Pete, Matt and Paul's presentation on tips and ideas for using IDEs for interacting with R and setting up your workflow

1. Interacting with R
making your life with R more pleasant

2. IDEs - huh? Why?
● IDE=integrated development environment
● blurred line - many text editors have features
in this direction
● syntax highlighting (at minimum)
● integrated completion, help
● …
● Make your life easier!

3. IDEs/editors
● default editor/GUI
● RStudio
● TextMate
● Sublime
● emacs
● vim
● RCommander etc….

4. Emacs
● Emacs is a very powerful text editor
● Serves as an IDE for any code
(e.g. C++, python, …)
● Heavy on keyboard shortcuts
● Ships with ESS=Emacs Speaks Statistics for
interacting with R, S and SAS, which has
been in development for 20 years

5. Emacs
Can set up
with
autocomplete,
and automatic
help

6. Emacs
Easily select
and execute
chunks
Integrated,
executable
help
E.g. C-c C-r execute region; C-enter execute line; C-c C-f re/load function
Integrated,
executable
help

7. Emacs
Multisyntax
highlighting (e.
g. for Knitr)
Integration with
git

8. Emacs: pros/cons
Pros
● Amazingly powerful
● Very efficient editing
● Multi-code
● Great if you already
use emacs
● free/open, X-platform
Cons
● Steep learning curve
● You already use
another editor
● RSI?!

9. Emacs
Some resources:
http://en.wikipedia.org/wiki/Emacs
http://ess.r-project.org/
http://ess.r-project.org/refcard.pdf
http://www.gnu.org/software/emacs/

10. TextMate Workflow
TextMate is a
“plain old” text
editor (similar to
SublimeText2) TextMate
Analysis scripts
Rmd files
Shiny ui & server files
R shell
source(“file.R”)
runApp()
Shell
knitRmd
make

11. bash
R Workflow
Generate data
Store it
Clean it
Analyse it

12. Analyse it
knitr

13. TextMate R Features
R shell
source(“file.R”)
runApp()
Can run R within TM.
Templates for most things

14. Pros, Cons
• Load up and tear down R
shells easily
• Easy to test code without
polluting analysis workspace
• Can work on remote server
with SSH
• Copy pasting to test code
• Time waiting for scripts to
reload data (caching helps)

15. Tips
• Script as much as possible with shell, R, perl etc.
• Makefiles make it easy to build workflows: https://github.com/mathew-hall/SheffieldR/blob/master/dplyr/Makefile
• Unix philosophy: Files/scripts/functions should do one thing and do it well
• Consider using virtual machines to package up your environment
• Emacs shortcuts work in R console (some in TextMate):
• ^R back-search
• ^A ^E jump to start, end of line
• ^T,M-t transpose char, word
• ^U,^K, ^Y,M-y kill to start,end of line, yank last killed text, cycle through killed text

16. R on the web - R-fiddle.org
• Don’t have access to R? Don’t panic!!!
• R-fiddle lets you use R in the cloud via your browser
• As name suggests - this is best for just fiddling….
• But you can embed the console into your own page

17. Click “save” to store code on their server
Use URL to retreive
Click embed to either embed just code, or code + console
Cool huh?!

18. Jupyter (in development)
• Building on iPython notebooks - interactive documents integrating
Python code, graphics, text etc. Easy to write if you know JSON
• Although iPython can be extended to integrate R code, Jupyter extends
the idea to numerous languages including R
• Still under development but R example notebook is viewable online