在Python中似乎有很多方法来定义单例对象。对Stack Overflow是否有一致的意见?
当前回答
我对此非常不确定,但我的项目使用'惯例单例'(不是强制单例),也就是说,如果我有一个名为DataController的类,我在同一个模块中定义这个:
_data_controller = None
def GetDataController():
global _data_controller
if _data_controller is None:
_data_controller = DataController()
return _data_controller
它并不优雅,因为它足足有六行。但是我所有的单例都使用这个模式,而且它至少是非常显式的(这是python的)。
其他回答
这是我自己对单例对象的实现。你所要做的就是布置课堂;为了获得单例,你必须使用Instance方法。这里有一个例子:
@Singleton
class Foo:
def __init__(self):
print 'Foo created'
f = Foo() # Error, this isn't how you get the instance of a singleton
f = Foo.instance() # Good. Being explicit is in line with the Python Zen
g = Foo.instance() # Returns already created instance
print f is g # True
下面是代码:
class Singleton:
"""
A non-thread-safe helper class to ease implementing singletons.
This should be used as a decorator -- not a metaclass -- to the
class that should be a singleton.
The decorated class can define one `__init__` function that
takes only the `self` argument. Also, the decorated class cannot be
inherited from. Other than that, there are no restrictions that apply
to the decorated class.
To get the singleton instance, use the `instance` method. Trying
to use `__call__` will result in a `TypeError` being raised.
"""
def __init__(self, decorated):
self._decorated = decorated
def instance(self):
"""
Returns the singleton instance. Upon its first call, it creates a
new instance of the decorated class and calls its `__init__` method.
On all subsequent calls, the already created instance is returned.
"""
try:
return self._instance
except AttributeError:
self._instance = self._decorated()
return self._instance
def __call__(self):
raise TypeError('Singletons must be accessed through `instance()`.')
def __instancecheck__(self, inst):
return isinstance(inst, self._decorated)
正如公认的答案所说,最常用的方法是只使用一个模块。
考虑到这一点,下面是一个概念的证明:
def singleton(cls):
obj = cls()
# Always return the same object
cls.__new__ = staticmethod(lambda cls: obj)
# Disable __init__
try:
del cls.__init__
except AttributeError:
pass
return cls
有关__new__的更多详细信息,请参阅Python数据模型。
例子:
@singleton
class Duck(object):
pass
if Duck() is Duck():
print "It works!"
else:
print "It doesn't work!"
注:
为此,您必须使用new-style类(派生自object)。 单例在定义时初始化,而不是在第一次使用时初始化。 这只是一个简单的例子。我从未在产品代码中实际使用过它,也不打算这样做。
我对此非常不确定,但我的项目使用'惯例单例'(不是强制单例),也就是说,如果我有一个名为DataController的类,我在同一个模块中定义这个:
_data_controller = None
def GetDataController():
global _data_controller
if _data_controller is None:
_data_controller = DataController()
return _data_controller
它并不优雅,因为它足足有六行。但是我所有的单例都使用这个模式,而且它至少是非常显式的(这是python的)。
Python文档涵盖了这些内容:
class Singleton(object):
def __new__(cls, *args, **kwds):
it = cls.__dict__.get("__it__")
if it is not None:
return it
cls.__it__ = it = object.__new__(cls)
it.init(*args, **kwds)
return it
def init(self, *args, **kwds):
pass
我可能会重写成这样:
class Singleton(object):
"""Use to create a singleton"""
def __new__(cls, *args, **kwds):
"""
>>> s = Singleton()
>>> p = Singleton()
>>> id(s) == id(p)
True
"""
it_id = "__it__"
# getattr will dip into base classes, so __dict__ must be used
it = cls.__dict__.get(it_id, None)
if it is not None:
return it
it = object.__new__(cls)
setattr(cls, it_id, it)
it.init(*args, **kwds)
return it
def init(self, *args, **kwds):
pass
class A(Singleton):
pass
class B(Singleton):
pass
class C(A):
pass
assert A() is A()
assert B() is B()
assert C() is C()
assert A() is not B()
assert C() is not B()
assert C() is not A()
它应该是相对干净的扩展:
class Bus(Singleton):
def init(self, label=None, *args, **kwds):
self.label = label
self.channels = [Channel("system"), Channel("app")]
...
好吧,我知道,单胞胎可能是好的,也可能是坏的。这是我的实现,我只是扩展了一个经典的方法,在里面引入一个缓存,并产生许多不同类型的实例,或者许多相同类型的实例,但具有不同的参数。
我称它为Singleton_group,因为它将相似的实例分组在一起,并防止创建具有相同参数的相同类的对象:
# Peppelinux's cached singleton
class Singleton_group(object):
__instances_args_dict = {}
def __new__(cls, *args, **kwargs):
if not cls.__instances_args_dict.get((cls.__name__, args, str(kwargs))):
cls.__instances_args_dict[(cls.__name__, args, str(kwargs))] = super(Singleton_group, cls).__new__(cls, *args, **kwargs)
return cls.__instances_args_dict.get((cls.__name__, args, str(kwargs)))
# It's a dummy real world use example:
class test(Singleton_group):
def __init__(self, salute):
self.salute = salute
a = test('bye')
b = test('hi')
c = test('bye')
d = test('hi')
e = test('goodbye')
f = test('goodbye')
id(a)
3070148780L
id(b)
3070148908L
id(c)
3070148780L
b == d
True
b._Singleton_group__instances_args_dict
{('test', ('bye',), '{}'): <__main__.test object at 0xb6fec0ac>,
('test', ('goodbye',), '{}'): <__main__.test object at 0xb6fec32c>,
('test', ('hi',), '{}'): <__main__.test object at 0xb6fec12c>}
每个对象都携带单例缓存…这可能是邪恶的,但对一些人来说很有用:)
推荐文章
- 插入一行到熊猫数据框架
- 要列出Pandas DataFrame列
- 在Django模型中存储电话号码的最佳方法是什么?
- 从导入的模块中模拟函数
- 滚动或滑动窗口迭代器?
- python的方法找到最大值和它的索引在一个列表?
- 如何读取文件的前N行?
- 如何删除matplotlib中的顶部和右侧轴?
- 解析.py文件,读取AST,修改它,然后写回修改后的源代码
- 工厂模式和策略模式之间的区别是什么?
- Visual Studio Code:如何调试Python脚本的参数
- 使用元组/列表等等。从输入vs直接引用类型如list/tuple/etc
- 结合conda环境。Yml和PIP requirements.txt
- 将命名元组转换为字典
- 如何使x轴和y轴的刻度相等呢?