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

List Price: $49.99
SKU:
9781633436015
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25 unit(s)
Expected release date is Jun 9th 2026
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  • Product Details

    Author:
    Aneev Kochakadan
    Format:
    Paperback
    Pages:
    480
    Publisher:
    Manning (June 9, 2026)
    Imprint:
    Manning
    Release Date:
    June 9, 2026
    Language:
    English
    ISBN-13:
    9781633436015
    ISBN-10:
    1633436012
    Weight:
    16.9oz
    Dimensions:
    7.375" x 9.25"
    File:
    Eloquence-SimonSchuster_05152026_P10092570_onix30-20260515.xml
    Folder:
    Eloquence
    List Price:
    $49.99
    Pub Discount:
    37
    As low as:
    $38.49
    Publisher Identifier:
    P-SS
    Discount Code:
    A
  • Overview

    Get the eBook free when you register your print book at Manning.

    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 Kochakadan is 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