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.
Introduction
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 Notebook app and notebook 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 corresponding 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 simple JSON files with the extension .ipynb. Since JSON is just plain text, they can be easily version-controlled and shared with colleagues. The notebook stores 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 rich 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 new nbconvert command.
Furthermore, any .ipynb notebook document available from a public URL can be shared via the IPython Notebook Viewer service. 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. NbViewer is simply nbconvert as a simple webservice.
See the :ref:`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.
Basic workflow in the IPython Notebook web app
Starting up
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 IPython Notebook application, the dashboard, shows the notebooks currently available in the notebook directory (By default, 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.
You can open an existing notebook directly, without having to go via the dashboard, with:
ipython notebook my_notebook
The .ipynb extension is assumed if no extension is given.
The File | Open... menu option will open the dashboard in a new browser tab, to allow you to select a current notebook from the notebook directory or to create a new notebook.
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.
Toolbar
The tool bar gives a quick way of accessing the most-used operations within the Notebook, by clicking on an icon.
Creating a new notebook document
A new notebook space/document 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.
Structure of a notebook document
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.
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, 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.
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 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. 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 of LaTeX functionality
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. (Note, however, that more care must be taken when using nbconvert to output to LaTeX).
Raw input cells
Raw input cells provide a place in which you can write output directly. Raw cells are not evaluated by the Notebook, and have no output. When passed through nbconvert, Raw cells arrive in the destination format unmodified, allowing 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 input 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. (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
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.
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 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 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. :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 input 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.
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 |
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. This can be a URL for a remote file.
%timeit code:
An easy 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.
%%timeit:
Version of %timeit which times the entire block of code in the current code cell.
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 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.
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 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.
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
Importing .py files
.py files will be imported into the IPython Notebook 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 the Notebook will preserve this structxure.
Warning
You can "roundtrip" a notebook to Python, by exporting the notebook to a .py script, editing the script, and then importing it back into the Notebook without loss of main content. However, in general this is not guaranteed to work. First, there is extra metadata saved in the notebook that may not be saved to the .py format. Second, 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.