我有一个由装饰器转移变量insurance_mode的问题。我将通过以下装饰器语句来实现:

@execute_complete_reservation(True)
def test_booking_gta_object(self):
    self.test_select_gta_object()

但不幸的是,这种说法并不管用。也许也许有更好的办法来解决这个问题。

def execute_complete_reservation(test_case,insurance_mode):
    def inner_function(self,*args,**kwargs):
        self.test_create_qsf_query()
        test_case(self,*args,**kwargs)
        self.test_select_room_option()
        if insurance_mode:
            self.test_accept_insurance_crosseling()
        else:
            self.test_decline_insurance_crosseling()
        self.test_configure_pax_details()
        self.test_configure_payer_details

    return inner_function

当前回答

在我的实例中,我决定通过一行lambda来解决这个问题,以创建一个新的decorator函数:

def finished_message(function, message="Finished!"):

    def wrapper(*args, **kwargs):
        output = function(*args,**kwargs)
        print(message)
        return output

    return wrapper

@finished_message
def func():
    pass

my_finished_message = lambda f: finished_message(f, "All Done!")

@my_finished_message
def my_func():
    pass

if __name__ == '__main__':
    func()
    my_func()

执行时,输出:

Finished!
All Done!

也许不像其他解决方案那样可扩展,但对我来说是可行的。

其他回答

以下是对t.dubrownik的回答稍加修改的版本。为什么?

作为通用模板,您应该返回原始函数的返回值。 这将改变函数的名称,这可能会影响其他装饰器/代码。

所以使用@functools.wraps():

from functools import wraps

def create_decorator(argument):
    def decorator(function):
        @wraps(function)
        def wrapper(*args, **kwargs):
            funny_stuff()
            something_with_argument(argument)
            retval = function(*args, **kwargs)
            more_funny_stuff()
            return retval
        return wrapper
    return decorator

众所周知,下面两段代码几乎是等价的:

@dec
def foo():
    pass    foo = dec(foo)

############################################
foo = dec(foo)

一个常见的错误是认为@只是隐藏了最左边的参数。

@dec(1, 2, 3)
def foo():
    pass    
###########################################
foo = dec(foo, 1, 2, 3)

如果@是这样工作的,那么编写装饰器会容易得多。不幸的是,事情不是这样的。


考虑decorator Waitwhich haults 程序执行几秒钟。 如果你没有通过等待时间 缺省值为1秒。 用例如下所示。

##################################################
@Wait
def print_something(something):
    print(something)

##################################################
@Wait(3)
def print_something_else(something_else):
    print(something_else)

##################################################
@Wait(delay=3)
def print_something_else(something_else):
    print(something_else)

当Wait有一个参数,比如@Wait(3),那么调用Wait(3) 在发生任何其他事情之前执行。

也就是说,下面两段代码是等价的

@Wait(3)
def print_something_else(something_else):
    print(something_else)

###############################################
return_value = Wait(3)
@return_value
def print_something_else(something_else):
    print(something_else)

这是一个问题。

if `Wait` has no arguments:
    `Wait` is the decorator.
else: # `Wait` receives arguments
    `Wait` is not the decorator itself.
    Instead, `Wait` ***returns*** the decorator

解决方案如下:

让我们从创建以下类开始,DelayedDecorator:

class DelayedDecorator:
    def __init__(i, cls, *args, **kwargs):
        print("Delayed Decorator __init__", cls, args, kwargs)
        i._cls = cls
        i._args = args
        i._kwargs = kwargs
    def __call__(i, func):
        print("Delayed Decorator __call__", func)
        if not (callable(func)):
            import io
            with io.StringIO() as ss:
                print(
                    "If only one input, input must be callable",
                    "Instead, received:",
                    repr(func),
                    sep="\n",
                    file=ss
                )
                msg = ss.getvalue()
            raise TypeError(msg)
        return i._cls(func, *i._args, **i._kwargs)

现在我们可以这样写:

 dec = DelayedDecorator(Wait, delay=4)
 @dec
 def delayed_print(something):
    print(something)

