Understanding Python's for Loop: Syntax, Else Clause, Iterables, Iterators, and Bytecode Disassembly

In this tutorial we explore the inner workings of Python's for loop, starting with a simple example that iterates over a list of strings and prints each element.

We then introduce the optional else clause, explaining when it runs (after the iterator is exhausted without a break ) and how it can replace a manual boolean flag for post‑loop actions.

The article defines iterable objects as any object that can be passed to iter() to obtain an iterator, and shows built‑in examples such as lists, tuples, and strings.

It describes iterators as objects that implement the iterator protocol: the __iter__() method returning the iterator itself and the __next__() method returning the next element or raising StopIteration . The relationship between iterables and iterators is illustrated with diagrams.

Next, we implement a custom iterator class Range that mimics range() by storing a start, stop, and step, and defining __iter__ and __next__ . We also create a corresponding iterable wrapper that returns a fresh Range instance on each call to __iter__ , demonstrating how to use it in a for loop.

The execution flow of a for loop is broken down into five steps: (1) call iter() on the target, (2) repeatedly call next() , (3) execute the loop body with the retrieved value, (4) continue until StopIteration is raised, and (5) optionally run the else block. The impact of a break statement on this flow is also noted.

An equivalent while loop is presented to show that the same behavior can be achieved by manually handling the iterator and catching StopIteration .

Finally, the article demonstrates how to disassemble a for loop using Python's dis module. It walks through the generated bytecode line by line, explaining instructions such as SETUP_LOOP , GET_ITER , FOR_ITER , STORE_NAME , CALL_FUNCTION , POP_BLOCK , and the final RETURN_VALUE , highlighting how the interpreter implements the loop and the optional else block.

By the end, readers should have a clear mental model of how Python's for loop operates at both the source‑code and bytecode levels, and how to create their own iterable and iterator types.