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R Object-oriented Programming
by Kelly BlackThis book is designed for people with some experience in basic programming practices. It is also assumed that they have some basic experience using R and are familiar using the command line in an R environment. Our primary goal is to raise a beginner to a more advanced level to make him/her more comfortable creating programs and extending R to solve common problems.
R Packages
by Hadley WickhamTurn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham's package development philosophy. In the process, you'll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language.Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You'll learn to focus on what you want your package to do, rather than think about package structure.Learn about the most useful components of an R package, including vignettes and unit testsAutomate anything you can, taking advantage of the years of development experience embodied in devtoolsGet tips on good style, such as organizing functions into filesStreamline your development process with devtoolsLearn the best way to submit your package to the Comprehensive R Archive Network (CRAN)Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr
R Packages
by Hadley Wickham Jennifer BryanTurn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used by the team that maintains the "tidyverse" suite of packages. In the process, you'll learn how to automate common development tasks using a set of R packages, including devtools, usethis, testthat, and roxygen2.Authors Hadley Wickham and Jennifer Bryan from Posit (formerly known as RStudio) help you create packages quickly, then teach you how to get better over time. You'll be able to focus on what you want your package to do as you progressively develop greater mastery of the structure of a package.With this book, you will:Learn the key components of an R package, including code, documentation, and testsStreamline your development process with devtools and the RStudio IDEGet tips on effective habits such as organizing functions into filesGet caught up on important new features in the devtools ecosystemLearn about the art and science of unit testing, using features in the third edition of testthatTurn your existing documentation into a beautiful and user friendly website with pkgdownGain an appreciation of the benefits of modern code hosting platforms, such as GitHub
R Programming: Statistical Data Analysis in Research
by Samira Hosseini Kingsley OkoyeThis book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE). R is an open-source software with a development environment (RStudio) for computing statistics and graphical displays through data manipulation, modeling, and calculation. R packages and supported libraries provide a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical software, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system. Therefore, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the users. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and nonparametric procedures. This includes a description of the different conditions or assumptions that are necessary for performing the various statistical methods or tests, and how to understand the results of the methods. The book also covers the different data formats and sources, and how to test for the reliability and validity of the available datasets. Different research experiments, case scenarios, and examples are explained in this book. The book provides a comprehensive description and step-by-step practical hands-on guide to carrying out the different types of statistical analysis in R particularly for research purposes with examples. Ranging from how to import and store datasets in R as objects, how to code and call the methods or functions for manipulating the datasets or objects, factorization, and vectorization, to better reasoning, interpretation, and storage of the results for future use, and graphical visualizations and representations thus congruence of Statistics and Computer programming in Research.
R Programming By Example: Practical, hands-on projects to help you get started with R
by Omar Trejo Peter C. FigliozziKey Features Get a firm hold on the fundamentals of R through practical hands-on examples Get started with good R programming fundamentals for data science Exploit the different libraries of R to build interesting applications in R Book Description R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable. What you will learn Discover techniques to leverage R’s features, and work with packages Perform a descriptive analysis and work with statistical models using R Work efficiently with objects without using loops Create diverse visualizations to gain better understanding of the data Understand ways to produce good visualizations and create reports for the results Read and write data from relational databases and REST APIs, both packaged and unpackaged Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel
R Programming for Actuarial Science
by Peter McQuire Alfred KumeR Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth. Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles. An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic. Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.
R Programming Fundamentals: Deal with data using various modeling techniques
by Kaelen MedeirosStudy data analysis and visualization to successfully analyze data with RKey FeaturesGet to grips with data cleaning methodsExplore statistical concepts and programming in R, including best practicesBuild a data science project with real-world examplesBook DescriptionR Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you’ll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.Once you have grasped the basics, you’ll move on to studying data visualization and graphics. You’ll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you’ll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values.By the end of this book, you’ll have completed an entire data science project of your own for your portfolio or blog.What you will learnUse basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow controlImport data to R from various formats such as CSV, Excel, and SQLClean data by handling missing values and standardizing fieldsPerform univariate and bivariate analysis using ggplot2Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plotsApply data management techniques, such as factoring, pivoting, aggregating, merging, and dealing with missing values, on the example datasetsWho this book is forR Programming Fundamentals is for you if you are an analyst who wants to grow in the field of data science and explore the latest tools.
