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🚀 Advanced Python

Python Iterators – __iter__, __next__, and the Iterator Protocol

Iterators are the engine behind Python's for loops, list comprehensions, and unpacking. Everything you iterate over — lists, strings, dicts, files, generators — is an iterator or iterable under the hood. Understanding the iterator protocol lets you create custom sequences and work efficiently with large data.

⏱️ 20 min read🎯 Advanced📅 Updated 2026

The Iterator Protocol

An object is an iterator if it implements two methods: __iter__() (returns the iterator itself) and __next__() (returns the next value, raises StopIteration when done).

Python
# What a for loop actually does:
my_list = [1, 2, 3]
iterator = iter(my_list)   # calls __iter__()

print(next(iterator))   # 1 — calls __next__()
print(next(iterator))   # 2
print(next(iterator))   # 3
# next(iterator)        # Raises StopIteration
▶ Output
1 2 3

Creating a Custom Iterator

Implement __iter__ and __next__ to make any class iterable.

Python
class Countdown:
    """Counts from n down to 1."""
    def __init__(self, start):
        self.current = start

    def __iter__(self):
        return self   # The iterator IS the object

    def __next__(self):
        if self.current <= 0:
            raise StopIteration
        value = self.current
        self.current -= 1
        return value

for num in Countdown(5):
    print(num, end=" ")
▶ Output
5 4 3 2 1

Iterators vs Generators

Generators are iterators created with yield — much less code for the same result.

Python
# Iterator (verbose)
class EvenNumbers:
    def __init__(self, limit):
        self.num, self.limit = 0, limit
    def __iter__(self): return self
    def __next__(self):
        if self.num > self.limit: raise StopIteration
        val = self.num; self.num += 2; return val

# Generator (same thing, 4 lines)
def even_numbers(limit):
    for n in range(0, limit+1, 2):
        yield n

print(list(even_numbers(10)))
▶ Output
[0, 2, 4, 6, 8, 10]
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itertools – Powerful Iterator Combinators

The itertools module provides fast, memory-efficient iterator tools.

Python
import itertools

# chain: combine multiple iterables
result = list(itertools.chain([1,2], [3,4], [5]))
print(result)   # [1, 2, 3, 4, 5]

# islice: slice any iterator
result = list(itertools.islice(range(100), 5))
print(result)   # [0, 1, 2, 3, 4]

# cycle: repeat infinitely
counter = 0
for item in itertools.cycle(["A","B","C"]):
    print(item, end=" ")
    counter += 1
    if counter == 7: break
▶ Output
[1, 2, 3, 4, 5] [0, 1, 2, 3, 4] A B C A B C A
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