7/2/2013 R packaging with Rstudio Topics:

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1 7/2/2013 R packaging with Rstudio Topics: How to make an R package using RStudio Sharing packages using github or url Tip for speeding up code Using Sweave and RStudio to do 'reproducible research/programming'. Knitr, an very similar but more flexible alternative to Sweave Sweave can also be used with OpenOffice if you prefer a Wordlike environment Using Rstudio to create web-apps that run your R code

2 Why make packages? Share stable version of R functions with collaborators or the public Make sure everyone uses the latest version of code. Framework for documenting and organizing code and writing stand-alone code. Keep you stable code separate from your indevelopment code Keep bundles of code that should be stand-alone separate. Say model B depends on only model A and model C depends on A & B. Packages make it easy to allow that kind of partial dependency.

3 Creating packages?package.skeleton automates some of the process but the process is so simple that this is not necessary and seems like more work (to me). Build the package from scratch, then point RStudio at it. RStudio comes with all the tools you need to build a package.

4 Using RStudio to build a package You ll learn today about the Build tab in Rstudio BUILD

5 Structure of an R package data (optional) inst (optional documentation) man (optional help files) R code (functions) DESCRIPTION NAMESPACE

6 R directory has your R functions not scripts, functions

7 man directory has all the help files technically, optional (meaning package will work fine without man files)

8 data directory has any data files (.rda or.rdata) that you want with the package

9 Hands on part: build a package You will need Rstudio and Rtools (PC) or XCode (MAC) When you install Rtools make sure you do it as administrator because it needs to update your system path and can t if not installed as admin (and it won t tell you there was a problem.) Copy the Template.zip file in the Files tab to your computer and unzip someplace convenient Open up RStudio

10 Make an Rstudio project from Template In the upper right corner of Rstudio, you see project. Click that. Click Create Project Click From Existing Directory Navigate to the Template directory and click that You should see the Build tab. Rstudio recognized that this is a package because NAMESPACE and DESCRIPTION are in the folder.

11 Make your first R package From the Build tab, click Build and Reload You just built the package Foo Take a look at NAMESPACE and DESCRIPTION Add a bug to foo.r in the R directory and build again. Notice that a bug is listed and the package won t build. Fix the bug and try again.

12 Checking your package Look at foo.r You ll notice I refer to d which is not defined anywhere. That s a bug but not easy to catch, especially if the user happens to have d defined in their workspace. Click Check from the Build tab. It s kind of buried but notice that R warns you about undefined d.

13 Making a tar.gz file or zip file for sharing your package Click More from the Build tab Click Build source package Now you have Foo.tar.gz which you can share ( or put on the web somewhere to download)

14 Sharing your package (that is not on CRAN) You can make a tar.gz file from RStudio and that. You can put the package on github and install directly from R. Install devtools R package library(devtools) install_github("foo", username="eeholmes") library(foo) foo(1,2)

15 Other ways to install using devtools install_url() install from a link pointing to a tar.gz file (that you can created from Rstudio) I put the tar.gz on my website and you can install Foo like so: install_url( les/foo_1.0.tar.gz ) PC users and devtools vs 1.1 You will probably need to create a new system environment variable for this to work. Right click on your computer from the Start Menu, click properies, click Advanced system properties, login as admin, click Environment Variables, Click New in the System Variables box (2 nd one), give the new variable CYGWIN and value nodosfilewarning. Restart your computer. install_git() install from a git repository that is not on github.

16 Work flow for building a package: the initial phases (not for an established package) #1 Copy over a template. Usually it s a package I ve already written. Or I download a similar package from CRAN. Download the tar.gz version of a package and unzip. #2 Initial phase. Create 2 Rstudio projects: package sandbox and package itself. Sandbox: mock up functions here Package itself: functional functions get copied over here #3 End of initial phase is once I have a minimal functional set of functions, a package. Only R code at this phase.

17 Intermediate phase Function development continues in sandbox, but now the rest of the functions are loaded using library(foo). Make sure you export all package functions in the NAMESPACE for the development period. Otherwise you have to use foo:::fun to access fun. When a new function is ready to migrate to package, debugging moves to the package. build, debug, check, debug. Etc. Then back to sandbox to develop a new function.

18 Established package Once the package is fairly well-developed, I switch to a more standard code development work-flow: branch off code, develop, migrate back in using github or something else.

19 The number 1 problem I find with R programming Your functions can read the user workspace! Fortunately checking the package will alert you to undefined globals. Unfortunately, you might not check very often and this will cause endless misery. Make a habit of keeping your workspace empty Periodically delete everything in the workspace; rm(list = ls()) Does working from a clean workspace interfere with your work flow? Then you are not using a very robust work flow and it ll bite you later on. Do not use globals. Period. R and globals don t mix.

20 The number 2 & 3 problems I find with R programming R can be horribly slow. R does not like for loops and many of us use for loops a lot. Avoid for loops if you can. R was not written by computer scientists and likes to think for you instead of throwing errors. This leads to impossible to find bugs.

21 github

22 Make a zip and tar file from RStudio Note, if you are on a MAC you can t build a package for PC, but PC users can build that MAC users can install.

23 Creating web applications using RStudio and shiny (an RStudio package) Examples OpenCPU More info go here:

24 Sweave examples (knitr is basically the same) Rockfish Puget Sound Rockfish Report MARSS User Guide file structure Hands on example You will need LaTeX installed for this Look in the doc folder in the inst folder in the Foo package. Click on Foo.Rnw and click Compile PDF

25 OpenOffice + Sweave example You will need OpenOffice installed Open up the document nile_river_with_r.odt file in OpenOffice. Notice it has regular text and formatting along with some code chunks that look just like Sweave (or knitr) code chunks. Open Rstudio and install the odfweave package. Switch your working directory to whereever nile_river_with_r.odt is and run: library(odfweave) odfweave(file="nile_river_with_r.odt", dest="nile_river.odt") This creates a new OpenOffice document called nile_river.odt with the figures, R code, and tables embedded. Use Save As, select Word, if you need to share this with folks who don t have OpenOffice.

26 For PC Users: If you use MikTeX, you need to add a root path on MikTex Step 1: All Programs: MikTex, click it

$to Add the share\texmf folder for the vers$

27 Click Maintenance (Admin) then Settings Step 3: Finish by clicking this Step 2: You need to Add the share\texmf folder for the vers of R you have. Will look like the path above.

Code Autocomplete Manual

Code Autocomplete Manual Release 2.0.0 Jacques Lucke July 02, 2016 Contents 1 Setup 3 1.1 Installation................................................ 3 1.2 Check the Installation..........................................