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.

就这么简单

def real_decorator(any_number_of_arguments):
   def pseudo_decorator(function_to_be_decorated):

       def real_wrapper(function_arguments):
           print(function_arguments)
           result = function_to_be_decorated(any_number_of_arguments)
           return result

       return real_wrapper
   return pseudo_decorator

Now

@real_decorator(any_number_of_arguments)
def some_function(function_arguments):
        return "Any"

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

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

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)

我想展示一个想法，在我看来很优雅。t.dubrownik提出的解决方案显示了一个始终相同的模式:无论装饰器做什么，您都需要三层包装器。

所以我认为这是一个元装饰师的工作，也就是说，装饰师的装饰师。由于decorator是一个函数，它实际上是一个带有参数的常规decorator:

def parametrized(dec):
    def layer(*args, **kwargs):
        def repl(f):
            return dec(f, *args, **kwargs)
        return repl
    return layer

这可以应用于常规的装饰器，以便添加参数。例如，我们有一个decorator，它将一个函数的结果加倍:

def double(f):
    def aux(*xs, **kws):
        return 2 * f(*xs, **kws)
    return aux

@double
def function(a):
    return 10 + a

print function(3)    # Prints 26, namely 2 * (10 + 3)

使用@ parameterized，我们可以构建一个带参数的通用@multiply装饰器

@parametrized
def multiply(f, n):
    def aux(*xs, **kws):
        return n * f(*xs, **kws)
    return aux

@multiply(2)
def function(a):
    return 10 + a

print function(3)    # Prints 26

@multiply(3)
def function_again(a):
    return 10 + a

print function(3)          # Keeps printing 26
print function_again(3)    # Prints 39, namely 3 * (10 + 3)

通常，参数化装饰器的第一个参数是函数，而其余参数将对应于参数化装饰器的参数。

一个有趣的用法示例可以是类型安全的断言装饰器:

import itertools as it

@parametrized
def types(f, *types):
    def rep(*args):
        for a, t, n in zip(args, types, it.count()):
            if type(a) is not t:
                raise TypeError('Value %d has not type %s. %s instead' %
                    (n, t, type(a))
                )
        return f(*args)
    return rep

@types(str, int)  # arg1 is str, arg2 is int
def string_multiply(text, times):
    return text * times

print(string_multiply('hello', 3))    # Prints hellohellohello
print(string_multiply(3, 3))          # Fails miserably with TypeError

最后注意:这里我没有使用functools。包装器函数，但我建议始终使用它。