Create R Dockerfile

Build a Dockerfile for R projects using rocker base images with proper dependency management.

When to Use

• Containerizing an R application or analysis
• Creating reproducible R environments
• Deploying R-based services (Shiny, Plumber, MCP server)
• Setting up consistent development environments

Inputs

• Required: R project with dependencies (DESCRIPTION or renv.lock)
• Required: Purpose (development, production, or service)
• Optional: R version (default: latest stable)
• Optional: Additional system libraries needed

Procedure

Step 1: Choose Base Image

Use Case	Base Image	Size
Minimal R runtime	rocker/r-ver:4.5.0	~800MB
With tidyverse	rocker/tidyverse:4.5.0	~1.8GB
With RStudio Server	rocker/rstudio:4.5.0	~1.9GB
Shiny server	rocker/shiny-verse:4.5.0	~2GB

Expected: A base image is selected that matches the project's requirements without unnecessary bloat.

On failure: If unsure which image to use, start with rocker/r-ver (minimal) and add packages as needed. Check rocker-org for the full image catalog.

Step 2: Write Dockerfile

FROM rocker/r-ver:4.5.0

# Install system dependencies
# Group by purpose for clarity
RUN apt-get update && apt-get install -y \
    # HTTP/SSL
    libcurl4-openssl-dev \
    libssl-dev \
    # XML processing
    libxml2-dev \
    # Git integration
    libgit2-dev \
    libssh2-1-dev \
    # Graphics
    libfontconfig1-dev \
    libharfbuzz-dev \
    libfribidi-dev \
    libfreetype6-dev \
    libpng-dev \
    libtiff5-dev \
    libjpeg-dev \
    # Utilities
    git \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install R packages
# Order: least-changing first for cache efficiency
RUN R -e "install.packages(c( \
    'remotes', \
    'devtools', \
    'renv' \
    ), repos='https://cloud.r-project.org/')"

# Set working directory
WORKDIR /workspace

# Copy renv files first (cache layer)
COPY renv.lock renv.lock
COPY renv/activate.R renv/activate.R

# Restore packages from lockfile
RUN R -e "renv::restore()"

# Copy project files
COPY . .

# Default command
CMD ["R"]

Expected: Dockerfile builds successfully with docker build -t myproject .

On failure: If the build fails during apt-get install, check package names for the target distro (Debian). If renv::restore() fails, ensure renv.lock and renv/activate.R are copied before the restore step.

Step 3: Create .dockerignore

.git
.Rproj.user
.Rhistory
.RData
renv/library
renv/cache
renv/staging
docs/
*.tar.gz

Expected: .dockerignore excludes Git history, IDE files, local renv library, and build artifacts from the Docker context.

On failure: If the Docker build still copies unwanted files, verify .dockerignore is in the same directory as the Dockerfile and uses correct glob patterns.

Step 4: Build and Test

docker build -t r-project:latest .
docker run --rm -it r-project:latest R -e "sessionInfo()"

Expected: Container starts with correct R version and all packages available. sessionInfo() output confirms the expected R version.

On failure: Check build logs for system dependency errors. Add missing -dev packages to the apt-get install layer.

Step 5: Optimize for Production

For production deployments, use multi-stage builds:

# Build stage
FROM rocker/r-ver:4.5.0 AS builder
RUN apt-get update && apt-get install -y libcurl4-openssl-dev libssl-dev
COPY renv.lock .
RUN R -e "install.packages('renv'); renv::restore()"

# Runtime stage
FROM rocker/r-ver:4.5.0
COPY --from=builder /usr/local/lib/R/site-library /usr/local/lib/R/site-library
COPY . /app
WORKDIR /app
CMD ["Rscript", "main.R"]

Expected: Multi-stage build produces a smaller final image. Runtime stage contains only compiled R packages, not build tools.

On failure: If packages fail to load in the runtime stage, ensure the library path in COPY --from=builder matches where R installed packages. Check with R -e ".libPaths()" in both stages.

Validation

• docker build completes without errors
• Container starts and R session works
• All required packages are available
• .dockerignore excludes unnecessary files
• Image size is reasonable for the use case
• Rebuilds are fast when only code changes (layer caching works)

Common Pitfalls

• Missing system dependencies: R packages with compiled code need -dev libraries. Check error messages during install.packages()
• Layer cache invalidation: Copying all files before installing packages invalidates cache on every code change. Copy lockfile first.
• Large images: Use rm -rf /var/lib/apt/lists/* after apt-get install. Consider multi-stage builds.
• Timezone issues: Add ENV TZ=UTC or install tzdata for timezone-aware operations
• Running as root: Add a non-root user for production: RUN useradd -m appuser && USER appuser

Examples

# Development container with mounted source
docker run --rm -it -v $(pwd):/workspace r-project:latest R

# Plumber API service
docker run -d -p 8000:8000 r-api:latest

# Shiny app
docker run -d -p 3838:3838 r-shiny:latest

Related Skills

• setup-docker-compose - orchestrate multiple containers
• containerize-mcp-server - special case for MCP R servers
• optimize-docker-build-cache - advanced caching strategies
• manage-renv-dependencies - renv.lock feeds into Docker builds