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"Python (Computer program language) Problems, exercises, etc."
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Learn Python 3 the hard way : a very simple introduction to the terrifyingly beautiful world of computers and code
Zed Shaw has perfected the world's best system for learning Python. Following it, students will succeed-just like the hundreds of thousands of beginners Zed has taught to date! InLearn Python 3 the Hard Way, students will learn Python while working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix mistakes. Watch the programs run. As they do, they'll learn how software works; what good programs look like; how to read, write, and think about code; and how to find and fix your mistakes using tricks professional programmers use. -- Provided by publisher.
Book
Good habits for great coding : improving programming skills with examples in Python
Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more. Taking an informal, conversational tone, author Michael Stueben offers programming stories, anecdotes, observations, advice, tricks, examples, and challenges based on his 38 years experience writing code and teaching programming classes. Trying to teach style to beginners is notoriously difficult and can easily appear pedantic. Instead, this book offers solutions and many examples to back up his ideas. Good Habits for Great Coding distills Stueben's three decades of analyzing his own mistakes, analyzing student mistakes, searching for problems that teach lessons, and searching for simple examples to illustrate complex ideas. Having found that most learn by trying out challenging problems, and reflecting on them, each chapter includes quizzes and problems in each chapter. The final chapter introduces dynamic programming to reduce complex problems to subcases, and illustrates many concepts discussed in the book. Code samples are provided in Python and designed to be understandable by readers familiar with any modern programming language. At the end of this book, you will have acquired a lifetime of good coding advice; the lessons the author wishes he had learned when he was a novice.
Book
Python Programming Using Problem Solving
Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter.
eBook
Testing Python® - Applying Unit Testing, TDD, BDD, and Acceptance Testing
This book is the most comprehensive book available on testing for one of the top software programming languages in the world. Python is a natural choice for new and experienced developers, and this hands-on resource is a much needed guide to enterprise-level testing development methodologies. The book will show you why Unit Testing and TDD can lead to cleaner, more flexible programs. Unit Testing and Test-Driven Development (TDD) are increasingly must-have skills for software developers, no matter what language they work in. In enterprise settings, it's critical for developers to ensure they always have working code, and that's what makes testing methodologies so attractive. This book will teach you the most widely used testing strategies and will introduce to you to still others, covering performance testing, continuous testing, and more.
eBook
Computational physics
The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming.
This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scientific projects. It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations.
The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded. Then there are exercises and problems at the end of each chapter for the reader to work on their own (with model programs given for that purpose).
eBook