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.. _htmlnotebook:
An HTML Notebook IPython
.. seealso::
:ref:`Installation requirements <installnotebook>` for the Notebook.
The IPython Notebook consists of two related components:
* An JSON based Notebook document format for recording and distributing
Python code and rich text.
* A web-based user interface for authoring and running notebook documents.
The Notebook can be used by starting the Notebook server with the
$ ipython notebook
Note that by default, the notebook doesn't load pylab, it's just a normal
IPython session like any other. If you want pylab support, you must use::
$ ipython notebook --pylab
which will behave similar to the terminal and Qt console versions, using your
default matplotlib backend and providing floating interactive plot windows. If
you want inline figures, you must manually select the ``inline`` backend::
$ ipython notebook --pylab inline
This server uses the same ZeroMQ-based two process kernel architecture as
the QT Console as well Tornado for serving HTTP/S requests. Some of the main
features of the Notebook include:
* Display rich data (png/html/latex/svg) in the browser as a result of
* Compose text cells using HTML and Markdown.
* Import and export notebook documents in range of formats (.ipynb, .py).
* In browser syntax highlighting, tab completion and autoindentation.
* Inline matplotlib plots that can be stored in Notebook documents and opened
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 in port 8888, later notebooks search for random ports near
that one. You can also manually specify the port with the ``--port``
Basic Usage
The landing page of the notebook server application, which we call the IPython
Notebook *dashboard*, shows the notebooks currently available in the directory
in which the application was started, and allows you to create new notebooks.
A notebook is a combination of two things:
1. An interactive session connected to an IPython kernel, controlled by a web
application that can send input to the console and display many types of
output (text, graphics, mathematics and more). This is the same kernel used
by the :ref:`Qt console <qtconsole>`, but in this case the web console sends
input in persistent cells that you can edit in-place instead of the
vertically scrolling terminal style used by the Qt console.
2. A document that can save the inputs and outputs of the session as well as
additional text that accompanies the code but is not meant for execution.
In this way, notebook files serve as a complete computational record of a
session including explanatory text and mathematics, code and resulting
figures. These documents are internally JSON files and are saved with the
``.ipynb`` extension.
If you have ever used the Mathematica or Sage notebooks (the latter is also
web-based__) you should feel right at home. If you have not, you should be
able to learn how to use it in just a few minutes.
.. __:
Creating and editing notebooks
You can create new notebooks from the dashboard with the ``New Notebook``
button or open existing ones by clicking on their name. Once in a notebook,
your browser tab will reflect the name of that notebook (prefixed with "IPy:").
The URL for that notebook is not meant to be human-readable and is *not*
persistent across invocations of the notebook server.
You can also drag and drop into the area listing files any python file: it
will be imported into a notebook with the same name (but ``.ipynb`` extension)
located in the directory where the notebook server was started. This notebook
will consist of a single cell with all the code in the file, which you can
later manually partition into individual cells for gradual execution, add text
and graphics, etc.
Workflow and limitations
The normal workflow in a notebook is quite similar to a normal IPython session,
with the difference that you can edit a cell in-place multiple times until you
obtain the desired results rather than having to rerun separate scripts with
the ``%run`` magic (though magics also work in the notebook). Typically
you'll work on a problem in pieces, organizing related pieces into cells and
moving forward as previous parts work correctly. This is much more convenient
for interactive exploration than breaking up a computation into scripts that
must be executed together, especially if parts of them take a long time to run
(In the traditional terminal-based IPython, you can use tricks with namespaces
and ``%run -i`` to achieve this capability, but we think the notebook is a more
natural solution for that kind of problem).
The only significant limitation the notebook currently has, compared to the qt
console, is that it can not 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* work in the notebook! We intend to
correct this limitation, but in the meantime, there is a way to debug problems
in the notebook: 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, you can just type ``%qtconsole`` in the notebook and a Qt console
will open up connected to that same kernel.
In general, the notebook server prints the full details of how to connect to
each kernel at the terminal, with lines like::
[IPKernelApp] To connect another client to this kernel, use:
[IPKernelApp] --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
This is the name of a JSON file that contains all the port and validation
information necessary to connect to the kernel. You can manually start a
qt console with::
ipython qtconsole --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
and if you only have 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.
Text input
In addition to code cells and the output they produce (such as figures), you
can also type text not meant for execution. To type text, change the type of a
cell from ``Code`` to ``Markdown`` by using the button or the :kbd:`Ctrl-m m`
keybinding (see below). You can then type any text in Markdown_ syntax, as
well as mathematical expressions if you use ``$...$`` for inline math or
``$$...$$`` for displayed math.
