دانلود کتاب ساختار داده ها و الگوریتم ها با پایتون

Thanks for choosing Data Structures and Algorithms with Python. This text was written based on classroom notes for two courses, an introductory data structures and algorithms course and an advanced data structures and algorithms course. The material contained in this text can be taught in two semesters. The early chapters in this text are intended as an introductory text for data structures and algorithms while the latter chapters cover advanced topics that are suitable for a second course. The Python language is used throughout the text, and some familiarity with Python or some other object-oriented language is assumed. However, the first chapter contains a Python primer for those coming from a different language background. This text serves well as a follow-on text to Python Programming Fundamentals by Kent D. Lee and published by Springer, but does not require you to have read that text. In this text, the next steps are taken to teach you how to handle large amounts of data efficiently. A number of algorithms are introduced, and the need for them is motivated through examples that bring meaning to the problems we face as computer programmers. An algorithm is a well-defined procedure for accomplishing a task. Algorithms are an important part of Computer Science, and this text explores many algorithms to give you the background you need when writing programs of your own. The goal is that having seen some of the sorts of algorithms presented in this text, you will be able to apply these techniques to other programs you write in the future. Another goal of this text is to introduce you to the idea of computational complexity. While there are many unique and interesting algorithms that we could explore, it is important to understand that some algorithms are more efficient than others. While computers are very good at doing calculations quickly, an inefficient algorithm can make the fastest computer seem very slow or even make it appear to come to a halt. This text will show you what can and cannot be computed efficiently. The text builds this idea of efficiency from the most basic of facts giving you the tools you’ll need to determine just how efficient any algorithm is so you can make informed judgements about the programs you write. Two new chapters are now included with the book on parallel programming using multiprocessing. An API that can support today’s demanding dynamic workloads is essential, and the Python multiprocessing API was designed for this purpose. While the final two chapters are optional, the concepts introduced in these chapters work well as a capstone to an advanced data structures and algorithms course. The text assumes that you have some prior experience in computer programming, probably from an introductory programming course where you learned to break simple problems into steps that could be solved by a computer. The language you used may have been Python, but not necessarily. Python is an excellent language for a text on data structures and algorithms whether you have used it before or not. Python is an object-oriented programming language with operator overloading and dynamic typing. Whether this is your first exposure to Python or you used it in your first course, you’ll learn more about the language from this text. The first chapter of the text reviews some of the fundamentals of computer programming along with the basic syntax of Python to get you up to speed in the language. Then subsequent chapters dive into more advanced topics and should be read in sequence.