monkeyking/docs/source/examples/Notebook/rstversions/JavaScript Notebook Extensions.rst

`View the original notebook on nbviewer <http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/JavaScript%20Notebook%20Extensions.ipynb>`__

Embracing web standards
=======================

One of the main reasons why we developed the current notebook web
application was to embrace the web technology.

By being a pure web application using HTML, Javascript, and CSS, the
Notebook can get all the web technology improvement for free. Thus, as
browser support for different media extend, the notebook web app should
be able to be compatible without modification.

This is also true with performance of the User Interface as the speed of
Javascript VM increases.

The other advantage of using only web technology is that the code of the
interface is fully accessible to the end user and is modifiable live.
Even if this task is not always easy, we strive to keep our code as
accessible and reusable as possible. This should allow us - with minimum
effort - development of small extensions that customize the behavior of
the web interface.

Tampering with the Notebook application
---------------------------------------

The first tool that is available to you and that you should be aware of
are browser "developers tool". The exact naming can change across
browser and might require the installation of extensions. But basically
they can allow you to inspect/modify the DOM, and interact with the
javascript code that runs the frontend.

-  In Chrome and Safari, Developer tools are in the menu
   ``View > Developer > Javascript Console``
-  In Firefox you might need to install
   `Firebug <http://getfirebug.com/>`__

Those will be your best friends to debug and try different approaches
for your extensions.

Injecting JS
~~~~~~~~~~~~

Using magics
^^^^^^^^^^^^

The above tools can be tedious for editing edit long JavaScript files.
Therefore we provide the ``%%javascript`` magic. This allows you to
quickly inject JavaScript into the notebook. Still the javascript
injected this way will not survive reloading. Hence, it is a good tool
for testing an refining a script.

You might see here and there people modifying css and injecting js into
the notebook by reading file(s) and publishing them into the notebook.
Not only does this often break the flow of the notebook and make the
re-execution of the notebook broken, but it also means that you need to
execute those cells in the entire notebook every time you need to update
the code.

This can still be useful in some cases, like the ``%autosave`` magic
that allows you to control the time between each save. But this can be
replaced by a JavaScript dropdown menu to select the save interval.

.. code:: python

    ## you can inspect the autosave code to see what it does.
    %autosave??

custom.js
^^^^^^^^^

To inject Javascript we provide an entry point: ``custom.js`` that
allows the user to execute and load other resources into the notebook.
Javascript code in ``custom.js`` will be executed when the notebook app
starts and can then be used to customize almost anything in the UI and
in the behavior of the notebook.

``custom.js`` can be found in the Jupyter dir. You can share your
custom.js with others.

Back to theory
''''''''''''''

.. code:: python

    from jupyter_core.paths import jupyter_config_dir
    jupyter_dir = jupyter_config_dir()
    jupyter_dir

and custom js is in

.. code:: python

    import os.path
    custom_js_path = os.path.join(jupyter_dir, 'custom', 'custom.js')

.. code:: python

    #  my custom js
    if os.path.isfile(custom_js_path):
        with open(custom_js_path) as f:
            print(f.read())
    else:
        print("You don't have a custom.js file")  

Note that ``custom.js`` is meant to be modified by user. When writing a
script, you can define it in a separate file and add a line of
configuration into ``custom.js`` that will fetch and execute the file.

**Warning** : even if modification of ``custom.js`` takes effect
immediately after browser refresh (except if browser cache is
aggressive), *creating* a file in ``static/`` directory needs a **server
restart**.

Exercise :
----------

-  Create a ``custom.js`` in the right location with the following
   content:

   .. code:: javascript

       alert("hello world from custom.js")

-  Restart your server and open any notebook.
-  Be greeted by custom.js

Have a look at `default
custom.js <https://github.com/jupyter/notebook/blob/4.0.x/notebook/static/custom/custom.js>`__,
to see it's content and for more explanation.

For the quick ones :
~~~~~~~~~~~~~~~~~~~~

We've seen above that you can change the autosave rate by using a magic.
This is typically something I don't want to type every time, and that I
don't like to embed into my workflow and documents. (readers don't care
what my autosave time is). Let's build an extension that allows us to do
it.

Create a dropdown element in the toolbar (DOM
``Jupyter.toolbar.element``), you will need

-  ``Jupyter.notebook.set_autosave_interval(miliseconds)``
-  know that 1 min = 60 sec, and 1 sec = 1000 ms

.. code:: javascript


    var label = jQuery('<label/>').text('AutoScroll Limit:');
    var select = jQuery('<select/>')
         //.append(jQuery('<option/>').attr('value', '2').text('2min (default)'))
         .append(jQuery('<option/>').attr('value', undefined).text('disabled'))

         // TODO:
         //the_toolbar_element.append(label)
         //the_toolbar_element.append(select);
         
    select.change(function() {
         var val = jQuery(this).val() // val will be the value in [2]
         // TODO
         // this will be called when dropdown changes

    });

    var time_m = [1,5,10,15,30];
    for (var i=0; i < time_m.length; i++) {
         var ts = time_m[i];
                                              //[2]   ____ this will be `val` on [1]  
                                              //     | 
                                              //     v 
         select.append($('<option/>').attr('value', ts).text(thr+'min'));
         // this will fill up the dropdown `select` with
         // 1 min
         // 5 min
         // 10 min
         // 10 min
         // ...
    }

A non-interactive example first
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

I like my cython to be nicely highlighted

.. code:: javascript

    Jupyter.config.cell_magic_highlight['magic_text/x-cython'] = {}
    Jupyter.config.cell_magic_highlight['magic_text/x-cython'].reg = [/^%%cython/]

``text/x-cython`` is the name of CodeMirror mode name, ``magic_`` prefix
will just patch the mode so that the first line that contains a magic
does not screw up the highlighting. ``reg``\ is a list or regular
expression that will trigger the change of mode.

