Build Python Web Apps with Streamlit: AI and data applications in minutes

You just built something amazing in Python and you’re ready to share it with the world! But does shipping it to the web mean…learning JavaScript? With the Streamlit framework, you can build interactive web apps entirely in Python incredibly fast. By providing a collection of pre-built UI components and streamlined configurations, Streamlit turns your ideas for data tools and AI workflows into usable applications without any tedious HTML, CSS, and JavaScript.

Build Python Web Apps with Streamlit follows a proven learn-by-building approach. Each chapter introduces a new hands-on project. You’ll create data dashboards, interactive checklists, and even an AI chatbot optimized with RAG and agentic patterns. You’ll also learn from intentional mistakes and real-world debugging challenges that teach you how Streamlit actually works. As you go, each project helps you master software engineering skills you might not have learned as a Python programmer—gathering requirements, persistence and database integration, user authentication, deployment, and troubleshooting.

• Build interactive web apps without HTML/CSS/JavaScript
• Understand Streamlit’s execution model
• Work with databases and persistent data
• Create and deploy production-grade architectures
• Implement user authentication and authorization
• Build AI-powered applications with LLMs
• Develop dashboards, and visualizations
• Implement security best practices

About the technology

With the Streamlit framework, you can build interactive web apps entirely in Python incredibly fast. By providing a collection of pre-built UI components and streamlined configurations, Streamlit turns your ideas for data tools and AI workflows into usable applications without any tedious HTML, CSS, and JavaScript.

About the book

Build Python Web Apps with Streamlit follows a proven learn-by-building approach. Each chapter introduces a new hands-on project. You’ll create data dashboards, interactive checklists, and even an AI chatbot optimized with RAG and agentic patterns. As you go, you’ll practice debugging, deployment, database integration and other software engineering skills.

What’s inside

• Understand Streamlit’s execution model
• Work with databases and persistent data
• Implement user authentication and authorization
• Build AI-powered applications

About the reader

For Python programmers. No web app or AI skills required.

About the author

Aneev Kochakadanis a software engineer at OpenAI, with prior experience at Stripe and Google. He has designed and built systems ranging from online transactional services to data pipelines and business intelligence tools.

Table of Contents

Part 1
1 Introduction to Streamlit
2 Getting started with Streamlit
3 Taking an app from concept to code
4 Streamlit’s execution model
5 Sharing your apps with the world
Part 2
6 A dashboard fit for a CEO
7 The CEO strikes back: Supercharging the dashboard
8 Building a CRUD app with Streamlit
Part 3
9 Creating an AI-powered application
10 RAG and agentic apps with LangGraph and Streamlit
Part 4
11 Testing Streamlit apps
12 Packaging and deploying Streamlit apps
Appendixes
A Installing Python and Streamlit