If notebooks *.ipynb in github do not load, just paste links to https://nbviewer.jupyter.org/
Run this modified Jupyter docker with added Python packages and a default user: guest (1001,100)
Examples
https://github.com/ipython-books/cookbook-2nd-code
https://medium.com/@gongsta/how-to-use-pyspark-in-pycharm-ide-2fd8997b1cdd
see my notebooks in this repository
docker run -it --rm -p 8888:8888 -p 4040:4040 -e NB_USER=$(whoami) -e NB_UID=$(id -u) -e NB_GID=$(id -g) -v $(pwd):/home/guest/workspace 42n4/all-spark-notebook
Jupyter with the graphical gui
docker run -it --rm -p 8888:8888 -p 4040:4040 -e JUPYTER_ENABLE_LAB=yes -e NB_USER=$(whoami) -e NB_UID=$(id -u) -e NB_GID=$(id -g) -v $(pwd):/home/guest/work 42n4/all-spark-notebook
Build
You can pull my docker with all python packages (about 0.5h with a good internet connection)
docker pull 42n4/all-spark-notebook #pull my docker (about 14G in tar - all packages needed for machine learning)
or make it in five steps (about 1 hour on i7) - you can add your packages to Dockerfile:
1
git clone https://github.com/pwasiewi/jupyter-dockers
cd jupyter-dockers/base-notebook
# docker build --rm -t 42n4/base-notebook .
docker build --rm -t 42n4/$(basename `pwd`) .
2
cd ../minimal-notebook
# docker build --rm -t 42n4/minimal-notebook .
docker build --rm -t 42n4/$(basename `pwd`) .
3
cd ../scipy-notebook
# docker build --rm -t 42n4/scipy-notebook .
docker build --rm -t 42n4/$(basename `pwd`) .
4
cd ../pyspark-notebook
# docker build --rm -t 42n4/pyspark-notebook .
docker build --rm -t 42n4/$(basename `pwd`) .
5
cd ../all-spark-notebook
# docker build --rm -t 42n4/all-spark-notebook .
docker build --rm -t 42n4/$(basename `pwd`) .
docker login #docker-hub-user-login and pass to hub.docker.com
# docker push 42n4/all-spark-notebook
docker push 42n4/$(basename `pwd`) #send to docker-hub-user/docker-name
Jupyter Docker Stacks
Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools.
Quick Start
You can try a recent build of the jupyter/base-notebook image on mybinder.org by simply clicking the preceding link. Otherwise, the two examples below may help you get started if you have Docker installed know which Docker image you want to use, and want to launch a single Jupyter Notebook server in a container.
The User Guide on ReadTheDocs describes additional uses and features in detail.
Example 1: This command pulls the jupyter/scipy-notebook image tagged 17aba6048f44 from Docker Hub if it is not already present on the local host. It then starts a container running a Jupyter Notebook server and exposes the server on host port 8888. The server logs appear in the terminal. Visiting http://<hostname>:8888/?token=<token> in a browser loads the Jupyter Notebook dashboard page, where hostname is the name of the computer running docker and token is the secret token printed in the console. The container remains intact for restart after the notebook server exits.
docker run -p 8888:8888 jupyter/scipy-notebook:17aba6048f44
Example 2: This command performs the same operations as Example 1, but it exposes the server on host port 10000 instead of port 8888. Visiting http://<hostname>:10000/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console.::
docker run -p 10000:8888 jupyter/scipy-notebook:17aba6048f44
Example 3: This command pulls the jupyter/datascience-notebook image tagged 9b06df75e445 from Docker Hub if it is not already present on the local host. It then starts an ephemeral container running a Jupyter Notebook server and exposes the server on host port 10000. The command mounts the current working directory on the host as /home/guest/work in the container. The server logs appear in the terminal. Visiting http://<hostname>:10000/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console. Docker destroys the container after notebook server exit, but any files written to ~/work in the container remain intact on the host.
docker run --rm -p 10000:8888 -e JUPYTER_ENABLE_LAB=yes -v "$PWD":/home/guest/work jupyter/datascience-notebook:9b06df75e445
Contributing
Please see the Contributor Guide on ReadTheDocs for information about how to contribute package updates, recipes, features, tests, and community maintained stacks.
Alternatives
- jupyter/repo2docker - Turn git repositories into Jupyter-enabled Docker Images
- openshift/source-to-image - A tool for building/building artifacts from source and injecting into docker images
- jupyter-on-openshift/jupyter-notebooks - OpenShift compatible S2I builder for basic notebook images