dclong/jupyterhub-sagemath @DockerHub | @GitHub

JupyterHub with SageMath in Docker. This Docker image is best for math related work, especially calculus related. ** For data science related work, the Docker image dclong/jupyterhub-ds is recommended. **

Prerequisite

You need to install Docker before you use this Docker image.

Usage in Linux/Unix

Please refer to the section Usage of the post My Docker Images for detailed instruction on how to use the Docker image.

The following command starts a container and mounts the current working directory and /home on the host machine to /workdir and /home_host in the container respectively.

docker run -d --init \
    --hostname jupyterhub-sagemath \
    --log-opt max-size=50m \
    -p 8000:8000 \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -e DOCKER_ADMIN_USER=$(id -un) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-sagemath /scripts/sys/init.sh

Use the image with the next tag (which is the testing/next version of dclong/jupyterhub-ds).

docker run -d --init \
    --hostname jupyterhub-sagemath \
    --log-opt max-size=50m \
    -p 8000:8000 \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -e DOCKER_ADMIN_USER=$(id -un) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-sagemath:next /scripts/sys/init.sh

The following command (only works on Linux) does the same as the above one except that it limits the use of CPU and memory.

docker run -d --init \
    --hostname jupyterhub-sagemath \
    --log-opt max-size=50m \
    --memory=$(($(head -n 1 /proc/meminfo | awk '{print $2}') * 4 / 5))k \
    --cpus=$(($(nproc) - 1)) \
    -p 8000:8000 \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -e DOCKER_ADMIN_USER=$(id -un) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-sagemath /scripts/sys/init.sh

Use the image with the next tag (which is the testing/next version of dclong/jupyterhub-ds).

docker run -d --init \
    --hostname jupyterhub-sagemath \
    --log-opt max-size=50m \
    --memory=$(($(head -n 1 /proc/meminfo | awk '{print $2}') * 4 / 5))k \
    --cpus=$(($(nproc) - 1)) \
    -p 8000:8000 \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -e DOCKER_ADMIN_USER=$(id -un) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-sagemath:next /scripts/sys/init.sh

Launch a JupyterLab Instead of JupyterHub

You can still launch a JupyterLab service using this Docker image.

docker run -d --init \
    --hostname jupyterlab \
    --log-opt max-size=50m \
    --memory=$(($(head -n 1 /proc/meminfo | awk '{print $2}') * 4 / 5))k \
    --cpus=$(($(nproc) - 1)) \
    -p 8888:8888 \
    -e DOCKER_USER=$(id -un) \
    -e DOCKER_USER_ID=$(id -u) \
    -e DOCKER_PASSWORD=$(id -un) \
    -e DOCKER_GROUP_ID=$(id -g) \
    -e DOCKER_ADMIN_USER=$(id -un) \
    -v "$(pwd)":/workdir \
    -v "$(dirname $HOME)":/home_host \
    dclong/jupyterhub-sagemath /scripts/sys/init.sh /scripts/sys/launch_jlab.sh

Use the JupyterHub Server

Add a New User to the JupyterHub Server

Use Spark in JupyterLab Notebook

Log Information

Detailed Information

Known Issues

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