如何在Python中创建类(即静态)变量或方法?


当前回答

我发现最好的方法是使用另一个类。您可以创建一个对象,然后将其用于其他对象。

class staticFlag:
    def __init__(self):
        self.__success = False
    def isSuccess(self):
        return self.__success
    def succeed(self):
        self.__success = True

class tryIt:
    def __init__(self, staticFlag):
        self.isSuccess = staticFlag.isSuccess
        self.succeed = staticFlag.succeed

tryArr = []
flag = staticFlag()
for i in range(10):
    tryArr.append(tryIt(flag))
    if i == 5:
        tryArr[i].succeed()
    print tryArr[i].isSuccess()

通过上面的示例,我创建了一个名为staticFlag的类。

此类应显示静态变量__success(私有静态变量)。

tryIt类表示我们需要使用的常规类。

现在我为一个标志(staticFlag)创建了一个对象。此标志将作为对所有常规对象的引用发送。

所有这些对象都被添加到列表tryArr中。


此脚本结果:

False
False
False
False
False
True
True
True
True
True

其他回答

静态和类方法

正如其他答案所指出的,静态和类方法可以使用内置的修饰符轻松完成:

class Test(object):

    # regular instance method:
    def my_method(self):
        pass

    # class method:
    @classmethod
    def my_class_method(cls):
        pass

    # static method:
    @staticmethod
    def my_static_method():
        pass

通常,my_method()的第一个参数绑定到类实例对象。相反,my_class_method()的第一个参数绑定到类对象本身(例如,在本例中为Test)。对于my_static_method(),没有任何参数是绑定的,并且有任何参数都是可选的。

“静态变量”

然而,实现“静态变量”(好吧,可变静态变量,无论如何,如果这在术语上不是矛盾的话…)并不是那么直接。正如millerdev在回答中指出的,问题是Python的类属性并不是真正的“静态变量”。考虑:

class Test(object):
    i = 3  # This is a class attribute

x = Test()
x.i = 12   # Attempt to change the value of the class attribute using x instance
assert x.i == Test.i  # ERROR
assert Test.i == 3    # Test.i was not affected
assert x.i == 12      # x.i is a different object than Test.i

这是因为行x.i=12向x添加了一个新的实例属性i,而不是更改测试类i属性的值。

部分预期的静态变量行为,即在多个实例之间同步属性(但不与类本身同步;请参见下面的“gotcha”),可以通过将类属性转换为属性来实现:

class Test(object):

    _i = 3

    @property
    def i(self):
        return type(self)._i

    @i.setter
    def i(self,val):
        type(self)._i = val

## ALTERNATIVE IMPLEMENTATION - FUNCTIONALLY EQUIVALENT TO ABOVE ##
## (except with separate methods for getting and setting i) ##

class Test(object):

    _i = 3

    def get_i(self):
        return type(self)._i

    def set_i(self,val):
        type(self)._i = val

    i = property(get_i, set_i)

现在您可以:

x1 = Test()
x2 = Test()
x1.i = 50
assert x2.i == x1.i  # no error
assert x2.i == 50    # the property is synced

静态变量现在将在所有类实例之间保持同步。

(注意:除非类实例决定定义自己版本的_i!但如果有人决定这样做,他们应该得到什么,不是吗??)

注意,从技术上讲,i仍然不是一个“静态变量”;它是一种属性,是一种特殊类型的描述符。然而,属性行为现在相当于跨所有类实例同步的(可变)静态变量。

不可变的“静态变量”

对于不可变的静态变量行为,只需省略属性setter:

class Test(object):

    _i = 3

    @property
    def i(self):
        return type(self)._i

## ALTERNATIVE IMPLEMENTATION - FUNCTIONALLY EQUIVALENT TO ABOVE ##
## (except with separate methods for getting i) ##

class Test(object):

    _i = 3

    def get_i(self):
        return type(self)._i

    i = property(get_i)