R Projects For Dummies
by Joseph SchmullerMake the most of R’s extensive toolset R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R’s graphics, interactive, and machine learning tools, you’ll learn to apply R’s extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too! R is a free tool, and it’s the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience. This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more. Appropriate for R users at all levels Helps R programmers plan and complete their own projects Focuses on R functions and packages Shows how to carry out complex analyses by just entering a few commands If you’re brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.
R Quick Syntax Reference
by Margot TollefsonTheR Quick Syntax Referenceis a handy reference book detailing the intricacies of the R language. Not only is R a free, open-source tool, R is powerful, flexible, and has state of the art statistical techniques available. With the many details which must be correct when using any language, however, the R Quick Syntax Reference makes using R easier. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. With a copy of the R Quick Syntax Reference in hand, you will find that are able to use the multitude of functions availableto the R user and are even able to write your own functions to explore and analyze data. Takes you through learning R, from download to statistical analysis. Clears the confusion around object types and how to use and convert the types. Tells you how to search for statistical techniques using the R help pages. What you'll learn Download R and R packages for your platform. Work with R within your file structure. Enter data from the keyboard and from external files. Determine and assign modes, classes, and types of objects Do calculations using the computational tools in R. Use R functions and create new functions. Who this book is for TheR Quick Syntax Referenceis for statisticians and other data analysts who are starting to use the R language. It is also for veteran R users who want a quick reference to the language. The book is an excellent choice for the busy data scientist who likes to experiment with new ways of analysis and who needs the flexibility of the data editing available in R. Table of Contents Downloading R and Setting R Up in a File SystemThe R PromptAssignments and OperatorsModes of ObjectsThe Classes and TypesPackaged FunctionsUser Defined FunctionsHow to Use a Function Inputting or Creating Data Outputting Data and Output Manipulating Objects Flow Conditioners Condition Based Functions Some Examples of Conditioning Some Common Functions The Packages base, stats, and graphics Tricks of the Trade"
R Quick Syntax Reference: A Pocket Guide to the Language, APIs and Library
by Margot TollefsonThis handy reference book detailing the intricacies of R updates the popular first edition by adding R version 3.4 and 3.5 features. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings, and an example using the Twitter API.With a copy of the R Quick Syntax Reference in hand, you will find that you are able to use the multitude of functions available in R and are even able to write your own functions to explore and analyze data.What You Will LearnDiscover the modes and classes of R objects and how to use themUse both packaged and user-created functions in R Import/export data and create new data objects in RCreate descriptive functions and manipulate objects in RTake advantage of flow control and conditional statementsWork with packages such as base, stats, and graphicsWho This Book Is ForThose with programming experience, either new to R, or those with at least some exposure to R but who are new to the latest version.
R Recipes
by Larry A. PaceR Recipes is your handy problem-solution reference for learning and using the popular R programming language for statistics and other numerical analysis. Packed with hundreds of code and visual recipes, this book helps you to quickly learn the fundamentals and explore the frontiers of programming, analyzing and using R. R Recipes provides textual and visual recipes for easy and productive templates for use and re-use in your day-to-day R programming and data analysis practice. Whether you're in finance, cloud computing, big or small data analytics, or other applied computational and data science - R Recipes should be a staple for your code reference library.
The R Software
by Pierre Lafaye de Micheaux Rémy Drouilhet Benoit LiquetThe contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.
R Statistical Application Development by Example Beginner's Guide
by Prabhanjan Narayanachar TattarFull of screenshots and examples, this Beginner's Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.
