docs/source/interactive/htmlnotebook.txt

.. _htmlnotebook:

The IPython Notebook
====================

The IPython Notebook is part of the IPython package, which aims to provide a powerful, interactive approach to scientific computation.
The IPython Notebook extends the previous text-console-based approach, and the later Qt console, in a qualitatively new diretion, providing a web-based application suitable for capturing the whole scientific computation process.


.. seealso::

    :ref:`Installation requirements <installnotebook>` for the Notebook.


Basic structure
---------------

The IPython Notebook combines two components:

* **The IPython Notebook web application**:

  The IPython Notebook web app is a browser-based tool for interactive authoring of literate computations, in which explanatory text, mathematics,computations and rich media output may be combined. Input and output are stored in persistent cells that may be edited in-place.

* **Notebook documents**:

  *Notebook documents*, or *notebooks*, are plain text documents which record all inputs and outputs of the computations, interspersed with text, mathematics and HTML 5 representations of objects, in a literate style.

Since the similarity in names can lead to some confusion, in the documentation we will  use capitalization of the word "notebook" to distinguish the *N*otebook app and *n*otebook documents, thinking of the Notebook app as being a proper noun. We will also always refer to the "Notebook app" when we are referring to the browser-based interface, and usually to "notebook documents", instead of "notebooks", for added precision.

We refer to the current state of the computational process taking place in the Notebook app, i.e. the (numbered) sequence of input and output cells, as the 
*notebook space*. Notebook documents provide an *exact*, *one-to-one* record of all the content in the notebook space, as a plain text file in JSON format. The Notebook app automatically saves, at certain intervals, the contents of the notebook space to a notebook document stored on disk, with the same name as the title of the notebook space, and the file extension ``.ipynb`. For this reason, there is no confusion about using the same word "notebook" for both the notebook space and the corresonding notebook document, since they are really one and the same concept (we could say that they are "isomorphic").


Main features of the IPython Notebook web app
---------------------------------------------

The main features of the IPython Notebook app include:

* In-browser editing for code, with automatic syntax highlighting and indentation and tab completion/introspection.
* Literate combination of code with rich text using the Markdown markup language.
* Mathematics is easily included within the Markdown using LaTeX notation, and rendered natively by MathJax.
* Displays rich data representations (e.g. HTML / LaTeX / SVG) as the result of computations.
* Publication-quality figures in a range of formats (SVG / PNG), rendered by the ``matplotlib`` library, may be included inline and exported.


Notebook documents
------------------

Notebook document files are just standard text files with the extension 
``.ipynb``, stored in the working directory on your computer. This file can be easily put under version control and shared with colleagues.

Despite the fact that the notebook documents are plain text files, they use 
the JSON format in order to store a *complete*, *reproducible*, *one-to-one* copy of the state of the computational state as it is inside the Notebook app. 
All computations carried out, and the corresponding results obtained, can be 
combined in a literate way, mixing them with descriptive text, mathematics, 
and HTML 5 representations of objects.

Notebooks may easily be exported to a range of static formats, including 
HTML (for example, for blog posts), PDF and slide shows.
Furthermore, any publicly available notebook may be shared via the 
`IPython Notebook Viewer <http://nbviewer.ipython.org>`_ service, which will 
provide it as a static web page. The results may thus be shared without having to install anything.

See :ref:`our installation documentation <install_index>` for directions on
how to install the notebook and its dependencies.

.. note::

   You can start more than one notebook server at the same time, if you want to
   work on notebooks in different directories.  By default the first notebook
   server starts on port 8888, and later notebook servers search for  ports near
   that one.  You can also manually specify the port with the ``--port``
   option.
   

Starting up the IPython Notebook web app
----------------------------------------

You can start running the Notebook web app using the following command::

    $ ipython notebook

The landing page of the notebook server application, the *dashboard*, shows the notebooks currently available in the *working directory* (the directory from which the notebook was started).
You can create new notebooks from the dashboard with the ``New Notebook``
button, or open existing ones by clicking on their name.
You can also drag and drop ``.ipynb`` notebooks and standard ``.py`` Python source code files into the notebook list area.

