The title says it is the hard way to learn to writecode but it’s actually not. It’s the “hard” way only in that it’s the way people used to teach things. In this book youwill do something incredibly simple that all programmers actually do to learn a language: 1. Go through each exercise. 2. Type in each sample exactly. 3. Make it run.That’s it. This will be very difficult at first, but stick with it. If you go through this book, and do each exercise for1-2 hours a night, then you’ll have a good foundation for moving on to another book. You might not really learn“programming” from this book, but you will learn the foundation skills you need to start learning the language.This book’s job is to teach you the three most basic essential skills that a beginning programmer needs to know:Reading And Writing, Attention To Detail, Spotting Differences.

    By understanding what the browser can and cannot do, you’ll be able to make better design decisions and deliver faster web applications to your users.Author Ilya Grigorik—a developer advocate and web performance engineer at Google—starts with the building blocks of TCP and UDP, and then dives into newer technologies such as HTTP 2.0, WebSockets, and WebRTC. This book explains the benefits of these technologies and helps you determine which ones to use for your next application.- Learn how TCP affects the performance of HTTP- Understand why mobile networks are slower than wired networks- Use best practices to address performance bottlenecks in HTTP- Discover how HTTP 2.0 (based on SPDY) will improve networking- Learn how to use Server Sent Events (SSE) for push updates, and WebSockets for XMPP chat- Explore WebRTC for browser-to-browser applications such as P2P video chat- Examine the architecture of a simple app that uses HTTP 2.0, SSE, WebSockets, and WebRTC

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Displaying extraordinary creativity and programming virtuosity, Alexandrescu offers a cutting-edge approach to design that unites design patterns, generic programming, and C++, enabling programmers to achieve expressive, flexible, and highly reusable code. This book introduces the concept of generic components--reusable design templates that produce boilerplate code for compiler consumption--all within C++. Generic components enable an easier and more seamless transition from design to application code, generate code that better expresses the original design intention, and support the reuse of design structures with minimal recoding. The author describes the specific C++ techniques and features that are used in building generic components and goes on to implement industrial strength generic components for real-world applications. Recurring issues that C++ developers face in their day-to-day activity are discussed in depth and implemented in a generic way. These include: Policy-based design for flexibility Partial template specialization Typelists--powerful type manipulation structures Patterns such as Visitor, Singleton, Command, and Factories Multi-method engines For each generic component, the book presents the fundamental problems and design options, and finally implements a generic solution.

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    This book contains the fundamental laws of software development, the primary pieces of understanding that make the difference between a mid-level/junior programmer and the high-level senior software engineer. The book exists to help all programmers understand the process of writing software, on a very fundamental level that can be applied to any programming language or project, from here into eternity. Code Simplicity is also written in such a way that even non-technical managers of software teams can gain an understanding of what the “right way” and the “wrong way” is (and why they are right and wrong) when it comes to software design. The focus of the book is primarily on “software design,” the process of creating a plan for a software project and making technical decisions about the pattern and structure of a system.

    The answers aren't easy -- just incredibly successful.

    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

    This practical guide from renowned software architect Neal Ford helps you transition from a Java-writing imperative programmer to a functional programmer, using Java, Clojure, and Scala as examples.Rather than focus on specific language features, Functional Thinking looks at a variety of common practices in OOP languages and then shows you how to solve the same problems with a functional language. For instance, you know how to achieve code-reuse in Java via mechanisms such as inheritance and polymorphism. Code reuse is also possible in functional languages, using high-order functions, composition, and multi-methods.Ford encourages you to value results over steps, so you can begin to think like a functional programmer. Expect your mind to be bent, but you’ll finish with a much better understanding of both the syntax and semantics of functional languages.

    It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a worldwide best-seller. This second edition brings the classic original up to date to include the ANSI standard. From the Preface: We have tried to retain the brevity of the first edition. C is not a big language, and it is not well served by a big book. We have improved the exposition of critical features, such as pointers, that are central to C programming. We have refined the original examples, and have added new examples in several chapters. For instance, the treatment of complicated declarations is augmented by programs that convert declarations into words and vice versa. As before, all examples have been tested directly from the text, which is in machine-readable form. As we said in the first preface to the first edition, C "wears well as one's experience with it grows." With a decade more experience, we still feel that way. We hope that this book will help you to learn C and use it well.

    It guides you step by step from simple tests to tests that are maintainable, readable, and trustworthy. It covers advanced subjects like mocks, stubs, and frameworks such as Typemock Isolator and Rhino Mocks. And you'll learn about advanced test patterns and organization, working with legacy code and even untestable code. The book discusses tools you need when testing databases and other technologies. It's written for .NET developers but others will also benefit from this book.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.Table of ContentsThe basics of unit testingA first unit testUsing stubs to break dependenciesInteraction testing using mock objectsIsolation (mock object) frameworksTest hierarchies and organizationThe pillars of good testsIntegrating unit testing into the organizationWorking with legacy code

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    This one's a keeper." --Robert C. Martin "If you want to be an expert in the state of the art in TDD, you need to understand the ideas in this book."--Michael Feathers Test-Driven Development (TDD) is now an established technique for delivering better software faster. TDD is based on a simple idea: Write tests for your code before you write the code itself. However, this simple idea takes skill and judgment to do well. Now there's a practical guide to TDD that takes you beyond the basic concepts. Drawing on a decade of experience building real-world systems, two TDD pioneers show how to let tests guide your development and "grow" software that is coherent, reliable, and maintainable. Steve Freeman and Nat Pryce describe the processes they use, the design principles they strive to achieve, and some of the tools that help them get the job done. Through an extended worked example, you'll learn how TDD works at multiple levels, using tests to drive the features and the object-oriented structure of the code, and using Mock Objects to discover and then describe relationships between objects. Along the way, the book systematically addresses challenges that development teams encounter with TDD--from integrating TDD into your processes to testing your most difficult features. Coverage includes - Implementing TDD effectively: getting started, and maintaining your momentum throughout the project - Creating cleaner, more expressive, more sustainable code - Using tests to stay relentlessly focused on sustaining quality - Understanding how TDD, Mock Objects, and Object-Oriented Design come together in the context of a real software development project - Using Mock Objects to guide object-oriented designs - Succeeding where TDD is difficult: managing complex test data, and testing persistence and concurrency

    In 1999, "Refactoring" revolutionized design by introducing an effective process for improving code. With the highly anticipated " Refactoring to Patterns ," Joshua Kerievsky has changed our approach to design by forever uniting patterns with the evolutionary process of refactoring.This book introduces the theory and practice of pattern-directed refactorings: sequences of low-level refactorings that allow designers to safely move designs to, towards, or away from pattern implementations. Using code from real-world projects, Kerievsky documents the thinking and steps underlying over two dozen pattern-based design transformations. Along the way he offers insights into pattern differences and how to implement patterns in the simplest possible ways.Coverage includes: A catalog of twenty-seven pattern-directed refactorings, featuring real-world code examples Descriptions of twelve design smells that indicate the need for this book s refactorings General information and new insights about patterns and refactoringDetailed implementation mechanics: how low-level refactorings are combined to implement high-level patterns Multiple ways to implement the same pattern and when to use each Practical ways to get started even if you have little experience with patterns or refactoring"Refactoring to Patterns" reflects three years of refinement and the insights of more than sixty software engineering thought leaders in the global patterns, refactoring, and agile development communities. Whether you re focused on legacy or greenfield development, this book will make you a better software designer by helping you learn how to make important design changes safely and effectively. "