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1
2
3 .. _`nbconvert script`:
4
5 Converting notebooks to other formats
6 =====================================
7
8 Newly added in the 1.0 release of IPython is the ``nbconvert`` tool, which
9 allows you to convert an ``.ipynb`` notebook document file into various static
10 formats.
11
12 Currently, ``nbconvert`` is provided as a command line tool, run as a script
13 using IPython. In the future, a direct export capability from within the
14 IPython Notebook web app is planned.
15
16 The command-line syntax to run the ``nbconvert`` script is::
17
18 $ ipython nbconvert --format=FORMAT notebook.ipynb
19
20 This will convert the IPython document file ``notebook.ipynb`` into the output
21 format given by the ``FORMAT`` string.
22
23 The default output format is HTML, for which the ``--format`` modifier may be
24 omitted::
25
26 $ ipython nbconvert notebook.ipynb
27
28 The currently supported export formats are the following:
29
30 * HTML:
31
32 - **full_html**:
33 Standard HTML
34
35 - **simple_html**:
36 Simplified HTML
37
38 - **reveal**:
39 HTML slideshow presentation for use with the ``reveal.js`` package
40
41 * PDF:
42
43 - **sphinx_howto**:
44 The format for Sphinx_ HOWTOs; similar to an ``article`` in LaTeX
45
46 - **sphinx_manual**:
47 The format for Sphinx_ manuals; similar to a ``book`` in LaTeX
48
49 - **latex**:
50 An article formatted completely using LaTeX
51
52 * Markup:
53
54 - **rst**:
55 reStructuredText_ markup
56
57 - **markdown**:
58 Markdown_ markup
59
60 .. _Sphinx: http://sphinx-doc.org/
61 .. _reStructuredText: http://docutils.sourceforge.net/rst.html
62 .. _Markdown: http://daringfireball.net/projects/markdown/syntax
63
64 * Python:
65
66 Comments out all the non-Python code to produce a ``.py`` Python
67 script with just the code content. Currently the output includes IPython
68 magics, and so can be run with ``ipython``, after changing the extension
69 of the script to ``.ipy``.
70
71 The files output file created by ``nbconvert`` will have the same base name as
72 the notebook and will be placed in the current working directory. Any
73 supporting files (graphics, etc) will be placed in a new directory with the
74 same base name as the notebook, suffixed with ``_files``::
75
76 $ ipython nbconvert notebook.ipynb
77 $ ls
78 notebook.ipynb notebook.html notebook_files/
79
80 Each of the options for PDF export produces as an intermediate step a LaTeX
81 ``.tex`` file with the same basename as the notebook, as well as individual
82 files for each figure, and ``.text`` files with textual output from running
83 code cells.
84
85 To actually produce the final PDF file, run the following commands::
86
87 $ ipython nbconvert --format=latex notebook.ipynb
88 $ pdflatex notebook
89
90 This requires a local installation of LaTeX on your machine.
91 The output is a PDF file ``notebook.pdf``, also placed inside the
92 ``nbconvert_build`` subdirectory.
93
94 Alternatively, the output may be sent to standard output with::
95
96 $ ipython nbconvert notebook.ipynb --stdout
97
98 Multiple notebooks can be specified from the command line::
99
100 $ ipython nbconvert notebook*.ipynb
101 $ ipython nbconvert notebook1.ipynb notebook2.ipynb
102
103 or via a list in a configuration file, say ``mycfg.py``, containing the text::
104
105 c = get_config()
106 c.NbConvertApp.notebooks = ["notebook1.ipynb", "notebook2.ipynb"]
107
108 and using the command::
109
110 $ ipython nbconvert --config mycfg.py
111
112
113 Extracting standard Python files from notebooks
114 -----------------------------------------------
115 ``.ipynb`` notebook document files are plain text files which store a
116 representation in JSON format of the contents of a notebook space. As such,
117 they are not valid ``.py`` Python scripts, and so can be neither imported
118 directly with ``import`` in Python, nor run directly as a standard Python
119 script (though both of these are possible with simple workarounds).
120
121
122 To extract the Python code from within a notebook document, the simplest
123 method is to use the ``File | Download as | Python (.py)`` menu item; the
124 resulting ``.py`` script will be downloaded to your browser's default
125 download location.
126
127 An alternative is to pass an argument to the IPython Notebook, from the moment
128 when it is originally started, specifying that whenever it saves an ``.ipynb``
129 notebook document, it should, at the same time, save the corresponding
130 ``.py`` script. To do so, you can execute the following command::
131
132 $ ipython notebook --script
133
134 or you can set this option permanently in your configuration file with::
135
136 c = get_config()
137 c.NotebookManager.save_script=True
138
139 The result is that standard ``.py`` files are also now generated, which
140 can be ``%run``, imported from regular IPython sessions or other notebooks, or
141 executed at the command line, as usual. Since the raw code you have typed is
142 exported, you must avoid using syntax such as IPython magics and other
143 IPython-specific extensions to the language for the files to be able to be
144 successfully imported.