``.py`` files will be imported into the IPython Notebook as a notebook with the same name, but an ``.ipynb`` extension, located in the working directory.  The notebook created will have just one cell, which will contain all the 
code in the ``.py`` file. You can later manually partition this into individual cells using the ``Edit | Split Cell`` menu option, or the :kbd:`Ctrl-m -` keyboard shortcut.

.. Alternatively, prior to importing the ``.py``, you can manually add ``# <nbformat>2</nbformat>`` at the start of the file, and then add separators for text and code cells, to get a cleaner import with the file already broken into individual cells.


When you open or create a new notebook, your browser tab will reflect the name of that notebook, prefixed with "IPy".
The URL is currently not meant to be human-readable and is not persistent across invocations of the notebook server; however, this will change in a future version of IPython.


The IPython Notebook web app is based on a server-client structure. 
This server uses a two-process kernel architecture based on ZeroMQ, as well as Tornado for serving HTTP requests. Other clients may connect to the same underlying IPython kernel; see below.




Notebook user interface
-----------------------

When you open a new notebook document in the Notebook, you will be presented with the title associated to the notebook space/document, a *menu bar*, a *toolbar* and an empty *input cell*.

Notebook title
~~~~~~~~~~~~~~
The title of the notebook document that is currently being edited is displayed at the top of the page, next to the ``IP[y]: Notebook`` logo. This title may be edited directly by clicking on it. The title is reflected in the name of the ``.ipynb`` notebook document file that is saved.

Menu bar
~~~~~~~~
The menu bar presents different options that may be used to manipulate the way the Notebook functions.

