Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that they’re easier to test and debug.

    The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together.After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer- significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.

    Spammers, virus writers, phishermen, money launderers, and spies now trade busily with each other in a lively online criminal economy and as they specialize, they get better. In this indispensable, fully updated guide, Ross Anderson reveals how to build systems that stay dependable whether faced with error or malice. Here's straight talk on critical topics such as technical engineering basics, types of attack, specialized protection mechanisms, security psychology, policy, and more.

    It starts with core concepts like sending, receiving, routing, and transforming data and then shows readers the entire lifecycle. The book goes in depth on how to test, deal with errors, scale, deploy, and monitor apps and even how to build custom tooling. Written by core developers of Camel and the authors of the first edition, this book distills their experience and practical insights so that readers can tackle integration tasks like a pro.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

    On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as:Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports "quantified comparisons," but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.

    But while most of us today can work a computer--albeit with the help of the ever-present computer software manual--we know little about what goes on inside the box and virtually nothing about software designor the world of computer programming. In Patterns of Software, the respected software pioneer and computer scientist, Richard Gabriel, gives us an informative inside look at the world of software design and computer programming and the business that surrounds them. In this wide-ranging volume, Gabriel discusses such topics as whatmakes a successful programming language, how the rest of the world looks at and responds to the work of computer scientists, how he first became involved in computer programming and software development, what makes a successful software business, and why his own company, Lucid, failed in 1994, tenyears after its inception. Perhaps the most interesting and enlightening section of the book is Gabriel's detailed look at what he believes are the lessons that can be learned from architect Christopher Alexander, whose books--including the seminal A Pattern Language--have had a profound influence on the computer programmingcommunity. Gabriel illuminates some of Alexander's key insights--the quality without a name, pattern languages, habitability, piecemeal growth--and reveals how these influential architectural ideas apply equally well to the construction of a computer program. Gabriel explains the concept ofhabitability, for example, by comparing a program to a New England farmhouse and the surrounding structures which slowly grow and are modified according to the needs and desires of the people who live and work on the farm. Programs live and grow, and their inhabitants--the programmers--need to workwith that program the way the farmer works with the homestead. Although computer scientists and software entrepreneurs will get much out of this book, the essays are accessible to everyone and will intrigue anyone curious about Silicon Valley, computer programming, or the world of high technology.

    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.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    Now there's help. The long-awaited official documentation to Maven is here. Written by Maven creator Jason Van Zyl and his team at Sonatype, Maven: The Definitive Guide clearly explains how this tool can bring order to your software development projects. Maven is largely replacing Ant as the build tool of choice for large open source Java projects because, unlike Ant, Maven is also a project management tool that can run reports, generate a project website, and facilitate communication among members of a working team. To use Maven, everything you need to know is in this guide. The first part demonstrates the tool's capabilities through the development, from ideation to deployment, of several sample applications -- a simple software development project, a simple web application, a multi-module project, and a multi-module enterprise project. The second part offers a complete reference guide that includes:The POM and Project Relationships The Build Lifecycle Plugins Project website generation Advanced site generation Reporting Properties Build Profiles The Maven Repository Team Collaboration Writing Plugins IDEs such as Eclipse, IntelliJ, ands NetBeans Using and creating assemblies Developing with Maven ArchetypesSeveral sources for Maven have appeared online for some time, but nothing served as an introduction and comprehensive reference guide to this tool -- until now. Maven: The Definitive Guide is the ideal book to help you manage development projects for software, web applications, and enterprise applications. And it comes straight from the source.

    In this book, we'll will walk you through installing, deploying, managing, and extending Docker. We're going to do that by first introducing you to the basics of Docker and its components. Then we'll start to use Docker to build containers and services to perform a variety of tasks. We're going to take you through the development life cycle, from testing to production, and see where Docker fits in and how it can make your life easier. We'll make use of Docker to build test environments for new projects, demonstrate how to integrate Docker with continuous integration workflow, and then how to build application services and platforms. Finally, we'll show you how to use Docker's API and how to extend Docker yourself. We'll teach you how to: * Install Docker. * Take your first steps with a Docker container. * Build Docker images. * Manage and share Docker images. * Run and manage more complex Docker containers. * Deploy Docker containers as part of your testing pipeline. * Build multi-container applications and environments. * Explore the Docker API. * Getting Help and Extending Docker.

    Plenty of books describe what agile development is or why it helps software projects succeed, but very few combine information for developers, managers, testers, and customers into a single package that they can apply directly. This book provides no-nonsense advice on agile planning, development, delivery, and management taken from the authors' many years of experience with Extreme Programming (XP). You get a gestalt view of the agile development process, including comprehensive guidance for non-technical readers and hands-on technical practices for developers and testers. The Art of Agile Development gives you clear answers to questions such as:How can we adopt agile development? Do we really need to pair program? What metrics should we report? What if I can't get my customer to participate? How much documentation should we write? When do we design and architect? As a non-developer, how should I work with my agile team? Where is my product roadmap? How does QA fit in? The book teaches you how to adopt XP practices, describes each practice in detail, then discusses principles that will allow you to modify XP and create your own agile method. In particular, this book tackles the difficult aspects of agile development: the need for cooperation and trust among team members. Whether you're currently part of an agile team, working with an agile team, or interested in agile development, this book provides the practical tips you need to start practicing agile development. As your experience grows, the book will grow with you, providing exercises and information that will teach you first to understand the rules of agile development, break them, and ultimately abandon rules altogether as you master the art of agile development. "Jim Shore and Shane Warden expertly explain the practices and benefits of Extreme Programming. They offer advice from their real-world experiences in leading teams. They answer questions about the practices and show contraindications - ways that a practice may be mis-applied. They offer alternatives you can try if there are impediments to applying a practice, such as the lack of an on-site customer. --Ken Pugh, Author of Jolt Award Winner, Prefactoring "I will leave a copy of this book with every team I visit." --Brian Marick, Exampler Consulting

    This book provides a step-by-step framework on how to tackle a system design question. It includes many real-world examples to illustrate the systematic approach with detailed steps that you can follow.What’s inside?- An insider’s take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 15 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.Table Of ContentsChapter 1: Scale From Zero To Millions Of UsersChapter 2: Back-of-the-envelope EstimationChapter 3: A Framework For System Design InterviewsChapter 4: Design A Rate LimiterChapter 5: Design Consistent HashingChapter 6: Design A Key-value StoreChapter 7: Design A Unique Id Generator In Distributed SystemsChapter 8: Design A Url ShortenerChapter 9: Design A Web CrawlerChapter 10: Design A Notification SystemChapter 11: Design A News Feed SystemChapter 12: Design A Chat SystemChapter 13: Design A Search Autocomplete SystemChapter 14: Design YoutubeChapter 15: Design Google DriveChapter 16: The Learning Continues

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    Designed for readers who don't need the academic formality, it's a fast and easy computer science guide. It teaches essential concepts for people who want to program computers effectively. First, it introduces discrete mathematics, then it exposes the most common algorithms and data structures. It also shows the principles that make computers and programming languages work.