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)

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.

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

例如，我在下面创建了multiply()，它可以接受一个参数或不接受参数，也可以不接受装饰器的括号，我在下面创建了sum():

from numbers import Number

def multiply(num=1):
    def _multiply(func):
        def core(*args, **kwargs):
            result = func(*args, **kwargs)
            if isinstance(num, Number):
                return result * num
            else:
                return result
        return core
    if callable(num):
        return _multiply(num)
    else:
        return _multiply

def sum(num1, num2):
    return num1 + num2

现在，我把@multiply(5)放在sum()上，然后调用sum(4,6)，如下所示:

# (4 + 6) x 5 = 50

@multiply(5) # Here
def sum(num1, num2):
    return num1 + num2

result = sum(4, 6)
print(result)

那么，我可以得到如下结果:

50

接下来，我把@multiply()放在sum()上，然后调用sum(4,6)，如下所示:

# (4 + 6) x 1 = 10

@multiply() # Here
def sum(num1, num2):
    return num1 + num2
    
result = sum(4, 6)
print(result)

或者，我把@multiply放在sum()上，然后调用sum(4,6)，如下所示:

# 4 + 6 = 10

@multiply # Here
def sum(num1, num2):
    return num1 + num2
    
result = sum(4, 6)
print(result)

那么，我可以得到如下结果:

10

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。

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。