{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.8 将装饰器定义为类的一部分\n",
    "* 问题：想在类中定义装饰器，并作用在其他的函数上\n",
    "* 方案：在类中定义装饰器首先要确定它的使用方法，是作为一个实例方法还是作为一个类方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import wraps\n",
    "class A:\n",
    "    #作为一个实例方法\n",
    "    def decorator1(self,func):\n",
    "        @wraps(func)\n",
    "        def wrapper(*args, **kwargs):\n",
    "            print(\"decorator 1\")\n",
    "            return func(*args,**kwargs)\n",
    "        return wrapper\n",
    "    #作为一个类方法\n",
    "    @classmethod\n",
    "    def decorator2(cls, func):\n",
    "        @wraps(func)\n",
    "        def wrapper(*args, **kwargs):\n",
    "            print(\"decorator 2\")\n",
    "            return func(*args,**kwargs)\n",
    "        return wrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#作为实列使用\n",
    "a = A()\n",
    "@a.decorator1\n",
    "def spam():\n",
    "    print('spam')\n",
    "#作为类方法使用\n",
    "@A.decorator2\n",
    "def grok():\n",
    "    print(\"grok\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 在类中定义装饰器很奇怪，但是标准库中有很多这种方式，@property装饰器实际上是一个类，他内部定义了三个方法getter()、setter()、deleter()每个方法都是装饰器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Person:\n",
    "    first_name = property()\n",
    "    @first_name.getter\n",
    "    def first_name(self):\n",
    "        return self._first_name\n",
    "    \n",
    "    @first_name.setter\n",
    "    def first_name(self,value):\n",
    "        if not isinstance(value,str):\n",
    "            raise TypeError(\"Expected a string\")\n",
    "        self._first_name = value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.9 将装饰器定义为类\n",
    "* 问题：想使用一个装饰器去包装函数，但是希望返回一个可以调用的实例。需要让装饰器可以同时工作在类定义的内部和外部\n",
    "* 方案：为了将装饰器定义成一个实例，需要确保它实现了\\_\\_call\\_\\_()、\\_\\_get\\_\\_()方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import types\n",
    "from functools import wraps\n",
    "class Profiled:\n",
    "    def __init__(self,func):\n",
    "        wraps(func)(self)\n",
    "        self.ncalls = 0\n",
    "    def __call__(self,*args, **kwargs):\n",
    "        self.ncalls += 1\n",
    "        return self.__wrapped__(*args, **kwargs)\n",
    "    def __get__(self, instance, cls):\n",
    "        if instance is None:\n",
    "            return self\n",
    "        else:\n",
    "            return types.MethodType(self,instance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 接下来你可以将它作为一个装饰器使用，在类内或者外面都可以"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "@Profiled\n",
    "def add(x, y):\n",
    "    return x + y\n",
    "\n",
    "class Spam:\n",
    "    @Profiled\n",
    "    def bar(self, x):\n",
    "        print(self, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add(4,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add.ncalls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Spam object at 0x00B65350> 1\n"
     ]
    }
   ],
   "source": [
    "s = Spam()\n",
    "s.bar(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Spam object at 0x00B65350> 2\n"
     ]
    }
   ],
   "source": [
    "s.bar(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Spam object at 0x00B65350> 10\n"
     ]
    }
   ],
   "source": [
    "s.bar(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Spam.bar.ncalls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 也可以使用闭包和nonlocal变量来实现装饰器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import types\n",
    "from functools import wraps\n",
    "def profiled(func):\n",
    "    ncalls = 0\n",
    "    @wraps(func)\n",
    "    def wrapper(*args,**kwargs):\n",
    "        nonlocal ncalls\n",
    "        ncalls += 1\n",
    "        return func(*args, **kwargs)\n",
    "    wrapper.ncalls = lambda: ncalls\n",
    "    return wrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@profiled\n",
    "def add(x,y):\n",
    "    return x+y\n",
    "add(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add(3,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add.ncalls()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.10 为类和静态方法提供装饰器\n",
    "* 问题：想要给类或者静态方法提供装饰器\n",
    "* 方案：在@classmethod或者@staticmethod之前定义"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from functools import wraps\n",
    "def timethis(func):\n",
    "    @wraps(func)\n",
    "    def wrapper(*args, **kwargs):\n",
    "        start = time.time()\n",
    "        r = func(*args,**kwargs)\n",
    "        end = time.time()\n",
    "        print(end-start)\n",
    "        return r\n",
    "    return wrapper\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Spam:\n",
    "    @timethis\n",
    "    def instance_method(self, n ):\n",
    "        print(self, n)\n",
    "        while n > 0:\n",
    "            n -= 1\n",
    "    @classmethod\n",
    "    @timethis\n",
    "    def class_method(cls,n):\n",
    "        print(cls,n)\n",
    "        while n > 0:\n",
    "            n -= 1\n",
    "            \n",
    "    @staticmethod\n",
    "    @timethis\n",
    "    def static_method(n):\n",
