Python带参数的装饰器
在装饰器函数里传入参数
# -*- coding: utf-8 -*- # 2017/12/2 21:38 # 这不是什么黑魔法,你只需要让包装器传递参数: def a_decorator_passing_arguments(function_to_decorate):def a_wrapper_accepting_arguments(arg1, arg2):print("I got args! Look:", arg1, arg2)function_to_decorate(arg1, arg2)return a_wrapper_accepting_arguments# 当你调用装饰器返回的函数时,也就调用了包装器,把参数传入包装器里, # 它将把参数传递给被装饰的函数里.@a_decorator_passing_arguments def print_full_name(first_name, last_name):print("My name is", first_name, last_name)print_full_name("Peter", "Venkman") # 输出: #I got args! Look: Peter Venkman #My name is Peter Venkman
在Python里方法和函数几乎一样.唯一的区别就是方法的第一个参数是一个当前对象的(self
)
也就是说你可以用同样的方式来装饰方法!只要记得把self
加进去:
def method_friendly_decorator(method_to_decorate):def wrapper(self, lie):lie = lie - 3 # 女性福音 :-)return method_to_decorate(self, lie)return wrapperclass Lucy(object):def __init__(self):self.age = 32@method_friendly_decoratordef sayYourAge(self, lie):print("I am %s, what did you think?" % (self.age + lie))l = Lucy() l.sayYourAge(-3) #输出: I am 26, what did you think?
如果你想造一个更通用的可以同时满足方法和函数的装饰器,用*args,**kwargs
就可以了
def a_decorator_passing_arbitrary_arguments(function_to_decorate):# 包装器接受所有参数def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs):print("Do I have args?:")print(args)print(kwargs)# 现在把*args,**kwargs解包# 如果你不明白什么是解包的话,请查阅:# http://www.saltycrane.com/blog/2008/01/how-to-use-args-and-kwargs-in-python/function_to_decorate(*args, **kwargs)return a_wrapper_accepting_arbitrary_arguments@a_decorator_passing_arbitrary_arguments def function_with_no_argument():print("Python is cool, no argument here.")function_with_no_argument() #输出 #Do I have args?: #() #{} #Python is cool, no argument here.@a_decorator_passing_arbitrary_arguments def function_with_arguments(a, b, c):print(a, b, c)function_with_arguments(1,2,3) #输出 #Do I have args?: #(1, 2, 3) #{} #1 2 3@a_decorator_passing_arbitrary_arguments def function_with_named_arguments(a, b, c, platypus="Why not ?"):print("Do %s, %s and %s like platypus? %s" %(a, b, c, platypus))function_with_named_arguments("Bill", "Linus", "Steve", platypus="Indeed!") #输出 #Do I have args ? : #('Bill', 'Linus', 'Steve') #{'platypus': 'Indeed!'} #Do Bill, Linus and Steve like platypus? Indeed!class Mary(object):def __init__(self):self.age = 31@a_decorator_passing_arbitrary_argumentsdef sayYourAge(self, lie=-3): # 可以加入一个默认值print("I am %s, what did you think ?" % (self.age + lie))m = Mary() m.sayYourAge() #输出 # Do I have args?: #(<__main__.Mary object at 0xb7d303ac>,) #{} #I am 28, what did you think?
把参数传递给装饰器
好了,如何把参数传递给装饰器自己?
因为装饰器必须接收一个函数当做参数,所以有点麻烦.好吧,你不可以直接把被装饰函数的参数传递给装饰器.
在我们考虑这个问题时,让我们重新回顾下:
# 装饰器就是一个'平常不过'的函数 def my_decorator(func):print "I am an ordinary function"def wrapper():print "I am function returned by the decorator"func()return wrapper# 因此你可以不用"@"也可以调用他def lazy_function():print "zzzzzzzz"decorated_function = my_decorator(lazy_function) #输出: I am an ordinary function# 之所以输出 "I am an ordinary function"是因为你调用了函数, # 并非什么魔法.@my_decorator def lazy_function():print "zzzzzzzz"#输出: I am an ordinary function
看见了吗,和"my_decorator
"一样只是被调用.所以当你用@my_decorator
你只是告诉Python去掉用被变量my_decorator
标记的函数.
