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add dockerfile and workflow to build a jupyter
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‎.github/workflows/docker-jupyter-image.yml‎

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name: ghcr
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#on:
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# push:
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# branches: [ "main" ]
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# pull_request:
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# branches: [ "main" ]
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name: ghcr-jupyter
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on:
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push:
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branches: [ "main" ]
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jobs:
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build:
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build-amd64:
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runs-on: ubuntu-latest
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if: github.repository == 'stfc/janus-core'
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permissions:
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packages: write
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contents: read
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steps:
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- name: 'clone the repo'
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uses: actions/checkout@v4
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- name: 'login to ghcr'
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{github.actor}}
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password: ${{secrets.GITHUB_TOKEN}}
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: ./containers
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file: ./containers/Dockerfile.jupyter
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push: true
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tags: |
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ghcr.io/stfc/janus-core/jupyter:amd64-${{ github.sha }}
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ghcr.io/stfc/janus-core/jupyter:amd64-latest
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build-arm64:
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runs-on: ubuntu-latest-arm
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if: github.repository == 'stfc/janus-core'
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permissions:
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packages: write
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contents: read
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uses: docker/build-push-action@v5
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with:
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context: ./containers
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file: ./containters/Dockerfile.jupyter
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file: ./containers/Dockerfile.jupyter
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push: true
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tags: |
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ghcr.io/stfc/janus-core/jupyter:${{ github.sha }}
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ghcr.io/stfc/janus-core/jupyter:latest
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ghcr.io/stfc/janus-core/jupyter:arm64-${{ github.sha }}
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ghcr.io/stfc/janus-core/jupyter:arm64-latest

‎.github/workflows/docker-marimo-image.yml‎

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name: ghcr-marimo
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on:
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push:
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branches: [ "main" ]
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jobs:
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build-amd64:
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runs-on: ubuntu-latest
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if: github.repository == 'stfc/janus-core'
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permissions:
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packages: write
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contents: read
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steps:
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- name: 'clone the repo'
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uses: actions/checkout@v4
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- name: 'login to ghcr'
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{github.actor}}
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password: ${{secrets.GITHUB_TOKEN}}
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: ./containers
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file: ./containers/Dockerfile.marimo
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push: true
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tags: |
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ghcr.io/stfc/janus-core/marimo:amd64-${{ github.sha }}
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ghcr.io/stfc/janus-core/marimo:amd64-latest
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build-arm64:
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runs-on: ubuntu-latest-arm
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if: github.repository == 'stfc/janus-core'
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permissions:
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packages: write
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contents: read
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steps:
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- name: 'clone the repo'
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uses: actions/checkout@v4
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- name: 'login to ghcr'
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{github.actor}}
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password: ${{secrets.GITHUB_TOKEN}}
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: ./containers
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file: ./containers/Dockerfile.marimo
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push: true
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tags: |
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ghcr.io/stfc/janus-core/marimo:arm64-${{ github.sha }}
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ghcr.io/stfc/janus-core/marimo:arm64-latest

‎README.md‎

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@@ -17,6 +17,7 @@ Tools for machine learnt interatomic potentials
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- [Features](#features)
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- [Python interface](#python-interface)
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- [Command line interface](#command-line-interface)
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- [Docker/Podman images](#dockerpodman-images)
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- [Development](#development)
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- [License](#license)
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- [Funding](#funding)
@@ -294,6 +295,41 @@ This will run a singlepoint energy calculation on `KCl.cif` using the [MACE-MP](
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Minimal and full example configuration files for all calculations can be found
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[here](https://stfc.github.io/janus-core/examples/index.html).
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## Docker/Podman images
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You can use `janus_core` in a JupyterHub or marimo environment using [docker](https://www.docker.com) or [podman](https://podman.io/). We provide regularly updated docker/podman images, which can be dowloaded by running:
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```shell
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docker pull ghcr.io/stfc/janus-core/jupyter:amd64-latest
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docker pull ghcr.io/stfc/janus-core/marimo:amd64-latest
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```
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or using podman
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```shell
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podman pull ghcr.io/stfc/janus-core/jupyter-amd64:latest
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podman pull ghcr.io/stfc/janus-core/marimo-amd64:latest
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```
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for amd64 architecture, if you require arm64 replace amd64 with arm64 above, and next instructions.
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To start, for marimo run:
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```shell
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podman run --rm --security-opt seccomp=unconfined -p 8842:8842 ghcr.io/stfc/janus-core/marimo:amd64-latest
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```
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or for JupyterHub, run:
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```
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podman run --rm --security-opt seccomp=unconfined -p 8888:8888 ghcr.io/stfc/janus-core/jupyter:amd64-latest
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```
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For more details on how to share your filesystem and so on you can refer to this documentation: https://summer.ccp5.ac.uk/introduction.html#run-locally.
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## Development
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‎containers/Dockerfile.jupyter‎

