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
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)
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
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