Iterators

Learn about iterators in Python, the iterator protocol, creating custom iterators, and how iterators differ from iterables.

By Ali Berro

January 9, 2026 8 min read Section 1

From: Python Fundamentals: From Zero to Hero

python iterators iterables iteration

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Section 53 of 61

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Iterators

Iterators are objects that allow you to traverse through a collection of items one at a time. They provide a way to access elements sequentially without needing to know the underlying data structure’s implementation details.

Iterables vs Iterators

Understanding the difference between iterables and iterators is crucial:

Iterable: An object that can return an iterator (has __iter__() method)
Iterator: An object that implements the iterator protocol (has __iter__() and __next__() methods)

Iterables

An iterable is any object you can loop over. Common iterables include lists, tuples, strings, dictionaries, sets, and files.

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# All of these are iterables
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my_list = [1, 2, 3]
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my_string = "Python"
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my_dict = {"a": 1, "b": 2}
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# You can iterate over them
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for item in my_list:
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    print(item)  # 1, 2, 3
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for char in my_string:
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    print(char)  # P, y, t, h, o, n
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for key in my_dict:
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    print(key)  # a, b

Iterators

An iterator is an object that produces values one at a time. You get an iterator from an iterable using the iter() function:

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my_list = [1, 2, 3]
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iterator = iter(my_list)  # Get iterator from iterable
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print(next(iterator))  # 1
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print(next(iterator))  # 2
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print(next(iterator))  # 3
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# print(next(iterator))  # StopIteration exception

The Iterator Protocol

The iterator protocol consists of two methods:

__iter__(): Returns the iterator object itself
__next__(): Returns the next value from the iterator, or raises StopIteration when done

How `for` Loops Work

When you use a for loop, Python automatically:

Calls iter() on the iterable to get an iterator
Calls next() repeatedly until StopIteration is raised
Handles the StopIteration exception

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my_list = [1, 2, 3]
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# This for loop:
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for item in my_list:
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    print(item)
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# Is equivalent to:
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iterator = iter(my_list)
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while True:
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    try:
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        item = next(iterator)
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        print(item)
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    except StopIteration:
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        break

Creating Custom Iterators

You can create your own iterators by implementing the iterator protocol in a class:

Basic Iterator Class

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class CountDown:
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    def __init__(self, start):
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        self.current = start
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if self.current <= 0:
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            raise StopIteration
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        self.current -= 1
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        return self.current + 1
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# Usage
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counter = CountDown(5)
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for num in counter:
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    print(num)  # 5, 4, 3, 2, 1
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# Or manually
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counter = CountDown(3)
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print(next(counter))  # 3
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print(next(counter))  # 2
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print(next(counter))  # 1
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# print(next(counter))  # StopIteration

Iterator with Custom Range

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class MyRange:
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    def __init__(self, start, stop, step=1):
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        self.start = start
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        self.stop = stop
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        self.step = step
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        self.current = start
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if (self.step > 0 and self.current >= self.stop) or \
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           (self.step < 0 and self.current <= self.stop):
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            raise StopIteration
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        value = self.current
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        self.current += self.step
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        return value
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# Usage
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for num in MyRange(1, 10, 2):
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    print(num)  # 1, 3, 5, 7, 9
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for num in MyRange(10, 0, -2):
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    print(num)  # 10, 8, 6, 4, 2

Iterator for Fibonacci Sequence

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class Fibonacci:
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    def __init__(self, limit=None):
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        self.prev = 0
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        self.curr = 1
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        self.limit = limit
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        self.count = 0
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if self.limit and self.count >= self.limit:
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            raise StopIteration
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        self.count += 1
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        value = self.prev
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        self.prev, self.curr = self.curr, self.prev + self.curr
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        return value
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# Usage
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fib = Fibonacci(10)
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for num in fib:
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    print(num)  # 0, 1, 1, 2, 3, 5, 8, 13, 21, 34

Separating Iterable and Iterator

Sometimes it’s useful to separate the iterable from the iterator. This allows multiple independent iterations:

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class Squares:
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    def __init__(self, max_value):
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        self.max_value = max_value
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    def __iter__(self):
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        return SquareIterator(self.max_value)
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class SquareIterator:
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    def __init__(self, max_value):
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        self.current = 0
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        self.max_value = max_value
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if self.current >= self.max_value:
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            raise StopIteration
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        value = self.current ** 2
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        self.current += 1
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        return value
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# Usage - can create multiple independent iterators
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squares = Squares(5)
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for num in squares:
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    print(num)  # 0, 1, 4, 9, 16
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# Create another iterator
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for num in squares:
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    print(num)  # 0, 1, 4, 9, 16 (starts fresh)

Built-in Iterator Functions

Python provides several built-in functions that work with iterators:

