文件列表:

deploy.sh (750, 2017-07-02)
input (0, 2017-07-02)
input\data.csv (41, 2017-07-02)
main.Rmd (1058, 2017-07-02)
processData.R (162, 2017-07-02)

# A workflow for reproducible and transparent data journalism with R and GitHub **WARNING: This guide is outdated and (probably) flawed. Check out my new [rddj-template](https://github.com/grssnbchr/rddj-template) instead!** This repo is tutorial & example at the same time, yay! The goal of this workflow is to automagically upload your knitted RMarkdown file to a [**GitHub Page**](http://grssnbchr.github.io/rddj-reproducibility-workflow/) and to "build" your R code into a zipped folder which can be downloaded by your readers. Ideally, you would reference this zipped folder from within your knitted RMarkdown. Note: *The repo from which the knitted RMarkdown is served to the GitHub Page can also be private!* ## Steps ### Step 0 Init an empty repository & and add remote: ``` mkdir rddj-reproducibility-workflow cd rddj-reproducibility-workflow git init # replace the following with your account and repo git remote add origin https://github.com/grssnbchr/rddj-reproducibility-workflow.git ``` Add a `.gitignore` to ignore standard R output files & project files as well as the `tmp` folder we'll need for building ``` .Rdata .Rhistory .Rprofile main.html output/* ``` ### Step 1 (repetitive) All your "productive" R code goes into one RMarkdown file, but you can include source files (see `main.Rmd`). You can work with your repo as you would with any other, doing stuff like ``` git add git commit git push ... ``` ### Step 2 Now you want to publish your RMarkdown, and, ideally, your whole R script (together with the input files) on GitHub Pages. Initially, and only once, you need to do the following in your working directory: * Start a new branch gh-pages ``` git checkout -b gh-pages ``` * remove everything except gitignore (need to enable an extension in Bash shells in order for this command to work) ``` shopt -s extglob git rm -rf !(.gitignore) git add -u ``` * make an initial commit ``` git commit -m "first commit to gh-pages branch" ``` ### Step 3 For deployment, we want the following: (* The RMarkdown should be automagically knitted to HTML) * The knitted RMarkdown file (`main.html`) should be pushed as `index.html`, so it is shown on the GitHub Page * The R code and the input files should be made available for download as a **zipped folder**, so everyone can rerun the RMarkdown and/or modify the code and produce the output folder. In order to automate this deployment process, we create a little shell script. First, make sure you are in the master branch: ``` git checkout master ``` Then, fire up your favorite editor and create a shell script called `deploy.sh` in the top folder, with the following content: ``` #!/bin/bash # first, knit # only works if you have pandoc > 1.9.0 installed # R -e "rmarkdown::render('main.Rmd')" # make temporary copy of the stuff we want to commit in with all data we need in build mkdir tmp cp main.Rmd tmp/ cp -r input tmp/ cp processData.R tmp/ # replace this with the name your subroutines and add more, if needed # switch to gh-pages branch git checkout gh-pages # rename index file (the processed main.Rmd) from master branch mv main.html index.html # make folder for rscript mkdir rscript # copy over necessary scripts from master branch cp -r tmp/* rscript/ # zip the rscript folder zip -r rscript.zip rscript # remove the rscript folder rm -rf rscript # remove temporary folder rm -rf tmp # add everything for committing git add . # commit in gh-pages git commit -m "build and deploy to gh-pages" # push to remote:gh-pages git push origin gh-pages # checkout master again git checkout master ``` At the end, make the script executable ``` chmod 755 deploy.sh ``` ### Step 4 (repetitive) Now, every time you want to deploy your updated RMarkdown and your R script to your GitHub page, you can ``` ./deploy.sh ``` And your knitted RMarkdown will magically find its way into *username*.github.io/*reponame*. Note: This also works when *reponame* is a private repo! **For this to work best, make sure you are in the `master` branch and you have a clean working directory!** In the case of this demonstration repo, the results are viewable under http://grssnbchr.github.io/rddj-reproducibility-workflow.

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