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1 1 .. _htmlnotebook:
2 2
3 =========================
4 An HTML Notebook IPython
5 =========================
3 ====================
4 The IPython Notebook
5 ====================
6 6
7 7 .. seealso::
8 8
@@ -10,37 +10,50 b' An HTML Notebook IPython'
10 10
11 11 The IPython Notebook consists of two related components:
12 12
13 * An JSON based Notebook document format for recording and distributing
14 Python code and rich text.
15 * A web-based user interface for authoring and running notebook documents.
13 * A web application for interactive authoring of literate computations, combining explanatory text, mathematics, computations and rich media output. Input and output are stored in persistent cells that may be edited in-place.
14
15 * Notebook documents for recording and distributing
16 the results.
17
18
19 Features of the IPython Notebook web app
20 ----------------------------------------
21
22 Some of the main
23 features of the IPython Notebook app include:
24
25 * Display rich data representations (e.g. HTML / LaTeX / SVG) in the browser as a result of computations.
26 * Compose text cells using Markdown and HTML.
27 * Include mathematical equations, rendered directly in the browser by MathJax.
28 * Import standard Python scripts
29 * In-browser editing, syntax highlighting, tab completion and autoindentation.
30 * Inline figures rendered by the ``matplotlib`` library with publication quality, in a range of formats (SVG / PDF / PNG).
31
32 If you have ever used the Mathematica or SAGE notebooks (the latter is also
33 web-based__) you should feel right at home. If you have not, you will be
34 able to learn how to use it in just a few minutes.
35
36 .. __: http://sagenb.org
37
16 38
17 The Notebook can be used by starting the Notebook server with the
18 command::
19 39
20 $ ipython notebook
21 40
22 Note that by default, the notebook doesn't load pylab, it's just a normal
23 IPython session like any other. If you want pylab support, you must use::
24
25 $ ipython notebook --pylab
26 41
27 which will behave similar to the terminal and Qt console versions, using your
28 default matplotlib backend and providing floating interactive plot windows. If
29 you want inline figures, you must manually select the ``inline`` backend::
42 Notebook documents
43 ------------------
30 44
31 $ ipython notebook --pylab inline
45 Notebook documents, or *notebooks*, are files which record all computations carried out and the results obtained in a literate way, including inputs, outputs, toegether with descriptive text and mathematics.
32 46
33 This server uses the same ZeroMQ-based two process kernel architecture as
34 the QT Console as well Tornado for serving HTTP/S requests. Some of the main
35 features of the Notebook include:
47 They are plain text files, which are thus easy to share with colleagues and place under version control. But, by using the
48 JSON format, they can record all aspects of the computation, including embedding rich media output.
49 The standard file extension for notebook documents is ``.ipynb``.
50
51 Notebooks may easily be exported to a range of static formats, including HTML (for example, for blog posts), PDF and slide shows.
52 Furthermore, any publicly
53 available notebook may be shared via the `IPython Notebook Viewer
54 <http://nbviewer.ipython.org>`_ service, which will provide it as a static web
55 page. The results may thus be shared without having to install anything.
36 56
37 * Display rich data (png/html/latex/svg) in the browser as a result of
38 computations.
39 * Compose text cells using HTML and Markdown.
40 * Import and export notebook documents in range of formats (.ipynb, .py).
41 * In browser syntax highlighting, tab completion and autoindentation.
42 * Inline matplotlib plots that can be stored in Notebook documents and opened
43 later.
44 57
45 58 See :ref:`our installation documentation <install_index>` for directions on
46 59 how to install the notebook and its dependencies.
@@ -49,93 +62,74 b' how to install the notebook and its dependencies.'
49 62
50 63 You can start more than one notebook server at the same time, if you want to
51 64 work on notebooks in different directories. By default the first notebook
52 server starts in port 8888, later notebooks search for random ports near
65 server starts on port 8888, and later notebook servers search for ports near
53 66 that one. You can also manually specify the port with the ``--port``
54 67 option.
55 68
56 69
57 Basic Usage
58 ===========
70 Starting the IPython Notebook web app
71 =====================================
59 72
60 The landing page of the notebook server application, which we call the IPython
61 Notebook *dashboard*, shows the notebooks currently available in the directory
62 in which the application was started, and allows you to create new notebooks.
73 The Notebook web app can be started with the command::
63 74
64 A notebook is a combination of two things:
75 $ ipython notebook
65 76
66 1. An interactive session connected to an IPython kernel, controlled by a web
67 application that can send input to the console and display many types of
68 output (text, graphics, mathematics and more). This is the same kernel used
69 by the :ref:`Qt console <qtconsole>`, but in this case the web console sends
70 input in persistent cells that you can edit in-place instead of the
71 vertically scrolling terminal style used by the Qt console.
77 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).
78 You can create new notebooks from the dashboard with the ``New Notebook``
79 button, or open existing ones by clicking on their name.
72 80
73 2. A document that can save the inputs and outputs of the session as well as
74 additional text that accompanies the code but is not meant for execution.
75 In this way, notebook files serve as a complete computational record of a
76 session including explanatory text and mathematics, code and resulting
77 figures. These documents are internally JSON files and are saved with the
78 ``.ipynb`` extension.
79 81
80 If you have ever used the Mathematica or Sage notebooks (the latter is also
81 web-based__) you should feel right at home. If you have not, you should be
82 able to learn how to use it in just a few minutes.
82 You can also drag and drop into the area listing files any ``.py``
83 file: it will be imported into a notebook with the same name (but
84 ``.ipynb`` extension), located in the working directory. 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, and add text
85 and graphics, etc.
