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我终于弄懂了Python的装饰器(二)

此系列文档:

1. 我终于弄懂了Python的装饰器(一)

2. 我终于弄懂了Python的装饰器(二)

3. 我终于弄懂了Python的装饰器(三)

4. 我终于弄懂了Python的装饰器(四)

二、装饰器的高级用法
将参数传递给装饰函数
#它不是黑魔法,只是给包装(wrapper)传递参数:

def a_decorator_passing_arguments(function_to_decorate):
def a_wrapper_accepting_arguments(arg1, arg2):
print(“I got args! Look: {0}, {1}”.format(arg1, arg2))
function_to_decorate(arg1, arg2)
return a_wrapper_accepting_arguments

#因为当您调用装饰器返回的函数时,调用的包装器(wrapper),将参数传递给被包装器包装的函数

@a_decorator_passing_arguments
def print_full_name(first_name, last_name):
print(“My name is {0} {1}”.format(first_name, last_name))

print_full_name(“Peter”, “Venkman”)
# 输出:
#I got args! Look: Peter Venkman
#My name is Peter Venkman
将参数传递给装饰器
关于将参数传递给装饰器本身,您怎么认为?

因为装饰器必须接受一个函数作为参数,所以这可能会有些别扭。

因此,您不能将装饰函数的参数直接传递给装饰器。

在寻求解决方案之前,让我们写一些提醒:

#装饰器是普通函数
def my_decorator(func):
print(“I am an ordinary function”)
def wrapper():
print(“I am function returned by the decorator”)
func()
return wrapper

# 因此,你可以调用它,而不用 “@”

def lazy_function():
print(“zzzzzzzz”)

decorated_function = my_decorator(lazy_function)
#输出: I am an ordinary function

# 它输出了 “I am an ordinary function”, 因为你只是调用了装饰器,而没有调用函数:
# 这里没有什么神奇的地方,使用’@’

@my_decorator
def lazy_function():
print(“zzzzzzzz”)

#outputs: I am an ordinary function
结果一样。
my_decorator”被调用了。
因此,当您使用时@my_decorator,您要告诉Python,通过变量来调用my_decorator标记了的函数。

def decorator_maker():

print(“I make decorators! I am executed only once: ”
“when you make me create a decorator.”)

def my_decorator(func):

print(“I am a decorator! I am executed only when you decorate a function.”)

def wrapped():
print(“I am the wrapper around the decorated function. ”
“I am called when you call the decorated function. ”
“As the wrapper, I return the RESULT of the decorated function.”)
return func()

print(“As the decorator, I return the wrapped function.”)

return wrapped

print(“As a decorator maker, I return a decorator”)
return my_decorator

#让我们新建一个装饰器
new_decorator = decorator_maker()
#输出:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator

# 让我们装饰这个函数
def decorated_function():
print(“I am the decorated function.”)

decorated_function = new_decorator(decorated_function)
#输出:
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function

# 让我们调用这个函数
decorated_function()

#输出:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.
毫不奇怪,跟我们前边演示的内容一样。

让我们再做一次完全一样的事情,但是这次我们跳过所有讨厌的中间变量:

def decorated_function():
print(“I am the decorated function.”)
decorated_function = decorator_maker()(decorated_function)
#输出:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

# Finally:
decorated_function()
#输出:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.
让我们把它变的更精简:

@decorator_maker()
def decorated_function():
print(“I am the decorated function.”)
#输出:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

#最终:
decorated_function()
#输出:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.
嘿,你看到了吗?我们使用了带有“ @”语法的函数调用!

因此,回到带有参数的装饰器。
如果我们可以使用函数即时生成装饰器,则可以将参数传递给该函数,对吗?

def decorator_maker_with_arguments(decorator_arg1, decorator_arg2):

print(“I make decorators! And I accept arguments: {0}, {1}”.format(decorator_arg1, decorator_arg2))

def my_decorator(func):
#这里传递的参数是闭包的。
#如果您对封包感到不舒服,可以忽略这点。
print(“I am the decorator. Somehow you passed me arguments: {0}, {1}”.format(decorator_arg1, decorator_arg2))

#不要混淆装饰器参数和函数参数!
def wrapped(function_arg1, function_arg2) :
print(“I am the wrapper around the decorated function.\n”
“I can access all the variables\n”
“\t- from the decorator: {0} {1}\n”
“\t- from the function call: {2} {3}\n”
“Then I can pass them to the decorated function”
.format(decorator_arg1, decorator_arg2,
function_arg1, function_arg2))
return func(function_arg1, function_arg2)

return wrapped

return my_decorator

@decorator_maker_with_arguments(“Leonard”, “Sheldon”)
def decorated_function_with_arguments(function_arg1, function_arg2):
print(“I am the decorated function and only knows about my arguments: {0}”
” {1}”.format(function_arg1, function_arg2))

decorated_function_with_arguments(“Rajesh”, “Howard”)
#输出:
#I make decorators! And I accept arguments: Leonard Sheldon
#I am the decorator. Somehow you passed me arguments: Leonard Sheldon
#I am the wrapper around the decorated function.
#I can access all the variables
# – from the decorator: Leonard Sheldon
# – from the function call: Rajesh Howard
#Then I can pass them to the decorated function
#I am the decorated function and only knows about my arguments: Rajesh Howard
记住它:带参数的装饰器,可以将变量作为参数:

c1 = “Penny”
c2 = “Leslie”

@decorator_maker_with_arguments(“Leonard”, c1)
def decorated_function_with_arguments(function_arg1, function_arg2):
print(“I am the decorated function and only knows about my arguments:”
” {0} {1}”.format(function_arg1, function_arg2))

decorated_function_with_arguments(c2, “Howard”)
#输出:
#I make decorators! And I accept arguments: Leonard Penny
#I am the decorator. Somehow you passed me arguments: Leonard Penny
#I am the wrapper around the decorated function.
#I can access all the variables
# – from the decorator: Leonard Penny
# – from the function call: Leslie Howard
#Then I can pass them to the decorated function
#I am the decorated function and only know about my arguments: Leslie Howard
如您所见,您可以像任何函数传递参数一样传递参数给装饰器。
您甚至可以根据需要使用*args, **kwargs。
但是请记住,装饰器仅被调用一次,仅在Python导入脚本时。之后,您将无法动态设置参数。
当您执行“ import x”时,该函数已经被修饰,因此您无法进行任何更改。

 

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