145 .. or you can change the script's extension to ``.ipy`` and run it with::
146 ..
147 .. $ ipython script.ipy
148
149 In normal Python practice, the standard way to differentiate importable code
150 in a Python script from the "executable" part of a script is to use the
151 following idiom at the start of the executable part of the code::
152
153 if __name__ == '__main__'
154
155 # rest of the code...
156
157 Since all cells in the notebook are run as top-level code, you will need to
158 similarly protect *all* cells that you do not want executed when other scripts
159 try to import your notebook. A convenient shortand for this is to define
160 early on::
161
162 script = __name__ == '__main__'
163
164 Then in any cell that you need to protect, use::
165
166 if script:
167 # rest of the cell...
168
169
170
171 .. _notebook_format:
172
173 Notebook JSON file format
174 -------------------------
175 Notebook documents are JSON files with an ``.ipynb`` extension, formatted
176 as legibly as possible with minimal extra indentation and cell content broken
177 across lines to make them reasonably friendly to use in version-control
178 workflows. You should be very careful if you ever manually edit this JSON
179 data, as it is extremely easy to corrupt its internal structure and make the
180 file impossible to load. In general, you should consider the notebook as a
181 file meant only to be edited by the IPython Notebook app itself, not for
182 hand-editing.
183
184 .. note::
185
186 Binary data such as figures are also saved directly in the JSON file.
187 This provides convenient single-file portability, but means that the
188 files can be large; a ``diff`` of binary data is also not very
189 meaningful. Since the binary blobs are encoded in a single line, they
190 affect only one line of the ``diff`` output, but they are typically very
191 long lines. You can use the ``Cell | All Output | Clear`` menu option to
192 remove all output from a notebook prior to committing it to version
193 control, if this is a concern.
194
195 The notebook server can also generate a pure Python version of your notebook,
196 using the ``File | Download as`` menu option. The resulting ``.py`` file will
197 contain all the code cells from your notebook verbatim, and all Markdown cells
198 prepended with a comment marker. The separation between code and Markdown
199 cells is indicated with special comments and there is a header indicating the
200 format version. All output is removed when exporting to Python.
201
202 As an example, consider a simple notebook called ``simple.ipynb`` which
203 contains one Markdown cell, with the content ``The simplest notebook.``, one
204 code input cell with the content ``print "Hello, IPython!"``, and the
205 corresponding output.
206
207 The contents of the notebook document ``simple.ipynb`` is the following JSON
208 container::
209
210 {
211 "metadata": {
212 "name": "simple"
213 },
214 "nbformat": 3,
215 "nbformat_minor": 0,
216 "worksheets": [
217 {
218 "cells": [
219 {
220 "cell_type": "markdown",
221 "metadata": {},
222 "source": "The simplest notebook."
223 },
224 {
225 "cell_type": "code",
226 "collapsed": false,
227 "input": "print \"Hello, IPython\"",
228 "language": "python",
229 "metadata": {},
230 "outputs": [
231 {
232 "output_type": "stream",
233 "stream": "stdout",
234 "text": "Hello, IPython\n"
235 }
236 ],
237 "prompt_number": 1
238 }
239 ],
240 "metadata": {}
241 }
242 ]
243 }
244
245
246 The corresponding Python script is::
247
248 # -*- coding: utf-8 -*-
249 # <nbformat>3.0</nbformat>
250
251 # <markdowncell>
252
253 # The simplest notebook.
254
255 # <codecell>
256
257 print "Hello, IPython"
258
259 Note that indeed the output of the code cell, which is present in the JSON
260 container, has been removed in the ``.py`` script.
261
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1 .. _htmlnotebook:
2
3 The IPython Notebook
4 ====================
5
6 The IPython Notebook is part of the IPython package, which aims to provide a
7 powerful, interactive approach to scientific computation.
8 The IPython Notebook extends the previous text-console-based approach, and the
9 later Qt console, in a qualitatively new diretion, providing a web-based
10 application suitable for capturing the whole scientific computation process.
11
12 .. seealso::
13
14 :ref:`Installation requirements <installnotebook>` for the Notebook.
15
16
17 .. Basic structure
18 .. ---------------
19
20 Introduction
21 ------------
22
23 The IPython Notebook combines two components:
24
25 * **The IPython Notebook web application**:
26
27 The *IPython Notebook web app* is a browser-based tool for interactive
28 authoring of literate computations, in which explanatory text,
29 mathematics, computations and rich media output may be combined. Input
30 and output are stored in persistent cells that may be edited in-place.
