python中的 @ 修饰符

今天看到python中的一个修饰符'@'，不了解它的使用，查看了下官方文档，有了一点了解。

原文 PEP-318 网址：http://www.python.org/dev/peps/pep-0318/

不得不佩服老外，治学很严谨，在python网站相关网页上把为什么使用decorator（主要为了简便一些代码），以及使用什么字符，甚至语法怎么设计写了个详详细细，好长的一篇啊。

这是查看的其中一篇，我翻译关键部分的一些内容，又摘取一些有用的，有空再翻译。

@dec2
@dec1
def func(arg1, arg2, ...):
    pass

This is equivalent to（等价于）:

def func(arg1, arg2, ...):
    pass
func = dec2(dec1(func))

使用示例：

Much of the discussion on comp.lang.python and the python-dev mailing list focuses on the use of decorators as a cleaner way to use the staticmethod() and classmethod() builtins. This capability is much more powerful than that. This section presents some examples of use.

在comp.lang.python 和 python-dev的大部分讨论集中在更简捷地使用内置修饰符staticmethod() 和 classmethod() 上。但修饰符的功能远比这强大。下面会对它的使用进行一些讲解：

1.Define a function to be executed at exit. Note that the function isn't actually "wrapped" in the usual sense.

1.定义一个执行即退出的函数。注意，这个函数并不像通常情况那样，被真正包裹。

def onexit(f):
    import atexit
    atexit.register(f)
    return f

@onexit
def func():
    ...

Note that this example is probably not suitable for real usage, but is for example purposes only.

注意，这个示例可能并不能准确表达在实际中的使用，它只是做一个示例。

2. Define a class with a singleton instance. Note that once the class disappears enterprising programmers would have to be more creative to create more instances. (From Shane Hathaway onpython-dev.)

2.定义一个只能产生一个实例的类（有实例后，这个类不能再产生新的实例）。注意，一旦这个类失效了(估计意思是保存在下文的singleton中字典中的相应键失效)，就会促使程序员让这个类产生更多的实例。（来自于 python-dev的Shane Hathaway）

def singleton(cls):
    instances = {}
    def getinstance():
        if cls not in instances:
            instances[cls] = cls()
        return instances[cls]
    return getinstance

@singleton
class MyClass:
    ...

余下基本可以参照着读懂了，以后再翻译。

3.Add attributes to a function. (Based on an example posted by Anders Munch on  python-dev .)

def attrs(**kwds):
    def decorate(f):
        for k in kwds:
            setattr(f, k, kwds[k])
        return f
    return decorate

@attrs(versionadded="2.2",
       author="Guido van Rossum")
def mymethod(f):
    ...

4. Enforce function argument and return types. Note that this copies the func_name attribute from the old to the new function. func_name was made writable in Python 2.4a3:

def accepts(*types):
    def check_accepts(f):
        assert len(types) == f.func_code.co_argcount
        def new_f(*args, **kwds):
            for (a, t) in zip(args, types):
                assert isinstance(a, t), \
                       "arg %r does not match %s" % (a,t)
            return f(*args, **kwds)
        new_f.func_name = f.func_name
        return new_f
    return check_accepts

def returns(rtype):
    def check_returns(f):
        def new_f(*args, **kwds):
            result = f(*args, **kwds)
            assert isinstance(result, rtype), \
                   "return value %r does not match %s" % (result,rtype)
            return result
        new_f.func_name = f.func_name
        return new_f
    return check_returns

@accepts(int, (int,float))
@returns((int,float))
def func(arg1, arg2):
    return arg1 * arg2

5. Declare that a class implements a particular (set of) interface(s). This is from a posting by Bob Ippolito on  python-dev  based on experience with  PyProtocols   [27] .

def provides(*interfaces):
     """
     An actual, working, implementation of provides for
     the current implementation of PyProtocols.  Not
     particularly important for the PEP text.
     """
     def provides(typ):
         declareImplementation(typ, instancesProvide=interfaces)
         return typ
     return provides

class IBar(Interface):
     """Declare something about IBar here"""

@provides(IBar)
class Foo(object):
        """Implement something here..."""

Of course, all these examples are possible today, though without syntactic support.