create-r-dockerfile
关于
This Claude skill generates optimized Dockerfiles for R projects using rocker base images. It handles system dependencies, R package installation, and renv integration with smart layer ordering for fast rebuilds. Use it when containerizing R applications, creating reproducible environments, or deploying R-based services like Shiny or Plumber.
快速安装
Claude Code
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技能文档
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 |
Got: A base image is selected that matches the project's requirements without unnecessary bloat.
If fail: 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"]
Got: Dockerfile builds successfully with docker build -t myproject .
If fail: 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
Got: .dockerignore excludes Git history, IDE files, local renv library, and build artifacts from the Docker context.
If fail: 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()"
Got: Container starts with correct R version and all packages available. sessionInfo() output confirms the expected R version.
If fail: 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"]
Got: Multi-stage build produces a smaller final image. Runtime stage contains only compiled R packages, not build tools.
If fail: 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 buildcompletes without errors - Container starts and R session works
- All required packages are available
-
.dockerignoreexcludes unnecessary files - Image size is reasonable for the use case
- Rebuilds are fast when only code changes (layer caching works)
Pitfalls
- Missing system dependencies: R packages with compiled code need
-devlibraries. Check error messages duringinstall.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/*afterapt-get install. Consider multi-stage builds. - Timezone issues: Add
ENV TZ=UTCor installtzdatafor 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 containerscontainerize-mcp-server- special case for MCP R serversoptimize-docker-build-cache- advanced caching strategiesmanage-renv-dependencies- renv.lock feeds into Docker builds
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