`iter()` and `next()`

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my_list = [10, 20, 30]
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iterator = iter(my_list)
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print(next(iterator))  # 10
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print(next(iterator))  # 20
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print(next(iterator))  # 30
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# Default value for next()
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iterator = iter([1, 2])
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print(next(iterator, "No more items"))  # 1
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print(next(iterator, "No more items"))  # 2
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print(next(iterator, "No more items"))  # No more items (default)

`enumerate()`

Returns an iterator of tuples containing index and value:

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items = ['apple', 'banana', 'cherry']
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for index, value in enumerate(items):
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    print(f"{index}: {value}")
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# 0: apple
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# 1: banana
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# 2: cherry
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# With start parameter
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for index, value in enumerate(items, start=1):
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    print(f"{index}: {value}")
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# 1: apple
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# 2: banana
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# 3: cherry

`zip()`

Combines multiple iterables into an iterator of tuples:

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names = ['Alice', 'Bob', 'Charlie']
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ages = [25, 30, 35]
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for name, age in zip(names, ages):
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    print(f"{name} is {age} years old")
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# Alice is 25 years old
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# Bob is 30 years old
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# Charlie is 35 years old
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# Different lengths - stops at shortest
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list1 = [1, 2, 3]
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list2 = ['a', 'b']
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for item in zip(list1, list2):
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    print(item)  # (1, 'a'), (2, 'b')

`reversed()`

Returns a reverse iterator:

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my_list = [1, 2, 3, 4, 5]
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for item in reversed(my_list):
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    print(item)  # 5, 4, 3, 2, 1
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# Works with strings too
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for char in reversed("Python"):
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    print(char)  # n, o, h, t, y, P

Exercises

Exercise 1: Basic Iterator

Create a class called CountUp that implements the iterator protocol. It should start at 0 and count up to a given limit (exclusive). Read the limit from input and print all numbers from the iterator.

Answer:

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class CountUp:
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    def __init__(self, limit):
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        self.current = 0
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        self.limit = limit
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if self.current >= self.limit:
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            raise StopIteration
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        value = self.current
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        self.current += 1
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        return value
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limit = int(input())
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counter = CountUp(limit)
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for num in counter:
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    print(num)

Exercise 2: Using iter() and next()

Create a list with values [10, 20, 30, 40, 50]. Use iter() to get an iterator, then use next() three times to get the first three values. Print each value on a separate line.

Answer:

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my_list = [10, 20, 30, 40, 50]
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iterator = iter(my_list)
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print(next(iterator))
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print(next(iterator))
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print(next(iterator))

Exercise 3: Custom Range Iterator

Create a class called MyRange that implements the iterator protocol. It should work like range(): take start, stop, and optional step (default 1). Read start, stop, and step from input, then iterate and print all values.

Answer:

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class MyRange:
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    def __init__(self, start, stop, step=1):
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        self.start = start
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        self.stop = stop
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        self.step = step
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        self.current = start
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    def __iter__(self):
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        return self
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    def __next__(self):
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        if (self.step > 0 and self.current >= self.stop) or \
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           (self.step < 0 and self.current <= self.stop):
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            raise StopIteration
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        value = self.current
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        self.current += self.step
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        return value
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start = int(input())
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stop = int(input())
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step = int(input())
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my_range = MyRange(start, stop, step)
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for num in my_range:
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    print(num)

Exercise 4: Using enumerate()

Read a number n, then read n strings. Use enumerate() to iterate over the strings and print each one with its index in the format “Index: value”.

Answer:

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n = int(input())
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items = []
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for i in range(n):
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    items.append(input())
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for index, value in enumerate(items):
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    print(f"{index}: {value}")

Exercise 5: Using zip()

Read two numbers n and m, then read n names and m ages. Use zip() to combine them and print each name with its age in the format “Name is Age years old”. If the lists have different lengths, only process the shorter length.

Answer:

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n = int(input())
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m = int(input())
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names = []
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for i in range(n):
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    names.append(input())
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ages = []
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for i in range(m):
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    ages.append(int(input()))
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for name, age in zip(names, ages):
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    print(f"{name} is {age} years old")

Course Progress

Section 53 of 61

Back to Course

Iterators

Table of Contents

Table of Contents

Course Progress

Iterators

Iterables vs Iterators

Iterables

Iterators

The Iterator Protocol

How `for` Loops Work

Creating Custom Iterators

Basic Iterator Class

Iterator with Custom Range

Iterator for Fibonacci Sequence

Separating Iterable and Iterator

Built-in Iterator Functions

`iter()` and `next()`

`enumerate()`

`zip()`

`reversed()`

Exercises

Exercise 1: Basic Iterator

Basic Iterator

Exercise 2: Using iter() and next()

Using iter() and next()

Exercise 3: Custom Range Iterator

Custom Range Iterator

Exercise 4: Using enumerate()

Using enumerate()

Exercise 5: Using zip()

Using zip()

Course Progress