It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    An effective testing strategy will deliver new functionality more aggressively, accelerate user feedback, and improve quality. However, for many developers, creating effective automated tests is a unique and unfamiliar challenge. xUnit Test Patterns is the definitive guide to writing automated tests using xUnit, the most popular unit testing framework in use today. Agile coach and test automation expert Gerard Meszaros describes 68 proven patterns for making tests easier to write, understand, and maintain. He then shows you how to make them more robust and repeatable--and far more cost-effective. Loaded with information, this book feels like three books in one. The first part is a detailed tutorial on test automation that covers everything from test strategy to in-depth test coding. The second part, a catalog of 18 frequently encountered "test smells," provides trouble-shooting guidelines to help you determine the root cause of problems and the most applicable patterns. The third part contains detailed descriptions of each pattern, including refactoring instructions illustrated by extensive code samples in multiple programming languages. Topics covered includeWriting better tests--and writing them faster The four phases of automated tests: fixture setup, exercising the system under test, result verification, and fixture teardown Improving test coverage by isolating software from its environment using Test Stubs and Mock Objects Designing software for greater testability Using test "smells" (including code smells, behavior smells, and project smells) to spot problems and know when and how to eliminate them Refactoring tests for greater simplicity, robustness, and execution speed This book will benefit developers, managers, and testers working with any agile or conventional development process, whether doing test-driven development or writing the tests last. While the patterns and smells are especially applicable to all members of the xUnit family, they also apply to next-generation behavior-driven development frameworks such as RSpec and JBehave and to other kinds of test automation tools, including recorded test tools and data-driven test tools such as Fit and FitNesse.Visual Summary of the Pattern Language Foreword Preface Acknowledgments Introduction Refactoring a Test PART I: The Narratives Chapter 1 A Brief Tour Chapter 2 Test Smells Chapter 3 Goals of Test Automation Chapter 4 Philosophy of Test Automation Chapter 5 Principles of Test Automation Chapter 6 Test Automation Strategy Chapter 7 xUnit Basics Chapter 8 Transient Fixture Management Chapter 9 Persistent Fixture Management Chapter 10 Result Verification Chapter 11 Using Test Doubles Chapter 12 Organizing Our Tests Chapter 13 Testing with Databases Chapter 14 A Roadmap to Effective Test Automation PART II: The Test Smells Chapter 15 Code Smells Chapter 16 Behavior Smells Chapter 17 Project Smells PART III: The Patterns Chapter 18 Test Strategy Patterns Chapter 19 xUnit Basics Patterns Chapter 20 Fixture Setup Patterns Chapter 21 Result Verification Patterns Chapter 22 Fixture Teardown Patterns Chapter 23 Test Double Patterns Chapter 24 Test Organization Patterns Chapter 25 Database Patterns Chapter 26 Design-for-Testability Patterns Chapter 27 Value Patterns PART IV: Appendixes Appendix A Test Refactorings Appendix B xUnit Terminology Appendix C xUnit Family Members Appendix D Tools Appendix E Goals and Principles Appendix F Smells, Aliases, and Causes Appendix G Patterns, Aliases, and Variations Glossary References Index "

    Rust's modern, flexible types ensure your program is free of null pointer dereferences, double frees, dangling pointers, and similar bugs, all at compile time, without runtime overhead. In multi-threaded code, Rust catches data races at compile time, making concurrency much easier to use.Written by two experienced systems programmers, this book explains how Rust manages to bridge the gap between performance and safety, and how you can take advantage of it. Topics include:How Rust represents values in memory (with diagrams)Complete explanations of ownership, moves, borrows, and lifetimesCargo, rustdoc, unit tests, and how to publish your code on crates.io, Rust's public package repositoryHigh-level features like generic code, closures, collections, and iterators that make Rust productive and flexibleConcurrency in Rust: threads, mutexes, channels, and atomics, all much safer to use than in C or C++Unsafe code, and how to preserve the integrity of ordinary code that uses itExtended examples illustrating how pieces of the language fit together

    Topics covered include:Basic version control commands and conceptsIntroduction to Distributed Version Control Systems (DVCS)Advanced branching workflowsStrengths and weaknesses of DVCS vs. centralized toolsBest practicesHow distributed version control works under the hoodFeaturing these open source version control tools:Apache SubversionMercurialGitVeracity

    How can software developers, programmers and managers meet the challenges of the 90s and begin to resolve the software crisis?

