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Dedication
Foreword
Contributors
Preface
Your Book Comes with Exclusive Perks – Here's How to Unlock Them
Part 1 Foundations for Coding with GenAI
Chapter 1 From Automation to Full Software Development Life Cycle: The Current Opportunity for GenAI
Changing the software engineering field
Introducing the rise of LLMs
Exploring the software development lifecycle
Embracing a GenAI toolkit
Is GenAI worth learning for software engineering?
Summary
Further reading
Chapter 2 Your Quickstart Guide to OpenAI API
Technical requirements
Introducing OpenAI API
Lab 2.1 – sending your first OpenAI API request using the openai Python package
Learning how request costs are calculated
Understanding rate limits and usage restrictions for free and paid OpenAI accounts
Lab 2.2 – analyzing request parameters
Lab 2.3 – using OpenAI API to generate code
Summary
Quiz time
Further reading
Chapter 3 A Guide to GitHub Copilot with PyCharm, VS Code, and Jupyter Notebook
Technical requirements
Introducing GitHub Copilot – our AI pair programmer
Understanding GitHub Copilot's free account limits, costs, and policies
Setting up Copilot in PyCharm and VS Code
Using Copilot chat
Lab 3.1 – calculating geometric mean with chat completion
Lab 3.2 – introducing completion and keyboard shortcuts for geometric mean calculations
Analyzing code with Copilot
Lab 3.3 – working with Copilot in VS Code's Jupyter Notebook for Code Analysis
Summary
Quiz time
Further reading
Chapter 4 Best Practices for Prompting with ChatGPT
Technical requirements
Can we trust GenAI for coding tasks?
Best practices for crafting prompts for coding tasks
Crafting prompts for ChatGPT
Prompt samples by OpenAI
Summary
Quiz time
Further reading
Chapter 5 Best Practices for Prompting with OpenAI API and GitHub Copilot
Technical requirements
Extracting properties from Python objects for OpenAI API
Crafting precise prompts for OpenAI API
Lab 5.1 – Generating docstrings with OpenAI API
Crafting precise prompts for GitHub Copilot
Lab 5.2 – Fixing faulty implementation with GitHub Copilot
Summary
Quiz time
Further reading
Part 2 Basics to Advanced LLM Prompting for GenAI Coding
Chapter 6 Behind the Scenes: How ChatGPT, GitHub Copilot, and Other LLMs Work
Technical requirements
Statistical approach to LLMs
Small and large language models for words
Improving LLM output performance
What are the limitations of LLMs?
ChatGPT
GitHub Copilot
Summary
Quiz time
Further reading
Chapter 7 Reading and Understanding Code Bases with GenAI
Technical requirements
Reading and understanding the code base structure
Using LLMs to explain code
Explaining non-project files
Creating calls with example parameters
Summary
Quiz time
Further reading
Chapter 8 An Introduction to Prompt Engineering
Technical requirements
Utilizing prompt engineering for coding
Enhancing prompts with few-shot examples
Leveraging few-shot prompting with ChatGPT
Crafting a style guide for GitHub Copilot
Working with few-shot learning for OpenAI API
Introducing more prompt engineering techniques
Summary
Quiz time
Further reading
Chapter 9 Advanced Prompt Engineering for Coding-Related Tasks
Technical requirements
Extending the prompt implementation scope
Leveraging CoT reasoning with LLM
Using prompt chaining for LLMs
Summary
Quiz time
Further reading
Chapter 10 Refactoring Code with GenAI
Technical requirements
Introducing code refactoring
Refactoring with chain-of-thought
Performance refactoring with GenAI
Summary
Quiz time
Further reading
Chapter 11 Fine-Tuning Models with OpenAI
Technical requirements
Fine-tuning LLMs toward a specialization
Experimenting with the OpenAI API Playground
Crafting a JSONL file for fine-tuning
Fine-tuning a model with the OpenAI GUI
Comparing our results
Summary
Quiz time
Further reading
Part 3 From Code to Production with GenAI
Chapter 12 Documenting Code with GenAI
Technical requirements
Introducing software documentation
Using GenAI to write docstrings
Finding outdated docstrings with GitHub Copilot, ChatGPT, and OpenAI API
Practical insights
Summary
Quiz time
Further reading
Chapter 13 Writing and Maintaining Unit Tests
Technical requirements
Unit tests with GenAI
Data-driven tests
Test-driven development
Sample data creation with GenAI
Practical insights
Summary
Quiz time
Further reading
Chapter 14 GenAI for Runtime and Memory Management
Technical requirements
Introducing time and space analysis
Profiling runtime and memory consumption with GitHub Copilot
Analyzing maximal capacity with ChatGPT
Optimizing code with chained prompts
Summary
Quiz time
Further reading
Chapter 15 Going Live with GenAI: Logging, Monitoring, and Errors
Technical requirements
Introducing logging, monitoring, and raising errors
Leveraging GenAI for higher-level coding patterns
Applying inverse CoT with ChatGPT and OpenAI
Utilizing few-shot learning and fine-tuning as style guides
Summary
Quiz time
Further reading
Chapter 16 Architecture, Design, and the Future
The rapid rise of GenAI
Economics of faster software development
Will GenAI be adopted by software engineers?
Shifting landscape of software developers
Will GenAI change programming languages?
The future of GenAI in software engineering
Summary
Further reading
Appendix
Set up an OpenAI Account
Creating a virtual environment
Further reading
Other Books You May Enjoy
Index

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Supercharged Coding with GenAI