这非常重要!你的标记能直接指向装饰器.
def decorator_maker():print "I make decorators! I am executed only once: "+\"when you make me create a decorator."def my_decorator(func):print "I am a decorator! I am executed only when you decorate a function."def wrapped():print ("I am the wrapper around the decorated function. ""I am called when you call the decorated function. ""As the wrapper, I return the RESULT of the decorated function.")return func()print "As the decorator, I return the wrapped function."return wrappedprint "As a decorator maker, I return a decorator"return my_decorator# 让我们建一个装饰器.它只是一个新函数. new_decorator = decorator_maker() #输出: #I make decorators! I am executed only once: when you make me create a decorator. #As a decorator maker, I return a decorator# 下面来装饰一个函数def decorated_function():print "I am the decorated function."decorated_function = new_decorator(decorated_function) #输出: #I am a decorator! I am executed only when you decorate a function. #As the decorator, I return the wrapped function# Let’s call the function: decorated_function() #输出: #I am the wrapper around the decorated function. I am called when you call the decorated function. #As the wrapper, I return the RESULT of the decorated function. #I am the decorated function.
下面让我们去掉所有可恶的中间变量:
def decorated_function():print "I am the decorated function." decorated_function = decorator_maker()(decorated_function) #输出: #I make decorators! I am executed only once: when you make me create a decorator. #As a decorator maker, I return a decorator #I am a decorator! I am executed only when you decorate a function. #As the decorator, I return the wrapped function.# 最后: decorated_function() #输出: #I am the wrapper around the decorated function. I am called when you call the decorated function. #As the wrapper, I return the RESULT of the decorated function. #I am the decorated function.
让我们简化一下:
@decorator_maker() def decorated_function():print "I am the decorated function." #输出: #I make decorators! I am executed only once: when you make me create a decorator. #As a decorator maker, I return a decorator #I am a decorator! I am executed only when you decorate a function. #As the decorator, I return the wrapped function.#最终: decorated_function() #输出: #I am the wrapper around the decorated function. I am called when you call the decorated function. #As the wrapper, I return the RESULT of the decorated function. #I am the decorated function.
看到了吗?我们用一个函数调用"@
"语法!:-)
所以让我们回到装饰器的.如果我们在函数运行过程中动态生成装饰器,我们是不是可以把参数传递给函数?
def decorator_maker_with_arguments(decorator_arg1, decorator_arg2):print "I make decorators! And I accept arguments:", decorator_arg1, decorator_arg2def my_decorator(func):# 这里传递参数的能力是借鉴了 closures.# 如果对closures感到困惑可以看看下面这个:# http://stackoverflow.com/questions/13857/can-you-explain-closures-as-they-relate-to-pythonprint "I am the decorator. Somehow you passed me arguments:", decorator_arg1, decorator_arg2# 不要忘了装饰器参数和函数参数!def wrapped(function_arg1, function_arg2) :print ("I am the wrapper around the decorated function.\n""I can access all the variables\n""\t- from the decorator: {0} {1}\n""\t- from the function call: {2} {3}\n""Then I can pass them to the decorated function".format(decorator_arg1, decorator_arg2,function_arg1, function_arg2))return func(function_arg1, function_arg2)return wrappedreturn my_decorator@decorator_maker_with_arguments("Leonard", "Sheldon") def decorated_function_with_arguments(function_arg1, function_arg2):print ("I am the decorated function and only knows about my arguments: {0}"" {1}".format(function_arg1, function_arg2))decorated_function_with_arguments("Rajesh", "Howard") #输出: #I make decorators! And I accept arguments: Leonard Sheldon #I am the decorator. Somehow you passed me arguments: Leonard Sheldon #I am the wrapper around the decorated function. #I can access all the variables # - from the decorator: Leonard Sheldon # - from the function call: Rajesh Howard #Then I can pass them to the decorated function #I am the decorated function and only knows about my arguments: Rajesh Howard
上面就是带参数的装饰器.参数可以设置成变量:
c1 = "Penny" c2 = "Leslie"@decorator_maker_with_arguments("Leonard", c1) def decorated_function_with_arguments(function_arg1, function_arg2):print ("I am the decorated function and only knows about my arguments:"" {0} {1}".format(function_arg1, function_arg2))decorated_function_with_arguments(c2, "Howard") #输出: #I make decorators! And I accept arguments: Leonard Penny #I am the decorator. Somehow you passed me arguments: Leonard Penny #I am the wrapper around the decorated function. #I can access all the variables # - from the decorator: Leonard Penny # - from the function call: Leslie Howard #Then I can pass them to the decorated function #I am the decorated function and only knows about my arguments: Leslie Howard
你可以用这个小技巧把任何函数的参数传递给装饰器.如果你愿意还可以用*args,**kwargs
.但是一定要记住了装饰器只能被调用一次.当Python载入脚本后,你不可以动态的设置参数了.当你运行import x
,函数已经被装饰,所以你什么都不能动了.
