python实现装饰器、描述符

Python  /  管理员 发布于 7年前   194

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)@NoParamDecdef foo1():  foo2()@NoParamDecdef 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 <class 'str'> ERROS!!!!c must be <class 'str'> ('a', 2, ['b', 'd'])  '''from functools import wrapsfrom inspect import signaturedef 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

'''假定有一个需求是：输入类似代码：@makebold@makeitalicdef say():  return "Hello"输出：<b><i>Hello</i></b>'''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 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__()

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 = 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 = f    def __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 = 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'))