R Statistics Cookbook: Over 100 recipes for performing complex statistical operations with R 3.5
by Francisco JuretigSolve real-world statistical problems using the most popular R packages and techniques Key Features Learn how to apply statistical methods to your everyday research with handy recipes Foster your analytical skills and interpret research across industries and business verticals Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques Book Description R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools. You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making. By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry. What you will learn Become well versed with recipes that will help you interpret plots with R Formulate advanced statistical models in R to understand its concepts Perform Bayesian regression to predict models and input missing data Use time series analysis for modelling and forecasting temporal data Implement a range of regression techniques for efficient data modelling Get to grips with robust statistics and hidden Markov models Explore ANOVA (Analysis of Variance) and perform hypothesis testing Who this book is for If you are a quantitative researcher, statistician, data analyst, or data scientist looking to tackle various challenges in statistics, this book is what you need! Proficiency in R programming and basic knowledge of linear algebra is necessary to follow along the recipes covered in this book.
R Visualizations: Derive Meaning from Data
by David GerbingR Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate any of the basic visualizations with the R visualization systems. Further, this book introduces the author’s lessR system, which always can accomplish a visualization with less coding than the use of other systems, sometimes dramatically so, and also provides accompanying statistical analyses. Key Features Presents thorough coverage of the leading R visualization system, ggplot2. Gives specific guidance on using base R graphics to attain visualizations of the same quality as those provided by ggplot2. Shows how to create a wide range of data visualizations: distributions of categorical and continuous variables, many types of scatterplots including with a third variable, time series, and maps. Inclusion of the various approaches to R graphics organized by topic instead of by system. Presents the recent work on interactive visualization in R. David W. Gerbing received his PhD from Michigan State University in 1979 in quantitative analysis, and currently is a professor of quantitative analysis in the School of Business at Portland State University. He has published extensively in the social and behavioral sciences with a focus on quantitative methods. His lessR package has been in development since 2009.
R Web Scraping Quick Start Guide: Techniques and tools to crawl and scrape data from websites
by Olgun AydinWeb Scraping techniques are getting more popular, since data is as valuable as oil in 21st century. Through this book get some key knowledge about using XPath, regEX; web scraping libraries for R like rvest and RSelenium technologies. Key FeaturesTechniques, tools and frameworks for web scraping with RScrape data effortlessly from a variety of websites Learn how to selectively choose the data to scrape, and build your datasetBook DescriptionWeb scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming.You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R.What you will learnWrite and create regEX rulesWrite XPath rules to query your dataLearn how web scraping methods workUse rvest to crawl web pagesStore data retrieved from the webLearn the key uses of Rselenium to scrape dataWho this book is forThis book is for R programmers who want to get started quickly with web scraping, as well as data analysts who want to learn scraping using R. Basic knowledge of R is all you need to get started with this book.
R2DBC Revealed: Reactive Relational Database Connectivity for Java and JVM Programmers
by Robert HedgpethUnderstand the newest trend in database programming for developers working in Java, Kotlin, Clojure, and other JVM-based languages. This book introduces Reactive Relational Database Connectivity (R2DBC), a modern way of connecting to and querying relational databases from Java and other JVM languages. The book begins by helping you understand not only what reactive programming is, but why it is necessary. Then building on those fundamentals, the book takes you into the world of databases and the newly released Reactive Relational Database Connectivity (R2DBC) specification. Examples in the book are worked using the freely available MariaDB database along with MariaDB’s vendor-implementation of the R2DBC service-provider interface (SPI). Following along with the examples and the provided example code helps prepare you to work with any of the growing number of R2DBC implementations for popular enterprise databases such as Oracle Database and SQL Server. You’ll be well prepared for what is becoming the future of database access from Java and other languages built on the JVM.What You Will LearnUnderstand why R2DBC was created and how it utilizes the Reactive Streams API Understand the components of the R2DBC service-provider interfaceCreate and manage reactive database connections and connection pools using an R2DBC clientProgrammatically execute queries on a relational database using an R2DBC clientEffectively utilize transactions using an R2DBC clientBuild relational database-driven applications that are event-driven and non-blockingWho This Book Is ForSoftware developers building solutions using JVM languages and the JVM ecosystem, and developers who need an introduction to the R2DBC specification and reactive programming with relational databases and want to understand what Reactive Relational Database Connectivity is and why it came about. This book includes practical examples of using the R2DBC specification with Java and MariaDB that will provide developers with the knowledge they need to create their own solutions.
