Getting Started with Python: Understand key data structures and use Python in object-oriented programming

Python becomes more useful when you understand not only its syntax, but also how to choose data structures, reason about algorithms, and shape code into maintainable programs. Getting Started with Python builds that understanding step by step, beginning with the language’s core features and extending into algorithms and object-oriented design.

Start with the building blocks

The opening chapters introduce Python’s environment, execution model, built-in data types, decisions, loops, and functions. From there, the discussion turns to files and data persistence, including working with directories, JSON, streams, and databases. This foundation helps connect everyday coding choices to the way a program is organized and behaves.

Understand the structures behind the code

Data structures and algorithms take center stage as the book explores linked lists, stacks, queues, trees, hash tables, and graphs. Searching, sorting, selection, and runtime analysis add a way to think about how these structures solve problems—and how their trade-offs affect a program.

Bring object-oriented ideas into practice

Later sections examine classes and objects, interfaces, encapsulation, composition, inheritance, polymorphism, and exceptions. The book also covers iterators, generators, design patterns, and testing, giving readers a broader vocabulary for organizing Python applications and checking that their code works as intended.

Who will find it useful?

This book suits readers beginning to write Python scripts or programs, as well as developers coming from another object-oriented language who want to work with Python’s approach. Its progression from fundamentals to algorithms and design makes it useful for readers who want to understand how individual coding concepts fit together.

Follow the path from first principles to more structured software, with Python’s data structures and design choices kept firmly in view.