Reactive Web Dashboards with Shiny for Python Course

Reactive Web Dashboards with Shiny
1.5 hours, 100% free
Take this course for FREE

Course Summary

There are dozens of ways to build web applications in Python. You can use Django or FastAPI with a Javascript front-end, or build a simple dashboard using a tool like Streamlit. However, almost all of the python web app frameworks are event-driven and require you to manually manage callback functions and application state.

Shiny uses transparent reactive programming to let you build efficient dashboards and applications without the headaches. Shiny automatically detects the relationships between application components and uses those relationships to minimally re-rennder the app. In this course you will learn how to use Shiny to build a simple dashboard, and also the essential concepts which will allow you to build more ambitious applications in Shiny.

What students are saying

I just finished the course last night and tonight and WOW, it's going to be worth sooo much more to be than the price I paid for it. I've been a TP2M listener for a couple years and love your stuff Michael. Be encouraged: you're changing people's lives. Seriously.
-- Rick

Source code and course GitHub repository

github.com/talkpython/reactive-web-dashboards-with-shiny-course

What's this course about and how is it different?

This course gives you a full understanding of reactive programming, and how to use Shiny’s declarative syntax to build reactive applications. It uses a set of interactive examples written in Pyodide to iteratively test your understanding and reinforce what you learn in the lecture.

What topics are covered

In this course, you will:

  • Learn how to build full featured web applications in Shiny
  • Understand how Shiny uses transparent reactive programming to efficiently update your application
  • Learn how to use reactive calculations to automatically cache shared calculations
  • Build dynamic user interfaces which respond to user actions
  • Layout and style your application to create a beautiful dashboards
  • And lots more, see the full course outline.

Who is this course for?

This course is for anyone who knows basic Python and wants to build data-driven web applications. Shiny is very easy to learn but has all the tools you need to build complex, mission-critical applications.

Who am I? Why should you take my course?

Who is Gordon Shotwell?

Hi, I'm Gordon Shotwell! I'm part of the developer relations team at Posit (the makers of Shiny). I have over ten years of experience building data science applications in various industries. Most recently, I was a Lead Data Scientist at Socure where I was responsible for data science tooling.

Get hands-on for almost every chapter

This course comes with exercises for each topic covered so you can follow along! They are based on Pyodide so you can even run them in your browser using client-side Python without the need to install anything.

This course is delivered in very high resolution

Example of 1440p high res video

This course is delivered in 1440p (4x the pixels as 720p). When you're watching the videos for this course, it will feel like you're sitting next to the instructor looking at their screen.

Every little detail, menu item, and icon is clear and crisp. Watch the introductory video at the top of this page to see an example.

Follow along with subtitles and transcripts

Each course comes with subtitles and full transcripts. The transcripts are available as a separate searchable page for each lecture. They also are available in course-wide search results to help you find just the right lecture.

Each course has subtitles available in the video player.

The time to act is now

If you've wanted to bring your data science projects to life, Shiny (now available for Python) is an awesome choice of platforms. This 100% free course will help you jumpstart your Shiny for Python journey.

Course Outline: Chapters and Lectures

Welcome to the course
3:30
Introduction
0:26
Course website orientation
3:04
Hello Shiny
18:56
Setting up the environment
3:01
Running shiny code
2:17
First Shiny app
3:36
Adding user interactions
3:52
Creating interactive inputs
1:17
Plotting data
2:37
Shiny components
0:55
Running course notebooks
1:21
Basic user interfaces
7:15
Basic UI
7:15
Reactivity
24:12
Basic reactivity
6:26
Dynamic reactivity
4:19
Reactive calc
8:31
Reactive calc example
4:56
Reactive effects and events
12:12
Reactive event
6:03
Reactive effect
6:09
Advanced UIs
18:29
Render express
7:18
Value boxes tabs
11:11
Publishing
3:03
Publishing your app
3:03
Wrap up
1:27
Final thoughts
1:27
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