    Swift builds on the best of C and Objective-C, without the constraints of C compatibility. Swift adopts safe programming patterns and adds modern features to make programming easier, more flexible, and more fun. Swift’s clean slate, backed by the mature and much-loved Cocoa and Cocoa Touch frameworks, is an opportunity to reimagine how software development works.

    To grow professionally, you also need soft skills and effective learning techniques. Honing those skills is what this book is all about. Authors Dave Hoover and Adewale Oshineye have cataloged dozens of behavior patterns to help you perfect essential aspects of your craft. Compiled from years of research, many interviews, and feedback from O'Reilly's online forum, these patterns address difficult situations that programmers, administrators, and DBAs face every day. And it's not just about financial success. Apprenticeship Patterns also approaches software development as a means to personal fulfillment. Discover how this book can help you make the best of both your life and your career. Solutions to some common obstacles that this book explores in-depth include:Burned out at work? "Nurture Your Passion" by finding a pet project to rediscover the joy of problem solving.Feeling overwhelmed by new information? Re-explore familiar territory by building something you've built before, then use "Retreat into Competence" to move forward again.Stuck in your learning? Seek a team of experienced and talented developers with whom you can "Be the Worst" for a while. "Brilliant stuff! Reading this book was like being in a time machine that pulled me back to those key learning moments in my career as a professional software developer and, instead of having to learn best practices the hard way, I had a guru sitting on my shoulder guiding me every step towards master craftsmanship. I'll certainly be recommending this book to clients. I wish I had this book 14 years ago!" -Russ Miles, CEO, OpenCredo

    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.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    With the 97 short and extremely useful tips for programmers in this book, you'll expand your skills by adopting new approaches to old problems, learning appropriate best practices, and honing your craft through sound advice.With contributions from some of the most experienced and respected practitioners in the industry--including Michael Feathers, Pete Goodliffe, Diomidis Spinellis, Cay Horstmann, Verity Stob, and many more--this book contains practical knowledge and principles that you can apply to all kinds of projects.A few of the 97 things you should know:"Code in the Language of the Domain" by Dan North"Write Tests for People" by Gerard Meszaros"Convenience Is Not an -ility" by Gregor Hohpe"Know Your IDE" by Heinz Kabutz"A Message to the Future" by Linda Rising"The Boy Scout Rule" by Robert C. Martin (Uncle Bob)"Beware the Share" by Udi Dahan

    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. "

    The key, as the authors show, is to integrate regularly and often using continuous integration (CI) practices and techniques. The authors first examine the concept of CI and its practices from the ground up and then move on to explore other effective processes performed by CI systems, such as database integration, testing, inspection, deployment, and feedback. Through more than forty CI-related practices using application examples in different languages, readers learn that CI leads to more rapid software development, produces deployable software at every step in the development lifecycle, and reduces the time between defect introduction and detection, saving time and lowering costs. With successful implementation of CI, developers reduce risks and repetitive manual processes, and teams receive better project visibility. The book covers How to make integration a "non-event" on your software development projects How to reduce the amount of repetitive processes you perform when building your software Practices and techniques for using CI effectively with your teams Reducing the risks of late defect discovery, low-quality software, lack of visibility, and lack of deployable software Assessments of different CI servers and related tools on the market The book's companion Web site, www.integratebutton.com, provides updates and code examples

    Tracy Kidder got a preview of this world in the late 1970s when he observed the engineers of Data General design and build a new 32-bit minicomputer in just one year. His thoughtful, prescient book, The Soul of a New Machine, tells stories of 35-year-old "veteran" engineers hiring recent college graduates and encouraging them to work harder and faster on complex and difficult projects, exploiting the youngsters' ignorance of normal scheduling processes while engendering a new kind of work ethic.These days, we are used to the "total commitment" philosophy of managing technical creation, but Kidder was surprised and even a little alarmed at the obsessions and compulsions he found. From in-house political struggles to workers being permitted to tease management to marathon 24-hour work sessions, The Soul of a New Machine explores concepts that already seem familiar, even old-hat, less than 20 years later. Kidder plainly admires his subjects; while he admits to hopeless confusion about their work, he finds their dedication heroic. The reader wonders, though, what will become of it all, now and in the future. —Rob Lightner

    We'll introduce you to various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years.This book is great for:Beginners who have just finished the Django tutorial.Developers with intermediate knowledge of Django who want to improve their Django projects.

    These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.