Reference notebook examples, fixes #4146.

docs/source/interactive/notebook.rst

@@ -1,492 +1,495 b''
 .. _htmlnotebook:
 
 The IPython Notebook
 ====================
 
 Introduction
 ------------
 
 The notebook extends the console-based approach to interactive computing in
 a qualitatively new direction, providing a web-based application suitable for
 capturing the whole computation process: developing, documenting, and
 executing code, as well as communicating the results.  The IPython notebook
 combines two components:
 
 **A web application**: a browser-based tool for interactive authoring of
 documents which combine explanatory text, mathematics, computations and their
 rich media output.
 
 **Notebook documents**: a representation of all content visible in the web
 application, including inputs and outputs of the computations, explanatory
 text, mathematics, images, and rich media representations of objects.
 
 .. seealso::
 
     See the :ref:`installation documentation <installnotebook>` for directions
     on how to install the notebook and its dependencies.
 
 
 Main features of the web application
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * In-browser editing for code, with automatic syntax highlighting,
   indentation, and tab completion/introspection.
 
 * The ability to execute code from the browser, with the results of
   computations attached to the code which generated them.
 
 * Displaying the result of computation using rich media representations, such
   as HTML, LaTeX, PNG, SVG, etc. For example, publication-quality figures
   rendered by the matplotlib_ library, can be included inline.
 
 * In-browser editing for rich text using the Markdown_ markup language, which
   can provide commentary for the code, is not limited to plain text.
 
 * The ability to easily include mathematical notation within markdown cells
   using LaTeX, and rendered natively by MathJax_.
 
 
 
 .. _MathJax: http://www.mathjax.org/
 
 
 Notebook documents
 ~~~~~~~~~~~~~~~~~~
 Notebook documents contains the inputs and outputs of a interactive session as
 well as additional text that accompanies the code but is not meant for
 execution.  In this way, notebook files can serve as a complete computational
 record of a session, interleaving executable code with explanatory text,
 mathematics, and rich representations of resulting objects. These documents
 are internally JSON_ files and are saved with the ``.ipynb`` extension. Since
 JSON is a plain text format, they can be version-controlled and shared with
 colleagues.  
    
 .. _JSON: http://en.wikipedia.org/wiki/JSON
 
 Notebooks may be exported to a range of static formats, including HTML (for
 example, for blog posts), reStructeredText, LaTeX, PDF, and slide shows, via
 the new :ref:`nbconvert <nbconvert>` command.
 
 Furthermore, any  ``.ipynb`` notebook document available from a public 
 URL can be shared via the `IPython Notebook Viewer <nbviewer>`_ (nbviewer_).
 This service loads the notebook document from the URL and renders it as a
 static web page.  The results may thus be shared with a colleague, or as a
 public blog post, without other users needing to install IPython themselves.
 In effect, nbviewer_ is simply :ref:`nbconvert <nbconvert>` as a web service,
 so you can do your own static conversions with nbconvert, without relying on
 nbviewer.
 
 
 
 .. seealso::
 
     :ref:`Details on the notebook JSON file format <notebook_format>` 
    
 
 Starting the notebook server
 ----------------------------
 
 You can start running a notebook server from the command line using the
 following command::
 
     ipython notebook
 
 This will print some information about the notebook server in your console,
 and open a web browser to the URL of the web application (by default,
 ``http://127.0.0.1:8888``).
 
 The landing page of the IPython notebook web application, the **dashboard**,
 shows the notebooks currently available in the notebook directory (by default,
 the directory from which the notebook server 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.
 
 When starting a notebook server from the command line, you can also open a
 particular notebook directly, bypassing the dashboard, with ``ipython notebook
 my_notebook.ipynb``. The ``.ipynb`` extension is assumed if no extension is
 given.
 
 When you are inside an open notebook, the `File | Open...` menu option will
 open the dashboard in a new browser tab, to allow you to open another notebook
 from the notebook directory or to create a new notebook.
 
 
 .. 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.
 
 Creating a new notebook document
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 A new notebook may be created at any time, either from the dashboard, or using
 the `File | New` menu option from within an active notebook. The new notebook
 is created within the same directory and will open in a new browser tab. It
 will also be reflected as a new entry in the notebook list on the dashboard.
 
 
 Opening notebooks
 ~~~~~~~~~~~~~~~~~
 An open notebook has **exactly one** interactive session connected to an
 :ref:`IPython kernel <ipythonzmq>`, which will execute code sent by the user
 and communicate back results.  This kernel remains active if the web browser
 window is closed, and reopening the same notebook from the dashboard will
 reconnect the web application to the same kernel. In the dashboard, notebooks
 with an active kernel have a ``Shutdown`` button next to them, whereas
 notebooks without an active kernel have a ``Delete`` button in its place.
 