31
32 * **Notebook documents**:
33
34 *Notebook documents*, or *notebooks*, are plain text documents which
35 record all inputs and outputs of the computations, interspersed with
36 text, mathematics and HTML 5 representations of objects, in a literate
37 style.
38
39 Since the similarity in names can lead to some confusion, in this
40 documentation we will use capitalization of the word "notebook" to
41 distinguish the Notebook app and notebook documents, thinking of the
42 Notebook app as being a proper noun. We will also always refer to the
43 "Notebook app" when we are referring to the browser-based interface,
44 and usually to "notebook documents", instead of "notebooks", for added
45 precision.
46
47 We refer to the current state of the computational process taking place in the
48 Notebook app, i.e. the (numbered) sequence of input and output cells, as the
49 *notebook space*. Notebook documents provide an *exact*, *one-to-one* record
50 of all the content in the notebook space, as a plain text file in JSON format.
51 The Notebook app automatically saves, at certain intervals, the contents of
52 the notebook space to a notebook document stored on disk, with the same name
53 as the title of the notebook space, and the file extension ``.ipynb``. For
54 this reason, there is no confusion about using the same word "notebook" for
55 both the notebook space and the corresponding notebook document, since they are
56 really one and the same concept (we could say that they are "isomorphic").
57
58
59 Main features of the IPython Notebook web app
60 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
61
62 The main features of the IPython Notebook app include:
63
64 * In-browser editing for code, with automatic syntax highlighting and
65 indentation and tab completion/introspection.
66
67 * Literate combination of code with rich text using the Markdown_ markup
68 language.
69
70 * Mathematics is easily included within the Markdown using LaTeX notation, and
71 rendered natively by MathJax_.
72
73 * Displays rich data representations (e.g. HTML / LaTeX / SVG) as the result
74 of computations.
75
76 * Publication-quality figures in a range of formats (SVG / PNG), rendered by
77 the matplotlib_ library, may be included inline and exported.
78
79
80 .. _MathJax: http://www.mathjax.org/
81 .. _matplotlib: http://matplotlib.org/
82 .. _Markdown: http://daringfireball.net/projects/markdown/syntax
83
84
85 Notebook documents
86 ~~~~~~~~~~~~~~~~~~
87
88 Notebook document files are simple JSON_ files with the
89 extension ``.ipynb``.
90 Since JSON is just plain text, they can be easily version-controlled and shared with colleagues.
91 The notebook stores a *complete*, *reproducible*, *one-to-one* copy of the state of the
92 computational state as it is inside the Notebook app. All computations
93 carried out, and the corresponding results obtained, can be combined in
94 a literate way, interleaving executable code with rich text, mathematics,
95 and rich representations of objects.
96
97 .. _JSON: http://en.wikipedia.org/wiki/JSON
98
99 Notebooks may easily be exported to a range of static formats, including
100 HTML (for example, for blog posts), PDF and slide shows,
101 via the new nbconvert_ command.
102
103 Furthermore, any ``.ipynb`` notebook document available from a public
104 URL can be shared via the `IPython Notebook Viewer <nbviewer>`_ service.
105 This service loads the notebook document from the URL and will
106 render it as a static web page. The results may thus be shared with a
107 colleague, or as a public blog post, without other users needing to install
108 IPython themselves. NbViewer is simply NbConvert as a simple heroku webservice.
109
110 See the :ref:`installation documentation <install_index>` for directions on
111 how to install the notebook and its dependencies.
112
113 .. _nbviewer: http://nbviewer.ipython.org
114
115 .. note::
116
117 You can start more than one notebook server at the same time, if you want
118 to work on notebooks in different directories. By default the first
119 notebook server starts on port 8888, and later notebook servers search for
120 ports near that one. You can also manually specify the port with the
121 ``--port`` option.
122
123
124 Basic workflow in the IPython Notebook web app
125 ----------------------------------------------
126
127 Starting up
128 ~~~~~~~~~~~~
129
130 You can start running the Notebook web app using the following command::
131
132 $ ipython notebook
133
134 (Here, and in the sequel, the initial ``$`` represents the shell prompt,
135 indicating that the command is to be run from the command line in a shell.)
136
137 The landing page of the IPython Notebook application, the *dashboard*, shows
138 the notebooks currently available in the *notebook directory* (By default, the directory
139 from which the notebook was started).
140 You can create new notebooks from the dashboard with the ``New Notebook``
141 button, or open existing ones by clicking on their name.
142 You can also drag and drop ``.ipynb`` notebooks and standard ``.py`` Python
143 source code files into the notebook list area.
