Iterables and Iterators- Part 2

In continuation to my previous post on Iterables, we should now get familiar with something new. Let's again create a list.

lst = [1,2,3,4]
dir(lst)

--->['__add__', '__class__', '__contains__', '__delattr__', '__delitem__', '__dir__', '__doc__', '__eq__', 
'__format__', '__ge__', '__getattribute__', '__getitem__', '__gt__', '__hash__', '__iadd__', '__imul__', 
'__init__', '__init_subclass__', '__iter__', '__le__', '__len__', '__lt__', '__mul__', '__ne__', '__new__', 
'__reduce__', '__reduce_ex__', '__repr__', '__reversed__', '__rmul__', '__setattr__', '__setitem__', 
'__sizeof__', '__str__', '__subclasshook__', 'append', 'clear', 'copy', 'count', 'extend', 'index', 
'insert', 'pop', 'remove', 'reverse', 'sort']

The functions with "__" in front and behind ('__add__') are called dunder methods. More on this in later posts. You can see a method called __iter__ . All iterables will contain this method. Generally, __iter__ method returns an iterator. So if the object is an iterator, inside the __iter__ method, you will generally see return self . We will talk more about classes and methods in later posts. Ignore this if you do not understand it for now. Python gives you the flexibility to create an object so as to iterate over a Python data structure. We call this an Iterator . An iterator can be created using the iter keyword. For the list "lst" that we created before, this is how we create an iterator.

it =  iter(lst)
for element in it:
    print(element)
--->   1
       2
       3
       4

Let's inspect what happens when we create an iterator

dir(it)
---> ['__class__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__iter__', '__le__', '__length_hint__', '__lt__', '__ne__', '__new__', '__next__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setstate__', '__sizeof__', '__str__', '__subclasshook__']

The iterator object internally creates two methods __iter__ and __next__. When some one new to Python reads this, the first thing which comes to mind is how is this even useful? I already have a "for" loop which can help me iterate through an iterable. So why do I need to create an iterator now? Very valid question and the answer in this context is that, the iterator is not so useful. We will work on scenarios later which will make iterators useful. For now, all we need to understand is that in order to create an iterator, we need to have two methods in place . __iter__ and __next__. Let's create the iterator again.

it =  iter(lst)
 

Let's see the effect of using next() on the iterator object at each step

next(it)
---> 1
next(it
---> 2
next(it)
---> 3
next(it)
---> 4
next(it)
-----------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
 in 
----> 1 next(it)

StopIteration: 

The moment we have traversed all elements in the list using the it iterator , you will receive a StopIteration error to indicate that there are no more elements to be traversed. At this stage, if you run the below command, it turns out, you will get no output as well.

for i in it:
  print(i)

--->  

If you want to see results from your iterator, you need to recreate the iterator as done before.

it =  iter(lst)
 

We will use these concepts as building blocks to understand more complex ideas in later posts.