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 this 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, ASCII-coded text files with the extension .ipynb, stored in the working directory on your computer. Since the contents of the files are just plain text, they can be easily version-controlled and shared with colleagues.

Internally, notebook document files use the JSON format, allowing them 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, interleaving executable code with rich 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, via the newly-included nbconvert script functionality.

Furthermore, any .ipynb notebook document with a publicly-available URL can be shared via the IPython Notebook Viewer service. This service loads the notebook document from the URL which will provide 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.

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

Starting up the IPython Notebook web app

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

$ ipython notebook

(Here, and in the sequel, the initial $ represents the shell prompt, indicating that the command is to be run from the command line in a shell.)

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.

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 by the "IPy" icon denoting that the tab corresponds to the IPython Notebook. 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.

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 calculation which is taking too long to complete. This may be done with the Kernel | Interrupt menu option, or the :kbd:Ctrl-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-. shortcut. This gives an equivalent state to loading the notebook document afresh.

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 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.

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.

Plotting

One major feature of the Notebook is the ability to interact with 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 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, importing the following names into the namespace:

numpy as np; matplotlib.pyplot as plt; matplotlib, pylab and mlab from matplotlib; and all names from within numpy and pylab.

However, the use of %pylab is discouraged, since names coming from different packages may collide. In general, the use of from package import * is discouraged. A better option is then:

%pylab --no-import-all

which imports the names listed above, but does not perform this import * imports.

If the %matplotlib or %pylab` magics are 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 is the inline backend. This is applicable only for the IPython Notebook and the IPython Qtconsole. It can be invoked as follows:

%matplotlib inline

With this backend, output of plotting commands is displayed inline within the notebook format, directly below the input cell that produced it. The resulting plots will then also be stored in the notebook document. This provides a key part of the functionality for reproducibility that the IPython Notebook provides.

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 various static formats.

Currently, nbconvert is provided as a command line tool, run as a script using IPython. In the future, a direct export capability from within the IPython Notebook web app is planned.

The command-line syntax to run the nbconvert script 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 may be omitted:

$ 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 .py Python script with just the code content. Currently the output includes IPython magics, and so can be run with ipython, after changing the extension of the script to .ipy.

The files output file created by nbconvert will have the same base name as the notebook and will be placed in the current working directory. Any supporting files (graphics, etc) will be placed in a new directory with the same base name as the notebook, suffixed with _files:

$ ipython nbconvert notebook.ipynb
$ ls
notebook.ipynb   notebook.html    notebook_files/

Each of the options for PDF export produces as an intermediate step a LaTeX .tex file with the same basename as the notebook, as well as individual files for each figure, and .text files with textual output from running code cells.

To actually produce the final PDF file, run the following commands:

$ ipython nbconvert --format=latex notebook.ipynb
$ pdflatex notebook

This requires a local installation of LaTeX on your machine. The output is a PDF file notebook.pdf, also placed inside the nbconvert_build subdirectory.

Alternatively, the output may be sent to standard output with:

$ ipython nbconvert notebook.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

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, they are not valid .py Python scripts, and so can be neither imported directly with import in Python, nor run directly as a standard Python script (though both of these are possible with simple workarounds).

To extract the Python code from within a notebook document, the simplest method is to use the File | Download as | Python (.py) menu item; the resulting .py script will be downloaded to your browser's default download location.

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

.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, which 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; or you can change the script's extension to .ipy and run it with:

$ ipython script.ipy

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...

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`:

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

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

$ 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.

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 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.

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.