 Other clients may connect to the same underlying IPython 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::
 
     [NotebookApp] Kernel started: 87f7d2c0-13e3-43df-8bb8-1bd37aaf3373
 
 This long string is the kernel's ID which is sufficient for getting the
 information necessary to connect to the kernel.  You can also request this
 connection data by running the ``%connect_info`` :ref:`magic
 <magics_explained>`. This will print the same ID information as well as the
 content of the JSON data structure it contains.
 
 You can then, for example, manually start a Qt console connected to the *same*
 kernel from the command line, by passing a portion of the ID::
 
     $ ipython qtconsole --existing 87f7d2c0
 
 Without an ID, ``--existing`` will  connect to the most recently 
 started kernel. This can also be done by running the ``%qtconsole``
 :ref:`magic <magics_explained>` in the notebook.
 
 .. seealso::
 
     :ref:`ipythonzmq`
 
 Notebook user interface
 -----------------------
 
 When you create a new notebook document, you will be presented with the
 **notebook name**, a **menu bar**, a **toolbar** and an empty **code
 cell**.
 
 **notebook name**: The name of the notebook document is displayed at the top
 of the page, next to the ``IP[y]: Notebook`` logo. This name reflects the name
 of the ``.ipynb`` notebook document file.  Clicking on the notebook name
 brings up a dialog which allows you to rename it. Thus, renaming a notebook
 from "Untitled0" to "My first notebook" in the browser, renames the
 ``Untitled0.ipynb`` file to ``My first notebook.ipynb``. 
 
 **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 performing the most-used
 operations within the notebook, by clicking on an icon.
 
 **code cell**: the default type of cell, read on for an explanation of cells
 
 
 Structure of a notebook document
 --------------------------------
 
 The notebook consists of a sequence of cells.  A cell is a multi-line
 text input field, and its contents can be executed by using
 :kbd:`Shift-Enter`, or by clicking either the "Play" button the toolbar, or
 `Cell | Run` in the menu bar.  The execution behavior of a cell is determined
 the cell's type.  There are four types of cells: **code cells**, **markdown
 cells**, **raw cells** and **heading cells**.  Every cell starts off
 being a **code cell**, but its type can be changed by using a dropdown on the
 toolbar (which will be "Code", initially), or via :ref:`keyboard shortcuts
 <keyboard-shortcuts>`.  
 
+For more information on the different things you can do in a notebook,
+see the `collection of examples
+<https://github.com/ipython/ipython/tree/master/examples/notebooks#readme>`_.
 
 Code cells
 ~~~~~~~~~~
 A *code cell* allows you to edit and write new code, with full syntax
 highlighting and tab completion. By default, the language associated to a code
 cell is Python, but other languages, such as ``Julia`` and ``R``, can be
 handled using :ref:`cell magic commands <magics_explained>`.
 
 When a code cell is executed, code that it contains is sent to the kernel
 associated with the notebook.  The results that are returned from this 
 computation  are then displayed in the notebook as the cell's *output*. The
 output is not limited to text, with many other possible forms of output are
 also possible, including ``matplotlib`` figures and HTML tables (as used, for 
 example, in the ``pandas`` data analysis package). This is known as IPython's 
 *rich display* capability.
 
 .. seealso::
 
     `Basic Output`_  example notebook
 
     `Rich Display System`_  example notebook
 
 Markdown cells
 ~~~~~~~~~~~~~~
 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 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 cell is executed, the Markdown code is converted into 
 the corresponding formatted 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. When the Markdown cell is executed, 
 the LaTeX portions are automatically rendered in the HTML output as equations 
 with high quality typography. This is made possible by MathJax_, which 
 supports a `large subset <mathjax_tex>`_ of LaTeX functionality 
 
 .. _mathjax_tex: http://docs.mathjax.org/en/latest/tex.html
 
 Standard mathematics environments defined by LaTeX and AMS-LaTeX (the 
 `amsmath` package) also work, such as 
 ``\begin{equation}...\end{equation}``, and ``\begin{align}...\end{align}``.
 New LaTeX macros may be defined using standard methods, 
 such as ``\newcommand``, by placing them anywhere *between math delimiters* in 
 a Markdown cell. These definitions are then available throughout the rest of 
 the IPython session. 
 
 .. seealso::
 
