Python Concepts for Data Science: Iterators

In this blog, we will talk about iterator which is an object used to iterate over an iterable object.

Before moving to examples let's make a distinction between two things iterator and iterable :

Firstly: An iterable object is that contains data that can be iterated over e.g. List, String, Set, Tuple, Dictionary. And you can get an iterator from it using the iter method

Second: An iterator is an object that can return data one at a time while iterating over it as we said using the next() method.

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let's take a look at an example of iterable:

mylist=['red','blue','yellow']

if we tried to use the next() method over the above iterable, we will get an error like this:

print(next(mylist) )

---------------------------------------------------------------------------TypeError                                 Traceback (most recent call last)
<ipython-input-4-82d387c9e81c> in <module>      2 mylist=['red','blue','yellow']      3----> 4 print(next(mystring))TypeError: 'str' object is not an iterator

So we get this as the next() method accepts an iterator as an argument not iterable so if we want to use the next() method and deal with the iterators we have to transform it into an iterator object by the iter() method as follows:

mylist=iter(mylist)

print(next(mylist))
print(next(mylist))
print(next(mylist))

red
blue
yellow

As we said we first transform the iterable object to an iterator and then using the next() method we iterate over the list and each time we call it, it outputs one element after another.

But what is the difference between using for loop and using the next method as before?

It turns out that For loop actually calls iter() method to transform the iterable object into an iterator and then it will loop over it, so the following two examples will do the same thing:

mylist2=['apple','orange','banana']
for item in mylist2:
    print(item)

apple
orange
banana

mylist2=['apple','orange','banana']
for item in iter(mylist2):
    print(item)

apple
orange
banana

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At the end of this blog let's go to one last example to create an iterator by ourselves to get the even numbers:

# creating an iterator for even numbers
class Even:
    def __init__(self,max):
        self.n=2
        self.max=max
        
    def __iter__(self):
        return self
    
    def __next__(self):
        if self.n <=self.max:
            result=self.n
            self.n+=2
            return result
        else:
            raise StopIteration
            

this Even class will get the even numbers up to maximum number that we should specify as an argument in the constructor and it has the next() method that will get the next even number as long as this number is less than the maximum number that we provided as an argument otherwise it will raise StopIteration.

# We will check if the above code works by creating an object from the Even class and set the maximum number to be 10          
nums=Even(10)

# we will get the even numbers by iterating over them by the next method 
print(next(nums))
print(next(nums))
print(next(nums))
print(next(nums))
print(next(nums))

2
4
6
8
10

Here we created an object from the Even class and set the maximum number to be 10 and we iterate over these numbers through the next() method. So the output became as shown above.

If we get the next() method one more time we will get StopIteration as follows:

print(next(nums))

---------------------------------------------------------------------------StopIteration                             Traceback (most recent call last)
<ipython-input-10-ddf9ec797e52> in <module>----> 1 print(next(nums))<ipython-input-9-da5cd2672051> in __next__(self)     14             return result
     15         else:---> 16             raise StopIteration
     17     18StopIteration: 

Link for GitHub repo here