现在尝试设置实例i属性将返回AttributeError:

x = Test()
assert x.i == 3  # success
x.i = 12         # ERROR

需要注意的一点

请注意,上述方法仅适用于类的实例-当使用类本身时,它们将不起作用。例如:

x = Test()
assert x.i == Test.i  # ERROR

# x.i and Test.i are two different objects:
type(Test.i)  # class 'property'
type(x.i)     # class 'int'

assert Test.i==x.i行产生错误,因为Test和x的i属性是两个不同的对象。

许多人会觉得这令人惊讶。然而,它不应该是。如果我们回去检查我们的测试类定义(第二个版本),我们会注意到这一行:

    i = property(get_i) 

显然,Test的成员i必须是属性对象,这是从属性函数返回的对象类型。

如果您发现上述问题令人困惑,那么您很可能仍然从其他语言(例如Java或c++)的角度来考虑它。您应该研究属性对象、Python属性的返回顺序、描述符协议和方法解析顺序(MRO)。

我提出了一个解决上述问题的方法;然而,我强烈建议,至少在你彻底理解为什么断言Test.I=x.I会导致错误之前,不要尝试执行以下操作。

实际静态变量-测试.i==x.i

我在下面介绍(Python3)解决方案,仅供参考。我并不赞同这是一个“好的解决方案”。我怀疑是否真的有必要在Python中模拟其他语言的静态变量行为。然而,不管它是否实际有用,下面的内容应该有助于进一步了解Python的工作原理。

更新:这种尝试真的很糟糕;如果你坚持这样做(提示:请不要这样做;Python是一种非常优雅的语言,不需要强迫它表现得像另一种语言),请使用Ethan Furman答案中的代码。

使用元类模拟其他语言的静态变量行为

元类是类的类。Python中所有类的默认元类(即,我认为Python 2.3之后的“新样式”类)是类型。例如:

type(int)  # class 'type'
type(str)  # class 'type'
class Test(): pass
type(Test) # class 'type'

但是,您可以这样定义自己的元类:

class MyMeta(type): pass

并将其应用于您自己的类,如下所示(仅适用于Python 3):

class MyClass(metaclass = MyMeta):
    pass

type(MyClass)  # class MyMeta

下面是我创建的元类,它试图模拟其他语言的“静态变量”行为。它基本上通过用检查所请求的属性是否为“静态变量”的版本替换默认的getter、setter和deleter来工作。

“静态变量”的目录存储在StaticVarMeta.statics属性中。最初尝试使用替代解析顺序解析所有属性请求。我将其称为“静态解决顺序”或“SRO”。这是通过在给定类(或其父类)的“静态变量”集合中查找所请求的属性来完成的。如果该属性未出现在“SRO”中,则类将返回默认的属性get/set/delete行为(即“MRO”)。

from functools import wraps

class StaticVarsMeta(type):
    '''A metaclass for creating classes that emulate the "static variable" behavior
    of other languages. I do not advise actually using this for anything!!!
    
    Behavior is intended to be similar to classes that use __slots__. However, "normal"
    attributes and __statics___ can coexist (unlike with __slots__). 
    
    Example usage: 
        
        class MyBaseClass(metaclass = StaticVarsMeta):
            __statics__ = {'a','b','c'}
            i = 0  # regular attribute
            a = 1  # static var defined (optional)
            
        class MyParentClass(MyBaseClass):
            __statics__ = {'d','e','f'}
            j = 2              # regular attribute
            d, e, f = 3, 4, 5  # Static vars
            a, b, c = 6, 7, 8  # Static vars (inherited from MyBaseClass, defined/re-defined here)
            
        class MyChildClass(MyParentClass):
            __statics__ = {'a','b','c'}
            j = 2  # regular attribute (redefines j from MyParentClass)
            d, e, f = 9, 10, 11   # Static vars (inherited from MyParentClass, redefined here)
            a, b, c = 12, 13, 14  # Static vars (overriding previous definition in MyParentClass here)'''
    statics = {}
    def __new__(mcls, name, bases, namespace):
        # Get the class object
        cls = super().__new__(mcls, name, bases, namespace)
        # Establish the "statics resolution order"
        cls.__sro__ = tuple(c for c in cls.__mro__ if isinstance(c,mcls))
                        