144
145
146 You can open an existing notebook directly, without having to go via the
147 dashboard, with:
148
149 ipython notebook my_notebook
150
151 The `.ipynb` extension is assumed if no extension is given.
152
153 The `File | Open...` menu option will open the dashboard in a new browser tab,
154 to allow you to select a current notebook
155 from the notebook directory or to create a new notebook.
156
157
158
159 Notebook user interface
160 ~~~~~~~~~~~~~~~~~~~~~~~
161
162 When you open a new notebook document in the Notebook, you will be presented
163 with the title associated to the notebook space/document, a *menu bar*, a
164 *toolbar* and an empty *input cell*.
165
166 Notebook title
167 ^^^^^^^^^^^^^^
168 The title of the notebook document that is currently being edited is displayed
169 at the top of the page, next to the ``IP[y]: Notebook`` logo. This title may
170 be edited directly by clicking on it. The title is reflected in the name of
171 the ``.ipynb`` notebook document file that is saved.
172
173 Menu bar
174 ^^^^^^^^
175 The menu bar presents different options that may be used to manipulate the way
176 the Notebook functions.
177
178 Toolbar
179 ^^^^^^^
180 The tool bar gives a quick way of accessing the most-used operations within
181 the Notebook, by clicking on an icon.
182
183
184 Creating a new notebook document
185 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
186
187 A new notebook space/document may be created at any time, either from the
188 dashboard, or using the `File | New` menu option from within an active
189 notebook. The new notebook is created within the same directory and
190 will open in a new browser tab. It will also be reflected as a new entry in
191 the notebook list on the dashboard.
192
193
194 Structure of a notebook document
195 --------------------------------
196
197 Input cells
198 ~~~~~~~~~~~
199 Input cells are at the core of the functionality of the IPython Notebook.
200 They are regions in the document in which you can enter different types of
201 text and commands. To *execute* or *run* the *current cell*, i.e. the cell
202 under the cursor, you can use the :kbd:`Shift-Enter` key combination.
203 This tells the Notebook app to perform the relevant operation for each type of
204 cell (see below), and then to display the resulting output.
205
206 The notebook consists of a sequence of input cells, labelled ``In[n]``, which
207 may be executed in a non-linear way, and outputs ``Out[n]``, where ``n`` is a
208 number which denotes the order in which the cells were executed over the
209 history of the computational process. The contents of all of these cells are
210 accessible as Python variables with the same names, forming a complete record
211 of the history of the computation.
212
213
214
215 Input cell types
216 ~~~~~~~~~~~~~~~~
217 Each IPython input cell has a *cell type*, of which there is a restricted
218 number. The type of a cell may be set by using the cell type dropdown on the
219 toolbar, or via the following keyboard shortcuts:
220
221 * **code**: :kbd:`Ctrl-m y`
222 * **markdown**: :kbd:`Ctrl-m m`
223 * **raw**: :kbd:`Ctrl-m t`
224 * **heading**: :kbd:`Ctrl-m 1` - :kbd:`Ctrl-m 6`
225
226 Upon initial creation, each input cell is by default a code cell.
227
228
229 Code cells
230 ^^^^^^^^^^
231 A *code input cell* allows you to edit code inline within the cell, with full
232 syntax highlighting and autocompletion/introspection. By default, the language
233 associated to a code cell is Python, but other languages, such as ``julia``
234 and ``R``, can be handled using magic commands (see below).
235
236 When a code cell is executed with :kbd:`Shift-Enter`, the code that it
237 contains is transparently exported and run in that language (with automatic
238 compiling, etc., if necessary). The result that is returned from this
239 computation is then displayed in the notebook space as the cell's
240 *output*. If this output is of a textual nature, it is placed into a
241 numbered *output cell*. However, many other possible forms of output are also
242 possible, including ``matplotlib`` figures and HTML tables (as used, for
243 example, in the ``pandas`` data analyis package). This is known as IPython's
244 *rich display* capability.
245
246
247 Markdown cells
248 ^^^^^^^^^^^^^^
249 You can document the computational process in a literate way, alternating
250 descriptive text with code, using *rich text*. In IPython this is accomplished
251 by marking up text with the Markdown language. The corresponding cells are
252 called *Markdown input cells*. The Markdown language provides a simple way to
253 perform this text markup, that is, to specify which parts of the text should
254 be emphasized (italics), bold, form lists, etc.
255
256
257 When a Markdown input cell is executed, the Markdown code is converted into
258 the corresponding formatted rich text. This output then *replaces* the
259 original Markdown input cell, leaving just the visually-significant marked up
260 rich text. Markdown allows arbitrary HTML code for formatting.
