Jupyter nbviewer is the web application behind The Jupyter Notebook Viewer, which is graciously hosted by Rackspace.

Run this locally to get most of the features of nbviewer on your own network.

If you need help using or installing Jupyter Notebook Viewer, please use the jupyter/help issue tracker.

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 GITHUB_OAUTH_KEY and GITHUB_OAUTH_SECRET:

$ 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 GITHUB_API_TOKEN.

To use nbviewer on your own GitHub Enterprise instance you need to set GITHUB_API_URL. The relevant API endpoints for GitHub Enterprise are prefixed with http://hostname/api/v3. You must also specify your OAUTH or 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 your Enterprise instance so you can view all of your internal notebooks.

You can build a docker image that uses your local branch.

$ cd <path to repo>
$ docker build -t nbviewer .

$ cd <path to repo>
$ docker run -p 8080:8080 nbviewer

The Notebook Viewer uses memcached in production. To locally try out this setup, a docker-compose configuration is provided to easily start/stop the nbviewer and memcached containers together from a your current branch. You will need to install docker prior to this.

$ cd <path to repo>
$ pip install docker-compose
$ docker-compose up

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.

$ cd <path to repo>
$ pip install -r requirements.txt

Static assets are maintained with bower and less (which require having npm installed), and the invoke python module.

$ cd <path to repo>
$ pip install -r requirements-dev.txt
$ npm install
$ invoke bower
$ invoke less [-d]

This will download the relevant assets into nbviewer/static/components and create the built assets in nbviewer/static/build.

Pass -d or --debug to 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.

nose is used to run the test suite. The tests currently make calls to external APIs such as GitHub, so it is best to use your Github API Token when running:

$ cd <path to repo>
$ pip install -r requirements-dev.txt
$ GITHUB_API_TOKEN=<your token> python setup.py test

Providers are sources of notebooks and directories of notebooks and directories.

nbviewer ships with several providers

• url
• gist
• github
• local

There are several already additional providers proposed/requested. Some providers are more involved than others, and some, such as those which would require user authentication, will take some work to support properly.

A provider is implemented as a python module, which can expose a few functions:

If you just need to rewrite URLs (or URIs) of another site/namespace, implement uri_rewrites, which will allow the front page to transform an arbitrary string (usually an URI fragment), escape it correctly, and turn it into a "canonical" nbviewer URL. See the dropbox provider for a simple example of rewriting URLs without using a custom API client.

If you need custom logic, such as connecting to an API, implement default_handlers. See the github provider for a complex example of providing multiple handlers.

While you could re-implement upstream HTTP error handling, a small convenience method is provided for intercepting HTTP errors. On a given URL handler that inherits from BaseHandler, overload the client_error_message and re-call it with your message (or None). See the gist provider for an example of customizing the error message.

Formats are ways to present notebooks to the user.

nbviewer ships with three providers:

• html
• slides
• script

If you'd like to write a new format, open a ticket, or speak up on [gitter][]! We have some work yet to do to support your next big thing in notebook publishing, and we'd love to here from you.

You can run the viewer as a JupyterHub 0.7+ service. Running the viewer as a service prevents users who have not authenticated with the Hub from acccessing the nbviewer instance. This setup can be useful for protecting access to local notebooks rendered with the --localfiles option.

Add an entry like the following to your jupyterhub_config.py to have it start nbviewer as a managed service:

c.JupyterHub.services = [
    {
        # the /services/<name> path for accessing the notebook viewer
        'name': 'nbviewer',
        # the interface and port nbviewer will use
        'url': 'http://127.0.0.1:9000',
        # the api token for nbviewer to check user auth
        'api_token': 'my-secret-nbviewer-token',
        # command to start the nbviewer
        'command': ['python', '-m', 'nbviewer']
    }
]

The nbviewer instance will automatically read the various JUPYTERHUB_* environment variables and configure itself accordingly. You can also run the nbviewer instance as an externally managed JupyterHub service, but must set the requisite environment variables yourself.