, dict)来说还会调用tp_init指向的函数，这在自定义metaclass时会用到。
typeobject.c
static PyObject *
type_new(PyTypeObject *metatype, PyObject *args, PyObject *kwds)
{
...
/* Special case: type(x) should return x->ob_type */
{
const Py_ssize_t nargs = PyTuple_GET_SIZE(args);
const Py_ssize_t nkwds = kwds == NULL ? 0 : PyDict_Size(kwds);
if (PyType_CheckExact(metatype) && nargs == 1 && nkwds == 0) {
PyObject *x = PyTuple_GET_ITEM(args, 0);
Py_INCREF(Py_TYPE(x));
return (PyObject *) Py_TYPE(x);
}
...
}
...
}
object.h
#define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)
可见type(obj)其实就是返回对象的ob_type。
为什么a在改变__class__后，type(a)还是ASML呢
要回答这个问题，我们要先回顾下通过obj.xxx查找对象的 attribute 时的搜索顺序：
1. type对象及其基类的__dict__。如果是 data descriptor，返回这个 data descriptor的 __get__ 结果
2. obj的__dict__
3. 第一步中找到的如果是 non-data descriptor， 返回这个 non-data descriptor的 __get__ 结果
4. type对象中的__dict__，也就是直接返回第一步中找到的对象
obj.__class__就是一个 attribute 查找。
typeobject.c
static PyGetSetDef object_getsets[] = {
{"__class__", object_get_class, object_set_class,
PyDoc_STR("the object's class")},
{0}
};
PyTypeObject PyBaseObject_Type = {
PyVarObject_HEAD_INIT(&PyType_Type, 0)
"object", /* tp_name */
...
PyObject_GenericGetAttr, /* tp_getattro */
PyObject_GenericSetAttr, /* tp_setattro */
...
object_getsets, /* tp_getset */
...
};
来看下f = Foo(); f.__class__;中的函数调用链：
object.c
PyObject *
PyObject_GetAttr(PyObject *v, PyObject *name)
{
PyTypeObject *tp = Py_TYPE(v);
...
if (tp->tp_getattro != NULL)
return (*tp->tp_getattro)(v, name);
...
return NULL;
}
这里的v就是f, 而tp就是Foo, tp->tp_getattro就是PyObject_GenericGetAttr函数。
object.c
PyObject *
PyObject_GenericGetAttr(PyObject *obj, PyObject *name)
{
return _PyObject_GenericGetAttrWithDict(obj, name, NULL);
}
PyObject *
_PyObject_GenericGetAttrWithDict(PyObject *obj, PyObject *name, PyObject *dict)
{
PyTypeObject *tp = Py_TYPE(obj);
PyObject *descr = NULL;
PyObject *res = NULL;
...
descr = _PyType_Lookup(tp, name);
Py_XINCREF(descr);
f = NULL;
if (descr != NULL &&
PyType_HasFeature(descr->ob_type, Py_TPFLAGS_HAVE_CLASS)) {
f = descr->ob_type->tp_descr_get;
if (f != NULL && PyDescr_IsData(descr)) {
res = f(descr, obj, (PyObject *)obj->ob_type);
Py_DECREF(descr);
goto done;
}
}
...
return res;
}
PyObject *
_PyType_Lookup(PyTypeObject *type, PyObject *name)
{
Py_ssize_t i, n;
PyObject *mro, *res, *base, *dict;
unsigned int h;
...
/* Look in tp_dict of types in MRO */
mro = type->tp_mro;
...
res = NULL;
assert(PyTuple_Check(mro));
n = PyTuple_GET_SIZE(mro);
for (i = 0; i < n; i++) {
base = PyTuple_GET_ITEM(mro, i);
if (PyClass_Check(base))
dict = ((PyClassObject *)base)->cl_dict;
else {
assert(PyType_Check(base));
dict = ((PyTypeObject *)base)->tp_dict;
}
assert(dict && PyDict_Check(dict));
res = PyDict_GetItem(dict, name);
if (res != NULL)
break;
}
...
return res;
}
_PyObject_GenericGetAttrWithDict中先调用_PyType_Lookup从Foo的tp_mro中查到__class__属性(来自Foo的基类object)，该属性是一个data descriptor，最终调用了object_get_class。
typeobject.c
static PyObject *
object_get_class(PyObject *self, void *closure)
{
Py_INCREF(Py_TYPE(self));
return (PyObject *)(Py_TYPE(self));
}
从object_get_class函数可以看出，对于f = Foo(); f.__class__;来说也是返回的Foo对象的ob_type。这就解释了Case 1中为什么type(b)和b.__class__是相等的。
___
那为什么Case 2中的type(a)和a.__class__不相等呢？
因为Case 1中没有自定义__class__，所以查找__class__时在Bar中没找到，接着就去Bar的基类object中找，正好object中定义了一个__class__的 data descriptor, 就返回这个。
而在Case 2中我们自定义了__class__，所以在ASML.__dict__中找到有这个 attribute 后就返回了，不会再去找mro中的下一个(object)。但是这里找到的这个 attribute 不是 data descriptor，根据前面提到的 attribute 搜索顺序，我们接着在a.__dict__中找，也没有，那就直接返回ASML中的找到的那个了。
___
为什么设置__class__后，Case 1和Case 2有差别
obj.xxx = yyy 设置attribute时的顺序
1. 先从type对象及其基类的__dict__中查找该 attribute，找到就返回。如果找到的是 data descriptor，则用该 data descriptor的__set__来设置
2. 否则添加到obj.__dict__里
Case 1中得到的__class__是一个 data descriptor，给它赋值实际上调用的是object_set_class函数。
typeobject.c
static int
object_set_class(PyObject *self, PyObject *value, void *closure)
{
PyTypeObject *oldto = Py_TYPE(self);
PyTypeObject *newto;
...
