Python 什么'；在iter（）中使用产量的优点是什么？

在

\uuuu iter\uuuu（）函数中使用生成器（
收益率
）有什么好处？在阅读了Python食谱之后，我明白了“如果您希望生成器向用户公开额外的状态，请不要忘记，您可以轻松地
将其作为类实现，将生成器函数代码放入
\uuuu iter\uuu（）
方法中。”

问题：

额外状态在这里意味着什么
使用
yield
内部
\uuu iter\uu（）
而不是使用单独的
yield
函数有什么好处
如果要遵循最佳实践，如果没有生成器函数，则必须实现如下内容：

In [7]: class IterableContainer:
   ...:     def __init__(self, data=(1,2,3,4,5)):
   ...:         self.data = data
   ...:     def __iter__(self):
   ...:         return IterableContainerIterator(self.data)
   ...:

In [8]: class IterableContainerIterator:
   ...:     def __init__(self, data):
   ...:         self.data = data
   ...:         self._pos = 0
   ...:     def __iter__(self):
   ...:         return self
   ...:     def __next__(self):
   ...:         try:
   ...:              item = self.data[self._pos]
   ...:         except IndexError:
   ...:             raise StopIteration
   ...:         self._pos += 1
   ...:         return item
   ...:

In [9]: container = IterableContainer()

In [10]: for x in container:
    ...:     print(x)
    ...:
1
2
3
4
5

当然，上面的例子是人为的，但希望你能理解这一点。对于发电机，这可以是：

In [11]: class IterableContainer:
    ...:     def __init__(self, data=(1,2,3,4,5)):
    ...:         self.data = data
    ...:     def __iter__(self):
    ...:         for x in self.data:
    ...:             yield x
    ...:
    ...:

In [12]: list(IterableContainer())
Out[12]: [1, 2, 3, 4, 5]

至于状态，就是-对象可以有状态，比如属性。您可以在运行时操纵该状态。你可以这样做，尽管我认为这是非常不可取的：

In [19]: class IterableContainerIterator:
    ...:     def __init__(self, data):
    ...:         self.data = data
    ...:         self._pos = 0
    ...:     def __iter__(self):
    ...:         return self
    ...:     def __next__(self):
    ...:         try:
    ...:              item = self.data[self._pos]
    ...:         except IndexError:
    ...:             raise StopIteration
    ...:         self._pos += 1
    ...:         return item
    ...:     def rewind(self):
    ...:         self._pos = min(0, self._pos - 1)
    ...:

In [20]: class IterableContainer:
    ...:     def __init__(self, data=(1,2,3,4,5)):
    ...:         self.data = data
    ...:     def __iter__(self):
    ...:         return IterableContainerIterator(self.data)
    ...:

In [21]: container = IterableContainer()

In [22]: it = iter(container)

In [23]: next(it)
Out[23]: 1

In [24]: next(it)
Out[24]: 2

In [25]: it.rewind()

In [26]: next(it)
Out[26]: 1

In [27]: next(it)
Out[27]: 2

In [28]: next(it)
Out[28]: 3

In [29]: next(it)
Out[29]: 4

In [30]: next(it)
Out[30]: 5

In [31]: it.rewind()

In [32]: next(it)
Out[32]: 1

导入json
导入URL库
serviceurl=http://www.py4e.com/code3/geojson.py'
尽管如此：
地址=输入（“输入位置：”）
如果len（address）因为now
playyild
是可编辑的，但您不必编写迭代器类，因为now
playyied.\uuuuuuuuu iter\uuuuuu
返回一个生成器，它是迭代器。这很方便。你的问题没有提供全部的上下文。您在Python烹饪书中提到的这句话是关于问题的：*您想定义一个生成器函数，但它涉及到您想以某种方式向用户公开的额外状态。这里的额外状态意味着与程序的其他部分相关的其他信息。我也建议在一年前检查此项，但为什么不在
IterableContainer
类中只包含
\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuucode>？只需将
def\uuuuu iter\uuuuuuuuuuuself（self）:return self
，并将
\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu。所有迭代器都是可迭代的，但并非所有可迭代的都是迭代器。理想情况下，您应该将两者分开。例如，迭代器应该是单遍的，但通常情况下，您希望能够在大多数容器上多次迭代。我想我在语义上迷失的地方是，生成器自动提供
\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu，因此，使用生成器或
\uuuuuuuuuuuuuuuuuuuuuuuu
和
\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu？我认为生成器是一个迭代器，所以选择任何一种方法都是基于您希望如何使用该类。但我确实认为，作为一个生成器，它一次只能执行一次，而作为迭代器实现则允许更多的操作。@pstatix关注点分离是一个加号。生成器对象是迭代器。生成器函数返回生成器对象。因此，由于容器的
\uuuu iter\uuuu
返回一个迭代器，因此它现在是一个iterable。但是我们不希望容器成为迭代器并实现
\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu。我不确定你的意思是“更多的动作”。请考虑给你的代码添加解释，它是如何回答这个问题的。
In [19]: class IterableContainerIterator:
    ...:     def __init__(self, data):
    ...:         self.data = data
    ...:         self._pos = 0
    ...:     def __iter__(self):
    ...:         return self
    ...:     def __next__(self):
    ...:         try:
    ...:              item = self.data[self._pos]
    ...:         except IndexError:
    ...:             raise StopIteration
    ...:         self._pos += 1
    ...:         return item
    ...:     def rewind(self):
    ...:         self._pos = min(0, self._pos - 1)
    ...:

In [20]: class IterableContainer:
    ...:     def __init__(self, data=(1,2,3,4,5)):
    ...:         self.data = data
    ...:     def __iter__(self):
    ...:         return IterableContainerIterator(self.data)
    ...:

In [21]: container = IterableContainer()

In [22]: it = iter(container)

In [23]: next(it)
Out[23]: 1

In [24]: next(it)
Out[24]: 2

In [25]: it.rewind()

In [26]: next(it)
Out[26]: 1

In [27]: next(it)
Out[27]: 2

In [28]: next(it)
Out[28]: 3

In [29]: next(it)
Out[29]: 4

In [30]: next(it)
Out[30]: 5

In [31]: it.rewind()

In [32]: next(it)
Out[32]: 1