You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    And how to move all of this data becomes nearly as important as the data itself. If you� re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you� ll learn Kafka� s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.Understand publish-subscribe messaging and how it fits in the big data ecosystem.Explore Kafka producers and consumers for writing and reading messagesUnderstand Kafka patterns and use-case requirements to ensure reliable data deliveryGet best practices for building data pipelines and applications with KafkaManage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasksLearn the most critical metrics among Kafka� s operational measurementsExplore how Kafka� s stream delivery capabilities make it a perfect source for stream processing systems

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    In a 1995 interview, the late Steve Jobs claimed that the secret to his and Apple’s success was talent. “We’ve gone to exceptional lengths to hire the best people,” he said, believing that the talented resource was twenty-five times more valuable than an average alternative. For Microsoft founder Bill Gates, the multiple was even higher:A great lathe operator commands several times the wage of an average lathe operator, but a great writer of software code is worth 10,000 times the price of an average software writer.While the actual number might be up for debate, the importance of technical talent is not. The most successful companies today are those that understand the strategic role that developers will play in their success or failure. Not just successful technology companies – virtually every company today needs a developer strategy. There’s a reason that ESPN and Sears have rolled out API programs, that companies are being bought not for their products but their people. The reason is that developers are the most valuable resource in business.How did we get here? How did developers become the most important constituency in business seemingly overnight? The New Kingmakers explores the rise of the developer class, its implications and provides suggestions for navigating the new developer-centric landscape.

    The book covers lambdas, streams, and functional-style programming. With Java 8's functional features you can now write more concise code in less time, and also automatically benefit from multicore architectures. It's time to dig in!

    Written in a frank but engaging style, Debuggingprovides simple, foolproof principles guaranteed to help find any bug quickly. This book makes those shelves of application-specific debugging books (on C++, Perl, Java, etc.) obsolete. It changes the way readers think about debugging, making those pesky problems suddenly much easier to find and fix. Illustrating the rules with real-life bug-detection war stories, the book shows readers how to: * Understand the system: how perceiving the ""roadmap"" can hasten your journey * Quit thinking and look: when hands-on investigation can’t be avoided * Isolate critical factors: why changing one element at a time can be an essential tool * Keep an audit trail: how keeping a record of the debugging process can win the day

    It's a beautifully written tutorial that begins with the basic steps to get your first Ruby program up and running and goes on to explore sophisticated topics like callable objects, reflection, and threading. Whether the topic is simple or tough, the book's easy-to-follow examples and explanations will give you immediate confidence as you build your Ruby programming skills.The Well-Grounded Rubyist is a thoroughly revised and updated edition of the best-selling Ruby for Rails. In this new book, expert author David A. Black moves beyond Rails and presents a broader view of Ruby. It covers Ruby 1.9, and keeps the same sharp focus and clear writing that made Ruby for Rails stand out.Starting with the basics, The Well-Grounded Rubyist explains Ruby objects and their interactions from the ground up. In the middle chapters, the book turns to an examination of Ruby's built-in, core classes, showing the reader how to manipulate strings, numbers, arrays, ranges, hashes, sets, and more. Regular expressions get attention, as do file and other I/O operations.Along the way, the reader is introduced to numerous tools included in the standard Ruby distribution--tools like the task manager Rake and the interactive Ruby console-based interpreter Irb--that facilitate Ruby development and make it an integrated and pleasant experience.The book encompasses advanced topics, like the design of Ruby's class and module system, and the use of Ruby threads, taking even the new Rubyist deep into the language and giving every reader the foundations necessary to use, explore, and enjoy this unusually popular and versatile language.It's no wonder one reader commented: "The technical depth is just right to not distract beginners, yet detailed enough for more advanced readers."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.

