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 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
'''
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
'''
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()
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).
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).
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'))
参考资料
1, statckoverflow: how to make a chain of decorators
2, python doc:how to descriptor
4, difference-between-staticmethod-and-classmethod-in-python
