This is the code repository for Getting Started with Taipy, First Edition, published by Packt.
Eric Narro
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.
- 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
- Discovering Taipy
- Creating User Interfaces with Taipy
- Connecting to Data Sources with Data Nodes
- Orchestrating Taipy Applications
- Managing Scenarios with Taipy
- Deploying Your Taipy Applications
- Taipy for Finance: Sales Forecasting and BI Reports
- Taipy for Logistics: Creating Supply Chain Management Apps
- Taipy for Urban Planning: Creating a Satellite Image App
- Building an LLM Chatbot with Taipy
- Improving the Performance of Taipy Applications
- Handling Big Data in Taipy Applications
- Creating Real-Time Apps with Taipy
- Embedding Iframes in Taipy Applications
- Exploring Taipy Designer (Enterprise Version)
- Who Uses Taipy?
Taipy is a Python library designed for teams that manipulate data using Python to take their models, algorithms, and visual representations, and turn them into web applications that run in production environments for multiple users. Therefore, the only strong prerequisite is to know how to use Python.
Having some general knowledge of web development can certainly help, since Taipy apps can be styled using CSS (although this isn’t strictly necessary). Chapter 6 assumes some knowledge of Linux systems, the cloud, and Docker, since it discusses deployment strategies. Some chapters use specialized libraries to create more realistic examples, but the book and the GitHub repo provide examples and comments to understand them.
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.