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

Examples of Streamlit’s capabilities

Here are some useful examples of Streamlit’s capabilities:

  • Interactive data exploration: Streamlit is great for building dashboards that allow users to explore datasets interactively. Users can filter, sort, pivot, search, select features, and analyze data from multiple perspectives.
  • Prototyping minimum viable products (MVPs): Streamlit’s ease of use makes it perfect for building quick prototypes and MVPs. New ideas can be converted into shareable web apps in no time without any complex setup. This “code-first” approach speeds up iteration and feedback.
  • Model deployment: Streamlit apps can expose trained machine learning (ML) models as web services. This allows other apps, scripts, or users to interact with and make predictions from the models. Apps become deployable, productive ML applications and platforms.
  • Embeddings: Streamlit code and widgets can be embedded into Jupyter notebooks, JupyterLab...