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() |
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' ])) |
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> |
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 |
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' )) |
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' )) |
原文链接:https://segmentfault.com/a/1190000013425128