Regular Expression Puzzles And Ai Coding Assistants
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Regular Expression Puzzles and AI Coding Assistants
Regular Expression Puzzles and AI Coding Assistants is the perfect starting point for programmers of any experience level who want to understand the capabilities -- and the limitations -- of these exciting new tools. Author David Mertz presents 24 challenging regex puzzles, their traditional human-made solutions, and the fascinating answers given by popular AI assistants. Alongside these eye-opening puzzles, you will learn how to write prompts, integrate AI-generated coding suggestions, and interact with the assistant to get the results you want. By the end of the book, you will have a clear understanding of where AI assistants can reliably write code for you and where you will still need a human touch. Plus, you will learn a lot about regular expressions! About the reader Code examples use simple Python and Regular Expressions. No experience with AI coding tools is required.
Regular Expression Puzzles and AI Coding Assistants
Learn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) writing regular expressions and other programs. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done, he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which makes smarter use of lesser known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the technology Groundbreaking large language model research from OpenAI, Google, Amazon, and others have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions—a workhorse technology for developers used to describe, find, and manipulate patterns in text. Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge? About the book Regular Expression Puzzles and AI Coding Assistants is the perfect starting point for programmers of any experience level who want to understand the capabilities—and the limitations—of these exciting new tools. Author David Mertz presents 24 challenging regex puzzles, their traditional human-made solutions, and the fascinating answers given by popular AI assistants. Alongside these eye-opening puzzles you’ll learn how to write prompts, integrate AI-generated coding suggestions, and interact with the assistant to get the results you want. By the end of the book, you'll have a clear understanding of where AI assistants can reliably write code for you and where you’ll still need a human touch. Plus, you’ll learn a lot about regular expressions! About the reader Code examples use simple Python and Regular Expressions. No experience with AI coding tools required. About the author David Mertz is the founder of KDM Training and an acclaimed contributor to the Python community. He is also the author of The Puzzling Quirks of Regular Expressions, Cleaning Data for Effective Data Science: Doing the Other 80% of the Work, and other books. Table of Contents 1 The map and the territory 2 Quantifiers and special sub-patterns 3 Pitfalls and sand in the gears 4 Creating functions using regex 5 Easy, difficult, and impossible tasks 6 Conclusions Appendix A: Learning to use regular expressions
Build Financial Software with Generative AI (From Scratch)
Author: Christopher Kardell
language: en
Publisher: Simon and Schuster
Release Date: 2025-05-20
Build working and regulation-compliant financial software—from scratch! The software used by banks, trading firms, and other financial services has special requirements at every level, from securing the UI to making sure backend services comply with a host of regulations. Build Financial Software with Generative AI (From Scratch) shows you how to deliver full stack financial services software—and how generative AI can make you even more productive. In Build Financial Software with Generative AI (From Scratch) you will: • Explore the core concepts of FinTech • Speed development with generative AI tools • Develop and deploy containerized services • Create and document APIs • Effectively visualize your data In Build Financial Software with Generative AI (From Scratch) you’ll build working software for processing Automated Clearing House (ACH) files, a cornerstone technology of banking that moves trillions of dollars every year. You’ll work with generative AI technology throughout the full stack application, including researching the tech for your application, spinning up a bare bone starting project, answering domain questions, clarifying functionality, and troubleshooting. Along the way, you’ll learn what sets FinTech projects apart from normal web apps. About the technology The financial industry is awash with regulatory and compliance challenges, complex technical requirements, and stringent security demands. There’s a huge demand for developers who can create financial services software and this book will get you started. You’ll build your own FinTech app from the ground up—with a big productivity boost from Generative AI! About the book Build Financial Software with Generative AI (From Scratch) guides you through modernizing a full-stack Automated Clearing House (ACH) application, layer-by-layer. You’ll start with a quick review of FinTech basics and an introduction to GenAI tools. Then, you’ll develop a data visualization dashboard with React, containerize components with Docker, create and refine APIs, implement backend processing, and even design a custom database. Throughout, you’ll see how AI tools aid with coding, testing, research, security, documentation, and even Agile practices. What's inside • Learn the core concepts of FinTech development • Create and document APIs using Generative AI • Build an awesome data visualization dashboard About the reader Examples are in Python. No experience with generative AI or financial services required. About the author Christopher Kardell and Mark Brouwer have both spent more than 20 years working in the Fintech industry. Table of Contents Part 1 1 Exploring FinTech and generative AI 2 Parsing payments Part 2 3 Getting started with Docker 4 APIs: The piping between our components 5 Storing our ACH files 6 Taking the next step with Next.js 7 Our minimum viable product Part 3 8 Exceptions 9 Searching and auditing 10 Company information 11 International ACH transactions and OFAC scanning 12 Where to go from here