我能想到的最干净的方法是使用一个类装饰器，它可以让你声明一个静态类，并将其重写为一个具有正常命名属性的结构体:

from as_struct import struct

@struct
class Product():
    name = 'unknown product'
    quantity = -1
    sku = '-'

# create instance
p = Product('plush toy', sku='12-345-6789')

# check content:
p.name     # plush toy
p.quantity # -1 
p.sku      # 12-345-6789

使用以下装饰器代码:

def struct(struct_class):
    # create a new init
    def struct_init(self, *args, **kwargs):
        i = 0 # we really don't need enumerate() here...
        for value in args:
            name = member_names[i]
            default_value = member_values[i]
            setattr(self, name, value if value is not None else default_value)
            i += 1 # ...we just need to inc an int
        for key,value in kwargs.items():
            i = member_names.index(key)
            default_value = member_values[i]
            setattr(self, key, value if value is not None else default_value)
    # extract the struct members
    member_names = []
    member_values = []
    for attr_name in dir(struct_class):
        if not attr_name.startswith('_'):
            value = getattr(struct_class, attr_name)
            if not callable(value):
                member_names.append(attr_name)
                member_values.append(value)
    # rebind and return
    struct_class.init = struct_init
    return struct_class

它的工作原理是获取类，提取字段名及其默认值，然后重写类的__init__函数，根据知道哪个参数索引映射到哪个属性名来设置self属性。

我能想到的最干净的方法是使用一个类装饰器，它可以让你声明一个静态类，并将其重写为一个具有正常命名属性的结构体:

from as_struct import struct

@struct
class Product():
    name = 'unknown product'
    quantity = -1
    sku = '-'

# create instance
p = Product('plush toy', sku='12-345-6789')

# check content:
p.name     # plush toy
p.quantity # -1 
p.sku      # 12-345-6789

使用以下装饰器代码:

def struct(struct_class):
    # create a new init
    def struct_init(self, *args, **kwargs):
        i = 0 # we really don't need enumerate() here...
        for value in args:
            name = member_names[i]
            default_value = member_values[i]
            setattr(self, name, value if value is not None else default_value)
            i += 1 # ...we just need to inc an int
        for key,value in kwargs.items():
            i = member_names.index(key)
            default_value = member_values[i]
            setattr(self, key, value if value is not None else default_value)
    # extract the struct members
    member_names = []
    member_values = []
    for attr_name in dir(struct_class):
        if not attr_name.startswith('_'):
            value = getattr(struct_class, attr_name)
            if not callable(value):
                member_names.append(attr_name)
                member_values.append(value)
    # rebind and return
    struct_class.init = struct_init
    return struct_class

它的工作原理是获取类，提取字段名及其默认值，然后重写类的__init__函数，根据知道哪个参数索引映射到哪个属性名来设置self属性。

每当我需要一个“行为像字典一样的即时数据对象”(我不会想到C结构体!)，我就会想到这个可爱的hack:

class Map(dict):
    def __init__(self, **kwargs):
        super(Map, self).__init__(**kwargs)
        self.__dict__ = self

现在你可以说:

struct = Map(field1='foo', field2='bar', field3=42)

self.assertEquals('bar', struct.field2)
self.assertEquals(42, struct['field3'])

当你需要一个“不是类的数据包”的时候，非常方便，当命名元组是不可理解的……

这里的一些答案非常详尽。我找到的最简单的选项是(from: http://norvig.com/python-iaq.html):)

class Struct:
    "A structure that can have any fields defined."
    def __init__(self, **entries): self.__dict__.update(entries)

初始化:

>>> options = Struct(answer=42, linelen=80, font='courier')
>>> options.answer
42

添加更多的:

>>> options.cat = "dog"
>>> options.cat
dog

编辑:对不起，没有看到这个例子已经进一步。

NamedTuple很舒服。但是没有人共享性能和存储。

from typing import NamedTuple
import guppy  # pip install guppy
import timeit


class User:
    def __init__(self, name: str, uid: int):
        self.name = name
        self.uid = uid


class UserSlot:
    __slots__ = ('name', 'uid')

    def __init__(self, name: str, uid: int):
        self.name = name
        self.uid = uid


class UserTuple(NamedTuple):
    # __slots__ = ()  # AttributeError: Cannot overwrite NamedTuple attribute __slots__
    name: str
    uid: int


def get_fn(obj, attr_name: str):
    def get():
        getattr(obj, attr_name)
    return get

if 'memory test':
    obj = [User('Carson', 1) for _ in range(1000000)]      # Cumulative: 189138883
    obj_slot = [UserSlot('Carson', 1) for _ in range(1000000)]          # 77718299  <-- winner
    obj_namedtuple = [UserTuple('Carson', 1) for _ in range(1000000)]   # 85718297
    print(guppy.hpy().heap())  # Run this function individually. 
    """
    Index  Count   %     Size   % Cumulative  % Kind (class / dict of class)
     0 1000000    24 112000000 34 112000000  34 dict of __main__.User
     1 1000000    24 64000000  19 176000000  53 __main__.UserTuple
     2 1000000    24 56000000  17 232000000  70 __main__.User
     3 1000000    24 56000000  17 288000000  87 __main__.UserSlot
     ...
    """

if 'performance test':
    obj = User('Carson', 1)
    obj_slot = UserSlot('Carson', 1)
    obj_tuple = UserTuple('Carson', 1)

    time_normal = min(timeit.repeat(get_fn(obj, 'name'), repeat=20))
    print(time_normal)  # 0.12550550000000005

    time_slot = min(timeit.repeat(get_fn(obj_slot, 'name'), repeat=20))
    print(time_slot)  # 0.1368690000000008

    time_tuple = min(timeit.repeat(get_fn(obj_tuple, 'name'), repeat=20))
    print(time_tuple)  # 0.16006120000000124

    print(time_tuple/time_slot)  # 1.1694481584580898  # The slot is almost 17% faster than NamedTuple on Windows. (Python 3.7.7)

如果你的__dict__没有被使用，请在__slots__(更高的性能和存储)和NamedTuple(清晰的阅读和使用)之间选择。

您可以查看此链接(插槽的使用 )来获取更多的__slots__信息。

这里有一个快速而肮脏的技巧:

>>> ms = Warning()
>>> ms.foo = 123
>>> ms.bar = 'akafrit'

它是如何工作的?它只是重用内置类警告(从异常派生)，并使用它，因为它是你自己定义的类。

优点是您不需要首先导入或定义任何东西，“警告”是一个简短的名称，并且它还清楚地表明您正在做一些肮脏的事情，不应该在其他地方使用，而应该在您的小脚本中使用。

顺便说一下，我试图找到一些更简单的东西，如ms = object()，但不能(最后一个例子是不工作)。如果你有的话，我很感兴趣。