    But many organizations adopting these technologies have found that it only leads to a faster-growing sprawl of unmanageable systems. This is where infrastructure as code can help. With this practical guide, author Kief Morris of ThoughtWorks shows you how to effectively use principles, practices, and patterns pioneered through the DevOps movement to manage cloud age infrastructure.Ideal for system administrators, infrastructure engineers, team leads, and architects, this book demonstrates various tools, techniques, and patterns you can use to implement infrastructure as code. In three parts, you'll learn about the platforms and tooling involved in creating and configuring infrastructure elements, patterns for using these tools, and practices for making infrastructure as code work in your environment.Examine the pitfalls that organizations fall into when adopting the new generation of infrastructure technologiesUnderstand the capabilities and service models of dynamic infrastructure platformsLearn about tools that provide, provision, and configure core infrastructure resourcesExplore services and tools for managing a dynamic infrastructureLearn specific patterns and practices for provisioning servers, building server templates, and updating running servers

    You'll find the latest methodologies for the design of effective test cases, including information on psychological and economic principles, managerial aspects, test tools, high-order testing, code inspections, and debugging. Accessible, comprehensive, and always practical, this edition provides the key information you need to test successfully, whether a novice or a working programmer. Buy your copy today and end up with fewer bugs tomorrow.

    This is one of those cases. The UNIX System Administration Handbook is one of the few books we ever measured ourselves against." -From the Foreword by Tim O'Reilly, founder of O'Reilly Media "This book is fun and functional as a desktop reference. If you use UNIX and Linux systems, you need this book in your short-reach library. It covers a bit of the systems' history but doesn't bloviate. It's just straightfoward information delivered in colorful and memorable fashion." -Jason A. Nunnelley"This is a comprehensive guide to the care and feeding of UNIX and Linux systems. The authors present the facts along with seasoned advice and real-world examples. Their perspective on the variations among systems is valuable for anyone who runs a heterogeneous computing facility." -Pat Parseghian The twentieth anniversary edition of the world's best-selling UNIX system administration book has been made even better by adding coverage of the leading Linux distributions: Ubuntu, openSUSE, and RHEL. This book approaches system administration in a practical way and is an invaluable reference for both new administrators and experienced professionals. It details best practices for every facet of system administration, including storage management, network design and administration, email, web hosting, scripting, software configuration management, performance analysis, Windows interoperability, virtualization, DNS, security, management of IT service organizations, and much more. UNIX(R) and Linux(R) System Administration Handbook, Fourth Edition, reflects the current versions of these operating systems: Ubuntu(R) LinuxopenSUSE(R) LinuxRed Hat(R) Enterprise Linux(R)Oracle America(R) Solaris(TM) (formerly Sun Solaris)HP HP-UX(R)IBM AIX(R)

    

    You need to assume it will run in the most hostile environments imaginable -- and design, code, and test accordingly. Writing Secure Code, Second Edition shows you how. This edition draws on the lessons learned and taught throughout Microsoft during the firm s massive 2002 Windows Security Push. It s a huge upgrade to the respected First Edition, with new coverage across the board. Michael Howard and David LeBlanc first help you define what security means to your customers -- and implement a three-pronged strategy for securing design, defaults, and deployment. There s especially useful coverage of threat modeling -- decomposing your application, identifying threats, ranking them, and mitigating them. Then, it s on to in-depth coverage of today s key security issues from the developer s standpoint. Everyone knows buffer overruns are bad: Here s a full chapter on avoiding them. You ll learn how to establish appropriate access controls and default to running with least privilege. There s detailed coverage of overcoming attacks on cryptography (for example, avoiding poor random numbers and bit-flipping attacks). You ll learn countermeasures for virtually every form of user input attack, from malicious database updates to cross-site scripting. We ve just scratched the surface: There are authoritative techniques for securing sockets and RPC, protecting against DOS attacks, building safer .NET applications, reviewing and testing code, adding privacy features, and even writing high-quality security documentation. Following these techniques won t just improve security -- it ll dramatically improve robustness and reliability, too. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks For Dummies®, Second Edition.

