Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

Table of Contents....5

About the Author....12

About the Technical Reviewer....13

Acknowledgments....14

Introduction....15

Chapter 1: Introduction to Streamlit....18

What Is Streamlit?....18

Why Streamlit?....19

Why Streamlit for Data Science and ML Engineers?....19

Features of Streamlit....20

Open Source....20

Platforms....20

Ease of Development....20

Interactive Applications....20

Reduced Time of Development....20

No Core Web Development Knowledge....21

Easy to Learn....21

Model Implementation....21

Compatibility....21

Literate Programming Document....22

Streamlit Cloud....22

Optimize Change....22

Error Notifications....23

Comparing Streamlit to Alternative Frameworks....23

Installing Python....25

Installing Streamlit on Windows....26

Installing Streamlit on Linux....26

Installing Streamlit on macOS....26

Testing the Streamlit Installation....27

Creating Our First App....29

Summary....32

Chapter 2: Text and Table Elements....33

Text Elements....33

Titles....34

Headers....35

Subheaders....36

Captions....37

Plain Text....39

Markdown....40

LaTeX....41

Code....42

Data Elements....45

Dataframes....45

Tables....48

Metrics....50

JSON....52

The write() Function as a Superfunction....54

Magic....58

Summary....61

Chapter 3: Visualization....62

The Importance of Visualization....62

Visualization in Streamlit....62

Purpose of Visualization....63

Streamlit Functions....63

Bar....63

Line....65

Area....66

Map....68

Graphviz....69

Seaborn....71

Count....72

Violin....73

Strip....74

Altair....75

Boxplot....76

Area....77

Heatmap....78

Plotly....80

Pie....80

Donut....82

Scatter....83

Line....85

Bar....86

Bar Horizontal....89

Subplots....90

Summary....92

Chapter 4: Data and Media Elements....94

Images....94

Multiple Images....99

Background Image....102

Resizing an Image....103

Audio....105

Video....107

Balloon....110

Snowflake....111

Emojis....112

Summary....113

Chapter 5: Buttons and Sliders....114

Buttons....114

Radio Buttons....115

Check Boxes....117

Drop-Downs....119

Multiselects....121

Download Buttons....123

Progress Bars....124

Spinners....126

Summary....127

Chapter 6: Forms....128

Text Box....128

Text Area....132

Number Input....133

Time....135

Date....136

Color....138

File Upload....140

Text/Docx Document....141

PDF Upload....146

Dataset Upload....148

Image Upload....150

Uploading Multiple Images....151

Saving Uploaded Documents....153

Submit Button....157

Summary....158

Chapter 7: Columns and Navigation....159

Columns....159

Spaced-Out Columns....160

Columns with Padding....162

Grids....164

Expanders/Accordions....165

Containers....167

Empty Containers....169

Sidebars....170

Multipage Navigation....171

Main Page....172

Pages....172

Summary....174

Chapter 8: Control Flow and Advanced Features....175

Alert Box....175

st.info()....175

st.warning()....176

st.success()....176

st.error()....176

st.exception()....176

Control Flow....177

Stop Execution....178

Rerun the Script....178

st.form_submit_button....179

Advanced Features....180

Configuring the Page....180

st.echo....181

st.experimental_show....182

Session State....183

Performance....185

Caching....185

st.experimental_memo....186

st.experimental_memo.clear()....187

st.experimental_singleton....187

st.experimental_singleton.clear....187

Summary....188

Chapter 9: Natural Language Processing....189

NLP App Creation....189

User Input....190

Cleaning the Text....190

Predictions....191

Setting Up Files....194

Requirement Text....195

setup.sh....195

Procfile....196

GitHub Repository Creation....197

Heroku....197

Deployment....199

Summary....201

Chapter 10: Computer Vision in Streamlit....202

Installing Libraries....202

Model Deployment....203

Upload Image....203

Map Image Classes....204

Apply Imaging Techniques....204

Model Preprocessing....205

Predictions....205

Complete Code....206

Index....209

This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you’ll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models.

Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You’ll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you’ll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit.

After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own.

What You Will Learn

• How to start developing web applications using Streamlit
• What are Streamlit's components
• Media elements in Streamlit
• How to visualize data using various interactive and dynamic Python libraries
• How to implement models in Streamlit web applications

Who This Book Is For

Professionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.