Prototyping Python Dashboards for Scientists and Engineers, Houlahan P., 2024

Prototyping Python Dashboards for Scientists and Engineers, Houlahan P., 2024.
    
   This book is intended for those who work with data and also have the need to share insights regarding data. An essential aspect is a desire to help their end user “lift the veil" and understand underlying data features such as trends and patterns. Large organizations can have teams of developers and experts to achieve these goals, but many who could benefit from such capability (e.g., college faculty and graduate students) work with minimal resources and need to take a jack-of-all-trades approach to building applications; they need to solve the data access, data importation, data display, analytical tool build, server operating system management, and deployment problems (if your dashboard is wildly successful, you will need a scalable solution!). All these must be done in a realistic manner. Some corners can be cut - there are fewer deployment concerns if the project is behind a firewall or if the users are all experts, and primitive graphics can work if there are deadline constraints. Regardless, there is a daunting task and skillset list the graduate or faculty member must master.




Coding Design: Python and OOD.
My first exposure to scientific programming (a long, long time ago) was through developing scientific software for research using FORTRAN. The coding style was very linear - written to process data from the start of a data file to the end, applying various algorithms as appropriate. There was very little interaction between the user and the code - parameters could be set in a configuration file and through command-line arguments, with text messages being output to indicate progress as needed. The advent of GUI interfaces revolutionized programming; displays could provide buttons and sliders and images responding to cursor position.

Essentially, this new paradigm demanded a different, nonlinear approach; it required main loops that simply monitored and reacted to events: mouse positions, command keys, and clicks. This was the start of event-driven (reactive) programming.

Contents.
About the Author.
About the Technical Reviewer.
Acknowledgments.
Introduction.
Chapter 1: Working with Python.
Coding Design: Python and OOD.
Python Data Types.
Lists, Tuples, and Sets.
Dictionaries.
Series.
Dataframes.
The Spyder IDE.
Summary.
Chapter 2: Reactive Programming with PLOTLY and DASH.
Getting Started with PLOTLY.
Getting Started with DASH.
Summary.
Chapter 3: Working with Online Data.
About the ATADS Dataset.
ATADS Screen Scraping.
Converting Excel to CSV with Data Cleanup.
Managing and Keeping Our Files Up to Date.
Summary.
Chapter 4: Planning the Dashboard Prototype.
Overview.
Project Tasks.
Trends and Forecasts.
Other Design Considerations.
Summary.
Chapter 5: Our First Dashboard.
The atads.py File.
The atads_layout Class.
The atads_figures Class.
Initialization.
Class Methods.
Fine-Tuning with CSS.
Summary.
Chapter 6: Dashboard Enhancements.
Adding the Banner and the Instruction Panels.
Monthly and Weekday Histogram Panels.
The Spectrum Panel.
Quantifying Weekly and Seasonal Effects.
The Final ATADS Dashboard.
Summary.
Chapter 7: Hosting an Application on a UNIX Server.
Creating the Python Environment.
Running a Flask Application.
Using uWSGI.
Using GUNICORN.
Summary.
Chapter 8: Deploying Your Project As a UNIX Service.
Creating a Hello World System Service.
Using NGINX to Share Your Hello World App.
Adding the Dashboard Project to Your Server.
Creating the Dashboard System Service and Deploying with NGINX.
Securing Your Server.
Summary.
Chapter 9: The BTS T100 Dataset: Interacting Controls and Tables.
The BTS T100dm Dataset.
Prototyping a T100dm Display.
Managing Modes and Interacting Menus.
Figures and Tables.
Summary.
Chapter 10: Creating a Web Portal.
Troubleshooting WordPress.
Summary.
Chapter 11: Using Our Dashboard for Data Visualization and Analysis.
Airport Type, Trends, and Location.
Airshows and Seasonal – Using Spectra.
Incorporating Models.
Media, Presentations, Reports, and Projects.
Summary.
Chapter 12: Afterword.
Appendix A: Utilities for Managing ATADS Data.
Index.



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