“Python闭包和装饰器”的版本间的差异
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ret = test3() | ret = test3() | ||
print(ret) | print(ret) | ||
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[[File:Wrapper2.png|Wrapper2|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= | =参考= |
2024年11月12日 (二) 02:37的最新版本
要先理解闭包,再理解装饰器
闭包
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 """
装饰器
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)
decorator2024
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.
参考
https://segmentfault.com/a/1190000004461404
http://www.cnblogs.com/ChrisChen3121/p/3208119.html