如何在Python中声明常量?

在Java中,我们做:

public static final String CONST_NAME = "Name";

当前回答

PEP 591有“final”限定符。执行取决于类型检查器。

所以你可以这样做:

MY_CONSTANT: Final = 12407

注意:Final关键字仅适用于Python 3.8版本

其他回答

我将创建一个重写基对象类的__setattr__方法的类,并用它包装我的常量,注意我使用的是python 2.7:

class const(object):
    def __init__(self, val):
        super(const, self).__setattr__("value", val)
    def __setattr__(self, name, val):
        raise ValueError("Trying to change a constant value", self)

换行字符串:

>>> constObj = const("Try to change me")
>>> constObj.value
'Try to change me'
>>> constObj.value = "Changed"
Traceback (most recent call last):
   ...
ValueError: Trying to change a constant value
>>> constObj2 = const(" or not")
>>> mutableObj = constObj.value + constObj2.value
>>> mutableObj #just a string
'Try to change me or not'

这很简单,但如果你想像使用非常量对象一样使用常量(不使用constObj.value),它会更密集一些。这可能会导致问题,所以最好保留.value来显示和知道您正在使用常量进行操作(尽管可能不是最“python”的方式)。

我们可以创建一个描述符对象。

class Constant:
  def __init__(self,value=None):
    self.value = value
  def __get__(self,instance,owner):
    return self.value
  def __set__(self,instance,value):
    raise ValueError("You can't change a constant")

1)如果我们想在实例级使用常量,那么:

class A:
  NULL = Constant()
  NUM = Constant(0xFF)

class B:
  NAME = Constant('bar')
  LISTA = Constant([0,1,'INFINITY'])

>>> obj=A()
>>> print(obj.NUM)  #=> 255
>>> obj.NUM =100

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: You can't change a constant

2)如果我们只想在类级别上创建常量,我们可以使用元类作为常量(描述符对象)的容器;所有下降的类将继承我们的常量(我们的描述符对象),没有任何可以修改的风险。

# metaclass of my class Foo
class FooMeta(type): pass

# class Foo
class Foo(metaclass=FooMeta): pass

# I create constants in my metaclass
FooMeta.NUM = Constant(0xff)
FooMeta.NAME = Constant('FOO')

>>> Foo.NUM   #=> 255
>>> Foo.NAME  #=> 'FOO'
>>> Foo.NUM = 0 #=> ValueError: You can't change a constant

如果我创建一个Foo的子类,这个类将继承常量,而不可能修改它们

class Bar(Foo): pass

>>> Bar.NUM  #=> 255
>>> Bar.NUM = 0  #=> ValueError: You can't change a constant

下面是一个“Constants”类的实现,它创建具有只读(常量)属性的实例。例如,可以使用Nums。PI来获得一个已初始化为3.14159的值,Nums。PI = 22引发异常。

# ---------- Constants.py ----------
class Constants(object):
    """
    Create objects with read-only (constant) attributes.
    Example:
        Nums = Constants(ONE=1, PI=3.14159, DefaultWidth=100.0)
        print 10 + Nums.PI
        print '----- Following line is deliberate ValueError -----'
        Nums.PI = 22
    """

    def __init__(self, *args, **kwargs):
        self._d = dict(*args, **kwargs)

    def __iter__(self):
        return iter(self._d)

    def __len__(self):
        return len(self._d)

    # NOTE: This is only called if self lacks the attribute.
    # So it does not interfere with get of 'self._d', etc.
    def __getattr__(self, name):
        return self._d[name]

    # ASSUMES '_..' attribute is OK to set. Need this to initialize 'self._d', etc.
    #If use as keys, they won't be constant.
    def __setattr__(self, name, value):
        if (name[0] == '_'):
            super(Constants, self).__setattr__(name, value)
        else:
            raise ValueError("setattr while locked", self)

if (__name__ == "__main__"):
    # Usage example.
    Nums = Constants(ONE=1, PI=3.14159, DefaultWidth=100.0)
    print 10 + Nums.PI
    print '----- Following line is deliberate ValueError -----'
    Nums.PI = 22

感谢@MikeGraham的FrozenDict,我将其作为一个起点。更改后,使用语法不再是Nums['ONE'],而是Nums.ONE。

感谢@Raufio的回答,对于覆盖__ setattr __的想法。

或者要了解更多功能的实现,请参阅@Hans_meine的实现 named_constants在GitHub

您可以将一个常量包装在numpy数组中,将其标记为仅写,并始终通过下标0调用它。

import numpy as np

# declare a constant
CONSTANT = 'hello'

# put constant in numpy and make read only
CONSTANT = np.array([CONSTANT])
CONSTANT.flags.writeable = False
# alternatively: CONSTANT.setflags(write=0)

# call our constant using 0 index    
print 'CONSTANT %s' % CONSTANT[0]

# attempt to modify our constant with try/except
new_value = 'goodbye'
try:
    CONSTANT[0] = new_value
except:
    print "cannot change CONSTANT to '%s' it's value '%s' is immutable" % (
        new_value, CONSTANT[0])

# attempt to modify our constant producing ValueError
CONSTANT[0] = new_value



>>>
CONSTANT hello
cannot change CONSTANT to 'goodbye' it's value 'hello' is immutable
Traceback (most recent call last):
  File "shuffle_test.py", line 15, in <module>
    CONSTANT[0] = new_value
ValueError: assignment destination is read-only

当然,这只保护numpy的内容,而不是变量“CONSTANT”本身;你仍然可以:

CONSTANT = 'foo'

和CONSTANT会改变,然而,这将很快抛出TypeError第一次在脚本中调用CONSTANT[0]。

尽管……我想如果你在某个时候把它改成

CONSTANT = [1,2,3]

现在你不会再得到TypeError了。嗯……

https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.setflags.html

我忍不住要提供我自己的极简元类实现(这可能是前面元类答案的变体)。

常量存储在容器类中(不需要实例化)。值只能设置一次,但设置后不能更改(或删除)。

就我个人而言,我目前还没有这个用例,但这是一个有趣的练习。

class MetaConstant(type):
    ''' Metaclass that allows underlying class to store constants at class-level (subclass instance not needed).
        Non-existent attributes of underlying class (constants) can be set initially, but cannot be changed or deleted.
    '''

    def __setattr__(klass, attr, value):
        'If attribute (constant) doesn\'t exist, set value. If attribute exists, raise AttributeError.'
        if hasattr(klass, attr):
            raise AttributeError(f'Can\'t change the value of the constant {klass.__name__}.{attr} to {value}'
                                 f' (the value of {klass.__name__}.{attr} is already set to'
                                 f' {getattr(klass, attr)}).')
        super().__setattr__(attr, value)

    def __delattr__(klass, attr):
        if hasattr(klass, attr):
            raise AttributeError(f'Can\'t delete constant {klass.__name__}.{attr}'
                                 f' (set to {getattr(klass, attr)}).')


class Constants(metaclass=MetaConstant):
    'Container class for constants. No instantiation required.'
    #pass               # uncomment if no constants set upon class creation
    B = 'Six'           # sets Constants.B to 'Six'


Constants.B = 6         # AttributeError
del Constants.B         # AttributeError

Constants.A = 'Five'    # sets Constants.A to 'Five'
Constants.A = 5         # AttributeError
del Constants.A         # AttributeError

请随意提出改进建议。