Book Image

Web App Development Made Simple with Streamlit

By : Rosario Moscato
Book Image

Web App Development Made Simple with Streamlit

By: Rosario Moscato

Overview of this book

This book is a comprehensive guide to the Streamlit open-source Python library and simplifying the process of creating web applications. Through hands-on guidance and realistic examples, you’ll progress from crafting simple to sophisticated web applications from scratch. This book covers everything from understanding Streamlit's central principles, modules, basic features, and widgets to advanced skills such as dealing with databases, hashes, sessions, and multipages. Starting with fundamental concepts like operation systems virtualization, IDEs, development environments, widgets, scripting, and the anatomy of web apps, the initial chapters set the groundwork. You’ll then apply this knowledge to develop some real web apps, gradually advancing to more complex apps, incorporating features like natural language processing (NLP), computer vision, dashboards with interactive charts, file uploading, and much more. The book concludes by delving into the implementation of advanced skills and deployment techniques. By the end of this book, you’ll have transformed into a proficient developer, equipped with advanced skills for handling databases, implementing secure login processes, managing session states, creating multipage applications, and seamlessly deploying them on the cloud.
Table of Contents (23 chapters)
Free Chapter
1
Part 1: Getting Started with Streamlit
5
Part 2: Building a Basic Web App for Essential Streamlit Skills
10
Part 3: Developing Advanced Skills with a Covid-19 Detection Tool
15
Part 4: Advanced Techniques for Secure and Customizable Web Applications

Utilizing Pretrained Models to Create Specialized and Personalized Web Applications

So far, we have used Streamlit’s components and libraries, made in Python, to create and build up our web application. However, with Streamlit, we can do even more.

This incredible framework is extremely powerful when used with artificial intelligence (AI) models to make predictions. Developing machine learning (ML) models or neural networks is something very complex and outside the scope of this book, but considering that there are a lot of pretrained models available that perform well to provide solutions for many different use cases, knowing how to use them in our web application to increase their effectiveness and usefulness is something very important.

Simply put, importing and using pretrained ML models in Streamlit is an advanced technique for creating very powerful web applications. Users can import any kind of pretrained model and use it to make predictions on new data within their...