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python实现装饰器、描述符

时间:2021-01-18 00:34     来源/作者:Geekrun

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

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