Show your work: Tutorial on building and hosting web applications

📅 Tuesday, July 8, 2025 | 08:00–12:00 (US/Pacific) | Ballroom C

Note

For setup instructions and environment details, see setup instructions.

Welcome to the Tutorial!

Transform your Python functions into interactive web applications and ensure your scientific work reaches the audience it deserves. In this hands-on session, you’ll learn to bridge the gap between analysis and presentation using modern, open-source tools—all without leaving the Python ecosystem.

What You’ll Accomplish

By the end of this 4-hour tutorial, you will have:

Built and deployed multiple interactive web applications
Created a personal app store/portfolio
Gained practical experience building and deploying web applications
Developed reproducible workflows you can apply to future projects

For example: https://dkedar7.quarto.pub/my-web-app-gallery/

What We’ll Cover

Framework Landscape

Compare and contrast the leading Python web frameworks:

Jupyter widgets and Voila -
Streamlit
Gradio
Fast Dash
Quarto

Fast Dash Deep Dive

Learn to use this library designed specifically for rapid prototyping:

Convert functions to web apps with minimal code
Handle complex data visualization seamlessly
Deploy professional-grade applications quickly

Schedule

08:00 - 08:40: Introduction, motivation and core concepts
08:40 - 08:50: Getting set up (per setup instructions)
08:50 - 09:00: Break
—

09:00 - 09:15: Setting up Quarto
09:15 - 09:50: Jupyter, widgets and Voila
09:50 - 10:00: Break
—

10:00 - 10:30: Streamlit and Gradio
10:30 - 10:50: Fast Dash
10:50 - 11:00: Break
—

11:00 - 11:20: More Fast Dash
11:20 - 12:00: Deploy your app gallery and wrap-up

Prerequisites

Before the session, please ensure you have:

Python 3.9+ installed on your system
Basic Python programming familiarity
Code editor or IDE of your choice
Git installed for accessing tutorial materials

Required Installation

Run this command before the tutorial:

pip install fast-dash streamlit gradio

Bring Your Own Data

While I’ll provide example datasets and use cases, you’re encouraged to bring your own:

Datasets you’re currently analyzing
Functions you’d like to turn into web apps
Specific use cases from your domain
Visualization challenges you’re facing

Meet Your Instructor

Kedar Dabhadkar

Instructor Photo

I am a Data scientist at Lam Research with >6 years of experience in statistical data analysis, engineering, and machine learning. I’ve built and deployed over 50 web applications for my teams and colleagues at work, friends and family. I built Fast Dash, an open-source Python library that transforms Python functions into interactive web applications.

Questions? Feel free to reach out during the session or connect with fellow participants. If you have any questions or feedback, please email me at kdabhadk@gmail.com.