假设你有一个函数

def f(*args):
    print(*args)

你想要添加一个接受参数的装饰器，就像这样:

@decorator(msg='hello')
def f(*args):
    print(*args)

这意味着Python将对f进行如下修改:

f = decorator(msg='hello')(f)

因此，部件装饰器(msg='hello')的返回值应该是一个包装器函数，它接受函数f并返回修改后的函数。然后可以执行修改后的函数。

def decorator(**kwargs):
    def wrap(f):
        def modified_f(*args):
            print(kwargs['msg']) # use passed arguments to the decorator
            return f(*args)
        return modified_f
    return wrap

所以，当你调用f时，就像你在做: 装饰(味精= '你好')(f) (args) === wrap(f)(args) === modified_f(args) 但是modified_f可以访问传递给装饰器的kwargs

的输出

f(1,2,3)

将会是:

hello
(1, 2, 3)

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

在这里，我们用两个不同的名称和两个不同的年龄运行了两次display info。 现在，每当我们运行display info时，我们的装饰器还添加了打印换行函数前后一行的功能。

def decorator_function(original_function):
    def wrapper_function(*args, **kwargs):
        print('Executed Before', original_function.__name__)
        result = original_function(*args, **kwargs)
        print('Executed After', original_function.__name__, '\n')
        return result
    return wrapper_function


@decorator_function
def display_info(name, age):
    print('display_info ran with arguments ({}, {})'.format(name, age))


display_info('Mr Bean', 66)
display_info('MC Jordan', 57)

输出:

Executed Before display_info
display_info ran with arguments (Mr Bean, 66)
Executed After display_info 

Executed Before display_info
display_info ran with arguments (MC Jordan, 57)
Executed After display_info 

现在让我们继续让decorator函数接受参数。 例如，假设我想为包装器中的所有这些打印语句添加一个可定制的前缀。 现在这将是一个很好的候选参数的装饰。 我们传入的参数就是那个前缀。现在为了做到这一点，我们将添加另一个外层到我们的装饰器中，我将把这个函数称为前缀装饰器。

def prefix_decorator(prefix):
    def decorator_function(original_function):
        def wrapper_function(*args, **kwargs):
            print(prefix, 'Executed Before', original_function.__name__)
            result = original_function(*args, **kwargs)
            print(prefix, 'Executed After', original_function.__name__, '\n')
            return result
        return wrapper_function
    return decorator_function


@prefix_decorator('LOG:')
def display_info(name, age):
    print('display_info ran with arguments ({}, {})'.format(name, age))


display_info('Mr Bean', 66)
display_info('MC Jordan', 57)

输出:

LOG: Executed Before display_info
display_info ran with arguments (Mr Bean, 66)
LOG: Executed After display_info 

LOG: Executed Before display_info
display_info ran with arguments (MC Jordan, 57)
LOG: Executed After display_info 

现在我们在包装器函数的print语句之前有了LOG:前缀，你可以随时更改它。

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

下面是一个使用带有参数的装饰器的Flask示例。假设我们有一个路由'/user/name'，我们想要映射到他的主页。

def matchR(dirPath):
    def decorator(func):
        def wrapper(msg):
            if dirPath[0:6] == '/user/':
                print(f"User route '{dirPath}' match, calling func {func}")
                name = dirPath[6:]
                return func(msg2=name, msg3=msg)
            else:
                print(f"Input dirPath '{dirPath}' does not match route '/user/'")
                return
        return  wrapper
    return decorator

#@matchR('/Morgan_Hills')
@matchR('/user/Morgan_Hills')
def home(**kwMsgs):
    for arg in kwMsgs:
        if arg == 'msg2':
            print(f"In home({arg}): Hello {kwMsgs[arg]}, welcome home!")
        if arg == 'msg3':
            print(f"In home({arg}): {kwMsgs[arg]}")

home('This is your profile rendered as in index.html.')

输出:

User route '/user/Morgan_Hills' match, calling func <function home at 0x000001DD5FDCD310>
In home(msg2): Hello Morgan_Hills, welcome home!
In home(msg3): This is your profile rendered as in index.html.

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)