https://github.com/korniichuk/scipy-k3d-notebook
The scipy-k3d-notebook stack of ready-to-run "Jupyter Notebook Scientific Python with K3D" application in Docker
https://github.com/korniichuk/scipy-k3d-notebook
Last synced: 2 months ago
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The scipy-k3d-notebook stack of ready-to-run "Jupyter Notebook Scientific Python with K3D" application in Docker
- Host: GitHub
- URL: https://github.com/korniichuk/scipy-k3d-notebook
- Owner: korniichuk
- License: unlicense
- Created: 2015-11-27T16:46:16.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2016-02-26T00:05:27.000Z (over 9 years ago)
- Last Synced: 2025-01-17T08:28:11.674Z (9 months ago)
- Homepage:
- Size: 10.7 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- License: LICENSE.txt
Awesome Lists containing this project
README
.. contents:: Table of contents
:depth: 2
Full description
================
The `korniichuk/scipy-notebook `_ Docker image with K3D.
Docker Hub
==========
The `korniichuk/scipy-k3d-notebook `_ repo.
Quickstart
==========
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 without authentication configured::
$ docker run -d -p 8888:8888 -u root korniichuk/scipy-k3d-notebook
User guide
==========
Detached
--------
To start a container in detached mode, you use ``-d`` or ``--detach`` option. By design, containers started in detached mode exit when the root process used to run the container exits. A container in detached mode cannot be automatically removed when it stops, this means you cannot use the ``--rm`` option with ``-d`` option.
::
$ docker run -d -p HOST_PORT:CONTAINER_PORT -u USERNAME IMAGE
$ docker run -d -p 8888:8888 -u root korniichuk/scipy-k3d-notebook
or::
$ docker run --detach -p HOST_PORT:CONTAINER_PORT -u USERNAME IMAGE
$ docker run --detach -p 8888:8888 -u root korniichuk/scipy-k3d-notebook
Where:
* ``-d`` or ``--detach`` -- run container in background and print container ID.
Ports
-----
You can bind Docker containers to specific ports using the ``-p`` or ``--publish`` option, for example::
$ docker run -d -p HOST_PORT:CONTAINER_PORT -u USERNAME IMAGE
$ docker run -d -p 8888:8888 -u root korniichuk/scipy-k3d-notebook
or::
$ docker run -d --publish HOST_PORT:CONTAINER_PORT -u USERNAME IMAGE
$ docker run -d --publish 8888:8888 -u root korniichuk/scipy-k3d-notebook
Where:
* ``-p`` or ``--publish`` -- publish a container's port(s) to the host.
Users
-----
You can start a container with ``root`` user by passing the ``-u`` option::
$ docker run -d -p HOST_PORT:CONTAINER_PORT -u USERNAME IMAGE
$ docker run -d -p 8888:8888 -u root korniichuk/scipy-k3d-notebook
or::
$ docker run -d -p HOST_PORT:CONTAINER_PORT --user USERNAME IMAGE
$ docker run -d -p 8888:8888 --user root korniichuk/scipy-k3d-notebook
Where:
* ``-u`` or ``--user`` -- username or UID (format: [:]).
Interactive processes
---------------------
For interactive processes (like a shell), you must use ``-i -t`` together in order to allocate a tty for the container process. ``-i -t`` is often written ``-it``::
$ docker run -it IMAGE COMMAND
$ docker run -it korniichuk/scipy-k3d-notebook bash
Where:
* ``-i`` or ``--interactive`` -- keep STDIN open even if not attached,
* ``-t`` or ``--tty`` -- allocate a pseudo-TTY.
Own try.jupyter.org
===================
**First**, the following commands launches a docker container for each user that requests one::
$ export TOKEN=$( head -c 30 /dev/urandom | xxd -p )
$ docker run --net=host -d -e CONFIGPROXY_AUTH_TOKEN=$TOKEN \
--name=proxy jupyter/configurable-http-proxy \
--default-target http://127.0.0.1:9999
$ docker run --net=host -d -e CONFIGPROXY_AUTH_TOKEN=$TOKEN \
-v /var/run/docker.sock:/docker.sock jupyter/tmpnb python orchestrate.py \
--image='korniichuk/scipy-k3d-notebook' --command="ipython notebook \
--NotebookApp.base_url={base_path} --ip=0.0.0.0 --port {port}"
**Second**, visit your host on port 8000.