With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    The Web is awash in Ruby code that is now virtually impossible to change or extend. This text helps you solve that problem by using powerful real-world object-oriented design techniques, which it thoroughly explains using simple and practical Ruby examples. Sandi Metz has distilled a lifetime of conversations and presentations about object-oriented design into a set of Ruby-focused practices for crafting manageable, extensible, and pleasing code. She shows you how to build new applications that can survive success and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples, all downloadable from the companion Web site, poodr.info. The first title to focus squarely on object-oriented Ruby application design, Practical Object-Oriented Design in Ruby will guide you to superior outcomes, whatever your previous Ruby experience. Novice Ruby programmers will find specific rules to live by; intermediate Ruby programmers will find valuable principles they can flexibly interpret and apply; and advanced Ruby programmers will find a common language they can use to lead development and guide their colleagues. This guide will help you Understand how object-oriented programming can help you craft Ruby code that is easier to maintain and upgrade Decide what belongs in a single Ruby class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Design cost-effective tests Solve common problems associated with poorly designed Ruby code

    It turns out that all the buzz is well earned. I think this is the best book currently available for learning Python. I would recommend Chun's book over Learning Python (O'Reilly), Programming Python (O'Reilly), or The Quick Python Book (Manning)." --David Mertz, Ph.D., IBM DeveloperWorks(R) "I have been doing a lot of research [on] Python for the past year and have seen a number of positive reviews of your book. The sentiment expressed confirms the opinion that Core Python Programming is now considered the standard introductory text." --Richard Ozaki, Lockheed Martin "Finally, a book good enough to be both a textbook and a reference on the Python language now exists." --Michael Baxter, Linux Journal "Very well written. It is the clearest, friendliest book I have come across yet for explaining Python, and putting it in a wider context. It does not presume a large amount of other experience. It does go into some important Python topics carefully and in depth. Unlike too many beginner books, it never condescends or tortures the reader with childish hide-and-seek prose games. [It] sticks to gaining a solid grasp of Python syntax and structure." --http: //python.org bookstore Web site "[If ] I could only own one Python book, it would be Core Python Programming by Wesley Chun. This book manages to cover more topics in more depth than Learning Python but includes it all in one book that also more than adequately covers the core language. [If] you are in the market for just one book about Python, I recommend this book. You will enjoy reading it, including its wry programmer's wit. More importantly, you will learn Python. Even more importantly, you will find it invaluable in helping you in your day-to-day Python programming life. Well done, Mr. Chun!" --Ron Stephens, Python Learning Foundation "I think the best language for beginners is Python, without a doubt. My favorite book is Core Python Programming." --s003apr, MP3Car.com Forums "Personally, I really like Python. It's simple to learn, completely intuitive, amazingly flexible, and pretty darned fast. Python has only just started to claim mindshare in the Windows world, but look for it to start gaining lots of support as people discover it. To learn Python, I'd start with Core Python Programming by Wesley Chun." --Bill Boswell, MCSE, Microsoft Certified Professional Magazine Online "If you learn well from books, I suggest Core Python Programming. It is by far the best I've found. I'm a Python newbie as well and in three months time I've been able to implement Python in projects at work (automating MSOffice, SQL DB stuff, etc.)." --ptonman, Dev Shed Forums "Python is simply a beautiful language. It's easy to learn, it's cross-platform, and it works. It has achieved many of the technical goals that Java strives for. A one-sentence description of Python would be: 'All other languages appear to have evolved over time--but Python was designed.' And it was designed well. Unfortunately, there aren't a large number of books for Python. The best one I've run across so far is Core Python Programming." --Chris Timmons, C. R. Timmons Consulting "If you like the Prentice Hall Core series, another good full-blown treatment to consider would be Core Python Programming. It addresses in elaborate concrete detail many practical topics that get little, if any, coverage in other books." --Mitchell L Model, MLM Consulting "Core Python Programming is an amazingly easy read! The liberal use of examples helps clarify some of the more subtle points of the language. And the comparisons to languages with which I'm already familiar (C/C++/Java) get you programming in record speed." --Michael Santos, Ph.D., Green Hills Software The Complete Developer's Guide to Python New to Python? The definitive guide to Python development for experienced programmersCovers core language features thoroughly, including those found in the latest Python releases--learn more than just the syntax!Learn advanced topics such as regular expressions, networking, multithreading, GUI, Web/CGI, and Python extensionsIncludes brand-new material on databases, Internet clients, Java/Jython, and Microsoft Office, plus Python 2.6 and 3Presents hundreds of code snippets, interactive examples, and practical exercises to strengthen your Python skills Python is an agile, robust, expressive, fully object-oriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. In Core Python Programming, Second Edition , leading Python developer and trainer Wesley Chun helps you learn Python quickly and comprehensively so that you can immediately succeed with any Python project. Using practical code examples, Chun introduces all the fundamentals of Python programming: syntax, objects and memory management, data types, operators, files and I/O, functions, generators, error handling and exceptions, loops, iterators, functional programming, object-oriented programming and more. After you learn the core fundamentals of Python, he shows you what you can do with your new skills, delving into advanced topics, such as regular expressions, networking programming with sockets, multithreading, GUI development, Web/CGI programming and extending Python in C. This edition reflects major enhancements in the Python 2.x series, including 2.6 and tips for migrating to 3. It contains new chapters on database and Internet client programming, plus coverage of many new topics, including new-style classes, Java and Jython, Microsoft Office (Win32 COM Client) programming, and much more. Learn professional Python style, best practices, and good programming habitsGain a deep understanding of Python's objects and memory model as well as its OOP features, including those found in Python's new-style classesBuild more effective Web, CGI, Internet, and network and other client/server applicationsLearn how to develop your own GUI applications using Tkinter and other toolkits available for PythonImprove the performance of your Python applications by writing extensions in C and other languages, or enhance I/O-bound applications by using multithreadingLearn about Python's database API and how to use a variety of database systems with Python, including MySQL, Postgres, and SQLiteFeatures appendices on Python 2.6 & 3, including tips on migrating to the next generation! Core Python Programming delivers Systematic, expert coverage of Python's core featuresPowerful insights for developing complex applicationsEasy-to-use tables and charts detailing Python modules, operators, functions, and methodsDozens of professional-quality code examples, from quick snippets to full-fledged applications

