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 ("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, tab completion and autoindentation.
• 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 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.

Starting up the IPython Notebook web app

The Notebook web app is started with the 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 will consist of a single cell containing all the code in the .py file, which you can later manually partition 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.

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 outpus Out[n], where n is a number which denotes the order in which the cells were executed over the history of the computational process.

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'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

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 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 127.0.0.1), 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 restart, all relevant cells must be re-evaluated

A notebook may be downloaded in either .ipynb or raw .py form from the menu option File -> Download as Choosing the .py option removes all output and saves the text cells in comment areas. See ref:below <notebook_format> for more details on the 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`: This is the prefix for all of the other shortcuts, which consist of an additional single letter or character. 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.

Cell types

Each IPython input cell has a cell type. There is a restricted number of possible cell types, which 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`

Magic commands

Magic commands, or magics, are one-word commands beginning with the symbol %, which send commands to IPython itself (as opposed to standard Python commands which are exported to be run in a Python interpreter).

Magics control different elements of the way that the IPython notebook operates. They are entered into standard code cells and executed as usual with :kbd:`Shift-Enter`.

There are two types of magics: line magics, which begin with a single % and operate on a single line of the code cell; and cell magics, which begin with %% and operate on the entire contents of the cell.

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

• %load: Loads a file and places its content into a new code cell.
• %timeit: A simple way to time how long a single line of code takes to run
• %config: Configuration of the IPython Notebook
• %lsmagic: Provides a list of all available magic commands

Cell magics ˜˜˜˜˜˜˜˜˜˜˜

• %%bash: Send the contents of the code cell to be executed by bash
• %%file: Writes a file with with contents of the cell. Caution: The file is ovewritten without asking.
• %%R: Execute the contents of the cell using the R language.
• %%cython: Execute the contents of the cell using Cython.

Plotting

One major feature of the Notebook is the ability to capture the result of plots as inline output. IPython is designed to work seamlessly together with the %matplotlib plotting library. In order to set this up, the %matplotlib magic command must be run before any plotting takes place.

Note that %matplotlib only sets up IPython to work correctly with matplotlib; it does not actually execute any import commands and does not add anything to the namespace.

There is an alternative magic, %pylab, which, in addition, also executes a sequence of standard import statements required for working with the %matplotlib library. In particular, it automatically imports all names in the numpy and matplotlib packages to the namespace. A less invasive solution is %pylab --no-import-all, which imports just the standard names np for the numpy module and plt for the matplotlib.pyplot module.

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

which captures the output inline within the notebook format. This has the benefit that the resulting plots will 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; at present, this functionality is not available for direct exports from within the Notebook app. The syntax is:

$ ipython nbconvert --format=FORMAT notebook.ipynb

which will convert the IPython document file notebook.ipynb into the output format specified by the FORMAT string.

The default output format is HTML, for which the --format` modifier is not required:

$ ipython nbconvert notebook.ipynb

Otherwise, the following FORMAT

where FORMAT is the desired export format. The currently export format options available 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 article in LaTeX
  • sphinx_manual: The format for Sphinx manuals; similar to book in LaTeX
  • latex: LaTeX article

• Markup:

  • rst: reStructuredText
  • markdown: Markdown

• Python:

  Produces a standard .py script, with the non-Python code commented out.

The output files are currently placed in a new subdirectory called nbconvert_build.

The PDF options produce 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, simply run:

$ pdflatex notebook

which produces 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 at the command line in a couple of different ways:

$ ipython nbconvert notebook*.ipynb
$ ipython nbconvert notebook1.ipynb notebook2.ipynb

or via a list in a configuration file, containing:

c.NbConvertApp.notebooks = ["notebook1.ipynb", "notebook2.ipynb"]

and using the command:

> ipython nbconvert --config mycfg.py

Configuration

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

The native format of the notebook, a file with a .ipynb `extension, is a JSON container of all the input and output of the notebook, and therefore not valid Python by itself. This means that by default, you cannot directly import a notebook from Python, nor execute it as a normal python script.

But if you want to be able to use notebooks also as regular Python files, you can start the notebook server with:

ipython notebook --script

or you can set this option permanently in your configuration file with:

c.NotebookManager.save_script=True

This will instruct the notebook server to save the .py export of each notebook, in addition to the .ipynb, at every save. These are standard .py files, and so they can be %run, imported from regular IPython sessions or other notebooks, or executed at the command line. Since we export the raw code you have typed, for these files to be importable from other code, you will have to avoid using syntax such as ``%magic``s and other IPython-specific extensions to the language.

In regular practice, the standard way to differentiate importable code from the 'executable' part of a script is to put at the bottom:

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__'

and then on any cell that you need to protect, use:

if script:
  # rest of the cell...

Security

You can protect your Notebook server with a simple singlepassword 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.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 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.

Connecting to an existing kernel

The notebook server always prints to the terminal the full details of how to connect to each kernel, 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.

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 ipython_notebook_config.py. 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 https://your.host.com:9999 with ipython notebook --profile=nbserver.

Running with a different URL prefix

The notebook dashboard (i.e. the default landing page with an overview of all your notebooks) typically lives at a URL path of "http://localhost:8888/". If you want to have it, and the rest of the notebook, live under a sub-directory, e.g. "http://localhost:8888/ipython/", you can do so with configuration options like these (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 server stores notebooks as files in the working directory of the notebook server, 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.