这里有一个解决方案，它使用一个类(从未实例化)来保存数据。我喜欢这种方式涉及很少的输入，不需要任何额外的软件包等。

class myStruct:
    field1 = "one"
    field2 = "2"

您可以稍后根据需要添加更多字段:

myStruct.field3 = 3

要获取值，可以像往常一样访问字段:

>>> myStruct.field1
'one'

还可以按位置将初始化参数传递给实例变量

# Abstract struct class       
class Struct:
    def __init__ (self, *argv, **argd):
        if len(argd):
            # Update by dictionary
            self.__dict__.update (argd)
        else:
            # Update by position
            attrs = filter (lambda x: x[0:2] != "__", dir(self))
            for n in range(len(argv)):
                setattr(self, attrs[n], argv[n])

# Specific class
class Point3dStruct (Struct):
    x = 0
    y = 0
    z = 0

pt1 = Point3dStruct()
pt1.x = 10

print pt1.x
print "-"*10

pt2 = Point3dStruct(5, 6)

print pt2.x, pt2.y
print "-"*10

pt3 = Point3dStruct (x=1, y=2, z=3)
print pt3.x, pt3.y, pt3.z
print "-"*10

就我个人而言，我也喜欢这种变体。它扩展了@dF的答案。

class struct:
    def __init__(self, *sequential, **named):
        fields = dict(zip(sequential, [None]*len(sequential)), **named)
        self.__dict__.update(fields)
    def __repr__(self):
        return str(self.__dict__)

它支持两种初始化模式(可以混合使用):

# Struct with field1, field2, field3 that are initialized to None.
mystruct1 = struct("field1", "field2", "field3") 
# Struct with field1, field2, field3 that are initialized according to arguments.
mystruct2 = struct(field1=1, field2=2, field3=3)

而且，它打印得更好:

print(mystruct2)
# Prints: {'field3': 3, 'field1': 1, 'field2': 2}

使用命名元组，该元组被添加到Python 2.6标准库中的collections模块中。如果你需要支持Python 2.4，也可以使用Raymond Hettinger的命名元组配方。

它适用于基本示例，但也适用于稍后可能遇到的一些边缘情况。你上面的片段可以写成:

from collections import namedtuple
MyStruct = namedtuple("MyStruct", "field1 field2 field3")

新创建的类型可以这样使用:

m = MyStruct("foo", "bar", "baz")

你也可以使用命名参数:

m = MyStruct(field1="foo", field2="bar", field3="baz")

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。

您可以子类化标准库中可用的C结构。ctypes模块提供了一个Structure类。文档中的例子:

>>> from ctypes import *
>>> class POINT(Structure):
...     _fields_ = [("x", c_int),
...                 ("y", c_int)]
...
>>> point = POINT(10, 20)
>>> print point.x, point.y
10 20
>>> point = POINT(y=5)
>>> print point.x, point.y
0 5
>>> POINT(1, 2, 3)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
ValueError: too many initializers
>>>
>>> class RECT(Structure):
...     _fields_ = [("upperleft", POINT),
...                 ("lowerright", POINT)]
...
>>> rc = RECT(point)
>>> print rc.upperleft.x, rc.upperleft.y
0 5
>>> print rc.lowerright.x, rc.lowerright.y
0 0
>>>