我还想添加一个使用插槽的解决方案:

class Point:
    __slots__ = ["x", "y"]
    def __init__(self, x, y):
        self.x = x
        self.y = y

Definitely check the documentation for slots but a quick explanation of slots is that it is python's way of saying: "If you can lock these attributes and only these attributes into the class such that you commit that you will not add any new attributes once the class is instantiated (yes you can add new attributes to a class instance, see example below) then I will do away with the large memory allocation that allows for adding new attributes to a class instance and use just what I need for these slotted attributes".

添加属性到类实例的例子(因此不使用插槽):

class Point:
    def __init__(self, x, y):
        self.x = x
        self.y = y

p1 = Point(3,5)
p1.z = 8
print(p1.z)

输出:8

尝试向使用插槽的类实例添加属性的示例:

class Point:
    __slots__ = ["x", "y"]
    def __init__(self, x, y):
        self.x = x
        self.y = y

p1 = Point(3,5)
p1.z = 8

'Point'对象没有属性'z'

这可以有效地作为结构体工作，并且比类使用更少的内存(就像结构体一样，尽管我没有研究具体有多少内存)。如果要创建对象的大量实例且不需要添加属性，建议使用slot。点对象就是一个很好的例子，因为很可能会实例化许多点来描述一个数据集。

一本字典怎么样?

就像这样:

myStruct = {'field1': 'some val', 'field2': 'some val'}

然后你可以使用这个来操作值:

print myStruct['field1']
myStruct['field2'] = 'some other values'

值不一定是字符串。它们可以是其他任何物体。

下面结构的解决方案是受namedtuple实现和前面一些答案的启发。然而，与namedtuple不同的是，它的值是可变的，但就像c风格的结构体在名称/属性中是不可变的，而普通的类或dict不是。

_class_template = """\
class {typename}:
def __init__(self, *args, **kwargs):
    fields = {field_names!r}

    for x in fields:
        setattr(self, x, None)            

    for name, value in zip(fields, args):
        setattr(self, name, value)

    for name, value in kwargs.items():
        setattr(self, name, value)            

def __repr__(self):
    return str(vars(self))

def __setattr__(self, name, value):
    if name not in {field_names!r}:
        raise KeyError("invalid name: %s" % name)
    object.__setattr__(self, name, value)            
"""

def struct(typename, field_names):

    class_definition = _class_template.format(
        typename = typename,
        field_names = field_names)

    namespace = dict(__name__='struct_%s' % typename)
    exec(class_definition, namespace)
    result = namespace[typename]
    result._source = class_definition

    return result

用法:

Person = struct('Person', ['firstname','lastname'])
generic = Person()
michael = Person('Michael')
jones = Person(lastname = 'Jones')


In [168]: michael.middlename = 'ben'
Traceback (most recent call last):

  File "<ipython-input-168-b31c393c0d67>", line 1, in <module>
michael.middlename = 'ben'

  File "<string>", line 19, in __setattr__

KeyError: 'invalid name: middlename'

我还想添加一个使用插槽的解决方案:

class Point:
    __slots__ = ["x", "y"]
    def __init__(self, x, y):
        self.x = x
        self.y = y

Definitely check the documentation for slots but a quick explanation of slots is that it is python's way of saying: "If you can lock these attributes and only these attributes into the class such that you commit that you will not add any new attributes once the class is instantiated (yes you can add new attributes to a class instance, see example below) then I will do away with the large memory allocation that allows for adding new attributes to a class instance and use just what I need for these slotted attributes".

添加属性到类实例的例子(因此不使用插槽):

class Point:
    def __init__(self, x, y):
        self.x = x
        self.y = y

p1 = Point(3,5)
p1.z = 8
print(p1.z)

输出:8

尝试向使用插槽的类实例添加属性的示例:

class Point:
    __slots__ = ["x", "y"]
    def __init__(self, x, y):
        self.x = x
        self.y = y

p1 = Point(3,5)
p1.z = 8

'Point'对象没有属性'z'

这可以有效地作为结构体工作，并且比类使用更少的内存(就像结构体一样，尽管我没有研究具体有多少内存)。如果要创建对象的大量实例且不需要添加属性，建议使用slot。点对象就是一个很好的例子，因为很可能会实例化许多点来描述一个数据集。

有一个python包正是用于此目的。看到cstruct2py

cstruct2py是一个纯python库，用于从C代码生成python类，并使用它们来打包和解包数据。该库可以解析C头文件(结构体、联合、枚举和数组声明)，并在python中模拟它们。生成的python类可以解析和打包数据。

例如:

typedef struct {
  int x;
  int y;
} Point;

after generating pythonic class...
p = Point(x=0x1234, y=0x5678)
p.packed == "\x34\x12\x00\x00\x78\x56\x00\x00"

如何使用

首先，我们需要生成python结构体:

import cstruct2py
parser = cstruct2py.c2py.Parser()
parser.parse_file('examples/example.h')

现在我们可以从C代码中导入所有的名称:

parser.update_globals(globals())

我们也可以直接这样做:

A = parser.parse_string('struct A { int x; int y;};')

使用C代码中的类型和定义

a = A()
a.x = 45
print a
buf = a.packed
b = A(buf)
print b
c = A('aaaa11112222', 2)
print c
print repr(c)

输出将是:

{'x':0x2d, 'y':0x0}
{'x':0x2d, 'y':0x0}
{'x':0x31316161, 'y':0x32323131}
A('aa111122', x=0x31316161, y=0x32323131)

克隆

对于克隆cstruct2py运行:

git clone https://github.com/st0ky/cstruct2py.git --recursive

这可能有点晚了，但我使用Python元类(下面也有装饰器版本)做了一个解决方案。

当__init__在运行时被调用时，它会获取每个参数及其值，并将它们作为实例变量分配给你的类。通过这种方式，您可以创建一个类结构的类，而不必手动分配每个值。

我的例子没有错误检查，所以更容易遵循。

class MyStruct(type):
    def __call__(cls, *args, **kwargs):
        names = cls.__init__.func_code.co_varnames[1:]

        self = type.__call__(cls, *args, **kwargs)

        for name, value in zip(names, args):
            setattr(self , name, value)

        for name, value in kwargs.iteritems():
            setattr(self , name, value)
        return self 

这是它的行动。

>>> class MyClass(object):
    __metaclass__ = MyStruct
    def __init__(self, a, b, c):
        pass


>>> my_instance = MyClass(1, 2, 3)
>>> my_instance.a
1
>>> 

我把它发布在reddit上，/u/matchu发布了一个更干净的装饰版本。我鼓励您使用它，除非您想扩展元类版本。

>>> def init_all_args(fn):
    @wraps(fn)
    def wrapped_init(self, *args, **kwargs):
        names = fn.func_code.co_varnames[1:]

        for name, value in zip(names, args):
            setattr(self, name, value)

        for name, value in kwargs.iteritems():
            setattr(self, name, value)

    return wrapped_init

>>> class Test(object):
    @init_all_args
    def __init__(self, a, b):
        pass


>>> a = Test(1, 2)
>>> a.a
1
>>>