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Python Iterators

Python Tutorial

Introduction

Python Data Types & Oper...

Python Strings

Python Lists

Python Tuples

Python Sets

Python Dictionaries

Conditional Statements

Python Loops

Python Functions

Python Modules

Python OOPS

Advanced Topics

File Handling

Edit Template

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Python Iterators

Python Iterators

In Python, iterators allow you to loop through elements in data structures like strings, lists, sets, and more — one item at a time.

To build a custom iterator or use one properly, we need to understand two important methods:

__iter__() – Prepares the object to be used as an iterator.
__next__() – Returns the next value every time it’s called.

Let’s walk through this step by step.

Using Built-in Iterators

Python automatically provides iterator support for strings, lists, and other collections. You can turn any iterable into an iterator using the built-in iter() function, and loop through it using next().

				
					message = "Arshyan"
iterator = iter(message)

while True:
    try:
        letter = next(iterator)
        print(letter)
    except StopIteration:
        break

Output:

				
					A
r
s
h
y
a
n

In this example:

iter(message) creates an iterator.
next(iterator) gives one character at a time.
When all items are used, StopIteration is raised, and the loop stops.

Creating a Custom Iterator

Let’s build our own iterator that returns multiples of 3 up to 30.

				
					class MultiplesOf3:
    def __iter__(self):
        self.num = 0
        return self

    def __next__(self):
        if self.num <= 30:
            result = self.num
            self.num += 3
            return result
        else:
            raise StopIteration

obj = MultiplesOf3()
itr = iter(obj)

for value in itr:
    print(value)

Output:

What’s Going On?

__iter__() is called once when the loop starts and sets the initial value.
__next__() is called again and again until it hits StopIteration.
This gives us full control over what gets returned and when to stop.

Why Use Iterators?

They’re memory efficient — great for looping through large datasets.
They help you build custom, controllable looping behavior.
They give structure to your iteration logic.

Summary

Use iter() to create an iterator from a built-in iterable.
Use next() to go one step forward.
Define __iter__() and __next__() in your class to create your own iterator.
Always raise StopIteration to avoid infinite loops.