Toolbar
~~~~~~~
The tool bar gives a quick way of accessing the most-used operations within the Notebook, by clicking on an icon.


Input cells
-----------
Input cells are at the core of the functionality of the IPython Notebook.
They are regions in the document in which you can enter different types of text and commands. To *execute* or *run* the *current cell*, i.e. the cell under the cursor, you can use the :kbd:`Shift-Enter` key combination. 
This tells the Notebook app to perform the relevant operation for each type of cell (see below), and then to display the resulting output.

The notebook consists of a sequence of input cells, labelled ``In[n]``, which may be executed in a non-linear way, and outputs ``Out[n]``, where ``n`` is a number which denotes the order in which the cells were executed over the history of the computational process. The contents of all of these cells are accessible as Python variables with the same names, forming a complete record of the history of the computation.


Basic workflow
--------------
The normal workflow in a notebook is, then, quite similar to a standard IPython session, with the difference that you can edit cells in-place multiple 
times until you obtain the desired results, rather than having to 
rerun separate scripts with the ``%run`` magic command. (Magic commands do, however, also work in the notebook; see below).   

Typically, you will work on a computational problem in pieces, organizing related ideas into cells and moving forward once previous parts work correctly. This is much more convenient for interactive exploration than breaking up a computation into scripts that must be executed together, as was previously necessary, especially if parts of them take a long time to run

The only significant limitation that the Notebook currently has, compared to the Qt console, is that it cannot run any code that expects input from the kernel (such as scripts that call :func:`raw_input`).  Very importantly, this means that the ``%debug`` magic does *not* currently work in the notebook!  

This limitation will be overcome in the future, but in the meantime, there is a simple solution for debugging: you can attach a Qt console to your existing notebook kernel, and run ``%debug`` from the Qt console.
If your notebook is running on a local computer (i.e. if you are accessing it via your localhost address at ``127.0.0.1``), then you can just type 
``%qtconsole`` in the notebook and a Qt console will open up, connected to that same kernel.

At certain moments, it may be necessary to interrupt a particularly long calculation, or even to kill the entire computational process. This may be achieved by interrupting or restarting the kernel, respectively.
After a kernel restart, it as if the notebook were loaded afresh.


A notebook may be downloaded in either ``.ipynb`` or raw ``.py`` form from the menu option ``File | Download as``.
Choosing the ``.py`` option downloads a Python ``.py`` script, in which all output has been removed and the content of Markdown cells 
in comment areas.  See ref:`below <notebook_format>` for more details on the
notebook format.

    
.. warning::

   While in simple cases you can "roundtrip" a notebook to Python, edit the
   Python file, and then import it back without loss of main content, this is in general *not guaranteed to work*.  First, there is extra metadata
   saved in the notebook that may not be saved to the ``.py`` format.  And as
   the notebook format evolves in complexity, there will be attributes of the
   notebook that will not survive a roundtrip through the Python form.  You
   should think of the Python format as a way to output a script version of a
   notebook and the import capabilities as a way to load existing code to get a
   notebook started.  But the Python version is *not* an alternate notebook
   format.


Keyboard shortcuts
------------------
All actions in the notebook can be achieved with the mouse, but 
keyboard shortcuts are also available for the most common ones, so that productive use of the notebook can be achieved with minimal mouse usage. The main shortcuts to remember are the following:

* :kbd:`Shift-Enter`: 
    Execute the current cell, show output (if any), and jump to the next cell below. If :kbd:`Shift-Enter` is invoked on the last input cell, a new code cell will also be created. Note that in the notebook, typing :kbd:`Enter` on its own *never* forces execution, but rather just inserts a new line in the current input cell. In the Notebook it is thus always necessary to use :kbd:`Shift-Enter` to execute the cell (or use the ``Cell | Run`` menu item).

* :kbd:`Ctrl-Enter`: 
    Execute the current cell as if it were in "terminal mode", where any output is shown, but the cursor *remains* in the current cell. This is convenient for doing quick experiments in place, or for querying things like filesystem content, without needing to create additional cells that you may not want to be saved in the notebook.

* :kbd:`Alt-Enter`: 
    Executes the current cell, shows the output, and inserts a *new* input cell between the current cell and the adjacent cell (if one exists). This  is thus a shortcut for the sequence :kbd:`Shift-Enter`, :kbd:`Ctrl-m a`.
    (:kbd:`Ctrl-m a` adds a new cell below the current one.)
  


* :kbd:`Ctrl-m`: 
  This is the prefix for *all* other shortcuts, which consist of :kbd:`Ctrl-m` followed by a single letter or character. For example, if you type :kbd:`Ctrl-m h` (that is, the sole letter :kbd:`h` after :kbd:`Ctrl-m`), IPython will show you all the available keyboard shortcuts.
   

Input cell types
----------------
Each IPython input cell has a *cell type*, of which there is a restricted number. The type of a cell may be set by using the cell type dropdown on the toolbar, or via the following keyboard shortcuts:

* **code**: :kbd:`Ctrl-m y`
* **markdown**: :kbd:`Ctrl-m m`
* **raw**: :kbd:`Ctrl-m t`
* **heading**: :kbd:`Ctrl-m 1` - :kbd:`Ctrl-m 6`

Upon initial creation, each input cell is by default a code cell.


Code cells
~~~~~~~~~~
A *code input cell* allows you to edit code inline within the cell, with full syntax highlighting and autocompletion/introspection. By default, the language associated to a code cell is Python, but other languages, such as ``julia`` and ``R``, can be handled using magic commands (see below).

When a code cell is executed with :kbd:`Shift-Enter`, the code that it contains is transparently exported and run in that language 
(with automatic compiling, etc., if necessary). The result that is returned from this computation  is then displayed in the notebook space as the cell's 
*output*. If this output is of a textual nature, then it is placed into a numbered *output cell*. 
However, many other possible forms of output are also possible, including
``matplotlib`` figures and HTML tables (as used, for example, in the 
``pandas`` data analyis package). This is known as IPython's *rich display* capability.


Rich text using Markdown
~~~~~~~~~~~~~~~~~~~~~~~~
You can document the computational process in a literate way, alternating descriptive text with code, using *rich text*. In IPython this is accomplished by marking up text with the Markdown language. The corresponding cells are called *Markdown input cells*. The Markdown language provides a simple way to perform this text markup, that is, to specify which parts of the text should be emphasized (italics), bold, form lists, etc. 

When a Markdown input cell is executed, the Markdown code is converted into the corresponding formatted rich text. This output then *replaces* the original Markdown input cell, leaving just the visually-significant marked up rich text.  Markdown allows arbitrary HTML code for formatting.

Within Markdown cells, you can also include *mathematics* in a straightforward way, using standard LaTeX notation: ``$...$`` for inline mathematics and ``$$...$$`` for displayed mathematics. Mathematics is rendered natively in the browser by MathJax. Standard LaTeX and AMS-math environments, such as 
``\begin{equation}...\end{equation}``, and ``\begin{align}...\end{align}`` also work, and new LaTeX macros may be defined using standard LaTeX methods, such as ``\newcommand``, by placing them anywhere in a Markdown cell.

Raw input cells
~~~~~~~~~~~~~~~
*Raw* input cells provide a place in which you can put additional information which you do not want to evaluated by the Notebook. This can be used, for example, to include extra information that is needed when exporting to a certain format. The output after evaluating a raw cell is just a verbatim copy of the input.

