Streamlit Essentials From basics to advanced data app development (Surabhi Pandey) (z-library.sk, 1lib.sk, z-lib.sk)

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Streamlit Essentials From basics to advanced data app development Surabhi Pandey www.bpbonline.com

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First Edition 2025 Copyright © BPB Publications, India ISBN: 978-93-65890-822 All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means. LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY The information contained in this book is true to correct and the best of author’s and publisher’s knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book. All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information. www.bpbonline.com

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Dedicated to My partner, the fundamental constant in my equation.

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About the Author Surabhi is a data enthusiast with over a decade of experience across various data-focused roles. She holds a Bachelor’s Degree in Computer Science from Amrita Vishwavidyapeetham. She enjoys the challenges and opportunities that come with turning raw data into meaningful insights and creating data-driven solutions that empower business decision-making. Her background includes a mix of programming languages and tools; her current favorite toolkit includes DBT, Airflow, and Great Expectations, and her go-to language is Python. She has a keen interest in building frameworks to improve and streamline data quality and governance. Currently based in Kuala Lumpur, Surabhi enjoys a good cup of coffee and is an avid reader of epic fantasy novels.

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About the Reviewers ❖ Afaque is an enthusiastic machine learning engineer who has gained experience in data science, AI, and the advancing fields of MLOps and GenAI. He approaches his work with curiosity and a willingness to learn, utilizing various tools and technologies. His current focus is on GenAI projects, emphasizing deployment, scaling, latency optimization, and monitoring. Outside of his professional role, Afaque shares insights and experiences through his Substack and Medium platforms, exploring various aspects of the data science and AI realm. ❖ Vishu Aasliya is an emerging tech enthusiast with a strong passion for machine learning and artificial intelligence. She has extensive experience in Docker and DevOps, focusing on developing and automating solutions that enhance efficiency and reduce manual intervention. Alongside her academic pursuits, Vishu is also a freelance developer, where she customizes web platforms and implements solutions to optimize user experience and drive engagement. She has worked on various projects, gaining hands-on experience in programming, containerization technologies, and process automation. Currently pursuing a degree in computer science with a specialization in artificial intelligence, Vishu is always eager to explore new technologies and broaden her skill set. In her free time, she enjoys exploring new tools, contributing to open-source projects,

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and staying updated with the latest advancements in tech. ❖ Smaranjit Ghose is a freelance machine learning engineer and lifelong learner specializing in data and algorithms to build fantastic tools and scalable applications. He is currently focused on developing distributed systems for applications serving millions of users, with particular emphasis on computer vision and natural language processing (NLP) implementations. Smaranjit is passionate about creating efficient, automated solutions and avoiding manual work wherever possible. As a technical reviewer, he has contributed to various IT books covering machine learning, React, TensorFlow, large language models (LLMs), and Python and JavaScript ecosystems. Beyond his professional endeavors, Smaranjit is an avid history enthusiast and UFC fan. Smaranjit is also dedicated to mentoring, having guided over 10,000 students across India, the US, UAE, Ireland, and Mexico in building and contributing to open-source organizations and research labs. His commitment to education and open-source development reflects his belief in collaborative innovation and knowledge sharing in the tech community.

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Acknowledgement I would like to express my sincere gratitude to everyone who contributed to completing this book. First and foremost, I extend my heartfelt appreciation to my family for their unwavering support and encouragement; their love and encouragement have been a constant source of motivation. I would also like to thank the BPB Publications team for their excellent work. I would also like to acknowledge the reviewers and technical experts who provided valuable feedback and contributed to the refinement of this manuscript. Their insights and suggestions have significantly enhanced the quality of the book. Some people leave a lasting impression when they cross your path. I had the pleasure of working with Dennis Lau and Raymond Au Yong a few years back. Dennis introduced me to Streamlit (and many other tools), reigniting my spark for experimentation. Raymond was always encouraging and supportive of the ideas I brought to the table, offering valuable feedback that refined my ideas and improved my design thinking. Their belief and their expertise helped me build confidence and trust in my abilities. Their influence still resonates in my tech journey today, and I am grateful to have crossed paths with them. Last but not least, we want to express our gratitude to the readers who have shown interest in our book. Your support and encouragement have been deeply appreciated.

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Thank you to everyone who has played a part in making this book a reality.

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Preface “Streamlit Essentials: From basics to advanced data app development” provides a comprehensive introduction to Streamlit, a powerful framework that simplifies the process of building and deploying data apps. The chapters in this book take readers from the fundamentals of Streamlit to advanced techniques. It begins with the basics, covering Introduction to Streamlit and Getting Started with Streamlit, ensuring that the readers understand the platform’s needs and core concepts. As you progress, you will explore the intricacies of Layouts and Widgets and how to integrate data to create visually appealing Data Visualizations. With a focus on real-world applications, you will also learn about Machine Learning Model Deployments. The later chapters focus on more advanced topics, such as Advanced Streamlit Concepts and Deploying Streamlit Apps, helping you leverage Streamlit’s features like secret management, callbacks, Database connectivity, App testing and streamlining your workflow to make your application production-ready. In addition, hands-on projects in the book will enable you to showcase your skills by building a professional portfolio. Building and Enhancing your Portfolio will help to use the power of networking and community building to get the most out of Streamlit and create a portfolio that resonates with potential employers and collaborators. Enhancing Streamlit development with AI Tools introduces AI-

