Python Lists: The Workhorse of Sequences

Welcome to the most fundamental and versatile data structure in Python: the list. A list is an ordered, mutable (changeable) collection of items. It’s the go-to container for storing a sequence of elements, whether you’re managing a simple to-do list or handling complex data streams.

Lists are incredibly flexible. They can hold items of different data types, grow and shrink on demand, and provide a rich set of methods for manipulation.

Core Characteristics of Python Lists

Ordered: The items in a list maintain a specific order. [1, 2, 3] is different from [3, 2, 1].
Mutable: You can change a list after it’s created—add, remove, or modify elements.
Dynamic: Lists automatically resize themselves as you add or remove items.
Heterogeneous: A single list can contain a mix of data types (integers, strings, objects, even other lists).

A Quick Example

Pyground

Create a reading list, add a new book, and print the updated list.

Expected Output:

My reading list: ['Clean Code', 'Python Tricks', 'Automate the Boring Stuff', 'Fluent Python']
I have 4 books to read.

Output:

What You’ll Learn in This Section

This chapter provides a comprehensive guide to Python lists, from the basics to advanced techniques.

Creating Lists

Learn all the ways to create a list, from simple literals ([]) to the list() constructor and dynamic generation with list comprehensions. We’ll cover how to initialize lists with default values and build them from other iterables.

Core Operations

Master the fundamental operations you’ll use every day. This includes accessing elements by index, slicing to get sub-lists, concatenating lists with +, and repeating lists with *. You’ll also learn about membership testing with in.

List Methods

Dive deep into the powerful methods built into the list object. We’ll explore methods that modify the list in-place (like .append(), .extend(), .sort(), and .reverse()) and methods that return information about the list (like .index() and .count()).

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How to Approach This Section:

Start with Creation and Operations to build a solid foundation.
Use the Methods page as a reference guide.
Move on to Comprehensions to learn a more Pythonic way of working with lists.
Explore Advanced topics when you’re ready to optimize your code.
Test your skills with the Practice Problems.

Practice Problems Creating Lists