        # Replace class getter, setter, and deleter for instance attributes
        cls.__getattribute__ = StaticVarsMeta.__inst_getattribute__(cls, cls.__getattribute__)
        cls.__setattr__ = StaticVarsMeta.__inst_setattr__(cls, cls.__setattr__)
        cls.__delattr__ = StaticVarsMeta.__inst_delattr__(cls, cls.__delattr__)
        # Store the list of static variables for the class object
        # This list is permanent and cannot be changed, similar to __slots__
        try:
            mcls.statics[cls] = getattr(cls,'__statics__')
        except AttributeError:
            mcls.statics[cls] = namespace['__statics__'] = set() # No static vars provided
        # Check and make sure the statics var names are strings
        if any(not isinstance(static,str) for static in mcls.statics[cls]):
            typ = dict(zip((not isinstance(static,str) for static in mcls.statics[cls]), map(type,mcls.statics[cls])))[True].__name__
            raise TypeError('__statics__ items must be strings, not {0}'.format(typ))
        # Move any previously existing, not overridden statics to the static var parent class(es)
        if len(cls.__sro__) > 1:
            for attr,value in namespace.items():
                if attr not in StaticVarsMeta.statics[cls] and attr != ['__statics__']:
                    for c in cls.__sro__[1:]:
                        if attr in StaticVarsMeta.statics[c]:
                            setattr(c,attr,value)
                            delattr(cls,attr)
        return cls
    def __inst_getattribute__(self, orig_getattribute):
        '''Replaces the class __getattribute__'''
        @wraps(orig_getattribute)
        def wrapper(self, attr):
            if StaticVarsMeta.is_static(type(self),attr):
                return StaticVarsMeta.__getstatic__(type(self),attr)
            else:
                return orig_getattribute(self, attr)
        return wrapper
    def __inst_setattr__(self, orig_setattribute):
        '''Replaces the class __setattr__'''
        @wraps(orig_setattribute)
        def wrapper(self, attr, value):
            if StaticVarsMeta.is_static(type(self),attr):
                StaticVarsMeta.__setstatic__(type(self),attr, value)
            else:
                orig_setattribute(self, attr, value)
        return wrapper
    def __inst_delattr__(self, orig_delattribute):
        '''Replaces the class __delattr__'''
        @wraps(orig_delattribute)
        def wrapper(self, attr):
            if StaticVarsMeta.is_static(type(self),attr):
                StaticVarsMeta.__delstatic__(type(self),attr)
            else:
                orig_delattribute(self, attr)
        return wrapper
    def __getstatic__(cls,attr):
        '''Static variable getter'''
        for c in cls.__sro__:
            if attr in StaticVarsMeta.statics[c]:
                try:
                    return getattr(c,attr)
                except AttributeError:
                    pass
        raise AttributeError(cls.__name__ + " object has no attribute '{0}'".format(attr))
    def __setstatic__(cls,attr,value):
        '''Static variable setter'''
        for c in cls.__sro__:
            if attr in StaticVarsMeta.statics[c]:
                setattr(c,attr,value)
                break
    def __delstatic__(cls,attr):
        '''Static variable deleter'''
        for c in cls.__sro__:
            if attr in StaticVarsMeta.statics[c]:
                try:
                    delattr(c,attr)
                    break
                except AttributeError:
                    pass
        raise AttributeError(cls.__name__ + " object has no attribute '{0}'".format(attr))
    def __delattr__(cls,attr):
        '''Prevent __sro__ attribute from deletion'''
        if attr == '__sro__':
            raise AttributeError('readonly attribute')
        super().__delattr__(attr)
    def is_static(cls,attr):
        '''Returns True if an attribute is a static variable of any class in the __sro__'''
        if any(attr in StaticVarsMeta.statics[c] for c in cls.__sro__):
            return True
        return False

