1. 普通装饰器

 import logging

 1. foo = use_loggine(foo)
 def use_loggine(func):
 def wrapper():
  logging.warn("%s is running " % func.__name__)
  return func()
 return wrapper

 @use_loggine
 def foo():
 print "aaa"
 foo()
 print foo.__name__

2. func 需要参数：

foo = use_loggine(foo) 第一个参数就是func这个函数对象，不包含参数foo(params)

 def use_loggine(func):
 def wrapper(name):
  logging.warn("%s is running " % func.__name__)
  return func(name)
 return wrapper


 @use_loggine
 def foo(name):
 print "name is %s" % name

3. 装饰器带参数

 foo = use_logging('warn')(foo) 还是把被装饰的函数当做参数赋给装饰器

 def use_logging(level):
 def decorator(func):
 def wrapper(*args, **kwargs):
  if level == 'warn':
  logging.warn("%s is running" % func.__name__)
  elif level == 'info':
  logging.warn("%s is running" % func.__name__)
  return func(*args)
 return wrapper
 return decorator

 @use_logging('warn')
 def foo(name):
 print "i am %s" % name

 foo = use_logging('warn')(foo)
 print foo.__name__
 foo('foo')

4. 类装饰器，还是把被装饰的函数当做参数赋给装饰器

 foo = Foo(params)(func)

 class Foo(object):
 def __init__(self, name):
 self.name = name

 def __call__(self, func):
 def aa():
  print "class decorator running"
  print "name is :%s" % self.name
  func()
  print 'class decorator ending'
 return aa

 @Foo("hello")
 def bar():
 print "world"

 bar()

 @deco
 def foo()
 pass

 foo = deco(foo)

 @deco(xx)
 def foo():
 pass

 foo = deco(xx)(foo)

5. 类方法装饰器

类方法装饰器和其他装饰器没有什么区别，只不过在装饰器内部返回的函数中，第一个参数是固定的，是调用方法的对象本身，如

果是实例对象，就是self，是类方法的话，就是cls，静态方法的话，没有第一个参数。

 from functools import wraps


 def method_decor(func):
 @wraps(func)
 def wrapper(*args, **kwargs):
  try:
  u = func(*args, **kwargs)
  return u
  except Exception as e:
  args[0].bb() # args[0]就是self或者cls。可以在args前面定义self，更加方便u = func(self，*args, **kwargs)
  return 'an Exception raised.'

 return wrapper


 class Foo(object):

 @method_decor
 def aa(self):
  # print("This is wraped method")
  raise Exception('aa')

 def bb(self):
  print("This is called method")



 a = Foo()
 a.aa()

以上这篇python装饰器相当于函数的调用方式就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持python博客。