Heading cells
~~~~~~~~~~~~~
You can provide a conceptual structure for your computational document as a whole using different levels of headings; there are 6 levels available, from level 1 (main title) down to level 6 (paragraph). These can be used later for constructing tables of contents, etc.

As with Markdown cells, a heading input cell is replaced by a rich text rendering of the heading when the cell is executed.


Magic commands
~~~~~~~~~~~~~~
Magic commands, or *magics*, are commands for controlling IPython itself.
They all begin with ``%`` and are entered into code input cells; the code cells are executed as usual with :kbd:`Shift-Enter`.

The magic commands call special functions defined by IPython which manipulate the computational state in certain ways.

There are two types of magics:

  **line magics**:
     These begin with a single ``%`` and take as arguments the rest of the *same line* of the code cell. Any other lines of the code cell are treated as if they were part of a standard code cell.

  **cell magics**:
    These begin with ``%%`` and operate on the *entire* remaining contents of the code cell.

Line magics
~~~~~~~~~~~
Some of the available line magics are the following:

  * ``%load filename``:
    Loads the contents of the file ``filename`` into a new code cell.

  * ``%timeit code``:
    A simple way to time how long the single line of code ``code`` takes to run

  * ``%config``:
    Configuration of the IPython Notebook

  * ``%lsmagic``:
    Provides a list of all available magic commands

Cell magics
~~~~~~~~~~~

  * ``%%latex``:
    Renders the entire contents of the cell in LaTeX, without needing to use explicit LaTeX delimiters.

  * ``%%bash``:
    The code cell is executed by sending it to be executed by ``bash``. The output of the ``bash`` commands is captured and displayed in the notebook.

  * ``%%file filename``:
    Writes the contents of the cell to the file ``filename``.
    **Caution**: The file is over-written without warning!

  * ``%%R``:
    Execute the contents of the cell using the R language.


Several of the cell magics provide functionality to manipulate the filesystem of a remote server to which you otherwise do not have access.  


Plotting
--------
One major feature of the Notebook is the ability to capture the result of plots as *inline* output, thus displaying the result of running some code right next to the code itself. IPython is designed to work seamlessly with the ``matplotlib`` plotting library to attain this functionality. 

To set this up, before any plotting is performed you must execute the
``%matplotlib`` magic command. This performs the necessary behind-the-scenes setup for IPython to work correctly hand in hand with ``matplotlib``; it does 
*not*, however, actually execute any Python ``import`` commands, that is, no names are added to the namespace.

For more agile *interactive* use of the notebook space, an alternative magic, ``%pylab``, is provided. This does the same work as the ``%matplotlib`` magic, but *in addition* it automatically executes a standard sequence of ``import`` statements required to work with the ``%matplotlib`` library:

It will import at the top level `numpy` as `np`, `pyplot` as `plt`, `matplotlib`, `pylab` and `mlab` from `matplotlib`, as well as *all names* from ``numpy`` and ``pylab``. A less invasive, but less interactive, option is ``%pylab --no-import-all``, which does not do these ``import *`` imports.

When the default ``%matplotlib`` or ``%pylab`` magics are used, the output of a plotting command is captured in a *separate* window. An alternative is to use::

  %matplotlib inline

or::

  %pylab inline

These instead capture the output of the plot and display it *inline* within the notebook format, below the input cell that produced it. The resulting plots will then also be stored in the notebook document.


Converting notebooks to other formats
-------------------------------------
Newly added in the 1.0 release of IPython is the ``nbconvert`` tool, which allows you to convert an ``.ipynb`` notebook document file into another static format. 

