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。

我发现做到这一点的最好方法是使用自定义字典类，如本文所述:https://stackoverflow.com/a/14620633/8484485

如果需要iPython自动补全支持，只需像这样定义dir()函数:

class AttrDict(dict):
    def __init__(self, *args, **kwargs):
        super(AttrDict, self).__init__(*args, **kwargs)
        self.__dict__ = self
    def __dir__(self):
        return self.keys()

然后像这样定义你的伪结构(这个是嵌套的)

my_struct=AttrDict ({
    'com1':AttrDict ({
        'inst':[0x05],
        'numbytes':2,
        'canpayload':False,
        'payload':None
    })
})

然后你可以像这样访问my_struct中的值:

打印(my_struct.com1.inst)

= > [5]

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。

你可以通过以下方式在python中访问C-Style struct。

class cstruct:
    var_i = 0
    var_f = 0.0
    var_str = ""

如果你只想使用cstruct的对象

obj = cstruct()
obj.var_i = 50
obj.var_f = 50.00
obj.var_str = "fifty"
print "cstruct: obj i=%d f=%f s=%s" %(obj.var_i, obj.var_f, obj.var_str)

如果你想创建一个cstruct对象的数组

obj_array = [cstruct() for i in range(10)]
obj_array[0].var_i = 10
obj_array[0].var_f = 10.00
obj_array[0].var_str = "ten"

#go ahead and fill rest of array instaces of struct

#print all the value
for i in range(10):
    print "cstruct: obj_array i=%d f=%f s=%s" %(obj_array[i].var_i, obj_array[i].var_f, obj_array[i].var_str)

注意: 请使用你的struct名称，而不是'cstruct'名称 请定义结构的成员变量，而不是var_i, var_f, var_str。

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。

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。