如何在Python中声明常量?
在Java中,我们做:
public static final String CONST_NAME = "Name";
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
我知道这是一个老问题,但由于新的解决方案仍在添加,我想使可能的解决方案列表更加完整。你可以通过从类中继承属性来实现实例中的常量,如下所示:
class ConstantError(Exception):
pass # maybe give nice error message
class AllowConstants:
_constants = None
_class_constants = None
def __init__(self):
self._constants = {}
if self._class_constants is not None:
self._constants.update(self._class_constants)
def constant(self, name, value):
assert isinstance(name, str)
assert self._constants is not None, "AllowConstants was not initialized"
if name in self._constants or name in self.__dict__:
raise ConstantError(name)
self._constants[name] = value
def __getattr__(self, attr):
if attr in self._constants:
return self._constants[attr]
raise AttributeError(attr)
def __setattr__(self, attr, val):
if self._constants is None:
# not finished initialization
self.__dict__[attr] = val
else:
if attr in self._constants:
raise ConstantError(attr)
else:
self.__dict__[attr] = val
def __dir__(self):
return super().__dir__() + list(self._constants.keys())
子类化this时,你创建的常量将受到保护:
class Example(AllowConstants):
def __init__(self, a, b):
super().__init__()
self.constant("b", b)
self.a = a
def try_a(self, value):
self.a = value
def try_b(self, value):
self.b = value
def __str__(self):
return str({"a": self.a, "b": self.b})
def __repr__(self):
return self.__str__()
example = Example(1, 2)
print(example) # {'a': 1, 'b': 2}
example.try_a(5)
print(example) # {'a': 5, 'b': 2}
example.try_b(6) # ConstantError: b
example.a = 7
print(example) # {'a': 7, 'b': 2}
example.b = 8 # ConstantError: b
print(hasattr(example, "b")) # True
# To show that constants really do immediately become constant:
class AnotherExample(AllowConstants):
def __init__(self):
super().__init__()
self.constant("a", 2)
print(self.a)
self.a=3
AnotherExample() # 2 ConstantError: a
# finally, for class constants:
class YetAnotherExample(Example):
_class_constants = {
'BLA': 3
}
def __init__(self, a, b):
super().__init__(a,b)
def try_BLA(self, value):
self.BLA = value
ex3 = YetAnotherExample(10, 20)
ex3.BLA # 3
ex3.try_BLA(10) # ConstantError: BLA
ex3.BLA = 4 # ConstantError: BLA
常量是局部的(从AllowConstants继承的类的每个实例都有自己的常量),只要它们没有被重新赋值,就像普通的属性一样,并且编写从这个继承的类允许或多或少与支持常量的语言相同的风格。
此外,如果您想通过直接访问实例来防止任何人更改值。_constants,您可以使用其他答案中建议的许多不允许这样做的容器之一。最后,如果你真的觉得有必要,你可以阻止人们设置所有的实例。通过AllowConstants的更多属性访问,将_constants赋给一个新字典。(当然,这些都不是非常python化的,但这不是重点)。
编辑(因为使python非python化是一个有趣的游戏):为了使继承更容易一点,你可以修改AllowConstants如下:
class AllowConstants:
_constants = None
_class_constants = None
def __init__(self):
self._constants = {}
self._update_class_constants()
def __init_subclass__(cls):
"""
Without this, it is necessary to set _class_constants in any subclass of any class that has class constants
"""
if cls._class_constants is not None:
#prevent trouble where _class_constants is not overwritten
possible_cases = cls.__mro__[1:-1] #0 will have cls and -1 will have object
for case in possible_cases:
if cls._class_constants is case._class_constants:
cls._class_constants = None
break
def _update_class_constants(self):
"""
Help with the inheritance of class constants
"""
for superclass in self.__class__.__mro__:
if hasattr(superclass, "_class_constants"):
sccc = superclass._class_constants
if sccc is not None:
for key in sccc:
if key in self._constants:
raise ConstantError(key)
self._constants.update(sccc)
def constant(self, name, value):
assert isinstance(name, str)
assert self._constants is not None, "AllowConstants was not initialized"
if name in self._constants or name in self.__dict__:
raise ConstantError(name)
self._constants[name] = value
def __getattr__(self, attr):
if attr in self._constants:
return self._constants[attr]
raise AttributeError(attr)
def __setattr__(self, attr, val):
if self._constants is None:
# not finished initialization
self.__dict__[attr] = val
else:
if attr in self._constants:
raise ConstantError(attr)
else:
self.__dict__[attr] = val
def __dir__(self):
return super().__dir__() + list(self._constants.keys())
这样你就可以:
class Example(AllowConstants):
_class_constants = {
"BLA": 2
}
def __init__(self, a, b):
super().__init__()
self.constant("b", b)
self.a = a
def try_a(self, value):
self.a = value
def try_b(self, value):
self.b = value
def __str__(self):
return str({"a": self.a, "b": self.b})
def __repr__(self):
return self.__str__()
class ChildExample1(Example):
_class_constants = {
"BLI": 88
}
class ChildExample2(Example):
_class_constants = {
"BLA": 44
}
example = ChildExample1(2,3)
print(example.BLA) # 2
example.BLA = 8 # ConstantError BLA
print(example.BLI) # 88
example.BLI = 8 # ConstantError BLI
example = ChildExample2(2,3) # ConstantError BLA
其他回答
这里是我创建的一些习语的集合,试图改进一些已有的答案。
我知道常量的使用不是python式的,你不应该在家里这样做!