86 Alternatively,
87 prior to import, you can manually add ``# <nbformat>2</nbformat>``
88 markers at the start and then add separators for text/code cells, to get a cleaner import with the file already broken into individual cells.
83 89
84 .. __: http://sagenb.org
85 90
91 The IPython Notebook web app is based on a server-client structure.
92 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.
86 93
87 Creating and editing notebooks
88 ------------------------------
89 94
90 You can create new notebooks from the dashboard with the ``New Notebook``
91 button or open existing ones by clicking on their name. Once in a notebook,
92 your browser tab will reflect the name of that notebook (prefixed with "IPy:").
93 The URL for that notebook is not meant to be human-readable and is *not*
94 persistent across invocations of the notebook server.
95 95
96 You can also drag and drop into the area listing files any python file: it
97 will be imported into a notebook with the same name (but ``.ipynb`` extension)
98 located in the directory where the notebook server was started. This notebook
99 will consist of a single cell with all the code in the file, which you can
100 later manually partition into individual cells for gradual execution, add text
101 and graphics, etc.
96 Basic workflow
97 ------------------------
102 98
103 99
104 Workflow and limitations
105 ------------------------
100 Once in a notebook, your browser tab will reflect the name of that notebook (prefixed with "IPy").
101 The URL for that notebook is currently not meant to be human-readable and is not persistent across invocations of the notebook server; however, this will change soon.
102
103 The normal workflow in a notebook is quite similar to a normal IPython
104 session, with the difference that you can edit a cell in-place multiple
105 times until you obtain the desired resultsj, rather than having to
106 rerun separate scripts with the ``%run`` magic (though magics also work
107 in the notebook). Typically you'll work on a problem in pieces,
108 organizing related pieces into cells and moving forward as previous
109 parts work correctly. This is much more convenient for interactive exploration than breaking up a computation into scripts that must be
110 executed together, especially if parts of them take a long time to run
111
112 The only significant limitation that the notebook currently has, compared to the qt console, is that it can not run any code that
113 expects input from the kernel (such as scripts that call
114 :func:`raw_input`). Very importantly, this means that the ``%debug``
115 magic does *not* currently work in the notebook! This limitation will
116 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.
117 If your notebook is running on a local
118 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.
119
120
121 Connecting to an existing kernel
122 ---------------------------------
106 123
107 The normal workflow in a notebook is quite similar to a normal IPython session,
108 with the difference that you can edit a cell in-place multiple times until you
109 obtain the desired results rather than having to rerun separate scripts with
110 the ``%run`` magic (though magics also work in the notebook). Typically
111 you'll work on a problem in pieces, organizing related pieces into cells and
112 moving forward as previous parts work correctly. This is much more convenient
113 for interactive exploration than breaking up a computation into scripts that
114 must be executed together, especially if parts of them take a long time to run
115 (In the traditional terminal-based IPython, you can use tricks with namespaces
116 and ``%run -i`` to achieve this capability, but we think the notebook is a more
117 natural solution for that kind of problem).
118
119 The only significant limitation the notebook currently has, compared to the qt
120 console, is that it can not run any code that expects input from the kernel
121 (such as scripts that call :func:`raw_input`). Very importantly, this means
122 that the ``%debug`` magic does *not* work in the notebook! We intend to
123 correct this limitation, but in the meantime, there is a way to debug problems
124 in the notebook: you can attach a Qt console to your existing notebook kernel,
125 and run ``%debug`` from the Qt console. If your notebook is running on a local
126 computer (i.e. if you are accessing it via your localhost address at
127 127.0.0.1), you can just type ``%qtconsole`` in the notebook and a Qt console
128 will open up connected to that same kernel.
129
130 In general, the notebook server prints the full details of how to connect to
131 each kernel at the terminal, with lines like::
124 The notebook server always prints to the terminal the full details of
125 how to connect to each kernel, with lines like::
132 126
133 127 [IPKernelApp] To connect another client to this kernel, use:
134 128 [IPKernelApp] --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
135 129
136 This is the name of a JSON file that contains all the port and validation
137 information necessary to connect to the kernel. You can manually start a
138 qt console with::
130 This is the name of a JSON file that contains all the port and
131 validation information necessary to connect to the kernel. You can
132 manually start a Qt console with::
139 133
140 134 ipython qtconsole --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
141 135
@@ -143,10 +137,10 b' and if you only have a single kernel running, simply typing::'
143 137
144 138 ipython qtconsole --existing
145 139
146 will automatically find it (it will always find the most recently started
147 kernel if there is more than one). You can also request this connection data
148 by typing ``%connect_info``; this will print the same file information as well
149 as the content of the JSON data structure it contains.
140 will automatically find it (it will always find the most recently
141 started kernel if there is more than one). You can also request this
142 connection data by typing ``%connect_info``; this will print the same
143 file information as well as the content of the JSON data structure it contains.
150 144
151 145
152 146 Text input
@@ -181,12 +175,6 b' in the `Download` drop list. This removes all output and saves the text cells'
181 175 in comment areas. See ref:`below <notebook_format>` for more details on the
182 176 notebook format.
183 177
184 The notebook can also *import* ``.py`` files as notebooks, by dragging and
185 dropping the file into the notebook dashboard file list area. By default, the
186 entire contents of the file will be loaded into a single code cell. But if
187 prior to import, you manually add the ``# <nbformat>2</nbformat>`` marker at
188 the start and then add separators for text/code cells, you can get a cleaner
189 import with the file broken into individual cells.
190 178
191 179 .. warning::
192 180
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