Transition from a back-end developer to a full-stack developer with knowledge of all the dimensions of web application development, namely, front-end, back-end and server-side software. In this new edition, Streamlit for Web Development, provides a comprehensive overview of Streamlit, allowing developers and programmers of all backgrounds to get up to speed in as little time as possible.


Streamlit is a pure Python web framework that will bridge the skills gap and shorten development time from weeks to hours. This book walks you through the complete cycle of web application development, from an introductory to advanced level with accompanying source code and resources. You will be exposed to developing basic, intermediate, and sophisticated user interfaces and subsequently you will be acquainted with data visualization, database systems, application security, and cloud deployment in Streamlit. In a market with a surplus demand for full stack developers, this skill set could not possibly come at a better time. In one sentence, Streamlit is a means for the empowerment of developers every-where and all stand to gain from it.


You Will: 




Learn how to mutate big data in real-time
Understand how to visualize big data interactively
Implement web application security and privacy protocols 
How to successfully deploy Streamlit web applications to the cloud using Streamlit, Linux and Windows servers


New For This Edition:




Covers updates from the Streamlit 1.4 release
Showcases Streamlit's latest UI features
Expands on the use and development of Streamlit Components
Introduces new chapters on unit testing and integrating AI with Streamlit
Demonstrates the implementation of LLMs, chatbots, and generative AI applications


Who is this Book for?
Developers with solid programming experience wanting to learn Streamlit; Back-end developers looking to upskill and transition to become a full-stack developers; Those who wish to learn and become more acquainted with data visualization, database systems, security and cloud deployment with Streamlit