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

这是curry函数的一个很好的用例。

curry函数本质上是延迟函数的调用,直到提供了所有输入。

这可以用于各种事情,如包装器或函数式编程。在本例中,让我们创建一个接受输入的包装器。

我将使用一个简单的包pamda,其中包含一个用于python的curry函数。这可以用作其他函数的包装器。

安装 Pamda:

pip install pamda

创建一个简单的带有两个输入的装饰函数:

@pamda.curry()
def my_decorator(input, func):
    print ("Executing Decorator")
    print(f"input:{input}")
    return func

使用提供给目标函数的第一个输入应用你的装饰器:

@my_decorator('Hi!')
def foo(input):
    print('Executing Foo!')
    print(f"input:{input}")

执行你的包装函数:

x=foo('Bye!')

把所有东西放在一起:

from pamda import pamda

@pamda.curry()
def my_decorator(input, func):
    print ("Executing Decorator")
    print(f"input:{input}")
    return func

@my_decorator('Hi!')
def foo(input):
    print('Executing Foo!')
    print(f"input:{input}")

x=foo('Bye!')

将:

Executing Decorator
input:Hi!
Executing Foo!
input:Bye!

其他回答

它是一个可以以多种方式调用的装饰器(在python3.7中测试):

import functools


def my_decorator(*args_or_func, **decorator_kwargs):

    def _decorator(func):

        @functools.wraps(func)
        def wrapper(*args, **kwargs):

            if not args_or_func or callable(args_or_func[0]):
                # Here you can set default values for positional arguments
                decorator_args = ()
            else:
                decorator_args = args_or_func

            print(
                "Available inside the wrapper:",
                decorator_args, decorator_kwargs
            )

            # ...
            result = func(*args, **kwargs)
            # ...

            return result

        return wrapper

    return _decorator(args_or_func[0]) \
        if args_or_func and callable(args_or_func[0]) else _decorator


@my_decorator
def func_1(arg): print(arg)

func_1("test")
# Available inside the wrapper: () {}
# test


@my_decorator()
def func_2(arg): print(arg)

func_2("test")
# Available inside the wrapper: () {}
# test


@my_decorator("any arg")
def func_3(arg): print(arg)

func_3("test")
# Available inside the wrapper: ('any arg',) {}
# test


@my_decorator("arg_1", 2, [3, 4, 5], kwarg_1=1, kwarg_2="2")
def func_4(arg): print(arg)

func_4("test")
# Available inside the wrapper: ('arg_1', 2, [3, 4, 5]) {'kwarg_1': 1, 'kwarg_2': '2'}
# test

PS感谢用户@norok2 - https://stackoverflow.com/a/57268935/5353484

UPD装饰器,用于根据注释验证类的函数和方法的参数和/或结果。可用于同步或异步版本:https://github.com/EvgeniyBurdin/valdec

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

编辑:为了深入了解装饰师的心理模型,请看看这个很棒的Pycon Talk。这30分钟很值得。

考虑带参数的装饰器的一种方式是

@decorator
def foo(*args, **kwargs):
    pass

翻译为

foo = decorator(foo)

如果decorator有参数,

@decorator_with_args(arg)
def foo(*args, **kwargs):
    pass

翻译为

foo = decorator_with_args(arg)(foo)

Decorator_with_args是一个函数,它接受自定义参数并返回实际的装饰器(将应用于被装饰的函数)。

我使用了一个简单的技巧与部分,使我的装饰容易

from functools import partial

def _pseudo_decor(fun, argument):
    def ret_fun(*args, **kwargs):
        #do stuff here, for eg.
        print ("decorator arg is %s" % str(argument))
        return fun(*args, **kwargs)
    return ret_fun

real_decorator = partial(_pseudo_decor, argument=arg)

@real_decorator
def foo(*args, **kwargs):
    pass

更新:

上面,foo变成了real_decorator(foo)

修饰函数的一个效果是,foo的名字在修饰器声明中被重写。Foo被real_decorator返回的任何东西“覆盖”。在本例中,是一个新的函数对象。

foo的所有元数据都会被重写,尤其是文档字符串和函数名。

>>> print(foo)
<function _pseudo_decor.<locals>.ret_fun at 0x10666a2f0>

functools。Wraps为我们提供了一个方便的方法,将文档字符串和名称“提升”到返回的函数中。

from functools import partial, wraps

def _pseudo_decor(fun, argument):
    # magic sauce to lift the name and doc of the function
    @wraps(fun)
    def ret_fun(*args, **kwargs):
        # pre function execution stuff here, for eg.
        print("decorator argument is %s" % str(argument))
        returned_value =  fun(*args, **kwargs)
        # post execution stuff here, for eg.
        print("returned value is %s" % returned_value)
        return returned_value

    return ret_fun

real_decorator1 = partial(_pseudo_decor, argument="some_arg")
real_decorator2 = partial(_pseudo_decor, argument="some_other_arg")

@real_decorator1
def bar(*args, **kwargs):
    pass

>>> print(bar)
<function __main__.bar(*args, **kwargs)>

>>> bar(1,2,3, k="v", x="z")
decorator argument is some_arg
returned value is None

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