Hands-On APIs for AI and Data Science

Chapter 11. Using APIs in Streamlit Data Apps

A Note for Early Release Readers

With Early Release ebooks, you get books in their earliest form—the author’s raw and unedited content as they write—so you can take advantage of these technologies long before the official release of these titles.

This will be the 11th chapter of the final book. The GitHub repo for this book is https://github.com/handsonapibook/apibook-part-one.

If you have comments about how we might improve the content and/or examples in this book, or if you notice missing material within this chapter, please reach out to the editor at [e-mail].

A simple app today is better than an over-designed app three months late.

Thiago Teixeira, co-founder of Streamlit

If you want to demonstrate your data science skills to other people, it’s hard to beat a data app — a web application displaying your data science models, graphs, charts, and spreadsheets. Sending a recruiter or potential client a link to a data app you created is a sure way to get their attention.

In this chapter, you will build a data app with Streamlit, an open-source library that helps you create colorful and interactive web apps using Python. Streamlit handles all the complexity of the web interface so you can focus on the data backend code, such as data files, Pandas DataFrames, and APIs.

Streamlit apps can be deployed in a limited fashion for free on the Streamlit Community Cloud or paid web hosting platforms.

Engaging Users with Interactive ...