Python学习笔记（七）——魔法方法

1.构造和析造

魔法方法就是被双下划线包围的方法

__init__()方法

__init__方法默认没有参数，返回值为none。类实例化对象需有明确的初始化步骤要重写函数

>>> class Rectangle:
    def __init__(self,x,y):
        self.x = x
        self.y = y
    def getPeri(self):
        return (self.x+self.y)*2
    def getArea(self):
        return self.x * self.y

>>> rect = Rectangle(3,4)
>>> rect.getPeri()
14
>>> rect.getArea()
12
>>> #init返回值一定是None
>>> class A:
    def __init__(self):
        return "A"

>>> a = A()
Traceback (most recent call last):
  File "", line 1, in
    a = A()
TypeError: __init__() should return None, not 'str'

__new__()方法

__new__()方法在实例化对象时返回一个实例对象，参数是cls，是第一个被调用的方法

>>> class CapStr(str):
    def __new__(cls,string):
        string = string.upper()
        return str.__new__(cls,string)

>>> a = CapStr("I love FishC.com")
>>> a
'I LOVE FISHC.COM'

__del__()方法

__del__()方法在对象将要被销毁时被调用

>>> class C:
    def __init__(self):
        print("我是init方法，我被调用了")
    def __del__(self):
        print("我是del方法，我被调用了")

>>> c1 = C()
我是init方法，我被调用了
>>> c2 = c1
>>> c3 = c2
>>> del c3
>>> del c2
>>> del c1
我是del方法，我被调用了

对象生成后，所有对它的引用都被del之后，才会启动垃圾回收机制

关于垃圾回收机制

2.算数运算

运算符	对应的魔法方法	中文注释
+	__ add__(self, other)	加法
-	__ sub__(self, other)	减法
*	__ mul__(self, other)	乘法
/	__ truediv__(self, other)	真除法
//	__ floordiv__(self, other)	整数除法
%	__ mod__(self, other)	取余除法
divmod(a, b)	__ divmod__(self, other)	把除数和余数运算结果结合
**	__ pow__(self, other[,modulo])	self的other次方再对modulo取余
<<	__ lshift__(self, other)	按位左移
>>	__ rshift__(self, other)	按位右移
&	__ and__(self, other)	按位与操作
^	__ xor__(self, other)	按位异或操作(同为0，异为1)
丨	__ or__(self, other)	按位或操作(有1则1)

反运算的魔方方法

>>> class Nint(int):
    def __radd__(self,other):
        return int.__sub__(self,other)

>>> a = Nint(5)
>>> b = Nint(3)
>>> a + b
8
>>> 1 + b
2
>>> #此处执行了3-1，self是3，other是1

3. 简单定制(计时器)

time模块

import time as t

class MyTimer():
    def __init__(self):
        self.unit = ['年','月','日','小时','分','秒']
        self.prompt = "未开始计时！"
        self.lasted = []
        self.begin = 0
        self.end = 0
    # 调用实例直接显示结果
    def __str__(self):
        return self.prompt

    __repr__ = __str__

    # 计算两次计时器对象之和
    def __add__(self, other):
        prompt = "总共运行了"
        result = []
        for index in range(6):
            result.append(self.lasted[index] + other.lasted[index])
            if result[index]:
                prompt += (str(result[index]) + self.unit[index])
        return prompt

    # 开始计时
    def start(self):
        self.begin = t.localtime()
        self.prompt = "提示：请先调用stop()停止计时!"
        print("计时开始")

    # 停止计时

    def stop(self):
        if not self.begin:
            print("提示：请先调用start（）进行计时")
        else:
            self.end = t.localtime()
            self._calc()
            print("计时结束")

    # 内部方法，计算运行时间
    def _calc(self):
        self.lasted = []
        self.prompt = "总共运行了"
        for index in range(6):
            self.lasted.append(self.end[index] - self.begin[index])
            if self.lasted[index]:
                self.prompt += (str(self.lasted[index]) + self.unit[index])
        # 为下一轮计时初始化变量
        self.begin = 0
        self.end = 0
        print(self.prompt)

>>> t1 = MyTimer()
>>> t2 = MyTimer()
>>> t1.start()
计时开始
>>> t2.start()
计时开始
>>> t1.stop()
总共运行了1分21秒
计时结束
>>> t2.stop()
总共运行了15秒
计时结束
>>> t1
总共运行了1分21秒
>>> t2
总共运行了15秒
>>> t1+t2
'总共运行了1分36秒'

利用perf_counter()和process_time()

import time as t

class MyTimer:
    def __init__(self):
        self.prompt = "未开始计时"
        self.lasted = 0.0
        self.begin = 0
        self.end = 0
        self.default_timer = t.perf_counter

    def __str__(self):
        return self.prompt
    __repr__ = __str__
    def __add__(self,other):
        result = self.lasted + other.lasted
        prompt = "总共运行了%0.2f秒" % result
        return prompt
    def start(self):
        self.begin = self.default_timer()
        self.prompt = "提示：请先调用stop()停止计时"
        print("计时开始！")
    def stop(self):
        if not self.begin:
            print("提示：请先调用start()开始计时")
        else:
            self.end = self.default_timer()
            self._calc()
            print("计时结束")
    def _calc(self):
        self.lasted = self.end - self.begin
        self.prompt = "总共运行了%0.2f秒" % self.lasted
        print(self.prompt)
        self.begin = 0
        self.end = 0

    def set_timer(self,timer):
        if timer == 'process_time':
            self.default_timer = t.process_time
        elif timer == 'perf_counter':
            self.default_timer = t.perf_counter
        else:
            print("输入无效")

t1 = MyTimer()
t1.set_timer('perf_counter')
t1.start()
t.sleep(5.2)
t1.stop()
t2 = MyTimer()
t2.set_timer('perf_counter')
t2.start()
t.sleep(5.2)
t2.stop()
print(t1 + t2)

