Introduction to Python Decorators

Before you know the adorner, be sure to understand the function as a parameter pass, what is the function inline, please refer to my previous blog function introduction

The Python decorator idea is somewhat similar to the decorative pattern of the design pattern, with the intention of dynamically adding additional functionality to the function object. Like the ability to add log printing, it's a bit of a facet-oriented programming (AOP) feeling.

Adorner syntax

Begins with @, followed by the adorner's name and optional parameters. Decorator syntax is a syntactic sugar.
The format is as follows

@decomaker(deco_args)    def foo(func_opt_args)

Can be combined, equivalent to Foo = g (f (foo))

@g@fdef foo():    statement

Simple decorator

Instance

#!/usr/bin/pythondef  deco(func):    print‘start‘    func()    print‘end‘    return func@decodef foo():    print‘In foo‘foo()foo()

Output

startIn fooendIn fooIn foo

With inline function adorner

Inline function guarantees that each new function is called
Instance

def  deco(func):    def _deco():    #该函数为内嵌函数        print‘start‘        func()        print‘end‘     return _deco@decodef foo():    print‘In foo‘foo()foo()

Output:

startIn fooendstartIn fooend

Adorner with parameters

You need to return the adorner with the function as a parameter. In other words, Decomaker () did something with Deco_args and returned
A function object, which is an adorner with Foo as its argument. Simply put: foo = Decomaker (Deco_args) (foo)

Instance

 defdeco(ARG):       def wrapper(func):         def _deco(x):            Print "Get param is:", x func (x)return_decoreturnWrapper@deco ("type1") def foo(x):    Print ' in foo 'Foo123)

Output

getis:  123In foo

Introduction to Python Decorators