然而,Python是如此动态的语言!这个论坛展示了如何创建看起来和感觉起来像常量的构造。这个答案的主要目的是探索语言可以表达什么。
请不要对我太苛刻。
为了了解更多细节,我写了一篇关于这些习语的博客。
在这篇文章中,我将调用一个常量变量来引用一个常量值(不可变或其他)。此外,我说,当一个变量引用了一个客户机代码无法更新的可变对象时,它的值就被冻结了。
常量空间(SpaceConstants)
这个习惯用法创建了一个看起来像常量变量的名称空间(又名SpaceConstants)。它是Alex Martelli对代码片段的修改,以避免使用模块对象。具体地说,这种修改使用了我称之为类工厂的东西,因为在SpaceConstants函数中定义了一个名为SpaceConstants的类,并返回了它的一个实例。
我在stackoverflow和一篇博客文章中探讨了如何使用类工厂在Python中实现基于策略的设计。
def SpaceConstants():
def setattr(self, name, value):
if hasattr(self, name):
raise AttributeError(
"Cannot reassign members"
)
self.__dict__[name] = value
cls = type('SpaceConstants', (), {
'__setattr__': setattr
})
return cls()
sc = SpaceConstants()
print(sc.x) # raise "AttributeError: 'SpaceConstants' object has no attribute 'x'"
sc.x = 2 # bind attribute x
print(sc.x) # print "2"
sc.x = 3 # raise "AttributeError: Cannot reassign members"
sc.y = {'name': 'y', 'value': 2} # bind attribute y
print(sc.y) # print "{'name': 'y', 'value': 2}"
sc.y['name'] = 'yprime' # mutable object can be changed
print(sc.y) # print "{'name': 'yprime', 'value': 2}"
sc.y = {} # raise "AttributeError: Cannot reassign members"
一个冻结值的空间(SpaceFrozenValues)
下一个习惯用法是对SpaceConstants的修改,其中冻结了引用的可变对象。这个实现利用了setattr和getattr函数之间的共享闭包。可变对象的值由函数共享闭包内的变量缓存定义复制和引用。它形成了我所说的可变对象的闭包保护副本。
在使用这种习惯用法时必须小心,因为getattr通过执行深度复制来返回缓存的值。该操作可能对大型对象的性能产生重大影响!
from copy import deepcopy
def SpaceFrozenValues():
cache = {}
def setattr(self, name, value):
nonlocal cache
if name in cache:
raise AttributeError(
"Cannot reassign members"
)
cache[name] = deepcopy(value)
def getattr(self, name):
nonlocal cache
if name not in cache:
raise AttributeError(
"Object has no attribute '{}'".format(name)
)
return deepcopy(cache[name])
cls = type('SpaceFrozenValues', (),{
'__getattr__': getattr,
'__setattr__': setattr
})
return cls()
fv = SpaceFrozenValues()
print(fv.x) # AttributeError: Object has no attribute 'x'
fv.x = 2 # bind attribute x
print(fv.x) # print "2"
fv.x = 3 # raise "AttributeError: Cannot reassign members"
fv.y = {'name': 'y', 'value': 2} # bind attribute y
print(fv.y) # print "{'name': 'y', 'value': 2}"
fv.y['name'] = 'yprime' # you can try to change mutable objects
print(fv.y) # print "{'name': 'y', 'value': 2}"
fv.y = {} # raise "AttributeError: Cannot reassign members"
常量空间(ConstantSpace)
这个习惯用法是常量变量或ConstantSpace的不可变名称空间。它结合了Jon Betts在stackoverflow中给出的非常简单的答案和类工厂。
def ConstantSpace(**args):
args['__slots__'] = ()
cls = type('ConstantSpace', (), args)
return cls()
cs = ConstantSpace(
x = 2,
y = {'name': 'y', 'value': 2}
)
print(cs.x) # print "2"
cs.x = 3 # raise "AttributeError: 'ConstantSpace' object attribute 'x' is read-only"
print(cs.y) # print "{'name': 'y', 'value': 2}"
cs.y['name'] = 'yprime' # mutable object can be changed
print(cs.y) # print "{'name': 'yprime', 'value': 2}"
cs.y = {} # raise "AttributeError: 'ConstantSpace' object attribute 'x' is read-only"
cs.z = 3 # raise "AttributeError: 'ConstantSpace' object has no attribute 'z'"
冰冻空间(FrozenSpace)