    Git permits virtually an infinite variety of methods for development and collaboration. Created by Linus Torvalds to manage development of the Linux kernel, it's become the principal tool for distributed version control. But Git's flexibility also means that some users don't understand how to use it to their best advantage. Version Control with Git offers tutorials on the most effective ways to use it, as well as friendly yet rigorous advice to help you navigate Git's many functions. With this book, you will:Learn how to use Git in several real-world development environments Gain insight into Git's common-use cases, initial tasks, and basic functions Understand how to use Git for both centralized and distributed version control Use Git to manage patches, diffs, merges, and conflicts Acquire advanced techniques such as rebasing, hooks, and ways to handle submodules (subprojects) Learn how to use Git with Subversion Git has earned the respect of developers around the world. Find out how you can benefit from this amazing tool with Version Control with Git.

    Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular expressions can be an outlet for creativity, for brilliant programming, and for the elegant solution. Regular Expression Pocket Reference offers an introduction to regular expressions, pattern matching, metacharacters, modes and constructs, and then provides separate sections for each of the language APIs, with complete regex listings including:Supported metacharacters for each language API Regular expression classes and interfaces for Ruby, Java, .NET, and C# Regular expression operators for Perl 5.8 Regular expression module objects and functions for Python Pattern-matching functions for PHP and the vi editor Pattern-matching methods and objects for JavaScript Unicode Support for each of the languages With plenty of examples and other resources, Regular Expression Pocket Reference summarizes the complex rules for performing this critical text-processing function, and presents this often-confusing topic in a friendly and well-organized format. This guide makes an ideal on-the-job companion.