261
262 Within Markdown cells, you can also include *mathematics* in a straightforward
263 way, using standard LaTeX notation: ``$...$`` for inline mathematics and
264 ``$$...$$`` for displayed mathematics. When the Markdown cell is executed,
265 the LaTeX portions are automatically rendered in the HTML output as equations
266 with high quality typography. This is made possible by MathJax_, which
267 supports a `large subset <mathjax_tex>`_ of LaTeX functionality
268
269 .. _mathjax_tex: http://docs.mathjax.org/en/latest/tex.html
270
271 Standard mathematics environments defined by LaTeX and AMS-LaTeX (the
272 `amsmath` package) also work, such as
273 ``\begin{equation}...\end{equation}``, and ``\begin{align}...\end{align}``.
274 New LaTeX macros may be defined using standard methods,
275 such as ``\newcommand``, by placing them anywhere *between math delimiters* in
276 a Markdown cell. These definitions are then available throughout the rest of
277 the IPython session. (Note, however, that more care must be taken when using
278 nbconvert_ to output to LaTeX).
279
280 Raw input cells
281 ~~~~~~~~~~~~~~~
282
283 *Raw* input cells provide a place in which you can write *output* directly.
284 Raw cells are not evaluated by the Notebook, and have no output.
285 When passed through nbconvert, Raw cells arrive in the destination format unmodified,
286 allowing you to type full latex into a raw cell, which will only be rendered
287 by latex after conversion by nbconvert.
288
289 Heading cells
290 ~~~~~~~~~~~~~
291
292 You can provide a conceptual structure for your computational document as a
293 whole using different levels of headings; there are 6 levels available, from
294 level 1 (top level) down to level 6 (paragraph). These can be used later for
295 constructing tables of contents, etc.
296
297 As with Markdown cells, a heading input cell is replaced by a rich text
298 rendering of the heading when the cell is executed.
299
300
301 Basic workflow
302 --------------
303
304 The normal workflow in a notebook is, then, quite similar to a standard
305 IPython session, with the difference that you can edit cells in-place multiple
306 times until you obtain the desired results, rather than having to
307 rerun separate scripts with the ``%run`` magic command. (Magic commands do,
308 however, also work in the notebook; see below).
309
310 Typically, you will work on a computational problem in pieces, organizing
311 related ideas into cells and moving forward once previous parts work
312 correctly. This is much more convenient for interactive exploration than
313 breaking up a computation into scripts that must be executed together, as was
314 previously necessary, especially if parts of them take a long time to run
315
316 The only significant limitation that the Notebook currently has, compared to
317 the Qt console, is that it cannot run any code that expects input from the
318 kernel (such as scripts that call :func:`raw_input`). Very importantly, this
319 means that the ``%debug`` magic does *not* currently work in the notebook!
320
321 This limitation will be overcome in the future, but in the meantime, there is
322 a simple solution for debugging: you can attach a Qt console to your existing
323 notebook kernel, and run ``%debug`` from the Qt console.
324 If your notebook is running on a local computer (i.e. if you are accessing it
325 via your localhost address at ``127.0.0.1``), then you can just type
326 ``%qtconsole`` in the notebook and a Qt console will open up, connected to
327 that same kernel.
328
329 At certain moments, it may be necessary to interrupt a calculation which is
330 taking too long to complete. This may be done with the ``Kernel | Interrupt``
331 menu option, or the :kbd:``Ctrl-i`` keyboard shortcut.
332 Similarly, it may be necessary or desirable to restart the whole computational
333 process, with the ``Kernel | Restart`` menu option or :kbd:``Ctrl-.``
334 shortcut. This gives an equivalent state to loading the notebook document
335 afresh.
336
337
338 .. warning::
339
340 While in simple cases you can "roundtrip" a notebook to Python, edit the
341 Python file, and then import it back without loss of main content, this is
342 in general *not guaranteed to work*. First, there is extra metadata
343 saved in the notebook that may not be saved to the ``.py`` format. And as
344 the notebook format evolves in complexity, there will be attributes of the
345 notebook that will not survive a roundtrip through the Python form. You
346 should think of the Python format as a way to output a script version of a
347 notebook and the import capabilities as a way to load existing code to get
348 a notebook started. But the Python version is *not* an alternate notebook
349 format.
350
351
352 Keyboard shortcuts
353 ~~~~~~~~~~~~~~~~~~
354 All actions in the notebook can be achieved with the mouse, but keyboard
355 shortcuts are also available for the most common ones, so that productive use
356 of the notebook can be achieved with minimal mouse usage. The main shortcuts
357 to remember are the following:
358
359 * :kbd:`Shift-Enter`:
360
361 Execute the current cell, show output (if any), and jump to the next cell
362 below. If :kbd:`Shift-Enter` is invoked on the last input cell, a new code
363 cell will also be created. Note that in the notebook, typing :kbd:`Enter`
364 on its own *never* forces execution, but rather just inserts a new line in
365 the current input cell. In the Notebook it is thus always necessary to use
366 :kbd:`Shift-Enter` to execute the cell (or use the ``Cell | Run`` menu
367 item).
