Merge pull request #24 from ryanlovett/apps

Update workflows and tech docs.

_toc.yml

@@ -20,19 +20,17 @@ format: jb-book
 root: intro
 title: Home
 parts:
-- caption: Getting started with DataHub tools
+- caption: Getting Started with DataHub
   chapters:
   - file: technology/pedagogy-and-technology/introduction-to-jupyter
     title: Jupyter Notebooks and JupyterHub
-  - file: technology/r-datahub
-    title: R Hub
+  - file: technology/rstudio
   - file: technology/shiny
-    title: Shiny  
   - file: technology/quarto
-    title: Quarto
-  - file: workflow/vscode.md
-  - file: workflow/real-time-collaboration
-  - file: workflow/syncthing
+  - file: technology/remote-desktop
+  - file: technology/vscode.md
+  - file: technology/real-time-collaboration
+  - file: technology/syncthing
   - file: technology/pedagogy-and-technology/external
 - caption: Workflow Basics
   chapters:
@@ -63,6 +61,8 @@ parts:
     title: Work with Large Datasets
   - file: workflow/bestpractices
     title: Instructional Design Best Practices for Creating Jupyter Notebooks
+  # FIXME: r-datahub has very little to do with using R on DataHub
+  - file: workflow/r-datahub
   - file: faq/share
     title: Sharing information about the Hub
 - caption: DataHub Frequently Asked Questions (FAQ)

technology/remote-desktop.md

@@ -0,0 +1,19 @@
+---
+title: Remote Desktop
+---
+
+Some GUI applications require a full desktop environment to run. Instead of
+trying to get students to install software locally, we offer a full fledged
+Linux desktop environment they can access from inside their browser. This is
+just a different user interface with the same infrastructure. Users are
+operating in their DataHub home directories.
+
+Try remote desktop on [EECS DataHub](https://eecs.datahub.berkeley.edu/hub/user-redirect/desktop) with a berkeley.edu account, or [on Binder](https://mybinder.org/v2/gh/yuvipanda/jupyter-desktop-server/master?urlpath=desktop) without a berkeley.edu account.
+
+```{figure} ../images/desktop.png
+:width: 500px
+:align: center
+:name: Shiny Demo
+
+Example of image processing with Qt in remote desktop
+```

technology/rstudio.md

@@ -0,0 +1,24 @@
+---
+title: RStudio
+---
+
+[RStudio](https://posit.co/products/open-source/rstudio) is an integrated development environment that is popular among R users.
+
+```{figure} ../images/rstudio.png
+:width: 500px
+:align: center
+:name: RStudio
+
+Example of running RStudio on DataHub
+```
+
+RStudio is available on many of our R-based hubs, and is the default application on [R hub](https://r.datahub.berkeley.edu).
+
+
+## RStudio Applications
+
+RStudio has integration with applications such as [Quarto](quarto) and [Shiny](shiny). These applications should work as they do on desktop machines. Windows and tabs will be launched as expected.
+
+## Using nbgitpuller
+
+As one might do with Jupyter notebooks, one can use nbgitpuller to pull in code and data into hub environments with RStudio. However unlike JupyterLab, the web-based version of RStudio cannot be configured to open a specific document at server launch. After launching the server, one must manually navigate to the pulled file.

technology/shiny.md

@@ -1,21 +1,29 @@
-# Shiny
+---
+title: Shiny
+---
 
-[Shiny](https://shiny.rstudio.com/) is a R package which makes it easy to build interactive web apps. R shiny server in DataHub is used to build interactive dashboards. Here is a short demo of a shiny application below,
+[Shiny](https://shiny.posit.co) is a platform that makes it easy to build
+interactive web apps. R shiny server in DataHub is used to build interactive
+dashboards.
 
 ```{figure} ../images/shiny_combined.gif
 :width: 500px
 :align: center
 :name: Shiny Demo
 
-Short Demo to launch Shiny application in DataHub
+Short demo of Shiny application on DataHub
 ```
 
-If you are interested to explore Shiny application further then you can play with examples from this [Github repository](https://github.com/rstudio/shiny-examples) and [few other examples](https://github.com/gastonstat/shiny-introstats/) created by a stats faculty. Here are couple of approaches you can take to launch a shiny application,
+If you are interested to explore Shiny application further then you can play
+with [examples from Posit](https://github.com/rstudio/shiny-examples) and some
+[from a Stat instructor](https://github.com/gastonstat/shiny-introstats/).
 
-**Approach I:**
-- Install the nbgitpuller plugin in [Google Chrome](https://chrome.google.com/webstore/detail/nbgitpuller-link-generato/hpdbdpklpmppnoibabdkkhnfhkkehgnc)/[Mozilla Firefox](https://addons.mozilla.org/en-US/firefox/addon/nbgitpuller-link-generator/) browser.
-- Upload the chosen Shiny application to Github
+## Using nbgitpuller
+
+- Install the nbgitpuller plugin for [Google Chrome](https://chrome.google.com/webstore/detail/nbgitpuller-link-generato/hpdbdpklpmppnoibabdkkhnfhkkehgnc) or [Mozilla Firefox](https://addons.mozilla.org/en-US/firefox/addon/nbgitpuller-link-generator/).
+- Upload the chosen Shiny application to a GitHub repository.
 - Paste the URL for the datahub you are using (If you are using Shiny hub then paste https://shiny.datahub.berkeley.edu/) and open it using "Shiny" option in the nbgitpuller plugin.
+
 ```{figure} ../images/launchshinyapp.PNG
 :width: 500px
 :align: center
@@ -25,7 +33,7 @@ Launch Shiny application via nbgitpuller plugin
 ```
 - Paste the link in a browser to access the shiny application. Here is an example [link](https://datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Frstudio%2Fshiny-examples&branch=main&urlpath=shiny%2Fshiny-examples%2F003-reactivity%2F).
 
-**Approach II:**
+## Manual Application Installation
 
 - Clone the required [GitHub repository](https://github.com/rstudio/shiny-examples) having Shiny examples to your instance of Jupyterhub.
 - Launch the Shiny server.
@@ -57,4 +65,4 @@ You can also view the code that generated the dashboard in the rendered output.
 :name: Code for Shiny
 
 Code that generates Shiny dashboard
-```
+```