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README.md

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# shiny-python-workshop-2023
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# Reactive Web Dashboards with Shiny Course
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This is the repository for the 2023 Shiny for Python workshop.
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This is the repository for Talk Python's [Reactive Web Dashboards with Shiny course](https://training.talkpython.fm/courses/reactive-web-dashboards-with-shiny-for-data-science). This 2-hour video course is 100% free so [visit the course page and sign up](https://training.talkpython.fm/courses/reactive-web-dashboards-with-shiny-for-data-science) if you're interested.
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# Installation
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_quarto.yml

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website:
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title: "Shiny for Python Workshop"
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sidebar:
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style: docked
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contents:
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- section: "Exercises"
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contents:
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- exercises/1-hello-world.qmd
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- exercises/2-basic-ui.qmd
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- exercises/3-reactivity.qmd
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- exercises/4-dynamic-ui.qmd
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- exercises/5-reactive-effect.qmd
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- exercises/4-dynamic-ui.qmd
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navbar:
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tools:
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- icon: github
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href: https://github.com/posit-dev/shiny-python-workshop-2023
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- icon: fa-dicord
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href: https://discord.gg/AQVJzG2bnN
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href: https://github.com/talkpython/reactive-web-dashboards-with-shiny-course
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left:
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- href: index.qmd
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text: Home
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format:
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html:
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theme: cosmo
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margin-right: 0px
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css: styles.css
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toc: true
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toc-location: left
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exercises/1-hello-world.qmd

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title: "Hello Shiny"
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---
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These exercises should be done after Chapter 2 of the course.
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```{python}
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# | echo: false
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import os

exercises/2-basic-ui.qmd

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---
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title: "Basic UI"
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---
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These exercises should be done after Chapter 3 of the course.
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```{python}
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# | echo: false
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import os

exercises/3-reactivity.qmd

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---
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title: "Reactivity"
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---
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These exercises should be done after Chapter 4 of the course.
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```{python}
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# | echo: false
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import os

exercises/4-dynamic-ui.qmd

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---
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title: "Dynamic UI"
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---
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These exercises should be done after Chapter 5 of the course.
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```{python}
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# | echo: false
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import os

exercises/5-reactive-effect.qmd

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---
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title: "Reactive Effects"
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---
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These exercises should be done after Chapter 6 of the course.
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```{python}
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# | echo: false
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import os

helpers.py

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block = QuartoPrint(
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[
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formatted_title,
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"::::: {.column-screen-inset}",
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"::::: {.column-screen-inset-right}",
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"::: {.panel-tabset}",
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"## Goal",
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]
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)
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block.append("## {{< bi github >}}")
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block.append(
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f"The source code for this exercise is [here](https://github.com/posit-dev/shiny-python-workshop-2023/tree/main/{path})."
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f"The source code for this exercise is [here](https://github.com/talkpython/reactive-web-dashboards-with-shiny-course/tree/main/{path})."
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)
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block.append(":::")

index.qmd

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---
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title: "Shiny for Python Workshop"
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title: "Reactive Web Dashboards with Shiny"
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---
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::: callout-warning
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This website is under active development and will be unstable.
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:::
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# Web applications without the headaches
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# Background
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Shiny lets you build beautiful, performant dashboards and web applications without a lot of effort.
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Instead of manually managing callback functions and application state, Shiny uses a reactive framework to automatically determine the best way to run your application.
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This means that you can focus on communicating insights rather than debugging your web application.
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This workshop is aimed at people who are somewhat familiar with doing data analysis in Python, but do not have much of a background in Shiny. If you are brand new to Python we recommend spending a bit of time familiarizing yourself with the following topics before the workshop:
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This site is a companion to the [Talk Python video course](https://training.talkpython.fm/purchase/access_code/f3180ced-3d5c-42ad-a318-e81e6355a4fd), and provides some exercises that let you practice what you learned in the videos.
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- How to install Python packages in a virtual environment
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- How to do basic data manipulation with pandas or polars
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- How to draw plots
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- How to clone a repository with git
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# Who is this course for?
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This course assumes that you have a basic understanding of Python, but does not require any knowledge of web applications, JavaScript, or HTML.
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If you can read a CSV, manipulate data, and draw a plot in Python, then you have everything you need to start building a Shiny application.
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# Setup
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## 2) Locally with VS Code
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While Shinylive is great, it likely isn't the environment you'll use to develop Shiny apps, and so it makes sense to set up VS Code and run the examples locally. To do this follow these steps before the workshop:
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While Shinylive is great, it likely isn't the environment you'll use to develop Shiny apps, and so it makes sense to set up VS Code and run the examples locally. To do this, follow these steps before the workshop:
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1) Install [VS Code](https://code.visualstudio.com/)
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2) Install the [Shiny extension for VS Code](https://marketplace.visualstudio.com/items?itemName=posit.shiny)
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3) Clone the repository with `git clone https://github.com/rstudio/shiny-python-workshop-2023.git`, or alternately download the repository as a zip file: \
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![](images/git-download-button.png){width="287"}
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4) Navigate to the project directory and create a new virtual environment with `python3 -m venv .venv`
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5) Set your python interpreter to the virtual environment with `CMD + SHIFT + P` \> `Select Interpreter`
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5) Set your Python interpreter to the virtual environment with `CMD + SHIFT + P` > `Select Interpreter`
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6) Open a new terminal prompt, which should switch to `(.venv)`
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7) Install the relevant packages with `pip install -r requirements.txt`
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requirements.txt

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shinylive
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pandas
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plotnine
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seaborn
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seaborn
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jupyter

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