python装饰器、描述符模拟源码分析

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
''' 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 wrapsdef 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(): passif __name__ == "__main__":foo1()

  • 有参装饰器
''' 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 ERROS!!!!c must be ('a', 2, ['b', 'd'])''' from functools import wraps frominspect import signaturedef typeAssert(*args, **kwargs): deco_args = args deco_kwargs = kwargsdef 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 wrapperreturn 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
''' 假定有一个需求是: 输入类似代码: @makebold @makeitalic def say(): return "Hello"输出: Hello ''' from functools import wrapsdef 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 wrappedreturn 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'))# -> Hello world

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()
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__ = docdef __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 = valif __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).
class StaticMethod(object): "python代码实现staticmethod原理"def __init__(self, f): self.f = fdef __get__(self, obj, objtype=None): return self.fclass E(object): #StaticMethod=StaticMethod(f) @StaticMethod def f( x): return xif __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).
class ClassMethod(object): "python代码实现classmethod原理"def __init__(self, f): self.f = fdef __get__(self, obj, klass=None): if klass is None: klass = type(obj)def newfunc(*args): return self.f(klass, *args)return newfuncclass E(object): #ClassMethod=ClassMethod(f) @ClassMethod def f(cls,x): return xif __name__ == "__main__": print(E().f('classMethod Test'))

参考资料
1, statckoverflow: how to make a chain of decorators
【python装饰器、描述符模拟源码分析】2, python doc:how to descriptor
3,知乎:如何理解装饰器
4, difference-between-staticmethod-and-classmethod-in-python
5,meaning-of-classmethod-and-staticmethod-for-beginner

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