My Docker Template for R – Kazuharu Yanagimoto

Docker is one of the best environments for reproductivity of the research. I use Docker for basically all my projects, but it took me about 2 years to get to a satisfactory environment setup. I would like to share it here as a template.

Quick Start

Clone this repository
Open it in VSCode and add Remote-Containers Extension
From the command palette, choose “open folder in container”
Open localhost:8787 in a browser
Create a project for this project directory (by default, choose /home/rstudio/work)
RUN renv::init() in the R console
Set up a DVC environment
1. Prepare a folder in Google Drive (and copy the folder code)
2. Init DVC
```
dvc init
dvc remote add --default myremote gdrive://GDRIVE_FOLDER_CODE
```

Brief Explanations

In this section, I briefly comment on each file. I assume you are familiar with

R, Rstudio & renv
Docker
VSCode and its Remote-Containers extension

I manage data files by DVC. But if you have another strategy for data management, ignore these parts.

`Dockerfile`

FROM rocker/verse

RUN apt update && apt install -y gnupg openssh-client libpoppler-cpp-dev

# DVC
RUN wget \
       https://dvc.org/deb/dvc.list \
       -O /etc/apt/sources.list.d/dvc.list && \
    wget -qO - https://dvc.org/deb/iterative.asc | apt-key add - && \
    apt update && \
    apt install -y dvc 

# R Packages
RUN R -e "install.packages(c('languageserver', 'renv'))"

# Rstudio Global Options
COPY --chown=rstudio:rstudio .config/rstudio/rstudio-prefs.json /home/rstudio/.config/rstudio/rstudio-prefs.json

R image

If you don’t have any preferences, I recommend you use one of the rocker image series of rocker-org:

rocker/rstudio
rocker/tidyverse
rocker/verse
rocker/geospatial

Because I currently write a paper by Rmarkdown, I usually use rocker/verse and use rocker/geospatial for spatial analysis.

DVC

I just follow the official guide for Install from repository. If your environment includes python, it is easier to install it via pip.

R packages

I use renv for dependency management. languageserver allows us to run a code in VSCode, but I don’t usually use it.

Rstudio Global Options

When Rstudio launches, it loads the ~/.config/rstudio/rstudio-prefs.json file for general settings. So I prepare /.config/rstudio/rstudio-prefs.json, and it allows me to use Rstudio with my favorite settings.

If you want to use your own settings, I recommend you

Open Rstudio
Set up by GUI (Tools -> Global Options)
Copy ~/.config/rstudio/rstudio-prefs.json (in container)
Paste it on /.config/rstudio/rstudio-prefs.json (in host)

`docker-compose.yml`

version: '3'
services:
    rstudio:
        build:
            context: .
        environment:
            - TZ=Europe/Madrid
            - DISABLE_AUTH=true
            - RENV_PATHS_CACHE=/home/rstudio/.renv/cache
        volumes:
            - .:/home/rstudio/work
            - $HOME/.renv:/home/rstudio/.renv/cache

DISABLE_AUTH=true

You don’t need to type a password for each new session.

Cache for `renv`

By setting the RENV_PATH_CACHE and mounting the directory, you don’t need to re-install packages. In other words, you can share packages with other (docker) projects and don’t have to re-install all the packages when you rebuild a container.

Have fun!

--- title: "My Docker Template for R" date: 2022-05-24 author: Kazuharu Yanagimoto draft: false categories: [R, Docker] image: "feature.png" twitter-card: image: "feature.png" execute: eval: false --- Docker is one of the best environments for **reproductivity** of the research. I use Docker for basically all my projects, but it took me about 2 years to get to a satisfactory environment setup. I would like to share it here as a template. ## Quick Start 1. Clone [this repository](https://github.com/kazuyanagimoto/dockerR) 1. Open it in VSCode and add Remote-Containers Extension 1. From the command palette, choose "open folder in container" 1. Open `localhost:8787` in a browser 1. Create a project for this project directory (by default, choose `/home/rstudio/work`) 1. RUN `renv::init()` in the R console 1. Set up a [DVC](https://dvc.org/) environment 1. Prepare a folder in Google Drive (and copy the folder code) 1. Init DVC ```{bash} dvc init dvc remote add --default myremote gdrive://GDRIVE_FOLDER_CODE ``` ## Brief Explanations In this section, I briefly comment on each file. I assume you are familiar with - R, Rstudio & `renv` - [Docker](https://www.docker.com/) - [VSCode](https://code.visualstudio.com/) and its [Remote-Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension I manage data files by [DVC](https://dvc.org/). But if you have another strategy for data management, ignore these parts. ### `Dockerfile` ```{.bash} FROM rocker/verse RUN apt update && apt install -y gnupg openssh-client libpoppler-cpp-dev # DVC RUN wget \ https://dvc.org/deb/dvc.list \ -O /etc/apt/sources.list.d/dvc.list && \ wget -qO - https://dvc.org/deb/iterative.asc | apt-key add - && \ apt update && \ apt install -y dvc # R Packages RUN R -e "install.packages(c('languageserver', 'renv'))" # Rstudio Global Options COPY --chown=rstudio:rstudio .config/rstudio/rstudio-prefs.json /home/rstudio/.config/rstudio/rstudio-prefs.json ``` #### R image If you don't have any preferences, I recommend you use one of the rocker image series of [rocker-org](https://github.com/rocker-org/rocker): - rocker/rstudio - rocker/tidyverse - rocker/verse - rocker/geospatial Because I currently write a paper by Rmarkdown, I usually use `rocker/verse` and use `rocker/geospatial` for spatial analysis. #### DVC I just follow the official guide for [Install from repository](https://dvc.org/doc/install/linux#from-repo-on-debian-ubuntu). If your environment includes python, it is easier to install it via `pip`. #### R packages I use `renv` for dependency management. `languageserver` allows us to run a code in VSCode, but I don't usually use it. #### Rstudio Global Options When Rstudio launches, it loads the `~/.config/rstudio/rstudio-prefs.json` file for general settings. So I prepare `/.config/rstudio/rstudio-prefs.json`, and it allows me to use Rstudio with my favorite settings. If you want to use your own settings, I recommend you 1. Open Rstudio 1. Set up by GUI (Tools -> Global Options) 1. Copy `~/.config/rstudio/rstudio-prefs.json` (in container) 1. Paste it on `/.config/rstudio/rstudio-prefs.json` (in host) ### `docker-compose.yml` ```{.yaml} version: '3' services: rstudio: build: context: . environment: - TZ=Europe/Madrid - DISABLE_AUTH=true - RENV_PATHS_CACHE=/home/rstudio/.renv/cache volumes: - .:/home/rstudio/work - $HOME/.renv:/home/rstudio/.renv/cache ``` #### DISABLE_AUTH=true You don't need to type a password for each new session. #### Cache for `renv` By setting the `RENV_PATH_CACHE` and mounting the directory, you don't need to re-install packages. In other words, you can share packages with other (docker) projects and don't have to re-install all the packages when you rebuild a container. Have fun!