|Peter Parente 27ba573645 Merge pull request #529 from nbonnotte/master||1 month ago|
|.github||1 year ago|
|all-spark-notebook||3 months ago|
|base-notebook||1 month ago|
|datascience-notebook||2 months ago|
|examples||7 months ago|
|internal||6 months ago|
|minimal-notebook||4 months ago|
|pyspark-notebook||4 months ago|
|r-notebook||2 months ago|
|scipy-notebook||2 months ago|
|tensorflow-notebook||4 months ago|
|test||3 months ago|
|.gitignore||1 year ago|
|.travis.yml||3 months ago|
|LICENSE.md||2 years ago|
|Makefile||3 months ago|
|README.md||2 months ago|
|conftest.py||3 months ago|
|requirements-test.txt||3 months ago|
Opinionated stacks of ready-to-run Jupyter applications in Docker.
If you're familiar with Docker, have it configured, and know exactly what you'd like to run, one of these commands should get you up and running:
# Run an ephemeral Jupyter Notebook server in a Docker container in the terminal foreground. # Note that any work saved in the container will be lost when it is destroyed with this config. # -ti: pseudo-TTY+STDIN open. # -rm: remove the container on exit. # -p: publish port to the host docker run -ti --rm -p 8888:8888 jupyter/<your desired stack>:<git-sha-tag> # Run a Jupyter Notebook server in a Docker container in the terminal foreground. # Any files written to ~/work in the container will be saved to the current working # directory on the host. docker run -ti --rm -p 8888:8888 -v "$PWD":/home/jovyan/work jupyter/<your desired stack>:<git-sha-tag> # Run an ephemeral Jupyter Notebook server in a Docker container in the background. # Note that any work saved in the container will be lost when it is destroyed with this config. # -d: detach, run container in background. # -P: Publish all exposed ports to random ports docker run -d -P jupyter/<your desired stack>:<git-sha-tag>
If this is your first time using Docker or any of the Jupyter projects, do the following to get started.
Here's a diagram of the
FROM relationships between all of the images defined in this project:
The following are quick-links to READMEs about each image and their Docker image tags on Docker Cloud:
Starting with git commit SHA 9bd33dcc8688:
jupyter/<stack name>on Docker Hub (e.g., all-spark-notebook → jupyter/all-spark-notebook).
latesttag in each Docker Hub repository tracks the
HEADreference on GitHub. This is a moving target and will make backward-incompatible changes regularly.
4.0on Docker Hub which point to images prior to our versioning scheme switch.
latestis a moving target which can change in backward-incompatible ways as packages and operating systems are updated.
cc9feab481f7. If you wish to continue using Python 2.x, pin to tag
tini -- start-notebook.shis the default Docker entrypoint-plus-command in every notebook stack. If you plan to modify it in any way, be sure to check the Notebook Options section of your stack's README to understand the consequences.
To build new images on Docker Cloud and publish them to the Docker Hub registry, do the following:
When there's a security fix in the Ubuntu base image, do the following in place of the last command:
ubuntu:16.04 SHA in the most-base images (e.g., base-notebook). Submit it as a regular PR and go through the build process. Expect the build to take a while to complete: every image layer will rebuild.
When there's a new stack definition, do the following before merging the PR with the new stack:
jupyterorg on Docker Cloud named after the stack folder in the git repo.
stacksteam permission to write to the repo.
jupyter/docker-stacksas the source repository.
When there's a new maintainer, do the following:
If automated builds have got you down, do the following:
docker loginwith your Docker Hub/Cloud credentials.
make retry/release-all successfully pushes the last of its images to Docker Hub (currently
jupyter/all-spark-notebook), Docker Hub invokes the webhook which updates the Docker build history wiki page.