Exporting a notebook and importing existing scripts
If you want to provide others with a static HTML or PDF view of your notebook,
use the ``Print`` button. This opens a static view of the document, which you
can print to PDF using your operating system's facilities, or save to a file
with your web browser's 'Save' option (note that typically, this will create
both an html file *and* a directory called `notebook_name_files` next to it
that contains all the necessary style information, so if you intend to share
this, you must send the directory along with the main html file).
The `Download` button lets you save a notebook file to the Download area
configured by your web browser (particularly useful if you are running the
notebook server on a remote host and need a file locally). The notebook is
saved by default with the ``.ipynb`` extension and the files contain JSON data
that is not meant for human editing or consumption. But you can always export
the input part of a notebook to a plain python script by choosing Python format
in the `Download` drop list. This removes all output and saves the text cells
in comment areas. See ref:`below <notebook_format>` for more details on the
notebook format.
The notebook can also *import* ``.py`` files as notebooks, by dragging and
dropping the file into the notebook dashboard file list area. By default, the
entire contents of the file will be loaded into a single code cell. But if
prior to import, you manually add the ``# <nbformat>2</nbformat>`` marker at
the start and then add separators for text/code cells, you can get a cleaner
import with the file broken into individual cells.
If you want use notebooks as scripts a lot, then you can set::
which will instruct the notebook server to save the ``.py`` export of each
notebook adjacent to the ``.ipynb`` at every save. Then these can be ``%run``
or imported from regular IPython sessions or other notebooks.
.. warning::
While in simple cases you can roundtrip a notebook to Python, edit the
python file and import it back without loss of main content, this is in
general *not guaranteed to work at all*. 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
Keyboard use
All actions in the notebook can be achieved with the mouse, but we have also
added keyboard shortcuts for the most common ones, so that productive use of
the notebook can be achieved with minimal mouse intervention. The main
key bindings you need to remember are:
* :kbd:`Shift-Enter`: execute the current cell (similar to the Qt console),
show output (if any) and create a new cell below. Note that in the notebook,
simply using :kbd:`Enter` *never* forces execution, it simply inserts a new
line in the current cell. Therefore, in the notebook you must always use
:kbd:`Shift-Enter` to get execution (or use the mouse and click on the ``Run
Selected`` button).
* :kbd:`Ctrl-Enter`: execute the current cell in "terminal mode", where any
output is shown but the cursor stays in the current cell, whose input
area is flushed empty. This is convenient to do quick in-place experiments
or query things like filesystem content without creating additional cells you
may not want saved in your notebook.
* :kbd:`Ctrl-m`: this is the prefix for all other keybindings, which consist
of an additional single letter. Type :kbd:`Ctrl-m h` (that is, the sole
letter :kbd:`h` after :kbd:`Ctrl-m`) and IPython will show you the remaining
available keybindings.
.. _notebook_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:``:
.. sourcecode:: ipython
In [1]: from IPython.lib import passwd
In [2]: passwd()
Enter password:
Verify password:
Out[2]: 'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
.. note::
:func:`` 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:``, e.g.::
# Password to use for web authentication
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 by
$ 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 for free,
`as explained in detailed in this tutorial`__.
.. __:
Keep in mind that when you enable SSL support, you'll need to access the
notebook server over ``https://``, not over plain ``http://``. The startup
message from the server prints this, but it's easy to overlook and think the
server is for some reason non-responsive.
Quick Howto: running a public notebook server
If you want to access your notebook server remotely with just a web browser,
here is a quick set of instructions. Start by creating a certificate file and
a hashed password as explained above. Then, create a custom profile for the
notebook. At the command line, type::
ipython profile create nbserver
In the profile directory, edit the file ````. By
default the file has all fields commented, the minimum set you need to
uncomment and edit is here::
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's 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
.. _notebook_format:
The notebook format
The notebooks themselves 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 edit manually 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 IPython itself, not for hand-editing.
.. note::
Binary data such as figures are directly saved in the JSON file. This
provides convenient single-file portability but means the files can be
large and diffs of binary data aren't very meaningful. Since the binary
blobs are encoded in a single line they only affect one line of the diff
output, but they are typically very long lines. You can use the
'ClearAll' button 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,
by clicking on the 'Download' button and selecting ``py`` as the format. This
file will contain all the code cells from your notebook verbatim, and all text
cells prepended with a comment marker. The separation between code and text
cells is indicated with special comments and there is a header indicating the
format version. All output is stripped out when exporting to python.
Here is an example of a simple notebook with one text cell and one code input
cell, when exported to python format::
# <nbformat>2</nbformat>
# <markdowncell>
# A text cell
# <codecell>
print "hello IPython"
Known Issues
When behind a proxy, especially if your system or browser is set to autodetect
the proxy, the html notebook 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.
In Firefox, for example, 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:
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