functools
模块在2.5被引进.它包含了一个functools.wraps()
函数,可以复制装饰器函数的名字,模块和文档给它的包装器.
如何为被装饰的函数保存元数据解决方案:使用标准库functools中的装饰器wraps 装饰内部包裹函数,可以 制定将原函数的某些属性,更新到包裹函数的上面其实也可以通过wrapper.name = func.nameupdate_wrapper(wrapper, func, (‘name‘,’doc‘), (‘dict‘,))f.__name__ 函数的名字f.__doc__ 函数文档字符串f.__module__ 函数所属模块名称f.__dict__ 函数的属性字典f.__defaults__ 默认参数元组f.__closure__ 函数闭包
>>> def f(): ... a=2 ... return lambda k:a**k ... >>> g=f() >>> g.__closure__ (<cell at 0x000001888D17F2E8: int object at 0x0000000055F4C6D0>,) >>> c=g.__closure__[0] >>> c.cell_contents 2
from functools import wraps,update_wrapper def log(level="low"):def deco(func):@wraps(func)def wrapper(*args,**kwargs):''' I am wrapper function'''print("log was in...")if level == "low":print("detailes was needed")return func(*args,**kwargs)#wrapper.__name__ = func.__name__#update_wrapper(wrapper, func, ('__name__','__doc__'), ('__dict__',))return wrapperreturn deco@log() def myFunc():'''I am myFunc...'''print("myFunc was called")print(myFunc.__name__) print(myFunc.__doc__) myFunc()""" myFunc I am myFunc... log was in... detailes was needed myFunc was called """
如何定义带参数的装饰器
实现一个装饰器,它用来检查被装饰函数的参数类型,装饰器可以通过参数指明函数参数的类型,
调用时如果检测出类型不匹配则抛出异常。
提取函数签名python3 inspect.signature()
带参数的装饰器,也就是根据参数定制化一个装饰器可以看生成器的工厂
每次调用typeassert,返回一个特定的装饰器,然后用它去装饰其他函数
>>> from inspect import signature >>> def f(a,b,c=1):pass >>> sig=signature(f) >>> sig.parameters mappingproxy(OrderedDict([('a', <Parameter "a">), ('b', <Parameter "b">), ('c', <Parameter "c=1">)])) >>> a=sig.parameters['a'] >>> a.name 'a' >>> a <Parameter "a"> >>> dir(a) ['KEYWORD_ONLY', 'POSITIONAL_ONLY', 'POSITIONAL_OR_KEYWORD', 'VAR_KEYWORD', 'VAR_POSITIONAL', '__class__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setstate__', '__sizeof__', '__slots__', '__str__', '__subclasshook__', '_annotation', '_default', '_kind', '_name', 'annotation', 'default', 'empty', 'kind', 'name', 'replace'] >>> a.kind <_ParameterKind.POSITIONAL_OR_KEYWORD: 1> >>> a.default <class 'inspect._empty'> >>> c=sig.parameters['c'] >>> c.default 1 >>> sig.bind(str,int,int) <BoundArguments (a=<class 'str'>, b=<class 'int'>, c=<class 'int'>)> >>> bargs=sig.bind(str,int,int) >>> bargs.arguments OrderedDict([('a', <class 'str'>), ('b', <class 'int'>), ('c', <class 'int'>)]) >>> bargs.arguments['a'] <class 'str'> >>> bargs.arguments['b'] <class 'int'>
