A server extension for jupyter notebook which provides configuration interfaces for notebook extensions (nbextensions).

The jupyter_nbextensions_configurator jupyter server extension provides graphical user interfaces for configuring which nbextensions are enabled (load automatically for every notebook), and display their readme files. In addition, for extensions which include an appropriate yaml descriptor file (see below), the interface also provides controls to configure the extensions' options.

This project was spun out of work from ipython-contrib/IPython-notebook-extensions.

The installation has three steps:

1. Installing the pip package. This should be as simple as

   pip install jupyter_nbextensions_configurator
   

2. Configuring the notebook server to load the server extension. A jupyter subcommand is provided for this. You can enable the serverextension for the current user with

   jupyter nbextensions_configurator enable --user
   

   The command accepts the same flags as the jupyter serverextension command provided by notebook versions >= 4.2, including --system to enable in system-wide config (the default), or --sys-prefix to enable in config files inside python's sys.prefix, such as for a virtual environment. The provided jupyter nbextensions_configurator command can also be used to disable, and since it is essentially a wrapper around jupyter serverextension, for notebook >= 4.2, one can use that command equivalently.

3. Finally, you'll need to restart the notebook server. Once restarted, you should be able to find the configurator user interfaces as described below.

Once jupyter_nbextensions_configurator is installed and enabled, and your notebook server has been restarted, you should be able to find the nbextensions configuration interface at the url <base_url>nbextensions, where <base_url> is described below (for simple installs, it's usually just /, so the UI is at /nbextensions).

For most single-user notebook servers, the dashboard (the file-browser view) is at

http://localhost:8888/tree

So the base_url is the part between the host (http://localhost:8888) and tree, so in this case it's the default value of just /. If you have a non-default base url (such as with JupyterHub), you'll need to prepend it to the url. So, if your dashboard is at

http://localhost:8888/custom/base/url/tree

then you'll find the configurator UI page at

http://localhost:8888/custom/base/url/nbextensions

In addition to the main standalone page, the nbextensions configurator interface is also available as a tab on the dashboard, once it's been configured to appear there. To do this, go to the /nbextensions url described above, and enable the nbextension Nbextensions dashboard tab.

You don't need to know about the yaml files in order simply to use jupyter_nbextensions_configurator. A notebook extension is 'found' by the jupyter_nbextensions_configurator server extension when a special yaml file describing the nbextension and its options is found in the notebook server's nbextensions_path. The yaml file can have any name with the extension .yaml or .yml, and describes the notebook extension and its options to jupyter_nbextensions_configurator.

The case-sensitive keys in the yaml file are as follows:

• Type, (required) a case-sensitive identifier, must be IPython Notebook Extension or Jupyter Notebook Extension
• Main, (required) the main javascript file that is loaded, typically main.js
• Name, the name of the extension
• Description, a short explanation of the extension
• Link, a URL for more documentation. If this is a relative url with a .md extension (recommended!), the markdown readme is rendered in the configurator UI.
• Icon, a URL for a small icon for the configurator UI (rendered 120px high, should preferably end up 400px wide. Recall HDPI displays may benefit from a 2x resolution icon).
• Compatibility, Jupyter major version compatibility, e.g. 3.x or 4.x, 3.x 4.x, 3.x, 4.x, 5.x
• Parameters, an optional list of configuration parameters. Each item is a dictionary with (some of) the following keys
  • name, (required) the name used to store the configuration variable in the config json. It follows a json-like structure, so you can use . to separate sub-objects e.g. myextension.buttons_to_add.play.
  • description, a description of the configuration parameter
  • default, a default value used to populate the tag in the configurator UI, if no value is found in config. Note that this is more of a hint to the user than anything functional - since it's only set in the yaml file, the javascript implementing the extension in question might actually use a different default, depending on the implementation.
  • input_type, controls the type of html tag used to render the parameter in the configurator UI. Valid values include text, textarea, checkbox, [html5 input tags such as number, url, color, ...], plus a final type of list
  • list_element, a dictionary with the same default and input_type keys as a Parameters entry, used to render each element of the list for parameters with input_type list
  • finally, extras such as min, step and max may be used by number tags for validation

Example:

Type: Jupyter Notebook Extension
Name: Limit Output
Description: This extension limits the number of characters that can be printed below a codecell
Link: readme.md
Icon: icon.png
Main: main.js
Compatibility: 4.x
Parameters:
- name: limit_output
  description: Number of characters to limit output to
  input_type: number
  default: 10000
  step: 1
  min: 0
- name: limit_output_message
  description: Message to append when output is limited
  input_type: text
  default: '**OUTPUT MUTED**'

If you encounter problems with this server extension, you can:

• check the issues page for the github repository. If you can't find one that fits your problem, please create a new one!
• ask in the project's gitter chatroom

For debugging, useful information can (sometimes) be found by:

• Checking for error messages in the browser's JavaScript console.
• Checking for messages in the notebook server's logs. This is particularly useful when the server is run with the --debug flag, to get as many logs as possible.

First public release!

Remove tests dependency on ipython_genutils