    What makes an operating system modern? According to author Andrew Tanenbaum, it is the awareness of high-demand computer applications--primarily in the areas of multimedia, parallel and distributed computing, and security. The development of faster and more advanced hardware has driven progress in software, including enhancements to the operating system. It is one thing to run an old operating system on current hardware, and another to effectively leverage current hardware to best serve modern software applications. If you don't believe it, install Windows 3.0 on a modern PC and try surfing the Internet or burning a CD. Readers familiar with Tanenbaum's previous text, Operating Systems, know the author is a great proponent of simple design and hands-on experimentation. His earlier book came bundled with the source code for an operating system called Minux, a simple variant of Unix and the platform used by Linus Torvalds to develop Linux. Although this book does not come with any source code, he illustrates many of his points with code fragments (C, usually with Unix system calls). The first half of Modern Operating Systems focuses on traditional operating systems concepts: processes, deadlocks, memory management, I/O, and file systems. There is nothing groundbreaking in these early chapters, but all topics are well covered, each including sections on current research and a set of student problems. It is enlightening to read Tanenbaum's explanations of the design decisions made by past operating systems gurus, including his view that additional research on the problem of deadlocks is impractical except for "keeping otherwise unemployed graph theorists off the streets." It is the second half of the book that differentiates itself from older operating systems texts. Here, each chapter describes an element of what constitutes a modern operating system--awareness of multimedia applications, multiple processors, computer networks, and a high level of security. The chapter on multimedia functionality focuses on such features as handling massive files and providing video-on-demand. Included in the discussion on multiprocessor platforms are clustered computers and distributed computing. Finally, the importance of security is discussed--a lively enumeration of the scores of ways operating systems can be vulnerable to attack, from password security to computer viruses and Internet worms. Included at the end of the book are case studies of two popular operating systems: Unix/Linux and Windows 2000. There is a bias toward the Unix/Linux approach, not surprising given the author's experience and academic bent, but this bias does not detract from Tanenbaum's analysis. Both operating systems are dissected, describing how each implements processes, file systems, memory management, and other operating system fundamentals. Tanenbaum's mantra is simple, accessible operating system design. Given that modern operating systems have extensive features, he is forced to reconcile physical size with simplicity. Toward this end, he makes frequent references to the Frederick Brooks classic The Mythical Man-Month for wisdom on managing large, complex software development projects. He finds both Windows 2000 and Unix/Linux guilty of being too complicated--with a particular skewering of Windows 2000 and its "mammoth Win32 API." A primary culprit is the attempt to make operating systems more "user-friendly," which Tanenbaum views as an excuse for bloated code. The solution is to have smart people, the smallest possible team, and well-defined interactions between various operating systems components. Future operating system design will benefit if the advice in this book is taken to heart. --Pete Ostenson

    Abbott and Michael T. Fisher cover everything IT and business leaders must know to build technology infrastructures that can scale smoothly to meet any business requirement. Drawing on their unparalleled experience managing some of the world s highest-transaction-volume Web sites, the authors provide detailed models and best-practice approaches available in no other book. Unlike previous books on scalability, "The Art of Scalability" doesn t limit its coverage to technology. Writing for both technical and nontechnical decision-makers, this book covers everything that impacts scalability, including architecture, processes, people, and organizations. Throughout, the authors address a broad spectrum of real-world challenges, from performance testing to IT governance. Using their tools and guidance, organizations can systematically overcome obstacles to scalability and achieve unprecedented levels of technical and business performance. Coverage includes Staffing the scalable organization: essential organizational, management, and leadership skills for technical leaders Building processes for scale: process lessons from hyper-growth companies, from technical issue resolution to crisis management Making better build versus buy decisions Architecting scalable solutions: powerful proprietary models for identifying scalability needs and choosing the best approaches to meet them Optimizing performance through caching, application and database splitting, and asynchronous design Scalability techniques for emerging technologies, including clouds and grids Planning for rapid data growth and new data centers Evolving monitoring strategies to tightly align with customer requirements "

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates