如何在Python中创建类(即静态)变量或方法?


当前回答

您可以使用列表或字典来获取实例之间的“静态行为”。

class Fud:

     class_vars = {'origin_open':False}

     def __init__(self, origin = True):
         self.origin = origin
         self.opened = True
         if origin:
             self.class_vars['origin_open'] = True


     def make_another_fud(self):
         ''' Generating another Fud() from the origin instance '''

         return Fud(False)


     def close(self):
         self.opened = False
         if self.origin:
             self.class_vars['origin_open'] = False


fud1 = Fud()
fud2 = fud1.make_another_fud()

print (f"is this the original fud: {fud2.origin}")
print (f"is the original fud open: {fud2.class_vars['origin_open']}")
# is this the original fud: False
# is the original fud open: True

fud1.close()

print (f"is the original fud open: {fud2.class_vars['origin_open']}")
# is the original fud open: False

其他回答

关于静态财产和实例财产,需要注意一件特殊的事情,如下例所示:

class my_cls:
  my_prop = 0

#static property
print my_cls.my_prop  #--> 0

#assign value to static property
my_cls.my_prop = 1 
print my_cls.my_prop  #--> 1

#access static property thru' instance
my_inst = my_cls()
print my_inst.my_prop #--> 1

#instance property is different from static property 
#after being assigned a value
my_inst.my_prop = 2
print my_cls.my_prop  #--> 1
print my_inst.my_prop #--> 2

这意味着在将值分配给实例属性之前,如果我们试图通过“实例”访问属性,则使用静态值。python类中声明的每个属性在内存中总是有一个静态槽。

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

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。

当在任何成员方法之外定义某个成员变量时,该变量可以是静态的,也可以是非静态的,具体取决于该变量的表达方式。

CLASSNAME.var是静态变量INSTANCENAME.var不是静态变量。类内部的self.var不是静态变量。未定义类成员函数内的var。

例如:

#!/usr/bin/python

class A:
    var=1

    def printvar(self):
        print "self.var is %d" % self.var
        print "A.var is %d" % A.var


    a = A()
    a.var = 2
    a.printvar()

    A.var = 3
    a.printvar()

结果是

self.var is 2
A.var is 1
self.var is 2
A.var is 3

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。