Go Crazy: A Fun Projects-based Approach to Golang Programming

Go beyond the basics of Go and build complete applications using open-source libraries or the Go programming language by Google. This book will take you deep into the memory lane of the Go language with crunchy details straight from outer space. The applications in this book include the framework for a 2D Go-based game, an image random generator Rest API, financial time series handling for trading, a Kubernetes operator, a Blockchain coding and more. You'll also get refreshers on Go constructs and useful code tricks to build performant projects, and develop an HTTP based cloud ready image generator. Each chapter will be organized in the following format: what the particular application looks like; requirements and user stories of our example program; an introduction to the Go libraries or frameworks used; and the actual implementation of the example program, including common pitfalls and their solutions. Go Crazy will open your eyes to a new world of practical applications for Go. After reading the book, you will be able to apply your Golang knowledge to build your own crazy projects. Free source code will be available on this book's Apress GitHub page. What You'll Learn Compile and inline other programming languages, including GPU coding. Handle Kubernetes clusters via your own operator Write Go to code against Ethereum based block chains. Write intelligent bot code to get you rich and famous. Who This Book Is For Go programmers both experienced and novice. Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: Go to the Basics First Steps Run and Debug Your First Go Program A Short Note on Debugging with GoLand Before Talking to OpenAI: Reviewing Concepts Read from Input Reading from a File Custom Data: Go Structs Writing and Reading Structs from Files Reading a Struct from a File Slicing Program Arguments Using a Custom Library to Load the API Key Asynchronous Code: Go Routines Asynchronous Code: Go Routines and Channels Using Go Contexts Putting Things Together Into a ChatGPT Client Getting an API Key First Request Customize the ChatGPT Request Create a Loop Prompt Streaming the Response Query and Use a Custom Model Summary Chapter 2: Write a Tested HTTP Image Generator API Pour Me Some Gin! Working with Queues Image Generators Image Generator in a Gin Quick Gin Tonic and Templates Use a Synchronized Map Testing the API Simple Go and Gin Testing Testing the Image Generator Summary Chapter 3: Writing the Basics for a 2D Game in Go Some Tile Set History Library Setup: Raylib Game Setup Quick Game Generation with ChatGPT Display the Date in Real Time Hangman Game The Moyashi Game The Basic Game Loop Loading Textures Adding a Player Texture Using Key Inputs Doing the Game Music Game Camera Animate Sprites Animation for an Idle Moyashi Loading the World Map Loading the Full World Map Full Map and Full Screen Summary Chapter 4: Trend Follower for Blockchain Trading Go Crazy or Go Home Why Trade in the Financial Markets? The Origins of Money The Financial Economy vs. the Real Economy Market Efficiency Why Automate Trading? The Secret Sauce Charts Data News and Content Strategy Backtesting Real-Time Trading The Recipe Clear Objectives and a Structured Approach Macroeconomic Tendencies Timeframe Risk Management Testing and Debugging Performance Evaluation Scalability and Maintainability Compliance and Regulation Security Building Confidence Refining Trading Strategies Utensils in the Kitchen Modern Trading Tool Brokers Cloud Infrastructure Cooking Backtesting Data Indicators Levels Simple Moving Averages Exponential Moving Averages Relative Strength Index Additional Notes Enhancing Discipline and Consistency Why So Many Features? Sample Code Exchange Connectivity (Listing 4-1) Building Indicators (Listing 4-2) The Strategy Run the Bot Performance Evaluation Stats PnL PnL in Backtesting PnL in Real-Time Testing Hit Rate Hit Rate in Trading Strategy Evaluation The Potential Drawbacks of an Excessively High Hit Rate Sharpe Ratio Risk-Adjusted Performance Benchmarking and Comparison Portfolio Diversification Potential Pitfalls MAR Ratio Emphasis on Drawdown Risk Risk-Adjusted Performance Comparison of Strategies Suitability for Trend-Following Strategies Potential Pitfalls Success or Failure and Why Benchmark Comparison Timeframe Risk Management and Continuous Improvement Potential Pitfalls Example of Backtesting Multiple Strategies A Taste Before Serving the Meal Ensuring System Stability Hidden Difficulties Forensic Analysis Potential Pitfalls Dinner Is Served Skin in the Game Fear vs. Greed Which Products to Trade Machine Learning Dessert! The Exponential Age Is Here The Proverbial “Cherry on Top” Appendix Finance Jargon Glossary One-liner Extra Indicators of Interest Tom Demark’s Indicators Extra Statistics Side Notes on Geth Ethereum’s GoLang Implementation: Geth GoLang’s Advantages for Blockchain Development References Chapter 5: Writing a Kubernetes Operator to Run EVM-Compatible Blockchains Setting Up Kubernetes on Your Machine Resources Overview Let’s Run a Pod Demystifying Kubernetes Operators Custom Resource Definition Controller Bootstrapping the Project with Operator-SDK Creating an API Generating the Manifests Configuring the Makefile Implementing the Operator Reconciliation Logic Using the Kubernetes Go SDK Interacting with the JSON-RPC API Using Port-Forward Parameterizing Resources and Ports Implementing the Update Logic Implementing Health Checks Creating a Minimal Go HTTP Server Performing a net_peerCount Health Check Configuring the Readiness Probe Summary Chapter 6: Go Beyond: Connecting to C for a Performance Boost C is for Change Calling C Calling C Code Located in a C File C Code Calling Go Code Passing Parameters Using a Header File Using a C Struct from Go Matisse, ImageMagick, and Sepia ImageMagick on OSX ImageMagick on Linux ImageMagick on Raspberry Pi GPU Coding on OSX Basics: Adding Values from Two Arrays Back to the Plot Generic GPU Processing Go Code Opens ETHUSD Hourlies Quotes: Moving Average Slightly Better Moving Average on the GPU Normalized Set Pearson Coefficient Moving Factor Sepia Gopher Extreme Calling OpenCV/C++ from Go Summary Chapter 7: Alef from Plan 9 Plan 9 from Bell Labs The Network Is the Computer The Alef Language Hello Tuple! Channels and Processes Proc and Task Have Fun with Plan 9 Index