matchObj/None = re.match(pattern, string, flags=0)

matchObj/None = re.search(pattern, string, flags=0)

f=lambda a,b,c,d:a*b*c*d
print(f(1,2,3,4))  


#相当于下面这个函数

def test01(a,b,c,d):
    return a*b*c*d
print(test01(1,2,3,4))

1 print([f(2) for f in [lambda x:i*x for i in range(5)]])
2 print([f(2) for f in [lambda x,i=i:i*x for i in range(5)]])
3 print([(lambda x:i*x)(2) for i in range(5)])


[8, 8, 8, 8, 8]
[0, 2, 4, 6, 8]
[0, 2, 4, 6, 8]


1 先声5个匿名函数 x是匿名函数的变量，i是匿名函数外部的变量，所以会变，用的是最后的i ，最后调用匿名函数
2 先声5个匿名函数 x,i是匿名函数的变量，i的默认值从外部的i传入 ，最后调用匿名函数 
3 一边声明 一边调用 x是匿名函数的变量，i是匿名函数外部的变量

实现了__iter__的对象就是可迭代对象
class IsIterable:
        def __iter__(self):
            return self

实现了 __ iter __  +__ next __
>>> class MyIterator:
        """
        迭代器类
        Author：可乐python说
        """
        def __init__(self):
            self.num = 0
        def __iter__(self):
            return self
        def __next__(self):
            return_num = self.num
            # 只要值大于等于6，就停止迭代
            if return_num >= 6:
                raise StopIteration
            self.num += 2
            return return_num

>>> my_iterator = MyIterator()
>>> next(my_iterator)
0
>>> next(my_iterator)
2
>>> next(my_iterator)
4
>>> next(my_iterator)
Traceback (most recent call last):
  File "<input>", line 1, in <module>
StopIteration

特殊的迭代器 
不需要实现 __ iter __  +__ next __ 又可以实现相同的作用 ，有以下两种方式

>>> def my_generator():
        my_num = 0
        while my_num < 5:
            yield my_num
            my_num += 1

>>>generator_ = my_generator()
>>> next(generator_)
0
>>> next(generator_)
1
>>> next(generator_)
2
>>> next(generator_)
3
>>> next(generator_)
4
>>> next(generator_)
# 终止迭代则会抛出 StopIteration 异常
Traceback (most recent call last):
  File "<input>", line 1, in <module>
StopIteration

g = ((i)**2 for i in range(5))
print (next(g))
print (next(g))
print (next(g))
print (next(g))
print (next(g))
print (next(g))
print (next(g))



0
1
4
9
16
Traceback (most recent call last):
  File "d:\python\test.py", line 7, in <module>
    print (next(g))
StopIteration

import sys

my_list = [i for i in range(1000000)]
print(	"列表消耗的内存：{}".format(sys.getsizeof(my_list)))

my_generator = (i for i in range(1000000))
print("生成器消耗的内存：{}".format(sys.getsizeof(my_generator)))


列表消耗的内存：8448728
生成器消耗的内存：112

class dataset(object):
    @property
    def fun1(self):
        return 13
    def fun2(self):
        return 13

a=dataset()
print(a.fun1)
print(a.fun2())