Python装饰器笔记

装饰器本原

装饰器就是一个函数，并不需要特殊语法定义。当你在别的函数头上写@时，就相当于调用装饰器函数，传入参数是被装饰函数，返回值也被赋给被装饰函数。参考《Two of the simplest Python decorator examples》

@mydecorator
def myfunc():
    pass

等价于

def myfunc():
    pass
myfunc = mydecorator(myfunc)

可以见@装饰器，是调用装饰器函数。(1)它可以执行一些一次性的代码，只在定义被装饰函数的时候执行一次。(2)它也可以使得被装饰函数每次调用时都执行一些额外代码。这是通过给原函数加wrapper实现的。

包装

我们在装饰器里定义一个内部函数，它接受的参数与原函数一样，它调用原函数并将这些参数传递给原函数。此外，它还额外执行一些代码。然后我们把这个内部函数作为装饰器的返回值。

普通的wrapper不会保持原函数的.name和.doc等属性。所以最好用标准库提供的@wraps包装我们的wrapper，它会自动将原函数的这些属性赋予我们定义的wrapper。

Without the use of this decorator factory, the name of the example function would have been 'wrapper', and the docstring of the original example() would have been lost. Python文档

例子：

from functools import wraps

def mydecorator(f):
    @wraps(f)
    def wrapped(*args, **kwargs):
        print "Before decorated function"
        r = f(*args, **kwargs)
        print "After decorated function"
        return r
    return wrapped

@mydecorator
def myfunc(myarg):
    print "my function", myarg
    return "return value"

r = myfunc('asdf')
print r

带参数的装饰器（重要pattern！）

默认的装饰器是没有参数的（它的隐含参数是被装饰函数）。如果要定义带参数的装饰器，那就要再套一层。看着有点费解！！反正这种代码我看了很晕。但是这种pattern很常见。

from functools import wraps

def mydecorator_not_actually(count):
    def true_decorator(f):
        @wraps(f)
        def wrapped(*args, **kwargs):
            for i in range(count):
                print "Before decorated function"
            r = f(*args, **kwargs)
            for i in range(count):
                print "After decorated function"
            return r
        return wrapped
    return true_decorator

@mydecorator_not_actually(count=5)
def myfunc(myarg):
    print "my function", myarg
    return "return value"

r = myfunc('asdf')
print r

装饰器的典型应用

Flask里面的@route就是执行一次性代码的例子。它是一个带参数的装饰器，所以套一层，里面才是真正的装饰器。但是它没有改变原函数，被修饰函数f还是原样返回，只是执行了一些一次性的代码。将这个函数添加到路由表中。
参见：StackOverflow

def route(self, rule, **options):
        """A decorator that is used to register a view function for a
        given URL rule.  This does the same thing as :meth:`add_url_rule`
        but is intended for decorator usage::
            @app.route('/')
            def index():
                return 'Hello World'
        For more information refer to :ref:`url-route-registrations`.
        :param rule: the URL rule as string
        :param endpoint: the endpoint for the registered URL rule.  Flask
                         itself assumes the name of the view function as
                         endpoint
        :param options: the options to be forwarded to the underlying
                        :class:`~werkzeug.routing.Rule` object.  A change
                        to Werkzeug is handling of method options.  methods
                        is a list of methods this rule should be limited
                        to (``GET``, ``POST`` etc.).  By default a rule
                        just listens for ``GET`` (and implicitly ``HEAD``).
                        Starting with Flask 0.6, ``OPTIONS`` is implicitly
                        added and handled by the standard request handling.
        """
        def decorator(f):
            endpoint = options.pop('endpoint', None)
            self.add_url_rule(rule, endpoint, f, **options)
            return f
        return decorator

Flask文档里面的login_required装饰器，是执行多次代码的例子。它在原函数外面套了一层wrapper，这样每次执行原函数前，都会执行检查是否登陆的代码，如果未登录，直接就返回redirect，而不执行原函数，否则照常执行。

from functools import wraps
from flask import g, request, redirect, url_for

def login_required(f):
    @wraps(f)
    def decorated_function(*args, **kwargs):
        if g.user is None:
            return redirect(url_for('login', next=request.url))
        return f(*args, **kwargs)
    return decorated_function

另外还有标准库里面的@cache简直是神器，一行代码就实现了memoize，写自顶向下的DP只要普通递归，加这个装饰器就搞定。

参考

Real Python