Data Structures And Algorithms In Python
Code Java like a TRUE EXPERT! " Great book for learning Java. This book backs up concepts introduced with clear and logical examples." " - Allen B, from Amazon.com " "The beauty of this book is that you can study these foundations at your own pace, always at just the right speed." " - Denis Chen, from Amazon.com " " I would recommend it to all aspiring Java programmers! " " - Jason Smith, from Amazon.
Python has been growing rapidly as the language for CS1. The lack of texts and lack of consensus in departments have prevented wide adoption in CS2 so far, However, this is changing as more schools are discovering how well Python is working in CS1 and more texts become available. This textbook is based on the authors' market-leading data structures books in Java and C and offers a comprehensive, definitive introduction to data structures in Python.
It is the Python version of "Data Structures and Algorithms Made Easy." Table of Contents: goo.gl/VLEUca Sample Chapter: goo.gl/8AEcYk Source Code: goo.gl/L8Xxdt The sample chapter should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our Python coding style. This book focuses on giving solutions for complex problems in data structures and algorithm.
This book covers a wide breadth of important and useful subject matter without sacrificing depth. It introduces the reader to the Python programming language, but does not assume deep prior knowledge of computer science or computer programming. The book also provides an in-depth introduction to a variety of algorithms and data structures that are used throughout the industry.
This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use.