概要
本人python理论知识远达不到传授级别,写文章主要目的是自我总结,并不能照顾所有人,请见谅,文章结尾贴有相关链接可以作为补充
全文分为三个部分装饰器理论知识、装饰器应用、装饰器延申
- 装饰理基础:无参装饰器、有参装饰器、functiontools、装饰器链
- 装饰器进阶:property、staticmethod、classmethod源码分析(python代码实现)
装饰器基础
无参装饰器
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'''
假定有一个需求是:打印程序函数运行顺序
此案例打印的结果为:
foo1 function is starting
foo2 function is starting
'''
from functools import wraps
def NoParamDec(func):
#函数在被装饰器装时后,其函数属性也会改变,wraps作用就是保证被装饰函数属性不变
@wraps (func)
def warpper( * args, * * kwargs):
print ( '{} function is starting' . format (func.__name__))
return func( * args, * * kwargs)
return warpper
#python黑魔法省略了NoParamDec=NoParamDec(foo1)
@NoParamDec
def foo1():
foo2()
@NoParamDec
def foo2():
pass
if __name__ = = "__main__" :
foo1()
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有参装饰器
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'''
假定有一个需求是:检查函数参数的类型,只允许匹配正确的函数通过程序
此案例打印结果为:
('a', 'b', 'c')
-----------------------分割线------------------------
ERROS!!!!b must be <class 'str'>
ERROS!!!!c must be <class 'str'>
('a', 2, ['b', 'd'])
'''
from functools import wraps
from inspect import signature
def typeAssert( * args, * * kwargs):
deco_args = args
deco_kwargs = kwargs
def factor(func):
#python标准模块类,可以用来检查函数参数类型,只允许特定类型通过
sig = signature(func)
#将函数形式参数和规定类型进行绑定
check_bind_args = sig.bind_partial( * deco_args, * * deco_kwargs).arguments
@wraps (func)
def wrapper( * args, * * kwargs):
#将实际参数值和形式参数进行绑定
wrapper_bind_args = sig.bind( * args, * * kwargs).arguments.items()
for name, obj in wrapper_bind_args:
#遍历判断是否实际参数值是规定参数的实例
if not isinstance (obj, check_bind_args[name]):
try :
raise TypeError( 'ERROS!!!!{arg} must be {obj} ' . format ( * * { 'arg' : name, 'obj' : check_bind_args[name]}))
except Exception as e:
print (e)
return func( * args, * * kwargs)
return wrapper
return factor
@typeAssert ( str , str , str )
def inspect_type(a, b, c):
return (a, b, c)
if __name__ = = "__main__" :
print (inspect_type( 'a' , 'b' , 'c' ))
print ( '{:-^50}' . format ( '分割线' ))
print (inspect_type( 'a' , 2 , [ 'b' , 'd' ]))
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装饰器链
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'''
假定有一个需求是:
输入类似代码:
@makebold
@makeitalic
def say():
return "Hello"
输出:
<b><i>Hello</i></b>
'''
from functools import wraps
def html_deco(tag):
def decorator(fn):
@wraps (fn)
def wrapped( * args, * * kwargs):
return '<{tag}>{fn_result}<{tag}>' . format ( * * { 'tag' : tag, 'fn_result' : fn( * args, * * kwargs)})
return wrapped
return decorator
@html_deco ( 'b' )
@html_deco ( 'i' )
def greet(whom = ''):
# 等价于 geet=html_deco('b')(html_deco('i)(geet))
return 'Hello' + ( ' ' + whom) if whom else ''
if __name__ = = "__main__" :
print (greet( 'world' )) # -> <b><i>Hello world</i></b>
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装饰器进阶
property 原理
通常,描述符是具有“绑定行为”的对象属性,其属性访问已经被描述符协议中的方法覆盖。这些方法是__get__()、__set__()和__delete__()。如果一个对象定义这些方法中的任何一个,它被称为一个描述符。如果对象定义__get__()和__set__(),则它被认为是数据描述符。仅定义__get__()的描述器称为非数据描述符(它们通常用于方法,但是其他用途也是可能的)。
属性查找优先级为:
- 类属性
- 数据描述符
- 实例属性
- 非数据描述符
- 默认为__getattr__()
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class Property ( object ):
'''
内部property是用c实现的,这里用python模拟实现property功能
代码参考官方doc文档
'''
def __init__( self , fget = None , fset = None , fdel = None , doc = None ):
self .fget = fget
self .fset = fset
self .fdel = fdel
self .__doc__ = doc
def __get__( self , obj, objtype = None ):
if obj is None :
return self
if self .fget is None :
raise (AttributeError, "unreadable attribute" )
print ( 'self={},obj={},objtype={}' . format ( self ,obj,objtype))
return self .fget(obj)
def __set__( self , obj, value):
if self .fset is None :
raise (AttributeError, "can't set attribute" )
self .fset(obj, value)
def __delete__( self , obj):
if self .fdel is None :
raise (AttributeError, "can't delete attribute" )
self .fdel(obj)
def getter( self , fget):
return type ( self )(fget, self .fset, self .fdel, self .__doc__)
def setter( self , fset):
return type ( self )( self .fget, fset, self .fdel, self .__doc__)
def deleter( self , fdel):
return type ( self )( self .fget, self .fset, fdel, self .__doc__)
class Student( object ):
@Property
def score( self ):
return self ._score
@score .setter
def score( self , val ):
if not isinstance ( val, int ):
raise ValueError( 'score must be an integer!' )
if val > 100 or val < 0 :
raise ValueError( 'score must between 0 ~ 100!' )
self ._score = val
if __name__ = = "__main__" :
s = Student()
s.score = 60
s.score
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staticmethod 原理
@staticmethod means: when this method is called, we don't pass an instance of the class to it (as we normally do with methods). This means you can put a function inside a class but you can't access the instance of that class (this is useful when your method does not use the instance).
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class StaticMethod ( object ):
"python代码实现staticmethod原理"
def __init__( self , f):
self .f = f
def __get__( self , obj, objtype = None ):
return self .f
class E( object ):
#StaticMethod=StaticMethod(f)
@StaticMethod
def f( x):
return x
if __name__ = = "__main__" :
print (E.f( 'staticMethod Test' ))
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classmethod
@staticmethod means: when this method is called, we don't pass an instance of the class to it (as we normally do with methods). This means you can put a function inside a class but you can't access the instance of that class (this is useful when your method does not use the instance).
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class ClassMethod ( object ):
"python代码实现classmethod原理"
def __init__( self , f):
self .f = f
def __get__( self , obj, klass = None ):
if klass is None :
klass = type (obj)
def newfunc( * args):
return self .f(klass, * args)
return newfunc
class E( object ):
#ClassMethod=ClassMethod(f)
@ClassMethod
def f( cls ,x):
return x
if __name__ = = "__main__" :
print (E().f( 'classMethod Test' ))
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原文链接:https://segmentfault.com/a/1190000013425128