可迭代对象
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| 实现了__iter__的对象就是可迭代对象
class IsIterable:
def __iter__(self):
return self
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迭代器
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| 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
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生成器
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| 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
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生成器函数
借助yield实现
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| >>> 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
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生成器表达式
使用 () 包裹，而不是【】
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| 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))
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Traceback (most recent call last):
File "d:\python\test.py", line 7, in <module>
print (next(g))
StopIteration
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优势
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| 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
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参考
https://www.runoob.com/python3/python3-iterator-generator.html
https://kelepython.readthedocs.io/zh/latest/c01/c01_11.html