下面是我的小抄:

 sequence
  +
  |
  v
   def __getitem__(self, index: int):
  +    ...
  |    raise IndexError
  |
  |
  |              def __iter__(self):
  |             +     ...
  |             |     return <iterator>
  |             |
  |             |
  +--> or <-----+        def __next__(self):
       +        |       +    ...
       |        |       |    raise StopIteration
       v        |       |
    iterable    |       |
           +    |       |
           |    |       v
           |    +----> and +-------> iterator
           |                               ^
           v                               |
   iter(<iterable>) +----------------------+
                                           |
   def generator():                        |
  +    yield 1                             |
  |                 generator_expression +-+
  |                                        |
  +-> generator() +-> generator_iterator +-+

小测验:你看到…

每个迭代器都是可迭代对象? 容器对象的__iter__()方法可以实现为生成器? 具有__next__方法的迭代器不一定是迭代器?

答案:

Every iterator must have an __iter__ method. Having __iter__ is enough to be an iterable. Therefore every iterator is an iterable. When __iter__ is called it should return an iterator (return <iterator> in the diagram above). Calling a generator returns a generator iterator which is a type of iterator. class Iterable1: def __iter__(self): # a method (which is a function defined inside a class body) # calling iter() converts iterable (tuple) to iterator return iter((1,2,3)) class Iterable2: def __iter__(self): # a generator for i in (1, 2, 3): yield i class Iterable3: def __iter__(self): # with PEP 380 syntax yield from (1, 2, 3) # passes assert list(Iterable1()) == list(Iterable2()) == list(Iterable3()) == [1, 2, 3] Here is an example: class MyIterable: def __init__(self): self.n = 0 def __getitem__(self, index: int): return (1, 2, 3)[index] def __next__(self): n = self.n = self.n + 1 if n > 3: raise StopIteration return n # if you can iter it without raising a TypeError, then it's an iterable. iter(MyIterable()) # but obviously `MyIterable()` is not an iterator since it does not have # an `__iter__` method. from collections.abc import Iterator assert isinstance(MyIterable(), Iterator) # AssertionError

迭代对象有一个__iter__方法，每次都会实例化一个新的迭代器。 迭代器实现了一个__next__方法返回单个项，以及一个__iter__方法返回self。 因此，迭代器也是可迭代的，但可迭代的不是迭代器。

卢西亚诺·拉马略，流利的蟒蛇。

iterable是一个具有__iter__()方法的对象。它可以迭代多次，比如list()和tuple()。

迭代器是进行迭代的对象。它由__iter__()方法返回，通过自己的__iter__()方法返回自身，并有一个next()方法(3.x中的__next__())。

迭代是调用next()响应的过程。__next__()直到引发StopIteration。

例子:

>>> a = [1, 2, 3] # iterable
>>> b1 = iter(a) # iterator 1
>>> b2 = iter(a) # iterator 2, independent of b1
>>> next(b1)
1
>>> next(b1)
2
>>> next(b2) # start over, as it is the first call to b2
1
>>> next(b1)
3
>>> next(b1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> b1 = iter(a) # new one, start over
>>> next(b1)
1

我不认为你能得到比文档更简单的东西，但我会尝试:

Iterable是可以被迭代的对象。在实践中，它通常是指一个序列，例如，有开始和结束的东西，以及一些贯穿其中所有项目的方法。 您可以将Iterator视为一个辅助伪方法(或伪属性)，它给出(或保存)可迭代对象中的下一个(或第一个)项。(实际上它只是一个定义next()方法的对象) 《韦氏词典》对迭代这个词的定义可能是最好的解释:

B:重复指定的计算机指令序列 次数或直到满足条件-比较递归

下面是我的小抄:

 sequence
  +
  |
  v
   def __getitem__(self, index: int):
  +    ...
  |    raise IndexError
  |
  |
  |              def __iter__(self):
  |             +     ...
  |             |     return <iterator>
  |             |
  |             |
  +--> or <-----+        def __next__(self):
       +        |       +    ...
       |        |       |    raise StopIteration
       v        |       |
    iterable    |       |
           +    |       |
           |    |       v
           |    +----> and +-------> iterator
           |                               ^
           v                               |
   iter(<iterable>) +----------------------+
                                           |
   def generator():                        |
  +    yield 1                             |
  |                 generator_expression +-+
  |                                        |
  +-> generator() +-> generator_iterator +-+

小测验:你看到…

每个迭代器都是可迭代对象? 容器对象的__iter__()方法可以实现为生成器? 具有__next__方法的迭代器不一定是迭代器?

答案:

Every iterator must have an __iter__ method. Having __iter__ is enough to be an iterable. Therefore every iterator is an iterable. When __iter__ is called it should return an iterator (return <iterator> in the diagram above). Calling a generator returns a generator iterator which is a type of iterator. class Iterable1: def __iter__(self): # a method (which is a function defined inside a class body) # calling iter() converts iterable (tuple) to iterator return iter((1,2,3)) class Iterable2: def __iter__(self): # a generator for i in (1, 2, 3): yield i class Iterable3: def __iter__(self): # with PEP 380 syntax yield from (1, 2, 3) # passes assert list(Iterable1()) == list(Iterable2()) == list(Iterable3()) == [1, 2, 3] Here is an example: class MyIterable: def __init__(self): self.n = 0 def __getitem__(self, index: int): return (1, 2, 3)[index] def __next__(self): n = self.n = self.n + 1 if n > 3: raise StopIteration return n # if you can iter it without raising a TypeError, then it's an iterable. iter(MyIterable()) # but obviously `MyIterable()` is not an iterator since it does not have # an `__iter__` method. from collections.abc import Iterator assert isinstance(MyIterable(), Iterator) # AssertionError

迭代是一个通用术语，指一个接一个地获取某物的每一项。任何时候使用循环，显式或隐式，遍历一组项，这就是迭代。

在Python中，iterable和iterator有特定的含义。

iterable是一个具有__iter__方法的对象，该方法返回一个迭代器，或者定义了__getitem__方法，该方法可以接受从0开始的顺序索引(并在索引不再有效时引发IndexError)。iterable是一个你可以从中获取迭代器的对象。

迭代器是具有next (Python 2)或__next__ (Python 3)方法的对象。

无论何时在Python中使用for循环、map或列表推导式等，都会自动调用下一个方法从迭代器中获取每一项，从而完成迭代过程。

开始学习的一个好地方是教程的迭代器部分和标准类型页面的迭代器类型部分。在您理解了基础知识之后，请尝试函数式编程HOWTO中的迭代器部分。