You're reading from Web App Development Made Simple with Streamlit A web developer's guide to effortless web app development, deployment, and scalability

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781835086315

Length 350 pages

Edition 1st Edition

Languages

Python

Tools

Streamlit

Concepts

Web Programming

Author (1):

Rosario Moscato

Preface

1. Part 1: Getting Started with Streamlit

2. Chapter 1: Getting to Know Streamlit – A Brief Overview FREE CHAPTER

3. Chapter 2: Setting Up the Python Coding Environment

4. Chapter 3: Exploring Streamlit’s Features and Functionality

5. Part 2: Building a Basic Web App for Essential Streamlit Skills

6. Chapter 4: Streamlit Essentials – Configuring the Environment, Managing Packages, and More

7. Chapter 5: Organizing and Displaying Content with Columns, Expanders, and NLP Techniques

8. Chapter 6: Implementing NLP Techniques for Text Analysis and Processing in Streamlit

9. Chapter 7: Sharing and Deploying Your Apps on the Cloud Using Streamlit Share

10. Part 3: Developing Advanced Skills with a Covid-19 Detection Tool

11. Chapter 8: Advanced Environment Setup and Package Management for Building an AI-Powered Web App

12. Chapter 9: Optimizing Streamlit Web App UX with Customization and UI Features

13. Chapter 10: Utilizing Pretrained Models to Create Specialized and Personalized Web Applications

14. Chapter 11: Deploying and Managing Complex Libraries on Streamlit Share

15. Part 4: Advanced Techniques for Secure and Customizable Web Applications

16. Chapter 12: Smart File Uploading – Advanced Techniques for Professional Web Applications

17. Chapter 13: Creating a Secure Login and Signup Process for Web Applications

18. Chapter 14: Customizing Pages, Personalizing Themes, and Implementing Multi-Pages

19. Chapter 15: Enhancing Web Apps with Forms, Session State, and Customizable Subdomains

20. Chapter 16: Takeaways and Conclusion

21. Index

22. Other Books You May Enjoy

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...