The Iterator Protocol

Expert Answer & Key Takeaways

Mastering The Iterator Protocol is essential for high-fidelity technical performance and advanced exam competency in 2026.

The Iterator Protocol: iter, next and Custom Iterables (2026)

The Iterator Protocol is the fundamental mechanism that allows any Python object to be used in a for loop or comprehension by implementing the __iter__ and __next__ dunder methods.

1. The Proof Code (Custom Range Implementation)

from typing import Self

class CustomRange:
    """A custom iterable that replicates the basic behavior of range()."""
    def __init__(self, start: int, end: int):
        self.start = start
        self.end = end

    def __iter__(self) -> Self:
        # Returns the iterator object (self)
        self.current = self.start
        return self

    def __next__(self) -> int:
        # Logic to produce the next value
        if self.current >= self.end:
            raise StopIteration
        
        val = self.current
        self.current += 1
        return val

if __name__ == "__main__":
    nums = CustomRange(1, 4)
    for n in nums:
        print(n)

# Output:
# 1
# 2
# 3

2. Execution Breakdown

The Iterable Interface: An 'Iterable' is an object that implements __iter__. When you start a for loop, Python calls iter(obj), which triggers obj.__iter__().
The Iterator Interface: An 'Iterator' is an object that implements __next__. On every loop iteration, Python calls next(it), which triggers it.__next__().
StopIteration: This exception is the signal that the iteration is complete. It is the only way Python knows when to stop a loop without a fixed size.
State Management: The iterator itself must maintain the state of where it is in the collection. Once an iterator is exhausted, it cannot be 'reset' unless a new iterator is created via __iter__.

3. Detailed Theory

Understanding the separation between an Iterable and its Iterator is key to building complex data structures.

Iterable vs. Iterator

Iterable: The collection itself (e.g., a List, String, or our CustomRange class). It 'produces' iterators.
Iterator: The stateful object that knows which element is next. In many custom classes, __iter__ simply returns self, making the object both an iterable and its own iterator.

The C-Level 'for' Loop

Internally, a Python for loop is equivalent to this while loop:

_it = iter(iterable)
while True:
    try:
        item = next(_it)
        # ... loop body ...
    except StopIteration:
        break

Infinite Iterators

Because iterators only produce values on demand, they can represent infinite sequences. The itertools.count() function is a classic example of an infinite iterator that uses the protocol without a predefined end point.

[!TIP] Senior Secret: If you are building a custom collection, keep the 'Iterator' separate from the 'Iterable' if you want to support multiple simultaneous iterations. If __iter__ returns self, you can only iterate over the object once at a time. If it returns a new Iterator object, you can have multiple for loops running on the same collection independently.

The Iterator Protocol

Expert Answer & Key Takeaways