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

编写一个带参数和不带参数的装饰器是一个挑战,因为Python在这两种情况下期望完全不同的行为!许多答案都试图解决这个问题,下面是@norok2对答案的改进。具体来说,这种变化消除了locals()的使用。

下面是@norok2给出的相同示例:

import functools

def multiplying(f_py=None, factor=1):
    assert callable(f_py) or f_py is None
    def _decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            return factor * func(*args, **kwargs)
        return wrapper
    return _decorator(f_py) if callable(f_py) else _decorator


@multiplying
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying()
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying(factor=10)
def summing(x): return sum(x)

print(summing(range(10)))
# 450

玩一下这段代码。

问题是用户必须提供键、值对的参数,而不是位置参数,并且第一个参数是保留的。

其他回答

这是一个函数装饰器模板,如果没有参数,则不需要(),并且支持位置参数和关键字参数(但需要检查locals(),以确定第一个参数是否是要装饰的函数):

import functools


def decorator(x_or_func=None, *decorator_args, **decorator_kws):
    def _decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kws):
            if 'x_or_func' not in locals() \
                    or callable(x_or_func) \
                    or x_or_func is None:
                x = ...  # <-- default `x` value
            else:
                x = x_or_func
            return func(*args, **kws)

        return wrapper

    return _decorator(x_or_func) if callable(x_or_func) else _decorator

下面是一个例子:

def multiplying(factor_or_func=None):
    def _decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            if 'factor_or_func' not in locals() \
                    or callable(factor_or_func) \
                    or factor_or_func is None:
                factor = 1
            else:
                factor = factor_or_func
            return factor * func(*args, **kwargs)
        return wrapper
    return _decorator(factor_or_func) if callable(factor_or_func) else _decorator


@multiplying
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying()
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying(10)
def summing(x): return sum(x)

print(summing(range(10)))
# 450

或者,如果不需要位置参数,可以不检查wrapper()中的第一个参数(从而不需要使用locals()):

import functools


def decorator(func_=None, **decorator_kws):
    def _decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kws):
            return func(*args, **kws)
        return wrapper

    if callable(func_):
        return _decorator(func_)
    elif func_ is None:
        return _decorator
    else:
        raise RuntimeWarning("Positional arguments are not supported.")

下面是一个例子:

import functools


def multiplying(func_=None, factor=1):
    def _decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            return factor * func(*args, **kwargs)
        return wrapper

    if callable(func_):
        return _decorator(func_)
    elif func_ is None:
        return _decorator
    else:
        raise RuntimeWarning("Positional arguments are not supported.")


@multiplying
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying()
def summing(x): return sum(x)

print(summing(range(10)))
# 45


@multiplying(factor=10)
def summing(x): return sum(x)

print(summing(range(10)))
# 450


@multiplying(10)
def summing(x): return sum(x)
print(summing(range(10)))
# RuntimeWarning Traceback (most recent call last)
#    ....
# RuntimeWarning: Positional arguments are not supported.

(部分改编自@ShitalShah的回答)

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
def decorator(argument):
    def real_decorator(function):
        def wrapper(*args):
            for arg in args:
                assert type(arg)==int,f'{arg} is not an interger'
            result = function(*args)
            result = result*argument
            return result
        return wrapper
    return real_decorator

装饰器的使用

@decorator(2)
def adder(*args):
    sum=0
    for i in args:
        sum+=i
    return sum

然后

adder(2,3)

生产

10

but

adder('hi',3)

生产

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-143-242a8feb1cc4> in <module>
----> 1 adder('hi',3)

<ipython-input-140-d3420c248ebd> in wrapper(*args)
      3         def wrapper(*args):
      4             for arg in args:
----> 5                 assert type(arg)==int,f'{arg} is not an interger'
      6             result = function(*args)
      7             result = result*argument

AssertionError: hi is not an interger

匿名设置中的参数装饰。

在许多可能的“嵌套”语法糖装饰的两种变化中被提出。它们之间的区别在于执行wrt到目标函数的顺序,并且它们的效果通常是独立的(不相互作用)。

装饰器允许在目标函数执行之前或之后“注入”自定义函数。

这两个函数的调用都发生在一个元组中。默认情况下,返回值是目标函数的结果。

语法糖装饰@first_internal(send_msg)('…end')要求版本>= 3.9,请参阅PEP 614放松对装饰器的语法限制。

functools使用。以保留目标函数的文档字符串。

from functools import wraps


def first_external(f_external):
    return lambda *args_external, **kwargs_external:\
           lambda f_target: wraps(f_target)(
               lambda *args_target, **kwargs_target:
                  (f_external(*args_external, **kwargs_external),
                   f_target(*args_target, **kwargs_target))[1]
           )


def first_internal(f_external):
    return lambda *args_external, **kwargs_external:\
           lambda f_target: wraps(f_target)(
               lambda *args_target, **kwargs_target:
                  (f_target(*args_target, **kwargs_target),
                   f_external(*args_external, **kwargs_external))[0]
           )


def send_msg(x):
   print('msg>', x)


@first_internal(send_msg)('...end')    # python >= 3.9
@first_external(send_msg)("start...")  # python >= 3.9
def test_function(x):
    """Test function"""
    print('from test_function')
    return x


test_function(2)

输出

msg> start...
from test_function
msg> ...end

讲话

composition decorators, such as pull-back and push-forward (maybe in a more Computer Science terminology: co- and resp. contra-variant decorator), could more useful but need ad-hoc care, for example composition rules, check which parameters go where, etc syntactic sugar acts as a kind of partial of the target function: once decorated there is no way back (without extra imports) but it is not mandatory, a decorator can be used also in its extended forms, i.e. first_external(send_msg)("start...")(test_function)(2) the results of a workbench with timeit.repeat(..., repeat=5, number=10000) which compare the classical def and lambda decoration shows that are almost equivalent: for lambda: [6.200810984999862, 6.035239247000391, 5.346362481000142, 5.987880147000396, 5.5331550319997405] - mean -> 5.8206 for def: [6.165001932999985, 5.554595884999799, 5.798066574999666, 5.678178028000275, 5.446507932999793] - mean -> 5.7284 naturally an non-anonymous counterpart is possible and provides more flexibility

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。