Iterator protocol and traversal methods in Python programming

Preface

The introduction of the previous part should make it easy for us to understand and master iterable objects and iterators (Iterable & Iterator) in Python. In this content, we will further introduce the related content of iterators.

Iterator protocol

In Python, the iterator (Iterator) object needs to support the following two methods, which together form the iterator protocol:

1) __iter__(): This method of

object returns the iterator object itself. This is required for containers and iterators to be used with for-in statements. You can also use the built-in iter() function, which essentially calls the __iter__() method behind the scenes.

2)__next__():

Return the next item from the iterator. If there are no other items, a StopIteration exception is thrown. You can also use the built-in next() function to read the next item, which is essentially calling the __next__() method.

As we said before, lists, tuples, dictionaries and sets are all iterable types. In other words, they are types from which iterators can be obtained. Look at the example:

Code snippet list-01

The input results are as follows:

A
B
C

In the sample code, we define a Iterate over tuples. Then call the iter() function on this iterable object. The iter() function returns an iterator, which we name tupIter. Then call the next() function multiple times. Each time the next() function is executed, it will automatically return the next item in the iterator.

Look at the next sample code:

Code snippet-02

The result of the running output is:

P
y

In the above code listing, the __ iter__() method is called on the string object. String objects implement the iterator protocol, so strings are iterable objects that contain sequences of characters. Calling the __iter__() method directly returns an iterator. Then call the __next__() method through the returned iterator to output the elements in the iterator one by one.

In a nutshell, as long as the object implements the iterator protocol, the object can be called iteratively according to the above two methods.

Iterator traversal

As we saw in the previous introduction, we use the next() function (or __next__() method) to manually traverse the items of an iterator. When the next() function reaches the end of the iterator, there is no more data to return and you will get a StopIteration exception.

Please see the example:

Code snippet list-03

Run the above program, the output will be similar to the following:

##10

##20

30

##Traceback (most recent call last):

##File ……, in

##print(next(listIter))

StopIteration

In the above code, the next() function is called four times, which is more than the number of items in the iterator. In the last call, a StopIteration exception was thrown - because the elements in the iterator have been iterated. Moreover, in order to ensure that exceptions may be thrown after the manual iteration is completed, exception handling must be performed by yourself, otherwise the subsequent execution will no longer be normal.

What needs to be realized is: in most scenarios, we do not need to manually call the next method ourselves. The for loop in Python can automatically traverse any object that can return an iterator. In other words, a for loop can iterate over any iterable object in Python.

Please see the example:

Code List Snippet 04

In the above code, we use a for loop to traverse the list defined earlier. It is obvious that we did not use the next() function manually and did not get any StopIteration exception. This is the beauty of for loops in Python. It handles all of this for us behind the scenes.

Of course, we can handle loop iteration ourselves this way. Now define our own version of the for loop. We will use a while loop and replicate the behavior of a for loop. Here we build everything needed for this implementation ourselves. As shown below:

Code Listing Snippet-05

In the above listing, we have implemented our own version of a simulated for loop. An infinite while loop is used in the code: while True. A try-except block is set up inside the loop. In the try block, get the next element by calling the __next__() method on the iterator. If the call is successful, the element is printed. If an error of type StopIteration occurs, the exception is caught in the except block. What you do in the except block is very simple. We just break out of this loop, which means we've reached the end of the iterator.

Summary

That’s it for this article, which mainly introduces the iterator protocol and iterator traversal. The text of the content is not long, and combined with the code can help you better understand and master these Python programming knowledge points.

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