查看“Python闭包和装饰器”的源代码

要先理解闭包，再理解装饰器

==闭包==
<pre>
 什么是闭包

#定义一个函数
def test(number):

    #在函数内部再定义一个函数，并且这个函数用到了外边函数的变量，那么将这个函数以及用到的一些变量称之为闭包
    def test_in(number_in):
        print("in test_in 函数, number_in is %d"%number_in)
        return number+number_in
    #其实这里返回的就是闭包的结果
    return test_in


#给test函数赋值，这个20就是给参数number
这时候 ret 指向是test_in 也就是里面的那个function
ret = test(20)

#注意这里的100其实给参数number_in
print(ret(100))

#注意这里的200其实给参数number_in
print(ret(200))
运行结果：


in test_in 函数, number_in is 100
120

in test_in 函数, number_in is 200
220

cat 1.py 
"""
--1--
--3--
*************************
--2--
200

"""
def test(number):

    print("--1--")

    def test_in():
        print("--2--")
        print(number+100)

    print("--3--")
    return test_in
ret = test(100)
print("*"*25)
ret()


  
def test(number):

    print("--1--")

    def test_in():
        print("--2--")
        print(number+100)

    print("--3--")
    return test_in

test(100)
#ret = test(100)

"""
--1--
--3--
"""

def test(number):

    print("--1--")

    def test_in(number2):
        print("--2--")
        print(number+number2)

    print("--3--")
    return test_in


ret = test(100)
print("-"*30)
ret(1)
ret(100)
ret(200)

"""
 python3  01-闭包/01-闭包1.py 
--1--
--3--
------------------------------
--2--
101
--2--
200
--2--
300

"""
</pre>

==装饰器==
<pre>

现在，假设我们要增强now()函数的功能，比如，在函数调用前后自动打印日志，但又不希望修改now()函数的定义，这种在代码运行期间动态增加功能的方式，称之为“装饰器”（Decorator）。

本质上，decorator就是一个返回函数的高阶函数。所以，我们要定义一个能打印日志的decorator，可以定义如下：

把@log放到now()函数的定义处，相当于执行了语句：
now = log(now)



"""
---正在验证权限----
---f1---
"""
def w1(func):
    def inner():
        print("---正在验证权限----")
        func()
    return inner

def f1():
    print("---f1---")

def f2():
    print("---f2---")

#innerFunc = w1(f1)
#innerFunc()

#这是的f1 其实是inner了  只有func才是原来的f1
f1 = w1(f1)  
f1()

运行流程如下  一开始是 f1 = w1(f1)   先算右边的 w1(f1)  这时候 func指向def f1 ，而左边的f1 为def inner  所以 运行最后一行 f1()时  就是先运行 inner fun 打印 ---正在验证权限----，第二步 func() 也就是原来的f1 fun 所以打印---f1---

不明请看下面的wrapp原理图片
<2019-03-28 四>

****************************分隔线**********************************************************

#定义函数：完成包裹数据
"""
----1---
----2---
----3---
<b><i>hello world-3</i></b>

"""
def makeBold(fn):
    def wrapped():
        print("----1---")
        return "<b>" + fn() + "</b>"
     return wrapped

#定义函数：完成包裹数据
def makeItalic(fn):
    def wrapped():
        print("----2---")
        return "<i>" + fn() + "</i>"
    return wrapped

@makeBold
@makeItalic
def test3():
    print("----3---")
    return "hello world-3"

ret = test3()
print(ret)



</pre>
[[File:Wrapper原理.png|Wrapper原理|50px]]


[[File:Wrapper2.png|Wrapper2|50px]]

==decorator2024 ==
<pre>
FUNCTION DECORATORS
Python decorators are a special syntax for functions which take other functions as arguments. Python
functions are objects, so any function can take a function as an argument. The decorator syntax provides a
clean and easy way to do this. The basic format of a decorator is:

In [2]: def some_decorator(wrapped_function):
def wrapper():
print('Do something before calling wrapped function')
wrapped_function()
print('Do something after calling wrapped function')
return wrapper

You can define a function and pass it as an argument to this function:

In [3]: def foobat():
...:
print('foobat')
...:
In [4]: f = some_decorator(foobat)
In [5]: f()
Do something before calling wrapped function
foobat
Do something after calling wrapped function

The decorator syntax simplifies this by indicating which function should be wrapped by decorating it with
@decorator_name. Here is an example using the decorator syntax with our some_decorator function:

In [6]: @some_decorator
...: def batfoo():
...:
print('batfoo')
...:
In [7]: batfoo()
Do something before calling wrapped function
batfoo
Do something after calling wrapped function

Now you call your wrapped function using its name rather than the decorator name. Pre-built functions
intended as decorators are offered both as part of the Python Standard Library (staticMethod,
classMethod) and as part of third-party packages, such as Flask and Click.

</pre>

=参考=

[https://www.zhihu.com/question/26930016 如何理解Python装饰器？]


[http://www.cnblogs.com/zhiyong-ITNote/p/7384955.html 深入浅出理解python 装饰器]


[https://www.cnblogs.com/rhcad/archive/2011/12/21/2295507.html Python装饰器学习（九步入门）]


https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000/0014318435599930270c0381a3b44db991cd6d858064ac0000

[http://book42qu.readthedocs.io/en/latest/python/python-closures-and-decorators.html Python 的闭包和装饰器]

https://segmentfault.com/a/1190000004461404

http://www.cnblogs.com/ChrisChen3121/p/3208119.html

https://www.zhihu.com/question/31792789

http://www.cnblogs.com/zhiyong-ITNote/p/7384955.html

[[category:python]]