这个习惯用法是冻结变量或FrozenSpace的不可变名称空间。它通过关闭生成的FrozenSpace类使每个变量成为受保护的属性,从前面的模式派生而来。
from copy import deepcopy
def FreezeProperty(value):
cache = deepcopy(value)
return property(
lambda self: deepcopy(cache)
)
def FrozenSpace(**args):
args = {k: FreezeProperty(v) for k, v in args.items()}
args['__slots__'] = ()
cls = type('FrozenSpace', (), args)
return cls()
fs = FrozenSpace(
x = 2,
y = {'name': 'y', 'value': 2}
)
print(fs.x) # print "2"
fs.x = 3 # raise "AttributeError: 'FrozenSpace' object attribute 'x' is read-only"
print(fs.y) # print "{'name': 'y', 'value': 2}"
fs.y['name'] = 'yprime' # try to change mutable object
print(fs.y) # print "{'name': 'y', 'value': 2}"
fs.y = {} # raise "AttributeError: 'FrozenSpace' object attribute 'x' is read-only"
fs.z = 3 # raise "AttributeError: 'FrozenSpace' object has no attribute 'z'"
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)。
Python没有常量。
也许最简单的替代方法是为它定义一个函数:
def MY_CONSTANT():
return 42
MY_CONSTANT()现在拥有常量的所有功能(加上一些讨厌的大括号)。
(这一段本来是对那些提到namedtuple的答案的注释,但它太长了,不适合注释,所以,就这样吧。)
上面提到的命名元组方法绝对是创新的。不过,为了完整起见,在其官方文档的NamedTuple部分的末尾,它如下所示:
枚举常量可以用命名元组实现,但使用简单的类声明更简单高效: 类的状态: 打开,待处理,关闭= range(3)
换句话说,官方文档更倾向于使用一种实用的方式,而不是实际实现只读行为。我想这是Python的另一个禅宗的例子:
简单比复杂好。 实用胜过纯粹。
在我的例子中,我需要不可变字节数组来实现包含许多文字数字的加密库,我想确保这些数字是常量。
这个答案是有效的,但是尝试重赋bytearray元素不会引发错误。
def const(func):
'''implement const decorator'''
def fset(self, val):
'''attempting to set a const raises `ConstError`'''
class ConstError(TypeError):
'''special exception for const reassignment'''
pass
raise ConstError
def fget(self):
'''get a const'''
return func()
return property(fget, fset)
class Consts(object):
'''contain all constants'''
@const
def C1():
'''reassignment to C1 fails silently'''
return bytearray.fromhex('deadbeef')
@const
def pi():
'''is immutable'''
return 3.141592653589793
常量是不可变的,但是常量bytearray赋值默默失败:
>>> c = Consts()
>>> c.pi = 6.283185307179586 # (https://en.wikipedia.org/wiki/Tau_(2%CF%80))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "consts.py", line 9, in fset
raise ConstError
__main__.ConstError
>>> c.C1[0] = 0
>>> c.C1[0]
222
>>> c.C1
bytearray(b'\xde\xad\xbe\xef')
一种更强大、更简单,甚至可能更“python化”的方法涉及使用memoryview对象(<= python-2.6中的缓冲区对象)。
import sys
PY_VER = sys.version.split()[0].split('.')
if int(PY_VER[0]) == 2:
if int(PY_VER[1]) < 6:
raise NotImplementedError
elif int(PY_VER[1]) == 6:
memoryview = buffer
class ConstArray(object):
'''represent a constant bytearray'''
def __init__(self, init):
'''
create a hidden bytearray and expose a memoryview of that bytearray for
read-only use
'''
if int(PY_VER[1]) == 6:
self.__array = bytearray(init.decode('hex'))
else:
self.__array = bytearray.fromhex(init)
self.array = memoryview(self.__array)
def __str__(self):
return str(self.__array)
def __getitem__(self, *args, **kwargs):
return self.array.__getitem__(*args, **kwargs)
ConstArray项赋值是一个TypeError:
>>> C1 = ConstArray('deadbeef')
>>> C1[0] = 0
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'ConstArray' object does not support item assignment
>>> C1[0]
222