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@@ -105,6 +105,40 @@ RUN set -x && \
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fix-permissions "${CONDA_DIR}" && \
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fix-permissions "/home/${NB_USER}"
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# setup the notebook... pretty basic stuff
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USER ${NB_UID}
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WORKDIR /tmp
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RUN mamba install --yes \
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'jupyterhub-singleuser' \
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'jupyterlab' \
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'nbclassic' \
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# Sometimes, when the new version of `jupyterlab` is released, latest `notebook` might not support it for some time
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# Old versions of `notebook` (<v7) didn't have a restriction on the `jupyterlab` version, and old `notebook` is getting installed
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# That's why we have to pin the minimum notebook version
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# More info: https://github.com/jupyter/docker-stacks/pull/2167
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'notebook>=7.2.2' && \
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jupyter server --generate-config && \
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mamba clean --all -f -y && \
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jupyter lab clean && \
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rm -rf "/home/${NB_USER}/.cache/yarn" && \
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fix-permissions "${CONDA_DIR}" && \
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fix-permissions "/home/${NB_USER}"
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ENV JUPYTER_PORT=8888
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EXPOSE $JUPYTER_PORT
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# Configure container startup
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CMD ["start-notebook.py"]
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# Copy local files as late as possible to avoid cache busting
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COPY start-notebook.py start-notebook.sh start-singleuser.py start-singleuser.sh /usr/local/bin/
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COPY jupyter_server_config.py /etc/jupyter/
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# Fix permissions on /etc/jupyter as root
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USER root
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RUN fix-permissions /etc/jupyter/
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RUN rm -rf "/home/${NB_USER}/.cache/"
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# Switch back to jovyan to avoid accidental container runs as root
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'sympy' \
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'widgetsnbextension'\
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'xlrd' \
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'meson' \
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'spglib' && \
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'gxx' \
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'spglib' 'jupyter-server-proxy' 'jupyter-collaboration' && \
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mamba clean --all -f -y && \
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fix-permissions "${CONDA_DIR}" && \
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fix-permissions "/home/${NB_USER}"
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mamba clean --all -f -y && \
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rm -rf "/home/${NB_USER}/.cache"
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EXPOSE 8888
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WORKDIR "${HOME}"

‎containers/Dockerfile.marimo‎

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FROM python:3.12-slim
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
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LABEL maintainer="Alin Elena <[email protected]>"
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ARG UID="1001"
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ARG GID="100"
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ENV user=drFaustroll
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ENV group=drFaustroll
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RUN useradd -m ${user}
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WORKDIR /app
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USER root
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ENV DEBIAN_FRONTEND=noninteractive
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RUN apt update --yes && \
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apt upgrade --yes && \
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apt install --yes --no-install-recommends \
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ca-certificates \
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locales \
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sudo \
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tini \
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wget bzip2 curl git gcc g++ make cmake && \
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apt clean && rm -rf /var/lib/apt/lists/* && \
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echo "en_US.UTF-8 UTF-8" > /etc/locale.gen && \
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locale-gen
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ARG marimo_version=0.16.2
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ENV MARIMO_SKIP_UPDATE_CHECK=1
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ENV UV_SYSTEM_PYTHON=1
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RUN uv pip install --no-cache-dir marimo==${marimo_version} && \
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mkdir -p /app/data && \
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chown -R ${user}:${group} /app
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COPY --chown=${user}:${group} assets/tutorials tutorials
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ENV PORT=8842
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EXPOSE $PORT
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ENV HOST=0.0.0.0
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RUN uv pip install --no-cache-dir marimo[recommended,lsp,sql] altair pandas python-lsp-server websockets \
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duckdb \
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sqlglot \
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vegafusion vl-convert-python \
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ruff \
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openai \
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nbformat \
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pytest
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RUN uv pip install --no-cache-dir 'janus-core[all]@git+https://github.com/stfc/janus-core.git@main'
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RUN uv pip install --no-cache-dir cuequivariance==0.5.1 \
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cuequivariance-torch==0.5.1 \
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cuequivariance-ops-torch-cu12==0.5.1 \
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torchvision \
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pack-mm \
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seaborn \
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data-tutorials \
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pymatviz \
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opentsne \
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pymatgen \
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pymatviz \
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git+https://github.com/imagdau/aseMolec@main
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CMD marimo edit --no-token -p $PORT --host $HOST

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