Docker Environment Setup

Docker Environment Setup

Set up a Docker container environment for running Nextflow training examples. This skill handles all Docker configuration needed to match the Codespaces/​Gitpod environment that learners use.

Initial Questions

Use AskUserQuestion to determine the setup type:

Which Docker setup do you need?

• Basic setup (Recommended) - For tutorials without containerized processes (e.g., hello_nextflow basics, plugin_development)
• DooD setup - For tutorials with containerized processes (e.g., genomics, essential_scripting_patterns)
• Check/​restart existing - Verify or restart an existing nf-training container

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Determine NXF_VER

Before any Docker commands, read the Nextflow version from devcontainer.json:

NXF_VER=$(grep -o '"NXF_VER":\s*"[^"]*"' .devcontainer/​devcontainer.json | cut -d'"' -f4)
echo "Using NXF_VER=${NXF_VER}"

This ensures you use the same version learners get in Codespaces.

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Basic Setup

For tutorials that don't use containerized processes:

# Clean up any existing container
docker stop nf-training 2>/​dev/​null; docker rm nf-training 2>/​dev/​null

# Start fresh container with UTF-8 locale support
NXF_VER=$(grep -o '"NXF_VER":\s*"[^"]*"' .devcontainer/​devcontainer.json | cut -d'"' -f4)
docker run -d --name nf-training \
  -e NXF_VER=${NXF_VER} \
  -e LANG=C.UTF-8 \
  -e LC_ALL=C.UTF-8 \
  -v "${PWD}:/​workspaces/​training" \
  -w /​workspaces/​training \
  ghcr.io/​nextflow-io/​training:latest \
  sleep infinity

Important: The LANG=C.UTF-8 and LC_ALL=C.UTF-8 environment variables are critical for handling non-ASCII characters (like "Holà", "Grüß Gott") in file names and content.

Running Commands

docker exec -e LANG=C.UTF-8 -e LC_ALL=C.UTF-8 \
  -w /​workspaces/​training/<working-dir> \
  nf-training \
  <command>

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Docker-outside-of-Docker (DooD) Setup

For tutorials with containerized processes (FASTP, BWA, SAMTOOLS, etc.):

# Clean up any existing container
docker stop nf-training 2>/​dev/​null; docker rm nf-training 2>/​dev/​null

# Get NXF_VER and host path
NXF_VER=$(grep -o '"NXF_VER":\s*"[^"]*"' .devcontainer/​devcontainer.json | cut -d'"' -f4)
HOST_PATH="${PWD}"

# Start container with DooD support
docker run -d --name nf-training \
  -e NXF_VER=${NXF_VER} \
  -e LANG=C.UTF-8 \
  -e LC_ALL=C.UTF-8 \
  -v /​var/​run/​docker.sock:/​var/​run/​docker.sock \
  -v "${HOST_PATH}:${HOST_PATH}" \
  -w "${HOST_PATH}" \
  ghcr.io/​nextflow-io/​training:latest \
  sleep infinity

# Create symlink for Codespaces paths
docker exec nf-training bash -c "rm -rf /​workspaces/​training && mkdir -p /​workspaces && ln -sf ${HOST_PATH} /​workspaces/​training"

Critical differences from basic setup:

1. Docker socket mount (-v /​var/​run/​docker.sock:/​var/​run/​docker.sock) - Allows Nextflow to spawn sibling containers
2. Matching host paths (-v "${HOST_PATH}:${HOST_PATH}") - Work directories resolve correctly between containers
3. Symlink - Makes /​workspaces/​training/​... paths work locally

Running Commands with DooD

docker exec -e LANG=C.UTF-8 -e LC_ALL=C.UTF-8 -e USER=testuser \
  -w "${HOST_PATH}/<working-dir>" \
  nf-training \
  nextflow run <script.nf> [options]

When DooD is Needed

Any tutorial where processes specify containers:

• hello_nextflow (later lessons with containers)
• nf4_science/​genomics and other domain modules
• Side quests: essential_scripting_patterns, metadata, etc.

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Apple Silicon (ARM) Macs

Most bioinformatics containers are built for x86_64/​amd64. On ARM Macs, create a platform config:

docker exec nf-training bash -c 'cat > /​tmp/​platform.config << EOF
docker.runOptions = "--platform linux/​amd64"
EOF'

Include when running:

docker exec -e LANG=C.UTF-8 -e LC_ALL=C.UTF-8 -e USER=testuser \
  -w "${HOST_PATH}/<working-dir>" \
  nf-training \
  nextflow run <script.nf> -c /​tmp/​platform.config

Note: Platform emulation uses more memory. For OOM errors (exit code 137), increase Docker Desktop memory in Preferences → Resources.

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Troubleshooting

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Container Restart Procedure

The container may stop during long sessions. To restart:

# 1. Check if container is running
docker ps | grep nf-training

# 2. If not running, restart with DooD setup
docker stop nf-training 2>/​dev/​null; docker rm nf-training 2>/​dev/​null

HOST_PATH="${PWD}"
NXF_VER=$(grep -o '"NXF_VER":\s*"[^"]*"' .devcontainer/​devcontainer.json | cut -d'"' -f4)

docker run -d --name nf-training \
  -e NXF_VER=${NXF_VER} \
  -e LANG=C.UTF-8 \
  -e LC_ALL=C.UTF-8 \
  -v /​var/​run/​docker.sock:/​var/​run/​docker.sock \
  -v "${HOST_PATH}:${HOST_PATH}" \
  -w "${HOST_PATH}" \
  ghcr.io/​nextflow-io/​training:latest \
  sleep infinity

# 3. Recreate symlink (critical!)
docker exec nf-training bash -c "rm -rf /​workspaces/​training && mkdir -p /​workspaces && ln -sf ${HOST_PATH} /​workspaces/​training"

# 4. Recreate platform config if needed (ARM Macs)
docker exec nf-training bash -c 'cat > /​tmp/​platform.config << EOF
docker.runOptions = "--platform linux/​amd64"
EOF'

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Cleanup

When done with testing:

docker stop nf-training && docker rm nf-training

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Notes

• Always verify you're in the repository root before starting (check for mkdocs.yml)
• The container uses sleep infinity so it persists across multiple command executions
• Symlink must be recreated each time the container restarts
• For long sessions, periodically check container is still running: docker ps | grep nf-training