newto = (PyTypeObject *)value;
...
if (compatible_for_assignment(newto, oldto, "__class__")) {
Py_INCREF(newto);
Py_TYPE(self) = newto;
Py_DECREF(oldto);
return 0;
}
else {
return -1;
}
}
从该函数的实现可以看到b.__class__ = Foo实际上会把b的ob_type设为Foo。所以赋值后type(b)和b.__class__都跟着变了。
>>> b.__dict__
{}
>>> Bar.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'Bar' objects>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'Bar' objects>, '__doc__': None})
>>>
>>> b.__class__ = Foo
>>>
>>> b.__class__, type(b)
(<class '__main__.Foo'>, <class '__main__.Foo'>)
>>> b.__dict__
{}
>>> Bar.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'Bar' objects>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'Bar' objects>, '__doc__': None})
而Case 2中得到的__class__不是 data descriptor。所以a.__class__ = Foo会在a.__dict__中添加一条记录，而a的ob_type不会变，ASML.__dict__也不会变。
>>> a.__dict__
{}
>>> ASML.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'ASML' objects>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'ASML' objects>, '__class__': <class '__main__.Foo'>, '__doc__': None})
>>>
>>> a.__class__ = Brion
>>>
>>> a.__dict__
{'__class__': <class '__main__.Brion'>}
>>> ASML.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'ASML' objects>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'ASML' objects>, '__class__': <class '__main__.Foo'>, '__doc__': None})
以上的讨论都是基于new style class。对于old style class来说, type()不等于__class__:
>>> class A():
pass
>>> a = A()
>>> a.__class__, type(a)
(<class __main__.A at 0x0270CFB8>, <type 'instance'>)
另外一个关于 isintance(obj, cls) 的问题
>>> class Foo(object):
pass
>>> class ASML(object):
__class__ = Foo
>>> a = ASML()
>>> isinstance(a, Foo)
True
>>> isinstance(a, ASML)
True
为什么这里的两个isinstance都返回True呢？
object.h
#define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)
#bltinmodule.c
static PyMethodDef builtin_methods[] = {
...
{"isinstance", builtin_isinstance, METH_VARARGS, isinstance_doc},
...
}
static PyObject *
builtin_isinstance(PyObject *self, PyObject *args)
{
PyObject *inst;
PyObject *cls;
int retval;
if (!PyArg_UnpackTuple(args, "isinstance", 2, 2, &inst, &cls))
return NULL;
retval = PyObject_IsInstance(inst, cls);
if (retval < 0)
return NULL;
return PyBool_FromLong(retval);
}
最终isinstance(obj, cls)会调用PyObject_IsInstance。
abstract.c
int
PyObject_IsInstance(PyObject *inst, PyObject *cls) // Yun: "isinstance(obj, cls)" will call it
{
static PyObject *name = NULL;
/* Quick test for an exact match */
if (Py_TYPE(inst) == (PyTypeObject *)cls) // Yun: "isinstacne(b, ASML)" returns True
return 1;
...
if (!(PyClass_Check(cls) || PyInstance_Check(cls))) {
PyObject *checker;
checker = _PyObject_LookupSpecial(cls, "__instancecheck__", &name);
...
res = PyObject_CallFunctionObjArgs(checker, inst, NULL); // Yun: "isinstance(b, Foo)" call recursive_isinstance() and returns True
if (res != NULL) {
ok = PyObject_IsTrue(res);
...
}
return ok;
}
return recursive_isinstance(inst, cls);
}
static int
recursive_isinstance(PyObject *inst, PyObject *cls)
{
...
static PyObject *__class__ = NULL;
int retval = 0;
if (__class__ == NULL) {
__class__ = PyString_InternFromString("__class__");
if (__class__ == NULL)
return -1;
}
...
if (PyClass_Check(cls) && PyInstance_Check(inst)) {
...
}
else if (PyType_Check(cls)) {
retval = PyObject_TypeCheck(inst, (PyTypeObject *)cls);
if (retval == 0) {
PyObject *c = PyObject_GetAttr(inst, __class__);
...
retval = PyType_IsSubtype(
(PyTypeObject *)c,
(PyTypeObject *)cls); // Yun: Both "c" and "cls" are "Foo" here
}
...
return retval;
}
从__instancecheck__ 到 recursive_isinstance:
typeobject.c
static PyMethodDef type_methods[] = {
{"mro", (PyCFunction)mro_external, METH_NOARGS,
PyDoc_STR("mro() -> list\nreturn a type's method resolution order")},
{"__subclasses__", (PyCFunction)type_subclasses, METH_NOARGS,
PyDoc_STR("__subclasses__() -> list of immediate subclasses")},
{"__instancecheck__", type___instancecheck__, METH_O,
PyDoc_STR("__instancecheck__() -> bool\ncheck if an object is an instance")},
{"__subclasscheck__", type___subclasscheck__, METH_O,
PyDoc_STR("__subclasscheck__() -> bool\ncheck if a class is a subclass")},
{0}
};
static PyObject *
type___instancecheck__(PyObject *type, PyObject *inst)
{
switch (_PyObject_RealIsInstance(inst, type)) {
case -1:
return NULL;
case 0:
Py_RETURN_FALSE;
default:
Py_RETURN_TRUE;
}
}
int
_PyObject_RealIsInstance(PyObject *inst, PyObject *cls)
{
return recursive_isinstance(inst, cls);
}
简单来说就是isinstance(obj, cls)会先看ob_type，然后在看__class__。
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