from inspect import signature def typeassert(*ty_args,**ty_kargs):def decorator(func):#func ->a,b#d = {'a':int,'b':str}sig = signature(func)btypes = sig.bind_partial(*ty_args,**ty_kargs).argumentsdef wrapper(*args,**kargs):#arg in d,instance(arg,d[arg])for name, obj in sig.bind(*args,**kargs).arguments.items():if name in btypes:if not isinstance(obj,btypes[name]):raise TypeError('"%s" must be "%s"' %(name,btypes[name]))return func(*args,**kargs)return wrapperreturn decorator@typeassert(int,str,list) def f(a,b,c):print(a,b,c)f(1,'abc',[1,2,3]) # f(1,2,[1,2,3])
如何实现属性可修改的函数装饰器
为分析程序内哪些函数执行时间开销较大,我们定义一个带timeout参数的函数装饰器,装饰功能如下:
1.统计被装饰函数单词调用运行时间
2.时间大于参数timeout的,将此次函数调用记录到log日志中
3.运行时可修改timeout的值。
解决方案:
python3 nolocal
为包裹函数添加一个函数,用来修改闭包中使用的自由变量.
python中,使用nonlocal访问嵌套作用域中的变量引用,或者在python2中列表方式,这样就不会在函数本地新建一个局部变量
from functools import wraps import time import logging def warn(timeout):# timeout = [timeout]def deco(func):def wrapper(*args,**kwargs):start = time.time()res = func(*args,**kwargs)used = time.time() -startif used > timeout:msg = '"%s" : %s > %s'%(func.__name__,used,timeout)logging.warn(msg)return resdef setTimeout(k):nonlocal timeout# timeout[0] = ktimeout=kprint("timeout was given....")wrapper.setTimeout = setTimeoutreturn wrapperreturn decofrom random import randint @warn(1.5) def test():print("in test...")while randint(0,1):time.sleep(0.5)for _ in range(30):test()test.setTimeout(1) print("after set to 1....") for _ in range(30):test()
小练习:
#为了debug,堆栈跟踪将会返回函数的 __name__ def foo():print("foo")print(foo.__name__) #输出: foo ######################################## # 如果加上装饰器,将变得有点复杂 def bar(func):def wrapper():print("bar")return func()return wrapper@bar def foo():print("foo")print(foo.__name__) #输出: wrapper ####################################### # "functools" 将有所帮助 import functoolsdef bar(func):# 我们所说的"wrapper",正在包装 "func",# 好戏开始了@functools.wraps(func)def wrapper():print("bar")return func()return wrapper@bar def foo():print("foo")print(foo.__name__) #输出: foo
转载于:https://www.cnblogs.com/ExMan/p/10171142.html
Python带参数的装饰器相关推荐
- Python 带参数的装饰器
带参数的装饰器讲解 # !/usr/bin/env python # -*- coding:utf-8 -*-# 1.带参数的装饰器 def wrapper_out(parameter):print( ...
- python带参数的装饰器_Python-----带参数的装饰器以及补充
带参数的装饰器 def wrapper_out(n): # def wrapper(f): # def inner(*args,**kwargs): # # if n == 'qq': # # use ...
- python带参数的装饰器的作用_Python带参数的装饰器运行原理解析
关于装饰器的理解,特别像<盗梦空间>中的进入梦境和从梦境出来的过程,一层一层的深入梦境,然后又一层一层的返回,被带入梦境的是被装饰的函数,装饰器就是使人入梦的工具. 上代码: from f ...
- python 装饰器 参数-python函数装饰器之带参数的函数和带参数的装饰器用法示例...