368
369 * :kbd:`Ctrl-Enter`:
370 Execute the current cell as if it were in "terminal mode", where any
371 output is shown, but the cursor *remains* in the current cell. This is
372 convenient for doing quick experiments in place, or for querying things
373 like filesystem content, without needing to create additional cells that
374 you may not want to be saved in the notebook.
375
376 * :kbd:`Alt-Enter`:
377 Executes the current cell, shows the output, and inserts a *new* input
378 cell between the current cell and the adjacent cell (if one exists). This
379 is thus a shortcut for the sequence :kbd:`Shift-Enter`, :kbd:`Ctrl-m a`.
380 (:kbd:`Ctrl-m a` adds a new cell above the current one.)
381
382 * :kbd:`Ctrl-m`:
383 This is the prefix for *all* other shortcuts, which consist of :kbd:`Ctrl-m`
384 followed by a single letter or character. For example, if you type
385 :kbd:`Ctrl-m h` (that is, the sole letter :kbd:`h` after :kbd:`Ctrl-m`),
386 IPython will show you all the available keyboard shortcuts.
387
388
389 Magic commands
390 --------------
391 Magic commands, or *magics*, are commands for controlling IPython itself.
392 They all begin with ``%`` and are entered into code input cells; the code
393 cells are executed as usual with :kbd:`Shift-Enter`.
394
395 The magic commands call special functions defined by IPython which manipulate
396 the computational state in certain ways.
397
398 There are two types of magics:
399
400 - **line magics**:
401
402 These begin with a single ``%`` and take as arguments the rest of the
403 *same line* of the code cell. Any other lines of the code cell are
404 treated as if they were part of a standard code cell.
405
406 - **cell magics**:
407
408 These begin with ``%%`` and operate on the *entire* remaining contents
409 of the code cell.
410
411 Line magics
412 ~~~~~~~~~~~
413 Some of the available line magics are the following:
414
415 * ``%load filename``:
416
417 Loads the contents of the file ``filename`` into a new code cell. This
418 can be a URL for a remote file.
419
420 * ``%timeit code``:
421
422 An easy way to time how long the single line of code ``code`` takes to
423 run
424
425 * ``%config``:
426
427 Configuration of the IPython Notebook
428
429 * ``%lsmagic``:
430
431 Provides a list of all available magic commands
432
433 Cell magics
434 ~~~~~~~~~~~
435
436 * ``%%latex``:
437
438 Renders the entire contents of the cell in LaTeX, without needing to use
439 explicit LaTeX delimiters.
440
441 * ``%%bash``:
442
443 The code cell is executed by sending it to be executed by ``bash``. The
444 output of the ``bash`` commands is captured and displayed in the
445 notebook.
446
447 * ``%%file filename``:
448
449 Writes the contents of the cell to the file ``filename``.
450 **Caution**: The file is over-written without warning!
451
452 * ``%%R``:
453
454 Execute the contents of the cell using the R language.
455
456 * ``%%timeit``:
457
458 Version of ``%timeit`` which times the entire block of code in the
459 current code cell.
460
461
462
463 Several of the cell magics provide functionality to manipulate the filesystem
464 of a remote server to which you otherwise do not have access.
465
466
467 Plotting
468 --------
469 One major feature of the Notebook is the ability to interact with
470 plots that are the output of running code cells. IPython is designed to work
471 seamlessly with the ``matplotlib`` plotting library to provide this
472 functionality.
473
474 To set this up, before any plotting is performed you must execute the
475 ``%matplotlib`` magic command. This performs the necessary behind-the-scenes
476 setup for IPython to work correctly hand in hand with ``matplotlib``; it does
477 *not*, however, actually execute any Python ``import`` commands, that is, no
478 names are added to the namespace.
479
480 For more agile *interactive* use of the notebook space, an alternative magic,
481 ``%pylab``, is provided. This does the same work as the ``%matplotlib`` magic,
482 but *in addition* it automatically executes a standard sequence of ``import``
483 statements required to work with the ``%matplotlib`` library, importing the
484 following names into the namespace:
485
486 ``numpy`` as ``np``; ``matplotlib.pyplot`` as ``plt``;
487 ``matplotlib``, ``pylab`` and ``mlab`` from ``matplotlib``; and *all names*
488 from within ``numpy`` and ``pylab``.
