我如何在Python中制作两个装饰器来完成以下操作?

@make_bold
@make_italic
def say():
   return "Hello"

调用say()应返回:

"<b><i>Hello</i></b>"

当前回答

#decorator.py
def makeHtmlTag(tag, *args, **kwds):
    def real_decorator(fn):
        css_class = " class='{0}'".format(kwds["css_class"]) \
                                 if "css_class" in kwds else ""
        def wrapped(*args, **kwds):
            return "<"+tag+css_class+">" + fn(*args, **kwds) + "</"+tag+">"
        return wrapped
    # return decorator dont call it
    return real_decorator

@makeHtmlTag(tag="b", css_class="bold_css")
@makeHtmlTag(tag="i", css_class="italic_css")
def hello():
    return "hello world"

print hello()

也可以在类中编写decorator

#class.py
class makeHtmlTagClass(object):
    def __init__(self, tag, css_class=""):
        self._tag = tag
        self._css_class = " class='{0}'".format(css_class) \
                                       if css_class != "" else ""

    def __call__(self, fn):
        def wrapped(*args, **kwargs):
            return "<" + self._tag + self._css_class+">"  \
                       + fn(*args, **kwargs) + "</" + self._tag + ">"
        return wrapped

@makeHtmlTagClass(tag="b", css_class="bold_css")
@makeHtmlTagClass(tag="i", css_class="italic_css")
def hello(name):
    return "Hello, {}".format(name)

print hello("Your name")

其他回答

这个答案早就有了答案,但我想我会分享我的Decorator类,这使编写新的Decorator变得简单而紧凑。

from abc import ABCMeta, abstractclassmethod

class Decorator(metaclass=ABCMeta):
    """ Acts as a base class for all decorators """

    def __init__(self):
        self.method = None

    def __call__(self, method):
        self.method = method
        return self.call

    @abstractclassmethod
    def call(self, *args, **kwargs):
        return self.method(*args, **kwargs)

首先,我认为这使装饰器的行为非常清晰,但也使定义新的装饰器变得非常简洁。对于上面列出的示例,您可以将其解为:

class MakeBold(Decorator):
    def call():
        return "<b>" + self.method() + "</b>"

class MakeItalic(Decorator):
    def call():
        return "<i>" + self.method() + "</i>"

@MakeBold()
@MakeItalic()
def say():
   return "Hello"

您也可以使用它来执行更复杂的任务,例如,一个装饰器,它会自动将函数递归地应用于迭代器中的所有参数:

class ApplyRecursive(Decorator):
    def __init__(self, *types):
        super().__init__()
        if not len(types):
            types = (dict, list, tuple, set)
        self._types = types

    def call(self, arg):
        if dict in self._types and isinstance(arg, dict):
            return {key: self.call(value) for key, value in arg.items()}

        if set in self._types and isinstance(arg, set):
            return set(self.call(value) for value in arg)

        if tuple in self._types and isinstance(arg, tuple):
            return tuple(self.call(value) for value in arg)

        if list in self._types and isinstance(arg, list):
            return list(self.call(value) for value in arg)

        return self.method(arg)


@ApplyRecursive(tuple, set, dict)
def double(arg):
    return 2*arg

print(double(1))
print(double({'a': 1, 'b': 2}))
print(double({1, 2, 3}))
print(double((1, 2, 3, 4)))
print(double([1, 2, 3, 4, 5]))

哪些打印:

2
{'a': 2, 'b': 4}
{2, 4, 6}
(2, 4, 6, 8)
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]

注意,这个示例没有在decorator的实例化中包含列表类型,因此在最终的print语句中,该方法应用于列表本身,而不是列表的元素。

下面有make_bold()和make_italic():

def make_bold(func):
    def core(*args, **kwargs):
        result = func(*args, **kwargs)
        return "<b>" + result + "</b>"
    return core

def make_italic(func):
    def core(*args, **kwargs):
        result = func(*args, **kwargs)
        return "<i>" + result + "</i>"
    return core

您可以使用say()将它们用作装饰器,如下所示:

@make_bold
@make_italic
def say():
   return "Hello"

print(say())

输出:

<b><i>Hello</i></b>

当然,您可以直接使用make_bold()和make_italic()而不使用修饰符,如下所示:

def say():
    return "Hello"
    
f1 = make_italic(say)
f2 = make_bold(f1)
result = f2()
print(result)

简而言之:

def say():
    return "Hello"
    
result = make_bold(make_italic(say))()
print(result)

输出:

<b><i>Hello</i></b>

做同样事情的另一种方式:

class bol(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<b>{}</b>".format(self.f())

class ita(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<i>{}</i>".format(self.f())

@bol
@ita
def sayhi():
  return 'hi'

或者,更灵活地说:

class sty(object):
  def __init__(self, tag):
    self.tag = tag
  def __call__(self, f):
    def newf():
      return "<{tag}>{res}</{tag}>".format(res=f(), tag=self.tag)
    return newf

@sty('b')
@sty('i')
def sayhi():
  return 'hi'

这里是一个链接装饰器的简单示例。注意最后一行-它显示了封面下的情况。

############################################################
#
#    decorators
#
############################################################

def bold(fn):
    def decorate():
        # surround with bold tags before calling original function
        return "<b>" + fn() + "</b>"
    return decorate


def uk(fn):
    def decorate():
        # swap month and day
        fields = fn().split('/')
        date = fields[1] + "/" + fields[0] + "/" + fields[2]
        return date
    return decorate

import datetime
def getDate():
    now = datetime.datetime.now()
    return "%d/%d/%d" % (now.day, now.month, now.year)

@bold
def getBoldDate(): 
    return getDate()

@uk
def getUkDate():
    return getDate()

@bold
@uk
def getBoldUkDate():
    return getDate()


print getDate()
print getBoldDate()
print getUkDate()
print getBoldUkDate()
# what is happening under the covers
print bold(uk(getDate))()

输出如下所示:

17/6/2013
<b>17/6/2013</b>
6/17/2013
<b>6/17/2013</b>
<b>6/17/2013</b>

用于绘制图像的嵌套装饰器的又一示例:

import matplotlib.pylab as plt

def remove_axis(func):
    def inner(img, alpha):
        plt.axis('off')
        func(img, alpha)
    return inner

def plot_gray(func):
    def inner(img, alpha):
        plt.gray()
        func(img, alpha)
    return inner

@remove_axis
@plot_gray
def plot_image(img, alpha):
    plt.imshow(img, alpha=alpha)
    plt.show()

现在,让我们先使用嵌套的装饰器显示一个没有轴标签的彩色图像:

plot_image(plt.imread('lena_color.jpg'), 0.4)

接下来,让我们使用嵌套的装饰器remove_axis和plot_gray显示一个没有轴标签的灰度图像(我们需要cmap='gray',否则默认的颜色映射是viridis,因此除非明确指定,否则默认情况下灰度图像不会以黑白色显示)

plot_image(plt.imread('lena_bw.jpg'), 0.8)

上述函数调用缩减为以下嵌套调用

remove_axis(plot_gray(plot_image))(img, alpha)