本文实例讲述了python函数装饰器之带参数的函数和带参数的装饰器用法.分享给大家供大家参考,具体如下: 1. 函数带多个参数 # 普通的装饰器, 打印函数的运行时间 def decrator(fun ...
- python 装饰器 参数-[Python]写个带参数的装饰器
上篇文章 Python装饰器为什么难理解?从函数到装饰器一步一步介绍了Python装饰器的来由,不知你对装饰器理解了没有,强烈建议你自己动手写个装饰器应用到项目中加深理解.装饰器可以很简单,也可以很复 ...
- python装饰器函数-python函数装饰器之带参数的函数和带参数的装饰器用法示例
本文实例讲述了python函数装饰器之带参数的函数和带参数的装饰器用法.分享给大家供大家参考,具体如下: 1. 函数带多个参数 # 普通的装饰器, 打印函数的运行时间 def decrator(fun ...
- Python:闭包(简介、使用方法、nonlocal修改闭包内使用的外部变量)、装饰器(定义、作用、通用装饰器、多个装饰器、带参数的装饰器、类装饰器、装饰器方式添加WEB框架的路由)
一.闭包的介绍 闭包可以保存函数内的变量 当闭包执行完毕,外部函数的变量才释放. # 闭包的作用:可以保存外部函数的变量 # 闭包的形成条件 # 1.函数嵌套 # 2.内部函数使用了外部函数的变量或者 ...
- python装饰器模式带参数_Python进阶(七)----带参数的装饰器,多个装饰器修饰同一个函数和递归简单案例(斐波那契数列)...
Python进阶(七)----带参数的装饰器,多个装饰器修饰同一个函数和递归简单案例(斐波那契数列) 一丶带参数的装饰器 def wrapper_out(pt): def wrapper(func): ...
- python装饰器模式带参数_python函数装饰器、类装饰器和带参数的装饰器——装饰器模式...
装饰器模式: 动态地给对象添加一些额外的职责,就增加功能来说,装饰模式比生产子类更加灵活 Component 是定义一个对象接口,可以给这些对象动态地添加职责.concreteComponent是定义 ...
最新文章
- 线程通信问题--生产者和消费者问题
- 垃圾回收器机制(二):快速解读GC算法之标记-清除,复制及标记整理-算法
- 022_Table表格
- 最短路径·三:SPFA算法 HihoCoder - 1093 (spfa无向图)
- c++调用Java以及string互转
- kafka 集群服役新节点
- sql 时态表的意义_SQL Server中的时态表
- docker 安装mysql_安装docker并使用docker安装mysql
- mysql绿盟扫描_绿盟软件扫描到存储的安全隐患处理措施
- m4s格式转换mp3_AnyMP4 MP3 Converter for Mac(音视频mp3格式转换工具)
- 室内空气流动原理图_空气流动基本原理
- Gradle编译时,assets文件未打包进apk
- You are what you read 笔记
- 格式化代码_格式化代码是什么意思​
- 玉米社:SEM竞价推广转化成本高?做好细节转化率蹭蹭往上涨
- 立创EDA的元件库导入AD
- 河南省 第十一届 ACM 省赛 试题
- QT学习的相关博客论坛
- 如何在Mac上安装的Skype
- 你猜,帕特∙基辛格、郭尊华、郭为、田溯宁为什么相视而笑?
热门文章
- 祝贺!港中文助理教授周博磊宣布加入UCLA
- 重磅 | 华为自动驾驶团队公开招聘!
- 好书荐读:阿里达摩院算法专家领衔《深度学习与图像识别:原理与实践》
- typeorm 表名_typeORM 多对多关系不同情况的处理
- 推荐系统遇上深度学习(五)--DeepCross Network模型理论和实践
- linux镜像包含数据库数据么,docker 镜像中包含数据库环境和运行环境
- linux转码软件下载,格式工厂linux版
- mysql 客户端_Linux桌面应用之MySQL客户端DBeaver
- Centos 安装 JDK8
- 2021年下半年系统集成项目管理工程师案例分析真题及答案解析