489
490 However, the use of ``%pylab`` is discouraged, since names coming from
491 different packages may collide. In general, the use of ``from package import
492 *`` is discouraged. A better option is then::
493
494 %pylab --no-import-all
495
496 which imports the names listed above, but does *not* perform this
497 ``import *`` imports.
498
499 If the ``%matplotlib`` or ``%pylab` magics are called without an argument, the
500 output of a plotting command is displayed using the default ``matplotlib``
501 backend in a separate window. Alternatively, the backend can be explicitly
502 requested using, for example::
503
504 %matplotlib gtk
505
506 A particularly interesting backend is the ``inline`` backend.
507 This is applicable only for the IPython Notebook and the IPython Qtconsole.
508 It can be invoked as follows::
509
510 %matplotlib inline
511
512 With this backend, output of plotting commands is displayed *inline* within
513 the notebook format, directly below the input cell that produced it. The
514 resulting plots will then also be stored in the notebook document. This
515 provides a key part of the functionality for reproducibility_ that the IPython
516 Notebook provides.
517
518 .. _reproducibility: https://en.wikipedia.org/wiki/Reproducibility
519
520
521
522 Configuring the IPython Notebook
523 --------------------------------
524 The IPython Notebook can be run with a variety of command line arguments.
525 To see a list of available options enter::
526
527 $ ipython notebook --help
528
529 Defaults for these options can also be set by creating a file named
530 ``ipython_notebook_config.py`` in your IPython *profile folder*. The profile
531 folder is a subfolder of your IPython directory; to find out where it is
532 located, run::
533
534 $ ipython locate
535
536 To create a new set of default configuration files, with lots of information
537 on available options, use::
538
539 $ ipython profile create
540
541 .. seealso:
542
543 :ref:`config_overview`, in particular :ref:`Profiles`.
544
545
546 Importing `.py` files
547 ----------------------
548
549
550 ``.py`` files will be imported into the IPython Notebook as a notebook with
551 the same basename, but an ``.ipynb`` extension, located in the notebook
552 directory. The notebook created will have just one cell, which will contain
553 all the code in the ``.py`` file. You can later manually partition this into
554 individual cells using the ``Edit | Split Cell`` menu option, or the
555 :kbd:`Ctrl-m -` keyboard shortcut.
556
557 .. Alternatively, prior to importing the ``.py``, you can manually add ``# <
558 nbformat>2</nbformat>`` at the start of the file, and then add separators for
559 text and code cells, to get a cleaner import with the file already broken into
560 individual cells.
561
@@ -0,0 +1,182 b''
1 .. _working_remotely.txt
2
3 Working remotely
4 ================
5
6
7 The IPython Notebook web app is based on a server-client structure.
8 This server uses a two-process kernel architecture based on ZeroMQ, as well as
9 Tornado for serving HTTP requests. Other clients may connect to the same
10 underlying IPython kernel; see below.
11
12 .. _notebook_security:
13
14 Security
15 --------
16
17 You can protect your Notebook server with a simple single password by
18 setting the :attr:`NotebookApp.password` configurable. You can prepare a
19 hashed password using the function :func:`IPython.lib.security.passwd`:
20
21 .. sourcecode:: ipython
22
23 In [1]: from IPython.lib import passwd
24 In [2]: passwd()
25 Enter password:
26 Verify password:
27 Out[2]: 'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
28
29 .. note::
30
31 :func:`~IPython.lib.security.passwd` can also take the password as a string
32 argument. **Do not** pass it as an argument inside an IPython session, as it
33 will be saved in your input history.
34
35 You can then add this to your :file:`ipython_notebook_config.py`, e.g.::
36
37 # Password to use for web authentication
38 c = get_config()
39 c.NotebookApp.password =
40 u'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
41
42 When using a password, it is a good idea to also use SSL, so that your
43 password is not sent unencrypted by your browser. You can start the notebook
44 to communicate via a secure protocol mode using a self-signed certificate with
45 the command::
46
47 $ ipython notebook --certfile=mycert.pem
48
49 .. note::
50
51 A self-signed certificate can be generated with ``openssl``. For example,
52 the following command will create a certificate valid for 365 days with
53 both the key and certificate data written to the same file::
54
55 $ openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.
56 pem -out mycert.pem
57
58 Your browser will warn you of a dangerous certificate because it is
59 self-signed. If you want to have a fully compliant certificate that will not
60 raise warnings, it is possible (but rather involved) to obtain one,
61 `as explained in detailed in this tutorial`__.
62
63 .. __: http://arstechnica.com/security/news/2009/12/how-to-get-set-with-a-
64 secure-sertificate-for-free.ars
65
66 Keep in mind that when you enable SSL support, you will need to access the
67 notebook server over ``https://``, not over plain ``http://``. The startup
68 message from the server prints this, but it is easy to overlook and think the
69 server is for some reason non-responsive.
