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System Programming Essentials with Go

System Programming Essentials with Go

By : Alex Rios
5 (5)
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System Programming Essentials with Go

System Programming Essentials with Go

5 (5)
By: Alex Rios

Overview of this book

Alex Rios, a seasoned Go developer and active community builder, shares his 15 years of expertise in designing large-scale systems through this book. It masterfully cuts through complexity, enabling you to build efficient and secure applications with Go's streamlined syntax and powerful concurrency features. In this book, you’ll learn how Go, unlike traditional system programming languages (C/C++), lets you focus on the problem by prioritizing readability and elevating developer experience with features like automatic garbage collection and built-in concurrency primitives, which remove the burden of low-level memory management and intricate synchronization. Through hands-on projects, you'll master core concepts like file I/O, process management, and inter-process communication to automate tasks and interact with your system efficiently. You'll delve into network programming in Go, equipping yourself with the skills to build robust, distributed applications. This book goes beyond the basics by exploring modern practices like logging and tracing for comprehensive application monitoring, and advance to distributed system design using Go to prepare you to tackle complex architectures. By the end of this book, you'll emerge as a confident Go system programmer, ready to craft high-performance, secure applications for the modern world.
Table of Contents (24 chapters)
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1
Part 1: Introduction
4
Part 2: Interaction with the OS
10
Part 3: Performance
13
Part 4: Connected Apps
17
Part 5: Going Beyond

Best practices – guidelines for using pipes

Having explored practical aspects of using pipes in IPC, discussing best practices and guidelines is crucial. Adhering to these principles ensures that your implementation is efficient but also secure and maintainable.

Efficient data handling

In the context of efficient data handling, especially when minimizing data in transit, two key strategies are employed: chunking and compression.

Chunking involves breaking down large datasets into smaller, more manageable pieces. The primary advantage of chunking is that it prevents the overfilling of pipe buffers, which can lead to bottlenecks in data transmission. By segmenting the data, each chunk can be processed and transmitted sequentially, ensuring a smoother and more efficient flow of data. This technique is particularly useful in scenarios where data is streamed or processed in real time.

Example – Chunking data

In this snippet, the idea is the writer sends data...

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