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assisted development tools that can help speed up the process of application building from ideation to deployment. This book is designed for data professionals, from beginners looking to explore Streamlit for the first time to advanced users seeking to optimize their development process. With practical examples and hands-on projects, “Streamlit Mastery” is a valuable resource for anyone aiming to include Streamlit in their data tooling arsenal and build interactive, data-driven applications. Chapter 1: Introduction to Streamlit: This chapter discusses the challenges of data presentation and how this gap can be bridged. The most commonly used tools and also the challenges faced by the data developers while communicating and understanding the non-technical stakeholders. We discuss various challenges and explore why Streamlit fits in as an ideal solution for faster prototyping and custom data application development. Chapter 2: Getting Started with Streamlit: This chapter covers the installation, basic setup, and core concepts that make Streamlit so accessible. Here, readers will gain strong foundation of Streamlit’s working and understand how to get Streamlit up and running quickly. We will also dive into building the first interactive Data application, which we will enhance throughout future chapters. Chapter 3: Exploring Streamlit Widgets: This chapter covers Streamit-provided widgets, which help in faster development of the applications. Knowing what Streamlit supports natively, can help readers visualize their ideas faster. From creating form-based applications to embedding media, Streamlit widgets help create a fully functional data app in no time. Chapter 4: Styling and Layouts in Streamlit: This chapter covers layout options provided by Streamlit.

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Although not a full-fledged web application development framework, Streamlit provides great tools to enhance the design of your data application and apply design principles to build an aesthetic data application. We will discuss Streamlit state management, custom components library, and what it means to design an engaging and well- structured application. Chapter 5: Data Visualization with Streamlit: This chapter focuses on integrating and creating compelling visualizations with Streamlit. Whether it’s simple charts or complex real-time data-driven insights, transforming raw data into visually engaging content can be achieved using Streamlit. We will also explore Streamlit chat widgets and third-party visualization libraries and compare their functionalities and use cases. Chapter 6: Streamlit and Machine Learning: This chapter dives into integrating machine learning models with Streamlit, showcasing how to build and deploy interactive apps powered by machine learning. Readers will learn how to load pre-trained models, visualize predictions, and make the models accessible to a wider audience. Chapter 7: Advanced Streamlit Concepts: In this chapter, we explore more advanced features, including caching, secret management, app testing, and optimizing performance. We will also discuss the recommended design patterns and pitfalls, ensuring that the data application. Chapter 8: Deployment of Streamlit Apps: In this chapter, we will explore the steps required to deploy Streamlit applications using various options like Streamlit Sharing or cloud providers. We will deploy our Product Recommender application using Streamlit Sharing and Google Cloud Platform and compare various considerations to note when deciding on the deployment platform.

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Chapter 9-11: Hands-On Projects: Easy-Advanced: In these chapters, we dive into real-world projects from easy to advanced. These projects can help you streamline your learning and explore tooling options available with Streamlit. Chapter 12: Build and Enhance Your Portfolio: This chapters gives a walkthrough on Streamlit’s active and vibrant global community boards and how to leverage them to enhance your portfolio. From contributing to open-source projects to marketing your apps, you will learn practical tips for getting your work noticed in the broader data and tech community. Chapter 13: Enhancing Streamlit Development with AI Tools: The final chapter introduces how AI tools can complement Streamlit development. Readers will gain insights into how AI can speed up coding, assist in generating ideas, and even optimize the development process. We will also touch upon the ethical considerations when using AI tools in your projects.

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Code Bundle and Coloured Images Please follow the link to download the Code Bundle and the Coloured Images of the book: https://rebrand.ly/cfyi5zj The code bundle for the book is also hosted on GitHub at https://github.com/bpbpublications/Streamlit- Essentials. In case there’s an update to the code, it will be updated on the existing GitHub repository. We have code bundles from our rich catalogue of books and videos available at https://github.com/bpbpublications. Check them out! Errata We take immense pride in our work at BPB Publications and follow best practices to ensure the accuracy of our content to provide with an indulging reading experience to our subscribers. Our readers are our mirrors, and we use their inputs to reflect and improve upon human errors, if any, that may have occurred during the publishing processes involved. To let us maintain the quality and help us reach out to any readers who might be having difficulties due to any unforeseen errors, please write to us at : errata@bpbonline.com Your support, suggestions and feedbacks are highly appreciated by the BPB Publications’ Family.

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Table of Contents 1. Introduction to Streamlit Introduction Structure Objectives Challenges of data presentation Need for Streamlit Conclusion Exercises Answers 2. Getting Started with Streamlit Introduction Structure Objectives Setting up Streamlit Comparing installation options Running Streamlit locally using virtual environment Running Streamlit using Docker Running Streamlit using Streamlit community cloud Streamlit core concepts Streamlit app model Exploring the Streamlit hello app Hands-on: Product recommender app

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Project structure Running your first Streamlit app Conclusion Exercises Answers 3. Exploring Streamlit Widgets Introduction Structure Objectives Widgets overview Streamlit core widgets Display widgets Text input widgets Numerical input widgets Date and time widgets Other input widgets Single choice widgets Multiple choice widgets Button widgets Data widgets Streamlit magic Hands-on: Adding widgets to enhance the app Choosing the right widgets Conclusion Exercises Answers 4. Styling and Layouts in Streamlit Introduction

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Structure Objectives Designing engaging and well-structured application User interface design with Streamlit Streamlit layouts and containers Streamlit utility widgets Streamlit control flow widgets Streamlit theming Rendering HTML and CSS State management Streamlit custom components Hands-on enhancing product recommender application Conclusion Exercises Answers 5. Data Visualization with Streamlit Introduction Structure Objectives Importance of data visualization in data analysis Streamlit visualization options Streamlit core chart elements Summarizing the chart types and comparing use cases Streamlit supported charting libraries Streamlit display and aesthetics widgets Display progress and status widgets Display message widgets