    "        print(n)\n",
    "        while n > 0:\n",
    "            n -= 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 装饰后的类和静态方法可以正常工作，但是增加了计时功能"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Spam object at 0x00B79510> 10000000\n",
      "0.7324073314666748\n"
     ]
    }
   ],
   "source": [
    "s = Spam()\n",
    "s.instance_method(10000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class '__main__.Spam'> 1000000\n",
      "0.12408709526062012\n"
     ]
    }
   ],
   "source": [
    "Spam.class_method(1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000000\n",
      "0.8057591915130615\n"
     ]
    }
   ],
   "source": [
    "Spam.static_method(10000000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 注意：在使用的时候上面代码中@staticmethod和@timethis的顺序不能调换"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 如果想要定义一个抽象类方法，可以使用下面的那样："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from abc import ABCMeta, abstractmethod\n",
    "class A(metaclass=ABCMeta):\n",
    "    @classmethod\n",
    "    @abstractmethod\n",
    "    def method(cls):\n",
    "        pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 上面的两个@也是不可以交换顺序的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.11 装饰器为被包装函数增加参数\n",
    "* 问题：想要给被包装的函数增加额外的参数，但是不可以改变该函数的现有调用规则\n",
    "* 方案：可以使用关键字参数来给被包装的函数增加额外的参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import wraps\n",
    "def optional_debug(func):\n",
    "    @wraps(func)\n",
    "    def wrapper(*args, debug=False, **kwargs):\n",
    "        if debug:\n",
    "            print('Calling ', func.__name__)\n",
    "        return func(*args,**kwargs)\n",
    "    return wrapper\n",
    "@optional_debug\n",
    "def spam(a,b,c):\n",
    "    print(a,b,c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "spam(1,2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling  spam\n",
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "spam(1,2,3,debug=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 通过装饰器给被包装的函数增加参数并不常见，但有事该方法可以避免代码的重复"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def a(x,debug=False):\n",
    "    if debug:\n",
    "        print(\"calling a\")\n",
    "def b(x,y,z,debug=False):\n",
    "    if debug:\n",
    "        print(\"calling b\")\n",
    "def c(x,y,debug=False):\n",
    "    print(\"calling c\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 我们可以将上述代码重写为：\n",
    "from functools import wraps\n",
    "import inspect\n",
    "def optional_debug(func):\n",
    "    if 'debug' in inspect.getfullargspec(func).args:\n",
    "        raise TypeError(\"debug argument already defined\")\n",
    "    @wraps(func)\n",
    "    def wrapper(*args, debug=False, **kwargs):\n",
    "        if debug:\n",
    "            print(\"calling \",func.__name__)\n",
    "        return func(*args,**kwargs)\n",
    "    return wrapper\n",
    "\n",
    "@optional_debug\n",
    "def a(x):\n",
    "    pass\n",
    "@optional_debug\n",
    "def b(x,y,z):\n",
    "    pass\n",
    "@optional_debug\n",
    "def c(x,y):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.12 使用装饰器扩充类的功能\n",
    "* 问题：想通过反省或者重写类定义来修改其部分i行为，但是不想使用继承\n",
    "* 方案：使用类装饰器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def log_getattribute(cls):\n",
    "    orig_getattribute = cls.__getattribute__\n",
    "    def new_getattribute(self, name):\n",
    "        print(\"getting : \",name)\n",
    "        return orig_getattribute(self, name)\n",
    "    cls.__getattribute__ = new_getattribute\n",
    "    return cls\n",
    "\n",
    "@log_getattribute\n",
    "class A:\n",
    "    def __init__(self, x):\n",
    "        self.x = x\n",
    "    def spam(self):\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting :  x\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "22"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = A(22)\n",
    "a.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting :  spam\n"
     ]
    }
   ],
   "source": [
    "a.spam()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.13 使用元类控制实例的创建\n",
    "* 问题：想要通过改变实例创建的方式来实现单例、缓存、等特性\n",
    "* 方案：如下"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 我们知道python创建的类可以像函数一样调用它来创建实例\n",
    "class Spam:\n",
    "    def __init__(self,name):\n",
    "        self.name = name\n",
    "a = Spam(\"Guido\")\n",
    "b = Spam(\"Diana\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 假设我们不想让任何人创建该类的实例\n",
    "class NoInstance(type):\n",
    "    def __call__(self,*args,**kwargs):\n",
    "        raise TypeError(\"can't instance directly\")\n",
    "class Spam(metaclass=NoInstance):\n",
    "    @staticmethod\n",
    "    def grok(x):\n",
    "        print(\"Spam.grok\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spam.grok\n"
     ]
    }
   ],
   "source": [
    "#这样我们只能调用该类的静态方法，而不能进行实例化\n",