Get more documentation
^^^^^^^^^^^^^^^^^^^^^^

Sadly, you will have to read the js source file (but there are lots of
comments) and/or build the JavaScript documentation using yuidoc. If you
have ``node`` and ``yui-doc`` installed:

.. code:: bash

    $ cd ~/jupyter/notebook/notebook/static/notebook/js/
    $ yuidoc . --server
    warn: (yuidoc): Failed to extract port, setting to the default :3000
    info: (yuidoc): Starting YUIDoc@0.3.45 using YUI@3.9.1 with NodeJS@0.10.15
    info: (yuidoc): Scanning for yuidoc.json file.
    info: (yuidoc): Starting YUIDoc with the following options:
    info: (yuidoc):
    { port: 3000,
      nocode: false,
      paths: [ '.' ],
      server: true,
      outdir: './out' }
    info: (yuidoc): Scanning for yuidoc.json file.
    info: (server): Starting server: http://127.0.0.1:3000

and browse http://127.0.0.1:3000 to get documentation

Some convenience methods
^^^^^^^^^^^^^^^^^^^^^^^^

By browsing the documentation you will see that we have some convenience
methods that allows us to avoid re-inventing the UI every time :

.. code:: javascript

    Jupyter.toolbar.add_buttons_group([
            {
                 'label'   : 'run qtconsole',
                 'icon'    : 'icon-terminal', // select your icon from 
                                              // http://fortawesome.github.io/Font-Awesome/icons/
                 'callback': function(){Jupyter.notebook.kernel.execute('%qtconsole')}
            }
            // add more button here if needed.
            ]);

with a `lot of
icons <http://fortawesome.github.io/Font-Awesome/icons/>`__ you can
select from.

Cell Metadata
-------------

The most requested feature is generally to be able to distinguish an
individual cell in the notebook, or run a specific action with them. To
do so, you can either use ``Jupyter.notebook.get_selected_cell()``, or
rely on ``CellToolbar``. This allows you to register a set of actions
and graphical elements that will be attached to individual cells.

Cell Toolbar
~~~~~~~~~~~~

You can see some example of what can be done by toggling the
``Cell Toolbar`` selector in the toolbar on top of the notebook. It
provides two default ``presets`` that are ``Default`` and ``slideshow``.
Default allows the user to edit the metadata attached to each cell
manually.

First we define a function that takes at first parameter an element on
the DOM in which to inject UI element. The second element is the cell
this element wis registered with. Then we will need to register that
function and give it a name.

Register a callback
^^^^^^^^^^^^^^^^^^^

.. code:: python

    %%javascript
    var CellToolbar = Jupyter.CellToolbar
    var toggle =  function(div, cell) {
         var button_container = $(div)
    
         // let's create a button that shows the current value of the metadata
         var button = $('<button/>').addClass('btn btn-mini').text(String(cell.metadata.foo));
    
         // On click, change the metadata value and update the button label
         button.click(function(){
                     var v = cell.metadata.foo;
                     cell.metadata.foo = !v;
                     button.text(String(!v));
                 })
    
         // add the button to the DOM div.
         button_container.append(button);
    }
    
     // now we register the callback under the name foo to give the
     // user the ability to use it later
     CellToolbar.register_callback('tuto.foo', toggle);

Registering a preset
^^^^^^^^^^^^^^^^^^^^

This function can now be part of many ``preset`` of the CellToolBar.

.. code:: python

    %%javascript
    Jupyter.CellToolbar.register_preset('Tutorial 1',['tuto.foo','default.rawedit'])
    Jupyter.CellToolbar.register_preset('Tutorial 2',['slideshow.select','tuto.foo'])

You should now have access to two presets :

-  Tutorial 1
-  Tutorial 2

And check that the buttons you defined share state when you toggle
preset. Also check that the metadata of the cell is modified when you
click the button, and that when saved on reloaded the metadata is still
available.

Exercise:
^^^^^^^^^

Try to wrap the all code in a file, put this file in
``{jupyter_dir}/custom/<a-name>.js``, and add

::

    require(['custom/<a-name>']);

in ``custom.js`` to have this script automatically loaded in all your
notebooks.

``require`` is provided by a `javascript
library <http://requirejs.org/>`__ that allow you to express dependency.
For simple extension like the previous one we directly mute the global
namespace, but for more complex extension you could pass a callback to
``require([...], <callback>)`` call, to allow the user to pass
configuration information to your plugin.

In Python lang,

.. code:: javascript

    require(['a/b', 'c/d'], function( e, f){
        e.something()
        f.something()
    })

could be read as

.. code:: python

    import a.b as e
    import c.d as f
    e.something()
    f.something()

See for example @damianavila `"ZenMode"
plugin <https://github.com/ipython-contrib/IPython-notebook-extensions/blob/master/custom.example.js#L34>`__
:

.. code:: javascript


    // read that as
    // import custom.zenmode.main as zenmode
    require(['custom/zenmode/main'],function(zenmode){
        zenmode.background('images/back12.jpg');
    })

For the quickest
^^^^^^^^^^^^^^^^

Try to use `the
following <https://github.com/ipython/ipython/blob/1.x/IPython/html/static/notebook/js/celltoolbar.js#L367>`__
to bind a dropdown list to ``cell.metadata.difficulty.select``.

It should be able to take the 4 following values :

-  ``<None>``
-  ``Easy``
-  ``Medium``
-  ``Hard``

We will use it to customiZe the output of the converted notebook
depending on the tag on each cell

.. code:: python

    %load soln/celldiff.js

`View the original notebook on nbviewer <http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/JavaScript%20Notebook%20Extensions.ipynb>`__