Python - Iterator

Here, you will learn about the iterator function iter() in Python.

Iterators are implicitly used whenever we deal with collections of data types such as list, tuple or string (they are quite fittingly called iterables). The usual method to traverse a collection is using the for loop, as shown below.

myList = [1, 2, 3, 4]
for item in myList:
    print(item)

1 2 3 4

In the above example, the for loop iterates over a list object- myList, and prints each individual element.

When we use a for loop to traverse any iterable object, internally it uses the iter() method, same as below.

def traverse(iterable):
    it=iter(iterable)
    while True:
        try:
            item=next(it)
            print (item)
        except StopIteration:
            break

iter()

Instead of using the for loop as shown above, we can use the iterator function iter(). An iterator is an object which represents a data stream. It returns one element at a time. Python's built-in method iter() receives an iterable and returns an iterator object. The iterator object uses the __next__() method. Every time it is called, the next element in the iterator stream is returned. When there are no more elements available, StopIteration error is encountered.

In the above example, list L1 is specified in the iter(L1) method, which will return an iterator object for L1. Now, we can traverse a list of items using the __next__() method. So, it.__next__() will return the first item, and calling the __next__() method again will return the second item from L1 and so on. It will throw the StopIteration error when calling the __next__() method after receiving the last item.

next()

Calling the it.__next__() method every time is tedious. The built-in function next() accepts an iterator object as a parameter and calls the __next__() method internally. Hence, it.__next__() is the same as next(it). The following example uses the next() method to iterate the list.

If the argument is not iterable, e.g. number, boolean, etc., TypeError is encountered.

The limitation of an iterator function is that it raises an exception when there is no next item. You can create your own iterator function using generator. Learn about the Python generator next.