Python进阶--生成器和迭代器以及实现方法

生成器和迭代器

• generator: ⽣成器是一种特殊的迭代器, 不需要⾃定义 __iter__ 和 __next__

⽣成器函数 (yield)

[code]def foo():
...:     print(111)
...:     yield 222
...:     print(333)
...:     yield 444
...:     print(555)
...:

In [2]: n=foo()

In [3]: next(n)
111
Out[3]: 222

In [4]: next(n)
333
Out[4]: 444

In [5]: next(n)
555
---------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
<ipython-input-5-0fa053c92e6d> in <module>
----> 1 next(n)

StopIteration:

⽣成器表达式: (i*2 for i in range(5))  这里使用的是括号()，list是[ ].

[code]In [9]: gen = (i*2 for i in range(5))

In [10]: print(gen)
<generator object <genexpr> at 0x10e73a200>

• iterator:任何实现了__iter__和__next__方法的对象都是迭代器

1. __iter__ 得到一个迭代器。迭代器的 __iter__() 返回自身
2. __next__ 返回迭代器下一个值
3. 如果容器中没有更多元素, 则抛出 StopIteration 异常
4. Python2中没有 __next__() , ⽽是 next()

[code]class Range:
def __init__(self, start, end=None, step=1):
if end is None:
self.end = start
self.start = 0
else:
self.start = start
self.end = end
self.step = step

def __iter__(self):

return self

def __next__(self):
if self.start < self.end:
current = self.start
self.start += self.step
return current
else:
raise StopIteration()

Iter = Range(1, 4)

结果：
In [10]: print(next(Iter))
1

In [11]: print(next(Iter))
2

In [12]: print(next(Iter))
3

In [13]: print(next(Iter))
---------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
<ipython-input-13-2439b2fba63d> in <module>
----> 1 print(next(Iter))

<ipython-input-9-f1a6fab34350> in __next__(self)
19             return current
20         else:
---> 21             raise StopIteration()
22
23

StopIteration:

• str / bytes / list / tuple / dict / set ⾃身不是迭代器，他们自身不具备 __next__() , 但是具有 __iter__() , __iter__() 方法用来把⾃身转换成一个迭代器

练习：

[code]# 练习1: 定义⼀一个随机数迭代器器, 随机范围为[1, 50], 最⼤大迭代次数3

import random

class RandomIter:
def __init__(self, start, end, times):
self.start = start
self.end = end
self.count = times

def __iter__(self):
return self

def __next__(self):
self.count -= 1
if self.count >= 0:
return random.randint(self.start, self.end)
else:
raise StopIteration()

RandomIter = RandomIter(1,50,3)
print(next(RandomIter))
print(next(RandomIter))
print(next(RandomIter))
print(next(RandomIter))

[code]# 练习2: ⾃定义一个⽣成器函数, 实现斐波那契数列

def fib(max_value):
prev = 0
curr = 1
while curr < max_value:
yield curr
prev, curr = curr, curr + prev

for i in fib(20):
print(i, end=' ')

结果：1 1 2 3 5 8 13

各种推导式

分三部分:⽣成值的表达式, 循环主体, 过滤条件表达式

列表: [i*3 for i in range(5) i f %2 == 0]

字典: {i: i + 3 for i in range(5)}

集合: {i for i in range(5)}

生成器: (i for i in range(5))