In the first article in this series, we introduced Python iterators and how they can be used to streamline Python code. In this article, we will continue our look at iterators, beginning with the next function.

To support manual iteration code, Python 3.0 also provides a built-in function, next, that automatically calls an object’s __next__ method. Given an iterable object X, the call next(X) is the same as X.__next__(). With files, for example, either form could be used:

>>> f = open('simple.py')
>>> f.__next__()

>>> f = open('simple.py')
>>> next(f)

Technically, there is one more piece to the iteration protocol. When the for loop begins, it obtains an iterator from the iterable object by passing it to the iter built-in function; the object returned by iter has the required next method. We can illustrate this with the following code:

>>> LS = [1, 2, 3, 4, 5]
>>> myIter = iter(LS)
>>> myIter.next()
1
>>> myIter.next()
2

This initial step is not required for files, because a file object is its own iterator: files have their own __next__ method and so do not need to return a different object that does.

Lists and many other built-in object, are not their own iterators because they support multiple open operations. For such objects, we must call iter to start iterating. For example:

>>> LS = [1, 2, 3, 4, 5]
>>> iter(LS) is LS
False
>>> LS.__next__()
Traceback (most recent call last):
  File "<pyshell#50>", line 1, in 
    LS.__next__()
AttributeError: 'list' object has no attribute '__next__'

>>> myIter = iter(LS)
>>> myIter.__next__()
1
>>> next(myIter)
2

Although Python iteration tools call these functions automatically, we can use them to apply the iteration protocol manually, too. The following demonstrates the equivalence between automatic and manual iteration:

>>> LS = [1, 2, 3, 4, 5]
>>> for X in LS:
	print(X ** 2, end=' ')

1 4 9 16 25

>>> myIter = iter(LS)
>>> while True:
	try:
		X = next(I)
	except StopIteration:
		break
	print(X ** 2, end=' ')

1 4 9 16 25 

To understand this code, you need to know that try statements run an action and catch exceptions (we covered that in the series of articles on exceptions). Also, for loops and other iteration contexts can sometimes work differently for user-defined classes, repeatedly indexing an object instead of running the iteration protocol.

External Links:

Python Iterators at Python Wiki

Python Iterator tutorial at bogotobogo.com