Learning GitHub Copilot: Multiplying Your Coding Productivity Using Al

Foreword....8

Preface....11

The Structure of This Book....14

Intended Audience....15

Conventions Used in This Book....17

Using Code Examples....18

O’Reilly Online Learning....19

How to Contact Us....19

Acknowledgments....20

1. Foundations....24

What Is GitHub Copilot?....25

How Does Copilot Work?....28

Large Language Models....28

Code and Generative AI....30

High-Level Flow....34

Usage Considerations....42

Timeliness....42

Relevance....44

Completeness....45

Accuracy....46

Privacy....47

Security....50

Copilot Versus ChatGPT....52

Copilot Plans....54

Conclusion....61

2. Coding with Copilot....63

Inline Suggestions....65

Getting Additional Suggestions....70

Leveraging Comments....75

Directive Comments....76

Questions via Comments....84

Copilot and the Context Menu....86

Using Copilot to Review Your Code....93

Using Copilot’s Default Review Options....93

Creating Custom Review Instructions....96

Configuring Copilot in the IDE....101

Conclusion....110

3. Chatting with Copilot in the IDE....112

Accessing Chat’s Main Interface....113

Understanding Chat Output....120

Managing Chat Sessions....128

Prompt Engineering for Copilot....132

Making Effective Use of the Prompt Dialog....134

Adding Context Elements....136

Adding Participants....139

Understanding Options for Submitting Your Prompt....141

Using the Editor Inline Chat Interface....146

Using the Quick Chat Interface....154

Chat Shortcuts....155

Chat Participants....160

@workspace....162

@vscode....167

@terminal....169

Chat Variables....174

Chat in the Terminal....182

Creating Custom Code-Generation Instructions....184

Dealing with Hallucinations and Bad Answers....189

Conclusion....190

4. Advanced Editing and Autonomous Workflows in the IDE....192

Predictive Edits with Next Edit Suggestions....192

Copilot Edits....200

Agent Mode....211

Copilot Vision....228

Debugging with Copilot....242

Conclusion....249

5. Testing with Copilot....251

How Do I Test?....252

Creating Unit Tests....265

Using the /tests Command....266

Creating Tests from Explicit Prompts....272

Creating Tests from Comments....275

Validating Inputs....279

Creating Integration Tests....282

Defining Custom Testing Instructions....286

Testing Before the Coding and Leveraging Frameworks....288

Leveraging Agent Mode for Testing Workflows....298

Conclusion....303

6. Using Copilot to Document and Explain Code....305

Documenting Content....306

Generating Documentation Inline....306

Generating Documentation Through Chat....311

Generating Framework-Compatible Documentation....316

Generating Documentation for APIs....320

Creating Functional Documentation....322

Extracting Summary Documentation from the Code....325

Explaining Content....329

Understanding Code in a Language New to You....329

Understanding Generated Code and Conventions....331

Explaining the Logic Used in a Section of Code....334

Explaining What Might Go Wrong with a Set of Code....337

Explaining Items from the Terminal....338

Explaining How to Do Something in the Terminal....343

Conclusion....346

7. Keeping Copilot Timely and Relevant....348

Where Context Originates....349

How Timeliness and Relevancy May Be Affected....351

Training Cutoffs....352

Hallucinations....356

Lack of Real-Time Validation....357

Misplaced Context....359

Missing Context....362

User-Based Coping Strategies....365

Telling Copilot What to Use for Context....365

Changing the Model....370

Querying the Model to Determine Which Version Is Current....374

Guiding Copilot by Example....377

Adding Context to Make Code More Relevant....380

Conclusion....385

8. Other Ways to Leverage Copilot....388

Using Copilot with SQL....389

Queries....390

Stored Procedures....393

Optimizations....396

Working with YAML and Kubernetes....398

Generating Regular Expressions....408

Automatic Data Generation....410

GitHub CLI and Copilot....413

Conclusion....416

9. Using Copilot in GitHub....418

Using Chat with GitHub Repositories....419

Using Copilot for Change Workflows....433

Using Copilot with Pull Requests....445

Having Copilot Review Pull Requests....447

Leveraging Copilot to Simplify Initiating Pull Requests....452

Exploring Code Changes with Copilot....458

Using Copilot with GitHub Issues....467

Conclusion....472

10. Extending Copilot’s Functionality....474

Copilot Extensions Versus VS Code Extensions for Copilot....474

What Are Copilot Extensions?....476

Getting Copilot Extensions from the Marketplace....477

Understanding Copilot Extension Implementation Types....491

Assembling Building Blocks for Extensions....494

GitHub Apps....495

Endpoint Server....498

Implementing an Extension as an Agent....499

Performing a Basic Implementation....499

Configuring a GitHub App for a Copilot Agent Extension....510

Implementing an Extension via Skillsets....524

Performing a Basic Implementation....525

Configuring a GitHub App for a Copilot Extension Using Skillsets....530

Creating VS Code Extensions for Copilot....539

Conclusion....550

Index....552

About the Author....588

Supercharge your coding productivity with generative AI using GitHub Copilot. In this practical guide, author Brent Laster guides you through using generative AI for writing better code faster, generating tests with ease, creating polished documentation at any stage of development, and more. You'll also explore advanced uses—like leveraging Copilot's Agent functionality to add features autonomously and reviewing pull requests automatically.

Learning GitHub Copilot is for developers, testers, DevOps engineers, and software professionals at all levels. Alongside the fundamentals, you’ll dive into Copilot Edits, Agent mode, and Copilot Vision. You’ll also learn how to create your own Copilot extensions to expand its capabilities. Whether you’re working in Python, JavaScript, or any other language, this book helps you confidently integrate AI into your development workflow.

• Harness real-time AI insights to explore and understand unfamiliar code and algorithms
• Master inline completions and the chat interface to automate common tasks
• Turn natural language prompts into complete functions, tests, and docs quickly and easily
• Optimize AI results with context and prompts to get targeted solutions
• Streamline feature development and refactors with AI assistance in your IDE