R3 Corda for Architects and Developers: With Case Studies in Finance, Insurance, Healthcare, Travel, Telecom, and Agriculture
by Debajani MohantyExplore the entire R3 Corda ecosystem using theory, labs, and use cases. This book introduces distributed ledger technology, Corda architecture, and smart contract programming in Java, guiding you through testing and deployment. Further, you will explore various business problems in finance, insurance, healthcare, travel, and agriculture and discover how Corda can solve these issues through its unique and efficient distributed ledger technology. These business scenarios come with flowcharts, diagrams, and sample code that stakeholders can refer to and further enhance during live projects. After reading R3 Corda for Architects and Developers, you will understand how efficient usage of Corda can create value for your business processes by making business intelligence more readily available, user friendly, and interactive. What You Will Learn Work with distributed ledger technologyDiscover Corda’s differentiators Develop smart contracts, states, and business flows on Corda Take advantage of Corda in your business by going through case studies in various domains Who This Book Is For Blockchain developers and architects who wish to learn Corda.
R3 in Geomatics: First International Workshop in memory of Prof. Raffaele Santamaria on R3 in Geomatics: Research, Results and Review, R3GEO 2019, Naples, Italy, October 10–11, 2019, Revised Selected Papers (Communications in Computer and Information Science #1246)
by Claudio Parente Salvatore Troisi Antonio VettoreThis book constitutes the refereed proceedings of the First International Workshop in memory of Prof. Raffaele Santamaria on R3 in Geomatics: Research, Results and Review, R3GEO 2019, held in Naples, Italy*, in October 2019.The 27 full papers along with the 2 short papers presented were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on: GNSS and geodesy; photogrammetry and laser scanning; GIS and remote sensing.
RabbitMQ Cookbook
by Sigismondo Boschi Gabriele SantomaggioA practical book filled with advanced recipes as well as plenty of code and real-life examples which will make your learning curve quick and easy.If you are a software developer who wants to develop distributed applications based on messaging, then this book is for you. It's assumed that you have some experience with multithreading applications and distributed applications. You are also expected to know the basic concepts of Web and cloud applications in order to follow the recipes effectively.
RabbitMQ Essentials
by David DossotThis book is a quick and concise introduction to RabbitMQ. Follow the unique case study of Clever Coney Media as they progressively discover how to fully utilize RabbitMQ, containing clever examples and detailed explanations. Whether you are someone who develops enterprise messaging products professionally or a hobbyist who is already familiar with open source Message Queuing software and you are looking for a new challenge, then this is the book for you. Although you should be familiar with Java, Ruby, and Python to get the most out of the examples, RabbitMQ Essentials will give you the push you need to get started that no other RabbitMQ tutorial can provide you with.
RabbitMQ Essentials - Second Edition: Build distributed and scalable applications with message queuing using RabbitMQ, 2nd Edition
by David Dossot Lovisa JohanssonWhether you are someone who develops enterprise messaging products professionally or a hobbyist familiar with open source message queuing software and looking for a new challenge, RabbitMQ Essentials is for you. This book will give you the push you need to get started with creating new and exciting applications or migrating existing monoliths to a microservice architecture.