    "Spam.grok(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can't instance directly",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-30-ee1b074714bf>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ms\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSpam\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-28-8781af2ac6ac>\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mNoInstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"can't instance directly\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mSpam\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmetaclass\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNoInstance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: can't instance directly"
     ]
    }
   ],
   "source": [
    "s = Spam()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 假如你仅仅想要创建一个实例（单例模式）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Singleton(type):\n",
    "    def __init__(self, *args,**kwargs):\n",
    "        self.__instance = None\n",
    "        super().__init__(*args,**kwargs)\n",
    "    def __call__(self,*args, **kwargs):\n",
    "        if self.__instance is None:\n",
    "            self.__instance = super().__call__(*args, **kwargs)\n",
    "            return self.__instance\n",
    "        else:\n",
    "            return self.__instance\n",
    "class Spam(metaclass = Singleton):\n",
    "    def __init__(self):\n",
    "        print(\"creating Spam\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating Spam\n"
     ]
    }
   ],
   "source": [
    "a = Spam()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = Spam()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a == b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 假设想要缓存实例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import weakref\n",
    "class Cached(type):\n",
    "    def __init__(self, *args, **kwargs):\n",
    "        super().__init__(*args, **kwargs)\n",
    "        self.__cache = weakref.WeakValueDictionary()\n",
    "    def __call__(self, *args):\n",
    "        if args in self.__cache:\n",
    "            return self.__cache[args]\n",
    "        else:\n",
    "            obj = super().__call__(*args)\n",
    "            self.__cache[args] = obj\n",
    "            return obj\n",
    "class Spam(metaclass=Cached):\n",
    "    def __init__(self,name):\n",
    "        print(\"creating Spam({!r})\".format(name))\n",
    "        self.name = name\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating Spam('Guodo')\n"
     ]
    }
   ],
   "source": [
    "a = Spam('Guodo')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating Spam('Diana')\n"
     ]
    }
   ],
   "source": [
    "b = Spam(\"Diana\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = Spam(\"Guodo\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#注意上面并没有重新创建\n",
    "a is c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a is b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9.14 捕获类的属性定义顺序\n",
    "* 问题：想要自动的记录一个类中属性和方法的定义顺序\n",
    "* 方案：利用元类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import OrderedDict\n",
    "class Typed:\n",
    "    _expected_type = type(None)\n",
    "    def __init__(self,name=None):\n",
    "        self._name = name\n",
    "    def __set__(self, instance, value):\n",
    "        if not isinstance(value, self._expected_type):\n",
    "            raise TypeError('type Error')\n",
    "        instance.__dict__[self._name] = value\n",
    "\n",
    "class Integer(Typed):\n",
    "    _expected_type = int\n",
    "class Float(Typed):\n",
    "    _expected_type = float\n",
    "class String(Typed):\n",
    "    _expected_type = str\n",
    "class OrderMeta(type):\n",
    "    def __new__(cls, clsname, bases, clsdict):\n",
    "        d = dict(clsdict)\n",
    "        order = []\n",
    "        for name, value in clsdict.items():\n",
    "            if isinstance(value, Typed):\n",
    "                value._name = name\n",
    "                order.append(name)\n",
    "        d['_order'] = order\n",
    "        return type.__new__(cls, clsname, bases, d)\n",
    "    @classmethod\n",
    "    def __prepare__(cls, clsname, bases):\n",
    "        return OrderedDict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 下面将使用上面代码将一个类实例的数据序列化为一个csv数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Structure(metaclass=OrderMeta):\n",
    "    def as_csv(self):\n",
    "        return ','.join(str(getattr(self,name)) for name in  self._order)\n",
    "class Stock(Structure):\n",
    "    name = String()\n",
    "    shares = Integer()\n",
    "    price = Float()\n",
    "    def __init__(self, name, shares, price):\n",
    "        self.name = name\n",
    "        self.shares = shares\n",
    "        self.price = price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'google'"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = Stock(\"google\",100, 234.19)\n",
    "s.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'google,100,234.19'"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.as_csv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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