是否有一种方法可以方便地在Python中定义类c结构?我厌倦了写这样的东西:
class MyStruct():
def __init__(self, field1, field2, field3):
self.field1 = field1
self.field2 = field2
self.field3 = field3
是否有一种方法可以方便地在Python中定义类c结构?我厌倦了写这样的东西:
class MyStruct():
def __init__(self, field1, field2, field3):
self.field1 = field1
self.field2 = field2
self.field3 = field3
当前回答
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
>>>
其他回答
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。
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
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……
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。
如果您没有3.7的@dataclass,并且需要可变性,那么下面的代码可能适合您。它是非常自文档化和ide友好的(自动完成),防止编写两次内容,易于扩展,并且非常简单地测试所有实例变量都被完全初始化:
class Params():
def __init__(self):
self.var1 : int = None
self.var2 : str = None
def are_all_defined(self):
for key, value in self.__dict__.items():
assert (value is not None), "instance variable {} is still None".format(key)
return True
params = Params()
params.var1 = 2
params.var2 = 'hello'
assert(params.are_all_defined)