Currently, only a command line tool is provided; in the future, it will also be possible to export from within the Notebook app. The command line syntax is::

  $ ipython nbconvert --format=FORMAT notebook.ipynb

This will convert the IPython document file ``notebook.ipynb`` into the output format given by the ``FORMAT`` string.

The default output format is HTML, for which the `--format`` modifier is not actually required::
  
  $ ipython nbconvert notebook.ipynb

The currently supported export formats are the following:

* HTML:

  - ``full_html``:
    Standard HTML

  - ``simple_html``:
    Simplified HTML

  - ``reveal``:
    HTML slideshow presentation for use with the ``reveal.js`` package

* PDF:

  - ``sphinx_howto``:
    The format for Sphinx HOWTOs; similar to an ``article`` in LaTeX

  - ``sphinx_manual``:
    The format for Sphinx manuals; similar to a `book`` in LaTeX 

  - ``latex``:
    An article formatted completely using LaTeX

* Markup:

  - ``rst``:
    reStructuredText markup

  - ``markdown``:
    Markdown markup

* Python:

    Comments out all the non-Python code to produce a standard Python ``.py`` script with just the code content.
    
The files output by ``nbconvert` are currently placed in a new subdirectory called ``nbconvert_build``. 

Each of the options for PDF export produces as an intermediate step a root LaTeX ``.tex`` file with the same name as the notebook, as well as individual files for each figure, and ``.text` files with textual output from running code cells; all of these files are located together in the ``nbconvert_build`` subdirectory.

To actually produce the final PDF file, change into the ``nbconvert_build`` directory and run the following command::
  
  $ pdflatex notebook

This requires a local installation of LaTeX on your machine.
It produes the output PDF file ``notebook.pdf``, also inside the 
``nbconvert_build`` subdirectory.

Alternatively, the output may be piped to standard output, ``stdout``, with::
    
    $ ipython nbconvert mynotebook.ipynb --stdout
    
Multiple notebooks can be specified from the command line::
    
    $ ipython nbconvert notebook*.ipynb
    $ ipython nbconvert notebook1.ipynb notebook2.ipynb
    
or via a list in a configuration file, say ``mycfg.py``, containing the text::
    
    c = get_config()
    c.NbConvertApp.notebooks = ["notebook1.ipynb", "notebook2.ipynb"]

and using the command::

    $ ipython nbconvert --config mycfg.py


Configuring the IPython Notebook
--------------------------------
The IPython Notebook can be run with a variety of command line arguments. 
To see a list of available options enter::

  $ ipython notebook --help 

Defaults for these options can also be set by creating a file named 
``ipython_notebook_config.py`` in your IPython *profile folder*. The profile folder is a subfolder of your IPython directory; to find out where it is located, run::

  $ ipython locate

To create a new set of default configuration files, with lots of information on available options, use::

  $ ipython profile create

.. seealso:

    :ref:`config_overview`, in particular :ref:`Profiles`.


Extracting standard Python files from notebooks
-----------------------------------------------
``.ipynb`` notebook document files are plain text files which store a representation in JSON format of the contents of a notebook space. As such, it is not a valid ``.py`` Python script, and so can be neither imported with 
``import`` in Python, nor run as a standard Python script.

To extract just the Python code from within a notebook document, one option is to use ``ipython nbconvert``, as described above.
An alternative is to pass an argument to the IPython Notebook, from the moment when it is originally started, specifying that whenever it saves an ``.ipynb`` notebook document, it should, at the same time, save the corresponding standard ``.py`` script. To do so, you can execute the following command::

  ipython notebook --script

or you can set this option permanently in your configuration file with::
  c = get_config()
  c.NotebookManager.save_script=True

The result is that standard ``.py`` files are also now generated, and so they can be ``%run``, imported from regular IPython sessions or other notebooks, or executed at the command line, as usual.  Since the raw code you have typed is exported you must avoid using syntax such as IPython magics and other IPython-specific extensions to the language for the files to be able to be successfully imported.

