深入源码解析Python中的对象与类型
对象
对象, 在C语言是如何实现的?
Python中对象分为两类: 定长(int等), 非定长(list/dict等)
所有对象都有一些相同的东西, 源码中定义为PyObject和PyVarObject, 两个定义都有一个共同的头部定义PyObject_HEAD(其实PyVarObject有自己的头部定义PyObject_VAR_HEAD, 但其实际上用的也是PyObject_HEAD).
源码位置: Include/object.h
PyObject_HEAD
Python 内部, 每个对象拥有相同的头部.
定义
/* PyObject_HEAD defines the initial segment of every PyObject. */ #define PyObject_HEAD \ _PyObject_HEAD_EXTRA \ Py_ssize_t ob_refcnt; \ struct _typeobject *ob_type;
说明
1. _PyObject_HEAD_EXTRA
先忽略, 双向链表结构, 后面垃圾回收再说
2. Py_ssize_t ob_refcnt
Py_ssize_t在编译时确定, 整型
ob_refcnt, 引用计数, 跟Python的内存管理机制相关(基于引用计数的垃圾回收)
3. struct _typeobject *ob_type
*ob_type 指向类型对象的指针(指向_typeobject结构体)
决定了这个对象的类型!
PyObject
定义
typedef struct _object {
PyObject_HEAD
} PyObject;
说明
1. 依赖关系
PyObject -> PyObject_HEAD
结构
PyVarObject
定义
typedef struct {
PyObject_VAR_HEAD
} PyVarObject;
#define PyObject_VAR_HEAD \
PyObject_HEAD \
Py_ssize_t ob_size; /* Number of items in variable part */
说明
1. 依赖关系
PyVarObject -> PyObject_VAR_HEAD -> PyObject_HEAD
2.Py_ssize_t ob_size
ob_size, 变长对象容纳的元素个数
结构
代码关系
几个方法
跟对象相关的方法
#define Py_REFCNT(ob) (((PyObject*)(ob))->ob_refcnt)
读取引用计数
#define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)
获取对象类型
#define Py_SIZE(ob) (((PyVarObject*)(ob))->ob_size)
读取元素个数(len)
跟引用计数相关的方法
Py_INCREF(op) 增加对象引用计数
Py_DECREF(op) 减少对象引用计数, 如果计数位0, 调用_Py_Dealloc
_Py_Dealloc(op) 调用对应类型的 tp_dealloc 方法(每种类型回收行为不一样的, 各种缓存池机制, 后面看)
其他
几个参数涉及
ob_refcnt 引用计数, 与内存管理/垃圾回收相关
ob_type 类型, 涉及Python的类型系统
类型
一个例子
>>> a = 1 >>> a 1 >>> type(a) <type 'int'> #等价的两个 >>> type(type(a)) <type 'type'> >>> type(int) <type 'type'> #还是等价的两个 >>> type(type(type(a))) <type 'type'> >>> type(type(int)) <type 'type'>
我们反向推导一个int对象是怎么生成的.
1. 首先, 定义一种类型叫PyTypeObject
代码位置 Include/object.h
定义
typedef struct _typeobject {
/* MARK: base, 注意, 是个变长对象*/
PyObject_VAR_HEAD
const char *tp_name; /* For printing, in format "<module>.<name>" */ //类型名
Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */ // 创建该类型对象时分配的内存空间大小
// 一堆方法定义, 函数和指针
/* Methods to implement standard operations */
printfunc tp_print;
hashfunc tp_hash;
/* Method suites for standard classes */
PyNumberMethods *tp_as_number; // 数值对象操作
PySequenceMethods *tp_as_sequence; // 序列对象操作
PyMappingMethods *tp_as_mapping; // 字典对象操作
// 一堆属性定义
....
} PyTypeObject;
说明
1. PyObject_VAR_HEAD
变长对象
2. const char *tp_name
tp_name, 类型名字符串数组
所有Type都是PyTypeObject的"实例": PyType_Type/PyInt_Type
2. 然后, 用PyTypeObject初始化得到一个对象PyType_Type
代码位置 Objects/typeobject.c
定义
PyTypeObject PyType_Type = {
PyVarObject_HEAD_INIT(&PyType_Type, 0)
"type", /* tp_name */
sizeof(PyHeapTypeObject), /* tp_basicsize */
sizeof(PyMemberDef), /* tp_itemsize */
(destructor)type_dealloc, /* tp_dealloc */
// type对象的方法和属性初始化值
.....
};
说明
1. tp_name
类型名, 这里是"type"
2. PyVarObject_HEAD_INIT(&PyType_Type, 0)
PyVarObject_HEAD_INIT, 这个方法在 Include/object.h中,
等价于
ob_refcnt = 1
*ob_type = &PyType_Type
ob_size = 0
即, PyType_Type的类型是其本身!
结构
第一张图, 箭头表示实例化(google doc用不是很熟找不到对应类型的箭头)
第二张图, 箭头表示指向
使用
# 1. int 的 类型 是`type` >>> type(int) <type 'type'> # 2. type 的类型 还是`type`, 对应上面说明第二点 >>> type(type(int)) <type 'type'>
注意: 无论任何时候, ob_type指向的是 PyTypeObject的实例: PyType_Type/PyInt_Type...
3. 再然后, 定义具体的类型, 这里以PyInt_Type为例子
代码位置 Objects/intobject.c
定义
PyTypeObject PyInt_Type = {
PyVarObject_HEAD_INIT(&PyType_Type, 0)
"int",
sizeof(PyIntObject),
0,
// int类型的相关方法和属性值
....
(hashfunc)int_hash, /* tp_hash */
};
说明
1. "int"
PyInt_Type的类型名是int
2.PyVarObject_HEAD_INIT(&PyType_Type, 0)
PyInt_Type的
*ob_type = &PyType_Type
结构
使用
>>> type(1) <type 'int'> >>> type(type(1)) <type 'type'>
4. 最后, 生成一个整数对象int
代码位置 Include/intobject.h
定义
typedef struct {
PyObject_HEAD
long ob_ival;
} PyIntObject;
结构
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