Book Image

Getting Started with Streamlit for Data Science

By : Tyler Richards
Book Image

Getting Started with Streamlit for Data Science

By: Tyler Richards

Overview of this book

Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
Table of Contents (17 chapters)
1
Section 1: Creating Basic Streamlit Applications
7
Section 2: Advanced Streamlit Applications
11
Section 3: Streamlit Use Cases

Debugging Streamlit Sharing

Streamlit Sharing also gives us access to the logs of our apps themselves, which will show up on our terminal if we are deploying our apps locally. At the bottom right, whenever we are viewing our own applications, there is a Manage Application button, which allows us to access our logs. From this menu of options, we can reboot, delete, or download logs from our app, along with viewing our other available apps and logging out from Streamlit. 

Streamlit Secrets

When creating and deploying Streamlit apps, you may want to use some information that is not viewable by the user of your app. The default in Streamlit Sharing is for public GitHub repositories with entirely public code, data, and models. But if, say, you want to use a private API key as many APIs (for example, Twitter's scraping API, or the Google Maps API) require, or want to programmatically access data stored in a password protected database, or even if you would like to password...