The Iterator Protocol
Explore how Python processes data during loops by directly working with the iterator protocol. Understand the roles of iterables and iterators, manual iteration with iter() and next(), and the use of StopIteration to signal completion. This lesson equips you to create and use custom iterators and generators for efficient, memory-friendly data handling.
for loops are commonly used to process lists, strings, and files. From a user’s perspective, Python appears to automatically move from one item to the next during iteration. Internally, every for loop operates according to the iterator protocol.
Each time a for loop runs, Python creates an iterator object that tracks the current position in the data and signals when no items remain. The for loop is syntactic sugar built on top of this mechanism. In this lesson, we will examine this behavior and interact with the iterator protocol directly. This approach shows how Python processes sequences and streams data during iteration.
Iterables vs. iterators
To understand iteration, we must distinguish between two key terms: the iterable and the iterator.
Iterable: This is the data container itself (like a list, tuple, or string). stores the elements but does not track the current iteration position. It can produce an iterator.
Iterator: This is a temporary helper object produced by the iterable. It acts like a cursor or a bookmark. It knows which item is next and how to retrieve it. It does not hold ...