In normal Python practice, the standard way to differentiate importable code in a Python script from the "executable" part of a script is to use the following idiom at the start of the executable part of the code::

  if __name__ == '__main__'

    # rest of the code...
  
Since all cells in the notebook are run as top-level code, you will need to
similarly protect *all* cells that you do not want executed when other scripts
try to import your notebook.  A convenient shortand for this is to define early
on::

  script = __name__ == '__main__'

Then in any cell that you need to protect, use::

  if script:
    # rest of the cell...


.. _notebook_security:

Security
--------

You can protect your Notebook server with a simple single password by
setting the :attr:`NotebookApp.password` configurable. You can prepare a
hashed password using the function :func:`IPython.lib.security.passwd`:

.. sourcecode:: ipython

    In [1]: from IPython.lib import passwd
    In [2]: passwd()
    Enter password: 
    Verify password: 
    Out[2]: 'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
    
.. note::

  :func:`~IPython.lib.security.passwd` can also take the password as a string
  argument. **Do not** pass it as an argument inside an IPython session, as it
  will be saved in your input history.

You can then add this to your :file:`ipython_notebook_config.py`, e.g.::

    # Password to use for web authentication
    c = get_config()
    c.NotebookApp.password = u'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'

When using a password, it is a good idea to also use SSL, so that your password
is not sent unencrypted by your browser. You can start the notebook to
communicate via a secure protocol mode using a self-signed certificate with the command::

    $ ipython notebook --certfile=mycert.pem

.. note::

    A self-signed certificate can be generated with ``openssl``.  For example, the following command will create a certificate valid for 365 days with both the key and certificate data written to the same file::

        $ openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem

Your browser will warn you of a dangerous certificate because it is
self-signed.  If you want to have a fully compliant certificate that will not
raise warnings, it is possible (but rather involved) to obtain one,
`as explained in detailed in this tutorial`__.

.. __: http://arstechnica.com/security/news/2009/12/how-to-get-set-with-a-secure-sertificate-for-free.ars
	
Keep in mind that when you enable SSL support, you will need to access the
notebook server over ``https://``, not over plain ``http://``.  The startup
message from the server prints this, but it is easy to overlook and think the
server is for some reason non-responsive.


Connecting to an existing kernel
---------------------------------

The notebook server always prints to the terminal the full details of 
how to connect to each kernel, with messages such as the following::

    [IPKernelApp] To connect another client to this kernel, use:
    [IPKernelApp] --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json

This long string is the name of a JSON file that contains all the port and 
validation information necessary to connect to the kernel.  You can then, for example, manually start a Qt console connected to the *same* kernel with::

    $ ipython qtconsole --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json

If you have only a single kernel running, simply typing::

    $ ipython qtconsole --existing

will automatically find it. (It will always find the most recently 
started kernel if there is more than one.)  You can also request this 
connection data by typing ``%connect_info``; this will print the same 
file information as well as the content of the JSON data structure it contains.


Running a public notebook server
--------------------------------

If you want to access your notebook server remotely via a web browser,
you can do the following.  

Start by creating a certificate file and a hashed password, as explained above.  Then create a custom profile for the notebook, with the following command line, type::

  $ ipython profile create nbserver

In the profile directory just created, edit the file ``ipython_notebook_config.py``.  By default, the file has all fields commented; the minimum set you need to uncomment and edit is the following::

     c = get_config()

     # Kernel config
     c.IPKernelApp.pylab = 'inline'  # if you want plotting support always

     # Notebook config
     c.NotebookApp.certfile = u'/absolute/path/to/your/certificate/mycert.pem'
     c.NotebookApp.ip = '*'
     c.NotebookApp.open_browser = False
     c.NotebookApp.password = u'sha1:bcd259ccf...[your hashed password here]'
     # It is a good idea to put it on a known, fixed port
     c.NotebookApp.port = 9999

You can then start the notebook and access it later by pointing your browser to
``https://your.host.com:9999`` with ``ipython notebook --profile=nbserver``.