总结其他人的回答并补充,在python中声明静态方法或变量有很多种方法。

1.使用staticmethod()作为装饰符:

可以简单地在声明的方法(函数)上方放置一个修饰符,使其成为静态方法。例如。

class Calculator:
    @staticmethod
    def multiply(n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 * n2 * Res

print(Calculator.multiply(1, 2, 3, 4))              # 24

2.使用staticmethod()作为参数函数:

此方法可以接收函数类型的参数,并返回传递函数的静态版本。例如。

class Calculator:
    def add(n1, n2, *args):
        return n1 + n2 + sum(args)

Calculator.add = staticmethod(Calculator.add)
print(Calculator.add(1, 2, 3, 4))                   # 10

3.使用classmethod()作为装饰符:

@classmethod对函数的影响与@staticmethod类似,但是这一次,需要在函数中接受一个额外的参数(类似于实例变量的self参数)。例如。

class Calculator:
    num = 0
    def __init__(self, digits) -> None:
        Calculator.num = int(''.join(digits))

    @classmethod
    def get_digits(cls, num):
        digits = list(str(num))
        calc = cls(digits)
        return calc.num

print(Calculator.get_digits(314159))                # 314159

4.使用classmethod()作为参数函数:

@classmethod也可以用作参数函数,以防不想修改类定义。例如。

class Calculator:
    def divide(cls, n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 / n2 / Res

Calculator.divide = classmethod(Calculator.divide)

print(Calculator.divide(15, 3, 5))                  # 1.0

5.直接申报

在所有其他方法外部但在类内部声明的方法/变量自动是静态的。

class Calculator:   
    def subtract(n1, n2, *args):
        return n1 - n2 - sum(args)

print(Calculator.subtract(10, 2, 3, 4))             # 1

整个计划

class Calculator:
    num = 0
    def __init__(self, digits) -> None:
        Calculator.num = int(''.join(digits))
    
    
    @staticmethod
    def multiply(n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 * n2 * Res


    def add(n1, n2, *args):
        return n1 + n2 + sum(args)
    

    @classmethod
    def get_digits(cls, num):
        digits = list(str(num))
        calc = cls(digits)
        return calc.num


    def divide(cls, n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 / n2 / Res


    def subtract(n1, n2, *args):
        return n1 - n2 - sum(args)
    



Calculator.add = staticmethod(Calculator.add)
Calculator.divide = classmethod(Calculator.divide)

print(Calculator.multiply(1, 2, 3, 4))              # 24
print(Calculator.add(1, 2, 3, 4))                   # 10
print(Calculator.get_digits(314159))                # 314159
print(Calculator.divide(15, 3, 5))                  # 1.0
print(Calculator.subtract(10, 2, 3, 4))             # 1

有关掌握Python中的OOP,请参阅Python文档。

与@staticmethod不同,但类变量是类的静态方法,并与所有实例共享。

现在您可以像这样访问它

instance = MyClass()
print(instance.i)

or

print(MyClass.i)

必须为这些变量赋值

我在努力

class MyClass:
  i: str

并在一个方法调用中赋值,在这种情况下,它将不起作用,并将抛出错误

i is not attribute of MyClass

在类定义中声明但不在方法中声明的变量是类或静态变量:

>>> class MyClass:
...     i = 3
...
>>> MyClass.i
3 

正如@millerdev所指出的,这会创建一个类级别i变量,但这与任何实例级别i变量都不同,因此您可以

>>> m = MyClass()
>>> m.i = 4
>>> MyClass.i, m.i
>>> (3, 4)

这与C++和Java不同,但与C#没有太大区别,在C#中,不能使用对实例的引用来访问静态成员。

看看Python教程对类和类对象的主题有什么看法。

@Steve Johnson已经回答了静态方法的问题,也在Python库参考中的“内置函数”中进行了说明。

class C:
    @staticmethod
    def f(arg1, arg2, ...): ...

