Web App Development and Real-Time Web Analytics with Python: Develop and Integrate Machine Learning Algorithms Into Web Apps

ISBN-13: 9781484277829 / Angielski / Miękka / 2021 / 244 str.

Tshepo Chris Nokeri

Spis treści

Chapter 1: Static 2D and 3D Graphs

Chapter Goal: This chapter introduces the basics of tabulating data and constructing static

graphical representations. To begin with, it exhibits an approach of extracting and tabulating data by implementing the pandas and sqlalchemy library. Subsequently, it reveals a prevalent 2D and 3D charting recognized as Matplotlib, then exhibits a technique of constructing basic charts (i.e. box-whisker plot, histogram, line plot, and scatter plot).

● Tabulating Data

● 2D Charting

o Box-whisker-plot

o Histogram

o Line plot

o Scatter plot

o Density Plot

● 3D Charting

● Conclusion

Chapter 2: Interactive Charting

Chapter Goal: This chapter introduces an approach for constructing interactive charts by

implementing the most prevalent library, recognized as Plotly.

● Plotly

● 2D Charting

o Box-whisker-plot

o Histogram

o Line plot

o Scatter plot

o Density Plot

o Bar Chart

o Pie Chart

o Sunburst

● 3D Charting

● Conclusion

Chapter 3: Containing functionality in Interactive Graphs

Chapter Goal: This chapter extends to the preceding chapter. It introduces an approach to

updating interactive graphs to improve user experience. For instance, you will learn how to add buttons and range sliders, among other functionalities. Besides that, it exhibits an approach for integrating innumerable graphs into one graph with some functionality.

● Updating Graph Layout

● Updating Plotly Axes

● Including Range Slider

● Including Buttons to a Graph

● Styling Interactive Graphs

● Updating Plotly X-Axis

● Color Sequencing

● Subplots

● Conclusions

Chapter 4: Essentials of HTML

Chapter Goal: This chapter introduces the most prevalent markup language for developing

websites. It acquaints you with the essentials of designing websites. Besides that, it contains a rich

set of code and examples to support you in getting started with coding using HTML.

● The Communication between a Web Browser and Web Server

● Domain Hosting

o Shared Hosting

o Managed Hosting

● HyperText Markup Language

o HTML Elements

▪ Headings

▪ Paragraphs

▪ Div

▪ Span

▪ Buttons

▪ Text Box

▪ Input

▪ File Upload

▪ Label

▪ Form

▪ Meta Tag

● Practical Example

● Conclusion

Chapter 5: Python Web Frameworks and Applications

Chapter Goal: The preceding chapter acquainted you with interactive visualization using Plotly. This chapter introduces key Python web frameworks (i.e., flask and dash) and how they differ.Besides that, it provides practical examples and helps you get started with Python web development.

● Web Frameworks

● Web Applications

● Flask

o WSGI

o Werkzeug

o Jinja

o Installing Flask

o Initializing a Flask Web Application

o Flask Application Code

o Deploy a Flask Web Application

● Dash

o Installing Dash Dependencies

o Initializing a Dash Web Application

o Dash Application Code

o Deploy a Dash Web Application

● Jupyter Dash

● Conclusion

Chapter 6: Dash Bootstrap Components

Chapter Goal: This chapter covers dash_bootstrap_component. It is a Python library from the Plotly family, which enables us to have key bootstrap functionalities on a dash web application, thus

simplifying the web application development.

● Dash Bootstrap Components (cont.)

o Number Input

o Text Areas

o Select

o Radio Items

o Checklist

o Switches

o Tabs

o Button

o Table

● Conclusion

Chapter 7: Styling and Theming

Chapter Goal: This chapter introduces the basics of UX design for a web application, dash with plotly. To begin with, it introduces styling an HTML web page. Subsequently, it acquaints you with the Cascade styling sheet (css). Following that, it presents bootstrap. Afterward, it reveals bootstrapping dash web applications. It concludes by demonstrating a way of designing the layout of a dash web

application.