70
71
72 Connecting to an existing kernel
73 ---------------------------------
74
75 The notebook server always prints to the terminal the full details of
76 how to connect to each kernel, with messages such as the following::
77
78 [IPKernelApp] To connect another client to this kernel, use:
79 [IPKernelApp] --existing kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
80
81 This long string is the name of a JSON file that contains all the port and
82 validation information necessary to connect to the kernel. You can then, for
83 example, manually start a Qt console connected to the *same* kernel with::
84
85 $ ipython qtconsole --existing
86 kernel-3bb93edd-6b5a-455c-99c8-3b658f45dde5.json
87
88 If you have only a single kernel running, simply typing::
89
90 $ ipython qtconsole --existing
91
92 will automatically find it. (It will always find the most recently
93 started kernel if there is more than one.) You can also request this
94 connection data by typing ``%connect_info``; this will print the same
95 file information as well as the content of the JSON data structure it
96 contains.
97
98
99 Running a public notebook server
100 --------------------------------
101
102 If you want to access your notebook server remotely via a web browser,
103 you can do the following.
104
105 Start by creating a certificate file and a hashed password, as explained
106 above. Then create a custom profile for the notebook, with the following
107 command line, type::
108
109 $ ipython profile create nbserver
110
111 In the profile directory just created, edit the file
112 ``ipython_notebook_config.py``. By default, the file has all fields
113 commented; the minimum set you need to uncomment and edit is the following::
114
115 c = get_config()
116
117 # Kernel config
118 c.IPKernelApp.pylab = 'inline' # if you want plotting support always
119
120 # Notebook config
121 c.NotebookApp.certfile = u'/absolute/path/to/your/certificate/mycert.pem'
122 c.NotebookApp.ip = '*'
123 c.NotebookApp.open_browser = False
124 c.NotebookApp.password = u'sha1:bcd259ccf...[your hashed password here]'
125 # It is a good idea to put it on a known, fixed port
126 c.NotebookApp.port = 9999
127
128 You can then start the notebook and access it later by pointing your browser
129 to ``https://your.host.com:9999`` with ``ipython notebook
130 --profile=nbserver``.
131
132 Running with a different URL prefix
133 -----------------------------------
134
135 The notebook dashboard (the landing page with an overview
136 of the notebooks in your working directory) typically lives at the URL
137 ``http://localhost:8888/``. If you prefer that it lives, together with the
138 rest of the notebook, under a sub-directory,
139 e.g. ``http://localhost:8888/ipython/``, you can do so with
140 configuration options like the following (see above for instructions about
141 modifying ``ipython_notebook_config.py``)::
142
143 c.NotebookApp.base_project_url = '/ipython/'
144 c.NotebookApp.base_kernel_url = '/ipython/'
145 c.NotebookApp.webapp_settings = {'static_url_prefix':'/ipython/static/'}
146
147 Using a different notebook store
148 --------------------------------
149
150 By default, the Notebook app stores the notebook documents that it saves as
151 files in the working directory of the Notebook app, also known as the
152 ``notebook_dir``. This logic is implemented in the
153 :class:`FileNotebookManager` class. However, the server can be configured to
154 use a different notebook manager class, which can
155 store the notebooks in a different format.
156
157 Currently, we ship a :class:`AzureNotebookManager` class that stores notebooks
158 in Azure blob storage. This can be used by adding the following lines to your
159 ``ipython_notebook_config.py`` file::
160
161 c.NotebookApp.notebook_manager_class =
162 'IPython.html.services.notebooks.azurenbmanager.AzureNotebookManager'
163 c.AzureNotebookManager.account_name = u'paste_your_account_name_here'
164 c.AzureNotebookManager.account_key = u'paste_your_account_key_here'
165 c.AzureNotebookManager.container = u'notebooks'
166
167 In addition to providing your Azure Blob Storage account name and key, you
168 will have to provide a container name; you can use multiple containers to
169 organize your notebooks.
170
171
172 Known issues
173 ------------
174
175 When behind a proxy, especially if your system or browser is set to autodetect
176 the proxy, the Notebook app might fail to connect to the server's websockets,
177 and present you with a warning at startup. In this case, you need to configure
178 your system not to use the proxy for the server's address.
179
180 For example, in Firefox, go to the Preferences panel, Advanced section,
181 Network tab, click 'Settings...', and add the address of the notebook server
182 to the 'No proxy for' field.
@@ -10,6 +10,8 b' Using IPython for interactive work'
10 reference
10 reference
11 shell
11 shell
12 qtconsole
12 qtconsole
13 htmlnotebook
13 notebook
14 converting_notebooks
15 working_remotely
14
16
15
17
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