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

我认为这里有一个工作的、现实世界的示例,其中包含最通用的用例的使用示例。


下面是函数的装饰器,它在进入和退出函数时输出log。

参数控制是否打印输入输出值,日志级别等。

import logging 
from functools import wraps


def log_in_out(logger=logging.get_logger(), is_print_input=True, is_print_output=True, is_method=True, log_level=logging.DEBUG):
    """
    @param logger-
    @param is_print_input- toggle printing input arguments
    @param is_print_output- toggle printing output values
    @param is_method- True for methods, False for functions. Makes "self" not printed in case of is_print_input==True
    @param log_level-

    @returns- a decorator that logs to logger when entering or exiting the decorated function.
    Don't uglify your code!
    """

    def decor(fn):
        @wraps(fn)
        def wrapper(*args, **kwargs):
            if is_print_input:
                logger.log(
                    msg=f"Entered {fn.__name__} with args={args[1:] if is_method else args}, kwargs={kwargs}",
                    level=log_level
                )
            else:
                logger.log(
                    msg=f"Entered {fn.__name__}",
                    level=log_level
                )

            result = fn(*args, **kwargs)

            if is_print_output and result is not None:
                logger.log(
                    msg=f"Exited {fn.__name__} with result {result}",
                    level=log_level,
                )
            else:
                logger.log(
                    msg=f"Exited {fn.__name__}",
                    level=log_level
                )

            return result

        return wrapper

    return decor

用法:

 @log_in_out(is_method=False, is_print_input=False)
    def foo(a, b=5):
        return 3, a

Foo(2)—>打印

输入foo 输出结果为(3,2)的foo

    class A():
        @log_in_out(is_print_output=False)
        def bar(self, c, m, y):
            return c, 6

a = () A.bar (1,2, y=3)—>打印

输入bar with args=(1, 2), kwargs={y:3} 离开酒吧

其他回答

定义这个decoratorize函数来生成定制的decorator函数:

def decoratorize(FUN, **kw):
    def foo(*args, **kws):
        return FUN(*args, **kws, **kw)
    return foo

可以这样用:

    @decoratorize(FUN, arg1 = , arg2 = , ...)
    def bar(...):
        ...
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

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)

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