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Prompting Python for Full Stack Development

Prompting Python for Full Stack Development

SKU:9789349887084

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ISBN: 9789349887084
eISBN: 9789349887619
Rights: Worldwide
Author Name: Temidayo Adefioye
Publishing Date: 30-Apr-2026
Dimension: 7.5*9.25 Inches
Binding: Paperback
Page Count: 250

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Description

Stop Coding Alone—Build Full-Stack Python Applications Faster with AI-Powered Prompting

Key Features

● Get a free one-month digital subscription to www.avaskillshelf.com
● End-to-end AI-assisted Python workflow, from fundamentals to production-ready projects.
● Hands-on Python mastery covering syntax, automation, NLP, and web application development.
● Prompt-driven coding workflows using ChatGPT and AI tools for generation, debugging, and refactoring.

Book Description
Python skills open doors across software development, data, automation, and AI — and enable writing working code faster using natural language. Prompting Python for Full Stack Development shows you how to build real Python applications while using AI tools to generate, debug, and refine code at every stage of the development process.

You begin with Python fundamentals — syntax, data structures, control flow, functions, and error handling- and then progressively integrate AI tools to accelerate each step. The book takes you from writing your first scripts to building an AI task manager, automating data analysis, creating intelligent web scrapers, and deploying a Python web application, grounded in practical exercises and guided prompt workflows throughout.

As you progress, you learn how to craft effective prompts, refine and debug AI-generated code, and build reusable prompt templates for common development tasks. Thus, by the end of the book, you will write cleaner Python, build production-ready projects faster, and work confidently with AI as a programming partner.

What you will learn
Across every book in the Prompting Series, readers will learn how to:
● Learn complex technologies by expressing intent, not memorizing syntax
● Use AI prompts to generate, explain, and refine technical solutions
● Break intimidating tools into conversational learning steps
● Move from beginner understanding to production-ready output
● Build confidence to explore any new technology independently

Table of Contents

1. Getting Started with AI-Powered Development
2. Understanding Python Code with AI
3. Problem Decomposition and Prompt Engineering
4. Debugging and Refactoring with AI
5. Automating Tedious Tasks
6. Making an Interactive Game
7. Creating an Authorship Identification Program
8. Automating Data Reports
9. Building an AI-Powered Web Application
10. Best Practices and Optimization
Index

About Author & Technical Reviewer

Temidayo Adefioyeis a software developer and the author of five internationally published books, as well as the founder of “Talenvo”. He empowers African talents by bridging the work-experience gap, mentoring young professionals, and creating tech-driven solutions that connect skills to global opportunities, helping organizations access h

About the Technical Reviewer

Rahul Kumar Thatikonda is an Analytics Architect and Voting Member of the Python Software Foundation, dedicated to professionalizing the practice of Data Science. A recognized industry professional with over a decade of experience and a Master of Science in Business Analytics, he specializes in architecting decision intelligence frameworks and digital transformation strategies for highly regulated sectors, including healthcare, life sciences and financial services.


As an active researcher in Legacy Modernization, Rahul focuses on solving a critical global challenge: upgrading complex industrial infrastructure without the risk of total system replacement. His independent work on "Agentic AI" and resilience frameworks has demonstrated the ability to increase order processing throughput by over 117%, and reduce billing compliance errors by 75%.

Dedicated to advancing the competitive edge of the global AI landscape, Rahul codifies the engineering rigor necessary for large-scale industrial resilience. By advocating for high-performance, "Production-First" architectures, he provides a standardized roadmap for modernizing the international workforce and mission-critical supply chain infrastructure. His work bridges the gap between theoretical AI and safe industrial application, ensuring that data science delivers transformative value which is not only accurate but defensible, compliant, and engineered to support complex interests on a global stage.