Fundamentals of Python: Data Structures

Good Python programming depends on more than knowing the language syntax: it also means understanding how information is organized, how operations perform, and why one implementation may suit a problem better than another. Kenneth A. Lambert’s Fundamentals of Python: Data Structures builds that foundation in a carefully sequenced introduction to collections, object-oriented design, and algorithm analysis.

The second edition starts with Python fundamentals and moves from collection concepts into concrete structures and their implementations. Along the way, it considers not only how data structures work, but also the practical trade-offs in time and memory that shape a program’s design.

From Python basics to collection design 💻

Early chapters review program elements, functions, exceptions, files, and classes before introducing a taxonomy of collections. That progression helps connect the language’s everyday building blocks with the larger question of how to represent and process data.

Understand performance, not just behavior

Searching, sorting, and complexity analysis provide tools for thinking about algorithm efficiency. The book discusses run time, memory use, and best-, worst-, and average-case performance—useful context for comparing approaches rather than judging an algorithm only by whether it works.

Explore the structures behind everyday operations

Coverage includes arrays and linked structures, followed by interfaces, implementations, inheritance, and abstract classes. Dedicated chapters examine stacks, queues, lists, and trees; the book also addresses collections including sets, dictionaries, and graphs. Comparisons between array-based and link-based implementations bring the costs and benefits of different designs into view.

Who may find this book useful?

The publisher positions the material for readers with at least one semester of experience programming in an object-oriented language such as Python, Java, or C++. It is a useful fit for computing students and other learners ready to move beyond introductory syntax into data structures, collection design, and algorithm analysis.

For readers who want to understand both the shape of a data structure and the reasoning behind its implementation, Lambert’s text offers a structured route through the core ideas of Python data structures.