This repo contains all the required scripts to run the affiliated Rshiny app of the R package reportingGrofwild. For most users, this will be appropriate. Besides the R package, some deploy scripts are included in this repo to support the incorporation of the Rshiny app within the shinyproxy environment.
As the R code to create the visualisations is implemented as an R package, users for the R code itself should check the manuals in the reporting-grofwild subdirectory. Important to know is that the function runWildApp() of the package is the central piece to start the Rshiny app, as this is also used by the shinyproxy application.
For a detailed description of the shinyproxy application and in-depth knowledge of the setup and Docker settings, the user is referred to the documentation of shinyproxy. The full deployment on the AWS infrastructure is out of scope for this manual and the configuration and setup is provided in a private repo. However, the following elements are present here to support the deployment and should be taken into account when creating new Rshiny packages/application to be handled by the INBO instance of shinyproxy:
- Dockerfile to put the R package in a container as required by shinyproxy.
- Rprofile.site, an additional port forwarding feature for the Docker handling
- appspec.yml providing the required settings for the AWS codedeploy
scripts/reporting-rshiny-grofwildjacht.shproviding the minimal actions to enable the usage of this R package and R shiny application wihtin the shinyproxy environment, i.e. build a Docker with the package inside.
Remark: You can create and test the Docker locally as well, when Docker is installed. Execute docker build -t openanalytics/wildapp . inside the main repo folder to prepare the Docker image.
If you want to check on the EC2 or locally how the Rshiny App inside the Docker is running (without the shinyproxy wrap).
Build docker image.
sudo docker build --build-arg GIT_SHA=$(git rev-parse HEAD) -t inbo/wildapp .
Configure connection to S3 data buckets.
Run docker image, public app.
sudo docker run -p 3001:3838 inbo/wildapp R -e "Sys.setenv('AWS_DEFAULT_REGION'='eu-west-1','AWS_ACCESS_KEY_ID'='xxx','AWS_SECRET_ACCESS_KEY'='xxx'); reportingGrofwild::runWildApp(public=TRUE)"
Browse to localhost:3001.
Run docker image, private app for specific KBO.
sudo docker run -p 3001:3838 inbo/wildapp R -e "Sys.setenv('AWS_DEFAULT_REGION'='eu-west-1','AWS_ACCESS_KEY_ID'='xxx','AWS_SECRET_ACCESS_KEY'='xxx'); reportingGrofwild::runWildApp(public=FALSE, kbo = xxx)"
In a similar way, an R session can be started to run specific functions of the reportingGrofwild R package.
sudo docker run -p 3001:3838 inbo/wildapp R
We would like to thank openanalytics to open source their shinyproxy application, which enabled us to bring the Rshiny application to the web.