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# =============================================================================
# docker-compose.yml
#
# ACCESS:
# http://localhost:8888 — no password needed
# =============================================================================
services:
openmc-jupyter:
image: ghcr.io/light0vij/openmc-prism:latest
container_name: openmc-prism
ports:
- "8888:8888"
volumes:
# Mount Notebooks/ so notebooks (and any you add) persist on the host
# and are browsable/editable from JupyterLab's file tree.
- ./Notebooks:/workspace/Notebooks
# Mount environments/ so the model-specific OpenMC wrappers imported by
# the notebooks are visible and editable from JupyterLab too.
- ./environments:/workspace/environments
# OpenMC result files (statepoints, tallies, plots, CSVs, reports)
- ./Results:/workspace/Results
# Mount openmc_bo and openmc_ga source so they're browsable in
# JupyterLab's file tree. The pip-installed versions used for imports
# are unaffected.
#- ./openmc_bo:/workspace/openmc_bo
#- ./openmc_ga:/workspace/openmc_ga
# Nuclear data — stored in a named Docker volume so it only downloads
# once and persists across container restarts.
# To use existing data instead, replace with:
# - /path/to/your/nuclear_data:/nuclear_data
- nuclear_data:/nuclear_data #
environment:
- OPENMC_CROSS_SECTIONS=/nuclear_data/cross_sections.xml
- JUPYTER_ENABLE_LAB=yes
# Adjust cpus to how many cores you want to dedicate to OpenMC runs.
# Remove deploy block entirely to use all available resources.
deploy:
resources:
limits:
cpus: "4"
memory: "8g"
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8888/lab"]
interval: 30s
timeout: 10s
retries: 3
start_period: 30s
volumes:
nuclear_data:
name: neutronics_nuclear_data