@beidy推荐classmethods而不是staticmethod,因为该方法随后会接收类类型作为第一个参数。

可以使用静态类变量,但可能不值得这样做。

这里有一个用Python 3编写的概念证明——如果任何确切的细节都是错误的,那么可以对代码进行调整,以匹配静态变量所指的任何内容:


class Static:
    def __init__(self, value, doc=None):
        self.deleted = False
        self.value = value
        self.__doc__ = doc
    def __get__(self, inst, cls=None):
        if self.deleted:
            raise AttributeError('Attribute not set')
        return self.value
    def __set__(self, inst, value):
        self.deleted = False
        self.value = value
    def __delete__(self, inst):
        self.deleted = True

class StaticType(type):
    def __delattr__(cls, name):
        obj = cls.__dict__.get(name)
        if isinstance(obj, Static):
            obj.__delete__(name)
        else:
            super(StaticType, cls).__delattr__(name)
    def __getattribute__(cls, *args):
        obj = super(StaticType, cls).__getattribute__(*args)
        if isinstance(obj, Static):
            obj = obj.__get__(cls, cls.__class__)
        return obj
    def __setattr__(cls, name, val):
        # check if object already exists
        obj = cls.__dict__.get(name)
        if isinstance(obj, Static):
            obj.__set__(name, val)
        else:
            super(StaticType, cls).__setattr__(name, val)

使用中:

class MyStatic(metaclass=StaticType):
    """
    Testing static vars
    """
    a = Static(9)
    b = Static(12)
    c = 3

class YourStatic(MyStatic):
    d = Static('woo hoo')
    e = Static('doo wop')

以及一些测试:

ms1 = MyStatic()
ms2 = MyStatic()
ms3 = MyStatic()
assert ms1.a == ms2.a == ms3.a == MyStatic.a
assert ms1.b == ms2.b == ms3.b == MyStatic.b
assert ms1.c == ms2.c == ms3.c == MyStatic.c
ms1.a = 77
assert ms1.a == ms2.a == ms3.a == MyStatic.a
ms2.b = 99
assert ms1.b == ms2.b == ms3.b == MyStatic.b
MyStatic.a = 101
assert ms1.a == ms2.a == ms3.a == MyStatic.a
MyStatic.b = 139
assert ms1.b == ms2.b == ms3.b == MyStatic.b
del MyStatic.b
for inst in (ms1, ms2, ms3):
    try:
        getattr(inst, 'b')
    except AttributeError:
        pass
    else:
        print('AttributeError not raised on %r' % attr)
ms1.c = 13
ms2.c = 17
ms3.c = 19
assert ms1.c == 13
assert ms2.c == 17
assert ms3.c == 19
MyStatic.c = 43
assert ms1.c == 13
assert ms2.c == 17
assert ms3.c == 19

ys1 = YourStatic()
ys2 = YourStatic()
ys3 = YourStatic()
MyStatic.b = 'burgler'
assert ys1.a == ys2.a == ys3.a == YourStatic.a == MyStatic.a
assert ys1.b == ys2.b == ys3.b == YourStatic.b == MyStatic.b
assert ys1.d == ys2.d == ys3.d == YourStatic.d
assert ys1.e == ys2.e == ys3.e == YourStatic.e
ys1.a = 'blah'
assert ys1.a == ys2.a == ys3.a == YourStatic.a == MyStatic.a
ys2.b = 'kelp'
assert ys1.b == ys2.b == ys3.b == YourStatic.b == MyStatic.b
ys1.d = 'fee'
assert ys1.d == ys2.d == ys3.d == YourStatic.d
ys2.e = 'fie'
assert ys1.e == ys2.e == ys3.e == YourStatic.e
MyStatic.a = 'aargh'
assert ys1.a == ys2.a == ys3.a == YourStatic.a == MyStatic.a