在__iter __()中使用yield有什么好处？

Question

yield在__iter__()函数内部使用generator()有什么好处？通过阅读Python Cookbook后,我理解"如果你想让生成器向用户公开额外的状态,不要忘记你可以轻松地将它作为一个类实现,将生成器函数代码放在__iter__()方法中."

import io

class playyield:
    def __init__(self,fp):
        self.completefp = fp

    def __iter__(self):
        for line in self.completefp:
            if 'python' in line:
                yield line

if __name__ =='__main__':
    with io.open(r'K:\Data\somefile.txt','r') as fp:
        playyieldobj = playyield(fp)
        for i in playyieldobj:
            print I

问题:

1. 额外的国家在这里意味着什么？
2. 使用yield内部__iter__ ()而不是使用单独的函数有yield什么好处？

Answer 1

如果你想遵循最佳实践,如果没有生成器函数,你必须实现这样的东西:

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,但希望你明白这一点.使用生成器,这可以简单地:

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,嗯,确切地说 - 对象可以具有状态,例如属性.您可以在运行时操纵该状态.您可以执行以下操作,但我会说这是非常不可取的:

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