Now you can get in on the action as well. This book describes metaprogramming as an essential component of Ruby. Once you understand the principles of Ruby, including the object model, scopes, and eigenclasses, you're on your way to applying metaprogramming both in your daily work and in your fun, after-hours projects. Learning metaprogramming doesn't have to be difficult or boring. By taking you on a Monday-through-Friday workweek adventure with a pair of programmers, Paolo Perrotta helps make mastering the art of metaprogramming both straightforward and entertaining. The book is packed with:Pragmatic examples of metaprogramming in action, many of which come straight from popular libraries or frameworks, such as Rails. Programming challenges that let you experiment and play with some of the most fun, "out-there" metaprogramming concepts. Metaprogramming spells--34 practical recipes and idioms that you can study and apply right now, to write code that is sure to impress. Whether you're a Ruby apprentice on the path to mastering the language or a Ruby wiz in search of new tips, this book is for you.

    It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.A book by Git experts to turn you into a Git expert. Introduces the world of distributed version control Shows how to build a Git development workflow.

    Focus is on an in-depth analysis and exposition of not-so-obvious coding errors in the sample code provided. The theme is to answer the questions 'How couild I have automatically detected this bug' and 'How could I have prevented this bug'? Chapters include programmer attitudes, techniques and debugging methodology. A particularly revealing chapter is "Treacheries of the Trade", should be required reading for all C maniacs. The author has been a professional programmer for seventeen years and draws heavily (and candidly) on actual coding problems and practices based on years of experience at Microsoft.

    and abroad, this reader-friendly yet authoritative volume bridges the gap between circuits and new electromagnetics material. Ulaby begins coverage with transmission lines, leading readers from familiar concepts into more advanced topics and applications. Includes six new sections on Waveguides and Cavity Resonators, replacing the material on geometric optics in Chapter 8. Presents new Technology Briefs on relevant topics, connecting concepts in the book to everyday applications found in real life, such as liquid crystal displays, the laser, GPS, and x-ray tomography. Includes an interactive CD-ROM that allows readers to gain physical intuition about electromagnetics. A useful reference for engineers.

    It's available on almost every OS--if you master the techniques in this book, you'll never need another text editor. Practical Vim shows you 120 vim recipes so you can quickly learn the editor's core functionality and tackle your trickiest editing and writing tasks. Vim, like its classic ancestor vi, is a serious tool for programmers, web developers, and sysadmins. No other text editor comes close to Vim for speed and efficiency; it runs on almost every system imaginable and supports most coding and markup languages. Learn how to edit text the "Vim way:" complete a series of repetitive changes with The Dot Formula, using one keystroke to strike the target, followed by one keystroke to execute the change. Automate complex tasks by recording your keystrokes as a macro. Run the same command on a selection of lines, or a set of files. Discover the "very magic" switch, which makes Vim's regular expression syntax more like Perl's. Build complex patterns by iterating on your search history. Search inside multiple files, then run Vim's substitute command on the result set for a project-wide search and replace. All without installing a single plugin! You'll learn how to navigate text documents as fast as the eye moves--with only a few keystrokes. Jump from a method call to its definition with a single command. Use Vim's jumplist, so that you can always follow the breadcrumb trail back to the file you were working on before. Discover a multilingual spell-checker that does what it's told.Practical Vim will show you new ways to work with Vim more efficiently, whether you're a beginner or an intermediate Vim user. All this, without having to touch the mouse.What You Need: Vim version 7

    Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    More importantly, this book provides a framework for thinking about computer organization and design that will enable the reader to continue the lifetime of learning necessary for staying at the forefront of this competitive discipline. --John Crawford Intel Fellow Director of Microprocessor Architecture, Intel The performance of software systems is dramatically affected by how well software designers understand the basic hardware technologies at work in a system. Similarly, hardware designers must understand the far reaching effects their design decisions have on software applications. For readers in either category, this classic introduction to the field provides a deep look into the computer. It demonstrates the relationship between the software and hardware and focuses on the foundational concepts that are the basis for current computer design. Using a distinctive learning by evolution approach the authors present each idea from its first principles, guiding readers through a series of worked examples that incrementally add more complex instructions until they ha

    If you have received one of these copies, please contact the Pragmatic Bookshelf at support@pragprog.com, and we will replace it for you.Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby.Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Jay Wengrow brings to this book the key teaching practices he developed as a web development bootcamp founder and educator.Use these techniques today to make your code faster and more scalable.

    Mastering Algorithms with C offers you a unique combination of theoretical background and working code. With robust solutions for everyday programming tasks, this book avoids the abstract style of most classic data structures and algorithms texts, but still provides all of the information you need to understand the purpose and use of common programming techniques.Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included.Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth.Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters.Contents include:PointersRecursionAnalysis of algorithmsData structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs)Sorting and searchingNumerical methodsData compressionData encryptionGraph algorithmsGeometric algorithms

    Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review. If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    

    The text offers a flexible organization, enabling instructors to adapt the book to their particular courses. The book is both complete and careful, and it continues to maintain its emphasis on algorithms and applications. Excellent exercise sets allow students to perfect skills as they practice. This new edition continues to feature numerous computer science applications-making this the ideal text for preparing students for advanced study.

    It assumes absolutely no prior programming knowledge and will guide you carefully and slowly through the learning process.Learn Ruby The Hard Way is a translation of the original "Learn Python The Hard Way" to teaching Ruby, with the translation done by Rob Sobers. "Learn Python The Hard Way" has taught hundreds of thousands worldwide how to code in Python, and this book uses the same proven method for Ruby. When you are done with this book you will have the skill to move on to other books about Ruby and be ready to understand them.