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Python Iterators and Iterable Objects
From zip() to Building Your Own Iterators
In Python, an iterator is an object that lets you loop (iterate) over a certain “container”, such as lists, sets, tuples, or dictionaries, one element at a time, without loading all elements into memory at once. This makes iterators memory-efficient, especially when dealing with large datasets. The zip() function is an example of an iterator function. From a technical point of view, an iterator is an object that implements two methods: __iter__() and __next__().
Everything in Python is an object: lists, dictionaries, tuples, functions… Many of these are iterable objects, which means they can be looped over. This is the foundation behind for loops and comprehensions.
Under the hood, not all iterables are the same. Some objects are just containers that can be turned into an iterator. Others are also iterators and produce values one at a time, lazily, and remember where they left off. Understanding this distinction is useful if you’re working with large datasets, streams, or want to create clean and efficient interfaces.
In this article, we’ll explore how iteration works in Python. We’ll look at common built-in iterators like zip() and enumerate(), and then we'll write our own using classes and generator functions.
