This book is designed for a traditional college-level data structures course, often referred to as CS2. It presumes students possess a foundational understanding of Python syntax and familiarity with using existing classes. Most introductory CS1 courses utilizing Python should adequately cover these prerequisites, with some potentially touching upon topics explored in this book. We recognize that while most students completing a CS1 course can effectively utilize classes, many require additional practical experience in designing and implementing their own. To address this, we incorporate numerous class design examples within the initial chapters.
Python's object-oriented nature makes it an ideal language for initiating a data structures course, facilitating a smoother learning curve. However, Python's abstraction of memory management complexities presents a potential challenge for a data structures course. While beneficial in an introductory setting, a second course should expose students to these underlying, low-level details typically concealed by the Python interpreter. The efficiency of Python allows us to cover fundamental data structures more rapidly, creating time to introduce a second language within a single-semester CS2 course. By reinforcing Python programming skills in the early chapters, students can readily acquire proficiency in a second object-oriented language. C++ serves as an excellent choice for this second language, exposing students to a compiled language that operates at a lower level. While C++ syntax presents greater complexity than Python, this hurdle is manageable once students have grasped core programming concepts using Python. Their understanding of programming fundamentals, such as conditional and looping statements, allows them to focus on mastering the corresponding C++ syntax, promoting a deeper understanding of computer science principles.