     `Markdown Cells`_ example notebook
 
 Raw cells
 ~~~~~~~~~
 
 *Raw* cells provide a place in which you can write *output* directly.
 Raw cells are not evaluated by the notebook.
 When passed through :ref:`nbconvert <nbconvert>`, raw cells arrive in the
 destination format unmodified. For example, this allows you to type full LaTeX
 into a raw cell, which will only be rendered by LaTeX after conversion by
 nbconvert.
 
 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 (top level) down to level 6 (paragraph). These can be used later for 
 constructing tables of contents, etc.  As with Markdown cells, a heading 
 cell is replaced by a rich text rendering of the heading when the cell is
 executed.
 
 
 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. 
 
 
 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.
 
 At certain moments, it may be necessary to interrupt a calculation which is 
 taking too long to complete. This may be done with the `Kernel | Interrupt` 
 menu option, or the :kbd:`Ctrl-m i` keyboard shortcut.
 Similarly, it may be necessary or desirable to restart the whole computational 
 process, with the `Kernel | Restart` menu option or :kbd:`Ctrl-m .` 
 shortcut. 
 
 A notebook may be downloaded in either a ``.ipynb`` or ``.py`` file from the
 menu option `File | Download as`. Choosing the ``.py`` option downloads a
 Python ``.py`` script, in which all rich output has been removed and the
 content of markdown cells have been inserted as comments.  
 
 .. seealso::
 
     `Running Code in the IPython Notebook`_ example notebook
 
     `Basic Output`_ example notebook
 
     :ref:`a warning about doing "roundtrip" conversions <note_about_roundtrip>`.
 
 .. _keyboard-shortcuts:
 
 Keyboard shortcuts
 ~~~~~~~~~~~~~~~~~~
 All actions in the notebook can be performed with the mouse, but keyboard 
 shortcuts are also available for the most common ones. The essential shortcuts
 to remember are the following:
 
 * :kbd:`Shift-Enter`:  run cell
     Execute the current cell, show output (if any), and jump to the next cell 
     below. If :kbd:`Shift-Enter` is invoked on the last 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 cell. :kbd:`Shift-Enter` is equivalent to clicking the 
     ``Cell | Run`` menu item.
 
 * :kbd:`Ctrl-Enter`: run cell in-place
     Execute the current cell as if it were in "terminal mode", where any 
     output is shown, but the cursor *remains* in the current cell. The cell's
     entire contents are selected after execution, so you can just start typing
     and only the new input will be in the 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`: run cell, insert below
     Executes the current cell, shows the output, and inserts a *new* 
     cell between the current cell and the cell below (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 above 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.
 
 
 ..
     TODO: these live in IPython/html/static/notebook/js/quickhelp.js
     They were last updated for IPython 1.0 release, so update them again for
     future releases.
 
 Here is the complete set of keyboard shortcuts available:
 
 ============  ==========================
 **Shortcut**        **Action**
 ------------  --------------------------
 Shift-Enter    run cell
 Ctrl-Enter     run cell in-place
 Alt-Enter      run cell, insert below
 Ctrl-m x       cut cell
 Ctrl-m c       copy cell
 Ctrl-m v       paste cell
 Ctrl-m d       delete cell
 Ctrl-m z       undo last cell deletion
 Ctrl-m -       split cell
 Ctrl-m a       insert cell above
 Ctrl-m b       insert cell below
 Ctrl-m o       toggle output
 Ctrl-m O       toggle output scroll
 Ctrl-m l       toggle line numbers
 Ctrl-m s       save notebook
 Ctrl-m j       move cell down
 Ctrl-m k       move cell up
 Ctrl-m y       code cell
 Ctrl-m m       markdown cell
 Ctrl-m t       raw cell
 Ctrl-m 1-6     heading 1-6 cell
 Ctrl-m p       select previous
 Ctrl-m n       select next
 Ctrl-m i       interrupt kernel
 Ctrl-m .       restart kernel
 Ctrl-m h       show keyboard shortcuts
 ============  ==========================
 
    
 
 
 
 Plotting
 --------
 One major feature of the notebook is the ability to display plots that are the
 output of running code cells. IPython is designed to work seamlessly with the
 matplotlib_ plotting library to provide this functionality. 
 
 To set this up, before any plotting is performed you must execute the
 ``%matplotlib``  :ref:`magic command <magics_explained>`. 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.
 
 If the ``%matplotlib`` magic is called without an argument, the 
 output of a plotting command is displayed using the default ``matplotlib`` 
 backend in a separate window. Alternatively, the backend can be explicitly 
 requested using, for example::
 
   %matplotlib gtk
 
 A particularly interesting backend, provided by IPython, is the ``inline``
 backend.  This is available only for the IPython Notebook and the
 :ref:`IPython QtConsole <qtconsole>`.  It can be invoked as follows::
 
   %matplotlib inline
 
 With this backend, the output of plotting commands is displayed *inline*
 within the notebook, directly below the code cell that produced it. The
 resulting plots will then also be stored in the notebook document. 
 
 .. seealso::
 
     `Plotting with Matplotlib`_  example notebook
 
 
 Configuring the IPython Notebook
 --------------------------------
 The notebook server 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`.
     
     :ref:`notebook_security`
 
     :ref:`notebook_public_server`
 
 
 Importing ``.py`` files
 -----------------------
 
 ``.py`` files will be imported as a notebook with 
 the same basename, but an ``.ipynb`` extension, located in the notebook 
 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.
 
 Note that ``.py`` scripts obtained from a notebook document using nbconvert_ 
 maintain the structure of the notebook in comments. Reimporting such a
 script back into a notebook will preserve this structure.
 
 .. _note_about_roundtrip:
 
 .. 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.
 
 .. seealso::
     :ref:`notebook_format`
 
 .. include:: ../links.txt