Skip to content

README.md

Latest commit

 

History

History
131 lines (99 loc) · 3.98 KB

README.md

File metadata and controls

131 lines (99 loc) · 3.98 KB
Raw

Module 039: Iterators and the Iterator Protocol

Phase: 4. Functions | Estimated time: 1.5 hours | Milestone Project: No

Prerequisites

  • Module 038 (Generators and yield)

Learning Objectives

By the end of this module, you will be able to:

  • Explain the iterator protocol (__iter__, __next__, StopIteration)
  • Use iter() and next() built-in functions
  • Describe how for loops work under the hood
  • Create custom iterator classes
  • Distinguish between iterables and iterators

Why This Matters

The iterator protocol is the foundation of all iteration in Python — for loops, list comprehensions, map(), filter(), and more. Understanding it gives you deep insight into Python's design and lets you create your own iterable objects.

Concept Explanation

The Iterator Protocol

An iterable is any object that can return an iterator (has __iter__()).
An iterator is an object that produces values one at a time (has __next__() and __iter__()).

Protocol:
1. Call iter() on an iterable → get an iterator
2. Call next() on the iterator → get values
3. When exhausted → raises StopIteration

iter() and next() Built-ins

my_list = [1, 2, 3]
it = iter(my_list)       # get iterator from list
print(next(it))          # 1
print(next(it))          # 2
print(next(it))          # 3
print(next(it))          # StopIteration!

For Loop Mechanics Under the Hood

A for loop is syntactic sugar for the iterator protocol:

for item in iterable:
    print(item)

# Internally:
_it = iter(iterable)
while True:
    try:
        item = next(_it)
    except StopIteration:
        break
    print(item)

Creating Custom Iterators

Implement __iter__() and __next__() in a class:

class CountDown:
    """Iterate from n down to 1."""

    def __init__(self, n):
        self.n = n

    def __iter__(self):
        return self

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

for i in CountDown(5):
    print(i)  # 5 4 3 2 1

Iterable vs Iterator

Aspect Iterable Iterator
Has __iter__() Yes Yes
Has __next__() No Yes
Can be used in for Yes (returns iterator) Yes
Can be used multiple times Yes (new iterator each time) No (single use)
Example list, str, tuple file object, generator 
nums = [1, 2, 3]       # iterable
it1 = iter(nums)       # iterator
it2 = iter(nums)       # new iterator — can iterate again

Common Pitfalls

  1. Confusing iterable and iterator: Lists are iterable, not iterators — they don't have __next__().
  2. Forgetting __iter__ in custom iterators: Must return self.
  3. Not raising StopIteration: The for loop would run forever.
  4. Exhausting a generator: Generators are single-use iterators.

Hands-On Walkthrough

  1. Create a list, get an iterator with iter(), and manually call next() until StopIteration.
  2. Write a custom class Range that works like range() using the iterator protocol.
  3. Prove that for loops use the iterator protocol by manually simulating one.
  4. Check if different types are iterable using hasattr(obj, '__iter__').

Key Takeaways

  • Iterable has __iter__(); iterator has __iter__() and __next__().
  • for loop = iter() + next() + StopIteration.
  • Custom iterators are classes implementing the protocol.
  • Iterables can be iterated many times; iterators are single-use.
  • Generators are a concise way to create iterators.

Further Reading

Next Module

Continue to Module 040: Milestone Project: Text-Based Adventure Game Engine.