单例模式
保证一个类仅有一个实例,并提供一个访问它的全局访问点。
来看看tornado.IOLoop中的单例模式:
class IOLoop(object):
    @staticmethod
    def instance():
        """Returns a global `IOLoop` instance.
        Most applications have a single, global `IOLoop` running on the
        main thread.  Use this method to get this instance from
        another thread.  To get the current thread's `IOLoop`, use `current()`.
        """
        if not hasattr(IOLoop, "_instance"):
            with IOLoop._instance_lock:
                if not hasattr(IOLoop, "_instance"):
                    # New instance after double check
                    IOLoop._instance = IOLoop()
        return IOLoop._instance
为什么这里要double check?
简单的单例模式
先来看看代码:
class Singleton(object):
    @staticmathod
    def instance():
        if not hasattr(Singleton, '_instance'):
            Singleton._instance = Singleton()
        return Singleton._instance
在 Python 里,可以在真正的构造函数__new__里做文章:
class Singleton(object):
    def __new__(cls, *args, **kwargs):
        if not hasattr(cls, '_instance'):
            cls._instance = super(Singleton, cls).__new__(cls, *args, **kwargs)
        return cls._instance
这种情况看似还不错,但是不能保证在多线程的环境下仍然好用,看图:
 出现了多线程之后,这明显就是行不通的。
出现了多线程之后,这明显就是行不通的。
上锁使线程同步
上锁后的代码:
import threading
class Singleton(object):
    _instance_lock = threading.Lock()
    @staticmethod
    def instance():
        with Singleton._instance_lock:
            if not hasattr(Singleton, '_instance'):
                Singleton._instance = Singleton()
        return Singleton._instance
这里确实是解决了多线程的情况,但是我们只有实例化的时候需要上锁,其它时候Singleton._instance已经存在了,不需要锁了,但是这时候其它要获得Singleton实例的线程还是必须等待,锁的存在明显降低了效率,有性能损耗。
全局变量
在 Java/C++ 这些语言里还可以利用全局变量的方式解决上面那种加锁(同步)带来的问题:
class Singleton {
    private static Singleton instance = new Singleton();
    private Singleton() {}
    public static Singleton getInstance() {
        return instance;
    }
}
在 Python 里就是这样了:
class Singleton(object):
    pass
singleton = Singleton()  # 直接使用模块级别的全局变量
但是如果这个类所占的资源较多的话,还没有用这个实例就已经存在了,是非常不划算的……
总结
所以出现了像tornado.IOLoop.instance()那样的double check的单例模式了。在多线程的情况下,既没有同步(加锁)带来的性能下降,也没有全局变量直接实例化带来的资源浪费。
6-25 补充(使用 decorator):
https://wiki.python.org/moin/PythonDecoratorLibrary#Singleton
import functools
def singleton(cls):
    ''' Use class as singleton. '''
    cls.__new_original__ = cls.__new__
    @functools.wraps(cls.__new__)
    def singleton_new(cls, *args, **kw):
        it =  cls.__dict__.get('__it__')
        if it is not None:
            return it
        cls.__it__ = it = cls.__new_original__(cls, *args, **kw)
        it.__init_original__(*args, **kw)
        return it
    cls.__new__ = singleton_new
    cls.__init_original__ = cls.__init__
    cls.__init__ = object.__init__
    return cls
#
# Sample use:
#
@singleton
class Foo:
    def __new__(cls):
        cls.x = 10
        return object.__new__(cls)
    def __init__(self):
        assert self.x == 10
        self.x = 15
assert Foo().x == 15
Foo().x = 20
assert Foo().x == 20
https://wiki.python.org/moin/PythonDecoratorLibrary#The_Sublime_Singleton
def singleton(cls):
    instance = cls()
    instance.__call__ = lambda: instance
    return instance
#
# Sample use
#
@singleton
class Highlander:
    x = 100
    # Of course you can have any attributes or methods you like.
Highlander() is Highlander() is Highlander #=> True
id(Highlander()) == id(Highlander) #=> True
Highlander().x == Highlander.x == 100 #=> True
Highlander.x = 50
Highlander().x == Highlander.x == 50 #=> True
8-27 更:
import threading
class Singleton(object):
    _thread_lock = threading.Lock()
    def __new__(cls, *args, **kwargs):
        if not hasattr(cls, '_instance'):
            with cls._thread_lock:
                if not hasattr(cls, '_instance'):
                    # cls._instance = super(Singleton, cls).__new__(cls)
                    cls._instance = super(Singleton, cls).__new__(
                        cls, *args, **kwargs)
        return cls._instance
    def __init__(self, bar):
        self._bar = bar
    def print_arg(self):
        print(self._bar)
class SingletonGood(object):
    _thread_lock = threading.Lock()
    @classmethod
    def get_instance(cls, *args, **kwargs):
        if not hasattr(cls, '_instance'):
            with cls._thread_lock:
                if not hasattr(cls, '_instance'):
                    # cls._instance = super(SingletonGood, cls).__new__(cls)
                    # cls._instance.__init__(*args, **kwargs)
                    cls._instance = cls(*args, **kwargs)
        return cls._instance
    def __init__(self, bar):
        self._bar = bar
    def print_arg(self):
        print(self._bar)
if __name__ == '__main__':
    obj1 = Singleton('bar')
    obj2 = Singleton('foobar')
    assert id(obj1) == id(obj2)
    obj1.print_arg()  # foobar
    obj2.print_arg()  # foobar
    print('-' * 10)
    obj3 = SingletonGood.get_instance('bar')
    obj4 = SingletonGood.get_instance('foobar')
    assert id(obj3) == id(obj4)
    obj3.print_arg()  # bar
    obj4.print_arg()  # bar