Essential reference guide for Python programmers of all skill levels to use AI to speed up tedious tasks, reduce mistakes, and gather suggestions for better ways to use the language they already know. In just 6 laminated pages you can reference the skills to deliberately direct AI tools to explain unfamiliar code, navigate libraries faster, design cleaner architecture, and write better tests. Used the right way, AI becomes a second brain, true assistant, and force multiplier for serious developers. This is not a vibe coding guide. Author Robin Nixon worked with computers in the 80s and started developing websites in the 90s becoming an expert and writing over 40 programming books and over 500 articles for top computer magazines. With his expertise in the field and writing to his audience in our succinct and organized QuickStudy format, this reference has more quality actionable facts per page than any book or website. Designed for quick access to the facts you need, this inexpensive tool is an easy add to your programming toolbox. As our programming reference guides climb in sales to best-selling status, it is clear that print is not dead and this handy desktop tool is an unbeatable value.
6 page laminated guide includes:
- AI & Your Development Environment
- VS Code: Your AI Command Center
- Jupyter Notebooks with AI Assistance
- Setting Up AI API Keys
- Token Costs
- Copyright & AI-Generated Code
- AI Assistance Core Use Cases
- Code Completion & Refactoring
- Code Search & Retrieval
- Library & API Familiarization
- Code Conversion & Translation
- AI for Specific Coding Tasks
- Authentication & Integration
- AI for Testing
- AI for Regex & String Handling
- AI as Debugging Partner
- Diagnosing Errors & Exceptions
- Reading Stack Traces with AI
- Multilevel Stack Traces
- Context is Key
- AI for Code Design & Planning
- System Design via Conversation
- Data Models & Class Design
- AI for Advanced Python
- From Code Assistant to Engineering Partner
- AI-Assisted Docs & Commenting
- Commenting What Matters
- Markdown & README Generation
- AI in Responsible Python Development
- Hallucination Risks
- Lack of Long-term Memory
- Other Limitations
- When Not to Trust Autocomplete
- AI Prompt Hygiene & Version Control
- Always Check Your Diffs
- Use .gptignore or Equivalent for Sharing
- AI-Assisted Security
- Safe Coding
- AI-Assisted Optimization
- Improving Performance
- AI for Maintaining Legacy Code
- Reading & Understanding Old Code
- Refactoring & Modernization
- Risk Reduction & Safe Refactoring
- Top Prompts
- Popular AI Assistants