    Create a tiny virtual environment, called a container, for your application that includes only its particular set of dependencies. The Docker engine accounts for, manages, and builds these containers through functionality provided by the host operating system. Software running inside containers share the Linux OS and other resources, such as libraries, making their footprints radically smaller, and the containerized applications are easy to install, manage, and remove. Developers can package their applications without worrying about environment-specific deployment concerns, and the operations team gets cleaner, more efficient systems across the board. Better still, Docker is free and open source.Docker in Action teaches readers how to create, deploy, and manage applications hosted in Docker containers. The book starts with a clear explanation of the Docker model of virtualization, comparing this approach to the traditional hypervisor model. Developers will learn how to package applications in containers, including specific techniques for testing and distributing applications via Docker Hub and other registries. Readers will learn how to take advantage of the Linux OS features that Docker uses to run programs securely, and how to manage shared resources. Using carefully-designed examples, the book teaches you how to orchestrate containers and applications from installation to removal. Along the way, you'll learn techniques for using Docker on systems ranging from your personal dev-and-test machine to full-scale cloud deployments.

    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

    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

    

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    This Fourth Edition not only keeps this tradition alive, it actually improves on it."--Steve Vinoski, Chief Engineer, Product Innovation, IONA Technologies" The Primer really brings this large and complex language down to size."--Justin Shaw, Senior Member of Technical Staff, Electronic Programs Division, The Aerospace Corporation"It not only gets novices up and running early, but gets them to do so using good programming practices."--Nevin ": -)" Liber, Senior Principal Engineer (C++ developer since 1988)This popular tutorial introduction to standard C++ has been completely updated, reorganized, and rewritten to help programmers learn the language faster and use it in a more modern, effective way.Just as C++ has evolved since the last edition, so has the authors' approach to teaching it. They now introduce the C++ standard library from the beginning, giving readers the means to write useful programs without first having to master every language detail. Highlighting today's best practices, they show how to write programs that are safe, can be built quickly, and yet offer outstanding performance. Examples that take advantage of the library, and explain the features of C++, also show how to make the best use of the language. As in its previous editions, the book's authoritative discussion of fundamental C++ concepts and techniques makes it a valuable resource even for more experienced programmers.Program Faster and More Effectively with This Rewritten ClassicRestructured for quicker learning, using the C++ standard libraryUpdated to teach the most current programming styles and program design techniquesFilled with new learning aids that emphasize important points, warn about common pitfalls, suggest good programming practices, and provide general usage tipsComplete with exercises that reinforce skills learnedAuthoritative and comprehensive in its coverage The source code for the book's extended examples is available on the Web at the address below.www.awprofessional.com/cpp_primer

    By the end of the book, you'll understand how to develop a large, maintainable, and performant application with AngularJS.Guided by two engineers who worked on AngularJS at Google, you'll learn the components needed to build data-driven applications, using declarative programming and the Model-view-controller pattern. You'll also learn how to conduct unit tests on each part of your application.Learn how to use controllers for moving data to and from viewsUnderstand when to use AngularJS services instead of controllersCommunicate with the server to store, fetch, and update data asynchronouslyKnow when to use AngularJS filters for converting data and values to different formatsImplement single-page applications, using ngRoute to select views and navigationDive into basic and advanced directives for creating reusable componentsWrite an end-to-end test on a live version of your entire applicationUse best practices, guidelines, and tools throughout the development cycle

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    Based on "Practical Python," this newly-revised book is both an introduction and practical reference for a swath of Python-related programming topics, including addressing language internals, database integration, network programming, and web services. Advanced topics, such as extending Python and packaging/distributing Python applications, are also covered.Ten different projects illustrate the concepts introduced in the book. You will learn how to create a P2P file-sharing application and a web-based bulletin board, and how to remotely edit web-based documents and create games. Author Magnus Lie Hetland is an authority on Python and previously authored "Practical Python." He also authored the popular online guide, Instant Python Hacking, on which both books are based.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.