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Gain a deep understanding of concurrency and learn how to leverage concurrent algorithms to build high-throughput data processing applications, network servers and clients that scale. Key Features Learn about the Go concurrency primitives, Go memory model, and common concurrency patternsDevelop the insights on how to model solutions to real-life problems using concurrencyExplore practical techniques to analyze how concurrent programs behave Book Description The Go language has been gaining momentum due to its treatment of concurrency as a core language feature, making concurrent programming more accessible than ever. However, concurrency is still an inherently difficult skill to master, since it requires the development of the right mindset to decompose problems into concurrent components correctly. This book will guide you in deepening your understanding of concurrency and show you how to make the most of its advantages. You’ll start by learning what guarantees are offered by the language when running concurrent programs. Through multiple examples, you will see how to use this information to develop concurrent algorithms that run without data races and complete successfully. You’ll also find out all you need to know about multiple common concurrency patterns, such as worker pools, asynchronous pipelines, fan-in/fan-out, scheduling periodic or future tasks, and error and panic handling in goroutines. The central theme of this book is to give you, the developer, an understanding of why concurrent programs behave the way they do, and how they can be used to build correct programs that work the same way in all platforms. By the time you finish the final chapter, you’ll be able to develop, analyze, and troubleshoot concurrent algorithms written in Go. What you will learn Understand basic concurrency concepts and problemsLearn about Go concurrency primitives and how they workLearn about the Go memory model and why it is importantUnderstand how to use common concurrency patternsSee how you can deal with errors in a concurrent programDiscover useful techniques for troubleshooting Who this book is for If you are a developer with basic knowledge of Go and are looking to gain expertise in highly concurrent backend application development, then this book is for you. Intermediate Go developers who want to make their backend systems more robust and scalable will also find plenty of useful information. Prior exposure Go is a prerequisite.

Get to grips with modern software demands by learning the effective uses of Rust's powerful memory safety.About This Book• Learn and improve the sequential performance characteristics of your software• Understand the use of operating system processes in a high-scale concurrent system• Learn of the various coordination methods available in the Standard libraryWho This Book Is ForThis book is aimed at software engineers with a basic understanding of Rust who want to exploit the parallel and concurrent nature of modern computing environments, safely.What You Will Learn• Probe your programs for performance and accuracy issues• Create your own threading and multi-processing environment in Rust• Use coarse locks from Rust's Standard library• Solve common synchronization problems or avoid synchronization using atomic programming• Build lock-free/wait-free structures in Rust and understand their implementations in the crates ecosystem• Leverage Rust's memory model and type system to build safety properties into your parallel programs• Understand the new features of the Rust programming language to ease the writing of parallel programsIn DetailMost programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more.The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems.By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust.Style and approachReaders will be taken through various ways to improve the performance of their Rust code.

Gain a deep understanding of concurrency and learn how to leverage concurrent algorithms to build high-throughput data processing applications, network servers and clients that scale.Key FeaturesLearn about the Go concurrency primitives, Go memory model, and common concurrency patternsDevelop the insights on how to model solutions to real-life problems using concurrencyExplore practical techniques to analyze how concurrent programs behaveBook DescriptionThe Go language has been gaining momentum due to its treatment of concurrency as a core language feature, making concurrent programming more accessible than ever. However, concurrency is still an inherently difficult skill to master, since it requires the development of the right mindset to decompose problems into concurrent components correctly. This book will guide you in deepening your understanding of concurrency and show you how to make the most of its advantages. You'll start by learning what guarantees are offered by the language when running concurrent programs. Through multiple examples, you will see how to use this information to develop concurrent algorithms that run without data races and complete successfully. You'll also find out all you need to know about multiple common concurrency patterns, such as worker pools, asynchronous pipelines, fan-in/fan-out, scheduling periodic or future tasks, and error and panic handling in goroutines. The central theme of this book is to give you, the developer, an understanding of why concurrent programs behave the way they do, and how they can be used to build correct programs that work the same way in all platforms. By the time you finish the final chapter, you'll be able to develop, analyze, and troubleshoot concurrent algorithms written in Go.What you will learnUnderstand basic concurrency concepts and problemsLearn about Go concurrency primitives and how they workLearn about the Go memory model and why it is importantUnderstand how to use common concurrency patternsSee how you can deal with errors in a concurrent programDiscover useful techniques for troubleshootingWho this book is forIf you are a developer with basic knowledge of Go and are looking to gain expertise in highly concurrent backend application development, then this book is for you. Intermediate Go developers who want to make their backend systems more robust and scalable will also find plenty of useful information. Prior exposure Go is a prerequisite.