Running with a different URL prefix
-----------------------------------

The notebook dashboard (the landing page with an overview
of the notebooks in your working directory) typically lives at the URL
``http://localhost:8888/``. If you prefer that it lives, together with the rest of the notebook, under a sub-directory,
e.g. ``http://localhost:8888/ipython/``, you can do so with
configuration options like the following (see above for instructions about
modifying ``ipython_notebook_config.py``)::

    c.NotebookApp.base_project_url = '/ipython/'
    c.NotebookApp.base_kernel_url = '/ipython/'
    c.NotebookApp.webapp_settings = {'static_url_prefix':'/ipython/static/'}

Using a different notebook store
--------------------------------

By default, the Notebook app stores the notebook documents that it saves as files in the working directory of the Notebook app, also known as the ``notebook_dir``. This  logic is implemented in the :class:`FileNotebookManager` class. However, the server can be configured to use a different notebook manager class, which can 
store the notebooks in a different format. 

Currently, we ship a :class:`AzureNotebookManager` class that stores notebooks in Azure blob storage. This can be used by adding the following lines to your 
``ipython_notebook_config.py`` file::

    c.NotebookApp.notebook_manager_class = 'IPython.html.services.notebooks.azurenbmanager.AzureNotebookManager'
    c.AzureNotebookManager.account_name = u'paste_your_account_name_here'
    c.AzureNotebookManager.account_key = u'paste_your_account_key_here'
    c.AzureNotebookManager.container = u'notebooks'

In addition to providing your Azure Blob Storage account name and key, you will 
have to provide a container name; you can use multiple containers to organize 
your notebooks.

.. _notebook_format:

Notebook JSON file format
-------------------------
Notebook documents are JSON files with an ``.ipynb`` extension, formatted
as legibly as possible with minimal extra indentation and cell content broken
across lines to make them reasonably friendly to use in version-control
workflows.  You should be very careful if you ever manually edit this JSON
data, as it is extremely easy to corrupt its internal structure and make the
file impossible to load.  In general, you should consider the notebook as a
file meant only to be edited by the IPython Notebook app itself, not for hand-editing.

.. note::

     Binary data such as figures are also saved directly in the JSON file.  This provides convenient single-file portability, but means that the files can be large; a ``diff`` of binary data is also not very meaningful.  Since the binary blobs are encoded in a single line, they affect only one line of the ``diff`` output, but they are typically very long lines.  You can use the ``Cell | All Output | Clear`` menu option to remove all output from a notebook prior to committing it to version control, if this is a concern.

The notebook server can also generate a pure Python version of your notebook, 
using the ``File | Download as`` menu option. The resulting ``.py`` file will 
contain all the code cells from your notebook verbatim, and all Markdown cells 
prepended with a comment marker.  The separation between code and Markdown
cells is indicated with special comments and there is a header indicating the
format version.  All output is removed when exporting to Python.

As an example, consider a simple notebook called ``simple.ipynb`` which contains one Markdown cell, with the content ``The simplest notebook.``, one code input cell with the content ``print "Hello, IPython!"``, and the corresponding output.

The contents of the notebook document ``simple.ipynb`` is the following JSON container::

  {
   "metadata": {
    "name": "simple"
   },
   "nbformat": 3,
   "nbformat_minor": 0,
   "worksheets": [
    {
     "cells": [
      {
       "cell_type": "markdown",
       "metadata": {},
       "source": "The simplest notebook."
      },
      {
       "cell_type": "code",
       "collapsed": false,
       "input": "print \"Hello, IPython\"",
       "language": "python",
       "metadata": {},
       "outputs": [
        {
         "output_type": "stream",
         "stream": "stdout",
         "text": "Hello, IPython\n"
        }
       ],
       "prompt_number": 1
      }
     ],
     "metadata": {}
    }
   ]
  }


The corresponding Python script is::

  # -*- coding: utf-8 -*-
  # <nbformat>3.0</nbformat>

  # <markdowncell>

  # The simplest notebook.

  # <codecell>

  print "Hello, IPython"

Note that indeed the output of the code cell, which is present in the JSON container, has been removed in the ``.py`` script.


Known issues
------------

When behind a proxy, especially if your system or browser is set to autodetect
the proxy, the Notebook app might fail to connect to the server's websockets,
and present you with a warning at startup. In this case, you need to configure
your system not to use the proxy for the server's address.

For example, in Firefox, go to the Preferences panel, Advanced section,
Network tab, click 'Settings...', and add the address of the notebook server
to the 'No proxy for' field.

    
.. _Markdown: http://daringfireball.net/projects/markdown/basics