Getting Started with Taipy

Share your machine learning models, create chatbots, as well as build and deploy insightful dashboards speedily using Taipy with this hands-on book featuring real-world application examples from multiple industries

Key Features

• Create visually compelling, interactive data applications with Taipy
• Bring predictive models to end users and create data pipelines to compare scenarios with what-if analyses
• Go beyond prototypes to build and deploy production-ready applications using the cloud provider of your choice

Book Description

While data analysts, data scientists, and BI experts have the tools to analyze data, build models, and create compelling visuals, they often struggle to translate these insights into practical, user-friendly applications that help end users answer real-world questions, such as identifying revenue trends, predicting inventory needs, or detecting fraud, without wading through complex code.

Getting Started with Taipy is your comprehensive guide to overcoming this challenge. This book teaches you how to use Taipy, a powerful open-source Python library, to build intuitive, production-ready data apps quickly and efficiently. Instead of creating prototypes that nobody uses, you’ll learn how to build faster applications that process large amounts of data for multiple users and deliver measurable business impact. Taipy does the heavy lifting to enable your users to visualize their KPIs, interact with charts and maps, and compare scenarios for better decision-making. You’ll discover how to use Taipy to create apps that make your data accessible and actionable for end users in production environments, such as cloud services or Docker containers.

By the end of this book, you won’t just understand Taipy, you’ll be able to transform your data skills into impactful solutions that address real-world needs and deliver valuable insights.

What you will learn

• Explore Taipy, its use cases, and how it’s different from other projects
• Discover how to create visually appealing interactive apps, display KPIs, charts, and maps
• Understand how to compare scenarios to make better decisions
• Connect Taipy applications to several data sources and services
• Develop apps for diverse use cases, including chatbots, dashboards, ML apps, and maps
• Deploy Taipy applications on different types of servers and services
• Master advanced concepts for simplifying and accelerating your development workflow

Who this book is for

If you’re a data analyst, data scientist, or BI analyst looking to build production-ready data apps entirely in Python, this book is for you. If your scripts and models sit idle because non-technical stakeholders can’t use them, this book shows you how to turn them into full applications fast with Taipy, so your work delivers real business value. It’s also valuable for developers and engineers who want to streamline their data workflows and build UIs in pure Python.

Table of Contents

Part 1: Understanding Taipy and Its Components

Chapter 1: Discovering Taipy

Chapter 2: Creating User Interfaces with Taipy

Chapter 3: Connecting to Data Sources with Data Nodes

Chapter 4: Orchestrating Taipy Applications

Chapter 5: Managing Scenarios with Taipy

Chapter 6: Deploying Your Taipy Applications

Part 2: Building Real-World Applications with Taipy

Chapter 7: Taipy for Finance: Sales Forecasting and Bl Reports

Chapter 8: Taipy for Logistics: Creating Supply Chain Management Apps

Chapter 9: Taipy for Urban Planning: Creating a Satellite Image App

Chapter 10: Building an LLM Chatbot with Taipy

Part 3: Advanced Taipy: Building Efficient and Complex Apps

Chapter 11: Improving the Performance of Taipy Applications

Chapter 12: Handling Large Data in Taipy Applications

Chapter 13: Creating Real-Time Apps with Taipy

Chapter 14: Embedding lframes in Taipy Applications

Chapter 15: Exploring Taipy Designer (Enterprise Version)

Chapter 16: Who Uses Taipy?

About the Author

Eric Narro is a passionate data analyst and Python enthusiast with experience in insurance and agriculture. He transitioned from the wine industry to programming and data analysis, moved by the need for tools that enable professionals with little programming skills to create data applications.

In 2022, he discovered Taipy, fell in love with its concept and quickly became an active contributor. He has written several articles on Taipy’s main components, Taipy Gui and Taipy Core, and frequently uses Taipy to develop prototypes, dashboards, chatbots, and specialized apps. Eric is also engaged in contests, active on social media, and has actively contributed by suggesting new features and reporting bugs.