This book is your comprehensive guide to mastering concurrency and performance in Rust. It walks you through the foundational concepts of Rust and modern machine architectures, leading to advanced techniques for managing memory safety and concurrency efficiently. By the time you finish, you'll confidently design safe and high-performance parallel applications with Rust.What this Book will help me doUnderstand and optimize the performance of Rust programs on modern hardware.Implement robust concurrent systems using Rust's type system and memory model.Master threading and synchronization mechanisms within the Rust standard library.Build advanced lock-free and wait-free data structures for specific computational needs.Integrate Rust with other programming languages through FFI for versatile applications.Author(s)Brian L. Troutwine is a software engineer specializing in systems programming and high-performance architecture. With years of experience using Rust, he brings practical insights into the inner workings of concurrency and memory safety. His writing style is detailed and approachable, aimed at fostering a better understanding among learners.Who is it for?This book is perfect for software engineers already familiar with the basics of Rust who are looking to deepen their skills in concurrency and high-performance programming. It caters to those aiming to build efficient and safe parallel systems. Readers interested in leveraging Rust for advanced system-level tasks will find this book particularly beneficial.

PurposeThis paper investigates the moderating role of multitasking computer self-efficacy on the relationship between social media affordances and social media overload as well as its moderation between social media overload and social media fatigue.Design/methodology/approachThe authors hypothesize that social media affordances will have a positive impact on social media overload (i.e. information and communication overload). They also hypothesize that social media overload will affect social media fatigue. In addition, they hypothesize that multitasking computer self-efficacy will attenuate the effect of social media affordances on both information overload and communication overload. Similarly, they also hypothesize that multitasking computer self-efficacy will attenuate the effects of both information overload and communication overload on fatigue. The authors test this model by collecting two-wave data from 220 professionals using PLS techniques.FindingsSocial media affordances have significant impacts on information overload, but not on communication overload. In turn, information overload and communication overload significantly affect social media fatigue. Multitasking computer self-efficacy was found to attenuate the effect of social media affordances on both information overload and communication overload. Furthermore, the study results suggest that multitasking computer self-efficacy attenuates the effect of information overload and reinforces the effect of communication overload on social media fatigue.Originality/valueMost prior literature focused on students rather than on professionals. There is a lack of research that investigates how the affordances of social media relate to social media overload and fatigue. Furthermore, research that investigates mitigating mechanisms of social media fatigue has been rare. This paper fills these important research gaps.

Asynchronous Python Programming using asyncio and async/await lets you write code that runs many processes concurrently. It makes your code more responsive and stops it from wasting time waiting for slow file and internet access. It is simpler to write, easier to reason about, and uses less memory than threads and processes. We start the video with an overview of asyncio, showing the building blocks and core syntax in a few simple examples. Next, you will see how to make normal Python code work in an asynchronous environment, to minimize blocking and facilitate cooperative multi-tasking. Further, we cover an asyncio use-case working with network connections such as web servers using asynio's streams API, followed by communication between coroutines and synchronization of coroutines. We will also look at using the asyncio library to easily wrap blocking code into threads and processes, and some non-blocking replacement libraries used with asyncio such as aiohttp and aiofiles. The uvloop and unsync libraries will be discussed as ways to speed up and simplify your asyncio code. The following section covers writing more robust asyncio code to test and debug your code, handle stuck tasks using time out, logging and error handling and task management.