Jupyter Notebook Viewer
Run this locally to get most of the features of nbviewer on your own network.
If you have
docker installed, you can pull and run the currently built version of the Docker container by
$ docker pull jupyter/nbviewer $ docker run -p 8080:8080 jupyter/nbviewer
It automatically gets built with each push to
master, so you'll always be able to get the freshest copy.
For speed and friendliness to GitHub, be sure to set
$ docker run -p 8080:8080 -e 'GITHUB_OAUTH_KEY=YOURKEY' \ -e 'GITHUB_OAUTH_SECRET=YOURSECRET' \ jupyter/nbviewer
Or to use your GitHub personal access token, you can set just
To use nbviewer on against your own GitHub Enterprise instance you need to set
The relevant API endpoints for GitHub Enterprise are prefixed with
You must also specify your
API_TOKEN as explained above. For example:
$ docker run -p 8080:8080 -e 'GITHUB_OAUTH_KEY=YOURKEY' \ -e 'GITHUB_OAUTH_SECRET=YOURSECRET' \ -e 'GITHUB_API_URL=https://ghe.example.com/api/v3/' \ jupyter/nbviewer
With this configured all GitHub API requests will go to you Enterprise instance so you can view all of your internal notebooks.
You can build a docker image that uses your local branch
docker build -t nbviewer .
docker run -p 8080:8080 nbviewer
With Docker Compose
The Notebook Viewer uses
memcache in production. To locally try out this
setup, a docker-compose configuration is
provided to easily start/stop the
memcache containers together:
The Notebook Viewer requires several binary packages to be installed on your system. The primary ones are
libmemcached-dev libcurl4-openssl-dev pandoc libevent-dev. Package names may differ on your system, see salt-states for more details.
If they are installed, you can install the required Python packages via pip.
pip install -r requirements.txt`
Static assets are maintained with
$ cd <path to repo> $ invoke bower $ invoke less [-d]
This will download the relevant assets into
nbviewer/static/components and create the built assets in
invoke less to create a CSS sourcemap, useful for debugging.
$ cd <path to repo> $ python -m nbviewer --debug --no-cache
This will automatically relaunch the server if a change is detected on a python file, and not cache any results. You can then just do the modifications you like to the source code and/or the templates then refresh the pages.