● Styling

● Cascade Styling Sheet

● Bootstrap

● Dash Bootstrapping

o Dash Core Components

o Dash Bootstrap Components

o Implementing Dash Bootstrap Components Theming

o Dash HTML Components

o Dash Web Application Layout Design

● Responsive Grid System

Chapter 8: Real-Time Web Application

Chapter Goal: This chapter introduces you to creating a real-time web application with a

responsive navigation bar, sidebar, charts, tables, callbacks, and URL routing. After reading the contents of this chapter you should be able to develop a functional and responsive web application by implementing key Python web frameworks (i.e., dash, dash_core_components, dash_html_components). Besides that, you should be able to use the Input, State, and Output methods available for creating functional application callbacks. Equally, it acquaints you with an approach for implementing CSS to customize as a dash web application.

Sub-topics:

● Creating Icons

o Alert Icon

o Messages

o Profile Icon with Dropdown Menu

● Search Bar

● Navigation Bar

● Sidebar Styling

● Responsive Sidebar Styling

● Content Styling

● Sub Menu

● Finalize Sidebar Menu

● Footer Navigation Bar

● Web Application Layout

● Including Charts

● Including a Table

● Enabling Data Download

● Tabs

● Collapse

● Callbacks

o Callbacks for Responsive Menu

● URL Routing

● Conclusion

Chapter 9: Basic Authentication

Chapter Goal: This chapter introduces an approach to securing a dash web application. After reading the contents of this chapter, you should be able to implement user access control, thus providing users access to some web resources and restricting them to others.

Sub-topics:

● Dash Authentications

● Login Form

● Login on Home Page

● Conclusion

Chapter 10: Dash Into a Full Website

Chapter Goal: Prior chapters introduced a way of building dashboards as web applications,

integrated with machine learning models. This chapter takes it a step further. It introduces a way of building the front-end. After reading the contents of this chapter, you should be able to build important pages of a website, such as the home page, about us page, and contact us page, in addition to that, a page for billing/checkout.

Sub-topics:

● Building Home Page

● Building Contact Us Page

● Building Billing / Check-Out Building

Chapter 11: Integrate Machine Learning Models

Chapter Goal: This chapter introduces an approach to integrate machine learning models. Initially, it will provide an over of machine learning recognized as linear regression, including ways of preprocessing data and generating predictions. It concludes by exhibiting a technique of implementing it in web applications.

Sub-topics:

● An Introduction to Linear Regression

● An Introduction to Scikit learn

● Preprocessing

● Splitting Data into Training and Test Data

● Standardization

● Training an Algorithm

● Predictions

● Integrating an Algorithm to a Web App

● Conclusions

Chapter 12: Deploying Web App

Chapter Goal: This chapter concludes the book. It exhibits a way of deploying a web app. Initially, it summarizes an integrated development environment useful for developing, testing, and debugging Python web frameworks. Subsequently, it exhibits an approach of organizing the file structure prior to deploying a web app. Besides that, it provides a practical example that will help you better web app deployment.

Sub-topics:

● Integrated Development Environment

○ PyCharm

● Virtual Environment

● File Structure

● Integration among Multiple Innumerable Python Files

● Hosting Web App

O autorze

Tshepo Chris Nokeri harnesses big data, advanced analytics, and artificial intelligence to foster innovation and optimize business performance. In his functional work, he has delivered complex solutions to companies in the mining, petroleum, and manufacturing industries. He initially completed a bachelor’s degree in information management. He then graduated with an honors degree in business science at the University of the Witwatersrand on a TATA prestigious scholarship and a Wits Postgraduate Merit Award. They unanimously awarded him the Oxford University Press Prize. He has authored the Apress book Data Science Revealed and Implementing Machine Learning for Finance.

Blurb

Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps.

Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he’ll show you the key Python web frameworks and techniques for building web apps with them. You’ll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You’ll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms.

Web App Development  and Real-Time Web Analytics with Python is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning.

You will:

• Create interactive graphs and render static graphs into interactive ones
• Understand the essentials of HTML, CSS, and Bootstrap
• Gain insight into the key Python web frameworks, and how to develop web applications using them
• Develop machine learning algorithms and integrate them into web apps
• Secure web apps and deploy them to cloud platforms