注意:

dec does not not accept multiple arguments. dec only accepts the function to be wrapped. import inspect class PolyArgDecoratorMeta(type): def call(Wait, *args, **kwargs): try: arg_count = len(args) if (arg_count == 1): if callable(args[0]): SuperClass = inspect.getmro(PolyArgDecoratorMeta)[1] r = SuperClass.call(Wait, args[0]) else: r = DelayedDecorator(Wait, *args, **kwargs) else: r = DelayedDecorator(Wait, *args, **kwargs) finally: pass return r import time class Wait(metaclass=PolyArgDecoratorMeta): def init(i, func, delay = 2): i._func = func i._delay = delay def __call__(i, *args, **kwargs): time.sleep(i._delay) r = i._func(*args, **kwargs) return r

下面两段代码是等价的:

@Wait
def print_something(something):
     print (something)

##################################################

def print_something(something):
    print(something)
print_something = Wait(print_something)

我们可以非常缓慢地将“something”打印到控制台,如下所示:

print_something("something")

#################################################
@Wait(delay=1)
def print_something_else(something_else):
    print(something_else)

##################################################
def print_something_else(something_else):
    print(something_else)

dd = DelayedDecorator(Wait, delay=1)
print_something_else = dd(print_something_else)

##################################################

print_something_else("something")

最后指出

它可能看起来有很多代码,但你不必每次都写类DelayedDecorator和PolyArgDecoratorMeta。你必须亲自编写的代码如下所示,这是相当短的:

from PolyArgDecoratorMeta import PolyArgDecoratorMeta
import time
class Wait(metaclass=PolyArgDecoratorMeta):
 def __init__(i, func, delay = 2):
     i._func = func
     i._delay = delay

 def __call__(i, *args, **kwargs):
     time.sleep(i._delay)
     r = i._func(*args, **kwargs)
     return r

上面的回答很棒。这个例子还演示了@wraps,它从原始函数中获取文档字符串和函数名,并将其应用于新的包装版本:

from functools import wraps

def decorator_func_with_args(arg1, arg2):
    def decorator(f):
        @wraps(f)
        def wrapper(*args, **kwargs):
            print("Before orginal function with decorator args:", arg1, arg2)
            result = f(*args, **kwargs)
            print("Ran after the orginal function")
            return result
        return wrapper
    return decorator

@decorator_func_with_args("foo", "bar")
def hello(name):
    """A function which prints a greeting to the name provided.
    """
    print('hello ', name)
    return 42

print("Starting script..")
x = hello('Bob')
print("The value of x is:", x)
print("The wrapped functions docstring is:", hello.__doc__)
print("The wrapped functions name is:", hello.__name__)

打印:

Starting script..
Before orginal function with decorator args: foo bar
hello  Bob
Ran after the orginal function
The value of x is: 42
The wrapped functions docstring is: A function which prints a greeting to the name provided.
The wrapped functions name is: hello

在我的实例中,我决定通过一行lambda来解决这个问题,以创建一个新的decorator函数:

def finished_message(function, message="Finished!"):

    def wrapper(*args, **kwargs):
        output = function(*args,**kwargs)
        print(message)
        return output

    return wrapper

@finished_message
def func():
    pass

my_finished_message = lambda f: finished_message(f, "All Done!")

@my_finished_message
def my_func():
    pass

if __name__ == '__main__':
    func()
    my_func()

执行时,输出:

Finished!
All Done!

也许不像其他解决方案那样可扩展,但对我来说是可行的。

带参数的装饰器应该返回一个函数,该函数将接受一个函数,并返回另一个函数

def decorator_factory(argument):
    def decorator(function):
        def wrapper(*args, **kwargs):
            """
                add somhting
            """
            return  function(*args, **kwargs)
        return wrapper
    return decorator

或者你可以使用functools模块的部分

def decorator(function =None,*,argument ):
        if function is None :
            return partial(decorator,argument=argument)
        def wrapper(*args, **kwargs):
            """
                add somhting
            """
            return  function(*args, **kwargs)
        return wrapper

在第二个选项中,确保你像这样传递参数:

@decorator(argument = 'args')
def func():
    pass