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ENOUGH PYTHON: data structures, algorithms, and problem solving with code
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About ENOUGH PYTHON: Data Structures, Algorithms, And
OVERVIEW A minimalist guide to Python, this book introduces just enough of the language to start writing useful programs while avoiding unnecessary complexity. Through clear explanations and hands-on code examples, it builds a strong foundation in programming. It includes a self-contained project to reinforce key concepts and presents 99 carefully chosen coding problems with optimal solutions, deepening understanding of algorithms and data structures. Concluding with reflections on the future of programming in the age of AI, it emphasizes how mastering core principles remains essential even as AI-driven development evolves. FROM THE AUTHOR I was never satisfied with existing textbooks on introductory topics in Computer Science. Too often they overwhelm the reader with subjects that are too broad or go too deep. I believe that minimalism is a virtue when it comes to introducing a new subject to a diverse audience. This book is my attempt to address this gap. It is based on lecture notes I collected over several years of teaching university courses with a programming component. It is meant to be a concise, focused, and practical guide to Python programming for beginners. The content is structured to gradually build your understanding of programming principles without going too deep into the topics presented. Unlike many programming books that dive deeply into specific libraries or data science topics, this book steers clear of such details, opting instead to teach fundamental Python features and how to use them effectively. It serves as an ideal first book on both programming and Python, giving readers a complete but focused learning experience. Before going into details of Python syntax, the book starts with an introductory chapter on history of computing. This chapter links the development of Python to advances going back to ancient times, providing a broad perspective on the field of computing. It is meant to inspire readers and provide a context for the material that follows. I find such background often missing from programming books, which can make the subject seem dry and disconnected. Having the past in mind can help you appreciate the present and anticipate future developments in programming languages and computing in general. In the second to the last chapter, you'll find a self-contained programming project that ties together a selection of concepts covered earlier along with additional material. This project acts as a practical application of what you have learned, solidifying your understanding of Python and programming, while introducing a fundamental concept in theory of computing: cellular automata. It is also a fun project that you can extend and modify further on your own. The penultimate chapter, which is the most extensive, introduces you to the most useful data structures and algorithms. This section is presented through 99 coding problems, each with an optimal solution and explanation. These problems demonstrate various programming techniques, offering a deep dive into how data structures and algorithms can be applied effectively in Python. The last chapter is an epilogue discussing the future of programming in the era of artificial intelligence. In this new age of AI-powered development, tools can streamline coding more than ever — yet mastery of core principles remains the bedrock of truly effective programming. The ability to guide and refine AI-generated solutions depends on a deep understanding of data structures, algorithms, and language syntax. Mastering the material in this book, will make you a lot more efficient and successful at using AI assistants in code development. In summary, this book introduces just enough python to start writing useful programs and embark on your programming adventure. I hope you enjoy reading this book and find it useful in your self-development journey, wherever it leads you!