RabbitMQ in Action: Distributed Messaging for Everyone
by Jason WilliamsSummaryRabbitMQ in Action is a fast-paced run through building and managing scalable applications using the RabbitMQ messaging server. It starts by explaining how message queuing works, its history, and how RabbitMQ fits in. Then it shows you real-world examples you can apply to your own scalability and interoperability challenges.About the TechnologyThere's a virtual switchboard at the core of most large applications where messages race between servers, programs, and services. RabbitMQ is an efficient and easy-to-deploy queue that handles this message traffic effortlessly in all situations, from web startups to massive enterprise systems.About the BookRabbitMQ in Action teaches you to build and manage scalable applications in multiple languages using the RabbitMQ messaging server. It's a snap to get started. You'll learn how message queuing works and how RabbitMQ fits in. Then, you'll explore practical scalability and interoperability issues through many examples. By the end, you'll know how to make Rabbit run like a well-oiled machine in a 24 x 7 x 365 environment.Written for developers familiar with Python, PHP, Java, .NET, or any other modern programming language. No RabbitMQ experience required. 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. What's InsideLearn fundamental messaging design patternsUse patterns for on-demand scalabilityGlue a PHP frontend to a backend written in anythingImplement a PubSub-alerting service in 30 minutes flatConfigure RabbitMQ's built-in clusteringMonitor, manage, extend, and tune RabbitMQ============================================Table of ContentsPulling RabbitMQ out of the hatUnderstanding messagingRunning and administering RabbitSolving problems with Rabbit: coding and patternsClustering and dealing with failureWriting code that survives failureWarrens and Shovels: failover and replicationAdministering RabbitMQ from the WebControlling Rabbit with the REST APIMonitoring: Houston, we have a problemSupercharging and securing your Rabbit Smart Rabbits: extending RabbitMQ
RabbitMQ in Depth
by Gavin M. RoySummaryRabbitMQ in Depth is a practical guide to building and maintaining message-based applications. This book provides detailed coverage of RabbitMQ with an emphasis on why it works the way it does.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyAt the heart of most modern distributed applications is a queue that buffers, prioritizes, and routes message traffic. RabbitMQ is a high-performance message broker based on the Advanced Message Queueing Protocol. It?s battle tested, ultrafast, and powerful enough to handle anything you can throw at it. It requires a few simple setup steps, and you can instantly start using it to manage low-level service communication, application integration, and distributed system message routing.About the BookRabbitMQ in Depth is a practical guide to building and maintaining message-based applications. This book provides detailed coverage of RabbitMQ with an emphasis on why it works the way it does. You'll find examples and detailed explanations based in real-world systems ranging from simple networked services to complex distributed designs. You'll also find the insights you need to make core architectural choices and develop procedures for effective operational management. What's InsideAMQP, the Advanced Message Queueing ProtocolCommunicating via MQTT, Stomp, and HTTPValuable troubleshooting techniquesDatabase integrationAbout the ReaderWritten for programmers with a basic understanding of messaging-oriented systems.About the AuthorGavin M. Roy is an active, open source evangelist and advocate who has been working with internet and enterprise technologies since the mid-90s. Technical editor James Titcumb is a freelance developer, trainer, speaker, and active contributor to open source projects.Table of ContentsPART 1 - RABBITMQ AND APPLICATION ARCHITECTUREFoundational RabbitMQ How to speak Rabbit: the AMQ Protocol An in-depth tour of message properties Performance trade-offs in publishing Don't get messages; consume them Message patterns via exchange routing PART 2 - MANAGING RABBITMQ IN THE DATA CENTER OR THE CLOUDScaling RabbitMQ with clusters Cross-cluster message distribution PART 3 - INTEGRATIONS AND CUSTOMIZATIONUsing alternative protocols Database integrations
Race, Culture and the Video Game Industry: A Vicious Circuit
by Sam SrauyA detailed and much needed examination of how systemic racism in the US shaped the culture, market logic, and production practices of video game developers from the 1970s until the 2010s. Offering historical analysis of the video game industries (console, PC, and indie) from a critical, political economic lens, this book specifically examines the history of how such practices created, enabled, and maintained racism through the imagined ‘gamer.’ The book explores how the cultural and economic landscape of the United States developed from the 1970s through the 2000s and explains how racist attitudes are reflected and maintained in the practices of video games production. These practices constitute a 'Vicious Circuit' that normalizes racism and the centrality of an imagined gamer identity. It also explores how the industry, from indie game developers to larger profit-driven companies, responded to changing attitudes in the 2010s, where racism and lack of diversity in games was frequently being noted. The book concludes by offering potential solutions to combat this ‘Vicious Circuit’.A vital contribution to the study of video games that will be welcomed by students and scholars in the fields of media studies, cultural studies, game studies, critical race studies, and beyond.