Book Image

.Go Programming Blueprints - Second Edition

By : Mat Ryer
Book Image

.Go Programming Blueprints - Second Edition

By: Mat Ryer

Overview of this book

Go is the language of the Internet age, and the latest version of Go comes with major architectural changes. Implementation of the language, runtime, and libraries has changed significantly. The compiler and runtime are now written entirely in Go. The garbage collector is now concurrent and provides dramatically lower pause times by running in parallel with other Go routines when possible. This book will show you how to leverage all the latest features and much more. This book shows you how to build powerful systems and drops you into real-world situations. You will learn to develop high quality command-line tools that utilize the powerful shell capabilities and perform well using Go's in-built concurrency mechanisms. Scale, performance, and high availability lie at the heart of our projects, and the lessons learned throughout this book will arm you with everything you need to build world-class solutions. You will get a feel for app deployment using Docker and Google App Engine. Each project could form the basis of a start-up, which means they are directly applicable to modern software markets.
Table of Contents (19 chapters)
Go Programming Blueprints Second Edition
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface

Protocol buffers


Protocol buffers (called protobuf in code) are a binary serialization format that is very small and extremely quick to encode and decode. You describe data structures in an abstract way using a declarative mini language, and generate source code (in a variety of languages) to make reading and writing the data easy for users.

You can think of protocol buffers as a modern alternative to XML, except that the definition of the data structure is separated from the content, and the content is in a binary format rather than text.

It's clear to see the benefits when you look at a real example. If we wanted to represent a person with a name in XML, we could write this:

<person> 
  <name>MAT</name> 
</person> 

This takes up about 30 bytes (discounting whitespace). Let's see how it would look in JSON:

{"name":"MAT"} 

Now we're down to 14 bytes, but the structure is still embedded in the content (the name field is spelled out along with the value).

The equivalent...