Shiny
Shiny is an R package for building interactive web apps straight from R. You can visit Shiny Website for the most useful resources on mastering shiny or look for help from RStudio Community or shinyapps-users Google group.
To ensure the Shiny app is deployed under a reproducible environment, there are two tools we can use: renv and Docker.
To ensure the app is deployed under the same configuration as your local application, there are two tools we can use here.
{renv}{renv} package allows one to have a project-based library so others can run the dashboard locally. To create a reproducible renv library, here are the steps to follow:
Initiate the project with renv::init().
This function will create/modify the .Rprofile file at the root of your project, and creates a renv.lock file, which will list all the package dependencies.
# Loading and initiating {renv}
library(renv)
init()# Installing attempt
install.packages("attempt")
# Create a fake script that launches {attempt}
write("library(attempt)", "script.R")
snapshot() of the state of your project.# Snapshoting the current status of the environment
renv::snapshot(confirm = FALSE)renv::restore() the state of your project using renv.lock.
if you are either working as a team or deploying to a server, you will have to restore the state of your project, which is now living somewhere else, inside your current project/deployment. And to do that, the function to call is renv::restore(), which will update your local project with the dependencies listed inside your Lockfile.
Share .Rprofile, renv.lock, renv/activate.R and renv/settings.dcf files for reproducibility.
Docker is a program that allows to download, install, create, launch and stop multiple operating systems, called containers, on a machine, which will be called the host. This host can be your local computer, or the server where you deploy your application/s.
A. Building a Dockerfile with golem
For a golem project, you can run the following from the root of your package:
golem::add_dockerfile()B. {dockerfiler}
You can use dockerfiler package to generate a Dockerfile straight from R
# Creating a new Dockerfile object
my_dock <- Dockerfile$new()
# Adding RUN, ADD, WORKDIR and EXPOSE commands
my_dock$RUN("apt-get update && apt-get install -y git-core")
my_dock$ADD(".", "/")
my_dock$RUN("mkdir /build_zone")
my_dock$ADD(".", "/build_zone")
my_dock$WORKDIR("/build_zone")
my_dock$RUN(r(remotes::install_local(upgrade="never")))
my_dock$EXPOSE(80)
# Viewing the Dockerfile
my_dockC. Develop inside a Docker container
If you plan on using Docker as a deployment mechanism, you can also use Docker as a local developer environment.