 >>>
计时开始！
总共运行了5.23秒
计时结束
计时开始！
总共运行了5.21秒
计时结束
总共运行了10.44秒
>>>

4.属性访问

魔法方法	含义
__ getattr__(self, name)	定义当用户试图获取一个不存在的属性时的行为
__ getattribute__(self, name)	定义当该类的属性被访问时的行为
__ setattr__(self, name, value)	定义当一个属性被设置时的行为
__ delattr__(self, value)	定义当一个属性被删除时的行为

避免属性魔法方法的死循环：

使用super()调用基类、给特殊属性__dict__赋值

class Rectangle:
    def __init__(self,width=0,height=0):
        self.width = width
        self.height = height

    def __setattr__(self,name,value):
        if name == 'square':
            self.width = value
            self.height = value
        else:    #避免死循环的两种方式
           # super().__setattr__(name,value)
           self.__dict__[name] = value

    def getArea(self):
        return self.width * self.height

>>> r1 = Rectangle(4,5)
>>> r1.getArea()
20
>>> r1.square = 10
>>> r1.getArea()
100
>>>

5. 描述符

将某种特殊类型的类的实例指派给另一个类的属性

__get__(self,instance,owner)	访问属性，返回属性的值
__set__(self,instance,value)	在属性分配中调用，不返回任何内容
__delete__(self,instance)	控制删除操作，不返回任何值

>>> class Mydecript:
	def __get__(self,instance,owner):
		print("getting...",self,instance,owner)
	def __set__(self,instance,value):
		print("setting...",self,instance,value)
	def __delete__(self,instance):
		print("deleting...",self,instance)

>>> class Test:
	x = Mydescript()

Traceback (most recent call last):
  File "", line 1, in
    class Test:
  File "", line 2, in Test
    x = Mydescript()
NameError: name 'Mydescript' is not defined
>>> class Test:
	x = Mydecript()
#Mydecript是x的描述类

>>> test = Test()
>>> test.x
getting... <__main__.Mydecript object at 0x030EAFB0> <__main__.Test object at 0x03108050>
>>> test.x = "X-man"
setting... <__main__.Mydecript object at 0x030EAFB0> <__main__.Test object at 0x03108050> X-man
>>> del test.x
deleting... <__main__.Mydecript object at 0x030EAFB0> <__main__.Test object at 0x03108050>

例题：温度的转换

class Celsius:
    def __init__(self,value = 26.0):
        self.value = float(value)

    def __get__(self,instance,owner):
        return self.value

    def __set__(self,instance,value):
        self.value = float(value)

class Fahrenheit:
    def __get__(self,instance,owner):
        return instance.cel * 1.8 + 32

    def __set__(self,instance,value):
        instance.cel = (float(value) - 32) / 1.8

class Temperature:
    cel = Celsius()
    fah = Fahrenheit()

>>> temp = Temperature()
>>> temp.cel
26.0
>>> temp.cel = 30
>>> temp.fah
86.0
>>> temp.fah = 100
>>> temp.cel
37.77777777777778
>>>

6.定制序列

Python魔法方法详解

例题：编写一个不可变的自定义列表，要求记录列表中每个元素被访问的次数

class CountList:
    def __init__(self,*args):
        self.values = [x for x in args]
        self.count = { }.fromkeys(range(len(self.values)),0)

    def __len__(self):
        return len(self.values)

    def __getitem__(self,key):
        self.count[key] += 1
        return self.values[key]

>>> c1 = CountList(1,3,5,7,9)
>>> c1[1]
3
>>> c2 = CountList(2,4,6,8,10)
>>> c2[1]
4
>>> c1[1]+c2[1]
7
>>> c1.count
{0: 0, 1: 2, 2: 0, 3: 0, 4: 0}
>>> c2[1]
4
>>> c2.count
{0: 0, 1: 3, 2: 0, 3: 0, 4: 0}
>>>

7.迭代器

迭代器是实现了__next__()方法的对象，不能回退

>>> string = "FishC"
>>> it = iter(string)
>>> next(it)
'F'
>>> next(it)
'i'
>>> next(it)
's'
>>> next(it)
'h'
>>> next(it)
'C'
>>> next(it)
Traceback (most recent call last):
  File "", line 1, in
    next(it)
StopIteration
>>> string = "FishC"
>>> it = iter(string)
>>> while True:
	try:
		each = next(it)
	except StopIteration:
		break
	print(each)

F
i
s
h
C
>>> for each in string:
	print(each)

F
i
s
h
C
>>>

例题：使用迭代器实现斐波那契数列

>>> class Fibs:
	def __init__(self,n=10):
		self.a = 0
		self.b = 1
		self.n = n
	def __iter__(self):
		return self
	def __next__(self):
		self.a,self.b = self.b,self.a + self.b
		if self.a > self.n:
			raise StopIteration
		return self.a

>>> fibs = Fibs()
>>> for each in fibs:
	print(each)

1
1
2
3
5
8